Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Legibility: A Bibliometric and Visualization Analyses Using Vosviewer Software (1975-2023)

Spatial legibility has been associated in the literature as being comprehensible of the space, easy wayfinding in the space, and being able to draw a cognitive map of the space. This study aims to analyze the scope of spatial legibility research using bibliometric analysis and visualization using VOSviewer. The Web of Science database was utilized to gather information on spatial legibility studies. Title, keywords, and abstract requirements were used to construct the search results, which were based on topic categories from spatial legibility research. The Web of Science database research keywords (TS= ("spatial legibility")) OR TS= ("architectural legibility")) OR TS= ("urban legibility")) OR TS= ("legible cities")) OR TS= ("legible city"). It has been determined that the most used words by the authors in their publications are space syntax, legibility, intelligibility, cognitive map, image, landmark, spatial legibility, urban design, way finding, navigation, virtual environment, and perception. To sum up, this article will give an idea to researchers who will research spatial legibility.
Dietary linoleic acid intake in relation to breast cancer: A case-control study

Background: The present study aimed to investigate the association between dietary linoleic acid (LA) intake and breast cancer in women. Methods: In this population-based case-control study, we enrolled 350 pathologically confirmed breast cancer cases and 700 controls which were matched with cases in terms of age and socioeconomic status. Dietary intakes were assessed using a 106-item Willett-format semi-quantitative dish-based food frequency questionnaire (DS-FFQ). Odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were estimated. Results: A significant inverse association was found between LA intake and odds of breast cancer (OR: 0.41, 95% CI: 0.30-0.56). After adjusting for potential confounders, women in the highest tertile of dietary LA intake were 48% less likely to have breast cancer compared with those in the lowest tertile (OR: 0.52, 95% CI: 0.28-0.95). Such a significant inverse association was also seen among normal-weight women (OR: 0.29, 95% CI: 0.14-0.63), and premenopausal women (OR: 0.15, 95% CI: 0.02-0.95). Conclusion: The findings of current study provide evidence for a protective role of LA against breast cancer particularly among normal-weight and premenopausal women. Prospective studies are needed to confirm this association.
Identifying non‐adult attention‐deficit/hyperactivity disorder individuals using a stacked machine learning algorithm using administrative data population registers in a universal healthcare system

Abstract Background This research project aims to build a Machine Learning algorithm (ML) to predict first‐time ADHD diagnosis, given that it is the most frequent mental disorder for the non‐adult population. Methods We used a stacked model combining 4 ML approaches to predict the presence of ADHD. The dataset contains data from population health care administrative registers in Catalonia comprising 1,225,406 non‐adult individuals for 2013–2017, linked to socioeconomic characteristics and dispensed drug consumption. We defined a measure of proper ADHD diagnoses based on medical factors. Results We obtained an AUC of 79.6% with the stacked model. Significant variables that explain the ADHD presence are the dispersion across patients' visits to healthcare providers; the number of visits, diagnoses related to other mental disorders and drug consumption; age, and sex. Conclusions ML techniques can help predict ADHD early diagnosis using administrative registers. We must continuously investigate the potential use of ADHD early detection strategies and intervention in the health system.
Social media addiction and effect on academic performance among library and information science students in universities in Nigeria

The purpose of the study is to investigate the effect of social media addiction on academic performance of undergraduate students in universities in Nigeria. The study adopted a quantitative research method. Online questionnaire was developed by the researchers using Google form to collect data from 1,239 LIS students in Nigerian Universities. The study found that WhatsApp, Facebook, YouTube and Twitter are the commonly used social media tools by the students of Library and Information Science in Nigerian universities. The students mostly used the social media tools for the purpose of entertainment & fun, and social communications (e.g birthdays). The study also revealed that the majority of the students agree and strongly agree to the statements which show their level of social media addiction. The majority of the students agree that the time they spend on social media affect their school grades. The findings of the paper will inform the management of universities, lecturers, university authorities, healthcare practitioners, library staff, library directors, researchers and parents to take rectification measures to avoid facing the perils of social media addiction. The high prevalence of social media addiction among students therefore calls for university authorities to develop a policy on the use of social media among students.
MVS‐SLAM: Enhanced multiview geometry for improved semantic RGBD SLAM in dynamic environment

Simultaneous Localization and Mapping (SLAM) is a crucial technology for intelligent mobile robots to operate successfully in unknown environments. While many excellent SLAM systems have been developed in recent years, most assume that the environment is static, resulting in poor performance in dynamic environments. To address this limitation, we propose multiview stereo (MVS)‐SLAM (MVS‐SLAM), a real‐time semantic RGBD SLAM system with improved‐multiview geometry, built on the RGBD mode of ORB‐SLAM3. MVS‐SLAM tightly integrates semantic and geometric information to tackle the challenges posed by dynamic scenes. To meet the real‐time requirements, the semantic module leverages the latest and fastest object detection network, YOLOv7, to provide semantic prior knowledge for the geometric module. We introduce a novel geometric constraint method that capitalizes on depth images and semantic information to recover three‐dimensional (3D) feature points and initial camera pose. We use a 3D coordinate error threshold to identify dynamic points and remove them using the K‐means clustering algorithm. This approach effectively reduces the impact of dynamic points. We validate MVS‐SLAM using challenging dynamic sequences from the TUM data set, demonstrating that it significantly improves localization accuracy and system robustness in all types of dynamic environments.
Temperature Controlled Terahertz Absorbers based on Omega Resonators

In this article, the structural stability of a metasurface absorber that works at 2.8 THz is analyzed. Since the absorber is made of metallic titanium, its elemental inclusions will be heated up and expand when absorbing electromagnetic waves. To evaluate the accumulated heat, the structural thermal expansion and the stability of the wave-absorbing performance, electromagnetism-thermodynamics-structural mechanics multiphysics simulations are conducted. Based on the thermal stability study, thermistors are further introduced into the metasurface, leading to two thermal controlled terahertz absorbers. Numerical experiments show that the absorbers present a peak absorption coefficient of 92.7% at 2.79 THz up to the temperature of 1761.4 K. When the temperature rises, the absorption frequencies of the two absorbers shift to 3.51 THz and 3.94 THz, with the peak absorption coefficients of 92.8% and 93.8%, respectively.
Editorial: Advances in breeding for waterlogging tolerance in crops

COPYRIGHT © 2023 Ramlal, Lal and Sathuvalli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 18 September 2023 DOI 10.3389/fpls.2023. 1284730
Robust structured light 3D imaging with two fringe patterns using recurrent classification neural network

Robust and accurate 3D reconstruction using a limited number of fringe patterns has posed a challenge in the field of structured light 3D imaging. Unlike traditional approaches that rely on multiple fringe patterns, using only one or two patterns makes phase recovery and unwrapping difficult. To address this issue, a recurrent classification neural network (RCNN) has been developed, transforming the phase recovery and unwrapping tasks into a unified phase classification task. First, a training dataset consisting of 1200 groups of data was collected to generate a total of 38 400 training samples, enabling the RCNN to learn the mapping between the input fringe patterns and the corresponding label maps. Then, based on the well-trained network, a label map is generated based on the input two fringe patterns using the output classification results. Finally, 3D reconstruction data could be obtained by combining the inferred label map with the vision system’s parameters. A series of comprehensive experiments have been conducted to validate the performance of the proposed method.
Lemon flavonoids nutraceutical (Eriomin®) attenuates prediabetes intestinal dysbiosis: A double‐blind randomized controlled trial

Abstract Eriocitrin (eriodictyol 7‐O‐β‐rutinoside), a citrus flavonoid from lemon juice and peel, reduces hyperglycemia and improves diabetes‐related biomarkers in prediabetes patients. Eriocitrin is first metabolized by gut microbiota, producing energy for gut cells and short chain fatty acids that play a relevant role in glycemic control. The aim of this study was to assess the effect of Eriomin®, a nutraceutical composed of 70% eriocitrin, 5% hesperidin, and 4% naringin, on the microbiota of prediabetic patients. Patients were randomly divided into two groups and received unlabeled capsules of Eriomin® (200 mg/day) or placebo during 12 weeks. After treatment with the nutraceutical, it was a 6% decrease of hyperglycemia and 22% increase of GLP‐1 blood levels of (p < .05). The profile of intestinal microorganisms, obtained by 16S rRNA sequencing of the patients' feces extract, showed changes in microbiota composition, such as lower growth of Firmicutes and less abundance of the Lachnospiraceae family. The family Ruminococcaceae increased and Blautia genus reduced with Eriomin® supplementation. In additional, Blautia was positively correlated with hyperglycemia reduction. In conclusion, the nutraceutical Eriomin® moderately reduced the growth of microorganisms associated with intestinal dysbiosis and increased the abundance of beneficial bacteria. Changes promoted mainly by the flavonoid eriocitrin in the microbiota were related to a lower glycemic level and increased production of GLP‐1 in patients with prediabetes.
Threat Landscape for Industrial Automation Systems in H2 2017

The analysis of vulnerabilities was performed based on vendor advisories, publicly available information from open vulnerability databases (ICS-CERT, CVE, Siemens Product CERT), as well as the results of Kaspersky Lab ICS CERT’s own research. Vulnerability data published on the ICS-CERT website in 2017 was used to create statistical diagrams
Novel MYBPC3 Mutations in Indian Population with Cardiomyopathies

Background Mutations in Myosin Binding Protein C (MYBPC3) are one of the most frequent causes of cardiomyopathies in the world, but not much data are available in India. Methods We carried out targeted direct sequencing of MYBPC3 in 115 hypertrophic (HCM) and 127 dilated (DCM) cardiomyopathies against 197 ethnically matched healthy controls from India. Results We detected 34 single nucleotide variations in MYBPC3, of which 19 were novel. We found a splice site mutation [(IVS6+2T) T>G] and 16 missense mutations in Indian cardiomyopathies [5 in HCM; E258K, T262S, H287L, R408M, V483A: 4 in DCM; T146N, V321L, A392T, E393K and 7 in both HCM and DCM; L104M, V158M, S236G, R272C, T290A, G522E, A626V], but those were absent in 197 normal healthy controls. Interestingly, we found 7 out of 16 missense mutations (V158M, E258K, R272C, A392T, V483A, G522E, and A626V) in MYBPC3 were altering the evolutionarily conserved native amino acids, accounted for 8.7% and 6.3% in HCM and DCM, respectively. The bioinformatic tools predicted that those 7 missense mutations were pathogenic. Moreover, the co-segregation of those 7 mutations in families further confirmed their pathogenicity. Remarkably, we also identified compound mutations within the MYBPC3 gene of 6 cardiomyopathy patients (5%) with more severe disease phenotype; of which, 3 were HCM (2.6%) [(1. K244K + E258K + (IVS6+2T) T>G); (2. L104M + G522E + A626V); (3. P186P + G522E + A626V]; and 3 were DCM (2.4%) [(1. 5’UTR + A392T; 2. V158M+G522E; and 3.V158M + T262T + A626V]. Conclusion The present comprehensive study on MYBPC3 has revealed both single and compound mutations in MYBPC3 and their association with disease in Indian Population with Cardiomyopathies. Our findings may perhaps help in initiating diagnostic strategies and eventually recognizing the targets for therapeutic interventions.
Expression profiles of circular RNAs and interaction networks of competing endogenous RNAs in neurogenic bladder of rats following suprasacral spinal cord injury

Background Neurogenic bladder (NB) following suprasacral spinal cord injury (SSCI) is an interstitial disease with the structural remodeling of bladder tissue and matrix over-deposition. Circular RNAs (circRNAs) are involved in fibrotic disease development through their post-transcriptional regulatory functions. This study aimed to use transcriptome high-throughput sequencing to investigate the process of NB and bladder fibrosis after SSCI. Methods Spinal cord transection at the T10–T11 level was used to construct the SSCI model in rats (10–week–old female Wistar rats, weighing 200 ± 20 g). The bladders were collected without (sham group) and with (SSCI 1–3 groups) NB status. Morphological examination was conducted to assess the extent of bladder fibrosis. Additionally, RNA sequencing was utilized to determine mRNAs and circRNAs expression patterns. The dynamic changes of differentially expressed mRNAs (DEMs) and circRNAs (DECs) in different periods of SSCI were further analyzed. Results Bladder weight, smooth muscle cell hypertrophy, and extracellular matrix gradually increased after SSCI. Compared with the sham group, 3,255 DEMs and 1,339 DECs, 3,449 DEMs and 1,324 DECs, 884 DEMs, and 1,151 DECs were detected in the SSCI 1–3 groups, respectively. Specifically, circRNA3621, circRNA0617, circRNA0586, and circRNA4426 were significant DECs common to SSCI 1–3 groups compared with the sham group. Moreover, Gene Ontology (GO) enrichment suggested that inflammatory and chronic inflammatory responses were the key events in NB progression following SSCI. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment associated with the “Chemokine signaling pathway”, the “IL-17 signaling pathway”, and the “TGF-beta signaling pathway” suggests their potential involvement in regulating biological processes. The circRNA–miRNA–mRNA interaction networks of DECs revealed rno-circ-2239 (micu2) as the largest node, indicating that the rno-circ-2239–miRNA–mRNA–mediated network may play a critical role in the pathogenesis of SSCI-induced NB. Conclusions This study offers a comprehensive outlook on the possible roles of DEMs and DECs in bladder fibrosis and NB progression following SSCI. These findings have the potential to serve as novel biomarkers and therapeutic targets.
Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured against cyberattacks for their everyday functions on the road so that safety of passengers and vehicles can be ensured. This article presents a holistic review of cybersecurity attacks on sensors and threats regarding multi‐modal sensor fusion. A comprehensive review of cyberattacks on intra‐vehicle and inter‐vehicle communications is presented afterward. Besides the analysis of conventional cybersecurity threats and countermeasures for CAV systems, a detailed review of modern machine learning, federated learning, and blockchain approach is also conducted to safeguard CAVs. Machine learning and data mining‐aided intrusion detection systems and other countermeasures dealing with these challenges are elaborated at the end of the related section. In the last section, research challenges and future directions are identified.
Distribution and phytogeographical analysis of Quercus ithaburensis ssp. macrolepis in Greece

This paper presents the distribution of Q. ithaburensisssp. macrolepisin Greece, its basic ecological requirements such as rock and soil characteristics, topography, climatic and bioclimatic factors and chorological and life form spectra of its forests. Data were collected with questionnaires sent to all Forest Service offices around the country and were further completed with field observations. The results suggest that Q. ithaburensis ssp. macrolepis forests cover an area of 29,631.8 ha in the form of stands, thickets and groups, in lowlands and uplands of continental and insular Greece. Furthermore, isolated individuals are scattered throughout the country. The subspecies develops in a variety of rock and soil types, slope inclinations, aspects and different types of Mediterranean bioclimates. It prefers low to middle altitudes, on the sub-humid bioclimate and on shallow to moderate deep calcareous soils. All these characteristics, combined with human activities, influence vegetation types in each region. Due to climate and various human interventions, the Mediterranean elements dominate and only in the forests found in the more northern regions the percentage of the submeditteranean elements increase considerably. Additionally, Q. ithaburensis ssp. macrolepis forests are characterized by the dominance of therophytes.
Analytical Calculation of Magnetic Field and Electromagnetic Performance for Permanent Magnet Assisted Synchronous Reluctance Motors Considering Saturation Effect

The structural characteristics of multilayered interior permanent magnets, magnetic bridges, and flux barriers contribute to a remarkable saturation effect in permanent magnet assisted synchronous reluctance motors (PMaSynRMs), whereas the analytical calculation of the magnetic field and electromagnetic performance for PMaSynRMs considering the saturation effect remains to be a knotty problem. This article proposes a nonlinear analytical model (AM) to predict the magnetic field and electromagnetic performance of a PMaSynRM under the saturation effect. First, the studied PMaSynRM is reshaped to an equivalent concentric annular structure. Second, the technique of harmonic modeling is employed to obtain the analytical solution for the Maxwell field governing equations in each solution region. Finally, considering features of the complex motor structure, an adaptive convergence rate iterative algorithm is improved for the calculation of the saturation effect. To verify the feasibility and the accuracy of the proposed method, the analytical predictions of the magnetic flux density and the electromagnetic performance have been compared with finite element method analysis results. Meanwhile, the reasonable selection of the harmonic truncation order number has been discussed. The proposed nonlinear AM can consider the magnetic saturation and cross-saturation effect accurately, which is suitable for performance predictions and parametric studies of PMaSynRMs.
Stabilization for a Class of Feedforward Nonlinear Systems via Pulsewidth-Modulated Controllers

This article is concerned with the stabilization problem for a class of feedforward nonlinear systems via pulsewidth-modulated (PWM) controllers. First, a state observer, which features a dynamic predictor and a jumping update, is designed such that the unavailable full system state can be accurately estimated. With the obtained state estimations, a reference signal is also constructed. Second, a three-level-state-dependent PWM controller is proposed, which switches among three prescribed states during each cycle and can be determined by two key variables, namely, the duty cycle and the sign of the pulse. It is then demonstrated that the two controller variables can be both expressed in the form of the reference signal, and the design of the controller variables depends on a key parameter that regulates the reference signal. Furthermore, it is shown that the stabilization problem can be cast into a selection problem of the key parameter. By resorting to the Lyapunov stability theory, rigorous stability analysis of the resulting closed-loop system is performed. Finally, a resonant circuit system for liquid level control and a numerical example are provided to validate the effectiveness of the proposed PWM control method.
The Prognostic and Therapeutic Role of Histone Acetylation Modification in LIHC Development and Progression

Background and Objectives: The modification of histone acetylation plays a vital role in regulating tumor occurrence and development, but the interaction between histone acetylation modulator genes and the liver hepatocellular carcinoma (LIHC) microenvironment, as well as immunotherapy, has not been investigated. Materials and Methods: Analysis of all statistical data was carried out using R software (Version 4.2.0) and the online tool Sangerbox. Comprehensive bioinformatics analysis, including signature construction and validation, functional analyses, immune and genomic features analyses, and immunotherapy prediction analyses, were performed to explore the prognostic and therapeutic role of histone acetylation modulator genes in LIHC development and progression. Results: The LIHC cohort from The Cancer Genome Atlas (TCGA) database was selected as the training cohort; the GSE76427 cohort from the Gene Expression Omnibus (GEO) database and the LIRI-JP cohort from the International Cancer Genome Consortium (ICGC) database were selected as the validation cohorts. The histone acetylation modulator gene-based prognostic signature was constructed and validated successfully. Immune infiltration analysis showed that most immune cells and immune functions were enriched in patients with high histone acetylation risk scores (HARS). Additionally, high levels of checkpoint inhibitors (ICIs) and human leukocyte antigens (HLAs) were also observed in high HARS patients. Meanwhile, TIDE algorithm analysis was conducted to explore the relationship between HARS and immunotherapy response, and submap algorithm analysis was used for the verification of the results, from which we found that high HAPS patients were more likely to respond to immunotherapy. Conclusions: Our findings revealed that the histone acetylation modulator genes, particularly for KAT21, SIRT6, and HAT1, may have the potential to function as a new prognostic marker and therapeutic target for LIHC.