Search results for: step count

Authors: Przemyslaw J. Jodlowski, Roman J. Jedrzejczyk, Damian K. Chlebda, Anna Dziedzicka, Lukasz Kuterasinski, Anna Gancarczyk, Maciej Sitarz

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The aim of this study was to obtain highly active catalysts based on non-noble metal oxides supported on zirconia prepared via a sonochemical method. In this study, the influence of the stabilizers addition during the preparation step was checked. The final catalysts were characterized by using such characterization methods as X-ray Diffraction (XRD), nitrogen adsorption, X-ray fluorescence (XRF), scanning electron microscopy (SEM) equipped with energy dispersive X-ray spectrometer (EDS), transmission electron microscopy (TEM) and µRaman. The proposed preparation method allowed to obtain uniformly dispersed metal-oxide nanoparticles at the support’s surface. The catalytic activity of prepared catalyst samples was measured in a methane combustion reaction. The activity of the catalysts prepared by the sonochemical method was considerably higher than their counterparts prepared by the incipient wetness method.

Keywords: methane catalytic combustion, nanoparticles, non-noble metals, sonochemistry

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Authors: Hadiza Abdullahi

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Sialic Acids and sialidases have been implicated in many disease states particularly bacterial and viral infections which are common opportunist infections of HIV disease. Their role in HIV/AIDS is contemplated. A study was carried out to determine Sialic Acid profile and Sialidase Activity in HIV infected and Apparently Healthy individuals, and also determine the relationship between the sialic acid levels and sialidase activity. Blood samples were collected from 200 subjects (150 HIV infected individuals and 50 apparently healthy individuals divided into four groups- HIV ART Naïve, HIV Stable (on ART but have been stable with no clinical episodes), HIV-OI (on ART with opportunistic infections), and Apparently Healthy). Complete Blood Count, Erythrocyte Surface Sialic Acid (ESSA), Free Serum Sialic Acid (FSSA) concentrations and Sialidase activity were determined for all 200 subjects. Analysis of variance (ANOVA) was used to compare the results of the different groups of HIV infected individuals as well as controls. The mean haemoglobin (HGB), Packed Cell Volume (PCV) and Red Blood Cells (RBC) concentrations were significantly lower (P ≤ 0.05) in the HIV groups compared with the apparently healthy groups. Anaemia and neutropaenia were the most common heamatological abnormalities observed in this study with highest prevalence of anaemia found in the ART naive group. The mean FSSA was 0.4±0.4mg/ml. There was a significant difference (p ≤ 0.05) between some groups. The highest levels of FSSA was observed in the HIV ART naïve (0.65±0.5mg/ml). The mean ESSA value for the study population was 0.54±0.35mg/ml with no significant difference (p ≤ 0.05) between groups. The mean sialidase activity values were 0.52±0.1 µmol/min/µl, 0.40±0.1 µmol/min/µl, 0.45±0.1 µmol/min/µl and 0.41±0.1 µmol/min/µl for the HIV ART naïve, HIV stable, HIV/OIs and apparently healthy groups respectively. No significant difference (p ≤ 0.05) was found between groups and also in gender and age. The finding in this study of higher mean sialidase activity and FSSA levels in the ART naïve HIV group compared with other groups indicate that the virus and other opportunistic pathogens may be sialidase producers in vivo which cleave off sialic acids from erythrocytes surface, leading to high levels of FSSA, anaemia and neutropaenia seen in this group. The higher ESSA concentration found in the HIV stable group along with lowest FSSA concentration in the group suggests the presence of sialyltransferases.

Keywords: erythrocyte surface sialic acid, free serum sialic acid, HIV, sialidase

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Amro Issam Hamed Attia Ramadan, Marco Zappatore, Pasquale Balena, Antonella Longo

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Considering the energetic crisis that is hitting Europe, it becomes more and more necessary to change the energy policies to depend less on fossil fuels and replace them with energy from renewable sources. This has triggered the urge to use clean energy not only to satisfy energy needs and fulfill the required consumption but also to decrease the danger of climatic changes due to harmful emissions. Many countries have already started creating energetic communities based on renewable energy sources. The first step to understanding energy needs in any place is to perfectly know the consumption. In this work, we aim to estimate electricity consumption for a municipality that makes up part of a rural area located in southern Italy using forecast models that allow for the estimation of electricity consumption for the next ten years, and we then apply the same model to the province where the municipality is located and estimate the future consumption for the same period to examine whether it is possible to start from the municipality level to reach the province level when creating energy communities.

Keywords: ARIMA, electricity consumption, forecasting models, time series

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Authors: Nataša Kalajdžija, Strahinja Kovačević, Davor Lončar, Sanja Podunavac Kuzmanović, Lidija Jevrić

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In order to investigate the relationship between retention and structure, a quantitative Structure Retention Relationships (QSRRs) study was applied for the prediction of retention times of a set of 23 secoestrane derivatives in a reversed-phase thin-layer chromatography. After the calculation of molecular descriptors, a suitable set of molecular descriptors was selected by using step-wise multiple linear regressions. Artificial Neural Network (ANN) method was employed to model the nonlinear structure-activity relationships. The ANN technique resulted in 5-6-1 ANN model with the correlation coefficient of 0.98. We found that the following descriptors: Critical pressure, total energy, protease inhibition, distribution coefficient (LogD) and parameter of lipophilicity (miLogP) have a significant effect on the retention times. The prediction results are in very good agreement with the experimental ones. This approach provided a new and effective method for predicting the chromatographic retention index for the secoestrane derivatives investigated.

Keywords: lipophilicity, QSRR, RP TLC retention, secoestranes

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Authors: Sumudu Sameera Perera Kimmantudawage, Chapal Khasnabis

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Technology is changing at a rapid rate, with innovations in robotics being hailed and tested in countries such as Japan, the United States and Australia, however the conversation in a public health context is stagnant. While obvious barriers to robotics use in low and middle-income countries and regions exist, the avoidance of attempting to address these regions of the world may potentially lead to an ever-increasing divide between those of high income countries and those of less. A systematic review was undertaken to determine the number of projects involving research, development and testing of robotics considered low and middle-income regions. Major findings indicate that an overwhelmingly significant number of projects failed to consider low and middle-income countries or regions. These results are unsurprising however alarming, as bridging the divide is an important step forward in achieving the UN Sustainable Development Goals by 2030. It is hoped that this research would spawn future robotics research that focusses on lower and middle-income regions.

Keywords: assistive technology, health equality, robotics, socioeconomic

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Authors: Jian Shao

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The effect of entrepreneurship on economic, innovation, and employment has been widely acknowledged by scholars and governments. As an essential factor of influencing entrepreneurship activities, entrepreneurship policy creates a conducive environment to support and develop entrepreneurship. However, the challenge in developing entrepreneurship policy is that policy is normally a combination of many different goals and instruments. Instead of examining the effect of individual policy instruments, we argue that attention to a policy mix is necessary. In recent years, much attention has been focused on comparing a single policy instrument to a policy mix, evaluating the interactions between different instruments within a mix or assessment of particular policy mixes. However, another required step in understanding policy mixes is to understand how and why mixes evolve and change over time and to determine whether any changes are an improvement. In this paper, we try to trace the development of the policy mix for entrepreneurship in China by mapping the policy goals and instruments and reveal the process of policy mix changing over time. We find two main process mechanisms of the entrepreneurship policy mix in China: patching and stretching. Compared with policy repackaging, patching and stretching are more realistic processes in the real world of the policy mix, and they are possible to achieve effectiveness by avoiding conflicts and promoting synergies among policy goals and instruments.

Keywords: entrepreneurship, China, policy design, policy mix, policy patching

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Authors: Chun-Ying Lee, Mei-Wen Wu, Li-Yi Cheng, Chiang-Ho Cheng

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This research studies the electroplating of zinc coating in the zinc chloride bath mixed with supercritical CO2. The sodium fluoride (NaF) was used as the bath additive to change the structure and property of the coating, and therefore the roughness and corrosion resistance of the zinc coating was investigated. The surface characterization was performed using optical microscope (OM), X-ray diffractometer (XRD), and α-step profilometer. Moreover, the potentiodynamic polarization measurement in 3% NaCl solution was employed in the corrosion resistance evaluation. Because of the emulsification of the electrolyte mixed in Sc-CO2, the electroplated zinc produced the coating with smoother surface, smaller grain, better throwing power and higher corrosion resistance. The main role played by the NaF was to reduce the coating’s roughness and grain size. In other words, the CO2 mixed with the electrolyte under the supercritical condition performed the similar function as brighter and leveler in zinc electroplating to enhance the throwing power and corrosion resistance of the coating.

Keywords: supercritical CO2, zinc-electroplating, sodium fluoride, electroplating

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Authors: O. Squillace, R. L. Thompson

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Migration of small molecules to, and across the surface of polymer matrices is a little-studied problem with important industrial applications. Tackifiers in adhesives, flavors in foods and binding agents in paints all present situations where the function of a product depends on the ability of small molecules to migrate through a polymer matrix to achieve the desired properties such as softness, dispersion of fillers, and to deliver an effect that is felt (or tasted) on a surface. It’s been shown that the chemical and molecular structure, surface free energies, phase behavior, close environment and compatibility of the system, influence the migrants’ motion. When differences in behavior, such as occurrence of segregation to the surface or not, are observed it is then of crucial importance to identify and get a better understanding of the driving forces involved in the process of molecular migration. In this aim, experience is meant to be allied with theory in order to deliver a validated theoretical and computational toolkit to describe and predict these phenomena. The systems that have been chosen for this study aim to address the effect of polarity mismatch between the migrants and the polymer matrix and that of a second migrant over the first one. As a non-polar resin polymer, polyvinyl acetate is used as the material to which more or less polar migrants (sorbitol, carvone, octanoic acid (OA), triacetin) are to be added. Through contact angle measurement a surface excess is seen for sorbitol (polar) mixed with PVAc as the surface energy is lowered compare to the one of pure PVAc. This effect is increased upon the addition of carvon or triacetin (non-polars). Surface micro-structures are also evidenced by atomic force microscopy (AFM). Ion beam analysis (Nuclear Reaction Analysis), supplemented by neutron reflectometry can accurately characterize the self-organization of surfactants, oligomers, aromatic molecules in polymer films in order to relate the macroscopic behavior to the length scales that are amenable to simulation. The nuclear reaction analysis (NRA) data for deuterated OA 20% shows the evidence of a surface excess which is enhanced after annealing. The addition of 10% triacetin, as a second migrant, results in the formation of an underlying layer enriched in triacetin below the surface excess of OA. The results show that molecules in polarity mismatch with the matrix tend to segregate to the surface, and this is favored by the addition of a second migrant of the same polarity than the matrix. As studies have been restricted to materials that are model supported films under static conditions in a first step, it is also wished to address the more challenging conditions of materials under controlled stress or strain. To achieve this, a simple rig and PDMS cell have been designed to stretch the material to a defined strain and to probe these mechanical effects by ion beam analysis and atomic force microscopy. This will make a significant step towards exploring the influence of extensional strain on surface segregation, flavor release in cross-linked rubbers.

Keywords: polymers, surface segregation, thin films, molecular migration

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Authors: Ferhat Mohamed, Boukhatem Mohamed Nadjib, Chemat Farid

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Simultaneous distillation–extraction (SDE) is routinely used by analysts for sample preparation prior to gas chromatography analysis. In this work, a new process design and operation for microwave assisted simultaneous distillation – solvent extraction (MW-SDE) of volatile compounds was developed. Using the proposed method, isolation, extraction and concentration of volatile compounds can be carried out in a single step. To demonstrate its feasibility, MW-SDE was compared with the conventional technique, Simultaneous distillation–extraction (SDE), for gas chromatography-mass spectrometry (GC-MS) analysis of volatile compounds in a fresh orange juice and a dry spice “carvi seeds”. SDE method required long time (3 h) to isolate the volatile compounds, and large amount of organic solvent (200 mL of hexane) for further extraction, while MW-SDE needed little time (only 30 min) to prepare sample, and less amount of organic solvent (10 mL of hexane). These results show that MW-SDE–GC-MS is a simple, rapid and solvent-less method for determination of volatile compounds from aromatic plants.

Keywords: essential oil, extraction, distillation, carvi seeds

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Authors: Jer-Yuh Liu, Je-Chiuan Ye, Jin-Ming Hwang

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Protein kinase C alpha (PKCα) is a key signaling molecule in human cancer development. As a therapeutic strategy, targeting PKCα is difficult because the molecule is ubiquitously expressed in non-malignant cells. PKCα is regulated by the cooperative interaction of the transcription factors myeloid zinc finger 1 (MZF-1) and Ets-like protein-1 (Elk-1) in human cancer cells. By conducting tissue array analysis, herein, we determined the protein expression of MZF-1/Elk-1/PKCα in various cancers. The data show that the expression of MZF-1/Elk-1 is correlated with that of PKCα in hepatocellular carcinoma (HCC), but not in bladder and lung cancers. In addition, the PKCα down-regulation by shRNA Elk-1 was only observed in the HCC SK-Hep-1 cells. Blocking the interaction between MZF-1 and Elk-1 through the transfection of their binding domain MZF-160–72 decreased PKCα expression. This step ultimately depressed the epithelial-mesenchymal transition potential of the HCC cells. These findings could be used to develop an alternative therapeutic strategy for patients with the PKCα-derived HCC.

Keywords: protein kinase C alpha, myeloid zinc finger 1, ets-like protein-1, hepatocellular carcinoma

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Authors: Arlan S. Freitas, Leila M. Carvalho, Adriana L. Soares, Arnoud Neto, Marta S. Madruga, Rafael H. Carvalho, Elza I. Ida, Massami Shimokomaki

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The objective of this work was to evaluate the influence of microclimatic profile of broiler transport trucks and holding time (340) min under commercial conditions over the breast meat quality and DOA (Dead On Arrival) in a tropical Brazilian regions as the NorthEast. In this particular region routinely the season is divided into dry and wet seasons. Three loads of 4,100 forty seven days old broiler were monitored from farm to slaughterhouse in a distance of 273 km (320 min), morning periods of August, September and October 2015 rainy days. Meat qualities were evaluated by determining the occurrence of PSE (pale, soft, exudative) meat and DFD (dark, firm, dry) meat. The percentage of DOA per loaded truck was determined by counting the dead broiler during the hanging step at the slaughtering plant. Results showed the occurrence of 26.30% of PSE and 2.49% of DFD and 0.45% of DOA. By having PSE- and DFD- meat means that the birds were under thermal and cold stress leading as consequence to a relative high DOA index.

Keywords: animal welfare, DFD, microclimatic profile, PSE

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Authors: Somayyeh Kalami, Mojgan Nejad

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Based on the source (softwood, hardwood or annual crop) and isolation method (kraft, organosolv, sulfite or pre-enzymatic treatment), there are significant variations in lignin structure and properties. The first step in using lignin as biobased feedstock is to make sure that specific lignin is suitable for intended application. Complete characterization of lignin and measuring its chemical, physical and thermal properties can help to predict its suitability. To replace 100% phenol portion of phenolic adhesive, lignin should have high reactivity toward formaldehyde. Theoretically, lignins with closer backbone structure to phenol should be better candidate for this application. In this study, a number of different lignins were characterized and used to formulate phenolic adhesive. One of the main findings was that lignin sample with higher percentage of hydroxyl-phenyl units was better candidate than lignin with more syringyl units. This could be explained by the fact that hydroxyl-phenyl lignin units have two available ortho positions for reaction with formaldehyde while in syringyl units all ortho and para positions are occupied, and there is no available site in lignin structure to react with formaldehyde.

Keywords: lignin, phenolic adhesive, biobased, sustainable

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Authors: Zeynep R. Ege, Aydin Akan, Faik N. Oktar, Betul Karademir, Oguzhan Gunduz

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Early detection of cancer could save human life and quality in insidious cases by advanced biomedical imaging techniques. Designing targeted detection system is necessary in order to protect of healthy cells. Electrospun nanofibers are efficient and targetable nanocarriers which have important properties such as nanometric diameter, mechanical properties, elasticity, porosity and surface area to volume ratio. In the present study, indocyanine green (ICG) organic dye was stabilized and encapsulated in polymer matrix which polyethylene oxide (PEO) and chitosan (CHI) multilayer nanofibers via co-axial electrospinning method at one step. The co-axial electrospun nanofibers were characterized as morphological (SEM), molecular (FT-IR), and entrapment efficiency of Indocyanine Green (ICG) (confocal imaging). Controlled release profile of PEO/CHI/ICG nanofiber was also evaluated up to 40 hours.

Keywords: chitosan, coaxial electrospinning, controlled releasing, drug delivery, indocyanine green, polyethylene oxide

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Authors: Ahmed Elsayed Ahmed, Ashraf Hafez, A. N. Ouda, Hossam Eldin Hussein Ahmed, Hala Mohamed ABD-Elkader

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Unmanned Aircraft Systems (UAS) are playing increasingly prominent roles in defense programs and defense strategies around the world. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating a small unmanned aerial vehicle (SUAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. The first step in the UAV design is the mathematical modeling of the nonlinear equations of motion. In this paper, a survey with a standard method to obtain the full non-linear equations of motion is utilized,and then the linearization of the equations according to a steady state flight condition (trimming) is derived. This modeling technique is applied to an Ultrastick-25e fixed wing UAV to obtain the valued linear longitudinal and lateral models. At the end, the model is checked by matching between the behavior of the states of the non-linear UAV and the resulted linear model with doublet at the control surfaces.

Keywords: UAV, equations of motion, modeling, linearization

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: adaptive filtering, sparse system identification, TD-LMS algorithm, VSSLMS algorithm

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Authors: M. Laura Vazquez Maggio, Lilia Dominguez Villalobos, Jan Luka Frey

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This paper contributes to the understanding of the dynamic and the relational nature of identities formation among skilled middle-class migrants. Following the idea that identities are never singular, multifaceted and have a necessarily processual character, the authors specifically analyze three dimensions of the identity of qualified Mexican migrants in the US and the interplay between them. Drawing on semi-structured interviews with skilled Mexican middle-class migrants in the US, the paper explores how skilled Mexican migrants preserve their ethno-national identity (their ‘Mexicanness’) in reaction to a hostile socio-political reception context in the US. It further shows how these migrants recreate their class identity and show tendencies to distance themselves from what they perceive as lower-class Mexican migrants and the dominant popular Mexican and Latin-American cultural expressions. In a final step, it examines how the lived experience of migration itself impacts the migrants’ identities, their concept of self and feelings/modes of being and belonging.

Keywords: ethno-national identity, middle class identity, middle-class migration, migrants’ identity, skilled migration

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Authors: A. K. Tursunova, O. V. Chebonenko, A. Zh. Amirkulova, A. O. Abaildayev, O. A. Sapko, Y. M. Dyo, A. Sh. Utarbaeva

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Fusarium solani and its variants cause root and stem rot of plants. Dry rot is the most common disease of potato tubers during storage. The causative agents of fusariosis in contact with plants behave as antagonists, growth stimulants or parasites. The diversity of host-parasite relationships is explained by the parasite’s ability to produce a wide spectrum of biologically active compounds including toxins, enzymes, oligosaccharides, antibiotic substances, enniatins and gibberellins. Many of these metabolites contribute to the creation of compatible relations; others behave as elicitors, inducing various protective responses in plants. An important part of the strategy for developing plant resistance against pathogens is the activation of protein synthesis to produce protective ‘pathogenesis-related’ proteins. The family of PR-proteins known to confer the most protective response is chitinases (EC 3.2.1.14, Cht) and β-1,3-glucanases (EC 3.2.1.39, Glu). PR-proteins also include a large multigene family of peroxidases (EC 1.11.1.7, Pod), and increased activity of Pod and expression of the Pod genes leads to the development of resistance to a broad class of pathogens. Despite intensive research on the role of PR-proteins, the question of their participation in the mechanisms of formation of the F.solani–S.tuberosum pathosуstem is not sufficiently studied. Our aim was to investigate the effect of different classes of F. solani metabolites on the activity of chitinase, β-1,3-glucanases and peroxidases in tubers of Solanum tuberosum. Metabolite culture filtrate (CF) and cytoplasmic components were fractionated by extraction of the mycelium with organic solvents, salting out techniques, dialysis, column chromatography and ultrafiltration. Protein, lipid, carbohydrate and polyphenolic fractions of fungal metabolites were derived. Using enzymatic hydrolysis we obtained oligo glycans from fungal cell walls with different molecular weights. The activity of the metabolites was tested using potato tuber discs (d = 16mm, h = 5mm). The activity of PR-proteins of tubers was analyzed in a time course of 2–24 hours. The involvement of the analysed metabolites in the modulation of both early non-specific and late related to pathogenesis reactions was demonstrated. The most effective inducer was isolated from the CF (fraction of total phenolic compounds including naphtazarins). Induction of PR-activity by this fraction was: chitinase - 340-360%, glucanase - 435-450%, soluble forms of peroxidase - 400-560%, related forms of peroxidase - 215-237%. High-inducing activity was observed by the chloroform and acetonitrile extracts of the mycelium (induction of chitinase and glucanase activity was 176-240%, of soluble and bound forms of peroxidase - 190-400%). The fraction of oligo glycans mycelium cell walls of 1.2 kDa induced chitinase and β-1,3-glucanase to 239-320%; soluble forms and related peroxidase to 198-426%. Oligo glycans cell walls of 5-10 kDa had a weak suppressor effect - chitinase (21-25%) and glucanase (25-28%) activity; had no effect on soluble forms of peroxidase, but induced to 250-270% activity related forms. The CF polysaccharides of 8.5 kDa and 3.1 kDa inhibited synchronously the glucanase and chitinase specific response in step (after 24 hours at 42-50%) and the step response induced nonspecific peroxidase activity: soluble forms 4.8 -5.2 times, associated forms 1.4-1.6 times.

Keywords: fusarium solani, PR-proteins, peroxidase, solanum tuberosum

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Authors: Sri Wahjuningsih, Nur Ihsan, Hadiah

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In the embryo transfer program, to address the limited production of embryos in vivo, in vitro embryo production has become an alternative approach that is relatively inexpensive. One potential source of embryos that can be developed is to use immature oocytes then conducted in vitro maturation and in vitro fertilization. However, obstacles encountered were oocyte viability mammals have very limited that it cannot be stored for a long time, so we need oocyte cryopreservation. The research was conducted to know the optimal concentration use of ethylene glycol as a cryoprotectant on oocytes freezing.Material use in this research was immature oocytes; taken from abbatoir which was aspirated from follicle with diameter 2-6 mm. Concentration ethylen glycol used were 0,5 M, I M, 1,5 M and 2M. The freezing method used was conventional method combined with a five-step protocol washing oocytes from cryoprotectant after thawing. The result showed that concentration ethylen glycol have the significant effect (P<0.05) on oocytes quality after thawing and in vitro maturation. It was concluded that concentration 1,5 M was the best concentration for freezing oocytes using conventional method.

Keywords: bovine, conventional freezing, ethylen glycol, oocytes

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Authors: Walid M. Adel, Liang Guo-Zhu

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To investigate the characterization of the mechanical properties of composite solid propellant (CSP) based on hydroxyl-terminated polybutadiene (HTPB) at different temperatures and strain rates, uniaxial tensile tests were conducted over a range of temperatures -60 °C to +76 °C and strain rates 0.000164 to 0.328084 s^-1 using a conventional universal testing machine. From the experimental data, it can be noted that the mechanical properties of AP/HTPB propellant are mainly dependent on the applied strain rate and the temperature condition. The stress-strain responses exhibited an initial yielding followed by the viscoelastic phase, which was strongly affected by the strain rate and temperature. It was found that the mechanical properties increased with both increasing strain rate and decreasing temperature. Based on the experimental tests, the master curves of the tensile properties are drawn using predetermined shift factor and the results were discussed. This work is a first step in preliminary investigation the nonlinear viscoelasticity behavior of CSP.

Keywords: AP/HTPB composite solid propellant, mechanical behavior, nonlinear viscoelastic, tensile test, strain rate

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Authors: Chaudhary Archana, Dhingra Poshika

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The architecture of the world is at a crossroads with the advent of new technology. The issues of energy efficiency and global warming are getting important with the coming times. New technologies are making their mark. For the architecture profession, nanotechnology will greatly impact construction materials and their properties. Nanotechnology, the understanding and control of matter at a scale of one to one hundred billions of a meter, is bringing incredible changes to the materials and processes of buildings. Materials will behave in many different ways as we are able to more precisely control their properties at the nanoscale. It is precisely called the next industrial revolution. We live in an age where scientific progress continues to transform human lifestyle. This is evermore true when it comes to the progress being made in the field of nanotechnology. This science stands to change and advance the practice of design in a multitude of ways – where architectural progress is being made at the molecular level. The nanotechnology has already been adopted in various buildings across the world. What an impact it shall have on the futuristic architecture in Chandigarh, India shall be discussed in the paper. But before we hurtle off toward a nano-utopia, we need to step back and ask ourselves whether this is a direction in which we really want to go.

Keywords: building materials, energy efficiency, nanotechnology, sustainability

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Authors: Patrick Guggenberger

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Extant literature has highlighted the importance of individual employees in the entrepreneurial process, as they are those that come up with novel ideas and promote their implementation throughout the organization. However, research on antecedents of individual entrepreneurial behavior (IEB) is very limited. The present study takes an initial step to investigate the interplay between transformational leader behaviors of direct supervisors and employees’ ability and willingness to act entrepreneurial and sheds light on the moderating role of an individual’s hierarchical level. A theoretically derived research model is empirically tested, drawing on survey data of 450 individuals working in medium- and large-sized corporations in two countries. Findings indicate that various transformational leader behaviors have a strong positive impact on IEB, while the ability of direct supervisors to influence their followers’ entrepreneurial behavior depends strongly on their own hierarchical level. The study reveals that transformational leadership has most impact at lower hierarchical levels, where employees’ motivation to act entrepreneurial is the lowest.

Keywords: corporate entrepreneurship, hierarchy, individual entrepreneurial behavior, transformational leadership

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Authors: Tushar K. Routh

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If inputs are engineered in certain manners, they can influence deep neural networks’ (DNN) performances by facilitating misclassifications, a phenomenon well-known as adversarial attacks that question networks’ vulnerability. Recent studies have unfolded the relationship between vulnerability of such networks with their complexity. In this paper, the distinctive influence of additional convolutional layers at the decision boundaries of several DNN architectures was investigated. Here, to engineer inputs from widely known image datasets like MNIST, Fashion MNIST, and Cifar 10, we have exercised One Step Spectral Attack (OSSA) and Fast Gradient Method (FGM) techniques. The aftermaths of adding layers to the robustness of the architectures have been analyzed. For reasoning, separation width from linear class partitions and local geometry (curvature) near the decision boundary have been examined. The result reveals that model complexity has significant roles in adjusting relative distances from margins, as well as the local features of decision boundaries, which impact robustness.

Keywords: DNN robustness, decision boundary, local curvature, network complexity

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Authors: Gwanghee Heo, Geonhyeok Bang, Chunggil Kim, Chinok Lee

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This paper attempts to develop a wireless feedback control system as a primary step eventually toward a bio-inspired structure system where inanimate structure behaves like a life form autonomously. It is a standalone wireless control system which is supposed to measure externally caused structural responses, analyze structural state from acquired data, and take its own action on the basis of the analysis with an embedded logic. For an experimental examination of its effectiveness, we applied it on a model of two-span bridge and performed a wireless control test. Experimental tests have been conducted for comparison on both the wireless and the wired system under the conditions of Un-control, Passive-off, Passive-on, and Lyapunov control algorithm. By proving the congruence of the test result of the wireless feedback control system with the wired control system, its control performance was proven to be effective. Besides, it was found to be economical in energy consumption and also autonomous by means of a command algorithm embedded into it, which proves its basic capacity as a bio-inspired system.

Keywords: structural vibration control, wireless system, MR damper, feedback control, embedded system

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Authors: Anastasia Poliakova

Abstract:

Harmful algal bloom (HAB) is a known negative phenomenon that is caused both by natural factors and anthropogenic influence. HABs can result in a series of deleterious effects, such as beach fouling, paralytic shellfish poisoning, mass mortality of marine species, and a threat to human health, especially if toxins pollute drinking water or occur nearby public resorts. In South China, the problem of HABs has an ultimately important meaning. For this study, we used a 1.5 m sediment core LAX-2018-2 collected in 2018 from the Zhanjiang Mangrove National Nature Reserve (109°03´E, 20°30´N), Guangdong Province, South China. High-resolution coastal environment reconstruction with a specific focus on the HABs history during the last ca 2500 yrs was attempted. Age control was performed with five radiocarbon dates obtained from benthic foraminifera. A total number of 71 dinoflagellate cyst types was recorded. The most common types found consistently throughout the sediment sequence were autotrophic Spiniferites spp., Spiniferites hyperacanthus and S. mirabilis, S. ramosus, Operculodinium centrocarpum sensu Wall and Dale 1966, Polysphaeridium zoharyi, and heterotrophic Brigantedinium ssp., cyst of Gymnodinium catenatum and cysts mixture of Protoperidinium. Three local dinoflagellate zones LAX-1 to LAX-3 were established based on the results of the constrained cluster analysis and data ordination; additionally, the middle zone LAX-2 was derived into two subzones, LAX-2a and LAX-2b based on the dynamics of toxic and heterotrophic cysts as well as on the significant changes (probability, P=0.89) in percentages of eutrophic indicators. The total cyst count varied from 106 to 410 dinocysts per slide, with 177 cyst types on average. Dinocyst assemblages are characterized by high values of the dost-depositional degradation index (kt) that varies between 3.6 and 7.6 (averaging 5.4), which is relatively high and is very typical for the areas with selective dinoflagellate cyst preservation that is related to bottom-water oxygen concentrations.

Keywords: reconstruction of palaeoenvironment, harmful algal blooms, anthropogenic influence on coastal zones, South China Sea

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Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Sushant Singh, Anurag Jain, Seema Sabharwal

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Cloud computing is advancing with a rapid speed. Already, it has been adopted by a huge set of users. Easy to use and anywhere access like potential of cloud computing has made it more attractive relative to other technologies. This has resulted in reduction of deployment cost on user side. It has also allowed the big companies to sell their infrastructure to recover the installation cost for the organization. Roots of cloud computing have extended from Grid computing. Along with the inherited characteristics of its predecessor technologies it has also adopted the loopholes present in those technologies. Some of the loopholes are identified and corrected recently, but still some are yet to be rectified. Two major areas where still scope of improvement exists are security and performance. The proposed work is devoted to performance enhancement for the user of the existing cloud system by improving the basic throttled mapping approach between task and resources. The improved procedure has been tested using the cloud analyst simulator. The results are compared with the original and it has been found that proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, load balancing, throttled

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

Abstract:

At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: case-based reasoning, knowledge, police, public efficiency

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Authors: Pedro Pablo Ramírez Sánchez, Alassane Ballé Ndiaye, Roberto Rendeiro Martín-Cejas

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The aim of this paper is to analyse the different environmental policies adopted in Europe for car emissions, to comment on some of the possible perverse effects generated and point out these policies which are considered more efficient under the environmental perspective. This paper is focused on passenger cars as this category is the most significant in road transport. The utility of this research lies in this being the first step or basis to improve and optimise actual policies. The methodology applied in this paper refers to a comparative analysis from a practical and theoretical point of view of European environmental policies in road transport. This work describes an overview of the road transport industry in Europe pointing out some relevant aspects such as the contribution of road transport to total emissions and the vehicle fleet in Europe. Additionally, we propose a brief practice guide with the combined policies in order to optimise their aim.

Keywords: air quality, climate change, emission, environment, perverse effect, road transport, tax policy

Procedia PDF Downloads 166