Miracle-dz/UniFAR-FTUs huggingface dataset:
Needs and Difficulties of Parents with Children Suffering from Malignant Diseases

Malignant diseases are one of the leading causes of death in children in developed countries, although constant progress in therapy is continuously decreasing mortality. The diagnosis of malignant disease is a significant stressor in the life of a child and its family, significantly affecting the quality of life for the entire family. it constitutes the prototype of a stressful situation and a disease with a potentially devastating effect on the child and its family. This paper discusses 50 professional and scientific papers published between 1993 and 2022 that explore the needs and difficulties of parents of children with malignant diseases. To provide adequate help and care, a correct evaluation of the problem and parents’ needs is required. for the parents, the diagnosis of a malignant disease for their child constitutes a psy- chological and existential challenge. To meet the par- ents’ needs, as well as to ease their problems, further research – in most cases also supported by the parents themselves – is needed to help them cope with this extremely stressful and hard part of their lives.
The Challenges of Small and Medium Businesses in Managing Human Capital towards SMEs Performance – A Qualitative Study

Manuscript type: Research paper Research aims: Currently, machinery is replacing most human capital to save cost, but the value of human capital that contributes to the performance of SMEs is invaluable. SMEs were used to explain the connection between human capital and SMEs performance in South Australia. Design/Methodology/Approach: Five case studies on SMEs in South Australia were used in this study. The analysis of qualitative data entailed data coding, within-case analysis, and cross-case analysis. Research findings: The cross-case analysis result is unsurprising considering that all five firms depend on their employees to work and keep the firm in operation. The cross-case analysis results are mixed in respect to the connection between human capital and the several types of performance measurement. The results, therefore, need to be interpreted with caution. SMEs perform solely through the skills, experience, and knowledge of their employees. This distinction occurs when the knowledge and information that employees gain are focused directly on the employee’s initiative, decision-making and critical thinking skills. Investment in human capital should be done carefully based on the limited resources of SMEs. Theoretical contribution/Originality: Most research has shown the link between human capital and firm performance. However, the degree to which investment in human capital contributes to the type of performance is yet to be explored based on qualitative data especially regarding SMEs in South Australia. Practitioner/policy implication: The sustainable development goal (SDG) entails a steady improvement in people’s well-being in a good environment. Thus, decisions about investment in human capital and the use of temporary workers should be taken jointly by personnel managers, in accordance with the size of the firm. If this holistic view is ignored, a full understanding of the impact of human capital on the firm’s performance will be obscured. On the other hand, a common feature that large and small firms share is an incompatibility between human capital and temporary employment. Research limitation/implications: The main limitation of this study was the sample of the study that comprised solely of South Australia SMEs. Thus, this study outcome may not be generalisable to the whole Australia as a country. Further investigation across different states would expand knowledge of the complicated patterns of HC. Keywords: Human capital, SME, Productivity, Profitability, South Australia JEL Classification: M12
A tuberculose ao longo dos tempos

This paper outlines a picture of the representations of tuberculosis in different decades and how they have been handled by clinical medicine. The history of the disease, from the early days of the XIX century hygienist policies to the current control and prevention programs, displays a continual change of focus: social views were sometimes highlighted (the environment, work, housing), and at times the focus shifted to individual viewpoints (body fluids, lifestyle) regarding forms of prevention and cure of the disease. Such diverse representations and concepts about tuberculosis have influenced the way in which medicine and sick individuals perceived the disease and dealt with it.
Multiple Convolutional Neural Networks for Online Visual Tracking

The paper presents a new online visual tracking method based on convolutional neural network (CNN). Our algorithm consists of multiple CNN tracker units focusing on different object features, and each unit is trained with a proper number of domains determined by our method. For the model update process, traditional CNN online re-training is avoided, replaced by a timely tracker switching strategy. At each moment, only one main tracker predicts and others stand by to ensure efficiency. The experimental results show that our method can track objects in most scenarios, and implicate that our CNN model has a generalization ability in distinguishing target and background.
Mitigating climate biases in the mid-latitude North Atlantic by increasing model resolution: SST gradients and their relation to blocking and the jet.

Starting to resolve the oceanic mesoscale in climate models is a step change in model fidelity. This study examines how certain obstinate biases in the midlatitude North Atlantic respond to increasing resolution (from 1° to 0.25° in the ocean) and how such biases in sea surface temperature (SST) affect the atmosphere. Using a multi-model ensemble of historical climate simulations run at different horizontal resolutions, it is shown that a severe cold SST bias in the central North Atlantic, common to many ocean models, is significantly reduced with increasing resolution. The associated bias in the time-mean meridional SST gradient is shown to relate to a positive bias in low-level baroclinicity, while the cold SST bias causes biases also in static stability and diabatic heating in the interior of the atmosphere. The changes in baroclinicity and diabatic heating brought by increasing resolution lead to improvements in European blocking and eddy-driven jet variability. Across the multi-model ensemble a clear relationship is found between the climatological meridional SST gradients in the broader Gulf Stream Extension area and two aspects of the atmospheric circulation: the frequency of high-latitude blocking and the southern-jet regime. This relationship is thought to reflect the two-way interaction (with a positive feedback) between the respective oceanic and atmospheric anomalies. These North Atlantic SST anomalies are shown to be important in forcing significant responses in the midlatitude atmospheric circulation, including jet variability and the stormtrack. Further increases in oceanic and atmospheric resolution are expected to lead to additional improvements in the representation of Euro-Atlantic climate.
Party ideologies and European foreign policy. Examining the transnational foreign policy space

ABSTRACT The heterogeneity of foreign policy preferences has hampered a more effective Common Foreign and Security Policy. We examine the dimensionality of the EU foreign policy space by analyzing foreign policy votes in the European Parliament (1999–2019). As it contains the EU’s full geographical and ideological diversity, it is an important laboratory for testing expectations about what predicts foreign policy positions. Party ideologies structure voting on foreign policy: party-political disagreements over the CFSP and military interventions matter more on foreign policy votes than others. The left-right dimension and the EU integration dimension still explain a considerable share of voting patterns, although they matter less on foreign policy votes than others.
Efficient Plasmonic 2D Arrangement and Manipulation System, Suitable for Controlling Particle–Particle Interactions

Investigating interactions between biological or artificial micro and nanoparticles (NPs) are vital for understanding processes such as intercellular communications, and quantum and optical effects in an array of NPs. In this line of research, methods to precisely trap and manipulate NPs are essential to investigate such inter-particle interactions. Exciting higher order counter-propagating leaky surface plasmon modes (LSPMs) of a thin gold stripe, we present a simple and efficient method to arrange NPs into a two-dimensional (2D) periodic pattern, allowing precise control over inter-particle interactions. We demonstrate that the 2D lattice of traps is generated by interference of totally reflected surface plasmons from the gold stripe edges and also interference of two counter-propagating LSPMs. Analytical calculations and numerical simulations are in good agreement with the observed modal behavior of LSPMs. Due to the modal dependency of LSPMs on the incident wavelength, we show that in this system different inter-particle distance with nanometer resolution can be achieved by adjusting the wavelength of the incident laser beams. Moreover, we show that the trapped NP array shows waveguiding behavior, enhances the mode intensities and the resulted potential wells consequently. We expect that this self-induced enhancement of trapping efficiency is beneficial for the periodic arrangement of NPs and array formation. The proposed approach implemented in a simple plasmonic optophoresis system, opens the possibility to develop integrated optical manipulation chips, which allows simple and low-cost approach for controlling and studying the inter-particle interactions. Furthermore, the proposed approach is also promising for controllable assembling of NPs without the need for complicated and time consuming nano-lithography techniques.
The Efficacy of Vitamin D Supplementation in the Treatment of Fibromyalgia Syndrome and Chronic Musculoskeletal Pain

Fibromyalgia syndrome (FMS) and chronic widespread musculoskeletal pain (CMP) are diffuse suffering syndromes that interfere with normal activities. Controversy exists over the role of vitamin D in the treatment of these diseases. We carried out a systematic literature review of randomized controlled trials (RCT) to establish whether vitamin D (25OHD) deficiency is more prevalent in CMP patients and to assess the effects of vitamin D supplementation in pain management in these individuals. We searched PubMed, Physiotherapy Evidence Database (PEDro), and the Cochrane Central Register of Controlled Trials (CENTRAL) for RCTs published in English from 1 January 1990 to 10 July 2022. A total of 434 studies were accessed, of which 14 satisfied the eligibility criteria. In our review three studies, of which two had the best-quality evidence, a correlation between diffuse muscle pain and 25OHD deficiency was confirmed. Six studies, of which four had the best-quality evidence, demonstrated that appropriate supplementation may have beneficial effects in patients with established blood 25OHD deficiency. Eight studies, of which six had the best-quality evidence, demonstrated that 25OHD supplementation results in pain reduction. Our results suggest a possible role of vitamin D supplementation in alleviating the pain associated with FMS and CMP, especially in vitamin D-deficient individuals.
Trends in State Anxiety during the Full Lockdown in Italy: The Role Played by COVID-19 Risk Perception and Trait Emotional Intelligence

The COVID-19 pandemic is associated with mental health outcomes in the general population. This study assessed how state anxiety changed at different time points during the pandemic and how it was influenced by risk perception and trait emotional intelligence (trait EI). The study was conducted online in two data collections, at the beginning (wave 1, N = 1031) and at the end (wave 2, N = 700) of the lockdown. Participants were asked to self-report their state anxiety, risk perception of COVID-19 contagiousness, and trait EI. The interaction between risk perception and wave showed that, in wave 1 (but not in wave 2), anxiety increased as risk perception increased. Further, trait EI by wave interactions showed that effective (vs. ineffective) regulators experienced lower anxiety and this difference was larger in wave 2 than in wave 1. Because of the cross-sectional design of the study and the convenience sample we should be cautious when generalizing the present findings to the entire population. Our findings support the moderating role of trait EI on state anxiety during the COVID-19 pandemic. This knowledge provides further support for the importance of EI in coping with uncertain and stressful environmental conditions such as those posed by the COVID-19 pandemic.
The Cognitive Processes Underlying Moral Judgment Across Development

Some moral philosophers have suggested that a basic prohibition against intentional harm ought to be at the core of moral belief systems across human societies. Yet, experimental work suggests that not all harm is viewed equally—people often respond more negatively to harm that occurs among fellow social group members, rather than between members of different groups. The present two studies investigated how concerns about social group membership factor into the moral judgment system. Adults (N = 111, Study 1) and children (N = 110, Study 2) evaluated instances of interand intra-group harm under varying levels of cognitive load. Both children and adults responded more slowly to intergroup harm than to intragroup harm. Furthermore, adults under cognitive load rated intergroup harm more leniently than intragroup harm, but adults who were not under load rated the two types of behaviors similarly. These findings suggest that across development, evaluations of intergroup harm rely more heavily on conscious deliberation than evaluations of intragroup harm. Thus, people's evaluations of harmful behaviors are made in light of information about the social category membership of the people involved.
TCP-Based M2M Traffic via Random-Access Satellite Links: Throughput Estimation

Provisioning of Internet of Things/machine-to-machine (M2M) services over satellite has been experiencing a continuous growth in the last few years, which is expected to further increase in the near future so as to meet the demands of users and enterprises. The design of a suitable network architecture is, hence, of paramount importance to properly take into account the requirements imposed by the technology available nowadays and to properly consider the interaction of the so-defined physical layer with transport and application layers. In this light, this paper analyzes the use case of TCP-based M2M services operating over DVB-RCS2 satellite links, where a contention resolution diversity slotted ALOHA access scheme is applied. The main goal of this paper is to provide a thorough understanding of the interactions of TCP and random access schemes, recognized as key elements to enable efficient M2M services over satellite. In this regard, this paper also develops a novel TCP throughput model, which has been validated through extensive simulation campaigns, proving the value of the proposed theoretical framework and its applicability to study the performance of M2M services in more general satellite scenarios.
Public spending and informal economy in the Asian countries

Abstract The informal economy is a complex phenomenon present, to a large extent, in both developing and developed countries. Despite an increasing focus on the nexus between public spending and the informal economy, little is known about the moderating role of budget imbalance in this relationship. This study investigates how a budget imbalance moderates the effects of public spending on the informal economy of 32 Asian countries from 2000 to 2017. We have employed the generalized method of moments and various second-generation tests in this analysis to ensure the approach is appropriate and the findings are robust. Our results indicate that increasing public spending and budget imbalance will increase the informal economy size. Interestingly, the effect of public expenditure on the informal economy will enhance with an increase in the budget imbalance. Additionally, we also find that tax burden and economic growth contribute to the increased informal economy in Asian countries. This study also offers some useful policy implications for reducing the informal economy.
How Does Smartphone Usage Feedback Influence Mobility Behavior?

ABSTRACT Promoting mobility behavior can benefit individuals’ well-being and regional economic vitality. This study focuses on the role of a new ICT-related factor, smartphone usage feedback in promoting users’ mobility behavior. Though smartphone usage feedback is designed to help users to regulate their smartphone use, we find it also has the potential to increase their mobility. According to cognitive dissonance theory, smartphone usage feedback may make users realize that they are more addicted to smartphones in the digital world than they perceive, which causes users to experience dissonance and guilt. To relieve the dissonance and guilt, users may put more cognitive resources into the physical world and perform more life activities, possibly leading to higher-level mobility. Using large-scale smartphone data, findings verify that smartphone usage feedback encourages users to increase stopping- and moving-related mobility behavior. Besides, users with lower-level historical stopping-related mobility are less likely to increase their mobility.
Alternating Least Squares as Moving Subspace Correction

In this note we take a new look at the local convergence of alternating optimization methods for low-rank matrices and tensors. Our abstract interpretation as sequential optimization on moving subspaces yields insightful reformulations of some known convergence conditions that focus on the interplay between the contractivity of classical multiplicative Schwarz methods with overlapping subspaces and the curvature of low-rank matrix and tensor manifolds. While the verification of the abstract conditions in concrete scenarios remains open in most cases, we are able to provide an alternative and conceptually simple derivation of the asymptotic convergence rate of the two-sided block power method of numerical algebra for computing the dominant singular subspaces of a rectangular matrix. This method is equivalent to an alternating least squares method applied to a distance function. The theoretical results are illustrated and validated by numerical experiments.
Leveraging Graph and Deep Learning Uncertainties to Detect Anomalous Maritime Trajectories

Understanding and representing traffic patterns are key to detecting anomalous trajectories in the transportation domain. However, some trajectories can exhibit heterogeneous maneuvering characteristics despite confining to normal patterns. Thus, we propose a novel graph-based trajectory representation and association scheme for extraction and confederation of traffic movement patterns, such that data patterns and uncertainty can be learned by deep learning (DL) models. This paper proposes the usage of a recurrent neural network (RNN)-based evidential regression model, which can predict trajectory at future timesteps as well as estimate the data and model uncertainties associated, to detect anomalous maritime trajectories, such as unusual vessel maneuvering, using automatic identification system (AIS) data. Furthermore, we utilize evidential deep learning classifiers to detect unusual turns of vessels and the loss of transmitted signal using predicted class probabilities with associated uncertainties. Our experimental results suggest that the graphical representation of traffic patterns improves the ability of the DL models, such as evidential and Monte Carlo dropout, to learn the temporal-spatial correlation of data and associated uncertainties. Using different datasets and experiments, we demonstrate that the estimated prediction uncertainty yields fundamental information for the detection of traffic anomalies in the maritime and, possibly in other domains.
Mathematical modeling of folate-related processes in human placenta

Aim. Description the folate-related processes in the human placenta using the stoichiometric model and investigation the system’s behavior under various conditions. Methods. The model is based on the stoichiometry of the reactions of the folate-related processes at steady state conditions and constructed using CellNetAnalyzer. Behavior of the system is described by elementary flux modes and control-effective fluxes depending on the activity of methylenetetrahydrofolate reductase and methionine synthase and input methionine flux. Results. Change in methylenetetrahydrofolate reductase activity causes a decrease in fluxes through the main routes of homocysteine elimination and increases the need for 5-methyltetrahydrofolate. Methionine synthase inactivation reduces 5-methyltetrahydrofolate consumption and increases the flux through the taurine syn-thesis. Lack of methionine leads to increased 5-methyltetrahydrofolate consumption, reduced homocysteine concentration and reduces the fluxes through the methionine cycle. Conclusions. Analysis of model functioning has shown the compliance of system’s functioning changes with the clinic parameters. There is evidence that the homocysteine level as a marker of folate-related processes functioning of is not sufficient to justify the therapy.
Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms

We propose ZeroFPR, a nonmonotone linesearch algorithm for minimizing the sum of two nonconvex functions, one of which is smooth and the other possibly nonsmooth. ZeroFPR is the first algorithm that, despite being fit for fully nonconvex problems and requiring only the black-box oracle of forward-backward splitting (FBS) --- namely evaluations of the gradient of the smooth term and of the proximity operator of the nonsmooth one --- achieves superlinear convergence rates under mild assumptions at the limit point when the linesearch directions satisfy a Dennis-Mor\'e condition, and we show that this is the case for quasi-Newton directions. Our approach is based on the forward-backward envelope (FBE), an exact and strictly continuous penalty function for the original cost. Extending previous results we show that, despite being nonsmooth for fully nonconvex problems, the FBE still enjoys favorable first- and second-order properties which are key for the convergence results of ZeroFPR. Our theoretical results are backed up by promising numerical simulations. On large-scale problems, by computing linesearch directions using limited-memory quasi-Newton updates our algorithm greatly outperforms FBS and its accelerated variant (AFBS).
Determinan Dividen Payout Ratio pada Perusahaan Subsubsektor Perdagangan Eceran

Tujuan dari penelitian ini untuk mengetahui faktor-faktor yang mempengaruhi Dividen Payout Ratio pada perusahaan subsubsektor perdagangan eceran. Metode penelitian yang digunakan adalah metode kuantitatif, dengan menggunakan model fixed effect pada model regresi terbaik. Hasil penelitian yang ditemukan adalah ATO secara parsial memiliki pengaruh positif dan signifikan terhadap Dividen Payout Ratio. SIZE secara parsial memiliki pengaruh positif dan signifikan terhadap Dividen Payout Ratio. DER secara parsial memiliki pengaruh negatif dan signifikan terhadap Dividen Payout Ratio. CR secara parsial tidak berpengaruh terhadap Dividen Payout Ratio. ROA secara parsial memiliki pengaruh negatif dan signifikan terhadap Dividen Payout Ratio. Sehingga perusahaan subsekor perdagangan eceran dapat meningkatkan Dividend Payout Ratio dengan cara meningkatkan ATO dan SIZE kemudian menurunkan DER dan ROA serta tetap menjaga nilai CR pada kondisi optimal.