Search results for: biophysical and biochemical techniques

Authors: M. G. N. A. S. Fernando

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This study uses a researchable framework to improve the quality of ICT education and the Teaching Learning Assessment/ Evaluation (TLA/TLE) process. It utilizes existing resources while improving the methodologies along with pedagogical techniques and e-Learning approaches used in the secondary schools of Sri Lanka. The study was carried out in two phases. Phase I focused on investigating the factors which affect the quality of ICT education. Based on the key factors of phase I, the Phase II focused on the design of an Experimental Application Model with 6 activity levels. Each Level in the Activity Model covers one or more levels in the Revised Bloom’s Taxonomy. Towards further enhancement of activity levels, other pedagogical techniques (activity based learning, e-learning techniques, problem solving activities and peer discussions etc.) were incorporated to each level in the activity model as appropriate. The application model was validated by a panel of teachers including a domain expert and was tested in the school environment too. The validity of performance was proved using 6 hypotheses testing and other methodologies. The analysis shows that student performance with problem solving activities increased by 19.5% due to the different treatment levels used. Compared to existing process it was also proved that the embedded techniques (mixture of traditional and modern pedagogical methods and their applications) are more effective with skills development of teachers and students.

Keywords: activity models, Bloom’s taxonomy, ICT education, pedagogies

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Authors: H. Kelkoul, Y. Zaz

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Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: digital cinema, watermarking, wavelet DWT, spread spectrum, JPEG2000 MPEG4

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Authors: Paula K. Novelli, Margarida M. Barros, Luciana F. Flueri

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Utilization of agricultural by-products, wheat ban and soybean bran, as substrate for solid state fermentation (SSF) was studied, aiming the achievement of different enzymes from Aspergillus sp. with distinct biological characteristics and its application and improvement on animal nutrition. Aspergillus niger and Aspergillus oryzea were studied as they showed very high yield of phytase and protease production, respectively. Phytase activity was measure using p-nitrophenilphosphate as substrate and a standard curve of p-nitrophenol, as the enzymatic activity unit was the quantity of enzyme necessary to release one μmol of p-nitrophenol. Protease activity was measure using azocasein as substrate. Activity for phytase and protease substantially increased when the different biochemical characteristics were considered in the study. Optimum pH and stability of the phytase produced by A. niger with wheat bran as substrate was between 4.0 - 5.0 and optimum temperature of activity was 37oC. Phytase fermented in soybean bran showed constant values at all pHs studied, for optimal and stability, but low production. Phytase with both substrates showed stable activity for temperatures higher than 80oC. Protease from A. niger showed very distinct behavior of optimum pH, acid for wheat bran and basic for soybean bran, respectively and optimal values of temperature and stability at 50oC. Phytase produced by A. oryzae in wheat bran had optimum pH and temperature of 9 and 37oC, respectively, but it was very unstable. On the other hand, proteases were stable at high temperatures, all pH’s studied and showed very high yield when fermented in wheat bran, however when it was fermented in soybean bran the production was very low. Subsequently the upscale production of phytase from A. niger and proteases from A. oryzae were applied as an enzyme additive in fish fed for digestibility studies. Phytases and proteases were produced with stable enzyme activity of 7,000 U.g-1 and 2,500 U.g-1, respectively. When those enzymes were applied in a plant protein based fish diet for digestibility studies, they increased protein, mineral, energy and lipids availability, showing that these new enzymes can improve animal production and performance. In conclusion, the substrate, as well as, the microorganism species can affect the biochemical character of the enzyme produced. Moreover, the production of these enzymes by SSF can be up to 90% cheaper than commercial ones produced with the same fungi species but submerged fermentation. Add to that these cheap enzymes can be easily applied as animal diet additives to improve production and performance.

Keywords: agricultural by-products, animal nutrition, enzymes production, solid state fermentation

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Authors: Marwa T. Badawy, Alaa F. Bakr, Nesrine Hegazi, Mohamed A. Farag, Ahmed Abdellatif

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Diabetes Mellitus (DM) is a chronic disease affecting a large population worldwide. Africa is rich in native medicinal plants with myriad health benefits, though less explored towards the development of specific drug therapy as in diabetes. This study aims to determine the in vivo antidiabetic potential of the well-reported and traditionally used fruits of Baobab (Adansonia digitata L.) using STZ induced diabetic model. The in-vitro cytotoxic and antioxidant properties were examined using MTT assay on L-929 fibroblast cells and DPPH antioxidant assays, respectively. The extract showed minimal cytotoxicity with an IC50 value of 105.7 µg/mL. Histopathological and immunohistochemical investigations showed the hepatoprotective and the renoprotective effects of A. digitata fruits’ extract, implying its protective effects against diabetes complications. These findings were further supported by biochemical assays, which showed that i.p., injection of a low dose (150 mg/kg) of A. digitata twice a week lowered the fasting blood glucose levels, lipid profile, hepatic and renal markers. For a comprehensive overview of extract metabolites composition, ultrahigh performance (UHPLC) analysis coupled to high-resolution tandem mass spectrometry (HRMS/MS) in synchronization with molecular networks led to the annotation of 77 metabolites, among which 50% are reported for the first time in A. digitata fruits.

Keywords: adansonia digital, diabetes mellitus, metabolomics, streptozotocin, Sprague, dawley rats

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Authors: Mustafa Midilli, Mustafa Salman, Omer Hakan Muglali, Tülay Ögretmen, Sena Cenesiz, Neslihan Ormanci

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This study examined the effects of zinc (Zn) from different sources and microbial phytase on the broiler performance, biochemical parameters and digestibility of nutrients when they were added to broiler diets containing low available phosphorus. A total of 875, 1-day-old male broilers of the Ross 308 strain were randomly separated into two control groups (positive and negative) and five treatment groups each containing 125 birds; each group was divided into 5 replicates of 25 birds. The positive control (PC) group was fed a diet containing adequate concentration (0.45%) of available phosphorus due to mineral premix (except zinc) and feeds. The negative control (NC) group was fed a basal diet including low concentration (0.30%) of available phosphorus due to mineral premix (except zinc) and feeds. The basal diet was supplemented with 0.30% phosphorus and 500 FTU phytase (PH); 0.30% phosphorus and organic zinc (OZ; 75mg/kg of Zn from Zn-proteinate); 0.30% phosphorus and inorganic zinc (IZ; 75 mg/kg of Zn from ZnSO4); 0.30% phosphorus, organic zinc and 500 FTU phytase (OZ + PH); and 0.30% phosphorus, inorganic zinc and 500 FTU phytase (IZ + PH) in the treatment groups 1, 2, 3, 4 and 5, respectively. The lowest value for mean body weight was in the negative control group on a diet containing low available phosphorus. The use of supplementation with organic and inorganic zinc alone or in combination with microbial phytase significantly (P<0.05) increased the digestibility of Zn in the male broilers. Supplementation of those diets with OZ + PH or IZ + PH was very effective for increasing the body weight, body weight gain and the feed conversion ratio. In conclusion, the effects on broilers of diets with low phosphorus levels may be overcome by the addition of inorganic or organic zinc compounds in combination with microbial phytase.

Keywords: broiler, performance, phytase, phosphorus, zinc

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Authors: Yanto Santosa, Rozza Tri Kwatrina

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High Conservation Value (HCV) is an area with conservation function within oil palm plantation. Despite the important role of HCV area in biodiversity conservation and various studies on HCV, there was a lack of research studying the factors determining its success. A preliminary study was conducted to identify the determinant factor of HCV that affected the diversity. Line transect method was used to calculate the species diversity of butterfly, birds, mammals, and herpetofauna species as well as their richness. Specifically for mammals, camera traps were also used. The research sites comprised of 12 HCV areas in 3 provinces of Indonesia (Central Kalimantan, Riau, and Palembang). The relationship between the HCV biophysical factor with the species number and species diversity for each wildlife class was identified using Chi-Square analysis with Cross tab (contingency table). Results of the study revealed that species diversity varied by research locations. Four factors determining the success of HCV area in relations to the number and diversity of wildlife species are land cover types for mammals, the width of area and distance to rivers for birds, and distance to settlements for butterflies.

Keywords: wildlife diversity, oil palm plantation, high conservation value area, ecological factors

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Authors: N. Varsamis, M. Gerasimou, P. Christodoulou, S. Mantzoukis, G. Kolliopoulou, N. Zotos

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Purpose: Body fluids (pleural, peritoneal, synovial, pericardial, cerebrospinal) are an important element in the detection of microorganisms. For this reason, it is important to examine them in the Intensive Care Unit (ICU) patients. Material and Method: Body fluids are transported through sterile containers and enriched as soon as possible with Tryptic Soy Broth (TSB). After one day of incubation, the broth is poured into selective media: Blood, Mac Conkey No. 2, Chocolate, Mueller Hinton, Chapman and Saboureaud agar. The above selective media are incubated directly for 2 days. After this period, if any number of microbial colonies are detected, gram staining is performed. After that, the isolated organisms are identified by biochemical techniques in the automated Microscan system (Siemens) and followed by a sensitivity test on the same system using the minimum inhibitory concentration MIC technique. The sensitivity test is verified by Kirby Bauer-based plate test. Results: In 2017 the Laboratory of Microbiology received 60 samples of body fluids from the ICU. More specifically the Microbiology Department received 6 peritoneal fluid specimens, 18 pleural fluid specimens and 36 cerebrospinal fluid specimens. 36 positive cultures were tested. S. epidermidis was identified in 18 specimens, S. haemolyticus in 6, and E. faecium in 12. Conclusions: The results show low detection of microorganisms in body fluid cultures.

Keywords: body fluids, culture, intensive care unit, microorganisms

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Authors: Koteswara Rao Pagolu, Raghava Rao Tamanam

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In India, genetic disease is a disregarded service element in the community health- protection system. This study aims to gauge the accessibility of services for treating genetic disorders and also to evaluate the practices on deterrence and management services in the district health system. A cross-sectional survey of selected health amenities in the government health sector was conducted from 15 primary health centers (PHC’s), 4 community health centers (CHC’s), 1 district government hospital (DGH) and 3 referral hospitals (RH’s). From these, the existing manpower like 130 medical officers (MO’s), 254 supporting staff, 409 nursing staff (NS) and 45 lab technicians (LT’s) was examined. From the side of private health institutions, 25 corporate hospitals (CH’s), 3 medical colleges (MC’s) and 25 diagnostic laboratories (DL’s) were selected for the survey and from these, 316 MO’s, 995 NS and 254 LT’s were also reviewed. The findings show that adequate staff was in place at more than 70% of health centers, but none of the staff have obtained any operative training on genetic disease management. The largest part of the DH’s had rudimentary infrastructural and diagnostic facilities. However, the greater part of the CHC’s and PHC’s had inadequate diagnostic facilities related to genetic disease management. Biochemical, molecular, and cytogenetic services were not available at PHC’s and CHC’s. DH’s, RH’s, and all selected medical colleges were found to have offered the basic Biochemical genetics units during the survey. The district health care infrastructure in India has a shortage of basic services to be provided for the genetic disorder. With some policy resolutions and facility strengthening, it is possible to provide advanced services for a genetic disorder in the district health system.

Keywords: district health system, genetic disorder, infrastructural amenities, management practices

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Authors: Mustafa Kucukoduk, Evren Yildiztugay, A. Hediye Sekmen, Ismail Turkan, Yavuz Bagci

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In this study, physiological and biochemical responses of Centaurea tuzgoluensis, a Turkish endemic halophyte, to salinity were studied. Therefore, the changes in shoot growth, leaf relative water content (RWC), ion concentrations, lipid peroxidation, hydroxyl (OH.) radical scavenging activity, proline (Pro) content, and antioxidant system [superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX) and glutathione reductase (GR)] were investigated. The 60 days (d) old C. tuzgoluensis seedlings were subjected to 0, 150 and 300 mM NaCl for 7 d and 14 d. The relative shoot growth was generally did not change in the 150 mM NaCl, but reduced with 300 mM NaCl stress at 7 d and 14 d. RWC was higher in 150 mM NaCl-treated leaves than that of 300 mM NaCl. Salinity decreased K+/Na+ ratio, but increased Na+, Cl, Ca+2 and Na+/Cl ratio in the leaves. On the other hand, it did not change or increase the K+ content at 150 and 300 mM NaCl, respectively. MDA content in the 150 and 300 mM NaCl-treated leaves remained close to control at 7 d. This was related to enhanced activities of SOD, CAT, APX and GR enzymes, and their isoenzymes especially Fe-SOD in the leaves. On the other hand, the higher sensitivity to 300 mM NaCl at 14 d was associated with inadequate increase in antioxidant enzymes and the decreased OH radical scavenging activity. All these results suggest that C. tuzgoluensis has different antioxidant metabolisms between short- (7 d) and long-term (14 d) salt treatments and salinity tolerance of C. tuzgoluensis might be closely related to increased capacity of antioxidative system to scavenge reactive oxygen species (ROS) and accumulation of osmoprotectant proline under salinity conditions.

Keywords: antioxidant enzymes, endemic halophyte, ion exchange, lipid peroxidation, antioxidant, enzymes, endemic halophyte, ion exchange, lipid peroxidation, proline, Centaurea tuzgoluensis

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: Ram Prasad Baral

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A large number of herb materials contain Essential Oils with extensive bioactivities. Acknowledging the importance of plants and its medicinal value, extraction of Essential Oil had been done using Steam Distillation method. In this project, Steam Distillation was used to extract oil from different plant materials like Chamomilla recutita (L.) Rauschert, Artemisia Vulgaris L, Rhododendron anthopogon D. Don, Cymbopogon nardus L, Andropogon nardus, Cinnamomum tamala, Juniperus spp, Cymbopohonflexuosus flexuous, Mantha Arvensia, Nardostachys Jatamansi, Wintergreen Essential Oil, and Valeriana Officinalis. Research has confirmed centuries of practical use of essential oils, and we now know that the 'fragrant pharmacy' contains compounds with an extremely broad range of biochemical effects. Essential oils are so termed as they are believed to represent the very essence of odor and flavor. The recovery of Essential Oil from the raw botanical starting material is very important since the quality of the oil is greatly influenced during this step. There is a variety of methods for obtaining volatile oils from plants. Steam distillation method was found to be one of the promising techniques for the extraction of essential oil from plants as reputable distiller will preserve the original qualities of the plant. The distillation was conducted in Clevenger apparatus in which boiling, condensing, and decantation was done. Analysis of essential oil was done using Gas Chromatography-Mass Spectrometer apparatus, which gives evaluates essential oil qualitatively and quantitatively. The volume of essential oil obtained was changing with respect to temperature and time of heating.

Keywords: Chamomilla recutita (L.) Rauschert, Artemisia Vulgaris L, Rhododendron anthopogon D. Don, Cymbopogon nardus L, Andropogon nardus, Cinnamomum tamala, Juniperus spp, Cymbopohonflexuosus flexuous, Mantha

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Authors: Soufiane Fal, Abderahim Aasfar, Ali Ouhssain, Hasnae Choukri, Abelaziz Smouni, Hicham El Arroussi

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Heavy metals contamination is a major environmental concern around the world. It has a harmful impact on plant productivity and poses a serious risk to humans and animals health. In the present study, the effect of Microalgae Crude Extract (MCE) on tomato growth and nutrients uptake exposed to 2 mM Pb2+ and Cd2+ was investigated. In results, 2 mM Pb2+ and Cd2+ showed a significant reduction of tomatobiomass and perturbation in nutrients absorption. Moreover, MCE application in tomato plant exposed to Pb2+ and Cd2+ showed a significant enhancement of biomass compared to tomato plants under Pb2+ and Cd2+. On the other hand, MCE application favoured heavy metals accumulation in root and inhibited their translocation to shoot as phytostabilisation mechanism. Tomato plants showed biochemical responses to Pb2+ and Cd2+ stress with elevation of scavenging enzymes and molecules such as POD, CAT, SOD, Proline, and polyphenols, etc. In addition, the treatment by MCE showed a significant reduction level of the majority of these parameters. Furthermore, the metabolomic analysis revealed a significant change in important metabolites. Pb2+ and Cd2+ showed decrease in SFA and increase of UFA, VLFA, alkanes, alkenes, sterols, which known accumulated as tolerance and resistance mechanism to heavy metal (H.M) stress. However, MCE treatment showed the inverse of these response to return tomato plants to normal state and enhanced tolerance and resistance to heavy metal stress. In the present study, we emphasized that MCE can alleviate H.M stress, enhance tomato plant growth nutrients absorption and improve biochemical responses.

Keywords: microalgae crude extract, heavy metal stress, nutrient uptake, metabolomic analysis, solanum lycopersicum (Tomato), phytostabilisation

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Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

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Authors: Hana Rabbouch

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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

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Authors: A. M. S. S. Amarasiri, A. P. Attanayake, K. A. P. W. Jayatilaka, L. K. B. Mudduwa

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Adriamycin (ADR) is an effective anthracyclin antitumor drug, but its clinical use is limited due to renal toxicity. The leaves of Asparagus falcatus (Family: Liliaceae) have been used in the management of renal diseases since antiquity. In the present investigation, the aqueous leaf extract of A. falcatus was evaluated for acute nephroprotective activity in ADR induced nephrotoxic rats. Nephrotoxicity was induced in healthy male Wistar rats by intraperitoneal administration of ADR 20 mg/kg. The lyophilized powder of the aqueous refluxed (4h) leaf extract of A. falcatus was administered orally at three selected doses; 200, 400 and 600 mg/kg for three consecutive days. Fosinopril sodium (0.09 mg/kg) was used as the standard drug. Administration of the plant extract and the standard drug was commenced 24 hours after the induction of nephrotoxicity to rats. The nephroprotective effect was determined by selected biochemical parameters and by the assessment of histopathology on H and E stained kidney sections. The results were compared to a group of control rats with ADR induced nephrotoxicity. A group of rats administered with the equivalent volume of normal saline served as the healthy control. Administration of ADR 20 mg/kg produced a significant increase in the concentrations of serum creatinine (61%) and urine protein (73%) followed by a significant decrease in serum total protein (21%) and albumin (44%) of the plant extract treated animals compared to the healthy control group (p < 0.05). The aqueous extract of Asparagus falcatus at the three doses; 200, 400 and 600 mg/kg and the standard drug were found to decrease the elevation of concentrations of serum creatinine (33%, 51%, 54% and 42%) and urine protein (8%, 63%, 80% and 86%) respectively. The serum concentrations of total protein (12%, 17%, 29% and 12%) and albumin (3%, 17%, 17% and 16%) were significantly increased compared to the nephrotoxic control group respectively. Assessment of histopathology on H and E stained kidney sections demonstrated that ADR induced renal injury, as evidenced by loss of brush border, cytoplasmic vacuolization, pyknosis in renal tubular epithelial cells, haemorrhages, glomerular congestion and presence of hyaline casts. Treatment with the plant extract and the standard drug resulted in attenuation of the morphological destruction in rats. The results of the present study revealed that the aqueous leaf extract of A. falcatus possesses significant nephroprotective activity against adriamycin induced acute nephrotoxicity. The improved kidney functions were supported with the results of selected biochemical parameters and histological changes observed on H and E stained sections of the kidney tissues in Wistar rats.

Keywords: adriamycin induced nephrotoxicity, asparagus falcatus, biochemical assessment, histopathological assessment, nephroprotective activity

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Authors: Wael M. El-Deeb

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The aim of this study was to assess the pathophysiological importance of lipid profile, acute phase proteins, proinflammatory cytokines and oxidative stress markers in sheep with pneumonic pasteurellosis. Blood samples were collected from 36 Pasteurellamultocida-infected sheep, together with 20 healthy controls. Samples for bacteriological examination (nasal swabs, bronchoalveolar lavage) were collected from all animals and subjected to bacteriological examinations. Moreover, heart blood and lung samples were collected from the dead pneumonic sheep and subjected also to bacteriological examinations. A lipid profile was determined, along with a blood picture and other biochemical parameters. The acute phase proteins (fibrinogen, haptoglobin, serum amyloid A), the proinflammatory cytokine tumour necrosis factor-alpha, interleukins (IL-1α, IL-1β, IL-6), interferon-gamma and the oxidative stress markers malondialdehyde, super oxide dismutase, glutathione and catalase were also measured. The examined biochemical parameters were increased in the pneumonic sheep, except for cholesterol and high-density lipoprotein cholesterol (HDL-c), which were significantly lower than control group. Acute phase proteins and cytokines were significantly higher in the pneumonic sheep when compared to the healthy sheep. There was a significant increase in the levels of malondialdehyde; however, a significant decrease in the levels of super oxide dismutase, glutathione and catalase was observed. The present study shed the light on the possible pathphysiological role of lipid profile, acute phase proteins (APPs), proinflammatory cytokines and oxidative stress markers in pneumonic pasteurelosis in sheep.

Keywords: acute phase proteins, sheep, pasteurella, interleukins, stress

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Authors: Lubabatu Sada Sodangu

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Malaria is a major cause of death in tropical and subtropical nations. Malaria cases are continually rising as a result of a number of factors, despite the fact that the condition is now treatable using effective methods. In this situation, quick and effective diagnostic methods are essential for the management and control of malaria. Malaria diagnosis using conventional methods is still troublesome, hence new technologies have been created and implemented to get around the drawbacks. The review describes the currently known malaria diagnostic techniques, their strengths and shortcomings.

Keywords: malaria, technique, diagnosis, Africa

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Authors: Lubabatu Sada Sodangi

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Malaria is a major cause of death in tropical and subtropical nations. Malaria cases are continually rising as a result of a number of factors, despite the fact that the condition is now treatable using effective methods. In this situation, quick and effective diagnostic methods are essential for the management and control of malaria. Malaria diagnosis using conventional methods is still troublesome; hence, new technologies have been created and implemented to get around the drawbacks. The review describes the currently known malaria diagnostic techniques, their strengths, and shortcomings.

Keywords: malaria, technique, diagnosis, Africa

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Mukul Anand

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Quality oriented affordable shelter for all has always been the key issue in the housing sector of our country. Homelessness is the acute form of housing need. It is a paradox that in spite of innumerable government initiated programmes for affordable housing, certain section of society is still devoid of shelter. About nineteen million (18.78 million) households grapple with housing shortage in Urban India in 2012. In Indian scenario there is major mismatch between the people for whom the houses are being built and those who need them. The prime force faced by public authorities in facilitation of quality housing for all is high cost of construction. The present paper will comprehend executable techniques for dilution of cost factor in housing the homeless. The key actors responsible for delivery of cheap housing stock such as capacity building, resource optimization, innovative low cost building material and indigenous skeleton housing system will also be incorporated in developing these techniques. Time performance, which is an important angle of above actors, will also be explored so as to increase the effectiveness of low cost housing. Along with this best practices will be taken up as case studies where both conventional techniques of housing and innovative low cost housing techniques would be cited. Transportation consists of approximately 30% of total construction budget. Thus use of alternative local solutions depending upon the region would be covered so as to highlight major components of low cost housing. Government is laid back regarding base line information on use of innovative low cost method and technique of resource optimization. Therefore, the paper would be an attempt to bring to light simpler solutions for achieving low cost housing.

Keywords: construction, cost, housing, optimization, shelter

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Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

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his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Arushi Singh, Anjana Jain, Prakash Vyavahare

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Recently, Li-Fi(light-fiedelity) has been launched based on VLC(visible light communication) technique, 100 times faster than WiFi. Now 5G mobile communication system is proposed to use VLC-OFDM as the transmission technique. The VLC system focused on visible rays, is considered for efficient spectrum use and easy intensity modulation through LEDs. The reason of high speed in VLC is LED, as they flicker incredibly fast(order of MHz). Another advantage of employing LED is-it acts as low pass filter results no out-of-band emission. The VLC system falls under the category of ‘green technology’ for utilizing LEDs. In present scenario, OFDM is used for high data-rates, interference immunity and high spectral efficiency. Inspite of the advantages OFDM suffers from large PAPR, ICI among carriers and frequency offset errors. Since, the data transmission technique used in VLC system is OFDM, the system suffers the drawbacks of OFDM as well as VLC, the non-linearity dues to non-linear characteristics of LED and PAPR of OFDM due to which the high power amplifier enters in non-linear region. The proposed paper focuses on reduction of PAPR in VLC-OFDM systems. Many techniques are applied to reduce PAPR such as-clipping-introduces distortion in the carrier; selective mapping technique-suffers wastage of bandwidth; partial transmit sequence-very complex due to exponentially increased number of sub-blocks. The paper discusses three companding techniques namely- µ-law, A-law and advance A-law companding technique. The analysis shows that the advance A-law companding techniques reduces the PAPR of the signal by adjusting the companding parameter within the range. VLC-OFDM systems are the future of the wireless communication but non-linearity in VLC-OFDM is a severe issue. The proposed paper discusses the techniques to reduce PAPR, one of the non-linearities of the system. The companding techniques mentioned in this paper provides better results without increasing the complexity of the system.

Keywords: non-linear companding techniques, peak to average power ratio (PAPR), visible light communication (VLC), VLC-OFDM

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Wei Tian, Jie Liang, Hammad Naveed

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Beta-barrel membrane proteins are found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts. They carry out diverse biological functions, including pore formation, membrane anchoring, enzyme activity, and bacterial virulence. In addition, beta-barrel membrane proteins increasingly serve as scaffolds for bacterial surface display and nanopore-based DNA sequencing. Due to difficulties in experimental structure determination, they are sparsely represented in the protein structure databank and computational methods can help to understand their biophysical principles. We have developed a novel computational method to predict the 3D structure of beta-barrel membrane proteins using evolutionary coupling (EC) constraints and a reduced state space. Combined with an empirical potential function, we can successfully predict strand register at > 80% accuracy for a set of 49 non-homologous proteins with known structures. This is a significant improvement from previous results using EC alone (44%) and using empirical potential function alone (73%). Our method is general and can be applied to genome-wide structural prediction.

Keywords: beta-barrel membrane proteins, structure prediction, evolutionary constraints, reduced state space

Procedia PDF Downloads 618

Authors: Nur Azreena Idris, Soh Kheang Loh, Harrison Lau Lik Nang, Yuen May Choo, Eminour Muzalina Mustafa, Vijaysri Vello, Cheng Yau Tan, Siew Moi Phang

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It is estimated that about 0.65-0.67 m3 of palm oil mill effluent (POME) is generated when one tonne of fresh fruit bunches is processed. Owning to the high content of nutrients in POME, it has high potential as a medium for microalgae growth. This study attempted determining the growth rate, biomass productivity and biochemical composition of microalgae (Chlorella sp.) grown in different POME concentrations i.e. 6.25%, 12.5%, 25% and 50% at outdoor conditions using a 200-mL capacity high rate algae pond (HRAP) and 2 closed photobioreactors (PBRs) i.e. annular and flat panel. The strain, Chlorella sp. grown on 12.5% of POME in flat panel PBR exhibited the highest specific growth rate of 0.32/day and biomass productivity (27.1 mg/L/day) followed by those in HRAP and annular PBR. It further showed that a good growth of Chlorella sp. in 12.5% of POME could sufficiently reduce the nutrients of POME such as phosphate (PO4), nitrate (NO3), nitrite (NO2) and chemical oxygen demand (COD). The extracted algal oil from POME culture showed that the saturated fatty acids decreased while polyunsaturated fatty acids increased compared to those cultured in standard culture medium (Bold’s Basal medium). The biochemical compositions of the algae grown in flat panel PBR were the highest with lipid, protein and carbohydrate productivity of 17.91 mg/L/day, 34.65 mg/L/day and 21.44 mg/L/day, respectively. The microalgae cultivation in diluted POME had not only shown potential as biodiesel feedstock based on the fatty acids profile but also the ability to reduce pollutants e.g. PO4, NO3, NO2 and COD in biological wastewater treatment.

Keywords: wastewater treatment, photobioreactors, biomass productivity, specific growth rate

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Authors: Dilip Singh Sisodia, Shrish Verma

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Spamming is the most common issue seen nowadays in the Internet especially in Online Social Networking Sites (like Facebook, Twitter, and Google+ etc.). Spam messages keep wasting Internet bandwidth and the storage space of servers. On social network sites; spammers often disguise themselves by creating fake accounts and hijacking user’s accounts for personal gains. They behave like normal user and they continue to change their spamming strategy. To prevent this, most modern spam-filtering solutions are deployed on the receiver side; they are good at filtering spam for end users. In this paper we are presenting some spamming techniques their behaviour and possible solutions. We have analyzed how Spammers enters into online social networking sites (OSNSs) and how they target it and the techniques they use for it. The five discussed techniques of spamming techniques which are clickjacking, social engineered attacks, cross site scripting, URL shortening, and drive by download. We have used elgg framework for demonstration of some of spamming threats and respective implementation of solutions.

Keywords: online social networking sites, spam, attacks, internet, clickjacking / likejacking, drive-by-download, URL shortening, networking, socially engineered attacks, elgg framework

Procedia PDF Downloads 347

Authors: Saurabh Kumar

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In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.

Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth

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Authors: L. C. Sánchez, L. C. Corrales, A. G. Lancheros, E. Castañeda, Y. Ariza, L. S. Fuentes, L. Sierra, J. L. Cuervo

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The importance of environment friendly alternatives in agricultural processes is the reason why the research group Ceparium, the Colegio Mayor de Cundinamarca University, Colombia, investigated the genus Bacillus and its applicability for improving crops of economic importance in Colombia. In this investigation, we presented a study in which the genus Bacillus plays a leading role as beneficial microorganism. The objective was to identify the biochemical potential of three indigenous species of Bacillus, which were able to carry out actions for biological control against pathogens and pests or promoted growth to improve productivity of crops in Colombia. The procedures were performed in three phases: first, the production of biomass of an indigenous strain and a reference strain starting from culture media for production of spores and toxins were made. Spore count was done in a Neubauer chamber, concentrations of spores of Bacillus sphaericus were prepared and a bioassay was done at the Laboratory of Entomology at the University Jorge Tadeo Lozano of Plutella xylostella larvae, insect pest of crucifers in several Colombian regions. The second phase included the extraction in the liquid state fermentation, a secondary metabolite that has antibiosis action against fungi, call iturin B, and was obtained from strains of Bacillus subtilis. The molecule was identified using High Resolution Chromatography (HPLC) and its biocontrol effect on Fusarium sp fungus causes vascular wilt in economically important plant varieties, was confirmed using testing of antagonism in Petri dish. In the third phase, an initial procedure in that let recover and identify microorganisms of the genus Bacillus from the rhizosphere in two aromatic herbs, Rosmarinus officinalis and Thymus vulgaris L. was used. Subsequently, testing of antagonism against Fusarium sp were made and an assay was done under greenhouse conditions to observe biocontrol and growth promoting action by comparing growth in length and dry weight. In the first experiment, native Bacillus sphaericus was lethal to 92% Plutella xylostella larvae in 10 DDA. In the second experiment, iturin B was identified and biological control of Fusarium sp was demonstrated. In the third study, all strains demonstrated biological control and the B14 strain identified as Bacillus megaterium increased root length and productivity of the two plants in terms of weight. It was concluded that the native microorganisms of the genus Bacillus has a great biochemical potential that provides a beneficial interactions with plants, improve their growth and development and therefore a greater impact on production.

Keywords: genus bacillus, biological control, PGPRs, biochemical potential

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Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

Procedia PDF Downloads 394