Miracle-dz/UniFAR-FTUs huggingface dataset:
Lipoic Acid Attenuates Cholestasis Induced Cerebral Injury in Rats

Cholestasis is characterized by an abnormal accumulation of bile acids, which is caused by defectiveness in the process of bile acid transport. It is believed that oxidative stress is a likely mediator for cholestatic damage and antioxidant therapy is a recommended therapeutic strategy. The aim of this study was to evaluate protective effect o alpha lipoic acid as an anti oxidant agent on cerebral injury after bile act ligation in rats. forty five adult male wistar rats were randomly assigned to three groups each containing fifteen rats as follows: sham operation (SO) (control), bile duct ligation (BDL), and BDL+LA (25mg/kg). After fourteen day’s cerebral tissue sampled for pathologic and biochemical studies. Levels of SOD and GPx antioxidant enzymes were higher in BDL+LA group comparing to BDL group significantly, histologic damage and MDA levels were higher in BDL group comparing to BDL+LA group significantly (P<0.05). In our study LA treatment in BDL rats improved cellular SOD and GPx levels and reduced MDA levels in BDL+LA group comparing to BDL group. The findings of our present study showed that LA, with its potent free radical scavenging and antioxidant properties, seems to be a highly promising agent in protecting cerebral tissue against oxidative damage. [Mohammad Mehdi Hosseinian Zakaria, Babak Hajipour, Mohammad Taghizadieh, Ghafour Mousavi, Ali Khodadadi. Lipoic Acid Attenuates Cholestasis Induced Cerebral Injury in Rats. Life Sci J 2013;10(5s):539-545] (ISSN:1097-8135). http://www.lifesciencesite. com. 95
Correlation Between Volume of Root Canal , Cultivable Bacteria , B a c t e r i a l C

found in primary endodontic infection (PEI) with the volume of root canal determined by using Cone Beam Computed Tomography (CBCT); and to evaluate the bacterial diversity correlating with clinical features. Twenty patients with PEI were selected and clinical features were recorded. The volume (mm3) of root canal was determined by CBCT analysis. Root canal samples were analyzed by using kinetic LAL-assay test to determine the levels of endotoxins and anaerobic technique to determine the bacterial count (CFU/mL). DNA was extracted from all samples to determine bacterial diversity and quantified by using Checkerboard-DNA-DNAHybridization. Culturable bacteria and endotoxins were detected in 100% of the root canal samples. Linear regression analysis revealed a correlation between root canal volume and presence of anaerobic bacteria (p<0.05). Positive correlations were found between bacteria species and presence of different clinical features (p<0.05). After grouping the bacteria species into bacterial complexes, positive associations were found between green, orange and red complexes with presence of sinus tract (p<0.05). This clinical study revealed that larger root canals hold higher levels of culturable bacteria in PEI. Thus, the interaction of different virulent bacteria species in complexes seems to play an important role in the development of clinical features. Correlation Between Volume of Root Canal, Cultivable Bacteria, B a c t e r i a l C o m p l e x e s a n d Endotoxins in Primary Infection
Wireless Sensor Network Storage with Light Weight File System using Update Logic for Cloud Interface

This paper focuses on a wireless sensor network used for an intelligent storage technique for the data acquisition process. The data acquired from the various sensors are stored locally with timestamp using the update logic in this work. The rapid development of IoT enables the embedded system to send/receive the information across the two remote entities. In the multi-sensor wireless sensor nodes, the data are usually acquired and stored in a structured block file I/O. This data collection is done periodically through multi-sensor wireless sensor nodes and file system is updated in block level. Then, the wireless sensor data are organized without duplication between successive data collection. But in Hadoop Distributed File System (HDFS), the block size is fixed with 64MB. Whereas in other implementation has File system concept with successive redundant and this would significantly increase the file size. The proposed update logic flat file system is a variable with light weight feature. Our proposed logic with Update logic minimizes the network contention by the lightweight file without successive redundant information.
The use of Praat in corpus research

Praat is an open-source cross-platform computer program for analysing, synthesizing, and manipulating speech and other sounds, and for creating publication-quality graphics. This chapter first discusses the rationale behind Praat’s design decisions, and describes how to record, view, and analyse sounds. It then discusses Praat’s more specific tools for corpus study, namely annotation and the Corpus window.
Ja n 20 06 Vibrational spectrum of the H + 5 molecule using quantum Monte Carlo

In this article we present a caracterization of the vibrational spectrum of the H+5 molecule using the correlation function quantum Monte Carlo (CFQMC) method and a genetic algorithm study of the topology of the potential energy surface used in this work. The vibrational modes associated with the H+3 -H2 torsion and stretching posses very flat minima. As a consequence the fundamental frequencies corresponding to these modes are poorly described in the harmonic approximation. The vibrational frequencies obtained in this work are in good agreement with the available experimental data as well as other computational methods found in literature. In our genetic algorithm study of the potential energy surface using cartesian coordinates we have found some unexpected minima. A careful analysis shows that some of these minima are described by the same curviliniar coordinates in which the potential is described. However, they represent nonequivalent molecular geometries.
Behavior and Technological Identity During the Middle Paleolithic : An Issue of the Scale of Analysis ? Examples from the Paris Basin ( France ) during the early

Abstract: This article discusses the results obtained during doctoral research by the author defended at the end of 2009. This work focused on the Middle Paleolithic in France and on the possibility of identifying specific cultural dynamics. Its objective was to explain the impact of the choice of analytical tools used to study the Middle Paleolithic – and in particular the scales of analyses applied – on the grouping of industries and thus on the interpretations concerning human occupations that follow from this. To do so, ten lithic assemblages from the Paris Basin during the Early Weichselian were analyzed using an original model enabling comparison of the assemblages using four different scales of analysis. Several levels of interpretation could thus be demonstrated, revealing multiple results. While the assemblages are quite similar at a general scale of analysis, they are shown to be very different at a fine scale, at which five groups could be distinguished. Aided by cultural geography, we propose the hypothesis that these groups may reflect distinct technological traditions, included within similar cultural areas.
The Effect of Working Hours on Health I Inés Berniell

Does working time affect workers’ health? We study this question in the context of a French reform which reduced the standard workweek from 39 to 35 hours, at constant earnings. Our empirical analysis exploits variation in the reduction of working time across employers, which was driven by the institutional features of the reform and thus exogenous to workers’ health. We find that longer working hours increase smoking and decrease self-reported health, and that these impacts are concentrated among bluecollar workers. In contrast, white-collar workers’ body mass index increases with hours worked.
Too Big to Fail: Larger Samples and False Discoveries

The Internet presents great opportunities for research about information technology, allowing IS researchers to collect very large and rich datasets. It is common to see research papers with tens or even hundreds of thousands of data points, especially when reading about electronic commerce. Large samples are better than smaller samples in that they provide greater statistical power and produce more precise estimates. However, statistical inference using p-values does not scale up to large samples and often leads to erroneous conclusions. We find evidence of an over-reliance on p-values in large sample IS studies in top IS journals and conferences. In this commentary, we focus on interpreting effects of individual independent variables on a dependent variable in regression-type models. We discuss how p-values become deflated with a large sample and illustrate this deflation in analyzing data from over 340,000 digital camera auctions on eBay. The commentary recommends that IS researchers be more conservative in interpreting statistical significance in large sample studies, and instead, interpret results in terms of practical significance. In particular, we suggest that authors of large-sample IS studies report and discuss confidence intervals for independent variables of interest rather than coefficient signs and p-values. We also suggest taking advantage of a large dataset for examining how coefficients and p-values change as sample size increases, and for estimating models on multiple subsamples to further test robustness.
Computing Spatial Features to Allocate Collision-free Motion-paths for Tele-presence Avatars

Recently, indoor-intelligent services like “Tele-presence” have made quite an advancement. Therefore, to completely 1) understand the diverse indoor environment, 2) efficiently calculate similarity for semantic spaces and 3) for defining an efficient path movement for an augmented reality-based Avatar; we propose spatial features computation, graphical representation and Topology-based graph-similarity measure for complex domains to overcome the limited visibility of an Avatar. Thus, collision with the surrounding objects in a given indoor-space can be avoided. This study begins by securing spatial features of objects, e.g., furniture, doorways, etc., of an indoor environment from an FBSMAP (Function-Behaviour-Structure Map). Then, we establish a method for defining similarity for locations and paths.
Current challenges and methodological issues of functional safety and security management in hazardous technical systems

Celem artykulu jest zidentyfikowanie problemow oceny ryzyka w kontekście stosowania systemow elektrycznych / elektronicznych / programowalnych elektronicznych (E/E/PE) z uwzglednieniem aspektow bezpieczenstwa funkcjonalnego i zabezpieczen (ochrony). Zadaniem rozwiązan bezpieczenstwa funkcjonalnego jest efektywne redukowanie ryzyka wychodząc z poziomu nieakceptowanego. Ryzyko jest definiowane jako kombinacja prawdopodobienstwa wystąpienia szkody i krytyczności tej szkody. Ochrona polega na zabezpieczeniu szeroko rozumianych aktywow, wlączając w to systemy E/E/PE lub przyrządowe systemy bezpieczenstwa SIS, od potencjalnych zagrozen, w tym cyberatakow. W artykule przedstawia sie aktualne wyzwania i problemy metodyczne integrowania aspektow bezpieczenstwa funkcjonalnego i zabezpieczen (ochrony) w systemach programowalnych do sterowania i zabezpieczania przemyslowych obiektow i systemow podwyzszonego ryzyka.
Association of Vitamin D and Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus

With the rapid increase in the incidence of diabetes mellitus (DM) in recent years, the complications related to diabetes have become a larger health problem. Inadequately controlled diabetes precipitates various long-term microvascular (blindness, neuropathy and n e p h r o p a t h y ) a n d m a c r o v a s c u l a r (cardiovascular and stroke) complications (1, 2) which form the leading cause of morbidity and mortality in diabetic patients worldwide (1). Diabetic retinopathy (DR) being one of the most prevalent complication of diabetes, is considered as a major culprit of blindness globally (1, 3). DR is also the most common cause of non-traumatic visual loss in the working-age population. It has been estimated that the worldwide prevalence of DR was 93 million (35%) and the prevalence of vision-
Enhanced Map-Based Indoor Navigation System of a Humanoid Robot Using Ultrasound Measurements

During recent years, walking humanoid robots have gained popularity from wheeled vehicle robots in various assistive roles in human’s environment. Self-localization is a necessary requirement for the humanoid robots used in most of the assistive tasks. This is because the robots have to be able to locate themselves in their environment in order to accomplish their tasks. In addition, autonomous navigation of walking robots to the pre-defined destination is equally important mission, and therefore it is required that the robot knows its initiate location precisely. The indoor navigation is based on the map of the environment used by the robot. Assuming that the walking robot is capable of locating itself based on its initiate location and the distance walked from it, there are still factors that impair the map-based navigation. One of them is the robot’s limited ability to keep its direction when it is walking, which means that the robot is not able to walk directly from one point to another due to a stochastic error in walking direction. In this paper we present an algorithm for straightening the walking path using distance measurements by built-in sonar sensors of a NAO humanoid robot. The proposed algorithm enables the robot to walk directly from one point to another, which enables precise map-based indoor navigation.
PATH TO SUSTAINED USAGE: A MODEL FOR LONG TERM EXPERIENCE IN TECHNOLOGICAL PRODUCTS

Such an identiﬁcation can highlight a signiﬁcant relation between user’s holistic perceptions with products. According to Hassenzahl and Tractinsky (2006), inherent emotional states refer to universal human needs that are satisﬁed by the hedonic aspects of UX, yet do not necessarily have to accommodate functional/pragmatic qualities of the products. Moreover, the empirical studies showed that hedonic and pragmatic qualities both promote the desirability and attractiveness of products (Cila & Erbug, 2008; Has-senzahl, 2003, 2007; Schrepp et al., 2006). Their inﬂuence relatively changes in relation to the context of evolution and impulsive orientation of the user (Hassenzahl, 2008). Currently, user experience literature has evolved from solely understanding the emotions towards products, but has kept the dynamism of emotions and turned those into a long-term positive experience (Desmet & Hassenzahl, 2012). Thus, understanding people’s experience in long-term usage can lead designers to turn an experience into a ‘happy experience’. The study of Chitturi et al. (2008) showed that the impact of hedon-ABSTRACT Happiness is one of the major inﬂuences in what makes people use products, and what makes those products an important part of daily life. What drives these aspects, some arisen from personal appraisement and some directly related to the product qualities, are important for designers, as the experiences designers form tend to affect these aspects heavily. Driven from this idea, in this paper, an exploration on the evolution of positive user experience with technological products was conducted. We asked users to think about the technological products they enjoy the most, how their experiences changed over time, and what makes them still use the product. Different qualities regarding their experience were found, some human-related, some product-related, and the relations between these qualities were looked upon further in depth. The result presented itself as a theoretical model to achieve sustained usage of technological products.
Manufacture and Characterization of Additively Manufactured Ceramic Electromagnetic Structures

Additive Manufacturing (AM, also known as 3D printing) can produce novel three-dimensional structures using low-loss dielectric materials. This enables the construction of dielectrics with complex shapes that enable innovative microwave applications such as resonators, filters, and metamaterial lenses. This thesis addresses the production and characterization of cellular structures of various designed densities created with a low loss ceramic material, alumina (aluminum oxide), via vat photopolymerization. The permittivity of these printed structures is variable over roughly an octave, with a range of relative permittivites from 1.78 to 3.60, controlled via part geometry. Two additional materials, ferrite and nickel, have been explored for inclusion within these dielectric structures to enable the production of multi-material electromagnetic structures with conductive, magnetic, and dielectric elements. Manufacture and Characterization of Additively Manufactured Ceramic Electromagnetic Structures
Algorithm Feasibility on IoT Devices with Memory and Computational Power Constraints

Internet of Things is a subject of much interest as well as, in last couple of years, safety of the IoT systems is a field of remarkable research activities. Shared verification between IoT devices as well as IoT web servers is a fundamental part of secure IoT systems. Solitary password-based verification mechanisms, which are commonly used, are vulnerable to side-channel and also dictionary attacks. In this paper, we present a multi-key (or multi-password) based shared verification device. In our strategy, the common key in between the IoT server as well as the IoT device is called protected vault, which is a collection of equal sized tricks. First components of the safe vault are shared in between the web server as well as the IoT device and components of the safe and secure vault modification after every successful communication session. We have implemented this device on an Arduino device to confirm our algorithm is practical on IoT devices with memory as well as computational power constraints. Keyword: IoT Device Authentication, IoT Security, Secure Vault
A New Framework for Representing , Rendering , Editing , and Animating Type

In this paper, we present a new framework for representing, rendering, editing, and animating character glyphs. Our framework is based on Adaptively Sampled Distance Fields (ADFs), which provide an ideal computational substrate for performing these operations. We introduce higher-order ADFs and describe why this succinct representation of 2-dimensional shapes strikes the optimal balance between memory use and computational load. We present a new antialiasing method, which exploits the distance field to achieve superior rendering quality for both static and animated type. We describe how perceptual rules used by professional type designers to create hand-tuned glyphs can be automatically applied during rendering in this framework, thus mitigating the labor-intensive process of manual hinting. For designing fonts within our framework, we provide an editor with a seamless interface between curve-based, stroke-based, and component-based design paradigms. Finally, we show how the distance field can be exploited to simulate interactions and behaviors that are difficult to compute directly from outline-based representations, thereby enabling creative design with animated type, some examples of which are provided.
AAPOR Report on Big Data

In recent years we have seen an increase in the amount of statistics in society describing different phenomena based on so called Big Data. The term Big Data is used for a variety of data as explained in the report, many of them characterized not just by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, the way in which they are collected, and disseminated are fundamental. The change constitutes a paradigm shift for survey research.
Role Play in Blended Learning: A Case Study Exploring the Impact of Story and Other Elements.

Role play is an increasingly popular technique in tertiary education, being student centred, constructivist and suitable for a range of subject areas. The choice of formats is wide open, with options ranging from the traditional face to face performance through to multi-user online computer games. Some teachers prefer to take advantage of features of both online and face to face formats and offer a blended form. This case study describes an innovative blended role play in which the online component plays a small but important part. The findings show that decisions on not only how to make the best use of technology but also how to design and facilitate a role play can have a profound effect on the creation of an engaging first-person story from which powerful learning can be drawn-in this case, learning outcomes including deep insights into strengths and weaknesses of participants' personal change management styles.
Bayesian non-linear matching of pairwise microarray gene expressions

In this paper, we present a Bayesian non-linear model to analyze matching pairs of microarray expression data. This model generalizes, in terms of neural networks, standard linear matching models. As a practical application, we analyze data of patients with Acute Lymphoblastic Leukemia and we find out the best neural net model that relates the expression levels of two types of cytogenetically different samples from them.
Autonomous Quadrotor for the 2017 International Aerial Robotics Competition

Unmanned Aerial Vehicles (UAV) are becoming more popular for both professional and casual uses, but are restricted to open areas and require GPS for navigation. Vehicles capable of flying in environments without relying on GPS will pave the way toward redefining currently outdated and expensive methods of structural inspection, search and rescue, and law enforcement operations that often take place in areas with limited GPS availability. Michigan Autonomous Aerial Vehicles (MAAV) designs and builds lightweight quadrotor UAVs capable of stable, autonomous flight without GPS. MAAV’s vehicle will compete in the 2017 International Aerial Robotics Competition (IARC) where it will demonstrate its ability to autonomously manage a herd of ground vehicles in an open environment. Using a combination of control, computer vision, and path planning algorithms, it will herd ground robots over the goal line in the required time.
Maximum-likelihood training of the PLCG-based language model

In Van Uytsel et al. (2001) a parsing language model based on a probabilistic left-comer grammar (PLCG) was proposed and encouraging performance on a speech recognition task using the PLCG-based language model was reported. In this paper we show how the PLCG-based language model can be further optimized by iterative parameter reestimation on unannotated training data. The precalculation of forward, inner and outer probabilities of states in the PLCG network provides an elegant crosscut to the computation of transition frequency expectations, which are needed in each iteration of the proposed reestimation procedure. The training algorithm enables model training on very large corpora. In our experiments, test set perplexity is close to saturation after three iterations, 5 to 16% lower than initially. We however observed no significant improvement of recognition accuracy after reestimation.
PROCESSING AND RECYCLING OF A THERMOPLASTIC COMPOSITE FIBRE/PEEK AEROSPACE PART

This work presents an alternative way of recycling typical thermoplastic composites (TPC) used in aerospace industry with high contents of carbon fibres. Through a cradle to cradle procedure developed by the authors, TPCs become good candidates for replacing thermoset composites (TSC) and metallic complex parts in aerospace applications, not only due to their low density, excellent mechanical properties and processability, but also regarding the new perspective of recycling that offers a novel grinding process known as the electrodynamical fragmentation.