bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioactive Properties of Campomanesia lineatifolia: Correlation Between Anti-Helicobacter pylori Activity, Antioxidant Potential and Chemical Composition
Authors: Neves Nívea Cristina Vieira , de Mello Morgana Pinheiro , Smith Sinéad Marian , Boylan Fabio , Caliari Marcelo Vidigal , Castilho Rachel Oliveira
Published: November 2024

Helicobacter pylori is found in the stomach of patients with chronic gastritis and peptic ulcers, infecting approximately half of the world’s population. Current treatment for H. pylori infection involves a multi-drug therapeutic regime with various adverse effects, which leads to treatment abandonment and contributes to the emergence of resistant strains of H. pylori. Previously, we demonstrated that the essential oil of Campomanesia lineatifolia leaves exhibited an anti-H. pylori activity. In this study, we aimed to evaluate the phenolic content of the phenolic-rich ethanol extract (PEE) from C. lineatifolia and its anti-H. pylori and antioxidant properties. Additionally, the anti-H. pylori activity was assessed in polar and non-polar fractions from PEE, isolated myricitrin (MYR) and a mixture of myricitrin and quercitrin (MYR/QUER) from polar fractions, and aqueous extract (tea) to correlate the responsible fractions or compounds with the observed activity. Broth microdilution assays were performed to assess the anti-H. pylori activity using type cultures (ATCC 49503, NCTC 11638, both clarithromycin-sensitive) and clinical isolate strains (SSR359, clarithromycin-sensitive, and SSR366, clarithromycin-resistant). The antioxidant activity was evaluated using the DPPH assay. The total tannin and flavonoid contents were determined using the hide-powder method, the Folin-Ciocalteu reagent, and the aluminium chloride colourimetric assay, respectively. The tea (MIC 1:100), PEE, polar and non-polar fractions, MYR, and MYR/QUER inhibited the growth of H. pylori strains tested (MIC values ranging from 0.49 to 250 μg/mL). The antioxidant assays revealed that PEE exhibited a higher antioxidant activity (EC50 = 18.47 μg/mL), which correlated to the high phenolic content (tannin and flavonoid, 22.31 and 0.15% w/w, respectively). These findings support the traditional use of C. lineatifolia as a multitarget medicinal plant for treating gastric ulcers and reinforce the potential use of the species as a coadjuvant in therapeutic regimes involving patients with resistant H. pylori infection.
The Influence of the Ionic Core on Structural and Thermodynamic Properties of Dense Plasmas
Authors: Ismagambetova Tomiris , Muratov Mukhit , Gabdullin Maratbek
Published: November 2024

In this paper, a new ion–ion screened potential was numerically calculated, which takes into account the ion core effect, i.e., the influence of strongly bound electrons. The pseudopotential model describing the shielding of ion cores and the screening using the density response function in the long wavelength approximation were used. To study the influence of this ion core effect on dense plasma’s structural and thermodynamic properties, the integral Ornstein–Zernike equation was solved in the hypernetted chain approximation. Our results show that the ion core has a significant impact on ionic radial distribution functions and thermodynamic properties when compared to the results obtained for the Yukawa potential, which does not take the ion core into account. Increasing the steepness of the core edge or decreasing the depth of the minimum leads to more pronounced screening due to bound electrons.
New Materials from the Integral Milk Kefir Grain Biomass and the Purified Kefiran: The Role of Glycerol Content on the Film’s Properties
Authors: Ramírez Tapias Yuly A. , Rezzani Guillermo D. , Delgado Juan F. , Peltzer Mercedes A. , Salvay Andrés G.
Published: November 2024

Microbial exopolymers are gaining attention as sources for the development of biodegradable materials. Milk kefir, a fermented dairy product produced by a symbiotic community of microorganisms, generates milk kefir grains as a by-product, consisting of the polysaccharide kefiran and proteins. This study develops two materials, one from whole milk kefir grains and another from purified kefiran. Film-forming dispersions were subjected to ultrasonic homogenisation and thermal treatment, yielding homogeneous dispersions. Kefiran dispersion exhibited lower pseudoplastic behaviour and higher viscous consistency, with minimal effects from glycerol. Both films exhibited continuous and homogeneous microstructures, with kefiran films being transparent and milk kefir films displaying a yellowish tint. Analysis revealed that milk kefir films comprised approximately 30% proteins and 70% kefiran. Kefiran films demonstrated stronger interpolymeric interactions, as evidenced using thermogravimetric and mechanical tests. Glycerol increased hydration while decreasing thermal stability, glass transition temperature, elastic modulus, and tensile strength in both films. However, in kefiran films, elongation at the break and water vapour permeability decreased at low glycerol content, followed by an increase at higher plasticiser contents. This suggests an unusual interaction between glycerol and kefiran in the absence of proteins. These findings underscore differences between materials derived from the whole by-product and purified kefiran, offering insights into their potential applications.
Welcome to Populations: A New Platform for Demographic and Population Science Research
Authors: Lopez-Carr David
Published: November 2024

With great excitement and pride, I introduce the inaugural issue of Populations, a new research journal dedicated to advancing our understanding of population dynamics and its interactions with socio-economic, political, and environmental processes [...]
A Multi-Step Furnace Temperature Prediction Model for Regenerative Aluminum Smelting Based on Reversible Instance Normalization-Convolutional Neural Network-Transformer
Authors: Dai Jiayang , Ling Peirun , Shi Haofan , Liu Hangbin
Published: November 2024

In the regenerative aluminum smelting process, the furnace temperature is critical for the quality and energy consumption of the product. However, the process requires protective sensors, making real-time furnace temperature measurement costly, while the strong nonlinearity and distribution drift of the process data affect furnace temperature prediction. To handle these issues, a multi-step prediction model for furnace temperature that incorporates reversible instance normalization (RevIN), convolutional neural network (CNN), and Transformer is proposed. First, the self-attention mechanism of the Transformer is combined with CNN to extract global and local information in the furnace temperature data, thus addressing the strong nonlinear characteristics of the furnace temperature. Second, RevIN with learnable affine transformation is utilized to address the distribution drift in the furnace temperature data. Third, the temporal correlation of the prediction model is enhanced by a time-coding method. The experimental results show that the proposed model demonstrates higher prediction accuracy for furnace temperature at different prediction steps in the regenerative aluminum smelting process compared to other models.
Intelligent Pressure Monitoring Method of BP Neural Network Optimized by Genetic Algorithm: A Case Study of X Well Area in Yinggehai Basin
Authors: Liu Ting , Ye Xiaobin , Cheng Leli , Hu Yitao , Guo Dongming , Huang Baotong , Li Yongkang , Su Jiarong
Published: November 2024

While drilling formation pressure monitoring is an important basis for ensuring drilling safety and oil and gas discovery, the calculation of existing pressure monitoring methods is complicated and the accuracy is difficult to improve. Taking the actual well data of well area X in Yinggehai Basin as the object, correlation analysis was first carried out to select and standardize the data features, and relevant effective parameters were extracted. Two kinds of neural networks, back-propagation network BP and back-propagation network GA-BP optimized by genetic algorithm, were used to establish artificial intelligence monitoring models of formation pressure based on 10 kinds of measuring and logging data, respectively. The application effect of the model was evaluated based on the results of monitoring the pressure while drilling. The results show that the monitoring accuracy of the BP neural network model is 91.25%, and that of the GA-BP neural network model is 92.89%. The latter has a better monitoring effect on formation pore pressure. In formation pressure monitoring in areas with a high degree of well control, the introduction of artificial intelligence technology has the advantages of simplicity, speed and high precision, and can provide a reference for other areas of pressure monitoring while drilling.
Numerical Study of Hydrogen-Rich Fuel Coherent Jet in Blast Furnace Tuyere
Authors: Shi Jianchun , Xu Peng , Han Peng , He Zhijun , Wang Jiaying
Published: November 2024

Injecting hydrogen-rich fuel into blast furnaces is an effective strategy to reduce carbon dioxide (CO2) emissions. The present study established a three-dimensional (3D) model based on a coherent jet of hydrogen-rich fuel. The combustion characteristics and the flow, heat, and mass transfer behaviors in the reaction region were simulated by the Computational Fluid Dynamics (CFD) method. The effects of fuel jet velocity on the distributions of gas velocity, temperature, and species in the reaction region were systematically analyzed. The results show that hydrogen-rich fuel burned around the main jet, generating a high-temperature, low-density flame. As flame length increased, the main jet experienced less decay. The outward expansion of the jet caused continuous diffusion of gas temperature and its components. As the fuel jet velocity increased, the temperature along the main jet centerline rose sharply, while the length of the high-concentration gas region extended. Doubling the jet velocity increased its centerline velocity by 11% and raised the average reaction region temperature by 4.12%. The obtained highlighted results are of paramount importance for optimizing hydrogen-rich smelting in blast furnaces.
Exploring the Extraction and Application of Anthocyanins in Food Systems
Authors: Nthimole Confidence Tsholofelo , Kaseke Tafadzwa , Fawole Olaniyi Amos
Published: November 2024

The continued use of synthetic additives in food production and preservation has raised concerns among consumers, given their potential negative health effects. Researchers and food industry experts have been exploring plants with potent functional compounds as an alternative source of natural compounds such as anthocyanins, which can be utilized to produce safe food additives. Given their various biological activities, great potential exists for anthocyanins to be used as additives to preserve food or produce functional foods with health benefits. However, to fully realize the economic and health benefits of anthocyanins, a deep understanding of the different plant sources of anthocyanins, as well as their composition, extraction techniques, and function in various products, is warranted. Therefore, this paper critically reviews the different plant sources of anthocyanins and their application in the food and nutraceutical industries, highlighting emerging extraction techniques, health benefits, and challenges in the use of anthocyanins in the food industry. This review also offers insights that could be used in future research and help establish novel and sustainable methods for manufacturing anthocyanin-based value-added products and ingredients.
Experimental and Numerical Study on Nonlinear Shear Behavior and Constitutive Model of Deep Shale Laminae Planes
Authors: Zhuo Renyan , Ma Xinfang , Li Jianmin , Zhang Shicheng , Ma Junxiu
Published: November 2024

The direct shear tests showed that the degradation of unevenness and waviness of the laminae plane is the primary reason for the dynamic decrease in shear strength. A shear constitutive model was proposed which considers the scale effect and the asperity geometry of the unevenness and waviness of the laminar plane. The evolution of the shear strength and stiffness with a normal stress and scale effect during the shearing of shale laminae planes was explored. The results show that high normal stress aggravates the stiffness hardening of laminae planes and forms larger peak shear stress and peak shear displacement. At the lab scale, the increase in the unevenness wavelength has a hardening effect on the shear stiffness and strength. The small-scale unevenness contributes most to the shear strength of shale laminae planes at the lab scale. At the field scale, the increase in the waviness wavelength has a softening effect on the shear stiffness and strength.
Analysis of Influence of Excitation Source Direction on Sound Transmission Loss Simulation Based on Alloy Steel Phononic Crystal
Authors: Guo Zhaofeng , Wang Ziming , Zhang Yanchao , Li Lei , Chen Chuanmin
Published: November 2024

As a type of locally resonant phononic crystal, alloy steel phononic crystals have achieved notable advancements in vibration and noise reduction, particularly in the realm of low-frequency noise. Their exceptional band gap characteristics enable the efficient reduction of vibration and noise at low frequencies. However, the conventional transmission loss (TL) simulation of finite structures remains the benchmark for plate structure TL experiments. In this context, the TL in the XY-direction of phononic crystal plate structures has been thoroughly investigated and analyzed. Given the complexity of sound wave incident directions in practical applications, the conventional TL simulation of finite structures often diverges from reality. Taking tungsten steel phononic crystals as an example, this paper introduces a novel finite element method (FEM) simulation approach for analyzing the TL of alloy steel phononic crystal plates. By setting the Z-direction as the excitation source, the tungsten steel phononic crystal plate exhibits distinct responses compared to excitation in the XY-direction. By combining energy band diagrams and modes, the impact of various excitation source directions on the TL simulations is analyzed. It is observed that the tungsten steel phononic crystal plate exhibits a more pronounced energy response under longitudinal excitation. The TL map excited in the Z-direction lacks the flat region present in the XY-direction TL map. Notably, the maximum TL in the Z-direction is 131.5 dB, which is significantly lower than the maximum TL of 298 dB in the XY-direction, with a more regular peak distribution. This indicates that the TL of alloy steel phononic crystals in the XY-direction is closely related to the acoustic wave propagation characteristics within the plate, whereas the TL in the Z-direction aligns more closely with practical sound insulation and noise reduction engineering applications. Therefore, future research on alloy steel phononic crystal plates should not be confined to the TL in the XY-direction. Further investigation and analysis of the TL in the Z-direction are necessary. This will provide a novel theoretical foundation and methodological guidance for future research on alloy steel phononic crystals, enhancing the completeness and systematicness of studies on alloy steel phononic crystal plates. Simultaneously, it will advance the engineering application of alloy steel phononic crystal plates.
Prosthetically Driven Approach to Post-Ablative Maxilla Rehabilitation with an Implant-Supported Overdenture: A Case Report
Authors: Malgaj Tine , Kansky Andrej , Ludvig Ribič Alenka , Kobe Tom , Berce Blaž , Jevnikar Peter
Published: November 2024

This clinical report details the prosthetic rehabilitation of a patient following maxillary ablation to remove a peripheral giant cell granuloma. After a hemimaxillectomy, the defect was reconstructed with a fasciocutaneous radial free flap. Implant placement was digitally planned using the dual scanning technique, and implants were inserted with the aid of an acrylic surgical guide. After implant osseointegration, a removable implant-supported overdenture with an electroplated secondary structure retained on a titanium bar was fabricated. At the 3-year follow-up, peri-implant tissues remained healthy, showing only mild gingival hyperplasia around the bar, while no prosthesis retention loss or significant technical complications were observed. In conclusion, the reconstruction of the moderate maxillary defect using a soft-tissue flap provided satisfactory functional and esthetic outcomes, significantly enhancing patient satisfaction. However, the limited bone availability necessitated precise implant planning to ensure adequate biomechanical support for the overdenture.
A Customized Distribution of the Coefficient of Friction of the Porous Coating in the Short Femoral Stem Reduces Stress Shielding
Authors: Solou Konstantina , Solou Anna Vasiliki , Tatani Irini , Lakoumentas John , Tserpes Konstantinos , Megas Panagiotis
Published: November 2024

Stress shielding and aseptic loosening have been identified as adverse effects of short-stem total hip arthroplasty resulting in hardware failure. However, there is a gap in research regarding the impact of stress shielding in customized porous coatings. The purpose of this study was to optimize the distribution of the coefficients of friction in the porous coating of a metaphyseal femoral stem to minimize stress shielding. Static structural analysis of an implanted short, tapered-wedge stem with a titanium porous coating was performed with the use of Analysis System Mechanical Software under axial loading. To limit computational time, we randomly sampled only 500 of the possible combinations of coefficients of friction. Results indicate that the coefficient of friction in the distal lateral porous coating significantly affected the mid-distal medial femoral surface and lateral femoral surface. The resultant increased proximal strains resulted from an increased coefficient of friction in lateral porous coating and a reduction in the coefficient of friction in medial mid-distal coating. These findings suggest that a customized porous coating distribution may produce strain patterns that are biomechanically closer to intact bone, thereby reducing stress shielding in short femoral stems.
Digital Technologies, Materials and Telemedicine in Dentistry
Authors: Minervini Giuseppe
Published: November 2024

As we delve into this Special Issue on prosthesis, it is evident that digital dentistry continues to revolutionize the field, offering improved precision, efficiency, and patient satisfaction [...]
Transcriptomics Revealed Differentially Expressed Transcription Factors and MicroRNAs in Human Diabetic Foot Ulcers
Authors: Rai Vikrant
Published: November 2024

Non-healing diabetic foot ulcers (DFUs) not only significantly increase morbidity and mortality but also cost a lot and drain healthcare resources. Persistent inflammation, decreased angiogenesis, and altered extracellular matrix remodeling contribute to delayed healing or non-healing. Recent studies suggest an increasing trend of DFUs in diabetes patients, and non-healing DFYs increase the incidence of amputation. Despite the current treatment with offloading, dressing, antibiotics use, and oxygen therapy, the risk of amputation persists. Thus, there is a need to understand the molecular and cellular factors regulating healing in DFUs. The ongoing research based on proteomics and transcriptomics has predicted multiple potential targets, but there is no definitive therapy to enhance healing in chronic DFUs. Increased or decreased expression of various proteins encoded by genes, whose expression transcriptionally and post-transcriptionally is regulated by transcription factors (TFs) and microRNAs (miRs), regulates DFU healing. For this study, RNA sequencing was conducted on 20 DFU samples of ulcer tissue and non-ulcerated nearby healthy tissues. The IPA analysis revealed various activated and inhibited transcription factors and microRNAs. Further network analysis revealed interactions between the TFs and miRs and the molecular targets of these TFs and miRs. The analysis revealed 30 differentially expressed transcription factors (21 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and seven miRs, including mir-486, mir-324, mir-23, mir-186, mir-210, mir-199, and mir-338 in upstream regulators (p < 0.05), while causal network analysis (p < 0.05) revealed 28 differentially expressed TFs (19 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and five miRs including mir-155, mir-486, mir-324, mir-210, and mir-1225. The protein–protein interaction analysis revealed the interaction of various novel proteins with the proteins involved in regulating DFU pathogenesis and healing. The results of this study highlight many activated and inhibited novel TFs and miRs not reported in the literature so far, as well as the targeted molecules. Since proteins are the functional units during biological processes, alteration of gene expression may result in different proteoforms and protein species, making the wound microenvironment a complex protein interaction (proteome complexity). Thus, investigating the effects of these TFs and miRs on protein expression using proteomics and combining these results with transcriptomics will help advance research on DFU healing and delineate potential therapeutic strategies.
Optimization of Hydrocarbon Production in Catalytic Pyrolysis of Macaúba Epicarp and Macaúba and Baru Endocarps
Authors: Cavallaro Reginaldo José , Duarte Claudio Roberto , Hori Carla Eponina , Barrozo Marcos Antonio de Souza
Published: November 2024

The objective of this study was to examine the catalytic pyrolysis process of three distinct types of biomasses: baru endocarp (ENB), macaúba endocarp (ENM), and macaúba epicarp (EPM). This was performed with the aim of optimizing the production of hydrocarbons and other volatile compounds of interest through the use of different catalysts. The catalysts utilized in this study were calcium oxide (CaO), phosphate mining waste (PO), niobium pentoxide (Nb2O5), and Ni/Nb2O5. The methodology entailed pyrolyzing the biomass at temperatures spanning from 508 °C to 791 °C, utilizing a micropyrolyzer in conjunction with a gas chromatograph with mass spectrometry (GC/MS) for product analysis. An experimental design was implemented to assess the impact of catalyst concentration and temperature on the yield and composition of the volatile products. The findings demonstrated that CaO was efficacious in deoxygenating the compounds, particularly at elevated temperatures, thereby promoting the generation of saturated and unsaturated hydrocarbons. In contrast, Nb2O5 was effective in the formation of oxygenated compounds, particularly carboxylic acids and phenols. Ni/Nb2O5 has been shown to be effective in the production of cyclic, aromatic, alkadienes, and alkenes hydrocarbons. Phosphate mining waste exhibited moderate performance, with potential for specific applications at high temperatures, with important production of cyclic, aromatic, and alkane hydrocarbons. Among the biomasses, EPM demonstrated the greatest potential for hydrocarbon production, indicating its suitability for the development of advanced biofuels. This study advances our understanding of the catalytic pyrolysis of alternative biomasses and underscores the pivotal role of catalysts in optimizing the process, offering invaluable insights for the sustainable production of biofuels and interest in renewable chemicals.
The Ten Commandments in Reformed Worship Traditions
Authors: Moon Hwarang
Published: November 2024

This paper examines the role of the Ten Commandments in Christian worship and its influence on believers’ spiritual and ethical formation. Although historically the use of the Commandments in public worship was limited, particularly outside Reformed traditions, they remain a powerful tool for moral reflection and spiritual discipline. By reciting, singing, or creatively incorporating the Commandments into worship, believers are invited to engage in continuous self-reflection and reaffirm their commitment to living according to God’s will. This paper argues that, while not mandatory for every service, the regular use of the Ten Commandments provides essential moral guidance and helps shape the ethical identity of Christians, offering a framework for navigating relationships with God and others in a faithful, disciplined way.
Patterns of Infertility and Sociodemographic Characteristics Among Patients with Infertility Attending Benjamin Mkapa Hospital in Tanzania: Analytical Cross-Sectional Study
Authors: Kasililika Anna Gideon , Hussein Hindu Ibrahim , Joseph Henry Stephen , Ng’weshemi Secilia Kapalata , Chandika Alphonce Bilola
Published: November 2024

(1) Background: Infertility is a global health problem that affects one of six couples worldwide, leading to significant negative impacts on their quality of life. Despite numerous studies on infertility patterns and sociodemographic characteristics, there remains a lack of clarity on these aspects among patients seeking care in Tanzania. (2) Methods: This hospital-based analytical cross-sectional study aimed to determine infertility patterns and sociodemographic characteristics among 385 randomly selected male and female patients attending the Benjamin Mkapa Hospital. Structured interviews using a clinical proforma collected data on the patterns of infertility and sociodemographic characteristics of the participants. The analysis included descriptive statistics and logistic regression. (3) Results: The findings indicated that the dominant pattern of infertility for both male and female participants was secondary infertility, accounting for 59.00% (228). Multivariate logistic regression analysis for both male and female patients revealed sociodemographic characteristics of infertility: age (38–43) years, AOR 5.068, 95% CI 1.573–16.33, p = 0.007), and duration of cohabiting or marriage of more than 10 years (AOR 0.406,95% CI 0.189–0.873, p = 0.021). (4) Conclusion: Integrating reproductive health education on appropriate fertility age into the reproductive health package and enhancing fertility care in public hospitals in Tanzania is recommended.
Use of Laughter Therapy for In Vitro Fertilization: A Systematic Review
Authors: Rodríguez-García Daniela , Rodríguez-Suárez Claudio-Alberto , González-de la Torre Héctor
Published: November 2024

Background/Objectives: In vitro fertilization (IVF) is an assisted reproductive technique for women and couples experiencing difficulties in achieving a spontaneous pregnancy, often due to stressors that negatively affect fertility. Humor can be beneficial in these stressful situations, helping to reduce symptoms of anxiety and depression. The primary aim was to analyze the effectiveness of laughter therapy in increasing pregnancy rates in women undergoing IVF. The secondary aims were to identify different types of laughter therapy interventions and evaluate their benefits. Methods: A systematic review was conducted using Medline, Web of Science, Scopus, Cinahl, ProQuest and Lilacs, with the search terms “laughter”, “laughter therapy”, “fertilization in vitro” and “fertilization”. Intervention studies published in English, Spanish, or Portuguese were included, with no limits on the date of publication. Studies with other designs, those conducted with animals and grey literature were excluded. The quality of the included studies was assessed using the Joanna Briggs Institute critical appraisal tools. Results: In total, n = 3 studies (1 randomized clinical trial and 2 quasi-experimental) were included, evaluating pregnancy rates and symptoms of depression and anxiety. The interventions included clowns performing magic tricks and interpreting comic situations. Additionally, they incorporated hand clapping, breathing exercises, childlike playfulness, drinking milk, muscle relaxation exercises, candles, and music. Conclusions: This review does not provide clear evidence on the effectiveness of laughter therapy in increasing pregnancy success in IVF. Although it may have some positive effects in reducing symptoms of depression and anxiety, it is important to note that while the reduction of these symptoms may enhance the emotional well-being of patients, it has not been demonstrated to directly lead to an increase in pregnancy rates. Laughter therapy is an innovative, non-pharmacological intervention that is simple, non-invasive, easy to implement and cost-effective; however, the number of available studies is insufficient. More research is needed to provide better and higher-quality evidence using rigorous designs to evaluate this intervention in IVF clinical practice.
Physiopathological Aspects of Synovial Fluid and Membrane in Psoriatic Arthritis
Authors: Damasco Amelia Carmela , Ramonda Roberta , Cozzi Giacomo , Lorenzin Mariagrazia , Sfriso Paolo , Oliviero Francesca , Baggio Chiara
Published: November 2024

Background: Psoriatic arthritis (PsA) is a chronic inflammatory arthropathy characterized by a variety of clinical manifestations, mainly affecting joints and entheses, but also skin, nails, the eye, and the intestine. Objectives: In this review, we describe the essential characteristics of both synovial membranes and synovial fluid (SF) in PsA. Similarly to other inflammatory arthritis, the histological peculiarities in PsA synovitis are lining hyperplasia, neoangiogenesis, and sublining infiltration by immune cells and inflammatory mediators. Synovial effusions are frequent in PsA patients and SF analysis allows us to determine the pathological process occurring in the joint. Routine examinations help clinicians in defining the inflammatory status and possibly the detection of specific cell subsets. In addition, pathogenic crystals including monosodium urate and calcium pyrophosphate may be found in PsA SF. Conclusions: SF represents a potential substrate to identify the biomarkers that are useful to predict disease progression and response to medications in PsA patients, thus guiding the choice of appropriate and tailored pharmacological treatment.
Large-Kernel Central Block Masked Convolution and Channel Attention-Based Reconstruction Network for Anomaly Detection of High-Resolution Hyperspectral Imagery
Authors: Ran Qiong , Zhong Hong , Sun Xu , Wang Degang , Sun He
Published: November 2024

In recent years, the rapid advancement of drone technology has led to an increasing use of drones equipped with hyperspectral sensors for ground imaging. Hyperspectral data captured via drones offer significantly higher spatial resolution, but this also introduces more complex background details and larger target scales in high-resolution hyperspectral imagery (HRHSI), posing substantial challenges for hyperspectral anomaly detection (HAD). Mainstream reconstruction-based deep learning methods predominantly emphasize spatial local information in hyperspectral images (HSIs), relying on small spatial neighborhoods for reconstruction. As a result, large anomalous targets and background details are often well reconstructed, leading to poor anomaly detection performance, as these targets are not sufficiently distinguished from the background. To address these limitations, we propose a novel HAD network for HRHSI based on large-kernel central block masked convolution and channel attention, termed LKCMCA. Specifically, we first employ the pixel-shuffle technique to reduce the size of anomalous targets without losing image information. Next, we design a large-kernel central block masked convolution to make the network pay more attention to the surrounding background information, enabling better fusion of the information between adjacent bands. This, coupled with an efficient channel attention mechanism, allows the network to capture deeper spectral features, enhancing the reconstruction of the background while suppressing anomalous targets. Furthermore, we introduce an adaptive loss function by down-weighting anomalous pixels based on the mean absolute error. This loss function is specifically designed to suppress the reconstruction of potentially anomalous pixels during network training, allowing our model to be considered an excellent background reconstruction network. By leveraging reconstruction error, the model effectively highlights anomalous targets. Meanwhile, we produced four benchmark datasets specifically for HAD tasks using existing HRHSI data, addressing the current shortage of HRHSI datasets in the HAD field. Extensive experiments demonstrate that our LKCMCA method achieves superior detection performance, outperforming ten state-of-the-art HAD methods on all datasets.
Behavioral, Physiological and Hormonal Changes in Primiparous and Multiparous Goats and Their Kids During Peripartum
Authors: Cano-Suarez Paolo , Damian Juan Pablo , Soto Rosalba , Ayala Karen , Zaragoza Joob , Ibarra Rocio , Ramírez-Espinosa Jesús Jonathan , Castillo Laura , Candanosa Aranda Irma Eugenia , Terrazas Angélica
Published: November 2024

The objective of this study was to evaluate the effect of maternal experience on behavior, progesterone and estradiol concentrations, weight and body condition in goats in the peripartum period, as well as the behavior and weight of the kids in the first hours after birth. Twenty multiparous and 10 primiparous dairy goats were enrolled. Behaviors such as walking, isolation, aggression, eating, inactivity and rumination were recorded in females during the last three days prior to the day of delivery, as well as the behaviors of the dam and her progeny in the first 2 h postpartum and the ability of the mother to discriminate between own kid and the alien one (selectivity test) at 2 h postpartum. Gestational and postpartum plasma progesterone and estradiol concentrations were determined. In the prepartum period there was a higher percentage of primiparous goats that were eating and remained less inactive compared to multiparous goats (p < 0.05). During the postpartum period, the lick latency to the kid was shorter in multiparous than in primiparous goats (p = 0.015). There was a greater proportion of kids born from multiparous (67%) than from primiparous (27%) that stood up in the first 30 min postpartum (p < 0.0001). Therefore, the proportion of multiparous kids (33%) than primiparous kids (9%) that were nursed within the first hour after birth was also higher (p < 0.0001). Progesterone and estradiol concentrations were not affected by maternal experience, neither in the prepartum nor the postpartum. In conclusion, maternal experience affected some behaviors at peripartum of the dam and vitality in the kid; however, the differences in behavior were not accompanied by differences in the variations in circulating estradiol and progesterone levels in the dam.
ARMNet: A Network for Image Dimensional Emotion Prediction Based on Affective Region Extraction and Multi-Channel Fusion
Authors: Zhang Jingjing , Sun Jiaying , Wang Chunxiao , Tao Zui , Zhang Fuxiao
Published: November 2024

Compared with discrete emotion space, image emotion analysis based on dimensional emotion space can more accurately represent fine-grained emotion. Meanwhile, this high-precision representation of emotion requires dimensional emotion prediction methods to sense and capture emotional information in images as accurately and richly as possible. However, the existing methods mainly focus on emotion recognition by extracting the emotional regions where salient objects are located while ignoring the joint influence of objects and background on emotion. Furthermore, in the existing literature, when fusing multi-level features, no consideration has been given to the varying contributions of features from different levels to emotional analysis, which makes it difficult to distinguish valuable and useless features and cannot improve the utilization of effective features. This paper proposes an image emotion prediction network named ARMNet. In ARMNet, a unified affective region extraction method that integrates eye fixation detection and attention detection is proposed to enhance the combined influence of objects and backgrounds. Additionally, the multi-level features are fused with the consideration of their different contributions through an improved channel attention mechanism. In comparison to the existing methods, experiments conducted on the CGnA10766 dataset demonstrate that the performance of valence and arousal, as measured by Mean Squared Error (MSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²), has improved by 4.74%, 3.53%, 3.62%, 1.93%, 6.29%, and 7.23%, respectively. Furthermore, the interpretability of the network is enhanced through the visualization of attention weights corresponding to emotional regions within the images.
Optimization of Communication Signal Adversarial Examples by Selectively Preserving Low-Frequency Components of Perturbations
Authors: Zhang Yi , Wang Lulu , Wang Xiaolei , Shi Dianxi , Bai Jiajun
Published: November 2024

Achieving high attack success rate (ASR) with minimal perturbed distortion has consistently been a prominent and challenging research topic in the field of adversarial examples. In this paper, a novel method to optimize communication signal adversarial examples is proposed by focusing on low-frequency components of perturbations (LFCP). Observations on model attention towards DCT coefficients reveal the crucial role of LFCP within adversarial examples in altering the model’s predictions. As a result, selectively preserving LFCP is established as the fundamental concept of the optimization strategy. By utilizing the binary search algorithm, which considers the inconsistency in the model’s predictions as a constraint, LFCP can be effectively identified, and the aim of minimizing perturbed distortion while maintaining ASR can be achieved. Experimental results conducted on a publicly available dataset, six adversarial attacks and two DNN models, indicate that the proposed method not only significantly minimizes perturbed distortion for FGSM, BIM, PGD, and MI-FGSM but also achieves a modest improvement in ASR. Notably, even for DeepFool and BS-FGM, which introduce small perturbations and exhibit high ASRs, the proposed method can still deliver feasible performance.
Enhanced RF Energy Harvesting System Utilizing Piezoelectric Transformer
Authors: Al Ahmad Mahmoud , Kiranmai K. S. Phani , Alnuaimi Abdulla , Alyammahi Obaid , Alkaabi Hamad , Alnasri Saeed , Dahir Abdulrahman
Published: November 2024

RF energy harvesting converts ambient signals into electrical power, providing a sustainable energy source. This study demonstrates the use of a piezoelectric transformer for efficient RF energy harvesting. In this work, a piezoelectric transformer (PT) is employed as a high-gain, efficient inverting amplifier to enhance RF wireless energy harvesting. The PT, composed of lead zirconate titanate (PZT), is placed after the receiving loop antenna, with its output connected to an AC-to-DC converter circuit. Maximum harvested power was observed at the PT’s resonance frequency of 50 kHz, with an optimal load of 40 kΩ. The system, comprising the antenna, transformer, and rectifier circuit, continues to resonate at 50 kHz, as confirmed by input impedance measurements, demonstrating stable and effective performance. The overall system efficiency was characterized to be 88%.
Improved EMAT Sensor Design for Enhanced Ultrasonic Signal Detection in Steel Wire Ropes
Authors: Rossteutscher Immanuel , Blaschke Oliver , Dötzer Florian , Uphues Thorsten , Drese Klaus Stefan
Published: November 2024

This study is focused on optimizing electromagnetic acoustic transducer (EMAT) sensors for enhanced ultrasonic guided wave signal generation in steel cables using CAD and modern manufacturing to enable contactless ultrasonic signal transmission and reception. A lab test rig with advanced measurement and data processing was set up to test the sensors’ ability to detect cable damage, like wire breaks and abrasion, while also examining the effect of potential disruptors such as rope soiling. Machine learning algorithms were applied to improve the damage detection accuracy, leading to significant advancements in magnetostrictive measurement methods and providing a new standard for future development in this area. The use of the Vision Transformer Masked Autoencoder Architecture (ViTMAE) and generative pre-training has shown that reliable damage detection is possible despite the considerable signal fluctuations caused by rope movement.
Maintaining Cyber Resilience in the Reconfigurable Networks with Immunization and Improved Network Game Methods
Authors: Kalinin Maxim , Pavlenko Evgeny , Gavva Georgij , Pakhomov Maxim
Published: November 2024

The paper proposes a technique for protecting reconfigurable networks that implements topology rebuilding, which combines immunization and network gaming methods, as a solution for maintaining cyber resilience. Immunization presumes an adaptive set of protective reconfigurations destined to ensure the functioning of a network. It is a protective reconfiguration aimed to preserve/increase the functional quality of the system. Network nodes and edges are adaptively reorganized to counteract an invasion. This is a functional component of cyber resilience. It can be implemented as a global strategy, using knowledge of the whole network structure, or a local strategy that only works with a certain part of a network. A formal description of global and local immune strategies based on hierarchical and peer-to-peer network topologies is presented. A network game is a kind of the well-defined game model in which each situation generates a specific network, and the payoff function is calculated based on the constructed networks. A network game is proposed for analyzing a network topology. This model allows quickly identifying nodes that require disconnection or replacement when a cyber attack occurs, and understanding which network sectors might be affected by an attack. The gaming method keeps the network topology resistant to unnecessary connections. This is a structural component of cyber resilience. The basic network game method has been improved by using the criterion of maximum possible path length to reduce the number of reconfigurations. Network optimization works together with immunization to preserve the structural integrity of the network. In an experimental study, the proposed method demonstrated its effectiveness in maintaining system quality within given functional limits and reducing the cost of system protective restructuring.
Implementation of an Image Tampering Detection System with a CMOS Image Sensor PUF and OP-TEE
Authors: Oyama Tatsuya , Hagizaki Manami , Okura Shunsuke , Fujino Takeshi
Published: November 2024

Since image recognition systems use image data acquired by image sensors for analysis by AI technology, an important security issue is guaranteeing the authenticity of data transmitted from image sensors to successfully perform inference using AI. There have been reports of physical attacks on image sensor interfaces by tampering with images to cause misclassifications in AI classification results. As a countermeasure against these attacks, it is effective to add authenticity to image data with a message authentication code (MAC). For the implementation of this, it is important to have technologies for generating MAC keys on image sensors and to create an environment for secure MAC verification on the host device. For MAC key generation, we used the CIS-PUF technology, which generates MAC keys from PUF responses and random numbers from CMOS image sensor variations. For the secure MAC verification, we used TEE technology, which executes security-critical processes in an environment isolated from the normal operating system. In this study, we propose and demonstrate an image tampering detection system based on MAC verification with CIS-PUF and OP-TEE in an open portable TEE on an ARM processor. In the experiments, we demonstrated a system that computed and transmitted MAC for captured images using the CIS-PUF key and then performed MAC verification in the secure world of the OP-TEE.
Energy Management System for Polygeneration Microgrids, Including Battery Degradation and Curtailment Costs
Authors: Ennassiri Yassine , de-Simón-Martín Miguel , Bracco Stefano , Robba Michela
Published: November 2024

Recent advancements in sensor technologies have significantly improved the monitoring and control of various energy parameters, enabling more precise and adaptive management strategies for smart microgrids. This work presents a novel model of an energy management system (EMS) for grid-connected polygeneration microgrids that allows optimizing the management of electrical storage systems, electric vehicles, and other deferrable loads such as heat pumps. The main novelty of this model is that it incorporates both climate comfort variables and the consideration of the degradation of the energy storage capacity in the control strategy, as well as a penalty for the dumping of surpluses. The model has been applied to a smart, sustainable building as a case study. The results show that the proposed model is highly adaptable to diverse weather conditions, minimizing renewable energy losses while satisfying the energy demand and providing comfort to the building’s users. The study shows (i) that EVs’ dynamic charging schedules play a crucial role, (ii) that it is possible to minimize a battery’s degradation by optimizing its cycling, averaging one cycle per day, and (iii) the critical impact of seasonal weather patterns on microgrid energy management and the strategic role of EVs and storage systems in maintaining energy balance and efficiency.
Deep Fuzzy Credibility Surfaces for Integrating External Databases in the Estimation of Operational Value at Risk
Authors: Peña Alejandro , Sepúlveda-Cano Lina M. , Gonzalez-Ruiz Juan David , Marín-Rodríguez Nini Johana , Botero-Botero Sergio
Published: November 2024

Operational risk (OR) is usually caused by losses due to human errors, inadequate or defective internal processes, system failures, or external events that affect an organization. According to the Basel II agreement, OR is defined by seven risk events: internal fraud, external fraud, labor relations, clients, damage to fixed assets, technical failures and failures in the execution and administration of processes. However, the low frequency with which a loss event occurs creates a technological challenge for insurers in estimating the operational value at risk (OpVar) for the protection derived from an organization’s business activities. Following the above, this paper develops and analyzes a Deep Fuzzy Credibility Surface model (DFCS), which allows the integration in a single structure of different loss event databases for the estimation of an operational value at risk (OpVar), overcoming the limitations imposed by the low frequency with which a risk event occurs within an organization (sparse data). For the estimation of OpVar, the DFCS model incorporates a novel activation function based on the generalized log-logistic function to model random variables of frequency and severity that define a loss event (linguistic random variables), as well as a credibility surface to integrate the magnitude and heterogeneity of losses in a single structure as a result of the integration of databases. The stability provided by the DFCS model could be evidenced through the structure exhibited by the aggregate loss distributions (ALDs), which are obtained as a result of the convolution process between frequency and severity random variables for each database and which are expected to achieve similar structures to the probability distributions suggested by Basel II agreements (lean, long tail, positive skewness) against the OR modeling. These features make the DFCS model a reference for estimating the OpVar to protect the risk arising from an organization’s business operations by integrating internal and external loss event databases.