Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti-DFS70 Antibodies Among Patient and Healthy Population Cohorts in China: Results From a Multicenter Training Program Showing Spontaneous Abortion and Pediatric Systemic Autoimmune Rheumatic Diseases Are Common in Anti-DFS70 Positive Patients

Objective Anti-DFS70 antibodies correlating with the nuclear dense fine speckled (DFS) pattern in the HEp-2 indirect immunofluorescence assay (IFA) are less common in patients with systemic autoimmune rheumatic disease (SARD) than in healthy subjects and their clinical associations remain elusive. We hosted a multi-center HEp-2 IFA training program to improve the ability of clinical laboratories to recognize the DFS pattern and to investigate the prevalence and relevance of anti-DFS70 antibodies. Methods DFS pattern sera identified by HEp-2 IFA in 29 centers in China were redirected to a central laboratory for anti-DFS70 testing by line immunoblot assay (LIA), enzyme-linked immunosorbent assay (ELISA), and IFA with HEp-2 ELITE/DFS70-KO substrate. Anti-extractable nuclear antigen antibodies were measured by LIA and the clinical relevance was examined in adult and pediatric patients. Results HEp-2 IFA positive rate and DFS pattern in positive sera were 36.2% (34,417/95,131) and 1.7% (582/34,417) in the patient cohort, and 10.0% (423/4,234) and 7.8% (33/423) in a healthy population, respectively. Anti-DFS70 prevalence among sera presenting the DFS pattern was 96.0, 93.7, and 49.6% by ELISA, LIA, and HEp-2 ELITE, respectively. 15.5% (52/336) of adult and 50.0% (20/40) of pediatric anti-DFS70 positive patients were diagnosed with SARD. Diseases most common in anti-DFS70 positive patients were spontaneous abortion (28.0%) in adults and juvenile idiopathic arthritis (22.5%) in pediatric patients. Conclusion Accurate DFS pattern identification increased the detection rate of anti-DFS70 antibodies by ELISA and LIA. Anti-DFS70 antibodies are remarkably high in cases of spontaneous abortion and in pediatric SARD patients, but not prevalent in adult SARD patients.
Research and Analysis of Sports Training Real-Time Monitoring System Based on Mobile Artificial Intelligence Terminal

With the rapid development of artificial intelligence, related technologies and applications come into being, and industries based on artificial intelligence are booming, among which image recognition and target tracking technologies are widely used in various fields, especially in the fields of security monitoring and augmented reality. In this paper, combined with the characteristics of athletes, based on mobile artificial intelligence terminal technology, the C/S mode of athlete training process monitoring system is developed and designed, which uses GPS to obtain the real-time position information of athletes and provide real-time guidance for athletes. In order to reveal the changing rules of various indexes of athletes in training state, the author makes synchronous tracking analysis from the aspects of individual sports function characteristics of athletes, training plan arrangement of coaches, brain function state, routine physiological and biochemical indexes, nutrition regulation, and injury conditions.
The Relationship of Symmetry, Complexity, and Shape in Mobile Interface Aesthetics, from an Emotional Perspective - A Case Study of the Smartwatch

Products with interactive interfaces can be seen everywhere, and product interface design aesthetics is a topic that has begun to receive wide attention. Consumers’ perceptions of product interfaces come from their own emotions, and emotion plays a significant role in product interface design aesthetics. In other words, it must meet the users’ emotional and aesthetic requirements. Therefore, we need to better understand the aesthetic design criteria and how they stimulate specific emotional responses. This study takes the dial interface of smartwatches as its experimental sample and explores how the interaction effects of the screen shape (square and round) and the symmetry type and the complexity type of the interface design influence the users’ emotional arousal and valence. In addition, it analyzes the effects of the symmetry type, the complexity type, and the screen shape on the users’ arousal and valence. The results show that the attributes of interface design aesthetics (symmetry-asymmetry, complexity-simplicity, and square-round) affect the users’ emotional responses. Moreover, the interface shape is one of the important factors in the emotional response to an interface design. This paper, based on previous research, provides vital theoretical support for the relevant literature on interface design aesthetics and the users’ emotional state. In addition, it may provide a reference for designers and developers who wish to develop and implement emotional user interfaces that are designed to more effectively appeal to their emotions.
Who Is the Next "Wolf of Wall Street"? Detection of Financial Intermediary Misconduct

Financial intermediaries are essential for investors’ participation in financial markets. Because of their position within the financial system, intermediaries who commit misconduct not only harm investors but also undermine trust in the financial system, which ultimately has a significant negative impact on the economy as a whole. Building upon information manipulation theory and warranting theory and making use of self-disclosed data with different levels of external verification, we propose different classifiers to automatically detect financial intermediary misconduct. In particular, we focus on self-disclosed information by financial intermediaries on the business network LinkedIn. We match user profiles with regulator-disclosed information and use these data for classifier training and evaluation. We find that self-disclosed information provides valuable input for detecting financial intermediary misconduct. In terms of external verification, our classifiers achieve the best predictive performance when also taking regulator-confirmed information into account. These results are supported by an economic evaluation. Our findings are highly relevant for both investors and regulators seeking to identify financial intermediary misconduct and thus contribute to the societal challenge of building and ensuring trust in the financial system.
Capillary Electrophoresis Coupled with Electrochemiluminescence for the Facile Separation and Determination of Salbutamol and Clenbuterol in Urine

A capillary electrophoresis coupled with tris(2,2'-bipyridyl) ruthenium(II) (Ru(bpy)32+) electrochemiluminescence detection system was developed to determine salbutamol and clenbuterol in urine. Some factors that affected the performances of separation and detection were investigated. Under the optimized conditions, one single quantitative analysis of salbutamol and clenbuterol was achieved at a separation voltage of 15 kV within 9 min, and the LODs (S/N=3) and LOQs (S/N=10) of salbutamol and clenbuterol were 8.43x10-8 mol/L, 2.61x10-7 mol/L and 2.73x10-7 mol/L, 8.21x10-7 mol/L, respectively. The recovery obtained from the analysis of spiked urine samples was between 88.6? % and 104.7? % with RSDs lower than 6.70? %. The method was successfully applied to determine salbutamol and clenbuterol in urine samples.
Wavelet Feature Outdoor Fingerprint Localization Based on ResNet and Deep Convolution GAN

Due to the explosive development of location-based services (LBS), localization has attracted significant research attention over the past decade. Among the associated techniques, wireless fingerprint positioning has garnered much interest due to its compatibility with existing hardware. At present, with the widespread deployment of long-term evolution (LTE) networks and the uniqueness of wireless information fingerprints, fingerprint positioning based on LTE networks is the mainstream method for outdoor positioning. However, in order to improve its accuracy, this method needs to collect enough data at a large number of reference points, which is a labor-intensive task. In this paper, experimental data are collected at different reference points and then converted into wavelet feature maps. Then, a Deep Convolutional Generative Adversarial Network (DCGAN) is leveraged to generate a symmetric fingerprint database. Localization is then carried out by the proposed Deep Residual Network (Resnet), which is capable of learning reliable features from a fingerprint image database. To further increase the robustness of the positioning system, a variety of data enhancement methods are used. Finally, we experimentally demonstrate that the generated symmetric fingerprint database and proposed Resnet reduce the manpower required for fingerprint database collection and improve the accuracy of the outdoor positioning system.
The Potential Benefits of HPV E6/E7 mRNA Test in Cervical Cancer Screening in China

This study aims to evaluate the clinical performance of the HPV E6/E7 mRNA test in cervical cancer screening in China. A hospital-based study was conducted with mRNA, DNA, and liquid-based cytology (LBC) as primary screening tests. Each woman with a positive result received colposcopy with lesion-targeted-biopsy. Histopathological diagnosis was used as the gold standard. The total agreement of HPV DNA and mRNA was 90.7% (95%CI: 87.9, 92.9) with a kappa value of 0.81. The positive rates of HPV DNA, mRNA, and LBC increased with the severity of histopathology diagnosis, from 25.5, 19.1, and 11.4% in normal to 100.0% in SCC, respectively. The sensitivities for mRNA to detect CIN2+ and CIN3+ were 93.8% (95%CI: 89.7–96.4) and 95.7% (95%CI: 91.3–97.9), respectively, which were not different from HPV DNA testing (95.7% [95%CI: 92.0–97.7], 96.3% [95%CI: 92.1–98.3]), but higher than LBC (80.4% [95%CI: 74.5–85.2] and 88.8% [95%CI: 83.0–92.8]). The specificities for mRNA to detect CIN2+ (79.0% [95%CI: 74.2–83.0]) and CIN3+ (70.5% [95%CI: 65.7–74.9]) were higher than HPV DNA testing (71.0% [95%CI: 65.9–75.7], 62.8% [95%CI: 57.8–67.5]), but lower than LBC (84.5% [95%CI: 80.1–88.0] 79.8% [95%CI: 75.4–83.6]). All tests were more effective in women older than 30 years. HPV mRNA test showed excellent agreement with the DNA test, with similar sensitivity and a higher specificity in detecting high-grade cervical lesions. It is promising that mRNA test could be used for the national cervical cancer screening to reduce false positive without losing sensitivity.
Cognitive Modeling of Automation Adaptation in a Time Critical Task

This paper presents a cognitive model that simulates an adaptation process to automation in a time-critical task. The paper uses a simple tracking task (which represents vehicle operation) to reveal how the reliance on automation changes as the success probabilities of the automatic and manual mode vary. The model was developed by using a cognitive architecture, ACT-R (Adaptive Control of Thought-Rational). We also introduce two methods of reinforcement learning: the summation of rewards over time and a gating mechanism. The model performs this task through productions that manage perception and motor control. The utility values of these productions are updated based on rewards in every perception-action cycle. A run of this model simulated the overall trends of the behavioral data such as the performance (tracking accuracy), the auto use ratio, and the number of switches between the two modes, suggesting some validity of the assumptions made in our model. This work shows how combining different paradigms of cognitive modeling can lead to practical representations and solutions to automation and trust in automation.
Affective and Stress Consequences of Cyberbullying

The primary objective of this study was to investigate the effects of cyberbullying through social exclusion and verbal harassment on emotional, stress, and coping responses. Twenty-nine undergraduate students (16 females aged 18.25 ± 0.58 years and 13 males aged 18.46 ± 1.13 years) volunteered for the study. All volunteers participated in two experiments that stimulated cyberbullying through social exclusion or verbal harassment. In the first experiment, the effects of cyberbullying through social exclusion were investigated using a virtual ball-tossing game known as Cyberball. In the second experiment, the influence of cyberbullying through verbal harassment was tested using a hypothetical scenario together with reading of online comments. Emotional, stress, and coping responses were measured via the Positive Affect and Negative Affect Scale, the Dundee Stress State Questionnaire, and the Coping Inventory for Task Stress, respectively. The results demonstrated that social exclusion and verbal harassment induced a negative emotional state. We also found that verbal harassment through the use of impolite language increased engagement, and increased worry compared with social exclusion effects.
A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

Many scientific papers are devoted to solving multi-criteria problems. Researchers solve these problems, usually using methods that find discrete solutions and with the collaboration of domain experts. In both symmetrical and asymmetrical problems, the challenge is when new decision-making variants emerge. Unfortunately, discreet identification of preferences makes it impossible to determine the preferences for new alternatives. In this work, we propose a new approach to identifying a multi-criteria decision model to address this challenge. Our proposal is based on stochastic optimization techniques and the characteristic objects method (COMET). An extensive work comparing the use of hill-climbing, simulated annealing, and particle swarm optimization algorithms are presented in this paper. The paper also contains preliminary studies on initial conditions. Finally, our approach has been demonstrated using a simple numerical example.
Graphene Oxide Hybridised TiO2 for Visible Light Photocatalytic Degradation of Phenol

In industrial pollutants, phenol is a kind of degradation-resistant hazardous compound. It is generated during industrial processes in factories and treatment at sewage plants. In this study, we analyse the photocatalytic activity of TiO2 and rGO as a composite for the degradation of phenol. Hybridised titanium dioxide/reduced graphene oxide (TiO2/rGO) nanocomposites were synthesised by a simple hydrothermal method using flake graphite and tetrabutyl titanate as raw materials. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brunauer–Emmet–Teller (BET) specific area analysis, Fourier transform infrared spectroscopy (FTIR), Raman, X-ray photoelectron spectroscopy (XPS), photoelectrochemical analysis, and UV–vis diffuse reflectance spectra (DRS) were employed to characterise the physicochemical properties of the as-prepared nanocomposites. The results showed the TiO2/rGO nanocomposites’ significant anatase phase and a small fraction of the rutile phase the same as that of the as-prepared TiO2 nanoparticles. The spherical TiO2 nanoparticles (diameter 20–50 nm) were agglomerated slightly and the agglomerates were anchored on the rGO sheets and dispersed symmetrically. The specific surface area of TiO2/rGO-4% nanocomposites was 156.4 m2/g, revealing a high specific surface area. Oxygen-containing functional groups that existed in TiO2/rGO-4% nanocomposites were almost removed during hydrothermal processing. The photocurrent response of TiO2/rGO-4% was strongest among the TiO2/rGO nanocomposites, and the bandgap of TiO2/rGO-4% was 2.91 eV, showing a redshift of absorption into the visible region, which was in favour of the high photocatalytic activity of TiO2/rGO nanocomposites under visible light (λ > 420 nm). Moreover, the samples were employed to photodegrade phenol solution under visible light irradiation. TiO2/rGO-4% nanocomposite degraded the phenol solution up to 97.9%, and its degradation rate constant was 0.0190 h−1, which had higher degradation activity than that of other TiO2/rGO nanocomposites. This is a promising candidate catalyst material for organic wastewater treatment.
BEHAVIOUR OF SHELDUCKS TADORNA TADORNA IN A WINTER FLOCK: DOES REGULATION OCCUR?

SUMMARY (1) This study sets out to test the hypothesis of Jenkins, Murray & Hall (1975) that the size of the population of shelducks at Aberlady Bay, East Lothian, is regulated by competition for feeding space in the late winter flock, the formation of a dominance hierarchy and exclusion of subordinate birds. (2) The predictions of this hypothesis were tested, using individually marked birds, by removal and re-addition experiments, observations of aggressive interactions and feeding behaviour in the winter flock and of subsequent territoriality and breeding performance. (3) Experimental removals of birds from the winter flock were not followed by settlement of an equivalent number of birds, even though birds were passing through the area.
The detection of Alternaria solani infection on tomatoes using ensemble learning

This paper presents a detection method of Alternaria solani in tomatoes. Several machine learning models were used to detect the pathogen, such as the implementation of decision trees and ensemble learning methods. The use of these methods requires the acquisition of large volumes of data and adequate preprocessing of this data. For the presented study the dataset of hyperspectral measurements of two varieties of tomatoes was used. Measurements were split into two groups: one inoculated with the Alternaria solani pathogen and the other one was treated as the reference. Measurements were taken by the spectroradiometer in consecutive measurement series. The main part of the study was the evaluation of the decision trees and the popular ensemble learning algorithms to select the most accurate one. After subsequent iterations of the training process and adjustment of hyperparameters, satisfactory accuracy results, equal to 0.987 for random forest, were obtained. This paper also covers the examination of the spectral range required for Alternaria solani identification. From several variants, the accuracy of models based on VIS and NIR spectral range was the closest to the accuracy obtained with the whole spectrum of measured absolute reflectance.
Diet of nestling winter wrens in relationship to food availability

We identified major arthropod taxa in the feces of nestling Winter Wrens (Troglodytes troglodytes) and quantified their number, size, and biomass. These data were compared with samples of arthropods obtained from habitats and microhabitats that were typical of breeding territories. Larval Lepidoptera on shrubs in the clearcut were more numerous and had a higher biomass than those on shrubs in forested areas. Total arthropod biomass, the biomass of Coleoptera, and numbers of Araneae on Vaccinium shrubs were higher in the forest. On the ground, numbers and biomass of most taxa were higher in the clearcut than in the forest. Coleoptera and Araneae were fed to nestlings in high proportions relative to their proportionate numbers and biomass in the environmental samples.
Diversity of endophytic fungi associated with Ginkgo biloba

The endophytic fungi were isolated from samples of roots, branches, leaves and bark of Ginkgo biloba from Fujian, Jiangsu and Guizhou provinces in China. They were identified based on morphology and ITS rDNA sequences. Amongst the 175 isolates, 47 groups were erected with their morphological characteristics. One representative isolate of each group was selected for ITS sequencing and phylogenetic analysis. The results showed that all the fungal isolates belonged to eight different fungal groups, namely Eurotiales, Hypocreales, Xylariales, Trichosphaeriales, Glomerellales, Diaporthales, Botryosphaeriales and Pleosporales in Ascomycota. Colletotrichum, Alternaria, Fusarium and Phomopsis were the dominant genera. For the first time, the genera Neonectria and Bionectria were isolated from G. biloba. The Shannon-Wiener and Simpson diversity index values for the overall fungal community were H=2.4192 and 1-D=0.8856, respectively, which suggest that G. biloba harbors highly diverse mycota.
The genetic basis of natural variation in C. elegans telomere length

Telomeres are involved in the maintenance of chromosomes and the prevention of genome instability. Despite this central importance, significant variation in telomere length has been observed in a variety of organisms. The genetic determinants of telomere-length variation and their effects on organismal fitness are largely unexplored. Here, we describe natural variation in telomere length across the Caenorhabditis elegans species. We identify a large-effect variant that contributes to differences in telomere length. The variant alters the conserved oligosaccharide/oligonucleotide-binding fold of POT-2, a homolog of a human telomere-capping shelterin complex subunit. Mutations within this domain likely reduce the ability of POT-2 to bind telomeric DNA, thereby increasing telomere length. We find that telomere-length variation does not correlate with offspring production or longevity in C. elegans wild isolates, suggesting that naturally long telomeres play a limited role in modifying fitness phenotypes in C. elegans.
Primary Studies on Community Ecology of Floating Algae in Poyang Lake

Seasonal observations were made on species composition of floating algae, their quantitaties, distribution and their relations with environmental factors in Poyang Lake during October 1987 to March 1993. Three hundreds and nineteen species of floating algae were identified. Of which, 169 species belong to 83 genera of Chlorophyta; 73 species to 32 genera of Bacilliariphyta; and 43 species to 25 genera of Cyanophyta; The dominant species were Selenastrum biliraianum, Cryptomonas marrssonii, Dinobryon sertuldaria, Fragilaria crotonensis, Chirella vularis and Scenedesmus bijiga, Cryptomonas ovata, Oscillatoria amoena, Fragilaria virescens, Closterium tumidum, Dactylococcopsis acicularis, Oscillatoria formosa, Tribonema vulgare and Ulotherix moniliformis. The annual mean density in the whole lake was 51.52 ind. /L. The maximum density of 118.2×10 4 ind. /L occurred in IV station in October, and the minimum density of 19.6×10 4 ind. /L in Ⅲ station in July, and Chlorophyta was the most abundant, with an average density of 21.7×10 4 ind. /L in the whole lake. The water quality of Poyang Lake was also evaluated with TSI and other index standards.
Consensus-based Nodal Pricing Mechanism for Automated Demand Response Considering Congestion Management on Distribution Networks

This paper investigates a consensus-based nodal pricing mechanism for incenting automated demand response in the deregulated market environment. These small-scale customers are autonomously managed by automated demand response (DR) controllers, which are capable of scheduling user’s load devices to follow a day-ahead 24h price signal from electricity distribution companies (EDC). First, an alternating current optimal power flow (ACOPF) on the distribution network is formulated considering the participation of automated DR. Then, a consensusbased approach is exploited to adjust the nodal price and DR profile for each customer using primal-dual decomposition. The proposed mechanism is compared with a day-ahead pricing (DAP) program on a test distribution network and numerical results have shown promising performance in supporting the congestion management on the distribution grid.