Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has re...
In this paper, we study the single machine vector scheduling problem (SMVS) with general penalties, in which each job is characterized by a d-dimensional vector and can be accepted and processed on the machine or rejected. The objective is to minimiz...
We study a scheduling problem in which jobs with release times and due dates are to be processed on a single machine. With the primary objective to minimize the maximum job lateness, the problem is strongly NP-hard. We describe a general algorithmic...
We investigate the single-machine parallel-batch scheduling problem with nonidentical job sizes and rejection. In this problem, a set of jobs with different processing times and nonidentical sizes is given to be possibly processed on a parallel-batch...
In recent years, the diversity of cancer cells in tumor tissues as a result of intratumor heterogeneity has attracted attention. In particular, the development of single-cell analysis technology has made a significant contribution to the field; techn...
This paper considers the single-machine scheduling problem of total tardiness minimization. Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal s...
This work studies single-machine scheduling with general position-dependent deterioration, where job processing times are general non-decreasing functions dependent on their positions in a sequence. The goal is to find a job sequence such that makesp...
In non-synchronous machine sources (N-SMSs), power sources are connected to the grid through power electronic devices, which typically exhibit a voltage-controlled current source characteristic during faults. Due to the current-limiting feature of in...
In recent years, the need for generation mixes that consider the inertial constraints in unit commitment (UC) has increased because the inertia of these systems has decreased with the increased use of renewable energy. In these circumstances, single-...
The problem of the approximation of the coefficients of the objective function of a scheduling problem for a single machine is considered. It is necessary to minimize the total weighted completion times of jobs with unknown weight coefficients when a...
This paper presents the design and validation of a novel multi-mode transmission (MMT) for a hybrid electric vehicle (HEV) using a single electric machine (EM), which implies compact and low cost. The topology of the MMT planetary gearset is the same...
The authors of this article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of th...
Since the publication of the first scheduling paper in 1954, a huge number of works dealing with different types of single machine problems have appeared. They addressed many heuristics and enumerative procedures, complexity results or structural pro...
The rapid evolution of transcriptome sequencing technologies has driven significant breakthroughs across the life sciences. The advent of single-cell RNA-sequencing (scRNA-seq) has enabled gene expression profiling at single-cell resolution, whereas...
Single-particle tracking is a powerful technique to investigate the motion of molecules or particles. Here, we review the methods for analyzing the reconstructed trajectories, a fundamental step for deciphering the underlying mechanisms driving the m...
The performance improvement of an all-solid-state single-frequency continuous-wave (CW) laser with high output power is presented in this paper, which is implemented by employing a temperature control system based on machine learning to control the t...
Predicting compounds with single- and multi-target activity and exploring origins of compound specificity and promiscuity is of high interest for chemical biology and drug discovery. We present a large-scale analysis of compound promiscuity including...
In order to cut down influence on the uncertainty disturbances of a linear motion single axis robot machine, such as the external load force, the cogging force, the column friction force, the Stribeck force, and the parameters variations, the microme...
Demand for brushless alternatives to the series universal motors and induction motors in domestic applications and automotive applications is increasing. Among the available candidates, single-phase flux-switching permanent magnet (SP-FSPM) machines...
In shallow water, passive sonar usually has great difficulty in discriminating a surface acoustic source from an underwater one. To solve this problem, a supervised machine learning method using only one hydrophone is implemented in this paper. First...
We consider a single machine scheduling problem with uncertain durations of the given jobs. The objective function is minimizing the sum of the job completion times. We apply the stability approach to the considered uncertain scheduling problem using...
Individual cells have many unique properties that can be quantified to develop a holistic understanding of a population. This can include understanding population characteristics, identifying subpopulations, or elucidating outlier characteristics tha...
This study investigates a single-machine throughput maximization problem (TMP), in which each job is characterized by a processing time, ready date, due date, and weight, and must be completed within its time window to yield profit. The objective is...
Machine learning (ML) is transforming the analysis of biomolecular data, holding significant promise for improving the efficiency and accuracy of microscopy image analysis and for studying the dynamics of molecules in live cells. As data-driven appro...
Lanthanide-based single-molecule magnets are promising candidates for potential applications. Their magnetism is governed by ligand-field splittings, which may require up to 27 ligand-field parameters for accurate modeling. Determining these paramete...
An Estimation of Distribution Algorithm (EDA), which depends on explicitly sampling mechanisms based on probabilistic models with information extracted from the parental solutions to generate new solutions, has constituted one of the major research a...
Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorpor...
The absence of standardized evaluation methodologies for single-layer dimensional accuracy significantly hinders the broader implementation of direct ink writing (DIW) technology. Addressing the critical need for precision non-contact assessment in D...
A hybrid differential evolution (HDE) algorithm that minimizes the total earliness and tardiness time (ET), a just-in-time objective, is studied for a single-batch-processing machine (SBPM) scheduling problem with different processing times, release...
Single-vesicle molecular profiling of cancer-associated extracellular vesicles (EVs) is increasingly being recognized as a powerful tool for cancer detection and monitoring. Mask and target dual imaging is a facile method to quantify the fraction of...
Intelligent gas sensors (IGSs) have garnered significant attention owing to their highly sensitive, selective, and reliable gas detection in industrial safety, environmental monitoring, food quality assessment, healthcare diagnostics, and smart Inter...
Protein kinases are major drug targets. Most kinase inhibitors are directed against the adenosine triphosphate (ATP) cofactor binding site, which is largely conserved across the human kinome. Hence, such kinase inhibitors are often thought to be prom...
Driver drowsiness is an important contributor to road accidents, but conventional multichannel electroencephalography (EEG) systems are difficult to deploy in everyday driving contexts. This study investigates whether band-power features obtained fro...
Feed-forward neural networks (NNs) are widely used for the machine learning of properties of materials and molecules from descriptors of their composition and structure (materials informatics) as well as in other physics and chemistry applications. O...
High-throughput single-cell RNA sequencing (scRNA-seq) has substantially advanced plant transcriptional landscapes. However, decoding cell-type-specific transcriptional regulation in non-model crops like tomato (Solanum lycopersicum) remains challeng...
As an important part of industrialized society, manufacturing consumes a large amount of raw materials and energy, which motivates decision-makers to tackle this problem in different manners. Process planning is an important optimization method to re...
Order acceptance and scheduling (OAS) problems are realistic for enterprises. They have to select the appropriate orders according to their capacity limitations and profit consideration, and then complete these orders by their due dates or no later t...
We study a single-machine scheduling problem to minimize the total completion time of the given set of jobs, which have to be processed without job preemptions. The lower and upper bounds on the job duration is the only information that is available...
This paper proposes a novel disruptive innovation-like algorithm (DILA) for the problem of scheduling a single machine with sequence-dependent family setup times to minimize the total tardiness. The proposed algorithm is derived from Christensen&rsqu...
Background and Aims: Hypothermic oxygenated machine perfusion (HOPE) improves outcomes in orthotopic liver transplantation (OLT), but reliance on University of Wisconsin machine perfusion solution (UW-MPS) increases costs and logistical burden. Histi...
In this paper, we investigate a single machine scheduling problem with a proportional job deterioration. Under release times (dates) of jobs, the objective is to minimize the total weighted completion time. For the general condition, some dominance p...
Background: Neuroinflammation is recognized as a key contributor to Parkinson’s disease (PD), but the relationships between inflammatory signaling, immune-state alterations, and cell-type-specific transcriptional programs remain unclear. Method...
The aim of this research is to develop and compare single, hybrid, and stacking ensemble machine learning models under spatial and temporal climate variations in the Nile Delta regarding the estimation of the blue and green water footprint (BWFP and...
Influenza A virus (IAV) infection triggers excessive activation of PANoptosis—a coordinated form of programmed cell death integrating pyroptosis, apoptosis, and necroptosis—which contributes to severe immunopathology and acute lung injury...
This paper considers the single-machine problem with job release times and flexible preventive maintenance activities to minimize total weighted tardiness, a complicated scheduling problem for which many algorithms have been proposed in the literatur...
This paper discusses the use of a stochastic metaheuristic population-based optimization algorithm known as the sine cosine algorithm (SCA) to design the parameters of a power system stabilizer (PSS) for damping electromechanical oscillations in a si...
To improve energy efficiency and maintain the stability of the power grid, time-of-use (TOU) electricity tariffs have been widely used around the world, which bring both opportunities and challenges to the energy-efficient scheduling problems. Single...
Brain metastasis (BM) occurs commonly in patients with lung adenocarcinomas. Limited evidence indicates safety and efficacy of immunotherapy for this metastatic tumor, though immune checkpoint blockade has become the front-line treatment for primary...
We study single-machine group green scheduling considering group setup time deterioration effects and job-processing time learning effects, where the setup time of a group is a general deterioration function on its starting setup time and the process...
Green manufacturing, which takes environmental effect and production benefit into consideration, has attracted increasing concern with the target of carbon peaking and carbon neutrality proposed. As a critical process in the manufacturing system, sho...
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