Miracle-dz/UniFAR-FTUs huggingface dataset:
Increased Levels of Low Affinity Platelet Factor 4 in Plasma and Urine of Patients With Chronic Renal Failure.

Low affinity platelet factor 4 (LA-PF4) is a specific platelet secretory protein immunologically related to β-thromboglobulin and to platelet basic protein that stimulates cell growth. The level of LA-PF4 antigen was determined by specific radioimmunoassay in platelet poor plasma (PPP) and platelet rich plasma (PRP) of 17 normal individuals (NI), 9 patients on hemodialysis (HD) and 18 patients with chronic renal failure (CRF) who were not dialysed. Eight patients with glomerular filtration rate (GFR) 5-20 ml/min were included to group 1 and 10 patients with GFR 30-50 ml/min were included to group 2. Levels of LA-PF4 in ng/ml PPP were 31.9 ± 2.8 in NI, 291.8 ± 26.3 in HD, 149.4 ± 45.2 in group 1 of CRF and 103.7 ± 11.1 in group 2 of CRF. Differences between patients and NI were significant at P <0.05. After 3 hours of hemodialysis LA-PF4 increased to 505.0 ± 92.3 (P < 0.05), however, there was no changes in PPP level across the artifical kidney at one hour. The levels of LA-PF4 in PRP of patients with CRF and HD did not differ from NI. Mean LA-PF4 excretion in urine (ng/day/100mg creatinine) was 57.7 ± 6.4 (range 33.3-75.7) in 6 NI with GFR >60 ml/min and 1461.5 ± 674.6 (range 105.3-7041.6) in 10 CRF patients. In conclusion, elevation of LA-PF4 in PPP of patients with CRF and its increased urinary excretion suggest stimulation of platelet secretion and/or decreased metabolism of LA-PF4 in the kidney.
CONTEXTS, NON-SPECIFICITY, AND MINIMALISM

Atlas (2007) argues that semantic minimalism (as defended by Cappelen & Lepore 2005) fails because it cannot deal with semantic non-specificity. I argue that there is a plausible version of minimalism—viz., situated minimalism—which doesn’t succumb to the non-specificity charge insofar as non-specificity can be dealt with at a postsemantic level. Thus, pragmatics plays no role when it comes to determining the (minimal) proposition expressed. Instead, pragmatic and other extra-semantic considerations enter the scene in characterizing the situation vis-à-vis which the proposition is evaluated. For this reason a plausible form of minimalism must embrace a form of truth-relativism: a proposition is not universally true/false, but true/false only relative to a situation. I show how the position defended is not only (i) more cognitively plausible than either (semantic) minimalism as proposed by Cappelen & Lepore or the positions appealing to pragmatic intrusion into the proposition expressed, but is also (ii) in accordance with ordinary people’s intuitions.
Multiple Superwettable Nanofiber Arrays Prepared by a Facile Dewetting Strategy via Controllably Localizing a Low‐Energy Compound

Superwettable solid surfaces have attracted substantial research interest due to their outstanding performance. Various approaches have been developed for preparing superwettable surfaces via constructing a highly textured surface roughness and/or altering the surface free energy. Here, a facile dewetting strategy is proposed to produce multiple superwettabilities on copper hydroxide nanofiber arrays (Cu(OH)2‐NFAs) by controlling the localized state of low‐energy silicone oil. It is proposed that both the capillary forces along each nanofiber and the evaporation of the octane solvent contribute to the localization of the silicone oil in the NFAs. By varying the concentration of the silicone oil, its localized state changes from a scattered discontinuous distribution to a continuous thin/thick film, which leads to variations in the surface energy and surface roughness. Consequently, Cu(OH)2‐NFAs with superhydrophilicity, superhydrophobicity with both high and low adhesion, and super slippery properties are prepared. Notably, a very small amount of silicone oil can alter the surface wettability of the Cu(OH)2‐NFAs from superhydrophilic to superhydrophobic, which is attributable to the migration of silicone oil to the top of the nanofibers during the dewetting process. These results will provide new insights on the facile fabrication of functional surfaces with multiple superwettabilities.
The Study of Self-mutilation in Patients with Psychiatric Disorders Admitted to the Lavasani Hospital in 2014-2015

Introduction: Self-mutilation can be defined as a deliberate behavior that directly damages the body and damages body tissues or even amputations which, for a few minutes, deprives a person of the feeling or misery position. This study was performed to examine different types of self-mutilation in patients suffering from psychiatric disorders and its relation with the type of illness among patients attending to Lavasani Hospital in 2014-15. Methods: This study is a cross-sectional observation. Forty-two patients suffering from psychiatric illnesses who had performed self-mutilation entered the study. The prevalence of the type of self-mutilation, the used device, and its relation with the type of mental disorder was analyzed. Results: The Results showed that 90.5% of patients used sharp objects, 4.8% used fire, 2.4% used rocks, and 2.4% used other devices for self-mutilation. 76.2% of patients injured the organs, 19% injured the head and neck, 24% injured the body, and 2.4% injured the stomach area. Age and sex did not have a direct correlation with the place and device used (P>0.05), but type of disorder did show a significant relationship with the place and device used (P=0.001). Conclusion: It is concluded that self-mutilation in mental patients is done mainly using sharp objects in the organs.
NBER WORKING PAPER SERIES THE RACE BETWEEN DEMAND AND SUPPLY : TINBERGEN ' S PIONEERING STUDIES OF EARNINGS INEQUALITY

This research was supported in part by the American Bar Foundation and by NIH grants NICHD R37HD065072 and NICHD R01HD054702. The views expressed in this paper are solely those of the authors and do not necessarily represent those of the funders or the official views of the National Institutes of Health. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.
How do we consider the impact of clinical supervisor education? A participatory literature review

Background: This research forms the initial part of a PhD research study, based in the critical paradigm, with an emphasis on developing education strategies that impact on learning in the non-classroom setting. The focus of this article is the education required to enable clinical supervisors to undertake their role supporting nursing students in clinical practice. Aims: There are two aims of this literature review. First, to determine what peer-reviewed, published literature reveals concerning effective learning and teaching strategies for clinical supervisor education. Second, to gain an understanding from a group of clinical supervisors of their perspective on the literature review findings, and develop recommendations for their preparatory education. Methods: This research used a literature review with a participatory phase built in. A traditional review was completed and then extended to include the clinical supervisors reviewing the findings, providing their perspectives and developing recommendations for their own future education development. Findings: During phase one of the research, 22 peer-reviewed articles were included for review and four themes identified and explored. In phase two, 36 clinical supervisors provided their perspectives on these themes. They highlighted the need for a variety of modalities for education to ensure supervisors have shared values, knowledge and skills to work in clinical practice with nursing students and, more broadly, to influence the development of person-centred learning cultures. Conclusions: The literature review revealed a limited amount of peer-reviewed literature. Further, there is little published literature on person-centred situated education for clinical supervisors. When evidence is shared with clinical supervisors, they can contribute to designing their education needs.
Design of Fuzzy PID Load Frequency Controller Tuned by Relative Rate Observer for the Egyptian Power System

This paper deals with the design of Fuzzy Proportional Integral and Derivative FPID controller self tuned by Relative Rate Observer RRO method. The developed approach is applied to the Load-Frequency Control LFC of the Egyptian power system EPS as a single area with multi unit power system. The studied power system comprises three power plants; non-reheat, reheat and hydro generation plants. The proposed FPID controller is designed on an average point of four loading conditions of the EPS during summer and winter of 2008. The effectiveness of the proposed FPID self tuned by RRO (FPID-RRO) has been demonstrated by introducing the system nonlinearities using MATLAB-SIMULINK simulation program. Moreover, a comparison of the FPID with FPID-RRO controllers under different disturbances and parameter variations are presented to validate the FPID-RRO controller. The simulation results reflect and prove fast settling time and accurate tracking for the LFC of the Egyptian Power System.
Bayesian Clustering of Block Structured Relational Data

The discovery of latent information in large-scale databases has become a major problem of information technology and statistics in the recent years. The investigation of relational data, e.g. the structures of graphs is an important field of this problem. One notable task is the clustering of the nodes of the graph. This means the discovery of cohesive groups and the modelling of the cohesion. Bayesian networks have become the most popular tools for modelling data having unobserved or latent variables, since are able to represent the causal relations between the latent and the observable variables. There are several inference methods for these networks, but they provide only general frameworks. The particular cases are depending on the chosen model, the distribution of the random variables, and in many cases they are not tractable. This thesis reviews the probabilistic methods of relational data modelling and the Bayesian inference procedures that are able to cluster and discover the latent structures of (occasionally huge) graphs. Based on the previous methods a new generative model is proposed for clustering graphs. For the estimation of the model parameters a Markov Chain Monte Carlo (MCMC) algorithm is used, by implementing two different type of samplers. The new method is compared to the previous algorithms. Small graphs are investigated with it in order to choose the best parameters and to measure the clustering efficiency. Based on the experiments, the new model turns out to be more efficient than the foregoer methods. Finally, the new tool is used on a real, large-sized dataset.
Spatial distribution of environmental indicators in surface sediments of Lake Bolshoe Toko, Yakutia, Russia

Abstract. Rapidly changing climate in the Northern Hemisphere and associated socio-economic impacts require reliable understanding of lake systems as important freshwater resources and sensitive sentinels of environmental change. To better understand time-series data in lake sediment cores, it is necessary to gain information on within-lake spatial variabilities of environmental indicator data. Therefore, we retrieved a set of 38 samples from the sediment surface along spatial habitat gradients in the boreal, deep, and yet pristine Lake Bolshoe Toko in southern Yakutia, Russia. Our methods comprise laboratory analyses of the sediments for multiple proxy parameters, including diatom and chironomid taxonomy, oxygen isotopes from diatom silica, grain-size distributions, elemental compositions (XRF), organic carbon content, and mineralogy (XRD). We analysed the lake water for cations, anions, and isotopes. Our results show that the diatom assemblages are strongly influenced by water depth and dominated by planktonic species, i.e. Pliocaenicus bolshetokoensis. Species richness and diversity are higher in the northern part of the lake basin, associated with the availability of benthic, i.e. periphytic, niches in shallower waters. δ18Odiatom values are higher in the deeper south-western part of the lake, probably related to water temperature differences. The highest amount of the chironomid taxa underrepresented in the training set used for palaeoclimate inference was found close to the Utuk River and at southern littoral and profundal sites. Abiotic sediment components are not symmetrically distributed in the lake basin, but vary along restricted areas of differential environmental forcing. Grain size and organic matter are mainly controlled by both river input and water depth. Mineral (XRD) data distributions are influenced by the methamorphic lithology of the Stanovoy mountain range, while elements (XRF) are intermingled due to catchment and diagenetic differences. We conclude that the lake represents a valuable archive for multiproxy environmental reconstruction based on diatoms (including oxygen isotopes), chironomids, and sediment–geochemical parameters. Our analyses suggest multiple coring locations preferably at intermediate depth in the northern basin and the deep part in the central basin, to account for representative bioindicator distributions and higher temporal resolution, respectively.
Essential updates to the surgical treatment of biliary tract cancer

Biliary tract cancer, which includes intrahepatic cholangiocarcinoma, extrahepatic bile duct cancer, gallbladder cancer, and ampullary cancer, is an intractable disease with a dismal prognosis. Prognosis is particularly poor in cases involving vessels or lymph nodes. Hepatobiliary pancreatic surgeons worldwide have consistently focused on improving surgical treatment, perioperative management, and chemotherapy to improve the outcomes of these diseases. There has been significant progress even in the last 2 years (2017 and 2018), such as promising findings reported by studies on the optimal extent of surgical treatment and multi‐institutional randomized controlled trials on adjuvant chemotherapy. We overview the current trends and advancements made in surgical treatment in 2017 and 2018.
Fuzzy System and Time Window Applied to Traffic Service Network Problems under a Multi-Demand Random Network

The transportation network promotes key human development links such as social production, population movement and resource exchange. As cities continue to expand, transportation networks become increasingly complex. A bad traffic network design will affect the quality of urban development and cause regional economic losses. How to plan transportation routes and allocate transportation resources is an important issue in today’s society. This study uses the network reliability method to solve traffic network problems. Network reliability refers to the probability of a successful connection between the source and sink nodes in the network. There are many systems in the world that use network architecture; therefore, network reliability is widely used in various practical problems and cases. In the past, some scholars have used network reliability to solve traffic service network problems. However, the processing of time is not detailed enough to fully express the real user’s time requirements and does not consider that the route traffic will affect the reliability of the entire network. This study improves on past network reliability methods by using a fuzzy system and a time window to construct a network model. Using the concept of fuzzy systems, according to past experience, data or expert predictions to define the degree of flow, time and reliability, can also determine the relationship between these factors. The time window can be adjusted according to the time limit in reality, reaching the limit of the complete expression time. In addition, the network reliability algorithm used in this study is a direct algorithm. Compared with the past indirect algorithms, the computation time is greatly reduced and complex problems can be solved more efficiently.
Estimation of Adaptive Antenna Induced Phase Biases in Global Navigation Satellite Systems Receiver Measurements

It is well known that an antenna can introduce direction dependent biases into the code and carrier phase measurements of Global Navigation Satellite System (GNSS) receivers. If the antenna has a fixed pattern, these biases can be calibrated and corrected. However, the pattern of an adaptive antenna changes based on the incident signals and, as a result, so do its bias errors. In this thesis, we will examine these adaptive antenna induced biases in the receiver measurements, and show that currently used calibration measurements do not fully correct for the antenna induced error once interference is introduced. We propose and explain an efficient estimation method that calculates these biases on-the-fly. Using computer simulations, we show that this estimation technique can accurately correct the biases both in the absence and in the presence of interference. Furthermore, we extend the commonly used calibration technique for GNSS receivers to include additional measurements in order to solve for the in situ antenna response used in these calculations.
The Effect of Menstrual Cycle on Metamemory, Everyday Memory and Prospective Memory in Women Aged 18-45 Years

Introduction: The menstrual cycle is one of the biological cycles which has affect on human system because of hormonal fluctuation such as neural system and cognitive function. This study investigated the effects of menstrual cycle on metamemory, everyday memory and prospective memory in women. Methods: This field study was conducted on 60 women aged 18-45 years with natural menstrual cycle. They completed the questionnaire for 3 times; day 1-5 of menstrual cycle and 21th day of the first and third cycles they did past-test. Multi factorial memory questionnaire was used for measuring metamemory and Sunderland test for everyday memory. To assess prospective memory requested to do one predetermined task. Data were analyzed using SPSS software version 15. Repeated measurements method and Mauchly's test was used to test the homogeneity of variances. Results: Menstrual cycle did not affect on metamemory and contentment with memory, but affected on perception of ability and strategies (the two subscales of metamemory) and also everyday memory. Time-based and event-based prospective memory without recall get better during mid-luteal phase but both time-based and event-based prospective memory had no changes through natural menstrual cycle. Conclusion: Hormonal fluctuation has no effect on the monitoring centers of memory during menstrual cycle but can have influence on women’s perception of ability of memory and consequently change their functions.
Keratosis Follicularis Spinulosa Decalvans: A New Observation

Scarring alopecia in association with follicular hyperkeratosis is the primary characteristic of keratosis pilaris atrophicans (KPA). It affects mainly the face and scalp and can be inflammatory in nature [1]. Widespread KP can also be seen. keratosis pilaris atrophicans is a group of cutaneous disorders that may represent a spectrum of 1 disease. Differences in localization and the degree of inflammation and atrophy have been used to distinguish these various disorders [1]. They are genetic disorders with different modes of inheritance. Heterogeneity in the mode of inheritance exists not only between different types of KPA but also within 1 type, such as keratosis follicularis spinulosa decalvans (KFSD) [1, 2]. The pathogenesis is not known, but abnormal follicular keratinization has been suggested.
Data column prediction: experiment in automated column tagging using machine learning

The lack of tools to rapidly identify and align data from different sources is a critical, needed capability for the Department of Defense especially when it comes to automated ingestion. In the current open source Karma Mapping Tool, the Steiner tree optimization algorithm suggests semantic types during data alignment. We hypothesize that Machine Learning (ML) may perform better than the Steiner approach on a subset of column types, or “labels”, where 1. ) the data is extremely similar in structure and content and 2. ) inferring column type correctly is highly dependent on the interrelated components of the dataset. In this session we discuss the experimental design, our initial results, and a path toward future work in broader applications beginning with intelligence analysis in the maritime domain. The initial results from this experiment show there is promise in using ML to do column prediction in analysis environments where there are many similar or overlapping data.
BIOFERTILIZATION WITH ARBUSCULAR MYCORRHIZAL FUNGI (AMF) IN FOREST SPECIES IN NURSERY

The use Arbuscular Mycorrhizal Fungi (AMF) has become an interesting alternative to reduce losses in the multiplication, acclimatization and adaptation processes of different plant species (semester and perennial) to various agroecological condition. The aim of this research was to evaluate in greenhouse the effect of the biofertilization with AMF in four forest species, Pachira quinata (Jac.) W.S. Alverson, Gmelina arborea Roxb, Eucalyptus sp. y Acacia mangium Willd. A complete random blocks experiment were established with three repetitions, thirty plants as the experimental unit and six treatments: two controls (with 50 and 100% fertilization) and four AMF inocula + 50% chemical fertilizartion. Plant height, stem diameter and nutrient concentration were measured. The plants inoculated with Glomus sp. + Gigaspora sp. presented the higher values in heights and diameters as well as a greater translocation of nutrients to the species G. arborea, P. quinata, A. mangium and Eucalyptus sp. AMF and forest species symbiosis has beneficial effects on plant development, which is reflected in the reduction of cost production and reduce time in greenhouse.
The hypermethylation of the CDKN2A and CHFR promoter region is a key regulatory mechanism of CDKN2A and CHFR expression in esophageal squamous cell carcinoma

Background The aim of this study was to evaluate the correlation between CDKN2A and CHFR expression and the methylation status of the CpG island in the promoter region of esophageal squamous cell carcinoma (ESCC) cell lines, radioresistant ESCC cell lines and ESCC clinical tissue specimens. Methods To determine whether the methylation of CHFR and CDKN2A occurs in ESCC and enhanced in radioresistant ESCC cell lines, the DNA methylation of the following was analyzed by pyrosequencing and quantitative real-time polymerase chain reaction (PCR): (I) 28 ESCC tissues; (II) the ESCC cell lines KYSE-150 and KYSE-180; and (III) the radioresistant ESCC cell lines KYSE-150-radioresistance and KYSE-180-radioresistance. Results The methylation of CDKN2A and CHFR was found to be enhanced in the radioresistant ESCC cell lines KYSE-150-radioresistance and KYSE-180-radioresistance (P<0.05), and the expression of CDKN2A and CHFR was found to decrease correspondingly (P<0.05). The methylation of CDKN2A and CHFR was found to be higher in the ESCC tissue and paracarcinoma tissue than in the adjacent benign tissue. The overall survival rates for ESCC patients were significantly correlated with the levels of CDKN2A and CHFR expression (P<0.05). Conclusions Our findings suggest that the hypermethylation of the CDKN2A and CHFR promoter region is a key regulatory mechanism of CDKN2A and CHFR expression in ESCC. Hypermethylated CDKN2A and CHFR are potential biomarkers for predicting the radioresistance of ESCC.