Miracle-dz/UniFAR-FTUs huggingface dataset:
Top Down or Bottom Up? A Cross-National Study of Vertical Occupational Sex Segregation in Twelve European Countries

Starting with a comparative assessment of different welfare regimes and political economies from the perspective of gender awareness and "pro-women" policies, this paper identifies the determinants of cross-national variation in women's chances of being in a high-status occupation in twelve West European countries. Special emphasis is given to size and structure of the service sector, including share of women in public employment and structural factors such as trade union density and employment protection. The first level of comparison between men and women concentrates on gender representation in the higher echelons of the job hierarchy, while in the second section we extend the scope of analysis, comparing women in high-status occupations and low-wage employment in order to allow for a more nuanced study of gender and class interaction. The first analysis is based on European Social Survey data for the years 2002, 2004, 2006, and 2008, capturing recent trends in occupational dynamics. Results indicate that in general a large service sector and a high trade union density enhance women's chances of being in high-status occupations while more specifically a large public sector helps to reduce channeling women into low-wage employment. Thus, equality at the top can well be paired with inequality at the bottom, as postindustrial countries with a highly polarized occupational hierarchy such as the UK show.
Body-Mind-Language: Multilingual Knowledge Extraction Based on Embodied Cognition

Cognitive linguistics has provided compelling evidence that semantic structure in natural language reflects conceptual structure that arises from our embodied experience in the world. To capture this conceptual structure, a set of spatio-temporal cognitive building blocks called image schemas was introduced by Lakoff and Johnson. Detecting image schemas in natural language can provide further insights into how embodied experiences are encoded in natural language and potentially contribute to research on conceptual understanding and symbol grounding in cognitive systems. Methods for (semi-)automatically extracting image schemas from natural language are an open challenge. We propose a spectral clustering approach paired with semantic role labeling to semi-automatically extract image schemas from multilingual text, obtaining a precision of more than 80% on three languages.
Bayesian and frequentist two‐stage treatment strategies based on sequential failure times subject to interval censoring

For many diseases, therapy involves multiple stages, with the treatment in each stage chosen adaptively based on the patient's current disease status and history of previous treatments and clinical outcomes. Physicians routinely use such multi‐stage treatment strategies, also called dynamic treatment regimes or treatment policies. We present a Bayesian framework for a clinical trial comparing two‐stage strategies based on the time to overall failure, defined as either second disease worsening or discontinuation of therapy. Each patient is randomized among a set of treatments at enrollment, and if disease worsening occurs the patient is then re‐randomized among a set of treatments excluding the treatment received initially. The goal is to select the two‐stage strategy having the largest average overall failure time. A parametric model is formulated to account for non‐constant failure time hazards, regression of the second failure time on the patient's first worsening time, and the complications that the failure time in either stage may be interval censored and there may be a delay between first worsening and the start of the second stage of therapy. Four different criteria, two Bayesian and two frequentist, for selecting a best strategy are considered. The methods are applied to a trial comparing two‐stage strategies for treating metastatic renal cancer, and a simulation study in the context of this trial is presented. Advantages and disadvantages of this design compared to standard methods are discussed. Copyright © 2007 John Wiley & Sons, Ltd.
Robust ultrasound-based room-level localization system using COTS components

Location-based services have become very popular in recent years. Although many previous works targeted the problem of indoor localization, several reasons still prevent the widespread adoption of most systems' implementations. Some of these reasons are their insufficient availability, and the need for extensive node deployment and maintenance. In this work, we present a highly accurate room-level indoor localization system that is based on ultrasound technology. Our system is robust to noise, scalable, has a low complexity on the receiver, and does not require synchronization between transmitter and receiver. Moreover, it uses commercial off-the-shelf (COTS) components and does not require special hardware or additional infrastructure to be deployed. The system relies solely on ultrasound, and does not use any RF signals. To deal with the problem of signal interference, we explain how signal collisions can be detected, and we propose a method for collision avoidance. The system was implemented and tested in scenarios with realistic conditions. The results prove that the proposed system is accurate and robust to ambient noise. This work was conducted in the frame of the European project ‘SmartHeat’, which aims to improve heating conditions of elderly people, and reduce energy consumption. It employs rooms' occupancy information with other inputs, to adapt the heating according to users' habits.
Intrinsic spontaneous brain activity predicts individual variability in associative memory in older adults

Older adults demonstrate notable individual differences in associative memory. Here, resting-state functional magnetic resonance imaging (rsfMRI) was used to investigate whether intrinsic brain activity at rest could predict individual differences in associative memory among cognitively healthy older adults. Regional amplitude of low-frequency fluctuations (ALFF) analysis and a correlation-based resting-state functional connectivity (RSFC) approach were used to analyze data acquired from 102 cognitively normal elderly who completed the paired-associative learning test (PALT) and underwent fMRI scans. Participants were divided into two groups based on the retrospective self-reports on whether or not they utilized encoding strategies during the PALT. The behavioral results revealed better associative memory performance in the participants who reported utilizing memory strategies compared with participants who reported not doing so. The fMRI results showed that higher associative memory performance was associated with greater functional connectivity between the right superior frontal gyrus and the right posterior cerebellum lobe in the strategy group. The regional ALFF values in the right superior frontal gyrus were linked to associative memory performance in the no-strategy group. These findings suggest that the regional spontaneous fluctuations and functional connectivity during rest may subserve the individual differences in the associative memory in older adults, and that this is modulated by self-initiated memory strategy use.
Environmental Risk Factors for Acute Leukemia and Non-Hodgkin Lymphoma in Children

1Department of Occupational Medicine, Hematology, Oncology and Genetics Research Center, Shahid Sadoughi University of Medical Sciences and Health Services, Yazd, Iran 2Department of Pediatrics, Hematology, Oncology and Genetics Research Center, Shahid Sadoughi University of Medical Sciences and Health Services, Yazd, Iran 3General Practitioner, Yazd, Iran 4MSc Nursing 5Hematology, Oncology and Genetics Research Center, Shahid Sadoughi University of Medical Sciences and Health Services, Yazd, Iran
Polyamine Metabolism and Oxidative Protein Folding in the ER as ROS-Producing Systems Neglected in Virology

Reactive oxygen species (ROS) are produced in various cell compartments by an array of enzymes and processes. An excess of ROS production can be hazardous for normal cell functioning, whereas at normal levels, ROS act as vital regulators of many signal transduction pathways and transcription factors. ROS production is affected by a wide range of viruses. However, to date, the impact of viral infections has been studied only in respect to selected ROS-generating enzymes. The role of several ROS-generating and -scavenging enzymes or cellular systems in viral infections has never been addressed. In this review, we focus on the roles of biogenic polyamines and oxidative protein folding in the endoplasmic reticulum (ER) and their interplay with viruses. Polyamines act as ROS scavengers, however, their catabolism is accompanied by H2O2 production. Hydrogen peroxide is also produced during oxidative protein folding, with ER oxidoreductin 1 (Ero1) being a major source of oxidative equivalents. In addition, Ero1 controls Ca2+ efflux from the ER in response to e.g., ER stress. Here, we briefly summarize the current knowledge on the physiological roles of biogenic polyamines and the role of Ero1 at the ER, and present available data on their interplay with viral infections.
Development of Protective Scheme against Collaborative Black Hole Attacks in Mobile Ad hoc Networks

Mobile Ad hoc Network (MANET) is a collection of nodes or communication devices that wish to communicate without any fixed infrastructure and predetermined organization of available links. The effort has been made by proposing a scheme to overcome the critical security issue in MANET. The insufficiency of security considerations in the design of Ad hoc On-Demand Distance Vector protocol makes it vulnerable to the threats of collaborative black hole attacks, where hacker nodes attack the data packets and drop them instead of forwarding. To secure mobile ad hoc networks from collaborative black hole attacks, we implement our scheme and considered sensor's energy as a key feature with a better packet delivery ratio, less delay time and high throughput. The proposed scheme has offered an improved solution to diminish collaborative black hole attacks with high performance and benchmark results as compared to the existing schemes EDRIAODV and DRIAODV respectively. This paper has shown that throughput and packet delivery ratio increase while the end to end delay decreases as compared to existing schemes. It also reduces the overall energy consumption and network traffic by maintaining accuracy and high detection rate which is more safe and reliable for future work.
On the nature of the verb in present day English (existential) there-constructions. Formal and communicative implications

There is general agreement that be is the verb "par excellence" in so-called English existential there-constructions (existential TCs). In fact, on many occasions, a distinction is made between existential TCs -be TCs- and presentational TCs (non-be TCs). It is true, however, that other verbs may also occur in TCs. These are mainly intransitive verbs that express the ideas of permanence, being, existence, movement, position, entrance into the scene of discourse, arrival or continuation of an event (seem, come, remain, follow, develop, etc.). From a corpus-driven perspective, the proportion of non-be TCs in Present Day English (PDE) is analysed, granting special attention to their communicative value. It is hypothesised that even though, strictly speaking, non-be TCs do not primarily express existence, they do share with be TCs their main pragmatic function -i.e. signal function- a trait genuinely linked to the use of there. It is also examined whether any significant difference is observed between the use of non-be TCs in speech and writing, and what is the rationale for this difference (if any).
Role of Microenvironment in Glioma Invasion: What We Learned from In Vitro Models

The invasion properties of glioblastoma hamper a radical surgery and are responsible for its recurrence. Understanding the invasion mechanisms is thus critical to devise new therapeutic strategies. Therefore, the creation of in vitro models that enable these mechanisms to be studied represents a crucial step. Since in vitro models represent an over-simplification of the in vivo system, in these years it has been attempted to increase the level of complexity of in vitro assays to create models that could better mimic the behaviour of the cells in vivo. These levels of complexity involved: 1. The dimension of the system, moving from two-dimensional to three-dimensional models; 2. The use of microfluidic systems; 3. The use of mixed cultures of tumour cells and cells of the tumour micro-environment in order to mimic the complex cross-talk between tumour cells and their micro-environment; 4. And the source of cells used in an attempt to move from commercial lines to patient-based models. In this review, we will summarize the evidence obtained exploring these different levels of complexity and highlighting advantages and limitations of each system used.
Deformable boundary detection of stents in angiographic images

A procedure is described for deformable boundary detection of medical tools, called stents, in angiographic images. A stent is a surgical stainless steel coil that is placed in the artery in order to improve blood circulation in regions where a stenosis has appeared. Assuming initially a set of three-dimensional (3-D) models of stents and using perspective projection of various deformations of the 3-D model of the stent, a large set of synthetic two-dimensional (2-D) images of stents is constructed. These synthetic images are then used as a training set for deriving a multivariate Gaussian density estimate based on eigenspace decomposition and formulating a maximum-likelihood estimation framework in order to reach an initial rough estimate for automatic object recognition. The silhouette of the detected stent is then refined by using a 2-D active contour (snake) algorithm integrated with a novel iterative initialization technique, which takes into consideration the geometry of the stent. The algorithm is experimentally evaluated using real angiographic images containing stents.
Basal ganglia functional connectivity in combat-related PTSD

Introduction Posttraumatic stress disorder (PTSD) is an anxiety disorder that can develop following traumatic experience. PTSD symptoms are characterized by re-experiencing of traumatic memory, hyper-arousal, avoidance and emotional numbing [1]. Blood oxygenation level dependent functional MRI (BOLD-fMRI), is helpful in revealing PTSD associated neuropathology [2]; however, previous studies have been focused on the responsivity patterns of a few regions such as the amygdala and hippocampus, not much attention has been paid to other important regions and the functional connectivity in the brain. The present study aims to investigate the functional connectivity with the basal ganglia. Basal ganglia are a group of nuclei suited at the base of the forebrain with intensive connections with the cerebral cortex. They are involved in many functions such as voluntary motor control, action selection [3], procedural learning, as well as related cognitive and emotional processing. This important structure has not been paid much attention in the PTSD literature; however, potentially the basal ganglia may play important roles in the intrusive traumatic memory recollection and emotion dysregulation in PTSD patients.
Abusive supervision, leader-member exchange, and moral disengagement: A moderated-mediation model of organizational deviance

ABSTRACT This paper draws from social exchange theory and social cognitive theory to explore moral disengagement as a potential mediator of the relationship between abusive supervision and organizational deviance. We also explore the moderating effect of leader-member exchange (LMX) on this mediated relationship. Results indicate that employees with abusive supervisors engaged in moral disengagement strategies and subsequently in organizational deviance behaviors. Additionally, this relationship was stronger for those higher in LMX. Important implications for management research and practice are discussed.
Improving Spark performance with zero-copy buffer management and RDMA

With the ever increasing demand on interactive data analytics, latency for big data frameworks becomes more important. We present our preliminary experience designing and implementing NetSpark, an improved Spark [1] framework that is highly optimized for network latency. Combining optimizations on data serialization, network buffer management with hardware-supported Remote Direct Memory Access (RDMA) technology, we show that we can eliminate most of the data copies from end to end, significantly reducing the Spark task running time. Our preliminary experiments show that NetSpark improves GroupBy operation in Spark by about 40% and the PageRank algorithm in GraphX by about 20% on a 10Gbps data center network over the legacy network stack.
Robots with Display Screens: A Robot with a More Humanlike Face Display Is Perceived To Have More Mind and a Better Personality

It is important for robot designers to know how to make robots that interact effectively with humans. One key dimension is robot appearance and in particular how humanlike the robot should be. Uncanny Valley theory suggests that robots look uncanny when their appearance approaches, but is not absolutely, human. An underlying mechanism may be that appearance affects users’ perceptions of the robot’s personality and mind. This study aimed to investigate how robot facial appearance affected perceptions of the robot’s mind, personality and eeriness. A repeated measures experiment was conducted. 30 participants (14 females and 16 males, mean age 22.5 years) interacted with a Peoplebot healthcare robot under three conditions in a randomized order: the robot had either a humanlike face, silver face, or no-face on its display screen. Each time, the robot assisted the participant to take his/her blood pressure. Participants rated the robot’s mind, personality, and eeriness in each condition. The robot with the humanlike face display was most preferred, rated as having most mind, being most humanlike, alive, sociable and amiable. The robot with the silver face display was least preferred, rated most eerie, moderate in mind, humanlikeness and amiability. The robot with the no-face display was rated least sociable and amiable. There was no difference in blood pressure readings between the robots with different face displays. Higher ratings of eeriness were related to impressions of the robot with the humanlike face display being less amiable, less sociable and less trustworthy. These results suggest that the more humanlike a healthcare robot’s face display is, the more people attribute mind and positive personality characteristics to it. Eeriness was related to negative impressions of the robot’s personality. Designers should be aware that the face on a robot’s display screen can affect both the perceived mind and personality of the robot.
Rapid and Reusable Text Visualization and Exploration Development with DELVE

We present DELVE (Document ExpLoration and Visualization Engine), a framework for developing interactive visualizations as modular Web-applications to assist researchers with exploratory literature search. The goal for web-applications driven by DELVE is to better satisfy the information needs of researchers and to help explore and understand the state of research in scientific liter ature by providing immersive visualizations that both contain facets and are driven by facets derived from the literature. We base our framework on principles from user-centered design and human-computer interaction (HCI). Preliminary evaluations demon strate the usefulness of DELVE’s techniques: (1) a clinical researcher immediately saw that her original query was inappropriate simply due to the frequencies displayed via generalized clouds and (2) a muscle biologist quickly learned of vocabulary differences found between two disciplines that were referencing the same idea, which we feel is critical for interdisciplinary work. We dis cuss the underlying category-theoretic model of our framework and show that it naturally encourages the development of reusable visualizations by emphasizing interoperability.
Evaluation of aqueous methanolic extract of Sorghum bicolor leaf base for antinociceptive and anti- inflammatory activities

Sorghum bicolor (Family: Gramineae; Poaceae) is used traditionally for some ailments related to pain and inflammation . This study was therefore aimed at investigating possible antinociceptive and antiinflammatory effects of this plant. The aqueous methanolic (70% methanol ) extract of the leaf base, its aqueous and ethylacetate fractions were evaluated for antinociceptive activity using acetic acidinduced writhing test (test on chemical pain) and tail flick test (test on mechanical pain) in Swiss albino mice. The site for antinociception was determined using formalin test in Wistar rats. Anti-inflammatory activity was evaluated using egg albumin-induced hind paw oedema in Wistar rats. Acute toxicity studies of all the extracts were also carried out on rats and mice to determine their LD 50 . The aqueous methanolic extract and its aqueous fraction exhibited a significant (P < 0.05) antinociceptive activity while the ethylacetate fraction did not show antinociceptive effect. The aqueous methanolic extract showed higher percent pain inhibition in the early phase of formalin test but did not inhibit inflammation. The calculated oral LD 50 value for the aqueous methanolic extract was ≥ 2000 mg/kg in both mice and rats. In rats, the calculated intraperitoneal LD 50 value 48 h post treatment observation was 1,414.2 mg/kg while in mice, the calculated intraperitoneal LD 50 value was 1341.6 mg/kg for 48 h post treatment time. The intraperitoneal LD 50 value for both aqueous and ethylacetate fractions were ≥ 2000 mg/kg 48 h post treatment. The study revealed that S. bicolor leaf base contains analgesic components which are probably more in the aqueous fraction of the crude extract. This effect appeared centrally mediated. The extract did not show anti-inflammatory property.
Indications and technique for laparoscopic liver resection in patients with hepatocellular carcinoma and liver cirrhosis

Liver resection is the preferable initial treatment option for solitary or limited multifocal HCCs with no extrahepatic spread. [2-6] The mortality and morbidity of liver resection have significantly decreased in the last two decades because of improvements in patient evaluation, surgical technique, and perioperative care. Resection is the ideal treatment, as it allows for complete removal and pathological confirmation of lesions. However, it is more invasive than other locoregional therapies such as transarterial chemoembolization, tumor ablative therapy, and radiation therapy. [7-10]
Perfect and ε-perfect simulation methods for the one-dimensional Kac equation

Abstract We review the derivation of the Kac master equation model for random collisions of particles, its relationship to the Poisson process, and existing algorithms for simulating values from the marginal distribution of velocity for a single particle at any given time. We describe and implement a new algorithm that efficiently and more fully leverages properties of the Poisson process, show that it performs at least as well as existing methods, and give empirical evidence that it may perform better at capturing the tails of the single particle velocity distribution. Finally, we derive and implement a novel “ε-perfect sampling” algorithm for the limiting marginal distribution as time goes to infinity. In this case the importance is a proof of concept that has the potential to be expanded to more interesting (DSMC) direct simulation Monte Carlo applications.