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Abstract Background Artemisia campestris L. (AC) leaves are widely recognized for their importance in traditional medicine. Despite the considerable amount of research conducted on this plant overworld, the chemical composition and the biological activity of the leaves grown in Tunisia remains poorly investigated. In this study of AC, a successive extraction method was employed (hexane, ethyl acetate and methanol) to investigate its bioactive constituents by LC-MS analysis, and their antioxidant, antibacterial, antifungal, and anticancer activities. Results Data analysis revealed diverse compound profiles in AC extracts. Methanolic and ethyl acetate extracts exhibited higher polyphenolic content and antioxidant activities, while Hexane showed superior phytosterol extraction. Ethyl acetate extract displayed potent antibacterial activity against multi-resistant Staphylococcus aureus and Pseudomonas aeruginosa. Additionally, all extracts demonstrated, for the first time, robust antifungal efficacy against Aspergillus flavus and Aspergillus niger. Cytotoxicity assays revealed the significant impact of methanolic and ethyl acetate extracts on metastatic breast cancer and multiple myeloma, examined for the first time in our study. Moreover, further analysis on multiple myeloma cells highlighted that the ethyl acetate extract induced apoptotic and necrotic cell death and resulted in an S phase cell cycle blockage, underscoring its therapeutic potential. Conclusions This investigation uncovers novel findings in Tunisian AC, notably the identification of lupeol, oleanolic acid, ursolic acid, stigmasterol and β-sitosterol. The study sheds light on the promising role of AC extracts in therapeutic interventions and underscores the need for continued research to harness its full potential in medicine and pharmaceutical development.

Vacant land in residual urban areas is a crucial resource to tackle the current climate and housing crises. In this study, we present the development of a geodatabase to determine the occurrence of vacant land in the urban core of Oklahoma City, USA (OKC), and assess its potential for infill housing. As a starting point, we define urban vacant land through a literature review. We present a description of the case study’s social and urbanistic context by highlighting its relevance to this study. We explain the methodology for the development of the geodatabase to quantify residual urban land in OKC’s urban core. We examine the spatial distribution and recurring characteristics of vacant parcels using QGIS, Python scripting for Rhinoceros 3D, and aerial imagery. We find that small parcels have higher vacancy rates than average-sized parcels and there is a correlation between higher vacancy rates and proximity to downtown and brownfields. Finally, we discuss the implications of the findings by assessing the urban vacant land potential for residential development and its contribution to OKC’s housing provision. Under all the proposed scenarios, the considered developable vacant land in the urban core could entirely fulfill the need for new housing units for the entire city.

Venoms are a rich source of bioactive compounds, and among them is leberagin-C (Leb-C), a disintegrin-like protein derived from the venom of Macrovipera lebetina transmediterrannea snakes. Leb-C has shown promising inhibitory effects on platelet aggregation. Previous studies have demonstrated that this SECD protein specifically targets α5β1, αvβ3, and αvβ6 integrins through a mimic mechanism of RGD disintegrins. In our current study, we focused on exploring the potential effects of Leb-C on metastatic breast cancer. Our findings revealed that Leb-C disrupted the adhesion, migration, and invasion capabilities of MDA-MB-231 breast cancer cells and its highly metastatic D3H2LN sub-population. Additionally, we observed significant suppression of adhesion, migration, and invasion of human umbilical vein endothelial cells (HUVECs). Furthermore, Leb-C demonstrated a strong inhibitory effect on fibroblast-growth-factor-2-induced proliferation of HUVEC. We conducted in vivo experiments using nude mice and found that treatment with 2 µM of Leb-C resulted in a remarkable 73% reduction in D3H2LN xenograft tumor size. Additionally, quantification of intratumor microvessels revealed a 50% reduction in tumor angiogenesis in xenograft after 21 days of twice-weekly treatment with 2 µM of Leb-C. Collectively, these findings suggest the potential utility of this disintegrin-like protein for inhibiting aggressive and resistant metastatic breast cancer.

Energy storage system (ESS) possesses tremendous potential to counter both the rapid growth of intermittent renewable energy resources (RESs) and provide frequency support to the microgrid (MG). Since the deployment of ESS has overcome the imbalance between generation and consumption, however, their massive cost, as well as degradation tendency, are the restricting considerations that demand alternative solutions to provide stable microgrid operation. To assist ESS, the electric vehicles (EVs) are incorporated into the system. EVs have been gradually commercially viable and considerable focus has been paid to vehicle-to-grid technologies. Appropriate collaboration between ESS and EVs has good capability to manage the frequency irregularities to ensure the efficient operation of the MG. This article presents a novel combination of two control techniques i.e., model predictive control (MPC) and adaptive droop control (ADC), to tackle the frequency regulation issue in the isolated MG, by effectively controlling the ESS and EVs during the large-scale integration of RESs or huge change in load demand. Firstly, the MPC regulates the ESS according to the system frequency deviation, and secondly, the ADC manages the power of EVs according to system specifications by retaining the least possible power for potential usage of EVs. Moreover, an advanced genetic algorithm is applied to tune the MPC and ADC parameters in order to achieve optimized performance. An isolated MG is modeled and verified in MATLAB/Simulink using the above-mentioned control techniques. Further, different case studies are taken into account to validate the combination of ADC and MPC for frequency regulation of an isolated MG. Additionally, the proposed MPC controller is compared with fuzzy logic proportional-integral (FPI) controller and proportional-integral (PI) controller, the MPC provides better performance results as compared with FPI and PI controllers.

The number of electric vehicles and renewable energy resources integrated into the power system is increasing day by day. The objective behind the development of electric vehicles and renewable energy sources is to build a sustainable and green power system. The renewables either don't possess system inertia or have less system inertia, therefore, they don't effectively respond to the load variations. The battery storage system of electric vehicles is used as the first line of defense to counter the effect of load/frequency variations and make the system stable. As active power is inversely proportional to the system frequency, for this purpose electric vehicles are included in the microgrid environment. In this paper, an isolated microgrid having a reheat turbine system, wind turbine system, photovoltaic system, and electric vehicles is studied. The output of the renewables is not controlled to utilize its maximum output power. Therefore, adaptive droop control and fuzzy PI control mechanisms are implemented to cater to the frequency variations of the isolated microgrid; the former regulates the power of electric vehicles while maintaining the energy needs of each EV and the later controls the output power of reheat turbine system according to the frequency variation. Furthermore, the genetic algorithm optimization toolbox is utilized to optimize the parameters of the adaptive and fuzzy PI controllers. The proposed model is developed in MATLAB/Simulink which shows that these control techniques effectively sustained the system frequency of isolated microgrid in the desired limits.

After nearly a century with internal combustion engines dominating the transportation sector, it now appears that electric vehicles (EVs) are on the brink of enjoying rapid development due to numerous useful features they possess, such as less operational cost and reduced carbon emissions. EVs can act as load as well as source, by utilizing the technique known as Vehicle-to-Grid (or Grid-to-Vehicle technique if EVs are used as a load). This technique adds key features to an industrial microgrid in the form of primary frequency control and congestion management. In this paper, two controllers (grid regulation and charger controller) are proposed by considering different charging profiles, state of charge of electric vehicle batteries, and a varying number of electric vehicles in an electric vehicle fleet. These controllers provide bidirectional power flow, which can provide primary frequency control during different contingencies that an industrial microgrid may face during a 24-hour period. Simulation results prove that the proposed controllers provide reliable support in terms of frequency regulation to an industrial microgrid during contingencies. Furthermore, simulation results also depict that by adding more electric vehicles in the fleet during the vehicle-to-grid mode, the frequency of an industrial microgrid can be improved to even better levels. Different case studies in this article constitute an industrial microgrid with varied distributed energy resources (i.e. solar and wind farm), electric vehicles fleet, industrial and residential load along with diesel generator. These test cases are simulated and results are analyzed by using MATLAB/SIMULINK.

With increasing the installation of the photovoltaic modules, the different failures on components of the system are dramatically increased and thus lead to a direct impact on system productivity and efficiency. Fault detection and diagnosis accurately have an extreme impact on the maintenance and reliability of photovoltaic array. Moreover, for detecting the different faults, selecting the proper indicators for monitoring the system improves the fault diagnosis techniques performance and avoids the complexity of the system. In this paper, an efficient detection and diagnosis model for different fault types is proposed. This model has sequential steps. Firstly, the performance of seven indicators is initially analyzed to predict accurately the nonlinear output behavior of the photovoltaic system under changing environmental conditions, hence select the minimum indicators to detect the typical faults. Secondly, ten fault cases, considering single-fault types and another three faults considering multi-fault types, are investigated. At the same time, the impact of these faults on the selected indicators is deeply analyzed. Finally, the typical fault types are classified and detected effectively depending on three sequential probabilistic neural network models, which give a precise classification of the data inputs. Both theoretical and experimental tests are operated to validate the performance and effectiveness of the proposed model.

Candida and dermatophyte infections are difficult to treat due to increasing antifungal drugs resistance such as fluconazole, as well as the emergence of multi-resistance in clinical bacteria. Here, we first synthesized silver nanoparticles using aqueous fruit extracts from Scabiosa atropurpurea subsp. maritima (L.). The characterization of the AgNPs by means of UV, XRD, FTIR, and TEM showed that the AgNPs had a uniform spherical shape with average sizes of 40–50 nm. The biosynthesized AgNPs showed high antioxidant activity when investigated using 1,1-diphenyl-2-picryl-hydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. The AgNPs displayed strong antibacterial potential expressed by the maximum zone inhibition and the lowest MIC and MBC values. The AgNPs revealed a significant antifungal effect against the growth and biofilm of Candida species. In fact, the AgNPs were efficient against Trichophyton rubrum, Trichophyton interdigitale, and Microsporum canis. The antifungal mechanisms of action of the AgNPs seem to be due to the disruption of membrane integrity and a reduction in virulence factors (biofilm and hyphae formation and a reduction in germination). Finally, the silver nanoparticles also showed important cytotoxic activity against the human multiple myeloma U266 cell line and the human breast cancer cell line MDA-MB-231. Therefore, we describe new silver nanoparticles with promising biomedical application in the development of novel antimicrobial and anticancer agents.

In this case report we describe an unusual presentation of severe acute papillary necrosis in a COVID-19-positive patient. An emergency flexible ureteroscopy greatly helped in the establishment of the diagnosis. In the international literature, there is a paucity of intraoperative endoscopic images representing severe renal papillary necrosis. We present a case of severe acute renal papillary necrosis in a 49-year-old south-Asian, COVID-19-positive male patient who needed emergency urological intervention for macroscopic hematuria and urinary retention due to clot formation in the urinary bladder. The patient underwent emergency cystoscopy, clot evacuation, and by rigid and flexible ureteroscopy. The diagnosis was only confirmed in the postoperative period, retrospectively. Finally, the patient fully recovered due to the multidisciplinary management. Diagnosis of rare clinical entities can be sometimes challenging in the everyday routine practice. Having atypical clinical course, the surgeon should be prepared and sometimes must take responsible decisions promptly, even if needed intraoperatively, to manage unexpected findings in order to get the right diagnosis without compromising the patient’s safety.

The advent of renewable energy resources and distributed energy systems herald a new set of challenges of power quality, efficient distribution, and stability in the power system. Furthermore, the power electronic converters integration has been increased in interfacing alternate energy systems and industries with the transmission and distribution grids. Owing to the intermittency of renewable energy resources and the application of power electronic converters the power distribution faces peculiar challenges. The dead-time effects are among the main challenges, which leads to the distortion of third harmonics, phase angle, torque pulsation, and induction motor current, causing severe quality problems for power delivery. To tackle these problems, this paper proposes a novel dead time compensation technique for improving the power quality parameters and improving the efficiency of power converters. The proposed model is simulated in MATLAB and the parametric equations are plotted against the corresponding parametric values. Furthermore, by implementing the proposed strategy, significant improvements are attained in the torque pulsation, speed, and total harmonic distortion of the induction motor. The comparisons are drawn between with and without dead time compensation technique, the former shows significant improvements in all aspects of the power quality parameters and power converters efficiency.

With the gradual increase in the installed capacity of wind turbines, more and more attention has been paid to the economy of wind power. Economic model-predictive control (EMPC) has been developed as an effective advanced control strategy, which can improve the dynamic economy performance of the system. However, the variable-speed wind turbine (VSWT) system widely used is generally nonlinear and highly coupled nonaffine systems, containing multiple economic terms. Therefore, a nonlinear EMPC strategy considering power maximization and mechanical load minimization is proposed based on the comprehensive VSWT model, including the dynamics of the tower and the gearbox in this paper. Three groups of simulations verify the effectiveness and reliability/practicability of the proposed nonlinear EMPC strategy.

Breast cancer metastasis is a leading cause of death by malignancy in women worldwide. Efforts are being made to further characterize the rate-limiting steps of cancer metastasis, i.e. extravasation of circulating tumor cells and colonization of secondary organs. In this study, we investigated whether angiotensin II, a major vasoactive peptide both produced locally and released in the bloodstream, may trigger activating signals that contribute to cancer cell extravasation and metastasis. We used an experimental in vivo model of cancer metastasis in which bioluminescent breast tumor cells (D3H2LN) were injected intra-cardiacally into nude mice in order to recapitulate the late and essential steps of metastatic dissemination. Real-time intravital imaging studies revealed that angiotensin II accelerates the formation of metastatic foci at secondary sites. Pre-treatment of cancer cells with the peptide increases the number of mice with metastases, as well as the number and size of metastases per mouse. In vitro, angiotensin II contributes to each sequential step of cancer metastasis by promoting cancer cell adhesion to endothelial cells, trans-endothelial migration and tumor cell migration across extracellular matrix. At the molecular level, a total of 102 genes differentially expressed following angiotensin II pre-treatment were identified by comparative DNA microarray. Angiotensin II regulates two groups of connected genes related to its precursor angiotensinogen. Among those, up-regulated MMP2/MMP9 and ICAM1 stand at the crossroad of a network of genes involved in cell adhesion, migration and invasion. Our data suggest that targeting angiotensin II production or action may represent a valuable therapeutic option to prevent metastatic progression of invasive breast tumors.

INTRODUCTION: The poor efficacy of various anti-cancer treatments against metastatic cells has focused attention on the role of tumor microenvironment in cancer progression. To understand the contribution of the extracellular matrix (ECM) environment to this phenomenon, we isolated ECM surrogate invading cell populations from MDA-MB-231 breast cancer cells and studied their genotype and malignant phenotype. METHODS: We isolated invasive subpopulations (INV) from non invasive populations (REF) using a 2D-Matrigel assay, a surrogate of basal membrane passage. INV and REF populations were investigated by microarray assay and for their capacities to adhere, invade and transmigrate in vitro, and to form metastases in nude mice. RESULTS: REF and INV subpopulations were stable in culture and present different transcriptome profiles. INV cells were characterized by reduced expression of cell adhesion and cell-cell junction genes (44% of down regulated genes) and by a gain in expression of anti-apoptotic and pro-angiogenic gene sets. In line with this observation, in vitro INV cells showed reduced adhesion and increased motility through endothelial monolayers and fibronectin. When injected into the circulation, INV cells induced metastases formation, and reduced injected mice survival by up to 80% as compared to REF cells. In nude mice, INV xenografts grew rapidly inducing vessel formation and displaying resistance to apoptosis. CONCLUSION: Our findings reveal that the in vitro ECM microenvironment per se was sufficient to select for tumor cells with a stable metastatic phenotype in vivo characterized by loss of adhesion molecules expression and induction of pro-angiogenic and survival factors.

BACKGROUND: Although there was growing evidence in the potential use of Bisphosphonates (BPs) in cancer therapy, their strong osseous affinities that contrast their poor soft tissue uptake limited their use. Here, we developed a new strategy to overcome BPs hydrophilicity by masking the phosphonic acid through organic protecting groups and introducing hydrophobic functions in the side chain. METHODOLOGY/PRINCIPAL FINDINGS: We synthesized non-nitrogen BPs (non N-BPs) containing bromobenzyl group (BP7033Br) in their side chain that were symmetrically esterified with hydrophobic 4-methoxphenyl (BP7033BrALK) and assessed their effects on breast cancer estrogen-responsive cells (T47D, MCF-7) as well as on non responsive ones (SKBR3, MDA-MB-231 and its highly metastatic derived D3H2LN subclone). BP7033Br ALK was more efficient in inhibiting tumor cell proliferation, migration and survival when compared to BP7033Br. Although both compounds inhibited tumor growth without side effects, only BP7033Br ALK abrogated tumor angiogenesis and D3H2LN cells-induced metastases formation. CONCLUSION/SIGNIFICANCE: Taken together these data suggest the potential therapeutic use of this new class of esterified Bisphosphonates (BPs) in the treatment of tumor progression and metastasis without toxic adverse effects.

Phishing attacks are increasing every year, both in terms of number and technique. Using only human weaknesses, an attacker can easily obtain the victim's credentials or access their network. The problem persists despite many approaches offered by researchers, due to its dynamic nature, in which new phishing tactics are created every time. We, therefore, need more robust and effective methods to detect phishing emails. In this paper, we aim to detect phishing emails using the body text of the email with the hybrid approach combining case-based reasoning (CBR) and a deep learning model. Our proposed model, called DL-CBR, consists of a Bidirectional Long Short-Term Memory (Bi-LSTM) + Temporal Convolutional Network (TCN) network with an attention mechanism followed by a CBR classifier. The deep learning model is used for email representation, where it is trained using the N -pair loss function. To demonstrate the performance of DL-CBR, evaluation metrics, such as precision, accuracy, recall, and F-measure, were used, where we obtained an accuracy of 98.28%. The results show that our model outperformed other CBRs that utilize classical text representations like TF-IDF and Bag-of-Words. Additionally, while our model's performance is slightly below that of the state-of-the-art models, it offers several advantages inherent to CBR. For instance, it can learn from new cases and update their database accordingly. [ABSTRACT FROM AUTHOR]

This study investigates the effect of tool pin eccentricity and welding speed on the grain structure, crystallographic texture, and mechanical properties of friction stir welded (FSWed) AA5754-H24. Three tool pin eccentricities of 0, 0.2, and 0.8 mm at different welding speeds ranging from 100 mm/min to 500 mm/min and a constant tool rotation rate of 600 rpm were investigated. High-resolution electron backscattering diffraction (EBSD) data were acquired from each weld's center of the nugget zone (NG) and processed to analyze the grain structure and texture. In terms of mechanical properties, both hardness and tensile properties were investigated. The grain structure in the NG of the joints produced at 100 mm/min, 600 rpm, and different tool pin eccentricities showed significant grain refining due to dynamic recrystallization with average grain sizes of 18, 15, and 18 µm at 0, 0.2, and 0.8 mm pin eccentricities, respectively. Increasing the welding speed from 100 to 500 mm/min further reduced the average grain size of the NG zone to 12.4, 10, and 11 µm at 0, 0.2, and 0.8 mm eccentricity, respectively. The simple shear texture dominates the crystallographic texture with both B ¯ /B texture component with the C component at their ideal positions after rotating the data to align the shear reference frame with the FSW reference frame in both the PFs and ODF sections. The tensile properties of the welded joints were slightly lower than the base material due to the hardness reduction in the weld zone. However, the ultimate tensile strength and the yield stress for all welded joints increased by increasing the friction stir welding (FSW) speed from 100 to 500 mm/min. Welding using the pin eccentricity of 0.2 mm resulted in the highest tensile strength; at a welding speed of 500 mm/min, it reached 97% of the base material strength. The hardness profile showed the typical W shape with a reduction in the hardness of the weld zone and a slight recovery of the hardness in the NG zone. [ABSTRACT FROM AUTHOR]

The motivation for the current study was to improve the wear and frictional properties of Al, Al–Al2O3, and SiC MMCs through HPT processing. The wear test using a tungsten carbide (WC) ball was carried out for different PM and HPT-processed Al and MMC samples. The effect of the sample processing methods on the wear rate, friction, and wear surface morphology was thoroughly investigated. The high hardness after Al grain refinement and reinforcement fragmentation through the HPT processing of the samples increased the wear resistance by 16–81% over that of the PM samples. The average coefficient values and variation ranges were reduced after HPT processing. The Al and Al MMC processing methods affected the wear mechanism and surface morphologies, as proven by the microscopic observations and analyses of the worn surfaces of the samples and WC balls. [ABSTRACT FROM AUTHOR]

Al-Al2O3 and SiC metal matrix composites (MMCs) samples with different volume fractions up to 20% were produced by high-pressure torsion (HPT) using 10 GPa for 30 revolutions of Al-Al2O3, and SiC and powder metallurgy (PM). The effect of the processing method of micro-size Al MMCs on the density, microstructure evolution, mechanical properties, and tensile fracture mode was thoroughly investigated. HPT processing produces fully dense samples relative to those produced using powder metallurgy (PM). The HPT of the Al MMCs reduces the Al matrix grain size and fragmentation of the reinforcement particles. The Al matrix average grain size decreased to 0.39, 0.23, and 0.2 µm after the HPT processing of Al, Al-20% Al2O3, and SiC samples. Moreover, Al2O3 and SiC particle sizes decreased from 31.7 and 25.5 µm to 0.15 and 0.13 µm with a 99.5% decrease. The production of ultrafine grain (UFG) composite samples effectively improves the microhardness and tensile strength of the Al and Al MMCs by 31–88% and 10–110% over those of the PM-processed samples. The good bonding between the Al matrix and reinforcement particles noted in the HPTed Al MMCs increases the strength relative to the PM samples. The tensile fracture surface morphology results confirm the tensile properties results. [ABSTRACT FROM AUTHOR]

Due to the strong nonlinearities of the boiler-turbine system, feasibility and high response capability are hard to realize using traditional linear controllers. Advanced controllers that can ensure stability and feasibility without violating system constraints, and enhance the system’s dynamic output performance, are needed. Therefore, this paper proposes a stable input/output feedback linearization (IOFL) model predictive controller (MPC) technique for the boiler-turbine system. This nonlinear system is decoupled using the IOFL method into a novel linearized model, which is then used for constituting the proposed stable IOFL MPC problem. The proposed scheme uses a constraint mapping method that converts actual input limits into limits on the basis of the control output variable to ensure a feasible solution over the whole prediction horizon. Moreover, a min-max MPC technique in the form of linear matrix inequality with the realization of the input rate-of-change constraints is utilized to ensure the boiler-turbine unit’s stability. The process model and proposed control scheme are executed using MATLAB and the simulation results demonstrate that the proposed controller has an enhanced dynamic output performance compared with an advanced control scheme under various load variations. [ABSTRACT FROM AUTHOR]

The influence of the number of passes and the tube materials on the microstructural evolution, mechanical properties, and wear behavior of Cu and brass tubes after parallel tubular channel angular pressing (PTCAP) was investigated. The grain size decreased to final grain sizes of 138.6 nm and 142.7 nm, after PTCAP of the Cu and brass tubes was conducted in up to 4 and 2 passes, respectively. PTCAP contributes to obtaining an ultra-fine grain (UFG) microstructure, with a mixture of different grain sizes that conferred high hardness. The present results indicate the superior wear resistance of Cu and brass PTCAP tubes, relative to Cu and brass samples that were previously deformed by different severe plastic deformation (SPD) processes. The wear mechanism of the Cu tubes changed from delamination and cracks with a high degree of adhesive wear before PTCAP into a combination of adhesive and abrasive wear, with a decrease in the presence of oxygen content after the PTCAP procedure. The wear mechanism also changed from a combination of adhesive and abrasive mechanisms into abrasive ones with the absence of oxygen after the PTCAP of brass tubes. [ABSTRACT FROM AUTHOR]