Search results for: protein stability prediction

Authors: Ahmed Atwa, Ashraf Hafez, Mohamed Abdelhameed, Adel Nabeeh, Mohamed Dawaba, Tamer Helmy

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Introduction and Objective: Tumour staging and grading do not usually reflect the future behavior of Wilms' tumor (WT) regarding mortality. Therefore, in this study, P53, Ki67 and cyclin A immunohistochemistry were used in a trial to predict WT cancer-specific survival (CSS). Methods: In this nonconcurrent cohort study, patients' archived data, including age at presentation, gender, history, clinical examination and radiological investigations, were retrieved then the patients were reviewed at the outpatient clinic of a tertiary care center by history-taking, clinical examination and radiological investigations to detect the oncological outcome. Cases that received preoperative chemotherapy or died due to causes other than WT were excluded. Formalin-fixed, paraffin-embedded specimens obtained from the previously preserved blocks at the pathology laboratory were taken on positively charged slides for IHC with p53, Ki67 and cyclin A. All specimens were examined by an experienced histopathologist devoted to the urological practice and blinded to the patient's clinical findings. P53 and cyclin A staining were scored as 0 (no nuclear staining),1 (<10% nuclear staining), 2 (10-50% nuclear staining) and 3 (>50% nuclear staining). Ki67 proliferation index (PI) was graded as low, borderline and high. Results: Of the 75 cases, 40 (53.3%) were males and 35 (46.7%) were females, and the median age was 36 months (2-216). With a mean follow-up of 78.6±31 months, cancer-specific mortality (CSM) occurred in 15 (20%) and 11 (14.7%) patients, respectively. Kaplan-Meier curve was used for survival analysis, and groups were compared using the Log-rank test. Multivariate logistic regression and Cox regression were not used because only one variable (cyclin A) had shown statistical significance (P=.02), whereas the other significant factor (residual tumor) had few cases. Conclusions: Cyclin A IHC should be considered as a marker for the prediction of WT CSS. Prospective studies with a larger sample size are needed.

Keywords: wilms’ tumour, nephroblastoma, urology, survival

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: G. R. Khan, Sadia Mahjabin, A. S. Mollah, M. R. Mawla

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Atmospheric dispersion modeling is significant for any nuclear facilities in the country to predict the impact of radiological doses on environment as well as human health. That is why to ensure safety of workers and population at plant site; Atmospheric dispersion modeling and radiation dose calculations were carried out for a hypothetical accidental release of airborne radionuclide from the 3 MW TRIGA research reactor of Savar, Bangladesh. It is designed with reactor core which consists of 100 fuel elements(1.82245 cm in diameter and 38.1 cm in length), arranged in an annular corefor steady-state and square wave power level of 3 MW (thermal) and for pulsing with maximum power level of 860MWth.The fuel is in the form of a uniform mixture of 20% uranium and 80% zirconium hydride. Total effective doses (TEDs) to the public at various downwind distances were evaluated with a health physics computer code “HotSpot” developed by Lawrence Livermore National Laboratory, USA. The doses were estimated at different Pasquill stability classes (categories A-F) with site-specific averaged meteorological conditions. The meteorological data, such as, average wind speed, frequency distribution of wind direction, etc. have also been analyzed based on the data collected near the reactor site. The results of effective doses obtained remain within the recommended maximum effective dose.

Keywords: accidental release, dispersion modeling, total effective dose, TRIGA

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Authors: P. Saha, R. Ganguly, N. K .Singha, A. Pich

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Microgel, a smart class of material, has drawn attention in the past few years due to its response to external stimuli like temperature, pH, and ionic strength of the solution. Among them, one type of polymer becomes soluble, and the other becomes insoluble in water upon heating displaying upper critical solution temperature (UCST) (e.g., polysulfobetaine, PSB) and lower critical solution temperature (LCST) (e.g., poly(N-vinylcaprolactam, PVCL)) respectively. Polyzwitterions, electrically neutral polymers are biocompatible, biodegradable, and non-cytotoxic in nature, and presence of zwitterionic pendant group in the main backbone makes them stable against temperature and pH variations and strong hydration capability in salt solution promotes them to be used as interfacial bio-adhesion resistance material. Majority of zwitterionic microgels have been synthesized in mini- emulsion technique using free radical polymerization approach. Here, a new route to synthesize dual thermo-responsive PVCL microgels decorated with appreciable amount of zwitterionic PSB chains was developed by a purely water-based surfactant-free reversible addition–fragmentation chain transfer (RAFT) precipitation polymerization. PSB macro-RAFTs having different molecular weights were synthesized and utilized for surface-grafting with PVCL microgels varying the macro-RAFT concentration using N,N′-methylenebis(acrylamide) (BIS) as cross-linker. Increasing the PSB concentration in the PVCL microgels resulted in a linear increase in UCST but decrease in hydrodynamic radius due to strong intrachain coulombic attraction forces acting between the opposite charges present in the zwitterionic groups. Anti- fouling effect was observed on addition of BSA protein solution on the microgel-coated membrane surfaces as studied by fluorescence spectrophotoscopy.

Keywords: microgels, polyzwitterions, upper critical solution temperature-lower critical solution temperature, UCST-LCST, ionic crosslinking

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Authors: Juan Antonio Mondragon Sanchez, Ruben Santamaria

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The DNA G-quadruplex is a four-stranded DNA structure conformed by stacked planes of four base paired guanines (G-quartet). The guanine rich DNA sequences are present in many sites of genomic DNA and can potentially lead to the formation of G-quadruplexes, especially at the 3'-terminus of the human telomeric DNA with many TTAGGG repeats. The formation and stabilization of a G-quadruplex by small ligands at the telomeric region can inhibit the telomerase activity. In turn, the ligands can be used to regulate oncogene expression making the G-quadruplex an attractive target for anticancer therapy. Clearly, the G-quadruplex structured in the telomeric DNA is of fundamental importance for rational drug design. In this context, we investigate two G-quadruplex structures, the first follows from the sequence TTAGGG(TTAGGG)3TT (HUT1), and the second from AAAGGG(TTAGGG)3AA (HUT2), both in a K+ solution. We determine the free energy surfaces of the HUT1 and HUT2 structures and investigate their conformations using replica-exchange metadynamics simulations. The carbonyl-carbonyl distances belonging to different guanines residues are selected as the main collective variables to determine the free energy surfaces. The surfaces exhibit two main local minima, compatible with experiments on the conformational transformations of HUT1 and HUT2 under substitution of the K+ ions by the Na+ ions. The conformational transitions are not observed in short MD simulations without the use of the metadynamics approach. The results of this work should be of help to understand the formation and stability of human telomeric G-quadruplex in environments including the presence of K+ and Na+ ions.

Keywords: g-quadruplex, metadynamics, molecular dynamics, replica-exchange

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Authors: A. Pattulee, I. Lawan, N. Boonnao, R. Gholami, P. Rimdusit, S. Rimdusit

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Varied types and content of ultrafine vulcanized powdered natural rubbers (UFPNR) as toughening fillers of polybenzoxazine composite are investigated in this work. Four types of UFPNR were prepared by graft polymerization of acrylonitrile monomer (AN), styrene monomer (ST), styrene-acrylonitrile copolymer (ST/AN), and styrene-methyl methacrylate copolymer (ST/MMA) onto deproteinized natural rubber (DPNR). The solid UFPNR powders with different types of grafting were finally obtained by electron beam vulcanization and a spray-drying technique. Additionally, effects of various UFPNR contents (0, 5, 10, 15, 20, and 25 wt%) on toughness of polybenzoxazine composites were studied. It was observed that the UFPNR grafted with the styrene-methyl methacrylate copolymer (UFPNR-g-(PS-co-PMMA)) exhibited the most effective toughening agent for polybenzoxazine, whereas the rubber powder content of 25 wt% was found to be the optimal filler loading in enhancing the toughness of the resulting composite. The experimental results revealed an increase of 86% in toughness and 56% in impact strength at the above UFPNR-g- (PS-co-PMMA powdered rubber content. Interestingly, the utilization of the UFPNR-g-(PS-co-PMMA as toughening agent was found to increase thermal stability (degradation temperature at 5wt.% (Td5) and glass transition temperature (Tg) of the composite i.e. an increase of 8°C and 6 °C has been observed for the Td5 and Tg, respectively.

Keywords: natural rubber, ultrafine fully vulcanized powder rubber, polybenzoxazine, polymer composite, toughening

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Al-Naqdi Ibtehal Abdulmonem

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Kindergarten buildings are essential for early childhood education, providing a secure environment for children's development. However, they are susceptible to seismic forces, which can endanger occupants during earthquakes. This article emphasizes the importance of conducting thorough seismic analysis and implementing proper structural design to protect the well-being of children, staff, and visitors. By prioritizing structural integrity and considering functional requirements, engineers can mitigate risks associated with seismic events. The use of specialized software like ETABS is crucial for designing earthquake-resistant kindergartens. An analysis using ETABS software compared the structural performance of two single-story kindergartens in Iraq's Ministry of Education, designed with and without seismic considerations. The analysis aimed to assess the impact of seismic design on structural integrity and safety. The kindergarten was designed with seismic considerations, including moment frames. In contrast, the same kindergarten was analyzed without seismic effects, revealing a lack of structural elements to resist lateral forces, rendering it vulnerable to structural failure during an earthquake. Maximum major shear increased over 4 times and over 5 times for bending moment in both kindergartens designed with seismic considerations induced by lateral loads and seismic forces. This component of shear force is vital for designing elements to resist lateral loads and ensure structural stability.

Keywords: seismic analysis, structural design, lateral loads, earthquake resistance, major shear, ETABS

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Authors: Min L. Stewart, Patrick Johnston

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Predictive coding has been proposed as a general explanatory framework for understanding the neural mechanisms of perception. As such, an underweighting of perceptual priors has been hypothesised to underpin a range of differences in inferential and sensory processing in autism spectrum disorders. However, empirical evidence to support this has not been well established. The present study uses an electroencephalography paradigm involving changes of facial identity and person category (actors etc.) to explore how levels of autistic traits (AT) affect predictive coding at multiple stages in the visual processing hierarchy. The study uses a rapid serial presentation of faces, with hierarchically structured sequences involving both periodic and aperiodic repetitions of different stimulus attributes (i.e., person identity and person category) in order to induce contextual expectations relating to these attributes. It investigates two main predictions: (1) significantly larger and late neural responses to change of expected visual sequences in high-relative to low-AT, and (2) significantly reduced neural responses to violations of contextually induced expectation in high- relative to low-AT. Preliminary frequency analysis data comparing high and low-AT show greater and later event-related-potentials (ERPs) in occipitotemporal areas and prefrontal areas in high-AT than in low-AT for periodic changes of facial identity and person category but smaller ERPs over the same areas in response to aperiodic changes of identity and category. The research advances our understanding of how abnormalities in predictive coding might underpin aberrant perceptual experience in autism spectrum. This is the first stage of a research project that will inform clinical practitioners in developing better diagnostic tests and interventions for people with autism.

Keywords: hierarchical visual processing, face processing, perceptual hierarchy, prediction error, predictive coding

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Authors: Shaya Mahmoudian, Mohammad Reza Sazegar, Nazanin Afshari

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Graphene, a single layer of carbon atoms in a hexagonal lattice, has recently attracted great attention due to its unique mechanical, thermal and electrical properties. The high aspect ratio and unique surface features of graphene resulted in significant improvements of the nano composites properties. In this study, nano composite fibres made of cellulose and graphene nano platelets were wet spun from solution by using ionic liquid, 1-ethyl-3-methylimidazolium acetate (EMIMAc) as solvent. The effect of graphene loading on the thermal and electrical properties of the nanocomposite fibres was investigated. The nano composite fibres characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis. XRD analysis revealed a cellulose II crystalline structure for regenerated cellulose and the nano composite fibres. SEM images showed a homogenous morphology and round cross section for the nano composite fibres along with well dispersion of graphene nano platelets in regenerated cellulose matrix. The incorporation of graphene into cellulose matrix generated electrical conductivity. At 6 wt. % of graphene, the electrical conductivity was 4.7 × 10-4 S/cm. The nano composite fibres also showed considerable improvements in thermal stability and char yield compared to pure regenerated cellulose fibres. This work provides a facile and environmentally friendly method of preparing nano composite fibres based on cellulose and graphene nano platelets that can find several applications in cellulose-based carbon fibres, conductive fibres, apparel, etc.

Keywords: nanocomposite, graphene nanoplatelets, regenerated cellulose, electrical properties

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Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

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In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

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Authors: Jiangang Shen

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Olfactory dysfunction is a common symptom companied by anxiety- and depressive-like behaviors in depressive patients. Chronic stress triggers hormone responses and inhibits the proliferation and differentiation of neural stem cells (NSCs) in the hippocampus and subventricular zone (SVZ)-olfactory bulb (OB), contributing to depressive behaviors and olfactory dysfunction. However, the cellular signaling molecules to regulate chronic stress mediated olfactory dysfunction are largely unclear. Adaptor proteins containing the pleckstrin homology domain, phosphotyrosine binding domain, and leucine zipper motif (APPLs) are multifunctional adaptor proteins. Herein, we tested the hypothesis that APPL2 could inhibit hippocampal neurogenesis by affecting glucocorticoid receptor (GR) signaling, subsequently contributing to depressive and anxiety behaviors as well as olfactory dysfunctions. The major discoveries are included: (1) APPL2 Tg mice had enhanced GR phosphorylation under basic conditions but had no different plasma corticosterone (CORT) level and GR phosphorylation under stress stimulation. (2) APPL2 Tg mice had impaired hippocampal neurogenesis and revealed depressive and anxiety behaviors. (3) GR antagonist RU486 reversed the impaired hippocampal neurogenesis in the APPL2 Tg mice. (4) APPL2 Tg mice displayed higher GR activity and less capacity for neurogenesis at the olfactory system with lesser olfactory sensitivity than WT mice. (5) APPL2 negatively regulates olfactory functions by switching fate commitments of NSCs in adult olfactory bulbs via interaction with Notch1 signaling. Furthermore, baicalin, a natural medicinal compound, was found to be a promising agent targeting APPL2/GR signaling and promoting adult neurogenesis in APPL2 Tg mice and chronic corticosterone-induced depression mouse models. Behavioral tests revealed that baicalin had antidepressant and olfactory-improving effects. Taken together, APPL2 is a critical therapeutic target for antidepressant treatment.

Keywords: APPL2, hippocampal neurogenesis, depressive behaviors and olfactory dysfunction, stress

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Authors: Bhavana V. Mohite, Satish V. Patil

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Bacterial cellulose (BC) is an alternative for plant cellulose (PC) that prevents global warming leads to preservation of nature. Although PC and BC have the same chemical structure, BC is superior with its properties like its size, purity, porosity, degree of polymerization, crystallinity and water holding capacity, thermal stability etc. On this background the present study focus production and applications of BC as antimicrobial wound dressing material. BC was produced by Gluconoacetobacter hansenii (strain NCIM 2529) under shaking condition and statistically enhanced upto 7.2 g/l from 3.0 g/l. BC was analyzed for its physico mechanical, structural and thermal characteristics. BC produced at shaking condition exhibits more suitable properties in support to its high performance applications. The potential of nano silver impregnated BC was determined for sustained release modern antimicrobial wound dressing material by swelling ratio, mechanical properties and antimicrobial activity against Staphylococcus aureus. BC in nanocomposite form with other synthetic polymer like PVA shows improvement in its properties such as swelling ratio (757% to 979%) and sustainable release of antibacterial agent. The high drug loading and release potential of BC was evidenced in support to its nature as antimicrobial wound dressing material. The nontoxic biocompatible nature of BC was confirmed by MTT assay on human epidermal cells with 90% cell viability that allows its application as a regenerative biomaterial. Thus, BC as a promising new generation antimicrobial wound dressing material was projected.

Keywords: agitated culture, biopolymer, gluconoacetobacter hansenii, nanocomposite

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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Authors: Saba Atefyekta

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Aim: Control of bacterial bioburden in wounds is an important step for minimizing the risk of wound infection. An antimicrobial hydrogel wound dressing is developed out of soft polymeric hydrogels that contain antimicrobial peptides (AMPs). Such wound dressings can bind and kill all types of bacteria, even the resistance types at the wound site. Methods: AMPs are permanently bonded onto a soft nanostructured polymer via covalent attachment and physical entanglement. This improves stability, rapid antibacterial activity, and, most importantly, prevents the leaching of AMPs. Major Findings: Antimicrobial analysis of antimicrobial hydrogels using in-vitro wound models confirmed >99% killing efficiency against multiple bacterial trains, including MRSA, MDR, E. Coli. Furthermore, the hydrogel retained its antibacterial activity for up to 4 days when exposed to human serum. Tests confirmed no release of AMPs, and it was proven non-toxic to mammalian cells. An in-vivo study on human intact skin showed a significant reduction of bacteria for part of the subject’s skin treated with antibacterial hydrogels. A similar result was detected through a qualitative study in veterinary trials on different types of surgery wounds in cats, dogs, and horses. Conclusions: Antimicrobial hydrogels wound dressings developed by permanent attachment of AMPs can effectively and rapidly kill bacteria in contact. Such antibacterial hydrogel wound dressings are non-toxic and do not release any substances into the wound.

Keywords: antibacterial wound dressing, antimicrobial peptides, post-surgical wounds, infection

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Authors: Ahmed. S. Alasmari, M. S. Soliman, Magdy M. El-Rayes

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This study focuses on the effect of the addition of magnesium (Mg) and silver (Ag) on the mechanical properties of aluminum based alloys. The alloying elements will be added at different levels using the factorial design of experiments of 2²; the two factors are Mg and Ag at two levels of concentration. The superior mechanical properties of the produced Al-Cu-Mg-Ag alloys after aging will be resulted from a unique type of precipitation named as Ω-phase. The formed precipitate enhanced the tensile strength and thermal stability. This paper further investigated the microstructure and mechanical properties of as cast Al–Cu–Mg–Ag alloys after being complete homogenized treatment at 520 °C for 8 hours followed by isothermally age hardening process at 190 °C for different periods of time. The homogenization at 520 °C for 8 hours was selected based on homogenization study at various temperatures and times. The alloys’ microstructures were studied by using optical microscopy (OM). In addition to that, the fracture surface investigation was performed using a scanning electronic microscope (SEM). Studying the microstructure of aged Al-Cu-Mg-Ag alloys reveal that the grains are equiaxed with an average grain size of about 50 µm. A detailed fractography study for fractured surface of the aged alloys exhibited a mixed fracture whereby the random fracture suggested crack propagation along the grain boundaries while the dimples indicated that the fracture was ductile. The present result has shown that alloy 5 has the highest hardness values and the best mechanical behaviors.

Keywords: precipitation hardening, aluminum alloys, aging, design of experiments, analysis of variance, heat treatments

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Authors: Ömer Tamer, Davut Avcı, Yusuf Atalay

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Novel picolinate complex of manganese(II) ion, [Mn(pic)2] [pic: picolinate or 2-pyridinecarboxylate], was prepared and fully characterized by single crystal X-ray structure determination. The manganese(II) complex was characterized by FT-IR, FT-Raman and UV–Vis spectroscopic techniques. The C=O, C=N and C=C stretching vibrations were found to be strong and simultaneously active in IR and spectra. In order to support these experimental techniques, density functional theory (DFT) calculations were performed at Gaussian 09W. Although the supramolecular interactions have some influences on the molecular geometry in solid state phase, the calculated data show that the predicted geometries can reproduce the structural parameters. The molecular modeling and calculations of IR, Raman and UV-vis spectra were performed by using DFT levels. Nonlinear optical (NLO) properties of synthesized complex were evaluated by the determining of dipole moment (µ), polarizability (α) and hyperpolarizability (β). Obtained results demonstrated that the manganese(II) complex is a good candidate for NLO material. Stability of the molecule arising from hyperconjugative interactions and charge delocalization was analyzed using natural bond orbital (NBO) analysis. The highest occupied and the lowest unoccupied molecular orbitals (HOMO and LUMO) which is also known the frontier molecular orbitals were simulated, and obtained energy gap confirmed that charge transfer occurs within manganese(II) complex. Molecular electrostatic potential (MEP) for synthesized manganese(II) complex displays the electrophilic and nucleophilic regions. From MEP, the the most negative region is located over carboxyl O atoms while positive region is located over H atoms.

Keywords: DFT, picolinate, IR, Raman, nonlinear optic

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Authors: Mona Alharbi

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Melioidosis has emerged as a lethal disease. Unfortunately, the molecular mechanisms of virulence and pathogenicity of Burkholderia pseudomallei remain unknown. However, proteomics research has selected putative targets in B. pseudomallei that might play roles in the B. pseudomallei virulence. BPSL 2418 putative protein has been predicted as a free methionine sulfoxide reductase and interestingly there is a link between the level of the methionine sulfoxide in pathogen tissues and its virulence. Therefore in this work, we describe the cloning expression, purification, and crystallization of BPSL 2418 and the solution of its 3D structure using X-ray crystallography. Also, we aimed to identify the substrate binding and reduced forms of the enzyme to understand the role of BPSL 2418. The gene encoding BPSL2418 from B. pseudomallei was amplified by PCR and reclone in pETBlue-1 vector and transformed into E. coli Tuner DE3 pLacI. BPSL2418 was overexpressed using E. coli Tuner DE3 pLacI and induced by 300μM IPTG for 4h at 37°C. Then BPS2418 purified to better than 95% purity. The pure BPSL2418 was crystallized with PEG 4000 and PEG 6000 as precipitants in several conditions. Diffraction data were collected to 1.2Å resolution. The crystals belonged to space group P2 21 21 with unit-cell parameters a = 42.24Å, b = 53.48Å, c = 60.54Å, α=γ=β= 90Å. The BPSL2418 binding MES was solved by molecular replacement with the known structure 3ksf using PHASER program. The structure is composed of six antiparallel β-strands and four α-helices and two loops. BPSL2418 shows high homology with the GAF domain fRMsrs enzymes which suggest that BPSL2418 might act as methionine sulfoxide reductase. The amino acids alignment between the fRmsrs including BPSL 2418 shows that the three cysteines that thought to catalyze the reduction are fully conserved. BPSL 2418 contains the three conserved cysteines (Cys⁷⁵, Cys⁸⁵ and Cys¹⁰⁹). The active site contains the six antiparallel β-strands and two loops where the disulfide bond formed between Cys⁷⁵ and Cys¹⁰⁹. X-ray structure of free methionine sulfoxide binding and native forms of BPSL2418 were solved to increase the understanding of the BPSL2418 catalytic mechanism.

Keywords: X-Ray Crystallography, BPSL2418, Burkholderia pseudomallei, Melioidosis

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Salami Abiodun Olusola, Bankole Faith Ayobami

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Agro-wastes are wastes produced from various agricultural activities and include manures, corncob, plant stalks, hulls, leaves, sugarcane bagasse, oil-palm spadix, and rice bran. In farming situation, the agro-waste is often useless and, thus, discarded. Huge quantities of waste resources generated from Nigerian agriculture could be converted to more useful forms of energy, which could contribute to the country’s primary energy needs and reduce problems associated with waste management. Accumulation of agro-wastes may cause health, safety, and environmental concern. However, biotechnological use of agro-waste could enhance food security through its bioconversion to useful renewable energy. Mushrooms are saprophytes which feed by secreting extracellular enzymes, digesting food externally, and absorb the nutrients in net-like hyphae. Therefore, mushrooms could be exploited for bioconversion of the cheap and numerous agro-wastes for providing nutritious food for animals, human and carbon recycling. The study investigated the bioconversion potentials of Pleurotus florida on agro-wastes using a simple and cost-effective biotechnological method. Four agro-wastes; corncobs, oil-palm spadix, corn straw, and sawdust, were composted and used as substrates while the biological efficiency (BE) and the nutritional composition of P. florida grown on the substrates were determined. Pleurotus florida contained 26.28-29.91% protein, 86.90-89.60% moisture, 0.48-0.91% fat, 19.64-22.82% fibre, 31.37-38.17% carbohydrate and 5.18-6.39% ash. The mineral contents ranged from 342-410 mg/100g Calcium, 1009-1133 mg/100g Phosphorus, 17-21 mg/100g Iron, 277-359 mg/100g Sodium, and 2088-2281 mg/100g Potassium. The highest yield and BE were obtained on corncobs (110 g, 55%), followed by oil-palm spadix (76.05 g, 38%), while the least BE was recorded on corn straw substrate (63.12 g, 31.56%). Utilization of the composted substrates yielded nutritional and edible mushrooms. The study presents biotechnological procedure for bioconversion of agro-wastes to edible and nutritious mushroom for efficient agro-wastes’ management, utilization, and recycling.

Keywords: agrowaste, bioconversion, biotechnology, utilization, recycling

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Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

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A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

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Authors: P. S. Percin, O. Inanli, S. Karakaya

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Bitter melon (Momordica charantia) is a medicinal vegetable, which is used traditionally to remedy diabetes. Bitter melon contains several classes of primary and secondary metabolites. In traditional Turkish medicine bitter melon is used for wound healing and treatment of peptic ulcers. Nowadays, bitter melon is used for the treatment of diabetes and ulcerative colitis in many countries. The main constituents of bitter melon, which are responsible for the anti-diabetic effects, are triterpene, protein, steroid, alkaloid and phenolic compounds. In this study total phenolics, total carotenoids and β-carotene contents of mature and immature bitter melons were determined. In addition, in vitro α-amylase and α-glucosidase activities of mature and immature bitter melons were studied. Total phenolic contents of immature and mature bitter melon were 74 and 123 mg CE/g bitter melon respectively. Although total phenolics of mature bitter melon was higher than that of immature bitter melon, this difference was not found statistically significant (p > 0.05). Carotenoids, a diverse group of more than 600 naturally occurring red, orange and yellow pigments, play important roles in many physiological processes both in plants and humans. The total carotenoid content of mature bitter melon was 4.36 fold higher than the total carotenoid content of immature bitter melon. The compounds that have hypoglycaemic effect of bitter melon are steroidal saponins known as charantin, insulin-like peptides and alkaloids. α-Amylase is one of the main enzymes in human that is responsible for the breakdown of starch to more simple sugars. Therefore, the inhibitors of this enzyme can delay the carbohydrate digestion and reduce the rate of glucose absorption. The immature bitter melon extract showed α-amylase and α-glucosidase inhibitory activities in vitro. α-Amylase inhibitory activity was higher than that of α-glucosidase inhibitory activity when IC50 values were compared. In conclusion, the present results provide evidence that aqueous extract of bitter melon may have an inhibitory effect on carbohydrate breakdown enzymes.

Keywords: bitter melon, in vitro antidiabetic activity, total carotenoids, total phenols

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Authors: Bohuslava Juhasova, Martin Juhas, Renata Masarova, Zuzana Sutova

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The article deals with the tool in Matlab GUI form that is designed to analyse a mechatronic system sensitivity and tolerance. In the analysed mechatronic system, a torque is transferred from the drive to the load through a coupling containing flexible elements. Different methods of control system design are used. The classic form of the feedback control is proposed using Naslin method, modulus optimum criterion and inverse dynamics method. The cascade form of the control is proposed based on combination of modulus optimum criterion and symmetric optimum criterion. The sensitivity is analysed on the basis of absolute and relative sensitivity of system function to the change of chosen parameter value of the mechatronic system, as well as the control subsystem. The tolerance is analysed in the form of determining the range of allowed relative changes of selected system parameters in the field of system stability. The tool allows to analyse an influence of torsion stiffness, torsion damping, inertia moments of the motor and the load and controller(s) parameters. The sensitivity and tolerance are monitored in terms of the impact of parameter change on the response in the form of system step response and system frequency-response logarithmic characteristics. The Symbolic Math Toolbox for expression of the final shape of analysed system functions was used. The sensitivity and tolerance are graphically represented as 2D graph of sensitivity or tolerance of the system function and 3D/2D static/interactive graph of step/frequency response.

Keywords: mechatronic systems, Matlab GUI, sensitivity, tolerance

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Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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Authors: A. Aslihan Gokaltun, Ali Tuncel

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The unique properties of capillary electrochromatography (CEC) such as high performance, high selectivity, low consumption of both reagents and analytes ensure this technique an attractive one for the separation of biomolecules including nucleosides and nucleotides, peptides, proteins, carbohydrates. Monoliths have become a well-established separation media for CEC in the format that can be compared to a single large 'particle' that does not include interparticular voids. Convective flow through the pores of monolith significantly accelerates the rate of mass transfer and enables a substantial increase in the speed of the separation. In this work, we propose a new approach for the preparation of cationic monolithic stationary phase for capillary electrochromatography. Instead of utilizing a charge bearing monomer during polymerization, the desired charge-bearing group is generated on the capillary monolith after polymerization by using the reactive moiety of the monolithic support via one-pot, simple reaction. Optimized monolithic column compensates the disadvantages of frequently used reversed phases, which are difficult for separation of polar solutes. Rapid separation and high column efficiencies are achieved for the separation of neutral analytes, nucleic acid bases and nucleosides in reversed phase mode. Capillary monolith showed satisfactory hydrodynamic permeability and mechanical stability with relative standard deviation (RSD) values below 2 %. A new promising, reactive support that has a 'ligand selection flexibility' due to its reactive functionality represent a new family of separation media for CEC.

Keywords: biomolecules, capillary electrochromatography, cationic monolith, neutral analytes

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Authors: Wenzheng Fu, Yue Fu, Zhijiang Dong, Yujian Fu

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The integration of artificial intelligence (AI) and machine learning (ML) into project management is transforming how engineering projects are executed, monitored, and controlled. This paper provides a comprehensive survey of AI and ML applications in project management, systematically categorizing their use in key areas such as project data analytics, monitoring, tracking, scheduling, and reporting. As project management becomes increasingly data-driven, AI and ML offer powerful tools for improving decision-making, optimizing resource allocation, and predicting risks, leading to enhanced project outcomes. The review highlights recent research that demonstrates the ability of AI and ML to automate routine tasks, provide predictive insights, and support dynamic decision-making, which in turn increases project efficiency and reduces the likelihood of costly delays. This paper also examines the emerging trends and future opportunities in AI-driven project management, such as the growing emphasis on transparency, ethical governance, and data privacy concerns. The research suggests that AI and ML will continue to shape the future of project management by driving further automation and offering intelligent solutions for real-time project control. Additionally, the review underscores the need for ongoing innovation and the development of governance frameworks to ensure responsible AI deployment in project management. The significance of this review lies in its comprehensive analysis of AI and ML’s current contributions to project management, providing valuable insights for both researchers and practitioners. By offering a structured overview of AI applications across various project phases, this paper serves as a guide for the adoption of intelligent systems, helping organizations achieve greater efficiency, adaptability, and resilience in an increasingly complex project management landscape.

Keywords: artificial intelligence, decision support systems, machine learning, project management, resource optimization, risk prediction

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Authors: Mohamed Youssry, Dominique Guyomard, Bernard Lestriez

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In order to enhance the energy and power densities of electrodes for energy storage systems, the formulation and processing of electrode slurries proved to be a critical issue in determining the electrode performance. In this study, we introduce novel approach to formulate carbon black slurries based on microemulsion and lyotropic liquid crystalline phases (namely, lamellar phase) composed of non-ionic surfactant (Triton X100), decanol and water. Simultaneous measurements of electrical properties of slurries under shear flow (rheology) have been conducted to elucidate the microstructure evolution with the surfactant concentration and decanol/water ratio at rest, as well as, the structural transition under steady-shear which has been confirmed by rheo-microscopy. Interestingly, the carbon black slurries at low decanol/water ratio are weak-gel (flowable) with higher electrical conductivity than those at higher ratio which behave strong-gel viscoelastic response. In addition, the slurries show recoverable electrical behaviour under shear flow in tandem with the viscosity trend. It is likely that oil-in-water microemulsion enhances slurries’ stability without affecting on the percolating network of carbon black. On the other hand, the oil-in-water analogous and bilayer structure of lamellar phase cause the slurries less conductive as a consequence of losing the network percolation. These findings are encouraging to formulate microemulsion-based electrodes for energy storage system (lithium-ion batteries).

Keywords: electrode slurries, microemulsion, microstructure transition, rheo-electrical properties

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Authors: David Lynch Steinicke, Citlali Aguilera Lira, Andrea León García

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The proposal posed in this work comes from a researching-action approach. In Mexico, a dialogue of knowledge may function as a link between traditional, local, pragmatic knowledge, and technological, scientific knowledge. The advantage of generating this nexus lies on the positive impact in the environment, in society and economy. This work attempts to combine, on the one hand the traditional Mexican knowledge such as the usage of medicinal herb and the agroecosystem milpa; and on the other hand make use of a newly created agricultural ecotechnology which main function is to take advantage of the urban space and to save water. This ecotechnology is the wicking bed. In a globalized world, is relevant to have a proposal where the most important aspect is to revalorize the culture through the acquisition of traditional knowledge but at the same time adapting them to the new social and urbanized structures without threatening the environment. The methodology used in this work comes from a researching-action approach combined with a practical dimension where an experimental model made of three wickingbeds was implemented. In this model, there were cultivated medicinal herb and milpa components. The water efficiency and the social acceptance were compared with a traditional ground crop, all this practice was made in an urban social context. The implementation of agricultural ecotechnology has had great social acceptance as its irrigation involves minimal effort and it is economically feasible for low-income people. The wicking bed system raised in this project is attainable to be implemented in schools, urban and peri-urban environments, homemade gardens and public areas. The proposal managed to carry out an innovative and sustainable knowledge-based traditional Mexican agricultural technology, allowing regain Milpa agroecosystem in urban environments to strengthen food security in favour of nutritional and protein benefits for the Mexican fare.

Keywords: milpa, traditional medicine, urban agriculture, wicking bed

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Authors: Othoman Elsayah, Naren Gupta, Binsheng Zhang

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The construction sector constitutes one of the most important sectors in the economy of any country. Contractor selection is a critical decision that is undertaken by client organizations and is central to the success of any construction project. Contractor selection (CS) is a process which involves investigating, screening and determining whether candidate contractors have the technical and financial capability to be accepted to formally tender for construction work. The process should be conducted prior to the award of contract, characterized by many factors such as: contactor’s skills, experience on similar projects, track- record in the industry, and financial stability. However, this paper evaluates the current state of knowledge in relation to contractor selection process and demonstrates the findings from the analysis of the data collected from the Delphi questionnaire survey. The survey was conducted with a group of 12 experts working in the Libyan construction industry (LCI). The paper starts by briefly explaining the general outline of the questionnaire including the survey participation rate, the different fields the experts came from, and the business titles of the participants. Then, the paper describes the tests used to determine when the experts had reached consensus. The paper is based on research which aims to develop rank contractor selection criteria with specific application to make construction projects in the Libyan context. The findings of this study will be utilized to establish the scope of work that will be used as part of a PhD research.

Keywords: contractor selection, Libyan construction industry, decision experts, Delphi technique

Procedia PDF Downloads 332