bluuebunny/crossref_metadata_2025 huggingface dataset:
The function of web decorations in orb web spiders
Authors: Walter André
Published: April 2024

Visual signal, mechanical reinforcement, protein storage, or non-functional stress response? Web decorations constructed by a number of orb web spider species puzzle behavioural ecologists. While some species use a variety of construction materials, it seems particularly difficult to solve the issue for silk decorations. The visual pattern of decoration structures has sparked the researchers’ imagination, and the conclusion that they act as signals is unsurprising. For over a century, however, we have not found a conclusive answer on a specific signal function of silk decorations. More recent studies even suggest that the construction mode of web decorations may render a specific signal function rather unlikely. In this review, I discuss reasons for the continuous struggle to find conclusive answers and what could be alternative routes for unravelling their adaptive significance. Based on my own experience in the field, I present a personal viewpoint, which I hope will be inspiring at a stage where research in this field seems to have reached a dead end. We are faced with a controversial debate, inconclusive and sometimes contradicting results; and an interest in new studies is fading. I draw the attention to three trouble areas, covering research gaps, logical inconsistencies and conceptual misunderstandings. More specifically: 1) Web decorations should be treated more as the dependent variable. 2) Experimental setups of several earlier studies appear flawed in retrospect, and their results thus overinterpreted. 3) We have not understood the evolutionary origin of web decoration. We may look at a signal that is still in an early phase of shaping, and inconclusive results may thus be inevitable. Finally, if web decorations do not act as signals, studies that look for exactly that cannot find conclusive results. In discussing these issues critically, I argue, we can open new routes for progress in finding a satisfying solution of the riddle of the silk decoration function.
A systematic review identifying the drivers and barriers to the adoption of climate-smart agriculture by smallholder farmers in Africa
Authors: Finizola e Silva Maíra , Van Schoubroeck Sophie , Cools Jan , Van Passel Steven
Published: April 2024

Climate change impact, food security concerns, and greenhouse gas emissions are pressuring agricultural production systems in developing countries. There is a need for a shift toward sustainable food systems. One of the concepts introduced to drive this shift is climate-smart agriculture (CSA), endorsed by international organizations to address multifaceted challenges. Despite widespread attention and support, the adoption of CSA among African farmers remains low. This systematic literature review aims to shed light on the factors influencing CSA adoption amongst African farmers. Within the articles identified as relevant, over 50 CSA practices and more than 40 factors influencing CSA adoption were distinguished. These influencing factors can be categorized as personal, farm-related, financial, environmental, and informational. The focus of this review is to identify and explain the overall impact (positive, negative, or mixed) of these factors on CSA adoption. Overall, many factors result in mixed effects, only some factors have an unambiguous positive or negative effect on CSA adoption. For instance, educational level emerges as a key personal factor, positively impacting CSA adoption, along with positive influences from farmers' experience and farm size among farm-related factors. Financial factors reveal distinct patterns, with income from farming and access to credit positively influencing adoption, while off-farm income exhibits a negative effect. Environmental factors, though less researched, indicate positive impacts related to changes in rainfall patterns, temperature, and droughts. Lastly, informational factors consistently exhibit a positive effect on CSA adoption, with training, access to extension, group memberships, climate information, and CSA awareness playing crucial roles. These findings provide valuable insights for policymakers seeking to enhance CSA adoption in Africa, offering a nuanced understanding of the multifaceted dynamics at play.
Intestinal bacteria-derived tryptamine and its impact on human gut microbiota
Authors: Otaru Nize , Greppi Anna , Plüss Serafina , Zünd Janina , Mujezinovic Denisa , Baur Jana , Koleva Ekaterina , Lacroix Christophe , Pugin Benoit
Published: April 2024

Tryptamine, a neuromodulator derived from tryptophan, has been shown to significantly impact the host gut homeostasis through its production by the gut microbiota. However, the characterization of tryptamine-producing gut bacteria remains limited, the factors regulating tryptamine production largely unexplored, and its effects on the rest of the gut microbial community unknown. In this study, we screened 13 intestinal strains closely related to known tryptamine producers, characterized their production kinetics, and evaluated whether tryptophan decarboxylation to tryptamine contributes to acid stress tolerance, as shown in other amino acid-dependent acid tolerance systems. We also examined the impact of tryptamine on the composition and function of four healthy human gut microbiota by conducting 48-h ex vivo fecal batch fermentations. To complement the ex vivo experiments, we tested the effect of tryptamine exposure (range: 0.5–8 mM) on the growth of 18 intestinal strains. We identified tryptamine production in five taxa, i.e., Enterocloster asparagiformis, Blautia hansenii, Clostridium nexile, Clostridium sporogenes, and Ruminococcus gnavus, with R. gnavus DSM 108212 accumulating up to 3.4 mM tryptamine after 48 h. An increased tryptophan concentration led to higher tryptamine production. However, tryptamine production was not promoted at low pH and may not protect cells from acid-induced cellular damage. Exposing gut microbial communities to 2.4 mM tryptamine caused mild changes in gut microbiota function and composition. All donors showed reduced carbohydrate consumption after 5 h, leading to donor-specific alterations of short-chain fatty acids (SCFAs) (i.e., propionate, acetate, butyrate) and branched-chain fatty acids (BCFAs) (i.e., isobutyrate and isovalerate) after 48 h. Tryptamine also induced a mild change of community structure, with a consistent reduction in the phylum Bacteroidota as well as amplicon sequence variants (ASVs) related to the genera Bacteroides, Blautia, and Faecalibacterium. We confirmed the sensitivity of Bacteroides and Faecalibacterium strains in vitro at concentrations of 2 mM and above. Multiple gut commensals remained unaffected when exposed to 8 mM tryptamine. Taken together, our findings demonstrated that intestinal bacteria-derived tryptamine is a bioactive molecule that not only alters host homeostasis locally but also modulates the physiology of gut microbial communities. The specific mechanism through which tryptamine exerts its inhibitory effects on specific gut microbes while leaving others unaffected remains to be elucidated.
Public Opinions on Removing Disincentives and Introducing Incentives for Organ Donation: Proposing a European Research Agenda
Authors: Ambagtsheer Frederike , Bunnik Eline , Pengel Liset H. M. , Reinders Marlies EJ , Elias Julio J. , Lacetera Nicola , Macis Mario
Published: April 2024

The shortage of organs for transplantations is increasing in Europe as well as globally. Many initiatives to the organ shortage, such as opt-out systems for deceased donation and expanding living donation, have been insufficient to meet the rising demand for organs. In recurrent discussions on how to reduce organ shortage, financial incentives and removal of disincentives, have been proposed to stimulate living organ donation and increase the pool of available donor organs. It is important to understand not only the ethical acceptability of (dis)incentives for organ donation, but also its societal acceptance. In this review, we propose a research agenda to help guide future empirical studies on public preferences in Europe towards the removal of disincentives and introduction of incentives for organ donation. We first present a systematic literature review on public opinions concerning (financial) (dis)incentives for organ donation in European countries. Next, we describe the results of a randomized survey experiment conducted in the United States. This experiment is crucial because it suggests that societal support for incentivizing organ donation depends on the specific features and institutional design of the proposed incentive scheme. We conclude by proposing this experiment’s framework as a blueprint for European research on this topic.
The Impact of Long-Term Fallowing on the Yield and Quality of Winter Rape and Winter and Spring Wheat
Authors: Sienkiewicz Stanisław , Żarczyński Piotr Jarosław , Wierzbowska Jadwiga , Krzebietke Sławomir Józef
Published: April 2024

The proper fallowing of soil maintains or even improves its yield potential. The aim of this research was to compare five methods of soil protection with high production potential on the yield and quality of strategic plants. The tested methods consisted of five variants: bare fallow—BF; natural fallow—NF; fodder galega (Galega orientalis Lam.)—FG; a mixture of fodder galega (Galega orientalis Lam.) with smooth brome (Bromus inermis)—FG+SB; and smooth brome (Bromus inermis)—SB. The soil had been set aside for 9 years, after which time the fallows were terminated and the fields were cropped with winter oilseed rape, winter wheat, and spring wheat in three consecutive years. After the end of fallowing, the content of Nog. and Ctot., pH, and forms of available macro- and microelements in the soil were determined. The influence of each type of fallow on the yield of seeds/grain, straw, total protein, crude fat, and the content of macronutrients in the seeds/grain and straw of the grown crops was determined. Regarding the yields of the crops, the best solution was long-term soil protection via sowing fodder galega or a mixture of fodder galega and smooth brome. A field previously maintained as a fallow with these plants (singly or in combination) could produce over twice-as-high yields of wheat and oilseed rape as those harvested from a field established on bare fallow. The yields of the cereals and oilseed rape obtained in this study prove that food security and environmental protection issues can be reconciled. The methods for protecting farmland temporarily excluded from agricultural production presented in this paper correspond perfectly to the framework of the Green Deal for Europe. Arable land excluded from cultivation can be used to overcome new challenges facing modern agriculture.
Resistant S. aureus Isolates Capable of Producing Biofilm from the Milk of Dairy Cows with Subclinical Mastitis in Slovakia
Authors: Király Ján , Hajdučková Vanda , Gregová Gabriela , Szabóová Tatiana , Pilipčinec Emil
Published: April 2024

Staphylococcus spp. is the most common cause of mastitis, with a significantly low cure rate. Bacterial characteristics like adhesion and biofilm formation, as well as extracellular factors, can affect the pathogenesis of staphylococcal mastitis. The study’s objectives were to confirm S. aureus, assess their antibiotic resistance, identify methicillin resistance genes, verify biofilm formation, and detect biofilm-associated genes from bovine mastitis samples using multiplex PCR (mPCR). From 215 milk samples, six were confirmed as S. aureus. Most isolates were sensitive to all measured antibiotics. One isolate was identified as an inducible form of MLSB resistance (macrolides, lincosamides, and streptogramin B resistance), while the other two isolates were resistant to penicillins and carboxypenicillins. In S. aureus cultures used for methicillin resistance genotypic analysis by PCR, the mecA and mecC genes were not found. Biofilm formation phenotypes were determined in four strains. An mPCR analysis revealed that all strains of S. aureus carried icaABCD, agrA, srtA, fnbA, clfA, and clfB genes. Only in one isolate was the fnbB gene detected; the bap gene was not detected in any of the isolates. This emphasizes the importance of using appropriate treatment and continuous monitoring of S. aureus to prevent the spread of antibiotic-resistant strains in dairy cow farms.
Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation
Authors: Zhu Kangwen , Zhang Yan , Tian Xiaosong , Guan Dongjie , Zhang Sheng , He Yong , Zhou Lilei
Published: April 2024

Analysis of the relationship between future land use change and agricultural non-point source pollution (ANPSP) evolution is vital to promoting sustainable regional development. By simulating future land use types, we can identify and analyze the evolution trend of ANPSP. This study takes Chongqing as a case study to establish an integrated solution based on the PLUS model, output coefficient model, and GIS technology. The solution can simulate data, identify trends, and identify key control areas under future development scenarios. The results show that the PLUS model can simulate land use types at the provincial scale with high accuracy, with a Kappa coefficient of around 0.9. The land use type changes show that urban expansion has occupied a large amount of cultivated land. From 2000 to 2020, the proportion of high-load areas with TN pollution load levels was 4.93%, 5.02%, and 4.73%, respectively. Under the two scenarios in 2030–2050, the number of high-load areas decreased, and the average load level decreased from west to east. Sensitivity analysis found that risk changes are more sensitive to the increase in fertilizer application. When the TN and TP output coefficients are increased, the number of towns with increased levels is greater than those with decreased levels when the output coefficients are decreased. Sensitivity analysis can better identify key pollution control areas. The areas sensitive to changes in farmers’ behavior are mainly the Hechuan District, Nanchuan District, Qijiang District, Jiangjin District, and Bishan District. This study provides data and decision-making support for rural green development and water environment improvement.
Headspace-Selected Ion Flow Tube Mass Spectrometry Workflows for Rapid Screening and Quantitation of Hazardous Volatile Impurities in Personal Care Products
Authors: Perkins Mark J. , Hastie Colin J. , Langford Vaughan S.
Published: April 2024

Personal care products (PCPs) are intended for regular application by consumers and therefore assuring the safety of these products is very important. Recently, benzene contamination has been highlighted in certain PCPs. The present study applies selected ion flow tube mass spectrometry (SIFT-MS) to a simultaneous headspace analysis of benzene, 1,4-dioxane, and formaldehyde—all known or suspected carcinogens—in nine haircare products with supporting qualitative analysis by gas chromatography–mass spectrometry (GC-MS). Headspace-SIFT-MS method development is compatible with the method of standard additions, which is necessary for the quantitation of volatile impurities in these complex emulsions. Benzene was quantified above the low-ng g−1 limit of quantitation (LOQ) in three products, dioxane above the sub-μg g−1 LOQ in all products, and formaldehyde above the low-μg g−1 LOQ in two products, providing a quantitative analysis at concentrations relevant to consumer safety. This study facilitated the development of generic workflows for SIFT-MS method development and application in routine analysis of PCPs. The assessment of workflows for SIFT-MS compared to a conventional GC-MS analysis suggests that 8- to 30-fold throughput enhancements may be possible for quantitative and screening analysis using SIFT-MS.
New Insights into Geometric Morphometry Applied to Fish Scales for Species Identification
Authors: Traverso Francesca , Aicardi Stefano , Bozzo Matteo , Zinni Matteo , Amaroli Andrea , Galli Loris , Candiani Simona , Vanin Stefano , Ferrando Sara
Published: April 2024

The possibility of quick and cheap recognition of a fish species from a single dermal scale would be interesting in a wide range of contexts. The methods of geometric morphometry appear to be quite promising, although wide studies comparing different approaches are lacking. We aimed to apply two methods of geometric morphometry, landmark-based and outline-based, on a dataset of scales from five different teleost species: Danio rerio, Dicentrarchus labrax, Mullus surmuletus, Sardina pilchardus, and Sparus aurata. For the landmark-based method the R library “geomorph” was used. Some issues about landmark selection and positioning were addressed and, for the first time on fish scales, an approach with both landmarks and semilandmarks was set up. For the outline-based method the R library “Momocs” was used. Despite the relatively low number of scales analyzed (from 11 to 81 for each species), both methods achieved quite good clustering of all the species. In particular, the landmark-based method used here gave generally higher R2 values in testing species clustering than the outline-based method, but it failed to distinguish between a few couples of species; on the other hand, the outline-based method seemed to catch the differences among all the couples except one. Larger datasets have the potential to achieve better results with outline-based geometric morphometry. This latter method, being free from the problem of recognizing and positioning landmarks, is also the most suitable for being automatized in future applications.
Tibetan Sentence Boundaries Automatic Disambiguation Based on Bidirectional Encoder Representations from Transformers on Byte Pair Encoding Word Cutting Method
Authors: Li Fenfang , Zhao Zhengzhang , Wang Li , Deng Han
Published: April 2024

Sentence Boundary Disambiguation (SBD) is crucial for building datasets for tasks such as machine translation, syntactic analysis, and semantic analysis. Currently, most automatic sentence segmentation in Tibetan adopts the methods of rule-based and statistical learning, as well as the combination of the two, which have high requirements on the corpus and the linguistic foundation of the researchers and are more costly to annotate manually. In this study, we explore Tibetan SBD using deep learning technology. Initially, we analyze Tibetan characteristics and various subword techniques, selecting Byte Pair Encoding (BPE) and Sentencepiece (SP) for text segmentation and training the Bidirectional Encoder Representations from Transformers (BERT) pre-trained language model. Secondly, we studied the Tibetan SBD based on different BERT pre-trained language models, which mainly learns the ambiguity of the shad (“།”) in different positions in modern Tibetan texts and determines through the model whether the shad (“།”) in the texts has the function of segmenting sentences. Meanwhile, this study introduces four models, BERT-CNN, BERT-RNN, BERT-RCNN, and BERT-DPCNN, based on the BERT model for performance comparison. Finally, to verify the performance of the pre-trained language models on the SBD task, this study conducts SBD experiments on both the publicly available Tibetan pre-trained language model TiBERT and the multilingual pre-trained language model (Multi-BERT). The experimental results show that the F1 score of the BERT (BPE) model trained in this study reaches 95.32% on 465,669 Tibetan sentences, nearly five percentage points higher than BERT (SP) and Multi-BERT. The SBD method based on pre-trained language models in this study lays the foundation for establishing datasets for the later tasks of Tibetan pre-training, summary extraction, and machine translation.
Clustering Method for Signals in the Wideband RF Spectrum Using Semi-Supervised Deep Contrastive Learning
Authors: Olesiński Adam , Piotrowski Zbigniew
Published: April 2024

This paper presents the application of self-supervised deep contrastive learning in clustering signals detected in the wideband RF spectrum, presented in the form of spectrograms. Radio clustering is a method of searching for similar signals within the analyzed part of the radio spectrum. Typically, it is based on one or several specific parameters processed from the signal in a given channel. The authors propose a slightly different, innovative approach; thanks to the self-supervised learning of neural networks, there is no need to define specific parameters, and the feature vector, enabling comparison of Euclidean distances between signals, is generated by a deep neural network trained using a contrastive loss function on a dataset containing different radio modulations. The authors describe self-supervised solutions based on contrastive learning and the methods of signal segmentation and augmentation. The training process utilizes a custom database and the Resnet-50 network with a contrastive cost function. Radio clustering is used for autonomous spectrum analysis across wide frequency ranges and enables, among other things, the detection of tactical radio stations operating with widely dispersed frequency-hopping or a significant reduction in computational power required for real-time analysis of a large number of radio signals.
Experimental Investigation of Airfoil Instability Tonal Noise Reduction Using Structured Porous Trailing Edges
Authors: Wang Yong , Zuo Kongcheng , Guo Peng , Zhao Kun , Kopiev Victor Feliksovich
Published: April 2024

Reducing the tonal noise from airfoil instabilities has attracted significant interest from the aeronautical community in the past few years. The aim of this paper is to investigate the effect of structured porous trailing edges on the tonal noise reduction performance of a symmetrical NACA 0012 airfoil. Detailed parametric testing was performed in an open-jet wind tunnel between the baseline solid trailing edge and seventeen structured porous trailing edges with different sub-millimeter-scale pores. The experimental results demonstrate that structured porous trailing edges can reduce the noticeable tonal noise of the symmetrical NACA 0012 airfoil. Moreover, the design parameters for the structured porous edges have slightly different impacts on the tonal noise reduction performance between a zero angle of attack (α = 0°) and a non-zero angle of attack (α = 10°): better airfoil tonal noise reduction is due to the porous parameters of small pore coverage, small-to-moderate chordwise spacing, and moderate spanwise spacing at α = 0°. On the other hand, the optimal combination of the structured porous edge at α = 10° is the configuration with larger pore coverage, smaller chordwise spacing, and spanwise spacing.
Enhancing Scrap Reduction in Electric Motor Manufacturing for the Automotive Industry: A Case Study Using the PDCA (Plan–Do–Check–Act) Approach
Authors: Rangel-Sánchez Miguel-Ángel , Urbina-González José-De-Jesús , Carrera-Escobedo José-Luis , Guirette-Barbosa Omar-Alejandro , Murillo-Rodríguez Virgilio-Alfonso , Celaya-Padilla José-María , Durán-Muñoz Héctor-Antonio , Cruz-Domínguez Oscar
Published: April 2024

The automotive industry is increasingly focused on waste management, elimination, and reduction to achieve sustainability and cost reduction. This focus drives the industry towards resource-efficient operations that minimize environmental impact while exceeding customer expectations. Meeting these demands necessitates the adoption of more efficient production methodologies, such as the PDCA cycle. This work presents a case study that illustrates the application of the PDCA methodology to minimize scrap generation due to process variability in a multinational company that manufactures electric motors for the automotive industry. The aim was to demonstrate how the PDCA methodology can improve quality standards by minimizing scrap generated during the manufacture of electrical armatures. Notably, the organization in this case study set a waste target of 0.7%, which was significantly exceeded. Finally, the implementation of this methodology can deliver significant economic benefits, with a total annual cost reduction of approximately USD 135,000.
Developing a Framework for Data-Driven Generation of Building Information Modeling from Sketches: Enhancing Efficiency in Space Configuration and Building Performance Analysis
Authors: Jeong WoonSeong , Kong ByungChan , Yum Sang-Guk
Published: April 2024

The demand for compact housing is on the rise, driven by the need for floor plans that accommodate stakeholders’ preferences. However, clients frequently struggle to convey their spatial needs to professionals, such as architects, due to a lack of means to present evidence, such as spatial configurations or cost projections. This study seeks to develop a methodology that translates sketched, data-driven spatial requirements into 3D building components within BIM (Building Information Modeling) to enhance spatial comprehension and offer building performance analysis, assisting in budget considerations during the initial design stages. The research methodology encompasses the formulation of a process model, its implementation, and subsequent validation. The process model outlines the data flow within the system and delineates necessary functionalities. Implementation includes the creation of systems and user interfaces for the integration of various components. Validation confirms the system’s capability to automatically transform sketched spatial requirements into BIM model elements, such as walls, floors, and roofs, and to autonomously compute material and energy expenses based on the BIM model. This system enables clients to effectively generate 3D building components from sketches, aiding stakeholders in spatial understanding and building performance evaluation through the generated BIM models.
An Innovative Polypropylene/Waste Cork Composite Material for Spirit and Wine Stopper Caps
Authors: Suffo Miguel , Pérez-Muñoz Celia , Alba Gonzalo , Villar María Pilar
Published: April 2024

In the wine bottling process, thermoplastics are commonly used to manufacture the crown of cork stoppers. The production of agglomerated cork stoppers generates a type of waste called cork powder (CoP) in large volumes with known properties but which are still underutilized. At present, although there are many agrocomposites available with additives such as natural fibers or solid residues from agricultural products, there are no studies describing the formation of these agrocomposites from petroleum-derived synthetic plastics combined with cork dust as a reinforcement for the polymeric matrix. The present study describes a novel agrocomposite, which has been obtained by mixing polypropylene-type materials, as they are some of the most widely used and versatile thermoplastics, with cork dust, which is a waste product obtained from the cork industry. The composite is obtained directly, without the need for grafting, adhesive polymers, or coupling agents. A superior mechanical performance compared to the unprocessed polymer was highlighted in the test results, thus evidencing the reinforcing function played by the waste in the polymer matrix. Therefore, this novel agrocomposite could be a promising alternative to replace some petroleum-derived synthetic plastics, which are currently experiencing high demand. The use of this new agrocomposite is well aligned with sustainability strategies, the principles of the circular economy, and oriented towards the fulfilment of the Sustainable Development Goals required by the European Union, considering that it contributes (a) to recycling agricultural waste that would otherwise be difficult to recover and valorize; (b) to the reduction in the CO2 footprint; and (c) to promoting the use of high-quality secondary raw materials.
Advancements in the Intelligent Detection of Driver Fatigue and Distraction: A Comprehensive Review
Authors: Fu Shichen , Yang Zhenhua , Ma Yuan , Li Zhenfeng , Xu Le , Zhou Huixing
Published: April 2024

Detecting the factors affecting drivers’ safe driving and taking early warning measures can effectively reduce the probability of automobile safety accidents and improve vehicle driving safety. Considering the two factors of driver fatigue and distraction state, their influences on driver behavior are elaborated from both experimental data and an accident library analysis. Starting from three modes and six types, intelligent detection methods for driver fatigue and distraction detection from the past five years are reviewed in detail. Considering its wide range of applications, the research on machine vision detection based on facial features in the past five years is analyzed, and the methods are carefully classified and compared according to their innovation points. Further, three safety warning and response schemes are proposed in light of the development of autonomous driving and intelligent cockpit technology. Finally, the paper summarizes the current state of research in the field, presents five conclusions, and discusses future trends.
An Assessment of the Natural Radioactivity Content in Pigments and an Estimation of the Radiological Health Risk for the Public
Authors: Caridi Francesco , Mottese Antonio Francesco , Paladini Giuseppe , Marguccio Santina , D’Agostino Maurizio , Belvedere Alberto , Majolino Domenico , Venuti Valentina
Published: April 2024

In this article, an investigation into the natural radioactivity content in natural inorganic pigments was carried out, together with the assessment of the radiological health risk for the public related to external exposure to ionizing radiations, via High-Purity Germanium (HPGe) γ-ray spectrometry measurements and the calculation of several indices like the absorbed γ-dose rate (D), the annual effective dose equivalent outdoor (AEDEout) and indoor (AEDEin), and the activity concentration index (I). From the obtained results, it was possible to reasonably exclude radiological hazard effects. In addition, Pearson’s correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA) were carried out with the aim of determining correlations between natural radioactivity content and radiological indices and with the analyzed samples. As a result, five clusters of the investigated pigments were recognized at the highest level of detail based on their chemical composition and mineralogical nature.
A High-Resolution Method for the Experimental Determination of the Heat Transfer Coefficients of Industrial Nozzle Systems in Heat Treatment Plants
Authors: Trampe Eileen , Rademacher Nico , Wulfmeier Maximilian , Büschgens Dominik , Pfeifer Herbert
Published: April 2024

In industrial plants, metal strips are quenched using convective heat transfer. This involves accelerating gas through a nozzle system onto the material to be quenched, resulting in a fast and uniform cooling process. The efficiency of the heat transfer is determined by the specific nozzle system. The presented work is focussed on the analysis of the heat transfer by forced convection through impingement jets both theoretically and experimentally. A unique method for determining the forced convective heat transfer coefficient is described and its application to industrial size nozzle arrays of annealing-line cooling sections is presented.
Molecular Characterization of the Gorgonzola Cheese Mycobiota and Selection of a Putative Probiotic Saccharomyces cerevisiae var. boulardii for Evaluation as a Veterinary Feed Additive
Authors: Voyron Samuele , Bietto Francesca , Fontana Mauro , Martello Elisa , Bruni Natascia , Pessione Enrica
Published: April 2024

Gorgonzola is an Italian “erborinato” blue cheese from cow’s milk, bearing blue-green “parsley-like” spots due to the spread of Penicillium roqueforti mycelium. Due to its pH, water activity, and high nutrient content, as well as the environmental conditions required for its maturation, Gorgonzola constitutes an optimal ecological niche supporting the growth of both yeasts and filamentous fungi. Therefore, exploring the abundant mycobiota present in this peculiar habitat is of great interest regarding the search for new probiotic strains. The present investigation aimed to characterize the Gorgonzola mycobiota using both phenotypic (macroscopic and microscopic morphological analyses) and genotypic (DNA barcoding) analyses to find possible putative probiotic strains to be used in veterinary medicine in feed supplements. Among the different isolated filamentous fungi (Mucor and Penicillium) and yeasts (Yarrowia, Debaryomyces, Saccharomyces, and Sporobolomyces), we selected a strain of Saccharomyces cerevisiae var. boulardii. We tested its adaptation to thermal stress and its stability in feed matrices. The overall results highlight that the selected strain is stable for three months and can be considered as a possible candidate for use as a probiotic in veterinary feed supplements.
A Series Approximation for the Analytic Fourier–Feynman Transform on Wiener Space
Authors: Chung Hyun Soo
Published: April 2024

In this paper, we first establish an evaluation formula to calculate Wiener integrals of functionals on Wiener space. We then apply our evaluation formula to carry out easy an calculation for the analytic Fourier–Feynman transform of the functionals. Some examples are furnished to illustrate the usefulness of the evaluation formula. Finally, using the evaluation formula, we establish the series approximation for the analytic Fourier–Feynman transform.
Generating Synthetic Sperm Whale Voice Data Using StyleGAN2-ADA
Authors: Kopets Ekaterina , Shpilevaya Tatiana , Vasilchenko Oleg , Karimov Artur , Butusov Denis
Published: April 2024

The application of deep learning neural networks enables the processing of extensive volumes of data and often requires dense datasets. In certain domains, researchers encounter challenges related to the scarcity of training data, particularly in marine biology. In addition, many sounds produced by sea mammals are of interest in technical applications, e.g., underwater communication or sonar construction. Thus, generating synthetic biological sounds is an important task for understanding and studying the behavior of various animal species, especially large sea mammals, which demonstrate complex social behavior and can use hydrolocation to navigate underwater. This study is devoted to generating sperm whale vocalizations using a limited sperm whale click dataset. Our approach utilizes an augmentation technique predicated on the transformation of audio sample spectrograms, followed by the employment of the generative adversarial network StyleGAN2-ADA to generate new audio data. The results show that using the chosen augmentation method, namely mixing along the time axis, makes it possible to create fairly similar clicks of sperm whales with a maximum deviation of 2%. The generation of new clicks was reproduced on datasets using selected augmentation approaches with two neural networks: StyleGAN2-ADA and WaveGan. StyleGAN2-ADA, trained on an augmented dataset using the axis mixing approach, showed better results compared to WaveGAN.
Determining Which Combinatorial Combat-Relevant Factors Contribute to Heterotopic Ossification Formation in an Ovine Model
Authors: Epperson Richard T. , Isaacson Brad M. , Rothberg David L. , Olsen Raymond E. , Kawaguchi Brooke , Rasmussen Ryan M. , Dickerson Mary , Pasquina Paul F. , Shero John , Williams Dustin L.
Published: April 2024

Traumatic heterotopic ossification (HO) is frequently observed in Service Members following combat-related trauma. Estimates suggest that ~65% of wounded warriors who suffer limb loss or major extremity trauma will experience some type of HO formation. The development of HO delays rehabilitation and can prevent the use of a prosthetic. To date there are limited data to suggest a standard mechanism for preventing HO. This may be due to inadequate animal models not producing a similar bone structure as human HO. We recently showed that traumatic HO growth is possible in an ovine model. Within that study, we demonstrated that 65% of sheep developed a human-relevant hybrid traumatic HO bone structure after being exposed to a combination of seven combat-relevant factors. Although HO formed, we did not determine which traumatic factor contributed most. Therefore, in this study, we performed individual and various combinations of surgical/traumatic factors to determine their individual contribution to HO growth. Outcomes showed that the presence of mature biofilm stimulated a large region of bone growth, while bone trauma resulted in a localized bone response as indicated by jagged bone at the linea aspera. However, it was not until the combinatory factors were included that an HO structure similar to that of humans formed more readily in 60% of the sheep. In conclusion, data suggested that traumatic HO growth can develop following various traumatic factors, but a combination of known instigators yields higher frequency size and consistency of ectopic bone.
GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues
Authors: Zhang Tianjiao , Zhang Ziheng , Li Liangyu , Ren Jixiang , Wu Zhenao , Gao Bo , Wang Guohua
Published: April 2024

The heterogeneity of tumors poses a challenge for understanding cell interactions and constructing complex ecosystems within cancer tissues. Current research strategies integrate spatial transcriptomics (ST) and single-cell sequencing (scRNA-seq) data to thoroughly analyze this intricate system. However, traditional deep learning methods using scRNA-seq data tend to filter differentially expressed genes through statistical methods. In the context of cancer tissues, where cancer cells exhibit significant differences in gene expression compared to normal cells, this heterogeneity renders traditional analysis methods incapable of accurately capturing differences between cell types. Therefore, we propose a graph-based deep learning method, GTADC, which utilizes Silhouette scores to precisely capture genes with significant expression differences within each cell type, enhancing the accuracy of gene selection. Compared to traditional methods, GTADC not only considers the expression similarity of genes within their respective clusters but also comprehensively leverages information from the overall clustering structure. The introduction of graph structure effectively captures spatial relationships and topological structures between the two types of data, enabling GTADC to more accurately and comprehensively resolve the spatial composition of different cell types within tissues. This refinement allows GTADC to intricately reconstruct the cellular spatial composition, offering a precise solution for inferring cell spatial composition. This method allows for early detection of potential cancer cell regions within tissues, assessing their quantity and spatial information in cell populations. We aim to achieve a preliminary estimation of cancer occurrence and development, contributing to a deeper understanding of early-stage cancer and providing potential support for early cancer diagnosis.
The Genetic Markers of Knee Osteoarthritis in Women from Russia
Authors: Tyurin Anton , Akhiiarova Karina , Minniakhmetov Ildar , Mokrysheva Natalia , Khusainova Rita
Published: April 2024

Osteoarthritis is a chronic progressive joint disease that clinically debuts at the stage of pronounced morphologic changes, which makes treatment difficult. In this regard, an important task is the study of genetic markers of the disease, which have not been definitively established, due to the clinical and ethnic heterogeneity of the studied populations. To find the genetic markers for the development of knee osteoarthritis (OA) in women from the Volga-Ural region of Russia, we conducted research in two stages using different genotyping methods, such as the restriction fragment length polymorphism (RFLP) measurement, TaqMan technology and competitive allele-specific PCR—KASPTM. In the first stage, we studied polymorphic variants of candidate genes (ACAN, ADAMTS5, CHST11, SOX9, COL1A1) for OA development. The association of the *27 allele of the VNTR locus of the ACAN gene was identified (OR = 1.6). In the second stage, we replicated the GWAS results (ASTN2, ALDH1A2, DVWA, CHST11, GNL3, NCOA3, FILIP/SENP1, MCF2L, GLT8D, DOT1L) for knee OA studies. The association of the *T allele of the rs7639618 locus of the DVWA gene was detected (OR = 1.54). Thus, the VNTR locus of ACAN and the rs7639618 locus of DVWA are risk factors for knee OA in women from the Volga-Ural region of Russia.
Correction: Štofilová et al. Probiotic-Based Intervention in the Treatment of Ulcerative Colitis: Conventional and New Approaches. Biomedicines 2022, 10, 2236
Authors: Štofilová Jana , Kvaková Monika , Kamlárová Anna , Hijová Emília , Bertková Izabela , Guľašová Zuzana
Published: April 2024

The authors would like to add the following clarification regarding the clinical trials evaluating the probiotic product VSL#3 cited in the published paper [...]
Narrative Review of Biological Markers in Chronic Limb-Threatening Ischemia
Authors: Popescu Alexandra Ioana , Rata Andreea Luciana , Barac Sorin , Popescu Roxana , Onofrei Roxana Ramona , Vlad Cristian , Vlad Daliborca
Published: April 2024

Background: Chronic limb-threatening ischemia (CLTI), the advanced stage of peripheral arterial disease, is diagnosed in the presence of ischemic rest pain, non-healing ulcers, or gangrene. Several studies have demonstrated that inflammation and endothelial dysfunction are some of the main substrates of CLTI. Methods: A narrative review was conducted and reported according to PRISMA guidelines. Three databases were searched—Web of Science, Medline, and EMBASE—for the studies assessing CLTI and the biological markers related to it. Results: We included 22 studies, and all the markers identified (C-reactive protein, D-dimers, fibrinogen, cytokines, IL-6, TNF-α, ICAM-1 (Intracellular Adhesion Molecule-1), VCAM-1 (Vascular Cell Adhesion Molecule-1), neutrophile-to-lymphocytes ratio (NLR), IL-8, Pentraxin-3, neutrophil gelatinase-associated lipocalin (NGAL), calprotectin, E-selectin, P-selectin, neopterin, High-Mobility Group Box-1 protein (HGMB-1), Osteoprotegerin (OPG) and Sortilin) were positively associated with advanced CLTI, with major limb or major cardiovascular events in these patients. Conclusions: All the studied markers had increased values in patients with CLTI, especially when associated with diabetes mellitus, proving a very important association between diabetes and major limb or cardiovascular events in these patients. There is a need for more studies to validate these markers in terms of diagnosis or prognosis in CLTI patients and in trying to find new medical strategies that target inflammation or endothelial dysfunction in these patients.
Design and Modelling of an Induction Heating Coil to Investigate the Thermal Response of Magnetic Nanoparticles for Hyperthermia Applications
Authors: Drake Philip , Algaddafi Ali , Swift Thomas , Abd-Alhameed Raed A.
Published: April 2024

Magnetic Field Hyperthermia is a technique where tumours are treated through an increase in local temperature upon exposure to alternating magnetic fields (AMFs) that are mediated by magnetic nano-particles (MNPs). In an AMF, these particles heat-up and kill the cells. The relationship between an AMF and the heating-rate is complex, leading to confusion when comparing data for different MNP and AMF conditions. This work allows for the thermal-response to be monitored at multiple AMF amplitudes while keeping other parameters constant. An induction-heating coil was designed based on a Zero-Voltage-Zero-Current (ZVZC) resonant circuit. The coil operates at 93 kHz with a variable DC drive-voltage (12–30 V). NEC4 software was used to model the magnetic field distribution, and MNPs were synthesised by the coprecipitation method. The magnetic field was found to be uniform at the centre of the coil and ranged from 1 kAm−1 to 12 kAm−1, depending on the DC drive-voltage. The MNPs were found to have a specific absorption rate (SAR) of 1.37 Wg−1[Fe] and 6.13 Wg−1[Fe] at 93 kHz and 2.1 kAm−1 and 12.6 kAm−1, respectively. The measured SAR value was found to be directly proportional to the product of the frequency and field-strength (SARα f Ho). This leads to the recommendation that, when comparing data from various groups, the SAR value should be normalized following this relationship and not using the more common relationship based on the square of the field intensity (SARα f Ho2).
The Effect of Antipsychotics on Cognition in Schizophrenia—A Current Narrative Review
Authors: Lungu Petru Fabian , Lungu Corina Miruna , Ciobica Alin , Balmus Ioana Miruna , Vitalaru Raluca , Mavroudis Ioannis , Dobrin Romeo , Cimpeanu Mirela , Gurzu Irina Luciana
Published: April 2024

The majority of schizophrenia-affected individuals display deficiencies in multiple cognitive domains such as attention, working memory, long-term memory, and learning, deficiencies that are stable throughout the disease. The purpose of this narrative review was to examine the effect of antipsychotics on several cognitive domains affected by schizophrenia. Methods: We searched MEDLINE, Elsevier, Scopus, and DOAJ databases for randomized controlled trials and other studies investigating the effects of typical and atypical antipsychotics on cognition in patients with schizophrenia in studies conducted in the last decade. Results: The majority of studies included in this review showed that antipsychotics (especially SGAs) have positive effects on both cognition and general psychopathology of schizophrenia. We mention that treatment with antipsychotic substances represents an ongoing effort of the researchers, who are constantly searching for the best approach to meet the mental health needs of schizophrenia patients. Conclusions: Even with those positive results, it should be noted that more studies are needed in order to fully observe the various effects of certain antipsychotic substances on cognition.
How Does Smartphone Use Impact Loneliness in the Post-COVID Landscape in Japan?
Authors: Kuramoto Yu , Nabeshima Honoka , Khan Mostafa Saidur Rahim , Kadoya Yoshihiko
Published: April 2024

Smartphone use during the active phase of the COVID-19 pandemic emerged as a crucial means of facilitating communication when strict physical distancing was recommended. Previous studies conducted during the pandemic have suggested that smartphone use contributes to reduced loneliness. However, the influence of smartphone usage on the experience of loneliness in the aftermath of the active phase of the COVID-19 pandemic, also referred to as the post-COVID era, remains unclear, particularly because many physical communication restrictions were lifted during this period. To explore the association of smartphone use with the experience of loneliness in the post-COVID era, we analyzed the latest data from 2022 and 2023, when the COVID-19 pandemic gradually concluded. Our findings revealed that, in 2023, smartphone use increased the risk of loneliness among individuals aged 50–64 years. Conversely, among the younger generations, increased smartphone use was associated with decreased loneliness. The results of our study suggest that smartphones can serve as a significant tool for alleviating loneliness among the younger generations during the post-pandemic period.