bluuebunny/crossref_metadata_2025 huggingface dataset:
Beacon, a Lightweight Deep Reinforcement Learning Benchmark Library for Flow Control
Authors: Viquerat Jonathan , Meliga Philippe , Jeken-Rico Pablo , Hachem Elie
Published: April 2024

Recently, the increasing use of deep reinforcement learning for flow control problems has led to a new area of research focused on the coupling and adaptation of the existing algorithms to the control of numerical fluid dynamics environments. Although still in its infancy, the field has seen multiple successes in a short time span, and its fast development pace is certainly partly imparted by the open-source effort that drives the expansion of the community. Yet this emerging domain is still missing a common ground to (i) ensure the reproducibility of the results and (ii) offer a proper ad hoc benchmarking basis. To this end, we propose beacon, an open-source benchmark library composed of seven lightweight one-dimensional and two-dimensional flow control problems with various characteristics, action and observation space characteristics, and CPU requirements. In this contribution, the seven considered problems are described, and reference control solutions are provided. The sources for the following work are publicly available.
Preliminary Estimation for Software Development Projects Empowered with a Method of Recommending Optimal Duration and Team Composition
Authors: Teslyuk Vasyl , Batyuk Anatoliy , Voityshyn Volodymyr
Published: April 2024

In the early software development stages, the aim of estimation is to obtain a rough understanding of the timeline and resources required to implement a potential project. The current study is devoted to a method of preliminary estimation applicable at the beginning of the software development life cycle when the level of uncertainty is high. The authors’ concepts of the estimation life cycle, the estimable items breakdown structure, and a system of working-time balance equations in conjunction with an agile-fashioned sizing approach are used. To minimize the experts’ working time spent on preliminary estimation, the authors applied a decision support procedure based on integer programming and the analytic hierarchy process. The method’s outcomes are not definitive enough to make commitments; instead, they are supposed to be used for communication with project stakeholders or as inputs for the subsequent estimation stages. For practical usage of the preliminary estimation method, a semistructured business process is proposed.
Human versus Rat PRF on Collagen Membranes: A Pilot Study of Mineralization in Rat Calvaria Defect Model
Authors: Apaza Alccayhuaman Karol Ali , Heimel Patrick , Tangl Stefan , Lettner Stefan , Kampleitner Carina , Panahipour Layla , Kuchler Ulrike , Gruber Reinhard
Published: April 2024

Platelet-rich fibrin, the coagulated plasma fraction of blood, is commonly used to support natural healing in clinical applications. The rat calvaria defect is a standardized model to study bone regeneration. It remains, however, unclear if the rat calvaria defect is appropriate to investigate the impact of human PRF (Platelet-Rich Fibrin) on bone regeneration. To this end, we soaked Bio-Gide® collagen membranes in human or rat liquid concentrated PRF before placing them onto 5 mm calvarial defects in Sprague Dawley rats. Three weeks later, histology and micro-computed tomography (μCT) were performed. We observed that the collagen membranes soaked with rat PRF show the characteristic features of new bone and areas of mineralized collagen matrix, indicated by a median mineralized volume of 1.5 mm3 (range: 0.9; 5.3 mm3). Histology revealed new bone growing underneath the membrane and hybrid bone where collagen fibers are embedded in the new bone. Moreover, areas of passive mineralization were observed. The collagen membranes soaked with human PRF, however, were devoid of histological features of new bone formation in the center of the defect; only occasionally, new bone formed at the defect margins. Human PRF (h-PRF) caused a median bone volume of 0.9 mm3 (range: 0.3–3.3 mm3), which was significantly lower than what was observed with rat PRF (r-PRF), with a BV median of 1.2 mm3 (range: 0.3–5.9 mm3). Our findings indicate that the rat calvaria defect model is suitable for assessing the effects of rat PRF on bone formation, but caution is warranted when extrapolating conclusions regarding the efficacy of human PRF.
Pathogenic Homocystinuria-Associated T236N Mutation Dramatically Alters the Biochemical Properties of Cystathionine Beta-Synthase Protein
Authors: Al-Sadeq Duaa W. , Thanassoulas Angelos , Theodoridou Maria , Nasrallah Gheyath K. , Nomikos Michail
Published: April 2024

Background: Cystathione beta-synthase (CBS) T236N is a novel mutation associated with pyridoxine non-responsiveness, which presents a significant difficulty in the medical treatment of homocystinuria. Reported severe phenotypes in homocystinuria patients highlight the urgent requirement to comprehend the molecular mechanisms underlying mutation pathogenicity for the advancement of the disease. Methodology: In this study, we used a multidisciplinary approach to investigate the molecular properties of bacterially expressed and purified recombinant CBST236N protein, which we directly compared to those of the wild-type (CBSWT) protein. Results: Our data revealed a profound impact of the p.T236N mutation on CBS enzymatic activity, with a dramatic reduction of ~96% compared to the CBSWT protein. Circular dichroism (CD) experiments indicated that the p.T236N mutation did not significantly alter the secondary structure of the protein. However, CD spectra unveiled distinct differences in the thermal stability of CBSWT and CBST236N mutant protein species. In addition, chemical denaturation experiments further highlighted that the CBSWT protein exhibited greater thermodynamic stability than the CBST236N mutant, suggesting a destabilizing effect of this mutation. Conclusions: Our findings provide an explanation of the pathogenicity of the p.T236N mutation, shedding light on its role in severe homocystinuria phenotypes. This study contributes to a deeper understanding of CBS deficiency and may improve the development of targeted therapeutic strategies for affected individuals.
The Role of Biomarkers in Diagnosis of Sepsis and Acute Kidney Injury
Authors: Ferreira Gillene Santos , Frota Melissa Lopes , Gonzaga Maria José Dias , Vattimo Maria de Fátima Fernandes , Lima Camila
Published: April 2024

Sepsis and acute kidney injury (AKI) are two major public health concerns that contribute significantly to illness and death worldwide. Early diagnosis and prompt treatment are essential for achieving the best possible outcomes. To date, there are no specific clinical, imaging, or biochemical indicators available to diagnose sepsis, and diagnosis of AKI based on the KDIGO criterion has limitations. To improve the diagnostic process for sepsis and AKI, it is essential to continually evolve our understanding of these conditions. Delays in diagnosis and appropriate treatment can have serious consequences. Sepsis and AKI often occur together, and patients with kidney dysfunction are more prone to developing sepsis. Therefore, identifying potential biomarkers for both conditions is crucial. In this review, we talk about the main biomarkers that evolve the diagnostic of sepsis and AKI, namely neutrophil gelatinase-associated lipocalin (NGAL), proenkephalin (PENK), and cell-free DNA.
lncRNA Biomarkers of Glioblastoma Multiforme
Authors: Pokorná Markéta , Černá Marie , Boussios Stergios , Ovsepian Saak V. , O’Leary Valerie Bríd
Published: April 2024

Long noncoding RNAs (lncRNAs) are RNA molecules of 200 nucleotides or more in length that are not translated into proteins. Their expression is tissue-specific, with the vast majority involved in the regulation of cellular processes and functions. Many human diseases, including cancer, have been shown to be associated with deregulated lncRNAs, rendering them potential therapeutic targets and biomarkers for differential diagnosis. The expression of lncRNAs in the nervous system varies in different cell types, implicated in mechanisms of neurons and glia, with effects on the development and functioning of the brain. Reports have also shown a link between changes in lncRNA molecules and the etiopathogenesis of brain neoplasia, including glioblastoma multiforme (GBM). GBM is an aggressive variant of brain cancer with an unfavourable prognosis and a median survival of 14–16 months. It is considered a brain-specific disease with the highly invasive malignant cells spreading throughout the neural tissue, impeding the complete resection, and leading to post-surgery recurrences, which are the prime cause of mortality. The early diagnosis of GBM could improve the treatment and extend survival, with the lncRNA profiling of biological fluids promising the detection of neoplastic changes at their initial stages and more effective therapeutic interventions. This review presents a systematic overview of GBM-associated deregulation of lncRNAs with a focus on lncRNA fingerprints in patients’ blood.
Combinatorial Therapy: Targeting CD133+ Glioma Stem-like Cells with a Polysaccharide–Prodrug Complex Functionalised Gold Nanocages
Authors: Raveendran Sreejith , Giram Amit , Elmi Mehrnaz , Ray Santanu , Ireson Christopher , Alavijeh Mo , Savina Irina N.
Published: April 2024

Cancer treatments are advancing to harness the body’s immune system against tumours, aiming for lasting effects. This progress involves combining potent chemotherapy drugs with immunogens to kill cancer cells and trigger lasting immunity. Developing new prodrugs that integrate both chemotherapy and immune-boosting elements could significantly improve anticancer outcomes by activating multiple mechanisms to kill cancer cells. While bacterial polysaccharides are typically not used in therapy due to their immune-stimulating properties, we propose a safe application of an extremophilic bacterial polysaccharide, Mauran (MR), modified with the anticancer drug 5-fluorouracil (5FU) to create a novel prodrug. This obtained prodrug, chloracetyl-MR-5FU, is specifically targeted using gold nanocages to CD133+ glioma cells. Test results have shown a high encapsulation efficiency of the drug during the polysaccharide modification process; its anticancer activity was demonstrated in vitro and the release of the prodrug was demonstrated in ex vivo studies.
Cytomegalovirus Immunoglobulin G Levels and Subclinical Arterial Disease among People Living with HIV in Botswana: A Cross-Sectional Study
Authors: Moshomo Thato , Molefe-Baikai Onkabetse Julia , Bennett Kara , Gaolathe Tendani , Moyo Sikhulile , Gaseitsewe Simani , Mohammed Terence , Lockman Shahin , Mosepele Mosepele
Published: April 2024

Cytomegalovirus (CMV) has been linked with increased cardiovascular risk and monocyte activation in people living with HIV (PLWH). This cross-sectional study aimed to compare CMV immunoglobulin G (IgG) levels between combined antiretroviral therapy (cART)-treated PLWH versus ART-naïve PLWH and those without HIV, and to investigate their associations with biomarkers of endothelial injury and carotid atherosclerosis, in Gaborone, Botswana. All participants were between 30 and 50 years old. Carotid intimal media thickness (cIMT) and biomarkers of endothelial injury and monocyte activation were also assessed. The association between quantitative CMV IgG and cardiovascular disease risk was assessed in multivariate logistic regression analysis. The results showed that the mean CMV IgG level among ART-naïve participants was significantly higher than both the cART group and controls. However, CMV IgG levels did not differ significantly between the controls and cART groups. Among PLWH, CMV IgG levels were associated with ICAM-1 levels and cIMT. Increases in CMV IgG among ART-naïve participants were significantly associated with increases in log VCAM-1. In conclusion, CMV IgG levels are elevated among PLWH in sub-Saharan Africa, and higher levels are associated with biomarkers of endothelial injury and cIMT. Future research should investigate the long-term impact of elevated CMV IgG among PLWH.
Methylglyoxal and Advanced Glycation End Products (AGEs): Targets for the Prevention and Treatment of Diabetes-Associated Bladder Dysfunction?
Authors: Oliveira Akila Lara , de Oliveira Mariana Gonçalves , Mónica Fabíola Zakia , Antunes Edson
Published: April 2024

Methylglyoxal (MGO) is a highly reactive α-dicarbonyl compound formed endogenously from 3-carbon glycolytic intermediates. Methylglyoxal accumulated in plasma and urine of hyperglycemic and diabetic individuals acts as a potent peptide glycation molecule, giving rise to advanced glycation end products (AGEs) like arginine-derived hydroimidazolone (MG-H1) and carboxyethyl-lysine (CEL). Methylglyoxal-derived AGEs exert their effects mostly via activation of RAGE, a cell surface receptor that initiates multiple intracellular signaling pathways, favoring a pro-oxidant environment through NADPH oxidase activation and generation of high levels of reactive oxygen species (ROS). Diabetic bladder dysfunction is a bothersome urological complication in patients with poorly controlled diabetes mellitus and may comprise overactive bladder, urge incontinence, poor emptying, dribbling, incomplete emptying of the bladder, and urinary retention. Preclinical models of type 1 and type 2 diabetes have further confirmed the relationship between diabetes and voiding dysfunction. Interestingly, healthy mice supplemented with MGO for prolonged periods exhibit in vivo and in vitro bladder dysfunction, which is accompanied by increased AGE formation and RAGE expression, as well as by ROS overproduction in bladder tissues. Drugs reported to scavenge MGO and to inactivate AGEs like metformin, polyphenols, and alagebrium (ALT-711) have shown favorable outcomes on bladder dysfunction in diabetic obese leptin-deficient and MGO-exposed mice. Therefore, MGO, AGEs, and RAGE levels may be critically involved in the pathogenesis of bladder dysfunction in diabetic individuals. However, there are no clinical trials designed to test drugs that selectively inhibit the MGO–AGEs–RAGE signaling, aiming to reduce the manifestations of diabetes-associated bladder dysfunction. This review summarizes the current literature on the role of MGO–AGEs–RAGE–ROS axis in diabetes-associated bladder dysfunction. Drugs that directly inactivate MGO and ameliorate bladder dysfunction are also reviewed here.
ACE Phenotyping in Human Blood and Tissues: Revelation of ACE Outliers and Sex Differences in ACE Sialylation
Authors: Enyedi Enikő E. , Petukhov Pavel A. , Kozuch Alexander J. , Dudek Steven M. , Toth Attila , Fagyas Miklós , Danilov Sergei M.
Published: April 2024

Angiotensin-converting enzyme (ACE) metabolizes a number of important peptides participating in blood pressure regulation and vascular remodeling. Elevated ACE expression in tissues (which is generally reflected by blood ACE levels) is associated with an increased risk of cardiovascular diseases. Elevated blood ACE is also a marker for granulomatous diseases. Decreased blood ACE activity is becoming a new risk factor for Alzheimer’s disease. We applied our novel approach—ACE phenotyping—to characterize pairs of tissues (lung, heart, lymph nodes) and serum ACE in 50 patients. ACE phenotyping includes (1) measurement of ACE activity with two substrates (ZPHL and HHL); (2) calculation of the ratio of hydrolysis of these substrates (ZPHL/HHL ratio); (3) determination of ACE immunoreactive protein levels using mAbs to ACE; and (4) ACE conformation with a set of mAbs to ACE. The ACE phenotyping approach in screening format with special attention to outliers, combined with analysis of sequencing data, allowed us to identify patient with a unique ACE phenotype related to decreased ability of inhibition of ACE activity by albumin, likely due to competition with high CCL18 in this patient for binding to ACE. We also confirmed recently discovered gender differences in sialylation of some glycosylation sites of ACE. ACE phenotyping is a promising new approach for the identification of ACE phenotype outliers with potential clinical significance, making it useful for screening in a personalized medicine approach.
Signatures and Discriminative Abilities of Multi-Omics between States of Cognitive Decline
Authors: Anagnostakis Filippos , Kokkorakis Michail , Walker Keenan A. , Davatzikos Christos
Published: April 2024

Dementia poses a substantial global health challenge, warranting an exploration of its intricate pathophysiological mechanisms and potential intervention targets. Leveraging multi-omic technology, this study utilizes data from 2251 participants to construct classification models using lipidomic, gut metabolomic, and cerebrospinal fluid (CSF) proteomic markers to distinguish between the states of cognitive decline, namely, the cognitively unimpaired state, mild cognitive impairment, and dementia. The analysis identifies three CSF proteins (apolipoprotein E, neuronal pentraxin-2, and fatty-acid-binding protein), four lipids (DEDE.18.2, DEDE.20.4, LPC.O.20.1, and LPC.P.18.1), and five serum gut metabolites (Hyodeoxycholic acid, Glycohyodeoxycholic acid, Hippuric acid, Glyceric acid, and Glycodeoxycholic acid) capable of predicting dementia prevalence from cognitively unimpaired participants, achieving Area Under the Curve (AUC) values of 0.879 (95% CI: 0.802–0.956), 0.766 (95% CI: 0.700–0.835), and 0.717 (95% CI: 0.657–0.777), respectively. Furthermore, exclusively three CSF proteins exhibit the potential to predict mild cognitive impairment prevalence from cognitively unimpaired subjects, with an AUC of 0.760 (95% CI: 0.691–0.828). In conclusion, we present novel combinations of lipids, gut metabolites, and CSF proteins that showed discriminative abilities between the states of cognitive decline and underscore the potential of these molecules in elucidating the mechanisms of cognitive decline.
The Tibial Tuberosity–Trochlear Groove Distance Can either Increase or Decrease during Adolescent Growth
Authors: Randsborg Per-Henrik , Banitalebi Hasan , Årøen Asbjørn , Straume-Næsheim Truls
Published: April 2024

Increased Tibial Tuberosity–Trochlear Groove (TT-TG) distance is a risk factor for recurrent lateral patella dislocations (RLPD). Population-based cross-sectional studies on healthy subjects demonstrate that the TT-TG increases gradually during growth until skeletal maturity, but changes in the TT-TG distance during adolescence in patients with RLPD on an individual basis have not been previously investigated. This study aimed to measure changes in TT-TG distance during skeletal maturity. The TT-TG of 13 consecutive patients with open physes (mean age 13 years) with RLPD was measured on MRI at baseline and three years later. The change in TT-TG distance over the three-year period was measured. The mean change in TT-TG distance from the baseline to the three-year follow-up increased overall (2.9 mm, 95% Confidence Interval (CI) 2.1–3.7). However, the TT-TG distance could either increase or decrease during final growth. Our results suggest that the TT-TG distance in patients suffering from RLPD may either decrease or increase individually during the growth spurt. This contradicts the current concept that the TT-TG distance increases gradually during growth.
Applying Bounding Techniques on Grammatical Evolution
Authors: Tsoulos Ioannis G. , Tzallas Alexandros , Karvounis Evangelos
Published: April 2024

The Grammatical Evolution technique has been successfully applied to some datasets from various scientific fields. However, in Grammatical Evolution, the chromosomes can be initialized at wide value intervals, which can lead to a decrease in the efficiency of the underlying technique. In this paper, a technique for discovering appropriate intervals for the initialization of chromosomes is proposed using partition rules guided by a genetic algorithm. This method has been applied to feature construction techniques used in a variety of scientific papers. After successfully finding a promising interval, the feature construction technique is applied and the chromosomes are initialized within that interval. This technique was applied to a number of known problems in the relevant literature, and the results are extremely promising.
Role of B Cells beyond Antibodies in HBV-Induced Oncogenesis: Fulminant Cancer in Common Variable Immunodeficiency—Clinical and Immunotransplant Implications with a Review of the Literature
Authors: Zdziarski Przemyslaw , Gamian Andrzej
Published: April 2024

Although lymphoma is the most frequent malignancy in common variable immunodeficiency (CVID), solid tumors, especially affected by oncogenic viruses, are not considered. Furthermore, in vitro genetic studies and cell cultures are not adequate for immune system and HBV interaction. We adopted a previously introduced clinical model of host–virus interaction (i.e., infectious process in immunodeficiency) for analysis of B cells and the specific IgG role (an observational study of a CVID patient who received intravenous immunoglobulin (IVIG). Suddenly, the patient deteriorated and a positive results of for HBs and HBV-DNA (369 × 106 copies) were detected. Despite lamivudine therapy and IVIG escalation (from 0.3 to 0.4 g/kg), CT showed an 11 cm intrahepatic tumor (hepatocellular carcinoma). Anti-HBs were positive in time-lapse analysis (range 111–220 IU/mL). Replacement therapy intensification was complicated by an immune complex disease with renal failure. Fulminant HCC in CVID and the development of a tumor as the first sign is of interest. Unfortunately, treatment with hepatitis B immune globulins (HBIG) plays a major role in posttransplant maintenance therapy. Anti-HB substitution has not been proven to be effective, oncoprotective, nor safe. Therefore, immunosuppression in HBV-infected recipients should be carefully minimized, and patient selection more precise with the exclusion of HBV-positive donors. Our clinical model showed an HCC pathway with important humoral host factors, contrary to epidemiological/cohort studies highlighting risk factors only (e.g., chronic hepatitis). The lack of cell cooperation as well as B cell deficiency observed in CVID play a crucial role in high HBV replication, especially in carcinogenesis.
DiffFSRE: Diffusion-Enhanced Prototypical Network for Few-Shot Relation Extraction
Authors: Chen Yang , Shi Bowen
Published: April 2024

Supervised learning methods excel in traditional relation extraction tasks. However, the quality and scale of the training data heavily influence their performance. Few-shot relation extraction is gradually becoming a research hotspot whose objective is to learn and extract semantic relationships between entities with only a limited number of annotated samples. In recent years, numerous studies have employed prototypical networks for few-shot relation extraction. However, these methods often suffer from overfitting of the relation classes, making it challenging to generalize effectively to new relationships. Therefore, this paper seeks to utilize a diffusion model for data augmentation to address the overfitting issue of prototypical networks. We propose a diffusion model-enhanced prototypical network framework. Specifically, we design and train a controllable conditional relation generation diffusion model on the relation extraction dataset, which can generate the corresponding instance representation according to the relation description. Building upon the trained diffusion model, we further present a pseudo-sample-enhanced prototypical network, which is able to provide more accurate representations for prototype classes, thereby alleviating overfitting and better generalizing to unseen relation classes. Additionally, we introduce a pseudo-sample-aware attention mechanism to enhance the model’s adaptability to pseudo-sample data through a cross-entropy loss, further improving the model’s performance. A series of experiments are conducted to prove our method’s effectiveness. The results indicate that our proposed approach significantly outperforms existing methods, particularly in low-resource one-shot environments. Further ablation analyses underscore the necessity of each module in the model. As far as we know, this is the first research to employ a diffusion model for enhancing the prototypical network through data augmentation in few-shot relation extraction.
LF3PFL: A Practical Privacy-Preserving Federated Learning Algorithm Based on Local Federalization Scheme
Authors: Li Yong , Xu Gaochao , Meng Xutao , Du Wei , Ren Xianglin
Published: April 2024

In the realm of federated learning (FL), the exchange of model data may inadvertently expose sensitive information of participants, leading to significant privacy concerns. Existing FL privacy-preserving techniques, such as differential privacy (DP) and secure multi-party computing (SMC), though offering viable solutions, face practical challenges including reduced performance and complex implementations. To overcome these hurdles, we propose a novel and pragmatic approach to privacy preservation in FL by employing localized federated updates (LF3PFL) aimed at enhancing the protection of participant data. Furthermore, this research refines the approach by incorporating cross-entropy optimization, carefully fine-tuning measurement, and improving information loss during the model training phase to enhance both model efficacy and data confidentiality. Our approach is theoretically supported and empirically validated through extensive simulations on three public datasets: CIFAR-10, Shakespeare, and MNIST. We evaluate its effectiveness by comparing training accuracy and privacy protection against state-of-the-art techniques. Our experiments, which involve five distinct local models (Simple-CNN, ModerateCNN, Lenet, VGG9, and Resnet18), provide a comprehensive assessment across a variety of scenarios. The results clearly demonstrate that LF3PFL not only maintains competitive training accuracies but also significantly improves privacy preservation, surpassing existing methods in practical applications. This balance between privacy and performance underscores the potential of localized federated updates as a key component in future FL privacy strategies, offering a scalable and effective solution to one of the most pressing challenges in FL.
Support without Status: Inequities in Student–Advisor Relational Dynamics between First-Generation and Continuing-Generation Doctoral Students
Authors: McCain Jesse , Roksa Josipa , Breen Stephanie
Published: April 2024

One of the most important developmental relationships in the doctoral student experience is that of the faculty advisor, and yet we know little about whether and how advisor relationships vary between first-generation and continuing-generation doctoral students. Drawing on qualitative interviews with 83 late-stage doctoral students in biological sciences, we explore differences in student perceptions of their relationships with advisors. Narratives reveal a continuum of relationship types, including strained, evolving, supportive, and equal. In equal relationships, doctoral students feel more like collegial partners working alongside their advisors. While continuing-generation and first-generation students are similarly represented among strained and evolving relationships, first-generation students rarely attain equal relationship status. The presented findings offer implications for understanding how inequality shapes student–advisor relationships, the role of collegiality in doctoral education’s hidden curriculum, and the supports needed to foster equity for first-generation students in graduate programs.
Canicross Pilot Programme: Basic Considerations for Its Implementation as an Extracurricular Sports Activity
Authors: Gonzalez-Santamaria Xabier , Borrajo Erika , Sanchez-Mencia Eneko , Aurrekoetxea-Casaus Maite
Published: April 2024

Canicross is a sport that consists of running while being pulled by a dog in a natural environment. Due to the benefits to health and well-being that it brings to the people and dogs that practise it, this sport could be implemented as an animal-assisted intervention (AAI) in the educational field. Against this background, the present work describes a pilot experience carried out in an educational centre in the Basque Country for the implementation of canicross as an extracurricular sports activity. The main objective is to describe the educational potential of canicross as an extracurricular activity that fosters students’ values of respect for animals and physical activity (PA) in natural environments. The results of this innovative experience provide the first evidence of the valuable role of animal activities in this educational context, where current academic research is practically non-existent. In conclusion, we highlight the novelty of the proposal and the motivating effect that the dogs in this case had among the students in encouraging them to practise PA and adhere to values of respect and animal welfare.
Advancing into Millimeter Wavelengths for IoT: Multibeam Modified Planar Luneburg Lens Antenna with Porous Plastic Material
Authors: Pourahmadazar Javad , Virdee Bal S. , Denidni Tayeb A.
Published: April 2024

This paper introduces an innovative antenna design utilizing a cylindrical dielectric Luneburg lens tailored for 60 GHz Internet of Things (IoT) applications. To optimize V-band communications, the permittivity of the dielectric medium is strategically adjusted by precisely manipulating the physical porosity. In IoT scenarios, employing a microstrip dipole antenna with an emission pattern resembling cos10 enhances beam illumination within the waveguide, thereby improving communication and sensing capabilities. The refractive index gradient of the Luneburg lens is modified by manipulating the material’s porosity using air holes, prioritizing signal accuracy and reliability. Fabricated with polyimide using 3D printing, the proposed antenna features a slim profile ideal for IoT applications with space constraints, such as smart homes and unmanned aerial vehicles. Its innovative design is underscored by selective laser sintering (SLS), offering scalable and cost-effective production. Measured results demonstrate the antenna’s exceptional performance, surpassing IoT deployment standards. This pioneering approach to designing multibeam Luneburg lens antennas, leveraging 3D printing’s porosity control for millimeter-wave applications, represents a significant advancement in antenna technology with scanning ability between −67 and 67 degrees. It paves the way for enhanced IoT infrastructure characterized by advanced sensing capabilities and improved connectivity.
SlowR50-SA: A Self-Attention Enhanced Dynamic Facial Expression Recognition Model for Tactile Internet Applications
Authors: Neshov Nikolay , Christoff Nicole , Sechkova Teodora , Tonchev Krasimir , Manolova Agata
Published: April 2024

Emotion recognition from facial expressions is a challenging task due to the subtle and nuanced nature of facial expressions. Within the framework of Tactile Internet (TI), the integration of this technology has the capacity to completely transform real-time user interactions, by delivering customized emotional input. The influence of this technology is far-reaching, as it may be used in immersive virtual reality interactions and remote tele-care applications to identify emotional states in patients. In this paper, a novel emotion recognition algorithm is presented that integrates a Self-Attention (SA) module into the SlowR50 backbone (SlowR50-SA). The experiments on the DFEW and FERV39K datasets demonstrate that the proposed model achieves good performance in terms of both Unweighted Average Recall (UAR) and Weighted Average Recall (WAR) metrics, achieving a UAR (WAR) of 57.09% (69.87%) on the DFEW dataset, and UAR (WAR) of 39.48% (49.34%) on the FERV39K dataset. Notably, SlowR50-SA operates with only eight frames of input at low temporal resolution, highlighting its efficiency. Furthermore, the algorithm has the potential to be integrated into Tactile Internet applications, where it can be used to enhance the user experience by providing real-time emotion feedback. SlowR50-SA can also be used to enhance virtual reality experiences by providing personalized haptic feedback based on the user’s emotional state. It can also be used in remote tele-care applications to detect signs of stress, anxiety, or depression in patients.
Modified Rime-Ice Growth Optimizer with Polynomial Differential Learning Operator for Single- and Double-Diode PV Parameter Estimation Problem
Authors: Hakmi Sultan Hassan , Alnami Hashim , Moustafa Ghareeb , Ginidi Ahmed R. , Shaheen Abdullah M.
Published: April 2024

A recent optimization algorithm, the Rime Optimization Algorithm (RIME), was developed to efficiently utilize the physical phenomenon of rime-ice growth. It simulates the hard-rime and soft-rime processes, constructing the mechanisms of hard-rime puncture and soft-rime search. In this study, an enhanced version, termed Modified RIME (MRIME), is introduced, integrating a Polynomial Differential Learning Operator (PDLO). The incorporation of PDLO introduces non-linearities to the RIME algorithm, enhancing its adaptability, convergence speed, and global search capability compared to the conventional RIME approach. The proposed MRIME algorithm is designed to identify photovoltaic (PV) module characteristics by considering diverse equivalent circuits, including the One-Diode Model (ONE-DM) and Two-Diode Model TWO-DM, to determine the unspecified parameters of the PV. The MRIME approach is compared to the conventional RIME method using two commercial PV modules, namely the STM6-40/36 module and R.T.C. France cell. The simulation results are juxtaposed with those from contemporary algorithms based on published research. The outcomes related to recent algorithms are also compared with those of the MRIME algorithm in relation to various existing studies. The simulation results indicate that the MRIME algorithm demonstrates substantial improvement rates for the STM6-40/36 module and R.T.C. France cell, achieving 1.16% and 18.45% improvement for the ONE-DM, respectively. For the TWO-DM, it shows significant improvement rates for the two modules, reaching 1.14% and 50.42%, respectively. The MRIME algorithm, in comparison to previously published results, establishes substantial superiority and robustness.
Flow Characteristic Analysis of the Impeller Inlet Diameter in a Double-Suction Pump
Authors: Jang Hyunjun , Suh Junho
Published: April 2024

Pumps are considered crucial mechanical devices in any industry. Especially, double-suction pumps, due to their high-flow design and high head, are utilized in diverse industrial sectors. However, despite these advantages, double-suction pumps are vulnerable to issues like losses, vibrations, and cavitation. Pump vibration is mainly caused by suction recirculation occurring at the impeller inlet. Therefore, this study investigates the impact of the impeller inlet design on enhancing the stability of double-suction pumps while expanding the operating flow range. Through a validated CFD study, the influence of the impeller inlet passage size on the head and efficiency was analyzed. Furthermore, research was conducted on the phenomenon of suction recirculation occurring at the impeller inlet, proposing design guidelines to minimize it, especially for operation at low flow rates. The results demonstrate that the ratio of the hub diameter to the shroud diameter at the impeller inlet significantly impacts the avoidance of recirculation at low flow rates. These findings are expected to contribute to improving the stability and efficiency of high-flow pumps.
Local DER Control with Reduced Loop Interactions in Active Distribution Networks
Authors: Fusco Giuseppe , Russo Mario
Published: April 2024

Active Distribution Networks are Multi-Input Multi-Output (MIMO) systems with coupled dynamics, which cause interactions among the control loops of Distributed Energy Resources (DERs). This undesired effect leads to performance degradation of voltage control. To mitigate the effects of this unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction’s sources. In detail, each DER is equipped with a double-loop PI to control the active and reactive power output of the voltage source converter, which connects the DER to the network’s node. Furthermore, to guarantee ancillary services, the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter’s pulse are designed according to a procedure with two sequential steps based on the Internal Model Control (IMC) technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in the presence of model parameter uncertainty in the MIMO plant, modeling various operating conditions of the ADN, including a step connection of large loads, renewable energy source variations, and changes in the substation transformer ratio.
Convolutional Long Short-Term Memory (ConvLSTM)-Based Prediction of Voltage Stability in a Microgrid
Authors: Abbass Muhammad Jamshed , Lis Robert , Awais Muhammad , Nguyen Tham X.
Published: April 2024

The maintenance of an uninterrupted electricity supply to meet demand is of paramount importance for maintaining the stable operation of an electrical power system. Machine learning and deep learning play a crucial role in maintaining that stable operation. These algorithms have the ability to acquire knowledge from past data, enabling them to efficiently identify and forecast potential scenarios of instability in the future. This work presents a hybrid convolutional long short-term memory (ConvLSTM) technique for training and predicting nodal voltage stability in an IEEE 14-bus microgrid. Analysis of the findings shows that the suggested ConvLSTM model exhibits the highest level of precision, reaching a value of 97.65%. Furthermore, the ConvLSTM model has been shown to perform better compared to alternative machine learning and deep learning models such as convolutional neural networks, k-nearest neighbors, and support vector machine models, specifically in terms of accurately forecasting voltage stability. The IEEE 14-bus system tests indicate that the suggested method can quickly and accurately determine the stability status of the system. The comparative analysis obtained the results and further justified the efficiency and voltage stability of the proposed model.
The Lower Paleolithic Engravings of Bilzingsleben, Germany
Authors: Bednarik Robert G.
Published: April 2024

Some of the earliest known engravings are described, analyzed, and interpreted, following their microscopic examination. They are of significance in exploring the cognitive evolution of hominins several hundred thousand years ago and have not been described together before. The Steinrinne site near Bilzingsleben, north of Weimar, Germany, is one of Europe’s most important Lower Paleolithic occupation sites. Its extensive human habitation floor, excavated over 1000 square meters, comprises some of the world’s oldest evidence of dwellings, broadly matching or exceeding the age of examples proposed in Africa, India, and France. It has yielded numerous hominin remains, many wooden artefacts, other exquisitely preserved organic remains, and more portable engravings than any other Middle Pleistocene site. The latter are reviewed here, presenting the results of a detailed microscopic examination of the main finds. Bilzingsleben has so far produced the largest number of engraved Lower Paleolithic objects reported, which are particularly important to exploring the cognitive developments of hominins.
Challenges in Restoring Mediterranean Seagrass Ecosystems in the Anthropocene
Authors: Montefalcone Monica
Published: April 2024

The intense human pressures in the Anthropocene epoch are causing an alarming decline in marine coastal ecosystems and an unprecedented loss of biodiversity. This situation underscores the urgency of making ecological restoration a global priority to recover degraded ecosystems. Meadows of the endemic Mediterranean seagrass Posidonia oceanica have lost more than half of their original extent in the last century, necessitating immediate conservation and management measures, supported by active restoration interventions. This paper explores new opportunities and provides specific recommendations to enhance restoration as a fundamental strategy for reversing the decline of P. oceanica ecosystems in the Mediterranean Sea. When a return to a historical pristine reference condition may not be feasible in the short term or desirable given current environmental conditions and uncertainty, transplanting the tolerant and fast-growing seagrass species Cymodocea nodosa could facilitate natural recolonization. This would occur through secondary ecological succession, benefiting the sensitive and slow-growing species P. oceanica. Future global and local efforts should primarily focus on proactive management to prevent further alterations by planning appropriate conservation measures in a timely manner to mitigate and reverse global changes. As a secondary step, restoration programs can be implemented with a focus on ‘target-oriented’ rather than ‘reference-oriented’ conditions, aiming to establish ecosystems capable of sustaining the future rather than replicating the historical environment.
Triple Attention Mechanism with YOLOv5s for Fish Detection
Authors: Long Wei , Wang Yawen , Hu Lingxi , Zhang Jintao , Zhang Chen , Jiang Linhua , Xu Lihong
Published: April 2024

Traditional fish farming methods suffer from backward production, low efficiency, low yield, and environmental pollution. As a result of thorough research using deep learning technology, the industrial aquaculture model has experienced gradual maturation. A variety of complex factors makes it difficult to extract effective features, which results in less-than-good model performance. This paper proposes a fish detection method that combines a triple attention mechanism with a You Only Look Once (TAM-YOLO)model. In order to enhance the speed of model training, the process of data encapsulation incorporates positive sample matching. An exponential moving average (EMA) is incorporated into the training process to make the model more robust, and coordinate attention (CA) and a convolutional block attention module are integrated into the YOLOv5s backbone to enhance the feature extraction of channels and spatial locations. The extracted feature maps are input to the PANet path aggregation network, and the underlying information is stacked with the feature maps. The method improves the detection accuracy of underwater blurred and distorted fish images. Experimental results show that the proposed TAM-YOLO model outperforms YOLOv3, YOLOv4, YOLOv5s, YOLOv5m, and SSD, with a mAP value of 95.88%, thus providing a new strategy for fish detection.
Dynamic In Vitro Gastric Digestion Behaviour of Commercial Infant Formulae Made with Cow, Goat and Sheep Milk
Authors: Song Xuan , Wang Xin , Yang Mengxiao , Acevedo-Fani Alejandra , Singh Harjinder , Ye Aiqian
Published: April 2024

There are a wide range of commercial infant formulae available on the market. These are made using milk from different species, such as goat, sheep, and cow. The different protein compositions of these milks and the process used during infant-formulae manufacture, such as heat treatment, may impact the digestion of nutrients. This study compared the effect of protein composition and heat treatment on the in vitro gastric digestion behaviour of commercial infant formulae made with cow, goat, and sheep milk using a dynamic infant human gastric simulator (IHGS). During the simulated dynamic gastric digestion, the goat milk infant formula (GIF) showed earlier signs of aggregate formation compared to cow milk infant formula (CIF) and sheep milk infant formula (SIF). In addition, the microstructures of GIF chyme showed fragmented and porous structures. On the contrary, CIF formed dense protein networks that trapped oil droplets, whereas SIF exhibited a microstructure of smooth oil droplets surrounded by fewer protein networks. The different aggregation behaviours and aggregate structures of the three infant-formulae chyme were related to their different protein compositions, especially the different casein compositions. Furthermore, the open fragile structure of GIF aggregates provided easier access to pepsin, allowing it to hydrolyse protein. The results from the present study provided some information to assist in understanding the coagulation and digestion behaviours of commercial infant formulae made from different species of milk.
Curcumin Inhibits α-Synuclein Aggregation by Acting on Liquid–Liquid Phase Transition
Authors: Li Jian-Feng , Jiang Zi-Qun , Cao Sen , Zhang Meng-Xin , Wang Li-Hui , Liu Jun , Lu Yan-Hua , Wang Hong-Yan , Hong Xiao-Jing , Wang Zhi-Guo , Liu Jun-Ping
Published: April 2024

Parkinson’s disease (PD), the second most common neurodegenerative disorder, is linked to α-synuclein (α-Syn) aggregation. Despite no specific drug being available for its treatment, curcumin, from the spice turmeric, shows promise. However, its application in PD is limited by a lack of understanding of its anti-amyloidogenic mechanisms. In this study, we first reconstructed the liquid–liquid phase separation (LLPS) of α-Syn in vitro under different conditions, which may be an initial step in entraining the pathogenic aggregation. Subsequently, we evaluated the effects of curcumin on the formation of droplets, oligomers, and aggregated fibers during the LLPS of α-synuclein, as well as its impact on the toxicity of aggregated α-synuclein to cultured cells. Importantly, we found that curcumin can inhibit amyloid formation by inhibiting the occurrence of LLPS and the subsequent formation of oligomers of α-Syn in the early stages of aggregation. Finally, the molecular dynamic simulations of interactions between α-Syn decamer fibrils and curcumin showed that van der Waal’s interactions make the largest contribution to the anti-aggregation effect of curcumin. These results may help to clarify the mechanism by which curcumin inhibits the formation of α-Syn aggregates during the development of PD.
Impact of Oil Bodies on Structure, Rheology and Function of Acid-Mediated Soy Protein Isolate Gels
Authors: Liu Songbin , Zhao Zhihao , Zhou Pengfei , Deng Yuanyuan , Liu Guang , Li Ping , Zeng Jiarui , Zhang Yi , Zhang Mingwei
Published: April 2024

Oil bodies (OBs) are naturally occurring pre-emulsified oil droplets that have broad application prospects in emulsions and gels. The main purpose of this research was to examine the impact of the OB content on the structure and functional aspects of acid-mediated soy protein isolate (SPI) gel filled with OBs. The results indicated that the peanut oil body (POBs) content significantly affected the water holding capacity of the gel. The rheological and textural analyses showed that POBs reduced the gel strength and hardness. The scanning electron and confocal laser scanning microscopy analyses revealed that POBs aggregated during gel formation and reduced the gel network density. The Fourier transform infrared spectrum (FTIR) analysis demonstrated that POBs participated in protein gels through hydrogen bonds, steric hindrance and hydrophobic interactions. Therefore, OBs served as inactive filler in the acid-mediated protein gel, replaced traditional oils and provided alternative ingredients for the development of new emulsion-filled gels.