bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Long-Term Nitrogen Fertilization on Nitrous Oxide Emission and Yield in Acidic Tea (Camellia sinensis L.) Plantation Soils
Authors: Jiang Fuying , Chang Yunni , Han Jiabao , Yang Xiangde , Wu Zhidan
Published: December 2024

The responses of nitrous oxide (N2O) emissions to nitrogen (N) application in acidic, perennial agricultural systems, and the factors driving these emissions, remain poorly understood. To address this gap, a 12-year field experiment was conducted to investigate the effects of different N application rates (0, 112.5, 225, and 450 kg N ha−1 yr−1) on N2O emissions, tea yield, and the associated driving factors in a tea plantation. The study found that soil pH significantly decreased with long-term N application, dropping by 0.32 to 0.85 units. Annual tea yield increased significantly, by 148–243%. N application also elevated N2O emission fluxes by 33–277%, with notable seasonal fluctuations observed. N2O flux was positively correlated with N rates, water-filled pore space (WFPS), soil temperature (Tsoil), and inorganic N (NH4+-N and NO3−-N), while showing a negative correlation with soil pH. Random forest (RF) modeling identified WFPS, N rates, and Tsoil as the most important variables influencing N2O flux. The cumulative N2O emissions for N112.5, N225, and N450 were 1584, 2791, and 45,046 g N ha−2, respectively, representing increases of 1.33, 2.34, and 3.77 times compared to N0. The N2O-N emission factors (EF) were 0.35%, 0.71%, and 0.74%, respectively, and increased with higher N rates. These findings highlight the importance of selecting appropriate fertilization timing and improving water and fertilizer management as key strategies for mitigating soil acidification, enhancing nitrogen use efficiency (NUE), and reducing N2O emissions in acidic tea-plantation systems. This study offers a theoretical foundation for developing rational N fertilizer management practices and strategies aimed at reducing N2O emissions in tea-plantation soils.
Towards Automated Chicken Monitoring: Dataset and Machine Learning Methods for Visual, Noninvasive Reidentification
Authors: Kern Daria , Schiele Tobias , Klauck Ulrich , Ingabire Winfred
Published: December 2024

The chicken is the world’s most farmed animal. In this work, we introduce the Chicks4FreeID dataset, the first publicly available dataset focused on the reidentification of individual chickens. We begin by providing a comprehensive overview of the existing animal reidentification datasets. Next, we conduct closed-set reidentification experiments on the introduced dataset, using transformer-based feature extractors in combination with two different classifiers. We evaluate performance across domain transfer, supervised, and one-shot learning scenarios. The results demonstrate that transfer learning is particularly effective with limited data, and training from scratch is not necessarily advantageous even when sufficient data are available. Among the evaluated models, the vision transformer paired with a linear classifier achieves the highest performance, with a mean average precision of 97.0%, a top-1 accuracy of 95.1%, and a top-5 accuracy of 100.0%. Our evaluation suggests that the vision transformer architecture produces higher-quality embedding clusters than the Swin transformer architecture. All data and code are publicly shared under a CC BY 4.0 license.
The Effects of Mixed Inoculum Storage Time on In Vitro Rumen Fermentation Characteristics, Microbial Diversity, and Community Composition
Authors: Liu Chang , Ge Jing , Dai Jiaqi , Qu Mingren , Ouyang Kehui , Qiu Qinghua
Published: December 2024

This study aimed to investigate the effects of different storage times of the mixed inoculum on in vitro rumen fermentation characteristics, microbial diversity, and community composition. The experiment was divided into five groups, with mixed inoculum composed of fresh rumen fluid and culture medium being stored at 39 °C for 0 h (H0), 12 h (H12), 24 h (H24), 36 h (H36), and 48 h (H48). After 48 h of in vitro fermentation, the fermentation fluid was collected to assess rumen fermentation characteristics and microbial community composition. The H24 group showed higher total gas production, ammoniacal nitrogen levels, and total volatile fatty acids, as well as higher concentrations of individual volatile fatty acids except propionate, compared to the H0 and H48 groups (p < 0.05). The Shannon and Simpson evenness indices were significantly higher in the H0, H12, and H24 groups than in the H48 group (p < 0.05). A total of nine phyla and sixteen genera involved in starch and fiber degradation were found to be more abundant in the H24 or H48 groups (p < 0.05). Moreover, nine predicted metabolic pathways were observed to be significantly enriched in either the H24 or H48 group (p < 0.05). Both principal coordinates analysis (PCoA) and non-metric multidimensional scaling (NMDS) analysis revealed distinct clustering patterns among the H0, H12, H24, H36, and H48 groups, and analysis of similarities (ANOSIM) confirmed these significant differences (R = 1.00, p < 0.05). This study demonstrates that the storage time of mixed inoculum influences rumen fermentation characteristics and microbial community composition in a time-dependent manner. It is recommended to use a mixed inoculum that has been stored within 24 h in an anaerobic environment at 39 °C for in vitro rumen fermentation tests. This study offers valuable microbial insights into the storage strategies for mixed inoculum, thereby improving the methodologies for variable control in in vitro rumen fermentation techniques.
Effectiveness of a Novel Liposomal Methylglyoxal–Tobramycin Formulation in Reducing Biofilm Formation and Bacterial Adhesion
Authors: Alluhaim Wed , Alkhulaifi Manal M. , Alzahrani Raghad R. , Alrfaei Bahauddeen M. , Yassin Alaa Eldeen B. , Alghoribi Majed F. , Alsaadi Ahlam M. , Al-Asmari Ahmed I. , Al-Fahad Ahmed J. , Ali Rizwan , Alhawiti Naif M. , Halwani Majed A.
Published: December 2024

Background: The emergence of multidrug-resistant bacteria presents a significant global health threat. Liposomal antibiotics have shown a potential to improve antibiotic delivery and efficacy. This study aimed to develop liposomes encapsulating tobramycin (TOB) and methylglyoxal (MGO) to enhance TOB activity while reducing bacterial adhesion and biofilm formation. Methods: Clinical isolates of Pseudomonas aeruginosa and Klebsiella pneumoniae were characterized using whole-genome sequencing. Liposomes (Lip-MGO-TOB) were formulated using Manuka honey as a surfactant and loaded with MGO and TOB. Antibacterial activity, biofilm formation, and bacterial cell adhesion assays were performed to compare the efficacy of Lip-MGO-TOB against free TOB. Liposome characterization included analyses of morphology, zeta potential, TOB encapsulation efficiency, and stability under various biological conditions. Results: The Lip-MGO-TOB formulation, at a minimum inhibitory concentration (MIC) of 32 µg/mL, reduced the biofilm formation of the P. aeruginosa isolate (PA85) by 68%. Conversely, free TOB, at a MIC of 64 µg/mL, achieved only a 21% reduction. For the K. pneumoniae isolate (KP57), Lip-MGO-TOB inhibited bacterial adhesion to A549 cells at a lower concentration (256 µg/mL) compared to free TOB (512 µg/mL). Lip-MGO-TOB demonstrated sustained drug release over 24 h under tested conditions and retained over 99% of TOB. Conclusions: The Lip-MGO-TOB formulation significantly enhanced TOB activity against resistant bacteria compared to free TOB. Additionally, it provided a stable drug delivery system with controlled drug release. Liposomal TOB represents a promising advancement in combating antibiotic resistance by improving the efficacy and delivery of conventional antibiotics.
A New Approach in PLS/TPS Compatibilization Using Garlic Oil: Effect on Morphological and Antioxidant Properties
Authors: Castro Maria Cidália R. , Rodrigues Pedro Veiga , Cruz Vasco , Machado Ana Vera
Published: December 2024

The packaging industry has made efforts to reduce food waste and improve the resilience of food systems worldwide. Active food packaging, which incorporates active agents, represents a dynamic area where industry and academia have developed new strategies to produce innovative and sustainable packaging solutions that are more compatible with conventional options. Due to health and environmental concerns, industries have sought alternatives to petroleum-based materials and have found biopolymers to be a viable option because of their biodegradable and safe nature. The combination of PLA/TPS has emerged as an effective system for packaging film; however, they are thermodynamically immiscible. This work highlights the development of a starch-based compatibilizer to connect the PLA and TPS phases by functionalizing maize starch with glycidyl methacrylate, glycerol, or garlic oil. Garlic oil was chosen for its plasticizing ability and antioxidant properties. The films produced exhibited excellent compatibility, with enhanced interfacial adhesion between PLA and TPS components. The introduction of compatibilizers also increased the systems’ crystallinity and improved their mechanical properties. The wettability of the films significantly increased with higher garlic oil content, along with enhanced antioxidant properties. These advancements will enable the production of a compatible PLA/TPS system with improved properties for application in the packaging industry.
SocialJGCF: Social Recommendation with Jacobi Polynomial-Based Graph Collaborative Filtering
Authors: Lu Heng , Chen Ziwei
Published: December 2024

With the flourishing of social media platforms, data in social networks, especially user-generated content, are growing rapidly, which makes it hard for users to select relevant content from the overloaded data. Recommender systems are thus developed to filter user-relevant content for better user experiences and also the commercial needs of social platform providers. Graph neural networks have been widely applied in recommender systems for better recommendation based on past interactions between users and corresponding items due to the graph structure of social data. Users might also be influenced by their social connections, which is the focus of social recommendation. Most works on recommendation systems try to obtain better representations of user embeddings and item embeddings. Compared with recommendation systems only focusing on interaction graphs, social recommendation has an additional task of combining user embedding from the social graph and interaction graph. This paper proposes a new method called SocialJGCF to address these problems, which applies Jacobi-Polynomial-Based Graph Collaborative Filtering (JGCF) to the propagation of the interaction graph and social graph, and a graph fusion is used to combine the user embeddings from the interaction graph and social graph. Experiments are conducted on two real-world datasets, epinions and LastFM. The result shows that SocialJGCF has great potential in social recommendation, especially for cold-start problems.
MScope: A Reliable Battery for Functional Status Assessment in Multiple Sclerosis
Authors: Lisardo Daniel , López-Ortiz Susana , Jauregui-Fajardo Irati , Pinto-Fraga José , García-Chico Celia , Chavarría-Miranda Alba , Téllez Nieves , Maroto-Izquierdo Sergio
Published: December 2024

Multiple sclerosis (MS) is a neurodegenerative disease that often leads to severe disability. Although exercise, particularly strength training, improves health outcomes in MS, no standardized, reliable tool exists for functional assessment to inform tailored exercise prescriptions and patients’ categorization. This study aimed to validate the reliability of the MScope battery, a comprehensive tool incorporating structural, functional, and neuromuscular assessments to objectively evaluate patients with MS. A reproducibility study was conducted with 40 MS patients who completed the MScope battery twice, 72 h apart. Tests included structural (muscle thickness of the vastus lateralis and rectus femoris), functional (sit-to-stand, timed up-and-go, 10 m and six-minute walking test), and neuromuscular tests (isometric strength during the squat and leg extension exercises and handgrip strength). Intraclass correlation coefficients (ICCs), Bland–Altman plots, and the coefficient of variation (CV) were used to evaluate intra- and inter-day reliability. The MScope battery showed high intra- and inter-day reliability, with ICC values ranging from 0.79 to 0.99. Muscle thickness measurements, along with handgrip strength, demonstrated excellent reliability (ICC > 0.9, CV < 5%). Functional tests, including the timed up-and-go, 10 m walk, and sit-to-stand variations, maintained consistent scores (ICC > 0.85, CV < 10%). The six-minute walking test exhibited excellent inter-day reliability (ICC = 0.94, CV < 4%). Neuromuscular assessments showed strong reliability with minor day-to-day variability (ICC = 0.75–0.95, CV < 8%). The battery’s overall consistency supports its use as a reliable tool for assessing functional status in MS patients.
Fuzzy Cognitive Maps for Decision Support in Post-COVID Syndrome with Speech-Language Pathology-Related Problems
Authors: Tola Manila , Georgopoulos Voula Chris , Geronikou Eleftheria , Plotas Panagiotis , Stylios Chrysostomos
Published: December 2024

Detecting and managing speech-language pathology symptoms in patients with post-COVID syndrome (long COVID) presents a significant challenge, as the condition is marked by persistent and varied symptoms such as cognitive deficits, communication difficulties, and voice disorders. To address these challenges, a Fuzzy Cognitive Map Decision Support System (FCM-DSS) was developed to model causal relationships and integrate expert knowledge. A systematic review approach, though not comprehensive, was utilized to identify key symptoms and their prevalence from 19 studies, focusing on brain fog, attention deficits, memory problems, dyspnea, and swallowing difficulties. The weighted prevalence of these symptoms informed the development of the FCM-DSS model, designed to link symptoms to medical specialties and recommend specialist referrals. Preliminary testing on four case studies demonstrated the tool’s potential, but further validation through pilot studies is necessary.
Raising Awareness of Climate Heritage Resilience and Vulnerability by Playing Serious Video Games
Authors: Bontchev Boyan , Terzieva Valentina , De Bonis Luciano , Nocera Rossella , Vassileva Dessislava , Ottaviano Giovanni
Published: December 2024

Contemporary climate change affects not only human beings and natural ecosystems but tangible cultural heritage, too. Understanding and appreciating climate change’s influence on built cultural heritage involves raising awareness of vulnerability and resilience issues. Hence, educators need to develop integrated approaches to teaching the protection and preservation of architectural heritage from climate change, including the creation of educational resources, including serious video games, to teach climate resilience and vulnerability. In this context, the authors developed two 3D maze video games—“Let Us Save Venice” and the Vulnerability game—focused on engaging students and raising awareness of climate heritage issues. The article discusses the results from the experimental validation of the Vulnerability game and tries to answer how game design enhanced by using the revised Bloom taxonomy and active collaboration with domain specialists can improve learning outcomes, learnability factors, and game experience. The findings suggest that the maze games can effectively supplement traditional teaching approaches in raising awareness and teaching climate resilience in cultural heritage contexts.
Wavelet-Based Analysis of Motor Current Signals for Detecting Obstacles in Train Doors
Authors: Shiao Yaojung , Gadde Premkumar , Liu Chun-Yu
Published: December 2024

Trains used in urban mass passenger transit often have side entrance doors through which passengers can rapidly enter and exit the train. These doors are typically electrically powered and automated. Many incidents have occurred in which a passenger is trapped and injured while passing through the doors as they are closing. Existing solutions rely on sensitive-edge sensors and current signal peak detection in the time domain to detect door obstructions. However, these methods have notable limitations: sensors are expensive, and sensor failure can result in safety risks, while time-domain signal analysis is prone to noise, potentially leading to false peak detection. The proposed efficient and cost-effective method enhances safety by implementing the torque control of a DC motor which limits the door closing force to prevent potential injuries. In addition, it reduces reliance on traditional edge sensors, which are prone to failure and may result in undetected obstructions. By using a robust time–frequency domain approach, the system ensures more accurate detection, minimizing potential injury risks. An obstruction of the door causes a corresponding change in the motor current. These changes can be detected by using the discrete wavelet transform to decompose the current signal. The norm and peak of the current are used as obstacle detection features, and appropriate threshold values are obtained from a simulation. The simulation results were validated through an experiment. The proposed novel system effectively detects forces between 100 and 200 N (indicating the presence of an object) within 0.3 s and complies with EN14752 safety standard. It can also differentiate between soft and hard objects trapped in train doors.
Correlation of Laser-Accelerated Electron Energy with Electromagnetic Pulse Emission from Thin Metallic Targets
Authors: Marcu Aurelian , Stafe Mihai , Groza Andreea , Serbanescu Mihai , Ungureanu Razvan , Cojocaru Gabriel , Diplasu Constantin , Mihalcea Bogdan , Ganciu Mihai , Negutu Constantin , Giubega Georgiana , Puscas Niculae
Published: December 2024

High-power pulsed lasers are used more and more as tools for particle acceleration. Characterization of the accelerated particles in real-time and monitoring of the electromagnetic pulses (EMPs) during particle acceleration are critical challenges in laser acceleration experiments. Here, we used the CETAL-PW laser facility at NILPRP for particle acceleration from different thin metallic targets, at laser intensities of the order of 3×1021 W/cm2. We investigated the dependence of EMP amplitude (EMPA) and the accelerated electrons’ maximal energy (AEME), on thickness, resistivity, and atomic number of the target. We have found a quasi-linear dependence between EMPA and AEME and propose an analytical model for the GHz EMP emission. The model considers the neutralization current flowing through the target stalk as the main source of the EMP in the GHz domain, the current being produced by the positive charge accumulated on the target after the electron’s acceleration from the rear side of a metallic target. The data presented here support the possibility of using EMP signals to characterize the laser-accelerated particles in a real-time non-invasive way.
Quantitative Analysis of Basalt Damage Under Microwave Radiation Utilizing Uniaxial Compression and Nuclear Magnetic Resonance (NMR) Experiments
Authors: Yin Tubing , Wang Jihao , Ma Jiexin , Lu Jianfei , Dai Hao
Published: December 2024

Microwave-assisted rock breaking is recognized as an effective technology for reducing tool wear and enhancing rock-breaking efficiency. In this study, basalt rock was irradiated with a microwave power of 3 kW and 6 kW for 30 s, 60 s, 90 s, and 120 s. Subsequently, uniaxial compression, uniaxial loading and unloading, and acoustic emission tests were performed. The damage evolution of basalt was assessed through non-destructive acoustic testing methods and nuclear magnetic resonance (NMR) techniques. The results showed that the P-wave velocity, uniaxial compressive strength (UCS), and modulus of elasticity (E) exhibited varying degrees of deterioration as the microwave radiation time increased. An increase in microwave radiation time and power led to heightened acoustic emission activity in basalt and a significant rise in the proportion of shear cracks during uniaxial compression. From an energy perspective, microwave irradiation decreased the energy storage capacity of the basalt specimen prior to its peak point, with increased power and duration. At a microscopic level, porosity and the macroporous fractal dimension increased with extended microwave radiation time and power, indicating that microwave irradiation facilitated the growth of larger fractal pore structures. The findings of this study offer scientific insights for the application of microwave-assisted rock crushing.
A Low-Cost IoT System Based on the ESP32 Microcontroller for Efficient Monitoring of a Pilot Anaerobic Biogas Reactor
Authors: Kalamaras Sotirios D. , Tsitsimpikou Maria-Athina , Tzenos Christos A. , Lithourgidis Antonios A. , Pitsikoglou Dimitra S. , Kotsopoulos Thomas A.
Published: December 2024

A pilot anaerobic bioreactor requires near-daily monitoring and frequent maintenance. This study aimed to upgrade a pilot bioreactor into a low-cost IoT device via ESP32 microcontrollers. The methodology was based on remote data acquisition and online monitoring of various parameters towards assessing the anaerobic digestion performance. A semi-continuous tank bioreactor with a 60 L total volume was initially inoculated mainly with livestock manure and fed daily with a mixture of glucose, gelatin, and oleic acid, supplemented with a basic anaerobic medium. Under steady-state conditions, the organic loading rate was 2 g VS LR−1 d−1. Sensors for pH, temperature, REDOX potential, and ammonium concentration, along with devices measuring biogas volume and methane content, were integrated and validated against analytical methods. Biogas production was recorded accurately, enabling the early detection of production declines through ex-situ data analysis. Methane concentration variance was less than 6% compared to gas chromatography, while temperature and pH deviations were 0.15% and 1.67%, respectively. Ammonia ion measurements required frequent recalibration due to larger fluctuations. This IoT-enhanced system effectively demonstrated real-time monitoring of critical bioreactor parameters, with ESP32 enabling advanced control and monitoring capabilities.
The Dynamic Response of an Arch Dam During a Recorded Low-Intensity Earthquake
Authors: Gomes Jorge P. , Lemos José V.
Published: December 2024

The dynamic behavior of a concrete arch dam, the Baixo Sabor dam, built in Portugal, is investigated. A numerical model was developed to represent the dam, foundation, and reservoir system. This model was calibrated and validated through comparison with experimental data from forced vibration tests and ambient vibration monitoring. Recently, a low-intensity earthquake occurred in the region and the dam response was recorded by a seismic monitoring system. The previously calibrated numerical model was used to analyze the dynamic response of the dam under this seismic input, employing a dynamic boundary formulation that takes into account the wave propagation in the rock mass, preventing wave reflections. The results obtained show generally good agreement with the experimental measurements at the dam crest and abutments. The analysis methodology and the main issues involved in the modelling of arch dams under seismic action are discussed.
Investigating the Adsorption Behavior of Zwitterionic Surfactants on Middle Bakken Minerals
Authors: Oguntade Tomiwa Isaac , Fadairo Adesina Samson , Ogunkunle Temitope Fred , Oladepo David Adebowale , Nkok Luc Yvan
Published: December 2024

Zwitterionic surfactants are a promising option for application in harsh reservoir conditions due to their exceptional stability, compatibility, and interfacial activity. However, surfactant adsorption remains a significant concern. This study investigates the adsorption behavior of zwitterionic surfactants was studied on complex Middle Bakken minerals under high-salinity (total dissolved solids (TDS) = 29 wt%) and high-temperature (90 °C) conditions using the spectrophotometric method. The adsorbents were prepared by grinding Bakken core plugs using a ball mill and sifting them through 40 μm mesh sieves to ensure uniform particle size distribution. The results showed that the Langmuir adsorption model accurately describes the adsorption isotherms of zwitterionic surfactants. The impact of salinity on the zwitterionic surfactants adsorption varied depending on the presence of acidic and/or basic groups in the surfactants. Using Bakken formation brine instead of brine solutions with 2% TDS resulted in a decrease in adsorption of approximately 1.06 ± 0.02 mg/g for CG3 and 0.3 ± 0.04 mg/g for both CD2 and ME1. This reduction was observed in betaine-type zwitterionic surfactants with −COO− functional groups that may gain protons, compared to their adsorption capacities in the 2% TDS brine (2.35 mg/g, 2.1 mg/g, and 1.89 mg/g, respectively). This study provides critical insights into the behavior of interfacial tension (IFT) between crude oil and surfactant solutions, which is vital for optimizing enhanced oil recovery (EOR) processes. The findings underline the importance of surfactant concentration and adsorption characteristics, offering valuable guidelines for practical applications in petroleum reservoir management. Overall, zwitterionic surfactants exhibit higher adsorption on Bakken minerals regardless of the salinity condition.
Quality Comparison of Chicken Meat Treated with Origanum syriacum L. and Origanum vulgare L. Essential Oil Incorporated with Aloe vera Gel
Authors: Al-Hijazeen Marwan A.
Published: December 2024

This comparison study assessed the antioxidant effectiveness of two oregano essential oils extracted from different plant species, namely, Origanum syriacum L. and Origanum vulgare subsp. hirtum, applied to 5% Aloe barbadensis miller gel using chicken meat. In addition, all treatment samples contained the same amount (5%) of Aloe vera gel. The results of the current research will help to distinguish between both oil types accurately. This study involved four different treatments: (1) Control, (2) 300 ppm of Origanum syriacum L. essential oil (OR-S), (3) 300 ppm of Origanum vulgare subsp. hirtum (OR-V), and (4) 14 ppm of butylated hydroxyanisole (BHA). Generally, natural antioxidants have many limitations when used for meat preservation compared to synthetic ones and should be combined with natural carriers. The treated meat patties were used to analyze lipid oxidation, color, total volatiles, and specific sensorial characteristics. Based on the current investigation, comparisons between treatments (OR-V, OR-S, and BHA) demonstrated that both of the combined oregano oils showed lower TBARS values. The control treatment showed the lowest preservation effect. Origanum syriacum L. (OR-S) and OR-V showed significant antioxidant effects compared to synthetic BHA. However, OR-S exhibited the strongest significant antioxidant effect and could be the best choice for industrial meat preservation.
Assessment of Dental Arch Width Expansion Effectiveness Using a Novel Hybrid Aligner with Virtual Brackets and Nickel–Titanium Archwires: A Prospective Clinical Study
Authors: Leon-Valencia Jhonny , Alarcon Jose Antonio , Martin Conchita
Published: December 2024

Objectives: This study aimed to evaluate the effectiveness of a novel hybrid aligner system, Geniova Technologies™ (GT), for arch expansion and to compare the predictability of its virtual setup with a conventional clear aligner system (CA) after the first treatment phase. Materials and Methods: Forty (mean age: 31.3 years for GT, 38.4 years for CA) adult patients with maxillary dentoalveolar compression and anterior crowding >3 mm were enrolled and assigned to GT and CA groups. Transverse changes for canines and premolars were measured at the cusp and cervical levels. Results: No significant baseline differences in transverse dimensions were found between groups. Treatment duration (4.25 months for GT vs. 9.75 months for CA) and the number of aligners (4.25 in GT vs. 28.25 in CA) significantly differed (p < 0.001). At the cusp level, mean transverse expansions for the maxillary first premolars were 2.78 mm (GT) and 2.44 mm (CA). However, effectiveness comparisons revealed no significant differences in expansion outcomes, with both groups showing similar accuracy. Conclusions: The GT group achieved comparable dentoalveolar expansion of canines and premolars in significantly less time and with fewer aligners than the CA group. The predictability of virtual setup measurements was similar for both systems, confirming their comparable performance in achieving planned expansion.
Application of Thermodynamic Methods to the Study of Plant Biomass and Its Components—A Review
Authors: Michael Ioelovich
Published: December 2024

This article describes the basics of chemical thermodynamics and its application to the study of plant biomass and its main components, cellulose, hemicelluloses, lignin, etc. The energy potential of various biomass types, as well as biomass-based solid, liquid, and gaseous biofuels, is determined. A method of additive contributions of combustion enthalpies of main components is proposed to calculate the combustion enthalpy of biomass samples. It is also established that the potential of thermal energy of the initial biomass is higher than the energy potential of secondary biofuels released from this biomass. The thermodynamic functions of plant biopolymers are calculated. Moreover, the thermodynamic stability of various crystalline allomorphs of cellulose and amorphous cellulose is studied. The melting enthalpies of crystallites with different types of crystalline structures are estimated. A thermochemical method for determining the degree of crystallinity of cellulose is proposed. The most important biomass components are cellulose and other polysaccharides. The thermodynamics of the enzymatic hydrolysis of polysaccharides and their conversion into glucose are described. In addition, the thermodynamic analysis of the conversion process of glucose into bioethanol is performed. Considerable attention is also paid to the thermochemistry of cellulose alkalization, etherification, and esterification.
Exploring Stochastic Heat Equations: A Numerical Analysis with Fast Discrete Fourier Transform Techniques
Authors: Khattab Ahmed G. , Semary Mourad S. , Hammad Doaa A. , Fareed Aisha F.
Published: December 2024

This paper presents an innovative numerical technique for specific classes of stochastic heat equations. Our approach uniquely combines a sixth-order compact finite difference algorithm with fast discrete Fourier transforms. While traditional discrete sine transforms are effective for approximating second-order derivatives, they are inadequate for first-order derivatives. To address this limitation, we introduce an innovative variant based on exponential transforms. This method is rigorously evaluated on two forms of stochastic heat equations, and the solutions are compared with those obtained using the established stochastic ten non-polynomial cubic-spline method. The results confirm the accuracy and applicability of our proposed method, highlighting its potential to enhance the numerical treatment of stochastic heat equations.
Evaluation of Certain Definite Integrals Involving Generalized Hypergeometric Functions
Authors: Jayarama Prathima , Lim Dongkyu , Rathie Arjun K. , Kilicman Adem
Published: December 2024

In 2012, Chu investigated the generalization of classical Watson–Whipple–Dixon summation theorems in the form of analytical formulas. By employing four generalized Watson summation formulas, the objective of this paper is to evaluate a new class of several Eulerian-type integrals (single and double) and Laplace-type integrals involving a hypergeometric function. Several interesting special cases are also given. Symmetry arises spontaneously in the hypergeometric function.
Sentiment Analysis of Product Reviews Using Machine Learning and Pre-Trained LLM
Authors: Ghatora Pawanjit Singh , Hosseini Seyed Ebrahim , Pervez Shahbaz , Iqbal Muhammad Javed , Shaukat Nabil
Published: December 2024

Sentiment analysis via artificial intelligence, i.e., machine learning and large language models (LLMs), is a pivotal tool that classifies sentiments within texts as positive, negative, or neutral. It enables computers to automatically detect and interpret emotions from textual data, covering a spectrum of feelings without direct human intervention. Sentiment analysis is integral to marketing research, helping to gauge consumer emotions and opinions across various sectors. Its applications span analyzing movie reviews, monitoring social media, evaluating product feedback, assessing employee sentiments, and identifying hate speech. This study explores the application of both traditional machine learning and pre-trained LLMs for automated sentiment analysis of customer product reviews. The motivation behind this work lies in the demand for more nuanced understanding of consumer sentiments that can drive data-informed business decisions. In this research, we applied machine learning-based classifiers, i.e., Random Forest, Naive Bayes, and Support Vector Machine, alongside the GPT-4 model to benchmark their effectiveness for sentiment analysis. Traditional models show better results and efficiency in processing short, concise text, with SVM in classifying sentiment of short length comments. However, GPT-4 showed better results with more detailed texts, capturing subtle sentiments with higher precision, recall, and F1 scores to uniquely identify mixed sentiments not found in the simpler models. Conclusively, this study shows that LLMs outperform traditional models in context-rich sentiment analysis by not only providing accurate sentiment classification but also insightful explanations. These results enable LLMs to provide a superior tool for customer-centric businesses, which helps actionable insights to be derived from any textual data.
Edge-AI Enabled Wearable Device for Non-Invasive Type 1 Diabetes Detection Using ECG Signals
Authors: Gragnaniello Maria , Marrazzo Vincenzo Romano , Borghese Alessandro , Maresca Luca , Breglio Giovanni , Riccio Michele
Published: December 2024

Diabetes is a chronic condition, and traditional monitoring methods are invasive, significantly reducing the quality of life of the patients. This study proposes the design of an innovative system based on a microcontroller that performs real-time ECG acquisition and evaluates the presence of diabetes using an Edge-AI solution. A spectrogram-based preprocessing method is combined with a 1-Dimensional Convolutional Neural Network (1D-CNN) to analyze the ECG signals directly on the device. By applying quantization as an optimization technique, the model effectively balances memory usage and accuracy, achieving an accuracy of 89.52% with an average precision and recall of 0.91 and 0.90, respectively. These results were obtained with a minimal memory footprint of 347 kB flash and 23 kB RAM, showcasing the system’s suitability for wearable embedded devices. Furthermore, a custom PCB was developed to validate the system in a real-world scenario. The hardware integrates high-performance electronics with low power consumption, demonstrating the feasibility of deploying Edge-AI for non-invasive, real-time diabetes detection in resource-constrained environments. This design represents a significant step forward in improving the accessibility and practicality of diabetes monitoring.
Effect of Age on the Biomechanical Properties of Porcine LCL
Authors: Singh Narendra , Trajkovski Jovan , Matas Jose Felix Rodriguez , Kunc Robert
Published: December 2024

The Lateral Collateral Ligament (LCL), one of the four major ligaments in the knee joint, resides on the outer aspect of the knee. It forms a vital connection between the femur and the fibula. The LCL’s primary role is to provide stability against Varus forces, safeguarding the knee from undue rotation and tibial displacement. Uniaxial mechanical testing was conducted on the dog bone (DB) samples in this study. The porcine of different ages, from 3 months to 48 months (4 years) old, were used to analyse the effect of age. A constant head speed of 200 mm/s was applied throughout the tests to mimic strain–stress and damage responses at an initial strain rate of 13.3/s. The mechanical properties of LCL were evaluated, with a specific focus on the effect of age. The LMM (Linear Mixed Model) analysis revealed a marginally significant positive slope for Young’s modulus (p = 0.0512) and a significant intercept (p = 0.0016); for Maximum Stress, a negative slope (p = 0.0346) and significant intercept (p < 0.0001); while Maximum Stretch showed a significant negative slope (p = 0.0007) and intercept (p < 0.0001), indicating the muscle reduces compliance and load-bearing capacity with age.
Effects of Floral Characters on the Pollination Biology and Breeding System of Iris setosa (Iridaceae): A Cold-Tolerant Ornamental Species from Jilin Province
Authors: Zhang Xiyue , Liu Ruoqi , Chen Lifei , Pei Tianhao , Gao Yu , Lu Xi , Zhou Yunwei
Published: December 2024

Floral phenology and features are intricately linked to pollinator behavior and pollination systems. Iris setosa is one of the ornamental irises of the family Iridaceae with beautiful flowers and leaves, and little research has been reported on its pollination biology. This study analyzed how phenology, floral features, breeding systems, and pollinator visits affect reproductive success of I. setosa populations in Jilin Province. Field observations and pollination studies demonstrated that I. setosa reached the bud stage in late May, with an average flowering time of 30 days. The anthers were outwardly dehiscent toward the outer edge of the style branches. In herkogamy, the relative locations of the anthers and stigma remained unchanged during flower opening. The stamens matured first. The pollen was most viable and the stigmas were most receptive on the first day of flowering. The nectar had the maximum sugar content. The sexual reproduction system was mainly outcrossing, with some self-compatibility and a need for pollinators. After artificial self-pollination, fluorescent microscopy revealed the winding of pollen tubes. The predominant flower-visiting insects were Apis mellifera, Megachile sp., Syrphus corollae, Episyrphus balteatus, and Lasioglossum sp., among which A. mellifera, Megachile sp., and Lasioglossum sp. were effective pollinators. Understanding the pollination mechanisms and strategies of I. setosa provides basic reference data on the potential for reproduction, and conservation efforts.
The Possible Crystallization Process in the Origin of Bacteria, Archaea, Viruses, and Mobile Elements
Authors: Yoshimura Akari , Seki Masayuki
Published: December 2024

We propose a hypothesis for the simultaneous emergence of bacteria, archaea, viruses, and mobile elements by sequential and concrete biochemical pathways. The emergence process can be considered analogous to crystallization, where genetic and biochemical systems stabilize as organisms evolve from their common ancestor, the LUCA, which was a non-free-living pool of single operon type genomes including double-stranded (ds) DNA at an ancient submarine alkaline vent. Each dsDNA operon was transcribed by different systems in σ, TFIIB, or TBP genomes. Double-stranded DNA operons can fuse and stabilize through the action of specific transcription systems, leading to differentiation between the Bacteria (σ genome) and Archaea (TBP genome) domains. Error catastrophe can be overcome by the parallel gain of DNA replication and DNA repair mechanisms in both genomes. Enlarged DNA enabled efficient local biochemical reactions. Both genomes independently recruited lipids to facilitate reactions by forming coacervates at the chamber of the vent. Bilayer lipid membrane formation, proto-cell formation with a permeable membrane, proto-cell division, and the evolution of membrane-associated biochemistry are presented in detail. Simultaneous crystallization of systems in non-free-living bacteria and non-free-living archaea triggered the co-crystallization of primitive viruses and mobile elements. An arms race between non-free-living cells and primitive viruses finally led to free-living cells with a cell wall and mature viruses.
Introduced Spiders in Panama: Species Distributions and New Records
Authors: Murcia-Moreno Daniel , Gálvez Dumas
Published: December 2024

Biological invasions occur when organisms are moved from their native range and introduced into new areas, where they can spread and become a potential risk for native organisms. Invasive species are well recorded for vertebrates, plants and a number of invertebrates. A taxa for which there is a lack of information in some countries are arachnids, and this is the case of reports on introduced species in Panama. Here, we report the first list of introduced spider species in the country as a result of reviewing scientific literature, online databases, museum collections and carrying out field collections. We report six new introduced species out of a total of 31 species, belonging to 10 families and 25 genera. A large proportion of these species originated from Asia. Moreover, most of the species, with historic data available, have expanded their distribution in the country. We also present a list of species that might be already present in the country or may be introduced in the future. Our work highlights the capability of spiders to invade and spread into new territories. Therefore, monitoring policies and control strategies should also consider them as potential risk for local ecosystems.
The Difference a Year Can Make: How Antibiotic Resistance Mechanisms in Pseudomonas aeruginosa Have Changed in Northwestern Transylvania
Authors: Dobrescu Matei-Ștefan , Țoc Dan-Alexandru , Pană Adrian-Gabriel , Costache Carmen , Butiuc-Keul Anca
Published: December 2024

This study examines the prevalence and the mechanisms of antibiotic resistance in Pseudomonas aeruginosa isolates collected from healthcare units in Northwestern Transylvania, Romania, between 2022 and 2023. Given the alarming rise in antibiotic resistance, the study screened 34 isolates for resistance to 10 antibiotics, 46 ARGs, and integrase genes using PCR analysis. The results reveal a concerning increase in multidrug-resistant (MDR) and extensively drug-resistant (XDR) isolates over the two-year period. Notably, the prevalence of ARGs encoding resistance to sulfonamides and beta-lactams, particularly sul1 and blaOXA-50, has shown a significant rise. Furthermore, the study detected the emergence of new resistance mechanisms in the same time interval. These include target protection and even more specific mechanisms, such as metallo-beta-lactamases or enzymes involved in the methylation of 23S rRNA. Statistical analysis further confirmed the correlation between Class I integrons and several ARGs, underscoring the role of horizontal gene transfer in the dissemination of resistance. These findings emphasize the urgent need for updated treatment strategies and monitoring programs to effectively combat the spread of ARGs in clinical settings.
The Expression Regulation and Cancer-Promoting Roles of RACGAP1
Authors: Lin Jiacheng , Zhu Yuhao , Lin Zhaoping , Yu Jindong , Lin Xiaobing , Lai Weiyuan , Tong Beibei , Xu Liyan , Li Enmin , Long Lin
Published: December 2024

RACGAP1 is a Rho-GTPase-activating protein originally discovered in male germ cells to inactivate Rac, RhoA and Cdc42 from the GTP-bound form to the GDP-bound form. GAP has traditionally been known as a tumor suppressor. However, studies increasingly suggest that overexpressed RACGAP1 activates Rac and RhoA in multiple cancers to mediate downstream oncogene overexpression by assisting in the nuclear translocation of signaling molecules and to promote cytokinesis by regulating the cytoskeleton or serving as a component of the central spindle. Contradictorily, it was also reported that RACGAP1 in gastric cancer could inactivate Rac and RhoA. In addition, studies have revealed that RACGAP1 can be a biomarker for prognosis, and its role in reducing doxorubicin sensitivity poses difficulties for treatment, while the current drug targets mainly focus on its downstream molecule. This article mainly reviews the expression regulation of RACGAP1 and its cancer-promoting functions through oncogene expression mediation and Rho-GTPase activation.
mTOR Inhibitor Everolimus Modulates Tumor Growth in Small-Cell Carcinoma of the Ovary, Hypercalcemic Type and Augments the Drug Sensitivity of Cancer Cells to Cisplatin
Authors: Zheng Kewei , Gao Yi , Xu Jing , Kang Mingyi , Chai Ranran , Jin Guanqin , Kang Yu
Published: December 2024

Background: Small-cell carcinoma of the ovary, hypercalcemic type (SCCOHT), is a rare and aggressive cancer with a poor prognosis and limited treatment options. Current chemotherapy regimens are predominantly platinum-based; however, the development of platinum resistance during treatment significantly worsens patient outcomes. Everolimus, an mTOR inhibitor, has been widely used in combination cancer therapies and has successfully enhanced the efficacy of platinum-based treatments. Method: In this study, we investigated the combined effects of everolimus and cisplatin on SCCOHT through both in vitro and in vivo experiments, complemented by RNA sequencing (RNA-seq) analyses to further elucidate the therapeutic impact. Result: Our findings revealed that everolimus significantly inhibits the proliferation of SCCOHT cells, induces cell cycle arrest, and accelerates apoptosis. When combined with cisplatin, everolimus notably enhances the therapeutic efficacy without increasing the toxicity typically associated with platinum-based drugs. RNA-seq analysis uncovered alterations in the expression of apoptosis-related genes, suggesting that the underlying mechanism involves autophagy regulation. Conclusions: Despite the current challenges in treating SCCOHT and the suboptimal efficacy of platinum-based therapies, the addition of everolimus significantly suppresses tumor growth. This indicates that everolimus enhances cisplatin efficacy by disrupting survival-promoting signaling cascades and inducing cell cycle arrest. Furthermore, it points to potential biomarkers for predicting therapeutic response.
T-Cell Subpopulations and Differentiation Bias in Diabetic and Non-Diabetic Patients with Chronic Kidney Disease
Authors: Granda Alacote Ana Cecilia , Goyoneche Linares Gabriela , Castañeda Torrico María Gracia , Diaz-Obregón Daysi Zulema , Núñez Michael Bryant Castro , Murillo Carrasco Alexis Germán , Liendo Cesar Liendo , Rufasto Goche Katherine Susan , Correa Víctor Arrunátegui , de León Delgado Joel
Published: December 2024

Background: Chronic kidney disease (CKD) patients often experience dysregulated inflammation, particularly when compounded by comorbidities such as type 2 diabetes (T2D). Objective: The aim of this study was to determine whether T2D influences the profile of memory T lymphocytes, regulatory T cells (Tregs), and the gene expression of transcription factors such as T-bet (Tbx21), GATA3, RORyT (RORC), and FOXP3 in CKD patients. Methods: Twenty-two CKD patients undergoing hemodialysis were selected for the study. Flow cytometry was used to identify naïve T cells, Tregs (CD4+CD25+CD127-), central memory T lymphocytes (CCR7+CD45RA-), effector memory T lymphocytes (CCR7-CD45RA-), and TEMRA cells (CCR7-CD45RA+). The expression of helper T cell differentiation regulatory genes was assessed using real-time RT-PCR. Results: Both helper and cytotoxic effector memory T cell populations were found to be higher than naïve lymphocytes in CKD patients, regardless of T2D status. However, Tregs were significantly more frequent in diabetic CKD patients (5.1 ± 2.6%) compared to non-diabetic patients (2.8 ± 3.1%). In terms of transcription factor expression, a significant correlation was observed between T-bet and FOXP3 in diabetic patients, and between RORyT and FOXP3 in non-diabetic patients. Conclusions: While T2D does not notably alter the distribution of memory T cells in CKD patients, it significantly impacts the frequency of Tregs and their correlation with pro-inflammatory transcription factors like T-bet (Tbx21) and RORyT.