Miracle-dz/UniFAR-FTUs huggingface dataset:
WeLa-VAE: Learning Alternative Disentangled Representations Using Weak Labels

Learning disentangled representations without supervision or inductive biases, often leads to non-interpretable or undesirable representations. On the other hand, strict supervision requires detailed knowledge of the true generative factors, which is not always possible. In this paper, we consider weak supervision by means of high-level labels that are not assumed to be explicitly related to the ground truth factors. Such labels, while being easier to acquire, can also be used as inductive biases for algorithms to learn more interpretable or alternative disentangled representations. To this end, we propose WeLa-VAE, a variational inference framework where observations and labels share the same latent variables, which involves the maximization of a modified variational lower bound and total correlation regularization. Our method is a generalization of TCVAE, adding only one extra hyperparameter. We experiment on a dataset generated by Cartesian coordinates and we show that, while a TCVAE learns a factorized Cartesian representation, given weak labels of distance and angle, WeLa-VAE is able to learn and disentangle a polar representation. This is achieved without the need of refined labels or having to adjust the number of layers, the optimization parameters, or the total correlation hyperparameter.
Testing correlation of unlabeled random graphs

We study the problem of detecting the edge correlation between two random graphs with $n$ unlabeled nodes. This is formalized as a hypothesis testing problem, where under the null hypothesis, the two graphs are independently generated; under the alternative, the two graphs are edge-correlated under some latent node correspondence, but have the same marginal distributions as the null. For both Gaussian-weighted complete graphs and dense Erdős-Renyi graphs (with edge probability $n^{-o(1)}$), we determine the sharp threshold at which the optimal testing error probability exhibits a phase transition from zero to one as $n\to \infty$. For sparse Erdős-Renyi graphs with edge probability $n^{-\Omega(1)}$, we determine the threshold within a constant factor. The proof of the impossibility results is an application of the conditional second-moment method, where we bound the truncated second moment of the likelihood ratio by carefully conditioning on the typical behavior of the intersection graph (consisting of edges in both observed graphs) and taking into account the cycle structure of the induced random permutation on the edges. Notably, in the sparse regime, this is accomplished by leveraging the pseudoforest structure of subcritical Erdős-Renyi graphs and a careful enumeration of subpseudoforests that can be assembled from short orbits of the edge permutation.
Privacy-preserving targeted mobile advertising: A Blockchain-based framework for mobile ads

The targeted advertising is based on preference profiles inferred via relationships among individuals, their monitored responses to previous advertising and temporal activity over the Internet, which has raised critical privacy concerns. In this paper, we present a novel proposal for a Blockchain-based advertising platform that provides: a system for privacy preserving user profiling, privately requesting ads from the advertising system, the billing mechanisms for presented and clicked ads, the advertising system that uploads ads to the cloud according to profiling interests, various types of transactions to enable advertising operations in Blockchain-based network, and the method that allows a cloud system to privately compute the access policies for various resources (such as ads, mobile user profiles). Our main goal is to design a decentralized framework for targeted ads, which enables private delivery of ads to users whose behavioral profiles accurately match the presented ads, defined by the ad system. We implement a POC of our proposed framework i.e. a Bespoke Miner and experimentally evaluate various components of Blockchain-based in-app advertising system, implementing various critical components; such as, evaluating user profiles, implementing access policies, encryption and decryption of users' profiles. We observe that the processing delay for traversing policies of various tree sizes, the encryption/decryption time of user profiling with various key-sizes and user profiles of various interests evaluates to an acceptable amount of processing time as that of the currently implemented ad systems.
Isochrone fitting of Galactic globular clusters – II. NGC 6205 (M13)

We present new isochrone fits to colour–magnitude diagrams of the Galactic globular cluster NGC 6205 (M13). We utilize 34 photometric bands from the ultraviolet to mid-infrared by use of data from the HST, Gaia DR2, SDSS, unWISE, Pan-STARRS DR1, and other photometric sources. In our isochrone fitting we use the PARSEC, MIST, DSEP, BaSTI, and IAC-BaSTI theoretical models and isochrones, both for the solar-scaled and He–α-enhanced abundances, with a metallicity of about [Fe/H] = −1.58 adopted from the literature. The colour–magnitude diagrams, obtained with pairs of filters from different datasets but of similar effective wavelengths, show some colour offsets up to 0.04 mag between the fiducial sequences and isochrones. We attribute these offsets to systematic differences of the datasets. Some intrinsic systematic differences of the models/isochrones remain in our results: the derived distances and ages are different for the ultraviolet, optical and infrared photometry used, while the derived ages are different for the different models/isochrones, e.g. in the optical range from 12.3 ± 0.7 Gyr for He–α-enhanced DSEP to 14.4 ± 0.7 Gyr for MIST. Despite the presence of multiple stellar populations, we obtain convergent estimates for the dominant population: best-fitting distance 7.4 ± 0.2 kpc, true distance modulus 14.35 ± 0.06 mag, parallax 0.135 ± 0.004 mas, extinction AV = 0.12 ± 0.02, and reddening E(B − V) = 0.04 ± 0.01. These estimates agree with other recent estimates; however, the extinction and reddening are twice as high as generally accepted. The derived empirical extinction law agrees with the Cardelli–Clayton–Mathis extinction law with the best-fitting $R_\mathrm{V}=3.1^{+1.6}_{-1.1}$.
Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep Reinforcement Learning Approach

Industrial robot manipulators are playing a significant role in modern manufacturing industries. Though peg-in-hole assembly is a common industrial task that has been extensively researched, safely solving complex, high-precision assembly in an unstructured environment remains an open problem. Reinforcement-learning (RL) methods have proven to be successful in autonomously solving manipulation tasks. However, RL is still not widely adopted in real robotic systems because working with real hardware entails additional challenges, especially when using position-controlled manipulators. The main contribution of this work is a learning-based method to solve peg-in-hole tasks with hole-position uncertainty. We propose the use of an off-policy, model-free reinforcement-learning method, and we bootstraped the training speed by using several transfer-learning techniques (sim2real) and domain randomization. Our proposed learning framework for position-controlled robots was extensively evaluated in contact-rich insertion tasks in a variety of environments.
Online Visual Tracking with One-Shot Context-Aware Domain Adaptation

Online learning policy makes visual trackers more robust against different distortions through learning domain-specific cues. However, the trackers adopting this policy fail to fully leverage the discriminative context of the background areas. Moreover, owing to the lack of sufficient data at each time step, the online learning approach can also make the trackers prone to over-fitting to the background regions. In this paper, we propose a domain adaptation approach to strengthen the contributions of the semantic background context. The domain adaptation approach is backboned with only an off-the-shelf deep model. The strength of the proposed approach comes from its discriminative ability to handle severe occlusion and background clutter challenges. We further introduce a cost-sensitive loss alleviating the dominance of non-semantic background candidates over the semantic candidates, thereby dealing with the data imbalance issue. Experimental results demonstrate that our tracker achieves competitive results at real-time speed compared to the state-of-the-art trackers.
Unsupervised Deep Metric Learning via Orthogonality Based Probabilistic Loss

Metric learning is an important problem in machine learning. It aims to group similar observations together. Existing state-of-the-art metric learning approaches require class labels to induce a metric. Sometimes it is expensive or not possible to collect these labels. In this paper, we propose an unsupervised learning approach that learns a metric without making use of class labels. The lack of class labels is compensated by obtaining pseudo-labels of data using a graph-based clustering approach. The pseudo-labels are used to form triplets of examples, which guide the metric learning process. We propose a probabilistic loss function that minimizes the chances of each triplet violating an angular constraint. A weight function and an orthogonality constraint in the objective speed up convergence and avoid a model collapse. We also provide a stochastic formulation of our method to scale up to large-scale datasets. Our studies demonstrate the competitiveness of our approach against state-of-the-art methods. Impact Statement —Adequately detecting the similarity among two observations is the essence of many Artificial Intelligence (AI) algorithms, and to an extent, impacts their success. Similarity, hence distance, depends on the manner we represent observations. Existing AI algorithms that automatically learn a good representation of data, require huge manual intervention and effort in the form of annotations. However, it is not possible in many crucial applications to obtain a large amount of manually annotated data. For example, some applications of significant technological and economic impacts, such as invasive medical imaging, insurance, and computer security, produce a huge amount of unlabeled data. We present an algorithm for this problem that when compared to a rival, increased recall between 1.4% to 6.4%.
Bimanual coordination: neuromagnetic and behavioral data

It has been suggested that bimanual coordination is associated with stronger activation of the left motor cortex in right-handers. The aim of the present study was to investigate whether left motor cortex dominance constitutes a fundamental feature of bimanual coordination. We investigated neuromagnetic responses while subjects performed a bimanual tapping task using a 122-channel whole-head neuromagnetometer. Three neuromagnetic sources localized in the primary sensorimotor cortex of each hemisphere were found. Sources represent neuromagnetic correlates of the motor command and of somatosensory feedback. Since we found no differences of amplitudes or latencies of corresponding sources of both hemispheres, our data suggest that dominance of the left motor cortex is not a fundamental characteristic for bimanual coordination.
Determination of Hematological and Biochemical Parameters in Three Stocks of Mice

Hematological and blood bicohemical Parameters of three stocks of mice were determinated.The results showed:(1)Hematological values:There was significant differences in neutrophil and Lymphocyte cells of BALB/c inbred strain between sexes;There was no significant difference between sexes in C 57 BL/6J inbred strain and KM closed colony.The km mouse had lower white blood\|cell count than that of BALB/c and C 57 BL/6J inbred strain;The BALB/c inbred strain had lower eosinophil and basophilic cells than those of C 57 BL/6J inbred strain and KM mouse. (2)Biochemical values:The C 57 BL/6J inbred strain had higher CHO\,Tbili\,ALT\,AST than those of BALB/c and KM mouse,But the KM mouse had lower Cl than those of BALB/c and C 57 BL/6J inbred strain.The BALB/c inbred strain had higher Ck than those of C 57 BL/6J inbred strain.
Shade-Inducible Gene Expression Change in Arabidopsis thaliana at Different Temperatures

We tested whether the plant response to an environmental factor could be affected by the context of another factor by using shade avoidance response at different temperatures. Depleting the red light (R; λmax = 660 nm) and/or enriching the far-red light (FR; λmax = 730 nm) results in a low R:FR ratio in the environment, which induces shade avoidance response such as elongation of petioles and reduction of plant pigments. On the other hand, warmer environmental temperature is known to mimic shade avoidance response under normal light condition, suggesting a potential crosstalk between the temperature and the light quality signals. Therefore, we investigated the patterns of gene expression responses to low R:FR ratio in different temperature contexts (22°C and 26°C) through microarray analyses. Similar, yet distinct patterns between the two responses were implicated by the levels of correlation in the commonly affected MapMan bins. However, the induction levels of typical shade genes such as ATHB2, IAA29, IAA19, HFR1, YUC8, and FT were very similar at both temperatures. Moreover, petiole length, chlorophylls, carotenoids, and anthocyanins contents did not support any statistically significant interaction between the light quality and the high temperature responses despite the obvious independent effect of each signal, which suggests cumulative effects of two independent responses. Nevertheless, other types of low R: FR-responsive genes with differential expression patterns at different temperatures were identified. They are overrepresented in secondary metabolism, lipid transport, oxidative stress, jasmonic acid, ethylene, light, pathogen defense responses, and extracellular region.
The Chinese-bilingual SCID-I/P Project: Stage 1 — Reliability for Mood Disorders and Schizophrenia

Objective: To report on the reliability of the Chinese-bilingual Structured Clinical Interview for DSM-IV (Axis I, Patient version) Project (CB-SCID-I/P), stage 1: ‘Mood disorders’ and ‘Schizophrenia and other psychotic disorders’. Patients and Methods: The CB-SCID-I/P project is a multi-staged translation-validation study of the SCID-I/P (patient research version 2.0, 8/98 revision). Inpatients from the Prince of Wales Hospital were consecutively recruited. Two DSM-IV diagnostic groups were chosen for reliability study for this stage: ‘mood disorders’ and ‘schizophrenia and other psychotic disorders’. Testretest and joint assessment methods were used to assess inter-rater reliability and clinicians’ best-estimate diagnosis was used to assess rater-clinician reliability. Kappa value was used to represent the level of reliability. Results: 144 inpatients were recruited during a 4-month period. The overall kappa for interrater reliability was 0.84, with percentage agreement at 89.6%. Rater-clinician reliability had a kappa of 0.84 for bipolar affective disorder, 0.76 for mood disorder, and 0.75 for schizophrenia. The overall kappa value was 0.77. Conclusion: A good degree of agreement was achieved between the SCID raters as well as between the rater and clinician diagnoses. The Chinese-bilingual SCID-I/P is therefore a reliable instrument in generating DSM-IV schizophrenia and mood disorders diagnoses for inpatients.
The occurrence of sclerotium rot on Momordica charantia caused by Sclerotium rolfsii in Korea

Sclerotium rolfsii is one of the most destructive pathogens and thought to affect a broad range of plant hosts. In July 2014, an occurrence of sclerotium rot was observed on bitter melon (Momordica charantia L.) in Jinju, South Korea. The rot symptoms were most developed on stems and fruit near the soil line, and infected bitter melon plants withered and eventually died. White mycelial mats with numerous sclerotia were produced on diseased stems and fruit near the soil surface. Based on the morphological characteristics, pathogenicity tests, and DNA sequencing and phylogenetic analysis of the internal transcribed spacer (ITS) ribosomal RNA (rRNA) gene region, the causal fungus was identified as S. rolfsii Saccardo. This is the first report of sclerotium rot caused by S. rolfsii on bitter melon in Korea. The recent occurrence of sclerotium rot on bitter melon poses a potential threat to its production in Korea.
Secondary Structural and Functional Studies of Rotavirus NSP4 and Caveolin-1 Peptide-Peptide Interactions

Secondary Structural and Functional Studies of Rotavirus NSP4 and Caveolin-1 PeptidePeptide Interactions. (December 2009) Megan Elizabeth Schroeder, B.A., Bellarmine University Chair of Advisory Committee: Dr. Judith M. Ball The rotavirus NSP4 protein is the first described viral enterotoxin. Abundant data from our laboratory reveals that NSP4 binds both the Nand C-termini of caveolin1 (aa2-31 and 161-178, respectively). Yeast two-hybrid and peptide binding analysis mapped the caveolin-1 binding site to three hydrophobic residues within the amphipathic -helix, enterotoxic peptide domain (aa114-135). The research studies herein utilized peptides to investigate the interaction between NSP4 and caveolin-1. Peptides were synthesized corresponding to the amphipathic -helix and caveolin-1 binding domain of NSP4 (aa112-140) and to the N(aa2-20 and 19-40) and C(161-178) termini of caveolin-1, and were utilized in structural and functional studies. Fluorescence binding assays revealed that NSP4 (aa112-140) binds to the N-terminus (aa19-40) of caveolin-1 with a stronger affinity than the C-terminus (aa161-178). In addition, this assay further delineated the NSP4 binding domain on caveolin-1 to aa19-40. Secondary structural changes following NSP4-caveolin-1 peptide-peptide interactions were investigated by circular dichroism analysis. Changes in -helix formation were observed only upon
Changes in Circulating Extracellular Vesicles in Patients with ST-Elevation Myocardial Infarction and Potential Effects of Remote Ischemic Conditioning—A Randomized Controlled Trial

(1) Background: Extracellular vesicles (EVs) have been recognized as a cellular communication tool with cardioprotective properties; however, it is unknown whether cardioprotection by remote ischemic conditioning (RIC) involves EVs. (2) Methods: We randomized patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI) to additionally receive a protocol of RIC or a sham-intervention. Blood was taken before and immediately, 24 h, four days and one month after PCI. Additionally, we investigated EVs from healthy volunteers undergoing RIC. EVs were characterized by a high-sensitive flow cytometer (Beckman Coulter Cytoflex S, Krefeld, Germany). (3) Results: We analyzed 32 patients (16 RIC, 16 control) and five healthy volunteers. We investigated platelet-, endothelial-, leukocyte-, monocyte- and granulocyte-derived EVs and their pro-thrombotic sub-populations expressing superficial phosphatidylserine (PS+). We did not observe a significant effect of RIC on the numbers of circulating EVs, although granulocyte-derived EVs were significantly higher in the RIC group. In line, RIC had not impact on EVs in healthy volunteers. Additionally, we observed changes of PS+/PEV, EEVs and PS+/CD15+ EVs irrespective of RIC with time following STEMI. 4) Conclusion: We provide further insights into the course of different circulating EVs during the acute and sub-acute phases of STEMI. With respect to the investigated EV populations, RIC seems to have no effect, with only minor differences found for granulocyte EVs.
Nucleotide variation of the mitochondrial cytochrome B gene in the Malay population

Identification of coding region polymorphism in addition to the hypervariable regions is helpful to increase the value of mitochondrial DNA polymorphic data in forensic genetics. In this study, DNA sequence of the mitochondrial cytochrome b gene was analysed among unrelated ethnic Malays as an initial effort to determine the sequence variation within the cytochrome b gene of mtDNA coding region. Totally 13 different sequence types containing 15 polymorphic sites were found. Sequence positions with high frequency and a novel polymorphism site were observed. The results suggest that sequence polymorphisms of the human mitochondrial DNA cytochrome b gene can be applied as an additional marker in individual identification for forensic casework and may be valuable in anthropological and population studies. However, more samples must be analysed. K ey Words: coding region, cytochrome B gene, forensic science, Malay population, mitochondrial DNA, nucleotide
Crystal structure and Hirshfeld surface analysis of phenyl(5,7,8a-triphenyl-1,2,3,7,8,8a-hexahydroimidazo[1,2-a]pyridin-6-yl)methanone with an unknown solvent

The crystal exhibits weak intramolecular π–π interactions between the phenyl rings. In the crystal, molecules are linked via pairs of C—H⋯ O, forming inversion dimers. The dimers are further linked by pairs of C—H⋯π interactions, forming infinite chains along the c-axis direction.
Two-Dimensional Image-Based Screening Tool for Infants with Positional Cranial Deformities: A Machine Learning Approach

Positional cranial deformities are relatively common conditions, characterized by asymmetry and changes in skull shape. Although three-dimensional (3D) scanning is the gold standard for diagnosing such deformities, it requires expensive laser scanners and skilled maneuvering. We therefore developed an inexpensive, fast, and convenient screening method to classify cranial deformities in infants, based on single two-dimensional vertex cranial images. In total, 174 measurements from 80 subjects were recorded. Our screening software performs image processing and machine learning-based estimation related to the deformity indices of the cranial ratio (CR) and cranial vault asymmetry index (CVAI) to determine the severity levels of brachycephaly and plagiocephaly. For performance evaluations, the estimated CR and CVAI values were compared to the reference data obtained using a 3D cranial scanner. The CR and CVAI correlation coefficients obtained via support vector regression were 0.85 and 0.89, respectively. When the trained model was evaluated using the unseen test data for the three CR and three CVAI classes, an 86.7% classification accuracy of the proposed method was obtained for both brachycephaly and plagiocephaly. The results showed that our method for screening cranial deformities in infants could aid clinical evaluations and parental monitoring of the progression of deformities at home.