Search results for: component labelling

Authors: Anita Paddy, Millicent Obodai, Lebbaeus Asamani

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The management of sickle cell disease requires a multidisciplinary team for better outcomes. Thus, literature on the application of the biopsychosocial model for the management and explanation of chronic pain in sickle cell disease (SCD) and other chronic diseases abound. However, there is limited research on the use of the biopsychosocial model, together with a spiritual component (biopsychosocial-spiritual model). The study investigated the extent to which healthcare providers utilized the biopsychosocial-spiritual model in the management of chronic pain to improve the quality of life (QoL) of patients with SCD. This study employed the descriptive survey design involving a consecutive sampling of 261 patients with SCD who were between the ages of 18 to 79 years and were accessing hematological services at the Clinical Genetics Department of the Korle Bu Teaching Hospital. These patients willingly consented to participate in the study by appending their signatures. The theory of integrated quality of life, the gate control theory of pain and the biopsychosocial(spiritual) model were tested. An instrument for the biopsychosocial-spiritual model was developed, with a basis from the literature reviewed, while the World Health Organisation Quality of Life BREF (WHOQoLBref) and the spirituality rating scale were adapted and used for data collection. Data were analyzed using descriptive statistics (means, standard deviations, frequencies, and percentages) and partial least square structural equation modeling. The study revealed that healthcare providers had a great leaning toward the biological domain of the model compared to the other domains. Hence, participants’ QoL was not fully improved as suggested by the biopsychosocial(spiritual) model. Again, the QoL and spirituality of patients with SCD were quite high. A significant negative impact of spirituality on QoL was also found. Finally, the biosocial domain of the biopsychosocial-spiritual model was the most significant predictor of QoL. It was recommended that policymakers train healthcare providers to integrate the psychosocial-spiritual component in health services. Also, education on SCD and its resultant impact from the domains of the model should be intensified while health practitioners consider utilizing these components fully in the management of the condition.

Keywords: biopsychosocial (spritual), sickle cell disease, quality of life, healthcare, accra

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Authors: Ghada Soltane

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The objective of this study was to identify factors impacting supply chain collaboration. a quantitative study was carried out on a sample of 84 Tunisian industrial companies. To verify the research hypotheses and test the direct effect of these factors on supply chain collaboration a multiple regression method was used using SPSS 26 software. The results show that there are four factors direct effects that affect supply chain collaboration in a meaningful and positive way, including: trust, engagement, information sharing and information quality

Keywords: supply chain collaboration, factors of collaboration, principal component analysis, multiple regression

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Authors: Ishith Seth, Lyndel Hewitt, Takako Yabe, James Wykes, Jonathan Clark, Bruce Ashford

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Background: Vastus lateralis (VL) can be used to reconstruct defects of the head and neck. Whilst the advantages are documented, donor-site morbidity is not well described. This study aimed to assess donor-site morbidity after VL flap harvest. The results will determine future directions for preventative and post-operative care to improve patient health outcomes. Methods: Ten participants (mean age 55 years) were assessed for the presence of donor-site morbidity after VL harvest. Musculoskeletal (pain, muscle strength, muscle length, tactile sensation), quality of life (SF-12), and lower limb function (lower extremity function, gait (function and speed), sit to stand were assessed using validated and standardized procedures. Outcomes were compared to age-matched healthy reference values or the non-operative side. Analyses were conducted using descriptive statistics and non-parametric tests. Results: There was no difference in muscle strength (knee extension), muscle length, ability to sit-to-stand, or gait function (all P > 0.05). Knee flexor muscle strength was significantly less on the operated leg compared to the non-operated leg (P=0.02) and walking speed was slower than age-matched healthy values (P<0.001). Thigh tactile sensation was impaired in 89% of participants. Quality of life was significantly less for the physical health component of the SF-12 (P<0.001). The mental health component of the SF-12 was similar to healthy controls (P=0.26). Conclusion: There was no effect on donor site morbidity with regards to knee extensor strength, pain, walking function, ability to sit-to-stand, and muscle length. VL harvest affected donor-site knee flexion strength, walking speed, tactile sensation, and physical health-related quality of life.

Keywords: vastus lateralis, morbidity, head and neck, surgery, donor-site morbidity

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Authors: V. Markogianni, D. Kalivas, G. Petropoulos, E. Dimitriou

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Lake water quality monitoring in combination with the use of earth observation products constitutes a major component in many water quality monitoring programs. Landsat 8 images of Trichonis Lake (Greece) acquired on 30/10/2013 and 30/08/2014 were used in order to explore the possibility of Landsat 8 to estimate water quality parameters and particularly CDOM absorption at specific wavelengths, chlorophyll-a and nutrient concentrations in this oligotrophic freshwater body, characterized by inexistent quantitative, temporal and spatial variability. Water samples have been collected at 22 different stations, on late August of 2014 and the satellite image of the same date was used to statistically correlate the in-situ measurements with various combinations of Landsat 8 bands in order to develop algorithms that best describe those relationships and calculate accurately the aforementioned water quality components. Optimal models were applied to the image of late October of 2013 and the validation of the results was conducted through their comparison with the respective available in-situ data of 2013. Initial results indicated the limited ability of the Landsat 8 sensor to accurately estimate water quality components in an oligotrophic waterbody. As resulted by the validation process, ammonium concentrations were proved to be the most accurately estimated component (R = 0.7), followed by chl-a concentration (R = 0.5) and the CDOM absorption at 420 nm (R = 0.3). In-situ nitrate, nitrite, phosphate and total nitrogen concentrations of 2014 were measured as lower than the detection limit of the instrument used, hence no statistical elaboration was conducted. On the other hand, multiple linear regression among reflectance measures and total phosphorus concentrations resulted in low and statistical insignificant correlations. Our results were concurrent with other studies in international literature, indicating that estimations for eutrophic and mesotrophic lakes are more accurate than oligotrophic, owing to the lack of suspended particles that are detectable by satellite sensors. Nevertheless, although those predictive models, developed and applied to Trichonis oligotrophic lake are less accurate, may still be useful indicators of its water quality deterioration.

Keywords: landsat 8, oligotrophic lake, remote sensing, water quality

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Authors: Hamza Zidoum

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This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Ravinder Singh, Pratima Syal

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Background: The rising prevalence and incidence of Acute Pancreatitis (AP) and its associated metabolic variables known as metabolic syndrome (MetS) are common medical conditions with catastrophic consequences and substantial treatment costs. The correlation between MetS and AP, as well as their impact on Health Related Quality of Life (HRQoL) is uncertain, and because there are so few published studies, further research is needed. As a result, we planned this study to determine the relationship between MetS components impact on HRQoL in AP patients. Patients and Methods: A prospective, observational study involving the recruitment of patients with AP with and without MetS was carried out in tertiary care hospital of North India. Patients were classified with AP if they were diagnosed with two or more components of the following criteria, abdominal pain, serum amylase and lipase levels two or more times normal, imaging trans-abdominal ultrasound, computed tomography, or magnetic resonance. The National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III) criterion was used to diagnose the MetS. The various socio-demographic variables were also taken into consideration for the calculation of statistical significance (P≤.05) in AP patients. Finally, the correlation between AP and MetS, along with their impact on HRQoL was assessed using Student's t test, Pearson Correlation Coefficient, and Short Form-36 (SF-36). Results: AP with MetS (n = 100) and AP without MetS (n = 100) patients were divided into two groups. Gender, Age, Educational Status, Tobacco use, Body Mass Index (B.M.I), and Waist Hip Ratio (W.H.R) were the socio-demographic parameters found to be statistically significant (P≤.05) in AP patients with MetS. Also, all the metabolic variables were also found to statistically significant (P≤.05) and found to be increased in patients with AP with MetS as compared to AP without MetS except HDL levels. Using the SF-36 form, a greater significant decline was observed in physical component summary (PCS) and mental component summary (MCS) in patients with AP with MetS as compared to patients without MetS (P≤.05). Furthermore, a negative association between all metabolic variables with the exception of HDL, and AP was found to be producing deterioration in PCS and MCS. Conclusion: The study demonstrated that patients with AP with MetS had a worse overall HRQOL than patients with AP without MetS due to number of socio-demographic and metabolic variables having direct correlation impacting physical and mental health of patients.

Keywords: metabolic disorers, QOL, cost effectiveness, pancreatitis

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Authors: Sergio Haram Sarmiento, Arcady Ponosov

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Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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Authors: Bernice Boafoaa Gyapong, Anne Jones, Sam Bassett, Janet Anderson

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Background: Maternal mortality and morbidity are global concerns, especially in sub-Saharan Africa (SSA). Most maternal mortalities occur at the time of birth. Quality intrapartum care is essential for improving maternal and newborn health outcomes. This scoping review aimed to assess and describe the quality of care during childbirth in SSA to provide an overview of the regional trend of the quality of intrapartum care, the challenges to quality care provision, and identify research gaps. Methods: A scoping review based on Arksey and O’Malley’s scoping review framework was conducted. Medline, CINAHL, PsycINFO, and maternal-infant databases were searched to identify the relevant studies for this review. A narrative summary was presented using themes based on the Donabedian structure, process, and outcome quality of care model. Results: A total of five hundred and forty-seven (547) publications were identified. Fifty-six (56) studies conducted in twenty (20) countries were included in the review. Thirty-four (34) were quantitative, sixteen (16) were qualitative, and six (6) were mixed methods. Most of the studies were related to the process component of quality of care. The provision of emergency obstetric care services, infrastructure, and availability of essential staff and equipment for perinatal care was inadequate in many facilities, particularly rural and peripheral health facilities. Many women experienced disrespectful care during childbirth. Routine care during labour and delivery was observed to be sub-optimal, yet some women reported high satisfaction with care. The use of health facilities for delivery was lower in health centres compared to hospitals. Conclusion: There are variations in the quality of maternity care provided in SSA. Intrapartum care quality is generally deficient in SSA, particularly in peripheral health facilities, health centres, and community clinics. Many of the quality-of-care issues identified are related to the structure component. Stakeholders must develop interventions that comprehensively address these interrelated issues to improve maternal healthcare quality, especially in primary healthcare facilities.

Keywords: quality of care, maternity health, Sub-Saharan Africa, intrapartum

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Authors: Aliya Hisam, Zia Ul Haq, Sohail Aziz, Patrick Doherty, Jill Pell

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Objective: To determine the effectiveness of Mobile health augmented Cardiac rehabilitation (MCard) on health-related quality of life (HRQoL) among post-acute coronary syndrome(post-ACS) patients. Methodology: In a randomized controlled trial, post-ACS patients were randomly allocated (1:1) to an intervention group (received MCard; counseling, empowering with self-monitoring devices, short text messages, in addition to standard post-ACS care) or control group (standard post-ACS care). HRQoL was assessed by generic Short Form-12 and MacNew quality of life myocardial infarction (QLMI) tools. Participants were followed for 24 weeks with data collection and analysis at three-time points (baseline, 12 weeks and 24 weeks). Result: At baseline, 160 patients (80 in each group; mean age 52.66+8.46 years; 126 males, 78.75%) were recruited, of which 121(75.62%) continued and were analyzed at 12-weeks and 119(74.37%) at 24-weeks. The mean SF-12 physical component score significantly improved in the MCard group at 12 weeks follow-up (48.93 vs. control 43.87, p<.001) and 24 weeks (53.52 vs. 46.82 p<.001). The mean SF-12 mental component scores also improved significantly in the MCard group at 12 weeks follow-up (44.84 vs. control 41.40, p<.001) and 24 weeks follow-up (48.95 vs 40.12, p<.001). At 12-and 24-week follow-up, all domains of MacNew QLMI (social, emotional, physical and global) were also statistically significant (p<.001) improved in the MCard group, unlike the control group. Conclusion: MCard is feasible and effective at improving all domains of HRQoL. There was an improvement in physical, mental, social, emotional and global domains among the MCard group in comparison to the control group. The addition of MCard programs to post-ACS standard care may improve patient outcomes and reduce the burden on the health care setting.

Keywords: acute coronary syndrome, mobile health augmented cardiac rehabilitation (MCard), cardiovascular diseases, cardiac rehabilitation, health-related quality of life, short form 12, MacNew QLMI

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Authors: K. Subbaiah, C. V. Jeyakumar, S. R. Koteswara Rao

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Cast Aluminum-Magnesium-Scandium alloy was Gas Tungsten Arc (GTA) welded, and the microstructure and mechanical properties of the joint and its component parts were examined and analyzed. The global joint fractured in the base metal, and thus possessed slightly greater tensile strength than the base metal. These results clearly show that Gas Tungsten Arc welding is an optimum / suitable welding process for cast Aluminum-Magnesium-Scandium alloys.

Keywords: cast Al-Mg-Sc alloy, GTAW, microstructure, mechanical properties

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Authors: Pedram Behyar, Zahra Bayat

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The internet and web are changing ways of “far reaching scope and potential for transformation of the marketing functions”. The web is developing in a faster rate than any previous new communication medium. The website of destination has become a crucial branding channel, that is why all businesses are changing their way to communicate with their customers to encounter their needs and wants in better ways. Website provides numerous opportunities for businesses to strengthen their relationship with their customers. One of these opportunities is website component that enables internet users to make two-way communication with the businesses.

Keywords: marketing communication, brand image, usability, privacy and security, personalization and customization, responsiveness, customer online web experience

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: Sonia Arradaza-Pajaron

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This study examined the relationship between transformational leadership (TL) and self-efficacy (SE) of academic heads in the implementation of a customized English language curriculum (CELC) among technological state universities and colleges in Leyte provinces and Biliran, Philippines. Results manifested that academic leaders practiced transformational leadership and are self-efficacious enough but with only moderate level in the effectiveness of CELC implementation. It was found out; further, that of the four identified transformational leadership components, except idealized influence, three of which demonstrated a significant relationship with CELC component variables, although in varying degree. Moreover, self-efficacy sources, especially vicarious experiences and verbal persuasion manifested moderate to high significant relationships with effective CELC curriculum implementation. Further, verbal persuasion and physiological/emotional condition manifested significant relationship with CELC-resource and CELC-contextual/community influence, respectively. Regression analysis showed that TL-individualized consideration component explained wider extent when correlated with CELC contextual/community components, while self-efficacy source-verbal persuasion demonstrated a wider extent with the three CELC components, namely; resource, process and physiological/emotional condition. Results further revealed that TL-individualized consideration manifested lesser influence with CELC implementation, while SE-verbal persuasion demonstrated stronger influence or effect on CELC-process, CELC-physiological/emotional, while lesser influence with CELC-resource. This implies that academic leaders, in order to carry out effective curriculum implementation, should provide more emphasis on school culture, its beliefs, practices and academic atmosphere but most of all empower human resources who are considered the backbone of the work place and can be directly affected by any curriculum shifts and challenges. To realize this, more values-skilled training programs must be designed for academic heads are needed to equip them with the necessary leadership skills, beliefs in their capacity to lead and their own enhance emotional well-being in leading subordinates and facilitating curriculum implementation.

Keywords: Customized English Language curriculum, CELC, self-efficacy, transformational leadership, values-skilled training

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Authors: Fuad M. Alkoot

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The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

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Authors: K. O’Mara, T. Cresswell

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Nearly half of the world’s population live near the coast, and as a result, estuaries and coastal bays in populated or industrialized areas often receive metal pollution. Heavy metals have a chemical affinity for sediment particles and can be stored in estuarine sediments and become biologically available under changing conditions. Organisms inhabiting estuaries can be exposed to metals from a variety of sources including metals dissolved in water, bound to sediment or within contaminated prey. Metal uptake and assimilation responses can vary even between species that are biologically similar, making pollution effects difficult to predict. A multi-trophic level experiment representing a common Eastern Australian estuarine food chain was used to study the sources for Cd, Mn and Zn uptake and assimilation in organisms occupying several trophic levels. Sand cockles (Katelysia scalarina), school prawns (Metapenaeus macleayi) and sand whiting (Sillago ciliata) were exposed to radiolabelled seawater, suspended sediment and food. Three pulse-chase trials on filter-feeding sand cockles were performed using radiolabelled phytoplankton (Tetraselmis sp.), benthic microalgae (Entomoneis sp.) and suspended sediment. Benthic microalgae had lower metal uptake than phytoplankton during labelling but higher cockle assimilation efficiencies (Cd = 51%, Mn = 42%, Zn = 63 %) than both phytoplankton (Cd = 21%, Mn = 32%, Zn = 33%) and suspended sediment (except Mn; (Cd = 38%, Mn = 42%, Zn = 53%)). Sand cockles were also sensitive to uptake of Cd, Mn and Zn dissolved in seawater. Uptake of these metals from the dissolved phase was negligible in prawns and fish, with prawns only accumulating metals during moulting, which were then lost with subsequent moulting in the depuration phase. Diet appears to be the main source of metal assimilation in school prawns, with 65%, 54% and 58% assimilation efficiencies from Cd, Mn and Zn respectively. Whiting fed contaminated prawns were able to exclude the majority of the metal activity through egestion, with only 10%, 23% and 11% assimilation efficiencies from Cd, Mn and Zn respectively. The findings of this study support previous studies that find diet to be the dominant accumulation source for higher level trophic organisms. These results show that assimilation efficiencies can vary depending on the source of exposure; sand cockles assimilated more Cd, Mn, and Zn from the benthic diatom than phytoplankton and assimilation was higher in sand whiting fed prawns compared to artificial pellets. The sensitivity of sand cockles to metal uptake and assimilation from a variety of sources poses concerns for metal availability to predators ingesting the clam tissue, including humans. The high tolerance of sand whiting to these metals is reflected in their widespread presence in Eastern Australian estuaries, including contaminated estuaries such as Botany Bay and Port Jackson.

Keywords: cadmium, food chain, metal, manganese, trophic, zinc

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Authors: Samuele Ghignoli, Valentina de Lorenzi, Gianmarco Ferri, Stefano Luin, Francesco Cardarelli

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Insulin and glucagon are the two essential hormones for maintaining proper blood glucose homeostasis, which is disrupted in Diabetes. A constantly growing research interest has been focused on the study of the subcellular structures involved in hormone secretion, namely insulin- and glucagon-containing granules, and on the mechanisms regulating their behaviour. Yet, while several successful attempts were reported describing the dynamic properties of insulin granules, little is known about their counterparts in α cells, the glucagon-containing granules. To fill this gap, we used αTC1 clone 9 cells as a model of α cells and ZIGIR as a fluorescent Zinc chelator for granule labelling. We started by using spatiotemporal fluorescence correlation spectroscopy in the form of imaging-derived mean square displacement (iMSD) analysis. This afforded quantitative information on the average dynamical and structural properties of glucagon granules having insulin granules as a benchmark. Interestingly, the iMSD sensitivity to average granule size allowed us to confirm that glucagon granules are smaller than insulin ones (~1.4 folds, further validated by STORM imaging). To investigate possible heterogeneities in granule dynamic properties, we moved from correlation spectroscopy to single particle tracking (SPT). We developed a MATLAB script to localize and track single granules with high spatial resolution. This enabled us to classify the glucagon granules, based on their dynamic properties, as ‘blocked’ (i.e., trajectories corresponding to immobile granules), ‘confined/diffusive’ (i.e., trajectories corresponding to slowly moving granules in a defined region of the cell), or ‘drifted’ (i.e., trajectories corresponding to fast-moving granules). In cell-culturing control conditions, results show this average distribution: 32.9 ± 9.3% blocked, 59.6 ± 9.3% conf/diff, and 7.4 ± 3.2% drifted. This benchmarking provided us with a foundation for investigating selected experimental conditions of interest, such as the glucagon-granule relationship with the cytoskeleton. For instance, if Nocodazole (10 μM) is used for microtubule depolymerization, the percentage of drifted motion collapses to 3.5 ± 1.7% while immobile granules increase to 56.0 ± 10.7% (remaining 40.4 ± 10.2% of conf/diff). This result confirms the clear link between glucagon-granule motion and cytoskeleton structures, a first step towards understanding the intracellular behaviour of this subcellular compartment. The information collected might now serve to support future investigations on glucagon granules in physiology and disease. Acknowledgment: This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 866127, project CAPTUR3D).

Keywords: glucagon granules, single particle tracking, correlation spectroscopy, ZIGIR

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Authors: Alena O. Stepanova, Vera S. Chernonosova, Tatyana S. Godovikova, Konstantin A. Bulatov, Andrey Y. Patrushev, Pavel P. Laktionov

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Trauma and arthrosis, not to mention cartilage destruction in overweight and elders put hyaline cartilage lesion among the most frequent diseases of locomotor system. These problems combined with low regeneration potential of the cartilage make regeneration of articular cartilage a high-priority task of tissue engineering. Many types of matrices, the procedures of their installation and autologous chondrocyte implantation protocols were offered, but certain aspects including adhesion of the implant with surrounding cartilage/bone, prevention of the ossification and fibrosis were not resolved. Simplification and acceleration of the procedures resulting in restoration of normal cartilage are also required. We have demonstrated that human chondroblasts can be successfully cultivated at the surface of electrospun scaffolds and produce extracellular matrix components in contrast to chondroblasts grown in homogeneous hydrogels. To restore cartilage we offer to use stacks of electrospun scaffolds fixed with photopolymerized solution of prepared from gelatin and chondroitin-4-sulfate both modified by glycidyl methacrylate and non-toxic photoinitator Darocur 2959. Scaffolds were prepared from nylon 6, polylactide-co-glicolide and their mixtures with modified gelatin. Illumination of chondroblasts in photopolymerized solution using 365 nm LED light had no effect on cell viability at compressive strength of the gel less than0,12 MPa. Stacks of electrospun scaffolds provide good compressive strength and have the potential for substitution with cartilage when biodegradable scaffolds are used. Vascularization can be prevented by introduction of biostable scaffolds in the layers contacting the subchondral bone. Studies of two-component materials (2-3 sheets of electrospun scaffold) implanted in the knee-joints of rabbits and fixed by photopolymerization demonstrated good crush resistance, biocompatibility and good adhesion of the implant with surrounding cartilage. Histological examination of the implants 3 month after implantation demonstrates absence of any inflammation and signs of replacement of the biodegradable scaffolds with normal cartilage. The possibility of intraoperative population of the implants with autologous cells is being investigated.

Keywords: chondroblasts, electrospun scaffolds, hyaline cartilage, photopolymerized gel

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Authors: Jaehoon Ha, Byungmo Kang, Kilho Hong, Jungsoo Park

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Electro-optical (EO) stabilized platforms have been widely used for surveillance and reconnaissance on various types of vehicles, from surface ships to unmanned air vehicles (UAVs). EO stabilized platforms usually consist of an assembly of structure, bearings, and motors called gimbals in which a gyroscope is installed. EO elements such as a CCD camera and IR camera, are mounted to a gimbal, which has a range of motion in elevation and azimuth and can designate and track a target. In addition, a laser range finder (LRF) can be added to the gimbal in order to acquire the precise slant range from the platform to the target. Recently, a versatile functionality of target localization is needed in order to cooperate with the weapon systems that are mounted on the same platform. The target information, such as its location or velocity, needed to be more accurate. The accuracy of the target information depends on diverse component errors and alignment errors of each component. Specially, the type of moving platform can affect the accuracy of the target information. In the case of flying platforms, or UAVs, the target location error can be increased with altitude so it is important to measure altitude as precisely as possible. In the case of surface ships, target location error can be increased with obliqueness of the elevation angle of the gimbal since the altitude of the EO stabilized platform is supposed to be relatively low. The farther the slant ranges from the surface ship to the target, the more extreme the obliqueness of the elevation angle. This can hamper the precise acquisition of the target information. So far, there have been many studies on EO stabilized platforms of flying vehicles. However, few researchers have focused on ship-borne EO stabilized platforms of the surface ship. In this paper, we deal with a target localization method when an EO stabilized platform is located on the mast of a surface ship. Especially, we need to overcome the limitation caused by the obliqueness of the elevation angle of the gimbal. We introduce a well-known approach for target localization using Unscented Kalman Filter (UKF) and present the problem definition showing the above-mentioned limitation. Finally, we want to show the effectiveness of the approach that will be demonstrated through computer simulations.

Keywords: target localization, ship-borne electro-optical stabilized platform, unscented kalman filter

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Authors: Natalia Moreno-Castellanos, Amaia Rodriguez, Gema Frühbeck

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Introduction: In adipocytes, the cytoskeleton undergoes important expression and distribution in adipocytes rearrangements during adipogenesis and in obesity. Indeed, a role for these proteins in the regulation of adipocyte differentiation and response to insulin has been demonstrated. Recently, septins have been considered as new components of the cytoskeletal network that interact with other cytoskeletal elements (actin and tubulin) profoundly modifying their dynamics. However, these proteins have not been characterized as yet in adipose tissue. In this work, were examined the cellular, molecular and functional features of a member of this family, septin 11 (SEPT11), in adipocytes and evaluated the impact of obesity on the expression of this protein in human adipose tissue. Methods: Adipose gene and protein expression levels of SEPT11 were analysed in human samples. SEPT11 distribution was evaluated by immunocytochemistry, electronic microscopy, and subcellular fractionation techniques. GST-pull down, immunoprecipitation and a Yeast-Two Hybrid (Y2H) screening were used to identify the SEPT11 interactome. Gene silencing was employed to assess the role of SEPT11 in the regulation of insulin signaling and lipid metabolism in adipocytes. Results: SEPT11 is expressed in human adipocytes, and its levels increased in both omental and subcutaneous adipose tissue in obesity, with SEPT11 mRNA content positively correlating with parameters of insulin resistance in subcutaneous fat. In non-stimulated adipocytes, SEPT11 immunoreactivity showed a ring-like distribution at the cell surface and associated to caveolae. Biochemical analyses showed that SEPT11 interacted with the main component of caveolae, caveolin-1 (CAV1) as well as with the fatty acid-binding protein, FABP5. Notably, the three proteins redistributed and co-localized at the surface of lipid droplets upon exposure of adipocytes to oleate. In this line, SEPT11 silencing in 3T3-L1 adipocytes impaired insulin signaling and decreased insulin-induced lipogenesis. Conclusions: Those findings demonstrate that SEPT11 is a novel component of the adipocyte cytoskeleton that plays an important role in the regulation of lipid traffic, metabolism and can thus represent a potential biomarker of insulin resistance in obesity in adipocytes through its interaction with both CAV1 and FABP5.

Keywords: caveolae, lipid metabolism, obesity, septins

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Authors: Renu Saini, Deepak Agrawal

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Background: Patients with head and spinal cord injury frequently have deranged coagulation profiles and require blood products transfusion perioperatively. Thromboelastography (TEG) is a ‘bedside’ global test of coagulation which may have role in deciding the need of transfusion in such patients. Aim: To assess the usefulness of TEG in department of neurosurgery in decreasing transfusion rates and coagulation-related mortality in traumatic head and spinal cord injury. Method and Methodology: A retrospective comparative study was carried out in the department of neurosurgery over a period of 1 year. There are two groups in this study. ‘Control’ group constitutes the patients in whom data was collected over 6 months (1/6/2009-31/12/2009) prior to installation of TEG machine. ‘Test’ group includes patients in whom data was collected over 6months (1/1/2013-30/6/2013) post TEG installation. Total no. of platelet, FFP, and cryoprecipitate transfusions were noted in both groups along with in hospital mortality and length of stay. Result: Both groups were matched in age and sex of patients, number of head and spinal cord injury cases, number of patients with thrombocytopenia and number of patients who underwent operation. Total 178 patients (135 head injury and 43 spinal cord injury patents) were admitted in neurosurgery department during time period June 2009 to December 2009 i.e. prior to TEG installation and after TEG installation a total of 243 patients(197 head injury and 46 spinal cord injury patents) were admitted. After TEG introduction platelet transfusion significantly reduced (p=0.000) compare to control group (67 units to 34 units). Mortality rate was found significantly reduced after installation (77 patients to 57 patients, P=0.000). Length of stay was reduced significantly (Prior installation 1-211days and after installation 1-115days, p=0.02). Conclusion: Bedside TEG can dramatically reduce platelet transfusion components requirement in department of neurosurgery. TEG also lead to a drastic decrease in mortality rate and length of stay in patients with traumatic head and spinal cord injuries. We recommend its use as a standard of care in the patients with traumatic head and spinal cord injuries.

Keywords: blood component transfusion, mortality, neurosurgery ICU, thromboelastography

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Authors: Mingqian Zhang

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Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

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Authors: S. S. Awanti, Aravindakumar B. Harwalkar

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Concrete construction in future has to be environmental friendly apart from being safe so that society at large is benefited by the huge investments made in the infrastructure projects. To achieve this, component materials of the concrete system have to be optimized with reference to sustainability. This paper presents a study on development of mix proportions of high volume fly ash concrete (HFC). A series of HFC mixtures with cement replacement levels varying between 50% and 65% were prepared with water/binder ratios of 0.3 and 0.35. Compressive strength values were obtained at different ages. From the experimental results, pozzolanic efficiency ratios and mix design curves for HFC were established.

Keywords: age factor, compressive strength, high volume fly ash concrete, pozolanic efficiency ratio

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Authors: Ji Young Lee, Jong Woon Kim

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It is essential to secure high availability of railway vehicles to realize high quality and efficiency of railway service. Once the availability decreased, planned railway service could not be provided or more cars need to be reserved. additional cars need to be purchased or the frequency of railway service could be decreased. Such situation would be a big loss in terms of quality and cost related to railway service. Therefore, we make various efforts to get high availability of railway vehicles. Because it is a big loss to operators, we make various efforts to get high availability of railway vehicles. To secure high availability, the idle time of the vehicle needs to be reduced and the following methods are applied to railway vehicles. First, through modularization design, exchange time for line replaceable units is reduced which makes railway vehicles could be put into the service quickly. Second, to reduce periodic preventive maintenance time, preventive maintenance with short period would be proceeded test oriented to minimize the maintenance time, and reliability is secured through overhauls for each main component. With such design changes for railway vehicles, modularized components are exchanged first at the time of vehicle failure or overhaul so that vehicles could be put into the service quickly and exchanged components are repaired or overhauled. Therefore, spare components are required for any future failures or overhauls. And, as components are modularized and costs for components are high, it is considerably important to get reasonable quantities of spare components. Especially, when a number of railway vehicles were put into the service simultaneously, the time of overhauls come almost at the same time. Thus, for some vehicles, components need to be exchanged and overhauled before appointed overhaul period so that these components could be secured as spare parts for the next vehicle’s component overhaul. For this reason, components overhaul time and spare parts quantities should be decided at the same time. This study deals with the time of overhauls for repairable components of railway vehicles and the calculation of spare parts quantities in consideration of future failure/overhauls. However, as railway vehicles are used according to the service schedule, maintenance work cannot be proceeded after the service was closed thus it is quite difficult to resolve this situation mathematically. In this study, Simulation software system is used in this study for analyzing the time of overhauls for repairable components of railway vehicles and the spare parts for the railway systems.

Keywords: overhaul time, rolling stocks, simulation, spare parts

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Authors: Saroj Bijarnia, Preety Singh

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We propose a simple and effective biometrics system based on face verification across aging using a new variant of texture feature, Pyramid Binary Pattern. This employs Local Binary Pattern along with its hierarchical information. Dimension reduction of generated texture feature vector is done using Principal Component Analysis. Support Vector Machine is used for classification. Our proposed method achieves an accuracy of 92:24% and can be used in an automated age-invariant face verification system.

Keywords: biometrics, age invariant, verification, support vector machine

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Authors: Virve Pääkkönen, Heidi M. Cuffaro, Leo Tjäderhane

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Objectives: Odontoblasts are the outermost cell layer of dental pulp and form the dentin. Importance of bacterial products, e.g. lipoteichoic acid (LTA), a cell wall component of Gram-positive bacteria and lipopolysaccharide (LPS), a cell wall component of Gram-negative bacteria, have been indicated in the pathogenesis of pulpitis. Gram-positive bacteria are more prevalent in superficial carious lesion while the amount gram-negative is higher in the deep lesions. Objective of this study was to investigate the effect of these bacterial products on inflammatory response of pulp tissue. Interleukins (IL) were of special interest. Various ILs have been observed in the dentin-pulp complex of carious tooth in vivo. Methods: Tissue culture method was used for testing the effect of LTA and LPS on human odontoblasts. Enzymatic isolation technique was used to extract living odontoblasts for cell cultures. DNA microarray and quantitative PCR (qPCR) were used to characterize the changes in the expression profile of the tissue cultured odontoblasts. Laser microdissection was used to cut healthy and affected dentin and odontoblast layer directly under carious lesion for experiments. Cytokine array detecting 80 inflammatory cytokines was used to analyze the protein content of conditioned culture media as well as dentin and odontoblasts from the carious teeth. Results: LPS caused increased gene expression IL-1α, and -8 and decrease of IL-1β, 12 , -15 and -16 after 1h treatment, while after 24h treatment decrease of IL-8, -11 and 23 mRNAs was observed. LTA treatment caused cell death in the tissue cultured odontoblasts but in in the cell culture but not in cell culture. Cytokine array revealed at least 2-fold down-regulation of IL-1β, -10 and -12 in response to LPS treatment. Cytokine array of odontoblasts of carious teeth, as well as LPS-treated tissue-cultured odontoblasts, revealed increased protein amounts of IL-16, epidermal growth factor (EGF), angiogenin and IGFBP-1 as well as decreased amount of fractalkine. In carious dentin, increased amount of IL-1β, EGF and fractalkine was observed, as well as decreased level of GRO-1 and HGF. Conclusion: LPS caused marked changes in the expression of inflammatory cytokines in odontoblasts. Similar changes were observed in the odontoblasts cut directly under the carious lesion. These results help to shed light on the inflammatory processes happening during caries.

Keywords: inflammation, interleukin, lipoteichoic acid, odontoblasts

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Authors: Wan-Ting Liao, Angela K. Tzeng

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Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: empathy, cognitive, emotional, psychopathy

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: Beloulou Mohamed Lamine, Fedili Benamar, Meliani Walid, Chaid Dalila, Lamara Abdelhak

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Introduction: Post-surgical chronic pain (PSCP) is a pathological condition with a rather complex etiopathogenesis that extensively involves sensitization processes and neuronal damage. The neuropathic component of these pains is almost always present, with variable expression depending on the type of surgery. Objective: To assess the presumed beneficial effect of Regional Anesthesia-Analgesia Techniques (RAAT) on the development of post-surgical chronic neuropathic pain (PSCNP) in various surgical procedures. Patients and Methods: A comparative study involving 510 patients distributed across five surgical models (mastectomy, thoracotomy, hernioplasty, cholecystectomy, and major abdominal-pelvic surgery) and randomized into two groups: Group A (240) receiving conventional postoperative analgesia and Group B (270) receiving balanced analgesia, including the implementation of a Regional Anesthesia-Analgesia Technique (RAAT). These patients were longitudinally followed over a 6-month period, with postsurgical chronic neuropathic pain (PSCNP) defined by a Neuropathic Pain Score DN2≥ 3. Comparative measurements through univariate and multivariable analyses were performed to identify associations between the development of PSCNP and certain predictive factors, including the presumed preventive impact (protective effect) of RAAT. Results: At the 6th month post-surgery, 419 patients were analyzed (Group A= 196 and Group B= 223). The incidence of PSCNP was 32.2% (n=135). Among these patients with chronic pain, the prevalence of neuropathic pain was 37.8% (95% CI: [29.6; 46.5]), with n=51/135. It was significantly lower in Group B compared to Group A, with respective percentages of 31.4% vs. 48.8% (p-value = 0.035). The most significant differences were observed in breast and thoracopulmonary surgeries. In a multiple regression analysis, two predictors of PSCNP were identified: the presence of preoperative pain at the surgical site as a risk factor (OR: 3.198; 95% CI [1.326; 7.714]) and RAAT as a protective factor (OR: 0.408; 95% CI [0.173; 0.961]). Conclusion: The neuropathic component of PSCNP can be observed in different types of surgeries. Regional analgesia included in a multimodal approach to postoperative pain management has proven to be effective for acute pain and seems to have a preventive impact on the development of PSCNP and its neuropathic nature, particularly in surgeries that are more prone to chronicization.

Keywords: post-surgical chronic pain, post-surgical chronic neuropathic pain, regional anesthesia-analgesia techniques, neuropathic pain score DN2, preventive impact

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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