Malicious JavaScript code in webpages on the Internet is an emergent security issue because of its universality and potentially severe impact. Because of its obfuscation and complexities, detecting it has a considerable cost. Over the last few years, several machine learning-based detection approaches have been proposed; most of them use shallow discriminating models with features that are constructed with artificial rules. However, with the advent of the big data era for information transmission, these existing methods already cannot satisfy actual needs. In this paper, we present a new deep learning framework for detection of malicious JavaScript code, from which we obtained the highest detection accuracy compared with the control group. The architecture is composed of a sparse random projection, deep learning model, and logistic regression. Stacked denoising auto-encoders were used to extract high-level features from JavaScript code; logistic regression as a classifier was used to distinguish between malicious and benign JavaScript code. Experimental results indicated that our architecture, with over 27 000 labeled samples, can achieve an accuracy of up to 95%, with a false positive rate less than 4.2% in the best case.

Objective: This meta-analysis evaluated the efficacy of acupuncture in improving cognitive impairment of post-stroke patients.Design: Randomized controlled trials (RCTs) investigating the effects of acupuncture compared with no treatment or sham acupuncture on post-stroke cognitive impairment (PSCI) before December 2019 were identified from databases (PubMed, EMBASE, Ovid library, Cochrane Library, Chinese National Knowledge Infrastructure, VIP Chinese Periodical Database, Wanfang Database, and SinoMed). The literature searching and data extracting were independently performed by two investigators. Study quality was assessed using the Cochrane Handbook for Systematic Reviews of Interventions. Meta-analyses were performed for the eligible RCTs with Revman 5.3 software.Results: Thirty-seven RCTs (2,869 patients) were included in this meta-analysis. Merged Random-effects estimates of the gain of MMSE (Mini-Mental State Examination) or MoCA (Montreal Cognitive Assessment) were calculated for the comparison of acupuncture with no acupuncture or sham acupuncture. Following 2–8 weeks of intervention with acupuncture, pooled results demonstrated significant effects of acupuncture in improving PSCI assessed by MMSE (MD [95% CI] = 2.88 [2.09, 3.66], p < 0.00001) or MoCA (MD [95% CI] = 2.66 [1.95, 3.37], p < 0.00001).Conclusion: The results suggest that acupuncture was effective in improving PSCI and supported the needs of more rigorous design with large-scale randomized clinical trials to determine its therapeutic benefits.

Objective To investigate the relationship between fractional anisotropy (FA), a suggested biomarker for tissue integrity, and motor recovery in stroke patients following post-acute rehabilitation. Design Retrospective study. Setting Acute rehabilitation hospital. Participants 43 subjects, 28 diagnosed with ischemic stroke, and 15 diagnosed with hemorrhagic stroke. The average age for subjects was (68±14 years). Interventions MRI and Diffusion Tensor Imaging (DTI) were conducted on all patients. Main Outcome Measure(s) This is a retrospective study. The admission and discharge motor sub-scores of the Functional Independence Measure (FIM) were obtained from medical records, and relative gain was calculated using the Montebello Rehabilitation Factor Score (MRFS). K-means cluster analysis (K=3) using both MRFS and gain of FIM motor sub-score (ΔFIM) was performed. ANOVA test was used to determine the difference in FA among the clusters. Spearman analysis was conducted to examine the relationship between FA, ΔFIM, and MRFS in each cluster. Results FA was significantly higher in the clusters of good and moderate recovery in the corticospinal tract (CST), peduncle, and posterior limb of the internal capsule (PLIC) bilaterally (all P<0.05) compared to the poor recovery group. Significant positive correlations were observed in multiple regions along CST between FA, ΔFIM, and MRFS in the clusters of good and moderate recovery, but not in the poor recovery group. Conclusion Our results showed an association between FA values within the corticospinal tract and motor recovery in stroke patients undergoing post-acute rehabilitation. This finding may help to identify novel targets for new interventions to promote stroke recovery.

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Objective: This study synthesized evidence regarding the prevalence of post-traumatic stress disorder (PTSD) in the United States (US). Methods: A systematic literature review (SLR) identified recently published (2015)(2016)(2017)(2018)(2019) observational studies of PTSD prevalence in the US via the MEDLINE, EMBASE, and PsycINFO databases. Eligible studies' most recent data were collected no earlier than 2013. Data elements extracted included study design, sample size, location, data source/year(s), study population(s), traumatic event type, prevalance estimates with corresponding look-back periods, and clinical metrics. Results: Data from 38 identified articles were categorized by population, diagnostic criteria, and lookback period. Among civilians, point prevalence ranged from 8.0% to 56.7%, 1-year prevalence from 2.3% to 9.1%, and lifetime prevalence from 3.4% to 26.9%. In military populations, point prevalence ranged from 1.2% to 87.5%, 1-year prevalence from 6.7% to 50.2%, and lifetime prevalence from 7.7% to 17.0%. Within these ranges, several estimates were derived from relatively high quality data; these articles are highlighted in the review. Prevalence was elevated in subpopulations including emergency responders, refugees, American Indian/Alaska Natives, individuals with heavy substance use, individuals with a past suicide attempt, trans-masculine individuals, and women with prior military sexual trauma. Female sex, lower income, younger age, and behavioral health conditions were identified as risk factors for PTSD. Conclusions: PTSD prevalence estimates varied widely, partly due to different study designs, populations, and methodologies, and recent nationally representative estimates were lacking. Efforts to increase PTSD screening and improve disease awareness may allow for a better detection and management of PTSD.

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