Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct prognostic values of alcohol dehydrogenase mRNA expression in pancreatic adenocarcinoma

Background Alcohol dehydrogenase (ADH) isoenzymes have been reported as a potential diagnostic marker for pancreatic cancer, but their prognostic value in pancreatic cancer remains unclear. The aim of this investigation was to identify the prognostic value of ADH genes in human patients with pancreatic adenocarcinoma (PAAD). Materials and methods An RNA sequencing dataset and corresponding survival profiles of PAAD were obtained from The Cancer Genome Atlas. Survival analysis and gene set enrichment analysis were used to investigate the prediction value and potential mechanism of ADH genes in PAAD prognosis. Results Survival analysis of ADH genes suggests that a high expression of ADH1A (adjusted P=0.037, adjusted hazard ratio [HR] =0.627, 95% CI =0.404–0.972) and ADH6 (adjusted P=0.018, adjusted HR =0.588, 95% CI =0.378–0.914) were associated with a significantly decreased risk of death, while a high expression of ADH5 was associated with a significantly increased risk of death (adjusted P=0.043, adjusted HR =1.564, 95% CI =1.013–2.414). Joint effects analysis of three ADH gene prognostic markers suggests that the prognosis difference for any marker combination was more significant than that for any individual marker. The potential mechanism of ADH1A and ADH6 in PAAD prognosis was that a high expression of ADH1A and ADH6 was involved in the P450 pathway and biological processes, while high ADH5 expression was involved in transforming growth factor β regulation-related pathways and biological processes, Wnt, the cell cycle, ErbB, and mitogen-activated protein kinase signaling pathways. Conclusion Our data suggest that ADH1A, ADH5, and ADH6 expression may be potential prognostic markers of PAAD and in combination have a strong interaction and better predictive value for PAAD prognosis.
Between Neotraditionalism and New Resistance - Soldiers' Mothers of St. Petersburg

In spite of the attention that Russia's Soldiers' Mothers received even in the western media, especially during the War in Chechnya, this institution has not yet been subjected to scientific analysis. The present study is an attempt to reduce the gap in this area of research. The starting point is the violation of the rights of the members of the armed forces in the Russian military complex as the immediate subject of engagement of Soldiers' Mothers. The ensuing examination of the Soldiers' Mothers organization in the transformation process serves to describe its political and historical categorization. Details regarding the Soldiers' Mothers of S1. Petersburg are then dealt with in the following section. An examination of the gender-specific consequences of the formation of a civil society in Russia should help clarify the social climate of neotraditionalism in which this organization pursues its activity. It becomes clear that the key to success of this organization lies on the one hand in current social developments and, on the other, in the way in which the organization has been able to call into question the alienated structures of the military forces themselves.
Wearable security: Key derivation for Body Area sensor Networks based on host movement

The Internet-of-Things relies on ad-hoc connections, which also requires an on-demand approach to the negotiation of security parameters. We propose a new approach to shared key derivation for Body Area Networks (BANs). Body area networks are quickly becoming increasingly important in the world of healthcare with wide application in the treatment and monitoring of chronic patients using on-body devices. Advancements in the field will result in quicker response times in emergency situations, and detect complications in patients at a much earlier stage potentially saving many lives. In this paper, we have used motion sensors instead of the more common physiological signals that need physical access to the body, like electrocardiograms (ECG), to pair devices and secure communication in Body Area Networks. Our method considers the acceleration of the devices that needs to communicate. These measurements tend to be similar as devices are deployed on the same host body, which means that these could be used to derive shared keys. We show that these measurements results in derived keys that are unpredictable and exhibit significant difference with previous keys. This is an improvement over existing schemes where keys vary for different hosts but tend to be similar over time.
Fs 2 Egypt Cotton Fs 3 Egypt Cotton Fs 4 Egypt Cotton Fs 5 Egypt Cotton

Early, precise detection and identification of soil-borne fungi are essential for efficient plant disease management. Three sets of specific primers were designed from the internal transcribed spacer (ITS) regions, ITS-Fs-forward and ITS-Fs-reverse, of the rRNA gene to identify Fusarium solani isolates in pure mycelial culture. The specificity and suitability of the PCR techniques has been tested with different cotton fungal pathogens, including various Fusarium species and 29 F. solani isolates. ITS-Fs7 and ITS-FS8 primers amplified two fragments (480 and 390 bp) from F. solani genomic DNA, and the ITS-Fs2 primer set amplified two different sizes (540 and 420 bp) of fragments. The 390 bpand 420 bpfragments were specific to F. solani. The primer sets amplified none of fragments from Rhizoctonia solani and Macrophomina phaseolina. In the assay, SYBR Green I was used as fluorescent dye enabling real-time detection of PCR products. Characterization of the amplicons was achieved by melting point analysis (85 ± 0.1°C). In conventional PCR the detection limit of all primers was 100 pg, whereas detection threshold of the LightCycler PCR were 100 fg of genomic DNA from F. solani mycelium. Real-time PCR assay allows a more reliable and rapid detection of F. solani which is considerably faster than conventional detection assays. The present PCR test represents a rapid and reliable method for genetically based identification of F. solani cultures. To the best of our knowledge, this is the first report describing the application of real-time PCR assay for the identification of F. solani isolates recovered from cotton. _____________________________________________________________________________________________________________
Chinese monetary policy and the dollar peg

This paper investigates to what extent Chinese monetary policy is constrained by the dollar peg. To this end, we use a cointegration framework to examine whether Chinese interest rates are driven by the Fed's policy. In a second step, we estimate a monetary model for China, in which we include also other monetary policy tools besides the central bank interest rate, namely reserve requirement ratios and open market operations. Our results suggest China has been relatively successful in isolating its monetary policy from the US policy and that the interest rate tool has not been effectively made use of. We therefore conclude that by employing capital controls and relying on other instruments than the interest rate China has been able to exert relatively autonomous monetary policy.
Paucity of Clinical Disease despite Serological Autoimmunity and Kidney Pathology in Lupus-Prone New Zealand Mixed 2328 Mice Deficient in BAFF1

Constitutive overexpression of B cell-activating factor belonging to the TNF family (BAFF) promotes development of systemic lupus erythematosus (SLE), and treatment of SLE mice with BAFF antagonists ameliorates disease. To determine whether SLE can develop de novo in BAFF-deficient hosts, BAFF-deficient New Zealand Mixed (NZM) 2328 (NZM.Baff−/−) mice were generated. In NZM.Baff−/− mice, spleen B cells (including CD5+ B1a and CD5− B1b B cells), germinal centers, Ig-secreting cells, and T cells were reduced in comparison to NZM.Baff+/+ mice. Serum total Ig and autoantibody levels were reduced at 4–6 mo but approached wild-type levels with increasing age, indicating that autoreactive B cells can survive and secrete autoantibodies despite the complete absence of BAFF. At least some of these autoantibodies are nephrophilic in that glomerular deposition of total IgG and IgG1 (but not of IgG2a, IgG2b, or C3) was substantial in NZM.Baff−/− mice by 12–13 mo of age. Despite proliferative glomerulonephritis, highlighted by widespread glomerular hyaline thrombi, being common among NZM.Baff−/− mice by 6–7 mo of age, severe proteinuria and mortality were greatly attenuated. These results demonstrate that the lifelong absence of BAFF does not protect NZM 2328 mice from serological autoimmunity and renal pathology. Nevertheless, the character of the renal pathology is altered, and the mice are largely spared from clinically overt disease (severe proteinuria and premature death). These observations may have profound ramifications for the use of BAFF antagonists in human SLE and related diseases.
Returns to Scale and the Effectiveness of Money Spent on the Expanded Food and Nutrition Education Program

In operation for more than 40 years and now in all 50 states and 6 territories, the Expanded Food and Nutrition Education Program has become a cornerstone in US nutrition education. The aim of the program is to assist limited resource audiences to acquire the knowledge, skills, attitudes, and changed behavior necessary for nutritionally sound diets, and to contribute to their personal development and improvement of the overall family diet and nutritional well-being. However, very little is known about the effectiveness of this program, especially at the national level. The purpose of this research is to determine the effectiveness of money spent on the Expanded Food and Nutrition Education Program in satisfying its stated goals for adult participants. Data from all states and territories participating in the program for the years 2000-2006 are utilized in a non-linear seemingly unrelated regression framework to estimate returns to scale and related cost measures. Controlling for participant and program characteristics, the amount of money spent on the Expanded Food and Nutrition Education Program has a positive and significant impact on two of three federal outcome indices used to measure outcomes for adults. Larger-funded programs (states/territories) are relatively more cost efficient than smaller programs.
A Trustworthy Electronic Voting System for Australian Federal Elections

The existing system for determining election results in Australia is, for the most part, secure, accurate and understandable by the average voter. This thesis explores the design of electronic voting systems designed to achieve these same goals, while also improving on the existing system in the areas of counting speed, accuracy, tamper resistance and accessibility. Electronic voting systems have seen limited use within Australian elections, most prominently for State Elections in Victoria (2014), New South Wales (2015) and Western Australia (2017), along with trials of electronic voting systems in federal elections in 2007. This thesis presents an analysis of the iVote electronic voting system used for the 2017 Western Australian State Election (iVote WA), outlining a number of security risks introduced by the use of cloud-based distributed denial of service mitigation. In addition, this thesis presents the results of a cross-sectional survey of Australian voters regarding levels of trust for three voting systems: the existing paper-based system used for Australian federal elections, the iVote WA system, and the vVote system used for the 2014 Victorian State Election. The analysis of iVote, combined with the survey results, are used to inform a recommendation for future research and public policy regarding the use of electronic voting systems in Australian federal elections.
A V 2 I Communication Based Pipe Model for Adaptive Urban Traffic Light Scheduling

Adaptive traffic light scheduling based on realtime traffic information processing has proven effective in urban traffic congestion management. However, fine-grained information of individual vehicles is difficult to acquire with traditional data collection techniques, and the accuracy cannot be guaranteed due to congestion and harsh surroundings. In this study, we first build a pipe model based on vehicleto-infrastructure (V2I) communication, a salient technique in vehicular ad hoc networks (VANETs). The model enables acquiring fine-grained and accurate traffic information at realtime via message exchange between vehicles and road side units (RSUs). Thereafter, we propose an intelligent traffic light scheduling method (ITLM) according to a “demand assignment” principle by considering the types and turning intentions of vehicles. In the context of the principle, a signal phase with more vehicles will be assigned longer green time. Moreover, a green-way traffic light scheduling method (GTLM) is investigated for special vehicles (e.g. ambulances, fire engines) in an emergency scenario, signal states will be adjusted or maintained by traffic light control system to keep the special vehicle moving smoothly. The comparative experiments show that ITLM reduces 34%-78% average waiting time and 12%-34% average stop frequency under the premise of ensuring traffic ability. GTLM reduces 22%-44% and 30%-55% consumed time under two kinds of traffic conditions, and it works better in a congested scenario.
Leveraging Twitter to better identify suicide risk

While many studies have explored the use of social media and behavioral changes of individuals, few examined the utility of using social media for suicide detection and prevention. The study by Jashinsky et al, in particular, identified specific language patterns associated with a set of twelve suicide risk factors. We utilized their findings to assess the significance of the language used on Twitter for suicide detection. We quantified the use of Twitter to express suicide related language and its potential to detect users at high risk of suicide. First, we evaluated the presence of language related to twelve different suicide risk factors on Twitter using a list of terms/statements published by Jashinsky et al and searched Twitter for tweets indicative of 12 suicide risk factors. Using network analysis, for each suicide risk factor we established a subnetwork of users and their tweets related to that suicide risk factor. We computed the density of each subnetwork to estimate the presence of the language of that suicide risk factor. Second, we investigated relationships between suicide risk factors, using associated language patterns, In two groups “high risk” and “at risk”. We divided Twitter users into “high risk” and “at risk” based on two of the risk factors (“selfharm” and “prior suicide attempts”) and examined language patterns by computing co-occurrences of terms in tweets. We identified relationships between suicide risk factors in both groups using co-occurrences. We found that users within a subnetwork used similar language to express their feeling/thoughts. Stratifying users into “high-risk” and “at-risk”, we found stronger relationships between pairs of risk factors such as (“depressive feelings”, ”drug abuse”), (“suicide around individual”, ”selfharm”), and (“suicide ideation”, ”drug abuse”) in the “high-risk” group relative to the “at-risk” group. In addition, the presence of social-related suicide risk factors including “gun ownership”, “suicide around individual”, “family violence”, and “prior suicide attempts” was more pronounced in the “high-risk” group.
A CMOS RF-to-DC Power Converter With 86% Efficiency and −19.2-dBm Sensitivity

This paper proposes an RF-to-dc power converter for ambient wireless powering that is efficient, highly sensitive, and less dependent on the load resistance with an extended dynamic range. The proposed rectifier utilizes a variable biasing technique to control the conduction of the rectifying transistors selectively, hence minimizing the leakage current; unlike the prior work that has a fixed feedback resistors, which limits the efficient operation to a relatively high RF power and causes a drop in the peak power conversion efficiency (PCE). The proposed design is fabricated using a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> standard CMOS technology and occupies an area of <inline-formula> <tex-math notation="LaTeX">$8800~\mu \text{m}^{2}$ </tex-math></inline-formula>. The measurement results show an 86% PCE and −19.2-dBm (<inline-formula> <tex-math notation="LaTeX">$12~\mu \text{W}$ </tex-math></inline-formula>) sensitivity when operating at the medical band 433 MHz with a 100-<inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula> load. Furthermore, the PCE is 66%, and the sensitivity is −18.2 dBm (<inline-formula> <tex-math notation="LaTeX">$15.1~\mu \text{W}$ </tex-math></inline-formula>) when operating at UHF 900 MHz with a 100-<inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula> load.
A Panel Data Analysis of Capital Structure Determinants: Empirical Results from Turkish Capital Market

The determinants of capital structure have been a widely discussed subject in the finance literature. The purpose of this paper is to determine whether firm-specific capital structure determinants in the emerging market of Turkey support the capital structure theories which were developed to explain the company structure in developed economies. Specifically, we try to answer the following questions: Firstly, are determinants of capital structure correlated with the leverage that has been declared in the developed economies setting correlated in Turkey as emerging market as well? And secondly are the modern capital structure theories (e.g. trade-off and pecking-order hypothesis) valid in explaining capital structure of the Turkish companies? In this paper, we apply econometric techniques and panel data analyses. We empirically examine the capital structure of 242 companies of different sectors that are traded in Istanbul Stock Exchange (ISE). In the period of 2000-2009 depending on the findings of the panel data analysis, we can conclude that Turkish companies do not have debt ratio targets. We suggest that Turkish companies follow a hierarchical company structure. More specifically, we claim that trade-off theory is less successful than the pecking order hypothesis in explaining the capital structure of the Turkish companies. Therefore, Turkish companies are following pecking-order hypothesis in their debt behaviors.
MSNet: Multi-Scale Convolutional Network for Point Cloud Classification

Point cloud classification is quite challenging due to the influence of noise, occlusion, and the variety of types and sizes of objects. Currently, most methods mainly focus on subjectively designing and extracting features. However, the features rely on prior knowledge, and it is also difficult to accurately characterize the complex objects of point clouds. In this paper, we propose a concise multi-scale convolutional network (MSNet) for adaptive and robust point cloud classification. Both the local feature and global context are incorporated for this purpose. First, around each point, the spatial contexts of different sizes are partitioned as voxels of different scales. A voxel-based MSNet is then simultaneously applied at multiple scales to adaptively learn the discriminative local features. The class probability of a point cloud is predicted by fusing the features together across multiple scales. Finally, the predicted class probabilities of MSNet are optimized globally using the conditional random field (CRF) with a spatial consistency constraint. The proposed method was tested with data sets of mobile laser scanning (MLS), terrestrial laser scanning (TLS), and airborne laser scanning (ALS) point clouds. The experimental results show that the proposed method was able to achieve appreciable classification accuracies of 83.18%, 98.24%, and 97.02% on the MLS, TLS, and ALS data sets, respectively. The results also demonstrate that the proposed network has a strong generalization capability for classifying different kinds of point clouds under complex urban environments.
Association between Pulse Wave Velocity and Coronary Artery Calcification in Japanese men.

AIM Pulse wave velocity (PWV) is a simple and valid clinical method for assessing arterial stiffness. Coronary artery calcification (CAC) is an intermediate stage in the process leading to overt cardiovascular disease (CVD) and an established determinant of coronary artery disease. This study aimed to examine the association between PWV and CAC in a population-based sample of Japanese men. METHODS This is a cross-sectional study of 986 randomly selected men aged 40-79 years from Shiga, Japan. CVD-free participants were examined from 2006 to 2008. Brachial-ankle PWV (baPWV) was measured using an automatic waveform analyzer. CAC was assessed using computed tomography. Agatston scores ≥ 10 were defined as the presence of CAC. RESULTS Prevalence of CAC progressively increased with rising levels of baPWV: 20.6%, 41.7%, 56.3%, and 66.7% across baPWV quartiles ＜ 1378, 1378-1563, 1564-1849, and ＞ 1849 cm/s (P ＜ 0.001 for trend). Associations remained significant after adjusting for age and other factors, including body mass index, systolic blood pressure, pulse rate, total and high-density lipoprotein cholesterol, hemoglobin A1c, drinking, smoking and exercise status, and the use of medication to treat hypertension, dyslipidemia and diabetes (P=0.042 for trend). The optimal cutoff level of baPWV to detect CAC was 1612 cm/s using receiver operating characteristic curve analysis. CONCLUSIONS Arterial stiffness as defined by an elevated baPWV is associated with an increased prevalence of CAC in a general population-based setting among Japanese men.
Biotechnology in the textile/clothing industry – a review

This paper focuses on the use of biotechnology in the textile/clothing industry by identifying where and how such processes are already established and considers the latest developments, either in the research stage or in the early stages of commercialization. It has been found that biotechnology systems are already well known to those involved in fabric preparation, particularly as regards desizing. Enzymes used in detergent formulations have also been successfully used for the past 30–40 years. Most recent commercial advances have been in fabric finishing processes where handle modifications to cotton fabrics in particular are fast becoming established. Cutting-edge research falls in the areas of fibre modification and the generation of new fibres from natural sources, such as natural polyester from bacteria. The isolation of DNA from the shaft of hair fibres and the encoding of detectable specific antigens to designer labels is providing new ways of helping to combat fraud and counterfeit in the fashion trade. The treatment of textile effluent continues to be a major problem to the industry, but here, biotechnological developments in other industries are helping to provide some answers.