Systematic Search Algorithm Research Articles

Optimal High Pass FIR Filter Based on Adaptive Systematic Cuckoo Search Algorithm

Abstract This paper presents the design of a desired linear phase digital Finite Impulse Response (FIR) High Pass (HP) filter based on Adaptive Systematic Cuckoo Search Algorithm (ACSA). The deviation, or error from the desired response, is assessed along with the stop-band and pass-band attenuation of the filter. The Cuckoo Search algorithm (CS) is used to avoid local minima because the error surface is typically non-differentiable, nonlinear, and multimodal. The ACSA is applied to the minimax criterion (L∞-norm) based error fitness function, which offers a better equiripple response for passband and stopband, high stopband attenuation, and rapid convergence for the developed optimal HP FIR filter algorithm. The simulation findings demonstrate that when compared to the Parks McClellan (PM), Particle Swarm Optimization (PSO), CRazy Particle Swarm Optimization (CRPSO), and Cuckoo Search algorithms, the proposed HP FIR filter employing ACSA leads to better solutions.

The Prevalence of Hepatitis C Infection in Blood Donors: A Meta-Analysis and Systematic Review

Context: Hepatitis C virus (HCV) infection is one of the major diseases worldwide. Although many screening tests were introduced and utilized for donations, as the main source of HCV transmission, it has still remained a global concern. Evidence Acquisition: The prevalence of HCV infection among donors in every country and every WHO region was investigated. A Comprehensive electronic systematic search algorithm in the international databases PubMed, ISI, Scopus, and ProQuest were adopted for articles published until October 2016, using the following keywords: (Blood Donors OR OR donor OR donation OR blood OR safety OR bloodborne OR residual risk OR transfusion-transmitted infections) AND (prevalence OR epidemiology) in combination with “hepatitis C” OR “HCV” for hepatitis C. Only cross-sectional studies, which had appropriate measurement and sampling methods, were selected. Results: The review of the literature showed that the global prevalence of HCV was 854.09 in 100,000. The highest and lowest rates of HCV among WHO divisions were seen in the African region by 2503.61 and the European region by 450.21 in 100,000, respectively. The highest and lowest rates among the countries were seen in Cambodia by 14,670 and Netherlands by 25.370 in 100,000. Conclusions: It seems that strategies for prevention of HCV infection in donations should be considered for the policymakers; low prevalence countries are suggested to share their knowledge and countries with lower socioeconomic status should be aided to control the HCV infection among their donors.

Hybrid Hydraulic Vehicle Parameter Optimization using Multi-Objective Genetic Algorithm

Parameter optimizations of HHV torque distribution must deal with conflicting objectives between the engine torque and fuel economy without compromising the vehicle driving quality. The torque generation from an internal combustion engine (ICE) is directly influenced by the amount of fuel burnt, hence cannot be solved using a classical single-objective optimization method. In this paper, multi-objective genetic algorithm (MOGA) is used to optimize the power split of a parallel hybrid hydraulic vehicle (HHV) that utilizes an ICE and a hydraulic motor. The simulation runs on three operating modes, engine only, power assist and regenerative modes to optimize two conflicting objectives, engine torque and fuel economy considering both highway and city drive cycles. Using a single unified formulation, a number of design objectives can be simultaneously optimized through a systematic search algorithm within a diverse parameter space. Simulation results have shown both objectives have good compromises that lie along the Pareto optimal front. In comparison, it is observed that there is a significant improvement on fuel economy for HHV as compared to a conventional ICE especially at low-torque operation when the hydraulic motor assists the vehicle for both highway and city drive cycles.
 

A New Search Algorithm for Reducing the Incidence of Missing Cottonoids in the Operating Theater

Study DesignRetrospective study.PurposeMissing cottonoids during and after spinal surgery is a persistent problem and account for the most commonly retained surgical instruments (RSIs) noticed during a final cottonoid count. The aim of this study was to enumerate risk factors and describe the sequence to look out for misplaced cottonoids during spinal surgery and provide an algorithm for resolving the problem.Overview of LiteratureThere are only a few case reports on RSIs among various surgical branches. The data is inconclusive and there is little evidence in the literature that relates to spinal surgery.MethodsThis retrospective study was conducted at Indian Spinal Injuries Centre. The data was collected from hospital records ranging from January 2013 to December 2017. The surgical cases in which cottonoid counts were inconsistent during or after the procedure were included in the study. The case files along with operating theater records were thoroughly screened for selecting those in which there was confirmed evidence of such an event.ResultsThere were 7,059 spinal surgeries performed during the study period. Fifteen cases of miscounts were recorded with an incidence of one in every 471 cases. Cottonoids were most commonly lost under the shoes of the surgeon or assistants. In two instances, cottonoids were found in the surgical field and trapped in the interbody cage site. Based on these locations, a systematic search algorithm was createdConclusionsThis study enumerates RSI risk factors in spinal surgical procedures and describes steps that can be followed to account for any missing cottonoids. The incidence of missing cottonoids can be decreased using a goal-oriented approach and ensuring that surgical teams work in collaboration.

Systematic search algorithm for potential thermochemical energy storage systems

Thermochemical energy storage (TCES) is considered as an emerging green technology for increased energy utilization efficiency, thereby achieving a reduction of greenhouse gases. Various reaction systems based on different substance classes (e.g. hydrates, hydroxides, oxides) were suggested and investigated so far. Nevertheless, the number of know reactions which are suitable is still limited, as the main focus concentrates on the investigation of a handful known substances, their further improvement or applicability. To find novel promising candidates for thermochemical energy storage and also to allow for a broader view on the topic, this work present a systematic search approach for thermochemical storage reactions based on chemical databases. A mathematical search algorithm identifies potential reactions categorized by the reactant necessary for the reaction cycle and ranked by storage density. These candidates are listed in the online available VIENNA TCES-database, combined with experimental results, assessing the suitability of these reactions regarding of e.g. decomposition/recombination temperature, reversibility, cycle stability, etc.

Identification of high affinity bioactive Salbutamol conformer directed against mutated (Thr164Ile) beta 2 adrenergic receptor.

Salbutamol forms an important and widely administered β2 agonist prescribed in the symptomatic treatment of bronchial asthma. Unfortunately, a subset of patients show refractoriness to it owing to ADRB2 gene variant (rs 1800888). The variant substitutes Thr to Ile at the position 164 in the β2 adrenergic receptor leading to sub-optimal binding of agonists. The present study aims to associate the Salbutamol response with the variant and select the bioactive conformer of Sabutamol with optimal binding affinity against mutated receptor by in silico approaches. To assess bronchodilator response spirometry was performed before and 15 min after Salbutamol (200 mcg) inhalation. Responders to Salbutamol were categorized if percentage reversibility was greater than or equal to 12%, while those showing FEV₁ reversibility less than 12% were classified as non-responders. Among the 344 subjects screened, 238 were responders and 106 were non-responders. The frequency of mutant allele "T" was significantly higher in case of non-responders (p < 0.05). In silico process involved generation of Salbutamol conformer ensembles supported by systematic search algorithm. 4369 conformers were generated of which only 1882 were considered bioactive conformers (threshold RMSD≤1 in reference to normalized structure of salbutamol). All the bioactive conformers were evaluated for the binding affinity against (Thr164 Ile) receptor through MolDock aided docking algorithm. One of the bioactive conformer (P.E. = -57.0038, RMSD = 0.6) demonstrated 1.54 folds greater affinity than the normal Salbutamol in the mutated receptor. The conformer identified in the present study may be put to pharmacodynamic and pharmacokinetic studies in future ahead.

Minimizing Dimensional Variation and Robot Traveling Time in Welding Stations

Complex assembled products as an automotive car body consist of about 300 sheet metal parts joined by up to 4000 spot welds. In the body factory, there are several hundred robots organized into lines of welding stations. The distribution of welds between robots and the welding sequences have a significant influence on both dimensional quality and throughput. Therefore, this paper proposes a novel method for quality and throughput optimization based on a systematic search algorithm which exploits properties of the welding process. It uses approximated lower bounds to speed up the search and to estimate the quality of the solution. The method is successfully tested on reference assemblies, including detailed fixtures, welding robots and guns.

Temperature-Dependent Self-Assembly of Adenine Derivative on HOPG

Temperature-dependent self-assembly formed by the adsorption of the nucleobase adenine derivative on a graphite surface were investigated by in situ scanning tunneling microscopy (STM). The high-resolution STM images reveal two types of structures, α phase and β phase, which are mainly driven by either hydrogen bonding or aromatic π-π interactions between adenine bases, respectively, as well as the interactions of alkyl chains. α-Phase structures can be transformed into β-phase structures by increasing temperature. The reverse is true for decreasing temperature. This reflects structural stabilities resulting from the different interactions. Density functional theory (DFT) calculations were performed to characterize possible arrangements of adjacent adenine moieties systematically in terms of binding energies and structural properties. Via a systematic search algorithm, all possible network structures were determined on a microscopic level. In this way, it is possible to rationalize the structural parameters as found in the STM images.

Aerodynamic pitch control design for reversal of missile’s flight direction

This paper proposes a purely aerodynamic pitch control design scheme for agile missiles that need to reverse their flight directions for tracking a target. The main challenge in performing this kind of manoeuvre is that the missiles may enter the high angle of attack domain in which aerodynamic actuation is ineffective. Assuming that reliable aerodynamic data are available for the flight envelope, a systematic search algorithm is employed to find an aerodynamic control parameter and the motor thrust activation time, so as to enable the missile’s required manoeuvre. The strength of the proposed design scheme is that no third control mechanism such as thrust vectoring is required for the missile control even in the high angle of attack domain. The proposed design scheme is tested on aerodynamic data available in literature, and is shown to be promising via simulations.

Anytime QoS-aware service composition over the GraphPlan

Automatic service composition is the generation of a business process to fulfill business goals that cannot be fulfilled by individual services. Planning algorithms are frequently used to solve this problem. In addition to satisfying functional goals, recent research is geared toward selecting the best services to optimize the QoS of the result business process. Without considering QoS, the planning algorithm normally searches for the shortest plan, which actually implies the unit execution time for each service. With QoS, a longer plan may have better QoS values and thus is preferred over a shorter one. In this paper, we are motivated to combine a systematic search algorithm like Dijkstra's algorithm with a planning algorithm, GraphPlan, to achieve both functional goals and QoS optimization at the same time. The planning graph generated by GraphPlan is a compact representation of all execution paths, which makes it feasible to apply Dijkstra's principle. In our new QoSGraphPlan algorithm, we extend Dijkstra's algorithm from working on a single-source graph to working on the planning graph whose nodes have multiple sources. Using our method, we can get the best QoS value for throughput and response time in polynomial time when they are the single criteria. For the other QoS criteria, such as execution time, reputation, successful execution rate, and availability, our algorithm is exponential for both single criterion problem and multiple criteria problem. In this case, we extend QoSGraphPlan with beam search to solve the combination explosion problem. As our algorithms search for an optimal solution during the process of constructing the planning graph, they belong to the category of anytime algorithms that return better solutions if they keep running for a longer time.

Analysis of transmit beamforming performance on multiple-transmit binary ZCZ waveforms

The Transmit BeamForming (TBF) technology, applied in a multiple-transmit radar system, is studied in this paper, where multiple elements of antenna array transmit binary Zero Correlation Zones Orthogonal Signals (ZCZ-OS) independently. For each Direction Of Arrival (DOA) with respect to the transmitting array, the analysis on the gain and sidelobe level of TBF output is presented. This paper focuses on the range sidelobes performance within the main beam (in angle domain). For the normal direction, due to the inherent phase property of ZCZ-OS, the TBF output has part zero sidelobes area, of which the distribution is discussed. For the other directions, a systematic search algorithm to optimize the transmission order of signals is proposed for an optimal relationship chart of DOA and transmission order. The range sidelobe performance within the main beam can be improved as the optimal transmission order is adopted.

Most effective adjuvant treatments after surgery in peripheral nerve laceration: Systematic review of the literature on rodent models

Surgical repair alone does not lead to satisfactory recovery after nerve laceration injury, yet no adjuvant clinical treatments are available. The goal of this review is to systematically survey all adjuvant treatments after surgery investigated in rat and mouse models. Both PubMed and Embase were explored with a systematic bibliographic search algorithm. Inclusion criteria consisted of treatments applied to rats or mice after complete transection and microsurgical repair of lower-limb motor or mixed nerves. Effect size statistics enabled numerical comparison between outcomes of treated and untreated animals and ranked the best treatments. 1,553 articles were found according to our search strategies, and 22 of them corresponded to our pre-defined inclusion criteria. After data extraction and analysis, the top 3 adjuvant strategies in terms of combined average effect size were citicoline, neurotrophin-4, and nitric oxide synthesis inhibitor, with values of 5.52, 5.14 and 4.08, respectively. Definitive treatment comparison was difficult due to the lack of uniformity in outcome evaluation in the experiments performed. Animal studies, comparing treatments administered within the same experimental protocol, are needed to truly assess efficiency and to provide solid recommendations for future clinical investigation.

A seasonal pattern of presentation in younger patients with de novo acute myeloid leukemia (AML).

6617 Background: Seasonal variation in AML has been studied in a wide variety of populations and locations, with primarily negative results. These investigations may have been undermined by the heterogeneity of the disease, as de novo and secondary AML can vary in disease presentation and trajectory, likely reflecting distinct pathogenesis.We investigated seasonal variation in the incidence of AML diagnosed at Massachusetts General Hospital (MGH) from 1992 through 2011, focusing on de novo disease among younger patients. Methods: We assembled a database of 511 biopsy-proven cases of adult-onset AML (age &gt; 18 years), from the MGH electronic medical record, using a systematic search algorithm with IRB approval. We subdivided this database into three cohorts: (1) de novo AML diagnosed prior to age 50 (2) de novo AML diagnosed after age 50, and (3) secondary AML, preceded by chemotherapy, myelodysplasia or myeloproliferative disease. Diagnosis dates were grouped into quarters (Jan-Mar, Apr-Jun, Jul-Sep, Oct-Dec). Divergence of quarterly incidence from a null hypothesis of uniformity was evaluated by chi square analysis. Results: Among patients under 50-years-old with de novo AML, we found a 44% increase in incidence between October and December (Table, p=0.04). There was no significant variation throughout the rest of the calendar year. Furthermore, the incidence of both de novo AML diagnosed after age 50 and secondary AML conformed to a uniform quarterly distribution. As expected, the majority of AML patients under age 50 demonstrated intermediate-risk cytogenetics, most frequently normal karyotype. Conclusions: We found a significantly increased incidence of de novo AML in younger patients between the months of October and December, diagnosed at MGH from 1992 through 2011. This may reflect a local environmental or infectious exposure that is not relevant to the pathogenesis of AML in older patients or those in whom AML develops due to prior therapy or previous hematological disorder. Investigation of this exposure is ongoing. [Table: see text]

CONNECTING SYMMETRIC AND ASYMMETRIC FAMILIES OF PERIODIC ORBITS IN SQUARED SYMMETRIC HAMILTONIANS

In this work, we study a generic squared symmetric Hamiltonian of two degrees of freedom. Our aim is to show a global methodology to analyze the evolution of the families of periodic orbits and their bifurcations. To achieve it, we use several numerical techniques such as a systematic grid search algorithm in sequential and parallel, a fast chaos indicator and a tool for the continuation of periodic orbits. Using them, we are able to study the special and generic bifurcations of multiplicity one that allow us to understand the dynamics of the system and we show in detail the evolution of some symmetric breaking periodic orbits.

Completeness of reporting in abstracts from clinical trials of pre-harvest interventions against foodborne pathogens

Abstracts are the most commonly read part of a journal article, and play an important role as summaries of the articles, and search and screening tools. However, research on abstracts in human biomedicine has shown that abstracts often do not report key methodological features and results. Little research has been done to examine reporting of such features in abstracts from papers detailing pre-harvest food safety trials. Thus, the objective of this study was to assess the quality of reporting of key factors in abstracts detailing trials of pre-harvest food safety interventions.A systematic search algorithm was used to identify all in vivo trials of pre-harvest interventions against foodborne pathogens in PubMed and CAB Direct published from 1999 to October 2009. References were screened for relevance, and 150 were randomly chosen for inclusion in the study. A checklist based on the CONSORT abstract extension and the REFLECT Statement was used to assess the reporting of methodological features and results. All screening and assessment was performed by two independent reviewers with disagreements resolved by consensus.The systematic search returned 3554 unique citations; 356 were found to be relevant and 150 were randomly selected for inclusion. The abstracts were from 51 different journals, and 13 out of 150 were structured. Of the 124 abstracts that reported whether the trial design was deliberate disease challenge or natural exposure, 113 were deliberate challenge and 11 natural exposure. 103 abstracts detailed studies involving poultry, 20 cattle and 15 swine.Most abstracts reported the production stage of the animals (135/150), a hypothesis or objective (123/150), and results for all treatment groups (136/150). However, few abstracts reported on how animals were grouped in housing (25/150), the location of the study (5/150), the primary outcome (2/126), level of treatment allocation (15/150), sample size (63/150) or whether study units were lost to follow up (4/150). Forty-eight (48/150) abstracts reported the name, mode of administration, dose and duration of the intervention(s), while 102 (102/150) reported at least one of these elements. Nine (9/150) abstracts specified that allocation of study units to treatments was randomized, and none of the abstracts reported whether blinding was used (0/150).These results reveal gaps in reporting of methodological features and results. Thus, improving reporting quality in abstracts should be a crucial goal to be pursued by authors, reviewers and journal editors.

Synthesis, characterization and conformational analysis of chloro-bis(glycylglycinate)germanium(iv) chloride

Chloro-bis(glycylglycinate)germanium(IV) chloride, [Cl(glygly)2Ge]Cl, was synthesized and characterized in the solid state by elemental analysis, thermogravimetry and infrared spectroscopy. Solution studies were also performed by 1H-NMR and 13C-NMR in dimethylsulfoxide (DMSO-d6) and by electric conductivity. The structural determination of the complex and the interpretation of the spectroscopic results were performed by employing an integrated computational approach, based on a systematic conformational search analysis on the [Cl(glygly)2Ge]+ ion performed by the Systematic Conformational Search Algorithm (SCSA) code, working at the hybrid B3LYP/6-31G(d,p) level. The combination of experimental and computational findings allowed us to draw the structure of the complex both in solid and in solution, showing the usefulness of the conformational search as well as the need to also take into account relatively high energy structures and secondary minima to obtain a clear picture of the title compound.

An improved fuzzy forecasting method for seasonal time series

Several time-variant fuzzy time series models have been developed during the last decade. These models usually focus on forecasting stationary of trend time series, but they are not suitable for forecasting seasonal time series. Furthermore, several factors that affect the forecasting accuracy are not carefully examined, such as interval length, interval number, and level of window base. Aiming to solve these issues, the goal of this study is to develop an improved fuzzy time series forecasting method that can effectively deal with seasonal time series. The proposed method can determine appropriate length interval. Moreover, a systematic search algorithm is used to find the best window base. The proposed method can provide decision analysts with more precise forecasted values. Two numerical data sets are employed to illustrate the proposed method and to compare the forecasting accuracy between the proposed method and four fuzzy time series methods. The results of the comparison indicate that the proposed method produces more accurate forecasted results.

Nanotubes sorted using DNA

A vast number of DNA sequences are possible, and so finding the few that bind to a particular non-DNA entity is a daunting task. A systematic search algorithm has found sequences that target specific carbon nanotubes.

Applications of Advanced Polynomial Neural Networks for Prediction of Multi-well Reservoir Performance

The major impediment in the formal optimization of large petroleum-producing fields is the cost of computing the state of the objects being optimized. Previous studies for prediction of reservoir performance with respect to time have used local inflow performance relationships or material balance models. These approaches, however, ignored flow interactions among wells during the optimization process, often resulting in suboptimal operations. In this study, a new polynomial neural network (PNN) with layer over-passing structure has been developed to replace a relatively time consuming reservoir simulator through robust and systematic search algorithm. The networks are subject to some form of training based on a representative sample of simulations that can be used as a re-useable knowledge base of information for addressing many different management questions. The proposed approach significantly reduces computational effort for optimizing the development scheme within reasonable accuracy and outperforms other neural network models.

A Quantum Mechanically Guided View of Mg44Rh7.

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract, please click on HTML or PDF.