bluuebunny/crossref_metadata_2025 huggingface dataset:
Pedestrian detection under weather conditions using conditional generative adversarial network
Authors: Razzok Mohammed , Badri Abdelmajid , Mourabit Ilham EL , Ruichek Yassine , Sahel Aïcha
Published: August 2023

Nowadays, many pedestrians are injured or killed in traffic accidents. As a result, several artificial vision solutions based on pedestrian detection have been developed to assist drivers and reduce the number of accidents. Most pedestrian detection techniques work well on sunny days and provide accurate traffic data. However, detection decreases dramatically in rainy conditions. In this paper, a new pedestrian detection system (PDS) based on generative adversarial network (GAN) module and the real-time object detector you only look once (YOLO) v3 is proposed to mitigate adversarial weather attacks. Experimental evaluations performed on the VOC2014 dataset show that our proposed system performs better than models based on existing noise reduction methods in terms of accuracy for weather situations.
Developing Viola Jones' algorithm for detecting and tracking a human face in video file
Authors: Younis Ansam Nazar , Ramo Fawziya Mahmood
Published: August 2023

Face detecting and tracking in video clips is very important in many areas of
daily life. All institutions, public departments, streets, and large stores use
cameras from a security point of view, and detecting and tracking human
faces is necessary for indexing and preserving information concerning the
visual media. This paper presents a novel method for hybridizing the
Viola_Jones face detection algorithm to track and identify a human face in
video sequences. The method represents a combination of Viola Jones'
algorithm with a measured normalized cross-correlation (NCC) algorithm
with a template matching method using the Manhattan distance measure
equation in the video between successive sequences After that, the fuzzy
logic method is added in comparing the image of the face to be detected with
the images of templates taken in the proposed algorithm, which increased the
accuracy of the results, which reached 99.3%.
Finger vein identification system using capsule networks with hyperparameter tuning
Authors: Yulianto Vandy Achmad , Effendy Nazrul , Arif Agus
Published: August 2023

Safety and security systems are essential for personnel who need to be protected and valuables. The security and safety system can be supported using a biometric system to identify and verify permitted users or owners. Finger vein is one type of biometric system that has high-level security. The finger vein biometrics system has two primary functions: identification and verification. Safety and security technology development is often followed by hackers' development of science and technology. Therefore, the science and technology of safety and security need to be continuously developed. The paper proposes finger vein identification using capsule networks with hyperparameter tuning. The augmentation, convolution layer parameters, and capsule layers are optimized. The experimental results show that the capsule network with hyperparameter tuning successfully identifies the finger vein images. The system achieves an accuracy of 91.25% using the Shandong University machine learning and applications-homologous multimodal traits (SDUMLA-HMT) dataset.
Facial recognition and body temperature measurements based on thermal images using a deep-learning algorithm
Authors: Dwijayanti Suci , Ramadhan Muhammad Ridho , Suprapto Bhakti Yudho
Published: August 2023

Recognizing the early symptoms of the SARS-CoV-2 virus (COVID-19) is essential for minimizing its spread. One of the typical symptoms of a person infected with COVID-19 is increased body temperature beyond the normal range. Facial recognition can be used to separate healthy people from those with high body temperatures based on thermal images of the faces. In this study, the XEAST XE-27 thermal imager modes 2, 3, and 4 comprising 1500 thermal images each were compared. The facial recognition was performed using a convolutional neural network. Additionally, body temperatures were extracted from thermal images using matrix laboratory (MATLAB) by considering the minimum and maximum temperatures of each mode and class. The network training results indicate that the accuracies achieved by the proposed facial recognition system in modes 2, 3, and 4 are 87.33%, 92.33%, and 91.66%, respectively. Furthermore, the accuracies of body temperature extraction in modes 2, 3, and 4 are 70%, 60%, and 40%, respectively. Thus, the proposed system serves as a contactless technique for the early detection of COVID-19 symptoms by combining facial recognition and body temperature measurements.
Machine learning approach for predicting heart and diabetes diseases using data-driven analysis
Authors: Sekar Usha , Selvarajan Kanchana
Published: August 2023

Environmental changes and food habits affect people's health with numerous
diseases in today's life. Machine learning is a technique that plays a vital role
in predicting diseases from collected data. The health sector has plenty of
electronic medical data, which helps this technique to diagnose various
diseases quickly and accurately. There has been an improvement in accuracy
in medical data analysis as data continues to grow in the medical field. Doctors
may have a hard time predicting symptoms accurately. This proposed work
utilized Kaggle data to predict and diagnose heart and diabetic diseases. The
diseases heart and diabetes are the foremost cause of higher death rates for
people. The dataset contains target features for the diagnosis of heart disease.
This work finds the target variable for diabetic disease by comparing the
patient's blood sugars to normal levels. Blood pressure, body mass index
(BMI), and other factors diagnose these diseases and disorders. This work
justifies the filter method and principal component analysis for selecting and
extracting the feature. The main aim of this work is to highlight the
implementation of three ensemble techniques-Adaptive boost, Extreme
Gradient boosting, and Gradient boosting-as well as the emphasis placed on
the accuracy of the results.
Predictive maintenance of electromechanical systems based on enhanced generative adversarial neural network with convolutional neural network
Authors: Abood Azhar Muneer , Nasser Ahmed Raoof , Al-Khazraji Huthaifa
Published: August 2023

Predictive maintenance (PdM) is a cost-cutting method that involves avoiding breakdowns and production losses. Deep learning (DL) algorithms can be used for defect prediction and diagnostics due to the huge amount of data generated by the integration of analog and digital systems in manufacturing operations. To improve the predictive maintenance strategy, this study uses a hybrid of the convolutional neural network (CNN) and conditional generative adversarial neural network (CGAN) model. The proposed CNN-CGAN algorithm improves forecast accuracy while substantially reducing model complexity. A comparison with standalone CGAN utilizing a public dataset is performed to evaluate the proposed model. The results show that the proposed CNN-CGAN model outperforms the conditional GAN (CGAN) in terms of prediction accuracy. The average F-Score is increased from 97.625% for the CGAN to 100% for the CNN-CGAN.
Short-term hand gestures recognition based on electromyography signals
Authors: Essa Raghad Radi , Jaber Hanadi A. , Jasim Abbas A.
Published: August 2023

Electromyography pattern recognition to predict limb movements can
significantly enhance the control of the prosthesis. However, this technique
has not yet been widely used in clinical practice. Improvements in the
myoelectric pattern recognition (MPR) system can improve the functionality
of the prosthesis. This study proposes new sets of time domain features to
enhance the MPR control system. Three groups of features are evaluated, time
domain with auto regression (TD-AR), frequency domain (FD), and timefrequency domain (TFD). The electromyography signals (EMG) are obtained from the Ninapro database-5 (DB5), a publicly available dataset for hand prosthetics. The long-term signals of DB5 are divided into short-term signals to perform short-term signals recognition. The three feature sets are extracted from the short-term signals. The results showed that the performance of the proposed TD-AR features outperformed that of the FD and TFD feature sets. The TD-AR-based discrimination performance of 40 gestures achieved a precision of 88.8% and a sensitivity of 82.6%. The integration of short-term identification with reliable features can improve classification accuracy even for a large number of gestures. A comparison with the latest works shows the reliability of the proposed work.
Improving Indonesian multietnics speaker recognition using pitch shifting data augmentation
Authors: Nugroho Kristiawan , Nugroho Isworo , Moses Setiadi De Rosal Igniatus , Farooq Omar
Published: August 2023

Speaker recognition to recognize multiethnic speakers is an interesting research topic. Various studies involving many ethnicities require the right approach to achieve optimal model performance. The deep learning approach has been used in speaker recognition research involving many classes to achieve high accuracy results with promising results. However, multi-class and imbalanced datasets are still obstacles encountered in various studies using the deep learning method which cause overfitting and decreased accuracy. Data augmentation is an approach model used in overcoming the problem of small amounts of data and multiclass problems. This approach can improve the quality of research data according to the method applied. This study proposes a data augmentation method using pitch shifting with a deep neural network called pitch shifting data augmentation deep neural network (PSDA-DNN) to identify multiethnic Indonesian speakers. The results of the research that has been done prove that the PSDA-DNN approach is the best method in multi-ethnic speaker recognition where the accuracy reaches 99.27% and the precision, recall, F1 score is 97.60%.
Hate speech detection on Indonesian text using word embedding method-global vector
Authors: Hayaty Mardhiya , Laksito Arif Dwi , Adi Sumarni
Published: August 2023

Hate speech is defined as communication directed toward a specific individual or group that involves hatred or anger and a language with solid arguments leading to someone's opinion can cause social conflict. It has a lot of potential for individuals to communicate their thoughts on an online platform because the number of Internet users globally, including in Indonesia, is continually rising. This study aims to observe the impact of pre-trained global vector (GloVe) word embedding on accuracy in the classification of hate speech and non-hate speech. The use of pre-trained GloVe (Indonesian text) and single and multi-layer long short-term memory (LSTM) classifiers has performance that is resistant to overfitting compared to pre-trainable embedding for hatespeech detection. The accuracy value is 81.5% on a single layer and 80.9% on a double-layer LSTM. The following job is to provide pre-trained with formal and non-formal language corpus; pre-processing to overcome non-formal words is very challenging.
High uncertainty aware localization and error optimization of mobile nodes for wireless sensor networks
Authors: Nandyala Raja Thejaswini , Gandhi Muthupandi
Published: August 2023

The localization of mobile sensor nodes in a wireless sensor network (WSN) is a key research area for the speedy development of wireless communication and microelectronics. The localization of mobile sensor nodes massively depends upon the received signal strength (RSS). Recently, the least squared relative error (LSRE) measurements are optimized using traditional semidefinite programming (SDP) and the location of the mobile sensor nodes was determined using the previous localization methods like least squared relative error and semidefinite programming (LSRE-SDP), and approximate nonlinear least squares and semidefinite programming (ANLS-SDP). Therefore, in this work, a novel high uncertainty aware-localization error correction and optimization (HUA-LECO) model is employed to minimize the aforementioned problems regarding the localization of mobile sensor nodes and enhance the performance efficiency of root mean square error (RMSE) results. Here, the position of target mobile sensor nodes is evaluated based on the gathered measurements while discarding faulty data. Here, an iterative weight updation approach is utilized to perform localization based on Monte Carlo simulations. Simulation results show significant improvement in terms of RMSE results in comparison with traditional LSRE-SDP and ANLS-SDP methods under high uncertainty.
Lembrar e esquecer em história intelectual: o Brasil e as ciências sociais francesas no século XX
Authors: Osés Mariana
Published: August 2023

Resenha do livro: MERKEL, Ian. Terms of Exchange: Brazilian Intellectuals and the French Social Sciences. Chicago: University of Chicago Press, 2022.
Molecular characterisation of the potato cyst nematode, Globodera ellingtonae Handoo et al., 2012 (Tylenchida: Heteroderidae) from Bolivia
Authors: Subbotin Sergei A. , Sainz Claudia , Villarroel Carmen L. , Franco Javier
Published: August 2023

In 2022, during potato cyst nematode surveys in several departments of Bolivia, the potato cyst nematode Globodera ellingtonae Handoo et al., 2012 was detected for the first time in Bolivia from potato fields located in the Department of Tarija. Cysts and second-stage juveniles of the Bolivian populations were morphologically and morphometrically similar to those of the USA (Oregon and Idaho) and Argentina. Nine new ITS rRNA, 15 COI, 13 cytb gene sequences of G. ellingtonae from ten Bolivian populations were obtained in this study. The phylogenetic analyses of the ITS rRNA and cytb genes showed that all Bolivian sequences clustered together and formed a major clade with other G. ellingtonae sequences from Argentina, Chile and the USA. Molecular results confirmed the hypothesis that the mountain region in southern Bolivia, northwest Argentina and northern Chile could be considered as an ancient centre of origin of G. ellingtonae. The present molecular results suggested that G. ellingtonae was likely introduced into the USA from Chile, rather than from Bolivia and Argentina.
Spirit in the Sisters: The Church Cracked Open
Authors: Varghese Winnie Sara
Published: August 2023

A brief reflection on the Rev. Canon Stephanie Spellers’ contribution to the movements to center evangelism and radical welcome in the Episcopal Church.
Business Agility: Key Themes and Future Directions
Authors: Girod Stéphane J. G. , Birkinshaw Julian , Prange Christiane
Published: August 2023

The need for business agility, that is, the capacity to adapt to changing external circumstances (and even to shape them), is high on the agenda of executives around the world, as they face up to increasing levels of uncertainty. But uncertainty still abounds about what business agility is, and most executives still struggle to master this capability. The introduction to this special issue reviews what we know and still do not know about business agility and introduces the six articles and suggests a path for more research.
The Effects of Auditory Working Memory Task on Situation Awareness in Complex Dynamic Environments: An Eye-movement Study
Authors: Xie Xudong , Li Tiantian , Xu Shuai , Yu Yingyue , Ma Yifeng , Liu Zhen , Ji Ming
Published: August 2023

Objective

This study investigated the effect of auditory working memory task on situation awareness (SA) and eye-movement patterns in complex dynamic environments.

Background

Many human errors in aviation are caused by a lack of SA, and distraction from auditory secondary tasks is a serious threat to SA. However, it remains unclear how auditory working memory tasks affect SA and eye-movement patterns.

Method

Participants (n = 28) were randomly allocated to two groups and received different periods of visual search training (short versus long). They subsequently completed a situation awareness measurement task in three auditory secondary task conditions (without secondary task, auditory calculation task, and auditory 2-back task). Eye-movement data were collected during the situation awareness measurement task.

Results

The auditory 2-back task significantly reduced overall SA, Level 1 SA, dwell times, and total percentage of fixation time on task-related areas of interests in the SA measurement task. Overall SA and Level 3 SA were not reduced by the auditory 2-back task in individuals in the longer visual search training time condition.

Conclusion

Auditory working memory load impairs SA in the perception and projection stage; however, greater experience can overcome impairment of SA in the projection stage.

Application

This study provided possible approaches to preventing loss of SA: (1) improving crew members’ communication skills to ensure the accurate and clear transmission of information, reducing the difficulty of processing information, and (2) providing targeted cognitive training tailored to each pilot’s level of experience.
Folding organizational paradoxes: Narrative practices for legitimation amid competing stakeholder demands
Authors: Molecke Greg , Hahn Tobias , Pinkse Jonatan
Published: August 2023

In paradoxical situations, organizational actors face various demands that are contradictory and interdependent at the same time. While the current literature focuses on how organizational actors respond to these paradoxical demands, it does so in a depersonalized manner with little attention to the stakeholders behind these demands. Therefore, it fails to explain how organizational actors legitimize their responses to paradox to those stakeholders who bring up the paradoxical demands. Using a narrative sensemaking approach, we study how social entrepreneurs legitimize their efforts to respond to paradoxical stakeholder demands for both delivering and measuring social impact. We find that social entrepreneurs legitimize their responses to this paradoxical situation through a narrative mechanism of folding. Through folding, narrators construct legitimizing accounts by narratively producing temporary alignments with some stakeholder interests, while opposing others. Through the recurring and consistently inconsistent use of the narrative practices of embodying and positioning, narrators produce a legitimizing account that overall portrays their responses to paradox as balanced and non-biased. As our main contribution, we offer a model of folding as a narrative, interest-based mechanism that explains how organizational actors legitimize their efforts to navigate paradoxical situations by portraying themselves as attending to paradoxical demands through a temporary and fluid shift between momentary alignments and oppositions of stakeholder interests.
Changes of stressful life events, coping strategies and mental health among youths in the pre- and post-coronavirus 2019 pandemic era: A cross-sectional study
Authors: Ding Hexiao , Xu Ziruo , Hu Wangjing , Guo Yannan , Wang Cailing , Li Sicheng , Hui Zhengyang , Wang Jing , Peng Xinran , Xia Wei
Published: August 2023

Background:

In the pandemic era, stressful life events (StressLEv) aggravated the impact on mental health. However, youths exhibited different responses to StressLEv because of diverse coping strategies, social support, and emotional intelligence before and after the pandemic.

Aims:

To explore the changes in StressLEv and coping strategies before and after the coronavirus 2019 pandemic, as well as report the associations among mental health and related factors in a sample of Chinese youths experiencing the post-pandemic era.

Method:

A cross-sectional study using convenience sampling was conducted from July 1 to August 30, 2022, covering 3,038 youths aged 14 to 25 in China. Multiple logistic regression was conducted for crude odds ratios (ORs) and adjusted ORs. The relationships between lasso-selected variables was examined using structural equation modeling.

Results:

More StressLEv and limited coping strategies were reported after the pandemic. In the post-pandemic era, BSI-positive youths (youths diagnosed as considered case by Brief Symptom Inventory, BSI) reported more StressLEv (BSI-positive: mean = 75.47; BSI-negative: mean = 28.69), less social support (BSI-positive: mean = 31.81; BSI-negative: mean = 39.22), and lower emotional intelligence (BSI-positive: mean = 75.34; BSI-negative: mean = 89.42). The willingness to engage in mental health counseling (OR: no vs. yes: 1.89; uncertain vs. yes: 4.42), being punished (OR: 1.27), adaptation problems (OR: 1.06), task-oriented coping (OR: 0.95), social diversion coping (OR: 0.90), objective support (OR: 0.90), utilization of social support (OR: 0.81), and regulation of emotion in oneself (OR: 0.94) were associated with mental health. Structural equation modeling supported our theoretical framework.

Conclusions:

Pandemic-induced mental health problems should not be ignored. The proposed response mechanisms could guide the development of effective interventions, which can help youths better cope with StressLEv and maintain good mental health.
Effects of thermal process conditions on crystallinity and mechanical properties in material extrusion additive manufacturing of discontinuous carbon fibre reinforced polyphenylene sulphide composites
Authors: Lyu Yahui , Wu Jiang , Zhang Haoqi , Brádaigh Conchúr M. Ó , Yang Dongmin
Published: August 2023

This study investigates the thermal behaviour of discontinuous carbon fibre reinforced polyphenylene sulphide (CF/PPS), additively manufactured by material extrusion, with a focus on the effects of thermal process conditions on the degree of crystallinity, oxidation crosslinking and mechanical properties of CF/PPS from filament fabrication, material extrusion to annealing treatment. The screw extrusion parameters are optimised by performing a thermal analysis of the fabricated filaments. The effect of crosslinking reactions on the crystallinity process in determining the mechanical properties of the printed samples is illustrated by investigating the influence of the printing conditions. Furthermore, the effect of annealing treatment on the semi-crystalline polyphenylene sulphide (PPS) is studied by measuring the degree of crystallinity and viscoelasticity behaviours. Results demonstrate that the flexural properties of the printed CF/PPS composites at elevated processing temperatures are determined by the oxidation crosslinking between PPS chains. These enhance the crystallisation process of semi-crystalline polymers by acting as the nucleating agent first but negatively affect the mechanical properties at higher temperatures because of the detrimental effects of the polymer inter-chain bonding. The maximum flexural strength of printed CF/PPS reached 164.65 MPa when processing at an extrusion temperature of 280°C, a printing temperature of 320°C, and an annealing temperature of 130°C for 6 h. By adjusting the thermal treatment conditions, the degree of the crystallinity and the mechanical properties of the printed CF/PPS composites can be designed, controlled and tailored.
ChatGPT: Forensic, legal, and ethical issues
Authors: Guleria Ankita , Krishan Kewal , Sharma Vishal , Kanchan Tanuj
Published: August 2023

Artificial intelligence (AI) refers to a group of technologies that enable people to perform a variety of activities, including observing, comprehending, analysing and translating data, among other things. Nowadays, practically every school of thought is interested in AI. One such innovation, a chatbot by the name of ChatGPT (Chat Generative Pre-Trained Transformer), launched by OpenAI recently, has taken the internet by storm. It had one million users within 1 week of its launch. The present communication explores the practicability and versatility of the ChatGPT in forensic examinations and scenarios, and also addresses the ethical and legal issues surrounding its usage. The observations suggest that the said technology, in its current form, has limited relevance in the realm of forensic science and the law. Only human critical thinking, expertise, and practical experience can provide the information and competencies needed in the realms of forensics, research, clinical and legal practices. Thus, the ChatGPT should be used with utmost caution in the disciplines of medicine, forensic science and the law, irrespective of its many positive attributes.
Research on AGV path tracking method based on global vision and reinforcement learning
Authors: Zhu Qixuan , Zheng Zhaolun , Wang Chao , Lu Yujun
Published: August 2023

As the key to the movement of automated guided vehicle (AGV), the design of control algorithm directly affects whether AGV can follow the preset path. Aiming at the difficulty of AGV control, an AGV path tracking control method based on global vision and reinforcement learning is proposed. Firstly, the global view is obtained by the visual sensor, and the position information of obstacles and AGV is obtained by the target detection algorithm. Secondly, the path planning algorithm is used to obtain the driving path information which is used to establish a virtual environment. Thirdly, the position and pose of the physical AGV are introduced into the virtual environment by the visual sensor, and the virtual AGV is reset. Finally, the image obtained by virtual vehicle camera is input into the reinforcement learning model and the output action is sent to the physical AGV for execution. In the experimental part, this method can not only plan the driving path in different environments but also well control AGV to drive along the specified path, which proves that this method has strong robustness and feasibility.
Operationalising social protection: Reflections from urban India
Authors: Bhan Gautam
Published: August 2023

A global pandemic has brought renewed attention to an old question: what do we owe each other? Calls to engage in thinking about a ‘new social contract’ have emerged rooted both in an intimate memory of crisis as well as in the possibilities rooted in relief work, mutual aid and stimulus packages. Scholars have sought to learn, for example, what relief measures could teach us about social protection in a ‘post-pandemic’ world, even while cautioning that socio-economic inequalities were only revealed rather than caused by the pandemic. Drawing on a set of empirical cases collectively produced by researchers (including this author) at the Indian Institute for Human Settlements, Bangalore, this article turns to a specific part of any social contract: the design and operation of social protection systems. Within this, it argues that operational modes of delivering social protection need specific attention within scholarly debates, especially in their complexities within the spatial and economic informality that marks cities of the global south. Put simply: how we deliver both existing and new entitlements is as important as deciding what entitlements urban residents should be entitled to. I offer four main operational concerns that mark the delivery of social protection to informal workers in urban India: (a) residence as an operational barrier; (b) workplaces as sites of delivery; (c) working with worker organisations as delivery infrastructures; and (d) building systems of recognition and registration of informal workers.
Sector connectors, specialists and scrappers: How cities use civic capital to compete in high-technology markets
Authors: Creutzberg Tijs , Ornston Darius , Wolfe David A
Published: August 2023

This article uses three cities in the same Canadian province (Ontario): Toronto, Ottawa and Waterloo, to examine how regions compete in high-technology markets. We find that regions use civic capital to leverage new, technological windows of opportunity, but they do so in very different ways. Tracing Toronto’s evolution from a marketing hub for foreign multinationals into a centre for entrepreneurship, we illustrate how weak ties and cross-sectoral buzz created a ‘super connector’, scaling high-technology firms in a wide variety of areas. In Ottawa, task-specific cooperation in R&D, education and specialised infrastructure enabled the region to overcome the disadvantages of its small size as a ‘specialist’ in a single, capital-intensive niche, telecommunications equipment. Finally, entrepreneurs in Waterloo eschewed task-specific cooperation for peer-to-peer mentoring. By diffusing generic knowledge about how to circumvent the liabilities of smallness, mentoring networks enabled this ‘scrapper’ city to support smaller start-ups in a broad range of niches.
Community-Based Treatment for Individuals Convicted of Sexual Offenses Using the Integrated Risk Assessment and Treatment System Model Versus Standard Correctional Programming
Authors: Abracen Jeffrey , Picheca Janice , Looman Jan , Stirpe Tania , Harkins Leigh
Published: August 2023

The present investigation examined a group of 90 clients receiving treatment for issues related to sexual offending in The Central District (Ontario) Sex Offender Treatment Program operated by Correctional Service Canada (CSC). Treatment was provided in line with the Integrated Risk Assessment and Treatment System (IRATS) Model developed by the authors. A group of 55 individuals who had not received sexual offense–specific treatment but who received standard correctional programming offered by paraprofessionals were used as a basis of comparison. Risk assessment data were available for all clients included in the analyses. Results indicated that there were no differences between groups on the RRASOR (an actuarial instrument designed to assess risk of sexual offense recidivism) with reference to sexual offender recidivism risk. With reference to sexual offense recidivism, only one of the treated clients recidivated sexually over 8.17 years of follow-up versus four of the 55 comparison group who were followed for a significantly shorter period of time (i.e., 6.9 years).
Private Bank Public Values and Priorities Under the Community Reinvestment Act
Authors: Kennedy Alexis R.
Published: August 2023

The Community Reinvestment Act (CRA) requires banks to grant low-income communities access to credit. Federal agencies monitor CRA activity and rate banks on compliance. As an economic development tool, the CRA supports private investment of public outcomes. This paper uses qualitative content analysis to examine bank and nonprofit comments regarding proposed CRA rule changes and bank shareholder reports through the lens of the realized publicness framework, to explore how banks express public values. This study finds that banks espouse public values, but that the context of those values is not aligned with community nonprofit values.
Two-stage multirate state feedback control designs for systems with slow and fast eigenvalue modes
Authors: Munje Ravindra , Patre Balasaheb
Published: August 2023

Design of feedback control, for a system with slow and fast eigenvalue modes, using single sampling rate results in either information loss (for a larger sampling period) or increased computations (for a smaller sampling period). This paper contributes to designing multirate state feedback controllers for such systems. In this, it is shown that the feedback control for a linear time-invariant system, having slow and fast eigenvalue modes, can be successfully designed by multirate sampling of states in two stages. Multirate sampling refers to sampling slow- and fast-varying states at different rates, that is sampling slow states at a lower rate than the fast states. Here, two approaches for multirate sampling of states are presented, depending on the sampling sequence. In the first approach, fast subsystem states are sampled initially, and then, slow subsystem states are sampled, whereas in the second approach, slow subsystem states are sampled before sampling the fast subsystem states. As far as the two-stage design is concerned, the first stage of the design of feedback control is initiated just after sampling the first subsystem. Then, the left subsystem is sampled, and the second stage of the design of feedback control is accomplished. It is proved that the feedback controls derived with the multirate sampling of states stabilize the full-order system in both approaches. The design and implementation aspects of both approaches are compared. Finally, the applicability of the proposed control is demonstrated by simulating two examples. Simulations are also compared with other methods proposed in the literature.
Quantifying the effects of different hydrocarbon charging periods on reservoir quality: A case study of the Upper Wuerhe Formation, Junggar Basin, NW China
Authors: Huang Linjun , Wang Zecheng , Pan Shuxin , Wu Haiguang , Xu Duonian , Jiang Shuai , Kang Xun
Published: August 2023

Mineral dissolution and precipitation is an important factor affecting pore genesis and hydrocarbon accumulation in sedimentary basins. Differential diagenetic processes at different hydrocarbon charging periods generally cause disparate effects on reservoir quality, which is important for reservoir evaluation and prediction. Focusing on this question, petrologic work, quantitative analysis on reservoir quality including porosity, permeability, and micro-scale X-ray computer tomography were conducted in conglomeratic reservoirs of the late Permian Upper Wuerhe Formation (P3 w) in the Shawan Sag, Junggar Basin, northwestern China. The results show that tuff and volcanic debris are enriched in the formation. Laumontites generally occur as cements in the reservoirs due to the alteration of volcanic materials and small amounts of early-stage calcite precipitated during eodiagenesis. Partial laumontite and calcite cements, as well as some debris and feldspar, are differentially dissolved due to differential hydrocarbon charging. During the continuous compaction of the reservoir, first-stage hydrocarbon charging occurred in the middle Jurassic when primary porosity almost disappeared. Hydrocarbon charging inhibited the precipitation of laumontite and calcite, promoting their dissolution. Second-stage hydrocarbon charging in the early Cretaceous further caused more extensive dissolution of laumontite and calcite, forming more than 70% secondary porosity. Authigenic quartz, kaolinite, and late-stage calcite are precipitated as the associated minerals of laumontite dissolution. This study presents the significance of reservoir reconstruction after hydrocarbon charging and suggests prospective hydrocarbon accumulations in deeply buried clastic reservoirs when hydrocarbon supply is sufficient from source rocks.
Investigating Cortisol in a STEM Classroom: The Association Between Cortisol and Academic Performance
Authors: Park Hyun Joon , Turetsky Kate M. , Dahl Julia L. , Pasek Michael H. , Germano Adriana L. , Harper Jackson O. , Purdie-Greenaway Valerie , Cohen Geoffrey L. , Cook Jonathan E.
Published: August 2023

Science, technology, engineering, and mathematics (STEM) education can be stressful, but uncertainty exists about (a) whether stressful academic settings elevate cortisol, particularly among students from underrepresented racial/ethnic groups, and (b) whether cortisol responses are associated with academic performance. In four classes around the first exam in a gateway college STEM course, we investigated participants’ ( N = 271) cortisol levels as a function of race/ethnicity and tested whether cortisol responses predicted students’ performance. Regardless of race/ethnicity, students’ cortisol, on average, declined from the beginning to the end of each class and across the four classes. Among underrepresented minority (URM) students, higher cortisol responses predicted better performance and a lower likelihood of dropping the course. Among non-URM students, there were no such associations. For URM students, lower cortisol responses may have indicated disengagement, whereas higher cortisol responses may have indicated striving. The implication of cortisol responses can depend on how members of a group experience an environment.
Meta-Analysis of Tablet-Mediated Interventions to Teach Mathematics for Individuals With Autism Spectrum Disorder and/or Intellectual Disability
Authors: Liu Di , Mao Yiwen , Cai Weiwei , Lei Qingli , Kang Rui , Zeng Yingying
Published: August 2023

Tablet-mediated interventions have shown promise in improving the mathematical skills of individuals with autism spectrum disorder (ASD) and/or intellectual disability (ID). This meta-analysis aims to provide a quantitative synthesis of single-case experimental studies of using tablet-mediated interventions to teach mathematics to individuals with ASD and/or ID. Twenty-seven published studies between 2012 and 2022 were included. The Tau-U effect size index was used to gauge the overall effect size of tablet-mediated interventions. The obtained effect size (Tau-U = 0.98, 95% CI 0.92–1.00) indicated large improvements in mathematics performance after using tablet-mediated interventions. The analysis of potential moderating variables, including participant characteristics, intervention components, and target mathematical skills found no statistically significant moderators. Implications for researchers and practitioners who use tablet-mediated interventions to teach mathematics to individuals with ASD and/or ID are also discussed.
Social media actually used by people with visual impairment: A scoping review
Authors: Gkatzola Katerina , Papadopoulos Konstantinos
Published: August 2023

Social media use is an integral part of people’s daily routine nowadays. Obviously, individuals with visual impairment are not excluded and use social media as well, even though they still face accessibility issues. The purpose of this review was to provide an overview of the existing literature on social media used by individuals with visual impairment and of the ways social media have been conceptualized throughout it. A literature search took place in the databases EBSCOhost, ERIC, Scopus and ResearchGate as well as the search engine Google Scholar. A total of 13 studies, published from 2011 to 2022 met our criteria and were included in this scoping review. According to our results, Facebook is the most used social media website by individuals with visual impairment as it was referenced in almost every single one of the studies reviewed and was recognized as the most used by individuals with visual impairment in the majority of them. Twitter is the second most popular social media website among individuals with visual impairment, followed by YouTube, WhatsApp, LinkedIn, Instagram, and Skype. Consequently, the statement that Facebook is the most popular social media website based on the number of its users is also confirmed with regard to users with visual impairment. However, the fact that an instant messaging service, such as WhatsApp, is recognized among researchers as a social medium when various social media definitions in the existing literature exclude this type of services showcases the confusion prevailing among researchers in this field. Thus, the literature would greatly benefit if researchers proposed a more thorough and robust definition for the widely, often inaccurately, used term social media.
The low hemoglobin levels were associated with mortality in post-cardiotomy patients undergoing venoarterial extracorporeal membrane oxygenation
Authors: Shao Juanjuan , Shao Chengcheng , Wang Yan , Fu Hongfu , Li Jin , Hao Xing , Du Zhongtao , Li Chenglong , Wang Liangshan
Published: August 2023

Background

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is used as a rescue strategy for patients with refractory post-cardiotomy cardiogenic shock (PCS). These patients often have varying degrees of reduced hemoglobin levels, and there are few detailed investigations about the impact of hemoglobin level on their mortality. The objective of this study was to evaluate whether hemoglobin levels at day 1 from VA-ECMO initiation were associated with in-hospital mortality.

Methods

We performed a retrospective analysis of adult VA-ECMO patients over approximately a 2-year period. We divided patients into survival and death groups based on their clinical outcomes and compared the differences in parameters between the two groups. Multivariate logistic regression analyses were performed to estimate whether hemoglobin level was related to the mortality.

Results

One hundred and sixteen patients were included in final analysis. There were 52 patients in the survival group and 64 in the death group. The patients were younger in the survival group than the death group (58 vs 63, p = .023). The median (IQR) hemoglobin level at day 1 was 80 (73−89) × g/L, and the median (IQR) RelΔ hemoglobin was 41% (32–48%). Survival patients had a higher hemoglobin level at day 1 and a lower RelΔ hemoglobin than the death patients (91 vs 76 g/L, p < .001; 35% vs 45%, p < .001). The multivariable logistic regression analyses showed that the low hemoglobin levels at day 1 were independently associated with in-hospital mortality (OR 0.808; 95% CI, 0.747–0.874; p < .001). The AUROC for hemoglobin level was 0.89 (95% CI, 0.83–0.95) which was better than that of RelΔ hemoglobin (0.77, 95% CI, 0.68–0.86).

Conclusions

In patients receiving VA-ECMO for PCS, the low hemoglobin levels at day 1 were independently associated with in-hospital mortality.
Probing into Driver Speeding Patterns and Their Influence on Child Occupancy in Urban Areas
Authors: Das Subasish , Kong Xiaoqiang , Wei Zihang , Xiao Xiao , Mills David , Hossain Ahmed
Published: August 2023

Many studies have investigated how child occupants lead to distraction-associated crashes. However, not many studies have focused on how the presence of child passengers influences drivers’ speeding behavior. This study examines how the presence of child passengers can affect driving behavior considering sociodemographic characteristics such as driver’s age, gender, ethnicity, employment, and driving aggressiveness. The current study used resourceful, open-source data based on urban areas in Texas to identify the key patterns of speeding behavior and associated safety surrogates in the presence or absence of child occupants. A unique data analysis procedure known as Taxicab Correspondence Analysis (TCA) was used to analyze the data. The results indicate that speeding patterns are affected by child occupancy during a trip. The results find that regardless of the presence of child passengers, female and unemployed drivers are more likely to drive defensively and male and employed drivers are more likely to drive aggressively. The findings also indicate that drivers from the young age group (20–29 years old) are strongly associated with speeding trips without child occupancy. However, young parent drivers from this age group are strongly associated with non-speeding trips and driving defensively. The study also finds that the impact of child occupancy on driving behaviors varies across different ethnicities. These findings will benefit transportation agencies in identifying aggressive driver groups and developing countermeasures to mitigate speeding behaviors, especially for trips with child occupancy.
The SCN-HPA-Periphery Circadian Timing System: Mathematical Modeling of Clock Synchronization and the Effects of Photoperiod on Jetlag Adaptation
Authors: Li Yannuo , Androulakis Ioannis P.
Published: August 2023

Synchronizing the circadian timing system (CTS) to external light/dark cycles is crucial for homeostasis maintenance and environmental adaptation. The CTS is organized hierarchically, with the central pacemaker located in the suprachiasmatic nuclei (SCN) generating coherent oscillations that are entrained to light/dark cycles. These oscillations regulate the release of glucocorticoids by the hypothalamus-pituitary-adrenal (HPA) axis, which acts as a systemic entrainer of peripheral clocks throughout the body. The SCN adjusts its network plasticity in response to variations in photoperiod, leading to changes in the rhythmic release of glucocorticoids and ultimately impacting peripheral clocks. However, the effects of photoperiod-induced variations of glucocorticoids on the synchronization of peripheral clocks are not fully understood, and the interaction between jetlag adaption and photoperiod changes is unclear. This study presents a semi-mechanistic mathematical model to investigate how the CTS responds to changes in photoperiod. Specifically, the study focuses on the entrainment properties of a system composed of the SCN, HPA axis, and peripheral clocks. The results show that high-amplitude glucocorticoid rhythms lead to a more coherent phase distribution in the periphery. In addition, our study investigates the effect of photoperiod exposure on jetlag recovery time and phase shift, proposing different interventional strategies for eastward and westward jetlag. The findings suggest that decreasing photic exposure before jetlag during eastward traveling and after jetlag during westward traveling can accelerate jetlag readaptation. The study provides insights into the mechanisms of CTS organization and potential recovery strategies for transitions between time zones and lighting zones.
Experimental study on structural adhesive properties of aluminum plate and carbon fiber-reinforced polymer heterogeneous materials
Authors: Bo Liu , Jian Yang , Yongxin Tang , Jinsheng Zhang , Qin Yang , Cong Gao , Gang Feng
Published: August 2023

Structural adhesive bonding between aluminum and carbon fiber-reinforced polymer (CFRP) is an important part of the vehicle's lightweight design and must ensure high strength and durability during the life of the structural member. The paper presents a precise assessment scheme to accurately and reliably infer the performance of adhesive joints through a short-term experimental test method that focuses on intrinsic and extrinsic factors affecting bond strength. The experimental results show that the surface of CFRP is polished, which is beneficial to improve the bonding quality, and the damage type transitioned from adhesion damage to substrate or cohesion damage. Aluminum alloy electrophoresis and non-electrophoresis have no significant effect on the bonding performance. Secondly, the design of the bonding nodes should be considered to bring them into a state of shear stress and be able to withstand greater loads. Meanwhile, the moderate thickness of the adhesive layer and increased bonding area serve to enhance bond reliability. In addition, various environments can cause various physical and chemical changes within structural adhesives, which can reduce the cohesive strength and durability of adhesives. This experiment is designed to select process parameters and adhesive applications for structural adhesives, which are crucial in predicting and evaluating the performance of newly developed structural adhesives and bonded joints.