Search results for: sensory processing sensitivity

Authors: João Pedro Albino, Ana Cláudia Pires Ferreira de Lima

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Humanity has undergone a transformation from the physical to the virtual world, generating an enormous amount of data on the world wide web, known as big data. Many facts that occur in the physical world or in the digital world are proven through records made on the internet, such as digital photographs, posts on social media, contract acceptances by digital platforms, email, banking, and messaging applications, among others. These data recorded on the internet have been used as evidence in judicial proceedings. The identification of internet users is essential for the security of legal relationships. This research was carried out on scientific articles and materials from courses and lectures, with an analysis of Brazilian legislation and some judicial decisions on the request of static data from logs and Internet Protocols (IPs) from application and connection providers. In this article, we will address the determination of authorship of data processing on the internet by obtaining the IP address and the appropriate judicial procedure for this purpose under Brazilian law.

Keywords: IP address, digital forensics, big data, data analytics, information and communication technology

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Authors: Yu-Ting Wang, Yun-Hsiang Cheng, Chien-Cheng Lin, Kun-Lin Lin

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Using a transient liquid phase method, Al was successfully bonded with Al₂O₃, which deposited Ni, Cu, Ge, and Si at the surface of the Al₂O₃ substrate after annealing at the relatively low melting point of Al. No reaction interlayer existed at the interface of any Al/Al₂O₃ specimens. Al−Fe intermetallic compounds, such as Al₉Fe₂ and Al₃Fe, formed in the Al substrate because of the precipitation of Fe, which was an impurity of the Al foil, and the reaction with Al at the grain boundaries of Al during annealing processing. According to the evaluation results of mechanical and thermal properties, the Al/Al₂O₃ specimen deposited on the Ni film possessed the highest shear strength, thermal conductivity, and bonding area percentage, followed by the Cu, Ge, and Si films. The properties of the Al/Al₂O₃ specimens deposited with Ge and Si were relatively unsatisfactory, which could be because the deposited amorphous layers easily formed oxide, resulting in inferior adhesion between Al and Al₂O₃. Therefore, the optimal choice for use in high-power devices is Al/Al₂O₃, with the deposition of Ni film.

Keywords: direct-bonded aluminum, transient liquid phase, thermal conductivity, microstructures, shear strength

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Authors: Sakura Ganegama Bogodage, Andrew Yee Tat Leung

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This paper describes experimental, Computational Fluid Dynamics (CFD) and theoretical analysis of a cyclone performance, operated 1.0 g/m3 solid loading rate, at two different inlet velocities (5 m/s and 10 m/s). Comparing experimental results with theoretical and CFD simulation results, it is pronounced that the influence of solid in processing flow is significant than expected. Experimental studies based on gas- solid flows of cyclone separators are complicated as they required advanced sensitive measuring techniques, especially flow characteristics. Thus, CFD modelling and theoretical analysis are economical in analyzing cyclone separator performance but detailed clarifications of the application of these in cyclone separator performance evaluation is not yet discussed. The present study shows the limitations of influencing parameters of CFD and theoretical considerations, comparing experimental results and flow characteristics from CFD modelling.

Keywords: cyclone performance, inlet velocity, pressure drop, solid loading rate

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Authors: Radu Soflau, Lia-Ecaterina Oltean

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Background: Increasing evidence supports the efficacy of psychological interventions for psychosis. However, it is unclear which one of these interventions is most likely to address negative psychotic symptoms and related outcomes. We aimed to determine the relative efficacy of psychological and psychosocial interventions for negative symptoms, overall psychotic symptoms, and related outcomes. Methods: To attain this goal, we conducted a systematic review and network meta-analysis. We searched for potentially eligible trials in PubMed, EMBASE, PsycInfo, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases up until February 08, 2022. We included randomized controlled trials that investigated the efficacy of psychological for adults with psychosis. We excluded interventions for prodromal or “at risk” individuals, as well as patients with serious co-morbid medical or psychiatric conditions (others than depressive and/or anxiety disorders). Two researchers conducted study selection and performed data extraction independently. Analyses were run using STATA network and mvmeta packages, applying a random effect model under a frequentist framework in order to compute standardized mean differences or risk ratio. Findings: We identified 47844 records and screened 29466 records for eligibility. The majority of eligible interventions were delivered in addition to pharmacological treatment. Treatment as usual (TAU) was the most frequent common comparator. Theoretically driven psychological interventions generally outperformed TAU at post-test and follow-up, displaying small and small-to-medium effect sizes. A similar pattern of results emerged in sensitivity analyses focused on studies that employed an inclusion criterion for relevant negative symptom severity. Conclusion: While the efficacy of some psychological interventions is promising, there is a need for more high-quality studies, as well as more trials directly comparing psychological treatments for negative psychotic symptoms.

Keywords: psychosis, network meta-analysis, psychological interventions, efficacy, negative symptoms

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Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

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Authors: Mohammad S. Rouhi, Magdalena Juntikka

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Processing of polymer fiber composites has a remarkable influence on their mechanical performance. These mechanical properties are even more influenced when using recycled reinforcement. Therefore, we place particular attention on the evaluation of micromechanical models to estimate the mechanical properties and compare them against the experimental results of the manufactured composites. For the manufacturing process, an epoxy matrix and carbon fiber production cut-offs as reinforcing material are incorporated using a vacuum infusion process. In addition, continuous textile reinforcement in combination with the epoxy matrix is used as reference material to evaluate the kick-down in mechanical performance of the recycled composite. The experimental results show less degradation of the composite stiffness compared to the strength properties. Observations from the modeling also show the same trend as the error between the theoretical and experimental results is lower for stiffness comparisons than the strength calculations. Yet still, good mechanical performance for specific applications can be expected from these materials.

Keywords: composite recycling, carbon fibers, mechanical properties, micromechanics

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Authors: Diana G. Ramirez-Wong, Marius Ramirez, Regina Sanchez-Leija, Adriana Rugerio, R. Araceli Mauricio-Sanchez, Martin A. Hernandez-Landaverde, Arturo Carranza, John A. Pojman, Josue D. Mota-Morales, Gabriel Luna-Barcenas

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Chitin films were prepared using alpha-chitin from shrimp shells as raw material and a simple method of precipitation-evaporation. Choline chloride: urea Deep Eutectic Solvent (DES) was used to disperse chitin and compared against hexafluoroisopropanol (HFIP). A careful analysis of the chemical and crystalline structure was followed along the synthesis of the films, revealing crystalline-phase transitions. The full conversion of alpha- to beta-, or alpha- to gamma-chitin structure were detected by XRD and NMR on the films. The synthesis of highly crystalline monophasic gamma-chitin films was achieved using a DES; whereas HFIP helps to promote the beta-phase. These results are encouraging to continue in the study of DES as good processing media to control the final properties of chitin based materials.

Keywords: chitin, deep eutectic solvent, polymorph, phase transformation

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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Authors: Melissa C. Monney

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Psychological testing has been of interest to researchers for many years as useful tools in assessing and diagnosing various disorders as well as to assist in understanding human behavior. However, for over 20 years now, researchers and laypersons alike have been interested in using them for other purposes, such as determining factors in employee selection, promotion, and even termination. In recent years, psychological assessments have been useful in facilitating workplace decision processing, regarding employee circulation within organizations. This literature review explores four of the most commonly used psychological tests in workplace environments, namely cognitive ability, emotional intelligence, integrity, and personality tests, as organizations have used these tests to assess different factors of human behavior as predictive measures of future employee behaviors. The findings suggest that while there is much controversy and debate regarding the validity and reliability of these tests in workplace settings as they were not originally designed for these purposes, the use of such assessments in the workplace has been useful in decreasing costs and employee turnover as well as increase job satisfaction by ensuring the right employees are selected for their roles.

Keywords: cognitive ability, personality testing, predictive validity, workplace behavior

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: Cesar Maximo Oliva González, Javier Acevedo Cortez, Boris Kharisov, Thelma Serrano Quezada

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The importance of the crude oil refining process is due to the demand for petroleum products such as gasoline, kerosene, asphalt, etc., which are used in daily activities and have a high impact on the global economy. In the processes of oil obtaining and refining, it is common to find problems such as spills on seabed and high energy consumption in processing. In order to quickly and efficiently attack these problems, the use of adsorbents has taken on great importance due to its ease of implementation, as well as the possibility of their regeneration to be reused. In this work, the use of two types of adsorbents is proposed: the first is a natural adsorbent such as aloe vera or nopal, which were lyophilized and hydrophobized to achieve a selectivity in oil adsorption in oil / water mixtures. The second is a mixed iron/nickel oxide, which is specially designed to adsorb the asphaltenes in the heavy fractions of the oil; in addition, this type of adsorbents presents catalytic properties that manage to decompose the heavier fractions of the petroleum in light hydrocarbons, descending thus the energy required for the oil refining process.

Keywords: nanomaterials, oil spills, remediation, natural adsorbents, mixed oxides

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Authors: Chattrarat Hotrawaisaya

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This research aims to formulate the logistics collaborative model which is the management tool for orchid flower exporter. The researchers study logistics activities in orchid supply chain that stakeholders can collaborate and develop, including demand forecasting, inventory management, warehouse and storage, order-processing, and transportation management. The research also explores logistics collaboration implementation into orchid’s stakeholders. The researcher collected data before implementation and after model implementation. Consequently, the costs and efficiency were calculated and compared between pre and post period of implementation. The research found that the results of applying the logistics collaborative model to orchid exporter reduces inventory cost and transport cost. The model also improves forecasting accuracy, and synchronizes supply chain of exporter. This research paper contributes the uniqueness logistics collaborative model which value to orchid industry in Thailand. The orchid exporters may use this model as their management tool which aims in competitive advantage.

Keywords: logistics, orchid, supply chain, collaboration

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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: Qingsheng Qi, Cuijuan Gao, Carol Sze Ki Lin

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Food waste can be defined as a by-product of food processing by industries and consumers, which has not been recycled or used for other purposes. Stringent waste regulations worldwide are pushing local companies and sectors towards higher sustainability standards. The development of novel strategies for food waste re-use is economically and environmentally sound, as it solves a waste management issue and represents an inexpensive nutrient source for biotechnological processes. For example, Yarrowia lipolytica is a yeast which can utilize hydrophobic substrates, such as fatty acids, lipids, and alkanes and simple carbon sources, such as glucose and glycerol, which can all be found in food waste. This broad substrate range makes Y. lipolytica a promising candidate for the degradation and valorisation of food waste, and for the production of organic acids, such as citric and α-ketoglutaric acids. Current research conducted in our group demonstrated that Y. lipolytica was shown to be able to produce succinic acid. In this talk, we will focus on the application of genetically modified yeast Y. lipolytica for fermentative succinic acid production with an aim to increase productivity and yield.

Keywords: food waste, succinic acid, Yarrowia lipolytica, bioplastic

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

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In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

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Authors: Adel Alblihy, Reem Ali, Mashael Algethami, Ahmed Shoqafi, Michael S. Toss, Juliette Brownlie, Natalie J. Tatum, Ian Hickson, Paloma Ordonez Moran, Anna Grabowska, Jennie N. Jeyapalan, Nigel P. Mongan, Emad A. Rakha, Srinivasan Madhusudan

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Platinum resistance is a clinical challenge in ovarian cancer. Platinating agents induce DNA damage which activate Mre11 nuclease directed DNA damage signalling and response (DDR). Upregulation of DDR may promote chemotherapy resistance. Here we have comprehensively evaluated Mre11 in epithelial ovarian cancers. In clinical cohort that received platinum- based chemotherapy (n=331), Mre11 protein overexpression was associated with aggressive phenotype and poor progression free survival (PFS) (p=0.002). In the ovarian cancer genome atlas (TCGA) cohort (n=498), Mre11 gene amplification was observed in a subset of serous tumours (5%) which correlated highly with Mre11 mRNA levels (p<0.0001). Altered Mre11 levels was linked with genome wide alterations that can influence platinum sensitivity. At the transcriptomic level (n=1259), Mre11 overexpression was associated with poor PFS (p=0.003). ROC analysis showed an area under the curve (AUC) of 0.642 for response to platinum-based chemotherapy. Pre-clinically, Mre11 depletion by gene knock down or blockade by small molecule inhibitor (Mirin) reversed platinum resistance in ovarian cancer cells and in 3D spheroid models. Importantly, Mre11 inhibition was synthetically lethal in platinum sensitive XRCC1 deficient ovarian cancer cells and 3D-spheroids. Selective cytotoxicity was associated with DNA double strand break (DSB) accumulation, S-phase cell cycle arrest and increased apoptosis. We conclude that pharmaceutical development of Mre11 inhibitors is a viable clinical strategy for platinum sensitization and synthetic lethality in ovarian cancer.

Keywords: MRE11; XRCC1, ovarian cancer, platinum sensitization, synthetic lethality

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Authors: Daniel Monsalve, Takafumi Noguchi

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Mycelium-based composites (MBC) are made by growing living mycelium on lignocellulosic fibres to create a porous composite material which can be lightweight, and biodegradable, making them suitable as a sustainable thermal insulation. Thus, they can help to reduce material extraction while improving the energy efficiency of buildings, especially when agricultural by-products are used. However, as MBC are hygroscopic materials, moisture can reduce their thermal insulation efficiency. It is known that surface growth, or “mycelium skin”, can form a natural coating due to the hydrophobic properties in the mycelium cell wall. Therefore, this research aims to biofabricate a homogeneous mycelium skin and measure its influence on the final composite material by testing material properties such as thermal conductivity, vapour permeability and water absorption by partial immersion over 24 hours. In addition, porosity, surface morphology and chemical composition were also analyzed. The white-rot fungi species Pleurotus ostreatus, Ganoderma lucidum, and Trametes versicolor were grown on 10 mm hemp fibres (Cannabis sativa), and three different biofabrication protocols were used during incubation, varying the time and surface treatment, including the addition of pre-colonised sawdust. The results indicate that density can be reduced by colonisation time, which will favourably impact thermal conductivity but will negatively affect vapour and liquid water control. Additionally, different fungi can exhibit different resistance to prolonged water absorption, and due to osmotic sensitivity, mycelium skin may also diminish moisture control. Finally, a collapse in the mycelium network after water immersion was observed through SEM, indicating how the microstructure is affected, which is also dependent on fungi species and the type of skin achieved. These results help to comprehend the differences and limitations of three of the most common species used for MBC fabrication and how precise engineering is needed to effectively control the material output.

Keywords: mycelium, thermal conductivity, vapor permeability, water absorption

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Authors: Oktavian Prasetia Wardana, Martono Tri Utomo, Risa Etika, Kartika Darma Handayani, Dina Angelika, Wurry Ayuningtyas

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Background: Critically ill neonates are newborn babies with high-risk factors that potentially cause disability and/or death. Scoring systems for determining the severity of the disease have been widely developed as well as some designs for use in neonates. The SNAPPE-II method, which has been used as a mortality predictor scoring system in several referral centers, was found to be slow in assessing the outcome of critically ill neonates in the Neonatal Intensive Care Unit (NICU). Objective: To analyze the predictive value of MSNS on the outcome of critically ill neonates at the time of arrival up to 24 hours after being admitted to the NICU. Methods: A longitudinal observational analytic study based on medical record data was conducted from January to August 2022. Each sample was recorded from medical record data, including data on gestational age, mode of delivery, APGAR score at birth, resuscitation measures at birth, duration of resuscitation, post-resuscitation ventilation, physical examination at birth (including vital signs and any congenital abnormalities), the results of routine laboratory examinations, as well as the neonatal outcomes. Results: This study involved 105 critically ill neonates who were admitted to the NICU. The outcome of critically ill neonates was 50 (47.6%) neonates died, and 55 (52.4%) neonates lived. There were more males than females (61% vs. 39%). The mean gestational age of the subjects in this study was 33.8 ± 4.28 weeks, with the mean birth weight of the subjects being 1820.31 ± 33.18 g. The mean MSNS score of neonates with a deadly outcome was lower than that of the lived outcome. ROC curve with a cut point MSNS score <10.5 obtained an AUC of 93.5% (95% CI: 88.3-98.6) with a sensitivity value of 84% (95% CI: 80.5-94.9), specificity 80 % (CI 95%: 88.3-98.6), Positive Predictive Value (PPV) 79.2%, Negative Predictive Value (NPV) 84.6%, Risk Ratio (RR) 5.14 with Hosmer & Lemeshow test results p>0.05. Conclusion: The MSNS score has a good predictive value and good calibration of the outcomes of critically ill neonates admitted to the NICU.

Keywords: critically ill neonate, outcome, MSNS, NICU, predictive value

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Authors: Tarantino E., Disciglio G., Gagliardi A., Gatta G., Tarantino A.

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Fertilizer is a critical input for improving production and increasing crop yields. Consecutive experimental trials during six years (from 2010-2015) were carried out in Apulia region (south-eastern Italy) on seven crops grown in cylinder pots. The aim was to determinate the effects of chemical and organic fertilizer on marketable yield and other parameters of processing tomato (Lycopersicum esculentum L., cv Docet), lettuce (Lactuca sativa L., cv Canasta), cauliflower (Brassica oleracea L., cv Casper), pepper (Capsicum annum L., cv Akron), fennel (Foeniculum vulgare L., cv Tarquinia), eggplant (Solanum melongena L. cv Primato F1) and chard (Beta vulgaris L., Argentata). At harvest the quail-quantitative yield characteristics of each crop were determined. All of the experimental data were subjected to analysis of variance (ANOVA). Results showed that the yields for all of these crops were greater under the chemical system than the organic system whereas quite variable results were generally observed for the other characteristics of the yield.

Keywords: fertilizers, herbaceous crops, yield characteristics, succession

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Authors: Eylem G. Cengiz, Ersin Çilek, Gözde Başkaya, Havva Nur Taş

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It is possible to define the abuse and neglect of the child as a social problem. Such adverse experiences of the child are witnessed by wider social circles as well as his or her immediate environment. The most effective institution among these social circles is the school. The awareness of teachers, administrators, and even auxiliary personnel on this issue can act as a protective and preventive buffer because teachers have the opportunity to be with children every day and constantly observe them; therefore, they can notice the physical and mental changes in students. Furthermore, school administrators have an undeniable role in recognizing and responding to the risk of neglect and abuse. This study aims to evaluate the awareness of school administrators on the risk factors, clues, and ways of intervention towards abuse and neglect through the scenarios given to them. Data were collected from 37 primary, secondary, and high school administrators working in various provinces of Turkey through descriptive and scenario-based questions to determine their general knowledge of the concepts of neglect and abuse and their general tendencies towards practice. Descriptive questions were evaluated with content analysis, and scenario-based questions were evaluated with numerical qualitative data analysis. Concepts and themes were tried to be reached by content analysis from the descriptive data collected. When the results are evaluated in general, it is striking that the concept of child abuse means only sexual abuse for some school administrators. There is an important uncertainty for school administrators in the content of the idea of neglect. When the views on the causes of neglect and abuse are examined, the family factor was seen as the primary source of both neglect and abuse. In addition, among the prevention strategies applied by school administrators, intervention for the family -interviewing and informing- was recommended by only 9 (29%) out of 31 administrators. When the responses to the physical, emotional, and sexual abuse scenarios are examined, it is revealed that the administrators generally realize the abuse but fail to develop an appropriate/whole intervention method. The research results show that school administrators' awareness should be increased. Although administrators have sensitivity towards children, they should be empowered to recognize all types of neglect and abuse and develop appropriate intervention tools.

Keywords: assessment child abuse and neglect, child abuse, child neglect, school administrators

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Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

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Authors: Angsumalin Puntho

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Disruptive technology has had a great influence on our everyday lives and the existence of an organization. Geologists in the public sector need to keep up with digital technology and be able to work and collaborate in a more effective manner. The result from SWOT and 7S McKinsey analyses suggest that there are inadequate IT personnel, no individual digital literacy development plan, and a misunderstanding of management policies. The Office of Civil Service Commission develops digital literacy skills that civil servants and government officers should possess in order to work effectively; it consists of nine dimensions, including computer skills, internet skills, cyber security awareness, word processing, spreadsheets, presentation programs, online collaboration, graphics editors and cyber security practices; and six steps of digital literacy development including self-assessment, individual development plan, self-learning, certified test, learning reflection, and practices. Geologists can use digital literacy as a learning tool to develop themselves for better career opportunities.

Keywords: disruptive technology, digital technology, digital literacy, computer skills

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Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

Abstract:

Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference

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Authors: Leyli Khavari, Javad Yousefian

Abstract:

The aim of this study was to investigate the effect of physical biorhythm cycle on health-related fitness factors. For this purpose, 120 athlete and non-athlete male and female students were selected randomly and based on the level of physical activity divided into athletic and non-athletic groups. The exact date of birth and also when the subjects were in the positive, negative and critical physical biorhythm cycle was determined by calculation software biorhythm. The physical fitness factors tests, including Queens College Step Test, AAHPERD sit-ups; Wells stretch test and hand dynamometer. Students in three stages in positive, negative and critical physical cycle were tested. Data processing using SPSS software and statistical tests ANOVA with repeated measures and student t test was used for dependent. The results of this study showed that changes in physical fitness and physical biorhythm were not affected by changes in the 23-day physical cycle.

Keywords: AAHPERD test, biorhythm, physical cycle, Queens College Step Test

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

Abstract:

Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

Procedia PDF Downloads 453

Authors: Fei Sun, Meilan Xu, Jianghui Zhu, Maria Stefanie Dwiyanti, Cheolwoo Park, Fanjiang Kong, Baohui Liu, Tetsuya Yamada, Jun Abe

Abstract:

Reduced or lack of sensitivity to long daylengths is a key character for soybean, a short-day crop, to adapt to higher latitudinal environments. However, the photoperiod-insensitivity often results in a reduction of the duration of vegetative growth and final yield. To overcome this limitation, a photoperiod insensitive line (RIL16) was developed in this study that delayed flowering from the recombinant inbred population derived from a cross between a photoperiod-insensitive cultivar AGS292 and a late-flowering Thai cultivar K3. Expression analyses under SD and LD conditions revealed that the expression levels of FLOWERING LOCUS T (FT) orthologues, FT2a and FT5a, were lowered in RIL16 relative to AGS292, although the expression of E1, a soybean-specific suppressor for FTs, was inhibited in both conditions. A soybean orthologue of TARGET OF EAT1 (TOE1), another suppressor of FT, showed an upregulated expression in RIL16, which appeared to reflect a lower expression of miR172a. Our data suggest that the delayed flowering of RIL16 most likely is controlled by genes involved in an age-dependent pathway in flowering. The QTL analysis based on 1,125 SNPs obtained from Restriction Site Associated DNA Sequencing revealed two major QTLs for flowering dates in Chromosome 16 and two minor QTLs in Chromosome 4, all of which accounted for 55% and 48% of the whole variations observed in natural day length and artificially-induced long day length conditions, respectively. The intervals of the major QTLs harbored FT2a and FT5a, respectively, on the basis of annotated genes in the Williams 82 reference genome. Sequencing analysis further revealed a nonsynonymous mutation in FT2a and an SNP in the 3′ UTR region of FT5a. A further study may elucidate a detailed mechanism underlying the QTL for late flowering. The alleles from K3 at the two QTLs can be used singly or in combination to retain an appropriate duration of vegetative growth to maximize the final yield of photoperiod-insensitive soybeans.

Keywords: FT genes, miR72a, photoperiod-insensitive, soybean flowering

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

Abstract:

In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Abdelhadi Adel, Kadri Ouahab

Abstract:

This paper proposes an improved approach based on MAS Architecture and Heuristic Algorithm for systematic maintenance to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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Authors: M. P. Tripathi, Priti Tiwari

Abstract:

Soil and Water Assessment Tool (SWAT) is a distributed parameter continuous time model and was tested on daily and fortnightly basis for a small agricultural watershed (Dhangaon) of Chhattisgarh state in India. The SWAT model recently interfaced with ArcGIS and called as ArcSWAT. The watershed and sub-watershed boundaries, drainage networks, slope and texture maps were generated in the environment of ArcGIS of ArcSWAT. Supervised classification method was used for land use/cover classification from satellite imageries of the years 2009 and 2012. Manning's roughness coefficient 'n' for overland flow and channel flow and Fraction of Field Capacity (FFC) were calibrated for monsoon season of the years 2009 and 2010. The model was validated on a daily basis for the years 2011 and 2012 by using the observed daily rainfall and temperature data. Calibration and validation results revealed that the model was predicting the daily surface runoff and sediment yield satisfactorily. Sensitivity analysis showed that the annual sediment yield was inversely proportional to the overland and channel 'n' values whereas; annual runoff and sediment yields were directly proportional to the FFC. The model was also tested (calibrated and validated) for the fortnightly runoff and sediment yield for the year 2009-10 and 2011-12, respectively. Simulated values of fortnightly runoff and sediment yield for the calibration and validation years compared well with their observed counterparts. The calibration and validation results revealed that the ArcSWAT model could be used for identification of critical sub-watershed and for developing management scenarios for the Dhangaon watershed. Further, the model should be tested for simulating the surface runoff and sediment yield using generated rainfall and temperature before applying it for developing the management scenario for the critical or priority sub-watersheds.

Keywords: watershed, hydrologic and water quality, ArcSWAT model, remote sensing, GIS, runoff and sediment yield

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Authors: G. Cunningham, E. Cantor, X. Wu, F. Shen, G. Jiang, S. Philips, C. Bales, Y. Xiao, T. R. Cummins, J. C. Fehrenbacher, B. P. Schneider

Abstract:

Background: Taxane-induced peripheral neuropathy (TIPN) is the most devastating survivorship issue for patients receiving therapy. Dose reductions due to TIPN in the curative setting lead to inferior outcomes for African American patients, as prior research has shown that this group is more susceptible to developing severe neuropathy. The mechanistic underpinnings of TIPN, however, have not been entirely elucidated. While it would be appealing to use primary tissue to study the development of TIPN, procuring nerves from patients is not realistically feasible, as nerve biopsies are painful and may result in permanent damage. Therefore, our laboratory has investigated paclitaxel-induced neuronal morphological and molecular changes using an ex vivo model of human-induced pluripotent stem cell (iPSC)-derived neurons. Methods: iPSCs are undifferentiated and endlessly dividing cells that can be generated from a patient’s somatic cells, such as peripheral blood mononuclear cells (PBMCs). We successfully reprogrammed PBMCs into iPSCs using the Erythroid Progenitor Reprograming Kit (STEMCell Technologiesᵀᴹ); pluripotency was verified by flow cytometry analysis. iPSCs were then induced into neurons using a differentiation protocol that bypasses the neural progenitor stage and uses selected small-molecule modulators of key signaling pathways (SMAD, Notch, FGFR1 inhibition, and Wnt activation). Results: Flow cytometry analysis revealed expression of core pluripotency transcription factors Nanog, Oct3/4 and Sox2 in iPSCs overlaps with commercially purchased pluripotent cell line UCSD064i-20-2. Trilineage differentiation of iPSCs was confirmed with immunofluorescent imaging with germ-layer-specific markers; Sox17 and ExoA2 for ectoderm, Nestin, and Pax6 for mesoderm, and Ncam and Brachyury for endoderm. Sensory neuron markers, β-III tubulin, and Peripherin were applied to stain the cells for the maturity of iPSC-derived neurons. Patch-clamp electrophysiology and calcitonin gene-related peptide (CGRP) release data supported the functionality of the induced neurons and provided insight into the timing for which downstream assays could be performed (week 4 post-induction). We have also performed a cell viability assay and fluorescence-activated cell sorting (FACS) using four cell-surface markers (CD184, CD44, CD15, and CD24) to select a neuronal population. At least 70% of the cells were viable in the isolated neuron population. Conclusion: We have found that these iPSC-derived neurons recapitulate mature neuronal phenotypes and demonstrate functionality. Thus, this represents a patient-derived ex vivo neuronal model to investigate the molecular mechanisms of clinical TIPN.

Keywords: chemotherapy, iPSC-derived neurons, peripheral neuropathy, taxane, paclitaxel

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