Determinants of Online Buying Behaviour of Social Media Users in Cameroon

Online shopping in Cameroon is growing rapidly and gaining considerable ground.The phenomenon is relatively new as compared to the traditional brick-and-mortar store(serving customers face-to-face in a building rather than online).As the world faces digital transformations,businesses in Cameroon are seeking new ways to reach their customers and create favourable environments to effectively carryout online purchase.This study examines the factors that affect consumer online buying behaviour in Cameroon.Three theories guided this investigation:the Technology Acceptance Model(Davis,1989),Diffusion of Innovations Theory(Rogers,1995),and Uses and Gratifications Theory(Katz&Blumler,1974).The study focuses on students of the University of Buea who carry out online shopping.Purposive sampling is used,and data are collected from 365 respondents through a questionnaire with open and closed ended questions.Analysis of data is done with the use of the Statistical Package for Social Scientists(SPSS)Version 21 to determine the types of products consumers buy online;the degree to which consumer trust and satisfaction affect consumer loyalty;and the specific social,economic,and market factors that affect online buying behaviour.Findings indicate that:Consumers mostly buy fashion items(74.3%),electronics(44.7%),cosmetics(37.3%),and house equipment(34%)online.Consumers will repeat purchase from a marketer if they trust and are satisfied with the product and service quality(81.1%);hence,they will also encourage others to buy.If they are dissatisfied,they will not repeat purchase from the online store.Advertisement(76.1%),attractive pricing/discount(71.7%),product quality(71%),service quality(64.1%),convenience(72.3%),available income/money(49.6%),word of mouth recommendation(41.9%),and personal motivation(62.7%)constitute the major factors that affect consumer online buying behaviour.Results of the hypotheses testing show that:H1=Consumers buy more of fashion items online(X^(2)=9.950;df=16;p=0.869);H2=There is a significant relationship between trust and satisfaction and consumers online buying behaviour(X^(2)=270.765;df=16;p=0.000);and H3=Social,economic,and market factors significantly affect consumer online buying behaviour(X^(2)=106.328;df=16;p=0.000).The study recommends online marketers to develop their marketing strategies towards customer orientation and focus on the ease of use of their online shopping services.

Hepatitis B Surface Antigen and Hepatitis C Virus Antibodies among Drug Users in Burkina Faso

Introduction: The epidemiology of both hepatitis B virus (HBV) and hepatitis C virus (HCV) infections among drug users (DUs) is little known in West Africa. The study aimed to assess the prevalence of hepatitis B and C viruses among drug users in Burkina Faso. Methodology: This was a cross-sectional biological and behavioral survey conducted between June and August 2022, among drug users in Ouagadougou and Bobo Dioulasso, the two main cities of Burkina Faso. A respondent-driven sampling (RDS) was used to recruit drug users. Hepatitis B surface antigen was determined using lateral flow rapid test kits and antibodies to hepatitis C virus in serum determined using an Enzyme-Linked Immunosorbent Assay. Data were entered and analyzed using Stata 17 software. Weighted binary logistic regression was used to identify the associated factors of hepatitis B and C infections and a p-value Results: A total of 323 drug users were recruited with 97.5% males. The mean age was 32.7 years old. The inhaled or smoked mode was the most used by drug users. The adjusted hepatitis B and hepatitis C prevalence among study participants were 11.1% and 2.3% respectively. The marital status (p = 0.001), and the nationality (p = 0.011) were significantly associated with hepatitis B infection. The type of drug used was not significantly associated with hepatitis B infection or hepatitis C infection. Conclusion: The prevalence of HBsAg and anti-HCV antibodies among DUs are comparable to those reported in the general population in Burkina Faso. This result suggests that the main routes of contamination by HBV and HCV among DUs are similar to those in the population, and could be explained by the low use of the injectable route by DUs in Burkina Faso.

Reform of the Irrigation Sector and Creation of Functional and Sustainable Irrigation Water Users Associations (AUEI) in Niger: Capitalization of the Experience of the Konni AHA

During the 1980s, as part of a policy of liberalization, following budgetary cuts linked to the implementation of structural adjustment programs, management responsibilities for AHAs were transferred from ONAHA to cooperatives concerned. Due to lack of financial resources, but also because of poor management, everywhere in Niger we are witnessing an accelerated deterioration of the irrigation infrastructure of hydro-agricultural developments. Institutional studies carried out on this situation led the State of Niger to initiate a reform of the governance of hydro-agricultural developments, by streng-thening the status of ONAHA, by creating an Association of Irrigation Water Users (AUEI) and by restructuring the old cooperatives. Indeed, this research aims to analyze the creation of functional and sustainable Irrigation Water User Associations (AUEI) in Niger in a context of reform of the irrigation sector, and based on the experience of the Konni AHA. It is based on a methodological approach which takes into account documentary research and the collection of data from 115 farmers, selected by reasoned choice and directly concerned by the management of the irrigated area. The data collected was analyzed and the results were analyzed using the systemic approach and the diagnostic process. The results show that the main mission of the AUEI is to ensure better management of water, hydraulic equipment and infrastructure on the hydro-agricultural developments of Konni. The creation of the Konni AUEI was possible thanks to massive support from the populations and authorities in the implementation process. After its establishment, the AUEI experienced a certain lethargy for some time due to the rehabilitation work of the AHA but currently it is functional and operational in terms of associative life and governance. Thus, the constraints linked to the legal system, the delay in the completion of the work, the uncertainties of access to irrigation water but also the problems linked to the change in mentality of certain ONAHA agents constitute the challenges that must be resolved in the short term for the operationalization of the Konni AUEI.

Enable Excel-Based Basic Cybersecurity Features for End Users by Using Python-Excel Integration

In the digital age, the global character of the Internet has significantly improved our daily lives by providing access to large amounts of knowledge and allowing for seamless connections. However, this enormously interconnected world is not without its risks. Malicious URLs are a powerful menace, masquerading as legitimate links while holding the intent to hack computer systems or steal sensitive personal information. As the sophistication and frequency of cyberattacks increase, identifying bad URLs has emerged as a critical aspect of cybersecurity. This study presents a new approach that enables the average end-user to check URL safety using Microsoft Excel. Using the powerful VirusTotal API for URL inspections, this study creates an Excel add-in that integrates Python and Excel to deliver a seamless, user-friendly interface. Furthermore, the study improves Excel’s capabilities by allowing users to encrypt and decrypt text communications directly in the spreadsheet. Users may easily encrypt their conversations by simply typing a key and the required text into predefined cells, enhancing their personal cybersecurity with a layer of cryptographic secrecy. This strategy democratizes access to advanced cybersecurity solutions, making attentive digital integrity a feature rather than a daunting burden.

Orthogonal Frequency Division Multiplexing Adaptive Technology for Multinode Users of Seawater Channel Based on Inductively Coupled Mooring Chain

As an important part of buoy-type ocean monitoring systems,the inductively coupled mooring chain solves the problem of data cotransmission through the multinode sensors that it carries,which is significant for the rapid acquisition of fish,hydrology,and other information.This paper is based on a seawater channel transmission model with a depth of 300 m and a bandwidth of 2 MHz.An orthogonal frequency division multiplexing(OFDM)technology is used to overcome the multipath effect of signal transmission on a seawater medium.The adaptive technology is integrated into the OFDM,and an improved joint subcarrier and bit power allocation algorithm is proposed.This algorithm solves the problem of dynamic subcarrier allocation during the cotransmission of underwater multinode user data in seawater channels.The results show that the algorithm complexity can be reduced by 0.18126×10^(-2)s during one complete OFDM system data transmission by the improved greedy algorithm,and a total of 216 bits are transmitted by the OFDM.The normalized channel capacity can be improved by 0.012 bit s^(-1)Hz^(-1).At the bit error ratio(BER)of 10^(-3),the BER performance can be improved by approximately 6 d B.When the numbers of users are 4 and 8,the improved algorithm increases the channel capacity,and the higher the number of users,the more evident the channel capacity improvement effect is.The results of this paper have an important reference value for enhancing the transmission performance of inductively coupled mooring chain underwater multinode data.

Effects of Emotion on Decision-Making ofMethamphetamine Users: Based on theEmotional Iowa Gambling Task

The relapse of methamphetamine (meth) is associated with decision-making dysfunction. The present study aims to investigate theimpact of different emotions on the decision-making behavior of meth users. We used 2 (gender: male, female) × 3 (emotion:positive, negative, neutral) × 5 (block: 1, 2, 3, 4, 5) mixed experiment design. The study involved 168 meth users who weredivided into three groups: positive emotion, negative emotion and neutral emotion group, and tested by the emotional IowaGambling Task (IGT). The IGT performance of male users exhibited a decreasing trend from Block 1 to Block 3. Female methusers in positive emotion had the best performance in IGT than females in the other two groups. In positive emotion, the IGTperformance of female meth users was significantly better than that of men. Female meth users in positive emotion had betterdecision-making than those in negative or neutral emotion. Female meth users in positive emotion had better decision-makingperformance than males in positive emotion. In negative and neutral emotions, there was no significant gender difference indecision-making.

Identification of Influential Users in Online Social Network: A Brief Overview

Information networks where users join a network, publish their own content, and create links to other users are called Online Social Networks (OSNs). Nowadays, OSNs have become one of the major platforms to promote both new and viral applications as well as disseminate information. Social network analysis is the study of these information networks that leads to uncovering patterns of interaction among the entities. In this regard, finding influential users in OSNs is very important as they play a key role in the success above phenomena. Various approaches exist to detect influential users in OSNs, starting from simply counting the immediate neighbors to more complex machine-learning and message-passing techniques. In this paper, we review the recent existing research works that focused on identifying influential users in OSNs.

Trip Purposes of Automobile Users Inference Using Multi-day Traffic Monitoring Data

Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to analyze their travel characteristics,and focus on the classification and prediction of automobileu sers’trip purposes. However,previous studies on trip purposes mainly focused on questionnaires and GPSd ata,which cannot well reflect the characteristics of automobile travel. In order to avoid the multi-dayb ehavior variability and unobservable heterogeneity of individual characteristics ignored in traditional traffic questionnaires,traffic monitoring data from the Northern District of Qingdao are used,and the K-meansc lustering method is applied to estimate the trip purposes of automobile users. Then,Adaptive Boosting(AdaBoost)and Random Forest(RF)methods are used to classify and predict trip purposes. Finally,ther esult shows:(1)the purpose of automobile users can be mainly divided into four clusters,which includeC ommuting trips,Flexible life demand travel in daytime,Evening entertainment and leisure shopping,andT axi-based trips for the first three types of purposes,respectively;(2)the Random Forest method performss ignificantly better than AdaBoost in trip purpose prediction for higher accuracy;(3)the average predictiona ccuracy of Random Forest under hyper-parameters optimization reaches96.25%,which proves the feasibilitya nd rationality of the above clustering results.

Reliable and Privacy-Preserving Federated Learning with Anomalous Users

Recently,various privacy-preserving schemes have been proposed to resolve privacy issues in federated learning(FL).However,most of them ignore the fact that anomalous users holding low-quality data may reduce the accuracy of trained models.Although some existing works manage to solve this problem,they either lack privacy protection for users’sensitive information or introduce a two-cloud model that is difficult to find in reality.A reliable and privacy-preserving FL scheme named reliable and privacy-preserving federated learning(RPPFL)based on a single-cloud model is proposed.Specifically,inspired by the truth discovery technique,we design an approach to identify the user’s reliability and thereby decrease the impact of anomalous users.In addition,an additively homomorphic cryptosystem is utilized to provide comprehensive privacy preservation(user’s local gradient privacy and reliability privacy).We give rigorous theoretical analysis to show the security of RPPFL.Based on open datasets,we conduct extensive experiments to demonstrate that RPPEL compares favorably with existing works in terms of efficiency and accuracy.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Virtual reality-based cognitive-behavioural therapy for the treatment of anxiety in patients with acute myocardial infarction:a randomised clinical trial

Background The presence of mental health conditions is pervasive in patients who experienced acute myocardial infarction(AMI),significantly disrupting their recovery.Providing timely and easily accessible psychological interventions using virtual reality-based cognitive-behavioural therapy(VR-CBT)could potentially improve both acute and long-term symptoms affecting their mental health.Aims We aim to examine the effectiveness of VR-CBT on anxiety symptoms in patients with AMI who were admitted to the intensive care unit(ICU)during the acute stage of their illness.Methods In this single-blind randomised clinical trial,participants with anxiety symptoms who were admitted to the ICU due to AMI were continuously recruited from December 2022 to February 2023.Patients who were Han Chinese aged 18-75 years were randomly assigned(1:1)via block randomisation to either the VR-CBT group to receive VR-CBT in addition to standard mental health support,or the control group to receive standard mental health support only.VR-CBT consisted of four modules and was delivered at the bedside over a 1-week period.Assessments were done at baseline,immediately after treatment and at 3-month follow-up.The intention-to-treat analysis began in June 2023.The primary outcome measure was the changes in anxiety symptoms as assessed by the Hamilton Anxiety Rating Scale(HAM-A).Results Among 148 randomised participants,70 were assigned to the VR-CBT group and 78 to the control group.The 1-week VR-CBT intervention plus standard mental health support significantly reduced the anxiety symptoms compared with standard mental health support alone in terms of HAM-A scores at both post intervention(Cohen’s d=−1.27(95%confidence interval(CI):−1.64 to−0.90,p<0.001)and 3-month follow-up(Cohen’s d=−0.37(95%CI:−0.72 to−0.01,p=0.024).Of the 70 participants who received VR-CBT,62(88.6%)completed the entire intervention.Cybersickness was the main reported adverse event(n=5).Conclusions Our results indicate that VR-CBT can significantly reduce post-AMI anxiety at the acute stage of the illness;the improvement was maintained at the 3-month follow-up.Trial registration number The trial was registered at www.chictr.org.cn with the identifier:ChiCTR2200066435.

Heart Failure-Like Reaction Is Likely Involved in the Feeding Behaviour of Blood-Sucking Leeches

Medicinal leeches have been utilized in therapy for thousands of years. However, the adaptation physiology between leeches and hosts is not fully understand. To disclose the molecular mechanisms of adaptation between leech and host, the body transcriptomes of hunger and fed blood-sucking Poecilobdella javanica, Haemadipsa cavatuses, and Hirudo nipponia leeches were obtained by RNA sequencing, after comparison, a stratified unigenes group was obtained, which closely correlated to body distension. In the group, Rfamide receptor decreased significantly (P < 0.05) while serotonin receptor increased significantly (P < 0.05). Moreover, four KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, including cardiac muscle contraction, complement and coagulation cascades, renin-angiotensin system, and hypertrophic cardiomyopathy were significantly enriched. The unigenes annotation, neuroregulators correlation analysis and induced function of the KEGG pathways, were consistently supported the same result as: vasoconstriction and systole reaction enhance in hunger leeches and vice versa vasodilation and diastole increase in fed leeches, meanwhile, Interspecific comparison and correlative analyses of physiological function showed that the strongest reaction of induced heart failure from four KEGG occur in strongest reaction of systole in hungry P. javanica and in strongest reaction of diastole in fed H. nipponia. Overall, heart failure is likely a physiological function involved in feeding behaviour.

Pregnancy stressors and postpartum symptoms of depression and anxiety:the moderating role of a cognitivebehavioural therapy(CBT)intervention

Background Little is known about the association between stressors(especially positive stressors)during pregnancy and postpartum depression and anxiety.Aims We investigated the association between positive and negative stress events during different stages of pregnancy and postpartum mental health outcomes among low-income pregnant women with symptoms of anxiety in Pakistan and evaluated whether an intervention based on cognitive behavioural therapy(CBT)had a regulatory effect.Methods Participants were 621 pregnant Pakistani women with mild anxiety.Using the Pregnancy Experience Scale-Brief Version,six scores were created to assess positive and negative stressors.We performed a multivariate linear regression to examine whether these six scores,measured both at baseline and in the third trimester,were associated with postpartum anxiety and depressive symptoms.The effect of the intervention on this relationship was examined by adding an interaction term to the regression model.Results Hassles frequency measured in the third trimester was positively associated with depression(B=0.22,95%confidence interval(Cl):0.09 to 0.36)and anxiety(B=0.19,95%Cl:0.08to 0.30).At the same timepoint,uplifts intensity was negatively associated with symptoms of depression(B=-0.82,95%Cl:1.46 to-0.18)and anxiety(B=-0.70,95%Cl:-1.25 to-0.15),whereas hassles intensity was positively related to symptoms of depression(B=1.02,95%Cl:0.36 to 1.67)and anxiety(B=0.90,95%Cl:0.34 to 1.47).The intensity ratio of hassles to uplifts reported in the third trimester was positively related to both depression(B=1.40,95%Cl:0.59 to 2.20)and anxiety(B=1.26,95%Cl:0.57 to 1.96).The intervention strengthened the overall positive effects of uplfts and the negative effects of hassles.Pregnancy experiences at baseline during early pregnancy to mid-pregnancy were not associated with mental health outcomes.Conclusions Stressors in the third trimester but not earlier in pregnancy were associated with postpartum symptoms of anxiety and depression.The CBT intervention modified the association between pregnancy stressors and postpartum mental health outcomes.Programmes that promote positive experiences and reduce negative experiences,especially in late pregnancy,may mitigate postpartum mental health consequences.

User Preference Aware Hierarchical Edge-User Cooperative Caching Strategy

The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been considered as a feasible scheme.However,how to efficiently utilize the limited caching resources to cache diverse contents has been confirmed as a tough problem in the past decade.In this paper,considering the time-varying user requests and the heterogeneous content sizes,a user preference aware hierarchical cooperative caching strategy in edge-user caching architecture is proposed.We divide the caching strategy into three phases,that is,the content placement,the content delivery and the content update.In the content placement phase,a cooperative content placement algorithm for local content popularity is designed to cache contents proactively.In the content delivery phase,a cooperative delivery algorithm is proposed to deliver the cached contents.In the content update phase,a content update algorithm is proposed according to the popularity of the contents.Finally,the proposed caching strategy is validated using the MovieLens dataset,and the results reveal that the proposed strategy improves the delay performance by at least 35.3%compared with the other three benchmark strategies.

User Profile & Attitude Analysis Based on Unstructured Social Media and Online Activity

As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Deep Learning Social Network Access Control Model Based on User Preferences

A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous graphs.Secondly,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social network.Then,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user preferences.Finally,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny access.The fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural network.The model is validated using a dataset and compared with other methods without losing generality.The model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.

Mechanical behaviours of bedded sandstone under hydromechanical coupling

The combination of the dipping effect and hydromechanical(H-M)coupling effect can easily lead to water inrush disasters in water-rich roadways with different dip angles in coal mines.Therefore,H-M coupling tests of bedded sandstones under identical osmotic pressure and various confining pressures were conducted.Then,the evolution curves of stress-strain,permeability and damage,macro-and mesoscopic failure characteristics were obtained.Subsequently,the mechanical behaviour was characterized,and finally the failure mechanism was revealed.The results showed that:(1)The failure of the sandstone with the bedding angle of 45°or 60°was the structure-dominant type,while that with the bedding angle of 0°,30°or 90°was the force-dominant type.(2)When the bedding angle was in the range of(0°,30°)or(45°,90°),the confining pressure played a dominant role in influencing the peak strength.However,withinβ∈(30°,45°),the bedding effect played a dominant role in the peak strength.(3)With the increase in bedding angle,the cohesion increased first,then decreased and finally increased,while the internal friction angle was the opposite.(4)When the bedding angle was 0°or 30°,the“water wedging”effect and the“bedding buckling”effect would lead to the forking or converging shear failure.When the bedding angle was 45°or 60°,the sliding friction effect would lead to the shear slipping failure.When the bedding angle was 90°,the combination of the“bedding buckling”effect and shear effect would lead to the mixed tension-shear failure.The above conclusions obtained are helpful for the prevention of water inrush disasters in water-rich roadways with different dips in coal mines.

When Fleeing Matters:Differences in Escape Behaviours of Three Northeast Asian Anurans

Prey species may have their own optimal escape strategy to balance predation risks and the energetic cost of fleeing.Some species have an advantage when maintaining a short fleeing distance,while others may favour an earlier escape based on microhabitat,size,or body condition.Here,we examined the escape behaviour of the three syntopic Northeast Asian anuran species:Mongolian toads(Strauchbufo raddei),Amur brown frogs(Rana amurensis),and Japanese treefrogs(Dryophytes japonicus)in Mongolia,Russia,China and DPR Korea.We examined flight initiation distance(FID;the distance from a potential predator to the point when the individual starts to flee)and distance fled(DF;distance between flight initiation and flight termination points)of each species and the effects of microhabitat,sex,and body size.Strauchbufo raddei and R.amurensis had a longer FID than D.japonicus,and S.raddei also had a longer DF than D.japonicus.These trends remained similar when dividing FID and DF by a size proxy(snout-vent length)for all individuals.This suggests that the treefrog D.japonicus used a strategy to stay immobile even when they were detected,and the toad S.raddei reacted quicker and more sensitively to predators despite the presence of toxin.Female S.raddei had a significantly longer FID than males suggesting that females are more sensitive to predation risk in this species,but body size was not significant for any of the three species.Our results indicate that the three sympatric species have different escaping strategies,likely related to differences in physiology and crypticity.

Suicidal Behaviours in Sickle Cell Patients at the Douala Sickle Cell Care Centre in Cameroon

Introduction: Sickle cell anaemia is a hereditary disease that combines physical and psychological manifestations, including suicidal tendencies. So far, to our knowledge, no study has been conducted on suicidal behaviours among people with sickle cell disease in Cameroon. This is what justifies our study on the prevalence and factors related to suicidal behaviors in our study population. Methods: We conducted a cross-sectional, analytical study of 171 sickle cell patients aged from 12 years upwards who came to the sickle cell disease care service of the Laquintinie Hospital in Douala, over a period of 6 months, that is, from 1 January to 31 June 2022. Data were collected using a structured questionnaire with questions on suicidal behaviours based on the “MINI” (Mini International Neuropsychiatric Interview). The data were processed using the SPSS 26.0 software. The related factors were studied in both a bivariate and multivariate analysis. Results: Female sickle cell patients accounted for 60.2% of the sample. The mean age was 23.36 ± 8.42 years. Suicidal ideation was prevalent in 56% of cases and 13% attempted suicide. The factors most associated with suicidal ideation were: primary level of education (OR = 0.08 (0.09 - 0.79);p = 0.03), feeling unworthy of life (OR = 0.40 (0.08 - 1.96);p = 0.02), not often being considered by those around them (OR = 2.97 (1.26 - 6.99);p = 0.01), lack of family support (OR = 0.34 (0.15 - 0.77);p = 0.01). Meanwhile, the factors associated with suicide attempts were: the fact of being rarely exposed to suicide-related media (OR = 4.17 (1.40 - 71.80);p = 0.03), and a constant feeling of sadness when returning home (OR = 18.02 (1.59 - 20.55);p = 0.01). Conclusion: More than half of sickle cell patients had had suicidal thoughts and 1/6 had made at least one suicide attempt, women and young adults being the most concerned. It is therefore necessary to ensure optimum psychological care for patients with sickle cell disease.