Miracle-dz/UniFAR-FTUs huggingface dataset:
Uptake of Serotonin at the Apical and Basolateral Membranes of Human Intestinal Epithelial (Caco-2) Cells Occurs through the Neuronal Serotonin Transporter (SERT)

Serotonin plays important physiological functions at the intestinal level. However, nothing is known concerning its inactivation mechanisms in the human intestine. So, the aim of this work was to characterize the uptake of serotonin at the apical and basolateral membranes of human intestinal epithelial (Caco-2) cells. Uptake of [3H]serotonin at the apical membrane of Caco-2 cells was specific and Na+-, Cl–-, and potential-dependent. It was concentration dependently inhibited by several monoamines (with the following rank order of potency: serotonin >> dopamine ≥ noradrenaline) and tricyclic and nontricyclic antidepressants (with the following rank order of potency: fluoxetine > desipramine > cocaine > GBR 12909). In contrast, it was not affected by corticosterone (0.01–100 μM) and was only partially inhibited by decynium-22 (0.001–10 μM). Transepithelial apparent permeability (Papp) to [3H]serotonin in the apical-to-basolateral direction was reduced by desipramine (0.4 μM) and fluoxetine (0.02 μM), and it was not Na+-dependent nor affected by corticosterone (100 μM). Uptake of [3H]serotonin at the basolateral membrane of Caco-2 cells was Na+-dependent and reduced by desipramine (0.4 μM) and fluoxetine (0.02 μM), and it was not affected by corticosterone (100 μM). The Papp to [3H]serotonin in the basolateral-to-apical direction was reduced by desipramine (0.4 μM) and fluoxetine (0.02 μM), and it was not affected by Na+ omission or by corticosterone (100 μM). Reverse transcriptase-polymerase chain reaction indicates that mRNA of the neuronal serotonin transporter (SERT) is present in Caco-2 cells and in human small intestine. In conclusion, these results suggest that human intestinal epithelial Caco-2 cells functionally express SERT, both at their apical and basolateral cell membranes.
Visibilizing and Invisibilizing Paradox: A process study of interactions in a hospital executive board

Studies on organizational paradoxes often explain paradox salience exogenously, as a state of latency awaiting detection. Based on social systems theory, this process study develops an explanation of paradox salience and latency beyond an actor’s cognitive ability to think paradoxically. Such an explanation lies endogenously within the interactions of actors coping with paradox. Analysing the discussions of a hospital executive board during a change initiative reveals how factual, social and temporal references surface and submerge contradictory tensions. The proposed model for visibilizing and invisibilizing paradox explains salience and latency – even if individuals are aware of paradox – as integral to coping with paradox. As a paradox invisibilizes in an interaction it resurfaces somewhere along the line and thereby transforms within an organization.
A robust position controller design for PM synchronous motor using neural network

A robust position controller for permanent magnet synchronous motor is described in this paper. First, linear quadratic method is employed to design the permanent magnet synchronous motor system approximately linear using field orientation theory. Then, the neural network technique with adaptive learning rates is implemented to make the system insensitive to the uncertainties including parameter variations and external disturbance in the whole control process. Finally, the experimental results verify that the dynamic behaviors of the proposed control systems are robust with regards to uncertainties.
Efficiency Enhancement of Doherty Amplifier Through Mitigation of the Knee Voltage Effect

This paper presents an approach to maximize the efficiency of a Doherty power amplifier (PA) with the knee voltage effect. Since the carrier PA with , which is the usual matching impedance for a carrier PA at a low power region, does not reach to the saturated operation at the 6-dB back-off power level, the maximum efficiency could not be achieved. However, the carrier amplifier can be driven into the saturation using the load impedance larger than and can deliver the maximum efficiency even under the knee voltage effect. The optimized design for the maximum efficiency at the back-off level is derived. The optimized amplifier is analyzed and simulated in terms of its load modulation behavior, efficiency, and output power, then compared with the conventional Doherty PA. The enhanced performance is demonstrated by the Doherty PA built using CREE's GaN HEMT CGH40045 devices at 2.655 GHz. For worldwide interoperability for microwave access applications with a 7.8-dB peak-to-average power ratio, the proposed PA delivers an efficiency of 49.3% at an output power of 42 dBm with an acceptable linearity of 23.1 dBc. The linearity is improved to 43 dBc by employing a digital feedback predistortion technique, satisfying the system linearity specification.
A Heuristic Algorithm for Finding the Closest Trio of 3-Colored Points from a Given Set of 3-Colored Points on Plane

The problem considering in this paper is as follows: Given n red points, m green points and p blue points on plane, how to find a trio of red-green-blue points such that the distance between them is smallest. This problem could be solved by an exhaustive search algorithm: test all trios of 3 different colored points and find the closest one. However, this algorithm has a big complexity: O(nmp). In this paper, we will present a heuristic algorithm with a better complexity to solve this problem. The heuristic algorithm is based on 2D Voronoi diagram.
Dynamic Light Field Reconstruction and Rendering for Multiple Moving Objects

Light field reco n stru ctio n is still m o stly lim ited to sta tic scen es o r is o n ly a p p lica b le to d yn a m ic scen es u sin g so p histica ted a n d co stly ha rd w a re. In co n tra st to tha t, o u r co n trib u tio n d escrib es a system w hich a llo w s the reco n stru ctio n o f a light field o f a scen e in clu d in g o n e o r m o re rigid ly m o vin g o b jects u sin g o n ly o n e ha n d -held ca m era . B y sep a ra tin g a u to m a tica lly tra cked fea tu re p o in ts in to d ifferen t o b jects, stru ctu re-fro m -m o tio n a lgo rithm s ca n b e a p p lied fo r ea ch o b ject. T he exten sio n to lo n g im a ge seq u en ces is d o n e itera tively a n d the d yn a m ic light field is crea ted b y m ergin g the in d ivid u a l reco n stru ctio n s a n d q u a n tizin g the o b ject p o ses in to d istin ct tim e step s. F o r ren d erin g p u rp o ses,a n exten sio n o f the U n stru ctu red Lu m igra p h is in tro d u ced w hich u ses co n fid en ce m a p s to m a rk scen e b a ckgro u n d ,visib le a n d in visib le o b ject p o ses.
Efficient Workstealing for Multicore Event-Driven Systems

Many high-performance communicating systems are designed using the event-driven paradigm. As multicore platforms are now pervasive, it becomes crucial for such systems to take advantage of the available hardware parallelism. Event-coloring is a promising approach in this regard. First, it allows programmers to simply and progressively inject support for the safe, parallel execution of multiple event handlers through the use of annotations. Second, it relies on a workstealing algorithm to dynamically balance the execution of event handlers on the available cores. This paper studies the impact of the workstealing algorithm on the overall system performance. We first show that the only existing workstealing algorithm designed for event-coloring runtimes is not always efficient: for instance, it causes a 33% performance degradation on a Web server. We then introduce several enhancements to improve the workstealing behavior. An evaluation using both micro benchmarks and real applications, a Web server and the Secure File Server (SFS), shows that our system consistently outperforms a state-of-the-art runtime (Libasync-smp), with or without workstealing. In particular, our new workstealing improves performance by up to +25% compared to Libasync-smp without workstealing and by up to +73% compared to the Libasync-smp workstealing algorithm, in the Web server case.
Is AdaBoost competitive for phoneme classification?

In the phoneme classification task of speech recognition, usually Gaussian Mixture Models and Artificial Neural Networks are used. For other machine learning tasks, however, several other classification algorithms are also applied. One of them is AdaBoost.MH, reported to have high accuracy, which we tested for phoneme recognition on the well-known TIMIT dataset. We found that it can achieve an accuracy comparable to standard ANNs in this task, but lags behind recently-proposed Deep Neural Networks. Based on our experimental results, we list a number of possible reasons why this might be so.
On deriving the upper bound of α-lifetime for large sensor networks

In this paper, we explore the fundamental limits of sensor network lifetime that all algorithms can possibly achieve. Specifically, under the assumptions that nodes are deployed as a Poisson point process with density λ in a square region with side length <i>l</i> and each sensor can cover a unit-area disk, we first derive the necessary and sufficient condition of the node density in order to maintain complete <i>k</i>-coverage with probability approaching 1. With this result, we obtain that if #955; = log <i>l</i><sup>2</sup> + (<i>k</i>+2)log log <i>l</i><sup>2</sup> + <i>c</i>(<i>l</i>), <i>c</i>(<i>l</i>) → -∞, as <i>l</i> → +∞, the sensor network lifetime (for maintaining complete coverage) is upper bounded by <i>kT</i> with probability approaching 1 as <i>l</i> → +∞, where <i>T</i> is the lifetime of each sensor. Second, we derive, given a fixed node density in a finite (but reasonably large) region, the upper bounds of lifetime when only α-portion of the region is required to be covered at any time. We also carry out simulations to validate the derived results. Simulation results indicate that the derived upper bounds apply not only to networks of large areas but also to small-area networks.
Enhancing User-Centredness in Agile Teams: A Study on Programmer's Values for a better Understanding on how to Position Usability Methods in XP

We present a study on programmer’s high-level goals in eXtreme Programming settings (XP). We talked to 10 programmers using so-called “laddering interviews”. The result presented is a “Hierarchical Value Map (HVM)” indicating agile programmer’s high-level goals. This study was done to better orchestrate usability methods and integrate them into agile development processes. The study’s results were used to position and adapt usability methods in a way that they are better aligned to the programmer’s goals and therefore are more likely to be accepted. We draw conclusions on the basis of the study’s results and experiences using agile usability methods in practise.
Coping With Cancer

IN BRIEF: A comprehensive review of the recent literature reveals that exercise has a positive effect on a broad range of quality-of-life parameters after patients are diagnosed as having cancer. The general exercise prescription is moderate-intensity exercise, 3 to 5 days per week, 20 to 30 minutes per session. Conditions that warrant prescription modification include fatigue periods during treatment, acute or chronic physical impairments that may have resulted from surgery or adjuvant therapy, and the presence of bone cancer. Research suggests that physicians who prescribe exercise improve motivation and adherence in their patients who have cancer.
A Genetic Algorithm for Solving the Optimal Power Flow Problem

This paper presents solution of optimal power flow problem of large distribution systems via a simple genetic algorithm. The objective is to minimize the fuel cost and keep the power outputs of generators, bus voltages, shunt capacitors/reactors and transformers tap-setting in their secure limits. CPU times can be reduced by decomposing the optimization constraints to active constraints manipulated directly by the genetic algorithm, and passive constraints maintained in their soft limits using a conventional constraint load flow. The IEEE 30-bus system has been studied to show the effectiveness of the algorithm.
Performance analysis of multi-fiber all-optical switches employing fixed-input/tunable-output wavelength converters

A Multi-fiber all-optical switch which employs wavelength converters with fixed input wavelength is presented. Being the converters tuned over a fixed input wavelength, each one is shared by channels on the same wavelength, so the resulting architecture is called shared-per-wavelength. Here the space switching matrices are simpler with respect to similar switching architectures proposed in the past (i.e. shared-per-node ones) leading to easier and less costly implementation. Moreover, fixed- input/tunable-output converters are expected to be less costly than tunable-input/tunable-output ones. A scheduling algorithm to forward optical packets in synchronous scenario and an analytical model to evaluate performance of the shared-per- wavelength architecture are presented. The analytical model is validated against simulation and the results show good accuracy in most cases of interest for optical switch design.
Optimal market making strategies under inventory constraints ∗

We study the problem of a market-maker acting as a liquidity provider by continuously setting bid and ask prices for an illiquid asset. We assume that the market maker has a contractual obligation to permanently quote bid and ask prices for the security and therefore to satisfy any sell or buy order from the asset’s investors. On the opposite side of the trades, there are investors who act as liquidity takers by submitting either sell or buy market orders. The arrival of buy (and sell) market orders submitted by the investors is assumed to follow a Cox process with regime-shifting Markov intensity. The role of the market maker is very important in the trading of illiquid assets as it acts as a facilitator of trades between different investors. The market maker may therefore benefit from the bid-ask spread but faces a number of constraints, in particular the liquidity and inventory constraints. The objective is to maximize the expected utility of the market maker’s terminal wealth. We characterize our objective functions as unique viscosity solutions to the associated HJB system. We further enrich our study with some numerical results.
Exploiting Hierarchical Structures for Unsupervised Feature Selection

Feature selection has been proven to be effective and efficient in preparing high-dimensional data for many mining and learning tasks. Features of real-world high-dimensional data such as words of documents, pixels of images and genes of microarray data, usually present inherent hierarchical structures. In a hierarchical structure, features could share certain properties. Such information has been exploited to help supervised feature selection but it is rarely investigated for unsupervised feature selection, which is challenging due to the lack of labels. Since real world data is often unlabeled, it is of practical importance to study the problem of feature selection with hierarchical structures in an unsupervised setting. In particular, we provide a principled method to exploit hierarchical structures of features and propose a novel framework HUFS, which utilizes the given hierarchical structures to help select features without labels. Experimental study on real-world datasets is conducted to assess the effectiveness of the proposed framework.
A cognitive model of motor planning for virtual creatures

The planning is one of the most important cognitive functions of the human beings. It is essential for the solution of mental and physical problems. This paper shows a conceptual and computational model of motor planning. It is based on recent findings of the human brain and how the human can develop several motor plans in order to solve their daily problems. The objective of our bio-inspired model is to develop appropriate mechanisms to endow virtual creatures with them, in order to emulate both internal and external processes of the human brain.
Blood pressure control by home monitoring: meta-analysis of randomised trials

Abstract Objective To determine the effect of home blood pressure monitoring on blood pressure levels and proportion of people with essential hypertension achieving targets. Design Meta-analysis of 18 randomised controlled trials. Participants 1359 people with essential hypertension allocated to home blood pressure monitoring and 1355 allocated to the “control” group seen in the healthcare system for 2-36 months. Main outcome measures Differences in systolic (13 studies), diastolic (16 studies), or mean (3 studies) blood pressures, and proportion of patients achieving targets (6 studies), between intervention and control groups. Results Systolic blood pressure was lower in people with hypertension who had home blood pressure monitoring than in those who had standard blood pressure monitoring in the healthcare system (standardised mean difference 4.2 (95% confidence interval 1.5 to 6.9) mm Hg), diastolic blood pressure was lower by 2.4 (1.2 to 3.5) mm Hg, and mean blood pressure was lower by 4.4 (2.0 to 6.8) mm Hg. The relative risk of blood pressure above predetermined targets was lower in people with home blood pressure monitoring (risk ratio 0.90, 0.80 to 1.00). When publication bias was allowed for, the differences were attenuated: 2.2 (−0.9 to 5.3) mm Hg for systolic blood pressure and 1.9 (0.6 to 3.2) mm Hg for diastolic blood pressure. Conclusions Blood pressure control in people with hypertension (assessed in the clinic) and the proportion achieving targets are increased when home blood pressure monitoring is used rather than standard blood pressure monitoring in the healthcare system. The reasons for this are not clear. The difference in blood pressure control between the two methods is small but likely to contribute to an important reduction in vascular complications in the hypertensive population.
Towards the assessment of GRN algorithms based on (disease) ontology

The inference of biological networks from experimental data is a growing area in bioinformatics and systems biology. Biological network inference aims to reconstruct network of interactions (or associations) among biological molecules (e.g. genes or proteins) starting from experimental observations. The growing of the number of these algorithms has been not accompanied from the appearance of fair assessments and comparisons. Current assessments are usually based on the comparison of the algorithms using reference networks or gold standard dataset. Low attention has been posed on the ability of algorithms to reconstruct network that are related to diseases or phenotypes. It has been observed that highly connected or central genes in a GRN or PPI networks are essential genes and possible key players for disease diagnosis. Consequently we designed a novel assessment methodology that relies on the ranking of inferred network on the basis of the similarity of their top genes (i.e. hubs) with respect to diseases. The assessment is based on a three step methodology. Initially, we infer regulatory networks using few popular inference methods. Next, we analyse the topology of the network to determine a list of top central genes and finally we match those genes to disease specific ontologies. We hypothesise that more number of top ranked genes from a GRN inferred by a method is matching with disease ontologies more it is influential. The results show a marked change in the ranking of participating methods while assessing network inferability with respect to disease specific ontologies.
The Influence of Gender on the Mother- Child Interaction

Children are born with their natural style of interacting with or reacting to people, places and things. This natural behaviour style in everyday situations is known as temperament. Temperament refers to our inborn personality traits, which are genetic in nature. The different ways infants interact with and react to their environment and experiences are reflective of their temperament, or behavioral style. Temperament is an individual's innate style of responding to the environment in both behavioural and emotional ways (Griggs et al., 2009). All children have a temperament that will influence their emotions and how they adapt to change in their environments (Steinberg, 2004). In other words, the structure of adult personality is presumed to emerge from early temperament that serves as a basis for personality development (Costa and McCrae, 2000).
Challenges to Research in MOOCs

Over the past five years, the emergence of interactive social media has influenced the development of learning environments. Learning management systems have come to maturity, but because they are controlled by educational institutions and are subsequently used to support institutional learning, have been seen by learning technologists as not capturing the spirit and possibilities that new media have to offer for learning. Academics and researchers are currently investigating a different learning environment, more open and networked, while the underpinning learning theory is moving from social constructivism towards connectivism. Research in open learning environments is only in its infancy and researchers have only started to become interested in massive open online courses (MOOCs) as a topic of investigation. Recent research and development efforts have focused on generating technologies that might facilitate learning within a self-directed information and communication stream. In this paper, the authors report on an exploratory case study of PLENK, a connectivist-style MOOC, and highlight some of the challenges in the research and analysis process, especially as significant amounts of both quantitative and qualitative data were involved. Important findings related to activity levels and important dimensions of self-directed learning in an open learning environment are presented.
A practical guide to male hypogonadism in the primary care setting

There is a high prevalence of hypogonadism in the older adult male population and the proportion of older men in the population is projected to rise in the future. As hypogonadism increases with age and is significantly associated with various comorbidities such as obesity, type 2 diabetes, hypertension, osteoporosis and metabolic syndrome, the physician is increasingly likely to have to treat hypogonadism in the clinic. The main symptoms of hypogonadism are reduced libido/erectile dysfunction, reduced muscle mass and strength, increased adiposity, osteoporosis/low bone mass, depressed mood and fatigue. Diagnosis of the condition requires the presence of low serum testosterone levels and the presence of hypogonadal symptoms. There are a number of formulations available for testosterone therapy including intramuscular injections, transdermal patches, transdermal gels, buccal patches and subcutaneous pellets. These are efficacious in establishing eugonadal testosterone levels in the blood and relieving symptoms. Restoration of testosterone levels to the normal range improves libido, sexual function, and mood; reduces fat body mass; increases lean body mass; and improves bone mineral density. Testosterone treatment is contraindicated in subjects with prostate cancer or benign prostate hyperplasia and risks of treatment are perceived to be high by many physicians. These risks, however, are often exaggerated and should not outweigh the benefits of testosterone treatment.