Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamically Feasible Periodic Trajectories for Generic Spatial 3-DOF Cable-Suspended Parallel Robots

Cable suspended robots may move beyond their static workspace by keeping all cables under tension, thanks to end-effector inertia forces. This may be used to extend the robot capabilities, by choosing suitable dynamical trajectories. In this paper, we consider 3D elliptical trajectories of a point-mass end-effector suspended by 3 cables from a base of generic geometry. Elliptical trajectories are the most general type of spatial sinusoidal motions. We find a range of admissible frequencies for which said trajectories are feasible; we also show that there is a special frequency which allows the robot to have arbitrarily large oscillations. The feasibility of these trajectories is verified via algebraic conditions that can be quickly verified, thus being compatible with real-time applications. By generalizing previous studies, we also study the possibility to change the frequency of oscillation: this allows the velocity at which a given ellipse is tracked to be varied, thus providing more latitude in the trajectory definition. We finally study transition trajectories to move the robot from an initial state of rest (within the static workspace) to the elliptical trajectory (and vice versa) or to connect two identical ellipses having different centres.
Small Object Detection Based on Deep Learning for Remote Sensing: A Comprehensive Review

With the accelerated development of artificial intelligence, remote-sensing image technologies have gained widespread attention in smart cities. In recent years, remote sensing object detection research has focused on detecting and counting small dense objects in large remote sensing scenes. Small object detection, as a branch of object detection, remains a significant challenge in research due to the image resolution, size, number, and orientation of objects, among other factors. This paper examines object detection based on deep learning and its applications for small object detection in remote sensing. This paper aims to provide readers with a thorough comprehension of the research objectives. Specifically, we aggregate the principal datasets and evaluation methods extensively employed in recent remote sensing object detection techniques. We also discuss the irregularity problem of remote sensing image object detection and overview the small object detection methods in remote sensing images. In addition, we select small target detection methods with excellent performance in recent years for experiments and analysis. Finally, the challenges and future work related to small object detection in remote sensing are highlighted.
Investigating the Ability of Edwardsiella ictaluri and Flavobacterium covae to Persist within Commercial Catfish Pond Sediments under Laboratory Conditions

Two prevalent bacterial diseases in catfish aquaculture are enteric septicemia of catfish and columnaris disease caused by Edwardsiella ictaluri and Flavobacterium covae, respectively. Chronic and recurring outbreaks of these bacterial pathogens result in significant economic losses for producers annually. Determining if these pathogens can persist within sediments of commercial ponds is paramount. Experimental persistence trials (PT) were conducted to evaluate the persistence of E. ictaluri and F. covae in pond sediments. Twelve test chambers containing 120 g of sterilized sediment from four commercial catfish ponds were inoculated with either E. ictaluri (S97-773) or F. covae (ALG-00-530) and filled with 8 L of disinfected water. At 1, 2, 4-, 6-, 8-, and 15-days post-inoculation, 1 g of sediment was removed, and colony-forming units (CFU) were enumerated on selective media using 6 × 6 drop plate methods. E. ictaluri population peaked on Day 3 at 6.4 ± 0.5 log10 CFU g−1. Correlation analysis revealed no correlation between the sediment physicochemical parameters and E. ictaluri log10 CFU g−1. However, no viable F. covae colonies were recovered after two PT attempts. Future studies to improve understanding of E. ictaluri pathogenesis and persistence, and potential F. covae persistence in pond bottom sediments are needed.
A Postmortem Case Study—An Analysis of microRNA Patterns in a Korean Native Male Calf (Bos taurus coreanae) That Died of Fat Necrosis

Simple Summary A 6-month-old male Korean native calf, known for its highly marbled meat, was purchased but found dead three days later, without any notable medical history. The calf had a significantly higher body weight than average for its age. Postmortem examination revealed fat necrosis, along with gastric dilatation, volvulus and intestinal obstruction, as the cause of death. Serum chemistry analysis indicated disrupted lipid metabolism and pancreatic damage—obstructive acute pancreatitis. To investigate the cause of fat necrosis, microRNA patterns were analyzed. Interestingly, the results resembled those found in human patients with diabetes mellitus. To explore the potential correlation between fat necrosis and human diabetic-like miRNA patterns, a comprehensive analysis of miRNAs and the miRNA-mediated Kyoto Encyclopedia of Gene and Genome (KEGG) pathway were conducted. The bovine target gene prediction and KEGG analysis indicated a significant association between multiple genes and diabetic-like clinical conditions. These findings suggest fat necrosis can occur in high-spec cattle such as Korean native calves, and in such cases clinical indicators such as diabetes are observed, providing the factors contributing to the breed’s high meat quality and marbling. The in-depth analysis of miRNA and the KEGG pathway offers valuable insights into the potential mechanisms underlying this correlation. Abstract Korean native cattle are highly valued for their rich marbling and flavor. Nonetheless, endeavors to enhance marbling levels can result in obesity, a prevalent contributor to fat necrosis. Fat necrosis is characterized by the formation of necrotic fat masses in the abdominal cavity, which physically puts pressure on affected organs, causing physical torsion or obstruction, resulting in death and consequent economic loss. Pancreatic injuries or diabetes mellitus were reported as factors of fat necrosis in humans; however, the pathogenesis in animals has not been established. In this study, we identified fat necrosis in a 6-month-old Korean native cow and investigated its potential underlying causes. Serum samples were utilized for a microarray analysis of bovine miRNA. Comparative examination of miRNA expression levels between cattle afflicted with fat necrosis and healthy cattle unveiled notable variances in 24 miRNAs, such as bta-miR-26a, bta-miR-29a, bta-miR-30a-5p and bta-miR-181a. Upon conducting miRNA-mediated KEGG pathway analysis, several pathways including the prolactin signal pathway, insulin resistance, autophagy, the insulin-signaling pathway and the FoxO-signaling pathway were found to be significantly enriched in the calf affected by fat necrosis. As a result, this study potentially indicates a potential connection between fat necrosis and diabetes in Korean native cattle.
The relationship between the Dark Triad and bullying among Chinese adolescents: the role of social exclusion and sense of control

Introduction Abundant evidence has proved the association between the Dark Triad and bullying. However, the underlying mechanisms of this relationship are still not fully understood. Based on the temporal need-threat model, three studies were designed to explore the mediating role of social exclusion and sense of control in this research. Methods In study 1 we recruited 571 Chinese adolescents (Mage = 14.53, SD = 0.716) to participate in a cross-sectional study. And two experiments were respectively designed in Study 2 (N = 88) and Study 3 (N = 102) to verify the effects of real and cyber social exclusion on adolescent bullying behavior. Results Study 1 showed that social exclusion and sense of control would play the serial mediating role in the relationship between the Dark Triad and bullying (except social exclusion as a mediator between the Dark Triad and cyberbullying). Study 2 and 3 showed that adolescents with high Dark Triad show lower sense of control and more bullying behavior after experiencing social exclusion. Discussion These findings extend the research on the Dark Triad and bullying by providing a solid empirical foundation and intervention strategies to avoid bullying so that the problem can be rationally and scientifically approached.
Preparation of a nano insecticide using dried Lawasonia Inermis leaves with TeO2 and investigate its effectiveness against house flie

Background: Lawasonia Inermis (henna) extract and trillium dioxide (TeO2) has many applications among them is biomedicine and pharmaceutical industry. Objective: the current study aimed to prepare extract from henna leaves, and synthesize novel nanoparticles derived from henna extract and TeO2, characterized them and test its bioactivity against house flies. Materials and Methods: Lawasonia Inermis (henna) leaves and TeO2 were collected from local markets in Baghdad, Iraq. The extraction of henna leaves was prepared and the TeO2nano particles was synthesized according to a certain procedures, the nanoparticles of the combination of henna extract and TeO2 was prepared a characterized successfully using different techniques such UV-Vis, XRD, AFM. The bioactivity of all the compounds was evaluated and tested. Results: The UV-Vis, XRD and AFM spectra was collected and evaluated. The bioactivity was also examined against house fly and the collected data was clear and very optimistic. It was found that the highest effect was of trillium nanoparticles prepared at a concentration of 500ppm to reach 100% to kill the 1st larval. It also shows clear decreases in the effect at the same concentration above for the 1st larval stage when using only trillium oxide or only henna leaves extract, 30% and 10% respectively, Conclusions: Many conclusions were found in this work, among them are; extract of Lawasonia Inermis leaves was prepared successfully, novel nanoparticles were synthesized from henna extract and TeO2 nanoparticles (HennaTeO2NPs) was prepared, characterization of the novel hennaTeO2NPs was carried out, and the bioactivity of the novel nanoparticles was carried out against house fly and it was noticed that the novel henna nanoparticles shows best activity.
A Description of the Yield of Genetic Reinvestigation in Patients with Inherited Retinal Dystrophies and Previous Inconclusive Genetic Testing

In the present era of evolving gene-based therapies for inherited retinal dystrophies (IRDs), it has become increasingly important to verify the genotype in every case, to identify all subjects eligible for treatment. Moreover, combined insight concerning phenotypes and genotypes is crucial for improved understanding of thevisual impairment, prognosis, and inheritance. The objective of this study was to investigate to what extent renewed comprehensive genetic testing of patients diagnosed with IRD but with previously inconclusive DNA test results can verify the genotype, if confirmation of the genotype has an impact on the understanding of the clinical picture, and, to describe the genetic spectrum encountered in a Swedish IRD cohort. The study included 279 patients from the retinitis pigmentosa research registry (comprising diagnosis within the whole IRD spectrum), hosted at the Department of Ophthalmology, Skåne University hospital, Sweden. The phenotypes had already been evaluated with electrophysiology and other clinical tests, e.g., visual acuity, Goldmann perimetry, and fundus imaging at the first visit, sometime between 1988–2015 and the previous—in many cases, multiple—genetic testing, performed between 1995 and 2020 had been inconclusive. All patients were aged 0–25 years at the time of their first visit. Renewed genetic testing was performed using a next generation sequencing (NGS) IRD panel including 322 genes (Blueprint Genetics). Class 5 and 4 variants, according to ACMG guidelines, were considered pathogenic. Of the 279 samples tested, a confirmed genotype was determined in 182 (65%). The cohort was genetically heterogenous, including 65 different genes. The most prevailing were ABCA4 (16.5%), RPGR (6%), CEP290 (6%), and RS1 (5.5%). Other prevalent genes were CACNA1F (3%), PROM1 (3%), CHM (3%), and NYX (3%). In 7% of the patients there was a discrepancy between the diagnosis made based on phenotypical or genotypical findings alone. To conclude, repeated DNA-analysis was beneficial also in previously tested patients and improved our ability to verify the genotype–phenotype association increasing the understanding of how visual impairment manifests, prognosis, and the inheritance pattern. Moreover, repeated testing using a widely available method could identify additional patients eligible for future gene-based therapies.
Brain Tumor Segmentation using K-Means Clustering Algorithm

Since image segmentation is a classic inverse problem which consist of achieving a compact region based description of the image scene by decomposing it into meaningful or spatially regions sharing similar attributes. Tumor is nothing but uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different treatments. The K-means algorithm is an iterative technique that is used to partition an image into K clusters. In developed countries most research show that the number of people who have brain tumors were died due to inaccurate detection of tumor . CT scan or MRI is directed into intracranial cavity produces a complete image of brain and this image is visually examined for detection.
Rapid and Quantitative Detection of Lung Cancer Biomarker ENOX2 Using a Novel Aptamer in an Electrochemical DNA-Based (E-DNA) Biosensor

To overcome early cancer detection challenges, diagnostic tools enabling more sensitive, rapid, and noninvasive detection are necessary. An attractive cancer target for diagnostic blood tests is human Ecto-NOX disulfide–thiol exchanger 2 (ENOX2), expressed in most human cancer types and regularly shed into blood sera. Here, we developed an electrochemical DNA-based (E-DNA) biosensor that rapidly detects physiologically relevant levels of ENOX2. To identify ENOX2-binding aptamers that could potentially be used in a biosensor, recombinantly expressed ENOX2 was used as a binding target in an oligonucleotide library pull-down that generated a highly enriched ENOX2-binding aptamer. This candidate aptamer sensitively bound ENOX2 via gel mobility shift assays. To enable this aptamer to function in an ENOX2 E-DNA biosensor, the aptamer sequence was modified to adopt two conformations, one capable of ENOX2 binding, and one with disrupted ENOX2 binding. Upon ENOX2 introduction, a conformational shift to the ENOX2 binding state resulted in changed dynamics of a redox reporter molecule, which generated a rapid, significant, and target-specific electrical current readout change. ENOX2 biosensor sensitivity was at or below the diagnostic range. The ENOX2 E-DNA biosensor design presented here may enable the development of more sensitive, rapid, diagnostic tools for early cancer detection.
Identification of Milling Status Using Vibration Feature Extraction Techniques and Support Vector Machine Classifier

The objective of this study is to use the vibration signal features of spindles during the cutting processing to identify the different milling statuses in cases of diverse tooling parameter combinations. Accelerometers were placed on a spindle to measure vibration behaviors, and the milling status could be divided into idle cutting, initial feeding, and stable cutting. Vibration signal processing and analysis were conducted in the time domain, as well as in the frequency domain. The original vibration measurements were separated using empirical mode decomposition (EMD) in the time domain, so that the signal features could be extracted in certain frequency bands and the useless signal components and trends could be removed. Multi-scale entropy (MSE) and root mean square (RMS) were computed to extract the time domain features. In the frequency domain, the specific intrinsic mode functions (IMFs) that were decomposed using the EMD method were analyzed by fast fourier transform (FFT) and a frequency normalization technique to extract the features of apparent physical representations. The Fisher scores (FS) of the extracted features are calculated to select the high-priority signal features. The selected high-priority signal features are utilized to identify the different milling statuses through a support vector machine (SVM). The results show that an identification accuracy of 98.21% could be obtained at the Z axis, and the average accuracy would be 95.91% for the three axes combination.
The impact of pre-entry work experience on university students’ perceived employability

ABSTRACT Much research on the employability development of university students and the employability experience of graduates treats learners as experientially homogenous and ignores the potential impact of pre-entry work experience on either students’ confidence or their employability-related behaviours. This study explored the confidence of commencing students aged 17 to 21. The objective was to understand whether and how study and career confidence differs among commencing students according to whether they have never worked, are working whilst studying, or have worked previously and have stopped work. The impact of work experience including that gained prior to university entry is often overlooked when discussing students’ perceived employability. This largely quantitative study explores the perceived employability of commencing university students who began their studies soon after finishing high school and compares these self-perceptions relative to work experience. The study employed a self-measure of study and career confidence (Bennett, 2021) grounded in social cognitive career theory with 2,374 full-time students. Differences across the categories were explored using t-tests and multivariate analysis. The analysis concluded that 1,272 students (53.6%) were working at the time of the study, 1,025 students (46.4%) had previously worked but were not working at the time of the study and 77 students (3.2%) had never worked. The findings, illustrated by students’ text-based descriptions of their employability development activities, suggest a hierarchical relationship between pre-entry work-experience and more confident self-perceptions of employability. Implications for higher education employability development are discussed.
Genomics and Antimicrobial Susceptibility of Clinical Pseudomonas aeruginosa Isolates from Hospitals in Brazil

Pseudomonas aeruginosa, an opportunistic pathogen causing infections in immunocompromised patients, usually shows pronounced antimicrobial resistance. In recent years, the frequency of carbapenemases in P. aeruginosa has decreased, which allows use of new beta-lactams/combinations in antimicrobial therapy. Therefore, the in vitro evaluation of these drugs in contemporary isolates is warranted. We evaluated the antimicrobial susceptibility and genomic aspects of 119 clinical P. aeruginosa isolates from 24 different hospitals in Brazil in 2021–2022. Identification was performed via MALDI-TOF-MS, and antimicrobial susceptibility was identified through broth microdilution, gradient tests, or disk diffusion. Whole-genome sequencing was carried out using NextSeq equipment. The most active drug was cefiderocol (100%), followed by ceftazidime–avibactam (94.1%), ceftolozane–tazobactam (92.4%), and imipenem–relebactam (81.5%). Imipenem susceptibility was detected in 59 isolates (49.6%), and the most active aminoglycoside was tobramycin, to which 99 (83.2%) isolates were susceptible. Seventy-one different sequence types (STs) were detected, including twelve new STs described herein. The acquired resistance genes blaCTX-M-2 and blaKPC-2 were identified in ten (8.4%) and two (1.7%) isolates, respectively. Several virulence genes (exoSTUY, toxA, aprA, lasA/B, plcH) were also identified. We found that new antimicrobials are effective against the diverse P. aeruginosa population that has been circulating in Brazilian hospitals in recent years.
NUMERICAL INVESTIGATION OF THE INFLUENCE OF AN IMPINGING SHOCK WAVE AND HEAT TRANSFER ON A DEVELOPING TURBULENT BOUNDARY LAYER

As a prerequesite for relevant model development and improvement of design methodologies for supersonic vehicles, this study aims at investigating the influence of wall heat-transfer and shock interaction on the turbulence structure of supersonic boundary layers. The numerical strategy relies on the full resolution of threedimensional compressible Navier-Stokes equations by means of state-of-art high-order WENO and compact schemes. A fully-developped turbulent boundary layer is simulated by means of upstream wall perturbations triggering the transition in order to dispose of fully-reliable data upstream of the analysis region. Insipient separation conditions and two different wall thermal boundary conditions (adiabatic and cold) are considered. The analysis focuses on the evolution of mean and turbulent flow properties along the interaction region and in the relaxation region downstream of the shock-system. The strong influence of the mean pressure gradient is quantified through the analysis of mean flow profiles and boundary layer integral parameters. The anisotropic amplification of turbulent quantities through the interaction region is characterized and the turbulent events associated with the modification of the turbulence structure of the perturbed boundary layer are identified. The mean and turbulent thermal fields are shown to be strongly modified by the wall cooling which significantly dampens more particularly the turbulent thermal quantities levels across the boundary layer. In addition, a reduction of the upstream influence and separation lengths by the wall cooling are evidenced along with a faster recovery process downstream of the shock-system.
Influence of Surface Texturing on the Dry Tribological Properties of Polymers in Medical Devices

There is a constant need to improve patient comfort and product performance associated with the use of medical devices. Efforts to optimise the tribological characteristics of medical devices usually involve modifying existing devices without compromising their main design features and functionality. This article constitutes a state-of-the-art review of the influence of dry friction on polymeric components used in medical devices, including those having microscale surface features. Surface tribology and contact interactions are discussed, along with alternative forms of surface texturing. Evident gaps in the literature, and areas warranting future research are highlighted; these include friction involving polymer Vs polymer surfaces, information regarding which topologies and feature spacings provide the best performing textured surfaces, and design guidelines that would assist manufacturers to minimise or maximise friction under non-lubricated conditions.