bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Finding on Magnetic Resonance Imaging for Diagnosis of Hemifacial Spasm with High Accuracy and Interobserver Correlation
Authors: Finger Guilherme , Wu Kyle C. , Vignolles-Jeong Joshua , Godil Saniya S. , McGahan Ben G. , Kreatsoulas Daniel , Shujaat Mohammad T. , Prevedello Luciano M. , Prevedello Daniel M.
Published: October 2023

Among patients with clinical hemifacial spasm (HFS), imaging exams aim to identify the neurovascular conflict (NVC) location. It has been proven that the identification in the preoperative exam increases the rate of surgical success. Despite the description of specific magnetic resonance image (MRI) acquisitions, the site of neurovascular compression is not always visualized. The authors describe a new MRI finding that helps in the diagnosis of HFS, and evaluate the sensitivity, specificity, and interobserver correlation of the described sign. A cross-sectional study including cases of hemifacial spasm treated surgically from 1 August 2011 to 31 July 2021 was performed. The MRIs of the cases were independently evaluated by two experienced neuroradiologists, who were blinded regarding the side of the symptom. The neuroradiologists were assigned to evaluate the MRIs in two separate moments. Primarily, they evaluated whether there was a neurovascular conflict based on the standard technique. Following this initial analysis, the neuroradiologists received a file with the description of the novel sign, named Prevedello Sign (PS). In a second moment, the same neuroradiologists were asked to identify the presence of the PS and, if it was present, to report on which side. A total of 35 patients were included, mostly females (65.7%) with a mean age of 59.02 (+0.48). Since the 35 cases were independently evaluated by two neuroradiologists, a total of 70 reports were included in the analysis. The PS was present in 66 patients (sensitivity of 94.2%, specificity of 91.4% and positive predictive value of 90.9%). When both analyses were performed in parallel (standard plus PS), the sensitivity increased to 99.2%. Based on the findings of this study, the authors conclude that PS is helpful in determining the neurovascular conflict location in patients with HFS. Its presence, combined with the standard evaluation, increases the sensitivity of the MRI to over 99%, without increasing risks of harm to patients or resulting in additional costs.
The Catalytic Wet Oxidation of Excess Activated Sludge from a Coal Chemical Wastewater Treatment Process
Authors: Wang Zhongquan , Qin Shulin , Zheng Weicheng , Lou Xiaodan , Zeng Xu , Wu Taihang
Published: October 2023

An improved catalytic wet oxidation method for the disposal of excess activated sludge from a coal chemical wastewater treatment process by using the prepared Cu-Ce/γ-Al2O3 catalyst was reported. The effects of catalyst dosage, reaction temperature and time, and initial oxygen pressure on the degradation of the sludge were investigated. The maximum removal rate of volatile suspended solids, 93.2%, was achieved at 260 °C for 60 min with the catalyst 7.0 g·L−1 and initial oxygen pressure 1.0 MPa. The removal rate of chemical oxygen demand was 78.3% under the same conditions. The production of volatile fatty acids, including mainly acetic acid, propanoic acid, and isobutyric acid, increased with the increasing temperature. These acids have the potential to be carbon sources for the biological treatment of wastewater. Scanning electron microscopy images showed that the sludge became a loose porous structure, which is beneficial for dewatering performance. The results of an energy dispersive spectroscopy analysis illustrated that the carbon element in the sludge substantially migrated from solid to liquid phases. Therefore, these results demonstrated that the proposed catalytic wet oxidation method offers a promising pathway for the disposal and utilization of excess activated sludge from the coal chemical wastewater treatment process.
Current Nutritional and Pharmacological Approaches for Attenuating Sarcopenia
Authors: Sakuma Kunihiro , Hamada Kento , Yamaguchi Akihiko , Aoi Wataru
Published: October 2023

Sarcopenia is characterized by a gradual slowing of movement due to loss of muscle mass and quality, decreased power and strength, increased risk of injury from falls, and often weakness. This review will focus on recent research trends in nutritional and pharmacological approaches to controlling sarcopenia. Because nutritional studies in humans are fairly limited, this paper includes many results from nutritional studies in mammals. The combination of resistance training with supplements containing amino acids is the gold standard for preventing sarcopenia. Amino acid (HMB) supplementation alone has no significant effect on muscle strength or muscle mass in sarcopenia, but the combination of HMB and exercise (whole body vibration stimulation) is likely to be effective. Tea catechins, soy isoflavones, and ursolic acid are interesting candidates for reducing sarcopenia, but both more detailed basic research on this treatment and clinical studies in humans are needed. Vitamin D supplementation has been shown not to improve sarcopenia in elderly individuals who are not vitamin D-deficient. Myostatin inhibitory drugs have been tried in many neuromuscular diseases, but increases in muscle mass and strength are less likely to be expected. Validation of myostatin inhibitory antibodies in patients with sarcopenia has been positive, but excessive expectations are not warranted.
Inhibition of Phagocytosis by Silibinin in Mouse Macrophages
Authors: Sun Kyung-Hoon , Lee Min-Young , Jeon Young-Jin
Published: October 2023

This study investigated the effects of silibinin, derived from milk thistle (Silybum marianum), on lipopolysaccharide (LPS)-induced morphological changes in mouse macrophages. Silibinin was treated at various doses and time points to assess its effects on macrophage activation, including morphological changes and phagocytosis. Silibinin effectively inhibited LPS-induced pseudopodia formation and size increase, while unstimulated cells remained round. Silibinin’s impact on phagocytosis was dose- and time-dependent, showing a decrease. We explored its mechanism of action on kinases using a MAPK array. Among the three MAPK family members tested, silibinin had a limited effect on JNK and p38 but significantly inhibited ERK1/2 and related RSK1/2. Silibinin also inhibited MKK6, AKT3, MSK2, p70S6K, and GSK-3β. These findings highlight silibinin’s potent inhibitory effects on phagocytosis and morphological changes in macrophages. We suggest its potential as an anti-inflammatory agent due to its ability to target key inflammatory pathways involving ERK1/2 and related kinases. Overall, this study demonstrates the promising therapeutic properties of silibinin in modulating macrophage function and inflammation.
In Vitro and In Silico Antiviral Activity of Di-Halogenated Compounds Derived from L-Tyrosine against Human Immunodeficiency Virus 1 (HIV-1)
Authors: Serna-Arbeláez Maria S. , García-Cárcamo Valentina , Rincón-Tabares Daniel S. , Guerra Diego , Loaiza-Cano Vanessa , Martinez-Gutierrez Marlen , Pereañez Jaime A. , Pastrana-Restrepo Manuel , Galeano Elkin , Zapata Wildeman
Published: October 2023

HIV-1 infection is considered one of the major public health problems worldwide. Due to the limited access to antiretroviral therapy, the associated side effects, and the resistance that the virus can generate, it has become necessary to continue the development of new antiviral agents. The study aimed to identify potential antiviral agents for HIV-1 by evaluating the in vitro and in silico activity of 16 synthetic di-halogenated compounds derived from L-Tyrosine. The compounds were tested for cytotoxicity, which was determined using MTT, and a combined antiviral screening strategy (pre- and post-infection treatment) was performed against R5 and X4 strains of HIV-1. The most promising compounds were evaluated against a pseudotyped virus (HIV-GFP-VSV-G), and the effectiveness of these compounds was measured through GFP flow cytometry. Also, the antiviral effect of these compounds was evaluated in PBMCs using flow cytometry and ELISA for p24. The TODB-2M, TODC-2M, TODC-3M, and YDC-3M compounds showed low toxicity and significant inhibitory activity against HIV-1. In silico docking and molecular dynamics assays suggest that the compounds’ antiviral activity may be due to interaction with reverse transcriptase, viral protease, or envelope gp120.
Oil Extracted from Spent Coffee Grounds as a Green Corrosion Inhibitor for Copper in a 3 wt% NaCl Solution
Authors: Rouin Ghada , Abdelmouleh Makki , Mallah Abdulrahman , Masmoudi Mohamed
Published: October 2023

The aim of this research is to study the use of the spent coffee grounds (SCGs) as a novel and environmentally friendly corrosion inhibitor. The oily fraction obtained from decoction extraction was subjected to analysis using Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). The inhibitive action of SCG extract on the corrosion of copper in a 3 wt% NaCl solution was studied via potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). The research findings elucidate that the extract derived from SCGs functions as a cathodic inhibitor, primarily impeding the diffusion of oxygen molecules towards the copper substrate. Notably, the inhibitory effectiveness exhibits an improvement with ascending concentrations of the SCG extract. This augmentation culminates in a remarkable 96% inhibition efficiency when the SCG extract concentration reaches 0.6 g/L. Furthermore, it is observed that the SCG extract undergoes adsorption onto the copper surface, a phenomenon that conforms to the Langmuir adsorption isotherm.
Enhancement of Human Gingival Fibroblasts Bioactivity and Proliferation on Plasma Sprayed Yttria-Stabilised Zirconia/TiO2 Surface Coating of Titanium Alloys: An In-Vitro Study
Authors: Jemat Afida , Razali Masfueh , Otsuka Yuichi , Ghazali Mariyam Jameelah
Published: October 2023

Titanium-coated ceramic materials with varying roughness and surface topography have been developed and utilized in clinical trials within the realms of medical and dental implantology. The objective of this study was to assess how cellular attachment is affected by the surface porosity and roughness of the titanium alloy (Ti-6Al-4V) coated with titania (TiO2)-reinforced yttria-stabilized zirconia (YZP). Additionally, the wettability of different types of TiO2-coated YZP was also evaluated for its effect on cellular migration and attachment. The results showed excellent adhesion between fibroblast cells and the surface of the YZP/TiO2 coating, with TiO2 reinforcement exhibiting bioactive properties that promote rapid cell growth and reproduction. Despite its average micro surface roughness measuring 5.86 ± 0.36 µm, the YZP/TiO2 surface coating demonstrated superior suitability for both fibroblast cell adhesion and the promotion of osseointegration. The YZP coating with 30% TiO2 demonstrated the most desirable properties, significantly enhancing biocompatibility. This study can serve as a basis for determining the biocompatibility and bioactivity of the YZP/TiO2 coating, which holds promise as a new coating material.
Evaluation of the Diagnostic Performances of the SD-Bioline®HBeAg Rapid Test Used Routinely for the Management of HBV-Infected Individuals in Burkina Faso
Authors: Dera Abdoulaye , Sanou Armel M. , Ouattara Mathuola N. G. , Ilboudo Abdoul K. , Lankoande David B. , Ilboudo Dieudonné , Napon-Zongo Delphine , Gomgnimbou Michel K.
Published: October 2023

Hepatitis B e antigen (HBeAg) is a marker of wild-type hepatitis B virus replication. In resource-limited countries where access to enzyme-linked immunosorbent assay (ELISA) remains a challenge, rapid diagnostic tests (RDT) constitute a good alternative. The HBeAg status is employed to evaluate eligibility for antiviral therapy and to prevent the transmission of hepatitis B from mother to child (PMTCT). The objective of this study was to assess the diagnostic performance of the SD-Bioline®HBeAg RDT commonly used for detecting HBeAg in laboratories in Burkina Faso. The sample panel used was collected from HBsAg-positive patients received in the laboratory for the detection of HBeAg with the rapid test. The samples were retested for HBeAg using the VIDAS HBe/Anti-HBe enzyme-linked fluorescent assay (ELFA) (Gold standard). Then, the viral load (VL) of HBV DNA was determined using the GENERIC HBV CHARGE VIRLAE kit (GHBV-CV). The diagnostic performances of the SD-Bioline®HBeAg and its agreement with the gold standard were calculated with their 95% confidence intervals. Overall, 340 sera obtained from HBsAg-positive patients were included in this evaluation Compared to the VIDAS HBe/Anti-HBe ELFA test, the sensitivity (Se) and specificity (Sp) of the SD-Bioline®HBeAg test were 33.3% and 97.9%, respectively. The concordance between the two tests was 0.42. Depending on the viral load, the Se and Sp varied from 8.8% and 98.3% for a VL < 2000 IU/mL to 35.5% and 98.4% for a VL > 2,000,000 IU/mL. The results showed a low sensibility of the SD-Bioline®HBeAg RDT test, indicating that its use is inappropriate for the clinical management of HBV-infected patients. They also highlight the urgent need to develop HBeAg rapid tests with better sensitivities.
Unlocking Precision Medicine for Prognosis of Chronic Kidney Disease Using Machine Learning
Authors: Dubey Yogita , Mange Pranav , Barapatre Yash , Sable Bhargav , Palsodkar Prachi , Umate Roshan
Published: October 2023

Chronic kidney disease (CKD) is a significant global health challenge that requires timely detection and accurate prognosis for effective treatment and management. The application of machine learning (ML) algorithms for CKD detection and prediction holds promising potential for improving patient outcomes. By incorporating key features which contribute to CKD, these algorithms enhance our ability to identify high-risk individuals and initiate timely interventions. This research highlights the importance of leveraging machine learning techniques to augment existing medical knowledge and improve the identification and management of kidney disease. In this paper, we explore the utilization of diverse ML algorithms, including gradient boost (GB), decision tree (DT), K-nearest neighbor (KNN), random forest (RF), histogram boost (HB), and XGBoost (XGB) to detect and predict chronic kidney disease (CKD). The aim is to improve early detection and prognosis, enhancing patient outcomes and reducing the burden on healthcare systems. We evaluated the performance of the ML algorithms using key metrics like accuracy, precision, recall, and F1 score. Additionally, we conducted feature significance analysis to identify the most influential characteristics in the detection and prediction of kidney disease. The dataset used for training and evaluation contained various clinical and demographic attributes of patients, including serum creatinine level, blood pressure, and age, among others. The proficiency analysis of the ML algorithms revealed consistent predictors across all models, with serum creatinine level, blood pressure, and age emerging as particularly effective in identifying individuals at risk of kidney disease. These findings align with established medical knowledge and emphasize the pivotal role of these attributes in early detection and prognosis. In conclusion, our study demonstrates the effectiveness of diverse machine learning algorithms in detecting and predicting kidney disease. The identification of influential predictors, such as serum creatinine level, blood pressure, and age, underscores their significance in early detection and prognosis. By leveraging machine learning techniques, we can enhance the accuracy and efficiency of kidney disease diagnosis and treatment, ultimately improving patient outcomes and healthcare system effectiveness.
Automatic Identification of Glomerular in Whole-Slide Images Using a Modified UNet Model
Authors: Kaur Gurjinder , Garg Meenu , Gupta Sheifali , Juneja Sapna , Rashid Junaid , Gupta Deepali , Shah Asadullah , Shaikh Asadullah
Published: October 2023

Glomeruli are interconnected capillaries in the renal cortex that are responsible for blood filtration. Damage to these glomeruli often signifies the presence of kidney disorders like glomerulonephritis and glomerulosclerosis, which can ultimately lead to chronic kidney disease and kidney failure. The timely detection of such conditions is essential for effective treatment. This paper proposes a modified UNet model to accurately detect glomeruli in whole-slide images of kidney tissue. The UNet model was modified by changing the number of filters and feature map dimensions from the first to the last layer to enhance the model’s capacity for feature extraction. Moreover, the depth of the UNet model was also improved by adding one more convolution block to both the encoder and decoder sections. The dataset used in the study comprised 20 large whole-side images. Due to their large size, the images were cropped into 512 × 512-pixel patches, resulting in a dataset comprising 50,486 images. The proposed model performed well, with 95.7% accuracy, 97.2% precision, 96.4% recall, and 96.7% F1-score. These results demonstrate the proposed model’s superior performance compared to the original UNet model, the UNet model with EfficientNetb3, and the current state-of-the-art. Based on these experimental findings, it has been determined that the proposed model accurately identifies glomeruli in extracted kidney patches.
Deep Learning-Based Weed Detection Using UAV Images: A Comparative Study
Authors: Shahi Tej Bahadur , Dahal Sweekar , Sitaula Chiranjibi , Neupane Arjun , Guo William
Published: October 2023

Semantic segmentation has been widely used in precision agriculture, such as weed detection, which is pivotal to increasing crop yields. Various well-established and swiftly evolved AI models have been developed of late for semantic segmentation in weed detection; nevertheless, there is insufficient information about their comparative study for optimal model selection in terms of performance in this field. Identifying such a model helps the agricultural community make the best use of technology. As such, we perform a comparative study of cutting-edge AI deep learning-based segmentation models for weed detection using an RGB image dataset acquired with UAV, called CoFly-WeedDB. For this, we leverage AI segmentation models, ranging from SegNet to DeepLabV3+, combined with five backbone convolutional neural networks (VGG16, ResNet50, DenseNet121, EfficientNetB0 and MobileNetV2). The results show that UNet with EfficientNetB0 as a backbone CNN is the best-performing model compared with the other candidate models used in this study on the CoFly-WeedDB dataset, imparting Precision (88.20%), Recall (88.97%), F1-score (88.24%) and mean Intersection of Union (56.21%). From this study, we suppose that the UNet model combined with EfficientNetB0 could potentially be used by the concerned stakeholders (e.g., farmers, the agricultural industry) to detect weeds more accurately in the field, thereby removing them at the earliest point and increasing crop yields.
Integrating a UAV System Based on Pixhawk with a Laser Methane Mini Detector to Study Methane Emissions
Authors: Filkin Timofey , Lipin Iliya , Sliusar Natalia
Published: October 2023

This article describes the process of integrating one of the most commonly used laser methane detectors, the Laser Methane mini (LMm), and a multi-rotor unmanned aerial vehicle (UAV) based on the Pixhawk flight controller to create an unmanned aerial system designed to detect methane leakages from the air. The integration is performed via the LaserHub+, a newly developed device which receives data from the laser methane detector, decodes it and transmits it to the flight controller with the protocol used by the ArduPilot platform for laser rangefinders. The user receives a single data array from the UAV flight controller that contains both the values of the methane concentrations measured by the detector, and the co-ordinates of the corresponding measurement points in three-dimensional space. The transmission of data from the UAV is carried out in real time. It is shown in this project that the proposed technical solution (the LaserHub+) has clear advantages over not only similar serial commercial solutions (e.g., the SkyHub complex by SPH Engineering) but also experimental developments described in the scientific literature. The main reason is that LaserHub+ does not require a deep customization of the methane detector or the placement of additional complex devices on board the UAV. Tests using it were carried out in aerial gas surveys of a number of municipal solid waste disposal sites in Russia. The device has a low cost and is easy for the end user to assemble, connect to the UAV and set up. The authors believe that LaserHub+ can be recommended as a mass solution for aerial surveys of methane sources. Information is provided on the approval of LaserHub+ for aerial gas surveys of a number of Russian municipal waste disposal facilities.
A Hierarchical Blockchain-Based Trust Measurement Method for Drone Cluster Nodes
Authors: Zuo Jinxin , Cao Ruohan , Qi Jiahao , Gao Peng , Wang Ziping , Li Jin , Zhang Long , Lu Yueming
Published: October 2023

In response to the challenge of low accuracy in node trust evaluation due to the high dynamics of entry and exit of drone cluster nodes, we propose a hierarchical blockchain-based trust measurement method for drone cluster nodes. This method overcomes the difficulties related to trust inheritance for dynamic nodes, trust re-evaluation of dynamic clusters, and integrated trust calculation for drone nodes. By utilizing a multi-layer unmanned cluster blockchain for trusted historical data storage and verification, we achieve scalability in measuring intermittent trust across time intervals, ultimately improving the accuracy of trust measurement for drone cluster nodes. We design a resource-constrained multi-layer unmanned cluster blockchain architecture, optimize the computing power balance within the cluster, and establish a collaborative blockchain mechanism. Additionally, we construct a dynamic evaluation method for trust in drone nodes based on task perception, integrating and calculating the comprehensive trust of drone nodes. This approach addresses trusted sharing and circulation of task data and resolves the non-inheritability of historical data. Experimental simulations conducted using NS3 and MATLAB demonstrate the superior performance of our trust value measurement method for unmanned aerial vehicle cluster nodes in terms of accurate malicious node detection, resilience to trust value fluctuations, and low resource delay retention.
Ramadan Fasting and Short-Term Maximal Physical Performance: Searching for Optimal Timing of the Last Meal “Suhoor” in Female Pre-University Handball Players
Authors: Bougrine Houda , Salem Atef , Nasser Nidhal , Ammar Achraf , Chtourou Hamdi , Souissi Nizar
Published: October 2023

Aiming to identify the ideal suhoor timing for maintaining optimal physical performance and health indicators during Ramadan intermittent fasting, the present study compares the effects of early vs. late Suhoor on short-term high-intensity physical exercise while controlling the body mass index (BMI) oral temperature (OT), dietary intake, and sleep patterns. In a randomized design, 19 female pre-university handball players (age: 16.8 ± 0.4 y; height: 1.70 ± 0.9 m; and body mass: 61.5 ± 6.9 kg) underwent two test sessions (at 08:00 a.m. and 05:00 p.m.) at four different conditions: ten days prior to Ramadan (R − 10), the final ten days of Ramadan (R) including both Early Suhoor R(ES) and Late Suhoor R(LS) conditions, and the ten days immediately following Ramadan (R + 10). A recovery period of at least 48 h has been set between successive test sessions at each period. Outcome measures included the Countermovement Jumps Test (CMJ), Modified Agility t-Test (MATT), Repeated Sprint Ability (RSA), and Rating of Perceived Exertion (RPE). The Pittsburgh Sleep Quality Index (PSQI), OT, BMI, and daily diary intake were assessed across the three periods. The total scores of PSQI decreased significantly during R and R + 10 compared to R − 10. When performed in the afternoon, CMJ, MATT, and RSA performance decreased significantly at R(ES) and R(LS) conditions compared to R − 10. However, these performances decreased only after R(ES) when performed in the morning. Furthermore, performances were lower during R(ES) compared to R(LS) in the afternoon for all tests and the morning for MATT and RSA tests. These findings support prior research showing a deterioration of physical performance during Ramadan fasting and indicate a more pronounced impact following early Suhoor condition. Therefore, consuming a late suhoor, closer to pre-dawn time, could be suggested as an effective strategy to minimize physical performance decline during short-term high-intensity exercise.
Is a Fishing Moratorium Needed in Lake Honghu, Southern China? A Stomach Content Analysis of the Anchovy (Coilia brachygnathus)
Authors: Melaku Abelneh Yimer , Cao Liang , Shen Jiang-Zhong , Zhang E
Published: October 2023

Since 2017, a fishing moratorium has been enforced in Lake Honghu as part of Chang–Jiang’s biodiversity conservation strategy. However, given that the lake is a semi-closed aquatic ecosystem and no longer serves as a habitat for certain fishes of the mid–lower Chang–Jiang basin, the efficacy of this moratorium remains uncertain. To address the question from a trophic ecology perspective, a stomach content analysis was performed on captured anchovies of C. brachygnathus, a current predominant species in Lake Honghu, from November 2020 to October 2021. The results showed that copepods, shrimps, and macrophytes were the main components of this anchovy’s diet, and there were size-related shifts in diets. The dominance of C. brachygnathus, a pelagic–littoral omnivore in this lake, implies a lacustrine environment shift triggered by continued human disturbances. The utilization of macrophytes as the main food items by large-sized anchovies of Lake Honghu has partially contributed to the rapid degradation of submerged vegetation. This highlights the need to remove large-sized individuals of C. brachygnathus and Carassius auratus, another benthic-omnivorous dominant fish, in order to effectively restore the aquatic vegetation and ecosystem of Lake Honghu. The current implementation of fishing moratoriums in subtropical shallow floodplain lakes such as Lake Honghu should be reviewed critically.
Approximate Controllability of Neutral Differential Systems with Fractional Deformable Derivatives
Authors: Raju Sreedharan , Sevugan Raja Balachandar , Udhayakumar Ramalingam , AlNemer Ghada , Arunachalam Umamaheswaran
Published: October 2023

This article deals with the existence and uniqueness of solutions, as well as the approximate controllability of fractional neutral differential equations (ACFNDEs) with deformable derivatives. The findings are achieved using Banach’s, Krasnoselskii’s, and Schauder’s fixed-point theorems and semigroup theory. Three numerical examples are used to illustrate the application of the theories discussed in the conclusion.
Antioxidant Potential and Known Secondary Metabolites of Rare or Underutilized Plants of Yucatan Region
Authors: Uuh-Narvaez Jonatan Jafet , Segura-Campos Maira Rubi , Sytar Oksana
Published: October 2023

The screening of rare plants from the Yucatan region and the known native plants in Mexico, that have been successfully introduced worldwide, has been conducted. Based on a literature analysis and a search of English and Spanish scientific information regarding botanical, plant biochemical, and antioxidant potential in databases such as Google Scholar, Scopus, Web of Knowledge, as well as the national databases of Mexico (Flora: Yucatan Peninsula (cicy.mx) and Especies endémicas|Biodiversidad Mexicana), rare or underutilized plants from the Yucatan region with antioxidant potential have been selected. The formulas of the most studied secondary metabolites of these selected rare plants are shown. Among the selected rare plants with antioxidant potential, the families Sapidaceae and Anacardiaceae had the highest number of representatives. Additionally, representatives from the families Annonaceae, Moraceae, Malpighiaceae, Solanaceae, Ebenaceae, Asteraceae, Ranunculaceae, and Leguminosae were also presented. The current scientific data analysis of selected rare plants from the Yucatan region, Mexico, provides significant background for their further use and introduction in not only the Yucatan region of Mexico, but also worldwide.
Development of a Machine Learning-Based Model to Predict Timed-Up-and-Go Test in Older Adults
Authors: Kraus Moritz , Stumpf Ulla Cordula , Keppler Alexander Martin , Neuerburg Carl , Böcker Wolfgang , Wackerhage Henning , Baumbach Sebastian Felix , Saller Maximilian Michael
Published: October 2023

Introduction: The measurement of physical frailty in elderly patients with orthopedic impairments remains a challenge due to its subjectivity, unreliability, time-consuming nature, and limited applicability to uninjured individuals. Our study aims to address this gap by developing objective, multifactorial machine models that do not rely on mobility data and subsequently validating their predictive capacity concerning the Timed-up-and-Go test (TUG test) in orthogeriatric patients. Methods: We utilized 67 multifactorial non-mobility parameters in a pre-processing phase, employing six feature selection algorithms. Subsequently, these parameters were used to train four distinct machine learning algorithms, including a generalized linear model, a support vector machine, a random forest algorithm, and an extreme gradient boost algorithm. The primary goal was to predict the time required for the TUG test without relying on mobility data. Results: The random forest algorithm yielded the most accurate estimations of the TUG test time. The best-performing algorithm demonstrated a mean absolute error of 2.7 s, while the worst-performing algorithm exhibited an error of 7.8 s. The methodology used for variable selection appeared to exert minimal influence on the overall performance. It is essential to highlight that all the employed algorithms tended to overestimate the time for quick patients and underestimate it for slower patients. Conclusion: Our findings demonstrate the feasibility of predicting the TUG test time using a machine learning model that does not depend on mobility data. This establishes a basis for identifying patients at risk automatically and objectively assessing the physical capacity of currently immobilized patients. Such advancements could significantly contribute to enhancing patient care and treatment planning in orthogeriatric settings.
Landslides and Cultural Heritage—A Review
Authors: Bonini José Eduardo , Vieira Bianca Carvalho , Corrêa Antonio Carlos de Barros , Soldati Mauro
Published: October 2023

Cultural heritage sites can be affected by landslides, often causing damage to their integrity, value, and accessibility. Several studies worldwide were focused on the assessment of the potential threats that landslides can pose to the preservation of cultural heritage sites. This article aims to review landslide studies at cultural heritage sites worldwide, analyzing the publications’ temporal distribution, selected methods, geographical and climate contexts, and investigated landslide types. We analyzed a database of 331 publications from 2000 to 2023 in study areas distributed across 47 countries, compiled through systematic queries of the Web of Science and Scopus catalogs. The results show an increase in the number of publications from 2012 onwards, with most studies performing landslide susceptibility analyses on cultural heritage sites. The majority of the studies deployed a geomorphological approach address slope instability mechanisms that threaten site integrity, with a significant number of publications presenting model-based, multidisciplinary and engineering geological approaches. Europe, North America, and Asia and the Pacific concentrate the majority of studies, with Italy and China having the highest number of case studies. The threats to cultural heritage sites located in Latin America and the Caribbean, and Africa are the least studied. Block slides, earth slides, and rock falls are the most studied processes, with fewer studies dealing with other landslide types.
The Spatial Structure and Driving Mechanisms of Multi-Source Networks in the Chengdu–Chongqing Economic Circle of China
Authors: Zhang Ludan , Zuo Xueman , Wu Ziyi , Chen Cheng , Pan Zibao , Hu Xisheng
Published: October 2023

The phenomenon of polarized development among regional cities has sparked extensive contemplation and indicated a need for research on multi-source regional networks. However, such research faces two obstacles: the absence of quantitative measurement of differences in network structures and the lack of a thorough examination of the degree of city clustering and the dynamics of community composition in hierarchical networks. Thus, we identified 16 cities in the Chengdu–Chongqing Economic Circle (CCEC) as the spatial units to examine the spatial network structures of population, resources, and transportation and the integrated spatial network structure. Using social network analysis, this paper describes the structural characteristics of the three networks (population, resource, and transportation), followed by an analysis of their collective and hierarchical network clustering characteristics, and explores the driving mechanisms and factors that make up each network model. Our results show the following: (1) All three networks exhibit an “east dense, west sparse” characteristic, but there are differences in the layouts of the core cities in terms of the three networks. (2) The clustering characteristics of the hierarchical networks are more pronounced than those of the overall network. The results of the analysis combined with the network formation mechanisms can help effectively plan the future coordinated development of the CCEC.
BibRank: Automatic Keyphrase Extraction Platform Using Metadata
Authors: Eldallal Abdelrhman , Barbu Eduard
Published: October 2023

Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks, such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. This paper introduces a platform that integrates keyphrase datasets and facilitates the evaluation of keyphrase extraction algorithms. The platform includes BibRank, an automatic keyphrase extraction algorithm that leverages a rich dataset obtained by parsing bibliographic data in BibTeX format. BibRank combines innovative weighting techniques with positional, statistical, and word co-occurrence information to extract keyphrases from documents. The platform proves valuable for researchers and developers seeking to enhance their keyphrase extraction algorithms and advance the field of natural language processing.
A Deep Learning Methodology for Predicting Cybersecurity Attacks on the Internet of Things
Authors: Alkhudaydi Omar Azib , Krichen Moez , Alghamdi Ans D.
Published: October 2023

With the increasing severity and frequency of cyberattacks, the rapid expansion of smart objects intensifies cybersecurity threats. The vast communication traffic data between Internet of Things (IoT) devices presents a considerable challenge in defending these devices from potential security breaches, further exacerbated by the presence of unbalanced network traffic data. AI technologies, especially machine and deep learning, have shown promise in detecting and addressing these security threats targeting IoT networks. In this study, we initially leverage machine and deep learning algorithms for the precise extraction of essential features from a realistic-network-traffic BoT-IoT dataset. Subsequently, we assess the efficacy of ten distinct machine learning models in detecting malware. Our analysis includes two single classifiers (KNN and SVM), eight ensemble classifiers (e.g., Random Forest, Extra Trees, AdaBoost, LGBM), and four deep learning architectures (LSTM, GRU, RNN). We also evaluate the performance enhancement of these models when integrated with the SMOTE (Synthetic Minority Over-sampling Technique) algorithm to counteract imbalanced data. Notably, the CatBoost and XGBoost classifiers achieved remarkable accuracy rates of 98.19% and 98.50%, respectively. Our findings offer insights into the potential of the ML and DL techniques, in conjunction with balancing algorithms such as SMOTE, to effectively identify IoT network intrusions.
Synthesis and X-ray Structure Analysis of the Polymeric [Ag2(4-Amino-4H-1,2,4-triazole)2(NO3)]n(NO3)n Adduct: Anticancer, and Antimicrobial Applications
Authors: El-Naggar Mostafa A. , Al-Rasheed Hessa H. , AL-khamis Sarah A. , El-Faham Ayman , Abu-Youssef Morsy A. M. , Haukka Matti , Barakat Assem , Sharaf Mona M. , Soliman Saied M.
Published: October 2023

A new Ag(I) adduct was synthesized by the reaction of 4-amino-4H-1,2,4-triazole (L) with AgNO3. Its chemical structure was approved to be [Ag2(L)2(NO3)]n(NO3)n utilizing elemental analysis, FTIR spectra, and single crystal X-ray diffraction (SC-XRD). According to SC-XRD, there are two independent silver atoms which are coordinated differently depending on whether the nitrate anion is coordinated or not. The coordination geometry of Ag1 is a slightly bent configuration while Ag2 has a distorted tetrahedral structure. The 4-amino-4H-1,2,4-triazole ligand and one of the nitrate groups adopt bridging mode, which connects the crystallographically independent Ag1 and Ag2 atoms resulting in the formation of two-dimensional coordination polymer. Hirshfeld surface analysis displays that the intermolecular O···H (34.0%), Ag···N (10.6%), H···H (10.4%), Ag···O (9.3%), and N···H (9.0%) contacts are the most abundant interactions. Regarding anticancer activity, the [Ag2(L)2(NO3)]n(NO3)n demonstrates stronger cytotoxic efficacy against lung (IC50 = 3.50 ± 0.37 µg/mL) and breast (IC50 = 2.98 ± 0.26 µg/mL) carcinoma cell lines than the anticancer medication cis-platin. The [Ag2(L)2(NO3)]n(NO3)n complex showed interesting antibacterial and antifungal activities compared to the free components (AgNO3 and 4-amino-4H-1,2,4-triazole). The investigated silver(I) complex exhibits remarkable antibacterial activity against E. coli (MIC = 6.1 µg/mL) that may be on par with Gentamycin (MIC = 4.8 µg/mL). As a result, the newly synthesized Ag(I) complex could be suggested for anticancer and antibacterial treatments.
Early Season Monitoring of Tarnished Plant Bug, Lygus lineolaris, in Wild Hosts Using Pheromone Traps
Authors: George Justin , Glover James P. , Reddy Gadi V. P. , Johnson Chris , Hall David R.
Published: October 2023

The tarnished plant bug, Lygus lineolaris (Hemiptera: Miridae), has a wide host range of over 700 plant species, including 130 crops of economic importance. During early spring, managing the field edges with weeds and other wild hosts is important in preventing early-season infestations of L. lineolaris in cotton to prevent damage to the squares and other fruiting structures. Scouting fields for L. lineolaris is time- and labor-intensive, and end-user variability associated with field sampling can lead to inaccuracies. Insect traps that combine visual cues and pheromones are more accurate, sustainable, and economically feasible in contrast to traditional insect detection methods. In this study, we investigated the application of red or white sticky cards baited with the female-produced sex pheromone to monitor overwintering L. lineolaris populations in early spring. Field experiments demonstrated that the red sticky cards baited with a pheromone blend containing hexyl butyrate, (E)-2-hexenyl butyrate, and (E)-4-oxo-2-hexenal in 4:10:7 ratio are highly effective in trapping L. lineolaris adults in early spring before the row crops are planted, and in monitoring their movement into a cotton crop. The monitoring of L. lineolaris should help growers to make judicious decisions on insecticide applications to control early pest infestations, thereby reducing economic damage to cotton.
Insulin Resistance: An Unresolved Riddle
Authors: Tatti Patrizio , Singh Pavandeep
Published: October 2023

Insulin resistance (IR) is a rather common condition that is often diagnosed on the basis of an arbitrary “increased insulin value” or the presence of symptoms indicative of the Metabolic Syndrome [...]
Aryloxyphosphazene-Modified and Graphite-Filled Epoxy Compositions with Reduced Flammability and Electrically Conductive Properties
Authors: Konstantinova Anastasia , Yudaev Pavel , Orlov Alexey , Loban Oleg , Lukashov Nikolay , Chistyakov Evgeniy
Published: October 2023

A method has been developed for producing an epoxy composition based on a low-viscosity epoxy-resorcinol resin, a phosphazene-containing curing agent, isophoronediamine, and thermally expanded graphite as a filler. The degree of cure and the absence of side reactions during the curing process were confirmed using IR spectroscopy. The influence of the content of phosphazene-containing curing agent and filler on the physico-mechanical properties of the composition, its fire resistance, and antistatic properties were studied. Using the UL-94 HB horizontal burning test, it was found that the addition of 10 and 20 wt. % phosphazene-containing curing agent (relative to isophoronediamine) reduces the burning speed by 10 times compared to a sample without phosphazene. The addition of a filler to a composition containing phosphazene reduces the burning speed by 25 times compared to a composition without phosphazene and imparts antistatic properties to the epoxy composition, as evidenced by the specific volume electrical resistance of the order of 101 Ohm·m. Phosphazene-containing curing agent had no statistically significant effect on specific volume electrical resistivity (p > 0.05). Tests of physico-mechanical and adhesive properties (tensile strength, compressive strength, water absorption, water solubility, abrasion resistance, and adhesive strength) of filled epoxy compositions with 10 and 20 wt. % phosphazene-containing curing agent demonstrated that these properties met the requirements for floor coverings in construction and parts of electrical devices.
The Accumulation of Metal Ions by a Soy Protein–Inorganic Composite Material
Authors: Yamada Masanori , Ujihara Maika , Yamada Tetsuya
Published: October 2023

Water-soluble soy protein (SP), which contains many acidic amino acids in its structure, was complexed by mixing with a silane coupling agent, 3-glycidoxypropyltrimethoxysilane (GPTMS). These SP−GPTMS composite materials showed stability in water. This property is due to the cross-linking between SP and GPTMS through the ring cleavage reaction of the epoxy group in the GPTMS molecule and an encapsulation of SP into the 3D siloxane network of GPTMS. When the SP−GPTMS composite material was immersed in an aqueous Cu(II) ion solution, the composite material changed from light brown to blue green by the coordination of Cu(II) ions into the SP. Hence, we evaluated the accumulation of heavy ions, rare-earth ions, and light metal ions. The accumulating affinity of metal ions was Cd(II) << Zn(II), Cu(II), Pb(II) < La(III) < Al(III) < Nd(III), In(III) << Mg(II) < Ca(II) ions. In addition, the sorption capacities of Ca(II), Mg(II), In(III), Nd(III), Al(III), La(III), Pb(II), Cu(II), Zn(II), and Cd(II) ions were 700 nmol/mg, 660 nmol/mg, 470 nmol/mg, 470 nmol/mg, 410 nmol/mg, 380 nmol/mg, 350 nmol/mg, 350 nmol/mg, 300 nmol/mg, and 200 nmol/mg, respectively. These properties suggest that the SP−GPTMS composite material has a divalent light metal ion selectivity. Additionally, the accumulative mechanism of the light metal ions was related to the carboxylate group and the hydroxyl group in the composite material.
Assessment of the Attenuation Properties of Commercial Lead-Free Radiation-Shielding Composite Materials Against Medical X-rays
Authors: Trajkovska Petkoska Anka
Published: October 2023

Six commercial, lead-free, radiation protective materials were tested for their attenuation across a range of X-ray energies used in medical diagnostic imaging and interventional radiology. While all the tested materials showed the specified attenuation at the X-ray energy claimed by their manufacturers, only two of the materials showed satisfactory attenuation in an extended range of medical X-ray energies (generated in X-ray tubes with voltages between 50 and 150 kV). The lead-free materials are lighter than the lead-containing materials, which is very important for those wearing the radiation protective garments for an extended time; however, the main focus in the promotion of radiation-shielding materials should still be on their attenuation efficacy against both the primary and the scattered X-rays present in medical environments. The end users should be informed on the material attenuation in an extended energy range, especially in the range where scatter radiation occurs, and not just about the peak material attenuation performance at energies where the X-rays are generated. Scatter radiation is the main reason for the occupational radiation exposure of medical personnel, who should have the whole picture about the shielding ability of the protective garments that they strongly rely on.
Biphasic Bioceramic Obtained from Byproducts of Sugar Beet Processing for Use in Bioactive Coatings and Bone Fillings
Authors: Suffo-Pino Miguel , Cauqui-López Miguel Ángel , Pérez-Muñoz Celia , Goma-Jiménez Daniel , Fernández-Delgado Natalia , Herrera-Collado Miriam
Published: October 2023

This study focuses on developing hydroxyapatite synthesized from a CaCO3-rich byproduct of sugar beet processing called Carbocal® using a hydrothermal reactor. The purpose of this biomaterial is to enhance the osteoinductivity of implantable surfaces and serve as a bone filler, providing a sustainable and economically more affordable alternative. This research involved compositional analysis and micro- and macrostructural physicochemical characterization, complemented with bioactivity and live/dead assays. The biphasic nature of the Carbocal®-derived sample was significant within the context of the bioactivity concept previously proposed in the literature. The bioactivity of the biomaterial was demonstrated through a viability test, where the cell growth was nearly equivalent to that of the positive control. For comparison purposes, the same tests were conducted with two additional samples: hydroxyapatite obtained from CaCO3 and commercial hydroxyapatite. The resulting product of this process is biocompatible and possesses properties similar to natural hydroxyapatite. Consequently, this biomaterial shows potential as a scaffold in tissue engineering and as an adhesive filler to promote bone regeneration within the context of the circular bioeconomy in the geographical area proposed.