Miracle-dz/UniFAR-FTUs huggingface dataset:
A Combined Batteryless Radio and WiFi Indoor Positioning for Hospital Nursing

This paper proposes a design of an efficient hospital nurse calling system which combines two types of indoor localization systems. The purpose of the first system is to locate patients while the second is to locate nurses equipped with their smart phones. The main goal of developing such system is to decrease the time taking for nurses to provide healthcare for patients. Patients' positioning system is RF based. Indeed, each patient is equipped with a wireless and battery-free call button. When the switch is pressed, a wireless telegram is sent to reference nodes that act like Wireless Sensor Networks (WSN). The positioning of patient is performed using trilateration method with the help of Received Signal Strength Indicator (RSSI) values. Hence, beacons will forward the received signal from patient’s call button to a central receiver module connected to a computer. A dedicated program has been developed to calculate the position of the call button and post it on an online database. On the other hand, the nurses’ localization system is WiFi-based. Nurses' positioning is done by determining the Time of Arrival (ToA) and the Angle of Arrival (AoA) between the mobile phone and the WiFi router. The mobile phone locations are posted to the online database as well. Our program performs a comparison between the nurses' and the patient's coordinates. The nearest nurse gets an alarm. As consequence, a patient gets care from the nearest available nurse in an efficient way and with less time. The proposed system is user-friendly and Internet of Things (IoT) based architecture integrating two heterogeneous localization systems seamlessly.
Oligonucleotide DNA Microarray Profiling of Lung Adenocarcinoma Revealed Significant Downregulation and Deletions of Vasoactive Intestinal Peptide Receptor 1

ABSTRACT The purpose of this study was to find novel gene(s) involved in the development of lung adenocarcinoma (AD). Using DNA microarrays, we identified 31 up-regulated and 8 downregulated genes in 12 AD. Real time PCR was used to measure expression of VIPR1 and SPP1 mRNA and possible losses or gains of genes in 32 AD. We describe significant upregulation of the SPP1 gene, downregulation of VIPR1, and losses of the VIPR1 gene. Our findings complement a proposed VIPR1 tumor suppressor role, in which deletions in the 3p22 chromosome region are an important mechanism leading to loss of the VIPR1 gene.
Hypocrea jecorina (Trichoderma reesei) Cel7A as a molecular machine: A docking study

Hypocrea jecorina (formerly Trichoderma reesei) Cel7A has a catalytic domain (CD) and a cellulose‐binding domain (CBD) separated by a highly glycosylated linker. Very little is known of how the 2 domains interact to degrade crystalline cellulose. Based on the interaction energies and forces on cello‐oligosaccharides computationally docked to the CD and CBD, we propose a molecular machine model, where the CBD wedges itself under a free chain end on the crystalline cellulose surface and feeds it to the CD active site tunnel. Enzyme–substrate interactions produce the forces required to pull cellulose chains from the surface and also to help the enzyme move on the cellulose chain for processive hydrolysis. The energy to generate these forces is ultimately derived from the chemical energy of glycosidic bond breakage. Proteins 2005. © 2005 Wiley‐Liss, Inc.
Modélisation Mathématique et Simulation Numérique de Systèmes Fluides Quantiques. (Mathematical modeling and Numerical Simulation of Quantum Fluid Systems)

Le sujet de la these porte sur l'etude d'une nouvelle classe de modeles de transport quantique: les modeles fluides quantiques issus du principe de minimisation d'entropie. Ces modeles ont ete derives dans deux articles publies en 2003 et 2005 par Degond, Mehats et Ringhofer dans Journal of Statistical Physics en adaptant au cadre de la theorie quantique la methode des moments developpee par Levermore dans le cadre classique. Cette methode consiste a prendre les moments de l'equation de Liouville quantique et a fermer ce systeme par un equilibre local (ou Maxwellienne quantique) defini comme minimiseur d'une certaine entropie quantique sous contrainte de conservation de certaines quantites physiques comme la masse, le courant, et l'energie. Le principal interet des modeles quantiques ainsi obtenus provient du fait qu'etant macroscopiques, ils sont biens moins couteux numeriquement que des modeles microscopiques comme l'equation de Schrodinger ou l'equation de Wigner, et de plus, ils prennent en compte implicitement des effets de collision bien plus difficiles a modeliser a un niveau microscopique. Le but de cette these est donc de proposer des methodes numeriques pour implementer ces modeles et de les tester sur des dispositifs physiques adequats. Nous avons donc commence dans le chapitre I par proposer une discretisation du plus simple de ces modeles qu'est le modele de Derive-Diffusion Quantique sur un domaine ferme. Puis nous avons decide dans le chapitre II et III d'appliquer ce modele au transport d'electrons dans les semiconducteurs en choisissant comme dispositif ouvert la diode a effet tunnel resonnant. Ensuite nous nous sommes interesses au chapitre IV a l'etude et l'implementation du modele d'Euler Quantique Isotherme, avant de s'attaquer aux modeles non isothermes dans le chapitre V avec l'etude des modeles d'Hydrodynamique Quantique et de Transport d'Energie Quantique. Enfin, le chapitre VI s'interesse a un probleme un petit peu different en proposant un schema asymptotiquement stable dans la limite semi-classique pour l'equation de Schrodinger ecrite dans sa formulation fluide: le systeme de Madelung.
Detection of Intracellular Granularity Induction in Prostate Cancer Cell Lines by Small Molecules Using the HyperCyt® High-Throughput Flow Cytometry System

Prostate cancer is a leading cause of death among men due to the limited number of treatment strategies available for advanced disease. Discovery of effective chemotherapeutics involves the identification of agents that inhibit cancer cell growth. Increases in intracellular granularity have been observed during physiological processes that include senescence, apoptosis, and autophagy, making this phenotypic change a useful marker for identifying small molecules that induce cellular growth arrest or death. In this regard, epithelial-derived cancer cell lines appear uniquely susceptible to increased intracellular granularity following exposure to chemotherapeutics. We have established a novel flow cytometry approach that detects increases in side light scatter in response to morphological changes associated with intracellular granularity in the androgen-sensitive LNCaP and androgen-independent PC3 human prostate cancer cell lines. A cell-based assay was developed to screen for small molecule inducers of intracellular granularity using the HyperCyt® high-throughput flow cytometry platform. Validation was performed using the Prestwick Chemical Library, where known modulators of LNCaP intracellular granularity, such as testosterone, were identified. Nonandrogenic inducers of granularity were also detected. A further screen of ~25,000 small molecules led to the identification of a class of aryl-oxazoles that increased intracellular granularity in both cell lines, often leading to cell death. The most potent agents exhibited submicromolar efficacy in LNCaP and PC3 cells. (Journal of Biomolecular Screening. 2009:596-609)
Influence of post-traumatic stress disorder on pain experience in subjects on opioid maintenance therapy

Post-traumatic stress disorder (PTSD) and pain often co-occur in the same subjects. Chronic pain is a common symptom in subjects with PTSD and PTSD is a risk factor for chronic pain and the related disability. PTSD is also highly prevalent in subjects with substance abuse disorders. While a number of studies have examined interactions between PTSD and chronic pain in general populations, these studies have generally used self-reported pain instead of experimental pain testing methods. To date, little is known regarding the influence of PTSD on pain experience in subjects on opioid maintenance therapy for the treatment of opioid addiction. We tested the hypothesis that PTSD is associated with altered pain experience in subjects on opioid maintenance therapy. Specifically, we examined whether subjects with PTSD would 1) have altered sensitivity (pain tolerance and temporal pain summation) to experimental pain testing and 2) self-report higher pain severity and pain interference as compared to controls. Forty-one eligible subjects were assessed in the study. All
Sex in the New World: An Empowerment Model for HIV Prevention in Latina Immigrant Women

In 1996, nearly 60% of U.S. AIDS cases among Latinas were attributed to unprotected sex with men. Economic disadvantage, language barriers, and strong cultural gender norms regarding sex exacerbate the risk for HIV infection among Latina immigrant women. Through a collaboration among scientists and providers, this study was designed to evaluate the impact of a multifaceted empowerment program for Latina immigrant women on HIV risk behaviors. Women (N = 74) were followed for the first 6 months of their participation and attended up to nine distinct types of activities (e.g., information meetings, friendship circles, and workshops). Although the program was not developed to specifically target HIV risk behaviors, women showed significant increases in sexual communication comfort, were less likely to maintain traditional sexual gender norms, and reported changes in decision-making power. Targeting broader sociocultural issues may increase the necessary skills for Latina women to prevent HIV infection from their sexual partners. Successful collaborations between scientists and providers are critical in developing effective, community-relevant interventions.
the Environment Reaching the Limits of Genome-wide Significance in Alzheimer Disease : Back to

Supplementary material http://jama.ama-assn.org/cgi/content/full/303/18/1832/DC1 eSupplement Correction Contact me if this article is corrected. Citations Contact me when this article is cited. This article has been cited 3 times. Topic collections Contact me when new articles are published in these topic areas. Genetics, Other Neurology; Alzheimer Disease; Neurogenetics; Genetics; Genetic Disorders;
TDAS: a touch dynamics based multi-factor authentication solution for mobile devices

Purpose The use of mobile devices in handling our daily activities that involve the storage or access of sensitive data (e.g. on-line banking, paperless prescription services, etc.) is becoming very common. These mobile electronic services typically use a knowledge-based authentication method to authenticate a user (claimed identity). However, this authentication method is vulnerable to several security attacks. To counter the attacks and to make the authentication process more secure, this paper aims to investigate the use of touch dynamics biometrics in conjunction with a personal identification number (PIN)-based authentication method, and demonstrate its benefits in terms of strengthening the security of authentication services for mobile devices. Design/methodology/approach The investigation has made use of three light-weighted matching functions and a comprehensive reference data set collected from 150 subjects. Findings The investigative results show that, with this multi-factor authentication approach, even when the PIN is exposed, as much as nine out of ten impersonation attempts can be successfully identified. It has also been discovered that the accuracy performance can be increased by combining different feature data types and by increasing the input string length. Originality/value The novel contributions of this paper are twofold. Firstly, it describes how a comprehensive experiment is set up to collect touch dynamics biometrics data, and the set of collected data is being made publically available, which may facilitate further research in the problem domain. Secondly, the paper demonstrates how the data set may be used to strengthen the protection of resources that are accessible via mobile devices.
A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans

In this paper, an efficient method for automatic and accurate detection of multiple objects from images using a region similarity measure is presented. This method involves the construction of two knowledge databases: The first one contains several distinctive textures of objects to be extracted. The second one is composed with textures representing background. Both databases are provided by some examples (training set) of images from which one wants to recognize objects. The proposed procedure starts by an initialization step during which the studied image is segmented into homogeneous regions. In order to separate the objects of interest from the image background, an evaluation of the similarity between the regions of the segmented image and those of the constructed knowledge databases is then performed. The proposed approach presents several advantages in terms of applicability, suitability and simplicity. Experimental results obtained from the method applied to extract building roofs from orthophotoplans prove its robustness and performance over popular methods like K Nearest Neighbours (KNN) and Support Vector Machine (SVM).
The Effects of the Real Exchange Rate on the Trade Balance: Is There A J-Curve For Vietnam? A VAR Approach

This study employs a reduced-form VAR model to estimate trade balance’s responses to a positive shock to the real VND/USD exchange rate. For this purpose, we apply identification restrictions based on the conclusion by Krugman, Obstfeld and Melitz (2012), and on the theory of the AA-DD model to estimate the impulse response functions of the trade balance. We use a monthly data set of four endogenous variables and two exogenous variables from January 1995 to December 2012. Since the data of two endogenous variables is unavailable in monthly basis, we interpolate those series using Chow and Lin’s (1971) annualized approach from their annual series. Overall, we find that there exists a J-curve for Vietnam, and its effect lasts for 11 months. Particularly, the worsening effect on the trade balance becomes most severe in the third and the fourth months.
Effective control for an upper-body exoskeleton robot using ANFIS

In responding to the coming of an aging society, the exoskeleton robot is of focus, which provides assistance for people with locomotive problems. As the exoskeleton robot is worn by the user, the interaction in between induces several severe challenges, including adequate controller design. To deal with the nonlinearity involved during motion governing, in this paper, we take advantage of the capability of the adaptive network-based fuzzy inference system (ANFIS), and propose an ANFIS-PID controller for the exoskeleton type of robot. Especially, we apply it to a 2-DOF upper-body exoskeleton robot, HAMEXO-I, developed in our laboratory. With the proposed controller, we intend to let HAMEXO-I adaptable for a wide range of users, and able to serve for simple daily activities. Experiments are performed to demonstrate its effectiveness.
Interactive Dense 3 D Modeling of Indoor Environments

The arrival of cheap consumer depth cameras, led by Microsoft’s Kinect system, presents a huge opportunity for 3D modeling of personal spaces. While 3D indoor mapping techniques are becoming increasingly robust, they are still too brittle to enable non-technical users to build consistent and complete maps of indoor environments. This is due to technical challenges such as limited lighting, occlusion, and lack of texture, and to the fact that novice users lack a deep understanding of the underlying algorithms and their limitations. In this research, we use a prototype affordable RGB-D camera, which provides both color and depth, to build a real-time interactive system that assists and guides a user through the modeling process. Color and depth are jointly utilized to achieve robust 3D alignment. The system offers online feedback and guidance, tolerates user errors and alignment failures, and enables novice users to capture complete and dense 3D models. We evaluate our system and algorithms with extensive experiments.
Incineration of hazardous waste. A critical review.

Over the last ten years, concern over improper disposal practices of the past has manifested itself in the passage of a series of federal and state-level hazardous waste clean-up and control statutes of unprecedented scope. The impact of these various statutes will be a significant modification of waste management practices. The more traditional and lowest cost methods of direct landfilling, storage in surface impoundments and deep-well injection will be replaced, in large measure, by waste minimization at the source of generation, waste reuse, physical/chemical/biological treatment, incineration and chemical stabilization/solidification methods. Of all of the "terminal" treatment technologies, properly-designed incineration systems are capable of the highest overall degree of destruction and control for the broadest range of hazardous waste streams. Substantial design and operational experience exists and a wide variety of commercial systems are available. Consequently, significant growth is anticipated .
Improved search strategies and extensions to k-medoids-based clustering algorithms

In this paper two categories of improvements are suggested that can be applied to most k-medoids-based algorithms - conceptual/algorithmic improvements, and implementational improvements. These include the revisiting of the accepted cases for swap comparison and the application of partial distance searching and previous medoid indexing to clustering. Various hybrids are then applied to a number of k-medoids-based algorithms and the method is shown to be generally applicable. Experimental results on both artificial and real datasets demonstrate that when applied to CLARANS the number of distance calculations can be reduced by up to 98%.
Multicanonical Simulation of Communication Systems

In this paper, we introduce the multicanonical (MUC) sampling technique to efficiently simulate the performance of communication systems. MUC can be considered as a unique importance sampling technique that employs an iterative procedure to converge to the optimal biasing of the distribution of the system random sources. As one example, multicanonical sampling is applied to the performance simulation of optimum combining of multiple antennas in the presence of cochannel interference in fading channels
Gunshot Wounds Involving the Brachial Plexus: Surgical Techniques and Outcomes

This paper presents the management and outcomes for two consecutive operative series of gunshot wounds (GSWs) involving the brachial plexus. The cases were from Louisiana State University Health Sciences Center (LSUHSC) and were obtained by retrospective chart reviews. Series 1 includes patients with injuries managed between 1968 and 1980 and series 2, from 1981 to 1998. Pre- and postoperative motor function was assessed using the LSUHSC grading system. The outcomes for each surgical technique for each series are presented. Fewer cases of brachial plexus elements injured by GSWs in series 2 may be due to decreased firearm-related injuries between 1993-1997, i.e., 39,595 versus 32,436 deaths, respectively. The graft repair increase in series 2 may have been the result of more severe injuries, since documented trends between 1971 and 1997 show the use of larger caliber bullets. This paper shows that with the outlined management and surgical techniques, surgery on certain GSWs of the brachial plexus is worthwhile.
Phosphate fertilizers’ domestic price movement in Vietnam

This research analyses long-run and short-run co-movements among the three variables “international prices,” “domestic prices,” and “import prices” of phosphate fertilizers using co-integration test, Granger causality test, and VEC model. The findings revealed that the domestic phosphate fertilizer market in Vietnam has well integrated into the international phosphate market since shifts in the domestic phosphate fertilizer price have been in long-run equilibrium with those in the international phosphate fertilizer price. Furthermore, changes in the domestic phosphate fertilizer price were brisker than those in the import price and were uncorrelated with the import prices.
A1ATVar: a relational database of human SERPINA1 gene variants leading to α1‐antitrypsin deficiency and application of the VariVis software

We have developed a relational database of human SERPINA1 gene mutations, leading to α1‐antitrypsin (AAT) deficiency, called A1ATVar, which can be accessed over the World Wide Web at www.goldenhelix. org/A1ATVar. Extensive information has been extracted from the literature and converted into a searchable database, including genotype information, clinical phenotype, allelic frequencies for the commonest AAT variant alleles, methods of detection, and references. Mutation summaries are automatically displayed and user‐generated queries can be formulated based on fields in the database. A separate module, linked to the FINDbase database for frequencies of inherited disorders allows the user to access allele frequency information for the three most frequent AAT alleles, namely PiM, PiS, and PiZ. The available experimental protocols to detect AAT variant alleles at the protein and DNA levels have been archived in a searchable format. A visualization tool, called VariVis, has been implemented to combine A1ATVar variant information with SERPINA1 sequence and annotation data. A direct data submission tool allows registered users to submit data on novel AAT variant alleles as well as experimental protocols to explore SERPINA1 genetic heterogeneity, via a password‐protected interface. Database access is free of charge and there are no registration requirements for querying the data. The A1ATVar database is the only integrated database on the Internet offering summarized information on AAT allelic variants and could be useful not only for clinical diagnosis and research on AAT deficiency and the SERPINA1 gene, but could also serve as an example for an all‐in‐one solution for locus‐specific database (LSDB) development and curation. Hum Mutat 0,1–6, 2008. © 2008 Wiley‐Liss, Inc.
Speaker adaptive joint training of Gaussian mixture models and bottleneck features

In the tandem approach, the output of a neural network (NN) serves as input features to a Gaussian mixture model (GMM) aiming to improve the emission probability estimates. As has been shown in our previous work, GMM with pooled covariance matrix can be integrated into a neural network framework as a softmax layer with hidden variables, which allows for joint estimation of both neural network and Gaussian mixture parameters. Here, this approach is extended to include speaker adaptive training (SAT) by introducing a speaker dependent neural network layer. Error backpropagation beyond this speaker dependent layer realizes the adaptive training of the Gaussian parameters as well as the optimization of the bottleneck (BN) tandem features of the underlying acoustic model, simultaneously. In this study, after the initialization by constrained maximum likelihood linear regression (CMLLR) the speaker dependent layer itself is kept constant during the joint training. Experiments show that the deeper backpropagation through the speaker dependent layer is necessary for improved recognition performance. The speaker adaptively and jointly trained BN-GMM results in 5% relative improvement over very strong speaker-independent hybrid baseline on the Quaero English broadcast news and conversations task, and on the 300-hour Switchboard task.