A Research on Tourism E-Business of Shanxi

E-business has become a new growth point of current economic development in the world. The natural adaptability between tourism and E-business gives birth to tourism E-business. The tourism resources in Shanxi are unique, yet its tourism development level and the abundant resources are not harmonious. To transform its resource advantage into economic advantage, developing tourism E-business is very urgent and necessary. In this article, through quantitative analysis and qualitative analysis methods, we find out the problems existing in the development of tourism E-business in Shanxi, and put forward corresponding development measures, especially the mobile E-tourism based on 3G technology, which is a new pattern and will become the development direction of Shanxi’s tourism E-business in the future. The research aims at providing practical references for the tourism management departments and enterprises in Shanxi to enhance its competitiveness and promote its sustainable development

Machine Learning Methods in Real-World Studies of Cardiovascular Disease

Objective: Cardiovascular disease (CVD) is one of the leading causes of death worldwide, and answers are urgently needed regarding many aspects, particularly risk identification and prognosis prediction. Real-world studies with large numbers of observations provide an important basis for CVD research but are constrained by high dimensionality, and missing or unstructured data. Machine learning (ML) methods, including a variety of supervised and unsupervised algorithms, are useful for data governance, and are effective for high dimensional data analysis and imputation in real-world studies. This article reviews the theory, strengths and limitations, and applications of several commonly used ML methods in the CVD field, to provide a reference for further application. Methods: This article introduces the origin, purpose, theory, advantages and limitations, and applications of multiple commonly used ML algorithms, including hierarchical and k-means clustering, principal component analysis, random forest, support vector machine, and neural networks. An example uses a random forest on the Systolic Blood Pressure Intervention Trial (SPRINT) data to demonstrate the process and main results of ML application in CVD. Conclusion: ML methods are effective tools for producing real-world evidence to support clinical decisions and meet clinical needs. This review explains the principles of multiple ML methods in plain language, to provide a reference for further application. Future research is warranted to develop accurate ensemble learning methods for wide application in the medical field

Impact of pesticide regulations on mortality from suicide by pesticide in China: an interrupted time series analysis

BackgroundPesticide bans and regulatory restrictions have been shown to be effective strategies for preventing suicide in several countries. Suicide and suicide by pesticides have decreased significantly in China over the past two decades. However, whether the reduction was associated with pesticide regulation is unknown.MethodsThe monthly data on suicide and suicide by pesticide from 2006 to 2018 were obtained from China's Disease Surveillance Point (DSP) system. Information on China's pesticide regulations since 1970 was obtained from Pesticide Action Network International (PAN International), Joint Meeting on Pesticide Management Highly Hazardous Pesticides (JMPM HHP) lists, the website of the Ministry of Agriculture of China, Pesticide Information Network of China, and the Wan Fang database. Change point detection and policy analysis were combined to identify the time of any trend change breakpoint of suicide and suicide by pesticide. Interrupted time series analysis was used to investigate the pre- and post-breakpoint trends of monthly standardized rates in suicide and suicide by pesticide.ResultsThe standardized pesticide suicide rate decreased by 60.5% from 6.50 in 2006 to 2.56 per 100,000 in 2018. Larger declines were evident among people in urban areas (67.3%), female individuals (63.5%), and people aged 15–44 years (68.1%). The effect of policies banning highly hazardous organophosphorus pesticides (HHOP) [rate ratio (RR) = 0.993, 95% CIs (0.991–0.994)] in December 2008 and stopping domestic sales and use of paraquat aqueous solution (RR = 0.992, 95% CIs: 0.990–0.994) in July 2016 were more pronounced than regulating the paraquat-related products (RR = 1.003, 95% CIs: 1.002–1.004) in April 2012.ConclusionDeclines in suicide by pesticide in China occurred contemporaneously with regulatory bans and restrictions implemented on several pesticides, particularly in urban areas, among female individuals, and the relatively low age profile. These findings indicate the potential influence of these bans on trends of suicide by pesticides

An online tool for predicting ovarian responses in unselected patients using dynamic inhibin B and basal antimüllerian hormone levels

BackgroundReliable predictive models for predicting excessive and poor ovarian response in controlled ovarian stimulation (COS) is currently lacking. The dynamic (Δ) inhibin B, which refers to increment of inhibin B responding to exogenous gonadotropin, has been indicated as a potential predictor of ovarian response.ObjectiveTo establish mathematical models to predict ovarian response at the early phase of COS using Δinhibin B and other biomarkers.Materials and methodsProspective cohort study in a tertiary teaching hospital, including 669 cycles underwent standard gonadotropin releasing hormone (GnRH) antagonist ovarian stimulation between April 2020 and September 2020. Early Δinhibin B was defined as an increment in inhibin B from menstrual day 2 to day 6 through to the day of COS. Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression with 5-fold cross-validation was applied to construct ovarian response prediction models. The area under the receiver operating characteristic curve (AUC), prevalence, sensitivity, and specificity were used for evaluating model performance.ResultsEarly Δinhibin B and basal antimüllerian hormone (AMH) levels were the best measures in building models for predicting ovarian hypo- or hyper-responses, with AUCs and ranges of 0.948 (0.887–0.976) and 0.904 (0.836–0.945) in the validation set, respectively. The contribution of the early Δinhibin B was 67.7% in the poor response prediction model and 56.4% in the excessive response prediction model. The basal AMH level contributed 16.0% in the poor response prediction model and 25.0% in the excessive response prediction model. An online website-based tool (http://121.43.113.123:8001/) has been developed to make these complex algorithms available in clinical practice.ConclusionEarly Δinhibin B might be a novel biomarker for predicting ovarian response in IVF cycles. Limiting the two prediction models to the high and the very-low risk groups would achieve satisfactory performances and clinical significance. These novel models might help in counseling patients on their estimated ovarian response and reduce iatrogenic poor or excessive ovarian responses

Propagation of Non-Linear Lamb Waves in Adhesive Joint with Micro-Cracks Distributing Randomly

With the advantages of uniform stress transfer and weight reduction, adhesive joints are widely used in engineering. The propagation of non-linear Lamb waves in an adhesive joint with micro-cracks distributing in a random way is systematically investigated by using the numerical simulation method in this paper. A finite element model of the tri-layer adhesive structure with micro-cracks distributing randomly is established, and the Lamb wave mode pair with a matching condition of the phase velocity is chosen to examine the interaction of the micro-cracks with Lamb waves. The results show that the micro-cracks within the adhesive layer will lead to the generation of second harmonics. We also find that the Acoustic Non-linearity Parameters (ANP) increase with the propagation distance in the micro-crack damage zone and the density of the micro-cracks. However, ANPs are less concerned with the friction coefficients of the surface of micro-cracks. This numerical research reveals that non-linear Lamb waves can be employed to effectively characterize the micro-cracks related damages within an adhesive joint

The epidemiology and disease burden of children hospitalized for viral infections within the family Flaviviridae in China: A national cross-sectional study.

BackgroundViruses of the family Flaviviridae, including Japanese encephalitis virus (JEV), dengue virus (DENV), yellow fever virus (YFV) and hepatitis C virus (HCV), are widely distributed worldwide. JEV, DENV and YFV belong to the genus Flavivirus, whereas HCV belongs to the genus Hepacivirus. Children's symptoms are usually severe. As a result, rates of hospitalization due to infection with these viruses are high. The epidemiology and disease burden of hospitalized children have rarely been described in detail to date. The objective of this study was to report the general epidemiological characteristics, clinical phenotype, length of stay (LOS), burden of disease, and potential risk factors for hospitalized children infected with JEV, DENV, YFV, or HCV in Chinese pediatric hospitals.MethodologyA cross-sectional study of epidemiology and disease burden of children hospitalized for Flaviviridae virus infections between December 2015 and December 2020 in China was performed. Face sheets of discharge medical records (FSMRs) were collected from 27 tertiary children's hospitals in the Futang Research Center of Pediatric Development and aggregated into FUTang Update medical REcords (FUTURE). Information on sociodemographic variables, clinical phenotype, and LOS as well as economic burden was included in FSMRs and compared using appropriate statistical tests.FindingsThe study described 490 children aged 0-15 years hospitalized for infections with Flaviviridae viruses. Japanese encephalitis (JE) cases are the highest, accounting for 92.65% of the total hospitalization cases caused by Flaviviridae virus infection. The incidence of JE peaked from July to October with a profile of a high proportion of severe cases (68.06%) and low mortality (0.44%). Rural children had a significantly higher incidence than urban children (91.63%). Most hospitalized dengue cases were reported in 2019 when dengue outbreaks occurred in many provinces of China, although only 14 dengue cases were collected during the study period. Yellow fever (YF) is still an imported disease in China. The hospitalizations for children with hepatitis C (HC) were not high, and mild chronic HC was the main clinical phenotype of patients. Among the four viral infections, JE had the highest disease burden (LOS and expenditure) for hospitalized children.ConclusionFirst, the present study reveals that JE remains the most serious disease due to Flaviviridae virus infection and threatens children's health in China. Many pediatric patients have severe illnesses, but their mortality rate is lower, suggesting that existing treatment is effective. Both JEV vaccination and infection control of rural children should represent a focus of study. Second, although the dual risks of indigenous epidemics and imports of DENV still exist, the prevalence of DENV in children is generally manageable. Third, YFV currently shows no evidence of an epidemic in China. Finally, the proportion of children with chronic hepatitis C (CHC) is relatively large among hospitalized children diagnosed with HCV. Thus, early and effective intervention should be offered to children infected with HCV to ease the burden of CHC on public health

RFA: R-Squared Fitting Analysis Model for Power Attack

Correlation Power Analysis (CPA) introduced by Brier et al. in 2004 is an important method in the side-channel attack and it enables the attacker to use less cost to derive secret or private keys with efficiency over the last decade. In this paper, we propose R-squared fitting model analysis (RFA) which is more appropriate for nonlinear correlation analysis. This model can also be applied to other side-channel methods such as second-order CPA and collision-correlation power attack. Our experiments show that the RFA-based attacks bring significant advantages in both time complexity and success rate

Side-Channel Attacks and Countermeasures for Identity-Based Cryptographic Algorithm SM9

Identity-based cryptographic algorithm SM9, which has become the main part of the ISO/IEC 14888-3/AMD1 standard in November 2017, employs the identities of users to generate public-private key pairs. Without the support of digital certificate, it has been applied for cloud computing, cyber-physical system, Internet of Things, and so on. In this paper, the implementation of SM9 algorithm and its Simple Power Attack (SPA) are discussed. Then, we present template attack and fault attack on SPA-resistant SM9. Our experiments have proved that if attackers try the template attack on an 8-bit microcontrol unit, the secret key can be revealed by enabling the device to execute one time. Fault attack even allows the attackers to obtain the 256-bit key of SM9 by performing the algorithm twice and analyzing the two different results. Accordingly, some countermeasures to resist the three kinds of attacks above are given

Clinical epidemiology and disease burden of adenoviral encephalitis in hospitalized children in China: A nationwide cross‐sectional study

ABSTRACT Importance Adenovirus encephalitis is a significant infectious disease of the central nervous system that commonly affects children under the age of 5 and has a profound impact on the health of infants and young children throughout China. National multicenter epidemiological studies have significant public health implications. Objective This study aims to report the epidemiology of adenovirus encephalitis in hospitalized children in China, providing valuable guidance for clinicians. Methods The data utilized in this study were extracted from the comprehensive Futang Update Medical Records database, which comprises discharge medical records collected by 27 tertiary children's hospitals between January 2016 and December 2018 in China. Specifically, the face sheet of discharge medical records encompassed critical sociodemographic variables and basic medical care details. Results In this database, a total of 544 children were hospitalized due to adenoviral encephalitis. The male‐to‐female ratio was 1.62:1, with more boys being affected across different age groups and places of residence. Of the children hospitalized, the highest number of hospitalizations occurred in the 1–3‐year age group and the number of hospitalizations decreased each year from 2016 to 2018. The disease exhibits seasonal characteristics with a pronounced peak in the summer months of June and July. While most children (58%) did not have any significant complications, one‐third of them developed respiratory complications, including pneumonia and acute bronchitis. The median length of stay for adenoviral encephalitis was 7 days, and the median cost of hospitalization was 2145.56 US dollars. Interpretation This study highlights the prevalence of adenovirus encephalitis in hospitalized children in China. Children aged 1–3 years were found to be the main demographic hospitalized due to this condition, with boys being significantly more affected than girls. The seasonal variations of adenovirus encephalitis were also found to be significant. Fortunately, the fatality rate associated with this condition was low, and the prognosis was generally favorable