Miracle-dz/UniFAR-FTUs huggingface dataset:
ERADICATING POVERTY AND HUMAN CAPITAL DEVELOPMENT IN INDONESIA: An Approach with Multilevel Logistic Regression Model

This study investigated the socio-economic determinants at the individual and contextual level of household poverty in Indonesia. The data used in this study is drawn from the March 2020 Indonesia-National Socio-Economic Survey (Susenas) provided by BPS, Statistics-Indonesia. The data were analyzed using the Multilevel Logistics Regression Model. This study indicates that the achievement of the Human Development Index at the provincial level affects the reduction of the poor at the household level. Moreover, at the individual level, household size, education level, and employment status of the household head significantly affect household poverty. The results of this study underscore the need to look beyond the influence of individual-level factors in addressing regional variations in household poverty in Indonesia. Therefore, Government policies to increase human development in provinces with low HDI are needed.
Has the relationship between the real exchange rate and its fundamentals changed over time?

ABSTRACT In this paper we contribute to the literature on determining the real exchange rate by using models that incorporate structural breaks and nonlinearities. We estimate cointegrated dynamic ordinary least squares regressions and quantile regressions. We find that the estimated coefficients for the EU members from central and eastern Europe are different to those for the other member states. We also find that the models are different before and after the crisis that started in 2008, and this affects the outcome of the long-run equations for the EU15 + Cyprus and Malta.
Mind wandering and contextual binding

ABSTRACT In a memory-scanning task, participants were shown two rows of items followed by a cue indicating which row was the relevant memory set. The target item could be in the relevant set (a positive target), in the irrelevant set (a negative lure target), or an item not seen on the trial (a negative control target). After each block of trials, participants indicated the extent to which they were on or off task. Consistent with prior research, lure targets were more difficult to discriminate from positive targets than were control targets. However, this effect was larger when participants reported being off task. Our interpretation is that lures are more difficult to reject when mind wandering because less attention is devoted to the process of binding items to an appropriate spatial context.
Characterization of all Possible Orbits in the Schwarzschild Metric Revisited

All possible orbital trajectories and their analytical expressions in the Schwarzschild metric are presented in a single complete map characterized by two dimensionless parameters. While three possible pairs of parameters with different advantages are described, the parameter space that gives the most convenient reduction to the Newtonian case is singled out and used which leads to a new insight on Newtonian limits among other results. Numerous analytic relations are presented. A comparison is made with the widely used formulation and presentation given by S. Chandrasekhar.
A -20 to 30 dBm Input Power Range Wireless Power System With a MPPT-Based Reconfigurable 48% Efficient RF Energy Harvester and 82% Efficient A4WP Wireless Power Receiver With Open-Loop Delay Compensation

This paper presents a reconfigurable wide input power range radio frequency (RF) energy harvester (EH) with alliance for wireless power (A4WP) wireless power receiver (WPR). A reconfigurable RF-DC converter for RF EH and maximum power point tracking algorithm are proposed to maintain high efficiency over a wide input power range –20 to +20 dBm. The A4WP WPR is designed and merged with the EH to receive power higher than +20 dBm. In order to improve the power conversion efficiency (PCE), the delay between the ac input voltage and current is compensated by the proposed open-loop delay compensation method. The chip is implemented in 0.18 μm bipolar-CMOS-double-diffused metal-oxide-semiconductor process. The die area of the chip is 4.3 mm × 3.2 mm, including the pads. The proposed EH with WPR achieves a measured peak PCE of 48.19% with respect to the input power of 0 dBm at 900 MHz. It also has a peak PCE of 82.14% with respect to the input power of 30 dBm in an A4WP mode operation at 6.78 MHz.
Real-Time Charging Scheduling and Optimization of Electric Buses in a Depot

To improve the air quality in urban areas, diesel buses are getting replaced by battery electric buses (BEBs). This conversion introduces several challenges, such as the proper control of the charging process and a reduction in the operational costs, which can be addressed by introducing smart charging concepts for BEB fleets. Therefore, this paper proposes a real-time scheduling and optimization (RTSO) algorithm for the charging of multiple BEBs in a depot. The algorithm assigns a variable charging current to the different time slots the charging process of each BEB is divided to provide an optimal charging schedule that minimizes the charging cost, while satisfying the power limitations of the distribution network and maintaining the operation schedule of the BEBs. A genetic algorithm is used to solve the formulated cost function in real time. Several charging scenarios are tested in simulation, which show that a reduction in the charging cost up to 10% can be obtained under a dynamic electricity price scheme. Furthermore, the RTSO is implemented in a high-level charging management system, a new feature required to enable smart charging in practice, to test the developed algorithm with existing charging infrastructure. The experimental validation of the RTSO algorithm has proven the proper operation of the entire system.
A signal domain transform method for spatial resolution improvement of Lamb wave signals with synthetically measured relative wavenumber curves

In practical structural health monitoring with Lamb waves, the signal spatial resolution is usually restricted by not only dispersion but also the space duration of excitation waveforms, that is, the initial spatial resolution for the signals before traveling. As a result, the final resolution and accuracy of damage identification could be badly impaired. To overcome this problem, a signal domain transform method is presented in this article. In signal domain transform, the original dispersive Lamb wave signals are transformed from the time to distance domains, with the time–distance scaling on the excitation waveforms particularly modified. Then, both dispersion compensation and initial spatial resolution enhancement can be actualized to efficiently improve the signal spatial resolution. Considering the practical situation that the structural property parameters could be unavailable to theoretically derive the requisite wavenumber relations, signal domain transform with synthetically measured relative wavenumber curves is further explored. After the frequency domain representation and spatial resolution of Lamb wave signals are basically analyzed, the principle and numerical realization of signal domain transform are investigated. Hereafter, the synthetic measurement of relative wavenumber curves for signal domain transform is discussed and preliminarily validated in an aluminum plate. Finally, signal domain transform is applied for high-resolution imaging of adjacent multiple damages. The efficiency of signal domain transform and signal domain transform–based imaging methods has been well demonstrated by the experimental study on a glass fiber–reinforced composite plate with unknown material parameters.
Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models

Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and harvesting fish, while still being environmentally friendly. The proposed 2D computer vision method is aimed at non-intrusively estimating the weight of Tilapia fish in turbid water environments. Additionally, the proposed method avoids the issue of using high-cost stereo cameras and instead uses only a low-cost video camera to observe the underwater life through a single channel recording. An in-house curated Tilapia-image dataset and Tilapia-file dataset with various ages of Tilapia are used. The proposed method consists of a Tilapia detection step and Tilapia weight-estimation step. A Mask Recurrent-Convolutional Neural Network model is first trained for detecting and extracting the image dimensions (i.e., in terms of image pixels) of the fish. Secondly, is the Tilapia weight-estimation step, wherein the proposed method estimates the depth of the fish in the tanks and then converts the Tilapia’s extracted image dimensions from pixels to centimeters. Subsequently, the Tilapia’s weight is estimated by a trained model based on regression learning. Linear regression, random forest regression, and support vector regression have been developed to determine the best models for weight estimation. The achieved experimental results have demonstrated that the proposed method yields a Mean Absolute Error of 42.54 g, R2 of 0.70, and an average weight error of 30.30 (±23.09) grams in a turbid water environment, respectively, which show the practicality of the proposed framework.
Postacute Laryngeal Injuries and Dysfunctions in COVID-19 Patients: A Scoping Review

Objective: To investigate post-acute laryngeal injuries and dysfunctions (PLID) in coronavirus disease 2019 (COVID-19) patients. Methods: Three independent investigators performed a systematic review of the literature studying PLID in patients with a history of COVID-19. The review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. Epidemiological, clinical, hospitalization features, laryngeal diseases, and voice outcomes were extracted from the included papers. Results: Eight papers met our inclusion criteria (393 patients) corresponding to five uncontrolled prospective and three retrospective studies. The most prevalent PLID were vocal fold dysmotility (65%), vocal fold edema (35%), muscle tension dysphonia (21%), and laryngopharyngeal reflux (24%). Posterior glottic stenosis (12%), granuloma (14%), and posterior glottic diastasis (12%) were the most common injuries. Most patients with PLID were obese and had a history of intensive care unit hospitalization, and orotracheal intubation. The delay between the discharge and the laryngology office consultation ranged from 51 to 122 days. The mean duration of intubation ranged from 10 to 34 days. Seventy-eight (49%) intubated patients were in the prone position. The proportion of patients requiring surgical treatment ranged from 39% to 70% (mean = 48%). There was an important heterogeneity between studies about inclusion, exclusion criteria, and outcomes. Conclusions: COVID-19 appeared to be associated with PLID, especially in patients with a history of intubation. However, future controlled studies are needed to evaluate if intubated COVID-19 patients reported more frequently PLID than patients who were intubated for other conditions.
Restoring Confidence in Troubled Financial Institutions After a Financial Crisis

After an unprecedented number of banks suspended operations in the during Panic of 1893, the head regulator of banks chartered by the United States government allowed about 100 banks to reopen after certifying their solvency. We evaluate whether actions by bank owners to change management, contract with depositors to extend liability maturity structure, write off bad assets, and/or inject capital affected bank survival and deposit retention. This historical episode is particularly informative because there was no expectation of government intervention. We find that contracting with depositors provided short-term benefits while dealing with bad assets was key for long-run viability.
Human Factor Analysis (HFA) Based on a Complex Network and Its Application in Gas Explosion Accidents

Humans are at the core of the social-technical system, and their behavioral errors affect the reliability and safety of the entire system in varying degrees. Occupational accidents and large-scale industrial accidents are often attributed to human errors, accounting for more than 80% of accidents. In view of the complexity of systems and the coupling of elements, a new HFA method is proposed based on a complex network. According to system safety theory, a complex network is regarded as a network composed of humans, matters, environments, and management, and the basic structure of the HFA network is summarized. On this basis, a system safety method of HFA is developed which proposes a universal human error causation model. Moreover, a network analysis method for human errors is also presented, which is a comprehensive analysis of human errors that have occurred. Finally, the above methods are applied to gas explosion accidents that occurred in China. Results show that the two methods proposed are universal to all fields, and their combination improves the effectiveness of human error management and promotes the targeted, proactive, systematic, and dynamic prevention of critical nodes and paths from a holistic perspective.
Derivation and Application of a New Transmission Loss Formula for Power System Economic Dispatch

The expression and calculation of transmission loss (TL) play key roles for solving the power system economic dispatch (ED) problem. ED including TL must compute the total TL and incremental transmission loss (ITL) by executing power flow equations. However, solving the power flow equations is time-consuming and may result in divergence by the iteration procedure. This approach is unsuitable for real-time ED in practical power systems. To avoid solving nonlinear power flow equations, most power companies continue to adopt the TL formula in ED. Traditional loss formulas are composed of network parameters and in terms of the generator’s real power outputs. These formulas are derived by several assumptions, but these basic assumptions sacrifice accuracy. In this study, a new expression for the loss formula is proposed to improve the shortcomings of traditional loss formulas. The coefficients in the new loss formula can be obtained by recording the power losses according to varying real and reactive power outputs without any assumptions. The simultaneous equations of the second-order expansion of the Taylor series are then established. Finally, the corresponding coefficients can be calculated by solving the simultaneous equations. These new coefficients can be used in optimal real and reactive power dispatch problems. The proposed approach is tested by IEEE 14-bus and 30-bus systems, and the results are compared with those obtained from the traditional B coefficient method and the load flow method. The numerical results show that the proposed new loss formula for ED can hold high accuracy for different loading conditions and is very suitable for real-time applications.
Öz Anahtar Kelimeler Smartphone Addiction and Awareness of University Students During the Pandemic Period: The Case of Bitlis Eren University

Üniversite Covid-19 The Usage of Smartphone, Smartphone Addiction, University Students, Smartphone Addiction Awareness, COVID-19 Geliş Tarihi Çağırkan, B. , A. Smartphone addiction and awareness of university students during the pandemic The case of Bitlis 2022(12), not think. It has been seen that first-year students are more smartphone addicted than second-year students, and finally, those who use a smartphone for 1 year or less are more addicted to smartphone than those who use it for 5 years or more. The research reveals that the awareness of smartphone addiction among university students (no difference between male and female) is low. Especially in cities such as Bitlis where social activities are limited, students’ smartphone addiction is increasing. In addition, as the duration of smartphone use among students increases, the risk of addiction decreases in general. While the use of smartphones in general among university students is relatively new, they learn how to use smartphones over time.
Supervised Learning via Discriminative k q -Flats

— The k q -ﬂats algorithm is a generalization of the popular k -means algorithm, where k diﬀerent q -dimensional aﬃne spaces are considered, instead of points, as prototypes. A new modiﬁcation of the k - q -ﬂats algorithm for pattern classiﬁcation is introduced in this work. The basic idea is to replace the original reconstruction only energy, which is optimized to obtain the k aﬃne spaces, by a new one that incorporates discriminative terms. The presentation of the proposed framework is complemented with experimental results, showing that the method is computationally very eﬃcient and gives excellent results on standard supervised learning benchmarks.
Underlying Mechanisms of Reductive Amination on Pd-Catalysts: The Unique Role of Hydroxyl Group in Generating Sterically Hindered Amine

Pd nanospecies supported on porous g-C3N4 nanosheets were prepared for efficient reductive amination reactions. The structures of the catalysts were characterized via FTIR, XRD, XPS, SEM, TEM, and TG analysis, and the mechanisms were investigated using in situ ATR–FTIR spectroscopic analysis complemented by theoretical calculation. It transpired that the valence state of the Pd is not the dominating factor; rather, the hydroxyl group of the Pd(OH)2 cluster is crucial. Thus, by passing protons between different molecules, the hydroxyl group facilitates both the generation of the imine intermediate and the reduction of the C=N unit. As a result, the sterically hindered amines can be obtained at high selectivity (>90%) at room temperature.
Estrogen receptor 1 and Aurora kinase A as potential diagnostic biomarkers for cervical cancer

Cervical cancer (CC) is the fourth most common cause of death among women globally. Nearly 90% of CC mortality occurs in low- and middle-income countries. Hence there is an urgent need for identification of new biomarkers for the early diagnosis and treatment of CC. Current research aims to investigate the effect and mechanism of estrogen receptor 1 and aurora kinase A as potential diagnostic biomarkers for cervical cancer. Gene microarray datasets GSE8703 and GSE9750 were acquired from the Gene Set Omnibus and evaluated using GEO2R to identify the differentially expressed genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially expressed genes were performed using the clusterProfiler R package. A protein-protein interaction (PPI) network was constructed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and visualized using Cytoscape; hub genes were screened using the cytoHubba plug-in. Receiver operating characteristic curve and survival analysis was performed for candidate genes in the Gene Expression Profiling Interactive Analysis Database. The University of California, Santa Cruz, (UCSC)-XENA platform was used to analyze the pan-cancer biomarker expression. The relative expression of biomarkers in normal and cervical cancer tissues was determined using the Human Protein Atlas Database. Estrogen receptor 1 (ESR1) and Aurora kinase A (AURKA) were identified as potential biomarkers for cervical cancer. ESR1 was actively expressed in normal cervical tissues but limited in cervical cancer tissues. AURKA was least expressed in normal tissues and highly expressed in cervical cancer tissues. The results were confirmed by immunohistochemistry. The biomarkers identified herein can enable early diagnosis and serve as the therapeutic targets for cervical cancer.
3×3 MIMO 60-GHz OFDM-RoF System With Long-Distance Wireless Transmission Enabled by MIMO Volterra Filtering

A 3×3 60-GHz multiple-input multiple-output (MIMO) radio-over-fiber system with an MIMO Volterra filter was demonstrated. The main objective of the proposed scheme is to compensate for the nonlinear distortion caused by radio frequency (RF) power amplifiers (PAs) before the signals reaches the transmitter antennas—particularly when the PAs operate with a high input power to achieve a high output RF power for long-distance wireless transmission. When the required wireless transmission distance is only 7 m, the 3×3 MIMO system with careful control of the PA input power can achieve a data rate of 126 Gbps. However, the data rate decreases rapidly over a longer wireless distance because of the larger loss. By eliminating nonlinear distortion and interchannel interference simultaneously, MIMO Volterra filtering can significantly increase the achievable data rate of a long-distance system. When the required data rate is 90 Gbps (or 100 Gbps), the maximum wireless transmission distance is 118 m (or 70 m) with the aid of MIMO Volterra filtering, but it is only 74 m (or 40 m) without MIMO Volterra filtering.
Broadcast-TDMA: A Cost-Effective Fault-Tolerance Method for TSV Lifetime Reliability Enhancement

Editor’s notes: Through-silicon via (TSV) failure can occur due to various reliability issues. In this article, an interesting broadcast time-division multiplexing-access (TDMA) mechanism is used as a cost-effective fault-tolerance method for TSV yield improvement and lifetime enhancement. —Hailong Jiao, Peking University
The Corruption of Project Governance Through Normalization of Deviance

Organizational mistakes and accidents have a long history in practice and have been studied extensively in the engineering and organizational literature. One of the primary causes of persistent organizational error is the existence of deviance; i.e., behavior violating organizational norms. We examined the behaviors and motivations of project team members in situations where deviant behaviors had been accepted and normalized as part of project operations. We used NVivo content analysis to classify the narratives of 52 project professionals as they related to normalization of deviance (NoD) situations, their perceived causes, and subsequent outcomes for their organizations. Our findings suggest that NoD occurs in three primary dimensions: project processes, relationships, and outcomes. We discuss the implications of these findings for project organization performance improvement and avoiding NoD situations.
Joint Trajectory and Velocity-Time Optimization for Throughput Maximization in Energy-Constrained UAV

In this article, we aim to study an unmanned aerial vehicle (UAV)-assisted Internet of Things (IoT) communication system where a rotary-wing UAV travels from the initial to the final location to communicate with multiple IoT ground devices. The limited onboard energy of the UAV poses a constraint to the overall system’s performance. UAV’s energy consumption is majorly based on its kinematics, i.e., UAV’s velocity and acceleration. Therefore, in this work, we maximize the sum user throughput by jointly optimizing the 3-D UAV trajectory, and velocity-time profile in the presence of onboard energy, velocity, acceleration, and completion time constraints. Noting the nonconvexity of the optimization problem, the original problem is decoupled into two subproblems. First, the trajectory is optimized considering the velocity constraint, while in the second subproblem, the velocity and time optimization in each time slot is carried out. Simulation results show insights on the UAV trajectory and velocity-time profile with the variation in the onboard energy availability. In addition, we demonstrate the superior performance of the proposed approach in comparison to the benchmark schemes.