bluuebunny/crossref_metadata_2025 huggingface dataset:
Expanding NAEP and TIMSS Analysis to Include Additional Variables or a New Scoring Model Using the R Package Dire
Authors: Bailey Paul Dean , Webb Blue
Published: August 2023

The R packages Dire and EdSurvey allow analysts to make a conditioning model with new variables and then draw new plausible values. This is important because results for a variable not in the conditioning model are biased. For regression-type analyses, users can also use direct estimation to estimate parameters without generating new plausible values. Dire is distinct from other available software in R in that it requires fixed item parameters and simplifies calculation of high-dimensional integrals necessary to calculate composite or subscales. When used with EdSurvey, it is very easy to use published item parameters to estimate a new conditioning model. We show the theory behind the methods in Dire and a coding example where we perform an analysis that includes simple process data variables. Because the process data is not used in the conditioning model, the estimator is biased if a new conditioning model is not added with Dire.
The Transnational Experience of a Chinese Buddhist Master in the Asian Buddhist Network
Authors: Zhang Xing
Published: August 2023

Wuqian (1922–2010) was one of the most important modern Buddhist masters in the modern history of Sino-Indian Buddhist relations. In his early years, he studied all the major schools of the Buddhist tradition, focusing on Yogācāra philosophy, probably due to Xuanzang’s influence and in alignment with contemporary Buddhist trends. Furthermore, he became one of the few masters from the Central Plains who received systematic training in Tibetan Buddhist tantric rituals. He went to India in the middle of the 20th century. He dedicated his life to the revival of Buddhist thought in India, especially promoting Chinese Buddhism in Calcutta by establishing Buddhist institutions, managing Buddhist sites, organizing Buddhist activities, and building the Xuanzang Temple. In his later years, he devoted himself to facilitating mutual Buddhist exchanges and monastic visits between Buddhist organizations in mainland China, Taiwan, and India. In 1998, he presented two Buddhist relics to the Daci’en Temple in Xi’an. At the beginning of the 21st century, he established the Institute of Buddhist Studies at Xuanzang Temple in Calcutta. He organized the translation of many important Buddhist treatises, again reflecting his intention of following the spirit of Xuanzang to contribute to Chinese Buddhism. His transnational journey manifested that there was an active Asian Buddhist network during the Cold War era, despite various difficulties.
A Comprehensive Multi-Metric Index for Health Assessment of the Poyang Lake Wetland
Authors: Yang Wenjing , Zhong Jie , Xia Ying , Hu Qiwu , Fang Chaoyang , Cong Mingyang , Yao Bo , You Qinghui
Published: August 2023

The Poyang Lake wetland is home to many unique and threatened species. However, it has been severely degraded in recent decades due to the joint effects of human influence and climate change. Here we establish a wetland health index (WHI) for Poyang Lake, which considers five types of attributes (biological, water quality, sediment, land use and remote sensing, and socio-economic attributes) of the wetland to evaluate wetland conditions. Forty-nine variables across five categories were assembled as candidate metrics for the WHI through field surveys conducted in 2019 at 30 sample sites. Principal component analyses were performed to identify the most important variables in each of the five categories as the primary metrics of each index category (e.g., biological index). Eighteen variables were finally selected from the five categories to construct the WHI. The WHI scores varied from 0.34 to 0.80 at the 30 sample sites, with a mean of 0.55. The Poyang Lake wetland is generally in fair condition according to our WHI scores. Sample sites where connected rivers flow into the lake were assessed to be in a poor condition, highlighting the importance of reducing pollution input from rivers for wetland conservation. Scores of individual indices of the five categories were not highly correlated (0.29 ≤ pairwise Spearman’s r ≤ 0.69), suggesting that information provided by each index is different and might be complementary. The composite WHI as well as the individual category indices can provide comprehensive information on wetland conditions that would facilitate the development of more targeted and effective strategies for wetland management.
Artificial Intelligence Forecasting of Marine Heatwaves in the South China Sea Using a Combined U-Net and ConvLSTM System
Authors: Sun Wenjin , Zhou Shuyi , Yang Jingsong , Gao Xiaoqian , Ji Jinlin , Dong Changming
Published: August 2023

Marine heatwaves (MHWs) are extreme events characterized by abnormally high sea surface temperatures, and they have significant impacts on marine ecosystems and human society. The rapid and accurate forecasting of MHWs is crucial for preventing and responding to the impacts they can lead to. However, the research on relevant forecasting methods is limited, and a dedicated forecasting system specifically tailored for the South China Sea (SCS) region has yet to be reported. This study proposes a novel forecasting system utilizing U-Net and ConvLSTM models to predict MHWs in the SCS. Specifically, the U-Net model is used to forecast the intensity of MHWs, while the ConvLSTM model is employed to predict the probability of their occurrence. The indication of an MHW relies on both the intensity forecasted by the U-Net model exceeding threshold T and the occurrence probability predicted by the ConvLSTM model surpassing threshold P. Incorporating sensitivity analysis, optimal thresholds for T are determined as 0.9 °C, 0.8 °C, 1.0 °C, and 1.0 °C for 1-, 3-, 5-, and 7-day forecast lead times, respectively. Similarly, optimal thresholds for P are identified as 0.29, 0.30, 0.20, and 0.28. Employing these thresholds yields the highest forecast accuracy rates of 0.92, 0.89, 0.88, and 0.87 for the corresponding forecast lead times. This innovative approach gives better predictions of MHWs in the SCS, providing invaluable reference information for marine management authorities to make well-informed decisions and issue timely MHW warnings.
PbS QD-Coated Si Micro-Hole Array/Graphene vdW Schottky Near-Infrared Photodiode for PPG Heart Rate Measurement
Authors: Xu Mingyuan , Cui Yinghao , Zhang Tao , Lu Mengxue , Yu Yongqiang
Published: August 2023

Near-infrared (NIR) photodetectors (PDs) have attracted much attention for use in noninvasive medical diagnosis and treatments. In particular, self-filtered NIR PDs are in high demand for a wide range of biomedical applications due to their ability for wavelength discrimination. In this work, we designed and then fabricated a Si micro-hole array/Graphene (Si MHA/Gr) van der Waals (vdW) Schottky NIR photodiode using a PbS quantum dot (QD) coating. The device exhibited a unique self-filtered NIR response with a responsivity of 0.7 A/W at −1 V and a response speed of 61 μs, which is higher than that seen without PbS QD coating and even in most previous Si/Gr Schottky photodiodes. The light trapping of the Si MHA and the PbS QD coating could be attributed to the high responsivity of the vdW photodiode. Furthermore, the presented NIR photodiode could also be integrated in photoplethysmography (PPG) for real-time heart rate (HR) monitoring. The extracted HR was in good accord with the values measured with the patient monitor—determined by analyzing the Fourier transform of the stable and reliable fingertip PPG waveform—suggesting its potential for practical applications.
Malicious Traffic Identification with Self-Supervised Contrastive Learning
Authors: Yang Jin , Jiang Xinyun , Liang Gang , Li Siyu , Ma Zicheng
Published: August 2023

As the demand for Internet access increases, malicious traffic on the Internet has soared also. In view of the fact that the existing malicious-traffic-identification methods suffer from low accuracy, this paper proposes a malicious-traffic-identification method based on contrastive learning. The proposed method is able to overcome the shortcomings of traditional methods that rely on labeled samples and is able to learn data feature representations carrying semantic information from unlabeled data, thus improving the model accuracy. In this paper, a new malicious traffic feature extraction model based on a Transformer is proposed. Employing a self-attention mechanism, the proposed feature extraction model can extract the bytes features of malicious traffic by performing calculations on the malicious traffic, thereby realizing the efficient identification of malicious traffic. In addition, a bidirectional GLSTM is introduced to extract the timing features of malicious traffic. The experimental results show that the proposed method is superior to the latest published methods in terms of accuracy and F1 score.
Optimal Reactive Power Dispatch in ADNs using DRL and the Impact of Its Various Settings and Environmental Changes
Authors: Zamzam Tassneem , Shaban Khaled , Massoud Ahmed
Published: August 2023

Modern active distribution networks (ADNs) witness increasing complexities that require efforts in control practices, including optimal reactive power dispatch (ORPD). Deep reinforcement learning (DRL) is proposed to manage the network’s reactive power by coordinating different resources, including distributed energy resources, to enhance performance. However, there is a lack of studies examining DRL elements’ performance sensitivity. To this end, in this paper we examine the impact of various DRL reward representations and hyperparameters on the agent’s learning performance when solving the ORPD problem for ADNs. We assess the agent’s performance regarding accuracy and training time metrics, as well as critic estimate measures. Furthermore, different environmental changes are examined to study the DRL model’s scalability by including other resources. Results show that compared to other representations, the complementary reward function exhibits improved performance in terms of power loss minimization and convergence time by 10–15% and 14–18%, respectively. Also, adequate agent performance is observed to be neighboring the best-suited value of each hyperparameter for the studied problem. In addition, scalability analysis depicts that increasing the number of possible action combinations in the action space by approximately nine times results in 1.7 times increase in the training time.
Research on Yaw Stability Control Strategy for Distributed Drive Electric Trucks
Authors: Gao Feng , Zhao Fengkui , Zhang Yong
Published: August 2023

With the advancement of vehicle electrification and intelligence, distributed drive electric trucks have emerged as the preferred choice for heavy-duty electric trucks. However, the control of yaw stability remains a significant issue. To tackle this concern, this study introduces a layered control strategy for yaw moment. Specifically, the upper layer utilizes a yaw moment controller based on linear quadratic regulator (LQR) to compute the additional yaw moment required. Additionally, in order to enhance the performance of the yaw moment controller, the weight matrix in LQR is optimized using a hybrid Genetic Algorithm and Particle Swarm Optimization algorithm (GA-PSO). The lower layer consists of a torque distribution layer, which establishes an objective function for minimizing tire utilization rate. Quadratic Programming algorithm is then employed to compute the optimal torque distribution value, thereby improving the vehicle’s stability. Subsequently, the stability control effects of the vehicle are simulated and compared on the Matlab/Simulink Trucksim joint simulation platform using four control strategies: the proposed control strategy, SMC, LQR, and without yaw moment control. These simulations are conducted under two working conditions: serpentine and double lane change. The results demonstrate that the proposed approach reduces the average yaw rate by 14.4%, 19.6%, and 42.15% while optimizing the average sideslip angle by 25.9%, 24.8%, and 52.3% in comparison to the other three control strategies. Consequently, the proposed control strategy significantly enhances the driving stability of the vehicle. Furthermore, the optimized allocation method reduces the average tire utilization rate by 42.6% in contrast to the average allocation method, thereby improving the stability control margin of the vehicle. These findings successfully validate the efficiency of the yaw stability control strategy presented in this article.
Block-Active ADMM to Minimize NMF with Bregman Divergences
Authors: Li Xinyao , Tyagi Akhilesh
Published: August 2023

Over the last ten years, there has been a significant interest in employing nonnegative matrix factorization (NMF) to reduce dimensionality to enable a more efficient clustering analysis in machine learning. This technique has been applied in various image processing applications within the fields of computer vision and sensor-based systems. Many algorithms exist to solve the NMF problem. Among these algorithms, the alternating direction method of multipliers (ADMM) and its variants are one of the most popular methods used in practice. In this paper, we propose a block-active ADMM method to minimize the NMF problem with general Bregman divergences. The subproblems in the ADMM are solved iteratively by a block-coordinate-descent-type (BCD-type) method. In particular, each block is chosen directly based on the stationary condition. As a result, we are able to use much fewer auxiliary variables and the proposed algorithm converges faster than the previously proposed algorithms. From the theoretical point of view, the proposed algorithm is proved to converge to a stationary point sublinearly. We also conduct a series of numerical experiments to demonstrate the superiority of the proposed algorithm.
A Comprehensive Overview of IoT-Based Federated Learning: Focusing on Client Selection Methods
Authors: Khajehali Naghmeh , Yan Jun , Chow Yang-Wai , Fahmideh Mahdi
Published: August 2023

The integration of the Internet of Things (IoT) with machine learning (ML) is revolutionizing how services and applications impact our daily lives. In traditional ML methods, data are collected and processed centrally. However, modern IoT networks face challenges in implementing this approach due to their vast amount of data and privacy concerns. To overcome these issues, federated learning (FL) has emerged as a solution. FL allows ML methods to achieve collaborative training by transferring model parameters instead of client data. One of the significant challenges of federated learning is that IoT devices as clients usually have different computation and communication capacities in a dynamic environment. At the same time, their network availability is unstable, and their data quality varies. To achieve high-quality federated learning and handle these challenges, designing the proper client selection process and methods are essential, which involves selecting suitable clients from the candidates. This study presents a comprehensive systematic literature review (SLR) that focuses on the challenges of client selection (CS) in the context of federated learning (FL). The objective of this SLR is to facilitate future research and development of CS methods in FL. Additionally, a detailed and in-depth overview of the CS process is provided, encompassing its abstract implementation and essential characteristics. This comprehensive presentation enables the application of CS in diverse domains. Furthermore, various CS methods are thoroughly categorized and explained based on their key characteristics and their ability to address specific challenges. This categorization offers valuable insights into the current state of the literature while also providing a roadmap for prospective investigations in this area of research.
Molecularly Imprinted Polymer-Based Nanoporous Carbon Nanocomposite for Effective Adsorption of Hg(II) Ions from Aqueous Suspensions
Authors: Abubakar Lawal , Yusof Nor Azah , Abdullah Abdul Halim , Mohammad Faruq , Wahid Mohd Hanif , Ismail Suhainie , Abdul Rahim Zulaiha , Al-Lohedan Hamad A. , Soleiman Ahmed A.
Published: August 2023

Due to the release of hazardous heavy metals from various industries, water pollution has become one of the biggest challenges for environmental scientists today. Mercury Hg(II) is regarded as one of the most toxic heavy metals due to its ability to cause cancer and other health issues. In this study, a tailor-made modern eco-friendly molecularly imprinted polymer (MIP)/nanoporous carbon (NC) nanocomposite was synthesized and examined for the uptake of Hg(II) using an aqueous solution. The fabrication of the MIP/NC nanocomposite occurred via bulk polymerization involving the complexation of the template, followed by polymerization and, finally, template removal. Thus, the formed nanocomposite underwent characterizations that included morphological, thermal degradation, functional, and surface area analyses. The MIP/NC nanocomposite, with a high specific surface area of 884.9 m2/g, was evaluated for its efficacy towards the adsorptive elimination of Hg(II) against the pH solution changes, the dosage of adsorbent, initial concentration, and interaction time. The analysis showed that a maximum Hg(II) adsorption effectiveness of 116 mg/g was attained at pH 4, while the Freundlich model fitted the equilibrium sorption result and was aligned with pseudo-second-order kinetics. Likewise, thermodynamic parameters like enthalpy, entropy, and Gibbs free energy indicated that the adsorption was consistent with spontaneous, favorable, and endothermic reactions. Furthermore, the adsorption efficiency of MIP/NC was also evaluated against a real sample of condensate from the oil and gas industry, showing an 87.4% recovery of Hg(II). Finally, the synthesized MIP/NC showed promise as a selective adsorbent of Hg(II) in polluted environments, suggesting that a variety of combined absorbents of different precursors is recommended to evaluate heavy metal and pharmaceutical removals.
Proposal of a Mathematical Modelling Activity to Facilitate Students’ Learning of Ordinary Differential Equation Concepts
Authors: Lozada Esperanza , Guerrero-Ortiz Carolina , Coronel Aníbal , Medina Rigoberto
Published: August 2023

We present results that come from analysing students’ processes of solving tasks designed particularly for the learning of differential equations in a situational context. A teaching sequence was implemented during a semester-long course that comprised several tasks to cover the content of the course. Following a qualitative analysis, we show how a contextualised task can favour the construction of meanings associated with differential equations and how the interpretation of the terms present in those equations is developed. We also highlight some difficulties that may arise in students’ interpretations when the task involves meanings from other disciplines.
Research on Energy Management of Hydrogen Fuel Cell Bus Based on Deep Reinforcement Learning Considering Velocity Control
Authors: Shen Yang , Zhou Jiaming , Zhang Jinming , Yi Fengyan , Wang Guofeng , Pan Chaofeng , Guo Wei , Shu Xing
Published: August 2023

In the vehicle-to-everything scenario, the fuel cell bus can accurately obtain the surrounding traffic information, and quickly optimize the energy management problem while controlling its own safe and efficient driving. This paper proposes an energy management strategy (EMS) that considers speed control based on deep reinforcement learning (DRL) in complex traffic scenarios. Using SUMO simulation software (Version 1.15.0), a two-lane urban expressway is designed as a traffic scenario, and a hydrogen fuel cell bus speed control and energy management system is designed through the soft actor–critic (SAC) algorithm to effectively reduce the equivalent hydrogen consumption and fuel cell output power fluctuation while ensuring the safe, efficient and smooth driving of the vehicle. Compared with the SUMO–IDM car-following model, the average speed of vehicles is kept the same, and the average acceleration and acceleration change value decrease by 10.22% and 11.57% respectively. Compared with deep deterministic policy gradient (DDPG), the average speed is increased by 1.18%, and the average acceleration and acceleration change value are decreased by 4.82% and 5.31% respectively. In terms of energy management, the hydrogen consumption of SAC–OPT-based energy management strategy reaches 95.52% of that of the DP algorithm, and the fluctuation range is reduced by 32.65%. Compared with SAC strategy, the fluctuation amplitude is reduced by 15.29%, which effectively improves the durability of fuel cells.
Anti-Disturbance Integrated Control Method and Energy Consumption Analysis of Central Heating Systems Based on Resistance–Capacitance Reactance
Authors: Jin Lu , Shi Liguo , Li Dezhi , Liu Kaicheng , Zhong Ming , Pang Jingshuai
Published: August 2023

Under the dual carbon strategy, with the frequent occurrence of extreme weather and the further increase in uncertainty of multi-user behavior, it is urgent to improve the stability of the heating systems and reduce heating energy consumption. Aiming at the problem of fault-disturbance control of the multi-user heating network in an integrated energy system, this paper proposes a novel analysis method of resistance–capacitance reactance based on the circuit principle to construct a dynamic thermal-power-flow model of the whole link of the multi-user heating network and analyze the fault-disturbance propagation characteristics of the heating network by this model. It shows that the difference in disturbance characteristics of different users in a multi-user heating network mainly depends on the characteristics of the heating pipeline between the heat user and the heat source, which provides a necessary basis for formulating intelligent control strategies against fault disturbance. Finally, taking a typical daily outdoor temperature in Beijing in winter as an example, this paper compares two different heating strategies and the blocker installation methods of the multi-user heating network to obtain a better heating strategy under actual conditions. Considering the heating fault disturbance, this paper proposes a novel intelligent heating strategy whose heating temperature will decrease during the fault-disturbance time, with an energy saving of about 16.5% compared with the heating strategy under actual conditions during the same period.
Study on Uniaxial Mechanical Behavior and Damage Evolution Mechanism of Water-Immersed Mudstone
Authors: Song Yanqi , Zheng Junjie , Ma Hongfa , Shao Zhixin , Yang Jiangkun , Shen Fuxin , Liu Chuanpeng
Published: August 2023

The existence of mudstone weak interlayers has a significant impact on the stability of open-pit coal mine slopes. Under the combined influence of rainfall and groundwater, the mechanical properties of the mudstone of weak interlayers deteriorate, leading to a local loss of bearing capacity of the slope and further accelerating the overall instability of the slope. In order to investigate the changes of macroscopic and mesoscopic structures, mechanical failure behavior, and the damage evolution mechanism of water-immersed mudstone, non-destructive water immersion experiments and uniaxial compression experiments were conducted. The results indicate that the main causes of macroscopic structure failure of water-immersed mudstone are the initiation, propagation, and mutual penetration of micro cracks. The mesoscopic structure characteristics of water-immersed mudstone are primarily manifested by increased surface smoothness, increased occurrence of small-scale pores, the presence of a dense network of fissures on the surface, and fusion of mineral unit boundaries. With the increasing immersion time, the quality, relative water content, and peak strain increase, while the uniaxial mechanical parameters and energy parameters decrease. In addition, a statistically damaged constitutive model for mudstone considering the coupling damage of water immersion and low-stress loading was established, and the model is consistent with experimental results. Finally, the water-softening characteristics of mudstone are caused by the propensity of clay minerals to expand and disintegrate upon water contact, changes in pore structure, variations in mineral types and distributions, and the presence of pore water pressure. This study provides valuable insights into the water–rock deterioration mechanism of mudstone and the stability of slopes containing weak interlayers.
Integrating Mobile Technologies: Two Stage Study on Academic Performance and Social Presence
Authors: Ergün-Elverici Sibel
Published: August 2023

The ubiquity of mobile technologies has sparked interest in their potential impact. However, current research predominantly concentrates on adults, neglecting the younger demographic that is more profoundly immersed in mobile technologies. To bridge this gap, this study introduces a specialized instructional design, integrating the widely used application Duolingo into English classes, to explore the ramifications of mobile technologies on the academic performance and social presence of high school students in their initial years. Conducted within a private school where English is mandatory, the research adopts a mixed-method approach, with quantitative and qualitative facets. Data collection comprises a needs analysis, a standardized English test (KET), a social presence scale and follow-up interviews. Participants were selected using purposive sampling, 16 students each for the experimental and control groups. Semi-structured interviews were conducted with eight voluntary participants. Analysis techniques, including t-tests for the social presence scale, descriptive analysis for interviews, and grading for exam results were applied. Noteworthy distinctions in students’ academic performances were revealed through effect size measurements in writing (0.78), listening (1.01), and speaking (0.82), with a minor change in reading (−0.1). Additionally, a significant variation in social presence emerged (t = −9.194; p < 0.05). Qualitative themes emerged, highlighting Duolingo’s entertainment value, curriculum alignment, content diversity, accessibility, parental consent, and teacher guidance. Quantitative results demonstrated Duolingo’s positive impact on academic performance, while qualitative insights reflected students’ enthusiasm for its integration. Findings invite a critical examination of the role of such technologies, prompting inquiries into their potential advantages and challenges.
Business IT Alignment Impact on Corporate Sustainability
Authors: Zabukovšek Uroš , Tominc Polona , Bobek Samo
Published: August 2023

Business–IT alignment (BITA) has become crucial for effective organisational management in today’s interconnected global economy. This article investigates the relationship between BITA and corporate sustainability, exploring how businesses can leverage BITA for sustainable growth and development. The study employs a case research approach in a multinational manufacturing organisation, utilising a mixed methods research (MMR) design. In the quantitative part of the research, the PLS-SEM technique was used to examine the influence of six BITA factors on employees’ self-perceived action competence for sustainability (SPACS). This study confirmed that all six BITA factors strongly influence all three SPACS factors. In the qualitative part of the research, semi-structured interviews were used to measure the BITA maturity level of the organisation and the influence of BITA factors on corporate sustainability. Based on quantitative and qualitative research results, it can be confirmed that BITA strongly influences corporate sustainability. Results also confirm that there is no universal approach to BITA and its influence on corporate sustainability. Organisations must focus on all factors of BITA equally to achieve better levels of BITA and ensure its influence on corporate sustainability.
Expression of Cholera Toxin (CT) and the Toxin Co-Regulated Pilus (TCP) by Variants of ToxT in Vibrio cholerae Strains
Authors: Lee Donghyun , Choi Hunseok , Son Seonghyeon , Bae Jonghyun , Joo Jayun , Kim Dong Wook , Kim Eun Jin
Published: August 2023

The expression of the two major virulence genes of Vibrio cholerae—tcpA (the major subunit of the toxin co-regulated pilus) and ctxAB (cholera toxin)—is regulated by the ToxR regulon, which is triggered by environmental stimuli during infection within the human small intestine. Special culture methods are required to induce the expression of virulence genes in V. cholerae in the laboratory setting. In the present study, induction of the expression of virulence genes by two point mutations (65th and 139th amino acids) in toxT, which is produced by the ToxR regulon and activates the transcription of the virulence genes in V. cholerae, under laboratory culture conditions has been investigated. Each of the four toxT alleles assessed displayed different transcriptional activator functions in a given V. cholerae strain. Although the ToxR regulon has been known to not be expressed by El Tor biotype V. cholerae strains cultured under standard laboratory conditions, the variant toxT alleles that we assessed in this study enabled the expression virulence genes in El Tor biotype strains grown under simple culture conditions comprising shake culture in LB medium, suggesting that the regulation of virulence gene expression may be regulated more complexly than previously thought and may involve additional factors beyond the production of ToxT by the ToxR regulon.
Epidemiological Differences in Hajj-Acquired Airborne Infections in Pilgrims Arriving from Low and Middle-Income versus High-Income Countries: A Systematised Review
Authors: Mahdi Hashim A. , Alluhidan Mohammed , Almohammed Abdulrahman B. , Alfelali Mohammad , Shaban Ramon Z. , Booy Robert , Rashid Harunor
Published: August 2023

This systematised review aims to compare the epidemiological patterns of Hajj-acquired airborne infections among pilgrims from low and middle-income countries (LMIC) versus those from high-income countries (HIC). A PubMed search was carried out for all published articles before February 2023, using a combination of MeSH terms and text words. The Newcastle–Ottawa Scale (NOS) was used to assess data quality. From a total of 453 titles identified, 58 studies were included in the review (LMIC = 32, and HIC = 26). In the pooled sample, there were 27,799 pilgrims aged 2 days to 105 years (male: female = 1.3:1) from LMIC and 70,865 pilgrims aged 2 months to 95 years (male: female = 1:1) from HIC. Pilgrims from both HIC and LMIC had viral and bacterial infections, but pilgrims from HIC tended to have higher attack rates of viral infections than their LMIC counterparts. However, the attack rates of bacterial infections were variable: for instance, pilgrims from LMIC seemed to have higher rates of meningococcal infections (0.015–82% in LMIC vs. 0.002–40% in HIC) based on the study population, but not Mycobacterium tuberculosis (0.7–20.3% in LMIC vs. 38% in HIC). Targeted measures are needed to prevent the spread of airborne infections at Hajj.
An Attempt of a New Strategy in PRV Prevention: Co-Injection with Inactivated Enterococcus faecium and Inactivated Pseudorabies Virus Intravenously
Authors: Cui Yuan , Huang Libo , Li Jinlian , Wang Gang , Shi Youfei
Published: August 2023

Pseudorabies virus (PRV) is one of the causative agents of common infectious diseases in swine herds. Enterococcus faecium is a probiotic belonging to the group of lactic acid bacteria and has excellent immunomodulatory effects. Vaccine immunization is an important approach to prevent animal diseases in the modern farming industry, and good immunization outcomes can substantially reduce the damage caused by pathogens to animals, improve the quality of animals’ lives, and reduce economic losses. In the present study, we showed that inactivated E. faecium and inactivated PRV when co-injected intravenously significantly reduced the mortality of mice after inoculation with PRV. The inactivated E. faecium + inactivated PRV intravenous injection group induced more production of Th cells and Tc cells. Additionally, the inactivated E. faecium + inactivated PRV intravenous injection group showed higher concentrations of cytokines (IFN-γ and IL-10) and induced higher antibody production. Thus, the co-injection of inactivated E. faecium and inactivated PRV could remarkably prevent and control the lethality of PRV infection in mice, which is a critical finding for vaccination and clinical development.
Effectiveness of Bivalent Omicron-Containing Booster Vaccines against SARS-CoV-2 Omicron Variant among Individuals with and without Prior SARS-CoV-2 Infection
Authors: Widyasari Kristin , Jang Jieun , Kang Taejoon , Kim Sunjoo
Published: August 2023

In this study, we evaluated the effectiveness of the bivalent mRNA COVID-19 vaccines against the Omicron variant in individuals with or without prior SARS-CoV-2 infection history. We assessed the SARS-CoV-2-specific neutralizing antibody in serum samples by surrogate virus neutralizing assay (sVNT) and determined the serum’s neutralizing capacity against the Omicron BA.5 by a plaque reduction neutralizing test (PRNT50). The results of the sVNT assay demonstrate a higher percentage of inhibition of the serum samples from the infected group than from the uninfected group (p = 0.01) before the bivalent vaccination but a similarly high percentage of inhibition after the vaccination. Furthermore, the results of the PRNT50 assay demonstrate a higher neutralizing capacity of the serum samples against Omicron BA.5 in the infected group compared to the uninfected group, both before and after the bivalent vaccine administration (p < 0.01 and p = 0.02 for samples collected before and after the bivalent vaccination, respectively). A higher neutralizing capacity of the serum samples against BA.5 following bivalent vaccination compared to those before vaccination suggests the efficacy of bivalent mRNA COVID-19 vaccines in triggering an immune response against the Omicron variant, particularly BA.5, regardless of infection history.
The “Psychologization” of Self-Images: Parents Views on the Gendered Dynamics of Sexting and Teen Social Media Cultures
Authors: Dobson Amy Shields , Delaney Maria
Published: August 2023

This paper reports on data from interviews conducted with parents of high school-aged teens as part of a study which was aimed at better understanding the gendered dimensions of youth sexting and social media use, and the community responses to it. Here, we outline the findings on parents’ key concerns around digital and social media, their perceptions of the gendered dynamics of youth self-imaging practices, and their attitudes towards sexting and potentially “sexualized” self-images. Echoing other research in this area, parents were not overly concerned about sexting, nor sexual image-sharing or sexual media use among teens. Rather, their key concerns were more generally about the intensities and pressures of constant contact with peers in the digital era. They did, however, articulate key gender differences and socialization processes around youth self-imaging practices. We discuss the gendered cultural “attunements to sexualization” that parents negotiate in relation to social media image-sharing practices and suggest that the perspectives and experiences described can be understood as part of a broader cultural “psychologization”, and often psycho-pathologizing, of youth self-images in digitally networked intimate publics that is particularly intense around the vectors of gender and sexuality.
Poverty and the “Free Rider Problem” in Russian Society. Interrelationship and Solutions
Authors:   Mendeleev Institute of Social and Economic Forecasting, Shcherbakov Andrey V. ,   LLC «NPO "Kurs"»
Published: August 2023

Two shortcomings of our economy — poverty and the “free rider problem” — have the same origin — an exorbitant tax burden on wages. Mathematical modeling of the transition process from modern to transactional taxation, carried out by a group of Russian scientists, has shown that due to this transition, the country's economy will begin to grow at a rate of 6–7% per year. And most importantly, the very concept of misery will disappear in the country and poverty will be reduced significantly.
Food Safety for 4-H Youth: A Survey of Interests and Educational Methods
Authors: Diehl David , Pracht Dale , Forthun Larry , Simonne Amy
Published: August 2023

Improper food safety practices cause numerous illnesses and cost Americans billions of dollars each year. The study reported here addressed food safety issues by analyzing data from surveys with 4-H youth about their food safety attitudes, behaviors, and preferred methods of educational delivery. Analyses of gender differences indicate that males and females have distinct attitudes, behaviors, and preferences, necessitating more tailored educational approaches. Youth are most interested in food safety information that is fun, interactive, and built around cooking demonstrations. 4-H staff and others in Extension can optimize youth learning and practice change by approaching food safety from this experiential perspective.
Enhancing Cluster Effects to Reduce Regional Labor-Supply Gaps: An Example in South Carolina
Authors: Dickes Lori , Robinson Kenneth
Published: August 2023

A series of regional focus groups and interviews reveal the practical economic development challenges that small and rural communities experience in an environment of globalization and industrial restructuring. The analysis reported here found that many economically distressed communities face immediate human capital and labor market concerns that may prevent the implementation of competitive economic development approaches. Unless these regions address these human capital constraints, they are at continued risk of falling further behind. They must begin with the development of programs and policies that build regional partnerships among local school districts, career centers, local businesses, and community colleges, and universities.
Five Social Media Tools for the Extension Toolbox
Authors: Kinsey Joanne
Published: August 2023

Social media tools can be used to assist in the dissemination of research-based information. Five social media tools, wikis, blogs, podcasts, Facebook, and YouTube, may extend Extension's educational reach into the community. Extension educators will find social media tools easy to use, readily available on the Internet, free of charge, and an interesting addition to the toolbox of dissemination strategies.
Have You Used Clickers in Programming?
Authors: Bird Carolyn , McClelland Jacquelyn
Published: August 2023

Extension agents must provide pertinent programming to their audiences as well as show the impact of their programs. While understanding the audience is a basic tenet of effective public speaking, Extension audiences are not always homogeneous, and typically Extension Agents provide education to participants with different educational levels and life experiences. This article illustrates that Extension educators and their participants can benefit greatly through strategic use of clickers and extends the discussion to the advantages of use for heterogeneous audiences and in applied research. Techniques for using clickers to collect program impact data are discussed.
Operation Cleansweep in Florida: Extension's Role in an Environmentally Friendly Program Opportunity
Authors: Fishel Fred
Published: August 2023

Operation Cleansweep is a free pesticide disposal program that has operated in Florida since 1995. The program is open to commercial facilities, including agricultural production establishments, golf course operators, and pest control companies. Since its inception, the program has had more than 1,700 participants and collected more than 1,000,000 pounds of unused pesticides. University of Florida Extension's role with the program has been to serve as a member of the steering committee and promote and market Operation Cleansweep through normal Extension channels.
Current Immunotherapy Strategies for Rheumatoid Arthritis: The Immunoengineering and Delivery Systems
Authors: Zhang Chenyu , Ma Peixiang , Qin An , Wang Liao , Dai Kerong , Liu Yuanyuan , Zhao Jie , Lu Zuyan
Published: August 2023

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease accompanied by persistent multiarticular synovitis and cartilage degradation. The present clinical treatments are limited to disease-modifying anti-rheumatic drugs (DMARDs) and aims to relieve pain and control the inflammation of RA. Despite considerable advances in the research of RA, the employment of current clinical procedure is enormous, hindered by systemic side effect, frequent administration, tolerance from long-lasting administration, and high costs. Emerging immunoengineering-based strategies, such as multiple immune-active nanotechnologies via mechanism-based immunology approaches, have been developed to improve specific targeting and to reduce adverse reactions for RA treatments. Here, we review recent studies in immunoengineering for the treatment of RA. The prospect of future immunoengineering treatment for RA has also been discussed.
Comparison of Some Hematological Parameters in Unipolar and Bipolar Depressive Disorder
Authors: İMRE Okan
Published: August 2023

Background: Major depressive disorder and bipolar disorder, which are the most severe types of mood disorders, are among the diseases that cause the most disability worldwide. One of the biggest challenges in providing early and effective treatment in mood disorders is the inability to make an early differential diagnosis between UD and BD. Many studies have suggested that neuroinflammation may play a role in the pathophysiology of mood disorders. Neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and monocyte/lymphocyte ratio (MLR) are relatively cheap hematological parameters recommended to measure the level of inflammation. This study aimed to examine the potential role of inflammatory processes in the pathogenesis of unipolar depression(UD) and bipolar depression(BD) by analyzing various hematologic markers, including NLR, PLR, and MLR
Materials and Methods: The patient group comprised 54 individuals(UD: 31, BD: 23), while the healthy control(HC) group comprised 40 individuals. The study compared the values of hematologic markers between the groups.
Results:The study found significant differences only in the levels of NLR among the analyzed hematologic markers(p=0.004). When the UD and BD groups were compared with HC separately, NLR was significantly higher in both the UD and BD groups compared to the HC group(p=0.002, p=0.015). When UD and BD were compared with each other, there was no significant difference in terms of NLR(P=0,416).
Conclusions: In our study, although there was no significant difference between BD and UD in terms of NLR, PLR and MLR, the higher NLR in both patient groups compared to HC suggests the presence of inflammation in both BD and UD patients. More evidence is needed to evaluate it as a disease-specific marker.
Comparison of Risk Factors for Falls in the Old and the Oldest Old Admitted to the Emergency Department
Authors: BEKTAN KANAT Bahar , İNCEALTIN Onur
Published: August 2023

Background: Falls can cause a wide range of consequences from a simple injury to life-threatening situations. As falls are a major cause of mortality and morbidity in older adults, it is important to identify risk factors. Our aim was to evaluate fall risk factors in geriatric patients presenting to the emergency department with fall and to evaluate the variability of fall risk factors in the group below and above 85 years of age (oldest old).
Materials and Methods: A total of 132 geriatric patients admitted to the emergency department of a univer-sity hospital due to falls were retrospectively analysed. Demographic characteristics and chronic diseases of patients, number of drugs, previous fall history, unintentional weight loss, depressive symptoms, anaemia, urinary incontinence, fear of falling, orthostatic hypotension were recorded. Edmonton frail scale, clock-draw-ing test and geriatric depression scale score was also evaluated.
Results: The mean age of our study population was 80.5 ±8.3. While 80 (60.6%) of the patients were below 85 years of age, 52 (39.4%) were aged 85 years and older. 62 (47%) of the patients were frail and orthostatic hypotension was found in 10 (7.6%) of the patients. Fear of falling was observed in 67 (50.8%) patients. Polypharmacy was present in 62 (47%) patients. Frequency of diabetes mellitus, frailty, fear of falling, walking aid usage and the need for a regular caregiver were significantly higher and clock-drawing test score was lower in the oldest old group (p<0.05, for all).
Conclusions: Falls are common in older patients. Our study clearly revealed the frequency of fall risk factors in the geriatric population admitted to the emergency department. The frequency of frailty was higher in the oldest old (over 85 years old) who presented with falls, and fear of falling was found in these patients even if there was no previous history of falling. Necessary precautions should be taken considering the negative con-sequences of falls.
Piles of Bits: Notes on the Virtual Grounds of Post-digital Practice
Authors:   University of Nebraska-Lincoln, Tate Porter Zachary
Published: August 2023

The relationship between building and ground is one of the most significant dynamics within the discipline of architecture. During the twentieth century, for instance, numerous critics interpreted the building/ground joint as a symbolic representation of the discipline’s conceptual posture towards modernity’s shifting technological, socio-cultural, and geopolitical conditions. This paper examines architectural conceptions of ground amidst another transformative moment: namely, the arrival of a “post-digital” or “second digital” era. Whereas designers of the so-called “first digital turn” emphasized the formal possibilities facilitated by virtual space’s liberation from gravity and physics, there is an emerging generation of designers who are using digital tools in a completely different manner. Rather than formal virtuosity, these designers of the post-digital generation focus on the integration of physics, along with the properties of matter, into the virtual realm. Among the experimental approaches that fall within this larger conceptual project is the simulation of gravity, a technique that often results with the piling up of digital bits. By examining the recent proliferation of simulated piles, this paper highlights the ways in which shifting applications of digital tools are reshaping disciplinary conceptions of ground.