Comparative Analysis of Metaheuristic Approaches for Makespan Minimization for No Wait Flow Shop Scheduling Problem

This paper provides comparative analysis of various metaheuristic approaches for m-machine no wait flow shop scheduling (NWFSS) problem with makespan as an optimality criterion. NWFSS problem is NP hard and brute force method unable to find the solutions so approximate solutions are found with metaheuristic algorithms. The objective is to find out the scheduling sequence of jobs to minimize total completion time. In order to meet the objective criterion, existing metaheuristic techniques viz. Tabu Search (TS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are implemented for small and large sized problems and effectiveness of these techniques are measured with statistical metric

Dental Prosthetic Status and Prosthetic Needs of Patients Visiting Gandaki Medical College, Western Nepal

Introduction: The study of prosthetic status and prosthetic need will help us to find out the degree of treatment required in the population which will help to frame the health care services. Objective: The objective of the study was to find out the prosthetic status, prosthetic need in different age groups and their correlation with socio-economic status in patients visiting Department of Prosthodontics, College of Dental Surgery, Gandaki Medical College, Pokhara, Nepal. Materials and Methods: The patients visiting Department of Prosthodontics, College of Dental Surgery, Gandaki Medical College, Pokhara, Nepal were screened. The demographic profile of the patients was obtained and clinical examination for prosthetic status and prosthetic need was done based on WHO method. Results: There were total of 309 patients who visited the department during the study period. There were 133 (43%) male and 176 (57%) female patients. The majority of patients had no prosthesis in upper arch 78.6% and 83.8% in lower arch. The number of patients with replacement of missing teeth in upper arch was 66 (21.4%) and in lower arch were 50 (16.2%). There were 159 (51.5%) of patients requiring one or the other form of prosthesis in upper arch and 161 (52.1%) of patients in lower arch. Conclusion: The majority of patients had no prosthesis 78.6% in upper arch and 83.8% in lower arch. The need of prosthesis was 51.5% in upper arch and 52.1 % in lower arch

Integrative genome-wide association studies (GWAS) to understand complex genetic architecture of quantitative traits in chickpea

Development of high-yielding stress-tolerant chickpea cultivars is essential to enhance its yield potential and productivity amidst climate change scenario. Unfortunately, superior lines/recombinants producing higher pod and seed yield under stress are not available in world chickpea collection. Therefore, genetic dissection of complex stress tolerance and yield-contributing quantitative traits is the prime objective in current chickpea genomics and breeding research. Our study employed diverse GWAS-assisted integrated genomic strategies involving classical genetic inheritance analysis, QTL mapping, differential transcript profiling, molecular haplotyping and haplotype-based gene domestication/ evolution study for rapid quantitative dissection of complex yield and stress tolerance traits in chickpea. To accomplish this, multi-location/years replicated yield traits-related field phenotyping and high-throughput marker genotyping information generated from numerous natural germplasm accessions (association panel) and multiple intra- and inter-specific mapping populations of chickpea were deployed in the aforesaid combinatorial genomic approaches. These analyses delineated 12 novel alleles and six haplotypes from 10 transcription factor genes and 16 major QTLs/eQTLs governing yield and stress tolerance traits that were mapped on 10 ultra-high density chickpea genetic linkage maps. The superior natural alleles/haplotypes of two major genes (QTLs) regulating seed weight and pod/seed number identified from cultivated and wild Cicer gene pools are being introduced into multiple high-yielding Indian varieties of chickpea for its marker-assisted genetic improvement. The potential molecular signatures delineated using integrated genomics- assisted breeding strategies have functional significance to understand the molecular genetic mechanism and natural allelic diversity-led domestication pattern underlying these complex quantitative traits at a genome-wide scale, leading to fast-paced translational genomics for chickpea genetic enhancement. These essential outcomes will be useful for devising the most efficient strategies to produce high-yielding climate-resilient chickpea cultivars for sustaining global food security

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Evolutionary Hybrid Particle Swarm Optimization Algorithm for Solving NP-Hard No-Wait Flow Shop Scheduling Problems

The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO) metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO) algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH) heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard’s benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance

Remote Monitoring and Control for an Isolate Prototype Substation Model

The objective of this paper is to monitor the electrical parameters like voltage, current, etc., remotely and display all the obtained real time values for a substation isolate. This paper is furnished to assure the load and electrical system equipment by the activation of relay, whenever the acquired parameters exceed the predefined values. Generally, this Proposed system design makes use of microcontroller, but the prototype of this circuit modelled in Proteus and can be executed by using ATmega 168 microcontroller. When supply is given to the designed hardware, all the sensors start sensing their respective parameters i. e., voltage, current, temperature etc., and modernize all the values on the display. Comparison between the problem-solving time values and the preordained values is continuously carried out by the microcontroller, if any of these values go beyond the pre-defined values, it sends fault alert to the relay, updates it on the screen and sends the same as an SMS through GSM for the rectification

Evaluating EcxR for Its Possible Role in Ehrlichia chaffeensis Gene Regulation

Ehrlichia chaffeensis, a tick-transmitted intraphagosomal bacterium, is the causative agent of human monocytic ehrlichiosis. The pathogen also infects several other vertebrate hosts. E. chaffeensis has a biphasic developmental cycle during its growth in vertebrate monocytes/macrophages and invertebrate tick cells. Host- and vector-specific differences in the gene expression from many genes of E. chaffeensis are well documented. It is unclear how the organism regulates gene expression during its developmental cycle and for its adaptation to vertebrate and tick host cell environments. We previously mapped promoters of several E. chaffeensis genes which are recognized by its only two sigma factors: σ32 and σ70. In the current study, we investigated in assessing five predicted E. chaffeensis transcription regulators; EcxR, CtrA, MerR, HU and Tr1 for their possible roles in regulating the pathogen gene expression. Promoter segments of three genes each transcribed with the RNA polymerase containing σ70 (HU, P28-Omp14 and P28-Omp19) and σ32 (ClpB, DnaK and GroES/L) were evaluated by employing multiple independent molecular methods. We report that EcxR binds to all six promoters tested. Promoter-specific binding of EcxR to several gene promoters results in varying levels of gene expression enhancement. This is the first detailed molecular characterization of transcription regulators where we identified EcxR as a gene regulator having multiple promoter-specific interactions