Miracle-dz/UniFAR-FTUs huggingface dataset:
THE INEVITABILITY OF DIGITAL PUBLIC SPACE HETEROREGULATION: FRAMING THE PORTUGUESE

The expectations and behaviors transferred to digital environments harbor broader structures and historical processes that predate the establishment of digital culture itself. For this reason, the actions of individuals in the digital arena represent different forms of technology appropriation. Digital platforms are now recognized as utopian because they amplify new censorious mechanisms. On the one hand, hate speech and various forms of violence shape a new media system; on the other hand, they allow individuals and groups to attempt to condition and silence digital public spaces, especially the female universe. Journalistic activity has always been recognized as an ethical and deontological duty to combat censorship. Based on semi-structured indepth interviews with 31 Portuguese women journalists, this research aims to identify the follow-up of Portuguese media to the successive decadent transformations of digital culture. Using the descriptive approach of thematic analysis, the results expose the inoperability of self-regulation of media and journalists. The bias of traditional values of denunciation is developed in internal rhetoric of violence normalization suffered by journalists, the subsequent disregard of audience participation and the practice of some censorship practices in journalistic contents. This scenario has potentiated the invasive temptations of heteroregulation by the political power, delegating to a public institution the competences for determining which digital contents are worthy of “sanctioning regimes”.
Paediatric paranasal sinus fibrous dysplasia

Fibrous dysplasia in the bony walls of a paranasal sinus is a developmental tumour that is associated with a marked facial deformity. Delay in hospital presentation contributes to the destructive resection techniques employed and the management outcome. Our study looks at the factors for delay in hospital presentation and the management outcome by a retrospective review between January 1997 and December 2018. Of 43 children (M: F 1:1.2) with a mean age of 12 ± 1.75 years, the maxillary bones were mostly affected. All underwent surgical resection with good management outcomes except for maxillectomy. Tumour recurrence was noted in five and there was no mitotic cell at histology. The clinical symptoms of fibrous dysplasia vary in severity and age of onset, often with late hospital presentation already with complications. Health education is needed to reverse this trend.
Detection of F94L marker in myostatin (MSTN/TaqI) gene of Indonesian Sumba Ongole cattle (Bos indicus)

Sumba Ongole (SO) cattle are Ongole cattle from India which were imported to Indonesia during the Dutch colonial era and were well adapted on Sumba Island, East Nusa Tenggara, Indonesia. Sumba Ongole (SO) cattle are known for high meat production. This research was conducted to identify one point mutation of g.415C/A (F94L marker) in the myostatin (MSTN) gene (exon 1) using PCR-RFLP method with TaqI restriction enzyme (T*CGA). DNA samples of SO bulls and cows (Total 153) from Sumba Island were used in this study. Results revealed that all samples in this study had CC genotype with C allele as the common allele. The mutation point of g.415C/A was not found in this study. However, one mutation point of g.400G/A was detected in this study without amino acid changes (synonymous). It was concluded that MSTN/TaqI gene in the present study is monomorphic and cannot be used as the genetic marker for productive traits of SO cattle.
A Supervoxel Segmentation Method With Adaptive Centroid Initialization for Point Clouds

Supervoxels find applications as a pre-processing step in many image processing problems due to their ability to present a regional representation of points by correlating them into a set of clusters. Besides reducing the overall computational time for subsequent algorithms, the desirable properties in supervoxels are adherence to object boundaries and compactness. Existing supervoxel segmentation methods define the size of a supervoxel based on a user inputted resolution value. A fixed resolution results in poor performance in point clouds with non-uniform density. Whereas, other methods, in their quest for better boundary adherence, produce supervoxels with irregular shapes and elongated boundaries. In this article, we propose a new supervoxel segmentation method, based on k-means algorithm, with dynamic cluster seed initialization to ensure uniform distribution of cluster seeds in point clouds with variable densities. We also propose a new cluster seed initialization strategy, based on histogram binning of surface normals, for better boundary adherence. Our algorithm is parameter-free and gives equal importance to the color, spatial location and orientation of the points resulting in compact supervoxels with tight boundaries. We test the efficacy of our algorithm on a publicly available point cloud dataset consisting of 1449 pairs of indoor RGB-D images, i.e., color (RGB) images coupled with depth information (D) mapped per pixel. Results are compared against three state-of-the-art algorithms based on four quality metrics. Results show that our method provides significant improvement over other methods in the undersegmentation error and compactness metrics and, performs equally well in the boundary recall and contour density metrics.
Consequences of Assumption Violations Regarding Classical Location Tests

Nearly all classical statistical hypothesis tests are derived under a few fundamental assumptions, which may or may not be met in real world applications. The main aim of this article is to study consequences of a normality assumption violation concerning classical statistical methods, mainly its effect on type I and type II errors when dealing with one-sample or two-sample location tests. The focus will be on a very popular one-sample t-test, as well as on a Behrens-Fisher problem, i.e. on hypothesis testing concerning the difference between expected values of two random variables with unknown and possibly different variances. Based on a simulation study the consequences of different forms of non-normality will be examined for various sample sizes. Type I and type II errors of the classical tests will be then compared with those of appropriate nonparametric tests, specifically with the errors of the Wilcoxon signed-rank and rank-sum tests, as well as the tests based on bootstrap methodology. Based on the results of the conducted simulation study it can be inferred that the classical t-tests tend to be conservative or liberal depending on a form of non-normality. It will be also demonstrated that in case of a contaminated distribution with possible outliers the Wilcoxon tests should be always considered, and that for skewed data and a large sample size the bootstrap BCa method may also be preferable.
Variability in Biological Activities of Satureja montana Subsp. montana and Subsp. variegata Based on Different Extraction Methods

Winter savory (Satureja montana L.) is a well-known spice and medicinal plant with a wide range of activities and applications. Two subspecies of S. montana, subsp. montana and subsp. variegata, were used for the preparation of seven different extracts: steam distillation (essential oil (EO) and hydrolate (HY)), subcritical water (SWE), ultrasound-assisted (UAE-MeOH and UAE-H2O), and microwave-assisted (MAE-MeOH and MAE-H2O) extraction. The obtained EOs, HYs, and extracts were used for an in vitro evaluation of the antioxidant activity (DPPH, ABTS, reducing power, and superoxide anion methods) and in vitro antimicrobial activity against Bacillus cereus, Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, Salmonella Typhimurium, Saccharomyces cerevisiae, and Candida albicans. The antimicrobial screening was conducted using disk-diffusion assessment, minimal inhibitory concentration, time–kill kinetics modeling, and pharmacodynamic study of the biocide effect. The total phenolic content (TPC) was highest in EO, followed by SWE, MAE, and UAE, and the lowest was in HY. The highest antimicrobial activity shows EO and SWE for both varieties, while different UAE and MAE extracts have not exhibited antimicrobial activity. The natural antimicrobials in the S. montana extract samples obtained by green extraction methods, indicated the possibility of ecologically and economically better solutions for future in vivo application of the selected plant subspecies.
An Energy Efficient STDP-Based SNN Architecture With On-Chip Learning

In this paper, we propose a spike-time based unsupervised learning method using spiking-timing dependent plasticity (STDP). A simplified linear STDP learning rule is proposed for the energy efficient weight updates. To reduce unnecessary computations for the input spike values, a stop mechanism of the forward pass is introduced in the forward pass. In addition, a hardware-friendly input quantization scheme is used to reduce the computational complexities in both the encoding phase and the forward pass. We construct a two-layer fully-connected spiking neuron network (SNN) based on the proposed method. Compared to general rate-based SNNs trained by STDP, the proposed method reduces the complexity of network architecture (an extra inhibitory layer is not needed) and the computations of synaptic weight updates. According to the fixed-point simulation with 9-bit synaptic weights, the proposed SNN with 6144 excitatory neurons achieves 96% of recognition accuracy on MNIST dataset without any supervision. An SNN processor that contains 384 excitatory neurons with on-chip learning capability is designed and implemented with 28 nm CMOS technology based on the proposed low complexity methods. The SNN processor achieves an accuracy of 93% on MNIST dataset. The implementation results show that the SNN processor achieves a throughput of 277.78k FPS with $0.50~\mu \text{J}$ /inference energy consuming in inference mode, and a throughput of 211.77k FPS with $0.66~\mu \text{J}$ /learning energy consuming in learning mode.
Emetine in Combination with Chloroquine Induces Oncolytic Potential of HIV-1-Based Lentiviral Particles

Chloroquine and Emetine are drugs used to treat human parasitic infections. In addition, it has been shown that these drugs have an antiviral effect. Both drugs were also found to cause a suppressive effect on the growth of cancer cells of different origins. Here, using the replication-deficient HIV-1-based lentiviral vector particles, we evaluated the ability of the combination of these drugs to reduce viral transduction efficiency. We showed that these drugs act synergistically to decrease cancer cell growth when added in combination with medium containing lentiviral particles. We found that the combination of these drugs with lentiviral particles decreases the viability of treated cells. Taken together, we state the oncolytic potential of the medium containing HIV-1-based particles provoked by the combination of Chloroquine and Emetine.
Intelligent classification of land cover types in open-pit mine area using object-oriented method and multitask learning

Abstract. Although the exploitation of mineral areas brings wealth to society, it inevitably leads to the degradation of the surrounding natural environment. To understand and assess the influences of mining activities on the geological and ecological environment, land cover classification in open-pit mine areas (LCCMA) is of great significance. This research proposes an intelligent classification framework for LCCMA based on an object-oriented method and multitask learning (MTL), named the MTL Classification Framework (MTLCF). With the help of MTL, each land cover type in open-pit mine areas obtains its exclusive and receivable object-oriented feature sets using the model-agnostic method. After that, the feature sets are fused with the original images. EfficientNet, a spatial pyramid pooling module, and a global attention upsample module are assembled as the segmentation models with the structure of the encoder and decoder to classify intelligently each land cover type in open-pit mine areas. Finally, the models were trained, and ablation experiments were performed. The experimental results show that our proposed framework -MTLCF was effective for classification in LCCMA, and the overall accuracy and the mean of F1 score for the MTLCF in LCCMA were 85.6% and 86.06%, respectively.
Fatigue performance investigation on the automotive welded structure under damped loads using the Taguchi method

In the present paper, a three‐dimensional numerical model has been built using ANSYS code to analyze the static and fatigue behavior of a welded design based on four rectangular profiles under damped loads for automotive application. The fatigue of the proposed design is generally influenced by a number of factors. The aim of this study is to investigate the effect of the load level, the stress ratio, the mean stress theory, the geometry size, the weld bead height, the temperature of the weld bead on the durability (P1), and the maximum of von Mises stress (P2) at the critical areas in the welded structure. As well as the length and the stiffness of the spring have been furtherly investigated. For this purpose, the application of the Taguchi method with computational simulation was performed for the target to determine the optimum operating parameters conditions. The results indicated that the optimum levels yielding a higher performance for P1 and P2 were (L1, L2, L2, L3, L1, L1, L3, and L3) and (L2, L3, L3, L3, L3, L3, L3, and L2), respectively. Thus, it revealed that the weld temperature was the predominant parameter influencing P1 and the mean stress theory factor was the most significant parameter influencing P2. This study led to defining a regression equation relating the output parameters with the selected factors. Consequently, the percentage error between regression equation calculations and computational outputs of fatigue life and maximum von Mises stress corresponding to the most optimal combinations obtained from Taguchi calculations was 0.92% and 0.63%, respectively. In fact, several parameters have been employed in this durability assessment to characterize the behavior of welded rectangular profiles prototype to predict the overall behavior of the suspension system of the automotive.
Topological relationship model for geographical flows

ABSTRACT Geographical flows depict the movement of geographical objects from origin to destination. They can be applied to represent activities such as commuting, commodity trade, information exchange, and migration. The topological relationship model of geographical flows can provide information on the interactions between objects by describing whether two flows are disjoint or coincide partially or completely. For example, it can be applied to determine whether car trips within a city can be shared, identify takeout orders that can be delivered together, and prevent drone collisions. The ability to describe the topological relationship and relative direction between flows is important for analyzing the interaction between two objects. However, although many topological relationship models exist for lines, they are unable to describe both the topological relationship and the relative direction between lines accurately. To address this issue, this study developed a topological relationship model for geographical flows through the formalism of the 9-intersection model that can describe both the topological relationship and the relative direction between two flows. By removing non-existent relationships based on certain constraints, fifteen topological relationships are obtained and classified into six topological predicates. A method for determining the topological relationships was also developed that compares the section IDs and offsets of flows. The developed topological relationship model for flows was evaluated by examining a carpooling scheme based on taxi origin–destination flow data. The results show that the topological relationship model can describe the interactions among objects and select the flows that have specific interactions with other flows. A topological relationship model is proposed that describes topological relationships between flows more accurately and from more perspectives than extant models. Considering its practicability, it can be applied to alleviate various pressing issues in modern society. The model can be applied to the design of carpooling schemes to reduce carbon dioxide emissions. It can be applied to prevent drone collisions and thereby improve air transportation safety and efficiency. It can be applied to identify abnormal areas in cities to help governments better plan the layout of facilities.
Evaluation of the Main Control Strategies for Grid-Connected PV Systems

The present study aims at analyzing and assessing the performance of grid-connected photovoltaic (PV) systems, where the considered arrangement is the two-stage PV system. Normally, the maximum power point tracking (MPPT) process is utilized in the first stage of this topology (DC-DC). Furthermore, the active and reactive power control procedure is accomplished in the second stage (DC-AC). Different control strategies have been discussed in the literature for grid integration of the PV systems. However, we present the main techniques, which are considered the commonly utilized and effective methods to control such system. In this regard, and for MPPT, popularly the perturb and observe (P&O) and incremental conductance (INC) are employed to extract the maximum power from the PV source. Moreover, and to improve the performance of the aforementioned methods, an adaptive step can be utilized to enhance the steady-state response. For the inversion stage, the well-known and benchmarking technique voltage-oriented control, the dead-beat method, and the model predictive control algorithms will be discussed and evaluated using experimental tests. The robustness against parameters variation is considered and an extended Kalman filter (EKF) is used to estimate the system’s parameters. Future scope and directions for the research in this area are also addressed.
The Role of the Amino Acid (Methionine) Protected on the Productivity Performance of the Dairy Cow

One of the most important aspects of livestock is the supply of essential quantities of balanced nutrients manufacture. In several physiological functions of nutrients, concerning organisms, protein has an important role. Ruminants are not wholly protected of amino acids by microflora degradation of animal feed sources and by maintaining proteins from the breakdown in the rumen where both high and medium yielding ruminant amino acids are required, they must be met; therefore, rumen-protected protein (RPP) dietary supplementation, including primarily rumen-protected protein (RPP), methionine (RPMeth), protected from rumen flora, it was necessary. Numerous scientists are attracted in the study of the character of (RPMeth) in a dairy cow about it’s an impact on milk produce, growth rate, N- efficiency, coefficient digestibility, intake of DM. Unluckily, the findings obtained from many RPMeth investigations showed excessive fluctuation results in ruminant nutrition between its helpful and useless influence, specifically during early and late lactation periods. Thus, for ruminants, when they use this review post, farm owners may be careful when they are plan to apply RPMeth to the diet of animals. In summary, supplementation RPMeth also has a positive balanced effect, even with no detrimental effect on the yield of milk, animal productivity and hemato-biochemical parameters, especially during the early lactation when used with a ruminant diet low in crude protein
Genome sequencing of eggplant reveals Eggplant mild leaf mottle virus existence with associated two endogenous viruses in diseased eggplant in Iraq

Abstract Eggplant has recently suffered a serious threat from a virus infection that causes mosaic and fruit deformation in eggplant fields in Iraq. The infection ratio has registered between 1-80% in examined eggplant fields. The Illumina platform has been applied to sequencing genomic DNA and total RNAseq of symptomatic samples in addition to healthy genomic DNA. The analysis of an entire RNA data revealed Eggplant mild leaf mottle virus (EMLMV) as a causal agent of the symptoms. The sequence of EMLMV was composed of 9280 nt encodes ten protein domains and the transcripts per million (TPM) was 9. Two endogenous pararetroviruses registered, Caulimovirus - SMe and SmelV belong to Caulimovirus and Florendovirus genera with lengths of 8233 and 6198 nt respectively, and both were found interestingly in the RNA transcripts. Phylogeny has revealed EMLMV and endogenous elements’ relations to related viruses.
The Dual Beveridge Curve

This study introduces a dual vacancy model to explain the recent anomalous behavior of the Beveridge curve. The model proposes that job vacancies are partitioned into two categories, one for the unemployed and the other for job-to-job transitions, and that they function in separate markets. We estimate the monthly numbers of both job vacancy types for the U
Effects of High Cervical Spinal Cord Stimulation on Gait Disturbance and Dysarthropneumophonia in Parkinson’s Disease and Parkinson Variant of Multiple System Atrophy: A Case Series

High cervical spinal cord stimulation (HCSCS) was found to have therapeutic effects on Parkinsonian gait disturbance. However, the results were inconsistent and confounded with symptoms of pain. This study aimed to reveal the gait and dysarthric effects of HCSCS in PD (Parkinson’s disease) and MSA-P (Parkinson variant of multiple system atrophy) patients without pain. Three PD and five MSA-P patients without painful comorbidities were assessed for gait performance and speech before SCS surgery and at 3- and 6-month follow-up. Stride length and the time spent in the Timed Up-and-Go task showed little change after HCSCS surgery. Overall voice quality (measured by dysphonia severity index) and perceptual speech intelligence improved significantly at 3 months, but improvements slightly diminished at 6 months postoperatively. Change in quality of life (measured by 8-item Parkinson’s disease questionnaire) was also notable at 3 months but narrowed over time following HCSCS. In conclusion, HCSCS showed therapeutic effects in improving the dysarthria but not gait disturbance in pain-free PD and MSA-P patients.