Food sales prediction model using machine learning techniques

Food sales prediction means how to obtain future results of sales of companies. The purpose of this step is to increase the profits of these companies by avoiding spoilage of food products and avoiding buying more quantities than the needs of these companies, which means the accumulation of these products in the warehouses without selling them. Stocked and expired products require a model that guesses the actual future need for these products. In this study, a model for food sales prediction using machine learning algorithms is proposed to achieve two objectives, first: make a comparison between two datasets, one dataset with a high correlation between its features, and another dataset has a low correlation between its features. The second objective is to use several machine learning algorithms for prediction and comparing between these algorithms to find the best three algorithms that give the best prediction. By using the most important metrics such as root mean square error (RMSE) and mean square error (MSE) found the best three algorithms by using the first dataset are support vector machines (SVMs), least absolute shrinkage and selection operator (LASSO), and bagging regressor) and the best three algorithms by using the second dataset are (gradient boosting, random forest regressor, and decision tree)

Reforestation in Algeria: History, current practice and future perspectives

Reforestation in Algeria has been recognized as a priority in different programs for the development and enhancement of forest heritage. Degradation factors of forest and soil contribute significantly to the decline in land values. The Algerian forests in the past, during the colonial period suffered considerable degradation. The degraded forest heritage has been undertaken with serious programs since independence. Several programs for the development of the forest sector through reforestation have been carried out. Unfortunately, the achievements were still below expectations. The launch of the National Reforestation Plan in 2000 has given the forestry sector a new lease of life with a vision that incorporates the productive aspect of reforestation, the industrial aspect, and the recreational aspect. Before the end of the NRP timeline, significant reforestation projects are completed. In a future projection, reforestation is integrated into the land use planning within the framework of the National Plan of Land Use Planning

Influence of Highway Traffic on Contamination of Roadside Soil with Heavy Metals

This study is one of the first works which examined the assessment of heavy metal contamination of pavement-side soils in Algeria. It deals with the section of National Highway 3 (RN3), which crosses the wilaya of Batna. In the environment of sampling sites there is no industry or dangerous activity on the environment, the heavy metals addressed in this study are (Pb, Cu, Cr, Fe, Ni, Zn), their origin being road traffic. The objectives of this study were to: (1) Determine the concentrations of heavy metals in road dust; (2) Identify the sources of different heavy metals in soils and road dust; (3) Exploring the extent of heavy metal pollution in neighbouring soils. To this end, 33 samples were collected, including 03 road dust and 30 soil samples over different distances from 1m to 80m. The samples were analyzed by FRX. Results indicated that concentrations in road dust were higher than in soil. The distribution of heavy metal concentrations in dust is Fe>Pb>Zn>Cu>Cr>Ni, and the distribution in the ground is Fe>Pb>Cu>Zn>Cr>Ni in the direction of Biskra and in the opposite direction and decreases away from the road, while the distribution in the central solid ground is Fe> Cu>Cr>Pb>Zn>Ni. Climatic conditions such as wind, rainfall, temperature, humidity and the nature of the terrain were also significantly related to their enrichment in these roadside soils. The enrichment factor (EF) and the geo-accumulation index (Igeo) were calculated, as well as all elements with a (EF) that ranges from moderate to high to extremely contaminated, reflecting the high anthropogenic load of these metals in the study area and the results of the Igéo accumulation indices confirm the results obtained for the enrichment factor (EF). Doi: 10.28991/cej-2021-03091736 Full Text: PD

Experimental and Numerical Study on RC Beams Strengthened by NSM Using CFRP Reinforcements

Near Surface Mounted (NSM) Carbon Fiber-Reinforced Polymer (CFRP) reinforcement technique to improve the flexural strength of reinforced concrete members has become increasingly attractive in recent years. In this study, the practical problem of concrete cover depth cutting limitation was investigated. Twelve specimens were tested by four-point bending until failure. Experimental parameters include concrete cover depth, CFRP reinforcement type, CFRP positioning, and stirrups status. Furthermore, a nonlinear FEA model was developed to simulate the tested beams and was able to predict the experimental behavior satisfactorily. A series of parametric studies were then performed using this model to understand the effect of various reinforcement parameters on the flexural performance of the beam. The results showed that Strengthening with CFRP resulted in a significant increase in yield and ultimate strengths, but a significant ductility loss was recorded due to CFRP strip debonding in the strengthened beams, this problem was addressed by using more efficient strengthening techniques utilizing the effective bond length and a proper groove depth and positioning for the NSM bars

Changes in MiRNA-5196 expression as a potential biomarker of anti-TNF-α therapy in rheumatoid arthritis and ankylosing spondylitis Patients

In this study, we analysed the expression level of sera circulating miRNA-5196 in rheumatoid arthritis (RA) and ankylosing spondylitis (AS) patients before and after tumor necrosis factor (TNF)-α therapy as biomarkers predicting positive treatment outcome. We enrolled 10 RA patients, 13 AS patients, and 12 healthy individuals in the study. The expression of miRNA-5196 was measured by real-time polymerase chain reaction before and after anti-TNF-α therapy. Disease activity of RA patients was assessed using disease activity score 28 (DAS28), whereas ankylosing spondylitis DAS (ASDAS) was used in AS patients. MiRNA-5196 expression was significantly higher in patients with RA and AS before TNF-α therapy than in those following anti-TNF-α therapy and healthy controls. Changes in miRNA-5196 expression positively correlated with delta DAS28 or delta ASDAS, respectively, following TNF-α therapy. In contrast, changes in C-reactive protein (CRP) levels in RA and AS patients did not positively correlate with DAS28 or ASDAS changes. Receiver-operating characteristic analysis showed better diagnostic accuracy of miRNA-5196 expression both in RA (area under curve (AUC) = 0.87, p = 0.055) and AS patients (AUC = 0.90, p = 0.050) compared to CRP levels in RA (AUC = 0.75, p = 0.201) and AS patients (AUC = 0.85, p = 0.086) upon biologic therapy treatment. Finding novel biomarkers, including miRNA-5196 which allow to predict and monitor anti-TNF-α response, would be of clinical value especially during the early phase of RA or AS development

Plasma concentration of 36 (poly)phenols and prospective body weight change in participants from the EPIC cohort.

Introduction: Dietary intake of (poly)phenols has been linked to reduced adiposity and body weight (BW) in several epidemiological studies. However, epidemiological evidence on (poly)phenol biomarkers, particularly plasma concentrations, is scarce. We aimed to investigate the associations between plasma (poly)phenols and prospective BW change in participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: This study included 761 participants with data on BW at baseline and after 5 years of follow-up. Plasma concentrations of 36 (poly)phenols were measured at baseline using liquid chromatography-tandem mass spectrometry. Associations were assessed through general linear mixed models and multinomial logistic regression models, using change in BW as a continuous or as a categorical variable (BW loss, maintenance, gain), respectively. Plasma (poly)phenols were assessed as log2-transformed continuous variables. The false discovery rate (FDR) was used to control for multiple comparisons. Results: Doubling plasma (poly)phenol concentrations showed a borderline trend towards a positive association with BW loss. Plasma vanillic acid showed the strongest association (-0.53 kg/5 years; 95% confidence interval [CI]: -0.99, -0.07). Similar results were observed for plasma naringenin comparing BW loss versus BW maintenance (odds ratio: 1.1; 95% CI: 1.0, 1.2). These results did not remain significant after FDR correction. Conclusion: Higher concentrations of plasma (poly)phenols suggested a tendency towards 5-year BW maintenance or loss. While certain associations seemed promising, they did not withstand FDR correction, indicating the need for caution in interpreting these results. Further studies using (poly)phenol biomarkers are needed to confirm these suggestive protective trends. Keywords: Body weight; Cohort; EPIC; Nutritional biomarker; Plasma (poly)phenol

Aging behavior and modeling studies of unsaturated polyester resin and unsaturated polyester resin-based blends

This chapter deals with various cases of degradation of unsaturated polyester resin (UPR)-based materials (composites with polyester matrices and polyester interpenetrated networks). The consequences of degradation mainly on mechanical and engineering properties are presented from a structure-relationships point of view. Two main kinds of mechanisms are presented, namely physical (chemicals and water penetration) and chemical mechanisms (hydrolysis, radiolysis, photolysis and photooxidation, and thermal oxidation) together with experimental trackers, existing kinetic models, and some of their available parameters. It seems in particular that the lifetime prediction of UPR-based materials submitted to chemical aging remains an open issue due to the nonideality of networks