Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrophotometric pH measurements in the presence of dissolved organic matter and hydrogen sulfide

Spectrophotometric pH measurements were first introduced for oceanic environments and they facilitated the determination of the marine CO2 system, including the direct observation of Ocean Acidification. Extended characterizations of the indicator dye m‐Cresol purple over the past two decades enabled the application of this method to natural waters ranging from brines to freshwaters. However, the required determination of the dye's dissociation constants and absorbance properties were exclusively performed in buffer solutions prepared with artificial seawater. Potential perturbations by substances that occur in natural waters, but are not included in the buffer solutions, have never been tested. Therefore, we studied the impact of elevated amounts of dissolved organic matter (DOM) and hydrogen sulfide (H2S) on spectrophotometric pH measurements. We did not observe an impact on spectrophotometric pH measurements by H2S concentrations up to 400 μmol kg−1, which reflect high levels such as those reported from the Black Sea. Likewise, natural DOM did not interfere with the spectrophotometric measurements at concentrations typical for oceanic environments and large estuarine systems. However, strongly colored river waters can cause spectral disturbances resulting in calculated pH values that are up to tenths of pH units too low. To circumvent such disturbances, we recommend using intense light sources, a shorter cuvette length or spectrophotometrically calibrated glass electrodes when performing spectrophotometric measurements under critical conditions.
Quantifying the Suicidal Tendency on Social Media: A Survey

Amid lockdown period more people express their feelings over social media platforms due to closed third-place and academic researchers have witnessed strong associations between the mental healthcare and social media posts. The stress for a brief period may lead to clinical depressions and the long-lasting traits of prevailing depressions can be life threatening with suicidal ideation as the possible outcome. The increasing concern towards the rise in number of suicide cases is because it is one of the leading cause of premature but preventable death. Recent studies have shown that mining social media data has helped in quantifying the suicidal tendency of users at risk. This potential manuscript elucidates the taxonomy of mental healthcare and highlights some recent attempts in examining the potential of quantifying suicidal tendency on social media data. This manuscript presents the classification of heterogeneous features from social media data and handling feature vector representation. Aiming to identify the new research directions and advances in the development of Machine Learning (ML) and Deep Learning (DL) based models, a quantitative synthesis and a qualitative review was carried out with corpus of over 77 potential research articles related to stress, depression and suicide risk from 2013 to 2021.
Generative Modeling with Optimal Transport Maps

With the discovery of Wasserstein GANs, Optimal Transport (OT) has become a powerful tool for large-scale generative modeling tasks. In these tasks, OT cost is typically used as the loss for training GANs. In contrast to this approach, we show that the OT map itself can be used as a generative model, providing comparable performance. Previous analogous approaches consider OT maps as generative models only in the latent spaces due to their poor performance in the original high-dimensional ambient space. In contrast, we apply OT maps directly in the ambient space, e.g., a space of high-dimensional images. First, we derive a min-max optimization algorithm to efficiently compute OT maps for the quadratic cost (Wasserstein-2 distance). Next, we extend the approach to the case when the input and output distributions are located in the spaces of different dimensions and derive error bounds for the computed OT map. We evaluate the algorithm on image generation and unpaired image restoration tasks. In particular, we consider denoising, colorization, and inpainting, where the optimality of the restoration map is a desired attribute, since the output (restored) image is expected to be close to the input (degraded) one.
The Criterion for Chaos in Three-planet Systems

We establish the criterion for chaos in three-planet systems, for systems similar to those discovered by the Kepler spacecraft. Our main results are as follows: (i) The simplest criterion, which is based on overlapping mean motion resonances (MMRs), only agrees with numerical simulations at a very crude level. (ii) Much greater accuracy is attained by considering neighboring MMRs that do not overlap. We work out the widths of the chaotic zones around each of the neighbors, and also provide simple approximate expressions for the widths. (iii) Even greater accuracy is provided by the overlap of three-body resonances (3BRs), which accounts for the fine-grained structure seen in maps from N-body simulations, and also predicts Lyapunov times. From previous studies, it is unclear whether interplanetary chaos should be attributed to the overlap of MMRs or of 3BRs. We show that the two apparently contradictory viewpoints are in fact consistent: both predict the same criterion for chaos. (iv) We compare the predicted criterion with high-resolution maps of chaos from N-body simulations, and show that they agree at a high level of detail.
Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies

This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene into a canonical neural radiance field and a set of deformation fields that map observation-space points to the canonical space, thereby enabling them to learn the dynamic scene from images. However, they represent the deformation field as translational vector field or SE(3) field, which makes the optimization highly under-constrained. Moreover, these representations cannot be explicitly controlled by input motions. Instead, we introduce neural blend weight fields to produce the deformation fields. Based on the skeleton-driven deformation, blend weight fields are used with 3D human skeletons to generate observation-to-canonical and canonical-to-observation correspondences. Since 3D human skeletons are more observable, they can regularize the learning of deformation fields. Moreover, the learned blend weight fields can be combined with input skeletal motions to generate new deformation fields to animate the human model. Experiments show that our approach significantly outperforms recent human synthesis methods. The code and supplementary materials are available at https://zju3dv.github. io/animatable_nerf/.
Temporal patterns of wildlife roadkill in the UK

Wildlife-vehicle collisions are one of the main causes of mortality for wild mammals and birds in the UK. Here, using a dataset of 54,000+ records collated by a citizen science roadkill recording scheme between 2014–2019, we analyse and present temporal patterns of wildlife roadkill of the 19 most commonly reported taxa in the UK (84% of all reported roadkill). Most taxa (13 out of 19) showed significant and consistent seasonal variations in road mortality and fitted one of two seasonal patterns; bimodal or unimodal: only three species (red fox Vulpes vulpes, European polecat Mustela putorius and Reeves’ muntjac deer Muntiacus reevesi) showed no significant seasonality. Species that increase movement in spring and autumn potentially have bimodal patterns in roadkill due to the increase in mate-searching and juvenile dispersal during these respective time periods (e.g. European badger Meles meles). Unimodal patterns likely represent increased mortality due to a single short pulse in activity associated with breeding (e.g. birds) or foraging (e.g. grey squirrels Sciurus carolinensis in autumn). Importantly, these patterns also indicate periods of increased risk for drivers, potentially posing a greater threat to human welfare. In addition to behaviour-driven annual patterns, abiotic factors (temperature and rainfall) explained some variance in roadkill. Notably, high rainfall was associated with decreased observations of two bird taxa (gulls and Eurasian magpies Pica pica) and European rabbit Oryctolagus cuniculus. By quantifying seasonal patterns in roadkill, we highlight a significant anthropogenic impact on wild species, which is important in relation to conservation, animal welfare, and human safety.
Interoceptive sensibility predicts the ability to infer others’ emotional states

Emotional sensations and inferring another’s emotional states have been suggested to depend on predictive models of the causes of bodily sensations, so-called interoceptive inferences. In this framework, higher sensibility for interoceptive changes (IS) reflects higher precision of interoceptive signals. The present study examined the link between IS and emotion recognition, testing whether individuals with higher IS recognize others’ emotions more easily and are more sensitive to learn from biased probabilities of emotional expressions. We recorded skin conductance responses (SCRs) from forty-six healthy volunteers performing a speeded-response task, which required them to indicate whether a neutral facial expression dynamically turned into a happy or fearful expression. Moreover, varying probabilities of emotional expressions by their block-wise base rate aimed to generate a bias for the more frequently encountered emotion. As a result, we found that individuals with higher IS showed lower thresholds for emotion recognition, reflected in decreased reaction times for emotional expressions especially of high intensity. Moreover, individuals with increased IS benefited more from a biased probability of an emotion, reflected in decreased reaction times for expected emotions. Lastly, weak evidence supporting a differential modulation of SCR by IS as a function of varying probabilities was found. Our results indicate that higher interoceptive sensibility facilitates the recognition of emotional changes and is accompanied by a more precise adaptation to emotion probabilities.
Comparison of the Incidence of Cardiovascular Diseases in Weight Groups with Healthy and Unhealthy Metabolism

Background We aimed to identify the relationship between metabolically healthy obesity (MHO), a special subtype of obesity, and the incidence of cardiovascular disease (CVD) in rural Xinjiang. Methods Body mass index (BMI) and the Joint Interim Statement criteria were utilized to define obesity and metabolic status, respectively. A baseline survey was conducted between 2010 and 2012. The cohort was followed-up until 2017, including 5059 participants (2953 Uyghurs and 2106 Kazakhs) in the analysis. Results During 6.78 years of follow-up, 471 individuals developed CVD, 10.8% (n=545) of whom were obese, and the prevalence of MHO and MHNW was 5.2% and 54.5%, respectively. Compared with metabolically healthy normal weight subjects, the subjects with MHO had an increased risk of CVD (hazard ratio [HR]=1.76, 95% confidence interval [CI]: 1.23−2.51), while the metabolically unhealthy obesity (MUO) group had an even higher risk (HR=3.80, 95% CI: 2.87−5.03). Additionally, there were sex differences in the relationship between BMI-metabolic status and incident CVD (Pinteraction =0.027). Compared with the subjects with MHO, those with MUO had an increased risk of CVD (HR=1.84, 95% CI: 1.26−2.71). Conclusion MHO was associated with a high risk of CVD among adults in rural Xinjiang. In each BMI category, metabolically unhealthy subjects had a higher risk of developing CVD than did metabolically healthy subjects.
Expression of Sex Hormone Receptor and Immune Response Genes in Peripheral Blood Mononuclear Cells During the Menstrual Cycle

Sex hormones are known to interact with the immune system on multiple levels but information on the types of sex hormone receptors (SHR) and their expression levels in immune cells is scarce. Estrogen, testosterone and progesterone are all considered to interact with the immune system through their respective cell receptors (ERα and ERβ including the splice variant ERβ2, AR and PGR). In this study expression levels of SHR genes in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4+ and CD8+ T-cells, CD56+ NK-cells, CD14+ monocytes and CD19+ B-cells) were analyzed using standard manual qPCR or a qPCR array (TLDA). Nine healthy individuals including men (n = 2), premenopausal (Pre-MP, n = 5) and postmenopausal (post-MP, n = 2) women were sampled for PBMCs which were separated to cell subsets using FACS. Ten Pre-MP women were longitudinally sampled for total PBMCs at different phases of the menstrual cycle. We found that ERα was most abundant and, unexpectedly, that ERβ2 was the dominant ERβ variant in several FACS sorted cell subsets. In total PBMCs, SHR (ERα, ERβ1, ERβ2, and AR) expression did not fluctuate according to the phase of the menstrual cycle and PGR was not expressed. However, several immune response genes (GATA3, IFNG, IL1B, LTA, NFKB1, PDCD1, STAT3, STAT5A, TBX21, TGFB1, TNFA) were more expressed during the ovulatory and mid-luteal phases. Sex hormone levels did not correlate significantly with gene expression of SHR or immune response genes, but sex hormone-binding globulin (SHBG), a steroid hormone transporting protein, was positively correlated to expression of ERβ1 gene. This study provides new insights in the distribution of ERs in immune cells. Furthermore, expression patterns of several immune response genes differ significantly between phases of the menstrual cycle, supporting a role for sex hormones in the immune response.
The role of social support in reducing the impact of violence on adolescents’ mental health in São Paulo, Brazil

Objectives We investigated whether perceived social support among adolescent students moderated the association between violence exposure and internalising symptoms in São Paulo city, Brazil. Methods We tested the stress-buffering model using data from the cross-sectional school-based, survey São Paulo Project on the Social Development of Children and Adolescents. Internalising symptoms were measured using an adapted version of the Social Behaviour Questionnaire; serious victimisation, being bullied once/week, school violence and community violence, friend and teacher support were scales adapted by the research team; the Alabama Parenting Questionnaire measured parenting style. Linear mixed-effects models were used to quantify moderation effects of (i) social support between violence exposure and internalising symptoms and (ii) gender between violence exposure and internalising symptoms across schools. Results Across schools, being bullied once/week, school violence, and community violence were associated with a significant (p<0.001) increase in internalising symptoms (e.g., bullied b = 5.76, 95% CI 2.26, 9.26; school violence b = 0.48, 95% CI 0.30, 0.67; community violence b = 0.36; 95% CI 0.22, 0.50). Males exposed to all types of violence had significantly lower (p<0.01) internalising symptoms compared to females (e.g., serious victimisation: b = -1.45; 95% CI -2.60, -0.29; school violence b = -0.27; 95% CI -0.30, -0.24; community violence b = -0.23; 95% CI -0.25, -0.20). As a main effect, social support was associated with a significant (p<0.01) decrease in internalising symptoms across schools (e.g., positive parenting b = -2.42; 95% CI -3.12, -1.72; parent involvement b = -2.75; 95% CI -3.32, -2.17; friend support b = -1.05; 95% CI -1.74, -0.34; teacher support b = -0.90; 95% CI -1.58, -0.22). Social support did not moderate the association between violence exposure and internalising symptoms. Conclusions Adolescent students in São Paulo exposed to violence have a higher likelihood of internalising symptoms, compared to those who are not. Support from parents, friends, and teachers, independent of violence, appear to be protective against internalising symptoms, pointing to potential programmes that could improve adolescent mental health.
Prospect of Artificial Intelligence Based on Electronic Medical Record

With the advent of the big data era, the interest of the international community is focusing on increasing the utilization of medical big data. Many hospitals are attempting to increase the efficiency of their operations and patient management by adopting artificial intelligence (AI) technology that enables the use of electronic medical record (EMR) data. EMR includes information about a patient's health history, such as diagnoses, medicines, tests, allergies, immunizations, treatment plans, personalized medical care, and improvement of medical quality and safety. EMR data can also be used for AI-based new drug development. In particular, it is effective to develop AI that can predict the occurrence of specific diseases or provide individualized customized treatments by classifying the individualized characteristics of patients. In order to improve performance of artificial intelligence research using EMR data, standardization and refinement of data are essential. In addition, since EMR data deal with sensitive personal information of patients, it is also vital to protect the patient's privacy. There are already various supports for the use of EMR data in the Korean government, and researchers are encouraged to be proactive.
Comparative Analysis of Unsupervised Protein Similarity Prediction Based on Graph Embedding

The study of protein–protein interaction and the determination of protein functions are important parts of proteomics. Computational methods are used to study the similarity between proteins based on Gene Ontology (GO) to explore their functions and possible interactions. GO is a series of standardized terms that describe gene products from molecular functions, biological processes, and cell components. Previous studies on assessing the similarity of GO terms were primarily based on Information Content (IC) between GO terms to measure the similarity of proteins. However, these methods tend to ignore the structural information between GO terms. Therefore, considering the structural information of GO terms, we systematically analyze the performance of the GO graph and GO Annotation (GOA) graph in calculating the similarity of proteins using different graph embedding methods. When applied to the actual Human and Yeast datasets, the feature vectors of GO terms and proteins are learned based on different graph embedding methods. To measure the similarity of the proteins annotated by different GO numbers, we used Dynamic Time Warping (DTW) and cosine to calculate protein similarity in GO graph and GOA graph, respectively. Link prediction experiments were then performed to evaluate the reliability of protein similarity networks constructed by different methods. It is shown that graph embedding methods have obvious advantages over the traditional IC-based methods. We found that random walk graph embedding methods, in particular, showed excellent performance in calculating the similarity of proteins. By comparing link prediction experiment results from GO(DTW) and GOA(cosine) methods, it is shown that GO(DTW) features provide highly effective information for analyzing the similarity among proteins.
Hedera rhombea inhibits the biofilm formation of Candida, thereby increases the susceptibility to antifungal agent, and reduces infection

Candida is an opportunistic pathogen and a common cause of fungal infections worldwide. Anti-fungal use against Candida infections has resulted in the appearance of resistant strains. The limited choice of anti-fungal therapy means alternative strategies are needed to control fungal infectious diseases. The aim of this study was to evaluate the inhibition of Candida biofilm formation by Hedera rhombea (Korean name: songak) extract. Biofilm formation was assessed using the crystal violet assay which showed a dose dependent reduction in the presence of extract with the biofilm formation inhibitory concentration of C. albicans (IC50 = 12.5μg/ml), C. tropicalis var. tropicalis (IC50 = 25μg/ml), C. parapsilosis var. parapsilosis (IC50 = 6.25μg/ml), C. glabrata (IC50 = 6.25μg/ml), C. tropicalis (IC50 = 12.5μg/ml), and C. parapsilosis (IC50 = 12.5μg/ml) without directly reducing Candida growth. Treatment with 6. 25μg/mL of extract increased the antifungal susceptibility to miconazole from 32% decreasing of fungal growth to 98.8% of that based on the fungal growth assay. Treatment of extract dose-dependently reduced the dimorphic transition of Candida based on the dimorphic transition assay and treatment of 3. 125μg/mL of extract completely blocked the adherence of Candida to the HaCaT cells. To know the molecular mechanisms of biofilm formation inhibition by extract, qRT-PCR analysis was done, and the extract was found to dose dependently reduce the expression of hyphal-associated genes (ALS3, ECE1, HWP1, PGA50, and PBR1), extracellular matrix genes (GSC1, ZAP1, ADH5, and CSH1), Ras1-cAMP-PKA pathway genes (CYR1, EFG1, and RAS1), Cph2-Tec1 pathway gene (TEC1) and MAP kinases pathway gene (HST7). In this study, Hedera rhombea extract showed inhibition of fungal biofilm formation, activation of antifungal susceptibility, and reduction of infection. These results suggest that fungal biofilm formation is good screen for developing the antifungal adjuvant and Hedera rhombea extract should be a good candidate against biofilm-related fungal infection.
Pilot study to investigate differences in middle molecules, oxidative stress and markers of peripheral vascular disease in patients treated by high flux haemodialysis and haemodiafiltration

Background Dialysis patients have an increased risk of mortality. Recently treatment with haemodiafiltration (HDF) has been reported to reduce mortality, particularly cardiovascular mortality, compared to standard high-flux haemodialysis (HD). However, why HDF may offer a survival advantage remains to be determined. So, we conducted a pilot study to explore differences in middle-molecules, inflammation and markers of vascular disease in patients treated by HD and HDF. Methods Observational cross-sectional study measuring serum β2-microglobulin (β2M), Advanced Glycosylation End Products (AGEs) by skin autofluorescence (SAF), oxidative stress with ischaemia modified albumin ratio (IMAR) and peripheral vascular disease assessment using Ankle-Brachial Index (ABI), and arterial stiffness using Cardio-Ankle Vascular Index (CAVI). Results We studied 196 patients, mean age 69.1 ± 12.4 years, 172 (87.8%) treated by HD and 24 (12.2%) by HDF. Age, body mass index, co-morbidity and dialysis vintage were not different between HD and HDF groups. Middle molecules; β2M (31±9.9 vs 31.2±10 ug/mL) and SAF (2.99±0.72 vs 3.0±0.84 AU), ABI (1.06±0.05 vs 1.07±0.10) and CAVI (9.34±1.55 vs 9.35±1.23) were not different, but IMAR was higher in the HD patients (38.4±14.8 vs 31.3 ± 17.4, P = 0.035) Conclusions In this pilot observational study, we found patients treated by HDF had lower oxidative stress as measured by IMAR, with no differences in middle molecules. Lower oxidative stress would be expected to have diverse protective effects on the cardiovascular system Although we found no differences in ABI and CAVI, future studies are required to determine whether reduced oxidative stress translates into clinically relevant differences over time.