Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness and cost-effectiveness of an exposure-based return-to-work programme for patients on sick leave due to common mental disorders

Background: To reduce the duration of sick leave and loss of productivity due to common mental disorders (CMDs), we developed a return-to-work programme to be provided by occupational physicians (OPs) based on the principles of exposure in vivo (RTW-E programme). This study evaluates this programme's effectiveness and cost-effectiveness by comparing it with care as usual (CAU). The three research questions we have are: 1) Is an RTW-E programme more effective in reducing the sick leave of employees with common mental disorders, compared with care as usual? 2) Is an RTW-E programme more effective in reducing sick leave for employees with anxiety disorders compared with employees with other common mental disorders? 3) From a societal perspective, is an RTW-E programme cost-effective compared with care as usual? Methods/design: This study was designed as a pragmatic cluster-randomized controlled trial with a one-year follow-up and randomization on the level of OPs. We aimed for 60 OPs in order to include 200 patients. Patients in the intervention group received the RTW-E programme. Patients in the control group received care as usual. Eligible patients had been on sick leave due to common mental disorders for at least two weeks and no longer than eight weeks. As primary outcome measures, we calculated the time until full return to work and the duration of sick leave. Secondary outcome measures were time until partial return to work, prevalence rate of sick leave at 3, 6, 9, and 12 months' follow-up, and scores of symptoms of distress, anxiety, depression, somatization, and fatigue; work capacity; perceived working conditions; self-efficacy for return to work; coping behaviour; avoidance behaviour; patient satisfaction; and work adaptations. As process measures, we used indices of compliance with the intervention in the intervention group and employee-supervisor communication in both groups. Economic costs were calculated from a societal perspective. The total costs consisted of the costs of consuming health care, costs of production loss due to sick leave and reduced productivity, and out-of-pocket costs of patients for travelling to their OP. Discussion: The results will be published in 2009. The strengths and weaknesses of the study protocol are discussed. Trial registration: ISRCTN72643128 Published: 13 May 2009 BMC Public Health 2009, 9:140 doi:10.1186/1471-2458-9-140 Received: 15 February 2009 Accepted: 13 May 2009 This article is available from: http://www.biomedcentral. com/1471-2458/9/140 © 2009 Noordik et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Emotion Detection from Text and Sentiment Analysis of Ukraine Russia War using Machine Learning Technique

—In the human body, emotion plays a critical function. Emotion is the most significant subject in human-machine interaction. In economic contexts, emotion detection is equally essential. Emotion detection is crucial in making any decision. Several approaches were explored to determine emotion in text. People increasingly use social media to share their views, and researchers strive to decipher emotions from this medium. There has been some work on emotion detection from the text and sentiment analysis. Although some work has been done in which emotion has been recognized, there are many things to improve. There is not much work to detect racism and analysis sentiment on Ukraine -Russia war. We suggested a unique technique in which emotion is identified, and the sentiment is analyzed. We utilized Twitter data to analyze the sentiment of the Ukraine-Russia war. Our system performs better than prior work. The study increases the accuracy of detecting emotion. To identify emotion and racism, we used classical machine learning and the ensemble method. An unsupervised approach and NLP modules were used to analyze sentiment. The goal of the study is to detect emotion and racism and also analyze the sentiment.
Transformer-based Cross-Lingual Summarization using Multilingual Word Embeddings for English - Bahasa Indonesia

—Cross-lingual summarization (CLS) is a process of generating a summary in the target language from a source document in another language. CLS is a challenging task because it involves two different languages. Traditionally, CLS is carried out in a pipeline scheme that involves two steps: summarization and translation. This approach has a problem, it introduces error propagation. To address this problem, we present a novel end-to-end abstractive CLS without the explicit use of machine translation. The CLS architecture is based on Transformer which is proven to be able to perform text generation well. The CLS model is a jointly trained CLS task and monolingual summarization (MS) task. This is accomplished by adding a second decoder to handle the MS task, while the first decoder handles the CLS task. We also incorporated multilingual word embeddings (MWE) components into the architecture to further improve the performance of the CLS models. Both English and Bahasa Indonesia are represented by MWE whose embeddings have already been mapped into the same vector space. MWE helps to better map the relation between input and output that use different languages. Experiments show that the proposed model achieves improvement up to +0.2981 ROUGE-1, +0.2084 ROUGE-2, and +0.2771 ROUGE-L when compared to the pipeline baselines and up to +0.1288 ROUGE-1, +0.1185 ROUGE-2, and +0.1413 ROUGE-L when compared to the end-to-end baselines.
IoT Based Intrusion Detection Systems from The Perspective of Machine and Deep Learning: A Survey and Comparative Study

The term "Internet of Things" (IoT) refers to a group of gadgets that are capable of connecting to the Internet in order to gather and share data. The growth of Internet connections and the arrival of new technologies like the Internet of Things (IoT) have increased the privacy and security threats associated with the introduction of various gadgets. In order to increase the detection of cyber-attacks, industries are increasing their research spending. Institutions choose wise testing and verification techniques by comparing the highest rates of accuracy. IoT use has been accelerating recently across a variety of industries, including health care, smart homes, intelligent transportation, smart cities, and smart grids. where technology researchers and developers started to take notice of the IoT possibilities. Unfortunately, the privacy and security concerns imposed on by energy restrictions and the scalability of IoT devices present the most significant challenge to IoT. Therefore, how to address the IoT's security and privacy challenges remains an essential issue in the field of information security. With a decentralized design, edge computing plays a vital role in enabling IoT devices to compute, make decisions, take actions, and push only pertinent information to the cloud. Since sensitive data is more readily available and can be used right away, the IDS performs better when employing machine learning (ML) and deep learning (DL) algorithms to identify and prevent various threats. In terms of technical limitations, this study classifies the current, recent research in IoT intrusion detection systems employing machine learning, deep learning, and edge computing architecture.
Determinant expression of Selberg zeta functions. II

We will prove that for PSL(2, R) and its cofinite subgroup, the Selberg zeta function is expressed by the determinant of the Laplacian. We will also give an explicit calculation in case of congruence subgroups, and deduce that the part of the determinant of the Laplacian composed of the continuous spectrum is expressed by Dirichlet ? -functions. The first discovery of the relation between the Selberg zeta function and the determinant of the Laplacian was by physicists (3, 4, 7). Sarnak (14) and Voros ( 15) obtained the determinant expression of Selberg zeta functions for compact Riemann surfaces with torsionfree fundamental groups. In those cases, all the spectrum of the Laplacians are discrete. The determinant was defined via the holomorphy at the origin of the spectral zeta function of Minakshisundaram and Pleijel (13). For noncompact but finite Riemann surfaces with torsion- free fundamental groups, these results are generalized by Efrat (5). In this case there exist both discrete and continuous spectrum. He constructs the spectral zeta function composed not only of eigenvalues but some values concerning continuous spectrum, which are decided by all the poles of the scattering de- terminant in the Selberg trace formula. The determinant of the Laplacian is defined by the standard method with the holomorphy of the spectral zeta func- tion at the origin. The aim of the present paper is to generalize his results to the case with any fundamental group Y (§3) and to give some arithmetic examples of the determinant of the Laplacians (§4). In §4, we restrict ourselves to the case when Y is a congruence subgroup of PSL(2, Z). In this case the partial spectral zeta function composed of only eigenvalues is also holomorphic at the origin (11, Theorem 3.3). Hence we have a decomposition of the determinant into parts corresponding to the discrete and continuous spectrum. The scatter- ing determinant is expressed very explicitly by Huxley (8) in terms of Dirichlet 7-functions £(i, x) ■ Almost all the poles of the scattering determinant are de- scribed by nontrivial zeros of L(s, x) ■ The continuous part of the determinant
Determinates of Savings and Economic Growth in Poland in Comparison to the OECD Countries

Authors investigate interactions between the rate of economic growth and the saving rate in Poland in the 1990s. Tendencies observed in the Polish economy are related to the long term trends of growth and saving in a number of OECD countries. A simulation of possible development paths of the Polish economy is conducted using results of the estimation of the saving function for the OECD countries in the period 1971-1994. The model implies that, if the factors determining the rate of saving and the rate of growth were the same as those in the OECD countries during the last 25 years, the rate of saving in Poland would be higher by 5 percentage points and would equal 22 percent. Moreover, assuming the medium term rate of growth of 5-7 percent, a reduction of the budget deficit and the current account deficit, would result in a rise in the saving rate up to the level of 25-27 percent of GDP. Savings of households would rise by 2-3 percentage points to the level of 12 percent of GDP. The long term rate of growth would either be lowered down to 4 percent or raised up to 8 percent depending on the extent of utilisation of externalities and increasing returns from the employment of the human capital and technological change.
Simulation-based analysis of an L-patterned negative-capacitance dual tunnel VTFET

ABSTRACT This paper investigates the design and analog the behaviour of an L-Patterned Negative-Capacitance Dual Tunneling Vertical TFET (L-NC-DT-VTFET) device with the idea of corner tunnelling and vertical tunnelling. In this proposed structure, the tunnel junction can be used over a large region in a perpendicular alignment to the channel direction. Furthermore, the gate of an L-NC-DT-VTFET is positioned vertically in the L-shaped to boost ON current. Moreover, adding the p+ pocket in the channel helps reduce ambipolar current and improves the ON current. By adjusting the thicknesses of the ferroelectric layer and pocket, the device design is created deliberately to improve the on current to off current ratio $${{({I_{ON}}} \mathord{\left/ {\vphantom {{({I_{ON}}} {{I_{OFF}}}}} \right. \kern-\nulldelimiterspace} {{I_{OFF}}}})$$(ION/IOFF). The tunnelling current generated by dual tunnelling and negative capacitance extricates the collected holes, minimising the kink effect. The characteristics of the proposed L-NC-DT-VTFET structure are examined to those of known TFET architectures, and the suggested design appears to be a better match for high-performance, low-power applications as the device design maximise vertical tunnelling over corner tunnelling.
Identification of lumped linear time-varying systems via block-pulse functions

This paper presents a recursive algorithm using orthogonal block-pulse functions to identify the parameters of a system described by a linear differential equation with coefficients of finite-order polynomials in time t. The key point is the derivation of a set of operational matrices Pij (i = 0, 1, 2, … ; j=0, 1, 2, …) that relate the (th integral of the time-multiplicated block-pulse vector tiφ(t) to the block-pulse vector φ(t) itself. By using this elegant set of operational matrices the original time-varying differential input-output model is converted to a set of linear algebraic equations which can be solved recursively by a least-squares method to give unknown parameters and initial conditions. Two examples are included, one to illustrate the superiority of Pij over Fj (Wang 1982) in the solution of a time-varying differential equation and the other to show the effectiveness of the identification method.
Study of green reductant effects of highly reduced graphene oxide production and their characteristics

The study of the green reductant effects to produce reduced graphene oxide (rGO) has been completed successfully. The reduction of graphene oxide (GO) was carried out chemically using various reductants such as ascorbic acid (rGO-AA), gallic acid (rGO-AG), and trisodium citrate (rGO-NS). The GO was prepared using the Tour method at a temperature of 65 ? for 6 hours with potassium permanganate: graphite weight ratio 1:3.5. The results showed that rGO-AA had the highest electrical conductivity value of 755.70 S/m, with characteristics such as a surface area of 255.93 m2/g, a pore volume of 0.61 cm3/g, an average pore diameter of 7.10 nm, ID/IG ratio of 1.93, and three graphene layers in the material nanostructure stack. Therefore, it can be concluded that the reduction of GO with ascorbic acid (rGO-AA) is the most effective in producing rGO.
Reynolds Number Effects on the Near-Exit Region of Turbulent Jets

In this paper, attention has been focused on the near-exit region of a round turbulent free jet to study the large-scale coherent structures and to document the signatures of the vortices over a range of Reynolds numbers. Particle image velocimeter measurements were conducted at three jet exit Reynolds numbers of 10,000, 30,000, and 55,000. The large-scale structures in the near field ( X/D<12 ) were investigated by performing a proper orthogonal decomposition analysis of the velocity fields. A vortex identification algorithm was complemented by swirling strength maps to identify the vortex centers, rotational sense, size, and circulation of the vortices. The influence of the Reynolds number on the distribution of the number, size, and circulation of the identified vortices was studied. Proper orthogonal decomposition of the velocity fields revealed that Reynolds number has a strong influence on the mean circulation of vortices. The present results show that the axial location where vortices first appear .
Dietary Calcium Intake and Overweight in Adolescence . ( December 2004 )

Dietary Calcium Intake and Overweight in Adolescence. (December 2004) Amira Sami Gerges, B.S., Texas A&M University Co-Chairs of Advisory Committee: Dr. Debra B. Reed Dr. Susan A. Bloomfield Recent research has shown an association between low dietary calcium intake and obesity in adults as well as overweight in young children; however, this relationship has not been investigated in adolescents. The purpose of this study was to examine the relationship between inadequate calcium intake and overweight in adolescents. The hypothesis of this study was that there is a negative correlation between dietary calcium intake and overweight in adolescents. The study population consisted of middle school and high school students (n = 102) in a local school district. The gender and ethnic distributions of the sample were as follows: 74% female, 26% male, 63% Caucasian, 16% African-American, 12% Hispanic, and 8% other. Dietary calcium and energy intakes were assessed using a previously validated calcium-focused food frequency questionnaire (FFQ) for youths. Calcium intake was also assessed using a single question on daily milk consumption. The FFQ was administered by trained interviewers to groups of three to five students. Body fat was assessed using body mass index for age (BMI-forage) and sum of triceps and subscapular skinfolds (STS). The mean reported calcium intake was 1,972 ± 912 mg/day, and mean reported energy intake was 3,421 ± 1,710 kcals/day. Reported calcium intake from the FFQ was inflated since approximately 75% reported drinking less than three glasses of milk a day. According to BMI-for-age, 29% were classified as at risk of overweight or overweight. Using STS, 39% were classified as overweight. Chi-square analysis using either method of dietary calcium intake and either method of overweight assessment did not show dependence between categories of calcium intake and level of weight or body fat. This study failed to show a relationship between dietary calcium intake and risk of overweight or overweight in adolescents.
QN Inversion of Large-scale MT Data

A limited memory quasi-Newton (QN) method with simple bounds is applied to a 1-D magnetotel- luric (MT) problem. The method is used to invert a realistic synthetic MT impedance dataset, calculated for a layered earth model. An adjoint method is employed to calculate the gradients and to speed up the inverse problem solution. In addition, it is shown that regularization stabilizes the QN inversion result. We demonstrate that only a few correction pairs are enough to produce reasonable results. Comparison with inversion based on known L-BFGS-B optimization algorithm shows similar convergence rates. The study presented is a first step towards the solution of large-scale electromagnetic problems with a full 3-D conductivity structure of the Earth.
Fabrication of double layer optical tissue phantom by spin coating method: mimicking epidermal and dermal layer

Methodologies to fabricate a solid optical tissue phantom (OTP) mimicking epidermal thin-layer have been developed for in vitro human skin experiment. However, there are cumbersome and time-consuming efforts in fabrication process such as a custom-made casting and calculation of solvent volume before curing process. In a previous study, we introduced a new methodology based on spin coating method (SCM) which is utilized to fabricate a thin-layer OTP analogous to epidermal thickness. In this study, a double layer solid OTP which has epidermal and dermal layers was fabricated to mimic the morphological and optical similarity of human tissue. The structural characteristic and optical properties of fabricated double layer OTP were measured using optical coherence tomography and inverse adding doubling algorithms, respectively. It is expected that the new methodology based on the SCM may be usefully used in the fabrication of double layer OTP.
Dynamic Force-directed Graph with Weighted Nodes for Scholar Network Visualization

—Through the growth of portals and venues to publish academic publications, the number of academic publications is growing exponentially in recent years. An effective exploration and fast navigation in the collection of academic publications become an urgent need to help academic researchers find publications related to their research and the surrounding community. A scholar network visualization approach is proposed to help users to explore a large number of academic publications concerning the strength of the relationship between each publication. The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. The proposed approach visualizes data by incorporating a force-directed graph with weighted nodes and vertices to give more descriptive information of millions of raw data such as author names, publication title, publication year, publication venue and number of citations from the scholar network dataset. By introducing a weighted relationship in the network visualization, the proposed approach can give a more insightful detail of each publication such as a highly cited publication by looking at and exploring the generated interactive graph. The proposal is targeted to be incorporated into a larger-scale scholar network analytical dashboard that can offer various visualization approaches under one flagship application.
Are relative depletions altered inside diffuse clouds

The data of Jenkins, Savage, and Spitzer (1986) were used to analyze interstellar abundances and depletions of Fe, P, Mg, and Mn toward 37 stars, spanning nearly 1.0 (dex) in mean line-of-sight depletion. It was found that the depletions of these elements are linearly correlated and do not show evidence of differences in the rates of depletion or sputtering from one element to another. For a given level of overall depletion, the sightline-to-sightline rms variance in the depletion for each of these elements was less than 0.16 (dex), which is significantly smaller than is the element-to-element variance. The results suggest that, for most diffuse lines of sight, the relative abundances of these elements are set early in the lifetime of the grains and are not altered significantly thereafter. 53 references.
A Multi-Swarm Cooperative Perturbed Particle Swarm Optimization

Combined with a variety of ideas a Multi-swarm cooperative Perturbed Particle Swarm Optimization algorithm (MpPSO) is presented to improve the performance and to reduce the premature convergence of PSO. This algorithm includes the idea of multiple swarms to improve the evolution efficiency by information sharing between populations to avoid falling into local optimum caused by single population. It also includes the idea of perturbing the swarms beside the global best solution, which can escape from local optimum. Experiments show that the proposed algorithm MpPSO has better performance, better convergence and stability when comparing with the traditional and the recently improved particle swarm optimization.