Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic Impact of Spontaneous Tumor Rupture in Patients With Hepatocellular Carcinoma: An Analysis of 1160 Cases From a Nationwide Survey

Objective:The aim of the present study was to investigate the background characteriscs of ruptured hepatocellular carcinoma (HCC) and to clarify the true impact of tumor rupture on patient prognosis in a large patient cohort. Background:Spontaneous tumor rupture of HCC has been associated with a very poor patient prognosis and the current TNM staging systems classify ruptured HCC as T4 based on insufficient evidence. Methods:In total, 1106 patients with ruptured HCC were extracted from the database of a nationwide survey conducted in Japan from 2000 to 2005. The clinicopathological parameters associated with HCC rupture were investigated using univariate and multivariate logistic regression models. The survival curves for ruptured and nonruptured HCC were generated and compared to evaluate the impact of the event (rupture) itself on patient prognosis and the TNM staging systems. Results:The multivariate analyses showed that tumor rupture was associated with both a poor liver functional reserve and an advanced tumor status. Analyses of the survival curves stratified according to the baseline TNM staging showed that tumor rupture had an additional impact on the baseline survival curves without rupture, and the impact corresponded to the addition of 0.5 to 2 stages to the baseline tumor staging. Conclusions:The present study suggested that tumor rupture itself had a negative impact on patient survival. However, its impact was not strong enough to cancel the effects of the other tumor-related parameters. Therefore, it may be appropriate to give additional stages to the baseline tumor staging in cases of ruptured HCC.
How Genetic and Other Biological Factors Interact with Smoking Decisions

Abstract Despite clear links between genes and smoking, effective public policy requires far richer measurement of the feedback between biological, behavioral, and environmental factors. The Kavli HUMAN Project (KHP) plans to exploit the plummeting costs of data gathering and to make creative use of new technologies to construct a longitudinal panel data set that would compare favorably to existing longitudinal surveys, both in terms of the richness of the behavioral measures and the cost-effectiveness of the data collection. By developing a more comprehensive approach to characterizing behavior than traditional methods, KHP will allow researchers to paint a much richer picture of an individual's life-cycle trajectory of smoking, alcohol, and drug use, and interactions with other choices and environmental factors. The longitudinal nature of KHP will be particularly valuable in light of the increasing evidence for how smoking behavior affects physiology and health. The KHP could have a transformative impact on the understanding of the biology of addictive behaviors such as smoking, and of a rich range of prevention and amelioration policies.
Effect of gate dielectric on threshold voltage of Nanoscale MOSFETS

An integrated circuit (IC) dimensions continue to decrease, RC delay, crosstalk noise, and power dissipation of the interconnect structure become limiting factors for ultra-large-scale integration of integrated circuits. Modern microcircuits may have eight metal layers, each separated by only 0.1 micrometers. RC delays and cross talk rather than transistor speed are now the major performance limitations. The semiconductor industry has responded by developing copper metallization to replace aluminum and lower dielectric constant materials to replace silicon oxide. Materials with different low dielectric constant are being analyzed to replace silicon dioxide as inter level dielectrics. In this paper, how the dielectric constant is affecting the threshold voltage is first discussed. The simulation works are carried using MATLAB, SCHRED software. Based on the results obtained on the effect of k- values on VT in nano MOSFETs, the low-k material (PTFE) is suggested as a suitable material for the development of MOSFET as well as interconnects.
Deterministic analog circuit placement using hierarchically bounded enumeration and enhanced shape functions

The analog placement algorithm Plantage, presented in this paper, generates placements for analog circuits with comprehensive placement constraints. Plantage is based on a hierarchically bounded enumeration of basic building blocks, using B*-trees. The practically relevant solution space is thereby enumerated quasi-complete. The sets of possible placements of the basic building blocks are represented and combined in a new efficient way, using enhanced shape functions. The result of Plantage is the Pareto front of placements with respect to different aspect ratios. The whole approach is deterministic, in contrast to existing analog placement algorithms.
Dysfunction of Glia-Neuron Communication in Pathophysiology of Schizophrenia

Multiple lines of evidence suggest that genetic factors and environmental factors as well as a dysfunction in the glutamatergic neurotransmission contribute to the pathophysiology of schizophrenia. Communication between neurons and glia is essential for axonal conduction, synaptic neurotransmission, and information processing, and thus is required for normal functioning of the nervous system during development and throughout adult life. A number of studies have demonstrated that the substances which communicate between neurons and glia are altered in the blood, cerebrospinal fluid (CSF), and postmortem brain samples of schizophrenic patients. These findings suggest that neuron-glia communication might be impaired in the brains of schizophrenic patients. In this article, we review the imbalance of neuron-glia communication presented in the neurodevelopmental hypothesis as well as the glutamate hypothesis of schizophrenia. First, we discuss the role of growth factors (e.g., basic fibroblast growth factor (bFGF), epidermal growth factor (EGF), midkine), brain-derived neurotrophic factor (BDNF) and cytokines in the pathophysiology of schizophrenia. Second, we focus on the role of endogenous substances (glutamate, glutamine, D-serine, kynurenic acid, and glutathione), which modulate the NMDA receptor function, in the pathophysiology of schizophrenia.
Recognizing actions using embodiment & empathy

Here I demonstrate the power of using embodied arti cial intelligence to attack the action recognition problem, which is the challenge of recognizing actions performed by a creature given limited data about the creature’s actions, such as a video recording. I solve this problem in the case of a worm-like creature performing actions such as curling and wiggling. To attack the action recognition problem, I developed a computational model of empathy (EMPATH) which allows me to recognize actions using simple, embodied representations of actions (which require rich sensory data), even when that sensory data is not actually available. The missing sense data is imagined by combining previous experiences gained from unsupervised free play. The worm is a ve-segment creature equipped with touch, proprioception, and muscle tension senses. It recognizes actions using only proprioception data. In order to build this empathic, action-recognizing system, I created a program called CORTEX, which is a complete platform for embodied AI research. It provides multiple senses for simulated creatures, including vision, touch, proprioception, muscle tension, and hearing. Each of these senses provides a wealth of parameters that are biologically inspired. CORTEX is able to simulate any number of creatures and senses, and provides facilities for easily modeling and creating new creatures. As a research platform it is more complete than any other system currently available. Thesis Supervisor: Patrick H. Winston Title: Ford Professor of Arti cial Intelligence and Computer Science
Domain-Specific Allocentrism-Idiocentrism

Concerned with individual differences in allocentrism-idiocentrism with reference to the family, Study 1 describes the assessment of an initial item pool of statements. Selection of good items was based on several criteria met by both an "Eastern" cultural group and a "Western" cultural group, thereby providing cross-cultural comparability at the item selection stage of test development. Scores on the Family Allocentrism Scale were positively related to a measure of norm-oriented identity style in both "Western" and "Eastern" samples (Study 2). With a "Western" sample (Study 3), individuals with higher levels of family allocentrism exhibited a greater sense of relatedness to their ethnic origins. In Study 4, with a group of Vietnamese immigrant university students, family connectedness moderated the relation between daily hassles and depression. In Study 5, with Russian immigrants, the relation between family allocentrism and depression depended on the level of bicultural competence. Future research plans and needs are considered.
A theoretical framework for cognitive and non-cognitive interventions for older adults: stimulation versus compensation

Background: Recently, interest in cognitive training for older adults has grown significantly, reflecting a need for preserving the quality of life into late adulthood. In spite of increasing interest in cognitive rehabilitation, recent meta-analyses have questioned reported training gains and determined that cognitive gain from cognitive training might be no larger than the gain observed from active controls such as unspecific, non-cognitive activities. Aims: This paper presents a theoretical framework for clarifying specificity of cognitive training by exploring mechanisms of current cognitive and non-cognitive interventions for older adults. By differentiating compensatory aspects from the components of specific and non-specific stimulation in current training, two related strategies of interventions for age-related cognitive decline, i.e., stimulation versus compensation, are proposed. Overview: Current interventions for age-related cognitive decline are reviewed in terms of stimulation- and compensation-focused interventions. Stimulation-focused, cognitive and non-cognitive training, with or without specific targets, tend to result in general improvement in attention and sensory or other cognitive functions. Meanwhile, compensation-focused training is likely to be the most effective when the intervention specifically supports the frontally mediating activity in accordance with the direction of indigenous adjustments in the aging brain. Conclusions: It can be inferred that stimulation-focused training is to ameliorate the adverse effects of neurological aging, whereas compensation-focused cognitive training is primarily to facilitate compensatory adaptation in the brain.
Lessons (not) learned on climate change adaptation policy: qualitative research on the case of floods in Western Balkan countries

In this paper we present the findings of our qualitative research on adaptation to climate change within the context of the major floods that hit countries in Central and South-Eastern Europe in 2014. Adaptation here refers to the response of any given social system regarding existing and expected impacts of climate change and extreme climate events. The effectiveness of the response depends on how vulnerable or how resilient a particular system is, and this includes not only technical and biophysical aspects, but also social, cultural, political and economic ones. We conducted empirical research in order to describe how actors in environmental governance structures in three countries – Bosnia and Herzegovina, Croatia and Serbia – viewed the climate change adaptation process, and whether they recognized climate change as a trans-sectoral problem during all the phases of the 2014 flood crisis. The results show that even though most interviewees are aware of the connection between climate change and the 2014 floods, they are unable to properly address these kinds of crises. Given that in all three countries climate mitigation and adaptation measures are divided between different ministries and departments, which are not complementary, this lack of interconnectedness is thus reflected in the interviewees’ observations.
Constructing a contexual collaborative recommending approach to social network system

Recommender system is mainly based on collaborative filtering algorithms in social network, where it takes folksonomy as basic data structure. Collaborative filtering as a classical method of information retrieval has been also used in helping people to deal with information overload in folksonomies system. When context is taken into account, there might be difficulties when it comes to making recommendations to users who are placed in a context other than the usual one, since these main elements of folksonomy are dependent on their context informations. In this paper, a contextual collaborative filtering model is proposed, which produces recommendations based on the context, and may be better solution to folksonomies in the recommender system. In order to solve the contextual problems emerging in the process of recommendational application, this paper offers a feasible means for developers to handle context problems for folksonomy application.
A two‐dimensional proteome map of the aflatoxigenic fungus Aspergillus flavus

The filamentous fungus Aspergillus flavus is an opportunistic soil‐borne pathogen that produces aflatoxins, the most potent naturally occurring carcinogenic compounds known. This work represents the first gel‐based profiling analysis of A. flavus proteome and establishes a 2D proteome map. Using 2DE and MALDI‐TOF‐MS/MS, we identified 538 mycelial proteins of the aflatoxigenic strain NRRL 3357, the majority of which were functionally annotated as related to various cellular metabolic and biosynthetic processes. Additionally, a few enzymes from the aflatoxin synthesis pathway were also identified.
The Role of Ephs and Ephrins in Memory Formation

The ability to efficiently store memories in the brain is a fundamental process and its impairment is associated with multiple human mental disorders. Evidence indicates that long-term memory formation involves alterations of synaptic efficacy produced by modifications in neural transmission and morphology. The Eph receptors and their cognate ephrin ligands have been shown to be involved in these key neuronal processes by regulating events such as presynaptic transmitter release, postsynaptic glutamate receptor conductance and trafficking, synaptic glutamate reuptake, and dendritic spine morphogenesis. Recent findings show that Ephs and ephrins are needed for memory formation in different organisms. These proteins participate in the formation of various types of memories that are subserved by different neurons and brain regions. Ephs and ephrins are involved in brain disorders and diseases with memory impairment symptoms, including Alzheimer’s disease and anxiety. Drugs that agonize or antagonize Ephs/ephrins signaling have been developed and could serve as therapeutic agents to treat such diseases. Ephs and ephrins may therefore induce cellular alterations mandatory for memory formation and serve as a target for pharmacological intervention for treatment of memory-related brain diseases.
A comparison of a generic MCMC-based algorithm for Bayesian estimation in C++, R and Julia: application to plant growth modeling

Plant growth is understood through the use of dynamical systems involving many interacting processes and model parameters whose estimation is therefore a crucial issue, all the more so since experimental data obtained from agronomical systems are most of the time characterized by their scarcity and their heterogeneity owing to the complex underlying acquisition. One of the approaches used to solve this kind of problem within a Bayesian paradigm involves Markov Chain Monte Carlo (MCMC) algorithms, one of the drawbacks of the latter being that they lead to some intensive computation because of the statistical framework employed, which is why the efficiency of the implemented computing methods is of particular importance. In this paper, we compare three implementations of a generic MCMC-based algorithm for Bayesian estimation in C++, R and Julia so as to compare the performance and precision of these languages. Here, genericness means that the estimation algorithm can be used for any dynamic model provided that it is implemented in a given modeling template. Such genericness is of crucial importance in a scientific field such as plant growth modeling for which no reference model exists and new models are constantly developed and evaluated. The tests are conducted for the particular cases of Lotka--Volterra model and the Log-Normal Allocation and Senescence model for sugar beet.
Investigation of Sensor Parameters for Kinematic Assessment of Steady State Running Using Foot Mounted IMUs

The continuous sensing of kinematics provides an opportunity to monitor changes in sporting technique or to aid in injury rehabilitation. Inertial sensors are now small enough to integrate into footwear, providing a potential platform for continuous monitoring that does not require additional components to be worn by the athlete and can be used to assess foot kinematics during running. To facilitate widespread adoption, sensor systems must be as cheap as possible. To achieve this it is required that such systems be engineered with sampling rates that are not unnecessarily high and with sensor components that meet the requirements of the task, including required accuracy. We investigate multiple sensor parameters (sampling rate, acceleration range) and their effect on the accuracy of kinematic assessment using foot worn inertial sensors. We find that Extended Kalman Filter based trajectory recovery seems to be little affected by sampling rates until below 250Hz. We investigate impact accelerations using an inertial measurement unit attached to the foot and find that, at 250Hz, the acceleration signal peaks at up to 70g around heel strike.
UWM-HBUT at TREC 2014 Microblog Track: Using Query Expansion (QE) and Event Identification Algorithm (EIA) to improve microblog retrieval effectiveness

Abstract : This paper reports our contributions and results to TREC 2014 Microblog Track. Different from traditional web pages or database documents, microblogs have their own unique features. Considering sensitivity to time, we introduce a new factor to help to improve tweet retrieval effectiveness. The ranking score of a retrieved tweet is adjusted by considering how close the tweet time stamp is to the event using Event Identification Algorithm (EIA). In addition, we also evaluate the Query Expansion (QE) approach using Google as an external data corpus. There are 55 search topics and the data set contains a total of 243 million tweets provided by the TREC 2014 Microblog Track. Our initial results indicated that QE helped to improve the performance. We also discussed why the EIA approach failed to enhance the retrieval performance.
Looking for Audience Costs

The methodological issues that arise in testing Fearon's argument about domestic political audience costs and signaling in international crises are examined, in particular the difficulty of finding direct evidence (1) that escalating a crisis and then backing down jeopardizes a leader's tenure in office, and (2) that democratic leaders are more vulnerable to removal in this event than are nondemocratic leaders. Tests that seek to measure the existence and magnitude of audience costs encounter severe problems of partial observability and strategic selection: the effect of audience costs on a leader's political survival can only be detected by looking at cases in which the costs are actually incurred, but strategic choice implies that the probability of incurring audience costs is a function of their value. A formal model, brief case studies, and Monte Carlo simulations are used to show that these problems bias direct tests against supporting either of the audience cost propositions. Tests based on observed audience costs understate both the mean level of audience costs in the full population and the difference in means across regime types.
A Study on the Prevalence of Bovine Mastitis and Associated Risk Factors in and the Surrounding areas of Sodo Town, Wolaita Zone, Ethiopia

Ethiopia is believed to have the largest livestock population in Africa. This livestock sector has been contributing considerable portion to the economy of the country, and still promising to rally round the economic development of the country. It is eminent that livestock products and by-products in the form of meat, milk, honey, eggs, cheese, and butter supply provide mainly the needed animal protein that contributes to the improvement of the nutritional status of the people (CSA, 2009). Even though Ethiopia is the most populous country in cattle than any African country; the per capita milk consumption was 16 kg, which was lower than other countries in the region (Asfaw, 1997). This is partly due to the low genetic milk production potential of the indigenous zebu cattle. To increase milk production cross breeding of indigenous zebu with exotic breeds particularly with Holstein Friesian is widely practiced which resulted in a larger portion of the dairy cattle population especially in urban areas to be with a high level of exotic blood. However, this market oriented dairy production, a rapidly growing system in many African countries, is subjected to diseases of intensification including mastitis and reproductive disorders (Lemma et al., 2001).
Expository Discourse Intervention for Adolescents With Language Disorders

Speech-language pathologists play a crucial role in helping adolescents with language disorders improve their ability to comprehend and produce the language of the curriculum (i.e., expository discourse) and, thus, enhance their potential for academic success. The purpose of this article is to present numerous treatment techniques and strategies for increasing both spoken and written expository discourse skills in this population.
Personality traits in learning and education

Personality traits judged relevant for the context of learning and education are identified as a subset of a comprehensive set of 1203 trait descriptive adjectives, constructed by Brokken (1979). The identification procedure is described and relevant statistics are provided. Self- and peer-ratings (N = 400) on the resulting subset of 194 trait adjectives were subjected to principal components analysis. The eigenvalues indicate two factors as being sufficient to capture most of the education relevant meanings. The trait terms judged non-relevant to the context of learning and education were correlated with the two Varimax rotated educational trait factors. The results me circularly expressed in the forms of an Educational Trait Circumplex. The contents of the two factors are discussed relative to the findings in the literature, and the two factors are evaluated against the framework of the Big Five factors.