Search results for: stochastic subspace identification

Authors: M. A. Meslem

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For precise geoid determination, we use a reference field to subtract long and medium wavelength of the gravity field from observations data when we use the remove-compute-restore technique. Therefore, a comparison study between considered models should be made in order to select the optimal reference gravity field to be used. In this context, two recent global geopotential models have been selected to perform this comparison study over Northern Algeria. The Earth Gravitational Model (EGM2008) and the Global Gravity Model (GECO) conceived with a combination of the first model with anomalous potential derived from a GOCE satellite-only global model. Free air gravity anomalies in the area under study have been used to compute residual data using both gravity field models and a Digital Terrain Model (DTM) to subtract the residual terrain effect from the gravity observations. Residual data were used to generate local empirical covariance functions and their fitting to the closed form in order to compare their statistical behaviors according to both cases. Finally, height anomalies were computed from both geopotential models and compared to a set of GPS levelled points on benchmarks using least squares adjustment. The result described in details in this paper regarding these two models has pointed out a slight advantage of GECO global model globally through error degree variances comparison and ground-truth evaluation.

Keywords: quasigeoid, gravity aomalies, covariance, GGM

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Authors: Aurora Gitto, Philipp Proksch

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The presence of various microorganisms (bacteria, fungi) in surface water and groundwater represents an important issue for human health worldwide. The matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS) has emerged as a promising and reliable tool for bacteria identification in clinical diagnostic microbiology and environmental strains thanks to an ionization technique that uses a laser energy absorbing matrix to create ions from large molecules with minimal fragmentation. The study aims first to conceptualise and set up library information and create a comprehensive database of MALDI-TOF-MS spectra from environmental water samples. The samples were analysed over a year (2021-2022) using membrane filtration methodology (0.45 μm and 0.22 μm) and then isolated on R2A agar for a period of 5 days and Yeast extract agar growing at 22 °C up to 4 days and 37 °C for 48 hours. The undetected organisms by MALDI-TOF-MS were analysed by PCR and then sequenced. The information obtained by the sequencing was further implemented in the MALDI-TOF-MS library. Among the culturable bacteria, the results show how the incubator temperature affects the growth of some genera instead of others, as demonstrated by Pseudomonas sp., which grows at 22 °C, compared to Bacillus sp., which is abundant at 37 °C. The bacteria community shows a variation in composition also between the media used, as demonstrated with R2A agar which has been defined by a higher presence of organisms not detected compared to YEA. Interesting is the variability of the Genus over one year of sampling and how the seasonality impacts the bacteria community; in fact, in some sampling locations, we observed how the composition changed, moving from winter to spring and summer. In conclusion, the bacteria community in groundwater and river bank filtration represents important information that needs to be added to the library to simplify future water quality analysis but mainly to prevent potential risks to human health.

Keywords: water quality, MALDI-TOF-MS, sequencing, library

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Authors: Peter David Reiss

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The concept of the psychosis prodrome has allowed for the identification of adolescent and young adult patients who have a significantly elevated risk of developing schizophrenia spectrum disorders. A number of different interventions have been tested in order to prevent or delay progression of symptoms. To date, there has been no consistent meta-analytical evidence to support efficacy of antipsychotic treatment for patients in the prodromal state, and their use remains therefore inconclusive. Although antipsychotics may manage symptoms transiently, they have not been found to prevent or delay onset of psychotic disorders. Furthermore, pharmacological intervention in high-risk individuals remains controversial, because of the antipsychotic side effect profile in a population in which only about 20 to 35 percent will eventually convert to psychosis over a two-year period, with even after two years conversion rates not exceeding 30 to 40 percent. This general estimate is additionally problematic, in that it ignores the fact that there is significant variation in individual risk among clinical high-risk cases. The current lack of reliable tests for at-risk patients makes it difficult to justify individual treatment decisions. Preventive treatment should ideally be dictated by an individual’s risk while minimizing potentially harmful medication exposure. This requires more accurate predictive assessments by using valid and accessible prognostic markers. The following will compare prediction and risk modification potential of behavioral biomarkers such as disturbances of basic sense of self and emotion awareness, neurocognitive biomarkers such as attention, working and declarative memory, and neurophysiological biomarkers such as glutamatergic abnormalities and NMDA receptor dysfunction. Identification of robust biomarkers could therefore not only provide more reliable means of psychosis prediction, but also help test and develop new clinical interventions targeted at the prodromal state.

Keywords: at-risk mental state, biomarkers, glutamatergic system, NMDA receptor, psychosis prodrome, schizophrenia

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Authors: Charmi Chande, Ravindra Phadke

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Microfluidics devices are fabricated by using multiple fabrication methods. Photolithography is one of the common methods wherein SU8 is widely used for making master which in turn is used for making working chip by the process of soft lithography. The high-aspect ratio features of SU-8 makes it suitable to be used as micro moulds for injection moulding, hot embossing, and moulds to form polydimethylsiloxane (PDMS) structures for bioMEMS (Microelectromechanical systems) applications. But due to high cost, difficulty in procuring and need for clean room, restricts the use of this polymer especially in developing countries and small research labs. ‘Bisphenol –A’ based polymers in mixture with curing agent are used in various industries like Paints and coatings, Adhesives, Electrical systems and electronics, Industrial tooling and composites. We present the novel use of ‘Bisphenol – A’ based polymer in fabricating micro channels for Lab On Chip(LOC) devices. The present paper describes the prototype for production of microfluidics chips using range of ‘Bisphenol-A’ based polymers viz. GY 250, ATUL B11, DER 331, DER 330 in mixture with cationic photo initiators. All the steps of chip production were carried out using an inexpensive approach that uses low cost chemicals and equipment. This even excludes the need of clean room. The produced chips using all above mentioned polymers were validated with respect to height and the chip giving least height was selected for further experimentation. The lowest height achieved was 7 micrometers by GY250. The cost of the master fabricated was $ 0.20 and working chip was $. 0.22. The best working chip was used for morphological identification and profiling of microorganisms from environmental samples like soil, marine water and salt water pan sites. The current chip can be adapted for various microbiological screening experiments like biochemical based microbial identification, studying uncultivable microorganisms at single cell/community level.

Keywords: bisphenol–A based epoxy, cationic photoinitiators, microfabrication, photolithography

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Authors: Michaela Storen, Michelle Harvey, Xavier Conlan

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Gun violence internationally is increasing at an unprecedented level, becoming a favoured means for executing violence against another individual. Not only is this putting a strain on forensic scientists who attempt to determine the cause of death in circumstances where firearms have been involved in the death of an individual, but it also highlights the need for an alternative technique of identification of a gunshot wound when other established techniques have been exhausted. A corpse may be colonized by necrophagous insects following death, and this close association between the time of death and insect colonization makes entomological samples valuable evidence when remains become decomposed beyond toxicological utility. Entomotoxicology provides the potential for the identification of toxins in a decomposing corpse, with recent research uncovering the capabilities of entomotoxicology to detect gunshot residue (GSR) in a corpse. However, shortcomings of the limited literature available on this topic have not been addressed, with the bioaccumulation, detection limits, and sensitivity to gunshots not considered thus far, leaving questions as to the applicability of this new technique in the forensic context. Larvae were placed on meat contaminated with GSR at different concentrations and compared to a control meat sample to establish the uptake of GSR by the larvae, with bioaccumulation established by placing the larvae on fresh, uncontaminated meat for a period of time before analysis using ICP-MS. The findings of Pb, Ba, and Sb at each stage of the lifecycle and bioaccumulation in the larvae will be presented. In addition, throughout these previously mentioned experiments, larvae were washed once, twice and three times to evaluate the effectiveness of existing entomological practices in removing external toxins from specimens prior to entomotoxicologyical analysis. Analysis of these larval washes will be presented. By addressing these points, this research extends the utility of entomotoxicology in cause-of-death investigations and provides an additional source of evidence for forensic scientists in the circumstances involving a gunshot wound on a corpse, in addition to advising the effectiveness of current entomology collection protocols.

Keywords: bioaccumulation, chemistry, entomology, gunshot residue, toxicology

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Authors: Muhamad Hafiz Ismail, Ahmad H., Nelfianty M. R.

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The longitudinal study is conducted to identify predictive factors of soccer talent among male players aged 14 to 17 years. Convenience sampling involving elite respondents (n=20) and sub-elite respondents (n=20) male soccer players. Descriptive statistics were reported as frequencies and percentages. The inferential statistical analysis is used to report the status of reliability, independent samples t-test, paired samples t-test, and multiple regression analysis. Generally, there are differences in mean of height, muscular strength, muscular endurance, cardiovascular endurance, task orientation, cognitive anxiety, self-confidence, juggling skills, short pass skills, long pass skills, dribbling skills, and shooting skills for 20 elite players and sub-elite players. Accordingly, there was a significant difference between pre and post-test for thirteen variables of height, weight, fat percentage, muscle strength, muscle endurance, cardiovascular endurance, flexibility, BMI, task orientation, juggling skills, short pass skills, a long pass skills, and dribbling skills. Based on the first predictive factors (physical), second predictive factors (fitness), third predictive factors (psychological), and fourth predictive factors (skills in playing football) pledged to the soccer talent; four multiple regression models were produced. The first predictive factor (physical) contributed 53.5 percent, supported by height and percentage of fat in soccer talents. The second predictive factor (fitness) contributed 63.2 percent and the third predictive factors (psychology) contributed 66.4 percent of soccer talent. The fourth predictive factors (skills) contributed 59.0 percent of soccer talent. The four multiple regression models could be used as a guide for talent scouting for soccer players of the future.

Keywords: soccer talent identification, fitness and physical test, soccer skills test, psychological test

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Authors: Awais Ahmed, Javed Iqbal

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Pakistan has been for many years facing extreme challenges in energy deficit due to the shortage of power generation compared to increasing demand. A part of this energy deficit is also contributed by the power lost in transmission and distribution network. Unfortunately, distribution companies are not equipped with modern technologies and methods to identify and eliminate these losses. According to estimate, total energy lost in early 2000 was between 20 to 26 percent. To address this issue the present research study was designed with the objectives of developing a standalone GIS application for distribution companies having the capability of loss calculation as well as identification of overloaded transformers. For this purpose, Hilal Road feeder in Faisalabad Electric Supply Company (FESCO) was selected as study area. An extensive GPS survey was conducted to identify each consumer, linking it to the secondary pole of the transformer, geo-referencing equipment and documenting conductor sizes. To identify overloaded transformer, accumulative kWH reading of consumer on transformer was compared with threshold kWH. Technical losses of 11kV and 220V lines were calculated using the data from substation and resistance of the network calculated from the geo-database. To automate the process a standalone GIS application was developed using ArcObjects with engineering analysis capabilities. The application uses GIS database developed for 11kV and 220V lines to display and query spatial data and present results in the form of graphs. The result shows that about 14% of the technical loss on both high tension (HT) and low tension (LT) network while about 4 out of 15 general duty transformers were found overloaded. The study shows that GIS can be a very effective tool for distribution companies in management and planning of their distribution network.

Keywords: geographical information system, GIS, power distribution, distribution transformers, technical losses, GPS, SDSS, spatial decision support system

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Authors: J. M. Hernández-Ontiveros, E. E. García-Guerrero, E. Inzunza-González, O. R. López-Bonilla

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This paper presents the implementation of an algorithm that identifies and accounts different fish species: Catfish, Sea bream, Sawfish, Tilapia, and Totoaba. The main contribution of the method is the fusion of the characteristics of invariance to the position, rotation and scale of the Hu moments, with the proper counting of fish. The identification and counting is performed, from an image under different noise conditions. From the experimental results obtained, it is inferred the potentiality of the proposed algorithm to be applied in different scenarios of aquaculture production.

Keywords: counting fish, digital image processing, invariant moments, pattern recognition

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Authors: B. Bakchiche, H. Guenane, M. Bireche, A. Noureddinne, A. Gherib

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The chemical composition of the essential oils obtained by hydrodistillation from Artemisia campestris L (family Asteraceae) collected in Djebel Amour (Sahara Atlas, Algeria). Aerial parts were also evaluated by gas chromatography (GC) and gas chromatography coupled to mass spectrometry (GC-MS). The analyses for leaves and fruits of A. campestris resulted in the identification of thirty-one compounds, representing 91.8 % of the total oil and the yields were 0.33% (v/dry weight). The main components were β-pinene and sabinene (25.6% and 17% respectively) followed by α-pinene (9.9%), limonene (6.6 %) and p-cymene (4.1%).

Keywords: essential oil, GC-MS, Artemesia campestris, Algeria

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Authors: Tong Ming Liu

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Human mesenchymal stem cells (MSCs) represent the most used stem cells for clinical application, which have been used in over 1000 clinical trials to treat over 30 diseases due to multilineage differentiation potential, secretome and immunosuppression. Gene therapies of MSCs hold great promise in the treatment of many diseases due to enhanced MSC-based clinical outcomes. To identify genes for gene therapy of MSCs, by comparing gene expression profile before and after MSC differentiation following by functional screening, we have identified ZNF145 that regulated MSC differentiation. Forced expression of ZNF145 resulted in enhanced in vitro chondrogenesis of MSCs as an upstream factor of SOX9 and improved osteochondral repair upon implant into osteochondral defects in rodents. By comparing gene expression profile during differentiation of iPSCs toward MSCs, we also identified gene HOX regulating MSC stemness, which was much downregulated in late-passaged MSCs. Knockdown of this gene greatly compromised MSC stemness including abolished proliferation, decreased CFU-F, promoted senescence and reduced expression of cell surface antigens linked to the MSC phenotype. In addition, multi-linage differentiation was also greatly impaired. Notably, HOX overexpression resulted in improved multi-lineage differentiation. In the mechanism, HOX expression significantly deceased in late passage of MSCs compared with early passage of MSCs, correlating with MSC important genes. ChIP-seq data shown that HOX binds to genes related to MSC self-renewal and differentiation. Most importantly, most HOX binding sites are lost in late passage of MSCs. HOX exerts its effects by directing binding Twist1, one important gene of MSCs. The identification of the genes regulating MSC differentiation and stemness will provide and promising strategies for gene therapy of MSCs in regenerative medicine.

Keywords: mesenchymal stem cell, novel transcription factor, stemness, gene therapy, cartilage repair, signaling pathway

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Authors: Meenu Joshi, Natalie Naidoo, Farzeen Kader

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Identification of body fluids is an essential step in forensic investigation to aid in crime reconstruction. Tissue-specific differentially methylated regions (tDMRs) of the human genome can be targeted to be used as biomarkers to differentiate between body fluids. The present study was undertaken to establish the methylation status of potential tDMRs in blood, semen, saliva, and vaginal fluid by using methylation-specific PCR (MSP) and bisulfite sequencing (BS). The methylation statuses of 3 potential tDMRS in genes ZNF282, PTPRS, and HPCAL1 were analysed in 10 samples of each body fluid. With MSP analysis, the ZNF282, and PTPRS1 tDMR displayed semen-specific hypomethylation while HPCAL1 tDMR showed saliva-specific hypomethylation. With quantitative analysis by BS, the ZNF282 tDMR showed statistically significant difference in overall methylation between semen and all other body fluids as well as at individual CpG sites (p < 0.05). To evaluate the effect of environmental conditions on the stability of methylation profiles of the ZNF282 tDMR, five samples of each body fluid were subjected to five different forensic simulated conditions (dry at room temperature, wet in an exsiccator, outside on the ground, sprayed with alcohol, and sprayed with bleach) for 50 days. Vaginal fluid showed highest DNA recovery under all conditions while semen had least DNA quantity. Under outside on the ground condition, all body fluids except semen showed a decrease in methylation level; however, a significant decrease in methylation level was observed for saliva. A statistical significant difference was observed for saliva and semen (p < 0.05) for outside on the ground condition. No differences in methylation level were observed for the ZNF282 tDMR under all conditions for vaginal fluid samples. Thus, in the present study ZNF282 tDMR has been identified as a novel and stable semen-specific hypomethylation marker.

Keywords: body fluids, bisulphite sequencing, forensics, tDMRs, MSP

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Authors: Naragain Phumchusri, Kittitach Pongpairoj

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Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level.

Keywords: overbooking, car rental industry, revenue management, stochastic model

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Authors: Keunock Lew, Seungryul Ma

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The paper analyzes risk and expected return of lenders who provide mortgage loans to households in the shared mortgage program of Korea. In 2013, the Korean government introduced the mortgage program to help low income householders to convert their renting into purchasing houses. The financial source for the mortgage program is the Urban Housing Fund set up by the Korean government. Through the program, low income households can borrow money from lenders to buy a house at a very low interest rate (e.g. 1 % per year) for a long time. The motivation of adopting this mortgage program by the Korean government is that the cost of renting houses has been rapidly increased especially in large urban areas during the past decade, which became financial difficulties to low income households who do not have their own houses. As the analysis methodology, the paper uses a spread sheet model for projecting cash flows of the mortgage product over the period of loan contract. It also employs Monte Carlo simulation method to analyze the risk and expected yield of the lenders with assumption that the future housing price and market rate of interest follow a stochastic process. The study results will give valuable implications to the Korean government and lenders who want to stabilize the mortgage program and innovate the related loan products.

Keywords: expected return, Monte Carlo simulation, risk, shared mortgage program

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Authors: L. Sun, T. Hargreaves, Z. Ahmad

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Newly-qualified Foundation Year 1 doctors in the United Kingdom are frequently expected to perform practical skills involving the upper limb in clinical practice (for example, venipuncture, cannulation, and blood gas sampling). However, a move towards systems-based undergraduate medical education in the United Kingdom often precludes or limits dedicated time to anatomy teaching with cadavers or prosections, favouring only applied anatomy in the context of pathology. The authors hypothesised that detailed anatomical knowledge may consequently be adversely affected, particularly with respect to long-term retention. A simple picture quiz and accompanying questionnaire testing the identification of 7 upper limb surface landmarks was distributed to a total of 98 final year medical students from two universities - one with a systems-based curriculum, and one with a dedicated longitudinal dissection-based anatomy module in the first year of study. Students with access to dissection and prosection-based anatomy teaching performed more strongly, with a significantly higher rate of correct identification of all but one of the landmarks. Furthermore, it was notable that none of the students who had previously undertaken a systems-based course scored full marks, compared with 20% of those who had participated in the more dedicated anatomy course. This data suggests that a traditional, dissection-based approach to undergraduate anatomy teaching is superior to modern system-based curricula, in terms of aiding long-term retention of anatomical knowledge pertinent to newly-qualified doctors. The authors express concern that this deficit in proficiency could be detrimental to patient care in clinical practice, and propose that, where dissection-led anatomy teaching is not available, further anatomy revision modules are implemented throughout undergraduate education to aid knowledge retention and support clinical excellence.

Keywords: dissection, education, surface anatomy, upper limb

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Authors: Oleg Reva, Ilya Korotetskiy, Marina Lankina, Murat Kulmanov, Aleksandr Ilin

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Molecular docking approaches are widely used for design of new antibiotics and modeling of antibacterial activities of numerous ligands which bind specifically to active centers of indispensable enzymes and/or key signaling proteins of pathogens. Widespread drug resistance among pathogenic microorganisms calls for development of new antibiotics specifically targeting important metabolic and information pathways. A generally recognized problem is that almost all molecular targets have been identified already and it is getting more and more difficult to design innovative antibacterial compounds to combat the drug resistance. A promising way to overcome the drug resistance problem is an induction of reversion of drug resistance by supplementary medicines to improve the efficacy of the conventional antibiotics. In contrast to well established computer-based drug design, modeling of drug resistance reversion still is in its infancy. In this work, we proposed an approach to identification of compensatory genetic variants reducing the fitness cost associated with the acquisition of drug resistance by pathogenic bacteria. The approach was based on an analysis of the population genetic of Mycobacterium tuberculosis and on results of experimental modeling of the drug resistance reversion induced by a new anti-tuberculosis drug FS-1. The latter drug is an iodine-containing nanomolecular complex that passed clinical trials and was admitted as a new medicine against MDR-TB in Kazakhstan. Isolates of M. tuberculosis obtained on different stages of the clinical trials and also from laboratory animals infected with MDR-TB strain were characterized by antibiotic resistance, and their genomes were sequenced by the paired-end Illumina HiSeq 2000 technology. A steady increase in sensitivity to conventional anti-tuberculosis antibiotics in series of isolated treated with FS-1 was registered despite the fact that the canonical drug resistance mutations identified in the genomes of these isolates remained intact. It was hypothesized that the drug resistance phenotype in M. tuberculosis requires an adjustment of activities of many genes to compensate the fitness cost of the drug resistance mutations. FS-1 cased an aggravation of the fitness cost and removal of the drug-resistant variants of M. tuberculosis from the population. This process caused a significant increase in genetic heterogeneity of the Mtb population that was not observed in the positive and negative controls (infected laboratory animals left untreated and treated solely with the antibiotics). A large-scale search for linkage disequilibrium associations between the drug resistance mutations and genetic variants in other genomic loci allowed identification of target proteins, which could be influenced by supplementary drugs to increase the fitness cost of the drug resistance and deprive the drug-resistant bacterial variants of their competitiveness in the population. The approach will be used to improve the efficacy of FS-1 and also for computer-based design of new drugs to combat drug-resistant infections.

Keywords: complete genome sequencing, computational modeling, drug resistance reversion, Mycobacterium tuberculosis

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Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

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Authors: Recep Keşli, Gülşah Aşık, Cengiz Demir, Onur Türkyılmaz

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Objective: Proteus mirabilis (P. mirabilis) is one of Gram-negative pathogens in human and it causes urinary tract and nosocomial infections. P. mirabilis is susceptible to β-lactams, aminoglycosides, fluoroquinolones, and trimethoprim/sulfamethoxazole. It was aimed to investigate the resistance status to antimicrobial agents of Proteus mirabilis strains produced from samples sent to Afyon Kocatepe University, ANS Research and Practice Hospital, Microbiology Laboratory from different clinics and polyclinics during the period of 24 months. Methods: Between October 2013 and September 2015, a total of 30 Proteus were isolated from clinical samples of patients were hospitalized in intensive care units and in various departments of Afyon Kocatepe University, ANS Research and Practice Hospital. Identification of the bacteria was determined by conventional methods and VITEK 2 system (bioMérieux, France) was used additionally. Antibacterial susceptibility tests were performed by Kirby Bauer disc (Oxoid, Hempshire, England) diffusion method following the recommendations of CLSI. Results: Of the total 30 Proteus strains isolated from clinical samples, 19 from urine, 7 from wound, 4 from tracheal aspiration materials were isolated. Antimicrobial resistant for these strains were determined to 24,3% for meropenem, 26.2% for imipenem, 20.2% for amikacin 10.5% for cefepim, 33.3% for ciprofloxacin and levofloxacine, 31.6% for ceftazidime, 20% for ceftriaxone, 15.2% for gentamicin and 26.6% for amoxicillin-clavulanate, 26.2% trimethoprim-sulfamethoxale. Conclusion: In the present study, the highest number of clinical isolates of P. mirabilis were isolated from urine (63,3%), followed by the others (36,6%). The distribution of samples P. mirabilis strains to the clinics were as fallows; 16,8% intensive care unit (ICU), 29,9% polyclinics, 53,3% hospital service units The most effective antibiotic on the total of strains were found to be cefepim, the least effective antibiotics on the total of strains were found to be trimethoprim-sulfamethoxale.

Keywords: proteus mirabilis, antibiotic resistance, intensive care unit, Proteus spp.

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Authors: Hanan Khojah, RuAngelie Edrada-Ebel

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Neurodegenerative disease including Alzheimer’s disease is a major cause of long-term disability. Oxidative stress is frequently implicated as one of the key contributing factors to neurodegenerative diseases. Protection against neuronal damage remains a great challenge for researchers. Ficus carica (commonly known as fig) is a species of great antioxidant nutritional value comprising a protective mechanism against innumerable health disorders related to oxidative stress as well as Alzheimer’s disease. The purpose of this work was to characterize the non-polar active metabolites in Ficus carica endocarp, mesocarp, and exocarp. Crude extracts were prepared using several extraction solvents, which included 1:1 water: ethylacetate, acetone and methanol. The dried extracts were then solvent partitioned between equivalent amounts of water and ethylacetate. Purification and fractionation were accomplished by high-throughput chromatography. The isolated metabolites were tested on their effect on human neuroblastoma cell line by cell viability test and cell cytotoxicity assay with acrolein. Molecular weights of the active metabolites were determined via LC–HRESIMS and GC-EIMS. Metabolomic profiling was performed to identify the active metabolites by using differential expression analysis software (Mzmine) and SIMCA for multivariate analysis. Structural elucidation and identification of the interested active metabolites were studied by 1-D and 2-D NMR. Significant differences in bioactivity against a concentration-dependent assay on acrolein radicals were observed between the three fruit parts. However, metabolites obtained from mesocarp and the endocarp demonstrated bioactivity to scavenge ROS radical. NMR profiling demonstrated that aliphatic compounds such as γ-sitosterol tend to induce neuronal bioactivity and exhibited bioactivity on the cell viability assay. γ-Sitosterol was found in higher concentrations in the mesocarp and was considered as one of the major phytosterol in Ficus carica.

Keywords: alzheimer, Ficus carica, γ-Sitosterol, metabolomics

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Authors: Abrha Ybeyn Gebremedhn, Yitea Seneshaw Getahun, Alebachew Shumye Moges, Fikrey Tesfay

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Rainfed agriculture in Ethiopia has failed to produce enough food, to achieve the increasing demand for food. Pinpointing the appropriate site for rainwater harvesting (RWH) have a substantial contribution to increasing the available water and enhancing agricultural productivity. The current study related to the identification of the potential RWH sites was conducted at the Chacha watershed central highlands of Ethiopia which is endowed with rugged topography. The Geographic Information System with Analytical Hierarchy Process was used to generate the different maps for identifying appropriate sites for RWH. In this study, 11 factors that determine the RWH locations including slope, soil texture, runoff depth, land cover type, annual average rainfall, drainage density, lineament intensity, hydrologic soil group, antecedent moisture content, and distance to the roads were considered. The overall analyzed result shows that 10.50%, 71.10%, 17.90%, and 0.50% of the areas were found under highly, moderately, marginally suitable, and unsuitable areas for RWH, respectively. The RWH site selection was found highly dependent on a slope, soil texture, and runoff depth; moderately dependent on drainage density, annual average rainfall, and land use land cover; but less dependent on the other factors. The highly suitable areas for rainwater harvesting expansion are lands having a flat topography with a soil textural class of high-water holding capacity that can produce high runoff depth. The application of this study could be a baseline for planners and decision-makers and support any strategy adoption for appropriate RWH site selection.

Keywords: runoff depth, antecedent moisture condition, AHP, weighted overlay, water resource

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Kukuri Tavartkiladze, Nana Bolashvili

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The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Keywords: aridity, climate change, desertification, precipitation

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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Authors: Kathryn Rooney, Kaitlyn Eddy, Evan Landers, Weihui Li

Abstract:

The international mortality rate for neonates and infants has been declining at a disproportionally low rate when compared to the overall decline in child mortality in recent decades. A significant portion of infant deaths could be prevented with the implementation of low-cost and easy to use physiological monitoring devices, by enabling early identification of symptoms before they progress into life-threatening illnesses. The oral diagnostic device discussed in this paper serves to continuously monitor the key vital signs of body temperature, respiratory rate, heart rate, and oxygen saturation. The device mimics an infant pacifier, designed to be easily tolerated by infants as well as orthodontically inert. The fundamental measurements are gathered via thermistors and a pulse oximeter, each encapsulated in medical-grade silicone and wired internally to a microcontroller chip. The chip then translates the raw measurements into physiological values via an internal algorithm, before outputting the data to a liquid crystal display screen and an Android application. Additionally, a biological sample collection chamber is incorporated into the internal portion of the device. The movement within the oral chamber created by sucking on the pacifier-like device pushes saliva through a small check valve in the distal end, where it is accumulated and stored. The collection chamber can be easily removed, making the sample readily available to be tested for various diseases and analytes. With the vital sign monitoring and sample collection offered by this device, abnormal fluctuations in physiological parameters can be identified and appropriate medical care can be sought. This device enables preventative diagnosis for infants who may otherwise have gone undiagnosed, due to the inaccessibility of healthcare that plagues vast numbers of underprivileged populations.

Keywords: neonate mortality, infant mortality, low-cost diagnostics, vital signs, saliva testing, preventative care

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: Tehreem Fatima, Enjun Xia

Abstract:

The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

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Authors: Adewale Oladapo, Carolyn A. Afolami

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Agricultural production should be the major financial contributor to the Nigerian economy; however, the petroleum sector had taken the importance attached to this sector. The situation tends to be more worsening unless necessary attention is given to adequate credit supply among food crop farmers. This research analyses the effect of credit use on the technical efficiency of cassava farmers in Ondo State, Nigeria. Primary data were collected from two hundred randomly selected cassava farmers through a multistage sampling procedure in the study area. Data were analysed using descriptive statistics and stochastic frontier analysis (SFA). Findings revealed that 95.0% of the farmers were male while 56.0% had no formal education and were married. The SFA showed that cassava farmer’s efficiency increased with farm size, herbicide and planting material at 5%,10% and 1% respectively but decreased with fertilizer application at 1% level while farmers’ age, education, household size, experience and access to credit increased technical inefficiency at 10%. The study concluded that cassava farmers are technically inefficient in the use of farm resources and recommended that adequate and workable agricultural policy measures that will ensure availability and efficient fertilizer distribution should be put in place to increase efficiency. Furthermore, the government should encourage youth participation in cassava production and ensure improvement in farmer’s access to credit to increase farmer’s technical efficiency.

Keywords: agriculture, access to credit, cassava farmers, technical efficiency

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Authors: Felipa de Mello-Sampayo

Abstract:

The aim of this study is to undertake, from patient’s perspective, the timing and probability of using teledermatology, comparing it with a conventional referral system. The dynamic stochastic model’s main value-added consists of the concrete application to patients waiting for dermatology surgical intervention. Patients with low health level uncertainty must use teledermatology treatment as soon as possible, which is precisely when the teledermatology is least valuable. The results of the model were then tested empirically with the teledermatology network covering the area served by the Hospital Garcia da Horta, Portugal, links the primary care centers of 24 health districts with the hospital’s dermatology department via the corporate intranet of the Portuguese healthcare system. Health level volatility can be understood as the hazard of developing skin cancer and the trend of health level as the bias of developing skin lesions. The results of the survival analysis suggest that the theoretical model can explain the use of teledermatology. It depends negatively on the volatility of patients' health, and positively on the trend of health, i.e., the lower the risk of developing skin cancer and the younger the patients, the more presurgical teledermatology one expects to occur. Presurgical teledermatology also depends positively on out-of-pocket expenses and negatively on the opportunity costs of teledermatology, i.e., the lower the benefit missed by using teledermatology, the more presurgical teledermatology one expects to occur.

Keywords: teledermatology, wait time, uncertainty, opportunity cost, survival analysis

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Authors: Yerbolat Iztleuov

Abstract:

Stochastic effects, which are currently largely associated with exposure to ionizing radiation or a combination of ionizing radiation with other chemical, physical, and biological agents, are expressed in the form of various mutations. In the first stage of the study, rats of both sexes were divided into 3 groups. 1st - control group, animals of the 2nd group were exposed to gamma radiation at a dose of 0.2 Gy. The third group received hexavalent chromium in a dose of 180 mg/ l with drinking water for a month before irradiation and a day after the end of chromium consumption and was subjected to total gamma irradiation at a dose of 0.2 Gy. The second stage of the experiment. After 3 days, the males were mated with the females. The obtained offspring were studied for peroxidation, cytokine profile and micronucleus in the nuclei. This study shows that 5-month-old offspring whose parents were exposed to combined exposure to chromium and γ-irradiation exhibit hereditary instability of the genome, decreased activity of antioxidant enzymes and sulfhydryl blood groups, and increased levels of lipid peroxidation. There is also an increase in the level of inflammatory markers (IL-6 and TNF) in the blood plasma against the background of a decrease in anti-inflammatory cytokine (IL-10). Thus, the combined effect of hexavalent chromium and ionizing radiation can lead to the development of an oncological process.

Keywords: hexavalent chromium, ionizing radiation, first generation, oxidative stress, cytokines, mutagenesis, cancer

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Authors: Tan Zhang, Zhongjian Wang, Jack Xin, Zhiwen Zhang

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We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed.

Keywords: KPP front speeds, random flows, Feynman-Kac semigroups, interacting particle method, convergence analysis

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Authors: Bozena Dohnalkova

Abstract:

This paper presents a part of the project solving which is dedicated to the identification of the hazardous waste with the most critical production within the Czech Republic with the aim to study and find the optimal composition of the cement matrix that will ensure maximum content disposal of chosen hazardous waste. In the first stage of project solving – which represents this paper – a specific hazardous waste was chosen, its properties were identified and suitable solidification agents were chosen. Consequently solidification formulas and testing methodology was proposed.

Keywords: cementation, solidification, waste, binder

Procedia PDF Downloads 392