Recent publications
The Covid-19 pandemic has significantly spurred the development of deep learning (DL) models for the pathology automatic diagnosis based on CT scan images. However, the assumption about the generalization of the proposed models remains to be assessed and shown for concrete clinical use. In this work, we have investigated the real value of widely used public datasets for the elaboration of DL models that are dedicated to automatic diagnosis of Covid-19 using CT scans. We have collected various international public datasets from 13 countries. Different Convolutional Neural Networks (CNNs) have been trained and their performances carefully assessed. Two evaluations have been conducted: (1) an internal evaluation following a cross-validation procedure, and (2) an external evaluation on real patients coming from new and different sources. The objective is to assess the generalization capabilities considering real-world conditions: different acquisition conditions, devices and configurations. Three families from the most effective CNN models have been selected (ResNet, DenseNet and EfficientNet). These have been fine-tuned, evaluated and used within a training methodology based on transfer learning. The most effective models have been further customized in order to create new models that are dedicated to the task at hand. These models have significantly improved the diagnosis performance.
This study proposes locally available and environment-friendly Algerian palm (Washingtonia filifera) waste fibers to develop biocomposites. Waste palm fibers (WPFs) were chosen as an effective high-intensity polyethylene (HDPE) reinforcement material to create WPF/HDPE biocomposites. WPFs were treated with sodium hydroxide (NaOH) solution to improve their adhesion to the HDPE matrix. Tensile strength and Young’s modulus were evaluated using mixes generated by the response surface methodology (RSM). Based on RSM, the central composite design was used to investigate the effect of various parameters on the tensile properties of cured WPF/HDPE biocomposites. The tensile properties of cured WPF/HDPE biocomposites were influenced by variables such as NaOH (0–3%), fiber treatment duration (0–24 h), and WPF content (0–30% (wt.)). RSM shows that tensile strength increases significantly with a NaOH concentration of 3%, a fiber treatment duration of 10.12 h, and a maximum content of 30% (wt.) in WPFs. The experimental validation reveals that these values correlate with predicted values with an error of less than 3.55%.
Consumers’ willingness to pay a price premium is pivotal for assessing brand value and competitive advantage. Yet, limited and scattered research has focused on how combining brand emotion, strength, and brand loyalty can influence consumers’ willingness to accept a price premium. The present study examines the role of brand attachment, brand strength, and brand loyalty in determining consumers’ willingness to pay a price premium and explores their interplay using a serial mediation model within a unified framework, specifically focusing on home appliance brands. Data from 323 valid questionnaires collected from Algerian households were analyzed using PLS-SEM. Results demonstrate that consumers’ willingness to pay a price premium is significantly and positively influenced by brand strength, brand attachment, and brand loyalty. Furthermore, the relationship between brand strength and consumers’ willingness to pay a price premium is mediated positively by brand attachment and brand loyalty. Grounded on various theories and addressing gaps captured in previous studies, this research is considered pioneering in this field. This study significantly advances our understanding of how brand emotional bonds, brand relationships, and brand strength interplay to influence consumers’ willingness to pay a premium. The findings highlight the importance for brand managers to sustain robust brands to stimulate consumers’ opening to pay extra, thereby achieving and maintaining long-term success in a competitive market.
In this paper, we initiate the study of a variant less restrictive than double Roman dominating functions. Let be a graph and f a function defined from V(G) to A vertex v of G is said to be doubly unprotected with respect to f if where N[v] is a set consisting of vertex v and all vertices adjacent to v. The function f is said to be a weak double Roman dominating function (WDRD-function) if for every vertex v with there is a neighbor u of v with such that the function g defined by and for all has no doubly unprotected vertex. The weight of a WDRD-function f is the sum , and the weak double Roman domination number equals the minimum weight of a WDRD-function on G. Sharp bounds involving the weak double Roman domination number with some (Roman) domination parameters are established. Moreover, we show that the weak double Roman domination number of a nontrivial connected graph G is bounded above by the order of G, and we establish the exact values of this parameter for paths, cycles and ladders. We also show that the associated decision problem is NP-complete, even for bipartite and chordal graphs.
Background
Hypertension is the most prevalent cardiovascular risk factor, with several detrimental effects on the cardiovascular system. Contrasting results have been reported so far on its prognostic role in patients admitted for ST-segment elevation myocardial infarction (STEMI). Therefore, we investigated the impact of hypertension on short-term mortality in a large multicenter contemporary registry of STEMI patients, including patients treated during COVID-19 pandemic.
Methods
The ISACS-STEMI COVID-19 was a retrospective registry that included STEMI patients treated with primary percutaneous coronary intervention (PCI) between March and June of 2019 and 2020 in 109 high-volume primary PCI centers from 4 continents. We collected data on baseline, clinical and procedural characteristics, in-hospital outcome and 30-day mortality. For this analysis patients were grouped according to history of hypertension at admission.
Results
A total of 16083 patients were assessed, including 8813 (54.8%) with history of hypertension. These patients were more often elderly, with a worse cardiovascular risk profile, but were less frequently active smoker. Some procedural differences were observed between the two groups, including lower rate of thrombectomy and use of glycoprotein IIb/IIIa inhibitors or cangrelor but more extensive coronary disease in patients with hypertension. Between patients with and without hypertension, there was no significant difference in SARS-CoV-2 positivity. Hypertensive patients had a significantly higher in-hospital and 30-day mortality, similarly observed in both pre-COVID-19 and COVID-19 era, and confirmed after adjustment for main baseline differences and propensity score (in-hospital mortality: adjusted odds ratio (OR) [95% confidence interval (CI)] =1.673 [1.389–2.014], P < 0.001; 30-day mortality: adjusted hazard ratio (HR) [95% CI] = 1.418 [1.230–1.636], P < 0.001).
Conclusion
This is one of the largest and contemporary study assessing the impact of hypertension in STEMI patients undergoing primary angioplasty, including also the COVID-19 pandemic period. Hypertension was independently associated with significantly higher rates of in-hospital and 30-day mortality.
Research on natural fibers as greener substitutes for synthetic ones has surged in response to the growing need for
sustainable materials. An underutilized natural resource, Chamaerops humilis trunk (ChT), is the subject of this
study's extraction and characterization process. The work examines these fibers' possible uses in biocomposites
by examining their structural, physicochemical, and mechanical characteristics. Numerous characterization
techniques were used to evaluate ChT fibers (ChTFs) thoroughly, including density measurement, diameter
determination, analysis of the fibers' moisture content, X-ray diffraction, scanning electron microscopy, Fourier
transform infrared spectroscopy, thermal analysis, water absorption tests, and tensile testing. Experimental re
sults show that ChTFs possess an average density of 0.97 g/cm
3
, an average diameter of 562 ± 60
regain ranging from 7.94 to 8.63 %, an average linear density of 9.338 Tex, heat resistance to 225
μ
m, a moisture
◦
C andamean
traction resistance of 45.08 ± 9.92 MPa. Such findings underscore the significance of comprehending the ChT's
mechanical characteristics to enhance fiber-reinforced composites and explore their possible uses in the textile
sector besides their promising reinforcements in biocomposites and as a source of biomass for renewable
bioenergy.
The enthalpy calculation is essential in computational thermodynamics and related physical fields. For this matter a new form of enthalpy was investigated numerically. The new equation included the thermal and caloric imperfections represented by the real gas theory, focusing on Berthelot SE in its development. In contrast to previous approaches, it was found that the new form of enthalpy is very easy to use and comprehensive, without using tables and charts and particularly important to correct the HT model and to compute the change in enthalpy when it varies with pressure. This work is complemented with suitable theoretical development, applications in thermodynamics and gas dynamics was made as a studies cases, this type of work may complement experimental works by providing a good view of the process. Especially the enthalpy computation remains difficult in most fields, but with this study we extend the calculation of the changes of enthalpy with the thermodynamic properties whatever the circumstances. The comparison of error between the current model, which is based on real gas theory, and the HT model presents that the pressure- temperature combinations and the thermal –caloric imperfections effects play a significant role, and the error can reach up to 10 %.
Manufacturing composites using natural fibers support the development of more ecologically friendly applications in many industrial areas, including sports equipment, wind turbine blades, construction materials, packaging, medical devices, and prosthetics. To investigate the tests’ number (N) impact on the fibers’ tensile behavior, newly developed fibers from the Strelitzia juncea (SJ) plant are being studied for their mechanical properties using various statistical laws. This study aims to assess the SJ fibers’ performance with a gauge length of 50 mm under quasi-static stress conditions. 150 SJ fibers were tensile tested in five groups (30, 60, 90, 120, and 150) to determine the N impact on the fibers’ tensile strength, break deformation, and Young’s modulus. Weibull and log-normal distributions were used to study statistically the mechanical properties results, and their dispersion was investigated and quantified using least squares and maximum likelihood prediction model with a confidence level of 95%.
This study examines the reduction efficiency of chemical pollution of freshwater by electrocoagulation (EC) process using aluminium (Al) and iron (Fe) electrodes. Several parameters affecting the EC efficiency were investigated in batch manner. Results indicate that both Al and Fe electrodes can eliminate satisfactorily the chemical pollutants of water. The Fe/Fe pair electrode showed an excellent efficiency in reducing turbidity (≈ 99%) within 30 min of time and at 3.0 A intensity. The COD value increased from 62 to 65% with current intensity from 0.3 to 1.0, and from 70 to 98% following the increase in intensity from 2.0 to 3.0A by using the Al electrode. The removal of COD reached 86% with Fe electrode (for 10 min) while it was 99% with Al electrode (after 45 min) using Al electrode (at 2.5 intensity). It was also found that the P value is greater than 0.05 for COD and less than 0.05 for TSS with both electrodes (Al, Fe). The finding also confirmed that the significant difference exists in the case of TSS reduction and it does not exist in the case of COD. Overall, the study underscores the performance of electrocoagulation using both Al and Fe electrodes for removing chemical pollutants in freshwater, highlighting its potential as a sustainable and adaptable solution for their application in water treatment units.
Graphical abstract
Bluetongue (BT) is a vector-borne disease affecting wild and domestic ruminants in many parts of the world. Although bluetongue virus (BTV) is widespread in ungulates in Africa, available epidemiological information on BT in this continent is limited. This systematic review and meta-analysis aimed to estimate the seroprevalence of BTV and summarize information on associated risk factors in domestic ruminants and camels in Africa. Systematic searches were conducted from the inception of the database to November 2022 on PubMed/MEDLINE, ScienceDirect, Web of Science, and Google/Google Scholar. Forty-four eligible publications were identified, published in the range from 1973 to 2020, and statistically analyzed. The pooled overall seroprevalence of BTV was 45.02% (95% confidence interval [CI]: 36.00-54.00%). The pooled seroprevalence was 49.70% (95% CI: 34.50-65.00%) in cattle, 47.00% (95% CI: 29.90-64.50%) in goats, 40.80% (95% CI: 19.60-63.90%) in camels, and 36.30% (95% CI: 29.00-44.90%) in sheep. The pooled seroprevalence decreased after 1990 and increased again after 2010. The highest pooled overall seroprevalence was found in the southeastern region, and the highest pooled overall seroprevalence was obtained by Competitive Enzyme-Linked Immunosorbent Assay. Finally, the seroprevalence in females (53.30%, 95% CI: 34.80-71.00%) was significantly higher than in males (28.10%, 95% CI: 17.40-40.30%) (p < 0.05). We showed that antibodies against BTV were common in African ruminants and camels. Monitoring the seroprevalence of BTV, as well as systematic and continuous surveillance of the Culicoides population, are encouraged to prevent and control the spread of BT.
Modeling and simulating photovoltaic (PV) cells or modules involve using mathematical and computational models to predict their behavior and performance under various conditions. This can include modeling the electrical characteristics of solar cells, as well as the interactions between multiple cells in a PV module. In ISIS-Proteus software, the existing research works have modeled the PV modules either by using a Proteus Spice model of the PV panel without including the effect of climatic conditions variation or by using pure mathematical relations that describe all physical and environmental parameters that lead to a static behavior. Therefore, this paper proposes a new improved ISIS-Proteus model of a PV cell/module for dynamic performance emulation under varying climatic conditions. The proposed model is designed based on the equivalent circuit of a five-parameter single-diode as an electrical part controlled by a numerical part that includes the mathematical expressions corresponding to each parameter. The designed model can capture the impact of solar irradiance and temperature on PV outputs, thereby enhancing real-world PV performance prediction. Also, it can effectively simulate the effect of the partial shading. To validate the accuracy of the proposed model, a comparative study is conducted evaluating the model's performance against PVsyst software models and real-world data brought from a large-scale grid-connected PV station in Ain El-Melh, Algeria. In this study, the simulation tests are carried out using ISIS-Proteus considering several PV module types and under various operating conditions, including uniform test conditions (UTCs) and partial shading conditions (PSCs). The findings, including I–V and P–V curves and several standard metrics, prove the proposed model's effectiveness in accurately predicting the behavior of PV modules under both UTCs and PSCs, aligning closely with real-world performance.
In this work, we have developed Cu-Fe alloys with a nanometric structure through the process of mechanosynthesis. We then followed the formation mechanism of these alloys and proceeded with a crucial step, which is cold compaction. We have elaborated Cu-Fe alloys with a nanometric structure by mechanosynthesis and following the mechanism of formation of these alloys, the we employed various analytical techniques to characterize the structural and microstructural properties of our powders. The X-ray diffraction method (XRD) was used to calculate the structural parameters, while laser granulometry was employed to study the evolution of particle size. Scanning electron microscopy (SEM) was then utilized to examine the morphology of the powders. Additionally, we investigated the electrochemical behavior of our alloys, focusing on their corrosion resistance. Electrochemical impedance spectroscopy (EIS) was performed in the frequency range of 10 kHz to 15 mHz to evaluate the corrosion performance.
This work aims to synthesize and characterize a biocomposite made of nontronite clay (Non) and grafted green algae, Enteromorpha sp. (Ep) to efficiently eliminate the dye methylene blue (MB). The produced material underwent characterization using various techniques, including Fourier transform infrared spectroscopy, X-ray diffraction, energy dispersive X-ray, scanning electron microscopy, pH-potentiometric titrations, and point of zero charge (pHPZC) determination. The synthesis conditions and adsorption essential parameters, Non loading between 0 and 50% (A), Ep/Non dose between 0.02 and 0.06 g (B), solution pH between 4 and 10 (C), temperature between 30 and 60 °C (D), and contact time between 5 and 60 min (E), were optimized using a statistical approach called the Box-Behnken design. The best results, obtained from the percentage of MB (91.34%), can be achieved by loading 50% of the algae in the clay, Ep/Non dose 0.05 g, pH 7, temperature 45 °C, and contact time 32.5 min. The pseudo-second-order model accurately represented the adsorption kinetics, while the Freundlich isotherm model effectively characterized the adsorption equilibrium. At a temperature of 45 °C, the maximum adsorption capacity of MB that Ep/Non can adsorb is 113.5 mg.g⁻¹. The synergistic effects of several interactions like electrostatic forces, π-π stacking, n-π stacking, H-bonding, and Yoshida H-bonding were found to be responsible for the selective and efficient adsorption of MB on Ep/Non-50, as suggested by structural analysis and FTIR comparisons of samples before and after adsorption. According to our findings, the composite material that has been developed possesses the high capacity for the absorption and eradication of color.
Graphical Abstract
Our research evaluates advanced artificial (AI) methodologies to enhance diagnostic accuracy in pulmonary radiography. Utilizing DenseNet121 and ResNet50, we analyzed 108,948 chest X-ray images from 32,717 patients and DenseNet121 achieved an area under the curve (AUC) of 94% in identifying the conditions of pneumothorax and oedema. The model’s performance surpassed that of expert radiologists, though further improvements are necessary for diagnosing complex conditions such as emphysema, effusion, and hernia. Clinical validation integrating Latent Dirichlet Allocation (LDA) and Named Entity Recognition (NER) demonstrated the potential of natural language processing (NLP) in clinical workflows. The NER system achieved a precision of 92% and a recall of 88%. Sentiment analysis using DistilBERT provided a nuanced understanding of clinical notes, which is essential for refining diagnostic decisions. XGBoost and SHapley Additive exPlanations (SHAP) enhanced feature extraction and model interpretability. Local Interpretable Model-agnostic Explanations (LIME) and occlusion sensitivity analysis further enriched transparency, enabling healthcare providers to trust AI predictions. These AI techniques reduced processing times by 60% and annotation errors by 75%, setting a new benchmark for efficiency in thoracic diagnostics. The research explored the transformative potential of AI in medical imaging, advancing traditional diagnostics and accelerating medical evaluations in clinical settings.
Repeated and multiple traffic loads, along with climatic conditions, influence the mechanical behavior of linear
pavements, leading to the formation of cracks that propagate significantly across the wearing surface and result
in a loss of load-bearing capacity of the pavement body. To remedy this problem, various reinforcement and
repair methods (traditional and modern) are applied to address this issue. The use of geogrids, involving the
insertion of sheets at the interfaces of the sub-base layers, has proven effective as an alternative solution due to
their mechanical and aesthetic performance. However, these geogrids, primarily serving as a separation layer,
are sometimes limited in the gains they make in reducing stresses and strains, since these gains do not exceed
5 to 10%. Consequently, researchers have sought other techniques that provide both separation (to prevent crack
propagation) and strengthening (to increase the bearing capacity of the pavement). In this article, we propose
to study the reinforcement of rigid cement concrete pavements through an experimental approach, using
two laboratory batches, each comprising a number of twenty-two (22) small-scale slabs, with dimensions of
400 × 400 × 50 (mm). The first batch was produced at an ambient temperature of 20°C while the second batch
was produced at an elevated temperature of 50°C (arid climate). These slabs will be tested in 4-point bending,
after reinforcement with different combinations of geogrids and carbon fibers composites. To compare the
experimental results obtained, a numerical simulation based on the finite element method, using appropriate
software, was conducted. The results regarding stresses and strains, as well as dissipation energy, showed that
the combination adopted is very effective, yielding gains of up to 20 to 35%, additionally the integration of
geogrids, with the addition of the composite, enhances the reinforced pavement’s longevity, ensuring longterm
savings on its upkeep and maintenance.
Keywords: Concrete Pavement; Geogrid; Composite; Experimental Test; Numerical Analysis.
New cellulose (CL) fibers are derived from Chamaerops humilis (Ch) rachis. They play an essential role in various industries to produce environmentally friendly products as an alternative to enhancing and strengthening lightweight composites, such as dashboards automotive. Distinctive properties of Ch fibers (ChFs) were determined by extracting fibers from dwarf palm plant branches using anaerobic analysis. This search comprehensively studies morphological, physical, mechanical, and thermal characteristics and water absorption testing. The fiber diameter was 241.23 ± 34.77 µm, while the obtained linear density and density were 13.71 ± 0.57 Tex and 0.801 ± 0.05 g/cm3, respectively. The moisture content was 8.5%, and the moisture regain was 9.29%. Scanning electron microscopy images showed the fibers and smooth and rough surfaces. The thermogravimetric analysis demonstrated the maximum degradation of 352°C, thermal stability of 243°C, and the kinetic activation energy reached (79.78 kJ/mol). X-ray diffraction proves the availability of CL, with a crystallinity index = 68.38% and crystal size = 2.92 nm. Fourier transform infrared succeeded in detecting functional groups and chemical compounds of fibers. The fibers exhibited a tensile stress of 110.85 ± 77.08 MPa, an elongation at a break rate of 2.29 ± 1.27%, and Young's modulus of 6.05 ± 3.9 GPa. The maximum likelihood method (2P-Weibull distribution) was employed to examine the distribution of mechanical properties of fibers. According to the results above, new ChFs are an excellent reinforcement for elaborating fiber-reinforced biocomposites.
This study aims to enhance the mechanical properties of date palm fibers (DPFs) by implementing a targeted treatment technique. The response surface methodology (RSM) is utilized for modeling and optimizing. The study seeks to identify the optimal Alkaline treatment settings for improving the mechanical properties of DPFs by carefully analyzing parameters such as average diameter, time, and NaOH concentration. The analytical results offer valuable insights into the possible use of DPFs in many engineering applications, contributing to the industrial advancement of sustainable and eco-friendly materials. The experimental findings are analyzed using a full-factorial design (4³), incorporating analysis of variance and RSM. Combining RSM and desirability function is used to get the best mechanical properties, including stress, strain, and Young’s modulus. The model appropriateness is evaluated by analyzing residual values. The findings suggest that the sodium hydroxide concentration (%NaOH) has the most significant impact on strain (11.63%), stress (12%), and Young’s modulus (11.72%) besides the time t (h) also significantly influences 6.01%, 6.26%, and 5.79% strain, stress, and Young’s modulus, respectively.
Background
Celiac disease (CD) is an autoimmune disorder in which genetically susceptible individuals cannot digest gluten (wheat) and its homologs such as Scalin (rye) and Hordein (barley).
Aim
This systematic review and meta‐analysis aimed to investigate the measures of associations between CD and psychiatric disorders, specifically anxiety and depression, and explore the relationship between adherence to a Gluten‐Free Diet (GFD) and the psychiatric aspects of the disease.
Methods
We searched PubMed, Scopus and Web of Science for articles investigating anxiety and depression in CD patients. The following inclusion criteria were implemented: Primary research articles (either observational or experimental) that include participants with a CD diagnosis ‐confirmed either serologically, with anti‐endomysial antibodies, anti‐tissue transglutaminase antibodies, or with duodenum biopsy, whether on a GFD or not,—who have depression or anxiety symptoms identified through self‐report or clinician‐administered scales.
Results
CD patients are at a higher odds of developing anxiety, as the odds ratio was (OR: 2.26, 95% CI: [1.10, 4.67]) and depression symptoms (OR: 3.36, 95% CI: [1.36, 8.32]). Results of both State‐Trait Anxiety Inventory Y‐1 and Y‐2 improved after 1 year of GFD with mean difference of 3.48, 95% CI: (0.26, 6.71), and MD: 3.45, 95% CI: (1.39, 5.52), respectively.
Conclusion
Anxiety and depression are prevalent among adults and children CD patients as they are observed to have high odds of anxiety and depression as expressed by various scales. It is reported that GFD is associated with decreased levels of anxiety and depression, however, further studies are required to confirm these findings and to investigate the main mechanism of psychiatric disorders among CD patients.
Purpose
In this study, we retrospectively reviewed the use of flow cytometry (FCM) in the diagnosis of inborn errors of immunity (IEIs) at a single center in Algeria. Sharing insights into our practical experience, we present FCM based diagnostic approaches adapted to different clinical scenarios.
Methods
Between May 2017 and February 2024, pediatric and adult patients presenting with clinical features suggestive of immunodeficiency were subjected to FCM evaluation, including lymphocyte subset analysis, detection of specific surface or intracellular proteins, and functional analysis of immune cells.
Results
Over a nearly seven-year period, our laboratory diagnosed a total of 670 patients (372 (55.5%) males and 298 (44.5%) females), distributed into 70 different IEIs belonging to 9 different categories of the International Union of Immunological Societies classification. FCM was used to diagnose and categorize IEI in 514 patients (76.7%). It provided direct diagnostic insights for IEIs such as severe combined immunodeficiency, Omenn syndrome, MHC class II deficiency, familial hemophagocytic lymphohistiocytosis, and CD55 deficiency. For certain IEIs, including hyper-IgE syndrome, STAT1-gain of function, autoimmune lymphoproliferative syndrome, and activated PI3K delta syndrome, FCM offered suggestive evidence, necessitating subsequent genetic testing for confirmation. Protein expression and functional assays played a crucial role in establishing definitive diagnoses for various disorders. To setup such diagnostic assays at high and reproducible quality, high level of expertise is required; in house reference values need to be determined and the parallel testing of healthy controls is highly recommended.
Conclusion
Flow cytometry has emerged as a highly valuable and cost-effective tool for diagnosing and studying most IEIs, particularly in low-income countries where access to genetic testing can be limited. FCM analysis could provide direct diagnostic insights for most common IEIs, offer clues to the underlying genetic defects, and/or aid in narrowing the list of putative genes to be analyzed.
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