162 research outputs found
The effect of repeated freeze-thaw cycles on the meat quality of rabbit
[EN] We investigated the effect of repeated freeze-thaw cycles on the quality of rabbit meat. Twenty-five Hyla rabbits were slaughtered using standard commercial procedures. A freeze-thaw procedure—i.e., seven days frozen at –18°C followed by thawing at 4°C for 12h— was repeated 5 times, and 9 Longissimus thoracis et lumborum muscles were randomly selected at pre-set cycles (0, 1, 2, 3, and 5). The Longissimus lumborum muscles were used to determine meat quality parameters, while the Longissimus thoracis muscles were used for chemical analysis. During the repeated freeze-thaw process, muscle pH, redness, hardness, and water holding capacity gradually decreased, whereas meat lightness and yellowness gradually increased. The amount of total volatile basic nitrogen significantly increased (P<0.05) and exceeded the threshold value for frozen meat after 5 repeated freeze-thaw cycles. The metmyoglobin proportion, thiobarbituric acid-reactive substances (TBARS) and protein carbonyl content in rabbit meat samples increased with a higher number of freeze-thaw cycles (P<0.05), and the proportions of these compounds were positively correlated. During the repeated freeze-thaw process, extractable haeme iron levels significantly decreased (P<0.05), and non-haeme iron levels markedly increased (P<0.05). An sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis indicated that the degradation of both water- and salt-soluble proteins was more prevalent in samples subjected to higher numbers of freeze-thaw cycles. Additionally, a principal component analysis identified good correlations between physicochemical properties (TBARS, protein carbonyl levels and metmyoglobin content) and quality parameters (thawing loss, redness, lightness and hardness). Taken together, we conclude that the repeated freeze-thaw process can strongly affect rabbit meat quality as well as its physicochemical properties.The authors gratefully acknowledge financial support from the General Program of National Natural Science Foundation of China (31671787), the National Rabbit Industry Technology System Programme (Grant No. CARS-43-E-1), and the Chongqing Herbivorous Livestock Industry Technology System (Y201706).Wang, Z.; He, Z.; Gan, X.; Li, H. (2018). The effect of repeated freeze-thaw cycles on the meat quality of rabbit. World Rabbit Science. 26(2):165-177. https://doi.org/10.4995/wrs.2018.8616SWORD165177262Ali S., Rajput N., Li C.B., Zhang W., Zhou G.H. 2016. Effect of freeze-thaw cycles on lipid oxidation and myowater in broiler chickens. Revista Brasileira de CiĂŞncia AvĂcola, 18: 35-40.https://doi.org/10.1590/1516-635x1801035-040Ali S., Zhang W., Rajput N., Khan M.A., Li C.B., Zhou G.H. 2015. 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Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis
The assessment of Alzheimer's Disease (AD) and Mild Cognitive Impairment
(MCI) associated with brain changes remains a challenging task. Recent studies
have demonstrated that combination of multi-modality imaging techniques can
better reflect pathological characteristics and contribute to more accurate
diagnosis of AD and MCI. In this paper, we propose a novel tensor-based
multi-modality feature selection and regression method for diagnosis and
biomarker identification of AD and MCI from normal controls. Specifically, we
leverage the tensor structure to exploit high-level correlation information
inherent in the multi-modality data, and investigate tensor-level sparsity in
the multilinear regression model. We present the practical advantages of our
method for the analysis of ADNI data using three imaging modalities (VBM- MRI,
FDG-PET and AV45-PET) with clinical parameters of disease severity and
cognitive scores. The experimental results demonstrate the superior performance
of our proposed method against the state-of-the-art for the disease diagnosis
and the identification of disease-specific regions and modality-related
differences. The code for this work is publicly available at
https://github.com/junfish/BIOS22
A Comparison of Image Denoising Methods
The advancement of imaging devices and countless images generated everyday
pose an increasingly high demand on image denoising, which still remains a
challenging task in terms of both effectiveness and efficiency. To improve
denoising quality, numerous denoising techniques and approaches have been
proposed in the past decades, including different transforms, regularization
terms, algebraic representations and especially advanced deep neural network
(DNN) architectures. Despite their sophistication, many methods may fail to
achieve desirable results for simultaneous noise removal and fine detail
preservation. In this paper, to investigate the applicability of existing
denoising techniques, we compare a variety of denoising methods on both
synthetic and real-world datasets for different applications. We also introduce
a new dataset for benchmarking, and the evaluations are performed from four
different perspectives including quantitative metrics, visual effects, human
ratings and computational cost. Our experiments demonstrate: (i) the
effectiveness and efficiency of representative traditional denoisers for
various denoising tasks, (ii) a simple matrix-based algorithm may be able to
produce similar results compared with its tensor counterparts, and (iii) the
notable achievements of DNN models, which exhibit impressive generalization
ability and show state-of-the-art performance on various datasets. In spite of
the progress in recent years, we discuss shortcomings and possible extensions
of existing techniques. Datasets, code and results are made publicly available
and will be continuously updated at
https://github.com/ZhaomingKong/Denoising-Comparison.Comment: In this paper, we intend to collect and compare various denoising
methods to investigate their effectiveness, efficiency, applicability and
generalization ability with both synthetic and real-world experiment
Inconsistency of QED in the Presence of Dirac Monopoles
A precise formulation of local gauge invariance in QED is presented,
which clearly shows that the gauge coupling associated with the unphysical
longitudinal photon field is non-observable and actually has an arbitrary
value. We then re-examine the Dirac quantization condition and find that its
derivation involves solely the unphysical longitudinal coupling. Hence an
inconsistency inevitably arises in the presence of Dirac monopoles and this can
be considered as a theoretical evidence against their existence. An
alternative, independent proof of this conclusion is also presented.Comment: Extended and combined version, refinements added; 20 LaTex pages,
Published in Z. Phys. C65, pp.175-18
New depsidones and isoindolinones from the mangrove endophytic fungus Meyerozyma guilliermondii (HZ-Y 2 ) isolated from the South China Sea
Abstract Three new depsidones, botryorhodines E-G (1-3), and two new isoindolinones, meyeroguillines A and B (7 and 9), along with five known compounds were isolated from an endophytic fungus Meyerozyma guilliermondii, derived from the mangrove plant Kandelia obovata. Their structures were elucidated by 1D and 2D NMR spectroscopy and high resolution mass spectrometry (HREIMS). Compounds 1-6 exhibited strong α-glucosidase inhibitory activity with IC 50 values ranging from 2.1 to 13.3 μM. Moreover, kinetic studies of compounds 2 and 6 showed that both of them were noncompetitive inhibitors of α-glucosidase
Biological Synthesis of Size-Controlled Cadmium Sulfide Nanoparticles Using ImmobilizedRhodobacter sphaeroides
Size-controlled cadmium sulfide nanoparticles were successfully synthesized by immobilizedRhodobacter sphaeroidesin the study. The dynamic process that Cd2+was transported from solution into cell by livingR. sphaeroideswas characterized by transmission electron microscopy (TEM). Culture time, as an important physiological parameter forR. sphaeroidesgrowth, could significantly control the size of cadmium sulfide nanoparticles. TEM demonstrated that the average sizes of spherical cadmium sulfide nanoparticles were 2.3 ± 0.15, 6.8 ± 0.22, and 36.8 ± 0.25 nm at culture times of 36, 42, and 48 h, respectively. Also, the UV–vis and photoluminescence spectral analysis of cadmium sulfide nanoparticles were performed
Symmetry and topology in antiferromagnetic spintronics
Antiferromagnetic spintronics focuses on investigating and using
antiferromagnets as active elements in spintronics structures. Last decade
advances in relativistic spintronics led to the discovery of the staggered,
current-induced field in antiferromagnets. The corresponding N\'{e}el
spin-orbit torque allowed for efficient electrical switching of
antiferromagnetic moments and, in combination with electrical readout, for the
demonstration of experimental antiferromagnetic memory devices. In parallel,
the anomalous Hall effect was predicted and subsequently observed in
antiferromagnets. A new field of spintronics based on antiferromagnets has
emerged. We will focus here on the introduction into the most significant
discoveries which shaped the field together with a more recent spin-off
focusing on combining antiferromagnetic spintronics with topological effects,
such as antiferromagnetic topological semimetals and insulators, and the
interplay of antiferromagnetism, topology, and superconductivity in
heterostructures.Comment: Book chapte
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