Search results for: decision tree algorithm

Authors: Leen Al Kassab, Sarah Johns, Helen Noble, Nawal Nour, Elizabeth Janiak, Sarrah Shahawy

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Introduction: Immigrant and refugee women experience disparities in sexual and reproductive health (SRH) outcomes, partially as a result of barriers to SRH literacy and to regular healthcare access and engagement. Despite the existing data highlighting growing needs for culturally relevant and structurally competent care, interventions are scarce and not well-documented. Methods: In this IRB-approved study, we used a community-based participatory research approach, with the assistance of a community advisory board, to conduct a qualitative needs assessment of SRH knowledge and service engagement with immigrant and refugee women from Africa or the Middle East and currently residing in Boston. We conducted a total of nine focus group discussions (FGDs) in partnership with medical, community, and religious centers, in six languages: Arabic, English, French, Somali, Pashtu, and Dari. A total of 44 individuals participated. We explored migrant and refugee women’s current and evolving SRH care needs and gaps, specifically related to the development of interventions and clinical best practices targeting SRH literacy, healthcare engagement, and informed decision-making. Recordings of the FGDs were transcribed verbatim and translated by interpreter services. We used open coding with multiple coders who resolved discrepancies through consensus and iteratively refined our codebook while coding data in batches using Dedoose software. Results: Participants reported immigrant adaptation experiences, discrimination, and feelings of trust, autonomy, privacy, and connectedness to family, community, and the healthcare system as factors surrounding SRH knowledge and needs. The context of previously learned SRH knowledge was commonly noted to be in schools, at menstruation, before marriage, from family members, partners, friends, and online search engines. Common themes included empowering strength drawn from religious and cultural communities, difficulties bridging educational gaps with their US- born daughters, and a desire for more SRH education from multiple sources, including family, health care providers, and religious experts & communities. Regarding further SRH education, participants’ preferences varied regarding ideal platform (virtual vs. in-person), location (in religious and community centers or not), smaller group sizes, and the involvement of men. Conclusions: Based on these results, empowering SRH initiatives should include both community and religious center-based, as well as clinic-based, interventions. Interventions should be composed of frequent educational workshops in small groups involving age-grouped women, daughters, and (sometimes) men, tailored SRH messaging, and the promotion of culturally, religiously, and linguistically competent care.

Keywords: community, immigrant, religion, sexual & reproductive health, women's health

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Authors: Valentina Dolmova

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What consumers choose to buy and who voters select on election days are two questions that have captivated the interest of both academics and practitioners for many decades. The importance of understanding what influences the behavior of those groups and whether or not we can predict or control it fuels a steady stream of research in a range of fields. By looking only at the past 40 years, more than 70 thousand scientific papers have been published in each field – consumer behavior and political psychology, respectively. From marketing, economics, and the science of persuasion to political and cognitive psychology - we have all remained heavily engaged. The ever-evolving technology, inevitable socio-cultural shifts, global economic conditions, and much more play an important role in choice-equations regardless of context. On one hand, this makes the research efforts always relevant and needed. On the other, the relatively low number of cross-field collaborations, which seem to be picking up only in more in recent years, makes the existing findings isolated into framed bubbles. By performing systematic research across both areas of psychology and building a parallel between theories and factors of influence, however, we find that there is not only a definitive common ground between the behaviors of consumers and voters but that we are moving towards a global model of choice. This means that the lines between contexts are fading which has a direct implication on what we should focus on when predicting or navigating buyers and voters’ behavior. Internal and external factors in four main categories determine the choices we make as consumers and as voters. Together, personal, psychological, social, and cultural create a holistic framework through which all stimuli in relation to a particular product or a political party get filtered. The analogy “consumer-voter” solidifies further. Leading academics suggest that this fundamental parallel is the key to managing successfully political and consumer brands alike. However, we distinguish additional four key stimuli that relate to those factor categories (1/ opportunity costs; 2/the memory of the past; 3/recognisable figures/faces and 4/conflict) arguing that the level of expertise a person has determines the prevalence of factors or specific stimuli. Our efforts take into account global trends such as the establishment of “celebrity politics” and the image of “ethically concerned consumer brands” which bridge the gap between contexts to an even greater extent. Scientists and practitioners are pushed to accept the transformative nature of both fields in social psychology. Existing blind spots as well as the limited number of research conducted outside the American and European societies open up space for more collaborative efforts in this highly demanding and lucrative field. A mixed method of research tests three main hypotheses, the first two of which are focused on the level of irrelevance of context when comparing voting or consumer behavior – both from the factors and stimuli lenses, the third on determining whether or not the level of expertise in any field skews the weight of what prism we are more likely to choose when evaluating options.

Keywords: buyers’ behaviour, decision-making, voters’ behaviour, social psychology

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Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

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Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

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Authors: Patricia Huedo, Maria José Ruá, Raquel Agost-Felip

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Ensuring sustainable development of urban environments means guaranteeing adequate environmental conditions, being resilient and meeting conditions of safety and inclusion for all people, regardless of their condition. All existing buildings should meet basic safety conditions and be equipped with safe and accessible routes, along with visual, acoustic and tactile signals to protect their users or potential visitors, and regardless of whether they undergo rehabilitation or change of use processes. Moreover, from a social perspective, we consider the need to prioritize buildings occupied by the most vulnerable groups of people that currently do not have specific regulations tailored to their needs. Some residential models in operation are not only outside the scope of application of the regulations in force; they also lack a project or technical data that would allow knowing the fire behavior of the construction materials. However, the difficulty and cost involved in adapting the entire building stock to current regulations can never justify the lack of safety for people. Hence, this work develops a simplified model to assess compliance with the basic safety conditions in case of fire and its compatibility with the specific accessibility needs of each user. The purpose is to support the designer in decision making, as well as to contribute to the development of a basic fire safety certification tool to be applied in inclusive residential models. This work has developed a methodology to support designers in adapting Social Services Centers, usually intended to vulnerable people. It incorporates a checklist of 9 items and information from sources or standards that designers can use to justify compliance or propose solutions. For each item, the verification system is justified, and possible sources of consultation are provided, considering the possibility of lacking technical documentation of construction systems or building materials. The procedure is based on diagnosing the degree of compliance with fire conditions of residential models used by vulnerable groups, considering the special accessibility conditions required by each user group. Through visual inspection and site surveying, the verification model can serve as a support tool, significantly streamlining the diagnostic phase and reducing the number of tests to be requested by over 75%. This speeds up and simplifies the diagnostic phase. To illustrate the methodology, two different buildings in the Valencian Region (Spain) have been selected. One case study is a mental health facility for residential purposes, located in a rural area, on the outskirts of a small town; the other one, is a day care facility for individuals with intellectual disabilities, located in a medium-sized city. The comparison between the case studies allow to validate the model in distinct conditions. Verifying compliance with a basic security level can allow a quality seal and a public register of buildings adapted to fire regulations to be established, similarly to what is being done with other types of attributes such as energy performance.

Keywords: fire safety, inclusive housing, universal accessibility, vulnerable people

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Authors: Neil Fourati

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Collaboration between public and private stakeholders for agricultural development are today lacking in Tunisia. The last dictatorship witnessed by the country has deteriorated the necessary trust between the state and small farmers for the realization of development projects, in particular in the interior, disadvantaged regions of the country. These regions, where the youth unemployment rate is above 30%, have been the heart of the uprising that preceded the revolution. The transitional period that the country is going through since 2011 is an opportunity for the emergence of new governance systems in the context of the decentralization. The latter is recognized in the 2nd Tunisian Republic constitution as the basis of regional management. Civil society participation to the decision-making process is considered as a mean to identify measures that are more coherent with local populations’ needs. The development of agriculture and food value chains in rural areas is relevant within the framework of the implementation of new decisions systems that require public-private collaborations. These new systems can lead to actions in favor of improving living conditions of rural populations. The diverisification of activities around agriculture can be a solution for job creation and local value creation. The project for the promotion of sustainable agriculture and rural development in Tunisia has designed and implemented a multi-stakeholder dialogue process for the development of local value chains platforms in disadvantaged areas of the country. The platforms gather public and private organizations ; as well civil society organizations ; that intervene in a locality in relation to the production transformation or product’s commercialization. The role of these platforms is to formulate realize and evaluate collaborative actions or projects for the promotion of the concerned product and territory. The dialogue process steps allow to create the necessary collaboration conditions in order to promote viable collectivities, dynamic economies and healthy environments. Effectively, the dialogue process steps allow to identify the local leaders. These leaders recognize the development constraints and opportunities. They deal with key and gathering subjects around the collaborative projects or actions. They take common decisions in order to create effective coalitions for the implementation of common actions. The plateforms realize quick success so as to build trust. The project has supported the formulation of 22 collaborative projects. Seven priority collaborative projects have been realized. Each collaborative project includes 3 parts : the signature of the collaboration conventions between public and private organizations, investment in the relevant material in order to increase productivity and the quality of local and products and finally management and technical training in favour of producers’ organizations for the promotion of local products. The implementation of this process has enabled to enhance the capacities of collaboration between local actors : producers, traders, processors and support structures from public sector and civil society. It also allowed to improve the efficiency and relevance of actions and measures for agriculture and rural development programs. Thus, the process for the development of local value chain platform is a basis for sustainable development of agriculture.

Keywords: governance, public private collaboration, rural development, value chains

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Authors: Chenyao Shen, Jie Shen

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The rating system provides an effective framework for assessing building environmental performance and integrating sustainable development into building and construction processes; as it can be used as a design tool by developing appropriate sustainable design strategies and determining performance measures to guide the sustainable design and decision-making processes. Healthcare buildings are resource (water, energy, etc.) intensive. To maintain high-cost operations and complex medical facilities, they require a great deal of hazardous and non-hazardous materials, stringent control of environmental parameters, and are responsible for producing polluting emission. Compared with other types of buildings, the impact of healthcare buildings on the full cycle of the environment is particularly large. With broad recognition among designers and operators that energy use can be reduced substantially, many countries have set up their own green rating systems for healthcare buildings. There are four main green healthcare building evaluation systems widely acknowledged in the world - Green Guide for Health Care (GGHC), which was jointly organized by the United States HCWH and CMPBS in 2003; BREEAM Healthcare, issued by the British Academy of Building Research (BRE) in 2008; the Green Star-Healthcare v1 tool, released by the Green Building Council of Australia (GBCA) in 2009; and LEED Healthcare 2009, released by the United States Green Building Council (USGBC) in 2011. In addition, the German Association of Sustainable Building (DGNB) has also been developing the German Sustainable Building Evaluation Criteria (DGNB HC). In China, more and more scholars and policy makers have recognized the importance of assessment of sustainable development, and have adapted some tools and frameworks. China’s first comprehensive assessment standard for green building (the GBTs) was issued in 2006 (lately updated in 2014), promoting sustainability in the built-environment and raise awareness of environmental issues among architects, engineers, contractors as well as the public. However, healthcare building was not involved in the evaluation system of GBTs because of its complex medical procedures, strict requirements of indoor/outdoor environment and energy consumption of various functional rooms. Learn from advanced experience of GGHC, BREEAM, and LEED HC above, China’s first assessment criteria for green hospital/healthcare buildings was finally released in December 2015. Combined with both quantitative and qualitative assessment criteria, the standard highlight the differences between healthcare and other public buildings in meeting the functional needs for medical facilities and special groups. This paper has focused on the assessment criteria framework for sustainable healthcare buildings, for which the comparison of different rating systems is rather essential. Descriptive analysis is conducted together with the cross-matrix analysis to reveal rich information on green assessment criteria in a coherent manner. The research intends to know whether the green elements for healthcare buildings in China are different from those conducted in other countries, and how to improve its assessment criteria framework.

Keywords: assessment criteria framework, green building design, healthcare building, building performance rating tool

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

Procedia PDF Downloads 155

Authors: Qian Chen, Lin Xu, Ping Ju, Zhuoran Li, Yiping Yu, Yuqing Jin

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The operation of power grid is becoming more and more complex and difficult due to its rapid development towards high voltage, long distance, and large capacity. For instance, many large-scale wind farms have connected to power grid, where their fluctuation and randomness is very likely to affect the stability and safety of the grid. Fortunately, many new-type equipments based on power electronics have been applied to power grid, such as UPFC (Unified Power Flow Controller), TCSC (Thyristor Controlled Series Compensation), STATCOM (Static Synchronous Compensator) and so on, which can help to deal with the problem above. Compared with traditional equipment such as generator, new-type controllable devices, represented by the FACTS (Flexible AC Transmission System), have more accurate control ability and respond faster. But they are too expensive to use widely. Therefore, on the basis of the comparison and analysis of the controlling characteristics between traditional control equipment and new-type controllable equipment in both time and space scale, a coordinated optimizing control method within mutil-time-space frame is proposed in this paper to bring both kinds of advantages into play, which can better both control ability and economical efficiency. Firstly, the coordination of different space sizes of grid is studied focused on the fluctuation caused by large-scale wind farms connected to power grid. With generator, FSC (Fixed Series Compensation) and TCSC, the coordination method on two-layer regional power grid vs. its sub grid is studied in detail. The coordination control model is built, the corresponding scheme is promoted, and the conclusion is verified by simulation. By analysis, interface power flow can be controlled by generator and the specific line power flow between two-layer regions can be adjusted by FSC and TCSC. The smaller the interface power flow adjusted by generator, the bigger the control margin of TCSC, instead, the total consumption of generator is much higher. Secondly, the coordination of different time sizes is studied to further the amount of the total consumption of generator and the control margin of TCSC, where the minimum control cost can be acquired. The coordination method on two-layer ultra short-term correction vs. AGC (Automatic Generation Control) is studied with generator, FSC and TCSC. The optimal control model is founded, genetic algorithm is selected to solve the problem, and the conclusion is verified by simulation. Finally, the aforementioned method within multi-time-space scale is analyzed with practical cases, and simulated on PSASP (Power System Analysis Software Package) platform. The correctness and effectiveness are verified by the simulation result. Moreover, this coordinated optimizing control method can contribute to the decrease of control cost and will provide reference to the following studies in this field.

Keywords: FACTS, multi-space-time frame, optimal control, TCSC

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Khethiwe Mtshali, Zamantungwa T. H. Khumalo, Stanford Kwenda, Ismail Arshad, Oriel M. M. Thekisoe

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Ecologically, the gut, mammary glands and bloodstream consist of distinct microbial communities of commensals, mutualists and pathogens, forming a complex ecosystem of niches. The by-products derived from these body sites i.e. faeces, milk and blood, respectively, have many uses in rural communities where they aid in the facilitation of day-to-day household activities and occasional rituals. Thus, although livestock rearing plays a vital role in the sustenance of the livelihoods of rural communities, it may serve as a potent reservoir of different pathogenic organisms that could have devastating health and economic implications. This study aimed to simultaneously explore the microbial profiles of corresponding faecal, milk and blood samples from lactating cows using 16S rRNA metagenomic sequencing. Bacterial communities were inferred through the Divisive Amplicon Denoising Algorithm 2 (DADA2) pipeline coupled with SILVA database v138. All downstream analyses were performed in R v3.6.1. Alpha-diversity metrics showed significant differences between faeces and blood, faeces and milk, but did not vary significantly between blood and milk (Kruskal-Wallis, P < 0.05). Beta-diversity metrics on Principal Coordinate Analysis (PCoA) and Non-Metric Dimensional Scaling (NMDS) clustered samples by type, suggesting that microbial communities of the studied niches are significantly different (PERMANOVA, P < 0.05). A number of taxa were significantly differentially abundant (DA) between groups based on the Wald test implemented in the DESeq2 package (Padj < 0.01). The majority of the DA taxa were significantly enriched in faeces than in milk and blood, except for the genus Anaplasma, which was significantly enriched in blood and was, in turn, the most abundant taxon overall. A total of 30 phyla, 74 classes, 156 orders, 243 families and 408 genera were obtained from the overall analysis. The most abundant phyla obtained between the three body sites were Firmicutes, Bacteroidota, and Proteobacteria. A total of 58 genus-level taxa were simultaneously detected between the sample groups, while bacterial signatures of at least 8 of these occurred concurrently in corresponding faeces, milk and blood samples from the same group of animals constituting a pool. The important taxa identified in this study could be categorized into four potentially pathogenic clusters: i) arthropod-borne; ii) food-borne and zoonotic; iii) mastitogenic and; iv) metritic and abortigenic. This study provides insight into the microbial composition of bovine faeces, milk, and blood and its extent of overlapping. It further highlights the potential risk of disease occurrence and transmission between the animals and the inhabitants of the sampled rural community, pertaining to their unsanitary practices associated with the use of cattle by-products.

Keywords: microbial profiling, 16S rRNA, NGS, feces, milk, blood, lactating cows, small-scale farmers

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Authors: Dimitriu Corneliu-Ioan, Gheorghe FrațIlă

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Romania has one of the highest rates of road deaths among European Union Member States, and there is a concern that the country will not meet its goal of "zero deaths" by 2050. The European Union also aims to halve the number of people seriously injured in road accidents by 2030. Therefore, there is a need to improve road infrastructure safety management in Romania. The aim of this study is to analyze road accident data through statistical methods to assess the current state of road infrastructure safety in Bucharest. The study also aims to identify trends and make forecasts regarding serious road accidents and their consequences. The objective is to provide insights that can help prioritize measures to increase road safety, particularly in urban areas. The research utilizes statistical analysis methods, including exploratory analysis and descriptive statistics. Databases from the Traffic Police and the Romanian Road Authority are analyzed using Excel. Road risks are compared with the main causes of road accidents to identify correlations. The study emphasizes the need for better quality and more diverse collection of road accident data for effective analysis in the field of road infrastructure engineering. The research findings highlight the importance of prioritizing measures to improve road safety in urban areas, where serious accidents and their consequences are more frequent. There is a correlation between the measures ordered by road safety auditors and the main causes of serious accidents in Bucharest. The study also reveals the significant social costs of road accidents, amounting to approximately 3% of GDP, emphasizing the need for collaboration between local and central administrations in allocating resources for road safety. This research contributes to a clearer understanding of the current road infrastructure safety situation in Romania. The findings provide critical insights that can aid decision-makers in allocating resources efficiently and institutionally cooperating to achieve sustainable road safety. The data used for this study are collected from the Traffic Police and the Romanian Road Authority. The data processing involves exploratory analysis and descriptive statistics using the Excel tool. The analysis allows for a better understanding of the factors contributing to the current road safety situation and helps inform managerial decisions to eliminate or reduce road risks. The study addresses the state of road infrastructure safety in Bucharest and analyzes the trends and forecasts regarding serious road accidents and their consequences. It studies the correlation between road safety measures and the main causes of serious accidents. To improve road safety, cooperation between local and central administrations towards joint financial efforts is important. This research highlights the need for statistical data processing methods to substantiate managerial decisions in road infrastructure management. It emphasizes the importance of improving the quality and diversity of road accident data collection. The research findings provide a critical perspective on the current road safety situation in Romania and offer insights to identify appropriate solutions to reduce the number of serious road accidents in the future.

Keywords: road death rate, strategic objective, serious road accidents, road safety, statistical analysis

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Authors: Kenneth A. Rostowsky, Alexander S. Maher, Nahian F. Chowdhury, Andrei Irimia

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The clinical significance of cerebral microbleeds (CMBs) due to mild traumatic brain injury (mTBI) remains unclear. Here we use magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and connectomic analysis to investigate the statistical association between mTBI-related CMBs, post-TBI changes to the human connectome and neurological/cognitive deficits. This study was undertaken in agreement with US federal law (45 CFR 46) and was approved by the Institutional Review Board (IRB) of the University of Southern California (USC). Two groups, one consisting of 26 (13 females) mTBI victims and another comprising 26 (13 females) healthy control (HC) volunteers were recruited through IRB-approved procedures. The acute Glasgow Coma Scale (GCS) score was available for each mTBI victim (mean µ = 13.2; standard deviation σ = 0.4). Each HC volunteer was assigned a GCS of 15 to indicate the absence of head trauma at the time of enrollment in our study. Volunteers in the HC and mTBI groups were matched according to their sex and age (HC: µ = 67.2 years, σ = 5.62 years; mTBI: µ = 66.8 years, σ = 5.93 years). MRI [including T1- and T2-weighted volumes, gradient recalled echo (GRE)/susceptibility weighted imaging (SWI)] and gradient echo (GE) DWI volumes were acquired using the same MRI scanner type (Trio TIM, Siemens Corp.). Skull-stripping and eddy current correction were implemented. DWI volumes were processed in TrackVis (http://trackvis.org) and 3D Slicer (http://www.slicer.org). Tensors were fit to DWI data to perform DTI, and tractography streamlines were then reconstructed using deterministic tractography. A voxel classifier was used to identify image features as CMB candidates using Microbleed Anatomic Rating Scale (MARS) guidelines. For each peri-lesional DTI streamline bundle, the null hypothesis was formulated as the statement that there was no neurological or cognitive deficit associated with between-scan differences in the mean FA of DTI streamlines within each bundle. The statistical significance of each hypothesis test was calculated at the α = 0.05 level, subject to the family-wise error rate (FWER) correction for multiple comparisons. Results: In HC volunteers, the along-track analysis failed to identify statistically significant differences in the mean FA of DTI streamline bundles. In the mTBI group, significant differences in the mean FA of peri-lesional streamline bundles were found in 21 out of 26 volunteers. In those volunteers where significant differences had been found, these differences were associated with an average of ~47% of all identified CMBs (σ = 21%). In 12 out of the 21 volunteers exhibiting significant FA changes, cognitive functions (memory acquisition and retrieval, top-down control of attention, planning, judgment, cognitive aspects of decision-making) were found to have deteriorated over the six months following injury (r = -0.32, p < 0.001). Our preliminary results suggest that acute post-TBI CMBs may be associated with cognitive decline in some mTBI patients. Future research should attempt to identify mTBI patients at high risk for cognitive sequelae.

Keywords: traumatic brain injury, magnetic resonance imaging, diffusion tensor imaging, connectomics

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Authors: Maggie Hall, Haley O'Neill

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The U.S. faces a severe shortage of abortion providers, exacerbated by the June 2022 Dobbs v. Jackson Women’s Health Organization decision. Midwives, especially certified nurse midwives, are well-positioned to fill this gap in abortion care. However, a lack of clinical education and training prevents midwives from exercising their full scope of practice. National and international organizations that set obstetrics and midwifery education standards, including the International Confederation of Midwives, American College of Obstetricians and Gynecologists, and American Public Health Association, call for expansion of midwifery-managed abortion care through the first trimester. In the U.S., midwifery programs are accredited based on compliance with ACME standards and compliance is a prerequisite for the American Midwifery Certification Board exams. We conducted a literature review of studies in the last five years regarding abortion didactic and clinical education barriers via CINAHL, EBSCO and PubMed database reviews. We gave preference for primary sources within the last five years; however, due to the rapid changes in abortion education and access, we also included literature from 2012-2022. We evaluated ACME-accredited programs in relation to their geography within abortion-protected or restricted states and assessed state-specific barriers to abortion care education and provision as clinical students. There are 43 AMCB-accredited midwifery schools in 28 states across the U.S. Twenty schools (47%) are in the 15 states in which advanced practice clinicians can provide non-surgical abortion care, such as medication abortion and MVA procedures. Twenty-four schools (56%) are in the 16 states in which abortion care provision is restricted to Licensed Physicians and cannot offer in-state clinical training opportunities for midwifery students. Six schools are in the five states in which abortion is completely banned and are geographically concentrated in the southernmost region of the U.S., including Alabama, Kentucky, Louisiana, Tennessee, and Texas. Subsequently, these programs cannot offer in-state clinical training opportunities for midwifery students. Notably, there are seven ACME programs in six states that do not restrict abortion access by gestational age, including Colorado, Connecticut, Washington, D.C., New Jersey, New Mexico, and Oregon. These programs may be uniquely positioned for midwifery involvement in abortion care beyond the first trimester. While the following states don’t house ACME programs, abortion care can be provided by advanced practice clinicians in Rhode Island, Delaware, Hawaii, Maine, Maryland, Montana, New Hampshire, and Vermont, offering clinical placement and/or new ACME program development opportunities. We identify existing barriers to clinical education and training opportunities for midwifery-managed abortion care, which are both geographic and institutional in nature. We recommend expansion and standardization of clinical education and training opportunities for midwifery-managed abortion care in ACME-accredited programs to improve access to abortion care. Midwifery programs and teaching hospitals need to expand education, training, and residency opportunities for midwifery students to strengthen access to midwife-managed abortion care. ACNM and ACME should re-evaluate accreditation criteria and the implications of ACME programs in states where students are not able to learn abortion care in clinical contexts due to state-specific abortion restrictions.

Keywords: midwifery education, abortion, abortion education, abortion access

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Authors: Laura Roe

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This study draws on twelve months of ethnographic fieldwork conducted in 2017 with heroin and poly-substance users in Scotland and explores experiences of time and temporality as factors in continuing drug use. The research largely took place over the year in which drug-related deaths in Scotland reached a record high, and were statistically recorded as the highest in Europe. This qualitative research is therefore significant in understanding both evolving patterns of drug use and the experiential lifeworlds of those who use heroin and other substances in high doses. Methodologies included participant observation, structured and semi-structured interviews, and unstructured conversations with twenty-two regular participants. The fieldwork was conducted in two needle exchanges, a community recovery group and in the community. The initial aim of the study was to assess evolving patterns of drug preferences in order to explore a clinical and user-reported rise in the use of novel psychoactive substances (NPS), which are typically considered to be highly potent, synthetic substances, often available at a low cost. It was found, however, that while most research participants had experimented with NPS with varying intensity, those who used every day regularly consumed heroin, methadone, and alcohol with benzodiazepines such as diazepam or anticonvulsants such as gabapentin. The research found that many participants deliberately pursued the non-fatal effects of overdose, aiming to induce states of dissociation, detachment and uneven consciousness, and did so by both mixing substances and experimenting with novel modes of consumption. Temporality was significant in the decision to consume cocktails of substances, as users described wishing to sever themselves from time; entering into states of ‘non-time’ and insensibility through specific modes of intoxication. Time and temporality similarly impacted other aspects of addicted life. Periods of attempted abstinence witnessed a slowing of time’s passage that was tied to affective states of boredom and melancholy, in addition to a disruptive return of distressing and difficult memories. Abject past memories frequently dominated and disrupted the present, which otherwise could be highly immersive due to the time and energy-consuming nature of seeking drugs while in financial difficulty. There was furthermore a discordance between individual user temporalities and the strict time-based regimes of recovery services and institutional bodies, and the study aims to highlight the impact of such a disjuncture on the efficacy of treatment programs. Many participants had difficulty in adhering to set appointments or temporal frameworks due to their specific temporal situatedness. Overall, exploring increasing tendencies of heroin users in Scotland towards poly-substance use, this study draws on experiences and perceptions of time, analysing how temporality comes to bear on the ways drugs are sought and consumed, and how recovery is imagined and enacted. The study attempts to outline the experiential, intimate and subjective worlds of heroin and poly-substance users while explicating the structural and historical factors that shape them.

Keywords: addiction, poly-substance use, temporality, timelessness

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Authors: Brenda Ravenscroft, Ulemu Luhanga, Bev King

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A comprehensive evaluation of online learning needs to include a blend of educational design, technology use, and online instructional practices that integrate technology appropriately for developing and delivering quality online courses. Research shows that classroom-based evaluation tools do not adequately capture the dynamic relationships between content, pedagogy, and technology in online courses. Furthermore, studies suggest that using classroom evaluations for online courses yields lower than normal scores for instructors, and may affect faculty negatively in terms of administrative decisions. In 2014, the Faculty of Arts and Science at Queen’s University responded to this evidence by seeking an alternative to the university-mandated evaluation tool, which is designed for classroom learning. The Faculty is deeply engaged in e-learning, offering large variety of online courses and programs in the sciences, social sciences, humanities and arts. This paper describes the process by which a new student survey instrument for online courses was developed and piloted, the methods used to analyze the data, and the ways in which the instrument was subsequently adapted based on the results. It concludes with a critical reflection on the challenges of evaluating e-learning. The Student Evaluation of Online Teaching Effectiveness (SEOTE), developed by Arthur W. Bangert in 2004 to assess constructivist-compatible online teaching practices, provided the starting point. Modifications were made in order to allow the instrument to serve the two functions required by the university: student survey results provide the instructor with feedback to enhance their teaching, and also provide the institution with evidence of teaching quality in personnel processes. Changes were therefore made to the SEOTE to distinguish more clearly between evaluation of the instructor’s teaching and evaluation of the course design, since, in the online environment, the instructor is not necessarily the course designer. After the first pilot phase, involving 35 courses, the results were analyzed using Stobart's validity framework as a guide. This process included statistical analyses of the data to test for reliability and validity, student and instructor focus groups to ascertain the tool’s usefulness in terms of the feedback it provided, and an assessment of the utility of the results by the Faculty’s e-learning unit responsible for supporting online course design. A set of recommendations led to further modifications to the survey instrument prior to a second pilot phase involving 19 courses. Following the second pilot, statistical analyses were repeated, and more focus groups were used, this time involving deans and other decision makers to determine the usefulness of the survey results in personnel processes. As a result of this inclusive process and robust analysis, the modified SEOTE instrument is currently being considered for adoption as the standard evaluation tool for all online courses at the university. Audience members at this presentation will be stimulated to consider factors that differentiate effective evaluation of online courses from classroom-based teaching. They will gain insight into strategies for introducing a new evaluation tool in a unionized institutional environment, and methodologies for evaluating the tool itself.

Keywords: evaluation, online courses, student survey, teaching effectiveness

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Jérôme de Reffye, Marc Antoni

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Following the development of the ERTMS system, we think it is interesting to develop another software-based track circuit system which would fit secondary railway lines with an easy-to-work implementation and a low sensitivity to rail-wheel impedance variations. We called this track circuit 'Track Railway by Automatic Circuits.' To be internationally implemented, this system must not have any mechanical component and must be compatible with existing track circuit systems. For example, the system is independent from the French 'Joints Isolants Collés' that isolate track sections from one another, and it is equally independent from component used in Germany called 'Counting Axles,' in French 'compteur d’essieux.' This track circuit is fully interoperable. Such universality is obtained by replacing the train detection mechanical system with a space-time filtering of train position. The various track sections are defined by the frequency of a continuous signal. The set of frequencies related to the track sections is a set of orthogonal functions in a Hilbert Space. Thus the failure probability of track sections separation is precisely calculated on the basis of signal-to-noise ratio. SNR is a function of the level of traction current conducted by rails. This is the reason why we developed a very powerful algorithm to reject noise and jamming to obtain an SNR compatible with the precision required for the track circuit and SIL 4 level. The SIL 4 level is thus reachable by an adjustment of the set of orthogonal functions. Our major contributions to railway engineering signalling science are i) Train space localization is precisely defined by a calibration system. The operation bypasses the GSM-R radio system of the ERTMS system. Moreover, the track circuit is naturally protected against radio-type jammers. After the calibration operation, the track circuit is autonomous. ii) A mathematical topology adapted to train space localization by following the train through a linear time filtering of the received signal. Track sections are numerically defined and can be modified with a software update. The system was numerically simulated, and results were beyond our expectations. We achieved a precision of one meter. Rail-ground and rail-wheel impedance sensitivity analysis gave excellent results. Results are now complete and ready to be published. This work was initialised as a research project of the French Railways developed by the Pi-Ramses Company under SNCF contract and required five years to obtain the results. This track circuit is already at Level 3 of the ERTMS system, and it will be much cheaper to implement and to work. The traffic regulation is based on variable length track sections. As the traffic growths, the maximum speed is reduced, and the track section lengths are decreasing. It is possible if the elementary track section is correctly defined for the minimum speed and if every track section is able to emit with variable frequencies.

Keywords: track section, track circuits, space-time crossing, adaptive track section, automatic railway signalling

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Authors: Jennifer Kehinde, Claire O’Donnell, Annmarie Grealish

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Introduction: Breastfeeding has been shown to provide numerous health benefits for both infants and mothers. The decision to breastfeed is influenced by physiological, psychological, and emotional factors. However, the importance of equipping mothers with the necessary knowledge for successful breastfeeding practice cannot be ruled out. The decline in global breastfeeding rate can be linked to a lack of adequate breastfeeding education during the prenatal stage. This systematic review examined the effectiveness of prenatal breastfeeding education on breastfeeding uptake postpartum. Method: This review was undertaken and reported in conformity with the Preferred Reporting Items for Systemic Reviews and Meta-Analysis statement (PRISMA) and was registered on the international prospective register for systematic reviews (PROSPERO: CRD42020213853). A PICO analysis (population, intervention, comparison, outcome) was undertaken to inform the choice of keywords in the search strategy to formulate the review question, which was aimed at determining the effectiveness of prenatal breastfeeding educational programs in improving breastfeeding uptake following birth. A systematic search of five databases (Cumulative Index to Nursing and Allied Health Literature, Medline, Psych INFO, and Applied Social Sciences Index and Abstracts) was searched between January 2014 until July 2021 to identify eligible studies. Quality assessment and narrative synthesis were subsequently undertaken. Results: Fourteen studies were included. All 14 studies used different types of breastfeeding programs; eight used a combination of curriculum-based breastfeeding education programs, group prenatal breastfeeding counselling, and one-to-one breastfeeding educational programs, which were all delivered in person; four studies used web-based learning platforms to deliver breastfeeding education prenatally which were both delivered online and face to face over a period of 3 weeks to 2 months with follow-up periods ranging from 3 weeks to 6 months; one study delivered breastfeeding educational intervention using mother-to-mother breastfeeding support groups in promoting exclusive breastfeeding, and one study disseminated breastfeeding education to participants based on the theory of planned behaviour. The most effective interventions were those that included both theory and hands-on demonstrations. Results showed an increase in breastfeeding uptake, breastfeeding knowledge, an increase in a positive attitude to breastfeeding, and an increase in maternal breastfeeding self-efficacy among mothers who participated in breastfeeding educational programs during prenatal care. Conclusion: Prenatal breastfeeding education increases women’s knowledge of breastfeeding. Mothers who are knowledgeable about breastfeeding and hold a positive approach towards breastfeeding have the tendency to initiate breastfeeding and continue for a lengthened period. Findings demonstrate a general correlation between prenatal breastfeeding education and increased breastfeeding uptake postpartum. The high level of positive breastfeeding outcomes inherent in all the studies can be attributed to prenatal breastfeeding education. This review provides rigorous contemporary evidence that healthcare professionals and policymakers can apply when developing effective strategies to improve breastfeeding rates and ultimately improve the health outcomes of mothers and infants.

Keywords: breastfeeding, breastfeeding programs, breastfeeding self-efficacy, prenatal breastfeeding education

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Authors: A. Abubakar, A. Parsa, S. Walker

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Despite advances made in the diagnosis and management of drug-sensitive tuberculosis (TB) over the past decades, treatment of multidrug-resistant tuberculosis (MDR-TB) remains challenging and complex particularly in high burden countries including Nigeria. Treatment of MDR-TB is cost-prohibitive with success rate generally lower compared to drug-sensitive TB and if care is not taken it may become the dominant form of TB in future with many treatment uncertainties and substantial morbidity and mortality. Addressing these challenges requires collaborative efforts thorough sustained researches to evaluate the current treatment guidelines, particularly in high burden countries and prevent progression of resistance. To our best knowledge, there has been no research exploring the acceptability, effectiveness, and cost-effectiveness of community-based-MDR-TB treatment model in Nigeria, which is among the high burden countries. The previous similar qualitative study looks at the home-based management of MDR-TB in rural Uganda. This research aimed to explore patient’s views and acceptability of community-based-MDR-TB treatment model and to evaluate and compare the effectiveness and cost-effectiveness of community-based versus hospital-based MDR-TB treatment model of care from the Nigerian perspective. Knowledge of patient’s views and acceptability of community-based-MDR-TB treatment approach would help in designing future treatment recommendations and in health policymaking. Accordingly, knowledge of effectiveness and cost-effectiveness are part of the evidence needed to inform a decision about whether and how to scale up MDR-TB treatment, particularly in a poor resource setting with limited knowledge of TB. Mixed methods using qualitative and quantitative approach were employed. Qualitative data were obtained using in-depth semi-structured interviews with 21 MDR-TB patients in Nigeria to explore their views and acceptability of community-based MDR-TB treatment model. Qualitative data collection followed an iterative process which allowed adaptation of topic guides until data saturation. In-depth interviews were analyzed using thematic analysis. Quantitative data on treatment outcomes were obtained from medical records of MDR-TB patients to determine the effectiveness and direct and indirect costs were obtained from the patients using validated questionnaire and health system costs from the donor agencies to determine the cost-effectiveness difference between community and hospital-based model from the Nigerian perspective. Findings: Some themes have emerged from the patient’s perspectives indicating preference and high acceptability of community-based-MDR-TB treatment model by the patients and mixed feelings about the risk of MDR-TB transmission within the community due to poor infection control. The result of the modeling from the quantitative data is still on course. Community-based MDR-TB care was seen as the acceptable and most preferred model of care by the majority of the participants because of its convenience which in turn enhanced recovery, enables social interaction and offer more psychosocial benefits as well as averted productivity loss. However, there is a need to strengthen this model of care thorough enhanced strategies that ensure guidelines compliance and infection control in order to prevent the progression of resistance and curtail community transmission.

Keywords: acceptability, cost-effectiveness, multidrug-resistant TB treatment, community and hospital approach

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Authors: Wen Liu, Errol Haarhoff, Lee Beattie

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In 2010, New Zealand’s central government re-organise the local governments arrangements in Auckland, New Zealand by amalgamating its previous regional council and seven supporting local government units into a single unitary council, the Auckland Council. The Auckland Council is charged with providing local government services to approximately 1.5 million people (a third of New Zealand’s total population). This includes addressing Auckland’s strategic urban growth management and setting its urban planning policy directions for the next 40 years. This is expressed in the first ever spatial plan in the region – the Auckland Plan (2012). The Auckland plan supports implementing a compact city model by concentrating the larger part of future urban growth and development in, and around, existing and proposed transit centres, with the intention of Auckland to become globally competitive city and achieving ‘the most liveable city in the world’. Turning that vision into reality is operatized through the statutory land use plan, the Auckland Unitary Plan. The Unitary plan replaced the previous regional and local statutory plans when it became operative in 2016, becoming the ‘rule book’ on how to manage and develop the natural and built environment, using land use zones and zone standards. Common to the broad range of literature on urban growth management, one significant issue stands out about intensification. The ‘gap’ between strategic planning and what has been achieved is evident in the argument for the ‘compact’ urban form. Although the compact city model may have a wide range of merits, the extent to which these are actualized largely rely on how intensification actually is delivered. The transformation of the rhetoric of the residential intensification model into reality is of profound influence, yet has enjoyed limited empirical analysis. In Auckland, the establishment of the Auckland Plan set up the strategies to deliver intensification into diversified arenas. Nonetheless, planning policy itself does not necessarily achieve the envisaged objectives, delivering the planning system and high capacity to enhance and sustain plan implementation is another demanding agenda. Though the Auckland Plan provides a wide ranging strategic context, its actual delivery is beholden on the Unitary Plan. However, questions have been asked if the Unitary Plan has the necessary statutory tools to deliver the Auckland Plan’s policy outcomes. In Auckland, there is likely to be continuing tension between the strategies for intensification and their envisaged objectives, and made it doubtful whether the main principles of the intensification strategies could be realized. This raises questions over whether the Auckland Plan’s policy goals can be achieved in practice, including delivering ‘quality compact city’ and residential intensification. Taking Auckland as an example of traditionally sprawl cities, this article intends to investigate the efficacy plan making and implementation directed towards higher density development. This article explores the process of plan development, plan making and implementation frameworks of the first ever spatial plan in Auckland, so as to explicate the objectives and processes involved, and consider whether this will facilitate decision making processes to realize the anticipated intensive urban development.

Keywords: urban intensification, sustainable development, plan making, governance and implementation

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Magdalena Orth, Gunnar Gotz

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Background: Domestic accountability, budget transparency and public financial management (PFM) are considered vital components of good governance in developing countries. The aid modality budget support (BS) promotes these governance functions in developing countries. BS engages in political decision-making and provides financial and technical support to poverty reduction strategies of the partner countries. Nevertheless, many donors have withdrawn their support from this modality due to cases of corruption, fraud or human rights violations. This exit from BS is leaving a finance and governance vacuum in the countries. The evaluation team analyzed the consequences of terminating the use of this modality and found particularly negative effects for good governance outcomes. Methodology: The evaluation uses a qualitative (theory-based) approach consisting of a comparative case study design, which is complemented by a process-tracing approach. For the case studies, the team conducted over 100 semi-structured interviews in Malawi, Uganda, Rwanda and Zambia and used four country-specific, tailor-made budget analysis. In combination with a previous DEval evaluation synthesis on the effects of BS, the team was able to create a before-and-after comparison that yields causal effects. Main Findings: In all four countries domestic accountability and budget transparency declined if other forms of pressure are not replacing BS´s mutual accountability mechanisms. In Malawi a fraud scandal created pressure from the society and from donors so that accountability was improved. In the other countries, these pressure mechanisms were absent so that domestic accountability declined. BS enables donors to actively participate in political processes of the partner country as donors transfer funds into the treasury of the partner country and conduct a high-level political dialogue. The results confirm that the exit from BS created a governance vacuum that, if not compensated through external/internal pressure, leads to a deterioration of good governance. For example, in the case of highly aid dependent Malawi did the possibility of a relaunch of BS provide sufficient incentives to push for governance reforms. Overall the results show that the three good governance areas are negatively affected by the exit from BS. This stands in contrast to positive effects found before the exit. The team concludes that the relationship is causal, because the before-and-after comparison coherently shows that the presence of BS correlates with positive effects and the absence with negative effects. Conclusion: These findings strongly suggest that BS is an effective modality to promote governance and its abolishment is likely to cause governance disruptions. Donors and partner governments should find ways to re-engage in closely coordinated policy-based aid modalities. In addition, a coordinated and carefully managed exit-strategy should be in place before an exit from similar modalities is considered. Particularly a continued framework of mutual accountability and a high-level political dialogue should be aspired to maintain pressure and oversight that is required to achieve good governance.

Keywords: budget support, domestic accountability, public financial management and budget transparency, Sub-Sahara Africa

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Authors: Ronald Orth, Johanna Haunschild, Sara Tsog

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The bioeconomy is an inter- and cross-disciplinary field covering a large number and wide scope of existing and emerging technologies. It has a great potential to contribute to the transformation process of industry landscape and ultimately drive the economy towards sustainability. However, bioeconomy per se is not necessarily sustainable and technology should be seen as an enabler rather than panacea to all our ecological, social and economic issues. Therefore, to draw and maximize benefits from bioeconomy in terms of sustainability, we propose that innovative activities should encompass not only novel technologies and bio-based new materials but also multifocal innovations. For multifocal innovation endeavors, innovation management plays a substantial role, as any innovation emerges in a complex iterative process where communication and knowledge exchange among relevant stake holders has a pivotal role. The knowledge generation and innovation are although at the core of transition towards a more sustainable bio-based economy, to date, there is a significant lack of concepts and models that approach bioeconomy from the innovation management approach. The aim of this paper is therefore two-fold. First, it inspects the role of transformative approach in the adaptation of bioeconomy that contributes to the environmental, ecological, social and economic sustainability. Second, it elaborates the importance of technology and innovation management as a tool for smooth, prompt and effective transition of firms to the bioeconomy. We conduct a qualitative literature study on the sustainability challenges that bioeconomy entails thus far using Science Citation Index and based on grey literature, as major economies e.g. EU, USA, China and Brazil have pledged to adopt bioeconomy and have released extensive publications on the topic. We will draw an example on the forest based business sector that is transforming towards the new green economy more rapidly as expected, although this sector has a long-established conventional business culture with consolidated and fully fledged industry. Based on our analysis we found that a successful transition to sustainable bioeconomy is conditioned on heterogenous and contested factors in terms of stakeholders , activities and modes of innovation. In addition, multifocal innovations occur when actors from interdisciplinary fields engage in intensive and continuous interaction where the focus of innovation is allocated to a field of mutually evolving socio-technical practices that correspond to the aims of the novel paradigm of transformative innovation policy. By adopting an integrated and systems approach as well as tapping into various innovation networks and joining global innovation clusters, firms have better chance of creating an entire new chain of value added products and services. This requires professionals that have certain capabilities and skills such as: foresight for future markets, ability to deal with complex issues, ability to guide responsible R&D, ability of strategic decision making, manage in-depth innovation systems analysis including value chain analysis. Policy makers, on the other hand, need to acknowledge the essential role of firms in the transformative innovation policy paradigm.

Keywords: bioeconomy, innovation and technology management, multifocal innovation, sustainability, transformative innovation policy

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Authors: Colin S. Chen, Chien-Jung Tien, Hsin-Jan Huang

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For weathering studies, the change of chemical constituents by biodegradation effect in diesel-contaminated soils are important factors to be considered, especially when there is a prolonged period of weathering processes. The objective was to evaluate biodegradation effects onto hydrocarbon fingerprinting and distribution patterns of diesel fuels, fuel source screening and differentiation, source-specific marker compounds, and diagnostic ratios of diesel fuel constituents by laboratory and field studies. Biodegradation processes of diesel contaminated soils were evaluated by experiments lasting for 15 and 12 months, respectively. The degradation of diesel fuel in top soils was affected by organic carbon content and biomass of microorganisms in soils. Higher depletion of total petroleum hydrocarbon (TPH), n-alkanes, and polynuclear aromatic hydrocarbons (PAHs) and their alkyl homologues was observed in soils containing higher organic carbon content and biomass. Decreased ratio of selected isoprenoids (i.e., pristane (Pr) and phytane (Ph)) including n-C17/pristane and n-C18/phytane was observed. The ratio of pristane/phytane was remained consistent for a longer period of time. At the end of the experimental period, a decrease of pristane/phytane was observed. Biomarker compounds of bicyclic sesquiterpanes (BS) were less susceptible to the effects of biodegradation. The ratios of characteristic factors such as C15 sesquiterpane/ 8β(H)-drimane (BS3/BS5), C15 sesquiterpane/ 8β(H)-drimane (BS4/BS5), 8β(H)-drimane/8β(H)-homodrimane (BS5/BS10), and C15 sesquiterpane/8β(H)-homodrimane (BS3/BS10) could be adopted for source identification of diesel fuels in top soil. However, for biodegradation processes lasted for six months but shorter than nine months, only BS3/BS5 and BS3/BS10 could be distinguished in two diesel fuels. In subsoil experiments (contaminated soil located 50 cm below), the ratios of characteristic factors including BS3/BS5, BS4/BS5, and BS5/BS10 were valid for source identification of two diesel fuels for nine month biodegradation. At the early stage of contamination, biomass of soil decreased significantly. However, 6 and 7 dominant species were found in soils in top soil experiments, respectively. With less oxygen and nutrients in subsoil, less biomass of microorganisms was observed in subsoils. Only 2 and 4 diesel-degrading species of microorganisms were identified in two soils, respectively. Parameters of double ratio such as fluorene/C1-fluorene: C2-phenanthrene/C3-phenanthrene (C0F/C1F:C2P/C3P) in both top and subsoil, C2-naphthalene/C2-phenanthrene: C1-phenanthrene/C3-phenanthrene (C2N/C2P:C1P/C3P), and C1-phenanthrene/C1-fluorene: C3-naphthalene/C3-phenanthrene (C1P/C1F:C3N/C3P) in subsoil could serve as forensic indicators in diesel contaminated sites. BS3/BS10:BS4/BS5 could be used in 6 to 9 months of biodegradation processes. Results of principal component analysis (PCA) indicated that source identification of diesel fuels in top soil could only be perofrmed for weathering process less than 6 months. For subsoil, identification can be conducted for weathering process less than 9 months. Ratio of isoprenoids (pristane and phytane) and PAHs might be affected by biodegradation in spilled sites. The ratios of bicyclic sesquiterpanes could serve as forensic indicators in diesel-contaminated soils. Finally, source identification was attemped for samples collected from different fuel contaminated sites by using the unique pattern of sesquiterpanes. It was anticipated that the information generated from this study would be adopted by decision makers to evaluate the liability of cleanup in diesel contaminated sites.

Keywords: biodegradation, diagnostic ratio, diesel fuel, environmental forensics

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: Maria Ledinskaya

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This paper is part case study and part literature review. It seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation by looking at their practical application on a recent conservation project at the Sainsbury Centre for Visual Arts. The author outlines the advantages of leaner and more agile conservation practices in today’s faster, less certain, and more budget-conscious museum climate where traditional project structures are no longer as relevant or effective. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre by private collectors Michael and Joyce Morris. It was a medium-sized conservation project of moderate complexity, planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown conditions and materials, unconfirmed budget. The project was later impacted by the COVID-19 pandemic, introducing indeterminate lockdowns, budget cuts, staff changes, and the need to accommodate social distancing and remote communications. The author, then a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. The paper examines the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, including the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics. Although not intentionally planned as such, the Morris Project had a number of Agile and Lean features which were instrumental to its successful delivery. These key features are identified as distributed decision-making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point in favour of a hybrid model, which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: agile project management, conservation, hybrid project management, lean project management, waterfall project management

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Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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Authors: Shierwin Agagen Cabunilas

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The unitary form of Philippine government has built a tradition of bureaucracy that strengthened oligarch and clientele politics. Consequently, the Philippines is lagged behind development. There is so much poverty, unemployment, and inadequate social services. In addition, it seems that the rights of national ethnic minority groups like the Igorots to develop their political and economic interests, linguistic and cultural heritage are neglected. Given these circumstances, a paradigm shift is inevitable. The author advocates a transition from a unitary to a federal system of government. Contrary to the notion that a unitary system facilitates better governance, it actually stifles it. As a unitary government, the Philippines seems (a) to exhibit incompetence in delivering efficient, necessary services to the people and (b) to exclude the minority from political participation and policy making. This shows that Philippine unitary system is highly centralized and operates from a top-bottom scheme. However, a federal system encourages decentralization, plurality and political participation. In my view, federalism is beneficial to the Philippine society and congenial to the Igorot indigenous peoples insofar as participative decision-making and development goals are concerned. This research employs critical and constructive analyses. The former interprets some complex practices of Philippine politics while the latter investigates how theories of federalism can be appropriated to deal with political deficits, ethnic diversity, and indigenous peoples’ rights to self-determination. The topic is developed accordingly: First, the author briefly examines the unitary structure of the Philippines and its impact on inter-governmental affairs and processes, asserting that bureaucracy and corruption, for example, are counterproductive to a participative political life, to economic development and to the recognition of national ethnic minorities. Second, he scrutinizes why federalism might transform this. Here, he assesses various opposing philosophical contentions on federal system in managing ethnically diverse society, like the Philippines, and argue that decentralization of political power, economic and cultural developments are reasons to exit from unitary government. Third, he suggests that federalism can be instrumental to Igorots self-determination. Self-determination is neither opposed to national development nor to the ideals of democracy – liberty, justice, solidarity. For example, as others have already noted, a politics in the vernacular facilitates greater participation among the people. Hence, there is a greater chance to arrive at policies that serve the interest of the people. Some may wary that decentralization disintegrates a nation. According to the author, however, the recognition of minority rights which includes self-determination may promote filial devotion to the state. If Igorot indigenous peoples have access to suitable institutions to determine their political life, economic goals, social needs, i.e., education, culture, language, chances are it moves the country forward to development fostering national unity. Remarkably, federal system thus best responds to the Philippines’s democratic and development deficits. Federalism can also significantly rectify the practices that oppress and dislocate national ethnic minorities as it ensures the creation of localized institutions for optimum political, economic, cultural determination and maximizes representation in the public sphere.

Keywords: federalism, Igorot, indigenous peoples, self-determination

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Authors: Jennifer Kehinde, Claire O'donnell, Annmarie Grealish

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Introduction: Breastfeeding has been shown to provide numerous health benefits for both infants and mothers. The decision to breastfeed is influenced by physiological, psychological, and emotional factors. However, the importance of equipping mothers with the necessary knowledge for successful breastfeeding practice cannot be ruled out. The decline in global breastfeeding rate can be linked to lack of adequate breastfeeding education during prenatal stage.This systematic review examined the effectiveness of prenatal breastfeeding education on breastfeeding uptake postpartum. Method: This review was undertaken and reported in conformity with the Preferred Reporting Items for Systemic Reviews and Meta-Analysis statement (PRISMA) and was registered on the international prospective register for systematic reviews (PROSPERO: CRD42020213853). A PICO analysis (population, intervention, comparison, outcome) was undertaken to inform the choice of keywords in the search strategy to formulate the review question which was aimed at determining the effectiveness of prenatal breastfeeding educational programs at improving breastfeeding uptake following birth. A systematic search of five databases (Cumulative Index to Nursing and Allied Health Literature, Medline, Psych INFO, and Applied Social Sciences Index and Abstracts) were searched between January 2014 until July 2021 to identify eligible studies. Quality assessment and narrative synthesis were subsequently undertaken. Results: Fourteen studies were included. All 14 studies used different types of breastfeeding programs; eight used a combination of curriculum based breastfeeding education program, group prenatal breastfeeding counselling and one-to-one breastfeeding educational programs which were all delivered in person; four studies used web-based learning platforms to deliver breastfeeding education prenatally which were both delivered online and face to face over a period of 3 weeks to 2 months with follow-up periods ranging from 3 weeks to 6 months; one study delivered breastfeeding educational intervention using mother-to-mother breastfeeding support groups in promoting exclusive breastfeeding and one study disseminated breastfeeding education to participants based on the theory of planned behaviour. The most effective interventions were those that included both theory and hands-on demonstrations. Results showed an increase in breastfeeding uptake, breastfeeding knowledge, increase in positive attitude to breastfeeding and an increase in maternal breastfeeding self-efficacy among mothers who participated in breastfeeding educational programs during prenatal care. Conclusion: Prenatal breastfeeding education increases women’s knowledge of breastfeeding. Mothers who are knowledgeable about breastfeeding and hold a positive approach towards breastfeeding have the tendency to initiate breastfeeding and continue for a lengthened period. Findings demonstrates a general correlation between prenatal breastfeeding education and increased breastfeeding uptake postpartum. The high level of positive breastfeeding outcome inherent in all the studies can be attributed to prenatal breastfeeding education. This review provides rigorous contemporary evidence that healthcare professionals and policymakers can apply when developing effective strategies to improve breastfeeding rates and ultimately improve the health outcomes of mothers and infants.

Keywords: breastfeeding, breastfeeding programs, breastfeeding self-efficacy, prenatal breastfeedng education

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Authors: Marta Gràcia, Ana Luisa Adam-Alcocer, Jesús M. Alvarado, Verónica Quezada, Tere Zarza, Priscila Garza

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In secondary education, integrating linguistic content and reflection on it is a crucial challenge that should be included in course plans to enhance students' oral communication competence. In secondary education classrooms, a continuum can be identified in relation to teaching methodologies: 1) the traditional teacher-dominated transmission approach, which is described as that in which teachers transmit content to students unidirectionally; 2) dialogical, bidirectional teaching approach that encourages students to adopt a critical vision of the information provided by the teacher or that is generated through students’ discussion. In this context, the EVALOE-DSS (Assessment Scale of Oral Language Teaching in the School Context-Decision Support System) digital instrument has emerged to help teachers in transforming their classes into spaces for communication, dialogue, reflection, evaluation of the learning process, teaching linguistic contents, and to develop curricular competencies. The tool includes various resources, such as a tutorial with the objectives and an initial screen for teachers to describe the class to be evaluated. One of the main resources of the digital instrument consists of 30 items-actions with three qualitative response options (green, orange, and red face emoji) grouped in five dimensions. In the context of the participation of secondary education teachers in a professional development program using EVALOE-DSS, a digital tool resource aimed to generate more participatory, interactive, dialogic classes, the objectives of the study were: 1) understanding the changes in classrooms’ dynamics and in the teachers’ strategies during their participation in the professional developmental program; 2) analyzing the impact of these changes in students’ oral language development according to their teachers; 3) Deeping on the impact of these changes in the students’ assessment of the classes and the self-assessment of oral competence; 4) knowing teachers’ assessment and reflections about their participation in the professional developmental program. Participants were ten teachers of different subjects and 250 students of secondary education (16-18 years) schools in Spain. The principal instrument used was the digital tool EVALOE-DSS. For 6 months, teachers used the digital tool to reflect on their classes, assess them (their actions and their students’ actions), make decisions, and introduce changes in their classes to be more participatory, interactive, and reflective about linguistic contents. Other collecting data instruments and techniques used during the study were: 1) a questionnaire to assess students’ oral language competence before and at the end of the study, 2) a questionnaire for students’ assessment of the characteristics of classes, 3) teachers’ meetings during the professional developmental program to reflect collaboratively on their experience, 4) questionnaire to assess teacher’s experience during their participation in the professional developmental program, 5) focus group meetings between the teachers and two researchers at the end of the study. The results showed relevant changes in teaching strategies, in the dynamics of the classes, which were more interactive, participative, dialogic and self-managed by the students. Both teachers and students agree about the progressive classes’ transformation into spaces for communication, discussion, and reflection on the language, its development, and its use as an essential instrument to develop curricular competencies.

Keywords: digital tool, individual and collaborative reflection, oral language competence, professional development program, secondary education

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