Biophysical warming patterns of an open-top chamber and its short-term influence on a Phragmites wetland ecosystem in China

Passive-warming, open-top chambers(OTCs) are widely applied for studying the effects of future climate warming on coastal wetlands. In this study, a set of six OTCs were established at a Phragmites wetland located in the Yellow River Delta of Dongying City, China. With data collected through online transmission and in-situ sensors, the attributes and patterns of realized OTCs warming are demonstrated.The authors also quantified the preliminary influence of experimental chamber warming on plant traits.OTCs produced an elevated average air temperature of 0.8°C(relative to controls) during the growing season(June to October) of 2018, and soil temperatures actually decreased by 0.54°C at a depth of 5 cm and 0.46°C at a depth of 30 cm in the OTCs. Variations in diel patterns of warming depend greatly on the heat sources of incoming radiation in the daytime versus soil heat flux at night. Warming effects were often larger during instantaneous analyses and influenced OTCs air temperatures from-2.5°C to 8.3°C dependent on various meteorological conditions at any given time, ranging from cooling influences from vertical heat exchange and vegetation to radiation-associated warming. Night-time temperature depressions in the OTCs were due to the low turbulence inside OTCs and changes in surface soilatmosphere heat transfer. Plant shoot density, basal diameter, and biomass of Phragmites decreased by23.2%, 6.3%, and 34.0%, respectively, under experimental warming versus controls, and plant height increased by 4.3%, reflecting less carbon allocation to stem structures as plants in the OTCs experienced simultaneous wind buffering. While these passive-warming OTCs created the desired warming effects both to the atmosphere and soils, pest damages on the plant leaves and lodging within the OTCs were extensive and serious, creating the need to consider control options for these chambers and the replicated OTCs studies underway in other Chinese Phragmites marshes(Panjin and Yancheng).

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.

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.

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.

A Study on Chengdu Museum’s Endeavor to Expand Its International Influence

Expanding a city’s cultural influence through museums is a growing trend in local efforts to promote cultural advancement and communication in China in the context of international engagement in the new era.Chengdu Museum,which opened its new venue to the public in 2016,has emphasized the importance of engagement with foreign visitors as a key focus of its recent development.This aligns with Chengdu’s goal of establishing itself as a world-renowned cultural and creative city during the 14th Five-Year Plan period(2021–2025).This paper summarizes the approaches of renowned Chinese and foreign museums to expanding their international influence,citing examples such as the British Museum,the Louvre Museum,and the National Museum of China.Based on a case study of Chengdu Museum’s efforts to enhance its international communication capacity since 2016,several suggestions are put forward for urban museums regarding how to increase research capability,create a media matrix,and develop cloud exhibition platforms.This study aims to provide some insights for museums to effectively integrate resources to preserve urban culture urban culture and enhance the global influence of Chinese culture.

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.

Microbiologically influenced corrosion resistance enhancement of coppercontaining high entropy alloy Fe_(x)Cu_(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.

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 Influence of Air Pollution Concentrations on Solar Irradiance Forecasting Using CNN-LSTM-mRMR Feature Extraction

Maintaining a steady power supply requires accurate forecasting of solar irradiance,since clean energy resources do not provide steady power.The existing forecasting studies have examined the limited effects of weather conditions on solar radiation such as temperature and precipitation utilizing convolutional neural network(CNN),but no comprehensive study has been conducted on concentrations of air pollutants along with weather conditions.This paper proposes a hybrid approach based on deep learning,expanding the feature set by adding new air pollution concentrations,and ranking these features to select and reduce their size to improve efficiency.In order to improve the accuracy of feature selection,a maximum-dependency and minimum-redundancy(mRMR)criterion is applied to the constructed feature space to identify and rank the features.The combination of air pollution data with weather conditions data has enabled the prediction of solar irradiance with a higher accuracy.An evaluation of the proposed approach is conducted in Istanbul over 12 months for 43791 discrete times,with the main purpose of analyzing air data,including particular matter(PM10 and PM25),carbon monoxide(CO),nitric oxide(NOX),nitrogen dioxide(NO_(2)),ozone(O₃),sulfur dioxide(SO_(2))using a CNN,a long short-term memory network(LSTM),and MRMR feature extraction.Compared with the benchmark models with root mean square error(RMSE)results of 76.2,60.3,41.3,32.4,there is a significant improvement with the RMSE result of 5.536.This hybrid model presented here offers high prediction accuracy,a wider feature set,and a novel approach based on air concentrations combined with weather conditions for solar irradiance prediction.

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.

Influence of Anthropogenic Activities on Surface Water Resources—Case of the Sub-Prefecture of Kamsar-Boké

Living fishery resources, although rich and important for human populations, are subject to strong anthropization, thus causing a change in the environmental parameters of aquatic ecosystems. These multiple combined pressures: chemical, hydro-morphological, thermal or trophic, affect and disrupt the functioning of aquatic organisms. The objective of this study was to assess the main human pressures influencing the surface water resources of the Kamsar sub-prefecture, in order to propose mitigation measures. The following methodological approach was adopted: 1) Survey of managers and analysis records;2) Survey of stakeholders;3) Assessment of the effect of human activities on surface water resources;4) Data processing;5) Corrective measures. The survey farmers working near aquatic environments, revealed a low use of chemical substances, in particular 3 to 11 kg of fertilizer and 0 to 3 boxes of herbicide on fields of 40 m2 to 2 ha. Some physico-chemical parameters have been determined: Temperature (28.5˚C, 23.7˚C, 22.8˚C, 21.3˚C, 21.6˚C), Salinity (26.9‰, 21.9‰, 21.5‰, 15‰, 15.3‰) and Turbidity (21.3 UTN, 19.3 UTN, 17.8 UTN, 16.7 UTN, 17 UTN). These values show a fluctuation in the environmental parameters of aquatic ecosystems, which constitutes an obstacle to the development and survival of the resources.

A framework of force of information influence and application for C4KISR system

The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.