Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of External Debt on Economic Growth of Nepalese Economy

This paper aims to identify the impact of external debt on the GDP of Nepal using a qualitative and quantitative research design (mixed design). The test of the unit root of the series is the first step in determining whether the data are stationary or not. An augmented Dicky-Fuller unit root test and a co-integration test are employed to check the relationship of the variables under study. This study reveals that LNED, LNGFCF, LNTR, LNEXP, LNREM, and LNBRATE are insignificant. The coefficient of LNED (-0.82) implies that a 1 percent increase in external debt leads to a decrease of 0.82 percent in gross domestic production, just as a 1 percent increase in gross fixed capital formation contributes to an increase of 3.28 percent in GDP. other macroeconomic variables like the coefficient of LNTR (-3.78) imply that a 1 percent increase in total revenue decreases 3.78 percent in GDP; the coefficient of LNEXP (2.93) implies that a 1 percent increase in government expenditure increases 2.93 percent in GDP. In the same way, LNREM and LNBRATE contribute negatively to GDP. The speed of adjustment from the previous year’s disequilibrium in GDP added to the current year’s equilibrium is only 20.63 percent. Heteroscedasticity test: Breusch-Pagan-Godfrey and normality test are greater than 5 percent, which is desirable. So, this model is free from heteroscedasticity. The residual is normally distributed. The model is robust and stable, as both the lines’ long-run and short-run coefficients are acceptable over the study period from 1974/1975 to 2019/20. The diagnostic tests confirm that the models have the desired econometric properties.
The role of in situ ocean data assimilation in ECMWF subseasonal forecasts of sea‐surface temperature and mixed‐layer depth over the tropical Pacific ocean

The tropical Pacific plays an important role in modulating the global climate through its prevailing sea‐surface temperature spatial structure and dominant climate modes like El Niño–Southern Oscillation (ENSO), the Madden–Julian Oscillation (MJO), and their teleconnections. These modes of variability, including their oceanic anomalies, are considered to provide sources of prediction skill on subseasonal timescales in the Tropics. Therefore, this study aims to examine how assimilating in situ ocean observations influences the initial ocean sea‐surface temperature (SST) and mixed‐layer depth (MLD) and their subseasonal forecasts. We analyze two subseasonal forecast systems generated with the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), where the ocean states were initialized using two Observing‐System Experiment (OSE) reanalyses. We find that the SST differences between forecasts with and without ocean data assimilation grow with time, resulting in a reduced cold‐tongue bias when assimilating ocean observations. Two mechanisms related to air–sea coupling are considered to contribute to this growth of SST differences. One is a positive feedback between the zonal SST gradient, pressure gradient, and surface wind. The other is the difference in Ekman suction and mixing at the Equator due to surface wind‐speed differences. While the initial mixed‐layer depth (MLD) can be improved through ocean data assimilation, this improvement is not maintained in the forecasts. Instead, the MLD in both experiments shoals rapidly at the beginning of the forecast. These results emphasize how initialization and model biases influence air–sea interaction and the accuracy of subseasonal forecasts in the tropical Pacific.
How job crafting behaviors influence the innovative behavior of knowledge workers in the gig economy: based on the organismic integration theory

Introduction The gig economy is extolled for its potential to stimulate economic and social development. This study examines the mediating roles of controlled and autonomous motivation in the relationship between job crafting and innovative behavior in the context of knowledge workers in the gig economy. Methods To examine these relationships, we propose and test a conceptual framework using an online survey conducted among knowledge workers in China. The participants consisted of 302 knowledge workers who voluntarily participated in the study. We used structural equation modeling to test the proposed relationships among the variables. Results Controlled and autonomous motivation mediates the relationship between job crafting and innovative behavior. Discussion Our study shed light on the knowledge workers’ motivation dilemma in the gig economy, with theoretical implications for research regarding job crafting, motivation, and practice implications about the job crafting and innovative behavior of knowledge workers.
Compact Low Repetition Rate Optical Parametric Oscillators Enabled by Herriott Cells

Three-photon fluorescence microscopy exploits a tissue transparency window around $1.6-1.8\ \mu \mathrm{m}$ to enable imaging at greater depths than can be achieved using two-photon fluorescence [1], but typically requires expensive few-MHz laser sources such as optical parametric amplifiers (OPAs). Such systems are optically inefficient, requiring bulky, high-average-power pump lasers. An ultrafast optical parametric oscillator (OPO) can in theory provide the same performance with a fraction of the pump power, yet requires a long cavity length to achieve few-MHz operation in a synchronous configuration. To address this issue we present a synchronously-pumped OPO which employs an intracavity Herriott cell (HC) [2] to provide the same optical path in a compact footprint.
Reducing cost in DNA-based data storage by sequence analysis-aided soft information decoding of variable-length reads

Abstract Motivation DNA-based data storage is one of the most attractive research areas for future archival storage. However, it faces the problems of high writing and reading costs for practical use. There have been many efforts to resolve this problem, but existing schemes are not fully suitable for DNA-based data storage, and more cost reduction is needed. Results We propose whole encoding and decoding procedures for DNA storage. The encoding procedure consists of a carefully designed single low-density parity-check code as an inter-oligo code, which corrects errors and dropouts efficiently. We apply new clustering and alignment methods that operate on variable-length reads to aid the decoding performance. We use edit distance and quality scores during the sequence analysis-aided decoding procedure, which can discard abnormal reads and utilize high-quality soft information. We store 548.83 KB of an image file in DNA oligos and achieve a writing cost reduction of 7.46% and a significant reading cost reduction of 26.57% and 19.41% compared with the two previous works. Availability and implementation Data and codes for all the algorithms proposed in this study are available at: https://github.com/sjpark0905/DNA-LDPC-codes.
Electride and Magnetic Properties of Ternary Intermetallic Compounds LaTMSi

We present a theoretical study of the electronic, spectral, and magnetic properties of ternary intermetallic LaTMSi (where TM = Mn, Sc) compounds within the DFT+DMFT method combining density functional theory with dynamical mean-field theory. It is demonstrated that compounds of the LaTMSi series are interesting for magnetic orderings and electride properties prospective for catalytic applications. The DFT+DMFT calculations for manganese compounds at 1000 K indicate a high-spin to low-spin crossover in Mn-3d ions with pressure. We find that scandium ternary compound LaScSi exhibits high interstitial density characteristics of electrides. Our calculations show that both lanthanum and scandium 5d orbitals contribute electrons to the strongly localized interstitial electron density, which can be considered an electride anion with pronounced s-symmetry.
Torque Characteristic Analysis and Measurement of Magnetic Rack–Pinion Gear Based on Analytical Method

This paper analyzes the torque characteristics of a magnetic rack-and-pinion gear using an analytical method based on the spatial harmonic method. We obtain the magnetic field distribution due to the permanent magnets and derive the magnetic torque from the magnetic field using the Maxwell stress tensor. The analytical results are extensively validated by comparing with finite element analysis results. Finally, we obtain an accurate analytical solution to reduce the analysis time and experimentally verify this solution by applying it to a newly manufactured rack–pinion gear model.
The individual tree and forest stand level impacts of winter moth defoliation in eastern Massachusetts, USA

5 Introduction.6 Methods. 9 Results.15 Discussion. 17 Acknowledgements.22 References.23 Tables. 28 Figures. 30 III. THE EFFECTS OF NOVEL WINTER MOTH DEFOLIATION IN FOREST STANDS IN EASTERN MASSACHUSETTS, USA**. 34
Fighter Cockpit Adaption to Online Situation Awareness Measurement

Fighter pilots face a broad task spectrum in the cockpit. Their tasks are considerably more challenging than those of civil pilots due to additional mission tasks, which include control of sensors, weapons, and other systems, under consideration of constraints and uncertainties. In addition, the pilots coordinate with manned and, as envisioned in fighter development programs (e.g., FCAS), unmanned platforms. This adds coordination with manned-unmanned teams to the pilots’ responsibilities (Lindner et al., 2022). In this multitasking environment, efficient management of attention is crucial to pilot performance (Olivier Lefrancois et al., 2016). Attention-related problems in human-automation interaction are well known and often described as a possible cause of aviation accidents (Jones & Endsley, 1996; Kelly & Efthymiou, 2019; Shorrock, 2007). There are different problems described in literature, such as attentional tunneling (Wickens, 2005), inattentional blindness or deafness (Dehais et al., 2019), vigilance performance decrement (Thomson et al., 2015) or complacency (Parasuraman & Manzey, 2010). The consequence of all these phenomena is a loss of situation awareness (SA) in specific situational aspects when the pilot fails to attend relevant information in the cockpit (Jones & Endsley, 1996). Effective training in monitoring and automation operation is crucial to improve pilot attention management, but nevertheless, the interaction between pilots and cockpit remains ‘hierarchical’ in the sense, that the cockpit cannot be aware of the pilot’s errors. In this context, the idea of developing user-aware systems has been proposed to enable error-reducing adaption of a workplace (Brand & Schulte, 2018; Fortmann & Mengeringhausen, 2014; Peysakhovich et al., 2018).
Assessment of Noise Pollution and Health Impacts of the Exposed Population in an Urban Area of Chhattisgarh, India

The present study aimed to evaluate the possible impact of noise pollution. This study was conducted in Raipur, the capital of Chhattisgarh state, India, to analyze the relationship between noise pollution and health complaints. A total of 18 locations were selected for monitoring noise pollution levels in the morning (9:00-10:30 AM) and evening (7:00-8:30 PM). Noise maps were prepared for both the time interval, and it was found that the highest equivalent noise level (Leq)of 81.31 dBA was observed at location L3 whereas the lowest Leq of 63.25 dBA was observed at L16 in the morning and in the evening 77.33 dBA at L3 and 60.14 dBA at L16 were observed. A questionnaire survey was performed on the population (n = 400) exposed to noise and analyzed through a variance-based partial least square (PLS) structural equation model (SEM). From the survey, it was found that most of the respondents are exposed to higher noise levels and are facing health issues of “pain in the ear,” “rise in blood pressure,” “loss of sleep,” “whistling and buzzing” in their ear, “headache,” “heaviness” and “efficiency problem. ” A total of 109 hypotheses were proposed and analyzed through bootstrapping with a subsample size of 5000 in SmartPLS software. 18 hypotheses were found to be significant in the proposed model. SEM analysis revealed an interrelation between noise pollution and health effects. It is recommended that strict regulation in nearby sensitive areas must be imposed and an awareness drive on a large scale shall be conducted to enlighten the city’s population regarding noise effects as well as various measures for controlling.
Review Article Topographic Slope as a Proxy for Seismic Site Conditions and Amplification

We describe a technique to derive first-order site-condition maps di- rectly from topographic data. For calibration, we use global 30 arc sec topographic data and VS 30 measurements (here VS 30 refers to the average shear-velocity down to 30 m) aggregated from several studies in the United States, as well as in Taiwan, Italy, and Australia. VS 30 values are correlated against topographic slope to develop two sets of parameters for deriving VS 30 : one for active tectonic regions where to- pographic relief is high, and one for stable shields where topography ismoresubdued. By taking the gradient of the topography and choosing ranges of slope that maximize the correlation with shallow shear-velocity observations, we can recover, to first order, many of the spatially varying features of site-condition maps developed for California. Our site-condition map for the low-relief Mississippi Embayment also predicts the bulk of the VS 30 observations in that region despite rather low slope ranges. We find that maps derived from the slope of the topography are often well cor- related with other independently derived, regional-scale site-condition maps, but the latter maps vary in quality and continuity, and subsequently, also in their ability to match observed V S 30 measurements contained therein. Alternatively, the slope-based method provides a simple approach to uniform site-condition mapping. After validating this approach in regions with numerous V S 30 observations, we subsequently estimate and map site conditions for the entire continental United States using the respective slope correlations.
Effect of Various Parameters on Finishing of Inner Surfaces of Brass Tubes Using Magnetic Abrasive by RSM: A Study

With the increase of technology and the demand of industry the surface finish requirements are also increasing. Conventional echnologies like grinding and lapping etc. fail to finish some pieces such as pipes, complex shape tubes consisting of straight and bent sections up to desired accuracy. Magnetic Abrasive Finishing (MAF) is one of the a dvanced finishing methods, proposed to produce highly finished surfaces of brass340 pipes. In this research work the process, finishing characteristics and the principle of magnetic abrasive finishing of pipes using sintered magnetic abrasives are described. The sintered based of Al2O3 magnetic abrasives with iron particle of size 106 μm were used in this work. The Statistically designed experiments based on Taguchi methods show that weight of abrasive, Revolutions per minute (rpm), finishing time and type of lubricant which have significant effect on the surface roughness obtained. The effects of lubricants on surface finish are also analyzed in this work by using different types of lubricants. It is noticed that the surface finish was affected by the change of type of lubricant and the internal surface finish of pipes were analyzed in terms of percent improvement in surface finish (PISF) and using Response Surface Methodology (RSM). The obtained maximum PISF was 60% by using toothpaste as a lubricant and minimum surface r oughness w as 0 . 126 μ m R a. T he improvement in surface finish was further validated using RRay Diffraction (XRD) technique.
Vehicle Detection Using 2-axis MI sensors Based on Moving Vehicle Magnetic Field Simulation

With the number of vehicles increasing year by year, the development of Internet of Things (IoT) in Intelligent Transportation Systems (ITS) is accelerating. Using magnetic sensors to detect vehicles on the road has been regarded as an efficient and cost-effective approach for traffic surveillance. In this paper, we propose a bar magnet model and a magnetic dipole model to simulate the magnetic perturbations during the vehicle movement. The characteristics of the two models were analyzed by comparing simulated signals to measured signals. We propose a detection method using a 2-axis magneto-impedance (MI) sensor and use an algorithm to calculate the dynamic threshold for detecting the car, achieved a 98% detection rate for a single lane and an 86% detection rate for the second lane included.
Influence of Environmental Scanning on the Performance of Small and Medium Manufacturing Enterprises in Kenya

This paper addresses the Influence of Environmental Scanning on the Performance of Small and Medium Manufacturing Enterprises in Kenya. Methodically, the study was guided by the positivism research philosophy. The study applied cross-sectional descriptive research design since data collection in this study was carried out in a structured inexpensive and minimal time-consuming manner, assisting in answering the when, who, where, what and how questions and also determine whether a relationship exists between the dependent and independent variables. The population of the study targeted was 622 manufacturing SMEs registered under the Kenya Association of Manufacturers (KAM) membership, based in Kenya. This study adopted stratified random sampling technique to select 243 managers for the study. Primary data was collected using a structured questionnaire that was designed based on the research objectives. Both descriptive and inferential analyses were employed for analysis. Regression analysis found that environmental scanning significantly predicts performance of Small and Medium Manufacturing Enterprises in Kenya, R2 = . 398, F (1,194) = 63.840, p = . 000 < . 05. Hence, the null hypothesis of the study was rejected and the study concluded that environmental scanning significantly influences performance of Small and Medium Manufacturing Enterprises in Kenya. The managers and owners of the SMEs should develop an awareness of their industry and competitors, and consequently scan the environment regularly. In addition, the government should work together with manufacturing SME firms in creating and providing conducive business environments that aid sustainable organizational growth resulting in better business performance.
A Miniaturized Magic-T Using Microstrip-to-Coplanar Strips Transition and its Application to a Reflection-Type Phase Shifter

This article proposes a miniaturized magic-T and experimentally demonstrates that the magic-T is a suitable hybrid circuit for designing a wideband reflection-type phase shifter (RTPS) with a simple configuration. Conventional RTPSs employ quadrature hybrid couplers with narrow bandwidths and complicated structures. The proposed magic-T makes an RTPS broadband and compact with low insertion loss (IL) and wide relative phase shifts. The practical challenge is that the circuit must achieve compactness, low IL, and wide bandwidth simultaneously. A magic-T that meets the conditions is designed, combining a ring-shaped T-divider with a microstrip-to-coplanar strips (CPSs) transition. The circumference is a half-guided wavelength, and an IL is less than 1.0 dB in a 100% fractional bandwidth (FBW). Then, an RTPS based on the circuit is designed at 2.0 GHz. The prototype has 46% FBW, where $|S_{11}|$ is less than −10 dB, IL of 1.6± 0.5 dB, and relative phase shifts of 290°.
A Lightweight Knowledge-Distillation-Based Model for the Detection and Classification of Impacted Mandibular Third Molars

The extraction of impacted third molars is one of the most common dental operations. When the impacted third molar is extracted, the operation plan is generally different because of the different impacted positions of the tooth. Therefore, judging the impacted type of the third molar is the basis of the third molar extraction operation. At present, oral health professionals usually analyze panoramic radiographs to determine the types of impacted third molars, but the diagnosis is easily affected by oral health professionals’ subjective consciousnesses. Computer vision technology can help doctors analyze medical images faster and more accurately, so it is very desirable to use computer vision to detect and classify the impacted third molars. Based on the panoramic radiographs of the School of Stomatology, Lanzhou University, this paper establishes an object detection dataset containing six types of impacted third molars. On the basis of this dataset, the lightweight third molar impacted detection and classification model is studied in this paper. This study introduces the method of knowledge distillation on the basis of YOLOv5s and uses YOLOv5x as the teacher’s model to guide YOLOv5s, which not only ensures the light weight of the model but also improves the accuracy of the model. Finally, the YOLOv5s-x model is obtained. The experimental results show that the introduction of knowledge distillation effectively improves the accuracy of the model while ensuring its light weight, the mAP of YOLOv5s-x is increased by 2.9% compared with the original model, and the amount of parameters and calculations is also reduced to a certain extent. Compared with mainstream object detection networks, including YOLOv8, YOLOv5s-x also has certain advantages, which can provide oral health professionals with better impacted third molar detection and classification services.
Design and performance evaluation of a high power density EMI filter for PWM inverter-fed induction motor drives

This paper presents the design of an electromagnetic interference (EMI) filter for a low voltage high current induction motor drives supplied by DC power grids, such as those used in several vehicle applications. In order to effectively design the EMI filter a suitable Common Mode/Differential Mode (CM/DM) separation technique has been used. In consideration of the high operating currents, a software based separation technique using time domain measurements has been applied. The proposed technique allows the CM and DM sections of the EMI filter to be properly selected in a more economical way, i.e. without the need of dedicated hardware or costly radio frequency (RF) instrumentation. The design has been done according to a power density criterion. The effectiveness of the proposed CM/DM separation technique and the EMI filter features/performance have been assessed by experimental tests, carried out with a 1.1 kW PWM inverter-fed induction motor drive, supplied by a 48V DC power grid.
An Adaptive Robust Optimization Model for Microgrids Operation Using Convexified AC Power Flow Equations

Considering the increasing penetration of renewable energy sources (RESs) into power grids, adopting efficient energy management strategies is vital to mitigate the uncertainty issues resulting from the intermittent nature of their output power. This paper aims to resolve the energy management problem by presenting an adaptive robust optimization (ARO) model in which uncertainties associated with solar and wind powers, consumer demand, and electricity prices are considered. The proposed model comprises three stages, one master and two subproblems, using both linearized and convexified power flow equations. Meanwhile, a new optimization-based bound tightening (OBBT) method is also presented to strengthen the relaxation. The proposed solution method solves the microgrid (MG) operation management problem with high accuracy due to considering the convexification method in a reasonable computational time and reducing operational costs compared to conventional models. The numerical results indicate the benefits of the proposed ARO and solution approach over traditional methods.