286 research outputs found

    Numerical Strategies for Mixed-Integer Optimization of Power-Split and Gear Selection in Hybrid Electric Vehicles

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    This paper presents numerical strategies for a computationally efficient energy management system that co-optimizes the power split and gear selection of a hybrid electric vehicle (HEV). We formulate a mixed-integer optimal control problem (MIOCP) that is transcribed using multiple-shooting into a mixed-integer nonlinear program (MINLP) and then solved by nonlinear model predictive control. We present two different numerical strategies, a Selective Relaxation Approach (SRA), which decomposes the MINLP into several subproblems, and a Round-n-Search Approach (RSA), which is an enhancement of the known ‘relax-n-round’ strategy. Subsequently, the resulting algorithmic performance and optimality of the solution of the proposed strategies are analyzed against two benchmark strategies; one using rule-based gear selection, which is typically used in production vehicles, and the other using dynamic programming (DP), which provides a global optimum of a quantized version of the MINLP. The results show that both SRA and RSA enable about\ua03.6%\ua0cost reduction compared to the rule-based strategy, while still being within\ua01%\ua0of the DP solution. Moreover, for the case studied RSA takes about\ua035%\ua0less mean computation time compared to SRA, while both SRA and RSA being about\ua099\ua0times faster than DP. Furthermore, both SRA and RSA were able to overcome the infeasibilities encountered by a typical rounding strategy under different drive cycles. The results show the computational benefit of the proposed strategies, as well as the energy saving possibility of co-optimization strategies in which actuator dynamics are explicitly included

    Identification and phylogenetic analysis of filamentous Cyanobacteria using random amplified polymorphic DNA (RAPD) fingerprinting

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    RAPD techniques were used for the detection of genetic heterogeneticity among the axenic culture of fresh water cyanobacterial isolates. The electrophoretic patterns for 12 cyanobacterial strainsbelonging to 2 genera (8 Oscillatoria strains and 4 Lyngbya strains) were used for molecular analysis using the RAPD technique. A total of 12 cyanobacterial isolates were selected and mass cultured inBG11 medium. Genomic DNA was extracted from fresh water cyanobacterial isolates and was amplified using primers D7, M13, OPC11, OPC12, OPC13, OPC14 and OPC15 and distinct PCR fingerprint were generated. Unique banding patterns were observed from all tested cyanobacterial species and their molecular weights of each band were used to calculate their genetic distance among them. Random amplification of polymorphic DNA (RAPD) was carried out for the phylogenetic characterization of these strains. RAPD fingerprinting results clearly showed the genetic variation among the cyanobacterial isolates

    Bone health after menopause: effect of surgical menopaus on bone mineral density and osteoporosis

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    Background: Natural menopause or surgical menopause is associated with endocrinological changes and alteration in bone and mineral metabolism. Hence this study was conducted to assess the bone mineral density changes in women with surgical menopause. Methods: This is a prospective observational study conducted in the department of obstetrics and gynaecology at Sri Ramachandra medical college, which is a tertiary care teaching hospital. 60 women with surgical menopause were included in the study. BMD was assessed by dual energy X-ray absorptiometry at the lumbar spine and hip joint. All the data was entered in Microsoft excel spread sheet and analysed by using SPSS software.Results: Among 60 study subjects, 41 individuals had a normal BMD, 16 had osteopenia, and 3 were diagnosed with osteoporosis. Osteopenia and osteoporosis is significantly higher in patients who had undergone hysterectomy with removal of ovaries. Observations of osteopenia and osteoporosis were significantly higher with increasing number of years post hysterectomy.Conclusions: Prevalence of osteoporosis is high in patients who undergo hysterectomy. Oophorectomy is associated with postoperative bone loss. Targeted management strategies should include routine BMD assessment and hormone therapy improves management of bone health in this population. Further more studies are needed in large populations to test alternative treatments for post oophorectomy osteoporosis

    SCANMOT: searching for similar sequences using a simultaneous scan of multiple sequence motifs

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    Establishment of similarities between proteins is very important for the study of the relationship between sequence, structure and function and for the analysis of evolutionary relationships. Motif-based search methods play a crucial role in establishing the connections between proteins that are particularly useful for distant relationships. This paper reports SCANMOT, a web-based server that searches for similarities between proteins by simultaneous matching of multiple motifs. SCANMOT searches for similar sequences in entire sequence databases using multiple conserved regions and utilizes inter-motif spacing as restraints. The SCANMOT server is available via

    Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

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    <p>Abstract</p> <p>Background</p> <p>RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis.</p> <p>Results</p> <p>In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes.</p> <p>Conclusions</p> <p>We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.</p

    Bold:Bio-inspired optimized leader election for multiple drones

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    Over the past few years, unmanned aerial vehicles (UAV) or drones have been used for many applications. In certain applications like surveillance and emergency rescue operations, multiple drones work as a network to achieve the target in which any one of the drones will act as the master or coordinator to communicate, monitor, and control other drones. Hence, drones are energy-constrained; there is a need for effective coordination among them in terms of decision making and communication between drones and base stations during these critical situations. This paper focuses on providing an efficient approach for the election of the cluster head dynamically, which heads the other drones in the network. The main objective of the paper is to provide an effective solution to elect the cluster head among multi drones at different periods based on the various physical constraints of drones. The elected cluster head acts as the decision-maker and assigns tasks to other drones. In a case where the cluster head fails, then the next eligible drone is re-elected as the leader. Hence, an optimally distributed solution proposed is called Bio-Inspired Optimized Leader Election for Multiple Drones (BOLD), which is based on two AI-based optimization techniques. The simulation results of BOLD compared with the existing Particle Swarm Optimization-Cluster head election (PSO-C) in terms of network lifetime and energy consumption, and from the results, it has been proven that the lifetime of drones with the BOLD algorithm is 15% higher than the drones with PSO-C algorithm

    UTILIZATION OF SAMANYA SHODHANA IN THE PURIFICATION OF EXCESS MERCURY OBTAINED FROM DENTAL OPERATORY- A PRELIMINARY STUDY

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    Background: Concerns about toxicity of mercury and disposal of excessive mercury has led to decreased usage of mercury in dental profession but still tooth colored restorative materials are not affordable by all the classes of any society. The disposal of excess mercury has always been a matter of concern. Thus, in the present study, we attempted to evaluate a simple procedure from Rasa Shastra using lime powder, garlic and rock salt for recycling of excess mercury obtained from dental operatory.Materials and methods: The excess mercury was recycled by the standard procedure explained in Ayurveda texts (Samanya shodhana) using Sudha churna (lime powder), Lashuna kalka (paste of Allium sativum L.) and Saindhava lavanaa (rock salt). The commercially available mercury and recycled mercury was analyzed by inductively coupled plasma mass spectrometry (ICP-MS) for the detection of elements in ppm level.Results: It was found that the excess impure mercury contained 5138 ppm, 2866.1 ppm and 0.371 ppm of Silver, Copper and Tin respectively. After Shodhana, the level of silver, tin and copper were markedly reduced. Purified mercury showed a level of 119.5ppm silver, 0.5324 ppm copper and 0.3233 ppm tin.Conclusion: Samanya shodhana is a simple promising procedure which can be used for mercury recycling. The procedure doesnot require sophisticated equipments and maneuver. Further, the materials used in the procedure are easily available and affordable at low cost

    Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

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    Background Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease. Methods Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology. Results Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years). Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied

    METHODS FOR PREDICTING THE REMAINING LIFE OF ELECTRONIC ASSEMBLIES WITH CARBON NANOTUBES AND AN OPTICAL TRANSDUCTION TECHNIQUE

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    ABSTRACT Life consumption monitoring is a method of quantifying the degradation of a system by monitoring the life cycle environment. With current research demonstrating the value of nanotubes as sensors, they may prove to be an inexpensive, compact, and reliable means to monitor not only system environments, but also physical signs of degradation. Life consumption monitoring of electronic assemblies can be cost-effectively done using optical strain measurement techniques. In this study, current output from an optical sensor can be used to interpret combined temperature and vibration histories. This may be accomplished by passing monofrequency light through optical fibers in a peripheral arrangement on a dummy chip. Any deviation from the null condition results in misalignment of the fibers, and hence reduction in intensity and current output. With appropriate failure data at different stress levels, it is possible to determine damage and estimate the remaining life. The key challenges are to determine whether such an optical health monitoring scheme can be sufficiently accurate and robust, and whether the results can be applied to a variety of packages at any location on a circuit assembly
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