Search results for: combining ability

Authors: O. Lasaga

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Defining professional objectives and the search for work are some of the greatest stress factors for final year university students and recent graduates. To manage correctly the stress brought about by the uncertainty, confusion and frustration this process often generates, a course to control stress based on mindfulness has been designed and taught. This course provides tools based on relaxation, mindfulness and meditation that enable students to address personal and professional challenges in the transition to the job market, eliminating or easing the anxiety involved. The course is extremely practical and experiential, combining theory classes and practical classes of relaxation, meditation and mindfulness, group dynamics, reflection, application protocols and session integration. The evaluation of the courses highlighted on the one hand the high degree of satisfaction and, on the other, the usefulness for the students in becoming aware of stressful situations and how these affect them and learning new coping techniques that enable them to reach their goals more easily and with greater satisfaction and well-being.

Keywords: employability, meditation, mindfulness, relaxation techniques, stress

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Authors: Ismael Lins Patriota

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Arvo Pärt is an Estonian composer who started his musical career under the influence of twelve-tone music and dodecaphonism. From 1968 to 1976, he isolated himself to search for a new path as a composer. In this period, he converted to Russian orthodoxy and changed his composing to tintinnabuli, a musical technique combining triadic chords with simple melodies. The recent analysis of Pärt’s output demonstrates that mathematics remained an influence after the invention of tintinnabuli. The present discussion deals with the relationship between math and religion in his work Out of the Depths (1980), proposing a musical-text approach and examining the minimum elements of the piece, such as motives and sub-phrases, which is the main focus of this work, considering text patterns and the role of the organ, which also uses the tintinnabuli system. The analysis of these elements demonstrates that Pärt uses math as a formal element, and the composer combines musical parameters to execute a personal and innovative interpretation of the text.

Keywords: Arvo Pärt, Out of the Depths, math, religion, analysis

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Authors: Bijan Nahavandi, Navid Jafarinejad, Somayeh Mehrafzad

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Strategy maps represent the way of value creation in in each organization. Nowadays, implementation of strategy is the main concern for all organizations. Strategy map establishment is the start-up point of strategy implementation and this shows the critical importance of this concept. After some years past since emergence of strategy map, there are some shortcomings in its methodology that frequently quoted by many of researchers. One of these shortcomings is the shortage of a mechanism for refinement of objectives candidate for entrance to map. Organizations in practice have obsession and avidity to determine more number of objectives in strategy map. This study wants to represent a step by step approach to help obviate this problem using quality function deployment (QFD) as a helpful tool and fuzzy screening method. Finally, represented approach applies in a practical case and conclusions have been explained.

Keywords: balanced scorecard, fuzzy screening, house of strategic objectives (HoSO), quality function deployment, strategy map

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Authors: Husham Bayazed

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Immune responses following surgical trauma play a pivotal role in predicting postoperative outcomes from healing and recovery to postoperative complications. Postoperative complications, including infections and protracted recovery, occur in a significant number of about 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on the healthcare system in any community. The accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain major clinical provocations. Recent Findings: Recent studies are focusing on immune dysregulation mechanisms that occur in response to surgical trauma as a key determinant of postoperative complications. Antecedent studies mainly were plunging into the detection of inflammatory plasma markers, which facilitate in providing important clues regarding their pathogenesis. However, recent Single-cell technologies, such as mass cytometry or single-cell RNA sequencing, have markedly enhanced our ability to understand the immunological basis of postoperative immunological trauma complications and to identify their prognostic biological signatures. Summary: The advent of proteomic technologies has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers and providing patients and surgeons with information to improve surgical outcomes. However, more studies are required to accurately predict the risk of postoperative complications in individual patients.

Keywords: immune dysregulation, postoperative complications, surgical trauma, flow cytometry

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Authors: Shao-Di Feng, Von-Wun Soo

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To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: Ni̇sa Yeni̇kalayci, Türkan Aybi̇ke Akarca

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The ability of correlation the number and space relations, one of the basic scientific process skills, is being used in the transformation of a two-dimensional object into a three-dimensional image or in the expression of symmetry axes of the object. With this research, it is aimed to determine the ability of science students to establish number and space relations. The research was carried out with a total of 90 students studying in the first semester of the Science Education program of a state university located in the Turkey’s Black Sea Region in the fall semester of 2017-2018 academic year. An ‘Integrative Perception Test (IPT)’ was designed by the researchers to collect the data. Within the scope of IPT, the courses and workbooks specific to the field of science were scanned and the ones without symmetrical structure from the visual items belonging to the ‘Physics - Chemistry – Biology’ sub-fields were selected and listed. During the application, it was expected that students would imagine and draw images of the missing half of the visual items that were given incomplete in the first place. The data obtained from the test in which there are 30 images or pictures in total (f Physics = 10, f Chemistry = 10, f Biology = 10) were analyzed descriptively based on the drawings created by the students as ‘complete (2 points), incomplete/wrong (1 point), empty (0 point)’. For the teaching of new concepts in small aged groups, images or pictures showing symmetrical structures and similar applications can also be used.

Keywords: integrative perception, number and space relations, science education, scientific process skills

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Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg

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In composite manufacturing, the fabrication of tooling and tooling maintenance contributes to a large portion of the total cost. However, as the applications of composite materials continue to increase, there is also a growing demand for more tooling. The demand for more tooling places heavy emphasis on the industry’s ability to fabricate high quality tools while maintaining the tool’s cost effectiveness. One of the popular techniques of tool fabrication currently being developed utilizes additive manufacturing technology known as 3D printing. The popularity of 3D printing is due to 3D printing’s ability to maintain low material waste, low cost, and quick fabrication time. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite mold. A steel valve cover from an aircraft reciprocating engine was modeled utilizing 3D scanning and computer-aided design (CAD) to create a 3D printed composite mold. The mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The carbon fiber valve covers were evaluated for dimensional accuracy and quality while the 3D printed composite mold was evaluated for durability and dimensional stability. The data collected from this study provided valuable information in the understanding of 3D printed composite molds, potential improvements for the molds, and considerations for future tooling design.

Keywords: additive manufacturing, carbon fiber, composite tooling, molds

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Authors: Lauren Kathryn Stretch

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A study was conducted in the underprivileged setting of Nelson Mandela Bay, South Africa in order to monitor the progress of learners whose teachers receive training through the Early Inspiration Training Programme. Through tracking children’s growth & development, the effectiveness of the practitioner-training programme, which focuses on empowering women from underprivileged communities in South Africa, was analyzed. The aim was to identify impact & reach and to assess the effectiveness of this intervention programme through identifying impact on children’s growth and development. A Pre- and Post-Test was administered on about 850 young children in Pre-Grade R and Grade R classes in order to understand children’s ability level & the growth that would be evident as a result of effective teacher training. A pre-test evaluated the level of each child’s abilities, including physical-motor development, language, and speech development, cognitive development including visual perceptual skills, social-emotional development & play development. This was followed by a random selection of the classes of children into experimental and control groups. The experimental group’s teachers (practitioners) received 8-months of training & intervention, as well as mentorship & support. After the 8-month training programme, children from the experimental & control groups underwent post-assessment. The results indicate that the impact of effective practitioner training and enhancing a deep understanding of stimulation on young children, that this understanding is implemented in the classroom, highlighting the areas of growth & development in the children whose teachers received additional training & support, as compared to those who did not receive additional training. Monitoring & Evaluation systems not only track children’s ability levels, but also have a core focus on reporting systems, mentorship and providing ongoing support. As a result of the study, an Online Application (for Apple or Android Devices) was developed which is used to track children’s growth via age-appropriate assessments. The data is then statistically analysed to provide direction for relevant & impactful intervention. The App also focuses on effective reporting strategies, structures, and implementation to support organizations working with young children & maximize on outcomes.

Keywords: early childhood development, developmental child assessments, online application, monitoring and evaluating online

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Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

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We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

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Authors: Dorota Habrat

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In Polish law, the idea of the introduction of corporate responsibility for crimes is becoming more popular and creates a lot of questions. The need to introduce into the Polish legal system liability of corporate (collective entities) has resulted, among others, from the Polish Republic's international commitments, in particular related to membership in the European Union. The Act of 28 October 2002 on the liability of collective entities for acts prohibited under penalty is one of the example of adaptation of Polish law to Community law. Introduction to Polish law a criminal nature liability of corporations (legal persons) has resulted in a lot of controversy and lack of acceptance from both the scientific community as well as the judiciary. The responsibility of collective entities under the Act has a criminal nature. The main question concerns the ability of the collective entity to be brought to guilt under criminal law sense. Polish criminal law knows only the responsibility of individual persons. So far, guilt as a personal feature of action, based on the ability of the offender to feel in his psyche, could be considered only in relation to the individual person, while the said Act destroyed this conviction. Guilt of collective entity must be proven under at least one of the three possible forms: the guilt in the selection or supervision and so called organizational guilt. The next question is how the principle of proportionality in relation to criminal measures in response of collective entities should be considered. It should be remembered that the legal subjectivity of collective entities, including their rights and freedoms, is an emanation of the rights and freedoms of individual persons which create collective entities and through these entities implement their rights and freedoms. The adopted Act largely reflects the international legal regulations but also contains the unknown and original legislative solutions.

Keywords: criminal corporate responsibility, Polish criminal law, legislative solutions, Act of 28 October 2002

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Authors: Sol Girouard, Zona Kostic

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A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

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Authors: Mohammad Saeed Bahramy

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Transition metal dichalcogenides have experienced a resurgence of interest in the past few years owing to their rich properties, ranging from metals and superconductors to strongly spin-orbit-coupled semiconductors and charge-density-wave systems. In all these cases, the transition metal d-electrons mainly determine the ground state properties. This presentation focuses on the chalcogen-derived states. Combining density-functional theory calculations with spin- and angle-resolved photoemission, it is shown that these states generically host a coexistence of type I and type II three-dimensional bulk Dirac fermions as well as ladders of topological surface states and surface resonances. It will be discussed how these naturally arise within a single p-orbital manifold as a general consequence of a trigonal crystal field, and as such can be expected across many compounds. Our finding opens a new route to design topological materials with advanced functionalities.

Keywords: topology, electronic structure, Dirac semimetals, transition metal dichalcogenides

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Authors: Abderrahmane Khiat, Moussa Benaissa

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Due to the increasing number of sources of information available on the web and their distribution and heterogeneity, ontology alignment became a very important and inevitable problem to ensure semantic interoperability. Instance-based ontology alignment is based on the comparison of the extensions of concepts; and represents a very promising technique to find semantic correspondences between entities of different ontologies. In practice, two situations may arise: ontologies that share many common instances and ontologies that share few or do not share common instances. In this paper, we describe an approach to manage the latter case. This approach exploits the reasoning on ontologies in order to create a corpus of common instances. We show that it is theoretically powerful because it is based on description logics and very useful in practice. We present the experimental results obtained by running our approach on ontologies of OAEI 2012 benchmark test. The results show the performance of our approach.

Keywords: description logic inference, instance-based ontology alignment, semantic interoperability, semantic web

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Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

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The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: UWB, propagation, LOS, NLOS, identification

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Authors: Samad Lotfollahzadeh

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Escherichia coli (E.coli) is the most isolated bacteria from blood circulation of septicemic calves. Given the prevalence of septicemia in animals and its economic importance in veterinary practice, better understanding of changes in clinical signs following disease, may contribute to early detection of the disorder. The present study has been carried out to detect changes of clinical signs in induced sepsis in calves with E.coli. Colisepticemia has been induced in 10 twenty-day old healthy Holstein- Frisian calves with intravenous injection of 1.5 X 109 colony forming units (cfu) of O111: H8 strain of E.coli. Clinical signs including rectal temperature, heart rate, respiratory rate, shock, appetite, sucking reflex, feces consistency, general behavior, dehydration and standing ability were recorded in experimental calves during 24 hours after induction of colisepticemia. Blood culture was also carried out from calves four times during the experiment. ANOVA with repeated measure is used to see changes of calves’ clinical signs to experimental colisepticemia, and values of P≤ 0.05 was considered statistically significant. Mean values of rectal temperature and heart rate as well as median values of respiratory rate, appetite, suckling reflex, standing ability and feces consistency of experimental calves increased significantly during the study (P<0.05). In the present study, median value of shock score was not significantly increased in experimental calves (P> 0.05). The results of present study showed that total score of clinical signs in calves with experimental colisepticemia increased significantly, although the score of some clinical signs such as shock did not change significantly.

Keywords: calves, clinical signs scoring, E. coli O111:H8, experimental colisepticemia

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Authors: Guoliang Lu, Changhou Lu, Xueyong Li

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In action recognition, previous studies have demonstrated the effectiveness of using multiple features to improve the recognition performance. We focus on two practical issues: i) most studies use a direct way of concatenating/accumulating multi features to evaluate the similarity between two actions. This way could be too strong since each kind of feature can include different dimensions, quantities, etc; ii) in many studies, the employed classification methods lack of a flexible and effective mechanism to add new feature(s) into classification. In this paper, we explore an unified scheme based on recently-proposed multi-dimensional dynamic time warping (MD-DTW). Experiments demonstrated the scheme's effectiveness of combining multi-feature and the flexibility of adding new feature(s) to increase the recognition performance. In addition, the explored scheme also provides us an open architecture for using new advanced classification methods in the future to enhance action recognition.

Keywords: action recognition, multi features, dynamic time warping, feature combination

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Claudius Peter Van Wyk

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Given the increasingly manifest phenomena, as described in complexity theory, of volatility, uncertainty, complexity and ambiguity (VUCA), Taleb's notion of 'antifragility, has a significant contribution to make to positive psychology applied to wellbeing. Antifragility is argued to be fundamentally different from the concepts of resiliency; as the ability to recover from failure, and robustness; as the ability to resist failure. Rather it describes the capacity to reorganise in the face of stress in such a way as to cope more effectively with systemic challenges. The concept, which has been applied in disciplines ranging from physics, molecular biology, planning, engineering, and computer science, can now be considered for its application in individual human and social wellbeing. There are strong correlations to Antonovsky's model of 'salutogenesis' in which an attitude and competencies are developed of transforming burdening factors into greater resourcefulness. We demonstrate, from the perspective of neuroscience, how technology measuring nervous system coherence can be coupled to acquired psychodynamic approaches to not only identify contextual stressors, utilise biofeedback instruments for facilitating greater coherence, but apply these insights to specific life stressors that compromise well-being. Employing an on-going case study with BMW South Africa, the neurological mapping is demonstrated together with 'reframing' and emotional anchoring techniques from neurolinguistic programming. The argument is contextualised in the discipline of psychoneuroimmunology which describes the stress pathways from the CNS and endocrine systems and their impact on immune function and the capacity to restore homeostasis.

Keywords: antifragility, complexity, neuroscience, psychoneuroimmunology, salutogenesis, volatility

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Authors: Matthew Fleet, Savannah Elliott

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Background: This study investigates the use of teaching and learning to meet the needs of deaf children in the UK PE curriculum. Research has illustrated that deaf students in mainstream schools do not receive sufficient support from teachers in lessons. This research examines the impact of different types of hearing loss and its implications within Physical Education (PE) in secondary schools. Purpose: The purpose of this study is to highlight challenges PE teachers face and make recommendations for more inclusive learning environments for deaf students. The aims and objectives of this research are: to critically analyse the current situation for deaf students accessing the PE curriculum, by identifying barriers deaf students face; to identify the challenges for PE teachers in providing appropriate support for deaf students; to provide recommendations for deaf awareness training, to enhance PE teachers’ understanding and knowledge. Method: Semi-structured interviews collected data from both PE teachers and deaf students, to examine: the support available and coping mechanisms deaf students use when they do not receive support; strategies PE teachers use to provide support for deaf students; areas for improvement and potential strategies PE teachers can apply to their practice. Results & Conclusion: The findings from the study concluded that PE teachers were inconsistent in providing appropriate support for deaf students in PE lessons. Evidence illustrated that PE teachers had limited exposure to deaf awareness training. This impacted on their ability to support deaf students effectively. Communication was a frequent barrier for deaf students, affecting their ability to retain and learn information. Also, the use of assistive technology was found to be compromised in practical PE lessons.

Keywords: physical education, deaf, inclusion, education

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Authors: Perumal Siddhuraju, Arumugam Abirami, Gunasekaran Nagarani, Marimuthu Sangeethapriya

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Aqueous ethanol and aqueous acetone extracts of Moringa oleifera (outer pericarp of immature fruit and flower) and Sesbania grandiflora white variety (flower and leaf) were examined for radical scavenging capacities and antioxidant activities. Ethanol extract of S. grandiflora (flower and leaf) and acetone extract of M. oleifera (outer pericarp of immature fruit and flower) contained relatively higher levels of total dietary phenolics than the other extracts. The antioxidant potential of the extracts were assessed by employing different in vitro assays such as reducing power assay, DPPH˙, ABTS˙+ and ˙OH radical scavenging capacities, antihemolytic assay by hydrogen peroxide induced method and metal chelating ability. Though all the extracts exhibited dose dependent reducing power activity, acetone extract of all the samples were found to have more hydrogen donating ability in DPPH˙ (2.3% - 65.03%) and hydroxyl radical scavenging systems (21.6% - 77.4%) than the ethanol extracts. The potential of multiple antioxidant activity was evident as it possessed antihemolytic activity (43.2 % to 68.0 %) and metal ion chelating potency (45.16 - 104.26 mg EDTA/g sample). The result indicate that acetone extract of M. oleifera (OPIF and flower) and S. grandiflora (flower and leaf) endowed with polyphenols, could be utilized as natural antioxidants/nutraceuticals.

Keywords: antioxidant activity, Moringa oleifera, polyphenolics, Sesbania grandiflora, underutilized vegetables

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Authors: M. P. Leroux, C. Coulombe

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Projects are popular vehicles through which international aid is delivered in developing countries. To achieve their objectives, many northern organizations develop projects with local partner organizations in the developing countries through technical assistance projects. International aid and international development projects precisely have long been criticized for poor results although billions are spent every year. Little empirical research in the field of project management has the focus on knowledge transfer in international development context. This paper focuses particularly on personal dimensions of international assignees participating in project within local team members in the host country. We propose to explore the possible links with a human resource management perspective in order to shed light on the less research problematic of knowledge transfer in development cooperation projects. The process leading to capacity building being far complex, involving multiple dimensions and far from being linear, we propose here to assess if traditional research on expatriate in multinational corporations pertain to the field of project management in developing countries. The following question is addressed: in the context of international development project cooperation, what personal determinants should the selection process focus when looking to fill a technical assistance position in a developing country? To answer that question, we first reviewed the literature on expatriate in the context of inter organizational knowledge transfer. Second, we proposed a theoretical framework combining perspectives of development studies and management to explore if parallels can be draw between traditional international assignment and technical assistance project assignment in developing countries. We conducted an exploratory study using case studies from technical assistance initiatives led in Haiti, a country in Central America. Data were collected from multiple sources following qualitative study research methods. Direct observations in the field were allowed by local leaders of six organization; individual interviews with present and past international assignees, individual interview with local team members, and focus groups were organized in order to triangulate information collected. Contrary from empirical research on knowledge transfer in multinational corporations, results tend to show that technical expertise rank well behind many others characteristics. Results tend to show the importance of soft skills, as a prerequisite to succeed in projects where local team have to collaborate. More importantly, international assignees who were talking knowledge sharing instead of knowledge transfer seemed to feel more satisfied at the end of their mandate than the others. Reciprocally, local team members who perceived to have participated in a project with an expat looking to share instead of aiming to transfer knowledge seemed to describe the results of project in more positive terms than the others. Results obtained from this exploratory study open the way for a promising research agenda in the field of project management. It emphasises the urgent need to achieve a better understanding on the complex set of soft skills project managers or project chiefs would benefit to develop, in particular, the ability to absorb knowledge and the willingness to share one’s knowledge.

Keywords: international assignee, international project cooperation, knowledge transfer, soft skills

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Authors: Edwina Luck, Rory Mulcahy

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This paper explores a distinctive perspective of resources which are integrated to co-destroy transformative value in sport. Combining previously published transformative service research and sports literature with data from twenty in-depth interviews with elite and Olympic rowers, our study uncovers the co-destructive resources of ‘interpersonal misbehavior’ and ‘sport misbehavior’. We also identified transformative value in sport is multi-dimensional, encompassing important benefits that support well-being. This research has important implications for transformative sport service research, recommending the need to embrace a transformative service lens to value, a more holistic understanding of co-destruction, and the need to utilise multi-dimensional frameworks to ensure greater insights into sport and sports services and their impact on sportsperson’s well-being. Gaining this understanding will encourage sport managers, sporting bodies to justify resources that they integrate based upon their impact on co-destruction of value.

Keywords: elite sports, sport misbehavior, transformative sport service research, value co-destruction

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Authors: Nick Weir, Robert Stevens, Alan Hargreaves, Martin McGinnity, Chris Tinsley

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Hydrophobic materials have previously demonstrated the ability to elevate cell-cell interactions and promote the formation of neural networks whilst aligned nanofibers demonstrate the ability to induce extensive neurite outgrowth in an aligned manner. Hydrophobic materials typically elicit an immune response upon implantation and thus materials used for implantation are typically hydrophilic. Poly-L-lactic acid (PLLA) is a hydrophobic, non-immunogenic, FDA approved material that can be electrospun to form aligned nanofibers. Primary rat cortical neurons cultured for 10 days on aligned PLLA nanofibers formed 3D cell clusters, approximately 800 microns in diameter. Neurites that extended from these clusters were highly aligned due to the alignment of the nanofibers they were cultured upon and fasciculation was also evident. Plasma treatment of the PLLA nanofibers prior to seeding of cells significantly reduced the hydrophobicity and abolished the cluster formation and neurite fasciculation, whilst reducing the extent and directionality of neurite outgrowth; it is proposed that hydrophobicity induces the changes to cellular behaviors. Aligned PLLA nanofibers induced the formation of a structure that mimics the grey-white matter compartmentalization that is observed in vivo and thus represents a step forward in generating organoids or biomaterial-based implants. Upon implantation into the brain, the biomaterial architectures described here may provide a useful platform for both brain repair and brain remodeling initiatives.

Keywords: hydrophobicity, nanofibers, neurite fasciculation, neurite outgrowth, PLLA

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Authors: Liu Lin Xin

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With the increasing complexity of systems, log parsing and anomaly detection have become crucial for maintaining system stability. However, traditional methods often struggle with adaptability and accuracy, especially when dealing with rapidly evolving log content and unfamiliar domains. To address these challenges, this paper proposes approach that integrates Retrieval Augmented Generation (RAG) technology with Prompt Engineering for Large Language Models, applied specifically in LogPrompt. This approach enables dynamic log parsing and intelligent anomaly detection by combining real-time information retrieval with prompt optimization. The proposed method significantly enhances the adaptability of log analysis and improves the interpretability of results. Experimental results on several public datasets demonstrate the method's superior performance, particularly in scenarios lacking training data, where it significantly outperforms traditional methods. This paper introduces a novel technical pathway for log parsing and anomaly detection, showcasing the substantial theoretical value and practical potential.

Keywords: log parsing, anomaly detection, RAG, prompt engineering, LLMs

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Authors: Kingkan Chumjamras

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There are permanent and temporary tracheostomies, and in a permanent tracheostomy, care giver are important persons to know and be able to care for the tracheostomy patient. The objective of this quasi-experimental study was to evaluate outcomes of educating care giver in tracheostomy wound care for discharge planning of tracheostomy patients. The subjects of the study were relatives who directly cared for tracheostomy patients. Thirty subjects were selected according to specified criteria. The research instruments consisted of practice guidelines, manual for relatives in caring for the tracheostomy wound, an assisted model with a tracheostomy wound, a test, an observation form, and a patient’s relative satisfaction questionnaire. The instrument validity was tested by three experts, and the questionnaire reliability was tested with Cronbach’s alpha, and the reliability coefficient was 0.83; the data were analyzed using descriptive statistics, and paired t-test. The results of the study on educating relatives in tracheostomy wound care for discharge planning of tracheostomy patients revealed that the score for knowledge and ability in caring for the tracheostomy wound before receiving the education was at a low level (M= 19.23, SD= 1.57) compared with the very high score (M= 36.40, SD= 19.23) after receiving the education. The difference was statistically significant (p < .05), and relatives’ satisfaction was at a high level (80 percent). Knowledge and ability in caring for tracheostomy patients among patients’ relatives could cause tracheostomy wound complications for tracheostomy patients. One way to control such complications and returns to hospital from infection, in addition to care by the health care team, is educating relatives in tracheostomy wound care for discharge planning of tracheostomy patients.

Keywords: outcomes, educating, care giver, Tracheostomy Wound Care, discharge planning

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Authors: Cristina-Maria Păcurar

Abstract:

The paper presents an original Python-based application that outlines the advantages of combining some elementary notions of mathematics with the study of a programming language. The application support refers to some of the first lessons of analytic geometry, meaning conics and quadrics and their reduction to a standard form, as well as some related notions. The chosen programming language is Python, not only for its closer to an everyday language syntax – and therefore, enhanced readability – but also for its highly reusable code, which is of utmost importance for a mathematician that is accustomed to exploit already known and used problems to solve new ones. The purpose of this paper is, on one hand, to support the idea that one of the most appropriate means to initiate one into programming is throughout mathematics, and reciprocal, one of the most facile and handy ways to assimilate some basic knowledge in the study of mathematics is to apply them in a personal project. On the other hand, besides being a mean of learning both programming and analytic geometry, the application subject to this paper is itself a useful tool for it can be seen as an independent original Python package for analytic geometry.

Keywords: analytic geometry, conics, python, quadrics

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Authors: Abdulrahman Abdulhamid Arabo, Raji Arabi Bamanga, Mujiburrahman Fadilu, Musa Abubakar, Fatima Abdullahi Shehu, Hafeez Muhammad Yakasai, Nasiru Abdullahi

Abstract:

The aim of this study was to isolate and identify biosurfactant-producing and diesel alkanes degrading bacteria. For this reason, bacteria isolated from the diesel-contaminated site were screened for their potential to produce biosurfactants and degrade diesel alkanes. Primary selection of diesel degraders was carried out by using the conventional enrichment culture technique, where 12 bacterial strains were isolated based on their ability to grow on minimal media supplemented with diesel as the sole carbon source, which was followed by qualitative screening methods for potential biosurfactant production. Isolate B11 was the only candidate that showed positive signs for drop collapse, foaming, hemolytic test, oil displacement of more than 22 ± 0.05 mm, and emulsification (E24) of 14 ± 0.30%. The effect of various culture parameters (incubation time, diesel concentration, nitrogen source, pH and temperature) on the biodegradation of diesel was evaluated. The optimum incubation time was confirmed to be 120 days for isolate B11, and the optimum PH was confirmed as 8.0 for the isolate; similarly, the optimum temperature was confirmed as 35oC. In addition, diesel oil was used as the sole carbon source for the isolates. The favorable diesel concentration was 12.5 % (v/v) for the isolate. The isolate has shown degradative ability towards Tridecane (C13), dodecane, 2, 6, 10-trimethyl- (C15), Tetradecane (C14), 2,6,10-Trimethyltridecane (C16), Pentadecane (C15). It degraded between 0.27% - 9.65% of individual diesel oil alkanes. The strain has exhibited the potential of degrading diesel oil n-alkanes and was identified as Alcaligenes species strain B11 (MZ027604) using the 16S rRNA. Sequencing.

Keywords: diesel oil, biosurfactant, Alcaligenes sp, biodegradation

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Authors: Marie Guittonny-LarchevêQue

Abstract:

In boreal Canada, industrial activities such as forestry, peat extraction and metal mines often occur nearby. At closure, mine waste storage facilities have to be reclaimed. On tailings storage facilities, tree plantations can achieve rapid restoration of forested landscapes. However, trees poorly grow in mine tailings and organic amendments like peat are required to improve tailings’ structure and nutrients. Canada is a well-known producer of horticultural quality peat, but some lower quality peats coming from areas adjacent to the reclaimed mines could allow successful revegetation. In particular, hemic peat coming from the bottom of peat-bogs is more decomposed than fibric peat and is less valued for horticulture. Moreover, forest peat is sometimes excavated and piled by the forest industry after cuttings to stimulate tree regeneration on the exposed mineral soil. The objective of this project was to compare the ability of peats of differing quality and origin to improve tailings structure, nutrients and tree development. A greenhouse experiment was conducted along one growing season in 2016 with a complete randomized block design combining 8 repetitions (blocks) x 2 tree species (Populus tremuloides and Pinus banksiana) x 6 substrates (tailings, commercial horticultural peat, and mixtures of tailings with commercial peat, forest peat, local fibric peat, or local hemic peat) x 2 fertilization levels (with or without mineral fertilization). The used tailings came from a gold mine and were low in sulfur and trace metals. The commercial peat had a slightly acidic pH (around 6) while other peats had a clearly acidic pH (around 3). However, mixing peat with slightly alkaline tailings resulted in a pH close to 7 whatever the tested peats. The macroporosity of mixtures was intermediate between the low values of tailings (4%) and the high values of commercial peat alone (34%). Seedling survival was lower on tailings for poplar compared to all other treatments, with or without fertilization. Survival and growth were similar among all treatments for pine. Fertilization had no impact on the maximal height and diameter of poplar seedlings but changed the relative performance of the substrates. When not fertilized, poplar seedlings grown in commercial peat were the highest and largest, and the smallest and slenderest in tailings, with intermediate values in mixtures. When fertilized, poplar seedlings grown in commercial peat were smaller and slender compared to all other substrates. However for this species, foliar, shoot, and root biomass production was the greatest in commercial peat and the lowest in tailings compared to all mixtures, whether fertilized or not. The mixture with local fibric peat provided the seedlings with the lowest foliar N concentrations compared to all other substrates whatever the species or the fertilization treatment. At the short-term, the performance of all the tested peats were close when mixed to tailings, showing that peats of lower quality could be valorized instead of using horticultural peat. These results demonstrate that intersectorial synergies in accordance with the principles of circular economy may be developed in boreal Canada between local industries around the reclamation of mine waste dumps.

Keywords: boreal trees, mine spoil, mine revegetation, intersectorial synergies

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

Abstract:

In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

Procedia PDF Downloads 248