bluuebunny/crossref_metadata_2025 huggingface dataset:
Iteratively Refined Multi-Channel Speech Separation
Authors: Zhang Xu , Bao Changchun , Yang Xue , Zhou Jing
Published: July 2024

The combination of neural networks and beamforming has proven very effective in multi-channel speech separation, but its performance faces a challenge in complex environments. In this paper, an iteratively refined multi-channel speech separation method is proposed to meet this challenge. The proposed method is composed of initial separation and iterative separation. In the initial separation, a time–frequency domain dual-path recurrent neural network (TFDPRNN), minimum variance distortionless response (MVDR) beamformer, and post-separation are cascaded to obtain the first additional input in the iterative separation process. In iterative separation, the MVDR beamformer and post-separation are iteratively used, where the output of the MVDR beamformer is used as an additional input to the post-separation network and the final output comes from the post-separation module. This iteration of the beamformer and post-separation is fully employed for promoting their optimization, which ultimately improves the overall performance. Experiments on the spatialized version of the WSJ0-2mix corpus showed that our proposed method achieved a signal-to-distortion ratio (SDR) improvement of 24.17 dB, which was significantly better than the current popular methods. In addition, the method also achieved an SDR of 20.2 dB on joint separation and dereverberation tasks. These results indicate our method’s effectiveness and significance in the multi-channel speech separation field.
Design of Robust Broadband Frequency-Invariant Broadside Beampatterns for the Differential Loudspeaker Array
Authors: Zhang Yankai , Wei Hongjian , Zhu Qiaoxi
Published: July 2024

The directional loudspeaker array has various applications due to its capability to direct sound generation towards the target listener and reduce noise pollution. Differential beamforming has recently been applied to the loudspeaker line array to produce a broadside frequency-invariant radiation pattern. However, the existing methods cannot achieve a compromise between robustness and broadband frequency-invariant beampattern preservation. This paper proposed a robust broadband differential beamforming design to allow the loudspeaker line array to radiate broadside frequency-invariant radiation patterns with robustness. Specifically, we propose a method to determine the ideal broadside differential beampattern by combining multiple criteria, namely null positions, maximizing the directivity factor, and achieving a desired beampattern with equal sidelobes. We derive the above ideal broadside differential beampattern into the target beampattern in the modal domain. We propose a robust modal matching method with Tikhonov regularization to optimize the loudspeaker weights in the modal domain. Simulations and experiments show improved frequency-invariant broadside beamforming over the 250–4k Hz frequency range compared with the existing modal matching and null-constrained methods.
Controller of Pneumatic Muscles Implemented in Active Seat Suspension
Authors: Maciejewski Igor , Pecolt Sebastian , Błażejewski Andrzej , Krzyzynski Tomasz , Glowinski Sebastian
Published: July 2024

In this work, we present a study on seat suspension technology that integrates pneumatic muscles, marking a significant advancement in active vibration control. This innovative approach addresses the limitations of traditional suspension systems, providing enhanced comfort and adaptability. A key achievement is the development of a mathematical model for controlling horizontal seat vibration, which serves as a valuable design tool for evaluating seat suspension under various conditions and control strategies. The creation of a custom microcontroller, benchmarked against a standard from National Instruments, highlights the practical applications of this research. Positive results suggest a promising future for this technology in industrial settings, where vibration reduction is critical. The system’s scalability and user-adjustable signal levels further enhance its potential for widespread industrial adoption.
Composite Copolymer Beads Incorporating Red Mud for Water Amendment by Adsorption—Oxidation Processes
Authors: Sandu Teodor , Olaru Elena Alina , Mitran Raul-Augustin , Miron Andreea , Dolana Sorin-Viorel , Zaharia Anamaria , Gavrilă Ana-Mihaela , Dumitru Marinela-Victoria , Chiriac Anita-Laura , Sârbu Andrei , Iordache Tanța-Verona
Published: July 2024

We face significant environmental pollution problems due to various industries, such as the aluminum industry, which generates large amounts of red mud (RM) waste, or agriculture, in which case the use of pesticides creates huge water pollution problems. In this context, the present study offers a better perspective to originally solve both environmental issues. Thus, the main target of the study referred to using RM waste as a filler for preparing composite copolymer beads. Thereafter, this can achieve significant removal of water pollutants due to their adsorption/oxidation characteristics. As evidenced by the changes in chemical structure and composition, thermal stability, morphology, and porosity, RM was homogenously incorporated in poly(acrylonitrile-co-acrylic acid) beads prepared by wet phase inversion. The final assessment for the removal of pesticides by adsorption and oxidation processes was proven successful. In this regard, 2,4-dichlorophenoxyacetic acid was chosen as a model pollutant, for which an adsorption capacity of 16.08 mg/g composite beads was achieved.
A Longitudinal Study on the Adoption of Cloud Computing in Micro, Small, and Medium Enterprises in Montenegro
Authors: Ognjanović Ivana , Šendelj Ramo , Daković-Tadić Milica , Kožuh Ines
Published: July 2024

In recent years, small and medium enterprises worldwide have increasingly adopted digital technologies and cloud computing. The pace of this digital transition has varied across countries, and the socioeconomic conditions during the pandemic have further accelerated the digitalization of enterprises. This situation calls for an examination of the reasons, benefits, and risks associated with enterprises adopting cloud computing in different settings. Our study aimed to collect longitudinal data from 71 Montenegrin micro, small, and medium enterprises. We conducted a repeated measurement study with two measurement periods: 2017 and 2023. The quantitative results were analyzed alongside qualitative data from a semi-structured interview (N = 15) conducted in 2023. The findings revealed substantial shifts in SME attitudes towards cloud computing, highlighting key catalysts and influencing factors such as security, technological accessibility, external expertise, effort expectations, privacy, social influence, perceived security and safety, ease of use, and usefulness. These factors were examined in the context of global digital innovation, the impact of the COVID-19 pandemic, and recent cyberattacks that disrupted national e-services in Montenegro for 3–9 months. The findings provide new insights into how enterprises can become more prepared to effectively use cloud computing.
The Validation of the Defensive Reactive Agility Test in Top-Level Volleyball Male Players: A New Approach to Evaluating Slide Speed Using Witty SEM
Authors: Horička Pavol , Paška Ľubomír , Popowczak Marek , Koźlenia Dawid , Šimonek Jaromír , Domaradzki Jarosław
Published: July 2024

Aim: The aim of the study is to provide a new tool to measure the level of defensive agility objectively. Methods: The sample included 14 elite male volleyball players of the University of Nitra club (22.3 ± 5.7 years). Measurements consisted of body height (BH); body weight (BM); body mass index (BMI), and the defensive agility test (DRAT (test-retest)) with an interval of one week between the two tests using an electronic timer (Witty photocell) and Witty SEM lights (Microgate, ITA). The validation included assessing the equality of mean values in the test and retest (t-Student), effect sizes with Cohen’s d, analysis of variance (ANOVA), intraclass correlation coefficient determinations (ICC model), and random intercept correlation (Φ). Results: The results indicated no significant differences in both tests except for left movement (p = 0.0255). The ICC value of the test time was statistically significant (0.91); standard error of measurement (SEM = 0.02); repeatability coefficient (RC = 0.20); minimal difference (MD = 0.04). Effect sizes were trivial to small (d = ˂−0.05–0.17>; right), medium (d = 0.35; backward) a large (d = −0.67; left). Conclusions: The DRAT test showed excellent reliability in total time (ICC = 0.91). Validation of the DRAT test’s consistency, reliability, accuracy and validity can help coaches make decisions about evaluating and monitoring defensive reactive agility performance in sports games.
Lawsonia inermis as an Active Corrosion Inhibitor for Mild Steel in Hydrochloric Acid
Authors: Okore Glory , Ejiogu Blessing , Okeke Pamela , Amanze Kenneth , Okore Sunday , Oguzie Emeka , Enyoh Christian Ebere
Published: July 2024

Corrosion is a pervasive issue affecting metallic materials, with significant economic losses and safety risks in various industries. Mild steel, extensively used in construction and infrastructure, faces corrosion challenges, needing continuous research to effectively tackle them. Natural compounds, because of their eco-friendliness and corrosion inhibition potential, are attracting increasing interest for corrosion control. Lawsonia inermis (LI), or henna, a plant native to North Africa and South Asia, has bioactive compounds exhibiting corrosion inhibitive properties. This study comprehensively explores Lawsonia inermis’s effectiveness as a corrosion inhibitor for mild steel, filling a gap in the existing research. Various concentrations of Lawsonia inermis extract were tested in acidic solutions to evaluate corrosion inhibition. Experimental results indicate a significant reduction in the corrosion rate with increasing inhibitor concentration. Langmuir adsorption isothermal analyses reveal the adsorption mechanism as being an interplay between physisorption and weak chemisorption. Electrochemical measurements demonstrate Lawsonia inermis’s capability to alter both cathodic and anodic reactions, leading to improved corrosion resistance. Scanning electron microscopy reveals a more even surface morphology in the presence of the Lawsonia inermis, indicating corrosion inhibition. Gas chromatography–mass spectrometry (GC-MS) analyses identified organic compounds in Lawsonia inermis extract responsible for corrosion inhibition. Overall, Lawsonia inermis emerges as a promising corrosion inhibitor for mild steel, offering excellent inhibition efficiencies. This study sheds light on its adsorption behaviour and provides insights into its mechanism of action. These findings underscore Lawsonia inermis’s potential as a green corrosion inhibitor, paving the way for its practical application in industrial corrosion protection strategies.
A Machine Learning Approach to Evaluating the Impact of Natural Oils on Alzheimer’s Disease Progression
Authors: Amawi Rema M. , Al-Hussaeni Khalil , Keeriath Joyce James , Ashmawy Naglaa S.
Published: July 2024

Alzheimer’s Disease is among the major chronic neurodegenerative diseases that affects more than 50 million people worldwide. This disease irreversibly destroys memory, cognition, and the overall daily activities which occur mainly among the elderly. Few drugs are approved for Alzheimer’s Disease management despite its high prevalence. To date, the available drugs in the market cannot reverse the damage of neurons caused by the disease leading to the exacerbation of symptoms and possibly death. Medicinal plants are considered a rich source of chemical constituents and have been contributing to modern drug discovery in many therapeutic areas including cancer, infectious, cardiovascular, neurodegenerative and Central Nervous System (CNS) diseases. Moreover, essential oils that are extracted from plant organs have been reported for a wide array of biological activities, and their roles as antioxidants, antiaging, cytotoxic, anti-inflammatory, antimicrobial, and enzyme inhibitory activities. This article highlights the promising potential of plants’ essential oils in the discovery of novel therapeutic options for Alzheimer’s Disease and halting its progression. In this article, 428 compounds were reported from the essential oils isolated from 21 plants. A comparative study is carried out by employing a variety of machine learning techniques, validation, and evaluation metrics, to predict essential oils’ efficacy against Alzheimer’s Disease progression. Extensive experiments on essential oil data suggest that a prediction accuracy of up to 82% can be achieved given the proper data preprocessing, feature selection, and model configuration steps. This study underscores the potential of integrating machine learning with natural product research to prioritize and expedite the identification of bioactive essential oils that could lead to effective therapeutic interventions for Alzheimer’s Disease. Further exploration and optimization of machine learning techniques could provide a robust platform for drug discovery and development, facilitating faster and more efficient screening of potential treatments.
Perceived Accessibility: Impact of Social Factors and Travel Modes in Melbourne’s West
Authors: Chau Hing-Wah , Gaisie Eric , Jamei Elmira , Chan Melissa , Lättman Katrin
Published: July 2024

Accessibility is commonly defined and operationalised through objective measurements, such as travel time and physical distance to destinations; however, there is a lack of empirical studies capturing perceived accessibility from individual perspectives. With the aim of sustainable transport for inclusive communities, it is crucial to investigate the impact of socio-economy and travel mode on perceived accessibility and key driving factors of perceived safety and service quality. Through the collection of primary data from one of the fastest-growing suburbs in Melbourne, this study examined variation of perceptions towards accessibility, safety, and service quality among diverse social groups and travellers using different modes of transport. The findings of this study would assist transport planners in making informed decisions in creating inclusive transport networks that can improve community health and well-being.
The Effect of Energy Management in Heating–Cooling Systems of Electric Vehicles on Charging and Range
Authors: Kılıç Muhsin , Korukçu Mehmet Özgün
Published: July 2024

In this study, an energy management model for electric vehicles including the entire vehicle such as the cabin, electric motors, battery, and the heating–cooling system was prepared. The heating and cooling processes for electric vehicles were run according to the internationally recognized driving cycles as well as at constant speeds to investigate them under different ambient conditions. The heating–cooling processes were managed in line with the cabin temperature target determined by considering the comfort conditions. The energy consumption of each of the system elements and the system in the heating–cooling process in electric vehicles was analyzed. Under different operating conditions, the variation of cabin temperature with time, instantaneous power, and cumulative energy consumption was calculated. The effect of heating and cooling processes on energy consumption, charging rate, and range were analyzed and interpreted. The results showed that the heating–cooling system for the heating process consumed more energy when the ambient temperature decreased, and the charge consumption ratio as well as the range deformation rate increased to about 30% when the ambient temperature was –10 °C. Similarly, the heating–cooling system for the cooling process consumed more energy when the ambient temperature increased, and the charge consumption ratio as well as the range deformation rate reached up to 40% when the ambient temperature was 40 °C. When the outdoor conditions were close to the thermal comfort temperature of 23 °C inside the cabin, the total energy consumption and the range deformation rates were reduced to less than 10%.
Topological Interlocking Assembly: Introduction to Computational Architecture
Authors: Miodragovic Vella Irina , Markovic Sladjana
Published: July 2024

Topological interlocking assembly (TIA) and computational architecture treat form as an emergent property of a material system, where the final shape results from the interplay of geometries and geometric interdependencies influenced by contextual constraints (material, structure, and fabrication). This paper posits that TIA is an ideal pedagogical tool for introducing students to computational architecture, and its theoretical foundations and design principles. Specifically, defining TIA as a material system provides a robust educational approach for engaging students with computation; fostering design processes through bottom-up, hands-on investigations; expressing design intents as procedural logic; understanding generative geometric rules; and exploring the flexibility of parametric variations. The methodology is detailed and illustrated through a design workshop and study unit from the Bachelor’s and Master’s programs at the Faculty for the Built Environment, University of Malta. Four case studies of TIA—of tetrahedra, cones, octahedra, and osteomorphic blocks—demonstrate how these exercises introduce students to computational thinking, parametric design, and fabrication techniques. This paper discusses the advantages and limitations of this pedagogical methodology, concluding that integrating computational architecture in education shifts students’ design processes to investigation and innovation-based approaches, enabling them to address contemporary design challenges through context-driven solutions.
A High-Precision Sub-Grid Parameterization Scheme for Clear-Sky Direct Solar Radiation in Complex Terrain—Part I: A High-Precision Fast Terrain Occlusion Algorithm
Authors: Li Changyi , Wu Wei , Chen Yanan , Feng Guili , Chen Bin , Wen Xiaopei
Published: July 2024

In atmospheric modeling, sub-grid parameterization is an important method for studying the topographic effects of solar radiation using high-resolution Digital Elevation Model (DEM) data. For reducing the amount of computation, some approximate methods that can lead to errors are used in existing sub-grid parameterization schemes for clear-sky direct solar radiation (SPS-CSDSR). The lack of a high-precision fast terrain occlusion algorithm (HPFTOA) remains one of the biggest constraints in this field. This study proposed an HPFTOA. It mainly uses two kinds of acceleration algorithms. One method is to use a dynamic, lossless, and fast occlusion search radius. Another way is to use the rectangular grid for calculations within the accuracy of DEM data to avoid coordinate projection conversions. The test results indicate that the HPFTOA can carry out large-scale computation based on DEM data with a resolution of 90 m. Because it rarely uses approximation algorithms and considers the curvature of the Earth, SPS-CSDSR can achieve unprecedented precision. The HPFTOA can also be used in the fields of mountain solar energy assessment, remote sensing, and telemetry, including terrain-obscuring the probe. As computer performance improves and algorithms and execution code are optimized, the application prospects will be very broad.
A High-Precision Sub-Grid Parameterization Scheme for Clear-Sky Direct Solar Radiation in Complex Terrain—Part II: Considering Atmospheric Transparency Differences in Sub-Grid; Pre-Research for Application
Authors: Li Changyi , Chen Bin , Wu Wei , Chen Yanan , Feng Guili , Wen Xiaopei
Published: July 2024

Existing sub-grid parameterization schemes for clear-sky direct solar radiation (SPS-CSDSR) assume that the sub-grid cells have the same atmospheric transparency. This study shows that in undulating terrain, significant errors can occur when the sub-grid is in turbid weather or partly above the cloud top. A correction factor was proposed. It can effectively eliminate errors under a cloudless sky and can reduce some errors when part of the sub-grid is above the cloud or fog top. For atmospheric models with high horizontal resolution, example test verification shows that the cast shadowless coverage method can lead to large errors. It should no longer be used based on current computing power. These improvements and the high-precision fast terrain occlusion algorithm in Part I will allow SPS-CSDSR to achieve unprecedented high accuracy. Based on the proposed daily interpolation method, the high-precision SPS-CSDSR is also feasible for regional climate simulation. The analysis pointed out that the sub-grid terrain radiative effect (STRE) is distributed over inclined surfaces with larger areas and at different heights. Existing methods of coupling STRE on one flat surface have certain physical drawbacks. This paper suggests introducing parameterization of STRE at different altitudes and improving the coupling of land–air.
Multi-Year Continuous Observations of Ambient PM2.5 at Six Sites in Akure, Southwestern Nigeria
Authors: Saetae Sawanya , Abulude Francis Olawale , Ndamitso Mohammed Mohammed , Akinnusotu Akinyinka , Oluwagbayide Samuel Dare , Matsumi Yutaka , Kanegae Kenta , Kawamoto Kazuaki , Nakayama Tomoki
Published: July 2024

The spatial–temporal variations of fine particulate matter (PM2.5) in Akure, a city in southwestern Nigeria, are examined based on multi-year continuous observations using low-cost PM2.5 sensors at six different sites. The average annual concentration of PM2.5 across these sites was measured at 41.0 µg/m3, which surpassed both the Nigerian national air quality standard and the World Health Organization air quality guideline level. PM2.5 levels were significantly higher during the dry season (November–March), often exceeding hazardous levels (over 350 µg/m3), than during the wet season. The analyses of trends in air mass trajectories and satellite data on fire occurrences imply that the transport of dust and accumulation of PM2.5 originating from local/regional open burning activities played crucial roles in increased PM2.5 concentrations during the dry season. Further, site-to-site variations in the PM2.5 levels were observed, with relatively high concentrations at less urbanized sites, likely due to high local emissions from solid fuel combustion, waste burning, and unpaved road dust. Diurnal patterns showed morning and evening peaks at less urbanized sites, accounting for an estimated 51–77% of local emissions. These results highlight the importance of local emission sources in driving spatial–temporal PM2.5 variations within the city and the need for targeted mitigation strategies to address the significant air pollution challenges in Akure and similar regional cities in West Africa.
Investigating Equatorial Plasma Depletions through CSES-01 Satellite Data
Authors: De Michelis Paola , Consolini Giuseppe , Alberti Tommaso , Pignalberi Alessio , Coco Igino , Tozzi Roberta , Giannattasio Fabio , Pezzopane Michael
Published: July 2024

Ionospheric plasma density irregularities, which are one of the primary sources of disturbance for the Global Navigation Satellite System, significantly impact the propagation of electromagnetic signals, leading to signal degradation and potential interruptions. In the equatorial ionospheric F region after sunset, certain plasma density irregularities, identified as equatorial plasma bubbles, encounter optimal conditions for their formation and development. The energy spectra of electron density fluctuations associated with these irregularities exhibit a power-law scaling behavior qualitatively similar to the Kolmogorov power law observed in fluid turbulence theory. This intriguing similarity raises the possibility that these plasma density irregularities may possess turbulent characteristics. In this study, we analyzed electron density, temperature, and pressure data obtained from the China Seismo-Electromagnetic Satellite (CSES-01) to delve into the spectral properties of equatorial plasma depletions in the ionospheric F region at an altitude of about 500 km. This research marks the first exploration of these properties utilizing CSES-01 data and focuses on 14 semi-orbits that crossed the equator after midnight (01:00–03:00 LT), characterized by a geomagnetic quiet condition (Kp < 1). The analysis of electron temperature, density and pressure within equatorial plasma depletions revealed power-law scaling behavior for all the selected parameters. Notably, the spectral index values of these parameters are different from each other. The significance of these findings in terms of investigating plasma depletions via magnetic field signatures, as well as their relationship to the occurrence of Rayleigh–Taylor convective turbulence, is examined and discussed.
Testing Strategies for Planting Design in Urban Squares to Improve Human Comfort throughout the Seasons
Authors: Stark da Silva Priscila Weruska , Duarte Denise Helena Silva , Rahman Mohammad Asrafur , Rötzer Thomas , Pauleit Stephan
Published: July 2024

Green urban squares are essential in densely built neighborhoods and enhance their quality of life. Investment in the greening of urban areas will have a beneficial impact, particularly regarding human thermal comfort. Smaller than parks, squares can be easily spread over the cities and should be part of any neighborhood. While the cooling effect of green squares during hot summer days is increasingly well established, microclimatic assessments during all seasons are still missing. This study aimed to determine whether it is possible to identify an optimal greenery design that maximizes human thermal comfort, as indexed by physiological equivalent temperature (PET), in temperate climates across all seasons. This study employed a “research by design” methodology, utilizing the micrometeorological simulation model ENVI-met to analyze the impact of greenery on PET improvement across different seasons. The objective was to identify the most effective combination of greenery for PET improvement. To achieve these objectives, two urban squares in Munich, Germany were selected. This selection was based on the assumption that typical greening practices, exemplified by the presence of trees, shrubs, and grass, would significantly impact urban squares and their microclimatic effects on human thermal comfort. The small square with a grass surface underneath trees, Alpenplatz, is highly influenced by the surrounding buildings, affecting the sky view factor (SVF), a crucial aspect of the urban environment. Marstallplatz, an open, large square that is not highly affected by urban morphology, was analyzed through simulation scenarios combining grass, shrubs, and trees. The results demonstrate that hot summer days are of primary concern for climate-sensitive urban square design in order to avoid health risks and thus need to be prioritized without compromising comfort for cold days. To attend to both needs, increasing the number of deciduous trees for shading during the day and the amount of grass to enhance air cooling at night are particularly effective. Nevertheless, microclimate design for the spring and autumn periods must also be considered, with the provision of adaptable opportunities for sheltered and sun-exposed spaces.
Identification of an Unknown Stationary Emission Source in Urban Geometry Using Bayesian Inference
Authors: Gkirmpas Panagiotis , Tsegas George , Ioannidis Giannis , Vlachokostas Christos , Moussiopoulos Nicolas
Published: July 2024

Estimating the parameters of an unidentified toxic pollutant source is crucial for public safety, especially in densely populated urban areas. Implementing source term estimation methods in real-world urban environments is challenging due to complex phenomena and the absence of concentration observational data. This work combines a computational fluid dynamics numerical simulation with the Metropolis–Hastings MCMC algorithm to identify the location and quantify the release rate of an unknown source within the geometry of Augsburg city center. To address the lack of concentration measurements, synthetic observations are generated by a forward dispersion model. The methodology is tested using these datasets, both as directly calculated by the forward model and with added Gaussian noise under different source release and wind flow scenarios. The results indicate that in most cases, both the source location and the release rate are estimated accurately. Although a higher performance is achieved using synthetic datasets without additional noise, high accuracy predictions are also obtained in many applications of noisy measurement datasets. In general, the outcomes demonstrate that the presented methodology can be a useful tool for estimating unknown source parameters in real-world urban applications.
Analysis of Different Height Correction Models for Tropospheric Delay Grid Products over the Yunnan Mountains
Authors: Zhou Fangrong , Li Luohong , Wang Yifan , Dai Zelin , Ding Chenchen , Li Hui , Yuan Yunbin
Published: July 2024

Accurate tropospheric delays are of great importance for both Global Navigation Satellite System (GNSS)-based positioning and precipitable water vapor monitoring. The gridded tropospheric delay products, including zenith hydrostatic delays (ZHD) and zenith wet delays (ZWD), are the most ideal method for accessing accurate tropospheric delays. The vertical adjustment method is critical for implementing the gridded tropospheric products. In this work, we consider the different models used for grid products and assess their performance over Yunnan mountains with complex topography. We summarize the main results as follows: (1) The products can provide accurate ZHD with mean biases of −2.6 mm and mean Standard Deviation (STD) of 1.5 mm while the ZWD results from grid products show a performance with biases of −0.4 mm and STD of 1.3 cm over the Yunnan area. (2) The Tv-based model shows a better performance than the T0-based model and IGPZWD in rugged areas with large height differences. The grid products can provide hourly ZHD with biases of 3 mm and wet delay with mean biases of within 2 cm and mean STD of below 3 cm in the Yunnan mountains, which exhibit a large height difference of around 1.5 km. (3) The radiosondes results confirm that the Tv-based model has an obvious advantage in calculating ZHD height corrections for differences within 2 km while the T0-model suffers from a loss in accuracy in the case of large height differences. If the site is located more than 1 km below the reference height, the IGPZWD model can provide a better ZWD with a mean bias of 1.5 cm and a mean STD of 1.7 cm. With vertical reduction models, the grid products can provide accurate ZHD and ZWD in real time, even if in complex area.
Electron and Positron Impact Ionization of Molecules
Authors: Nagy Ladislau , Tóth István , Campeanu Radu I.
Published: July 2024

We review our group’s most significant results concerning the collision of positrons and electrons with small molecules. Total and triple differential cross sections for the ionization of these targets were calculated in the distorted wave Born approximation using Gaussian molecular orbitals. Different models were tested. The obtained theoretical results reproduced, in most cases, the features observed in the experimental data.
On Some Distance Spectral Characteristics of Trees
Authors: Hayat Sakander , Khan Asad , Alenazi Mohammed J. F.
Published: July 2024

Graham and Pollack in 1971 presented applications of eigenvalues of the distance matrix in addressing problems in data communication systems. Spectral graph theory employs tools from linear algebra to retrieve the properties of a graph from the spectrum of graph-theoretic matrices. The study of graphs with “few eigenvalues” is a contemporary problem in spectral graph theory. This paper studies graphs with few distinct distance eigenvalues. After mentioning the classification of graphs with one and two distinct distance eigenvalues, we mainly focus on graphs with three distinct distance eigenvalues. Characterizing graphs with three distinct distance eigenvalues is “highly” non-trivial. In this paper, we classify all trees whose distance matrix has precisely three distinct eigenvalues. Our proof is different from earlier existing proof of the result as our proof is extendable to other similar families such as unicyclic and bicyclic graphs. The main tools which we employ include interlacing and equitable partitions. We also list all the connected graphs on ν ≤ 6 vertices and compute their distance spectra. Importantly, all these graphs on ν ≤ 6 vertices are determined from their distance spectra. We deliver a distance cospectral pair of order 7, thus making it a distance cospectral pair of the smallest order. This paper is concluded with some future directions.
Differential Back Muscle Flexion–Relaxation Phenomenon in Constrained versus Unconstrained Leg Postures
Authors: Chen Yi-Lang , Liao Ying-Hua
Published: July 2024

Previous studies examining the flexion–relaxation phenomenon (FRP) in back muscles through trunk forward flexion tests have yielded inconsistent findings, primarily due to variations in leg posture control. This study aimed to explore the influence of leg posture control and individual flexibility on FRP in back and low limb muscles. Thirty-two male participants, evenly distributed into high- and low-flexibility groups, were recruited. Activities of the erector spinae, biceps femoris, and gastrocnemius muscles, alongside the lumbosacral angle (LSA), were recorded as participants executed trunk flexion from 0° to 90° in 15° increments, enabling an analysis of FRP and its correlation with the investigated variables. The findings highlighted significant effects of all examined factors on the measured responses. At a trunk flexion angle of 60°, the influence of leg posture and flexibility on erector spinae activities was particularly pronounced. Participants with limited flexibility exhibited the most prominent FRP under constrained leg posture, while those with greater flexibility and unconstrained leg posture displayed the least FRP, indicated by their relatively larger LSAs. Under constrained leg posture conditions, participants experienced an approximate 1/3 to 1/2 increase in gastrocnemius activity throughout trunk flexion from 30° to 90°, while biceps femoris activity remained relatively constant. Using an inappropriate leg posture during back muscle FRP assessments can overestimate FRP. These findings offer guidance for designing future FRP research protocols.
A Comparative Study on Imputation Techniques: Introducing a Transformer Model for Robust and Efficient Handling of Missing EEG Amplitude Data
Authors: Khan Murad Ali
Published: July 2024

In clinical datasets, missing data often occur due to various reasons including non-response, data corruption, and errors in data collection or processing. Such missing values can lead to biased statistical analyses, reduced statistical power, and potentially misleading findings, making effective imputation critical. Traditional imputation methods, such as Zero Imputation, Mean Imputation, and k-Nearest Neighbors (KNN) Imputation, attempt to address these gaps. However, these methods often fall short of accurately capturing the underlying data complexity, leading to oversimplified assumptions and errors in prediction. This study introduces a novel Imputation model employing transformer-based architectures to address these challenges. Notably, the model distinguishes between complete EEG signal amplitude data and incomplete data in two datasets: PhysioNet and CHB-MIT. By training exclusively on complete amplitude data, the TabTransformer accurately learns and predicts missing values, capturing intricate patterns and relationships inherent in EEG amplitude data. Evaluation using various error metrics and R2 score demonstrates significant enhancements over traditional methods such as Zero, Mean, and KNN imputation. The Proposed Model achieves impressive R2 scores of 0.993 for PhysioNet and 0.97 for CHB-MIT, highlighting its efficacy in handling complex clinical data patterns and improving dataset integrity. This underscores the transformative potential of transformer models in advancing the utility and reliability of clinical datasets.
Extended Reality-Based Head-Mounted Displays for Surgical Education: A Ten-Year Systematic Review
Authors: Qi Ziyu , Corr Felix , Grimm Dustin , Nimsky Christopher , Bopp Miriam H. A.
Published: July 2024

Surgical education demands extensive knowledge and skill acquisition within limited time frames, often limited by reduced training opportunities and high-pressure environments. This review evaluates the effectiveness of extended reality-based head-mounted display (ExR-HMD) technology in surgical education, examining its impact on educational outcomes and exploring its strengths and limitations. Data from PubMed, Cochrane Library, Web of Science, ScienceDirect, Scopus, ACM Digital Library, IEEE Xplore, WorldCat, and Google Scholar (Year: 2014–2024) were synthesized. After screening, 32 studies comparing ExR-HMD and traditional surgical training methods for medical students or residents were identified. Quality and bias were assessed using the Medical Education Research Study Quality Instrument, Newcastle–Ottawa Scale-Education, and Cochrane Risk of Bias Tools. Results indicate that ExR-HMD offers benefits such as increased immersion, spatial awareness, and interaction and supports motor skill acquisition theory and constructivist educational theories. However, challenges such as system fidelity, operational inconvenience, and physical discomfort were noted. Nearly half the studies reported outcomes comparable or superior to traditional methods, emphasizing the importance of social interaction. Limitations include study heterogeneity and English-only publications. ExR-HMD shows promise but needs educational theory integration and social interaction. Future research should address technical and economic barriers to global accessibility.
Investigating the Endophyte Actinomycetota sp. JW0824 Strain as a Potential Bioinoculant to Enhance the Yield, Nutritive Value, and Chemical Composition of Different Cultivars of Anise (Pimpinella anisum L.) Seeds
Authors: Mahmoud Ahmed M. , Reyad Ahmed M. , Khalaf Maha H. , Sheteiwy Mohamed S. , Dawood Mona F. A. , El-Sawah Ahmed M. , Shaban Ahmed Enas , Malik Abdul , Al-Qahtani Wahidah H. , Abdel-Maksoud Mostafa A. , Mousa Nermien H. S. , Alyafei Mohammed , AbdElgawad Hamada
Published: July 2024

Anise (Pimpinella anisum L.) seeds have various nutritional and therapeutic benefits and are thus considered a valuable addition to animal and human health. Hence, in this study, we aimed to induce the nutritive and biological value of anise seeds. To this end, the potential biofortification effect of the endophytic Actinomycetota sp. JW0824 strain, isolated during the fall of 2023 from the medicinal plant Achyranthes aspera, exhibiting natural distribution in the Jazan region of Saudi Arabia, was investigated in four varieties of anise seeds from Egypt, Tunisia, Syria, and Morocco. Results revealed significant increments (p < 0.05) in the seed dry weight percentage (DW%) and oil yields. In line with increased biomass accumulation, the metabolism of the primary and secondary metabolites was increased. There were differential increases in proteins, sugars, flavonoids, alkaloids, phenols, vitamins (e.g., β-carotene, ascorbic acid), and essential oil components (e.g., phenylpropanoids and monoterpenes), along with their precursor phenylalanine. Consistently, the activity of L-phenylalanine aminolyase (PAL) was increased in the Egyptian and Tunisian varieties at 83.88% and 77.19%, respectively, while 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase (DAHPS) activity increased in all varieties, with a significant 179.31% rise in the Egyptian variety. These findings highlight the beneficial effects of Actinomycetota sp. JW0824 as a bioinoculant for anise seeds, suggesting its potential application in agricultural practices to improve seed yield and quality. Further field trials are recommended to assess the commercial viability of this endophyte for enhancing anise seed production and potentially benefiting other plant species.
Diminished Immune Response and Elevated Abundance in Gut Microbe Dubosiella in Mouse Models of Chronic Colitis with GBP5 Deficiency
Authors: Li Yichen , Wang Wenxia , Liu Yuxuan , Li Senru , Wang Jingyu , Hou Linlin
Published: July 2024

Guanylate binding protein 5 (GBP5) is an emerging immune component that has been increasingly recognized for its involvement in autoimmune diseases, particularly inflammatory bowel disease (IBD). IBD is a complex disease involving inflammation of the gastrointestinal tract. Here, we explored the functional significance of GBP5 using Gbp5 knockout mice and wildtype mice exposed to dextran sulfate sodium (DSS) to generate chronic colitis model. We found that Gbp5 deficiency protected mice from DSS-induced chronic colitis. Transcriptome analysis of colon tissues showed reduced immune responses in Gbp5 knockout mice compared to those in corresponding wildtype mice. We further observed that after repeated DSS exposure, the gut microbiota was altered, both in wildtype mice and Gbp5 knockout mice; however, the gut microbiome health index was higher in the Gbp5 knockout mice. Notably, a probiotic murine commensal bacterium, Dubosiella, was predominantly enriched in these knockout mice. Our findings suggest that GBP5 plays an important role in promoting inflammation and dysbiosis in the intestine, the prevention of which might therefore be worth exploring in regards to IBD treatment.
How Transcription Factor Clusters Shape the Transcriptional Landscape
Authors: Munshi Rahul
Published: July 2024

In eukaryotic cells, gene transcription typically occurs in discrete periods of promoter activity, interspersed with intervals of inactivity. This pattern deviates from simple stochastic events and warrants a closer examination of the molecular interactions that activate the promoter. Recent studies have identified transcription factor (TF) clusters as key precursors to transcriptional bursting. Often, these TF clusters form at chromatin segments that are physically distant from the promoter, making changes in chromatin conformation crucial for promoter–TF cluster interactions. In this review, I explore the formation and constituents of TF clusters, examining how the dynamic interplay between chromatin architecture and TF clustering influences transcriptional bursting. Additionally, I discuss techniques for visualizing TF clusters and provide an outlook on understanding the remaining gaps in this field.
Radiation-Induced Endothelial Ferroptosis Accelerates Atherosclerosis via the DDHD2-Mediated Nrf2/GPX4 Pathway
Authors: Su Xi , Liang Feng , Zeng Ya , Yang Zhang-Ru , Deng Yue-Zhen , Xu Yun-Hua , Cai Xu-Wei
Published: July 2024

This study sought to explore potential roles of endothelial ferroptosis in radiation-associated atherosclerosis (RAA) and molecular mechanisms behind this phenomenon. Here, an in vivo RAA mouse model was used and treated with ferroptosis inhibitors. We found that the RAA group had a higher plaque burden and a reduction in endothelial cells with increased lipid peroxidation compared to the control group, while ameliorated by liproxstatin-1. In vitro experiments further confirmed that radiation induced the occurrence of ferroptosis in human artery endothelial cells (HAECs). Then, proteomics analysis of HAECs identified domain-containing protein 2 (DDHD2) as a co-differentially expressed protein, which was enriched in the lipid metabolism pathway. In addition, the level of lipid peroxidation was elevated in DDHD2-knockdown HAECs. Mechanistically, a significant decrease in the protein and mRNA expression of glutathione peroxidase 4 (GPX4) was observed in HAECs following DDHD2 knockdown. Co-immunoprecipitation assays indicated a potential interaction between DDHD2 and nuclear factor erythroid 2-related factor 2 (Nrf2). The downregulation of Nrf2 protein was also detected in DDHD2-knockdown HAECs. In conclusion, our findings suggest that radiation-induced endothelial ferroptosis accelerates atherosclerosis, and DDHD2 is a potential regulatory protein in radiation-induced endothelial ferroptosis through the Nrf2/GPX4 pathway.
Gut Microbiome Dysbiosis in Patients with Pemphigus and Correlation with Pathogenic Autoantibodies
Authors: Li Si-Zhe , Wu Qing-Yang , Fan Yue , Guo Feng , Hu Xiao-Min , Zuo Ya-Gang
Published: July 2024

Background: Pemphigus is a group of potentially life-threatening autoimmune bullous diseases induced by pathogenic autoantibodies binding to the surface of epidermal cells. The role of the gut microbiota (GM) has been described in various autoimmune diseases. However, the impact of the GM on pemphigus is less understood. This study aimed to investigate whether there was alterations in the composition and function of the GM in pemphigus patients compared to healthy controls (HCs). Methods: Fecal samples were collected from 20 patients with active pemphigus (AP), 11 patients with remission pemphigus (PR), and 47 HCs. To sequence the fecal samples, 16S rRNA was applied, and bioinformatic analyses were performed. Results: We found differences in the abundance of certain bacterial taxa among the three groups. At the family level, the abundance of Prevotellaceae and Coriobacteriaceae positively correlated with pathogenic autoantibodies. At the genus level, the abundance of Klebsiella, Akkermansia, Bifidobacterium, Collinsella, Gemmiger, and Prevotella positively correlated with pathogenic autoantibodies. Meanwhile, the abundance of Veillonella and Clostridium_XlVa negatively correlated with pathogenic autoantibodies. A BugBase analysis revealed that the sum of potentially pathogenic bacteria was elevated in the AP group in comparison to the PR group. Additionally, the proportion of Gram-negative bacteria in the PR group was statistically significantly lower in comparison to the HC group. Conclusion: The differences in GM composition among the three groups, and the correlation between certain bacterial taxa and pathogenic autoantibodies of pemphigus, support a linkage between the GM and pemphigus.
The Beak of Eukaryotic Ribosomes: Life, Work and Miracles
Authors: Martín-Villanueva Sara , Galmozzi Carla V. , Ruger-Herreros Carmen , Kressler Dieter , de la Cruz Jesús
Published: July 2024

Ribosomes are not totally globular machines. Instead, they comprise prominent structural protrusions and a myriad of tentacle-like projections, which are frequently made up of ribosomal RNA expansion segments and N- or C-terminal extensions of ribosomal proteins. This is more evident in higher eukaryotic ribosomes. One of the most characteristic protrusions, present in small ribosomal subunits in all three domains of life, is the so-called beak, which is relevant for the function and regulation of the ribosome’s activities. During evolution, the beak has transitioned from an all ribosomal RNA structure (helix h33 in 16S rRNA) in bacteria, to an arrangement formed by three ribosomal proteins, eS10, eS12 and eS31, and a smaller h33 ribosomal RNA in eukaryotes. In this review, we describe the different structural and functional properties of the eukaryotic beak. We discuss the state-of-the-art concerning its composition and functional significance, including other processes apparently not related to translation, and the dynamics of its assembly in yeast and human cells. Moreover, we outline the current view about the relevance of the beak’s components in human diseases, especially in ribosomopathies and cancer.