Université Ibn-Tofail

In this work, we have presented a very detailed review of the different classification of azo dyes as a function of the number of azo groups and the appropriate functional groups. Then we pointed out some chemical properties of these dyes such as reactivity, isomerization and tautomerism and listed. In the following, we have summarized some recent syntheses of azo dyes and the mechanism of azo dye/polymer conjugation. Finally, we indicate the principle of Gewald's reaction and its application to the synthesis of new azo dyes.

For thousands of years, nature has been a source of medical substances, and an astounding numeral of contemporary remedies have been identified from natural origins. Plants have long been used as folk herbal medicines to treat various disorders, and their different natural products have inspired the design, discovery, and development of new drugs. With the invention of recent molecular targets based on proteins, there is a growing need for fresh chemical diversification in screening. Natural products will play a vital part in supplying this need via the continuous exploration of global biodiversity, the majority of which remains unexplored. Even though drug discovery from medicinal plants remains an important source of novel therapeutic leads, various hurdles exist, including identifying and executing suitable high-throughput screening bioassays, scaling up the supply of bioactive molecules, and acquiring plant materials. Investigating these natural resources takes multi-disciplinary, nationwide, and global partnerships in design, synthesis, discovery, and drug development techniques. This review article discusses current advancements and future approaches for discovering natural items such as health- and wellness-promoting remedies. It also summarizes strategies to unify the therapeutic use of plant-derived natural products worldwide to support future drug discoveries derived from plant sources.

In the present review, we have been able to describe the different families of dyes and pigments used in textile finishing processes (Yarns, fabrics, nonwovens, knits and rugs) such as dyeing and printing. These dyes are reactive, direct, dispersed, indigo, sulphur and vats. Such that their presence in the liquid effluents resulting from the textile washing constitutes a serious risk, in the absence of their purification, for the quality of receiving aquatic environments. Indeed, the presence of these dyes and pigments can cause a significant alteration in the ecological conditions of the aquatic fauna and flora, because of the lack of their biodegradability. This has a negative impact on the equilibrium of the aquatic environment by causing serious dangers, namely the obvious dangers (Eutrophication, under-oxygenation, color, turbidity and odor), the long-term dangers (Persistence, bioaccumulation of carcinogenic aromatic products and formation of by-products of chlorination), mutagenicity and carcinogenicity.

Developing Big Data applications has become increasingly important in the last few years. In fact, several organizations from different sectors depend increasingly on knowledge extracted from huge volumes of data. However, in Big Data context, traditional data techniques and platforms are less efficient. They show a slow responsiveness and lack of scalability, performance and accuracy. To face the complex Big Data challenges, much work has been carried out. As a result, various types of distributions and technologies have been developed. This paper is a review that survey recent technologies developed for Big Data. It aims to help to select and adopt the right combination of different Big Data technologies according to their technological needs and specific applications’ requirements. It provides not only a global view of main Big Data technologies but also comparisons according to different system layers such as Data Storage Layer, Data Processing Layer, Data Querying Layer, Data Access Layer and Management Layer. It categorizes and discusses main technologies features, advantages, limits and usages.

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

: This paper describes the reconstruction of electrons and photons with the ATLAS detector, employed for measurements and searches exploiting the complete LHC Run 2 dataset. An improved energy clustering algorithm is introduced, and its implications for the measurement and identification of prompt electrons and photons are discussed in detail. Corrections and calibrations that affect performance, including energy calibration, identification and isolation efficiencies, and the measurement of the charge of reconstructed electron candidates are determined using up to 81 fb -1 of proton-proton collision data collected at s = 13 TeV between 2015 and 2017.

Combined measurements of Higgs boson production cross sections and branching fractions are presented. The combination is based on the analyses of the Higgs boson decay modes $H\ensuremath{\rightarrow}\ensuremath{\gamma}\ensuremath{\gamma}$, $Z{Z}^{*}$, $W{W}^{*}$, $\ensuremath{\tau}\ensuremath{\tau}$, $b\overline{b}$, $\ensuremath{\mu}\ensuremath{\mu}$, searches for decays into invisible final states, and on measurements of off-shell Higgs boson production. Up to $79.8\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of proton--proton collision data collected at $\sqrt{s}=13\text{ }\text{ }\mathrm{TeV}$ with the ATLAS detector are used. Results are presented for the gluon--gluon fusion and vector-boson fusion processes, and for associated production with vector bosons or top-quarks. The global signal strength is determined to be $\ensuremath{\mu}=1.1{1}_{\ensuremath{-}0.08}^{+0.09}$. The combined measurement yields an observed (expected) significance for the vector-boson fusion production process of $6.5\ensuremath{\sigma}$ ($5.3\ensuremath{\sigma}$). Measurements in kinematic regions defined within the simplified template cross section framework are also shown. The results are interpreted in terms of modifiers applied to the Standard Model couplings of the Higgs boson to other particles, and are used to set exclusion limits on parameters in two-Higgs-doublet models and in the simplified minimal supersymmetric Standard Model. No significant deviations from Standard Model predictions are observed.

Abstract The algorithms used by the ATLAS Collaboration during Run 2 of the Large Hadron Collider to identify jets containing b-hadrons are presented. The performance of the algorithms is evaluated in the simulation and the efficiency with which these algorithms identify jets containing b-hadrons is measured in collision data. The measurement uses a likelihood-based method in a sample highly enriched in $$t{\bar{t}}$$ tt¯ events. The topology of the $$t \rightarrow W b$$ t→Wb decays is exploited to simultaneously measure both the jet flavour composition of the sample and the efficiency in a transverse momentum range from 20 to 600 GeV. The efficiency measurement is subsequently compared with that predicted by the simulation. The data used in this measurement, corresponding to a total integrated luminosity of 80.5 $$\hbox {fb}^{-1}$$ fb-1 , were collected in proton–proton collisions during the years 2015–2017 at a centre-of-mass energy $$\sqrt{s}=$$ s= 13 TeV. By simultaneously extracting both the efficiency and jet flavour composition, this measurement significantly improves the precision compared to previous results, with uncertainties ranging from 1 to 8% depending on the jet transverse momentum.

Abstract The standard model of particle physics 1–4 describes the known fundamental particles and forces that make up our Universe, with the exception of gravity. One of the central features of the standard model is a field that permeates all of space and interacts with fundamental particles 5–9 . The quantum excitation of this field, known as the Higgs field, manifests itself as the Higgs boson, the only fundamental particle with no spin. In 2012, a particle with properties consistent with the Higgs boson of the standard model was observed by the ATLAS and CMS experiments at the Large Hadron Collider at CERN 10,11 . Since then, more than 30 times as many Higgs bosons have been recorded by the ATLAS experiment, enabling much more precise measurements and new tests of the theory. Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons—the carriers of the strong, electromagnetic and weak forces—are studied in detail. Interactions with three third-generation matter particles (bottom ( b ) and top ( t ) quarks, and tau leptons ( τ )) are well measured and indications of interactions with a second-generation particle (muons, μ ) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model.

Abstract Electron and photon triggers covering transverse energies from 5 $$\text {GeV }$$ GeV to several $$\text {TeV }$$ TeV are essential for the ATLAS experiment to record signals for a wide variety of physics: from Standard Model processes to searches for new phenomena in both proton–proton and heavy-ion collisions. To cope with a fourfold increase of peak LHC luminosity from 2015 to 2018 (Run 2), to $$2.1 \times 10^{34}\,\hbox {cm}^{-2}\hbox { s}^{-1}$$ 2.1 × 10 34 cm - 2 s - 1 , and a similar increase in the number of interactions per beam-crossing to about 60, trigger algorithms and selections were optimised to control the rates while retaining a high efficiency for physics analyses. For proton–proton collisions, the single-electron trigger efficiency relative to a single-electron offline selection is at least 75% for an offline electron of 31 $$\text {GeV }$$ GeV , and rises to 96% at 60 $$\text {GeV }$$ GeV ; the trigger efficiency of a 25 $$\text {GeV }$$ GeV leg of the primary diphoton trigger relative to a tight offline photon selection is more than 96% for an offline photon of 30 $$\text {GeV }$$ GeV . For heavy-ion collisions, the primary electron and photon trigger efficiencies relative to the corresponding standard offline selections are at least 84% and 95%, respectively, at 5 $$\text {GeV }$$ GeV above the corresponding trigger threshold.

The business environment of this new century has undertaken several changes, creating more and more complexity and uncertainty. In this changing environment, which characterizes the global economy today, firms face severe competitive pressure to do things better, faster, and low-priced. They need to cope with a growing number of challenges arising from their environment, and also increase their ability to adapt. Nowadays, continuous performance is the objective of any firm. This is because it is only through performance that companies are able to experience development and make progress. Consequently, assessing and measuring business performance is of significant importance, since companies are constantly seeking effective and efficient results.

Abstract This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 $$\hbox {fb}^{-1}$$ fb - 1 of pp collision data at $$\sqrt{s}=13$$ s = 13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of $$Z\rightarrow \mu \mu $$ Z → μ μ and $$J/\psi \rightarrow \mu \mu $$ J / ψ → μ μ decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of $$|\eta |<2.7$$ | η | < 2.7 .

Autosomal recessive, complete TYK2 deficiency was previously described in a patient (P1) with intracellular bacterial and viral infections and features of hyper-IgE syndrome (HIES), including atopic dermatitis, high serum IgE levels, and staphylococcal abscesses. We identified seven other TYK2-deficient patients from five families and four different ethnic groups. These patients were homozygous for one of five null mutations, different from that seen in P1. They displayed mycobacterial and/or viral infections, but no HIES. All eight TYK2-deficient patients displayed impaired but not abolished cellular responses to (a) IL-12 and IFN-α/β, accounting for mycobacterial and viral infections, respectively; (b) IL-23, with normal proportions of circulating IL-17(+) T cells, accounting for their apparent lack of mucocutaneous candidiasis; and (c) IL-10, with no overt clinical consequences, including a lack of inflammatory bowel disease. Cellular responses to IL-21, IL-27, IFN-γ, IL-28/29 (IFN-λ), and leukemia inhibitory factor (LIF) were normal. The leukocytes and fibroblasts of all seven newly identified TYK2-deficient patients, unlike those of P1, responded normally to IL-6, possibly accounting for the lack of HIES in these patients. The expression of exogenous wild-type TYK2 or the silencing of endogenous TYK2 did not rescue IL-6 hyporesponsiveness, suggesting that this phenotype was not a consequence of the TYK2 genotype. The core clinical phenotype of TYK2 deficiency is mycobacterial and/or viral infections, caused by impaired responses to IL-12 and IFN-α/β. Moreover, impaired IL-6 responses and HIES do not appear to be intrinsic features of TYK2 deficiency in humans.

The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately 100 kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015–2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at $\sqrt{s}=$13 TeV certified for physics analysis.

The performance of the ATLAS muon trigger system is evaluated with proton-proton ( ) and heavy-ion (HI) collision data collected in Run 2 during 2015-2018 at the Large Hadron Collider. It is primarily evaluated using events containing a pair of muons from the decay of Z bosons to cover the intermediate momentum range between 26 GeV and 100 GeV. Overall, the efficiency of the single-muon triggers is about 68% in the barrel region and 85% in the endcap region. The T range for efficiency determination is extended by using muons from decays of J/ mesons, W bosons, and top quarks. The performance in HI collision data is measured and shows good agreement with the results obtained in collisions. The muon trigger shows uniform and stable performance in good agreement with the prediction of a detailed simulation. Dedicated multi-muon triggers with kinematic selections provide the backbone to beauty, quarkonia, and low-mass physics studies. The design, evolution and performance of these triggers are discussed in detail.

Abstract Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb $$^{-1}$$ - 1 of proton–proton collision data with a centre-of-mass energy of $$\sqrt{s}=13$$ s = 13 $${\text {Te}}{\text {V}}$$ TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti- $$k_t$$ k t jet algorithm with radius parameter $$R=0.4$$ R = 0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets ( $$|\eta |<1.2$$ | η | < 1.2 ) vary from 1% for a wide range of high- $$p_{{\text {T}}}$$ p T jets ( $$250 250 < p T < 2000 GeV ), to 5% at very low $$p_{{\text {T}}}$$ p T ( $$20~{\text {Ge}}{\text {V}}$$ 20 GeV ) and 3.5% at very high $$p_{{\text {T}}}$$ p T ( $$>2.5~{\text {Te}}{\text {V}}$$ > 2.5 TeV ). The relative jet energy resolution is measured and ranges from ( $$24 \pm 1.5$$ 24 ± 1.5 )% at 20 $${\text {Ge}}{\text {V}}$$ GeV to (

Underwater communication remains a challenging technology via communication cables and the cost of underwater sensor network (UWSN) deployment is still very high. As an alternative, underwater wireless communication has been proposed and have received more attention in the last decade. Preliminary research indicated that the Radio Frequency (RF) and Magneto-Inductive (MI) communication achieve higher data rate in the near field communication. The optical communication achieves good performance when limited to the line-of-sight positioning. The acoustic communication allows long transmission range. However, it suffers from transmission losses and time-varying signal distortion due to its dependency on environmental properties. These latter are salinity, temperature, pressure, depth of transceivers, and the environment geometry. This paper is focused on both the acoustic and magneto-inductive communications, which are the most used technologies for underwater networking. Such as acoustic communication is employed for applications requiring long communication range while the MI is used for real-time communication. Moreover, this paper highlights the trade-off between underwater properties, wireless communication technologies, and communication quality. This can help the researcher community by providing clear insight for further research.

Recent spectacular progress in computational technologies has led to an unprecedented boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas and has demonstrated its capability to bring new approaches and solutions to various research problems. However, the extensive computation required to train AI algorithms comes with a cost. Driven by the need to reduce the energy consumption, the carbon footprint and the cost of computers running machine learning algorithms, TinyML is nowadays considered as a promising AI alternative focusing on technologies and applications for extremely low-profile devices. This paper presents the results of a literature survey of all TinyML applications and related research efforts. Our survey builds a taxonomy of TinyML techniques that have been used so far to bring new solutions to various domains, such as healthcare, smart farming, environment, and anomaly detection. Finally, this survey highlights the remaining challenges and points out possible future research directions. We anticipate that this survey will motivate further discussions on the various fields of applications of TinyML and the synergy of resource-constrained devices and edge intelligence.

Abstract A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139 fb $$^{-1}$$ -1 of proton–proton collisions recorded by the ATLAS detector at the Large Hadron Collider at $$\sqrt{s}=13$$ s=13 $$\text {TeV}$$ TeV . ThreeR-parity-conserving scenarios where the lightest neutralino is the lightest supersymmetric particle are considered: the production of chargino pairs with decays via eitherWbosons or sleptons, and the direct production of slepton pairs. The analysis is optimised for the first of these scenarios, but the results are also interpreted in the others. No significant deviations from the Standard Model expectations are observed and limits at 95% confidence level are set on the masses of relevant supersymmetric particles in each of the scenarios. For a massless lightest neutralino, masses up to 420 $$\text {Ge}\text {V}$$ Ge are excluded for the production of the lightest-chargino pairs assumingW-boson-mediated decays and up to 1 $$\text {TeV}$$ TeV for slepton-mediated decays, whereas for slepton-pair production masses up to 700 $$\text {Ge}\text {V}$$ Ge are excluded assuming three generations of mass-degenerate sleptons.

Pentaglycidyl ether pentabisphenol A of phosphorus (PGEPBAP) phosphorus polymer was investigated as corrosion inhibition for carbon steel in aggressive solution using potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), weight loss (WL), scanning electron microscope (SEM), density functional theory (DFT), electrostatic potential (ESP), radial distribution function (RDF), molecular dynamics (MD) and Monte Carlo (MC) simulations. The higher inhibition efficiencies for PDP, EIS and WL studies at 10−3 M concentration of PGEPBA phosphorus polymer are 94.18 %, 91.79 % and 91.3 %, respectively. ΔEcorr (23.7 mV) value of PGEPBAP phosphorus polymer is lower than 85 mV has been assigned to mixed type inhibitor. PGEPBAP formed protective film on carbon steel surface by adsorption according to Langmuir adsorption isotherm. SEM morphology suggested that PGEPBAP could effectively block acid attack by chemisorption on metal surface. To evaluate the polymer inhibitor and potential mechanism were especially realized DFT, ESP, RDF, MD and MC simulations.