The impact damping capabilities of four different boxing gloves were assessed under two different conditions of target padding to determine whether target characteristics might influence previous conclusions concernin...The impact damping capabilities of four different boxing gloves were assessed under two different conditions of target padding to determine whether target characteristics might influence previous conclusions concerning potential for impact mitigation through novel glove design. A conventional 10?oz glove (Std 10?oz), a conventional 16?oz glove (Std 16?oz), a prototype pneumatic glove with a sealed bladder (SBLI) and a prototype pneumatic glove with a bladder allowing air exchange with the external environment (ARLI) were each dropped three times on to a force plate from six heights ranging from 2.5 to 5.0 metres. The force plate was covered by a 50 mm thick mat of EVA material and results obtained were compared with those of an earlier experiment involving use of a similar protocol but a 25 mm thick EVA force plate covering. The thicker mat greatly reduced peak impact forces for all gloves, with values for the Std 10?oz glove becoming much closer to those reported by other researchers for punches delivered by elite boxers to crash test manikins. Peak rates of force development were also substantially decreased. Protective effects provided by the ARLI glove relative to the Std 10?oz glove were diminished but still in the order of 17%?-?22% for peak impact force and 27%?-?49% for peak rate of force development across the range of drop heights. With the 50 mm mat thickness, the SBLI glove was as effective as the ARLI glove in reducing peak impact force, whereas this was not the case with the 25 mm mat. It was, however, always inferior to the ARLI glove in decreasing peak rate of force development. The ability of the ARLI glove to afford protection across a spectrum of impact conditions could yield important practical advantages.展开更多
This study was aimed at improved understanding of the mechanisms of previously reported protective effects of a pneumatic boxing glove. A Motion Capture System was used to obtain velocity data from four different boxi...This study was aimed at improved understanding of the mechanisms of previously reported protective effects of a pneumatic boxing glove. A Motion Capture System was used to obtain velocity data from four different boxing gloves dropped on to a force plate from nine heights ranging from 1 to 5 metres. Two gloves were of the conventional type but differed in mass. The other two were prototype pneumatic gloves. One of these (SBLI) had a sealed bladder while the other (ARLI) incorporated a port allowing air exchange with the external environment. The pneumatic gloves decelerated more slowly than the conventional gloves following impact and compressed through a greater absolute distance. Consequently, they took longer to reach zero velocity. As drop height increased, these trends became more pronounced for the ARLI glove than the SBLI glove. Increase in velocity during rebound was also slower for the pneumatic gloves. The ARLI glove had a lower coefficient of restitution than any of the other gloves at low to moderate drop heights but not at high drop heights. The SBLI glove had a higher coefficient of restitution than the other gloves at all drop heights from 2 metres upwards. This indicated that, overall, the ARLI glove was the most effective, and the SBLI glove the least effective, in dissipating the kinetic energy of impact through conversion to other energy forms. For all gloves at all drop heights, peak positive acceleration at the beginning of rebound was of lower absolute magnitude than peak negative acceleration at the end of compression. The influence of drop height on an index characterising this relationship differed between the conventional and pneumatic gloves, possibly reflecting structural changes to gloves as impact energy increased. The conventional and pneumatic gloves differed regarding temporal alignment between key kinematic and kinetic events, and there were some differences between the two pneumatic gloves in this respect. Nevertheless, peak glove deceleration correlated highly with peak impact force, not only for each glove individually but also when data for all gloves were combined. The findings confirmed the potential practical utility of the ARLI glove and identified air cushion thickness, glove compressibility and capacity for air release and subsequent reuptake as critical aspects of its design.展开更多
Ranging based on the reflection principle of ultrasonic wave propagating in the air has been widely used in modern life, such as car reversing radar, robot automatic obstacle avoidance etc. Aiming at the situation tha...Ranging based on the reflection principle of ultrasonic wave propagating in the air has been widely used in modern life, such as car reversing radar, robot automatic obstacle avoidance etc. Aiming at the situation that the blinds have no way to know whether there are obstacles or big safety risks in front of them when they are walking, this paper designed obstacle avoidance gloves for the blinds based on ultrasonic sensors. With Arduino Nano single chip microcomputer as main controller, combined with ultrasonic sensor module, bluetooth module and speaker module, the glove realized the function of obstacle detection and alarm. The main working principle is by using the ultrasonic sensors to transmit and receive ultrasonic, the time difference for transmitting and receiving to detect the distance of obstacles ahead. Besides, by means of voice module output audio signals with different frequency according to the obstacle distance, the blinds can judge the distance between them to the obstacles based on the sound with different frequencies they heard. In this way, they can make responses in advance to avoid the obstacles ahead and the happening of the risk.展开更多
Two prototype pneumatic boxing gloves of different design were compared against conventional 10?oz (Std 10?oz) and 16?oz (Std 16?oz) gloves in terms of ability to reduce impact forces delivered to a target. One of the...Two prototype pneumatic boxing gloves of different design were compared against conventional 10?oz (Std 10?oz) and 16?oz (Std 16?oz) gloves in terms of ability to reduce impact forces delivered to a target. One of the pneumatic gloves (SBLI) contained a sealed air bladder inflated to a pressure of 2?kPa. The other (ARLI) incorporated a bladder that allowed release of air to the external environment upon contact with a target, followed by rapid air reuptake. Each glove was placed on to a mechanical fist and dropped 10 times on to an in-floor force plate from each of nine heights ranging from 1.0 to 5.0 metres, with the 5-metre drop generating a peak pre-impact glove velocity close to the reported maximum for elite boxers. Compared to the conventional gloves, the ARLI glove substantially reduced peak impact forces at all drop heights, with the reduction exceeding 30% even at the 5-metre level. The SBLI glove was as effective as the ARLI glove in reducing peak impact forces at drop heights of up to 2.5 metres, but its performance then progressively diminished, and at drop heights of 4.0, 4.5 and 5.0 metres it produced peak force readings similar to those recorded for the Std 10?oz and Std 16?oz gloves. The superiority of the ARLI glove was even more evident in relation to peak rate of force development, with reductions relative to the Std 10?oz glove being ~60% at drop heights up to 3.5 metres and still ~47% at 5 metres. Peak rate of force development for the SBLI glove exceeded that for the ARLI glove for all drop heights of 2.0 metres and above, and at 4.0, 4.5 and 5.0 metres it was higher than the readings for the Std 10 oz and 16?oz gloves. The protective effect of the ARLI glove was?associated with an increase in impact compliance and prolongation of contact time between glove and target. It is concluded that a pneumatic boxing glove that provides for air exchange with the external environment can greatly reduce impact magnitudes across the whole range of pre-impact glove velocities likely to be encountered in boxing, thereby mitigating risks associated with the sport. While acceptance of the gloves by the boxing community is uncertain, opportunity may exist for almost immediate uptake in modified boxing programs.展开更多
Stroke represents a severe,widespread,and widely acknowledged health crisis on both national and international levels.It is one of the most prevalent life-threatening conditions.Despite impressive advances in treating...Stroke represents a severe,widespread,and widely acknowledged health crisis on both national and international levels.It is one of the most prevalent life-threatening conditions.Despite impressive advances in treating stroke,in addition to a need for effective patient care services,many sufferers still rely solely on physical interventions.The present paper describes and explains the use of a newly designed gadget for stroke survivors who cannot move their fingers.This is a sophisticated mobile device that enables stroke patients to regain their muscle memory and thus their ability to perform repetitive actions by continuing to tighten and stretch their muscles without the intervention of a physiotherapist.Gamification methodology is used to encourage patients to become involved in the process of rehabilitation.The device also has sensors that take information and transmit it to an app through an ESP32 connection.This enables physicians to view glove usage information remotely and keep track of an individual patient’s health.Communication between app and glove is facilitated by a broker in the Amazon Web Service IoT.With the robotic glove presented here,the recovery rate is found to be 90.23%over four weeks’duration,which represents a significant improvement compared with existing hospital-based rehabilitation techniques.展开更多
This study aimed to investigate the effects of firefighters’protective gloves on physiological responses,psychological responses,and manual performance in a cold environment through human trials.Twelve participants w...This study aimed to investigate the effects of firefighters’protective gloves on physiological responses,psychological responses,and manual performance in a cold environment through human trials.Twelve participants wearing firefighter protective equipment were exposed to a 16℃ environment,while their hands were exposed to a small chamber of 0℃ with(FPG)and without(CON)firefighting protective gloves.During the trials,physiological responses(core temperature(Tc),the mean skin temperature(Tsk),and heart rate(HR)),psychological responses(thermal sensation vote(TSV)and pain sensation vote(PSV)),and manual performance(handgrip strength,manual dexterity,maximum finger flexion,and tactile sensitivity)were obtained.The results indicated a significant difference(p<0.05)between FPG and CON regarding Tsk.Furthermore,pain sensation occurred when the mean skin temperature of the hand was between 15℃ and 20℃.Gloves significantly(p<0.05)reduced handgrip strength,manual dexterity,and tactile sensitivity in the cold exposure.This study provides fundamental knowledge for cold strain assessment and high-performance protective glove development with the potential to improve firefighters’safety and health.展开更多
The surge in medical waste,fueled by the impact of COVID-19 and the influenza A virus,poses substantial challenges to waste treatment.Nevertheless,pyrolysis technology introduces a novel approach to the treatment of m...The surge in medical waste,fueled by the impact of COVID-19 and the influenza A virus,poses substantial challenges to waste treatment.Nevertheless,pyrolysis technology introduces a novel approach to the treatment of medical waste.This study investigated the pyrolytic characteristics,kinetics,thermodynamic parameters,volatile gases,and pyrolytic pathways of medical rubber gloves(MRGs)in a N2 atmosphere utilizing Thermal Gravimetric Analyzer(TGA),Thermogravimetric-Fourier transform infrared spectroscopy(TG-FTIR)and Pyrolysis gas chrogams-mass spectrometry(Py-GC/MS)analyses.Pyrolysis of MRG predominantly occurs between 284-501℃ and 613-701℃.The initial stage is the primary reaction phase,exhibiting an average activation energy of 339.77 kJ/mol,following the reaction order model(Fn).The second pyrolysis stage has an average activation energy of 236.93 kJ/mol and adheres to the geometric contraction model(Rn).The volatile products from MRG pyrolysis primarily comprise olefins,alkanes,and aromatic hydrocarbons.The olefins consist primarily of 1,2-pentadiene and D-limonene,while the alkanes include cyclopropane,cyclohexane,and 1,4-dimethyl.Aromatic compounds are chiefly benzene,toluene,and xylene.展开更多
通过检索关键词,指定一个或多个类别标签实现文本的高效组织和自动分类,是发现文档中的隐含关系、推动知识传播和创新的重要途径。然而,检索关键词的获取位置、词性以及选取是否全面等因素,会导致关键词语义信息缺失和关键词识别准确性...通过检索关键词,指定一个或多个类别标签实现文本的高效组织和自动分类,是发现文档中的隐含关系、推动知识传播和创新的重要途径。然而,检索关键词的获取位置、词性以及选取是否全面等因素,会导致关键词语义信息缺失和关键词识别准确性较差;这两大问题,正是影响文档高效、精准自动分类的突出障碍。基于此,论文构建了一个融合TF-IDF(Term Frequency-Inverse Document Frequency)和GloVe(Global Vectors for Word Representation)的文本自动分类系统。该系统首先就词性影响因子和位置权重系数对TF-IDF算法进行改进,以弥补传统TF-IDF算法在关键词识别和语义分析上的不足;其次,使用GloVe模型对关键词集进一步扩充,使文本自动分类的准确率和召回率分别达到92.6%和90.9%;最后,通过实验比对,进一步验证该系统在处理多类别文本自动分类任务中的有效性。展开更多
In the dim light of Studio A at the Jack Doyle Athletics and Recreation Centre,the air is thick with sweat and the sounds of focused concentrated effort.The rhythmic pounding of gloves hitting bags and the steady boun...In the dim light of Studio A at the Jack Doyle Athletics and Recreation Centre,the air is thick with sweat and the sounds of focused concentrated effort.The rhythmic pounding of gloves hitting bags and the steady bounce of jump ropes fill the room.This is my hideaway—a place where every strike and kick is a conversation with myself.展开更多
Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent solution.In this study,we developed an...Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent solution.In this study,we developed an innovative,lightweight,and detachable data glove tailored for finger motion tracking in VR environments.Methods The glove design incorporates a potentiometer coupled with a flexible rack and pinion gear system,facilitating precise and natural hand gestures for interaction with VR applications.Initially,we calibrated the potentiometer to align with the actual finger bending angle,and verified the accuracy of angle measurements recorded by the data glove.To verify the precision and reliability of our data glove,we conducted repeatability testing for flexion(grip test)and extension(flat test),with 250 measurements each,across five users.We employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable data.Furthermore,we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration tool.Conclusions The repeatability analysis revealed an aggregate error of 1.45 degrees in both the gripped and flat hand positions.This outcome was notably favorable when compared with the findings from assessments of nine alternative data gloves that employed similar protocols.In these experiments,users navigated and engaged with virtual objects,underlining the glove's exact tracking of finger motion.Furthermore,the proposed data glove exhibited a low response time of 17-34 ms and back-drive force of only 0.19 N.Additionally,according to a comfort evaluation using the Comfort Rating Scales,the proposed glove system is wearable,placing it at the WL1 level.展开更多
With the rapid development of flexible electronics,the tactile systems for object recognition are becoming increasingly delicate.This paper presents the design of a tactile glove for object recognition,integrating 243...With the rapid development of flexible electronics,the tactile systems for object recognition are becoming increasingly delicate.This paper presents the design of a tactile glove for object recognition,integrating 243 palm pressure units and 126 finger joint strain units that are implemented by piezoresistive Velostat film.The palm pressure and joint bending strain data from the glove were collected using a two-dimensional resistance array scanning circuit and further converted into tactile images with a resolution of 32×32.To verify the effect of tactile data types on recognition precision,three datasets of tactile images were respectively built by palm pressure data,joint bending strain data,and a tactile data combing of both palm pressure and joint bending strain.An improved residual convolutional neural network(CNN)model,SP-ResNet,was developed by light-weighting ResNet-18 to classify these tactile images.Experimental results show that the data collection method combining palm pressure and joint bending strain demonstrates a 4.33%improvement in recognition precision compared to the best results obtained by using only palm pressure or joint bending strain.The recognition precision of 95.50%for 16 objects can be achieved by the presented tactile glove with SP-ResNet of less computation cost.The presented tactile system can serve as a sensing platform for intelligent prosthetics and robot grippers.展开更多
The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situati...The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situation is raising significant concerns regarding the integrity and authenticity of academic work.In light of the above,the current research evaluates the effectiveness of Bidirectional Long Short-TermMemory(BiLSTM)networks enhanced with pre-trained GloVe(Global Vectors for Word Representation)embeddings to detect AIgenerated scientific Abstracts drawn from the AI-GA(Artificial Intelligence Generated Abstracts)dataset.Two core BiLSTM variants were assessed:a single-layer approach and a dual-layer design,each tested under static or adaptive embeddings.The single-layer model achieved nearly 97%accuracy with trainable GloVe,occasionally surpassing the deeper model.Despite these gains,neither configuration fully matched the 98.7%benchmark set by an earlier LSTMWord2Vec pipeline.Some runs were over-fitted when embeddings were fine-tuned,whereas static embeddings offered a slightly lower yet stable accuracy of around 96%.This lingering gap reinforces a key ethical and procedural concern:relying solely on automated tools,such as Turnitin’s AI-detection features,to penalize individuals’risks and unjust outcomes.Misclassifications,whether legitimate work is misread as AI-generated or engineered text,evade detection,demonstrating that these classifiers should not stand as the sole arbiters of authenticity.Amore comprehensive approach is warranted,one which weaves model outputs into a systematic process supported by expert judgment and institutional guidelines designed to protect originality.展开更多
In this work,we present a reconfigurable data glove design to capture different modes of human hand-object interactions,which are critical in training embodied artificial intelligence(AI)agents for fine manipulation t...In this work,we present a reconfigurable data glove design to capture different modes of human hand-object interactions,which are critical in training embodied artificial intelligence(AI)agents for fine manipulation tasks.To achieve various downstream tasks with distinct features,our reconfigurable data glove operates in three modes sharing a unified backbone design that reconstructs hand gestures in real time.In the tactile-sensing mode,the glove system aggregates manipulation force via customized force sensors made from a soft and thin piezoresistive material;this design minimizes interference during complex hand movements.The virtual reality(VR)mode enables real-time interaction in a physically plausible fashion:A caging-based approach is devised to determine stable grasps by detecting collision events.Leveraging a state-of-the-art finite element method,the simulation mode collects data on fine-grained four-dimensionalmanipulation events comprising hand and object motions in three-dimensional space and how the object's physical properties(e.g.,stress and energy)change in accordance with manipulation over time.Notably,the glove system presented here is the first to use high-fidelity simulation to investigate the unobservable physical and causal factors behind manipulation actions.In a series of experiments,we characterize our data glove in terms of individual sensors and the overall system.More specifically,we evaluate the system's three modes by①recording hand gestures and associated forces,②improving manipulation fluency in VR,and③producing realistic simulation effects of various tool uses,respectively.Based on these three modes,our reconfigurable data glove collects and reconstructs fine-grained human grasp data in both physical and virtual environments,thereby opening up new avenues for the learning of manipulation skills for embodied AI agents.展开更多
文摘The impact damping capabilities of four different boxing gloves were assessed under two different conditions of target padding to determine whether target characteristics might influence previous conclusions concerning potential for impact mitigation through novel glove design. A conventional 10?oz glove (Std 10?oz), a conventional 16?oz glove (Std 16?oz), a prototype pneumatic glove with a sealed bladder (SBLI) and a prototype pneumatic glove with a bladder allowing air exchange with the external environment (ARLI) were each dropped three times on to a force plate from six heights ranging from 2.5 to 5.0 metres. The force plate was covered by a 50 mm thick mat of EVA material and results obtained were compared with those of an earlier experiment involving use of a similar protocol but a 25 mm thick EVA force plate covering. The thicker mat greatly reduced peak impact forces for all gloves, with values for the Std 10?oz glove becoming much closer to those reported by other researchers for punches delivered by elite boxers to crash test manikins. Peak rates of force development were also substantially decreased. Protective effects provided by the ARLI glove relative to the Std 10?oz glove were diminished but still in the order of 17%?-?22% for peak impact force and 27%?-?49% for peak rate of force development across the range of drop heights. With the 50 mm mat thickness, the SBLI glove was as effective as the ARLI glove in reducing peak impact force, whereas this was not the case with the 25 mm mat. It was, however, always inferior to the ARLI glove in decreasing peak rate of force development. The ability of the ARLI glove to afford protection across a spectrum of impact conditions could yield important practical advantages.
文摘This study was aimed at improved understanding of the mechanisms of previously reported protective effects of a pneumatic boxing glove. A Motion Capture System was used to obtain velocity data from four different boxing gloves dropped on to a force plate from nine heights ranging from 1 to 5 metres. Two gloves were of the conventional type but differed in mass. The other two were prototype pneumatic gloves. One of these (SBLI) had a sealed bladder while the other (ARLI) incorporated a port allowing air exchange with the external environment. The pneumatic gloves decelerated more slowly than the conventional gloves following impact and compressed through a greater absolute distance. Consequently, they took longer to reach zero velocity. As drop height increased, these trends became more pronounced for the ARLI glove than the SBLI glove. Increase in velocity during rebound was also slower for the pneumatic gloves. The ARLI glove had a lower coefficient of restitution than any of the other gloves at low to moderate drop heights but not at high drop heights. The SBLI glove had a higher coefficient of restitution than the other gloves at all drop heights from 2 metres upwards. This indicated that, overall, the ARLI glove was the most effective, and the SBLI glove the least effective, in dissipating the kinetic energy of impact through conversion to other energy forms. For all gloves at all drop heights, peak positive acceleration at the beginning of rebound was of lower absolute magnitude than peak negative acceleration at the end of compression. The influence of drop height on an index characterising this relationship differed between the conventional and pneumatic gloves, possibly reflecting structural changes to gloves as impact energy increased. The conventional and pneumatic gloves differed regarding temporal alignment between key kinematic and kinetic events, and there were some differences between the two pneumatic gloves in this respect. Nevertheless, peak glove deceleration correlated highly with peak impact force, not only for each glove individually but also when data for all gloves were combined. The findings confirmed the potential practical utility of the ARLI glove and identified air cushion thickness, glove compressibility and capacity for air release and subsequent reuptake as critical aspects of its design.
文摘Ranging based on the reflection principle of ultrasonic wave propagating in the air has been widely used in modern life, such as car reversing radar, robot automatic obstacle avoidance etc. Aiming at the situation that the blinds have no way to know whether there are obstacles or big safety risks in front of them when they are walking, this paper designed obstacle avoidance gloves for the blinds based on ultrasonic sensors. With Arduino Nano single chip microcomputer as main controller, combined with ultrasonic sensor module, bluetooth module and speaker module, the glove realized the function of obstacle detection and alarm. The main working principle is by using the ultrasonic sensors to transmit and receive ultrasonic, the time difference for transmitting and receiving to detect the distance of obstacles ahead. Besides, by means of voice module output audio signals with different frequency according to the obstacle distance, the blinds can judge the distance between them to the obstacles based on the sound with different frequencies they heard. In this way, they can make responses in advance to avoid the obstacles ahead and the happening of the risk.
文摘Two prototype pneumatic boxing gloves of different design were compared against conventional 10?oz (Std 10?oz) and 16?oz (Std 16?oz) gloves in terms of ability to reduce impact forces delivered to a target. One of the pneumatic gloves (SBLI) contained a sealed air bladder inflated to a pressure of 2?kPa. The other (ARLI) incorporated a bladder that allowed release of air to the external environment upon contact with a target, followed by rapid air reuptake. Each glove was placed on to a mechanical fist and dropped 10 times on to an in-floor force plate from each of nine heights ranging from 1.0 to 5.0 metres, with the 5-metre drop generating a peak pre-impact glove velocity close to the reported maximum for elite boxers. Compared to the conventional gloves, the ARLI glove substantially reduced peak impact forces at all drop heights, with the reduction exceeding 30% even at the 5-metre level. The SBLI glove was as effective as the ARLI glove in reducing peak impact forces at drop heights of up to 2.5 metres, but its performance then progressively diminished, and at drop heights of 4.0, 4.5 and 5.0 metres it produced peak force readings similar to those recorded for the Std 10?oz and Std 16?oz gloves. The superiority of the ARLI glove was even more evident in relation to peak rate of force development, with reductions relative to the Std 10?oz glove being ~60% at drop heights up to 3.5 metres and still ~47% at 5 metres. Peak rate of force development for the SBLI glove exceeded that for the ARLI glove for all drop heights of 2.0 metres and above, and at 4.0, 4.5 and 5.0 metres it was higher than the readings for the Std 10 oz and 16?oz gloves. The protective effect of the ARLI glove was?associated with an increase in impact compliance and prolongation of contact time between glove and target. It is concluded that a pneumatic boxing glove that provides for air exchange with the external environment can greatly reduce impact magnitudes across the whole range of pre-impact glove velocities likely to be encountered in boxing, thereby mitigating risks associated with the sport. While acceptance of the gloves by the boxing community is uncertain, opportunity may exist for almost immediate uptake in modified boxing programs.
文摘Stroke represents a severe,widespread,and widely acknowledged health crisis on both national and international levels.It is one of the most prevalent life-threatening conditions.Despite impressive advances in treating stroke,in addition to a need for effective patient care services,many sufferers still rely solely on physical interventions.The present paper describes and explains the use of a newly designed gadget for stroke survivors who cannot move their fingers.This is a sophisticated mobile device that enables stroke patients to regain their muscle memory and thus their ability to perform repetitive actions by continuing to tighten and stretch their muscles without the intervention of a physiotherapist.Gamification methodology is used to encourage patients to become involved in the process of rehabilitation.The device also has sensors that take information and transmit it to an app through an ESP32 connection.This enables physicians to view glove usage information remotely and keep track of an individual patient’s health.Communication between app and glove is facilitated by a broker in the Amazon Web Service IoT.With the robotic glove presented here,the recovery rate is found to be 90.23%over four weeks’duration,which represents a significant improvement compared with existing hospital-based rehabilitation techniques.
文摘This study aimed to investigate the effects of firefighters’protective gloves on physiological responses,psychological responses,and manual performance in a cold environment through human trials.Twelve participants wearing firefighter protective equipment were exposed to a 16℃ environment,while their hands were exposed to a small chamber of 0℃ with(FPG)and without(CON)firefighting protective gloves.During the trials,physiological responses(core temperature(Tc),the mean skin temperature(Tsk),and heart rate(HR)),psychological responses(thermal sensation vote(TSV)and pain sensation vote(PSV)),and manual performance(handgrip strength,manual dexterity,maximum finger flexion,and tactile sensitivity)were obtained.The results indicated a significant difference(p<0.05)between FPG and CON regarding Tsk.Furthermore,pain sensation occurred when the mean skin temperature of the hand was between 15℃ and 20℃.Gloves significantly(p<0.05)reduced handgrip strength,manual dexterity,and tactile sensitivity in the cold exposure.This study provides fundamental knowledge for cold strain assessment and high-performance protective glove development with the potential to improve firefighters’safety and health.
基金financially supported by the LiaoNing Revitalization Talents Program(No.XLYC2008013)National Natural Science Foundation(No.U21A20142).
文摘The surge in medical waste,fueled by the impact of COVID-19 and the influenza A virus,poses substantial challenges to waste treatment.Nevertheless,pyrolysis technology introduces a novel approach to the treatment of medical waste.This study investigated the pyrolytic characteristics,kinetics,thermodynamic parameters,volatile gases,and pyrolytic pathways of medical rubber gloves(MRGs)in a N2 atmosphere utilizing Thermal Gravimetric Analyzer(TGA),Thermogravimetric-Fourier transform infrared spectroscopy(TG-FTIR)and Pyrolysis gas chrogams-mass spectrometry(Py-GC/MS)analyses.Pyrolysis of MRG predominantly occurs between 284-501℃ and 613-701℃.The initial stage is the primary reaction phase,exhibiting an average activation energy of 339.77 kJ/mol,following the reaction order model(Fn).The second pyrolysis stage has an average activation energy of 236.93 kJ/mol and adheres to the geometric contraction model(Rn).The volatile products from MRG pyrolysis primarily comprise olefins,alkanes,and aromatic hydrocarbons.The olefins consist primarily of 1,2-pentadiene and D-limonene,while the alkanes include cyclopropane,cyclohexane,and 1,4-dimethyl.Aromatic compounds are chiefly benzene,toluene,and xylene.
文摘通过检索关键词,指定一个或多个类别标签实现文本的高效组织和自动分类,是发现文档中的隐含关系、推动知识传播和创新的重要途径。然而,检索关键词的获取位置、词性以及选取是否全面等因素,会导致关键词语义信息缺失和关键词识别准确性较差;这两大问题,正是影响文档高效、精准自动分类的突出障碍。基于此,论文构建了一个融合TF-IDF(Term Frequency-Inverse Document Frequency)和GloVe(Global Vectors for Word Representation)的文本自动分类系统。该系统首先就词性影响因子和位置权重系数对TF-IDF算法进行改进,以弥补传统TF-IDF算法在关键词识别和语义分析上的不足;其次,使用GloVe模型对关键词集进一步扩充,使文本自动分类的准确率和召回率分别达到92.6%和90.9%;最后,通过实验比对,进一步验证该系统在处理多类别文本自动分类任务中的有效性。
文摘In the dim light of Studio A at the Jack Doyle Athletics and Recreation Centre,the air is thick with sweat and the sounds of focused concentrated effort.The rhythmic pounding of gloves hitting bags and the steady bounce of jump ropes fill the room.This is my hideaway—a place where every strike and kick is a conversation with myself.
基金Supported by the Sirindhorn International Institute of Technology,Thammasat University,EFS-G(Excellent foreign Student-Graduate)research fund.
文摘Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent solution.In this study,we developed an innovative,lightweight,and detachable data glove tailored for finger motion tracking in VR environments.Methods The glove design incorporates a potentiometer coupled with a flexible rack and pinion gear system,facilitating precise and natural hand gestures for interaction with VR applications.Initially,we calibrated the potentiometer to align with the actual finger bending angle,and verified the accuracy of angle measurements recorded by the data glove.To verify the precision and reliability of our data glove,we conducted repeatability testing for flexion(grip test)and extension(flat test),with 250 measurements each,across five users.We employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable data.Furthermore,we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration tool.Conclusions The repeatability analysis revealed an aggregate error of 1.45 degrees in both the gripped and flat hand positions.This outcome was notably favorable when compared with the findings from assessments of nine alternative data gloves that employed similar protocols.In these experiments,users navigated and engaged with virtual objects,underlining the glove's exact tracking of finger motion.Furthermore,the proposed data glove exhibited a low response time of 17-34 ms and back-drive force of only 0.19 N.Additionally,according to a comfort evaluation using the Comfort Rating Scales,the proposed glove system is wearable,placing it at the WL1 level.
基金supported by the Key Research and Development Program of Shaanxi Province(No.2024 GX-YBXM-178)the Shaanxi Province Qinchuangyuan“Scientists+Engineers”Team Development(No.2022KXJ032)。
文摘With the rapid development of flexible electronics,the tactile systems for object recognition are becoming increasingly delicate.This paper presents the design of a tactile glove for object recognition,integrating 243 palm pressure units and 126 finger joint strain units that are implemented by piezoresistive Velostat film.The palm pressure and joint bending strain data from the glove were collected using a two-dimensional resistance array scanning circuit and further converted into tactile images with a resolution of 32×32.To verify the effect of tactile data types on recognition precision,three datasets of tactile images were respectively built by palm pressure data,joint bending strain data,and a tactile data combing of both palm pressure and joint bending strain.An improved residual convolutional neural network(CNN)model,SP-ResNet,was developed by light-weighting ResNet-18 to classify these tactile images.Experimental results show that the data collection method combining palm pressure and joint bending strain demonstrates a 4.33%improvement in recognition precision compared to the best results obtained by using only palm pressure or joint bending strain.The recognition precision of 95.50%for 16 objects can be achieved by the presented tactile glove with SP-ResNet of less computation cost.The presented tactile system can serve as a sensing platform for intelligent prosthetics and robot grippers.
文摘The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situation is raising significant concerns regarding the integrity and authenticity of academic work.In light of the above,the current research evaluates the effectiveness of Bidirectional Long Short-TermMemory(BiLSTM)networks enhanced with pre-trained GloVe(Global Vectors for Word Representation)embeddings to detect AIgenerated scientific Abstracts drawn from the AI-GA(Artificial Intelligence Generated Abstracts)dataset.Two core BiLSTM variants were assessed:a single-layer approach and a dual-layer design,each tested under static or adaptive embeddings.The single-layer model achieved nearly 97%accuracy with trainable GloVe,occasionally surpassing the deeper model.Despite these gains,neither configuration fully matched the 98.7%benchmark set by an earlier LSTMWord2Vec pipeline.Some runs were over-fitted when embeddings were fine-tuned,whereas static embeddings offered a slightly lower yet stable accuracy of around 96%.This lingering gap reinforces a key ethical and procedural concern:relying solely on automated tools,such as Turnitin’s AI-detection features,to penalize individuals’risks and unjust outcomes.Misclassifications,whether legitimate work is misread as AI-generated or engineered text,evade detection,demonstrating that these classifiers should not stand as the sole arbiters of authenticity.Amore comprehensive approach is warranted,one which weaves model outputs into a systematic process supported by expert judgment and institutional guidelines designed to protect originality.
基金the National Key Research and Development Program of China(2021ZD0150200)the Beijing Nova Program.
文摘In this work,we present a reconfigurable data glove design to capture different modes of human hand-object interactions,which are critical in training embodied artificial intelligence(AI)agents for fine manipulation tasks.To achieve various downstream tasks with distinct features,our reconfigurable data glove operates in three modes sharing a unified backbone design that reconstructs hand gestures in real time.In the tactile-sensing mode,the glove system aggregates manipulation force via customized force sensors made from a soft and thin piezoresistive material;this design minimizes interference during complex hand movements.The virtual reality(VR)mode enables real-time interaction in a physically plausible fashion:A caging-based approach is devised to determine stable grasps by detecting collision events.Leveraging a state-of-the-art finite element method,the simulation mode collects data on fine-grained four-dimensionalmanipulation events comprising hand and object motions in three-dimensional space and how the object's physical properties(e.g.,stress and energy)change in accordance with manipulation over time.Notably,the glove system presented here is the first to use high-fidelity simulation to investigate the unobservable physical and causal factors behind manipulation actions.In a series of experiments,we characterize our data glove in terms of individual sensors and the overall system.More specifically,we evaluate the system's three modes by①recording hand gestures and associated forces,②improving manipulation fluency in VR,and③producing realistic simulation effects of various tool uses,respectively.Based on these three modes,our reconfigurable data glove collects and reconstructs fine-grained human grasp data in both physical and virtual environments,thereby opening up new avenues for the learning of manipulation skills for embodied AI agents.
