Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic Factors for Adrenocortical Carcinoma Outcomes

Purpose Adrenocortical carcinoma (ACC) is an aggressive tumor characterized by a high recurrence rate and poor response to treatment. This study analyzes a consecutive series of ACC patients to evaluate the prognostic value of various clinical and pathological characteristics. Methods We retrospectively evaluated 32 ACC patients followed at our Medical Center from 1997 to 2015 and evaluated the prognostic value of age at diagnosis, gender, tumor functional status, stage, and type of treatment with respect to overall survival (OS) and disease-free survival (DFS), as determined by Kaplan–Meier curves. Results ACC was associated with hormonal overproduction in 50% of cases, and patients with isolated hyperandrogenism had a better prognosis. Recurrence was observed in 12/26 (46.2%) patients with no evidence of disease after surgery. Tumor size [hazard ratio (HR) 1.32, 95% confidential intervals (CI) 1.12–1.64; p = 0.007], ki-67 (HR 1.06, 95% CI 1.02–1.11; p = 0.009) and advanced stage at diagnosis (III–IV) (HR 6.51, 95% CI 1.65–24.68; p = 0.006) were associated with recurrence in the 26 R0 patients in the univariate analysis. Advanced stage was an independent risk factor for recurrence in the multivariate analysis (HR 8.10, 95% CI 1.55–41.35; p = 0.01). Five-year survival was 40.0%. Positive resection margins (HR 10.61, 95% CI 3.02–38.31; p = < 0.001), ki-67 (HR 1.04, 95% CI 1.01–1.07; p = 0.01) and advanced stage (HR 11.31, 95% CI 1.45–87.76; p = 0.02) were associated with poor survival in all 32 patients, but only positive resection margins were an independent predictor of mortality in the multivariate analysis (HR 6.22, 95% CI 1.44–26.05; p = 0.01). Conclusion ACC has a poor prognosis with a high recurrence rate. Tumor stage at diagnosis and the completeness of surgical excision are the most relevant prognostic factors.
Autonomous Robot Control Using Facial Expressions

In this paper, a novel real time robot control system using human facial expressions is presented. The proposed system mainly consists of three modules: face detection, facial expression recognition and robot control. The first module aims to find the user's face from the image captured from a live video through a series of steps including skin color classification, edge detection and mathematical morphology, while the second module analyses the detected face to recognize the facial expressions like happiness, sadness, surprise, anger and neutral using Principal Component Analysis (PCA) and Euclidian distance calculation. Finally, the detected facial expressions are used as controlling commands for the robot. Experiments were conducted for respective modules. 150 images under different lightening conditions and complex background were employed. In the experiment on detecting the facial region, the rate of detection was 99.3% and on recognizing the facial expression, the recognition rate was 97.3%. The robot was then controlled autonomously with an accuracy of 100%. Combining the above three rates, the overall rate of success of our system was 97.3%.
Mechanics and Microstructures of Concentrated Particle Gels

It is often assumed that the viscoelastic properties of dense colloids are determined by the colloid volume fraction, the interaction potential, as well as the particle size distribution and shape. The dependence of the viscoelastic behavior of particle suspensions and gels on these parameters has been widely studied, and is well understood in many cases. In contrast, our knowledge on the influence of microstructure on mechanical and rheological properties, in particular for high solid loading suspensions as used in ceramic processing, is much less developed. This aspect has been the focus of recent experiments, which show that small changes in microstructure can have dramatic effects on the mechanics and dynamics of concentrated colloidal gels. In this article, we attempt to give an overview of the influence of microstructure on the mechanical and rheological properties of colloidal systems. Particular attention is given to colloidal particle gels at high volume fractions.
Core Self-Evaluations and Leadership Emergence in Autonomous Work Teams: The Mediating Effect of Team Process

Fifty two Autonomous work teams consisting of 208 participants were examined whether and how individual¿s dispositional trait -- core self evaluations (CSES) affected the leadership emergence which is measured by three indicators. Results showed that CSES, measured as a single construct, positively related to leadership emergence, and the team process, indicated by three variables, was found to partially mediate the relationship between CSES and leadership emergence. Also this correlation was not moderated by task type or goal type. This study provided empirical support for the dispositional base of leadership emergence and explored the effect of moderation and mediation factors on the relationship between the dispositional effect and leadership emergence in autonomous work teams limitation and further research direction are also discussed.
Palpable Privacy through Declarative Information Flows Tracking for Smart Buildings

Smart buildings are more and more common due to recent technological advances. They promise to improve users' lives, but they are packed with sensors that gather user related data, fueling ever increasing privacy infringement suspicions. Captured data usually takes the form of dynamic streams, hence such buildings can naturally be programmed using Data Stream Management Systems (DSMSs) that execute long-running queries on data flowing from sensors. In this paper we address the problem of the dissemination control of private data, encountered in smart buildings. We introduce Tuple-Based Access Control (TBAC), a novel access control model that tracks sensor information flows in a DSMS. We provide users with the ability to enforce easy-to-understand, intuitive security policies on sensor-produced data. When such data are combined by queries in the system, so are their security policies, hence data access control is disseminated throughout the system. We argue that such a model is mandatory to ease the acceptance of smart buildings. Nevertheless, TBAC can also be relevant to other scenarios involving dissemination of aggregable private data.
A relationship between HNN extensions and amalgamated free products in operator algebras

With a minor change made in the previous construction we observe that any reduced HNN extension is precisely a compressed algebra of a certain reduced amalgamated free product in both the von Neumann algebra and the $C^*$-algebra settings. It is also pointed out that the same fact holds true even for universal HNN extensions of C$^*$-algebras. We apply the observation to the questions of factoriality and type classification of HNN extensions of von Neumann algebras and also those of simplicity and $K$-theory of (reduced or universal) HNN extensions of $C^*$-algebras.
Gene Selection Using Iterative Feature Elimination Random Forests for Survival Outcomes

Although many feature selection methods for classification have been developed, there is a need to identify genes in high dimensional data with censored survival outcomes. Traditional methods for gene selection in classification problems have several drawbacks. First, the majority of the gene selection approaches for classification are single-gene based. Second, many of the gene selection procedures are not embedded within the algorithm itself. The technique of random forests has been found to perform well in high-dimensional data settings with survival outcomes. It also has an embedded feature to identify variables of importance. Therefore, it is an ideal candidate for gene selection in high-dimensional data with survival outcomes. In this paper, we develop a novel method based on the random forests to identify a set of prognostic genes. We compare our method with several machine learning methods and various node split criteria using several real data sets. Our method performed well in both simulations and real data analysis. Additionally, we have shown the advantages of our approach over single-gene-based approaches. Our method incorporates multivariate correlations in microarray data for survival outcomes. The described method allows us to better utilize the information available from microarray data with survival outcomes.
An investigation of the relationship between organizational citizenship behavior and emotional intelligence in employees'Payam Noor University

The main purpose of this study was the relation between organizational citizenship behavior and emotional intelligence. For this reason,60 people were chosen random stratified and their data were gathered by Schutte emotional intelligence scale and Van Dyne et al organizational citizenship behavior scale. After that, to analyze the data, Pearson correlation, regression analyzes. Result showed that there is a relation between organizational citizenship behavior and emotional intelligence. Results were further analyzed using regression analysis with the model accounting for 28% of the variance in total OCB using the variable of total EI. Implication for future research are discussed
A research on examination of medical errors through court judgments

Aim: Medical errors are one of the most important and chronic problems of health care systems. In this study, medical error cases decided by the Supreme Court were examined. Materials-Methods: The work is retrospective, descriptive and analytical, and it is limited to civil court decisions on a suit for error. Sixty court decisions that were randomly selected in the study were obtained via www.yargitay. gov.tr and www.kazanci. com.tr. The decisions were examined in detail by researchers. Results: According to the research result, it is understood that the medical errors mostly occur in gynecology and obstetrics and general surgery branches. Treatment errors are the most important cause of medical errors. Material and moral damage ranks first, and death ranks the second due to medical errors. It has been revealed that the predominant responsibilities of medical errors are on physicians in large part. The two most common causes of medical errors are the choice of the wrong treatment method and surgical errors. Conclusion: In the light of the analyzes, it is seen that medical errors are largely human-induced factors. Therefore, establishing mechanism to minimize medical errors, increasing the level of awareness of medical staff about medical errors, to minimize wrong treatment method and surgical errors thought to be effective strategies to prevent medical errors.
Output Impedance Diffusion Into Lossy Power Lines

Output impedances are inherent elements of power sources in the electrical grids. In this paper, we give an answer to the following question: What is the effect of output impedances on the inductivity of the power network? To address this question, we propose a measure to evaluate the inductivity of a power grid, and we compute this measure for various types of output impedances. Following this computation, it turns out that network inductivity highly depends on the algebraic connectivity of the network. By exploiting the derived expressions of the proposed measure, one can tune the output impedances in order to enforce a desired level of inductivity on the power system. Furthermore, the results show that the more “connected” the network is, the more the output impedances diffuse into the network. Finally, using Kron reduction, we provide examples that demonstrate the utility and validity of the method.
Models for Dice Factories and Amino Acid Probability Vectors . Draft 1 . 1

Protein alignments are commonly characterized by the probability vectors over amino acids in each column of the alignment. This paper develops various models for the probability distribution of these probability vectors. First a simple Dirichlet distribution is used, then a mixture of Dirich-lets. Finally a componential model employing a `density network' is described. These models are optimized and compared using Bayesian methods.
Integrative and Translational Physiology : Integrative Aspects of Energy Homeostasis and Metabolic Diseases Vasopressin and oxytocin excite MCH neurons , but not other lateral hypothalamic GABA neurons

Yao Y, Fu L-Y, Zhang X, van den Pol AN. Vasopressin and oxytocin excite MCH neurons, but not other lateral hypothalamic GABA neurons. Am J Physiol Regul Integr Comp Physiol 302: R815–R824, 2012. First published January 18, 2012; doi:10.1152/ajpregu.00452. 2011. —Neurons that synthesize melanin-concentrating hormone (MCH) colocalize GABA, regulate energy homeostasis, modulate water intake, and influence anxiety, stress, and social interaction. Similarly, vasopressin and oxytocin can influence the same behaviors and states, suggesting that these neuropeptides may exert part of their effect by modulating MCH neurons. Using whole cell recording in MCH-green fluorescent protein (GFP) transgenic mouse hypothalamic brain slices, we found that both vasopressin and oxytocin evoked a substantial excitatory effect. Both peptides reversibly increased spike frequency and depolarized the membrane potential in a concentration-dependent and tetrodotoxin-resistant manner, indicating a direct effect. Substitution of lithium for extracellular sodium, Na /Ca exchanger blockers KB-R7943 and SN-6, and intracellular calcium chelator BAPTA, all substantially reduced the vasopressin-mediated depolarization, suggesting activation of the Na /Ca exchanger. Vasopressin reduced input resistance, and the vasopressin-mediated depolarization was attenuated by SKF-96265, suggesting a second mechanism based on opening nonselective cation channels. Neither vasopressin nor oxytocin showed substantial excitatory actions on lateral hypothalamic inhibitory neurons identified in a glutamate decarboxylase 67 (GAD67)-GFP mouse. The primary vasopressin receptor was vasopressin receptor 1a (V1aR), as suggested by the excitation by V1aR agonist [Arg]vasotocin, the selective V1aR agonist [Phe]OVT and by the presence of V1aR mRNA in MCH cells, but not in other nearby GABA cells, as detected with single-cell RT-PCR. Oxytocin receptor mRNA was also detected in MCH neurons. Together, these data suggest that vasopressin or oxytocin exert a minimal effect on most GABA neurons in the lateral hypothalamus but exert a robust excitatory effect on presumptive GABA cells that contain MCH. Thus, some of the central actions of vasopressin and oxytocin may be mediated through MCH cells.
Characterizing Visitors to a WebsiteAcrossMultiple Sessions ArindamBanerjeeandJoydeepGhosh

Characterizing web users basedon their interactions with a particular websiteis a key problemin webmining. Such interactionsare reflectedby clickstreamdata in weblogs,thecontentof thepagesthat they view, aswell astheir actionssuch assearch queriestypedin. In general a wide variety of behaviors is observedat popular websites.So, to make theproblemmore tractable, it is oftenwiseto first group similar users into relativelyhomogeneoussegments andthentry to characterizeeach such segment.There has beenmuch work doneon clusteringvisitors at a site, but typically the analysesusesubstantiallysimplifieddescriptionsof sessionbehavior , andalsodonotcharacterizeusers basedon their footprintsacrossmultiple visits to the site. In this paper, each webuseris representedby a setof sessions,anda twostagemethodologyfor groupingsuch users is proposed. In the first stage, sessionsare clustered into conceptualsessiontypesbasedonboththetrajectorytaken throughthewebsiteaswell as thetimespentat each page. Thedistribution of a user’smultiplevisitsacrossthesesession typesforms the basisof usergrouping in the second stage. Such clustering basedon a rich user description formsa platform for further characterization. Resultsare presentedusingweblogs of a popular websiteto illustrate
Early Detection of Acute Drug-Induced Liver Injury in Mice by Noninvasive Near-Infrared Fluorescence Imaging

Hepatocellular and cholestatic forms of drug-induced liver injury (DILI) are major reasons for late-stage termination of small-molecule drug discovery research projects. Biochemical serum markers are limited in their ability to sensitively and specifically detect both of these common DILI forms in preclinical models, and tissue-specific approaches to assessing this are labor intensive, requiring extensive animal dosing, tissue preparation, and pathology assessment. In vivo fluorescent imaging offers noninvasive detection of biologic changes detected directly in the livers of living animals. Three different near-infrared fluorescent imaging probes, specific for cell death (Annexin-Vivo 750), matrix metalloproteases (MMPSense 750 FAST), and transferrin receptor (Transferrin-Vivo 750) were used to measure the effects of single bolus intraperitoneal doses of four different chemical agents known to induce liver injury. Hepatocellular injury–inducing agents, thioacetamide and acetaminophen, showed optimal injury detection with probe injection at 18–24 hours, the liver cholestasis-inducing drug rifampicin required early probe injection (2 hours), and chlorpromazine, which induces mixed hepatocellular/cholestatic injury, showed injury with both early and late injection. Different patterns of liver responses were seen among these different imaging probes, and no one probe detected injury by all four compounds. By using a cocktail of these three near-infrared fluorescent imaging probes, all labeled with 750-nm fluorophores, each of the four different DILI agents induced comparable tissue injury within the liver region, as assessed by epifluorescence imaging. A strategy of probe cocktail injection in separate cohorts at 2 hours and at 20–24 hours allowed the effective detection of drugs with either early- or late-onset injury.
A conceptual model for preventing web bypass vulnerabilities

This paper provides a conceptual model for reducing bypass vulnerabilities in web applications. The typical and primary two kinds of bypass vulnerabilities are authentication and access control vulnerabilities. Authentication attacks occur when a web application authenticates users incorrectly and grants access for users without appropriate credentials. Access control attacks happen when access control check is incorrect or missing, allowing unauthorized access to privileged resources. Such attacks are getting increasingly common and have occurred in many famous web applications such as IIS and WordPress, and 14% of surveyed web sites [5]. However, currently no available tools or methods can prevent these attacks efficiently. By using Dynamic Information Flow Tracking (DIFT) techniques to track the flow of user credentials through the application's language runtime, the model presented in this paper can automatically detect when an application safely and correctly authenticates users. Then the model combines authentication information with programmer-supplied access control rules to automatically ensure that only properly authenticated users are granted access to privileged resources or data.
The Social Modulation of Imitation Fidelity in School-Age Children

Children copy the actions of others with high fidelity, even when they are not causally relevant. This copying of visibly unnecessary actions is termed overimitation. Many competing theories propose mechanisms for overimitation behaviour. The present study examines these theories by studying the social factors that lead children to overimitate actions. Ninety-four children aged 5- to 8-years each completed five trials of an overimitation task. Each trial provided the opportunity to overimitate an action on familiar objects with minimal causal reasoning demands. Social cues (live or video demonstration) and eye contact from the demonstrator were manipulated. After the imitation, children's ratings of action rationality were collected. Substantial overimitation was seen which increased with age. In older children, overimitation was higher when watching a live demonstrator and when eye contact was absent. Actions rated as irrational were more likely to be imitated than those rated as rational. Children overimitated actions on familiar objects even when they rated those actions as irrational, suggesting that failure of causal reasoning cannot be driving overimitation. Our data support social explanations of overimitation and show that the influence of social factors increases with age over the 5- to 8-year-old age range.
Architecture-based SW process model

Explicit software architecture is principal in the development of a software project. In this paper Architecture-Based Software Process model (ABSP) is presented. ABSP model divides software process based on architecture into six sub processes: requirements, design, documentation, review, implementation, and evolution. Compared with traditional software process model, ABSP model has many advantages such as explicit structure, easy understandability, better portability and large reusable granularity.
A parallel 3D free surface Navier-Stokes solver for high performance computing at the German Waterways Administration

This paper deals with the numerical modeling of the highly complicated interactions between topography, hydraulic structures and vessels with the two phases water and air. Standard 3D models for river hydraulics are not necessarily in the position to describe these phenomena. For the approximation, a two-phase Navier-Stokes solver is indispensable. The goal is accordingly to extend the parallel 3D two-phase flow source code NaSt3DGPF for applications in the near vicinity of hydraulic structures and vessels. The model includes all significant processes relevant to hydraulic structures at waterways. Providing the transition between water and air the Level Set Method is implemented, turbulence is modeled by using a LES concept. Regarding an automated meshing of real world CAD applications, the substantial advantages of using a Finite Difference Method based on a non-uniform structured grid will be shown. In view of an effective usage of the HPC resources, the limitations concerning the sizes of the 3D modeling domains, the possibilities of optimizing the grid spaces and a necessary coupling with 1D far field models are in the focus of interest. The validation against laboratory models and recent projects at German waterways with up to 10 million grid points will be presented.
Social Networks and the Dynamics of Labour Market Outcomes: Evidence from Refugees Resettled in the U.S

This paper examines the dynamic implications of social networks for the labour market outcomes of refugees resettled in the U.S. A theoretical model of job information transmission shows that the relationship between social network size and labour market outcomes is heterogeneous and depends on the vintage of network members: an increase in network size can negatively impact some cohorts in a network while benefiting others. To test this prediction, I use new data on political refugees resettled in the U.S. and exploit the fact that these refugees are distributed across cities by a resettlement agency, precluding individuals from sorting. The results indicate that an increase in the number of social network members resettled in the same year or one year prior to a new arrival leads to a deterioration of outcomes, while a greater number of tenured network members improves the probability of employment and raises the hourly wage. Copyright 2012, Oxford University Press.