Search results for: available potential energy

Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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Authors: Wen Cai Ng, Saman Ilankoon, Meng Nan Chong

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The vast increase in global energy demand, coupled with the growing concerns on environmental issues, has triggered the search for cleaner alternative energy sources. In view of this, the photoelectrochemical (PEC) water splitting offers a sustainable hydrogen (H2) production route that only requires solar energy, water, and PEC system operating in an ambient environment. However, the current advancement of PEC water splitting technologies is still far from the commercialization benchmark indicated by the solar-to-H2 (STH) efficiency of at least 10 %. This is largely due to the shortcomings of photoelectrodes used in the PEC system, such as the rapid recombination of photogenerated charge carriers and limited photo-responsiveness in the visible-light spectrum. Silver orthophosphate (Ag3PO4) possesses many desirable intrinsic properties for the fabrication into photoanode used in PEC systems, such as narrow bandgap of 2.4 eV and low valence band (VB) position. Hence, in this study, a highly efficient Ag3PO4-based photoanode was synthesized and characterized. The surface of the Ag foil substrate was directly oxidized to fabricate a top layer composed of {111}-bound Ag3PO4 tetrahedrons layer with a porous structure, forming the dual-layer Ag/Ag3PO4 photoanode. Furthermore, the key synthesis parameters were systematically investigated by varying the concentration ratio of capping agent-to-precursor (R), the volume ratio of hydrogen peroxide (H2O2)-to-water, and reaction period. Results showed that the optimized dual-layer Ag/Ag3PO4 photoanode achieved a photocurrent density as high as 4.19 mA/cm2 at 1 V vs. Ag/AgCl for the R-value of 4, the volume ratio of H2O2-to-water of 3:5 and 20 h reaction period. The current work provides a solid foundation for further nanoarchitecture modification strategies on Ag3PO4-based photoanodes for more efficient PEC water splitting applications. This piece of information needs to be backed up by evidence; therefore, you need to provide a reference. As the abstract should be self-contained, all information requiring a reference should be removed. This is a fact known to the area of research, and not necessarily required a reference to support.

Keywords: solar-to-hydrogen fuel, photoelectrochemical water splitting, photoelectrode, silver orthophosphate

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Authors: Dilip Saikia, Suparna Bhattacharjee, Nirab Adhikary

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In this piece of work, we have presented the synthesis and characterization of CdTe/ZnS core/shell (CS) quantum dots (QD). CS QDs are used as a fluorescence probe to design a simple cost-effective and ultrasensitive sensor for the detection of toxic Hg(II) in an aqueous medium. Mercaptosuccinic acid (MSA) has been used as a capping agent for the synthesis CdTe/ZnS CS QD. Photoluminescence quenching mechanism has been used in the detection experiment of Hg(II). The designed sensing technique shows a remarkably low detection limit of about 1 picomolar (pM). Here, the CS QDs are synthesized by a simple one-pot aqueous method. The synthesized CS QDs are characterized by using advanced diagnostics tools such as UV-vis, Photoluminescence, XRD, FTIR, TEM and Zeta potential analysis. The interaction between CS QDs and the Hg(II) ions results in the quenching of photoluminescence (PL) intensity of QDs, via the mechanism of excited state electron transfer. The proposed mechanism is explained using cyclic voltammetry and zeta potential analysis. The designed sensor is found to be highly selective towards Hg (II) ions. The analysis of the real samples such as drinking water and tap water has been carried out and the CS QDs show remarkably good results. Using this simple sensing method we have designed a prototype low-cost electronic device for the detection of Hg(II) in an aqueous medium. The findings of the experimental results of the designed sensor is crosschecked by using AAS analysis.

Keywords: photoluminescence, quantum dots, quenching, sensor

Procedia PDF Downloads 254

Authors: Mohsun Rasim Alizada, Azar Inshalla Ahmdov

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Prompt photons are perhaps the most versatile tools for studying the dynamics of relativistic collisions of heavy ions. The study of photon radiation is of interest that in most hadron interactions, photons fly out as a background to other studied signals. The study of the birth of prompt photons in nucleon-nucleon collisions was previously carried out in experiments on Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). Due to the large energy of colliding nucleons, in addition to prompt photons, many different elementary particles are born. However, the birth of additional elementary particles makes it difficult to determine the accuracy of the effective section of the birth of prompt photons. From this point of view, the experiments planned on the Nuclotron-based Ion Collider Facility (NICA) complex will have a great advantage, since the energy obtained for colliding heavy ions will reduce the number of additionally born elementary particles. Of particular importance is the study of the processes of birth of prompt photons to determine the gluon leaving hadrons since the photon carries information about a rigid subprocess. At present, paper production of prompt photon in Compton scattering of quark-gluon and annihilation of quark–antiquark processes is investigated. The matrix elements Compton scattering of quark-gluon and annihilation of quark-antiquark pair processes has been written. The Square of matrix elements of processes has been calculated in FeynCalc. The phase volume of subprocesses has been determined. Expression to calculate the differential cross-section of subprocesses has been obtained: Given the resulting expressions for the square of the matrix element in the differential section expression, we see that the differential section depends not only on the energy of colliding protons, but also on the mass of quarks, etc. Differential cross-section of subprocesses is estimated. It is shown that the differential cross-section of subprocesses decreases with the increasing energy of colliding protons. Asymmetry coefficient with polarization of colliding protons is determined. The calculation showed that the squares of the matrix element of the Compton scattering process without and taking into account the polarization of colliding protons are identical. The asymmetry coefficient of this subprocess is zero, which is consistent with the literary data. It is known that in any single polarization processes with a photon, squares of matrix elements without taking into account and taking into account the polarization of the original particle must coincide, that is, the terms in the square of the matrix element with the degree of polarization are equal to zero. The coincidence of the squares of the matrix elements indicates that the parity of the system is preserved. The asymmetry coefficient of annihilation of quark–antiquark pair process linearly decreases from positive unit to negative unit with increasing the production of the polarization degrees of colliding protons. Thus, it was obtained that the differential cross-section of the subprocesses decreases with the increasing energy of colliding protons. The value of the asymmetry coefficient is maximal when the polarization of colliding protons is opposite and minimal when they are directed equally. Taking into account the polarization of only the initial quarks and gluons in Compton scattering does not contribute to the differential section of the subprocess.

Keywords: annihilation of a quark-antiquark pair, coefficient of asymmetry, Compton scattering, effective cross-section

Procedia PDF Downloads 137

Authors: Kevin A. Droguett, Edwin G. Pérez, Denis Fuentealba, Margarita E. Aliaga, Angélica M. Fierro

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Supramolecular chemistry is a field of growing interest. Moreover, studying the formation of host-guest complexes between macrocycles and dyes is highly attractive due to their potential applications. Examples of the above are drug delivery, catalytic process, and sensing, among others. There are different dyes of interest in the literature; one example is the quinolinone derivatives. Those molecules have good optical properties and chemical and thermal stability, making them suitable for developing fluorescent probes. Secondly, several macrocycles can be seen in the literature. One example is the cucurbiturils. This water-soluble macromolecule family has a hydrophobic cavity and two identical carbonyl portals. Additionally, the thermodynamic analysis of those supramolecular systems could help understand the affinity between the host and guest, their interaction, and the main stabilization energy of the complex. In this work, two 7-(diethylamino) quinoline-2 (1H)-one derivative (QD1-2) and their interaction with cucurbit[7]uril (CB[7]) were studied from an experimental and in-silico point of view. For the experimental section, the complexes showed a 1:1 stoichiometry by HRMS-ESI and isothermal titration calorimetry (ITC). The inclusion of the derivatives on the macrocycle lends to an upward shift in the fluorescence intensity, and the pKa value of QD1-2 exhibits almost no variation after the formation of the complex. The thermodynamics of the inclusion complexes was investigated using ITC; the results demonstrate a non-classical hydrophobic effect with a minimum contribution from the entropy term and a constant binding on the order of 106 for both ligands. Additionally, dynamic molecular studies were carried out during 300 ns in an explicit solvent at NTP conditions. Our finding shows that the complex remains stable during the simulation (RMSD ~1 Å), and hydrogen bonds contribute to the stabilization of the systems. Finally, thermodynamic parameters from MMPBSA calculations were obtained to generate new computational insights to compare with experimental results.

Keywords: host-guest complexes, molecular dynamics, quinolin-2(1H)-one derivatives dyes, thermodynamics

Procedia PDF Downloads 78

Authors: Tolga Arda Eraslan

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The quality of the indoor environment is significant to occupants’ health, comfort, and productivity, as Covid-19 spread throughout the world, people started spending most of their time indoors. Since buildings are getting bigger, mechanical ventilation systems are widely used where natural ventilation is insufficient. Four primary tasks of a ventilation system have been identified indoor air quality, comfort, contamination control, and energy performance. To fulfill such requirements, air diffusers, which are a part of the ventilation system, have begun to enter our lives in different airflow distribution systems. Detailed observations are needed to assure that such devices provide high levels of comfort effectiveness and energy efficiency. This study addresses these needs. The objective of this article is to observe air characterizations of different air diffusers at different angles and their effect on people by the thermal comfort model in CFD simulation and to validate the outputs with the help of data results based on a simulated office room. Office room created to provide validation; Equipped with many thermal sensors, including head height, tabletop, and foot level. In addition, CFD simulations were carried out by measuring the temperature and velocity of the air coming out of the supply diffuser. The results considering the flow interaction between diffusers and surroundings showed good visual illustration.

Keywords: computational fluid dynamics, fanger’s model, predicted mean vote, thermal comfort

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Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

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Authors: Ziba Khalili, Mohsen Sheikholeslami, Ladan Momayez

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Combining the photovoltaic/thermal (PVT) systems with a thermoelectric (TE) module can raise energy yields since the TE module boosts the system's energy conversion efficiency. In the current study, a PVT system integrated with a TE module was designed and simulated in ANSYS Fluent 19.2. A copper heat transfer tube (HTT) was employed for cooling the photovoltaic (PV) cells. Four different shapes of HTT cross-section, i.e., circular, square, elliptical, and triangular, with equal cross-section areas were investigated. Also, the influence of Cu-Al2O3/water hybrid nanofluid (0.024% volume concentration), fluid inlet velocity (uᵢ ), and amount of solar radiation (G), on the PV temperature (Tₚᵥ) and system performance were investigated. The ambient temperature (Tₐ), wind speed (u𝓌), and fluid inlet temperature (Tᵢ), were considered to be 25°C, 1 m/s, and 27°C, respectively. According to the obtained data, the triangular case had the greatest impact on reducing the compared to other cases. In the triangular case, examination of the effect of hybrid nanofluid showed that the use of hybrid nanofluid at 800 W/m2 led to a reduction of the TPV by 0.6% compared to water, at 0.19 m/s. Moreover, the thermal efficiency ( ) and the overall electrical efficiency (nₜ) of the system improved by 0.93% and 0.22%, respectively, at 0.19 m/s. In a triangular case where G and were 800 W/m2 and 19 m/s, respectively, the highest amount of, thermal power (Eₜ), and, were obtained as 72.76%, 130.84 W and 12.03%, respectively.

Keywords: electrical performance, photovoltaic/thermal, thermoelectric, hybrid nanofluid, thermal efficiency

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Authors: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: Violina R. Angelova, Radka V. Ivanova, Givko M. Todorov, Krasimir I. Ivanov

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A field study was conducted to evaluate the efficacy of Salvia sclarea L. for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The content of heavy metals in different parts of Salvia sclarea L. (roots, stems, leaves and inflorescences) was determined by ICP. The essential oil of the Salvia sclarea L. was obtained by steam distillation in laboratory conditions and was analyzed for heavy metals and its chemical composition was determined. Salvia sclarea L. is a plant which is tolerant to heavy metals and can be grown on contaminated soils. Based on the obtained results and using the most common criteria, Salvia sclarea L. can be classified as Pb hyperaccumulator and Cd and Zn accumulators, therefore, this plant has suitable potential for the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the Salvia sclarea L., as well as on the quality and quantity of the essential oil. For clary sage oil obtained from the processing of clary sage grown on highly contaminated soils, its key odour-determining ingredients meet the quality requirements of the European Pharmacopoeia and BS ISO 7609 regarding Bulgarian clary sage oil and/or have values that are close to the limits of these standards. The possibility of further industrial processing will make Salvia sclarea L. an economically interesting crop for farmers of phytoextraction technology.

Keywords: clary sage, heavy metals, phytoremediation, polluted soils

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Authors: Safak Isik, Ozalp Vayvay

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Strategic partnerships with suppliers play a vital role for the long-term value-based supply chain. This strategic collaboration keeps still being one of the top priority of many business organizations in order to create more additional value; benefiting mainly from supplier’s specialization, capacity and innovative power, securing supply and better managing costs and quality. However, many organizations encounter difficulties in initiating, developing and managing those partnerships and many attempts result in failures. One of the reasons for such failure is the incompatibility of members of this partnership or in other words wrong supplier selection which emphasize the significance of the selection process since it is the beginning stage. An effective selection process of strategic suppliers is critical to the success of the partnership. Although there are several research studies to select the suppliers in literature, only a few of them is related to strategic supplier selection for long-term partnership. The purpose of this study is to propose a conceptual model for the selection of strategic partnership suppliers. A two-stage approach has been used in proposed model incorporating first segmentation and second selection. In the first stage; considering the fact that not all suppliers are strategically equal and instead of a long list of potential suppliers, Kraljic’s purchasing portfolio matrix can be used for segmentation. This supplier segmentation is the process of categorizing suppliers based on a defined set of criteria in order to identify types of suppliers and determine potential suppliers for strategic partnership. In the second stage, from a pool of potential suppliers defined at first phase, a comprehensive evaluation and selection can be performed to finally define strategic suppliers considering various tangible and intangible criteria. Since a long-term relationship with strategic suppliers is anticipated, criteria should consider both current and future status of the supplier. Based on an extensive literature review; strategical, operational and organizational criteria have been determined and elaborated. The result of the selection can also be used to determine suppliers who are not ready for a partnership but to be developed for strategic partnership. Since the model is based on multiple criteria for both stages, it provides a framework for further utilization of Multi-Criteria Decision Making (MCDM) techniques. The model may also be applied to a wide range of industries and involve managerial features in business organizations.

Keywords: Kraljic’s matrix, purchasing portfolio, strategic supplier selection, supplier collaboration, supplier partnership, supplier segmentation

Procedia PDF Downloads 230

Authors: Akbar Esmaeili, Mahnoosh Aliahmadi

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This study synthesized a modified imaging of gallium@deferoxamine/folic acid/chitosan/polyaniline/polyvinyl alcohol (Ga@DFA/FA/CS/PANI/PVA). It contains Morus nigra extract by selenium nanoparticles prepared from Lactobacillus acidophilus. Using the impregnation method, Se nanoparticles were then deposited on (Ga@DFA/FA/ CS/PANI/PVA). The modified contrast agents were mixed with M. nigra extract, and investigated their antibacterial activities by applying to L929 cell lines. The influence of variable factors, including 1. surfactant, 2. solvent, 3. aqueous phase, 4. pH, 5. buffer, 6. minimum Inhibitory concentration (MIC), 7. minimum bactericidal concentration (MBC), 8. cytotoxicity on cancer cells., 9. antibiotic, 10. antibiogram, 11. release and loading, 12. the emotional effect, 13. the concentration of nanoparticles, 14. olive oil, and 15. they have investigated thermotical methods. The structure and morphology of the synthesized contrast agents were characterized by zeta potential sizer analysis (ZPS), X-Ray diffraction (XRD), Fourier-transform infrared (FT-IR), energy dispersive X-ray (EDX), ultraviolet–visible (UV–Vis) spectra, and scanning electron microscope (SEM). The experimental section was conducted and monitored by response surface methods (RSM), MTT, MIC, MBC, and cancer cytotoxic conversion assay. Antibiogram testing of NCs on Pseudomonas aeruginosa bacteria was successful and obtained MIC = 2 factors with less harmful effect. All experimental sections confirmed that our synthesized particles have potent antioxidant properties. Antibiogram testing revealed that NPS could kill P. aeruginosa and P. aeruginosa. A variety of synthetic conditions were done by diffusion emulsion method by varying parameters, the optimum state of DFA release Ga@DFA/FA/CS/PANI/PVA NPs (6 ml) with pH = 5.5, time = 3 h, NCs and DFA (3 mg), and achieved buffer (20 ml). DFA in Ga@DFA/FA/ CS/PANI/PVA was released and showed an absorption peak at 378 nm by applying a 300-rpm magnetic rate. In this report, Ga decreased the harmful effect on the human body.

Keywords: nanocapsules, technolgy, biology, nano

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Authors: Ashit Syngle, Inderjit Verma, Pawan Krishan

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Aim: Endothelial progenitor cells (EPCs) are unique populations which have reparative potential in overcoming the endothelial damage and reducing cardiovascular risk. Patients with ankylosing spondylitis (AS) have increased risk of cardiovascular morbidity and mortality. The aim of this study was to investigate the endothelial progenitor cell population in AS patients and its potential relationships with disease variables. Methods: Endothelial progenitor cells were measured in peripheral blood samples from 20 AS and 20 healthy controls by flow cytometry on the basis of CD34 and CD133 expression. Disease activity was evaluated by using Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). Functional ability was monitored by using Bath Ankylosing Spondylitis Functional Index (BASFI). Results: EPCs were depleted in AS patients as compared to the healthy controls (CD34+/CD133+: 0.027 ± 0.010 % vs. 0.044 ± 0.011 %, p<0.001). EPCs depletion were significantly associated with disease duration (r=-0.52, p=0.01) and BASDAI (r=-0.45, p=0.04). Conclusion: This is the first study to demonstrate endothelial progenitor cells depletion in AS patients. EPCs depletion inversely correlates with disease duration and disease activity, suggesting the pivotal role of inflammation in depletion of EPCs. EPC would possibly also serve as a therapeutic target for preventing cardiovascular disease in AS.

Keywords: ankylosing spondylitis, endothelial progenitor cells, inflammation, vascular damage

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Authors: Jeonghun Lee

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Thyroid-stimulating hormone (TSH) is regulated by the negative feedback of T3 and T4 but is affected by cortisol and cytokines during allostasis. Hence, TSH levels can be influenced by stress through cortisol. In the present study, changes in TSH levels under stress and the potential of TSH as a stress marker were examined in patients lacking T3 or T4 feedback after thyroid surgery. The three stress questionnaires (Korean version of the Daily Stress Inventory, Social Readjustment Rating Scale, and Stress Overload Scale-Short [SOSS]), open-ended question (OQ), and thyroid function tests were performed twice in 106 patients enrolled from January 2019 to October 2020. Statistical analysis was performed using the generalized linear mixed effect model (GLMM) in R software version 4.1.0. In a multiple LMM involving 106 patients, T3, T4, SOSS (category), open-ended questions, the extent of thyroidectomy, and preoperative TSH were significantly correlated with lnTSH. T3 and T4 increased by 1 and lnTSH decreased by 0.03, 3.52, respectively. In case of a stressful event on OQ, lnTSH increased by 1.55. In the high-risk group, lnTSH increased by 0.79, compared with the low group (p<0.05). TSH had a significant relationship with stress, together with T3, T4, and the extent of thyroidectomy. As such, it has the potential to be used as a stress marker, though it showed a low correlation with other stress questionnaires. To address this limitation, questionnaires on various social environments and research on copy strategies are necessary for future studies.

Keywords: stress, surgery, thyroid stimulating hormone, thyroidectomy

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Authors: Ali Mohammed Ali Lmbash

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The global refugee crisis points to the vital need for sustainable and resistant solutions to different kinds of problems for displaced persons all over the world. Among the myriads of sustainable concerns, however, there are diverse considerations including energy consumption, waste management, water access, and resiliency of structures. Our research aims to develop distinct ideas for sustainable architecture given the exigent problems in disaster-threatened areas starting with the Hatay Refugee camp in Turkey where the majority of the camp dwellers are Syrian refugees. Commencing community-based participatory research which focuses on the socio-environmental issues of displaced populations, this study will apply two approaches with a specific focus on the Hatay region. The initial experiment uses Richter's predictive model and simulations to forecast earthquake outcomes in refugee campers. The result could be useful in implementing architectural design tactics that enhance structural reliability and ensure the security and safety of shelters through earthquakes. In the second experiment a model is generated which helps us in predicting the quality of the existing water sources and since we understand how greatly water is vital for the well-being of humans, we do it. This research aims to enable camp administrators to employ forward-looking practices while managing water resources and thus minimizing health risks as well as building resilience of the refugees in the Hatay area. On the other side, this research assesses other sustainability problems of Hatay Refugee Camp as well. As energy consumption becomes the major issue, housing developers are required to consider energy-efficient designs as well as feasible integration of renewable energy technologies to minimize the environmental impact and improve the long-term sustainability of housing projects. Waste management is given special attention in this case by imposing recycling initiatives and waste reduction measures to reduce the pace of environmental degradation in the camp's land area. As well, study gives an insight into the social and economic reality of the camp, investigating the contribution of initiatives such as urban agriculture or vocational training to the enhancement of livelihood and community empowerment. In a similar fashion, this study combines the latest research with practical experience in order to contribute to the continuing discussion on sustainable architecture during disaster relief, providing recommendations and info that can be adapted on every scale worldwide. Through collaborative efforts and a dedicated sustainability approach, we can jointly get to the root of the cause and work towards a far more robust and equitable society.

Keywords: smart architecture, Hatay Camp, sustainability, machine learning.

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Authors: Nokwethaba Makhanya, Babatunde J. Abiodun, Piotr Wolski

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Climate change possibly intensifies hydrological droughts and reduces water availability in river basins. Despite this, most research on climate change effects in southern Africa has focused exclusively on meteorological droughts. This thesis projects the potential impact of climate change on the future characteristics of hydrological droughts in the Limpopo River Basin (LRB). The study uses regional climate model (RCM) measurements (from the Coordinated Regional Climate Downscaling Experiment, CORDEX) and a combination of hydrological simulations (using the Soil and Water Assessment Tool Plus model, SWAT+) to predict the impacts at four global warming levels (GWLs: 1.5℃, 2.0℃, 2.5℃, and 3.0℃) under the RCP8.5 future climate scenario. The SWAT+ model was calibrated and validated with a streamflow dataset observed over the basin, and the sensitivity of model parameters was investigated. The performance of the SWAT+LRB model was verified using the Nash-Sutcliffe efficiency (NSE), Percent Bias (PBIAS), Root Mean Square Error (RMSE), and coefficient of determination (R²). The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) have been used to detect meteorological droughts. The Soil Water Index (SSI) has been used to define agricultural drought, while the Water Yield Drought Index (WYLDI), the Surface Run-off Index (SRI), and the Streamflow Index (SFI) have been used to characterise hydrological drought. The performance of the SWAT+ model simulations over LRB is sensitive to the parameters CN2 (initial SCS runoff curve number for moisture condition II) and ESCO (soil evaporation compensation factor). The best simulation generally performed better during the calibration period than the validation period. In calibration and validation periods, NSE is ≤ 0.8, while PBIAS is ≥ ﹣80.3%, RMSE ≥ 11.2 m³/s, and R² ≤ 0.9. The simulations project a future increase in temperature and potential evapotranspiration over the basin, but they do not project a significant future trend in precipitation and hydrological variables. However, the spatial distribution of precipitation reveals a projected increase in precipitation in the southern part of the basin and a decline in the northern part of the basin, with the region of reduced precipitation projected to increase with GWLs. A decrease in all hydrological variables is projected over most parts of the basin, especially over the eastern part of the basin. The simulations predict meteorological droughts (i.e., SPEI and SPI), agricultural droughts (i.e., SSI), and hydrological droughts (i.e., WYLDI, SRI) would become more intense and severe across the basin. SPEI-drought has a greater magnitude of increase than SPI-drought, and agricultural and hydrological droughts have a magnitude of increase between the two. As a result, this research suggests that future hydrological droughts over the LRB could be more severe than the SPI-drought projection predicts but less severe than the SPEI-drought projection. This research can be used to mitigate the effects of potential climate change on basin hydrological drought.

Keywords: climate change, CORDEX, drought, hydrological modelling, Limpopo River Basin

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Authors: Rubén Bãnos, José Arcos, Oscar Bautista, Federico Méndez

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The Oscillatory electroosmotic flow (OEOF) in power law fluids through a microchannel is studied numerically. A time-dependent external electric field (AC) is suddenly imposed at the ends of the microchannel which induces the fluid motion. The continuity and momentum equations in the x and y direction for the flow field were simplified in the limit of the lubrication approximation theory (LAT), and then solved using a numerical scheme. The solution of the electric potential is based on the Debye-H¨uckel approximation which suggest that the surface potential is small,say, smaller than 0.025V and for a symmetric (z : z) electrolyte. Our results suggest that the velocity profiles across the channel-width are controlled by the following dimensionless parameters: the angular Reynolds number, Reω, the electrokinetic parameter, ¯κ, defined as the ratio of the characteristic length scale to the Debye length, the parameter λ which represents the ratio of the Helmholtz-Smoluchowski velocity to the characteristic length scale and the flow behavior index, n. Also, the results reveal that the velocity profiles become more and more non-uniform across the channel-width as the Reω and ¯κ are increased, so oscillatory OEOF can be really useful in micro-fluidic devices such as micro-mixers.

Keywords: low zeta potentials, non-newtonian, oscillatory electroosmotic flow, power-law model

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Authors: Ganesh Meshram, Gloria Biswal

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In this study, we present the numerical investigation of surface wettability on triangular micropillar surfaces by using a two-dimensional (2D) pseudo-potential multiphase lattice Boltzmann method with a D2Q9 model for various interaction parameters of the range varies from -1.40 to -2.50. Initially, simulation of the equilibrium state of a water droplet on a flat surface is considered for various interaction parameters to examine the accuracy of the present numerical model. We then imposed the microscale pillars on the bottom wall of the surface with different heights of the pillars to form the hydrophobic and superhydrophobic surfaces which enable the higher contact angle. The wettability of surfaces is simulated with water droplets of radius 100 lattice units in the domain of 800x800 lattice units. The present study shows that increasing the interaction parameter of the pillared hydrophobic surfaces dramatically reduces the contact area between water droplets and solid walls due to the momentum redirection phenomenon. Contact angles for different values of interaction strength have been validated qualitatively with the analytical results.

Keywords: contact angle, lattice boltzmann method, d2q9 model, pseudo-potential multiphase method, hydrophobic surfaces, wenzel state, cassie-baxter state, wettability

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Authors: K. Sushma Varma, Rajesh Singh

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Non-engineered landfills cause serious environmental damage due to toxic emissions and mobilization of persistent pollutants, organic and inorganic contaminants, as well as soluble metal ions. The available treatment technologies for landfill leachate and solid waste are not effective from an economic, environmental, and social standpoint. The present study assesses the potential of the bioelectrochemical system (BES) integrated with sulfate-reducing bacteria (SRB) in the sustainable treatment and decontamination of landfill wastes. For this purpose, solid waste and landfill leachate collected from different landfill sites were evaluated for long-term treatment using the integrated SRB-BES anaerobic designed bioreactors after pre-treatment. Based on periodic gas composition analysis, physicochemical characterization of the leachate and solid waste, and metal concentration determination, the present system demonstrated significant improvement in volumetric hydrogen production by suppressing methanogenesis. High reduction percentages of Be, Cr, Pb, Cd, Sb, Ni, Cr, COD, and sTOC removal were observed. This mineralization can be attributed to the synergistic effect of ammonia-assisted pre-treatment complexation and microbial sulphide formation. Despite being amended with 0.1N ammonia, the treated leachate level of NO³⁻ was found to be reduced along with SO₄²⁻. This integrated SRB-BES system can be recommended as an eco-friendly solution for landfill reclamation. The BES-treated solid waste was evidently more stabilized, as shown by a five-fold increase in surface area, and potentially useful for leachate immobilization and bio-fortification of agricultural fields. The vector arrangement and magnitude showed similar treatment with differences in magnitudes for both leachate and solid waste. These findings support the efficacy of SRB-BES in the treatment of landfill leachate and solid waste sustainably, inching a step closer to our sustainable development goals. It utilizes low-cost treatment, and anaerobic SRB adapted to landfill sites. This technology may prove to be a sustainable treatment strategy upon scaling up as its outcomes are two-pronged: landfill waste treatment and energy recovery.

Keywords: bio-electrochemical system, leachate /solid waste treatment, landfill leachate, sulfate-reducing bacteria

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Authors: Fayssal Ynineb, Toufik Hadjersi, Fatsah Moulai, Wafa Achour

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Currently, tremendous attention has been paid to the rational design and synthesis of core/shell heterostructures for high-performance supercapacitors. In this study, the hierarchical NiO/ZnCo₂O₄ Core-Shell Nanorods Arrays were successfully deposited onto ITO substrate via a two-step hydrothermal and electrodeposition methods. The effect of the thin carbon layer between NiO and ZnCo₂O₄ in this multi-scale hierarchical structure was investigated. The selection of this structure was based on: (i) a high specific area of pseudo-capacitive NiO to maximize specific capacitance; (ii) an effective NiO-electrolyte interface to facilitate fast charging/discharging; and (iii) conducting carbon layer between ZnCo₂O₄ and NiO enhance the electric conductivity which reduces energy loss, and the corrosion protection of ZnCo₂O₄ in alkaline electrolyte. The obtained results indicate that hierarchical NiO/ZnCo₂O₄ present a high specific capacitance of 63 mF.cm⁻² at a current density of 0.05 mA.cm⁻² higher than that of pristine NiO and ZnCo₂O₄ of 6 and 3 mF.cm⁻², respectively. The carbon layer improves the electrical conductivity among NiO and ZnCo₂O₄ in the hierarchical NiO/C/ZnCo₂O₄ electrode. As well, the specific capacitance drastically increased to reach 125 mF.cm⁻². Moreover, this multi-scale hierarchical structure exhibits superior cycling stability with ~ 95.7 % capacitance retention after 65k cycles. These results indicate that the NiO/C/ZnCo₂O₄ nanocomposite material is an outstanding electrode material for supercapacitors.

Keywords: NiO/C/ZnCo₂O₄, specific capacitance, hydrothermal, supercapacitors

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Authors: Vikas Sharma, V. K. Dixit

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Anacyclus pyrethrum (A. pyrethrum) has been used as Vajikaran Rasayana (aphrodisiac) in traditional Indian ayurvedic medicine to treat male sexual dysfunction, including infertility. Aphrodisiac activity may be due to an increase in the production or effect of androgens, so this study sought to evaluate the androgenic and spermatogenic potential of the alkylamide-rich ethanol solution extract. Male Wistar strain rats weighing between 150 and 180 g were completely randomized divided into five groups. The ethanol solution extract of A. pyrethrum was administered to groups of rats in 50, 100, and 150 mg/kg doses for a period of 28 days, and the action was compared with control and testosterone-treated rats. Thirteen N-alkylamides were detected in the extract by using HPLC/UV/electrospray ionization mass spectrometry method. Extract administration at all the doses produced significant increase in body weight, sperm count, motility, and viability along with serum testosterone, luteinizing hormone, and follicle-stimulating hormone concentrations. Histoarchitecture of testis revealed increased spermatogenic activities. Seminal fructose content was also significantly increased after 28 days of treatment. Our results suggest that the ethanol solution extract of the roots of A. pyrethrum has androgenic potential and may improve male fertility by enhancing spermatogenesis.

Keywords: N-alkylamides, testosterone, Anacyclus pyrethrum, androgen

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: G. Nyongombe, Guy L. Kabongo, B. M. Mothudi, M. S. Dhlamini

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A series of Transition Metals Oxides (TMOs) doped graphene were synthesized and successfully used as supercapacitor electrode materials. The as-synthesized materials exhibited exceptional electrochemical properties owing to the combined properties of its constituents; high surface area and good conductivity were achieved. Several analytical characterization techniques were employed to investigate the morphology, crystal structure atomic arrangement and elemental chemical state in the materials for which scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were conducted, respectively. Moreover, the electrochemical properties of the as-synthesized materials were examined by performing cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS) measurements. Furthermore, the effect of doping concentration on the interlayer distance of the graphene materials and the charge transfer resistance are investigated and correlated to the exceptional current density which was multiplied by a factor of ~80 after TMOs doping in graphene. Finally, the resulting high capacitance obtained confirms the contribution of grapheme exceptional electronic conductivity and large surface area on the electrode materials. Such good-performing electrode materials are highly promising for supercapacitors and other energy storage devices.

Keywords: energy density, graphene, supercapacitors, TMOs

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Authors: M. Ali Mandegari, S. Farzad, , J. F. Görgens

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Sugar is one of the main agricultural industries in South Africa and approximately livelihoods of one million South Africans are indirectly dependent on sugar industry which is economically struggling with some problems and should re-invent in order to ensure a long-term sustainability. Second generation biorefinery is defined as a process to use waste fibrous for the production of biofuel, chemicals animal food, and electricity. Bioethanol is by far the most widely used biofuel for transportation worldwide and many challenges in front of bioethanol production were solved. Biorefinery annexed to the existing sugar mill for production of bioethanol and electricity is proposed to sugar industry and is addressed in this study. Since flowsheet development is the key element of the bioethanol process, in this work, a biorefinery (bioethanol and electricity production) annexed to a typical South African sugar mill considering 65ton/h dry sugarcane bagasse and tops/trash as feedstock was simulated. Aspen PlusTM V8.6 was applied as simulator and realistic simulation development approach was followed to reflect the practical behaviour of the plant. Latest results of other researches considering pretreatment, hydrolysis, fermentation, enzyme production, bioethanol production and other supplementary units such as evaporation, water treatment, boiler, and steam/electricity generation units were adopted to establish a comprehensive biorefinery simulation. Steam explosion with SO2 was selected for pretreatment due to minimum inhibitor production and simultaneous saccharification and fermentation (SSF) configuration was adopted for enzymatic hydrolysis and fermentation of cellulose and hydrolyze. Bioethanol purification was simulated by two distillation columns with side stream and fuel grade bioethanol (99.5%) was achieved using molecular sieve in order to minimize the capital and operating costs. Also boiler and steam/power generation were completed using industrial design data. Results indicates that the annexed biorefinery can be self-energy sufficient when 35% of feedstock (tops/trash) bypass the biorefinery process and directly be loaded to the boiler to produce sufficient steam and power for sugar mill and biorefinery plant.

Keywords: biorefinery, self-energy sufficiency, tops/trash, bioethanol, electricity

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Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

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Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L. were in-silico screened using molecular docking and pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect on the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer's therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interaction stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries toward the rational development of potent anti-Alzheimer agents.

Keywords: Alzheimer’s disease, molecular docking, Cannabis sativa L., cholinesterase inhibitors, molecular dynamics, ADMET, MM-PBSA

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Authors: Amira Abdelrasoul, Huu Doan, Ali Lohi

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The goal of the present study was to minimize the ultrafiltration fouling of latex effluent using Cetyltrimethyl ammonium bromide (CTAB) as a cationic surfactant. Hydrophilic Polysulfone and Ultrafilic flat heterogeneous membranes, with MWCO of 60,000 and 100,000, respectively, as well as hydrophobic Polyvinylidene Difluoride with MWCO of 100,000, were used under a constant flow rate and cross-flow mode in ultrafiltration of latex solution. In addition, a Polycarbonate flat membrane with uniform pore size of 0.05 µm was also used. The effect of CTAB on the latex particle size distribution was investigated at different concentrations, various treatment times, and diverse agitation duration. The effects of CTAB on the zeta potential of latex particles and membrane surfaces were also investigated. The results obtained indicated that the particle size distribution of treated latex effluent showed noticeable shifts in the peaks toward a larger size range due to the aggregation of particles. As a consequence, the mass of fouling contributing to pore blocking and the irreversible fouling were significantly reduced. The optimum results occurred with the addition of CTAB at the critical micelle concentration of 0.36 g/L for 10 minutes with minimal agitation. Higher stirring rate had a negative effect on membrane fouling minimization.

Keywords: cationic surfactant, latex particles, membrane fouling, ultrafiltration, zeta potential

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Authors: Rajneesh, Priyanka Singh

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Biomass resources have been one of the main energy sources for mankind since the dawn of civilization. There is a vast scope to convert these energy sources into biogas which is a clean, low carbon technology for efficient management and conversion of fermentable organic wastes into a cheap and versatile fuel and bio/organic manure. Thus, in order to enhance the performance of anaerobic digester, an optimizing analysis of resultant parameters (organic dry matter (oDM) content, methane percentage, and biogas yield) has been done for a plug flow anaerobic digester having mesophilic conditions (20-40°C) with the wet fermentation process. Based on the analysis, correlations for oDM, methane percentage, and biogas yield are derived using multiple regression analysis. A statistical model is developed to correlate the operating variables using the design of experiment approach by selecting central composite design (CCD) of a response surface methodology. Results shown in the paper indicates that as the operating temperature increases the efficiency of digester gets improved provided that the pH and hydraulic retention time (HRT) remains constant. Working in an optimized range of carbon-nitrogen ratio for the plug flow digester, the output parameters show a positive change with the variation of dry matter content (DM).

Keywords: biogas, digester efficiency, design of experiment, plug flow digester

Procedia PDF Downloads 363