Search results for: combined capture

Authors: Linghua Kong, Xinxia Chen, Mika Gissler, Catharina Lavebratt

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Background: Prenatal exposure to preeclampsia has been associated with an increased risk of offspring attention-deficit/hyperactivity disorders (ADHD), autism spectrum disorder (ASD), and intellectual disability. However, little is known about the association between prenatal exposure to severe preeclampsia and neurodevelopmental and psychiatric disorders in offspring. Objective: This study aimed to assess the risk of maternal preeclampsia combined with perinatal problems, specifically low birth weight and prematurity, on offspring neuropsychiatric disorders. Methods: All singleton live births in Finland between 1996 and 2014 (n=1 012 723) were followed up in nation-wide registries until 2018. Main exposures included pre-eclampsia, small for gestational age, and delivery before 34 gestational weeks. Offspring neurodevelopmental and psychiatric disorders (ICD-10 codes) were examined as outcomes variables. Offspring birth year, sex, maternal age at delivery, parity, marital status at birth, mother's country of birth, maternal smoking, maternal gestational diabetes, maternal use of psychotropic medication during pregnancy, and maternal systemic inflammatory diseases were used as covariates. Risks for neurodevelopmental and psychiatric disorders were estimated using Cox proportional hazards modeling. Results: Of the 1 012 723 offspring, 25 901 (2.6%) were exposed to preeclampsia, and 93 281 (9.2%) were diagnosed with a neuropsychiatric disorder. Compared to births unexposed to preeclampsia, small for gestational age or delivery before 34 gestational weeks, those exposed to preeclampsia only had a 21% increase in the likelihood of any neuropsychiatric disorders after adjusting for potential confounding (adjusted HR=1.21, 95% CI: 1.15-1.26), while exposure to preeclampsia combined with small for gestational age or delivery before 34 gestational weeks had a more than twofold increased risk of having a child with neuropsychiatric disorders (adjusted HR=2.16, 95% CI: 2.02-2.32). The adjusted HR for neuropsychiatric disorders in offspring with small for gestational age or delivery before 34 gestational weeks only was 1.79 (95% CI: 1.73-1.83). In addition, the risk estimate in offspring exposed to both preeclampsia and perinatal problems was greater than those only exposed to preeclampsia for having personality disorders (adjusted HR=1.66; 95% CI: 1.07-2.57), intellectual disabilities (adjusted HR=3.47; 95% CI: 2.86-4.22), specific developmental disorders (adjusted HR=2.91; 95% CI: 2.69-3.15), ASD (adjusted HR=1.75; 95% CI: 1.42-2.17), ADHD and conduct disorders (adjusted HR=2.00; 95%CI: 1.76-2.27), and other behavioral and emotional disorders (adjusted HR=2.09; 95% CI: 1.84-2.37). Conclusion: In utero exposure to severe preeclampsia increased the risk of several neurodevelopmental and psychiatric disorders in offspring. Our findings are relevant to women with hypertensive disorders with regard to pregnancy consultation and management and may yield effective clues for the prevention of neurodevelopmental and psychiatric disorders in childhood.

Keywords: low birth weight, neurodevelopmental disorders, preeclampsia, prematurity, psychiatric disorders

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

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This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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Authors: Ibrahim Aly, Waleed Elawamy, Hanan Taher, Amira Matar

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Schistosomiasis is infection with blood flukes of the genus Schistosoma, which are acquired trans-cutaneously by swimming or wading in contaminated freshwater. The present study was proposed to produce ultra-sensitive, field-friendly high-throughput rapid immunochromatography diagnostic device for accurate detection of asymptomatic parasite carriers in schistosomiasis pre-elimination settings.For assessing diagnostic potential of rapid device, 50 blood samples from patients with schistosomiasis mansoni, 29 other proven parasitic diseases and 25 blood samples as negative control were from healthy individuals were used. The sensitivity of Quantitative antigen-capture nano-ELISAwas 82 %, and specificity was 87.1 %, where the sensitivity of Nano Dot- ELISA was 86 % and specificity was 90.7 %. The sensitivity of diagnostic device was 78 % and specificity was 85.2 %, with PPV and NPV of 86.2 % and 83.1 %, respectively.The Point of care device resulted in a good performance for the diagnosis of low-intensity infections, it was able to identify 19 out of 25 (76 %) individuals with ⩽7 eggs, 10 out of 14 individuals (71.4 %) with 11–99 eggs and 100 % of individuals with 100–399 eggs.

Keywords: schistosomiasis, immunochromatography, naon-dot-ELISa, diagnostis device

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Authors: H. Tédjini, Y. Meslem, B. Guesbaoui, A. Safa

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Flexible AC Transmission Systems (FACTS) are potentially becoming more flexible and more economical local controllers in the power system; and because of the high MVA ratings, it would be expensive to provide independent, equal, regulated DC voltage sources to power the multilevel converters which are presently proposed for STATCOMs. DC voltage sources can be derived from the DC link capacitances which are charged by the rectified ac power. In this paper a new stronger control combined of nonlinear control based Lyapunov’s theorem and Ant Colony Algorithm (ACA) to maintain stability of multilevel STATCOM and the utility.

Keywords: Static Compensator (STATCOM), ant colony optimization (ACO), lyapunov control theory, Decoupled power control, neutral point clamped (NPC)

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Authors: Sneha Noble, Rahul Krishnan, Uma G., D. K. Vijaykumar

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Breast-Cancer related Lymphedema is a major problem that affects many women. Lymphedema is the swelling that generally occurs in the arms or legs caused by the removal of or damage to lymph nodes as a part of cancer treatment. Treating it at the earliest possible stage is the best way to manage the condition and prevent it from leading to pain, recurrent infection, reduced mobility, and impaired function. So, this project aims to focus on the multi-modal approaches to identify the risks of Lymphedema in post-surgical oncology patients and prevent it at the earliest. The Kinect IR Sensor is utilized to capture the images of the body and after image processing techniques, the region of interest is obtained. Then, performing the voxelization method will provide volume measurements in pre-operative and post-operative periods in patients. The formation of a mathematical model will help in the comparison of values. Clinical pathological data of patients will be investigated to assess the factors responsible for the development of lymphedema and its risks.

Keywords: Kinect IR sensor, Lymphedema, voxelization, lymph nodes

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Authors: Gowtham Kalkere Jayanna, Mohamad Nazri Husin

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Graph theory, chemistry, and technology are all combined in cheminformatics. The structure and physiochemical properties of organic substances are linked using some useful graph invariants and the corresponding molecular graph. In this paper, we study specific reverse topological indices such as the reverse sum-connectivity index, the reverse Zagreb index, the reverse arithmetic-geometric, and the geometric-arithmetic, the reverse Sombor, the reverse Nirmala indices for the bistar graphs B (n: m) and the corona product Kₘ∘Kₙ', where Kₙ' Represent the complement of a complete graph Kₙ.

Keywords: reverse topological indices, bistar graph, the corona product, graph

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Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

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Authors: Feng-Hisang Lai

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CFD(Computational Fluid Dynamics) is conducted to numerically study the flow and heat transfer features of a two-pole, 6,080HP, 60Hz, 3,150V open drip-proof (ODP) motor. The stator and rotor cores in this high voltage induction motor are segmented with the use of spacers for cooling purposes, which leads to difficulties in meshing when the entire system is to be simulated. The system is divided into 4 parts, meshed separately and then combined using interfaces. The deviation between the CFD and experimental results in temperature and flow rate is less than 10%. The internal flow is further examined and a final design is proposed to reduce the winding temperature by 10 degrees.

Keywords: CFD, open drip proof, induction motor, cooling

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Daphne Meza, Louie Abejar, David A. Rubenstein, Wei Yin

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Endothelial cell (ECs) morphology and function is highly impacted by the mechanical stresses these cells experience in vivo. Any change in the mechanical environment can trigger pathological EC responses. A detailed understanding of EC morphological response and function upon subjection to individual and simultaneous mechanical stimuli is needed for advancement in mechanobiology and preventive medicine. To investigate this, a programmable device capable of simultaneously applying physiological fluid shear stress (FSS) and cyclic strain (CS) has been developed, characterized and validated. Its validation was performed both experimentally, through tracer tracking, and theoretically, through the use of a computational fluid dynamics model. The effectiveness of the device was evaluated through EC morphology changes under mechanical loading conditions. Changes in cell morphology were evaluated through: cell and nucleus elongation, cell alignment and junctional actin production. The results demonstrated that the combined FSS-CS stimulation induced visible changes in EC morphology. Upon simultaneous fluid shear stress and biaxial tensile strain stimulation, cells were elongated and generally aligned with the flow direction, with stress fibers highlighted along the cell junctions. The concurrent stimulation from shear stress and biaxial cyclic stretch led to a significant increase in cell elongation compared to untreated cells. This, however, was significantly lower than that induced by shear stress alone, indicating that the biaxial tensile strain may counteract the elongating effect of shear stress to maintain the shape of ECs. A similar trend was seen in alignment, where the alignment induced by the concurrent application of shear stress and cyclic stretch fell in between that induced by shear stress and tensile stretch alone, indicating the opposite role shear stress and tensile strain may play in cell alignment. Junctional actin accumulation was increased upon shear stress alone or simultaneously with tensile stretch. Tensile stretch alone did not change junctional actin accumulation, indicating the dominant role of shear stress in damaging EC junctions. These results demonstrate that the shearing-stretching device is capable of applying well characterized dynamic shear stress and tensile strain to cultured ECs. Using this device, EC response to altered mechanical environment in vivo can be characterized in vitro.

Keywords: cyclic stretch, endothelial cells, fluid shear stress, vascular biology

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Authors: Laila Oubahman, Duleba Szabolcs

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Public transport stakeholders aim to increase the ridership ratio by encouraging citizens to use common transportation modes. For this sight, improving service quality is a crucial option to reach the quality desired by users and reduce the gap between desired and perceived quality. Multi-criteria decision aid has been applied in literature in recent decades because it provides efficient models to assess the most impacting criteria on the overall assessment. In this paper, the PROMETHEE method is combined with the best-worst approach to construct a consensual model that avoids rank reversal to support stakeholders in ameliorating service quality.

Keywords: best-worst method, MCDA, PROMETHEE, public transport

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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Authors: Navab Karimi, Tohid Alizadeh

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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

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Authors: Nermin Isik, Ozlem Derinbay Ekici, Oguzhan Avci

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The aim of this study was to determination of role infection in neonatal calves in Central Anatolian, Turkey. A total 300 fecal samples were collected from diarrheic neonatal calves, aged between 0–90 days from Konya, Karaman, and Aksaray from January to April 2014. Fecal specimens from calves with clinically diarrheic symptoms were examined for the presence of Bovine Coronavirus, Bovine Rotavirus, Cryptosporidium sp., and E. coli by commercially available capture direct enzyme linked immunosorbent assay (ELISA) kit and Modified Ziehl Neelsen method (MZN). Calves were grouped according to their age as follows: 1-14, 15-29, and 30-90 days. Cryptosporidium sp. infection was detected in 52.8%, 58.8%, and 39.2% by ELISA and 33.9%, 47%, 26.7% by MZN in the respective age groups. The seroprevalance of Rotavirus (12.5 %, 40 %, 12.5 %), Coronavirus (2.5%, 0%, 3.5%) and E. coli (5%, 4.7%, 8.9%) infections were determined according to the age groups respectively. Cryptosporidium sp. was the most detected enteropathogen (52 %) of calves and coronavirus was the least detected (2 %). The detection rate of the mixed enfection was 12.3%. In conclusion, it must be evaluated by mix infections in calves with diarrhea. These results will provide an important contribution against the factors that cause diarrhea

Keywords: cryptosporidium sp., bovine coronavirus, bovine rotavirus, E.coli, calve, ELISA

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Authors: A. M. Sagir

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This paper derived four newly schemes which are combined in order to form an accurate and efficient block method for parallel or sequential solution of third order ordinary differential equations of the form y^'''= f(x,y,y^',y^'' ), y(α)=y_0,〖y〗^' (α)=β,y^('' ) (α)=μ with associated initial or boundary conditions. The implementation strategies of the derived method have shown that the block method is found to be consistent, zero stable and hence convergent. The derived schemes were tested on stiff and non-stiff ordinary differential equations, and the numerical results obtained compared favorably with the exact solution.

Keywords: block method, hybrid, linear multistep, self-starting, third order ordinary differential equations

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Authors: Isaac Kofi Mensah

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Public sector organizations, ministries, departments and local government agencies are adopting e-government as a means to provide efficient and quality service delivery to citizens. The purpose of this research paper is to examine the extent to which perceived usefulness (PU) of e-government services moderates between perceived ease-of-use (PEOU) of e-government services and intention to use (IU) e-government services in Ghana. A structured research questionnaire instrument was developed and administered to 700 potential respondents in Ghana, of which 693 responded, representing 99% of the questionnaires distributed. The Technology Acceptance Model (TAM) was used as the theoretical framework for the study. The Statistical Package for Social Science (SPSS) was used to capture and analyze the data. The results indicate that even though predictors such as PU and PEOU are main determiners of citizens’ intention to adopt and use e-government services in Ghana, it failed to show that PEOU and IU e-government services in Ghana is significantly moderated by the PU of e-government services. The implication of this finding on theory and practice is further discussed.

Keywords: e-government services, intention to use, moderating role, perceived ease of use, perceived usefulness, Ghana, technology acceptance model

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Authors: Tianfang Zhang, Luxi He, Zhengbin He, Songlin Yi

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Moso bamboo is a common non-wood forest resource in Asia that is widely used in construction, furniture, and other fields. Influenced by the heterogeneous structure and various hygroscopic groups of bamboo, the deformation occurs as moisture absorption and desorption when the environment temperature and humidity conditions change. Thermal modification is a well-established commercial technology for improving the dimensional stability of bamboo. However, the higher energy consumption and carbon emissions limit its further development. Previous studies have indicated that inorganic salt-assisted thermal modification could lead to significant reductions in moisture absorption and energy consumption. Represented by metal chlorides, it could show Lewis acid properties when dissolved in water, generating metal ion ligand complexes. In addition, ultrasonic treatment, as an efficient and environmentally friendly physical treatment method, improved the accessibility of pretreatment chemical impregnation agents and intensified mass and heat transfer during reactions. To save energy and reduce deformation, this study elucidates the influence of zinc chloride-ultrasonic treatment on the physicochemical properties of heat-treated bamboo, and the details of the bamboo deformation mechanism with Lewis acid are explained. Three sets of parameters (inorganic salt concentration, ultrasonic frequency and heat treatment temperature) were designed, and an optimized process was proposed to clarify this scientific question, that is: 5% (w/w) zinc chloride solution, 40 kHz ultrasonic waves and heat treatment at 160 °C. The samples were characterized by different means to analyze changes in their macroscopic features, pore structure, chemical structure and chemical composition. The results suggested that the maximum weight loss rate was reduced by at least 19.75%. The maximum thermal degradation peak of hemicellulose was significantly shifted forward. The hygroscopicity was reduced by 10.15%, the relative crystallinity was increased by 4.4%, the surface contact angle was increased by 25.2%, and the color change was increased by 23.60 in the optimal condition. From the electron microscope observation, the treated surface became rougher, and cracks appeared in some weaker areas, accelerating starch loss and removing granular attachments around the pits. By ion diffusion, zinc ions diffused into hemicellulose and a partial amorphous region of cellulose. Parts of the cell wall structure were subjected to swelling and degradation, leading to the broken state of parenchyma cells. From the Raman spectrum, compared to conventional thermal modifications, hemicellulose thermal degradation and lignin migration is promoted by Lewis acid under dilute acid-thermal condition. As shown in this work, the combined Lewis acid and ultrasonic pretreatment as an environmentally friendly, safe, and efficient physic-chemical combined pretreatment method improved the dimensional stability of Moso bamboo and lowered the thermal degradation conditions. This method has great potential for development in the field of bamboo heat treatment, and it might provide some guidance for making dark bamboo flooring.

Keywords: Moso bamboo, Lewis acid, ultrasound, heat treatment

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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Authors: Wu Chao

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The urban design of the new district in China is different from other existing cities at the city planning level, including Beijing, Shanghai, Guangzhou, etc. And the urban problems of these super-cities are same as many big cities around the world. The goal of the new district construction plan is to enable people to live comfortably, to improve the well-being of residents, and to create a way of life different from that of other urban communities. To avoid the emergence of the super community, the idea of "decentralization" is taken as the overall planning idea, and the function and form of each community are set up with a homogeneous allocation of resources so that the community can grow naturally. Similar to the growth of vines in nature, each community groups are independent and connected through roads, with clear community boundaries that limit their unlimited expansion. With a community contained 20,000 people as a case, the community is a mixture for living, production, office, entertainment, and other functions. Based on the development of the Internet, to create more space for public use, and can use data to allocate resources in real time. And this kind of shared space is the main part of the activity space in the community. At the same time, the transformation of spatial function can be determined by the usage feedback of all kinds of existing space, and the use of space can be changed by the changing data. Take the residential unit as the basic building function mass, take the lower three to four floors of the building as the main flexible space for use, distribute functions such as entertainment, service, office, etc. For the upper living space, set up a small amount of indoor and outdoor activity space, also used as shared space. The transformable space of the bottom layer is evenly distributed, combined with the walking space connected the community, the service and entertainment network can be formed in the whole community, and can be used in most of the community space. With the basic residential unit as the replicable module, the design of the other residential units runs through the idea of decentralization and the concept of the vine community, and the various units are reasonably combined. At the same time, a small number of office buildings are added to meet the special office needs. The new functional mixed community can change many problems of the present city in the future construction, at the same time, it can keep its vitality through the adjustment function of the Internet.

Keywords: decentralization, mixed functional community, shared space, spatial usage data

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Authors: J. Becker, R. Arnold

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The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structures. Combined with qualitative measures the decision support system will contribute to a more efficient design of distribution logistics.

Keywords: decision support system, distribution logistics, potential analyses, supply chain management

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Authors: Otana A. Jakpor

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Air pollution is without a doubt one of the gravest environmental threats the world is facing today in terms of its sheer toll on human lives. Each year an estimated 70,000 Americans lose their lives to air pollution -- a number equal to deaths from both breast and prostate cancer combined. Since Americans spend nearly 90% of their time indoors, more research is needed on indoor air pollution and common exposures such as candles. Paraffin wax is a by-product of petroleum, and similarities have been observed between fine particulate emissions from paraffin candles and diesel exhaust. The purpose of this study is to determine whether or not paraffin candles are a major potential source of indoor air pollution. Furthermore, this study aims to determine whether or not soy candles are a safer, cleaner alternative to paraffin candles.

Keywords: soy candle, soy, paraffin candle, paraffin

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Authors: Faizan Ahmad, Jenna Wong

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Time lag between peak values of horizontal and vertical seismic waves is a well-known phenomenon. Horizontal and vertical seismic waves, secondary and primary waves in nature respectively, travel through different layers of soil and the travel time is dependent upon the medium of wave transmission. In seismic analysis, many standardized codes do not require the actual vertical acceleration to be part of the analysis procedure. Instead, a factor load addition for a particular site is used to capture strength demands in case of vertical excitation. This study reviews the effects of vertical accelerations to analyze the behavior of a linearly rubber isolated structure in different time lag situations and frequency content by application of historical and simulated ground motions using SAP2000. The response of the structure is reviewed under multiple sets of ground motions and trends based on time lag and frequency variations are drawn. The accuracy of these results is discussed and evaluated to provide reasoning for use of real vertical excitations in seismic analysis procedures, especially for isolated structures.

Keywords: seismic analysis, vertical accelerations, time lag, isolated structures

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Authors: A. Vani, M. N. Mamatha

Abstract:

Visual signal processing in human beings occurs in the occipital lobe of the brain. The signals that are generated in the brain are universal for all the human beings and they are called Visual Evoked Potential (VEP). Generally, the visually impaired people lose sight because of severe damage to only the eyes natural photo sensors, but the occipital lobe will still be functioning. In this paper, a technique of artificially generating VEP is proposed to enhance the visual ability of the subject. The system uses the electrical photoreceptors to capture image, process the image, to detect and recognize the subject or object. This voltage is further processed and can transmit wirelessly to a BIOMEMS implanted into occipital lobe of the patient’s brain. The proposed BIOMEMS consists of array of electrodes that generate the neuron potential which is similar to VEP of normal people. Thus, the neurons get the visual data from the BioMEMS which helps in generating partial vision or sight for the visually challenged patient. 

Keywords: BioMEMS, neuro-prosthetic, openvibe, visual evoked potential

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Authors: Marwa Sahnoun, Chokri Abdennadher

Abstract:

This article comes, very timely, to look at the effectiveness of active labor market policies (ALMP) in improving labor market outcomes. Using panel data estimates for 19 European countries during the period 2000-2012, this article showed the role of institutional factors, especially the role of employment policies implementation based on three variables: the allocation of resources for the implementation of policies, continuity and timing in the implementation of policies to capture their effectiveness on the labor market. Empirical results shows favor effect of training, employment incentives, sheltered employment and rehabilitation and direct job creation on the entire population employment growth. Results shows also that start-up incentives seems to be more effective in increasing employment than other types of policies. Importantly, two aspects are important in terms of implementation: public expenditure on program administration, e.g. (PES) watches the most favorable aspect and the continuity of policies implemented.

Keywords: active labor market policies, implementation, public expenditure on program administration, start-up incentives, training

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Authors: Willy Mbenza, Sho Kenjiro

Abstract:

Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

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Authors: Francesco Coraci, Abdul-Hadi G. Abulrub

Abstract:

Digital technology is transforming the landscape of the industrial sector at a precedential level by connecting people, processes, and machines in real-time. It represents the means for a new pathway to achieve innovative, dynamic competitive advantages, deliver unique customers’ values, and sustain critical relationships. Thus, success in a constantly changing environment is governed by the ability of an organization to revolutionize their business models, deliver innovative solutions, and capture values from big data analytics and insights. Businesses need to re-strategize operations and develop extra capabilities to cope with the necessity for additional flexibility and agility. The traditional “command and control” leadership style is structurally and operationally incompatible with the digital era. In this paper, the authors discuss how transformational leaders can act as a glue in the social, organizational context, which is crucial to enable the workforce and develop a psychological attachment to the digital vision.

Keywords: internet of things, strategy, change leadership, dynamic competitive advantage, digital transformation

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Authors: Álvaro Ramírez Vidal, Martín Muñoz Morales, Francisco Jesús Fernández Morales, Luis Rodríguez Romero, José Villaseñor Camacho, Javier Llanos López

Abstract:

In recent times, environmental problems have led to the extensive use of biological systems to solve them. Among the different types of biological systems, the use of plants such as aquatic macrophytes in constructed wetlands and terrestrial plant species for treating polluted soils and sludge has gained importance. Though the use of constructed wetlands for wastewater treatment is a well-researched domain, the slowness of pollutant degradation and high biomass production pose some challenges. Plants used in CW participate in different mechanisms for the capture and degradation of pollutants that also can retain some pharmaceutical and personal care products (PPCPs) that are very persistent in the environment. Thus, these systems present advantages in line with the guidelines published for the transition towards friendly and ecological procedures as they are environmentally friendly systems, consume low energy, or capture atmospheric CO₂. However, the use of CW presents some drawbacks, as the slowness of pollutant degradation or the production of important amounts of plant biomass, which need to be harvested and managed periodically. Taking this opportunity in mind, it is important to highlight that this residual biomass (of lignocellulosic nature) could be used as the feedstock for the generation of carbonaceous materials using thermochemical transformations such as slow pyrolysis or hydrothermal carbonization to produce high-value biomass-derived carbons through sustainable processes as adsorbents, catalysts…, thereby improving the circular carbon economy. Thus, this work carried out the analysis of some PPCPs commonly found in urban wastewater, as salicylic acid or ibuprofen, to evaluate the remediation carried out for the Phragmites Australis. Then, after the harvesting, this biomass can be used to synthesize electrodes through hydrothermal carbonization (HTC) and produce high-value biomass-derived carbons with electrocatalytic activity to remove heavy metals and persistent pollutants, promoting circular economy concepts. To do this, it was chosen biomass derived from the natural environment in high environmental risk as the Daimiel Wetlands National Park in the center of Spain, and the rest of the biomass developed in a CW specifically designed to remove pollutants. The research emphasizes the impact of the composition of the biomass waste and the synthetic parameters applied during HTC on the electrocatalytic activity. Additionally, this parameter can be related to the physicochemical properties, as porosity, surface functionalization, conductivity, and mass transfer of the electrodes lytic inks. Data revealed that carbon materials synthesized have good surface properties (good conductivities and high specific surface area) that enhance the electro-oxidants generated and promote the removal of PPCPs and the chemical oxygen demand of polluted waters.

Keywords: constructed wetlands, carbon materials, heavy metals, pharmaceutical and personal care products, hydrothermal carbonization

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Authors: A. Kianifar, M. Afzali, I. Pishbin

Abstract:

In this paper, design details, theoretical analysis and thermal performance analysis of a solar energy concentrator suited to combined heat and thermoelectric power generation are presented. The thermoelectric device is attached to the absorber plate to convert concentrated solar energy directly into electric energy at the focus of the concentrator. A cooling channel (water cooled heat sink) is fitted to the cold side of the thermoelectric device to remove the waste heat and maintain a high temperature gradient across the device to improve conversion efficiency.

Keywords: concentrator thermoelectric generator, CTEG, solar energy, thermoelectric cells

Procedia PDF Downloads 288