Assessment of spermatogenesis in camels via seminiferous tubule staging and testosterone profiling

Objective:To investigate the successive morphological stages of spermatogenesis,hormonal regulation,and testosterone profile in dromedary camel reproduction.Methods:Testicular tissue samples were obtained from 12 dromedary bull camels aged 7 to 8 at a local abattoir.The histological assessment involved tissue processing,hematoxylin and eosin(H&E)staining,and examination under a microscope.Stereological analysis,germ cell identification,and assessment of seminiferous tubules and maturation were conducted.Testosterone assay was performed by radioimmunoassay using blood samples collected at regular intervals.Results:The study revealed 12 phases of the dromedary camel's seminiferous epithelium cycle,highlighting distinct morphological characteristics and cellular processes.Acrosomal migration,maturation,cap formation,and the Golgi-mediated synthesis of proacrosomal vesicles were also explained in dimension,as were the steps of acrosome biogenesis.Spermatids and mature sperm cells were present when spermatogenesis phases were examined.An analysis of the dimensions of seminiferous tubules revealed specific measures for diameter,area,and epithelial height about luminal characteristics.Moreover,there were noticeable variations in the serum testosterone concentrations during the study period,indicating temporal dynamics.Conclusions:This study outlines the spermatogenesis process in dromedary camels across 12 stages,emphasizing cellular dynamics and acrosomal biogenesis.It also provides seminiferous tubule measurements and observes seasonal testosterone fluctuations,offering insights into reproductive regulation and potential strategies for camel breeding conservation.

Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

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.

Genomic profiling of colorectal cancer in large-scale Chinese patients:amplification and somatic mutations in ERBB2

Objectives:Human epidermal growth factor receptor 2(HER2)-targeted therapies have demonstrated potential benefits for metastatic colorectal cancer(mCRC)patients with HER2 amplification,but are not satisfactory in cases of HER2 mutant CRCs.Methods:Consequently,further elucidation of amplifications and somatic mutations in erythroblastic oncogene B-2(ERBB2)is imperative.Comprehensive genomic profiling was conducted on 2454 Chinese CRC cases to evaluate genomic alterations in 733 cancer-related genes,tumor mutational burden,microsatellite instability,and programmed death ligand 1(PD-L1)expression.Results:Among 2454 CRC patients,85 cases(3.46%)exhibited ERBB2 amplification,and 55 cases(2.24%)carried ERBB2 mutation.p.R678Q(28%),p.V8421(24%),and p.S310F/Y(12%)were the most prevalent of the 16 detected mutation sites.In comparison to the ERBB2 altered(alt)group,KRAS/BRAF mutations were more prevalent in ERBB2 wild-type(wt)samples(ERBB2wt vs.ERBB2alt,KRAS:50.9%vs.25.6%,p<0.05;BRAF:8.5%vs.2.3%,p<0.05).32.7%(18/55)of CRCs with ERBB2 mutation exhibited microsatellite instability high(MSI-H),while no cases with HER2 amplification displayed MSI-H.Mutant genes varied between ERBB2 copy number variation(CNV)and ERBB2 single nucleotide variant(SNV);TP53 alterations tended to co-occur with ERBB2 amplification(92.3%)as opposed to ERBB2 mutation(58.3%).KRAS and PIK3CA alterations were more prevalent in ERBB2 SNV cases(KRAS/PIK3CA:45.8%/31.2%)compared to ERBB2 amplification cases(KRAS/PIK3CA:14.1%/7.7%).Conclusion:Our study delineates the landscape of HER2 alterations in a large-scale cohort of CRC patients from China.These findings enhance our understanding of the molecular features of Chinese CRC patients and offer valuable implications for further investigation.

ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and genders.To improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and assessment.To evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are compared.The findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,respectively.Additional metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling tasks.This study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and education.The results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

DMMIC derivatization-assisted liquid chromatography-mass spectrometry method for metabolite profiling of the glutathione anabolic pathway in esophageal cancer tissues and cells

In this work,a new pyrylium derivatization-assisted liquid chromatography-mass spectrometry(LC-MS)method was developed for metabolite profiling of the glutathione anabolic pathway(GAP)in cancer tissues and cells.The pyrylium salt of 6,7-dimethoxy-3-methyl isochromenylium tetrafluoroborate(DMMIC)was used to label the amino group of metabolites,and a reductant of dithiothreitol(DTT)was employed to stabilize the thiol group.By combining DMMIC derivatization with LC-MS,it was feasible to quantify the 13 main metabolites on the GAP in complex biological samples,which had good linearity(R^(2)=0.99810.9999),precision(interday precision of 1.6%e19.0%and intraday precision of 1.4%e19.8%)and accuracy(83.4%-115.7%).Moreover,the recovery assessments in tissues(82.5%e107.3%)and in cells(98.1%e118.9%)with GSH-^(13)C2,^(15)N,and Cys-^(15)N demonstrated the reliability of the method in detecting tissues and cells.Following a methodological evaluation,the method was applied successfully to investigate difference in the GAP between the carcinoma and para-carcinoma tissues of esophageal squamous cell carcinoma(ESCC)and the effect of p-hydroxycinnamaldehyde(CMSP)on the GAP in KYSE150 esophageal cancer cells.The results demonstrate that the developed method provides a promising new tool to elucidate the roles of GAP in physiological and pathological processes,which can contribute to research on drugs and diseases.

Fuzzy Feedback Control for Electro-Hydraulic Actuators

Electro-hydraulic actuators(EHA)have recently played a significant role in modern industrial applications,especially in systems requiring extremely high precision.This can be explained by EHA’s ability to precisely control the position and force through advanced sensors and innovative control algorithms.One of the promising approaches to improve control accuracy for EHA systems is applying classical to modern control algorithms,in which the proportional–inte-gral–derivative(PID)algorithm,fuzzy logic controller,and a hybrid of these methods are popular options.In this paper,we developed a novel version of the fuzzy control algorithm and linear feedback control method,namely fuzzy lin-ear feedback control,to improve the control performance.To achieve the highest performance,wefirst designed a mathematical EHA model based on the Matlab/Simulink software packages thanks to the selected parameters,which are similar to a real EHA system.Then,we respectively applied PID,fuzzy PID(FPID),and fuzzy linear feedback control(FLFC)before comparing them to have a full view of the outstanding advantages of the proposed algorithm.The simulation results showed that the proposed FLFC algorithm is approximately 99%and 77%super-ior in performance to the PID and feedback control algorithms,respectively.

Molecular Profiling of Sugarcane Wine, a Traditional Fermented Beverage (Loungouila) from Madingou

A number of studies reported that traditional fermented beverages possessed pharmaceutical biomolecules involved in biocatalysis for good therapeutic effects on various pathology including tumor, diabetes, inflammation, and obesity. This dimension of understanding is the prerogative of the biomolecular profile found in these fermented foods and beverages. The current work aimed to study the postfermentation molecular profile of the Congolese fermented beverage (Lougwila). The determination of pH, the acidity titratable, the distillation of sugar cane, the determination of total polyphenols and flavonoids and the matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) have been used. As results, the fermenting sugar cane juice at room temperature for a period of seven days, leading to a decrease of the pH value to 4.25 ± 0.10 and increase in titratable acidity and alcohol content of at least 6.421 g/L (w/v) and 7% respectively. The polyphenol concentration of Loungouila increase from 14.9 to 20.5 mg Eq AG/g Ms after 10 days of fermentation. The flavonoid concentration varies from 1.70 to 5.22 mg Eq Cat/g Ms. among 46 isolates of Bacillus species, 55% (25/45) were able to show a very interesting clear zones in terms of cellulolytic activity with the percentage ranging from 37.3% to 83.9%, and 41.3% of amylolytic activity for the percentage ranging from 52.02% to 75%. 65.21% (30/46) of the isolates tested were found to be positive by the caseinolytic test with zones of inhibition ranging in diameter from 1.10 ± 0.09 to 3.25 ± 0.07 cm. In addition to the determination of biomolecule profile, 34.78% (16/46) of Bacillus isolates were able to produce biosurfactants with percentages ranging from 14% to 100%. Proteomic profiling of Loungouila has been investigated by using MALDI-TOF Technique. Short sequences showed 100% identity and were associated with AprE, SubC, amyE, NprE, CelA, lytF, Mut, and ykfC proteins. The National Center for Biotechnology Information (NCBI) allowed to associate short sequences to Bacillus species.

Depth profiling of arsenian pyrite in Carlin-type ores through wet chemistry

Enrichment of As and Au at the overgrowth rims of arsenian pyrite is a distinctive feature of Carlin-type gold ores.Revealing distribution of such key elements in high resolution is of fundamental importance yet often proves challenging.In this study,repeated non-oxidative acid etching of ore samples from Shuiyindong gold deposit was applied to enable elemental depth profiling of goldbearing arsenian pyrite grains.ICP-OES and AAS were used to determine the dissolved Fe,As,and Au concentrations in each of the etching solutions,and XPS was carried out to exam the etched mineral surfaces.In contrast to conventional ion beam etching that may cause substantial sample damage,our acid etching method does not seem to significantly alter the composition and chemical state of the samples.The etched depths directly converted from the measured elemental concentrations can reproducibly reach a very high resolution of~1 nm,and can be conveniently controlled through varying the etching time.While the Fe and As depth profiles consistently reflect the surface oxidation property of arsenian pyrite,the Au profile displaying an obvious upward trend reveals the ore fluid evolution at the late stage of mineralization.Based on our experimental results,we demonstrate that our wet chemistry method is capable of effective depth profiling of gold ore and perhaps other geological samples,with advantages surpassing many instrumental techniques including negligible sample damage,nanoscale resolution as well as isotropic etching.

Thermal integrity profiling of cast-in-situ piles in sand using fiber-optic distributed temperature sensing

Defects in cast-in-situ piles have an adverse impact on load transfer at the pile‒soil interface and pile bearing capacity. In recent years, thermal integrity profiling (TIP) has been developed to measure temperature profiles of cast-in-situ piles, enabling the detection of structural defects or anomalies at the early stage of construction. However, using this integrity testing method to evaluate potential defects in cast-in-situ piles requires a comprehensive understanding of the mechanism of hydration heat transfer from piles to surrounding soils. In this study, small-scale model tests were conducted in laboratory to investigate the performance of TIP in detecting pile integrity. Fiber-optic distributed temperature sensing (DTS) technology was used to monitor detailed temperature variations along model piles in sand. Additionally, sensors were installed in sand to measure water content and matric suction. An interpretation method against available DTS-based thermal profiles was proposed to reveal the potential defective regions. It shows that the temperature difference between normal and defective piles is more obvious in wet sand. In addition, there is a critical zone of water migration in sand due to the water absorption behavior of cement and temperature transfer-induced water migration in the early-age concrete setting. These findings could provide important insight into the improvement of the TIP testing method for field applications.

三维薛定谔方程组的线性Profile分解

为了研究线性薛定谔方程组解Strichartz估计的紧性缺失问题,针对H•^(1)(R^(3))×H•^(1)(R^(3))中的三维线性薛定谔方程组的有界解向量序列,使用解序列的Profile分解方法,构造为解向量子列的(1/√h_(n))U(t-t_(n))/h_(n)^(2),(x-x_(n))/h_(n)类型的Profile分解和.其中,U是线性薛定谔方程组的解向量,在Strichartz范数估计下具有一个很小的余项.首先确定伸缩变换参数序列族,利用傅里叶变换和迭代的思想确定Profile分解族.其次验证了Profile分解和的收敛性,说明了Strichartz范数下余项的收敛性.最后证明了当线性薛定谔方程组的解序列有界时,都可以分解为解向量子列和的形式.

Deep learning approaches to recover the plasma current density profile from the safety factor based on Grad–Shafranov solutions across multiple tokamaks

Many magnetohydrodynamic stability analyses require generation of a set of equilibria with a fixed safety factor q-profile while varying other plasma parameters.A neural network(NN)-based approach is investigated that facilitates such a process.Both multilayer perceptron(MLP)-based NN and convolutional neural network(CNN)models are trained to map the q-profile to the plasma current density J-profile,and vice versa,while satisfying the Grad–Shafranov radial force balance constraint.When the initial target models are trained,using a database of semianalytically constructed numerical equilibria,an initial CNN with one convolutional layer is found to perform better than an initial MLP model.In particular,a trained initial CNN model can also predict the q-or J-profile for experimental tokamak equilibria.The performance of both initial target models is further improved by fine-tuning the training database,i.e.by adding realistic experimental equilibria with Gaussian noise.The fine-tuned target models,referred to as fine-tuned MLP and fine-tuned CNN,well reproduce the target q-or J-profile across multiple tokamak devices.As an important application,these NN-based equilibrium profile convertors can be utilized to provide a good initial guess for iterative equilibrium solvers,where the desired input quantity is the safety factor instead of the plasma current density.

Three-Channel Interference Interpretation of Fano Profile

Fano resonance is a ubiquitous phenomenon, and it is commonly interpreted as a two-channel interference of the discrete and continuous channels. The present work investigates the Fano profile from a perspective of the temporal evolution of the wave function. By exciting the atom with a δ pulse and calculating the evolution of the wave function, the Fano formula is deduced. The results clearly show that the Fano resonance is of a three-channel interference, which is different from the traditional understanding. The three channels are revealed as the groundcontinuum, ground-discrete-continuum, and a previously unmentioned third channel, i.e., ground-continuumdiscrete-continuum. The present three-channel interpretation can be easily generalized to other physical systems,contributing to a deeper understanding of the Fano profile.

Genomic Profile of SARS-COV-2 Associated with COVID-19 Outbreaks in N’Djamena, Chad

Background: SARS-CoV-2 has circulated worldwide with dramatic consequences. In Chad, we have no data reported of variants. The aim of this study was to identify the SARS-CoV-2 variants that circulated during the epidemic from 2020 to 2021. Methods: This is a cross-sectional, descriptive study carried out between 2020 and 2021. Samples from patients with suspected COVID-19 were tested in five laboratories in N’Djamena. One hundred quality samples of the positives were sequenced in Kinshasa using Oxford nanopore technologies minion and the Protocol Midnight SARS-CoV2. Data were processed using Excel version 16 software. Results: Of the 100 samples sequenced, 77 (77%) produced sequences, 23 (23%) did not. The genomic profiles were wild-type Wuhan and minor mutations (19A, 19B (A), 20A (B.1, B.2), 20B (AV.1), 20D (B.1.1.1 /C.36), 20C), variant of concern Alpha (20I), variant of concern Delta (21A/J), variant of interest Eta (21D), variant of concern Omicron (21K) and unclassified variant under surveillance (B.1.640). Of these variants, the maximums were detected in patients aged 26 - 35 with 30.26% and 25.26% in 36 - 45. However, 24.67% were in travelers and 75.32% in residents, 35.06% in those vaccinated against COVID-19 and 62.33% in non-vaccinates. The estimated case-fatality rate was 2.44% (107/4374). Conclusion: This work has provided preliminary data on COVID-19 and SARS-CoV-2 variants circulating during the 2020-2021 epidemics in Chad.

Baseline design of the KunLun Turbulence Profiler instrument

Adaptive optics systems are the most powerful tools to counteract the image blurring caused by atmospheric turbulence,allowing ground-based telescopes to capture high-resolution images.A critical parameter influencing adaptive optics system performance is the atmospheric refractive index structure constant,C_(n)^(2),which characterizes the intensity of atmospheric optical turbulence as a function of altitude.Given its simplicity,the lunar scintillometer is the preferred method for detecting atmospheric turbulence in challenging environments like Dome A in Antarctica,where sites are still in the developmental stages and local environmental conditions are extremely harsh.However,optimizing the performance of such instruments requires carefully determining the baseline configuration of photon sensors according to each site's specific optical turbulence profile characteristics.This study uses a Monte Carlo method to identify the optimal configuration for the KunLun Turbulence Profiler(KLTP),an instrument comparable to the lunar scintillometer,developed for use at Dome A.Simulations conducted using the obtained optimal baseline configuration recovered three different model optical turbulence profiles,demonstrating the effectiveness of our method in obtaining an optimal baseline configuration.Our approach can be easily applied to baseline design for similar turbulence profilers at other sites.

Profile of Full-Term Births in Maternity Wards of Public Hospitals in Douala Cameroon

Introduction: Pregnancy as much as childbirth constitutes a risky situation, potentially fraught with sometimes dramatic complications: maternal death. Objective: We conducted this study with the aim of establishing the profile of those giving birth in our context with the aim to anticipate operationally in the future on morbidity but more on maternal deaths. Methodology: We conducted, using a structured questionnaire, a prospective descriptive study in representative maternity wards in the city of Douala;the study variables were socio-economic, anthropometric, obstetrical and clinical. Statistical analyses were carried out with CS Pro 7.3 and SPSS version 25.0 software. The Student, Chi-square and Fischer tests were used to compare the means of the variables and the percentages. Results: We recruited 305 births for our study. The average age of our births was 28.7 years ± 6.1 with an average height of 161.6 cm ± 5.06;an average body mass index at the start of pregnancy of 28.0 kilograms/square meter and 31.3 kilograms/square meter at delivery;the average weight gain was 8.4 g ± 5.37;an average gestation of 2.84±1.90;an average parity of 2.2 ± 2.1 with an average birth interval of 27.7 months ± 23.7. The average gestational age was 39.2 weeks ± 1.21 with pregnancy pathology dominated by malaria;85.9% began their prenatal follow-up before the 14th week of amenorrhea. Conclusion: The profile of childbirth in urban Cameroon does not seem potentially dystocic compared to that of the same regional and racial area.

Immunovirological Profile of HIV1 Infection in Children and Adolescents Followed at the Bangui Pediatric University Hospital

History: Pediatric management of HIV infection in children in the Central African Republic began in 2004 with the use of fractionated adult antiretrovirals and Cotrimoxazole. It has evolved over the years with the use of pediatric forms, oral suspensions and dispersible tablets. The transition to Dolutegravir took place in 2020. The active file of our patients will grow from 78 to over 1900 today. Follow-up examinations are carried out to assess adherence to treatment. Objective: To determine the immunovirological profile and factors associated with treatment failure during follow-up of children on ART at the Bangui pediatric university hospital. Patients and Method: This was a cross-sectional, analytical study from May 30 to December 02, 2022. The study sample was drawn from a cohort of HIV-1-infected children followed up at the Bangui pediatric university hospital and on ART for three semesters who met the selection criteria. Results: The prevalence of treatment failure varied from one semester to the next. Thus, the prevalence of therapeutic failure was 20% in the first semester, 10% in the second semester and 7% in the third semester. The prevalence of virological failure was 10.28% in the first half of the year, 6.91% in the second half and 4.98% in the third. Secondly, immunological failure was 0.48% in the first half of the year, 0.32% in the second 0.64% in the third half. Finally, clinical failure was 8.82% in the first half, 4.82% in the second half, 1.92% in the third half. Socio-demographic and clinical factors associated with treatment failure were male gender (p 1000 copies/ml (p Conclusion: The occurrence of treatment failures in children is a major problem, especially in our resource-limited countries, given the challenges facing antiretroviral therapy. It is therefore necessary to carry out a study on resistance genotyping in order to propose correct management protocols, as the future of treatment programs depends on it.

TP-PROFILE: Monitoring the Thermodynamic Structure of the Troposphere over the Third Pole

Ground-based microwave radiometers(MWRs)operating in the K-and V-bands(20–60 GHz)can help us obtain temperature and humidity profiles in the troposphere.Aside from some soundings from local meteorological observatories,the tropospheric atmosphere over the Tibetan Plateau(TP)has never been continuously observed.As part of the Chinese Second Tibetan Plateau Scientific Expedition and Research Program(STEP),the Tibetan Plateau Atmospheric Profile(TPPROFILE)project aims to construct a comprehensive MWR troposphere observation network to study the synoptic processes and environmental changes on the TP.This initiative has collected three years of data from the MWR network.This paper introduces the data information,the data quality,and data downloading.Some applications of the data obtained from these MWRs were also demonstrated.Our comparisons of MWR against the nearest radiosonde observation demonstrate that the TP-PROFILE MWR system is adequate for monitoring the thermal and moisture variability of the troposphere over the TP.The continuous temperature and moisture profiles derived from the MWR data provide a unique perspective on the evolution of the thermodynamic structure associated with the heating of the TP.The TP-PROFILE project reveals that the low-temporal resolution instruments are prone to large uncertainties in their vapor estimation in the mountain valleys on the TP.

Neurocognitive Profile of People Living with Human Immunodeficiency Virus Initiating Treatment in Kinshasa in the Dolutegravir Era, Democratic Republic of Congo

Context: Antiretroviral therapies improve the prognosis of NeuroAIDS contrasting with a high frequency of Minor Neurocognitive Disorders (MND) even in aviremic subjects. Objective: The objective of this study is to present the neurological and cognitive profile of People Living with HIV (PLHIV) initiating antiretroviral treatment in Kinshasa in the era of Dolutegravir (DTG). Methods: This is a multicenter, cross-sectional study with a descriptive aim carried out in 16 HIV Outpatient Treatment Centers (OTC) in Kinshasa from October 4, 2021 to February 15, 2022. The International HIV Dementia Scale (IHDS) correlated with the Activities of Daily Living (IADL) scale facilitated the categorization of NeuroCognitive Disorders (NCD) of PLHIV evaluated after carrying out a summary neurological examination. Results: Of the 96 patients recruited, 56.3% were women with a sex ratio of 0.68. The average age was 40.1 ± 12.1 years. The secondary education level was the majority at 64.6%. Malaria (44.8%) and tuberculosis (32.3%) were more common as opportunistic infections. They were alcoholics in (30.2%). Their history was heart disease (15.6%), high blood pressure (18.8%);drug abuse (10.4%). The IHDS score was light in 55.2% of cases. The correlation between IHDS/IADL watches asymptomatic neurocognitive impairments (ANI) in 77.1%, almost all of subjects are found with normal overall functioning (94.8%) and a disturbed neurological examination in 53.1% of cases with a predominance of motor impairments in 79.1%. Conclusion: In view of these results, early and systematic screening of NCD and associated factors remains necessary in our context. .

An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.