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Nowadays, prickly pears are increasingly being processed into juices, and a variety of processed products are offered to consumers. As a consequence, a significant amount of by-product is generated, possessing a large potential for utilization as a source of dietary, and functional fibers. This work aimed to study and compare the effect of the incorporation of red prickly pear by-products (RPPBP) and green prickly pear by-products (GPPBP) from fruit processing as potential ingredients in cakes to promote them as high-value products. The proximate, morphological, and physical characteristics of powders of prickly pear by-products (PPBP) were investigated. The results indicated that the lipid content was approximately 5% for the two prickly pears by-products, and the protein content was between 12.7% and 15.31%. RPPBP and GPPBP are rich in total dietary fiber and exhibited a good water retention capacity (WRC) and oil retention capacity. RPPBP demonstrated better functional properties compared to GPPBP in terms of WRC and swelling capacity, with values of 6.37 g/g and 4.0 ml/g, respectively. In comparison, GPPBP showed a higher least gelation concentration that could enhance texture within products. We investigated the aptitude of RPPBP and GPPBP [1%, 2%, 5%, 10%, and 15% (g/100 g)] to be mixed with wheat flour for cakes preparation through the analysis of the physical characteristics, color, and texture properties of cakes and through sensory evaluation. Compared to the respective control, incorporation of PPBP in wheat cakes increased the cakes’ hardness whereas L* and a* color values decreased. Incorporating GPPBP resulted in better acceptability of wheat flour cakes compared to those containing RPPBP. PPBP up to 10% level can successfully be used to obtain delicious and healthy nutritious fiber-enriched cakes. Valorization of prickly pears processing by-product could be a promising step towards a zero-waste in the juice processing industry.

Previously, we developed a series of processes that involved chemical and enzymatic treatments to extract and separate the fibers from alfa leaves, while also preserving their native mechanical properties, by optimizing the implementation parameters. In this study, we describe the morphology of the alfa leaf, characterize the alfa fibers, and study the influence of different treatments on their crystalline structure, their colorimetric, and thermal properties. This work mentions the application of Weibull statistics to analyze the mechanical properties of alfa fibers, which helps in understanding the probability of failure under different stress conditions. Additionally, we also examined the difference in mechanical properties between a fiber bundle and a single fiber. The results show that the cellulose has not been attacked after different treatments, and the thermal stability of the fibers has improved. X-ray analysis shows that the crystallinity index of the fibers increased by about 16.4% for the alkaline and pectinase treatments. Also, we noticed that the enzymatic treatments led to reduction in the dispersion of mechanical properties. Moreover, we observed that the bundle with a smaller diameter is stronger than the one with a larger diameter. Under tensile loading, it behaves similarly to a unitary fiber, demonstrating a single break.Keywords: Enzymatic treatments, Alkaline treatment, Thermal stability, Weibull approach, Mechanical properties, Single fiber.

Pelargonium graveolensis acknowledged as a medicinal herb possessing noteworthy therapeutic properties. The plant was cultivated in two distinct regions in Chebba, Tunisia, distinguished by a lower semi-arid bioclimate. The initial site was designated as an agricultural region, while the second site, situated in a coastal area, was identified as a saline region. Investigating the plant species response to environmental conditions and soil characteristics uncovering morpho-physiological aspects of the species and its essential oil profiling was unveiled. Significant variations in the essential oil composition were noted upon analysis using GC-FID. Geranyl acetate (22.59%), cis-ocimene (13.99%), trans-rose oxide (11.58%) and linalyle acetate (5.28%) were considered among the main components of Pelargoniumcultivated in the first location. While, the plant species thriving in the coastal region was primarily composed of geranyl acetate (16.66%), trans-rose oxide (14.05%), cis-ocimene (7.25%) and menthol (5.36%). The geranium subjected to salt stress exhibited the highest concentrations of phenolic compounds (221.62 mg GAE/g DW), flavonoids (75.78 mg QE/g DW), flavonols (25.84 mg QE/g DW) and condensed tannins (20.5 mg CTE/g DW). In addition, its essential oil displayed remarkable antioxidant activity for DPPH radical-scavenging assay with an IC50value of 73.65 μg/mL. Hence, this plant holds promise as a natural reservoir of bioactive compounds for food and pharmaceutical sectors. The impact of salinity stress on the antioxidant activities of plant extracts is substantial, suggesting that it could serve as a suitable strategy to augment the antioxidant capacity.

PurposeTo characterise the relationship between a deep-layer microvasculature dropout (MvD) and central visual field (VF) damage in primary open-angle glaucoma (POAG) patients with and without high axial myopia.DesignCross-sectional study.MethodsSeventy-one eyes (49 patients) with high axial myopia and POAG and 125 non-highly myopic POAG eyes (97 patients) were enrolled. Presence, area and angular circumference of juxtapapillary MvD were evaluated on optical coherence tomography angiography B-scans and en-face choroidal images.ResultsJuxtapapillary MvD was detected more often in the highly myopic POAG eyes (43 eyes, 86%) than in the non-highly myopic eyes (73 eyes, 61.9%; p=0.002). In eyes with MvD, MvD area and angular circumference (95% CI) were significantly larger in the highly myopic eyes compared with the non-highly myopic eyes (area: (0.69 (0.40, 0.98) mm2vs 0.31 (0.19, 0.42) mm2, p=0.011) and (angular circumference: 84.3 (62.9, 105.8) vs 74.5 (58.3, 90.9) degrees, p<0.001), respectively. 24-2 VF mean deviation (MD) was significantly worse in eyes with MvD compared with eyes without MvD in both groups (p<0.001). After adjusting for 24-2 MD VF, central VF defects were more frequently found in eyes with MvD compared with eyes without MvD (82.7% vs 60.9%, p<0.001). In multivariable analysis, higher intraocular pressure, worse 24-2 VF MD, longer axial length and greater MvD area and angular circumference were associated with worse 10-2 VF MD.ConclusionsMvD was more prevalent and larger in POAG eyes with high myopia than in non-highly myopic POAG eyes. In both groups, eyes with MvD showed worse glaucoma severity and more central VF defects.

For artificial intelligence (AI)-driven companies, awareness of the urgency of the responsible application of AI became essential with increased interest from different stakeholders. Responsible AI (RAI) has emerged as a practice to guide the design, development, deployment, and use of AI systems to ensure a benefit to users and those impacted by the systems’ outcomes. This benefit is achieved through trustworthy models and strategies that assimilate ethical principles to ensure compliance with regulations and standards for long-term trust. However, RAI comes with the challenge of lack of standardization when it comes to which principles to adopt, what they mean, and how they can be operationalized. This article aims to bridge the gap between principles and practice through a study of different approaches taken in the literature and the proposition of a foundational framework.

Background: Sepsis could affect the outcomes of patients with postcardiotomy cardiogenic shock supported with extracorporeal membrane oxygenation (ECMO). Our objectives were to characterize sepsis patients with ECMO support for postcardiotomy cardiogenic shock and assess its predictors and effect on patients’ outcomes.Methods: This retrospective study included 103 patients with ECMO for postcardiotomy cardiogenic shock from 2009 to 2020. Patients were divided according to the occurrence and timing of sepsis into three groups. Group 1 included patients with no sepsis (n= 67), Group 2 included patients with ECMO-related sepsis (n= 10), and Group 3 included patients with non-ECMO-related sepsis (n= 26).Results: Lactate level before ECMO was highest in the ECMO-associated sepsis group (Group 1 and 2 p= 0.003 and Group 2 and 3 p= 0.003). Dialysis and gastrointestinal bleeding were highest in ECMO-associated sepsis (p= 0.03 and 0.04, respectively). Blood transfusion was higher in ECMO-associated sepsis than in patients with no sepsis (p= 0.01). Mortality was nonsignificantly higher in patients with ECMO-associated sepsis. High BMI (OR: 1.11; p= 0.004), preoperative dialysis (OR: 7.35; p= 0.02), preoperative IABP (OR: 9.9.61; p= 0.01) and CABG (OR: 6.29; p= 0.01) were significantly associated with sepsis. Older age (OR: 1.08; p = 0.004), lower BSA (OR: 0.004; p= 0.003), peripheral cannulation (OR: 29.82; p= 0.03), and high pre ECMO lactate level (OR: 1.24; p= 0.001) were associated with increased mortality. Sepsis did not predict mortality (OR: 1.83; p= 0.21).Conclusions: Sepsis is a dreaded complication in patients with postcardiotomy cardiogenic shock, especially ECMO-associated sepsis. Preoperative risk factors could predict postoperative sepsis in ECMO patients.

Objectives: Corrosive substance ingestion in children represents a significant public health issue due to its long-term health sequelae. Esophageal stricture, main complication of this dangerous condition, is treated by pneumatic dilation and eventually by esophageal replacement. We aimed, through this study, to report the outcomes of esophageal pneumatic dilation complicating corrosive substance ingestion in children in a developing country. Methods: This cross-sectional study was performed on the population of pediatric patients with caustic esophageal stenosis between January 2005 and December 2020. All patients underwent pneumatic balloon dilation. A logistic regression model was built to predict the probability of the occurrence of the event (success/failure) of the dilation. The ROC curve is used to evaluate the performance of the logistic regression model to discriminate between positive and negative values of the dependent variable. Results: The success rate of pneumatic balloon dilation was 80.4%. The median duration of overall management was 11 months. The severity of caustic stricture observed during endoscopy was significantly linked to worse outcomes (p= 0.001). Multivariate analysis indicated that the severity of stenosis and the number of dilation sessions were independent risk factors for failure of dilation. ROC curve analysis showed that the area under the curve was 71.7%. A Cut-Off point value of 7 provided the best sensitivity and specificity. Conclusion: Pneumatic balloon dilation has been proven to be efficacious in infants with caustic esophageal stricture. Pediatric surgeons should take into account factors to promptly switch to replacement surgery and avoid unnecessary and time-consuming serial dilations.

There is a great interest in the use of by-products from food processing such us pea pods (PP) and broad bean pods (BBP) that still contain many valuable substances such as dietary fiber, minerals, vitamins, and polyphenols which are generally underestimated and used in animal feed. The present study describes the extraction process of polyphenols from PP and BBP using different solvents (hexane, methanol, ethanol and water). Water extract (WE) containing the highest extraction yield (42.25% for PP and 34.75% for BBP) showed the highest levels of total phenolic content for the PP flour (100.48 ± 8.80 mg of GAE/g extract) and BBP flour (330.75 ± 17.32 mg of GAE/g extract), respectively. Methanol extract and WE have the most important antioxidant activities. The inhibitory activity of the extracts from PP and BBP against Gram negative bacteria was significantly higher than against Gram positive ones. The highest Minimum Inhibitory concentration value was detected with K. pneumoniaeATCC 13883 (21.42 mg/mL) for the ME and EE (ethanol extract) from BBP. The identification of the phenolic compounds was studied using UPLC–HRMS and revealed a difference in the quality and quantity of polyphenols in the WE from PP or BBP. Therefore, these legumes by-products polyphenols could be a potential source of natural antioxidants and functional compounds for various industrial uses.

This article describes how the named data networking (NDN) has recently received a lot of attention as a potential information-centric networking (ICN) architecture for the future Internet. The NDN paradigm has a great potential to efficiently address and solve the current seminal IP-based IoT architecture issues and requirements. NDN can be used with different sets of caching algorithms and caching replacement policies. The authors investigate the most suitable combination of these two features to be implemented in an IoT environment. For this purpose, the authors first reviewed the current research and development progress in ICN, then they conduct a qualitative comparative study of the relevant ICN proposals and discuss the suitability of the NDN as a promising architecture for IoT. Finally, they evaluate the performance of NDN in an IoT environment with different caching algorithms and replacement policies. The obtained results show that the consumer-cache caching algorithm used with the Random Replacement (RR) policy significantly improve NDN content validity in an IoT environment.

Over the last decade, emotion recognition has become a widely researched area worth considering in any project related to affective computing. Due to the limitless applications of this new discipline, the development of emotion recognition systems has emerged as a lucrative opportunity in the corporate sector. Emotion recognition can be detected in many ways, such as face, speech, text, gestures, etc. Hence, this article presents a comprehensive survey of emotion recognition methods, focusing on three key modalities: visual, speech, and audio-visual. Moreover, a novel approach for each modality is proposed, and a comparative analysis is conducted with existing methods to assess their effectiveness. The results of this study revealed that face emotion recognition on the RAVDESS dataset can achieve good results compared to speech emotion recognition, which was the opposite case in previous literature. Combined modalities were found to likely achieve even better results with an accuracy of 89% compared to previous works. Finally, this article concludes by offering new insights and suggestions for future research.

IMPORTANCE: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the cost and improve the efficiency of reading center assessment of end points in clinical trials. OBJECTIVE: To investigate the diagnostic accuracy of DL algorithms trained on fundus photographs from the Ocular Hypertension Treatment Study (OHTS) to detect primary open-angle glaucoma (POAG). DESIGN, SETTING, AND PARTICIPANTS: In this diagnostic study, 1636 OHTS participants from 22 sites with a mean (range) follow-up of 10.7 (0-14.3) years. A total of 66 715 photographs from 3272 eyes were used to train and test a ResNet-50 model to detect the OHTS Endpoint Committee POAG determination based on optic disc (287 eyes, 3502 photographs) and/or visual field (198 eyes, 2300 visual fields) changes. Three independent test sets were used to evaluate the generalizability of the model. MAIN OUTCOMES AND MEASURES: Areas under the receiver operating characteristic curve (AUROC) and sensitivities at fixed specificities were calculated to compare model performance. Evaluation of false-positive rates was used to determine whether the DL model detected POAG before the OHTS Endpoint Committee POAG determination. RESULTS: A total of 1147 participants were included in the training set (661 [57.6%] female; mean age, 57.2 years; 95% CI, 56.6-57.8), 167 in the validation set (97 [58.1%] female; mean age, 57.1 years; 95% CI, 55.6-58.7), and 322 in the test set (173 [53.7%] female; mean age, 57.2 years; 95% CI, 56.1-58.2). The DL model achieved an AUROC of 0.88 (95% CI, 0.82-0.92) for the OHTS Endpoint Committee determination of optic disc or VF changes. For the OHTS end points based on optic disc changes or visual field changes, AUROCs were 0.91 (95% CI, 0.88-0.94) and 0.86 (95% CI, 0.76-0.93), respectively. False-positive rates (at 90% specificity) were higher in photographs of eyes that later developed POAG by disc or visual field (27.5% [56 of 204]) compared with eyes that did not develop POAG (11.4% [50 of 440]) during follow-up. The diagnostic accuracy of the DL model developed on the optic disc end point applied to 3 independent data sets was lower, with AUROCs ranging from 0.74 (95% CI, 0.70-0.77) to 0.79 (95% CI, 0.78-0.81). CONCLUSIONS AND RELEVANCE: The model’s high diagnostic accuracy using OHTS photographs suggests that DL has the potential to standardize and automate POAG determination for clinical trials and management. In addition, the higher false-positive rate in early photographs of eyes that later developed POAG suggests that DL models detected POAG in some eyes earlier than the OHTS Endpoint Committee, reflecting the OHTS design that emphasized a high specificity for POAG determination by requiring a clinically significant change from baseline.

Yeasts have received significant attention in recent years as major sources of value-added metabolites endowed with various natural biological activities. Among the yeasts studied until now, the so-called red yeasts have a great potential in microbial lipids and carotenoids production serving as precursor for biofuels, oleo-chemicals, and food additives. In this work, biodiesel-derived crude glycerol was used as feedstock for concomitant valuable metabolites production by the oleaginous yeast Rhodotorula babjevaeY-SL7. Under specific conditions, this strain has been shown to accumulate a high intracellular content of microbial oil (> 40%) and to secrete a mixture of polyol esters of fatty acids (PEFA). Using fed-batch fermentation, the appropriate culture conditions were established for maximum lipids and carotenoids production. The characterization of extracted carotenoids reveals the presence of two major compounds, the torularhodin (63.7%) and torulene (36.3%) and their related antimicrobial and antioxidant activities were investigated. Moreover, secreted PEFAs showed therapeutically promising cytotoxic effect against cancer cells and their synergistic action with commercial drug was also established. On the other hand, flow cytometry analysis showed that culture on crude glycerol increases cells membrane permeability and further enhances metabolites recovery. This can facilitate downstream processing and therefore increase the profitability of the production system. Indeed, the present study opens new perspectives for multifunctional metabolites production using cheap industrial by-product through completely eco-friendly processes

The Internet of Things (IoT) is an innovative and revolutionary technology. It promises to serve humanity and improve our lives by integrating a huge number of heterogeneous end devices and providing diverse interesting services. However, security remains the main key for the success of any technology. In this paper, we aim to provide structural guidelines to secure IoT-based smart cities. We should consider the IoT-based functional requirements in parallel with the security requirements based on the security triad: Confidentiality, Integrity and Availability. Moreover, we should consider the security challenges of smart cities based on the cube: Big data, Resource limitation, Interoperability, and Scalability. We then present solutions to the main threats. Finally, we assess vulnerabilities of some services offered in an IoT-based smart cities context. We show that current available services still suffer from several vulnerabilities and need associated security countermeasures for the success of the IoT-based smart cities.

IMPORTANCE: Clinical trials of glaucoma therapies focused on protecting the optic nerve have required large sample sizes and lengthy follow-up to detect clinically relevant change due to its slow rate of progression. Whether shorter trials may be possible with more frequent testing and use of rate of change as the end point warrants further investigation. OBJECTIVE: To describe the design for the Short-term Assessment of Glaucoma Progression (STAGE) model and provide guidance on sample size and power calculations for shorter clinical trials. DESIGN, SETTING, AND PARTICIPANTS: A cohort study of patients with mild, moderate, or advanced open-angle glaucoma recruited from the Diagnostic Innovations in Glaucoma Study at the University of California, San Diego. Enrollment began in May 2012 with follow-up for every 3 months for 2 years after baseline examination. Follow-up was concluded in September 2016. Data were analyzed from July 2019 to January 2021. Visual fields (VF) and optic coherence tomography (OCT) scans were obtained at baseline and for 2 years with visits every 3 months. EXPOSURES: Glaucoma was defined as glaucomatous appearing optic discs classified by disc photographs in at least 1 eye and/or repeatable VF damage at baseline. MAIN OUTCOMES AND MEASURES: Longitudinal rates of change in retinal nerve fiber layer (RNFL) thickness and VF mean deviation (MD) are estimated in study designs of varying length and observation frequency. Power calculations as functions of study length, observation frequency, and sample size were performed. RESULTS: In a total referred sample of 97 patients with mild, moderate, or advanced glaucoma (mean [SD] age, 69 [11.4] years; 50 [51.5%] were female; 19 [19.6%]), over the 2-year follow-up, the mean VF 24-2 MD slope was −0.32 dB/y (95% CI, −0.43 to −0.21 dB/y) and the mean RNFL thickness slope was −0.54 μm/y (95% CI, −0.75 to −0.32 μm/y). Sufficient power (80%) to detect similar group differences in the rate of change in both outcomes was attained with total follow-up between 18 months and 2 years and fewer than 300 total participants. CONCLUSIONS AND RELEVANCE: In this cohort study, results from the STAGE model with reduction of the rate of progression as the end point, frequent testing, and a moderate effect size, suggest that clinical trials to test efficacy of glaucoma therapy can be completed within 18 months of follow-up and with fewer than 300 participants.

This paper deals with a new control approach of an exoskeleton-upper limb system. The considered system is a two-DoF robot in interaction with an upper limb used for rehabilitation. The objective is to control the flexion/extension movement of the shoulder and the elbow joints in presence of disturbances. First, the modelling and the control of the system using different laws were made, and a stability study is realised. Then, a comparison study between these different algorithms was done. To prove the performance of the tested controllers, a robustness analysis was needed. For that, a state of the art of different robustness analysis methods was presented. The application and the comparison between these methods were realised to obtain the most robust one. Finally, the control of the exoskeleton-upper limb system by the model free terminal sliding mode is developed. A Monte Carlo study is done. The performance and the robustness of the model free terminal sliding mode algorithm in presence of disturbances and uncertainties are provided by simulation results.

Epilepsy is a chronic brain disease, it causes seizures that damage patients’ lives. The main examination of epilepsy diagnosis is encephalography since its acquisition simplicity, low cost and significant results. However, the exploitation of electroencephalogram (EEG) signals require a neurological consultation, which is very time-consuming and it is not possible at all times. Recently, several published research propose different machine learning systems for EEG signals classification to detect patients’ brain states, healthy, epileptic during seizures free intervals and epileptic during seizures. Developed systems deal with real-time applications requirement, in addition to program accuracy, run time must be as short as possible and uses the lowest storage memory. So, proposed systems must be based on a simple model using few features that are fast calculated and classified by a simple method. In this paper, we propose a novel approach for EEG features extraction based on a new method for the determination of the Correlation Dimension (CD). The experimental test through a benchmark database shows the efficiency of our method in comparison to other published works. In terms of reliability, we achieve an accuracy of 100 % for almost all classification problems with specific combinations of subsets. In terms of program simplicity, we use few features and fast running model.

The compass-type bipedal robot is an impulsive hybrid mechanical system that can produce complex behaviors, chaos and bifurcations. In this work, we analyze the passive dynamic walking of the compass robot to further explore its complexity and these nonlinear phenomena while descending inclined surfaces. The bifurcation diagrams are mainly adopted to investigate the complex walking behaviors by varying the slope angle and the length of the lower-leg segment. We show exhibition of the period-doubling bifurcation, the Neimark-Sacker bifurcation, the period-remerging phenomenon, bubbles and chaos. The Poincaré map and the state space are also used to further analyze these complex behaviors.

Irregularity is the main characteristic of electroencephalographic signals (EEG), which needs a specific analysis method for neurological disease diagnosis. An efficient tool for signal irregularity analysis is Sample Entropy (SampEn). In this context, our paper was elaborated. We used SampEn to design a Machine Learning model for brain state detection based on EEG signals, which allows to differentiate between healthy (H) subjects, epileptic subjects during seizures free intervals (E) and epileptic subjects during seizures (S). Two main novelties are presented in our paper. The first one is related to the outline of the designed machine learning model, signal derivatives are determined as preprocessing step, then extracted features are SampEn and Standard Deviation (STD) from EEG signals and its first and second derivatives. These features are firstly used to train a K-Nearest Neighbor classifier (KNN) and yield high accuracy. After that, we select the most relevant features and we design our proposed classifier that provides better accuracy. The second one is related to the performance of our model to overcome some crucial purposes. In addition to the highest achieved accuracy, 100% for seizure detection, 99.2% for epilepsy detection and 99.86% for three class classification cases, our model used few features and simple classifier which involves fast running time. That is why we can consider our model as a suitable tool for real time applications.

In this paper, we suggest a control synthesis approach for the robust stabilization of an underactuated mechanical system, the Inertial Wheel Inverted Pendulum (IWIP), with norm-bounded parametric uncertainties and subject to both motion constraints and actuator saturation. A state-feedback controller is adopted to achieve such robust stabilization of the IWIP at its upright position, while the problem of the motion constraints is addressed by considering the saturation effect of the control input. Our design methodology of the robust saturated state-feedback control law is realized within the framework of Linear Matrix Inequalities (LMIs). We show first that the synthesis problem of such controller is written in terms of Bilinear Matrix Inequalities (BMIs), which are hardly tractable numerically. Then, in order to overcome this obstacle, we use some judicious mathematical tools to convert these BMIs into LMIs. Moreover, we consider the problem of enlarging the domain of attraction by computing the largest attractive invariant ellipsoid for the uncertain constrained nonlinear dynamics of the underactuated IWIP under the saturated state-feedback control law. Simulation results demonstrate the effectiveness and the robustness of the proposed robust saturated state-feedback controller towards norm-bounded parametric uncertainties while constraints on the system motion and the control input are respected.

This paper presents a new adaptive gain terminal sliding mode with gravity compensation control of an exoskeleton-upper limb system. The treated system is a two-degree-of-freedom robot (2-DoF) in interaction with an upper limb used for rehabilitation. The objective is to control the flexion/extension movement of the shoulder and the elbow in presence of matched disturbances. First, the modelling, the control and the stability study of the considered system using different laws were made. Next, a comparison study between these tested algorithms was done based on Monte Carlo robustness analysis method. Finally, the performance and the effectiveness of the adaptive gain terminal sliding mode algorithm combined with the Gravity Compensation in presence of uncertainties are provided by simulation results.

There have been few clinical or scientific reports of autosomal dominant tubulointerstitial kidney disease due to RENmutations (ADTKD-REN), limiting characterization. To further study this, we formed an international cohort characterizing 111 individuals from 30 families with both clinical and laboratory findings. Sixty-nine individuals had a RENmutation in the signal peptide region (signal group), 27 in the prosegment (prosegment group), and 15 in the mature renin peptide (mature group). Signal group patients were most severely affected, presenting at a mean age of 19.7 years, with the prosegment group presenting at 22.4 years, and the mature group at 37 years. Anemia was present in childhood in 91% in the signal group, 69% prosegment, and none of the mature group. RENsignal peptide mutations reduced hydrophobicity of the signal peptide, which is necessary for recognition and translocation across the endoplasmic reticulum, leading to aberrant delivery of preprorenin into the cytoplasm. RENmutations in the prosegment led to deposition of prorenin and renin in the endoplasmic reticulum-Golgi intermediate compartment and decreased prorenin secretion. Mutations in mature renin led to deposition of the mutant prorenin in the endoplasmic reticulum, similar to patients with ADTKD-UMOD, with a rate of progression to end stage kidney disease (63.6 years) that was significantly slower vs. the signal (53.1 years) and prosegment groups (50.8 years) (significant hazard ratio 0.367). Thus, clinical and laboratory studies revealed subtypes of ADTKD-RENthat are pathophysiologically, diagnostically, and clinically distinct.

In this paper, we have studied the effect of the degree of asymmetry and peakedness on the performances of a rough contact. A numerical model is proposed to evaluate the real area, the number of contacting asperities and the normal stiffness. The contact between two rough surfaces was modeled as a contact between a rigid flat and an elastic–plastic rough surface taking into account the work hardening and interaction among asperities. The Pearson system of frequency curves was used to generate non-Gaussian random surfaces. Results show that a negative skewness and/or a low kurtosis improve the contact performances by increasing the normal stiffness. This increase is governed by much more asperities into contact and more elastic behavior.

In this paper, we improve our palm vein recognition system to be based on phase response information of nonsubsampled contourlet transform (NSCT). First, we localise the region of interest (ROI), next, we have divided the ROI into a non-overlapping block and we proposed an encoding method based on extracting phase response information of NSCT coefficients, then XOR pattern is applied to extract invariant from local region of the palm vein to create a palm vein template of 512 bytes. Finally, we have calculated the modified hamming distance between templates to estimate the similarity between two palm veins filtered images. The method is tested on the CASIA Multispectral Palmprint Database. The experimental results illustrate the effectiveness of this coding in two modes of biometric palm vein: 99.90% of rank-one recognition rate and 0.19% of equal error rate in verification.

This paper addresses the problem of Static Output Feedback (SOF) stabilization for continuous-time linear systems subject to norm-bounded parameter uncertainties. Usually this issue leads to the feasibility of a Bilinear Matrix Inequality (BMI), which is difficult to linearize to get non conservative Linear matrix inequality (LMI) conditions. In this paper, by means of some technical lemmas, we transform the BMI into a new LMI with a line search over two scalar variables. The obtained LMI conditions are less conservative than those existing in the literature. Numerical evaluations are presented to show the superiority of the proposed method.

The Salicorniaspecies have been used for treatment and prevention of a various diseases. To the best of my knowledge, little information is regarding the antioxidant and protective activities of lipid extract from Salicornia Arabica(SALE). The objectives of this present work were designed to determine the in vitro antioxidant activities of SALE against cadmium-induced toxicity in erythrocytes isolated from rats. The distribution of fatty acid reflected the richness in saturated fatty acids that were predominated by palmitic acid. Our analysis showed that the major fatty acid components were palmitic acid (47.78%), linoleic acid (17.75%), followed by nanadecenoic acid (10.96%). Minor fatty acids including lignoseric acid and palmatoleic acid (C16:0). The in vitro antioxidant activity of SALE was evaluated using both test DPPH and ABTS assays. An important antioxidant potential was observed. The protective potential of SALE was evaluated by estimating the levels of stress markers like MDA concentration and SOD, CAT and GPx activities. Our results showed that cadmium significantly decreased the SOD, CAT and GPx activities in erythrocytes homogenates and enhanced lipid peroxidation. The pre-treatment with SALE ameliorated antioxidant status and inhibited MDA level in erythrocytes. In conclusion, the lipid isolated from S. arabicashowed protective potential against Cd-induced erythrocytes damage, which could be related to active compounds present in this fraction.

•La transformation numérique de l’industrie pharmaceutique est devenue une nécessité pour une meilleure visualisation des données et prise de décision.•L’objectif de la mise en place d’un système de « Planification et Ordonnancement avancé », comme nouvel outil de l’industrie 4.0, est d’améliorer la performance opérationnelle en matière de productivité et de flexibilité face aux aléas de la demande.•L’intégration du système de « Planification et Ordonnancement avancé » au « Progiciel de Gestion Intégré » permet de générer des simulations efficaces pour une analyse prédictive optimisée.

Phishing attacks have become the preferred vehicle to gather sensitive information as well as to deliver dangerous malware. So far, there is still no phishing detection system that can perfectly detect and progressively self adapt to differentiate between phishing and legitimate websites. This paper proposes the case-based reasoning Phishing detection system (CBR-PDS) that relies on previous cases to detect phishing attacks. CBR-PDS is highly adaptive and dynamic as it can adapt to detect new phishing attacks using rather a small dataset size in contrast to other machine learning techniques. CBR-PDS aims to improve the detection accuracy and the reliability of the results by identifying a set of discriminative features and discarding irrelevant features. CBR-PDS relies on a two stage hybrid procedure using Information gain and Genetic algorithms. The reduction of the data dimensionality amounts to an improved accuracy rate, yet it necessitates a reduced processing time. The CBR-PDS is tested using different scenarios on a various balanced datasets. The obtained performances clearly show the suitability of our proposed hybrid feature selection procedure as well as the efficiency of the proposed CBR-PDS system. The obtained accuracy rates exceed 95%. We also show that the integration of an Online Phishing Threats component into the CBR-PDS system improves further the accuracy rate. Finally, CRB-PDS performances are compared to those of several known competitive classifiers.