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Authors: F. Varga, Z. Liber, J. Jakše, A. Turudić, Z. Šatović, I. Radosavljević, N. Jeran, M. Grdiša

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Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.; Asteraceae), a source of the commercially dominant plant insecticide pyrethrin, is a species endemic to the eastern Adriatic. Genetic diversity of T. cinerariifolium was previously studied using amplified fragment length polymorphism (AFLP) markers. However, microsatellite markers (single sequence repeats - SSRs) are more informative because they are codominant, highly polymorphic, locus-specific, and more reproducible, and thus are most often used to assess the genetic diversity of plant species. Dalmatian pyrethrum is an outcrossing diploid (2n = 18) whose large genome size and high repeatability have prevented the success of the traditional approach to SSR markers development. The advent of next-generation sequencing combined with the specifically developed method recently enabled the development of, to the author's best knowledge, the first set of SSRs for genomic characterization of Dalmatian pyrethrum, which is essential from the perspective of plant genetic resources conservation. To evaluate the effectiveness of the developed SSR markers in genetic differentiation of Dalmatian pyrethrum populations, a preliminary genetic diversity study was conducted on 30 individuals from three geographically distinct natural populations in Croatia (northern Adriatic island of Mali Lošinj, southern Adriatic island of Čiovo, and Mount Biokovo) based on 12 SSR loci. Analysis of molecular variance (AMOVA) by randomization test with 10,000 permutations was performed in Arlequin 3.5. The average number of alleles per locus, observed and expected heterozygosity, probability of deviations from Hardy-Weinberg equilibrium, and inbreeding coefficient was calculated using GENEPOP 4.4. Genetic distance based on the proportion of common alleles (DPSA) was calculated using MICROSAT. Cluster analysis using the neighbor-joining method with 1,000 bootstraps was performed with PHYLIP to generate a dendrogram. The results of the AMOVA analysis showed that the total SSR diversity was 23% within and 77% between the three populations. A slight deviation from Hardy-Weinberg equilibrium was observed in the Mali Lošinj population. Allele richness ranged from 2.92 to 3.92, with the highest number of private alleles observed in the Mali Lošinj population (17). The average observed DPSA between 30 individuals was 0.557. The highest DPSA (0.875) was observed between several pairs of Dalmatian pyrethrum individuals from the Mali Lošinj and Mt. Biokovo populations, and the lowest between two individuals from the Čiovo population. Neighbor-joining trees, based on DPSA, grouped individuals into clusters according to their population affiliation. The separation of Mt. Biokovo clade was supported (bootstrap value 58%), which is consistent with the previous study on AFLP markers, where isolated populations from Mt. Biokovo differed from the rest of the populations. The developed SSR markers are an effective tool for assessing the genetic diversity and structure of natural Dalmatian pyrethrum populations. These preliminary results are encouraging for a future comprehensive study with a larger sample size across the species' range. Combined with the biochemical data, these highly informative markers could help identify potential genotypes of interest for future development of breeding lines and cultivars that are both resistant to environmental stress and high in pyrethrins. Acknowledgment: This work has been supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.) insecticidal potential’- (PyrDiv) (IP-06-2016-9034) and by project KK.01.1.1.01.0005, Biodiversity and Molecular Plant Breeding, at the Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia.

Keywords: Asteraceae, genetic diversity, genomic SSRs, NGS, pyrethrum, Tanacetum cinerariifolium

Procedia PDF Downloads 100

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Jai Bakliya, Palak Dhamecha

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Today customer satisfaction is given utmost priority be it any industry. But when it comes to hospitality industry this applies even more as they come in direct contact with customers while providing them services. Employee engagement is new concept adopted by Human Resource Department which impacts customer satisfactions. To satisfy your customers, it is necessary to see that the employees in the organisation are satisfied and engaged enough in their work that they meet the company’s expectations and contribute in the process of achieving company’s goals and objectives. After all employees is human capital of the organisation. Employee engagement has become a top business priority for every organisation. In this fast moving economy, business leaders know that having a potential and high-performing human resource is important for growth and survival. They recognize that a highly engaged manpower can increase innovation, productivity, and performance, while reducing costs related to retention and hiring in highly competitive talent markets. But while most executives see a clear need to improve employee engagement, many have yet to develop tangible ways to measure and tackle this goal. Employee Engagement is an approach which is applied to establish an emotional connection between an employee and the organisation which ensures the employee’s commitment towards his work which affects the productivity and overall performance of the organisation. The study was conducted in hospitality industry. A popular branded hotel was chosen as a sample unit. Data were collected, both qualitative and quantitative from respondents. It is found that employee engagement level of the organisation (Hotel) is quite low. This means that employees are not emotionally connected with the organisation which may in turn, affect performance of the employees it is important to note that in hospitality industry individual employee’s performance specifically in terms of emotional engagement is critical and, therefore, a low engagement level may contribute to low organisation performance. An attempt to this study was made to identify employee engagement level. Another objective to take this study was to explore the factors impeding employee engagement and to explore employee engagement facilitation. While in the hospitality industry where people tend to work for as long as 16 to 18 hours concepts like employee engagement is essential. Because employees get tired of their routine job and in case where job rotation cannot be done employee engagement acts as a solution. The study was conducted at Trident Hotel, Udaipur. It was conducted on the sample size of 30 in-house employees from 6 different departments. The various departments were: Accounts and General, Front Office, Food & Beverage Service, Housekeeping, Food & Beverage Production and Engineering. It was conducted with the help of research instrument. The research instrument was Questionnaire. Data collection source was primary source. Trident Udaipur is one of the busiest hotels in Udaipur. The occupancy rate of the guest over there is nearly 80%. Due the high occupancy rate employees or staff of the hotel used to remain very busy and occupied all the time in their work. They worked for their remuneration only. As a result, they do not have any encouragement for their work nor they are interested in going an extra mile for the organisation. The study result shows working environment factors including recognition and appreciation, opinions of the employee, counselling, feedback from superiors, treatment of managers and respect from the organisation are capable of increasing employee engagement level in the hotel. The above study result encouraged us to explore the factors contributed to low employee engagement. It is being found that factors such as recognition and appreciation, feedback from supervisors, opinion of the employee, counselling, feedback from supervisors, treatment from managers has contributed negatively to employee engagement level. Probable reasons for the low contribution are number of employees gave the negative feedback in accordance to the factors stated above of the organisation. It seems that the structure of organisation itself is responsible for the low contribution of employee engagement. The scope of this study is limited to trident hotel situated in the Udaipur. The limitation of the study was that that the results or findings were only based on the responses of respondents of Trident, Udaipur. And so the recommendations were also applicable in Trident, Udaipur and not to all the like organisations across the country. Through the data collected was further analysed, interpreted and concluded. On the basis of the findings, suggestions were provided to the hotel for improvisation.

Keywords: human resource, employee engagement, research, study

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Authors: Kevin F. Hsu, Alvin Chua, Sarah X. Lin

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As a multilingual society, Singaporean names for different parts of the city have changed over time. Residents included Indigenous Malays, dialect-speakers from China, European settler-colonists, and Tamil-speakers from South India. Each group would name locations in their own languages. Today, as ancestral tongues are increasingly supplanted by English, contemporary Singaporeans’ understanding of once-common place names is disappearing. After demolition or redevelopment, some urban places will only exist in archival records or in human memory. United Nations conferences on the standardization of geographic names have called attention to how place names relate to identity, well-being, and a sense of belonging. The Singapore Place-Naming Project responds to these imperatives by capturing past and present place names through digitizing historical maps, mining archival records, and applying selective crowd-sourcing to trace the evolution of place names throughout the city. The project ensures that both formal and vernacular geographical names remain accessible to historians, city planners, and the public. The project is compiling a gazetteer, a geospatial archive of placenames, with streets, buildings, landmarks, and other points of interest (POI) appearing in the historic maps and planning documents of Singapore, currently held by the National Archives of Singapore, the National Library Board, university departments, and the Urban Redevelopment Authority. To create a spatial layer of information, the project links each place name to either a geo-referenced point, line segment, or polygon, along with the original source material in which the name appears. This record is supplemented by crowd-sourced contributions from civil service officers and heritage specialists, drawing from their collective memory to (1) define geospatial boundaries of historic places that appear in past documents, but maybe unfamiliar to users today, and (2) identify and record vernacular place names not captured in formal planning documents. An intuitive interface allows participants to demarcate feature classes, vernacular phrasings, time periods, and other knowledge related to historical or forgotten spaces. Participants are stratified into age bands and ethnicity to improve representativeness. Future iterations could allow additional public contributions. Names reveal meanings that communities assign to each place. While existing historical maps of Singapore allow users to toggle between present-day and historical raster files, this project goes a step further by adding layers of social understanding and planning documents. Tracking place names illuminates linguistic, cultural, commercial, and demographic shifts in Singapore, in the context of transformations of the urban environment. The project also demonstrates how a moderated, selectively crowd-sourced effort can solicit useful geospatial data at scale, sourced from different generations, and at higher granularity than traditional surveys, while mitigating negative impacts of unmoderated crowd-sourcing. Stakeholder agencies believe the project will achieve several objectives, including Supporting heritage conservation and public education; Safeguarding intangible cultural heritage; Providing historical context for street, place or development-renaming requests; Enhancing place-making with deeper historical knowledge; Facilitating emergency and social services by tagging legal addresses to vernacular place names; Encouraging public engagement with heritage by eliciting multi-stakeholder input.

Keywords: collective memory, crowd-sourced, digital heritage, geospatial, geographical names, linguistic heritage, place-naming, Singapore, Southeast Asia

Procedia PDF Downloads 109

Authors: Lolwa Alansari, Abdelhamid Azhaghdani, Sufia Athar, Hanen Mrabet, Annaliza Cruz, Tamara Alshadafat, Almunzer Zakaria

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Introduction: Improving the patient experience is a fundamental pillar of healthcare's quadruple aims. Recognizing the importance of patient experiences and perceptions in healthcare interactions is pivotal for driving quality improvement. This abstract centers around the Patient Experience Program, an endeavor crafted with the purpose of comprehending and elevating the experiences of patients in the Obstetrics & Gynecology Emergency Department (OB/GYN ED). Methodology: This comprehensive endeavor unfolded through a structured sequence of phases following Plan-Do-Study-Act (PDSA) model, spanning over 12 months, focused on enhancing patient experiences in the Obstetrics & Gynecology Emergency Department (OB/GYN ED). The study meticulously examined the journeys of patients with acute obstetrics and gynecological conditions, collecting data from over 100 participants monthly. The inclusive approach covered patients of different priority levels (1-5) admitted for acute conditions, with no exclusions. Historical data from March and April 2022 serves as a benchmark for comparison, strengthening causality claims by providing a baseline understanding of OB/GYN ED performance before interventions. Additionally, the methodology includes the incorporation of staff engagement surveys to comprehensively understand the experiences of healthcare professionals with the implemented improvements. Data extraction involved administering open-ended questions and comment sections to gather rich qualitative insights. The survey covered various aspects of the patient journey, including communication, emotional support, timely access to care, care coordination, and patient-centered decision-making. The project's data analysis utilized a mixed-methods approach, combining qualitative techniques to identify recurring themes and extract actionable insights and quantitative methods to assess patient satisfaction scores and relevant metrics over time, facilitating the measurement of intervention impact and longitudinal tracking of changes. From the themes we discovered in both the online and in-person patient experience surveys, several key findings emerged that guided us in initiating improvements, including effective communication and information sharing, providing emotional support and empathy, ensuring timely access to care, fostering care coordination and continuity, and promoting patient-centered decision-making. Results: The project yielded substantial positive outcomes, significantly improving patient experiences in the OB/GYN ED. Patient satisfaction levels rose from 62% to a consistent 98%, with notable improvements in satisfaction with care plan information and physician care. Waiting time satisfaction increased from 68% to a steady 97%. The project positively impacted nurses' and midwives' job satisfaction, increasing from 64% to an impressive 94%. Operational metrics displayed positive trends, including a decrease in the "left without being seen" rate from 3% to 1%, the discharge against medical advice rate dropping from 8% to 1%, and the absconded rate reducing from 3% to 0%. These outcomes underscore the project's effectiveness in enhancing both patient and staff experiences in the healthcare setting. Conclusion: The use of a patient experience questionnaire has been substantiated by evidence-based research as an effective tool for improving the patient experience, guiding interventions, and enhancing overall healthcare quality in the OB/GYN ED. The project's interventions have resulted in a more efficient allocation of resources, reduced hospital stays, and minimized unnecessary resource utilization. This, in turn, contributes to cost savings for the healthcare facility.

Keywords: patient experience, patient survey, person centered care, quality initiatives

Procedia PDF Downloads 43

Authors: Kristina F. Wolff

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Background: In the Federal Republic of Germany, violence against women is deeply embedded in society. Germany is, as of March 2020, the most populous member state of the European Union with 83.2 million inhabitants and, although more than half of its inhabitants are women, gender equality was not certified in the Basic Law until 1957. Women have only been allowed to enter paid employment without their husband's consent since 1977 and have marital rape prosecuted only since 1997. While the lack of equality between men and women is named in the preamble of the Istanbul Convention as the cause of gender-specific, structural, traditional violence against women, Germany continues to sink on the latest Gender Equality Index. According to Police Crime Statistics (PCS), women are significantly more often victims of lethal violence, emanating from men than vice versa. The PCS, which, since 2015, also collects gender-specific data on violent crimes, is kept by the Federal Criminal Police Office, but without taking into account the relevant criteria for targeted prevention, such as the history of violence of the perpetrator/killer, weapon, motivation, etc.. Institutions such as EIGE or the World Health Organization have been asking Germany for years in vain for comparable data on violence against women in order to gain an overview or to develop cross-border synergies. The PCS are the only official data collection on violence against women. All players involved are depend on this data set, which is published only in November of the following year and is thus already completely outdated at the time of publication. In order to combat German femicides causally, purposefully and efficiently, evidence-based data was urgently needed. Methodology: Beginning in January 2019, a database was set up that now tracks more than 600 German femicides, broken down by more than 100 crime-related individual criteria, which in turn go far beyond the official PCS. These data are evaluated on the one hand by daily media research, and on the other hand by case-specific inquiries at the respective public prosecutor's offices and courts nationwide. This quantitative long-term study covers domestic violence as well as a variety of different types of gender-specific, lethal violence, including, for example, femicides committed by German citizens abroad. Additionallyalcohol/ narcotic and/or drug abuse, infanticides and the gender aspect in the judiciary are also considered. Results: Since November 2020, evidence-based data from a scientific survey have been available for the first time in Germany, supplementing the rudimentary picture of reality provided by PCS with a number of relevant parameters. The most important goal of the study is to identify "red flags" that enable general preventive awareness, that serve increasingly precise hazard assessment in acute hazard situations, and from which concrete instructions for action can be identified. Already at a very early stage of the study it could be proven that in more than half of all femicides with a sexual perpetrator/victim constellation there was an age difference of five years or more. Summary: Without reliable data and an understanding of the nature and extent, cause and effect, it is impossible to sustainably curb violence against girls and women, which increasingly often culminates in femicide. In Germany, valid data from a scientific survey has been available for the first time since November 2020, supplementing the rudimentary reality picture of the official and, to date, sole crime statistics with several relevant parameters. The basic research provides insights into geo-concentration, monthly peaks and the modus operandi of male violent excesses. A significant increase of child homicides in the course of femicides and/or child homicides as an instrument of violence against the mother could be proven as well as a danger of affected persons due to an age difference of five years and more. In view of the steadily increasing wave of violence against women, these study results are an eminent contribution to the preventive containment of German femicides.

Keywords: femicide, violence against women, gender specific data, rule Of law, Istanbul convention, gender equality, gender based violence

Procedia PDF Downloads 67

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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