Mixed Set Research Articles

Circular mixed sets

In this article, we introduce the new mathematical concept of circular mixed sets of words over an arbitrary finite alphabet. These circular mixed sets may not be codes in the classical sense and hence allow a higher amount of information to be encoded. After describing their basic properties, we generalize a recent graph theoretical approach for circularity and apply it to distinguish codes from sets (i.e. non-codes). Moreover, several methods are given to construct circular mixed sets. Finally, this approach allows us to propose a new evolution model of the present genetic code that could have evolved from a dinucleotide world to a trinucleotide world via circular mixed sets of dinucleotides and trinucleotides.

The PC Algorithm and the Inference to Constitution

Alexander Gebharter (2017) has proposed to use one of the best known Bayesian network (BN) causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this paper is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in the widespread non-compliance of mechanistic systems with PC’s assumptions. This casts severe doubts on the attempt to implicitly define constitution as a form of deterministic direct causation complying with PC’s assumptions.

Hydrodynamics and Transport Mechanism of Microfluidic Mixing in Precipitation of Nanodrugs: A Review

AbstractPoor aqueous solubility drugs are a concern of pharmaceutical industries due to low dissolution rates and low bioavailability. Various approaches and techniques address these issues by customizing drug micro–nanonization, as investigated by many researchers. Establishing a compelling synthesis of tailored nanoparticles with highly variable qualities intended for therapeutic applications needs the flexibility to vary particle size, content, crystallinity, and shape. Such an approach necessitates getting to the desired yield and developing a synthetic process that is durable, reproducible, and scalable. However, precipitation techniques to produce nanoparticles are more convenient than other approaches. Liquid antisolvent precipitation is one of the robust crystal manipulation approaches extensively used for producing nanoparticles, where mixing sets the basis to create supersaturation followed by corresponding quality precipitation. Various process intensification equipments are in use for adequate mixing‐based precipitation. Nowadays, microfluidic precipitation system is gaining interest in the production of nanodrugs. Further, the use of ultrasound in a microfluidic system improves the mixing quality by cavitation phenomena. This review focuses on the transport phenomena and hydrodynamics involved in mixing to enhance the mass transfer during antisolvent precipitation of synthesized nanodrugs in the microfluidic system.

Principal component analysis in pig breeds identification

Maintaining the purity of pig breeds is an essential task for their economic value. The traditional breed identification methods through coat colour are prone to error due to huge intra-breed variation. This paper uses principal component Analysis (PCA) to classify the pig breeds using their images. Individual images of five different pure breeds were captured from organized farms in India under both controlled and uncontrolled environments. Three different image sets were created, containing images in the controlled, uncontrolled, and mixed environment image sets. With 80:20 training to testing datasets, 93% accuracy was found in the proposed method of principal component analysis. Finally, two performance-based comparative analyses of our method were done with PCA-based methods and other renowned techniques used for animal breed identification, wherein our PCA method outperformed others in both comparative scenarios.

Distinctive Attributes of Indian Patients With Classical BCR::ABL1 Negative Myeloproliferative Neoplasms: Unified Clinical and Laboratory Data.

We report one of the largest single center data from a mixed referral setting in India describing baseline characteristics and outcomes of patients with classical BCR::ABL1 negative myeloproliferative neoplasms (MPNs). Patients diagnosed from June 2019 to 2022 were included. Workup and treatment was as per current guidelines. Diagnosis comprised polycythemia vera (PV) in 51(49%), ET in 33(31.7%) and prefibrotic primary myelofibrosis (MF) pre fibrotic myelofibrosis (prePMF) and myelofibrosis in 10(9.6%) patients each. Median age at diagnosis was 52 years for PV and ET, 65.5 for MF and 79 years for prePMF. Diagnosis was incidental in 63(56.7%) and after thrombosis in 8(7.2%) patients. Baseline next generation sequencing (NGS) was available for 63(60.5%) patients. Driver mutations in PV: JAK2 in 80.3%; in ET: JAK2 in 41%, CALR in 26%, MPL in 2.9%; in prePMF JAK2 in 70%, CALR in 20%, MPL in 10%, and in MF: JAK2 in 10%, MPL in 30% and CALR in 40%. Seven novel mutations were detected of which 5 were potentially pathogenic on computational analysis. After median follow up of 30 months, 2 patients had disease transformation and none had new episodes of thrombosis. Ten patients died, most commonly with cardiovascular events(n=5,50%). Median overall survival was not reached. Mean OS time was 10.19 years(95%CI, 8.6 to 11.74) and mean time to transformation was 12.2 years(95% CI,11.8 to 12.6). Our data indicates comparatively indolent presentation of MPNs in India with younger age and lower risk of thrombosis. Further follow up will enable correlation with molecular data and guide modification of age based risk stratification models.

Characterization of landslide displacements in an active fault zone in Northwest China

AbstractLandslides can be caused by natural forcing and anthropogenic activities. Zhouqu County (China) on the eastern margin of Qinghai‐Tibet Plateau is set within the active Pingding‐Huama fault zone with evident fractures on the land surface. Frequent landslides and debris flows have occurred in this region due to river erosion, rainfall and deforestation. Here we quantified the slope movements using time‐series synthetic aperture radar interferometry (InSAR) based on the ascending and descending Sentinel‐1 satellite images acquired between October 2014 and August 2020. We observed distinct displacements in the highly fractured fault zone. The eastward and vertical displacement time series between February 2017 and July 2020 were constrained by the common‐day ascending and descending acquisitions. The eastward rates (461 mm/year) were greater than those in the vertical direction (−185 mm/year). We also note displacement discontinuities across the thrust faults beneath the Suoertou and Zhongpai landslides. Seasonal variations in the displacement time series suggest that the cyclic rainfall is the primary driver for the mass wasting processes rather than the tectonic loading. As a complement to in situ observations, our results demonstrate that InSAR is an effective tool to characterize the spatio‐temporal nature of landslide displacements in complicated geological environments.Plain Language SummaryZhouqu County in the Pingding‐Huama fault zone in the eastern margin of Qinghai‐Tibet Plateau is identified as a high priority site to research on clusters of landslides and debris flows in a mixed geodynamic setting of active tectonics, seasonal rainfall, river erosion and anthropogenic activities. However, our knowledge about landslide kinematics in this complicated region is still limited. We relied on remote sensing images from one ascending and one descending Sentinel‐1 satellite tracks to constrain the spatial–temporal displacement dynamics of active landslides from 2014 to 2020. The spatial patterns of displacements are determined by thrust faulting, river erosion, and anthropogenic activities. The temporal variations of landslide speed are mainly controlled by the seasonal rainfall rather than the tectonic loading.

Quality control of the initial magnetotelluric data: Analysis of calibration curves using a fitting function represented by the ratio of 4th-order polynomials

The research is based on the typical measurement calibration procedure of magnetotelluric soundings (MTS) prior to deep Earth exploration. We suggest the testing and new possibilities of the using MTS equipment calibration. We used two Phoenix MTS station boxes with different magnetic coil sets and mixed sets of coils for verification (check-up) stations calibration and the identity sessions. As a result of the experiments carried out and careful running over sorting of standard functions (exponential, power-law, polynomial), the verification of the proposed method was performed. Eventually this study proposes a “universal” fitting curve after one-station calibration curves to be normalized and are compared to another (etalon) station calibration curves (written in the form of two polynomials ratio). This procedure can be generalized for the case x → f(x), where f(x) is known function. It enables to fit all these 4 typical normalized curves (two for amplitudes (mV) and two for phases (degrees)) by the ratio of fourth degree function containing 9 fitting parameters C0-7 and B0, simply calculated as numeric constants through linear least squares method (LLSM).

Optimizing Mixed Autonomy Traffic Flow with Decentralized Autonomous Vehicles and Multi-Agent Reinforcement Learning

We study the ability of autonomous vehicles to improve the throughput of a bottleneck using a fully decentralized control scheme in a mixed autonomy setting. We consider the problem of improving the throughput of a scaled model of the San Francisco–Oakland Bay Bridge: a two-stage bottleneck where four lanes reduce to two and then reduce to one. Although there is extensive work examining variants of bottleneck control in a centralized setting, there is less study of the challenging multi-agent setting where the large number of interacting AVs leads to significant optimization difficulties for reinforcement learning methods. We apply multi-agent reinforcement algorithms to this problem and demonstrate that significant improvements in bottleneck throughput, from 20% at a 5% penetration rate to 33% at a 40% penetration rate, can be achieved. We compare our results to a hand-designed feedback controller and demonstrate that our results sharply outperform the feedback controller despite extensive tuning. Additionally, we demonstrate that the RL-based controllers adopt a robust strategy that works across penetration rates whereas the feedback controllers degrade immediately upon penetration rate variation. We investigate the feasibility of both action and observation decentralization and demonstrate that effective strategies are possible using purely local sensing. Finally, we open-source our code at https://github.com/eugenevinitsky/decentralized_bottlenecks .

Mixed radial‐angular integrability for rough maximal singular integrals and Marcinkiewicz integrals with mixed homogeneity

AbstractThis paper is devoted to studying maximal singular integrals and Marcinkiewicz integrals with rough kernels in a mixed homogeneity setting. Assuming that the kernels satisfy certain rather weak size conditions, the boundedness of such operators on the mixed radial‐angular spaces are established, respectively. Meanwhile, the corresponding vector‐valued versions are also given.

A heuristic mixed real-time task allocation of virtual utilization in multi-core processor

Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft, and various types of real-time tasks are dynamically added at runtime. In order to improve the utilization of multi-core processors and ensure the real-time performance of the system, it is necessary to adopt a reasonable real-time task allocation method, but the existing methods are only for single-core processors or the performance is too low to be applicable. Aiming at the task allocation problem when mixed real-time tasks are dynamically added, we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF (Virtual Utilization Worst Fit) in multi-core processor. First, a 4-tuple task model is established to describe the fixed-point task and the sporadic task in a unified manner. Then, a VDS (Virtual Deferral Server) for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is derived. Finally, combined with the analysis of VDS's capacity, VU-WF is proposed, which selects cores in ascending order of virtual utilization for the schedulability test. Experiments show that the overall performance of VU-WF is better than available algorithms, not only has a good schedulable ratio and load balancing but also has the lowest runtime overhead. In a 4-core processor, compared with available algorithms of the same schedulability ratio, the load balancing is improved by 73.9%, and the runtime overhead is reduced by 38.3%. In addition, we also develop a visual multi-core mixed task scheduling simulator RT-MCSS (open source) to facilitate the design and verification of multi-core scheduling for users. As the high performance, VU-WF can be widely used in resource-constrained and safety-critical real-time systems, such as spacecraft, self-driving cars, industrial robots, etc.

Spectroscopic Characterization, Cyclic Voltammetry, Biological Investigations, MOE, and Gaussian Calculations of VO(II), Cu(II), and Cd(II) Heteroleptic Complexes.

A novel hydrazone ligand (o-H2BMP) N-(benzo[d]thiazol-2-yl)-3-oxo-3-(2-(1-(pyridin-2-yl)ethylidene)hydrazinyl)propanamide alongside its Cu(II), Cd(II), and VO(II) complexes were prepared and structurally characterized via various spectroscopic analyses (Fourier transform infrared spectroscopy, UV-visible spectroscopy, 1H/13C NMR spectroscopy, liquid chromatography coupled to mass spectrometry, and electron paramagnetic resonance spectroscopy) as well as by elemental analysis, thermal gravimetry analysis/differential thermal analysis, and magnetic moment measurements. Powder X-ray diffraction analysis was also performed for the free ligand and its metal complexes to determine the crystallographic structures and atomic spacing. It also provided information on unit cell dimensions and the average crystallite size. Furthermore, geometric optimization and computational studies were carried out by applying Gaussian (09) software based on density-functional theory coupled with the B3LYP functional and LANL2DZ/6-31+G(d,p) mixed basis set to evaluate some distinct features such as molecular electrostatic potential, E HOMO, and E LUMO. Moreover, electrochemical measurements were performed for Cu(II) in the absence/presence of the chelating agent to predict the effect of complexation interaction in the solution state study. As part of the biological examination, antioxidant and antimicrobial assays were conducted for each compound individually, in addition to cytotoxicity evaluations via MTT assays for all isolated complexes compared to the corresponding metal salts. The MOE (molecular operating environment) approach was also applied to model the interface between the isolated compounds and proteins that were expressed in breast cancer at the atomic level.

Lelong numbers of currents of full mass intersection

We study Lelong numbers of currents of full mass intersection on a compact K\"ahler manifold in a mixed setting. Our main theorems cover some recent results due to Darvas-Di Nezza-Lu. The key ingredient in our approach is a new notion of products of pseudoeffective $(1,1)$-classes which captures some ``pluripolar part'' of the ``total intersection'' of given pseudoeffective $(1,1)$-classes.

Collaborative stochastic expansion planning of cyber‐physical system considering extreme scenarios

AbstractIn this paper, a collaborative stochastic expansion planning model of cyber‐physical system (CPS) with resilience constraints is proposed. The model can reduce the coupling risk and enhance the resilience under extreme scenarios, from the perspective of the structural/functional coupling between the physical and cyber systems. The model is to collaboratively optimize expansion transmission line siting, expansion communication fibre siting, and service routing distribution to minimize total investment cost. Constraints are divided into conventional constraints and resilience constraints. In the resilience constraints, the impact of cyber failures on the dispatch strategy is analyzed, and the load shedding in stochastic scenarios is limited to guarantee the resilience of the planning scheme. Particularly, to reach a stable solution for the stochastic planning, a mixed scenario set is proposed based on the probabilistic typhoon model and the complex network theory. Finally, the model is solved by the progressive hedging (PH) algorithm. The case studies of the IEEE RTS‐79 test system demonstrate that, compared with the traditional independent planning model, the model proposed in this paper performs better in limiting load loss and enhancing resilience under extreme scenarios.

Detection of Dipole Modulation in CMB Temperature Anisotropy Maps from WMAP and Planck using Artificial Intelligence

Breakdown of rotational invariance of the primordial power spectrum manifests in the statistical anisotropy of the observed Cosmic Microwave Background (CMB) radiation. Hemispherical power asymmetry in the CMB may be caused due to a dipolar modulation, indicating the presence of a preferred direction. Appropriately rescaled local variance maps of the CMB temperature anisotropy data effectively encapsulate this dipolar pattern. As a first-of-its-kind method, we train Artificial Neural Networks (ANNs) with such local variances as input features to distinguish statistically isotropic CMB maps from dipole-modulated ones. Our trained ANNs are able to predict components of the amplitude times the unit vector of the preferred direction for mixed sets of modulated and unmodulated maps, with goodness-of-fit (R 2) scores >0.97 for full sky and >0.96 for partial sky coverage. On all observed foreground-cleaned CMB maps, the ANNs detect the dipolar modulation signal with overall consistent values of amplitudes and directions. This detection is significant at 97.21%–99.38% C.L. for all full sky maps, and at 98.34%–100% C.L. for all partial sky maps. Robustness of the signal holds across full and partial skies, various foreground cleaning methods, inpainting algorithms, instruments, and all the different periods of observation for Planck and WMAP satellites. The significant and robust detection of the signal, in addition to the consistency of values of amplitude and directions, as found independent of any preexisting methods, further mitigates the criticisms of look-elsewhere effects and a posteriori inferences for the preferred dipole direction in the CMB.

IEEE 802.11ay enabled integrated mmWave radar detection and wireless communications

Integrated sensing and communication (ISAC) under the same frequency band and hardware has emerged as a key technology in future wireless networks. Meanwhile, the harmonious coexistence between detection and communication modules has also attracted tremendous research interest in both academia and industry, currently. In this work, we propose a novel Integrated detection and communication (IDAC) scheme in the promising IEEE 802.11ay enabled millimeter wave (mmWave) networks. Particularly, we first introduce a mixing personal basic service set control point or access point (PCP/AP) architecture to support the IDAC function. Thereafter, we embed the radar detection into the IEEE 802.11ay beamforming training (BFT) period by utilizing its directional scanning feature. Furthermore, a BFT and energy allocation strategy is derived to balance the performance between detection and communication. Numerical results demonstrate the effectiveness of the proposed scheme.

ViT-rPPG: a vision transformer-based network for remote heart rate estimation

Remote photoplethysmography (rPPG) is a video-based heart rate measurement technology, which is widely used in special scenes where contact equipment is difficult to measure. However, the rPPG signal is very weak, and it is easily affected by factors such as uneven environmental illumination changes and the tester’s head movement, which leads to the poor robustness of the existing methods in natural scenes. A deep learning model based on vision transformer is proposed to segment the facial skin region to generate the spatiotemporal feature map of the video sequence, inputs the feature map into the model for rPPG physiological feature extraction, and then fits the rPPG signal. The experiments verify the effectiveness of the method on mixed data sets and can ensure that the model has a high degree of signal fitting while significantly reducing the computational complexity of the transformer.

Accuracy of Evaluation of Fatty Liver with Third-Generation Unenhanced Dual-Energy CT and MRI: Prospective Comparison with MR Spectroscopy

Abstract Background and Objectives The purpose of this study is to evaluate and establish the accuracy of noninvasive methods, including third-generation dual-source dual-energy computed tomography (DECT) and proton density fat (PDF) fraction on magnetic resonance imaging (MRI) using three-dimensional multiecho multipoint chemical shift-encoded spoiled gradient echo (q-Dixon) sequence in the quantification of hepatic steatosis; with H1-MR spectroscopy (MRS) as the reference standard. Materials and Methods A total of 47 patients were included in this prospective study. We studied the accuracy of fatty liver detection using third-generation DECT using mixed set images (MSIs), virtual monochromatic images (VMIs), and MRI q-Dixon. The results were compared with H1-MRS. Data were analyzed using linear regression for each technique compared with MRS. Results Our study's correlation and linear regression analysis showed a good correlation between PDF values obtained by H1-MRS and MR q-Dixon methods (r = 0.821, r 2 = 0.674, p < 0.001). On MSI, H1-MRS showed a low correlation with average liver attenuation (r 2 = 0.379, p < 0.001) and a moderate correlation with liver attenuation index (r 2 = 0.508, p < 0.001) noted. There was a moderate correlation between H1-MRS and average liver attenuation and liver attenuation index on VMI at 80 to 120 keV with r 2 = 0.434, p < 0.001, and r 2 = 0.485, p < 0.001, respectively. Conclusion MRI q-Dixon is the method of choice for evaluating fat quantification in the absence of H1 MRS. Among DECT images, VMI is valuable in the evaluation of hepatic fat as compared with the mixed set of images.

Biological determination, molecular docking and Hirshfeld surface analysis of rhoduim(I)-N-heterocyclic carbene complex: Synthesis, crystal structure, DFT calculations, optical and non linear optical properties

The synthesis and characterization of 1-(isobutyl)-3-(2.3.5.6 tetramethylbenzyl)-5.6-dimethylbenzimidazolium chloride and its N-functionalized Rhodium(I) N-heterocyclic carbene complex have been described. The ligand 2 and the complex 3 were characterized by IR, 1H NMR and 13C NMR spectroscopy, DART-TOF mass spectrometry and elemental analysis. The coordination mode of the complex was confirmed by single crystal XRD analysis. We performed a comparative theoretical study in order to investigate the impact of the iridium on the optoelectronic and non-linear optical properties of the complex. The M06-2X functional with the mixed basis set (6-31G(d): def2tzvp) was found the best method for optimizing the studied complex since it displayed close geometric data to the experiment. As a novelty in this work, iridium was found to be a performer for NLO applications over rhodium. This Rh(I)- N-Heterocyclic carbenes (NHC) showed good catalytic performance for the hydrosilylation of acetophenone derivatives with triethylsilane at 80 °C for 1 h by using 1 mol % of this complex. The cytotoxic properties of the rhodium(I)–NHC complex have been assessed against MCF7 and MDA-MB-231 cancer cells and the complex show interest activity. The in vitro antibacterial activity of this complex were also investigated against Micrococcus luteus LB 14110, Listeria monocytogenes ATCC 19117, Salmonella Typhimurium ATCC 14028, Staphylococcus aureus ATCC 6538, Pseudomonas aeruginosa and Candida albicans microorganisms indicated their significant biological potential. Additionally, the antioxidant activity of the same complex has been analyzed with DPPH∙ free radical through spectrophotometric method and the result inferred them as an antioxidant. The potential biological activities were investigated by using molecular docking analysis.

Ombining words and drawings, the better to understand students’ lived experiences

This case study presents and interprets two data sets – interviews and line drawings – about barriers to learning in the HE context, as seen from the student perspective. Eleven undergraduate students participated in this exploratory study, which took place at a United Kingdom higher education (HE) institution. The findings help reveal to the reader the lived experiences of students and present opportunities to consider intervention practices that can be used to support student transition from further education (FE) into HE. This case study also discusses how to collect and use this mixed data set and highlights how employing this method promotes student voice. Researchers may find that the approach may be applicable to their own project design.

Enhanced damage imaging in three-dimensional composite structures via electrical impedance tomography with mixed and level set regularization

Electrical impedance tomography (EIT) is a promising tool for nondestructive evaluation (NDE) of materials that exhibit stimulus-responsive electrical conductivity. To date, materials practitioners of EIT have used standard regularization methods such as smoothness-promoting operators to solve the ill-posed EIT inverse problem. However, more sophisticated and better performing regularization methods exist. It is essential that these other regularization methods be explored in order for EIT to see more widespread adoption in NDE. To that end, we present two novel regularization techniques – a mixed smoothness/focal method and a level set method – for application to damage imaging via EIT. These new techniques are experimentally validated on two three-dimensional composite components, a carbon black-modified glass fiber/epoxy tube and a carbon fiber/epoxy laminate airfoil subject to multiple damaging impacts. It is shown that both of the new regularization techniques markedly outperform traditional smoothness-only methods. These results are an important step towards adoption of more sophisticated EIT formulations in NDE and transition of EIT from the proof-of-concept phase and into practice for engineered materials.