Analysis of the causes of primary revision after unicompartmental knee arthroplasty: A case series

BACKGROUND Unicompartmental knee arthroplasty(UKA)has great advantages in the treatment of unicompartmental knee osteoarthritis,but its revision rate is higher than that of total knee arthroplasty.AIM To summarize and analyse the causes of revision after UKA.METHODS This is a retrospective case series study in which the reasons for the first revision after UKA are summarized.We analysed the clinical symptoms,medical histories,laboratory test results,imaging examination results and treatment processes of the patients who underwent revision and summarized the reasons for primary revision after UKA.RESULTS A total of 13 patients,including 3 males and 10 females,underwent revision surgery after UKA.The average age of the included patients was 67.62 years.The prosthesis was used for 3 d to 72 months.The main reasons for revision after UKA were improper suturing of the surgical opening(1 patient),osteophytes(2 patients),intra-articular loose bodies(2 patients),tibial prosthesis loosening(2 patients),rheumatoid arthritis(1 patient),gasket dislocation(3 patients),anterior cruciate ligament injury(1 patient),and medial collateral ligament injury with residual bone cement(1 patient).CONCLUSION The causes of primary revision after UKA were gasket dislocation,osteophytes,intra-articular loose bodies and tibial prosthesis loosening.Avoidance of these factors may greatly reduce the rate of revision after UKA,improve patient satisfaction and reduce medical burden.

Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation

The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios.

Characteristics and Preliminary Causes of Tropical Cyclone Remote Precipitation over China

In this study,the characteristics and preliminary causes of tropical cyclone remote precipitation(TRP)over China during the period from 1979 to 2020 are investigated.Results indicated that approximately 72.42%of tropical cyclones(TCs)in the Western Pacific produce TRP over China.The peak months for TRP are July and August.The four key regions of TRP are the adjacent areas between the Sichuan and Shaanxi Provinces,the northern coast of the Bohai Sea,the coast of the Yellow Sea,and the southern coast area.The typical distance between the station with TRP and the TC center ranges from 1500 to 2500 km.Most of these stations are situated north to 60°west of north of the TC.The south–west water vapor transportation on the west side of the TC is crucial to TRP.TRP has a decreasing trend because of the decrease in the number of TCs that generate TRP.From the perspective of large-scale environmental conditions,a decrease in the integrated horizontal water vapor transport in China' Mainland,the weakening of upward motion at approximately 25°–35°N,which is inconducive to convection,and an increase in low-level vertical wind shear,which is unfavorable for the development of TC in areas with high frequencies of TRP-related TCs,are the factors that result in the decreasing trend of TRP.

Influence of Production Factors on the Physico-Chemical Characteristics of Fermented Cassava Dough and Sensory Evaluation of Attieke

Attieke is an Ivorian semolina which obtained by fermenting, pressing and steaming cassava dough. Attieke production remains a traditional activity carried out by less literate women. However, perceived differences in measurable factors and attieke qualities require an investigation of their influence on the characteristics of the pressed dough and attieke. The aim of this study is to improve the quality of the dough in relation to that of the attieke produced. The experiment was carried out on 4 production factors, namely the type of boiled or braised ferment, the incorporation rate of the ferment between 8 and 10%, the addition of oil from 0.1 to 1% and the fermentation time from 12 to 15 hours applied to the Improved African Cassava (IAC) variety. A complete experiment design of 16 samples of fermented dough and attieke was employed. These samples underwent physic-chemical analyses for the fermented dough and sensory evaluation for the attieke. It was found that, except for titratable acidity, reducing sugar content and ash content, the physico-chemical characteristics of the dough of IAC variety were significantly influenced by all production factors and their interaction. Fermentation time significantly influences 60% of the physico-chemical characteristics of the fermented dough. The type of ferment, the oil addition and the ferment rate have a significant influence at 40% of these characteristics. At the sensory level, color, acidity and grain binding with an explained variance of 34.60% were essential for the appreciation of the attieke samples. Thus, these production factors could be considered for the improvement of the fermented dough and attieke production process.

Ascertaining the influences of auxiliary qubits on the Einstein–Podolsky–Rosen steering and its directions

Einstein–Podolsky–Rosen(EPR) steering is an example of nontrivial quantum nonlocality and characteristic in the non-classical world.The directivity(or asymmetry) is a fascinating trait of EPR steering,and it is different from other quantum nonlocalities.Here,we consider the strategy in which two atoms compose a two-qubit X state,and the two atoms are owned by Alice and Bob,respectively.The atom of Alice suffers from a reservoir,and the atom of Bob couples with a bit flip channel.The influences of auxiliary qubits on EPR steering and its directions are revealed by means of the entropy uncertainty relation.The results indicate that EPR steering declines with growing time t when adding fewer auxiliary qubits.The EPR steering behaves as damped oscillation when introducing more auxiliary qubits in the strong coupling regime.In the weak coupling regime,the EPR steering monotonously decreases as t increases when coupling auxiliary qubits.The increases in auxiliary qubits are responsible for the fact that the steerability from Alice to Bob(or from Bob to Alice) can be more effectively revealed.Notably,the introductions of more auxiliary qubits can change the situation that steerability from Alice to Bob is certain to a situation in which steerability from Bob to Alice is certain.

A Problem Not to Be Ignored: The Influencing Factors of Mobile Phone Addiction and Its Influence on Sleep Quality

Background and Objective: With the popularity and widespread use of mobile phones, the effects of mobile phone dependence and addiction on individuals’ physical and mental health have attracted more and more attention. The present study aims to analyze the current state of mobile phone addiction and its impact on sleep quality within the population, while also exploring the influence of related factors on sleep quality. Ultimately, this research will provide a scientific foundation for targeted intervention measures and strategies. Methods: A total of 253 permanent residents in Nanjing were randomly selected as study subjects. The Mobile Phone Addiction Index (MPAI) and Pittsburgh Sleep Quality Index (PSQI) were used to evaluate the degree of smartphone addiction and sleep quality of the study subjects. Body mass index (BMI) was measured according to standardized procedures. Independent sample t-test, Chi-square test, rank sum test and multiple linear regression were used to analyze the correlation between mobile phone addiction and sleep quality, and P Results: 117 people (46.2%) were addicted to mobile phones. Chi-square test showed that the rate of mobile phone addiction in drinking group was significantly higher than that in non-drinking group (P P P P P P P P P P Conclusion: Mobile phone addiction may lead to shorter sleep duration and reduce sleep efficiency. The withdrawal of mobile phone addiction may have a negative impact on sleep quality. According to the characteristics of the population, appropriate comprehensive intervention measures should be taken to build an effective evaluation system, so as to reduce the impact of mobile phone addiction and withdrawal problems on sleep and improve sleep quality.

Influencer identification of dynamical networks based on an information entropy dimension reduction method

Identifying critical nodes or sets in large-scale networks is a fundamental scientific problem and one of the key research directions in the fields of data mining and network science when implementing network attacks, defense, repair and control.Traditional methods usually begin from the centrality, node location or the impact on the largest connected component after node destruction, mainly based on the network structure.However, these algorithms do not consider network state changes.We applied a model that combines a random connectivity matrix and minimal low-dimensional structures to represent network connectivity.By using mean field theory and information entropy to calculate node activity,we calculated the overlap between the random parts and fixed low-dimensional parts to quantify the influence of node impact on network state changes and ranked them by importance.We applied this algorithm and the proposed importance algorithm to the overall analysis and stratified analysis of the C.elegans neural network.We observed a change in the critical entropy of the network state and by utilizing the proposed method we can calculate the nodes that indirectly affect muscle cells through neural layers.

Prevalence and Causes of Neonatal Mortality at Chu-Mel, Cotonou in 2023

Introduction: Neonatal mortality represents a global health problem that has been at the core of programs developed by the World Health Organization (WHO) for more than 30 years. In our country, it represents a real scourge and remains high despite the efforts made by the Ministry of Health. The goal of this study was to investigate the prevalence and causes of neonatal mortality at CHU-MEL of Cotonou in 2023. Material and Methods: This was a cross-sectional and descriptive study with retrospective data collection, carried out in the neonatology unit of the Mother and Child Teaching Hospital of Lagune (CHU-MEL) in Cotonou over a period of six months from January 1, 2023 to June 30, 2023. All neonates, premature or full-term, born alive and who died during hospitalization in the unit were included. Results: 211 cases of neonatal deaths were recorded among the 2884 neonates hospitalized in the unit during the study period, representing a hospital prevalence of 7.31%. Early neonatal mortality represented 81.5% of cases. The average age at admission was 4.6 days ± 5.3. The average weight of deceased neonates was 1609.08 ± 798.35 g. The most frequent reasons for hospitalization were represented by prematurity (60.66%) and respiratory distress (23.22%), respectively. Prematurity was the leading cause of neonatal mortality (41.7%), followed by neonatal infections (29.4%) and perinatal asphyxia (10.9%). Conclusion: The prevalence of neonatal mortality in the neonatology unit of CHU-MEL is high. Efforts to improve the quality of perinatal care departments must be intensified to reduce this prevalence.

Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content recommen-dations.Social relationship-based methods represent a classical approach for geolocating social media.However,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user geolocation.To address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation accuracy.Firstly,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among users.There are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate users.Exploiting this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social network.To better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure influence.The algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation performance.Experimental results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social relationships.Moreover,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.

CRB:A new rumor blocking algorithm in online social networks based on competitive spreading model and influence maximization

The virtuality and openness of online social platforms make networks a hotbed for the rapid propagation of various rumors.In order to block the outbreak of rumor,one of the most effective containment measures is spreading positive information to counterbalance the diffusion of rumor.The spreading mechanism of rumors and effective suppression strategies are significant and challenging research issues.Firstly,in order to simulate the dissemination of multiple types of information,we propose a competitive linear threshold model with state transition(CLTST)to describe the spreading process of rumor and anti-rumor in the same network.Subsequently,we put forward a community-based rumor blocking(CRB)algorithm based on influence maximization theory in social networks.Its crucial step is to identify a set of influential seeds that propagate anti-rumor information to other nodes,which includes community detection,selection of candidate anti-rumor seeds and generation of anti-rumor seed set.Under the CLTST model,the CRB algorithm has been compared with six state-of-the-art algorithms on nine online social networks to verify the performance.Experimental results show that the proposed model can better reflect the process of rumor propagation,and review the propagation mechanism of rumor and anti-rumor in online social networks.Moreover,the proposed CRB algorithm has better performance in weakening the rumor dissemination ability,which can select anti-rumor seeds in networks more accurately and achieve better performance in influence spread,sensitivity analysis,seeds distribution and running time.

Microbiologically influenced corrosion resistance enhancement of coppercontaining high entropy alloy FexCu(1−x)CoNiCrMn against Pseudomonas aeruginosa

To enhance the microbiologically influenced corrosion(MIC)resistance of FeCoNiCrMn high entropy alloy(HEAs),a series of Fe_(x)Cu_((1−x))CoNiCrMn(x=1,0.75,0.5,and 0.25)HEAs were prepared.Microstructural characteristics,corrosion behavior(morphology observation and electrochemical properties),and antimicrobial performance of Fe_(x)Cu_((1−x))CoNiCrMn HEAs were evaluated in a medium inoculated with typical corrosive microorganism Pseudomonas aeruginosa.The aim was to identify copper-containing FeCoNiCrMn HEAs that balance corrosion resistance and antimicrobial properties.Results revealed that all Fe_(x)Cu_((1−x))CoNiCrMn(x=1,0.75,0.5,and 0.25)HEAs exhibited an FCC(face centered cubic)phase,with significant grain refinement observed in Fe_(0.75)Cu_(0.25)CoNiCrMn HEA.Electrochemical tests indicated that Fe_(0.75)Cu_(0.25)CoNiCrMn HEA demonstrated lower corrosion current density(i_(corr))and pitting potential(E_(pit))compared to other Fe_(x)Cu_((1−x))CoNiCrMn HEAs in P.aeruginosa-inoculated medium,exhibiting superior resistance to MIC.Anti-microbial tests showed that after 14 d of immersion,Fe_(0.75)Cu_(0.25)CoNiCrMn achieved an antibacterial rate of 89.5%,effectively inhibiting the adhesion and biofilm formation of P.aeruginosa,thereby achieving resistance to MIC.

Distribution and Formation Causes of PM_(2.5) and O_(3) Double High Pollution Events in China during 2013–20

Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely clear.In this study,the spatiotemporal distribution of DHP events in China during 2013–20 is analyzed.The synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification method.The meteorological and chemical causes of DHP events controlled by the main synoptic types are further investigated.Results show that DHP events(1655 in total for China during 2013–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central China.The occurrence frequency increases by 5.1%during 2013–15,and then decreases by 56.1%during 2015–20.The main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1℃)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1200 LST,Local Standard Time=UTC+8 hours)and O_(3)(1500–2100 LST)to exceed the national standards at different periods of the DHP day.Three pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 13.1%,4.7%and 4.4%,respectively.The results of this study can be informative for future decisions on the management of DHP events.

Influence of hypocalcemia on the prognosis of patients with multiple trauma

BACKGROUND Hypocalcemia is highly common in hospitalized patients,especially in those with trauma,On the other hand,abnormal calcium metabolism is an important metabolic challenge;however,it is often neglected and untreated,and certain factors may induce serious neurological and cardiovascular complications.AIM To retrospectively analyze the impact of hypocalcemia on the prognosis of patients with multiple traumas.METHODS The study was conducted from January 2020 to December 2021.Ninety-nine patients with multiple injuries were treated at the critical care medicine department of Fuyang People’s Hospital.The selected indicators included sex,age,and blood calcium and hematocrit levels.Many indicators were observed,including within 24 h of hospitalization,and the prognosis was collected after 28 d.Based on the blood calcium levels,the patients were divided into the following two groups:Normocalcemia and hypocalcemia.Of the 99 patients included,81 had normocalcemia,and 18 had hypocalcemia.Separate experiments were conducted for these two groups.RESULTS There was an association between serum calcium levels and the prognosis of patients with polytrauma.CONCLUSION Clinically,the prognosis of patients with multiple traumas can be preliminarily evaluated based on serum calcium levels.

The Influence of Airflow Transport Pathways on Precipitation during the Rainy Season in the Liupan Mountains of Northwest China

This study investigates the influence of airflow transport pathways on seasonal rainfall in the mountainous region of the Liupan Mountains(LM) during the rainy seasons from 2020 to 2022, utilizing observational data from seven ground gradient stations located on the eastern slopes, western slopes, and mountaintops combined with backward trajectory cluster analysis. The results indicate 1) that the LM's rainy season, characterized by overcast and rainy days, is mainly influenced by cold and moist airflows(CMAs) from the westerly direction and warm and moist airflows(WMAs) from a slightly southern direction. The precipitation amounts under four airflow transport paths are ranked from largest to smallest as follows: WMAs, CMAs, warm dry airflows(WDAs), and cold dry airflows(CDAs). 2) WMAs contribute significantly more to the intensity of regional precipitation than the other three types of airflows. During localized precipitation events,warm airflows have higher precipitation intensities at night than cold airflows, while the opposite is true during the afternoon. 3) During regional precipitation events, water vapor content is the primary influencing factor. Precipitation characteristics under humid airflows are mainly affected by high water vapor content, whereas during dry airflow precipitation, dynamic and thermodynamic factors have a more pronounced impact. 4) During localized precipitation events, the influence of dynamic and thermodynamic factors is more complex than during regional precipitation, with the precipitation characteristics of the four airflows closely related to their water vapor content, air temperature and humidity attributes, and orographic lifting. 5) Compared to regional precipitation, the influence of topography is more prominent in localized precipitation processes.

Influence of transcatheter arterial embolization on symptom distress and fatigue in liver cancer patients

BACKGROUND Hepatocellular carcinoma(HCC)is a prevalent malignancy,and transcatheter arterial embolization(TAE)has emerged as a pivotal therapeutic modality.How-ever,TAE may induce symptom distress and fatigue,adversely affecting the quality of life of patients.AIM To investigate symptom distress,fatigue,and associated factors in HCC patients undergoing TAE.METHODS We used a cross-sectional design and purposive sampling to enroll HCC patients who underwent TAE at our institution from January to December 2022.Question-naires were utilized to collect data on symptom distress and fatigue scores from the first to the third day after TAE.RESULTS Our study revealed a significant reduction in fatigue and symptom distress among patients after TAE.Pain,fatigue,insomnia,fever and abdominal dis-tension were the most common symptoms troubling patients during the first 3 d post-TAE.Marital status,presence of family support,physical functional status,age,and symptom distress were identified as predictors of fatigue in patients.CONCLUSION Healthcare professionals should educate HCC patients on symptom distress and INTRODUCTION Hepatocellular carcinoma(HCC)ranks as the fifth most prevalent cancer and the third leading cause of cancer-related mortality globally.Surgical intervention remains the cornerstone of HCC treatment;however,due to the challenges associated with early diagnosis and the lack of specific diagnostic markers,a considerable proportion of patients are diagnosed at advanced stages,rendering them ineligible for surgical interventions.Transcatheter arterial embolization(TAE)is an interventional therapeutic approach involving the insertion of a fine catheter via the femoral artery to reach the vasculature near the tumor site.TAE aims to obstruct the arterial supply to the tumor by deploying embolic agents,thereby inducing necrosis in cancer cells.This procedure is suitable for patients with good liver function and overall health,particularly those with large HCCs that have not invaded the portal vein[1,2].Nonetheless,following TAE,hepatocytes incur variable degrees of damage,leading to the development of a constel-lation of symptoms reminiscent of acute hepatitis.These symptoms include fatigue and systemic discomfort,such as nausea,vomiting,fever,abdominal pain,as well as transient elevations in aspartate aminotransferase(AST)and alanine aminotransferase(ALT),collectively referred to as postembolization syndrome[3,4].These symptoms may arise due to ischemia of the liver and gallbladder,temporary liver enlargement,and peritoneal irritation.While many studies have explored fatigue and symptom distress in cancer patients both nationally and internationally,with some focusing on symptom distress following transcatheter arterial chemoembolization,there has been limited in-depth investigation into the fatigue and symptom distress resulting from TAE treatment[5-8].Fatigue and pain are both subjective experiences,typically arising from the gradual depletion of energy reserves during the course of illness[9].Fatigue is particularly prevalent among cancer patients,with rates soaring as high as 90%.Despite extensive research exploring cancer-related fatigue and its influencing factors,a unanimous consensus remains elusive.Hence,the primary objective of this study was to investigate the symptom distress and fatigue experienced by liver cancer patients following TAE treatment and to analyze potential contributing factors.

The Impacts and Causes of Land Fragmentation on Farm Productivity: Case Review of East African Countries

This report provides an overall assessment of land fragmentation problems in East Africa. Many parts of East Africa have become highly fragmented, putting development systems and activities in these areas at risk of complete collapse. Land fragmentation occurs when land gets converted for agriculture, industrialization, or urbanization, invaded by non-local plants, or enclosed for individual use and by subdividing farmlands into subsequent smaller units called parcels with varying average farm sizes. Fragmentation results from inappropriate agricultural development processes and ineffective land use planning that fails to recognize how farmland is used, and the importance of its interconnected areas. Insecurity of tenure and resource rights are key factors in making this possible. Land fragmentation is one of the key reasons why the ability of most resources in East Africa becomes scarcer, and those remaining become “privatized” by more powerful community members—keen to maintain their access to them. Such individualistic attitudes are new and disadvantage the poorest even further by affecting the traditional customary safety nets and agricultural outputs. Neither the government nor customary governance systems effectively protect resource access for the poorest. This review summary report identifies the key causes, measures, and implications, government interventions, and the common remedies to land fragmentation problems in the East African Countries of Kenya, Uganda, Rwanda, and Tanzania including neighboring Ethiopia, and the Sudan. The findings indicated from 2005 to 2015, the population kept increasing for all the named countries in East Africa with Rwanda and Uganda having a substantial increase in population density. The study review further explores the trend in the performance of agriculture by average farm sizes within the intervals of five years by highlighting their strong linkages and found that the average farm size has declined drastically, especially for Kenya. This can only mean that small farms kept becoming smaller and smaller and that there were more small-scale farmers. The results further depicted that the major and commonly cultivated food crops among the East African countries include maize, sorghum, rice, cassava, sweet potatoes, bananas, Irish potatoes, beans, peas, etc., with maize yields (Mt/ha) in 2003 for Uganda being the highest (1.79 Mt/ha) and the lowest in Rwanda (0.77 Mt/ha) respectively. Therefore, from the review results, recommendations are being made as to how the negative impacts of land fragmentation on agricultural productivity can be reduced or mitigated. One way is by community sensitization and awareness about the importance of land consolidation and its proposition on farm productivity.

Influence of Blended Course Teaching Reform on Student Satisfaction

With the rapid development of information technology in contemporary times,the blended teaching mode that blends online and offline courses has become an international trend in higher education.Taking blended tourism management courses at Chongqing Three Gorges University as an example,we explored the impact of such teaching reform on student satisfaction based on the SERVPERF model.Empirical analysis of 179 valid questionnaires revealed that five elements of the reform,namely,reliability,assurance,valuableness,responsiveness,and empathy,have a significant positive impact on students’learning satisfaction.Specifically,in the context of blended courses,factors such as a stable and reliable teaching environment,comprehensively guaranteed educational conditions,teaching content that highly aligns with students’demands and value expectations,prompt responses to students’needs and feedback,and empathetic consideration of students’perspectives are critical for enhancing student satisfaction.Based on these conclusions,we propose several strategies and methods for improving the effectiveness of blended teaching in the hope of propelling its continuous improvement and optimization,thus further elevating the quality of higher education.

Spatial distribution characteristics and influence factor analysis of landslides——case study of the Hanwang area in Qinba Mountains

The geological hazards of landslides in Hanwang Town, Ziyang County, Ankang City, Shaanxi Province, have emerged. Yet, the current understanding of the spatial distribution characteristics and influencing factors of landslides in this area remains unclear. Combining the results of remote sensing interpretation and field investigation, seven influencing factors, namely, elevation, slope direction, slope gradient, distance from rivers, distance from faults, engineering geologic lithology, and distance from roads, are selected for the study. The distribution characteristics of landslides in each influencing factor and the influence of the resolution of the Digital Elevation Model(DEM) on the results are statistically and analytically analyzed. Furthermore, two highrisk landslides within the study area were subjected to comprehensive analysis, integrating the findings from drilling and other field investigations in order to examine their deformation mechanisms. Based on this analysis,the following conclusions were derived:(1) 34 landslides in the study area, mainly small earth landslides, with a distribution density of 0.42/km~2, threatening 414 people and property of about 55.87 million Yuan.(2)The landslides in the study area easily occur in the <400 m elevation range;the landslides are developed in all slope directions, the gradient is mainly concentrated in the range of 10°–40°, the distribution density of the landslides is higher in the closer distance from the river and the faults(0–200 m), the landslide-prone strata are mainly the softer and weaker metamorphic rocks, and the landslides are mainly around roads.(3) The resolution of the DEM should be selected based on the specific conditions of the study area, the requirements of the investigation, and the scale of the landslide. Opting for an appropriate DEM resolution is advantageous for understanding the patterns of landslides and conducting risk assessments in the region.(4) The Zhengjiabian landslide is a traction Landslide. The landslide body is a binary structure of gravel soil and slate weathering layer, and the damage process can be divided into three stages:(1)damage to the leading edge and stress release,(2)continuous creep and cracking,(3)rainfall infiltration and damage. The predominant slope material in the Brickyard landslide comprises clay, and the landslide is triggered by a combination of the traction effect resulting from the excavation at the slope's base and the nudging effect caused by the stacking load of the brick factory. Additionally, the Brickyard landslide exhibits persistent creep deformation. The study results provide a scientific basis for disaster prevention and mitigation in the Hanwang Township area.

Influence of perinatal factors on full-term low-birth-weight infants and construction of a predictive model

BACKGROUND Being too light at birth can increase the risk of various diseases during infancy.AIM To explore the effect of perinatal factors on term low-birth-weight(LBW)infants and build a predictive model.This model aims to guide the clinical management of pregnant women’s healthcare during pregnancy and support the healthy growth of newborns.METHODS A retrospective analysis was conducted on data from 1794 single full-term pregnant women who gave birth.Newborns were grouped based on birth weight:Those with birth weight<2.5 kg were classified as the low-weight group,and those with birth weight between 2.5 kg and 4 kg were included in the normal group.Multiple logistic regression analysis was used to identify the factors influencing the occurrence of full-term LBW.A risk prediction model was established based on the analysis results.The effectiveness of the model was analyzed using the Hosmer–Leme show test and receiver operating characteristic(ROC)curve to verify the accuracy of the predictions.RESULTS Among the 1794 pregnant women,there were 62 cases of neonatal weight<2.5 kg,resulting in an LBW incidence rate of 3.46%.The factors influencing full-term LBW included low maternal education level[odds ratio(OR)=1.416],fewer prenatal examinations(OR=2.907),insufficient weight gain during pregnancy(OR=3.695),irregular calcium supplementation during pregnancy(OR=1.756),and pregnancy hypertension syndrome(OR=2.192).The prediction model equation was obtained as follows:Logit(P)=0.348×maternal education level+1.067×number of prenatal examinations+1.307×insufficient weight gain during pregnancy+0.563×irregular calcium supplementation during pregnancy+0.785×pregnancy hypertension syndrome−29.164.The area under the ROC curve for this model was 0.853,with a sensitivity of 0.852 and a specificity of 0.821.The Hosmer–Leme show test yieldedχ^(2)=2.185,P=0.449,indicating a good fit.The overall accuracy of the clinical validation model was 81.67%.CONCLUSION The occurrence of full-term LBW is related to maternal education,the number of prenatal examinations,weight gain during pregnancy,calcium supplementation during pregnancy,and pregnancy-induced hypertension.The constructed predictive model can effectively predict the risk of full-term LBW.

A Study on the Influence of Social Media Use on Psychological Anxiety among Young Women

To explore the relationship between social influence,social comparison,clarity of self-concept,and psychological anxiety among young women during their usage of social networking sites,our study selected 338 young women aged 14-34 from the social site platforms of Little Red Book and Weibo for questionnaire surveys.The Passive Social Network Utilization Scale,Social Comparison Scale(SCS),Social Influence Questionnaire,Self-Concept Clarity Scale(SCCS),and Generalized Anxiety Disorder Scale(GAD-7)were employed to measure the subjects.Our results show that the frequency of passive social media use is positively related to the level of psychological anxiety.Social comparison,social influence,and unclear self-concepts under social media use are negatively predictive of psychological anxiety.The chain mediation effects indicate that social comparison and social influence under social media use negatively predict the clarity of self-concept,thus having a negative impact on the psychological health of young women.Therefore,young women should strengthen their self-concepts,control their frequency of social media usage,avoid addiction,and pay special attention to their frequency of passive use,in order to protect their psychological health.Our study provides some practical implications and insights regarding the relationship between young women’s social media use and psychological health.