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Non ST elevation myocardial infarction (NSTEMI) has been the subject of numerous studies. Risk stratification is a fundamental element for the management of NSTEMI; therefore, several scores have been established in this direction, particularly prognostic markers derived from the ECG. Aims: The aim of our study is to correlate the dispersion of the QRS with the severity of coronary lesions assessed by the GENSINI score in patients admitted for NSTEMI at the University Hospital of Marrakech. Methods: A retrospective study was conducted in the cardiology department of Mohammed VI university hospital of Marrakech from January 01, 2022 to March 31, 2022. Data was derived from the hospitalization register, including 30 patients (16 women and 14 men). Age ranged from 56 to 74 years with an average of 64.6 ± 9.3. Data was analyzed by SPSS, the level of significance set at p 20 ms) and admission heart rate (p=0.003) as well as the level of ultrasensitive troponins (p=0.003). There is also a very significant correlation between QRS dispersion and corrected QT interval (p=0.005), Moreover, we concluded that in patients admitted for NSTEMI, the greater the dispersion of the QRS, the higher the score of GENSINI (p

In semi-arid contexts, the strong spatiotemporal fluctuation of rainfall and the sparsity of the rain gauge (RG) measurement networks are the main limitations for water resources management. Freely available satellite-based rainfall estimates can be a potential source of information to cop data limitations over poorly gauged regions. Thus, the main aim of this work was to investigate how eight Spatial Rainfall Products (SRP, ARC-2, CHIRPSp25, CHIRPSp5, CMORPH-CRT, GPM-IMERG, PERSIANN-CDR, RFE-2, and TRMM-3B42) can be able to reproduce the observed monthly rainfall over a semi-arid context. The SRP estimates were directly evaluated against the RG observations. Then, bias correction techniques were used to account for the bias in the SRPs. The results indicated that the SRPs poorly correlate with the daily rainfall patterns (with Pearson Correlation Coefficients (PCCs) mostly below 0.5) but agreed with the monthly observations. The agreement was stronger over the lowlands than over the mountainous region. Overall, out of all the considered SRPs, IMERG (with a short-term record) and PERSIANN (with a long-term record) performed the best. Still, the monthly SRP estimates were significantly biased as the large rainfall totals were frequently underestimated. However, when the bias correction was applied remarkable improvement in the SRP’s performance was observed. The different adopted correction techniques yielded close results, with a slight prevalence of the Cumulative Distribution Function (CDF) over the Linear Scaling (LS), and Simple Linear Regression (SLR) techniques. Still, to reliably adjust the bias in the SRP estimates, LS and SLR should be preferred over the CDF technique, as they demonstrated more spatially consistent performance after validation.

Mediterranean countries are strongly affected by reduced surface water resources. This study aims to assess the climate change impacts on runoff supply to the Bin El Ouidane dam in Morocco, the lar...

FVII (factor VII) is vitamin K-dependently synthesized in the liver. Hepatopathies, vitamin K deficiency, or use of vitamin K antagonists are the causes of acquired deficiency. Other types of acquired FVII deficiencies are rare. However, based on literature the incidence might be underestimated. The clinical manifestation of acquired FVII deficiency varies greatly in severity; asymptomatic course as well as severe life-threatening bleeding diathesis and fatal bleedings have been described. In this case report, we discuss a unique presentation of a 79-year-old male who was found to have cardiac tamponade revealing a severe acquired factor VII deficiency. A discordance between a prolonged PT and a normal aPTT was found in the biology lab report. And the diagnosis was confirmed by obtaining a factor VII activity assay. His management involved correction of his factor VII deficiency with fresh frozen plasma and pericardiocentesis.

Introduction:This study aims at reporting the RA male frequency while undergoing biotherapy and describing the epidemiological characteristics (clinical, biological and radiological) in relation to female RA. It also evaluates its impact on the response to biological treatments. Materials and methods: There are 224 patients followed for rheumatoid arthritis, responding to ACR/EULAR 2010 criteria during their biotherapy. They were included in the national RBSMR registry. The patients were divided into two groups and were compared at the basis of their gender in terms of the socio-demographic, clinical, biological, radiological parameters, and response to the treatement. Results: The average age of the patients under study is 51.94 ans±11.36 years old [20-80]. The presence of male rheumatoid arthritis under biotherapy is 12.4%. The mean age of RA male is 55.96+9 years old. The estimated duration of progression of male RA is 542 weeks with an average diagnostic deadline of 562.61 weeks. As a description of the case study, 28,6% of men are diagnosed with cormobidities (mainly tuberculosis 21.4%) while 10,7% of men are smokers. There is an average sedimentation rate (1st hour) at 52.6mm. Rheumatoid serology is found to be positive in 96.4% of cases. Radiological abnormalities are observed in 90.5% of the cases. Male rheumatoid arthritis is related to a shorter duration of progression (542 versus 768 weeks in females, p=0.01), liberal profession (p=0.00), study level (p=0.003), duration between diagnosis and the starting of biotherapy (p=0.021), EVA pain patient and physician (p=0.003, p=0.01) Tobacco (p=0.006), and pulmonary tuberculosis (p=0.029). On the other hand, it was not associated with the following parameters: age, duration of diagnosis, disease intensity, rheumatoid serology, structural damage nor with the DAS 28vs response during one year. Conclusion: The male RA rate in RBSMR study is 12.4% in that there is no significant difference between the sexes in clinical presentation, disease activity, disease severity, rheumatoid serology and response to the biotherapy. However, male RA was related to smoking, liberal profession, and history or occurrence of pulmonary tuberculosis.

In this paper, we study the two-machine no-wait flow shop scheduling problem with two competing agents. The objective is to minimize the overall completion time of one agent subject to an upper bound on the makespan of the second agent. We proved the $$\mathcal {NP}$$ -hardness for three special cases: (1) each agent has exactly two operations. (2) the jobs of one agent require processing only on one machine, (3) the no-wait constraint is only required for the jobs of one agent. We exhibited polynomial time algorithms for other restricted cases. We also proposed a mathematical programming model and a branch and bound scheme as solving approaches for small-scale problems. For large instances, we present a tabu search meta-heuristic algorithm. An intensive experimental study is conducted to illustrate the effectiveness of the proposed exact and approximation algorithms.

In this study, the potential of phenological indicators derived from Sentinel-2A (S2) time series were evaluated to explore the key variables that allow identifying both cropland and crop types. Ba...

Since the dawn of civilization, the Western Mediterranean region has been a unique path for encounters and exchanges. The stability of the general conditions prevailing in its surrounding was crucial to ensure this vital link between north and south and east and west. However, any imbalance would be the precursor of a harmful domino effect to these environments, where the natural vulnerabilities are combined to a worsening socioeconomic congestion. In both banks, efforts are made not to give way to the fragile balance of water availability and risks. Here, we show that the amount and recurrence of extreme rainfall events contradict with current management scenarios. Our pixel-based assessment of the rain components extracted from the African Rainfall Climatology product reveals an annual increase in the total amount of rainfall and extreme rainfall events. A spatial and a trend analysis of the studied rainfall components were carried out to determine their spatial patterns and magnitude. The cumulative annual rainfall alone will not mean if a year is dry or wet. A wet year can experience great periods of drought, which will have serious repercussions on the socioeconomic and ecological levels. In addition, the increased occurrence of extreme rains can produce floods, intensifying land degradation processes, loss of biodiversity, water availability and economic growth. Decision-makers should be aware that current models of territorial management will not be able to cope with this change and that interdisciplinary cohesion and cross-border actions are the most appropriate solution.

In the Atlas Mountains range, streamflow is largely generated from meltwater supplied by the snowpack during spring and early summer. In this manner, snow is considered an important factor which determining water availability in semi-arid and arid mountains. This substantial part of freshwater stored in the form of snow contributes significantly to mountainous runoff. However, the contribution of snow and rain to the annual and multi-annual water balance remain largely unknown. Hydrological modeling is needed to support water resource assessment and management in the Atlas range. As meteorological data is often scarce, the models must be able to simulate the spatiotemporal heterogeneity of forcing variables while maintaining a low data input requirement.In this study, the performance of the snowmelt runoff model (SRM) is assessed to simulate and forecast daily runoff essentially from snowmelt and rainfall at the Rheraya watershed in the Moroccan High Atlas range over the 2010 - 2016 period. The SRM runoff simulation is tested under two forcing inputs: (i) four snowmelt rates previously estimated by a classical temperature-index model (TI) and three enhanced temperature index models that respectively include the potential clear-sky direct radiation (HTI), the incoming solar radiation (ETI-A), and net solar radiation (ETI-B); (ii) calculated snowmelt from the snow cover area (SCA) products of Moderate-Resolution Imaging Spectroradiometer (MODIS).All SRM simulated runoff were subjected to calibration and validation through the measured runoff in the Tahanaout weather station. The sensibility of recession coefficients was also evaluated. The SRM simulations results over the validation period show an acceptable performance.Keywords: Runoff, SRM, snowmelt, SCA, temperature index model; enhanced degree-day models, MODIS, semi-arid climate, Rheraya, High Atlas, Morocco.

Changes in crop yields may have important implications for food security in Morocco. This study intends to develop an explicit model based solely on phenological parameters derived from Moderate-Re...

This paper addresses the problem of scheduling n identical jobs on a set of m parallel uniform machines. The jobs are subjected to conflicting constraints modelled by an undirected graph G, in which adjacent jobs are not allowed to be processed on the same machine. Minimising the maximum completion time in the schedule (makespan Cmax) is known to be NP-hard. We prove that when G is restricted to complete bipartite graphs the problem remains NP-hard for arbitrary number of machines, however, if m is fixed an optimal solution can be obtained in polynomial time. To solve the general case of the problem, we propose mixed-integer linear programming (MILP) formulations alongside with lower bounds and heuristic approaches. Furthermore, computational experiments are carried out to measure the performance of the proposed methods.

The use of remote sensing data provides valuable information to ensure sustainable land cover management. In this paper, the potential of phenological metrics data, derived from Sentinel-2A (S2) and Landsat 8 (L8) NDVI time series, was evaluated using Random Forest (RF) classification to identify and map various crop classes over two irrigated perimeters in Morocco. The smoothed NDVI time series obtained by the TIMESAT software was used to extract profiles and phenological metrics, which constitute potential explanatory variables for cropland classification. The method of classification applied involves the use of a supervised Random Forest (RF) classifier. The results demonstrated the capability of moderate-to-high spatial resolution (10–30 m) satellite imagery to capture the phenological stages of different cropping systems over the study area. Furthermore, the classification based on S2 data presents a higher overall accuracy of 93% and a kappa coefficient of 0.91 than those produced by L8 data, which are 90% and 0.88, respectively. In other words, phenological metrics obtained from S2 time series data showed high potential for agricultural crop-types classification in semi-arid regions and thus can constitute a valuable tool for decision makers to use in managing and monitoring a complex landscape such as an irrigated perimeter.

Air temperature is an important meteorological variable in many fields of our life. However, the availability of air temperature measurements over large geographic areas is often limited by the weather stations spatial distribution inadequacy, their low density and difficulties of data quality and collection. In this context, this study consists to develop four simple models to estimate the three components of air temperature (Tmin, Tmax and Tmean) from remotely sensed land surface temperature (Ts) derived from NOAA-AVHRR images, and based on the international Koppen-Geiger climate classification of Morocco. The results confirmed the existence of good relationships between the three components of measured air temperatures and land surface temperature derived from NOAA-AVHRR images for the main four climate classes of Morocco. The coefficient of determination, R2, varied between 0.69 and 0.80 for Tmin versus Ts, between 0.62 and 0.74 for Tmax versus Ts, and between 0.69 and 0.79 for Tmean versus Ts. The root mean square error varied between 3.1 °C and 3.3 °C for Tmin versus Ts, between 3.2 and 4.1 °C for Tmax versus Ts and between 2.7 and 3.4 °C for Tmean versus Ts. K-fold cross validation method was performed to assess the accuracy and the stability of proposed models. The limited number of proposed models is a great advantage to carry further studies requiring air temperature’s components at larger scale.

Scheduling problem with agreement graph on two identical machines is addressed. The problem consists in scheduling a set of non-preemptive jobs on two identical machines in a minimum time. Agreement constraints are imposed over the jobs. They express that only specific jobs can be scheduled concurrently on different machines. These constraints are represented by an agreement graph. This problem can be seen as a problem of partitioning a vertex-weighted graph into cliques. The problem is NP-hard for an arbitrary agreement graph, but for some particular graphs the problem is still open. For this reason, we study the complexity of the problem for some specific graphs. In particular, we prove the NP-hardness of the problem if the agreement graph is a tree. We also propose polynomial time algorithms to solve the problem for the cases of caterpillars and cycles.

To understand changes in agricultural systems, it is necessary to monitor vegetation dynamics based on the spatio-temporal characterization of phenological parameters. The purpose of this study is to identify the main agricultural systems using a phenology-based classification method in a semi-arid context. Phenological metrics were derived from Normalized Difference Vegetation Index time series extracted from MOD13Q1 product between 2012 and 2016. Furthermore, Support Vector Machine classification method was applied based on phenological metrics, to identify the main agricultural system classes in the study area. The main classes are; (1) irrigated annual crop, (2) irrigated perennial crop, (3) rainfed area and (4) fallow. The classification overall accuracy reached 88%, with a kappa coefficient of 0.83 and values of F1-score greater than 0.76. The results demonstrated the ability of phenological parameters to identify and monitor the main agricultural system classes in the study area and to control the illegal pumping zones.

Petrakos, G, Tynan, NC, Vallely-Farrell, AM, Kiely, C, Boudhar, A, and Egan, B. Reliability of the maximal resisted sprint load test and relationships with performance measures and anthropometric profile in female field sport athletes. J Strength Cond Res 33(6): 1704-1714, 2019-Resisted sled sprint (RSS) training is an effective modality for the improvement of linear sprint speed. Previous methods of RSS load prescription, e.g., an absolute load or as a percentage of body mass (%BM), do not account for interindividual differences in strength, power, or speed characteristics, although the "maximum resisted sled load" (MRSL) method of RSS load prescription may provide a solution. Maximum resisted sled load is defined as the final RSS load before an athlete can no longer accelerate between 2 phases (10-15 and 15-20 m) of a 20-m linear sprint. However, the MRSL test has not been analyzed for reliability. In addition, MRSL performance has not been compared with the outcome of other performance tests. The primary aim of this study was to investigate the reliability of the MRSL testing protocol in female field sport athletes. Participants (age, 20.8 ± 1.9 years; body mass, 64.3 ± 8.4 kg; height, 1.66 ± 0.65 m) tested for anthropometric measurements, strength and power performance testing, and twice for MRSL. Maximum resisted sled load values ranged from 20.7 to 58.9% BM. Maximum resisted sled load test-retest reliability intraclass correlation coefficient, confidence intervals, and coefficient of variations were 0.95, 0.85-0.98, and 7.6%, respectively. Maximum resisted sled load was"moderately" and "strongly" correlated with a number of anthropometric and performance tests (p ≤ 0.05), including percentage fat free mass, countermovement jump, loaded countermovement jump, rate of force development, horizontal jump, and horizontal bound performance. Maximum resisted sled load is a reliable measure for determining the RSS load at which an individual can no longer accelerate during a single RSS effort over 0-20 m. Maximum resisted sled load also accounts for interindividual variation in body composition, power, and speed characteristics of female field sport players.

Precipitation and surface runoff vary strongly in space and time across Morocco. The country’s water management is primarily governed at the basin level, following a decentralized approach. However, in some cases, water is shared between basins, which increases the complexity and the potential for conflicts. The current study, conducted at Oum Er Rbia (OER) basin and Moroccan country scales, evaluates the use of novel Earth Observation (EO) products (surface soil moisture and evapotranspiration) combined with global water balance model (PCR-GLOBWB) for basin level surface runoff and country level drought assessment. At the basin level, OER River discharges considerable surface water amounts from the Middle Atlas Mountains to large reservoirs, providing water for various sectors, predominantly irrigated agriculture. The EO based PCR-GLOBWB model yielded satisfactory monthly surface runoff results validated through two OER streamflow gauges. Spatially distributed quarterly annual surface runoff matched well with the simulations achieved through more detailed Soil and Water Assessment Tool (SWAT) modeling. EO data and PCR-GLOBWB model were subsequently used to investigate country scale drought occurrence using various drought indicators (Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Standardized Soil Moisture Index (SSMI)). The study concludes on a foremost local to regional nature of droughts. Consistent assessment of water stress situations, from the basin to the country scale, suggest the good potential of novel EO products and global models to support demand driven water management, especially in data scarce areas.

International audience; Since April 2002, the Gravity Recovery and Climate Experiment (GRACE) mission have opened new pathways for hydrologists to monitor the changes in terrestrial total water storage (TWS). Here, the Center for Space Research (CSR), Goddard Space Flight Center (GSFC), Jet Propulsion Laboratory (JPL), and the average (AVG) GRACE mascon solutions were used to examine the changes in TWS and groundwater storages (GWS) in Morocco, with an emphasis on natural replenishment events and their link to snow cover area (SCA) and rainfall variability. New hydrological insights for the region: The results showed that GRACE TWS from AVG (TWS AVG) and GSFC (TWS GSFC) can fairly describe the temporal patterns of the groundwater level (GWL). Moreover, during 2002-2020, the TWS underwent a strong depletion relatively masked by natural recharge events. This was revealed as we identified two intermittent depletion episodes with statistically significant rates (− 1.03 ± 0.11 to − 0.31 ± 0.1 cm yr − 1) higher than those obtained for the long-term trend lines (− 0.28 ± 0.11 to − 0.15 ± 0.07 cm yr − 1). The TWS appeared to be strongly linked with the SCA metrics and rainfall indices with 1-3 months of lag. Our findings suggest that the rainfall distribution can be more insightful about changes in groundwater levels compared to the rainfall monthly totals.

Introduction:This study aims at reporting the RA male frequency while undergoing biotherapy and describing the epidemiological characteristics (clinical, biological and radiological) in relation to female RA. It also evaluates its impact on the response to biological treatments. Materials and methods:There are 224 patients followed for rheumatoid arthritis, responding to ACR/EULAR 2010 criteria during their biotherapy. They were included in the national RBSMR registry.The patients were divided into two groups and were compared at the basis of their gender in terms of the socio-demographic, clinical, biological, radiological parameters, and response to the treatement. Results:The average age of the patients under study is 51.94 ans±11.36 years old [20-80]. The presence of male rheumatoid arthritis under biotherapy is 12.4%. The mean age of RA male is 55.96+9 years old. The estimated duration of progression of male RA is 542 weeks with an average diagnostic deadline of 562.61 weeks. As a description of the case study, 28,6% of men are diagnosed with cormobidities (mainly tuberculosis 21.4%) while 10,7% of men are smokers. There is an average sedimentation rate (1st hour) at 52.6mm. Rheumatoid serology is found to be positive in 96.4% of cases. Radiological abnormalities are observed in 90.5% of the cases. Male rheumatoid arthritis is related to a shorter duration of progression (542 versus 768 weeks in females, p=0.01), liberal profession (p=0.00), study level (p=0.003), duration between diagnosis and the starting of biotherapy (p=0.021), EVA pain patient and physician (p=0.003, p=0.01) Tobacco (p=0.006), and pulmonary tuberculosis (p=0.029). On the other hand, it was not associated with the following parameters: age, duration of diagnosis, disease intensity, rheumatoid serology, structural damage nor with the DAS 28vs response during one year. Conclusion:The male RA rate in RBSMR study is 12.4% in that there is no significant difference between the sexes in clinical presentation, disease activity, disease severity, rheumatoid serology and response to the biotherapy. However, male RA was related to smoking, liberal profession, and history or occurrence of pulmonary tuberculosis.

During the last few decades, the frequency of drought has significantly increased in Morocco especially for arid and semi-arid regions, leading to a rising of several environmental and economic issues. In this work, we analyse the spatial and temporal relationship between vegetation activity and drought severity at different moments of the year, across an arid area in the western Haouz plain in Morocco. Our approach is based on the use of a set of more than thirty satellite Landsat images data acquired for the period from 2008 to 2017, combined with the Standardized Precipitation Index (SPI) at different time scales and Standardized water-level Index (SWI). The Mann-Kendall and Sen’s slopes methods were used to estimate SPI trends and the Pearson correlation between NDVI and SPI were calculated to assess the sensitivity of vegetation types to drought. Results demonstrated that SPI experienced an overall upward trend in the Chichaoua-Mejjate region, except for 3-months time scale SPI in summer. The vegetation activity is largely controlled by the drought with clear differences between seasons and timesclaes at which drought is assessed. Positives correlations between the NDVI and SPI are dominant across the entire study area except in June when almost half of correlations is negative. More than 80% of the study domain exhibit a correlation exceeding 0.4 for SPI3 and SPI6 in March. Importantly, this study stresses that the irrigation status of land can introduce some uncertainties on the remote sensing drought monitoring. A weak correlation between the SPI and the SWI was observed at different time-scale. The fluctuations of the piezometric levels are strongly affected by the anthropogenic overexploitation of aquifers and proliferation of irrigated plots.

The seasonal snow cover in the Altas mountains of Morocco is an important resource, mostly because it provides melt-water runoff for irrigation during the crop growing season. However, the knowledge on physical properties of the snowpack (e.g., snow water equivalent (SWE) and snowmelt) is still very limited due to the scarcity or the lack of ground measurements in the elevated area. In this study we suggest that the recent progresses of meteorological reanalysis data (e.g., MERRA-2 and ERA-5) open new perspectives to overcome this issue. We fed a distributed snowpack evolution model (SnowModel) with downscaled ERA-5 and MERRA-2 reanalyses and evaluate their performance to simulate snow cover. The modeling covers the period 1981 to 2019 (37 water years). SnowModel simulations were assessed using observations of river discharge, snow height and snow cover area derived from MODIS.For most of hydrological years, the results show a good performance for both MERRA-2 and ERA-5 with a slight superiority of ERA-5, to reproduce the snowpack state.Key words: snow, snow water equivalent, reanalysis , MERRA-2, ERA-5

Crop type mapping provides essential information to control and make decisions related to agricultural practices and their regulations. To map crop types accurately, it is important to capture their phenological stages and fine spatial details, especially in a temporally and spatially heterogeneous landscape. The data availability of new generation multispectral sensors of Landsat-8 (L8) and Sentinel-2 (S2) satellites offers unprecedented options for such applications. Given this, our study aims to display how the synergistic use of these optical sensors can efficiently support crop type mapping research while integrating an object-based image analysis (OBIA). Through the applied methods, we used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) and the flexible spatiotemporal data-fusion model (FSDAF) to blend L8 and S2 data and obtain reliable normalized difference vegetation index (NDVI) datasets with fine spatial and temporal resolution. Then the crop phenological information was extracted using a Savitzky–Golay filter and fused NDVI time series. Finally, a model combining phenological metrics and fused reconstructed NDVI as classification features was developed using a random forest (RF) classifier/OBIA approach. The results show that the FSDAF method creates more accurate fused NDVI and keeps more spatial details than ESTARFM. The FSDAF model was then used to create fused, high-resolution time-series products that were able to extract crop phenology in single-crop fields while providing a very detailed pattern relative to that from individual sensor time-series data. Moreover, combined L8 and S2 data by FSDAF produced highly significant overall classification accuracies (90.03% for pixel-based RF to 93.12% OBIA RF), outperforming individual sensor use (82.57% for L8-only; 88.45% for S2-only). Our proposed workflow highlights the advantage of spatiotemporal fusing and OBIA environment in spatiotemporally heterogeneous areas and fragmented landscapes, which represents a promising step toward generating fast, accurate, and ready-to-use agricultural data products.

During the last few decades, the frequency of drought has significantly increased in Morocco especially for arid and semi-arid regions, leading to a rising of several environmental and economic issues. In this work, we analyse the spatial and temporal relationship between vegetation activity and drought severity at different moments of the year, across an arid area in the western Haouz plain in Morocco. Our approach is based on the use of a set of more than 30 satellite Landsat images acquired for the period from 2008 to 2017, combined with the Standardized Precipitation Index (SPI) at different time scales and Standardized Water-Level Index (SWI). The Mann-Kendall and Sen’s slope methods were used to estimate SPI trends, and the Pearson correlation between NDVI and SPI was calculated to assess the sensitivity of vegetation types to drought. Results demonstrated that SPI experienced an overall downward trend in the Chichaoua-Mejjate basin, except for SPI3 in summer. The vegetation activity is largely controlled by the drought with clear differences between seasons and time scales at which drought is assessed. Positive correlations between the NDVI and SPI are dominant across the entire study area except in June when almost half of correlations is negative. More than 80% of the study domains exhibit a correlation exceeding 0.4 for SPI3 and SPI6 in March. Importantly, this study stresses that the irrigation status of land can introduce some uncertainties on the remote sensing drought monitoring. A weak correlation between the SPI and the SWI was observed at different time scale. The fluctuations of the piezometric levels are strongly affected by the anthropogenic overexploitation of aquifers and proliferation of irrigated plots.

In many Mediterranean countries, climate change issues, namely the scarcity of water resources, are essential for overcoming the obstacles to sustainable food production. In Morocco, cereal growing is a strategic sector that contributes significantly to food security. In order to improve socio-economic conditions in rural areas, the purpose of this study is to develop models for estimating wheat grain yield based on the cost of production. Based on a sample of 100 farms in Tadla, central Morocco, a model for estimating wheat yield in terms of agricultural inputs’ costs, was developed using stepwise regression approach. To evaluate its accuracy, this model was validated subsequently through k-fold cross validation (K-fold CV). This research provides a model to examine the contribution of the cost of each agricultural input to wheat grain yield, with the objective of understanding the types of actions that farmers can take to reduce production costs and ensure their resilience. This is useful in controlling the use of agricultural inputs that have the greatest impact on yields such as irrigation, fertilizers and soil cultivation practices.

The problem of scheduling n unit-time jobs on m uniform machines is raised in this paper. The jobs are subject to conflicting constraints modeled by a graph G, called the conflict graph. Adjacent jobs (conflicting jobs) in G are not allowed to be processed on a same machine. The addressed objective is the minimization of the makespan of the schedule, which is known to be strongly NP-hard in the literature. The contribution of the current paper is an unorthodox branch-and-bound algorithm that proved to be highly efficient through empirical testing.

This study aims to provide accurate information about changes in agricultural systems (AS) using phenological metrics derived from the NDVI time series. Use of such information could help land managers optimize land use choices and monitor the status of agricultural lands, under a variety of environmental and socioeconomic conditions. For this purpose, the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data were used to derive phenological metrics over the Oum Er-Rbia basin (central Morocco). Random forest (RF), support vector machine (SVM), and K-nearest neighbor (KNN) classifiers were explored and compared on their ability to classify AS classes over the study area. Four main AS classes have been considered: (1) irrigated annual crop (IAC), (2) irrigated perennial crop (IPC), (3) rainfed area (RA), and (4) fallow (FA). By comparing the accuracy of the three classifiers, the RF method showed the best performance with an overall accuracy of 0.97 and kappa coefficient of 0.96. The RF method was then chosen to examine time variations in AS over a 16-year period (2000–2016). The AS main variations were detected and evaluated for the four AS classes. These variations have been found to be linked well with other indicators of local agricultural land management, as well as the historical agricultural drought changes over the study area. Overall, the results present a tool for decision makers to improve agricultural management and provide a different perspective in understanding the spatiotemporal dynamics of agricultural systems.

Introduction: Pleuropulmonary involvement in spondylarthritis has long been considered a rare and late manifestation of this group of diseases because of its asymptomatic nature and the failure of chest X-ray to detect early lung injury. However, with the advent of CT scanning, a wide variety of sub-clinical lung lesions that were not detectable on standard radiography have been objectified. Objectives: Research the correlations between lung involvement and the different characteristics and types of spondylarthritis. Materials and Methods: This is a retrospective cohort-type observational epidemiological study, conducted over a 3-year period. 133 patients with spondylarthritiswere included. All had a detailed clinical examination, chest X-ray, respiratory function tests and chest CT scan. Results: 133 patients with spondyloarthropathies; 57 spondyloarthritis, 54 psoriatic arthritis and 22 IBD-associated spondyloarthritis. M/F sex ratio of 1.14. Chest CT scan revealed abnormalities in 58 patients (43.6%) with 13 symptomatic respiratory patients, whereas the standard chest X-ray was abnormal in only 19 cases. Multivariate analysis showed factors associated with CT abnormalities in patients over 60 years of age, with dactylitis, and cervical stiffness. Factors associated with ventilatory abnormalities have also been found in patients over 60 years of age, cervical stiffness, coxitis, inflammatory syndrome, and osteoporosis. No influence of the type of spondylitis was found on the presence or type of lung involvement (p=0.230). Conclusion: This study allowed us to detect certain factors associated with lung damage, revealed early on thoracic CT and EFR, in patients with SpA. It would be judicious to propose this examination in patients with functional respiratory signs even if the standard radiography is normal, even for a wider screening in any SpA patient even asymptomatic.

With ever-increasing concerns about climate change, and in the context of diminishing fossil energy resources, energy consumption has become a subject of great importance. In this framework, our study is concerned with the reduction of the energy consumed by a manufacturing system composed of several unrelated parallel machines. We investigate the problem of scheduling a set of n deteriorating jobs on m parallel unrelated machines subject to a deterioration effect, where the processing time of each job is a linear deterioration function of the starting time. The objective is to determine the best scheduling of the jobs, minimizing the makespan and the total energy consumption. We implement a nondominated sorting-based multiobjective algorithm (NSGA-II)-based approaches with a given scheduling rules to solve the developed mathematical model of the considered problem. The performance of the proposed approaches are compared with an exact algorithm and evaluated through computational experiments. Then, we give a multiobjective decision-making method based on the TOPSIS (technique for order of preference by similarity to ideal solution) technique to determine the best solution from the Pareto front according to the decision-maker’s preferences.

Four models of increasing complexity were tested and compared to simulate snow water equivalent at the local scale in the Moroccan High Atlas range. A classical temperature index model (TI) and thr...

Surface soil moisture content (SSMC) monitoring constitutes an important parameter to estimate crop water requirements, especially in arid and semi-arid areas. Remote sensing became a useful tool f...

River flow and groundwater recharge in the Marrakech region are closely linked to the hydrological dynamics in the High Atlas Mountains. To anticipate the effects of climate change in this area where the pressure on water resources is increasing, it is essential to quantify the contribution of snowmelt and rainfall to runoff. This study aims to modeling the runoff of the Rheraya River in the Moroccan High Atlas (225 km(2), elevations ranging between 1030 and 4165 m.a.s.l.) taking into account its snow component. For this purpose, the GR4J conceptual and lumped model was applied over the period 1989-2009, coupling it with the CemaNeige module for semi-distributed snow dynamics. This work allows for an improved characterization of the hydrologic regime of this watershed. The daily snow coverage simulated by CemaNeige is in good agreement with that extracted from the MODIS snow product in the period 2000-2009 (R-2 = 0,64). In addition, the simulated daily snow water equivalent is consistent with that measured at a weather station (2004-2006, R-2 = 0,81). Finally, the runoff simulation reproduces quite well the strong seasonal and inter-annual variability. However, the low Nash value obtained as compared to standards (0,45), can be linked to the low quality of runoff measurements (unstable riverbed). In conclusion, the hydrological regime of the Rheraya River is pluvio-nival with an unimodal distribution whose maximum in April is linked with snowmelt. It is at this time of the year that downstream populations are most vulnerable to the flow deficit because irrigated crops come into their growth period.

N-phenyl-3-para nitro phenyl isoxazolidine-5-carbonitrile compound (C16H13N3O3) has been synthesized and characterized by single-crystal X-ray diffraction at 293 K. The title compound crystallized in the orthorhombic system (Pbca space group) with Z = 8 and the following unit cell dimensions: a = 12.9970 (9) A, b = 7.3090 (9) A, c = 29.658 (2) A. Raman spectroscopy has been investigated at room temperature. Raman spectra have been measured at 647.5 nm excited laser lines in the frequency range 125–4000 cm−1. The Raman spectrum is characterized by a series of bands in the 150–3500 cm−1 spectral range. The structure of the this compound was optimized by density functional theory (DFT) using B3LYP method and shows that the calculated values obtained by B3LYP/6-31G(d,p) basis are in much better agreement with the experimental data than those obtained by B3LYP/6- 31G(d). The vibrational frequencies were evaluated using density functional theory (DFT) with the standard B3LYP/6-31G(d,p) basis. The Molecular Frontiers Orbitals (FMOS) calculation is carried out to determine the charge transfer within the molecule.

This paper deals with open shops subject to the constraint that some conflicting jobs cannot be processed simultaneously on different machines. In the context of our study, these conflicts are given by an undirected graph, called the conflict graph. We seek a schedule that minimizes the maximum completion time (makespan). We first prove the NP-hardness of different versions of this problem. Then, we present polynomial-time solvable cases, for which we devise simple and efficient algorithms. On the other hand, we present heuristics and lower bounds for the general case. The heuristics are based on the construction of matchings in bipartite graphs as well as on a specific insertion technique combined with beam search. Finally, we test the efficiency of the heuristics and report our computational experiments that display satisfying results.

This paper addresses the problem of scheduling jobs on flow shops subject to constraints given by an undirected graph, in which each edge joins a pair of conflicting jobs that cannot be processed simultaneously on different machines. We first show that the problem of minimizing the maximum completion time (makespan) is NP-hard for several versions. Then, we present polynomial-time solvable cases. On the other hand, we propose heuristic approaches and lower bounds alongside with an experimental study.