Miracle-dz/UniFAR-FTUs huggingface dataset:
Status Quo in Requirements Engineering

Requirements Engineering (RE) has established itself as a software engineering discipline over the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically derive an empirical theory in context of the RE discipline have just recently been started. However, such a theory is needed if we are to define and motivate guidance in performing high quality RE research and practice. We aim at providing an empirical and externally valid foundation for a theory of RE practice, which helps software engineers establish effective and efficient RE processes in a problem-driven manner. We designed a survey instrument and an engineer-focused theory that was first piloted in Germany and, after making substantial modifications, has now been replicated in 10 countries worldwide. We have a theory in the form of a set of propositions inferred from our experiences and available studies, as well as the results from our pilot study in Germany. We evaluate the propositions with bootstrapped confidence intervals and derive potential explanations for the propositions. In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from the replication studies conducted in 10 countries with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirical theory of RE practice. The results reveal, for example, that there are no strong differences between organisations in different countries and regions, that interviews, facilitated meetings and prototyping are the most used elicitation techniques, that requirements are often documented textually, that traces between requirements and code or design documents are common, that requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly internally driven. Our study establishes a theory that can be used as starting point for many further studies for more detailed investigations. Practitioners can use the results as theory-supported guidance on selecting suitable RE methods and techniques.
Understanding Hydrological Processes under Land Use Land Cover Change in the Upper Genale River Basin, Ethiopia

The expansion of cultivated land in place of natural vegetation has a substantial influence on hydrologic characteristics of a watershed. However, due to basin characteristics and the nature and intensity of landscape modification, the response varies across basins. This study aims to evaluate the performance of a soil and water assessment tool (SWAT) model and its applicability in assessing the effects of land use land cover (LULC) changes on the hydrological processes of the upper Genale River basin. The results of satellite change detection over the past 30 years (between 1986 and 2016) revealed that the landscape of the basin has changed considerably. They showed that settlement, cultivated, and bare land areas had increased from 0.16% to 0.28%, 24.4% to 47.1%, and 0.16% to 0.62%, respectively. On the contrary, land cover units such as forest, shrubland, and grassland reduced from 29.6% to 13.5%, 23.9% to 19.5%, and 21.8% to 18.9%, respectively. Based on monthly measured flow data, the model was calibrated and validated in SWAT-CUP using the sequential uncertainty fitting (SUFI-2) algorithm. The result showed that the model performed well with coefficient of determination (R2) ≥ 0.74, Nash–Sutcliffe efficiency (NSE) ≥ 0.72, and percent bias (PBIAS) between −5% and 5% for the calibration and validation periods. The hydrological responses of LULC change for the 1986, 2001, and 2016 models showed that the average annual runoff increased by 13.7% and 7.9% and groundwater flow decreased by 2.85% and 2.1% between 1986 and 2001 and 2001 and 2016, respectively. Similarly, the total water yields increased from 324.42 mm to 339.63 mm and from 339.63 mm to 347.32 mm between 1986 and 2001 and 2001 and 2016, respectively. The change in hydrological processes, mainly the rise in runoff and total water yield as well as the reduction in lateral and groundwater flow in the watershed, resulted from LULC changes. This change has broader implications for the planning and management of the land use and water resource development.
Higher harmonics calculation of synchronous generators on the basis of magnetic field analysis considering rotor movement

A simple analysis method is proposed for output voltage waveforms and magnetic flux waveforms passing through the main stator parts of synchronous generators. The method considers the rotor movement in order to analyze the higher harmonic sequences and some techniques for simplifying the calculation using the symmetry of armature windings and stator slot arrangements. The effectiveness of the higher harmonics analysis method under saturated conditions, is verified by 50-MV A-class generator analysis. It is useful for quantitative evaluation of the voltage and magnetic flux waveforms and no-load saturation characteristics of synchronous generators. >
Unexpected shocks to movement and job search: evidence from COVID-19 policies in Singapore using Google data

This paper uses Google data in Singapore to study the impact of COVID-19 policies. First, I ﬁnd diﬀerences in the eﬃcacy of the two movement controls, and that their announcements led to same-day increases in foot traﬃc. Second, I ﬁnd evidence that online job search either stayed the same or has fallen. With a larger pool of potential candidates, this implies a drop in average search per worker. Finally, the data suggests that movement restrictions aﬀected job search intensity, the implication being that while stay-home mandates are nec-essary to ﬂatten the curve, it potentially creates another shock to labour supply which is more hidden than the demand side.
Design and Characterization of a Mckibben Pneumatic Muscle Prototype with an Embedded Capacitive Length Transducer

The McKibben muscle types are pneumatic actuators known to be intrinsically safe for their high power-to-weight ratio. For these reasons, they are suitable for robotic, biomechanical, and medical applications. In these application fields and, above all, in collaborative robotics, where safety must be ensured for human–robot interactions, the values of pressure, force, and length are necessary and must be continuously monitored and controlled. Force and pressure transducers are commercially available to be integrated into a McKibben muscle type. On the contrary, no commercial-length transducers can be adopted. This work presents a novel McKibben muscle prototype with an embedded capacitive-length transducer. The latter is a cylindrical capacitor made of a telescopic system composed of two tubes: one of its ends is connected to the muscle. A change in the length of the muscle causes a proportional change in the transducer capacitance. The paper reports in detail on the working principle of McKibben’s muscle, its fabrication, characterization, and validation of four prototype capacitive transducers. The results achieved from the experimental activities demonstrate that it is possible to control the variations of the muscle length relative to its elongation and compression for values less than 1 mm. This is the consequence of the ability to measure the transducer capacitance with a typical statistical relative indetermination better than 0.25%, which is a figure of merit for the reliability and mechanical and electrical stability of the proposed McKibben muscle prototype. Moreover, it has been demonstrated that the transducer capacitance as a function of the muscle length is linear, with maximum deviations from linearity equal to 2.44% and 5.22% during the muscle elongation and compression, respectively.
Effect of Fortified Formula on Growth and Nutritional Status in Young Children: A Systematic Review and Meta-Analysis

Previous reviews of the effect of young child formulas on health outcomes in infants and toddlers have been inconclusive. In this study, we undertook a contemporary synthesis of studies investigating the effects of consuming fortified milk beverages (compared to cow’s milk or unfortified comparator formula) on growth and/or nutritional status in children 1–3 years of age. Five electronic databases were searched (PubMed, Web of Science, Scopus, ProQuest, and Cochrane Library) for randomised controlled trials comparing fortified milk against control milk in young children (9–48 months), published between January 1990 and June 2022. Outcomes were growth, body composition, biochemical markers, and/or nutritional status. Mean differences (MD) were pooled using random-effects meta-analysis where there were ≥3 studies. The risk of bias was assessed using the Cochrane Risk of Bias 2.0 tool. Nineteen articles (12 studies; n = 4795) met the inclusion criteria. Heterogeneity was substantial, likely attributable to considerable variation in study characteristics. Fortified milk was associated with increased weight gain (MD = 0.14 kg [95% CI 0.06, 021], p = 0.0003) compared with control milk. Subgroup analyses demonstrated increases in weight in lower-income countries, and in studies with intervention periods > 6 months. There were no effects of fortified milks on other anthropometric measures. Haemoglobin (MD = 3.76 g/L [95% CI 0.17, 7.34], p = 0.04) and ferritin (MD = 0.01 nmol/L [95% CI 0.00, 0.02], p = 0.02) concentrations were increased in infants consuming fortified milks. Fortified milk beverages appear to offer a safe and acceptable source of complementary nutrition as a short-term strategy for addressing nutritional deficits and may modestly promote weight gain in vulnerable populations when provided for periods > 6 months. This study was prospectively registered with PROSPERO (CRD42022339920) and funded by the Infant Nutrition Council.
Regression Function Estimation Using Spline Wavelets

ABSTRACT We obtain an estimator for the non parametric regression function using spline wavelets. A bound for the mean integrated square error is also derived. We use this approach to fit a curve for the movement of stock price of Bombay Stock Exchange (BSE) with respect to time. The result of the above curve fitting is compared graphically with those obtained by using the Nadaraya–Watson's estimator, Lyche–Schumaker estimator, and an orthogonal series estimator.
Maximizing Student Retention using Supervised Models Informed by Student Counseling Data

Student retention is one main challenge faced by higher education institutions in Colombia. Over recent years, there has been an increasing trend of students dropping out of university for various academic, social, economic, institutional, or personal reasons. This has significant impacts on private higher education institutions, whose main livelihood depends on student numbers, with some institutions in a critical situation. In this paper, we design and implement a data analytics model that predicts the risk of dropout that students may present. The sources of information used to construct this model contain academic and socioeconomic variables, covering past academic periods to understand the problem in detail. Machine Learning approaches are used to determine the best model using the CRISP-DM methodology. This model is deployed via a decision-making tool for the academic counseling office, whose main objective is to maximize student retention.
Trees, stars, and multiple biological sequence alignment

One important problem in biological sequence comparison is how to simultaneously align several nucleic acid or protein sequences. A multiple alignment avoids possible inconsistencies among several pairwise alignments and can elucidate relationships not evident from pairwise comparisons. The basic dynamic programming algorithm for optimal multiple sequence alignment requires too much time to be practical for more than three sequences, the length of an average protein. Recently, Carrillo and Lipman (SIAMJ. Appl. Math., 48 (1988), pp. 1073–1082) have rendered feasible the optimal simultaneous alignment of as many as six sequences by showing that a consideration of minimal pairwise alignment costs can vastly decrease the number of cells a dynamic programming algorithm need consider. Their argument, however, requires the cost of a multiple alignment to be a weighted sum of the costs of its projected pairwise alignments.This paper presents an extension of Carrillo and Lipman's algorithm to the definition of mul.
Studies on Parameters Affecting Temperature of Liquid Steel and Prediction Using Modified AdaBoost.RT Algorithm Ensemble Extreme Learning Machine

The present work aimed to develop a predictive model for the end temperature of liquid steel in advance to support the smooth functioning of a vacuum tank degasser (VTD). An ensemble model that combines extreme learning machine (ELM) with a self-adaptive AdaBoost.RT algorithm was established for the regression problem. Based on analyzing the energy equilibrium of the VTD system, the factors were determined for predicting the end temperature of liquid steel. To establish a hybrid ensemble prediction model, an ELM algorithm was selected as the ensemble predictor due to its strong performance and robustness, and a modification of the AdaBoost.RT algorithm is proposed to overcome the drawback of the original AdaBoost.RT by embedding statistical theory to dynamically self-adjust the threshold value. For efficient VTD operations, an ensemble model that combines ELM with the self-adaptive AdaBoost.RT algorithm was established to model the end temperature of liquid steel. The proposed approach was analyzed and validated on actual production data derived from a steelmaking workshop in Baosteel. The experimental results reveal that the proposed model can improve the generalization performance, and the accuracy of the model is feasible for the secondary steel refining process. In addition, a polynomial equation is obtained from the ensemble predictive model for calculating the value of the end temperature. The predicted results are in good agreement with the actual data with <1.7% error.
Nuclear gyromagnetic ratios. II

The super-regenerative oscillator techniques described in earlier reports have been modified by introduction of a tuned narrow band amplifier with chart recorder and by improvements in magnetic-field regulation. Magnetic resonance frequencies of various nuclei have been compared with the resonance frequencies of ${\mathrm{H}}^{1}$, ${\mathrm{D}}^{2}$, ${\mathrm{Li}}^{7}$, and ${\mathrm{Sc}}^{45}$, which have been used as "standards. " Ratios of the observed resonance frequencies to the proton resonance frequency in the same magnetic field are given for the following nuclear species: ${\mathrm{Be}}^{9}$, ${\mathrm{B}}^{11}$, ${\mathrm{F}}^{19}$, ${\mathrm{Na}}^{23}$, ${\mathrm{Al}}^{27}$, ${\mathrm{P}}^{31}$, ${\mathrm{V}}^{51}$, ${\mathrm{Mn}}^{55}$, ${\mathrm{Cu}}^{63}$, ${\mathrm{Cu}}^{65}$, ${\mathrm{Br}}^{79}$, ${\mathrm{Br}}^{81}$, ${\mathrm{Rb}}^{87}$, ${\mathrm{Nb}}^{93}$, ${\mathrm{I}}^{127}$, ${\mathrm{Cs}}^{133}$, ${\mathrm{La}}^{139}$, ${\mathrm{Tl}}^{203}$, and ${\mathrm{Tl}}^{205}$. The nuclear magnetic moments of these species have been determined in terms of the proton moment from the known spins and the observed frequency ratios after making diamagnetic corrections; values for the nuclear magnetic moments are listed.
Grating-like Terahertz Metasurface for Large-Deflection-Angle Beam Manipulations

Multifunctional terahertz beam manipulations have attracted much attention because of the potential for wide-scale applications in terahertz imaging, communications, etc. In this work, a grating-like terahertz reflective-type metasurface is designed for terahertz beam manipulations on the basis of a frequency-scanning mechanism. The theoretical calculation based on the grating principle has predicted that the metasurface grating can steer the deflected beam from 59.5° to 47.3° as the frequency of the perpendicularly incident terahertz wave changes between 0.87 and 1.02 THz. The large-deflection-angle frequency-scanning performance is validated by both numerical simulations and experimental tests. The metasurface grating developed in this work possesses the potential for applications in terahertz beam steering and beam-splitting devices.
An Intelligent Semantici�cation Rules Enabled User-Specic Healthcare Framework Using IoT and Deep Learning Techniques

: Things or device under the Internet of Things, when connected to the internet, becomes a product, offers various applications and services for end-users. Existing methodologies offer sensor-based IoT based health-care services, to the end-users populated with lots of sensed values all at a time, making the health-care system with least robustness and inefficient due to unsystematic preview of patient’s health record. In order to address this issue, a novel semantic-based service framework is proposed in this paper which allows the end-user to subscribe for a specific physiological parameter, among all the available sensed data, making the health-care system more efficient. In the SeSem framework, Semantification rules and semantification relationship table are applied to the sensed JavaScript object Notation format (JSON) data, in order to semantically separate the JSON data, into a meaningful format. To list the sensed data according to the significance of health issues, a priority is assigned to the sensors in the semantification relationship table. Hence, semantically separated data can be done along with assigned priority. Sensor-based Sematic (SS) ontology is then applied to the semantically separated data, to transform the sensed data more relevant in terms of particular disease and sensor associated with it. The semantically separated sensed data are then published to the Message Queuing Telemetry Transport (MQTT) interface. Using MQTT subscribe, the end-user along with date and time, requests for a particular service, using a Semantic Similarity mapping algorithm, which compares the entire sensed data to that of requested data and responds with a particular physiological parameter request. To make the health care system deploy services in an intelligent way, deep learning algorithm Feedforward Recurrent Neural Networks are applied, which makes the prediction of sensed data based on the latest update when the end-user subscribes for a certain sensed data without specifying date and time. The proposed methodology is evaluated against IoT performance metrics which had shoed showing better results in terms of service-oriented IoT.
Treatments and Predictors of Mortality for Carbapenem-Resistant Gram-Negative Bacilli Infections in Malaysia: A Retrospective Cohort Study

This study evaluated the treatments, mortality rate and patient-related factors associated with mortality. This is a retrospective study involving hospitalised patients with infections caused by carbapenem-resistant Gram-negative bacilli (CR-GNB) in a tertiary hospital in Malaysia from January 2018 to June 2020. A clinical pharmacist reviewed patients’ electronic records and collected the data according to a pre-designed form. Data were analysed using both descriptive and inferential tests. The study included 145 patients with CR-GNB infections including 77, 40 and 28 Acinetobacter baumannii, enterobacteriaceae and Pseudomonas aeruginosa, respectively. The mean age was 57.9 ± 15.8 years. Pneumonia (40.7%) and bacteremia (25.5%) were the most common infections. Meropenem (24.7%) and piperacillin-tazobactam (20.4%) were the most commonly used empiric antibiotics while colistin (63.3%) and amikacin (8.3%) were the most common definitive antibiotics. The mean duration before active antibiotics was 4.6 ± 3.3 days. Overall, the in-hospital mortality rate was 41.4%. Multivariate logistic regression analysis showed that intensive care unit (ICU) admission (adjusted odds ratio (AOR): 5.201; 95% confidence interval (CI): 1.603–16.872; p = 0.006), sepsis/septic shock (AOR: 3.430; 95% CI: 1.021–11.522; p = 0.049) and elevated serum creatinine (AOR: 2.752; 95% CI: 1.005–7.536; p = 0.049) were independently associated with mortality. The mortality rate among patients with CR-GNB infection is high. A high rate of inappropriate antibiotic use was observed, including combination antibiotic therapy and delays in starting active antibiotics. Mortality was significantly associated with ICU admission, sepsis/septic shock and elevated serum creatinine.
Packet Delivery Ratio Guarantees for Differentiated LoRaWanServices

Motivated by the rapid deployment of applications based on connected objects, we propose in this paper an approach to differentiating Packet Delivery Ratios (PDRs) in LoRa Wide Area Networks (LoRaWAN). This type of network is simple to deploy and operate at the expense of loose commitments in terms of quality. To overcome this shortcoming, we propose an access control method for isolating clusters of devices and meeting differentiated PDR targets. Results show that our method outperforms known one in terms of PDR via improved parameter allocation and achieves high level of intra-cluster fairness, at the expense however of decreasing the maximum cell range.
Utilization of Corn Steep Liquor for the Production of Fairy Chemicals by Lepista sordida Mycelia

There are various potential practical uses of fairy chemicals (FCs) in the fields of agriculture, cosmetics, and medicine; however, the production costs of FCs are very high. To enable the practical use of FCs, more efficient and inexpensive methods of culturing the mycelia of FCs-producing fungi and producing FCs need to be developed. The purpose of the present study was to determine methods of reducing the production costs of FCs and mycelia of the FCs-producing fungus Lepista sordida. We investigated the effects of four food industrial by-products, i.e., corn steep liquor (CSL), rice bran, wheat bran, and Japanese liquor lees, as nutritional additives in the liquid culture medium of the fungus. We found that CSL was more effective than the other tested additives in increasing the production of FCs and mycelia. Medium containing 1% CSL was optimal for increasing the mycelial yield while medium containing 6% CSL was optimal for increasing the production of FCs. The reason for this difference in the optimal CSL concentration was considered to be related to the stress on the mycelia caused by the amount of nutrients in the liquid medium. These results are expected to facilitate the practical use of FCs and the mycelia of FCs-producing fungi.
Interaction between short‐scale Marangoni convection and long‐scale deformational instability

Nonlinear evolution of two interacting modes of the Marangoni convection, a long‐scale deformational mode and a short‐scale stationary convective pattern, is considered. It is shown that the interaction between modes stabilizes surface deformation and leads to formation of various convective structures: stationary long‐scale modulated roll patterns, traveling and standing long waves, and can also cause chaotic convection (interfacial turbulence).