Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-course transcriptomic alterations reflect the pathophysiology of polyhexamethylene guanidine phosphate-induced lung injury in rats

Abstract Objective: Humidifier-disinfectant-induced lung injury is a new syndrome associated with a high mortality rate and characterized by severe hypersensitivity pneumonitis, acute interstitial pneumonia, or acute respiratory distress syndrome. Polyhexamethylene guanidine phosphate (PHMG-P), a guanidine-based antimicrobial agent, is a major component associated with severe lung injury. In-depth studies are needed to determine how PHMG-P affects pathogenesis at the molecular level. Therefore, in this study, we analyzed short-term (4 weeks) and long-term (10 weeks) PHMG-P-exposure-specific gene-expression patterns in rats to improve our understanding of time-dependent changes in fibrosis. Materials and methods: Gene-expression profiles were analyzed in rat lung tissues using DNA microarrays and bioinformatics tools. Results: Clustering analysis of gene-expression data showed different gene-alteration patterns in the short- and long-term exposure groups and higher sensitivity to gene-expression changes in the long-term exposure group than in the short-term exposure group. Supervised analysis revealed 34 short-term and 335 long-term exposure-specific genes, and functional analysis revealed that short-term exposure-specific genes were involved in PHMG-P-induced initial inflammatory responses, whereas long-term exposure-specific genes were involved in PHMG-P-related induction of chronic lung fibrosis. Conclusion: The results of transcriptomic analysis were consistent with lung histopathology results. These findings indicated that exposure-time-specific changes in gene expression closely reflected time-dependent pathological changes in PHMG-P-induced lung injury.
Implementing Employment Quotas to Develop Human Resource Capital: A Comparison of Oman and the UAE

Over the past few decades, nations from the Arabian Gulf have relied on expatriates to enhance their booming economiesand support rapid economic development. The Gulf’s ability to attract international business and expertise has been successful (Ewers, 2013) and both Oman and the UAE have grown their economies while improving their overall global competitiveness (World Bank, 2011). While the relationship between nationals and expatriates has been mutually beneficial, today the reliance on external expertshas implications for the social, political and economic issuesfacing the nations. For this reason, the Gulf countries have embarked on strategies to ensure that employment quotas are regulated as part of the human capital development of nationals. The Economist commissioned a report in 2012 on expectations to be faced in human resource management strategies across the region, and their findings indicate that while the skill gap between nationals and expatriates will narrow, they predict it will not close by 2020.Both governments must address the challengeof providing meaningful employment opportunities for a growing generation of younger workers and at the same time maintain a high level of economic growth.
Land-Use Effect on Soil Carbon and Nitrogen Stock in a Seasonally Dry Tropical Forest

Total organic carbon (TOC) and total nitrogen (TN) concentration in the soil are an indicator of soil degradation. To understand how land-use may impact these concentrations in seasonally dry tropical forests (SDTF), we analyzed the effect of four land-uses on TOC stocks (STK.TOC) and TN stocks (STK.TN) in a semi-arid region of Brazil. Soil samples were collected in 12 trenches (three sites × four land-uses—dense caatinga (DC), open caatinga (OC), pasture (PA) and agriculture (AG)), in the 0–10; 10–20 and 20–30 cm layers or as far as the bedrock. The data were compared by the Kruskal–Wallis test (p ≤ 0.05) and similarity investigated by cluster analysis. STK.TOC and STK.TN the surface layer (0–10 cm) showed no significant difference (p ≤ 0.05) between the DC; OC and PA land-uses. The similarity in STK.TOC and STK.TN values between DC, OC and PA, indicate that it is possible to explore SDTF to produce biomass and protein by adopting open caatinga and pasture land uses on Neosols with very low TOC stocks. The greatest reduction in STK.TOC and STK.TN in the agriculture land-use may lead to soil degradation and contribute to the addition of CO2 to the atmosphere.
House Prices, Wealth Effects and Labour Supply

We examine the impact of house prices on labour supply decisions using UK micro data. We combine household survey data with local level house price measures and controls for local labour demand. Our micro data also allows us to control for individual level income expectations. We find significant house price effects on labour supply, consistent with leisure being a normal good. Labour supply responses to house prices are concentrated among young married female owners and older owners. This finding suggests house prices affect the decisions of marginal workers in the economy. Our estimates imply house prices are economically important for the participation decisions for these workers.
Assessment of Strategies Using Analytic Network process: Case of Media Company in Latvia

Republic of Latvia as a single state is divided into four regions, where there are socio-economical differences, depending on their location and geographical features. As one of the options contributing to the region’s economic climate and development is the use of regional media, which can be used to motivate the citizens to start they own business. This paper includes the assessment of the regional media strategies that will contribute to the growth of the business sector. Latgale region, which is less socio-economically developed, is taken as an example. To determine the best strategy, the authors use A’WOT hybrid method, that is a tool for company environment research and estimation. This method is a combination of two methods – SWOT and Analytic Hierarchy Process that has been used since 2000. The combination of the methods allows identifying the best strategy from the offered in TOWS matrix, taking into account SWOT factors and sub-factors values and their importance in implementing the strategies. As a result, each strategy was assigned a weight that helps to create the hierarchical structure of the strategies and identify the most important strategy to promote economic status of the region with no loss of money and time.
Effect of Duration and Drying Temperature on Characteristics of Dried Tomato (Lycopersicon esculentum L.) Cochoro Variety

Abstract The objective of the present study was to standardise the duration and temperatures of the conventional oven drying methods for best physical and sensory characteristics of dried tomato. The experiment consisted of two factor factorial design (3*2) with three levels of drying temperature (70°C, 80°C and 90°C) and two levels of drying duration (7 and 8 hours) with three replications. An improved and high yielding variety (Cochoro) of tomato released in 2007 for processing and widely grown in Ziwai (Maki), Ethiopia was used. Prior to drying, individual tomato fruits were washed and sliced into uniform thickness (8mm); then, the slices were placed on to the drying trays in a single layer to facilitate uniform drying in hot air oven set at predetermined temperatures per the respective treatments. Data were collected on different physical and sensory attributes and analysed using SAS software (version 9.2). The results showed that titratable acidity, total soluble solids and water absorption capacity were significantly (p≤0.001) increased due to the interaction of degree of temperature and duration of oven drying. In contrast, pH and water activity decreased as the drying temperature and duration increased. Drying at 70°C for 7 hours produced dried tomatoes with the highest sensorial acceptability and physical attributes while higher temperatures (80, 90°C) and longer duration (9 hours) significantly detract the quality of dried tomato. Hence, it is possible to add value and preserve tomatoes through oven drying at the right temperature and optimum duration.
Analyzing Genre Exemplars in Preparation for Writing: The Case of an L2 Graduate Student in the ESP Genre-based Instructional Framework of Academic Literacy

Some researchers believe that the ESP genre-based framework of writing instruction is effective in teaching discipline-specific English EAP writing to L2 learners, especially to advanced L2 graduate students. However, studies examining students’ genre-based learning in such a framework are still underrepresented in current ESP genre-based literature. This study focused on a Chinese-speaking graduate student in electrical engineering who analyzed genre exemplars in preparation for writing. My analysis of the data reveals this student's two prominent and interrelated ways of analyzing the discourse-level generic features in discipline-specific genre exemplars. They are (a) rhetorical, as evidenced in his consistent attention not only to the generic features, but also to the underlying rhetorical parameters, such as reader, writer, and purpose and (b) evaluative, as shown in his increasingly sophisticated evaluation of the discourse-level generic features in the genre exemplars. The student's rhetorical and evaluative reading of the genre exemplars highlights the potential power of genre as an explicit, supportive tool for building academic literacy.
Carotenoids and Periodontal Infection

Periodontitis is a polymicrobial infectious disease that leads to inflammation of the gingiva, resulting in teeth loss by various causes such as inflammation-mediated bone resorption. Recently, many investigators have reported that the periodontitis resulting from persistent low-grade infection of Gram-negative bacteria such as Porphyromonas gingivalis (Pg) is associated with increased atherosclerosis, diabetes mellitus, and other systemic diseases through blood stream. On the other hand, carotenoids belong among phytochemicals that are responsible for different colors of the foods. It is important to examine whether carotenoids are effective to the inhibition of periodontal infection/inflammation cascades. This review summarizes the advanced state of knowledge about suppression of periodontal infection by several carotenoids. A series of findings suggest that carotenoids intake may provide novel strategy for periodontitis treatment, although further study will be needed.
Bacteriostatic Effect of Piezoelectric Poly-3-Hydroxybutyrate and Polyvinylidene Fluoride Polymer Films under Ultrasound Treatment

Antibiotic resistance of bacteria stimulates the development of new treatment approaches. Piezoelectric-catalysis has attracted much attention due to the possibility to effectively provide antibacterial effect via generation of reactive oxygen species. However, the influence of the surface charge or potential of a piezopolymer on bacteria has not been sufficiently studied so far. This study reports the fabrication and characterization of thin films of piezoelectric polyhydroxybutyrate, polyvinylidene fluoride, and polyvinylidene fluoride trifluoroethylene as well as non-piezoelectric polycaprolactone polymers fabricated using solution casting approach. The piezoelectric coefficient (d33) and surface electric peak-to-peak potential generated by the cyclic mechanical stress applied to the films were measured. Neither any toxic effect of the polymer films nor ultrasound influence on Escherichia coli bacteria behavior is observed. However, significant inhibition of the growth of bacteria is revealed during mechanical stimulation of piezoelectric samples via ultrasound treatment. Thus, this study demonstrates clear bacteriostatic effect of piezoelectric polymers for different tissue engineering applications.
A Comparative Analysis of Parliamentary Governments in Post-War Europe

Why are some states more corrupt than others? Previous research explaining corruption suggests that multiparty governments are associated with higher levels of corruption since it is difficult for voters to hold parties in such cabinets accountable. Drawing on the literature on coalition governance, we suggest that a lack of government corruption has more to do with the ability of other key political actors to control the agents that have been delegated power in cabinet. We use a new dataset (Varieties of Democracy), giving us more specific measures on governmental corruption across a longer time-period. We show that corruption is significantly lower when the Prime Minister (PM) has strong constitutional powers, suggesting that the PM as a principal reduces agency problems. 1 We are very grateful for the help provided by Torbjörn Bergman, Svante Ersson, and Holger Döring, and for the excellent research assistance provided by Talib Jabbar. Hanna Bäck and Jan Teorell carried out most of the work on this article should be given the main credit for it.
Classification, Analysis, and Prediction of the Daily Operations of Airports Using Machine Learning

The Federal Aviation Administration (FAA) is the regulatory body in the United States responsible for the advancement, safety, and regulation of civil aviation. The FAA also oversees the development of the air traffic control system in the U.S. Over the years, the FAA has made tremendous progress in modernizing the National Airspace System (NAS) by way of technological advancements and the introduction of procedures and policies that have maintained the safety of the United States airspace. However, as with any other system, there is a need to continuously address evolving challenges pertaining to the sustainment and resiliency of the NAS. One of these challenges involves efficiently analyzing and assessing the operations of airports. In particular, there is a need to assess the impact and effectiveness of the implementation of Traffic Management Initiatives (TMI) and other procedures on daily airport operations, as this will lead to the identification of trends and patterns to inform better decision making. The FAA currently manually classifies the daily operations of airports into three categories: “Good Days”, “Average Days”, and “Bad Days” as a means to assess their efficiency. However, this exercise is time-consuming and can be improved. In particular, Big Data Analytics can be leveraged to develop a systematic approach for classifying or clustering the daily operations of airports. This research presents a methodology for clustering the daily operations of Newark International Airport (EWR) using metrics such as the number of diversions, Ground Stops, departure delays, etc. Each of these categories/clusters is then analyzed to identify key characteristics, trends and patterns, which can then be used by airport operators, and FAA analysts and researchers to improve the operations at the airport. Finally, the Boosting Ensemble Machine Learning algorithm is used to predict the category of operations at the airport, hence enabling airport operators, FAA analysts and researchers to take appropriate actions.
O (log log n) Worst-Case Local Decoding and Update Efficiency for Data Compression

This paper addresses the problem of data compression with local decoding and local update. A compression scheme has worst-case local decoding dwc if any bit of the raw file can be recovered by probing at most dwc bits of the compressed sequence, and has update efficiency of uwc if a single bit of the raw file can be updated by modifying at most uwc bits of the compressed sequence. This article provides an entropy-achieving compression scheme for memoryless sources that simultaneously achieves O (log log n) local decoding and update efficiency. Key to this achievability result is a novel succinct data structure for sparse sequences which allows efficient local decoding and local update.Under general assumptions on the local decoder and update algorithms, a converse result shows that the maximum of dwc and uwc must grow as Ω(log log n).
Joint Inference on Truth/Rumor and Their Sources in Social Networks

In the contemporary era of information explosion, we are often faced with the mixture of massive truth (true information) and rumor (false information) flooded over social networks. Under such circumstances, it is very essential to infer whether each claim (e.g., news, messages) is a truth or a rumor, and identify their sources, i.e., the users who initially spread those claims. While most prior arts have been dedicated to the two tasks respectively, this paper aims to offer the joint inference on truth/rumor and their sources. Our insight is that a joint inference can enhance the mutual performance on both sides.To this end, we propose a framework named SourceCR, which alternates between two modules, i.e., credibility-reliability training for truth/rumor inference and division-querying for source detection, in an iterative manner. To elaborate, the former module performs a simultaneous estimation of claim credibility and user reliability by virtue of an Expectation Maximization algorithm, which takes the source reliability outputted from the latter module as the initial input. Meanwhile, the latter module divides the network into two different subnetworks labeled via the claim credibility, and in each subnetwork launches source detection by applying querying of theoretical budget guarantee to the users selected via the estimated reliability from the former module. The proposed SourceCR is provably convergent, and algorithmic implementable with reasonable computational complexity. We empirically validate the effectiveness of the proposed framework in both synthetic and real datasets, where the joint inference leads to an up to 35% accuracy of credibility gain and 29% source detection rate gain compared with the separate counterparts.
Clinician perspective on VR Games for Managing Periprocedural Anxiety in Children

Many children experience periprocedural anxiety (occurring before, during, or immediately after the a medical procedure such as induction of anaesthesia or immunisation) in hospital settings. A number of strategies, such as distraction and focus shifting, are commonly used in medical practice to help paediatric patients manage their anxiety. In recent years, Virtual Reality (VR) has been investigated as a promising tool in hospital settings, particularly through mediating distraction. In this paper, we present the findings from a focus group with four clinicians and attempt to explore key elements inherent in their practice that can be leveraged for designing impactful VR applications for managing periprocedural anxiety in paediatric hospitals. Our contribution is a set of insights relevant to patients, their needs, tailoring of strategies, and future design directions. We benchmark three existing VR applications against our findings to generate potential design opportunities for VR applications.
Planet formation imager: project update

The Planet Formation Imager (PFI) is a near- and mid-infrared interferometer project with the driving science goal of imaging directly the key stages of planet formation, including the young proto-planets themselves. Here, we will present an update on the work of the Science Working Group (SWG), including new simulations of dust structures during the assembly phase of planet formation and quantitative detection efficiencies for accreting and non-accreting young exoplanets as a function of mass and age. We use these results to motivate two reference PFI designs consisting of a) twelve 3m telescopes with a maximum baseline of 1.2km focused on young exoplanet imaging and b) twelve 8m telescopes optimized for a wider range of young exoplanets and protoplanetary disk imaging out to the 150K H2O ice line. Armed with 4 x 8m telescopes, the ESO/VLTI can already detect young exoplanets in principle and projects such as MATISSE, Hi-5 and Heimdallr are important PFI pathfinders to make this possible. We also discuss the state of technology development needed to make PFI more affordable, including progress towards new designs for inexpensive, small field-of-view, large aperture telescopes and prospects for Cubesat-based space interferometry.
Borders of Biodiversity: Life at the Edge of the World's Large Lakes

The great lakes of the world represent a global heritage of surface freshwater and aquatic biodiversity. Species lists for 14 of the world's largest lakes reveal that 15% of the global diversity (the total number of species) of freshwater fishes, 9% of noninsect freshwater invertebrate diversity, and 2% of aquatic insect diversity live in this handful of lakes. The vast majority (more than 93%) of species inhabit the shallow, nearshore littoral zone, and 72% are completely restricted to the littoral zone, even though littoral habitats are a small fraction of total lake areas. Most fish species exploit benthic resources, which increases food web complexity. Moreover, littoral zones are both more negatively affected by human activity and less intensively studied than offshore waters. Conservation of the remarkable biodiversity and biotic integrity of large lakes will require better integration of littoral zones into our understanding of lake ecosystem functioning and focused efforts to alleviate human impacts along the shoreline.
EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update

Objectives To provide an update of the European League Against Rheumatism (EULAR) rheumatoid arthritis (RA) management recommendations to account for the most recent developments in the field. Methods An international task force considered new evidence supporting or contradicting previous recommendations and novel therapies and strategic insights based on two systematic literature searches on efficacy and safety of disease-modifying antirheumatic drugs (DMARDs) since the last update (2016) until 2019. A predefined voting process was applied, current levels of evidence and strengths of recommendation were assigned and participants ultimately voted independently on their level of agreement with each of the items. Results The task force agreed on 5 overarching principles and 12 recommendations concerning use of conventional synthetic (cs) DMARDs (methotrexate (MTX), leflunomide, sulfasalazine); glucocorticoids (GCs); biological (b) DMARDs (tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, etanercept, golimumab, infliximab), abatacept, rituximab, tocilizumab, sarilumab and biosimilar (bs) DMARDs) and targeted synthetic (ts) DMARDs (the Janus kinase (JAK) inhibitors tofacitinib, baricitinib, filgotinib, upadacitinib). Guidance on monotherapy, combination therapy, treatment strategies (treat-to-target) and tapering on sustained clinical remission is provided. Cost and sequencing of b/tsDMARDs are addressed. Initially, MTX plus GCs and upon insufficient response to this therapy within 3 to 6 months, stratification according to risk factors is recommended. With poor prognostic factors (presence of autoantibodies, high disease activity, early erosions or failure of two csDMARDs), any bDMARD or JAK inhibitor should be added to the csDMARD. If this fails, any other bDMARD (from another or the same class) or tsDMARD is recommended. On sustained remission, DMARDs may be tapered, but not be stopped. Levels of evidence and levels of agreement were mostly high. Conclusions These updated EULAR recommendations provide consensus on the management of RA with respect to benefit, safety, preferences and cost.