bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Trading Strategy for Virtual Power Plants with Incomplete Resource Aggregation Based on Hybrid Game Theory
Authors: Wan Jing , Tang Jinrui , Chen Rui , Suo Leiming , Yang Honghui , Song Yubo , Zhang Haibo
Published: February 2025

Shared energy storage (SES) and some photovoltaic prosumers (PVPs) are difficult to aggregate by the virtual power plant (VPP) in the short term. In order to realize the optimal operation of the VPP in the incomplete resource aggregation environment and to promote the mutual benefit of multiple market entities, the energy trading strategy based on the hybrid game of SES–VPP–PVP is proposed. Firstly, the whole system configuration with incomplete resource aggregation is proposed, as well as the preconfigured market rules and the general problem for the optimal energy trading strategy of VPP. Secondly, the novel hybrid game theory-based optimization for the energy trading strategy of VPP is proposed based on the multi-level game theory model. And, the corresponding solving process using Karush–Kuhn–Tucker (KKT), dichotomy, and alternating direction method of multipliers (ADMM) algorithms are also constructed to solve nonconvex nonlinear models. The effectiveness of the proposed strategy is verified through the comparison of a large number of simulation results. The results show that our proposed energy trading strategy can be used for optimal low-carbon operation of VPPs with large-scale renewable energy and some unaggregated electricity consumers and distributed photovoltaic stations, while SES participates as an independent market entity.
Cyber Environment Test Framework for Simulating Command and Control Attack Methods with Reinforcement Learning
Authors: Jeong Minki , Park Jongyoul , Oh Sang Ho
Published: February 2025

Recently, the IT industry has become larger, and cloud service has rapidly increased; thus cybersecurity to protect sensitive data from attacks has become an important factor. However, cloud services have become larger, making the surface area larger, and a complex cyber environment leads to difficulty managing and defending. With the rise of artificial intelligence, applying artificial intelligence to a cyber environment to automatically detect and respond to cyberattacks has begun to get attention. In order to apply artificial intelligence in cyber environments, a simulation framework that is easily applicable and can represent real situations well is needed. In this study, we introduce the framework Cyber Environment (CYE) that provides useful components that abstract complex and large cloud environments. Additionally, we use CYE to reproduce real-world situations into the scenario and apply reinforcement learning for training automated intelligence defense agents.
Policy-Based Reinforcement Learning Approach in Imperfect Information Card Game
Authors: Chrustowski Kamil , Duch Piotr
Published: February 2025

Games provide an excellent testing ground for machine learning and artificial intelligence, offering diverse environments with strategic challenges and complex decision-making scenarios. This study seeks to design a self-learning artificial intelligent agent capable of playing the trick-taking stage of the popular card game Thousand, known for its complex bidding system and dynamic gameplay. Due to the game’s vast state space and strategic complexity, other artificial intelligence approaches, such as Monte Carlo Tree Search and Deep Counterfactual Regret Minimisation, are infeasible. To address these challenges, the enhanced version of the REINFORCE policy gradient algorithm is proposed. Introducing a score-related parameter β designed to guide the learning process by prioritising valuable games, the proposed approach enhances policy updates and improves overall learning outcomes. Moreover, leveraging the off-policy experience replay, along with the importance weighting of behavioural policy, enhanced training stability and reduced model variance. The proposed algorithm was applied to the trick-taking stage of the popular game Thousand Schnapsen in a two-player setup. Four distinct neural network models were explored to evaluate the performance of the proposed approach. A custom test suite of selected deals and tournament evaluations was employed to assess effectiveness. Comparisons were made against two benchmark strategies: a random strategy agent and an alpha-beta pruning tree search with varying search depths. The proposed algorithm achieved win rates exceeding 65% against the random agent, nearly 60% against alpha-beta pruning at a search depth of 6, and 55% against alpha-beta pruning at the maximum possible depth.
E-Waste Plastics in the Environment: Assessment, Characterisation, and Bioprocessing
Authors: Ferreira-Filipe Diogo A. , Hursthouse Andrew , Duarte Armando C. , Rocha-Santos Teresa , Patrício Silva Ana L.
Published: February 2025

The accelerated growth of the electrical and electronic equipment market is a major driver behind increasing e-waste volumes worldwide. Although e-waste contains valuable resources, most remain unrecycled or improperly managed. Recycling efforts primarily focus on recovering metals, while plastic constituents remain overlooked. Furthermore, current e-waste plastic recycling approaches have led to environmental contamination by hazardous materials. Recent efforts for the valorisation of e-waste plastics have demonstrated the potential applications of these materials and their role in efforts towards implementing a more sustainable plastics economy. While the environmental impact and potential strategies for recycling e-waste plastics have been recently reviewed, a thorough discussion that accounts for the environmental impact, characterisation strategies, and potential biotechnological treatment options remains lacking. Accordingly, this review addresses this gap, discussing recent developments in the e-waste plastics field. It focuses on their environmental impacts, the collection of environmental samples and their characterisation, as well as innovative approaches for valorisation through biotechnological strategies. Specifically, the discussion is centred on studies that directly use or focus on plastics derived from e-waste. While progress has been made in the characterisation of environmental contaminants and remediation/bioprocessing strategies for this type of hazardous waste, challenges remain, including financial barriers, limited research volume compared to related fields (e.g., e-waste metals), and environmental impact and relevance concerns. This review identifies a need for increased research, interdisciplinary collaboration, and policy support to overcome these barriers and advance sustainable e-waste plastic management.
Recent Developments in Heterologous Expression of Cellulases Using the Pichia pastoris Expression System: A Comprehensive Literature Review
Authors: Muzaffar Nazish , Raziq Abdur , Khan Muhammad Waseem , Khan Niaz Muhammad , Shahid Bushra , Gul Anbareen , Ullah Hayat
Published: February 2025

Cellulosic biomass is considered an important and sustainable source of renewable energy, which needs a complex mixture of different enzymes for its degradation. After amylase, cellulases are the second most important enzymes, gain more importance due to their broad range of applications at the industrial level, and are considered more economical and environmentally friendly; researchers have focused more on the production of cellulase with its higher expression rate and low cost. Pichia pastoris, a methylotrophic yeast strain, has a more effective and well-established system for the production of heterologous proteins, particularly for industrial enzymes. Moreover, its readily achievable high-density fermentation, high capacity for protein secretion, tractable genetic modifications, typical post-transcriptional modifications, and strong regulated promoters makes it superior to other expression systems. In this review, we address the P. pastoris expression system including protein expression platforms, plasmids, and cellular metabolism quantification as a potential candidate for heterologous protein production, particularly for cellulase enzymes.
A Novel Statistical Test for Life Distribution Analysis: Assessing Exponentiality Against EBUCL Class with Applications in Sustainability and Reliability Data
Authors: Etman Walid B. H. , Bakr Mahmoud E. , Balogun Oluwafemi Samson , EL-Sagheer Rashad M.
Published: February 2025

A product’s lifespan may be ascertained by analyzing the dependability and aging class of its life distribution. Sustainability metrics are also crucial for assessing the impact on the environment and creating resource-saving strategies. Researchers extensively rely on statistical testing when making judgments; nonparametric tests are particularly useful, since they may be used for a broad variety of datasets and do not require knowledge of the data distribution. To provide effective assessments for well-informed decisions, this study introduces a novel life distribution class called “Exponential Better than Used in Increasing Convex in Laplace Transform Order (EBUCL)”. In this framework, a novel test statistic utilizing the moment inequalities method is introduced to evaluate exponentiality against the EBUCL class. By analyzing its asymptotic behavior, critical values are calculated for sample sizes between 5 and 100. Pitman’s asymptotic efficiency was taken into consideration by calculating the test’s power and comparing it with other tests through the use of simulation studies employing standard reliability distributions. In conclusion, this study addresses the treatment of right-censored data and applied the suggested test approach to real datasets across many domains. Our experimental results have practical implications for sustainability data assessments in engineering and the biological sciences.
Bayesian Hierarchical Modeling for Variance Estimation in Biopharmaceutical Processes
Authors: Schach Sonja , Eilert Tobias , Presser Beate , Kunzelmann Marco
Published: February 2025

Determining process variances in biopharmaceutical manufacturing is challenging due to limited data availability. To address this, we introduce a Bayesian hierarchical model designed for meta-analysis of process variance. This approach can improve process variance estimation by integrating data from multiple products, providing more reliable estimates of critical quality attributes in cases of data scarcity. Additionally, our model aids in evaluating process models, ensuring quality in process development. The paper demonstrates the new method using a simulation study, showcasing its potential to leverage historical data for both upstream and downstream phases of future CMC drug development. The new statistical model has great potential to expedite the market introduction of therapies while ensuring patient safety, allowing new treatments to reach patients more quickly without compromising quality or efficacy.
Energy Saving in Permanent Cardiac Pacing: Pulse Waveform and Charge Balancing Deserve Consideration
Authors: Di Gregorio Franco , Marcantoni Lina , Mozzi Aldo , Barbetta Alberto , Zanon Francesco
Published: February 2025

The pacing pulse produced by implantable stimulators can be described as a truncated exponential decay from the starting peak amplitude, corresponding to the discharge of the output stage capacitance (reservoir and isolation capacitors, in series) along the application time. Pulse decay and charge balancing have relevant implications on the ideal setting of a pacing device, as demonstrated by mathematical predictions based on well-acknowledged theoretical statements. Successful stimulation is achieved with minimum energy expense at a pulse duration shorter than the chronaxie time, which represents the upper border of the advisable duration interval. With any start amplitude, the stimulation safety margin can be improved by a duration increase beyond the chronaxie only up to an absolute limit (longest useful duration), which depends on the chronaxie and the pulse time-constant. At the longest useful duration, the threshold start amplitude is at the minimum and cannot decrease any further, though it and the corresponding pulse mean amplitude largely exceed the rheobase. The overall pacing performance is affected, in addition, by the load resistance and the electrode capacitance. Pulse amplitude decay limits the effectiveness of extended duration in implantable stimulators, making short pulses preferable whenever possible. Proper pulse settings based on actual waveform properties can prevent energy waste and reduce pacing consumption, thus prolonging the service life of the stimulator.
Proteome and Metabolome Alterations in Radish (Raphanus sativus L.) Seedlings Induced by Inoculation with Agrobacterium tumefaciens
Authors: Frolova Nadezhda , Gorbach Daria , Ihling Christian , Bilova Tatiana , Orlova Anastasia , Lukasheva Elena , Fedoseeva Ksenia , Dodueva Irina , Lutova Lyudmila A. , Frolov Andrej
Published: February 2025

Infection of higher plants with agrobacteria (Agrobacterium tumefaciens) represents one of the most comprehensively characterized examples of plant–microbial interactions. Incorporation of the bacterial transfer DNA (T-DNA) in the plant genome results in highly efficient expression of the bacterial auxin, cytokinin and opine biosynthesis genes, as well as the host genes of hormone-mediated signaling. These transcriptional events trigger enhanced proliferation of plant cells and formation of crown gall tumors. Because of this, infection of plant tissues with A. tumefaciens provides a convenient model to address the dynamics of cell metabolism accompanying plant development. To date, both early and late plant responses to agrobacterial infection are well-characterized at the level of the transcriptome, whereas only little information on the accompanying changes in plant metabolism is available. Therefore, here we employ an integrated proteomics and metabolomics approach to address the metabolic shifts and molecular events accompanying plant responses to inoculation with the A. tumefaciens culture. Based on the acquired proteomics dataset complemented with the results of the metabolite profiling experiment, we succeeded in characterizing the metabolic shifts associated with agrobacterial infection. The observed dynamics of the seedling proteome and metabolome clearly indicated rearrangement of the energy metabolism on the 10th day after inoculation (d.a.i.). Specifically, redirection of the energy metabolism from the oxidative to the anaerobic pathway was observed. This might be a part of the plant’s adaptation response to tumor-induced hypoxic stress, which most likely involved activation of sugar signaling.
G-Protein-Coupled Receptor (GPCR) Signaling and Pharmacology in Metabolism: Physiology, Mechanisms, and Therapeutic Potential
Authors: Cho Yun Yeong , Kim Soyeon , Kim Pankyung , Jo Min Jeong , Park Song-E , Choi Yiju , Jung Su Myung , Kang Hye Jin
Published: February 2025

G-protein coupled receptors (GPCRs), the largest family of integral membrane proteins, enable cells to sense and appropriately respond to the environment through mediating extracellular signaling to intercellular messenger molecules. GPCRs’ pairing with a diverse array of G protein subunits and related downstream secondary messengers, combined with their ligand versatility-from conventional peptide hormone to numerous bioactive metabolites, allow GPCRs to comprehensively regulate metabolism and physiology. Consequently, GPCRs have garnered significant attention for their therapeutic potential in metabolic diseases. This review focuses on six GPCRs, GPR40, GPR120, GLP-1R, and ß-adrenergic receptors (ADRB1, ADRB2, and ADRB3), with GLP-1R recognized as a prominent regulator of system-level metabolism, while the roles of GPR40, GPR120 and ß-adrenergic receptors in central carbon metabolism and energy homeostasis are increasingly appreciated. Here, we discuss their physiological functions in metabolism, the current pharmacological landscape, and the intricacies of their signaling pathways via G protein and ß-arrestin activation. Additionally, we discuss the limitations of existing GPCR-targeted strategies for treating metabolic diseases and offer insights into future perspectives for advancing GPCR pharmacology.
Short-Term In Vitro Exposure of Human Blood to 5G Network Frequencies: Do Sex and Frequency Additionally Affect Erythrocyte Morphometry?
Authors: Žura Nikolino , Vince Silvijo , Perić Porin , Vilić Marinko , Malarić Krešimir , Rimac Vladimira , Golubić Ćepulić Branka , Vajdić Marina , Jurak Ivan , Milinković Tur Suzana , Poljičak Milas Nina , Samardžija Marko , Nemir Jakob , Telebuh Mirjana , Žura Žaja Ivona
Published: February 2025

Background/Objectives: This study assessed the effects of 5G radiofrequency electromagnetic radiation (RF-EMR) at different frequencies (700 MHz, 2500 MHz, 3500 MHz) on the complete blood count (CBC), erythrocyte morphometry, and platelet activation after the short-term in vitro exposure of human blood. Methods: Blood samples from 30 healthy volunteers (15 men and 15 women, aged 25–40 years old) were collected at three intervals (14 days apart). For each collection, four tubes of blood were drawn per volunteer—two experimental and two controls. Experimental samples were exposed to 5G RF-EMR for 2 h at room temperature using a half-cone gigahertz transverse electromagnetic cell. The CBC was analysed via a haematology analyser, the erythrocyte morphometry was analysed using the SFORM program, and platelet activation was analysed via flow cytometry. Results: The CBC and platelet activation showed no significant differences between the experimental and control samples. However, the erythrocyte morphometry exhibited notable changes. At 700 MHz, the erythrocyte size, contour, and membrane roughness increased significantly for both sexes, with women’s cells showing greater sensitivity. At 2500 MHz, women exhibited an increased contour index and a decreased solidity and form factor. At 3500 MHz, women showed an increased contour index and outline but a decreased solidity, elongation, and form factor. Cluster analysis identified two erythrocyte subpopulations: smaller, rounder cells with smooth membranes and larger cells with rougher membranes. Conclusions: These results indicate that 5G RF-EMR exposure significantly alters erythrocyte morphometry. The strongest effects were observed at 700 MHz, where men exhibited greater membrane roughness, and women showed larger and rounder erythrocytes. These findings suggest that short-term in vitro 5G RF-EMR exposure disrupts the cytoskeleton, increasing membrane permeability and deformability.
Genetic Profiling of MC3T3-E1 Cells in Different Media: Implications for In Vitro Screening Development
Authors: Izumiya Makoto , Nobuoka Hidehiko , Endo Hono , Ueno Rintaro , Mimura Masaki , Saito Naoto , Haniu Hisao
Published: February 2025

Background/Objectives: The translation of in vitro biomaterial evaluations into successful clinical applications often fails due to discrepancies with in vivo results. Previously, we demonstrated that differences in culture medium conditions influence the bone formation process. This study aimed to investigate the influence of culture media on gene expression during calcification induction in osteoblasts. Methods: Using MC3T3-E1 cells cultured in α Minimum Essential Medium without L-ascorbic acid (αMEM(−)) and Dulbecco’s Modified Eagle Medium (DMEM), we screened gene expression profiles through microarray analysis and validated key findings with quantitative PCR. Additionally, we compared these gene expression patterns with those in primary osteoblasts (POBs) cultured under the same medium conditions. Results: The results revealed distinct gene expression profiles in MC3T3-E1 cells depending on the culture medium, while POBs exhibited minimal differences between media, except for the gene Alpl. In αMEM(−), Alpl expression in POBs was significantly increased approximately 4-fold via calcification stimulation (p < 0.0001). POBs cultured in DMEM showed calcification appearance differing from the αMEM(−) condition, even though no significant increase in Alpl expression via calcification stimulation was observed. Conclusions: Differences in media appear to remarkably impact osteoblast gene expression and mineralization. These findings may help improve biomaterial evaluation when transitioning from in vitro assessments to in vivo evaluations. Moreover, our results suggest the possibility that gene expression differences observed in MC3T3-E1 cells reflect the diverse bone formation processes in vivo. Focusing on these genes could facilitate the development of screening methods for bone formation, supporting future clinical applications in orthopedics.
Multi-Stress Loading Effect on Fatigue Response of Asphalt Binder Based on Dynamic Shear Rheometer Testing
Authors: Wang Guoqing , Ling Yiping , Du Qunle , Yu Huayang
Published: February 2025

Fatigue damage to asphalt pavements due to continuous loading occurs mainly at the binder–aggregate interface or within the asphalt binder. The mechanical response of asphalt binder under variable stress conditions was comprehensively analyzed by repeated loading tests. The viscoelastic intervals of three asphalt binders (Pen70–80, Pen60–70, and SBS) were determined by stress scanning tests, and two different sizes of stresses were selected for constant stress time scanning inside and outside of the intervals based on the experimental thresholds, to provide a reference for the selection of load combinations for variable stress fatigue tests. Cyclic loading of the samples using DSR focused on the complex shear modulus and phase angle behavior of asphalt binder samples under linear viscoelastic (LVE) and nonlinear viscoelastic (NLVE) stresses. The study reveals that under LVE and NLVE stresses, asphalt binders exhibit different mechanical behaviors, each indicating different aspects of damage accumulation and recovery capabilities. Under LVE stress, asphalt binders demonstrate an initial rapid decay of modulus, followed by a phase of slowed degradation and then a swift decline leading to fatigue failure. This pattern contrasts with the response under NLVE stress, where a more pronounced and quicker degradation is observed in both the initial and final phases, indicating significant initial damage. Analyzing the experimental results, at small stresses within the online viscoelastic interval, the modulus decay of asphalt specimens mainly occurs at the late loading stage, and the phase angle growth also occurs mainly at the late loading stage, while at large stresses, the asphalt specimens produce a large amount of modulus decay at the early loading stage. Furthermore, the study explores the NLVE-LVE loading mode, observing a rapid recovery phase in the early stages of the second phase. This phase is characterized by an increase in modulus accompanied by a decrease in phase angle, indicating an increase in the elasticity of the specimen. However, in the LVE-NLVE mode, a rapid accumulation of damage is observed without a similar recovery phase, highlighting the impact of NLVE stress on inducing irreversible damage. The findings suggest a complex interplay between the type of stress applied and the mechanical response of asphalt binders, with significant implications for understanding the fatigue and recovery behavior of asphalt materials under variable stress conditions. The aim is to investigate the mechanical response and damage evolution law of asphalt binder under repeated loading of variable stress to provide reference for material selection and development of durable pavements.
Real-World Evidence of Bevacizumab and Panitumumab Drug Resistance and Drug Ineffectiveness from EudraVigilance Database
Authors: Vonica Razvan Constantin , Morgovan Claudiu , Butuca Anca , Pumnea Manuela , Cipaian Remus Calin , Frum Adina , Dobrea Carmen Maximiliana , Vonica-Tincu Andreea Loredana , Pacnejer Aliteia-Maria , Batar Florina , Vornicu Vlad , Ghibu Steliana , Gligor Felicia Gabriela
Published: February 2025

Colorectal cancer (CRC) is the third most common cancer in the world, with an average 5-year overall survival (OS) rate of approximately 60% [...]
Risk Factors Predictive of Contralateral Recurrence of Upper Tract Urothelial Carcinoma Include Chronic Kidney Diseases and Postoperative Initiation of Dialysis
Authors: Wu Yi-Ru , Li Ching-Chia , Juan Yung-Shun , Li Wei-Ming , Wu Wen-Jeng , Chien Tsu-Ming
Published: February 2025

Background: The objective of the present study was to evaluate the impact of dialysis on patients with upper tract urothelial carcinoma (UTUC) who are undergoing surgical intervention, as well as to identify predictive factors linked to contralateral recurrence. Methods: A retrospective review was conducted on patients who underwent radical nephroureterectomy (RNU) for non-metastatic UTUC at our institution from 2000 to 2013. The contralateral recurrence rate was calculated using the Kaplan–Meier method, and multivariate logistic regression analysis was employed to examine the relationship between clinicopathological characteristics and contralateral recurrence. Results: A total of 593 patients were included in this analysis, of which 31 (5.8%) experienced metachronous recurrence on the contralateral side. Kaplan–Meier analysis indicated a statistically significant reduction in the contralateral recurrence-free survival rate among female patients (p = 0.040), those with a prior history of bladder cancer (p < 0.001), individuals presenting with multiple tumors (p = 0.011), patients with advanced chronic kidney disease (CKD) (p < 0.001), and those requiring postoperative dialysis (p < 0.001). In contrast, preoperative hemodialysis status did not show a significant correlation with contralateral recurrence (p = 0.08). The multivariate analysis identified a history of bladder cancer (hazard ratio (HR), 3.19; 95% confidence interval (CI), 1.2–8.4; p = 0.018), the necessity for new hemodialysis postoperatively (HR, 5.34; 95% CI, 1.3-25.6; p = 0.034), and advanced CKD (HR, 2.52; 95% CI, 1.4–4.9; p = 0.021) as independent risk factors associated with an increased rate of contralateral recurrence. Conclusions: In conclusion, advanced CKD, a history of bladder cancer, and the initiation of new dialysis following surgery were identified as independent prognostic indicators for contralateral recurrence in patients with initial unilateral UTUC undergoing RNU. It is recommended that patients exhibiting these three adverse characteristics undergo rigorous monitoring of the contralateral upper urinary tract throughout the follow-up period.
Surgery Versus Stereotactic Radiotherapy in Patients over 75 Years Treated for Stage IA–IIA NSCLC
Authors: Oliver Galdric , Boucekine Mohamed , Couderc Anne-Laure , Fourdrain Alex , Zaccariotto Audrey , Pougnet Isabelle , Kaeppelin Bertrand , Thomas Pascal Alexandre , Padovani Laetitia
Published: February 2025

Introduction: Lobectomy with lymph node dissection is the gold standard treatment for stage IA–IIA Non-Small Cell Lung Cancer (NSCLC). Surgery is responsible for higher early mortality but offers better overall long-term survival. The patient population concerned is often elderly and combines the comorbidities of smoking and age. Several trials have shown good results of stereotactic radiotherapy (SABR) in terms of local control and tolerance in elderly subjects. Our objective is to study the survival and regional control of patients over 75 years treated by surgery or SABR for localized NSCLC. Materials and Method: We conducted a single-center retrospective study between January 2012 and December 2022 including elderly patients who received surgery or SABR for NSCLC less than 5 cm in size, N0, M0. A cumulative comorbidity index was calculated for each patient, considering severity and impact of treatment. We performed subgroup analyses using CART method to identify factors impacting survival and early death. Results: After propensity score matching, 127 operated patients were matched to 85 patients treated with SABR. Overall survival at 1 and 5 years for the operated patients was 83.87% and 47.30% compared with 88.8% and 31.5% in the radiotherapy group (p = 0.068). We have identified four factors influencing the incidence of early mortality: gender, World Health Organization Performance status (WHO status), Forced Expiratory Volume in 1 s (FEV1), and treatment group. Conclusions: Surgery seems to remain the standard of treatment in terms of overall survival and locoregional recurrence, in a context where SABR nevertheless provides excellent local control and tolerance in the short and long term. In order to improve patient selection, we are proposing for the first time a tool to aid therapeutic decision-making.
Targeting Spinal Interneurons for Respiratory Recovery After Spinal Cord Injury
Authors: Paracha Maha , Brezinski Allison N. , Singh Rhea , Sinson Elizabeth , Satkunendrarajah Kajana
Published: February 2025

Spinal interneurons (SpINs) are pivotal to the function of neural circuits, orchestrating motor, sensory, and autonomic functions in the healthy, intact central nervous system. These interneurons (INs) are heterogeneous, with diverse types contributing to various neural systems, including those that control respiratory function. Research in the last few decades has highlighted the complex involvement of SpINs in modulating motor control. SpINs also partake in motor plasticity by aiding in adapting and rewiring neural circuits in response to injury or disease. This plasticity is crucial in the context of spinal cord injury (SCI), where damage often leads to severe and long-term breathing deficits. Such deficits are a leading cause of morbidity and mortality in individuals with SCI, emphasizing the need for effective interventions. This review will focus on SpIN circuits involved in the modulation of breathing and explore current and emerging approaches that leverage SpINs as therapeutic targets to promote respiratory recovery following SCI.
Angiotensin-(1-7) Provides Potent Long-Term Neurorepair/Neuroregeneration in a Rodent White Matter Stroke Model: Nonarteritic Ischemic Optic Neuropathy (rNAION)
Authors: Woo Kwang Min , Guo Yan , Mehrabian Zara , Walther Thomas , Miller Neil R. , Bernstein Steven L.
Published: February 2025

Nonarteritic anterior ischemic optic neuropathy (NAION) is an ischemic lesion of the anterior optic nerve (ON), currently untreatable due to the length of time from symptom onset until treatment. We evaluated angiotensin-(1-7) (Ang-(1-7)): the MAS1-receptor ligand, as a possible NAION treatment using the rodent NAION model (rNAION). Long-Evans rats were unilaterally rNAION-induced. One-day post-induction, lesion severity was quantified via optic nerve head (ONH) edema using spectral domain optical coherence tomography. Animals meeting rNAION induction criteria were randomized into (1) Subcutaneous Ang-(1-7) infusion for 28 days and (2) Vehicle. Visual function was assessed using both visual acuity and flash visual evoked potentials (fVEP). Tissues were collected >30d and RGC neurons were quantified by stereology. ONs were histologically examined for inflammation. Ang-(1-7) improved post-rNAION visual function. Ang-(1-7)-treated animals showed improved visual acuity (ANCOVA: p = 0.0084) and improved fVEP amplitudes (ANCOVA: p = 0.0378) vs vehicle controls. The relative degree of improvement correlated with ONH edema severity. Treated animals showed trends towards increased RGC survival, and reduced optic nerve inflammatory cell infiltration. Ang-(1-7) is the first agent effective ≥1 day after rNAION induction. Ang-(1-7) type agonists may be useful in improving long-term function and neuronal survival in clinical NAION and other forms of white matter ischemia.
Differential Regulation of Nav1.1 and SCN1A Disease Mutant Sodium Current Properties by Fibroblast Growth Factor Homologous Factors
Authors: Frazee Ashley , Zybura Agnes , Cummins Theodore R.
Published: February 2025

Fibroblast growth factor homologous factors (FHFs) regulate the activity of several different voltage-gated sodium channels (Navs). However, more work is needed to determine how specific FHF isoforms and variants affect the properties of different Nav isoforms. In addition, it is not known if FHFs can differentially modulate the properties of Nav variants associated with disease. Here, we investigated the effects of FHF2A and FHF2B on Nav1.1 properties as well as on a familial hemiplegic migraine 3 (FHM3) causing mutation in this channel, F1774S. We found that FHF2A, but not 2B, induced prominent long-term inactivation (LTI) in the wild-type (WT) Nav1.1. Interestingly, FHF2A induced LTI in the F1774S FHM3 mutant channel to a greater extent than in the WT. Furthermore, persistent currents caused by the F1774S mutation were attenuated by the co-expression of FHF2A, leading to a possible rescue of the mutant channel phenotype. By contrast, the P1894L mutation, which is associated with epilepsy and mild intellectual disability, greatly attenuated the LTI induced by FHF2A. Overall, our data show for the first time that FHF2A might be a significant modulator of Nav1.1 that can differentially modulate the impact of Nav1.1 disease-associated mutations.
Sorbent-Based Microextraction Combined with GC-MS: A Valuable Tool in Bioanalysis
Authors: Ntorkou Marianna , Zacharis Constantinos K.
Published: February 2025

Sample preparation is broadly recognized as the most critical, time-consuming, and error-prone step of a bioanalytical workflow. Over the years, the development of pretreatment methods aimed at the isolation and preconcentration of the target analytes from sample matrices has been an ongoing effort. Recent innovations have aimed at miniaturizing sample preparation to streamline laboratory processes and enhance analytical performance. Sorbent-based microextraction techniques, including solid-phase microextraction, microextraction by packed sorbent, bar adsorptive microextraction, capsule phase microextraction, etc., have recently gained attention as effective sample preparation tools prior to gas chromatography-mass spectrometric analysis. This article provides an overview of the bioanalytical GC-MS applications of sorbent-based techniques published in the last decade (2014–2024) that enable the efficient and sensitive determination of various compounds in biological samples.
On Modeling X-Ray Diffraction Intensity Using Heavy-Tailed Probability Distributions: A Comparative Study
Authors: Alam Farouq Mohammad A.
Published: February 2025

Crystallography, a cornerstone of materials science, provides critical insights into material structures through techniques such as X-ray diffraction (XRD). Among the metrics derived from XRD, intensity serves as a key parameter, reflecting the electron density distribution and offering information about atomic arrangements and sample quality. Due to its inherent variability and susceptibility to extreme values, intensity is best modeled using heavy-tailed, location-scale probability distributions. This paper investigates the model parameter estimation problem for three such distributions—log-Cauchy, half-Cauchy, and Cauchy Birnbaum–Saunders—using several methods, including maximum likelihood and the maximum product of spacings estimation methods. Monte Carlo simulations are conducted to assess the performance of these methods across various scenarios. Additionally, two real XRD intensity datasets are analyzed to compare the applicability and effectiveness of the proposed models. The results demonstrate the potential of heavy-tailed distributions for modeling XRD intensity data, providing a robust framework for future research and practical applications in material characterization.
RTMS: A Smart Contract Vulnerability Detection Method Based on Feature Fusion and Vulnerability Correlations
Authors: Gao Gaimei , Li Zilu , Jin Lizhong , Liu Chunxia , Li Junji , Meng Xiangqi
Published: February 2025

Smart contracts are at the core of blockchain technology, but the cost of fixing their security vulnerabilities is high, making pre-deployment vulnerability detection crucial. Existing methods rely on fixed rules, which have limitations in accuracy and scalability, and their efficiency decreases with the complexity of the rules. Neural-network-based methods can identify some vulnerabilities but are inefficient in multi-vulnerability scenarios and depend on source code. To address these issues, we propose a multi-vulnerability-based smart contract detection method called RTMS. RTMS takes bytecode as input, disassembles it into opcodes, uses the gas consumed by the contract for data slicing, and extends the length of input opcodes through a layered structure. It employs a weighted binary cross-entropy (BCE) function to handle data imbalance and combines channel-sequence attention mechanisms to extract vulnerability correlation features. By using transfer learning, it reduces training parameters and computational costs. Our RTMS model can detect multiple vulnerabilities simultaneously, enhancing detection accuracy and efficiency. In experiments with 100,000 real contract samples, the model achieved a Jaccard coefficient of 0.9312, a Hamming loss of 0.0211, and an F1 score that improved by about 11 percentage points compared to existing models, demonstrating its superiority and stability.
Federated Learning and Neural Circuit Policies: A Novel Framework for Anomaly Detection in Energy-Intensive Machinery
Authors: Palma Giulia , Geraci Giovanni , Rizzo Antonio
Published: February 2025

In the realm of predictive maintenance for energy-intensive machinery, effective anomaly detection is crucial for minimizing downtime and optimizing operational efficiency. This paper introduces a novel approach that integrates federated learning (FL) with Neural Circuit Policies (NCPs) to enhance anomaly detection in compressors utilized in leather tanning operations. Unlike traditional Long Short-Term Memory (LSTM) networks, which rely heavily on historical data patterns and often struggle with generalization, NCPs incorporate physical constraints and system dynamics, resulting in superior performance. Our comparative analysis reveals that NCPs significantly outperform LSTMs in accuracy and interpretability within a federated learning framework. This innovative combination not only addresses pressing data privacy concerns but also facilitates collaborative learning across decentralized data sources. By showcasing the effectiveness of FL and NCPs, this research paves the way for advanced predictive maintenance strategies that prioritize both performance and data integrity in energy-intensive industries.
Current Status and Reflections on Ocean CO2 Sequestration: A Review
Authors: Zhang Shanling , Jiang Sheng , Li Hongda , Li Peiran , Zhong Xiuping , Chen Chen , Tu Guigang , Liu Xiang , Xu Zhenhua
Published: February 2025

Climate change has become one of the most pressing global challenges, with greenhouse gas emissions, particularly carbon dioxide (CO2), being the primary drivers of global warming. To effectively address climate change, reducing carbon emissions has become an urgent task for countries worldwide. Carbon capture, utilization, and storage (CCUS) technologies are regarded as crucial measures to combat climate change, among which ocean CO2 sequestration has emerged as a promising approach. Recent reports from the International Energy Agency (IEA) indicate that by 2060, CCUS technologies could contribute up to 14% of global cumulative carbon reductions, highlighting their significant potential in mitigating climate change. This review discusses the main technological pathways for ocean CO2 sequestration, including oceanic water column sequestration, CO2 oil and gas/coal seam geological sequestration, saline aquifer sequestration, and seabed methane hydrate sequestration. The current research status and challenges of these technologies are reviewed, with a particular focus on the potential of seabed methane hydrate sequestration, which offers a storage density of approximately 0.5 to 1.0 Gt per cubic kilometer of hydrate. This article delves into the formation mechanisms, stability conditions, and storage advantages of CO2 hydrates. CO2 sequestration via hydrates not only offers high storage density but also ensures long-term stability in the low-temperature, high-pressure conditions of the seabed, minimizing leakage risks. This makes it one of the most promising ocean CO2 sequestration technologies. This paper also analyzes the difficulties faced by ocean CO2 sequestration technologies, such as the kinetic limitations of hydrate formation and leakage monitoring during the sequestration process. Finally, this paper looks ahead to the future development of ocean CO2 sequestration technologies, providing theoretical support and practical guidance for optimizing their application and promoting a low-carbon economy.
An Evaluation of Biogas Potential of Cassava, Yam and Plantain Peel Mixtures Using Theoretical Models and Hohenheim Biogas Yield Test-Based Experiments
Authors: Kusi Joseph Yankyera , Empl Florian , Müller Ralf , Pelz Stefan , Poetsch Jens , Sailer Gregor , Kirchhof Rainer , Derkyi Nana Sarfo Agyemang , Attiogbe Francis
Published: February 2025

This research aimed to evaluate the comparative biogas yields of waste (peels) of selected fibrous materials from the West African region: cassava, plantain, a mixture of cassava, plantain and yam. Three models: The Boyle model, the Modified Boyle’s model, and the Buswell and Müller’s model were used to determine the theoretical maximum biomethane potentials (TMBP), while the Hohenheim Biogas Yield test (D-HBT) was used to undertake a batch test of anaerobic digestion. The samples were co-digested with digested sewage sludge (DSS) for 39 days, with an operating temperature of 37 ± 0.5 °C. The study draws comparisons between the TBMPs and the experimental results, the experimental results of the different substrates, and the experimental results and figures reported in the literature. From the experimental results, plantain peels had the highest biogas yield (468 ± 72 mL/g oTS), followed by a mixture of yam, cassava and plantain peels (362 ± 31 mL/g oTS) and cassava peels obtained the least biogas yield (218 ± 19 mL/g oTS). TMBPS of 204.04, 209.03 and 217.45 CH4 mL/g oTS were obtained for plantain peels, a mixture of yam, cassava and plantain peels and cassava peels, respectively, evaluated using Boyle’s model. For all the samples, the TMBPS (205.56, 209.03 and 218.45 CH4 mL/g oTS, respectively) obtained using the Buswell and Mueller model were slightly higher than those obtained by both the Boyle and the modified Boyle’s model (163.23, 167.22 and 174.76 CH4 mL/g oTS, respectively). While the study result is sufficient to imply that generating biogas from fibrous waste materials in its mixture form is a valuable approach, it is not sufficient to conclude that the use of these waste materials in its naturally occurring mixture form has a technical added advantage in co-digestion over their individual potential. However, future studies could explore this possibility with different fractions of the mixture with a view to optimising generation. The study finds that theoretically modelling the biogas potential of fibrous materials is a good method for biogas evaluation despite having overestimation tendencies, as this challenge could be corrected by applying factors that result in these tendencies, biodegradability indices. The data can, therefore, find use in fibrous waste treatment and waste-to-energy technologies, especially in Africa. This application will not be negatively affected by whether single water streams are used or their mixture.
Study on the Wake Characteristics of the Loess Plateau Terrain Based on Wind Tunnel Experiment
Authors: Ma Yulong , Li Shoutu , Li Deshun , Gao Zhiteng , Guo Xingduo , Ma Qingdong
Published: February 2025

The northwest region of China’s loess plateau is an important area for wind power development. However, the unclear understanding of the evolution mechanism of the near-ground atmospheric boundary layer (ABL), which is influenced by its unique geomorphological features, has compromised the safety and stability of wind turbine operations. To address this challenge, wind tunnel experiments were conducted to investigate the mean and turbulent characteristics of wake flow generated by mountains in the loess plateau. The results indicate that the terrain significantly affects both the average velocity deficit and turbulence intensity distribution within the wake. Specifically, topographic features dominate turbulent energy transfer and modulate coherent structures in the inertial subrange. Additionally, the scale of these features enhances turbulence energy input at corresponding scales in the fluctuating wind speed spectrum, leading to a non-decaying energy interval within the inertial subregion.
Seasonal Dynamics and Microenvironmental Drivers of Transpiration in Scrub Rhizophora mangle L. Trees from Yucatan
Authors: Cerón-Aguilera Gabriela , Yáñez-Espinosa Laura , Echevarría-Machado Ileana , Méndez-Alonzo Rodrigo , Herrera-Silveira Jorge , Us-Santamaría Roberth , Salas-Rabaza Julio Alberto , González-Muñoz Karina Elizabeth , Andrade José Luis
Published: February 2025

Scrub mangrove forests, dominated by Rhizophora mangle L., are characterized by high porewater salinity, which might compromise individual sap flow rates (SF) due to seasonal and diurnal microenvironmental variations. We tested the functional, anatomical, and SF responses of 12 individuals to microenvironmental variables such as solar radiation, photosynthetic photon flux, wind speed, evaporative demand, and porewater salinity, measured using an in situ weather station. Measurements were made in the dry and rainy seasons in the Yucatan Peninsula, using Granier heat dissipation sensors, installed on tree branches. During the rainy season, SF was twice as high as that during the dry season (0.22 ± 0.00 L h−1 and 0.11 ± 0.00 L h−1, respectively), despite lower evaporative demand. In both seasons, negative relationships between SF with vapor pressure deficit (VPD; dry τ = −0.54; rainy τ = −0.56) and with photosynthetic photon flux (PPF; dry τ = −0.97; rainy τ = −0.98) were found, indicating a strong hydraulic coupling to atmospheric conditions. Sap flow and transpiration rates of this R. mangle scrub mangrove forest exceeded those of some tropical dry deciduous forests, suggesting adaptations that support water transport in saline environments. The clustered xylem vessels of R. mangle ensure safe sap flow year-round. As an evergreen species, it contributes water to the atmosphere all year-round, underscoring its critical role in the tropical ecohydrological environment.
A Multi-Input Residual Network for Non-Destructive Prediction of Wood Mechanical Properties
Authors: Ma Jingchao , Kuang Zhufang , Fang Yixuan , Huang Jiahui
Published: February 2025

Modulus of elasticity (MOE) and modulus of rupture (MOR) are crucial indicators for assessing the application value of wood. However, traditional physical testing methods for the mechanical properties of wood are typically destructive, costly, and time-consuming. To efficiently assess these properties, this study proposes a multi-input residual network (MIRN) model, which integrates microscopic images of wood with physical density data and leverages deep learning technology for rapid and accurate predictions. By using larger convolution kernels to enhance the receptive field, the model captures fine microstructural features in the images. Batch normalization layers were removed from the ResNet architecture to reduce the number of parameters and improve training stability. Shortcut connections were utilized to enable deeper network architectures and address the vanishing gradient problem. Two types of residual blocks, convolutional block and identity block, were defined based on input dimensional changes. The MIRN method, based on multi-input residual networks, is proposed for non-destructive testing of wood mechanical properties. The experimental results show that MIRN outperforms convolutional neural networks (CNNs) and ResNet-50 in predicting MOE and MOR, with an R2 of 0.95 for MOE and RMSE reduced to 46.88, as well as an R2 of 0.85 for MOR and an RMSE of 0.44. Thus, this method offers an efficient and cost-effective tool for wood processing and quality control.