Gender disparities and woman-specific trends in Barrett’s esophagus in the United States:An 11-year nationwide populationbased study

BACKGROUND Barrett's esophagus(BE)is a known premalignant precursor to esophageal adenocarcinoma(EAC).The prevalence rates continue to rise in the United States,but many patients who are at risk of EAC are not screened.Current practice guidelines include male gender as a predisposing factor for BE and EAC.The population-based clinical evidence regarding female gender remains limited.AIM To study comparative trends of gender disparities in patients with BE in the United States.METHODS A nationwide retrospective study was conducted using the 2009-2019 National Inpatient Sample(NIS)database.Patients with a primary or secondary diagnosis code of BE were identified.The major outcome of interest was determining the gender disparities in patients with BE.Trend analysis for respective outcomes for females was also reported to ascertain any time-based shifts.RESULTS We identified 1204190 patients with BE for the study period.Among the included patients,717439(59.6%)were men and 486751(40.4%)were women.The mean age was higher in women than in men(67.1±0.4 vs 66.6±0.3 years,P<0.001).The rate of BE per 100000 total NIS hospitalizations for males increased from 144.6 in 2009 to 213.4 in 2019(P<0.001).The rate for females increased from 96.8 in 2009 to 148.7 in 2019(P<0.001).There was a higher frequency of obesity among women compared to men(17.4%vs 12.6%,P<0.001).Obesity prevalence among females increased from 12.3%in 2009 to 21.9%in 2019(P<0.001).A lower prevalence of smoking was noted in women than in men(20.8%vs 35.7%,P<0.001).However,trend analysis showed an increasing prevalence of smoking among women,from 12.9%in 2009 to 30.7%in 2019(P<0.001).Additionally,there was a lower prevalence of alcohol abuse,Helicobacter pylori(H.pylori),and diabetes mellitus among females than males(P<0.001).Trend analysis showed an increasing prevalence of alcohol use disorder and a decreasing prevalence of H.pylori and diabetes mellitus among women(P<0.001).CONCLUSION The prevalence of BE among women has steadily increased from 2009 to 2019.The existing knowledge concerning BE development has historically focused on men,but our findings show that the risk in women is not insignificant.

Provenance of Coloured Gemstones-Availability,Testing Methods,Future Trends

Gemstones have fascinated mankind forever,and people traveled far to find them.The Silk Road is one of the most traditional trade routes in the middle ages that was used to bring the precious stones to the European market.Later,emeralds from Colombia were shipped via the ocean to the Old World.

从Google Trends看“一带一路”倡议的国际反响

[目的/意义]2013年中国提出“一带一路”倡议,这对推动我国继续繁荣发展并为全球提供中国治理体系方案等具有重大意义。[方法/过程]利用Google Trends,分析中国“一带一路”倡议的国际反响及其潜在阻碍因子。[结果/结论]“一带一路”倡议受到国际上绝大多数国家民众的支持和关注;个别国家为了压制中国的国际影响力,通过“债务陷阱外交”“珍珠链战略”以及环境问题等方面抹黑“一带一路”,行动上提出“重建更好世界”等企图替代中国的“一带一路”倡议。得益于“一带一路”倡议投资没有附加条件以及G7国家内部自身问题,“一带一路”倡议仍然获得了广大第三世界国家的支持,并将继续是推动世界经济发展的重要力量。

A method to predict rockburst using temporal trend test and its application

Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integrating the Mann-Kendall trend test(MKT)and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards.The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts.The MKT is then applied to analyze the real-time trend of each index,with adherence to rockburst characterization laws serving as the warning criterion.By employing a confusion matrix,the warning effectiveness of each index is assessed,enabling index preference determination.Ultimately,the integrated rockburst hazard index Q is derived through data fusion.The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q,surpassing the performance of any individual index.Moreover,the model’s adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data,making it suitable for complex underground working environments.By providing an efficient and accurate basis for decision-making,the proposed model holds great potential for the prevention and control of rockbursts.It offers a valuable tool for enhancing safety measures in underground mining operations.

Failure characterization of fully grouted rock bolts under triaxial testing

Confining stresses serve as a pivotal determinant in shaping the behavior of grouted rock bolts.Nonetheless,prior investigations have oversimplified the three-dimensional stress state,primarily assuming hydrostatic stress conditions.Under these conditions,it is assumed that the intermediate principal stress(σ_(2))equals the minimum principal stress(σ_(3)).This assumption overlooks the potential variations in magnitudes of in situ stress conditions along all three directions near an underground opening where a rock bolt is installed.In this study,a series of push tests was meticulously conducted under triaxial conditions.These tests involved applying non-uniform confining stresses(σ_(2)≠σ_(3))to cubic specimens,aiming to unveil the previously overlooked influence of intermediate principal stresses on the strength properties of rock bolts.The results show that as the confining stresses increase from zero to higher levels,the pre-failure behavior changes from linear to nonlinear forms,resulting in an increase in initial stiffness from 2.08 kN/mm to 32.51 kN/mm.The load-displacement curves further illuminate distinct post-failure behavior at elevated levels of confining stresses,characterized by enhanced stiffness.Notably,the peak load capacity ranged from 27.9 kN to 46.5 kN as confining stresses advanced from σ_(2)=σ_(3)=0 to σ_(2)=20 MPa and σ_(3)=10 MPa.Additionally,the outcomes highlight an influence of confining stress on the lateral deformation of samples.Lower levels of confinement prompt overall dilation in lateral deformation,while higher confinements maintain a state of shrinkage.Furthermore,diverse failure modes have been identified,intricately tied to the arrangement of confining stresses.Lower confinements tend to induce a splitting mode of failure,whereas higher loads bring about a shift towards a pure interfacial shear-off and shear-crushed failure mechanism.

Unbound^(28)O,the heaviest oxygen isotope observed:a cutting-edge probe for testing nuclear models

The beyond-dripline oxygen isotopes^(27,28)O were recently observed at RIKEN,and were found to be unbound decaying into^(24)O by emitting neutrons.The unbound feature of the heaviest oxygen isotope,^(28)O,provides an excellent test for stateof-the-art nuclear models.The atomic nucleus is a self-organized quantum manybody system comprising specific numbers of protons Z and neutrons N.

Human brain organoid:trends,evolution,and remaining challenges

Advanced brain organoids provide promising platforms for deciphering the cellular and molecular processes of human neural development and diseases.Although various studies and reviews have described developments and advancements in brain organoids,few studies have comprehensively summarized and analyzed the global trends in this area of neuroscience.To identify and further facilitate the development of cerebral organoids,we utilized bibliometrics and visualization methods to analyze the global trends and evolution of brain organoids in the last 10 years.First,annual publications,countries/regions,organizations,journals,authors,co-citations,and keywords relating to brain organoids were identified.The hotspots in this field were also systematically identified.Subsequently,current applications for brain organoids in neuroscience,including human neural development,neural disorders,infectious diseases,regenerative medicine,drug discovery,and toxicity assessment studies,are comprehensively discussed.Towards that end,several considerations regarding the current challenges in brain organoid research and future strategies to advance neuroscience will be presented to further promote their application in neurological research.

Big Data Testing Techniques:Taxonomy,Challenges and Future Trends

Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes.Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data.However,because of the diversity and complexity of data,testing Big Data is challenging.Though numerous research efforts deal with Big Data testing,a comprehensive review to address testing techniques and challenges of BigData is not available as yet.Therefore,we have systematically reviewed the Big Data testing techniques’evidence occurring in the period 2010–2021.This paper discusses testing data processing by highlighting the techniques used in every processing phase.Furthermore,we discuss the challenges and future directions.Our findings show that diverse functional,non-functional and combined(functional and non-functional)testing techniques have been used to solve specific problems related to Big Data.At the same time,most of the testing challenges have been faced during the MapReduce validation phase.In addition,the combinatorial testing technique is one of the most applied techniques in combination with other techniques(i.e.,random testing,mutation testing,input space partitioning and equivalence testing)to find various functional faults through Big Data testing.

Trend Analysis of HIV Testing Services in Zimbabwe, 2007-2016: A Secondary Dataset Analysis

Background: HIV Testing Services (HTS) is a full range of services (e.g. counselling and post-test referrals) that are offered together with HIV testing. It is an important prevention strategy and the gateway to treatment. The national targets in 2016 were to test 1.1 million people of which 54% was achieved. We determined trends of HTS in Zimbabwe from 2007 to 2016. Methods: A secondary dataset analysis was conducted using National Aids Council Core-Output Indicators dataset. Variables captured include total and repeat tests, counselling and referrals. Microsoft excel and Epi Info was used to generate frequencies, percentages and conduct chi square test for trends. Panda-Class Libraries was to attain estimates of HTS uptake till 2020. We used χ2 and p-values for statistical significance. Results: All (10,847.223) records were analysed. HIV tests per year increased from 340,705 in 2007, to 1,974,795 in 2015 (χ2 0.10492, p-value 0.74615). In 2007, 31% (n = 106,884) clients tested positive whilst in 2016 only 7% (n = 121,196) were positive (χ2 0.01166, p-value 0.91402). The 25 - 49 year age-group tested consistently highest throughout the 10year period (χ2 0.0558 p-value 0.813). The 15 - 24 year age-group had the highest yield (11% in 2015). Females (χ2 0.1074, p-value 0.743) consistently tested higher than males (χ2 0.0614, p-value 0.804). From 2007 to 2013 women had higher yields but by September 2016 males had a higher positivity of 8% (p-value χ2 0.658 p-value = 0.417). We estimate that 179,935 people living with HIV will know their status by 2020. Conclusion: HIV tests in Zimbabwe have increased but yield has decreased. Increase in repeat tests may be an indication of exhaustion of particular HTS strategies. Following this analysis it was recommended that HTS utilize various models such as HIV self-test to cater for populations with high yields.

Electrochemical biosensors for point-of-care testing

Point-of-care testing(POCT)is the practice of diagnosing and monitoring diseases where the patient is located,as opposed to traditional treatment conducted solely in a medical laboratory or other clinical setting.POCT has been less common in the recent past due to a lack of portable medical devices capable of facilitating effective medical testing.However,recent growth has occurred in this field due to advances in diagnostic technologies,device miniaturization,and progress in wearable electronics.Among these developments,electrochemical sensors have attracted interest in the POCT field due to their high sensitivity,compact size,and affordability.They are used in various applications,from disease diagnosis to health status monitoring.In this paper we explore recent advancements in electrochemical sensors,the methods of fabricating them,and the various types of sensing mechanisms that can be used.Furthermore,we delve into methods for immobilizing specific biorecognition elements,including enzymes,antibodies,and aptamers,onto electrode surfaces and how these sensors are used in real-world POCT settings.

Communicative Testing:A Trend of Modern EFL Testing

Communicative testing, with its purpose of measuring communicative competence, has brought changes to the current EFL tests in content and format and produced a widespread and profound influence on modern language testing models in the two decades. This paper gives a brief introduction to the development of communicative testing, and presents the trend of modern EFL testing in the aspects of oral test, proportion of subjective and objective items, content, context, incorporation of skills as well as criteria of assessment, which is the result of enlightenment of communicative testing theories.

Micromechanical testing and property upscaling of planetary rocks:A critical review

Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representative samples for conventional macroscale rock mechanics experiments(macro-RMEs).This critical review discusses recent advances in microscale RMEs(micro-RMEs)techniques and the upscaling methods for extracting mechanical parameters.Methods of mineralogical and microstructural analyses,along with non-destructive mechanical techniques,have provided new opportunities for studying planetary rocks with unprecedented precision and capabilities.First,we summarize several mainstream methods for obtaining the mineralogy and microstructure of planetary rocks.Then,nondestructive micromechanical testing methods,nanoindentation and atomic force microscopy(AFM),are detailed reviewed,illustrating the principles,advantages,influencing factors,and available testing results from literature.Subsequently,several feasible upscaling methods that bridge the micro-measurements of meteorite pieces to the strength of the intact body are introduced.Finally,the potential applications of planetary rock mechanics research to guiding the design and execution of space missions are environed,ranging from sample return missions and planetary defense to extraterrestrial construction.These discussions are expected to broaden the understanding of the microscale mechanical properties of planetary rocks and their significant role in deep space exploration.

Effects of temperature and precipitation on drought trends in Xinjiang, China

The characteristics of drought in Xinjiang Uygur Autonomous Region(Xinjiang),China have changed due to changes in the spatiotemporal patterns of temperature and precipitation,however,the effects of temperature and precipitation—the two most important factors influencing drought—have not yet been thoroughly explored in this region.In this study,we first calculated the standard precipitation evapotranspiration index(SPEI)in Xinjiang from 1980 to 2020 based on the monthly precipitation and monthly average temperature.Then the spatiotemporal characteristics of temperature,precipitation,and drought in Xinjiang from 1980 to 2020 were analyzed using the Theil-Sen median trend analysis method and Mann-Kendall test.A series of SPEI-based scenario-setting experiments by combining the observed and detrended climatic factors were utilized to quantify the effects of individual climatic factor(i.e.,temperature and precipitation).The results revealed that both temperature and precipitation had experienced increasing trends at most meteorological stations in Xinjiang from 1980 to 2020,especially the spring temperature and winter precipitation.Due to the influence of temperature,trends of intensifying drought have been observed at spring,summer,autumn,and annual scales.In addition,the drought trends in southern Xinjiang were more notable than those in northern Xinjiang.From 1980 to 2020,temperature trends exacerbated drought trends,but precipitation trends alleviated drought trends in Xinjiang.Most meteorological stations in Xinjiang exhibited temperature-dominated drought trend except in winter;in winter,most stations exhibited precipitation-dominated wetting trend.The findings of this study highlight the importance of the impact of temperature on drought in Xinjiang and deepen the understanding of the factors influencing drought.

C-CORE:Clustering by Code Representation to Prioritize Test Cases in Compiler Testing

Edge devices,due to their limited computational and storage resources,often require the use of compilers for program optimization.Therefore,ensuring the security and reliability of these compilers is of paramount importance in the emerging field of edge AI.One widely used testing method for this purpose is fuzz testing,which detects bugs by inputting random test cases into the target program.However,this process consumes significant time and resources.To improve the efficiency of compiler fuzz testing,it is common practice to utilize test case prioritization techniques.Some researchers use machine learning to predict the code coverage of test cases,aiming to maximize the test capability for the target compiler by increasing the overall predicted coverage of the test cases.Nevertheless,these methods can only forecast the code coverage of the compiler at a specific optimization level,potentially missing many optimization-related bugs.In this paper,we introduce C-CORE(short for Clustering by Code Representation),the first framework to prioritize test cases according to their code representations,which are derived directly from the source codes.This approach avoids being limited to specific compiler states and extends to a broader range of compiler bugs.Specifically,we first train a scaled pre-trained programming language model to capture as many common features as possible from the test cases generated by a fuzzer.Using this pre-trained model,we then train two downstream models:one for predicting the likelihood of triggering a bug and another for identifying code representations associated with bugs.Subsequently,we cluster the test cases according to their code representations and select the highest-scoring test case from each cluster as the high-quality test case.This reduction in redundant testing cases leads to time savings.Comprehensive evaluation results reveal that code representations are better at distinguishing test capabilities,and C-CORE significantly enhances testing efficiency.Across four datasets,C-CORE increases the average of the percentage of faults detected(APFD)value by 0.16 to 0.31 and reduces test time by over 50% in 46% of cases.When compared to the best results from approaches using predicted code coverage,C-CORE improves the APFD value by 1.1% to 12.3% and achieves an overall time-saving of 159.1%.

Bibliometric analysis of hotspots and trends of global myopia research

AIM:To gain insights into the global research hotspots and trends of myopia.METHODS:Articles were downloaded from January 1,2013 to December 31,2022 from the Science Core Database website and were mainly statistically analyzed by bibliometrics software.RESULTS:A total of 444 institutions in 87 countries published 4124 articles.Between 2013 and 2022,China had the highest number of publications(n=1865)and the highest H-index(61).Sun Yat-sen University had the highest number of publications(n=229)and the highest H-index(33).Ophthalmology is the main category in related journals.Citations from 2020 to 2022 highlight keywords of options and reference,child health(pediatrics),myopic traction mechanism,public health,and machine learning,which represent research frontiers.CONCLUSION:Myopia has become a hot research field.China and Chinese institutions have the strongest academic influence in the field from 2013 to 2022.The main driver of myopic research is still medical or ophthalmologists.This study highlights the importance of public health in addressing the global rise in myopia,especially its impact on children’s health.At present,a unified theoretical system is still needed.Accurate surgical and therapeutic solutions must be proposed for people with different characteristics to manage and intervene refractive errors.In addition,the benefits of artificial intelligence(AI)models are also reflected in disease monitoring and prediction.

Analysis of the spatiotemporal trends and influencing factors of Hyphantria cunea in China

In recent years,the situation of the Hyphantria cunea(Drury)(Lepidoptera:Erebidae),infestation in China has been serious and has a tendency to continue to spread.A comprehensive analysis was carried out to examine the spa-tial distribution trends and influencing factors of H.cunea.This analysis involved integrating administrative division and boundary data,distribution data of H.cunea,and envi-ronmental variables for 2021.GeoDetector and gravity analysis techniques were employed for data processing and interpretation.The results show that H.cunea exhibited high aggregation patterns in 2021 and 2022 concentrated mainly in eastern China.During these years,the focal point of the infestation was in Shandong Province with a spread towards the northeast.Conditions such as high vegetation density in eastern China provided favorable situations for growth and development of H.cunea.In China,the spatial distribution of the moth is primarily influenced by two critical factors:precipitation during the driest month and elevation.These play a pivotal role in determining the spread of the species.Based on these results,suggestions are provided for a mul-tifaceted approach to prevention and control of H.cunea infestation.

Data-enhanced revealing of trends in Geoscience

Purpose:This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023.By integrating bibliometric analysis with expert insights from the Deep-time Digital Earth(DDE)initiative,this article identifies key emerging themes shaping the landscape of Earth Sciences①.Design/methodology/approach:The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database.To map relationships between articles,citation networks were constructed,and spectral clustering algorithms were then employed to identify groups of related research,resulting in 407 clusters.Relevant research terms were extracted using the Log-Likelihood Ratio(LLR)algorithm,followed by statistical analyses on the volume of papers,average publication year,and average citation count within each cluster.Additionally,expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation,relevance,and impact within Geosciences,and finalize naming of these top trends with consideration of the content and implications of the associated research.This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists.Findings:Thirty significant trends were identified in the field of Geosciences,spanning five domains:deep space,deep time,deep Earth,habitable Earth,and big data.These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society,science,and technology.Research limitations:The analyzed data of this study only contain those were included in the Web of Science.Practical implications:This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science,especially on solid earth.The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study.Originality/value:This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.

Field testing of shear strength of granite residual soils

The characteristics of residual soils are very different from those of sedimentary soils.Although the strength characteristics of sedimentary soils have been studied extensively,the shear strength characteristics of granitic residual soils(GRS)subjected to the weathering of parent rocks have rarely been investigated.In this study,the shear strength characteristics of GRS in the Taishan area of southeast China(TSGRS)were studied by field and laboratory tests.The field tests consisted of a cone penetration test(CPT),borehole shear test(BST),self-boring pressuremeter test(SBPT),and seismic dilatometer Marchetti test(SDMT).The shortcomings of laboratory testing are obvious,with potential disturbances arising through the sampling,transportation,and preparation of soil samples.Due to the special structure of GRS samples and the ease of disturbance,the results obtained from laboratory tests were generally lower than those obtained from situ tests.The CPT and scanning electron microscopy(SEM)results indicated significant weathering and crustal hardening in the shallow TSGRS.This resulted in significant differences in the strength and strength parameters of shallow soil obtained by the BST.Based on the SDMT and SBPT results,a comprehensive evaluation method of shear strength for TSGRS was proposed.The SBPT was suitable for evaluating the strength of shallow GRS.The material index(ID)and horizontal stress index(KD)values obtained by the SDMT satisfied the empirical relationship proposed by Marchetti based on the ID index,and were therefore considered suitable for the evaluation of the shear strength of deep GRS.

Global Scientific Trends in Research Related to Diabetic Sarcopenia from 1993 to 2023: A Bibliometric Analysis

Objectives: In this study, bibliometric approach was used to explore the literature in the field of research related to Diabetic Myasthenia Gravis in order to identify the current research progress in Diabetic Myasthenia Gravis related research and to help the researchers to predict the future hotspots in the field of research and to provide reference for the research. Methods: Literature related to diabetic sarcopenia published from 1993 to 2023 since the inception of the repository was extracted from the Web of Science Core Collection (WoSCC) and bibliometric analyses were performed. We have analysed the published literature of the last approximately almost 30 years, as well as publication and citation analyses from different countries, institutions, journals and authors. For keywords, we performed co-occurrence, clustering, timeline view and citation burst analysis. Results: On the basis of 1564 publications, we found a continuous increase in the number of publications and citations, especially in the last six years. The United States is the most representative country, and Seoul National University (SNU) is the most representative institution. The most popular journal in the field is Diabetes Care;Fukui, Michiaki is the most prolific author, leading many studies related to diabetic sarcopenia. The most frequently cited reference was a revised European consensus on the definition and diagnosis of sarcopenia;the most cited keywords were related to physiological factors of diabetes, sarcopenia and related conditions, such as “insulin resistance”, “skeletal muscle”, “body composition”, “risk” and “prevalence”. Conclusion: With more and more studies on the relationship between diabetic sarcopenia, this study presents the current status and trend of research related to diabetic sarcopenia over the past nearly 30 years through the visualization software CiteSpace. It can help researchers identify potential collaborators and partner institutions, hotspots and research frontiers in the field of diabetic sarcopenia. However, our work is only based on the English language literature in the WoSCC database, and for future studies, we recommend that researchers explore the literature from multiple databases to enhance the scope of their research.

Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.