bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Compressed JPEG and JPEG2000 Medical Images in Deep Learning: A Review
Authors: Urbaniak Ilona Anna
Published: November 2024

Machine Learning (ML), particularly Deep Learning (DL), has become increasingly integral to medical imaging, significantly enhancing diagnostic processes and treatment planning. By leveraging extensive datasets and advanced algorithms, ML models can analyze medical images with exceptional precision. However, their effectiveness depends on large datasets, which require extended training times for accurate predictions. With the rapid increase in data volume due to advancements in medical imaging technology, managing the data has become increasingly challenging. Consequently, irreversible compression of medical images has become essential for efficiently handling the substantial volume of data. Extensive research has established recommended compression ratios tailored to specific anatomies and imaging modalities, and these guidelines have been widely endorsed by government bodies and professional organizations globally. This work investigates the effects of irreversible compression on DL models by reviewing the relevant literature. It is crucial to understand how DL models respond to image compression degradations, particularly those introduced by JPEG and JPEG2000—both of which are the only permissible irreversible compression techniques in the most commonly used medical image format—the Digital Imaging and Communications in Medicine (DICOM) standard. This study provides insights into how DL models react to such degradations, focusing on the loss of high-frequency content and its implications for diagnostic interpretation. The findings suggest that while existing studies offer valuable insights, future research should systematically explore varying compression levels based on modality and anatomy, and consider developing strategies for integrating compressed images into DL model training for medical image analysis.
Experimental Study on Interlayer Interference Characteristics During Commingled Production in a Multilayer Tight Sandstone Gas Reservoir
Authors: Lu Yang , He Wenlin , Wang Jingjian , Liu Jiaojiao , Shi Hongguang , Yang Daoyong
Published: November 2024

In this study, a practical and comprehensive experimental technique has been proposed to investigate the interlayer interference characteristics in multilayer tight sandstone gas reservoirs with multi-pressure systems and different reserves. Firstly, single-layer depletion simulation experiments were conducted to measure the gas flow rate and gas extraction efficiency for each of the six layers. A series of physical simulation experiments were then conducted to monitor gas production and pressure variations in commingled multilayer production scenarios under various conditions. Finally, interlayer interference characteristics and gas extraction efficiencies and the main controlling factors were evaluated, analyzed, and identified. The interlayer pressure differential is found to be the primary factor dictating both interference and gas production, followed by initial gas production rates, and permeability variations in the order of positive significance. A higher interlayer pressure differential, a lower initial gas production rate, and a larger permeability variation result in an increase in interlayer interference and a reduction in gas production during commingled production. Increasing the number of commingled layers leads to an overall increase in gas production losses of 10.95% for two layers to 13.35% for four layers. Layers exhibiting small interlayer pressure difference are positively compatible for commingled production.
The Influence of the Key Characteristics of Overburden Rock Structure on the Development Height of Water-Conducting Fracture in Yushenfu Coal Mine Area, China
Authors: Song Shijie , Ruan Hao , Wei Jiangbo , Niu Ruilin , Cheng Xing , Chen Baodeng
Published: November 2024

The destruction of shallow aquifers by water-conducting fractures of overlying strata caused by underground coal mining is the most representative form of mining-induced damage in the Yushenfu mining area. It has become an important factor restricting the green mining of coal in the Yushenfu mining area and even the ecological protection and high-quality development of the middle reaches of the Yellow River. As the key scientific problem of water-preserved coal mining, the scientific understanding of the development law and main influencing factors of water-conducting fractures in overlying strata has attracted great attention. Taking the geological occurrence characteristics of the main coal seam in Yushenfu mining area as the prototype, 24 different types of numerical models are constructed with the key characteristics of the overburden structure, such as the number of layers of sandstone in the overburden (sand layer coefficient) and the thickness ratio of sandstone and mudstone in the overburden (sand–mud ratio), as the main variables. By means of numerical simulation experiment and theoretical calculation, combined with field measurement and comparison, the influence of the key characteristics of overburden structure on the development height of water-conducting fracture is studied and revealed. It is proposed that the effective area for the study area to achieve water-preserved coal mining by using the height-limited mining method must conform to the coal seam overburden structure characteristics of “sand–mud ratio 6:4 and sand layer coefficient less than 70%” and “sand–mud ratio 8:2 and sand layer coefficient less than 80%”. The results not only enrich and deepen the research on the influence of geological factors and the law of controlling the development of water-flowing fractures in overlying strata, but also provide theoretical support for the precise protection of groundwater resources in the Yushenfu mining area in the middle reaches of the Yellow River.
Exploring External Peak Demands: The Influence of Contextual Factors on Male Basketball Players
Authors: Antoranz Yoel , Alonso-Pérez-Chao Enrique , Tejero-González Carlos M. , Salazar Hugo , del Campo-Vecino Juan del , Jiménez-Sáiz Sergio L.
Published: November 2024

Understanding the external load, particularly the peak demands (PDs), experienced by players is essential. Several factors, such as the playing time, team venue, score outcome, and match nature, can influence basketball performance. Accelerometry-based methods allow for the estimation of the load borne by athletes and the peaks they reach. The aim of this study was to analyze the influence of these factors on PDs across different time windows (30 s, 1 min, and 3 min). Eleven national-level athletes were monitored during 29 matches using measurement devices. Inertial movement units were used to measure peak PlayerLoad™ (PL) across any time window. Mixed linear models were used to compare the groups, and effect size was calculated to quantify the differences. Significant differences (p < 0.05, small effects) were found between occasional players (who play fewer minutes) and core players (who play intermediate minutes), with the latter reaching higher PDs, though with small effect sizes. Core players also reached higher PDs than top players (who play the most minutes), but the differences were not significant (p > 0.05, trivial effects). In summary, core players reach higher external PDs during competition compared to occasional players, while other contextual factors did not show a significant influence on external PDs.
Residual Stress Homogenization of Hybrid Implants
Authors: Sanjuán Álvarez Marta , Robles Daniel , Mur Javier Gil , Fernández-Hernández Saray , Pérez-Pevida Esteban , Brizuela-Velasco Aritza
Published: November 2024

Objectives: Hybrid implants commonly exhibit decreased corrosion resistance and fatigue due to differences in compressive residual stresses between the smooth and rough surfaces. The main objective of this study was to investigate the influence of an annealing heat treatment to reduce the residual stresses in hybrid implants. Methodology: Commercially pure titanium (CpTi) bars were heat-treated at 800 °C and different annealing times. Optical microscopy was used to analyze the resulting grain growth kinetics. Diffractometry was used to measure residual stress after heat treatment, corrosion resistance by open circuit potential (EOCP), corrosion potentials (ECORR), and corrosion currents (ICORR) of heat-treated samples, as well as fatigue behavior by creep testing. The von Mises distribution and the resulting microstrains in heat-treated hybrid implants and in cortical and trabecular bone were assessed by finite element analysis. The results of treated hybrid implants were compared to those of untreated hybrid implants and hybrid implants with a rough surface (shot-blasted). Results: The proposed heat treatment (800 °C for 30 min, followed by quenching in water at 20 °C) could successfully homogenize the residual stress difference between the two surfaces of the hybrid implant (−20.2 MPa). It provides better fatigue behavior and corrosion resistance (p ˂ 0.05, ANOVA). Stress distribution was significantly improved in the trabecular bone. Heat-treated hybrid implants performed worse than implants with a rough surface. Clinical significance: Annealing heat treatment can be used to improve the mechanical properties and corrosion resistance of hybrid surface implants by homogenizing residual stresses.
Leveraging Walnut Somatic Embryos as a Biomanufacturing Platform for Recombinant Proteins and Metabolites
Authors: Zaini Paulo A. , Haddad Katherine R. , Feinberg Noah G. , Ophir Yakir , Nandi Somen , McDonald Karen A. , Dandekar Abhaya M.
Published: November 2024

Biomanufacturing enables novel sources of compounds with constant demand, such as food coloring and preservatives, as well as new compounds with peak demand, such as diagnostics and vaccines. The COVID-19 pandemic has highlighted the need for alternative sources of research materials, thrusting research on diversification of biomanufacturing platforms. Here, we show initial results exploring the walnut somatic embryogenic system expressing the recombinant receptor binding domain (RBD) and ectodomain of the spike protein (Spike) from the SARS-CoV-2 virus. Stably transformed walnut embryo lines were selected and propagated in vitro. Both recombinant proteins were detected at 3–14 µg/g dry weight of tissue culture material. Although higher yields of recombinant protein have been obtained using more conventional biomanufacturing platforms, we also report on the production of the red pigment betanin in somatic embryos, reaching yields of 650 mg/g, even higher than red beet Beta vulgaris. This first iteration shows the potential of biomanufacturing using somatic walnut embryos that can now be further optimized for different applications sourcing specialized proteins and metabolites.
Extreme Precipitation Events During the Wet Season of the South America Monsoon: A Historical Analysis over Three Major Brazilian Watersheds
Authors: Freitas Aline Araújo de , Carvalho Vanessa Silveira Barreto , Reboita Michelle Simões
Published: November 2024

Most of South America, particularly the region between the southern Amazon and southeastern Brazil, as well as a large part of the La Plata Basin, has its climate regulated by the South American Monsoon System. Extreme weather and climate events in these areas have significant socioeconomic impacts. The Madeira, São Francisco, and Paraná river basins, three major watersheds in Brazil, are especially vulnerable to wet and drought periods due to their importance as freshwater ecosystems and sources of water for consumption, energy generation, and agriculture. The scarcity of surface meteorological stations in these basins makes meteorological studies challenging, often using reanalysis and satellite data. This study aims to identify extreme weather (wet) and climate (wet and drought) events during the extended wet season (October to March) from 1980 to 2022 and evaluate the performance of two gridded datasets (CPC and ERA5) to determine which best captures the observed patterns in the Madeira, São Francisco, and Paraná river basins. Wet weather events were identified using the 95th percentile, and wet and drought periods were identified using the Standardized Precipitation Index (SPI) on a 6-month scale. In general, CPC data showed slightly superior performance compared to ERA5 in reproducing statistical measures. For extreme day precipitation, both datasets captured the time series pattern, but CPC better reproduced extreme values and trends. The results also indicate a decrease in wet periods and an increase in drought events. Both datasets performed well, showing they can be used in the absence of station data.
Implantable Medical Device Security
Authors: Catuogno Luigi , Galdi Clemente
Published: November 2024

Implantable medical devices, or IMDs for short, are medical instruments that are placed into the human body through surgery. IMDs are typically used for treating chronic diseases. Currently available IMDs are capable of communicating using wireless channels with other devices, either in close proximity or even connected to the Internet, making IMDs part of the Internet of Medical Things. This capability opens the possibility of developing a wide range of services, like remote patient data control, localization in case of emergency, or telemedicine, which can improve patients’ lifestyle. On the other hand, given the limited resources of such tiny devices, and the access to the Internet, there are numerous security issues to be considered when designing and deploying IMDs and their support infrastructures. In this paper, we highlight security problems related to Internet-connected IMDs, and survey some solutions that have been presented in the literature.
Total Antioxidant Status in Critically Ill Patients with Traumatic Brain Injury and Secondary Organ Failure—A Systematic Review
Authors: Rynkiewicz-Szczepanska Ewa , Kosciuczuk Urszula , Maciejczyk Mateusz
Published: November 2024

Introduction: The available literature indicates that oxidant–antioxidant imbalance plays a significant role in the pathophysiology of traumatic brain injury and the subsequent secondary organ dysfunctions. However, there is a lack of studies summarizing the knowledge in this area, and no clear guidelines exist regarding the use of biomarkers of oxidative stress as diagnostics tools. Methods: The present work aims to provide a systematic review of the literature on the use of total antioxidant capacity (TAC) assays in predicting the outcomes of traumatic brain injury (TBI). A literature search was conducted up to 1 September 2024, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, using the PubMed and Scopus databases. Based on the inclusion criteria, 24 studies were used for the final review. Results: Promising data indicate that TAC assays are useful in predicting 30-day mortality and neurological outcomes. Moreover, they correlate with radiological findings on CT scans in brain injury and the clinical classifications of injuries, as well as the parameters of organ failure. Conclusions: Total antioxidant capacity assays can be used to assess the extent of brain damage and prognosticate general vital functions. Future experiments should include long-term randomized clinical trials on larger populations of TBI patients.
Comparison of Luting Cement Solubility: A Narrative Review
Authors: Kim Deok Yong , Aryan Nona , Lawson Nathaniel C. , Cheon Kyounga
Published: November 2024

Background: Dental restoration success relies on the physical properties of luting cements. Luting cements fill the space between teeth and the restoration, provide retention and protection from occlusal forces, and act as a barrier to microleakages in the oral environment. Objective: This review aims to evaluate and compare the solubility of the three most used dental luting cements: glass ionomer (GI), resin-modified glass ionomer (RMGI), and resin cement (RC). Methods: The studies selected for review compared the solubilities of combinations of GI, RMGI, and RC in solutions with different pH levels to replicate acidic oral pH. Results: A review of the studies concluded that resin cement had the overall lowest degree of solubility at all pH values and all storage periods, followed by RMGI and GI cement. Conclusions: The success of the restoration is dependent upon the choice of luting cement. The results of the studies reviewed show that all dental luting cements showed some degree of dissolution. Resin cement overall demonstrated the least amount of solubility, followed by RMGI and GI cement.
Quantum Control Design by Lyapunov Trajectory Tracking and Optimal Control
Authors: Yang Hongli , Yu Guohui , Ivanov Ivan Ganchev
Published: November 2024

In this paper, we investigate a Lyapunov trajectory tracking design method that incorporates a Schrödinger equation with a dipole subterm and polarizability. Our findings suggest that the proposed control law can overcome the limitations of certain existing control laws that do not converge. By integrating a quadratic performance index, we introduce an optimal control law, which we subsequently analyze for stability and optimality. We also simulate the spin-1/2 particle system to illustrate our results. These findings are further validated through numerical illustrations involving a 3D, 5D system, and a spin-1/2 particle system.
Machine Learning Supporting Virtual Reality and Brain–Computer Interface to Assess Work–Life Balance Conditions for Employees
Authors: Mikołajewski Dariusz , Piszcz Adrianna , Rojek Izabela , Galas Krzysztof
Published: November 2024

The widespread adoption of the Industry 5.0 paradigm puts people and their applications at the center of attention and, with the increasing automation and robotization of work, the need for workers to acquire new, more advanced skills increases. The development of artificial intelligence (AI) means that expectations for workers are further raised. This leads to the need for multiple career changes from life and throughout life. Belonging to a previous generation of workers makes this retraining even more difficult. The authors propose the use of machine learning (ML), virtual reality (VR) and brain–computer interface (BCI) to assess the conditions of work–life balance for employees. They use machine learning for prediction, identifying users based on their subjective experience of work–life balance. This tool supports intelligent systems in optimizing comfort and quality of work. The potential effects could lead to the development of commercial industrial systems that could prevent work–life imbalance in smart factories for Industry 5.0, bringing direct economic benefits and, as a preventive medicine system, indirectly improving access to healthcare for those most in need, while improving quality of life. The novelty is the use of a hybrid solution combining traditional tests with automated tests using VR and BCI. This is a significant contribution to the health-promoting technologies of Industry 5.0.
Position–Force Control of a Lower-Limb Rehabilitation Robot Using a Force Feed-Forward and Compensative Gravity Proportional Derivative Method
Authors: Gam Le T. H. , Quan Dam Hai , Ngoc Pham Van Bach , Quan Bui Hong , Thanh Bui Trung
Published: November 2024

The design and control of lower-limb rehabilitation robots for patients after a stroke has gained significant attention. This paper presents the dynamic analysis and control of a 3-degrees-of-freedom lower-limb rehabilitation robot using combined position–force control based on the force feed-forward and compensative gravity proportional derivative methods. In the lower-limb rehabilitation robot, the interaction force between the patient with the joints and links of the robot is uncertain and nonlinear due to the disturbance effect of Coriolis force, centrifugal force, gravitational force, and friction force. During recovery stages, the forces exerted by the patient’s lower limbs are also considered disturbances. Therefore, to meet the quality requirements in using the rehabilitation robot with different recovery stages of patient training, combining position control and force control is essential. In this paper, we proposed a combination of proportional–derivative gravity compensation motion control and force feed-forward control to form an advanced combined controller (position–force feed-forward control—PFFC) for a 3 DOF lower-limb functional rehabilitation robot. The forces can be sensed using a 3-axis force sensor. In addition, the robot’s position parameters are also measured by encoders. The control algorithm is implemented on the STM32F4 Discovery board. A verified test of the proposed control method is shown in the experiments, showing the good performance of the system.
Integrative Review-Based Conceptual Modeling: An Agent-Based Modeling Synthesis of Dynamic Energy Tariff Research and Models
Authors: Johanning Simon , Bruggemans Paul , Edelenbosch Oreane , Bruckner Thomas
Published: November 2024

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, often omitting non-financial decision variables. Moreover, methodologically robust integrative reviews on this topic are scarce. To address this gap, this paper develops a concept-centered integrative review methodology aimed at deriving computer models for socio-techno-economic simulations of household adoption of sustainable technologies. The methodology encompasses five sequential phases: Setup, Literature Search, Analysis, Synthesis and Conceptual Model, and Discussion. To illustrate the methodology, it is applied to the case of household adoption of dynamic energy tariffs, resulting in an abstract conceptual model adaptable to local contexts. The review reveals a lack of consensus on modeled tariffs but highlights the significance of tariff complexity, relative advantage, household heterogeneity, and various agent properties. It also identifies potential improvements in model fundamentals, particularly spatial modeling. The developed process model focuses on the stages ‘knowledge’, ‘decision’, and ‘reevaluation’. The article contributes by presenting a comprehensive review scheme and delivering a concept-centered integrative review along with an explicit conceptual model derived from it.
Biofuel Production in Oleic Acid Hydrodeoxygenation Utilizing a Ni/Tire Rubber Carbon Catalyst and Predicting of n-Alkanes with Box–Behnken and Artificial Neural Networks
Authors: Sánchez-Olmos Luis A. , Sánchez-Cárdenas Manuel , Trejo Fernando , Montes Rivera Martín , Olvera-Gonzalez Ernesto , Hernández Guerrero Benito Alexis
Published: November 2024

Oleic acid is a valuable molecule for biofuel production, as it is found in high proportions in vegetable oils. When used, oleic acid undergoes hydrodeoxygenation reactions and produces alkanes within the diesel range. These alkanes are free of oxygenated compounds and have molecular structures similar to petrodiesel. Our research introduces a novel approach incorporating oleic acid into the hydrodeoxygenation process of Ni/Tire Rubber Carbon (Ni/CTR) catalysts. These catalysts produced renewable biofuels with properties similar to diesel, particularly a high concentration of n-C17 alkanes. Moreover, our Ni/CTR catalyst produces n-C18 alkanes, but the generation of n-C18 alkanes typically requires more complex catalysts. Our procedure achieved 74.74% of n-C17 alkanes and 2.28% of n-C18 alkanes. We used Box–Behnken and artificial neural networks (ANNs) to find the optimal configuration based on the predicted data. We developed a dataset with pressure, temperature, metal content, reaction time, and catalyst composition variables as inputs. The output variables are the n-C17 and n-C18 alkanes obtained. ANN602020 was our best model for obtaining the peak response; it accurately forecasted the n-C17 and n-C18 generation with R2 scores of 0.9903 and 0.9525, respectively, resulting in an MSE of 0.0014, MAE of 0.02773, and MAPE of 2.03979%. The combined R2 score for both alkanes was 0.97139.
Design of Small Permanent-Magnet Linear Motors and Drivers for Automation Applications with S-Curve Motion Trajectory Control and Solutions for End Effects and Cogging Force
Authors: Ho Chia-Hsiang , Hwang Jonq-Chin
Published: November 2024

This paper designs and fabricates a small-type permanent-magnet linear motor and driver for automation applications. It covers structural design, magnetic circuit analysis, control strategies, and hardware development. Magnetic circuit analysis software JMAG is used for flux density distribution, back electromotive force (back-EMF), and electromagnetic force analysis. To address the lack of a complete closed magnetic circuit path at the ends of the linear motor, which causes magnetic field asymmetry, a phenomenon known as end effects, auxiliary core structures are proposed to compensate for the magnetic field at the ends. It successfully utilizes auxiliary cores to achieve the phase voltages of each phase, which are balanced at a phase voltage error of 0.02 V. To address the cogging force caused by variations in the magnetic reluctance of the core, this paper analyzes the relationship between electromagnetic force and mover position, conducting harmonic content analysis to obtain parameters. These parameters are applied to the designed cogging force control compensation strategy. It successfully achieves q-axis current compensation of around 1.05 A based on the mover’s position, ensuring that no jerking caused by cogging force occurs during closed-loop electromagnetic force control. The S-curve motion trajectory control is proposed to replace the traditional trapezoidal acceleration and deceleration, resulting in smoother position control of the linear motor. Simulations using JMAG-RT models in MATLAB/Simulink verified these control strategies. After verification, practical test results showed a maximum position error of approximately 5.0 μm. Practical tests show that the designed small-type permanent-magnet linear motor and its driver provide efficient, stable, and high-precision solutions for automation applications.
Durability Oriented Fuel Cell Electric Vehicle Energy Management Strategies Based on Vehicle Drive Cycles
Authors: Fu Xin , Fan Zengbin , Jiang Shangfeng , Fly Ashley , Chen Rui , Han Yong , Xie An
Published: November 2024

With the increasing severity of environmental problems and energy scarcity, fuel cell electric vehicles (FCEVs), as a sustainable and efficient means of transportation, are attracting more attention. The ageing of fuel cells (FCs) has become an urgent problem with the development of FCEV. In order to prolong the lifetime of FCs, this paper builds a model of a vehicle driven by two power sources, FC and lithium battery (Lib) using AVL Cruise. A rule-based energy management strategy (EMS) is developed in Simulink to explore the optimal control strategy for the vehicle in terms of the durability of the FC. An FC ageing model is used to quantify the degradation voltage of different duty cycles. The results show that the FC engagement levels, OCV operations, and start/stop operations can affect the lifetime of the FC significantly. By optimising the EMS, the lifetime of the FC is improved by 9.47%.
On-Line Parameter Identification and SOC Estimation for Lithium-Ion Batteries Based on Improved Sage–Husa Adaptive EKF
Authors: Tang Xuan , Huang Hai , Zhong Xiongwu , Wang Kunjun , Li Fang , Zhou Youhang , Dai Haifeng
Published: November 2024

For the Battery Management System (BMS) to manage and control the battery, State of Charge (SOC) is an important battery performance indicator. In order to identify the parameters of the LiFePO4 battery, this paper employs the forgetting factor recursive least squares (FFRLS) method, which considers the computational volume and model correctness, to determine the parameters of the LiFePO4 battery. On this basis, the two resistor-capacitor equivalent circuit model is selected for estimating the SOC of the Li-ion battery by combining the extended Kalman filter (EKF) with the Sage–Husa adaptive algorithm. The positivity is improved by modifying the system noise estimation matrix. The paper concludes with a MATLAB 2016B simulation, which serves to validate the SOC estimation algorithm. The results demonstrate that, in comparison to the conventional EKF, the enhanced EKF exhibits superior estimation precision and resilience to interference, along with enhanced convergence during the estimation process.
Topography and Wildfire Jointly Mediate Postfire Ecosystem Multifunctionality in a Chinese Boreal Forest
Authors: Kong Jianjian , Ding Zifan , Cai Wenhua , Zu Jiaxing , Liu Bo , Yang Jian
Published: November 2024

Both topography and wildfire can exert significant influences on ecosystem processes and functions during boreal forest successions. However, their impacts on ecosystem multifunctionality (EMF) remain unclear. A mega-fire burned an area of 8700 hectares in the Great Xing’an Mountains in 2000, creating a wide range of fire severity levels across various topographic positions. This provided a unique opportunity to explore the impacts of mixed-severity fire disturbance in boreal forests. We evaluated the effect pathways of wildfire and topography on aboveground multifunctionality (AEMF), soil multifunctionality (SEMF), and overall multifunctionality (OEMF). We found that high-severity burning resulted in lower AEMF, SEMF, and OEMF relative to low-severity burning. Topographic positions significantly influenced SEMF and OEMF, but not AEMF. Specifically, both lower SEMF and OEMF were observed on south-facing slopes. The structure equation model analysis showed that aspect had exerted strong indirect effects on AEMF, SEMF, and OEMF by affecting soil moisture and regenerated tree density (RTD). Fire severity had indirect negative effects on AEMF and OEMF by reducing RTD and on SEMF by reducing soil bacterial diversity and RTD. Our study elucidates the necessity of considering postfire site environments to better manage forest ecosystems and, in turn, promote the rapid recovery of boreal ecosystem functions.
Exploring the Nexus of Feeding and Processing: Implications for Meat Quality and Sensory Perception
Authors: Rodrigues Sandra S. Q. , Leite Ana , Vasconcelos Lia , Teixeira Alfredo
Published: November 2024

The intrinsic quality of meat is directly related to muscle and fat tissues. Factors such as the rate and extent of anaerobic glycolysis affect muscle pH, influencing the meat’s color, water holding, and texture. Postmortem anomalies can result in deviations from this intrinsic quality. The animals’ diet plays a crucial role in meat quality. Specific nutrients, such as proteins, vitamins, and minerals, affect meat’s texture, flavor, and juiciness. Feeds rich in omega-3 fatty acids can improve the sensorial quality of meat. Meat processing and methods such as aging, marinating, and cooking affect the texture, flavor, and juiciness, which can be evaluated by specific equipment or trained or untrained consumers. This comprehensive review investigates the relationship between animal feeding practices and meat processing techniques and their combined impact on meat quality and sensory perception. By synthesizing recent research, we explore how various feeding protocols (including diet composition and feed additives) and processing methods shape meat products’ nutritional value, texture, flavor profile, and overall consumer appeal. Understanding this nexus is crucial for optimizing meat quality while ensuring sustainability and safety in the food supply chain.
Detection of Short-Section Ballast Breakdown in Track: A Fractal Analysis Approach with Reduced Window Size
Authors: Korenjak Andrea Katharina , Offenbacher Stefan , Marschnig Stefan
Published: November 2024

Due to increasing demands on the available railway infrastructure, accurate estimates of safety-critical track condition as well as breakdowns of individual track components are crucial. This task can be supported by analyzing track measurement data. Ballast breakdown can be determined by analyzing the longitudinal level using fractal analysis: Commonly, a window with a width of 150 m is dragged over the signal computing an approximation of a fractal dimension of the signal for each position of the window. However, while a large window size can be used to describe the condition of ballast and substructure simultaneously, it fails to precisely localize short-section ballast breakdowns in the track. With the objective of describing and detecting these local effects in the ballast bed, this work analyzes a set of 114 known weak ballast spots. By reducing the width of the sliding window, the position of short-section ballast breakdowns can be reliably depicted. The application of a modified version of fractal analysis allows for a more accurate targeted maintenance on a component-specific basis.
Theory on New Fractional Operators Using Normalization and Probability Tools
Authors: Jornet Marc
Published: November 2024

We show how a rescaling of fractional operators with bounded kernels may help circumvent their documented deficiencies, for example, the inconsistency at zero or the lack of inverse integral operator. On the other hand, we build a novel class of linear operators with memory effects to extend the L-fractional and the ordinary derivatives, using probability tools. A Mittag–Leffler-type function is introduced to solve linear problems, and nonlinear equations are addressed with power series, illustrating the methods for the SIR epidemic model. The inverse operator is constructed, and a fundamental theorem of calculus and an existence-and-uniqueness result for differintegral equations are proven. A conjecture on deconvolution is raised, which would permit completing the proposed theory.
Earthquake Environmental Effects: The Case of Late Classical-Hellenistic Helike, Gulf of Corinth, Greece
Authors: Katsonopoulou Dora , Koukouvelas Ioannis
Published: November 2024

Human habitat is much controlled by the landscape and its ongoing processes overtime. Some of these processes occur instantaneously and are often triggered by seismic events with a major destructive impact on the human-built environment. Helike, on the southwest shore of the Gulf of Corinth, is a characteristic case of an ancient habitation site bearing witness to repetitious natural disasters from the Early Bronze Age to the Late Antiquity. The Late Classical-Hellenistic site, revived in the Helike plain after the 373 BC earthquake, has been systematically investigated thanks to the multidisciplinary research and excavations of the Helike Project in the last 35 years. This work has significantly enriched the historical seismicity of the region and shed light on past human-environment relationships. The study of the architectural remains excavated by the Helike Project, coupled with geological and soil micromorphological analysis on archaeological soils and sediments of the settlement, demonstrates a constant effort of the Helike people to reconcile with the elements of nature. Our results underline the destruction of a flourishing textile dyeworks operated at the settlement, due to a strong earthquake which triggered extensive morphological changes in a broader area. These changes include co-seismic liquefaction and lateral spreading, and post-seismic changes in the gradient of river channels. The former changes attest to an uplift in the headwater area and subsidence in the lowland plain of the ravine flowing near the ancient site.
Genome-Wide Identification of GRAS Gene Family in Cunninghamia lanceolata and Expression Pattern Analysis of ClDELLA Protein Under Abiotic Stresses
Authors: Luo Yi , Jin Mengshuang , Yang Junjie , Yang Ye , Guo Runxin , Luo Huan , Guo Tianhao , Xu Jin
Published: November 2024

The Chinese fir (Cunninghamia lanceolata) is a significant species utilized in afforestation efforts in southern China. It is distinguished by its rapid growth and adaptability to diverse environmental conditions. The GRAS gene family comprises a group of plant-specific transcription factors that play a pivotal role in plant growth and development, response to adversity, and hormone regulatory networks. However, the exploration of the GRAS family in gymnosperm Chinese fir has not yet begun. In this study, a total of 43 GRAS genes were identified in the whole genome of Chinese fir, and a phylogenetic analysis classified them into nine distinct subfamilies. Gene structure analysis revealed that the majority of ClGRAS genes lacked introns. It is notable that among these proteins, both ClGAI and ClGRA possess distinctive DELLA structural domains. Cis-acting element analysis revealed that nearly all ClGRAS genes contained light-responsive elements, while hormone-responsive elements, environmental-responsive elements (low-temperature- or defense-responsive elements), and meristem-organization-related elements were also identified. Based on transcriptome data and RT-qPCR expression patterns, we analyzed the expression of ClGAI and ClRGA genes across different developmental stages, hormones, and three abiotic stresses. Subcellular localization analysis demonstrated that ClGAI and ClRGA were localized to the nucleus. Transcriptional activation assays showed that both genes have self-activating activity. In conclusion, the results of this study indicate that the ClGRAS gene family is involved in the response of Chinese fir to environmental stress. Further research on the ClDELLA genes provides valuable information for exploring the potential regulatory network of DELLA proteins in Chinese fir.
ABA and Melatonin: Players on the Same Field?
Authors: Bychkov Ivan , Kudryakova Natalia , Pojidaeva Elena S. , Doroshenko Anastasia , Shitikova Victoria , Kusnetsov Victor
Published: November 2024

In plants, abscisic acid (ABA) and melatonin (MT) are conventionally treated as molecules mitigating stress responses. To understand the mechanisms of ABA–MT interplay, we examined the effects of ABA and MT treatment in ABA and MT loss-of-function mutants of Arabidopsis thaliana exposed to high light (HL) stress. ABA constantly suppressed ASMT encoding N-acetylserotonin methyltransferase in the context of differential responses of other MT biosynthesis genes in both the wild type (WT) and mutants. However, this response was absent in the mutant with the disrupted ABI4. Given that the ASMT promoter region contains several potential ABI4-binding elements, these data suggest that ASMT can be a potential target gene for ABI4. A role for ABI4 in the interactions between ABA and MT is supported by the finding that ABI4 is constitutively derepressed in the MT signaling mutants cand2 and gpa1, which exhibited elevated steady state levels of ABI4 transcripts and were not regulated by either stress or melatonin. In addition, the abi4 mutant showed increased modulations in the expression of the MT catabolic genes M2H and M3H in response to ABA treatment, inferring that this transcription factor is a negative regulator of ABA-dependent changes in MT content. Furthermore, all tested mutants with impaired ABA synthesis or signaling displayed elevated steady state MT levels compared to WT, while MT treatment contributed to the downregulation of key ABA synthesis and signaling genes. Collectively, our results suggest that ABA and melatonin act antagonistically, modulating the expression of ABA and MT signaling and metabolism genes. To understand the mechanisms of ABA–MT interactions, we studied the effects of ABA and MT treatment in ABA and MT loss-of-function mutants of Arabidopsis thaliana exposed to severe light stress (SLS).
The Fundamental Neurobiological Mechanism of Oxidative Stress-Related 4E-BP2 Protein Deamidation
Authors: Joseph Davis
Published: November 2024

Memory impairment is caused by the absence of the 4E-BP2 protein in the brain. This protein undergoes deamidation spontaneously in the neurons. 4E-BP2 deamidation significantly alters protein synthesis in the neurons and affects the balance of protein production required for a healthy nervous system. Any imbalance in protein production in the nervous system causes neurodegenerative diseases. Discovering what causes 4E-BP2 deamidation will make it possible to control this balance of protein production and develop effective treatments against neurodegenerative diseases such as Alzheimer’s and Parkinson’s. The purpose of this work is to discover the neurobiological mechanism that causes the deamidation reaction in the 4E-BP2 protein by performing immunoblotting in the retinal ganglia, the optic nerve, the dorsal root ganglia, the sciatic nerve, and the whole brain, extracted via dissection from 2-month-old, Wild-type male mice. The results show that axons and their unique properties cause neuron-specific 4E-BP2 deamidation in the nervous system, confirming conclusively that axons are the critical factors behind the fundamental neurobiological mechanism of 4E-BP2 protein deamidation.
Prognostic Significance of PD-L1 Expression on Circulating Myeloid-Derived Suppressor Cells in NSCLC Patients Treated with Anti-PD-1/PD-L1 Checkpoint Inhibitors
Authors: Salvia Roser , Rico Laura G. , Morán Teresa , Bradford Jolene A. , Ward Michael D. , Drozdowskyj Ana , Climent-Martí Joan , Martínez-Cáceres Eva M. , Rosell Rafael , Petriz Jordi
Published: November 2024

Even though anti-PD-1/PD-L1 immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) have improved survival, a high percentage of patients still do not respond to ICIs. Myeloid-derived suppressor cells (MDSCs) are circulating cells that express PD-L1 and can infiltrate and proliferate in the tumor microenvironment, inducing immunosuppression. By evaluating changes in PD-L1 expression of live peripheral blood MDSCs, we are able to define a new PD-L1 index, useful in predicting ICI escape in NSCLC patients before initiating anti-PD-1/PD-L1 immunotherapy. In this study, a cohort of 37 NSCLC patients was prospectively analyzed, obtaining independent PD-L1 indexes. In patients with a PD-L1 index > 5.88, progressive disease occurred in 58.33% of patients [median progression-free survival (PFS) = 5.73 months; 95%CI = 2.67–20.53], showing significant differences when compared with patients with a PD-L1 index ≤ 5.88, in whom 7.69% progressed and median PFS was not reached (NR); p-value = 0.0042. Overall survival (OS) was significantly worse in patients with a high vs. low PD-L1 index (41.67% vs. 76.92%; median OS = 18.03 months, 95%CI = 6.77–25.23 vs. NR, 95%CI = 1.87-NR; p-value = 0.035). The PD-L1 index can be applied to stratify NSCLC patients according to their probability of response to ICIs at baseline. In addition to quantifying tumoral expression, this index could be used to compare nonresponse to treatment.
Müller Glia Co-Regulate Barrier Permeability with Endothelial Cells in an Vitro Model of Hyperglycemia
Authors: Peña Juan S. , Berthiaume François , Vazquez Maribel
Published: November 2024

Diabetic retinopathy is a complex, microvascular disease that impacts millions of working adults each year. High blood glucose levels from Diabetes Mellitus lead to the accumulation of advanced glycation end-products (AGEs), which promote inflammation and the breakdown of the inner blood retinal barrier (iBRB), resulting in vision loss. This study used an in vitro model of hyperglycemia to examine how endothelial cells (ECs) and Müller glia (MG) collectively regulate molecular transport. Changes in cell morphology, the expression of junctional proteins, and the reactive oxygen species (ROS) of ECs and MG were examined when exposed to a hyperglycemic medium containing AGEs. Trans-endothelial resistance (TEER) assays were used to measure the changes in cell barrier resistance in response to hyperglycemic and inflammatory conditions, with and without an anti-VEGF compound. Both of the cell types responded to hyperglycemic conditions with significant changes in the cell area and morphology, the ROS, and the expression of the junctional proteins ZO-1, CX-43, and CD40, as well as the receptor for AGEs. The resistivities of the individual and dual ECs and MG barriers decreased within the hyperglycemia model but were restored to that of basal, normoglycemic levels when treated with anti-VEGF. This study illustrated significant phenotypic responses to an in vitro model of hyperglycemia, as well as significant changes in the expression of the key proteins used for cell–cell communication. The results highlight important, synergistic relationships between the ECs and MG and how they contribute to changes in barrier function in combination with conventional treatments.
NPHS Mutations in Pediatric Patients with Congenital and Steroid-Resistant Nephrotic Syndrome
Authors: Lee Jun Xin , Tan Yan Jin , Ismail Noor Akmal Shareela
Published: November 2024

NPHS1 and NPHS2 are kidney gene components that encode for nephrin and podocin, respectively. They play a role in the progression of congenital (CNS) and steroid-resistant (SRNS) nephrotic syndrome. Hence, this study aimed to determine the prevalence and renal outcomes of NPHS mutations among pediatric patients with CNS and SRNS. We also aimed to identify potential predictors of NPHS mutations in this patient cohort. Overall, this study included 33 studies involving 2123 patients screened for NPHS1, whereas 2889 patients from 40 studies were screened for NPHS2 mutations. The patients’ mean age was 4.9 ± 1 years (ranging from birth to 18 years), and 56% of patients were male (n = 1281). Using the random-effects model, the pooled proportion of NPHS1 mutations among pediatric patients with CNS and SRNS was 0.15 (95% CI 0.09; 0.24, p < 0.001, I2 = 92.0%). The pooled proportion of NPHS2 mutations was slightly lower, at 0.11 (95% CI 0.08; 0.14, p < 0.001, I2 = 73.8%). Among the 18 studies that reported ESRF, the pooled proportion was 0.47 (95% CI 0.34; 0.61, p < 0.001, I2 = 75.4%). Our study showed that the NPHS1 (β = 1.16, p = 0.35) and NPHS2 (β = 5.49, p = 0.08) mutations did not predict ESRF in CNS and SRNS pediatric patients. Nevertheless, patients from the European continent who had the NPHS2 mutation had a significantly higher risk of developing ESRF (p < 0.05, β = 1.3, OR = 7.97, 95% CI 0.30; 2.30) compared to those who had the NPHS1 mutation. We recommend NPHS mutation screening for earlier diagnosis and to avoid unnecessary steroid treatments. More data are needed to better understand the impact of NPHS mutations among pediatric patients with CNS and SRNS.