bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Study on Albino and Pigmented Rainbow Trout (Oncorhynchus mykiss): Growth, Non-Specific Immunity, Disease Resistance and Related Gene Expressions
Authors: Kayhan Muhammet Hayati , Bahrioğlu Ergi , Özil Öznur
Published: August 2024

In this study, a comparison has been made between the albino (AA), normal pigmented (PP), mixtures (Mix), and their crossbreds (AP and PA) of rainbow trout, in terms of growth performance, non-specific immune system parameters, mRNA relative expression levels, and disease resistance. Regarding the non-specific immune system parameters that were examined, the albino group (AA) showed the highest values of lysozyme, NBT, and IgM levels, while the normal pigmented (PP) group exhibited the lowest values. The lowest mortality rate was observed after the challenge test in the AA group (16%), followed by PA (30.66%), Mix (32.00%), and AP (36.00%), with the highest mortality rate recorded in the PP group (52.00%). The results obtained from experimental research have been confirmed through molecular analyses. The expression level of IL-8 showed the highest level in the AA group (6.05 ± 1.95a), followed by PA (4.44 ± 1.60ab), Mix (3.04 ± 0.72bc), and AP (1.29 ± 0.23c) groups compared to the PP group (1-fold). There was no statistical difference among the groups in terms of growth performance (except for specific growth rates and final weights) and IGF-1 mRNA expression levels. In conclusion, the study suggests that albinism does not have a detrimental effect on rainbow trout. In addition, observation of a strong non-specific immune system in albinism could promote more efficient and sustainable aquaculture.
Evaluation of Thermal Comfort Conditions in The Working Environments of Seasonal Agricultural Workers in Csa Koppen Climate Type
Authors: Karakuş Nihat , Selim Serdar , Selim Ceren , OLGUN Rifat
Published: August 2024

In the Mediterranean climate zone, characterized by the Csa climate type, people's thermal comfort conditions deteriorate due to heat stress. This study focuses on determining the thermal comfort conditions of seasonal agricultural workers during the hot periods of the year when agricultural production is intense in developing Türkiye, located in the Mediterranean climate zone, where agricultural production cannot yet be carried out with high technology, and developing suggestions that can guide the authorities in this context. In this study, the thermal comfort conditions of seasonal agricultural workers working in agricultural lands in Csa were determined using the modified Physiological Equivalent Temperature (mPET) index in the Rayman model, according to their activity energy during intensive and less intensive agricultural work. These conditions were evaluated for ten-day, monthly, and seasonal periods. As a result of the research, it was observed that there were differences in the thermal comfort conditions of seasonal agricultural workers according to time and activity energy. It has been observed that agricultural workers, especially those working in soil cultivation (intensive activity), have a higher mPET value between 2.1°C and 2.9°C than agricultural workers engaged in plant care and harvesting (less intense activity). It has been determined that the thermal comfort conditions of agricultural workers engaged in plant care and harvesting deteriorate between 09.00 and 15.00, and for agricultural workers engaged in soil cultivation, between 08.00 and 16.00. According to the results, suggestions were developed within legal limits for the regulation of the working systems of agricultural workers.
Network pharmacology and molecular docking to explore the potential mechanism of Chlorogenic acid in combined septic acute liver injury
Authors: fang shangping , Su Hui , Liu Jiameng , Zhai Kecheng , Gao Yangmengna , Li Huan , Sun Renke , Cheng Huixian
Published: August 2024

Objective
To investigate the biological activities and mechanisms of chlorogenic acid (CGA) in treating septic acute liver injury (SALI) using network pharmacology, molecular docking, and in vivo studies.
Methods
Potential targets related to both chlorogenic acid and septic acute liver injury were searched from public databases. Protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. Molecular docking was performed to predict the binding affinity between the active compounds and core targets. Finally, in vitro and in vivo experiments were carried out for further validation.
Results
A total of 60 common targets were identified between acute septic liver injury and chlorogenic acid, among which 10 shared core targets were screened using Cytoscape. Molecular docking results indicated that these core targets had good binding activity with chlorogenic acid. In the SALI mouse model, chlorogenic acid demonstrated significant protective effects on the liver and anti-inflammatory properties, acting through the TLR4/NF-κB pathway.
Conclusion
CGA not only improves pathological damage in acute septic liver injury but also exerts its effects potentially through multiple pathways including TLR4.
Orally consumed cannabinoids: the effect of carrier oil on acute tissue distribution in male C57BL/6 mice
Authors: Lust Cody A.C. , Hillyer Lyn M. , Pallister Mitchell , Wright Amanda J. , Rogers Michael A. , Rock Erin M. , Limebeer Cheryl L. , Parker Linda A. , Ma David W.L.
Published: August 2024

Background: Fundamental gaps in knowledge exist in understanding the tissue distribution of cannabinoids, cannabidiol (CBD) and tetrahydrocannabinol (THC), following oral ingestion. CBD and THC are lipid-soluble and oral bioavailability is increased when combined with long-chain fatty acid carrier oils prior to oral ingestion. Oils with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) confer positive health benefits and have yet to be examined as a carrier oil for oral cannabinoid delivery thus, examination is warranted.
Methods: This study investigated the acute tissue distribution of cannabinoids in serum, adipose, brain, liver, heart, and muscle of male C57BL/6 mice at 1, 2, and 3 hours (H) post oral ingestion. Mice were gavaged with CBD (5 mg/kg) and THC (1 mg/kg) combined with either sesame (SES), mixed EPA/DHA (EPA/DHA), or DHA enriched (DHA) oil as a carrier. With assistance of the Analytical Facility for Bioactive Molecules (Toronto, Canada), tissue concentration of cannabinoids was quantified using liquid chromatography with tandem mass spectrometry.
Results: SES oil resulted in a significantly greater concentration of CBD and THC (p<0.05) across all tissues and times compared to n-3 PUFA oils. The ratio of EPA:DHA in the carrier oils modestly affected distribution of cannabinoids to tissues, notably, DHA oil resulted in a greater concentration of CBD in the brain. Heart tissue had the highest concentration of CBD at 1 and 2H post-oral gavage, and adipose tissue had the highest concentration at 3H which was consistent across all three carrier oils.
Conclusions: This study profiled the greatest number of tissues to-date for the acute distribution of CBD and THC following oral consumption with a lipid carrier in mice which demonstrated a non-uniform distribution to tissues over time. SES oil proved to be far more effective as a carrier oil at delivering orally consumed cannabinoids to tissues compared to two different n-3 PUFA containing oils. Further developing our fundamental understanding of cannabinoid distribution across tissues following their consumption from foods and pharmaceuticals are necessary to establish specific pharmacokinetic profiles to aid oral dosing strategies and maximize the bioactive potential of cannabinoids.
Reducing Neonatal Infection Rate Among the Neonates Born at Remera Rukoma Hospital: A Report of Quality Improvement Project
Authors: SEBERA Emile , Diane UWIMPAYE , Philemon NZEYIMANA , Leonille NIZEYEMALIYA , AHISHAKIYE Albertine , HAGENIMANA Celestin , TWAGIRUMUKIZA Emile
Published: August 2024

Background
Neonatal infection is one of the leading causes of neonatal mortality globally, significantly higher mortality rates are observed in Lower and middle-income countries, where Rwanda is located. Remera Rukoma District Hospital reported an increasing rate of neonatal infection necessitating assessment of the contributing causes and urgent intervention.
Methods
The project was conducted from January to June 2024. The Fishbone diagram was adopted to conduct a comprehensive root cause analysis. A multidisciplinary team of a quality improvement officer, clinicians, and different stakeholders identified contributing factors across multiple domains were categorized into healthcare practices, equipment, hospital environment, and patient factors. Interventions were implemented and monitored using monthly Plan-Do-Study-Act (PDSA) cycles to track progress and make necessary adjustments.
Results
There was a downward trend from a high rate of neonatal infection of 22.9% in January to 13% in June 2024. Despite not meeting the ambitious target of 10%, the results indicated a significant improvement. The systematic approach, involving targeted training of all hospital personnel, and fostering infection control measures, contributed to this progress.
Conclusion
The project demonstrated that a structured, data-driven approach to quality improvement can reduce neonatal infection rates. Key lessons include the effectiveness of comprehensive root cause analysis and the importance of continuous staff engagement and education. While the initial target was not met, the reduction achieved lays a foundation for continued efforts to improve neonatal outcomes at Remera Rukoma Hospital. Sustained commitment and further refinement of strategies are essential for ongoing progress in infection control and overall patient care. Lessons learned include the value of staff engagement, continuous education, and data-driven decision-making in infection control efforts.
Assessment of Biocompatibility of 16HBE14o- Human Bronchial Epithelial Cells in Alginate-Methylcellulose Bioinks Revealed Spheroid Formation
Authors: Wood Nathan , Qin Hongmin , Li Wanhe , Doria Esther
Published: August 2024

The biocompatibility of 16HBE14o- human bronchial epithelial cells in ionically cross-linked alginate-methylcellulose bioinks was assessed. This was accomplished by encapsulating 16HBE14o- cells in either a sodium alginate bioink or a bioink with sodium alginate and added methylcellulose in a 1:1 ratio. To differentiate the effects of methylcellulose from those of cross-linking on cell viability, two concentrations of calcium chloride cross-linker were used for both alginate only and alginate-methylcellulose bioinks. Using fluorescence microscopy, it was observed that bioinks with methylcellulose showed a small but significant reduced cell viability and a decreased presence of cell spheroids compared to their methylcellulose free alginate counterparts. However, alginate-methylcellulose bioinks still supported cell proliferation and appeared to be biocompatible. Additionally, the concentration of cross-linker seemed to impact cell viability. This study has implications for the use of methylcellulose as a viscosity tuner for both general 3D 16HBE14o- human epithelial cell culture and 3D bioprinting. The presence of spheroids suggests that alginate-methylcellulose bioinks could be useful in generating 3D 16HBE14o- human epithelial cell culture to address questions in cell biology, including signal transduction, metabolic activity, and cancer hallmarks.
lista-GEM: the genome-scale metabolic reconstruction of Lipomyces starkeyi
Authors: Almeida Eduardo , Ferreira Mauricio , Silveira Wendel
Published: August 2024

Oleaginous yeasts cultivation in low-cost substrates is an alternative for more sustainable production of lipids and oleochemicals. Lipomyces starkeyi accumulates high amounts of lipids from different carbon sources, such as glycerol, and glucose and xylose (lignocellulosic sugars). Systems metabolic engineering approaches can further enhance its capabilities for lipid production, but no genome-scale metabolic networks have been reconstructed and curated for L. starkeyi. Herein, we propose lista-GEM, a novel genome-scale metabolic model of L. starkeyi. We reconstructed the model using two high-quality models of oleaginous yeasts as templates and further curated the model to reflect the metabolism of L. starkeyi. We simulated phenotypes and predicted flux distributions in good accordance with experimental data. We also predicted targets to improve lipid production in glucose, xylose, and glycerol. The phase plane analysis indicated that the carbon availability affected lipid production more than oxygen availability. We found that the maximum lipid production in glucose and xylose required more oxygen than glycerol. Enzymes related to lipid synthesis in the endoplasmic reticulum were the main targets to improve lipid production: stearoyl-CoA desaturase, fatty-acyl-CoA synthase, diacylglycerol acyltransferase, and glycerol-3-phosphate acyltransferase. The glycolytic genes encoding pyruvate kinase, enolase, phosphoglycerate mutase, glyceraldehyde-3-phosphate dehydrogenase, and phosphoglycerate kinase were predicted as targets for overexpression. Pyruvate decarboxylase, acetaldehyde dehydrogenase, acetyl-CoA synthetase, adenylate kinase, inorganic diphosphatase, and triose-phosphate isomerase were predicted only when glycerol was the carbon source. Therefore, we demonstrated that lista-GEM provides multiple metabolic engineering targets to improve lipid production by L. starkeyi using carbon sources from agricultural and industrial wastes.
Brazilian Ocean Thermal Energy Park and Its Sites: Definitions and Feasibility of Thermal Energy Conversion in the Blue Amazon
Authors: de Souza Roberto Valente , Fernandes Elisa Helena Leão , de Azevedo José Luiz Lima , Corrêa Rafaela Martins , Passos Mariana dos Santos , Gomes Rodrigo Klim , Junior Joel Sena Sales
Published: August 2024

The search for energy alternatives is becoming more important in the strategic development of countries, as global energy demand accelerates. The thermal energy in the oceans, the highest exploitation potential, is renewable and has the ability to remove heat from the oceans and carbonic gas from the atmosphere. In this study, we used the temperature results from the numerical model HYCOM for resoucers evaluation of Ocean Thermal Energy Conversion (OTEC). Based on these data, daily, monthly, seasonal and annual averages were calculated, allowing to evaluate the thermal gradient variability in the Blue Amazon, region where Brazil has sovereign rights for exploration, conservation and management of living and nonliving natural resources. Three thermal energy sites were obtained the definition of their viability and operational of his conversion by teorical OTEC plant throughout the period of the average. The brazilian northern region stands out with the higher energy potential between the surface and a depth range of 600m ≤ z ≥ 1000m, from the results we indicate that the Brazilian Ocean Thermal Energy Park (OTEP) is technically feasible for the operations of OTEC. However, form the economic perspective, results show that only portions closest to the continental shelf, have the capacity to operate.
Dormancy Regulator Prunus mume DAM6 Promotes Ethylene-Mediated Leaf Senescence and Abscission
Authors: Hsiang Tzu-Fan , Chen Yue-Yu , Nakano Ryohei , Oikawa Akira , Matsuura Takakazu , Ikeda Yoko , Yamane Hisayo
Published: August 2024

Leaf senescence and abscission in autumn are critical phenological events in deciduous woody perennials. After leaf fall, dormant buds remain on deciduous woody perennials, which then enter a winter dormancy phase. Thus, leaf fall is widely believed to be linked to the onset of dormancy. In Rosaceae fruit trees, DORMANCY-ASSOCIATED MADS-box (DAM) transcription factors control bud dormancy. However, apart from their regulatory effects on bud dormancy, the biological functions of DAMs have not been thoroughly characterized. In this study, we revealed a novel DAM function influencing leaf senescence and abscission in autumn. In Prunus mume, PmDAM6 expression was gradually up-regulated in leaves during autumn toward leaf fall. Our comparative transcriptome analysis using two RNA-seq datasets for the leaves of transgenic plants overexpressing PmDAM6 and peach (Prunus persica) DAM6 (PpeDAM6) indicated Prunus DAM6 may up-regulate the expression of genes involved in ethylene biosynthesis and signaling as well as leaf abscission. Significant increases in 1-aminocyclopropane-1-carboxylate accumulation and ethylene emission in DEX-treated 35S:PmDAM6-GR leaves reflect the inductive effect of PmDAM6 on ethylene biosynthesis. Additionally, ethephon treatments promoted autumn leaf senescence and abscission in apple and P. mume, mirroring the changes due to PmDAM6 overexpression. Collectively, these findings suggest that PmDAM6 may induce ethylene emission from leaves, thereby promoting leaf senescence and abscission. This study clarified the effects of Prunus DAM6 on autumn leaf fall, which is associated with bud dormancy onset. Accordingly, in Rosaceae, DAMs may play multiple important roles affecting whole plant growth during the tree dormancy induction phase.
Variable and slow-paced neural dynamics in HVC underlie plastic song production in juvenile zebra finches
Authors: Bistere Linda , Wilczek Stefan , Vallentin Daniela
Published: August 2024

Zebra finches undergo a gradual refinement of their vocalizations, transitioning from variable juvenile songs to the stereotyped song of adulthood. To investigate the neural mechanisms underlying song crystallization, a critical phase in this developmental process, we conducted intracellular recordings in HVC, a premotor nucleus essential for song learning and production. We found that HVC projection neurons in juvenile zebra finches in the song crystallization phase exhibited more variable spiking patterns compared to the precise bursting observed in adult HVC projection neurons. Additionally, subthreshold membrane potential fluctuations in juvenile neurons were characterized by longer duration and larger amplitude excitatory postsynaptic potentials. These distinct temporal dynamics in HVC during song crystallization likely play a crucial role in the fine-tuning processes that shape the precise timing and structure of the mature zebra finch song.
Nonlinear Plane-Wave Expansion Method for Analyzing Dispersion Properties of Piezoelectric Metamaterial Lattices with Encapsulated Resonators
Authors: Shen Yichang , Lacarbonara Walter
Published: August 2024

Wave propagation and band gap behavior of square lattices encapsulating identical nonlinear resonators in each cell are investigated through an asymptotic treatment of the wave propagation equations. The nonlinear effects of the resonators, composed of suspended piezoelectric membranes with a central mass, are investigated through the introduction of a generalized nonlinear version derived from the plane-wave expansion (PWE) method. This method leads to nonlinear wave propagation equations and the analytical derivation of nonlinear dispersion functions using the method of multiple scales. Extensive numerical simulations verify the validity of the analytical solutions. This study demonstrates that the proposed nonlinear PWE method overcomes the limitations of the popular approach based on the enforcement of the Floquet-Bloch theorem coupled with the cell projection method. While the latter provides the dispersion curves of the fundamental propagation mode, the nonlinear PWE delivers the nonlinear dispersion curves of all modes, offering a broader perspective into the design process for semi-adaptively programmable metamaterials aimed at controlling wave propagation.
From Table to Image: Boosting Credit Risk Prediction via Transfer MLP-like Network on Structured Data
Authors: Li Yan , Wen Guihua , Liu Bo
Published: August 2024

At present, deep learning has limited application in the field of financial credit risk because deep learning is good at processing unstructured data such as images, voice, and text, while the credit risk field processes structured tabular data, which makes the existing deep learning methods not well adapted to financial structured data tasks. To this end, this paper proposes a new Table-to-Image Converted Transfer MLP-like network for financial credit risk prediction. First, our method attempts to represent structured data from a new perspective and proposes a data homology based table-to-image conversion method to convert the tabular financial credit risk prediction data into image-like financial data. Then, based on the Strip-MLP structure, a pretrained MLP-like network is proposed to be applied to the credit prediction of the converted image-like financial data. The model is pre-trained with a public financial dataset, and its pre-trained parameters are transferred to the private dataset of financial institutions with different feature numbers and feature contents through transfer learning. Experimental results show that for the task of financial credit risk prediction, the methods proposed in this paper have significantly improved the effect compared with the baseline algorithm.
The Feasibility of Constructing Rubber Concrete Pavement Reinforced with Recycled and Industrial Steel Fibers
Authors: Shadfar Arash , Nani Mehdi , Shirinabadi Reza , Hosseini Seyed Azim
Published: August 2024

Using tires in the construction sector can have a lot of advantages because they are constructed of materials that are high resistance, durable, high quality, and flexible. Unlike asphalt pavements, rigid concrete pavements are not as flexible, even though they have a respectable resistance to bending. Rubber concrete reinforced with fibers is created by utilizing tire waste from worn automobile tires, which contains steel and rubber fibers. Because of its special qualities, this kind of concrete is a popular choice for concrete pavement construction. This paper's goal is to examine how rubber concrete reinforced with industrial and tire-derived steel fibers behaves when used to create concrete pavements. In this paper, various-sized rubber pieces were used in place of some of the coarse and fine grains. It was assessed whether kind of steel fibers—manufacturer-produced steel fibers (MSF) and recycled steel fibers from used car tires (RTSF)—would work best for reinforcing rubberized concrete. Based on the results, adding rubber to some of the concrete's natural particles reduced the material's density and efficiency while increasing its air content. The modulus of elasticity, compressive strength, and bending strength all declined with increased use of rubber; however, the compressive strength of regular concrete rose by almost 30% when 40 \(\:\raisebox{1ex}{$Kg$}\!\left/\:\!\raisebox{-1ex}{${m}^{3}$}\right.\) of steel fibers were added. Additionally, bending strength decreased when steel fibers were added to rubber concrete reinforcement, whereas compressive strength and modulus of elasticity increased by 12.5 and 28.4 percent, respectively. Ultimately, it was determined that replacing 60% of the rubber pieces with regular concrete particles and adding 20 \(\:\raisebox{1ex}{$Kg$}\!\left/\:\!\raisebox{-1ex}{${m}^{3}$}\right.\) of industrial and 20 \(\:Kg\) of recycled fibers was the optimal combination to use when building flexible rubber concrete pavement reinforced with steel fibers.
Nutritional niches of endemic, facultatively anaerobic heterotrophs from an isolated Antarctic terrestrial hydrothermal refugium elucidated through metagenomics
Authors: Herbold Craig W. , Noell Stephen E. , Lee Charles K. , Vickers Chelsea J. , Stott Matthew B. , Eisen Jonathan A. , McDonald Ian R. , Cary S. Craig
Published: August 2024

Background
Tramway Ridge, a geothermal Antarctic Specially Protected Area (1) (elevation 3340 m) located near the summit of Mount Erebus, is home to a unique community composed of cosmopolitan surface-associated micro-organisms and abundant, poorly understood subsurface-associated microorganisms (2–5). Here, we use shotgun metagenomics to compare the functional capabilities of this community to those found elsewhere on Earth and to infer endemism and metabolic capabilities of abundant subsurface taxa.
Results
We found that the functional potential in this community is most similar to that found in terrestrial hydrothermal environments (hot springs, sediments) and that the two dominant organisms in the subsurface are primarily endemic. They were found to be facultative anaerobic heterotrophs that likely share a pool of nitrogenous organic compounds while specializing in different carbon compounds.
Conclusions
Metagenomic insights have provided a detailed understanding of the microbe-based ecosystem found in geothermally heated fumaroles at Tramway Ridge. This approach enabled us to compare Tramway Ridge with other microbial systems, identify endemic taxa and elucidate the key metabolic pathways that may enable specific organisms to dominate the ecosystem.
FedscGen: privacy-aware federated batch effect correction of single-cell RNA sequencing data
Authors: Bakhtiari Mohammad , Bonn Stefan , Theis Fabian , Zolotareva Olga , Baumbach Jan
Published: August 2024

scRNA-seq data from clinical samples are prone to batch effects, while hospitals are hesitant to share their data for centralized analysis, including batch effect correction, due to the privacy sensitivity of human genomic data. We present FedscGen, a novel privacy-aware federated method based on the generative integration approach scGen. FedscGen presents two federated workflows for training and correction of batch effects with inclusion of new studies. We benchmark FedscGen and scGen using eight datasets and nine metrics to demonstrate competitive results. On the Human Pancreas dataset, for instance, the performance difference of all models is zero for NMI, GC, ILF1, ASW_C, and kBET while FedscGen outperforms by 0.03 in EBM. FedscGen opens a privacy-preserving path for single-cell RNAseq batch effect correction in particular in clinical multi-center studies. FedscGen is published as a FeatureCloud app to be used in real world federated collaboration (https://featurecloud.ai/app/fedscgen).
Classification of Imagined Speech Signals Using Functional Connectivity Graphs and Machine Learning Models.
Authors: Mohan Anand , Anand RS
Published: August 2024

EEG involves recording electrical activity generated by the brain through electrodes placed on the scalp. Imagined speech classification has emerged as an essential area of research in brain-computer interfaces (BCIs). Despite significant advances, accurately classifying imagined speech signals remains challenging due to their complex and non-stationary nature. Existing approaches often struggle with low signal-to-noise ratios and high inter-subject variability. A novel method named imagined speech functional connectivity graph (ISFCG) is implemented to deal with these issues. The functional connectivity graphs capture the complex relationships between brain regions during imagined speech tasks. These graphs are then used to extract features that serve as inputs to various machine-learning models. The ISFCG addresses the limitations of traditional methods by providing a more robust representation of imagined speech signals. Also, a convolutional neural network (CNN) is proposed to learn features from these complex graphs, leading to improved classification accuracy. Experimental results on a benchmark dataset demonstrate the effectiveness of our method.
Van-DETR: Enhanced Real-Time Object Detection with VanillaNet and Advanced Feature Fusion
Authors: Lu Xinbiao , Zhan Gaofan , Wu Wen , Zhang Wentao , Wu Xiaolong , Han Changjiang
Published: August 2024

Recently, end-to-end detectors based on transformer (DETRs) have made remarkable progress. However, their high computational cost still limits the performance of the DETRs series as real-time object detectors. In order to solve this problem, we introduce the Van-DETR model, which enhances the first real-time end-to-end object detector, RT-DETR. Specifically, we innovatively introduce a new, more lightweight backbone—VanillaNet, replacing the former backbone—ResNet. To address its weak nonlinearity and poor local analysis, we combine large kernel convolutions with small kernel convolutions to integrate global and local information, significantly enhancing feature extraction capabilities. Secondly, in the hybrid encoder, we cascade group process the features extracted by the backbone and design a gated linear unit with a star-shaped connection for intra-scale feature interaction. During the cross-scale feature fusion stage, we propose a high-low frequency feature fusion module with strong feature representation capabilities. To verify the effectiveness of the model, we conduct experiments on two public object detection datasets—visdrone dataset and a people dataset from roboflow. Experimental results show that the proposed Van-DETR model achieves MAP50 of 0.471 and 0.730 on two object detection datasets, respectively, representing improvements of 4.5% and 2.8% over the original RT-DETR model. Source code is available at https://github.com/vangoghzz/Van-DETR.
Flow Chemistry-Enabled Asymmetric Synthesis of Cyproterone Acetate: A Chemo-biocatalytic Approach
Authors: Chen Fen-Er , Zhang Yajiao , Liu Minjie , Zheng Xianjing , Gao Liang , Wan Li , Cheng Dang
Published: August 2024

Flow chemistry has many advantages over batch synthesis of organic small-molecules in terms of environmental compatibility, safety and synthetic efficiency especially when scale-up is considered. However, its application in manufacturing active pharmaceutical ingredients (APIs) is still rare due to the complexity involved with operating a multistep continuous reaction sequence. As the demonstration of an alternative approach in steroid chemistry, herein, we report the first 10-step chemo-biocatalytic continuous flow asymmetric synthesis of cyproterone acetate (4) in which 10 transformations are combined into a telescoped flow linear sequence from commercially available 4-androstene-3, 17-dione (11). This integrated one-flow synthesis features an engineered 3-ketosteroid-Δ1-dehydrogenase (ReM2)-catalyzed Δ1-dehydrogenation to form the C1, C2-double bond of the A ring, a substrate-controlled Co-catalyzed Mukaiyama hydration of Δ1, 4, 16-triene-3, 20-dione 9 to forge the crucial chiral C17α-OH group of the D ring with excellent stereoselectivity, and a rapid flow Corey-Chaykovsky cyclopropanation of 17α-hydroxy-Δ1, 4, 6-triene-3-one-20-ketal 7 to build the cyclopropyl core of the A ring. By strategic use of these three key reactions and fully continuous-flow operations, cyproterone acetate (4) was produced in an overall yield of 9.65% in 3 h of total reaction time, this is the shortest route to this steroid, and the highest total number of chemical transformation performance in any other continuous-flow synthesis reported to date. Also included is the Ni-catalyzed batch-mode nucleophilic cyclopropanation using DCM as methylene source for the formation of disubstituted three-membered ring on A ring in steroids with excellent chemo-regio-diastereoselectivity.
Fault Tolerance in Service Function Chains: A Taxonomy, Survey and Future Directions
Authors: Shahab Muhammad Hamza , Sharma Yogesh
Published: August 2024

The rise of Network Function Virtualization (NFV) has revolutionized the network services, by enabling the delivery of flexible and scalable solutions through Service Function Chains (SFCs). However, the virtualized deployment of SFCs increases their susceptibility to various types of failures in comparison to their physical deployment. Hence, a thorough understanding of the failure types, their reasons of occurrence and management methods is important. This will help us to achieve high fault tolerance in virtualized SFCs equivalent or perhaps higher to their physical counter parts while reaping the benefits of virtualization. This article attempts to present a systematic review of fault tolerance practices for SFCs. As an outcome, we propose a comprehensive taxonomy that categorizes the state-of-the-art in fault tolerance in SFCs based on failure types, and their pattern of occurrence, failure management approaches, and their evaluation metrics. A critical analysis of the state-of-the-art is performed to identify the key trends and research gaps. A conceptual framework to achieve high fault tolerance in SFCs is presented along with a discussion on future research directions.
Metallacage-Crosslinked Free-Standing Supramolecular Networks via Photo-induced Copolymerization for Photocatalytic Water Decontamination
Authors: Zhang Mingming , Li Rongrong , Zhang Haixin , Hou Yali , Gao Lingyan , Chu Dake
Published: August 2024

The development of polymer materials for water decontamination makes a significant contribution to environmental protection and public health. Herein, we report the preparation of metallacage-crosslinked free-standing supramolecular networks by photo-induced copolymerization of acrylate metallacages and butyl methacrylate for water decontamination. The integration of metallacages into polymer networks endows the networks good capability for generating singlet oxygen via photosensitization, making them serve as a type of decontamination materials that can effectively eliminate diverse organic pollutants and bacterial contaminants. This study not only provides a mild and effective strategy for the preparation of metallacage-cored supramolecular networks via photo-induced copolymerization but also explores their applications for photocatalytic dye degradation and bacterial killing, which will promote the future development of metallacage-based supramolecular materials for photocatalytic applications.
Botulinum Toxin Injections in Infantile Esotropia: Tailored Management Strategies in a Case series
Authors: Ciftci Suleyman
Published: August 2024

Purpose: To investigate the impact of a single dose of botulinum toxin on infantile esotropia.
Methods: This retrospective observational case series reviewed data from infants with esotropia who received 5 IU/0.05 mL botulinum toxin in both medial rectus muscles without EMG control. The study included five patients and any complications related to the injection or the toxin itself were documented.
Throughout their regular follow-up, parents were instructed to patch the dominant eye whenever fixation preference was observed, whether in the exotropia or esotropia phase. The patients underwent examinations between their 78th and 96th months to evaluate their current visual acuity and identify any late-term accompanying squints, nystagmus, or signs of amblyopia. Best-corrected visual acuity was assessed using Snellen optotypes or pictures.
Results: Five patients were included in the study. Inferior oblique muscle hyperfunction developed postinjection in all patients, occurring as early as the 7th month and as late as the 88th month. During the final examination, visual acuity was assessed. Among those with orthophoria, one patient exhibited 1.0/1.0 visual acuity, another had 0.4/0.6 visual acuity, and one had 0.2/0.2 visual acuity. In patients with monocular esotropia, the strabismic eye had a visual acuity of 0.1, while the dominant eye had a visual acuity of 1.0. Notably, none of the patients developed dissociated vertical deviations (DVD) or latent nystagmus.
Conclusions: Intervention with botulinum toxin can prevent latent nystagmus and the consequent DVD by suppressing monofixation syndrome.
“ Virtual Counseling was a Lifeline”- Lived experiences of Adolescent Cyberbullying Victims on Counselling Intervention during the COVID-19 Pandemic: An Interpretative Phenomenological Analysis
Authors: Mahmood Sabrina , Kalo Zsuzsa
Published: August 2024

Background
With the proliferation of digital communication platforms and increased screen time during the COVID-19 pandemic, the issue of cyberbullying become a global public health concern among adolescents. The Bangladeshi education system lacks effective cyberbullying intervention and prevention programs in school. Moreover, there is a limited understanding of the impact and meaning of counselling intervention for adolescent cyberbullying victims, even during the pandemic. Therefore, we aimed to conduct a novel study to explore the impact of counselling intervention on cyberbullying victims during the COVID-19 pandemic in Bangladesh.
Method
This study employed interpretative phenomenological analysis (IPA) to explore the subjective experiences of adolescent cyberbullying victims regarding counselling intervention. We conducted semi-structured interviews with a purposive sample of ten high school students (seven females and three males, agemean+SD =15.12± 0.81) who had undergone at least five counselling intervention sessions as victims of cyberbullying during the pandemic. The interviews were audio-recorded, transcribed verbatim, and subjected to interpretative phenomenological analysis to identify recurring patterns and themes concerning cyberbullying experiences and perceived outcomes of counselling intervention.
Results
Five main themes have emerged as a result of the analysis; 1) Sense of intensified emotional and psychological impact. 2) Perceived barriers to seeking counseling in the pandemic, 3) Counselling as a crucial support system, 4) Perceived positive changes of self, and, 5) Long-term impact and sustainability. The study explored the unique challenges posed by the pandemic, which intensified the effects of cyberbullying and required adaptations in counseling approaches. Virtual counseling, despite its limitations, emerged as a vital resource for the participants, highlighting the need for flexible and accessible mental health interventions in the digital age.
Conclusions
This novel study will likely facilitate further longitudinal studies, emphasizing the urgent need to develop effective cyberbullying intervention and prevention programs in schools across Bangladesh and other developing countries.
Integrated Bioinformatic Analysis Reveals the Gene Signatures, Epigenetic Roles, and Regulatory Networks in Endometriosis
Authors: Amanda Clara Riski , Fadilah  , Hestiantoro Andon , Suryandari Dwi Anita , Muharam Raden , Tulandi Togas , Asmarinah
Published: August 2024

Objectives: Endometriosis is a common gynecological disease with a significant economic burden. Growing evidence has suggested the role of aberrant gene expression and epigenetic mechanisms in the pathogenesis of endometriosis. This study aims to identify potential key genes, epigenetic features, and regulatory networks in endometriosis using an integrated bioinformatic approach.
Methods: Six microarray and RNA-sequencing datasets (GSE23339, GSE7305, GSE25628, GSE51981, GSE120103, GSE87809) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) of each dataset were analyzed using the GEO2R tool, and their mRNA, miRNA, and lncRNA components were identified subsequently. The common DEGs between datasets were combined, and the Gene ontology (GO) and pathway enrichment were analyzed using the ShinyGo. The protein-protein interaction (PPI) network of differentially expressed genes, miRNA, and lncRNA was constructed using STRING and Cytoscape, then the top 15 hub genes in the PPI network were identified using the CytoHubba.
Results: A total of 551 common DEGs were identified among four or more studies, including 292 upregulated and 259 downregulated genes. Besides alterations in protein-coding genes (mRNA), 16 miRNA were identified from all studies, along with 12 lncRNA that were common in at least three studies. Enriched DEGs were mainly associated with extracellular matrix (ECM) interaction, P53 signaling pathway, and focal adhesion, which are suggested to play vital roles in the pathogenesis of endometriosis. Through PPI network construction of common DEGs, 178 nodes and 683 edges were obtained, from which 15 hub genes were identified, including CDK1, CCNB1, KIF11, CCNA2, BUB1B, DLGAP5, BUB1, TOP2A, ASPM, CEP55, CENPF, TPX2, CCNB2, KIFC, NCAPG.
Conclusions: Our in-depth bioinformatics analysis reveals the critical molecular basis underlying endometriosis. The identified hub genes, miRNA, and lncRNA may also serve as potential biomarkers to predict the occurrence and prognosis of endometriosis.
Validating the Vegetable Variety Navigator Decision-support Tool Using Recent On-farm Variety Trial Data
Authors: Wehrbein Caleb D. , Wortman Sam E.
Published: August 2024

Local variety trial data are necessary for informing growers how a specific variety might perform on their farm but there is a growing deficiency in these data, particularly for specialty crops. To address this issue, an online decision-support tool named the Vegetable Variety Navigator (VVN) was developed in 2020 to compile, analyze, and visually communicate publicly available broccoli (Brassica oleracea var. italica), cucumber (Cucumis sativus), and sweet pepper (Capsicum annuum) variety trial data. To validate the accuracy and predictive potential of the VVN, we conducted 16 on-farm variety trials for broccoli, cucumber, and sweet pepper between 2020 and 2022. Yield of each variety in a trial was compared with the mean of all other varieties in the same trial to calculate a mean relative yield (MRY). The difference between observed relative yield in the field and predicted relative yield from the VVN (ΔMRY) was used to assess the accuracy of three different VVN prediction strategies. Strategies included using data from the following: 1) the single geographically nearest trial, 2) the mean of the three geographically nearest trials, or 3) the mean of all available trial data regardless of location. Compared with random predictions of MRY for each variety (from within a normal distribution of MRY values in the VVN database), the VVN predictions reduced ΔMRY and improved the accuracy of relative yield predictions across varieties by up to 21% in broccoli, 51% in cucumber (depending on strategy), and 51% in sweet pepper. Results confirm the value of the VVN as a decision-support tool for growers facing an ever-increasing number of crop variety options with less variety trial data. Future research and development are needed to improve the accuracy of the VVN by accounting for possible effects of crop types, management, and location on relative yield and quality.
Stochastic versus deterministic assembly of oceanic island biota: leaf-dwelling lichens on the Galápagos and on Cocos Island
Authors: Lücking Robert , Moncada Bibiana , Bungartz Frank
Published: August 2024

We used a simulation approach to test whether species compo­sition on oceanic islands follows deterministic assembly rules based on probabilities of successful dispersal and establishment. The study was performed with two island biota in the eastern Pacific: the Galápagos, dominated by dry vegetation and montane humid forest, and Cocos Island, covered by wet tropical forest. We used leaf-dwelling (foliicolous) lichens as the study group and compiled occurrence data from previous studies on both island biota and new collections from the Galápagos. Species composition was simulated using randomization from a continental species pool, without and with filtering through ecogeographic parameters. Parameters for filtering were continental distribution range, commonness, and microsite exposure for successful dispersal, and preferences regarding vegetation type, seasonality, elevation, and microhabitat for successful establishment. Whereas neutral random selection predicted insular species composition imprecisely, ecogeographic parameter filtering resulted in rather accurate prediction. Commonness was the parameter that most contributed to the determination of species assembly. Empirical comparison with sites in continental Ecuador and Costa Rica suggests a closer affinity of the Galápagos with Ecuador, indicating that distance plays some role in species assembly as well. Based on our results we conclude that insular species assembly in this group of organisms is largely deterministic, rejecting a purely neutral approach.

Composition of randomized assemblies from a known species pool occurring on the American continent supports the hypothesis that island colonization largely follows deterministic assembly rules.

Stochastic components included a small number of unpredictable species and missing species as a result of disharmonic assembly.

Commonness was the most important parameter in shaping assembly.

Empirical comparison with sites in continental Ecuador and Costa Rica suggests a closer affinity of the Galápagos with Ecuador.

This study appears to be the first to test species assembly in island biota through simulation based on predictions from continental source metacommunities.
Assessment of the betterness of a battery electric vehicle: A multi-criteria decision-making approach
Authors: Febransyah Ade
Published: August 2024

Despite the advantages and benefits of a battery electric vehicle, its adoption rate remains low. Previous studies have explored factors that influence the adoption of electric vehicles. However, studies investigating whether an electric car outperforms a gasoline car are still limited. Therefore, this study aims to assess the betterness of an electric vehicle compared with a gasoline vehicle in helping customers perform their jobs to be done. A multi-criteria decision-making approach using the analytic hierarchy process is built on two main criteria, namely, customer pains and customer gains, where customer pains are divided into cost pains and non-cost pains, and customer gains are divided into functional gains and emotional gains. Using the most affordable battery electric vehicle in the Indonesian market, interviewees who live in the greater Jakarta and drive to work were invited to perform the pairwise comparison processes. The finding of this study shows that with respect to helping customers perform their jobs to be done, a battery electric vehicle is equally to moderately worse than a gasoline vehicle with a worse score of 0.5946 compared with a better score of 0.4054. This finding comes from interviewees who prioritize customer gains with a priority score of 0.6993 over customer pains with a priority score of 0.3007. Considering that the analytic hierarchy process allows a small number of interviewees, the result obtained should be limited as an early prediction about the betterness of an electric car compared with a gasoline car from a certain group of persons.
Structural detection study of mine blanket area based on dynamic 3D deformation prediction
Authors: Chen Quanqiu , Jia Nan
Published: August 2024

Aiming at addressing the issues of structural parameter inversion and dynamic three-dimensional deformation prediction in mining areas, a method of structural parameter inversion in mining areas based on synthetic aperture radar interferometry is designed by optimising parameter settings and simplifying the calculation process. Meanwhile, a method is proposed to transform the 3D deformation prediction of the mining area into line-of-sight direction deformation prediction, based on the constraint relationship between horizontal movement and vertical deformation gradient, and using spatio-temporal Kalman filtering for spatio-temporal data processing. The outcomes showcase that the absolute errors of 3D deformation parameter prediction are within the interval of 0-63.8 m and the absolute errors are within the range of 0-8 %. The structural parameter inversion method for mining airspace zone proposed by the study has high accuracy and precision in both shape and parameter prediction of the airspace zone, and the prediction errors are all less than 10 %. Compared with the Weibull model, the prediction error of the Kalman filter model is reduced by 8 %, which helps to better understand and predict the deformation of the mine openings. The study offers powerful technical support for the prevention and control of ground deformation and mobile geological disasters caused by mining, which is meaningful for the safe production in mining areas.