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Promoting flexible energy demand through response programs in residential neighborhoods would play a vital role in addressing the issues associated with increasing the share of distributed solar systems and balancing supply and demand in energy networks. However, accurately identifying baseline-related energy measurements when activating energy demand response events remains challenging. In response, this study presents a deep learning-based, data-driven framework to improve short-term estimates of demand response baselines during the activation of response events. This framework includes bidirectional long-term memory (BiLSTM), long-term memory (LSTM), gated recurrent unit (GRU), convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN). Their performance is evaluated by considering different aggregation levels of the demand response baseline profile for 337 dwellings in the city of La Rochelle, France, over different time horizons, not exceeding 24 h. It is also compared with fifteen traditional statistical and machine learning methods in terms of forecasting accuracy. The results demonstrated that deep learning-based models, compared to others, significantly succeeded in minimizing the gap between the actual and forecasted values of demand response baselines at all different aggregation levels of dwelling units over the considered time-horizons. BiLSTM models, followed by GRU and LSTM, consistently demonstrated the lowest mean absolute percentage error (MAPE) in most comparison experiments, with values up to 9.08%, 8.71%, and 9.42%, respectively. Compared to traditional statistical and machine learning models, extreme gradient boosting (XGBoost) was among the best, with a value up to 11.56% of MAPE, but could not achieve the same level of forecasting accuracy in all comparison experiments. Such high performance reveals the potential of the proposed deep learning approach and highlights its importance for improving short-term estimates of future baselines when implementing demand response programs in residential neighborhood contexts.

Promoting flexible energy demand through response programs in residential neighborhoods would play a vital role in addressing the issues associated with increasing the share of distributed solar systems and balancing supply and demand in energy networks. However, accurately identifying baseline-related energy measurements when activating energy demand response events remains challenging. In response, this study presents a deep learning-based, data-driven framework to improve short-term estimates of demand response baselines during the activation of response events. This framework includes bidirectional long-term memory (BiLSTM), long-term memory (LSTM), gated recurrent unit (GRU), convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN). Their performance is evaluated by considering different aggregation levels of the demand response baseline profile for 337 dwellings in the city of La Rochelle, France, over different time horizons, not exceeding 24 h. It is also compared with fifteen traditional statistical and machine learning methods in terms of forecasting accuracy. The results demonstrated that deep learning-based models, compared to others, significantly succeeded in minimizing the gap between the actual and forecasted values of demand response baselines at all different aggregation levels of dwelling units over the considered time-horizons. BiLSTM models, followed by GRU and LSTM, consistently demonstrated the lowest mean absolute percentage error (MAPE) in most comparison experiments, with values up to 9.08%, 8.71%, and 9.42%, respectively. Compared to traditional statistical and machine learning models, extreme gradient boosting (XGBoost) was among the best, with a value up to 11.56% of MAPE, but could not achieve the same level of forecasting accuracy in all comparison experiments. Such high performance reveals the potential of the proposed deep learning approach and highlights its importance for improving short-term estimates of future baselines when implementing demand response programs in residential neighborhood contexts. [ABSTRACT FROM AUTHOR]

Effecient green tools of β-(3,4-dichlorophenyl-acrylic acid, thioglycolic acid and β-(2-oxopyrrolidin-1-yl) ethanol under ultrasonic and microwave-assisted irradiation (MW-US) as found to be a simple approach for preparing interesting Spiro derivatives. A novel class Spiro-pyrrolidine-2,3'-thieno[2,3-d]pyridazine derivatives (2–6) were efficiently synthesized via one-pot multicomponent reactions. Ethoxy acetyl Spiro pyrrolidine-2,3'-thieno[2,3-d]pyridazin-hydrazide (5) assessed as ecofriendly microbicidal and insecticidal activities to establish a structure-activity relationship. Elemental analysis and spectroscopic data were used to describe the structures of all synthesized products. The Spiro-heterocyclic compounds are exclusive non-planar structures and branded for binding to biomolecules. The microbicidal and insecticidal activities of the compounds were investigated on ATCC coded test microorganisms upon the applied dose and time was studied through two kinetic study. The interaction with these antibacterial and insect's third instar larvae was medicinal and economically valuable. The preliminary testing demonstrated flourishing microbicidal capability to prevent the growth of threatening pathogenic bacteria as well as blossoming insecticidal efficacy. Moreover, Molecular docking and density functional theory simulations can be used to validate the experimental results. Also, we utilized the docking approach with secondary bacterial infection indicated that Ethoxy acetyl Spiro hydrazide (5) and Spiro arylidene hybrid (6) have exerted the strongest docking binding value against the active sites of 6LU7. [ABSTRACT FROM AUTHOR]

In food safety implementation, bacterial inactivation is an imperative aspect of hygiene and sanitation. Studies on lithium magnesium silicate (LMS) hydrosol incorporated with slightly acidic electrolyzed water (SAEW) for decontamination of pathogenic bacteria are limited. This present study aimed to investigate the bactericidal efficacy of LMS hydrosol incorporated with SAEW against Escherichia coli. Optimum combination conditions of SAEW, hydrosol concentration, and available chlorine concentration (ACC) were optimized by response surface methodology under the central composite design against the growth of E. coli. The optimum combination conditions of exposure time, hydrosol concentration, and ACC were 9.5 minutes, 1.7%, and 20.5 ppm, respectively. The results showed that the increase in ACC led to inactivation in the survival of E. coli compared with the control (p<0.05). It can be concluded that the best combination percentage between SAEW and hydrosol ranged from 1.5-1.7%, in which E. coli was reduced by 4.50 log10 CFU/mL at an ACC of 9.94 ppm. When increasing the ACC to 14.84 ppm, E. coli was reduced by 4.51 log10 CFU/mL compared with the initial number of bacteria (8.20 log10 CFU/mL) in the control group. The number of bacteria was undetected after increasing ACC to 19.93, 25.15, and 29.88 ppm at 10 min. This study suggests that LMS hydrosol incorporated with SAEW could potentially be used as an effective sanitizer. [ABSTRACT FROM AUTHOR]

Essential oils, consisting of volatile compounds, are derived from various plant parts and possess antibacterial and antioxidant properties. Certain essential oils are utilized for medicinal purposes and can serve as natural preservatives in food products, replacing synthetic ones. This review describes how essential oils can promote the performance of bioactive films and preserve food through their antioxidant and antibacterial properties. Further, this article emphasizes the antibacterial efficacy of essential oil composite films for food preservation and analyzes their manufacturing processes. These films could be an attractive delivery strategy for improving phenolic stability in foods and the shelf-life of consumable food items. Moreover, this article presents an overview of current knowledge of the extraction of essential oils, their effects on bioactive films and food preservation, as well as the benefits and drawbacks of using them to preserve food products. [ABSTRACT FROM AUTHOR]

This study investigated the effects of fermentation and germination on the physicochemical, nutritional, functional, and bioactive quality attributes of samh seeds. Regardless of the processing treatment, samh seeds were found to be a rich source of phenolic compounds, namely gallic acid (79.6–96.36 mg/100 g DW), catechol (56.34–77.34 mg/100 g DW), and catechin (49.15–84.93 mg/100 g DW), and they possessed high DPPH antiradical activity (65.27–78.39%). They also contained high protein content (19.29–20.41%), essential amino acids content (39.07–44.16% of total amino acids), and unsaturated fatty acid content (81.95–83.46% of total fatty acids) and a low glycemic index (39.61–41.43). Fermentation and germination increased L*, b*, foaming capacity, oil absorption capacity (OAC), water absorption capacity (WAC), swelling power, microbial counts, antioxidant activity, total flavonoid content (TFC), total phenolic content (TPC), in vitro protein digestibility, protein efficiency ratio, and total essential amino acids and reduced water solubility, emulsion stability, tannin, and phytate contents compared to raw samh seeds (p < 0.05). The highest levels of pH, ash, carbohydrate, fiber, and glycemic index were observed in raw samh seeds, and both germination and fermentation processes reduced these attributes to various degrees (p < 0.05). Germination increased the redness (a*), moisture content, essential and non-essential amino acids, potassium, zinc, phosphorous, stearic acid, and oleic and unsaturated fatty acids and reduced total solids, fat content, iron, zinc, calcium, magnesium, sodium, palmitic acid, and total saturated fatty acids of the samh seeds compared to the raw ones. Fermentation increased the total solid, acidity, fat, protein, calcium, magnesium, sodium, phosphorous, iron, zinc, palmitic acid, and total saturated fatty acids and reduced the a* value, moisture, non-essential amino acids, and total unsaturated fatty acids of the samh seeds compared to the raw ones. In conclusion, samh seeds are a rich source of nutrients that could generally be enhanced by germination and fermentation processes. The reported information facilitates strategies towards the application of these underutilized seeds in foods. [ABSTRACT FROM AUTHOR]

Background: Vancomycin is one of the main therapies for methicillin-resistant S. aureus (MRSA), however emergence of resistant strains is rising. Nanoparticles can offer promising solution. So, we studied the effect of gold nanoparticles (AuNPs) in enhancing vancomycin potential against MRSA clinical isolates from different types of infections. Methods: The susceptibility patterns of vancomycin, AuNPs, and vancomycin-conjugated gold nanoparticles (V-AuNPs) were evaluated on 30 MRSA isolates obtained from various clinical samples by using the microtiter broth dilution method. AuNPs and V-AuNPs were prepared by using a straightforward technique of microwave-assisted synthesis. Results: Twenty-seven (90%) MRSA isolates were susceptible to vancomycin and three (10%) showed intermediate susceptibility, with mean minimum inhibitory concentration (MIC) 2.68 ± 2.07 µg/ml, inhibitory concentration (conc.) to 50% of MRSA (IC50) 1.95 µg/ml and inhibitory conc. to 90% of the isolates (IC90) 3.9 µg/ml. While the synthesized AuNPs demonstrated a bactericidal effect on all the tested isolates with mean MIC 164.6 ± 62.5 µg/ml, IC50 125 µg/ml, and IC90 250 µg/ml. Meanwhile, V-AuNPs demonstrated synergistic bactericidal effect on all thirty (100%) tested MRSA isolates with mean MIC 0.40 ± 0.46 µg/ml, IC50 0.24 µg/ml, and IC 90 0.48 µg/ml. Moreover, V-AuNPs demonstrated minimal cytotoxic concentration up to 100 and 98.65 percent viability on human foreskin fibroblast (HFF-1) cell line at conc. of 2 µg/ml and 3.9 µg/ml respectively. Conclusions: The V-AuNPs display superior antibacterial activity as compared to vancomycin and AuNPs alone as a potentially effective therapy against MRSA. [ABSTRACT FROM AUTHOR]

This study evaluated the cholesterol-alleviating effect and underlying mechanisms of chitosan-oligosaccharide (COS) in hypercholesterolemic hamsters. Male hamsters (n = 24) were divided into three groups in a random fashion, and each group was fed one particular diet, namely a non-cholesterol diet (NCD), a high-cholesterol diet (HCD), and an HCD diet substituting 5% of the COS diet for six weeks. Subsequently, alterations in fecal bile acids (BAs), short-chain fatty acids (SCFAs), and gut microflora (GM) were investigated. COS intervention significantly reduced and increased the plasma total cholesterol (TC) and high-density lipoprotein-cholesterol (HDL-C) levels in hypercholesteremic hamsters. Furthermore, Non-HDL-C and total triacylglycerols (TG) levels were also reduced by COS supplementation. Additionally, COS could reduce and increase food intake and fecal SCFAs (acetate), respectively. Moreover, COS had beneficial effects on levels of BAs and GM related to cholesterol metabolism. This study provides novel evidence for the cholesterol-lowering activity of COS. [ABSTRACT FROM AUTHOR]

Background: Multidrug-resistant (MDR) Klebsiella pneumoniae (K. pneumoniae) causes life threatening infections. Pharmaceutical nanotechnology is anticipated to produce new therapeutic products for biomedical uses. One of these compounds, silver nanoparticles (AgNPs), is with promising antibacterial and anti-biofilm characteristics. Aim of the work: To evaluate the anti-microbial and anti-biofilm activities of AgNPs against MDR K. pneumoniae clinical isolates in Ain-Shams university hospitals. Methodology: The study was conducted on fifty MDR K. pneumoniae. The isolates were retrieved from Ain Shams university Microbiology laboratory. The biofilm-forming activity was tested by a microtiter plate based on crystal violet staining, the AgNPs were synthesized biologically and characterized by different methods. The antibacterial and antibiofilm activities of biosynthesized AgNPs were investigated against selected strains using standard methods. Results: The results revealed that all isolates were resistant to tested antibiotics and biofilmforming ability was detected in 28/50 (56%) isolates. The antibacterial activities of AgNPs showed that all isolates were susceptible to AgNPs with Minimal Inhibitory Concentration (MIC) ranging from 15.625 µg/ml to 125 µg/ml. Also, AgNPs significantly reduced the biofilm formation as 26/28 of isolates became non-biofilm producers (0) and 2/28 became weak. Silver nanoparticles showed minimal cytotoxic concentration (conc.) up to 100 percent and 99.42 percent viability on normal human lung fibroblast cells (MRC-5) cell lines treated with AgNPs at conc. of 2 µg/ml and 3.9 µg/ml respectively. Conclusion: Multi drug resistant K. pneumoniae is a rising problem and the rate of biofilm formation in these isolates is high. Silver nanoparticles exhibit good antibacterial and antibiofilm activity against them. [ABSTRACT FROM AUTHOR]

The interaction between epigallocatechin gallate (EGCG) and whey protein isolate (WPI) under various pH and ion concentrations conditions was examined by ultraviolet-visible spectrophotometer and fluorescence spectra. The results showed that EGCG with WPI was linked mainly by electrostatic force, and EGCG caused the fluorescence quenching of WPI through a static quenching. Furthermore, in vitro static release results showed that the release process of EGCG from EGCG-WPI gel in release medium of different pH and ion concentrations follows the Korsmeyer-Peppas model and conform to the non-Fick diffusion law. Finally, the binding constant KA and the constant release Kapp kinetic model were established. The model followed the equation LnKA=A - 1 n LnKapp. [ABSTRACT FROM AUTHOR]

The present work described a novel synthesis of spiro[indoline-3,3′-pyrazol]-2-one derivatives 2, 4, 5, and 7 via a one-pot reaction of chalcones or β-aroyl acrylic acid 1a–c, isatin, and hydrazine derivatives e.g. hydrazine hydrate, methyl hydrazine, phenylhydrazine or acetohydrazide in sonicated reaction condition. The unexpected product 1,3-oxazino[3,2-a]indol-10-yl-ethanone derivative 6 can be generated instead of N-acetyl spiro[indoline-3,3′-pyrazol]-2-one as desired. Also, the Spiropyrazole-fused furanone and pyridazinone ring can be made. Owing to their unique 3-dimensional structures, spirooxindoles have been found as lucky chemotypes for antiviral drug enhancement in an attempt to achieve these spiropyrazole derivatives 2–10 with hydrophobic groups. Furthermore, the density functional theory (DFT) was used to elucidate the electronic and structural features of spiropyrazole derivatives and their reactive species, which supports the proposed mechanism of antibacterial and antiviral capabilities. [ABSTRACT FROM AUTHOR]

Energy consumption reduction under changing climate conditions is a major challenge in buildings design, where excessive energy consumption creates an economic and environmental burden. Improving thermal performance of the buildings through support applying phase change material (PCM) is a promising strategy for reducing building energy consumption under future climate change. Therefore, this study aims to investigate the energy saving potentials in buildings under future climate conditions in the humid and snowy regions in the hot continental and humid subtropical climates of the east Asia (Seoul, Tokyo and Hong Kong) when various PCMs with different phase change temperatures are applied to a lightweight building envelope. Methodology in this work is implemented in two phases: firstly, investigation of energy saving potentials in buildings through inclusion of three types of PCMs with different phase temperatures into the building envelop separately and use weather file in the present (2017); and, secondly, evaluation of the effect of future climate change on the performance of PCMs by analyzing energy saving potentials of PCMs with 2020, 2050 and 2080 weather data. The results show that the inclusion of PCM into the building envelope is a promising strategy to increase the energy performance in buildings during both heating and cooling seasons in Seoul, Tokyo and Hong Kong under future climate conditions. The energy savings achieved by using PCMs in those regions are electricity savings of 4.48–8.21%, 3.81–9.69%, and 1.94–5.15%, and gas savings of 1.65–16.59%, 7.60–61.76%), and 62.07–93.33% in Seoul, Tokyo and Hong Kong, respectively, for the years 2017, 2020, 2050 and 2080. In addition, BioPCM and RUBITHERMPCM are the most efficient for improving thermal performance and saving energy in buildings in the tested regions and years.

Synthesis of ethyl acetate (EA) using lipase as a catalyst, as an environmentally-friendly process, has attracted considerable attention. However, the slow rate of enzymatic reaction and higher cost limit its applications. Ultrasound irradiation (UI) is known as an effective tool for accelerating the rate of enzymatic reaction under mild conditions. To attain maximum yield, it is crucial to understand the effect of UI on EA synthesis and the underlying mechanism. Therefore, the present study investigated the effect of UI on lipase-catalyzed ethyl acetate synthesis. The results clearly demonstrated that UI could remarkably accelerate the process of lipase-catalyzed synthesis of ethyl acetate compared with mechanical shaking. The optimal conditions of ultrasound-assisted reaction by using Novozyme 435® were 6% enzyme loading, 4:1 molar ratio of ethanol to acetic acid, 150 W & 28 kHz ultrasonic power and frequency, respectively. Bi-bi ping-pong model was employed to give a deep insight into the underlying mechanism of the beneficial effect of UI. It was found that Vmax under UI was elevated by 143% compared with that under mechanical shaking. Application of UI could decrease Kacetic acid and Ki ethanol while increase Kethanol and Ki acetic acid. In conclusion, the present study addresses that UI could remarkably accelerate the process of lipase-catalyzed synthesis of EA compared with mechanical shaking, and kinetic model results explained why ultrasound can significantly speed up lipase catalyzed synthesis of ethyl acetate, which may help to improve the industrial application potential of ethyl acetate biosynthesis. [ABSTRACT FROM AUTHOR]

This paper sets out on a comparative analysis of similar word-formation processes in English and Arabic. In doing so, it hopes to emerge and serve as subsequent and reliable, albeit partial, reference material for English and Arabic linguistics, especially in reference to linguistic structures. The framework herein for the study and analysis of word-formation processes in both languages may also be applied in future studies and other genres, corpora, and texts. This study enriches the research findings and meta-theory in the field of linguistics, contributing to the current linguistic intellectualism trends. The specific processes discussed are acronyms, antonomasia, backformation, blending, borrowing, compounding, and derivation. [ABSTRACT FROM AUTHOR]

The application of phase change materials (PCMs) in building envelopes can help promote energy efficiency due to its high heat capacity. Our study aimed to provide energy and economic insights for deploying PCM to buildings in eight different regions of East Asia through a series of energy and economic analysis using computer modelling and simulations. The static payback period (SPP) and dynamic payback (DPP) methods were used to evaluate the economic feasibility of applying a PCM at different melting phase temperatures (20°C, 23°C, 25°C, 27°C and 29°C). Results show that the proper choice of a PCM melting temperature is a key factor to improve the performance of the PCM applied to buildings. A melting phase temperature of 29°C achieved the highest economic feasibility in Seoul, Tokyo; Pyongyang; Beijing; and Ulaanbaatar and a melting temperature of 23°C in Hong Kong had the highest economic feasibility. Overall, the combined economic and energy analysis presented in this study can play an important role in improving the energy and economic feasibility of PCM in buildings. [ABSTRACT FROM AUTHOR]

Optimizing the building performance at the early design stage is justified as a promising approach to achieve many sustainable design goals in buildings; in particular, it opens a new era of attractive energy-efficient design for designers and architects to create new building constructions with high-energy efficiency and better overall performance. Accordingly, this study aims to provide a comprehensive review of performance optimization studies on heating, cooling, and lighting energy systems of buildings during the design stages, conducting a systematical review covering various aspects ranging from the building type, optimization inputs, the approach used, and the main conclusion. Furthermore, the benefits and limitations of early optimizations in the energy-efficient design performance of buildings and future research directions are identified and discussed. The review results show that previous research efforts of optimizing energy-efficient design performance in buildings have addressed a wide variety of early stage design optimization issues, including orientation and multi-objective building function-related conflicts, such as cooling and lighting. However, significant research issues related to investigations of design envelope materials, proper energy-efficient design form, and other passive parameters, such as solar photovoltaic systems, are still lacking. Therefore, future research should be directed towards improving existing optimization approach frameworks in the context of appropriate energy-efficient design features; integrating sensitivity and uncertainty analyses in the performance optimization framework of buildings to provide a more balanced assessment of influential design envelope properties and extending optimal design envelope investigations of buildings to include other passive parameters and lifecycle assessment under long-term weather conditions. [ABSTRACT FROM AUTHOR]

• The review focuses on energy prediction techniques for large-scale buildings. • Five types of energy demand determinants in large-scale buildings were analyzed. • The techniques are classified the black, white, and grey-box based approaches. • A variety of energy-related applications, including energy-mapping were analyzed. • The hybrid models are suitable for energy predictions in large-scale buildings. Building energy prediction techniques are the primary tool for moving towards sustainable built environments. Energy prediction models play irreplaceable roles in making energy policy and the development of the building sector. This paper presents a comprehensive review of the prevailing prediction techniques used in large-scale building energy applications under different scopes and different archetypes, including black-box, white-box, and grey-box based methods. Additionally, the advantages and disadvantages of the applications of those approaches are compared and discussed in the context of large-scale buildings. The review results show that prediction techniques have addressed a variety of large-scale building energy related-applications, such as energy consumption forecasting and prediction, energy consumption profiling, energy mapping and benchmarking of buildings. However, there are still some research gaps that require more attention such as the inclusion of occupant behavior in white-box based models and the explicit representation of end-uses in black-box based models. Significantly, this review concludes with a few key tasks for modification of the current prediction approach framework, which can help with forecasting future energy use changes of specific buildings during the retrofit process or inclusion of renewable energy technology. This would assist in developing an appropriate strategy for the sustainability of the built environment. [ABSTRACT FROM AUTHOR]

Improvement of the medical textile industry has received more attention recently, especially with widespread of microbial and viral infections. Medical textiles with new properties, such as bacterial pathogens self-cleaning, have been explored with nanotechnology. In this study, an endophytic actinomycetes strain of Streptomyces laurentii R-1 was isolated from the roots of the medicinal plant Achillea fragrantissima. This is used as a catalyst for the mediated biosynthesis of silver nanoparticles (Ag-NPs) for applications in the textile industry. The biosynthesized Ag-NPs were characterized using UV-vis spectroscopy, Fourier transform infrared (FT-IR), transmission electron microscopy (TEM), and X-ray Diffraction (XRD), which confirmed the successful formation of crystalline, spherical metal nanoparticles. The biosynthesized Ag-NPs exhibited broad-spectrum antibacterial activity. Our data elucidated that the biosynthesized Ag-NPs had a highly cytotoxic effect against the cancerous caco-2 cell line. The selected safe dose of Ag-NPs for loading on cotton fabrics was 100 ppm, regarding their antibacterial activity and safe cytotoxic efficacy. Interestingly, scanning electron microscope connected with energy dispersive X-ray spectroscopy (SEM-EDX) of loaded cotton fabrics demonstrated the smooth distribution of Ag-NPs on treated fabrics. The obtained results highlighted the broad-spectrum activity of nano-finished fabrics against pathogenic bacteria, even after 5 and 10 washing cycles. This study contributes a suitable guide for the performance of green synthesized NPs for utilization in different biotechnological sectors. [ABSTRACT FROM AUTHOR]