Search results for: real time stress detection

Authors: Bhawna Chandravanshi, Ramesh Bhonde

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In the present study, we focused on the improvisation of islet survival in hypoxia. The Islet-like cell aggregates (ICAs) derived from Wharton's jelly mesenchymal stem cells (WJ-MSC) were cultured with and without WJ-MSC for 48h in hypoxia and normoxia and tested for their direct trophic effect on β cell survival. The WJ MSCs themselves secreted insulin upon glucose challenge and expressed the pancreatic markers at both transcription and translational level (C-peptide, Insulin, Glucagon and Glut 2). Direct contact of MSCs with ICAs facilitate the highest viability under hypoxia as evidenced by fluorescein diacetate/propidium iodide and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The cytokine analysis of the co-cultured ICAs revealed amplification of anti-inflammatory cytokine-like TGFβ and TNFα accompanied by depletion of pro-inflammatory cytokines. The increment in VEGF and PDGFa was also seen showing their ability to vascularize upon transplantation. This was further accompanied by reduction in total reactive oxygen species, nitric oxide, and super oxide ions and down-regulation of Caspase3, Caspase8, p53 and up regulation of Bcl2 confirming prevention of apoptosis in ICAs. There was a significant reduction in the expression of p38 protein in the presence of MSCs making the ICAs responsive to glucose. Taken together our data demonstrate for the first time that the WJ-MSC expressed pancreatic markers and their supplementation protected engineered islets against hypoxia, oxidative stress, and inflammatory cytokines by inhibiting p38 MAPK protein.

Keywords: hypoxia, islet-like cell aggregates, inflammatory cytokines, oxidative stress

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Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

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Authors: R. Velvarska, A. Vrablik, M. Fiedlerova, R. Cerny

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Near-infrared spectrometry (NIR) was tested as a rapid and alternative tool for determination of biodiesel oxidation stability. A PetroOxy method is standardly used for the determination, but this method is hazardous due to the possibility of explosion and ignition of flammable fuels. The second disadvantage is time consuming. The near-infrared spectrometry served for the development of the calibration model which was composed of 133 real samples (calibration standards). The reference values of these standards were obtained by PetroOxy method. Many chemometric diagnostics were used for the development of the final NIR model with the aim to have accurate prediction of the oxidation stability. The final NIR model was validated by 30 validation standards. The repeatability was determined as well with the acceptable residual standard deviation (8.59 %). The NIR spectrometry has proved to be an accurate alternative method for the determination of biodiesel oxidation stability with advantages as the time and cost saving, non-destructive character of analyzing and the possibility of online monitoring in safe mode.

Keywords: biodiesel, fatty acid methyl ester, NIR, oxidation stability

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Authors: Siddharth Rana

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As we know so far, there are 3 dimensions that we are capable of interpreting and perceiving, and there is a 4th dimension, called time, about which we don’t know much yet. We, as humans, live in the 4th dimension, not the 3rd. We travel 3 dimensionally but cannot yet travel 4 dimensionally; perhaps if we could, then visiting the past and the future would be like climbing a mountain or going down a road. So far, we humans are not even capable of imagining any higher dimensions than the three dimensions in which we can travel. We are the beings of the 4th dimension; we are the beings of time; that is why we can travel 3 dimensionally; however, if, say, there were beings of the 5th dimension, then they would easily be able to travel 4 dimensionally, i.e., they could travel in the 4th dimension as well. Beings of the 5th dimension can easily time travel. However, beings of the 4th dimension, like us, cannot time travel because we live in a 4-D world, traveling 3 dimensionally. That means to ever do time travel, we just need to go to a higher dimension and not only perceive it but also be able to travel in it. However, traveling to the past is not very possible, unlike traveling to the future. Even if traveling to the past were possible, it would be very unlikely that an event in the past would be changed. In this paper, some approaches are provided to define time, our movement in time to the future, some aspects of time travel using dimensions, and how we can perceive a higher dimension.

Keywords: time, dimensions, String theory, relativity

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Authors: Young Yoon, Jinsoo Kim

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The adoption of information and communication technologies (ICT) in all industry is growing under industry 4.0. Many oil companies also are increasingly adopting ICT to improve the efficiency of existing operations, take more accurate and quicker decision making and reduce entire cost by optimization. It is true that ICT is playing an important role in the process of unconventional oil and gas development and companies must take advantage of ICT to gain competitive advantage. In this study, real option approach has been applied to Unconventional gas R&D project to evaluate ICT of them. Many unconventional gas reserves such as shale gas and coal-bed methane(CBM) has developed due to technological improvement and high energy price. There are many uncertainties in unconventional development on the three stage(Exploration, Development, Production). The traditional quantitative benefits-cost method, such as net present value(NPV) is not sufficient for capturing ICT value. We attempted to evaluate the ICT valuation by applying the compound option model; the model is applied to real CBM project case, showing how it consider uncertainties. Variables are treated as uncertain and a Monte Carlo simulation is performed to consider variables effect. Acknowledgement—This work was supported by the Energy Efficiency & Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20152510101880) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-205S1A3A2046684).

Keywords: information and communication technologies, R&D, real option, unconventional gas

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Authors: R. Daira

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The electronic speckle interferometry technique used to measure the deformations of scatterers process is based on the subtraction of interference patterns. A speckle image is first recorded before deformation of the object in the RAM of a computer, after a second deflection. The square of the difference between two images showing correlation fringes observable in real time directly on monitor. The interpretation these fringes to determine the deformation. In this paper, we present experimental results of deformation out of the plane of two samples in aluminum, electronic boards and stainless steel.

Keywords: optical method, holography, interferometry, deformation

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Authors: Sahand Hamed Moeel Ardebil, Zohreh Taebi Noghondari, Mahmood Reza Ghorban Sabbagh

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Gillian Flynn’s Gone Girl, depicts a society in which, as a result of media dominance, the reality is very precarious and difficult to grasp. In Gone Girl, reality and image of reality represented on TV, are challenging to differentiate. Along with reality, individuals’ agency and independence before media and the capitalist rule are called in to question in the novel. In order to expose the unstable nature of reality and an individual’s complicated relationship with media, this study has deployed the ideas of Marxist-media theorist Guy Debord (1931-1992). In his book Society of the Spectacle (1966), Debord delineates a society in which images replace the objective reality, and people are incapable of making real changes. The results of the current study show that despite their efforts, Nick and Amy, the two main characters of the novel, are no more than spectators with very little agency before the media. Moreover, following Debord’s argument about the replacement of reality with images, everyone and every institution in Gone Girl projects an image that does not necessarily embody the objective reality, a fact that makes it very hard to differentiate the real from unreal.

Keywords: agency, Debord, Gone Girl, media studies, society of spectacle, reality

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Authors: Zbigniew Izdebski, Alicja Kozakiewicz, Maciej Białorudzki, Joanna Mazur

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Work is an extremely important part of everyone's life and affects functioning in daily life. Healthcare workers (HCW) are suffering from negative actions in and out of the workplace, such as harassment, abuse, long working hours, mental suffering, exhaustion, and professional burnout. Staff burnout is detrimental not only in terms of individual employees but also to working with patients and to the healthcare institution as a whole. The purpose of this study was to explore the level of professional burnout among HCW working in medical institutions during the COVID-19 pandemic in Poland. The extent to which selected sociodemographic factors and perceived stress increase the risk of professional burnout was assessed. In addition, the frequency of use of professional psychological help and less formal support groups by HCW in relation to the level of professional burnout was presented. The survey was conducted as part of a larger project on the humanization of medicine and clinical communication from February-April 2022. This study used a self-administered online survey (CAWI) technique and PAPI (pen and paper interview) technique. The BAT-12 scale was used to measure burnout, the PSS-4 scale was used to measure stress, and questions formulated by the research team were also used. For the purpose of analysis, the sample was limited to 2196 HCWs who worked on a daily basis with patients during the COVID-19 pandemic. Frequency distributions were analyzed, and multivariate logistic regression was performed. The mean scores (scores) of job burnout as measured by the BAT-12 scale ranged among the professional groups from 2.15(0.69) to 2.30 (0.69) and remained highest for the nurses' group. The groups differed significantly in levels of burnout (chi-sq=17.719; d.f.=8; p<0.023). In the final model, raised stress most likely increased the risk of burnout (OR=3.88; 95%CI <3.13-3.81>; p<0,001). Other significant predictors of burnout included: traumatic work-related experience (OR=1.91, p<0.001), mobbing (OR=1.83, p<0.001), and a higher workload than before the pandemic (OR=1.41, p=0.002). Only 7% of respondents decided to use various forms of psychological support during the pandemic. HCW experiences challenges in dealing with an unpredictable pandemic. Limited preparedness can lead to physical and psychological problems such as high-stress levels, anxiety, fear, helplessness, hopelessness, anger and stigma. The workload can lead to professional burnout, as well as threaten patient safety.

Keywords: burnout, work, healthcare, healthcare worker, stress

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Authors: S. H. Bae, D. W. Cho, W. B. Jeong, J. R. Cho

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Fatigue fracture of an aluminum welded structure is a phenomenon frequently occurring from pores in a weld. In order to grasp the state of the welded structure in operation in real time, the acceleration signal of the structure is measured. At this time, the vibration characteristic of the signal according to the fatigue load is an important parameter of the state diagnosis. This paper was an experimental study on the variation of vibration characteristics of welded beams with vibration aging (especially bending vibration). First simple beams were produced according to welding conditions. Each beam was vibrated and measured beam's PSD (power spectral density) according to the degree of aging. Also, modal testing was conducted to compare the transfer functions of welded beams. Testing result shows that the natural frequencies of the beam changed with the vibration aging due to the change of stiffness in welding part and its stiffness was estimated by the finite element method.

Keywords: modal testing, natural frequency, vibration aging, welded structure

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Authors: Vadim V. Yanshole, Lyudmila V. Yanshole, Alexey S. Kiryutin, Timofey D. Verkhovod, Yuri P. Tsentalovich

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Cataract, or clouding of the eye lens, is the leading cause of vision impairment in the world. The lens tissue have very specific structure: It does not have vascular system, the lens proteins – crystallins – do not turnover throughout lifespan. The protection of lens proteins is provided by the metabolites which diffuse inside the lens from the aqueous humor or synthesized in the lens epithelial layer. Therefore, the study of changes in the metabolite composition of a cataractous lens as compared to a normal lens may elucidate the possible mechanisms of the cataract formation. Quantitative metabolomic profiles of normal and cataractous human lenses were obtained with the combined use of high-frequency nuclear magnetic resonance (NMR) and ion-pairing high-performance liquid chromatography with high-resolution mass-spectrometric detection (LC-MS) methods. The quantitative content of more than fifty metabolites has been determined in this work for normal aged and cataractous human lenses. The most abundant metabolites in the normal lens are myo-inositol, lactate, creatine, glutathione, glutamate, and glucose. For the majority of metabolites, their levels in the lens cortex and nucleus are similar, with the few exceptions including antioxidants and UV filters: The concentrations of glutathione, ascorbate and NAD in the lens nucleus decrease as compared to the cortex, while the levels of the secondary UV filters formed from primary UV filters in redox processes increase. That confirms that the lens core is metabolically inert, and the metabolic activity in the lens nucleus is mostly restricted by protection from the oxidative stress caused by UV irradiation, UV filter spontaneous decomposition, or other factors. It was found that the metabolomic composition of normal and age-matched cataractous human lenses differ significantly. The content of the most important metabolites – antioxidants, UV filters, and osmolytes – in the cataractous nucleus is at least ten fold lower than in the normal nucleus. One may suppose that the majority of these metabolites are synthesized in the lens epithelial layer, and that age-related cataractogenesis might originate from the dysfunction of the lens epithelial cells. Comprehensive quantitative metabolic profiles of the human eye lens have been acquired for the first time. The obtained data can be used for the analysis of changes in the lens chemical composition occurring with age and with the cataract development.

Keywords: cataract, lens, NMR, LC-MS, metabolome

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Authors: Zintle Kolo, Ndiko Ludidi

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The enzymatic activity of p-coumarate 3-hydroxylase (C3H) synthesize caffeic acid from p-coumaric acid. We recently showed that exogenously applied caffeic acid confers salinity tolerance in soybean (Glycine max) by inducing antioxidant enzymatic activity to promote enhanced scavenging or reactive oxygen species, thus limiting salinity-induced oxidative stress. Recent evidence also establishes that pre-treatment of plants with exogenously supplied caffeic acid improves plant tolerance to osmotic stress by improving plant antioxidant capacity and enhancing biosynthesis of compatible solutes. We aimed to identify a C3H in maize (Zea mays) and evaluate the effect of drought on the spatial and temporal expression of the gene encoding the candidate maize C3H (ZmC3H). Primary sequence analysis shows that ZmC3H shares 71% identity with an Arabidopsis thaliana C3H that is implicated in the control of Arabidopsis cell expansion, growth, and responses to stress. In silico ZmC3H promoter analysis reveals the presence of cis-acting elements that interact with transcription factors implicated in plant responses to drought. Spatial expression analysis by semi-quantitative RT-PCR shows that ZmC3H is expressed in both leaves and roots under normal conditions. However, drought represses the expression of ZmC3H in leaves whereas it up-regulates its expression in roots. These changes in ZmC3H expression correlate with the changes in the content of caffeic acid in maize in response to drought. We illustrate the implications of these changes in the expression of the gene in relation to maize responses to drought and discuss the potential of regulating caffeic acid biosynthesis towards genetic improvement of maize tolerance to drought stress. These findings have implications for food security because of the potential of the implications of the study for drought tolerance in maize.

Keywords: caffeic acid, drought-responsive expression, maize drought tolerance, p-coumarate 3-hydroxylase

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Jochen Nelles, Susanne Kohns, Julia Spies, Friederike Schmitz-Buhl, Roland Thietje, Christopher Brandl, Alexander Mertens, Christopher M. Schlick

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Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.

Keywords: assistance robot, human-robot interaction, motion capture, stress-strain-concept, surface electromyography, tetraplegia

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Authors: Ravi Raghav Sonani, Niraj Kumar Singh, Jitendra Kumar, Datta Madamwar

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Phycobiliproteins (PBPs) are light harvesting proteins showing very strong absorbance and fluorescence in the visible range of the solar spectrum. Phycoerythrin (PE) and phycocyanin (PC) are majorly found PBPs in the cyanobacteria and red algae. In the present study, we have investigated the reactive oxygen species (ROS)-averting capacity of purified PE and PC of cyanobacterial origin. Furthermore, the possibility - whether the ROS-averting potential of PBPs can be explored in the therapeutics of oxidative stress associated physiological anomalies including aging and neurodegenerative diseases. The nematode Caenorhabditis elegans has been used as model organism in this study. PE and PC treatment moderated normal aging and associated physiological functionalities like pharyngeal pumping and locomotion of C. elegans. Moreover, PE-treatment enhanced the stress (oxidative and heat) tolerance upon PE and PC treatment. Specifically, PE treatment was also noted to moderate the progression of Alzheimer’s disease in transgenic C. elegans CL4176. However, PC-treatment curtailed the polyQ aggregation mediated proteotoxicity in C. elegans AM141 (Huntington disease model) under stressed (paraquat stress) as well as normal conditions. The effectiveness of PE and PC in expanding the lifespan of mutant C. elegans knockout for some up- (daf 16) and down- (daf-2 and age-1) stream regulators of insulin/IGF-1 signalling (IIS) shows the independency of their effects from DAF-2–AGE-1–DAF-16 signalling pathway. In conclusion, the present report demonstrates the anti-aging and neuro-protective potential of cyanobacterial PE and PC.

Keywords: phycobiliproteins, aging, alzheimer, huntington, C. elegans

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Authors: Lukasz Grabowski, Tytus Tulwin, Michal Geca, P. Karpinski

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This paper presents the radial aircraft engine model which has been created in AVL Boost software. This model is a one-dimensional physical model of the engine, which enables us to investigate the impact of an ignition system design on engine performance (power, torque, fuel consumption). In addition, this model allows research under variable environmental conditions to reflect varied flight conditions (altitude, humidity, cruising speed). Before the simulation research the identifying parameters and validating of model were studied. In order to verify the feasibility to take off power of gasoline radial aircraft engine model, some validation study was carried out. The first stage of the identification was completed with reference to the technical documentation provided by manufacturer of engine and the experiments on the test stand of the real engine. The second stage involved a comparison of simulation results with the results of the engine stand tests performed on a WSK ’PZL-Kalisz’. The engine was loaded by a propeller in a special test bench. Identifying the model parameters referred to a comparison of the test results to the simulation in terms of: pressure behind the throttles, pressure in the inlet pipe, and time course for pressure in the first inlet pipe, power, and specific fuel consumption. Accordingly, the required coefficients and error of simulation calculation relative to the real-object experiments were determined. Obtained the time course for pressure and its value is compatible with the experimental results. Additionally the engine power and specific fuel consumption tends to be significantly compatible with the bench tests. The mapping error does not exceed 1.5%, which verifies positively the model of combustion and allows us to predict engine performance if the process of combustion will be modified. The next conducted tests verified completely model. The maximum mapping error for the pressure behind the throttles and the inlet pipe pressure is 4 %, which proves the model of the inlet duct in the engine with the charging compressor to be correct.

Keywords: 1D-model, aircraft engine, performance, validation

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Authors: U. Pruthviraj, Praveen Kumar R. A. K. Athul, K. V. Gangadharan, S. Rao Shrikantha

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An open source based autonomous unmanned marine surface vehicle (UMSV) is developed for some of the marine applications such as pollution control, environmental monitoring and thermal imaging. A double rotomoulded hull boat is deployed which is rugged, tough, quick to deploy and moves faster. It is suitable for environmental monitoring, and it is designed for easy maintenance. A 2HP electric outboard marine motor is used which is powered by a lithium-ion battery and can also be charged from a solar charger. All connections are completely waterproof to IP67 ratings. In full throttle speed, the marine motor is capable of up to 7 kmph. The motor is integrated with an open source based controller using cortex M4F for adjusting the direction of the motor. This UMSV can be operated by three modes: semi-autonomous, manual and fully automated. One of the channels of a 2.4GHz radio link 8 channel transmitter is used for toggling between different modes of the USMV. In this electric outboard marine motor an on board GPS system has been fitted to find the range and GPS positioning. The entire system can be assembled in the field in less than 10 minutes. A Flir Lepton thermal camera core, is integrated with a 64-bit quad-core Linux based open source processor, facilitating real-time capturing of thermal images and the results are stored in a micro SD card which is a data storage device for the system. The thermal camera is interfaced to an open source processor through SPI protocol. These thermal images are used for finding oil spills and to look for people who are drowning at low visibility during the night time. A Real Time clock (RTC) module is attached with the battery to provide the date and time of thermal images captured. For the live video feed, a 900MHz long range video transmitter and receiver is setup by which from a higher power output a longer range of 40miles has been achieved. A Multi-parameter probe is used to measure the following parameters: conductivity, salinity, resistivity, density, dissolved oxygen content, ORP (Oxidation-Reduction Potential), pH level, temperature, water level and pressure (absolute).The maximum pressure it can withstand 160 psi, up to 100m. This work represents a field demonstration of an open source based autonomous navigation system for a marine surface vehicle.

Keywords: open source, autonomous navigation, environmental monitoring, UMSV, outboard motor, multi-parameter probe

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Authors: Mohammad Ranjbaran Madiseh

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In this research, an experimental apparatus has been developed for observing interfacial stability and deformation of multilayer pressure-driven channel flows. The interface instability of the co-extrusion flow of polyethylene and polypropylene is studied experimentally in a slit geometry. By investigating the growing interfacial wave (IW) and tensile stress of extrudate samples, a relationship between interfacial instability (II) and mechanical properties of polypropylene (PP) and high-density polyethylene (HDPE) has been established. It is shown that the mechanism of interfacial strength is related to interfacial instabilities as well as interfacial strength. It is shown that there is an ability to forecast the quality of final products in the co-extrusion process. In this study, it is found that the instability is controlled by its dominant wave number, which is associated with maximum tensile stress at the interface.

Keywords: interfacial instability, interfacial strength, wave number, interfacial wave

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Authors: Gurfateh Singh, Mu Khan, Razia Khanam, Govind Mohan

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Objective: The present study has been designed to investigate the beneficial role of Fenofibrate & Clofibrate in attenuated the cardioprotective effect of ischemic preconditioning (IPC) in hyperlipidemic rat hearts. Materials & Methods: Experimental hyperlipidemia was produced by feeding high fat diet to rats for a period of 28 days. Isolated langendorff’s perfused normal and hyperlipidemic rat hearts were subjected to global ischemia for 30 min followed by reperfusion for 120 min. The myocardial infarct size was assessed macroscopically using triphenyltetrazolium chloride staining. Coronary effluent was analyzed for lactate dehydrogenase (LDH) and creatine kinase-MB release to assess the extent of cardiac injury. Moreover, the oxidative stress in heart was assessed by measuring thiobarbituric acid reactive substance, superoxide anion generation and reduced form of glutathione. Results: The ischemia-reperfusion (I/R) has been noted to induce oxidative stress by increasing TBARS, superoxide anion generation and decreasing reduced form of glutathione in normal and hyperlipidemic rat hearts. Moreover, I/R produced myocardial injury, which was assessed in terms of increase in myocardial infarct size, LDH and CK-MB release in coronary effluent and decrease in coronary flow rate in normal and hyperlipidemic rat hearts. In addition, the hyperlipidemic rat hearts showed enhanced I/R-induced myocardial injury with high degree of oxidative stress as compared with normal rat hearts subjected to I/R. Four episodes of IPC (5 min each) afforded cardioprotection against I/R-induced myocardial injury in normal rat hearts as assessed in terms of improvement in coronary flow rate and reduction in myocardial infarct size, LDH, CK-MB and oxidative stress. On the other hand, IPC mediated myocardial protection against I/R-injury was abolished in hyperlipidemic rat hearts. However, Treatment with Fenofibrate (100 mg/kg/day, i.p.), Clofibrate (300mg/kg/day, i.p.) as a agonists of PPAR-α have not affected the cardioprotective effect of IPC in normal rat hearts, but its treatment markedly restored the cardioprotective potentials of IPC in hyperlipidemic rat hearts. Conclusion: It is noted that the high degree of oxidative stress produced in hyperlipidemic rat heart during reperfusion and consequent down regulation of PPAR-α may be responsible to abolish the cardioprotective potentials of IPC.

Keywords: Hyperlipidemia, ischemia-reperfusion injury, ischemic preconditioning, PPAR-α

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Muhammad Naeem Chaudhry, Fahim Nawaz, Rana Nauman Shabbir

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New strategies aimed at increasing the resilience of crop plants to the negative effects of climate change represent important research priorities of plant scientists. The use of soil microorganisms to alleviate abiotic stresses like drought has gained particular importance in recent past. A field experiment was planned to investigate the effect of phosphorous solubilizing bacteria on yield and seed quality of Camelina (Camelina sativa L.) under water deficit conditions. The study was conducted at Agronomic Research Farm, University College of Agriculture and Environmental Sciences, The Islamia University Bahawalpur, during 4th week of November, 2013. The available seeds of Camelina sativa were inoculated with two bacterial strains (pseudomonas and Bacillus spp.) and grown under various water stress levels i.e. D0, (four irrigations), D3 (three irrigation), D2 (two irrigations), and D1 (one irrigation). The results revealed that drought stress significantly reduced the plant growth and yield, consequently reducing protein contents and oil concentration in camelina. The exposure to drought stress decreased plant height (16%), plant population (27%), number of fertile branches (41-59%), number of pods per plant (35%) and seed per pod (33%). Drought stress also exerted a negative impact on yield characteristics by reducing the 1000-seed weight (65%), final seed yield (52%), biological yield (22%) and harvest index (39%) of camelina. However, the inoculation of seeds with Pseudomonas and Bacillus spp. promoted the plant growth characterized by increased plant height and enhanced plant population. It was noted that inoculation of seeds with Pseudomonas resulted in the maximum plant population (113.4 cm), primary branches (19 plant-1), and number of pods (664 plant-1), whereas Bacillus inoculation resulted in maximum plant height (113.4 cm), seeds per pod (15.9), 1000-seed weight (1.85 g), and seed yield (3378.8 kg ha-1). Moreover, the inoculation with Bacillus also significantly improved the quality attributes of camelina and gave 3.5% and 2.1% higher oil contents than Pseudomonas and control (no-inoculation), respectively. Similarly, the same strain also resulted in maximum protein contents (33.3%). Our results confirmed the hypothesis that inoculation of seeds with phosphorous solubilizing bacterial strains is an effective, viable and environment-friendly approach to improve yield and quality of camelina under water deficit conditions. However, further studies are suggested to investigate the physiological and molecular processes, stimulated by bacterial strains, for increasing drought tolerance in food crops.

Keywords: Camelina, drought stress, phosphate solubilizing bacteria, seed quality

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Authors: Hailemariam Solomon, Taye Tadesse, Daniel Nadew, Firezer Girma

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Sorghum is an important crop in semi-arid regions and has shown resilience to drought stress. However, recurrent drought is affecting its productivity. Therefore, it is necessary to explore genes that contribute to drought stress adaptation to increase sorghum productivity. The aim of this study is to evaluate and determine the effect of root system traits, specifically root angle, on drought stress adaptation and grain yield performance in sorghum genotypes. A total of 428 sorghum genotypes from the Ethiopian breeding program were evaluated in three drought-stress environments. Field trials were conducted using a row-column design with three replications. Root system traits were phenotyped using a high-throughput phenotyping platform and analyzed using a row-column design with two replications. Data analysis was performed using R software and regression analysis. The study found significant variations in root system architecture among the sorghum genotypes. Non-stay-green genotypes had a grain yield ranging from 1.63 to 3.1 tons/ha, while stay-green genotypes had a grain yield ranging from 2.4 to 2.9 tons/ha. The analysis of root angle showed that non-stay-green genotypes had an angle ranging from 8.0 to 30.5 degrees, while stay-green genotypes had an angle ranging from 12.0 to 29.0 degrees. Improved varieties exhibited angles between 14.04 and 19.50 degrees. Positive and significant correlations were observed between leaf areas and shoot dry weight, as well as between leaf width and shoot dry weight. Negative correlations were observed between root angle and leaf area, as well as between root angle and root length. This research highlights the importance of root system architecture, particularly root angle traits, in enhancing grain yield production in drought-stressed conditions. It also establishes an association between root angle and grain yield traits for maximizing sorghum productivity.

Keywords: roor sysytem architecture, root angle, narrow root angle, wider root angle, drought

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Authors: Y. T. Gebreslassie, Abrha Tadesse, R. C. Saini, Rishi Pal

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Caffeine, known chemically as 3,7-dihydro-1,3,7-trimethyl-1H-purine-2,6-dione, is a naturally occurring alkaloid classified as an N-methyl derivative of xanthine. Given its widespread use in coffee and other caffeine-containing products, it is the most commonly consumed psychoactive substance in everyday human life. This research aimed to develop a cost-effective, sensitive, and easily manufacturable sensor for the detection of caffeine. Antraquinone-modified carbon paste electrode (AQMCPE) was fabricated, and the electrochemical behavior of caffeine on this electrode was investigated using cyclic voltammetry (CV) and square wave voltammetry (SWV) in a solution of 0.1M perchloric acid at pH 0.56. The modified electrode displayed enhanced electrocatalytic activity towards caffeine oxidation, exhibiting a two-fold increase in peak current and an 82 mV shift of the peak potential in the negative direction compared to an unmodified carbon paste electrode (UMCPE). Exploiting the electrocatalytic properties of the modified electrode, SWV was employed for the quantitative determination of caffeine. Under optimized experimental conditions, a linear relationship between peak current and concentration was observed within the range of 2.0 x 10⁻⁶ to 1.0× 10⁻⁴ M, with a correlation coefficient of 0.998 and a detection limit of 1.47× 10⁻⁷ M (signal-to-noise ratio = 3). Finally, the proposed method was successfully applied to the quantitative analysis of caffeine in pharmaceutical formulations, yielding recovery percentages ranging from 95.27% to 106.75%.

Keywords: antraquinone-modified carbon paste electrode, caffeine, detection, electrochemical sensor, quantitative analysis

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Authors: Xiao Chen, Xiaoying Kong, Min Xu

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This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing

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Authors: N. F. Hanna, A. M. Haridy

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One of the main drawbacks of the Modal Pushover Analysis (MPA) is the need to perform nonlinear time-history analysis, which complicates the analysis method and time. A simplified version of the MPA has been proposed based on the concept of the inelastic deformation ratio. Furthermore, the effect of the higher modes of vibration is considered by assuming linearly-elastic responses, which enables the use of standard elastic response spectrum analysis. In this thesis, the simplified MPA (SMPA) method is applied to determine the target global drift and the inter-story drifts of steel frame building. The effect of the higher vibration modes is considered within the framework of the SMPA. A comprehensive survey about the inelastic deformation ratio is presented. After that, a suitable expression from literature is selected for the inelastic deformation ratio and then implemented in the SMPA. The estimated seismic demands using the SMPA, such as target drift, base shear, and the inter-story drifts, are compared with the seismic responses determined by applying the standard MPA. The accuracy of the estimated seismic demands is validated by comparing with the results obtained by the nonlinear time-history analysis using real earthquake records.

Keywords: modal analysis, pushover analysis, seismic performance, target displacement

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Authors: Jurriaan Gillissen

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This work is concerned with stabilizing the numerical integration of the Navier-Stokes equation (NSE), backwards in time. Applications involve the detection of sources of, e.g., sound, heat, and pollutants. Stable reverse numerical integration of parabolic differential equations is also relevant for image de-blurring. While the literature addresses the reverse integration problem of the advection-diffusion equation, the problem of numerical reverse integration of the NSE has, to our knowledge, not yet been addressed. Owing to the presence of viscosity, the NSE is irreversible, i.e., when going backwards in time, the fluid behaves, as if it had a negative viscosity. As an effect, perturbations from the perfect solution, due to round off errors or discretization errors, grow exponentially in time, and reverse integration of the NSE is inherently unstable, regardless of using an implicit time integration scheme. Consequently, some sort of filtering is required, in order to achieve a stable, numerical, reversed integration. The challenge is to find a filter with a minimal adverse affect on the accuracy of the reversed integration. In the present work, we explore an adjoint gradient method (AGM) to achieve this goal, and we apply this technique to two-dimensional (2D), decaying turbulence. The AGM solves for the initial velocity field u0 at t = 0, that, when integrated forward in time, produces a final velocity field u1 at t = 1, that is as close as is feasibly possible to some specified target field v1. The initial field u0 defines a minimum of a cost-functional J, that measures the distance between u1 and v1. In the minimization procedure, the u0 is updated iteratively along the gradient of J w.r.t. u0, where the gradient is obtained by transporting J backwards in time from t = 1 to t = 0, using the adjoint NSE. The AGM thus effectively replaces the backward integration by multiple forward and backward adjoint integrations. Since the viscosity is negative in the adjoint NSE, each step of the AGM is numerically stable. Nevertheless, when applied to turbulence, the AGM develops instabilities, which limit the backward integration to small times. This is due to the exponential divergence of phase space trajectories in turbulent flow, which produces a multitude of local minima in J, when the integration time is large. As an effect, the AGM may select unphysical, noisy initial conditions. In order to improve this situation, we propose two remedies. First, we replace the integration by a sequence of smaller integrations, i.e., we divide the integration time into segments, where in each segment the target field v1 is taken as the initial field u0 from the previous segment. Second, we add an additional term (regularizer) to J, which is proportional to a high-order Laplacian of u0, and which dampens the gradients of u0. We show that suitable values for the segment size and for the regularizer, allow a stable reverse integration of 2D decaying turbulence, with accurate results for more then O(10) turbulent, integral time scales.

Keywords: time reversed integration, parabolic differential equations, adjoint gradient method, two dimensional turbulence

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Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

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Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

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Authors: Faisal Al Yahmadi, Muhammad R. Ahmed

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Electric power is a fundamental necessity in the 21^st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.

Keywords: smart grid network, security, threats, vulnerabilities

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Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: Young-Hun Lee, Tae-Gwan Kim, Jong-Kyu Kim, Young-Chul Park

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In this study, Spring safety valve Heat - structure coupled analysis was carried out. Full analysis procedure and performing thermal analysis at a maximum temperature, them to the results obtained through to give an additional load and the pressure on the valve interior, and Disc holder Heat-Coupled structure Analysis was carried out. Modeled using a 3D design program Solidworks, For the modeling of the safety valve was used 3D finite element analysis program ANSYS. The final result to be obtained through the Analysis examined the stability of the maximum displacement and the maximum stress to the valve internal components occurring in the high-pressure conditions.

Keywords: finite element method, spring safety valve, gap, stress, strain, deformation

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Authors: Agata Twardoch

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The processes of commodification of real estate and changes in housing markets have led to a situation where the prices of free market housing in European capitals are significantly higher than the purchasing value of average wages. This phenomenon has many negative social and spatial consequences. At the same time, the attractiveness of real estate as an asset makes these processes progress. Out of concern for sustainable social development, city authorities apply solutions to balance the burdensome effects of codification of housing. One of them is a social provision for housing investments. The article presents a comparative study of solutions applied in selected European capitals, on the example of Warsaw, Paris, London, Berlin, Copenhagen, and Vienna. The study was conducted along with works on expert report for the master plan for Warsaw. The forms of commissions applied in Local Planning Acts were compared, with particular reference to spatial solutions. The results of the analysis made it possible to determine common features of the solutions applied and to establish recommendations for further practice. Major findings of the study indicate that requirement of social provision is achievable in spatial planning documents. Study shows that application of social provision in private housing investments is a useful tool in housing policy against commodification.

Keywords: affordable housing, housing provision, spatial planning, sustainable social development

Procedia PDF Downloads 180