Effect of the Alkyl Chain Length Incorporated into Donor Part on the Optoelectronic Properties of the Carbazole Based Dyes: Theoretical Study

In this paper, we report a theoretical study using density functional theory (DFT) and time-dependent (TD-DFT) for R-D-π-A systems with various alkyl chains (R). Results show that the LUMO of the dye lies above the semiconductor conduction band, promoting the injection of electrons; the lower HOMO level promotes dye regeneration. The incorporation of methyl chain (CH3) has a significant reduction in the gap energy, improved red-shift absorption spectrum and increase the molar extinction coefficient at the maximum absorption wavelength compared to D. While, the increase in alkyl chain length from C2H5 to C6H13 present a relatively reduce of gap energies, low effect on the wavelength (438 nm) and converged excitation energies. DOI: http://dx.doi.org/10.17807/orbital.v9i5.100

Visualization of hyperspectral images on parallel and distributed platform: Apache Spark

The field of hyperspectral image storage and processing has undergone a remarkable evolution in recent years. The visualization of these images represents a challenge as the number of bands exceeds three bands, since direct visualization using the trivial system red, green and blue (RGB) or hue, saturation and lightness (HSL) is not feasible. One potential solution to resolve this problem is the reduction of the dimensionality of the image to three dimensions and thereafter assigning each dimension to a color. Conventional tools and algorithms have become incapable of producing results within a reasonable time. In this paper, we present a new distributed method of visualization of hyperspectral image based on the principal component analysis (PCA) and implemented in a distributed parallel environment (Apache Spark). The visualization of the big hyperspectral images with the proposed method is made in a smaller time and with the same performance as the classical method of visualization

Psoriasis and staphylococcus aureus skin colonization in Moroccan patients

Psoriatic lesions are rarely complicated by recurrent infections. The aim of our study is to determine skin colonisation and nasal carriage of Staphylococcus aureus in patients with psoriasis and in healthy  persons. Patients and methods: a comparative study that include 33 patients with psoriasis and 33  healthy persons.Samples were taken from lesional and non lesional psoriatic skin and from healthy skin of control group. For S. aureus nasal carriage, we used sterile cotton tipped swabs. Out of165 samples (66 skin samples and 33 nasal swabs), 26 S. Aureus strains were isolated in 26 persons, 57.69% in the  control group and 42.3% in the psoriasisgroup. S. aureus skin colonization was found in one case (3%) inlesional psoriatic skin vs 9 cases (27.3%) in control skin OR=0.08 IC 95% (0.01-0.70) p=0.02 and in 12,1% in non lesional soriatic skin vs 27, 3% in control skin (p =0,13). This colonization was less important in lesional psoriatic skin (3%) than in non lesional psoriatic skin (12.1%) p= 0.20. Nasal screening identified (7/33) 21, 21% S. aureus carriers in psoriasis group and in control group. Our results are in consensus withliterature findings. They have confirmed the importance of antimicrobial peptides in Innateimmunity of human skin. These peptides are normally produced bykeratinocytes in response to inflammatory stimuli such as psoriasis. Their high  expression in psoriasis skin reduces the risk of skin infection and skin colonization with S. Aureus.Key words: Antimicrobial peptides, innate immunity, nasal carriage, psoriasis, skin colonization, staphylococcus aureu

Flood Hazard Mapping Using Two Digital Elevation Models: Application in a Semi-Arid Environment of Morocco

The High Atlas of Morocco is a semi-arid mountainous environment that frequently suffers from natural hazards. For example, the watersheds upstream of Marrakech city are subject to extreme floods, caused by heavy rains. These episodes are frequent and often devastating, as was the August 1995 event that caused hundreds of deaths in the Ourika Valley. The purpose of this work is to characterize the risk of flooding in this valley, by simulating the water levels and the floodplain extension. This watershed of the Ourika is characterized by a high relief, a rugged topography and a low permeability substratum. To perform this hydraulic simulation, the resolution and accuracy of Digital Elevation Models (DEM) can strongly impact the results in terms of water levels and flow velocities during floods. Two digital elevation models (DEM) were compared: a DEM ASTER with a spatial resolution of 30 m and a DEM derived from stereoscopic images of Pleiades with a resolution of 4 m. Using a hydraulic model (HEC-RAS) and the two DEM resolutions, flood areas corresponding to different return periods are simulated and compared. For the assessment of the two DEM, many areas are selected that are characterized by different types of exposure: highly frequented tourist areas near a regional road and agricultural areas on alluvial terraces, where cultivated fields and infrastructure are vulnerable. The results showed that the high-resolution Pleiades DEM allows for accurate mapping of floodplains in complex terrain, as it realistically representsthe topography and allows correct simulation of observed water levels. This study highlights the added value of a high-resolution remote sensing for flood modeling in areas where data are scarce

Predicting market performance using machine and deep learning techniques

Today, forecasting the stock market has been one of the most challenging issues for the “artificial intelligence” AI research community. Stock market investment methods are sophisticated and rely on analyzing massive volumes of data. In recent years, machine-learning techniques have come under increasing scrutiny to assess and improve market predictions over traditional approaches. The observation in time is due to their dependence. Their predictions are crucial tasks in data mining and have attracted great interest and considerable effort over the past decades. Tackling this challenge remains difficult due to the inherent characteristics of time series data, including its high dimensionality, large volume of data, and constant updates. Exploration of Machine Learning and Deep Learning methods undertaken to enhance the effectiveness of conventional approaches. In this document, we aim precisely to forecast the performance of the stock market at the close of the day by applying various machine-learning algorithms on the two data sets “CoinMarketCap, CryptoCurrency” and thus analyze the predictions of the architectures

Machine learning algorithms for forecasting and categorizing euro-to-dollar exchange rates

Forecasting changes in foreign exchange rates is a well-explored and widely recognized area within finance. Numerous research endeavors have delved into the utilization of methods in machine learning to analyze and predict movements in the foreign exchange market. This work employed several machine-learning techniques such as Adaboost, logistic regression, gradient boosting, random forest classifier, bagging, Gaussian naïve Bayes, extreme gradient boosting classifier, decision tree classifier, and our approach (we have combined three models: logistic regression, random forest classifier, and Gaussian naive Bayes). Our objective is to predict the most advantageous times for purchasing and selling the euro about the dollar. We integrated a range of technical indicators into the training dataset to enhance the precision of our techniques and strategy. The outcomes of our experiment demonstrate that our approach outperforms alternative methods, achieving superior prediction performance. Our methodology yielded an accuracy of 0.948. This study will empower investors to make informed decisions about their future EUR/USD transactions, helping them identify the most advantageous times to buy and sell within the market

Effect of the Alkyl Chain Length Incorporated into Donor Part on the Optoelectronic Properties of the Carbazole Based Dyes: Theoretical Study

In this paper, we report a theoretical study using density functional theory (DFT) and time-dependent (TD-DFT) for R-D-π-A systems with various alkyl chains (R). Results show that the LUMO of the dye lies above the semiconductor conduction band, promoting the injection of electrons; the lower HOMO level promotes dye regeneration. The incorporation of methyl chain (CH3) has a significant reduction in the gap energy, improved red-shift absorption spectrum and increase the molar extinction coefficient at the maximum absorption wavelength compared to D. While, the increase in alkyl chain length from C2H5 to C6H13 present a relatively reduce of gap energies, low effect on the wavelength (438 nm) and converged excitation energies. DOI: http://dx.doi.org/10.17807/orbital.v9i5.100

Characterization of Acute Lymphoblastic Leukemia Subtypes in Moroccan Children

We present the incidence and the immunologic characteristics of acute lymphoblastic leukemia (ALL) subsets in Moroccan children. We studied 279 unselected patients below the age of 18 years with newly diagnosed ALL. Cases were classified according to immunophenotype: 216 (77.42%) precursor B-cell phenotype (pB-cell), mature B-cell in 4 (1.43%), and T-cell in 59 (21.15%) cases. The subclassification using the CD10 antibody revealed 197 cases pB-ALL CD10+ (91.2%) and 9 cases T-ALL CD10+ (19.2%). The age distribution showed a peak in incidence between 3 and 5 years among the pB-cell ALLs subtype. There was a significantly higher frequency of males in the T-ALL subset (M/F ratio: 2.93 : 1) and more females in the T-ALL CD10+ subset when compared with the T-ALL CD10– subset. All tested pB-cell-lineage ALLs expressed CD19, CD79a, and surface CD22, terminal deoxynucleotidyl transferase (TdT) was detectable in 89.9% of cases, and cells in 74.1% of cases express CD34. All tested T-lineage ALL cells have surface CD7 and cytoplasmic CD3 (cCD3) antigens, CD5 was found in 98.2% cases, and 70.5% express TdT. CD1a, surface CD3 (sCD3), and CD4 are detected in more than 80% of cases; this frequency is higher than the 45% generally observed. Myeloid antigens occur more frequently and were expressed in 124 (57.4%) of pB-cell-ALL cases and 20 (33.9%) of T-cell ALL cases. Our results show that the distribution of ALLs in Moroccan children is similar with the general distribution pattern in developed countries except for the high frequency of T-ALL phenotype. The phenotypic profiles of our patients are close to those reported in literature for B-lineage ALLs; for the T-cell ALL subgroup, the blast cells express more CD1a, surface CD3, and CD4 while expressing less TdT. The high frequency of CD1a expression resulted in an excess of the common thymocyte subtype

Pain Perception in Patients Treated with Ligating/Self-Ligating Brackets Versus Patients Treated with Aligners

This study compared the perception of pain experienced by patients undergoing orthodontic treatment with conventional, self-ligating brackets and aligners, and investigated the impact that pain had on their daily lives. 346 consecutive patients were included in the study: 115 patients treated with conventional brackets, 112 Patients treated with self-ligating brackets, and 119 patients treated with aligners. The quantitative aspect of pain was assessed using the Visual Analogue Scale, while the qualitative aspect of pain was evaluated using the Moroccan Short Form of McGILL Pain questionnaire. In all three groups experienced pain after activation tended to decrease in the following week. This pain was greater in patients with conventional braces and less in patients with aligners. Using the M-SF-MPQ to describe the qualitative aspect of the pain revealed that the “cramping مزير,” “aching تيألم” aspect was most accentuated in the 3 groups. Medication intake was correlated with the intensity of pain experienced in all 3 systems. As for the impact of pain on daily activities, patients in groups of conventional and self-ligating braces showed more pain than those in the aligners group. Overall, aligners were less painful than conventional and self-ligating appliances. Patients did not suffer from an alteration in their quality of life due to orthodontic treatment

The ocean sampling day consortium.

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits