Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects on women empowerment of awareness raising

This work is based on a project developed by the ACCIG (Association of the Culture and Knowledge for the Gender Equality) for some rural municipalities in the Center of Portugal. This project was financed by national funds and by funds from the European Union through the NSRF (National Support Reference Framework). The ACCIG aims to empower people, namely the more disadvantaged, particularly the women who are in more vulnerable situation. From the project, for this work, was used the information about the awareness raising. Namely, the information about what was did in these actions of sensitization, about the characterization of the participants in these initiatives and about the receptivity of the women for these projects. The principal objective of this project is to empower the more disadvantaged social groups, particularly women, enabling these persons to a more civic participation.
A Generalized Birthday Problem (Extended Abstract)

We study a k-dimensional generalization of the birthday problem: given k lists of n-bit values, find some way to choose one el- ement from each list so that the resulting k values xor to zero. For k = 2, this is just the extremely well-known birthday problem, which has a square-root time algorithm with many applications in cryptogra- phy. In this paper, we show new algorithms for the case k> 2: we show a cube-root time algorithm for the case of k = 4 lists, and we give an algorithm with subexponential running time when k is unrestricted. We also give several applications to cryptanalysis, describing new subex- ponential algorithms for constructing one-more forgeries for certain blind signature schemes, for breaking certain incremental hash functions, and for finding low-weight parity check equations for fast correlation attacks on stream ciphers. In these applications, our algorithm runs in O(2 2 √ n ) time for an n-bit modulus, demonstrating that moduli may need to be at least 1600 bits long for security against these new attacks. As an example, we describe the first-known attack with subexponential com- plexity on Schnorr and Okamoto-Schnorr blind signatures over elliptic curve groups.
LXR signaling controls homeostatic dendritic cell maturation

Dendritic cells (DCs) mature in an immunogenic or tolerogenic manner depending on the context in which an antigen is perceived, preserving the balance between immunity and tolerance. Whereas the pathways driving immunogenic maturation in response to infectious insults are well-characterized, the signals that drive tolerogenic maturation during homeostasis are still poorly understood. We found that the engulfment of apoptotic cells triggered homeostatic maturation of type 1 conventional DCs (cDC1s) within the spleen. This maturation process could be mimicked by engulfment of empty, nonadjuvanted lipid nanoparticles (LNPs), was marked by intracellular accumulation of cholesterol, and was highly specific to cDC1s. Engulfment of either apoptotic cells or cholesterol-rich LNPs led to the activation of the liver X receptor (LXR) pathway, which promotes the efflux of cellular cholesterol, and repressed genes associated with immunogenic maturation. In contrast, simultaneous engagement of TLR3 to mimic viral infection via administration of poly(I:C)-adjuvanted LNPs repressed the LXR pathway, thus delaying cellular cholesterol efflux and inducing genes that promote T cell–mediated immunity. These data demonstrate that conserved cellular cholesterol efflux pathways are differentially regulated in tolerogenic versus immunogenic cDC1s and suggest that administration of nonadjuvanted cholesterol-rich LNPs may be an approach for inducing tolerogenic DC maturation. Description Apoptotic cell engulfment and concomitant changes in cholesterol metabolism drive homeostatic, tolerogenic dendritic cell maturation. Cholesterol triggers tolerogenic DCs Whereas dendritic cells (DCs) rapidly undergo immunogenic maturation in response to pathogen exposure, the signals driving their homeostatic maturation into tolerogenic DCs that help prevent autoimmunity remain unclear. Within the mouse spleen, Bosteels et al. identified engulfment of apoptotic cells as a key driver of the homeostatic maturation program among type 1 conventional DCs (cDC1s). Using single cell transcriptomics, they found that pathways controlling cholesterol efflux, including the liver X receptor (LXR) pathway, were induced during homeostatic cDC1 maturation. Cholesterol uptake, either via apoptotic cells or unadjuvanted lipid nanoparticles, promoted homeostastic DC maturation. Conversely, DCs lacking LXRα and LXRβ initiated an immunogenic maturation program after engulfment of apoptotic cells, demonstrating that cholesterol regulatory pathways control the decision between immunogenic and tolerogenic DC maturation. —CO
Deciphering the Patterns of Dual Primary Cases Registered at the Hospital-Based Cancer Registry: First Experience from Rural Cancer Center in North India

Abstract Objectives The objective is to present the patterns of dual primary malignancies diagnosed at the Pathology Laboratory of Cancer Hospital with the support from hospital-based cancer registry (HBCR), Sangrur, Punjab, India for the years 2018 and 2019. Methods HBCR abstracts data from electronic medical records. Trained cancer registry staff abstracts cases in standard pro forma. Dual primary was coded as per the International Agency for Research on Cancer rule and was rechecked by the pathologist. Statistical Analysis Data about multiple primary was entered and documented in an Excel sheet. Time interval was calculated by subtracting the date of diagnosis for second primary and first primary. Results A total of 6,933 cases were registered, 45 cases are dual primary (26 females, 19 males) of which 64.4% are synchronous and 35.6% metachronous cases. Seventy-nine percent received cancer-directed treatment for synchronous and 87% for metachronous. The most common sites of the primary tumor were breast (33%), head and neck (22.2%), gynecological sites (11%), prostate (9%), esophagus (4%), and remaining other tumors (20.8%). Most common sites for second malignancies were gastrointestinal (GI) tract (31%), gynecological sites (18%), head and neck (16%), hematological malignancies (7%), soft tissue sarcoma (4%), breast (2%), and other sites (22%). Conclusion More than 70% of cases of primary tumors were in breast, head and neck, gynecological, and prostate. Of these, more than 60% of the second malignancy was found in the GI tract, gynecological, and head and neck sites. Around two-thirds of dual tumors are synchronous. Breast cancer cases have higher incidence of second malignancy. Regular follow-up is necessary to assess the survival of the second primary.
Interaction of Some Amino-Nitrile Derivatives with Vascular Endothelial Growth Factor Receptor 1 (VEGFR1) Using a Theoretical Model

Abstract Background Some studies indicate that the angiogenesis process is related to vascular endothelial growth factor, which can interact with endothelial cell surface receptors (VEGF-R1, VEGF-R2, and VEGF-R3); this biochemical process and other factors result in the promotion and growth of new blood vessels under normal conditions. However, some studies indicate that this phenomenon could also occur in cancer cells. It is important to mention that some amino derivatives have been prepared as VEGF-R1 inhibitors; however, their interaction with VEGF-R1 is not clear, perhaps due to different experimental approaches or differences in their chemical structure. Objective The aim of this study was to evaluate the theoretical interaction of several amino-nitrile derivatives (Compounds 1 to 38) with VEGF-R1. Methods The theoretical interaction of amino-nitrile derivatives with VEGF-R1 was carried out using the 3hng protein as the theoretical model. In addition, cabozantinib, pazopanib, regorafenib, and sorafenib were used as controls in the DockingServer program. Results The results showed different amino acid residues involved in the interaction of amino-nitrile derivatives with the 3hng protein surface compared with the controls. In addition, the inhibition constant (Ki) was lower for Compounds 10 and 34 than for cabozantinib. Other results show that Ki for Compounds 9, 10, 14, 27–29 and 34–36 was lower in comparison with pazopanib, regorafenib, and sorafenib. Conclusions All theoretical data suggest that amino-nitrile derivatives could produce changes in the growth of some cancer cell lines through VEGFR-1 inhibition. Therefore, these amino-nitrile derivatives could be a therapeutic alternative to treat some types of cancer.
RAIN: robust and adaptive image manipulation based on GAN inversion with a text condition

Recent work has shown various interesting semantic image manipulation methods based on GAN guided by text descriptions. A method based on GAN inversion can achieve versatile image manipulation functions without a time-consuming preprocessing stage. However, the method suffers from a lack of self-adaptation due to the intrinsic conflict between multi-objective losses. Meanwhile, the method applied in image manipulation guided by text conditions is not robust due to the vast and ambiguous search space. To solve the above problems, we propose a novel framework RAIN based on GAN inversion, which can achieve robust and adaptive text-driven image manipulation. As shown in Fig. 1(c), RAIN contains two main parts: CEV Initialization and RAGAN inversion. CEV Initialization can adaptively provide a Candidate Editing Vector (CEV) in a short time. RGAN inversion is a multi-stage optimization scheme utilizing the CEV as prior knowledge to prune search space. In RAGAN inversion, we explore how to improve the vision-language model's perception capability to restrict search space further. The objective of the paper is guaranteeing semantic correctness and image quality in a time-constrained scenario compared to the SOTA image manipulation methods guided by text descriptions. Extensive experiments show that RAIN can manipulate images guided by text description while meeting robustness and self-adaptation.
BP neural network based wireless sensor network for solar energy prediction

Wireless sensor networks are generally deployed in remote areas and areas with complex geographical environments. It is difficult to replace sensor node batteries. Energy acquisition sensor network nodes are powered by solar cells to provide energy to wireless sensor nodes. The randomness and uncertainty of solar energy in the monitoring area make it impossible to continuously provide energy for sensor network nodes. By predicting the results of solar energy and combining the information collected by the wireless sensor network, the energy usage of wireless sensor network nodes is reasonably planned, thereby improving wireless transmission. sensor network lifetime and the accuracy and reliability of sensor node measurement information. Prediction of solar energy in the monitoring area is an important part of improving the monitoring quality and life of wireless sensor networks. In this paper, the BP neural network combined with the climatic factors in the wireless sensor network monitoring area, such as illumination, the average diffuse reflection intensity of the solar panel on the day, etc., are used as reference data to predict the solar energy in the wireless sensor network monitoring area. Compared with the traditional Exponentially Weighted Moving Average algorithm (EWMA), the error rate of the prediction results is lower, and the prediction effect is better due to the comprehensive consideration of various climatic factors.
Alzheimer’s severity classification using Transfer Learning and Residual Separable Convolution Network

Severity classification is the most pivotal task in Alzheimer’s disease diagnosis. Detection of brain structural changes from brain MR images is crucial for Alzheimer’s classification. In this paper, we have proposed a transfer learning and residual separable convolution network for the classification of Alzheimer’s. The proposed network includes three separable convolution layers with two average pooling layers. An upsampling has been performed to regain its spatial resolution for the residual connection. The main intuition of separable convolution is to optimize parameters with depth-wise convolution. Similarly, the residual connection has been used to reduce the vanishing gradient problem. Finally, a three-layer fully connected dense network has been used for the four-class Alzheimer’s classification. Kaggle dataset has been utilized for the experiments to report results. We have achieved an accuracy of 97.32% on the dataset with five-fold cross-validation. Our model has reported an improvement of 1% in jaccard similarity and outperforms the competing models in all vital metrics.
Detecting Coronavirus (COVID -19) Disease Cues from Chest Radiography Images

This paper proposes a deep learning-based approach to detect COVID-19 infections in lung tissues from chest Computed Tomography (CT) images. A two-stage classification model is designed to identify the infection from CT scans of COVID-19 and Community Acquired Pneumonia (CAP) patients. The proposed neural model named, Residual C-NiN uses a modified convolutional neural network (CNN) with residual connections and a Network-in-Network (NiN) architecture for COVID-19 and CAP detection. The model is trained with the Signal Processing Grand Challenge (SPGC) 2021 COVID dataset. The proposed neural model achieves a slice-level classification accuracy of 93.54% on chest CT images and patient-level classification accuracy of 86.59% with class-wise sensitivity of 92.72%, 55.55%, and 95.83% for COVID-19, CAP, and Normal classes, respectively. Experimental results show the benefit of adding NiN and residual connections in the proposed neural architecture. Experiments conducted on the dataset show significant improvement over the existing state-of-the-art methods reported in the literature.
Bioinformatics analysis identifies potential ferroptosis key genes in the pathogenesis of diabetic peripheral neuropathy

Background Diabetic peripheral neuropathy (DPN) is a serious complication in Diabetes Mellitus (DM) patients and the underlying mechanism is yet unclear. Ferroptosis has been recently intensively researched as a key process in the pathogenesis of diabetes but there yet has been no related bioinformatics-based studies in the context of DPN Methods We used data mining and data analysis techniques to screen differentially expressed genes (DEGs) and immune cell content in patients with DPN, DM patients and healthy participants (dataset GSE95849). These DEGs were then intersected with the ferroptosis dataset (FerrDb) to obtain ferroptosis DEGs and the associated key molecules and miRNAs interactions were predicted. Results A total of 33 ferroptosis DEGs were obtained. Functional pathway enrichment analysis revealed 127 significantly related biological processes, 10 cellular components, 3 molecular functions and 30 KEGG signal pathways. The biological processes that were significantly enriched were in response to extracellular stimulus and oxidative stress. Key modules constructed by the protein–protein interaction network analysis led to the confirmation of the following genes of interest: DCAF7, GABARAPL1, ACSL4, SESN2 and RB1. Further miRNA interaction prediction revealed the possible involvement of miRNAs such as miR108b-8p, miR34a-5p, mir15b-5p, miR-5838-5p, miR-192-5p, miR-222-3p and miR-23c. Immune-environment content of samples between DM and DPN patients revealed significant difference in the levels of endothelial cells and fibroblasts, which further speculates their possible involvement in the pathogenesis of DPN. Conclusion Our findings could provide insight for investigations about the role of ferroptosis in the development of DPN.
Art therapy as a comprehensive complementary treatment for Parkinson’s disease

Introduction Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease. Complementary and alternative therapies are increasingly utilized to address its complex multisystem symptomatology. Art therapy involves motoric action and visuospatial processing while promoting broad biopsychosocial wellness. The process involves hedonic absorption, which provides an escape from otherwise persistent and cumulative PD symptoms, refreshing internal resources. It involves the expression in nonverbal form of multilayered psychological and somatic phenomena; once these are externalized in a symbolic arts medium, they can be explored, understood, integrated, and reorganized through verbal dialogue, effecting relief and positive change. Methods 42 participants with mild to moderate PD were treated with 20 sessions of group art therapy. They were assessed before and after therapy with a novel arts-based instrument developed to match the treatment modality for maximum sensitivity. The House-Tree-Person PD Scale (HTP-PDS) assesses motoric and visuospatial processing–core PD symptoms–as well as cognition (thought and logic), affect/mood, motivation, self (including body-image, self-image, and self- efficacy), interpersonal functioning, creativity, and overall level of functioning. It was hypothesized that art therapy will ameliorate core PD symptoms and that this will correlate with improvements in all other variables. Results HTP-PDS scores across all symptoms and variables improved significantly, though causality among variables was indeterminate. Discussion Art therapy is a clinically efficacious complementary treatment for PD. Further research is warranted to disentangle causal pathways among the aforementioned variables, and additionally, to isolate and examine the multiple, discrete healing mechanisms believed to operate simultaneously in art therapy.
A Study of Viscous Incompressible Fluid Flow between Two Parallel Plates

In this paper an endeavor has been made to discover the arrangement of the Navier-Stokes mathematical statements for the stream of a thick incompressible liquid between two plates and the Navier stokes equations are unable to through light on the flow of Newtonian fluids , in derivation of Neiver stokes equation we regarded fluid as continuum , the Neiver stokes equation non linear in natural and prevent us to get single solution in which convective terms interact in a general manner with viscous term , the solution of these equations are valid only in a particular region in a real situation where the plates one very still and the other in uniform movement, with little uniform suction at the stationary plate. An answer has been gotten under the supposition that the weight between the two plates is uniform. It has been demonstrated that because of suction a direct transverse speed is superimposed over the longitudinal speed. With suction, the longitudinal speed conveyance between the plates gets to be allegorical and diminishes along the length of the plate we will discuss different way for that effect pressure and without effect of pressure also when the two plate as fixed with pressure not zero with some application. in This paper also analysis the Unsteady flow of viscous incompressible fluid between two plates .
A population intrinsic timer controls Hox gene expression and cell dispersion during progenitor addition to the body axis

During embryonic development, the timing of events at the cellular level must be coordinated across multiple length scales to ensure the formation of a well-proportioned body plan. This is clear during somitogenesis, where the progenitors must be allocated to the axis over time whilst maintaining a progenitor population for continued elaboration of the body plan. However, the relative importance of intrinsic and extrinsic signals in timing progenitor addition at the single cell level is not yet understood. Heterochronic grafts from older to younger embryos have suggested a level of intrinsic timing whereby later staged cells contribute to more posterior portions of the axis. To determine the precise step at which cells are delayed, we performed single-cell transcriptomic analysis on heterochronic grafts of somite progenitors in the chicken embryo. This revealed a previously undescribed cell state within which heterochronic grafted cells are stalled, post-ingression through the primitive streak. The delayed exit of older cells from this state correlates with expression of posterior Hox genes. Using grafting and explant culture, we find that both Hox gene expression and the migratory capabilities of progenitor populations are intrinsically regulated at the population level. Therefore, we demonstrate that cell dispersion is controlled by a population intrinsic timer to control progenitor addition to the presomitic mesoderm.
Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks

Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in devising corrective neural stimulation before the onset of behavior. Recurrent Neural Networks (RNNs) are common models for sequence data. However, standard RNNs are not able to handle data with temporal distributional shifts to guarantee robust classification across time. To enable the network to utilize all temporal features of the neural input data, and to enhance the memory of an RNN, we propose a novel approach: RNNs with time-varying weights, here termed Time-Varying RNNs (TV-RNNs). These models are able to not only predict the class of the time-sequence correctly but also lead to accurate classification earlier in the sequence than standard RNNs. In this work, we focus on early sequential classification of brain-wide neural activity across time using TV-RNNs applied to a variety of neural data from mice and humans, as subjects perform motor tasks. Finally, we explore the contribution of different brain regions on behavior classification using SHapley Additive exPlanation (SHAP) value, and find that the somatosensory and premotor regions play a large role in behavioral classification.
H1 restricts euchromatin-associated methylation pathways from heterochromatic encroachment

Silencing pathways prevent transposable element (TE) proliferation and help to maintain genome integrity through cell division. Silenced genomic regions can be classified as either euchromatic or heterochromatic, and are targeted by genetically separable epigenetic pathways. In plants, the RNA-directed DNA methylation (RdDM) pathway targets mostly euchromatic regions, while CMT DNA methyltransferases are mainly associated with heterochromatin. However, many epigenetic features - including DNA methylation patterning - are largely indistinguishable between these regions, so how the functional separation is maintained is unclear. The linker histone H1 is preferentially localized to heterochromatin and has been proposed to restrict RdDM from encroachment. To test this hypothesis, we followed RdDM genomic localization in an h1 mutant by performing ChIP-seq on the largest subunit, NRPE1, of the central RdDM polymerase, Pol V. Loss of H1 resulted in NRPE1 enrichment predominantly in heterochromatic TEs. Increased NRPE1 binding was associated with increased chromatin accessibility in h1, suggesting that H1 restricts NRPE1 occupancy by compacting chromatin. However, RdDM occupancy did not impact H1 localization, demonstrating that H1 hierarchically restricts RdDM positioning. H1 mutants experience major symmetric (CG and CHG) DNA methylation gains, and by generating an h1/nrpe1 double mutant, we demonstrate these gains are largely independent of RdDM. However, loss of NRPE1 occupancy from a subset of euchromatic regions in h1 corresponded to loss of methylation in all sequence contexts, while at ectopically bound heterochromatic loci, NRPE1 deposition correlated with increased methylation specifically in the CHH context. Additionally, we found that H1 similarly restricts the occupancy of the methylation reader, SUVH1, and polycomb-mediated H3K27me3. Together, the results support a model whereby H1 helps maintain the exclusivity of heterochromatin by preventing encroachment from other competing pathways.