bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of Income Inequality in South Africa: A Vector Error Correction Model Approach
Authors: Seabela Molepa , Ogujiuba Kanayo , Eggink Maria
Published: July 2024

The issue of income disparity has long plagued South Africa because of the political environment that existed before the country’s 1994 democratic transition. Based on the widely used Gini index, which gauges global inequality, the nation routinely has some of the highest rates of income disparity in the world. Income inequality in South Africa keeps rising even after a number of frameworks and policies have been put in place, which has a big influence on society. Thus, it is essential to comprehend the causes of income disparity and put suitable policies in place to remedy it. The purpose of this study is to look into the relationship between South Africa’s income disparity and its determinants. Using the Vector Error Correction Model (VECM) approach, this study empirically examines the effects of government spending on social grants, gross savings, population growth, and economic growth on income inequality from 1975 to 2017. Data on the Gini index are sourced from the Standardized World Income Inequality Database (SWIID). Findings reveal a statistically significant negative correlation between government spending on social grants and income inequality. Moreover, income inequality demonstrates a negative relationship with both gross savings and economic growth. However, population growth exhibits a positive correlation with income inequality. This study highlights the significance of implementing a comprehensive strategy to address income inequality in South Africa. This strategy should involve augmenting government expenditure on social grants, cultivating a savings culture within households, and enacting policies that incentivize job creation, particularly in areas with rapid population growth. In addition to making a substantial contribution to the body of evidence already available on income disparity, this study offers insightful information to policymakers working to improve the socioeconomic climate in South Africa.
Connectedness between Sustainable Investment Indexes: The QVAR Approach
Authors: Marín-Rodríguez Nini Johana , Gonzalez-Ruiz Juan David , Botero Sergio
Published: July 2024

We studied the relationship between sustainable investment indexes and examine whether this relationship varies in bullish, bearish, and stable financial markets. To understand this issue more deeply, we analyzed the connectedness between three indexes—the Sustainable Impact investments, Paris-aligned stocks, and green bonds indexes—using the daily closing prices from 1 June 2017 to 15 April 2024, encompassing 1793 observations. We used a quantile vector autoregressive (QVAR) model to understand the dynamic relationship among the considered indices. The findings indicate that sustainable investments are strongly interconnected in both high and low quantiles, but this connection weakens significantly during periods of market stability. The Sustainable Impact investments and Paris-aligned stocks indexes are net transmitters of impacts to other sustainable alternatives, while the green bonds index is a net receiver. We also observed an increase in interconnectedness across all quantiles during the pandemic, the Russia–Ukraine military conflict, and changes in the European Union and the United States’ monetary policies.
Outcomes of Equity-Based Multi-Tiered System of Support and Instructional Decision-Making for Autistic Students
Authors: Choi Jeong Hoon , Miller Dawn D. , McCart Amy B.
Published: July 2024

For many autistic students, to experience more successful outcomes, school processes must be restructured and given necessary resources. The probability of success can be increased by implementing a school system that integrates research-based academic and behavioral instructional support, along with collaborative data-informed decision-making routines. This paper presents an example of a transformational framework and technical assistance that were provided to six schools to reshape and increase the schools’ capacity to implement and sustain an equity-based multi-tiered system of support (MTSS) with intensified instructional decision making. Statistical analyses were used to examine the outcomes of autistic students (n = 23) who participated in a state assessment over three consecutive years in the same state. The results demonstrated an increase in academic scores, and many students transitioned to less-restrictive educational environments.
Cultivating Resilience and Success: Support Systems for Novice Teachers in Diverse Contexts
Authors: Diab Alkhansaa , Green Edna
Published: July 2024

This qualitative study explores the support systems that foster resilience and success among novice teachers in diverse sociocultural contexts within Israeli teacher training colleges. Semistructured interviews were conducted with a sample of 51 novice teachers from various educational backgrounds. The findings reveal a complex network of support encompassing formal institutional structures, such as mentorship programs and induction workshops, as well as informal networks of familial support and cultural connections. Utilizing a holistic framework that integrates social support theory, social connection theory, and self-determination theory, the study highlights the interplay between external support and novice teachers’ intrinsic motivations, which drive their pursuit of autonomy, competence, and relatedness. The key findings underscore the crucial role of comprehensive induction and mentoring programs that address novice teachers’ emotional, psychological, and professional needs. These programs should provide emotional support, opportunities for collaboration and peer learning, and personalized guidance from experienced mentors. The study also emphasizes the significance of supportive school cultures, meaningful mentoring relationships, and the strength of informal support networks in promoting novice teachers’ well-being and effectiveness. The implications of this research are far-reaching, offering valuable insights for the global educational community on developing supportive ecosystems that enhance novice teachers’ resilience, job satisfaction, and retention rates. By articulating the essential role of both formal and informal support systems, this study contributes significantly to the discourse on teacher education and addresses a crucial gap in the literature on support mechanisms across diverse educational settings.
Enhancing Rural Science Education through School District–University Partnership
Authors: Ferrell Venicia A. , Tharpe Alexis S.
Published: July 2024

This instrumental case study describes the steps taken to establish and implement a university–school partnership to improve rural science teachers’ content knowledge and teaching practices and students’ achievement in elementary science and high school biology courses. Our research questions explored the impact of professional development and place-based learning on student outcomes, with the study’s methodology involving needs assessments, teacher training, and continuous support through modeling and coaching. The findings include gains in achievement and substantial gains in science education. The findings have implications for the design, implementation, and evaluation of university–school partnerships designed to build teachers’ capacity to deliver high-quality science education and improve student success in rural school districts.
Thematic Teaching of Augmented Reality and Education for Sustainable Development in Preschool—The Importance of ‘Place’
Authors: Fridberg Marie , Redfors Andreas
Published: July 2024

In this study, we report on a case study of two Swedish preschool teachers’ first experiences of teaching sustainable development goals through the innovative use of augmented reality. Their statements about thematic work, children’s agency, teachers’ perspective, and augmented reality were analysed qualitatively through a theoretical framework based on transduction and place. The innovative use of augmented reality related to the importance of children’s agency in their exploration of local places associated with sustainable development goals is elaborated on, especially with the value of treating augmented reality as a ‘what’, or content, in teaching before it can be used as a ‘how’, or tool, for teaching sustainable development. It is seen in this exploratory study that transducing meaning between different representations such as physical places and the sustainable development goals in augmented reality applications opens up fruitful discussions regarding, for example, democracy aspects and source criticism between children and preschool teachers. Results indicate that the introduction of augmented reality technology is also worth pursuing in early-year teaching.
The System Architecture-Function-Outcome Framework for Fostering and Assessing Systems Thinking in First-Year STEM Education and Its Potential Applications in Case-Based Learning
Authors: Lavi Rea , Bertel Lykke Brogaard
Published: July 2024

Systems thinking is crucial for understanding and solving complex problems and is considered an important thinking skill in engineering. Active learning is considered an effective approach for fostering STEM students’ systems thinking. However, viable methods for teaching and assessing systems thinking with active learning across STEM disciplines, particularly in first-year undergraduate education, are still under-researched. In this paper, we introduce a research-based framework named System Architecture-Function-Outcome to help first-year STEM instructors both foster and assess students’ introductory systems thinking. To conduct an initial evaluation of the framework’s suitability in active learning settings, we designed a directed case-based learning assignment with an adapted article and a rubric for assessing ‘introductory systems thinking’, as defined in the framework. We deployed the assignment among 84 first-year STEM students and successfully tested its inter-rater reliability, with 75–100% inter-rater agreement across all assessment criteria. We discuss the implications of our results on fostering and assessing first-year STEM students’ systems thinking, and outline examples for potential applications of the framework, pending further validation, in case-based learning settings of varying degrees of learner autonomy, from lecture-based to problem-based learning.
A Multi-Hop End-Edge Cooperative Computing Scheme for Power IoT
Authors: Li Xue , Chen Xiaojuan , Li Guohua , Zhang Xuguang , Yang Hongliu
Published: July 2024

With the continuous development of the power Internet of Things (PIoT), smart devices (SDs) have been widely used in electric power inspections. Due to the limited resources of intelligent inspection SDs and the distance of overhead transmission lines, many inspection tasks cannot be processed promptly. This paper proposes a multi-hop-based end-edge cooperative computing (MHCC) scheme to address inspection task processing in power IoT. We formulate a multi-hop task offloading problem that minimizes the energy consumption of inspection SDs with delay constraints. We develop a JDPSO algorithm to solve the multi-hop task offloading problem and evaluate the algorithm’s performance based on numerous simulation experiments. The experimental results show that JDPSO reduces the system’s energy consumption by 56.30%, 48.56%, 78.87%, 50.89%, 30.85%, and 68.31%, and also reduces delay by 50.69%, 42.78%, 58.67%, 44.84%, 10.22%, and 62.88% compared to GA, RSA, SSA, MFO, DOA, and ALC schemes.
An Experimental Investigation of Noise Sources’ Contribution in the Multi-Chip Module Open-Loop Comb-Drive Capacitive MEMS Accelerometer
Authors: Jankowski Mariusz , Szermer Michał , Zając Piotr , Amrozik Piotr , Maj Cezary , Nazdrowicz Jacek , Jabłoński Grzegorz , Sakowicz Bartosz
Published: July 2024

The paper presents the noise analysis of a MEMS and ASIC readout integrated circuit (ROIC) constituting the accelerometer developed in the frame of the InnoReh project, aiming at the development of methods for monitoring patients with imbalance disorders. Several experiments were performed at different temperatures and in different configurations: ROIC alone, ROIC with emulated parasitic capacitances, MEMS and ROIC in separate packages, and MEMS and ROIC in a single package. Many noise/interference sources were considered. The results obtained experimentally were compared to the results of theoretical investigations and were within the same order of magnitude, although in practice, the observed noise was always greater than the theoretical estimation. The paper also includes an in-depth analysis to explain these differences. Moreover, it is argued that, in terms of noise, the MEMS sensing element, and not the ROIC, is the quality-limiting factor.
Exploring the Relationship and Predictive Accuracy for the Tadawul All Share Index, Oil Prices, and Bitcoin Using Copulas and Machine Learning
Authors: Alokley Sara Ali , Araichi Sawssen , Alomair Gadir
Published: July 2024

Financial markets are increasingly interlinked. Therefore, this study explores the complex relationships between the Tadawul All Share Index (TASI), West Texas Intermediate (WTI) crude oil prices, and Bitcoin (BTC) returns, which are pivotal to informed investment and risk-management decisions. Using copula-based models, this study identified Student’s t copula as the most appropriate one for encapsulating the dependencies between TASI and BTC and between TASI and WTI prices, highlighting significant tail dependencies. For the BTC–WTI relationship, the Frank copula was found to have the best fit, indicating nonlinear correlation without tail dependence. The predictive power of the identified copulas were compared to that of Long Short-Term Memory (LSTM) networks. The LSTM models demonstrated markedly lower Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Scaled Error (MASE) across all assets, indicating higher predictive accuracy. The empirical findings of this research provide valuable insights for financial market participants and contribute to the literature on asset relationship modeling. By revealing the most effective copulas for different asset pairs and establishing the robust forecasting capabilities of LSTM networks, this paper sets the stage for future investigations of the predictive modeling of financial time-series data. The study highlights the potential of integrating machine-learning techniques with traditional econometric models to improve investment strategies and risk-management practices.
Research on a Distributed Photovoltaic Two-Level Planning Method Based on the SCMPSO Algorithm
Authors: Dong Ang , Lee Seon-Keun
Published: July 2024

In response to challenges such as voltage limit violations, excessive currents, and power imbalances caused by the integration of distributed photovoltaic (distributed PV) systems into the distribution network, this study proposes at two-level optimization configuration method. This method effectively balances the grid capacity and reduces the active power losses, thereby decreasing the operating costs. The upper-level optimization enhances the distribution network’s capacity by determining the siting and sizing of distributed PV devices. The lower-level aims to reduce the active power losses, improve the voltage stability margins, and minimize the voltage deviations. The upper-level planning results, which include the siting and sizing of the distributed PV, are used as initial conditions for the lower level. Subsequently, the lower level feeds back its optimization results to further refine the configuration. The model is solved using an improved second-order oscillating chaotic map particle swarm optimization algorithm (SCMPSO) combined with a second-order relaxation method. The simulation experiments on an improved IEEE 33-bus test system show that the SCMPSO algorithm can effectively reduce the voltage deviations, decrease the voltage fluctuations, lower the active power losses in the distribution network, and significantly enhance the power quality.
Drought and Wildfire Trends in Native Forests of South-Central Chile in the 21st Century
Authors: Duarte Efraín , Rubilar Rafael , Matus Francisco , Garrido-Ruiz Claudia , Merino Carolina , Smith-Ramirez Cecilia , Aburto Felipe , Rojas Claudia , Stehr Alejandra , Dörner José , Nájera Francisco , Barrientos Guillermo , Jofré Ignacio
Published: July 2024

Over the last decades, Chile has experienced a long-term drought with significant consequences for water availability, forest productivity, and soil degradation, ultimately dramatically increasing the surface of burned area. Here, we quantify the Palmer Drought Severity Index (PDSI) to ascertain the extent of “moisture deficiency” across the central-southern region of Chile from 2000 to 2023 to assess the drought’s relationship with the frequency of wildfires focusing on the impact of native forests. Our methodology quantifies the PDSI from the burned area data using MODIS MCD64A1 satellite imagery, validated by in situ wildfire occurrence records. The findings indicate that 85.2% of fires occurred under moderate to severe drought conditions. We identified 407,561 ha showing varying degrees of degradation due to wildfires, highlighting the critical areas for targeted conservation efforts. A significant increase in both the frequency of wildfires and the extent of the affected area in native forests was observed with the intensification of drought conditions in the 21st century within mesic to humid Mediterranean climatic zones where drought explains up to 41% of the variability in the burned area (r2 = 0.41; p < 0.05). This study highlights the relationship between drought conditions and wildfire frequency, showing the paramount need to adopt comprehensive wildfire mitigation management in native forests.
Citrullus mucosospermus Extract Exerts Protective Effects against Methionine- and Choline-Deficient Diet-Induced Nonalcoholic Steatohepatitis in Mice
Authors: Park Sun Young , Kim Ji Eun , Kang He Mi , Park Ki Ho , Je Byoung Il , Lee Ki Won , Hwang Dae Youn , Choi Young Whan
Published: July 2024

In recent years, there has been increasing interest in exploring the potential therapeutic advantages of Citrullus mucosospermus extracts (CME) for nonalcoholic steatohepatitis (NASH). In this study, we investigated the therapeutic effects of CME on NASH using a mice model. High-performance liquid chromatography (HPLC) was employed to identify cucurbitacin E and cucurbitacin E-2-O-glucoside from the CME. Although CME did not significantly alter the serum lipid levels in methionine- and choline-deficient (MCD) mice, it demonstrated a protective effect against MCD diet-induced liver damage. CME reduced histological markers, reduced alanine transaminase (ALT) and aspartame transaminase (AST) levels, and modulated key NASH-related genes, including C/EBPα, PPARγ, Fas, and aP2. In addition, CME was found to restore hormone-sensitive lipase (HSL) and adipose triglyceride lipase (ATGL) activity, both crucial for fat catabolism, and reduced the levels of pro-inflammatory cytokines. Furthermore, CME demonstrated the potential to mitigate oxidative stress by maintaining or enhancing the activation and expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and superoxide dismutase (SOD), both pivotal players in antioxidant defense mechanisms. These findings underscore the promising therapeutic potential of CME in ameliorating liver damage, inflammation, and oxidative stress associated with NASH.
The “Dry-Lab” Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data
Authors: Spatola Gabriele , Giusti Alice , Armani Andrea
Published: July 2024

Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the “wet-lab” procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final “dry-lab” phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies’ self-control in order to detect species substitution and counterfeit frauds.
Stable Isotope Ratio Analysis for the Geographic Origin Discrimination of Greek Beans “Gigantes-Elefantes” (Phaseolus coccineus L.)
Authors: Thomatou Anna-Akrivi , Mazarakioti Eleni C. , Zotos Anastasios , Kokkotos Efthimios , Kontogeorgos Achilleas , Patakas Angelos , Ladavos Athanasios
Published: July 2024

Adulteration of high-value agricultural products is a critical issue worldwide for consumers and industries. Discrimination of the geographical origin can verify food authenticity by reducing risk and detecting adulteration. Between agricultural products, beans are a very important crop cultivated worldwide that provides food rich in iron and vitamins, especially for people in third-world countries. The aim of this study is the construction of a map of the locally characteristic isotopic fingerprint of giant beans, “Fasolia Gigantes-Elefantes PGI”, a Protected Geographical Indication product cultivated in the region of Kastoria and Prespes, Western Macedonia, Greece, with the ultimate goal of the discrimination of beans from the two areas. In total, 160 samples were collected from different fields in the Prespes region and 120 samples from Kastoria during each cultivation period (2020–2021 and 2021–2022). The light element (C, N, and S) isotope ratios were measured using Isotope Ratio Mass Spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques, including a one-way ANOVA and Binomial logistic regression. The mean values from the one-way ANOVA were δ15NAIR = 1.875‰, δ13CV-PDB = −25.483‰, and δ34SV-CDT = 4.779‰ for Kastoria and δ15NAIR = 1.654‰, δ13CV-PDB = −25.928‰, and δ34SV-CDT = −0.174‰ for Prespes, and showed that stable isotope ratios of C and S were statistically different for the areas studied while the Binomial logistic regression analysis that followed correctly classified more than 78% of the samples.
Relationship between Presentation, Attitude, and In-Flight Meal Food Healthiness: Moderating Role of Familiarity
Authors: Jang Ryeojin , Lee Won Seok , Moon Joonho
Published: July 2024

This work focused on the perception of the food healthiness of in-flight meals. This work adopts presentation as the determinant. This work also employs attitude as the consequence of food healthiness. This research also examines the moderating effect of familiarity on the relationship between food presentation and food healthiness. This research used a survey, and survey participants were recruited via a Clickworker platform service. Survey participants were experienced with in-flight meals. The number of observations was 317. Moreover, this research tested the research hypotheses using the Hayes process macro Model 7. The results revealed that food healthiness is positively influenced by presentation and that food healthiness positively affects attitude. Moreover, the results revealed that the type of presentation has a positive influence on attitude. Familiarity was a significant moderating variable for the relationship between food presentation and food healthiness. This work sheds light on the literature by identifying the associations among four attributes of in-flight meals. Additionally, the results of this study could be used as a reference to develop better in-flight meals.
Risk Factors and Effects of Climate Lag on Vibrio Parahaemolyticus Infection in Eastern Coastal Cities of China: A Study Based on Hangzhou City
Authors: Ren Hangqi , Liu Ting , Hou Hao , Qi Xiaojuan , Fang Lei , Yang Yinyi , Ma Rong
Published: July 2024

Bacterial foodborne diseases caused by Vibrio parahaemolyticus pose persistent challenges to coastal cities in China. In this study, we employed multiple logistic regression analysis and distributed lag non-linear models (DLNM) to investigate the epidemiological characteristics and associated risk factors of vibriosis in the metropolitan area of Hangzhou from 2014 to 2018. Analysis of foodborne cases indicated that certain demographics and occupational factors, including age between 16 and 44 years; houseworkers or unemployed individuals; preference for aquatic and meat products; and dining in collective canteens or catering services contribute to an increased likelihood of V. parahaemolyticus infection. Moreover, a higher per capita GDP and exposure to high temperatures were identified as risk factors for vibriosis. This study highlights the significance of the daily mean temperature as a meteorological factor influencing V. parahaemolyticus infection, with varying lag effects observed depending on temperature conditions. At low temperatures, the risk of infection occurs after a lag of 21 days, whereas at high temperatures, the risk is highest on the same day, while the second infection risk period occurs after a lag of 21 days. These findings provide a spatiotemporal perspective of the risk analysis of foodborne diseases, with a daily timescale and street spatial scale, which contributes to the development of public health strategies and food safety protocols in coastal cities.
Soy Protein Isolate Gel Subjected to Freezing Treatment: Influence of Methylcellulose and Sodium Hexametaphosphate on Gel Stability, Texture and Structure
Authors: Xia Xiaoyu , Zhang Binyang , Huang Yuyang , Zhu Ying , Qu Min , Liu Linlin , Sun Bingyu , Zhu Xiuqing
Published: July 2024

Freezing affects texture and induces the loss of gel quality. This study investigated the effects of methylcellulose (MC) (0.2%, 0.4%, 0.6%) and sodium hexametaphosphate (SHMP) (0.15%, 0.3%) on the gel textural and structural properties of SPI gels before and after freezing, and explores the synergistic enhancement of gel texture and the underlying mechanisms resulting from the simultaneous addition of SHMP and MC to SPI gels. It was revealed that MC improved the strength of SPI gels through its thickening properties, but it could not inhibit the reduction of SPI gels after freezing. The 0.4% MC-SPI gel exhibited the best gel strength (193.2 ± 2.4 g). SHMP inhibited gel reduction during freezing through hydrogen bonding and ionic interactions; it enhanced the freezing stability of SPI gels. The addition of 0.15% SHMP made the water-holding capacity in SPI gels reach the highest score after freezing (58.2 ± 0.32%). The synergistic effect of MC and SHMP could improve the strength and the freezing stability of SPI gels. MC facilitated the release of ionizable groups within SPI, causing negatively charged SHMP groups to aggregate on the SPI and inhibit the freezing aggregation of proteins. These results provide a strong basis for the improvement of cryogenic soy protein gel performance by SHMP and MC.
Robust Consensus Analysis in Fractional-Order Nonlinear Leader-Following Systems with Delays: Incorporating Practical Controller Design and Nonlinear Dynamics
Authors: Khan Asad , Javeed Muhammad Awais , Niazi Azmat Ullah Khan , Rehman Saadia , Zhong Yubin
Published: July 2024

This article investigates the resilient-based consensus analysis of fractional-order nonlinear leader-following systems with distributed and input lags. To enhance the practicality of the controller design, an incorporation of a disturbance term is proposed. Our modeling framework provides a more precise and flexible approach that considers the memory and heredity aspects of agent dynamics through the utilization of fractional calculus. Furthermore, the leader and follower equations of the system incorporate nonlinear functions to explore the resulting changes. The leader-following system is expressed by a weighted graph, which can be either undirected or directed. Analyzed using algebraic graph theory and the fractional-order Razumikhin technique, the case of leader-following consensus is presented algebraically. To increase robustness in multi-agent systems, input and distributive delays are used to accommodate communication delays and replicate real-time varying environments. This study lays the groundwork for developing control methods that are more robust and flexible in complex networked systems. It does so by advancing our understanding and practical application of fractional-order multi-agent systems. Additionally, experiments were conducted to show the effectiveness of the design in achieving consensus within the system.
An Examination of the Very First Polarimetric X-ray Observations of Radio-Quiet Active Galactic Nuclei
Authors: Marin Frédéric , Gianolli Vittoria E. , Ingram Adam , Kim Dawoon E. , Marinucci Andrea , Tagliacozzo Daniele , Ursini Francesco
Published: July 2024

Active galactic nuclei (AGNs), either radio-quiet or radio-loud, had never been observed in X-ray polarized light until the advent of the Imaging X-ray Polarimetry Explorer (IXPE) in the end of 2021. This satellite opened a new observational window for studying supermassive black holes and their complex environment. In this regard, radio-quiet AGNs are probably better targets than radio-loud objects to probe accretion processes due to the lack of synchrotron emission from jets that can dilute the polarized signal from the central engine. Their relatively clean environment not only allows to detect and measure the X-ray polarization originating from the hot corona responsible for X-ray emission, but also to assess the geometry of the media immediately surrounding the supermassive black hole. Such geometrical measurements work just as well for characterizing the corona morphology in pole-on AGNs as it does for determining the three-dimensional shape of the circumnuclear cold obscurer (the so-called torus) in edge-on AGNs. In this review paper, we will return to each of the observations made by IXPE so far in the field of radio-quiet AGNs and highlight the fundamental contribution of X-ray polarimetry to our understanding of how light is emitted and how matter is shaped around supermassive black holes.
Effects of Tempo-Controlled Resistance Training on Corticospinal Tract Plasticity in Healthy Controls: A Systematic Review
Authors: Gordon Talia , Jeanfavre Michael , Leff Gretchen
Published: July 2024

After musculoskeletal injuries, there is often a loss of corticospinal control. Current tendon rehabilitation may not adequately address the corticospinal control of the muscle which may contribute to the recalcitrance of symptom recurrence. This review provides a summary of the current literature regarding the effectiveness of tempo-controlled resistance training (TCRT) in (1) promoting corticospinal plasticity, (2) improving physical performance, and (3) improving strength outcomes in healthy adults. A comprehensive literature search was conducted using electronic databases (PubMed, CINAHL, Embase, and Google Scholar) to identify relevant studies published between 2010 and 2023. Randomized control (RCT) studies that included recreationally trained and untrained healthy adults between 18 and 60 years of age and that compared a TCRT intervention to a control condition were included. Twelve of the 1255 studies identified in the initial search were included in the final analysis. Throughout all included studies, TCRT was shown to elicit greater neural adaptations compared to traditional resistance training methods (i.e., self-paced strength training). These results indicate that TCRT holds promise as an effective method for modulating corticospinal plasticity in healthy adults and may enhance neuromuscular adaptations, including improvements in CSE, decreased SICI, enhanced motor unit synchronization, and voluntary muscle activation.
Epidemiology and Management of Bean Common Mosaic Virus (BCMV) in Traditional Phaseolus vulgaris L. Landraces within Protected Geographical Indications
Authors: Expósito-Goás Sonia , Pinacho-Lieti Lautaro Gabriel , Lago-Pena Fernando , Cabaleiro Cristina
Published: July 2024

Protected geographical indications (PGIs) share health problems related to plant propagation material. The PGI “Faba de Lourenzá” encompasses a 1660 km2 area in northern Galicia, Spain, renowned for its “Faba Galaica” (FG) and Faba do marisco” (FM) bean cultivars. The lack of certified virus-free seeds poses a challenge. From 2019 to 2023, seeds from 60 lots were tested for BCMV. Plants from several plots were tested periodically to develop disease progress curves (DPCs). Control methods (plots out PGI zone, virus-free seedlings, rogueing, corn borders, and intercropping) were tested. Yields in five plots were used to assess BCMV’s economic impact. Seed lots were 22.3% FG-infected and <5% FM-infected. The transmission rate of BCMV from infected FG plants to their seeds was 25.5 ± 5%, while for FM it was 12 ± 3%. FG yield losses were on average 31.6 ± 4.5%. Combining virus-free seedlings and infected plant removal in plots outside the PGI area proved effective at reducing infection rates; combining with intercropping resulted in the lowest incidence in an FG plot. Farmer training and off-site plot selection to produce healthy sowing beans are key to improving results.
Pre-Harvest UV-A Supplementation in Plant Factory with Artificial Lighting Improves Growth, Photosynthesis, and Phytonutrients in Kale
Authors: Sonjaroon Weerasin , Tepkaew Teerapat , Kupia Manop , Tongkok Pattama , Boonkorkaew Patchareeya , Thussagunpanit Jutiporn
Published: July 2024

UV-A (315–400 nm) is a component of solar radiation, which impacts plant physiology. Consequently, the impact was investigated of UV-A supplementation on various aspects of kale cultivation in a plant factory with artificial lighting. Three UV-A intensity treatments (5, 10, or 15 W/m2) were applied to kale plants for 5 days before harvesting. The results revealed that 5 or 10 W/m2 UV-A supplementation provided significant advantages for kale growth. The fresh weight of the kale shoots increased by over 35–50% after UV-A exposure. In particular, the 10 W/m2 UV-A exposure significantly improved the photosynthetic rate, water-use efficiency, and quantum efficiency of photosystem II (Y(II)). In addition, the treatment with UV-A positively impacted changes in leaf spectral indices, resulting in decreases in the simple ratio index (SR), the normalized phaeophytinization index (NPQI), and the normalized difference red edge index (NDRE). Furthermore, the phytonutrients in kale (Vitamin C, soluble protein, and total phenolics) were enhanced using the 10 W/m2 UV-A treatment. One notable outcome was the consistent reduction in nitrate contents across all UV-A treatment intensities. Therefore, supplementing kale cultivation with UV-A radiation was a valuable strategy for enhancing kale yield and quality in plant factory production.
Perceptions of Cryptocurrencies and Modern Money before and after the COVID-19 Pandemic in Poland and Germany
Authors: Maciejasz Marta , Poskart Robert , Wotzka Daria
Published: July 2024

Research background: Despite the fact that the issue of private, decentralized digital money (cryptocurrencies) is already quite extensively described in the literature dedicated to the financial system, especially its periphery, there is a deficiency in terms of research on the opinions of participants in the financial system, based on trust in money and its widespread acceptance. International comparative studies are lacking, particularly those conducted before and after the COVID-19 virus pandemic. The pandemic showed that people had significantly changed their willingness to use different forms of money. Being isolated at home and avoiding direct contact with others, people started to use digital money more frequently. Purpose of the article: In response to the identified research gap, this study reports research results on the perception of cryptocurrencies by young financial market participants. It attempts to provide answers to the following research questions: (1) Has the COVID-19 pandemic and the lockdown of economies caused changes at the international level in perceptions and attitudes toward the traditional monetary system and cryptocurrencies? (2) Has the COVID-19 pandemic changed perceptions of cryptocurrencies as a potential alternative to current fiat money? Methods: To evaluate respondents’ opinions, a survey in the form of a questionnaire was conducted. The respondent groups in 2019/2020 were N = 171 (Germany = 143 and Poland = 128), while in 2021, N = 157 (Germany = 95 and Poland = 62). For analytical purposes, statistical analysis using the Z ratio test was used to capture the characteristics of the response distributions and the relationships between them. These two moments in time allowed us to determine whether there were significant changes between opinions before and after COVID-19. Findings & value added: The study’s results showed that while there are significant differences in perceptions of the traditional monetary system and cryptocurrencies due to a variety of factors, the COVID-19 pandemic and the shutdown of economies did not cause statistically significant differences in this regard.
Optimizing Station Placement for Free-Floating Electric Vehicle Sharing Systems: Leveraging Predicted User Spatial Distribution from Points of Interest
Authors: Cao Qi , Wang Shunchao , Wang Bingtong , Ma Jingfeng
Published: July 2024

Rapid growth rate indicates that the free-floating electric vehicle sharing (FFEVS) system leads to a new carsharing idea. Like other carsharing systems, the FFEVS system faces significant regional demand fluctuations. In such a situation, the rental stations and charging stations should be constructed in high-demand areas to reduce the scheduling costs. However, the planning of the FFEVS system includes a series of aspects of rental stations and charging stations, such as the location, size, and number, which interact with each other. In this paper, we first provide a method for forecasting the demand for car sharing based on the land characteristics of Beijing FFEVS station catchment areas. Then, the multi-objective MILP model for planning FFEVS systems is developed, which considers the requirements of vehicle relocation and electric vehicle charging. Afterward, the capabilities of the proposed models are demonstrated by the real data obtained from Beijing, China. Finally, the sensitivity analysis of the model is made based on varying demand and subsidy levels. From the results, the proposed model can provide decision-makers with useful insights about the planning of FFEVS systems, which bring great benefits to formulating more rational policies.
Performance Analysis of Random Forest Algorithm in Automatic Building Segmentation with Limited Data
Authors: Widyastuti Ratri , Suwardhi Deni , Meilano Irwan , Hernandi Andri , Putri Nabila S. E. , Saptari Asep Yusup , Sudarman
Published: July 2024

Airborne laser technology produces point clouds that can be used to build 3D models of buildings. However, the work is a laborious process that could benefit from automation. Artificial intelligence (AI) has been widely used in automating building segmentation as one of the initial stages in the 3D modeling process. The algorithms with a high success rate using point clouds for automatic semantic segmentation are random forest (RF) and PointNet++, with each algorithm having its own advantages and disadvantages. However, the training and testing data to develop and test the model usually share similar characteristics. Moreover, producing a good automation model requires a lot of training data, which may become an issue for users with a small amount of training data (limited data). The aim of this research is to test the performance of the RF and PointNet++ models in different regions with limited training and testing data. We found that the RF model developed from a small amount data, in different regions between the training and testing data, performs well compared to PointNet++, yielding an OA score of 73.01% for the RF model. Furthermore, several scenarios have been used in this research to explore the capabilities of RF in several cases.
Multiscale Visualization of Surface Motion Point Measurements Associated with Persistent Scatterer Interferometry
Authors: Kalaitzis Panagiotis , Foumelis Michael , Mouratidis Antonios , Kavroudakis Dimitris , Soulakellis Nikolaos
Published: July 2024

Persistent scatterer interferometry (PSI) has been proven to be a robust method for studying complex and dynamic phenomena such as ground displacement over time. Proper visualization of PSI measurements is both crucial and challenging from a cartographic standpoint. This study focuses on the development of an interactive cartographic web map application, providing suitable visualization of PSI data, and exploring their geographic, cartographic, spatial, and temporal attributes. To this end, PSI datasets, generalized at different resolutions, are visualized in eight predefined cartographic scales. A multiscale generalization algorithm is proposed. The automation of this procedure, spurred by the development of a web application, offers users the flexibility to properly visualize PSI datasets according to the specific cartographic scale. Additionally, the web map application provides a toolset, offering state-of-the-art cartographic approaches for exploring PSI datasets. This toolset consists of exploration, measurement, filtering (based on the point’s spatial attributes), and exporting tools customized for PSI measurement. Furthermore, a graph tool, offering users the capability to interactively plot PSI time-series and investigate the evolution of ground deformation over time, has been developed and integrated into the web interface. This study reflects the need for appropriate visualization of PSI datasets at different cartographic scales. It is shown that each original PSI dataset possesses a suitable cartographic scale at which it should be visualized. Innovative cartographic approaches, such as web applications, can prove to be effective tools for users working in the domain of mapping and monitoring the dynamic behavior of surface motion.
Spatial Nonlinear Effects of Street Vitality Constrained by Construction Intensity and Functional Diversity—A Case Study from the Streets of Shenzhen
Authors: Li Jilong , Kong Niuniu , Lin Shiping , Zeng Jie , Ke Yilin , Chen Jiacheng
Published: July 2024

As an important part of urban vitality, street vitality is an external manifestation of street economic prosperity and is affected by the built environment and the surrounding street vitality. However, existing research on the formation mechanism of street vitality focuses only on the built environment itself, ignoring the spatial spillover effect on street vitality. This study uses 5290 street segments in Shenzhen as examples. Utilizing geospatial and other multisource big data, this study creates spatial weight matrices at varying distances based on different living circle ranges. By combining the panel threshold model (PTM) and the spatial panel Durbin model (SPDM), this study constructs a spatial autoregressive threshold model to explore the spatial nonlinear effects of street vitality, considering various spatial weight matrices and thresholds of construction intensity and functional diversity. Our results show the following: (1) Street vitality exhibits significant spatial spillover effects, which gradually weaken as the living circle range expands (Moran indices are 0.178***, 0.160***, and 0.145*** for the 500 m, 1000 m, and 1500 m spatial weight matrices, respectively). (2) Construction intensity has a threshold, which is 0.1466 under spatial matrices of different distances. Functional diversity has two thresholds: 0.6832 and 2.2065 for the 500 m spatial weight matrix, and 0.6832 and 1.4325 for the 1000 m matrices, and 0.6832 and 1.2724 for 1500 m matrices. (3) As an international metropolis, street accessibility in Shenzhen has a significant and strong positive impact on its street vitality. This conclusion provides stakeholders with spatial patterns that influence street vitality, offering a theoretical foundation to further break down barriers to street vitality.
Does Combined Reconstruction of the Medial Collateral and Anterior Cruciate Ligaments Provide Better Knee Function? A Systematic Review and Meta-Analysis
Authors: Csete Károly , Baráth Bálint , Sándor Lilla , Holovic Helga , Mátrai Péter , Török László , Hartmann Petra
Published: July 2024

Objective: This study aimed to determine if medial collateral ligament reconstruction (MCLR) alongside anterior cruciate ligament reconstruction (ACLR) preserves knee functionality better than isolated ACLR in combined ACL and MCL tears. Methods: MEDLINE, EMBASE, Scopus, CENTRAL, and Web of Science were searched systematically on 31 March 2023. Studies reporting post-operative function after ACLR and ACLR + MCLR in combined injuries were included. Outcomes included International Knee Documentation Committee (IKDC) score, side-to-side difference (SSD), Lysholm, and Tegner scale values. Results: Out of 2362 papers, 8 studies met the criteria. The analysis found no significant difference in outcomes (MD = 3.63, 95% CI: [−5.05, 12.3] for IKDC; MD = −0.64, 95% CI: [−3.24, 1.96] for SSD at 0° extension; MD = −1.79, 95% CI: [−4.61, 1.04] for SSD at 30° extension; MD = −1.48, 95% CI: [−16.35, 13.39] for Lysholm scale; MD = −0.21, 95% CI: [−4.29, 3.87] for Tegner scale) between treatments. Conclusions: This meta-analysis found no significant difference in outcomes between ACLR and ACLR + MCLR, suggesting that adding MCLR does not provide additional benefits. Due to the heterogeneity and quality of the included studies, further high-quality randomized controlled trials are needed to determine the optimal treatment for combined severe MCL–ACL injuries.