The clutch size,incubation behavior of Reeves’s Pheasant(Syrmaticus reevesii) and their responses to ambient temperature and precipitation

Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conservation.Reeves’ s Pheasant(Syrmaticus reevesii) is a threatened species endemic to China,which is characterized by female-only incubation.However,there is a lack of information regarding the impact of weather conditions on clutch size and incubation behavior in this species.Using satellite tracking,we tracked 27 wild female Reeves’ s Pheasants from 2020 to 2023 in Hubei Province,China.We explored their clutch size and incubation behavior,as well as their responses to ambient temperature and precipitation.Clutch size averaged 7.75 ±1.36,had an association with average ambient temperature and average daily precipitation during the egglaying period,and was potentially linked to female breeding attempts.Throughout the incubation period,females took an average of 0.73 ±0.46 recesses every 24 h,with an average recess duration of 100.80 ±73.37 min and an average nest attendance of 92.98 ±5.27%.They showed a unimodal recess pattern in which nest departures peaked primarily between 13:00 and 16:00.Furthermore,females rarely left nests when daily precipitation was high.Recess duration and nest attendance were influenced by the interaction between daily mean ambient temperature and daily precipitation,as well as day of incubation.Additionally,there was a positive correlation between clutch size and recess duration.These results contribute valuable insights into the lifehistory features of this endangered species.

Interconnected microstructure and flexural behavior of Ti_(2)C-Ti composites with superior Young’s modulus

To enhance the Young’s modulus(E)and strength of titanium alloys,we designed titanium matrix composites with intercon-nected microstructure based on the Hashin-Shtrikman theory.According to the results,the in-situ reaction yielded an interconnected microstructure composed of Ti_(2)C particles when the Ti_(2)C content reached 50vol%.With widths of 10 and 230 nm,the intraparticle Ti lamellae in the prepared composite exhibited a bimodal size distribution due to precipitation and the unreacted Ti phase within the grown Ti_(2)C particles.The composites with interconnected microstructure attained superior properties,including E of 174.3 GPa and ultimate flexural strength of 1014 GPa.Compared with that of pure Ti,the E of the composite was increased by 55% due to the high Ti_(2)C content and interconnected microstructure.The outstanding strength resulted from the strong interfacial bonding,load-bearing capacity of interconnected Ti_(2)C particles,and bimodal intraparticle Ti lamellae,which minimized the average crack driving force.Interrupted flexural tests revealed preferential crack initiation along the{001}cleavage plane and grain boundary of Ti_(2)C in the region with the highest tensile stress.In addition,the propagation can be efficiently inhibited by interparticle Ti grains,which prevented the brittle fracture of the composites.

Adsorption behavior of CO_(2)/H_(2)S mixtures in calcite slit nanopores for CO_(2) storage:An insight from molecular perspective

It is acknowledged that injecting CO_(2) into oil reservoirs and saline aquifers for storage is a practical and affordable method for CO_(2) sequestration.Most CO_(2) produced from industrial exhaust contains impurity gases such as H_(2)S that might impact CO_(2) sequestration due to competitive adsorption.This study makes a commendable effort to explore the adsorption behavior of CO_(2)/H_(2)S mixtures in calcite slit nanopores.Grand Canonical Monte Carlo(GCMC)simulation is employed to reveal the adsorption of CO_(2),H_(2)S as well as their binary mixtures in calcite nanopores.Results show that the increase in pressure and temperature can promote and inhibit the adsorption capacity of CO_(2) and H_(2)S in calcite nanopores,respectively.CO_(2)exhibits stronger adsorption on calcite surface than H_(2)S.Electrostatic energy plays the dominating role in the adsorption behavior.Electrostatic energy accounts for 97.11%of the CO_(2)-calcite interaction energy and 56.33%of the H_(2)S-calcite interaction energy at 10 MPa and 323.15 K.The presence of H_(2)S inhibits the CO_(2) adsorption in calcite nanopores due to competitive adsorption,and a higher mole fraction of H_(2)S leads to less CO_(2) adsorption.The quantity of CO_(2) adsorbed is lessened by approximately 33%when the mole fraction of H_(2)S reaches 0.25.CO_(2) molecules preferentially occupy the regions near the po re wall and H_(2)S molecules tend to reside at the center of nanopore even when the molar ratio of CO_(2) is low,indicating that CO_(2) has an adsorption priority on the calcite surface over H_(2)S.In addition,moisture can weaken the adsorption of both CO_(2) and H_(2)S,while CO_(2) is more affected.More interestingly,we find that pure CO_(2) is more suitable to be sequestrated in the shallower formations,i.e.,500-1500 m,whereas CO_(2)with H_(2)S impurity should be settled in the deeper reservoirs.

Research on the Influence of Family Education on Children’s Behavioral Habits

Under the background of the all-round deepening of quality education,the cultivation of comprehensive quality has become the main theme of contemporary education reform.Good behavior and habits are of great significance to children’s future learning,growth,and development.Through literature review and other methods,this paper analyzes the current situation of children’s family education and the influence of family education on the cultivation of children’s behavioral habits and provides some strategies for cultivating children’s good behavioral habits in family education.

基于DEMATEL-AISM的起重驾驶员态势感知与行为响应模型

为深入挖掘起重驾驶员态势感知信息-行为的因果关系,结合ENDSLEY态势感知模型与决策实验室分析(DEMATEL)-对抗解释结构模型(AISM)方法,构建起重驾驶员态势感知与行为响应模型。首先,以起重作业任务为研究对象,使用态势感知理论分析驾驶员行为响应过程,获取信息要素;其次,基于DEMATEL法,量化研究要素间的相互关系,得到综合影响矩阵,进而分析要素的属性及特征值,确定模型的关键要素;最后,采用AISM获得原因-结果属性稳定的层级结构,据此构建起重驾驶员态势感知与行为响应信息模型。结果表明:得到包含轨迹预测与规划、避碰等关键要素的22个要素及影响关系构成的5层信息模型;而且,模型明确了信息要素属性特征、影响关系及影响程度,较好地解释了驾驶员态势感知及行为响应过程。

Using microscopic video data measures for driver behavior analysis during adverse winter weather:opportunities and challenges

This paper presents a driver behavior analysis using microscopic video data measures including vehicle speed, lane-changing ratio, and time to collision. An analytical framework was developed to evaluate the effect of adverse winter weather conditions on highway driving behavior based on automated （computer） and manual methods. The research was conducted through two case studies. The first case study was conducted to evaluate the feasibility of applying an au- tomated approach to extracting driver behavior data based on 15 video recordings obtained in the winter 2013 at three dif- ferent locations on the Don Valley Parkway in Toronto, Canada. A comparison was made between the automated approach and manual approach, and issues in collecting data using the automated approach under winter conditions were identified. The second case study was based on high quality data collected in the winter 2014, at a location on Highway 25 in Montreal, Canada. The results demonstrate the effectiveness of the automated analytical framework in analyzing driver behavior, as well as evaluating the impact of adverse winter weather conditions on driver behavior. This approach could be applied to evaluate winter maintenance strategies and crash risk on highways during adverse winter weather conditions.

GREEN'S FUNCTION AND THE POINTWISE BEHAVIORS OF THE VLASOV-POISSON-FOKKER-PLANCK SYSTEM

The pointwise space-time behaviors of the Green’s function and the global solution to the Vlasov-Poisson-Fokker-Planck(VPFP)system in three dimensional space are studied in this paper.It is shown that the Green’s function consists of the diffusion waves decaying exponentially in time but algebraically in space,and the singular kinetic waves which become smooth for all(t,x,v)when t>0.Furthermore,we establish the pointwise space-time behaviors of the global solution to the nonlinear VPFP system when the initial data is not necessarily smooth in terms of the Green’s function.

Quantification of Ride Comfort Using Musculoskeletal Mathematical Model Considering Vehicle Behavior

This research aims to quantify driver ride comfort due to changes in damper characteristics between comfort mode and sport mode,considering the vehicle’s inertial behavior.The comfort of riding in an automobile has been evaluated in recent years on the basis of a subjective sensory evaluation given by the driver.However,reflecting driving sensations in design work to improve ride comfort is abstract in nature and difficult to express theoretically.Therefore,we evaluated the human body’s effects while driving scientifically by quantifying the driver’s behavior while operating the steering wheel and the behavior of the automobile while in motion using physical quantities.To this end,we collected driver and vehicle data using amotion capture system and vehicle CAN and IMU sensors.We also constructed a three-dimensional musculoskeletal mathematical model to simulate driver movements and calculate the power and amount of energy per unit of time used for driving the joints and muscles of the human body.Here,we used comfort mode and sport mode to compare damper characteristics in terms of hardness.In comfort mode,damper characteristics are soft and steering stability is mild,but vibration from the road is not easily transmitted to the driver making for a lighter load on the driver.In sport mode,on the other hand,damper characteristics are hard and steering stability is comparatively better.Still,vibration from the road is easily transmitted to the driver,whichmakes it easy for a load to be placed on the driver.As a result of this comparison,it was found that a load was most likely to be applied to the driver’s neck.This result in relation to the neck joint can therefore be treated as an objective measure for quantifying ride comfort.

Virtual Reality Driving Simulation for Measuring Driver Behavior and Characteristics

This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are used for the purpose of training and researching driver behavior and characteristics;3) the article addresses driver experience by involving new virtual reality technologies. A simulator has been used to assist novice drivers to learn how to drive in a very safe environment, and researching and collecting data for researchers has become easier due to this secure and user-friendly environment. The theoretical framework of this driving simulation has been designed by using the Unity3D game engine (5.4.f3 version) and was programmed with the C# programming language. To make the driving environment more realistic we, in addition, utilized the HTC Vive Virtual reality headset which is powered by Steamvr. We used Unity Game Engine to design our scenarios and maps because by doing this we are able to be more flexible with designing. In this study, we asked 10 people ranging from ages 19 - 37 to participate in this experiment. Four Japanese divers and six non-Japanese drivers engaged in this study, some of which do not have a driver’s license in Japan. A few Japanese drivers have a license and car, while others have a license but no car. In order to analyze the results of this experiment we are used MatlabR2016b to analyze the gathered data. The result of this research indicates that individual’s behavior and characteristics such as controlling the speed, remaining calm and relaxed when driving, driving at appropriate speeds depending on changes in road structures and etc. can affect their driving performance.

Driving Style Recognition Based on Driver Behavior Questionnaire

The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. The present study aims to research driver pattern and classification feature. Driver behavior self-reported investigation was conducted with standardized driver behavior questionnaire (DBQ) by 225 nonprofessional drivers on the internet in Beijing. Questionnaire’s reliability was verified by statistics analysis. Confirmatory factor analysis (CFA) was used to analyze the underlying factor structure. Speed advantage, space occupation, the contend right of way and the contend space advantage were extracted from the ques-tionnaire results to quantify driver characteristics. Based on fuzzy C-means (FCM) algorithm and taking the four factors as pattern features, the number of driver classification distribution was discussed. Then the number of driver classification was determined by statistical indices. The comparison of classification results with the survey finding on whether the driver occurred in traffic accidents within five years shows that the classification result is the same as the actual driving conditions. Finally, correlation between the demographic and types of driving behavior has been analyzed. Female were more likely than male to careful driving, and the older the driver and the less driving experience, the more careful and moderate driving behavior is.

Vehicles, Advanced Features, Driver Behavior, and Safety: A Systematic Review of the Literature

Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lane departure warning (LDW), blind spot warning (BSW), over speed warning (OSW), forward collision warning (FCW), lane keep assist (LKA), adaptive cruise control (ACC), cooperative ACC (CACC), and automated emergency braking (AEB) are designed to assist with, or in some cases take over, certain driving maneuvers. They can be broadly categorized into advanced driver assistance system (ADAS) and automated features. Each of these advanced features focuses on addressing a particular task of driving, thereby, aiding the driver, influencing their behavior, and enhancing safety. Many vehicles with these advanced features are penetrating into the market, yet the total reported number of crashes has increased in recent years. This paper presents a systematic review of these advanced features on driver behavior and safety. The review is categorized into 1) survey and mathematical methods to assess driver behavior, 2) field test methods to assess driver behavior, 3) microsimulation methods to assess driver behavior, 4) driving simulator methods to assess driver behavior, and 5) driver understanding and the effectiveness of advanced features. It is followed by conclusions, knowledge gaps, and need for further research.

改进YOLOv7-tiny与D-S理论结合的实验室人员行为检测研究

针对目前实验室场景缺少对人员行为检测的方法,且主流算法精度低、误检率高的问题,文中提出一种改进YOLOv7-tiny的人员行为检测算法,并通过多源信息融合,提高人员行为在实际实验室场景中的识别准确率。首先,在检测算法主干网络引入GhostNetV2轻量化网络,进一步降低模型计算量和复杂度;其次,在颈部网络嵌入改进后的CBAM_E注意力模块,加强目标重要特征的提取;再次,在预测端使用SIoU替换原有的损失函数,减少角度因素和边界框回归精度的影响。检测结果表明,相较于YOLOv7-tiny,文中算法精度提升10.08%,模型参数量和复杂度分别下降36.45%和46.76%。最后通过将检测数据与传感器采集数据运用D-S证据理论进行信息融合后发现,人员不规范行为检测的误检率得到有效降低。结果表明,该方法可实现对实验室人员不规范行为的有效检测。

热处理对电沉积Ni-S合金微观组织和析氢性能的影响

电解水制氢是目前最有望替代矿石燃料制氢的技术,低成本且高效的析氢电极是限制电解水制氢大规模应用的瓶颈问题,而Ni-S合金具有易制备和高活性等优点,作为电解水的阴极材料具有极大的潜力。通过电沉积法在泡沫镍表面制备了非晶Ni-S合金,研究了Ni-S合金的晶化行为对其析氢性能的影响,热处理促使非晶Ni-S合金镀层再结晶转变为以Ni_(3)S_(2)和Ni为主的结晶层,电化学分析结果表明热处理减少非晶Ni-S合金镀层的析氢活性位点,增大氢气从Ni-S合金表面脱附难度,显著削弱Ni-S/NF电极的电化学析氢性能。

SAMP8小鼠在中医药抗痴呆中的应用研究进展

快速老化小鼠是一种早期学习记忆障碍模型,因其表现出阿尔茨海默病发病机制的大多数特征,包括抗衰老因子的异常表达、炎症因子的过度升高、淀粉样蛋白沉积、tau蛋白过度磷酸化、线粒体自噬、血脑屏障损伤的中枢机制以及多系统多器官的病理损伤,因而成为阿尔茨海默病(Alzheimer's disease,AD)研究的理想模型而广泛应用。随着AD机制实验研究的不断深入,发现SAMP8小鼠在行为活动、组织病理及生化参数指标上相较于SAMR1发生明显变化,并与人体疾病相类似。基于此,本文对SAMP8小鼠的行为学、组织病理和中医药实验研究进行了系统综述,加深对SAMP8小鼠的认识,了解其生理病理特性,并依据中医药实验研究对其中医证型进行推测,以期对SAMP8小鼠的科学应用提供有益帮助。

Grifola frondosa polysaccharides alleviate Alzheimer's disease in rats

Objective:To evaluate the effect of Grifola frondosa polysaccharides(GFP)in a rat model of Alzheimer’s disease(AD).Methods:Seventy-five rats were divided into five groups:the normal control group and the AD group treated with or without GFP(100,200,and 400 mg/kg).Behavioral responses in the open field test and elevated plus maze test were assessed.Additionally,the levels of malondialdehyde and ferric-reducing ability of plasma,and the mRNA expressions of TNF-α,IL-6,and IL-1βin the hippocampus were measured.Results:Treatment with GFP significantly improved AD-induced behavioral changes in the open field test and elevated plus maze test(P<0.05).In addition,the level of malondialdehyde and the mRNA expressions of TNF-α,IL-6,and IL-1βwere decreased by GFP treatment in a dose-dependent manner in AD rats(P<0.05),while the level of ferric-reducing ability of plasma was significantly increased(P<0.05).Conclusions:Oral administration of GFP can reduce inflammation and oxidative stress,as well as improve behavioral responses associated with AD,suggesting its potential use in AD treatment.However,additional studies are needed to elucidate its underlying mechanisms and efficacy.

BEHAVIORAL TOXICOLOGICAL RESEARCHES ON AUTOMQBILE DRIVERS' DRIVING ACCIDENTS

125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core Test Battery (WHO NCTB). The results showed that there were obvious negative mood states such as tension-anxiety and fatigue in AG and drivers with accidents had more poor neurobehavioral performances, especially attention, response speed and perceptual-motor speed than drivers without accidents and controls. We also found that automobile drivers' neurobehavioral functions got weakened with the increase of their age and got strengthened with the elevation of their educational level. And the functions were inversely correlative to the accidents they cuased. The results of our study suggest that WHO NCTB can be an index of researches on driving accidents that automobile drivers caused and can be used in occupational selection and training of drivers.

Evaluating Hazard Response Behavior of a Driver Using Physiological Signals and Car-Handling Indicators in a Simulated Driving Environment

Road traffic accidents are a major cause of casualties and costly implications to all the stakeholders. Research focusing on the driver as one of the causal agent of accidents has been studied for centuries and with the advent of modernized driver assistance technologies. This paper sought to evaluate response of a driver using active-driving performance indicators like reaction time and physiological signal response (surface electromyogram), to understand hazard response behavior. Simulation of driving scenes was done using Unity3D engine and VR Head mounted display. The driver was presented with stimulus (collision objects) of different size and distance. From the results, an event scene that the driver considered hazardous was marked with increased electromyography response distinct from non-event scenes. From the results, we noted an increase in pedal misapplication during hazard response. The proposed approach is applicable in a real time driving analysis for on-road risk level classification.

Generation and Selection of Driver-Behavior-Based Transferable MotionPrimitives

To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framework for offline generation and online selection of MPs is proposed. Optimal control theory is applied to solve the boundary value problems in the process of generating MPs, where the driver behaviors and the vehicle motion characteristics are integrated into the optimization in the form of constraints. Moreover, a layered, unequal-weighted MP selection framework is proposed that utilizes a combination of environmental constraints, nonholonomic vehicle constraints,trajectory smoothness, and collision risk as the single-step extension evaluation index. The library of MPs generated offline demonstrates that the proposed generation method realizes the effective expansion of MP types and achieves diverse generation of MPs with various velocity attributes and platform types. We also present how the MP selection algorithm utilizes a unique MP library to achieve online extension of MP sequences. The results show that the proposed motion-planning framework can not only improve the efficiency and rationality of the algorithm based on driving experience but can also transfer between heterogeneous vehicle platforms and highlight the unique motion characteristics of the platform.

基于人脸识别的课堂教学行为S-T分析系统设计

提出并详细介绍了一种基于人脸识别技术的课堂教学行为S-T分析系统的设计。该系统以S-T分析法为理论基础,采用多种人脸识别算法,包括年龄检测、表情分析、姿态分析等,旨在自动识别并分析教师和学生在课堂上的行为。基于大量课堂视频数据的准备、软件系统原型的设计、深入研究课堂教学行为理论等,解决人脸识别技术的算法选型、视频关键帧的分析与因果关系模型的建立、系统运行的稳定性和界面设计等关键技术问题。通过系统性的需求分析、设计与架构、实现、评估与可视化等阶段的论述,详细展现了该系统的开发过程。

Feasibility Study of Neurofeedback Therapy for Alzheimer’s Disease

Objective: This study aims to evaluate the feasibility and effectiveness of neurofeedback therapy based on brain-computer interface (BCI) games in enhancing cognitive functions and reducing disruptive behaviors in patients with Alzheimer’s disease (AD). Methods: Forty-six AD patients aged 49 - 76 years were recruited for the study. Neurofeedback regulation was conducted using a BCI game designed to modulate EEG rhythms. Cognitive function was assessed using MMSE, MoCA, and ADAS-cog scales before and after a 10-day training period. EEG measurements were taken to evaluate changes in brain activity complexity. Statistical analyses were performed using SPSS25.0 software to compare pre- and post-training scores. Results: Post-intervention results showed significant improvement in the cognitive function of AD patients. The total scores of MMSE, MoCA, and ADAS-cog scales increased significantly (P < 0.01). Notable improvements were observed in memory, language, and attention domains. EEG complexity in the left frontal area also showed a significant increase (P < 0.05). Additionally, the disruptive behaviors of patients were significantly reduced, improving their overall quality of life. Conclusions: Neurofeedback therapy based on BCI games is a promising intervention for enhancing cognitive functions and reducing disruptive behaviors in AD patients. This innovative approach demonstrates significant potential for clinical application, providing a non-invasive method to improve patient outcomes. Further studies with larger sample sizes and long-term follow-ups are recommended to validate these findings and explore the specific effects of NFB training on different cognitive impairment levels.