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The operational data of advanced process systems have met with explosive growth, but its fluctuations are so slight that the number of the extracted representative samples is quite limited, making it difficult to reflect the nature of the process and to establish prediction models. In this study, inspired by the process of fisherman repairing nets, a Kriging-based virtual sample generation (VSG) named Kriging-VSG is proposed to generate feasible virtual samples in data sparse regions. Then, the accuracy of prediction models is further enhanced by applying the generated virtual samples. In order to reasonably find data sparse regions, a distance-based criterion is imposed on each dimension to identify important samples with large information gaps. Similar to the process of fisherman repairing nets, a certain dimension is initially fixed at different quantiles. A dimension-wise interpolation process using Kriging is then performed on the center between important samples with large information gaps. To validate the performance of the proposed Kriging-VSG, two numerical simulations and a real-world application from a cascade reaction process for high-density polyethylene are carried out. The results indicate that the proposed Kriging-VSG outperforms other methods.

As a typical representative of the public key cryptosystem, RSA has attracted a great deal of cryptanalysis since its invention, among which a famous attack is the small private exponent attack. It is well-known that the best theoretical upper bound for the private exponent d that can be attacked is d ≤ N 0.292 , where N is a RSA modulus. However, this bound may not be achieved in practical attacks since the lattice constructed by Coppersmith method may have a large enough dimension and the lattice-based reduction algorithms cannot work so well in both efficiency and quality. In this paper, we propose a new practical attack based on the binary search for the most significant bits (MSBs) of prime divisors of N and the Herrmann-May’s attack in 2010. The idea of binary search is inspired by the discovery of phenomena called “multivalued-continuous phenomena”, which can significantly accelerate our attack. Together with several carefully selected parameters according to our exact and effective numerical estimations, we can improve the upper bound of d that can be practically achieved. More specifically, without the binary search method, we successfully attack RSA with a 1024-bit-modulus N when d ≤ N 0.285 . Moreover, by our new method, we can implement a successful attack for a 1024-bit-modulus RSA when d ≤ N 0.292 and for a 2048-bit-modulus RSA when d ≤ N 0.287 in about a month. We believe our method can provide some inspiration to practical attacks on RSA with mainstream-size moduli.

Prostate cancer (PCa) is one of the most frequent cancers in men, and its biomolecular targets have been extensively studied. This study aimed to analyze the expression of toll-like receptor 9 (TLR9) and vascular endothelial growth factor C (VEGF-C) and the clinical value of the coexpression of TLR9 and VEGF-C in PCa. We retrospectively evaluated 55 patients with clinically localized, intermediate-risk, or high-risk PCa who underwent laparoscopic radical prostatectomy (LRP) and extended pelvic lymph node dissection (ePLND) without neoadjuvant hormonal therapy at a single institution from June 2013 to December 2016. In all 55 patients, the median number of lymph nodes (LNs) resected was 23 (range: 18-31), and a total of 1269 LNs were removed, of which 78 LNs were positive. Seventeen patients had positive LNs, with a positive rate of 30.9%. In addition, the immunohistochemical results in the above patients revealed that high TLR9 expression was correlated with higher Gleason score (GS) (P = 0.049), increased LN metastasis (P = 0.004), and more perineural invasion (PNI) (P = 0.033). Moreover, VEGF-C expression was associated with GS (P = 0.040), pathological stage (pT stage) (P = 0.022), LN metastasis (P = 0.003), and PNI (P = 0.001). Furthermore, a significant positive correlation between TLR9 and VEGF-C was found (P < 0.001), and the TLR9/VEGF-C phenotype was associated with LN metastasis (P = 0.047). Collectively, we propose that TLR9 stimulation may promote LN metastasis in PCa cells through the upregulation of VEGF-C expression, thereby affecting the prognosis of PCa patients. Therefore, these markers may serve as valuable targets for the treatment of PCa.

Chronic epididymitis (CE) refers to a long-lasting inflammatory condition of the epididymis, which is considered the most common site of intrascrotal inflammation and an important aetiological factor of male infertility. Recent studies demonstrate that small RNAs secreted from epididymal epithelium modulate embryo development and offspring phenotypes via sperm transmission, and the resulting modifications may lead to transgenerational inheritance. However, to date, the genome-wide analysis of small RNA together with the transcriptomic expression profiles of human epididymis and CE is still lacking. In this study, we facilitated next-generation sequencing and bioinformatics to comprehensively analyze the small RNA and mRNA in an integrative way and identified signatures associated with CE. Both of the small RNA and mRNA expression data demonstrated relatively larger molecular differences among the segmental region of the epididymides, including caput, corpus, and cauda, than that of the inflammatory conditions. By comparing the inflamed caputs to the controls, a total of 1727 genes (1220 upregulated and 507 downregulated; 42 most significant genes, adjusted P < 0.05) and 34 miRNAs (23 upregulated and 11 downregulated) were identified as differentially expressed. In silico functional enrichment analysis showed their roles in regulating different biological activities, including leukocyte chemotaxis, extracellular milieu reconstruction, ion channel and transporter-related processes, and nervous system development. Integrative analysis of miRNA and mRNA identified a regulatory network consisting of 22 miRNAs and 31 genes (miRNA-mRNA) which are strong candidates for CE. In addition, analysis about other species of small RNA, including (miRNA), piwi-interacting RNA (piRNA), tRNA-derived small RNA (tsRNA), Y RNA, and rsRNA identified the distinct expression pattern of tsRNA in CE. In summary, our study performed small RNA and miRNA profiling and integrative analysis in human CE. The findings will help to understand the role of miRNA-mRNA in the pathogenesis of CE and provide molecular candidates for the development of potential biomarkers for human CE.

Background The association between urbanization and myocardial infarction in China was not fully understood. We aim to evaluate the association between urbanization level and the risk of myocardial infarction. Methods Participants’ data from China Health and Nutrition Survey were analyzed. The survey is an ongoing open cohort with a multistage, random cluster process to draw a sample of over 30,000 individuals in 15 provinces and municipal cities. A multi-component score, urbanization index, was used to measure urbanization level. Urbanization index was categorized by cut-off values of 40, 60, and 80. Baseline characteristics were presented as percentage for categorical variables, and mean or median for continuous variables depending on normality. The association of urbanization index and myocardial infarction risk was evaluated longitudinally by a multilevel mixed-effects parametric survival model with urbanization index as a time-dependent variable using Stata software. Results A total of 16,565 participants without previous myocardial infarction were involved in the cohort. At baseline, urbanization index was positively correlated with myocardial infarction risk factors, including blood pressure, body mass index, diabetes, and stroke. In the univariate model, urbanization index was associated with risk of myocardial infarction in a “U-shape” manner, with the lowest myocardial infarction risk in urbanization index ranging from 40 to 60 (Hazard Ratio 0.55 and p =  0.013). However, in the multivariate model adjusting for myocardial infarction risk factors and other confounders, urbanization index ≥ 40 was consistently associated with lower MI risks (Hazard Ratio 0.46 and p =  0.002 for urbanization index 40–60; Hazard Ratio 0.56 and p =  0.021 for urbanization index 60–80; and Hazard Ratio 0.44 and p =  0.002 for urbanization index ≥ 80). Conclusions Our study indicated that urbanization of living communities was associated with a reduced risk of myocardial infarction.

Background Blood pressure variability (BPV) is a modifiable risk factor for stroke. This study was performed to determine the prognostic role of BPV in patients with acute hemorrhagic stroke. Methods The data of 131 hospitalized hypertensive patients with spontaneous intracerebral hemorrhage (sICH) were collected. All patients underwent examinations using several neurological scales (Glasgow Coma Scale, National Institutes of Health Stroke Scale, and modified Rankin scale [mRS]) and BP measurements at different time points. Results Sex, age, hematoma volume, and neurological scores were not significantly different between patients with a favorable and unfavorable prognosis for sICH. However, significant differences were found in hypertension, diabetes, metabolic syndrome, atrial fibrillation, smoking, and stroke history. The standard deviation (SD), coefficient of variation (CV), and maximum–minimum range (Max–Min) of diastolic BP and the mean, SD, CV, and Max–Min of systolic BP significantly differed between the groups. Statistical analysis also demonstrated correlations between the 90-day mRS score and BPV and between systolic BPV and the 90-day mRS score. Conclusion High systolic or diastolic BPV within 24 hours of hemorrhagic stroke onset is associated with the 90-day neurological prognosis. The 24-hour BPV plays a critical role in the neurological outcome of hemorrhagic stroke.

Epididymitis is an epididymal inflammation that may lead to male infertility. Dendritic cells (DCs) and myeloid differentiation primary response gene 88 (Myd88) were associated with epididymitis in rodents. However, the functions of Myd88 on epididymal DCs remain unclear. This study investigated the role of Myd88 in DCs for epididymitis. The Myd88 signaling pathway, phenotypes of DC subsets, and cytokines were investigated in lipopolysaccharide (LPS)-induced epididymitis in mice. CRISPR-Cas9 was used to knockout Myd88 in bone-marrow-derived dendritic cells (BMDCs) and immortalized mouse epididymal (DC2) cell line. In the vivo experiments, levels of the proinflammatory cytokines IL-1α, IL-6, IL-17A, TNF-α, IL-1β, MCP-1, and GM-CSF, mRNA for MyD88 related genes, and the percentages of monocyte-derived DCs (Mo-DCs) were significantly elevated in mice with epididymitis. In the vitro experiments, LPS significantly promoted the apoptosis of BMDCs. In addition, the concentration of inflammatory cytokines in BMDCs and DC2s were increased in the LPS group, while decreasing after the knockout of Myd88. These findings indicate that Myd88 on DCs is involved in the inflammation of epididymitis in mice, which may be a potential target for better strategies regarding the treatment of immunological male infertility.

Pseudorandom sequences are widely used in cryptography. Multiple recursive generators are an important class of pseudorandom sequence generators. A typical application is to obtain truncated sequences by truncating partial bits of the sequences output by the generators. This paper studies the predictability of truncated multiple recursive generators with unknown parameters. Given a few truncated digits of high-order bits output by a multiple recursive generator, we give a method based on lattice reduction to recover the parameters and the initial state of the generator. Our method is an extension of Stern’s algorithm which was proposed to predict the truncated sequences of linear congruential generators.

Small sample size (SSS) problems pose a tremendous challenge in modeling tasks due to insufficient training samples, especially in process industry where thousands of useless samples overwhelm very limited valuable samples, leading to deterioration on the prediction ability of trained models for key variables. In this study, the prediction ability to forecast models is enhanced by generating virtual samples. Considering the integrated effects of attributes, a new data augment approach, called ITNN-VSG, which integrates virtual sample generation (VSG) with input-training neural network (ITNN), was put forward to enlarge training datasets for improving the performance of forecasting models. In the absence of any available domain-specific knowledge about target models, a query-driven interpolation process was first developed to explore the overall tendency of data distribution in both sparse regions and dense regions. Second, an ITNN with fixed weights was used to calculate the input corresponding to the virtual output generated by the interpolation process. To validate the effectiveness of the proposed approach, several in silico experiments were carried out on a benchmark dataset from sinc( x ) function, followed by a real-world application to purified terephthalic acid (PTA) solvent system. The experimental results demonstrated that the proposed approach outperformed other existing approaches such as mega-trend-diffusion and tree-based-trend-diffusion.

People's Republic of China is one of the countries with the highest incidence of gastric cancer, accounting for 45% of all new gastric cancer cases in the world. Therefore, strong prognostic markers are critical for the diagnosis and survival of Chinese patients suffering from gastric cancer. Recent studies have begun to unravel the mechanisms linking the host inflammatory response to tumor growth, invasion and metastasis in gastric cancers. Based on this relationship between inflammation and cancer progression, several inflammation-based scores have been demonstrated to have prognostic value in many types of malignant solid tumors. To compare the prognostic value of inflammation-based prognostic scores and tumor node metastasis (TNM) stage in patients undergoing gastric cancer resection. The inflammation-based prognostic scores were calculated for 207 patients with gastric cancer who underwent surgery. Glasgow prognostic score (GPS), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), prognostic nutritional index (PNI), and prognostic index (PI) were analyzed. Linear trend chi-square test, likelihood ratio chi-square test, and receiver operating characteristic were performed to compare the prognostic value of the selected scores and TNM stage. In univariate analysis, preoperative serum C-reactive protein (P<0.001), serum albumin (P<0.001), GPS (P<0.001), PLR (P=0.002), NLR (P<0.001), PI (P<0.001), PNI (P<0.001), and TNM stage (P<0.001) were significantly associated with both overall survival and disease-free survival of patients with gastric cancer. In multivariate analysis, GPS (P=0.024), NLR (P=0.012), PI (P=0.001), TNM stage (P<0.001), and degree of differentiation (P=0.002) were independent predictors of gastric cancer survival. GPS and TNM stage had a comparable prognostic value and higher linear trend chi-square value, likelihood ratio chi-square value, and larger area under the receiver operating characteristic curve as compared to other inflammation-based prognostic scores. The present study indicates that preoperative GPS and TNM stage are robust predictors of gastric cancer survival as compared to NLR, PLR, PI, and PNI in patients undergoing tumor resection.