1,144 research outputs found

    The Possibility of Contamination of Deep Frozen Bull Semen During Long Periods of Storage in Containers with Liquid Nitrogen

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    Preservation of bull sperm by deep freeze is a technological process that allows you to store semen in theory for an unlimited period of time, national and international transport, without significant loss of quality and safety of semen. According to the literature, some microorganisms successfully survive the low temperatures during storage of semen in liquid nitrogen (-196 ° C), in deep-frozen semen, seeds, and in liquid nitrogen and ice sediment in the storage container for deep-frozen bull semen. The aim of this study was to do microbiological analysis of samples semen frozen bull and liquid nitrogen in containers for bull semen storage. 414 samples of frozen bull semen, and 53 samples of liquid nitrogen ice sediment were examined. From the deeply frozen semen were isolated Candida albicans, Citrobacter freundii and Pseudomonas stutzeri. Microorganisms isolated from the storage container of frozen semen are mostly members of the family Enterobacteriacae, and Citrobacter freundii was isolated from the largest number of samples. Considering the findings of microorganisms in the semen, and liquid nitrogen, there is the possibility of connection of contamination of the semen with microorganisms of the liquid nitrogen, and reversely, as would be the goal of our future investigations

    Context-sensitive dynamic ordinal regression for intensity estimation of facial action units

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    Modeling intensity of facial action units from spontaneously displayed facial expressions is challenging mainly because of high variability in subject-specific facial expressiveness, head-movements, illumination changes, etc. These factors make the target problem highly context-sensitive. However, existing methods usually ignore this context-sensitivity of the target problem. We propose a novel Conditional Ordinal Random Field (CORF) model for context-sensitive modeling of the facial action unit intensity, where the W5+ (who, when, what, where, why and how) definition of the context is used. While the proposed model is general enough to handle all six context questions, in this paper we focus on the context questions: who (the observed subject), how (the changes in facial expressions), and when (the timing of facial expressions and their intensity). The context questions who and howare modeled by means of the newly introduced context-dependent covariate effects, and the context question when is modeled in terms of temporal correlation between the ordinal outputs, i.e., intensity levels of action units. We also introduce a weighted softmax-margin learning of CRFs from data with skewed distribution of the intensity levels, which is commonly encountered in spontaneous facial data. The proposed model is evaluated on intensity estimation of pain and facial action units using two recently published datasets (UNBC Shoulder Pain and DISFA) of spontaneously displayed facial expressions. Our experiments show that the proposed model performs significantly better on the target tasks compared to the state-of-the-art approaches. Furthermore, compared to traditional learning of CRFs, we show that the proposed weighted learning results in more robust parameter estimation from the imbalanced intensity data

    A Splicing Mutation in the Novel Mitochondrial Protein DNAJC11 Causes Motor Neuron Pathology Associated with Cristae Disorganization, and Lymphoid Abnormalities in Mice

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    Mitochondrial structure and function is emerging as a major contributor to neuromuscular disease, highlighting the need for the complete elucidation of the underlying molecular and pathophysiological mechanisms. Following a forward genetics approach with N-ethyl-N-nitrosourea (ENU)-mediated random mutagenesis, we identified a novel mouse model of autosomal recessive neuromuscular disease caused by a splice-site hypomorphic mutation in a novel gene of unknown function, DnaJC11. Recent findings have demonstrated that DNAJC11 protein co-immunoprecipitates with proteins of the mitochondrial contact site (MICOS) complex involved in the formation of mitochondrial cristae and cristae junctions. Homozygous mutant mice developed locomotion defects, muscle weakness, spasticity, limb tremor, leucopenia, thymic and splenic hypoplasia, general wasting and early lethality. Neuropathological analysis showed severe vacuolation of the motor neurons in the spinal cord, originating from dilatations of the endoplasmic reticulum and notably from mitochondria that had lost their proper inner membrane organization. The causal role of the identified mutation in DnaJC11 was verified in rescue experiments by overexpressing the human ortholog. The full length 63 kDa isoform of human DNAJC11 was shown to localize in the periphery of the mitochondrial outer membrane whereas putative additional isoforms displayed differential submitochondrial localization. Moreover, we showed that DNAJC11 is assembled in a high molecular weight complex, similarly to mitofilin and that downregulation of mitofilin or SAM50 affected the levels of DNAJC11 in HeLa cells. Our findings provide the first mouse mutant for a putative MICOS protein and establish a link between DNAJC11 and neuromuscular diseases

    Thermal Behavior of Monocrystalline Silicon Solar Cells: A Numerical and Experimental Investigation on the Module Encapsulation Materials

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    This research outlines the numerical predictions of the heat distribution in solar cells, accompanied by their empirical validation. Finite element thermal models of five laminated silicon solar photovoltaic cells were firstly established using a simulation software (ANSYS®). The flexible laminated solar cells under study are made of a highly transparent frontsheet, a silicon cell between two encapsulants, and a backsheet. Different combinations of layers (i.e., materials and thicknesses) were taken into account in order to analyze their effect on thermal behavior. Thermal properties of materials were derived in accordance with the literature. Similarly, boundary conditions, loads, and heat losses by reflection and convection were also specified. The solar cells were tested using solar lamps under standard conditions (irradiance: 1000W/m2; room-temperature: 25°C) with real-time temperatures measured by a thermal imager. This analysis offers an interpretation of how temperature evolves through the solar cell and, consequently, how the design choice can influence the cells' efficiency

    Influence of Altitude on Phytochemical Composition of Hemp Inflorescence: A Metabolomic Approach

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    The phytochemical profiling of hemp inflorescences of clonal plants growing in different conditions related to altitude was investigated. Four strains of industrial hemp (Cannabis sativa L., family Cannabaceae) of Kompolti variety were selected and cloned to provide genetically uniform material for analyses of secondary metabolites (terpenes, cannabinoids, and flavonoids) at two different elevations: mountain (Alagna Valsesia 1200 m ASL) and plains (Vercelli Province 130 m ASL). Environmental conditions influenced by elevation have proven to be important factors inducing variations in hemp inflorescences\u2019 secondary metabolite composition. In fact, all plants grown at altitude exhibited a higher total amount of terpenes when compared with plains counterparts, with \u3b2-Myrcene, trans-Caryophyllene and \u3b1-Humulene as the main contributors. A metabolomic, un-targeted approach performed by HPLC-Q-Exactive-Orbitrap\uae-MS platform with subsequent data processing performed by Compound DiscovererTM software, was crucial for the appropriate recognition of many metabolites, clearly distinguishing mountain from plains specimens. Cannabidiolic acid CBDA was the most abundant phytocannabinoid, with significantly higher concentrations in the mountain samples. The metabolic pathway of CBGA (considered as the progenitor/precursor of all cannabinoids) was also activated towards the production of CBCA, which occurs in considerably 3 times higher quantities than in the clones grown at high altitude. Isoprenoid flavones (Cannaflavins A, B, and C) were correspondingly upregulated in mountain samples, while apigenin turned out to be more abundant in plains samples. The possibility to use hemp inflorescences in pharmaceutical/nutraceutical applications opens new challenges to understand how hemp crops respond in terms of secondary metabolite production in various environments. In this regard, our results with the applied analytical strategy may constitute an effective way of phytochemical profiling hemp inflorescences

    Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity

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    Joint modeling of the intensity of facial action units (AUs) from face images is challenging due to the large number of AUs (30+) and their intensity levels (6). This is in part due to the lack of suitable models that can efficiently handle such a large number of outputs/classes simultaneously, but also due to the lack of labelled target data. For this reason, majority of the methods proposed so far resort to independent classifiers for the AU intensity. This is suboptimal for at least two reasons: the facial appearance of some AUs changes depending on the intensity of other AUs, and some AUs co-occur more often than others. Encoding this is expected to improve the estimation of target AU intensities, especially in the case of noisy image features, head-pose variations and imbalanced training data. To this end, we introduce a novel modeling framework, Copula Ordinal Regression (COR), that leverages the power of copula functions and CRFs, to detangle the probabilistic modeling of AU dependencies from the marginal modeling of the AU intensity. Consequently, the COR model achieves the joint learning and inference of intensities of multiple AUs, while being computationally tractable. We show on two challenging datasets of naturalistic facial expressions that the proposed approach consistently outperforms (i) independent modeling of AU intensities, and (ii) the state-ofthe-art approach for the target task

    Collisional properties of cold spin-polarized nitrogen gas: theory, experiment, and prospects as a sympathetic coolant for trapped atoms and molecules

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    We report a combined experimental and theoretical study of collision-induced dipolar relaxation in a cold spin-polarized gas of atomic nitrogen (N). We use buffer gas cooling to create trapped samples of 14N and 15N atoms with densities 5+/-2 x 10^{12} cm-3 and measure their magnetic relaxation rates at milli-Kelvin temperatures. Rigorous quantum scattering calculations based on accurate ab initio interaction potentials for the 7Sigma_u electronic state of N2 demonstrate that dipolar relaxation in N + N collisions occurs at a slow rate of ~10^{-13} cm3/s over a wide range of temperatures (1 mK to 1 K) and magnetic fields (10 mT to 2 T). The calculated dipolar relaxation rates are insensitive to small variations of the interaction potential and to the magnitude of the spin-exchange interaction, enabling the accurate calibration of the measured N atom density. We find consistency between the calculated and experimentally determined rates. Our results suggest that N atoms are promising candidates for future experiments on sympathetic cooling of molecules.Comment: 48 pages, 17 figures, 3 table
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