Search results for: acid number

Authors: Haleh Dadgostar, Faramarz Akbari, Hosien Vahid Tari, Masoud Solaymani-Dodaran, Mohammad Razi

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Introduction: There are a number of exercises-protocols have been applied to improve low back pain. We compared the effect of supervised exercise therapy and home-based exercise therapy among patients with nonspecific chronic low back pain. Methods: 70 patients with nonspecific chronic low back pain were randomly (using a random number generator, excel) divided into two groups to compare the effects of two types of exercise therapy. After a common educational session to learn how to live with low back pain as well as to use core training protocols to strengthen the muscles, the subjects were randomly assigned to follow supervised exercise therapy (n = 31) or home-based exercise therapy (n = 34) for 20 weeks. Results: Although both types of exercise programs resulted in reduced pain, this factor decreased more significantly in supervised exercise program. All scores of fitness improved significantly in supervised exercise group. But only knee extensor strength score was increased in the home base exercise group. Conclusion: Comparing between two types of exercise, supervised group exercise showed more effective than the other one. Reduction in low back pain severity and improvement in muscle flexibility and strength can be more achieved by using a 20-week supervised exercise program compared to the home-based exercise program in patients with nonspecific chronic low back pain.

Keywords: low back pain, anthropometric parameters, supervised exercise therapy, home-based exercise therapy

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Authors: Yoshinori Wakatake

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Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

Procedia PDF Downloads 52

Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

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Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

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Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha

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Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.

Keywords: group decision making, intuitionistic fuzzy set, intuitionistic fuzzy entropy measure, vendor selection, VIKOR

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Authors: Ayman El Sabagh, Celaleddin Barutçular, Hirofumi Saneoka

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Drought is one of the most serious problems posing a grave threat to cereals production including maize. Maize improvement in drought-stress tolerance poses a great challenge as the global need for food and bio-enegry increases. Thus, the current study was planned to explore the variations and determine the performance of target traits of maize hybrids at grain growth stage under drought conditions during 2014 under Adana, Mediterranean climate conditions, Turkey. Maize hybrids (Sancia, Indaco, 71May69, Aaccel, Calgary, 70May82, 72May80) were evaluated under (irrigated and water stress). Results revealed that, grain yield and yield traits had a negative effects because of water stress conditions compared with the normal irrigation. As well as, based on the result under normal irrigation, the maximum biological yield and harvest index were recorded. According to the differences among hybrids were found that, significant differences were observed among hybrids with respect to yield and yield traits under current research. Based on the results, grain weight had more effect on grain yield than grain number during grain filling growth stage under water stress conditions. In this concern, according to low drought susceptibility index (less grain yield losses), the hybrid (Indaco) was more stable in grain number and grain weight. Consequently, it may be concluded that this hybrid would be recommended for use in the future breeding programs for production of drought tolerant hybrids.

Keywords: drought susceptibility index, grain growth, grain yield, maize, water stress

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Authors: Amina Bayazid, Habiba Fetati, Houari Toumi

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Introduction: The clinical value of vitamin K antagonists (VKA) has been widely demonstrated in numerous indications. Unfortunately, VKA are not devoid of drawbacks and risk of serious bleeding. The iatrogenic induced by these drugs is a major public health problem. Patients & Methods: We conducted a retrospective study period extending from February 2012 to August 2013 in the pharmacovigilance service of EHUO (clinical pharmacology unit). The prescription of painkillers was analyzed in patients on VKA followed at our level. The influence of these analgesics on the evolution of the INR is an important component in our work. Results: We counted a total of 195 patients, of whom 32 (or 16.41% of the total population) had received analgesic treatment. The frequencies of different categories of analgesics administered were: • Analgesics opioids: 0% • Analgesics weak opioids: Tramadol: 21.87% • The non-opioid analgesics: -AINS: 71.87% (indomethacin: 68.75% ibuprofen: 3.12%) - Paracetamol: 6.25% -Salicyles (Acetylsalicylic acid): 0%. Conclusion: The management of pain in patients under vitamin K antagonists has special features, given their many drug interactions with analgesics and their influence on the evolution of the INR which can have dramatic consequences. As such, special attention must be paid to the use of analgesics in this type of patient.

Keywords: vitamin K antagonists, pain killers, interactions, INR

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: Dinesh Kumar Srivastava

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After liberalization of the economy, technical education has seen rapid growth in India. A large number of institutions are offering various engineering and management programmes. Every year, a number of students complete B. Tech/M. Tech and MBA programmes of different institutes, universities in India and search for jobs in the industry. A large number of companies visit educational institutes for campus placements. These companies are interested in hiring competent managers. Most students show preference for jobs from reputed companies and jobs having high compensation. In this context, this study was conducted to understand career preference of postgraduate students and junior executives. Personality characteristics influence work life as well as personal life. In the last two decades, five factor model of personality has been found to be a valid predictor of job performance and job satisfaction. This approach has received support from studies conducted in different countries. It includes neuroticism, extraversion, and openness to experience, agreeableness, and conscientiousness. Similarly three social needs, namely, achievement, affiliation and power influence motivation and performance in certain job functions. Both approaches have been considered in the study. The objective of the study was first, to analyse the relationship between personality characteristics and career preference of students and executives. Secondly, the study analysed the relationship between personality characteristics and skills of students. Three managerial skills namely, conceptual, human and technical have been considered in the study. The sample size of the study was 266 including postgraduate students and junior executives. Respondents have completed BE/B. Tech/MBA programme. Three dimensions of career preference namely, identity, variety and security and three managerial skills were considered as dependent variables. The results indicated that neuroticism was not related to any dimension of career preference. Extraversion was not related to identity, variety and security. It was positively related to three skills. Openness to experience was positively related to skills. Conscientiousness was positively related to variety. It was positively related to three skills. Similarly, the relationship between social needs and career preference was examined using correlation. The results indicated that need for achievement was positively related to variety, identity and security. Need for achievement was positively related to managerial skills Need for affiliation was positively related to three dimensions of career preference as well as managerial skills Need for power was positively related to three dimensions of career preference and managerial skills Social needs appear to be stronger predictor of career preference and managerial skills than big five traits. Findings have implications for selection process in industry.

Keywords: big five traits, career preference, personality, social needs

Procedia PDF Downloads 263

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Archna Mall, Neelam Agrawal, Hari O. Saxena, Bhavana Sharma

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Butea monosperma occurs widely throughout central Indian states. Eco-friendly natural dyes were isolated in aqueous medium from leaves, bark and flowers of this plant. These dyes were used for dyeing on cotton fabric using various chemical (potassium aluminium sulphate, potassium dichromate, ferrous sulphate, stannous chloride & tannic acid) and natural mordants (rinds of Terminallia bellerica & Terminalia chebula fruits and shells of Prunus dulcis & Juglans regia nuts). Dyeing was carried out using the pre-mordanting technique. Large range of beautiful shades in terms of hue and darkness were recorded because of varying mordant concentrations and combinations. More importantly dyed fabrics registered varying the degree of colour fastness properties to washing (1-3, colour change and 4-5, colour staining), light (2-4), rubbing (4-5, dry and 3-5, wet) and perspiration (1-4, colour change and 4-5, colour staining). Thus, along with flowers which are traditionally known for natural dyes, the leaves and bark may also find their place in textile industries.

Keywords: Butea monosperma, cotton, mordants, natural dyes

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Authors: Carine Cridelich, Pablo Juesas Cano, Emmanuel Ramasso, Noureddine Zerhouni, Bernd Weiler

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Safety is one of the most important considerations when buying a new car. While active safety aims at avoiding accidents, passive safety systems such as airbags and seat belts protect the occupant in case of an accident. In addition to legal regulations, organizations like Euro NCAP provide consumers with an independent assessment of the safety performance of cars and drive the development of safety systems in automobile industry. Those ratings are mainly based on injury assessment reference values derived from physical parameters measured in dummies during a car crash test. The components and sub-systems of a safety system are designed to achieve the required restraint performance. Sled tests and other types of tests are then carried out by car makers and their suppliers to confirm the protection level of the safety system. A Knowledge Discovery in Databases (KDD) process is proposed in order to minimize the number of tests. The KDD process is based on the data emerging from sled tests according to Euro NCAP specifications. About 30 parameters of the passive safety systems from different data sources (crash data, dummy protocol) are first analysed together with experts opinions. A procedure is proposed to manage missing data and validated on real data sets. Finally, a procedure is developed to estimate a set of rough initial parameters of the passive system before testing aiming at reducing the number of tests.

Keywords: KDD process, passive safety systems, sled test, dummy injury assessment reference values, frontal impact

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Authors: Ali A. A. Alqarni, Gamal A. Mohamed, Hossam M. Abdallah, Sabrin R. M. Ibrahim

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Phytochemical investigation of the methanolic extract of aerial parts of Tagetes minuta L. (Family: Asteraceae) using different chromatographic techniques led to the isolation of five compounds; ecliptal (1), scopoletin (2), P-hydroxy benzoic acid (3), patuletin (4), and patuletin-7-O-β-D-glucopyranoside (5) (Figure 1). Their structures were established based on physical, chemical, and spectral data [Ultraviolet (UV), Proton ¹H, Carbon thirteen ¹³C, and Heteronuclear Multiple Bond Correlation (HMBC) NMR], as well as Electrospray Ionization Mass Spectroscopy (ESIMS) and comparison with literature data. Their cytotoxic activity was assessed towards human liver hepatocellular carcinoma (HepG2), human breast cancer (MCF-7), and human colon cancer (HCT116) cancer cell lines using sulphorhodamine B (SRB) assay. It is noteworthy that compound 1 demonstrated a significant cytotoxic potential towards HepG2, MCF7, and HCT116 cells with IC₅₀s ranging from 2.74 to 7.01 μM, compared to doxorubicin (IC₅₀ 0.18, 0.60, and 0.20 μM, respectively), whereas compounds 2, 4, and 5 showed moderate cytotoxic potential with IC50s ranging from 11.71 to 35.64 μM. However, 3 was inactive up to a concentration of 100 μM towards the three tested cancer cell lines.

Keywords: Asteraceae, cytotoxicity, metabolites, Tagetes minuta

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Authors: Mazifah Simis, Azahan Awang, Kadir Arifin

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The brownfield regeneration is being implemented in developped countries. However, as a group 1 developing country in the South East Asia, the rapid development and increasing number of urban population in Malaysia have urged the needs to incorporate the brownfield regeneration into its physical planning development. The increasing number of urban ex-landfills is seen as a new resource that could overcome the issues of inadequate urban green space provisions. With regards to the new development approach in urban planning, this perception study aims to identify the sustainable planning approach based on what the stakeholders have in mind. Respondents consist of 375 local communities within four urban ex-landfill areas and 61 landscape architect and town planner officers in the Malaysian Local Authorities. Three main objectives are set to be achieved, which are (i) to identify ex-landfill issues that need to be overcome prior to the ex-landfill redevelopment (ii) to identify the most suitable types of ex-landfill redevelopment, and (iii) to identify the priority function for ex-landfill redevelopment as the public parks. From the data gathered through the survey method, the order of priorities based on stakeholders' perception was produced. The results show different perception among the stakeholders, but they agreed to the development of the public park as the main development. Hence, this study attempts to produce an integrated approach as a model for sustainable ex-landfill redevelopment that could be accepted by the stakeholders as a beneficial future development that could change the image of 296 ex-landfills in Malaysia into the urban public parks by the year 2020.

Keywords: brownfield regeneration, ex-landfill redevelopment, integrated approach, stakeholders' perception

Procedia PDF Downloads 335

Authors: C. Soffritti, A. Fortini, E. Baroni, M. Merlin, G. L. Garagnani

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Aluminum alloys are widely used in many engineering applications due to their advantages such ashigh electrical and thermal conductivities, low density, high strength to weight ratio, and good corrosion resistance. However, their low hardness and poor tribological properties still limit their use in industrial fields requiring sliding contacts. Hard anodizing is one of the most common solution for overcoming issues concerning the insufficient friction resistance of aluminum alloys. In this work, the tribological behavior ofhard-anodized AW-4006 aluminum alloys in dry and lubricated conditions was evaluated. Three different hard-anodizing treatments were selected: a conventional one (HA) and two innovative golden hard-anodizing treatments (named G and GP, respectively), which involve the sealing of the porosity of anodic aluminum oxides (AAO) with silver ions at different temperatures. Before wear tests, all AAO layers were characterized by scanning electron microscopy (VPSEM/EDS), X-ray diffractometry, roughness (Ra and Rz), microhardness (HV0.01), nanoindentation, and scratch tests. Wear tests were carried out according to the ASTM G99-17 standard using a ball-on-disc tribometer. The tests were performed in triplicate under a 2 Hz constant frequency oscillatory motion, a maximum linear speed of 0.1 m/s, normal loads of 5, 10, and 15 N, and a sliding distance of 200 m. A 100Cr6 steel ball10 mm in diameter was used as counterpart material. All tests were conducted at room temperature, in dry and lubricated conditions. Considering the more recent regulations about the environmental hazard, four bio-lubricants were considered after assessing their chemical composition (in terms of Unsaturation Number, UN) and viscosity: olive, peanut, sunflower, and soybean oils. The friction coefficient was provided by the equipment. The wear rate of anodized surfaces was evaluated by measuring the cross-section area of the wear track with a non-contact 3D profilometer. Each area value, obtained as an average of four measurements of cross-section areas along the track, was used to determine the wear volume. The worn surfaces were analyzed by VPSEM/EDS. Finally, in agreement with DoE methodology, a statistical analysis was carried out to identify the most influencing factors on the friction coefficients and wear rates. In all conditions, results show that the friction coefficient increased with raising the normal load. Considering the wear tests in dry sliding conditions, irrespective of the type of anodizing treatments, metal transfer between the mating materials was observed over the anodic aluminum oxides. During sliding at higher loads, the detachment of the metallic film also caused the delamination of some regions of the wear track. For the wear tests in lubricated conditions, the natural oils with high percentages of oleic acid (i.e., olive and peanut oils) maintained high friction coefficients and low wear rates. Irrespective of the type of oil, smallmicrocraks were visible over the AAO layers. Based on the statistical analysis, the type of anodizing treatment and magnitude of applied load were the main factors of influence on the friction coefficient and wear rate values. Nevertheless, an interaction between bio-lubricants and load magnitude could occur during the tests.

Keywords: hard anodizing treatment, silver ions, bio-lubricants, sliding wear, statistical analysis

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Authors: Omaima G. Allam, O. A. Hakeim, K. Haggag, N. S. Elshemy

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In the midst of the two decades the use of microwave dielectric warming in the field of science has transformed into a powerful methodology to redesign compound procedures. The potential benefit of the application of these modern methods of treatment emphasize so as to reach to optimum treatment conditions and the best results, especially hydrophobicity, moisture content and increase dyeing processing while maintaining the physical and chemical properties of each textile. Moreover, polyester fibres are sometimes spun together with natural fibres to produce a cloth with blended properties. So that at the present task, the polyester/viscose mix fabrics (60 /40) were pretreated with 4 g/l of KOH for 2 min in microwave irradiation with a liquor ratio 1:25. Subsequently fabrics were inundated with different concentrations of sericin (10, 30, 50 g/l). Treated fabrics were coloured with the commercial dyes samples: Reactive Red 84(Dye 1). C. I. Acid Blue 203(Dye 2) and C.I. Reactive violet 5 (Dye 3). Colour value was specified as well as fastness properties. Likewise, the physical properties of untreated and treated fabrics such as moisture content %, tensile strength, elongation % and were evaluated. The untreated and treated fabrics are described by infrared spectroscopy (FTIR) and scanning electron microscopy.

Keywords: polyester viscose blends fabric, sericin, dyes, colour value

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Authors: Wynne De Jong, Robert Miller, Ross Riggs

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Beyond the number of nurses providing care for patients, having nurses with the right skills, experience and education is essential to ensure the best possible outcomes for patients. Research studies continue to link nurse staffing and skill mix with nurse-sensitive patient outcomes; numerous studies clearly show that superior patient outcomes are associated with higher levels of regulated staff. Due to the limited number of tools and processes available to assist nurse leaders with staffing models of care, nurse leaders are constantly faced with the ongoing challenge to ensure their staffing models of care best suit their patient population. In 2009, several hospitals in Ontario, Canada participated in a research study to develop and evaluate an RN/RPN utilization toolkit. The purpose of this study was to develop and evaluate a toolkit for Registered Nurses/Registered Practical Nurses Staff mix decision-making based on the College of Nurses of Ontario, Canada practice standards for the utilization of RNs and RPNs. This paper will highlight how an organization has further developed the Patient Care Needs Assessment (PCNA) questionnaire, a major component of the toolkit. Moreover, it will demonstrate how it has utilized the information from PCNA to clearly identify patient and family care needs, thus providing evidence-based results to assist leaders with matching the best staffing skill mix to their patients.

Keywords: nurse staffing models of care, skill mix, nursing health human resources, patient safety

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Authors: Mohammad Fereidoonnezhad, Seán Leen, Stephen Nash, Patrick McGarry

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From the perspective of research innovation, the tidal energy industry is still in its early stages. While a very small number of turbines have progressed to utility-scale deployment, blade breakage is commonly reported due to the enormous hydrodynamic loading applied to devices. The aim of this study is the development of computer simulation technologies for the design of next-generation fibre-reinforced composite tidal turbines. This will require significant technical advances in the areas of tidal turbine testing and multi-scale computational modelling. The complex turbine blade profiles are designed to incorporate non-linear distributions of airfoil sections to optimize power output and self-starting capability while reducing power fluctuations. A number of candidate blade geometries are investigated, ranging from spiral geometries to parabolic geometries, with blades arranged in both cylindrical and spherical configurations on a vertical axis turbine. A combined blade element theory (BET-start-up model) is developed in MATLAB to perform computationally efficient parametric design optimisation for a range of turbine blade geometries. Finite element models are developed to identify optimal fibre-reinforced composite designs to increase blade strength and fatigue life. Advanced fluid-structure-interaction models are also carried out to compute blade deflections following design optimisation.

Keywords: tidal turbine, composite materials, fluid-structure-interaction, start-up capability

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Authors: Lavanya Ratnabala, Robinroy Peter, E. Y. A. Charles

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This research paper addresses the challenges of exploration and navigation in unknown environments from an evolutionary swarm robotics perspective. Path formation plays a crucial role in enabling cooperative swarm robots to accomplish these tasks. The paper presents a method called the sub-goal-based path formation, which establishes a path between two different locations by exploiting visually connected sub-goals. Simulation experiments conducted in the Argos simulator demonstrate the successful formation of paths in the majority of trials. Furthermore, the paper tackles the problem of inter-collision (traffic) among a large number of robots engaged in path formation, which negatively impacts the performance of the sub-goal-based method. To mitigate this issue, a task allocation strategy is proposed, leveraging local communication protocols and light signal-based communication. The strategy evaluates the distance between points and determines the required number of robots for the path formation task, reducing unwanted exploration and traffic congestion. The performance of the sub-goal-based path formation and task allocation strategy is evaluated by comparing path length, time, and resource reduction against the A* algorithm. The simulation experiments demonstrate promising results, showcasing the scalability, robustness, and fault tolerance characteristics of the proposed approach.

Keywords: swarm, path formation, task allocation, Argos, exploration, navigation, sub-goal

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Authors: Barenten Suciu

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Classical matrix calculus and Routh-Hurwitz stability conditions, applied to the snake-like motion of the conical wheel axle, lead to the conclusion that the hunting mode is inherently unstable, and its natural frequency is a complex number. In order to analytically solve such a complicated vibration model, either the inertia terms were neglected, in the model designated as geometrical, or restrictions on the creep coefficients and yawing diameter were imposed, in the so-called dynamical model. Here, an alternative solution is proposed to solve the hunting mode, based on the observation that the bullet train wheel axle is equipped with cylindrical wheels. One argues that for such wheel treads, the geometrical hunting is irrelevant, since its natural frequency becomes nil, but the dynamical hunting is significant since its natural frequency reduces to a real number. Moreover, one illustrates that the geometrical simplification of the wheel causes the stabilization of the hunting mode, since the characteristic quartic equation, derived for conical wheels, reduces to a quadratic equation of positive coefficients, for cylindrical wheels. Quite simple analytical expressions for the damping ratio and natural frequency are obtained, without applying restrictions into the model of contact. Graphs of the time-depending hunting lateral perturbation, including the maximal and inflexion points, are presented both for the critically-damped and the over-damped wheel axles.

Keywords: bullet train, creep, cylindrical wheels, damping, dynamical hunting, stability, vibration analysis

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Surajj Sarode, G. Vidya Sagar, G. P. Vadnere

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The purpose of the present study was to prolong the gastric residence time of Stavudine by developing gastric floating drug delivery system (GFDDS). Moreover, to study influence of different polymers on its release rate using gas-forming agents, like sodium bicarbonate, citric acid. Floating tablets were prepared by wet granulation method using PVP K-30 as a binder and the other polymers include Pullulan Gum, HPMC K100M, six different formulations with the varying concentrations of polymers were prepared and the tablets were evaluated in terms of their pre-compression parameters like bulk density, tapped density, Haunsner ratio, angle of repose, compressibility index, post compression physical characteristics, in vitro release, buoyancy, floating lag time (FLT), total floating time (TFT) and swelling index. All the formulations showed good floating lag time i.e. less than 3 mins. The batch containing combination of Pullulan Gum and HPMC 100M (i.e. F-6) showed total floating lag time more than 12 h., the highest swelling index among all the prepared batches. The drug release was found to follow zero order kinetics.

Keywords: Suavudine, floating, total floating time (TFT), gastric residence

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Authors: Mahsa Kangazian Kangazi, Ali Akbar Ghareh Aghaji, Majid Montazer

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Nowadays, silica nanofibers are highly regarded among the inorganic nanofibers due to the high reactivity and availability of silicon compounds in nature. Sol-gel process is required for electrospinning of silica nanofibers in which a metal alkoxide is hydrolyzed, and the viscosity is increased. In this study, silica nanofibers containing silver nanoparticles were synthesized and electrospun from a mixture of silica sol with an easy spinnable polymer (PVA) as an additive. The silica sol contains tetraethyl orthosilicate (TEOS), silver nitrate, distilled water, nitric acid, and ethanol. Nanofibers were formed through electrospinning setup. The nanofibers were calcinated to remove the solvent and additive polymer. Consequently, pure silica nanofibers were produced. FTIR analysis indicated entire removal of polyvinyl alcohol from the structure and formation of silan groups. The presence of silver, silica and oxygen was confirmed by EDX. Also, XRD patterns revealed the presence of silver nanoparticles with a mean crystal size of 18 nm. FESEM images showed that adding silver nitrate into the sol-gel, resulted in lower nanofibers diameter from 286 to 136 nm. Furthermore, the electrospun nanofibers were more resistance in acidic media than alkaline media.

Keywords: in situ synthesis of silver nanoparticles, silica nanofibers, sol-gel, tetraethyl orthosilicate

Procedia PDF Downloads 160

Authors: Prem Kumar, Anuj Tyagi, Harsh Panwar, Vaneet Inder Kaur

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Though aquaculture started as an occupation for poor and weak farmers for livelihood, it has now acquired the shape of one of the biggest industry to grow live protein in the form of aquatic organisms. Industrialization of the aquaculture sector has led to intensification resulting in stress on aquatic organisms and frequent disease outbreaks leading to huge economic impacts. Indiscriminate use of antibiotics as growth promoter and prophylactic agent in aquaculture has resulted in rapid emergence and spread of antibiotic resistance in bacterial pathogens. Over the past few years, use of probiotics (as an alternative of antibiotics) in aquaculture has gained attention due to their immunostimulant and growth promoting properties. It has now well known that after administration, a probiotic bacterium has to compete and establish itself against native microbiota to show its eventual beneficial properties. Due to their non-fish origin, commercial probiotics sometimes may display poor probiotic functionalities and antagonistic effects. Thus, isolation and characterization of probiotic bacteria from same fish host is very much necessary. In this study, attempts were made to isolate potent probiotic lactic acid bacteria (LAB) from intestinal microflora of rohu fish. Twenty-five experimental rohu fishes (mean weight 400 ± 20gm, mean standard length 20 ± 3cm) were used in the study to collect fish gut after dissection in a sterile condition. A total of 150 tentative LAB isolates from selective agar media (de Man-Rogosa-Sharpe (MRS)) were screened for their antimicrobial activity against Aeromonas hydrophila and Microccocus leuteus. A total of 17 isolates, identified as Lactobacillus plantarum and Lactococcus lactis, identified by biochemical tests and PCR amplification and sequencing of 16S rRNA gene fragment, displayed promising antimicrobial activity against both the pathogens. Two isolates from each species (FLB1, FLB2 from L. plantarum; and FLC1, FLC2 from L. lactis) were subjected to downstream probiotic potential characterization. These isolates were compared in vitro for their hemolytic activity, acid and bile tolerance for growth kinetics, auto-aggregation, cell-surface hydrophobicity against xylene, and chloroform, tolerance to phenol, cell adhesion, and safety parameters (by intraperitoneal and intramuscular injections). None of the tested isolates showed any hemolytic activity indicating their potential safety. Moreover, these isolates were tolerant to 0.3% bile (75-82% survival), phenol stress (96-99% survival) with 100% viability at pH 3 over a period of 3 h. Antibiotic sensitivity test revealed that all the tested LAB isolates were resistant to vancomycin, gentamicin, streptomycin, and erythromycin and sensitive to Erythromycin, Chloramphenicol, Ampicillin, Trimethoprim, and Nitrofurantoin. Tetracycline resistance was found in L. plantarum (FLB1 and FLB2 isolates), whereas L. lactis were susceptible to it. Intramuscular and intraperitoneal challenges to fingerlings of rohu fish (5 ± 1gm weight) with FLB1 showed no pathogenicity and occurrence of disease symptoms in fishes over an observation period of 7 days. The results revealed FLB1 as a potential probiotic candidate for aquaculture application among other isolates.

Keywords: aquaculture, Lactobacillus plantarum, Lactococcus lactis, probiotics

Procedia PDF Downloads 117

Authors: M. P. S. Tomar, Himanshu R. Joshi, P. Jagapathi Ramayya, Rakhi Vaish, A. B. Shrivastav

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The morphology of an organ system varies according to the feeding habit, habitat and nature of their life-style. This phenomenon is called adaptation. During evolution these morphological changes make the system species specific so the study on the differential characteristics of them makes the understanding regarding the morpho-physiological adaptation easier. Hence the present study was conducted on esophagus of pariah kite, median egret, goshawk, dove and duck. Esophagus in all birds was comprised of four layers viz. Tunica mucosa, Tunica submucosa, Tunica muscularis and Tunica adventitia. The mucosa of esophagus showed longitudinal folds thus the lumen was irregular. The epithelium was stratified squamous in all birds but in Median egret the cells were large and vacuolated. Among these species very thick epithelium was observed in goshawk and duck but keratinization was highest in dove. The stratum spongiosum was 7-8 layers thick in both Pariah kite and Goshawk. In all birds, the glands were alveolar mucous secreting type. In Median egret and Pariah kite, these were round or oval in shape and with or without lumen depending upon the functional status whereas in Goshawk the shape of the glands varied from spherical / oval to triangular with openings towards the lumen according to the functional activity and in dove these glands were oval in shape. The glands were numerous in number in egret while one or two in each fold in goshawk and less numerous in other three species. The core of the mucosal folds was occupied by the lamina propria and showed large number of collagen fibers and cellular infiltration in pariah kite, egret and dove where as in goshawk and duck, collagen and reticular fibers were fewer and cellular infiltration was lesser. Lamina muscularis was very thick in all species and it was comprised of longitudinally arranged smooth muscle fibers. In Median egret, it was in wavy pattern. Tunica submucosa was very thin in all species. Tunica muscularis was mostly comprised of circular smooth muscle bundles in all species but the longitudinal bundles were very few in number and not continuous. The tunica adventitia was comprised of loose connective tissue fibers containing collagen and elastic fibers with numerous small blood vessels in all species. Further, it was observed that the structure of esophagus in birds varies according to their feeding habits.

Keywords: dove, duck, egret, esophagus, goshawk, kite

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Authors: Mandana Hoseini

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During last decades, intensive selection for higher growth rate in broiler chickens has accelerated daily body weight gain, which this has changed/increased the trends and amounts of nutrient requirements in the diet. As a result, considerable studies have been focused on the better determination of protein/amino acids requirements in modern broiler diets. One approach to minimize dietary crude protein inclusion levels is substitution of some of the dietary crude protein with synthetic amino acids. In addition, using synthetic forms of limiting essential amino acids in the diet could help better coincidence of dietary protein with ideal protein concept, which this in turn, minimizes nitrogen dissipation and environmental pollution. Threonine is usually considered as the third limiting amino acid in broiler diets. Recent studies have been demonstrated that dietary supplemental threonine would optimize growth performance, immune system, intestinal morphology, as well as oxidative defense in broiler chickens. In this review, threonine metabolism and its effects in relation with different aspects of broiler performance have been discussed.

Keywords: immune system, intestine, performance, requirement, threonine

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Authors: Kais Ben-Ahmed, Mhamed Ali-El-Aroui

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This paper develops a Local Generalized Linear Spatial Model (LGLSM) to describe the spatial variation of Visceral Leishmaniasis (VL) infection risk in northern and central Tunisia. The response from each region is a number of affected children less than five years of age recorded from 1996 through 2006 from Tunisian pediatric departments and treated as a poison county level data. The model includes climatic factors, namely averages of annual rainfall, extreme values of low temperatures in winter and high temperatures in summer to characterize the climate of each region according to each continentality index, the pluviometric quotient of Emberger (Q2) to characterize bioclimatic regions and component for residual extra-poison variation. The statistical results show the progressive increase in the number of affected children in regions with high continentality index and low mean yearly rainfull. On the other hand, an increase in pluviometric quotient of Emberger contributed to a significant increase in VL incidence rate. When compared with the original GLSM, Bayesian locally modeling is improvement and gives a better approximation of the Tunisian VL risk estimation. According to the Bayesian approach inference, we use vague priors for all parameters model and Markov Chain Monte Carlo method.

Keywords: generalized linear spatial model, local model, extra-poisson variation, continentality index, visceral leishmaniasis, Tunisia

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Authors: Irina Belozerova

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In the recent years, the number of crimes against peace and humanity has constantly been increasing. The development of the international community is inseparably connected to the compliance with the law which protects the rights and interests of citizens in all of their manifestations. The provisions of the law of criminal procedure are no exception. The rights of the victims of genocide, of the war crimes and the crimes against humanity, require particular attention. These crimes fall within the jurisdiction of the International Criminal Court governed by the Rome Statute of the International Criminal Court. These crimes have the following features. First, any such crime has a mass character and therefore requires specific regulation in the international criminal law and procedure and the national criminal law and procedure of different countries. Second, the victims of such crimes are usually children, women and old people; the entire national, ethnic, racial or religious groups are destroyed. These features influence the classification of victims by the age criterion. Article 68 of the Rome Statute provides for protection of the safety, physical and psychological well-being, dignity and privacy of victims and witnesses and thus determines the procedural status of these persons. However, not all the persons whose rights have been violated by the commission of these crimes acquire the status of victims. This is due to the fact that such crimes affect a huge number of persons and it is impossible to mention them all by name. It is also difficult to assess the entire damage suffered by the victims. While assessing the amount of damages it is essential to take into account physical and moral harm, as well as property damage. The procedural status of victims thus gains an exclusive character. In order to determine the full extent of the damage suffered by the victims it is necessary to collect sufficient evidence. However, it is extremely difficult to collect the evidence that would ensure the full and objective protection of the victims’ rights. While making requests for the collection of evidence, the International Criminal Court faces the problem of protection of national security information. Religious beliefs and the family life of victims are of great importance. In some Islamic countries, it is impossible to question a woman without her husband’s consent which affects the objectivity of her testimony. Finally, the number of victims is quantified by hundreds and thousands. The assessment of these elements demands time and highly qualified work. These factors justify the creation of a mechanism that would help to collect the evidence and establish the truth in the international criminal proceedings. This mechanism will help to impose a just and appropriate punishment for the persons accused of having committed a crime, since, committing the crime, criminals could not misunderstand the outcome of their criminal intent.

Keywords: crimes against humanity, evidence in international criminal proceedings, international criminal proceedings, protection of victims

Procedia PDF Downloads 232

Authors: Seema Sangwan, Ekta Narwal, Kannepalli Annapurna

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The aim of this study was to determine the effect of arbuscular mycorrhizal fungi (AMF) inoculation on drought stress tolerance in 3 genotypes of wheat subjected to moderate water stress, i.e. HD 3043 (drought tolerant), HD 2987 (drought tolerant), and HD 2967 (drought sensitive). Various growth parameters were studied, e.g. total dry weight, total shoot and root length, root volume, root surface area, grain weight and number, leaf area, chlorophyll content in leaves, relative water content, number of spores and percent colonisation of roots by arbuscular mycorrhizal fungi. Total dry weight, root surface area and chlorophyll content were found to be significantly high in AMF inoculated plants as compared to the non-mycorrhizal ones and also higher in drought-tolerant varieties of wheat as compared to the sensitive variety HD 2967, in moderate water stress treatments. Leakage of electrolytes was lower in case of AMF inoculated stressed plants. Under continuous water stress, leaf water content and leaf area were significantly increased in AMF inoculated plants as compared to un-inoculated stressed plants. Overall, the increased colonisation of roots of wheat by AMF in inoculated plants weather drought tolerant or sensitive could have a beneficial effect in alleviating the harmful effects of water stress in wheat and delaying its senescence.

Keywords: Arbuscular mycorrhizal fungi, wheat, drought, stress

Procedia PDF Downloads 178