Miracle-dz/UniFAR-FTUs huggingface dataset:
DOSSIÊ ESTUDO DAS EMOÇÕES Study of emotions

: This article aims to examine the possibility to explain the basis of moral behaviour in natural terms consistent with evolutionary theory. The defense position begins with the clarification of the concept of empathy, as done by Hume and Darwin, plus contemporary research in the areas of neuroscience, evolutionary psychology and ethology. My argument points in favor of the hypothesis that socially relevant emotions are regulators of social behaviour, being a criterion for distinguishing between moral and purely social relations. What should be understood is in that bases psychobiological mechanisms of sociability, particularly empathy and social instincts, operate as regulators of normative behaviour in small groups and how this relates to the way moral distinctions are made in everyday life. The focus of this investigation will be to identify the elements that are at the root of such behaviour and explain it without resorting to metaphysical concepts. I will present empathy as the candidate to answer the question of how these mechanisms developed within the evolutionary process and how to add an intersubjective element to social relevant emotions, so that they have the strength to inhibit socially relevant behaviours.
HMER_A_265473 125..138

Department of Hepatology and Gastroenterology, Charité Universitätsmedizin Berlin, Campus Virchow-Klinikum (CVK) Und Campus Charité Mitte (CCM), Berlin, Germany Abstract: Steatosis is a condition of hepatic fat overload that is associated with overweight and the metabolic syndrome. Nonalcoholic fatty liver disease (NAFLD) has become the most common liver disease with a global impact on healthcare. A proportion of NAFLD patients develops nonalcoholic steatohepatitis (NASH), liver fibrosis, cirrhosis or hepatocellular carcinoma (HCC). Identifying patients at risk for potentially life-threatening complications is crucial in their prevention, surveillance and treatment. In addition to hepatic disease progression (cirrhosis, portal hypertension, HCC), NAFLD patients are also at risk of cardiovascular and metabolic diseases as well as extrahepatic malignancies. Liver fibrosis is related to morbidity and mortality in NASH patients, and biomarkers, imaging techniques (ultrasound, elastography, MRI) as well as liver biopsy help in diagnosing fibrosis. In this review, we discuss the tools for identifying patients at risk and their reasonable application in clinical routine in order to stratify prevention and treatment of this emerging disease.
Lynch Syndrome Genetic Testing as an Exemplar of Translational Research as a Whole

The majority of studies involving translational research focus on the assessment of useful molecular mechanisms leading to basic scientific discoveries capable of being translated into diagnostic and therapeutic interventions. Often the full scope of translational research – from benchside discovery to clinical and community application and assessment of cost-effectiveness – gets lost in this initial focus. In this review we consider the development of genetic testing for Lynch syndrome, the most prevalent hereditary form of colorectal cancer, as an exemplar representing all the key phases of translational research. The details of each research stage and respective creative developments are examined, leading up to recent work at the T4 outcomes research stage. The review concludes with questions of implementation in the current healthcare environment.
EMPIRICAL ANALYSIS OF CORRELATION BETWEEN FOREIGN EXCHANGE FLUCTUATION AND PETROLEUM PRICE BASED ON BRAIN NEUROLOGY

The brain neural network, a complex system of interconnected neurons, has been successfully applied in areas like oil price simulation. From the perspective of brain neurology, this paper aims to identify the correlation between foreign exchange fluctuation and the oil price. First, the author introduced the basic principle of brain neural network. On this basis, a positivism model was established to explore the correlation between the said two factors. The empirical data were analyzed through dollar index stability test and Granger causality test. The results show that the international oil price has long been fluctuating severely, especially after the 2008 global financial crisis; the dollar currency rate for oil valuation also changed constantly; there is a significantly negative relationship between the oil price and the US dollar index, i.e. the foreign exchange has a significant impact on oil price. The research results provide new insights into the relationship between exchange rate and oil price.
LSHTM Research Online

Background: Oral cancers are preceded by oral potentially malignant disorders (OPMD). Understanding genetic susceptibility for OPMD risk could provide an opportunity for risk assessment of oral cancer through early disease course. We conducted a review of single nucleotide polymorphism (SNP) studies for OPMD risk. Methods: We identiﬁed all relevant studies examining associations of SNPs with OPMD (leukoplakia, ery- throplakia and oral sub-mucous ﬁbrosis) conducted world-wide between January, 2000 and February, 2016 using a combined keyword search on PubMed. Of these, 47 studies that presented results as odds ratios and 95% CI were considered for full review. Results: The majority of eligible studies that explored candidate gene associations for OPMD were small (N < 200 cases), limiting their scope to provide strong inference for any SNP identiﬁed to date in any population. Commonly studied SNPs were genes of carcinogen metabolism (n = 18 studies), DNA repair (n = 11 studies), cell cycle control (n = 8 studies), extra-cellular matrix alteration (n = 8 studies) and immune-inﬂammatory (n = 6 studies) pathways. Based on signiﬁcant associations as reported by two or more studies, suggestive markers included SNPs in GSTM1 (null), CCND1 (G870A), MMP3 (-1171; promotor region), TNF a (-308; rs800629), XPD (codon 751) and Gemin3 (rs197412) as well as in p53 (codon 72) in Indian populations. However, an equal or greater number of studies reported null or mixed associations for SNPs in GSTM1 (null), p53 (codon 72), XPD (codon 751), XRCC (rs25487 C/T), GSTT1 (null) and CYP1A1m1 (MspI site). Conclusion: Candidate gene association studies have not yielded consistent data on risk loci for OPMD. High-throughput genotyping approaches for OPMD, with concurrent efforts for oral cancer, could prove useful in identifying robust risk-loci to help understand early disease course susceptibility for oral cancer.
-Microglobulin-Deficient Mice 2 b in NK T Cells Induces Airway Hyperreactivity Activation of Nonclassical CD1d-Restricted

Allergic asthma is characterized by Th2-driven eosinophilic airway inﬂammation and by a central feature called airway hyperreactivity (AHR), development of which requires the presence of classical type I invariant NK T ( i NKT) cells. Allergen-induced AHR, however, develops in (cid:1) 2 -microglobulin ( (cid:1) 2 m) (cid:2) / (cid:2) mice, which lack classical i NKT cells, suggesting that in some situations i NKT cells may be dispensable for the development of AHR. In contrast, our studies now suggest that a CD1d-restricted, NK1.1 (cid:3) noninvariant TCR NKT cell population is present in (cid:1) 2 m (cid:2) / (cid:2) mice and is responsible for the development of AHR but not for Th2 responses. Furthermore, treatment of (cid:1) 2 m (cid:2) / (cid:2) mice with anti-CD1d mAb or anti-NK1.1 mAb unexpectedly abolished allergen-induced AHR. The CD1-restricted NKT cells in these mice, which failed to respond to (cid:4) -galactosylceramide and which therefore were not classical type I i NKT cells, appear to represent an NKT cell subset restricted by a (cid:1) 2 m-independent form of CD1d. These results indicate that, although classical type I i NKT cells are normally required for the development of AHR, under different circumstances other NKT cell subsets, including nonclassical NKT cells, may substitute for classical i NKT cells and induce AHR. The Journal of Immunology, 2008, 181:
density and ethnic differences exposed

Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO 2 ) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO 2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO 2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO 2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO 2 levels was small and may not translate into substantive differences in health.
A Wide-Angle and Fully Polarimetric Retrodirective Array Based on Tri-polarized Antennas with Pattern Complementation

A wide-angle and fully polarimetric Van Atta retrodirective array (RDA) based on tri-polarized antennas is proposed in this paper. By leveraging the pattern complementary and polarization orthogonality of three resonant modes including a TM02 monopole-like mode and two orthogonal TM11 microstrip patch modes, the RDA could better sense and retrodirect the incident wave with arbitrary polarization over a large field of view. A prototype of the RDA consisting of four tri-polarized antenna elements is designed and fabricated, which works at 5.8 GHz and has a low-profile planar structure with a compact volume of 1.93 × 0.56 × 0.059 λ03. The simulated and measured monostatic radar cross section (RCS) results show that, compared with the RDA composed of dual-polarized microstrip patches, this tri-polarized RDA has a significant improvement of the retrodictive angle range for the transverse-magnetic (TM) incident wave. Specifically, for the tri-polarized RDA, the -3 dB monostatic RCS beamwidth is 132°, and the -7 dB monostatic RCS beamwidth can reach 180°; while for the dual-polarized RDA, the -3 dB and -7 dB monostatic RCS beamwidth is only 52° and 73°, respectively.
Intelligent Reflecting Surface Based Backscatter Communication for Data Offloading

This paper investigates intelligent reflecting surface based backscatter communication (IRS-BackCom), in order to realize computational task offloading of energy-constrained mobile edge computing network in a self-sustainable manner. Specifically, the system operation is divided into two phases. In the first one, the ambient signal energy from a power beacon (PB) either provides the energy supply of local computing and energy harvesting circuits, or flows into the energy storage, when reaching the IRS. In the second one, the stored energy is used to enable IRS-BackCom for partial computational data offloading and energize local computing circuit. Based on this, the maximization problem of sum computational bits is formulated. By jointly optimizing the beamforming vector at the PB, the backscatter matrix at the IRS, the time scheduling of two-phase process, as well as the time of local computing, sum computational bits are maximized. In addition, this paper proposes element clustering to realize BackCom, so as to reduce the control and computation complexity of IRS. According to different operating mechanisms, two cluster operation modes are considered, namely independent cluster operation mode and joint cluster operation mode. Simulation results demonstrate the achievable sum computational bits by the proposed IRS-BackCom schemes.
Health Monitoring System Using IoT

A clinical benefit is basic for everyone all over the place. Since the time the pandemic started, managing prosperity is given the most need. The clinical consideration environment has cultivated a data-based distant sensor which helps in detaching most of the issues all over. Patients are standing up to an unsafe situation of startling destruction in light of the specific clarification of heart issues and assault which is an aftereffect of the nonexistence of good clinical help to patients at the necessary time. So the proposed system is IOT-based wellbeing observing framework for mature people. This contraption can screen mature people from any space in the world and nearly all experts can assist them with the required help. This endeavor uses sensor advancement and the web to confer. It uses a heartbeat sensor and temperature sensor which are connected to the Arduino-Uno board.
Voltage Tuning for Reliable Computation in Emerging Resistive Memories

Emerging non-volatile memories facilitate the Computation in Memory (CiM) paradigm. Performing operations with the concept of CiM plays a crucial role in the efficiency improvement of data-intensive applications. Resistive switching RAM (ReRAM) and Spin Transfer Torque Magnetic RAM (STT-MRAM) are promising candidates for the CiM implementation. Reliable CiM implementation with these resistive non-volatile memories (memristive devices) is challenging and error-prone since the manufacturing process of both the memristive components and the CMOS components are susceptible to the temperature- and voltage-dependent variation. Moreover, the small distance between the distinct resistive levels of the STT-MRAM, and time-dependent resistance drift in ReRAM, exacerbates the reliability of CiM implementations. In this paper, we perform a detailed study on the impact of the temperature and voltage biasing on the variation in both the STT-MRAM and ReRAM technologies as well as propose a voltage tuning scheme to significantly improve the sensing reliability of CiM implementations based on these technologies. We also investigate the impact of our proposed voltage tuning scheme on the power consumption and performance of the CiM circuitry.
Semi-Supervised Root-Cause Analysis with Co-Training for Integrated Systems

The increasing complexity of integrated systems has exacerbated the challenges associated with system diagnosis. To tackle these challenges, intelligent root-cause-analysis facilitated by machine learning has been proposed in recent years. However, most of these methods rely on a large amount of data with root-cause labels, which are often either not available or difficult to obtain. In this paper, we propose a semi-supervised root-cause-analysis method with co-training, where only a small set of labeled data is required. Using random forest as the learning kernel, a co-training technique is proposed to leverage the unlabeled data by automatically pre-labeling a subset of them and retraining each decision tree. In addition, several novel techniques are proposed to avoid over-fitting and determine hyper-parameters. Two case studies based on industrial designs demonstrate that the proposed approach significantly outperforms state-of-the-art methods by saving up to 43% of labeling efforts by human experts.
Fault-tolerant Embedding Algorithm for Node Failure in Airborne Tactical Network Virtualization

Airborne tactical networks (ATNs) are driving the promising development of Internet of Battle things by enabling efficient information sharing, which is impeded by the network ossification problem that is deep-rooted in the tightly coupled network architecture. As a solution, network virtualization (NV) can break the tight coupling between applications and network infrastructure, providing a more flexible and scalable architecture for ATNs. With complex interference and malicious attacks, the application of NV is challenged by network failures when instantiating multiple virtual networks on a shared substrate network, which is known as survivable virtual network embedding (SVNE). However, existing SVNE algorithms, mostly designed for wired networks, are not necessarily optimal for the virtualization of ATNs due to the complex wireless interference. To this end, a fault-tolerant SVNE algorithm, termed SVNE-FT, is proposed to recover virtual networks from single node failure (end or switching node failure) under the wireless interference. To end node failure, SVNE-FT firstly adopts a novel node ranking approach to select reliable substrate nodes for virtual nodes and then remaps the failed virtual nodes, affected by node failure, by releasing part of the substrate paths to improve the resource utilization. In addition, to switching node failure, it adopts the improved pre-configured cycle (p-Cycle) technology to augment the reliable link mapping with differentiated p-Cycles that protect switching node from node failure and reduce the resource consumption of backups. Numerical simulation results reveal that SVNE-FT outperforms typical and latest heuristic SVNE algorithms under the complex interference of ATNs. For instance, average acceptance ratio of virtual networks improves at least 12%.
Ultra-Thin Artificial Magnetic Conductor for Gain Enhancement of Antenna-on-Chip

System-on-chip (SoC) has become an attractive solution to achieve highly integrated wireless systems. However, the antenna-on-chip (AoC) suffers from poor radiation due to the lossy silicon substrate in standard complementary metal–oxide–semiconductor (CMOS) processes. Artificial magnetic conductors (AMCs) with the ground plane above the silicon can enhance the radiation; however, fitting the AMC completely in the thin stack-up (~10–15 $\mu \text{m}$ ) is extremely challenging, particularly for frequencies below 100 GHz. In this article, metallic posts (MPs) and embedded guiding structures (EGSs) have been investigated to reduce the AMC thickness by employing the available vias and metal layers in the stack-up. An in-house CMOS-compatible process has been used to realize the AoC, where typical low-conductivity adhesion layers have been avoided to reduce the undesired losses by using the surface roughness in a unique fashion. With MP and EGS approaches, AMC thickness can be reduced by 33% and 41%, respectively. The AMC with EGS fits within an oxide of a thickness of 16 $\mu \text{m}$ . A monopole antenna, backed by this AMC, demonstrates a gain of 5.85 dBi and a radiation efficiency of 57% at 94 GHz, bettering the gain and radiation efficiency by 9.15 dB and 42%, respectively, compared to the case without AMC.
PREVALENCE OF GASTROINTESTINAL NEMATODES AND ITS SUSCEPTIBILITY FOR DIFFERENT ANTHELMINTICS IN GRAZING SHEEP IN BENI-SUEF PROVINCE, EGYPT

This study aimed to detect the prevalence and susceptibility of gastrointestinal nematodes (GIT) against three major anthelmintic drugs. Therefore, a total of 1217 sheep from ten grazing flocks was examined for the detection of gastrointestinal parasites. A salt flotation technique and larval culture were carried out. Moreover, FAMACHA system was applied on the examined animals as a guide for anemia. Among examined sheep, a number of 80 infected animals were divided into four equal groups; control untreated group, albendazoleadminstered group-, levamisole-adminsetered group, and ivermectinadminstered one. Meanwhile, a group of 20 animals, GIT-parasites free, were used as a control non-infected. The efficacy of anthelmintics was detected by fecal egg reduction test (FERT) 7 days post treatment. Findings showed that, the overall prevalence of gastrointestinal nematodes was 21.36%. Among them, Haemonchus contortus was present in 16.1%, Trichostrongylus spp. in 2.8%, Strongyloides papillosus in 1.7%, Cooperia spp. in 0.25%, Bonostomum spp. in 0.25%, and Chabertia ovina in 0.25%. There was a correlation between FAMACHA, PCV and fecal egg per gram. FERT was 100% by the 7 th day post treatment in the three treated groups. In conclusion, H. contortus was the highest GIT nematodes among the examined animals, and anemia induced by them could be detected with FAMACHA. Anemia of nutritional disorders and other non-parasitic causes have to be considered parallel with the application of FAMACHA on grazing animals. Based on findings of FER post treatment, animals were susceptible for three anthelmintics, albendazole, levamisole, and ivermectin.
Explorations in Application of Machine Learning in Pre-Synthesis Power Estimation of Digital Systems

This paper presents an approach to exploit Machine Learning (ML) to accurately and efficiently predict power consumption in digital systems at the higher-levels of abstraction prior to synthesis. As valuable resources and much time are invested when developing new products, designers can greatly benefit to know early in the design process if the final design's power consumption is within the reasonable margins of the given constraints. This is done by analyzing the high-level models of the design (behavioral or register transfer level) and without investing resources for synthesizing the design. We have used machine learning models trained on tallies of cell groups that were parsed from gate-level netlists in order to estimate the design’s “internal”, “switching”, “leakage”, and “total” powers. Four supervised learning models, Multi-Layer Perceptron (MLP), Ridge Regression, Elastic Net, and K-Nearest Neighbors, were evaluated across three different technologies: 90 nm, 45 nm, and 15 nm cell libraries. Our experiments provide a meaningful comparison of these models for the 3 technology nodes. The most successful model in the 15 nm library was MLP, which had the smallest error in predicting total power. Additionally, MLP models improved the average error when predicting a single power component (internal, switching, or leakage), compared to simultaneously predicting all three power components in a single model.
Laser analysis of the exhaled air isotope composition in diagnosing nosologically different H. pylori-associated diseases

Laser spectroscopic analysis of the isotope composition of exhaled air was performed for diagnosing the digestive system diseases, associated with Helicobacter pylori infection. An analyzer of 13СО2/12СО2 ratio in exhaled air based on tunable diode lasers and 13С-urea breath test (13С-UBT) were used to diagnose the infection. Nosologically different gastro-intestinal tract diseases: gastric and duodenal ulcer, gastritis and duodenitis were studied. The data of morphologic analysis of the gastric and duodenal mucosa, obtained during fibreoptic gastroduodenoscopyfor 612 patientshave been compared with the results of isotope breath test. The dependence has been analysed of laser 13С-UBT results on nosology and localisation of the H. pylori colony.