Numerous hydrocarbon accumulations are found in ramp crest shoals worldwide and therefore this depositional setting has a high potential of being the hydrocarbon reservoir. In this paper, we combined digital outcrop g...Numerous hydrocarbon accumulations are found in ramp crest shoals worldwide and therefore this depositional setting has a high potential of being the hydrocarbon reservoir. In this paper, we combined digital outcrop geology and traditional geological mapping to build an outcrop-based geocellular model of the ramp-crest shoal complex of the Lower Triassic Feixianguan Formation in the Eastern Sichuan Basin. The outcrop model serves as an analogue for the subsurface reservoir of the Feixianguan Formation and illustrates the complexity of the lithofacies types, stratigraphic architecture, and reservoir heterogeneities at a scale below conventional subsurface data resolution. The studied ramp -crest shoal complex consists of thirteen types of lithofacies that can be grouped into three facies-groups corresponding to subtidal intraclastic shoal, sub- to inter-tidal oolitic shoal, and tidal flat depositional environments respectively. The stratigraphic architecture of the shoal complex shows mostly a strong progradation of the high energy facies associated with an overall decrease of accommodation space associated with relative sea level still stand. Two reservoir facies associations have been recognized. The first one consists of supratidai dolomudstone and upper intertidal partially dolomitized oolitic packstone with anhydrite or nodules. These facies were deposited above the high energy oolitic grainstones and occurs as thin-bedded and laterally continuous layers, characterized by high porosity and low permeability. The second reservoir facies association is composed of intertidal crystalline dolomite and subtidal intraclastic bindstone that occurs stratigraphically below the oolitic grainstones. These deposits consist of massive laterally discontinuously beds, and are characterized by high porosity and high permeability. Both types of reservoir facies tend to be stacked vertically and migrated laterally with the progradation of the shoal complex. The construction of the outcrop-based 3D geological model provide a description and quantification of the facies distribution within a robust stratigraphic framework and the style and amount of reservoir heterogeneities associated with a ramp-crest shoal complex reservoir such as the one found in Lower Triassic Feixianguan Formation and Cambrian Longwangmiao Formation in Sichuan Basin or other ramp-crest reservoir worldwide.展开更多
According to the principle of meshing engagement and the theory of the digitized conjugate surface, this paper applies the software Conjugater-1.0 that is developed by ourselves to compute, respectively, the digitized...According to the principle of meshing engagement and the theory of the digitized conjugate surface, this paper applies the software Conjugater-1.0 that is developed by ourselves to compute, respectively, the digitized conjugate curved surfaces of the straight-tooth surface and drum-tooth surface, which will establish the theoretical and technical foundation for digitized engaging analysis, simulation, and digitized manufacturing technology of the diversified gears.展开更多
Antibiotic abuse now poses a grave threat to global ecology and bestirs public concerns about the residue issue in daily necessities.The traceability measurements along supply chain or logistic circulation have become...Antibiotic abuse now poses a grave threat to global ecology and bestirs public concerns about the residue issue in daily necessities.The traceability measurements along supply chain or logistic circulation have become increasingly essential given the labile nature of diverse synthetic residuals on site.In an attempt to answer this urgency,here a miniaturized fluorometric aptasensor prototype was contrived that catered to the point-of-care screening norm for two typical additives:chloramphenicol and enrofloxacin.The key target-indicating module worked in vitro based on the competitive binding-induced fluorescence recovery of fluorescein-labeled aptamers,which were photobleached beforehand in the format of double helix on burlike nanogold carriers.The“prickly”geometry of the latter not just enriched the capture probes at preferentially substrate-accessible spires;but also contributed to a tip-enhanced surface plasmon effect,sensitizing the signal-on during the duplex dissociation even at nanomolar threshold of the analytes.On the other hand,to encompass a full portable,a set of optical devices were mounted within a 3D-printed cartridge(adaptor)to converge the light beam and route it towards the detector,for which the smartphone camera came up in handy with a home-developed App for calibrating the emissive brightness.Enlightened by the high-dynamic-range compression,an imaging diagnostic algorithm was built in to grid and digitize each slide in the album for augmented detection performance.Thus,a novel bio-to-silico integration was invented that capable of in situ rapid reporting on the antibiotic presence with high sensitivity and selectivity.Further field practices in spiked milk on sales proved the precision and rudimentary feasibility of the well-assembled model of appliance,thus holding nice prospects in nonexpert(e.g.,family and local community)utilities for foodborne antibiotic identification.展开更多
In order to meet the needs of designing and processing digitized surfaces, the method to spreading digitized surface has been proposed. The key technique is to solve the problem of digitized conjugate surface. In the ...In order to meet the needs of designing and processing digitized surfaces, the method to spreading digitized surface has been proposed. The key technique is to solve the problem of digitized conjugate surface. In the paper, the digitized conjugate surface was theoretically investigated, and the solution of conjugate surface based on digitized surface was also studied. The digitized conjugate surface theory was then proposed, and applied to build the model of solving conjugate surface based on digitized surface. A corresponding algorithm was developed. This paper applies the software Conjugater-1.0 that is developed by ourselves to compute the digitized conjugate surfaces of the drum-tooth surface. This study provides theoretical and technical bases for analyzing engagement of digitized surface, simulation and numerical processing technique. Key words digitized conjugate surface - generating method - simulation CLC number O 186.1 - TH 122 Foundation item: Supported by the National Natural Science Foundation of China (50075031)Biography: Xiao Lai-yuan (1957-), male, Professor, Ph. D candidate, research direction: machanical design & theory, digital technology展开更多
Reverse engineering in the manufacturing field is a process in which the digitized data are obtained from an existing object model or a part of it, and then the CAD model is reconstructed. This paper presents an RBF n...Reverse engineering in the manufacturing field is a process in which the digitized data are obtained from an existing object model or a part of it, and then the CAD model is reconstructed. This paper presents an RBF neural network approach to modify and fit the digitized data. The centers for the RBF are selected by using the orthogonal least squares learning algorithm. A mathematically known surface is used for generating a number of samples for training the networks. The trained networks then generated a number of new points which were compared with the calculating points from the equations. Moreover, a series of practice digitizing curves are used to test the approach. The results showed that this approach is effective in modifying and fitting digitized data and generating data points to reconstruct the surface model.展开更多
Metric measurement of digitized shapes is commonly applied in optical measuring systems.In this letter,three shape-related factors defined by the authors are used in the construction of amultiple linear regression mod...Metric measurement of digitized shapes is commonly applied in optical measuring systems.In this letter,three shape-related factors defined by the authors are used in the construction of amultiple linear regression model which is utilized to compute the circumference of the convex shapes inmillimeter unit.The model is first built upon the relationship hypothesis and then its adequacy ismathematically validated.The results of applying the developed model to the given number of convexshapes in a finite circumferential length range suggest that,in terms of percent error,the model pre-cision is to satisfaction by being within±4%.The test also shows the model’s robustness against theshape’s orientation anisotropy.展开更多
As digital technologies have advanced more rapidly,the number of paper documents recently converted into a digital format has exponentially increased.To respond to the urgent need to categorize the growing number of d...As digital technologies have advanced more rapidly,the number of paper documents recently converted into a digital format has exponentially increased.To respond to the urgent need to categorize the growing number of digitized documents,the classification of digitized documents in real time has been identified as the primary goal of our study.A paper classification is the first stage in automating document control and efficient knowledge discovery with no or little human involvement.Artificial intelligence methods such as Deep Learning are now combined with segmentation to study and interpret those traits,which were not conceivable ten years ago.Deep learning aids in comprehending input patterns so that object classes may be predicted.The segmentation process divides the input image into separate segments for a more thorough image study.This study proposes a deep learning-enabled framework for automated document classification,which can be implemented in higher education.To further this goal,a dataset was developed that includes seven categories:Diplomas,Personal documents,Journal of Accounting of higher education diplomas,Service letters,Orders,Production orders,and Student orders.Subsequently,a deep learning model based on Conv2D layers is proposed for the document classification process.In the final part of this research,the proposed model is evaluated and compared with other machine-learning techniques.The results demonstrate that the proposed deep learning model shows high results in document categorization overtaking the other machine learning models by reaching 94.84%,94.79%,94.62%,94.43%,94.07%in accuracy,precision,recall,F-score,and AUC-ROC,respectively.The achieved results prove that the proposed deep model is acceptable to use in practice as an assistant to an office worker.展开更多
Archaeological excavation involves disintegration, removal, and reassembly of the archaeological record;as such it is considered by many to be an unrepeatable, destructive activity. This perception has contributed to ...Archaeological excavation involves disintegration, removal, and reassembly of the archaeological record;as such it is considered by many to be an unrepeatable, destructive activity. This perception has contributed to an advancement in archaeological practice, namely, the development of computerized recording systems that digitally record archaeological excavations spatially and volumetrically during fieldwork. This paper is concerned with those archaeological sites where digital field recording has not been done. These sites, recorded by traditional methods, should not be excluded from attempts to restructure the spatial, volumetric, and stratigraphic archaeological data. A thorough methodology for the conversion of traditional records into digitized data is presented, including the detailed procedures required for three-dimensional plotting of recorded data—both the excavated material and the drawn site maps and cross-sections. Finally, the use of these methods is demonstrated on a complex Early to Middle Pleistocene site, illustrating the benefits of digitization and three-dimensional reconstruction in resolving stratigraphic and spatial questions.展开更多
This paper described the principle of digitized chromatographic fingerprint spectrum and established digitized chromatographic fingerprint spectra of ten brands of Chinese famous tea by the micellar electrokinetic chr...This paper described the principle of digitized chromatographic fingerprint spectrum and established digitized chromatographic fingerprint spectra of ten brands of Chinese famous tea by the micellar electrokinetic chromatography. This work was done using a 25 mmol·L -1 sodium dodecylsulfate in a 20 mmol·L -1 borate (pH 7 0) solution as running buffer, 20 kV applied potential and detection at 280 nm. The chromatographic fingerprint spectra were digitized by the relative retention value ( α ) and the relative area ( S r), and were analyzed to identify the tea samples. In the absence of the standard samples, the present method was easy setup and inexpensive, and provided the applicable information for the quality assessment of teas.展开更多
RENEWING THE FORBIDDEN CITY’S CENTURY-OLD LEGACY.Oriental Outlook.27 November 2025.At sunrise,the Forbidden City glows under a veil of gold;at night,it retreats into quiet dignity.But the palace never really sleeps.A...RENEWING THE FORBIDDEN CITY’S CENTURY-OLD LEGACY.Oriental Outlook.27 November 2025.At sunrise,the Forbidden City glows under a veil of gold;at night,it retreats into quiet dignity.But the palace never really sleeps.As visitors depart,the“digital relic vault”awakens online,where porcelain,calligraphy,jade and timepieces reveal their beauty in virtual form.History continues to breathe in the data stream.展开更多
A New Chapter of the Century-Old Palace Museum Oriental Outlook Issue 24,2025 The Palace Museum,the imperial palace of the Ming and Qing dynasties(1368-1911),opened to the public in 1925.Rather than a group of static ...A New Chapter of the Century-Old Palace Museum Oriental Outlook Issue 24,2025 The Palace Museum,the imperial palace of the Ming and Qing dynasties(1368-1911),opened to the public in 1925.Rather than a group of static ancient buildings,it stands today as a dynamic cultural organism filled with invaluable collections of cultural relics preserved by generations of artisans and now displayed to the world through digital technology in long-lasting exhibitions.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This...Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.展开更多
The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the...Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes.Over the past decade,the integration of artificial intelligence(AI)into gastroenterology has led to transformative advancements in medical practice.AI represents a major step towards personalized medicine,offering the potential to enhance diagnostic accuracy,refine prognostic assessments,and optimize treatment strategies.Its applications are rapidly expanding.This article explores the emerging role of AI in the management of MASLD,emphasizing its ability to improve clinical prediction,enhance the diagnostic performance of imaging modalities,and support histopathological confirmation.Additionally,it examines the development of AI-guided personalized treatments,where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
Designing materials with both structural load-bearing capacity and broadband electromagnetic(EM)wave absorption properties remains a significant challenge.In this work,SiOC/SiC/SiO_(2)composite with gyroid structures ...Designing materials with both structural load-bearing capacity and broadband electromagnetic(EM)wave absorption properties remains a significant challenge.In this work,SiOC/SiC/SiO_(2)composite with gyroid structures were prepared through digital light processing(DLP)3D printing,polymer-derived ceramics(PDCs),chemical vapor infiltration(CVI),and oxidation technologies.The incorporation of the CVISiC phase effectively increases the dissipation capability,while the synergistic interaction between the gyroid structure and SiO_(2)phase significantly improves impedance matching performance.The SiOC/SiC/SiO_(2)composite achieved a minimum reflection loss(RL min)of-62.2 d B at 4.3 mm,and the effective absorption bandwidth(EAB)covered the X-band,with a thickness range of 4.1 mm-4.65 mm.The CST simulation results explain the broadband and low-frequency absorption characteristics,with an EAB of 8.4 GHz(9.6-18 GHz)and an RL min of-21.5 dB at 5 GHz.The excellent EM wave attenuation performance is associated primarily with polarization loss,conduction loss,the gyroid structure's enhancement of multiple reflections and scattering of EM waves,and the resonance effect between the structural units.The SiOC/SiC/SiO_(2)composite also demonstrated strong mechanical properties,with a maximum compressive failure strength of 31.6 MPa in the height direction.This work opens novel prospects for the development of multifunctional structural wave-absorbing materials suitable for broadband microwave absorption and load-bearing properties.展开更多
Guo Wei, President and CEO of Digital China, answers questions about the company's operating strategies and prospects for China's IT service sector in a written interview with Beijing Review. Beijing Review: D...Guo Wei, President and CEO of Digital China, answers questions about the company's operating strategies and prospects for China's IT service sector in a written interview with Beijing Review. Beijing Review: Digital China has detailed its strategies as "IT Serves China" and "IT Service on Demand." What is the operating objective for 2006?展开更多
Background High-voltage analog X-ray examination is a main tool for pneumoconiosis,which is challenged by digital radiography （DR）.The tube voltage of DR chest films required for diagnosis and staging of pneumoconio...Background High-voltage analog X-ray examination is a main tool for pneumoconiosis,which is challenged by digital radiography （DR）.The tube voltage of DR chest films required for diagnosis and staging of pneumoconiosis is concerned technically.We investigated the influence of the tube voltage on chest X-ray DR image quality of patients exposed to occupational dust.Methods DR images of the CDRAD2.0model,an anatomical chest phantom,and 136 exposed workers were analyzed at different tube voltages by threereaders.Image quality factors （IQF） were calculated and compared using the CDRAD2.0 model.DR images of ten anatomic positions were scored against those of the high-kilovolt chest films in anatomical phantom and clinical cases,and differences in scores were analyzed.Results In the CDRAD2.0 model,all three readers had a minimal IQF at 120 kV （mean：22.25 kV）.The differences in the mean IQF of DR images at different tube voltages was significant （F=13.78,P〈0.001）.The IQF of DR imaging at 120 kV was similar to high kilovolt analog imaging （t=-0.58,P〉0.05）.In the anatomic phantom and clinical cases,the DR images at 120 kV were closest in anatomical detail to the high W analog images,and the means were similar （P〉0.05）.Conclusions Among different tube voltages,DR image quality is closest to the high kilovolt analog images at 120 kV in patients exposed to occupational dust.展开更多
基金supported by grants from the National Key Oil and Gas Program of China(No.2016ZX05004002)from Special Program of PetroChina(No.2014E-32-02)
文摘Numerous hydrocarbon accumulations are found in ramp crest shoals worldwide and therefore this depositional setting has a high potential of being the hydrocarbon reservoir. In this paper, we combined digital outcrop geology and traditional geological mapping to build an outcrop-based geocellular model of the ramp-crest shoal complex of the Lower Triassic Feixianguan Formation in the Eastern Sichuan Basin. The outcrop model serves as an analogue for the subsurface reservoir of the Feixianguan Formation and illustrates the complexity of the lithofacies types, stratigraphic architecture, and reservoir heterogeneities at a scale below conventional subsurface data resolution. The studied ramp -crest shoal complex consists of thirteen types of lithofacies that can be grouped into three facies-groups corresponding to subtidal intraclastic shoal, sub- to inter-tidal oolitic shoal, and tidal flat depositional environments respectively. The stratigraphic architecture of the shoal complex shows mostly a strong progradation of the high energy facies associated with an overall decrease of accommodation space associated with relative sea level still stand. Two reservoir facies associations have been recognized. The first one consists of supratidai dolomudstone and upper intertidal partially dolomitized oolitic packstone with anhydrite or nodules. These facies were deposited above the high energy oolitic grainstones and occurs as thin-bedded and laterally continuous layers, characterized by high porosity and low permeability. The second reservoir facies association is composed of intertidal crystalline dolomite and subtidal intraclastic bindstone that occurs stratigraphically below the oolitic grainstones. These deposits consist of massive laterally discontinuously beds, and are characterized by high porosity and high permeability. Both types of reservoir facies tend to be stacked vertically and migrated laterally with the progradation of the shoal complex. The construction of the outcrop-based 3D geological model provide a description and quantification of the facies distribution within a robust stratigraphic framework and the style and amount of reservoir heterogeneities associated with a ramp-crest shoal complex reservoir such as the one found in Lower Triassic Feixianguan Formation and Cambrian Longwangmiao Formation in Sichuan Basin or other ramp-crest reservoir worldwide.
文摘According to the principle of meshing engagement and the theory of the digitized conjugate surface, this paper applies the software Conjugater-1.0 that is developed by ourselves to compute, respectively, the digitized conjugate curved surfaces of the straight-tooth surface and drum-tooth surface, which will establish the theoretical and technical foundation for digitized engaging analysis, simulation, and digitized manufacturing technology of the diversified gears.
基金supported by National Natural Science Foundation of China(Nos.21874071 and 22204077)China Postdoctoral Science Foundation(No.2021M701722)Fundamental Research Funds for the Central Universities(Nos.30921013112 and 30922010501)。
文摘Antibiotic abuse now poses a grave threat to global ecology and bestirs public concerns about the residue issue in daily necessities.The traceability measurements along supply chain or logistic circulation have become increasingly essential given the labile nature of diverse synthetic residuals on site.In an attempt to answer this urgency,here a miniaturized fluorometric aptasensor prototype was contrived that catered to the point-of-care screening norm for two typical additives:chloramphenicol and enrofloxacin.The key target-indicating module worked in vitro based on the competitive binding-induced fluorescence recovery of fluorescein-labeled aptamers,which were photobleached beforehand in the format of double helix on burlike nanogold carriers.The“prickly”geometry of the latter not just enriched the capture probes at preferentially substrate-accessible spires;but also contributed to a tip-enhanced surface plasmon effect,sensitizing the signal-on during the duplex dissociation even at nanomolar threshold of the analytes.On the other hand,to encompass a full portable,a set of optical devices were mounted within a 3D-printed cartridge(adaptor)to converge the light beam and route it towards the detector,for which the smartphone camera came up in handy with a home-developed App for calibrating the emissive brightness.Enlightened by the high-dynamic-range compression,an imaging diagnostic algorithm was built in to grid and digitize each slide in the album for augmented detection performance.Thus,a novel bio-to-silico integration was invented that capable of in situ rapid reporting on the antibiotic presence with high sensitivity and selectivity.Further field practices in spiked milk on sales proved the precision and rudimentary feasibility of the well-assembled model of appliance,thus holding nice prospects in nonexpert(e.g.,family and local community)utilities for foodborne antibiotic identification.
文摘In order to meet the needs of designing and processing digitized surfaces, the method to spreading digitized surface has been proposed. The key technique is to solve the problem of digitized conjugate surface. In the paper, the digitized conjugate surface was theoretically investigated, and the solution of conjugate surface based on digitized surface was also studied. The digitized conjugate surface theory was then proposed, and applied to build the model of solving conjugate surface based on digitized surface. A corresponding algorithm was developed. This paper applies the software Conjugater-1.0 that is developed by ourselves to compute the digitized conjugate surfaces of the drum-tooth surface. This study provides theoretical and technical bases for analyzing engagement of digitized surface, simulation and numerical processing technique. Key words digitized conjugate surface - generating method - simulation CLC number O 186.1 - TH 122 Foundation item: Supported by the National Natural Science Foundation of China (50075031)Biography: Xiao Lai-yuan (1957-), male, Professor, Ph. D candidate, research direction: machanical design & theory, digital technology
文摘Reverse engineering in the manufacturing field is a process in which the digitized data are obtained from an existing object model or a part of it, and then the CAD model is reconstructed. This paper presents an RBF neural network approach to modify and fit the digitized data. The centers for the RBF are selected by using the orthogonal least squares learning algorithm. A mathematically known surface is used for generating a number of samples for training the networks. The trained networks then generated a number of new points which were compared with the calculating points from the equations. Moreover, a series of practice digitizing curves are used to test the approach. The results showed that this approach is effective in modifying and fitting digitized data and generating data points to reconstruct the surface model.
基金the Ningbo Natural Science Foundation(No.2006A610016)the Foundation of National EducationMinistry for Returned Overseas Students&Scholars(SRFfor ROCS,SEM.No.2006699).
文摘Metric measurement of digitized shapes is commonly applied in optical measuring systems.In this letter,three shape-related factors defined by the authors are used in the construction of amultiple linear regression model which is utilized to compute the circumference of the convex shapes inmillimeter unit.The model is first built upon the relationship hypothesis and then its adequacy ismathematically validated.The results of applying the developed model to the given number of convexshapes in a finite circumferential length range suggest that,in terms of percent error,the model pre-cision is to satisfaction by being within±4%.The test also shows the model’s robustness against theshape’s orientation anisotropy.
文摘As digital technologies have advanced more rapidly,the number of paper documents recently converted into a digital format has exponentially increased.To respond to the urgent need to categorize the growing number of digitized documents,the classification of digitized documents in real time has been identified as the primary goal of our study.A paper classification is the first stage in automating document control and efficient knowledge discovery with no or little human involvement.Artificial intelligence methods such as Deep Learning are now combined with segmentation to study and interpret those traits,which were not conceivable ten years ago.Deep learning aids in comprehending input patterns so that object classes may be predicted.The segmentation process divides the input image into separate segments for a more thorough image study.This study proposes a deep learning-enabled framework for automated document classification,which can be implemented in higher education.To further this goal,a dataset was developed that includes seven categories:Diplomas,Personal documents,Journal of Accounting of higher education diplomas,Service letters,Orders,Production orders,and Student orders.Subsequently,a deep learning model based on Conv2D layers is proposed for the document classification process.In the final part of this research,the proposed model is evaluated and compared with other machine-learning techniques.The results demonstrate that the proposed deep learning model shows high results in document categorization overtaking the other machine learning models by reaching 94.84%,94.79%,94.62%,94.43%,94.07%in accuracy,precision,recall,F-score,and AUC-ROC,respectively.The achieved results prove that the proposed deep model is acceptable to use in practice as an assistant to an office worker.
文摘Archaeological excavation involves disintegration, removal, and reassembly of the archaeological record;as such it is considered by many to be an unrepeatable, destructive activity. This perception has contributed to an advancement in archaeological practice, namely, the development of computerized recording systems that digitally record archaeological excavations spatially and volumetrically during fieldwork. This paper is concerned with those archaeological sites where digital field recording has not been done. These sites, recorded by traditional methods, should not be excluded from attempts to restructure the spatial, volumetric, and stratigraphic archaeological data. A thorough methodology for the conversion of traditional records into digitized data is presented, including the detailed procedures required for three-dimensional plotting of recorded data—both the excavated material and the drawn site maps and cross-sections. Finally, the use of these methods is demonstrated on a complex Early to Middle Pleistocene site, illustrating the benefits of digitization and three-dimensional reconstruction in resolving stratigraphic and spatial questions.
文摘This paper described the principle of digitized chromatographic fingerprint spectrum and established digitized chromatographic fingerprint spectra of ten brands of Chinese famous tea by the micellar electrokinetic chromatography. This work was done using a 25 mmol·L -1 sodium dodecylsulfate in a 20 mmol·L -1 borate (pH 7 0) solution as running buffer, 20 kV applied potential and detection at 280 nm. The chromatographic fingerprint spectra were digitized by the relative retention value ( α ) and the relative area ( S r), and were analyzed to identify the tea samples. In the absence of the standard samples, the present method was easy setup and inexpensive, and provided the applicable information for the quality assessment of teas.
文摘RENEWING THE FORBIDDEN CITY’S CENTURY-OLD LEGACY.Oriental Outlook.27 November 2025.At sunrise,the Forbidden City glows under a veil of gold;at night,it retreats into quiet dignity.But the palace never really sleeps.As visitors depart,the“digital relic vault”awakens online,where porcelain,calligraphy,jade and timepieces reveal their beauty in virtual form.History continues to breathe in the data stream.
文摘A New Chapter of the Century-Old Palace Museum Oriental Outlook Issue 24,2025 The Palace Museum,the imperial palace of the Ming and Qing dynasties(1368-1911),opened to the public in 1925.Rather than a group of static ancient buildings,it stands today as a dynamic cultural organism filled with invaluable collections of cultural relics preserved by generations of artisans and now displayed to the world through digital technology in long-lasting exhibitions.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
文摘Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
文摘Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes.Over the past decade,the integration of artificial intelligence(AI)into gastroenterology has led to transformative advancements in medical practice.AI represents a major step towards personalized medicine,offering the potential to enhance diagnostic accuracy,refine prognostic assessments,and optimize treatment strategies.Its applications are rapidly expanding.This article explores the emerging role of AI in the management of MASLD,emphasizing its ability to improve clinical prediction,enhance the diagnostic performance of imaging modalities,and support histopathological confirmation.Additionally,it examines the development of AI-guided personalized treatments,where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金financially supported by National Natural Science Foundation of China(Grant Nos.12141203,52202083,W2421013)the Natural Science Foundation Project of Shaanxi Province(Grant No.2024JC-YBMS-450)+1 种基金the Sichuan Science and Technology Program(Grant No.2024YFHZ0265)the Open Project of High-end Equipment Advanced Materials and Manufacturing Technology Laboratory(Grant No.2023KFKT0005)。
文摘Designing materials with both structural load-bearing capacity and broadband electromagnetic(EM)wave absorption properties remains a significant challenge.In this work,SiOC/SiC/SiO_(2)composite with gyroid structures were prepared through digital light processing(DLP)3D printing,polymer-derived ceramics(PDCs),chemical vapor infiltration(CVI),and oxidation technologies.The incorporation of the CVISiC phase effectively increases the dissipation capability,while the synergistic interaction between the gyroid structure and SiO_(2)phase significantly improves impedance matching performance.The SiOC/SiC/SiO_(2)composite achieved a minimum reflection loss(RL min)of-62.2 d B at 4.3 mm,and the effective absorption bandwidth(EAB)covered the X-band,with a thickness range of 4.1 mm-4.65 mm.The CST simulation results explain the broadband and low-frequency absorption characteristics,with an EAB of 8.4 GHz(9.6-18 GHz)and an RL min of-21.5 dB at 5 GHz.The excellent EM wave attenuation performance is associated primarily with polarization loss,conduction loss,the gyroid structure's enhancement of multiple reflections and scattering of EM waves,and the resonance effect between the structural units.The SiOC/SiC/SiO_(2)composite also demonstrated strong mechanical properties,with a maximum compressive failure strength of 31.6 MPa in the height direction.This work opens novel prospects for the development of multifunctional structural wave-absorbing materials suitable for broadband microwave absorption and load-bearing properties.
文摘Guo Wei, President and CEO of Digital China, answers questions about the company's operating strategies and prospects for China's IT service sector in a written interview with Beijing Review. Beijing Review: Digital China has detailed its strategies as "IT Serves China" and "IT Service on Demand." What is the operating objective for 2006?
文摘Background High-voltage analog X-ray examination is a main tool for pneumoconiosis,which is challenged by digital radiography （DR）.The tube voltage of DR chest films required for diagnosis and staging of pneumoconiosis is concerned technically.We investigated the influence of the tube voltage on chest X-ray DR image quality of patients exposed to occupational dust.Methods DR images of the CDRAD2.0model,an anatomical chest phantom,and 136 exposed workers were analyzed at different tube voltages by threereaders.Image quality factors （IQF） were calculated and compared using the CDRAD2.0 model.DR images of ten anatomic positions were scored against those of the high-kilovolt chest films in anatomical phantom and clinical cases,and differences in scores were analyzed.Results In the CDRAD2.0 model,all three readers had a minimal IQF at 120 kV （mean：22.25 kV）.The differences in the mean IQF of DR images at different tube voltages was significant （F=13.78,P〈0.001）.The IQF of DR imaging at 120 kV was similar to high kilovolt analog imaging （t=-0.58,P〉0.05）.In the anatomic phantom and clinical cases,the DR images at 120 kV were closest in anatomical detail to the high W analog images,and the means were similar （P〉0.05）.Conclusions Among different tube voltages,DR image quality is closest to the high kilovolt analog images at 120 kV in patients exposed to occupational dust.
