bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomass from Allelopathic Agroforestry and Invasive Plant Species as Soil Amendments for Weed Control—A Review
Authors: Valiño Antía , Pardo-Muras María , Puig Carolina G. , López-Periago J. Eugenio , Pedrol Nuria
Published: November 2023

Effective weed management faces increasing legislative restrictions for the use of herbicides due to their toxicity and environmental persistence. In addition, the linear increase in resistant weeds threatens to render authorized herbicides useless. In a post-herbicide era, under the IWM strategy, allelopathy can play a relevant role since many plants can produce a variety of allelochemicals with different structures and modes of action, capable of inhibiting the germination and growth of different weed species. Inspired by green manuring with cover crops, the use of allelopathic biomass from weeds, invasive species, residues of forestry plantations, and other abundant wild plants has some advantages over green manures grown in situ or other alternatives such as applying plant extracts or essential oils. Beyond the ecosystem services provided by green manures, the potential use of allelopathic biomass offers extra opportunities for the science and practice of holistically integrated weed management because (i) the investment of resources and time for producing cover crops would be alleviated, and (ii), new use of agroforestry residues and a sink for harmful weed biomass is provided. In this review, we compile the current knowledge of those allelopathic species whose biomass, used as soil amendment, effectively controlled weeds. In addition, the complex allelopathic processes underlying the effectiveness of cover crops and allelopathic biomass used as green manures for weed control are revisited.
Study on the Effect of Oleic Acid-Induced Lipogenic Differentiation of Skeletal Muscle Satellite Cells in Yanbian Cattle and Related Mechanisms
Authors: Sun Bin , Sun Jianfu , Li Qiang , Wang Ying , Wang Enze , Jin Huaina , Hua Huan , Jin Qiyun , Li Xiangzi
Published: November 2023

Skeletal muscle satellite cells have the ability to differentiate into various cells under different conditions. This study aimed to investigate the effects of different concentrations of oleic acid (50, 100, and 200 µmol/L) on the process of lipogenic transdifferentiation in Yanbian bovine satellite cells, as well as its molecular regulatory mechanism. After inducing differentiation with oleic acid for 96 h, it was observed that the addition of oleic acid resulted in the formation of lipid droplets in the bovine satellite cells, and the triglyceride content showed a dose-dependent relationship with the concentration of OA. qPCR results demonstrated a significant downregulation of myogenesis-related factors (Pax3 and MyoD) and upregulation of lipogenesis-related factors (C/EBP-β and PPARγ) (p < 0.05). Fatty acid metabolism-related factors, SCD and PLIN2, were also significantly upregulated (p < 0.05). These finding were consistent with the results obtained from Western blotting. Transcriptome sequencing analysis identified 278 differentially expressed genes between the control group and the groups treated with OA. KEGG enrichment analysis showed that differentially expressed genes were mainly concentrated in the adenosine monophosphate-activated protein kinase signaling pathway and fatty acid metabolic pathway. Our study presents that the OA induction of Yanbian bovine skeletal muscle satellite cells can promote cellular lipid transdifferentiation and reveals the potential genes and pathways related to OA induction of these satellite cells.
Dietary Zinc-Loaded Montmorillonite Supplementation Improves Growth Performance, Diarrhea, Intestinal Barrier Function and Regulating Gut Microbiota in Weaned Piglets
Authors: Huang Mingxing , Yi Jiang , Chen Hua , Song Yuehui , Hu Xinyue , Zhou Hua , Zhu Nianhua
Published: November 2023

This experiment was conducted to investigate whether low-dose zinc-loaded montmorillonite (Zn-MMT) could be used as a potential alternative for high-dose conventional ZnO in preventing diarrhea in weaned piglets. In total, 180 piglets were randomly divided to receive either of the three treatments, with six replicates per treatment and 10 piglets per replicate. The treatments were the control group (CT), the Zn-MMT group (ZM), and the ZnO group (ZO). Compared with the CT group, the ZM and ZO groups exhibited increased ADG at 14–28 days and during the whole period (p < 0.05), and a significantly decreased diarrhea rate during the whole period (p < 0.01). The activities of T-AOC and SOD were significantly increased (p < 0.05), whereas the MDA level decreased (p < 0.05) in the serum and colonic mucosa of Zn-MMT- and ZnO-fed piglets. Dietary supplementation with Zn-MMT and ZnO decreased the contents of IFN-γ, TNF-α, IL-1β, IL-6, DAO, and LPS in the serum and colonic mucosa (p < 0.01), and increased the IL-10 level (p < 0.01). The relative mRNA expressions of TLR-4, claudin 2, Pbd1, and MUC2 were elevated in the colonic mucosa of the Zn-MMT and ZnO groups (p < 0.05). 16S rRNA gene sequencing analysis revealed that the abundances of Proteobacteria and Actinobacteria in the ileum and the populations of Ruminnococcus and Faecalibacterium in the cecum were higher in the CT group than in the other two groups. Collectively, dietary addition of Zn from Zn-MMT was comparable to Zn from ZnO for increasing growth performance, alleviating diarrhea, as well as improving mucosal barrier integrity, and regulating the gut microbiota of weaned piglets.
Utilization of Cottonseed Meal Protein Hydrolysate by Crustaceans: Insights on Growth Performance, Protein Turnover, and Metabolism in Chinese Mitten Crab Eriocheir sinensis
Authors: He Chaofan , Liu Wenbin , Zhang Ling , Chen Weiliang , Liu Zishang , Qian Xiangyu , Li Xiangfei
Published: November 2023

Plant protein hydrolysates could enhance the growth performance and diet utilization of aquaculture species. The mechanisms underlying their beneficial effects, however, remain unclear. The purpose of this study was to appraise the effects of cottonseed meal protein hydrolysate (CPH) supplementation on the growth performance, amino acid profiles, and protein turnover and metabolism of Eriocheir sinensis. A total of 240 crabs (initial weight: 37.32 ± 0.38 g) were randomly assigned to six groups, and fed six iso-protein feeds supplemented with varying levels of 0% (the control group), 0.2%, 0.4%, 0.8%, 1.6% and 3.2% of CPH. These diets were continuously fed to the crabs for 12 weeks. The findings demonstrated that, compared with the control group, adding 0.4–0.8% CPH to the diet significantly increased the specific growth rate, nitrogen retention efficiency, hepatopancreas index, body crude protein content, hepatopancreas alanine aminotransferase and glutamine synthetase activities, hemolymph total protein content, the hepatopancreas transcription of S6 kinase-poly-peptide 1, and the hepatopancreas protein levels of insulin-like growth factor-1 (IGF-1), protein kinase B (Akt), and target of rapamycin (TOR) of crabs. In contrast, when the dose of dietary CPH reached 3.2%, the forkhead box O1 (FoxO1) protein expression showed a significant decrease compared with the control group. In addition, CPH supplementation also increased the amount of amino acids and free amino acids in hepatopancreas and hemolymph, respectively. Together, these findings demonstrated that dietary supplementation of 0.4–0.8% CPH could activate the IGF-1/Akt/TOR pathway of E. sinensis, thereby improving growth performance, protein synthesis, and utilization. For cost considerations, the recommended dietary dose of CPH for E. sinensis is 0.8%. Due to the above benefits, CPH has the potential to be used as a growth promoter for other aquatic animals, especially crustaceans.
Antioxidant Capacity of Free and Bound Phenolics from Olive Leaves: In Vitro and In Vivo Responses
Authors: Li Ting , Wu Wenjun , Zhang Jianming , Wu Qinghang , Zhu Shenlong , Niu Erli , Wang Shengfeng , Jiang Chengying , Liu Daqun , Zhang Chengcheng
Published: November 2023

Olive leaves are rich in phenolic compounds. This study explored the chemical profiles and contents of free phenolics (FPs) and bound phenolics (BPs) in olive leaves, and further investigated and compared the antioxidant properties of FPs and BPs using chemical assays, cellular antioxidant evaluation systems, and in vivo mouse models. The results showed that FPs and BPs have different phenolic profiles; 24 free and 14 bound phenolics were identified in FPs and BPs, respectively. Higher levels of phenolic acid (i.e., sinapinic acid, 4-coumaric acid, ferulic acid, and caffeic acid) and hydroxytyrosol were detected in the BPs, while flavonoids, triterpenoid acids, and iridoids were more concentrated in the free form. FPs showed a significantly higher total flavonoid content (TFC), total phenolic content (TPC), and chemical antioxidant properties than those of BPs (p < 0.05). Within the range of doses (20–250 μg/mL), both FPs and BPs protected HepG2 cells from H2O2-induced oxidative stress injury, and there was no significant difference in cellular antioxidant activity between FPs and BPs. The in vivo experiments suggested that FP and BP treatment inhibited malondialdehyde (MDA) levels in a D-galactose-induced oxidation model in mice, and significantly increased antioxidant enzyme activity of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and the total antioxidant capacity (T-AOC). Mechanistically, FPs and BPs exert their antioxidant activity in distinct ways; FPs ameliorated D-galactose-induced oxidative stress injury partly via the activation of nuclear factor erythroid-2-related factor 2 (Nrf2) signaling pathway, while the BP mechanisms need further study.
Modulation of Kynurenic Acid Production by N-acetylcysteine Prevents Cognitive Impairment in Adulthood Induced by Lead Exposure during Lactation in Mice
Authors: Ovalle Rodríguez Paulina , Ramírez Ortega Daniela , Blanco Ayala Tonali , Roldán Roldán Gabriel , Pérez de la Cruz Gonzalo , González Esquivel Dinora Fabiola , Gómez-Manzo Saúl , Sánchez Chapul Laura , Salazar Aleli , Pineda Benjamín , Pérez de la Cruz Verónica
Published: November 2023

Lead (Pb2+) exposure during early life induces cognitive impairment, which was recently associated with an increase in brain kynurenic acid (KYNA), an antagonist of NMDA and alpha-7 nicotinic receptors. It has been described that N-acetylcysteine (NAC) favors an antioxidant environment and inhibits kynurenine aminotransferase II activity (KAT II, the main enzyme of KYNA production), leading to brain KYNA levels decrease and cognitive improvement. This study aimed to investigate whether the NAC modulation of the brain KYNA levels in mice ameliorated Pb2+-induced cognitive impairment. The dams were divided into four groups: Control, Pb2+, NAC, and Pb2++NAC, which were given drinking water or 500 ppm lead acetate in the drinking water ad libitum, from 0 to 23 postnatal days (PNDs). The NAC and Pb2++NAC groups were simultaneously fed NAC (350 mg/day) in their chow from 0 to 23 PNDs. At PND 60, the effect of the treatment with Pb2+ and in combination with NAC on learning and memory performance was evaluated. Immediately after behavioral evaluation, brain tissues were collected to assess the redox environment; KYNA and glutamate levels; and KAT II activity. The NAC treatment prevented the long-term memory deficit exhibited in the Pb2+ group. As expected, Pb2+ group showed redox environment alterations, fluctuations in glutamate levels, and an increase in KYNA levels, which were partially avoided by NAC co-administration. These results confirmed that the excessive KYNA levels induced by Pb2+ were involved in the onset of cognitive impairment and could be successfully prevented by NAC treatment. NAC could be a tool for testing in scenarios in which KYNA levels are associated with the induction of cognitive impairment.
Serum Arylesterase, Paraoxonase, and Lactonase Activities and Paraoxonase-1 Concentrations in Morbidly Obese Patients and Their Relationship with Non-Alcoholic Steatohepatitis
Authors: Castañé Helena , Jiménez-Franco Andrea , Martínez-Navidad Cristian , Placed-Gallego Cristina , Cambra-Cortés Vicente , Perta Adelina-Miruna , París Marta , Castillo Daniel del , Arenas Meritxell , Camps Jordi , Joven Jorge
Published: November 2023

Paraoxonase-1 (PON1) is an antioxidant enzyme associated with high-density lipoproteins (HDL). Reduced serum PON1 activity is found in diseases marked by oxidative stress and inflammation, but its role in obesity remains unclear. This study investigated PON1 activities and concentrations in morbidly obese individuals and explored the impacts of the genetic polymorphism PON1 rs662 and non-alcoholic fatty liver disease on enzymatic properties. We recruited 1349 morbidly obese patients undergoing bariatric surgery and 823 non-obese volunteers. PON1-related variables, including arylesterase, paraoxonase, and lactonase activities and PON1 concentrations, were examined. Our results showed that morbidly obese individuals exhibited higher PON1 concentrations but lower enzymatic activities than non-obese individuals. We observed inverse associations of arylesterase and paraoxonase activities with waist circumference (rho = −0.24, p < 0.001, and rho = −0.30, p < 0.001, respectively) and body mass index (rho = −0.15, p = 0.001, and rho = −0.23, p < 0.001), as well as direct associations of arylesterase, paraoxonase, and lactonase activities with HDL cholesterol (rho = 0.11, p = 0.005, rho = 0.20, p < 0.001, and rho = 0.20, p < 0.001). No significant differences were observed regarding metabolic syndrome, type 2 diabetes mellitus, hypertension, dyslipidemia, rs662 polymorphism allele frequencies, or the diagnosis of non-alcoholic steatohepatitis. Nevertheless, correlations were found between certain PON1-related variables, steatosis, and ballooning. In conclusion, changes in PON1-related variables in morbidly obese patients are dependent on the disease itself and HDL levels. The relationships between these variables and specific liver histological changes raise intriguing questions for consideration in future studies.
Capability Enhancing of CO2 Laser Cutting for PMMA Sheet Using Statistical Modeling and Optimization
Authors: Moradi Mahmoud , Rezayat Mohammad , Meiabadi Saleh , Karamimoghadam Mojtaba , Hillyard Stephen , Mateo Antonio , Casalino Giuseppe , Tanveer Zammad , Adnan Manzoor Muhammad , Iqbal Muhammad Asad , Razmkhah Omid
Published: November 2023

Laser cutting is a widely used manufacturing process, and the quality of the resulting cuts plays a crucial role in its success. This research employed the Design of Experiments (DOE) to investigate the impact of input process parameters on kerf quality during the laser cutting of 5 mm polymethyl methacrylate (PMMA) sheets. Response surface methodology (RSM) was utilized to model the relationship between the input parameters and the kerf quality, with regression equations developed for each response using the Design Expert software. A statistical analysis revealed the significant effects of high laser power, cutting speed, and focal plane position on kerf quality. Optimization, guided by the desirability function, identified optimal parameter combinations that offered the most favorable tradeoff among various responses. Optimal conditions were found to involve a high laser power, a cutting speed ranging from 4 to 7 mm/s, and a focal plane position at the center. Experiments indicated the suitability of the models for practical applications. An overlay plot analysis revealed a weak negative correlation between the laser power and the cutting speed, while the focal plane’s position could be adjusted independently.
Deep Learning Approach for Deduction of 3D Non-Rigid Transformation Based on Multi-Control Point Perception Data
Authors: Yan Dongming , Li Lijuan , Liu Yue , Lin Xuezhu , Guo Lili , Chao Shihan
Published: November 2023

In complex measurement systems, scanning the shape data of solid models is time consuming, and real-time solutions are required. Therefore, we developed a 3D non-rigid transformation deduction model based on multi-control point perception data. We combined a convolutional neural network (CNN), gated recurrent unit (GRU), and self-attention mechanism (SA) to develop the CNN-GRU-SA deduction network, which can deduce 3D non-rigid transformations based on multiple control points. We compared the proposed network to several other networks, with the experimental results indicating that the maximum improvements in terms of loss and root-mean-squared error (RMSE) on the training set were 39% and 49%, respectively; the corresponding values for the testing set were 48% and 29%. Moreover, the average deviation of the inference results and average inference time were 0.55 mm and 0.021 s, respectively. Hence, the proposed deep learning method provides an effective method to simulate and deduce the 3D non-rigid transformation processes of entities in the measurement system space, thus highlighting its practical significance in optimizing entity deformation.
Engineering and Sustainable Challenges: Latest Advances in Computing and Systemic Tools
Authors: Seck-Tuoh-Mora Juan Carlos , Lizárraga-Mendiola Liliana , Medina-Marín Joselito , Hernández-Romero Norberto
Published: November 2023

Modeling highly nonlinear, coupled systems with a large number of variables is a current challenge in engineering and sustainability [...]
Explainability of Automated Fact Verification Systems: A Comprehensive Review
Authors: Vallayil Manju , Nand Parma , Yan Wei Qi , Allende-Cid Héctor
Published: November 2023

The rapid growth in Artificial Intelligence (AI) has led to considerable progress in Automated Fact Verification (AFV). This process involves collecting evidence for a statement, assessing its relevance, and predicting its accuracy. Recently, research has begun to explore automatic explanations as an integral part of the accuracy analysis process. However, the explainability within AFV is lagging compared to the wider field of explainable AI (XAI), which aims at making AI decisions more transparent. This study looks at the notion of explainability as a topic in the field of XAI, with a focus on how it applies to the specific task of Automated Fact Verification. It examines the explainability of AFV, taking into account architectural, methodological, and dataset-related elements, with the aim of making AI more comprehensible and acceptable to general society. Although there is a general consensus on the need for AI systems to be explainable, there a dearth of systems and processes to achieve it. This research investigates the concept of explainable AI in general and demonstrates its various aspects through the particular task of Automated Fact Verification. This study explores the topic of faithfulness in the context of local and global explainability. This paper concludes by highlighting the gaps and limitations in current data science practices and possible recommendations for modifications to architectural and data curation processes, contributing to the broader goals of explainability in Automated Fact Verification.
Verification of Industrial Worker Walking Efficiency with Wearable Hip Exoskeleton
Authors: Chang Yunhee , Kang Jungsun , Jeong Bora , Kim Gyoosuk , Lim Bokman , Choi Byungjune , Lee Younbaek
Published: November 2023

In highly mobile workplaces, wearable walking-assistant devices reduce muscle fatigue in workers’ lower extremities and increase energy efficiency. In our study, we verify this following the development of an ultralight wearable hip exoskeleton for industrial workers. Ten healthy male adults participated in this study, and their muscle activity, muscle fatigue, and energy expenditure were compared with and without a device while walking on a treadmill and going up stairs. While walking on a treadmill with the assistive device, muscle fatigue in the gastrocnemius decreased by 79.5%, and oxygen uptake and energy expenditure per minute decreased by 7.9% and 7.4%, respectively. While climbing stairs with the assistive device, muscle fatigue of the tibialis anterior decreased by 83.5%, average muscle activity of the rectus femoris, semitendinosus, and gastrocnemius muscles decreased significantly, and oxygen uptake and energy expenditure decreased by 14% and 12.9% per minute, respectively. We confirm that an ultralight wearable hip exoskeleton helps the wearer reduce lower-limb muscle fatigue and use metabolic energy more efficiently. The results of this study are intended as basic data to expand the use of ultralight wearable hip exoskeletons at industrial sites and to improve device performance.
Electron Impact Cross Sections and Transport Studies of C3F6O
Authors: Sinha Nidhi , Song Mi-Young , Chang Hyonu , Choi Heechol , Jang Hyun-Jae , Oh Yeon-Ho , Song Ki-Dong
Published: November 2023

Electron impact scattering from C3F6O is studied in this work. The R-matrix method was used for the calculations of elastic, momentum transfer, and excitation cross sections. The attachment cross section was obtained through a parametric estimator based on the R-matrix outputs. The Binary-Encounter-Bethe (BEB) method was used for computing the ionization cross section. The obtained cross section set was used for the transport studies using the BOLSIG+ code, which is a two-term Boltzmann equation solver. The present calculation was performed for steady-state Townsend experimental conditions for E/N, covering a range of 100–1000 Td. The critical dielectric strength of pure C3F6O was found to be 475 Td, which is much greater than that of SF6 (355 Td). The effect of the addition of different buffer gases, such as CO2, N2, and O2, was also examined. For the C3F6O–CO2, C3F6O–N2, and C3F6O–O2 mixtures with 65%, 55%, and 60% C3F6O, respectively, the critical dielectric strength was determined to be essentially the same as that of pure SF6. The presence of synergism was confirmed for these gas mixtures. We further derived the Paschen curve using a fitting method with the transport parameters as the basic inputs. The minimum breakdown voltage of C3F6O accounted for only 55% of that of SF6. The buffer gas mixture improved the condition; however, the performance of CO2 and O2 mixtures was not satisfactory. The addition of N2 as the buffer gas significantly improved the breakdown property of the gas. The mixture of ≥99% of N2 or ≤1% of C3F6O gave a better breakdown characteristic than SF6. Any proportion ≥90% of N2 or ≤10% of C3F6O was suitable in the higher pressure ranges. The present work demonstrates the potential of C3F6O as a substitute gas for SF6 with a negligible environmental threat.
A Simplistic Downlink Channel Estimation Method for NB-IoT
Authors: Magiera Jarosław
Published: November 2023

This paper presents a downlink channel estimation method intended for a Narrowband Internet of Things (NB-IoT) access link. Due to its low computational complexity, this method is well suited for energy-efficient IoT devices, still providing acceptable reception quality in terms of signal-to-noise (SNR) performance. This paper describes the physical layer of NB-IoT within the scope of channel estimation, and also reviews existing channel estimation methods for OFDM signals. The proposed method, based on linear interpolation of channel coefficients, is described as a three-step procedure. Next, indicators of channel quality assessment, which may be determined without prior knowledge about the transmitted signal, are defined. Two variants of channel estimation, differing in the frequency domain processing, are evaluated to assess the significance of frequency selectivity in an NB-IoT downlink. The chosen method is compared with another method implemented in MATLAB LTE ToolboxTM. An analysis of the computation time is conducted, subsequently demonstrating the definite advantage of the proposed method.
φunit: A Lightweight Module for Feature Fusion Based on Their Dimensions
Authors: Long Zhengyu , Zhou Rigui , Li Yaochong , Ren Pengju , Yang Xue , Cai Shuo
Published: November 2023

With the popularity of mobile devices, lightweight deep learning models have important value in various application scenarios. However, how to effectively fuse the feature information from different dimensions while ensuring the model’s lightness and high accuracy is a problem that has not been fully solved. In this paper, we propose a novel feature fusion module, called φunit, which can fuse the features extracted by different dimensional networks according to the order of feature information with a small computational cost, avoiding the problems of information fragmentation caused by simple feature stacking in traditional information fusion. Based on φunit, this paper further builds an extremely lightweight model φNet, which can achieve performance close to the highest accuracy on several public datasets under the condition of very limited parameter scale. The core idea of φunit is to use deconvolution to reduce the discrepancy among the features to be fused, and to lower the possibility of feature information fragmentation after fusion by fusing the features from different dimensions sequentially. φNet is a lightweight network composed of multiple φunits and bottleneck modules, with a parameter scale of only 1.24 M, much smaller than traditional lightweight models. This paper conducts experiments on public datasets, and φNet achieves an accuracy of 71.64% on the food101 dataset, and an accuracy of 75.31% on the random 50-category food101 dataset, both higher than or close to the highest accuracy. This paper provides a new idea and method for feature fusion of lightweight models, and also provides an efficient model selection for deep learning applications on mobile devices.
Design of a Semantic Understanding System for Optical Staff Symbols
Authors: Lou Fengbin , Lu Yaling , Wang Guangyu
Published: November 2023

Symbolic semantic understanding of staff images is an important technological support to achieve “intelligent score flipping”. Due to the complex composition of staff symbols and the strong semantic correlation between symbol spaces, it is difficult to understand the pitch and duration of each note when the staff is performed. In this paper, we design a semantic understanding system for optical staff symbols. The system uses the YOLOv5 to implement the optical staff’s low-level semantic understanding stage, which understands the pitch and duration in natural scales and other symbols that affect the pitch and duration. The proposed note encoding reconstruction algorithm is used to implement the high-level semantic understanding stage. Such an algorithm understands the logical, spatial, and temporal relationships between natural scales and other symbols based on music theory and outputs digital codes for the pitch and duration of the main notes during performances. The model is trained with a self-constructed SUSN dataset. Experimental results with YOLOv5 show that the precision is 0.989 and that the recall is 0.972. The system’s error rate is 0.031, and the omission rate is 0.021. The paper concludes by analyzing the causes of semantic understanding errors and offers recommendations for further research. The results of this paper provide a method for multimodal music artificial intelligence applications such as notation recognition through listening, intelligent score flipping, and automatic performance.
Android Malware Detection Based on Hypergraph Neural Networks
Authors: Zhang Dehua , Wu Xiangbo , He Erlu , Guo Xiaobo , Yang Xiaopeng , Li Ruibo , Li Hao
Published: November 2023

Android has been the most widely used operating system for mobile phones over the past few years. Malicious attacks against android are a major privacy and security concern. Malware detection techniques for android applications are therefore significant. A class of methods using Function Call Graphs (FCGs) for android malware detection has shown great potential. The relationships between functions are limited to simple binary relationships (i.e., graphs) in these methods. However, one function often calls several other functions to produce specific effects in android applications, which cannot be captured with FCGs. In this paper, we propose to formalize android malware detection as a hypergraph-level classification task. A hypergraph is a topology capable of portraying complex relationships between multiple vertices, which can better characterize the functional behavior of android applications. We model android applications using hypergraphs and extract the embedded features of android applications using hypergraph neural networks to represent the functional behavior of android applications. Hypergraph neural networks can encode high-order data correlation in a hypergraph structure for data representation learning. In experiments, we validate the gaining effect of hypergraphs on detection performance across two open-source android application datasets. Especially, HGNNP obtains the best classification performance of 91.10% on the Malnet-Tiny dataset and 97.1% on the Drebin dataset, which outperforms all baseline methods.
A Modified and Effective Blockchain Model for E-Healthcare Systems
Authors: Assiri Basem
Published: November 2023

The development of e-healthcare systems requires the application of advanced technologies, such as blockchain technology. The main challenge of applying blockchain technology to e-healthcare is to handle the impact of the delay that results from blockchain procedures during the communication and voting phases. The impacts of latency in blockchains negatively influence systems’ efficiency, performance, real-time processing, and quality of service. Therefore, this work proposes a modified model of a blockchain that allows delays to be avoided in critical situations in healthcare. Firstly, this work analyzes the specifications of healthcare data and processes to study and classify healthcare transactions according to their nature and sensitivity. Secondly, it introduces the concept of a fair-proof-of-stake consensus protocol for block creation and correctness procedures rather than famous ones such as proof-of-work or proof-of-stake. Thirdly, the work presents a simplified procedure for block verification, where it classifies transactions into three categories according to the time period limit and trustworthiness level. Consequently, there are three kinds of blocks, since every category is stored in a specific kind of block. The ideas of time period limits and trustworthiness fit with critical healthcare situations and the authority levels in healthcare systems. Therefore, we reduce the validation process of the trusted blocks and transactions. All proposed modifications help to reduce computational costs, speed up processing times, and enhance security and privacy. The experimental results show that the total execution time using a modified blockchain is reduced by about 49% compared to traditional blockchain models. Additionally, the number of messages using modified blockchain is reduced by about 53% compared to the traditional blockchain model.
A New Fuzzy Stochastic Integrated Model for Evaluation and Selection of Suppliers
Authors: Ulutaş Alptekin , Kiridena Senevi , Shukla Nagesh , Topal Ayse
Published: November 2023

In light of the rapid rate of change and unforeseen occurrences seen in the realms of technology, market dynamics, and the wider business landscape, there is a growing need for the inclusion of uncertainty and risk factors in the realm of supply chain planning. Supplier evaluation and selection (SES) is a major strategic decision area where the impact of uncertainty and risk can be more proactively dealt with. A review of extant literature reveals that there is a strong need for developing practitioner-oriented and more comprehensive frameworks and models to mitigate both the capability- and performance-related risks, in the context of SES decisions. This paper presents an integrated model to support SES decisions involving quantity discounts and multiple planning periods under stochastic conditions. The proposed model employs the Fuzzy Analytical Hierarchy Process (FAHP), Fuzzy Evaluation Based on Distance from Average Solution EDAS (EDAS-F), and fuzzy stochastic goal programming (FSGP) to effectively address the above requirements. A case study from a garment manufacturing industry is used to demonstrate the efficacy of the proposed model. The findings of the study provide confirmation that the suggested FSIM has the ability to provide substantial advantages in the context of making choices related to quantity discounts in SES. The proposed FSIM model incorporates the use of FAHP and EDAS-F techniques to effectively reduce the number of suppliers to a manageable level, taking into consideration capability-based risks. Additionally, fuzzy stochastic goal programming (FSGP) is employed to mitigate performance-based risks, enabling the selection of suppliers and the allocation of orders among them. The paper contributes to the literature by proposing a comprehensive framework to solve the SES problem, considering certain practical situations faced by organizations.
Optimal Sparse Control Formulation for Reconstruction of Noise-Affected Images
Authors: Kogut Peter , Kohut Yaroslav
Published: November 2023

We discuss the optimal control formulation for enhancement and denoising of satellite multiband images and propose to take it in the form of an L1 control problem for a quasi-linear parabolic equation with a nonlocal p[u] Laplacian and with a cost functional of a tracking type. The main characteristic features of the considered parabolic problem is that the variable exponent p(t,x) and the diffusion anisotropic tensor D(t,x) are not predefined well a priori; instead, these characteristics nonlocally depend on the form of the solution of this problem (i.e., pu=p(t,x,u) and Du=D(t,x,u)). We prove the existence of optimal pairs with sparse L1 controls used for the indirect approach and a special family of approximation problems.
The Free Energy of Nucleosomal DNA Based on the Landau Model and Topology
Authors: Yang Huimin , Shi Xuguang
Published: November 2023

The free energy of nucleosomal DNA plays a key role in the formation of nucleosomes in eukaryotes. Some work on the free energy of nucleosomal DNA have been carried out in experiments. However, the relationships between the free energy of nucleosomal DNA and its conformation, especially its topology, remain unclear in theory. By combining the Landau theory, the Hopfion model and experimental data, we find that the free energy of nucleosomal DNA is at the lower level. With the help of the energy minimum principle, we conclude that nucleosomal DNA stays in a stable state. Moreover, we discover that small perturbations on nucleosomal DNA have little effect on its free energy. This implies that nucleosomal DNA has a certain redundancy in order to stay stable. This explains why nucleosomal DNA will not change significantly due to small perturbations.
Correction: Finkelstein et al. How Can Ice Emerge at 0 °C? Biomolecules 2022, 12, 981
Authors: Finkelstein Alexei V. , Garbuzynskiy Sergiy O. , Melnik Bogdan S.
Published: November 2023

We regret to state that our article “How Can Ice Emerge at 0 °C?” [...]
Neutrophil to Lymphocyte Ratio as a Prognostic Marker in Amyotrophic Lateral Sclerosis
Authors: Cotet Camille , Alarcan Hugo , Hérault Olivier , Corcia Philippe , Vourc’h Patrick , Andres Christian R. , Blasco Hélène , Veyrat-Durebex Charlotte
Published: November 2023

Amyotrophic lateral sclerosis (ALS) is the most common neurodegenerative motor neuron disease and remains misunderstood with a difficult diagnosis and prognosis. The implication of the immune system is recognized in ALS pathophysiology, hence the interest in leucocyte count as lymphocytes and neutrophils. The neutrophil-to-lymphocyte ratio (NLR) has recently been used as a prognosis factor to assess the progression of ALS. Thus, the aim of this study was to analyze the evolution of the NLR during disease evolution in a French cohort of ALS patients and its relation with survival. In this monocentric retrospective study, clinical parameters and NLR were collected in ALS patients followed at the University Hospital of Tours (France). ALS patients were subdivided into three groups regarding their NLR value at inclusion: group 1 (NLR < 2); group 2 (NLR: 2–3); group 3 (NLR > 3). A comparison of qualitative and quantitative clinical and biological variables between NLR groups was performed. Then, Cox regressions were carried out to determine the association of NLR with survival. We observed a significant correlation of NLR with ALSFRS-r score (p < 0.0001) and with vital forced capacity (p = 0.0004) at inclusion. We observed that increased NLR at diagnosis is associated with decreased ALS patients’ survival.
The Role of Sphingosine-1-Phosphate Receptor 2 in Mouse Retina Light Responses
Authors: Shrestha Abhishek P. , Stiles Megan , Grambergs Richard C. , Boff Johane M. , Madireddy Saivikram , Mondal Koushik , Rajmanna Rhea , Porter Hunter , Sherry David M. , Proia Richard L. , Vaithianathan Thirumalini , Mandal Nawajes
Published: November 2023

The bioactive sphingolipid sphingosine-1-phosphate (S1P) acts as a ligand for a family of G protein-coupled S1P receptors (S1PR1-5) to participate in a variety of signaling pathways. However, their specific roles in the neural retina remain unclear. We previously showed that S1P receptor subtype 2 (S1PR2) is expressed in murine retinas, primarily in photoreceptors and bipolar cells, and its expression is altered by retinal stress. This study aims to elucidate the role of S1PR2 in the mouse retina. We examined light responses by electroretinography (ERG), structural differences by optical coherence tomography (OCT), and protein levels by immunohistochemistry (IHC) in wild-type (WT) and S1PR2 knockout (KO) mice at various ages between 3 and 6 months. We found that a- and b-wave responses significantly increased at flash intensities between 400~2000 and 4~2000 cd.s/m2, respectively, in S1PR2 KO mice relative to those of WT controls at baseline. S1PR2 KO mice also exhibited significantly increased retinal nerve fiber layer (RNFL) and outer plexiform layer (OPL) thickness by OCT relative to the WT. Finally, in S1PR2 KO mice, we observed differential labeling of synaptic markers by immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (RT-qPCR). These results suggest a specific involvement of S1PR2 in the structure and synaptic organization of the retina and a potential role in light-mediated functioning of the retina.
Application of Virtual Reality in Spatial Memory
Authors: Cimadevilla José Manuel , Nori Raffaella , Piccardi Laura
Published: November 2023

In recent years, virtual reality (VR) has become a widely used tool with a plethora of applications in neuroscience [...]
Pathogenetic Insights into Developmental Coordination Disorder Reveal Substantial Overlap with Movement Disorders
Authors: Garofalo Martinica , Vansenne Fleur , Sival Deborah A. , Verbeek Dineke S.
Published: November 2023

Developmental Coordination Disorder (DCD) is a neurodevelopmental condition characterized by non-progressive central motor impairments. Mild movement disorder features have been observed in DCD. Until now, the etiology of DCD has been unclear. Recent studies suggested a genetic substrate in some patients with DCD, but comprehensive knowledge about associated genes and underlying pathogenetic mechanisms is still lacking. In this study, we first identified genes described in the literature in patients with a diagnosis of DCD according to the official diagnostic criteria. Second, we exposed the underlying pathogenetic mechanisms of DCD, by investigating tissue- and temporal gene expression patterns and brain-specific biological mechanisms. Third, we explored putative shared pathogenetic mechanisms between DCD and frequent movement disorders with a known genetic component, including ataxia, chorea, dystonia, and myoclonus. We identified 12 genes associated with DCD in the literature, which are ubiquitously expressed in the central nervous system throughout brain development. These genes are involved in cellular processes, neural signaling, and nervous system development. There was a remarkable overlap (62%) in pathogenetic mechanisms between DCD-associated genes and genes linked with movement disorders. Our findings suggest that some patients might have a genetic etiology of DCD, which could be considered part of a pathogenetic movement disorder spectrum.
Oral Bacteria, Virus and Fungi in Saliva and Tissue Samples from Adult Subjects with Oral Squamous Cell Carcinoma: An Umbrella Review
Authors: Di Spirito Federica , Di Palo Maria Pia , Folliero Veronica , Cannatà Davide , Franci Gianluigi , Martina Stefano , Amato Massimo
Published: November 2023

Oral squamous cell carcinoma (OSCC) is the most common oral cavity malignancy associated with multiple risk factors. In the last 14 years, oral dysbiosis has attracted the scientific community’s attention as a potential oncogenic factor, in parallel with the development of omics technologies that have revolutionized microbiological research. The present umbrella review aimed to investigate the oral microbiological content (bacilli, viruses, and fungi) of tissue and saliva samples from adult (>18 years) patients with OSCC. The secondary objective was to compare the oral microbiome of OSCC subjects with non-OSCC subjects. The study protocol was under the PRISMA statement and registered on PROSPERO (CRD42023448153). Data from 32 systematic reviews were extracted, qualitatively summarized, and analyzed using AMSTAR-2. An increase in oral bacteria of the phylum Fusobacteria, Proteobacteria, and Bacteroidetes and a decrease in Firmicutes and Actinobacteria were observed in OSCC patients. The increased bacterial genera were periodontopathogens. The most common viruses were EBV and HPV, especially the high-risk genotypes. Candida was the most studied oral fungus and was always increased in OSCC subjects. Further studies should investigate the possible carcinogenic mechanisms of oral microorganisms found increased in tissue samples and saliva from adult subjects with OSCC.
Melanin—The Éminence Grise of Melanoma and Parkinson’s Disease Development
Authors: Krasowska Danuta , Małek Agata , Kurzepa Joanna , Kapka-Skrzypczak Lucyna , Krasowska Dorota , Kurzepa Jacek
Published: November 2023

A common feature of Parkinson’s disease (PD) and melanoma is their starting points being based on cells capable of converting tyrosine into melanin. Melanocytes produce two types of melanin: eumelanin and pheomelanin. These dyes are designed to protect epidermal cells from the harmful effects of UV radiation. Neurones of the substantia nigra, which degenerate during PD, produce neuromelanin, the physiological role of which is not fully explained. This article discusses the potential role of melanins in the pathogenesis of both diseases. Melanins, due to their ability to accumulate toxic substances, may become their sources over time. The use of glutathione for the synthesis of pheomelanins and neuromelanins may reduce the antioxidant capacity of cells, leading to an excessive synthesis of free radicals. This study also tested the hypothesis that certain drugs used in the treatment of PD (L-DOPA, MAO-B and COMT inhibitors, and amantadine), aimed at increasing dopamine concentration, could potentially contribute to the development of melanoma. The role and properties of melanins should continue to be researched. Whether excessive melanin synthesis or its accumulation in the extracellular space may be factors initiating the development of diseases remains an open question.
Outcomes of Primary Esophagectomy and Esophagectomy after Endoscopic Submucosal Dissection for Superficial Esophageal Squamous Cell Carcinoma: A Propensity-Score-Matched Analysis
Authors: Kim Minjee , Kim Tae Jun , Kim Ga Hee , Lee Yeong Chan , Lee Hyuk , Min Byung-Hoon , Lee Jun Haeng , Rhee Poong-Lyul , Kim Jae J. , Min Yang Won
Published: November 2023

Even though the conventional treatment for T1 esophageal cancer is surgery, ESD is becoming the primary treatment. Currently, it is unknown whether secondary esophagectomy after endoscopic submucosal dissection (ESD) is comparable to primary esophagectomy when considering outcomes in patients with T1 esophageal cancer. We compared short- and long-term clinical outcomes between the two groups. Primary surgery (esophagectomy) was performed in 191 patients between 2003 and 2014, and 62 patients underwent secondary surgery (esophagectomy) after ESD for T1 esophageal cancer between 2007 and 2019. Propensity matching was performed for age, sex, Charlson Comorbidity Index (CCI), location, pathology, degree of differentiation, tumor size, and invasion depth. Lymph node metastasis (LNM), overall survival (OS), disease-specific survival (DSS), recurrence-free survival (RFS), and post-operative complications were compared between groups. Sixty-eight patients were included after propensity score matching; LNM, OS, DSS, and RFS were comparable between the two groups. Comparing primary and secondary surgery, the respective LNM rates were 23.5% and 26.5%, 6-year OS 78.0% and 89.7%, p = 0.15; DSS were 80.4% and 96.8%, p = 0.057; and RFS were 80.8% and 89.7%, p = 0.069. Comparing the adverse events between the two groups, there was no significant difference in the overall adverse events. However, more early complications were observed in the primary surgery group than in the secondary surgery group (50% vs. 20.6%, p = 0.021). Secondary surgery did not increase the risk of LNM. The long-term outcomes were comparable. Therefore, attempts to perform upfront ESD for superficial esophageal squamous cell cancers are justified.