Impact of Constraint Conditions and Cutouts on Natural Frequency of Glass Fiber Reinforced Plastic Composite

Majority of the activities of a human being is associated with vibrations of one or other form. Application of vibrations can be found from a simple example like listening to music to challenging ones like design of complex machines and structures. Design of any system will not be rugged if it does not consider vibrations and its effects. The energy dissipated per cycle can be understood as damping. Presence of damping in a structure is represented by damping factor or damping ratio. Fibre reinforced plastic composites are a class of materials made from matrix and reinforcement. Matrix can be a resin system and reinforcement is usually fabric made of glass, carbon or aramid. The vibrating mechanical system causes resonance resulting in failure of machine components. By knowing the natural frequency and changing it from the range of operating machine member, resonance phenomenon could be avoided. This work focuses on finding the damping ratio and natural frequency of s glass fibre reinforced polymer composites through harmonic & modal analysis both by experimental method and FEM analysis for bare plate, plate with rectangular cutouts and plate with circular hole. The reduction in natural frequency and increase in damping corresponds to a change in stiffness and damping of the system. These changes are attributed to freeness of the system and introduction of cutouts in the laminate

Machine Learning, Quantum Mechanics, and Chemical Compound Space

We review recent studies dealing with the generation of machine learning models of molecular and solid properties. The models are trained and validated using standard quantum chemistry results obtained for organic molecules and materials selected from chemical space at random

Large Scale Immune Profiling of Infected Humans and Goats Reveals Differential Recognition of Brucella melitensis Antigens

Brucellosis is a widespread zoonotic disease that is also a potential agent of bioterrorism. Current serological assays to diagnose human brucellosis in clinical settings are based on detection of agglutinating anti-LPS antibodies. To better understand the universe of antibody responses that develop after B. melitensis infection, a protein microarray was fabricated containing 1,406 predicted B. melitensis proteins. The array was probed with sera from experimentally infected goats and naturally infected humans from an endemic region in Peru. The assay identified 18 antigens differentially recognized by infected and non-infected goats, and 13 serodiagnostic antigens that differentiate human patients proven to have acute brucellosis from syndromically similar patients. There were 31 cross-reactive antigens in healthy goats and 20 cross-reactive antigens in healthy humans. Only two of the serodiagnostic antigens and eight of the cross-reactive antigens overlap between humans and goats. Based on these results, a nitrocellulose line blot containing the human serodiagnostic antigens was fabricated and applied in a simple assay that validated the accuracy of the protein microarray results in the diagnosis of humans. These data demonstrate that an experimentally infected natural reservoir host produces a fundamentally different immune response than a naturally infected accidental human host

Computational design of syntheses leading to compound libraries or isotopically labelled targets

Although computer programs for retrosynthetic planning have shown improved and in some cases quite satisfactory performance in designing routes leading to specific, individual targets, no algorithms capable of planning syntheses of entire target libraries - important in modern drug discovery - have yet been reported. This study describes how network-search routines underlying existing retrosynthetic programs can be adapted and extended to multi-target design operating on one common search graph, benefitting from the use of common intermediates and reducing the overall synthetic cost. Implementation in the Chematica platform illustrates the usefulness of such algorithms in the syntheses of either (i) all members of a user-defined library, or (ii) the most synthetically accessible members of this library. In the latter case, algorithms are also readily adapted to the identification of the most facile syntheses of isotopically labelled targets. These examples are industrially relevant in the context of hitto-lead optimization and syntheses of isotopomers of various bioactive molecules

Sarcoidosis activates diverse transcriptional programs in bronchoalveolar lavage cells

Abstract Background Sarcoidosis is a multisystem immuno-inflammatory disorder of unknown etiology that most commonly involves the lungs. We hypothesized that an unbiased approach to identify pathways activated in bronchoalveolar lavage (BAL) cells can shed light on the pathogenesis of this complex disease. Methods We recruited 15 patients with various stages of sarcoidosis and 12 healthy controls. All subjects underwent bronchoscopy with lavage. For each subject, total RNA was extracted from BAL cells and hybridized to an Affymetrix U133A microarray. Rigorous statistical methods were applied to identify differential gene expression between subjects with sarcoidosis vs. controls. To better elucidate pathways differentially activated between these groups, we integrated network and gene set enrichment analyses of BAL cell transcriptional profiles. Results Sarcoidosis patients were either non-smokers or former smokers, all had lung involvement and only two were on systemic prednisone. Healthy controls were all non-smokers. Comparison of BAL cell gene expression between sarcoidosis and healthy subjects revealed over 1500 differentially expressed genes. Several previously described immune mediators, such as interferon gamma, were upregulated in the sarcoidosis subjects. Using an integrative computational approach we constructed a modular network of over 80 gene sets that were highly enriched in patients with sarcoidosis. Many of these pathways mapped to inflammatory and immune-related processes including adaptive immunity, T-cell signaling, graft vs. host disease, interleukin 12, 23 and 17 signaling. Additionally, we uncovered a close association between the proteasome machinery and adaptive immunity, highlighting a potentially important and targetable relationship in the pathobiology of sarcoidosis. Conclusions BAL cells in sarcoidosis are characterized by enrichment of distinct transcriptional programs involved in immunity and proteasomal processes. Our findings add to the growing evidence implicating alveolar resident immune effector cells in the pathogenesis of sarcoidosis and identify specific pathways whose activation may modulate disease progression

Mir-132/212 is required for maturation of binocular matching of orientation preference and depth perception

MicroRNAs (miRNAs) are known to mediate post-transcriptional gene regulation, but their role in postnatal brain development is still poorly explored. We show that the expression of many miRNAs is dramatically regulated during functional maturation of the mouse visual cortex with miR-132/212 family being one of the top upregulated miRNAs. Age-downregulated transcripts are significantly enriched in miR-132/miR-212 putative targets and in genes upregulated in miR-132/212 null mice. At a functional level, miR-132/212 deletion affects development of receptive fields of cortical neurons determining a specific impairment of binocular matching of orientation preference, but leaving orientation and direction selectivity unaltered. This deficit is associated with reduced depth perception in the visual cliff test. Deletion of miR-132/212 from forebrain excitatory neurons replicates the binocular matching deficits. Thus, miR-132/212 family shapes the age-dependent transcriptome of the visual cortex during a specific developmental window resulting in maturation of binocular cortical cells and depth perception

Serological Profiling of a Candida albicans Protein Microarray Reveals Permanent Host-Pathogen Interplay and Stage-Specific Responses during Candidemia

Candida albicans in the immunocompetent host is a benign member of the human microbiota. Though, when host physiology is disrupted, this commensal-host interaction can degenerate and lead to an opportunistic infection. Relatively little is known regarding the dynamics of C. albicans colonization and pathogenesis. We developed a C. albicans cell surface protein microarray to profile the immunoglobulin G response during commensal colonization and candidemia. The antibody response from the sera of patients with candidemia and our negative control groups indicate that the immunocompetent host exists in permanent host-pathogen interplay with commensal C. albicans. This report also identifies cell surface antigens that are specific to different phases (i.e. acute, early and mid convalescence) of candidemia. We identified a set of thirteen cell surface antigens capable of distinguishing acute candidemia from healthy individuals and uninfected hospital patients with commensal colonization. Interestingly, a large proportion of these cell surface antigens are involved in either oxidative stress or drug resistance. In addition, we identified 33 antigenic proteins that are enriched in convalescent sera of the candidemia patients. Intriguingly, we found within this subset an increase in antigens associated with heme-associated iron acquisition. These findings have important implications for the mechanisms of C. albicans colonization as well as the development of systemic infection

Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?

As machine learning/artificial intelligence algorithms are defeating chess masters and, most recently, GO champions, there is interest -and hope -that they will prove equally useful in assisting chemists in predicting outcomes of organic reactions. This paper demonstrates, however, that the applicability of machine learning to the problems of chemical reactivity over diverse types of chemistries remains limited -in particular, with the currently available chemical descriptors, fundamental mathematical theorems impose upper bounds on the accuracy with which raction yields and times can be predicted. Improving the performance of machine-learning methods calls for the development of fundamentally new chemical descriptors

The molecular response of the white-rot fungus Dichomitus squalens to wood and non-woody biomass as examined by transcriptome and exoproteome analyses

The ability to obtain carbon and energy is a major requirement to exist in any environment. For several ascomycete fungi, (post-)genomic analyses have shown that species that occupy a large variety of habitats possess a diverse enzymatic machinery, while species with a specific habitat have a more focused enzyme repertoire that is well-adapted to the prevailing substrate. White-rot basidiomycete fungi also live in a specific habitat, as they are found exclusively in wood. In this study, we evaluated how well the enzymatic machinery of the white-rot fungus Dichomitus squalens is tailored to degrade its natural wood substrate. The transcriptome and exoproteome of D. squalens were analyzed after cultivation on two natural substrates, aspen and spruce wood, and two non-woody substrates, wheat bran and cotton seed hulls. D. squalens produced ligninolytic enzymes mainly at the early time point of the wood cultures, indicating the need to degrade lignin to get access to wood polysaccharides. Surprisingly, the response of the fungus to the non-woody polysaccharides was nearly as good a match to the substrate composition as observed for the wood polysaccharides. This indicates that D. squalens has preserved its ability to efficiently degrade plant biomass types not present in its natural habitat.Peer reviewe