bluuebunny/crossref_metadata_2025 huggingface dataset:
Bed Separation Formation Mechanism and Water Inrush Evaluation in Coal Seam Mining under a Karst Cave Landform
Authors: Gao Zhu , Xu Guosheng , Li Huigui , Su Deguo , Liu Yuben
Published: December 2023

Understanding the formation mechanism of bed separation in coal seam mining under a karst landform is needed for the prevention and control of roof-separated water damage in such areas. This research used a mine in the northern Guizhou coalfield, China, as a case study, and applied theoretical analysis, numerical simulation, and on-site measurement to develop a circular cave structure model in a key stratum. The dynamic evolution of a separation bed was analyzed from several aspects, including the formation mechanism, development location, the mechanical condition of local karst caves, fracture evolution, and fractal rules. Verification using in situ measurements is presented for the case study mine, and a quantitative evaluation method for water inrush from bed separation and improved fusion weighting is proposed based on a cloud model. The research results indicate the following: (1) Tensile cracks are prone to occur above and below a karst cave, which produce an impact of connectivity on the separated space. (2) When the working face advances to 270 m in coal mining, longitudinal tensile cracks below the karst cave gradually increase and the width of the bed separation crack shrinks to 68.2 m, with a maximum separation layer height of 3.01 m. (3) Based on the cloud model and the improved weighted fusion method, the risk of water inrush in bed separation is judged as “high”. The En of the cloud digital features is 0.0622 and the He is 0.0307, achieving a quantitative evaluation of water inrush in the separation layer that is consistent with on-site practice, and is highly stable and reliable. This study improves the understanding of the development pattern of bed separation and water inrush risk assessment in coal seam mining under a karst cave landform.
Synthesis, Characterization, and Performance of Nano-Metal-Oxide (Al2O3) Blended Biochar for the Removal of Iron from Contaminated Water for Enhanced Kinetic and Adsorption Studies
Authors: Khan Aftab Ahmad , Iqbal Javed , Bashir Muhammad Tariq , Amin Muhammad Tahir , Sikandar Muhammad Ali , Rahman Muhammad Muhitur , Arifuzzman Md.
Published: December 2023

This paper explored synthesis, characterization, and adsorption modeling for the application of nano-metal-oxide (Al2O3) blended biochar (NMOBC) derived from date palm waste in removing iron (Fe3+) from contaminated water. The pseudo-second-order model provided a goodness-of-fit that was superior to the pseudo-first-order kinetic model based on the value of R2 with all of the initial concentrations. The Elovich kinetic model also presented a good fit, indicating that chemisorption is a predominant mechanism in the adsorption process. The Langmuir, Freundlich, Redlich-Petersons, Temkin, and Sips models provided an exclusive perspective of the adsorption dynamics based on the high value of R2. However, the Sips model suggested the best fit of all of the employed models, with the lowest RMSE value of 0.0239 mg/g and the maximum adsorption capacity of 22.680 mg/g for NMOBC. Both adsorbents were effectively regenerated and reused in multiple cycles, thus leading to sustainable practices. Numerous analytical techniques, including SEM/EDX, FTIR, and BET, were employed in characterizing the structural, morphological, and functional properties of the synthesized NMOBC and BC. Subsequently, it revealed that the adsorption process and the role of various interactions are attributed to surface area, porosity, and ion exchange.
Optimal Control of Hybrid Photovoltaic/Thermal Water System in Solar Panels Using the Linear Parameter Varying Approach
Authors: Jamaaoui Faycel , Puig Vicenç , Ayadi Mounir
Published: December 2023

During photovoltaic (PV) conversion in solar panels, a part of the solar radiation is not converted to electricity by the cells, producing heat that could increase their temperature. This increase in temperature deteriorates the performance of the PV panel. In this paper, a hybrid PV/thermal (PV/T) water system is proposed to mitigate this problem. This system combines a PV panel and a thermal collector. In this paper, we focused on the modeling and control of this hybrid system in the linear parameter varying (LPV) framework. An optimal linear quadratic regulator (LQR) is proposed to control the PV cell temperature around an optimal value that maximises electricity generation. Since the system model is nonlinear, an optimal LQR gain-scheduling state-feedback control approach based on an LPV representation of the nonlinear model is designed using the Linear Matrix Inequality (LMI) method. The goal is to obtain the maximum electrical power for each solar panel. Since a reduced number of sensors is available, an LPV Kalman filter is also proposed to estimate the system states required by the state-feedback controller. The obtained results in a laboratory setup in simulation are used to assess the proposed approach, showing promise in terms of control performance of the PV/T system.
Assessment of Energy-Efficient Spouted Bed Aerobic Composting Performance for Municipal Solid Waste: Experimental Study
Authors: Kaneesamkandi Zakariya , Sayeed Abdul
Published: December 2023

Municipal solid waste contains a high percentage of organic waste, and when it is not disposed of, it becomes a threat to the environment by contaminating the air, water, and soil. Composting is one of the recovery techniques in which the end product of waste eventually contributes to the agriculture industry, reducing the harmful effects on the environment. Composting municipal solid waste is a clean and effective technique for waste disposal. The mechanized composting process is carried out by several methods, like the windrow method or the rotary drum method. However, large-scale composting processes involve energy consumption and labor costs for waste preparation and handling. This increases the market cost of compost. Hence, an energy-efficient composting technique with minimum environmental impact is needed. This research work aims to analyze the performance of an energy-efficient spouted bed technique for aerobic composting of municipal solid waste for the first time using spouted bed technology with sand as the bed material. Spouted bed composting handles the waste using a pneumatic method with minimum power consumption in comparison to conventional mechanical methods with windrow processes or rotary composting machines. The experimental procedure involves a test run of waste along with bed material and the collection of temperature variations, pH variations, moisture variations, and volatile matter content during the progression of the composting process. The results of this experimental study on a single batch of waste are then used to analyze the quality of the compost generated and compare it with existing results. Specific energy consumption for the process was less than 800 kJ/ton of raw waste input, which is much less than the energy used for conventional composting techniques. pH, volatile content, moisture, and temperature measurements indicated agreement with the established parameters of the composting process.
Internal Tree Trunk Decay Detection Using Close-Range Remote Sensing Data and the PointNet Deep Learning Method
Authors: Hrdina Marek , Surový Peter
Published: December 2023

The health and stability of trees are essential information for the safety of people and property in urban greenery, parks or along roads. The stability of the trees is linked to root stability but essentially also to trunk decay. Currently used internal tree stem decay assessment methods, such as tomography and penetrometry, are reliable but usually time-consuming and unsuitable for large-scale surveys. Therefore, a new method based on close-range remotely sensed data, specifically close-range photogrammetry and iPhone LiDAR, was tested to detect decayed standing tree trunks automatically. The proposed study used the PointNet deep learning algorithm for 3D data classification. It was verified in three different datasets consisting of pure coniferous trees, pure deciduous trees, and mixed data to eliminate the influence of the detectable symptoms for each group and species itself. The mean achieved validation accuracies of the models were 65.5% for Coniferous trees, 58.4% for Deciduous trees and 57.7% for Mixed data classification. The accuracies indicate promising data, which can be either used by practitioners for preliminary surveys or for other researchers to acquire more input data and create more robust classification models.
Pasture Biomass Estimation Using Ultra-High-Resolution RGB UAVs Images and Deep Learning
Authors: Vahidi Milad , Shafian Sanaz , Thomas Summer , Maguire Rory
Published: December 2023

The continuous assessment of grassland biomass during the growth season plays a vital role in making informed, location-specific management choices. The implementation of precision agriculture techniques can facilitate and enhance these decision-making processes. Nonetheless, precision agriculture depends on the availability of prompt and precise data pertaining to plant characteristics, necessitating both high spatial and temporal resolutions. Utilizing structural and spectral attributes extracted from low-cost sensors on unmanned aerial vehicles (UAVs) presents a promising non-invasive method to evaluate plant traits, including above-ground biomass and plant height. Therefore, the main objective was to develop an artificial neural network capable of estimating pasture biomass by using UAV RGB images and the canopy height models (CHM) during the growing season over three common types of paddocks: Rest, bale grazing, and sacrifice. Subsequently, this study first explored the variation of structural and color-related features derived from statistics of CHM and RGB image values under different levels of plant growth. Then, an ANN model was trained for accurate biomass volume estimation based on a rigorous assessment employing statistical criteria and ground observations. The model demonstrated a high level of precision, yielding a coefficient of determination (R2) of 0.94 and a root mean square error (RMSE) of 62 (g/m2). The evaluation underscores the critical role of ultra-high-resolution photogrammetric CHMs and red, green, and blue (RGB) values in capturing meaningful variations and enhancing the model’s accuracy across diverse paddock types, including bale grazing, rest, and sacrifice paddocks. Furthermore, the model’s sensitivity to areas with minimal or virtually absent biomass during the plant growth period is visually demonstrated in the generated maps. Notably, it effectively discerned low-biomass regions in bale grazing paddocks and areas with reduced biomass impact in sacrifice paddocks compared to other types. These findings highlight the model’s versatility in estimating biomass across a range of scenarios, making it well suited for deployment across various paddock types and environmental conditions.
Path Planning of a Mobile Robot for a Dynamic Indoor Environment Based on an SAC-LSTM Algorithm
Authors: Zhang Yongchao , Chen Pengzhan
Published: December 2023

This paper proposes an improved Soft Actor–Critic Long Short-Term Memory (SAC-LSTM) algorithm for fast path planning of mobile robots in dynamic environments. To achieve continuous motion and better decision making by incorporating historical and current states, a long short-term memory network (LSTM) with memory was integrated into the SAC algorithm. To mitigate the memory depreciation issue caused by resetting the LSTM’s hidden states to zero during training, a burn-in training method was adopted to boost the performance. Moreover, a prioritized experience replay mechanism was implemented to enhance sampling efficiency and speed up convergence. Based on the SAC-LSTM framework, a motion model for the Turtlebot3 mobile robot was established by designing the state space, action space, reward function, and overall planning process. Three simulation experiments were conducted in obstacle-free, static obstacle, and dynamic obstacle environments using the ROS platform and Gazebo9 software. The results were compared with the SAC algorithm. In all scenarios, the SAC-LSTM algorithm demonstrated a faster convergence rate and a higher path planning success rate, registering a significant 10.5 percentage point improvement in the success rate of reaching the target point in the dynamic obstacle environment. Additionally, the time taken for path planning was shorter, and the planned paths were more concise.
Analyzing Peak-to-Average Power Ratio Characteristics in Multi-Channel Intensity Modulation and Direct Detection Flexible Transceivers Deploying Inverse Fast Fourier Transform/Fast Fourier Transform-Based Processing
Authors: Chen Lin , Huang Xiaoyu , Jin Wei , Wang Xinyu , Yang Gang , Jiang Mingyang , Huang Yi , Tang Jianming
Published: December 2023

Cascaded inverse fast Fourier transform/fast Fourier transform (IFFT/FFT)-based multi-channel aggregation/de-aggregation offers a promising solution in constructing highly desirable flexible optical transceivers for considerably improving optical networks’ elasticity, flexibility, and adaptability. However, the multi-channel aggregation operation unavoidably results in generated signals having high peak-to-average power ratios (PAPRs). To solve this technical challenge, this paper first explores the PAPR characteristics of the corresponding flexible transceivers in optical back-to-back (B2B) and 20 km intensity modulation and direct detection (IMDD) transmission systems, and then numerically investigates the feasibility and effectiveness of utilizing the conventional clipping techniques in reducing their PAPR reductions. The results show that the last IFFT operation size is the primary factor determining the PAPRs rather than the channel count and modulation format. For a given last IFFT operation size, the optimal clipping ratio can be identified, which is independent of channel count. With the identified optimal clipping ratio, when the channel count is >4, every two-channel increase in the channel count can only lead to <1.2 Gb/s decreases in the maximum aggregated signal transmission capacity.
A Neural Network-Based Random Access Protocol for Crowded Massive MIMO Systems
Authors: Bueno Felipe Augusto Dutra , Yamamura Cézar Fumio , Scalassara Paulo Rogério , Abrão Taufik , Marinello José Carlos
Published: December 2023

Fifth-generation (5G) and beyond networks are expected to serve large numbers of user equipments (UEs). Grant-based random access (RA) protocols are efficient when serving human users, typically with large data volumes to transmit. The strongest user collision resolution (SUCRe) is the first protocol that effectively uses the many antennas at the 5G base station (BS) to improve connectivity performance. In this paper, our proposal involves substituting the retransmission rule of the SUCRe protocol with a neural network (NN) to enhance the identification of the strongest user and resolve collisions in a decentralized manner on the UEs’ side. The proposed NN-based procedure is trained offline, admitting different congestion levels of the system, aiming to obtain a single setup able to operate with different numbers of UEs. The numerical results indicate that our method attains substantial connectivity performance improvements compared to other protocols without requiring additional complexity or overhead. In addition, the proposed approach is robust regarding variations in the number of BS antennas and transmission power while improving energy efficiency by requiring fewer attempts on the RA stage.
TSG-SLAM: SLAM Employing Tight Coupling of Instance Segmentation and Geometric Constraints in Complex Dynamic Environments
Authors: Zhang Yongchao , Li Yuanming , Chen Pengzhan
Published: December 2023

Although numerous effective Simultaneous Localization and Mapping (SLAM) systems have been developed, complex dynamic environments continue to present challenges, such as managing moving objects and enabling robots to comprehend environments. This paper focuses on a visual SLAM method specifically designed for complex dynamic environments. Our approach proposes a dynamic feature removal module based on the tight coupling of instance segmentation and multi-view geometric constraints (TSG). This method seamlessly integrates semantic information with geometric constraint data, using the fundamental matrix as a connecting element. In particular, instance segmentation is performed on frames to eliminate all dynamic and potentially dynamic features, retaining only reliable static features for sequential feature matching and acquiring a dependable fundamental matrix. Subsequently, based on this matrix, true dynamic features are identified and removed by capitalizing on multi-view geometry constraints while preserving reliable static features for further tracking and mapping. An instance-level semantic map of the global scenario is constructed to enhance the perception and understanding of complex dynamic environments. The proposed method is assessed on TUM datasets and in real-world scenarios, demonstrating that TSG-SLAM exhibits superior performance in detecting and eliminating dynamic feature points and obtains good localization accuracy in dynamic environments.
The Role of Deep Learning Models in the Detection of Anti-Social Behaviours towards Women in Public Transport from Surveillance Videos: A Scoping Review
Authors: Papini Marcella , Iqbal Umair , Barthelemy Johan , Ritz Christian
Published: December 2023

Increasing women’s active participation in economic, educational, and social spheres requires ensuring safe public transport environments. This study investigates the potential of machine learning-based models in addressing behaviours impacting the safety perception of women commuters. Specifically, we conduct a comprehensive review of the existing literature concerning the utilisation of deep learning models for identifying anti-social behaviours in public spaces. Employing a scoping review methodology, our study synthesises the current landscape, highlighting both the advantages and challenges associated with the automated detection of such behaviours. Additionally, we assess available video and audio datasets suitable for training detection algorithms in this context. The findings not only shed light on the feasibility of leveraging deep learning for recognising anti-social behaviours but also provide critical insights for researchers, developers, and transport operators. Our work aims to facilitate future studies focused on the development and implementation of deep learning models, enhancing safety for all passengers in public transportation systems.
Socio-Phenomenological Reflections on What Digital Death Brings and Denies in Terms of Relational Experiences to Orthodox Romanians
Authors: Toplean Adela
Published: December 2023

Informed by Alfred Schütz’s phenomenology of social relations and its recent developments addressing online relationality, this essay reflects on the differences between online and offline death-related experiences in contemporary Romania. In Orthodox death cultures, religious, social, and familial bonds overlap. Orthodox Christianity is sceptical about body–mind separation and values unmediated liturgical communities. It is, thus, pertinent to ask what death online brings and denies in terms of experience to Romanian internet users. Some preliminary findings from our fieldwork are discussed. So far, on Romanian Facebook, three clusters of experience emerged widely: 1. A realm of belief where faith, unchallenged by digital practices, “decodes” deadly events across life-worlds; 2. Experiences of resistance and ambivalence of those who are stuck “in-between“, that is, those less competent in their traditions, yet sceptical about digital change; 3. Death experiences seem less synchronised across life-worlds for those who value electronic proximity: digital death and real death obey different rules. Historical specificity, we shall conclude, sets typified combinations of motives for what Romanians do in the proximity of death and how they do it. Digital technologies modulate the “hows” and, less notably, the “whats”.
Exploring the Potential of 3D Printing Technology for Sustainable Plastic Roads: A Preliminary Investigation
Authors: Al-Atroush Mohamed Ezzat , Almushcab Jumana , Alhudaif Duha , Meskinyar Yosra
Published: December 2023

The urgency of climate change has highlighted the need for sustainable road construction materials, replacing the conventional asphalt, which significantly contributes to global warming and the urban heat island effect. With this in mind, the construction of the world’s first 30-m plastic road in Zwolle, Netherlands, in 2018, opened the door for novel plastic applications as paving materials. However, its application is currently still limited to sidewalks and light-load cycling lanes. The feasibility of utilizing 3D printing technology to provide the necessary structural design flexibility for the production of plastic pavement modules that can withstand heavy traffic and extreme weather conditions was examined in this preliminary study. The suitability of six plastic materials (PLA, PETG, ABS, TPU, Nylon, and polycarbonate) for 3D printing was evaluated. Polylactic acid (PLA), and polyethylene terephthalate glycol (PETG) were identified as the most suitable materials for this study. Three small-scale structural systems, namely hollow modular with plastic columns, hollow modular with solid plastic cones, and hollow modular with X-bracing, were designed and successfully printed using the adopted materials and a 3D printer. The developed systems were subsequently subjected to compression testing to assess their structural performance under heavy traffic loads and demonstrate the feasibility of the concept. The results showed that the PLA conic structural system was effective and exhibited the highest compression strength, while the PETG conic system exhibited ductile behavior with superior thermal stability. The study suggests that the hybrid system of PLA and PETG materials may improve the overall performance, combine flexibility and strength, and potentially improve the resistance to extreme weather and heavy traffic. These findings prove that 3D printing technology has the potential to revolutionize the road construction industry and provide more sustainable solutions for infrastructure development.
The Mediating Role of Dynamic Capability on the Relationship between E-Leadership Qualities and Innovation Management: Insights from Malaysia’s Medical Device Industry
Authors: Subramaniam Suguneswary , Salamzadeh Yashar , Mujtaba Bahaudin
Published: December 2023

The current research plans to investigate the role of e-leadership qualities in managing innovation with dynamic capability as a mediator with the aim to assess and measure how the rapidly changing demands are fulfilled for business sustainability through innovation management. Data have been obtained from a quantitative survey of 145 respondents using the stratified random sampling method. The samples were obtained from the medical device manufacturers located and registered in Malaysia. Data analysis was performed using Partial Least Square Structural Equation Modelling (PLS-SEM). The results show a significant influence of e-leadership qualities on innovation management indirectly with the mediating role of dynamic capabilities. Dynamic capabilities have a strong relationship with innovation management. This research shows the importance of different dimensions of e-leadership qualities in managing innovation for policy makers and practitioners and the impact of dynamic capabilities. Policy makers and managers can use these findings to use their resources to enhance their qualities and capabilities to perform better in managing innovation, which is among the top priorities of Malaysia at the national level. The results extend the literature on e-leadership qualities by empirically testing the relationship between innovation management and dynamic capability and by adding new contextual knowledge to the medical device industry.
Spatial Indices for Convivial Greenstreets
Authors: Kriehn Emmy , Tamminga Kenneth , Flohr Travis
Published: December 2023

Streetside gardening is an informal, resident-initiated activity undertaken in dense urban areas worldwide. Yardless urban areas with a high incidence of informal streetside gardening are called Convivial Greenstreets (CG). Site investigations in European and several U.S. cities over the last decade suggest that social, ecological, and local climate benefits may be found where CG are most intense. The aim of this research is to fill a gap in the research literature by better understanding the spatial distribution of CG and the potential benefits associated with them. Using inner-core neighborhoods in Delft, The Netherlands, and Philadelphia, USA, as test cases, we devised a Convivial Greenstreet Intensity (CGI) index to provide a consistent method for mapping and comparing levels of streetside gardening activity across neighborhoods and cities. We show that CG spatial patterning and quantification of informal gardening intensity using in situ documentation and integrated GIS and Google Earth analyses are feasible and should prove useful as a basis for further research. With the development of a reliable method for measuring and mapping informal streetside gardening activity with a focus on visually accessible biomass, we hope that opportunities for investigating links between convivial greenstreets and urban microclimatic and physical and mental health will be facilitated.
Mineral Resource Abundance: An Assessment Methodology for a Responsible Use of Mineral Raw Materials in Downstream Industries
Authors: Charles Nicolas , Lefebvre Gaétan , Tuloup Rémy , Carreaud Audrey , Boubault Antoine , Serrand Anne-Sophie , Picault Maxime , Piguet Virginie , Manzin Valeria , Deswarte Fabien , Aupoil Julien
Published: December 2023

The sustainability of mineral resources and, in particular, their abundance is a topic of growing interest. Nevertheless, the abundance of mineral raw materials is an extremely complex notion as it not only encompasses geological considerations but also environmental, technical, economic, and social constraints. In addition, to the best of our knowledge, no tools are currently available to allow a comprehensive evaluation of mineral raw material abundance. This research paper, therefore, aims to present an innovative and unique methodology to evaluate the abundance of non-energy mineral resources and determine a mineral abundance index (MAI). Based on a multicriteria analysis, MAI considers the natural abundance of a mineral raw material in the Earth’s crust and its availability on the market and integrates the influence of factors that could constrain or promote future market changes. This new index ranging from 0 (very scarce) to 100 (very abundant) aims to qualify the abundance of mineral resources in a simple and rapid manner based on published and reliable data. This new methodology could be a powerful decision-making support tool for any downstream industrials and end-users making use of mineral raw materials.
Are Human Development and Innovativeness Levels Good Predictors of the Competitiveness of Nations? A Panel Data Approach
Authors: Cetinguc Basak , Calisir Fethi , Guven Murat , Guloglu Bulent
Published: December 2023

Nations must adapt to the changing and developing world to sustain and develop their competitiveness. Human development and innovation are the two key concepts to increase the competitiveness of a nation. This study aims to examine the relationship between the Human Development Index (HDI), Global Innovation Index (GII), and Global Competitiveness Index (GCI) across different income groups from 2010 to 2019. The main objective is to identify potential variations in these relationships based on the income level of the countries involved. Panel data analyses using Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are conducted to examine the relationships. Additionally, Pairwise Dumitrescu Hurlin Panel Causality Tests are conducted to examine the causal relationships between variables. The results show that HDI has a significant positive effect on GCI in each income group. Improving human development such as raising living standards and providing equal education opportunities for every member of society can contribute to a country’s competitiveness. Moreover, it is found that the effect of GII on GCI varies by income group. Specifically, the results indicate that the effect of GII on GCI is not supported for upper-middle-income countries. Therefore, while developing strategies to increase competitiveness through innovation, it is important to consider the income group of a nation. The findings of this study may assist policymakers, researchers, academics, and politicians to enhance their perspectives and formulate strategic and effective recommendations for action.
Investigating the Link between Consumer Attitudes and Behaviour in the Context of Sustainable Clothing: The Role of Social Norms
Authors: Banytė Jūratė , Vaidelinskaitė Šarūnė , Šalčiuvienė Laura
Published: December 2023

This study investigates the sustainable clothing consumer attitude–behaviour link and identifies the role of social norms in this relationship. A total of 218 responses were collected in an online survey in one small European country. Findings reveal that sustainable clothing purchase behaviour is influenced by consumer attitudes towards sustainable clothing and sustainable clothing purchase intention, which acts as a mediator between consumer attitudes towards sustainable clothing and purchase behaviour. The findings uncover three types of social norms that could be represented among individuals in Lithuania, but no moderating effects were found. Unexpected results reveal that one type of social norms, that is, social order/commandment norms, influences both consumer attitudes towards sustainable clothing and their intention to purchase sustainable clothing. These findings attempt to contribute to the sustainable clothing consumer behaviour field development. Managerial implications of how to induce a change in consumer attitude and sustainable clothing purchase intentions for business leaders and public policy makers have been offered.
Teachers and Students as Promoters or Repressors of Sustainable Education: Navigating the Blended Learning Landscape
Authors: Boskovic Dusanka , Husremovic Dzenana , Muslic Merima , Kapo Amra
Published: December 2023

Technology is acting as a catalyst for the transformation towards sustainability in education and as a means of reshaping the educational experience. This transformation is part of an overall transformation in our society, and education should be dedicated to creating satisfied students able to think autonomously, take responsibility for their views, and contribute to society. Both sustainable education and education for sustainability benefit from blended learning, which facilitates participatory teaching and empowers learners. The aim of our research was to determine teachers’ and students’ (a) awareness of the development of digital platforms for teaching and learning, (b) perception of their own digital skills, (c) use and experience of Coursera, and (d) attitudes towards the content and benefits of digital platforms, such as Coursera, for teaching and learning. The analysis was carried out using a questionnaire in which we collected feedback from students and teachers at the University of Sarajevo about their awareness and preferences of the contents offered by Coursera and their readiness to use those additional learning and teaching resources. The results of this study show that there is a lack of awareness of online e-learning platforms among students, with more than half of the sample professing ignorance about these sites. The identified lack of experience and a noticeable lack of motivation could present significant repressors in the transformation of education if not addressed properly.
A New Solution to the Strong CP Problem
Authors: Larin Sergey A.
Published: December 2023

We suggest a new solution to the strong CP problem. The solution is based on the proper use of the boundary conditions for the QCD-generating functional integral. We expand the perturbative boundary conditions to both perturbative and nonperturbative fields integrated into the QCD-generating functional integral. It allows us to nullify the CP odd term in the QCD Lagrangian and, thus, to solve the strong CP problem. The presently popular solution to the strong CP problem of introducing axions violates the principle of renormalizability of the Quantum Field Theory, which is very successful phenomenologically. Our solution obeys the principle of renormalizability of the Quantum Field Theory and does not involve new exotic particles like axions.
Freshwater Lacustrine Zooplankton and Microplastic: An Issue to Be Still Explored
Authors: Lawrence Jassica , Santolini Carlotta , Binda Gilberto , Carnati Stefano , Boldrocchi Ginevra , Pozzi Andrea , Bettinetti Roberta
Published: December 2023

Lakes are essentially interlinked to humans as they provide water for drinking, agriculture, industrial and domestic purposes. The upsurge of plastic usage, its persistence, and potential detrimental effects on organisms cause impacts on the trophic food web of freshwater ecosystems; this issue, however, still needs to be explored. Zooplankton worldwide is commonly studied as an indicator of environmental risk in aquatic ecosystems for several pollutants. The aim of the review is to link the existing knowledge of microplastic pollution in zooplankton to assess the potential risks linked to these organisms which are at the first level of the lacustrine trophic web. A database search was conducted through the main databases to gather the relevant literature over the course of time. The sensitivity of zooplankton organisms is evident from laboratory studies, whereas several knowledge gaps exist in the understanding of mechanisms causing toxicity. This review also highlights insufficient data on field studies hampering the understanding of the pollution extent in lakes, as well as unclear trends on ecosystem–level cascading effects of microplastics (MPs) and mechanisms of toxicity (especially in combination with other pollutants). Therefore, this review provides insight into understanding the overlooked issues of microplastic in lake ecosystems to gain an accurate ecological risk assessment.
The Impact of Quadriceps Muscle Layer Thickness on Length of Stay of Patients Listed for Renal Transplant
Authors: Levine Max , Luke Patrick , Sener Alp , Resvick Heather , Braga Stephanie , St. Kitts Taralynn , De Marinis Sarah , Madill Janet
Published: December 2023

Background: Quadriceps muscle layer thickness (QMLT), which is measured using ultrasound, is an emerging strategy to identify sarcopenia. Purpose: The purpose of the study was to assess whether pre-operative QMLT values are associated with a prolonged length of stay (LOS; defined as >14 days) following a renal transplant. Methods: Between March 2019 and January 2020, we performed a prospective study among patients undergoing renal transplantation. Physical Frailty scores and QMLT measurements were performed pre-operatively. The primary outcome was a greater LOS following transplant. Secondary outcomes included complications and renal function. Statistical analysis: Percentiles divided patients into two categories of QMLT (low and high). Continuous outcomes were compared using a two-sided t-test or Mann–Whitney U test, and Chi-square analysis and Fisher exact testing were used for nominal variables. Results: Of 79 patients, the frailty prevalence was 16%. Among patients with low and higher QMLTs, LOS of >14 days were 21% vs. 3% [p = 0.04], respectively. Demographically, there was a higher percentage of patients with living donors in the high- vs. low-QMLT groups (40 vs. 7%). However, in a subgroup analysis excluding living-donor recipients, the difference between groups was preserved (23% vs. 0%, p = 0.01). No differences in secondary outcomes were seen between groups. Conclusions: Low quadriceps muscle layer thickness may be associated with a prolonged length of stay for renal recipients. Further research is needed to confirm our findings.
Evaluation of Loop-Mediated Isothermal Amplification (LAMP) in Urine Samples for the Diagnosis of Imported Schistosomiasis
Authors: Salas-Coronas Joaquín , Luzón-García María Pilar , Crego-Vicente Beatriz , Soriano-Pérez Manuel Jesús , Febrer-Sendra Begoña , Vázquez-Villegas José , Diego Juan García-Bernalt , Cabeza-Barrera Isabel María , Castillo-Fernández Nerea , Muro Antonio , Bargues María Dolores , Fernández-Soto Pedro
Published: December 2023

Migratory flows and international travel are triggering an increase in imported cases of schistosomiasis in non-endemic countries. The present study aims to evaluate the effectiveness of the LAMP technique on patients’ urine samples for the diagnosis of imported schistosomiasis in a non-endemic area in comparison to a commercial immunochromatographic test and microscopic examination of feces and urine. A prospective observational study was conducted in sub-Saharan migrants attending the Tropical Medicine Unit, Almería, Spain. For schistosomiasis diagnosis, serum samples were tested using an immunochromatographic test (Schistosoma ICT IgG-IgM). Stool and urine samples were examined by microcopy. Urine samples were evaluated by combining three LAMP assays for the specific detection of Schistosoma mansoni, S. haematobium, and for the genus Schistosoma. To evaluate the diagnostic accuracy, a latent class analysis (LCA) was performed. In total, 115 patients were included (92.2% male; median age: 28.3 years). Of these, 21 patients (18.3%) were diagnosed with schistosomiasis confirmed by microscopy, with S. haematobium being the most frequent species identified (18/115; 15.7%). The Schistosoma ICT IgG-IgM test result was 100% positive and Schistosoma-LAMP was 61.9% positive, reaching as high as 72.2% for S. haematobium. The sensitivity and specificity estimated by LCA, respectively, were: 92% and 76% for Schistosoma ICT IgG-IgM, 68% and 44% for Schistosoma-LAMP, and 46% and 97% for microscopy. In conclusion, the Schistosoma-LAMP technique presented a higher sensitivity than microscopy for the diagnosis of imported urinary schistosomiasis, which could improve the diagnosis of active infection, both in referral centers and in centers with limited experience or scarce resources and infrastructure.
Comparison between Sampling Techniques for Virological Molecular Analyses: Dolphin Morbillivirus and Herpesvirus Detection from FTA® Card and Frozen Tissue
Authors: Si Haiyang , Tucciarone Claudia Maria , Cecchinato Mattia , Legnardi Matteo , Mazzariol Sandro , Centelleghe Cinzia
Published: December 2023

Stranded animals offer valuable information on marine mammal physiology and pathology; however, the decomposition state of the carcasses and lack of a rigorous cold chain for sample preservation can sometimes discourage diagnostic analyses based on nucleic acid detection. The present paper aims at evaluating the reliability of FTA® card tissue imprints as an alternative matrix to frozen tissues for virological analyses based on biomolecular methods. Given the contribution of Cetacean morbillivirus (CeMV) to strandings and the increase of herpesvirus detection in cetaceans, these two pathogens were selected as representative of RNA and DNA viruses. Dolphin morbillivirus (DMV) and herpesvirus presence was investigated in parallel on tissue imprints on FTA® cards and frozen tissues collected during necropsy of dolphins stranded in Italy. Samples were analysed by nested RT-PCR for DMV and nested-PCR for herpesvirus. Only one animal was positive for herpesvirus, hampering further considerations on this virus. DMV was detected in all animals, both in FTA® card imprints and tissue samples, with differences possibly related to the decomposition condition category of the carcasses. Tissue sampling on FTA® cards seems a promising alternative to frozen tissues for biomolecular analyses, especially when ensuring adequate storage and shipment conditions for frozen tissues is difficult.
Characterization of a New Toti-like Virus in Sea Bass, Dicentrarchus labrax
Authors: Louboutin Lénaïg , Cabon Joëlle , Beven Véronique , Hirchaud Edouard , Blanchard Yannick , Morin Thierry
Published: December 2023

The European sea bass Dicentrarchus labrax is the main species reared in Mediterranean aquaculture. Its larval stage, which is very sensitive and highly affected by sanitary and environmental conditions, is particularly scrutinized in hatcheries. Recently, a Mediterranean sea bass farm had to deal with an abnormal increase in mortality, especially between 20 and 35 days post-hatching (dph). Biological investigations led to the observation of cytopathic effects on three different fish cell lines after almost 3 weeks of culture at 14 °C in contact with homogenized affected larvae, suggesting the presence of a viral agent. High-throughput sequencing revealed a 6818-nucleotide-long RNA genome with six putative ORFs, corresponding to the organization of viruses belonging to the Totiviridae family. This genome clustered with the newly described and suggested Pistolvirus genus, sharing 45.5% to 37.2% nucleotide identity with other piscine toti-like viruses such as Cyclopterus lumpus toti-like virus (CLuTLV) or piscine myocarditis virus (PMCV), respectively. Therefore, we propose to name this new viral agent sea bass toti-like virus (SBTLV). Specific real-time RT-PCR confirmed the presence of the viral genome in the affected larval homogenate from different production batches and the corresponding cell culture supernatant. Experimental infections performed on sea bass fingerlings did not induce mortality, although the virus could be detected in various organs and a specific immune response was developed. Additional studies are needed to understand the exact involvement of this virus in the mortality observed in hatcheries and the potential associated cofactors.
An Estimation of Ecosystem Service Value of Rice Paddy Wetland in Korea Using Contingent Valuation Method
Authors: Myeong Soojeong , Yi Donggyu
Published: December 2023

Agricultural land is an important ecosystem that is essential for human life, and rice paddies, in particular, provide many ecosystem services such as food production and the maintenance of biodiversity. Although the value of rice paddy wetlands is high, they are rapidly disappearing due to urbanization and development. This study aims to estimate the monetary value of the rice paddy wetland ecosystem and investigate the proportion of benefits for each rice paddy wetland function to provide policy implications for rice paddy wetland management. To this end, this study conducted a survey with 988 South Korean citizens regarding rice paddy wetlands and adopted the contingent valuation method (CVM) with various approaches (double-bounded dichotomous choice pooled model, double-bounded dichotomous choice panel model, pseudo referendum model, open-ended question model, etc.). Considering the characteristics of each approach, the present value of the total willingness to pay (WTP) per household was estimated to range from 327 to 347 USD. When extrapolated to the entire country, the total WTP of all households in South Korea is estimated from 6.7 to 7.1 billion USD. This study also finds that households have an average WTP distribution ratio by paddy wetlands function as follows: food supply 33.8%, biodiversity 27.2%, disaster and pollution control 24.2%, and cultural services 14.8%. These findings have policy implications by providing valuable insights for decision-making in determining the priority and allocation levels of financial resources in the future design of policies related to paddy wetlands.
Vape Gods, Vape Lords, and Fiends: The Language of Vaping
Authors: Walker Kandi L. , McLeish Alison C. , Wood Lindsey A. , Hart Joy L.
Published: December 2023

Little attention has been devoted to understanding the language surrounding e-cigarette use. Researchers employ terms such as users of e-cigarettes or ENDS, but language employed outside scholarly writing is relatively unexamined. Thus, this study examined the language used by college students to refer to people who use e-cigarettes. College students (N = 1037; Mage= 20.67, SD = 3.81; 72.1% female; 69.6% White) at a southern U.S. university responded to the open-ended question: “What do you call a person who uses e-cigarettes?” Of 1086 responses, e-cigarette users’ (n = 591) and nonusers’ (n = 495) responses were examined separately. Although users and nonusers had the same two top terms (“vaper” and “smoker”), a clearer consensus existed among users where “vaper” was most common (51.3%) followed by “smoker” (21.0%). These same terms were endorsed by 37.0% and 31.5% of nonusers, respectively. The third most popular responses of users related to addiction (e.g., “addict”, “fiend”; 8.46%), whereas nonusers’ responses indicated they did not know what to call an e-cigarette user (e.g., “I don’t know”; 7.1%). Users were equally likely to use positive (e.g., “Vape God”) and negative (e.g., “fool”) terms, whereas nonusers were nearly six times more likely to use negative terms. Therefore, it may be useful to capitalize on these language trends in health campaigns as well as develop separate messaging for users vs. nonusers.
A kínai nagy fal
Authors: Kraus Karl
Published: December 2023

Karl Kraus (1874–1936) hírnevét elsősorban "Die Fackel" (A fáklya) című folyóiratának köszönheti, amely közel negyven éven át, többé-kevésbé állandó rendszerességgel jelent meg Bécsben. A kezdeti időszakot leszámítva Kraus egymaga írt és szerkesztett minden számot, kifogyhatatlan energiával és nyelvi leleményességgel tűzve bennük tollhegyre a korabeli kultúra visszásságait. Egyszemélyes sajtóhadjáratának elsődleges célpontja maga a média, és ha gyakran úgy is tűnik, hogy társadalomkritikai rohamai során bolhákból csinál elefántot – vagy azt is mondhatnám, egyik kötetének címét kölcsön véve, "ágyúval lő verebekre" –, írásaiból mindig kiérződik, hogy valódi mozgatórugójuk a nyomtatott szó jelentőségébe vetett feltétlen hit. Mindenekelőtt ez adja aktualitását nemcsak főművének, "Az emberiség végnapjai"-nak, hanem tárcáinak és esszéinek is, melyek közül itt négy olvasható.