Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Neuronal Cells in the Hypothalamic Adaptation to Metabolic Signals

Although the brain is composed of numerous cell types, neurons have received the vast majority of attention in the attempt to understand how this organ functions. Neurons are indeed fundamental but, in order for them to function correctly, they rely on the surrounding “non-neuronal” cells. These different cell types, which include glia, epithelial cells, pericytes, and endothelia, supply essential substances to neurons, in addition to protecting them from dangerous substances and situations. Moreover, it is now clear that non-neuronal cells can also actively participate in determining neuronal signaling outcomes. Due to the increasing problem of obesity in industrialized countries, investigation of the central control of energy balance has greatly increased in attempts to identify new therapeutic targets. This has led to interesting advances in our understanding of how appetite and systemic metabolism are modulated by non-neuronal cells. For example, not only are nutrients and hormones transported into the brain by non-neuronal cells, but these cells can also metabolize these metabolic factors, thus modifying the signals reaching the neurons. The hypothalamus is the main integrating center of incoming metabolic and hormonal signals and interprets this information in order to control appetite and systemic metabolism. Hence, the factors transported and released from surrounding non-neuronal cells will undoubtedly influence metabolic homeostasis. This review focuses on what is known to date regarding the involvement of different cell types in the transport and metabolism of nutrients and hormones in the hypothalamus. The possible involvement of non-neuronal cells, in particular glial cells, in physiopathological outcomes of poor dietary habits and excess weight gain are also discussed.
Comparisons of automated blood pressures in a primary health care setting with self-measurements at the office and at home using the Omron i-C10 device

ObjectiveWe aimed to compare blood pressure (BP) levels recorded using the semiautomatic oscillometric Omron i-C10 BP device in patients with or without hypertension in three different settings: (a) when used by a doctor or a nurse at the office (OBP); (b) when used for self-measurement by the patient at the office (SMOBP); and (c) when used for 7 consecutive days at home (HBP). Materials and methodsA total of 247 individuals were invited to participate, but 78 of these individuals declined and a further seven were excluded, leaving a final cohort of 162 participants. ResultsThe mean OBP was higher than HBP (difference 8.1±14/3.1±8.8 mmHg, P<0.0001) and so was SMOBP compared with HBP (difference 7.0±13/4.2±7.3 mmHg, P<0.0001). Sixteen participants (9.9%) had at least 10 mmHg higher systolic SMOBP than OBP and 28 (17%) participants had at least 10 mmHg lower systolic SMOBP than OBP. Participants who were current smokers had a larger mean difference between systolic OBP and SMOBP than nonsmokers (OBP−SMOBP in smokers: 6.6±9.4 mmHg, OBP−SMOBP in nonsmokers: 0.5±9.2 mmHg, P=0.011 between groups). ConclusionSelf-measurement of BP in the office does not preclude an increase in BP when levels in the individual patients are compared with HBP using the same equipment. Thus, SMOBP with a semiautomatic device does not lead to a reduction in the white-coat effect in the same manner as fully automatic devices.
Growing Surface Structures

The thesis presents a surface reconstruction approach based on an iterative refinement strategy deduced from artificial neural networks. The presented approach is composed of three novel developments extending the capabilities as well as the concept of the Growing Cell Structures algorithm. The algorithm is evaluated both in a comparison to classical reconstruction algorithms and in reconstructing extremely challenging point clouds. The algorithm proves to be an efficient all-round high quality approach.
Zhang Et Al.: Online Service Switching Behavior Online Service Switching Behavior: the Case of Blog Service Providers

In recent years, there have been a growing number of online social platforms which allow users to publish and share their personal stories, opinions, knowledge, expertise, and product reviews. Online service switching has become a major challenge for marketers. In this study, we attempt to understand online service switching behavior through investigating blog service switching. We use the push-pull-mooring migration framework to guide our investigation. We empirically examine three salient factors for online service switching in general. Further, we analyze survey responses to elicit specific push, pull, and mooring factors pertaining to the switching of blog service providers. The findings suggest that satisfaction, attractive alternatives, and sunk costs can significantly affect bloggers' switching intention. Dissatisfaction with service stability, attractiveness in functionality, attractiveness in ease of use, and descriptive norms are found to be the most frequently cited reasons for bloggers' switching behavior. We believe that online service providers can benefit from the findings of this research regarding how to maintain current users and attract new users. The present study extends prior research on consumer service switching by examining switching behavior in the online service context. We find that the push-pull-mooring migration framework is an effective tool in identifying factors affecting blog service switching behavior. 1. Introduction Consumer service switching remains an important research area in the relationship marketing literature [Chiu et al. 2005]. In the last two decades, we have witnessed a significant number of studies examining the impact of consumer switching behavior [e.g., nt n et al. Prior research indicates that switching behavior generates negative impacts on market share and profitability of firms [Rust & Zahorik 1993]. Researchers also find that consumers with long-term relationships bring significant value to firms, such as positive word-of-mouth engagement [Dick & Basu 1994], high service usage [Bolton & Lemon 1999], and high propensity to respond to new promotions [Hawkins et al. 2004]. Some researchers postulate that consumers' service switching behavior poses a serious threat to long-term relationships [Ganesh et al. 2000]. Therefore, it is critical to understand why consumers decide to switch to other service providers. In recent years, there have been a growing number of online social platforms where users can publish and share their personal stories, opinions, knowledge, expertise, and product reviews [Qi 2011; Ye et al. 2012]. These online service providers are also facing the same challenge of keeping their users and preventing them from switching to other platforms [Luarn …
Avoidance of Priority Inversion in Real Time Systems Based on Resource Restoration

Priority inversion is a problem that occurs in concurrent processes when low-priority threads hold shared resources required by some high-priority threads, causing the high priority-threads to block indefinitely. This problem is enlarged when the concurrent processes are in a real time system where high- priority threads must be served on time. A novice approach for avoiding the priority inversion problem is presented for processes in real time systems. This approach is based on backing up and restoring the shared resources. A low priority thread always starts on a shadow version of the shared resource, the original resource remains unchanged. When a high-priority thread needs a resource engaged by a low-priority thread, the low priority thread is preempted, the original resource is restored and the high-priority thread is allowed to use the original resource. The approach has been implemented in Java and the experimental results are fetched which verify that the approach is very suitable for real time systems where high-priority threads must be served on time.
An arithmetic library and its application to the N-body problem

Computer arithmetic is a specialist field of study, and it is very difficult for designers to choose the most efficient method for implementing a given algorithm due to the large number of design choices available. In this paper, an object oriented arithmetic library is presented which can be used to simulate and generate designs which use fixed, floating, logarithmic and hybrid number representations. The advantages of this approach are that a user can explore tradeoffs concerning precision, accuracy and speed from single high level description. Furthermore, users need not be intimately familiar with the implementation details of the underlying libraries, thus allowing users to develop systems employing advanced computer arithmetic without detailed knowledge of its implementation. The application of this library to a coprocessor which implements the force pipeline for an N-body solver is described.
Walk 'n' Merge: A Scalable Algorithm for Boolean Tensor Factorization

Tensors are becoming increasingly common in data mining, and consequently, tensor factorizations are becoming more important tools for data miners. When the data is binary, it is natural to ask if we can factorize it into binary factors while simultaneously making sure that the reconstructed tensor is still binary. Such factorizations, called Boolean tensor factorizations, can provide improved interpretability and find Boolean structure that is hard to express using normal factorizations. Unfortunately the algorithms for computing Boolean tensor factorizations do not usually scale well. In this paper we present a novel algorithm for finding Boolean CP and Tucker decompositions of large and sparse binary tensors. In our experimental evaluation we show that our algorithm can handle large tensors and accurately reconstructs the latent Boolean structure.
Dynamic Multicast Routing and Wavelength Assignment with Minimal Conversions in Delay-Constrained WDM Networks

This paper addresses the problem of dynamic multicast routing and wavelength assignment in delay constrained wavelength-routed WDM network. Current algorithms focus in minimizing blocking probability or wavelength numbers used, but not on the number of wavelength conversions. Wavelength conversions on either optical or electronics plane are costly and time consuming, hence should be minimized to ensure good transmission quality and manageable cost. In this paper, we proposed an algorithm on generic layered auxiliary graph to construct delay constrained dynamic multicast trees with minimal conversions and low blocking, and compared it with existing optimal algorithms through simulations. The results indicate that our proposed algorithm is able to achieve near optimal performance in terms of blocking, wavelength conversions and delays between source and members.
The Quest for Ground Truth in Musical Artist Similarity

would be interesting and valuable to devise an automatic measure of the similarity between two musicians based only on an analysis of their recordings. To develop such a measure, however, presupposes some 'ground truth' training data describing the actual similarity between certain pairs of artists that constitute the desired output of the measure. Since artist similarity is wholly subjective, such data is not easily obtained. In this paper, we describe several attempts to construct a full matrix of similarity measures between a set of some 400 popular artists by regularizing limited subjective judgment data. We also detail our attempts to evaluate these measures by comparison with direct subjective similarity judgments collected via a web- based survey in April 2002. Overall, we find that subjective artist similarities are quite variable between users—casting doubt on the concept of a single 'ground truth'. Our best measure, however, gives reasonable agreement with the subjective data, and forms a useable stand-in. In addition, our evaluation methodology may be useful for comparing other measures of artist similarity.
Computing Solutions in Infinite-Horizon Discounted Adversarial Patrolling Games

Stackelberg games form the core of a number of tools deployed for computing optimal patrolling strategies in adversarial domains, such as the US Federal Air Marshall Service and the US Coast Guard. In traditional Stackelberg security game models the attacker knows only the probability that each target is covered by the defender, but is oblivious to the detailed timing of the coverage schedule. In many real-world situations, however, the attacker can observe the current location of the defender and can exploit this knowledge to reason about the defender’s future moves. We show that this general modeling framework can be captured using adversarial patrolling games (APGs) in which the defender sequentially moves between targets, with moves constrained by a graph, while the attacker can observe the defender’s current location and his (stochastic) policy concerning future moves. We offer a very general model of infinite-horizon discounted adversarial patrolling games. Our first contribution is to show that defender policies that condition only on the previous defense move (i.e., Markov stationary policies) can be arbitrarily suboptimal for general APGs. We then offer a mixed-integer non-linear programming (MINLP) formulation for computing optimal randomized policies for the defender that can condition on history of bounded, but arbitrary, length, as well as a mixed-integer linear programming (MILP) formulation to approximate these, with provable quality guarantees. Additionally, we present a non-linear programming (NLP) formulation for solving zero-sum APGs. We show experimentally that MILP significantly outperforms the MINLP formulation, and is, in turn, significantly outperformed by the NLP specialized to zero-sum games.
Dietary composition programmes placental phenotype in mice

Non‐technical summary Studies on mice using severe diets show alterations in placental function, and fetal and adult health. However, little is known about the effects of mild dietary variations on the placenta. We investigated placental growth and function in mice fed diets with similar energy, but small differences in protein and sugar content. We show that placental adaptations occur to help support fetal growth: reduced protein leads to increased glucose transport and transporter gene expression in late pregnancy; just prior to term, amino acid transport expression correlated with protein intake; the placental endocrine compartment was smaller with the least dietary protein and somewhat larger with slight reduction in protein. Placentas in mice fed the least protein were better adapted than those exposed to slight protein reduction. These results may provide a good index of conditions in the womb and have important implications for the pre‐birth programming of life expectancy.
A modular power-aware microsensor with >1000X dynamic power range

We introduce a power-aware microsensor architecture supporting a wide operational power range (from <1 mW to >10 W). The platform consists of a family of modules that follow a common set of design principles. Each module includes a local power microcontroller, power switches, and isolation switches to enable independent power-down control of modules and module subsystems. Processing resources are scaled appropriately on each module for their role in the collective system. Hard real-time functions are migrated to the sensor and radio modules for improved power efficiency. The optional Linux-based processor module supports high duty cycling and advanced sleep modes. Our reference hardware implementation is described in detail in this paper. Seven different modules have been developed. We utilize an acoustic vehicle tracking application to demonstrate how the architecture operates and report on results from field tests on tracked and wheeled vehicles.
Switches, Excitable Responses and Oscillations in the Ring1B/Bmi1 Ubiquitination System

In an active, self-ubiquitinated state, the Ring1B ligase monoubiquitinates histone H2A playing a critical role in Polycomb-mediated gene silencing. Following ubiquitination by external ligases, Ring1B is targeted for proteosomal degradation. Using biochemical data and computational modeling, we show that the Ring1B ligase can exhibit abrupt switches, overshoot transitions and self-perpetuating oscillations between its distinct ubiquitination and activity states. These different Ring1B states display canonical or multiply branched, atypical polyubiquitin chains and involve association with the Polycomb-group protein Bmi1. Bistable switches and oscillations may lead to all-or-none histone H2A monoubiquitination rates and result in discrete periods of gene (in)activity. Switches, overshoots and oscillations in Ring1B catalytic activity and proteosomal degradation are controlled by the abundances of Bmi1 and Ring1B, and the activities and abundances of external ligases and deubiquitinases, such as E6-AP and USP7.
Identification procedure for McKibben pneumatic artificial muscle systems

This paper proposes a procedure for identifying a hybrid system model of a pneumatic artificial muscle that vertically suspends a mass. The obtained model involves if-then formulation and nonlinearities such as flow dynamics and friction because it is derived from mechanical and hydrodynamic equations and is developed with empirical modifications. Via analysis of the hybrid nonlinear system, we can clarify several dominant parameters characterizing the PAM dynamics in terms of steady-state and transient characteristics respectively. Based on the analysis result, then, a reasonable identification procedure can be composed. Furthermore, with a practical testbed system of the PAM system, we validate the proposed procedure producing the hybrid model under several load conditions.
The application of image based visual servo control system for smart guard

Based on SmartGuard, a mobile robot for substation inspection, we propose an image based visual servo control system to precisely make the cameras with the pan & tilt to capture the substation equipment we expected to inspect. The vision control system contents of an image acquisition system, a pan & tilt and an embedded servo control system. The proposed approach firstly uses SURF local feature to take the offset of the new acquired image and the template image, which is invariant to light, scale and rotation. Without the calibration of the pan & tilt and the vision system, we calculate the Jacobian matrix based on the test movement. Then we take the servo until the image feature reach to the object image. Using this image based vision system, SmartGuard can avoid the effect of the motion error and the repeating errors of pan & tilt system, and take the precisely image of the power equipments for automatic optical inspection system.
Mechanisms Pertaining to Arsenic Toxicity

Arsenic is an environmental pollutant and its contamination in the drinking water is considered as a serious worldwide environmental health threat. The chronic arsenic exposure is a cause of immense health distress as it accounts for the increased risk of various disorders such as cardiovascular abnormalities, diabetes mellitus, neurotoxicity, and nephrotoxicity. In addition, the exposure to arsenic has been suggested to affect the liver function and to induce hepatotoxicity. Moreover, few studies demonstrated the induction of carcinogenicity especially cancer of the skin, bladder, and lungs after the chronic exposure to arsenic. The present review addresses diverse mechanisms involved in the pathogenesis of arsenic-induced toxicity and end-organ damage.
Episodic Tremor and Slip Explained by Fluid‐Enhanced Microfracturing and Sealing

Episodic tremor and slow‐slip events at the deep extension of plate boundary faults illuminate seismic to aseismic processes around the brittle‐ductile transition. These events occur in volumes characterized by overpressurized fluids and by near failure shear stress conditions. We present a new modeling approach based on a ductile grain size‐sensitive rheology with microfracturing and sealing, which provides a mechanical and field‐based explanation of such phenomena. We also model pore fluid pressure variation as a function of changes in porosity/permeability and strain rate‐dependent fluid pumping. The fluid‐enhanced dynamic evolution of microstructures defines cycles of ductile strain localization and implies increase in pore fluid pressure. We propose that slow‐slip events are ductile processes related to transient strain localization, while nonvolcanic tremor corresponds to fracturing of the whole rock at the peak of pore fluid pressure. Our model shows that the availability of fluids and the efficiency of fluid pumping control the occurrence and the P‐T conditions of episodic tremor and slip.
GRPling with PTEN.

Regulation of the Pten tumor suppressor is complex and mediated by varied mechanisms. In this issue of Blood , Wey and colleagues show in a biallelic conditional knockout mouse model of GRP78 and PTEN that heterozygous loss of Grp78 suppresses leukemogenesis mediated by Pten . [1][1] These findings
The renal kallikrein-kinin and prostaglandin systems interaction.

In 1972 McGiff and associates (27) found that renal arterial infusion of bradykinin increases the concentration of a prostaglandin E-like material in the renal venous blood of the dog, indicating a relationship between kinins and renal prostaglandins. More recently, studies by Colina-Chourio and coworkers (10) in the perfused lapine kidney suggested dependency of prostaglandin release on intrarenal kinin generation leading to the proposal that the renal kallikrein-kinin and prostaglandin systems are coupled. This review analyzes the renal kallikrein-kinin and prostaglandin systems in­ teraction and discusses the implication of that interaction with regard to the hemodynamic and excretory functions of the kidney.
Experimental evidence for a motivational origin of cognitive impairment in major depression

Background Diagnostic criteria and empirical evidence support the existence of cognitive deficits in depression. However, depressed mood, loss of interest and low self-efficacy might influence cognitive performance. Method Goal-setting instructions were used to promote motivation in depressed patients and control subjects during neuropsychological assessment. The resulting performance was compared with performance using standard instructions. Sixty in-patients with non-psychotic unipolar depression and 60 age- and education-matched healthy control subjects were assessed with standard neuropsychological tests [the Auditory Verbal Learning Test (AVLT), the Digit Symbol Test (DST), the Regensburg Word Fluency Test (RWT), and the Number Combination Test (Zahlen-Verbindungs-Test, ZVT)] using either goal-setting or standard test instructions. Results Depressed patients showed lower baseline performance and lower generalized self-efficacy (p<0.0005) than controls. However, goal-setting instructions significantly improved patients' memory performance by 10% [AVLT: F(5, 54)=3.611, p=0.007] and psychomotor performance by 13% [ZVT: F(3, 56)=3.667, p=0.017]. Consequently, patients and control subjects demonstrated similar results when goal-setting instructions were applied. Goal-setting instructions showed a statistical trend, increasing patients' performance in the DST by 12% [F(1, 58)=2.990, p=0.089], although their verbal fluency measured by the RWT did not increase. No significant correlations of increased performance with generalized self-efficacy were found. Conclusions Cognitive deficits in depressed patients are influenced by motivational shortcomings. Because generalized self-efficacy failed to correlate to increased test performance, future research needs to disentangle the effective components of goal-setting instructions. Task-specific self-efficacy as well as enhancement of task-focused attention might underlie the significant goal-setting effect in depressed patients.