The prevalence of tinnitus is increasing worldwide along with the aging population.The absence of a gold standard for diagnosis and treatment makes it difficult to assess the health status of a patient with tinnitus.T...The prevalence of tinnitus is increasing worldwide along with the aging population.The absence of a gold standard for diagnosis and treatment makes it difficult to assess the health status of a patient with tinnitus.The aim was to determine the prevalence of tinnitus among older adults in Almaty city and to evaluate the healthcare experience among the respondents who received treatment for tinnitus.Methods:A cross-sectional study was conducted among people aged 18 years and above in Almaty city.The data were collected using a questionnaire sent via a Google form and/or as a printed version.Fully completed responses were received from 851 respondents.The questionnaire consists of 31 questions.Simple and multiple logistic regression analyses were performed to identify the risk factors of tinnitus.Results:The prevalence of tinnitus in Almaty was 23.3%.The data showed that smoking and sleep regimen were associated with tinnitus.Older respondents indicated more symptoms associated with tinnitus than younger respondents did.Additional consultation was needed as part of the treatment of tinnitus.In addition,49.4%of the respondents indicated a need of a support group for people with tinnitus.The respondents also indicated that the access to appropriate resources for the treatment of tinnitus was poor.Conclusion:Similar to other studies,this analysis confirmed that tinnitus is prevalent in the adult population of Almaty city.Future activities should include measures for the improvement of public awareness of the risk factors of tinnitus,and multidisciplinary teamwork among healthcare specialists should be improved.展开更多
Seismic microzonation for Almaty city for the first time use probabilistic approach and hazard is expressed in terms of not only macroseismic intensity,but also Peak Ground Acceleration(PGA).To account for the effects...Seismic microzonation for Almaty city for the first time use probabilistic approach and hazard is expressed in terms of not only macroseismic intensity,but also Peak Ground Acceleration(PGA).To account for the effects of local soil conditions,the continual approach proposed by A.S.Aleshin[1,2]was used,in which soil coefficients are a function of the continuously changing seismic rigidity.Soil coefficients were calculated using the new data of geological and geophysical surveys and findings of previous geotechnical studies.The used approach made it possible to avoid using soil categories and a jump change in characteristics of soil conditions and seismic impact.The developed seismic microzonation maps are prepared for further introduction into the normative documents of the Republic of Kazakhstan.展开更多
Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient conditions.Among the available functional diagnos...Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient conditions.Among the available functional diagnostic methods,electrocardiography(ECG)is particularly well-known for its ability to detect MI.However,confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in practice.This study,therefore,proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of MI.In particular,the learning vector quantization(LVQ)algorithm was applied,considering the contribution of each ECG lead in the 12-channel system,which obtained an accuracy of 87%in localizing damaged myocardium.The developed model was tested on verified data from the PTB database,including 445 ECG recordings from both healthy individuals and MI-diagnosed patients.The results demonstrated that the 12-lead ECG system allows for a comprehensive understanding of cardiac activities in myocardial infarction patients,serving as an essential tool for the diagnosis of myocardial conditions and localizing their damage.A comprehensive comparison was performed,including CNN,SVM,and Logistic Regression,to evaluate the proposed LVQ model.The results demonstrate that the LVQ model achieves competitive performance in diagnostic tasks while maintaining computational efficiency,making it suitable for resource-constrained environments.This study also applies a carefully designed data pre-processing flow,including class balancing and noise removal,which improves the reliability and reproducibility of the results.These aspects highlight the potential application of the LVQ model in cardiac diagnostics,opening up prospects for its use along with more complex neural network architectures.展开更多
This article aims to enhance seismic hazard assessment methods for Kazakhstan’s seismotectonic conditions.It combines probabilistic seismic hazard analysis(PSHA),ground motion simulation,sitespecific geological and g...This article aims to enhance seismic hazard assessment methods for Kazakhstan’s seismotectonic conditions.It combines probabilistic seismic hazard analysis(PSHA),ground motion simulation,sitespecific geological and geotechnical data analysis,and seismic scenario analysis to develop Probabilistic General Seismic Zoning(GSZ)maps for Kazakhstan and Probabilistic Seismic Microzoning maps for Almaty.These maps align with Eurocode 8 principles,incorporating seismic intensity and engineering parameters like peak ground acceleration(PGA).The new procedure,applied in national projects,has resulted in GSZ maps for the country,seismic microzoning maps for Almaty,and detailed seismic zoning maps for East Kazakhstan.These maps,part of a regulatory document,guide earthquake-resistant design and construction.They offer a comprehensive assessment of seismic hazards,integrating traditional Medvedev-Sponheuer-Karnik(MSK-64)intensity scale points with quantitative parameters like peak ground acceleration.This innovative approach promises to advance methods for quantifying seismic hazards in specific regions.展开更多
This study focuses on the real-world context where artificial intelligence(AI)deeply permeates corporate operations,systematically exploring the core value,challenges,and optimization paths of corporate culture manage...This study focuses on the real-world context where artificial intelligence(AI)deeply permeates corporate operations,systematically exploring the core value,challenges,and optimization paths of corporate culture management during the process of intelligent transformation.By deeply analyzing the semantic deviations in the digitalization of cultural elements and the potential conflicts between algorithm-based decision-making and humanistic values in human-machine collaboration scenarios,and combining theories of organizational behavior with the characteristics of AI technology,a series of strategies for enhancing effectiveness are proposed,including dynamic cultural modeling and embedding cognitive-collaborative rules.With detailed empirical data and case studies,this research provides a theoretical basis and practical guidance for enterprises to achieve a dynamic balance between technological rationality and humanistic care.展开更多
Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing,enabling automated lesion detection,physiological monitoring,and therapy planning with accuracy that rivals expert p...Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing,enabling automated lesion detection,physiological monitoring,and therapy planning with accuracy that rivals expert performance.This survey reviews the principal model families as convolutional,recurrent,generative,reinforcement,autoencoder,and transfer-learning approaches as emphasising how their architectural choices map to tasks such as segmentation,classification,reconstruction,and anomaly detection.A dedicated treatment of multimodal fusion networks shows how imaging features can be integrated with genomic profiles and clinical records to yield more robust,context-aware predictions.To support clinical adoption,we outline post-hoc explainability techniques(Grad-CAM,SHAP,LIME)and describe emerging intrinsically interpretable designs that expose decision logic to end users.Regulatory guidance from the U.S.FDA,the European Medicines Agency,and the EU AI Act is summarised,linking transparency and lifecycle-monitoring requirements to concrete development practices.Remaining challenges as data imbalance,computational cost,privacy constraints,and cross-domain generalization are discussed alongside promising solutions such as federated learning,uncertainty quantification,and lightweight 3-D architectures.The article therefore offers researchers,clinicians,and policymakers a concise,practice-oriented roadmap for deploying trustworthy deep-learning systems in healthcare.展开更多
This study explores the cultural and value foundations of the educational goals of higher education in Kazakhstan and China.Based on the historical development and cultural traditions of the two countries,this study c...This study explores the cultural and value foundations of the educational goals of higher education in Kazakhstan and China.Based on the historical development and cultural traditions of the two countries,this study compares the similarities and differences of the educational goals of the two countries through qualitative literature content analysis.Both countries have taken“modernization and internationalization”as one of the core development directions of higher education development,but China’s educational philosophy is rooted in Confucianism and socialist core values,emphasizing country and collectivism;while Kazakhstan,based on neoliberal orientation,draws on the European education framework,gradually integrates multicultural concepts,emphasizes national identity and attaches importance to students’individual development.This study uses Hofstede’s cultural dimensions and postcolonial education theory to explore how different nation-building narratives affect the educational goals of higher education.By comparing value systems,institutional logics,and student training models,it helps to understand how the educational systems of the“Global South”countries seek a balance between international standards and local cultural identity.It provides inspiration for the development of education based on culture and mutual reference under the global education trend,and provides a comparative education perspective for reform localization.展开更多
Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path...Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility,motivating control-aware trajectory generation.This study presents a novel model predictive control(MPC)framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization.Unlike conventional interpolation techniques such as cubic splines,B-splines,and linear interpolation,which neglect physical constraints and system dynamics,the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while minimizing both tracking error and control effort.A key innovation lies in the use of Pareto front analysis for tuning prediction horizon and sampling time,enabling a systematic balance between accuracy and motion smoothness.Comparative evaluation using simulated experiments demonstrates that the proposed MPC approach achieves a minimum mean absolute error(MAE)of 0.170 and reduces maximum acceleration to 0.0217,compared to 0.0385 in classical linear methods.The maximum deviation error was also reduced by approximately 27.4%relative to MPC configurations without tuned parameters.All experiments were conducted in a simulation environment,with computational times per control cycle consistently remaining below 20 milliseconds,indicating practical feasibility for real-time applications.Thiswork advances the state-of-the-art inMPC-based trajectory planning by offering a scalable and interpretable control architecture that meets physical constraints while optimizing motion efficiency,thus making it suitable for deployment in safety-critical robotic applications.展开更多
A plasma screening model that accounts for electronic exchange-correlation effects and ionic nonideality in dense quantum plasmas is proposed.This model can be used as an input in various plasma interaction models to ...A plasma screening model that accounts for electronic exchange-correlation effects and ionic nonideality in dense quantum plasmas is proposed.This model can be used as an input in various plasma interaction models to calculate scattering cross-sections and transport properties.The applicability of the proposed plasma screening model is demonstrated using the example of the temperature relaxation rate in dense hydrogen and warm dense aluminum.Additionally,the conductivity of warm dense aluminum is computed in the regime where collisions are dominated by electron-ion scattering.The results obtained are compared with available theoretical results and simulation data.展开更多
BACKGROUND For over half a century,the administration of maternal corticosteroids before anticipated preterm birth has been regarded as a cornerstone intervention for enhancing neonatal outcomes,particularly in preven...BACKGROUND For over half a century,the administration of maternal corticosteroids before anticipated preterm birth has been regarded as a cornerstone intervention for enhancing neonatal outcomes,particularly in preventing respiratory distress syndrome.Ongoing research on antenatal corticosteroids(ACS)is continuously refining the evidence regarding their efficacy and potential side effects,which may alter the application of this treatment.Recent findings indicate that in resource-limited settings,the effectiveness of ACS is contingent upon meeting specific conditions,including providing adequate medical support for preterm newborns.Future studies are expected to concentrate on developing evidence-based strategies to safely enhance ACS utilization in low-and middle-income countries.AIM To analyze the clinical effectiveness of antenatal corticosteroids in improving outcomes for preterm newborns in a tertiary care hospital setting in Kazakhstan,following current World Health Organization guidelines.METHODS This study employs a comparative retrospective cohort design to analyze single-center clinical data collected from January 2022 to February 2024.A total of 152 medical records of preterm newborns with gestational ages between 24 and 34 weeks were reviewed,focusing on the completeness of the ACS received.Quantitative variables are presented as means with standard deviations,while frequency analysis of qualitative indicators was performed using Pearson'sχ^(2) test(χ^(2))and Fisher's exact test.If statistical significance was identified,pairwise comparisons between the three observation groups were conducted using the Bonferroni correction.RESULTS The obtained data indicate that the complete implementation of antenatal steroid prophylaxis(ASP)improves neonatal outcomes,particularly by reducing the frequency of birth asphyxia(P=0.002),the need for primary resuscitation(P=0.002),the use of nasal continuous positive airway pressure(P=0.022),and the need for surfactant replacement therapy(P=0.038)compared to groups with incomplete or no ASP.Furthermore,complete ASP contributed to a decrease in morbidity among preterm newborns(e.g.,respiratory distress syndrome,intrauterine pneumonia,cerebral ischemia,bronchopulmonary dysplasia,etc.),improved Apgar scores,and reduced the need for re-intubation and the frequency of mechanical ventilation.However,it was associated with an increased incidence of uterine atony in postpartum women(P=0.0095).CONCLUSION In a tertiary hospital setting,the implementation of ACS therapy for pregnancies between 24 and 34 weeks of gestation at high risk for preterm birth significantly reduces the incidence of neonatal complications and related interventions.This,in turn,contributes to better outcomes for this cohort of children.However,the impact of ACS on maternal outcomes requires further thorough investigation.展开更多
Chronic suppurative otitis media(CSOM)is a prevalent condition in otolaryngology with significant medical and social implications,including hearing loss and severe intracranial complications.This article discusses the...Chronic suppurative otitis media(CSOM)is a prevalent condition in otolaryngology with significant medical and social implications,including hearing loss and severe intracranial complications.This article discusses the challenges in diagnosing cholesteatoma,a common complication of CSOM,particularly when using computed tomography(CT)and magnetic resonance imaging(MRI).We present three clinical cases where MRI,particularly in the non-EPI diffusion-weighted imaging(DWI)and apparent diffusion coefficient(ADC)modes,effectively identified the presence and extent of cholesteatoma that CT could not reliably distinguish due to overlapping features with other soft tissue formations.The high sensitivity of MRI,highlight its value in both primary diagnosis and assessment of recurrence.Our findings advocate for the incorporation of MRI into the diagnostic protocols for CSOM in the Republic of Kazakhstan,emphasizing the need for reliable epidemiological data to inform future research and prevent potential intracranial complications.展开更多
This paper examines the application of the Verkle tree—an efficient data structure that leverages commitments and a novel proof technique in cryptographic solutions.Unlike traditional Merkle trees,the Verkle tree sig...This paper examines the application of the Verkle tree—an efficient data structure that leverages commitments and a novel proof technique in cryptographic solutions.Unlike traditional Merkle trees,the Verkle tree significantly reduces signature size by utilizing polynomial and vector commitments.Compact proofs also accelerate the verification process,reducing computational overhead,which makes Verkle trees particularly useful.The study proposes a new approach based on a non-positional polynomial notation(NPN)employing the Chinese Remainder Theorem(CRT).CRT enables efficient data representation and verification by decomposing data into smaller,indepen-dent components,simplifying computations,reducing overhead,and enhancing scalability.This technique facilitates parallel data processing,which is especially advantageous in cryptographic applications such as commitment and proof construction in Verkle trees,as well as in systems with constrained computational resources.Theoretical foundations of the approach,its advantages,and practical implementation aspects are explored,including resistance to potential attacks,application domains,and a comparative analysis with existing methods based on well-known parameters and characteristics.An analysis of potential attacks and vulnerabilities,including greatest common divisor(GCD)attacks,approximate multiple attacks(LLL lattice-based),brute-force search for irreducible polynomials,and the estimation of their total number,indicates that no vulnerabilities have been identified in the proposed method thus far.Furthermore,the study demonstrates that integrating CRT with Verkle trees ensures high scalability,making this approach promising for blockchain systems and other distributed systems requiring compact and efficient proofs.展开更多
Biometric authentication provides a reliable,user-specific approach for identity verification,significantly enhancing access control and security against unauthorized intrusions in cybersecurity.Unimodal biometric sys...Biometric authentication provides a reliable,user-specific approach for identity verification,significantly enhancing access control and security against unauthorized intrusions in cybersecurity.Unimodal biometric systems that rely on either face or voice recognition encounter several challenges,including inconsistent data quality,environmental noise,and susceptibility to spoofing attacks.To address these limitations,this research introduces a robust multi-modal biometric recognition framework,namely Quantum-Enhanced Biometric Fusion Network.The proposed model strengthens security and boosts recognition accuracy through the fusion of facial and voice features.Furthermore,the model employs advanced pre-processing techniques to generate high-quality facial images and voice recordings,enabling more efficient face and voice recognition.Augmentation techniques are deployed to enhance model performance by enriching the training dataset with diverse and representative samples.The local features are extracted using advanced neural methods,while the voice features are extracted using a Pyramid-1D Wavelet Convolutional Bidirectional Network,which effectively captures speech dynamics.The Quantum Residual Network encodes facial features into quantum states,enabling powerful quantum-enhanced representations.These normalized feature sets are fused using an early fusion strategy that preserves complementary spatial-temporal characteristics.The experimental validation is conducted using a biometric audio and video dataset,with comprehensive evaluations including ablation and statistical analyses.The experimental analyses ensure that the proposed model attains superior performance,outperforming existing biometric methods with an average accuracy of 98.99%.The proposed model improves recognition robustness,making it an efficient multimodal solution for cybersecurity applications.展开更多
While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong perfor...While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong performance in visual recognition and factual description,they often fail to account for the emotional context that is naturally present in human-generated captions.To address this gap,we propose the Sentiment-Driven Caption Generator(SDCG),which combines transformer-based visual and textual processing withmulti-level fusion.RoBERTa is used for extracting sentiment from textual input,while visual features are handled by the Vision Transformer(ViT).These features are fused using several fusion approaches,including Concatenation,Attention,Visual-Sentiment Co-Attention(VSCA),and Cross-Attention.Our experiments demonstrate that SDCG significantly outperforms baseline models such as the Generalized Image Transformer(GIT),which achieves 82.01%,and Bootstrapping Language-Image Pre-training(BLIP),which achieves 83.07%,in sentiment accuracy.While SDCG achieves 94.52%sentiment accuracy and improves scores in BLEU and ROUGE-L,the model demonstrates clear advantages.More importantly,the captions aremore natural,as they incorporate emotional cues and contextual awareness,making them resemble those written by a human.展开更多
The increasing atmospheric CO_(2)concentration linked to human activity results in global warming by the greenhouse effect.This anthropogenic CO_(2)may be sequestrated into geological formations,e.g.,porous basalts,sa...The increasing atmospheric CO_(2)concentration linked to human activity results in global warming by the greenhouse effect.This anthropogenic CO_(2)may be sequestrated into geological formations,e.g.,porous basalts,saline aquifers,depleted oil or gas reservoirs,and unmineable coal seams.Furthermore,carbon capture,utilization,and storage(CCUS)methods are an acceptable and sustainable technology to meet the goals of the Paris Agreement,in which Kazakhstan is expected to reduce greenhouse gas emissions by 25%compared with the 1990 level.Unmineable coal seams are an attractive option among all geostorage solutions,as CO_(2)sequestration in coal comes with an income stream via enhanced coalbed methane(ECBM)recovery.This paper identifies four carboniferous coal formations,namely Karagandy,Teniz-Korzhinkol,Ekibustuz,and Chu coal basins of Kazakhstan,as CO_(2)geostorage solutions for their unmineable coal seams.The ideal depth of CO_(2)storage is identified as 800 m to ensure the supercritical state of CO_(2).However,the Ekibustuz coal basin fails to meet the required depth of 800 m in its unmineable coal seams.The conventional formula for calculating CO_(2)storage in coal basins has been modified,and a new formula has been proposed for assessing the CO_(2)storage potential in a coal seam.The CO_(2)storage capacities of unmineable coal seam of these coal basins are 24.60 Bt,0.61 Bt,14.02 Bt,and 5.42 Bt,respectively.The Langmuir volume of the coal fields was calculated using the proximate analysis of coalfields and found to vary between 36.42 and 98.90 m3/ton.This paper is the first to outline CO_(2)storage potential in Kazakhstani coal basins,albeit with limited data,along with a detailed geological and paleographic review of the carboniferous coalfields of Kazakhstan.A short overview of the CO_(2)-ECBM process was also included in the paper.Instead of any experimental work for CO_(2)storage,this paper attempts to present the CO_(2)storage capacity of carboniferous coal formation using the modified version of previously determined formulas for CO_(2)storage.展开更多
Understanding migration patterns and spatial connectivity is crucial for conserving long-distance migratory birds. While satellite telemetry has advanced the study of large gulls, Pallas's Gull (Ichthyaetus ichthy...Understanding migration patterns and spatial connectivity is crucial for conserving long-distance migratory birds. While satellite telemetry has advanced the study of large gulls, Pallas's Gull (Ichthyaetus ichthyaetus) remains relatively understudied, with limited data on its migration routes and habitat use, particularly in Central Asia. This study integrates 684 ring recoveries (1968–2024) and GPS tracking data to analyze the migration ecology of individuals breeding at Alakol Lake, Kazakhstan. Ring recoveries confirm migratory connectivity across Kazakhstan, Russia, Uzbekistan, Turkmenistan, Iran, and Pakistan, with wintering records as far as India, Kuwait, Bangladesh, and Ethiopia. GPS tracking of a single individual (June 2020–August 2021) revealed a migration route from Alakol Lake to the Arabian Sea, with key stopovers at Zaisan Lake, Balkhash Lake, the Aral Sea, Aydar Lake, and the Amu Darya River. Notably, a post-breeding northward dispersal to Zaisan Lake and southern Russia was identified before the southward migration commenced. These findings highlight the significance of Kazakhstan's lakes as breeding and migratory hubs and the need to protect critical stopover sites in Central Asia. Given increasing anthropogenic pressures on wetland habitats, this research provides essential baseline data for conservation planning and enhances the broader understanding of gull migration ecology.展开更多
Local cattle breeds play a critical role in breeding programs due to their genetic adaptations to diverse environmental conditions.However,the genomic architecture of local cattle breeds in Kazakhstan remains largely ...Local cattle breeds play a critical role in breeding programs due to their genetic adaptations to diverse environmental conditions.However,the genomic architecture of local cattle breeds in Kazakhstan remains largely unexplored.This study utilized whole-genome sequencing data from Kazakh cattle to elucidate their genetic composition,uncovering three primary ancestral components:European,Eurasian,and East Asian taurine.The East Asian taurine lineage likely represents the earliest genetic contribution to Kazakh cattle but was largely replaced by subsequent waves of cattle migrations across Eurasia,leaving only a minor genetic signature in the current cattle population.In contrast,Eurasian taurine ancestry predominated in the Alatau and Kazakh local breeds,while the European taurine component was most prevalent in Kazakh white-headed cattle,consistent with their documented breeding history.Kazakh cattle exhibited higher genetic diversity and lower inbreeding coefficients compared to European commercial breeds,reflecting reduced exposure to intense artificial selection.A strong selection signal was identified on chromosome 6 at a locus encompassing PDGFRA,KIT,and KDR,which may be associated with the white-headed pigmentation characteristic of Kazakh white-headed cattle.Additional genes under selection were linked to lipid metabolism(IRS1,PRKG1,and ADCY8),meat production traits(KCNMA1,PDGFRA,HIF1A,and ANTXR1),and dairy production(ATP2B1,DHX15,FUK,NEGR1,CCDC91,COG4,and PTK2B).This study represents the first comprehensive analysis of nuclear genome data from local Kazakh cattle.It highlights the impact of historical cattle migrations across Eurasia on their genetic landscape and identifies key genomic regions under selection.These findings advance our understanding of the evolutionary history of cattle and offer valuable genetic resources for future breeding strategies.展开更多
In this review research,the full bio-medical potential and application of the severe acute respiratory syndrome(SARS)-CoV-2 viruses are discussed in detail with the aim of discovering innovative treatment strategies i...In this review research,the full bio-medical potential and application of the severe acute respiratory syndrome(SARS)-CoV-2 viruses are discussed in detail with the aim of discovering innovative treatment strategies in virology and medicine.The SARS-CoV-2 which caused an international health crisis also unraveled an opportunity to gain from its pathogenic effects to treat the affected people.The study aims at testing whether the newly discovered SARS-CoV-2 can be used for therapeutic and clinical purposes.With in-depth analytics,this investigation issue endeavors to unearth new ways of fighting infectious diseases and to improve existing medical interventions.Beside scientific and practical significance the role of this work is vital.By learning the biologic and molecular mysteries of SARS-CoV-2,the researchers can create precise medicines and vaccines not only against COVID-19 but also the other infectious diseases as well.Furthermore,this recommendation may open the door to the future development of gene therapy and vaccine technology.In this sense,it combines multiple approaches,such as viral studies,immunology,and molecular biology.Laboratory experiments,computer program modeling and clinical trials are applied to detection of the SARS-COV-2 in therapeutic implementation.The principal conclusion and analysis of this research put forth the fact that SARS-CoV-2 can be utilized in anti-viral treatment,cancer therapy,and vaccine programs.The study results confirm the inherent adaptability of viruses like SARS-CoV-2 and emphasis on the development of specific therapeutic measures.It is valuable because of its potential to add to virology and medication,showing new ways for virus-based treatment.In addition,the impact of these results on treatments would be revolutionary,with potential to invent superior and flexible interventions against infectious disease.In short,the therapeutic use of SARS-CoV-2 can be regarded as a bold innovation with tremendous consequences for general health,and ultimately for medical science.展开更多
文摘The prevalence of tinnitus is increasing worldwide along with the aging population.The absence of a gold standard for diagnosis and treatment makes it difficult to assess the health status of a patient with tinnitus.The aim was to determine the prevalence of tinnitus among older adults in Almaty city and to evaluate the healthcare experience among the respondents who received treatment for tinnitus.Methods:A cross-sectional study was conducted among people aged 18 years and above in Almaty city.The data were collected using a questionnaire sent via a Google form and/or as a printed version.Fully completed responses were received from 851 respondents.The questionnaire consists of 31 questions.Simple and multiple logistic regression analyses were performed to identify the risk factors of tinnitus.Results:The prevalence of tinnitus in Almaty was 23.3%.The data showed that smoking and sleep regimen were associated with tinnitus.Older respondents indicated more symptoms associated with tinnitus than younger respondents did.Additional consultation was needed as part of the treatment of tinnitus.In addition,49.4%of the respondents indicated a need of a support group for people with tinnitus.The respondents also indicated that the access to appropriate resources for the treatment of tinnitus was poor.Conclusion:Similar to other studies,this analysis confirmed that tinnitus is prevalent in the adult population of Almaty city.Future activities should include measures for the improvement of public awareness of the risk factors of tinnitus,and multidisciplinary teamwork among healthcare specialists should be improved.
基金provided through the Ministry of Education and Sciencecarried out as a part of the project“Development of the Seismic Microzonation Map for the Territory of Almaty City on a New Methodical Base”(state registration No 0115RK02701)funded within the state funding.
文摘Seismic microzonation for Almaty city for the first time use probabilistic approach and hazard is expressed in terms of not only macroseismic intensity,but also Peak Ground Acceleration(PGA).To account for the effects of local soil conditions,the continual approach proposed by A.S.Aleshin[1,2]was used,in which soil coefficients are a function of the continuously changing seismic rigidity.Soil coefficients were calculated using the new data of geological and geophysical surveys and findings of previous geotechnical studies.The used approach made it possible to avoid using soil categories and a jump change in characteristics of soil conditions and seismic impact.The developed seismic microzonation maps are prepared for further introduction into the normative documents of the Republic of Kazakhstan.
基金funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan,grant numbers AP14969403 and AP23485820.
文摘Myocardial infarction(MI)is one of the leading causes of death globally among cardiovascular diseases,necessitating modern and accurate diagnostics for cardiac patient conditions.Among the available functional diagnostic methods,electrocardiography(ECG)is particularly well-known for its ability to detect MI.However,confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in practice.This study,therefore,proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of MI.In particular,the learning vector quantization(LVQ)algorithm was applied,considering the contribution of each ECG lead in the 12-channel system,which obtained an accuracy of 87%in localizing damaged myocardium.The developed model was tested on verified data from the PTB database,including 445 ECG recordings from both healthy individuals and MI-diagnosed patients.The results demonstrated that the 12-lead ECG system allows for a comprehensive understanding of cardiac activities in myocardial infarction patients,serving as an essential tool for the diagnosis of myocardial conditions and localizing their damage.A comprehensive comparison was performed,including CNN,SVM,and Logistic Regression,to evaluate the proposed LVQ model.The results demonstrate that the LVQ model achieves competitive performance in diagnostic tasks while maintaining computational efficiency,making it suitable for resource-constrained environments.This study also applies a carefully designed data pre-processing flow,including class balancing and noise removal,which improves the reliability and reproducibility of the results.These aspects highlight the potential application of the LVQ model in cardiac diagnostics,opening up prospects for its use along with more complex neural network architectures.
基金The work was carried out in the framework of earmarked funding“Assessment of seismic hazard of territories of Kazakhstan on modern scientific and methodological basis”,programme code number F.0980.Source of funding-Ministry of Science and Higher Education of the Republic of Kazakhstan.
文摘This article aims to enhance seismic hazard assessment methods for Kazakhstan’s seismotectonic conditions.It combines probabilistic seismic hazard analysis(PSHA),ground motion simulation,sitespecific geological and geotechnical data analysis,and seismic scenario analysis to develop Probabilistic General Seismic Zoning(GSZ)maps for Kazakhstan and Probabilistic Seismic Microzoning maps for Almaty.These maps align with Eurocode 8 principles,incorporating seismic intensity and engineering parameters like peak ground acceleration(PGA).The new procedure,applied in national projects,has resulted in GSZ maps for the country,seismic microzoning maps for Almaty,and detailed seismic zoning maps for East Kazakhstan.These maps,part of a regulatory document,guide earthquake-resistant design and construction.They offer a comprehensive assessment of seismic hazards,integrating traditional Medvedev-Sponheuer-Karnik(MSK-64)intensity scale points with quantitative parameters like peak ground acceleration.This innovative approach promises to advance methods for quantifying seismic hazards in specific regions.
文摘This study focuses on the real-world context where artificial intelligence(AI)deeply permeates corporate operations,systematically exploring the core value,challenges,and optimization paths of corporate culture management during the process of intelligent transformation.By deeply analyzing the semantic deviations in the digitalization of cultural elements and the potential conflicts between algorithm-based decision-making and humanistic values in human-machine collaboration scenarios,and combining theories of organizational behavior with the characteristics of AI technology,a series of strategies for enhancing effectiveness are proposed,including dynamic cultural modeling and embedding cognitive-collaborative rules.With detailed empirical data and case studies,this research provides a theoretical basis and practical guidance for enterprises to achieve a dynamic balance between technological rationality and humanistic care.
基金supported by the Science Committee of the Ministry of Higher Education and Science of the Republic of Kazakhstan within the framework of grant AP23489899“Applying Deep Learning and Neuroimaging Methods for Brain Stroke Diagnosis”.
文摘Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing,enabling automated lesion detection,physiological monitoring,and therapy planning with accuracy that rivals expert performance.This survey reviews the principal model families as convolutional,recurrent,generative,reinforcement,autoencoder,and transfer-learning approaches as emphasising how their architectural choices map to tasks such as segmentation,classification,reconstruction,and anomaly detection.A dedicated treatment of multimodal fusion networks shows how imaging features can be integrated with genomic profiles and clinical records to yield more robust,context-aware predictions.To support clinical adoption,we outline post-hoc explainability techniques(Grad-CAM,SHAP,LIME)and describe emerging intrinsically interpretable designs that expose decision logic to end users.Regulatory guidance from the U.S.FDA,the European Medicines Agency,and the EU AI Act is summarised,linking transparency and lifecycle-monitoring requirements to concrete development practices.Remaining challenges as data imbalance,computational cost,privacy constraints,and cross-domain generalization are discussed alongside promising solutions such as federated learning,uncertainty quantification,and lightweight 3-D architectures.The article therefore offers researchers,clinicians,and policymakers a concise,practice-oriented roadmap for deploying trustworthy deep-learning systems in healthcare.
文摘This study explores the cultural and value foundations of the educational goals of higher education in Kazakhstan and China.Based on the historical development and cultural traditions of the two countries,this study compares the similarities and differences of the educational goals of the two countries through qualitative literature content analysis.Both countries have taken“modernization and internationalization”as one of the core development directions of higher education development,but China’s educational philosophy is rooted in Confucianism and socialist core values,emphasizing country and collectivism;while Kazakhstan,based on neoliberal orientation,draws on the European education framework,gradually integrates multicultural concepts,emphasizes national identity and attaches importance to students’individual development.This study uses Hofstede’s cultural dimensions and postcolonial education theory to explore how different nation-building narratives affect the educational goals of higher education.By comparing value systems,institutional logics,and student training models,it helps to understand how the educational systems of the“Global South”countries seek a balance between international standards and local cultural identity.It provides inspiration for the development of education based on culture and mutual reference under the global education trend,and provides a comparative education perspective for reform localization.
基金funded by the research project“BR24992947—Development of Robots,Scientific,Technical,and Software for Flexible Robotization and Industrial Automation(RPA)in Automotive Industrial Enterprises in Kazakhstan Using Artificial Intelligence”.
文摘Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility,motivating control-aware trajectory generation.This study presents a novel model predictive control(MPC)framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization.Unlike conventional interpolation techniques such as cubic splines,B-splines,and linear interpolation,which neglect physical constraints and system dynamics,the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while minimizing both tracking error and control effort.A key innovation lies in the use of Pareto front analysis for tuning prediction horizon and sampling time,enabling a systematic balance between accuracy and motion smoothness.Comparative evaluation using simulated experiments demonstrates that the proposed MPC approach achieves a minimum mean absolute error(MAE)of 0.170 and reduces maximum acceleration to 0.0217,compared to 0.0385 in classical linear methods.The maximum deviation error was also reduced by approximately 27.4%relative to MPC configurations without tuned parameters.All experiments were conducted in a simulation environment,with computational times per control cycle consistently remaining below 20 milliseconds,indicating practical feasibility for real-time applications.Thiswork advances the state-of-the-art inMPC-based trajectory planning by offering a scalable and interpretable control architecture that meets physical constraints while optimizing motion efficiency,thus making it suitable for deployment in safety-critical robotic applications.
基金funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan Grant No.AP19678033“The study of the transport and optical properties of hydrogen at high pressure.”。
文摘A plasma screening model that accounts for electronic exchange-correlation effects and ionic nonideality in dense quantum plasmas is proposed.This model can be used as an input in various plasma interaction models to calculate scattering cross-sections and transport properties.The applicability of the proposed plasma screening model is demonstrated using the example of the temperature relaxation rate in dense hydrogen and warm dense aluminum.Additionally,the conductivity of warm dense aluminum is computed in the regime where collisions are dominated by electron-ion scattering.The results obtained are compared with available theoretical results and simulation data.
基金Supported by Non-profit Joint Stock Company“S.D.Asfendiyarov Kazakh National Medical University”,Almaty,Kazakhstan。
文摘BACKGROUND For over half a century,the administration of maternal corticosteroids before anticipated preterm birth has been regarded as a cornerstone intervention for enhancing neonatal outcomes,particularly in preventing respiratory distress syndrome.Ongoing research on antenatal corticosteroids(ACS)is continuously refining the evidence regarding their efficacy and potential side effects,which may alter the application of this treatment.Recent findings indicate that in resource-limited settings,the effectiveness of ACS is contingent upon meeting specific conditions,including providing adequate medical support for preterm newborns.Future studies are expected to concentrate on developing evidence-based strategies to safely enhance ACS utilization in low-and middle-income countries.AIM To analyze the clinical effectiveness of antenatal corticosteroids in improving outcomes for preterm newborns in a tertiary care hospital setting in Kazakhstan,following current World Health Organization guidelines.METHODS This study employs a comparative retrospective cohort design to analyze single-center clinical data collected from January 2022 to February 2024.A total of 152 medical records of preterm newborns with gestational ages between 24 and 34 weeks were reviewed,focusing on the completeness of the ACS received.Quantitative variables are presented as means with standard deviations,while frequency analysis of qualitative indicators was performed using Pearson'sχ^(2) test(χ^(2))and Fisher's exact test.If statistical significance was identified,pairwise comparisons between the three observation groups were conducted using the Bonferroni correction.RESULTS The obtained data indicate that the complete implementation of antenatal steroid prophylaxis(ASP)improves neonatal outcomes,particularly by reducing the frequency of birth asphyxia(P=0.002),the need for primary resuscitation(P=0.002),the use of nasal continuous positive airway pressure(P=0.022),and the need for surfactant replacement therapy(P=0.038)compared to groups with incomplete or no ASP.Furthermore,complete ASP contributed to a decrease in morbidity among preterm newborns(e.g.,respiratory distress syndrome,intrauterine pneumonia,cerebral ischemia,bronchopulmonary dysplasia,etc.),improved Apgar scores,and reduced the need for re-intubation and the frequency of mechanical ventilation.However,it was associated with an increased incidence of uterine atony in postpartum women(P=0.0095).CONCLUSION In a tertiary hospital setting,the implementation of ACS therapy for pregnancies between 24 and 34 weeks of gestation at high risk for preterm birth significantly reduces the incidence of neonatal complications and related interventions.This,in turn,contributes to better outcomes for this cohort of children.However,the impact of ACS on maternal outcomes requires further thorough investigation.
文摘Chronic suppurative otitis media(CSOM)is a prevalent condition in otolaryngology with significant medical and social implications,including hearing loss and severe intracranial complications.This article discusses the challenges in diagnosing cholesteatoma,a common complication of CSOM,particularly when using computed tomography(CT)and magnetic resonance imaging(MRI).We present three clinical cases where MRI,particularly in the non-EPI diffusion-weighted imaging(DWI)and apparent diffusion coefficient(ADC)modes,effectively identified the presence and extent of cholesteatoma that CT could not reliably distinguish due to overlapping features with other soft tissue formations.The high sensitivity of MRI,highlight its value in both primary diagnosis and assessment of recurrence.Our findings advocate for the incorporation of MRI into the diagnostic protocols for CSOM in the Republic of Kazakhstan,emphasizing the need for reliable epidemiological data to inform future research and prevent potential intracranial complications.
基金funded by the Ministry of Science and Higher Education of Kazakhstan and carried out within the framework of the project AP23488112“Development and study of a quantum-resistant digital signature scheme based on a Verkle tree”at the Institute of Information and Computational Technologies.
文摘This paper examines the application of the Verkle tree—an efficient data structure that leverages commitments and a novel proof technique in cryptographic solutions.Unlike traditional Merkle trees,the Verkle tree significantly reduces signature size by utilizing polynomial and vector commitments.Compact proofs also accelerate the verification process,reducing computational overhead,which makes Verkle trees particularly useful.The study proposes a new approach based on a non-positional polynomial notation(NPN)employing the Chinese Remainder Theorem(CRT).CRT enables efficient data representation and verification by decomposing data into smaller,indepen-dent components,simplifying computations,reducing overhead,and enhancing scalability.This technique facilitates parallel data processing,which is especially advantageous in cryptographic applications such as commitment and proof construction in Verkle trees,as well as in systems with constrained computational resources.Theoretical foundations of the approach,its advantages,and practical implementation aspects are explored,including resistance to potential attacks,application domains,and a comparative analysis with existing methods based on well-known parameters and characteristics.An analysis of potential attacks and vulnerabilities,including greatest common divisor(GCD)attacks,approximate multiple attacks(LLL lattice-based),brute-force search for irreducible polynomials,and the estimation of their total number,indicates that no vulnerabilities have been identified in the proposed method thus far.Furthermore,the study demonstrates that integrating CRT with Verkle trees ensures high scalability,making this approach promising for blockchain systems and other distributed systems requiring compact and efficient proofs.
文摘Biometric authentication provides a reliable,user-specific approach for identity verification,significantly enhancing access control and security against unauthorized intrusions in cybersecurity.Unimodal biometric systems that rely on either face or voice recognition encounter several challenges,including inconsistent data quality,environmental noise,and susceptibility to spoofing attacks.To address these limitations,this research introduces a robust multi-modal biometric recognition framework,namely Quantum-Enhanced Biometric Fusion Network.The proposed model strengthens security and boosts recognition accuracy through the fusion of facial and voice features.Furthermore,the model employs advanced pre-processing techniques to generate high-quality facial images and voice recordings,enabling more efficient face and voice recognition.Augmentation techniques are deployed to enhance model performance by enriching the training dataset with diverse and representative samples.The local features are extracted using advanced neural methods,while the voice features are extracted using a Pyramid-1D Wavelet Convolutional Bidirectional Network,which effectively captures speech dynamics.The Quantum Residual Network encodes facial features into quantum states,enabling powerful quantum-enhanced representations.These normalized feature sets are fused using an early fusion strategy that preserves complementary spatial-temporal characteristics.The experimental validation is conducted using a biometric audio and video dataset,with comprehensive evaluations including ablation and statistical analyses.The experimental analyses ensure that the proposed model attains superior performance,outperforming existing biometric methods with an average accuracy of 98.99%.The proposed model improves recognition robustness,making it an efficient multimodal solution for cybersecurity applications.
基金funded by the Committee of Science of the Ministry of Science andHigher Education of the Republic of Kazakhstan(Grant No.BR24993166).
文摘While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong performance in visual recognition and factual description,they often fail to account for the emotional context that is naturally present in human-generated captions.To address this gap,we propose the Sentiment-Driven Caption Generator(SDCG),which combines transformer-based visual and textual processing withmulti-level fusion.RoBERTa is used for extracting sentiment from textual input,while visual features are handled by the Vision Transformer(ViT).These features are fused using several fusion approaches,including Concatenation,Attention,Visual-Sentiment Co-Attention(VSCA),and Cross-Attention.Our experiments demonstrate that SDCG significantly outperforms baseline models such as the Generalized Image Transformer(GIT),which achieves 82.01%,and Bootstrapping Language-Image Pre-training(BLIP),which achieves 83.07%,in sentiment accuracy.While SDCG achieves 94.52%sentiment accuracy and improves scores in BLEU and ROUGE-L,the model demonstrates clear advantages.More importantly,the captions aremore natural,as they incorporate emotional cues and contextual awareness,making them resemble those written by a human.
文摘The increasing atmospheric CO_(2)concentration linked to human activity results in global warming by the greenhouse effect.This anthropogenic CO_(2)may be sequestrated into geological formations,e.g.,porous basalts,saline aquifers,depleted oil or gas reservoirs,and unmineable coal seams.Furthermore,carbon capture,utilization,and storage(CCUS)methods are an acceptable and sustainable technology to meet the goals of the Paris Agreement,in which Kazakhstan is expected to reduce greenhouse gas emissions by 25%compared with the 1990 level.Unmineable coal seams are an attractive option among all geostorage solutions,as CO_(2)sequestration in coal comes with an income stream via enhanced coalbed methane(ECBM)recovery.This paper identifies four carboniferous coal formations,namely Karagandy,Teniz-Korzhinkol,Ekibustuz,and Chu coal basins of Kazakhstan,as CO_(2)geostorage solutions for their unmineable coal seams.The ideal depth of CO_(2)storage is identified as 800 m to ensure the supercritical state of CO_(2).However,the Ekibustuz coal basin fails to meet the required depth of 800 m in its unmineable coal seams.The conventional formula for calculating CO_(2)storage in coal basins has been modified,and a new formula has been proposed for assessing the CO_(2)storage potential in a coal seam.The CO_(2)storage capacities of unmineable coal seam of these coal basins are 24.60 Bt,0.61 Bt,14.02 Bt,and 5.42 Bt,respectively.The Langmuir volume of the coal fields was calculated using the proximate analysis of coalfields and found to vary between 36.42 and 98.90 m3/ton.This paper is the first to outline CO_(2)storage potential in Kazakhstani coal basins,albeit with limited data,along with a detailed geological and paleographic review of the carboniferous coalfields of Kazakhstan.A short overview of the CO_(2)-ECBM process was also included in the paper.Instead of any experimental work for CO_(2)storage,this paper attempts to present the CO_(2)storage capacity of carboniferous coal formation using the modified version of previously determined formulas for CO_(2)storage.
基金funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan,the Scientific Program BR21882199–Cadastre of wild animals of arid territories of the Balkhash-Alakol basin with an assessment of threats for their conservation and sustainable use.
文摘Understanding migration patterns and spatial connectivity is crucial for conserving long-distance migratory birds. While satellite telemetry has advanced the study of large gulls, Pallas's Gull (Ichthyaetus ichthyaetus) remains relatively understudied, with limited data on its migration routes and habitat use, particularly in Central Asia. This study integrates 684 ring recoveries (1968–2024) and GPS tracking data to analyze the migration ecology of individuals breeding at Alakol Lake, Kazakhstan. Ring recoveries confirm migratory connectivity across Kazakhstan, Russia, Uzbekistan, Turkmenistan, Iran, and Pakistan, with wintering records as far as India, Kuwait, Bangladesh, and Ethiopia. GPS tracking of a single individual (June 2020–August 2021) revealed a migration route from Alakol Lake to the Arabian Sea, with key stopovers at Zaisan Lake, Balkhash Lake, the Aral Sea, Aydar Lake, and the Amu Darya River. Notably, a post-breeding northward dispersal to Zaisan Lake and southern Russia was identified before the southward migration commenced. These findings highlight the significance of Kazakhstan's lakes as breeding and migratory hubs and the need to protect critical stopover sites in Central Asia. Given increasing anthropogenic pressures on wetland habitats, this research provides essential baseline data for conservation planning and enhances the broader understanding of gull migration ecology.
基金supported by the National Key R&D Program of China(2022YFF1000100)China Postdoctoral Science Foundation(2022M722615)。
文摘Local cattle breeds play a critical role in breeding programs due to their genetic adaptations to diverse environmental conditions.However,the genomic architecture of local cattle breeds in Kazakhstan remains largely unexplored.This study utilized whole-genome sequencing data from Kazakh cattle to elucidate their genetic composition,uncovering three primary ancestral components:European,Eurasian,and East Asian taurine.The East Asian taurine lineage likely represents the earliest genetic contribution to Kazakh cattle but was largely replaced by subsequent waves of cattle migrations across Eurasia,leaving only a minor genetic signature in the current cattle population.In contrast,Eurasian taurine ancestry predominated in the Alatau and Kazakh local breeds,while the European taurine component was most prevalent in Kazakh white-headed cattle,consistent with their documented breeding history.Kazakh cattle exhibited higher genetic diversity and lower inbreeding coefficients compared to European commercial breeds,reflecting reduced exposure to intense artificial selection.A strong selection signal was identified on chromosome 6 at a locus encompassing PDGFRA,KIT,and KDR,which may be associated with the white-headed pigmentation characteristic of Kazakh white-headed cattle.Additional genes under selection were linked to lipid metabolism(IRS1,PRKG1,and ADCY8),meat production traits(KCNMA1,PDGFRA,HIF1A,and ANTXR1),and dairy production(ATP2B1,DHX15,FUK,NEGR1,CCDC91,COG4,and PTK2B).This study represents the first comprehensive analysis of nuclear genome data from local Kazakh cattle.It highlights the impact of historical cattle migrations across Eurasia on their genetic landscape and identifies key genomic regions under selection.These findings advance our understanding of the evolutionary history of cattle and offer valuable genetic resources for future breeding strategies.
文摘In this review research,the full bio-medical potential and application of the severe acute respiratory syndrome(SARS)-CoV-2 viruses are discussed in detail with the aim of discovering innovative treatment strategies in virology and medicine.The SARS-CoV-2 which caused an international health crisis also unraveled an opportunity to gain from its pathogenic effects to treat the affected people.The study aims at testing whether the newly discovered SARS-CoV-2 can be used for therapeutic and clinical purposes.With in-depth analytics,this investigation issue endeavors to unearth new ways of fighting infectious diseases and to improve existing medical interventions.Beside scientific and practical significance the role of this work is vital.By learning the biologic and molecular mysteries of SARS-CoV-2,the researchers can create precise medicines and vaccines not only against COVID-19 but also the other infectious diseases as well.Furthermore,this recommendation may open the door to the future development of gene therapy and vaccine technology.In this sense,it combines multiple approaches,such as viral studies,immunology,and molecular biology.Laboratory experiments,computer program modeling and clinical trials are applied to detection of the SARS-COV-2 in therapeutic implementation.The principal conclusion and analysis of this research put forth the fact that SARS-CoV-2 can be utilized in anti-viral treatment,cancer therapy,and vaccine programs.The study results confirm the inherent adaptability of viruses like SARS-CoV-2 and emphasis on the development of specific therapeutic measures.It is valuable because of its potential to add to virology and medication,showing new ways for virus-based treatment.In addition,the impact of these results on treatments would be revolutionary,with potential to invent superior and flexible interventions against infectious disease.In short,the therapeutic use of SARS-CoV-2 can be regarded as a bold innovation with tremendous consequences for general health,and ultimately for medical science.
