Biomolecular condensates participate in diverse cellular processes, ranging from gene regulation to stress survival. Bottom-up engineering of synthetic advances our understanding the organizing principle condensates. It also enables synthesis artificial systems with novel functions. However, building a predictable organization and function remains challenging. Here, we use DNA as block create that are assembled through phase separation. The programmability intermolecular interactions between...

Fisher linear discriminant (FLD) has recently emerged as a more efficient approach for extracting features many pattern classification problems compared to traditional principal component analysis. However, the constraint on total number of available from FLD seriously limited its application large class problems. In order overcome this disadvantage, recursive procedure calculating is suggested in paper. The new algorithm incorporates same fundamental idea behind seeking projection that best...

A geometrical interpretation of the multilayer perceptron (MLP) is suggested in this paper. Some general guidelines for selecting architecture MLP, i.e., number hidden neurons and layers, are proposed based upon controversial issue whether four-layered MLP superior to three-layered also carefully examined.

The rapid advances of evolutionary methods for multi-objective (MO) optimization poses the difficulty keeping track developments in this field as well selecting an appropriate approach that best suits problem in-hand. This paper aims to analyze strength and weakness different proposed literature. For purpose, ten existing well-known MO approaches have been experimented compared extensively on two benchmark problems with difficulties characteristics. Besides considering usual important...

This paper presents an interactive graphical user interface (GUI) based multiobjective evolutionary algorithm (MOEA) toolbox for effective computer-aided (MO) optimization. Without the need of aggregating multiple criteria into a compromise function, it incorporates concept Pareto's optimality to evolve family nondominated solutions distributing along tradeoffs uniformly. The is also designed with many useful features such as goal and priority settings provide better support decision-making...

This paper presents an evolutionary algorithm with a new goal-sequence domination scheme for better decision support in multi-objective optimization. The approach allows the inclusion of advanced hard/soft priority and constraint information on each objective component, is capable incorporating multiple specifications overlapping or non-overlapping functions via logical 'OR' 'AND' connectives to drive search towards regions trade-off. In addition, we propose dynamic sharing that simple...

Phase separation of biomolecules plays key roles in physiological compartmentalization as well pathological aggregation. A deeper understanding biomolecular phase requires dissection a relation between intermolecular interactions and resulting behaviors. DNA nanostars, multivalent assemblies which sticky ends define attractive interactions, represent an ideal system to probe this fundamental governing processes. Here, we use nanostars systematically study how structural flexibility exhibited...

Developing a classification system that can predict the onset of neurodegenerative diseases or gait-related disorders in elders is vital for preventing incidents like falls. Early detection allows reduction symptoms and treatment cost elderly. In this study, step duration data from five healthy adolescents with age range 23 – 29 years old elderly individuals 71 77 were sourced PhysioNet. To ensure proper training deep learning models, synthetic was generated original dataset using noise...

Gait disorders are a significant concern for older adults, particularly those with neurodegenerative diseases such as Parkinson’s disease, Huntington’s and Amyotrophic Lateral Sclerosis. Accurately classifying these conditions using gait data remains complex challenge, especially in populations, due to age-related changes patterns, comorbidities, increased variability mobility, which can obscure disease-specific characteristics. This study explicitly classifies adults by analysing...

Genetic programming (GP) has emerged as a promising approach to deal with the classification task in data mining. This paper extends tree representation of GP evolve multiple comprehensible IF-THEN rules. We introduce concept mapping technique for fitness evaluation individuals. A covering algorithm that employs an artificial immune system-like memory vector is utilized produce rules well remove redundant The proposed classifier validated on nine benchmark sets, and simulation results...

In vehicle routing problems with time window constraints (VRPTW), a set of vehicles limited capacity, are to be routed from central depot geographically dispersed customers known demands and predefined windows. To solve the problem, optimized assignment each customer is needed as achieve minimal total cost without violating capacity constraints. Combinatorial optimization this kind NP-hard best solved near optimum by heuristics. The authors describe their research on rare class genetic...

This paper considers the problem of modeling an unknown system by a rule-based model constructed from measured data. In particular, we address two fundamental issues associated with modeling: rule-base construction and manipulation. A two-step approach consisting principal refining algorithm has been suggested to extract rules available data set. Starting notion product space clustering, have developed three algorithms in which fuzzy concepts competitive learning are utilized. particular...

This paper presents a kind of cooperative coevolutionary algorithm (CCEA) for multi-objective optimization (MOO). In this algorithm, solutions evolve in the form subpopulations. An archive stores non-dominated and helps to evaluate individuals The mechanism niching is applied maintain diversity archive. Meanwhile, an extending operator designed mine information on solution distribution from guide search regions that are not explored enough. Extensive simulations performed different benchmark...

This paper presents a distributed coevolutionary classifier (DCC) for extracting comprehensible rules in data mining. It allows different species to be evolved cooperatively and simultaneously, while the computational workload is shared among multiple computers over Internet. Through intercommunications of rule sets manner, concurrent processing speed classifiers are enhanced. The advantage performance proposed DCC validated upon various datasets obtained from UCI machine learning...

This paper presents the optimal control of drug scheduling in cancer chemotherapy using a distributed evolutionary computing software. Unlike conventional methods that often require gradient information or hybridization different approaches scheduling, proposed optimization methodology is simple and capable automatically finding near-optimal solutions for complex problems. It shown number variable pairs representation can be easily implemented via software, since computational workload...

This paper considers a transportation problem for moving empty or laden containers logistic company. A model this truck and trailer vehicle routing (TTVRP) is first constructed in the paper. The solution to TTVRP consists of finding complete schedule serving jobs with minimum distance number trucks, subject constraints such as time windows availability multimodal combinatorial optimization problem, hybrid multiobjective evolutionary algorithm (HMOEA) applied find Pareto optimal solutions...

Evolutionary techniques have become one of the most powerful tools for solving multiobjective optimization (MOO) problems. However computational cost involved in terms time and hardware often surprisingly burdensome as size complexity problem increases. We propose a distributed cooperative coevolutionary algorithm (DCCEA), which evolves multiple solutions form subpopulations exploits inherent parallelism by sharing workload among computers over network. Through its features such archiving,...

This paper presents a new approach of task-oriented developmental learning for humanoid robots. It is capable setting up multiple tasks representation automatically using real-time experiences, thereby enabling robot to handle various concurrently without the need predefining tasks. In approach, an evolvable partitioned tree structure used task knowledgebase that into different domains. The search/update knowledge focused on particular branch, considering whole often large and time consuming...

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system livestock. In this study, we propose deep learning framework pixel-wise bovine iris with minimized use annotation labels utilizing BovineAAEyes80 public dataset. The proposed image encompasses data collection, preparation, augmentation selection, training 15 neural network (DNN) models varying encoder backbones and decoder DNNs, evaluation using multiple metrics graphical...

The analysis of AR is widely used to detect loss acrosome in sperm, but the subjective decisions experts affect accuracy examination. Therefore, we develop an ARCS for objectivity and consistency using convolutional neural networks (CNNs) trained with various magnification images. Our models were on 215 microscopic images at 400× 438 1000× ResNet 50 Inception–ResNet v2 architectures. These distinctly recognized micro-changes PM sperms. Moreover, v2-based achieved a mean average precision...

The constraint on the total number of features available from Fisher linear discriminant (FLD) has seriously limited its application to a large class problems. In order overcome this disadvantage FLD, recursive procedure for calculating is suggested in paper. Extensive experiments comparing new algorithm with traditional PCA and FLD approaches have been carried out face recognition problem, which resulting improvement performance by feature extraction scheme significant.

Hematopoietic stem cells (HSCs) from the human placenta and umbilical cord blood (UCB) provide a rich source of highly proliferative for many clinical uses with advantages over traditional sources like bone marrow periphery blood. However, key current constraint this HSCs is inadequate number that can be harvested in single collection using approaches, which render large collections unusable on their own, even pediatric patients. This paper will present development device to enable more...