Supporting Regularized Logistic Regression Privately and Efficiently

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Increasing concerns over data privacy make it more and more difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used machine learning model in various disciplines while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluation on several studies validated the privacy guarantees, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc

Auxin response factor 6A regulates photosynthesis, sugar accumulation, and fruit development in tomato.

Auxin response factors (ARFs) are involved in auxin-mediated transcriptional regulation in plants. In this study, we performed functional characterization of SlARF6A in tomato. SlARF6A is located in the nucleus and exhibits transcriptional activator activity. Overexpression of SlARF6A increased chlorophyll contents in the fruits and leaves of tomato plants, whereas downregulation of SlARF6A decreased chlorophyll contents compared with those of wild-type (WT) plants. Analysis of chloroplasts using transmission electron microscopy indicated increased sizes of chloroplasts in SlARF6A-overexpressing plants and decreased numbers of chloroplasts in SlARF6A-downregulated plants. Overexpression of SlARF6A increased the photosynthesis rate and accumulation of starch and soluble sugars, whereas knockdown of SlARF6A resulted in opposite phenotypes in tomato leaves and fruits. RNA-sequence analysis showed that regulation of SlARF6A expression altered the expression of genes involved in chlorophyll metabolism, photosynthesis and sugar metabolism. SlARF6A directly bound to the promoters of SlGLK1, CAB, and RbcS genes and positively regulated the expression of these genes. Overexpression of SlARF6A also inhibited fruit ripening and ethylene production, whereas downregulation of SlARF6A increased fruit ripening and ethylene production. SlARF6A directly bound to the SAMS1 promoter and negatively regulated SAMS1 expression. Taken together, these results expand our understanding of ARFs with regard to photosynthesis, sugar accumulation and fruit development and provide a potential target for genetic engineering to improve fruit nutrition in horticulture crops

λϕ4\lambda\phi^4 model and Higgs mass in standard model calculated by Gaussian effective potential approach with a new regularization-renormalization method

Basing on new regularization-renormalization method, the $\lambda\phi^4$ model used in standard model is studied both perturbatively and nonperturbatively (by Gaussian effective potential). The invariant property of two mass scales is stressed and the existence of a (Landau) pole is emphasized. Then after coupling with the SU(2)$\times$U(1) gauge fields, the Higgs mass in standard model (SM) can be calculated as $m_H\approx$138GeV. The critical temperature ($T_c$) for restoration of symmetry of Higgs field, the critical energy scale ($\mu_c$, the maximum energy scale under which the lower excitation sector of the GEP is valid) and the maximum energy scale ($\mu_{max}$, at which the symmetry of the Higgs field is restored) in the standard model are $T_c\approx$476 GeV, $\mu_c\approx 0.547\times 10^{15}$GeV and $\mu_{\max}\approx 0.873 \times 10^{15}$ GeVv respectively.Comment: 12 pages, LaTex, no figur

The Effect of Raw Soybean on Oxidative Status of Digestive Organs in Mice

The present study was undertaken to specify the effect of raw soybean on oxidative status of digestive organs in mice. For this purpose, thirty male (C57BL/6J) mice were randomly divided into three groups and fed on different diets as follows: Group 1 was fed on control diet, Group 2 was fed on raw soybean diet and Group 3 was fed on raw soybean diet supplemented with 30 mg/kg cysteamine. After two weeks of feeding, duodenum, liver and pancreas samples were collected to measure oxidative and antioxidative parameters. The results show that ingestion of raw soybean markedly increased contents of superoxide anion and malondialdehyde (MDA) and activity of inducible nitric oxide synthase (iNOS), decreased activity of superoxide dismutase (SOD), T-AOC and content of reduced glutathione (GSH) in digestive organs of mice (P < 0.05). In the group fed with raw soybean diet supplemented with cysteamine, oxidative stress was mitigated. However, oxidative parameter levels were still higher than those of control diet-fed group. The present study indicates that ingestion of raw soybean could result in an imbalance between oxidant and antioxidant, and thus induce oxidative stress in digestive organs of mice

Global genetic diversity, introgression, and evolutionary adaptation of indicine cattle revealed by whole genome sequencing

Indicine cattle, also referred to as zebu (Bos taurus indicus), play a central role in pastoral communities across a wide range of agro-ecosystems, from extremely hot semiarid regions to hot humid tropical regions. However, their adaptive genetic changes following their dispersal into East Asia from the Indian subcontinent have remained poorly documented. Here, we characterize their global genetic diversity using high-quality whole-genome sequencing data from 354 indicine cattle of 57 breeds/populations, including major indicine phylogeographic groups worldwide. We reveal their probable migration into East Asia was along a coastal route rather than inland routes and we detected introgression from other bovine species. Genomic regions carrying morphology-, immune-, and heat-tolerance-related genes underwent divergent selection according to Asian agro-ecologies. We identify distinct sets of loci that contain promising candidate variants for adaptation to hot semi-arid and hot humid tropical ecosystems. Our results indicate that the rapid and successful adaptation of East Asian indicine cattle to hot humid environments was promoted by localized introgression from banteng and/or gaur. Our findings provide insights into the history and environmental adaptation of indicine cattle

Coupling the LSHM large scale hydrological model with the MM5 meteorological model for flow forecasting in the Upper Hanjiang river, China

Flood forecasting can be improved by coupling atmospheric and hydrological models. Withthe increasing development of large scale distributed hydrological models, large tests andoperational applications have been performed with coupling meteorological-hydrologicalmodel system. In order to evaluate the capability and adaptability of a large scale hydrologicalmodel applied in the Upper Hanjiang River basin, a grid-based large scale hydrological model(LSHM, grid cell size around 5×5 km) has been rebuilt and employed to mainly determineflow simulation driven by both gauged data during the period of the year 1996-2006 andMM5 during the period of June 1 to August 30, 2007, respectively. The Upper Hanjiang Rivercatchment is a humid climate region, which is part of the biggest tributary of the YangtzeRiver in China and local flood or drought events tend to easily occur with high-frequency.In the model experiments, two actual evapotranspiration estimation approaches have beenused: (1) the complementary relationship approach, and (2) the potential evapotranspirationapproach. Moreover, comparisons between the results estimated by different methods havebeen made. Flow simulations have mainly been performed respectively driven by two sets ofmeteorological input data: (1) surface observation data from station measurements, and (2)forecasting data from high resolution mesoscale meteorological model (MM5, horizontal gridcell size 9×9 km for the innermost domain). In addition, an operational flow forecastingexperiment has been applied with fixed lead time of 24 hours during the period of a severeflood event. Discussions about negative effects or disadvantages are presented roughly. Thepreliminary results are satisfactory and show a good potential for coupling meteorologicalmodel with hydrological model for the purpose of forecasting

Bilinear Coons Patch and its Application in Security Pattern Design

Nowadays, with the rapid development of printing and publishing industry, security printing technology becomes more and more important. Meanwhile, security pattern design is one of the most important techniques of security printing. A well designed security pattern should be difficult to counterfeit in any way. Therefore it can be used in printed security documents, such as banknotes, passports and certificates, etc. In this paper, based on the generalization of Coons patch construction, we propose a novel scheme of security pattern design. The practical pattern examples are presented, and some other applications of the novel method are also discussed. ? 2009 IEEE.EI

Lightweight Small Target Detection Algorithm with Multi-Feature Fusion

Unmanned aerial vehicles (UAVs) are a highly sought-after technology with numerous applications in both military and non-military uses. The identification of targets is a crucial aspect of UAV applications, but there are challenges associated with complex detection models and difficulty in detecting small targets. To address these issues, this study proposes the lightweight L-YOLO algorithm for target detection tasks from a UAV perspective. The L-YOLO algorithm improves on YOLOv5 by improving the model’s detection performance for small targets while reducing the number of parameters and computational effort. The GhostNet module replaces the relevant convolution in the YOLOv5 model to create a lightweight model. The EIoU loss is used as the loss function of the algorithm to accelerate convergence and improve regression accuracy. Furthermore, feature-level extensions based on YOLOv5 are implemented, and a new detection head is proposed to improve the model’s detection accuracy for small targets. The size of the anchor boxes is redesigned to suit the small targets using the K-means++ clustering algorithm. The experiments were conducted on the VisDrone-2022 dataset, and the L-YOLO algorithm demonstrated a reduction in computational effort by 42.42% and number of parameters by 48.6% compared to the original algorithm. Furthermore, recall and [email protected] improved by 2.1% and 1.4%, respectively. These results demonstrate that the L-YOLO algorithm not only has better detection performance for small targets but is also a lighter model, indicating promising prospects for target detection from a UAV perspective

16S rRNA gene sequencing reveals effects of photoperiod on cecal microbiota of broiler roosters

Photoperiod is an important factor in stimulating broiler performance in commercial poultry practice. However, the mechanism by which photoperiod affects the performance of broiler chickens has not been adequately explored. The current study evaluated the effects of three different photoperiod regimes (short day (LD) = 8 h light, control (CTR) = 12.5 h light, and long day (SD) = 16 h light) on the cecal microbiota of broiler roosters by sequencing bacterial 16S rRNA genes. At the phylum level, the dominant bacteria were Firmicutes (CTR: 68%, SD: 69%, LD: 67%) and Bacteroidetes (CTR: 25%, SD: 26%, and LD: 28%). There was a greater abundance of Proteobacteria (p < 0.01) and Cyanobacteria (p < 0.05) in chickens in the LD group than in those in the CTR group. A significantly greater abundance of Actinobacteria was observed in CTR chickens than in SD and LD chickens (p < 0.01). The abundance of Deferribacteres was significantly higher in LD chickens than in SD chickens (p < 0.01). Fusobacteria and Proteobacteria were more abundant in SD chickens than in CTR and LD chickens. The predicted functional properties indicate that cellular processes may be influenced by photoperiod. Conversely, carbohydrate metabolism was enhanced in CTR chickens as compared to that in SD and LD chickens. The current results indicate that different photoperiod regimes may influence the abundance of specific bacterial populations and then contribute to differences in the functional properties of gut microbiota of broiler roosters