Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating beaked whale’s regional habitat division and local density trends near the Deepwater Horizon oil spill site through acoustics

Pre-spill and post-spill passive acoustic data collected by multiple fixed acoustic sensors monitoring about 2400 km2 area to the west of the Deepwater Horizon oil spill in the northern Gulf of Mexico (GoM) were analyzed to understand long term local density trends and habitat use by different species of beaked whales. The data were collected in the Mississippi Valley/Canyon area between 2007 and 2017. A multistage algorithm based on unsupervised machine learning was developed to detect and classify different species of beaked whales and to derive species- and site-specific densities in different years before and after the oil spill. The results suggest that beaked whales continued to occupy and feed in these areas following the Deepwater Horizon oil spill thus raising concerns about (1) potential long-term effects of the spill on these species and (2) the habitat conditions after the spill. The average estimated local density of Cuvier’s beaked whales at the closest site, about 16 km away from the spill location showed statistically significant increase from July 2007 to September 2010, and then from September 2010 to 2015. This is the first acoustic study showing that Gervais’ beaked whales are predominantly present at the shallow site and that Cuvier’s species dominate at two deeper sites, supporting the habitat division (ecological niche) hypothesis. The findings call for continuing high-spatial-resolution long-term observations to fully characterize baseline beaked whale population and habitat use, to understand the causes of regional migrations, and to monitor the long-term impact of the spill.
Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma

Background Cuproptosis, a unique kind of cell death, has implications for cancer therapy, particularly lung adenocarcinoma (LUAD). Long non-coding RNAs (lncRNAs) have been demonstrated to influence cancer cell activity by binding to a wide variety of targets, including DNA, RNA, and proteins. Methods Cuproptosis-related lncRNAs (CRlncRNAs) were utilized to build a risk model that classified patients into high-and low-risk groups. Based on the CRlncRNAs in the model, Consensus clustering analysis was used to classify LUAD patients into different subtypes. Next, we explored the differences in overall survival (OS), the tumor immune microenvironment (TIME), and the mutation landscape between different risk groups and molecular subtypes. Finally, the functions of LINC00592 were verified through in vitro experiments. Results Patients in various risk categories and molecular subtypes showed statistically significant variations in terms of OS, immune cell infiltration, pathway activity, and mutation patterns. Cell experiments revealed that LINC00592 knockdown significantly reduced LUAD cell proliferation, invasion, and migration ability. Conclusion The development of a trustworthy prediction model based on CRlncRNAs may significantly aid in the assessment of patient prognosis, molecular features, and therapeutic modalities and may eventually be used in clinical applications.
Exploring the pathogenesis and immune infiltration in dilated cardiomyopathy complicated with atrial fibrillation by bioinformatics analysis

Background Atrial fibrillation (AF) is a serious complication of dilated cardiomyopathy (DCM), which increases the risk of thromboembolic events and sudden death in DCM patients. However, the common mechanism of DCM combined with AF remains unclear. This study aims to explore the molecular mechanism and analyze immune infiltration in DCM complicated with AF through comprehensive bioinformatics analysis. Methods The gene expression datasets of DCM (GSE141910) and AF (GSE41177 and GSE79768) were obtained from the Gene Expression Omnibus database. Gene enrichment analyses were performed after screening the common differentially expressed genes (DEGs) of DCM and AF. Protein-protein interaction network was constructed in the STRING database and visualized in Cytoscape software, which helped to further screen the central functional modules of DEGs and hub genes. In addition, ImmuCellAI algorithm was performed to estimate immune infiltration patterns, and Spearman correlation was conducted to investigate the correlation between the abundance of multiple immune cells and the expression levels of hub immune-related genes after obtaining hub immune-related genes from the ImmPort database. The hub immune-related genes expression and immune infiltration patterns were additionally verified in the validation datasets (GSE57338, GSE115574, and GSE31821). The diagnostic effectiveness of hub immune-related genes was evaluated through Receiver Operator Characteristic Curve analysis. Results A total of 184 common DEGs in DCM and AF were identified for subsequent analyses. The functions of hub genes were significantly associated with immune responses. We identified 7 hub immune-related genes (HLA-DRA, LCK, ITK, CD48, CD247, CD3D, and IL2RG) and a spectrum of immune cell subsets including Monocyte, Neutrophil, and follicular helper T (Tfh) cells were found to be concurrently dysregulated in both DCM and AF. 7 hub immune-related genes were predominantly favorably correlated with Tfh cells and were primarily negatively correlated with Neutrophil infiltrations in DCM and AF. CD48+CD3D were verified to diagnose DCM and AF with excellent sensitivity and specificity, showing favorable diagnostic value. Conclusions Our study reveals that immune cells (Tfh cells) disorders caused by hub immune-related genes (CD48 and CD3D) may be the common pathogenesis of DCM combined with AF, which lays a foundation for further immune mechanism research.
The influence of employees' perception of over-qualification on career compromise: Mediated by role conflict and sense of relative deprivation

In the external environment with the increasing level of education, there is a general phenomenon of excess qualification in the employment market. This research discusses employee career compromise from the perspective of employee over-qualification based on resource conservation theory and self-regulation theory. Combined with the survey data, a structural equation model (SEM) is constructed, and the mediation effect of relative deprivation and role conflict is analyzed according to the causal mediation model. The research find that employees' perception of over-qualification has three ways to affect employees' career compromise. First, employees' perception of over-qualification has a significant positive impact on their career compromise behavior through employees' emotions and self-cognition. Second, role conflict plays a partial intermediary role between the perception of over-qualification and career compromise by positively affecting career compromise behavior. Third, the sense of relative deprivation plays a partial intermediary role between the perception of over-qualification and career compromise by negatively affecting career compromise behavior. According to the research conclusions, the following suggestions are put forward. Enterprises need to establish a scientific employment mechanism to achieve talent-post matching and fundamentally reduce the phenomenon of over-qualifications. The company should pay attention to employee training, actively guide employees' career planning, instruct employees to correctly understand the sense of over-qualification and play a positive role in guiding employees' career planning.
Induced pain affects auricular and body biosignals: From cold stressor to deep breathing

Pain affects every fifth adult worldwide and is a significant health problem. From a physiological perspective, pain is a protective reaction that restricts physical functions and causes responses in physiological systems. These responses are accessible for evaluation via recorded biosignals and can be favorably used as feedback in active pain therapy via auricular vagus nerve stimulation (aVNS). The aim of this study is to assess the significance of diverse parameters of biosignals with respect to their deflection from cold stressor to deep breathing and their suitability for use as biofeedback in aVNS stimulator. Seventy-eight volunteers participated in two cold pressors and one deep breathing test. Three targeted physiological parameters (RR interval of electrocardiogram, cardiac deflection magnitude Z AC of ear impedance signal, and cardiac deflection magnitude PPG AC of finger photoplethysmogram) and two reference parameters (systolic and diastolic blood pressures BP S and BP D) were derived and monitored. The results show that the cold water decreases the medians of targeted parameters (by 5.6, 9.3%, and 8.0% of RR, Z AC, and PPG AC, respectively) and increases the medians of reference parameters (by 7.1% and 6.1% of BP S and BP D, respectively), with opposite changes in deep breathing. Increasing pain level from relatively mild to moderate/strong with cold stressor varies the medians of targeted and reference parameters in the range from 0.5% to 6.0% (e.g., 2.9% for RR, Z AC and 6.0% for BP D). The physiological footprints of painful cold stressor and relaxing deep breathing were shown for auricular and non-auricular biosignals. The investigated targeted parameters can be used as biofeedback to close the loop in aVNS to personalize the pain therapy and increase its compliance.
Fractured morphology of femoral head associated with subsequent femoral neck fracture: Injury analyses of 2D and 3D models of femoral head fractures with computed tomography

Background: The injury of femoral head varies among femoral head fractures (FHFs). In addition, the injury degree of the femoral head is a significant predictor of femoral neck fracture (FNF) incidence in patients with FHFs. However, the exact measurement methods have yet been clearly defined based on injury models of FHFs. This study aimed to design a new measurement for the injury degree of the femoral head on 2D and 3D models with computed tomography (CT) images and investigate its association with FHFs with FNF. Methods: A consecutive series of 209 patients with FHFs was assessed regarding patient characteristics, CT images, and rate of FNF. New parameters for injury degree of femoral head, including percentage of maximum defect length (PMDL) in the 2D CT model and percentage of fracture area (PFA) in the 3D CT-reconstruction model, were respectively measured. Four 2D parameters included PMDLs in the coronal, cross-sectional and sagittal plane and average PMDL across all three planes. Reliability tests for all parameters were evaluated in 100 randomly selected patients. The PMDL with better reliability and areas under curves (AUCs) was finally defined as the 2D parameter. Factors associated with FNF were determined by binary logistic regression analysis. The sensitivity, specificity, likelihood ratios, and positive and negative predictive values for different cut-off values of the 2D and 3D parameters were employed to test the diagnostic accuracy for FNF prediction. Results: Intra- and inter-class coefficients for all parameters were ≥0.887. AUCs of all parameters ranged from 0.719 to 0.929 (p < 0.05). The average PMDL across all three planes was defined as the 2D parameter. The results of logistic regression analysis showed that average PMDL across all three planes and PFA were the significant predictors of FNF (p < 0.05). The cutoff values of the average PMDL across all three planes and PFA were 91.65% and 29.68%. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, predictive positive value and negative predictive value of 2D (3D) parameters were 91.7% (83.3%), 93.4% (58.4%), 13.8 (2.0), 0.09 (0.29), 45.83% (10.87%), and 99.46% (98.29%). Conclusion: The new measurement on 2D and 3D injury models with CT has been established to assess the fracture risk of femoral neck in patients with FHFs in the clinic practice. 2D and 3D parameters in FHFs were a feasible adjunctive diagnostic tool in identifying FNFs. In addition, this finding might also provide a theoretic basis for the investigation of the convenient digital-model in complex injury analysis.
Chemical and organoleptic evaluation of silages of Sorghum bicolor ( L . ) Moench and Citrus sp . pulp

Objective: To evaluate the chemical composition and organoleptic characteristics of silages of Sorghum bicolor (L.) Moench Citrus sp. pulp. Materials and Methods: The work was done with chopped S. bicolor plant and fresh citrus fruit pulp. A complete randomized factorial design and five treatments were applied: T1) 100 % S. bicolor, T2) 75 % S. bicolor + 25 % citrus fruit pulp, T3) 50 % S. bicolor + 50 % citrus fruit pulp, T4) 25 % S. bicolor + 75 % citrus fruit pulp and T5) 100 % citrus fruit pulp. The silages were evaluated on days 14, 28, 42 and 56 to determine the bromatological and organoleptic characteristics at the moment of final opening (56 days). Variance analysis was carried out to determine the dynamics of chemical composition, for which a linear model was used in which the treatments, times and treatments x times interactions were taken as effects. Results: Treatments T1 and T2 showed excellent organoleptic quality; while T3, T4 and T5 were evaluated as of good quality. The dry matter decreased as the percentage of citrus fruit pulp increased, in a range between 37,5 and 14,1 %. The content of neutral detergent fiber showed significant differences among all the treatments (p < 0,0001) and increased when the percentage of inclusion of citrus fruit pulp decreased in the silages, with values between 31,2 and 70,0 %. The content of the minerals calcium and magnesium showed adequate levels for the requirements of grazing ruminants, between 3,3-4,9 and 1,9-2,4 g/kg DM, respectively, in the silages of S. bicolor and citrus fruit pulp. Conclusions: The organoleptic characteristics of silages confirmed that they had from good to excellent quality. The inclusion of citrus fruit pulp in the mixtures decreased the content of dry matter and neutral detergent fiber; while the crude protein behaved according to the utilized raw materials.
INSURANCE COMPANIES – WHAT DETERMINATES THEIR CREDIT RATINGS

The aim of the paper has been to analyse factors’ influence on insurance companies’ credit ratings. It has been made a literature review, and as a result there have been put the following hypotheses. The first one is: Insurance companies’ credit ratings are determined by capital adequacy, assets quality, management quality, efficiency and liquidity factors. The second one states: Countries’ credit ratings influence statistically significantly on insurance notes. To the analysis there have been used long-term issuer credit ratings proposed by small and big credit rating agencies. To verify the presented hypotheses there have been used ordered logit panel data models. The research has been prepared on quarterly data for all assessed insurance companies from all of the world. Data have been collected from Thomson Reuters Database from 1995 to 2016.
In-depth recommendation model of session-based potential intention and time information

The session-based recommendation system aims to predict the user’s next click behavior based on the anonymous session information of the current user. The existing session-based recommendation system based on recurrent neural network does not consider the user's staying time on the item and the user's potential intention at the same time when the user is modeled. In response to this problem, This paper proposes a deep recommendation model that integrates temporal information and user potential intentions (TAGSR). The Time-LSTM model is used to model the time interval that affects user behavior, and the attention mechanism and CRU gating modeling are used to capture the user's potential intentions. And experiments on two public data sets, the results of Recall@10 and MRR@10 two evaluation indicators have improved, which proves the effectiveness of the model.
Transparency and long-ranged fluctuations: The case of glass ceramics

Glass ceramics with nanosized crystallites shows an unexpected high transparency, which is not accounted for by the Rayleigh theory of light scattering. Simple analytic arguments ascribe this large transparency to large spatial correlations in the number distribution of the nanocrystallites. Introducing a two-dimensional lattice model that mimics the nucleation and the coarsening phenomena leading to their formation, we show that the extent of such correlations is determined by the spatially limited diffusion of the particles that form the crystallites.
PET imaging of retinal inflammation in mice exposed to blue light using [18F]-DPA-714

Purpose Positron emission tomography (PET) is widely used in high-precision imaging, which may provide a simple and noninvasive method for the detection of pathology and therapeutic effects. [18F]-DPA-714 is a second-generation translocator protein (TSPO) positron emission tomography radiotracer that shows great promise in a model of neuroinflammation. In this study, [18F]-DPA-714 micro-PET imaging was used to evaluate retinal inflammation in mice exposed to blue light, a well-established model of age-related macular degeneration (AMD) for molecular mechanism research and drug screening. Methods C57BL/6J melanized mice were subjected to 10,000, 15,000, and 20,000 lux blue light for 5 days (8 h/day) to develop the retinal injury model, and the structure and function of the retina were assessed using hematoxylin–eosin (HE) staining, electroretinography (ERG), and terminal-deoxynucleotidyl transferase (TdT)-mediated nick-end labeling (TUNEL) immunostaining. Then, [18F]-DPA-714 was injected approximately 100 μCi through each tail vein, and static imaging was performed 1 h after injection. Finally, the mice eyeballs were collected for biodistribution and immune analysis. Results The blue light exposure significantly destroyed the structure and function of the retina, and the uptake of [18F]-DPA-714 in the retinas of the mice exposed to blue light were the most significantly upregulated, which was consistent with the biodistribution data. In addition, the immunohistochemical, western blot, and immunofluorescence data showed an increase in microglial TSPO expression. Conclusions [18F]-DPA-714 micro-PET imaging might be a good method for evaluating early inflammatory status during retinal pathology.
Shelter disease surveillance and shelter welfare assessment in short term housing shelters: A cross-sectional study

Six shelters with 7,468 animals (2,305 cats and 5,163 dogs) were followed and diseases and shelter welfare conditions were recorded for one year. Disease records were obtained and categorised on three headings (surgery, internal medicine, and reproductive diseases and interventions) and subheading categories. Descriptive statistics was used to reveal disease distribution, which can attribute to surveillance data. To evaluate shelter welfare conditions, a protocol was developed and shelters were assessed. Under the surgical disease category, the most encountered disease records were open wounds (502, 59.41% and 175, 31.99%) for dogs and cats. For the internal medicine category, the most encountered were respiratory system diseases both for dogs (917, 33.26%) and cats (351, 58.21%). Under the reproductive disease category, the most common disease in dogs was orchitis (29, 60.42%). In cats, the most encountered disease was metritis (19, 79.16%). Ordinal logistic regression was used for evaluation of associations between diseases and shelter conditions. For dogs, with a one-point increase in shelter score, the odds of encountering reproductive diseases increased by 1.4%, while the odds of cumulative and internal diseases decreased 1.1 and 1.2 times (P<0.05) respectively. For cats, with an increase in shelter scores, the odds of encountering reproductive and cumulative diseases increased by 3.4% and 0.2%, respectively (P<0.05). Disease surveillance and their relation with shelter conditions may be helpful to design efficient plans in shelters.
High-sensitivity observations of 28 pulsars

Average 430-MHz pulse profiles and, where possible, modulation indices and pulse-nulling fractions are computed for 28 pulsars. Morphological classifications are determined for most of the pulsars. It is found that core emission components tend to have lower modulation indices than conal components, and that pulsars having only a core component never exhibit pulse pulling. PSR 1612 + 07 is shown to undergo mode changes.
Simulation of the dynamics of laser-cluster interaction

We study the interaction of an intense (I 1015 Wcm-2) femtosecond laser pulse with a large (N > 10000 atoms) rare-gas cluster. The simulations are based on a mean-field classical transport approach. The electronic dynamics during the interaction with the laser are discussed in more detail. In particular we point out the difference in behavior between the fast electrons and the collectively moving slow electrons and try to shed light on the acceleration mechanisms behind the high energy tail of the electron energy distribution. The benchmark for our simulations is experimental X-ray spectroscopy data. We show a comparison with the experimentally found total X-ray yields and charge-state distributions.
FAILURE OF THREE-DIMENSIONAL RANDOM COMPOSITES

Using an optimized bond breaking algorithm, we simulated the failure of three‐dimensional networks composed of two randomly interspersed components. We studied the strength and the number of bonds broken prior to the failure instability (the damage). When one phase is of low concentration, damage mostly occurs when the dilute phase is very weak and fails prematurely, although a limited ‘‘matrix damage’’ mechanism does exist. In contrast, when the composite is a 50/50 mixture and the two phases are macroscopically interpenetrating (both phases percolate), the ability to absorb damage is greatly enhanced. In the interpenetrating phase regime the strength of the composite is, in some cases, enhanced beyond that of the analogous particle reinforced composite. These features suggest that interpenetrating phase composites can have improved properties in comparison to conventional ‘‘particulate’’ composites. Analysis of the composite is neatly summarized in ‘‘damage maps’’ which give a quick indication of the re.
Theoretical study of the transmission properties of a metallic film with surface corrugations

Transmissions through a metallic film at near-infrared wavelengths with different surface corrugations on both sides are systemically studied. The calculations are performed by the three-dimensional finite-different time-domain method. Calculated results show that the transmissions are strongly dependent on the surface structures. Compared with other structures, the transmission for a film periodically drilled by cross air grooves are relatively larger. Transmission is enhanced more with symmetric conditions on both layers than the asymmetric case. The enhanced transmission can be explained by a competition between the absorption in the metal and enhanced transmission due to coupled surface plasmon resonance.
Application of finite-elements to the analysis of diffraction gratings

A numerical technique is presented for analysing diffraction gratings of arbitrary groove shape. The method is based on the application of finite element technique. It is suggested that this technique, thus far reserved mostly for the problems of bounded extent, may be used to advantage for analysing this problem. To this end, the infinite space is divided into two regions, one finite and the other infinite in extent. A series solution is employed in the infinite region, and in the finite one a functional is used. The two solutions are then matched on the common boundary of the two regions. The resulting equation for the field is finally solved by application of the finite element technique. The numerical results obtained for echelette gratings are favourably compared with a number of similar results reported in the literature.