bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved Nonlinear Health Index CRRMS for the Remaining Useful Life Prediction of Rolling Bearings
Authors: Jin Yongze , Yang Xubo , Liu Junqi , Yang Yanxi , Hei Xinhong , Shangguan Anqi
Published: February 2025

In this article, a novel prediction index is constructed, a hybrid filtering is proposed, and a remaining useful life (RUL) prediction framework is developed. In the proposed framework, different models are built for different operation states of rolling bearings. In the normal state, a linear model is built, and a Kalman filter (KF) is implemented to determine the failure start time (FST). In the degradation state, a dimensionless prediction index CRRMS is constructed, based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold. Then, a double exponential model is established, and the hybrid filtering is proposed to estimate the future trend of CRRMS, which is combined by a particle filter (PF) and an unscented Kalman filter (UKF). At the same time, dynamic failure threshold technology is adaptively used to determine the failure thresholds of different bearings. Furthermore, the RUL is extrapolated at the moment the prediction index exceeds the failure threshold. Finally, the effectiveness and practicability of the proposed method is verified on the bearing dataset given by the PRONOSTIA platform.
Effects of Fish Palm Rice and Coconut Palm Rice Oil Mixture on Intestinal Health of Weaned Piglets
Authors: Yang Kaiyun , Yang Wenjuan , Jiang Fei , Yu Bing , Huang Zhiqing , Luo Yuheng , Wu Aimin , Zheng Ping , Mao Xiangbing , Yu Jie , Luo Junqiu , Yan Hui , He Jun
Published: February 2025

Fat not only has a high effective energy value and extra energy effects but is also an ideal energy source. As one of the most commonly used feed oils at present, soybean oil has a high cost despite its good application effect on weaned piglets. In contrast, the cost of palm oil is lower. In order to explore the effect of palm oil-dominated fat combination on intestinal health of weaned piglets, we conducted a 28-day trial, randomly dividing 72 pigs into three groups: The SO group (fed with a basal diet containing 2% soybean oil), the PRFO group (replacing soybean oil with 2% fish palm rice oil mixture), and the PRCO group (replacing soybean oil with 2% coconut palm rice oil mixture), with eight replicate pens per group (3 pigs per pen) and intestinal chyme was collected on day 29. We observed a significant increase in the concentration of propionic acid (PA) in cecal digesta of the PRFO group (895.49 mmol/L p < 0.05) compared to the SO group (626.32 mmol/L). Meanwhile, the concentration of cecal PA, butyric acid (BA), valerate and colonic valeric acid were significantly increased in the PRCO group (p < 0.05). Moreover, piglets in the PRFO group had a higher abundance of Firmicutes in the cecum and colon, but a lower abundance of Actinomyces in the cecum than those in the SO group. These results indicate that replacing soybean oil with PRFO and PRCO in weaning diet can improve intestinal microflora structure and thus improve intestinal health of piglets.
Corn Seed Quality Detection Based on Spectroscopy and Its Imaging Technology: A Review
Authors: Zhang Jun , Dai Limin , Huang Zhiwen , Gong Caidie , Chen Junjie , Xie Jiashuo , Qu Maozhen
Published: February 2025

The quality assurance of corn seeds is of utmost significance in all stages of production, storage, circulation, and breeding. However, the traditional detection method has some disadvantages, such as high labor intensity, strong subjectivity, low efficiency, cumbersome operation, etc. In view of this, it is of great significance to study more advanced detection methods. In this paper, the application of near-infrared spectroscopy and its imaging technology in the quality detection of corn seeds was reviewed. Firstly, the principles of these two technologies were introduced, and their components, data acquisition, and processing methods, as well as portability, were compared and discussed. Then, the application of these methods to the main quality of corn seeds (including variety and purity, vigor, internal components, mycotoxins, and other qualities such as frost damage, hardness, and maturity, etc.) was reviewed. Breakthroughs and innovations have been made in detection methods, spectral preprocessing methods and recognition algorithms. The significance of corn quality characteristics and the function of the applied algorithm were emphasized. Finally, the challenges and future research direction of spectral and its imaging technology was proposed, aiming to further enhance the accuracy, reliability, and practicability of the detection technology. With the rapid development of spectral and its imaging technology, the detection methods of corn quality are also advancing with the times. This is not just for corn, but more and more crops can be accurately detected by these technologies. It will become an important means of agricultural production inspection in the future.
Monetary Policy Sentiment and Its Influence on Healthcare and Technology Markets: A Transformer Model Approach
Authors: Liu Dongnan , Kim Jong-Min
Published: February 2025

This study investigates how the Federal Open Market Committee’s (FOMC) statements impact healthcare spending, mental health trends, and stock performance in healthcare and tech sectors By analyzing FOMC’s sentiment from 2018 to 2024, we found that higher sentiment correlates with increased depressive disorders (2019–2021) and tech stock returns, especially for the “Magnificent Seven” (like Apple and Amazon). Although healthcare stocks showed weaker ties to sentiment, Granger causality tests suggest some influence, hinting at ways to adjust stock strategies based on FOMC trends. These results highlight how central bank communication can shape both mental health dynamics and investment decisions in healthcare and technology.
Towards Visual Analytics for Explainable AI in Industrial Applications
Authors: Kucher Kostiantyn , Zohrevandi Elmira , Westin Carl A. L.
Published: February 2025

As the levels of automation and reliance on modern artificial intelligence (AI) approaches increase across multiple industries, the importance of the human-centered perspective becomes more evident. Various actors in such industrial applications, including equipment operators and decision makers, have their needs and preferences that often do not align with the decisions produced by black-box models, potentially leading to mistrust and wasted productivity gain opportunities. In this paper, we examine these issues through the lenses of visual analytics and, more broadly, interactive visualization, and we argue that the methods and techniques from these fields can lead to advances in both academic research and industrial innovations concerning the explainability of AI models. To address the existing gap within and across the research and application fields, we propose a conceptual framework for visual analytics design and evaluation for such scenarios, followed by a preliminary roadmap and call to action for the respective communities.
A Step Toward Understanding Direct Impacts of a Higher Estrus-Associated Temperature (HEAT): Transcript Level Changes in Cumulus–Oocyte Complexes Directly Exposed to Acute Elevated Temperature
Authors: Klabnik Jessica L. , Beever Jonathan E. , Payton Rebecca R. , Lamour Kurt H. , Schrick F. Neal , Edwards J. Lannett
Published: February 2025

Elevated body temperature (HEAT) in sexually receptive females is a normal part of the periovulatory microenvironment. The objective was to identify direct (first 6 h) and delayed (4 h or 18 h of recovery) effects at 41 °C exposure during in vitro maturation (IVM) on transcripts involved in steroidogenesis, oocyte maturation, or previously impacted by elevated temperature using targeted RNA-sequencing. Most transcripts (72.3%) were impacted in the first 2 to 4 hIVM. Twelve of the fifteen transcripts first impacted at 4 hIVM had a higher abundance and three had a lower abundance. Direct exposure to 41 °C impacted the transcripts related to progesterone production and signaling, germinal vesicle breakdown, oocyte meiotic progression, transcriptional activity and/or alternative splicing, cell cycle, cumulus expansion, and/or ovulation. Three transcripts demonstrated a delayed impact; changes were not seen until the COCs recovered for 4 h. The use of multidimensional scaling plots to ‘visualize’ samples highlights that oocytes exposed to an acute elevation in temperature are more advanced at the molecular level during the initial stages of maturation. Described efforts represent important steps towards providing a novel insight into the dynamic physiology of the COC in the estrual female bovid, during HEAT and after body temperature returns to baseline.
Phenotypical, Behavioral, and Systemic Hallmarks in End-Point Mouse Scenarios
Authors: Castillo-Mariqueo Lidia , Alveal-Mellado Daniel , Giménez-Llort Lydia
Published: February 2025

The state of frailty is a clinical–biological syndrome that affects the older population with a higher risk of functional dependence. Animal models can provide a tool to study this complex scenario. In the present work, we analyzed the physical and behavioral hallmarks of end-point status in 16-month-old mice (C57BL/6J) according to animal welfare regulations compared to age-matched counterparts with normal aging. A group of 6-month-old mice was added to control for age bias. First, we identified ‘structural kyphosis’ (visible and unmodifiable deformation in locomotion) correlated with piloerection as the hallmarks of the physical frailty phenotype compared to the ‘postural kyphosis’ (adjustment to counteract increased visceral volume but attenuated during locomotion) of old mice with normal aging. Alopecia (barbering) was presented in both old groups. Normal levels of exploratory activity in the corner test for neophobia and triceps surae muscle weight but an increased latency of rearing indicated the poorest emotional phenotype, with a possible contribution of structural kyphosis. The presence of hepatomegaly and splenomegaly counteracted the significant WAT loss commonly associated with end-of-life traits, which should have a normal body weight but preserved muscle mass.
Oxidative Mechanism of Peyronie’s Disease and Effectiveness of Pentoxifylline in the Therapeutic Management: A Narrative Review
Authors: Paulis Gianni , Paulis Andrea
Published: February 2025

Peyronie’s disease (PD) is a chronic disease characterized by the development of fibrous tissue in the tunica albuginea of the penile corpora cavernosa that causes penile deformity. The precise cause of PD is not completely understood, but it is generally believed to be initiated by a specific injury in the affected area. Research has consistently shown that oxidative stress (OS) is a key player in PD. Pentoxifylline (PTX) is a synthetic derivative of methylxanthine that was initially used for the management of peripheral vascular disease. PTX has also been used in humans for several inflammatory and fibrotic conditions, including PD. PTX has several mechanisms of action, including antioxidant, antifibrotic, anti-inflammatory, and vasorelaxant. This article aims to verify, after a review of the literature regarding the use of PTX in PD, whether this substance is really able to cure PD. We conducted research by consulting the scientific literature on the topic. Results: After examining 39 articles, we considered 20 articles eligible for our narrative review, including a single randomized controlled clinical study, six clinical studies with a control group, a single uncontrolled clinical study, eight case report studies, and four systematic review articles. Conclusions: Although the systematic review articles selected in this paper showed no consistent evidence regarding the efficacy of PTX, in our opinion, the clinical studies we have analyzed undoubtedly demonstrate that PTX is able to combat PD, thanks to its ability to interfere with the pathogenic mechanisms of the disease. However, we believe that further new randomized controlled trials are necessary to more clearly demonstrate the effectiveness of PTX in the treatment of PD.
Grain Protein Function Prediction Based on CNN and Residual Attention Mechanism with AlphaFold2 Structure Data
Authors: Liu Jing , Zhang Xinping , Huang Kai , Wei Yuqi , Guan Xiao
Published: February 2025

The prediction of grain protein function is essential for the advancement of food science. Traditional experimental methods are associated with high costs and significant time requirements. Computational methods are recognized for their efficiency and reduced time demands. A new multimodal deep learning method, MMSNet, is proposed in this study, and protein data of four types of grains (japonica, indica, maize, and wheat) are analyzed. This method fuses the protein structure information predicted by AlphaFold2 and combines a multiscale one-dimensional convolutional neural network (1DCNN) with a two-dimensional convolutional neural network (2DCNN) to enable the model to capture sequence and structural information effectively. We used a residual attention mechanism to replace the traditional pooling layer, thereby improving the feature extraction capability of the network layers in 2DCNN. The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. Compared with two classical methods, MMSNet demonstrates optimal performance, which validates the effectiveness of our approach in integrating complex grain protein data and highlights its potential to open new avenues for grain protein function prediction.
Light Graph Convolutional Recommendation Algorithm Based on Hybrid Spreading
Authors: Duan Yaowei , Zhang Liang , Lu Xu , Li Junqing
Published: February 2025

With the explosive growth of information on the internet, personalized recommendation technology has become an important tool for helping users efficiently acquire information. However, existing spreading-based recommendation algorithms only consider user choices and fail to fully leverage the potential relationships between users and items. Additionally, the incomplete utilization of user and item information limits their application potential and applicable scenarios, resulting in suboptimal recommendation performance in practical applications. To address this issue, we propose a Light Graph Convolutional Recommendation Algorithm Based on Hybrid Spreading (LGCNHS). This algorithm first optimizes the embeddings of users and items using their respective feature matrix, then learns the latent embedding representations of users and items through a lightweight graph convolutional network. Finally, the latent embedding representations are incorporated as key parameters into the hybrid spreading recommendation algorithm to generate recommendations. Comparative experiments on two publicly available datasets, MovieLens and Douban, demonstrate that LGCNHS achieves improved accuracy and diversity in recommendations compared to related methods. The algorithm code is available on github.
Deep Learning vs. Machine Learning for Intrusion Detection in Computer Networks: A Comparative Study
Authors: Ali Md Liakat , Thakur Kutub , Schmeelk Suzanna , Debello Joan , Dragos Denise
Published: February 2025

In response to the increasing volume of network traffic and the growing sophistication of cyber threats, this study examines the use of deep learning-based intrusion detection systems (IDSs) in large-scale network environments. Traditional IDS face challenges such as high false positive rates, complex feature engineering, and class imbalances in datasets, all of which impede accurate threat detection. To overcome these limitations, we implement various deep learning models, including multilayer perceptron (MLP), convolutional neural network (CNN), and long short-term memory (LSTM), alongside traditional machine learning algorithms such as logistic regression, naive Bayes, random forest, K-nearest neighbors, and decision trees. A significant contribution of this study is the application of the synthetic minority over-sampling technique (SMOTE) to address class imbalance, enhancing the representativeness of the learning process. Additionally, we conduct a comprehensive performance comparison of the models, incorporating correlation-based feature selection and hyperparameter tuning to maximize detection accuracy. Our results indicate that deep learning models, particularly CNN and LSTM, outperform traditional machine learning approaches in cyber threat detection, achieving accuracy rates of 98%. However, random forest achieves the highest accuracy at 99.9%, demonstrating its effectiveness in structured intrusion detection tasks. Moreover, we evaluate computational efficiency and practical deployment considerations, discussing trade-offs between accuracy and resource consumption. These findings highlight the potential of deep learning-based IDS for large-scale network security applications while addressing key challenges such as interpretability and computational overhead. The study provides actionable insights for selecting the most suitable IDS models based on specific network environments and security requirements.
Advancing Fault Detection in Distribution Networks with a Real-Time Approach Using Robust RVFLN
Authors: Haydaroğlu Cem , Kılıç Heybet , Gümüş Bilal , Özdemir Mahmut Temel
Published: February 2025

In this paper, the fault type and location of high-impedance short-circuit faults, which are difficult to detect in distribution networks, are determined in real time using the Real-Time Digital Simulator (RTDS). In this study, an IEEE 39-bar system model is created using the Real-Time Simulation Software Package (RSCAD). In this model, a short-circuit fault is generated at different fault impedance values. For high-impedance short-circuit fault detection, 14 feature vectors are created. Six of these feature vectors are newly developed, and it is found that these six new feature vectors contribute 10% to the detection of hard-to-detect high-impedance short-circuit faults. We propose a data-driven online algorithm for fault type and location detection based on robust regularized random vector function networks (ORR-RVFLNs). Moreover, the robustness of the model is improved by adding a certain amount of noise to the detected short-circuit fault data. In this study, the method ORR-RVFLN for the 39-bus system IEEE detects the average error type for all error impedances, with 92.2% success for the data with noise added. In this study, the fault location is shown to be more than 90% accurate for distances greater than 400 m.
Artificial Intelligence in Ophthalmology: Advantages and Limits
Authors: Costin Hariton-Nicolae , Fira Monica , Goraș Liviu
Published: February 2025

In recent years, artificial intelligence has begun to play a salient role in various medical fields, including ophthalmology. This extensive review is addressed to ophthalmologists and aims to capture the current landscape and future potential of AI applications for eye health. From automated retinal screening processes and machine learning models predicting the progression of ocular conditions to AI-driven decision support systems in clinical settings, this paper provides a comprehensive overview of the clinical implications of AI in ophthalmology. The development of AI has opened new horizons for ophthalmology, offering innovative solutions to improve the accuracy and efficiency of ocular disease diagnosis and management. The importance of this paper lies in its potential to strengthen collaboration between researchers, ophthalmologists, and AI specialists, leading to transformative findings in the early identification and treatment of eye diseases. By combining AI potential with cutting-edge imaging methods, novel biomarkers, and data-driven approaches, ophthalmologists can make more informed decisions and provide personalized treatment for their patients. Furthermore, this paper emphasizes the translation of basic research outcomes into clinical applications. We do hope this comprehensive review will act as a significant resource for ophthalmologists, researchers, data scientists, healthcare professionals, and managers in the healthcare system who are interested in the application of artificial intelligence in eye health.
Control Strategy for Improving Dual Motor Synchronization Accuracy: Cross Coupling Method Based on Improved Global Fast Terminal Sliding Mode Control and Disturbance Observer
Authors: Wu Kelu , Zhang Yongchao , Qi Yubao , Shi Weimin
Published: February 2025

To improve the synchronization accuracy of dual motors under external disturbances, this paper proposes a cross-coupling control strategy based on an improved global fast terminal sliding mode control (GFTSMC) and disturbance observer (DOB). In practical applications, dual-motor systems are often affected by external disturbances, leading to synchronization errors between the motors, which in turn affect the system’s stability and accuracy. First, for single-motor control, this paper uses the improved GFTSMC method to design a speed loop, enhancing the tracking accuracy and dynamic response of the individual motor by optimizing the sliding surface. Then, the improved GFTSMC is combined with a cross-coupling strategy to effectively solve the synchronization problem of dual motors. The cross-coupling strategy coordinates the operation of the two motors, reducing the speed deviation between them, thus improving synchronization accuracy and enhancing the system’s disturbance rejection capability. Moreover, the DOB is used to precisely estimate the frictional torque, and compensating for these disturbances improves the system’s robustness and stability. The results show that the proposed control method significantly improves the speed synchronization of the dual motors and exhibits excellent dynamic performance, effectively coping with complex external disturbances.
Cascadable First-Order and Second-Order Inverse Filters Based on Second-Generation Voltage Conveyors
Authors: Roongmuanpha Natchanai , Likhitkitwoerakul Nutcha , Pukkalanun Tattaya , Faseehuddin Mohammad , Tangsrirat Worapong
Published: February 2025

This study introduces four novel configurations of first-order and second-order multifunction inverse filters in both voltage-mode (VM) and current-mode (CM) using second-generation voltage conveyors (VCIIs). The first-order VM and CM inverse filters utilize only three passive components together with one VCII for VM and two VCIIs for CM realizations, which can provide lowpass and highpass inverse filter responses. The latter, second-order VM and CM multifunction inverse filters, can be constructed using the corresponding first-order inverse filters as their core circuits. These filters offer all the basic inverse filter functions, including lowpass, bandpass, and highpass inverse responses with all gains obtained from the same design. All the inverse filter realizations are cascadable. No component matching requirements are necessary for all filter responses. The non-ideal effects of the VCII on the performance of the proposed inverse filters are thoroughly examined. To prove the feasibility of the designs, the PSPICE program performed several simulations, utilizing model parameters of 0.18 µm CMOS technology. Some testing experiments were conducted using the commercially available IC-type AD844s for evaluating the practical performance of the designed inverse filters.
Deposition and Characterization of Cu-Enhanced High-Entropy Alloy Coatings via DC Magnetron Sputtering
Authors: Sobetkii Arcadii , Mosinoiu Laurentiu-Florin , Caramarin Stefania , Mitrica Dumitru , Cursaru Laura-Madalina , Matei Alexandru-Cristian , Tudor Ioan-Albert , Serban Beatrice-Adriana , Ghita Mihai , Vitan Nicoleta , Witt Julia , Ozcan Ozlem , Postolnyi Bogdan , Pogrebnjak Alexander
Published: February 2025

Protection against microbiologically influenced corrosion (MIC) is critical for materials used in aquatic environments, as MIC accelerates material degradation and leads to faster structural failure. Copper (Cu) has the potential to substantially improve the MIC resistance in alloys. In this study, high-entropy alloy (HEA) coatings containing Cu were deposited using DC (Direct Current) magnetron sputtering to enhance the corrosion resistance and mechanical properties of various substrates. Two CuCrFeMnNi HEA compositions in the form of bulk alloys and PVD (Physical Vapor Deposition) coatings, with 5% and 10% Cu, were analyzed for their microstructural, mechanical, and anticorrosive characteristics. Deposition parameters were varied to select the optimal values. Microstructural evaluations using SEM-EDS (scanning electron microscopy and energy dispersive X-ray spectroscopy), XRD (X-ray diffraction), and AFM (atomic force microscopy) revealed uniform, dense coatings with good adhesion composed of dendritic and interdendritic BCC (body-centered cubic) and FCC (face centered cubic) structures, respectively. Microhardness tests indicated improved mechanical properties for the samples coated with developed HEAs. The coatings exhibited improved corrosion resistance in NaCl solution, the 10% Cu composition displaying the highest polarization resistance and lowest corrosion rate. These findings suggest that Cu-containing HEA coatings are promising candidates for applications requiring enhanced corrosion protection.
Analysis of Hydration Strength and CO2 Emissions of Cement–Quartz Powder Binary Blends Considering the Effects of Water/Binder Ratios and Quartz Contents
Authors: Yang Bo , Wang Xiao-Yong
Published: February 2025

Low-carbon design has become increasingly important in the cement and concrete industry. Previous studies have primarily focused on the impact of different types of admixtures on the carbon emissions of concrete while overlooking the influence of the water-to-cementitious materials ratio on concrete carbon emissions. To address this gap, this study aims to investigate the synergistic effects of the water-to-binder ratio and quartz powder dosage on concrete hydration, strength, and carbon emissions and to propose a comprehensive performance prediction model. Our proposed performance prediction model highlights the critical role of the water-to-cementitious materials ratio in low-carbon concrete design. It distinguishes between the dilution and nucleation effects of the quartz filler and evaluates the impact of quartz content (10% and 20%) and water-to-binder ratios (0.5 and 0.2) on the cement hydration rate; consequently, it is able to predict the concrete’s thermal, chemical, mechanical, and environmental properties. The model specifics are as follows: the parameters were determined using hydration heat data from a paste with a water-to-binder ratio of 0.5 over the first 3 days, and the chemically combined water and portlandite production was calculated up to 28 days. The water availability coefficient, derived from hydration product measurements with a ratio of 0.2, shows that lower water-to-binder ratios slow hydration as the coefficient exceeds 1. A linear equation predicts strength development based on the mix ratio and reaction degree. The CO2 emission analysis shows that when the water/binder ratio is 0.50, with a compressive strength of 1 MPa, the carbon emissions change little with an increase in the quartz powder replacement rate. However, when the water/binder ratio is 0.2, the percentage reductions in CO2 emissions per unit strength are 11% and 20% for the 10% and 20% quartz powder replacement rates, respectively, compared with the specimen without quartz powder. The model’s regression method is simple, versatile across mix ratios, and capable of predicting hydration heat, product composition, strength, and CO2 emissions.
The Use of Design of Experiments (DoE) Approaches for the Development of Self-Emulsifying Drug Delivery Systems (SEDDS)
Authors: Serrano Ana Carolina Carvalho Lopes , Viana Mateus Costa , Pinto Natalha Vicentina , Lages Eduardo Burgarelli , Carneiro Guilherme , Borges Gabriel Silva Marques
Published: February 2025

Self-emulsifying drug delivery systems (SEDDS) consist of isotropic mixtures of oils, surfactants, and solvents that after dispersion emulsify in the aqueous media of the gastrointestinal tract (GIT). SEDDS can deliver hydrophobic drugs, which could enhance their oral bioavailability by protecting them from precipitation and degradation. However, it is important to find the appropriate ratio of their excipients to produce emulsions with the desirable physicochemical characteristics. In this sense, Design of Experiments (DoE) approaches such as central composite design (CCD) and Box–Behnken design (BBD) can reduce the number of experiments necessary to determine the best composition and preparation process of a SEDDS formulation. Therefore, this article aims to discuss drug delivery through SEDDS and how DoE approaches can aid researchers in achieving product quality specifications and optimizing the formulation preparation processes. For this, the most recent and relevant papers were analyzed. This review is expected to guide future research directions for more rational development of SEDDS.
The Role of Atmospheric Circulation Patterns in Water Storage of the World’s Largest High-Altitude Landslide-Dammed Lake
Authors: Deng Xuefeng , Li Yizhen , Zhang Jingjing , Kong Lingxin , Abuduwaili Jilili , Gulayozov Majid , Kodirov Anvar , Ma Long
Published: February 2025

This study reconstructed the annual lake surface area (LSA) and absolute lake water storage (LWS) changes of Lake Sarez, the world’s largest high-altitude landslide-dammed lake, from 1992 to 2023 using multi-source remote sensing data. All available Landsat images were used to extract the LSA using an improved multi-index threshold method, which incorporates a slope mask and threshold adjustment to enhance the boundary delineation accuracy (Kappa coefficient = 0.94). By combining the LSA with high-resolution DEM and the GLOBathy bathymetry dataset, the absolute LWS was reconstructed, fluctuating between 12.3 × 109 and 12.8 × 109 m3. A water balance analysis revealed that inflow runoff (IRO) was the primary driver of LWS changes, contributing 54.57%. The cross-wavelet transform and wavelet coherence analyses showed that the precipitation (PRE) and snow water equivalent (SWE) were key climatic factors that directly influenced the variability of IRO, impacting the interannual water availability in the lake, with PRE having a more sustained impact. Temperature indirectly regulated IRO by affecting SWE and potential evapotranspiration. Furthermore, IRO exhibited different resonance periods and time lags with various atmospheric circulation factors, with the Pacific Decadal Oscillation and North Atlantic Oscillation having the most significant influence on its interannual variations. These findings provide crucial insights into the hydrological behavior of Lake Sarez under climate change and offer a novel approach for studying water storage dynamics in high-altitude landslide-dammed lakes, thereby supporting regional water resource management and ecological conservation.
Reflections on the Role of Differentiation Processes in Forming Behavioral Phenotypes: Can These Processes Replace the Concepts of Plastic Phenotype and Reversible Plastic Phenotype?
Authors: Chiappa Pilar
Published: February 2025

This essay presents two lines of argument to suggest that the extension into adulthood of specific phenotypic differentiation processes, typical of early development, is fundamental to the evolution of cognition. The first of these two lines of argument is organized in three steps. The first step reviews various studies of human development, highlighting that it has slowed down throughout evolution compared to that of great apes. The second step explores the relationship between this slowed development and human cognition. The third step discusses evolutionary comparative analyses that show a correlation between the evolution of cognitive processes and developmental changes. The second line of argument examines concepts of phenotype. First, the concepts of phenotype are reviewed in correspondence to the two meanings of the word plasticity (i.e., as the ability to alternate or as the ability to shape), and it is concluded that all phenotypes —rigid, plastic, and reversible—fit the meaning of shaping. It is proposed that a phenotypical process can be seen as a continuous series of functional differentiations that occur at different times during the life of the organism and at different contextual points, both inside and outside the organism. Finally, a brief recapitulation is presented that is focused on supporting the formation of behavioral phenotypes as a sequence of differentiation processes shaping the environmental interactions from the most general to the most particular.
Evaluation of Biological Properties and Beneficial Effects for a Sustainable and Conscious Exploitation of Achatina fulica Snails
Authors: Alogna Andrea , Liboni Alessia , Rizzo Roberta
Published: February 2025

In recent decades, there has been significant worldwide interest in the emergence of a new invasive species known as Achatina fulica. This is due to its dangerous habits for the environment, its biological characteristics and the fact that it is the intermediate host of several nematode parasites, such as Angiostrongylus cantonensis. This land snail species is native to tropical African countries, but has been introduced, accidentally or deliberately, to other parts of the world to be used for different purposes and is now established in a large part of the tropics. Since the 1980s, hundreds of researchers have been interested in the beneficial properties of its mucus, ranging from the antimicrobial and anticancer properties to the use of its powdered shell as a biocatalyst. This literature review aims to objectively describe the positive and negative aspects associated with the spread of A. fulica, highlighting in particular the opportunities for the local populations deriving from a conscious exploitation of this mollusc.
Mechanisms of Resistance to Anti-PD-1 Immunotherapy in Melanoma and Strategies to Overcome It
Authors: Zielińska Magdalena K. , Ciążyńska Magdalena , Sulejczak Dorota , Rutkowski Piotr , Czarnecka Anna M.
Published: February 2025

Resistance to anti-PD-1 therapy in melanoma remains a major obstacle in achieving effective and durable treatment outcomes, highlighting the need to understand and address the underlying mechanisms. The first key factor is innate anti-PD-1 resistance signature (IPRES), an expression of a group of genes associated with tumor plasticity and immune evasion. IPRES promotes epithelial-to-mesenchymal transition (EMT), increasing melanoma cells’ invasiveness and survival. Overexpressed AXL, TWIST2, and WNT5a induce phenotypic changes. The upregulation of pro-inflammatory cytokines frequently coincides with EMT-related changes, further promoting a resistant and aggressive tumor phenotype. Inflamed tumor microenvironment may also drive the expression of resistance. The complexity of immune resistance development suggests that combination therapies are necessary to overcome it. Furthermore, targeting epigenetic regulation and exploring novel approaches such as miR-146a modulation may provide new strategies to counter resistance in melanoma.
TIM8 Deficiency in Yeast Induces Endoplasmic Reticulum Stress and Shortens the Chronological Lifespan
Authors: Tang Dong , Guan Wenbin , Yang Xiaodi , Li Zhongqin , Zhao Wei , Liu Xinguang
Published: February 2025

Yeast TIM8 was initially identified as a homolog of human TIMM8A/DDP1, which is associated with human deafness–dystonia syndrome. Tim8p is located in the mitochondrial intermembrane space and forms a hetero-oligomeric complex with Tim13p to facilitate protein transport through the TIM22 translocation system. Previous research has indicated that TIM8 is not essential for yeast survival but does affect the import of Tim23p in the absence of the Tim8-Tim13 complex. Previous research on TIM8 has focused mainly on its involvement in the mitochondrial protein transport pathway, and the precise biological function of TIM8 remains incompletely understood. In this study, we provide the first report that yeast TIM8 is associated with the endoplasmic reticulum (ER) stress response and chronological senescence. We found that deletion of TIM8 leads to both oxidative stress and ER stress in yeast cells while increasing resistance to the ER stress inducer tunicamycin (TM), which is accompanied by an enhanced basic unfolded protein response (UPR). More importantly, TIM8 deficiency can lead to a shortened chronological lifespan (CLS) but does not affect the replicative lifespan (RLS). Moreover, we found that improving the antioxidant capacity further increased TM resistance in the tim8Δ strain. Importantly, we provide evidence that the knockdown of TIMM8A in ARPE-19 human retinal pigment epithelium cells can also induce ER stress, suggesting the potential function of the TIM8 gene in ER stress is conserved from budding yeast to higher eukaryotes. In summary, these results suggest novel roles for TIM8 in maintaining ER homeostasis and CLS maintenance.
Harnessing Pharmacomultiomics for Precision Medicine in Diabetes: A Comprehensive Review
Authors: Dhieb Dhoha , Mustafa Dana , Hassiba Maryam , Alasmar May , Elsayed Mohamed Haitham , Musa Ameer , Zirie Mahmoud , Bastaki Kholoud
Published: February 2025

Type 2 diabetes (T2D) is the fastest-growing non-communicable disease worldwide, accounting for around 90% of all diabetes cases and imposing a significant health burden globally. Due to its phenotypic heterogeneity and composite genetic underpinnings, T2D requires a precision medicine approach personalized to individual molecular profiles, thereby shifting away from the traditional “one-size-fits-all” medical methods. This review advocates for a thorough pharmacomultiomics approach to enhance precision medicine for T2D. It emphasizes personalized treatment strategies that enhance treatment efficacy while minimizing adverse effects by integrating data from genomics, proteomics, metabolomics, transcriptomics, microbiomics, and epigenomics. We summarize key findings on candidate genes impacting diabetic medication responses and explore the potential of pharmacometabolomics in predicting drug efficacy. The role of pharmacoproteomics in prognosis and discovering new therapeutic targets is discussed, along with transcriptomics’ contribution to understanding T2D pathophysiology. Additionally, pharmacomicrobiomics is explored to understand gut microbiota interactions with antidiabetic drugs. Emerging evidence on utilizing epigenomic profiles in improving drug efficacy and personalized treatment is also reviewed, illustrating their implications in personalized medicine. In this paper, we discuss the integration of these layers of omics data, examining recently developed paradigms that leverage complex data to deepen our understanding of diabetes. Such integrative approaches advance precision medicine strategies to tackle the disease by better understanding its complex biology.
Dysbiosis of Oral Microbiome: A Key Player in Oral Carcinogenesis? A Critical Review
Authors: Devaraja K. , Aggarwal Sadhna
Published: February 2025

The oral cavity is known to harbor hundreds of microorganisms, belonging to various genera, constituting a peculiar flora called the oral microbiome. The change in the relative distribution of the constituents of this microbial flora, due to any reason, leads to oral dysbiosis. For centuries, oral dysbiosis has been linked to the etiopathogenesis of several medical illnesses, both locally and systemically-. However, aided by the recent advent of bio-technological capabilities, several reports have re-emerged that link oral dysbiosis to oral carcinogenesis, and numerous studies are currently exploring their association and plausible mechanisms. Some of the proposed mechanisms of oral dysbiosis-induced carcinogenesis (ODIC) include—a bacteria-induced chronic inflammatory state leading to direct cellular damage, inflammatory-cytokine-mediated promotion of cellular proliferation and invasion, release of bacterial products that are carcinogenic, and suppression of local immunity by alteration of the tumor microenvironment. However, the actual interactions between these cellular mechanisms and their role in carcinogenesis are not yet fully understood. This review provides a comprehensive overview of the various hypotheses and mechanisms implicated in the ODIC, along with the corresponding molecular aberrations. Apart from discussing the usual constituents of the oral microbiome profile, the review also summarizes the various dysbiosis profiles implicated in ODIC. The review also sheds light on the potential clinical implications of the research on oral microbiome in the prevention and management of oral cancer.
Cognition and Cognitive Training in Patients with Neurodegenerative Diseases
Authors: Cavallo Marco , Lasaponara Stefano
Published: February 2025

This Special Issue presents some recent developments in the intriguing research and clinical field of cognition and cognitive training in patients with neurodegenerative diseases [...]
GIS-Based Study on the Suitability of Site Selection for Community Complexes in Old Residential Areas in Xi’an, China
Authors: Guo Xixi , Cui Xiaoping
Published: February 2025

As an important means to improve the construction of community services, community complexes can not only provide residents with “one-stop” services, but also promote the coordinated development of communities and cities while improving the efficiency of urban land use. In this paper, the distribution characteristics and influencing factors of the corresponding complex construction were sorted out by combing and investigating the problems of the old residential areas in Xi’an, China. GISmap10.2 software was used to obtain the data of social resource allocation, surrounding service facilities, and land use efficiency characteristics within the living circle. Combined with field research, the traditional communities were classified and discussed, so as to put forward strategies for the construction of community complexes with different types of community spaces.
Influence of Friction Models on the Seismic Response of Box-Girder RC Bridges with Double Concave Friction Pendulum Bearings Under Varying Deck Aspect and Mass Ratios
Authors: Borekci Muzaffer
Published: February 2025

Friction pendulum bearings are widely used seismic isolation devices for bridges, with their behavior governed by friction during excitation. Sliding velocity and contact pressure are among the factors that substantially affect the friction coefficient. Common friction models include the Coulomb model, which assumes constant friction and neglects both sliding velocity and contact pressure, and the velocity-dependent model, which ignores contact pressure. This study investigates the impact of neglecting contact pressure on bridge response by additionally employing a velocity-pressure-dependent friction model and comparing the effects of these three models on the bridge response. Five 3-span box-girder RC bridges were modeled in OpenSees (v3.5.0) using Coulomb, velocity-dependent, and velocity-pressure-dependent friction models. Deck height variations were introduced to account for axial load changes on bearings. Nonlinear time history analyses were performed to evaluate seismic responses. The study also explored the effects of substructure-to-superstructure mass ratio and variations in the experimentally obtained rate parameter of velocity-dependent and velocity-pressure-dependent models. Results indicate that the velocity-pressure-dependent model provides more consistent predictions, while the rate parameter has negligible effects. The velocity-pressure-dependent model increases isolator displacement by nearly 2.5 times compared to the Coulomb and velocity-dependent models. Differences in responses are influenced more by the mass ratio than by the deck aspect ratio.
User Well-Being as a Paramount Challenge in Contemporary Built Environment Design: The Architecture of Psychiatric Hospitals and Its Influence on Treatment Processes and the Health, Safety, and Comfort of Patients and Medical Staff—A Systematic Literature Review and Insights from the New European Bauhaus Initiative
Authors: Pawlaczyk-Szymańska Daria , Gębczyńska-Janowicz Agnieszka , Zdrojewska Joanna , Szarejko Wacław
Published: February 2025

The natural environment, urban systems, and the buildings in which we live, study, work, or undergo treatment affect our mental health. The aim of this literature review was to verify the state of knowledge on the impact of the forms of psychiatric hospital buildings and the architectural solutions used inside these facilities on their comfort and safety of use, more effective forms of therapy, and the health of patients, as well as the comfort and safety of medical staff. This literature review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The scientific databases that were accepted for review were Scopus, Web of Science, and PubMed. During the preliminary analysis, During the initial analysis, 175 potential publications addressing the architecture of psychiatric hospital buildings were obtained. After three-stage verification, 31 English-language publications qualified for the review. The review showed the state and form of the architecture of psychiatric hospitals. The obtained results confirm the significant impact of the buildings and interiors of psychiatric wards and hospitals on the safety, comfort, and well-being of their users, as well as on achieving better therapeutic effects. The literature review not only examined the current state and form of the architecture in psychiatric hospitals but also the architectural solutions increasingly used in these facilities in order to improve the quality of the space, which affects its users.
New Serious Safety Warnings for Targeted Anticancer Agents After Their Initial FDA Approval
Authors: Stefanovski Dimitar , Manevski Damjan , Ribnikar Domen , Šeruga Boštjan
Published: February 2025

Background: New safety concerns about targeted anticancer agents (TAAs) often emerge in the first few years after their initial regulatory approval. Our aim was to determine whether new serious and potentially fatal adverse drug reactions (ADRs) continue to emerge in the updated drug labels of TAAs several years after their initial regulatory approval and whether their emergence can be predicted. Methods: The updated drug labels of TAAs approved by the U.S. Food and Drug Administration before July 2013 were analyzed. Serious and potentially fatal ADRs were identified in the Warnings & Precautions (WPs) and Boxed Warnings (BWs) sections of the updated drug labels. Generalized linear mixed models were used to examine the associations between the number of adverse drug reactions and time, drug type (small molecules vs. monoclonal antibodies), and the availability of companion diagnostics for biomarkers. Results: Among 37 eligible TAAs, 25 (68%) were small molecules and 11 (30%) had available companion diagnostics for the biomarkers. Time was a significant predictor of new WPs (p ˂ 0.001) and BWs (p = 0.008). The updated drug labels of the small molecules received significantly more new WPs (p = 0.042) as compared to monoclonal antibodies. The availability of the companion diagnostics for the biomarkers did not have an impact on the emergence of new ADRs. Conclusions: New serious ADRs of TAAs continue to emerge in updated drug labels several years after their initial regulatory approval. Oncologists, regulators, and payers should be aware of the changing risk–benefit ratios of approved TAAs.