Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Semi-Immersive Virtual Reality-Based Cognitive Training Combined with Locomotor Activity on Cognitive Function and Gait Ability in Community-Dwelling Older Adults

This study aimed to investigate the effects of semi-immersive virtual reality-based cognitive training (VRCT) combined with locomotor activity on cognitive function, balance, and gait ability in older adults. Eighteen community-dwelling older adults participated in this study. Subjects who met the selection criteria were assigned to an experimental group (n = 9) and a control group (n = 9). The experimental group received VRCT combined with locomotor activity for 30 min a day, three times a week, for 6 weeks. The control group received tabletop activity-based cognitive training for the same amount of time. Before and after the training, the Korean Mini-Mental State Examination (K-MMSE), Trail Making Test (TMT; A and B), and Digit Span Test (DST; forward and backward) were used to evaluate cognitive function; and the Timed Up and Go (TUG) test and 10-m Walking Test (10MWT) were used to evaluate the improvement in the balance and gait ability parameters. After the intervention, the experimental group showed a significantly greater improvement in the TMT-A (p = 0.045) and DST-backward (p = 0.012) scores compared with the control group. Regarding the gait ability variable, the experimental group showed a significant improvement in the 10MWT test (p = 0.001). This study confirmed that semi-immersive VRCT combined with locomotor activity is useful for improving cognitive function and gait ability in older adults. Therefore, VRCT combined with locomotor activity can be used as a simultaneous intervention for cognitive rehabilitation and functional capacity improvement in older adults.
Subjective and Objective Quality Assessments of Display Products †

In recent years, people’s daily lives have become inseparable from a variety of electronic devices, especially mobile phones, which have undoubtedly become necessity in people’s daily lives. In this paper, we are looking for a reliable way to acquire visual quality of the display product so that we can improve the user’s experience with the display product. This paper proposes two major contributions: the first one is the establishment of a new subjective assessment database (DPQAD) of display products’ screen images. Specifically, we invited 57 inexperienced observers to rate 150 screen images showing the display product. At the same time, in order to improve the reliability of screen display quality score, we combined the single stimulation method with the stimulation comparison method to evaluate the newly created display products’ screen images database effectively. The second one is the development of a new no-reference image quality assessment (IQA) metric. For a given image of the display product, first our method extracts 27 features by analyzing the contrast, sharpness, brightness, etc., and then uses the regression module to obtain the visual quality score. Comprehensive experiments show that our method can evaluate natural scene images and screen content images at the same time. Moreover, compared with ten state-of-the-art IQA methods, our method shows obvious superiority on DPQAD.
Genetic diversity and population structure analysis of bambara groundnut (Vigna subterrenea L) landraces using DArT SNP markers

Understanding the genetic structure and diversity of crops facilitates progress in plant breeding. A collection of 270 bambara groundnut (Vigna subterrenea L) landraces sourced from different geographical regions (Nigeria/Cameroon, West, Central, Southern and East Africa) and unknown origin (sourced from United Kingdom) was used to assess genetic diversity, relationship and population structure using DArT SNP markers. The major allele frequency ranged from 0.57 for unknown origin to 0.91 for West Africa region. The total gene diversity (0.482) and Shannon diversity index (0.787) was higher in West African accessions. The genetic distance between pairs of regions varied from 0.002 to 0.028 with higher similarity between Nigeria/Cameroon-West Africa accessions and East-Southern Africa accessions. The analysis of molecular variance (AMOVA) revealed 89% of genetic variation within population, 8% among regions and 3% among population. The genetic relatedness among the collections was evaluated using neighbor joining tree analysis, which grouped all the geographic regions into three major clusters. Three major subgroups of bambara groundnut were identified using the ADMIXTURE model program and confirmed by discriminant analysis of principal components (DAPC). These subgroups were West Africa, Nigeria/Cameroon and unknown origin that gave rise to sub-population one, and Central Africa was sub-population two, while Southern and East Africa were sub-population three. In general, the results of all the different analytical methods used in this study confirmed the existence of high level of diversity among the germplasm used in this study that might be utilized for future genetic improvement of bambara groundnut. The finding also provides new insight on the population structure of African bambara groundnut germplasm which will help in conservation strategy and management of the crop.
The Genus Cladosporium: A Rich Source of Diverse and Bioactive Natural Compounds

Fungi are renowned as one of the most fruitful sources of chemodiversity and for their ubiquitous occurrence. Among the many taxonomic groupings considered for the implications deriving from their biosynthetic aptitudes, the genus Cladosporium stands out as one of the most common in indoor environments. A better understanding of the impact of these fungi on human health and activities is clearly based on the improvement of our knowledge of the structural aspects and biological properties of their secondary metabolites, which are reviewed in the present paper.
Multidimensional molecular measurements–environment interaction analysis for disease outcomes

Multiple types of molecular (genetic, genomic, epigenetic, etc.) measurements, environmental risk factors, and their interactions have been found to contribute to the outcomes and phenotypes of complex diseases. In each of the previous studies, only the interactions between one type of molecular measurement and environmental risk factors have been analyzed. In recent biomedical studies, multidimensional profiling, in which data from multiple types of molecular measurements are collected from the same subjects, is becoming popular. A myriad of recent studies have shown that collectively analyzing multiple types of molecular measurements is not only biologically sensible but also leads to improved estimation and prediction. In this study, we conduct an M–E interaction analysis, with M standing for multidimensional molecular measurements and E standing for environmental risk factors. This can accommodate multiple types of molecular measurements and sufficiently account for their overlapping as well as independent information. Extensive simulation shows that it outperforms several closely related alternatives. In the analysis of TCGA (The Cancer Genome Atlas) data on lung adenocarcinoma and cutaneous melanoma, we make some stable biological findings and achieve stable prediction.
Effects of Graphene Oxidation on Interaction Energy and Interfacial Thermal Conductivity of Polymer Nanocomposite: A Molecular Dynamics Approach

Interfacial characteristics of polymer nanocomposites represent a crucial aspect to understand their global properties and to evaluate the interaction between nanofillers and matrix. In this work we used a molecular dynamics (MD) approach to characterize the interfacial region at the atomistic scale of graphene-based polymer nanocomposites. Three different polymer matrixes were considered, polylactic acid (PLA), polypropylene (PP) and epoxy resin (EPO), which were reinforced with three types of graphene fillers: pristine graphene (G), graphene oxide (GO) and reduced graphene oxide (rGO). In particular, the compatibility of the nanofillers in polymer matrixes were evaluated in terms of the interaction energy, while the interfacial thermal resistance (Kapitza resistance) between matrices and fillers was calculated with a nonequilibrium molecular dynamics (NEMD) method. Results showed that the oxidation degree plays an important role on the studied properties of the interfacial region. In particular, it was observed that the Kapitza resistance is decreased in the oxidized graphene (GO and rGO), while interaction energy depended on the polarity of the polymer matrix molecules and the contribution of the Coulombic component.
Inorganic Element Determination of Romanian Populus nigra L. Buds Extract and In Vitro Antiproliferative and Pro-Apoptotic Evaluation on A549 Human Lung Cancer Cell Line

Populus nigra L. is a plant from Salicaceae family, native in Europe. Many parts of this tree can be used as active ingredients, but the most valuable are the buds. In recent years, a growing number of studies reported their activity in the development of a wide range of pharmacological activities including diabetes, cardiovascular diseases, and cancer. The aim of this study was to determine the phytochemical composition and to evaluate the inorganic elements’ concentration as well as the in vitro antiproliferative and pro-apoptotic potential of a Populus nigra L. buds extract collected from Timișoara (Romania) against A549 human lung cancer cell line. Populus nigra L. bud extract was found to contain twelve different phenolic compounds. The inorganic elements concentrations were below the limit of detection for Co, Pb, and As, whereas Cu = 6.66 µg/g; Cr = 0.79 µg/g; Ni = 3.28 µg/g; Fe = 39.00 µg/g; Zn = 14.84 µg/g; Mn = 0.59 µg/g; Al = 2109.87 µg/g; and Cd = 0.019 µg/g. The extract was tested for the in vitro antiproliferative and pro-apoptotic potential on A549 human lung cancer cell line using different concentrations, namely 10, 25, 50, 75, 100, and 150 μg/mL. Results have shown that poplar bud extract induced a significant decrease of tumor cell viability in a dose-dependent manner with an IC50 = 72.49 μg/mL and blocked the cells in the G0/G1 phase of the cell cycle. Phenomena of early apoptosis (from 1.34 ± 0.33% control cells to 2.68 ± 0.62% at 150 µg/mL) and late apoptosis (from 1.43 ± 0.14% control cells to 5.15 ± 1.02% at 150 µg/mL) were detected by Annexin V-PI double staining. Poplar bud extract can be regarded as a promising candidate for future studies involving lung cancer.
Cubic-Phase Metasurface for Three-Dimensional Optical Manipulation

The optical tweezer is one of the important techniques for contactless manipulation in biological research to control the motion of tiny objects. For three-dimensional (3D) optical manipulation, shaped light beams have been widely used. Typically, spatial light modulators are used for shaping light fields. However, they suffer from bulky size, narrow operational bandwidth, and limitations of incident polarization states. Here, a cubic-phase dielectric metasurface, composed of GaN circular nanopillars, is designed and fabricated to generate a polarization-independent vertically accelerated two-dimensional (2D) Airy beam in the visible region. The distinctive propagation characteristics of a vertically accelerated 2D Airy beam, including non-diffraction, self-acceleration, and self-healing, are experimentally demonstrated. An optical manipulation system equipped with a cubic-phase metasurface is designed to perform 3D manipulation of microscale particles. Due to the high-intensity gradients and the reciprocal propagation trajectory of Airy beams, particles can be laterally shifted and guided along the axial direction. In addition, the performance of optical trapping is quantitatively evaluated by experimentally measured trapping stiffness. Our metasurface has great potential to shape light for compact systems in the field of physics and biological applications.
Path Analysis of the Impact of Obesity on Postoperative Outcomes in Colorectal Cancer Patients: A Population-Based Study

Background: Obesity is adversely affecting perioperative outcomes; however, long-term outcomes do not appear to be affected by excess body weight (the obesity paradox). The purpose of this study is to examine the association between obesity and surgical outcomes in patients with colorectal cancer (CRC) using data from the United States National Inpatient Sample (NIS). Methods: Patients ≥20 years old diagnosed with CRC who received surgery were identified in the 2004–2014 NIS database. Patients who were obese (ICD-9-CM code: 278.0) were matched with controls (non-obese) in a 1:4 ratio for age, sex, and severity of CRC (metastasis vs. no metastasis). Linear regression and path analysis were used to compare outcomes between obese and non-obese patients. A total of 107,067 patients (53,376 males, 53,691 females) were included in the analysis, and 7.86% were obese. Results: The rates of postoperative infection, shock, bleeding, wound disruption, and digestive system complications were significantly different between the obese and non-obese groups. The obesity group had increased incidence of postoperative infection by 1.9% (∂P/∂X = 0.019), shock by 0.25% (∂P/∂X = 0.0025), postoperative bleeding by 0.5% (∂P/∂X = 0.005), wound disruption by 0.6% (∂P/∂X = 0.006), and digestive system complications by 1.35% (∂P/∂X = 0.0135). Path analysis showed that obesity group had higher in-hospital mortality through mentioned above five complications by 66.65 × 10−5%, length of hospital stay by 0.32 days, and total hospital charges by 2384 US dollars. Conclusions: Obesity increases the risk of postoperative complications in patients with CRC undergoing surgery. It also increased in-hospital mortality, length of hospital stay, and total hospital charges. Therefore, patients with obesity might require a higher level of preoperative interventions and complications monitoring to improve outcomes.
High Predatory Capacity of a Novel Arthrobotrys oligospora Variety on the Ovine Gastrointestinal Nematode Haemonchus contortus (Rhabditomorpha: Trichostrongylidae)

With the worldwide development of anthelmintic resistance, new alternative approaches for controlling gastrointestinal nematodes in sheep are urgently required. In this work, we identified and characterized native nematode-trapping fungi. We collected seven isolates of fungi with the capacity to form adhesive, three-dimensional networks as the main mechanism to capture, kill, and consume nematodes. The nematode-trapping fungi were classified into two groups; the first group includes the R2-13 strain, showing faster growth, abundant aerial hyphae, scarce conidia production, bigger conidia, and it formed a clade with Arthrobotrys oligospora sensu stricto. The second comprises the A6, A12, A13, R2-1, R2-6, and R2-14 strains, showing a growth adhering to the culture medium, forming little aerial hyphae, smaller conidia, and these formed a sister clade to A. oligospora. Except for the R2-6 strain, conidia production was induced by light. In all the strains, the predatory capacity against the sheep gastrointestinal nematode Haemonchus contortus was greater than 58% compared with the control group. The A6 and A13 strains were the most active against the infective H. contortus third instar (L3) larvae, with an average capture capacity of 91%. Altogether, our results support evidence for a novel A. oligospora variety with high nematode-trapping activity and promissory in helminthic control.
Identifying mislabelled samples: Machine learning models exceed human performance

Background It is difficult for clinical laboratories to identify samples that are labelled with the details of an incorrect patient. Many laboratories screen for these errors with delta checks, with final decision-making based on manual review of results by laboratory staff. Machine learning models have been shown to outperform delta checks for identifying these errors. However, a comparison of machine learning models to human-level performance has not yet been made. Methods Deidentified data for current and previous (within seven days) electrolytes, urea and creatinine results was used in the computer simulation of mislabelled samples. Eight different machine learning models were developed on 127,256 sets of results using different algorithms: artificial neural network, extreme gradient boosting, support vector machine, random forest, logistic regression, k-nearest neighbours and two decision trees (one complex and one simple). A separate test data-set (n = 14,140) was used to evaluate the performance of these models as well as laboratory staff volunteers, who manually reviewed a random subset of this data (n = 500). Results The best performing machine learning model was the artificial neural network (92.1% accuracy), with the simple decision tree demonstrating the poorest accuracy (86.5%). The accuracy of laboratory staff for identifying mislabelled samples was 77.8%. Conclusions The results of this preliminary investigation suggest that even relatively simple machine learning models can exceed human performance for identifying mislabelled samples. Machine learning techniques should be considered for implementation in clinical laboratories to assist with error identification.
Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System

Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology, an approach, through a monocular camera and marker, was proposed to estimate the pose parameters (including orientation and position) of the excavator manipulator. To simulate the pose estimation process, a measurement system was established with a common camera and marker. Through comprehensive experiments and error analysis, this approach showed that the maximum detectable depth of the system is greater than 11 m, the orientation error is less than 8.5°, and the position error is less than 22 mm. A prototype of the system that proved the feasibility of the proposed method was tested. Furthermore, this study provides an alternative CV technology for monitoring construction machines.
Maturation and Protection Effect of Retinal Tissue-Derived Bioink for 3D Cell Printing Technology

Retinal degeneration is a leading cause of incurable vision loss and blindness. The increasing incidence of retinal degeneration has triggered research into the development of in vitro retinal models for drug development and retinal alternatives for transplantation. However, the complex retinal structure and the retinal microenvironment pose serious challenges. Although 3D cell printing technology has been widely used in tissue engineering, including in vitro model development and regeneration medicine, currently available bioinks are insufficient to recapitulate the complex extracellular matrix environment of the retina. Therefore, in this study, we developed a retinal decellularized extracellular matrix (RdECM) from the porcine retina and evaluated its characteristics. The RdECM conserved the ECM components from the native retina without cellular components. Then, we mixed the RdECM with collagen to form a bioink and confirmed its suitability for 3D cell printing. We further studied the effect of the RdECM bioink on the differentiation of Muller cells. The retinal protective effect of the RdECM bioink was confirmed through a retinal degeneration animal model. Thus, we believe that the RdECM bioink is a promising candidate for retinal tissue engineering.
The process by which patients become aware of unilateral spatial neglect: A qualitative study

ABSTRACT Unilateral spatial neglect (USN), which can occur post-stroke, significantly impacts patients’ daily lives. We explored the process by which patients become aware of the facets of their USN from the acute to subacute phase using a qualitative method. Participant observations, semi-structured interviews, and medical-record surveys were conducted with eight patients with USN and thirty healthcare professionals. We identified three themes regarding the patients’ USN awareness process: inconsistency between present symptoms and perception of the left side, reconsidering the reasons for a vagueness on the left side, and acceptance of neglecting the left side. Additionally, healthcare professionals’ support consisted of four strategies: assessing patients’ perception of stimuli on their left side, compensating for patients’ behaviours, promoting awareness of USN, and promoting activities that involve the use of residual functions after a cerebrovascular accident. Patients with USN gradually became aware of their deficits through interactions with others, and they responded by creating and practicing their own self-developed management strategies. These findings indicate that recovery from USN requires a series of experiences and social interactions. A comprehensive understanding of the process of awareness and adaption to USN from onset to recovery can help provide support for patients with USN.
Proteomic Analysis of Liver from Finishing Beef Cattle Supplemented with a Rumen-Protected B-Vitamin Blend and Hydroxy Trace Minerals

Simple Summary Greater metabolic needs in high-producing beef cattle might lead to mineral and vitamin deficiency. Previous studies have shown the benefits of B-vitamin and trace mineral supplementation in animal performance of ruminants; however, little is known about the effects of supplementing finishing beef cattle with rumen-protected forms on the liver metabolism. Therefore, the aim of the present study was to determinate the impact of rumen-protected B-vitamin blend and hydroxy trace mineral supplementation on the hepatic proteome of finishing steers. This study reports the first evidence indicating that the supplementation of these micronutrients induces protein changes concerning oxidative metabolism and responses to oxidative stress in the liver tissue. Abstract Vitamin B and trace minerals are crucial molecular signals involved in many biological pathways; however, their bioavailability is compromised in high-producing ruminant animals. So far, studies have mainly focused on the effects of these micronutrients on animal performance, but their use in a rumen-protected form and their impact on liver metabolism in finishing beef cattle is poorly known. We used a shotgun proteomic approach combined with biological network analyses to assess the effects of a rumen-protected B-vitamin blend, as well as those of hydroxy trace minerals, on the hepatic proteome. A total of 20 non-castrated Nellore males with 353 ± 43 kg of initial body weight were randomly assigned to one of the following treatments: CTRL—inorganic trace minerals without supplementation of a protected vitamin B blend, or SUP—supplementation of hydroxy trace minerals and a protected vitamin B blend. All animals were fed the same amount of the experimental diet for 106 days, and liver biopsies were performed at the end of the experimental period. Supplemented animals showed 37 up-regulated proteins (p < 0.10), and the enrichment analysis revealed that these proteins were involved in protein folding (p = 0.04), mitochondrial respiratory chain complex I (p = 0.01) and IV (p = 0.01), chaperonin-containing T-complex 2 (p = 0.01), glutathione metabolism (p < 0.01), and other aspects linked to oxidative-stress responses. These results indicate that rumen-protected vitamin B and hydroxy trace mineral supplementation during the finishing phase alters the abundance of proteins associated with the electron transport chain and other oxidation–reduction pathways, boosting the production of reactive oxygen species, which appear to modulate proteins linked to oxidative-damage responses to maintain cellular homeostasis.