bluuebunny/crossref_metadata_2025 huggingface dataset:
From personification abuse to normal expression: emotional treatment for language disorders in schools
Authors: Ke Yuguo , Zhou Xiaozhen
Published: May 2024

Introduction

The escalating prevalence of personification abuse in language disorders among students poses a substantial challenge for autistic students in the domain of language disorders. While prior research has mainly focused on the cognitive hurdles faced by autistic students, ongoing debates persist about the onset, severity, and roots of these challenges in their classroom behavior, with limited exploration of how preconceived notions impact personification abuse. This study aims to delve into emotional treatments for language disorders, specifically targeting personification abuse, to facilitate the shift from distorted perceptions to normative expression. It seeks to pinpoint the primary emotional interventions linked to instances of personification abuse and scrutinize the emotional factors influencing therapeutic approaches for language disorders.

Methods

The research encompassed a cohort of 110 autistic students, aged 2 to 5 years, diagnosed with language disorders, all clinically determined to have autism by developmental pediatricians at a prestigious medical facility. Among these children, 95 were attending specialized schools, while 15 were situated in community settings.

Results

The outcomes disclosed that children across all developmental phases displayed instances of personification abuse in language disorders, showcasing noteworthy enhancements in personification abuse following emotional treatment. Significantly, the discernible disparity in personification abuse performance and emotional treatment can be linked to the simultaneous cognitive advancement of autistic students across four grade levels, with variations noted based on normative expressions.

Discussion

These findings underscore the insufficiency of solely relying on intrinsic trends to comprehend personification abuse within an emotional treatment context. The study accentuates the potential pitfalls associated with emotional treatment for language disorders and stresses the imperative need for additional research and psychiatric intervention strategies.
Resilience of mental health services amidst Ebola disease outbreaks in Africa
Authors: Wirsiy Frankline Sevidzem , Tahmo Nancy B. , Tatah Lambed , Brett-Major David M.
Published: May 2024

Introduction

Health systems including mental health (MH) systems are resilient if they protect human life and produce better health outcomes for all during disease outbreaks or epidemics like Ebola disease and their aftermaths. We explored the resilience of MH services amidst Ebola disease outbreaks in Africa; specifically, to (i) describe the pre-, during-, and post-Ebola disease outbreak MH systems in African countries that have experienced Ebola disease outbreaks, (ii) determine the prevalence of three high burden MH disorders and how those prevalences interact with Ebola disease outbreaks, and, (iii) describe the resilience of MH systems in the context of these outbreaks.

Methods

This was a scoping review employing an adapted PRISMA statement. We conducted a five-step Boolean strategy with both free text and Medical Subject Headings (MeSH) to search 9 electronic databases and also searched WHO MINDbank and MH Atlas.

Results

The literature search yielded 1,230 publications. Twenty-five studies were included involving 13,449 participants. By 2023, 13 African nations had encountered a total of 35 Ebola outbreak events. None of these countries had a metric recorded in MH Atlas to assess the inclusion of MH in emergency plans. The three highest-burden outbreak-associated MH disorders under the MH and Psychosocial Support (MHPSS) framework were depression, post-traumatic stress disorder (PTSD), and anxiety with prevalence ranges of 1.4–7%, 2–90%, and 1.3–88%, respectively. Furthermore, our analysis revealed a concerning lack of resilience within the MH systems, as evidenced by the absence of pre-existing metrics to gauge MH preparedness in emergency plans. Additionally, none of the studies evaluated the resilience of MH services for individuals with pre-existing needs or examined potential post-outbreak degradation in core MH services.

Discussion

Our findings revealed an insufficiency of resilience, with no evaluation of services for individuals with pre-existing needs or post-outbreak degradation in core MH services. Strengthening MH resilience guided by evidence-based frameworks must be a priority to mitigate the long-term impacts of epidemics on mental well-being.
Enriching the lives of children with acquired brain injury and their caregivers: experiences from peer mentorship sports camps
Authors: Wedege Pia , Mæland Silje , Divanoglou Anestis , Abrahamsen Frank Eirik
Published: May 2024

Peer-based community interventions have shown promise in improving health management and fostering coping skills and psychosocial functioning among individuals with a disability. Active Rehabilitation camps are examples of peer-based community interventions that provide structured, time-limited peer mentorship in conjunction with sports and leisure activities. These camps hold potential benefits for individuals with acquired neurological injury. However, the specific impact of Active Rehabilitation camps on children or individuals with acquired brain injury remains unexplored. In this longitudinal, qualitative study, we explored children with an acquired brain injury and their caregivers' experiences with an Active Rehabilitation camp in Norway through observations and interviews with nine children and ten caregivers. Using an abductive thematic analysis, we identified an overarching theme: Active Rehabilitation peer mentorship camps enrich the lives of children with acquired brain injury and their caregivers. The theme contains three sub-themes: (1) Interacting with peers made me wiser, (2) Nudging from peer mentors made me feel better, and (3) A sense of companionship through meeting peers. Peer mentorship, sports and leisure activities, and the safe camp atmosphere benefitted children with acquired brain injury and their caregivers. The children gained knowledge, motivation, and self-worth, and their caregivers had greater impetus to prioritize their children's independence. Meeting peers and peer mentors led to friendships and sustained social connections. The Self-Determination Theory was of assistance in explaining the informants' experiences. Active Rehabilitation camps provide children with acquired brain injury and their caregivers with an opportunity to develop better coping skills, improve psychological functioning, and build more robust social networks.
Max Well-Being: a modular platform for the gamification of rehabilitation
Authors: Kennard Maxwell , Hassan Modar , Shimizu Yukiyo , Suzuki Kenji
Published: May 2024

This study proposes a modular platform to improve the adoption of gamification in conventional physical rehabilitation programs. The effectiveness of rehabilitation is correlated to a patient’s adherence to the program. This adherence can be diminished due to factors such as motivation, feedback, and isolation. Gamification is a means of adding game-like elements to a traditionally non-game activity. This has been shown to be effective in providing a more engaging experience and improving adherence. The platform is made of three main parts; a central hardware hub, various wired and wireless sensors, and a software program with a stream-lined user interface. The software interface and hardware peripherals were all designed to be simple to use by either a medical specialist or an end-user patient without the need for technical training. A usability study was performed using a group of university students and a group of medical specialists. Using the System Usability Scale, the system received an average score of 69.25 ± 20.14 and 72.5 ± 17.16 by the students and medical specialists, respectively. We also present a framework that attempts to assist in selecting commercial games that are viable for physical rehabilitation.
Effects of a 6-week on-court training program on the International Tennis Number (ITN) and a range of physical fitness characteristics in young tennis players
Authors: Morais Jorge E. , Kilit Bulent , Arslan Ersan , Soylu Yusuf , Neiva Henrique P.
Published: May 2024

The study aimed to (i) verify the effects of an on-court training program on the International Tennis Number (ITN) of young tennis players, as well as on a set of change of direction, linear sprint, and maximal oxygen uptake (VO2max) variables, and (ii) identify the main predictors of ITN. The sample consisted of 20 young male tennis players (mean age, 13.62 ± 0.23 years). Players underwent a 6-week on-court training program. The ITN and a number of change of direction variables (T-drill and repeated sprint ability), linear sprint (5 m, 10 m, and 20 m distances), and VO2max were measured. All variables improved significantly between the pre- and posttest (p < 0.001). The ITN (7.98 ± 6.06%, d = 0.82) and VO2max (6.77 ± 1.21%, d = 1.53) showed the greatest relative improvement with moderate to large effect sizes. The hierarchical linear model retained the time (estimate = 18.90, p < 0.001) and the T-drill (estimate = −64.77, p < 0.001) as significant predictors of the ITN. This indicates that the ITN improved significantly over the 6-week training program and that the T-drill test was the best and most significant predictor. Coaches and researchers are encouraged to monitor the ITN along with other physical fitness and technical variables. They can also use the T-drill test to understand the ITN of their players.
Towards an understanding of maltreatment in football
Authors: Newman James A. , Rumbold James L.
Published: May 2024

Introduction

This study explored the understanding of maltreatment from the perspective of various personnel working in roles related to safeguarding and welfare in English professional and semi-professional football.

Method

Through a social constructivist position, the present study was able to explore multiple understandings and perceptions of maltreatment in football. Individual semi-structured interviews (MDuration = 68.00 minutes, SD = 9.05 minutes) were conducted with 19 participants working across league structures ranging from the English Premier League (EPL) to the English Northern Premier League Division One, as well as individuals working with some of the principal organizations in English professional football.

Results

Through reflexive thematic analysis, three general dimensions were highlighted: “current understanding of maltreatment in football,” “constituents of maltreatment,” and “signs and symptoms of maltreatment.” Findings from those working in a safeguarding capacity mirror the research literature around understanding the components of maltreatment but also demonstrate how wrongdoing is nuanced by the football context, in that certain forms of maltreatment are driven by the unique nature of this environment.

Discussion

From an applied perspective, the findings also outline how to distinguish both the more overt and covert signs and symptoms of maltreatment, whilst also highlighting the impact of maltreatment on individuals' mental health and their sense of self. Overall, the findings provide a platform for practitioners and researchers to consider in the design of safeguarding and welfare provision by highlighting the need to raise knowledge and awareness of maltreatment whilst intervening to challenge the prevailing workplace culture within professional football.
Metagenomic insights into isolable bacterial communities and antimicrobial resistance in airborne dust from pig farms
Authors: Hein Si Thu , Prathan Rangsiya , Srisanga Songsak , Muenhor Dudsadee , Wongsurawat Thidathip , Jenjaroenpun Piroon , Tummaruk Padet , Chuanchuen Rungtip
Published: May 2024

This study aims to investigate bacterial communities and antimicrobial resistance (AMR) in airborne dust from pig farms. Airborne dust, pig feces and feed were collected from nine pig farms in Thailand. Airborne dust samples were collected from upwind and downwind (25 meters from pig house), and inside (in the middle of the pig house) of the selected pig house. Pig feces and feed samples were individually collected from the pen floor and feed trough from the same pig house where airborne dust was collected. A direct total bacteria count on each sampling plate was conducted and averaged. The ESKAPE pathogens together with Escherichia coli, Salmonella, and Streptococcus were examined. A total of 163 bacterial isolates were collected and tested for MICs. Pooled bacteria from the inside airborne dust samples were analyzed using Metagenomic Sequencing. The highest bacterial concentration (1.9–11.2 × 103 CFU/m3) was found inside pig houses. Staphylococcus (n = 37) and Enterococcus (n = 36) were most frequent bacterial species. Salmonella (n = 3) were exclusively isolated from feed and feces. Target bacteria showed a variety of resistance phenotypes, and the same bacterial species with the same resistance phenotype were found in airborne dust, feed and fecal from each farm. Metagenomic Sequencing analysis revealed 1,652 bacterial species across all pig farms, of which the predominant bacterial phylum was Bacillota. One hundred fifty-nine AMR genes of 12 different antibiotic classes were identified, with aminoglycoside resistance genes (24%) being the most prevalent. A total of 251 different plasmids were discovered, and the same plasmid was detected in multiple farms. In conclusion, the phenotypic and metagenomic results demonstrated that airborne dust from pig farms contained a diverse array of bacterial species and genes encoding resistance to a range of clinically important antimicrobial agents, indicating the significant role in the spread of AMR bacterial pathogens with potential hazards to human health. Policy measurements to address AMR in airborne dust from livestock farms are mandatory.
A Comprehensive Exploration of Unsupervised Classification in Spike Sorting: A Case Study on Macaque Monkey and Human Pancreatic Signals
Authors: Iñiguez-Lomeli Francisco Javier , Franco-Ortiz Edgar Eliseo , Gonzalez-Acosta Ana Maria Silvia , Garcia-Granada Andres Amador , Rostro-Gonzalez Horacio
Published: May 2024

Spike sorting, an indispensable process in the analysis of neural biosignals, aims to segregate individual action potentials from mixed recordings. This study delves into a comprehensive investigation of diverse unsupervised classification algorithms, some of which, to the best of our knowledge, have not previously been used for spike sorting. The methods encompass Principal Component Analysis (PCA), K-means, Self-Organizing Maps (SOMs), and hierarchical clustering. The research draws insights from both macaque monkey and human pancreatic signals, providing a holistic evaluation across species. Our research has focused on the utilization of the aforementioned methods for the sorting of 327 detected spikes within an in vivo signal of a macaque monkey, as well as 386 detected spikes within an in vitro signal of a human pancreas. This classification process was carried out by extracting statistical features from these spikes. We initiated our analysis with K-means, employing both unmodified and normalized versions of the features. To enhance the performance of this algorithm, we also employed Principal Component Analysis (PCA) to reduce the dimensionality of the data, thereby leading to more distinct groupings as identified by the K-means algorithm. Furthermore, two additional techniques, namely hierarchical clustering and Self-Organizing Maps, have also undergone exploration and have demonstrated favorable outcomes for both signal types. Across all scenarios, a consistent observation emerged: the identification of six distinctive groups of spikes, each characterized by distinct shapes, within both signal sets. In this regard, we meticulously present and thoroughly analyze the experimental outcomes yielded by each of the employed algorithms. This comprehensive presentation and discussion encapsulate the nuances, patterns, and insights uncovered by these algorithms across our data. By delving into the specifics of these results, we aim to provide a nuanced understanding of the efficacy and performance of each algorithm in the context of spike sorting.
Multidisciplinary Perspectives of Challenges in Infective Endocarditis Complicated by Septic Embolic-Induced Acute Myocardial Infarction
Authors: Stamate Elena , Ciobotaru Oana Roxana , Arbune Manuela , Piraianu Alin Ionut , Duca Oana Monica , Fulga Ana , Fulga Iuliu , Balta Alexia Anastasia Stefania , Dumitrascu Adrian George , Ciobotaru Octavian Catalin
Published: May 2024

Background: Infective endocarditis (IE) management is challenging, usually requiring multidisciplinary collaboration from cardiologists, infectious disease specialists, interventional cardiologists, and cardiovascular surgeons, as more than half of the cases will require surgical procedures. Therefore, it is essential for all healthcare providers involved in managing IE to understand the disease’s characteristics, potential complications, and treatment options. While systemic embolization is one of the most frequent complications of IE, the coronary localization of emboli causing acute myocardial infarction (AMI) is less common, with an incidence ranging from 1% to 10% of cases, but it has a much higher rate of morbidity and mortality. There are no guidelines for this type of AMI management in IE. Methods: This narrative review summarizes the current knowledge regarding septic coronary embolization in patients with IE. Additionally, this paper highlights the diagnosis and management challenges in such cases, particularly due to the lack of protocols or consensus in the field. Results: Data extracted from case reports indicate that septic coronary embolization often occurs within the first two weeks of the disease. The aortic valve is most commonly involved with vegetation, and the occluded vessel is frequently the left anterior descending artery. Broad-spectrum antibiotic therapy followed by targeted antibiotic therapy for infection control is essential, and surgical treatment offers promising results through surgical embolectomy, concomitant with valve replacement or aspiration thrombectomy, with or without subsequent stent insertion. Thrombolytics are to be avoided due to the increased risk of bleeding. Conclusions: All these aspects should constitute future lines of research, allowing the integration of all current knowledge from multidisciplinary team studies on larger patient cohorts and, subsequently, creating a consensus for assessing the risk and guiding the management of this potentially fatal complication.
Correction: Furugaito et al. Antimicrobial Susceptibility to 27 Drugs and the Molecular Mechanisms of Macrolide, Tetracycline, and Quinolone Resistance in Gemella sp. Antibiotics 2023, 12, 1538
Authors: Furugaito Michiko , Arai Yuko , Uzawa Yutaka , Kamisako Toshinori , Ogura Kohei , Okamoto Shigefumi , Kikuchi Ken
Published: May 2024

The authors wish to make the following corrections to this paper [...]
Nitric Oxide Binding Geometry in Heme-Proteins: Relevance for Signal Transduction
Authors: De Simone Giovanna , di Masi Alessandra , Sbardella Diego , Ascenzi Paolo , Coletta Massimiliano
Published: May 2024

Nitric oxide (NO) synthesis, signaling, and scavenging is associated to relevant physiological and pathological events. In all tissues and organs, NO levels and related functions are regulated at different levels, with heme proteins playing pivotal roles. Here, we focus on the structural changes related to the different binding modes of NO to heme-Fe(II), as well as the modulatory effects of this diatomic messenger on heme-protein functions. Specifically, the ability of heme proteins to bind NO at either the distal or proximal side of the heme and the transient interchanging of the binding site is reported. This sheds light on the regulation of O2 supply to tissues with high metabolic activity, such as the retina, where a precise regulation of blood flow is necessary to meet the demand of nutrients.
Pitavastatin Calcium Confers Fungicidal Properties to Fluconazole by Inhibiting Ubiquinone Biosynthesis and Generating Reactive Oxygen Species
Authors: Li Wanqian , Feng Yanru , Feng Zhe , Wang Li , Whiteway Malcolm , Lu Hui , Jiang Yuanying
Published: May 2024

Fluconazole (FLC) is extensively employed for the prophylaxis and treatment of invasive fungal infections (IFIs). However, the fungistatic nature of FLC renders pathogenic fungi capable of developing tolerance towards it. Consequently, converting FLC into a fungicidal agent using adjuvants assumes significance to circumvent FLC resistance and the perpetuation of fungal infections. This drug repurposing study has successfully identified pitavastatin calcium (PIT) as a promising adjuvant for enhancing the fungicidal activity of FLC from a comprehensive library of 2372 FDA-approved drugs. PIT could render FLC fungicidal even at concentrations as low as 1 μM. The median lethal dose (LD50) of PIT was determined to be 103.6 mg/kg. We have discovered that PIT achieves its synergistic effect by inhibiting the activity of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase, thereby impeding ubiquinone biosynthesis, inducing reactive oxygen species (ROS) generation, triggering apoptosis, and disrupting Golgi function. We employed a Candida albicans strain that demonstrated a notable tolerance to FLC to infect mice and found that PIT effectively augmented the antifungal efficacy of FLC against IFIs. This study is an illustrative example of how FDA-approved drugs can effectively eliminate fungal tolerance to FLC.
Impacts of Land-Use Change from Primary Forest to Farmland on the Storage of Soil Organic Carbon
Authors: Xiao Changgui , Gong Yaoqi , Pei Xiaolei , Chen Hanyue , Li Sheng , Lu Chengwen , Chen Li , Zheng Xuhui , Zheng Jiaxin , Yan Xie
Published: May 2024

Land-use change (LUC) is a significant contributor to the increase in atmospheric CO2 concentrations, with previous studies demonstrating its profound impact on soil organic carbon (SOC). The conversion of primary forests to farmland has been recognized as the most significant type of LUC inducing CO2 release from the soil. Therefore, it is critical to understand the impacts of forest LUC on SOC storage, with a particular focus on primary forest to farmland conversion. In this study, we conducted a meta-analysis of 411 observations from 41 published works and found that SOC storage decreased significantly following the conversion of primary forests to farmland. Factors such as soil depth and climate zone influenced the degree of SOC storage loss, with SOC loss being less severe in deeper soil following a conversion from primary forests to farmland. Moreover, the loss of SOC storage was more severe in temperate regions compared to tropical regions. The input and output of surface SOC, changes in soil structure, and increases in atmospheric CO2 concentrations were significant reasons for the loss of SOC following primary forest to farmland LUC. However, improving tillage methods and implementing sustainable agricultural management strategies can help reduce SOC loss. These findings highlight the importance of sustainable land-use practices in mitigating the negative impacts of forest LUC on SOC storage and the global carbon cycle.
Accurate Identification of Partial Discharge Signals in Cable Terminations of High-Speed Electric Multiple Unit Using Wavelet Transform and Deep Belief Network
Authors: Liu Zhengwei , Li Jiali , Zhang Tingyu , Chen Shuai , Xin Dongli , Liu Kai , Chen Kui , Liu Yong-Chao , Sun Chuanming , Gao Guoqiang , Wu Guangning
Published: May 2024

Cable termination serves as a crucial carrier for high-speed train power transmission and a weak part of the cable insulation system. Partial discharge detection plays a significant role in evaluating insulation status. However, field testing signals are often contaminated by external corona interference, which affects detection accuracy. This paper proposes a classification model based on wavelet transform (WT) and deep belief network (DBN) to accurately and rapidly identify corona discharge in the partial discharge signals of vehicle-mounted cable terminals. The method utilizes wavelet transform for noise reduction, employing the sigmoid activation function and analyzing the impact of WT on DBN classification performance. Research indicates that this method can achieve an accuracy of over 89% even with limited training samples. Finally, the reliability of the proposed classification model is verified using measured mixed signals.
Arrangement Order Effects of Neuromuscular Training on the Physical Fitness of Youth Soccer Players
Authors: Lee Kwang-Jin , Seon Se-Young , An Keun-Ok
Published: May 2024

Knowledge is limited regarding how neuromuscular training, conducted before and after soccer training, affects the fitness levels of youth soccer players. In this study, we aimed to analyze the effects of an eight-week neuromuscular training (NMT) program implemented before or after a soccer session on physical fitness in youth soccer players. Thirty-two youth soccer players were categorized into two groups—namely, NMT before soccer-specific training (NBS; n = 15) and NMT after soccer-specific training (NAS; n = 17). NMT comprised integrated resistance, dynamic stability, core, and plyometric training three times weekly and was conducted for 8 weeks. Before and after the exercise intervention, the counter-movement jump (CMJ) and 10 and 20 m sprint were analyzed, and the results of the T-agility test, Illinois change of direction test (ICDT), and Y-balance test were assessed for all participants. In terms of the interaction between the effects of the time of observation and group, both groups showed improvement in the results of the 10 m sprint and T-agility and Y-balance tests. Regarding the difference in the time of observation, the NBS group showed positive improvements in the results of the CMJ, 10 and 20 m sprints, and T-agility test after the exercise intervention, and the NAS group showed positive improvements in the results of the CMJ, 10 m sprint, T-agility test, and ICDT after the exercise intervention. These findings suggest that neuromuscular training has the potential to improve the 10 m sprint ability and T-agility test results of youth soccer players, regardless of the training sequence.
TYCOS: A Specialized Dataset for Typical Components of Satellites
Authors: Bian He , Cao Jianzhong , Zhang Gaopeng , Zhang Zhe , Li Cheng , Dong Junpeng
Published: May 2024

The successful detection of key components within satellites is a crucial prerequisite for executing on-orbit capture missions. Due to the inherent data-driven functionality, deep learning-based component detection algorithms rely heavily on the scale and quality of the dataset for their accuracy and robustness. Nevertheless, existing satellite image datasets exhibit several deficiencies, such as the lack of satellite motion states, extreme illuminations, or occlusion of critical components, which severely hinder the performance of detection algorithms. In this work, we bridge the gap via the release of a novel dataset tailored for the detection of key components of satellites. Unlike the conventional datasets composed of synthetic images, the proposed Typical Components of Satellites (TYCOS) dataset comprises authentic photos captured in a simulated space environment. It encompasses three types of satellite, three types of key components, three types of illumination, and three types of motion state. Meanwhile, scenarios with occlusion in front of the satellite are also taken into consideration. On the basis of TYCOS, several state-of-the-art detection methods are employed in rigorous experiments followed by a comprehensive analysis, which further enhances the development of space scene perception and satellite safety.
The Use of Virtual Reflectance Transformation Imaging (V-RTI) in the Field of Cultural Heritage: Approaching the Materiality of an Ancient Egyptian Rock-Cut Chapel
Authors: Di Iorio Federico , Es Sebar Leila , Croci Sara , Taverni Federico , Auenmüller Johannes , Pozzi Federica , Grassini Sabrina
Published: May 2024

Recent progress in the realm of imaging technologies has swiftly disseminated fresh methodologies for representing objects, broadening the horizons for scholars such as art historians, archaeologists, conservators, and conservation scientists. Reflectance Transformation Imaging (RTI) and three-dimensional (3D) modeling via Structure from Motion (SfM) have rapidly gained popularity and are being employed by a wide range of users, expanding the possibilities for understanding objects of material cultural heritage from different perspectives. This paper explores the outcomes achieved through the application of these techniques to gain deeper insights into the surface of a bas-relief within a confined space. This methodology enhanced our understanding of the original sandstone surfaces of the bas-relief by integrating RTI and 3D visualization, thereby acquiring a novel investigative tool with enhanced illumination possibilities. A data fusion approach is proposed using photogrammetry to produce a Virtual RTI (V-RTI). In the case study reported in this paper, focusing on one inner wall of the chapel of Ellesiya at the Museo Egizio of Turin, V-RTI was employed to obtain useful surface information in a context where conventional RTI would have been impossible to achieve. Finally, the study compares the different techniques through direct qualitative and quantitative analysis, highlighting possible future developments from both instrumental and methodological points of view.
Visualising Static Features and Classifying Android Malware Using a Convolutional Neural Network Approach
Authors: Kiraz Ömer , Doğru İbrahim Alper
Published: May 2024

Android phones are widely recognised as the most popular mobile phone operating system. Additionally, tasks like browsing the internet, taking pictures, making calls, and sending messages may be completed with ease in daily life because of the functionality that Android phones offer. The number of situations in which users are harmed by unauthorised access to data emerging from these processes is growing daily. Because the Android operating system is open source and generated applications are not thoroughly reviewed before being released onto the market, this scenario has been the primary focus of hackers. Therefore, technologies to distinguish between malware and benign Android applications are required. CNN-based techniques are proven to produce important and successful outcomes when applied to Android malware detection on images. The CICMalDroid 2020 dataset, which is currently utilised in the literature, was used for this purpose. The features of the apps in the dataset were obtained using the AndroPyTool tool, and faster analysis files of 17,089 Android applications were obtained using the parallel execution technique. Permissions, intents, receivers, and services were used as static analysis features in this article. After these features were obtained, as data preprocessing, the ones with a grand total equal to 1 for each feature in the whole dataset were excluded in order to exclude the features that were specially created by the applications themselves. For each of the features specified for each application, a comma-separated text was obtained according to the usage status of the application. The BERT method was used to digitise the pertinent texts in order to create a unique embedding vector for every feature. Following the digitisation of the vectors, picture files were produced based on the length of each feature. To create a single image file, these image files were combined side by side. Finally, these image files were classified with CNNs. Experimental results were obtained by applying CNNs to the dataset used in the study. As a result of the experiments, a CNN with two outputs provided the highest performance with an accuracy of 91%, an F1-score of 89%, a Recall of 90%, and a Precision of 91%.
Disturbance Observer-Based Anti-Shock Controller for Laser Beam Steering Systems
Authors: Kim Jung-Gon
Published: May 2024

This paper presents an approach for improving the robustness of tip-tilt controllers for fast-steering mirror (FSM)-based laser beam steering (LBS) systems in the presence of dynamic disturbances such as external shocks. To this end, we propose the addition of a disturbance observer (DOB)-based anti-shock controller in parallel to the original linear servo control loop to improve its control performance in the presence of external shocks. To increase the tip-tilt control performance against external shocks, the DOB-based control method, which is an improved control method for eliminating nonperiodic disturbances, is implemented in the original tip-tilt control system. The results indicate that the control error of the DOB-based anti-shock controller decreased, resulting in an efficient improvement in its disturbance-rejection performance.
MoCoformer: Quantifying Temporal Irregularities in Solar Wind for Long-Term Sequence Prediction
Authors: Wang Zheng , Zhang Jiaodi , Sun Meijun
Published: May 2024

Long-term solar wind sequence forecasting is essential for understanding the influence of the solar wind on celestial settings, predicting variations in solar wind parameters, and identifying patterns of solar activity. The intrinsic erratic temporal features of solar wind datasets present significant challenges to the development of solar wind factor estimate techniques. In response to these challenges, we present MoCoformer, a novel model based on the Transformer model in deep learning that integrates the Multi-Mode Decomp Block and Mode Independence Attention. The Multi-Mode Decomp Block employs an optimized version of variational mode decomposition technology to flexibly handle irregular features by adaptively decomposing and modeling the impact of sudden events on the temporal dynamics, enhancing its ability to manage non-stationary and irregular features effectively. Meanwhile, the Mode Independence Attention module computes attention independently for each mode, capturing the correlation between sequences and mitigating the negative impact of irregular features on time series prediction. The experimental results on solar wind datasets demonstrate that MoCoformer significantly outperforms current state-of-the-art methods in time series forecasting, showcasing superior predictive performance. This underscores the resilience of MoCoformer in handling the intricate, irregular temporal characteristics of solar wind data, rendering it a valuable instrument for enhancing the understanding and forecasting of solar wind dynamics.
Modeling and Resolving Uncertainty in DIKWP Model
Authors: Wu Kunguang , Duan Yucong
Published: May 2024

The paper examines the various uncertainties encountered in high-frequency trading (HFT) environments and delves into the multiple challenges faced by HFT firms in navigating the Dodd–Frank Wall Street Reform and Consumer Protection Act (referred to as the “Dodd–Frank Act”), particularly during the initial stages of its enactment. These challenges include the ambiguity surrounding the definition of HFT, the lack of clarity regarding regulatory requirements and boundaries, inconsistencies in enforcement resulting from deviations in understanding the content, and the absence of detailed descriptions of the Act’s provisions. These hurdles significantly impact not only the daily operations of HFT firms but also pose higher demands on their long-term strategic planning and risk management. Drawing upon the Data, Information, Knowledge, Wisdom, and Purpose (DIKWP) model, this study employs an innovative analytical framework. Through the comprehensive application of Cognitive Space, Concept Space, and Semantic Space, it provides a systematic methodology for identifying and analyzing the aforementioned issues. This approach not only aids firms in better comprehending and adhering to complex regulatory requirements but also enables them to explore new business opportunities and competitive advantages while ensuring compliance.
Shear Lag Effect of Ultra-Wide Box Girder under Influence of Shear Deformation
Authors: Li Yanfeng , Xie Jiyuan , Wang Fengchi , Li Yuanhui
Published: May 2024

The objective of this study was to determine the reasonable flexural functions of ultra-wide box girders, reveal the mechanism of the shear lag effect, and improve the analysis theory of ultra-wide box girders. Considering a single-box three-chamber thin-walled box girder as an example, starting from an uneven transfer of shear flow, the flexural displacement function of the curved box girder under the influence of shear deformation of each plate was derived according to the flexural theory of a thin-walled box girder, balance equation of a thin-walled microelement plate, and theory of plane stress. The energy variational method was used to analyze the flexural displacement function, providing a theoretical solution for the shear lag effect of the curved box girder. A displacement correction of the cantilever plate displacement function was performed by comparing the calculation results for the shear lag coefficients. The results indicated that under the shear deformation of each plate, the flexural displacement functions of the wing and web plates of the box girder no longer satisfy the assumption of plane section. The flexural displacement function is a quadratic function of the transverse wing plate, and the web height is the sum of the first- and third-order functions. The theoretical calculation results agree sufficiently well with the experimental results, proving that the flexural displacement function of the box girder under the influence of the shear deformation of each plate is reliable.
Method for Evaluating Degradation of Battery Capacity Based on Partial Charging Segments for Multi-Type Batteries
Authors: Sun Yujuan , Tian Hao , Hu Fangfang , Du Jiuyu
Published: May 2024

Accurately estimating the capacity degradation of lithium-ion batteries (LIBs) is crucial for evaluating the status of battery health. However, existing data-driven battery state estimation methods suffer from fixed input structures, high dependence on data quality, and limitations in scenarios where only early charge–discharge cycle data are available. To address these challenges, we propose a capacity degradation estimation method that utilizes shorter charging segments for multiple battery types. A learning-based model called GateCNN-BiLSTM is developed. To improve the accuracy of the basic model in small-sample scenarios, we integrate a single-source domain feature transfer learning framework based on maximum mean difference (MMD) and a multi-source domain framework using the meta-learning MAML algorithm. We validate the proposed algorithm using various LIB cell and battery pack datasets. Comparing the results with other models, we find that the GateCNN-BiLSTM algorithm achieves the lowest root mean square error (RMSE) and mean absolute error (MAE) for cell charging capacity estimation, and can accurately estimate battery capacity degradation based on actual charging data from electric vehicles. Moreover, the proposed method exhibits low dependence on the size of the dataset, improving the accuracy of capacity degradation estimation for multi-type batteries with limited data.
Fast Li+ Transfer Scaffold Enables Stable High-Rate All-Solid-State Li Metal Batteries
Authors: Song Libo , He Yuanyue , Li Zhendong , Peng Zhe , Yao Xiayin
Published: May 2024

Sluggish transfer kinetics caused by solid–solid contact at the lithium (Li)/solid-state electrolyte (SE) interface is an inherent drawback of all-solid-state Li metal batteries (ASSLMBs) that not only limits the cell power density but also induces uneven Li deposition as well as high levels of interfacial stress that deteriorates the internal structure and cycling stability of ASSLMBs. Herein, a fast Li+ transfer scaffold is proposed to overcome the sluggish kinetics at the Li/SE interface in ASSLMBs using an α-MnO2-decorated carbon paper (CP) structure (α-MnO2@CP). At an atomic scale, the tunnel structure of α-MnO2 exhibits a great ability to facilitate Li+ adsorption and transportation across the inter-structure of α-MnO2@CP, leading to a high critical current density of 3.95 mA cm−2 at the Li/SE interface. Meanwhile, uniform Li deposition can be guided along the skeletons of α-MnO2@CP with minimized volume expansion, significantly improving the structural stability of the Li/SE interface. Based on these advantages, the ASSLMBs using α-MnO2@CP protected the Li anode and can stably cycle up to very high charge/discharge rates of 10C/10C, paving the way for developing high-power ASSLMBs.
Hierarchical Porosity and Surface Oxygenation of Carbon-Based Cathodes Enhances Discharge Capacity and Decreases Discharge Overpotential of Potassium–Oxygen Batteries
Authors: Singh Shikha , Küpper Jannis , Abouserie Ahed , Dalfollo Gianluca , Noyong Michael , Simon Ulrich
Published: May 2024

Potassium–oxygen batteries (KOBs) are a promising energy storage technology with high theoretical energy density, low overpotential and a long cycle life. The cathode microstructure plays a significant role in the electrochemical performance of KOB. In this article, hierarchical porosity was introduced to commercially available carbon paper cathodes by thermal pretreatment in air at different pretreatment times. This pretreatment modifies the properties, such as surface area, defects, oxygen functional groups, etc. The discharge performance was determined at three different current densities, i.e., 0.1 mA/cm2, 0.5 mA/cm2, and 1.0 mA/cm2. It has been found that an increase in specific surface area with the introduction of micropores and mesopores is beneficial for the improvement in the discharge capacity by enabling homogeneous discharge product, KO2 distribution and high degrees of pore filling over the volume of the cathode. A reduction in the discharge overpotentials was observed, which is attributed to the introduction of oxygenic functional groups and defects. Samples treated for the longest pretreatment time of 24 h showed the highest discharge capacity of 5 mAh/cm2 and lowest discharge overpotential of 0.03 V.
Inflammation as a Sex-Specific Mediator in the Relationship between Maternal and Offspring Obesity in C57Bl/6J Mice
Authors: Buckley Lauren A. , Kulhanek Debra R. , Bruder Adrienne , Gisslen Tate , Paulsen Megan E.
Published: May 2024

Maternal obesity is a well-established risk factor for offspring obesity development. The relationship between maternal and offspring obesity is mediated in part by developmental programming of offspring metabolic circuitry, including hypothalamic signaling. Dysregulated hypothalamic inflammation has also been linked to development of obesity. We utilized an established C57Bl/6J mouse model of high-fat, high-sugar diet induced maternal obesity to evaluate the effect of maternal obesity on systemic and hypothalamic TNF-α, IL-6, and IL-1β levels in neonatal and adult offspring. The offspring of dams with obesity demonstrated increased adiposity and decreased activity compared to control offspring. Maternal obesity was associated with decreased plasma TNF-α, IL-6 and IL-1β in adult female offspring and decreased plasma IL-6 in neonatal male offspring. Neonatal female offspring of obese dams had decreased TNF-α gene expression in the hypothalamus compared to control females, while neonatal and adult male offspring of obese dams had decreased IL-6 gene expression in the hypothalamus compared to control males. In summary, our results highlight important sex differences in the inflammatory phenotype of offspring exposed to maternal obesity. Sex-specific immunomodulatory mechanisms should be considered in future efforts to develop therapeutic interventions for obesity prevention and treatment.
Genome-Wide Identification of Specific Genetic Loci Common to Sheep and Goat
Authors: Liang Zuoxiang , Yue Xiaoyu , Liu Yangxiu , Ye Mengyan , Zhong Ling , Luan Yue , Wang Qin
Published: May 2024

Sheep and goat may become carriers of some zoonotic diseases. They are important livestock and experimental model animals for human beings. The fast and accurate identification of genetic materials originating from sheep and goat can prevent and inhibit the spread of some zoonotic diseases, monitor market product quality, and maintain the stability of animal husbandry and food industries. This study proposed a methodology for identifying sheep and goat common specific sites from a genome-wide perspective. A total of 150 specific sites were selected from three data sources, including the coding sequences of single copy genes from nine species (sheep, goat, cow, pig, dog, horse, human, mouse, and chicken), the dbSNPs for these species, and human 100-way alignment data. These 150 sites exhibited low intraspecific heterogeneity in the resequencing data of 1450 samples from five species (sheep, goat, cow, pig, and chicken) and high interspecific divergence in the human 100-way alignment data after quality control. The results were proven to be reliable at the data level. Using the process proposed in this study, specific sites of other species can be screened, and genome-level species identification can be performed using the screened sites.
HOMA-IR as a Predictor of PAI-1 Levels in Women with Severe Obesity
Authors: Martins Kattah Fabiana , Janjusevic Milijana , Figueiredo Nayra , Santos Oliveira Emilly , Carielo Lima Glaucia , Dâmaso Ana Raimunda , Oyama Lila Missae , Fluca Alessandra Lucia , de Melo Paulo Reis Eselin , Aderuza Horst Maria , Aleksova Aneta , Campos Corgosinho Flávia
Published: May 2024

Background: Obesity is a chronic inflammatory disorder that increases the risk of cardiovascular diseases (CVDs). Given the high CVD mortality rate among individuals with obesity, early screening should be considered. Plasminogen activator inhibitor (PAI-1), a cytokine that links obesity and CVDs, represents a promising biomarker. However, PAI-1 is not part of the clinical routine due to its high cost. Therefore, it is necessary to find good predictors that would allow an indirect assessment of PAI-1. Methods: This study enrolled 47 women with severe obesity (SO). The obtained anthropometric measurements included weight, height, neck (NC), waist (WC), and hip circumference (HC). Blood samples were collected to analyse glucose and lipid profiles, C-reactive protein, liver markers, adiponectin, and PAI-1 (determined by ELISA immunoassay). Homeostasis model assessment-adiponectin (HOMA-AD), homeostasis model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), triglyceride–glucose index (TyG), and atherogenic index of plasma (AIP) were calculated. The women were grouped according to PAI-1 levels. The data were analysed using IBM SPSS Statistics, version 21. The significance level for the analysis was set at 5%. Results: Women with SO who have higher levels of PAI-1 have lower values of high-density lipoprotein cholesterol (HDL) (p = 0.037) and QUICKI (0.020) and higher values of HOMA-AD (0.046) and HOMA-IR (0.037). HOMA-IR was demonstrated to be a good predictor of PAI-1 in this sample (B = 0.2791; p = 0.017). Conclusions: HOMA-IR could be used as a predictor of PAI-1 levels, pointing out the relevance of assessing glycaemic parameters for the prevention of CVDs in women with SO.