Time-intensive Operations Research Articles

Microcolumn and coelution hydration of oil seal blood spot for efficient screening of newborn α-thalassemia via chip isoelectric focusing

BackgroundThe global prevalence of α-thalassemia necessitates effective newborn screening strategies due to its severe clinical consequences. Traditional methods such as liquid chromatography (LC), capillary electrophoresis (CE), and isoelectric focusing (IEF) face limitations, including low separation efficiency, poor sensitivity for detecting Hb Bart’s, and time-intensive operations, particularly with dried blood spots (DBS). These limitations hinder timely and accurate screening. This study addresses the need for a more efficient, sensitive, and rapid method for detecting Hb Bart’s in newborns. ResultsWe enhanced IEF separation and sensitivity by designing a microfluidic IEF (mIEF) system with shortened columns and employing a coelution sample loading technique using oil-sealed blood spots for rapid sample pretreatment. Our experiments demonstrated significant improvements: the total analysis time was reduced from 1110 minutes (IPG IEF) and 46 minutes (LC) per batch to 36 minutes per batch. For individual samples, the focusing time decreased from 6 minutes (previous mIEF) to 3 minutes, with the microcolumn length shortened by 50%, from 30 mm to 15 mm. The developed method showed excellent consistency with clinical Bart’s detection and PCR diagnosis, achieving 100% sensitivity and 98% specificity for α-thalassemia screening. Significance and NoveltyOur novel mIEF method provides an efficient, sensitive, and rapid tool for screening newborns for α-thalassemia. This advancement addresses the limitations of traditional techniques, improving early diagnosis and intervention strategies and ultimately enhancing health outcomes for at-risk newborns.

Kartograf: A Geometrically Accurate Atom Mapper for Hybrid-Topology Relative Free Energy Calculations.

Relative binding free energy (RBFE) calculations have emerged as a powerful tool that supports ligand optimization in drug discovery. Despite many successes, the use of RBFEs can often be limited by automation problems, in particular, the setup of such calculations. Atom mapping algorithms are an essential component in setting up automatic large-scale hybrid-topology RBFE calculation campaigns. Traditional algorithms typically employ a 2D subgraph isomorphism solver (SIS) in order to estimate the maximum common substructure. SIS-based approaches can be limited by time-intensive operations and issues with capturing geometry-linked chemical properties, potentially leading to suboptimal solutions. To overcome these limitations, we have developed Kartograf, a geometric-graph-based algorithm that uses primarily the 3D coordinates of atoms to find a mapping between two ligands. In free energy approaches, the ligand conformations are usually derived from docking or other previous modeling approaches, giving the coordinates a certain importance. By considering the spatial relationships between atoms related to the molecule coordinates, our algorithm bypasses the computationally complex subgraph matching of SIS-based approaches and reduces the problem to a much simpler bipartite graph matching problem. Moreover, Kartograf effectively circumvents typical mapping issues induced by molecule symmetry and stereoisomerism, making it a more robust approach for atom mapping from a geometric perspective. To validate our method, we calculated mappings with our novel approach using a diverse set of small molecules and used the mappings in relative hydration and binding free energy calculations. The comparison with two SIS-based algorithms showed that Kartograf offers a fast alternative approach. The code for Kartograf is freely available on GitHub (https://github.com/OpenFreeEnergy/kartograf). While developed for the OpenFE ecosystem, Kartograf can also be utilized as a standalone Python package.

Simple electrochemical sensing for mercury ions in dairy product using optimal Cu2+-based metal-organic frameworks as signal reporting

A convenient sensor is developed for electrochemical assay of Hg2+ in dairy product using the optimal Cu2+-based metal-organic frameworks (Cu-MOFs) as signal reporting. Benefiting from specific recognition between Hg2+ and thymine (T)-rich DNA strands, the interferences of milk matrices are effectively eliminated, thereby greatly improving the accuracy of test results. Moreover, the suitable Cu-MOFs offer an efficient carrier for probe design, and the contained Cu2+ ions could be directly detected to output electrochemical signal of Hg2+ presence without labor- or time-intensive operations. Compared with previous methods, this sensor substantially simplifies the process of electrochemical measurement and facilitates highly sensitive, selective and rapid analysis of Hg2+ with detection limit of 4.8 fM, offering a valuable means for monitoring dairy product contamination with Hg2+.

Design and implementation of real‐time wideband software‐defined radio applications with GPGPUs

SummaryWideband software‐defined radio (SDR) applications include data and time intensive operations such as wideband spectrum, signal detection, digital down conversion (DDC), and analog demodulation. Each of these processes need to be performed in order to produce the audio signal from the wideband signals. However, serial implementation of SDR applications do not provide necessary rate speed to obtain the sound and speech data in real time. In this work, we propose a real time SDR implementation using a heterogeneous architecture with CPUs and GPUs. To obtain the sound and speech data from the signals received and processed in SDR algorithms in real time, we also provide necessary optimizations. We test the proposed design using both single CPU core, multiple CPU cores, and GPUs. High performance is observed with our proposed algorithm in experimental tests. We also provide test results in a mobile setup where resources such as power and size are limited. For this purpose, we provide test results on NVIDIA Jetson GPUs and portable laptop CPUs. This work shows a proof of concept that the sound of a signal can be detected in the wideband spectrum and can be played back continuously in a real time with the help of the parallel programming suitable for low power consumption.

Convenient analytic recurrence algorithms for the Adomian polynomials

In this article we present four analytic recurrence algorithms for the multivariable Adomian polynomials. As special cases, we deduce the four simplified results for the one-variable Adomian polynomials. These algorithms are comprised of simple, orderly and analytic recurrence formulas, which do not require time-intensive operations such as expanding, regrouping, parametrization, and so on. They are straightforward to implement in any symbolic software, and are shown to be very efficient by our verification using MATHEMATICA 7.0. We emphasize that from the summation expressions, A n = ∑ k = 1 n U n k for the multivariable Adomian polynomials and A n = ∑ k = 1 n f ( k ) ( u 0 ) C n k for the one-variable Adomian polynomials, we obtain the recurrence formulas for the U n k and the C n k . These provide a theoretical basis for developing new algorithmic approaches such as for parallel computing. In particular, the recurrence process of one particular algorithm for the one-variable Adomian polynomials does not involve the differentiation operation, but significantly only the arithmetic operations of multiplication and addition are involved; precisely C n 1 = u n ( n ⩾ 1 ) and C n k = 1 n ∑ j = 0 n - k ( j + 1 ) u j + 1 C n - 1 - j k - 1 ( 2 ⩽ k ⩽ n ) . We also discuss several other algorithms previously reported in the literature, including the Adomian–Rach recurrence algorithm [1] and this author’s index recurrence algorithm [23,36].

Microcomputer solutions to Em/Ek/S queuing systems

This research resulted in the development of microcomputer software for performing computations for Em/Ek/S queuing systems. The investigation established the viability of using Gaussian elimination to solve the Em/EkS rate balance equations in a reasonable length of time on a microcomputer. The use of dynamic storage for only the nonzero elements of the equations obviated the need for the time-intensive operations of swapping matrix contents between RAM and disk storage. With this software, a practitioner who confronts a design problem involving a Em/Ek/S queuing system without ready access to the appropriate tables may use his personal microcomputer to obtain results quickly without the need for interpolation between table values.

Optical Implementations In Boltzmann Machines

Boltzmann machines can be used to obtain solutions to problems for which direct mathematical calculation of a solution is not possible or would take too long. The range of problems for which such a machine might be useful is very broad, and inversion of a linear equation is described as one example. A method is described that allows time-intensive operations on a computer to be replaced with a highly parallel optical system that can be incorporated in such a way as to let the computer take full advantage of the speed of the optics without sacrificing the precision possible in the computer. A tie is made between Boltzmann machines and neural networks, and it is shown how a Boltzmann machine may perform functions demonstrated by other neural network architectures.