Search results for: supply chain delivery models

Authors: Madhvi Bhayani

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Introduction: Due to the rapid pace of urbanization, the urban health issues have become one of the significant threats to future development in India. It also poses serious repercussions on the citizen’s health. As urbanization in India is increasing at an unprecedented rate and it has generated the urban health crisis among the city dwellers especially the urban poor. The increasing proportion of the urban poor and vulnerable to the health indicators worse than the rural counterparts, they face social and financial barriers in accessing healthcare services and these conditions make human health at risk. The Local as well as the State and National governments are alike tackling with the challenges of urbanization as it has become very essential for the government to provide the basic necessities and better infrastructure that make life in cities safe and healthy. Thus, the paper argues that if no major realistic steps are taken with immediate effect, the citizens will face a huge burden of health hazards. Aim: This paper attempts to analyze the current infrastructure, government planning, and its future policy, it also discusses the challenges and outcomes of urbanization on health and its impact on it and it will also predict the future trend with regard to disease burden in the urban areas. Methods: The paper analyzes on the basis of the secondary data by taking into consideration the connection between the Rapid Urbanization and Public Health Challenges, health and health care system and its services delivery to the citizens especially to the urban poor. Extensive analyses of government census reports, health information and policy, the government health-related schemes, urban development and based on the past trends, the future status of urban infrastructure and health outcomes are predicted. The social-economic and political dimensions are also taken into consideration from regional, national and global perspectives, which are incorporated in the paper to make realistic predictions for the future. Findings and Conclusion: The findings of the paper show that India suffers a lot due to the double burden of rapidly increasing in diseases and also growing health inequalities and disparities in health outcomes. Existing tools of governance of urban health are falling short to provide the better health care services. They need to strengthen the collaboration and communication among the state, national and local governments and also with the non-governmental partners. Based on the findings the policy implications are then described and areas for future research are defined.

Keywords: health care, urbanization, urban health, service delivery

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Authors: Raghabendra Yadav, Baochun Chen, Huihui Yuan, Zhibin Lian

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Concrete Filled Steel Tube (CFST) columns are widely used in Civil Engineering Structures due to their abundant properties. CFST-RC column is a built up column in which CFST members are connected with RC web. The CFST-RC column has excellent static and earthquake resistant properties, such as high strength, high ductility and large energy absorption capacity. CFST-RC columns have been adopted as piers in Ganhaizi Bridge in high seismic risk zone with a highest pier of 107m. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. Under cyclic loading, the hysteretic performance of CFST-RC columns, such as failure modes, ductility, load displacement hysteretic curves, energy absorption capacity, strength and stiffness degradation are studied in this paper.

Keywords: CFST, cyclic load, Ganhaizi bridge, seismic performance

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Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou

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In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks

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Authors: Sukran Acikel, Mehmet Ekmekci, Otgonbayar Namkhai

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Lignite coal fields in western Turkey generally occurs in tensional Neogene basins bordered by major faults. Karacahisar coal field in Mugla province of western Turkey is a large Neogene basin filled with alternation of silisic and calcerous layers. The basement of the basin is composed of mainly karstified carbonate rocks of Mesozoic and schists of Paleozoic age. The basement rocks are exposed at highlands surrounding the basin. The basin fill deposits forms shallow, low yield and local aquifers whereas karstic carbonate rock masses forms the major aquifer in the region. The karstic aquifer discharges through a spring zone issuing at intersection of two major faults. Municipal water demand in Bodrum city, a touristic attraction area is almost totally supplied by boreholes tapping the karstic aquifer. A well field has been constructed on the eastern edge of the coal basin, which forms a ridge separating two Neogene basins. A major concern was raised about the plausible impact of mining activities on groundwater system in general and on water supply well field in particular. The hydrogeological studies carried out in the area revealed that the coal seam is located below the groundwater level. Mining operations will be affected by groundwater inflow to the pits, which will require dewatering measures. Dewatering activities in mine sites have two-sided effects: a) lowers the groundwater level at and around the pit for a safe and effective mining operation, b) continuous dewatering causes expansion of cone of depression to reach a spring, stream and/or well being utilized by local people, capturing their water. Plausible effect of mining operations on the flow of the spring zone was another issue of concern. Therefore, a detailed representative hydrogeological conceptual model of the site was developed on the basis of available data and field work. According to the hydrogeological conceptual model, dewatering of Neogene layers will not hydraulically affect the water supply wells, however, the ultimate perimeter of the open pit will expand to intersect the well field. According to the conceptual model, the coal seam is separated from the bottom by a thick impervious clay layer sitting on the carbonate basement. Therefore, the hydrostratigraphy does not allow a hydraulic interaction between the mine pit and the karstic carbonate rock aquifer. However, the structural setting in the basin suggests that deep faults intersecting the basement and the Neogene sequence will most probably carry the deep groundwater up to a level above the bottom of the pit. This will require taking necessary measure to lower the piezometric level of the carbonate rock aquifer along the faults. Dewatering the carbonate rock aquifer will reduce the flow to the spring zone. All findings were put together to recommend a strategy for safe and effective mining operation.

Keywords: conceptual model, dewatering, groundwater, mining operation

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Authors: A. Sgobba, C. Meskell

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The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.

Keywords: demand, energy system integration, load, manufacturing, national grid, renewable energy sources

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Authors: M. G. Smitha, M. V. Murugendrappa

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Perovskite manganite La_0.7Ca_0.3MnO₃ was synthesized by Sol-gel method. Polymerization of pyrrole was carried by in-situ polymerization method. The composite of pyrrole (Py)/La_0.7Ca_0.3MnO₃ composite in the presence of oxidizing agent ammonium per sulphate to synthesize polypyrrole (PPy)/La_0.7Ca_0.3MnO₃ (LCM) composite was carried out by the same in-situ polymerization method. The PPy/LCM composites were synthesized with varying compositions like 10, 20, 30, 40, and 50 wt.% of LCM in Py. The surface morphologies of these composites were analyzed by using scanning electron microscope (SEM). The images show that LCM particles are embedded in PPy chain. The impedance measurement of PPy/LCM at different temperature ranges from 30 to 180 °C was studied using impedance analyzer. The study shows that impedance is frequency and temperature dependent and it is found to decrease with increase in frequency and temperature.

Keywords: polypyrrole, sol gel, impedance, composites

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Authors: Farid Gaci, Zoubir Nemouchi

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A numerical study of laminar and turbulent fluid flows in 90° bend of square section was carried out. Three-dimensional meshes, based on hexahedral cells, were generated. The QUICK scheme was employed to discretize the convective term in the transport equations. The SIMPLE algorithm was adopted to treat the velocity-pressure coupling. The flow structure obtained showed interesting features such as recirculation zones and counter-rotating pairs of vortices. The performance of three different turbulence models was evaluated: the standard k- ω model, the SST k-ω model and the Reynolds Stress Model (RSM). Overall, it was found that, the multi-equation model performed better than the two equation models. In fact, the existence of four pairs of counter rotating cells, in the straight duct upstream of the bend, were predicted by the RSM closure but not by the standard eddy viscosity model nor the SST k-ω model. The analysis of the results led to a better understanding of the induced three dimensional secondary flows and the behavior of the local pressure coefficient and the friction coefficient.

Keywords: curved duct, counter-rotating cells, secondary flow, laminar, turbulent

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Authors: Sung-Min Kim, Joon-Hong Park, Hyuk Choi

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This study is focused on the comparative analysis and improvement to grasp the flow characteristic of the anti-splash device located under the P/V valve and new concept design models using the CFD. The P/V valve located upper deck to solve the pressure rising and vacuum condition of inner tank of the liquid cargo ships occurred oil outflow accident by transverse and longitudinal sloshing force. Anti-splash device is fitted to improve and prevent this problem in the shipbuilding industry, but the oil outflow accidents are still reported by ship owners. Thus, 4 types of new design model are presented by this study, and then comparative analysis is conducted with new models and existing model. Mostly the key criterion of this problem is flux in the outlet of the anti-splash device. Therefore, the flow and velocity are grasped by transient analysis, and then it decided optimum model and design parameters to develop model. Later, it is needed to develop an anti-splash device by flow test to get certification and verification using experiment equipments.

Keywords: anti-splash device, P/V valve, sloshing, CFD

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Authors: Iris Xiaohong Quan

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The global digital health market reached 175 billion U.S. dollars in 2019, and is expected to grow at about 25% CAGR to over 650 billion USD by 2025. Different terms such as digital health, e-health, mHealth, telehealth have been used in the field, which can sometimes cause confusion. The term digital health was originally introduced to refer specifically to the use of interactive media, tools, platforms, applications, and solutions that are connected to the Internet to address health concerns of providers as well as consumers. While mHealth emphasizes the use of mobile phones in healthcare, telehealth means using technology to remotely deliver clinical health services to patients. According to FDA, “the broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine.” Some researchers believe that digital health is nothing else but the cultural transformation healthcare has been going through in the 21st century because of digital health technologies that provide data to both patients and medical professionals. As digital health is burgeoning, but research in the area is still inadequate, our paper aims to clear the definition confusion and provide an overall picture of digital health companies. We further investigate how business models are designed and differentiated in the emerging digital health sector. Both quantitative and qualitative methods are adopted in the research. For the quantitative analysis, our research data came from two databases Crunchbase and CBInsights, which are well-recognized information sources for researchers, entrepreneurs, managers, and investors. We searched a few keywords in the Crunchbase database based on companies’ self-description: digital health, e-health, and telehealth. A search of “digital health” returned 941 unique results, “e-health” returned 167 companies, while “telehealth” 427. We also searched the CBInsights database for similar information. After merging and removing duplicate ones and cleaning up the database, we came up with a list of 1464 companies as digital health companies. A qualitative method will be used to complement the quantitative analysis. We will do an in-depth case analysis of three successful unicorn digital health companies to understand how business models evolve and discuss the challenges faced in this sector. Our research returned some interesting findings. For instance, we found that 86% of the digital health startups were founded in the recent decade since 2010. 75% of the digital health companies have less than 50 employees, and almost 50% with less than 10 employees. This shows that digital health companies are relatively young and small in scale. On the business model analysis, while traditional healthcare businesses emphasize the so-called “3P”—patient, physicians, and payer, digital health companies extend to “5p” by adding patents, which is the result of technology requirements (such as the development of artificial intelligence models), and platform, which is an effective value creation approach to bring the stakeholders together. Our case analysis will detail the 5p framework and contribute to the extant knowledge on business models in the healthcare industry.

Keywords: digital health, business models, entrepreneurship opportunities, healthcare

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Authors: Keyvan Ramin

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The geometric nonlinearity of Off-Diagonal Bracing System (ODBS) could be a complementary system to covering and extending the nonlinearity of reinforced concrete material. Finite element modeling is performed for flexural frame, x-braced frame and the ODBS braced frame system at the initial phase. Then the different models are investigated along various analyses. According to the experimental results of flexural and x-braced frame, the verification is done. Analytical assessments are performed in according to three-dimensional finite element modeling. Non-linear static analysis is considered to obtain performance level and seismic behavior, and then the response modification factors calculated from each model’s pushover curve. In the next phase, the evaluation of cracks observed in the finite element models, especially for RC members of all three systems is performed. The finite element assessment is performed on engendered cracks in ODBS braced frame for various time steps. The nonlinear dynamic time history analysis accomplished in different stories models for three records of Elcentro, Naghan, and Tabas earthquake accelerograms. Dynamic analysis is performed after scaling accelerogram on each type of flexural frame, x-braced frame and ODBS braced frame one by one. The base-point on RC frame is considered to investigate proportional displacement under each record. Hysteresis curves are assessed along continuing this study. The equivalent viscous damping for ODBS system is estimated in according to references. Results in each section show the ODBS system has an acceptable seismic behavior and their conclusions have been converged when the ODBS system is utilized in reinforced concrete frame.

Keywords: FEM, seismic behaviour, pushover analysis, geometric nonlinearity, time history analysis, equivalent viscous damping, passive control, crack investigation, hysteresis curve

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Authors: Delphine Morales, Florian Lombart, Agathe Truchot, Pauline Maire, Pascale Vigneron, Antoine Galmiche, Catherine Lok, Muriel Vayssade

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Targeted therapy molecules are used as a first-line treatment for metastatic melanoma with B-Raf mutation. Nevertheless, these molecules can cause side effects to patients and are efficient on 50 to 60 % of them. Indeed, melanoma cell sensitivity to targeted therapy molecules is dependent on tumor microenvironment (cell-cell and cell-extracellular matrix interactions). To better unravel factors modulating cell sensitivity to B-Raf inhibitor, we have developed and compared several melanoma models: from metastatic melanoma cells cultured as monolayer (2D) to a co-culture in a 3D dermal equivalent. Cell response was studied in different melanoma cell lines such as SK-MEL-28 (mutant B-Raf (V600E), sensitive to Vemurafenib), SK-MEL-3 (mutant B-Raf (V600E), resistant to Vemurafenib) and a primary culture of dermal human fibroblasts (HDFn). Assays have initially been performed in a monolayer cell culture (2D), then a second time on a 3D dermal equivalent (dermal human fibroblasts embedded in a collagen gel). All cell lines were treated with Vemurafenib (a B-Raf inhibitor) for 48 hours at various concentrations. Cell sensitivity to treatment was assessed under various aspects: Cell proliferation (cell counting, EdU incorporation, MTS assay), MAPK signaling pathway analysis (Western-Blotting), Apoptosis (TUNEL), Cytokine release (IL-6, IL-1α, HGF, TGF-β, TNF-α) upon Vemurafenib treatment (ELISA) and histology for 3D models. In 2D configuration, the inhibitory effect of Vemurafenib on cell proliferation was confirmed on SK-MEL-28 cells (IC50=0.5 µM), and not on the SK-MEL-3 cell line. No apoptotic signal was detected in SK-MEL-28-treated cells, suggesting a cytostatic effect of the Vemurafenib rather than a cytotoxic one. The inhibition of SK-MEL-28 cell proliferation upon treatment was correlated with a strong expression decrease of phosphorylated proteins involved in the MAPK pathway (ERK, MEK, and AKT/PKB). Vemurafenib (from 5 µM to 10 µM) also slowed down HDFn proliferation, whatever cell culture configuration (monolayer or 3D dermal equivalent). SK-MEL-28 cells cultured in the dermal equivalent were still sensitive to high Vemurafenib concentrations. To better characterize all cell population impacts (melanoma cells, dermal fibroblasts) on Vemurafenib efficacy, cytokine release is being studied in 2D and 3D models. We have successfully developed and validated a relevant 3D model, mimicking cutaneous metastatic melanoma and tumor microenvironment. This 3D melanoma model will become more complex by adding a third cell population, keratinocytes, allowing us to characterize the epidermis influence on the melanoma cell sensitivity to Vemurafenib. In the long run, the establishment of more relevant 3D melanoma models with patients’ cells might be useful for personalized therapy development. The authors would like to thank the Picardie region and the European Regional Development Fund (ERDF) 2014/2020 for the funding of this work and Oise committee of "La ligue contre le cancer".

Keywords: 3D human skin model, melanoma, tissue engineering, vemurafenib efficiency

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Authors: Shatha Khuzaee

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The study develops multimodal stylistic approach to analyse a number of BBC online news articles reporting some key events from the so called ‘Arab Uprisings’. Critical stylistics (CS) and visual grammar (VG) provide insightful arguments to the ways ideology is projected through different verbal and visual modes, yet they are mode specific because they examine how each mode projects its meaning separately and do not attempt to clarify what happens intersemiotically when the two modes co-occur. Therefore, it is the task undertaken in this research to propose multimodal stylistic approach that addresses the issue of ideology construction when the two modes co-occur. Informed by functional grammar and social semiotics, the analysis attempts to integrate three linguistic models developed in critical stylistics, namely, transitivity choices, prioritizing and hypothesizing along with their visual equivalents adopted from visual grammar to investigate the way ideology is constructed, in multimodal text, when text/image participate and interrelate in the process of meaning making on the textual level of analysis. The analysis provides comprehensive theoretical and analytical elaborations on the different points of integration between CS linguistic models and VG equivalents which operate on the textual level of analysis to better account for ideology construction in news as non-literary multimodal texts. It is argued that the analysis well thought out a plan that would remark the first step towards the integration between the well-established linguistic models of critical stylistics and that of visual analysis to analyse multimodal texts on the textual level. Both approaches are compatible to produce multimodal stylistic approach because they intend to analyse text and image depending on whatever textual evidence is available. This supports the analysis maintain the rigor and replicability needed for a stylistic analysis like the one undertaken in this study.

Keywords: multimodality, stylistics, visual grammar, social semiotics, functional grammar

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Authors: Mumtaz Ipek, Burak Erkayman

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Due date is assigned as an input for scheduling problems. At the same time, due date is selected as a decision variable for real time scheduling applications. Correct determination of due dates increases shop floor performance and number of jobs completed on time. This subject has been mentioned widely in the literature. Moreover rules for due date determination have been developed from analytical analysis. When a job arrives to the shop floor, a due date is assigned for delivery. Various due date determination methods are used in the literature. In this study six different due date methods are implemented for a hypothetical dynamic job shop and the performances of the due date methods are compared.

Keywords: scheduling, dynamic job shop, due date assignment, management engineering

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Xiaoci Li, Yonghua Huang, Hui Lin

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Optimization of the concentration of components in mixed refrigerants leads to potential improvement of either thermodynamic cycle performance or safety performance of heat pumps and refrigerators. R32+R1234yf and R125+R290 are two promising binary mixed refrigerants for the application of heat pumps working in the cold areas. The p-ρ-T data of these mixtures are one of the fundamental and necessary properties for design and evaluation of the performance of the heat pumps. Although the property data of mixtures can be predicted by the mixing models based on the pure substances incorporated in programs such as the NIST database Refprop, direct property measurement will still be helpful to reveal the true state behaviors and verify the models. Densities of the mixtures of R32+R1234yf an d R125+R290 are measured by an Anton Paar U shape oscillating tube digital densimeter DMA-4500 in the range of temperatures from 0°C to 100 °C and pressures up to 10 MPa. The accuracy of the measurement reaches 0.00005 g/cm³. The experimental data are compared with the predictions by Refprop in the corresponding range of pressure and temperature.

Keywords: mixed refrigerant, density measurement, densimeter, thermodynamic property

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Authors: F. Mutelet, L. Cesari

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Development of safer and environmentally friendly processes and products is needed to achieve sustainable production and consumption patterns. Ionic liquids, which are of great interest to the chemical and related industries because of their attractive properties as solvents, should be considered. Ionic liquids are comprised of an asymmetric, bulky organic cation and a weakly coordinating organic or inorganic anion. A large number of possible combinations allows for the ability to ‘fine tune’ the solvent properties for a specific purpose. Physical and chemical properties of ionic liquids are not only influenced by the nature of the cation and the nature of cation substituents but also by the polarity and the size of the anion. These features infer to ionic liquids numerous applications, in organic synthesis, separation processes, and electrochemistry. Separation processes required a good knowledge of the behavior of organic compounds with ionic liquids. Gas chromatography is a useful tool to estimate the interactions between organic compounds and ionic liquids. Indeed, retention data may be used to determine infinite dilution thermodynamic properties of volatile organic compounds in ionic liquids. Among others, the activity coefficient at infinite dilution is a direct measure of solute-ionic liquid interaction. In this work, infinite dilution thermodynamic properties of volatile organic compounds in specific bis(trifluoromethylsulfonyl)imide based ionic liquids measured by gas chromatography is presented. It was found that apolar compounds are not miscible in this family of ionic liquids. As expected, the solubility of organic compounds is related to their polarity and hydrogen-bond. Through activity coefficients data, the performance of these ionic liquids was evaluated for different separation processes (benzene/heptane, thiophene/heptane and pyridine/heptane). Results indicate that ionic liquids may be used for the extraction of polar compounds (aromatics, alcohols, pyridine, thiophene, tetrahydrofuran) from aliphatic media. For example, 1-benzylpyridinium bis(trifluoromethylsulfonyl) imide and 1-cyclohexylmethyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide are more efficient for the extraction of aromatics or pyridine from aliphatics than classical solvents. Ionic liquids with long alkyl chain length present important capacity values but their selectivity values are low. In conclusion, we have demonstrated that specific bis(trifluoromethylsulfonyl)imide based ILs containing polar chain grafted on the cation (for example benzyl or cyclohexyl) increases considerably their performance in separation processes.

Keywords: interaction organic solvent-ionic liquid, gas chromatography, solvation model, COSMO-RS

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Authors: Lin Po-Hsi, Sheu Ming-Thau

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Urea cycle disorders (UCD) are rare genetic metabolic disorders that compromise the body's urea cycle. Sodium phenylbutyrate (SPB) is a medication commonly administered in tablet or powder form to lower ammonia levels. Nonetheless, its high sodium content poses risks to sodium-sensitive UCD patients. This necessitates the creation of an alternative drug formulation to mitigate sodium load and optimize drug delivery for UCD patients. This study focused on crafting a novel oral drug formulation for UCD, leveraging choline bicarbonate and phenylbutyric acid. The active pharmaceutical ingredient-ionic liquids (API-ILs) and therapeutic deep eutectic systems (THEDES) were formed by combining these with choline chloride. These systems display characteristics like maintaining a liquid state at room temperature and exhibiting enhanced solubility. This in turn amplifies drug dissolution rate, permeability, and ultimately oral bioavailability. Incorporating choline-based phenylbutyric acid as a substitute for traditional SPB can effectively curtail the sodium load in UCD patients. Our in vitro dissolution experiments revealed that the ILs and DESs, synthesized using choline bicarbonate and choline chloride with phenylbutyric acid, surpassed commercial tablets in dissolution speed. Pharmacokinetic evaluations in SD rats indicated a notable uptick in the oral bioavailability of phenylbutyric acid, underscoring the efficacy of choline salt ILs in augmenting its bioavailability. Additional in vitro intestinal permeability tests on SD rats authenticated that the ILs, formulated with choline bicarbonate and phenylbutyric acid, demonstrate superior permeability compared to their sodium and acid counterparts. To conclude, choline salt ILs developed from choline bicarbonate and phenylbutyric acid present a promising avenue for UCD treatment, with the added benefit of reduced sodium load. They also hold merit in formulation engineering. The sustained-release capabilities of DESs position them favorably for drug delivery, while the low toxicity and cost-effectiveness of choline chloride signal potential in formulation engineering. Overall, this drug formulation heralds a prospective therapeutic avenue for UCD patients.

Keywords: phenylbutyric acid, sodium phenylbutyrate, choline salt, ionic liquids, deep eutectic systems, oral bioavailability

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Authors: Hamid Vahidkia

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Central to the World Court’s mission is the assurance of universal custom “as prove of a common hone acknowledged as law.” Understudies of the Court’s law have long been mindful that the Court has been superior at applying standard law than characterizing it. However until Nicaragua v. Joined together States, small hurt was done. For within the strongly challenged cases earlier to Nicaragua, the Court overseen to inspire commonalities in factious structure that floated its decisions toward the standard standards certain in state hone. The Court’s need of hypothetical unequivocality basically implied that a career opportunity emerged for a few eyewitnesses like me to endeavor to supply the lost hypothesis of custom.

Keywords: law, international law, jurisdication, customary

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Authors: Nermeen Saad Elbeltagy, Hoda Ghareeb, Hesham Adel Elsheshtawy, Nadim Hamed, Amany Ibrahim Mostafa, Sara Hazem Hassan

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Introduction: Depression is one of the most common mental health problems occurring in women during their child bearing years. Perinatal depression refers to major and minor depressive episodes that occur either during pregnancy or aer delivery. Although perinatal depression is common in developing countries, it is under-recognized in low and middle income countries making a substantial contribution to maternal and infant morbidity and mortality. About 12.5 - 42% of pregnant women and, 12 - 50% of post natal mothers in low and middle income countries such as Ethiopia had depression AIM OF THE WORK: To study prevalence, associated factors and impact of maternal perinatal depression in Alexandria. Patients and method: This study was conducted on 300 mothers at the postnatal ward in ElShatby Maternity Hospital from April 2022 unl October 2022. Females with past history of depression before pregnancy or females who receive medications inducing depression were excluded. The participants were asked to complete the questionnaire that includes the Edinburgh Postnatal Depression Scale (EPDS) as a screening test to obtain information concerning the current frame of mind at antepartum, partum and postpartum periods Results: The prevalence of perinatal depression was 22.3%. It was found that there is a significant negave moderate correlation between socioeconomic status and perinatal depression(r=-0.42). The present study revealed that about two thirds (60.7%) of postpartum women had low socioeconomic level. Also, less than one fourth (20%) of parents had high education and only one fourth (25.3%) of postpartum women were working. There was a statically significance difference between the number of previous abortions and perinatal depression (p=0.04). There was a significant moderate correlation between the amount of blood lost during delivery and an increased risk of developing postpartum depression. The prevalence of perinatal depression was high in cases of female neonates more than male ones. Conclusion: the prevalence of perinatal depression among the studied women was 22.3% of studied group. The significant factors identified in this study can be targeted to reduce the occurrence of perinatal depression among pregnant women in Alexandria through appropriate health interventions which includes perinatal depression screening, counseling, and the provision of support for pregnant women during antenatal care as well as lifestyle modification.

Keywords: mental health, depression in pregnancy, mental disorders, psychology in pregnancy

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Saeedullah J. Mandokhail, Shamsher Sadiq, Meer H. Khan

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This paper presents the comparison of excess pore water pressure ratio (ru) predicted by using accumulated stress based pore pressure model and plasticity model. One dimensional effective stress site response analyses were performed on a 30 m deep sand column (consists of a liquefiable layer in between non-liquefiable layers) using accumulated stress based pore pressure model in Deepsoil and PDMY2 (PressureDependentMultiYield02) model in Opensees. Three Input motions with different peak ground acceleration (PGA) levels of 0.357 g, 0.124 g, and 0.11 g were used in this study. The developed excess pore pressure ratio predicted by the above two models were compared and analyzed along the depth. The time history of the ru at mid of the liquefiable layer and non-liquefiable layer were also compared. The comparisons show that the two models predict mostly similar ru values. The predicted ru is also consistent with the PGA level of the input motions.

Keywords: effective stress, excess pore pressure ratio, pore pressure model, site response analysis

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: Zhifeng Kong

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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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Authors: Mujahid Sultan

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The IT industry has seen many transformations in the Software Development Life Cycle (SDLC) methodologies and development approaches. SDLCs range from waterfall to agile, and the development approaches from monolith to microservices. Management, orchestration, and monetization of microservices have created an API economy in the modern enterprise. There are two approaches to API design, code first and design first. Design first is gaining popularity in the industry as this allows capturing the API needs from the stakeholders rather than the development teams guesstimating the needs and associating a monetary value with the APIs and microservices. In this publication, we describe an approach to organizing and creating stakeholder needs and requirements for designing microservices and APIs.

Keywords: requirements engineering, enterprise architecture, APIs, microservices, DevOps, continuous delivery, continuous integration, stakeholder viewpoints

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Authors: Yuan Long, Fabrizio Ceschin, David Harrison

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Environmental sustainability is under the threat of excessive single-use plastic packaging waste, and current waste management fails to address this issue. Therefore, it has led to a reidentification of the alternative, which can curb the packaging waste without reducing social needs. Reusable packaging represents a circular approach to close the loop of consumption in which packaging can stay longer in the system to satisfy social needs. However, the implementation of reusable packaging is fragmented and lacks systematic approaches. The product-service system (PSS) is widely regarded as a sustainable business model innovation for embracing circular consumption. As a result, applying PSS to reusable packaging solutions will be promising to address the packaging waste issue. This paper aims at filling the knowledge gap relating to apply PSS to reusable packaging solutions and provide a strategic design tool that could support packaging professionals to design reusable packaging solutions. The methodology of this paper is case studies and workshops to provide a design tool. The respondents are packaging professionals who are packaging consultants, NGO professionals, and entrepreneurs. 57 cases collected show that 15 archetypal models operate in the market. Subsequently, a polarity diagram is developed to embrace those 15 archetypal models, and a total number of 24 experts were invited for the workshop to evaluate the design tool. This research finally provides a strategic design tool to support packaging professionals to design reusable packaging solutions. The application of the tool is to support the understanding of the reusable packaging solutions, analyzing the markets, identifying new opportunities, and generate new business models. The implication of this research is to provide insights for academics and businesses in terms of tackling single-use packaging waste and build a foundation for further development of the reusable packaging solution tool.

Keywords: environmental sustainability, product-service system, reusable packaging, design tool

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Authors: Kinneret Segal

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Background: The work of a midwife is emotionally challenging, both positively and negatively. Midwives share moments of joy when a baby is welcomed into the world and also attend difficult events of loss and trauma. The relationship that develops with the maternity is the essence of the midwife's care, and it is a fundamental source of motivation and professional satisfaction. This close relationship with the maternity may be used as a double-edged sword in cases of exposure to traumatic events at birth. Birth problems, exposure to emergencies and traumatic events, and loss can affect the professional quality of life and the Compassion satisfaction of the midwife. It seems that the issue of traumatic experiences in the work of midwives has not been sufficiently explored. Aim: The present study examined the associations between exposure to traumatic events, personal resilience and post-traumatic symptoms, professional quality of life, and organizational commitment among midwifery nurses in Israeli hospitals. Methods: 131 midwives from three hospitals in the country's center in Israel participated in this study. The data were collected during 2021 using a self-report questionnaire that examined sociodemographic characteristics, the degree of exposure to traumatic events in the delivery room, personal resilience, post-traumatic symptoms, professional quality of life, and organizational commitment. Results: The three most difficult traumatic events for the midwives were death or fear of death of a newborn, death or fear of the death of a mother, and a quiet birth. The higher the frequency of exposure to traumatic events, the more numerous and intense the onset of post-trauma symptoms. The more numerous and powerful the post-trauma symptoms, the higher the level of professional burnout and/or compassion fatigue, and the lower the level of compassion satisfaction. High levels of compassion satisfaction and/or low professional burnout were expressed in a heightened sense of organizational commitment. Personal resilience, country of birth, traumatic symptoms, and organizational commitment predicted satisfaction from compassion. Conclusions: Midwives are exposed to traumatic events associated with dissatisfaction and impairment of the professional quality of life that accompanies burnout and compassion fatigue. Exposure to traumatic events leads to the appearance of traumatic symptoms, a decrease in organizational commitment, and psychological and mental well-being. The issue needs to be addressed by implementing training programs, organizational support, and policies to improving well-being and quality of care among midwives.

Keywords: organizational commitment, traumatic experiences, personal resilience, quality of life

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Authors: Bharat Sapkota

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Nepal is the one of the victim country of climate change. Decreasing snow line, sometimes higher and sometime non-rain fall are common phenomena in hill area. Natural flood disaster and drought is also common every year in certain place of the country. So this paper analyze the effect of climate and natural water sources for sustainability of water sanitation and hygiene of Tanahun district. It is one of the Rural Water Supply and Sanitation Project Western Nepal Phase-II (RWSSP-WN Phase-II) project district out of 14 project districts of western and mid-western Nepal. RWSSP-WN II is a bilateral development cooperation of governments of Nepal and Finland. Big investment is still going on in water sanitation and hygiene sector but sustainability is still a challenge throughout the country. So RWSSP-WN has started the strengthen of the capacity of local Governments to deliver services in water supply, sanitation and hygiene and its sustainability through the implementation of cross cutting approach of climate change and disaster risk reduction. The study shows that the average yield in 685 natural point sources were around 0.045 l/s in 2014 but it was twice as high in 2004 i.e. 0.09 l/s. The maximum measured yield in 2014 was 1.87 l/s, whereas, the maximum yield was 3 l/s in 2004. Likewise, spring source mean and maximum yield measured in 2014 were 0.16 l/s and 3.33 l/s respectively, whereas, mean and maximum yields in 2004 were 0.204 l/s and 3 l/s respectively. Small streams average yield measured in 2014 was 0.32 l/s with the maximum of around 4.99 l/s. In 2004, mean and maximum yields of streams were 0.485 l/s and 5 l/s respectively. The overall climate between years 2002 to 2013 and measured yield data between 2004 and 2014 shows climate as one of the causes of water source decline. The temperature is rising with pace of 0.041°C per year and rainfall is decreased by 16.8 mm/year. The Khosla’s empirical formula shows decrease of 1.7 cm/year in runoff. At present sustainability of water, sanitation and hygiene is more challenge due to sources decreasing in the district. Sanitation and hygiene total behavior change and watershed conservation as well as design and implementation of recharge pound construction are the way forward of sustainability of water, sanitation and hygiene.

Keywords: water sanitation, hygiene, sustainability, climate change

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Authors: Mohsen Bagheri, Ahmad Afifi

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This paper presents a new method for read out of the piezoresistive accelerometer sensors. The circuit works based on instrumentation amplifier and it is useful for reducing offset in Wheatstone bridge. The obtained gain is 645 with 1 μv/°c equivalent drift and 1.58 mw power consumption. A Schmitt trigger and multiplexer circuit control output node. A high speed counter is designed in this work. The proposed circuit is designed and simulated in 0.18 μm CMOS technology with 1.8 v power supply.

Keywords: piezoresistive accelerometer, zero offset, Schmitt trigger, bidirectional reversible counter

Procedia PDF Downloads 305