Search results for: small series assembly
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7582

Search results for: small series assembly

7312 Integration of an Evidence-Based Medicine Curriculum into Physician Assistant Education: Teaching for Today and the Future

Authors: Martina I. Reinhold, Theresa Bacon-Baguley

Abstract:

Background: Medical knowledge continuously evolves and to help health care providers to stay up-to-date, evidence-based medicine (EBM) has emerged as a model. The practice of EBM requires new skills of the health care provider, including directed literature searches, the critical evaluation of research studies, and the direct application of the findings to patient care. This paper describes the integration and evaluation of an evidence-based medicine course sequence into a Physician Assistant curriculum. This course sequence teaches students to manage and use the best clinical research evidence to competently practice medicine. A survey was developed to assess the outcomes of the EBM course sequence. Methodology: The cornerstone of the three-semester sequence of EBM are interactive small group discussions that are designed to introduce students to the most clinically applicable skills to identify, manage and use the best clinical research evidence to improve the health of their patients. During the three-semester sequence, the students are assigned each semester to participate in small group discussions that are facilitated by faculty with varying background and expertise. Prior to the start of the first EBM course in the winter semester, PA students complete a knowledge-based survey that was developed by the authors to assess the effectiveness of the course series. The survey consists of 53 Likert scale questions that address the nine objectives for the course series. At the end of the three semester course series, the same survey was given to all students in the program and the results from before, and after the sequence of EBM courses are compared. Specific attention is paid to overall performance of students in the nine course objectives. Results: We find that students from the Class of 2016 and 2017 consistently improve (as measured by percent correct responses on the survey tool) after the EBM course series (Class of 2016: Pre- 62% Post- 75%; Class of 2017: Pre- 61 % Post-70%). The biggest increase in knowledge was observed in the areas of finding and evaluating the evidence, with asking concise clinical questions (Class of 2016: Pre- 61% Post- 81%; Class of 2017: Pre- 61 % Post-75%) and searching the medical database (Class of 2016: Pre- 24% Post- 65%; Class of 2017: Pre- 35 % Post-66 %). Questions requiring students to analyze, evaluate and report on the available clinical evidence regarding diagnosis showed improvement, but to a lesser extend (Class of 2016: Pre- 56% Post- 77%; Class of 2017: Pre- 56 % Post-61%). Conclusions: Outcomes identified that students did gain skills which will allow them to apply EBM principles. In addition, the outcomes of the knowledge-based survey allowed the faculty to focus on areas needing improvement, specifically the translation of best evidence into patient care. To address this area, the clinical faculty developed case scenarios that were incorporated into the lecture and discussion sessions, allowing students to better connect the research studies with patient care. Students commented that ‘class discussion and case examples’ contributed most to their learning and that ‘it was helpful to learn how to develop research questions and how to analyze studies and their significance to a potential client’. As evident by the outcomes, the EBM courses achieved the goals of the course and were well received by the students. 

Keywords: evidence-based medicine, clinical education, assessment tool, physician assistant

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7311 Quantum Decision Making with Small Sample for Network Monitoring and Control

Authors: Tatsuya Otoshi, Masayuki Murata

Abstract:

With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

Procedia PDF Downloads 52
7310 Small Micro and Medium Enterprises Perception-Based Framework to Access Financial Support

Authors: Melvin Mothoa

Abstract:

Small Micro and Medium Enterprises are very significant for the development of their market economies. They are the main creators of the new working places, and they present a vital core of the market economy in countries across the globe. Access to finance is identified as crucial for small, micro, and medium-sized enterprises for their growth and innovation. This paper is conceived to propose a perception-based SMME framework to aid in access to financial support. Furthermore, the study will address issues that impede SMMEs in South Africa from obtaining finance from financial institutions. The framework will be tested against data collected from 200 Small Micro & Medium Enterprises in the Gauteng province of South Africa. The study adopts a quantitative method, and the delivery of self-administered questionnaires to SMMEs will be the primary data collection tool. Structural equation modeling will be used to further analyse the data collected.

Keywords: finance, small business, growth, development

Procedia PDF Downloads 75
7309 Metal Layer Based Vertical Hall Device in a Complementary Metal Oxide Semiconductor Process

Authors: Se-Mi Lim, Won-Jae Jung, Jin-Sup Kim, Jun-Seok Park, Hyung-Il Chae

Abstract:

This paper presents a current-mode vertical hall device (VHD) structure using metal layers in a CMOS process. The proposed metal layer based vertical hall device (MLVHD) utilizes vertical connection among metal layers (from M1 to the top metal) to facilitate hall effect. The vertical metal structure unit flows a bias current Ibias from top to bottom, and an external magnetic field changes the current distribution by Lorentz force. The asymmetric current distribution can be detected by two differential-mode current outputs on each side at the bottom (M1), and each output sinks Ibias/2 ± Ihall. A single vertical metal structure generates only a small amount of hall effect of Ihall due to the short length from M1 to the top metal as well as the low conductivity of the metal, and a series connection between thousands of vertical structure units can solve the problem by providing NxIhall. The series connection between two units is another vertical metal structure flowing current in the opposite direction, and generates negative hall effect. To mitigate the negative hall effect from the series connection, the differential current outputs at the bottom (M1) from one unit merges on the top metal level of the other unit. The proposed MLVHD is simulated in a 3-dimensional model simulator in COMSOL Multiphysics, with 0.35 μm CMOS process parameters. The simulated MLVHD unit size is (W) 10 μm × (L) 6 μm × (D) 10 μm. In this paper, we use an MLVHD with 10 units; the overall hall device size is (W) 10 μm × (L)78 μm × (D) 10 μm. The COMSOL simulation result is as following: the maximum hall current is approximately 2 μA with a 12 μA bias current and 100mT magnetic field; This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.R7117-16-0165, Development of Hall Effect Semiconductor for Smart Car and Device).

Keywords: CMOS, vertical hall device, current mode, COMSOL

Procedia PDF Downloads 277
7308 Design of a Telemetry, Tracking, and Command Radio-Frequency Receiver for Small Satellites Based on Commercial Off-The-Shelf Components

Authors: A. Lovascio, A. D’Orazio, V. Centonze

Abstract:

From several years till now the aerospace industry is developing more and more small satellites for Low-Earth Orbit (LEO) missions. Such satellites have a low cost of making and launching since they have a size and weight smaller than other types of satellites. However, because of size limitations, small satellites need integrated electronic equipment based on digital logic. Moreover, the LEOs require telecommunication modules with high throughput to transmit to earth a big amount of data in a short time. In order to meet such requirements, in this paper we propose a Telemetry, Tracking & Command module optimized through the use of the Commercial Off-The-Shelf components. The proposed approach exploits the major flexibility offered by these components in reducing costs and optimizing the performance. The method has been applied in detail for the design of the front-end receiver, which has a low noise figure (1.5 dB) and DC power consumption (smaller than 2 W). Such a performance is particularly attractive since it allows fulfilling the energy budget stringent constraints that are typical for LEO small platforms.

Keywords: COTS, LEO, small-satellite, TT&C

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7307 Switching of Series-Parallel Connected Modules in an Array for Partially Shaded Conditions in a Pollution Intensive Area Using High Powered MOSFETs

Authors: Osamede Asowata, Christo Pienaar, Johan Bekker

Abstract:

Photovoltaic (PV) modules may become a trend for future PV systems because of their greater flexibility in distributed system expansion, easier installation due to their nature, and higher system-level energy harnessing capabilities under shaded or PV manufacturing mismatch conditions. This is as compared to the single or multi-string inverters. Novel residential scale PV arrays are commonly connected to the grid by a single DC–AC inverter connected to a series, parallel or series-parallel string of PV panels, or many small DC–AC inverters which connect one or two panels directly to the AC grid. With an increasing worldwide interest in sustainable energy production and use, there is renewed focus on the power electronic converter interface for DC energy sources. Three specific examples of such DC energy sources that will have a role in distributed generation and sustainable energy systems are the photovoltaic (PV) panel, the fuel cell stack, and batteries of various chemistries. A high-efficiency inverter using Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs) for all active switches is presented for a non-isolated photovoltaic and AC-module applications. The proposed configuration features a high efficiency over a wide load range, low ground leakage current and low-output AC-current distortion with no need for split capacitors. The detailed power stage operating principles, pulse width modulation scheme, multilevel bootstrap power supply, and integrated gate drivers for the proposed inverter is described. Experimental results of a hardware prototype, show that not only are MOSFET efficient in the system, it also shows that the ground leakage current issues are alleviated in the proposed inverter and also a 98 % maximum associated driver circuit is achieved. This, in turn, provides the need for a possible photovoltaic panel switching technique. This will help to reduce the effect of cloud movements as well as improve the overall efficiency of the system.

Keywords: grid connected photovoltaic (PV), Matlab efficiency simulation, maximum power point tracking (MPPT), module integrated converters (MICs), multilevel converter, series connected converter

Procedia PDF Downloads 100
7306 Exploring Challenges Faced by Small Business Owners on Poverty Reduction in Rural Eastern Cape, South Africa

Authors: Akinwale Olusola Mokayode, Emaanuel Adu, Seriki Idowu Ibrahim

Abstract:

Small business can serve as a tool for poverty reduction in South Africa, but it requires adequate support and development for its continuous sustenance in spite of rigorous challenges, especially in the rural environment. This study explored the challenges faced by the small business owners in the rural Eastern Cape Province of South Africa. The objective of the study is to identify the challenges faced by small business owners in the case study area and to examine the effects of those challenges on poverty rate. Survey research design was adopted, with the distribution of structured questionnaire for data collection through a simple random sampling method. Descriptive and inferential statistics was used to analyse the data. Findings showed that small business owners face various challenges in their commercial operations. It was also made clearer that these challenges have effects on the poverty rate as well as crime rate. In conclusion, in other for small businesses to be effective instrument to tackle poverty, certain measure must be taken into considerations. This therefore necessitates recommendation from the researcher that potential and current business owners must seek valuable advice from the more experienced business tycoon and seek information about the business assistance programmes provided by government and private sectors.

Keywords: eastern cape, poverty, poverty reduction, rural, small business, sustainable livelihood

Procedia PDF Downloads 458
7305 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 209
7304 The Role of Financial and Non-Financial Institutions in Promoting Entrepreneurship in Micro small and Medium Enterprises

Authors: Lemuel David

Abstract:

The importance of the Micro, Small, and Medium Enterprises sector is well recognized for its legitimate contribution to the Macroeconomic objectives of the Republic of Liberia, like generation of employment, input t, exports, and enhancing entrepreneurship. Right now, Medium and Small enterprises accounts for about 99 percent of the industrial units in the country, contributing 60 percent of the manufacturing sector output and approximately one-third of the nation’s exports. The role of various financial institutions like ECO bank and Non-financial Institutions like Bearch Limited support promoting the growth of Micro, Small, and Medium Enterprises is unique. A small enterprise or entrepreneur gets many types of assistance from different institutions for varied purposes in the course of his entrepreneurial journey. This paper focuses on the factors related to financial institutional support and non-financial institutional support entrepreneurs to the growth of Medium and Small enterprises in the Republic of Liberia. The significance of this paper is to support Policy and Institutional Support for Medium and Small enterprises to know the views of entrepreneurs about financial and non-financial support systems in the Republic of Liberia. This study was carried out through a survey method, with the use of questionnaires. The population for this study consisted of all registered Medium and Small enterprises which have been registered during the years 2004-2014 in the republic of Liberia. The sampling method employed for this study was a simple random technique and determined a sample size of 400. Data for the study was collected using a standard questionnaire. The questionnaire consisted of two parts: the first part consisted of questions on the profile of the respondents. The second part covers (1) financial, promotional factors and (2) non-financial promotional factors. The results of the study are based on financial and non-financial supporting activities provided by institutions to Medium and Small enterprises. After investigation, it has been found that there is no difference in the support given by Financial Institutions and non-financial Institutions. Entrepreneurs perceived “collateral-free schemes and physical infrastructure support factors are highest contributing to entry and growth of Medium and Small enterprises.

Keywords: micro, small, and medium enterprises financial institutions, entrepreneurship

Procedia PDF Downloads 62
7303 Degree of Approximation of Functions Conjugate to Periodic Functions Belonging to Lipschitz Classes by Product Matrix Means

Authors: Smita Sonker

Abstract:

Various investigators have determined the degree of approximation of conjugate signals (functions) of functions belonging to different classes Lipα, Lip(α,p), Lip(ξ(t),p), W(Lr,ξ(t), (β ≥ 0)) by matrix summability means, lower triangular matrix operator, product means (i.e. (C,1)(E,1), (C,1)(E,q), (E,q)(C,1) (N,p,q)(E,1), and (E,q)(N,pn) of their conjugate trigonometric Fourier series. In this paper, we shall determine the degree of approximation of 2π-periodic function conjugate functions of f belonging to the function classes Lipα and W(Lr; ξ(t); (β ≥ 0)) by (C1.T) -means of their conjugate trigonometric Fourier series. On the other hand, we shall review above-mentioned work in the light of Lenski.

Keywords: signals, trigonometric fourier approximation, class W(L^r, \xi(t), conjugate fourier series

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7302 Defining a Pathway to Zero Energy Building: A Case Study on Retrofitting an Old Office Building into a Net Zero Energy Building for Hot-Humid Climate

Authors: Kwame B. O. Amoah

Abstract:

This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: energy consumption, building energy analysis, energy retrofits, energy-efficiency

Procedia PDF Downloads 181
7301 Small Businesses as Vehicles for Job Creation in North-West Nigeria

Authors: Mustapha Shitu Suleiman, Francis Neshamba, Nestor Valero-Silva

Abstract:

Small businesses are considered as engine of economic growth, contributing to employment generation, wealth creation, and poverty alleviation and food security in both developed and developing countries. Nigeria is facing many socio-economic problems and it is believed that by supporting small business development, as propellers of new ideas and more effective users of resources, often driven by individual creativity and innovation, Nigeria would be able to address some of its economic and social challenges, such as unemployment and economic diversification. Using secondary literature, this paper examines the role small businesses can play in the creation of jobs in North-West Nigeria to overcome issues of unemployment, which is the most devastating economic challenge facing the region. Most studies in this area have focused on Nigeria as a whole and only a few studies provide a regional focus, hence, this study will contribute to knowledge by filling this gap by concentrating on North-West Nigeria. It is hoped that with the present administration’s determination to improve the economy, small businesses would be used as vehicles for diversification of the economy away from crude oil to create jobs that would lead to a reduction in the country’s high unemployment level.

Keywords: job creation, north-west, Nigeria, small business, unemployment

Procedia PDF Downloads 280
7300 Forecasting Issues in Energy Markets within a Reg-ARIMA Framework

Authors: Ilaria Lucrezia Amerise

Abstract:

Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.

Keywords: interval forecasts, time series, electricity prices, reg-SARIMA methods

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7299 Challenges of Sustainable Development of Small and Medium-Sized Enterprises in Georgia

Authors: Kharaishvili Eteri

Abstract:

The article highlights the importance of small and medium-sized enterprises in achieving the goals of sustainable development of the economy and increasing the well-being of the population. The opinion is put forward that it is necessary to adapt the activities of small and medium-sized firms in Georgia to sustainable business models. Therefore, it is important to identify the challenges that will ensure compliance with the goals and requirements of sustainable development of small and mediumsized enterprises. Objectives. The goal of the study is to reveal the challenges of sustainable development in small and medium-sized enterprises in Georgia and to develop recommendations for strategic development opportunities. Methodologies The challenges of sustainable development of small and medium-sized enterprises are investigated with the following methodology: bibliographic research of scientific works and reports of organizations is carried out; Based on the grouping of sustainable development goals, the performance indicators of these goals are studied; Differences with respect to the corresponding indicators of European countries are determined by the comparison method; The matrix scheme establishes the conditions and tools for sustainable development; Challenges of sustainable development are identified by factor analysis. Contributions Trends in the sustainable development of small and medium-sized enterprises are studied from the point of view of economic, social and environmental factors; To ensure sustainability, the conditions and tools for sustainable development are established (certified supply chains and global markets, allocation of financial resources necessary for sustainable development, proper public procurement, highly qualified workforce, etc.); Several main challenges have been identified in the sustainable development of small and medium-sized enterprises, including: limited internal resources; Institutional factors, especially vague and imperfect regulations, bureaucracy; low level of investments; Low level of qualification of human capital and others.

Keywords: small and medium-sized enterprises, sustainable development, conditions of sustainable development, strategic directions of sustainable development.

Procedia PDF Downloads 70
7298 Genome Sequencing, Assembly and Annotation of Gelidium Pristoides from Kenton-on-Sea, South Africa

Authors: Sandisiwe Mangali, Graeme Bradley

Abstract:

Genome is complete set of the organism's hereditary information encoded as either deoxyribonucleic acid or ribonucleic acid in most viruses. The three different types of genomes are nuclear, mitochondrial and the plastid genome and their sequences which are uncovered by genome sequencing are known as an archive for all genetic information and enable researchers to understand the composition of a genome, regulation of gene expression and also provide information on how the whole genome works. These sequences enable researchers to explore the population structure, genetic variations, and recent demographic events in threatened species. Particularly, genome sequencing refers to a process of figuring out the exact arrangement of the basic nucleotide bases of a genome and the process through which all the afore-mentioned genomes are sequenced is referred to as whole or complete genome sequencing. Gelidium pristoides is South African endemic Rhodophyta species which has been harvested in the Eastern Cape since the 1950s for its high economic value which is one motivation for its sequencing. Its endemism further motivates its sequencing for conservation biology as endemic species are more vulnerable to anthropogenic activities endangering a species. As sequencing, mapping and annotating the Gelidium pristoides genome is the aim of this study. To accomplish this aim, the genomic DNA was extracted and quantified using the Nucleospin Plank Kit, Qubit 2.0 and Nanodrop. Thereafter, the Ion Plus Fragment Library was used for preparation of a 600bp library which was then sequenced through the Ion S5 sequencing platform for two runs. The produced reads were then quality-controlled and assembled through the SPAdes assembler with default parameters and the genome assembly was quality assessed through the QUAST software. From this assembly, the plastid and the mitochondrial genomes were then sampled out using Gelidiales organellar genomes as search queries and ordered according to them using the Geneious software. The Qubit and the Nanodrop instruments revealed an A260/A280 and A230/A260 values of 1.81 and 1.52 respectively. A total of 30792074 reads were obtained and produced a total of 94140 contigs with resulted into a sequence length of 217.06 Mbp with N50 value of 3072 bp and GC content of 41.72%. A total length of 179281bp and 25734 bp was obtained for plastid and mitochondrial respectively. Genomic data allows a clear understanding of the genomic constituent of an organism and is valuable as foundation information for studies of individual genes and resolving the evolutionary relationships between organisms including Rhodophytes and other seaweeds.

Keywords: Gelidium pristoides, genome, genome sequencing and assembly, Ion S5 sequencing platform

Procedia PDF Downloads 127
7297 A Small Signal Model for Resonant Tunneling Diode

Authors: Rania M. Abdallah, Ahmed A. S. Dessouki, Moustafa H. Aly

Abstract:

This paper has presented a new simple small signal model for a resonant tunnelling diode device. The resonant tunnelling diode equivalent circuit elements were calculated and the results led to good agreement between the calculated equivalent circuit elements and the measurement results.

Keywords: resonant tunnelling diode, small signal model, negative differential conductance, electronic engineering

Procedia PDF Downloads 419
7296 A Plasmonic Mass Spectrometry Approach for Detection of Small Nutrients and Toxins

Authors: Haiyang Su, Kun Qian

Abstract:

We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis.

Keywords: plasmonic materials, laser desorption/ionization, mass spectrometry, small nutrients, toxins

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7295 Synthesis of a Library of Substituted Isoquinolines Based on a Triazolization Strategy, and Their Anti-HIV and C-X-C Chemokine Receptor Type 4 Antagonist Activity

Authors: Mastaneh Safarnejad Shad, Wim Dehaen, Steven De Jonghe

Abstract:

Since CXCR4 is the main coreceptor of HIV-1 and plays an important role in human immunodeficiency virus (HIV) entry, numerous efforts were directed towards the discovery of new classes of small molecules that act as CXCR4 antagonists. In addition, CXCR4 antagonists are potentially useful in the treatment of several other disorders, such as cancer cell metastasis, leukemia cell proliferation, rheumatoid arthritis, and pulmonary fibrosis. Since AMD3100 (plerixafor) is the only CXCR4 antagonist which obtained approval by the Food and Drug Administration (FDA), we were motivated to investigate a new category of molecules as CXCR4 antagonists. Most of the scaffolds which have been studied so far as CXCR4 antagonists are based on the tetrahydroquinoline (THQ) moiety in which AMD11070 (mavorixafor), GSK-812394, and TIQ15 displayed the most potent CXCR4 antagonism. Due to the high potency of these scaffolds, two different series of compounds were prepared in this work. In the first set, the THQ moiety is coupled to an amine chain and various isoquinoline derivatives (prepared by an in-house developed triazolization strategy), of which the upper part of molecules is identical to AMD11070 and TIQ15. In the second category of compounds, the THQ moiety was simplified by the synthesis of a substituted pyridine moiety. In order to investigate if CXCR4 antagonism requires the presence of an isoquinoline moiety, the corresponding pyridine analogues were also prepared. In both series of compounds, potent CXCR4 antagonism was noticed.

Keywords: CXCR4 coreceptor, CXCR4 antagonists, HIV inhibitor, tetrahydroquinoline

Procedia PDF Downloads 171
7294 Protection of Human Rights in Europe: The Parliamentary Dimension

Authors: Aleksandra Chiniaeva

Abstract:

The following paper describes the activity of national and international parliamentary assemblies of the European region in protection and promotion of human rights. It may be said that parliamentarians have a “double mandate” — as members of the international assembly and of their respective national parliaments. In other words, parliamentarization at both international and national level provides a situation for parliamentarians, where they link people, national governments and international organizations. The paper is aimed towards demonstrating that the activity of the main international parliamentary assemblies of the European region have a real positive impact on the human rights situation in the European region. In addition, the paper describes the assemblies that include protection of human rights in their Agenda as one of the main subjects: the EP, the PACE, the OSCE PA and the IPA CIS. Co-operation activities such as joint election observation; participation in inter-parliamentary associations, such as the IPU; conclusion agreements allow assemblies to provide observation of human right situation in the states that are not members of the particular organization and as consequence make their impact broader.

Keywords: human rights, international parliamentary assembly, IPU, EP, PACE, OSCE, international election observation

Procedia PDF Downloads 343
7293 Adaptation Mechanism and Planning Response to Resiliency Shrinking of Small Towns Based on Complex Adaptive System by Taking Wuhan as an Example

Authors: Yanqun Li, Hong Geng

Abstract:

The rapid urbanization process taking big cities as the main body leads to the unequal configuration of urban and rural areas in the aspects of land supply, industrial division of labor, service supply and space allocation, and induces the shrinking characterization of service energy, industrial system and population vitality in small towns. As an important spatial unit in the spectrum of urbanization that serves, connects and couples urban and rural areas, the shrinking phenomenon faced by small towns has an important influence on the healthy development of urbanization. Based on the census of small towns in Wuhan metropolitan area, we have found that the shrinking of small towns is a passive contraction of elastic tension under the squeeze in cities. Once affected by the external forces such as policy regulation, planning guidance, and population return, small towns will achieve expansion and growth. Based on the theory of complex adaptive systems, this paper comprehensively constructs the development index evaluation system of small towns from five aspects of population, economy, space, society and ecology, measures the shrinking level of small towns, further analyzes the shrinking characteristics of small towns, and identifies whether the shrinking is elastic or not. And then this paper measures the resilience ability index of small town contract from the above-mentioned five aspects. Finally, this paper proposes an adaptive mechanism of urban-rural interaction evolution under fine division of labor to response the passive shrinking in small towns of Wuhan. Based on the above, the paper creatively puts forward the planning response measures of the small towns on the aspects of spatial layout, function orientation and service support, which can provide reference for other regions.

Keywords: complex adaptive systems, resiliency shrinking, adaptation mechanism, planning response

Procedia PDF Downloads 91
7292 Work Related and Psychosocial Risk Factors for Musculoskeletal Disorders among Workers in an Automated flexible Assembly Line in India

Authors: Rohin Rameswarapu, Sameer Valsangkar

Abstract:

Background: Globally, musculoskeletal disorders are the largest single cause of work-related illnesses accounting for over 33% of all newly reported occupational illnesses. Risk factors for MSD need to be delineated to suggest means for amelioration. Material and methods: In this current cross-sectional study, the prevalence of MSDs among workers in an electrical company assembly line, the socio-demographic and job characteristics associated with MSD were obtained through a semi-structured questionnaire. A quantitative assessment of the physical risk factors through the Rapid Upper Limb Assessment (RULA) tool, and measurement of psychosocial risk factors through a Likert scale was obtained. Statistical analysis was conducted using Epi-info software and descriptive and inferential statistics including chi-square and unpaired t test were obtained. Results: A total of 263 workers consented and participated in the study. Among these workers, 200 (76%) suffered from MSD. Most of the workers were aged between 18–27 years and majority of the workers were women with 198 (75.2%) of the 263 workers being women. A chi square test was significant for association between male gender and MSD with a P value of 0.007. Among the MSD positive group, 4 (2%) had a grand score of 5, 10 (5%) had a grand score of 6 and 186 (93%) had a grand score of 7 on RULA. There were significant differences between the non-MSD and MSD group on five out of the seven psychosocial domains, namely job demand, job monotony, co-worker support, decision control and family and environment domains. Discussion: The current cross-sectional study demonstrates a high prevalence of MSD among assembly line works with inherent physical and psychosocial risk factors and recommends that not only physical risk factors, addressing psychosocial risk factors through proper ergonomic means is also essential to the well-being of the employee.

Keywords: musculoskeletal disorders, India, occupational health, Rapid Upper Limb Assessment (RULA)

Procedia PDF Downloads 319
7291 Small Text Extraction from Documents and Chart Images

Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

Abstract:

Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

Procedia PDF Downloads 98
7290 Exploring Time-Series Phosphoproteomic Datasets in the Context of Network Models

Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

Abstract:

Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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7289 Formulation and in Vitro Evaluation of Cubosomes Containing CeO₂ Nanoparticles Loaded with Glatiramer Acetate Drug

Authors: Akbar Esmaeili, Zahra Salarieh

Abstract:

Cerium oxide nanoparticles (nano-series) are used as catalysts in industrial applications due to their free radical scavenging properties. Given that free radicals play an essential role in the pathology of many neurological diseases, we investigated the use of nanocrystals as a potential therapeutic agent for oxidative damage. This project synthesized nano-series from a new and environmentally friendly bio-pathway. Investigation of cerium nitrate in culture medium containing inoculated Lactobacillus acidophilus strain before incubation produces nano-series. Loaded with glatiramer acetate (GA) was formed by coating carboxymethylcellulose (CMC) and CeO2. FE-SEM analysis showed nano-series in the 9-11 nm range, spherical shape, and uniform particle size distribution. Cubic nanoparticles containing anti-multiple sclerosis (anti-Ms) treatment called GA were used. Glycerol monostearate (GMS) was used as a fat base, and evening primrose extract was used as an anti-inflammatory in cubosomes. Design-Expert® software was used to study the effects of different formulation factors on the properties of GAloaded cubic dispersions. Thirty GA-labeled cubic dispersions were prepared with GA-labeled carboxymethylcellulose and evaluated in vitro. The results showed an average nano-series size of 89.02 and a zeta potential of -49.9. Cubosomes containing GA-CMC/CeO2 showed a stable release profile for 180 min. The results showed that cubosomes containing GA-CMC/CeO2 could be a promising drug carrier with normal release behavior.

Keywords: ciochemistry, biotechnology, molecular, biology

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7288 A Computational Framework for Decoding Hierarchical Interlocking Structures with SL Blocks

Authors: Yuxi Liu, Boris Belousov, Mehrzad Esmaeili Charkhab, Oliver Tessmann

Abstract:

This paper presents a computational solution for designing reconfigurable interlocking structures that are fully assembled with SL Blocks. Formed by S-shaped and L-shaped tetracubes, SL Block is a specific type of interlocking puzzle. Analogous to molecular self-assembly, the aggregation of SL blocks will build a reversible hierarchical and discrete system where a single module can be numerously replicated to compose semi-interlocking components that further align, wrap, and braid around each other to form complex high-order aggregations. These aggregations can be disassembled and reassembled, responding dynamically to design inputs and changes with a unique capacity for reconfiguration. To use these aggregations as architectural structures, we developed computational tools that automate the configuration of SL blocks based on architectural design objectives. There are three critical phases in our work. First, we revisit the hierarchy of the SL block system and devise a top-down-type design strategy. From this, we propose two key questions: 1) How to translate 3D polyominoes into SL block assembly? 2) How to decompose the desired voxelized shapes into a set of 3D polyominoes with interlocking joints? These two questions can be considered the Hamiltonian path problem and the 3D polyomino tiling problem. Then, we derive our solution to each of them based on two methods. The first method is to construct the optimal closed path from an undirected graph built from the voxelized shape and translate the node sequence of the resulting path into the assembly sequence of SL blocks. The second approach describes interlocking relationships of 3D polyominoes as a joint connection graph. Lastly, we formulate the desired shapes and leverage our methods to achieve their reconfiguration within different levels. We show that our computational strategy will facilitate the efficient design of hierarchical interlocking structures with a self-replicating geometric module.

Keywords: computational design, SL-blocks, 3D polyomino puzzle, combinatorial problem

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7287 A Study on Fundamental Problems for Small and Medium Agricultural Machinery Industries in Central Region Area

Authors: P. Thepnarintra, S. Nikorn

Abstract:

Agricultural machinery industry plays an important role in the industrial development especially the production industry of the country. There has been continuing development responding to the higher demand of the production. However, the problem in agricultural machinery production still exists. Thus, the purpose of this research is to investigate problems on fundamental factors of industry based on the entrepreneurs’ point of view. The focus was on the small and medium size industry receiving a factory license typed number 0660 from the Department of Industrial Works. The investigation was on the comparison between the management of the small and medium size agricultural industry in 3 provinces in the central region of Thailand. Population in this study consisted of 189 company managers or managing directors, of which 101 were from the small size and 88 were from the medium size industry. The data were analyzed to find percentage, arithmetic mean, and standard deviation with independent sample T-test at the statistical significance .05. The results showed that the small and medium size agricultural machinery manufacturers in the central region of Thailand reported high problems in every aspect. When compared the problems on basic factors in running the business, it was found that there was no difference statistically at .05 in managing of the small and medium size agricultural machinery manufacturers. However, there was a statistically significant difference between the small and medium size agricultural machinery manufacturers on the aspect of policy and services of the government. The problems reported by the small and medium size agricultural machinery manufacturers were the services on public tap water and the problem on politic and stability of the country.

Keywords: agricultural machinery, manufacturers, problems, on running the business

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7286 Culture of Manager of a Medium or Small Enterprises

Authors: Omar Bendjimaa, Karzabi Abdelatif

Abstract:

Small and medium enterprises have witnessed several developments in recent years thanks to the policies and programs of support given by the state, and that is due to their importance in local and national development. Nevertheless, the success and development of these firms depends on a number of factors, especially the human element, for instance, the culture of the manager has its origin in the culture of the community and is of crucial influence in these firms. In fact, this culture is nothing more than a set of values, perceptions, beliefs, symbols and practices repeated, in addition to the knowledge it has received from the readings and the modern means of education. All these factors have an impact on the effectiveness of governance, its resolutions, instructions and performance of its function as a manager of a medium or small enterprise is inevitably affected by these cultural values, it is the driving force, the leader, and the observer at the same time.

Keywords: small and medium enterprises, the culture of the manager, the culture of the community, values, perceptions, beliefs, symbols, performance

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7285 Fast Short-Term Electrical Load Forecasting under High Meteorological Variability with a Multiple Equation Time Series Approach

Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

Abstract:

In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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7284 Enhancing Project Management Performance in Prefabricated Building Construction under Uncertainty: A Comprehensive Approach

Authors: Niyongabo Elyse

Abstract:

Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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7283 New Machine Learning Optimization Approach Based on Input Variables Disposition Applied for Time Series Prediction

Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

Abstract:

One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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