Rainfall-induced landslides are often highly destructive.Reviewing and analyzing the causes,processes,impacts,and deficiencies in emergency response is critical for improving disaster prevention and management.From th...Rainfall-induced landslides are often highly destructive.Reviewing and analyzing the causes,processes,impacts,and deficiencies in emergency response is critical for improving disaster prevention and management.From the night of July 21 to the morning of July 22,2024,the Kencho Shacha Gozdi Village in Gezei Gofa,Southern Nations,Nationalities,and Peoples'Region,Ethiopia,suffered heavy rainfall that triggered two landslides.By July25,this event had claimed at least 257 lives.This study presents a detailed characterization of the landslides using multi-source data.By analyzing the landslide disaster process,this study summarizes key lessons and provides suggestions for preventing rainfall-induced geological hazards.The results indicate that rainfall has the greatest impact on the occurrence of landslides,while lithology and human activities have promoted and strengthened the landslide disaster.Despite the active disaster response in the local area,many problems were still exposed in the emergency response work.This analysis offers valuable insights for mitigating rainfall-induced geological hazards and enhancing emergency response capabilities.展开更多
Background:Scientific evidence to guide clinicians on the use of different antiseizure drugs in combination therapy is either very limited or lacking.In this study,the impact of lacosamide and perampanel alone and in ...Background:Scientific evidence to guide clinicians on the use of different antiseizure drugs in combination therapy is either very limited or lacking.In this study,the impact of lacosamide and perampanel alone and in combination was tested in corneal kindling model in mice,which is a cost-effective mechanism for screening of antiseizure drugs.Methods:The impact of lacosamide(5 mg/kg)and perampanel(0.125 mg/kg)alone and their combination was tested in corneal kindling process(3-mA current for 3 s applied twice daily for consecutive 12 days)in male BALB/c mice.Post-kindling,mice were subjected to a battery of behavioral tests assessing anxiety,memory,and depression-like behaviors.Brain tissues were then harvested for analysis of oxidative stress biomarkers.Results:Our results showed that the combination therapy of lacosamide and perampanel was more effective in reducing seizure progression than monotherapy of these drugs.Animals treated with combination therapy showed significant behavioral improvements,as reduced anxiety and depression were noticed,and their cognitive abilities were notably better compared to animals of all other groups.Moreover,biochemical assays of isolated brains from combination-treated group revealed lesser amount of oxidative stress.In addition,outcomes of dual regime were comparable to the phenytoin in seizure control but showed superior benefits in mitigation of kindling-prompted behavioral dysfunction and oxidative stress.Conclusions:This study suggests that the lacosamide and perampanel combination therapy worked noticeably better in halting the corneal kindling process in mice and improved the epilepsy-associated psychiatric disorders that might be due to antioxidant effects of both drugs.展开更多
Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by ...Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by enlarging the receptive field,which indicates how the convolution process extracts features in a high dimensional feature space.However,its functionality is restricted to the spatial dimension and network depth,limiting further improvements in network performance due to insufficient information interaction and representation.Crucially,the potential of high dimensional feature space in the channel dimension and the exploration of network width/resolution remain largely untapped.In this paper,we consider nonlinear transforms from the perspective of feature space,defining high-dimensional feature spaces in different dimensions and investigating the specific effects.Firstly,we introduce the dimension increasing and decreasing transforms in both channel and spatial dimensions to obtain high dimensional feature space and achieve better feature extraction.Secondly,we design a channel-spatial fusion residual transform(CSR),which incorporates multi-dimensional transforms for a more effective representation.Furthermore,we simplify the proposed fusion transform to obtain a slim architecture(CSR-sm),balancing network complexity and compression performance.Finally,we build the overall network with stacked CSR transforms to achieve better compression and reconstruction.Experimental results demonstrate that the proposed method can achieve superior ratedistortion performance compared to the existing LIC methods and traditional codecs.Specifically,our proposed method achieves 9.38%BD-rate reduction over VVC on Kodak dataset.展开更多
Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a system...Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a systematic evaluation of typical studies. Results: The fundamental problem is that brain researchers fail to differentiate between biological mental disorders in which brain processes cause the disorder (notably schizophrenia, bipolar disorder, and melancholic depression) and learned mental disorders in which brain processes mediate but do not cause the disorder (which is the case with reactive depression, reactive anxiety, OCD, and PTSD). Researchers have been unsuccessful in identifying mechanisms in the brain that cause biological mental disorders, and will never be able to locate the innumerable specific neural connections that mediate learned mental disorders. Moreover, the author’s review of typical studies in this field shows that they have serious problems with theory, measurement, and data analysis, and that their findings cannot be trusted. Conclusions: Neuroscience-based brain research on mental disorders, unlike other neurological research, has been an expensive failure and it is not worth continuing.展开更多
The query processing in distributed database management systems(DBMS)faces more challenges,such as more operators,and more factors in cost models and meta-data,than that in a single-node DMBS,in which query optimizati...The query processing in distributed database management systems(DBMS)faces more challenges,such as more operators,and more factors in cost models and meta-data,than that in a single-node DMBS,in which query optimization is already an NP-hard problem.Learned query optimizers(mainly in the single-node DBMS)receive attention due to its capability to capture data distributions and flexible ways to avoid hard-craft rules in refinement and adaptation to new hardware.In this paper,we focus on extensions of learned query optimizers to distributed DBMSs.Specifically,we propose one possible but general architecture of the learned query optimizer in the distributed context and highlight differences from the learned optimizer in the single-node ones.In addition,we discuss the challenges and possible solutions.展开更多
Depression is a chronic,recurring and potentially life-threatening illness that affects up to 20%of the population across the world.Despite its prevalence and considerable impact on human,little is known about its pat...Depression is a chronic,recurring and potentially life-threatening illness that affects up to 20%of the population across the world.Despite its prevalence and considerable impact on human,little is known about its pathogenesis.One of the major reasons is the restricted availability of validated animal models due to the absence of consensus on the pathology and etiology of depression.Besides,some core symptoms such as depressed mood,feeling of worthlessness,and recurring thoughts of death or suicide,are impossible to be modeled on laboratory animals.Currently,the criteria for identifying animal models of depression rely on either of the 2 principles：actions of known antidepressants and responses to stress.This review mainly focuses on the most widely used animal models of depression,including learned helplessness,chronic mild stress,and social defeat paradigms.Also,the behavioral tests for screening antidepressants,such as forced swimming test and tail suspension test,are also discussed.The advantages and major drawbacks of each model are evaluated.In prospective,new techniques that will be beneficial for developing novel animal models or detecting depression are discussed.展开更多
本期话题如下:1. What causes generation gap? How to face it?Different experiencesDifferent educationDifferent ideasDifferent goals in lifeRespect other peopleCompromise
To investigate the behavioral and biomolecular similarity between neuralgia and depression, a trigeminal neuralgia （TN） mouse model was established by constriction of the infraorbital nerve （CION） to mimic clinica...To investigate the behavioral and biomolecular similarity between neuralgia and depression, a trigeminal neuralgia （TN） mouse model was established by constriction of the infraorbital nerve （CION） to mimic clinical trigeminal neuropathic pain. A mouse learned helplessness （LH） model was developed to investigate inescapable footshock-induced psychiatric disorders like depression in humans. Mass spectrometry was used to assess changes in the biomolecules and signaling pathways in the hip- pocampus from TN or LH mice. TN mice developed not only significant mechanical allodynia but also depressive- like behaviors （mainly behavioral despair） at 2 weeks after CION, similar to LH mice. MS analysis demonstrated common and distinctive protein changes in the hippocampus between groups. Many protein function families （such as cell-to-cell signaling and interaction, and cell assembly and organization,） and signaling pathways （e.g., the Huntington＇s disease pathway） were involved in chronic neuralgia and depression. Together, these results demonstrated that the LH and TN models both develop depressive-like behaviors, and revealed the involvement of manypsychiatric disorder-related biomolecules/pathways in the pathogenesis of TN and LH.展开更多
Exercise is a potent force of nature with significant potential for extending longevity and boosting physical fitness. It is also be- ing increasingly used as a prophylactic and curative measure for various physical a...Exercise is a potent force of nature with significant potential for extending longevity and boosting physical fitness. It is also be- ing increasingly used as a prophylactic and curative measure for various physical ailments, such as cardiovascular diseases and diabetes.展开更多
Pollen collection is necessary for bee survival and important for flowering plant reproduction, yet if and how pollen extraction motor routines are modified with experience is largely unknown. Here, we used an automat...Pollen collection is necessary for bee survival and important for flowering plant reproduction, yet if and how pollen extraction motor routines are modified with experience is largely unknown. Here, we used an automated reward and monitoring system to evaluate modification in a common pollen-extraction routine, floral sonication. Through a series of laboratory experiments with the bumblebee, Bombus impatiens, we examined whether variation in sonication frequency and acceleration is due to instrumental learning based on rewards, a fixed behavioral response to rewards, and/or a mechanical constraint. We first investigated whether bees could learn to adjust their sonication frequency in response to pollen rewards given only for specified frequency ranges and found no evidenee of instrumental learning. However, we found that absenee versus receipt of a pollen reward did lead to a predictable behavioral resp on se, which depe nded on bee size. Fin ally, we found some evide nee of mechanical con straints, in that flower mass affected sonication acceleration (but not frequency) through an interaction with bee size. In generalz larger bees showed more flexibility in sonication frequency and acceleration, potentially reflecting a size-based constraint on the range over which smaller bees can modify frequency and accelerati on. Overall our results show that although bees did not display instrumental learning of sonication frequency, their sonication motor routine is nevertheless flexible.展开更多
Toxic insects advertise their defended state to potential predators using warning displays. Frequently these displays use cues through more than one sensory modality, and combine color, smell and sound to produce a mu...Toxic insects advertise their defended state to potential predators using warning displays. Frequently these displays use cues through more than one sensory modality, and combine color, smell and sound to produce a multimodal warning display. Signalling through more than one sensory pathway may enhance the rate of avoidance learning, and the memorability of the learned avoidance. A common insect warning odor, pyrazine, has previously been shown to increase the rate of learned avoidance of unpalatable yellow prey by domestic chicks （GaUus gallus domesticus）, and the odor also improved memory of this learned avoidance. However, to date no research has examined this response to pyrazine odor using wild birds under natural conditions. This study used wild robins （Erithacus rubecula） to investigate whether wild birds avoided yellow baits that smelled of pyrazine more strongly than those presented with no odor. The results provide some evidence that pyrazine odor does increase the level of protection an aposematic insect gains from a wild avian predator, but that the effect of pyrazine on learned avoidance was much weaker than was found with domestic chicks .展开更多
Fabric texture intelligent analysis comprises the following characteristics:objective detection results,high detection efficiency,and accuracy.It is significantly vital to replace manual inspection for smart green man...Fabric texture intelligent analysis comprises the following characteristics:objective detection results,high detection efficiency,and accuracy.It is significantly vital to replace manual inspection for smart green manufacturing in the textile industry,such as quality control and rating,and online testing.For detecting the global image,an unsupervised method is proposed to characterize the woven fabric texture image,which is the combination of principal component analysis(PCA)and dictionary learning.First of all,the PCA approach is used to reduce the dimension of fabric samples,the obtained eigenvector is used as the initial dictionary,and then the dictionary learning method is operated on the defect-free region to get the standard templates.Secondly,the standard templates are optimized by choosing the appropriate dictionary size to construct a fabric texture representat ion model that can effectively characterize the defec-free texture region,while ineffectively representing the defective sector.That is to say,through the mechanism of identifying normal texture from imperfect texture,a learned dictionary with robustness and discrimination is obtained to adapt the fabric texture.Thirdly,after matching the detected image with the standard templates,the average filter is used to remove the noise and suppress the background texture,while retaining and enhancing the defect region.In the final part,the image segmentation is operated to identify the defect.The experimental results show that the proposed algorithm can adequately inspect fabrics with defects such as holes,oil stains,skipping,other defective types,and non-defective materials,while the detection results are good and the algorithrm can be operated flexibly.展开更多
<strong>Background:</strong> Coronavirus-19 (COVID-19) dramatically impacted institutions of higher education. The effect was acute in the practice disciplines such as medicine, medical laboratory science,...<strong>Background:</strong> Coronavirus-19 (COVID-19) dramatically impacted institutions of higher education. The effect was acute in the practice disciplines such as medicine, medical laboratory science, and nursing. The purpose is to describe how an interdisciplinary team, led by nursing faculty, adapted to the changes driven by COVID-19 and the lessons that were learned for nursing and other disciplines in higher education. <strong>Method:</strong> The interdisciplinary group created a comprehensive list which captured the impact of COVID-19 on their academic disciplines. Similarities and differences between the disciplines regarding faculty experiences, teaching, and responding to student concerns were discovered. <strong>Results:</strong> Collective review resulted in the identification of four inclusive thematic categories and several sub-categories. These were: academic considerations (didactic, lab, clinical), perceptions (faculty, student), ethical considerations, and social determinants affecting the learning environment. Lessons Learned: This project utilized an innovative interdisciplinary approach to identify common COVID-19 effects on higher education. <strong>Conclusions:</strong> Nursing and other health-related disciplines should pursue interdisciplinary collaboration to address common academic issues that arise during the COVID.展开更多
Dr.Xu Ruizheng(许瑞征)is an expertacupuncturist renowned for his knowledgeand experience in this field.I have been for-tunate to be his student and learned his vari-ous modalities of acupuncture treatment forVerruca P...Dr.Xu Ruizheng(许瑞征)is an expertacupuncturist renowned for his knowledgeand experience in this field.I have been for-tunate to be his student and learned his vari-ous modalities of acupuncture treatment forVerruca Plana(flat wart),which I wouldlike to impart hereby to my colleagues.According to Dr.Xu,there are 5modalities of treatment for Verruca Plana;Iam introducing 2 of them as follows:展开更多
基金supported by the National Institute of Natural Hazards,Ministry of Emergency Management of China(2023-JBKY-57)the National Natural Science Foundation of China(42077259)。
文摘Rainfall-induced landslides are often highly destructive.Reviewing and analyzing the causes,processes,impacts,and deficiencies in emergency response is critical for improving disaster prevention and management.From the night of July 21 to the morning of July 22,2024,the Kencho Shacha Gozdi Village in Gezei Gofa,Southern Nations,Nationalities,and Peoples'Region,Ethiopia,suffered heavy rainfall that triggered two landslides.By July25,this event had claimed at least 257 lives.This study presents a detailed characterization of the landslides using multi-source data.By analyzing the landslide disaster process,this study summarizes key lessons and provides suggestions for preventing rainfall-induced geological hazards.The results indicate that rainfall has the greatest impact on the occurrence of landslides,while lithology and human activities have promoted and strengthened the landslide disaster.Despite the active disaster response in the local area,many problems were still exposed in the emergency response work.This analysis offers valuable insights for mitigating rainfall-induced geological hazards and enhancing emergency response capabilities.
基金The authors extended their appreciation to Distinguished Scientist Fellowship program at King Saud University,Riyadh,Saudi Arabia,for funding this work through research supporting project number(RSP2024R131).
文摘Background:Scientific evidence to guide clinicians on the use of different antiseizure drugs in combination therapy is either very limited or lacking.In this study,the impact of lacosamide and perampanel alone and in combination was tested in corneal kindling model in mice,which is a cost-effective mechanism for screening of antiseizure drugs.Methods:The impact of lacosamide(5 mg/kg)and perampanel(0.125 mg/kg)alone and their combination was tested in corneal kindling process(3-mA current for 3 s applied twice daily for consecutive 12 days)in male BALB/c mice.Post-kindling,mice were subjected to a battery of behavioral tests assessing anxiety,memory,and depression-like behaviors.Brain tissues were then harvested for analysis of oxidative stress biomarkers.Results:Our results showed that the combination therapy of lacosamide and perampanel was more effective in reducing seizure progression than monotherapy of these drugs.Animals treated with combination therapy showed significant behavioral improvements,as reduced anxiety and depression were noticed,and their cognitive abilities were notably better compared to animals of all other groups.Moreover,biochemical assays of isolated brains from combination-treated group revealed lesser amount of oxidative stress.In addition,outcomes of dual regime were comparable to the phenytoin in seizure control but showed superior benefits in mitigation of kindling-prompted behavioral dysfunction and oxidative stress.Conclusions:This study suggests that the lacosamide and perampanel combination therapy worked noticeably better in halting the corneal kindling process in mice and improved the epilepsy-associated psychiatric disorders that might be due to antioxidant effects of both drugs.
基金supported by the Key Program of the National Natural Science Foundation of China(Grant No.62031013)Guangdong Province Key Construction Discipline Scientific Research Capacity Improvement Project(Grant No.2022ZDJS117).
文摘Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by enlarging the receptive field,which indicates how the convolution process extracts features in a high dimensional feature space.However,its functionality is restricted to the spatial dimension and network depth,limiting further improvements in network performance due to insufficient information interaction and representation.Crucially,the potential of high dimensional feature space in the channel dimension and the exploration of network width/resolution remain largely untapped.In this paper,we consider nonlinear transforms from the perspective of feature space,defining high-dimensional feature spaces in different dimensions and investigating the specific effects.Firstly,we introduce the dimension increasing and decreasing transforms in both channel and spatial dimensions to obtain high dimensional feature space and achieve better feature extraction.Secondly,we design a channel-spatial fusion residual transform(CSR),which incorporates multi-dimensional transforms for a more effective representation.Furthermore,we simplify the proposed fusion transform to obtain a slim architecture(CSR-sm),balancing network complexity and compression performance.Finally,we build the overall network with stacked CSR transforms to achieve better compression and reconstruction.Experimental results demonstrate that the proposed method can achieve superior ratedistortion performance compared to the existing LIC methods and traditional codecs.Specifically,our proposed method achieves 9.38%BD-rate reduction over VVC on Kodak dataset.
文摘Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a systematic evaluation of typical studies. Results: The fundamental problem is that brain researchers fail to differentiate between biological mental disorders in which brain processes cause the disorder (notably schizophrenia, bipolar disorder, and melancholic depression) and learned mental disorders in which brain processes mediate but do not cause the disorder (which is the case with reactive depression, reactive anxiety, OCD, and PTSD). Researchers have been unsuccessful in identifying mechanisms in the brain that cause biological mental disorders, and will never be able to locate the innumerable specific neural connections that mediate learned mental disorders. Moreover, the author’s review of typical studies in this field shows that they have serious problems with theory, measurement, and data analysis, and that their findings cannot be trusted. Conclusions: Neuroscience-based brain research on mental disorders, unlike other neurological research, has been an expensive failure and it is not worth continuing.
基金partially supported by NSFC under Grant Nos.61832001 and 62272008ZTE Industry-University-Institute Fund Project。
文摘The query processing in distributed database management systems(DBMS)faces more challenges,such as more operators,and more factors in cost models and meta-data,than that in a single-node DMBS,in which query optimization is already an NP-hard problem.Learned query optimizers(mainly in the single-node DBMS)receive attention due to its capability to capture data distributions and flexible ways to avoid hard-craft rules in refinement and adaptation to new hardware.In this paper,we focus on extensions of learned query optimizers to distributed DBMSs.Specifically,we propose one possible but general architecture of the learned query optimizer in the distributed context and highlight differences from the learned optimizer in the single-node ones.In addition,we discuss the challenges and possible solutions.
文摘Depression is a chronic,recurring and potentially life-threatening illness that affects up to 20%of the population across the world.Despite its prevalence and considerable impact on human,little is known about its pathogenesis.One of the major reasons is the restricted availability of validated animal models due to the absence of consensus on the pathology and etiology of depression.Besides,some core symptoms such as depressed mood,feeling of worthlessness,and recurring thoughts of death or suicide,are impossible to be modeled on laboratory animals.Currently,the criteria for identifying animal models of depression rely on either of the 2 principles：actions of known antidepressants and responses to stress.This review mainly focuses on the most widely used animal models of depression,including learned helplessness,chronic mild stress,and social defeat paradigms.Also,the behavioral tests for screening antidepressants,such as forced swimming test and tail suspension test,are also discussed.The advantages and major drawbacks of each model are evaluated.In prospective,new techniques that will be beneficial for developing novel animal models or detecting depression are discussed.
文摘本期话题如下:1. What causes generation gap? How to face it?Different experiencesDifferent educationDifferent ideasDifferent goals in lifeRespect other peopleCompromise
基金supported by the National Natural Science Foundation of China(31421091,81471130,31371123 and 31420103903)a Development Project of Shanghai Peak Disciplines Integrated Chinese and Western Medicine,China
文摘To investigate the behavioral and biomolecular similarity between neuralgia and depression, a trigeminal neuralgia （TN） mouse model was established by constriction of the infraorbital nerve （CION） to mimic clinical trigeminal neuropathic pain. A mouse learned helplessness （LH） model was developed to investigate inescapable footshock-induced psychiatric disorders like depression in humans. Mass spectrometry was used to assess changes in the biomolecules and signaling pathways in the hip- pocampus from TN or LH mice. TN mice developed not only significant mechanical allodynia but also depressive- like behaviors （mainly behavioral despair） at 2 weeks after CION, similar to LH mice. MS analysis demonstrated common and distinctive protein changes in the hippocampus between groups. Many protein function families （such as cell-to-cell signaling and interaction, and cell assembly and organization,） and signaling pathways （e.g., the Huntington＇s disease pathway） were involved in chronic neuralgia and depression. Together, these results demonstrated that the LH and TN models both develop depressive-like behaviors, and revealed the involvement of manypsychiatric disorder-related biomolecules/pathways in the pathogenesis of TN and LH.
文摘Exercise is a potent force of nature with significant potential for extending longevity and boosting physical fitness. It is also be- ing increasingly used as a prophylactic and curative measure for various physical ailments, such as cardiovascular diseases and diabetes.
文摘Pollen collection is necessary for bee survival and important for flowering plant reproduction, yet if and how pollen extraction motor routines are modified with experience is largely unknown. Here, we used an automated reward and monitoring system to evaluate modification in a common pollen-extraction routine, floral sonication. Through a series of laboratory experiments with the bumblebee, Bombus impatiens, we examined whether variation in sonication frequency and acceleration is due to instrumental learning based on rewards, a fixed behavioral response to rewards, and/or a mechanical constraint. We first investigated whether bees could learn to adjust their sonication frequency in response to pollen rewards given only for specified frequency ranges and found no evidenee of instrumental learning. However, we found that absenee versus receipt of a pollen reward did lead to a predictable behavioral resp on se, which depe nded on bee size. Fin ally, we found some evide nee of mechanical con straints, in that flower mass affected sonication acceleration (but not frequency) through an interaction with bee size. In generalz larger bees showed more flexibility in sonication frequency and acceleration, potentially reflecting a size-based constraint on the range over which smaller bees can modify frequency and accelerati on. Overall our results show that although bees did not display instrumental learning of sonication frequency, their sonication motor routine is nevertheless flexible.
文摘Toxic insects advertise their defended state to potential predators using warning displays. Frequently these displays use cues through more than one sensory modality, and combine color, smell and sound to produce a multimodal warning display. Signalling through more than one sensory pathway may enhance the rate of avoidance learning, and the memorability of the learned avoidance. A common insect warning odor, pyrazine, has previously been shown to increase the rate of learned avoidance of unpalatable yellow prey by domestic chicks （GaUus gallus domesticus）, and the odor also improved memory of this learned avoidance. However, to date no research has examined this response to pyrazine odor using wild birds under natural conditions. This study used wild robins （Erithacus rubecula） to investigate whether wild birds avoided yellow baits that smelled of pyrazine more strongly than those presented with no odor. The results provide some evidence that pyrazine odor does increase the level of protection an aposematic insect gains from a wild avian predator, but that the effect of pyrazine on learned avoidance was much weaker than was found with domestic chicks .
基金the National Natural Science Foundation of China(Nos.61379011 and 52003245)the Open Fund of Clothing Engineering Research Center of Zhejiang Province(Zhejiang Sci-Tech University)(No.2019FZKF07)+1 种基金the Scientific Research Fund of Zhejiang Provincial Education Department(No.Y201942502)the Natural Science Foundation of Zhejiang Province(No.LQ18E030007)。
文摘Fabric texture intelligent analysis comprises the following characteristics:objective detection results,high detection efficiency,and accuracy.It is significantly vital to replace manual inspection for smart green manufacturing in the textile industry,such as quality control and rating,and online testing.For detecting the global image,an unsupervised method is proposed to characterize the woven fabric texture image,which is the combination of principal component analysis(PCA)and dictionary learning.First of all,the PCA approach is used to reduce the dimension of fabric samples,the obtained eigenvector is used as the initial dictionary,and then the dictionary learning method is operated on the defect-free region to get the standard templates.Secondly,the standard templates are optimized by choosing the appropriate dictionary size to construct a fabric texture representat ion model that can effectively characterize the defec-free texture region,while ineffectively representing the defective sector.That is to say,through the mechanism of identifying normal texture from imperfect texture,a learned dictionary with robustness and discrimination is obtained to adapt the fabric texture.Thirdly,after matching the detected image with the standard templates,the average filter is used to remove the noise and suppress the background texture,while retaining and enhancing the defect region.In the final part,the image segmentation is operated to identify the defect.The experimental results show that the proposed algorithm can adequately inspect fabrics with defects such as holes,oil stains,skipping,other defective types,and non-defective materials,while the detection results are good and the algorithrm can be operated flexibly.
文摘<strong>Background:</strong> Coronavirus-19 (COVID-19) dramatically impacted institutions of higher education. The effect was acute in the practice disciplines such as medicine, medical laboratory science, and nursing. The purpose is to describe how an interdisciplinary team, led by nursing faculty, adapted to the changes driven by COVID-19 and the lessons that were learned for nursing and other disciplines in higher education. <strong>Method:</strong> The interdisciplinary group created a comprehensive list which captured the impact of COVID-19 on their academic disciplines. Similarities and differences between the disciplines regarding faculty experiences, teaching, and responding to student concerns were discovered. <strong>Results:</strong> Collective review resulted in the identification of four inclusive thematic categories and several sub-categories. These were: academic considerations (didactic, lab, clinical), perceptions (faculty, student), ethical considerations, and social determinants affecting the learning environment. Lessons Learned: This project utilized an innovative interdisciplinary approach to identify common COVID-19 effects on higher education. <strong>Conclusions:</strong> Nursing and other health-related disciplines should pursue interdisciplinary collaboration to address common academic issues that arise during the COVID.
文摘Dr.Xu Ruizheng(许瑞征)is an expertacupuncturist renowned for his knowledgeand experience in this field.I have been for-tunate to be his student and learned his vari-ous modalities of acupuncture treatment forVerruca Plana(flat wart),which I wouldlike to impart hereby to my colleagues.According to Dr.Xu,there are 5modalities of treatment for Verruca Plana;Iam introducing 2 of them as follows:
