Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Distinct Interannual Variability and Physical Mechanisms of Snowfall Frequency over the Eurasian Continent during Autumn and Winter

This study investigates the dominant modes of interannual variability of snowfall frequency over the Eurasian continent during autumn and winter,and explores the underlying physical mechanisms.The first EOF mode(EOF1)of snowfall frequency during autumn is mainly characterized by positive anomalies over the Central Siberian Plateau(CSP)and Europe,with opposite anomalies over Central Asia(CA).EOF1 during winter is characterized by positive anomalies in Siberia and negative anomalies in Europe and East Asia(EA).During autumn,EOF1 is associated with the anomalous sea ice in the Kara–Laptev seas(KLS)and sea surface temperature(SST)over the North Atlantic.Increased sea ice in the KLS may cause an increase in the meridional air temperature gradient,resulting in increased synoptic-scale wave activity,thereby inducing increased snowfall frequency over Europe and the CSP.Anomalous increases of both sea ice in the KLS and SST in the North Atlantic may stimulate downstream propagation of Rossby waves and induce an anomalous high in CA corresponding to decreased snowfall frequency.In contrast,EOF1 is mainly affected by the anomalous atmospheric circulation during winter.In the positive phase of the North Atlantic Oscillation(NAO),an anomalous deep cold low(warm high)occurs over Siberia(Europe)leading to increased(decreased)snowfall frequency over Siberia(Europe).The synoptic-scale wave activity excited by the positive NAO can induce downstream Rossby wave propagation and contribute to an anomalous high and descending motion over EA,which may inhibit snowfall.The NAO in winter may be modulated by the Indian Ocean dipole and sea ice in the Barents-Kara-Laptev Seas in autumn.

Intraseasonal variability of the Kuroshio observed via mooring at 18°N

Insufficient observations near the origin of the Kuroshio have led to incomplete understanding of the intraseasonal variability(ISV)of the Kuroshio.Direct measurements of the Kuroshio velocity were performed with an array of three profiler moorings(122.7°E,123°E,and 123.3°E)along 18°N from January 2018 to February 2020.The ISV of the Kuroshio at 18°N was investigated based on a combination of mooring observations and global high-resolution HYbrid Coordinate Ocean Model reanalysis data.The estimated time-averaged transport in the upper 350 m across the observation transect was 6.5±2.6 Sv(1.0 Sv=10^(6)m^(3)/s).Two significant ISV peaks at 50-60 and~100 d were recognized in the power spectra of the meridional velocity and transport.Further analysis indicated that the ISV at 50-60 d was caused by westward-propagating eddies at average propagation speed of~13 cm/s and wavelength of~635 km.Another ISV peak at~100 d was mainly caused by northward-propagating eddies generated in the North Equatorial Current region.Further investigation indicated that the ISV of the Kuroshio at 18°N is dominated by meridional transport,rather than by the zonal migration of the Kuroshio main axis.Our findings provide a better understanding of the ISV of the Kuroshio east of Luzon Island.

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

Genetic variability and trait association analysis in linseed(Linum usitatissimum L.)for yield and related traits

Diversity information mining about a crop for different attributes is an essential step for effective breeding programs.The present investigation evaluates the quantum of genetic variability and determines the relationship among the important agro-economic traits based on two years of phenotypic data of 210 accessions of linseed.The traits,capsule weight per plant,capsule per plant,husk weight per plant,and seed weight per plant exhibited comparatively higher genetic coefficient of variation(GCV)and phenotypic coefficient of variation(PCV).In contrast,oil content and seed per capsule exhibited a lower value.The high magnitude of broad sense heritability was observed for all traits except seeds per capsule and husk weight per plant.The trait,capsules per plant,plant height,and days to 50%flowering showed high genetic advance coupled with high heritability.Hierarchical cluster analysis grouped 210 accessions into six distinct clusters.Out of 210,144(68.57%)accessions were grouped into three clusters(I,II,and III),in which cluster-III was the largest,containing 64 accessions followed by cluster II and cluster-I.The highest inter-cluster distance was observed between clusters-I and V(127.85),while the lowest was between clusters-II and IV(27.09).The positive correlation of capsule weight per plant with the seed weight per plant and a negative correlation with the days to 50%flowering indicates that high yielding linseed varieties with early flowering/maturity could be developed through direct and indirect selection.Further,seed yield and oil content could be enhanced together as indicated by ghe positive association among these two important traits.In this study,high yielding accessions with moderate to high oil content such as GP36,GP31,GP14,GP54,GP26,GP24,GP34,GP21,GP37 and GP27 and early flowering(less than 70 days)accessions such as GP2,GP26,GP27,CG33,CG44,CG42,CG132,and CG31 identified as potential genetic materials that could be exploited for developing early maturing varieties with high yield.In addition,information’s on various genetic parameters will help breeders to devise suitable breeding methodology for linseed genetic improvement for targeted traits.

Quran memorisation and heart rate variability:How do they correlate?

BACKGROUND Heart rate variability(HRV)was shown to be affected by performing religious activities.AIM To examine the relationship between the level of Quran(the holy book of Muslims)memorisation and HRV among teenagers.METHODS This experimental study included 16 Tahfiz students and 16 non-Tahfiz students(n=32).The HRV was measured in three tasks:Recalling familiar verses,memorising new verses,and recalling the newly memorised verses of the Quran.HRV analysis was done using these parameters:Standard deviation of N-N(heartbeat peak)interval;low frequency(LF);high frequency(HF)and LF/HF ratio.RESULTS There were significant differences between tasks for all parameters(P<0.05).However,between the groups,only the LF/HF ratio had significant differences,with F=5.04,P<0.05.Pearson correlation showed a moderate positive correlation between the number of pages memorised and the LF/HF ratio(r=0.61,P<0.05).CONCLUSION Quran memorisation increased the HRV and our results suggested that this activity could be developed as an effective sympathovagal modulation training activity.

A comprehensive review of heart rate variability as an indicator in the regulation of the autonomic nervous system by acupuncture:a bibliometric analysis

This study sought to conduct a bibliometric analysis of acupuncture studies focusing on heart rate variability(HRV)and to investigate the correlation between various acupoints and their effects on HRV by utilizing association rule mining and network analysis.A total of 536 publications on the topic of acupuncture studies based on HRV.The disease keyword analysis revealed that HRV-related acupuncture studies were mainly related to pain,inflammation,emotional disorders,gastrointestinal function,and hypertension.A separate analysis was conducted on acupuncture prescriptions,and Neiguan(PC6)and Zusanli(ST36)were the most frequently used acupoints.The core acupoints for HRV regulation were identified as PC6,ST36,Shenmen(HT7),Hegu(LI4),Sanyinjiao(SP6),Jianshi(PC5),Taichong(LR3),Quchi(LI11),Guanyuan(CV4),Baihui(GV20),and Taixi(KI3).Additionally,the research encompassed 46 reports on acupuncture animal experiments conducted on HRV,with ST36 being the most frequently utilized acupoint.The research presented in this study offers valuable insights into the global research trend and hotspots in acupuncture-based HRV studies,as well as identifying frequently used combinations of acupoints.The findings may be helpful for further research in this field and provide valuable information about the potential use of acupuncture for improving HRV in both humans and animals.

Geospatial Variability of Cholera Cases in Malawi Based on Climatic and Socioeconomic Influences

Cholera remains a public health threat in most developing countries in Asia and Africa including Malawi with seasonal recurrent outbreaks. Malawi’s recent Cholera outbreak in 2022 and 2023, exhibited higher morbidity and mortality rates than the past two decades. Lack of spatiotemporal-based technology and variability assessment tools in Malawi’s Cholera monitoring and management, limit our understanding of the disease’s epidemiology. The present work developed a spatiotemporal variability model for Cholera disease at district level and its relationship to socioeconomic and climatic factors based on cumulative confirmed Cholera cases in Malawi from March 2022 to July 2023 using Z-score statistic and multiscale geographically weighted regression (MGWR) in a Geographical Information System (GIS). We found out that socioeconomic factors such as access to safe drinking water, population density and poverty level, and climatic factors including temperature and rainfall strongly influenced Cholera prevalence in a complex and multifaceted manner. The model shows that Lilongwe, Mangochi, Blantyre and Balaka districts were highly vulnerable to Cholera disease followed by lakeshore districts of Salima, Nkhotakota, Nkhata-Bay and Karonga than other districts. We recommend strategic measures such as Water, Sanitation, and Hygiene (WASH) interventions, community awareness on proper water storage, Cholera case management, vaccination campaigns and spatial-based surveillance systems in the most affected districts. This research has shown that MGWR, as a surveillance system, has the potential of providing insights on the disease’s spatial patterns for public health authorities to identify high-risk districts and implement early response interventions to reduce the spread of the disease.

Extent and Structure of Phenotypic Variability in Solenostemon rotundifolius Germplasm from Ghana and Burkina Faso

Solenostemon rotundifolius is a species belonging to the Lamiaceae family. It is currently one of the minor plants of high socio-economic interest. One of the limitations to promoting this species in Burkina Faso is the lack of varieties that meet consumers’ demands. Implementing a breeding program is an important step toward achieving this goal. Such a program is based on the variability of agronomical traits of interest within evaluated germplasm. This study aimed to assess the level of two germplasms variability of S. rotundifolius from Ghana and Burkina Faso for traits related to vegetative development, cycle, and yield. Agromorphological characterization of 174 accessions, including 116 from Ghana and 58 from Burkina Faso was carried out in Randomised Complete Block Design with three replications. The characterization was made on the basis of fifteen (15) quantitative traits related to the canopy and leaf size, the cycle, and the yield. Analysis of variance revealed significant differences between accessions within each germplasm for all the evaluated traits. The analysis of the structuration of this agromorphological variability allowed organizing the accessions into different groups. These results could lead to the identification of accessions within each germplasm for breeding purposes or future research on genotype-environment interactions.

Application of Predictive Model for Efficient Cassava (Manihot esculenta Crantz) Yield in the Face of Climate Variability in Enugu State, Nigeria

Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate variability incidence which can be communicated to local farmers by agro-meteorological extension officers, research on crops that can grow with little or no rain, planning irrigation scheme, and improving tree planting culture in the study area.

Tea Production Response to Seasonal Rainfall Variability: Evidence from Rwanda

Tea is a very important cash crop in Rwanda, as it provides crucial income and employment for farmers in poor rural areas. From 2017 to 2020, this study was intended to determine the impact of seasonal rainfall on tea output in Rwanda while still considering temperature, plot size (land), and fertiliser for tea plantations in three of Rwanda’s western, southern, and northern provinces, western province with “Gisovu” and “Nyabihu”, southern with “Kitabi”, and northern with “Mulindi” tea company. The study tested the level of statistical significance of all considered variables in different formulation of panel data models to assess individual behaviour of independent variables that would affect tea production. According to this study, a positive change in rainfall of 1 mm will increase tea production by 0.215 percentage points of tons of fresh leaves. Rainfall is a statistically significant variable among all variables with a positive impact on tea output Qitin Rwanda’s Western, Southern, and Northern provinces. Rainfall availability favourably affects tea output and supports our claim. Therefore, there is a need for collaboration efforts towards developing sustainable adaptation and mitigation options against climate change, targeting tea farming and the government to ensure that tea policy reforms are targeted towards raising the competitiveness of Rwandan tea at local and global market.

Analysis of Extreme Temperature Variability in Rwanda

The temperature is one of the most important factors in weather and climate forecasting.Studying its behaviour is crucial to understanding climate variability,which could vary spatially and temporally at local,regional,and global scales.Several recent studies on air temperature findings show that the Earth’s near surface air temperature increased between 0.6℃ and 0.8℃ throughout the twentieth century.Using temperature records from ten meteorological stations,this study examined climate variability in Rwanda from the 1930s to 2014.The air temperature data were collected from Meteo Rwanda.Before making the analysis,the authors used software,such as Excel 2007 and INSTAT to control the quality of the raw data.The analysis of maxima and minima indicated that the trends of maximum air temperature were positive and significant at height meteorological stations,whereas the trends for minimum air temperature were found to be at 10 meteorological stations.For all parameters analysed,Kigali Airport meteorological station indicated the higher significance of the trends.The majority of meteorological stations showed an increase in both hot days and nights,confirming Rwanda’s warming over time.The analysis of average seasonal air temperature showed almost similar trends even though not all were significant.This similarity in trends could be attributed to the fact that Rwanda’s short and long dry seasons coincide with rainy seasons.

Influence of Continental Atmospheric Forcing on the Decadal Variability of the West African Monsoon

The West African Monsoon (WAM) is characterized by strong decadal and multi-decadal variability and the impacts can be catastrophic for the local populations. One of the factors put forward to explain this variability involves the role of atmospheric dynamics, linked in particular to the Saharan Heat Low (SHL). This article addresses this question by comparing the sets of preindustrial control and historical simulation data from climate models carried out in the framework of the CMIP5 project and observations data over the 20th century. Through multivariate statistical analyses, it was established that decadal modes of ocean variability and decadal variability of Saharan atmospheric dynamics significantly influence decadal variability of monsoon precipitation. These results also suggest the existence of external anthropogenic forcing, which is superimposed on the decadal natural variability inducing an intensification of the signal in the historical simulations compared to preindustrial control simulations. We have also shown that decadal rainfall variability in the Sahel, once the influence of oceanic modes has been eliminated, appears to be driven mainly by the activity of the Arabian Heat Low (AHL) in the central Sahel, and by the structure of the meridional temperature gradient over the inter-tropical Atlantic in the western Sahel.

Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.

Recent Enhancement in Co-Variability of the Western North Pacific Summer Monsoon and the Equatorial Zonal Wind

The western North Pacific summer monsoon(WNPSM)is an important subcomponent of the Asian summer monsoon.The equatorial zonal wind(EZW)in the lower troposphere over the western Pacific may play a critical role in the evolution of the El Niño-Southern Oscillation(ENSO).The possible linkage between the EZW over the western Pacific and the offequatorial monsoonal winds associated with the WNPSM and its decadal changes have not yet been fully understood.Here,we find a non-stationary relationship between the WNPSM and the western Pacific EZW,significantly strengthening their correlation around the late 1980s/early 1990s.This observed shift in the WNPSM–EZW relationship could be explained by the changes in the related sea surface temperature(SST)configurations across the tropical oceans.The enhanced influence from the springtime tropical North Atlantic,summertime tropical central Pacific,and maritime continent SST anomalies may be working together in contributing to the recent intensified WNPSM–EZW co-variability.The observed recent strengthening of the WNPSM–EZW relationship may profoundly impact the climate system,including prompting more effective feedback from the WNPSM on subsequent ENSO evolution and bolstering a stronger biennial tendency of the WNPSM–ENSO coupled system.The results obtained herein imply that the WNPSM,EZW,ENSO,and the tropical North Atlantic SST may be closely linked within a unified climate system with a quasi-biennial rhythm occurring during recent decades,accompanied by a reinforcement of the WNPSM–ENSO interplay quite possibly triggered by enhanced tropical Pacific–Atlantic cross-basin interactions.These results highlight the importance of the tropical Atlantic cross-basin influences in shaping the spatial structure of WNPSM-related wind anomalies and the WNPSM–ENSO interaction.

Synchronous measurements of prefrontal activity and pulse rate variability during online video game playing with functional near-infrared spectroscopy

Interactions between the central nervous system(CNS)and autonomic nervous system(ANS)play a crucial role in modulating perception,cognition,and emotion production.Previous studies on CNS–ANS interactions,or heart–brain coupling,have often used heart rate variability(HRV)metrics derived from electrocardiography(ECG)recordings as empirical measurements of sympathetic and parasympathetic activities.Functional near-infrared spectroscopy(fNIRS)is a functional brain imaging modality that is increasingly used in brain and cognition studies.The fNIRS signals contain frequency bands representing both neural activity oscillations and heartbeat rhythms.Therefore,fNIRS data acquired in neuroimaging studies can potentially provide a single-modality approach to measure task-induced responses in the brain and ANS synchronously,allowing analysis of CNS–ANS interactions.In this proof-of-concept study,fNIRS was used to record hemodynamic changes from the foreheads of 20 university students as they each played a round of multiplayer online battle arena(MOBA)game.From the fNIRS recordings,neural and heartbeat frequency bands were extracted to assess prefrontal activities and shortterm pulse rate variability(PRV),an approximation for short-term HRV,respectively.Under the experimental conditions used,fNIRS-derived PRV metrics showed good correlations with ECG-derived HRV golden standards,in terms of absolute measurements and video game playing(VGP)-related changes.It was also observed that,similar to previous studies on physical activity and exercise,the PRV metrics closely related to parasympathetic activities recovered slower than the PRV indicators of sympathetic activities after VGP.It is concluded that it is feasible to use fNIRS to monitor concurrent brain and ANS activations during online VGP,facilitating the understanding of VGP-related heart–brain coupling.

Preoperative carbohydrate load to reduce perioperative glycemic variability and improve surgical outcomes:A scoping review

The detrimental effects of both diabetes mellitus(DM)and hyperglycemia in the perioperative period are well established and have driven extensive efforts to control blood glucose concentration(BGC)in a variety of clinical settings.It is now appreciated that acute BGC spikes,hypoglycemia,and high glycemic variability(GV)lead to more endothelial dysfunction and oxidative stress than uncomplicated,chronically elevated BGC.In the perioperative setting,fasting is the primary approach to reducing the risk for pulmonary aspiration;however,prolonged fasting drives the body into a catabolic state and therefore may increase GV.Elevated GV in the perioperative period is associated with an increased risk for postoperative complications,including morbidity and mortality.These challenges pose a conundrum for the management of patients typically instructed to fast for at least 8 h before surgery.Preliminary evidence suggests that the administration of an oral preoperative carbohydrate load(PCL)to stimulate endogenous insulin production and reduce GV in the perioperative period may attenuate BGC spikes and ultimately decrease postoperative morbidity,without significantly increasing the risk of pulmonary aspiration.The aim of this scoping review is to summarize the available evidence on the impact of PCL on perioperative GV and surgical outcomes,with an emphasis on evidence pertaining to patients with DM.The clinical relevance of GV will be summarized,the relationship between GV and postoperative course will be explored,and the impact of PCL on GV and surgical outcomes will be presented.A total of 13 articles,presented in three sections,were chosen for inclusion.This scoping review concludes that the benefits of a PCL outweigh the risks in most patients,even in those with well controlled type 2 DM.The administration of a PCL might effectively minimize metabolic derangements such as GV and ultimately result in reduced postoperative morbidity and mortality,but this remains to be proven.Future efforts to standardize the content and timing of a PCL are needed.Ultimately,a rigorous data-driven consensus opinion regarding PCL administration that identifies optimal carbohydrate content,volume,and timing of ingestion should be established.

Agro-Climatic Risks Analysis in Climate Variability Context in Ségou Region

In the Sahel region, the population depends largely on rain-fed agriculture. In West Africa in particular, climate models turn out to be unable to capture some basic features of present-day climate variability. This study proposes a contribution to the analysis of the evolution of agro-climatic risks in the context of climate variability. Some statistical tests are used on the main variables of the rainy season to determine the trends and the variabilities described by the data series. Thus, the paper provides a statistical modeling of the different agro-climatic risks while the seasonal variability of agro-climatic parameters was analyzed as well as their inter annual variability. The study identifies the probability distributions of agroclimatic risks and the characterization of the rainy season was clarified.

Relationship between glycemic variability and cognitive function in lacune patients with type 2 diabetes

BACKGROUND Lacunes are the manifestations of lacunar infarction which can lead many patients to the clinical outcome of disability or dementia.However,the relationship between lacune burden,cognitive function and blood glucose fluctuation in patients with type 2 diabetes mellitus(T2DM)complicated with lacunes is not very clear.AIM To explore the correlation between glucose variability,lacune burden and cognitive function in patients with lacunes complicated with T2DM.METHODS The clinical and imaging data of 144 patients with lacunes combined with T2DM were reviewed retrospectively.72 h continuous glucose monitoring was performed.The Montreal Cognitive Assessment was used to assess cognitive function.The burden of lacunes was evaluated using magnetic resonance imaging performance.Multifactorial logistic regression analysis was used to study the affecting the lacune load and cognitive impairment in patients.To predict the value of patients’cognitive impairment with lacunes complicated with T2DM,a receiver operating characteristic(ROC)curve and a nomogram prediction model were constructed.RESULTS The standard deviation(SD)of the average blood glucose concentration,percentage coefficient of variation(%CV)and time of range(TIR)were significantly different between the low and the high load groups(P<0.05).The SD,%CV and TIR of the cognitive impairment group and non-cognitive impairment group were significantly different(P<0.05).SD(odds ratio(OR):3.558,95%confidence interval(CI):1.268-9.978,P=0.006),and%CV(OR:1.192,95%CI:1.081-1.315,P<0.05)were the risk factors for an increased infarct burden in lacunes patients complicated with T2DM.TIR(OR:0.874,95%CI:0.833-0.928,P<0.05)is a protective factor.In addition,an increased SD(OR:2.506,95%CI:1.008-6.23,P=0.003),%CV(OR:1.163,95%CI:1.065-1.270,P<0.05)were the risk factors for cognitive impairment in patients with lacunes complicated with T2DM,TIR(OR:0.957,95%CI:0.922-0.994,P<0.05)is a protective factor.A nomogram prediction model of the risk of cognitive impairment was established based on SD,%CV and TIR.Decision curve analysis and the internal calibration analysis were used for internal verification and showed that the model was clinical benefit.The area under the ROC curves for predicting cognitive impairment in patients with lacunes complicated with T2DM was drawn were%CV:0.757(95%CI:0.669-0.845,P<0.05),TIR:0.711(95%CI:0.623-0.799,P<0.05).CONCLUSION Blood glucose variability is closely associated with the level of lacune burden and cognitive dysfunction in lacune patients combined with T2DM.%CV,TIR have a certain predictive effect in cognitive impairment in lacune patients.