Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Marker to Determine Prognosis of Acute Pancreatitis: PLR and NLR Combination

Summary Background: We aimed to investigate the prognostic importance of platelet-lymphocyte ratio (PLR) and neutro - phil-lymphocyte ratio(NLR) combination for patients diagnosed with acute pancreatitis and its relationship with mortality. Methods: This retrospective study was included 142 patients diagnosed with acute pancreatitis. Ranson, Atlanta and BISAP 0h, 24h and 48h scores of the patients were calculated by examining their patient files. The patients were divided into three groups as low-risk, medium-risk and high-risk patients according to their PLR and NLR levels. Results: The number of patients with acute pancreatitis complications such as necrotizing pancreatitis, acute renal failure, sepsis and cholangitis was significantly higher in the high-risk group compared to other groups. Mortality rate was found to be 90% in the high-risk group, 16% in the medium-risk group, and 1.9% in the low-risk group. The number of patients with a Ranson score of 5 and 6, a severe Atlanta score, a BISAP 0h score of 3 and 4, a BISAP 24h and 48h score of 4 and 5 was higher in the high-risk group compared to other groups. PLR-NLR combination, Atlanta and Ranson scores, and C-reactive protein level were determined to be independent risk factors predicting mortality in stepwise regression model. PLR-NLR combination had the highest area under curve value in terms of predicting acute claspancreatitis prognosis and had a similar diagnostic discrimination with other scoring systems. Conclusion: In our study it was found that PLR-NLR combination had a similar prognostic importance with other scoring systems used to determine acute pancreatitis prognosis.
The Social and Sexual Networks of Black Transgender Women and Black Men Who Have Sex with Men: Results from a Representative Sample

Background: Little research has evaluated the social and sexual network-related health outcomes of young black transgender women (TGW) or compared these outcomes with those of black men who have sex with men (MSM). Social network analysis offers one potent means of understanding the dynamics driving the broad spectrum of adverse outcomes experienced by these subgroups. Methods: We examined the social and sexual health network traits of 618 black individuals assigned male at birth who have sex with men, 47 (7.6%) of whom identified as TGW. Using respondent-driven sampling, data collection occurred over three waves between 2013 and 2016, in Chicago, Illinois. Univariate, logistic regression, and confidant and sexual network analyses were conducted to characterize dynamic network features. Results: TGW's mean age was 22.1 (standard deviation ±2.6). TGW's sexual networks were significantly less stable (stability ratio of 0.175 vs. 0.278 among MSM, p=0.03) and had greater network turnover (turnover ratio of 0.825 vs. 0.735, p=0.04). TGW also had significantly more sex partners (7.6 vs. 4.0, p=0.0002) and exchange sex (odds ratio=2.97; 95% confidence interval: 1.66-5.32, p<0.001), lower rates of employment (39.6% vs. 71.1%, p<0.001), and more reported an income <$20,000 (93.5% vs. 80.8%, p=0.029). Within confidant networks, TGW had a borderline significantly higher network turnover ratio (0.703 vs. 0.625, p=0.06). Furthermore, both TGW and MSM had high, but similar, HIV rates (42.3% vs. 30.6%, respectively; p=0.17). There were no significant structural network differences vis-à-vis mean degree (p=0.46), betweenness centrality (p=0.40), closeness centrality (p=0.18), or average shortest path length (borderline statistically significant at p=0.06). Conclusion: Using data from a representative sample of younger black individuals, we observed black TGW have less sexual network stability in contrast to black MSM but comparable structural network features. We further observed that both groups, and black TGW especially, possess considerable system-level, socioeconomic, and sexual health burdens.
Posture similarity index: a method to compare hand postures in synergy space

Background The human hand can perform a range of manipulation tasks, from holding a pen to holding a hammer. The central nervous system (CNS) uses different strategies in different manipulation tasks based on task requirements. Attempts to compare postures of the hand have been made for use in robotics and animation industries. In this study, we developed an index called the posture similarity index to quantify the similarity between two human hand postures. Methods Twelve right-handed volunteers performed 70 postures, and lifted and held 30 objects (total of 100 different postures, each performed five times). A 16-sensor electromagnetic tracking system captured the kinematics of individual finger phalanges (segments). We modeled the hand as a 21-DoF system and computed the corresponding joint angles. We used principal component analysis to extract kinematic synergies from this 21-DoF data. We developed a posture similarity index (PSI), that represents the similarity between posture in the synergy (Principal component) space. First, we tested the performance of this index using a synthetic dataset. After confirming that it performs well with the synthetic dataset, we used it to analyze the experimental data. Further, we used PSI to identify postures that are “representative” in the sense that they have a greater overlap (in synergy space) with a large number of postures. Results Our results confirmed that PSI is a relatively accurate index of similarity in synergy space both with synthetic data and real experimental data. Also, more special postures than common postures were found among “representative” postures. Conclusion We developed an index for comparing posture similarity in synergy space and demonstrated its utility by using synthetic dataset and experimental dataset. Besides, we found that “special” postures are actually “special” in the sense that there are more of them in the “representative” postures as identified by our posture similarity index.
Serum Cystatin C Levels in COPD: Potential Diagnostic Value and Relation between Respiratory Functions

Summary Background: The aim of this study was to determine the level of serum cystatin C (CysC) in patients with Chronic Obstructive Pulmonary Disease (COPD) during exacerbation and stable periods and to investigate its potential diagnostic value and the relationship between CysC levels and the pulmonary function test (PFT). Methods: One hundred twenty-six patients with COPD (68 in stable periods, 58 during exacerbation periods) and 50 healthy subjects were included in the study. PFT, body mass index (BMI), white blood cell counts, C-reactive protein (CRP), serum urea and creatinine levels were evaluated in both groups of patients. CysC levels were measured in all participants. Results: Serum CysC levels were statistically higher in both COPD groups than the control group (p<0.001 for both) although there was no statistically significant difference between COPD groups (p>0.05). CysC levels showed negative correlation with forced expiratory volume in 1 second (FEV1) and a positive correlation with C-reactive protein (CRP) levels in patients with stable COPD. There was a positive correlation between serum CysC levels and serum urea, creatinine, CRP levels in patients with COPD exacerbation (r=0.333, p=0.011; r=0.260, p=0.049; r=0.414, p<0.01 respectively). When stable COPD and control groups were evaluated, serum CysC had an area under the curve (AUC) in the receiver operating characteristic (ROC) curve of 0.951 (0.909–0.994 95% CI: p<0.001). Conclusions: Our results showed that CysC levels increased in both COPD groups. Increased CysC levels may be related with lung function decline and inflammation in COPD patients. In addition, CysC levels may be a potential indicator for the diagnosis of COPD.
The Incidence Rate, Risk Factors and Clinical Outcome of Acute Kidney Injury in Critical Patients

Background Acute kidney injury (AKI) is the most common cause of organ dysfunction in intensive care unit (ICU) patients. There is no consensus definition of AKI in ICU patients. Therefore, we aimed to evaluate the incidence rate, risk factors and clinical outcome of AKI using the RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease) classification in ICU patients. Methods We performed a retrospective cohort study, on 900 patients admitted to the ICU during a one year period at Imam Khomeini Hospital in Ardebil, Iran from 2014 to 2015. AKI was defined by the consensus RIFLE criteria. Results The overall incidence rate of AKI was 37%. The patients with AKI were also classified according to RIFLE as follows: Risk (8.2%), Injury (13.4%), Failure (13.2%), Loss of kidney function (1.3%), and End-stage kidney disease (0.8%). The mortality rate was 58.3% for AKI patients, and 13.4% for non-AKI patients (P<0.001). Patients in RIFLE-R (Risk) had a mortality rate of 37.8% compared with 48.8% for those in RIFLE-I (Injury) and 76.5% for RIFLE-F (Failure) patients (P<0.0001). Significant risk factors to the development of AKI were included: age more than 60 yr, increased length of hospital stay, systolic blood pressure less than 100 mm Hg, requirement of mechanical ventilation, relevant comorbidities, anemia, thrombocytopenia, increased serum bilirubin and liver enzymes, and serum sodium abnormalities. Conclusion The RIFLE classification is a useful and suitable clinical tool to evaluate the incidence and mortality rate of AKI. In ICU patients, AKI is associated with increased mortality rate.
Chemerin, Resistin, and Adiponectin in Patients with Connective Tissue Diseases

Summary Background: The exact role of cytokines in inflammation and metabolic disorders in case of connective tissue diseases (CTDs) is under discussion. Methods: In this study, we intended to find the relationship between the selected cytokines in inflammatory and metabolic disorders in patients with CTDs (n=55) and compared the results with those of control group subjects (n=25) matched by age and body mass. We estimated their nutritional status by the bioimpedance method. The levels of basic biochemical parameters and the levels of adiponectin, resistin, and chemerin were also estimated. Multiple regressions and area under the curve in receiver operating characteristic (AUC–ROC) curve were used to find the associations of aforementioned parameters. Results: Patients with CTDs exhibited higher levels of chemerin than that of control group subjects. We found an inverse relationship between chemerin, RBC count, and hemoglobin levels. The concentration of adiponectin inversely correlated with the levels of platelets and concentrations of glucose and triglycerides as well as the erythrocyte sedimentation rate, whereas the concentration of resistin was positively correlated with WBC count, C-reactive protein (CRP), and the amount of used oral glucocorticosteroids. The mean ± standard deviation for the AUC–ROC curve in case of chemerin was the highest (AUC–ROC=0.714, p=0.0005) than that of both resistin and adiponectin. Conclusions: Chemerin and resistin levels are related to the inflammatory state in patients with CTDs, whereas adiponectin levels seem to be correlated with a protective effect. Chemerin can be considered as a marker differentiating a proinflammatory state present in CTDs.
Determination of venlafaxine and its active metabolite O-desmethylvenlafaxine in human plasma by HPLC fluorescence

Background Therapeutic drug monitoring guides clinical individualised medication by measuring plasma concentration, which could improve the curative effect, avoid drug overdose and reduce the incidence of adverse reactions. At present, there are few reports on the clinical detection of venlafaxine and its active metabolite O-desmethylvenlafaxine. In this paper, the detection method of venlafaxine and O-desmethylvenlafaxine in blood plasma was established, which provides an effective and convenient means for guiding clinical application of medication. Aim To establish a method for determination of venlafaxine and its active metabolite O-desmethylvenlafaxine in human plasma by high-performance liquid chromatography with fluorescence detection. Methods Chromatographic separation was achieved on an Agilent Eclipse XDB-C18 Column (4.6 × 150 mm, 5 µm) with water containing sodium dihydrogen phosphate (0.05 mol/L) and acetonitrile (72:28) as the mobile phases. The following parameters were employed: flow rate 0.5 mL/min, column temperature 30°C, fluorescence excitation wavelength 276 nm and emission wavelength 598 nm. Results The method showed good linearity in the concentration range 10–1000 ng/mL. The regression equation for venlafaxine was R=0.0054C+0.0264, r2=0.99991. The regression equation for O-desmethylvenlafaxine was R=0.0034C+0.0272, r2=0.99969. The intraday and interday precisions (relative SD) were less than 10%, and the quantitative limit was 10 ng/mL. Conclusion We established a sensitive, specific and simple method for the detection of venlafaxine and O-desmethylvenlafaxine. This method fully meets the needs of clinical trials of venlafaxine and the requirements of relevant guidelines. It provided a reference for the clinical detection of venlafaxine and O-desmethylvenlafaxine plasma concentrations and pharmacokinetic study.
Freshwater carbon and nutrient cycles revealed through reconstructed population genomes

Although microbes mediate much of the biogeochemical cycling in freshwater, the categories of carbon and nutrients currently used in models of freshwater biogeochemical cycling are too broad to be relevant on a microbial scale. One way to improve these models is to incorporate microbial data. Here, we analyze both genes and genomes from three metagenomic time series and propose specific roles for microbial taxa in freshwater biogeochemical cycles. Our metagenomic time series span multiple years and originate from a eutrophic lake (Lake Mendota) and a humic lake (Trout Bog Lake) with contrasting water chemistry. Our analysis highlights the role of polyamines in the nitrogen cycle, the diversity of diazotrophs between lake types, the balance of assimilatory vs. dissimilatory sulfate reduction in freshwater, the various associations between types of phototrophy and carbon fixation, and the density and diversity of glycoside hydrolases in freshwater microbes. We also investigated aspects of central metabolism such as hydrogen metabolism, oxidative phosphorylation, methylotrophy, and sugar degradation. Finally, by analyzing the dynamics over time in nitrogen fixation genes and Cyanobacteria genomes, we show that the potential for nitrogen fixation is linked to specific populations in Lake Mendota. This work represents an important step towards incorporating microbial data into ecosystem models and provides a better understanding of how microbes may participate in freshwater biogeochemical cycling.
Functional Diversity in the Retina Improves the Population Code

Within a given brain region, individual neurons exhibit a wide variety of different feature selectivities. Here, we investigated the impact of this extensive functional diversity on the population neural code. Our approach was to build optimal decoders to discriminate among stimuli using the spiking output of a real, measured neural population and compare its performance against a matched, homogeneous neural population with the same number of cells and spikes. Analyzing large populations of retinal ganglion cells, we found that the real, heterogeneous population can yield a discrimination error lower than the homogeneous population by several orders of magnitude and consequently can encode much more visual information. This effect increases with population size and with graded degrees of heterogeneity. We complemented these results with an analysis of coding based on the Chernoff distance, as well as derivations of inequalities on coding in certain limits, from which we can conclude that the beneficial effect of heterogeneity occurs over a broad set of conditions. Together, our results indicate that the presence of functional diversity in neural populations can enhance their coding fidelity appreciably. A noteworthy outcome of our study is that this effect can be extremely strong and should be taken into account when investigating design principles for neural circuits.
Interview with Stefan Savage: On the Spam Payment Trail

[STEFAN] The truth is that Vern Paxson (UC Berkeley), Geoff Voelker (UC San Diego), and I started down this path back in 2006 . We’d been working together for quite a few years on large-scale attacks (e .g ., worms, viruses, DDoS, etc .), and while we’d had lots of technical successes looking at those problems head on, it was pretty clear that the world wasn’t getting any more secure . Around that time we became exposed to the breadth of activity involved in underground trading of compromised accounts, credit cards, spam mailers, email lists, etc . —anything you could think of . This was really our inspiration, because we came to recognize the role that the profit motive was playing in all this (although spam was key to this evolution, we wouldn’t make the link until later) .
Detecting and Tracking the Rise of DGA-Based Malware

When bots go in search of their command and control (C&C) servers, they often use algorithmically generated domain names (DGAs). We have created a system (Pleiades) that watches unsuccessful DNS resolution requests (NXDomain) from recursive DNS servers in large networks. Pleiades can reliably identify new clusters of NXDomains generated by DGAs, the newly infected hosts, and often, the actual C&C servers the DGA malware employs. In this article, we explain how our system works, as well as the most interesting information about current bot infections and C&C structures
A Systematic and Minimalist Approach to Lower Barriers in Visual Data Exploration

Title of Dissertation: A SYSTEMATIC AND MINIMALIST APPROACH TO LOWER BARRIERS IN VISUAL DATA EXPLORATION Mehmet Adil Yalçın, Doctor of Philosophy, 2016 Dissertation directed by: Professor Benjamin B. Bederson Department of Computer Science Associate Professor Niklas Elmqvist College of Information Studies With the increasing availability and impact of data in our lives, we need to make quicker, more accurate, and intricate data-driven decisions. We can see and interact with data, and identify relevant features, trends, and outliers through visual data representations. In addition, the outcomes of data analysis reflect our cognitive processes, which are strongly influenced by the design of tools. To support visual and interactive data exploration, this thesis presents a systematic and minimalist approach. First, I present the Cognitive Exploration Framework, which identifies six distinct cognitive stages and provides a high-level structure to design guidelines, and evaluation of analysis tools. Next, in order to reduce decision-making complexities in creating effective interactive data visualizations, I present a minimal, yet expressive, model for tabular data using aggregated data summaries and linked selections. I demonstrate its application to common categorical, numerical, temporal, spatial, and set data types. Based on this model, I developed Keshif as an out-of-the-box, webbased tool to bootstrap the data exploration process. Then, I applied it to 160+ datasets across many domains, aiming to serve journalists, researchers, policy makers, businesses, and those tracking personal data. Using tools with novel designs and capabilities requires learning and help-seeking for both novices and experts. To provide self-service help for visual data interfaces, I present a data-driven contextual in-situ help system, HelpIn, which contrasts with separated and static videos and manuals. Lastly, I present an evaluation on design and graphical perception for dense visualization of sorted numeric data. I contrast the non-hierarchical treemaps against two multi-column chart designs, wrapped bars and piled bars. The results support that multi-column charts are perceptually more accurate than treemaps, and the unconventional piled bars may require more training to read effectively. This thesis contributes to our understanding on how to create effective data interfaces by systematically focusing on human-facing challenges through minimalist solutions. Future work to extend the power of data analysis to a broader public should continue to evaluate and improve design approaches to address many remaining cognitive, social, educational, and technical challenges. A SYSTEMATIC AND MINIMALIST APPROACH TO LOWER BARRIERS IN VISUAL DATA EXPLORATION
A Comprehensive Study of IoT and WSN MAC Protocols: Research Issues, Challenges and Opportunities

Recent advances in wireless technologies, micro-electro-mechanical systems, and embedded systems enable the popular usage of the Internet of Things (IoT) and wireless sensor networks (WSNs) in many important applications, such as smart buildings, security, target tracking, industrial automation, and so on. Typically, a WSN consists of a large number of tiny, low-cost sensor nodes that are limited in terms of their capabilities of computation, communication, memory, and power. In WSNs, energy-efficient algorithms are of paramount importance for a long lasting high throughput network. MAC protocol plays a prominent role in extending the life-time of WSNs. MAC protocols provide various schemes on how multiple nodes access a common wireless medium. To achieve a longer lifetime for the nodes and the networks, MAC protocols need to be energy-efficient and reduce the sources of energy wastage. Energy conservation in sensor nodes is generally achieved by duty cycling the radios, and it is the MAC layer protocol that controls when to switch on and off the radio. In this paper, we discuss the essential properties of MAC protocols, the MAC for IoT and the common causes of energy consumptions. Thereafter, we categorize the MAC layer protocols and discuss several protocols under each category in depth, emphasizing their strengths and weaknesses, and giving a detailed comparison of MAC protocols. Finally, we conclude the survey with the insights on future research directions.
FPGA Implementation of a Chaos Based PRNG Targetting Secret Communication

This paper describes the digital implementation of a chaos based cyptographic pseudo-random number generator using a Zynq SoC, offloading the computation to the FPGA. The implementation is based on the generalized Henon map, and it is done using fixed point 3.61 arithmetic. We will show that there is a performance improvement compared to the execution on the ARM Cortex A9 processor and that the generated random bytes are consistent with the software implementation. The generator is tested against the NIST, Dieharder and TestU01 suites.