Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Compressed Air Energy Conversion Processes in a Rotary Piston Pneumatic Engine

This article describes a rotary piston pneumatic engine with a gas exchange system design that minimizes the value of the relative dead volume, as well as ensures the minimum dimensions and weight of the engine. The main purpose of the study is to evaluate the conversion efficiency of compressed air energy in the working cylinder of the rotary piston pneumatic engines using the exergy method of thermodynamic analysis. To achieve the set goal of the study, physical modeling of various operation modes has been performed. The most significant result is that, based on the physical and mathematical modeling, a thermodynamic assessment of the efficiency of the compressed air energy conversion has been performed. The significance of the results obtained lies in the fact that the effect of the main operational parameters of the pneumatic engine on the efficiency of energy conversion is established. The basic equations of the exergy method of the thermodynamic analysis are presented. The results of physical and mathematical modeling of various operation modes are presented. The main reasons for the decrease in the energy conversion efficiency at low and rated loads are emphasized. The amount of exergy supplied with the air flow was established, which, depending on the operation mode, amounted to 2.2. 11.4 kW. According to the presented results, the most optimal speed range, based on the achievement of the maximum values of the specific efficient work and exergy efficiency, is 55.70% of the nominal value. It was found that an increase in the operation pressure decreases slightly the exergy efficiency. A twofold increase in the operation pressure of the pneumatic engine increases the efficient power by 46 % at a simultaneous decrease in the exergy efficiency by 8.2 %.
Efficient External Sorting for Memory-Constrained Embedded Devices with Flash Memory

Embedded devices are ubiquitous in areas of industrial and environmental monitoring, health and safety, and consumer appliances. A common use case is data collection, processing, and performing actions based on data analysis. Although many Internet of Things (IoT) applications use the embedded device simply for data collection, there are benefits to having more data processing done closer to data collection to reduce network transmissions and power usage and provide faster response. This work implements and evaluates algorithms for sorting data on embedded devices with specific focus on the smallest memory devices. In devices with less than 4 KB of available RAM, the standard external merge sort algorithm has limited application as it requires a minimum of three memory buffers and is not flash-aware. The contribution is a memory-optimized external sorting algorithm called no output buffer sort (NOBsort) that reduces the minimum memory required for sorting, has excellent performance for sorted or near-sorted data, and sorts on external memory such as SD cards or raw flash chips. When sorting large datasets, no output buffer sort reduces I/O and execution time by between 20% to 35% compared to standard external merge sort.
Shaping the Public Perception of Economic Phenomena During the COVID-19 Pandemic: Priority of Goals or Values?

: Purpose: The coronavirus pandemic has posed serious challenges to governments almost all over the world. To stop its development authorities have overwhelmingly introduced social distancing and locked down the economy. Apart from implementing measures restoring socio-economic activity, it was equally important how the government informed the society about them. The aim of this work is to determine the factors that impact the way in which the coronavirus pandemic is presented to the society in Poland. Design/Methodology/Approach: The analyses of selected literature and case study method were used to show how government communicated the actions taken in public finance and economy, as well as socio-political life. The uniqueness of the research should be related to the fact that two presidential campaigns were run during the epidemic. Findings: The research results indicate that the issue of the pandemic and the actions taken to combat the crisis it triggered, as well as the attitude towards social distancing, were used in the message addressed to the public with a view to achieving specific political objectives of the authorities. The coronavirus epidemic was presented differently by politicians and public media during each of the two campaigns accompanying the elections for the office of the President of Poland. Prior to the elections scheduled for 10 May 2020, the coronavirus pandemic was presented to the public as a serious threat to health and life which necessitated restrictive adherence to social distancing restrictions. In the second election campaign, those in power sent an optimistic message to society suggesting a victory over coronavirus had been achieved in terms of health and economy. Practical Implications: The paper shows the possibility of shaping the perception of economic phenomena by means of the mass media. Originality/Value: The research shows that topics important for the functioning of the state, such as the rapidly deteriorating condition of public finances or the entry of the economy into recession, were not the main axis of the political dispute during the election campaigns.
Linking Long-Term Changes in Soil Salinity to Paddy Land Abandonment in Jaffna Peninsula, Sri Lanka

Soil salinity is a serious threat to coastal agriculture and has resulted in a significant reduction in agricultural output in many regions. Jaffna Peninsula, a semi-arid region located in the northern-most part of Sri Lanka, is also a victim of the adverse effects of coastal salinity. This study investigated long-term soil salinity changes and their link with agricultural land use changes, especially paddy land. Two Landsat images from 1988 and 2019 were used to map soil salinity distribution and changes. Another set of images was analyzed at four temporal periods to map abandoned paddy lands. A comparison of changes in soil salinity with abandoned paddy lands showed that abandoned paddy lands had significantly higher salinity than active paddy lands, confirming that increasing salts owing to the high levels of sea water intrusion in the soils, as well as higher water salinity in wells used for irrigation, could be the major drivers of degradation of paddy lands. The results also showed that there was a dramatic increase in soil salinity (1.4-fold) in the coastal lowlands of Jaffna Peninsula. 64.6% of the salinity-affected land was identified as being in the extreme saline category. In addition to reducing net arable lands, soil salinization has serious implications for food security and the livelihoods of farmers, potentially impacting the regional and national economy.
From Science to Practice: Improving ROP by Utilizing a Cloud-Based Machine-Learning Solution in Real-Time Drilling Operations

This paper is a follow up to the URTeC (2019-343) publication where the training of a Machine Learning (ML) model to predict rate of penetration (ROP) is described. The ML model gathers recent drilling parameters and approximates drilling conditions downhole to predict ROP. In real time, the model is run through an optimization sweep by adjusting parameters which can be controlled by the driller. The optimal drilling parameters and modeled ROP are then displayed for the driller to utilize. The ML model was successfully deployed and tested in real time in collaboration with leading shale operators in the Permian Basin. The testing phase was split in two parts, preliminary field tests and trials of the end-product. The key learnings from preliminary field tests were used to develop an integrated driller's dashboard with optimal drilling parameters recommendations and situational awareness tools for high dysfunction and procedural compliance which was used for designed trials. The results of field trials are discussed where subject well ROP was improved between 19-33% when comparing against observation/control footage. The overall ROP on subject wells was also compared against offset wells with similar target formations, BHAs, and wellbore trajectories. In those comparisons against qualified offsets, ROP was improved by as little as 5% and as much as 33%. In addition to comparing ROP performance, results from post-run data analysis are also presented. Detailed drilling data analytics were performed to check if using the recommendations during the trial caused any detrimental effects such as divergence in directional trends or high lateral or axial vibrations. The results from this analysis indicate that the measured downhole axial and lateral vibrations were in the safe zone. Also, no significant deviations in rotary trends were observed.
Arithmetic properties of septic partition functions

Congruences and related identities are derived for a set of colored and weighted partition functions whose generating functions generate the graded algebra of integer weight modular forms of level seven. The work determines a general strategy for identifying and proving identities and associated congruences for modular forms on the principal congruence subgroup of level [Formula: see text]. Ramanujan’s partition congruence modulo [Formula: see text] serves as a prototype for the process used to prove new congruences for modular forms of level [Formula: see text].
Membrane scaling during seawater desalination by direct contact membrane distillation

Seawater desalination by membrane distillation (MD) has great potential for fresh water provision in small and remote areas. Amongst four basic MD configurations, direct contact membrane distillation (DCMD) has a simple arrangement; thus, it is most suited for small-scale seawater desalination application. In this study, membrane scaling during a seawater DCMD desalination process was systematically investigated. Mass transfer coefficient of the DCMD system was first determined with Milli-Q water. The obtained mass transfer coefficient was used to simulate the influence of feed salinity increase and membrane scaling on water flux. The simulation results were then validated by experimental data. Results reported here demonstrate a notable influence of feed salinity increase and membrane scaling on water flux, particularly at a high water recovery. The rapid increased feed salinity during the concentration of seawater at water recoveries above 50 % magnified both temperature and concentration polarization effects, thus reducing the experimentally measured water flux compared to the calculated one. In addition, membrane scaling caused by the precipitation of CaSO 4 and MgSO 4 at high water recoveries further reduced the measured water flux. Moreover, feed operating temperature had a profound effect on both water flux and membrane scaling. Increasing feed temperature favored higher water flux but also escalated membrane scaling. Finally, a DCMD process of seawater at a water recovery of 70 % without any observable membrane scaling was obtained either by operating the process at a reduced feed temperature or by anti-scalant addition. The results reported in this study demonstrate the viability of DCMD for small-scale seawater desalination in Vietnam given its long coastline together with a large number of islands and great solar energy availability.
A Group-based Dual Trajectory of Depression and Anxiety in Older Adults: An 8-year Follow-up of Population-based Study

Background: Depression and anxiety are common mental health conditions for elderly population. Understanding the trajectory developments of them will help us implementing treatments and interventions.Aims: This study aims to identify depression and anxiety trajectories in the elderly, evaluate the interrelationship of these conditions, and recognize trajectory-predicting characteristics.Methods: Group-based dual trajectory modeling (GBDTM) was applied to the data of 3,983 individuals, aged 65 years or older who participated in the Korean Health Panel Study between 2008 and 2015. Logistic regression was used to identify the association between characteristics and trajectory groups.Results: Four trajectory groups from GBDTM were identified in both the depression and anxiety outcomes. Depression has: “low-flat (87.0%)”, “low-to-middle (8.8%)”, “low-to-high (1.3%)” and “high-stable (2.8%)” trajectory groups. Anxiety has: “low-flat (92.5%)”, “low-to-middle (4.7%)”, “high-to-low (2.2%)” and “high-curve (0.6%)” trajectory groups. Interrelationship between depression and anxiety were identified. Members of the high-stable depression group were more likely to have “high-to-low” or “high-curved” anxiety trajectories. Female sex, the presence of more than three chronic diseases, and having income generating activity were significant factors in depression and anxiety.Conclusions: Dual trajectory analysis of depression and anxiety in older adults shows that when one condition is present, the probability of the other is increased. Sex, having more chronic disease, and income generating activity might be at increased risks for both depression and anxiety. Health policy decision-makers can use our findings in developing strategies for prevention of both depression and anxiety in older adults.
Trees Increase Ant Species Richness and Change Community Composition in Iberian Oak Savannahs

Iberian man-made oak savannahs (so called dehesas) are traditional silvopastoral systems with a high natural value. Scattered trees provide shelter and additional food to livestock (cattle in our study sites), which also makes possible for animals depending on trees in a grass-dominated landscape to be present. We compared dehesas with nearby treeless grasslands to assess the effects of oaks on ant communities. Formica subrufa, a species associated with decayed wood, was by far the most abundant species, especially in savannahs. Taxa specialized in warm habitats were the most common both in dehesas and grasslands, as expected in areas with a Mediterranean climate. Within dehesas, the number of species was higher below oak canopies than outside tree cover. Compared to treeless grasslands, the presence of oaks resulted in a higher species richness of aphid-herding and predator ants, probably because trees offer shelter and resources to predators. The presence of oaks changed also the species composition, which differed between grasslands and dehesas. In self-standing scattered oaks, ant communities did not differ between the trunks and soil below canopies. These results stress the conservation value of trees in dehesas; within grasslands, they offer an additional microhabitat for species that would otherwise be scarce or absent.
Investigating the international and pan‐African trade in giraffe parts and derivatives

Three of the four newly distinguished giraffe species are in significant decline. Concern over the species' threat status prompted a proposal to list the giraffe, which is still recognized as a single species by the IUCN, in Appendix II of the Convention on International Trade of Endangered Species (CITES). However, there is a distinct lack of quantitative data and research on the scale, extent and purpose of both illegal and legal hunting, and the use and/or trading of giraffe and their parts. As a first step towards addressing these knowledge gaps, we conducted a literature review as well as a specialist survey regarding the use and trade of giraffe. We found that the dynamics of legal and illegal trade and the use of giraffe parts vary throughout Africa, ranging from local consumption to cross border and international trade, and from ornamental adornment to medicinal and consumption use. While the CITES listing of giraffe provides a mechanism through which international trade can be monitored, our findings suggest that the majority of illegal hunting currently occurs domestically and only within certain giraffe populations. This article is the first step towards understanding the drivers and managing the associated impacts of unsustainable and illegal giraffe use and trade.
Development of data-to-text (D2T) on generic data using fuzzy sets

Data-to-Text (D2T) is an option for translating non-linguistic data into textual form. However, along with technological developments, the various fields of data and the variety of users are one of the focuses that must be considered in the development of D2T. This study aims to develop a D2T system with input in the form of general data so that it can receive data from any field or domain, whether the data have header information, data types, rules or not. Then fuzzy rule based systems are used to interpret data in general. The system developed can produce information in the form of data summaries, newest data information
Using Machine Learning Techniques for Asserting Cellular Damage Induced by High-LET Particle Radiation

This is a study concerning the use of Machine Learning (ML) techniques to ascertain the impacts of particle ionizing radiation (IR) on cell survival and DNA damage. Current empirical models do not always take into account intrinsic complexities and stochastic effects of the interactions of IR and cell populations. Furthermore, these models often lack in biophysical interpretations of the irradiation outcomes. The linear quadratic (LQ) model is a common way to associate the biological response of a cell population with the radiation dose. The parameters of the LQ model are used to extrapolate the relation between the dosage and the survival fraction of a cell population. The goal was to create a ML-based model that predicts the α and β parameters of the well known and established LQ model, along with the key metrics of DNA damage induction. The main target of this effort was, on the one hand, the development of a computational framework that will be able to assess key radiobiophysical quantities, and on the other hand, to provide meaningful interpretations of the outputs. Based on our results, as some metrics of the adaptability and training efficiency, our ML models exhibited 0.18 median error (relative root mean squared error (RRMSE)) in the prediction of the α parameter and errors of less than 0.01 for various DNA damage quantities; the prediction for β exhibited a rather large error of 0.75. Our study is based on experimental data from a publicly available dataset of irradiation studies. All types of complex DNA damage (all clusters), and the number of double-stranded breaks (DSBs), which are widely accepted to be closely related to cell survival and the detrimental biological effects of IR, were calculated using the fast Monte Carlo Damage Simulation software (MCDS). We critically discussed the varying importance of physical parameters such as charge and linear energy transfer (LET); we also discussed the uncertainties of our predictions and future directions, and the dynamics of our approach.
Building Trust through Knowledge Sharing: Implications for Incentive System Design

Abstract We examine whether knowledge sharing can enhance the efficacy of implicit, trust-based incentives. Using a stark laboratory experiment, we find support for theory suggesting that individuals believe that their knowledge is an important part of their identity, making it costly to share, but facilitating greater trust that recipients of this knowledge will reciprocate with future rewards. Utilizing participants with substantial work experience, results from additional scenario-based experiments demonstrate practical implications of this theory. Collectively, the results from our experiments show that individuals help others less when the help conveys personal knowledge relative to when it does not absent the prospect of rewards, but more when they can expect future rewards (i.e., with implicit incentives). Importantly, knowledge sharing increases the efficacy of implicit incentives more when they are determined by the help recipient relative to someone else (e.g., a supervisor). Collectively, we contribute to a better understanding of incentive systems designed to promote knowledge sharing in practice.
Non‐Destructive Testing in Civil Engineering (NDT‐CE)

<p>ML has been successfully applied to solve many NDT-CE tasks. This is usually demonstrated with performance metrics that evaluate the model as a whole based on a given set of data. However, since in most cases the creation of reference data is extremely expensive, the data used is generally much sparser than in other areas, such as e-commerce. As a result, performance indicators often do not reflect the practical applicability of the ML model. Estimates that quantify transferability from one case to another are necessary to meet this challenge and pave the way for real world applications. </p><p>In this contribution we invetigate the uncertainty of ML in new NDT-CE scenarios. For this purpose, we have extended an existing training data set for the classification of corrosion damage by a new case study. Our data set includes half-cell potential mapping and ground-penetrating radar measurements. The measurements were performed on large-area concrete samples with built-in chloride-induced corrosion of reinforcement. The experiment simulated the entire life cycle of chloride induced exposed concrete components in the laboratory. The unique ability to monitor deterioration and initiate targeted corrosion initiation allowed the data to be labelled - which is crucial to ML. To investigate transferability, we extend our data by including new design features of the test specimen and environmental conditions. This allows to express the change of these features in new scenarios as uncertainties using statistical methods. We compare different sampling and statistical distribution-based approaches and show how these methods can be used to close knowledge gaps of ML models in NDT. </p>
Reliability and Validity of the Side-lying Instability and Prone Instability Tests in Patients with Lumbar Segmental Instability

PURPOSE: The purpose of this study is to conduct inter-rater and intra-rater reliability tests in patients with low back pain (LBP) using the prone instability test (PIT) and side-lying instability test (SIT). We have analyzed the Korean version Oswestry disability index (K-ODI) correlations and radiograph finding (RF) for validity. METHODS: Individuals (n = 51) (mean age of 40.27 ± 13.28) with LBP for at least over a week were recruited, together with two participating physical therapist examiners. The measurement consisted of PIT, PST, K-ODI, and RF. Sensitivity (Sn), specificity (Sp), positive predictive value, negative predictive value, prevalence index, agreement %, Cohen's kappa, and prevalence-adjusted bias-adjusted kappa (PABAK) were calculated. The PIT and SIT were compared with RF for validity analysis, while PIT, SIT, K-ODI, and RF were calculated for the correlation analysis. RESULTS: The intra-rater reliability test measured for the PIT (kappa = .79, PABAK = .88) and SIT (kappa = .73, PABAK = .84), and inter-rater reliability test measured for the SIT (kappa = .80, PABAK = .88) showed good agreements. The PIT (Sn = .65, Sp = .63) and SIT validities (Sn = .68, Sp = .70) were compared with RF, showing a significant correlation in PIT and RF (r = .69), SIT and RF (r = .73), and PIT and K-ODI (r = .53). CONCLUSION: The SIT is a more comfortable position test than the PIT in patients. Both PIT and SIT have acceptable reliability and validity.