Search results for: face detection algorithm

Authors: Miriam Borchardt, Agata M. Ritter, Macaliston G. da Silva, Mauricio N. de Carvalho, Giancarlo M. Pereira

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This paper aims to analyze the barriers faced by social enterprises and based on that to propose a social business model framework that helps them to leverage their businesses and the social value delivered. A business model for social enterprises should amplify the value perception including social value for the beneficiaries while generating enough profit to escalate the business. Most of the social value beneficiaries are people from the base of the economic pyramid (BOP) or the ones that have specific needs. Because of this, products and services should be affordable to consumers while solving social needs of the beneficiaries. Developing products and services with social value require tie relationship among the social enterprises and universities, public institutions, accelerators, and investors. Despite being focused on social value and contributing to the beneficiaries’ quality of life as well as contributing to the governments that cannot properly guarantee public services and infrastructure to the BOP, many barriers are faced by the social enterprises to escalate their businesses. This is a work in process and five micro- and small-sized social enterprises in Brazil have been studied: (i) one has developed a kit for cervical uterine cancer detection to allow the BOP women to collect their own material and deliver to a laboratory for U$1,00; (ii) other has developed special products without lactose and it is about 70% cheaper than the traditional brands in the market; (iii) the third has developed prosthesis and orthosis to surplus needs that health public system have not done efficiently; (iv) the fourth has produced and commercialized menstrual panties aiming to reduce the consumption of dischargeable ones while saving money to the consumers; (v) the fifth develops and commercializes clothes from fabric wastes in a partnership with BOP artisans. The preliminary results indicate that the main barriers are related to the public system to recognize these products as public money that could be saved if they bought products from these enterprises instead of the multinational pharmaceutical companies, to the traditional distribution system (e.g. pharmacies) that avoid these products because of the low or non-existing profit, to the difficulty buying raw material in small quantities, to leverage investment by the investors, to cultural barriers and taboos. Interesting strategies to reduce the costs have been observed: some enterprises have focused on simplifying products, others have invested in partnerships with local producers and have developed their machines focusing on process efficiency to leverage investment by the investors.

Keywords: base of the pyramid, business model, social business, social business model, social enterprises

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Authors: Hugo Ribadeau Dumas

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In India, cities represent intense battlefields where patriarchal norms are simultaneously defied and reinforced. While Indian metropolises have witnessed numerous initiatives where women boldly claimed their right to the city, urban spaces still remain disproportionately unfriendly to female city-dwellers. As a result, the presence of strees (women, in Hindi) in the streets remains a socially and politically potent phenomenon. This paper explores how, in India, women engage with the city as compared to men. Borrowing analytical tools from urban geography, it uses Hindi cinema as a medium to map the extent to which activities, attitudes and experiences in urban spaces are highly gendered. The sample consists of 30 movies, both mainstream and independent, which were released between 2010 and 2020, were set in an urban environment and comprised at least one pivotal female character. The paper adopts a quantitative approach, consisting of the scrutiny of close to 3,000 minutes of footage, the labeling and time count of every scene, and the computation of regressions to identify statistical relationships between characters and the way they navigate the city. According to the analysis, female characters spend half less time in the public space than their male counterparts. When they do step out, women do it mostly for utilitarian reasons; inversely, in private spaces or in pseudo-public commercial places – like malls – they indulge in fun activities. For male characters, the pattern is the exact opposite: fun takes place in public and serious work in private. The characters’ attitudes in the streets are also greatly gendered: men spend a significant amount of time immobile, loitering, while women are usually on the move, displaying some sense of purpose. Likewise, body language and emotional expressiveness betray differentiated gender scripts: while women wander in the streets either smiling – in a charming role – or with a hostile face – in a defensive mode – men are more likely to adopt neutral facial expressions. These trends were observed across all movies, although some nuances were identified depending on the character's age group, social background, and city, highlighting that the urban experience is not the same for all women. The empirical pieces of evidence presented in this study are helpful to reflect on the meaning of public space in the context of contemporary Indian cities. The paper ends with a discussion on the link between universal access to public spaces and women's empowerment.

Keywords: cinema, Indian cities, public space, women empowerment

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Authors: V. S. Bessa, I. S. Moreira, S. Murgolo, C. Piccirillo, G. Mascolo, P. M. L. Castro

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The occurrence of pharmaceuticals in the environment has been a topic of increasing concern. Pharmaceuticals are not completely mineralized in the human body and are released on the sewage systems as the pharmaceutical itself and as their “biologically active” metabolites through excretion, as well as by improper elimination and disposal. Conventional wastewater treatment plants (WWTPs) are not designed to remove these emerging pollutants and they are thus released into the environment. The antiepileptic drug carbamazepine (CBZ) and the non-steroidal anti-inflammatory diclofenac (DCF) are two widely used pharmaceuticals, frequently detected in water bodies, including rivers and groundwater, in concentrations ranging from ng L 1 to mg L 1. These two compounds were classified as medium to high-risk pollutants in WWTP effluents and surface waters. Also, CBZ has been suggested as a molecular marker of wastewater contamination in surface water and groundwater and the European Union included DCF in the watch list of substances Directive to be monitored. In the present study, biodegradation of CBZ and DCF by the bacterial strain Labrys portucalensis F11, a strain able to degrade other pharmaceutical compounds, was assessed; tests were performed with F11 as single carbon and energy source, as well as in presence of 5.9mM of sodium acetate. In assays supplemented with 2.0 and 4.0 µM of CBZ, the compound was no longer detected in the bulk medium after 24hr and 5days, respectively. Complete degradation was achieved in 21 days for 11.0 µM and in 23 days for 21.0 µM. For the highest concentration tested (43.0 µM), 95% of degradation was achieved in 30days. Supplementation with acetate increased the degradation rate of CBZ, for all tested concentrations. In the case of DCF, when supplemented as a single carbon source, approximately 70% of DCF (1.7, 3.3, 8.4, 17.5 and 34.0 µM) was degraded in 30days. Complete degradation was achieved in the presence of acetate for all tested concentrations, at higher degradation rates. The detection of intermediates produced during DCF biodegradation was performed by UPLC-QTOF/MS/MS, which allowed the identification of a range of metabolites. Stoichiometric liberation of chorine occurred and no metabolites were detected at the end of the biodegradation assays suggesting a complete mineralization of DCF. Strain Labrys portucalensis F11 proved to be able to degrade these two top priority environmental contaminants and may be potentially useful for biotechnological applications/environment remediation.

Keywords: biodegradation, carbamazepine, diclofenac, pharmaceuticals

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: Srinaath Anbu Durai, Wang Zhaoxia

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Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

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Ensuring accurate radiotherapy with carbon therapy requires precise monitoring of radiation dose distribution within the patient's body. This monitoring is essential for targeted tumor treatment, minimizing harm to healthy tissues, and improving treatment effectiveness while lowering side effects. In our investigation, we employed a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo simulations. Initially, Geant4 simulations were utilized to extract the initial positions of secondary particles formed during interactions between carbon ions and water. These particles included protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we studied the relationship between the carbon ion beam and these secondary particles. Interaction Vertex Imaging (IVI) is valuable for monitoring dose distribution in carbon therapy. It provides details about the positions and amounts of secondary particles, particularly protons. The IVI method depends on charged particles produced during ion fragmentation to gather information about the range by reconstructing particle trajectories back to their point of origin, referred to as the vertex. In our simulations regarding carbon ion therapy, we observed a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the target's unique elongated geometry, which hindered the straightforward transmission of forward-generated protons. Consequently, the limited protons that emerged mostly originated from points close to the target entrance. The trajectories of fragments (protons) were approximated as straight lines, and a beam back-projection algorithm, using recorded interaction positions in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitoring of radiation dose, interaction vertex imaging

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Authors: Masoud Sheidai, Fahimeh Koohdar, Hashem Sharifi

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Juglans regia (L.) commonly known as Persian walnut of the genus Juglans L. (Juglandaceae) is one of the most important cultivated plant species due to its high-quality wood and edible nuts. The genetic diversity analysis is essential for conservation and management of tree species. Persian walnut is native from South-Eastern Europe to North-Western China through Tibet, Nepal, Northern India, Pakistan, and Iran. The species like Persian walnut, which has a wide range of geographical distribution, should harbor extensive genetic variability to adapt to environmental fluctuations they face. We aimed to study the population genetic structure of seven Persian walnut populations including three wild and four cultivated populations by using ISSR (Inter simple sequence repeats) and SRAP (Sequence related amplified polymorphism) molecular markers. We also aimed to compare the genetic variability revealed by ISSR neutral multilocus marker and rDNA ITS sequences. The studied populations differed in morphological features as the samples in each population were clustered together and were separate from the other populations. Three wild populations studied were placed close to each other. The mantel test after 5000 times permutation performed between geographical distance and morphological distance in Persian walnut populations produced significant correlation (r = 0.48, P = 0.002). Therefore, as the populations become farther apart, they become more divergent in morphological features. ISSR analysis produced 47 bands/ loci, while we obtained 15 SRAP bands. Gst and other differentiation statistics determined for these loci revealed that most of the ISSR and SRAP loci have very good discrimination power and can differentiate the studied populations. AMOVA performed for these loci produced a significant difference (< 0.05) supporting the above-said result. AMOVA produced significant genetic difference based on ISSR data among the studied populations (PhiPT = 0.52, P = 0.001). AMOVA revealed that 53% of the total variability is due to among population genetic difference, while 47% is due to within population genetic variability. The results showed that both multilocus molecular markers and ITS sequences can differentiate Persian walnut populations. The studied populations differed genetically and showed isolation by distance (IBD). ITS sequence based MP and Bayesian phylogenetic trees revealed that Iranian walnut cultivars form a distinct clade separated from the cultivars studied from elsewhere. Almost all clades obtained have high bootstrap value. The results indicated that a combination of multilpcus and sequencing molecular markers can be used in genetic differentiation of Persian walnut.

Keywords: genetic diversity, population, molecular markers, genetic difference

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Authors: Naum Simanovsky, Vladimir Goldman, Michael Zaidman

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Background: The optimal algorithm for the management of symptomatic tarsal coalition is still under discussion in pediatric literature. It's debatable what surgical steps are essential to achieve the best outcome. Method: The investigators retrospectively reviewed the records of twelve patients with symptomatic tarsal coalition that were treated operatively between 2017 and 2019. Only painful flat feet were operated. Two patients were excluded from the study due to lack of sufficient follow-up. Ten of eleven feet were treated with the combination of calcaneal lengthening osteotomy (CLO) and resection of coalition (RC). Only one foot was operated with CLO alone. In half of our patients, Achilles lengthening was performed. For two children, medial plication was added. Short leg cast was applied to all children for 6-8 weeks, and soft shoe insoles for medial arch support were prescribed after. Demographic, clinical, and radiographic records were reviewed. The outcome was evaluated using American Orthopedic Foot and Ankle Society (AOFAS) Ankle Hindfoot Score. Results: There were seven boys and three girls. The mean age at the time of surgery was 13.9 (range 12 to 17) years, and the mean follow-up was 18 (range 8 to 34) months. The early complications included one superficial wound infection and dehiscence. Late complication includes two children with residual forefoot supination. None of our patients required additional operations during the follow-up period. All feet achieved complete deformity correction or dramatic improvement. In the last follow-up, seven feet were painless, and four children had some mild pain after intensive activities. All feet achieved excellent and good scoring on AOFAS. Conclusions: Many patients with talocalcaneal coalition also have rigid or stiff, painful, flat feet. For these patients, the resection of coalition with concomitant CLO can be safely recommended.

Keywords: Tarsal coalition, calcaneal lengthening osteotomy., flat foot, coalition resection

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Authors: Chiou-Shiue Ko

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As is explicitly stipulated in Article 7 of the Enforcement Rules of the Special Education Act as amended in 1998, "in principle, children with disabilities should be integrated with normal children for preschool education". Since then, all cities and counties have been committed to promoting preschool inclusive education. The Education Department, New Taipei City Government, has been actively recruiting advisory groups of professors to assist in the implementation of inclusive education in preschools since 2001. Since 2011, the author of this study has been guiding Preschool Rainbow to implement inclusive education. Through field observations, meetings, and teaching demonstration seminars, this study explored the process of how inclusive education has been successfully implemented in collaboration with teachers of special education classes and regular classes in Preschool Rainbow. The implementation phases for inclusive education in a single academic year include the following: 1) Preparatory stage. Prior to implementation, teachers in special education and regular classes discuss ways of conducting inclusive education and organize reading clubs to read books related to curriculum modifications that integrate the eight education strategies, early treatment and education, and early childhood education programs to enhance their capacity to implement and compose teaching plans for inclusive education. In addition to the general objectives of inclusive education, the objective of inclusive education for special children is also embedded into the Individualized Education Program (IEP). 2) Implementation stage. Initially, a promotional program for special education is implemented for the children to allow all the children in the preschool to understand their own special qualities and those of special children. After the implementation of three weeks of reverse inclusion, the children in the special education classes are put into groups and enter the regular classes twice a week to implement adjustments to their inclusion in the learning area and the curriculum. In 2013, further cooperation was carried out with adjacent hospitals to perform development screening activities for the early detection of children with developmental delays. 3) Review and reflection stage. After the implementation of inclusive education, all teachers in the preschool are divided into two groups to record their teaching plans and the lessons learned during implementation. The effectiveness of implementing the objective of inclusive education is also reviewed. With the collaboration of all teachers, in 2015, Preschool Rainbow won New Taipei City’s “Preschool Light” award as an exceptional model for inclusive education. Its model of implementing inclusive education can be used as a reference for other preschools.

Keywords: collaboration, inclusive education, preschool, teachers, special education classes, regular classes

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Authors: Muhammad Naveed Babur, Maria Liaqat

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Background & Objective: People with disabilities especially neurological disabilities have many unmet health and rehabilitation needs, face barriers in accessing mainstream health-care services, and consequently have poor health. There are not sufficient epidemiological studies from Pakistan which assess barriers to neurorehabilitation and ways to counter it. Objectives: The objective of the study was to determine the challenges and to evaluate the barriers for neuro-rehabilitation services in developing countries. Methods: This is Exploratory sequential qualitative study based on the Panel discussion forum in International rehabilitation sciences congress and national rehabilitation conference 2017. Panel group discussion has been conducted in February 2017 with a sample size of eight professionals including Rehabilitation medicine Physician, Physical Therapist, Speech Language therapist, Occupational Therapist, Clinical Psychologist and rehabilitation nurse working in multidisciplinary/Interdisciplinary team. A comprehensive audio-videography have been developed, recorded, transcripted and documented. Data was transcribed and thematic analysis along with characteristics was drawn manually. Data verification was done with the help of two separate coders. Results: After extraction of two separate coders following results are emerged. General category themes are disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. Barriers identified at the level are high cost, stigma, lengthy course of recovery. Hospital related barriers are lack of social support and individually tailored goal setting processes. Organizational barriers identified are lack of basic diagnostic facilities, lack of funding and human resources. Recommendations given by panelists were investment in education, capacity building, infrastructure, governance support, strategies to promote communication and realistic goals. Conclusion: It is concluded that neurorehabilitation in developing countries need attention in following categories i.e. disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. This study also revealed barriers at the level of patient, hospital, organization. Recommendations were also given by panelists.

Keywords: disability, neurorehabilitation, telerehabilitation, disability

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Authors: Haiyan Huang, Jan Blommaert, Ellen Van Praet

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The embrace of neoliberal economic system in China has engendered the entry of global commodity capitalism into domestic Chinese market and ushered in the post-feminism that is closely associated with consumerism from western culture. Chinese women are instilled and thus hold the belief of empowering themselves and expressing their individualism through consumption. To unravel the consumerist ideologies embedded in Li’s discursive practices, we rely on critical discourse analysis (CDA) as our research framework. The data analyses suggest that cosmopolitanism and class are two repeating themes when Li engages in persuading consumerist behaviors from the female audience. Through hints and cues such as “going on business trips”, “traveling abroad”, “international brands” and among others, Li provides the access to and possibility of imagining cosmopolitan and middle class identity for his audience. Such yearning for western culture and global citizen identity also implicates the aspiration for a well-off socioeconomic status, proving that post-feminism in China not only embodies western consumerism but also implicates the struggle of class movement. These defining elements of choice and freedom are well-situated in contemporary Chinese society where women are enjoying more educational and economic independence than before. However a closer examination reveals conflicts between hegemonic discourse of post-feminism and the status quo. First, propagating women’s power through consumption obscure the entrenched gender inequality in China. Philosophies such as employment discrimination, equal payment, education right, etc., the cornerstones of feminism did not exist in China, leading to historical gender issues unsolved. Second, the lengthy broadcastings (which normally last more than 2 hours) featured with big discounts on products beg the question who are the real audience of ecommerce livestreaming. Seemingly addressing to young well-off Chinese females, Li’s discursive practice can be targeting at young but not wealthy girls who aspire to mimic the lifestyle of middle class women. By selling the idea of empowering and constructing identity through consuming beauty products (e.g., lipsticks), capitalists are endeavoring to create the post-feminism illusion and cause anxieties among Chinese females. Through in-depth analyses of hegemonic discourse on ecommerce livestreaming of lipsticks, the paper contributes to a better understanding of post-feminism in contemporary China and meanwhile illustrates the problems Chinese women face in securing power and equality.

Keywords: Chinese women, critical discourse analysis, ecommerce livestreaming, post-feminism

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Authors: Matthias Steffan, Franz Haas

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The production process grinding is one of the latest steps in a value-added manufacturing chain. Within this step, workpiece geometry and surface roughness are determined. Up to this process stage, considerable costs and energy have already been spent on components. According to the current state of the art, therefore, large safety reserves are calculated in order to guarantee a process capability. Especially for non-circular grinding, this fact leads to considerable losses of process efficiency. With present technology, various non-circular geometries on a workpiece must be grinded subsequently in an oscillating process where X- and Q-axis of the machine are coupled. With the approach of RPM-Synchronous Noncircular Grinding, such workpieces can be machined in an ordinary plung grinding process. Therefore, the workpieces and the grinding wheels revolutionary rate are in a fixed ratio. A non-circular grinding wheel is used to transfer its geometry onto the workpiece. The authors use a worldwide unique machine tool that was especially designed for this technology. Highest revolution rates on the workpiece spindle (up to 4500 rpm) are mandatory for the success of this grinding process. This grinding approach is performed in a two-step process. For roughing, a highly porous vitrified bonded grinding wheel with medium grain size is used. It ensures high specific material removal rates for efficiently producing the non-circular geometry on the workpiece. This process step is adapted by a force control algorithm, which uses acquired data from a three-component force sensor located in the dead centre of the tailstock. For finishing, a grinding wheel with a fine grain size is used. Roughing and finishing are performed consecutively among the same clamping of the workpiece with two locally separated grinding spindles. The approach of RPM-Synchronous Noncircular Grinding shows great efficiency enhancement in non-circular grinding. For the first time, three-dimensional non-circular shapes can be grinded that opens up various fields of application. Especially automotive industries show big interest in the emerging trend in finishing machining.

Keywords: efficiency enhancement, finishing machining, non-circular grinding, rpm-synchronous grinding

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Authors: Mohamed El Kory Yacoub, Ahmed Bezeid El Mamy Beyatt, Djibril Barry, Yanogo Pauline, Nicolas Meda

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Introduction: Rift Valley Fever is a zoonotic arbovirosis that severely affects ruminants, as well as humans. It causes abortions in pregnant females and deaths in young animals. The disease occurs during heavy rains followed by large numbers of mosquito vectors. The objective of this work is to evaluate the surveillance system for Rift Valley Fever. Methods: We conducted an evaluation of the Rift Valley Fiver surveillance system. Data were collected from the analysis of the national database of the Mauritanian Network of Animal Disease Epidemiological Surveillance at the Ministry of Rural Development, of RVF cases notified from the whole national territory, of questionnaires and interviews with all persons involved in RVF surveillance at the central level. The quality of the system was assessed by analyzing the quantitative attributes defined by the Centers for Disease Control and Prevention. Results: In 2019, 443 cases of RVF were notified by the surveillance system, of which 36 were positive. Among the notified cases of Rift Valley Fever, the 0- to the 3-year-old age group of small ruminants was the most represented with 49.21% of cases, followed by 33.33%, which was recorded in large ruminants in the 0 to 7-year-old age group, 11.11% of cases were older than seven years. The completeness of the data varied between 14.2% (age) and 100% (species). Most positive cases were recorded between October and November 2019 in seven different regions. Attribute analysis showed that 87% of the respondents were able to use the case definition well, and 78.8% said they were familiar with the reporting and feedback loop of the Rift Valley Fever data. 90.3% of the respondents found it easy, while 95% of them responded that it was easy for them to transmit their data to the next level. Conclusions: The epidemiological surveillance system for Rift Valley Fever in Mauritania is simple and representative. However, data quality, stability, and responsiveness are average, as the diagnosis of the disease requires laboratory confirmation and the average delay for this confirmation is long (13 days). Consequently, the lack of completeness of the recorded data and of description of cases in terms of time-place-animal, associated with the delay between the stages of the surveillance system can make prevention, early detection of epidemics, and the initiation of measures for an adequate response difficult.

Keywords: evaluation, epidemiological surveillance system, rift valley fever, mauritania, ruminants

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Authors: Deanne McArthur, Melinda Wall, Claire Hanlon, Dana Agnolin, Krista Davis, Melanie Dennis, Elizabeth Glidden, Anne Marie Smith, Claudette Thomson

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In Canada, as prevalence rates and severity of illness have increased among patients suffering from eating disorders, wait times have grown substantially. Patients in Canada often face wait times in excess of 12 months. It is known that delaying treatment for eating disorders contributes to poor patient outcomes and higher rates of symptom relapse. Improving interim services for adult patients awaiting outpatient treatment is a priority for an outpatient eating disorders clinic in Ontario, Canada. The clinical setting currently provides care for adults diagnosed with anorexia nervosa, bulimia nervosa and binge eating disorder. At present, the only support provided while patients are on the waitlist consists of communication with primary care providers regarding parameters for medical monitoring. The significance of this study will be to test the feasibility, acceptability and efficacy of an intervention to support adult patients awaiting outpatient eating disorder treatment for anorexia nervosa, bulimia nervosa and binge eating disorder. Methods: An intervention including psychoeducation, supportive resources, self-monitoring, and auxiliary referral will be pilot-tested with a group of patients in the summer of 2022 and detailed using a prospective cohort case study research design. The team will host patient focus groups in May 2022 to gather input informing the content of the intervention. The intervention will be pilot tested with newly-referred patients in June and July 2022. Patients who participate in the intervention will be asked to complete a survey evaluating the utility of the intervention and for suggestions, they may have for improvement. Preliminary findings describing the existing literature pertaining to waitlist interventions for patients with eating disorders, data gathered from the focus groups and early pilot testing results will be presented. Data analysis will continue throughout 2022 and early 2023 for follow-up publication and presentation in the summer of 2023. The aim of this study is to contribute to the body of knowledge pertaining to providing interim support to those patients waiting for treatment for eating disorders and, by extension, to improve outcomes for this population.

Keywords: eating disorders, waitlist management, intervention study, pilot test

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Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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Authors: Tao Zhang

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Job stress appears nearly everywhere especially in the hospitality industry because employees in this industry usually have to work long time and try to meet conflicting demands of their customers, managers, and company. To reduce job stress, employees of casino hotels try to perform leisure activities or tourism. However, casino employees often meet many obstacles or constraints when they plan to travel. Until now, there is little understanding as to why casino hotel employees often face many travel constraints or leisure barriers. What is more, few studies explore the relationship between travel constraints and job stress of casino employees. Therefore, this study is to explore the construct of casino hotel employees' travel constraints and the relationship among job stress, travel constraints, and job satisfaction. Using convenient sampling method, this study planned to investigate 500 front line employees and managers of ten casino hotels in Macau. A total of 500 questionnaires were distributed, and 414 valid questionnaires were received. The return rate of valid questionnaires is 82.8%. Several statistical techniques such as factor analysis, t-test, one-way ANOVA, and regression analysis were applied to analyze the collected data. The findings of this study are as follows. Firstly, by using factor analysis, this study found the travel constraints of casino employees include intrapersonal constraints, interpersonal constraints, and structural constraints. Secondly, by using regression analysis, the study found travel constraints are positively related with job stress while negatively related with job satisfaction. This means reducing travel constraints may create a chance for casino employees to travel so that they could reduce job stress, therefore raise their job satisfaction. Thirdly, this research divided the research samples into three groups by the degree of job stress. The three groups are low satisfaction group, medium satisfaction group, and high satisfaction group. The means values of these groups were compared by t-test. Results showed that there are significant differences of the means values of interpersonal constraints between low satisfaction group and high satisfaction group. This suggests positive interpersonal relationship especially good family member relationship reduce not only job stress but also travel constraints of casino employees. Interestingly, results of t-test showed there is not a significant difference of the means values of structural constraints between low satisfaction group and high satisfaction group. This suggests structural constraints are outside variables which may be related with tourism destination marketing. Destination marketing organizations (DMO) need use all kinds of tools and techniques to promote their tourism destinations so as to reduce structural constraints of casino employees. This research is significant for both theoretical and practical fields. From the theoretical perspective, the study found the internal relationship between travel constraints, job stress, and job satisfaction and the different roles of three dimensions of travel constraints. From the practical perspective, the study provides useful methods to reduce travel constraints and job stress, therefore, raise job satisfaction of casino employees.

Keywords: hotel, job satisfaction, job stress, travel constraints

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Authors: Katerina H. Takova, Ivan N. Minkov, Gergana G. Zahmanova

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Molecular farming is the production of recombinant proteins in plants with the aim to use the protein as a purified product, crude extract or directly in the planta. Plants gain more attention as expression systems compared to other ones due to the cost effective production of pharmaceutically important proteins, appropriate post-translational modifications, assembly of complex proteins, absence of human pathogens to name a few. In addition, transient expression in plant leaves enables production of recombinant proteins within few weeks. Hepatitis E virus (HEV) is a causative agent of acute hepatitis. HEV causes epidemics in developing countries and is primarily transmitted through the fecal-oral route. Presently, all efforts for development of Hepatitis E vaccine are focused on the Open Read Frame 2 (ORF2) capsid protein as it contains epitopes that can induce neutralizing antibodies. For our purpose, we used the CMPV-based vector-pEAQ-HT for transient expression of HEV ORF2 in Nicotiana benthamina. Different molecular analysis (Western blot and ELISA) showed that HEV ORF2 capsid protein was expressed in plant tissue in high-yield up to 1g/kg of fresh leaf tissue. Electron microscopy showed that the capsid protein spontaneously assembled in low abundance virus-like particles (VLPs), which are highly immunogenic structures and suitable for vaccine development. The expressed protein was recognized by both human and swine HEV positive sera and can be used as a diagnostic reagent for the detection of HEV infection. Production of HEV capsid protein in plants is a promising technology for further HEV vaccine investigations. Here, we reported for a rapid high-yield transient expression of a recombinant protein in plants suitable for vaccine production as well as a diagnostic reagent. Acknowledgments -The authors’ research on HEV is supported with grants from the Project PlantaSYST under the Widening Program, H2020 as well as under the UK Biotechnological and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Grant ‘Understanding and Exploiting Plant and Microbial Secondary Metabolism’ (BB/J004596/1). The authors want to thank Prof. George Lomonossoff (JIC, Norwich, UK) for his contribution.

Keywords: hepatitis E virus, plant molecular farming, transient expression, vaccines

Procedia PDF Downloads 150

Authors: Priyanshu Sharma

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Urban development mechanism has evolved over the years in India, and various planning models and tools have been adopted by different states. Large cities have been able to make and implement plans with the varied degree. However, it has been observed these mechanisms face challenges to gain the momentum in small and medium towns. Gujarat has a very robust legislation that empowers planning authorities to prepare development plans (DP) and town planning scheme (TPS). The DP- TPS planning methods are quite popular for large cities in Gujarat. However, it has been observed that in the smaller towns these methods of plan preparation are facing severe agitations. Recently, development authorities of many small towns like Himmatnagar, Nadiad, and Junagadh, etc. have faced serious protest from local residents. This is because of the large amount of land deduction under the provisions of DP and TPS. And this number of opposition has been increasing since 2012 in Gujarat. This study aims to understand in detail the reasons for agitation against the plans prepared by smaller towns. It will further try to see whether the current framework of urban planning (DP and TPS) are really suitable for these towns. After understanding the development concerns and background, the aim and objectives of the study were outlined: Aim: To evaluate the suitability and acceptability of the current urban development mechanism for the small and medium towns. Objectives: (i) To review the GTPUD Act and identify the provision related to small and medium towns (ii) To understand preparation process of development plan and town planning scheme and issues related to it (iii) To understand the issues raised by the different stakeholder w.r.t plan because of which the plan and authority was agitated (iv) To find out the possible option through which these plans can be made suitable and acceptable to the stakeholder. The approach of this study is more qualitative based with the intention to understand the time frame process of preparation of development plan and town planning scheme and issues related to it. On the basis of literature study, the three towns were selected, and the detailed questionnaire was prepared for the stakeholders (development authorities and local residents) which include the time process taken in the preparation of DP and TPS and what were issues faced during the process and who all were involved. Lastly, the study looks into aspects of the land value of original plots and readjusted plots by concluding the argument whether this TP scheme model really worked in small and medium towns. Because the land deduction under TP scheme is allowed up to 50% as per the act and there is no distinct provision for small and medium towns under the act, so how this could be justified to smaller towns where the market value have not changed over the years. After analyzing the issues and reason behind the agitation against the DP and TPS in these small and medium towns. The broader recommendation has been given which can make these plans acceptable and suitable for the stakeholder.

Keywords: development plans, medium towns, small towns, town planning schemes

Procedia PDF Downloads 155

Authors: Andleeb Zahra, Itrat Rubab, Sumaira Malik, Amina Khan, Muhammad Jawad Khan, M. Qaiser Fatmi

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Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. Recent studies have highlighted the role of miRNA in disease pathology, indicating its potential use in an early diagnostic tool. miRNAs are small, double stranded, non-coding RNAs that regulate gene expression by deregulating mRNAs. miRNAs play important roles in modifying various cellular processes such as cell growth, differentiation, apoptosis, and immune response. Dis-regulated expression of miRNAs is known to affect the cell growth, and this may function as tumor suppressors or oncogenes in various cancers. Objectives: The main objectives of this study were to characterize the extracellular miRNAs involved in oral cancer (OC) to assist early detection of cancer as well as to propose a list of genes that can potentially be used as biomarkers of OC. We used gene expression data by microarrays already available in literature. Materials and Methods: In the first step, a total of 318 miRNAs involved in oral carcinoma were shortlisted followed by the prediction of their target genes. Simultaneously, the differentially expressed genes (DEGs) of oral carcinoma from all experiments were identified. The common genes between lists of DEGs of OC based on experimentally proven data and target genes of each miRNA were identified. These common genes are the targets of specific miRNA, which is involved in OC. Finally, a list of genes was generated which may be used as biomarker of OC. Results and Conclusion: In results, we included some of pathways in cancer to show the change in gene expression under the control of specific miRNA. Ingenuity pathway analysis (IPA) provided a list of major biomarkers like CDH2, CDK7 and functional enrichment analysis identified the role of miRNA in major pathways like cell adhesion molecules pathway affected by cancer. We observed that at least 25 genes are regulated by maximum number of miRNAs, and thereby, they can be used as biomarkers of OC. To better understand the role of miRNA with respect to their target genes further experiments are required, and our study provides a platform to better understand the miRNA-OC relationship at genomics level.

Keywords: biomarkers, gene expression, miRNA, oral carcinoma

Procedia PDF Downloads 371

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 124

Authors: Lisa Tragbar

Abstract:

In post-war scenarios, reconstruction is a principle towards creating a Just Peace in order to restore a stable post-war society. Just peace theorists explore normative behaviour after war, including the duties and responsibilities of different actors and peacebuilding strategies to achieve a lasting, positive peace. Environmental peace ethicists have argued for including the role of nature in the Ethics of War and Peace. This text explores the question of why and how to rethink the value of nature in post-war scenarios. The aim is to include the rights of nature within a maximalist account of reconstruction by highlighting sumak kawsay in the post-war period. Destruction of nature is usually considered collateral damage in war scenarios. Common universal standards for post-war reconstruction are restitution, compensation and reparation programmes, which is mostly anthropocentric approach. The problem of reconstruction in the aftermath of war is the instrumental value of nature. The responsibility to rebuild needs to be revisited within a non-anthropocentric context. There is an ongoing debate about a minimalist or maximalist approach to post-war reconstruction. While Michael Walzer argues for minimalist in-and-out interventions, Alex Bellamy argues for maximalist strategies such as the responsibility to protect, a UN-concept on how face mass atrocity crimes and how to reconstruct peace. While supporting the tradition of maximalist responsibility to rebuild, these normative post-Bellum concepts do not yet sufficiently consider the rights of nature in the aftermath of war. While reconstruction of infrastructures seems important and necessary, concepts that strengthen the intrinsic value of nature in post-bellum measures must also be included. Peace is not Just Peace without a thriving nature that provides the conditions and resources to live and guarantee human rights. Ecuador's indigenous philosophy of life can contribute to the restoration of nature after war by changing the perspective on the value of nature. The sumak kawsay includes the de-hierarchisation of humans and nature and the principle of reciprocity towards nature. Transferring this idea of life and interconnectedness to post-war reconstruction practices, post bellum perpetrators have restorative obligations not only to people but also to nature. This maximalist approach would include both a restitutive principle, by restoring the balance between humans and nature, and a retributive principle, by punishing the perpetrators through compensatory duties to nature. A maximalist approach to post-war reconstruction that takes into account the rights of nature expands the normative post-war questions to include a more complex field of responsibilities. After a war, Just Peace is restored once not only human rights but also the rights of nature are secured. A minimalist post-bellum approach to reconstruction does not locate future problems at their source and does not offer a solution for the inclusion of obligations to nature. There is a lack of obligations towards nature after a war, which can be changed through a different perspective: The indigenous philosophy of life provides the necessary principles for a comprehensive reconstruction of Just Peace.

Keywords: normative ethics, peace, post-war, sumak kawsay, applied ethics

Procedia PDF Downloads 77

Authors: Shoaib Alvi

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Mahatma Gandhi was said “Man becomes great exactly in the degree in which he works for the welfare of his fellow-men”. Labor welfare is an important fact of Industrial relations. With the growth of industrialization, mechanization and computerization, labor welfare measures have got the fillip. The author believes that Labor welfare includes provisions of various facilities and amenities in and around the work place for the better life of the workers. Labor welfare is, thus, one of the major determinants of industrial relations. It comprises all human efforts the work place for the better life of the worker. The social and economic aspects of the life of the workers have the direct influence on the social and economic development of the nation. Author thinks that there could be multiple objectives in having, labor welfare programme the concern for improving the lot of the workers, a philosophy of humanitarianism or internal social responsibility, a feeling of concern, and caring by providing some of life's basic amenities, besides the basic pay packet. Such caring is supposed to build a sense of loyalty on the part of the employee towards the organization. The author thinks that Social security is the security that the State furnishes against the risks which an individual of small means cannot today, stand up to by himself even in private combination with his fellows. Social security is one of the pillars on which the structure of a welfare state rests, and it constitutes the hardcore of social policy in most countries. It is through social security measures that the state attempts to maintain every citizen at a certain prescribed level below which no one is allowed to fall. According to author, social assistance is a method according to which benefits are given to the needy persons, fulfilling the prescribed conditions, by the government out of its own resources. Author has analyzed and studied the relationship between the labor welfare social security and also studied various international conventions on provisions of social security by International Authorities like United Nations, International Labor Organization, and European Union etc. Author has also studied and analyzed concept of labor welfare and social security schemes of many countries around the globe ex:- Social security in Australia, Social security in Switzerland, Social Security (United States), Mexican Social Security Institute, Welfare in Germany, Social security schemes of India for labor welfare in both organized sector and unorganized sector. In this Research paper, Author has done the study on the Conceptual framework of the Labour Welfare. According to author, labors are highly perishable, which need constant welfare measures for their upgradation and performance in this field. At last author has studied role of trade unions and labor welfare unions and other institutions working for labor welfare, in this research paper author has also identified problems these Unions and labor welfare bodies’ face and tried to find out solutions for the problems and also analyzed various steps taken by the government of various countries around the globe.

Keywords: labor welfare, internal social responsibility, social security, international conventions

Procedia PDF Downloads 573

Authors: Nadia K. Thalji

Abstract:

The shamanic odyssey of Hushahu, a courageous indigenous woman from the Amazon, reverberates with profound significance, resonating far beyond the confines of her tribal boundaries. This abstract explores Hushahu's transformative journey, which serves as a beacon of empowerment for indigenous women across the Amazon region. Hushahu's narrative unfolds against the backdrop of entrenched gender norms and colonial legacies that have historically marginalized women from spiritual leadership and ritual practices. Despite societal expectations and entrenched traditions, Hushahu boldly embraces her calling as a shaman, defying cultural constraints and challenging prevailing gender norms. Her journey represents a symbolic uprising against centuries of patriarchal dominance, offering a glimpse into the resilience and strength of indigenous women. Drawing upon Jungian psychology, Hushahu's quest can be understood as a profound exploration of the symbolic dimensions of the psyche. Through Hushahu’s initiation rituals and visionary experiences, the initiate embarks on a transformative journey of self-discovery, encountering archetypal symbols and tapping into the collective unconscious. Symbolism permeates the path, guiding Hushahu through the depths of the rainforest and illuminating the hidden realms of consciousness. Central to Hushahu's narrative is the theme of empowerment—a theme that transcends individual experience to catalyze broader social change. As Hushahu finds a voice amidst the echoes of ancestral wisdom, the journey inspires a ripple effect of empowerment throughout indigenous communities. Other women within Hushahu's tribe and neighboring societies are emboldened to challenge traditional gender roles, stepping into leadership positions and reclaiming their rightful place in spiritual practices. The resonance of Hushahu's journey extends beyond the Amazon, reverberating across cultural boundaries and igniting conversations about gender equality and indigenous rights. Through courageous defiance of cultural norms, Hushahu emerges as a symbol of resilience and empowerment, offering hope and inspiration to marginalized women around the world. In conclusion, Hushahu's shamanic journey embodies the sacred echoes of empowerment, echoing across generations and landscapes. The story serves as a testament to the enduring power of the human spirit and the transformative potential of reclaiming one's voice in the face of adversity. As indigenous women continue to rise, Hushahu's legacy stands as a beacon of hope, illuminating the path towards a more equitable and inclusive world.

Keywords: shamanic leadership, indigenous empowerment, gender norms, cultural transformation

Procedia PDF Downloads 45

Authors: Arunas Burinskas, Aurelija Burinskiene

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On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

Procedia PDF Downloads 131

Authors: Anderson S. Fonseca, Italo F. S. Da Silva, Robert D. A. Santos, Mayara G. Da Silva, Pedro H. C. Vieira, Antonio M. S. Sobrinho, Victor H. B. Lemos, Petterson S. Diniz, Anselmo C. Paiva, Eliana M. G. Monteiro

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In Brazil, the National Electric Energy Agency (ANEEL) establishes that electrical energy companies are responsible for measuring and billing their customers. Among these regulations, it’s defined that a company must bill your customers within 27-33 days. If a relocation or a change of period is required, the consumer must be notified in writing, in advance of a billing period. To make it easier to organize a workday’s measurements, these companies create a reading plan. These plans consist of grouping customers into reading groups, which are visited by an employee responsible for measuring consumption and billing. The creation process of a plan efficiently and optimally is a capacitated clustering problem with constraints related to homogeneity and compactness, that is, the employee’s working load and the geographical position of the consuming unit. This process is a work done manually by several experts who have experience in the geographic formation of the region, which takes a large number of days to complete the final planning, and because it’s human activity, there is no guarantee of finding the best optimization for planning. In this paper, the GBKMeans method presents a technique based on K-Means and genetic algorithms for creating a capacitated cluster that respects the constraints established in an efficient and balanced manner, that minimizes the cost of relocating consumer units and the time required for final planning creation. The results obtained by the presented method are compared with the current planning of a real city, showing an improvement of 54.71% in the standard deviation of working load and 11.97% in the compactness of the groups.

Keywords: capacitated clustering, k-means, genetic algorithm, districting problems

Procedia PDF Downloads 195

Authors: Rammah Abdlbagi, Egmen Tazcan, Kiriti Tripathi, Vinayagam Sudhakar, Thomas Swallow, Aakash Pai

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Introduction and Objectives: MRI has an increasing role in the diagnosis and staging of prostate cancer. Multiparametric MRI includes multiple sequences, including T2 weighting, diffusion weighting, and dynamic contrast enhancement (DCE). Administration of DCE is expensive, time-consuming, and requires medical supervision due to the risk of anaphylaxis. Biparametric MRI (bpMRI), without DCE, overcomes many of these issues; however, there is conflicting data on its accuracy. Furthermore, data on the concordance between bpMRI lesion and pathology specimen, as well as the rates of cancer stage upgrading after surgery, is limited within the available literature. This study aims to examine the diagnostic test accuracy of bpMRI in the diagnosis of prostate cancer and radiological assessment of prostate cancer staging. Specifically, we aimed to evaluate the ability of bpMRI to accurately localise malignant lesions to better understand its accuracy and application in MRI-targeted biopsies. Materials and Methods: One hundred and forty patients who underwent bpMRI prior to radical prostatectomy (RP) were retrospectively reviewed from a single institution. Histological grade from the prostate biopsy was compared with surgical specimens from RP. Clinically significant prostate cancer (csPCa) was defined as Gleason grade group ≥2. bpMRI staging was compared with RP histology. Results: Overall sensitivity of bpMRI in diagnosing csPCa independent of location and staging was 98.87%. Of the 140 patients, 29 (20.71%) had their prostate biopsy histology upgraded at RP. 61 (43.57%) patients had csPca noted on RP specimens in areas that were not identified on the bpMRI. 55 (39.29%) had upstaging after RP from the original staging with bpMRI. Conclusions: Whilst the overall sensitivity of bpMRI in predicting any clinically significant cancer was good, there was notably poor concordance in the location of the tumour between bpMRI and eventual RP specimen. The results suggest that caution should be exercised when using bpMRI for targeted prostate biopsies and validates the continued role of systemic biopsies. Furthermore, a significant number of patients were upstaged at RP from their original staging with bpMRI. Based on these findings, bpMRI results should be interpreted with caution and can underestimate TNM stage, requiring careful consideration of treatment strategy.

Keywords: biparametric MRI, Ca prostate, staging, post prostatectomy histology

Procedia PDF Downloads 66

Authors: Neelam Kadyan, Pratima Ranga, Yogender

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Indigenous people are the One who are affected by the climate change the most, although there have contributed little to its causes. This is largely a result of their historic dependence on local biological diversity, ecosystem services and cultural landscapes as a source of their sustenance and well-being. Comprising only four percent of the world’s population they utilize 22 percent of the world’s land surface. Despite their high exposure-sensitivity indigenous peoples and local communities are actively responding to changing climatic conditions and have demonstrated their resourcefulness and resilience in the face of climate change. Traditional Indigenous territories encompass up to 22 percent of the world’s land surface and they coincide with areas that hold 80 percent of the planet’s biodiversity. Also, the greatest diversity of indigenous groups coincides with the world’s largest tropical forest wilderness areas in the Americas (including Amazon), Africa, and Asia, and 11 percent of world forest lands are legally owned by Indigenous Peoples and communities. This convergence of biodiversity-significant areas and indigenous territories presents an enormous opportunity to expand efforts to conserve biodiversity beyond parks, which tend to benefit from most of the funding for biodiversity conservation. Tapping on Ancestral Knowledge Indigenous Peoples are carriers of ancestral knowledge and wisdom about this biodiversity. Their effective participation in biodiversity conservation programs as experts in protecting and managing biodiversity and natural resources would result in more comprehensive and cost effective conservation and management of biodiversity worldwide. Addressing the Climate Change Agenda Indigenous Peoples has played a key role in climate change mitigation and adaptation. The territories of indigenous groups who have been given the rights to their lands have been better conserved than the adjacent lands (i.e., Brazil, Colombia, Nicaragua, etc.). Preserving large extensions of forests would not only support the climate change objectives, but it would respect the rights of Indigenous Peoples and conserve biodiversity as well. A climate change agenda fully involving Indigenous Peoples has many more benefits than if only government and/or the private sector are involved. Indigenous peoples are some of the most vulnerable groups to the negative effects of climate change. Also, they are a source of knowledge to the many solutions that will be needed to avoid or ameliorate those effects. For example, ancestral territories often provide excellent examples of a landscape design that can resist the negatives effects of climate change. Over the millennia, Indigenous Peoples have developed adaptation models to climate change. They have also developed genetic varieties of medicinal and useful plants and animal breeds with a wider natural range of resistance to climatic and ecological variability.

Keywords: ancestral knowledge, cost effective conservation, management, indigenous peoples, climate change

Procedia PDF Downloads 676

Authors: Yudo Prasetyo, Hana Sugiastu Firdaus, Diyanah Diyanah

Abstract:

The phenomenon of the lack of clean water supply in several big cities in Indonesia is a major problem in the development of urban areas. Moreover, in the city of Semarang, the population density and growth of physical development is very high. Continuous and large amounts of underground water (aquifer) exposure can result in a drastically aquifer supply declining in year by year. Especially, the intensity of aquifer use in the fulfilment of household needs and industrial activities. This is worsening by the land subsidence phenomenon in some areas in the Semarang city. Therefore, special research is needed to know the spatial correlation of the impact of decreasing aquifer capacity on the land subsidence phenomenon. This is necessary to give approve that the occurrence of land subsidence can be caused by loss of balance of pressure on below the land surface. One method to observe the correlation pattern between the two phenomena is the application of remote sensing technology based on radar and optical satellites. Implementation of Differential Interferometric Synthetic Aperture Radar (DINSAR) or Small Baseline Area Subset (SBAS) method in SENTINEL-1A satellite image acquisition in 2014-2017 period will give a proper pattern of land subsidence. These results will be spatially correlated with the aquifer-declining pattern in the same time period. Utilization of survey results to 8 monitoring wells with depth in above 100 m to observe the multi-temporal pattern of aquifer change capacity. In addition, the pattern of aquifer capacity will be validated with 2 underground water cavity maps from observation of ministries of energy and natural resources (ESDM) in Semarang city. Spatial correlation studies will be conducted on the pattern of land subsidence and aquifer capacity using overlapping and statistical methods. The results of this correlation will show how big the correlation of decrease in underground water capacity in influencing the distribution and intensity of land subsidence in Semarang city. In addition, the results of this study will also be analyzed based on geological aspects related to hydrogeological parameters, soil types, aquifer species and geological structures. The results of this study will be a correlation map of the aquifer capacity on the decrease in the face of the land in the city of Semarang within the period 2014-2017. So hopefully the results can help the authorities in spatial planning and the city of Semarang in the future.

Keywords: aquifer, differential interferometric synthetic aperture radar (DINSAR), land subsidence, small baseline area subset (SBAS)

Procedia PDF Downloads 181

Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

Abstract:

The COVID-19 pandemic has been a major and global disruption that has affected all supply chains on a worldwide scale. Consequently, the question posed by this communication is to understand how - in the face of such disruptions - supply chains, including their actors, management tools, and processes, react, survive, adapt, and even improve. To do so, the concepts of resilience and antifragility applied to a supply chain have been leveraged. This article proposes to perceive resilience as a step to surpass in moving towards antifragility. The research objective is to propose an analytical framework to measure and compare resilience and antifragility, with antifragility seen as a property of a system that improves when subjected to disruptions rather than merely resisting these disruptions, as is the case with resilience. A unique case study was studied - MSF logistics (France) - using a qualitative methodology. Semi-structured interviews were conducted in person and remotely in multiple phases: during and immediately after the COVID crisis (8 interviews from March 2020 to April 2021), followed by a new round from September to November 2023. A Delphi method was employed. The interviews were analyzed using coding and a thematic framework. One of the theoretical contributions is consolidating the field of supply chain resilience research by precisely characterizing the dimensions of resilience for a humanitarian supply chain (Reorganization, Collaboration mediated by IS, Humanitarian culture). In this regard, a managerial contribution of this study is providing a guide for managers to identify the four dimensions and sub-dimensions of supply chain resilience. This enables managers to focus their decisions and actions on dimensions that will enhance resilience. Most importantly, another contribution is comparing the concepts of resilience and antifragility and proposing an analytical framework for antifragility—namely, the mechanisms on which MSF logistics relied to capitalize on uncertainties, contingencies, and shocks rather than simply enduring them. For MSF Logistics, antifragility manifested through the ability to identify opportunities hidden behind the uncertainties and shocks of COVID-19, reducing vulnerability, and fostering a culture that encourages innovation and the testing of new ideas. Logistics, particularly in the humanitarian domain, must be able to adapt to environmental disruptions. In this sense, this study identifies and characterizes the dimensions of resilience implemented by humanitarian logistics. Moreover, this research goes beyond the concept of resilience to propose an analytical framework for the concept of antifragility. The organization studied emerged stronger from the COVID-19 crisis due to the mechanisms we identified, allowing us to characterize antifragility. Finally, the results show that the information system plays a key role in antifragility.

Keywords: antifragility, humanitarian supply chain, information systems, qualitative research, resilience.

Procedia PDF Downloads 63

Authors: Mohit Kumar, Beklashwar Salona, Shiv Murti, Mukesh Singh

Abstract:

We report here a case of five-months old male baby, born as second child of non-consanguineous parents with no considerable history of genetic abnormality which was referred to our cytogenetic laboratory for chromosomal analysis. Physical dysmorphic facial features including mongoloid face, cleft palate, simian crease, and developmental delay were observed. We present this case with unique balanced autosomal translocation of t(3;10)(p21;p13). The risk of phenotypic abnormalities based on de novo balanced translocation was estimated to be 7%. The association of balanced chromosomal rearrangement with Down syndrome features such as multiple congenital anomalies, facial dysmorphism and congenital heart anomalies are very rare in a 5-months old male child. Trisomy-21 is not uncommon in chromosomal abnormality with the birth defect and balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion (RSA). Two ml heparinized peripheral blood cells cultured in RPMI-1640 for 72 hours supplemented with 20% fetal bovine serum, phytohemagglutinin (PHA), and antibiotics were used for chromosomal analysis. A total 30 metaphases images were captured using Olympus-BX51 microscope and analyzed using Bio-view karyotyping software through GTG-banding (G bands by trypsin and Giemsa) according to International System for Human Cytogenetic Nomenclature 2016. The results showed balanced translocation between short arm of chromosome # 3 and short arm of chromosome # 10. The karyotype of the child was found to be 46,XY,t(3;10)(p21; p13). Chromosomal abnormalities are one of the major causes of birth defect in new born babies. Also, balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion. The index case presented with dysmorphic facial features and had a balanced translocation 46,XY,t(3;10)(p21;p13). This translocation with break points at (p21; p13) has not been reported in the literature in a child with facial dysmorphism. To the best of our knowledge, this is the first report of novel balanced translocation t(3;10) with break points in a child with dysmorphic features. We found balanced chromosomal translocation instead of any trisomy or unbalanced aberrations along with some phenotypic abnormalities. Therefore, we suggest that such novel balanced translocation with abnormal phenotype should be reported in order to enable the pathologist, pediatrician, and gynecologist to have a better insight into the intricacies of chromosomal abnormalities and their associated phenotypic features. We hypothesized that dysmorphic features as seen in this case may be the result of change in the pattern of genes located at the breakpoint area in balanced translocations or may be due to deletion or mutation of genes located on the p-arm of chromosome # 3 and p-arm of chromosome # 10.

Keywords: balanced translocation, karyotyping, phenotypic abnormalities, facial dimorphisms

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