Miracle-dz/UniFAR-FTUs huggingface dataset:
Branch-and-bound parallelization strategies applied to a depot location and container ̄ eet management problem

This paper presents branch-and-bound parallelization strategies applied to the location/ allocation problem with balancing requirements. This formulation is representative of a larger class of discrete network design and location problems arising in many transportation logistics and telecommunications applications: it displays a multicommodity network ̄ow structure and a complex objective function comprising ®xed and variable ̄ow costs. As for many problems of this class, the bounding procedure embedded in the branch-and-bound algorithm is complex and time-consuming. The parallelization strategies that we describe are designed to exploit this feature. Parallelism is obtained by dividing the search tree among processors and performing operations on several subproblems simultaneously. The strategies dier in the way they manage the list of subproblems and control the search. We report and analyze experimental results, on a distributed network of workstations, which aim to compare dierent implementations of these strategies. Ó 2000 Elsevier Science B.V. All rights reserved.
Evaluation of the scalability of an energy market for Smart Grid neighborhoods

The electric power grid is undergoing fundamental changes in light of the current focus on distributed generation, and in particular renewable generation (e.g., solar and wind). As a result, new methodologies and technologies are needed to effectively coordinate and make optimal use of the these resources. A distribution-system level energy market offers the potential to address this issue by providing an efficient mechanism for the pricing and allocation of resources. Market participants (e.g., households, ESCos, asset managers etc.) can apply economically driven strategies to trade energy while reacting to current and local levels of production and consumption. We evaluate here such a local neighborhood market and investigate its scalability under different numbers of participants and different penetrations photo-voltaic (PV) generation. The evaluation is carried out by simulating market operations under realistic production and consumption conditions. Results showed that the proposed market model scales well against both parameters.
Effects of Valproic Acid Derivatives on Inositol Trisphosphate Depletion, Teratogenicity, Glycogen Synthase Kinase-3β Inhibition, and Viral Replication: A Screening Approach for New Bipolar Disorder Drugs Derived from the Valproic Acid Core Structure

Inositol-1,4,5-trisphosphate (InsP3) depletion has been implicated in the therapeutic action of bipolar disorder drugs, including valproic acid (VPA). It is not currently known whether the effect of VPA on InsP3 depletion is related to the deleterious effects of teratogenicity or elevated viral replication, or if it occurs via putative inhibitory effects on glycogen synthase kinase-3β (GSK-3β). In addition, the structural requirements of VPA-related compounds to cause InsP3 depletion are unknown. In the current study, we selected a set of 10 VPA congeners to examine their effects on InsP3 depletion, in vivo teratogenic potency, HIV replication, and GSK-3β activity in vitro. We found four compounds that function to deplete InsP3 in the model eukaryote Dictyostelium discoideum, and these drugs all cause growth-cone enlargement in mammalian primary neurons, consistent with the effect of InsP3 depletion. No relationship was found between InsP3 depletion and teratogenic or elevated viral replication effects, and none of the VPA congeners were found to affect GSK-3β activity. Structural requirements of VPA congers to maintain InsP3 depletion efficacy greater than that of lithium are a carboxylic-acid function without dependence on side-chain length, branching, or saturation. Noteworthy is the enantiomeric differentiation if a chiral center exists, suggesting that InsP3 depletion is mediated by a stereoselective mode of action. Thus, the effect of InsP3 depletion can be separated from that of teratogenic potency and elevated viral replication effect. We have used this to identify two VPA derivatives that share the common InsP3-depleting action of VPA, lithium and carbamazepine, but do not show the side effects of VPA, thus providing promising novel candidates for bipolar disorder treatment.
Multi-domain Sentiment Classification

This paper addresses a new task in sentiment classification, called multi-domain sentiment classification, that aims to improve performance through fusing training data from multiple domains. To achieve this, we propose two approaches of fusion, feature-level and classifier-level, to use training data from multiple domains simultaneously. Experimental studies show that multi-domain sentiment classification using the classifier-level approach performs much better than single domain classification (using the training data individually).
Anisotropic Phase Unwrapping for Synthetic Aperture Radar Interferometry

This paper presents a new phase unwrapping method for synthetic aperture radar interferometry (InSAR). Compared with other phase observations, InSAR data are unique due to the foreshortening effect in SAR images. This effect makes the interferogram phase anisotropic, i.e., the statistics of phase gradients along the ground-range axis are different from those in the azimuth direction. Furthermore, the distribution of phase gradients in the ground-range direction is not symmetric. The proposed method targets the most likely unwrapped phase by considering the foreshortening effect in SAR observation, noise characteristics in InSAR phase data, and fractional Brownian surface as a suitable model for natural topography. Experiments with simulated terrains and real InSAR data show that the method gives comparable or better digital elevation model results than the other tested methods.
Serum thyroid stimulating hormone, total and free T4 during the neonatal period: Establishing regional reference intervals

Context: Congenital hypothyroidism (CH), the most common etiology of preventable mental retardation in children, is estimated to be more prevalent among Asian population. Aims: Since thyroid function tests (TFTs) varied among different ages and geographical regions, in this study, the neonatal thyroid reference intervals in a healthy neonatal population is determined for the first time in Iran. Settings and Design: A cross-sectional study performed on 246 healthy term newborns aged between 2 days and 1 month. Materials and Methods: Blood samples were obtained by venipuncture from all subjects. The median, 2.5th, 5th, 95th, and 97.5th percentile of serum thyroid-stimulating hormone (TSH), as well as the total and free T4 were assessed among different age groups. Statistical Analysis Used: Predictive Analytics Software (PASW Statistics 18) was used for the analysis. Results: Serum TSH, total and free T4 concentration peaked in 5th to 7th days of life, continued over 2 weeks, then decreased and started reaching to adult reference range. A significant negative correlation between age and serum concentration of TSH (P = 0.02), total T4 (P = 0.01) and free T4 (P = 0.01) was found. Conclusion: This study yielded fairly different values for TFTs compared compared values found in other countries and also different from values reported for laboratory kits we used. These differences were assumed to be due to variations in ethnicity, age, and laboratory methods used. Due to the lack of international standardization, conducting multicenter studies helps in making a more precise evaluation of thyroid status in neonates.
Cardio-miRNAs and onco-miRNAs: circulating miRNA-based diagnostics for non-cancerous and cancerous diseases

Cardiovascular diseases and cancers are the leading causes of morbidity and mortality in the world. MicroRNAs (miRNAs) are short non-coding RNAs that primarily repress target mRNAs. Here, miR-24, miR-125b, miR-195, and miR-214 were selected as representative cardio-miRs that are upregulated in human heart failure. To bridge the gap between miRNA studies in cardiology and oncology, the targets and functions of these miRNAs in cardiovascular diseases and cancers will be reviewed. ACVR1B, BCL2, BIM, eNOS, FGFR3, JPH2, MEN1, MYC, p16, and ST7L are miR-24 targets that have been experimentally validated in human cells. ARID3B, BAK1, BCL2, BMPR1B, ERBB2, FGFR2, IL6R, MUC1, SITR7, Smoothened, STAT3, TET2, and TP53 are representative miR-125b targets. ACVR2A, BCL2, CCND1, E2F3, GLUT3, MYB, RAF1, VEGF, WEE1, and WNT7A are representative miR-195 targets. BCL2L2, ß-catenin, BIM, CADM1, EZH2, FGFR1, NRAS, PTEN, TP53, and TWIST1 are representative miR-214 targets. miR-125b is a good cardio-miR that protects cardiomyocytes; miR-195 is a bad cardio-miR that elicits cardiomyopathy and heart failure; miR-24 and miR-214 are bi-functional cardio-miRs. By contrast, miR-24, miR-125b, miR-195, and miR-214 function as oncogenic or tumor suppressor miRNAs in a cancer (sub)type-dependent manner. Circulating miR-24 is elevated in diabetes, breast cancer and lung cancer. Circulating miR-195 is elevated in acute myocardial infarction, breast cancer, prostate cancer and colorectal adenoma. Circulating miR-125b and miR-214 are elevated in some cancers. Cardio-miRs and onco-miRs bear some similarities in functions and circulation profiles. miRNAs regulate WNT, FGF, Hedgehog and other signaling cascades that are involved in orchestration of embryogenesis and homeostasis as well as pathogenesis of human diseases. Because circulating miRNA profiles are modulated by genetic and environmental factors and are dysregulated by genetic and epigenetic alterations in somatic cells, circulating miRNA association studies (CMASs) within several thousands of cases each for common non-cancerous diseases and major cancers are necessary for miRNA-based diagnostics.
Image‐based detail reconstruction of non‐Lambertian surfaces

This paper presents a novel optimization framework for estimating the static or dynamic surfaces with details. The proposed method uses dense depths from a structured‐light system or sparse ones from motion capture as the initial positions, and exploits non‐Lambertian reflectance models to approximate surface reflectance. Multi‐stage shape‐from‐shading (SFS) is then applied to optimize both shape geometry and reflectance properties. Because this method uses non‐Lambertian properties, it can compensate for triangulation reconstruction errors caused by view‐dependent reflections. This approach can also estimate detailed undulations on textureless regions, and employs spatial‐temporal constraints for reliably tracking time‐varying surfaces. Experiment results demonstrate that accurate and detailed 3D surfaces can be reconstructed from images acquired by off‐the‐shelf devices. Copyright © 2010 John Wiley & Sons, Ltd.
Knockdown of CD44 inhibits the invasion and metastasis of hepatocellular carcinoma both in vitro and in vivo by reversing epithelial-mesenchymal transition

Mounting evidence has shown that induction of epithelial-mesenchymal transition (EMT) contributes to the the expression of CSC (cancer stem cell) markers. However, whether and how CSC markers could be involved in regulating EMT has rarely been reported. CD44, being one of the most commonly used CSC markers in hepatocellular carcinoma (HCC), has been demonstrated to act as a multidomain, transmembrane platform that serves to integrate a wide variety of extracellular signals. Therefore, we determined to seek whether CD44 is necessary for the EMT process in HCC. First, we noticed that CD44 expression was associated with the mesenchymal phenotype in HCC cell lines, and knocking down CD44 with lentivirus-mediated shRNA in HCC cell lines resulted in the mesenchymal-epithelial-transition (MET) and the subsequent impaired migration and invasion in vitro. Moreover, in a metastatic mice model established by tail vein injection of luciferase labelled MHCC97-H cells, we confirmed that CD44 knockdown resulted in the decreased metastasis of HCC cells. Furthermore, we found that the induction of MET by CD44 inhibition might be achieved, at least in part, by repressing the ERK/Snail pathway.
Escitalopram And Mirtazapine For The Treatment Of Depression In Hiv Patients: A Randomized Controlled Open Label Trial

Objective: The objective of this study was to compare the safety and efficacy of mirtazapine and escitalopram in HIV patients for the treatment of depression. Methods: In this trial, 70 adult HIV patients with major depression were randomized and assigned to receive 8 weeks of daily open label mirtazapine (5-30 mg) or escitalopram (7.5-20 mg). The primary outcome variables were endpoint response in Hamilton Rating Scale for Depression (HAM-D) score and change of HAM-D score from baseline to endpoint. Patients having improvement of > 50% on the HAM-D total scores during treatment were considered to have responded. A final 17-item HAM-D total score of 8 or less defined remission. Results: The response rate was 91.4 % (32/35) in Mirtazapine group and 85.7 % (30/35) in Escitalopram group (p= 0.71). The remission rate was more in escitalopram group (48.6 %, 17/35) compared to Mirtazapine group (34.3 %, 12/35); however it was not statistically significant (Chi square (1, N = 70) = 2.1, p = 0.22). After controlling for baseline score, the median HAMD score at 8 weeks was significantly lower in the Mirtazapine group (Median (Mdn)=4, Interquartile range (IQR)= 11) compared to Escitalopram group (Mdn=13, IQR= 12) (p Conclusions: Both these drugs are useful in the management of depression in HIV patients and need further study. ASEAN Journal of Psychiatry, Vol. 14 (1): January - June 2013: XX XX.
The influence of obesity on structure, biochemistry and function of brain regions involved in cognition

While there are many clinical findings associating obesity with cognitive deficits, this relationship has not been fully characterized in animal models. Using an animal model of diet induced obesity (DIO), we can assay cognitive behaviors in obese versus normal weight rats. In the current study, adult rats were maintained on a nutritionally complete, palatable, high-fat diet for 8 weeks. At this point, obesity, defined as elevated body weight, increased fat pad accrual and increased serum triglyceride levels, was obvious in the high-fat consuming rats compared to age and weight matched rats maintained on standard rodent chow. After obesity onset, behavioral tasks that are dependent on brain regions important in cognition and memory, including the medial prefrontal cortex (mPFC), perirhinal cortex (PRC), and hippocampus (HIP), were implemented. Rats were also tested for performance on standard sensory and locomotor tasks, to eliminate confounding behavioral deficits that might present as cognitive deficits. Obese rats showed deficits on behavioral tasks requiring the mPFC and PRC, but not HIP. Further, obese rats showed no deficits on sensory or locomotor tasks compared to controls. These results indicate a correlation between obesity and performance on cognitive functions requiring the mPFC and PRC. The data also provide a model, as well as motivation, to further explore potential cellular and structural
Partner relationships during pregnancy in anxious and depressed women and men

This research was supported by grants from the March of Dimes (12FY03-48) and NIMH (MH# 46586) and NIMH Research ScientistAwards (MH# 00331 andAT# 001585) to Tiffany Field, funding from Johnson & Johnson to the Touch Research Institutes, and a fellowship to Barbara Figueiredo (POCI/SAU-ESP/56397/2004, funded under the 2010 Science and Innovation Operational Program (POCI 2010) of the Community Support Board III, and supported by the European Community Fund FEDER).
The optimization of sensor arrangement and feature selection in activity recognition

This paper deals with the optimization of sensor arrangement and feature selection for activity recognition of the people living alone with sensors. We suggest an algorithm which picks up from several thousand to millions of characteristic sensor reactions as feature candidates, and selects best feature combinations and corresponding sensor arrangements for classification with as small numbers of sensors and features as possible. This paper introduces two kinds of approach; one is making the sensor number as small as possible with quasi-maximized precision, and another is getting the globally maxmized precision with only needed sensors. We confirmed by a pyroelectric sensor system that this algorithm could get such solution by applying some sparse selection methods to the real life data.
Energy-efficient opportunistic localization with indoor wireless sensor networks

Localization challenges researchers for its contradictive goals, i.e., how to tackle the problem of minimizing energy consumption as well as maintaining localization precision, which are two essential trade-offs in wireless sensor network systems. In this paper, we propose an Energy-Efficient Opportunistic Localization (EEOL) scheme to satisfy the requirement of positional accuracy and power consumption. We explore the idea of opportunistic wakeup probability to wake up an appropriate numbers of sensor nodes, while ensuring the high positional accuracy. Sensor nodes can be triggered by the opportunistic wakeup probability sent from the user. Through utilizing this method, the number of active sensors in the sensing range of the user is decreased, and the power consumption is significantly reduced. Theoretical analysis has been presented to evaluate the performance of EEOL. Simulation results show that EEOL confirms our theoretical analysis.
Skill transmission for hand positioning task through view-sharing system

In this paper, we describe the skill transmission through our view-sharing system that can mix or exchange the first person perspectives from the exact the partner's viewpoints. Since a non-skilled person can see the first person perspective of a skilled person, the motion of the non-skilled person is intuitively modified and supported. The task for the skill transmission is to play theremin that requires precise hand motions. As a result we show that the skill transmission effectively happens with our view-sharing system compared with the conventional method, side-by-side teaching. The way of effective augmenting human ability will be discussed.
Cost-effectiveness of antibiotic treatment of uncomplicated urinary tract infection in women: a comparison of four antibiotics

Background Urinary tract infections (UTIs) are one of the most common reasons for women to attend primary care. There are four different antibiotics currently recommended in England for treatment of uncomplicated UTI but little evidence on their comparative cost-effectiveness. Aim To assess the relative cost-effectiveness of the four antibiotics currently recommended in England for treatment of uncomplicated UTI in adult women. Design & setting A cost-effectiveness model in adult women with signs and symptoms of uncomplicated UTI in primary care in England treated with fosfomycin, nitrofurantoin, pivmecillinam, or trimethoprim. Method A decision tree economic model of the treatment pathway encompassed up to two rounds of treatment, accounting for different resistance levels. End points included recovery, persistence, pyelonephritis, and/or hospitalisation. Prescription, primary and secondary care treatment, and diagnostic testing costs were aggregated. Cost-effectiveness was assessed as cost per UTI resolved. Results Trimethoprim 200 mg twice daily (for 3 or 7 days) was estimated to be the most cost-effective treatment (£70 per UTI resolved) when resistance was <30%. However, if resistance to trimethoprim was ≥30%, fosfomycin 3 g once became more cost-effective; at resistance levels of ≥35% for trimethoprim, both fosfomycin 3 g once and nitrofurantoin 100 mg twice daily for 7 days were shown to be more cost-effective. Conclusion Knowing local resistance levels is key to effective and cost-effective empirical prescribing. Recent estimates of trimethoprim resistance rates are close to 50%, in which case a single 3 g dose of fosfomycin is likely to be the most cost-effective treatment option.
HZD-based control of a five-link underactuated 3D bipedal robot

This paper presents a within-stride feedback controller that achieves an exponentially stable, periodic, and fast walking gait for a 3D bipedal robot consisting of a torso, revolute knees, and passive (unactuated) point feet. The walking surface is assumed to be rigid and flat; the contact between the robot and the walking surface is assumed to inhibit yaw rotation. The studied robot has 8 DOF in the single support phase and 6 actuators. In addition to the reduced number of actuators, the interest of studying robots with point feet is that the feedback control solution must explicitly account for the robot¿s natural dynamics in order to achieve balance while walking. We use an extension of the method of virtual constraints and hybrid zero dynamics (HZD), a very successful method for planar bipeds, in order to determine a periodic orbit and an autonomous feedback controller that realizes the orbit, for a 3D (spatial) bipedal walking robot. The effect of output selection on the zero dynamics is highlighted and a pertinent choice of outputs is proposed, leading to stabilization without the use of a supplemental event-based controller.
Capacity planning with phased workloads

At the heart of any con guration or capacity planning algorithm for storage systems, there lies a \what if" question: given a device and a set of workloads accessing data on the device, will the quality of service requirement for each workload be satis ed? This is, in general, a hard question to answer because of the complexity of workloads in real life. In this paper, we consider QoS bounds on the 95th percentile of response time and demonstrate an approximate method to verify that the QoS requirement is satis ed for a complex and fairly general set of workloads, including workloads with phasing (on/o behavior) and correlations with other workloads.
1 Cloud Service Reliability : Modeling and Analysis

Cloud computing is a recently developed new technology for complex systems with massivescale service sharing, which is different from the resource sharing of the grid computing systems. Cloud reliability analysis and modeling are not easy tasks because of the complexity and large scale of the system. This paper systematically analyzes cloud computing and models the reliability of the cloud services. Various types of failures are interleaved in the cloud computing environment, such as overflow failure, timeout failure, resource missing failure, network failure, hardware failure, software failure, and database failure. This paper investigates all of them to achieve a comprehensive picture about cloud service reliability, and models those failures in a holistic manner using Markov models, Queuing Theory and Graph Theory. In accordance with the proposed model, a new evaluation algorithm is further developed in this paper integrating the Bayesian approaches together with the Graph Theory. Keyword Cloud computing, Reliability modeling, Graph theory, Queuing theory, Bayesian analysis
Integration of gestures and speech in human-robot interaction

We present an approach to enhance the interaction abilities of the Nao humanoid robot by extending its communicative behavior with non-verbal gestures (hand and head movements, and gaze following). A set of non-verbal gestures were identified that Nao could use for enhancing its presentation and turn-management capabilities in conversational interactions. We discuss our approach for modeling and synthesizing gestures on the Nao robot. A scheme for system evaluation that compares the values of users' expectations and actual experiences has been presented. We found that open arm gestures, head movements and gaze following could significantly enhance Nao's ability to be expressive and appear lively, and to engage human users in conversational interactions.