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C44H54N4Mn, monoclinic, C2/c (no. 15), a = 15.315(3) Å, b = 14.259(3) Å, c = 18.118(3) Å, β = 105.252(3)°, V = 3817.1(12) Å3, Z = 8, Rgt(F) = 0.0472, wRref(F2) = 0.1287, T = 185 K.

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods.

ObjectiveMarijuana, tobacco and alcohol use are prevalent among people with HIV and may adversely affect kidney function in this population. We determined the association of use of these substances with estimated glomerular filtration rate (eGFR) among women with HIV (WWH) and women without HIV.DesignWe undertook a repeated measures study of 1043 WWH and 469 women without HIV within the United States Women's Interagency HIV Study, a multicenter, prospective cohort of HIV-seropositive and HIV-seronegative women.MethodsWe quantified substance exposures using semi-annual questionnaires. Using pooled eGFR data from 2009 to 2019, we used linear regression models with multivariable generalized estimating equations to ascertain associations between current and cumulative substance use exposures with eGFR, adjusting for sociodemographics, chronic kidney disease risk factors and HIV-related factors.ResultsMarijuana use of 1-14 days/month versus 0 days/month was associated with 3.34 ml/min per 1.73 m 2 [95% confidence interval (CI) -6.63, -0.06] lower eGFR and marijuana use of >0.02-1.6 marijuana-years versus 0-0.2 marijuana-years was associated with 3.61 ml/min per 1.73 m 2 (95% CI -5.97, -1.24) lower eGFR. Tobacco use was not independently associated with eGFR. Alcohol use of seven or more drinks/week versus no drinks/week was associated with 5.41 ml/min per 1.73 m 2 (95% CI 2.34, 8.48) higher eGFR and alcohol use of >0.7-4.27 drink-years and >4.27 drink-years versus 0-0.7 drink-years were associated with 2.85 ml/min per 1.73 m 2 (95% CI 0.55, 5.15) and 2.26 ml/min per 1.73 m 2 (95% CI 0.33, 4.20) higher eGFR, respectively.ConclusionAmong a large cohort of WWH and women without HIV, marijuana use was associated with a lower eGFR while alcohol use was associated with a higher eGFR.

A sign pattern (matrix) is a matrix whose entries are from the set {+, −, 0} and a sign vector is a vector whose entries are from the set {+, −, 0}. A sign pattern or sign vector is full if it does not contain any zero entries. The minimum rank of a sign pattern matrix A is the minimum of the ranks of the real matrices whose entries have signs equal to the corresponding entries of A. The notions of essential row sign change number and essential column sign change number are introduced for full sign patterns and condensed sign patterns. By inspecting the sign vectors realized by a list of real polynomials in one variable, a lower bound on the essential row and column sign change numbers is obtained. Using point-line confiurations on the plane, it is shown that even for full sign patterns with minimum rank 3, the essential row and column sign change numbers can differ greatly and can be much bigger than the minimum rank. Some open problems concerning square full sign patterns with large minimum ranks are discussed.

Novel composite coatings consist of Al2O3 micro-layers alternating with Au nano-layers have been prepared on TiAl-based alloy by magnetron sputtering. The results of high-temperature cyclic oxidation test at 900 °C for 200 h revealed that the multi-sealed α-Al2O3 and Au layers effectively suppress the inward diffusion of oxygen to a low level. The formed oxide scales and composite coatings are compact and free of cracks. The thermal stress is decreased owing to the increase of thermal-expansion coefficient. And the surface scratch test exhibited that the brittle/ductile laminated structure can remarkably enhance the strength and toughness in combination with improved damage resistance of the Al2O3-Au laminated composite coatings. Consequently, the oxidation and spallation resistance of TiAl-based alloy have been improved significantly.

This paper presented a methodology to assess the operation safety of the urban rail transit system by using the generalized regression neural network. By comparing the evaluated values with the graded scores of the experts, the results indicated that predictions by using the generalized regression neural network only have 5.38% averaged relative error compared with experts’ scores. Therefore, the GRNN was capable of evaluating and predicting the operation safety of the urban rail transit system.

Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood.

Wearable sensors hold great potential in empowering personalized health monitoring, predictive analytics, and timely intervention toward personalized healthcare. Advances in flexible electronics, materials science, and electrochemistry have spurred the development of wearable sweat sensors that enable the continuous and noninvasive screening of analytes indicative of health status. Existing major challenges in wearable sensors include: improving the sweat extraction and sweat sensing capabilities, improving the form factor of the wearable device for minimal discomfort and reliable measurements when worn, and understanding the clinical value of sweat analytes toward biomarker discovery. This review provides a comprehensive review of wearable sweat sensors and outlines state-of-the-art technologies and research that strive to bridge these gaps. The physiology of sweat, materials, biosensing mechanisms and advances, and approaches for sweat induction and sampling are introduced. Additionally, design considerations for the system-level development of wearable sweat sensing devices, spanning from strategies for prolonged sweat extraction to efficient powering of wearables, are discussed. Furthermore, the applications, data analytics, commercialization efforts, challenges, and prospects of wearable sweat sensors for precision medicine are discussed.