Miracle-dz/UniFAR-FTUs huggingface dataset:
Caracterização do sistema de criação de frangos de corte em galpões de pressão negativa, das operações pré-abate e da qualidade do produto final

10 LISTA DE ABREVIATURAS E SIGLAS . 11 1 INTRODUÇÃO . 14 2 REVISÃO DE LITERATURA . 19 2.1. FATORES QUE AFETAM O BEM-ESTAR DE FRANGOS DE CORTE DURANTE A CRIAÇÃO . 22 2.1.1. Operações pré-porteira . 22 2.1. 2. Operações dentro da porteira . 23 2.1. 2.1. Cama de frango . 23 2.1. 2.2. Densidade de criação . 28 2.1. 2.3. Tipologia das construções rurais e conforto térmico . 30 2.2. FATORES QUE AFETAM O BEM-ESTAR DE FRANGOS DE CORTE DURANTE AS OPERAÇÕES PRÉ-ABATE . 33 2.2.1. Apanha . 33 2.2.2. Transporte . 34 2.2.2.1. Densidade e conforto térmico. 35 2.2.2.2. Impactos, distância percorrida e duração . 36 2.2.3. Espera para o abate . 37 2.2.3.1. Mortalidade à chegada ao abatedouro . 38 2.2. 4. Lesões: identificação e classificação . 39 2.3. BEM-ESTAR ANIMAL E QUALIDADE DA CARNE . 42 2.3.1. Condenações de carcaça . 42 2.3.1.1. Qualidade de carne . 43 2.3.2. Defeitos de qualidade de carne . 45 2.3.2.1. Fatores que influenciam a geração de defeitos de qualidade de carne . 47 3 CARACTERIZAÇÃO DA AMBIÊNCIA TÉRMICA E QUALIDADE DA CAMA DE FRANGOS DE CORTE CRIADOS EM GALPÕES DE PRESSÃO NEGATIVA, DO TRANSPORTE E DA ESPERA EM CONDIÇÕES COMERCIAIS . 60 RESUMO . 60 ABSTRACT . 61.61 3.1. INTRODUÇÃO . 62 3.2. MATERIAL E MÉTODOS . 63 Análise estatística . 68 3.3. RESULTADOS E DISCUSSÃO . 69 3.3.1. Características das instalações . 69 3.3.2. Caracterização climática da criação . 74 3.3.3. Caracterização do transporte . 80 3.3.4. Caracterização da espera . 85 3.4. CONCLUSÕES PARCIAIS . 89 4 AVICULTURA DE CORTE: LESÕES ORIGINADAS DURANTE A CRIAÇÃO E O PRÉ-ABATE DE FRANGOS CRIADOS EM GALPÕES COMERCIAIS DE PRESSÃO NEGATIVA . 96 RESUMO . 96 ABSTRACT . 97.97 4.1. INTRODUÇÃO . 98 4.2. MATERIAL E MÉTODOS . 99 4.2.1. Pododermatite e lesão de jarrete . 101 4.2.2. Arranhões da criação e do pré-abate. 101 4.2.3. Fraturas de perna da criação e do pré-abate . 102 4.2. 4. Fraturas de asa da criação e do pré-abate . 103 Análise estatística . 103
Twitter Influencers or Cheated Buyers?

Twitter is one of the most popular social networking platforms that people use to communicate and interact. Organisations and companies use Twitter, as well as other social media platforms, for the marketing of their products or services. To achieve this goal they seek to partner with influential Twitter users, as a part of their influencer marketing strategy. Influencer marketing is considered more effective than traditional marketing. Influencers are more trustworthy than a business due to the fact that they have developed close connection with their followers. This marketing trend has played an important role in the rise of fake influencers in Twitter. Fake influencers inflate their follower counts by buying fake Twitter accounts from vendors and they manage to partner with companies. However, that partnership does not benefit companies as the influencer’s engagement is fake. In this paper we analyse centrality and overall network characterization measures applied on Twitter fake influencer accounts and on legitimate influencer accounts. The results showed that the measures we propose are statistically significant and can be easily applied to automatically detect fake influencers on Twitter.
A realistic neuronal network and neurovascular coupling model for the study of multivariate directed connectivity in fMRI data

The use of Multivariate Granger Causality (MVGC) in estimating directed Blood-Oxygen-Level- Dependant (BOLD) connectivity is still controversial. This is mostly due to the short data Ienghts typically available in func- tional MRI (fMRI) acquisitions, to the very nature of the BOLD acquisition strategy (which yields extremely low signal- to-noise-ratio) and importantly to the fact that neuronal activi- ty is convolved with a slow-varying haemodynamic response function (HRF) which therefore generates a temporal confound which is arduous to account for when basing MVGC estimates on vector autoregressive models (VAR). In this paper, we em- ploy realistic complex network models based on Izhikevich neuronal populations, interlinked by realistic neuronal fiber bundles which exert compounded directed influences and cas- cade into Baloon-model-like neurovascular coupling, to explore and validate the MVGC approach to directed connectivity es- timation in realistic fMRI conditions and in a complex directed network setting. In particular, we show in silico that the top 1 percentile of a BOLD connectivity matrix estimated with MVGC from BOLD data similar to the one provided by the Human Connectome Project (HCP) has a Positive Predictive Value very close to 1, hence corroborating the evidence that the “strongest” connections can be safely studied with this method in fMRI.
In Situ Growth of PbS Nanocubes as Highly Catalytic Counter Electrodes for Quantum Dot Sensitized Solar Cells

In this work, a face-centered cubic phase of galena PbS nanocubes, directly in situ grown onto conducting substrates, was fabricated by a facile chemical bath deposition method. The as-prepared PbS nanocubes show a highly crystalline structure and a quite uniform rectangular shape with approximate dimensions of 60–80 nm. These PbS nanocubes are demonstrated to act as excellent counter electrode (CE) materials in quantum dot sensitized solar cells (QDSCs) for electrocatalyzing polysulfide electrolyte regeneration. A CdS/CdSe QDSC constructed with a PbS nanocube-based CE yields a considerable power conversion efficiency of 3.49%. Moreover, the performance characterizations reveal that PbS CEs exhibit comparable electrocatalytic activity to the conventional Cu2S CEs while significantly outperforming the noble Pt CEs. Meanwhile, PbS CEs bypass the stability and contamination problems of Cu2S CEs. This work provides an alternative CE with advantages of high catalytic capability and stability as well as the ease of fabrication.
Interpretable Machine Learning Techniques for Causal Inference Using Balancing Scores as Meta-features

Estimating individual causal effect is important for decision making in many fields especially for medical interventions. We propose an interpretable and accurate algorithm for estimating causal effects from observational data. The proposed scheme is combining multiple predictors’ outputs by an interpretable predictor such as linear predictor and if then rules. We secure interpretability using the interpretable predictor and balancing scores in causal inference studies as meta-features. For securing accuracy, we adapt machine learning algorithms for calculating balancing scores. We analyze the effect of t-PA therapy for stroke patients using real-world data, which has 64,609 records with 362 variables and interpret results. The results show that cross validation AUC of the proposed scheme is little less than original machine learning scheme; however, the proposed scheme provides interpretability that t-PA therapy is effective for severe patients.
Sphingosine kinase 1 promotes the metastasis of colorectal cancer by inducing the epithelial-mesenchymal transition mediated by the FAK/AKT/MMPs axis

It was demonstrated that Sphingosine kinase 1 (SphK1) promotes tumor progression and confers the malignancy phenotype of colorectal cancer by activating the focal adhesion kinase (FAK) pathway. However, further clarification is required to determine if SphK1 promotes the metastasis of colorectal cancer by inducing epithelial-mesenchymal transition (EMT), and its mechanisms have not been fully elucidated. Immunohistochemistry staining was used to detect protein expression in normal colonic mucosa tissues and colorectal cancer tissues. Cells were transfected to overexpress SphK1, downregulate SphK1 or downregulate FAK. An MTT assay was used to detect the drug toxicity to cells. Transwell and wound healing assays were used to detect cell migration ability. Reverse transcription-polymerase chain reaction and western blot analysis were used to detect the expression of mRNA and protein, respectively. Scanning electron microscopy was used to observe the microvilli and pseudopodia of the cells. The analysis of protein expression in 114 human colorectal cancer tissues demonstrated that the expressions of SphK1, FAK, phosphorylated (p)-FAK, E-cadherin and vimentin were associated with the metastasis of colorectal cancer. Furthermore, the patients with colorectal cancer with SphK1-positive cancer demonstrated poorer prognosis compared with SphK1-negative cancer. FAK knockdown and SphK1 knockdown of human colon cancer RKO cells inhibited the EMT and migrational potency, along with the expression of p-FAK, p-protein kinase B (AKT) and matrix metalloproteinase (MMP)2/9. In contrast, SphK1 overexpression promoted EMT, migrational potency, and the expression of p-FAK, p-AKT and MMP2/9 in HT29 cells. Additionally, the EMT and migrational potency of SphK1-overexpressing HT29 cells was suppressed by a FAK inhibitor, and the expression of p-FAK, p-AKT and MMP2/9 was suppressed by blocking the FAK pathway. In conclusion, SphK1 promoted the migration and metastasis of colon cancer by inducing EMT mediated by the FAK/AKT/MMPs axis.
ShieldScatter: Improving IoT Security with Backscatter Assistance

The lightweight protocols and low-power radio technologies open up many opportunities to facilitate Internet-of-Things (IoT) into our daily life, while their minimalist design also makes IoT devices vulnerable to many active attacks due to the lack of sophisticated security protocols. Recent advances advocate the use of an antenna array to extract fine-grained physical-layer signatures to mitigate these active attacks. However, it adds burdens in terms of energy consumption and hardware cost that IoT devices cannot afford. To overcome this predicament, we present ShieldScatter, a lightweight system that attaches battery-free backscatter tags to single-antenna devices to shield the system from active attacks. The key insight of ShieldScatter is to intentionally create multi-path propagation signatures with the careful deployment of backscatter tags. These signatures can be used to construct a sensitive profile to identify the location of the signals' arrival, and thus detect the threat. We prototype ShieldScatter with USRPs and ambient backscatter tags to evaluate our system in various environments. The experimental results show that even when the attacker is located only 15 cm away from the legitimate device, ShieldScatter with merely three backscatter tags can mitigate 97% of spoofing attack attempts while at the same time trigger false alarms on just 7% of legitimate traffic.
A limited capacity for microglial repopulation in the adult brain

Microglia are the resident immune cell of the central nervous system (CNS), and serve to protect and maintain the local brain environment. Microglia are critically dependent on signaling through the colony‐stimulating factor 1 receptor (CSF1R); administration of CSF1R inhibitors that cross the blood brain barrier (BBB) lead to the elimination of up to 99% of microglia, depending on CNS exposure and treatment duration. Once microglia are depleted, withdrawal of inhibitor stimulates repopulation of the entire CNS with new cells, conceivably enabling a therapeutic strategy for beneficial renewal of the entire microglial tissue. We have explored the kinetics and limits of this repopulation event and show that the rate of microglial repopulation is proportional to the extent of microglial depletion – greater depletion of microglia results in more rapid repopulation. Using a CSF1R inhibitor formulation that eliminates approximately 99% of microglia within 7 days, we subjected mice to multiple rounds of elimination (7 days’ treatment) and repopulation (7 days’ recovery) and found that the brain only has the capacity for a single complete repopulation event; subsequent elimination and CSF1R inhibitor withdrawal fail to repopulate the brain. However, if the recovery time between, or after, cycles is extended sufficiently then the brain can ultimately repopulate. These kinetic studies define the opportunities and possible limits of the remarkable renewal capacities of microglia.
Phonoloco: Facilitating Playful Interactions with Location Aware Smartphones

The Phonoloco technology allows to repurpose a set of regular smartphones into a system that allows for playful interactions. The most important feature of the proposed system is the use of the front-facing camera and a pattern on the ceiling in order to sense the position of each device lying on a flat surface at centimeter precision. This way each smartphone becomes a digital manipulative that can be displaced by the player. The details of the technology will be revealed and an overview of possible interactions will be given. Two games were developed and tested with preschoolers, illustrating the feasibility of the system.
Comparison of EEG microstates with resting state fMRI and FDG‐PET measures in the default mode network via simultaneously recorded trimodal (PET/MR/EEG) data

Simultaneous trimodal positron emission tomography/magnetic resonance imaging/electroencephalography (PET/MRI/EEG) resting state (rs) brain data were acquired from 10 healthy male volunteers. The rs‐functional MRI (fMRI) metrics, such as regional homogeneity (ReHo), degree centrality (DC) and fractional amplitude of low‐frequency fluctuations (fALFFs), as well as 2‐[18F]fluoro‐2‐desoxy‐d‐glucose (FDG)‐PET standardised uptake value (SUV), were calculated and the measures were extracted from the default mode network (DMN) regions of the brain. Similarly, four microstates for each subject, showing the diverse functional states of the whole brain via topographical variations due to global field power (GFP), were estimated from artefact‐corrected EEG signals. In this exploratory analysis, the GFP of microstates was nonparametrically compared to rs‐fMRI metrics and FDG‐PET SUV measured in the DMN of the brain. The rs‐fMRI metrics (ReHO, fALFF) and FDG‐PET SUV did not show any significant correlations with any of the microstates. The DC metric showed a significant positive correlation with microstate C (rs = 0.73, p = .01). FDG‐PET SUVs indicate a trend for a negative correlation with microstates A, B and C. The positive correlation of microstate C with DC metrics suggests a functional relationship between cortical hubs in the frontal and occipital lobes. The results of this study suggest further exploration of this method in a larger sample and in patients with neuropsychiatric disorders. The aim of this exploratory pilot study is to lay the foundation for the development of such multimodal measures to be applied as biomarkers for diagnosis, disease staging, treatment response and monitoring of neuropsychiatric disorders.
STUDENTS' SELF-EVALUATION IN THE CONTEXT OF PRACTICAL PEDAGOGICAL TRAINING

In this article we investigated the students’ self-evaluation in the context of practical pedagogical training in pedagogical second cycle study programmes at the Faculty of Natural Sciences and Mathematics, Faculty of Arts and Faculty of Education at the University of Maribor. The key research objectives were to determine how frequent the interviewed students performed self-evaluation of particular activities and, furthermore, self-evaluation of which activities students carried out the most during their practical training. 148 students participated in the research, namely 127 first year students and 21 second year students of second cycle study programmes at the previously mentioned faculties. The research results point out that less than 40 % of the interviewed students regularly self-evaluated particular activities during their practical training and that they used a highly varying number of hours for this purpose. Also, the results show a partly positive situation regarding the total performance of self-evaluation as well as regarding self-evaluation of particular activities. We believe that standardisation considering duration and scope of the students’ self-evaluation would lead to an improved performance of practical pedagogical training.
Depression, depressive symptoms and treatments in women who have recently given birth: UK cohort study

Objectives To investigate how depression is recognised in the year after child birth and treatment given in clinical practice. Design Cohort study based on UK primary care electronic health records. Setting Primary care. Participants Women who have given live birth between 2000 and 2013. Outcomes Prevalence of postnatal depression, depression diagnoses, depressive symptoms, antidepressant and non-pharmacological treatment within a year after birth. Results Of 206 517 women, 23 623 (11%) had a record of depressive diagnosis or symptoms in the year after delivery and more than one in eight women received antidepressant treatment. Recording and treatment peaked 6–8 weeks after delivery. Initiation of selective serotonin reuptake inhibitors (SSRI) treatment has become earlier in the more recent years. Thus, the initiation rate of SSRI treatment per 100 pregnancies (95% CI) at 8 weeks were 2.6 (2.5 to 2.8) in 2000–2004, increasing to 3.0 (2.9 to 3.1) in 2005–2009 and 3.8 (3.6 to 3.9) in 2010–2013. The overall rate of initiation of SSRI within the year after delivery, however, has not changed noticeably. A third of the women had at least one record suggestive of depression at any time prior to delivery and of these one in four received SSRI treatment in the year after delivery. Younger women were most likely to have records of depression and depressive symptoms. (Relative risk for postnatal depression: age 15–19: 1.92 (1.76 to 2.10), age 20–24: 1.49 (1.39 to 1.59) versus age 30–34). The risk of depression, postnatal depression and depressive symptoms increased with increasing social deprivation. Conclusions More than 1 in 10 women had electronic health records indicating depression diagnoses or depressive symptoms within a year after delivery and more than one in eight women received antidepressant treatment in this period. Women aged below 30 and from the most deprived areas were at highest risk of depression and most likely to receive antidepressant treatment.
The 2018 Shared Task on Extrinsic Parser Evaluation: On the Downstream Utility of English Universal Dependency Parsers

We summarize empirical results and tentative conclusions from the Second Extrinsic Parser Evaluation Initiative (EPE 2018). We review the basic task setup, downstream applications involved, and end-to-end results for seventeen participating teams. Based on in-depth quantitative and qualitative analysis, we correlate intrinsic evaluation results at different layers of morph-syntactic analysis with observed downstream behavior.
Applications of Anomaly Detection Using Deep Learning on Time Series Data

In the modern world, time series data has become a critical part of many systems underlying various types that are recorded to reflect the status of objects according to the timeline. There are many kinds of research investigating to automate the process of analyzing time series data. Long Short-Term Memory (LSTM) network have been demonstrated to be a useful tool for learning sequence data. In this paper, we explore LSTM based approach to analyzing temporal data for abnormal detection. Stacked Long Short-Term Memory (LSTM) network is utilized as a predictor which is trained on normal data to learn the higher level temporal features, then such predictor is used to predict future values. An error-distribution estimation model is built to calculate the anomaly in the score of the observation. Anomalies are detected using a window-based method based on anomaly scores. To prove the promise applicable potential of our approach, we conducted the experiment on some domains (industry system, health monitor system, social based event detection system) come up with time series data including power consumption, ECG signal, and social data respectively.
InP-Based Grounded Coplanar Waveguide to WR3 Transition for Monolithic Integration with THz Photodiodes

A novel monolithic integration concept of an indium phosphide (InP) THz-photodiode (PD) featuring a rectangular waveguide output is presented. The concept is based on a planar grounded coplanar waveguide to rectangular waveguide (GCPW-to-WR3) transition designed on an InP substrate. The presented integration eliminates the need for complex and high-cost hybrid integration and packaging techniques, like flip-chip, wire-bonding, and split-block. The numerical analysis of the designed transition shows a 3dB bandwidth of 44 GHz within the WR3-band. Its electrical performance and bandwidth are compared with the ultra-thin low-dielectric liquid crystalline polymer-based GCPW-to-WR3 transition.
Low Complexity Detectors for Spread Spectrum Receivers

In the context of the recent solutions proposed in the 3GPP for standardization group on NOMA (Non-Orthogonal Multiple Access) schemes, this paper discusses different approaches for implementing an approximate spread spectrum MMSE (Minimum Mean Square Error) detector. In addition, the implication of such detectors on the signal design is presented.
A New Model for RF Ablation Planning in Clinic

Numerical simulations provide effective way to acquire detailed temperature field during radiofrequency ablation (RF). Based on the patient’s real electrical resistance and RF power, we have designed a theoretical model suitable for clinical treatment planning. The human body is assumed to be two cylinders with the inner cylinder simulating the liver with real liver electrical conductivity, while the electrical conductivity of the out cylinder adjusted to match the real resistance recorded when treated with RFA. The orthogonal-array method has been applied to analyze the impact of the main geometric parameters. Results show that a limited range of model parameters with the same resistance and power condition results in similar prediction of ablation range. In addition, RF heating experiments have been performed in the liver of a live pig to validate this model. The simulated temperature fits well with the real temperature. The comparison of the results predicted using the proposed model and previous models finds that the previous uniform-electrical-conductivity model would significantly underestimates or overestimates the ablation range based on the magnitude of the electrical resistance recorded.
Expression Profiles of Phosphoenolpyruvate Carboxylase and Phosphoenolpyruvate Carboxylase Kinase Genes in Phalaenopsis, Implications for Regulating the Performance of Crassulacean Acid Metabolism

Phalaenopsis is one of the most important potted plants in the ornamental market of the world. Previous reports implied that crassulacean acid metabolism (CAM) orchids at their young seedling stages might perform C3 or weak CAM photosynthetic pathways, but the detailed molecular evidence is still lacking. In this study, we used a key species in white Phalaenopsis breeding line, Phalaenopsis aphrodite subsp. formosana, to study the ontogenetical changes of CAM performance in Phalaenopsis. Based on the investigations of rhythms of day/night CO2 exchange, malate contents and phosphoenolpyruvate carboxylase (PEPC) activities, it is suggested that a progressive shift from C3 to CAM occurred as the protocorms differentiated the first leaf. To understand the role of phosphoenolpyruvate carboxylase kinase (PEPC kinase) in relation to its target PEPC in CAM performance in Phalaenopsis, the expression profiles of the genes encoding PEPC (PPC) and PEPC kinase (PPCK) were measured in different developmental stages. In Phalaenopsis, two PPC isogenes were constitutively expressed over a 24-h cycle similar to the housekeeping genes in all stages, whereas the significant day/night difference in PaPPCK expression corresponds to the day/night fluctuations in PEPC activity and malate level. These results suggest that the PaPPCK gene product is most likely involved in regulation of CAM performance in different developmental stages of Phalaenopsis seedlings.