Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment of patients with COPD and recurrent exacerbations: the role of infection and inflammation

Exacerbations of COPD represent an important medical and health care problem. Certain susceptible patients suffer recurrent exacerbations and as a consequence have a poorer prognosis. The effects of bronchial infection, either acute or chronic, and of the inflammation characteristic of the disease itself raise the question of the possible role of antibiotics and anti-inflammatory agents in modulating the course of the disease. However, clinical guidelines base their recommendations on clinical trials that usually exclude more severe patients and patients with more comorbidities, and thus often fail to reflect the reality of clinicians attending more severe patients. In order to discuss aspects of clinical practice of relevance to pulmonologists in the treatment and prevention of recurrent exacerbations in patients with severe COPD, a panel discussion was organized involving expert pulmonologists who devote most of their professional activity to day hospital care. This article summarizes the scientific evidence currently available and the debate generated in relation to the following aspects: bacterial and viral infections, chronic bronchial infection and its treatment with cyclic oral or inhaled antibiotics, inflammatory mechanisms and their treatment, and the role of computerized tomography as a diagnostic tool in patients with severe COPD and frequent exacerbations.
Geographically patterned variation in diapause and its relationship to other climate-associated phenotypes and genotypes of Drosophila americana

To declare a trait adaptive, it is necessary to show heritability and beneficial fitness effects of a phenotype. Association between phenotypic and environmental variance is insufficient to identify adaptive traits because non-selective forces can build phenotype-environment associations without beneficial fitness effects. However, if the same phenotype-environment associations occur in independent lineages subject to similar environmental stresses, the traits shared among lineages may be more likely to have beneficial fitness effects and are likely targets for further study of adaptation. I tested the hypothesis that, among species sharing similar climate and habitat distributions, shared traits are candidates for adaptations to shared selective pressures. I used Drosophila americana as a model because it is endemic to temperate environmental conditions similar to those of other wellstudied populations and species of Drosophila and has other qualities that make it amenable to studies of putative adaptations. These include an ancient association with cold climates and previously defined regions of clinally distributed genetic variation maintained by selection. I demonstrated an association between reproductive diapause and clinally distributed genetic variation in D. americana. The fused X-4 chromosome is sufficient to increase the probability of diapause in D. americana, establishing heritability of the trait and linking genetic variation under selection to a phenotype.
Current State of Knowledge in Microbial Degradation of Polycyclic Aromatic Hydrocarbons (PAHs): A Review

Polycyclic aromatic hydrocarbons (PAHs) include a group of organic priority pollutants of critical environmental and public health concern due to their toxic, genotoxic, mutagenic and/or carcinogenic properties and their ubiquitous occurrence as well as recalcitrance. The increased awareness of their various adverse effects on ecosystem and human health has led to a dramatic increase in research aimed toward removing PAHs from the environment. PAHs may undergo adsorption, volatilization, photolysis, and chemical oxidation, although transformation by microorganisms is the major neutralization process of PAH-contaminated sites in an ecologically accepted manner. Microbial degradation of PAHs depends on various environmental conditions, such as nutrients, number and kind of the microorganisms, nature as well as chemical property of the PAH being degraded. A wide variety of bacterial, fungal and algal species have the potential to degrade/transform PAHs, among which bacteria and fungi mediated degradation has been studied most extensively. In last few decades microbial community analysis, biochemical pathway for PAHs degradation, gene organization, enzyme system, genetic regulation for PAH degradation have been explored in great detail. Although, xenobiotic-degrading microorganisms have incredible potential to restore contaminated environments inexpensively yet effectively, but new advancements are required to make such microbes effective and more powerful in removing those compounds, which were once thought to be recalcitrant. Recent analytical chemistry and genetic engineering tools might help to improve the efficiency of degradation of PAHs by microorganisms, and minimize uncertainties of successful bioremediation. However, appropriate implementation of the potential of naturally occurring microorganisms for field bioremediation could be considerably enhanced by optimizing certain factors such as bioavailability, adsorption and mass transfer of PAHs. The main purpose of this review is to provide an overview of current knowledge of bacteria, halophilic archaea, fungi and algae mediated degradation/transformation of PAHs. In addition, factors affecting PAHs degradation in the environment, recent advancement in genetic, genomic, proteomic and metabolomic techniques are also highlighted with an aim to facilitate the development of a new insight into the bioremediation of PAH in the environment.
Development of an efficient human hepatocyte culture platform for assessing novel therapeutic efficacy against Plasmodium liver parasites

viii Chapter One: Introductions 1 Malaria—An Ancient and Global Public Health Problem 1 A Brief History of Discovery 3 Plasmodium Taxonomy and Evolutionary History 4 The Plasmodium Life Cycle. 8 Current Prophylaxis and Standard of Care 14 Control and Eradication Efforts 16 Vector Control 16 Drugs 17 Vaccines 18 Liver Stage Drug and Vaccine Development. 20 Need for a More Efficient in vitro Plasmodium Liver Model. 22 Introduction to in vitro Liver Models 22 Role of Liver Models in Public Health. 22 Animal-Free ADMET. 23 Cytochrome P450 Enzymes. 25 Infectious Liver Disease Culture and Research. 27 Architecture of the Liver 27 Zone-Specific Liver Physiology. 29 Cell Types of the Liver. 29 Hepatic Cell Resources for Research. 31 Considerations for Designing in vitro Liver Models. 34 Advanced Cell Culture Platform Fabrication 38 Current Progress: Static Liver Systems 39 Current Progress: Perfused Liver Systems 42 Comparing and Contrasting Components and Systems 42 Tailoring Liver System for Experimental Question 44 Focus of Study 44 References 49
Instrumentation of Raman Spectrometry for Acquisition of Molecular Vibration Structure

Determining the structure of an organic compound are mainly based on the physical and chemical properties, because molecules are so small it is so hard to determine the molecular structure of a compound. In this study, a simple spectrometer is developed through instrumentation and control to perform acquisition of the molecular vibrations and determine the Raman shift in wavenumber of a sample. Because the vibration phenomenon of a molecular bond can be investigated under the Raman spectrum, a charged coupled device (CCD) was used in the instrumentation together with a diffraction grating of 1000lines/mm. The spectrometer built using a charged coupled device (CCD) array is capable of detecting ultra-violet, visible, and near-infrared spectrum. In the near-infrared region the identifying marks of the samples is recorded with energy spectral density that describes the optical wavelength and peaks in the IR spectrum. Using the reaction in the saccharomyces cerevisiae in water, the energy spectral density is monitored and shows that 81.52% of light is absorbed by the given sample during the reaction with wavenumber of 605.75cm-1 which suggest that the molecular vibration is occurring at the fingerprint region under the vibrational spectrum, and light absorption becomes weaker as saccharomyces cerevisiae stop producing carbon dioxide in water with 8.39% but with traces of chemical compounds at 623.14cm-1 Raman shift in wavenumber.
An Anthropomorphic Robust Robotic Torso for Ventral/Dorsal and Lateral Motion With Weight Compensation

The human torso is known to be highly versatile and dexterous in terms of motion capabilities and dynamic performance. Motivated by the human counterpart, we present the development of a new anthropomorphic robotic torso with comparable workspace, torques, velocities for running, and high level of mechanical robustness. In order to support large loads in ventral and lateral direction a parallel structure of actuation with tendons and a weight compensation via a spring mechanism is introduced into the system. That way, motors can be considerably downsized, which is, in turn, beneficial in terms of the dynamic characteristics of the torso. Robustness to withstand severe impacts is achieved through a clutch-based mechanism in the tendon pulleys. The entire mechanism is experimentally validated in various experiments and will be integrated as component of the compliant humanoid robot David of the DLR.
Characterisation of the roles of Poz1 and Stn1 at Schizosaccharomyces pombe telomeres

Telomeres protect the ends of chromosomes from the activity of DNA repair machinery and provide a solution to the end-replication problem. In humans, the core protein complex located at telomeres is known as shelterin and consists of six protein subunits. Although variation is seen in the telomeric complex between species, in fission yeast the complex has notable similarities to that of humans. Separately to shelterin, the CST complex (Cdc13/Stn1/Ten1) is conserved in budding yeast, plants and mammals and is thought to negatively regulate telomerase, in addition to being required for telomere protection. However, unlike Stn1 and Ten1, Cdc13 has not yet been identified in fission yeast. Poz1 is a bridging molecule equivalent to TIN2 in human shelterin, which links the Taz1-Rap1 and the Pot1-Tpz1-Ccq1 sub-complexes, respectively bound to double- and single-stranded DNA at telomeres. Poz1 is required for the regulation of telomerase activity, and it has been hypothesised that it might do so by playing a structural role in the switching of telomeres from an open to a closed state. In this study, a reverse-2-hybrid approach was used to generate Poz1 alleles unable to interact with Rap1 or Tpz1 specifically. These alleles were subjected to phenotypic and biochemical analysis which indicated that neither individual interaction is sufficient to maintain telomere homeostasis. With telomere lengths similar to a Poz1 deletion, it is proposed that negative regulation cannot occur without the ability to form a closed complex. Given that Cdc13 is currently the only missing component in fission yeast, a second study was initiated aiming to identify a homologue by yeast-2-hybrid screening of a cDNA library, using Stn1 and Ten1 as baits. However, this approach did not yield any positive candidates. In an alternative approach, Stn1 temperature-sensitive (ts) alleles were generated and characterised. These were used to screen a genomic library for suppressors of the Stn1 ts phenotype. Several candidates were identified that require further examination while the ts allele analysis indicated that telomeres are lost in their entirety at non-permissive temperatures and that survivors of this process did so by chromosome circularisation, similar to Pot1 mutants.
Augmented Reality Mobile Application for Museum: A Technology Acceptance Study

The tourism sector in Malaysia is reported for losing its global competitiveness when the nation missed its tourism targets recently. Mirrored at the state level, the tourism performance of Melaka, a heritage city inscribed by the UNESCO, is also experiencing similar downward trend. The museums, which play a pivotal role in showcasing the local culture and history, have seen decreasing number of visitors. Inspired by Tourism 4.0, many museums are now using digital technologies to enrich visitors’ experience, such as augmented reality (AR). This is because the tourists are now becoming more tech-savvy and expecting culture and heritage to be presented lively rather than exhibited in dusty glass boxes. In the “When History Comes Alive” Project, an AR mobile app was developed for the People’s Museum in Melaka. Although tourism studies have widely discussed the managerial implications of AR, user’s acceptance of AR in the tourism context is still in its infancy. Hence, this study aimed to examine the factors affecting museum visitors’ behavioural intention to use the AR mobile app. A survey was conducted among 120 museum visitors. The findings showed that playfulness expectancy, content relevance expectancy, performance expectancy, effort expectancy, and social influence positively affect the respondents’ behavioural intention to use the AR mobile app with a high explanatory power of 61.2%. Significant managerial and practical implications to the developers of AR mobile app, tourism businesses and policy makers are highlighted in this paper. The limitations of the study and suggestions for future studies are also addressed.
Distributed Joint Mapping and Registration with Limited Fields-of-View

The interest of this paper is to fuse maps, expressed in different local coordinates, of multiple mobile agents with limited fields-of-view, without knowledge of the relative poses among agents. To this end, the map is modeled as a multi-object Poisson process and a recently developed approach, named Cauchy-Schwarz fusion (CSF), is adopted. In order to perform calibration among local coordinates, the information-theoretic interpretation of CSF is exploited to build a suitable map discrepancy to be minimized with respect to the drift and orientation parameters. A multi-hypothesis method is adopted in order to efficiently solve the resulting optimization problem.
A RISC-V based hardware accelerator designed for Yolo object detection system

You only look once (YOLO) is a state-of-the-art, real-time object detection system. A hardware accelerator of YOLO is presented using the open source RISC-V core ROCKET as its controller. Extended customized instructions based on RISC-V were proposed for this accelerator. The hardware design was verified using Xilinx Virtex-7 FPGA VC709 and the results show that the accelerator costs about 400ms to finish the Yolo algorithm and is supposed to have higher speed with more computation modules.
Design and Simulation of Multiple Quantum well based InGaN/GaN Light Emitting Diode for High power applications

The electrical and optical characteristics of InGaN/GaN based light emitting diodes (LEDs) having V-shaped, trapezoidal and U-shaped quantum well is simulated using TCAD Silvaco software. Comparison of different well shape is studied and simulation results shows that the device with V-shaped quantum well has superior performance in terms of Internal Quantum Efficiency of 80% and optical power of 120 mW for a maximum current of 200 mA when compared with U-shaped and trapezoidal well.
Preliminary Investigation for Tamil cine music deployment for mood music recommender system

Music, as all other art forms, has been used primarily as a vehicle for conveying ideas, experiences and emotions in a stylistic manner. It thus makes sense to attempt to categorize a library of music into either its style or the emotions expressed in the tracks. In this work, preliminary results of the signal processing module and machine learning module with four songs in detail and with a database of 100 songs is carried out. The signal processing algorithms employed are Mel Frequency Cepstral Coefficients and beat Histogram. Human emotions were classified based on Thayers model into Happy, Sad, Angry and Relaxed. The Machine Learning classification algorithms employed are Decision Tree Classifier and Random Forest Classifier. A low accuracy suggests improvement in the features and better machine learning algorithm before porting to Android for development as a Mobile App.
Robust Control Design for DFIG based Wind Turbine under Voltage Sags

Recently, grid stability and power generation are key issues. Due to the high penetration of wind power, grid faults recovery behaviors of a wind turbine have significant effect on power system stability. Grid voltage faults cause voltage fluctuations and harmonic current in DC-linked capacitor of Doubly Fed Induction Generator (DFIG) based Wind Turbines (WTs), which degrade the performance and reliability of capacitor in voltage source converters. However, robust controller is required to provide stable DC-linked voltage. In this paper Adaptive Proportional Integral (API) algorithm is proposed for Grid Side Converter (GSC) of DFIG based WTs which mitigate voltage fluctuations and harmonic current in DC-linked capacitor. Furthermore, it also enhances active and reactive power quality injected to the grid. For validation of the proposed control algorithm, MATLAB/Simulink simulation of 2MW DFIG model has been considered and results are compared with conventional used Proportional Integral (PI) controller. Total Harmonic Distortion (THD) further validate and analyze the effectiveness of proposed controller by comparing it with the conventional PI controller.
Research and Performance Evaluation of Atomic Clock in GPS Timing Terminal

In order to evaluate the performance of the atomic clock on timing terminal more reasonably, the frequency stability analysis of the rubidium atomic clock was carried out under the same experimental conditions, and the definitions of Allan variance and Hadamard variance were expounded. Comparing their applicability for frequency stability through experimental simulation data and further proposed a technique of the adaptive frequency difference calibration for the taming experiment of the rubidium atomic clock. The results show that Hadamard variance is more suitable for analyzing long-term frequency stability of rubidium atomic clock. The frequency stability after taming is increased by an order of magnitude, and the accuracy of the output 1PPS (1Pulse Per Second) signal is within 10ns. Therefore, the tamed rubidium atomic clock can be better used as a time-frequency reference and have good applicability in navigation and timing.
Inhibitors of Online Shopping Amongst Higher Education Students

Given the dearth of research on online shopping in Mauritius and the intense competition amongst online shopping operators, enticing new customers and retaining existing ones is key for the survival of any online shopping business. This research examines the relationship between the inhibitors of adoption and behavioural intention to use online shopping amongst Mauritian consumers. Using a crosssectional survey, inhibitors of adoption were examined through a positivist lens. Data from a purposive sample of 268 respondents shows that online shopping are used by young adults, who are part of the Generation Y era. Perceived usefulness is a significant predictor of online shopping adoption while perceived anxiety and resistance to change are negatively related to behavioural intention, thus inhibiting online shopping adoption. These results also give credence to the dual factor theory and demonstrate that predictors of use have a stronger effect on intention to adopt online shopping than inhibitors.
A Smart Sensor-based Gesture Recognition System for Media Player Control*

With the rapid advancement of technology in the current era, mobile and wearable devices have attracted the attention of end users. Smartwatches available in the market have embedded movement sensors whose potential applications have not been explored to a great extent. This study proposes a gesture recognition module using a smart sensor Metawear which can potentially be used to control various functions of a media player. Inertial sensors data from 9 subjects for 12 different gestures (3 trials for each gesture) are acquired. Fifteen different features are extracted from the acquired data. Wrapper method for feature selection is applied on the extracted features which select features from six features groups among the fifteen extracted feature groups. Classification of gestures is performed using three different classifiers i.e., random forest (RF), Naive Bayes (NB) and k-nearest neighbors (kNN) algorithm. The best classification accuracy of 85.80% is achieved by using a fusion of features extracted from accelerometer and gyroscope data by kNN classifier. Experimental results show that the proposed scheme outperforms the existing schemes in literature in terms of classification accuracy for the larger number of gestures.
Educational Mobile Robotics Project "ROS-Controlled Balancing Robot" Based on Arduino and Raspberry Pi

Further development in the field of robotics requires from education system to organize effective preparation of highly skilled specialists. This problem concerns not only higher education, but also the system of secondary education. To ensure continuity between secondary and higher education in robotics, new methodological solutions are required. Along with using existing popular educational robotic kits and ready-made robots, an effective learning approach could be achieved through creating self-made robots. The paper presents an educational project of making a robot. That project was designed for learning activities in robotics. The goal of the project is the creation of ROScontrolled balancing robot with machine vision.
Deep Multilayer Fusion Dense Network for Hyperspectral Image Classification

Deep spectral–spatial features fusion has become a research focus in hyperspectral image (HSI) classification. However, how to extract more robust spectral–spatial features is still a challenging problem. In this article, a novel deep multilayer fusion dense network (MFDN) is proposed to improve the performance of HSI classification. The proposed MFDN simultaneously extracts the spatial and spectral features based on different sample input sizes, which can extract abundant spectral and spatial correlation information. First, the principal component analysis algorithm is performed on hyperspectral data to extract low-dimensional HSI data, and then the spatial features are extracted from the low-dimensional 3-D HSI data through 2-D convolutional, 2-D dense block, and average-pooling layers. Second, the spectral features are extracted directly from the raw 3-D HSI data by means of 3-D convolutional, 3-D dense block, and average-pooling layers. Third, the spatial and spectral features are fused together through 3-D convolutional, 3-D dense block, and average-pooling layers. Finally, the fused spectral–spatial features are sent into two full connection layers to extract high-level abstract features. Furthermore, densely connected structures can help alleviate the vanishing-gradient problem, strengthen feature propagation, encourage feature reuse, and improve the HSI classification accuracy. The proposed fusion network outperforms the other state-of-the-art methods especially with a small number of labeled samples. Experimental results demonstrate that it can achieve outstanding hyperspectral classification performance.