Search results for: silver clusters

Authors: Min Han, Di Wu, Lin Yuan, Fei Liu

Abstract:

Mechanical sensors have undergone a continuous evolution and have become an important part of many industries, ranging from manufacturing to process, chemicals, machinery, health-care, environmental monitoring, automotive, avionics, and household appliances. Concurrently, the microelectronics and microfabrication technology have provided us with the means of producing mechanical microsensors characterized by high sensitivity, small size, integrated electronics, on board calibration, and low cost. Here we report a new kind of mechanical sensors based on the quantum transport process of electrons in the closely spaced nanoparticle films covering a flexible polymer sheet. The nanoparticle films were fabricated by gas phase depositing of preformed metal nanoparticles with a controlled coverage on the electrodes. To amplify the conductance of the nanoparticle array, we fabricated silver interdigital electrodes on polyethylene terephthalate(PET) by mask evaporation deposition. The gaps of the electrodes ranged from 3 to 30μm. Metal nanoparticles were generated from a magnetron plasma gas aggregation cluster source and deposited on the interdigital electrodes. Closely spaced nanoparticle arrays with different coverage could be gained through real-time monitoring the conductance. In the film coulomb blockade and quantum, tunneling/hopping dominate the electronic conduction mechanism. The basic principle of the mechanical sensors relies on the mechanical deformation of the fabricated devices which are translated into electrical signals. Several kinds of sensing devices have been explored. As a strain sensor, the device showed a high sensitivity as well as a very wide dynamic range. A gauge factor as large as 100 or more was demonstrated, which can be at least one order of magnitude higher than that of the conventional metal foil gauges or even better than that of the semiconductor-based gauges with a workable maximum applied strain beyond 3%. And the strain sensors have a workable maximum applied strain larger than 3%. They provide the potential to be a new generation of strain sensors with performance superior to that of the currently existing strain sensors including metallic strain gauges and semiconductor strain gauges. When integrated into a pressure gauge, the devices demonstrated the ability to measure tiny pressure change as small as 20Pa near the atmospheric pressure. Quantitative vibration measurements were realized on a free-standing cantilever structure fabricated with closely-spaced nanoparticle array sensing element. What is more, the mechanical sensor elements can be easily scaled down, which is feasible for MEMS and NEMS applications.

Keywords: gas phase deposition, mechanical sensors, metallic nanoparticle arrays, quantum conductance

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Authors: Fekadu Gadissa, Kassahun Tesfaye, Kifle Dagne, Mulatu Geleta

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‘Ethiopian dinich’ also called ‘Ethiopian potato’ is one of the economically important ‘orphan’ edible tuber crops indigenous to Ethiopia. We evaluated the morphological and agronomic traits performances of 174 samples from Ethiopia at multiple locations using 12 qualitative and 16 quantitative traits, recorded at the correct growth stages. We observed several morphotypes and phenotypic variations for qualitative traits along with a wide range of mean performance values for all quantitative traits. Analysis of variance for each quantitative trait showed a highly significant (p<0.001) variation among the collections with eventually non-significant variation for environment-traits interaction for all but flower length. A comparatively high phenotypic and genotypic coefficient of variation was observed for plant height, days to flower initiation, days to 50% flowering and tuber number per hill. Moreover, the variability and coefficients of variation due to genotype-environment interaction was nearly zero for all the traits except flower length. High genotypic coefficients of variation coupled with a high estimate of broad sense heritability and high genetic advance as a percent of collection mean were obtained for tuber weight per hill, number of primary branches per plant, tuber number per hill and number of plants per hill. Association of tuber yield per hectare of land showed a large magnitude of positive phenotypic and genotypic correlation with those traits. Principal components analysis revealed 76% of the total variation for the first six principal axes with high factor loadings again from tuber number per hill, number of primary branches per plant and tuber weight. The collections were grouped into four clusters with the weak region (zone) of origin based pattern. In general, there is high genetic-based variability for ‘Ethiopian dinich’ improvement and conservation. DNA based markers are recommended for further genetic diversity estimation for use in breeding and conservation.

Keywords: agro-morphological traits, Ethiopian dinich, genetic diversity, variance components

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Authors: Yahoel Van Essen, Gordon Ho, Brett Russell, Hans-Georg Worms, Xiao Lin Long, Edward David Cooper, Avner Bachar

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Weeds reduce farm and forest productivity, invade crops, smother pastures and some can harm livestock. Farmers need to spend a significant amount of money to control weeds by means of biological, chemical, cultural, and physical methods. To solve the global agricultural labor shortage and remove poisonous chemicals, a fully autonomous, eco-friendly, and sustainable weeding technology is developed. This takes the form of a weeding robot, ‘Roboweeder’. Roboweeder includes a four-wheel-drive self-driving vehicle, a 4-DOF robotic arm which is mounted on top of the vehicle, an electromagnetic wave generator (magnetron) which is mounted on the “wrist” of the robotic arm, 48V battery packs, and a control/communication system. Cameras are mounted on the front and two sides of the vehicle. Using image processing and recognition, distinguish types of weeds are detected before being eliminated. The electromagnetic wave technology is applied to heat the individual weeds and clusters dielectrically causing them to wilt and die. The 4-DOF robotic arm was modeled mathematically based on its structure/mechanics, each joint’s load, brushless DC motor and worm gear’ characteristics, forward kinematics, and inverse kinematics. The Proportional-Integral-Differential control algorithm is used to control the robotic arm’s motion to ensure the waveguide aperture pointing to the detected weeds. GPS and machine vision are used to traverse the farm and avoid obstacles without the need of supervision. A Roboweeder prototype has been built. Multiple test trials show that Roboweeder is able to detect, point, and kill the pre-defined weeds successfully although further improvements are needed, such as reducing the “weeds killing” time and developing a new waveguide with a smaller waveguide aperture to avoid killing crops surrounded. This technology changes the tedious, time consuming and expensive weeding processes, and allows farmers to grow more, go organic, and eliminate operational headaches. A patent of this technology is pending.

Keywords: autonomous navigation, machine vision, precision heating, sustainable and eco-friendly

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Authors: Masome Moeni, Roya Abedizadeh, Elham Aram, Hamid Sadeghi-Abandansari, Davood Sabour, Robert Menzel, Ali Hassanpour

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Significant number of studies and preclinical research in formulation of cancer nano-pharmaceutics have led to an improvement in cancer care. Nonetheless, the antineoplastic agents have ‘failed to live up to its promise’ since their clinical performance is moderately low. For almost ninety years, iron oxide nanoparticles (IONPS) have managed to keep its reputation in clinical application due to their low toxicity, versatility and multi-modal capabilities. Drug Administration approved utilization of IONPs for diagnosis of cancer as contrast media in magnetic resonance imaging, as heat mediator in magnetic hyperthermia and for the treatment of iron deficiency. Furthermore, IONPs have high drug-loading capacity, which makes them good candidates as therapeutic agent transporters. There are yet challenges to overcome for successful clinical application of IONPs, including stability of drug and poor delivery, which might lead to (i) drug resistance, (ii) shorter blood circulation time, and (iii) rapid elimination and adverse side effects from the system. In this study, highly stable and super paramagnetic IONPs were prepared for efficient and targeted drug delivery in cancer treatment. The synthesis procedure was briefly involved the production of IONPs via co-precipitation followed by coating with tetraethyl orthosilicate and 3-aminopropylethoxysilane and grafting with folic acid for stability targeted purposes and controlled drug release. Physiochemical and morphological properties of modified IONPs were characterised using different analytical techniques. The resultant IONPs exhibited clusters of 10 nm spherical shape crystals with less than 100 nm size suitable for drug delivery. The functionalized IONP showed mesoporous features, high stability, dispersibility and crystallinity. Subsequently, the functionalized IONPs were successfully loaded with oxaliplatin, a chemotherapeutic agent, for a controlled drug release in an actively targeting cancer cells. FT-IR observations confirmed presence of oxaliplatin functional groups, while ICP-MS results verified the drug loading was ~ 1.3%.

Keywords: cancer treatment, chemotherapeutic agent, drug delivery, iron oxide, multi-functional nanoparticle

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Authors: Debanjan Dey, Tamal Banerjee, Kaustubha Mohanty

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Global scalar properties are calculated based on higher occupied molecular orbital (HOMO) and lower unoccupied molecular orbital (LUMO) energy to study the interaction between ionic liquids with Bituminous and Anthracite coal using density function theory (DFT) method. B3LYP/6-31G* calculation predicts HOMO-LUMO energy gap, electronegativity, global hardness, global softness, chemical potential and global softness for individual compounds with their clusters. HOMO-LUMO interaction, electron delocalization, electron donating and accepting is the main source of attraction between individual compounds with their complexes. Cation used in this study: 1-butyl-1-methylpyrrolidinium [BMPYR], 1-methyl -3-propylimmidazolium [MPIM], Tributylmethylammonium [TMA] and Tributylmethylphosphonium [MTBP] with the combination of anion: bis(trifluromethylsulfonyl)imide [Tf2N], methyl carbonate [CH3CO3], dicyanamide [N(CN)2] and methylsulfate [MESO4]. Basically three-tier approach comprising HOMO/LUMO energy, Scalar quantity and infinite dilution activity coefficient (IDAC) by sigma profile generation with COSMO-RS (Conductor like screening model for real solvent) model was chosen for simultaneous interaction. [BMPYR]CH3CO3] (1-butyl-1-methylpyrrolidinium methyl carbonate) and [MPIM][CH3CO3] (1-methyl -3-propylimmidazolium methyl carbonate ) are the best effective ILs on the basis of HOMO-LUMO band gap for Anthracite and Bituminous coal respectively and the corresponding band gap is 0.10137 hartree for Anthracite coal and 0.12485 hartree for Bituminous coal. Further ionic liquids are screened quantitatively with all the scalar parameters and got the same result based on CH-π interaction which is found for HOMO-LUMO gap. To check our findings IDAC were predicted using quantum chemical based COSMO-RS methodology which gave the same trend as observed our scalar quantity calculation. Thereafter a qualitative measurement is doing by sigma profile analysis which gives complementary behavior between IL and coal that means highly miscible with each other.

Keywords: coal-ionic liquids cluster, COSMO-RS, DFT method, HOMO-LUMO interaction

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Authors: Ahmet Ozcan, Onder Alparslan, Anil Sezgin, Omer Cetin

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The use of unmanned systems for different purposes has become very popular over the past decade. Expectations from these systems have also shown an incredible increase in this parallel. But meeting the demands of the tasks are often not possible with the usage of a single unmanned vehicle in a mission, so it is necessary to use multiple autonomous vehicles with different abilities together in coordination. Therefore the usage of the same type of vehicles together as a swarm is helped especially to satisfy the time constraints of the missions effectively. In other words, it allows sharing the workload by the various numbers of homogenous platforms together. Besides, it is possible to say there are many kinds of problems that require the usage of the different capabilities of the heterogeneous platforms together cooperatively to achieve successful results. In this case, cooperative working brings additional problems beyond the homogeneous clusters. In the scenario presented as an example problem, it is expected that an autonomous ground vehicle, which is lack of its position information, manage to perform point-to-point navigation without losing its way in a previously unknown labyrinth. Furthermore, the ground vehicle is equipped with very limited sensors such as ultrasonic sensors that can detect obstacles. It is very hard to plan or complete the mission for the ground vehicle by self without lost its way in the unknown labyrinth. Thus, in order to assist the ground vehicle, the autonomous air drone is also used to solve the problem cooperatively. The autonomous drone also has limited sensors like downward looking camera and IMU, and it also lacks computing its global position. In this context, it is aimed to solve the problem effectively without taking additional support or input from the outside, just benefiting capabilities of two autonomous vehicles. To manage the point-to-point navigation in a previously unknown labyrinth, the platforms have to work together coordinated. In this paper, cooperative work of heterogeneous unmanned systems is handled in an applied sample scenario, and it is mentioned that how to work together with an autonomous ground vehicle and the autonomous flying platform together in a harmony to take advantage of different platform-specific capabilities. The difficulties of using heterogeneous multiple autonomous platforms in a mission are put forward, and the successful solutions are defined and implemented against the problems like spatially distributed tasks planning, simultaneous coordinated motion, effective communication, and sensor fusion.

Keywords: unmanned systems, heterogeneous autonomous vehicles, coordination, task planning

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Lindsay Foreman

Abstract:

Introduction: Goals have become synonymous with the quest for the good life and the pursuit of happiness, with coaching and positive psychology gaining popularity as an approach in recent decades. And yet mental health is on the rise and the leading cause of disability, wellbeing is on the decline, stress is leading to 50-60% of workday absences and the need for action is indisputable and urgent. Purpose: The purpose of this study is to better understand two things we cannot see, but that play the most significant role in these outcomes - what we think and how we feel. With many working on the assumption that positive thinking and an optimistic outlook are necessary or valuable components of goal pursuit, this study uncovers the reality of the ‘inner-game’ from the coachees perspective. Method: With a mixed methods design using a Q Method study of subjectivity to ‘make the unseen seen’. First, a wide-ranging universe of subjective thoughts and feelings experienced during goal pursuit are explored.. These are generated from literature and a Qualtrics survey to create a Q-Set of 40 statements. Then 19 participants in professional and organisational settings offer their perspectives on these 40 Q-Set statements. Each rank them in a semi-forced distribution from ‘most like me’ to ‘least like me’ using Q-Sort software. From these individual perspectives, clusters of perspectives are identified using factor analysis and four distinct viewpoints, have emerged. Findings: These Goal Pursuit Viewpoints offer insight into the states and self-talk experienced by coachees and may not reflect the assumption of positive thinking associated with achieving goals. The four Viewpoints are 1) the Positive View, 2) the Realistic View 3) The Dreamer View and 4) The Conflicted View. With only a quarter of the Dreamer View, and a third of the Positive view going on to achieve their goals, these assumptions need review. And with all the Realistic View going on to achieve their goals, the role of self-doubt, overwhelm and anxiousness in goal achievement cannot be overlooked. Contribution: This study offers greater insight and understanding of people's inner experiences as they pursue goals and highlights the necessary and normal negative states associated with goal achievement. It also offers a practical tool of 40 ‘Clarity Card’ Q-set statements to help coaches and coachees explore the current state and help navigate the journey towards goal achievement. It calls into question whether goals should always be part of coaching, and if values, identity, and purpose may play a greater role than goals

Keywords: self-talk, mental health, inner critic, inner coach

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Authors: Pedro Augusto Da Silva E Souza Miranda, Niloofar Jalali, Shweta Mistry

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BACKGROUND: Software developers utilize automated solutions to scrape users’ reviews to extract meaningful knowledge to identify problems (e.g., bugs, compatibility issues) and possible enhancements (e.g., users’ requests) to their solutions. However, most of these solutions do not consider the health risk aspects to users. Recent works have shed light on the importance of including health risk considerations in the development cycle of mHealth apps to prevent harm to its users. PROBLEM: The COVID-19 Pandemic in Canada (and World) is currently forcing physical distancing upon the general population. This new lifestyle made the usage of mHealth applications more essential than ever, with a projected market forecast of 332 billion dollars by 2025. However, this new insurgency in mHealth usage comes with possible risks to users’ health due to mHealth apps problems (e.g., wrong insulin dosage indication due to a UI error). OBJECTIVE: These works aim to raise awareness amongst mHealth developers of the importance of considering risks to users’ health within their development lifecycle. Moreover, this work also aims to help mHealth developers with a Proof-of-Concept (POC) solution to understand, process, and identify possible health risks to users of mHealth apps based on users’ reviews. METHODS: We conducted a mixed-method study design. We developed a crawler to mine the negative reviews from two samples of mHealth apps (my fitness, medisafe) from the Google Play store users. For each mHealth app, we performed the following steps: • The reviews are divided into two groups, before starting the COVID-19 (reviews’ submission date before 15 Feb 2019) and during the COVID-19 (reviews’ submission date starts from 16 Feb 2019 till Dec 2020). For each period, the Latent Dirichlet Allocation (LDA) topic model was used to identify the different clusters of reviews based on similar topics of review The topics before and during COVID-19 are compared, and the significant difference in frequency and severity of similar topics are identified. RESULTS: We successfully scraped, filtered, processed, and identified health-related topics in both qualitative and quantitative approaches. The results demonstrated the similarity between topics before and during the COVID-19.

Keywords: natural language processing (NLP), topic modeling, mHealth, COVID-19, software engineering, telemedicine, health risks

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Authors: Gayathri Devi V, Aravamudan Kannan, Amit Sircar

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In the inner fuel cycle system of a nuclear fusion reactor, the Hydrogen Isotopes Removal System (HIRS) plays a pivoted role. It enables the effective extraction of the hydrogen isotopes from the breeder purge gas which helps to maintain the tritium breeding ratio and sustain the fusion reaction. One of the components of HIRS, Cryogenic Molecular Sieve Bed (CMSB) columns with zeolites adsorbents are considered for the physisorption of hydrogen isotopes at 1 bar and 77 K. Even though zeolites have good thermal stability and reduced activation properties making them ideal for use in nuclear reactor applications, their modest capacity for hydrogen isotopes adsorption is a cause of concern. In order to enhance the adsorbent capacity in an informed manner, it is helpful to understand the adsorption phenomena at the quantum electronic structure level. Physicochemical modifications of the adsorbent material enhances the adsorption capacity through the incorporation of active sites. This may be accomplished through the incorporation of suitable metal ions in the zeolite framework. In this work, molecular hydrogen isotopes adsorption on the active sites of functionalized zeolites are investigated in detail using Density Functional Theory (DFT) study. This involves the utilization of hybrid Generalized Gradient Approximation (GGA) with dispersion correction to account for the exchange and correlation functional of DFT. The electronic energies, adsorption enthalpy, adsorption free energy, Highest Occupied Molecular Orbital (HOMO), Lowest Unoccupied Molecular Orbital (LUMO) energies are computed on the stable 8T zeolite clusters as well as the periodic structure functionalized with different active sites. The characteristics of the dihydrogen bond with the active metal sites and the isotopic effects are also studied in detail. Validation studies with DFT will also be presented for adsorption of hydrogen on metal ion functionalized zeolites. The ab-inito screening analysis gave insights regarding the mechanism of hydrogen interaction with the zeolites under study and also the effect of the metal ion on adsorption. This detailed study provides guidelines for selection of the appropriate metal ions that may be incorporated in the zeolites framework for effective adsorption of hydrogen isotopes in the HIRS.

Keywords: adsorption enthalpy, functionalized zeolites, hydrogen isotopes, nuclear fusion, physisorption

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Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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Authors: Zeta Dooly, Aidan Duane

Abstract:

The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Sohyoung Won, Heebal Kim, Dajeong Lim

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Genomic prediction is an effective way to measure the abilities of livestock for breeding based on genomic estimated breeding values, statistically predicted values from genotype data using best linear unbiased prediction (BLUP). Using haplotypes, clusters of linked single nucleotide polymorphisms (SNPs), as markers instead of individual SNPs can improve the reliability of genomic prediction since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with markers is higher. To efficiently use haplotypes in genomic prediction, finding optimal ways to define haplotypes is needed. In this study, 770K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 2506 cattle. Haplotypes were first defined in three different ways using 770K SNP chip data: haplotypes were defined based on 1) length of haplotypes (bp), 2) the number of SNPs, and 3) k-medoids clustering by LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; in each method, haplotypes defined to have an average number of 5, 10, 20 or 50 SNPs were tested respectively. A modified GBLUP method using haplotype alleles as predictor variables was implemented for testing the prediction reliability of each haplotype set. Also, conventional genomic BLUP (GBLUP) method, which uses individual SNPs were tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight was used as the phenotype for testing. As a result, using haplotypes defined by all three methods showed increased reliability compared to conventional GBLUP. There were not many differences in the reliability between different haplotype defining methods. The reliability of genomic prediction was highest when the average number of SNPs per haplotype was 20 in all three methods, implying that haplotypes including around 20 SNPs can be optimal to use as markers for genomic prediction. When the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles. Using haplotype alleles for genomic prediction showed better performance, suggesting improved accuracy in genomic selection. The number of predictor variables was decreased when the LD-based method was used while all three haplotype defining methods showed similar performances. This suggests that defining haplotypes based on LD can reduce computational costs and allows efficient prediction. Finding optimal ways to define haplotypes and using the haplotype alleles as markers can provide improved performance and efficiency in genomic prediction.

Keywords: best linear unbiased predictor, genomic prediction, haplotype, linkage disequilibrium

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Authors: Lindsay Foreman

Abstract:

Introduction: Goals have become synonymous with the quest for the good life and the pursuit of happiness, with coaching and positive psychology gaining popularity as an approach in recent decades. And yet mental health is on the rise and the leading cause of disability, wellbeing is on the decline, stress is leading to 50-60% of workday absences and the need for action is indisputable and urgent. Purpose: The purpose of this study is to better understand two things we cannot see, but that play the most significant role in these outcomes - what we think and how we feel. With many working on the assumption that positive thinking and an optimistic outlook are necessary or valuable components of goal pursuit, this study uncovers the reality of the ‘inner-game’ from the coachee's perspective. Method: With a mixed methods design using a Q Method study of subjectivity to ‘make the unseen seen’. First, a wide-ranging universe of subjective thoughts and feelings experienced during goal pursuit are explored. These are generated from literature and a Qualtrics survey to create a Q-Set of 40 statements. Then 19 participants in professional and organisational settings offer their perspectives on these 40 Q-Set statements. Each rank them in a semi-forced distribution from ‘most like me’ to ‘least like me’ using Q-Sort software. From these individual perspectives, clusters of perspectives are identified using factor analysis and four distinct viewpoints have emerged. Findings: These Goal Pursuit Viewpoints offer insight into the states and self-talk experienced by coachees and may not reflect the assumption of positive thinking associated with achieving goals. The four Viewpoints are 1) the Optimistic View, 2) the Realistic View 3) The Dreamer View and 4) The Conflicted View. With only a quarter of the Dreamer View, and a third of the Optimistic view going on to achieve their goals, these assumptions need review. And with all the Realistic Views going on to achieve their goals, the role of self-doubt, overwhelm and anxiousness in goal achievement cannot be overlooked. Contribution: This study offers greater insight and understanding of people's inner experiences as they pursue goals and highlights the necessary and normal negative states associated with goal achievement. It also offers a practical tool of the Q-set statements to help coaches and coachees explore the current state and help navigate the journey towards goal achievement. It calls into question whether goals should always be part of coaching and if values, identity, and purpose may play a greater role than goals.

Keywords: coaching, goals, positive psychology, mindset, leadership, mental health, beliefs, cognition, emotional intelligence

Procedia PDF Downloads 84

Authors: Minwuyelet Maru, Solomon Habtemariam, Endalamaw Gadissa, Abraham Aseffa

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Background: Tuberculosis is a major public health problem in Ethiopia. The burden of TB is aggravated by emergence and expansion of drug resistant tuberculosis and different lineages of Mycobacterium tuberculosis (M. tuberculosis) have been reported in many parts of the country. Describing strains of Mycobacterial isolates and drug susceptibility pattern is necessary. Method: Sputum samples were collected from smear positive pulmonary TB patients age >= 7 years between October 1, 2012 to September 30, 2013 and Mycobacterial strains isolated on Loweensten Jensen (LJ) media. Each strain was characterized by deletion typing and Spoligotyping. Drug sensitivity testing was determined with the indirect proportion method using Middle brook 7H10 media and association to determine possible risk factors to drug resistance was done. Result: A total of 144 smear positive pulmonary tuberculosis patients were enrolled. The age of participants ranged from 7 to 78 with mean age of 29.22 (±10.77) years. In this study 82.2% (n=97) of the isolates were sensitive to the four first line anti-tuberculosis drugs and resistance to any of the four drugs tested was 17.8% (n=21). A high frequency of any resistance was observed in isoniazid, 13.6%, (n=16) followed by streptomycin, 11.8% (n=14). No significant association of isoniazid resistance with HIV, sex and history of previous TB treatment was observed but there was significant association with age, high between 31-35 years of age (p=0.01). Majority, 89.9% (n=128) of participants were new cases and only 11.1% (n=16) had history of previous TB treatment. No MDR-TB from new cases and 2 MDRTB (13.3%) was isolated from re-treatment cases which was significantly associated with previous TB treatment (p<0.01). Thirty two different types of spoligotype patterns were identified and 74.1% were grouped in to 13 clusters. The dominant strains were SIT 25, 18.1% (n=21), SIT 53, 17.2% (n=20) and SIT 149, 8.6% (n=10). Lineage 4 is the predominant lineage followed by lineage 3 and lineage 7 comprising 65.5% (n=76), 28.4% (n=33) and 6% (n=7) respectively. Majority of strains from lineage 3 and 4 were SIT 25 (63.6%) and SIT 53 (26.3%) whereas SIT 343 was the dominant strain from lineage 7 (71.4%). Conclusion: Wide spread of lineage 3 and lineage 4 of the modern lineage and high number of strain cluster indicates high ongoing transmission. The high proportion resistance to any of the first line anti-tuberculosis drugs may be a potential source in the emergence of MDR-TB. Wide spread of SIT 25 and SIT 53 having a tendency of ease transmission and presence of higher resistance of isoniazid in working and mobile age group, 31-35 years of age may increase risk of drug resistant strains transmission.

Keywords: tuberculosis, drug susceptibility, strain diversity, lineage, Ethiopia, spoligotyping

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Authors: Dana Cassandra Winkler, Delia Leiding, Rene Bergs, Franziska Kaiser, Ramona Kirchhart, Ute Habel

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Background: Violence is a multidimensional phenomenon, affecting people of every age, socio-economic status and gender. Nevertheless, most studies primarily focus on men perpetrating women. Aim of the present study is to identify the likelihood of mental and somatic disorders and risk-taking behavior in male violence affected. In addition, the relationship between age of violence experience and the risk for health-related problems was analyzed. Method: On the basis of current evidence, a questionnaire was developed focusing on demographic background, health status, risk-taking behavior, and active and passive violence exposure. In total, 5221 males (Mean: 56,1 years, SD: 17,6) were consulted. To account for the time of violence experience in an efficient way, age clusters ‘0-12 years’, ‘13-20 years’, ‘21-35 years’, ‘36-65 years’ and ‘over 65 years’ were defined. A binary logistic regression was calculated to reveal differences in violence-affected and non-violence affected males regarding health and risk-taking factors. Males who experienced violence on a daily/ almost daily basis vs. males who reported violence occurrence once/ several times a month/ year were compared with respect to health factors and risk-taking behavior. Data of males, who indicated active and passive violence exposure, were analyzed by a chi²-analysis, to investigate a possible relation between the age of victimization and violence perpetration. Findings: Results imply that general violence experience, independent of active and passive violence exposure increases the likelihood in favor of somatic-, psychosomatic- and mental disorders as well as risk-taking behavior in males. Experiencing violence on a daily or almost daily basis in childhood and adolescence may serve as a predictor for increased health problems and risk-taking behavior. Furthermore, the violence experience and perpetration occur significantly within the same age cluster. This underlines the importance of a near-term intervention to minimize the risk, that victims become perpetrators later. Conclusion: The present study reveals predictors concerning health risk factors as well as risk-taking behavior in males with violence exposure. The results of this study may underscore the benefit of intervention and regular health care approaches in violence-affected males and underline the importance of acknowledging the overlap of violence experience and perpetration for further research.

Keywords: health disease, male, mental health, prevalence, risk-taking behavior, violence

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Authors: Busra Gundede, Ozal Mutlu, Nagihan Gulsoy

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Background: Over the years, material research has led to the development of numerous metals and alloys for using in biomedical applications. One of the major tasks of biomaterial research is the functionalization of the material surface to improve the biocompatibility according to a specific application. 316L and 316L alloys are excellent for various bio-applications. This research was investigated the effect of titanium (Ti), niobium (Nb), and zirconium (Zr) additives on injection molded austenitic grade 316L stainless steels in vitro biocompatibility. For this purpose, cytotoxic tests were performed to evaluate the potential biocompatibility of the specimens. Materials and Methods: 3T3 fibroblast were cultivated in DMEM supplemented with 10% fetal bovine serum and %1 penicillin-streptomycin at 37°C with 5% CO2 and 95%humidity. Trypsin/EDTA solution was used to remove cells from the culture flask. Cells were reseeded at a density of 1×105cell in 25T flasks. The medium change took place every 3 days. The trypan blue assay was used to determine cell viability. Cell viability is calculated as the number of viable cells divided by the total number of cells within the grids on the cell counter machine counted the number of blue staining cells and the number of total cells. Cell viability should be at least 95% for healthy log-phase cultures. MTT assay was assessed for 96-hours. Cells were cultivated in 6-well flask within 5 ml DMEM and incubated as same conditions. 0,5mg/ml MTT was added for 4-hours and then acid-isoprohanol was added for solubilize to formazan crystals. Cell morphology after 96h was investigated by SEM. The medium was removed, samples were washed with 0.15 M PBS buffer and fixed for 12h at 4- 8°C with %2,5 gluteraldehyte. Samples were treated with 1% osmium tetroxide. Samples were then dehydrated and dried, mounted on appropriate stubs with colloidal silver and sputter-coated with gold. Images were collected using a scanning electron microscope. ROS assay is a cell viability test for in vitro studies. Cells were grown for 96h, ROS solution added on cells in 6 well plate flask and incubated for 1h. Fluorescence signal indicates ROS generation by cells. Results: Trypan Blue exclusion assay results were 96%, 92%, 95%, 90%, 91% for negative control group, 316L, 316L-Ti, 316L-Nb and 316L-Zr, respectively. Results were found nearly similar to each other when compared with control group. Cell viability from MTT analysis was found to be 100%, 108%, 103%, 107%, and 105% for the control group, 316L, 316L-Ti, 316L-Nb and 316L-Zr, respectively. Fluorescence microscopy analysis indicated that all test groups were same as the control group in ROS assay. SEM images demonstrated that the attachment of 3T3 cells on biomaterials. Conclusion: We, therefore, concluded that Ti, Nb and Zr additives improved physical properties of 316L stainless. In our in vitro experiments showed that these new additives did not modify the cytocompatibility of stainless steel and these additives on 316L might be useful for biomedical applications.

Keywords: 316L stainles steel, biocompatibility, cell culture, Ti, Nb, Zr

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Authors: Atilola O. Abidemi-Iromini, Oluayo A. Bello-Olusoji, Immanuel A. Adebayo

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Ecological studies were carried out in Asejire Reservoir (AR) and Lagos Lagoon (LL), Southwest Nigeria from January 2012 to December 2013 to determine the health status of Chrysichthys nigrodigitatus (CN) and Oreochromis niloticus (ON). The fish species samples were collected every month, these were separated into sexes, and growth pattern {length, (cm); weight (g), Isometric index, condition factor} were measured. Heavy metals (lead (Pb), iron (Fe), zinc (Zn), copper (Cu), and chromium (Cr) in ppm concentrations were also determined while bacteria occurrence(s), (load and prevalence) on fish skins, gills and intestine in the two ecological zones were determined. The fish ratio collected is in range with normal aquatic (1: 1+) male: female ratio. Growth assessment determined revealed no significant difference in length and weight in O. niloticus between locations, but a significant difference in weight occurred in C. nigrodigitatus between locations, with a higher weight (196.06 ±0.16 g) from Lagos Lagoon. Highest condition factor (5.25) was recorded in Asejire Reservoir O. niloticus, (ARON); and lowest condition factor (1.64) was observed in Asejire Reservoir C. nigrodigitatus (ARCN); as this indicated a negative allometric value which is normal in Bagridae species because it increases more in Length to weight gain than for the Cichlidae growth status. Normal growth rate (K > 1) occurred between sexes, with the male species having higher K - factors than female species within locations, between locations, between species, and within species, except for female C. nigrodigitatus having higher condition factor (K = 1.75) than male C. nigrodigitatus (K = 1.54) in Asejire Reservoir. The highest isometric value (3.05) was recorded in Asejire Reservoir O. niloticus and lowest in Lagos Lagoon C. nigrodigitatus. Male O. niloticus from Asejire Reservoir had highest isometric value, and O. niloticus species had higher condition factor which ranged between isometric (b ≤ 3) and positive allometric (b > 3), hence, denoted robustness of fish to grow more in weight than in length; while C. nigrodigitatus fish has negative allometric (b < 3) indicating fish add more length than in weight on growth. The status of condition factors and isometric values obtained is species-specific, and environmental influence, food availability or reproduction factor may as well be contributing factors. The concentrations of heavy metals in fish flesh revealed that Zn (6.52 ±0.82) had the highest, while Cr (0.01±0.00) was ranked lowest; for O. niloticus in Asejire Reservoir. In Lagos Lagoon, heavy metals concentration level revealed that O. niloticus flesh had highest in Zn (4.71±0.25) and lowest in Pb (0.01±0.00). Lagos Lagoon C. nigrodigitatus heavy metal concentration level revealed Zn (9.56±0.96) had highest, while Cr (0.06±0.01) had lowest; and Asejire Reservoir C. nigrodigitatus heavy metal level revealed that Zn (8.26 ±0.74) had highest, and Cr (0.08±0.00) had lowest. In all, Zinc (Zn) was top-ranked in level among species.

Keywords: Oreochromis niloticus, growth status, Chrysichthys nigrodigitatus, environments, heavy metals

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Authors: Deniz Sari, Selahattin İncecik, Nesimi Ozkurt

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Surface ozone, which named as one of the most critical pollutants in the 21th century, threats to human health, forest and vegetation. Specifically, in rural areas surface ozone cause significant influences on agricultural productions and trees. In this study, in order to understand to the surface ozone levels in rural areas we focus on the north-western side of Biga Peninsula which covers by the mountainous and forested area. Ozone concentrations were measured for the first time with passive sampling at 10 sites and two online monitoring stations in this rural area from 2013 and 2015. Using with the daytime hourly O3 measurements during light hours (08:00–20:00) exceeding the threshold of 40 ppb over the 3 months (May, June and July) for agricultural crops, and over the six months (April to September) for forest trees AOT40 (Accumulated hourly O3 concentrations Over a Threshold of 40 ppb) cumulative index was calculated. AOT40 is defined by EU Directive 2008/50/EC to evaluate whether ozone pollution is a risk for vegetation, and is calculated by using hourly ozone concentrations from monitoring systems. In the present study, we performed the trajectory analysis by The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to follow the long-range transport sources contributing to the high ozone levels in the region. The ozone episodes observed between 2013 and 2015 were analysed using the HYSPLIT model developed by the NOAA-ARL. In addition, the cluster analysis is used to identify homogeneous groups of air mass transport patterns can be conducted through air trajectory clustering by grouping similar trajectories in terms of air mass movement. Backward trajectories produced for 3 years by HYSPLIT model were assigned to different clusters according to their moving speed and direction using a k-means clustering algorithm. According to cluster analysis results, northerly flows to study area cause to high ozone levels in the region. The results present that the ozone values in the study area are above the critical levels for forest and vegetation based on EU Directive 2008/50/EC.

Keywords: AOT40, Biga Peninsula, HYSPLIT, surface ozone

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

Procedia PDF Downloads 306

Authors: Thayalan Nall, Andreas Putra

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A major offshore reclamation work is currently underway in Southeast Asia for a container terminal. The total extent of the reclamation extent is 2600m x 800m and the seabed level is around -5mRL below mean sea level. Subsoil profile below seabed comprises soft marine clays of thickness varying from 8m to 15m. To contain the dredging spoil within the reclamation area, perimeter bunds have been constructed to +2.5mRL. They include breakwaters of trapezoidal geometry, made of boulder size rock along the northern, eastern and western perimeters, with a sand bund along the southern perimeter. Breakwaters were constructed on a composite bamboo pile and raft foundation system. Bamboo clusters 8m long, with 7 individual Bamboos bundled together as one, have been installed within the footprint of the breakwater below seabed in soft marine clay. To facilitate drainage two prefabricated vertical drains (PVD) have been attached to each cluster. Once the cluster piles were installed, a bamboo raft was placed as a load transfer platform. Rafts were made up of 5 layers of bamboo mattress, and in each layer bamboos were spaced at 200mm centres. The rafts wouldn’t sink under their own weight, and hence, they were sunk by loading quarry run rock onto them. Bamboo is a building material available in abundance in Indonesia and obtained at a relatively low cost. They are commonly used as semi-rigid inclusions to improve compressibility and stability of soft soils. Although bamboo is widely used in soft soil engineering design, no local design guides are available and the designs are carried out based on local experience. In June 2015, when the 1st load of sand was pumped by a dredging vessel next to the breakwater, a 150m long section of the breakwater underwent failure and displaced the breakwater between 1.2m to 4.0m. The cause of the failure was investigated to implement remedial measures to reduce the risk of further failures. Analyses using both limit equilibrium approach and finite element modelling revealed two plausible modes of breakwater failure. This paper outlines: 1) Developed Geology and the ground model, 2) The techniques used for the installation of bamboo piles, 3) Details of the analyses including modes and mechanism of failure and 4) Design changes incorporated to reduce the risk of failure.

Keywords: bamboo piles, ground improvement, reclamation, breakwater failure

Procedia PDF Downloads 373

Authors: Hussain-Abdulah Arjmand, Nikki S. Rickard

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The response to stress can be highly heterogenous, and may be influenced by methodological factors. The integrity of data will be optimized by measuring both positive and negative affective responses to an event, by measuring responses in real time as close to the stressful event as possible, and by utilizing data collection methods that do not interfere with naturalistic behaviours. The aim of the current study was to explore short term prototypical responses to major stressor events on outcome measures encompassing both positive and negative indicators of psychological functioning. A novel mobile experience sampling methodology (m-ESM) was utilized to monitor both effective responses to stressors in real time. A smartphone mental health app (‘Moodprism’) which prompts users daily to report both their positive and negative mood, as well as whether any significant event had occurred in the past 24 hours, was developed for this purpose. A sample of 142 participants was recruited as part of the promotion of this app. Participants’ daily reported experience of stressor events, levels of depressive symptoms and positive affect were collected across a 30 day period as they used the app. For each participant, major stressor events were identified on the subjective severity of the event rated by the user. Depression and positive affect ratings were extracted for the three days following the event. Responses to the event were scaled relative to their general reactivity across the remainder of the 30 day period. Participants were first clustered into groups based on initial reactivity and subsequent recovery following a stressor event. This revealed distinct patterns of responding along depressive symptomatology and positive affect. Participants were then grouped based on allocations to clusters in each outcome variable. A highly individualised nature in which participants respond to stressor events, in symptoms of depression and levels of positive affect, was observed. A complete description of the novel profiles identified will be presented at the conference. These findings suggest that real-time measurement of both positive and negative functioning to stressors yields a more complex set of responses than previously observed with retrospective reporting. The use of smartphone technology to measure individualized responding also proved to shed significant insight.

Keywords: depression, experience sampling methodology, positive functioning, resilience

Procedia PDF Downloads 209

Authors: N. Balaban, A. Buernstein, F. Gelman, Z. Ronen

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Brominated flame retardants are widespread pollutants, and are known to be toxic, carcinogenic, endocrinic disrupting as well as recalcitrant. The industrial complex Neot Hovav, in the Northern Negev, Israel, is situated above a fractured chalk aquitard, which is polluted by a wide variety of halogenated organic compounds. Two of the abundant pollutants found in the site are Dibromoneopentyl-glycol (DBNPG) and tribromoneopentyl-alcohol (TBNPA). Due to the elusive nature of the groundwater flow, it is difficult to connect between the spatial changes in contaminant concentrations to degradation. In this study, we attempt to determine whether these compounds are biodegraded in the groundwater, and to gain a better understanding concerning the bacterial community in the groundwater. This was achieved through the application of compound-specific isotope analysis (CSIA) of carbon (13^C/12^C) and bromine (81^Br/79^Br), and new-generation MiSeq pyrosequencing. The sampled boreholes were distributed among three main areas of the industrial complex: around the production plant of TBNPA and DBNPG; along the Hovav Wadi (small ephemeral stream) which crosses and drains the industrial complex; and downstream to the industrial area. TBNPA and DBNPG are found in all three areas, with no clear connection to the proximity of the borehole to the production plant. Initial isotopic data of TBNPA from boreholes in the area surrounding the production plant, reveal no changes in the carbon and bromine isotopic values. When observing the microbial groundwater community, the dominant phylum is Proteobacteria. Known anaerobic dehalogenating bacteria such as Dehalococcoides from the Chloroflexi phylum have also been detected. A statistical comparison of the groundwater microbial diversity using a multi-variant ordination of non-metric multidimensional scaling (NMDS) reveals three main clusters in accordance to spatial location in the industrial complex: all the boreholes sampled adjacent to the production plant cluster together and separately from the Wadi Hovav boreholes cluster and the downstream to the industrial area borehole cluster. This work provides the basis for the development and implication of an isotopic fractionation based tool for assessing the biodegradation of brominated organic compounds in contaminated environments, and a novel attempt to characterize the spatial microbial diversity in the contaminated site.

Keywords: biodegradation, brominated flame retardants, groundwater, isotopic fractionation, microbial diversity

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Authors: Wee Tong Liaw, Elaine Wong Yee Sing

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Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. The rationale for implementing a sustained health promoting workplace and participating in SHA is obvious when company management is convinced that healthier employees, business productivity, and profitability are positively correlated. However, performing research or empirical studies on the impact of a sustained health promoting workplace on stock returns are not likely to yield any interests in the absence of a systematic and independent assessment on the comprehensiveness and sustainability of a health promoting workplace in most developed economies. The principles of diversification and mean-variance efficient portfolio in Modern Portfolio Theory developed by Markowitz (1952) laid the foundation for the works of many financial economists and researchers, and among others, the development of the Capital Asset Pricing Model from the work of Sharpe (1964), Lintner (1965) and Mossin (1966), and the Fama-French Three-Factor Model of Fama and French (1992). This research seeks to support the rationale by studying whether there is a significant relationship or impact of a sustained health promoting workplace on the performance of companies listed on the SGX. The research shall form and test hypotheses pertaining to the impact of a sustained health promoting workplace on company’s performances, including stock returns, of companies that participated in the SHA and companies that did not participate in the SHA. In doing so, the research would be able to determine whether corporate and fund manager should consider the significance of a sustained health promoting workplace as a risk factor to explain the stock returns of companies listed on the SGX. With respect to Singapore’s stock market, this research will test the significance and relevance of a health promoting workplace using the Singapore Health Award as a proxy for non-diversifiable risk factor to explain stock returns. This study will examine the significance of a health promoting workplace on a company’s performance and study its impact on stock price performance and beta and examine if it has higher explanatory power than the traditional single factor asset pricing model CAPM (Capital Asset Pricing Model). To study the significance there are three key questions pertinent to the research study. I) Given a choice, would an investor be better off investing in a listed company with a sustained health promoting workplace i.e. a Singapore Health Award’s recipient? II) The Singapore Health Award has four levels of award starting from Bronze, Silver, Gold to Platinum. Would an investor be indifferent to the level of award when investing in a listed company who is a Singapore Health Award’s recipient? III) Would an asset pricing model combining FAMA-French Three Factor Model and ‘Singapore Health Award’ factor be more accurate than single factor Capital Asset Pricing Model and the Three Factor Model itself?

Keywords: asset pricing model, company's performance, stock prices, sustained health promoting workplace

Procedia PDF Downloads 348

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

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Background: Avian influenza, more commonly known as Bird flu, is a viral zoonotic respiratory disease stemming from various species of poultry, including pets and migratory birds. Researchers have purported that the accessibility of health information online, in addition to the low-cost data collection methods the internet provides, has revolutionized the methods in which epidemiological and disease surveillance data is utilized. This paper examines the feasibility of using internet data sources, such as Twitter and livestock forums, for the early detection of the avian flu outbreak, through the use of text mining algorithms and social network analysis. Methods: Social media mining was conducted on Twitter between the period of 01/01/2021 to 31/12/2021 via the Twitter API in Python. The results were filtered firstly by hashtags (#avianflu, #birdflu), word occurrences (avian flu, bird flu, H5N1), and then refined further by location to include only those results from within the UK. Analysis was conducted on this text in a time-series manner to determine keyword frequencies and topic modeling to uncover insights in the text prior to a confirmed outbreak. Further analysis was performed by examining clinical signs (e.g., swollen head, blue comb, dullness) within the time series prior to the confirmed avian flu outbreak by the Animal and Plant Health Agency (APHA). Results: The increased search results in Google and avian flu-related tweets showed a correlation in time with the confirmed cases. Topic modeling uncovered clusters of word occurrences relating to livestock biosecurity, disposal of dead birds, and prevention measures. Conclusions: Text mining social media data can prove to be useful in relation to analysing discussed topics for epidemiological surveillance purposes, especially given the lack of applied research in the veterinary domain. The small sample size of tweets for certain weekly time periods makes it difficult to provide statistically plausible results, in addition to a great amount of textual noise in the data.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, avian influenza, social media

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Authors: Bi Xiao Fang, Tan Bao Zhen

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Soft skills, core competencies, and generic competencies are exchangeable terminologies often used to represent a similar concept. In the Singapore context, such skills are currently being referred to as Critical Core Skills (CCS). In 2019, SkillsFuture Singapore (SSG) reviewed the Generic Skills and Competencies (GSC) framework that was first introduced in 2016, culminating in the development of the Critical Core Skills (CCS) framework comprising 16 soft skills classified into three clusters. The CCS framework is part of the Skills Framework, and whose stated purpose is to create a common skills language for individuals, employers and training providers. It is also developed with the objectives of building deep skills for a lean workforce, enhance business competitiveness and support employment and employability. This further helps to facilitate skills recognition and support the design of training programs for skills and career development. According to SSG, every job role requires a set of technical skills and a set of Critical Core Skills to perform well at work, whereby technical skills refer to skills required to perform key tasks of the job. There has been an increasing emphasis on soft skills for the future of work. A recent study involving approximately 80 organizations across 28 sectors in Singapore revealed that more enterprises are beginning to recognize that soft skills support their employees’ performance and business competitiveness. Though CCS is of high importance for the development of the workforce’s employability, there is little attention paid to the CCS use and profiling across occupations. A better understanding of how CCS is distributed across the economy will thus significantly enhance SSG’s career guidance services as well as training providers’ services to graduates and workers and guide organizations in their hiring for soft skills. This CCS profiling study sought to understand how CCS is demanded in different occupations. To achieve its research objectives, this study adopted a quantitative method to measure CCS use across different occupations in the Singaporean workforce. Based on the CCS framework developed by SSG, the research team adopted a formative approach to developing the CCS profiling tool to measure the importance of and self-efficacy in the use of CCS among the Singaporean workforce. Drawing on the survey results from 2500 participants, this study managed to profile them into seven occupation groups based on the different patterns of importance and confidence levels of the use of CCS. Each occupation group is labeled according to the most salient and demanded CCS. In the meantime, the CCS in each occupation group, which may need some further strengthening, were also identified. The profiling of CCS use has significant implications for different stakeholders, e.g., employers could leverage the profiling results to hire the staff with the soft skills demanded by the job.

Keywords: employability, skills profiling, skills measurement, soft skills

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Authors: K. Vallianou, T. Alexopoulos, V. Plaka, M. K. Seleventi, V. Skanavis, C. Skanavis

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The present research addresses the role of place attachment and emotions in community resiliency and recovery within the context of a disaster. Natural disasters represent a disruption in the normal functioning of a community, leading to a general feeling of disorientation. This study draws on the trauma caused by a natural hazard such as a forest fire. The changes of the sense of togetherness are being assessed. Finally this research determines how the place attachment of the inhabitants was affected during the reorientation process of the community. The case study area is Mati, a small coastal town in eastern Attica, Greece. The fire broke out on July 23^rd, 2018. A quantitative research was conducted through questionnaires via phone interviews, one year after the disaster, to address community resiliency in the long-run. The sample was composed of 159 participants from the rural community of Mati plus 120 coming from Skyros Island that was used as a control group. Inhabitants were prompted to answer items gauging their emotions related to the event, group identification and emotional significance of their community, and place attachment before and a year after the fire took place. Importantly, the community recovery and reorientation were examined within the context of a relative absence of government backing and official support. Emotions related to the event were aggregated into 4 clusters related to: activation/vigilance, distress/disorientation, indignation, and helplessness. The findings revealed a decrease in the level of place attachment in the impacted area of Mati as compared to the control group of Skyros Island. Importantly, initial distress caused by the fire prompted the residents to identify more with their community and to report more positive feelings toward their community. Moreover, a mediation analysis indicated that the positive effect of community cohesion on place attachment one year after the disaster was mediated by the positive feelings toward the community. Finally, place attachment contributes to enhanced optimism and a more positive perspective concerning Mati’s future prospects. Despite an insufficient state support to this affected area, the findings suggest an important role of emotions and place attachment during the process of recovery. Implications concerning the role of emotions and social dynamics in meshing place attachment during the disaster recovery process as well as community resiliency are discussed.

Keywords: community resilience, natural disasters, place attachment, wildfire

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Fatemeh Moosavi, Tumelo Franck Nkoshwane

Abstract:

Peter Drucker the renowned management guru once said, “The best way to predict the future is to create it.” Mr. Drucker is also the man who placed human capital as the most vital resource of any institution. As such any institution bent on creating a better future, requires a competent human capital, one that is able to execute with efficiency and effectiveness the objective a society aspires to. Technology today is accelerating the rate at which many societies transition to knowledge based societies. In this accelerated paradigm, it is imperative that those in leadership establish a platform capable of sustaining the planned future; intellectual capital. The capitalist economy going into the future will not just be sustained by dollars and cents, but by individuals who possess the creativity to enterprise, innovate and create wealth from ideas. This calls for cities of the future, to have this premise at the heart of their future plan, if the objective of designing sustainable and liveable future cities will be realised. The knowledge economy, now transitioning to the creative economy, requires cities of the future to be ‘gardens’ of inspiration, to be places where knowledge, creativity, and innovation can thrive as these instruments are becoming critical assets for creating wealth in the new economic system. Developing nations must accept that learning is a lifelong process that requires keeping abreast with change and should invest in teaching people how to keep learning. The need to continuously update one’s knowledge, turn these cities into vibrant societies, where new ideas create knowledge and in turn enriches the quality of life of the residents. Cities of the future must have as one of their objectives, the ability to motivate their citizens to learn, share knowledge, evaluate the knowledge and use it to create wealth for a just society. The five functional factors suggested by Kevin Lynch;-vitality, meaning/sense, adaptability, access, control, and monitoring should form the basis on which policy makers and urban designers base their plans for future cities. The authors of this paper believe that developing nations “creative economy clusters”, cities where creative industries drive the need for constant new knowledge creating sustainable learning creative cities. Obviously the form, shape and size of these districts should be cognisant of the environmental, cultural and economic characteristics of each locale. Gaborone city in the republic of Botswana is presented as the case study for this paper.

Keywords: learning city, sustainable creative city, creative industry, good city form

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