Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Strategies for Cooperative Spectrum Sensing in Multiple Cross-over Cognitive Radio Networks

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.
Anthropogenic Habitat Disturbance and Ecological Divergence between Incipient Species of the Malaria Mosquito Anopheles gambiae

Background Anthropogenic habitat disturbance is a prime cause in the current trend of the Earth’s reduction in biodiversity. Here we show that the human footprint on the Central African rainforest, which is resulting in deforestation and growth of densely populated urban agglomerates, is associated to ecological divergence and cryptic speciation leading to adaptive radiation within the major malaria mosquito Anopheles gambiae. Methodology/Principal Findings In southern Cameroon, the frequency of two molecular forms–M and S–among which reproductive isolation is strong but still incomplete, was correlated to an index of urbanisation extracted from remotely sensed data, expressed as the proportion of built-up surface in each sampling unit. The two forms markedly segregated along an urbanisation gradient forming a bimodal cline of ∼6-km width: the S form was exclusive to the rural habitat, whereas only the M form was present in the core of densely urbanised settings, co-occurring at times in the same polluted larval habitats of the southern house mosquito Culex quinquefasciatus–a species association that was not historically recorded before. Conclusions/Significance Our results indicate that when humans create novel habitats and ecological heterogeneities, they can provide evolutionary opportunities for rapid adaptive niche shifts associated with lineage divergence, whose consequences upon malaria transmission might be significant.
Using Data Mining Methods to Detect Simulated Intrusions on a Modbus Network

In the era of Industry 4.0 we seek to create a smart factory environment in which everything is connected and well coordinated. Smart factories will also be connected to cloud service and/or all kinds of partners outside the boundary of the factory to achieve even better efficiency. However network connectivity also brings threats along with the promise of better efficiency, and makes Smart factories more vulnerable to intruders. There were already security incidents such as Iran's nuclear facilities' infection by the Stuxnet virus and German's steel mill destroyed by hackers in 2014. To protect smart factories from such threats traditional means of intrusion detection on the Internet could be used, but we must also refine them and have them adapted to the context of Industry 4.0. For example, network traffic in a smart factory might be more uniformed and predictable compared to the traffic on the Internet, but one should tolerate much less anomaly as the traffic is usually mission critical, and will cause much more loss once intrusion happens. The most widely used signature-based intrusion detection systems come with a large library of signatures that contains known attack have been proved to be very useful, but without the ability to detect unknown attack. We turn to supervised data mining algorithms to detect intrusions, which will help us to detect intrusions with similar properties with known attacks but not necessarily fully match the signatures in the library. In this study a simulated smart factory environment was built and a series of attacks were implemented. Neural network and decision trees were used to classify the traffic generated from this simulated environment. From the experiments we conclude that for the data set we used, decision tree performed better than neural network for detecting intrusion as it provides better accuracy, lower false negative rate and faster model building time.
Indications and outcomes of extracorporeal life support in trauma patients

BACKGROUND The use of extracorporeal life support (ECLS) in the trauma population remains controversial and has been reported only in small cohort studies. Recent ECLS technical advances have increased its use as an advanced critical care option in trauma. Given the degree of resource utilization, costs, and expertise required to provide ECLS support in trauma patients, we sought to perform a multi-institutional study to assess the indications and outcomes of ECLS in trauma. METHODS A retrospective review of adult (≥16 years) trauma patients receiving ECLS support in the Extracorporeal Life Support Organization (ELSO) registry (1989–2016) was performed. Standardized data from the contributing ELSO centers includes patient demographics, diagnoses, and ECLS technique and procedures. Additionally, baseline characteristics, precannulation and postcannulation physiologic data, complications, and outcomes were recorded. Survival was categorized both by transition off ECLS support and survival to hospital discharge. RESULTS Two hundred seventy-nine trauma patients were identified (0.92% of 30,273 adult ECLS patients). Extracorporeal life support increased significantly in the last 5 years (173 in 2011–2016, 62%) compared with 106 in the prior 18 years. Trauma patients were predominantly male (78%), with a mean age of 34.8 ± 15.4 years (range, 16–88 years). Thoracic injury was the most common diagnosis; acute respiratory distress syndrome was the most common indication. Extracorporeal life support was venovenous for respiratory failure (89%), VA for cardiac failure (7%), and VA for ECLS-assisted cardiopulmonary resuscitation (CPR) (E-CPR) (4%). Extracorporeal life support duration was 8.8 ± 9.5 days (longest 83 days), and was longer for respiratory support (9.3 ± 9.3 days) vs. cardiac support (4.1 ± 4.5 days) and E-CPR (6.5 ± 16.8 days). Overall survival from ECLS was 70% and survival to hospital discharge was 61% in the total cohort (63% respiratory, 50% cardiac, 25% E-CPR), similar to survival rates in other ELSO registry cohorts. More than 80% of patients had a reported complication during ECLS support. The most common complication was cardiovascular (51%) followed by a bleeding complication (29%). Multiple organ failure was the most common cause of death (15.4%). CONCLUSION Data from the largest registry of critically ill trauma patients receiving ECLS support demonstrates reasonable survival. With growing experience and improved safety profile, trauma should not be considered a contraindication for ECLS. Further analysis of the ELSO registry regarding trauma-specific risk factors and ECLS-specific practices may identify best candidates and improve trauma ECLS outcomes. LEVEL OF EVIDENCE Therapeutic study, level III.
Splice Variants of NaV1.7 Sodium Channels Have Distinct β Subunit-Dependent Biophysical Properties

Genes encoding the α subunits of neuronal sodium channels have evolutionarily conserved sites of alternative splicing but no functional differences have been attributed to the splice variants. Here, using NaV1.7 as an exemplar, we show that the sodium channel isoforms are functionally distinct when co-expressed with β subunits. The gene, SCN9A, encodes the α subunit of the NaV1.7 channel, and contains both sites of alternative splicing that are highly conserved. In conditions where the intrinsic properties of the NaV1.7 splice variants were similar when expressed alone, co-expression of β1 subunits had different effects on channel availability that were determined by splicing at either site in the α subunit. While the identity of exon 5 determined the degree to which β1 subunits altered voltage-dependence of activation (P = 0.027), the length of exon 11 regulated how far β1 subunits depolarised voltage-dependence of inactivation (P = 0.00012). The results could have a significant impact on channel availability, for example with the long version of exon 11, the co-expression of β1 subunits could lead to nearly twice as large an increase in channel availability compared to channels containing the short version. Our data suggest that splicing can change the way that NaV channels interact with β subunits. Because splicing is conserved, its unexpected role in regulating the functional impact of β subunits may apply to multiple voltage-gated sodium channels, and the full repertoire of β subunit function may depend on splicing in α subunits.
Accelerated Corona Aging Tests Analysis and Lifetime Prediction of HTV Silicone Rubber

High temperature valcanized(HTV) silicone rubber is a kind of organic meterials with many merits such as light weight,high hydrophobicity of the suface,as well as the weakness such as poor aging performance.Corona is one of the main factors that lead to the aging of HTV silicone rubber.Consequently,we experimentally investigated corona aging of HTV,and analyzed the test samples before and after corona aging by Fourier transform infrared spectroscopy(FTIR). The results showed that the rate of aging became slower with time.Furthermore,we established a lifetime evaluation model of HTV based on trap theory and the FTIR spectrum before and after corona aging,determined undetermined coefficients in the lifetime formula,and established a quantitative expression of the corona aging lifetime of HTV.This research could provide a method of predicting lifetime and modeling the corona aging of silicone rubber materials.
The Inhibition of Relapse of Orthodontic Tooth Movement by NaF Administration in Expressions of TGF-β1, Runx2, Alkaline Phosphatase and Microscopic Appearance of Woven Bone

The prevalence of post-treatment relapse in orthodontics in the community is high enough; therefore, relapses in orthodontic treatment must be prevented well. The aim of this study is to experimentally test the inhibition of relapse of orthodontics tooth movement in NaF of expression TGF-β1, Runx2, alkaline phosphatase (ALP) and microscopic of woven bone. The research method used was experimental laboratory research involving 30 rats, which were divided into three groups. Group A: rats were not given orthodontic tooth movement and without NaF. Group B: rats were given orthodontic tooth movement and without 11.5 ppm by topical application. Group C: rats were given orthodontic tooth movement and 11.75 ppm by topical application. Orthodontic tooth movement was conducted by applying ligature wires of 0.02 mm in diameter on the molar-1 (M-1) of left permanent maxilla and left insisivus of maxilla. Immunohistochemical examination was conducted to calculate the number of osteoblast to determine TGF β1, Runx2, ALP and haematoxylin to determine woven bone on day 7 and day 14. Results: It was shown that administrations of Natrium Fluoride topical application proved effective to increase the expression of TGF-β1, Runx2, ALP and to increase woven bone in the tension area greater than administration without natrium fluoride topical application (p < 0.05), except the expression of ALP on day 7 and day 14 which was significant. The results of the study show that NaF significantly increases the expressions of TGF-β1, Runx2, ALP and woven bone. The expression of the variables enhanced on day 7 compared on that on day 14, except ALP. Thus, it can be said that the acceleration of woven bone occurs on day 7.
YOLO-based Adaptive Window Two-stream Convolutional Neural Network for Video Classification

[1] Karpathy, A. , Toderici, G. , Shetty, S. , Leung, T. , Sukthankar, R. , & Fei-Fei, L. (2014). Largescale video classification with convolutional neural networks. In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition (pp. 1725-1732). [2] Simonyan, K. , & Zisserman, A. (2014). Two-stream convolutional networks for action recognition in videos. In Advances in neural information processing systems (pp. 568-576). [3] Wang, Y. , Song, J., Wang, L. , Van Gool, L. , & Hilliges, O. (2016). Two-Stream SR-CNNs for Action Recognition in Videos. BMVC. [4] Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. (2016). You Only Look Once: Unified, Real-Time Object Detection. CVPR. [5] Zuxuan Wu, Xi Wang, Yu-Gang Jiang, Hao Ye, Xiangyang Xue. (2015). Modeling SpatialTemporal Clues in a Hybrid Deep Learning Framework for Video Classification. ACM MM. Convolutional Neural Networks (CNN) have been adopted widely for image classification problems. As they demonstrate significant success, more and more researchers start to deploy CNN on video classification problems. The main challenge is to capture not only the appearance information present in single, static frames, but also complex temporal evolution. Among video classification tasks, human action recognition is the key problem.
Control of transcriptional pausing by biased thermal fluctuations on repetitive genomic sequences

Significance How does RNA polymerase (RNAP) accurately and orderly control elongation of RNA in nanosystems dominated by random thermal fluctuations? Our statistical approach challenges this open question by identifying a linkage between thermal fluctuations, repetitive DNA sequences encoded in a genome, and RNAP pausing during elongation. Until now, it has been reasonably assumed that the structure of an elongation complex (EC) at any given location along DNA ultimately controls its enzymatic function. Contrary to this assumption, we show that nonlocal thermal fluctuations of the EC on repetitive DNA sequence elements statistically and robustly affect RNAP elongation by stabilizing pausing. This study also provides a proof of concept for the significance of thermal fluctuations in a wide variety of enzymatic systems. In the process of transcription elongation, RNA polymerase (RNAP) pauses at highly nonrandom positions across genomic DNA, broadly regulating transcription; however, molecular mechanisms responsible for the recognition of such pausing positions remain poorly understood. Here, using a combination of statistical mechanical modeling and high-throughput sequencing and biochemical data, we evaluate the effect of thermal fluctuations on the regulation of RNAP pausing. We demonstrate that diffusive backtracking of RNAP, which is biased by repetitive DNA sequence elements, causes transcriptional pausing. This effect stems from the increased microscopic heterogeneity of an elongation complex, and thus is entropy-dominated. This report shows a linkage between repetitive sequence elements encoded in the genome and regulation of RNAP pausing driven by thermal fluctuations.
Usage of game theory in the internet wide scan

This article examines Usage of Game Theory in The Internet Wide Scan. There is compiled model of “Network Scanning” game. There is described process of players interaction in the coalition antagonistic and network games. The concept of target system's cost is suggested. Moreover, there is suggested its application in network scanning, particularly, when detecting honeypot/honeynet systems.
Morphological transition of Helicobacter pylori adapted to water.

AIM This study aims to investigate the morphological transition of Helicobacter pylori during adaptation to water. MATERIALS & METHODS Different strains were adapted to water. Changes regarding cultivability and cellular morphology were recorded. Expression of 11 genes involved in H. pylori morphological changes was evaluated by real-time PCR. RESULTS H. pylori presented increased cultivability in water after adaptation. The permanent loss of the spiral shape was observed, but no transition into coccoid form has occurred. Expression levels of genes involved in peptidoglycan assembly of H. pylori 26695 have shown significant changes between adapted and nonadapted strains. CONCLUSION Adaption to water favors the culturable phenotype and the morphological transition to the rod shape, into a process that implicates the peptidoglycan turnover.
Low hydrogen contents in the cores of terrestrial planets

During planetary accretion, hydrogen behaves as a lithophile element and is unlikely to be a major element in planetary cores. Hydrogen has been thought to be an important light element in Earth’s core due to possible siderophile behavior during core-mantle segregation. We reproduced planetary differentiation conditions using hydrogen contents of 450 to 1500 parts per million (ppm) in the silicate phase, pressures of 5 to 20 GPa, oxygen fugacity varying within IW-3.7 and IW-0.2 (0.2 to 3.7 log units lower than iron-wüstite buffer), and Fe alloys typical of planetary cores. We report hydrogen metal-silicate partition coefficients of ~2 × 10−1, up to two orders of magnitude lower than reported previously, and indicative of lithophile behavior. Our results imply H contents of ~60 ppm in the Earth and Martian cores. A simple water budget suggests that 90% of the water initially present in planetary building blocks was lost during planetary accretion. The retained water segregated preferentially into planetary mantles.
Polysilane as SiC Precursor: Preparation, Catalytic Cure and Pyrolysis

Liquid polysilane (methyl-terminated vinyl-containing oligomethylsilane, PSI) was prepared by lithium condensation and used as SiC precursor. With the increase of catalyst Ni(acac)2, the thermal cure exotherm shifted to lower temperatures gradually, and the ceramic yield was gradually increased. The crystallinity was promoted by catalyst addition, meanwhile the elements in the pyrolyzed β-SiC were distributed uniformly.
A Knowledge-Based Method for Association Studies on Complex Diseases

Complex disorders are a class of diseases whose phenotypic variance is caused by the interplay of multiple genetic and environmental factors. Analyzing the complexity underlying the genetic architecture of such traits may help develop more efficient diagnostic tests and therapeutic protocols. Despite the continuous advances in revealing the genetic basis of many of complex diseases using genome-wide association studies (GWAS), a major proportion of their genetic variance has remained unexplained, in part because GWAS are unable to reliably detect small individual risk contributions and to capture the underlying genetic heterogeneity. In this paper we describe a hypothesis-based method to analyze the association between multiple genetic factors and a complex phenotype. Starting from sets of markers selected based on preexisting biomedical knowledge, our method generates multi-marker models relevant to the biological process underlying a complex trait for which genotype data is available. We tested the applicability of our method using the WTCCC case-control dataset. Analyzing a number of biological pathways, the method was able to identify several immune system related multi-SNP models significantly associated with Rheumatoid Arthritis (RA) and Crohn’s disease (CD). RA-associated multi-SNP models were also replicated in an independent case-control dataset. The method we present provides a framework for capturing joint contributions of genetic factors to complex traits. In contrast to hypothesis-free approaches, its results can be given a direct biological interpretation. The replicated multi-SNP models generated by our analysis may serve as a predictor to estimate the risk of RA development in individuals of Caucasian ancestry.
The changing practice of transurethral resection of the prostate

INTRODUCTION Transurethral resection of the prostate (TURP) is considered the gold standard surgical treatment for lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia. The number of TURPs performed has declined significantly over the last three decades owing to pharmaceutical therapy. TURP data from a single institution for the years 1990, 2000 and 2010 were compared to assess the difference in performance. METHODS A retrospective analysis was undertaken of all patients who underwent TURP between January and December 2010. These findings were compared with historical data for the years 1990 and 2000: 100 sets of case notes were selected randomly from each of these years. RESULTS The number of TURPs performed fell from 326 in 1990 to 113 in 2010. The mean age of patients increased from 70.6 years to 74.0 years. There was also a significant increase in the mean ASA grade from 1.9 to 2.3. The most common indication for TURP shifted from LUTS to acute urinary retention. No significant change in operating time was observed. The mean resection weight remained constant (22.95g in 1990, 22.55g in 2000, 20.76g in 2010). A reduction in transfusion rates was observed but there were higher rates of secondary haematuria and bladder neck stenosis. There was an increase from 2% to 11.5% of patients with long‐term failure to void following TURP. CONCLUSIONS The number of TURPs performed continues to decline, which could lead to potential training issues. Urinary retention is still by far the most common indication. However, there has been a significant rise in the percentage of men presenting for TURP with high pressure chronic retention. The number of patients with bladder dysfunction who either have persistent storage LUTS or eventually require long‐term catheterisation or intermittent self‐catheterisation has increased markedly, which raises the question of what the long‐term real life impact of medical therapy is on men with LUTS secondary to benign prostatic hyperplasia who eventually require surgery.
Anonymous Obstruction-free $(n,k)$-Set Agreement with $n-k+1$ Atomic Read/Write Registers

The $k$-set agreement problem is a generalization of the consensus problem. Namely, assuming each process proposes a value, each non-faulty process has to decide a value such that each decided value was proposed, and no more than $k$ different values are decided. This is a hard problem in the sense that it cannot be solved in asynchronous systems as soon as $k$ or more processes may crash. One way to circumvent this impossibility consists in weakening its termination property, requiring that a process terminates (decides) only if it executes alone during a long enough period. This is the well-known obstruction-freedom progress condition. Considering a system of $n$ {\it anonymous asynchronous} processes, which communicate through atomic {\it read/write registers only}, and where {\it any number of processes may crash}, this paper addresses and solves the challenging open problem of designing an obstruction-free $k$-set agreement algorithm with $(n-k+1)$ atomic registers only. From a shared memory cost point of view, this algorithm is the best algorithm known so far, thereby establishing a new upper bound on the number of registers needed to solve the problem (its gain is $(n-k)$ with respect to the previous upper bound). The algorithm is then extended to address the repeated version of $(n,k)$-set agreement. As it is optimal in the number of atomic read/write registers, this algorithm closes the gap on previously established lower/upper bounds for both the anonymous and non-anonymous versions of the repeated $(n,k)$-set agreement problem. Finally, for $1 \leq x\leq k \textless{} n$, a generalization suited to $x$-obstruction-freedom is also described, which requires $(n-k+x)$ atomic registers only.