Miracle-dz/UniFAR-FTUs huggingface dataset:
Sobre a Influência dos Nós Egoístas no Descarregamento de Tráfego com Redes Oportunistas

A infraestrutura celular está sobrecarregada com o crescente número de dispositivos e aplicações móveis. Uma solução para este problema é descarregar parte do tráfego da rede utilizando outra rede como canal de comunicação secundário. Muitos trabalhos na literatura propõem o uso de redes oportunistas como este canal secundário. Para se ter sucesso na comunicação oportunista, entretanto, os nós precisam cooperar uns com os outros para encaminhar mensagens e confirmar para a infraestrutura o recebimento das mensagens encaminhadas por outros nós. Neste artigo, avalia-se a influência dos nós egoístas no descarregamento de tráfego com redes oportunistas. Nós egoístas são aqueles que não encaminham mensagens para outros nós ou não enviam reconhecimentos positivos para infraestrutura ou que combinam ambos os comportamentos. Resultados mostram que a eficiência do descarregamento é reduzida de 70% para até 18% com a presença de nós egoístas na rede.
Pandemic Rumination and Resilience on Frontline Health Care Professionals in India: A Cross-Sectional Survey

Background High workload during pandemic has caused psychological stress in Healthcare Professionals (HCPs). It is necessary to identify factors that lead to negative mental health effects, and those that create resilience to withstand stress. Aim: We examined relationship between stress & perseverative thinking, and social networking & resilience in HCPs working in Emergency Room (ER) and intensive care unit (ICU). Methods Cross-sectional survey conducted from 15 th April-15 th May, 2021 using questionnaire with clinically-validated scales: WHO 5 Well-being Index, Brief Resilience Scale (BRS), UCLA Loneliness Scale, Perseverative Thinking Arch Clin Biomed Res 2022; 6 (3): 481-491 DOI: 10.26502/acbr.50170262 Archives of Clinical and Biomedical Research Vol. 6 No. 3 – June 2022. [ISSN 2572-9292]. 482 Questionnaire (PTQ), Impact of Event Scale – 6 (IES 6), and Berkman-Syme Social Networking Index (SNI). We analysed effect of age, location of work, marital status, and participation in community activity on these indices. Results 39.6% had low resilience, 34.8% had high impact of pandemic. BRS and IES 6 score varied significantly when classified according to age and marital status (p<0.05). WHO-5 Wellbeing Index was negatively correlated with UCLA Loneliness Scale, PTQ and IES 6 (p<0.05). SNI and BRS was negatively correlated with UCLA loneliness scale (p<0.05). Conclusions Perseverative thinking exacerbates burden of ongoing stressors counteractive to psychological well-being. Modifiable factor, our findings underscore value of helping frontline HCPs manage these circumstances.
Animal Models and Helicobacter pylori Infection

Helicobacter pylori colonize the gastric mucosa of at least half of the world’s population. Persistent infection is associated with the development of gastritis, peptic ulcer disease, and an increased risk of gastric cancer and gastric-mucosa-associated lymphoid tissue (MALT) lymphoma. In vivo studies using several animal models have provided crucial evidence for understanding the pathophysiology of H. pylori-associated complications. Numerous animal models, such as Mongolian gerbils, transgenic mouse models, guinea pigs, and other animals, including non-human primates, are being widely used due to their persistent association in causing gastric complications. However, finding suitable animal models for in vivo experimentation to understand the pathophysiology of gastric cancer and MALT lymphoma is a complicated task. In this review, we summarized the most appropriate and latest information in the scientific literature to understand the role and importance of H. pylori infection animal models.
A comparative analysis for a deep learning model (hyDL-CO v1.0) and Kalman filter to predict CO concentrations in China

Abstract. The applications of novel deep learning (DL) techniques in atmospheric science are rising quickly. Here we build a hybrid DL model (hyDL-CO), based on convolutional neural networks (CNNs) and long short-term memory (LSTM) neural networks, to provide a comparative analysis between DL and Kalman filter (KF) to predict carbon monoxide (CO) concentrations in China in 2015–2020. We find the performance of DL model is better than KF in the training period (2015–2018): the mean bias and correlation coefficients are 9.6 ppb and 0.98 over eastern China and are −12.5 ppb and 0.96 over grids with independent observations (i.e., grids with CO observations that are not used in DL training and KF assimilation). By contrast, the assimilated CO concentrations by KF exhibit comparable correlation coefficients but larger negative biases. Furthermore, the DL model demonstrates good temporal extensibility in the test period (2019–2020): the mean bias and correlation coefficients are 95.7 ppb and 0.93 over eastern China and 81.0 ppb and 0.91 over grids with independent observations, while CO observations are not fed into the DL model as an input variable. Despite these advantages, we find a weaker prediction capability of the DL model than KF in the test period, and a noticeable underestimation of CO concentrations at extreme pollution events in the DL model. This work demonstrates the advantages and disadvantages of DL models to predict atmospheric compositions with respect to traditional data assimilation, which is helpful for better applications of this novel technique in future studies.
Effects of the VACES particle concentrator on secondary organic aerosol and ambient particle composition

Abstract The effects of concentrating particles using the Versatile Aerosol Concentration Enrichment System (VACES) were investigated with a focus on the organic particle composition. The VACES uses water condensation to grow particles and allow enrichment in particle concentrations by virtual impaction, followed by diffusion drying to remove excess liquid water. Aerosol mass spectrometry was used to compare the submicron organic composition before and after the VACES for laboratory-generated secondary organic aerosol (SOA) from ozonolysis of α-pinene as well as ambient particles. Size distributions were retained after the VACES for both types of samples. SOA particles showed evidence of high molecular weight compounds forming after enrichment, suggesting that some oligomerization occurs during the water condensation and/or evaporation stages, but with only slight changes in the elemental composition. Oligomerization was also observed for ambient particles, especially those with higher O/C in the accumulation mode. Ambient ultrafine particles with low O/C were not as efficiently enriched. Such composition changes in the organic fraction may be relevant to other methodologies where particles are grown through water uptake and then dried, as well as to atmospheric processes involving water uptake and evaporation. In the context of particle mass, the extent of oligomerization is small. However, given the widespread use of particle concentrators in health effects and particle composition studies, whether this impacts interpretation of health effects and particle composition data when using particle concentrators needs further exploration. Copyright © 2022 American Association for Aerosol Research
Anti-Photoaging Effect of Rhodiola rosea Fermented by Lactobacillus plantarum on UVA-Damaged Fibroblasts

UVA can cause oxidative stress and photoaging of cells. We established a UVA-induced oxidative stress model of human fibroblasts and focused on the antioxidant and anti-photoaging ability of Lactobacillus plantarum fermented Rhodiola rosea. Compared with the unfermented Rhodiola rosea, Lactobacillus plantarum fermented Rhodiola rosea has better DPPH free radical and hydroxyl free radical scavenging ability, significantly reduces the content of reactive oxygen species (ROS), and improves the antioxidant level. Further studies have shown that the Lactobacillus plantarum fermented Rhodiola rosea can activate the Nrf2/Keap1 signaling pathway and up-regulate heme oxygenase-1 (HO-1), NAD(P)H quinone dehydrogenase 1 (NQO1), catalase (CAT) and glutathione Peptide peroxidase (GSH-Px), and protect fibroblasts from oxidative stress caused by UVA. On the other hand, Lactobacillus plantarum fermented Rhodiola rosea significantly reduces the activity of metalloproteinases in the cell, thereby increasing the collagen and elastin in the cell, alleviating the photoaging caused by UVA. Finally, we concluded that the antioxidant capacity and anti-photoaging ability of Lactobacillus plantarum fermented Rhodiola rosea are better than that of unfermented Rhodiola rosea.
An improved high-power factor and low-cost three-phase rectifier

A new method to improve the power factor of three-phase rectifiers is introduced in this paper. The main features of the proposed circuit are low cost, small size, high efficiency, and simplicity. The power factor improvement is achieved with three bi-directional active switches rated at a small fraction of the total processed power, and gated at the line frequency. The principle of operation and design procedure, with a practical example, are also presented. The theoretical analysis was validated with experimental results from a laboratory prototype rated at 7.4 kW and connected to the 220-V 60-Hz AC system. The same circuit was also used in another prototype rated at 12 kW, with similar results.
Pharmacological, Neurochemical, and Behavioral Mechanisms Underlying the Anxiolytic- and Antidepressant-like Effects of Flavonoid Chrysin

Chrysin (5,7-dihydroxyflavone) is a flavonoid isolated from plants, such as Passiflora coerulea, Passiflora incarnata, and Matricaria chamomilla. This natural molecule exerts diverse pharmacological effects, which includes antioxidant, anti-inflammatory, anti-cancer, neuroprotective, and anti-apoptotic effects. Additionally, in brain structures, such as the hippocampus, prefrontal cortex, raphe nucleus, and striatum, involved in the physiopathology of anxiety and depression disorders, several neuropharmacological activities, including the activation of neurotransmitter systems (GABAergic, serotonergic, dopaminergic, and noradrenergic), neurotrophic factors, such as brain-derived neurotrophic factor and the nerve growth factor, and some signaling pathways are affected. The results showed that the anxiolytic and antidepressant-like effects of chrysin occurs through its interaction with specific neurotransmitter systems, principally the GABAergic and the serotonergic, and activation of other neurotrophic factors. However, it is not possible to discard the antioxidant and anti-inflammatory activities of chrysin while producing its anxiolytic- and antidepressant-like effects. Although these results have been obtained principally from pre-clinical research, they consistently demonstrate the potential therapeutic use of flavonoid chrysin as an anxiolytic and antidepressant agent. Therefore, this flavonoid could be considered as a promising novel therapy for anxiety and depression disorders.
Impact of direct-acting antivirals on the recurrence of hepatocellular carcinoma in chronic hepatitis C

Chronic hepatitis C virus (HCV) infection is estimated to affect 56.8 million individuals globally and is a major and independent risk factor for the development of hepatocellular carcinoma (HCC). After the introduction of safe and potent direct-acting antivirals (DAAs), capable of curing HCV infection also in patients with advanced liver disease at high risk of HCC, the beneficial effect on a de novo HCC development after viral clearance has been established. However, studies addressing the relationship between DAA-induced eradication and risk of HCC recurrence (i.e., reappearance of HCC treated before starting antivirals) have produced contradictory data, suggesting either an increase or a decrease of HCC recurrence rate, while some report no effect of these treatments. Thus, there seems to be an unclear benefit of viral clearance in patients with a history of HCC curative treatment, where the recurrence rate remains worryingly high. This short review aims to summarize current evidence on the impact of DAAs on HCC recurrence rates, the pathogenic mechanisms and characteristics of HCC recurrence after DAA treatment, the predictors of tumor recurrence, and the impact of DAAs on overall survival.
Design and validation of online fault tolerance architecture for TSV-based 3D-IC

This technical report presents the design, validation and evaluation of an efficient online fault tolerance technique for fault detection and recovery in presence of three TSV defects: voids, delamination between TSV and landing pad, and TSV short-to-substrate. The technique employs transition delay test for TSV fault detection. Fault recovery is carried out by employing redundant TSVs and rerouting input/output signals to fault-free TSVs. This technique is efficient because it requires small (2 x number of TSVs per group) number of clock cycles for fault detection and recovery. Using 65-nm technology, simulations are carried out using HSPICE and ModelSim to validate fault detection and recovery. Synthesized RTL model of this technique is used to evaluate the area overhead. It is shown that regular and redundant TSVs can be divided into groups to minimize area overhead without affecting fault tolerance capability of the technique.
The Use of Third-Party Logistics Services by Large American Manufacturers: The 2004 Survey

This article examines the findings of a survey conducted during 2004 of large American manufacturers that addressed their use of third-party logistics (3PL) services. The survey data show that the percentage of those companies using such services is at a record high level, and that users are giving a steadily increasing percentage of their logistics operating budgets to 3PL service providers. Many 3PL relationships are long-term in nature, and the service providers continue to deliver value to their clients. The movement of large American manufacturers into other geographies for sourcing, manufacturing, and sales has led many of their 3PL service providers to expand into those areas to support those activities. During the next several years, the possible adoption of radio frequency identification (RFID) technology by many of these manufacturers will pose significant challenges to their 3PL providers in attempting to meet the related needs of their clients.
EVALUATION OF PHARYNGEAL AIRWAY AND HYOID BONE POSITION ACCORDING TO DIFFERENT GROWTH-DEVELOPMENT PERIODS

Background: The aim of this study was to evaluate the pharyngeal airway and hyoid measurements according to gender and pre-peak, peak and post-peak growth-development stages.Method: In our study were included 531 people. The classification of the patients according to the pubertal growth attack periods in the grouping according to the growth-development period was determined from the lateral cephalometric films taken at the beginning of the treatment. The pharyngeal airway and hyoid measurements were compared according to three different growth-development periods. SPSS program was used for data analysis. Results: A statistical relationship was observed between growth-development periods, gender and chronological age (p<0.05). A statistically significant difference was found in the majority (86%) of pharyngeal airway dimensions and hyoid measurements in all three groups (p<0.05). Conclusions: With age and as the growth-development periods progress, the dimensions of the pharyngeal airway increase and the hyoid bone moves downwards.
Elastostatic Model of a New Hybrid Minimally-Invasive-Surgery Robot

In this paper, the elastostatic model of a novel hybrid robot for minimally invasive surgery is presented. The parallel robot has two identical limbs of SPU type and a RRR limb which allows the end-effector to accomplish spherical motion. The robot has three actuated joints for the parallel architecture and one for the translation along the longitudinal axis of the surgical instrument. The parallel manipulator provides remote centre of motion located at the incision point of the patient's body. First, the kinematics is solved in closed-form for the forward and inverse positioning problems, then elastostatic analysis of the parallel manipulator is modelled considering a system of flexible links and rigid bodies connected by means of joints. Local stiffness matrices are derived and finally combined to obtain the global stiffness matrix of the robotic system. Results are compared with those coming from commercial FE software for validation. Positioning and orienting errors due to flexibility are evaluated in order to improve quality in positioning and tracking of trajectories. Finally, some extensions to sensitivity analysis are provided to demonstrate that the elastostatic model can be used to improve the performance of the robot.
Extrapolation of Test Data in Time, Size and Risk: A Challenge for Concrete Design Codes

It is no secret that the lifetimes of concrete structures have been inadequate, and that structural failures are far too common, especially in the case of large structures of novel designs. This problem has two aspects: 1) randomness of loads such as those from traffic, environment and random vibrations, and 2) the uncertainty in material properties, role of corrosive agents, and failure mechanics. Significant progress has been achieved in the first, but less in the second, which is a problem of extrapolation. The second is just as important, yet has been mostly neglected by structural safety specialists. Only the second aspect is discussed in this lecture, and only in qualitative, non-mathematical, terms. A broad vision of the extrapolation problem is offered. Lapses of quality control are a different problem, not discussed here.
Efficient Software Implementations of Fantomas

We present a series of software implementations of the Fantomas block cipher in resource-constrained ARM devices like the Cortex-M3 and Cortex-M4; and more powerful processors such as the ARM Cortex-A15 and modern Intel platforms. Our implementations span a broad range of characteristics: 32-bit and 64-bit versions, side-channel resistant and vectorized code for NEON and SSE instructions. Our implementations of the algorithm improve the state of the art substantially, both in terms of efficiency or compactness, by making use of novel algorithmic techniques and features specific to the target platform. In particular, our unprotected 32-bit implementation achieves speedups from 35% to 66% in the ARM Cortex-M architecture, while consuming considerably less code size. The vectorized implementations improve performance over the state of the art by 40% in the ARM Cortex-A15 and 50% in the Core i7 Ivy Bridge, setting new speed records for the implementation of the block cipher.
Structural Equation Modelling for Validating Disruptive Factors in Livestock Supply Chain

The purpose of this paper is to deploy a structural equation modeling approach through the Partial Small Square technique to validate the disruptions factors that affect livestock supply chain performance. The disruption prediction factors were obtained from the analysis of literature studies and data from the Department of Veterinary Services (DSV) and expert evaluation. Factors considered in the study model are Livestock Process, Finance, Breeders, Quality, Facilities, Technology, Demand, Supply, Information Communication, Sales, Transportation, Government Involvement, Disaster and Syariah Compliance. The results of the study found that the factors of Livestock Process, Finance, Breeders, Livestock Quality, Technology, Supply, Sales, Transportation, Government Involvement and Syariah Compliance were accepted as disruptions in the livestock supply chain. The findings of this study will assist farmers and livestock stakeholders to take necessary measures to minimise the disruption and further the government's goal of enlivening small and medium livestock enterprises in Malaysia.
On the Bahadur Representation of Quantiles for a Sample from ρ*-Mixing Structure Population

In this paper, we establish the strong consistency and the Bahadur representation of sample quantiles for ρ*-mixing random variables. Additionally, the asymptotic normality and the Berry-Esseen bound of sample quantiles for ρ*-mixing random variabl es are presented. Moreover, numerical simulation is presented to ilustrate obtained results. Abstract In this paper, we establish the strong consistency and the Bahadur representation of sample quantiles for ρ ∗ -mixing random variables. Additionally, the asymptotic normality and the Berry-Esseen bound of sample quantiles for ρ ∗ -mixing random variables are presented. Moreover, numerical simulation is presented to ilustrate obtained results.
Using Machine Learning Techniques to Predict Bugs in Classes: An Empirical Study

—Software bug prediction is an important step in the software development life cycle that aims to identify bug-prone software modules. Identiﬁcation of such modules can reduce the overall cost and effort of the software testing phase. Many approaches have been introduced in the literature that have investigated the performance of machine learning techniques when used in software bug prediction activities. However, in most of these approaches, the empirical investigations were conducted using bug datasets that are small or have erroneous data leading to results with limited generality. Therefore, this study empirically investigates the performance of 8 commonly used machine learning techniques based on the Uniﬁed Bug Dataset which is a large and clean bug dataset that was published recently. A set of experiments are conducted to construct bug prediction models using the considered machine learning techniques. Each constructed model is evaluated using three performance metrics: accuracy, area under the curve, and F-measure. The results of the experiments show that logistic regression has better performance for bug prediction compared to other considered techniques.
A new electronic device for measuring pulse and oxygen concentration

2 ACKNOWLEDGEMENTS . 3 TABLE OF FIGURE . 8 LIST OF TABLE . 11 PUBLICATION . 12 GLOSSARY . 13 ABBREVIATION . 15
Balance between thermopower, electric and magnetic interactions in CuCrO2, Bi8Rh7O22 and MnSc2Se4

Transition metal based compounds with Ti, Cr, Mn, Fe, Co, and Ni are essential for many electronic functionalities. These compounds show rich physics with complex structural features that lead to interesting magnetic and electrical properties. Specific transition metal oxides reveal coupling between magnetic and electric order. This coupling requires a balance between crystal structure considerations and electronic interactions. In thermoelectric oxide materials, a balance must be found between the thermoelectric power factor, which is directly related to the Seebeck coefficient and the electrical conductivity, and the thermal conductivity. Finding this balance is facilitated in narrow band gap semiconductors, where the band gap can be modified by either intrinsic defects, extrinsic dopants or vacancies. This thesis covers both types of balance. The magnetic and thermoelectric properties are investigated in two p-type semiconductors, CuCrO2 and Bi8Rh7O22, and magneto-dielectric coupling is investigated in the A-site spinel, MnSc2Se4. CuCrO2 powder samples were synthesized using solid state reaction, sol-gel and hydrothermal methods, which provide different particle sizes. The morphology, grain interfaces and grain orientation have a more dominant effect on thermoelectric performance. The sol-gel synthesis is more promising by reducing the electrical resistivity, thus, increasing the thermoelectric properties. Furthermore, we study the pyroelectric current and the thermally stimulated depolarization of CuCrO2, which provides detailed information about the defect states of the compound.