Simple Approach Research Articles

HEALTH INFORMATICS: AI in health care: a tool for physician leaders

Artificial intelligence (AI) in health care is rapidly expanding, with the daily emergence of new initiatives, topics, and critical issues, making it challenging for physician leaders to organize and distill this complex topic. We offer a simple approach that involves classifying topics by three levels of scale: the individual, the organization, and the system or sector. Despite the widespread adoption of AI applications across all aspects of our daily lives, its implementation in health care remains limited. There is a need to engage, in all stages of development, key stakeholders, specifically governments, technology companies, health care providers, patients, and civil society. Cultural, social, and/or regional disparities can impact the integration of AI in health care, reflecting varied beliefs, attitudes, and practices. Our simplified approach to structuring and organizing this complex subject can serve as a valuable tool for physician leaders in conducting more focused discussions with stakeholders and decision-makers.

Extended Enrichment for Ultrasensitive Detection of Low-Frequency Mutations by Long Blocker Displacement Amplification.

Detecting low-frequency DNA mutations hotspots cluster is critical for cancer diagnosis but remains challenging. Quantitative PCR (qPCR) is constrained by sensitivity, and allele-specific PCR is restricted by throughput. Here we develop a long blocker displacement amplification (LBDA) coupled with qPCR for ultrasensitive and multiplexed variants detection. By designing long blocker oligos to perfectly match wildtype sequences while mispairing with mutants, long blockers enable 14-44 nt enrichment regions which is 2-fold longer than normal BDA in the experiments. For wild template with a specific nucleotide, LBDA can detect different mutation types down to 0.5 % variant allele frequency (VAF) in one reaction, with median enrichment fold of 1,000 on 21 mutant DNA templates compared to the wild type. We applied LBDA-qPCR to detect KRAS and NRAS mutation hotspots, utilizing a single plex assay capable of covering 81 mutations and tested in synthetic templates and colorectal cancer tissue samples. Moreover, the mutation types were verified through Sanger sequencing, demonstrating concordance with results obtained from next generation sequencing. Overall, LBDA-qPCR provides a simple yet ultrasensitive approach for multiplexed detection of low VAF mutations hotspots, presenting a powerful tool for cancer diagnosis and monitoring.

13C Metabolic Flux Analysis in Chondrocytes Reveals a Novel Switch in Metabolic Phenotype.

Chondrocytes are typically known for their anaerobic metabolism both in vivo and under culture conditions in vitro. However, chondrocytes have been shown to display greater biosynthetic activity when subjected to conditions that elicit aerobic metabolism. We have previously shown that tissue formation by chondrocytes can be upregulated by controlling nutrient availability and that this response arises from changes in glucose metabolism. The aim of the present study was to further characterize these changes through 13C-metabolic flux analysis (13C-MFA), as well as to determine the most optimal response. Primary bovine chondrocytes were grown in scaffold-free high-density tissue culture. [U-13C] glucose labeling experiments were combined with a tissue-specific metabolic network model to carry out 13C-MFA under varying levels of nutrient availability. 13C-MFA results demonstrated that when subjected to increasing nutrient availability, chondrocytes switch from a predominately anaerobic to a mixed aerobic-anaerobic phenotype. This metabolic switch was attributed to the saturation of the lactate fermentation pathway and metabolite overflow toward the tricarboxylic acid cycle. This effect appears to be similar to, but the inverse of, the Crabtree effect ("inverse Crabtree effect"). The relationships between metabolic flux and nutrient availability were then utilized to identify culture conditions that promote enhanced tissue formation. This novel metabolic effect presents a simple but effective approach for enhancing the biosynthetic response of chondrocytes-a key requirement to develop functional engineered cartilaginous tissue for joint resurfacing.

A Study on How Conformation Entropy of Attached Macromolecules Drives Polymeric Collapse and Protein Folding

AbstractThe conformation of macromolecules attached to a surface is influenced by both their excluded volume and steric forces. Here, self‐avoiding random walk simulations are used to evaluate the occurrence of various conformations as a function of the number of monomeric units to estimate the effect of conformational entropy of a tethered chain. Then, a more realistic scenario is assessed, which can more accurately reproduce the shape of a tethered macromolecule. The simulations presented here confirm that it is more likely for a polymer to undergo a collapse conformation rather than a stretched one, as a collapse conformation can be realized in more different ways. Also, they confirm the “mushroom” shape of polymers close to a surface. From this simple approach, the conformation entropy of a model 100‐unit polymer close to a surface is estimated to contribute with over 129 toward its collapse. This conformation entropy is higher than that of typical hydrogen bonds and even barriers that keep proteins folded. As such, entropic collapse of macromolecules plays an important role in realizing the mushroom shape of attached polymers and can be the driving force in protein folding, while the polypeptide chain emerges from the ribosome.

Universal Design and Efficient Synthesis for High Ambipolar Mobility Emissive Conjugated Polymers

High ambipolar mobility emissive conjugated polymers (HAME‐CPs) are perfect candidates for organic optoelectronic devices, such as polymer light emitting transistors. However, due to intrinsic trade‐off relationship between high ambipolar mobility and strong solid‐state luminescence, the development of HAME‐CPs suffers from high structural and synthetic complexity. Herein, a universal design principle and simple synthetic approach for HAME‐CPs are developed. A series of simple non‐fused polymers composed of charge transfer units, π bridges and emissive units are synthesized via a two‐step microwave assisted C‐H arylation and direct arylation polymerization protocol with high total yields up to 61%. The synthetic protocol is verified valid among 7 monomers and 8 polymers. Most importantly, all 8 conjugated polymers have strong solid‐state emission with high photoluminescence quantum yields up to 24%. Furthermore, 4 polymers exhibit high ambipolar field effect mobility up to 10‐2 cm2 V‐1 s‐1, and can be used in multifunctional optoelectronic devices. This work opens a new avenue for developing HAME‐CPs by efficient synthesis and rational design .

Rapid calculation of the efficiency of self-terminating four-level Q-switched lasers.

We have developed a simple approach to deriving the efficiency of Q-switched four-level lasers, valid even for arbitrarily long lower laser level lifetimes. By eliminating time dependence from the calculation, numerical solutions can be obtained very rapidly. Its threshold and limiting slope efficiency values provide useful estimates for free-running pulsed four-level lasers as well as Q-switched.

Fixing Inventory Inaccuracies at Scale

Problem definition: Inaccurate records of inventory occur frequently and, by some measures, cost retailers approximately 4% in annual sales. Detecting inventory inaccuracies manually is cost-prohibitive, and existing algorithmic solutions rely almost exclusively on learning from longitudinal data, which is insufficient in the dynamic environment induced by modern retail operations. Instead, we propose a solution based on cross-sectional data over stores and stock-keeping units (SKUs), viewing inventory inaccuracies as a problem of identifying anomalies in a (low-rank) Poisson matrix. State-of-the-art approaches to anomaly detection in low-rank matrices apparently fall short. Specifically, from a theoretical perspective, recovery guarantees for these approaches require that nonanomalous entries be observed with vanishingly small noise (which is not the case in our problem and, indeed, in many applications). Methodology/results: So motivated, we propose a conceptually simple entrywise approach to anomaly detection in low-rank Poisson matrices. Our approach accommodates a general class of probabilistic anomaly models. We show that the cost incurred by our algorithm approaches that of an optimal algorithm at a min-max optimal rate. Using synthetic data and real data from a consumer goods retailer, we show that our approach provides up to a 10× cost reduction over incumbent approaches to anomaly detection. Along the way, we build on recent work that seeks entrywise error guarantees for matrix completion, establishing such guarantees for subexponential matrices, a result of independent interest. Managerial implications: By utilizing cross-sectional data at scale, our novel approach provides a practical solution to the issue of inventory inaccuracies in retail operations. Our method is cost-effective and can help managers detect inventory inaccuracies quickly, leading to increased sales and improved customer satisfaction. In addition, the entrywise error guarantees that we establish are of interest to academics working on matrix-completion problems. History: This paper was selected for Fast Track in M&SOM from the 2022 MSOM Supply Chain Management SIG Conference. Funding: Financial support from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation [Grant CMMI 1727239] is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0146 .

Power control in LTE based on heuristic game theory for interference management

In the conventional LTE homogeneous network, sufficient transmit power of user equipment (UE) is determined by open-loop power control (OL-PC) and closed-loop power control (CL-PC) schemes. However, in a Het-Net environment, setting the UE’s transmit power requires delicate responsiveness to handle the severe and complicated uplink interference. In this paper, an interference-aware uplink power control mechanism based on Heuristic game theory approach is proposed for devices coexisting in a heterogeneous wireless network. Various wireless constraints like channel response, path loss, fading, shadowing, interference and metrics like SNR, SINR, throughput and bit rates are considered. Uplink power is controlled by suitably selecting the penalization factor (β) based on a simple Heuristic game theory approach considering the possible wireless constraints of each user depending on its location in the cell under consideration. The algorithm is framed in such a way to reduce inter-cell interference, limit transmit power, enhance bit rates and throughput of users. A significant improvement of 5.2% in the user coverage/distribution is achieved as a result of interference management compared to conventional power control scheme and power control with convex pricing.

A simple chemical equilibrium algorithm applied for single and multiple reaction systems

AbstractThermodynamics is a branch of physics of high importance for engineering applications but is usually considered by most students as a rather obscure field, full of abstract concepts. Therefore, simple algorithms, which can exemplify the use of thermodynamic principles for practical situations, should be viewed as valuable teaching tools with large applications in engineering undergraduate courses. This point served as motivation for the present work, which proposes an alternative and simple computational approach for solving chemical equilibrium problems via successive reaction quotient calculations, both for single and multireactional systems. The code was written using MATLAB software; its fundamental theory was explained through a step‐by‐step approach and applied to both Shift and Boudouard reactions. Comparisons with ASPEN HYSYS and HSC Chemistry simulations corroborate its versatility and thermodynamic consistency. The full script is available in its entirety at the as supporting information together with the necessary text (.txt) files. Also, a user guide was provided to help students to replicate the results presented in the article.

A simple and practical approach to improving the cost effectiveness of surgical inventory management

ABSTRACT Operating room inventories typically involve hundreds of surgical items. Managers require very high service levels since the cost of shortages can be excessive up to and including cancelling surgery. From our experience, many inventory managers rely on manual approaches and intuition to set inventory control parameters. Although there are classical theoretical methods available for deriving “optimal” inventory policies, these classical methods rely on assumptions that do not accurately represent typical operating room inventories. Using 5 years of data from a large Canadian hospital, we use simulation and a simple search heuristic to find the optimal (s, S) ordering policy and show that 1) current hospital methods dramatically underperform with respect to service level and 2) there are significant savings to be realised over the best available classical theoretical models. An example case testing potential lead time changes is discussed.

Improving regulatory T cell production through mechanosensing.

Induced Tregs (iTregs) have great promise in adoptive immunotherapy for treatment of autoimmune diseases. This report investigates the impacts of substrate stiffness on human Treg induction, providing a powerful yet simple approach to improving production of these cells. Conventional CD4+ human T cells were activated on materials of different elastic modulus and cultured under suppressive conditions. Enhanced Treg induction was observed on softer materials as early as 3 days following activation and persisted for multiple weeks. Substrate stiffness also affected epigenetic modification of Treg specific genes and Treg suppressive capacity. Tregs induced on substrates of an optimal stiffness balance quantity and suppressive quality.

Oxygen Vacancy and Heterostructure Modulation of Co2P/Fe2P Electrocatalysts for Improving Total Water Splitting.

Designing a stable and highly active catalyst for hydrogen evolution and oxygen evolution reactions (HER/OER) is essential for the industrialization of hydrogen energy but remains a major challenge. This work reports a simple approach to fabricating coupled Co2P/Fe2P nanorod array catalyst for overall water decomposition, demonstrating the source of excellent activity in the catalytic process. Under alkaline conditions, Co2P/Fe2P heterostructures exhibit an overpotential of 96 and 220 mV for HER and OER, respectively, at 10 mA cm-2. For total water splitting, a low voltage of 1.56 V is required to provide a current density of 10 mA cm-2. And the catalyst exhibits long-term durability for 30 h at a high current density of 250 mA cm-2. The analysis of the results revealed that the presence of interfacial oxygen vacancies and the strong interaction between Co2P/Fe2P provided the catalyst with more electrochemically active sites and a faster charge transfer capability, which improved the hydrolysis dissociation process. Electrochemically active metal (oxygen) hydroxide phases were produced after OER stability testing. The results of this study prove its great potential in practical industrial electrolysis and provide a reasonable and feasible strategy for the design of nonprecious metal phosphide electrocatalysts.

Upper bounds for Heilbronn's triangle problem in higher dimensions

AbstractWe develop a new simple approach to prove upper bounds for generalizations of the Heilbronn's triangle problem in higher dimensions. Among other things, we show the following: for fixed , any subset of of size contains points that span a simplex of volume at most , points whose convex hull has volume at most , points that span a ‐dimensional simplex of volume at most .

Direct Synthesis of CuP2 and Cu3P and Their Performance as Electrocatalysts for Hydrogen Evolution, Oxygen Evolution, and Oxygen Reduction Reactions

Copper phosphides are promising materials for energy conversion applications because of their unique electronic structure and controllable composition. Two stoichiometric copper phosphides, CuP2 and Cu3P, were prepared by direct wet-chemical synthesis using red phosphorus. They were characterized by powder X-ray diffraction, scanning and transmission electron microscopy, and X-ray photoelectron spectroscopy. The precursor selection, reaction temperature, time and solvent composition were also studied. CuP2 is the thermodynamically more stable product, but Cu3P is more commonly obtained. This work demonstrated that higher temperature helps in CuP2 formation. More importantly, using more trioctylphosphine oxide helps control the morphology leading to crystal growth along the crystallographic a-axis. CuP2 and Cu3P were tested for hydrogen evolution, oxygen evolution, and oxygen reduction reactions. CuP2 works better for HER in acidic conditions and OER in general, and Cu3P showed better activity than CuP2 for HER and ORR in an alkaline medium. This study has led to a simple approach to the synthesis of CuP2 nanowires.

Efficient Extraction and Analysis of Nanoplastics by Ionic Liquid-Assisted Cloud-Point Extraction Coupled with Electromagnetic Heating Pyrolysis Mass Spectrometry.

Nanoplastics have attracted much attention due to their potential hazards. However, analysis of nanoplastics remains challenging. In this study, ionic liquid-assisted cloud-point extraction (IL-assisted CPE) was developed to enrich nanoplastics in the aqueous environment and further coupled with electromagnetic heating pyrolysis mass spectrometry. The use of trace ILs improves the extraction efficiency of CPE for nanoplastics. The effects of ILs (types, contents), nanoplastic properties (type, size), and environmental factors (aging time, humic acid content) were systematically investigated to evaluate the applicability. The limits of detection of poly(methyl methacrylate) (PMMA) and polystyrene (PS) were determined to be 1.78 and 2.67 μg/L, respectively. Real environmental samples including lake water, rainwater, and influent and effluent from wastewater treatment plant were analyzed with good accuracy (79.58-116.87%) and satisfactory precision (RSD ≤ 11.99%). A possible mechanism for ILs being absorbed into the ordered surfactant micellar and generating larger micelles to synergically enclose hydrophobic nanoplastics was proposed. This work provides a simple and efficient approach to the extraction and analysis of nanoplastics in aqueous environments.

A Diagnostic Curve for Online Fault Detection in AC Drives

The AC drive is an important component and the most common element of any manufacturing process. A particularly serious task is the proper assessment of the AC drive’s technical condition, as its failure can cause problems for entire units and complexes of industrial enterprises. At present, there are several approaches either to determine electric drives’ condition or to find certain defects. Frequently, these methods require the installation of additional equipment that exceeds the price of the electric drive by several times. In this work, a simple approach is proposed. It includes the use of a diagnostic curve to assess the condition. This diagnostic curve is produced from the measurement results of the current sensors on the drive. Based on the Park vector modification, this is a simple and affordable way to obtain real-time information. The obtained curve can be used for the following purposes: directly for condition assessment by visual monitoring, as a sign for diagnostic systems built on artificial intelligence methods, for dynamic tuning of the drive control system. The article gives the algorithm for obtaining the diagnostic curve, showing its efficiency for model and field experiments. In model experiments, the faults in the rotor and stator of the drive were simulated; in field experiments, the state was analyzed by changing the load on the motor.

Handling syntactic difference in Chinese-Vietnamese neural machine translation

As the typical distant language pair, Chinese and Vietnamese vary widely in syntactic structure, which significantly influences the performance of Chinese-Vietnamese machine translation. To address this problem, we present a simple approach with a pre-reordering model for closing syntactic gaps of the Chinese-Vietnamese language pair. Specifically, we first propose an algorithm for recognizing the modifier inverse, one of the most representative syntactic different in Chinese-Vietnamese language pair. Then we pre-train a pre-reordering model based on the former recognition algorithm and incorporate it into the attention-based translation framework for syntactic different reordering. We conduct empirical studies on Chinese-Vietnamese neural machine translation task, the results show that our approach achieves average improvement of 2.75 BLEU points in translation quality over the baseline model. In addition, the translation fluency can be significantly improved by over 2.44 RIBES points.

Rapid natural hazard extent estimation from twitter data: investigation for hurricane impact areas

AbstractNatural hazards have occurred more frequently in the past years and pose a severe risk to human life. Their extents and, thereby, the most heavily affected areas must be estimated at the earliest to limit damages or initiate rescue services. For such estimations, a widely available data source, which is comparatively responsive to short-time changes, is needed and provided by volunteered geographic information (VGI) data. Tropical cyclones are natural hazard events that can cause enormous spatially extended damage. In this study, we introduce Machine Learning approaches such as Extremely Randomized Tree (ET) and Geographically Weighted Regression for estimating hurricane-impacted regions from VGI data. In addition to the general approximate track extent estimation, we also evaluate the possibilities of temporal estimation of track development from VGI data. Different scenarios are evaluated, and we find that the results mainly depend on the choice of the geographical splits for training and test data for the underlying regression task. Suitable splits lead to $$R^2$$ R 2 of 99% in the best cases with the ET model. The estimation results are satisfying when considering the temporal aspect and represent a use-case scenario. Such a combination of Machine Learning approaches and VGI is a simple and fast approach for early natural hazard estimation.

Transfer of III-nitride epitaxial layers onto pre-patterned silicon substrates for the simple fabrication of free-standing MEMS

In recent years, the remarkable properties and potential applications of III-nitride (III-N) semiconductors have sparked a significant interest in the field of microelectromechanical systems (MEMS). Traditionally, III-N MEMS are fabricated through a process involving the epitaxial growth of III-N epilayers on a silicon substrate followed by etching the handle wafer to generate free-standing structures. In this study, we explore the potential of a relatively simple approach based on the two-dimensional (2D) material-based liftoff and transfer to fabricate III-N mechanical resonators. The methodology involves van der Waals epitaxy of III-N layers on 2D hexagonal-boron nitride (h-BN), which leverages the weak van der Waals adhesion between h-BN layers to lift off and transfer these layers from their original growth substrate to an alternative host substrate. The employed method is demonstrated by fabricating 600 nm thick GaN/AlGaN and 2.5 μm thick h-BN micro-resonators onto pre-patterned cavities etched in silicon substrates. These devices are characterized using laser Doppler vibrometry, enabling the observation of well-defined modes of vibration and resonant frequencies. Furthermore, finite element method simulations are performed to gain insights into the experimental observations and the mechanical properties of the transferred layers. This approach could be extended to transfer high-quality III-N MEMS devices onto various host substrates, including flexible substrates, and could be used to assess the mechanical properties of emerging III-N semiconductor materials.

Low-Cost Nonfused-Ring Electron Acceptors Enabled by Noncovalent Conformational Locks.

ConspectusSince the first bilayer-structured organic solar cells (OSCs) in 1986, fullerenes and their derivatives have dominated the landscape for two decades due to their unique properties. In recent years, the breakthrough in nonfullerene acceptors (NFAs) was mainly attributed to the development of fused-ring electron acceptors (FREAs), whose photovoltaic performance surpassed that of fullerene derivatives. Through the unremitting efforts of the whole community, the power conversion efficiencies (PCEs) have surpassed 19% in FREA-based OSCs. However, FREAs generally suffered from complex synthetic approaches and high product costs, which hindered large-scale production. Therefore, many researchers are seeking a new type of NFA to achieve cost-effective, highly efficient OSCs.In collaboration with Marks and Facchetti in 2012, Huang et al. (Huang, H. J. Am. Chem. Soc. 2012, 134, 10966-10973, 10.1021/ja303401s) proposed the concept of "noncovalent conformational locks" (NoCLs). In the following years, our group has been focusing on the theoretical and experimental exploration of NoCLs, revealing their fundamental nature, formulating a simple descriptor for quantifying their strength, and employing this approach to achieve high-performance organic/polymeric semiconductors for optoelectronics, such as OSCs, thin-film transistors, room-temperature phosphorescence, and photodetectors. The NoCLs strategy has been proven to be a simple and effective approach for enhancing molecular rigidity and planarity, thus improving the charge transport mobilities of organic/polymeric semiconductors, attributed to reduced reorganization energy and suppressed nonradiative decay.In 2018, Chen et al. (Li, S. Adv. Mater. 2018, 30, 1705208, 10.1002/adma.201705208) reported the first example of nonfused-ring electron acceptors (NFREAs) with intramolecular noncovalent F···H interactions. The NoCLs strategy is essential in NFREAs, as it simplifies the conjugated structures while maintaining high coplanarity comparable to that of FREAs. Due to their simple structures and concise synthesis routes, NFREAs show great potential for achieving cost-effective and highly efficient OSCs. In this Account, we provide an overview of our efforts in developing NFREAs with the NoCLs strategy. We begin with a discussion on the distinct features of NFREAs compared with FREAs, and the structural simplification from FREAs to NFREAs to completely NFREAs. Next, we examine several selected typical examples of NFREAs with remarkable photovoltaic performance, aiming to provide an in-depth exploration of the molecular design principle and structure-property-performance relationships. Then, we discuss how to achieve a balance among efficiency, stability, and cost through a two-in-one strategy of polymerized NFREAs (PNFREAs). Finally, we offer our views on the current challenges and future prospects of NFREAs. We hope this Account will trigger intensive research interest in this field, thus propelling OSCs into a new stage.