Search results for: ADL identification

Authors: Caroline Provost, Francois Dumont

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Production of insects for human and animal consumption is an increasingly important activity in Canada. Protein production is more efficient and less harmful to the environment using insect rearing compared to the impact of traditional livestock, poultry and fish farms. Insects are rich in essential amino acids, essential fatty acids and trace elements. Thus, insect-based products could be used as a food supplement for livestock and domestic animals and may even find their way into the diets of high performing athletes or fine dining. Nevertheless, several parameters remain to be determined to ensure efficient and profitable production that meet the potential of these sectors. This project proposes to improve the production processes, rearing diets and processing methods for three species with valuable gastronomic and nutritional potential: the common mealworms (Tenebrio molitor), the small mealworm (Alphitobius diaperinus), and the giant mealworm (Zophobas morio). The general objective of the project is to acquire specific knowledge for mass rearing of insects dedicated to animal and human consumption in order to respond to current market opportunities and meet a growing demand for these products. Mass rearing of the three species of mealworm was produced to provide the individuals needed for the experiments. Mealworms eat flour from different cereals (e.g. wheat, barley, buckwheat). These cereals vary in their composition (protein, carbohydrates, fiber, vitamins, antioxidant, etc.), but also in their purchase cost. Seven different diets were compared to optimize the yield of the rearing. Diets were composed of cereal flour (e.g. wheat, barley) and were either mixed or left alone. Female fecundity, larvae mortality and growing curves were observed. Some flour diets have positive effects on female fecundity and larvae performance while each mealworm was found to have specific diet requirements. Trade-offs between mealworm performance and costs need to be considered. Experiments on the effect of flour composition on several parameters related to performance and nutritional and gastronomic value led to the identification of a more appropriate diet for each mealworm.

Keywords: mass rearing, mealworm, human consumption, diet

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Ayat-Allah Bouramdane

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Since 2010, there have been sustained decreases in the unit costs of onshore wind energy and large increases in its deployment, varying widely across regions. In fact, the onshore wind production is affected by air density— because cold air is more dense and therefore more effective at producing wind power— and by wind speed—as wind turbines cannot operate in very low or extreme stormy winds. The wind speed is essentially affected by the surface friction or the roughness and other topographic features of the land, which slow down winds significantly over the continent. Hence, the identification of the most appropriate locations of onshore wind systems is crucial to maximize their energy output and therefore minimize their Levelized Cost of Electricity (LCOE). This study focuses on the preliminary assessment of onshore wind energy potential, in several areas in Morocco with a particular focus on the Dakhla city, by analyzing the diurnal and seasonal variability of wind speed for different hub heights, the frequency distribution of wind speed, the wind rose and the wind performance indicators such as wind power density, capacity factor, and LCOE. In addition to climate criterion, other criteria (i.e., topography, location, environment) were selected fromGeographic Referenced Information (GRI), reflecting different considerations. The impact of each criterion on the suitability map of onshore wind farms was identified using the Analytic Hierarchy Process (AHP). We find that the majority of suitable zones are located along the Atlantic Ocean and the Mediterranean Sea. We discuss the sensitivity of the onshore wind site suitability to different aspects such as the methodology—by comparing the Multi-Criteria Decision-Making (MCDM)-AHP results to the Mean-Variance Portfolio optimization framework—and the potential impact of climate change on this suitability map, and provide the final recommendations to the Moroccan energy strategy by analyzing if the actual Morocco's onshore wind installations are located within areas deemed suitable. This analysis may serve as a decision-making framework for cost-effective investment in onshore wind power in Morocco and to shape the future sustainable development of the Dakhla city.

Keywords: analytic hierarchy process (ahp), dakhla, geographic referenced information, morocco, multi-criteria decision-making, onshore wind, site suitability.

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Authors: Sara Taghdisi, Mehrosadat Mirmohammadi, Mostafa Mokhtarian, Mohammad Hossein Pazandeh

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Leishmaniasis is one of the 10 most important diseases of the World Health Organization with health problems in more than 90 countries. Over one billion people are at risk of these diseases on almost every continent. The present human study was performed to evaluate the therapeutic effect of cotton plant on cutaneous leishmaniasis leision. firstly, the cotton seeds were cleaned and grinded to smaller particles. In the second step, the seeds were oiled by cold press method. In order to separate bioactive compound, after saponification of the oil, its gossypol was hydrolyzed and crystalized. finally, the therapeutic effect of Cottonseed Oil on cutaneous leishmaniasis was investigated. In the current project, Gossypol was extracted with a liquid-liquid extraction method in 120 minutes in the presence of Phosphoric acid from the cotton seed oil of Golestan beach varieties, then got crystallized in darkness using Acetic acid and isolated as Gossypol Acetic acid. The efficiency of the extracted crystal was obtained at 1.28±0.12. the cotton plant could be efficient in the treatment of Cutaneous leishmaniasis. This double-blind randomized controlled clinical trial was performed on 88 cases of leishmaniasis wounds. Patients were randomly divided into two groups of 44 cases. two groups received conventional treatment. In addition to the usual treatment (glucantime), the first group received cottonseed oil and the control group received placebo. The results of the present study showed that the surface of lesion before the intervention and in the first to fourth weeks after the intervention was not significantly different between the two groups (P-value> 0.05). But the surface of lesion in the Intervention group in the eighth and twelfth weeks was lower than the control group (P-value <0.05). This study showed that the improvement of leishmaniasis lesion using topical cotton plant mark in the eighth and twelfth weeks after the intervention was significantly more than the control group. Considering the most common chemical drugs for Cutaneous leishmaniasis treatment are sodium stibogluconate, and meglumine antimonate, which not only have relatively many side effects, but also some species of the Leishmania genus have become resistant to them. Therefore, a plant base bioactive compound such as cottonseed oil can be useful whit fewer side effects.

Keywords: cottonseed oil, crystallization, gossypol, leishmaniasis

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Authors: Luís R. Silva, Ana C. Gonçalves, Catarina Bento, Fábio Jesus, Branca M. Silva

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Prunus avium Linnaeus, more known as sweet cherry, is one of the most appreciated fruit worldwide. Most of these quantities are produced in Fundão region, being Saco the cultivar most produced. Saco is very rich in bioactive compounds, especially phenolics, and presents great antioxidant capacity. The purpose of the present study was to investigate the chemical profile and biological potential, concerning antioxidant, anti-diabetic activity and protective effects towards erythrocytes by Saco sweet cherry collected from Fundão region (Portugal). The hydroethanolic extracts were prepared and passed through a C18 solid-phase extraction column. The phenolic profile analyzed by LC-DAD method allowed to the identification of 22 phenolic compounds, being 16 non-phenolics and 6 anthocyanins. In respect to non-coloured phenolics, 3-O-caffeoylquinic and ρ-coumaroylquinic acids were the main ones. Concerning to anthocyanins, cyanidin-3-O-rutinoside was found in higher amounts. Relatively to biological potential, Saco showed great antioxidant potential, through DPPH and NO radical assays, with IC50 =16.24 ± 0.46 µg/mL and IC50 = 176.69 ± 3.35 µg/mL for DPPH and NO, respectively. These results were similar to those obtained for ascorbic acid control (IC50 = 16.92 ± 0.69 and IC50 = 162.66 ± 1.31 μg/mL for DPPH and NO, respectively). In respect to antidiabetic potential, Saco revealed capacity to inhibit α-glucosidase in a dose-dependent manner (IC50 = 10.79 ± 0.40 µg/mL), being much active than positive control acarbose (IC50 = 306.66 ± 0.84 μg/mL). Additionally, Saco extracts revealed protective effects against ROO•-mediated toxicity generated by AAPH in human blood erythrocytes, inhibiting hemoglobin oxidation (IC50 = 38.57 ± 0.96 μg/mL) and hemolysis (IC50 = 73.03 ± 1.48 μg/mL), in a concentration-dependent manner. However, Saco extracts were less effective than quercetin control (IC50 = 3.10 μg/mL and IC50 = 0.7 μg/mL for inhibition of hemoglobin oxidation and hemolysis, respectively). The results obtained showed that Saco is an excellent source of phenolic compounds. These ones are natural antioxidant substances, which easily capture reactive species. This work presents new insights regarding sweet cherry antioxidant properties which may be useful for the future development of new therapeutic strategies for preventing or attenuating oxidative-related disorders.

Keywords: antioxidant capacity, health benefits, phenolic compounds, saco

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

Procedia PDF Downloads 179

Authors: Bantie Getnet Yirsaw, Muluken Chanie Agimas, Gebrie Getu Alemu, Tigabu Kidie Tesfie, Nebiyu Mekonnen Derseh, Habtamu Wagnew Abuhay, Meron Asmamaw Alemayehu, Getaneh Awoke Yismaw

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Introduction: Hepatitis B virus (HBV) is one of the major public health problems globally and needs an urgent response. It is one of the most responsible causes of mortality among the five hepatitis viruses, and it affects almost every class of individuals. Thus, the main objective of this study was to determine the pooled prevalence and its determinants among pregnant women in East Africa. Methods: We searched studies using PubMed, Scopus, Embase, ScienceDirect, Google Scholar, and grey literature that were published between January 01/2020 to January 30/2024. The studies were assessed using the Newcastle Ottawa Scale (NOS) quality assessment scale. The random-effect (DerSimonian) model was used to determine the pooled prevalence and associated factors of HBV among pregnant women. Heterogeneity was assessed by I² statistic, sub-group analysis, and sensitivity analysis. Publication bias was assessed by the Egger test, and the analysis was done using STATA version 17. Result: A total of 45 studies with 35639 pregnant women were included in this systematic review and meta-analysis. The overall pooled prevalence of HBV among pregnant women in East Africa was 6.0% (95% CI: 6.0%−7.0%, I² = 89.7%). The highest prevalence of 8% ((95% CI: 6%, 10%), I² = 91.08%) was seen in 2021, and the lowest prevalence of 5% ((95% CI: 4%, 6%) I² = 52.52%) was observed in 2022. A pooled meta-analysis showed that history of surgical procedure (OR = 2.14 (95% CI: 1.27, 3.61)), having multiple sexual partners (OR = 3.87 (95% CI: 2.52, 5.95), history of body tattooing (OR = 2.55 (95% CI: 1.62, 4.01)), history of tooth extraction (OR = 2.09 (95% CI: 1.29, 3.39)), abortion history(OR = 2.20(95% CI: 1.38, 3.50)), history of sharing sharp material (OR = 1.88 (95% CI: 1.07, 3.31)), blood transfusion (OR = 2.41 (95% CI: 1.62, 3.57)), family history of HBV (OR = 4.87 (95% CI: 2.95, 8.05)) and history needle injury (OR = 2.62 (95% CI: 1.20, 5.72)) were significant risk factors associated with HBV infection among pregnant women. Conclusions: The pooled prevalence of HBV infection among pregnant women in East Africa was at an intermediate level and different across countries, ranging from 1.5% to 22.2%. The result of this pooled prevalence was an indication of the need for screening, prevention, and control of HBV infection among pregnant women in the region. Therefore, early identification of risk factors, awareness creation of the mode of transmission of HBV, and implementation of preventive measures are essential in reducing the burden of HBV infection among pregnant women.

Keywords: hepatitis B virus, prevalence, determinants, pregnant women, meta-analysis, East Africa

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Authors: Chen Wang, Jared Evans, Yan Asmann

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With the quick evolvement of next-generation sequencing techniques, whole-exome or exome-panel data have become a cost-effective way for detection of small exonic mutations, but there has been a growing desire to accurately detect copy number variations (CNVs) as well. In order to address this research and clinical needs, we developed a sequencing coverage pattern-based method not only for copy number detections, data integrity checks, CNV calling, and visualization reports. The developed methodologies include complete automation to increase usability, genome content-coverage bias correction, CNV segmentation, data quality reports, and publication quality images. Automatic identification and removal of poor quality outlier samples were made automatically. Multiple experimental batches were routinely detected and further reduced for a clean subset of samples before analysis. Algorithm improvements were also made to improve somatic CNV detection as well as germline CNV detection in trio family. Additionally, a set of utilities was included to facilitate users for producing CNV plots in focused genes of interest. We demonstrate the somatic CNV enhancements by accurately detecting CNVs in whole exome-wide data from the cancer genome atlas cancer samples and a lymphoma case study with paired tumor and normal samples. We also showed our efficient reuses of existing exome sequencing data, for improved germline CNV calling in a family of the trio from the phase-III study of 1000 Genome to detect CNVs with various modes of inheritance. The performance of the developed method is evaluated by comparing CNV calling results with results from other orthogonal copy number platforms. Through our case studies, reuses of exome sequencing data for calling CNVs have several noticeable functionalities, including a better quality control for exome sequencing data, improved joint analysis with single nucleotide variant calls, and novel genomic discovery of under-utilized existing whole exome and custom exome panel data.

Keywords: bioinformatics, computational genetics, copy number variations, data reuse, exome sequencing, next generation sequencing

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: Obiajulu Anthony Ugochukwu Nnedum, Bernard Chukwukelue Chine, Jerome Ogochukwu Ezisi

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A notable challenge of organizational citizenship behavior in Nigerian organizations is the prevalence of individualistic work cultures among employees, as this mindset can result in employees being less willing to go beyond their formal job requirements to contribute to the organization overall success. However, the dearth and scarce research on the antecedents of organizational citizenship behavior, such as paternalistic leadership and employee loyalty to supervisors in sub-Saharan African cultures such as Nigeria, motivated the current study to take a deep investigation into the moderating role of employee loyalty to supervisor on the relationship between paternalistic leadership and organizational citizenship behavior. The relevance of the current study ensures that when employees are loyal to their paternalistic leaders who show care and support, they are more likely to exhibit organizational citizenship behavior. The current study employed a sample size of four hundred and twenty participants (one hundred and five managers and three hundred and five subordinates) from eleven large organizations randomly selected through lucky dip from twenty-two large organizations from the directory of the Chamber of Commerce and Industry in Anambra state, south-eastern Nigeria. Also, a twelve-item organizational citizenship behavior scale, a thirty-nine-item paternalistic leadership scale, and a six-item loyalty to supervisor scale were employed for the collection of data for the current study. Adopting a one manager/Leader by triad subordinates cross-sectional survey design, Hayes process micro model and statistical package for social sciences (SPSS) version twenty-five, the findings from the result of the analysis of the hypotheses demonstrated that loyalty to supervisor moderated the relationship between paternalistic leadership and organizational citizenship behavior-conscientiousness. Also, the findings from the result revealed that loyalty to the supervisor moderated the relationship between authoritative leadership and organizational citizenship behavior identification. Furthermore, the findings from the result showed that loyalty to the supervisor moderated the relationship between moral leadership and organizational citizenship behavior. Accordingly, the result from the analysis implies that when employees are loyal to their supervisors, they are more likely to exhibit organizational citizenship behavior by going above and beyond their formal job requirements, as this loyalty can be fostered through a paternalistic leadership style that emphasizes a supportive and caring relationship between supervisors and subordinates.

Keywords: authoritative leadership, moral leadership, loyalty to supervisor, organizational citizenship behavior

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Authors: Mazoun Nasser Rashid Al Kharusi, Nada Al Siyabi

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Objectives: The main aim of this study is to Find the rate of susceptibility of ESBL E. coli causing UTI to oral antibiotics. Secondary objectives: Prevalence of ESBL E. coli from community urine samples, identify the best empirical oral antibiotics with the least resistance rate for UTI and identify alternative oral antibiotics for testing and utilization. Methods: This study is a retrospective descriptive study of the last three years in five major hospitals in Oman (Khowla Hospital, AN’Nahdha Hospital, Rustaq Hospital, Nizwa Hospital, and Ibri Hospital) equipped with a microbiologist. Inclusion criteria include all eligible outpatient urine culture isolates, excluding isolates from admitted patients with hospital-acquired urinary tract infections. Data was collected through the MOH database. The MOH hospitals are using different types of testing, automated methods like Vitek2 and manual methods. Vitek2 machine uses the principle of the fluorogenic method for organism identification and a turbidimetric method for susceptibility testing. The manual method is done by double disc diffusion for identifying ESBL and the disc diffusion method is for antibiotic susceptibility. All laboratories follow the clinical laboratory science institute (CLSI) guidelines. Analysis was done by SPSS statistical package. Results: Total urine cultures were (23048). E. coli grew in (11637) 49.6% of the urine, whereas (2199) 18.8% of those were confirmed as ESBL. As expected, the resistance rate to amoxicillin and cefuroxime is 100%. Moreover, the susceptibility of those ESBL-producing E. coli to nitrofurantoin, trimethoprim+sulfamethoxazole, ciprofloxacin and amoxicillin-clavulanate is progressing over the years; however, still low. ESBL E. coli was predominating in the female gender and those aged 66-74 years old throughout all the years. Other oral antibiotic options need to be explored and tested so that we add to the pool of oral antibiotics for ESBL E. coli causing UTI in the community. Conclusion: High rate of ESBL E. coli in urine from the community. The high resistance rates to oral antibiotics highlight the need for alternative treatment options for UTIs caused by these bacteria. Further research is needed to identify new and effective treatments for UTIs caused by ESBL-E. Coli.

Keywords: UTI, ESBL, oral antibiotics, E. coli, susceptibility

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Authors: Yao Cheng, Weihua Zhang

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Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

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Authors: Awadh O. Al-Anazi

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As part of the organizational needs toward successful maintaining activities, a proper management system need to be put in place, ensuring the effectiveness of maintenance activities. The management system shall clearly describes the process of identifying, prioritizing, planning, scheduling, execution, and providing valuable feedback for all maintenance activities. Completion and accuracy of the system with proper implementation shall provide the organization with a strong platform for effective maintenance activities that are resulted in efficient outcomes toward business success. The purpose of this research was to introduce a practical tool for measuring the maintenance efficiency level within Saudi organizations. A comprehensive study was launched across many maintenance professionals throughout Saudi leading organizations. The study covered five main categories: work process, identification, planning and scheduling, execution, and performance monitoring. Each category was evaluated across many dimensions to determine its current effectiveness through a five-level scale from 'process is not there' to 'mature implementation'. Wide participation was received, responses were analyzed, and the study was concluded by highlighting major gaps and improvement opportunities within Saudi organizations. One effective implementation of the efficiency enhancement efforts was deployed in Saudi Kayan (one of Sabic affiliates). Below details describes the project outcomes: SK overall maintenance wrench time was measured at 20% (on average) from the total daily working time. The assessment indicates the appearance of several organizational gaps, such as a high amount of reactive work, poor coordination and teamwork, Unclear roles and responsibilities, as well as underutilization of resources. Multidiscipline team was assigned to design and implement an appropriate work process that is capable to govern the execution process, improve the maintenance workforce efficiency, and maximize wrench time (targeting > 50%). The enhanced work process was introduced through brainstorming and wide benchmarking, incorporated with a proper change management plan and leadership sponsorship. The project was completed in 2018. Achieved Results: SK WT was improved to 50%, which resulted in 1) reducing the Average Notification completion time. 2) reducing maintenance expenses on OT and manpower support (3.6 MSAR Actual Saving from Budget within 6 months).

Keywords: efficiency, enhancement, maintenance, work force, wrench time

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Authors: Marizia Roberta Rasoanandrasana, Hery Lisy Tiana. Ranarijaona, Herintsitohaina Razakamanarivo, Eric Delaitre, Nandrianina Ramifehiarivo

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Madagascar is one of the producer’s countries of world's fine cocoa. Cocoa-based agroforestry systems (CBAS) plays a very important economic role for over 75% of the population in the north of Madagascar, the island's main cocoa-producing area. It is also viewed as a key factor in the deforestation of local protected areas. It is therefore urgent to establish a compromise between cocoa production and forest conservation in this region which is difficult due to a lack of accurate cocoa agro-systems data. In order to fill these gaps and to response to these socio-economic and environmental concerns, this study aims to describe CBAS by providing precise data on their characteristics and to establish a typology. To achieve this, 150 farms were surveyed and observed to characterize CBAS based on 11 agronomic and 6 socio-economic data. Also, 30 representative plots of CBAS among the 150 farms were inventoried for providing accurate ecological data (6 variables) as an additional data for the typology determination. The results showed that Madagascar’s CBAS systems are generally extensive and practiced by smallholders. Four types of cocoa-based agroforestry system were identified, with significant differences between the following variables: yield, planting age, cocoa density, density of associated trees, preceding crop, associated crops, Shannon-Wiener indices and species richness in the upper stratum. Type 1 is characterized by old systems (>45 years) with low crop density (425 cocoa trees/ha), installed after conversion of crops other than coffee (> 50%) and giving low yields (427 kg/ha/year). Type 2 consists of simple agroforestry systems (no associated crop 0%), fairly young (20 years) with low density of associated trees (77 trees/ha) and low species diversity (H'=1.17). Type 3 is characterized by high crop density (778 trees/ha and 175 trees/ha for cocoa and associated trees respectively) and a medium level of species diversity (H'=1.74, 8 species). Type 4 is particularly characterized by orchard regeneration method involving replanting and tree lopping (100%). Analysis of the potential of these four types has identified Type 4 as a promising practice for sustainable agriculture.

Keywords: conservation, practices, productivity, protect areas, smallholder, trade-off, typology

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Authors: Amr Saeb, Khalid Al-Rubeaan, Mohamed Abouelhoda, Manojkumar Selvaraju, Hamsa Tayeb

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Background: P. mirabilis is a common uropathogenic bacterium that can cause major complications in patients with long-standing indwelling catheters or patients with urinary tract anomalies. In addition, P. mirabilis is a common cause of chronic osteomyelitis in diabetic foot ulcer (DFU) patients. Methodology: P. mirabilis SCDR1 was isolated from a diabetic ulcer patient. We examined P. mirabilis SCDR1 levels of resistance against nano-silver colloids, the commercial nano-silver and silver containing bandages and commonly used antibiotics. We utilized next generation sequencing techniques (NGS), bioinformatics, phylogenetic analysis and pathogenomics in the identification and characterization of the infectious pathogen. Results: P. mirabilis SCDR1 is a multi-drug resistant isolate that also showed high levels of resistance against nano-silver colloids, nano-silver chitosan composite and the commercially available nano-silver and silver bandages. The P. mirabilis-SCDR1 genome size is 3,815,621 bp with G+C content of 38.44%. P. mirabilis-SCDR1 genome contains a total of 3,533 genes, 3,414 coding DNA sequence genes, 11, 10, 18 rRNAs (5S, 16S, and 23S), and 76 tRNAs. Our isolate contains all the required pathogenicity and virulence factors to establish a successful infection. P. mirabilis SCDR1 isolate is a potential virulent pathogen that despite its original isolation site, wound, it can establish kidney infection and its associated complications. P. mirabilis SCDR1 contains several mechanisms for antibiotics and metals resistance including, biofilm formation, swarming mobility, efflux systems, and enzymatic detoxification. Conclusion: P. mirabilis SCDR1 is the spontaneous nano-silver resistant bacterial strain. P. mirabilis SCDR1 strain contains all reported pathogenic and virulence factors characteristic for the species. In addition, it possesses several mechanisms that may lead to the observed nano-silver resistance.

Keywords: Proteus mirabilis, multi-drug resistance, silver nanoparticles, resistance, next generation sequencing techniques, genome analysis, bioinformatics, phylogeny, pathogenomics, diabetic foot ulcer, xenobiotics, multidrug resistance efflux, biofilm formation, swarming mobility, resistome, glutathione S-transferase, copper/silver efflux system, altruism

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Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: fault detection, ground robot, inverse simulation, rover

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Magdalena Smoktunowicz, Renata Wawrzyniak, Malgorzata Waleron, Krzysztof Waleron

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Pectobacterium spp. were previously classified into the Erwinia genus founded in 1917 to unite at that time all Gram-negative, fermentative, nonsporulating and peritrichous flagellated plant pathogenic bacteria. After work of Waldee (1945), on Approved Lists of Bacterial Names and bacteriology manuals in 1980, they were described either under the species named Erwinia or Pectobacterium. The Pectobacterium genus was formally described in 1998 of 265 Pectobacterium strains. Currently, there are 21 species of Pectobacterium bacteria, including Pectobacterium betavasculorum since 2003, which caused soft rot on sugar beet tubers. Based on the biochemical experiments carried out for this, it is known that these bacteria are gram-negative, catalase-positive, oxidase-negative, facultatively anaerobic, using gelatin and causing symptoms of soft rot on potato and sugar beet tubers. The mere fact of growing on sugar beet may indicate a metabolism characteristic only for this species. Metabolomics, broadly defined as the biology of the metabolic systems, which allows to make comprehensive measurements of metabolites. Metabolomics, in combination with genomics, are complementary tools for the identification of metabolites and their reactions, and thus for the reconstruction of metabolic networks. The aim of this study was to apply the GC-MS-based untargeted metabolomics to study the metabolism of P. betavasculorum in different growing conditions. The metabolomic profiles of biomass and biomass media were determined. For sample preparation the following protocol was used: extraction with 900 µl of methanol: chloroform: water mixture (10: 3: 1, v: v) were added to 900 µl of biomass from the bottom of the tube and up to 900 µl of nutrient medium from the bacterial biomass. After centrifugation (13,000 x g, 15 min, 4oC), 300µL of the obtained supernatants were concentrated by rotary vacuum and evaporated to dryness. Afterwards, two-step derivatization procedure was performed before GC-MS analyses. The obtained results were subjected to statistical calculations with the use of both uni- and multivariate tests. The obtained results were evaluated using KEGG database, to asses which metabolic pathways are activated and which genes are responsible for it, during the metabolism of given substrates contained in the growing environment. The observed metabolic changes, combined with biochemical and physiological tests, may enable pathway discovery, regulatory inference and understanding of the homeostatic abilities of P. betavasculorum.

Keywords: GC-MS chromatograpfy, metabolomics, metabolism, pectobacterium strains, pectobacterium betavasculorum

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Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

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Authors: Varsha Salian, Shama Rao, N. Narendra, B. Mohana Kumar

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Evolving evidence proposes the existence of a highly tumorigenic subpopulation of undifferentiated, self-renewing cancer stem cells, responsible for exhibiting resistance to conventional anti-cancer therapy, recurrence, metastasis and heterogeneous tumor formation. Importantly, the mechanisms exploited by cancer stem cells to resist chemotherapy are very less understood. Oral squamous cell carcinoma (OSCC) is one of the most regularly diagnosed cancer types in India and is associated commonly with alcohol and tobacco use. Therefore, the isolation and in vitro characterization of cancer stem-like cells from patients with OSCC is a critical step to advance the understanding of the chemoresistance processes and for designing therapeutic strategies. With this, the present study aimed to establish and characterize cancer stem-like cells in vitro from OSCC. The primary cultures of cancer stem-like cell lines were established from the tissue biopsies of patients with clinical evidence of an ulceroproliferative lesion and histopathological confirmation of OSCC. The viability of cells assessed by trypan blue exclusion assay showed more than 95% at passage 1 (P1), P2 and P3. Replication rate was performed by plating cells in 12-well plate and counting them at various time points of culture. Cells had a more marked proliferative activity and the average doubling time was less than 20 hrs. After being cultured for 10 to 14 days, cancer stem-like cells gradually aggregated and formed sphere-like bodies. More spheroid bodies were observed when cultured in DMEM/F-12 under low serum conditions. Interestingly, cells with higher proliferative activity had a tendency to form more sphere-like bodies. Expression of specific markers, including membrane proteins or cell enzymes, such as CD24, CD29, CD44, CD133, and aldehyde dehydrogenase 1 (ALDH1) is being explored for further characterization of cancer stem-like cells. To summarize the findings, the establishment of OSCC derived cancer stem-like cells may provide scope for better understanding the cause for recurrence and metastasis in oral epithelial malignancies. Particularly, identification and characterization studies on cancer stem-like cells in Indian population seem to be lacking thus provoking the need for such studies in a population where alcohol consumption and tobacco chewing are major risk habits.

Keywords: cancer stem-like cells, characterization, in vitro, oral squamous cell carcinoma

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Authors: D. Hammad, D. P. Tonge

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Rheumatoid arthritis (RA) is a disabling and common autoimmune disease during which the body's immune system attacks healthy tissues. This results in complicated and long-lasting actions being carried out by the immune system, which typically only occurs when the immune system encounters a foreign object. In the case of RA, the disease affects millions of people and causes joint inflammation, ultimately leading to the destruction of cartilage and bone. Interestingly, the disease mechanism still remains unclear. It is likely that RA occurs as a result of a complex interplay of genetic and environmental factors including an imbalance in the microorganism population inside our body. The human microbiome or microbiota is an extensive community of microorganisms in and on the bodies of animals, which comprises bacteria, fungi, viruses, and protozoa. Recently, the development of molecular techniques to characterize entire bacterial communities has renewed interest in the involvement of the microbiome in the development and progression of RA. We believe that an imbalance in some of the specific bacterial species in the gut, mouth and other sites may lead to atopobiosis; the translocation of these organisms into the blood, and that this may lead to changes in immune system status. The aim of this study was, therefore, to characterize the microbiome of RA serum samples in comparison to healthy control subjects using 16S rRNA gene amplification and sequencing. Serum samples were obtained from healthy control volunteers and from patients with RA both prior to, and following treatment. The bacterial community present in each sample was identified utilizing V4 region 16S rRNA amplification and sequencing. Bacterial identification, to the lowest taxonomic rank, was performed using a range of bioinformatics tools. Significantly, the proportions of the Lachnospiraceae, Ruminococcaceae, and Halmonadaceae families were significantly increased in the serum of RA patients compared with healthy control serum. Furthermore, the abundance of Bacteroides and Lachnospiraceae nk4a136_group, Lachnospiraceae_UGC-001, RuminococcaceaeUCG-014, Rumnococcus-1, and Shewanella was also raised in the serum of RA patients relative to healthy control serum. These data support the notion of a blood microbiome and reveal RA-associated changes that may have significant implications for biomarker development and may present much-needed opportunities for novel therapeutic development.

Keywords: blood microbiome, gut and oral bacteria, Rheumatoid arthritis, 16S rRNA gene sequencing

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Authors: Gozde Inal Kiziltepe, Ozgun Uyanik

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There is growing evidence that socioeconomic (SES)-related differences in mathematical knowledge primarily start in early childhood period. Preschoolers from low-income families are likely to perform substantially worse in mathematical knowledge than their counterparts from middle and higher income families. The differences are seen on a wide range of recognizing written numerals, counting, adding and subtracting, and comparing numerical magnitudes. Early differences in numerical knowledge have a permanent effect childrens’ mathematical knowledge in other grades. In this respect, analyzing the effect of number board game on the number knowledge of 48-60 month-old children from disadvantaged low-income families constitutes the main objective of the study. Participants were the 71 preschoolers from a childcare center which served low-income urban families. Children were randomly assigned to the number board condition or to the color board condition. The number board condition included 35 children and the color board game condition included 36 children. Both board games were 50 cm long and 30 cm high; had ‘The Great Race’ written across the top; and included 11 horizontally arranged, different colored squares of equal sizes with the leftmost square labeled ‘Start’. The numerical board had the numbers 1–10 in the rightmost 10 squares; the color board had different colors in those squares. A rabbit or a bear token were presented to children for selecting, and on each trial spun a spinner to determine whether the token would move one or two spaces. The number condition spinner had a ‘1’ half and a ‘2’ half; the color condition spinner had colors that matched the colors of the squares on the board. Children met one-on-one with an experimenter for four 15- to 20-min sessions within a 2-week period. In the first and fourth sessions, children were administered identical pretest and posttest measures of numerical knowledge. All children were presented three numerical tasks and one subtest presented in the following order: counting, numerical magnitude comparison, numerical identification and Count Objects – Circle Number Probe subtest of Early Numeracy Assessment. In addition, same numerical tasks and subtest were given as a follow-up test four weeks after the post-test administration. Findings obtained from the study; showed that there was a meaningful difference between scores of children who played a color board game in favor of children who played number board game.

Keywords: low income, numerical board game, numerical knowledge, preschool education

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Authors: May Fadheel Estephan, Richard Perks

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Context: Cancer is a serious health concern that affects millions of people worldwide. Early detection and treatment are essential for improving patient outcomes. However, current methods for cancer detection have limitations, such as low sensitivity and specificity. Research Aim: The aim of this study was to develop an optical sensor for cancer detection using elastic light scattering spectroscopy (ELSS). ELSS is a noninvasive optical technique that can be used to characterize the size and concentration of particles in a solution. Methodology: An optical probe was fabricated with a 100-μm-diameter core and a 132-μm centre-to-centre separation. The probe was used to measure the ELSS spectra of polystyrene spheres with diameters of 2, 0.8, and 0.413 μm. The spectra were then analysed to determine the size and concentration of the spheres. Findings: The results showed that the optical probe was able to differentiate between the three different sizes of polystyrene spheres. The probe was also able to detect the presence of polystyrene spheres in suspension concentrations as low as 0.01%. Theoretical Importance: The results of this study demonstrate the potential of ELSS for cancer detection. ELSS is a noninvasive technique that can be used to characterize the size and concentration of cells in a tissue sample. This information can be used to identify cancer cells and assess the stage of the disease. Data Collection: The data for this study were collected by measuring the ELSS spectra of polystyrene spheres with different diameters. The spectra were collected using a spectrometer and a computer. Analysis Procedures: The ELSS spectra were analysed using a software program to determine the size and concentration of the spheres. The software program used a mathematical algorithm to fit the spectra to a theoretical model. Question Addressed: The question addressed by this study was whether ELSS could be used to detect cancer cells. The results of the study showed that ELSS could be used to differentiate between different sizes of cells, suggesting that it could be used to detect cancer cells. Conclusion: The findings of this research show the utility of ELSS in the early identification of cancer. ELSS is a noninvasive method for characterizing the number and size of cells in a tissue sample. To determine cancer cells and determine the disease's stage, this information can be employed. Further research is needed to evaluate the clinical performance of ELSS for cancer detection.

Keywords: elastic light scattering spectroscopy, polystyrene spheres in suspension, optical probe, fibre optics

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Authors: Huiling Feng, Jihong Liang, Xiaodong Gong, Yongjun Xu

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Recording history is a tradition in ancient China. A record of a dynasty makes a dynastic history; a record of a locality makes a chorography, and a record of a clan makes a genealogy – the three combined together depicts a complete national history of China both macroscopically and microscopically, with genealogy serving as the foundation. Genealogy in ancient China traces back to a family tree or pedigrees in the early and medieval historical times. After Song Dynasty, the civilian society gradually emerged, and the Emperor had to allow people from the same clan to live together and hold the ancestor worship activities, thence compilation of genealogy became popular in the society. Since then, genealogies, regarded as important as ancestor and religious temples in a traditional villages even today, have played a primary role in identification of a clan and maintain local social order. Chinese genealogies are rich in their documentary materials. Take the Genealogy of Wu Clan in Gaoqian as an example. Gaoqian is a small village in Xianju County of Zhejiang Province. The Genealogy of Wu Clan in Gaoqian is composed of a whole set of materials from Foreword to Family Trees, Family Rules, Family Rituals, Family Graces and Glories, Ode to An ancestor’s Portrait, Manual for the Ancestor Temple, documents for great men in the clan, works written by learned men in the clan, the contracts concerning landed property, even notes on tombs and so on. Literally speaking, the genealogy, with detailed information from every aspect recorded in stylistic rules, is indeed the carrier of the entire culture of a clan. However, due to their scarcity in number and difficulties in reading, genealogies seldom fall into the horizons of common people. This paper, focusing on the case of the Genealogy of Wu Clan in the Village of Gaoqian, intends to reproduce a digital Genealogy by use of ICTs, through an in-depth interpretation of the literature and field investigation in Gaoqian Village. Based on this, the paper goes further to explore the general methods in transferring physical genealogies to digital ones and ways in visualizing the clanism culture embedded in the genealogies with a combination of digital technologies such as software in family trees, multimedia narratives, animation design, GIS application and e-book creators.

Keywords: clanism culture, multimedia narratives, genealogy of Wu Clan, GIS

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

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Authors: Ahmeda Ali, Mary Codd, Susan Brundage

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Importance: This research focuses on devising and improving Health Service Executive (HSE) policy and legislation and therefore improving patient trauma care and outcomes in Ireland. Objectives: The study measures components of the Trauma System in the district hospital setting of the Cavan/Monaghan Hospital Group (CMHG), HSE, Ireland, and uses the collected data to identify the strengths and weaknesses of the CMHG Trauma System organisation, to include governance, injury data, prevention and quality improvement, scene care and facility-based care, and rehabilitation. The information will be made available to local policy makers to provide objective situational analysis to assist in future trauma service planning and service provision. Design, setting and participants: From 28 April to May 28, 2016 a cross-sectional survey using World Health Organisation (WHO) Trauma System Assessment Tool (TSAT) was conducted among healthcare professionals directly involved in the level III trauma system of CMHG. Main outcomes: Identification of the strengths and weaknesses of the Trauma System of CMHG. Results: The participants who reported inadequate funding for pre hospital (62.3%) and facility based trauma care at CMHG (52.5%) were high. Thirty four (55.7%) respondents reported that a national trauma registry (TARN) exists but electronic health records are still not used in trauma care. Twenty one respondents (34.4%) reported that there are system wide protocols for determining patient destination and adequate, comprehensive legislation governing the use of ambulances was enforced, however, there is a lack of a reliable advisory service. Over 40% of the respondents reported uncertainty of the injury prevention programmes available in Ireland; as well as the allocated government funding for injury and violence prevention. Conclusions: The results of this study contributed to a comprehensive assessment of the trauma system organisation. The major findings of the study identified three fundamental areas: the inadequate funding at CMHG, the QI techniques and corrective strategies used, and the unfamiliarity of existing prevention strategies. The findings direct the need for further research to guide future development of the trauma system at CMHG (and in Ireland as a whole) in order to maximise best practice and to improve functional and life outcomes.

Keywords: trauma, education, management, system

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Natalia Kalinowska

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The adoption of the General Data Protection Regulation, (GDPR) finished the four-year work of the European Commission in this area in the European Union. Considering far-reaching changes, which will be applied by GDPR, the European legislator envisaged two-year transitional period. Member states and companies have to prepare for a new regulation until 25 of May 2018. The idea, which becomes a new look at an attitude to data protection in the European Union is risk-based approach. So far, as a result of implementation of Directive 95/46/WE, in many European countries (including Poland) there have been adopted very particular regulations, specifying technical and organisational security measures e.g. Polish implementing rules indicate even how long password should be. According to the new approach from May 2018, controllers and processors will be obliged to apply security measures adequate to level of risk associated with specific data processing. The risk in GDPR should be interpreted as the likelihood of a breach of the rights and freedoms of the data subject. According to Recital 76, the likelihood and severity of the risk to the rights and freedoms of the data subject should be determined by reference to the nature, scope, context and purposes of the processing. GDPR does not indicate security measures which should be applied – in recitals there are only examples such as anonymization or encryption. It depends on a controller’s decision what type of security measures controller considered as sufficient and he will be responsible if these measures are not sufficient or if his identification of risk level is incorrect. Data protection regulation indicates few levels of risk. Recital 76 indicates risk and high risk, but some lawyers think, that there is one more category – low risk/now risk. Low risk/now risk data processing is a situation when it is unlikely to result in a risk to the rights and freedoms of natural persons. GDPR mentions types of data processing when a controller does not have to evaluate level of risk because it has been classified as „high risk” processing e.g. processing on a large scale of special categories of data, processing with using new technologies. The methodology will include analysis of legal regulations e.g. GDPR, the Polish Act on the Protection of personal data. Moreover: ICO Guidelines and articles concerning risk based approach in GDPR. The main conclusion is that an appropriate risk assessment is a key to keeping data safe and avoiding financial penalties. On the one hand, this approach seems to be more equitable, not only for controllers or processors but also for data subjects, but on the other hand, it increases controllers’ uncertainties in the assessment which could have a direct impact on incorrect data protection and potential responsibility for infringement of regulation.

Keywords: general data protection regulation, personal data protection, privacy protection, risk based approach

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Authors: Luís R. Silva, Fábio Jesus, Catarina Bento, Ana C. Gonçalves

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Over the last few years, the traditional medicine has gained ground at nutritional and pharmacological level. The natural products and their derivatives have great importance in several drugs used in modern therapeutics. Plant-based systems continue to play an essential role in primary healthcare. Additionally, the utilization of their plant parts, such as leaves, stems and flowers as nutraceutical and pharmaceutical products, can add a high value in the natural products market, not just by the nutritional value due to the significant levels of phytochemicals, but also by to the high benefit for the producers and manufacturers business. Stems of Prunus avium L. are a byproduct resulting from the processing of cherry, and have been consumed over the years as infusions and decoctions due to its bioactive properties, being used as sedative, diuretic and draining, to relief of renal stones, edema and hypertension. In this work, we prepared a hydroethanolic and infusion extracts from stems of P. avium collected in Fundão Region (Portugal), and evaluate the phenolic profile by LC/DAD, antioxidant capacity, α-glucosidase inhibitory activity and protection of human erythrocytes against oxidative damage. The LC-DAD analysis allowed to the identification of 19 phenolic compounds, catechin and 3-O-caffolquinic acid were the main ones. In a general way, hydroethanolic extract proved to be more active than infusion. This extract had the best antioxidant activity against DPPH• (IC50=22.37 ± 0.28 µg/mL) and superoxide radical (IC50=13.93 ± 0.30 µg/mL). Furthermore, it was the most active concerning inhibition of hemoglobin oxidation (IC50=13.73 ± 0.67 µg/mL), hemolysis (IC50=1.49 ± 0.18 µg/mL) and lipid peroxidation (IC50=26.20 ± 0.38 µg/mL) on human erythrocytes. On the other hand, infusion revealed to be more efficient towards α-glucosidase inhibitory activity (IC50=3.18 ± 0.23 µg/mL) and against nitric oxide radical (IC50=99.99 ± 1.89 µg/mL). The Sweet cherry sector is very important in Fundão Region (Portugal), and taking profit from the great wastes produced during processing of the cherry to produce added-value products, such as food supplements cannot be ignored. Our results demonstrate that P. avium stems possesses remarkable antioxidant and free radical scavenging properties. It is therefore, suggest, that P. avium stems can be used as a natural antioxidant with high potential to prevent or slow the progress of human diseases mediated by oxidative stress.

Keywords: stems, Prunus avium, phenolic compounds, biological potential

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