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The application of green building approaches has significantly increased in many countries and buildings, accompanied by the development of numerous standards and methodologies for their implementation. Despite these efforts, not all risks and challenges facing green projects have been eliminated in some regions. Issues such as financing difficulties, budget overruns, and schedule delays continue to pose significant challenges. As a result, no substantial improvements have been made in the approach to green projects. Therefore, this study aims to develop a theoretical framework that enhances the approach to green projects. By utilizing the AGILE methodology, specifically SCRUM, the most significant risks facing green projects were identified and converted into indicators based on prior studies. Furthermore, Building Information Modeling (BIM) technology, particularly Green BIM (GBIM), was employed to create tools and elements to address these challenges, leading to the development of a conceptual framework capable of providing solutions. This framework was built around 30 indicators, whose weights were determined through an electronic questionnaire involving 140 specialists in green projects, AGILE methodology, and BIM technology. Assistance from academic experts was also sought. The results of the questionnaire, analyzed using statistical methods, contributed to the development of a theoretical framework aimed at improving the approach to green projects.

A reversed phase HPLC method with UV detection was designed for the first time for the simultaneous estimation of meloxicam and esomeprazole in their combined tablet dosage forms. Full factorial design was used for rapid optimization of the proposed method. Chromatographic separation was reached using isocratic elution on C18 column. The mobile phase was a mixture of methanol: acetonitrile: 0.05 M potassium dihydrogen phosphate buffer at pH 5, adjusted using phosphoric acid and/or NaOH when needed. The flow rate was 1 mL/min and the injection volume was 20 µL. The detection wavelength was 230 nm. The working ranges of the method were 5.0-100.0 and 10.0–100.0 µg/mL, LOD values were 0.8 and 1.8 µg/mL and LOQ values were 2.6 and 5.5 µg/mL for meloxicam and esomeprazole, respectively. The proposed method was successfully applied to their combined tablet dosage forms with acceptable % recoveries (100.4 − 100.7%) obtained. Four methods were used to evaluate the greenness of the proposed method, suggesting the acceptability of the greenness of the proposed method.

Food and Drug Administration (FDA) recently approved co-formulated celecoxib and tramadol for the treatment of acute pain in adults. Three spectrophotometric methods were efficiently applied to estimate the co-formulated Celecoxib and Tramadol in their tablets; second derivative 2D-spectrophotometry technique (method I), induced dual-wavelength technique (method II) and dual-wavelength resolution technique (method III). The proposed methods were successfully validated following the International Council for Harmonisation (ICH) guidelines and statistically assessed based on the correlation coefficients, relative standard deviations as well as detection and quantitation limits. The obtained results revealed non-significant differences compared to the reported results as revealed by the variance ratio F test and Student t test. Moreover, the applied techniques were further assessed concerning their greenness based on the analytical eco-scale method revealing an excellent green scale with a final score of 95. The proposed spectrophotometric techniques could be applied for the routine analysis and quality control of the studied drugs in their dosage form.

Hospitals are the type of buildings which need development and expansion continuously so it can achieve all the demands of the progress in the medical field, medical devices, and the updates in the infrastructure of the hospitals. Due to the spread of many bacteria that are related to the construction and development process, many countries had to take into considerations many strict precautions to reduce the danger of the infection spread. These precautions are important either inside the building of the hospital or outside, so the maximum reduction of infection spread should be reached as there are many patients suffer from lack of immunity. This research aims to reach a rational design criterion for hospital designers which gains the required demands to combat the infection spread during construction and development process meanwhile continuing to present the medical services. It is strongly recommended to introduce flexible structural module that can be reused in different activities. Also, isolation of patient’s spaces during construction becomes a mandatory manner. Moreover, it is advised to design an adaptable ventilation system which facilitates different sectors separation, either patient, medical stuff, or workers paths.

Jojoba shrubs are wild plants cultivated in arid and semiarid lands and characterized by tolerance to drought, salinity, and high temperatures. Fungi associated with such plants may be attributed to the tolerance of host plants against biotic stress in addition to the promotion of plant growth. Previous studies showed the importance of jojoba as jojoba oil in the agricultural field; however, no prior study discussed the role of jojoba-associated fungi (JAF) in reflecting plant health and the possibility of using JAF in biocontrol. Here, the culture-independent and culture-dependent approaches were performed to study the diversity of the jojoba-associated fungi. Then, the cultivable fungi were evaluated for in-vitro antagonistic activity and in vitro plant growth promotion assays. The metagenome analysis revealed the existence of four fungal phyla: Ascomycota, Aphelidiomycota, Basidiomycota, and Mortierellomycota. The phylum Ascomycota was the most common and had the highest relative abundance in soil, root, branch, and fruit samples (59.7%, 50.7%, 49.8%, and 52.4%, respectively). Alternaria was the most abundant genus in aboveground tissues: branch (43.7%) and fruit (32.1%), while the genus Discosia had the highest abundance in the underground samples: soil (24%) and root (30.7%). For the culture-dependent method, a total of 14 fungi were isolated, identified, and screened for their chitinolytic and antagonist activity against three phytopathogenic fungi ( Fusarium oxysporum, Alternaria alternata and Rhizoctonia solani ) as well as their in vitro plant growth promotion (PGP) activity. Based on ITS sequence analysis, the selected potent isolates were identified as Aspergillus stellatus EJ-JFF3, Aspergillus flavus EJ-JFF4, Stilbocrea  sp. EJ-JLF1, Fusarium solani EJ-JRF3 , and Amesia atrobrunnea EJ-JSF4. The endophyte strain A. flavus EJ-JFF4 exhibited the highest chitinolytic activity (9 Enzyme Index) and antagonistic potential against Fusarium oxysporum , Alternaria alternata , and Rhizoctonia solani phytopathogens with inhibitory percentages of 72, 70, and 80 respectively. Also, A. flavus EJ-JFF4 had significant multiple PGP properties, including siderophore production (69.3%), phosphate solubilization (95.4 µg ml −1 ). The greatest production of Indol-3-Acetic Acid was belonged to A.   atrobrunnea EJ-JSF4 (114.5 µg ml −1 ). The analysis of FUNGuild revealed the abundance of symbiotrophs over other trophic modes, and the guild of endophytes was commonly assigned in all samples. For the first time, this study uncovered fungal diversity associated with jojoba plants using a culture-independent approach and in-vitro assessed the roles of cultivable fungal strains in promoting plant growth and biocontrol. The present study indicated the significance of jojoba shrubs as a potential source of diverse fungi with high biocontrol and PGP activities. Graphical abstract

In this paper, an experimental study was conducted to examine the static and dynamic behaviors of rubberized fiber-reinforced concrete (RFRC). Crumb rubber was partially replaced from sand at volume fractions of 0%, 5%, 10%, 15%, and 20%. Steel fibers (SFs) with fiber volume fractions (Vf%) of 0%, 0.5%, 1%, and 1.5% were used for the production of FRCs, while polypropylene fiber (PPF) with Vf% = 0.4% was adopted to produce others FRCs. A combination of 0.4% PPF and 1% SF was used for hybrid FRC. The static properties were evaluated through compression, indirect tension, and flexural tests. However, the drop weight impact test was conducted to assess the dynamic property by estimating the impact energy. It was observed that the replacement of sand with rubber reduced all mechanical properties of concrete. In the case of RFRC, a reduction in compressive strength, compared to samples without fibers, was noted, and this reduction increased with higher Vf%. Both toughness indices and fracture energy were affected slightly by increasing rubber percentages while markedly increased with higher Vf%. However, adding rubber and/or fibers enhanced the impact energy of concrete.

Autophagy is a proposed route of amyloid-β (Aβ) clearance by microglia that is halted in Alzheimer’s Disease (AD), though mechanisms underlying this dysfunction remain elusive. Here, primary microglia from adult AD (5xFAD) mice were utilized to demonstrate that 5xFAD microglia fail to degrade Aβ and express low levels of autophagy cargo receptor NBR1. In 5xFAD mouse brains, we show for the first time that AD microglia express elevated levels of microRNA cluster Mirc1/Mir17-92a, which is known to downregulate autophagy proteins. By in situ hybridization in post-mortem AD human tissue sections, we observed that the Mirc1/Mir17-92a cluster member miR-17 is also elevated in human AD microglia, specifically in the vicinity of Aβ deposits, compared to non-disease controls. We show that NBR1 expression is negatively correlated with expression of miR-17 in human AD microglia via immunohistopathologic staining in human AD brain tissue sections. We demonstrate in healthy microglia that autophagy cargo receptor NBR1 is required for Aβ degradation. Inhibiting elevated miR-17 in 5xFAD mouse microglia improves Aβ degradation, autophagy, and NBR1 puncta formation in vitro and improves NBR1 expression in vivo . These findings offer a mechanism behind dysfunctional autophagy in AD microglia which may be useful for therapeutic interventions aiming to improve autophagy function in AD.

This paper presents an innovative AI-driven solution for the early detection of dust accumulation on solar energy modules, leveraging computer vision and machine learning techniques. The study identifies two significant gaps in existing literature: the impact of dataset quality on research outcomes and the predominance of binary classification models, which limit the analysis of dust levels on photovoltaic (PV) modules. To address these gaps, we propose a sophisticated system that utilizes a visual dataset of continuously monitored images captured by a Raspberry Pi camera, alongside a raw dataset from the inverter tracking real-time energy production metrics. Our model is trained using machine learning algorithms to optimize cleaning patterns dynamically, maximizing energy output while minimizing operational costs. The results indicate that the AI-powered system enhances PV performance and contributes to cost reductions, ultimately promoting sustainability in solar energy production. The cleaning classifier automates condition-based cleaning, reducing the need for routine inspections and preventing up to 30% energy loss due to dust accumulation. The system achieves a cleaning efficiency of 1.23, reflecting a 23% increase in energy production compared to traditional periodic cleaning methods, resulting in a cost saving of $2,023. Furthermore, the implementation of the WattsUp mobile application facilitates user interaction by allowing monitoring of solar panel status and maintenance instructions, enhancing user engagement with the system. The application design emphasizes user trust and participation, featuring onboarding elements that highlight the importance of solar energy management in combating climate change. This comprehensive approach not only demonstrates the feasibility of a dynamic cleaning model but also establishes a payback period of less than a year, underscoring the economic viability of the proposed system in real-world applications.

Cancer is one of the leading causes of death worldwide. In many cases, cancer is related to the elevated expression of a significant cytokine known as tumor necrosis factor-α (TNF-α). Breast cancer in particular is linked to increased proliferation of tumor cells, high incidence of malignancies, more metastases, and generally poor prognosis for the patient. The research sought to assess the effect of silver nanoparticles reduced with ethyl cellulose polymer (AgNPs-EC) on TNF-α expression in MCF-7 human breast cancer cells. The AgNPs-EC were produced using the green synthesis reduction method, and their formation was proofed via UV-VIS spectroscopy. Furthermore, AgNPs-EC were characterized for their size, charge, morphology, Ag ion release, and stability. The MCF-7 cells were treated with AgNPs-EC. Then, the expression of TNF-α genes was determined through PCR in real time, and protein expression was studied using ELISA. The AgNPs-EC were spherical with an average size of 150±5.1 nm and a zeta-potential of -41.4±0.98 mV. AgNPs-EC had an inhibitory effect on cytokine mRNA and protein expression levels, which suggests that they could be used safely in the fight against cancer. AgNPs-EC cytotoxicity was also found to be non-toxic to MCF-7. Our data determined AgNPs-EC as a novel inhibitor of TNF-α production. These results are promising for developing novel therapeutic approaches for the future treatment of cancer with safe materials.

Systematic reviews and/or meta-analyses generally provide the best evidence for medical research. Authors are recommended to use flow diagrams to present the review process, allowing for better understanding among readers. However, no studies as of yet have assessed the quality of flow diagrams in systematic review/meta-analyses. Our study aims to evaluate the quality of systematic review/meta-analyses over a period of ten years, by assessing the quality of the flow diagrams, and the correlation to the methodological quality. Two hundred articles of \"systematic review\" and/or \"meta-analysis\" from January 2004 to August 2015 were randomly retrieved in Pubmed to be assessed for the flow diagram and methodological qualities. The flow diagrams were evaluated using a 16-grade scale corresponding to the four stages of PRISMA flow diagram. It composes four parts: Identification, Screening, Eligibility and Inclusion. Of the 200 articles screened, 154 articles were included and were assessed with AMSTAR checklist. Among them, 78 articles (50.6%) had the flow diagram. Over ten years, the proportion of papers with flow diagram available had been increasing significantly with regression coefficient beta = 5.649 (p = 0.002). However, the improvement in quality of the flow diagram increased slightly but not significantly (regression coefficient beta = 0.177, p = 0.133). Our analysis showed high variation in the proportion of articles that reported flow diagram components. The lowest proportions were 1% for reporting methods of duplicates removal in screening phase, followed by 6% for manual search in identification phase, 22% for number of studies for each specific/subgroup analysis, 27% for number of articles retrieved from each database, and 31% for number of studies included in qualitative analysis. The flow diagram quality was correlated with the methodological quality with the Pearson's coefficient r = 0.32 (p = 0.0039). Therefore, this review suggests that the reporting quality of flow diagram is less satisfactory, hence not maximizing the potential benefit of the flow diagrams. A guideline with standardized flow diagram is recommended to improve the quality of systematic reviews, and to enable better reader comprehension of the review process.