Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of thermal contact conductance in vacuum-bagged thermoplastic prepreg stacks using infrared thermography

The infrared heating of a vacuum-bagged, thermoplastic prepreg stack of glass/PA66 was studied to investigate the influence of vacuum level on thermal contact resistance between plies. A higher vacuum level was shown experimentally to decrease the transverse heat transfer efficiency, indicating that considering only the effect of heat conduction at the plies interfaces is not sufficient to predict the temperature distribution. An inverse analysis was used to retrieve the contact resistance coefficients as a function of vacuum pressure.
Preparation of an optimized ciprofloxacin-loaded chitosan nanomicelle with enhanced antibacterial activity

Abstract Objective: The objective of this study was to evaluate the effect of lipid structure on physicochemical properties of chitosan-fatty acid nanomicelles and prepare an optimum ciprofloxacin-loaded formulation from these conjugates which could enhance the antibacterial effects of drug against some important pathogens like P. aeruginosa. Significance: Nowadays, resistance in infectious diseases is a growing worldwide concern. Nanocarriers can increase the therapeutic index and consequently reduce the antibiotic resistance. By site-specific delivery of drug, the adverse effects of broad-spectrum antibiotics such as ciprofloxacin would be reduced. Methods: Fatty acid grafted chitosan conjugates were synthetized in the presence of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide. The effects of fatty acid type (stearic acid, palmitic acid, and linoleic acid) on physicochemical properties of conjugates were investigated. Ciprofloxacin was encapsulated in nanomicelles by thin film hydration method. Also, the preparation process was optimized with a central composite design. The antibacterial effect of optimum formulation against P. aeruginosa, K. pneumoniae, and S. pneumoniae species was determined. Results: All conjugates were synthetized with high yield values and the substitution degrees ranged between 2.13 and 35.46%. Ciprofloxacin was successfully encapsulated in nanomicelles. The optimum formulation showed high drug loading (≈ 19%), with particle size of about 260 nm and a sustained release profile of ciprofloxacin. The minimum inhibitory concentrations of ciprofloxacin in optimum formulation against P. aeruginosa and K. pneumoniae species were 4 and 2 times lower in comparison with the free drug, respectively. Conclusions: The antibacterial effect of ciprofloxacin was improved by encapsulation of drug in chitosan nanomicelles.
Shotcrete elasticity revisited in the framework of continuum micromechanics : From submicron to meter level

Understanding the chemomechanical behavior of shotcrete (sprayed concrete) is a prerequisite for better design or failure risk assessment of civil engineering structures. Macroscopic material laws for shotcrete are preferably based on hydration degree–dependent material functions. For a given shotcrete mixture—that is, for a fixed water-cement ratio (w∕c) and aggregate-cement ratio (a∕c) —these functions are determined directly from macroscopic experiments. In a purely macroscopic context, considering changes in the w∕c ratio (as often encountered in large tunnel projects), or in the a∕c ratio would require additional experiments. As an alternative, such hydration degree–dependent material functions can be predicted by considering quantitative information at the microlevel of the cementitious material, in the framework of continuum micromechanics. In this contribution, we focus on the dependence of the elastic stiffness on the hydration degree. We employ a two-step homogenization procedure: within a repre.
Re-Weighted Learning for Sparsifying Deep Neural Networks

This paper addresses the topic of sparsifying deep neural networks (DNN's). While DNN's are powerful models that achieve state-of-the-art performance on a large number of tasks, the large number of model parameters poses serious storage and computational challenges. To combat these difficulties, a growing line of work focuses on pruning network weights without sacrificing performance. We propose a general affine scaling transformation (AST) algorithm to sparsify DNN's. Our approach follows in the footsteps of popular sparse recovery techniques, which have yet to be explored in the context of DNN's. We describe a principled framework for transforming densely connected DNN's into sparsely connected ones without sacrificing network performance. Unlike existing methods, our approach is able to learn sparse connections at each layer simultaneously, and achieves comparable pruning results on the architecture tested.
Vertebrate Intersectin1 Is Repurposed to Facilitate Cortical Midline Connectivity and Higher Order Cognition

Invertebrate studies have highlighted a role for EH and SH3 domain Intersectin (Itsn) proteins in synaptic vesicle recycling and morphology. Mammals have two Itsn genes (Itsn1 and Itsn2), both of which can undergo alternative splicing to include DBL/PH and C2 domains not present in invertebrate Itsn proteins. To probe for specific and redundant functions of vertebrate Itsn genes, we generated Itsn1, Itsn2, and double mutant mice. While invertebrate mutants showed severe synaptic abnormalities, basal synaptic transmission and plasticity were unaffected at Schaffer CA1 synapses in mutant mice. Surprisingly, intercortical tracts—corpus callosum, ventral hippocampal, and anterior commissures—failed to cross the midline in mice lacking Itsn1, but not Itsn2. In contrast, tracts extending within hemispheres and those that decussate to more caudal brain segments appeared normal. Itsn1 mutant mice showed severe deficits in Morris water maze and contextual fear memory tasks, whereas mice lacking Itsn2 showed normal learning and memory. Thus, coincident with the acquisition of additional signaling domains, vertebrate Itsn1 has been functionally repurposed to also facilitate interhemispheric connectivity essential for high order cognitive functions.
EF-1α DNA Sequences Indicate Multiple Origins of Introduced Populations of Essigella californica (Hemiptera: Aphididae)

Abstract Aphids in the pine-feeding Nearctic genus Essigella (Sternorrhyncha, Aphididae, Lachninae) have been introduced in Europe, North Africa, Oceania, and South America. Mitochondrial, nuclear, and endosymbiont DNA sequences of 12 introduced populations from three continents confirm they all belong to Essigella californica (Essig, 1909). Intron sequence variation of the nuclear gene EF-1α has revealed the existence of four distinct groups. Group I gathers one population from China, where the species is newly reported, and several from Europe (France and Italy); Group II is represented by one population from Argentina; Group III includes two populations from Southern Australia with one from New Zealand; and Group IV corresponds to five populations from Eastern and South-Eastern Australia. These results indicate that introduced populations of E. californica have at least four source populations. They also show that intron variation of EF-1α can be a method to discriminate populations of asexually reproducing aphids.
Associations between Social and Physical Environments, and Physical Activity in Adults from Urban and Rural Regions

Objectives This study investigates investigated the relationship between social and physical environments, and moderate to vigorous physical activity (MVPA) amongst adults in both rural and urban areas within Korea. Methods A sample of 128,735 adults from the 2013 Community Health Survey (CHS) was analyzed using a multilevel logistic analysis. Results Urban residents with higher satisfaction in public transportation satisfaction and rural residents with more access to sports parks, hiking trails, and bike cycle paths were more likely to be active. The MVPA of adults from rural areas correlated urban adults was uncorrelatedwith neighborhood factors, but that of rural adults was whereas no correlations were observed in adults from urban areas. Conclusion These differences should be considered when developing interventions strategies to enhance adult physical activity in different communities.
Evaluation of the Complex Nomenclature of the Clinically and Veterinary Significant Pathogen Salmonella

Salmonella encompasses a vast and highly related population of clinically and veterinary significant pathogens. The genus is responsible for an array of diseases such as typhoid fever and salmonellosis (a variety of illnesses including gastroenteritis), which cause public health issues globally. Even with the global recognition of Salmonella as a significant human and veterinary pathogen, the highly complex and evolving nomenclature system of Salmonella is problematic for clinicians, veterinarians, and microbiologists to comprehend. The present paper offers a review of the ever developing nomenclature for this bacterial species.
High-throughput and Sensitive Immunopeptidomics Platform Reveals Profound Interferonγ-Mediated Remodeling of the Human Leukocyte Antigen (HLA) Ligandome

Comprehensive knowledge of the human leukocyte antigen (HLA) class-I and class-II peptides presented to T-cells is crucial for designing innovative therapeutics against cancer and other diseases. However methodologies for their purification for mass-spectrometry analysis have been a major limitation. We designed a novel high-throughput, reproducible and sensitive method for sequential immuno-affinity purification of HLA-I and -II peptides from up to 96 samples in a plate format, suitable for both cell lines and tissues. Our methodology drastically reduces sample-handling and can be completed within five hours. We challenged our methodology by extracting HLA peptides from multiple replicates of tissues (n = 7) and cell lines (n = 21, 108 cells per replicate), which resulted in unprecedented depth, sensitivity and high reproducibility (Pearson correlations up to 0.98 and 0.97 for HLA-I and HLA-II). Because of the method's achieved sensitivity, even single measurements of peptides purified from 107 B-cells resulted in the identification of more than 1700 HLA-I and 2200 HLA-II peptides. We demonstrate the feasibility of performing drug-screening by using ovarian cancer cells treated with interferon gamma (IFNγ). Our analysis revealed an augmented presentation of chymotryptic-like and longer ligands associated with IFNγ induced changes of the antigen processing and presentation machinery. This straightforward method is applicable for basic and clinical applications.
Automatic speaker analysis 2.0: Hearing the bigger picture

Automatic Speaker Analysis has largely focused on single aspects of a speaker such as her ID, gender, emotion, personality, or health state. This broadly ignores the interdependency of all the different states and traits impacting on the one single voice production mechanism available to a human speaker. In other words, sometimes we may sound depressed, but we simply have a flu, and hardly find the energy to put more vocal effort into our articulation and sound production. Recently, this lack gave rise to an increasingly holistic speaker analysis — assessing the ‘larger picture’ in one pass such as by multi-target learning. However, for a robust assessment, this requires large amount of speech and language resources labelled in rich ways to train such interdependency, and architectures able to cope with multi-target learning of massive amounts of speech data. In this light, this contribution will discuss efficient mechanisms such as large socialmedia pre-scanning with dynamic cooperative crowd-sourcing for rapid data collection, cross-task-labelling of these data in a wider range of attributes to reach ‘big & rich’ speech data, and efficient multi-target end-to-end and end-to-evolution deep learning paradigms to learn an accordingly rich representation of diverse target tasks in efficient ways. The ultimate goal behind is to enable machines to hear the ‘entire’ person and her condition and whereabouts behind the voice and words — rather than aiming at a single aspect blind to the overall individual and its state, thus leading to the next level of Automatic Speaker Analysis.
The 24-2 Visual Field Test Misses Central Macular Damage Confirmed by the 10-2 Visual Field Test and Optical Coherence Tomography

Purpose To determine the extent to which the 24-2 visual field (VF) misses macular damage confirmed with both 10-2 VF and optical coherence tomography (OCT) tests and to evaluate the patterns of damage missed. Methods One hundred forty-one eyes of 141 glaucoma patients or suspects underwent 24-2 VF (mean deviation [MD] better than −6 dB), 10-2 VF, and OCT testing. Retinal nerve fiber layer (RNFL) and retinal ganglion cell plus inner plexiform (RGC+) probability plots were combined with 10-2 VF probability plots. Eyes were classified as “abnormal macula” if abnormal regions on both the 10-2 VF and OCT plots agreed. The number of abnormal eyes missed (i.e., false negatives) was determined for the following 24-2 VF metrics: MD; pattern standard deviation (PSD); glaucoma hemifield test (GHT); cluster criteria (CC); and abnormal points within ± 10°. Eyes that were missed on one or more of the 24-2 metrics were classified by damage type based upon circumpapillary RNFL thickness plots. Results Fifty-nine (41.8%) eyes were classified as “abnormal macula,” and comprised the reference standard. Of the 59, 31 (52.5%) were missed by one or more of the 24-2 metrics. The individual 24-2 metrics missed between 7 (CC) and 20 (MD) eyes. The eyes missed had widespread macular damage, as well as both shallow and deep local defects. Conclusions Eyes with macular glaucomatous damage may be classified as normal based on the 24-2 VF alone. Translational Relevance To detect macular damage with perimetry, the 10-2 VF test (or a modified 24-2 VF test) is essential.
Driver's movement monitoring system using capacitive ECG sensors

This paper proposes a method to monitor driver's movement using capacitive electrocardiogram (ECG) sensors. The sensor measures ECG by sensing voltage changes in our body, and voltage changes according to the movement of the body also can be measured by the sensor. The proposed method uses independent component analysis to decompose the signal component related to the body movement in the measured signals. In experiments, the signal component by the proposed method was compared with a true signal that represents the movement of a driver, and an averaged correlation coefficient value between the two signals was 0.77. The result shows that the proposed method can give information on the movement of a driver using capacitive ECG sensors, and the information can be utilized to various driver's condition monitoring systems.
Mixed-Resolution Image Representation and Compression with Convolutional Neural Networks

In this paper, we propose a end-to-end mixed-resolution image compression framework with convolutional neural networks. Firstly, given one input image, feature description neural network (FDNN) is used to generate a new representation of this image, so that this representation can be more efficiently compressed by standard coder, as compared to the input image. Furthermore, we use post-processing neural network (PPNN) to remove the coding artifacts caused by quantization of codec. Secondly, low-resolution representation is considered under low bit-rate for high efficiency compression in terms of most of bit spent by image's structures. However, more bits should be assigned to image details in the high-resolution, when most of structures have been kept after compression at the high bit-rate. This comes from that the low-resolution representation can't burden more information than high-resolution representation beyond a certain bit-rate. Finally, to resolve the problem of error back-propagation from the PPNN network to the FDNN network, we introduce a virtual codec neural network to intimate the procedure of standard compression and post-processing. The objective experimental results have demonstrated the proposed method has a large margin improvement, when comparing with several state-of-the-art approaches.
The evolution of duplicate gene expression in mammalian organs

Gene duplications generate genomic raw material that allows the emergence of novel functions, likely facilitating adaptive evolutionary innovations. However, global assessments of the functional and evolutionary relevance of duplicate genes in mammals were until recently limited by the lack of appropriate comparative data. Here, we report a large-scale study of the expression evolution of DNA-based functional gene duplicates in three major mammalian lineages (placental mammals, marsupials, egg-laying monotremes) and birds, on the basis of RNA sequencing (RNA-seq) data from nine species and eight organs. We observe dynamic changes in tissue expression preference of paralogs with different duplication ages, suggesting differential contribution of paralogs to specific organ functions during vertebrate evolution. Specifically, we show that paralogs that emerged in the common ancestor of bony vertebrates are enriched for genes with brain-specific expression and provide evidence for differential forces underlying the preferential emergence of young testis- and liver-specific expressed genes. Further analyses uncovered that the overall spatial expression profiles of gene families tend to be conserved, with several exceptions of pronounced tissue specificity shifts among lineage-specific gene family expansions. Finally, we trace new lineage-specific genes that may have contributed to the specific biology of mammalian organs, including the little-studied placenta. Overall, our study provides novel and taxonomically broad evidence for the differential contribution of duplicate genes to tissue-specific transcriptomes and for their importance for the phenotypic evolution of vertebrates.
Pharmacogenomics of Chemically Distinct Classes of Keap1-Nrf2 Activators Identify Common and Unique Gene, Protein, and Pathway Responses In Vivo

The Kelch-like erythroid-associated protein 1 (Keap1)–NF-E2-related factor 2 (Nrf2) signaling pathway is the subject of several clinical trials evaluating the effects of Nrf2 activation on the prevention of cancer and diabetes and the treatment of chronic kidney disease and multiple sclerosis. 3H-1,2-dithiole-3-thione (D3T) and 1-[2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oyl]imidazole (CDDO-Im) are representative members of two distinct series of Nrf2 chemical activators. Previous reports have described activator-specific effects on Nrf2-dependent gene regulation and physiologic outcomes. Here we used a robust chemical genomics approach to characterize expression profiles between D3T and CDDO-Im in livers from wild-type and Nrf2-null mice. At equally efficacious doses in wild-type mice, 406 genes show common RNA responses to both treatments. These genes enriched the Nrf2-regulated pathways of antioxidant defense and xenobiotic metabolism. In addition, 197 and 745 genes were regulated uniquely in response to either D3T or CDDO-Im, respectively. Functional analysis of the D3T-regulated set showed a significant enrichment of Nrf2-regulated enzymes involved in cholesterol biosynthesis. This result was supported by Nrf2-dependent increases in lanosterol synthase and CYP51 protein expression. CDDO-Im had no effect on cholesterol biosynthesis regardless of the dose tested. However, unlike D3T, CDDO-Im resulted in Nrf2-dependent elevation of peroxisome proliferator α and Kruppel-like factor 13, as well as the coactivator peroxisome proliferator γ coactivator 1β, together indicating regulation of β-oxidation and lipid metabolic pathways. These findings provide novel insights into the pharmacodynamic action of these two activators of Keap1-Nrf2 signaling. Although both compounds modify Keap1 to affect canonical cytoprotective gene expression, additional unique sets of Nrf2-dependent genes were regulated by each agent with enrichment of selective metabolic pathways.
Development of novel ultrashort antimicrobial peptide nanoparticles with potent antimicrobial and antibiofilm activities against multidrug-resistant bacteria

Conventional antibiotics are facing strong microbial resistance that has recently reached critical levels. This situation is leading to significantly reduced therapeutic potential of a huge proportion of antimicrobial agents currently used in clinical settings. Antimicrobial peptides (AMPs) could provide the medical community with an alternative strategy to traditional antibiotics for combating microbial resistance. However, the development of AMPs into clinically useful antibiotics is hampered by their relatively low stability, toxicity, and high manufacturing costs. In this study, a novel in-house-designed potent ultrashort AMP named RBRBR was encapsulated into chitosan-based nanoparticles (CS-NPs) based on the ionotropic gelation method. The encapsulation efficacy reported for RBRBR into CS-NPs was 51.33%, with a loading capacity of 10.17%. The release kinetics of RBRBR from the nanocarrier exhibited slow release followed by progressive linear release for 14 days. The antibacterial kinetics of RBRBR-CS-NPs was tested against four strains of Staphylococcus aureus for 4 days, and the developed RBRBR-CS-NPs exhibited a 3-log decrease in the number of colonies when compared to CS-NP and a 5-log decrease when compared to control bacteria. The encapsulated peptide NP formulation managed to limit the toxicity of the free peptide against both mammalian cells and human erythrocytes. Additionally, the peptide NPs demonstrated up to 98% inhibition of biofilm formation when tested against biofilm-forming bacteria. Loading RBRBR into CS-NPs could represent an innovative approach to develop delivery systems based on NP technology for achieving potent antimicrobial effects against multidrug-resistant and biofilm-forming bacteria, with negligible systemic toxicity and reduced synthetic costs, thereby overcoming the obstructions to clinical development of AMPs.
CK1ε Is Required for Breast Cancers Dependent on β-Catenin Activity

Background Aberrant β-catenin signaling plays a key role in several cancer types, notably colon, liver and breast cancer. However approaches to modulate β-catenin activity for therapeutic purposes have proven elusive to date. Methodology To uncover genetic dependencies in breast cancer cells that harbor active β-catenin signaling, we performed RNAi-based loss-of-function screens in breast cancer cell lines in which we had characterized β-catenin activity. Here we identify CSNK1E, the gene encoding casein kinase 1 epsilon (CK1ε) as required specifically for the proliferation of breast cancer cells with activated β-catenin and confirm its role as a positive regulator of β-catenin-driven transcription. Furthermore, we demonstrate that breast cancer cells that harbor activated β-catenin activity exhibit enhanced sensitivity to pharmacological blockade of Wnt/β-catenin signaling. We also find that expression of CK1ε is able to promote oncogenic transformation of human cells in a β-catenin-dependent manner. Conclusions/Significance These studies identify CK1ε as a critical contributor to activated β-catenin signaling in cancer and suggest it may provide a potential therapeutic target for cancers that harbor active β-catenin. More generally, these observations delineate an approach that can be used to identify druggable synthetic lethal interactions with signaling pathways that are frequently activated in cancer but are difficult to target with the currently available small molecule inhibitors.