Miracle-dz/UniFAR-FTUs huggingface dataset:
Title Optimum Performance of Direct Hydrogen Hybrid Fuel Cell Vehicles Permalink

Proton Exchange Membrane fuel cell (PEMFC) technology is one of the most attractive candidates for transportation applications due to its inherently high efficiency and high power density. However, the fuel cell system efficiency can suffer because of the need for forced air supply and water-cooling systems. Hence the operating strategy of the fuel cell system can have a significant impact on the fuel cell system efficiency and thus vehicle fuel economy. The key issues are how the fuel cell back pressure and air flow through the fuel cell are controlled. One approach is fixed back pressure control. The other is optimum varying back pressure control. In both cases, the air flow stoichiometry is optimized. In this paper, a dynamic forward-looking vehicle model with a dynamic fuel cell system model is employed. The effects of different fuel cell system operation modes and different power split strategies on fuel economy of fuel cell hybrid vehicles are simulated. The simulation results of light duty vehicles on various driving cycles indicate a significant improvement in fuel economy for optimum varying back pressure operation compared to high fixed back pressure operation. For various fuel cell system operation modes, the load leveling control can significantly improve fuel economy on some aggressive driving cycles such as US06. The vehicle with a small fuel cell system becomes more efficient during low speed or low power demand driving by avoiding low fuel cell output power region.
Phytoglycogen Improves the Water Solubility and Caco-2 Monolayer Permea- tion of Quercetin (Running title: PG Improves QC Solubility)

The study examined the capability of phytoglycogen (PG) to improve the water solubility of quercetin (QC). PG-QC formulations were prepared by mixing a QC ethanol solution with a PG aqueous solution followed with vacuum drying of the supernatant. PG-QC formulations with various PG to QC ratios were prepared; the solubility of QC reached 241.76 μg/mL at PG/QC ratio of 30/1 compared with approximately 4.32 μg/mL of QC alone. The X-ray powder diffraction and FTIR analyses showed a significant reduction of QC crystallinity upon formulating with PG that was associated with the intermolecular hydrogen bonding between the
A Data-Based Fault-Detection Model for Wireless Sensor Networks

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.
The Design and Implementation of an Object-Oriented Prolog Engine

The implementation of Prolog systems has a long history, starting from the first interpreter written in 1972, to the first Prolog compiler simplifying basic operations like unification and backtracking with the aim of optimizing performances, and to the Warren Abstract Machine, later becoming a de facto standard model. The tuProlog engine differs from those systems in that maximum efficiency is not amongst its primary concerns. Instead, it aims at becoming the enabling technology for building complex systems like dynamic Internet infrastructures based on intelligent components, a domain where logic languages could effectively face, in principle, the key issues of intelligence and interaction. To accomplish this task, a logic engine must meet engineering properties such as deployability, configurability and scalability; to be usable as a development tool, it also must sustain a certain degree of traceability, by allowing the inspection of its internal processes at runtime, thus easying the typical pain of debugging activities. The design and implementation of such a system must follow sound principles: object-oriented code structuring, reuse of established community knowledge under the form of patterns, loose coupling of composing elements, modularity and a clear and clean separation of concerns. In this paper, we present the architecture of tuProlog, based upon a set of managers handling control of sensible parts of the system and operating around a minimal core shaped as a Finite State Machine; then, the representation of Prolog data and the unification algorithm’s implementation are discussed; finally, the resolution part of the engine is illustrated.
The potential of using Unmanned Aerial Vehicles (UAVs) for precision pest control of possums (Trichosurus vulpecula)

Unmanned Aerial Vehicles (UAVs) and remote image sensing cameras have considerable potential for use in pest control operations. UAVs equipped with remote sensing cameras could be flown over forests and remnant bush sites, particularly those not currently receiving any pest control, to record the unique spectral signature of the vegetation and to detect the presence of possums (Trichosurus vulpecula) and the damage they cause. UAVs could then be deployed to precisely distribute either toxins or kill traps to these identified locations. Predator-free 2050 is an ambitious policy announced by the New Zealand Government where several pests, including possums, are to be eradicated by the year 2050. In order to achieve this goal, pests must be identified, targeted and controlled, requiring creative and novel ideas. UAVs provide flexibility, can fly in remote and difficult terrain, and are considerably cheaper to purchase and operate than the planes and helicopters currently used in conventional aerial pest control operations. Current challenges associated with UAVs include payload capacity, battery limitations, weather, and flying restrictions. However, these issues are rapidly being resolved with sophisticated technological advances and improved regulations. A directed and targeted approach using UAVs is an additional and novel tool in the pest management toolbox that could significantly reduce pest control costs, cover inaccessible areas not receiving any pest management, and will help New Zealand advance towards its predator-free aspiration by 2050.
Development of papaya tree in organic substrates

Papaya is a tropical fruit of great importance in the international and national market. For crop success, the use of quality seedlings is of paramount importance and substrates formulated from organic sources may be a viable alternative. In this context, the objective of this study was to evaluate the initial development of papaya seedlings in different formulations and levels of organic substrates. A completely randomized design was used in a 4x4+1 factorial scheme, corresponding to four substrate formulations, containing decomposed buriti stem (CDB). The treatments included of the following: (CDB, ½ CDB + ½ poultry manure, ½ CDB + ½ cattle manure and ½ CDB + ½ gray with plant origin sourced from materials resulting from the burning of plant material (stem, branches); four proportion levels of the formulations of the substrates mixed to the soil (25; 50; 75 and 100%) and the additional control (100% soil). The following variables were measured: plant height, leaf area, number of leaves, shoot dry matter, root length and root dry matter at 42 days of seedling cultivation. The results showed that use of an ideal source of organic matter is feasible in the production of papaya seedlings. The substrate consisting of CBD + poultry manure had great potential to be used in the production of papaya seedlings.
FIRM INTERNATIONALIZATION AND CAPITAL STRUCTURE IN DEVELOPING COUNTRIES: THE ROLE OF HOME COUNTRY FINANCIAL DEVELOPMENT DANIЁL JOZEF DE HAAN

With the ascendance of developing market firms in the world economy, the issue of how international expansion influences their capital structure is becoming increasingly pertinent. This paper investigates the combined effect of home country financial development and firm internationalization on capital structure in developing countries. While the standalone effects of these two factors on financing decisions have been documented at length, the combined effect has to date not been assessed in the literature. This paper first revisits the standalone effects and presents some interesting new insights particularly into the consequences they have for debt maturity amongst developing country firms. Thereafter, the combined effect is investigated and it is found that when it comes to the impact of internationalization on corporate financing decisions, home country financial development matters. It is shown that amongst developing countries, firm internationalization can bring with it a decrease in the agency costs of debt, increasing the reliance on long term debt. The scale of this benefit, however, seems to depend on the level of development of the banking sector in the home market.
Pulmonary , gastrointestinal and urogenital pharmacology Bradykinin-induced asthmatic fi broblast / myo fi broblast activities via bradykinin B 2 receptor and different MAPK pathways

Bradykinin drives normal lung fibroblasts into myofibroblasts, induces fibroblast proliferation and activates mitogen activated protein kinase pathways (MAPK) but its effects on bronchial fibroblasts from asthmatics (HBAFb) have not been yet studied. We studied bradykinin-induced fibroblast proliferation and differentiation and the related intracellular mechanisms in HBAFb compared to normal bronchial fibroblasts (HNBFb). Bradykinin-stimulated HBAFb and HNBFb were used to assess: bradykinin B2 receptor expression by Western blot analysis; cell proliferation by [ H] thymidine incorporation; α-smooth muscle actin (SMA) expression/polymerization by Western blot and immunofluorescence; epidermal growth factor (EGF) receptor, extracellular-regulated kinase (ERK) 1/2 and p38 MAPK activation by immunoprecipitation and Western blot, respectively. Constitutive bradykinin B2 receptor and α-SMA expression was higher in HBAFb as compared to HNBFb. Bradykinin increased bradykinin B2 receptor expression in HBAFb. Bradykinin, via bradykinin B2 receptor, significantly increased fibroblast proliferation at lower concentration (10 M) and α-SMA expression/ polymerization at higher concentration (10 M) in both cells. Bradykinin increased ERK1/2 and p38 phosphorylation via bradykinin B2 receptor; EGF receptor inhibitor AG1478 and panmetalloproteinase inhibitor GM6001 blocked bradykinin-induced ERK1/2 activation but not p38 phosphorylation. Bradykinin, via bradykinin B2 receptor, induced EGF receptor phosphorylation that was suppressed by AG1478. In HBAFb AG1478, GM6001, the ERK1/2-inhibitor U0126 and the p38 inhibitor SB203580 suppressed bradykinininduced cell proliferation, but only SB203580 reduced myofibroblast differentiation. These data indicate that bradykinin is actively involved in asthmatic bronchial fibroblast proliferation and differentiation, throughMAPK pathways and EGF receptor transactivation, by which bradykinin may contribute to airway remodeling in asthma, opening new horizons for potential therapeutic implications in asthmatic patients. & 2013 Elsevier B.V. All rights reserved.
AN EMPIRICAL ANALYSIS OF THE INFLUENCE OF RISK FACTORS ON THE FREQUENCY AND IMPACT OF SEVERE EVENTS ON THE SUPPLY CHAIN IN THE CZECH REPUBLIC

Purpose: This paper is focused on an analysis and evaluation of severe events according to their frequency of occurrence and their impact on the company's manufacturing and distribution supply chains performance in the Czech Republic. Risk factors are introduced for critical events. Design/methodology: An identification and classification of severe events are realized on the basis of median mapping and mapping of ordinal variability acquired through the questionnaire survey of 82 companies. Analysis of 46 risk factors was sorted into 5 groups. We used asymmetric Somers's d statistics for testing the dependence of frequency and impact of a severe event on selected risk sources. The hierarchical cluster analysis is performed to identify relatively homogeneous groups of critical severe events according to their dependency on risk factors and its strength. Findings: Results showed that ‘a lack of contracts’ is considered to be the most critical severe event. Groups of demand and supply side and an external risk factor group were identified to be the most significant sources of risk factors. The worst cluster encompasses 11% of examined risk factors which should be prevented. We concluded that organizations need to adopt appropriate precautions and risk management methods in logistics. Originality: In this paper, the methodology for severe events evaluation in supply chain is designed. This methodology involves assessing the critical factors which influence the critical events and which should be prevented
A generalised minimum variance controller for time-varying systems

In this paper, the problem of generalised minimum variance control of linear time-varying systems is studied. A time-varying optimal controller is developed for a standard controlled autoregressive moving average model using a cost function that is the sum of the plant output tracking error variance plus a penalty term of the squared manipulated variable. Copyright © 2005 IFAC
Initiating Cells − Inhibition Contributes to the Maintenance of Colon Cancer Induction of the Stem-like Cell Regulator CD 44 by Rho Kinase

The difficulty in expanding cancer-initiating cells in vitro is one of major obstacles for their biochemical characterization.We found that Rho kinase (ROCK) inhibitors aswell as blebbistatin, amyosin II inhibitor, greatly facilitated the establishment of spheroids from primary colon cancer. The spheroid cells expressed cancer stem cell markers, showed the ability to differentiate, and induced tumors in mice. The spheroids were composed of cells that express various levels of CD44, whereas CD44 cells were associated with increased sphere-forming ability, expression of the activating form of b-catenin, and elevated levels of glycolytic genes, CD44 /low cells showed increased levels of differentiationmarkers and apoptotic cells. The spheroid cells expressed variant forms of CD44 including v6, and the induction of the variants was associated with the activating phosphorylation of cMet. As expected from the predicted hierarchy, CD44 cells differentiated into CD44 /low cells. Unexpectedly, a fraction of CD44 /low cells generated CD44 cells, and the ROCK inhibitor or blebbistatin primed the transition by inducingCD44 expression.Wepropose that the transition fromCD44 /low toCD44 state helps tomaintain a CD44 fraction and the tumorigenic diversity in colon cancer. Cancer Res; 72(19); 5101–10. 2012 AACR.
Supervised Nearest Neighbor Searching for Visual Tracking

Supervised learning algorithms have been widely applied in tracking-by-detection based methods for object tracking in recent years. Most of these approaches treat tracking as a classification problem and solve it by training a discriminative classifier and exhaustively evaluating every possible target position; problems thus exist for two reasons. First, since the classifier describes the common feature of samples in an implicit way, it is not clear how well the classifier can represent the feature of the desired object against others; second, the brute-force search within the output space is usually time consuming, and thus limits the competence for real-time application. In this project, we treat object tracking as a problem of information retrieval for streaming data. We propose to apply unsupervised learning by Locality Sensitive Hashing (LSH) and use Nearest Neighbor Searching (NNS) as the main engine for target detection. In addition, our method applies a Support Vector Machine (SVM) based supervised classifier cooperating with the unsupervised detector. Both the proposed tracker and several selected trackers are tested on some well accepted challenging videos; and the experimental results demonstrate that the proposed tracker outperforms the selected other trackers in terms of the effectiveness as well as the robustness.
COORDINATED HOME ENERGY MANAGEMENT IN COMMUNITY MICROGRIDS WITH ENERGY SHARING AMONG SMART HOMES

This paper presents a coordination mechanism for smart homes in community microgrids (smart neighborhoods) whether photovoltaics (PV), home battery storage and electric vehicles (EV) are available. The objective of the proposed method is to reduce the electricity cost of the users, as well as the aggregated peak load of the area by establishing an energy sharing ability among neighbors. A decentralized control algorithm deployed by the smart homes is used for battery control and appliance scheduling. It is assumed that the users are the owners of these resources and that they are selfish decision-makers who focus on increasing own benefit. For the neighborhood, a dynamic price model is used, where the price is associated to the aggregated consumption of the neighborhood area. Numerical results show that proposed coordination mechanism with energy sharing provides benefits for both the users and the utility. Keyword Energy management, smart homes, neighborhood coordination, multiagent systems, electric vehicles.
WST 50.6-104 corr

Computer modelling has been used in the last 15 years as a powerful tool for understanding the behaviour of activated sludge wastewater treatment systems. However, computer models are mainly applied for domestic wastewater treatment plants (WWTPs). Application of these types of models to industrial wastewater treatment plants requires a different model structure and an accurate estimation of the kinetics and stoichiometry of the model parameters, which may be different from the ones used for domestic wastewater. Most of these parameters are strongly dependent on the wastewater composition. In this study a modified version of the activated sludge model No. 1 (ASM 1) was used to describe a tannery WWTP. Several biological tests and complementary physical-chemical analyses were performed to characterise the wastewater and sludge composition in the context of activated sludge modelling. The proposed model was calibrated under steady-state conditions and validated under dynamic flow conditions. The model was successfully used to obtain insight into the existing plant performance, possible extension and options for process optimisation. The model illustrated the potential capacity of the plant to achieve full denitrification and to handle a higher hydraulic load. Moreover, the use of a mathematical model as an effective tool in decision making was demonstrated.
PPA_A_215271 1463..1475

Jamuna Rani Appalasamy Joyce Pauline Joseph Siva Seeta Ramaiah Kia Fatt Quek Anuar Zaini Md Zain Kyi Kyi Tha 1Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia; 2Department of Neurology, Hospital Kuala Lumpur, Ministry of Health, Kuala Lumpur, Malaysia; 3Medical Department, Subang Jaya Medical Center, Sunway, Malaysia Background and aim: Evidence-based prescribing practices for stroke-preventive medication have benefited stroke survivors; however, medication-nonadherence rates remain high. Medication understanding and use self-efficacy (MUSE) has shown great importance in medication-taking behavior, but its relationship with medication nonadherence in strokepreventive regimens lacks exploration. The aim of this study was to determine the prevalence of MUSE and its association with nonadherence causes and other potential factors among stroke survivors in Malaysia. Methods: This cross-sectional study was conducted among 282 stroke patients who provided informed consent andwere in follow-up at theNeurologyOutpatient Department of Hospital Kuala Lumpur, Malaysia. The study employed a data-collection form that gathered information on sociodemographics, clinical treatment, outcome measures on MUSE, and medication-nonadherence reasons. Results: The prevalence of poor medication understanding and use self-efficacy among stroke patients was 46.5%, of which 29.1% had poor “learning about medication” self-efficacy, while 36.2% lacked self-efficacy in taking medication. Beliefs about medicine (74.02%) was the commonest reason for medication nonadherence, followed by medication-management issues (44.8%). In the multivariate model, independent variables significantly associated with MUSE were health literacy (AOR 0.2, 95% CI 0.069–0.581; P=0.003), medication-management issues (AOR 0.073, 95% CI 0.020-0.266; P<0.001), multiple-medication issues (AOR 0.28, 95% CI 0.085–0.925; P=0.037), beliefs about medicine (AOR 0.131, 95% CI 0.032–0.542; P=0.005), and forgetfulness/convenience issues (AOR 0.173, 95% CI 0.050–0.600; P=0.006). Conclusion: The relatively poor learning about medication and medication-taking self-efficacy in this study was highly associated with health literacy and modifiable behavioral issues related to nonadherence, such as medication management, beliefs about medicine, and forgetfulness/ convenience. Further research ought to explore these underlying reasons using vigorous techniques to enhance medication understanding and use self-efficacy among stroke survivors to determine cause–effect relationships.
A Dataset of Crowdsourced Word Sequences: Collections and Answer Aggregation for Ground Truth Creation

The target outputs of many NLP tasks are word sequences. To collect the data for training and evaluating models, the crowd is a cheaper and easier to access than the oracle. To ensure the quality of the crowdsourced data, people can assign multiple workers to one question and then aggregate the multiple answers with diverse quality into a golden one. How to aggregate multiple crowdsourced word sequences with diverse quality is a curious and challenging problem. People need a dataset for addressing this problem. We thus create a dataset (CrowdWSA2019) which contains the translated sentences generated from multiple workers. We provide three approaches as the baselines on the task of extractive word sequence aggregation. Specially, one of them is an original one we propose which models the reliability of workers. We also discuss some issues on ground truth creation of word sequences which can be addressed based on this dataset.