bluuebunny/crossref_metadata_2025 huggingface dataset:
Primary Methods and Algorithms in Artificial-Intelligence-Based Dental Image Analysis: A Systematic Review
Authors: Bonny Talal , Al Nassan Wafaa , Obaideen Khaled , Rabie Tamer , AlMallahi Maryam Nooman , Gupta Swati
Published: December 2024

Artificial intelligence (AI) has garnered significant attention in recent years for its potential to revolutionize healthcare, including dentistry. However, despite the growing body of literature on AI-based dental image analysis, challenges such as the integration of AI into clinical workflows, variability in dataset quality, and the lack of standardized evaluation metrics remain largely underexplored. This systematic review aims to address these gaps by assessing the extent to which AI technologies have been integrated into dental specialties, with a specific focus on their applications in dental imaging. A comprehensive review of the literature was conducted, selecting relevant studies through electronic searches from Scopus, Google Scholar, and PubMed databases, covering publications from 2018 to 2023. A total of 52 articles were systematically analyzed to evaluate the diverse approaches of machine learning (ML) and deep learning (DL) in dental imaging. This review reveals that AI has become increasingly prevalent, with researchers predominantly employing convolutional neural networks (CNNs) for detection and diagnosis tasks. Pretrained networks demonstrate strong performance in many scenarios, while ML techniques have shown growing utility in estimation and classification. Key challenges identified include the need for larger, annotated datasets and the translation of research outcomes into clinical practice. The findings underscore AI’s potential to significantly advance diagnostic support, particularly for non-specialist dentists, improving patient care and clinical efficiency. AI-driven software can enhance diagnostic accuracy, facilitate data sharing, and support collaboration among dental professionals. Future developments are anticipated to enable patient-specific optimization of restoration designs and implant placements, leveraging personalized data such as dental history, tissue type, and bone thickness to achieve better outcomes.
A Novel, Direct Matrix Solver for Supersonic Boundary Element Method Systems
Authors: Goates Cory , Hunsaker Douglas
Published: December 2024

For problems with very fine surface meshes, typically the most time-consuming step of a boundary element method (BEM, also called a panel method) is solving the final linear system of equations. Many have already studied how to efficiently solve the dense, asymmetric systems which arise in elliptic BEMs. However, this has not been studied for a supersonic aerodynamic BEM, for which the governing PDE is hyperbolic. Due to this hyperbolic character, the matrix equation which arises from a supersonic BEM has a large number of identically zero elements. But the resulting linear system of equations is also not sparse in the standard sense. Hence, the efficient solution of the linear system of equations arising in a supersonic BEM is here considered. A novel sorting algorithm is developed whereby the non-zero elements may be arranged into a useful structure with minimal cost. A novel direct solution method is developed here based on fast Givens rotations and the QR decomposition. This novel solver leverages the unique matrix structure to solve the supersonic system of equations more quickly than traditional direct methods. This novel method is then compared to other direct and iterative matrix solvers and is shown to be more robust than iterative solvers and more efficient than other direct solvers, with a computational time complexity of approximately O(N2.5).
D3-YOLOv10: Improved YOLOv10-Based Lightweight Tomato Detection Algorithm Under Facility Scenario
Authors: Li Ao , Wang Chunrui , Ji Tongtong , Wang Qiyang , Zhang Tianxue
Published: December 2024

Accurate and efficient tomato detection is one of the key techniques for intelligent automatic picking in the area of precision agriculture. However, under the facility scenario, existing detection algorithms still have challenging problems such as weak feature extraction ability for occlusion conditions and different fruit sizes, low accuracy on edge location, and heavy model parameters. To address these problems, this paper proposed D3-YOLOv10, a lightweight YOLOv10-based detection framework. Initially, a compact dynamic faster network (DyFasterNet) was developed, where multiple adaptive convolution kernels are aggregated to extract local effective features for fruit size adaption. Additionally, the deformable large kernel attention mechanism (D-LKA) was designed for the terminal phase of the neck network by adaptively adjusting the receptive field to focus on irregular tomato deformations and occlusions. Then, to further improve detection boundary accuracy and convergence, a dynamic FM-WIoU regression loss with a scaling factor was proposed. Finally, a knowledge distillation scheme using semantic frequency prompts was developed to optimize the model for lightweight deployment in practical applications. We evaluated the proposed framework using a self-made tomato dataset and designed a two-stage category balancing method based on diffusion models to address the sample class-imbalanced issue. The experimental results demonstrated that the D3-YOLOv10 model achieved an mAP0.5 of 91.8%, with a substantial reduction of 54.0% in parameters and 64.9% in FLOPs, compared to the benchmark model. Meanwhile, the detection speed of 80.1 FPS more effectively meets the demand for real-time tomato detection. This study can effectively contribute to the advancement of smart agriculture research on the detection of fruit targets.
Research Regarding the Influence of Some Technological Factors on the Productivity of Some Monoecious Hemp Varieties Cultivated at Agricultural Research and Development Station Secuieni in Romania
Authors: Buburuz Alexandra-Andreea , Naie Margareta , Mîrzan Oana , Popa Lorena-Diana , Enea Andreea
Published: December 2024

This paper aimed to study combinations of some monoecious hemp varieties created at A.R.D.S. Secuieni and evaluate the combined influence of the variety of hemp used, the distance between rows of hemp, and the application of the Secuieni method on seed production. The Secuieni method is a cultivation method for hemp seed that is suitable for mechanical harvesting with grain combined directly from fields. This method consists of reducing the height of plants below 2 m, increasing the field uniformity, increasing seed production (sometimes by over 50%), and reducing the seeding rate from 10–15 kg/ha to 4–5 kg/ha. An experiment was carried out within the Agricultural Research—Development Station Secuieni in an experimental field in the monoecious hemp breeding laboratory. The results obtained during 2019–2023 showed that the influence of the variety led to production increases of 276 Mg·ha−1, which were obtained by the Secuieni Jubileu variety compared to the control variety, Succesiv, which had a yield of 1808 Mg·ha−1. The distance between the rows generated seed yields with values between 1908 Mg·ha−1 and 1967 Mg·ha−1, with statistically insignificant differences. The use of the Secuieni method led to production increases with different degrees of significance compared to the control variant. When analyzing the influence of the interaction between the genotype and the distance between the rows, it was observed that the productions obtained varied between 1767 Mg·ha−1 (Succesiv × 50 cm) and 2121 Mg·ha−1 (Secuieni Jubileu × 70 cm). In the analyzed period, the yields oscillated between 1460 Mg·ha−1 (Zenit × uncut) and 2437 Mg·ha−1 (Secuieni × two cuttings). In the case of the interaction between the distances used and the cuttings applied, the obtained production values varied between 1458 Mg·ha−1 (50 cm × UC) and 2402 Mg·ha−1 (70 cm × c2). At the same time, in the case of the combined influence of the three experimental factors, the application of two cuttings, regardless of the variety and distance used, led to statistically assured production increases compared to the control variant (Succesiv × 50 CM × UC).
Genome-Wide Identification of Epidermal Pattern Factor (EPF) Gene Family in Potato and Functional Characterization of StEPF4 in Regulating Drought Stress
Authors: Qiao Run , Yang Jiangwei , Deng Yurong , Duan Xiaoqin , Li Xinxia , Zhu Fengjiao , Liu Mei , Mou Jiani , Zhang Ning , Si Huaijun
Published: December 2024

Plants require adequate water for growth, development, and reproduction. Peptides play a key role in plant growth and development and act in a similar manner to plant hormones. However, only a few peptides have been identified to play a role in abiotic stress tolerance in potato. In this study, we identified fourteen members of the epidermal patterning factor (EPF) family in potato, which were designated as StEPF1-14 according to their chromosomal locations. We also conducted a comprehensive analysis of their chromosomal distribution, gene structures, physicochemical properties, phylogenetic relationships, and tissue-specific expression patterns. RT-qPCR analysis revealed that the StEPF4 gene is significantly induced by drought stress, suggesting its potential role as a negative regulator in the plant’s response to drought. Furthermore, multiple cis-regulatory elements associated with drought-responsive regulation were identified within the promoter region of the StEPF genes. Here, we isolated an EPF secreted Cys-rich small peptide StEPF4 from ‘Atlantic’ and explored its mechanism in plant response to drought stress. We found that StEPF4 was greatly induced by dehydration treatment in potato. To investigate its potential biological functions, StEPF4 was knocked down in potato. The StEPF4 knocked down lines (KdStEPF4) significantly decreased stomatal density, resulting in a decrease in the transpiration rate. KdStEPF4 lines maintained a higher photosynthetic rate and lowered the water loss rate of leaves compared with the control, resulting in increased drought resistance. Taken together, this study provides detailed information about StEPFs, and our findings also show that StEPF4 plays an essential role in regulating drought resistance by reducing stomatal density in potato.
Foliar Application of Urea and Amino Acids Regulates Growth, Photosynthesis, Pigments, Antioxidant Activity, and the Essential Oil Content and Composition of Basil (Ocimum basilicum L.)
Authors: Jahanbani Saeedeh , Mumivand Hasan , Zahedi Bahman , Argento Sergio
Published: December 2024

Basil (Ocimum basilicum L.) is a prominent medicinal and aromatic plant, widely recognized for its bioactive compounds and substantial economic value across the pharmaceutical, culinary, and industrial sectors. In light of increasing global demand and environmental challenges, this study explores novel approaches to enhance its sustainable production and improve its quality. Urea is the most common form of nitrogen (N) for foliar application due to its quick absorption, affordability, high solubility, as well as relatively low cost per N unit. Amino acids are an organic form of N and play a role in plant protein structure, stress tolerance, and the biosynthesis of secondary metabolites. This research aimed to evaluate the effects of urea (0, 1, and 2 g L−1) and an amino acid-based biostimulant (AAB) (0, 4, and 8 mg L−1), applied foliarly, on the growth, photosynthesis, pigments, antioxidant activity, and essential oil production of basil (Ocimum basilicum L.). The best results in terms of leaf number, area, and fresh and dry weight were observed with the combination of 2 g L−1 urea and 8 mg L−1 AAB. The growth enhancement due to this treatment may be attributed to stimulatory effects on photosynthesis and N content. Chlorophyll, carotenoids, anthocyanins, photosynthesis, stomatal conductance, total phenols, and total flavonoids increased with urea application up to 1 g L−1. Additionally, AAB application up to 8 mg L−1 increased total chlorophyll, carotenoid, total phenols, and total flavonoids, while photosynthesis and anthocyanin content increased with 4 mg L−1 AAB. Although urea did not significantly affect essential oil content and yield, AAB application increased both. Finally, the combination of 1 g L−1 urea and 8 mg L−1 AAB had the most effective impact on improving content and yield of essential oil, total phenol, flavonoid, anthocyanin, and antioxidant activity, with a relatively high percentage of estragole.
Association of Small HDL Subclasses with Mortality Risk in Chronic Kidney Disease
Authors: Stadler Julia T. , Borenich Andrea , Pammer Anja , Emrich Insa E. , Habisch Hansjörg , Madl Tobias , Heine Gunnar H. , Marsche Gunther
Published: December 2024

High-density lipoproteins (HDL) exist in various subclasses, with smaller HDL particles possessing the highest anti-oxidative and anti-inflammatory properties. Understanding the role of these specific subclasses in chronic kidney disease (CKD) could provide valuable insights into disease progression and potential therapeutic targets. In the present study, we assessed HDL subclass composition in 463 patients with CKD stage 2–4 using nuclear magnetic resonance spectroscopy. Over a mean follow-up period of 5.0 years, 18.6% of patients died. Compared to survivors, deceased patients exhibited significantly lower levels of cholesterol, ApoA-I, and ApoA-II within the small and extra-small (XS) HDL subclasses. Multivariable Cox regression analysis, adjusted for traditional cardiovascular and renal risk factors, demonstrated that reduced levels of XS-HDL-cholesterol, XS-HDL-ApoA-I, and XS-HDL-ApoA-II were independently associated with an increased risk of mortality. Furthermore, receiver operating characteristic analysis identified XS-HDL-ApoA-II as the most potent prognostic marker for mortality. In conclusion, reduced small and XS-HDL subclasses, especially XS-HDL-ApoA-II, are strongly associated with increased all-cause mortality risk in CKD patients. Assessment of HDL subclass distribution could provide valuable clinical information and help identify patients at high risk.
Genetic and Functional Changes in Mitochondria in the Pituitary Adenoma: The Pathogenesis and Its Therapy
Authors: Wu Hansen , Xu Jie , Zhao Wenxuan , Lv Weiqiang , Feng Zhihui , Heng Lijun
Published: December 2024

Pituitary adenoma is a common neoplasm of the pituitary gland. Although most pituitary adenomas are benign, they can pose significant challenges in terms of their consequences and prognosis due to their tendency to invade surrounding tissues and their effects on hormone secretion. The management of pituitary adenomas typically involves surgery, medical therapy, and radiotherapy, each of which has its own limitations. Mitochondria play a crucial role in tumor development and progression by regulating various metabolic processes and signaling pathways within tumor cells and the tumor microenvironment. Multiple studies have indicated that mitochondrial dysfunction is implicated in human pituitary adenomas. Furthermore, several compounds with therapeutic effects on pituitary adenomas have been reported to target mitochondrial function. In this review, we summarize recent studies that highlight the involvement of mitochondrial homeostasis imbalance in the biology of pituitary adenomas. We conclude that mitochondria may represent a promising therapeutic target for the treatment of pituitary adenomas.
On Transient Stability Problems in DC Microgrids
Authors: Niu Decun , Wang Ziyang , Chen Minghao , Fang Jingyang
Published: December 2024

Transient stability, i.e., the ability of power systems to maintain synchronism when subjected to a severe disturbance, has extensively been investigated in AC grids. This article reveals that similar transient stability problems (but with different features) also exist in DC microgrids, as caused by the violation of power-transfer limitations between DC generators and grids. Through rigorous theoretical analysis and experimental validation, this article advances the field by establishing a comprehensive analytical framework that derives the equilibrium points, power-absorption limitations, and stable conditions of proportional–integral (PI) power-controlled and droop-controlled DC generators. The methodology combines small-signal stability analysis with large-signal nonlinear analysis to characterize the system dynamics under different control strategies. Our key findings demonstrate that droop-controlled generators benefit from better transient stability due to their enlarged stable operating region and enhanced robustness against voltage disturbances, which is particularly valuable for improving the reliability of renewable energy integration in DC microgrids. The theoretical analysis is comprehensively verified through experimental results using a prototype DC microgrid test platform.
One Shoe to Fit Them All? Effect of Various Carbon Plate Running Shoes on Running Economy in Male and Female Amateur Triathletes and Runners at Individual Training and Race Paces
Authors: Riedl Marlene , von Diecken Carlo , Ueberschär Olaf
Published: December 2024

Carbon plate running shoes (CPRSs) have gained widespread popularity among elite and amateur runners, representing one of the most substantial changes in running gear over the past decade. Compared to elite runners, however, amateurs run at lower speeds and show more diverse running styles. This is a meaningful difference as many previous studies on CPRSs focus either on highly trained male runners and higher speeds or only on a single CPRSs manufacturer. The present study aims at bridging this gap by investigating how CPRSs from four different manufacturers affect running economy in amateurs of both sexes at their individual running speeds. For this purpose, 21 trained amateur triathletes (12 men; 9 women) completed an incremental treadmill test until volitional exhaustion, yielding running speeds at ventilatory thresholds 1 (vVT1) and 2 (vVT2). In a second session, subjects ran five trials of 3 × 3 min (speeds of 90% vVT1, ½ (vVT1 + vVT2), and 100% vVT2), wearing one out of four different pairs of CPRSs or their own preferred non-CPRS shoes in each trial. Our results show that tested CPRS models resulted in a significant reduction in the mean energy cost of transport, compared to the non-CPRS control condition, with Cohen’s d amounting to −1.52 (p = 0.016), 2.31 (p < 0.001), 2.57 (p < 0.001), and 2.80 (p < 0.001), respectively, although effect sizes varied substantially between subjects and running speeds. In conclusion, this study provides evidence that amateur athletes may benefit from various manufacturers’ CPRS models at their typical running speeds to a similar degree as highly trained runners. It is recommended that amateur athletes evaluate a range of CPRSs and select the shoe that elicits the least subjective sensation of fatigue over a testing distance of at least 400–1000 m.
Complex Battery Storage Fire Propagation Translational Forensic Study Using Cellular Automata
Authors: Roghani Soroush , Braxtan Nicole L. , Chen Shen-En , Zhao Tiefu , Bombik Anthony , Huhn Eric , Lin Karl , Coe Corbin
Published: December 2024

The surge in lithium-ion battery (LIB) use, essential for mass-scale renewable energy storage, raises concerns about fire hazards. However, to date, there is a lack of industry-wide understanding of large-scale LIB fire propagation. This paper suggests a translational forensic approach to promote fire safety awareness and introduces the cellular automata (CA) model coupled with the Monte Carlo (MC) approach to address the complex fire propagation simulation within an energy storage system (ESS). The objective is to demonstrate that the CA-MC model can provide a flexible and scalable connection for all levels of battery fire studies. The numerical model is coupled with experimental tests which have been performed to establish the actual timing of fire propagation from a single source. Cellular automata simulation, conducted through hybrid modeling and an applied risk analysis approach to evaluate fire hazards associated with LIBs, offers crucial insights into potential risks. The results demonstrate that, with fire incident initiation at a probability of 0.1 (10%), 33% of batteries will burn, and at a probability of 0.6 (60%) and beyond, the entire battery module will face complete burndown. Achieving full combustion of the entire module will take only approximately 42 timesteps on average, indicating rapid fire propagation. The actual time for a complete fire to occur in the battery module has been estimated to be 304 s per timestep, or 3.5 h total. Using this example, it is shown that the CA-MC approach can be extended to many other aspects of battery fire studies and is ideal as a translational tool, spanning all domains of the LIB industry.
MSP U-Net: Crack Segmentation for Low-Resolution Images Based on Multi-Scale Parallel Attention U-Net
Authors: Kim Joon-Hyeok , Noh Ju-Hyeon , Jang Jun-Young , Yang Hee-Deok
Published: December 2024

As the expected lifespans of structures and road approaches, as well as the importance of road maintenance, increase globally, safety inspections have emerged as a crucial task. Nonetheless, the existing crack detection models focus on multi-scale feature loss and performance degradation in learning various types of cracks. We propose the Multi-Scale Parallel Attention U-Net (MSP U-Net) as a network designed for low-resolution images that considers the irregular characteristics of cracks. MSP U-Net applies a large receptive field flock to an attention U-Net, minimizing feature loss across multiple scales. Using the Crack500 dataset, our network achieved a mean intersection of union (mIoU) of 0.7752, outperforming the existing methods on low-resolution images.
Modeling the Conditions of Occurrence and State of Radial Cracks in Rock Specimens Under Axial Compression with Lateral Pressure
Authors: Shekov Vitali , Kolesnikov Gennady
Published: December 2024

This paper presents a model for predicting the thickness of the cracked surface layer in rock specimens subjected to axial compression with lateral pressure. The study focuses on radial cracks that are most prominently open on the lateral surface, manifesting as axial (or longitudinal) cracks on this surface. The research employs methods for analyzing mechanical and geotechnical systems. The proposed model determines the conditions under which damage to the surface layer decreases depending on Poisson’s ratio and lateral pressure. Radial cracks typically precede spalling, making it crucial to examine the conditions of their initiation and the potential for influencing their development, and this holds significant importance for mining and underground construction practices. A comparison indicated that the predicted values and those reported in the literature for the thickness of the damaged surface layer in rock pillars are within a similar range, varying from 44% to 70% of the initial cross-sectional radius. Although this study focuses on rock materials, the proposed model also offers potential applications in examining crack formation in cement and geopolymer concretes, serving as artificial analogs of rock, thereby helping to mitigate the risk of structural failure in building systems.
Smart Poly(acrylic acid)/Poly(acrylamide) Microgels with Interpenetrating Polymer Network Structure
Authors: Simeonov Marin , Shestakova Pavletta , Boye Susanne , Lederer Albena , Vassileva Elena
Published: December 2024

Microgels with precisely tuned properties are of great importance as drug delivery systems. Here, we report the synthesis of microgel particles (MGs) with an interpenetrating polymer network structure composed of poly(acrylic acid) (PAA) and polyacrylamide (PAAM) for their potential application as cationic drug carriers. The MG properties were investigated via several analytical techniques, such as Dynamic Light Scattering (DLS) and zeta potential (ZP) measurements, Diffusion Nuclear Magnetic Resonance (NMR) spectroscopy, Asymmetrical Flow Field-Flow Fractionation (AF4) and Transmission Electron Microscopy (TEM). The MGs show pH-dependent swelling behavior with a radius of ~100 nm at collapsed state (pH < 4.5) and swell up to ~450 nm (pH~7), while their ZP decreases from −5 to −40 mV, depending on their composition. The results of the conducted studies demonstrate the potential of synthesized microgels for drug delivery in the gastrointestinal tract.
Assessment of Simplified Rating Factor Methodology for Shallow Cover Metal Culverts
Authors: Liu Bujing , Anderson Brian J. , Davidson James S.
Published: December 2024

Culverts under existing roadways that do not meet current design and construction cover requirements are common. Even though they may have performed without any issues for decades, rating many of them using today’s specifications and methodologies will result in a score that represents insufficiency, thus requiring the owner to replace or post the culvert. While advanced analyses, such as nonlinear finite element modeling and load testing, can be used to rate culverts with better accuracy than typical simplified calculations, those approaches are costly and require a high level of expertise. Therefore, simplified approaches to load rating shallow buried corrugated metal culverts that emphasize the available resistance of the structure rather than automatically rendering a rating that defines the structure as insufficient when the design cover requirement is not satisfied are developed and assessed herein. The accuracy and applicability of the methodology are demonstrated using finite element results from a two-dimensional finite element software developed specifically for culvert analysis and design.
Application of Isotope Geochemistry in Determining the Extraction Ratio of Target CBM from Multi-Seams
Authors: Ding Hong , Wen Guangcai , Long Qingming
Published: December 2024

In most coal mines in China, the target coalbed methane (CBM) and its adjacent CBM generally require joint extraction before the target coalbed can be mined. But only the mixed CBM from multi-seams can be measured at the mouth of boreholes, and it is not possible to individually measure the CBM from a target coalbed. In view of this issue, the application of isotope geochemistry is proposed for the first time in the industry. Based on the law of mass conservation for the chemical composition of mixed CBM, according to the gas components and isotope difference characteristics of each coalbed in multi-seams, a calculation model for the extraction ratio from a target coalbed is established. Field experiments were selected in the Xiaotun Mine in Guizhou Province. The extraction ratio of the target coalbed 6m determined by isotope geochemistry ranged from 57.81% to 69.58%, and the deviation from the extraction ratio determined by the measured flow method was less than 7%. The residual gas content of the No. 14 mining face was calculated by combining the results of the above two methods, and the deviation from the measured residual gas content was less than 6%, indicating that the results obtained scientifically by isotope geochemistry were reliable. The results of the study can provide a new research tool for the judgment of target CBM extraction standards and, ultimately, ensure the safety of coal mine operation.
Enhancing Safety of Navigation: Redesigning Precautionary Areas into Roundabouts in Marine Traffic Separation Schemes
Authors: Bokau Joe Ronald Kurniawan , Camliyurt Gokhan , Priadi Antoni Arif , Park Youngsoo , Kim Daewon
Published: December 2024

Roundabouts are widely used in road transport to improve traffic flow and reduce congestion by enabling continuous movement in a circular pattern, minimizing stops, enhancing safety, and reducing delays compared to that of signaled intersections. However, roundabouts are rarely used in marine traffic. This study investigates the feasibility of redesigning existing rectangular precautionary areas within traffic separation schemes (TSSs) into circular roundabouts using marine traffic data incorporating both the number of ships passing and crossing, as well as microscopic movement data to further analyze the follow-up times and gaps based on ship domains. This study further assesses the overall performance of the proposed design, drawing on notable formulas and best practices in road transport. The Lombok Strait TSS, in Indonesia, is used as the study area, which is a particularly sensitive sea area and one of the critical “chokepoints” in the maritime supply chain. The results indicate that replacing rectangular areas with circular roundabouts in a TSS can significantly improve traffic management and navigation safety. This study offers a practical approach for redesigning rectangular precautionary areas into circular roundabouts and provides valuable insights for maritime authorities and policymakers aiming to develop more efficient TSS designs in the future.
A Critical Look at Density Functional Theory in Chemistry: Untangling Its Strengths and Weaknesses
Authors: Zois Konstantinos P. , Tzeli Demeter
Published: December 2024

Density functional theory (DFT) is a commonly used methodology favored by experts and non-experts alike. It is a useful tool for the investigation of atomic, molecular and surface systems, offering an efficient and often reliable approach to calculate ground state properties such as electron density, total energy and molecular structure. However, fundamental issues are not rare. Of course, no one can really question the bold impact of DFT on modern chemical science. It is not only the way research is conducted that has been influenced by DFT, but also textbooks, datasets and our chemical intuition as well. In this review, issues pertaining to DFT are discussed, and it is pointed out that without a clear understanding of why we use calculations, an effective combination of experiment and theory will never be accomplished. Using low-level theoretical frameworks surely does not shed light on profound problems. To excel in our scientific field and make good use of our tools, we must very carefully decide which methodologies we are to employ.
Many-Body Effects in a Composite Bosonic Josephson Junction
Authors: Haldar Sudip Kumar , Bhowmik Anal
Published: December 2024

In standard bosonic Josephson junctions (BJJs), particles tunnel between two single-well potentials linked by a finite barrier. The dynamics of standard BJJs have been extensively studied, both at the many-body and mean-field levels of theory. In the present work, we introduce the concept of a composite BJJ. In a composite BJJ, particles tunnel between two double-well potentials linked by a finite potential barrier between them. We focused on the many-body facets of quantum dynamics and investigate how the complex structure of the junction influences the tunneling. Employing the multiconfigurational time-dependent Hartree method for bosons, highly accurate many-boson wavefunctions were obtained, from which properties were computed. We analyzed the dynamics using the survival probability, the degree of fragmentation of the junction, and the fluctuations of the observables, and discuss how the many-boson tunneling behaved, and how it may be controlled, using the composite nature of the junction. A central result of this work relates to the degree of fragmentation of composite BJJs with different numbers of bosons. We provide strong evidence that a universal degree of fragmentation into multiple time-dependent modes takes place. Further applications are briefly discussed.
Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications
Authors: Rajendran Jegan , Wilson Sukumari Nimi , Jose P. Subha Hency , Rajendran Manikandan , Saikia Manob Jyoti
Published: December 2024

A battery-operated biomedical wearable device gradually assists in clinical tasks to monitor patients’ health states regarding early diagnosis and detection. This paper presents the development of a self-powered portable electronic module by integrating an onboard energy-harvesting facility for electrocardiogram (ECG) signal processing and personalized health monitoring. The developed electronic module provides a customizable approach to power the device using a lithium-ion battery, a series of silicon photodiode arrays, and a solar panel. The new architecture and techniques offered by the developed method include an analog front-end unit, a signal processing unit, and a battery management unit for the acquiring and processing of real-time ECG signals. The dynamic multi-level wavelet packet decomposition framework has been used and applied to an ECG signal to extract the desired features by removing overlapped and repeated samples from an ECG signal. Further, a random forest with deep decision tree (RFDDT) architecture has been designed for offline ECG signal classification, and experimental results provide the highest accuracy of 99.72%. One assesses the custom-developed sensor by comparing its data with those of conventional biosensors. The onboard energy-harvesting and battery management circuits are designed with a BQ25505 microprocessor with the support of silicon photodiodes and solar cells which detect the ambient light variations and provide a maximum of 4.2 V supply to enable the continuous operation of an entire module. The measurements conducted on each unit of the proposed method demonstrate that the proposed signal-processing method significantly reduces the overlapping samples from the raw ECG data and the timing requirement criteria for personalized and wearable health monitoring. Also, it improves temporal requirements for ECG data processing while achieving excellent classification performance at a low computing cost.
Identifying Significant SNPs of the Total Number of Piglets Born and Their Relationship with Leg Bumps in Pigs
Authors: Bakoev Siroj , Getmantseva Lyubov , Kolosova Maria , Bakoev Faridun , Kolosov Anatoly , Romanets Elena , Shevtsova Varvara , Romanets Timofey , Kolosov Yury , Usatov Alexander
Published: December 2024

The aim of this study was to identify genetic variants and pathways associated with the total number of piglets born and to investigate the potential negative consequences of the intensive selection for reproductive traits, particularly the formation of bumps on the legs of pigs. We used genome-wide association analysis and methods for identifying selection signatures. As a result, 47 SNPs were identified, localized in genes that play a significant role during sow pregnancy. These genes are involved in follicle growth and development (SGC), early embryonic development (CCDC3, LRRC8C, LRFN3, TNFRSF19), endometrial receptivity and implantation (NEBL), placentation, and embryonic development (ESRRG, GHRHR, TUSC3, NBAS). Several genes are associated with disorders of the nervous system and brain development (BCL11B, CDNF, ULK4, CC2D2A, KCNK2). Additionally, six SNPs are associated with the formation of bumps on the legs of pigs. These variants include intronic variants in the CCDC3, ULK4, and MINDY4 genes, as well as intergenic variants, regulatory region variants, and variants in the exons of non-coding transcripts. The results suggest important biological pathways and genetic variants associated with sow fertility and highlight the potential negative impacts on the health and physical condition of pigs.
Dysregulation of MiR-21, MiR-221 and MiR-451 During Neoadjuvant Treatment of Breast Cancer: A Prospective Study
Authors: Patury Carine Bispo , Santos Brenda Luanny Maia , Matos Anna Lucia Carvalho , Slabi José , Gastalho Luciene Cristina Campos , Kaneto Carla Martins
Published: December 2024

Background: Breast cancer is highly heterogeneous disease in which different responses are observed to the same treatment for different subtypes and extents of similar diseases. Considering this scenario, the search for tumor biomarkers is indispensable, with current evidence suggesting that circulating microRNAs are viable biomarkers. This study evaluated the expression of miR-21, miR-221, miR-195, and miR-451 in patients with breast cancer undergoing neoadjuvant treatment at oncology outpatient facilities in Brazil. Methods: We conducted a prospective and observational study in which blood samples were collected for microRNA expression analysis, comparing control and breast cancer patients who were candidates for neoadjuvant treatment groups. The expression of microRNAs was investigated by qRT-PCR method. For parametric data analysis, one-way ANOVA with Tukey’s post hoc test was used. Results: Thirty-three participants (all female) were included in the control group and twenty-seven participants were included in the study group. The non-special subtype of breast cancer was found in 96% of the study group participants; 88.9% were locally advanced tumors (T3, T4), 40.7% were luminal tumors, 33.3% were HER-2-positive, and 26% were triple negative tumors. Expression analysis of microRNAs during neoadjuvant treatment, using miR-16 as a normalizer, showed higher expression levels of miR-21 and miR-221 at the end of treatment, and high expression levels for miR-451 were also observed at the beginning of treatment. Conclusion: This is the first study that evaluates the expression of microRNAs in the context of neoadjuvant treatment of breast cancer in the Brazilian population. Our results suggest that there is a deregulation of miR-21, miR-221, and miR-451 during neoadjuvant treatment in these patients.
The VEGFA rs2010963 Gene Polymorphism Is a Potential Genetic Risk Factor for Myocardial Infarction in Slovenian Subjects with Type 2 Diabetes Mellitus
Authors: Grbić Emin , Letonja Jernej , Petrovič Danijel
Published: December 2024

Coronary artery disease (CAD) is a life-threatening condition caused by the chronic gradual narrowing of the lumen of the blood vessels of the heart by atherosclerotic plaque with a strong genetic component. The aim of our study was to investigate the association between the VEGFA polymorphism rs2010963 and myocardial infarction in patients with type 2 diabetes, as well as the expression of VEGFA. A total of 1589 unrelated Caucasians with T2DM lasting longer than 10 years were divided into two groups: case group subjects with MI (484) and a control group without a history of CAD (1105). A total of 25 endarterectomy sequesters were immunohistochemically stained to assess VEGFA expression. The rs2010963 polymorphism of the VEGFA gene was genotyped using a KBioscience Ltd. competitive allele-specific fluorescence-based PCR (KASPar) assay. The C allele was significantly more common in the case group according to the dominant model of inheritance (CC + CG vs. GG) (OR: 1.32; 95% CI: 1.05–1.66; p = 0.0197). A statistically significantly higher numerical areal density of VEGFA-positive cells was found in subjects with the C allele (CC + CG genotypes) in comparison to the GG genotype (117 ± 35/mm2 vs. 58 ± 21/mm2; p < 0.001). To conclude, the rs2010963 polymorphism is a potential genetic risk factor for myocardial infarction in Slovenian patients with T2DM.
Mucins as Precision Biomarkers in Glioma: Emerging Evidence for Their Potential in Biospecimen Analysis and Outcome Prediction
Authors: Erickson Anna , Jackson Luke R. , Camphausen Kevin , Krauze Andra V.
Published: December 2024

Despite attempts at improving survival by employing novel therapies, progression in glioma is nearly universal. Precision biomarkers are critical to advancing outcomes; however, biomarkers for glioma are currently unknown. Most data on which the field can draw for biomarker identification comprise tissue-based analysis requiring the biospecimen to be removed from the tumor. Non-invasive specimen-based precision biomarkers are needed. Mucins are captured in tissue and blood and are increasingly studied in cancer, with several studies exploring their role as biomarkers to detect disease and monitor disease progression. CA125, also known as MUC16, is implemented as a biomarker in the clinic for ovarian cancer. Similarly, several mucins are membrane-bound, facilitating downstream signaling associated with tumor resistance and hallmarks of cancer. Evidence supports mucin expression in glioma cells with relationships to tumor detection, progression, resistance, and patient outcomes. The differential expression of mucins across tissues and organs could also provide a means of attributing signals measured in serum or plasma. In this review, we compiled existing research on mucins as candidate precision biomarkers in glioma, focusing on promising mucins in relationship to glioma and leading to a framework for mucin analysis in biospecimens as well as avenues for validation as data evolve.
Machine Learning Model Discriminate Ischemic Heart Disease Using Breathome Analysis
Authors: Marzoog Basheer Abdullah , Chomakhidze Peter , Gognieva Daria , Gagarina Nina Vladimirovna , Silantyev Artemiy , Suvorov Alexander , Fominykha Ekaterina , Mustafina Malika , Natalya Ershova , Gadzhiakhmedova Aida , Kopylov Philipp
Published: December 2024

Background: Ischemic heart disease (IHD) impacts the quality of life and is the most frequently reported cause of morbidity and mortality globally. Aims: To assess the changes in the exhaled volatile organic compounds (VOCs) in patients with vs. without ischemic heart disease (IHD) confirmed by stress computed tomography myocardial perfusion (CTP) imaging. Objectives: IHD early diagnosis and management remain underestimated due to the poor diagnostic and therapeutic strategies including the primary prevention methods. Materials and Methods: A single center observational study included 80 participants. The participants were aged ≥ 40 years and given an informed written consent to participate in the study and publish any associated figures. Both groups, G1 (n = 31) with and G2 (n = 49) without post stress-induced myocardial perfusion defect, passed cardiologist consultation, anthropometric measurements, blood pressure and pulse rate measurements, echocardiography, real time breathing at rest into PTR-TOF-MS-1000, cardio-ankle vascular index, bicycle ergometry, and immediately after performing bicycle ergometry repeating the breathing analysis into the PTR-TOF-MS-1000, and after three minutes from the end of the second breath, repeat the breath into the PTR-TOF-MS-1000, then performing CTP. LASSO regression with nested cross-validation was used to find the association between the exhaled VOCs and existence of myocardial perfusion defect. Statistical processing performed with R programming language v4.2 and Python v.3.10 [^R], STATISTICA program v.12, and IBM SPSS v.28. Results: The VOCs specificity 77.6% [95% confidence interval (CI); 0.666; 0.889], sensitivity 83.9% [95% CI; 0.692; 0.964], and diagnostic accuracy; area under the curve (AUC) 83.8% [95% CI; 0.73655857; 0.91493173]. Whereas the AUC of the bicycle ergometry 50.7% [95% CI; 0.388; 0.625], specificity 53.1% [95% CI; 0.392; 0.673], and sensitivity 48.4% [95% CI; 0.306; 0.657]. Conclusions: The VOCs analysis appear to discriminate individuals with vs. without IHD using machine learning models. Other: The exhaled breath analysis reflects the myocardiocytes metabolomic signature and related intercellular homeostasis changes and regulation perturbances. Exhaled breath analysis poses a promise result to improve the diagnostic accuracy of the physical stress tests using machine learning models.
Recent Advances in Alzheimer’s Disease Research: From Biomarkers to Therapeutic Frontiers
Authors: López-Antón Raúl
Published: December 2024

At this moment in time, Alzheimer’s disease (AD) remains one of the most pressing public health problems [...]
Biomimetic Strategies of Slip Sensing, Perception, and Protection in Prosthetic Hand Grasp
Authors: Xie Anran , Zhang Zhuozhi , Zhang Jie , Li Tie , Chen Weidong , Patton James , Lan Ning
Published: December 2024

This study develops biomimetic strategies for slip prevention in prosthetic hand grasps. The biomimetic system is driven by a novel slip sensor, followed by slip perception and preventive control. Here, we show that biologically inspired sensorimotor pathways can be restored between the prosthetic hand and users. A Ruffini endings-like slip sensor is used to detect shear forces and identify slip events directly. The slip information and grip force are encoded into a bi-state sensory coding that evokes vibration and buzz tactile sensations in subjects with transcutaneous electrical nerve stimulation (TENS). Subjects perceive slip events under various conditions based on the vibration sensation and voluntarily adjust grip force to prevent further slipping. Additionally, short-latency compensation for grip force is also implemented using a neuromorphic reflex pathway. The reflex loop includes a sensory neuron and interneurons to adjust the activations of antagonistic muscles reciprocally. The slip prevention system is tested in five able-bodied subjects and two transradial amputees with and without reflex compensation. A psychophysical test for perception reveals that the slip can be detected effectively, with a success accuracy of 96.57%. A slip protection test indicates that reflex compensation yields faster grasp adjustments than voluntary action, with a median response time of 0.30 (0.08) s, a rise time of 0.26 (0.03) s, an execution time of 0.56 (0.07) s, and a slip distance of 0.39 (0.10) cm. Prosthetic grip force is highly correlated to that of an intact hand, with a correlation coefficient of 96.85% (2.73%). These results demonstrate that it is feasible to reconstruct slip biomimetic sensorimotor pathways that provide grasp stability for prosthetic users.
How Social Situations Affect the Relationships Between Academic Emotional Suppression and Expression and Likability Among Adolescents
Authors: Liu Ying , Sang Biao , Chai Xiaoyun
Published: December 2024

Social situation is an important factor in determining whether or not individuals express emotions and how effectively they express them, but few researchers have explored its role (e.g., with others of varying degrees of intimacy and hierarchy) in the social outcomes of academic emotional suppression and expression. Relationships between the adolescents’ suppression and expression of emotions and their likability in social situations involving a range of people (e.g., classmates, good friends, teachers) were examined in the current study. A total of 120 adolescents and 74 teachers were selected for this investigation, the results indicating a difference in an individual’s likability when suppressing and expressing academic emotions in the presence of others. Specifically, expressing academic emotions in the presence of good friends achieves a higher level of likability than in the presence of classmates; furthermore, suppressing negative academic emotions in the presence of classmates garners a higher level of likability. Adolescents who express their positive and negative academic emotions in the presence of good friends can get higher likability. Teachers prefer adolescents who express positive academic emotions in their presence. These findings emphasize the importance of social situations in the use of strategies to regulate academic emotion regulation and verify the adaptability of emotional regulation.