Miracle-dz/UniFAR-FTUs huggingface dataset:
GWAS identifies two novel colorectal cancer loci at 16q24.1 and 20q13.12

Colorectal cancer (CRC) is the fourth leading cause of cancer mortality worldwide. Genome-wide association studies (GWAS) identified more than 50 CRC loci. However, most of the previous studies were conducted in European population, and host genetic factors among Japanese population are largely remained to be identified. To identify novel loci in the Japanese population, here, we performed a large-scale GWAS using 6692 cases and 27 178 controls followed by a replication analysis using more than 11 000 case-control samples. We found the significant association of 10 loci (P < 5 × 10-8), including 2 novel loci on 16q24.1 (IRF8-FOXF1, rs847208, P = 3.15 × 10-9 and odds ratio = 1.107 with 95% confidence interval (CI) of 1.071-1.145) and 20q13.12 (TOX2, rs6065668, P = 4.47 × 10-11 and odds ratio = 0.897 with 95% CI of 0.868-0.926). Moreover, 35 previously reported single nucleotide polymorphisms (SNPs) in 24 regions were validated in the Japanese population (P < 0.05) with the same risk allele as in the previous studies. SNP rs6065668 was significantly associated with TOX2 expression in the sigmoid colon. In addition, nucleotide substitutions in the regulatory region of TOX2 were predicted to alter the binding of several transcription factors, including KLF5. Our findings elucidate the important role of genetic variations in the development of CRC in the Japanese population.
Double-Guided Filtering: Image Smoothing with Structure and Texture Guidance

Image smoothing is a fundamental technology which aims to preserve image structure and remove insignificant texture. Balancing the trade-off between preserving structure and suppressing texture, however, is not a trivial task. This is because existing methods rely on only one guidance to infer structure or texture and assume the other is dependent. However, in many cases, textures are composed of repetitive structures and difficult to be distinguished by only one guidance. In this paper, we aim to better solve the trade-off by applying two independent guidance for structure and texture. Specifically, we adopt semantic edge detection as structure guidance, and texture decomposition as texture guidance. Based on this, we propose a kernel-based image smoothing method called the double-guided filter (DGF). In the paper, for the first time, we introduce the concept of texture guidance, and DGF, the first kernel- based method that leverages structure and texture guidance at the same time to be both 'structure- aware' and 'texture-aware'. We present a number of experiments to show the effectiveness of the proposed filter.
Comparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary

Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation of a word given its graphemic or written form. It is a highly important part of both automatic speech recognition (ASR) and text-to-speech (TTS) systems. In this paper, we evaluate seven G2P conversion approaches: Adaptive Regularization of Weight Vectors (AROW) based structured learning (S-AROW), Conditional Random Field (CRF), Joint-sequence models (JSM), phrase-based statistical machine translation (PBSMT), Recurrent Neural Network (RNN), Support Vector Machine (SVM) based point-wise classification, Weighted Finite-state Transducers (WFST) on a manually tagged Myanmar phoneme dictionary. The G2P bootstrapping experimental results were measured with both automatic phoneme error rate (PER) calculation and also manual checking in terms of voiced/unvoiced, tones, consonant and vowel errors. The result shows that CRF, PBSMT and WFST approaches are the best performing methods for G2P conversion on Myanmar language.
Cobalt: BFT Governance in Open Networks

We present Cobalt, a novel atomic broadcast algorithm that works in networks with non-uniform trust and no global agreement on participants, and is probabilistically guaranteed to make forward progress even in the presence of maximal faults and arbitrary asynchrony. The exact properties that Cobalt satisfies makes it particularly applicable to designing an efficient decentralized "voting network" that allows a public, open-entry group of nodes to agree on changes to some shared set of rules in a fair and consistent manner while tolerating some trusted nodes and arbitrarily many untrusted nodes behaving maliciously. We also define a new set of properties which must be satisfied by any safe decentralized governance algorithm, and all of which Cobalt satisfies.
Microwave MTM-based sensor for blood glucose concentration measurement: Sensitivity analysis by means of numerical simulations

In this work two different models of dielectric properties of blood glucose solutions are used to evaluate metamaterial sensor sensitivity by means of numerical simulations. Model A is adopted from professional literature and the model B was created by our group using information about dielectric properties of blood plasma-glucose solutions, recently published dielectric properties of red blood cell cytoplasm-glucose solutions and an electromagnetic mixing formula. It can be concluded that the sensor shows smaller sensitivity for the model B than for the model A. Furthermore it shows due to non-linear dependency of dielectric properties on glucose concentration predicted by model B a lower sensitivity for high glucose concentrations.
Endurable Transient Inconsistency in Byte-Addressable Persistent B+-Tree

With the emergence of byte-addressable persistent memory (PM), a cache line, instead of a page, is expected to be the unit of data transfer between volatile and non-volatile devices, but the failure-atomicity of write operations is guaranteed in the granularity of 8 bytes rather than cache lines. This granularity mismatch problem has generated interest in redesigning blockbased data structures such as B+-trees. However, various methods of modifying B+-trees for PM degrade the efficiency of B+-trees, and attempts have been made to use in-memory data structures for PM. In this study, we develop Failure-Atomic ShifT (FAST) and Failure-Atomic In-place Rebalance (FAIR) algorithms to resolve the granularity mismatch problem. Every 8-byte store instruction used in the FAST and FAIR algorithms transforms a B+-tree into another consistent state or a transient inconsistent state that read operations can tolerate. By making read operations tolerate transient inconsistency, we can avoid expensive copy-on-write, logging, and even the necessity of read latches so that read transactions can be non-blocking. Our experimental results show that legacy B+-trees with FAST and FAIR schemes outperform the state-of-the-art persistent indexing structures by a large margin.
Fraud detection and frequent pattern matching in insurance claims using data mining techniques

Fraudulent insurance claims increase the burden on society. Frauds in health care systems have not only led to additional expenses but also degrade the quality and care which should be provided to patients. Insurance fraud detection is quite subjective in nature and is fettered with societal need. This empirical study aims to identify and gauge the frauds in health insurance data. The contribution of this insurance claim fraud detection experimental study untangle the fraud identification frequent patterns underlying in the insurance claim data using rule based pattern mining. This experiment is an effort to assess the fraudulent patterns in the data on the basis of two criteria-period based claim anomalies and disease based anomalies. Rule based mining results according to both criteria are analysed. Statistical Decision rules and k-means clustering are applied on Period based claim anomalies outliers detection and association rule based mining with Gaussian distribution is applied on disease based anomalies outlier detection. These outliers depict fraud insurance claims in the data. The proposed approach has been evaluated on real-world dataset of a health insurance organization and results show that our proposed approach is efficient in detecting fraud insurance claim using rule based mining.
Rate analysis and pilot reuse design for dense small cell networks

In this paper, we consider the uplink of a dense small cell network (SCN) using pilot reuse in channel training and maximum ratio combining (MRC) for data detection. Taking into account imperfect channel state information (CSI) caused by pilot contamination, we derive exact closed-form expressions of the per-user achievable ergodic rate with arbitrary pilot reuse factors. After that, we first reveal that the user terminals, which are geographically separated with large distance between each other, can reuse pilot, suffering only low pilot contamination. Based on this insight, we further propose a low-complexity pilot reuse algorithm based on the minimum sum of estimation error criterion. Simulation results verify our theoretical analysis and demonstrate that the proposed pilot reuse algorithm is very effective in suppressing pilot contamination in SCN.
Vagal Ischemia Induced Lung Immune Component Infarct Following Subarachnoid Hemorrhage: An Experimental Study.

AIM Neurogenic pulmonary edema (NPE) is the most serious complication of subarachnoid hemorrhage (SAH). As vagal nerves have vital roles in lung functions, vagal ischemia may have a causative role in the pathogenesis of NPE. We examined whether there was a relationship between vagal complex ischemia and lung immune complexes occupying the lymph node infarct in SAH. MATERIAL AND METHODS Thirty-two rabbits were divided into three groups: Control (n=5), SHAM (n=5) and SAH group (n=22). SAH was created by autologous blood injection into the cisterna magna and followed-up for 3 weeks. Vasospasm index (VSI) was defined as the ratio of the lung lymph node arteries (LLNA) wall section (wall ring) surface to the lumen surface. Degenerated axon numbers of vagal nerves, neuron densities of the nodose ganglion (NG) and VSIs of LLNA were compared for all groups. RESULTS The mean degenerated vagal nerve axon density, neuron density of NG, and VSI of LLNA were 26±8/mm < sup > 2 < /sup > , 30±5/mm < sup > 3 < /sup > , and 0.777±0.048 in the control group; 1300±100/mm2, 720±90/mm < sup > 3 < /sup > , and 1.148±0.090 in the animals with slight vasospasm (n=12); and 7300±530/mm < sup > 2 < /sup > , 5610±810/mm3, and 1.500±0.120 in the animals with severe vasospasm (n=10), respectively. CONCLUSION Degenerated vagal axon and NG neuron density may be a causative factor in the development of LLNA vasospasm induced lymph node infarct in SAH. Lung lymph node infarct may be an important factor in the prognosis of NPE.
ACA Marketplace premiums and competition among hospitals and physician practices.

OBJECTIVES To examine the association between annual premiums for health plans available in Federally Facilitated Marketplaces (FFMs) and the extent of competition and integration among physicians and hospitals, as well as the number of insurers. STUDY DESIGN We used observational data from the Center for Consumer Information and Insurance Oversight on the annual premiums and other characteristics of plans, matched to measures of physician, hospital, and insurer market competitiveness and other characteristics of 411 rating areas in the 37 FFMs. METHODS We estimated multivariate models of the relationship between annual premiums and Herfindahl-Hirschman indices of hospitals and physician practices, controlling for the number of insurers, the extent of physician-hospital integration, and other plan and rating area characteristics. RESULTS Premiums for Marketplace plans were higher in rating areas in which physician, hospital, and insurance markets were less competitive. An increase from the 10th to the 90th percentile of physician concentration and hospital concentration was associated with increases of $393 and $189, respectively, in annual premiums for the Silver plan with the second lowest cost. A similar increase in the number of insurers was associated with a $421 decrease in premiums. Physician-hospital integration was not significantly associated with premiums. CONCLUSIONS Premiums for FFM plans were higher in markets with greater concentrations of hospitals and physicians but fewer insurers. Higher premiums make health insurance less affordable for people purchasing unsubsidized coverage and raise the cost of Marketplace premium tax credits to the government.
Thermooxidative Aging Studies on Silicone Rubber and Lifetime Prediction

Silicone rubber have been aged in air while under 25% compression at temperature up to 250°C. These studies examined the compression set of silicone rubber at accelerated (elevated) temperatures and were then used to make predictions about compression set at room temperature. The data obtained could be amenable to timetemperature superposition and Arrhenius treatment. The results suggest the presence of two degradation processes with activation energies of 71.6 kJ mol-1 (for temperatures above 165 °C) and 26.08 kJ mol-1 (for temperatures below 165 °C). Based on the extrapolation of the non-Arrhenius behavior, it was estimated that significant compression set loss would occur after around 67 years at 25 °C.
An Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station

A new model for a viable battery swapping station is proposed to minimize its cost by determining the optimized charging schedule for swapped electric vehicle (EV) batteries. The aim is to minimize an objective function considering three factors: the number of batteries taken from stock to serve all the swapping orders from incoming EVs, potential charging damage with the use of high-rate chargers, and electricity cost for different time period of the day. A mathematical model is formulated for the charging process following the constant-current/constant-voltage charging strategy. An integrated algorithm is proposed to determine an optimal charging schedule, which is inspired by genetic algorithm, differential evolution, and particle swarm optimization. A series of simulation studies are executed to assess the feasibility of the proposed model and compare the performance between the proposed algorithm and the typical evolutionary algorithms.
Effects of electron-transfer chemical modification on the electrical characteristics of graphene

Because of the large reactivity of single layer graphene to electron-transfer chemistries, 4-nitrobenzene diazonium tetrafluoroborate is employed to modify the electrical properties of graphene field-effect transistors. After modification, the transfer characteristics of chemically modified graphene show a reduction in the minimum conductivity, electron–hole mobility asymmetry, a decrease in the electron/hole mobility, and a positive shift of the charge neutrality point with broadening of the minimum conductivity region. These phenomena are attributed to a dediazoniation reaction and the adsorbates on the graphene surface.
A CMOS programmable phase shifter for compensating synchronous detection bioimpedance systems

Electrical bioimpedance is used in a wide variety of biomedical applications. A common circuit topology for extracting tissue impedance from voltage measurements following excitation with an ac current, is synchronous detection (SD), which requires both quadrature (Q) and in phase (I) signals. These are often obtained by a quadrature oscillator, which also drives a voltage controlled current source (VCCS). At high frequencies the VCCS introduces phase delays to the output current, leading to frequency dependent errors in the calculated impedance, as the injected current will no longer be in phase or in quadrature with I and Q. In this paper, a novel low power programmable CMOS phase shifter is presented, which is driven by two quadrature sine waves to produce an output signal between 0° and 90°. The proposed technique is implemented with linearized transconductors operating in weak inversion for linear transconductance programmability. In contrast to other solutions, the phase delay is not a function of the power supply or a capacitor, and thus it is not affected by changes in the power supply and is more chip area efficient. Preliminary simulation results demonstrating the operation of the topology are presented with a 0.18 pm TSMC technology.
A new optimization procedure for extracting the point-based lip contour using active shape model

This paper presents a new optimization procedure for extracting the point-based lip contour using the active shape model (ASM). A 14-point ASM lip model is used to describe the lip contour. With the aid of fuzzy clustering analysis, a probability map of the color lip image is obtained and a region-based cost function is established. The new optimization procedure operates on the spatial domain (actual contour points) and all the points are pulled towards their desirable locations in each iteration. Hence, the lip contour evolution becomes better controlled and consequently fast convergence is achieved. The new procedure can also achieve real-time performance on lip contour extraction and tracking from lip image sequence.
PIN1 Modulates Huntingtin Levels and Aggregate Accumulation: An In vitro Model

Huntington's disease (HD) is a dominantly inherited neurodegenerative disorder characterized by a polyglutamine expansion within the N-terminal region of huntingtin protein (HTT). Cellular mechanisms promoting mutant huntingtin (mHTT) clearance are of great interest in HD pathology as they can lower the level of the mutant protein and its toxic aggregated species, thus affecting disease onset and progression. We have previously shown that the prolyl-isomerase PIN1 represents a promising negative regulator of mHTT aggregate accumulation using a genetically precise HD mouse model, namely HdhQ111 mice. Therefore, the current study aims at underpinning the mechanism by which PIN1 affects huntingtin's aggregates. We found that PIN1 overexpression led to a reduction of mHTT aggregates in HEK293 cells, and that this could be linked to a negative regulation of mHTT half-life by PIN1. Furthermore, we show that PIN1 has the ability to stimulate the proteasome presenting evidence of a mechanism regulating this phenomenon. Our findings provide a rationale for future investigation into PIN1 with the potential for the development of novel therapeutic strategies.
An ultra-wide-range fine-resolution two-step time-to-digital converter with built-in foreground coarse gain calibration

This paper proposes an ultra wide input time interval range, two-step (TS) time-to-digital converter (TDC) with a foreground coarse gain calibration. The proposed TS TDC converts the input time intervals by sequentially using two TDCs that have different dynamic ranges and time resolutions. The fine 2nd stage incorporates a pulse-shrinking ring architecture to achieve sub-gate-delay resolution, whereas the coarse 1st stage uses a simple ring-oscillator-based TDC. The time resolution of the 1st stage is foreground-calibrated at start-up by utilizing the fine 2nd stage TDC. The TDC simulated in a 0.18 pm standard CMOS technology demonstrates 1.8 ps resolution and 16 bit range that corresponds to 118 ns input time interval with 0.07 mm2 area. It operates at 3.3 MS/s with 12.7 mW, and achieves 1.28 ps single-shot precision.
Human tracking method based on improved HOG+Real AdaBoost

This paper proposes an object detection method that uses Histograms of Oriented Gradients (HOG) features using boosting algorithm. There has been done many research works in late years on statistical learning methods and object detection methods that associate low level of features obtained. However the proposed approach, low level of HOG features are associated by using Real AdaBoost to continuously achieve features. In this wise, it is possible to capture a shape of edge continuity, which single HOG features can't do, so highly accuracy detection is realized. This paper, to evaluate the effectiveness of the proposed method, three different experiments with different patterns are conducted for detecting humans. Moreover, a boosting classifier is used to represent the co-occurrence of HOG features appearance for detecting a human.
Evaluation of Legionella Air Contamination in Healthcare Facilities by Different Sampling Methods: An Italian Multicenter Study

Healthcare facilities (HF) represent an at-risk environment for legionellosis transmission occurring after inhalation of contaminated aerosols. In general, the control of water is preferred to that of air because, to date, there are no standardized sampling protocols. Legionella air contamination was investigated in the bathrooms of 11 HF by active sampling (Surface Air System and Coriolis®μ) and passive sampling using settling plates. During the 8-hour sampling, hot tap water was sampled three times. All air samples were evaluated using culture-based methods, whereas liquid samples collected using the Coriolis®μ were also analyzed by real-time PCR. Legionella presence in the air and water was then compared by sequence-based typing (SBT) methods. Air contamination was found in four HF (36.4%) by at least one of the culturable methods. The culturable investigation by Coriolis®μ did not yield Legionella in any enrolled HF. However, molecular investigation using Coriolis®μ resulted in eight HF testing positive for Legionella in the air. Comparison of Legionella air and water contamination indicated that Legionella water concentration could be predictive of its presence in the air. Furthermore, a molecular study of 12 L. pneumophila strains confirmed a match between the Legionella strains from air and water samples by SBT for three out of four HF that tested positive for Legionella by at least one of the culturable methods. Overall, our study shows that Legionella air detection cannot replace water sampling because the absence of microorganisms from the air does not necessarily represent their absence from water; nevertheless, air sampling may provide useful information for risk assessment. The liquid impingement technique appears to have the greatest capacity for collecting airborne Legionella if combined with molecular investigations.
Community detection in social networks through similarity virtual networks

Smart marketing models could utilize communities within the social Web to target advertisements. However, providing accurate community partitions in a reasonable time is challenging for current online large-scale social networks. In this paper, we propose an approach to enhance community detection in online social networks using node similarity techniques. We apply these techniques on unweighted social networks to detect community structure. Our proposed approach creates a virtual network based on the original social network. Virtual edges are added during this pre-processing step based on nodes' similarity in the original social network. Hence, a virtual link is established between any two similar nodes. Then the landmark CNM algorithm is applied on the generated virtual network to detect communities. This approach, labelled Similarity-CNM is expected to further maximize the quality of the inferred communities in terms of modularity and detection speed. Our experimental evaluation study asserts these gains, which accuracy is supported by a study based on Normalized Mutual Information Measure to determine how similar are the actual communities in the original network and the ones found by the proposed approach in this paper.