Search results for: double nearest proportion feature extraction

Authors: H. A. Lopez-Aguilar, E. A. Huerta-Reynoso, J. A. Gomez, J. A. Duarte-Moller, A. Perez-Hernandez

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Environmental performance of artisanal brick manufacture was studied by Lifecycle Assessment (LCA) methodology and Computational Fluid Dynamics (CFD) analysis in Mexico. The main objective of this paper is to evaluate the environmental impact during artisanal brick manufacture. LCA cradle-to-gate approach was complemented with CFD analysis to carry out an Environmental Impact Assessment (EIA). The lifecycle includes the stages of extraction, baking and transportation to the gate. The functional unit of this study was the production of a single brick in Chihuahua, Mexico and the impact categories studied were carcinogens, respiratory organics and inorganics, climate change radiation, ozone layer depletion, ecotoxicity, acidification/ eutrophication, land use, mineral use and fossil fuels. Laboratory techniques for fuel characterization, gas measurements in situ, and AP42 emission factors were employed in order to calculate gas emissions for inventory data. The results revealed that the categories with greater impacts are ecotoxicity and carcinogens. The CFD analysis is helpful in predicting the thermal diffusion and contaminants from a defined source. LCA-CFD synergy complemented the EIA and allowed us to identify the problem of thermal efficiency within the system.

Keywords: LCA, CFD, brick, artisanal

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Authors: Ali Faisal Saleem, Farheen Quadri, Mach Ondrej, Anita Zaidi

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Purpose: Pakistan is the final frontier for a polio-free world. Chronic malnutrition is associated with lack of effective gut immunity, and possibly associated with poliomyelitis in children received multiple OPV. We evaluate IPV dose administered together with OPV results in higher immunogenicity and mucosal immunity compared to OPV alone in chronically malnourished infants. Methods AND Materials: A community-based, unblinded-randomized-trial, conducted in 5 peri-urban, low-middle-income households of Karachi, in infants 9-12 months. Two study groups were non-malnourished (HAZ= -2 or more) and chronic malnourished (HAZ <-2SD), with 2-arms each i) OPV and ii) OPV and IPV. Two blood specimens (2ml) at baseline and at day 28 and two stool specimens (6 gm.) at day 29 and after 7 days. All infants received a bOPV challenge dose after first stool specimen. Calculates sample size was 210 in each arm. Serological (baseline compared to 28 days post-vaccine) and mucosal immunity after one week of bOPV challenge dose were study outcomes. Results: Baseline seroprevalence in malnourished infants were low compared to non-malnourished (P1, P2 and P3 (p=<0.001). There is significant rise in antibody titer and P1 seroprevalence in Mal A and B after receiving study vaccine; much higher in Mal B. Infants randomized to bOPV + IPV study vaccine showed incremental immune response against P1 (Mal B, 92.2%; Nor B, 98.4%), P2 (Mal B, 90.4%; Nor B, 94.7%), and P3 (Mal B, 85.6% and Nor B, 93.5%) was observed. A significant proportion of infants in malnourished (P1, 13%; P2, 24%; P3, 26%) and normally nourished group (P1, 5%; P2, 11%; P3, 14%) were found to be seronegative at baseline. Infants who received BOPV + IPV as their study vaccine showed a very high seroconversion response after vaccine (p=<0.001 for P1, P2 and P3). Majority of the specimens were negative at baseline (Mal A, 2%, Mal B, 1%; Nor A, 2%; Nor B, 1%), and remains negative after bOPV challenge dose (Mal A, 8%, Mal B, 6%; Nor A, 11%; Nor B, 10%). Conclusion: Malnourished-infants have low poliovirus-seroprevalence that increased remarkably after IPV. There is less viral shedding after IPV in infants.

Keywords: chronic malnutrition, infants, IPV, OPV

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Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

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Authors: Halil Demir, Ersin Polat

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This study, in which crispy salad plants was cultivated between the two rows of tomato, was conducted in Spring 2007 in a research glasshouse at Akdeniz University. Crispy salad (Lactuca sativa var. crispa cv. Bohemia) plants were intercropped with tomato (Solanum lycopersicon cv. Selin F1) plants as the main crop. Tomato seedlings were planted according to double line plantation system with 100 cm large spacing, 50 cm narrow spacing and 50 cm within row plant spacing. In both control and intercropping applications, each plot was 9.75 m2 according to plantation distances and there were 26 plants per each plot for tomato. Crispy salad seedlings were planted with 30 cm spacing as one row in the middle of tomato plants and with 30x30 spacing as two rows between plants rows. Moreover, salad seedlings were transplanted between tomato plants above the tomato rows that were planted in two rows with intervals of 50 cm and also with 25x25 cm spacing as the third row in the middle of tomato rows. While tomato plants were growing during the research, fruit width and height were measured periodically with 15 days in the tomato fruits of the third cluster from the formation of fruit to fruit ripening. According to results, while there were no differences between cropping systems in terms of fruit width, the highest fruit height was found in Control trial in the first measurement. In the second measurement while the highest fruit width was determined with 64.39 mm in Control, there were no differences between cropping systems. In the third measurement, the highest fruit width and height were obtained from Control with 68.47 mm and 55.52 mm, respectively. As a conclusion the trial, which crispy salad seedlings were planted with 30x30 cm spacing as two rows between tomato plants rows, was determined as a best intercropping application.

Keywords: crispy salad, glasshouse, intercropping, tomato

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Authors: Nadeem Yousuf Khan

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This paper proposes the formation of a digital emergency response system (dERS) in the aged, long-term care, and chronic disease setups in the post-COVID healthcare ecosystem, focusing on the Asia Pacific market where the aging population is increasing significantly. It focuses on the use of digital technologies such as wearables, a global positioning system (GPS), and mobile applications to build an integrated care system for old folks with co-morbidities and other chronic diseases. The paper presents a conceptual framework of a connected digital health ecosystem that not only provides proactive care to registered patients but also prevents the damages due to sudden conditions such as strokes by alerting and treating the patients in a digitally connected and coordinated manner. A detailed review of existing digital health technologies such as wearables, GPS, and mobile apps was conducted in context with the new post-COVID healthcare paradigm, along with a detailed literature review on the digital health policies and usability. A good amount of research papers is available in the application of digital health, but very few of them discuss the formation of a new framework for a connected digital ecosystem for the aged care population, which is increasing around the globe. A connected digital emergency response system has been proposed by the author whereby all registered patients (chronic disease and aged/long term care) will be connected to the proposed digital emergency response system (dERS). In the proposed ecosystem, patients will be provided with a tracking wrist band and a mobile app through which the control room will be monitoring the mobility and vitals such as atrial fibrillation (AF), blood sugar, blood pressure, and other vital signs. In addition to that, an alert in case if the patient falls down will add value to this system. In case of any variation in the vitals, an alert is sent to the dERS 24/7, and dERS clinical staff immediately trigger that alert which goes to the connected hospital and the adulatory service providers, and the patient is escorted to the nearest connected tertiary care hospital. By the time, the patient reaches the hospital, dERS team is ready to take appropriate clinical action to save the life of the patient. Strokes or myocardial infarction patients can be prevented from disaster if they are accessible to engagement healthcare. This dERS will play an effective role in saving the lives of aged patients or patients with chronic co-morbidities.

Keywords: aged care, atrial fibrillation, digital health, digital emergency response system, digital technology

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Authors: Reda Dzingelevičienė, Vytautas Abromaitis, Nerijus Dzingelevičius, Kęstutis Baranauskis, Saulius Raugelė, Malgorzata Mlynska-Szultka, Sergej Suzdalev, Reza Pashaei, Sajjad Abbasi, Boguslaw Buszewski

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A unique hybrid technology was developed for the removal of COVID-19 specific contaminants from wastewater. Reactor testing was performed using model water samples contaminated with COVID-19 pharmaceuticals and microplastics. Different hydraulic retention times, concentrations of pollutants and dissolved ozone were tested. Liquid Chromatography-Mass Spectrometry, solid phase extraction, surface area and porosity, analytical tools were used to monitor the treatment efficiency and remaining sorption capacity of the spent adsorbent. The combination of advanced oxidation and adsorption processes was found to be the most effective, with the highest 90-99% and 89-95% molnupiravir and microplastics contaminants removal efficiency from the model wastewater. The research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0014) under a grant agreement with the Research Council of Lithuania (LMTLT), and it was funded as part of the European Union’s measure in response to the COVID-19 pandemic.

Keywords: adsorption, hybrid reactor system, pharmaceuticals-microplastics, wastewater

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Authors: Małgorzata Drzewiecka, Tomasz Śliwiński, Maciej Radek

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The inhibition of histone deacetyles (HDACs) holds promise as a potential anti-cancer therapy because histone and non-histone protein acetylation is frequently disrupted in cancer, leading to cancer initiation and progression. Additionally, histone deacetylase inhibitors (HDACi) such as class I HDAC inhibitor - valproic acid (VPA) have been shown to enhance the effectiveness of DNA-damaging factors, such as cisplatin or radiation. In this study, we found that, using of VPA in combination with talazoparib (BMN-637 – PARP1 inhibitor – PARPi) and/or Dacarabazine (DTIC - alkylating agent) resulted in increased DNA double strand break (DSB) and reduced survival (while not affecting primary melanocytes )and proliferation of melanoma cells. Furthermore, pharmacologic inhibition of class I HDACs sensitizes melanoma cells to apoptosis following exposure to DTIC and BMN-637. In addition, inhibition of HDAC caused sensitization of melanoma cells to dacarbazine and BMN-637 in melanoma xenografts in vivo. At the mRNA and protein level histone deacetylase inhibitor downregulated RAD51 and FANCD2. This study provides that combining HDACi, alkylating agent and PARPi could potentially enhance the treatment of melanoma, which is known for being one of the most aggressive malignant tumors. The findings presented here point to a scenario in which HDAC via enhancing the HR-dependent repair of DSBs created during the processing of DNA lesions, are essential nodes in the resistance of malignant melanoma cells to methylating agent-based therapies.

Keywords: melanoma, hdac, parp inhibitor, valproic acid

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Authors: Y. V. S. Annapurna, V. V. Lakshmi

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Urinary tract infection (UTI) is one of the most common infectious diseases at the community level with a high rate of morbidity . This is further augmented by increase in the number of resistant and multi resistant strains of bacteria particularly by those producing Extended spectrum of beta lactamases. The present study was aimed at analysis of antibiograms of E.coli and Klebsiella sp causing urinary tract infections. Between November 2011 and April 2013, a total of 1120 urine samples were analyzed,. Antibiotic sensitivity testing was done with 542(48%) isolates of E.coli and 446(39%) of Klebsiella sp using the standard disc diffusion method against eleven commonly used antibiotics .Organisms showed high susceptibility to Amikacin and Netilimicin and low susceptibility to Cephalosporins. MAR index was calculated for the multidrug resistant strains. Maximum MAR index detected among the isolates was 0.9. Phenotypic identification for ESBL production was confirmed by double disk synergy test (DDST) according to CLSI guidelines. Plasmid profile of the isolates was carried out using alkaline hydrolysis method. Agarose-gel electrophoresis showed presence of high-molecular weight plasmid DNA among the ESBL strains. This study emphasizes the importance of indiscriminate use of antibiotics which if discontinued, in turn would prevent further development of bacterial drug resistance. For this, a proper knowledge of susceptibility pattern of uropathogens is necessary before prescribing empirical antibiotic therapy and it should be made mandatory.

Keywords: escherichia coli, extended spectrum of beta lactamase, Klebsiella spp, Uropathogens

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Authors: Jörg Lenhardt, Wolfram Schiffmann, Jörg Keller

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While the feature sizes of recent Complementary Metal Oxid Semiconductor (CMOS) devices decrease the influence of static power prevails their energy consumption. Thus, power savings that benefit from Dynamic Frequency and Voltage Scaling (DVFS) are diminishing and temporal shutdown of cores or other microchip components become more worthwhile. A consequence of powering off unused parts of a chip is that the relative difference between idle and fully loaded power consumption is increased. That means, future chips and whole server systems gain more power saving potential through power-aware load balancing, whereas in former times this power saving approach had only limited effect, and thus, was not widely adopted. While powering off complete servers was used to save energy, it will be superfluous in many cases when cores can be powered down. An important advantage that comes with that is a largely reduced time to respond to increased computational demand. We include the above developments in a server power model and quantify the advantage. Our conclusion is that strategies from datacenters when to power off server systems might be used in the future on core level, while load balancing mechanisms previously used at core level might be used in the future at server level.

Keywords: power efficiency, static power consumption, dynamic power consumption, CMOS

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Authors: Tamer M. El-Messery

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By-products from sunflower oil extraction, such as sunflower cakes, are rich sources of proteins with desirable functional properties for the food industry. However, challenges such as sensory drawbacks and the presence of phenolic compounds have hindered their widespread use. In this study, sunflower protein concentrates were obtained from sunflower cakes using different ant-greening solvents (ascorbic acid (ASC) and N-acetylcysteine (NAC)), and their functional properties were evaluated. The color of extracted proteins ranged from dark green to yellow, where the using of ASC and NAC agents enhanced the color. The protein concentrates exhibited high solubility (>70%) and antioxidant activity, with hydrophobicity influencing emulsifying activity. Emulsions prepared with these proteins showed stability and microencapsulation efficiency. Incorporation of protein concentrates into low-fat whipping cream formulations increased overrun and affected color characteristics. Rheological studies demonstrated pseudoplastic behavior in whipped cream, influenced by shear rates and protein content. Overall, sunflower protein isolates showed promising functional properties, indicating their potential as valuable ingredients in food formulations.

Keywords: functional properties, sunflower protein concentrates, antioxidant capacity, ant-greening agents, low-fat whipping cream

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Authors: Maryam Bordbar, Yaser Mokhayeri, Sajjad Roosta, Fatemeh Ghasemi, Saeed Choobkar, Hamidreza Nikbakht, Ebrahim Falahi

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Objective: Diabetes mellitus type 2 is the most common metabolic disorder that is growing exponentially worldwide. Satureja Khuzestanica Jamzad is a native plant of Iran that grows widely in the south of Iran. Its antimicrobial, antioxidant, anti-inflammatory and pain-relieving effects have been documented in animal studies. The purpose of this study is to investigate the effect of consumption daily S. khuzestanica on inflammatory and antioxidant indicators in type 2 diabetic patients. Methods and Materials: In a double-blind, placebo-controlled clinical trial, 67 patients with type 2 diabetes were included and divided into two groups. One group received S. khuzestanica (capsule containing 500 mg) and the other group received placebo (500 mg talcum powder) once a day for 12 weeks. After the intervention, the inflammatory and antioxidant indicators of the two groups were compared. Results: In comparison to placebo groups, there was a significant difference in levels of total antioxidant capacity, superoxide dismutase, catalase, glutathione reductase, and glutathione peroxidase; these antioxidant indicators were higher in the intervention group (P<0.05). Moreover, a considerable decrease in weight, CRP and IL-6 levels were observed in patients in the S.Khuzestanica group. Conclusion: Our findings may provide novel complementary treatments without adverse effects for diabetes complications.

Keywords: Satureja khuzestanica Jamzad, diabetes mellitus, antioxidant indicators, IL-6, C-reactive protein

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Authors: Eman A. Gani, Loay E. George, Faisel G. Mohammed, Kamal H. Sager

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Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy.

Keywords: retinal images, fundus images, diabetic retinopathy, background segmentation, damaged areas segmentation

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Authors: Taramani Yadav, Gajender Kumar, R.K. Yadav, H.S. Jat

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Soil Salinity and irrigation water salinity is critical threat to enhance agricultural food production to full fill the demand of billion plus people worldwide. Salt affected soils covers 6.73 Mha in India and ~1000 Mha area around the world. Irrigation scheduling of saline water is the way to ensure food security in salt affected areas. Research experiment was conducted at ICAR-Central Soil Salinity Research Institute, Experimental Farm, Nain, Haryana, India with 36 treatment combinations in double split plot design. Three sets of treatments consisted of (i) three regimes of irrigation viz., 60, 80 and 100% (I1, I2 and I3, respectively) of crop ETc (crop evapotranspiration at identified respective stages) in main plot; (ii) four levels of irrigation water salinity (sub plot treatments) viz., 2, 4, 8 and 12 dS m-1 (iii) applications of two PBRs along with control (without PBRs) i.e. salicylic acid (G1; 1 mM) and thiourea (G2; 500 ppm) as sub-sub plot treatments. Grain yield of wheat (Triticum aestivum) was increased with less amount of high salt loaded irrigation water at the same level of salinity (2 dS m-1), the trend was I3>I2>I1 at 2 dS m-1 with 8.10 and 17.07% increase at 80 and 100% ETc, respectively compared to 60% ETc. But contrary results were obtained by increasing amount of irrigation water at same level of highest salinity (12 dS m-1) showing following trend; I1>I2>I3 at 12 dS m-1 with 9.35 and 12.26% increase at 80 and 60% ETc compared to 100% ETc. Enhancement in grain yield of wheat (Triticum aestivum) is not need to increase amount of irrigation water under saline condition, with salty irrigation water less amount of irrigation water gave the maximum wheat (Triticum aestivum) grain yield.

Keywords: Irrigation, Salinity, Wheat, Yield

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Authors: Serap Keskin Tunç, Cennet Neslihan Eroğlu, Sevinç Şahin, Selda Seçkin

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It has been suggested that various viruses may play a role in the pathogenesis of cancerous oral lesions in the literature. The aim of this study was to investigate the presence of both possible precancerous viral markers (HPV, HHV8, HSV1, HSV2, and EBV), and p53 and Ki-67 in the dental follicles of asymptomatic impacted teeth. A hundred healthy volunteers, older than 18 years old, included in the study. Dental follicles of extracted impacted teeth were excised and fixated in 10% formaldehyde. Histopathological and immunohistochemical examinations using HPV (containing HPV 8 and HPV 11), p16 (containing HPV 16), HHV8, HSV1, HSV2, EBV, p53 and Ki-67 antibodies were carried out. Also, the immunohistochemical results were correlated with the clinicopathological feature by Chi-square test statistically No dysplasia or neoplasm was observed. 62% of the cases were positive for p16, 32% were positive for EBV, 26% were positive for HSV1, immunohistochemically. All cases were immunonegative for HPV, HSV2, and HHV8. There was statistically significant correlation between overexpression of p53 with both EBV and p16 positivity (p<0.05). Direct correlation between higher expression of Ki-67 between EBV immunopositivity was detected (p<0.05). Thus, these viruses may be suggested to show trophism to the dental follicles acting as a reservoir. In conclusion, all dental follicles of extracted impacted teeth should be examined histopathologically in order to detect and prevent possible viral oncogenesis.

Keywords: dental follicles, Ki67, p53, precancerous markers viral markers

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Authors: Muhammad Zubair Khan, Yugyung Lee

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Deep learning has recently achieved enormous response in semantic image segmentation. The previously developed U-Net inspired architectures operate with continuous stride and pooling operations, leading to spatial data loss. Also, the methods lack establishing long-term pixels connection to preserve context knowledge and reduce spatial loss in prediction. This article developed encoder-decoder architecture with bi-directional LSTM embedded in long skip-connections and densely connected convolution blocks. The network non-linearly combines the feature maps across encoder-decoder paths for finding dependency and correlation between image pixels. Additionally, the densely connected convolutional blocks are kept in the final encoding layer to reuse features and prevent redundant data sharing. The method applied batch-normalization for reducing internal covariate shift in data distributions. The empirical evidence shows a promising response to our method compared with other semantic segmentation techniques.

Keywords: deep learning, semantic segmentation, image analysis, pixels connection, convolution neural network

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Authors: Zahra Salehi Shahrbabaki, Zahra Chavoshzadeh, Fahimeh Abdollahimajd, Samin Sharafian, Tolue Mahdavi, Mahnaz Jamee

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Background: Inborn errors of immunity (IEIs) are monogenic diseases of the immune the system with broad clinical manifestations. Despite the increasing genetic advancements, the diagnosis of IEIs still leans on clinical diagnosis. Dermatologic manifestations are observed in a large number of IEI patients and can lead to proper approach, prompt intervention and improved prognosis. Methods: This cross-sectional study was carried out between 2018 and 2020 on IEIs at a Children's tertiary care center in Tehran, Iran. Demographic details (including age, sex, and parental consanguinity), age at onset of symptoms and family history of IEI with were recorded. Results :212 patients were included. Cutaneous findings were reported in (95 ,44.8%) patients. and 61 of 95 (64.2%) reported skin lesions as the first clinical presentation. Skin infection (69, 72.6%) was the most frequent cutaneous manifestation, followed by an eczematous rash (24, 25 %). Conclusions: Skin manifestations are common feature in IEI patients and can be readily recognizable by healthcare providers. This study tried to provide information on prognostic consequences.

Keywords: primary immuno deficiency, inborn errror of metabolism, skin manifestation, skin infection

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Authors: Bambang Heliyanto, Rully Dyah Purwati, Hasnam, Fadjry Djufry

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Jatropha curcas L., a drought tolerant and monoecious perennial shrub, has received attention worldwide during the past decade. Realizing the facts, the Indonesian government has decided to option for Jatropha and palm oil for in country biofuel production. To support the program development of high yielding jatropha varieties is necessary. This paper reviews Jatropha improvement program in Indonesia using mass selection and hybrid development. To start with, at the end of 2005, in-country germplasm collection was mobilized to Lampung and Nusa Tenggara Barat (NTB) provinces and successfully collected 15 provenances/sub-provenances which serves as a base population for selection. A significant improvement has been achieved through a simple recurrent breeding selection during 2006 to 2007. Seed yield productivity increased more than double, from 0.36 to 0.97 ton dry seed per hectare during the first selection cycle (IP-1), and then increased to 2.2 ton per hectare during the second cycles (IP-2) in Lampung provenance. Similar result was also observed in NTB provenance. Seed yield productivity increased from 0.43 ton to 1 ton dry seed per hectare in the first cycle (IP-1), and then 1.9 ton in the second cycle (IP-2). In 2008, the population IP-3 resulted from the third cycle of selection have been identified which were capable of producing 2.2 to 2.4 ton seed yield per hectare. To improve the seed yield per hectare, jatropha hybrid varieties was developed involving superior provenances. As a result a Jatropha Energy Terbarukan (JET) variety-2 was released in 2017 with seed yield potential of 2.6 ton per hectare. The use of this high yielding genotypes for biofuel is discussed.

Keywords: Jatropha curcas, provenance, biofuel, improve population, hybrid

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Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

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There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

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Authors: Vinay Kumar, M. Kishor, Sathyanarayana Rao Ts

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Background: Growth of elderly people in the general population in recent years is termed as ‘greying of the world’ where there is a shift from high mortality & fertility to low mortality and fertility, resulting in an increased proportion of older people as seen in India. Improved health care promises longevity but socio-economic factors like poverty, joint families and poor services pose a psychological threat. Epidemiological data regarding the prevalence of mental disorders in geriatric population with physical illness is required for proper health planning. Methods: Sixty consecutive elderly patients aged 60 years or above of both sexes, reporting with physical illness to general outpatient registration counter of JSS Medical College and Hospital, Mysore, India, were considered for the Study. With informed consent, they were screened with General Health Questionnaire (GHQ-12) and were further evaluated for diagnosing mental disorders according to WHO International Classification of Diseases (ICD-10) criteria. Results: Mental disorders were detected in 48.3%, predominantly depressive disorders, nicotine dependence, generalized anxiety disorder, alcohol dependence and least was dementia. Most common physical illness was cardiovascular disease followed by metabolic, respiratory and other diseases. Depressive disorders, substance dependence and dementia were more associated with cardiovascular disease compared to metabolic disease and respiratory diseases were more associated with nicotine dependence. Conclusions: Depression and Substance use disorders among elderly population is of concern, which needs to be further studied with larger population. Psychiatric morbidity will adversely have an impact on physical illness which needs proper assessment and management. This will enhance our understanding and prioritize our planning for future.

Keywords: Geriatric, mental disorders, physical illness, psychiatry

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Authors: Anjuri Srivastava, Akhouri Nishant Bhanu

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Soil is a natural material with a distinctive form. It is regarded to be a natural source of nutrients and minerals for plants. It meets many of our needs through the crops, trees, and inhabited places that have grown on or underneath it. Productive and rich soil plays a crucial role in both its wealth and well-being. If any external substance changes the soil's composition, it directly impacts the plant that was grown in that soil. If the soil is deficient in one or more essential components, fly ash can be utilized as fertilizer by incorporating it into the soil. This can also increase the porosity of the soil. Fly ash has a sufficient concentration of essential components to promote the growth of plants. The high concentration of elements in fly ash, including C, Na, K, Fe, and Zn, increases crop yields. Hazardous compounds harm plant life as soon as they get into the soil. The US Environmental Protection Agency and other regulatory agencies have found it as non-hazardous. By employing fly ash as a potential fertilizer supplement for degraded soils, the problem of disposing of solid waste can be partially handled. Fly ash's rapid growth can slow down mineralization because it contains a higher proportion of harmful heavy metals. The chemical characteristics, inclusion ratio, and composting process of fly ash have a significant impact on the fly ash compost’s potential to improve soil nutrition. Research institutions and regulatory agencies have been thoroughly investigating fly ash for a long time. Guard cells on plant leaves that accumulate fly ash trigger the regulatory system. Fly ash increases both chemical and physical damage at certain humidity levels. The lengthy sowing period is caused by the high levels of fly ash in the soil, which also slows down seedling germination and growth. For the sake of human health, it is crucial to consider the bioaccumulation of dangerous heavy metals and their necessary concentrations in plant tissues and soil.

Keywords: soil, fly ash, plant, fertilizer, composts

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Authors: Rana Tajammal Rashid

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Federalism is a political system in which government power and responsibility are divided between a federal legislature and units of the state or provincial legislatures. This system provides the structure for the states having large territory and through that can manage the state affairs and administration easily. Many of the largest countries in the world are federations, like; The United States, Canada, India, Pakistan South Africa, Argentina, and Australia. Every large democratic nation has a federal system of government. This study will explore the feature and good governance of two developed countries Canada and Australia. This study will be helpful to the developing countries like Pakistan, India which have a federal form of structure to run the affairs of the state. In the federal system of Pakistan there are lot of issues and conflicts with the provinces with a comparative study of these two developed countries, i.e., Australia and Canada, our policy and decision maker political actors will understand in which way a state will successfully manage the issues related to federalism. This study will also provide the help to the students of comparative politics that how to analysis the different political system of the developed countries of the world.

Keywords: federalism, features of federalism, types of federalism, history of federalism, Australian federalism, Canadian federalism, federalism developments, executives, federal and provincial autonomy legislative, judicial

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Ni Komang Desy Arya Pinatih

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Transnational crime is a crime with 'unique' feature because the activities benefit the lack of state monitoring on the borders so dealing with it cannot be based on conventional engagement but also need joint operation with other countries. On the other hand with the flow of globalization and the growth of information technology and transportation, states become more vulnerable to transnational crime threats especially human trafficking. This paper would examine transnational crime activities, especially human trafficking in Indonesia. With the case study on the mapping of human trafficking crime in East Java province, Indonesia, this paper would try to analyze how the difference in human trafficking crime trends at the national and sub-national levels. The findings of this research were first, there is difference in human trafficking crime trends whereas at the national level the trend is rising, while at sub-national (province) level the trend is declining. Second, regarding the decline of human trafficking number, it’s interesting to see how the method to decrease human trafficking crime in East Jawa Province in order to reduce transnational crime accounts in the region. These things are hopefully becoming a model for transnational crimes engagement in other regions to reduce human trafficking numbers as much as possible.

Keywords: transnational crime, human trafficking, southeast Asia, anticipation model on transnational crimes

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Authors: H. T. Le Luong, C. Hénaux, F. Messine, G. Bueno-Mariani, S. Mollov, N. Voyer

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This paper presents a comparative study of different modular brushless wound rotor synchronous machine (MB-WRSM). The goal of the study is to highlight the structure which offers the best fault tolerant capability and the highest output performances. The fundamental winding factor is calculated by using the method based on EMF phasors as a significant criterion to select the preferred number of phases, stator slots, and poles. With the limited number of poles for a small machine (3.67kW/7000rpm), 15 different machines for preferred phase/slot/pole combinations are analyzed using two-dimensional (2-D) finite element method and compared according to three criteria: torque density, torque ripple and efficiency. The 7phase/7slot/6pole machine is chosen with the best compromise of high torque density, small torque ripple (3.89%) and high nominal efficiency (95%). This machine is then compared with a reference design surface permanent magnet synchronous machine (SPMSM). In conclusion, this paper provides an electromagnetic analysis of a new brushless wound-rotor synchronous machine using multiphase non-overlapping fractional slot double layer winding. The simulation results are discussed and demonstrate that the MB-WRSM presents interesting performance features, with overall performance closely matching that of an equivalent SPMSM.

Keywords: finite element method (FEM), machine performance, modular wound rotor synchronous machine, non-overlapping concentrated winding

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: T. Heikkinen, J. Oksman, T. Bragge, A. Nurmi, O. Kontkanen, T. Ahtoniemi

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Motor impairment is an inherent phenotypic feature of several chronic neurodegenerative diseases, and pharmacological therapies aimed to counterbalance the motor disability have a great market potential. Animal models of chronic neurodegenerative diseases display a number deteriorating motor phenotype during the disease progression. There is a wide array of behavioral tools to evaluate motor functions in rodents. However, currently existing methods to study motor functions in rodents are often limited to evaluate gross motor functions only at advanced stages of the disease phenotype. The most commonly applied traditional motor assays used in CNS rodent models, lack the sensitivity to capture fine motor impairments or improvements. Fine motor skill characterization in rodents provides a more sensitive tool to capture more subtle motor dysfunctions and therapeutic effects. Importantly, similar approach, kinematic movement analysis, is also used in clinic, and applied both in diagnosis and determination of therapeutic response to pharmacological interventions. The aim of this study was to apply kinematic gait analysis, a novel and automated high precision movement analysis system, to characterize phenotypic deficits in three different chronic neurodegenerative animal models, a transgenic mouse model (SOD1 G93A) for amyotrophic lateral sclerosis (ALS), and R6/2 and Q175KI mouse models for Huntington’s disease (HD). The readouts from walking behavior included gait properties with kinematic data, and body movement trajectories including analysis of various points of interest such as movement and position of landmarks in the torso, tail and joints. Mice (transgenic and wild-type) from each model were analyzed for the fine motor kinematic properties at young ages, prior to the age when gross motor deficits are clearly pronounced. Fine motor kinematic Evaluation was continued in the same animals until clear motor dysfunction with conventional motor assays was evident. Time course analysis revealed clear fine motor skill impairments in each transgenic model earlier than what is seen with conventional gross motor tests. Motor changes were quantitatively analyzed for up to ~80 parameters, and the largest data sets of HD models were further processed with principal component analysis (PCA) to transform the pool of individual parameters into a smaller and focused set of mutually uncorrelated gait parameters showing strong genotype difference. Kinematic fine motor analysis of transgenic animal models described in this presentation show that this method isa sensitive, objective and fully automated tool that allows earlier and more sensitive detection of progressive neuromuscular and CNS disease phenotypes. As a result of the analysis a comprehensive set of fine motor parameters for each model is created, and these parameters provide better understanding of the disease progression and enhanced sensitivity of this assay for therapeutic testing compared to classical motor behavior tests. In SOD1 G93A, R6/2, and Q175KI mice, the alterations in gait were evident already several weeks earlier than with traditional gross motor assays. Kinematic testing can be applied to a wider set of motor readouts beyond gait in order to study whole body movement patterns such as with relation to joints and various body parts longitudinally, providing a sophisticated and translatable method for disseminating motor components in rodent disease models and evaluating therapeutic interventions.

Keywords: Gait analysis, kinematic, motor impairment, inherent feature

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Authors: Abe Degale D., Cheng Jian

Abstract:

When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Arfaoui Emna, Nouira Mariem

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Background and aims: Breastfeeding is the reference feeding for a child, especially during the first months of life. It is not widespread in many countries due to many factors. There has been a decline in exclusive breastfeeding (EB) practice, particularly in the middle- and low-income countries, i.e., Tunisia. The aim of our study was to describe the knowledge, attitudes, and practice of a sample of Tunisian mothers toward breastfeeding. Methods: It was a descriptive cross-sectional study conducted during the year 2022 over a period of two months in three health structures in the north of Tunisia among mothers of infants aged 2 to 18 months. Levels of mothers’ knowledge (low/moderate/high) were determined using a score ranging from 0 to 11 points. EB was defined as the proportion of infants who were exclusively breastfed during the first six months of life. Results: A total of 180 women with a mean age of 33±4.9 years were included. The average knowledge score was equal to 6.4 ±1.5 points, with extremes ranging from 3 to 11 points. Most of the respondents had a moderate knowledge level (44.4%). More than half of surveyed mothers (66.1%) thought that breastfeeding deforms breasts, and 16.7% thought that breastfeeding is specific to women who do not work. Breastfeeding experience during the first week of life was considered difficult in 70% of cases. The prevalence of EB up to 6 months of age was equal to 16.4% [10.8-23.2]. The main reported obstacles during breastfeeding practice were having an insufficient quantity of breast milk (18.3%) and child difficulties with sucking (12.8%), and having pain in the breast while breastfeeding (12.80%). Conclusion: Our results highlighted the insufficient level of knowledge and a low prevalence of EB in our study population. Improving mothers’ knowledge and promoting EB practice is needed. Implementing health education strategies involving healthcare workers, who represent a main actor in education and breastfeeding promotion, is very important to reach a satisfactory frequency for EB.

Keywords: breastfeeding, practices, knowledge, Tunisia

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Authors: Arnold S. Freitas Neto, Rodrigo E. Coelho, Erick S. Mendonça

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The study aims to assess if high-purity iron powder in iron-aluminum alloys can be replaced by SAE 1020 steel chips with an atomicity proportion of 50% for each element. Chips of SAE 1020 are rejected in industrial processes. Thus, the use of SAE 1020 as a replaceable composite for iron increase the sustainability of ferrous alloys by recycling industrial waste. The alloys were processed by high energy milling, of which the main advantage is the minimal loss of raw material. The raw material for three of the six samples were high purity iron powder and recyclable aluminum cans. For the other three samples, the high purity iron powder has been replaced with chips of SAE 1020 steel. The process started with the separate milling of chips of aluminum and SAE 1020 steel to obtain the powder. Subsequently, the raw material was mixed in the pre-defined proportions, milled together for five hours and then underwent a closed-die hot compaction at the temperature of 500 °C. Thereafter, the compacted samples underwent heat treatments known as sintering and solubilization. All samples were sintered one hour, and 4 samples were solubilized for either 4 or 10 hours under well-controlled atmosphere conditions. Lastly, the composition and the mechanical properties of their hardness were analyzed. The samples were analyzed by optical microscopy, scanning electron microscopy and hardness testing. The results of the analysis showed a similar chemical composition and interesting hardness levels with low standard deviations. This verified that the use of SAE 1020 steel chips can be a low-cost alternative for high-purity iron powder and could possibly replace high-purity Iron in industrial applications.

Keywords: Fe-Al alloys, high energy milling, iron-aluminum alloys, metallography characterization, powder metallurgy, recycling ferrous alloy, SAE 1020 steel recycling

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Authors: Billel Kenidra, Mohamed Benmohammed

Abstract:

Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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