Miracle-dz/UniFAR-FTUs huggingface dataset:
Involvement of the Basal Ganglia and Cerebellar Motor Pathways in the Preparation of Self-Initiated and Externally Triggered Movements in Humans

The subthalamic nucleus (STN) is part of the cortico-basal ganglia (BG)–thalamocortical circuit, whereas the ventral lateral nucleus of the thalamus (VL) is a relay nucleus in the cerebello-dentato-thalamocortical (CTC) pathway. Both pathways have been implicated in movement preparation. We compared the involvement of the STN and VL in movement preparation in humans by recording local field potentials (LFPs) from seven patients with Parkinson's disease with deep-brain stimulation (DBS) electrodes in the STN and five patients with tremor and electrodes in VL. LFPs were recorded from DBS electrodes and scalp electrodes simultaneously while the patients performed self-paced and externally cued (ready, go/no-go) movements. For the self-paced movement, a premovement-related potential was observed in all patients from scalp, STN (phase reversal, five of six patients), and VL (phase reversal, five of five patients) electrodes. The onset times of the potentials were similar in the cortex, STN, and VL, ranging from 1.5 to 2 s before electromyogram onset. For the externally cued movement, an expectancy potential was observed in all patients in cortical and STN electrodes (phase reversal, six of six patients). The expectancy potential was recorded from the thalamic electrodes in four of five patients. However, phase reversal occurred only in one case, and magnetic resonance imaging showed that this contact was outside the VL. The cortico-BG–thalamocortical circuit is involved in the preparation of both self-paced and externally cued movements. The CTC pathway is involved in the preparation of self-paced but not externally cued movements, although the pathway may still be involved in the execution of these movements.
Spatial Disparities in Emotional Responses to Education : Feelings of ‘ Guilt ’ amongst Student-Parents

This article explores the emotional responses to higher education of students with dependent children, and draws on 68 in-depth interviews conducted with student-parents in universities in the UK and Denmark. By focussing on one specific emotion – guilt – it contends that emotions are important in helping to understand the way in which particular groups of students engage with education, and the barriers they often face. Moreover, by considering four different higher education contexts (across two European nations), it suggests that emotional responses are spatially differentiated, and mediated by national policies and norms as well as the social characteristics of students.
MOPF : A Multi-Objective Planning Framework for Generation of Pareto-Optimal Plan Frontiers using Satisficing Planners

Current planners focus on finding a single solution to a given problem. The decision maker (DM) has a choice of either finding the solution fast using a satisficing planner or finding a high quality solution using an optimal planner. The quality of the solution is evaluated in terms of a metric function given by the DM. That forces the DM to specify preferences in terms of a single metric function which in many real life problems is hard. This work is based on the need to relax this constraint and to allow the planning process to be carried out without the need to specify the single metric function. A single plan is sufficient when minimising a single objective function, however, it is very unlikely that a single solution would minimize multiple objective functions at the same time. The solution for a problem with multiple metric functions is no longer a single plan but a set of plans which represents the trade-off between different objectives. Satisficing planners are doing remarkably well in finding solutions to planning problems efficiently. Although they are not optimal, the speed with which they find a solution makes them very valuable. We explore how we can use them to quickly find solutions in various areas of the search space, which combined together give a high quality solutions set. In multi objective optimisation we can divide the interaction with the DM into three main categories [Horn, 1997]. First, when DM can articulate its preferences before planning, we can construct an aggregated function of all preferences knowing weights between them. The second category is an interactive articulation of preferences by the DM, this approach is least common and appears when the DM helps to guide the search, keeping in mind that his preferences might change with time. The last category is aposteriori articulation of preferences, where the task for the system is to present a good choice of alternative solutions. The last category has received a lot of attention in OR, however, in planning this area is not well explored and this research aims to fill this gap. In this paper we present a Multi-Objective Planning Framework (MOPF) which is capable of generating sets of qualitatively good plans. A method to evaluate pareto-frontier (PF) of plans is introduced and used to evaluate the planning system. We start by giving a background to this research. Following that we introduce MOPF which works on problems with multiple metrics. In the final sections we present evaluation of this system, solution it generates and discussion of some multi-objective domains.
Code Size reduction by difference classification and customized look-up table generation

Code size has become an important constraint for applications on mobile devices. Not only should the applications be very responsive and execute fast, they should also consume low power, and be reasonably compact in size to fit in the limited memory of the mobile devices. In this paper we focus on a specific opportunity of code size optimization that is detected in software for mobile devices like wireless networking protocols, modems, etc. These applications have large amount of code-regions across the control-flow graph that are inherently similar, but with slight differences that are compile time constants. Examples of such similar code regions are: case statements labeled by “jump tables”, tail regions that merge to a common point, cascaded sequence of similar code-regions with unique predecessor-successor relationship, etc. This paper presents a novel approach where similar code-regions across the control flow graph are classified into disjoint sets based on their differences, and then replaced by a single representative code-region with the differences encoded in customized look-up tables resulting in reduced code size. The methodology shows remarkable reduction in code size for large switch-case constructs that have very similar case statements. Implementation is done in the Open64 compiler, even though it could be integrated with other compilers (e.g., GCC). We also provide some results of code size reduction, which are in the range of 30% to 80% for pure text (instructions only), and 5% to 60% for total text (instructions and read only data), achieved by the algorithm on some of the functions in software applications for mobile
Growth Hormone/Insulin-Like Growth Factor-1 Axis as Related to Body Mass Index in Patients with Idiopathic Short Stature

Objective: Idiopathic short stature (ISS) is a heterogeneous disorder. An impairment of growth hormone (GH)/insulin-like growth factor 1 (IGF-1)/IGF-1 receptor (IGF-1 R) axis is postulated. To evaluate the somatotropic axis in relation to body mass index (BMI), serum IGF-1, IGF-binding protein-3 (IGFBP-3) and the expression of IGF-1 R genes in patients with ISS. Methods: Fifty-five ISS patients (24F/31M) aged 14.6±5.5 years (range 3.5-28.5 years) and 25 BMI- and pubertal stage-matched peers were enrolled in the study. The ISS patients underwent a four-day standard GH stimulation test to evaluate IGF-1 generation. mRNA expression of the IGF-1 R gene in peripheral blood leukocytes was evaluated. ISS patients and controls were compared with respect to anthropometric and laboratory data. The results were also analyzed after subdividing the two groups into low-normal [BMI standard deviation score (SDS) between -2 to -1)] and normal (BMI SDS between -1 to +1) BMI subgroups. Results: Basal serum IGF-1 concentrations were lower in ISS subjects compared to controls who had similar BMI SDS values (p=0.000). Subgroup analyses revealed that there were no significant differences between low-normal BMI ISS subjects and low-normal BMI controls with respect to serum IGF-1 and IGFBP-3 concentrations. However, in the normal BMI ISS subgroup, basal and stimulated IGF-1 levels were significantly lower than the basal values in their control counterparts (basal: p=0.000; stimulated: p=0.007). mRNA expression of IGF-1 R gene was not found to be significantly different in ISS subjects and controls. Conclusions: ISS patients were found to have lower IGF-1 concentrations than BMI-matched peers, a finding supporting presence of an impairment in the somatotropic axis. IGF-1 R expression does not seem to be impaired in ISS patients. ISS patients with low-normal BMI SDS also tend to display a relative IGF-1 resistance, whereas those with normal BMI SDS tend to be less GH-sensitive than healthy peers. Conflict of interest:None declared.
Networked Robots : from Telerobotics to Cloud Robotics

As of 2013, almost all robots have access to computer networks that offer extensive computing, memory, and other resources that can dramatically improve performance. The underlying enabling framework is the focus of this chapter: networked robots. Networked robots trace their origin to telerobots, or remotely controlled robots. Telerobots are widely used to explore undersea terrains and outer space, to defuse bombs, and to clean up hazardous waste. Until 1994, telerobots were accessible only to trained and trusted experts through dedicated communication channels. This chapter will describe relevant network technology, the history of networked robots as it evolves from teleoperation to cloud robotics, properties of networked robots, how to build a networked robot, example systems. Later in the chapter we focus on the recent progress on cloud robotics, and topics for future research.
Unsupervised Compound Splitting With Distributional Semantics Rivals Supervised Methods

In this paper we present a word decom-pounding method that is based on distributional semantics. Our method does not require any linguistic knowledge and is initialized using a large monolingual corpus. The core idea of our approach is that parts of compounds (like “candle” and “stick”) are semantically similar to the entire compound, which helps to exclude spurious splits (like “candles” and “tick”). We report results for German and Dutch: For German, our unsupervised method comes on par with the performance of a rule-based and a supervised method and sig-niﬁcantly outperforms two unsupervised base-lines. For Dutch, our method performs only slightly below a rule-based optimized compound splitter.
Challenge Paper: Marginal Probabilities for Instances and Classes (Poster Presentation SRL Workshop)

In classic AI research on combining logic and probability, Halpern introduced an inference principle for marginal probabilities of ground atoms: If the corresponding population frequency is known, the marginal probability should be equal to it. For instance, if the only thing we know about Tweety is that Tweety is a bird, then the probability that Tweety flies should be the frequency of flyers in the class of birds. We provide several arguments for why a statistical-relational inference system should satisfy Halpern’s principle. If the principle is accepted, the technical challenge is then to construct inference models to meet this specification. The technical part of the paper gives examples of structures and parameterizations that do and do not satisfy the constraint on marginal probabilities, using Parametrized Bayes nets.
In‐situ Sampling of a Large‐Scale Particle Simulation for Interactive Visualization and Analysis

We describe a simulation‐time random sampling of a large‐scale particle simulation, the RoadRunner Universe MC3 cosmological simulation, for interactive post‐analysis and visualization. Simulation data generation rates will continue to be far greater than storage bandwidth rates by many orders of magnitude. This implies that only a very small fraction of data generated by a simulation can ever be stored and subsequently post‐analyzed. The limiting factors in this situation are similar to the problem in many population surveys: there aren't enough human resources to query a large population. To cope with the lack of resources, statistical sampling techniques are used to create a representative data set of a large population. Following this analogy, we propose to store a simulation‐time random sampling of the particle data for post‐analysis, with level‐of‐detail organization, to cope with the bottlenecks. A sample is stored directly from the simulation in a level‐of‐detail format for post‐visualization and analysis, which amortizes the cost of post‐processing and reduces workflow time. Additionally by sampling during the simulation, we are able to analyze the entire particle population to record full population statistics and quantify sample error.
Promoter Methylation and mRNA Expression of Response Gene to Complement 32 in Breast Carcinoma

Background. Response gene to complement 32 (RGC32), induced by activation of complements, has been characterized as a cell cycle regulator; however, its role in carcinogenesis is still controversial. In the present study we compared RGC32 promoter methylation patterns and mRNA expression in breast cancerous tissues and adjacent normal tissues. Materials and Methods. Sixty-three breast cancer tissues and 63 adjacent nonneoplastic tissues were included in our study. Design. Nested methylation-specific polymerase chain reaction (Nested-MSP) and quantitative PCR (qPCR) were used to determine RGC32 promoter methylation status and its mRNA expression levels, respectively. Results. RGC32 methylation pattern was not different between breast cancerous tissue and adjacent nonneoplastic tissue (OR = 2.30, 95% CI = 0.95–5.54). However, qPCR analysis displayed higher levels of RGC32 mRNA in breast cancerous tissues than in noncancerous tissues (1.073 versus 0.959; P = 0.001), irrespective of the promoter methylation status. The expression levels and promoter methylation of RGC32 were not correlated with any of patients' clinical characteristics (P > 0.05). Conclusion. Our findings confirmed upregulation of RGC32 in breast cancerous tumors, but it was not associated with promoter methylation patterns.
Increased frequency of migraine among women with endometriosis.

BACKGROUND Our aim is to assess the prevalence and characteristics of headache in patients with endometriosis compared with women without this disease. METHODS One hundred and thirty-three women with histologically proven endometriosis and 166 controls were interviewed by a neurologist experienced in headache diagnosis; the headache disorders were classified according to the 1988 International Headache Society criteria. RESULTS The prevalence of migraine was significantly higher among women with endometriosis [n = 51, 38.3%; 95% confidence interval (CI) 30.1-47.2%] than in controls (n = 25, 15.1%; 95% CI 10.0-21.4%) (P < 0.001). Migraine with aura was observed in 18 women with endometriosis (13.5%) and in two controls (1.2%; P < 0.001). The age at migraine onset was significantly lower in women with endometriosis than in controls (16.4 versus 21.9 years; P = 0.001). No significant difference was observed in pain intensity and attack frequency between the two groups; a trend for women with endometriosis to have longer unmedicated attacks was observed. No significant correlation was observed between attack frequency, unmedicated headache duration, migraine intensity and the severity of endometriosis. CONCLUSION Migraine is more frequent in women with endometriosis than in controls, although its presence and characteristics are not related to the severity of endometriosis.
Hierarchical Markov Fields and Fuzzy Image Segmentation

This paper deals with fuzzy statistical image segmentation. We introduce a new hierarchical Markovian fuzzy hidden field model, which extends to the fuzzy case the classical Perez and Heitz hard model. Two fuzzy statistical segmentation methods related with the model proposed are defined in this paper and we show via simulations that they are competitive with, in some cases than, the classical Maximum Posterior Mode (MPM) based methods. Furthermore, they are faster, which will should facilitate extensions to more than two hard classes in future work. In addition, the model proposed is applicable to the multiscale segmentation and multiresolution images fusion problems.
Substrate-induced Nuclear Export and Peripheral Compartmentalization of Hepatic Glucokinase Correlates with Glycogen Deposition

Hepatic glucokinase (GK) is acutely regulated by binding to its nuclear-anchored regulatory protein (GKRP). Although GK release by GKRP is tightly coupled to the rate of glycogen synthesis, the nature of this association is obscure. To gain insight into this coupling mechanism under physiological stimulating conditions in primary rat hepatocytes, we analyzed the subcellular distribution of GK and GKRP with immunofluorescence, and glycogen deposition with glycogen cytochemical fluorescence, using confocal microscopyand quantitative image analysis. Following stimulation, a fraction of the GK signal translocated from the nucleus to the cytoplasm. The reduction in the nuclear to cytoplasmic ratio of GK, an index of nuclear export, correlated with a >50% increase in glycogen cytochemical fluorescence over a 60min stimulation period. Furthermore, glycogen accumulation was initially deposited in a peripheral pattern in hepatocytes similar to that of GK. These data suggest that a compartmentalization exists of both active GK and the initial sites of glycogen deposition at the hepatocyte surface.
Inflammation Recapitulates the Ontogeny of Lymphoid Stromal Cells1

Stromal cells in lymphoid tissues regulate lymphocyte recruitment and survival through the expression of specific chemokines and cytokines. During inflammation, the same signals recruit lymphocytes to the site of injury; however, the “lymphoid” stromal (LS) cells producing these signals remain poorly characterized. We find that mouse inflammatory lesions and tumors develop gp38+ LS cells, in recapitulation of the development of LS cells early during the ontogeny of lymphoid organs and the intestine, and express a set of genes that promotes the development of lymphocyte-permissive tissues. These gp38+ LS cells are induced by a robust pathway that requires myeloid cells but not known Toll- or NOD-like receptors, the inflammasome, or adaptive immunity. Parabiosis and inducible genetic cell fate mapping experiments indicate that local precursors, presumably resident fibroblasts rather that circulating precursors, massively proliferate and give rise to LS cells during inflammation. Our results show that LS cells are both programmed during ontogeny and reinduced during inflammation.
A Whole-Body Physiologically Based Pharmacokinetic Model of Gefitinib in Mice and Scale-Up to Humans

Gefitinib (Iressa) is a selective and potent EGFR tyrosine kinase inhibitor. It received an accelerated FDA approval in 2003 for the treatment of patients with nonsmall cell lung cancer (NSCLC) and represents the first-line therapy for NSCLC with EGFR mutations. In the work presented herein, the disposition of gefitinib was investigated extensively in mouse in both plasma and 11 organs (liver, heart, lung, spleen, gut, brain, skin, fat, eye, kidney, and muscle) after a single IV dose of 20 mg/kg. Gefitinib demonstrated extensive distribution in most tissues, except for the brain, and tissue to plasma partition coefficients (Kpt) ranged from 0.71 (brain) to 40.5 (liver). A comprehensive whole-body physiologically based pharmacokinetic (PBPK) model of gefitinib in mice was developed, which adequately captured gefitinib concentration-time profiles in plasma and various tissues. Predicted plasma and tissue AUC values agreed well with the values calculated using the noncompartmental analysis (<25% difference). The PBPK model was further extrapolated to humans after taking into account the interspecies differences in physiological parameters. The simulated concentrations in human plasma were in line with the observed concentrations in healthy volunteers and patients with solid malignant tumors after both IV infusion and oral administration. Considering the extensive tissue distribution of gefitinib, plasma concentration may not be an ideal surrogate marker for gefitinib exposure at the target site or organ of toxicity (such as the skin). Since our whole-body PBPK model can predict gefitinib concentrations not only in plasma but also in various organs, our model may have clinical applications in efficacy and safety assessment of gefitinib.
1001 Ways To Implement Kђѐѐюј

The structure of Kђѐѐюј allows a fair amount of diversity in the way it can be implemented. However, it is oĞen not trivial to select the optimal options in given circumstances, and sometimes one may even not be aware of all of Kђѐѐюј’s implementation techniques. We here briefly present different techniques, referring to external documents for the details. Kђѐѐюј defines a family of sponge functions with seven different permutations and most implementation techniques work on all of them. For clarity, however, we take as example Kђѐѐюјf [1600], the permutation used in the proposed SHA-3 hash function candidates [5].
An Improved Combined Component Aggregated HARQ A/N

In this paper, we mainly introduce several A/N bundling schemes in LTE-Advanced for carrier aggregation, also we propose a novel A/N bundling scheme based on the Combined Component Aggregated HARQ A/N (the CoCoAH) [1] [2] [3], this is the improved Combined Component Aggregated HARQ A/N (the improved CoCoAH). Compared with CoCoAH, the improved CoCoAH reduces the unnecessary retransmission of correctly received code words caused by bundling, while these two kinds of ways use the same number of A/N bit. The simulation results demonstrate that the improved CoCoAH is more reliable than CoCoAH when A/N bits pass through the channel.
Improving El Niño Forecasting: The Potential Economic Benefits

For an improved ENSO forecast to have value, two conditions must be met. First, economic wealth or income must be affected by the weather, and second, it must be possible to make better economic decisions when a reliable ENSO forecast is available. This paper presents a brief discussion of a number of areas where these two conditions may be met. Of these, agricultural production may be the most important. Other areas where an improved forecast may have significant value are prevention of storm damage, natural gas storage, and management of hydroelectric facilities.
Convolution Kernels on Constituent, Dependency and Sequential Structures for Relation Extraction

This paper explores the use of innovative kernels based on syntactic and semantic structures for a target relation extraction task. Syntax is derived from constituent and dependency parse trees whereas semantics concerns to entity types and lexical sequences. We investigate the effectiveness of such representations in the automated relation extraction from texts. We process the above data by means of Support Vector Machines along with the syntactic tree, the partial tree and the word sequence kernels. Our study on the ACE 2004 corpus illustrates that the combination of the above kernels achieves high effectiveness and significantly improves the current state-of-the-art.