Search results for: degree-days methods

Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: biomass, diatom, flocculation, microalgae

Procedia PDF Downloads 330

Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Jacky Liu, Dulani Jayasuriya, Ryan Elmore

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Match fixing and anomalous sports events have increasingly threatened the integrity of professional sports, prompting concerns about existing detection methods. This study addresses prior research limitations in match fixing detection, improving the identification of potential fraudulent matches by incorporating advanced anomaly detection techniques. We develop a novel method to identify anomalous matches and player performances by examining series of matches, such as playoffs. Additionally, we investigate bettors' potential profits when avoiding anomaly matches and explore factors behind unusual player performances. Our literature review covers match fixing detection, match outcome forecasting models, and anomaly detection methods, underscoring current limitations and proposing a new sports anomaly detection method. Our findings reveal anomalous series in the 2022 NBA playoffs, with the Phoenix Suns vs Dallas Mavericks series having the lowest natural occurrence probability. We identify abnormal player performances and bettors' profits significantly decrease when post-season matches are included. This study contributes by developing a new approach to detect anomalous matches and player performances, and assisting investigators in identifying responsible parties. While we cannot conclusively establish reasons behind unusual player performances, our findings suggest factors such as team financial difficulties, executive mismanagement, and individual player contract issues.

Keywords: anomaly match detection, match fixing, match outcome forecasting, problematic players identification

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Authors: Gopinath Ganapathy, Chellammal Surianarayanan

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Services are growing rapidly and generally they are aggregated into a composite service to accomplish complex business processes. There may be several services that offer the same required function of a particular task in a composite service. Hence a choice has to be made for selecting suitable services from alternative functionally similar services. Quality of Service (QoS)plays as a discriminating factor in selecting which component services should be selected to satisfy the quality requirements of a user during service composition. There are two categories of approaches for QoS based service selection, namely global and local approaches. Global approaches are known to be Non-Polynomial (NP) hard in time and offer poor scalability in large scale composition. As an alternative to global methods, local selection methods which reduce the search space by breaking up the large/complex problem of selecting services for the workflow into independent sub problems of selecting services for individual tasks are coming up. In this paper, distributed architecture for selecting services based on QoS using local selection is presented with an overview of local selection methodology. The architecture describes the core components, namely, selection manager and QoS manager needed to implement the local approach and their functions. Selection manager consists of two components namely constraint decomposer which decomposes the given global or workflow level constraints in local or task level constraints and service selector which selects appropriate service for each task with maximum utility, satisfying the corresponding local constraints. QoS manager manages the QoS information at two levels namely, service class level and individual service level. The architecture serves as an implementation model for local selection.

Keywords: architecture of service selection, local method for service selection, QoS based service selection, approaches for QoS based service selection

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

Procedia PDF Downloads 422

Authors: Kalangi Rodrigo

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The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

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Authors: Ali Ozvan, Ismail Akkaya, Mucip Tapan

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Travertine is generally a weak or medium strong rock, and physical, mechanical and structural properties of travertines are direct impacts on geotechnical studies. New settlement areas were determined on travertine units after two destructive earthquakes which occurred on October 23rd, 2011 (M=7.1) and November 9th, 2011 (M=5.6) in Tabanlı and Edremit districts of Van province in Turkey, respectively. In the study area, the travertines have different lithotype and engineering properties such as strong crystalline crust, medium strong shrub, and weak reed which can affect mechanical and engineering properties of travertine and each level have different handicaps. Travertine has a higher strength when compared to the soil ground; however, it can have different handicaps such as having poor rock mass, karst caves and weathering alteration. Physico-mechanical properties of travertine in the study area are determined by laboratory tests and field observations. Uniaxial compressive strength (UCS) values were detected by indirect methods, and the strength map of different lithotype of Edremit travertine was created in order to define suitable settlement areas. Also, rock mass properties and underground structure were determined by bore holes, field studies, and geophysical method. The reason of this study is to investigate the relationship between lithotype and physicomechanical properties of travertines. According to the results, lithotype has an effect on physical, mechanical and rock mass properties of travertine levels. It is detected by several research methods that various handicaps may occur on such areas when the active tectonic structure of the area is evaluated along with the karstic cavities within the travertine and different lithotype qualities.

Keywords: travertine, lithotype, geotechnical parameters, Van earthquake

Procedia PDF Downloads 231

Authors: Chih-Yi Ho, Tzu-Fang Chang, Chih-Chia Huang, Chia-Yen Lee

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In dental clinics, the dentists use the periapical radiography image to assess the effectiveness of endodontic treatment of teeth with chronic apical periodontitis. Periapical radiography images are taken at different times to assess alveolar bone variation before and after the root canal treatment, and furthermore to judge whether the treatment was successful. Current clinical assessment of apical tissue recovery relies only on dentist personal experience. It is difficult to have the same standard and objective interpretations due to the dentist or radiologist personal background and knowledge. If periapical radiography images at the different time could be registered well, the endodontic treatment could be evaluated. In the image registration area, it is necessary to assign representative control points to the transformation model for good performances of registration results. However, detection of representative control points (feature points) on periapical radiography images is generally very difficult. Regardless of which traditional detection methods are practiced, sufficient feature points may not be detected due to the low-contrast characteristics of the x-ray image. Barnard detector is an algorithm for feature point detection based on grayscale value gradients, which can obtain sufficient feature points in the case of gray-scale contrast is not obvious. However, the Barnard detector would detect too many feature points, and they would be too clustered. This study uses the local extrema of clustering feature points and the suppression radius to overcome the problem, and compared different feature point detection methods. In the preliminary result, the feature points could be detected as representative control points by the proposed method.

Keywords: feature detection, Barnard detector, registration, periapical radiography image, endodontic treatment

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Authors: Zhou Shangcheng, Yi Sicen

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Objective: To understand the mortality patterns of Zhangwan District in 2010 and provide the basis for the development of scientific and rational health policy. Methods: Data are collected from the Sixth Census of Zhangwan District and disease surveillance system. The statistical analysis include death difference between age, gender, region and time and the related factors. Methods developed for the Global Burden of Disease (GBD) Study by the World Bank and World Health Organization (WHO) were adapted and applied to Zhangwan District population health data. DALY rate per 1,000 was calculated for varied causes of death. SPSS 16 is used by statistic analysis. Results: From the data of death population of Zhangwan District we know the crude mortality rate was 6.03 ‰. There are significant differences of mortality rate in male and female population which was respectively 7.37 ‰ and 4.68 ‰. 0 age group population life expectancy in Zhangwan District in 2010 was 78.40 years old(Male 75.93, Female 81.03). The five leading causes of YLL in descending order were: cardiovascular diseases(42.63DALY/1000), malignant neoplasm (23.73DALY/1000), unintentional injuries (5.84DALY/1000), Respiratory diseases(5.43 DALY/1000), Respiratory infections (2.44DALY/1000). In addition, there are strong relation between the marital status , educational level and mortality in some to a certain extend. Conclusion Zhangwan District, as city level, is at lower mortality levels. The mortality of the total population of Zhangwan District has a downward trend and life expectancy is rising.

Keywords: sixth census, Zhangwan district, death level differences, influencing factors, cause of death

Procedia PDF Downloads 271

Authors: Shreyash Hadke, Manendra Singh Parihar, Rajesh Khatirkar

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In the present investigation, the variation in the microstructure with the changes in the heat treatment conditions i.e. temperature and time was observed. Ti-6Al-4V alloy was subject to solution annealing treatments in β (1066C) and α+β phase (930C and 850C) followed by quenching, air cooling and furnace cooling to room temperature respectively. The effect of solution annealing and cooling on the microstructure was studied by using optical microscopy (OM), scanning electron microscopy (SEM), electron backscattered diffraction (EBSD) and x-ray diffraction (XRD). The chemical composition of the β phase for different conditions was determined with the help of energy dispersive spectrometer (EDS) attached to SEM. Furnace cooling resulted in the development of coarser structure (α+β), while air cooling resulted in much finer structure with widmanstatten morphology of α at the grain boundaries. Quenching from solution annealing temperature formed α’ martensite, their proportion being dependent on the temperature in β phase field. It is well known that the transformation of β to α follows Burger orientation relationship (OR). In order to reconstruct the microstructure of parent β phase, a MATLAB code was written using neighbor-to-neighbor, triplet method and Tari’s method. The code was tested on the annealed samples (1066C solution annealing temperature followed by furnace cooling to room temperature). The parent phase data thus generated was then plotted using the TSL-OIM software. The reconstruction results of the above methods were compared and analyzed. The Tari’s approach (clustering approach) gave better results compared to neighbor-to-neighbor and triplet method but the time taken by the triplet method was least compared to the other two methods.

Keywords: Ti-6Al-4V alloy, microstructure, electron backscattered diffraction, parent phase reconstruction

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Authors: B. Cilek Tatar, G. Sumnu, M. Oztop, E. Ayaz

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Encapsulation protects sensitive food ingredients against heat, oxygen, moisture and pH until they are released to the system. It can mask the unwanted taste of nutrients that are added to the foods for fortification purposes. Cherry laurels (Prunus laurocerasus) contain phenolic compounds which decrease the proneness to several chronic diseases such as types of cancer and cardiovascular diseases. The objective of this research was to study the effects of centrifugation, different coating materials and homogenization methods on microencapsulation of powders obtained from cherry laurels. In this study, maltodextrin and mixture of maltodextrin:whey protein with a ratio of 1:3 (w/w) were chosen as coating materials. Total solid content of coating materials was kept constant as 10% (w/w). Capsules were obtained from powders of freeze-dried cherry laurels through encapsulation process by silent crusher homogenizer or microfluidization. Freeze-dried cherry laurels were core materials and core to coating ratio was chosen as 1:10 by weight. To homogenize the mixture, high speed homogenizer was used at 4000 rpm for 5 min. Then, silent crusher or microfluidizer was used to complete encapsulation process. The mixtures were treated either by silent crusher for 1 min at 75000 rpm or microfluidizer at 50 MPa for 3 passes. Freeze drying for 48 hours was applied to emulsions to obtain capsules in powder form. After these steps, dry capsules were grounded manually into a fine powder. The microcapsules were analyzed for total antioxidant activity with DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging method. Prior to high speed homogenization, the samples were centrifuged (4000 rpm, 1 min). Centrifugation was found to have positive effect on total antioxidant activity of capsules. Microcapsules treated by microfluidizer were found to have higher total antioxidant activities than those treated by silent crusher. It was found that increasing whey protein concentration in coating material (using maltodextrin:whey protein 1:3 mixture) had positive effect on total antioxidant activity for both silent crusher and microfluidization methods. Therefore, capsules prepared by microfluidization of centrifuged mixtures can be selected as the best conditions for encapsulation of cherry laurel powder by considering their total antioxidant activity. In this study, it was shown that capsules prepared by these methods can be recommended to be incorporated into foods in order to enhance their functionality by increasing antioxidant activity.

Keywords: antioxidant activity, cherry laurel, microencapsulation, microfluidization

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Authors: Badryah Alshehri, Kevin Gormley, Gillian Prue, Karen McCutcheon

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In a disaster event, sharing patient information between the pre-hospital Emergency Medical Services (EMS) and Emergency Department (ED) hospitals is a complex process during which important information may be altered or lost due to poor communication. The aim of this study was to critically discuss the current evidence base in relation to communication between pre- EMS hospital and ED hospital professionals by the use of Information and Communication Systems (ICT). This study followed the systematic approach; six electronic databases were searched: CINAHL, Medline, Embase, PubMed, Web of Science, and IEEE Xplore Digital Library were comprehensively searched in January 2018 and a second search was completed in April 2020 to capture more recent publications. The study selection process was undertaken independently by the study authors. Both qualitative and quantitative studies were chosen that focused on factors that are positively or negatively associated with coordinated communication between pre-hospital EMS and ED teams in a disaster event. These studies were assessed for quality, and the data were analyzed according to the key screening themes which emerged from the literature search. Twenty-two studies were included. Eleven studies employed quantitative methods, seven studies used qualitative methods, and four studies used mixed methods. Four themes emerged on communication between EMTs (pre-hospital EMS and ED staff) in a disaster event using the ICT. (1) Disaster preparedness plans and coordination. This theme reported that disaster plans are in place in hospitals, and in some cases, there are interagency agreements with pre-hospital and relevant stakeholders. However, the findings showed that the disaster plans highlighted in these studies lacked information regarding coordinated communications within and between the pre-hospital and hospital. (2) Communication systems used in the disaster. This theme highlighted that although various communication systems are used between and within hospitals and pre-hospitals, technical issues have influenced communication between teams during disasters. (3) Integrated information management systems. This theme suggested the need for an integrated health information system that can help pre-hospital and hospital staff to record patient data and ensure the data is shared. (4) Disaster training and drills. While some studies analyzed disaster drills and training, the majority of these studies were focused on hospital departments other than EMTs. These studies suggest the need for simulation disaster training and drills, including EMTs. This review demonstrates that considerable gaps remain in the understanding of the communication between the EMS and ED hospital staff in relation to response in disasters. The review shows that although different types of ICTs are used, various issues remain which affect coordinated communication among the relevant professionals.

Keywords: emergency medical teams, communication, information and communication technologies, disaster

Procedia PDF Downloads 127

Authors: Fatima Achouri, Kaddour Chouicha, Abdelwahab Khatir

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It is clear that concrete of quality must be made with selected materials chosen in optimum proportions that remain after implementation, a minimum of voids in the material produced. The different methods of formulations what we use, are based for the most part on a granular curve which describes an ‘optimal granularity’. Many authors have engaged in fundamental research on granular arrangements. A comparison of mathematical models reproducing these granular arrangements with experimental measurements of compactness have to verify that the minimum porosity P according to the following extent granular exactly a power law. So the best compactness in the finite medium are obtained with power laws, such as Furnas, Fuller or Talbot, each preferring a particular setting between 0.20 and 0.50. These considerations converge on the assumption that the optimal granularity Caquot approximates by a power law. By analogy, it can then be analyzed as a granular structure of fractal-type since the properties that characterize the internal similarity fractal objects are reflected also by a power law. Optimized mixtures may be described as a series of installments falling granular stuff to better the tank on a regular hierarchical distribution which would give at different scales, by cascading effects, the same structure to the mix. Likely this model may be appropriate for the entire extent of the size distribution of the components, since the cement particles (and silica fume) correctly deflocculated, micrometric dimensions, to chippings sometimes several tens of millimeters. As part of this research, the aim is to give an illustration of the application of fractal analysis to characterize the granular concrete mixtures optimized for a so-called fractal dimension where different concretes were studying that we proved a fractal structure of their granular mixtures regardless of the method of formulation or the type of concrete.

Keywords: concrete formulation, fractal character, granular packing, method of formulation

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand the smallholder farming communities within Scotland by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted in conjunction with text mining of the data in search of common themes, words, and topics found within the text. Results from bi-grams and topic modelling uncover four main topics of interest within the data pertaining to aspects of livestock husbandry: feeding, breeding, slaughter, and disposal. These topics were found amongst both the poultry and pig sub-forums. Topic modeling appears to be a useful method of unsupervised classification regarding this form of data, as it has produced clusters that relate to biosecurity and animal welfare. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter and Facebook/Meta, in addition to time series analysis to highlight temporal patterns.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, smallholding, social media, web scraping, sentiment analysis, geolocation, text mining, NLP

Procedia PDF Downloads 101

Authors: Merve Gücen

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One of the aims of education is to educate individuals who have embraced universal moral principles and transform universal moral principles into moral values. Character education aims to educate behaviors of individuals in their mental activities to transform moral principles into moral values in their lives. As the result of this education, individuals are expected to develop positive character traits and become morally indifferent individuals. What are the characteristics of the factors that influence character education at this stage? How should character education help individuals develop positive character traits? Which methods are more effective? These questions come to mind when studying character education. Our research was developed within the framework of these questions. The aim of our study is to provide the most effective use of the education factor that affects character. In this context, we tried to explain character definition, character development, character education and the factors affecting character education using qualitative research methods. At this stage, character education programs applied in various countries were examined and a character education program consisting of Islamic values was prepared and implemented in an International Imam Hatip High School in Istanbul. Our application was carried out with the collaboration of school and families. Various seminars were organized in the school and participation of families was ensured. In the last phase of our study, we worked with the students and their families on the effectiveness of the events held during the program. In this study, it was found that activities such as storytelling and theater in character education programs were effective in recognizing wrong behaviors in individuals. It was determined that our program had a positive effect on the quality of education. It was seen that applications of this educational program affected the behavior of the employees in the educational institution.

Keywords: character development, family activities, values education, education program

Procedia PDF Downloads 172

Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: Eliane G. Tótoli, Hérida Regina N. Salgado

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Daptomycin is an important antimicrobial agent used in clinical practice nowadays, since it is very active against some Gram-positive bacteria that are particularly challenges for the medicine, such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). The importance of environmental preservation has receiving special attention since last years. Considering the evident need to protect the natural environment and the introduction of strict quality requirements regarding analytical procedures used in pharmaceutical analysis, the industries must seek environmentally friendly alternatives in relation to the analytical methods and other processes that they follow in their routine. In view of these factors, green analytical chemistry is prevalent and encouraged nowadays. In this context, infrared spectroscopy stands out. This is a method that does not use organic solvents and, although it is formally accepted for the identification of individual compounds, also allows the quantitation of substances. Considering that there are few green analytical methods described in literature for the analysis of daptomycin, the aim of this work was the development and validation of a green analytical method for the quantification of this drug in lyophilized powder for injectable solution, by Fourier-transform infrared spectroscopy (FT-IR). Method: Translucent potassium bromide pellets containing predetermined amounts of the drug were prepared and subjected to spectrophotometric analysis in the mid-infrared region. After obtaining the infrared spectrum and with the assistance of the IR Solution software, quantitative analysis was carried out in the spectral region between 1575 and 1700 cm-1, related to a carbonyl band of the daptomycin molecule, and this band had its height analyzed in terms of absorbance. The method was validated according to ICH guidelines regarding linearity, precision (repeatability and intermediate precision), accuracy and robustness. Results and discussion: The method showed to be linear (r = 0.9999), precise (RSD% < 2.0), accurate and robust, over a concentration range from 0.2 to 0.6 mg/pellet. In addition, this technique does not use organic solvents, which is one great advantage over the most common analytical methods. This fact contributes to minimize the generation of organic solvent waste by the industry and thereby reduces the impact of its activities on the environment. Conclusion: The validated method proved to be adequate to quantify daptomycin in lyophilized powder for injectable solution and can be used for its routine analysis in quality control. In addition, the proposed method is environmentally friendly, which is in line with the global trend.

Keywords: daptomycin, Fourier-transform infrared spectroscopy, green analytical chemistry, quality control, spectrometry in IR region

Procedia PDF Downloads 381

Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Rachelle McFarlane

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The Second Decade of Action Road Safety has begun with increased focus on countries who are disproportionately affected by road fatalities. Researchers highlight the low effectiveness of road safety campaigns in Latin America and the Caribbean (LAC) still reporting approximately 130,000 deaths and six million injuries annually. The regional fatality rate 19.2 per 100,000 with heightened concern for persons 15 to 44 years. In 2021, 483 Jamaicans died in 435 crashes, with 33% of these fatalities occurring during Covid-19 curfew hours. The study objective is to conduct a systemic safety review of Jamaican road crashes and provide a framework for its use in complementing traditional methods. The methodology involves the use of the FHWA Systemic Safety Project Selection Tool for analysis. This tool reviews systemwide data in order to identify risk factors across the network associated with severe and fatal crashes, rather that only hotspots. A total of 10,379 crashes with 745 fatalities and serious injuries were reviewed. Of the focus crash types listed, 50% of ‘Pedestrian Accidents’ resulted in fatalities and serious injuries, followed by 32% ‘Bicycle’, 24% ‘Single’ and 12% of ‘Head-on’. This study seeks to understand the associated risk factors with these priority crash types across the network and recommend cost-effective countermeasures across common sites. As we press towards Vision Zero, the inclusion of the systemic safety review method, complementing traditional methods, may create a wider impact in reducing road fatalities and serious injury by targeting issues across network with similarities; focus crash types and contributing factors.

Keywords: systemic safety review, risk factors, road crashes, crash types

Procedia PDF Downloads 91

Authors: Abdelkader Mendas

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The integration of MultiCriteria Decision Making (MCDM) approaches in a Geographical Information System (GIS) provides a powerful spatial decision support system which offers the opportunity to efficiently produce the land suitability maps for agriculture. Indeed, GIS is a powerful tool for analyzing spatial data and establishing a process for decision support. Because of their spatial aggregation functions, MCDM methods can facilitate decision making in situations where several solutions are available, various criteria have to be taken into account and decision-makers are in conflict. The parameters and the classification system used in this work are inspired from the FAO (Food and Agriculture Organization) approach dedicated to a sustainable agriculture. A spatial decision support system has been developed for establishing the land suitability map for agriculture. It incorporates the multicriteria analysis method ELECTRE Tri (ELimitation Et Choix Traduisant la REalité) in a GIS within the GIS program package environment. The main purpose of this research is to propose a conceptual and methodological framework for the combination of GIS and multicriteria methods in a single coherent system that takes into account the whole process from the acquisition of spatially referenced data to decision-making. In this context, a spatial decision support system for developing land suitability maps for agriculture has been developed. The algorithm of ELECTRE Tri is incorporated into a GIS environment and added to the other analysis functions of GIS. This approach has been tested on an area in Algeria. A land suitability map for durum wheat has been produced. Through the obtained results, it appears that ELECTRE Tri method, integrated into a GIS, is better suited to the problem of land suitability for agriculture. The coherence of the obtained maps confirms the system effectiveness.

Keywords: multicriteria decision analysis, decision support system, geographical information system, land suitability for agriculture

Procedia PDF Downloads 642

Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Agoston Restas

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Introduction: In case of managing disasters decision makers can face many times such a special situation where any pre-sign of the drastically change is missing therefore the improvised decision making can be required. The complexity, ambiguity, uncertainty or the volatility of the situation can require many times the improvisation as decision making. It can be taken at any level of the management (strategic, operational and tactical) but at tactical level the main reason of the improvisation is surely time pressure. It is certainly the biggest problem during the management. Methods: The author used different tools and methods to achieve his goals; one of them was the study of the relevant literature, the other one was his own experience as a firefighting manager. Other results come from two surveys that are referred to; one of them was an essay analysis, the second one was a word association test, specially created for the research. Results and discussion: This article proves that, in certain situations, the multi-criteria, evaluating decision-making processes simply cannot be used or only in a limited manner. However, it can be seen that managers, directors or commanders are many times in situations that simply cannot be ignored when making decisions which should be made in a short time. The functional background of decisions made in a short time, their mechanism, which is different from the conventional, was studied lately and this special decision procedure was given the name recognition-primed decision. In the article, author illustrates the limits of the possibilities of analytical decision-making, presents the general operating mechanism of recognition-primed decision-making, elaborates on its special model relevant to managers at tactical level, as well as explore and systemize the factors that facilitate (catalyze) the processes with an example with fire managers.

Keywords: decision making, disaster managers, recognition primed decision, model for making decisions in emergencies

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Authors: Recep Kesli, Gulsah Asik, Cengiz Demir, Onur Turkyilmaz

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Objective: Pseudomonas aeruginosa (P. aeruginosa) is an important nosocomial pathogen which causes serious hospital infections and is resistant to many commonly used antibiotics. P. aeruginosa can develop resistance during therapy and also it is very resistant to disinfectant chemicals. It may be found in respiratory support devices in hospitals. In this study, the antibiotic resistance of P. aeruginosa strains isolated from bronchial aspiration samples was evaluated retrospectively. Methods: Between October 2013 and September 2015, a total of 318 P. aeruginosa were isolated from clinical samples obtained from various intensive care units and inpatient patients hospitalized at Afyon Kocatepe University, ANS Practice and Research Hospital. Isolated bacteria identified by using both the conventional methods and automated identification system-VITEK 2 (bioMerieux, Marcy l’etoile France). Antibacterial resistance tests were performed by using Kirby-Bauer disc (Oxoid, Hampshire, England) diffusion method following the recommendations of CLSI. Results: Antibiotic resistance rates of identified 318 P. aeruginosa strains were found as follows for tested antibiotics; 32 % amikacin, 42% gentamicin, 43% imipenem, 43% meropenem, 50% ciprofloxacin, 57% levofloxacin, 38% cefepime, 63% ceftazidime, and 85% piperacillin/tazobactam. Conclusion: Resistance profiles change according to years and provinces for P. aeruginosa, so these findings should be considered empirical treatment choices. In this study, the highest and lowest resistance rates found against piperacillin/tazobactam % 85, and amikacin %32.

Keywords: Pseudomonas aeruginosa, antibiotic resistance rates, intensive care unit, Pseudomonas spp.

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Authors: André Rui Coelho Fernandes, Mariana Rufino, Divakar Hamal, Amr Sousa, Emma Fossett, Kamalpreet Cheema

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Aim: A single patella tendon rupture is relatively uncommon, but a simultaneous bilateral event is a rare occurrence and has been scarcely reviewed in the literature. This review was carried out to analyse the existing literature on this event, with the aim of proposing a standardised approach to the diagnosis and management of this injury. Methods: A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three independent reviewers conducted searches in PubMed, OvidSP for Medline and Embase, as well as Cochrane Library using the same search strategy. From a total of 183 studies, 45 were included, i.e. 90 patellas. Results: 46 patellas had a Type 1 Rupture equating to 51%, with Type 3 being the least common, with only 7 patellas sustaining this injury. The mean Insall-Salvio ratio for each knee was 1.62 (R) and 1.60 (L) Direct Primary Repair was the most common surgical technique compared to Tendon Reconstruction, with End to End and Transosseous techniques split almost equally. Brace immobilisation was preferred over cast, with a mean start to weight-bearing of 3.23 weeks post-op. Conclusions: Bilateral patellar tendon rupture is a rare injury that should be considered in patients with knee extensor mechanism disruption. The key limitation of this study was the low number of patients encompassed by the eligible literature. There is space for a higher level of evidence study, specifically regarding surgical treatment choice and methods, as well as post-operative management, which could potentially improve the outcomes in the management of this injury.

Keywords: trauma and orthopaedic surgery, bilateral patella, tendon rupture, trauma

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Authors: Murad Gasanov, Shagen Danielyan, Ali Gasanov, Yuri Teterin, Peter Yartsev

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Background: Despite the advances made in modern surgery, the treatment of patients with esophageal injuries remains one of the most topical and complex issues. In recent years, high-technology minimally invasive methods, such as endoscopic vacuum therapy (EVT) in the treatment of esophageal injuries. The effectiveness of EVT has been sufficiently studied in case of failure of esophageal anastomoses, however the application of this method in case of mechanical esophageal injuries is limited by a small series of observations, indicating the necessity of additional study. Aim: The aim was to аnalyzed of own experience in the use of endoscopic vacuum therapy (EVT) in a comprehensive examination of patients with esophageal injuries. Methods: We analyzed the results of treatment of 24 patients with mechanical injuries of the esophagus for the period 2019-2021. Complex treatment of patients included the use of minimally invasive technologies, including percutaneous endoscopic gastrostomy (PEG), EVT and video-assisted thoracoscopic debridement. Evaluation of the effectiveness of treatment was carried out using multislice computed tomography (MSCT), endoscopy and laboratory tests. The duration of inpatient treatment and the duration of EVT, the number of system replacements, complications and mortality were taken into account. Result: EVT in patients with mechanical injuries of the esophagus allowed to achieve epithelialization of the esophageal defect in 21 patients (87.5%) in the form of linear scar on the site of perforation or pseudodiverticulum. Complications were noted in 4 patients (16.6%), including bleeding (2) and and esophageal stenosis in the perforation area (2). Lethal outcome was in one observation (4.2%). Conclusion. EVT may be the method of choice in complex treatment in patients with esophageal lesions.

Keywords: esophagus injuries, damage to the esophagus, perforation of the esophagus, spontaneous perforation of the esophagus, mediastinitis, endoscopic vacuum therapy

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Authors: Gebrekiros Welegebriel Asfaw

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The management of the fragile, unique and irreplaceable cultural heritage from different perspectives is becoming a major challenge as important elements of culture are vanishing throughout the globe. The major purpose of this study is to assess how the cultural heritages of Aksum are managed for their future sustainability from heritage conservation and interpretation perspectives. Descriptive type of research design inculcating both quantitative and qualitative research methods is employed. Primary quantitative data was collected from 189 respondents (19 professionals, 88 tourism service providers and 82 tourists) and interview was conducted with 33 targeted informants from heritage and related professions, security employees, local community, service providers and church representatives by applying probability and non probability sampling methods. Findings of the study reveal that the overall sustainable management status of the cultural heritage of Aksum is below average. It is found that the sustainability of cultural heritage management in Aksum is facing a lot of unfavorable factors like lack of long term planning, incompatible system of heritage administration, limited capacity and number of professionals, scant attention to community based heritage and tourism development, dirtiness and drainage problems, problems with stakeholder involvement and cooperation, lack of organized interpretation and presentation systems and others. So, re-organization of the management system, creating platform for coordination among stakeholders and developing appropriate interpretation system can be good remedies. Introducing community based heritage and tourism development concept is also recommendable for a long term win-win success in Aksum.

Keywords: Aksum, conservation, interpretation, Sustainable Cultural Heritage Management

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Authors: Parvin Malhami

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The purpose of the present study was to investigate the effects of two functional and functional stretching methods of the leg muscles on a selection of kinematical and kinetic indicators among women with ankle instability. Twenty-four persons were targeted and randomly divided into the functional exercise (8 persons), extra-functional exercise (8 persons) and control (8 persons) groups on the basis of inclusion and exclusion criteria. The experimental groups received stretching for eight weeks, 3 sessions each week, and the control group merely performed its daily activities. Then, in order to measure the pre -test and post -test variables, the dorsi flexion, Plantar flexion and ground reaction force were investigated and measured. Data were analyzed using paired T-test and independent T-tests at a significant level of 0.05. All statistical analyses were conducted using SPSS 25 software. The results of the T-test showed the significant effect of eight weeks of functional and Extra functional exercises on dorsi Flexion, Plantar Flexion and ground reaction force. (P≤ 0/001). The results of this study showed that the implementation of the functional and Extra-functional exercise protocol had an impact on the amount of Ankle dorsi Flexion and the Plantar felxion of women with an ankle instability. It was also found that muscle flexibility following the stretch ability of the gastrocnemius muscles facilitates the walking of the wrist installation by affecting the amount of wrist flexion, so these people are recommended to use the functional and extra-functional exercise protocol.

Keywords: functional stretching, extra functional stretching, dorsi flexion, plantar flexion

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Authors: Steven G. Sclan

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Background: Since December 2019, the world has been afflicted by the spread of the Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2), which is responsible for the condition referred to as Covid-19. The illness has had a cataclysmic impact on the political, social, economic, and overall well-being of the population of the entire globe. While Covid-19 has had a substantial universal fatality impact, it may have an even greater effect on the socioeconomic, medical well-being, and healthcare planning for remaining societies. Significance: As these numbers illustrate, many more persons survive the infection than die from it, and many of those patients have noted ongoing, persistent symptoms after successfully enduring the acute phase of the illness. Recognition and understanding of these symptoms are crucial for developing and arranging efficacious models of care for all patients (whether or not having been hospitalized) surviving acute covid illness and plagued by post-acute symptoms. Furthermore, regarding Covid infection in children (< 18 y/o), although it may be that Covid “+” children are not major vectors of infective transmission, it now appears that many more children than initially thought are carrying the virus without accompanying obvious symptomatic expression. It seems reasonable to wonder whether viral effects occur in children – those children who are Covid “+” and now asymptomatic – and if, over time, they might also experience similar symptoms. An even more significant question is whether Covid “+” asymptomatic children might manifest increased multiple health problems as they grow – i.e., developmental complications (e.g., physical/medical, metabolic, neurobehavioral, etc.) – in comparison to children who had been consistently Covid “ - ” during the pandemic. Topics Addressed and Theoretical Importance: This review is important because of the description of both quantitative and qualitative methods for clinical and biomedical research. Topics reviewed will consider the importance of well-designed, comprehensive (i.e., quantitative and qualitative methods) longitudinal studies of Post Covid-19 symptoms in both adults and children. Also reviewed will be general characteristics of longitudinal studies and a presentation of a model for a proposed study. Also discussed will be the benefit of longitudinal studies for the development of efficacious interventions and for the establishment of cogent, practical, and efficacious community healthcare service planning for post-acute covid patients. Conclusion: Results of multi-dimensional, longitudinal studies will have important theoretical implications. These studies will help to improve our understanding of the pathophysiology of long COVID and will aid in the identification of potential targets for treatment. Such studies can also provide valuable insights into the long-term impact of COVID-19 on public health and socioeconomics.

Keywords: COVID-19, post-COVID-19, long COVID, longitudinal research, quantitative research, qualitative research

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Authors: Traci A. Hefner

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Limited research exists on the readiness of emergency departments to respond to human trafficking (HT). The purpose of this qualitative case study was to improve the readiness of a Department of Emergency Medicine (ED), located in the southeast region of the United States, in identifying, assessing, and responding to trafficked individuals. The research objectives were to 1) provide an organizing framework to understand the ED’s readiness to respond to HT, using the Transtheoretical Model’s stages of change construct, 2) explain the readiness of the ED through a three-pronged contextual approach that included policies and procedures, patient data collection processes, and clinical practice methods, and 3) develop recommendations to respond to HT. Content analysis was used for document reviews and on-site observations, while thematic analysis identified themes of staff perceptions of the ED’s readiness in interviews of over 30 clinical and non-clinical healthcare professionals. Results demonstrated low levels of readiness to identify HT through the ED’s policies and procedures, data collection processes, and clinical practice methods. Clinical practice-related factors consisted of limited awareness of HT warning signs and low-levels of knowledge about community resources for possible HT referrals. Policy and practice recommendations to increase the ED’s readiness to respond to HT included: developing staff trainings across the ED system to enhance awareness of HT warning signs, incorporating HT into current policies and procedures for vulnerable patient populations as well as creating a HT protocol that addresses policies and procedures, screening tools, and community referrals.

Keywords: emergency medicine, human trafficking, organizational assessment, stages of change

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