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Image data augmentation plays a crucial role in data augmentation (DA) by increasing the quantity and diversity of labeled training data. However, existing methods have limitations. Notably, techniques like image manipulation, erasing, and mixing can distort images, compromising data quality. Accurate representation of objects without confusion is a challenge in methods like auto augment and feature augmentation. Preserving fine details and spatial relationships also proves difficult in certain techniques, as seen in deep generative models. To address these limitations, we propose OFIDA, an object-focused image data augmentation algorithm. OFIDA implements one-to-many enhancements that not only preserve essential target regions but also elevate the authenticity of simulating real-world settings and data distributions. Specifically, OFIDA utilizes a graph-based structure and object detection to streamline augmentation. Specifically, by leveraging graph properties like connectivity and hierarchy, it captures object essence and context for improved comprehension in real-world scenarios. Then, we introduce DynamicFocusNet, a novel object detection algorithm built on the graph framework. DynamicFocusNet merges dynamic graph convolutions and attention mechanisms to flexibly adjust receptive fields. Finally, the detected target images are extracted to facilitate one-to-many data augmentation. Experimental results validate the superiority of our OFIDA method over state-of-the-art methods across six benchmark datasets.

BACKGROUND:The Asian bush mosquito Aedes japonicus is invading Europe and was first discovered in Lelystad, the Netherlands in 2013, where it has established a permanent population. In this study, we investigated the vector competence of Ae. japonicus from the Netherlands for the emerging Zika virus (ZIKV) and zoonotic Usutu virus (USUV). ZIKV causes severe congenital microcephaly and Guillain-Barré syndrome in humans. USUV is closely related to West Nile virus, has recently spread throughout Europe and is causing mass mortality of birds. USUV infection in humans can result in clinical manifestations ranging from mild disease to severe neurological impairments. METHODOLOGY/PRINCIPAL FINDINGS:In our study, field-collected Ae. japonicus females received an infectious blood meal with ZIKV or USUV by droplet feeding. After 14 days at 28°C, 3% of the ZIKV-blood fed mosquitoes and 13% of the USUV-blood fed mosquitoes showed virus-positive saliva, indicating that Ae. japonicus can transmit both viruses. To investigate the effect of the mosquito midgut barrier on virus transmission, female mosquitoes were intrathoracically injected with ZIKV or USUV. Of the injected mosquitoes, 96% (ZIKV) and 88% (USUV) showed virus-positive saliva after 14 days at 28°C. This indicates that ZIKV and USUV can efficiently replicate in Ae. japonicus but that a strong midgut barrier is normally restricting virus dissemination. Small RNA deep sequencing of orally infected mosquitoes confirmed active replication of ZIKV and USUV, as demonstrated by potent small interfering RNA responses against both viruses. Additionally, de novo small RNA assembly revealed the presence of a novel narnavirus in Ae. japonicus. CONCLUSIONS/SIGNIFICANCE:Given that Ae. japonicus can experimentally transmit arthropod-borne viruses (arboviruses) like ZIKV and USUV and is currently expanding its territories, we should consider this mosquito as a potential vector for arboviral diseases in Europe.

[This corrects the article DOI: 10.1371/journal.pone.0050093.].

BACKGROUND:The Sustainable Development Goals (SDGs), adopted by all United Nations (UN) member states in 2015, established a set of bold and ambitious health-related targets to achieve by 2030. Understanding China's progress toward these targets is critical to improving population health for its 1.4 billion people. METHODS AND FINDINGS:We used estimates from the Global Burden of Disease (GBD) Study 2016, national surveys and surveillance data from China, and qualitative data. Twenty-eight of the 37 indicators included in the GBD Study 2016 were analyzed. We developed an attainment index of health-related SDGs, a scale of 0-100 based on the values of indicators. The projection model is adjusted based on the one developed by the GBD Study 2016 SDG collaborators. We found that China has achieved several health-related SDG targets, including decreasing neonatal and under-5 mortality rates and the maternal mortality ratios and reducing wasting and stunting for children. However, China may only achieve 12 out of the 28 health-related SDG targets by 2030. The number of target indicators achieved varies among provinces and municipalities. In 2016, among the seven measured health domains, China performed best in child nutrition and maternal and child health and reproductive health, with the attainment index scores of 93.0 and 91.8, respectively, followed by noncommunicable diseases (NCDs) (69.4), road injuries (63.6), infectious diseases (63.0), environmental health (62.9), and universal health coverage (UHC) (54.4). There are daunting challenges to achieve the targets for child overweight, infectious diseases, NCD risk factors, and environmental exposure factors. China will also have a formidable challenge in achieving UHC, particularly in ensuring access to essential healthcare for all and providing adequate financial protection. The attainment index of child nutrition is projected to drop to 80.5 by 2025 because of worsening child overweight. The index of NCD risk factors is projected to drop to 38.8 by 2025. Regional disparities are substantial, with eastern provinces generally performing better than central and western provinces. Sex disparities are clear, with men at higher risk of excess mortality than women. The primary limitations of this study are the limited data availability and quality for several indicators and the adoption of "business-as-usual" projection methods. CONCLUSION:The study found that China has made good progress in improving population health, but challenges lie ahead. China has substantially improved the health of children and women and will continue to make good progress, although geographic disparities remain a great challenge. Meanwhile, China faced challenges in NCDs, mental health, and some infectious diseases. Poor control of health risk factors and worsening environmental threats have posed difficulties in further health improvement. Meanwhile, an inefficient health system is a barrier to tackling these challenges among such a rapidly aging population. The eastern provinces are predicted to perform better than the central and western provinces, and women are predicted to be more likely than men to achieve these targets by 2030. In order to make good progress, China must take a series of concerted actions, including more investments in public goods and services for health and redressing the intracountry inequities.

BackgroundThe addition of neonatal (NN) mortality targets in the Sustainable Development Goals highlights the increased need for age-specific quantification of mortality trends, detail that is not provided by summary birth histories (SBHs). Several methods exist to indirectly estimate trends in under-5 mortality from SBHs; however, efforts to monitor mortality trends in important age groups such as the first month and first year of life have yet to utilize the vast amount of SBH data available from household surveys and censuses.Methods and findingsWe analyzed 243 Demographic and Health Surveys (DHS) from 76 countries, which collected both complete and SBHs from 8.5 million children from 2.3 million mothers to develop a new empirically based method to indirectly estimate time trends in age-specific mortality. We used complete birth history (CBH) data to train a discrete hazards generalized additive model in order to predict individual hazard functions for children based on individual-, mother-, and country-year-level covariates. Individual-level predictions were aggregated over time by assigning probability weights to potential birth years from mothers from SBH data. Age-specific estimates were evaluated in three ways: using cross-validation, using an external database of an additional 243 non-DHS census and survey data sources, and comparing overall under-5 mortality to existing indirect methods. Our model was able to closely approximate trends in age-specific child mortality. Depending on age, the model was able to explain between 80% and 95% of the variation in the validation data. Bias was close to zero in every age, with median relative errors spanning from 0.96 to 1.09. For trends in all under-5s, performance was comparable to the methods used for the Global Burden of Disease (GBD) study and significantly better than the standard indirect (Brass) method, especially in the 5 years preceding a survey. For the 15 years preceding surveys, the new method and GBD methods could explain more than 95% of the variation in the validation data for under-5s, whereas the standard indirect variants tested could only explain up to 88%. External validation using census and survey data found close agreement with concurrent direct estimates of mortality in the NN and infant age groups. As a predictive method based on empirical data, one limitation is that potential issues in these training data could be reflected in the resulting application of the method out of sample.ConclusionsThis new method for estimating child mortality produces results that are comparable to current best methods for indirect estimation of under-5 mortality while additionally producing age-specific estimates. Use of such methods allows researchers to utilize a massive amount of SBH data for estimation of trends in NN and infant mortality. Systematic application of these methods could further improve the evidence base for monitoring of trends and inequalities in age-specific child mortality.

Based on the database data of Chinese industrial enterprises from 2000 to 2007 and the LP method, this paper measures the total factor productivity of enterprises and investigates the effect of different mixed ownership forms on enterprises' efficiency and the effect of heterogeneous ownership balance on the mixed ownership enterprises' efficiency. The state-owned enterprise and mixed ownership enterprise are identified by the enterprise's paid-up capital. The results show that, on the whole, for the mixed ownership enterprise, the higher the diversification degree of the shareholders is, the higher the efficiency becomes, and in different types of industries, the mixed forms of shareholders have different effects on the efficiency of enterprises. The heterogeneous ownership balance and the enterprise efficiency show nonlinear U-type relationships. Both the higher and lower heterogeneous ownership balance degrees will promote the enterprise's efficiency. However, when the ownership balance degree is in the range of [0.2 0.5], the increase in ownership balance will lead to the decline of enterprise efficiency. Therefore, when introducing non-state-owned capital, state-owned enterprises should take full account of their own characteristics by rationally controlling the shareholding ratio of non-state-owned capital and play the positive role of a mixed ownership structure in corporate governance with appropriate ownership balances.

The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health services and to address the stigma of mental illness. Moreover, our results showing the accelerating burden of mental health are alarming as the region is seeing an increased level of instability. Indeed, mental health problems, if not properly addressed, will lead to an increased burden of diseases in the region.

Mortality and morbidity are increased in patients with muscle atrophy resulting from catabolic diseases such as diabetes. At present there is no pharmacological treatment that successfully reverses muscle wasting from catabolic conditions. We hypothesized that acupuncture plus low frequency electric stimulation (Acu-LFES) would mimic the impact of exercise and prevent diabetes-induced muscle loss. Streptozotocin (STZ) was used to induce diabetes in mice. The mice were then treated with Acu-LFES for 15 minutes daily for 14 days. Acupuncture points were selected according to the WHO Standard Acupuncture Nomenclature guide. The needles were connected to an SDZ-II electronic acupuncture device delivering pulses at 20Hz and 1mA. Acu-LFES prevented soleus and EDL muscle weight loss and increased hind-limb muscle grip function in diabetic mice. Muscle regeneration capacity was significantly increased by Acu-LFES. The expression of Pax7, MyoD, myogenin and embryo myosin heavy chain (eMyHC) was significantly decreased in diabetic muscle vs. control muscle. The suppressed levels in diabetic muscle were reversed by Acu-LFES. The IGF-1 signaling pathway was also upregulated by Acu-LFES. Phosphorylation of Akt, mTOR and p70S6K were downregulated by diabetes leading to a decline in muscle mass, however, Acu-LFES countered the diabetes-induced decline. In addition, microRNA-1 and -206 were increased by Acu-LFES after 24 days of treatment. We conclude that Acu-LFES is effective in counteracting diabetes-induced skeletal muscle atrophy by increasing IGF-1 and its stimulation of muscle regeneration.

BackgroundDastarcus helophoroides is known as the most valuable natural enemy insect against many large-body longhorned beetles. The molecular mechanism of its long lifespan and reproduction makes it a unique resource for genomic research. However, molecular biological studies on this parasitic beetle are scarce, and genomic information for D. helophoroides is not currently available. Thus, transcriptome information for this species is an important resource that is required for a better understanding of the molecular mechanisms of D. helophoroides. In this study, we obtained transcriptome information of D. helophoroides using high-throughput RNA sequencing.ResultsUsing Illumina HiSeq 2000 sequencing, 27,543,746 clean reads corresponding to a total of 2.48 Gb nucleotides were obtained from a single run. These reads were assembled into 42,810 unigenes with a mean length of 683 bp. Using a sequence similarity search against the five public databases (NR, Swiss-Prot, GO, COG, KEGG) with a cut-off E-value of 10(-5) using Blastx, a total of 31,293 unigenes were annotated with gene description, gene ontology terms, or metabolic pathways.ConclusionsTo the best of our knowledge, this is the first study on the transcriptome information of D. helophoroides. The transcriptome data presented in this study provide comprehensive information for future studies in D. helophoroides, particularly for functional genomic studies in this parasitic beetle.

Variable number of tandem repeats (VNTRs) that are widely distributed in the genome of Yersinia pestis proved to be useful markers for the genotyping and source-tracing of this notorious pathogen. In this study, we probed into the features of VNTRs in the Y. pestis genome and developed a simple hierarchical genotyping system based on optimized VNTR loci.Capillary electrophoresis was used in this study for multi-locus VNTR analysis (MLVA) in 956 Y. pestis strains. The general features and genetic diversities of 88 VNTR loci in Y. pestis were analyzed with BioNumerics, and a "14+12" loci-based hierarchical genotyping system, which is compatible with single nucleotide polymorphism-based phylogenic analysis, was established.Appropriate selection of target loci reduces the impact of homoplasies caused by the rapid mutation rates of VNTR loci. The optimized "14+12" loci are highly discriminative in genotyping and source-tracing Y. pestis for molecular epidemiological or microbial forensic investigations with less time and lower cost. An MLVA genotyping datasets of representative strains will improve future research on the source-tracing and microevolution of Y. pestis.

A motif in a network is a connected graph that occurs significantly more frequently as an induced subgraph than would be expected in a similar randomized network. By virtue of being atypical, it is thought that motifs might play a more important role than arbitrary subgraphs. Recently, a flurry of advances in the study of network motifs has created demand for faster computational means for identifying motifs in increasingly larger networks. Motif detection is typically performed by enumerating subgraphs in an input network and in an ensemble of comparison networks; this poses a significant computational problem. Classifying the subgraphs encountered, for instance, is typically performed using a graph canonical labeling package, such as Nauty, and will typically be called billions of times. In this article, we describe an implementation of a network motif detection package, which we call NetMODE. NetMODE can only perform motif detection for [Formula: see text]-node subgraphs when [Formula: see text], but does so without the use of Nauty. To avoid using Nauty, NetMODE has an initial pretreatment phase, where [Formula: see text]-node graph data is stored in memory ([Formula: see text]). For [Formula: see text] we take a novel approach, which relates to the Reconstruction Conjecture for directed graphs. We find that NetMODE can perform up to around [Formula: see text] times faster than its predecessors when [Formula: see text] and up to around [Formula: see text] times faster when [Formula: see text] (the exact improvement varies considerably). NetMODE also (a) includes a method for generating comparison graphs uniformly at random, (b) can interface with external packages (e.g. R), and (c) can utilize multi-core architectures. NetMODE is available from netmode.sf.net.