Search results for: diffusion driven instability

Authors: Wen Feiming

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As the ecological barrier of the Yangtze River, the ecological security of the Parallel Range-Valley area is very important. However, the unique geomorphic features aggravate the contradiction between man and land, resulting in the encroachment of ecological space. In recent years , relevant researches has focused on the single field of land science, ecology and landscape ecology, and it is difficult to systematically reflect the regularities of distribution and evolution trends of ecological patterns in the process of urban development. Therefore, from the perspective of "Production-Living-Ecological space", using spatial analysis methods such as Remote Sensing (RS) and Geographic Information Systems (GIS), this paper analyzes the evolution characteristics and driving factors of the ecological pattern of mountain towns in the parallel range-valley region from the aspects of land use structure, change rate, transformation relationship, and spatial correlation. It is concluded that the ecological pattern of mountain towns presents a trend from expansion and diffusion to agglomeration, and the dynamic spatial transfer is a trend from artificial transformation to the natural origin, while the driving effect analysis shows the significant characteristics of terrain attraction and construction barrier. Finally, combined with the evolution characteristics and driving mechanism, the evolution modes of "mountain area - concentrated growth", "trough area - diffusion attenuation" and "flat area - concentrated attenuation" are summarized, and the differentiated zoning and stratification ecological planning strategies are proposed here, in order to provide the theoretical basis for the sustainable development of mountain towns in parallel range-valley areas.

Keywords: parallel range-valley, ecological pattern, evolution characteristics, driving factors

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Authors: A. Chellil, A. Nour, S. Lecheb, H.Mechakra, A. Bouderba, H. Kebir

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In this paper, the numerical study for the instability of a composite rotor is presented, under dynamic loading response in the harmonic analysis condition. The analysis of the stress which operates the rotor is done. Calculations of different energies and the virtual work of the aerodynamic loads from the rotor is developed. The use of the composite material for the rotor, offers a good Stability. Numerical calculations on the model develop of three dimensions prove that the damage effect has a negative effect on the stability of the rotor. The study of the composite rotor in transient system allowed to determine the vibratory responses due to various excitations.

Keywords: rotor, composite, damage, finite element, numerical

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Authors: Sawyer Spurry

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Problem: Palliative care providers at an academic medical center in Maryland stated medical intensive care unit (MICU) patients are often referred late in their hospital stay. The MICU has performed well below the hospital quality performance metric of 80% of patients who expire with expected outcomes should have received a palliative care consult within 48 hours of admission. Purpose: The purpose of this quality improvement (QI) project is to increase palliative care utilization in the MICU through the implementation of a Nurse-Driven PalliativeTriggerTool to prompt the need for specialty palliative care consult. Methods: MICU nursing staff and providers received education concerning the implications of underused palliative care services and the literature data supporting the use of nurse-driven palliative care tools as a means of increasing utilization of palliative care. A MICU population specific criteria of palliative triggers (Palliative Care Trigger Tool) was formulated by the QI implementation team, palliative care team, and patient care services department. Nursing staff were asked to assess patients daily for the presence of palliative triggers using the Palliative Care Trigger Tool and present findings during bedside rounds. MICU providers were asked to consult palliative medicinegiven the presence of palliative triggers; following interdisciplinary rounds. Rates of palliative consult, given the presence of triggers, were collected via electronic medical record e-data pull, de-identified, and recorded in the data collection tool. Preliminary Results: Over 140 MICU registered nurses were educated on the palliative trigger initiative along with 8 nurse practitioners, 4 intensivists, 2 pulmonary critical care fellows, and 2 palliative medicine physicians. Over 200 patients were admitted to the MICU and screened for palliative triggers during the 15-week implementation period. Primary outcomes showed an increase in palliative care consult rates to those patients presenting with triggers, a decreased mean time from admission to palliative consult, and increased recognition of unmet palliative care needs by MICU nurses and providers. Conclusions: Anticipatory findings of this QI project would suggest a positive correlation between utilizing palliative care trigger criteria and decreased time to palliative care consult. The direct outcomes of effective palliative care results in decreased length of stay, healthcare costs, and moral distress, as well as improved symptom management and quality of life (QOL).

Keywords: palliative care, nursing, quality improvement, trigger tool

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Authors: Foyewa R. A.

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This paper examined the role of English language and the quest for a national language in Nigeria. Various hindrances to the choice of a national language in Nigeria were observed. These include: The dominant role of English language, political instability and multilingual nature of the country. The writer suggested that ’’the three big’’ that is, Hausa, Igbo and Yoruba should be selected as the national languages. It was also suggested that a credit pass in a student’s mother tongue and one of “the three big” (Hausa, Igbo and Yoruba) should constitute the prerequisite for admission into Nigerian higher institutions.

Keywords: English, roles of English, national language, Nigerian languages, Hausa, Igbo, Yoruba

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Authors: Alemayehu Mengesha, Solomon Belay

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We determine the general dispersion relation for the propagation of magnetohydrodynamic (MHD) waves in an astrophysical plasma by considering the effect of viscosity with an anisotropic pressure tensor. Basic MHD equations have been derived and linearized by the method of perturbation to develop the general form of the dispersion relation equation. Our result indicates that an astrophysical plasma with an anisotropic pressure tensor is stable in the presence of viscosity and a strong magnetic field at considerable wavelength. Currently, we are doing the numerical analysis of this work.

Keywords: astrophysical, magnetic field, instability, MHD, wavelength, viscosity

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Authors: Teresa Roco, Mario Perez Won, Roberto Lemus-Mondaca, Sebastian Pizarro

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This research presents the simultaneous application of high hydrostatic pressure application (HHP) and osmotic dehydration (DO) as a pretreatment to hot –air drying of abalone cubes. The drying time was reduced to 6 hours at 60ºC as compared to the abalone drying by only a 15% NaCl osmotic pretreatment and at an atmospheric pressure that took 10 hours to dry at the same temperature. This was due to the salt and HHP saturation since osmotic pressure increases as water loss increases, thus needing a more reduced time in a convective drying, so water effective diffusion in drying plays an important role in this research. Different working conditions as pressure (350-550 MPa), pressure time ( 5-10 min), salt concentration, NaCl 15% and drying temperature (40-60ºC) will be optimized according to kinetic parameters of each mathematical model (Table 1). The models used for drying experimental curves were those corresponding to Weibull, Logarithmic and Midilli-Kucuk, but the latest one was the best fitted to the experimental data (Figure 1). The values for water effective diffusivity varied from 4.54 – to 9.95x10-9 m2/s for the 8 curves (DO+HHP) whereas the control samples (neither DO nor HHP) varied among 4.35 and 5.60x10-9 m2/s, for 40 and 60°C, respectively and as to drying by osmotic pretreatment at 15% NaCl from 3.804 to 4.36x10-9 m2/s at the same temperatures. Finally as to energy and efficiency consumption values for drying process (control and pretreated samples) it was found that they would be within a range of 777-1815 KJ/Kg and 8.22–19.20% respectively. Therefore, a knowledge concerning the drying kinetic as well as the consumption energy, in addition to knowledge about the quality of abalones subjected to an osmotic pretreatment (DO) and a high hydrostatic pressure (HHP) are extremely important to an industrial level so that the drying process can be successful at different pretreatment conditions and/or variable processes.

Keywords: abalone, convective drying, high pressure hydrostatic, pretreatments, diffusion coefficient

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Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

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Authors: Debamitra Chakravorty, Pratap K. Parida

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Cold-adapted proteases enhance wash performance in low-temperature laundry resulting in a reduction in energy consumption and wear of textiles and are also used in the dehairing process in leather industries. Unfortunately, the possible drawbacks of using cold-adapted proteases are their instability at higher temperatures. Therefore, proteases with broad temperature stability are required. Unfortunately, wild-type cold-adapted proteases exhibit instability at higher temperatures and thus have low shelf lives. Therefore, attempts to engineer cold-adapted proteases by protein engineering were made previously by directed evolution and random mutagenesis. The lacuna is the time, capital, and labour involved to obtain these variants are very demanding and challenging. Therefore, rational engineering for cold stability without compromising an enzyme's optimum pH and temperature for activity is the current requirement. In this work, mutations were rationally designed with the aid of high throughput computational methodology of network analysis, evolutionary conservation scores, and molecular dynamics simulations for Savinase from Bacillus lentus with the intention of rendering the mutants cold stable without affecting their temperature and pH optimum for activity. Further, an attempt was made to incorporate a mutation in the most stable mutant rationally obtained by this method to introduce oxidative stability in the mutant. Such enzymes are desired in detergents with bleaching agents. In silico analysis by performing 300 ns molecular dynamics simulations at 5 different temperatures revealed that these three mutants were found to be better in cold stability compared to the wild type Savinase from Bacillus lentus. Conclusively, this work shows that cold adaptation without losing optimum temperature and pH stability and additionally stability from oxidative damage can be rationally designed by in silico enzyme engineering. The key findings of this work were first, the in silico data of H5 (cold stable savinase) used as a control in this work, corroborated with its reported wet lab temperature stability data. Secondly, three cold stable mutants of Savinase from Bacillus lentus were rationally identified. Lastly, a mutation which will stabilize savinase against oxidative damage was additionally identified.

Keywords: cold stability, molecular dynamics simulations, protein engineering, rational design

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Authors: W. Q. Wang, Y. Yin, D. B. Zou, T. P. Yu, J. M. Ouyang, F. Q. Shao

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High-energy-density state, i.e., matter and radiation at energy densities in excess of 10^11 J/m^3, is related to material, nuclear physics, astrophysics, and geophysics. Laser-driven particle beams are better suited to heat the matter as a trigger due to their unique properties of ultrashort duration and low emittance. Compared to X-ray and electron sources, it is easier to generate uniformly heated large-volume material for the proton and ion beams because of highly localized energy deposition. With the construction of state-of-art high power laser facilities, creating of extremely conditions of high-temperature and high-density in laboratories becomes possible. It has been demonstrated that on a picosecond time scale the solid density material can be isochorically heated to over 20 eV by the ultrafast proton beam generated from spherically shaped targets. For the above-mentioned technique, the proton energy density plays a crucial role in the formation of warm dense matter states. Recently, several methods have devoted to realize the focusing of the accelerated protons, involving externally exerted static-fields or specially designed targets interacting with a single or multi-pile laser pulses. In previous works, two co-propagating or opposite direction laser pulses are employed to strike a submicron plasma-shell. However, ultra-high pulse intensities, accurately temporal synchronization and undesirable transverse instabilities for a long time are still intractable for currently experimental implementations. A mechanism of the focusing of laser-driven proton beams from two-ion-species arched targets is investigated by multi-dimensional particle-in-cell simulations. When an intense linearly-polarized laser pulse impinges on the thin arched target, all electrons are completely evacuated, leading to a Coulomb-explosive electric-field mostly originated from the heavier carbon ions. The lighter protons in the moving reference frame by the ionic sound speed will be accelerated and effectively focused because of this radially isotropic field. At a 2.42×10^21 W/cm^2 laser intensity, a ballistic proton bunch with its energy-density as high as 2.15×10^17 J/m^3 is produced, and the highest proton energy and the focusing position agree well with that from the theory.

Keywords: Coulomb explosion, focusing, high-energy-density, ion acceleration

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Authors: Jayshree Patnaik, Bhaskar Bhowmick

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The economic growth of any nation is steered and dependent on innovation in technology. It can be preferably argued that technology has enhanced the quality of life. Technology is linked both with an economic and a social structure. But there are some parts of the world or communities which are yet to reap the benefits of technological innovation. Business and organizations are now well equipped with cutting-edge innovations that improve the firm performance and provide them with a competitive edge, but rarely does it have a positive impact on any community which is weak and marginalized. In recent times, it is observed that communities are actively handling social or ecological issues with the help of indigenous technologies. Thus, "Appropriate Technology" comes into the discussion, which is quite prevalent in the rural third world. Appropriate technology grew as a movement in the mid-1970s during the energy crisis, but it lost its stance in the following years when people started it to describe it as an inferior technology or dead technology. Basically, there is no such technology which is inferior or sophisticated for a particular region. The relevance of appropriate technology lies in penetrating technology into a larger and weaker section of community where the “Bottom of the pyramid” can pay for technology if they find the price is affordable. This is a theoretical paper which primarily revolves around how appropriate technology has faded and again evolved in both developed and developing countries. The paper will try to focus on the various concepts, history and challenges faced by the appropriate technology over the years. Appropriate technology follows a documented approach but lags in overall design and diffusion. Diffusion of technology into the poorer sections of community remains unanswered until the present time. Appropriate technology is multi-disciplinary in nature; therefore, this openness allows having a varied working model for different problems. Appropriate technology is a friendly technology that seeks to improve the lives of people in a constraint environment by providing an affordable and sustainable solution. Appropriate technology needs to be defined in the era of modern technological advancement for sustainability.

Keywords: appropriate technology, community, developing country, sustainability

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Authors: Runlian Miao, Wei Xie, Hong Zhang

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In China, Beijing-Tianjin-Hebei is regarded as a strategically important region because itenjoys highest development in economic development, opening up, innovative capacity and andpopulation. Integrated development of Beijing-Tianjin-Hebei region is increasingly emphasized by the government recently years. In 2014, it has ascended to one of the national great development strategies by Chinese central government. In 2015, Coordinated Development Planning Compendium for Beijing-Tianjin-Hebei Region was approved. Such decisions signify Beijing-Tianjin-Hebei region would lead innovation-driven economic development in China. As an essential factor to achieve national innovation-driven development and significant part of regional industry chain, the optimization of science and technology resources allocation will exert great influence to regional economic transformation and upgrading and innovation-driven development. However, unbalanced distribution, poor sharing of resources and existence of information isolated islands have contributed to different interior innovation capability, vitality and efficiency, which impeded innovation and growth of the whole region. Under such a background, to integrate and vitalize regional science and technology resources and then establish high-end, fast-responding and precise innovation service system basing on regional resources, would be of great significance for integrated development of Beijing-Tianjin-Hebei region and even handling of unbalanced and insufficient development problem in China. This research uses the method of literature review and field investigation and applies related theories prevailing home and abroad, centering service path of science and technology resources for innovation. Based on the status quo and problems of regional development of Beijing-Tianjin-Hebei, theoretically, the author proposed to combine regional economics and new economic geography to explore solution to problem of low resource allocation efficiency. Further, the author puts forward to applying digital map into resource management and building a platform for information co-building and sharing. At last, the author presents the thought to establish a specific service mode of ‘science and technology plus digital map plus intelligence research plus platform service’ and suggestion on co-building and sharing mechanism of 3 (Beijing, Tianjin and Hebei ) plus 11 (important cities in Hebei Province).

Keywords: Beijing-Tianjin-Hebei, science and technology resources, innovation service, digital platform

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Chukwuka Justus Iwegbu, Monye Christopher Prayer

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Propeller aircraft engines, and more generally engines with a large rotating part (turboprops, high bypass ratio turbojets, etc.) are widely used in the industry and are subject to numerous developments in order to reduce their fuel consumption. In this context, unconventional architectures such as open rotors or distributed propulsion appear, and it is necessary to consider the influence of these systems on the aircraft's stability in flight. Indeed, the tendency to lengthen the blades and wings on which these propulsion devices are fixed increases their flexibility and accentuates the risk of whirl flutter. This phenomenon of aeroelastic instability is due to the precession movement of the axis of rotation of the propeller, which changes the angle of attack of the flow on the blades and creates unsteady aerodynamic forces and moments that can amplify the motion and make it unstable. The whirl flutter instability can ultimately lead to the destruction of the engine. We note the existence of a critical speed of the incident flow. If the flow velocity is lower than this value, the motion is damped and the system is stable, whereas beyond this value, the flow provides energy to the system (negative damping) and the motion becomes unstable. A simple model of whirl flutter is based on the work of Houbolt & Reed who proposed an analytical expression of the aerodynamic load on a rigid blade propeller whose axis orientation suffers small perturbations. Their work considered a propeller subjected to pitch and yaw movements, a flow undisturbed by the blades and a propeller not generating any thrust in the absence of precession. The unsteady aerodynamic forces were then obtained using the thin airfoil theory and the strip theory. In the present study, the unsteady aerodynamic loads are expressed for a general movement of the propeller (not only pitch and yaw). The acceleration and rotation of the flow by the propeller are modeled using a Blade Element Momentum Theory (BEMT) approach, which also enable to take into account the thrust generated by the blades. It appears that the thrust has a stabilizing effect. The aerodynamic model is further developed using Theodorsen theory. A reduced order model of the aerodynamic load is finally constructed in order to perform linear stability analysis.

Keywords: advancing, entrepreneurial, knowledge, industralization

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Authors: M. Naresh, Pratik Chaturvedi, Srishti Yadav, Varun Dutt, K. V. Uday

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Changes in the Earth’s climate are likely to increase natural hazards such as drought, floods, earthquakes, landslides, etc. The present study focusing on to early warning systems (EWS) of landslides, major issues in Himalayan region without prominence to deforestation, encroachments and un-engineered cutting of slopes and reforming for infrastructural purposes. EWS can be depicted by conducting a series of flume tests using micro-electro mechanical systems sensors data after reaching threshold values under controlled laboratory conditions. Based on the threshold value database, an alert will be sent via SMS.

Keywords: slope-instability, flume test, sensors, early warning system

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Authors: Karlee J. Hall, Mark Laylor, Jessy Varghese, Paula Polastri, Karen Van Ooteghem, William McIlroy

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Balance training is a common part of physiotherapy treatment and often involves a set of proprioceptive exercises which the patient carries out in the clinic and as part of their exercise program. Understanding all contributing factors to altered balance is of utmost importance to the clinical success of treatment of balance dysfunctions. A critical role for the autonomic nervous system (ANS) in the control of balance reactions has been proposed previously, with evidence for potential involvement being inferred from the observation of phasic galvanic skin responses (GSR) evoked by external balance perturbations. The current study explored whether the coupling between ANS reactivity and balance reactions would be observed during spontaneously occurring instability while standing, including standard positions typical of physiotherapy balance assessments. It was hypothesized that time-varying changes in GSR (ANS reactivity) would be associated with time-varying changes in the mediolateral center of pressure (ML-COP) (somatomotor reactivity). Nine individuals (5 females, 4 males, aged 19-37 years) were recruited. To induce varying balance demands during standing, the study compared ML-COP and GSR data across different task conditions varying the availability of vision and width of the base of support. Subjects completed 3, 30-second trials for each of the following stance conditions: standard, narrow, and tandem eyes closed, tandem eyes open, tandem eyes open with dome to shield visual input, and restricted peripheral visual field. ANS activity was evaluated by measures of GSR recorded from Ag-AgCl electrodes on the middle phalanges of digits 2 and 4 on the left hand; balance measures include ML-COP excursion frequency and amplitude recorded from two force plates embedded in the floor underneath each foot. Subjects were instructed to stand as still as possible with arms crossed in front of their chest. When comparing mean task differences across subjects, there was an expected increase in postural sway from tasks with a wide stance and no sensory restrictions (least challenging) to those with a narrow stance and no vision (most challenging). The correlation analysis revealed a significant positive relationship between ML-COP variability and GSR variability when comparing across tasks (r=0.94, df=5, p < 0.05). In addition, correlations coincided within each subject and revealed a significant positive correlation in 7 participants (r= 0.47, 0.57, 0.62, 0.62, 0.81, 0.64, 0.69 respectively, df=19, p < 0.05) and no significant relationship in 2 participants (r=0.36, 0.29 respectively, df=19, p > 0.05). The current study revealed a significant relationship between ML-COP and GSR during balance tasks, revealing the ANS reactivity associated with naturally occurring instability when standing still, which is proportional to the degree of instability. Understanding the link between ANS activity and control of COP is an important step forward in the enhancement of assessment of contributing factors to poor balance and treatment of balance dysfunctions. The next steps will explore the temporal association between the time-varying changes in COP and GSR to establish if the ANS reactivity phase leads or lags the evoked motor reactions, as well as exploration of potential biomarkers for use in screening of ANS activity as a contributing factor to altered balance control clinically.

Keywords: autonomic nervous system, balance control, center of pressure, somatic nervous system

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Authors: Siamak Feizi, Gunvor Baardvik

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Soil erosion has special consequences for landfills that are more serious than those found at conventional construction sites. Different potential heads between two sides of a landfill and the subsequent movement of water through pores within the soil body could trigger the soil erosion and construction instability. Such a condition was encountered in a landfill project in the southern part of Norway. To check the risk of internal erosion due to changes in the groundwater level (because of seasonal flooding in the river), a series of numerical simulations by means of Geo-Seep software was conducted. Output of this study provides a total picture of the landfill stability, possibilities of erosions, and necessary measures to prevent or reduce the risk for the landfill operator.

Keywords: erosion, seepage, landfill, stability

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Authors: Aneri Mehta, Krunal Mehta

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The unpredictable and vacillating relationship between India and Pakistan since days of Independence struggle is known world over. And this instability has never lost its magnitude to decrease the tensions between the two countries. Since India aspires to run for the race of future superpower and Pakistan struggles to remove the tag of a highly fickle and under developed economy; ruined largely not by the outsiders, but its own people and systems; it becomes really important to gauge what steps would these neighbors take in years to come. The progress and stability of both countries heavily relies on the favorable equations between the two nations. Therefore the paper tries to trace some roots of their faltering relationship and attempts to predict their future in a multidimensional perspective.

Keywords: economy, faltering relationship, multidimensional perspective, international relations

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Authors: Sarah J. C. Slabbert

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The uptake of research as part of the diffusion or adoption of innovation by practitioners, whether individuals or organisations, has been a popular topic in agricultural development studies for many decades. In the classical, linear model of innovation theory, the innovation originates from an expert source such as a state-supported research organisation or academic institution. The changing context of agriculture led to the development of the agricultural innovation systems model, which recognizes innovation as a complex interaction between individuals and organisations, which include private industry and collective action organisations. In terms of this model, an innovation can be developed and adopted without any input or intervention from a state or parastatal research organisation. This evolution in the diffusion of agricultural innovation has put forward new challenges for state or parastatal research organisations, which have to demonstrate the impact of their research to the legislature or a regulatory authority: Unless the organisation and the research it produces cross the knowledge paths of the intended audience, there will be no awareness, no uptake and certainly no impact. It is therefore critical for such a research organisation to base its communication strategy on a thorough understanding of the knowledge needs, information sources and knowledge networks of the intended target audience. In 2016, the South African Water Research Commission (WRC) commissioned a study to investigate the knowledge needs, information sources and knowledge networks of Water User Associations and commercial irrigators with the aim of improving uptake of its research on efficient water use in irrigation. The first phase of the study comprised face-to-face interviews with the CEOs and Board Chairs of four Water User Associations along the Orange River in South Africa, and 36 commercial irrigation farmers from the same four irrigation schemes. Intermediaries who act as knowledge conduits to the Water User Associations and the irrigators were identified and 20 of them were subsequently interviewed telephonically. The study found that irrigators interact regularly with grower organisations such as SATI (South African Table Grape Industry) and SAPPA (South African Pecan Nut Association) and that they perceive these organisations as credible, trustworthy and reliable, within their limitations. State and parastatal research institutions, on the other hand, are associated with a range of negative attributes. As a result, the awareness of, and interest in, the WRC and its research on water use efficiency in irrigated agriculture are low. The findings suggest that a communication strategy that involves collaboration with these grower organisations would empower the WRC to participate much more efficiently and with greater impact in agricultural innovation networks. The paper will elaborate on the findings and discuss partnering frameworks and opportunities to manage perceptions and uptake.

Keywords: agricultural innovation systems, communication strategy, diffusion of innovation, irrigated agriculture, knowledge paths, research organisations, target audiences, water use efficiency

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Authors: Muteeb Ulhaq, Rizwan Latif, Sayed Adnan Qasim, Imran Shafi

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Diesel engines are most efficient and reliable in terms of efficiency, reliability and adaptability. Most of the research and development up till now have been directed towards High-Speed Diesel Engine, for Commercial use. In these engines objective is to optimize maximum acceleration by reducing exhaust emission to meet international standards. In high torque low-speed engines the requirement is altogether different. These types of Engines are mostly used in Maritime Industry, Agriculture industry, Static Engines Compressors Engines etc. Unfortunately due to lack of research and development, these engines have low efficiency and high soot emissions and one of the most effective way to overcome these issues is by efficient combustion in an engine cylinder, the fuel spray atomization process plays a vital role in defining mixture formation, fuel consumption, combustion efficiency and soot emissions. Therefore, a comprehensive understanding of the fuel spray characteristics and atomization process is of a great importance. In this research, we will examine the effects of primary breakup modeling on the spray characteristics under diesel engine conditions. KH-ACT model is applied to cater the effect of aerodynamics in an engine cylinder and also cavitations and turbulence generated inside the injector. It is a modified form of most commonly used KH model, which considers only the aerodynamically induced breakup based on the Kelvin–Helmholtz instability. Our model is extensively evaluated by performing 3-D time-dependent simulations on Open FOAM, which is an open source flow solver. Spray characteristics like Spray Penetration, Liquid length, Spray cone angle and Souter mean diameter (SMD) were validated by comparing the results of Open Foam and Matlab. Including the effects of cavitation and turbulence enhances primary breakup, leading to smaller droplet sizes, decrease in liquid penetration, and increase in the radial dispersion of spray. All these properties favor early evaporation of fuel which enhances Engine efficiency.

Keywords: Kelvin–Helmholtz instability, open foam, primary breakup, souter mean diameter, turbulence

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Adele Pierre, Nadia Amoroso

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Changing climate patterns are resulting in increased in storm severity, challenging traditional methods of managing stormwater runoff. This research compares a system of bioswales to existing curb and gutter infrastructure in a post-industrial streetscape of Hamilton, Ontario. Using the geodesign process, including rule-based set parameters and an integrated approach combining geospatial information with stakeholder input, a section of Ottawa St. North was modelled to show how green infrastructure can ease the burden on aging, combined sewer systems. Qualitative data was gathered from residents of the neighbourhood through field notes, and quantitative geospatial data through GIS and site analysis. Parametric modelling was used to generate multiple design scenarios, each visualizing resulting impacts on stormwater runoff along with their calculations. The selected design scenarios offered both an aesthetically pleasing urban bioswale street-scape system while minimizing and controlling stormwater runoff. Interactive maps, videos and the 3D model were presented for stakeholder comment via ESRI’s (Environmental System Research Institute) web-scene. The results of the study demonstrate powerful tools that can assist landscape architects in designing, collaborating and communicating stormwater strategies.

Keywords: bioswale, geodesign, data-driven and rule-based design, geodesign, GIS, stormwater management

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Belbaly Nassim

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Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

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Authors: Sudhir Kumar Tewatia, Kanishck Tewatia, Anttriksh Tewatia

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Advancements in soil consolidation are discussed, and further improvements are proposed with particular reference to Tewatia’s Y-Y’ Approach, which is called the Settlement versus Rate of Settlement Approach in consolidation. A branch of calculus named Y-Y' (or y versus dy/dx) is suggested (as compared to the common X-Y', x versus dy/dx, dy/dx versus x or Newton-Leibniz branch) that solves some complicated/unsolved theoretical and practical problems in physical sciences (Physics, Chemistry, Mathematics, Biology, and allied sciences) and engineering in an amazingly simple and short manner, particularly when independent variable X is unknown and X-Y' Approach can’t be used. Complicated theoretical and practical problems in 1D, 2D, 3D Primary and Secondary consolidations with non-uniform gradual loading and irregularly shaped clays are solved with elementary school level Y-Y' Approach, and it is interesting to note that in X-Y' Approach, equations become more difficult while we move from one to three dimensions, but in Y-Y' Approach even 2D/3D equations are very simple to derive, solve, and use; rather easier sometimes. This branch of calculus will have a far-reaching impact on understanding and solving the problems in different fields of physical sciences and engineering that were hitherto unsolved or difficult to be solved by normal calculus/numerical/computer methods. Some particular cases from soil consolidation that basically creeps and diffusion equations in isolation and in combination with each other are taken for comparison with heat transfer. The Y-Y’ Approach can similarly be applied in wave equations and other fields wherever normal calculus works or fails. Soil mechanics uses mathematical analogies from other fields of physical sciences and engineering to solve theoretical and practical problems; for example, consolidation theory is a replica of the heat equation from thermodynamics with the addition of the effective stress principle. An attempt is made to give them mathematical analogies.

Keywords: calculus, clay, consolidation, creep, diffusion, heat, settlement

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Authors: Jiazhen Liao, Xiaolan Zeng

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A series of BiOCl nanoplates with different oxygen vacancies (OVs) concentrations were successfully synthesized via a facile solvothermal method. The concentration of OVs of BiOCl can be tuned by the ratios of water/ethylene glycol. Such nanoplates containing oxygen vacancies served as an efficient visible-light-driven photocatalyst for NO oxidation. Compared with pure BiOCl, the enhanced photocatalytic performance was mainly attributed to the introduction of OVs, which greatly enhanced light absorption, promoted electron transfer, activated oxygen molecules. The present work could provide insights into the understanding of the role of OVs in photocatalysts for reference. Combined with characterization analysis, such as XRD（X-ray diffraction）, XPS（X-ray photoelectron spectroscopy), TEM（Transmission Electron Microscopy）, PL（Fluorescence Spectroscopy）, and DFT (Density Functional Theory) calculations, the effect of vacancies on photoelectrochemical properties of BiOCl photocatalysts are shown. Furthermore, the possible reaction mechanisms of photocatalytic NO oxidation were also revealed. According to the results of in situ DRIFTS （ Diffused Reflectance Infrared Fourier Transform Spectroscopy）, various intermediates were produced during different time intervals of NO photodegradation. The possible pathways are summarized below. First, visible light irradiation induces electron-hole pairs on the surface of OV-BOC (BiOCl with oxygen vacancies). Second, photogenerated electrons form superoxide radical with the contacted oxygen. Then, the NO molecules adsorbed on the surface of OV-BOC are attacked by superoxide radical and form nitrate instead of NO₂ (by-products). Oxygen vacancies greatly improve the photocatalytic oxidation activity of NO and effectively inhibit the production of harmful by-products during the oxidation of NO.

Keywords: OVs-BiOCl nanoplate, oxygen vacancies, NO oxidation, photocatalysis

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Authors: Hongyan Chen, Megan Jobson, Andrew J. Masters, Maria Gonzalez-Miquel, Simon Halstead, Mayri Diaz de Rienzo

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Ionic liquids offer excellent advantages over conventional solvents for industrial extraction of metals from aqueous solutions, where such extraction processes bring opportunities for recovery, reuse, and recycling of valuable resources and more sustainable production pathways. Recent research on the use of ionic liquids for extraction confirms their high selectivity and low volatility, but there is relatively little focus on how their properties can be best exploited in practice. This work addresses gaps in research on process modelling and simulation, to support development, design, and optimisation of these processes, focusing on the separation of the highly similar transition metals, cobalt, and nickel. The study exploits published experimental results, as well as new experimental results, relating to the separation of Co and Ni using trihexyl (tetradecyl) phosphonium chloride. This extraction agent is attractive because it is cheaper, more stable and less toxic than fluorinated hydrophobic ionic liquids. This process modelling work concerns selection and/or development of suitable models for the physical properties, distribution coefficients, for mass transfer phenomena, of the extractor unit and of the multi-stage extraction flowsheet. The distribution coefficient model for cobalt and HCl represents an anion exchange mechanism, supported by the literature and COSMO-RS calculations. Parameters of the distribution coefficient models are estimated by fitting the model to published experimental extraction equilibrium results. The mass transfer model applies Newman’s hard sphere model. Diffusion coefficients in the aqueous phase are obtained from the literature, while diffusion coefficients in the ionic liquid phase are fitted to dynamic experimental results. The mass transfer area is calculated from the surface to mean diameter of liquid droplets of the dispersed phase, estimated from the Weber number inside the extractor. New experiments measure the interfacial tension between the aqueous and ionic phases. The empirical models for predicting the density and viscosity of solutions under different metal loadings are also fitted to new experimental data. The extractor is modelled as a continuous stirred tank reactor with mass transfer between the two phases and perfect phase separation of the outlet flows. A multistage separation flowsheet simulation is set up to replicate a published experiment and compare model predictions with the experimental results. This simulation model is implemented in gPROMS software for dynamic process simulation. The results of single stage and multi-stage flowsheet simulations are shown to be in good agreement with the published experimental results. The estimated diffusion coefficient of cobalt in the ionic liquid phase is in reasonable agreement with published data for the diffusion coefficients of various metals in this ionic liquid. A sensitivity study with this simulation model demonstrates the usefulness of the models for process design. The simulation approach has potential to be extended to account for other metals, acids, and solvents for process development, design, and optimisation of extraction processes applying ionic liquids for metals separations, although a lack of experimental data is currently limiting the accuracy of models within the whole framework. Future work will focus on process development more generally and on extractive separation of rare earths using ionic liquids.

Keywords: distribution coefficient, mass transfer, COSMO-RS, flowsheet simulation, phosphonium

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Authors: Zydrunas Kavaliauskas, Aleksandras Iljinas, Liutauras Marcinauskas, Mindaugas Milieska, Vitas Valincius

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The magnetron sputtering deposition method is often used to obtain thin film coatings. The main advantage of magnetron vaporization compared to other deposition methods is the high rate erosion of the cathode material (e.g., copper, aluminum, etc.) and the ability to operate under low-pressure conditions. The structure of the formed coatings depends on the working parameters of the magnetron deposition system, which is why it is possible to influence the properties of the growing film, such as morphology, crystal orientation, and dimensions, stresses, adhesion, etc. The properties of these coatings depend on the distance between the substrate and the magnetron surface, the vacuum depth, the gas used, etc. Using this deposition technology, substrates are most often placed near the anode. The magnetic trap of the magnetrons for localization of electrons in the cathode region is formed using a permanent magnet system that is on the side of the cathode. The scientific literature suggests that, after insertion of a small amount of copper into graphite, the electronic conductivity of graphite increase. The aim of this work is to create thin (up to 300 nm) layers on a graphite surface using a magnetron evaporation method, to investigate the formation peculiarities and microstructure of thin films, as well as the mechanism of copper diffusion into graphite inner layers at different thermal treatment temperatures. The electron scanning microscope was used to investigate the microrelief of the coating surface. The chemical composition is determined using the EDS method, which shows that, with an increase of the thermal treatment of the copper-carbon layer from 200 °C to 400 °C, the copper content is reduced from 8 to 4 % in atomic mass units. This is because the EDS method captures only the amount of copper on the graphite surface, while the temperature of the heat treatment increases part of the copper because of the diffusion processes penetrates into the inner layers of the graphite. The XRD method shows that the crystalline copper structure is not affected by thermal treatment.

Keywords: carbon, coatings, copper, magnetron sputtering

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Authors: Mohammed Ghazwani, Shyma Ali Alshahrani, Zahra Abdu Yousef, Taif Torki Asiri, Ghofran Abdur Rahman, Asma Ali Alshahrani, Umme Hani

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Background and introduction: Piroxicam is a nonsteroidal anti-inflammatory drug characterized by low solubility-high permeability used to reduce pain, swelling, and joint stiffness from arthritis. Hydrotropes are a class of compounds that normally increase the aqueous solubility of insoluble solutes. Aim: The objective of the present research study was to formulate and optimize Piroxicam hydrotropic starch gel using sodium salicylate, sodium benzoate as hydrotropic salts, and potato starch for topical application. Materials and methods: The prepared Piroxicam hydrotropic starch gel was characterized for various physicochemical parameters like drug content estimation, pH, tube extrudability, and spreadability; all the prepared formulations were subjected to in-vitro diffusion studies for six hours in 100 ml phosphate buffer (pH 7.4) and determined gel strength. Results: All formulations were found to be white opaque in appearance and have good homogeneity. The pH of formulations was found to be between 6.9-7.9. Drug content ranged from 96.8%-99.4.5%. Spreadability plays an important role in patient compliance and helps in the uniform application of gel to the skin as gels should spread easily; F4 showed a spreadability of 2.4cm highest among all other formulations. In in vitro diffusion studies, extrudability and gel strength were good with F4 in comparison with other formulations; hence F4 was selected as the optimized formulation. Conclusion: Isolated potato starch was successfully employed to prepare the gel. Hydrotropic salt sodium salicylate increased the solubility of Piroxicam and resulted in a stable gel, whereas the gel prepared using sodium benzoate changed its color after one week of preparation from white to light yellowish. Hydrotropic potato starch gel proposed a suitable vehicle for the topical delivery of Piroxicam.

Keywords: Piroxicam, potato starch, hydrotropic salts, hydrotropic starch gel

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