gebhart/patrepeval huggingface dataset:
Sorting and separation of microparticles by surface properties using liquid crystal-enabled electro-osmosis (2018)

Sorting and separation of microparticles is a challenging problem of interdisciplinary nature. Existing technologies can differentiate microparticles by their bulk properties, such as size, density, electric polarizability, etc. The next level of challenge is to separate particles that show identical bulk properties and differ only in subtle surface features, such as functionalization with ligands. In this work, we propose a technique to sort and separate particles and fluid droplets that differ in surface properties. As a dispersive medium, we use a nematic liquid crystal (LC) rather than an isotropic fluid, which allows us to amplify the difference in surface properties through distinct perturbations of LC order around the dispersed particles. The particles are placed in a LC cell with spatially distorted molecular orientation subject to an alternating current electric field. The gradients of the molecular orientation perform two functions. First, elastic interactions between these pre-imposed gradients and distortions around the particles separate the particles with different surface properties in space. Second, these pre-imposed patterns create electro-osmotic flows powered by the electric field that transport the sorted particles to different locations thus separating them. The demonstrated unique sorting and separation capability opens opportunities in lab-on-a-chip, cell sorting and bio-sensing applications.
ChemInform Abstract: Stereospecific Synthesis of Spirohydantoins of β‐Glucopyranose: Inhibitors of Glycogen Phosphorylase. (1997)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Use Metaheuristics to Improve the Quality of Drilling Real-Time Data for Advance Artificial Intelligent and Machine Learning Modeling. Case Study: Cleanse Hook-Load Real-Time Data (2018)

Abstract The drilling engineers are overmild with huge amount of data-points, argue the need to develop Artificial Intelligent (AI) and Machine Learning (ML) models to crunch these huge amount of data generating decision-like information. There are a lot of challenges developing such approach, varying from computational power, lack of subject matter experts, and develop the optimum algorithm. But the main bottleneck is the quality of the data. Regardless of how advance AI/ML model, if the data is bad, the model will generate bad result; garbage-in garbage-out. The scope of this paper is to use metaheuristics models to improve the data quality. The process start by extracting Hook-Load drilling real-time data. And explore the raw data quality using visualization and statistical methods. Then apply several Metaheuristics models to generate functional approximation equation that identify/ follow the trend of the good-quality data. This will be by employ multiple scenarios with different degree of randomness that lead to the highest matching which generate the high quality level. The process will cover different technique including Greedy, Hill-Climbing, Random Search, and Simulated Annealing. During this process hundreds of thousands of scenarios will be conducted to simulate the Hook-Load data, to identify the optimum functional approximation equation that match the best data quality. Which can then safely integrated into the advance Artificial Intelligent and Machine Learning models. Running such process require an expensive computational cost, since it includes huge amount of real-time data need to be process under complex advance models. Moreover it require a deep understanding of the internal process of each models to ensure finest manipulating them to get the optimum data quality result. Running these scenarios, lead successfully to functional approximation that spill the data behavior, with Mean Absolute Error (MAE) equal to 10.5. It is worth height that functional approximation is very expensive in term of time and complexity, but it generate the highest quality result, leading to better AI/ML model. Moreover it is the most dynamic approach allowing it to be applied in other drilling real-time parameters as well. Utilizing Metaheuristics approach to improve the data quality is new to the upstream domain in general, with almost no application in drilling in specific. The novelty is to introduce this advance technique into the drilling real-time data domain, it will sharply improve the data quality leading to higher Artificial Intelligent and Machine Learning prediction/ analytical models. It worth mentioning that such approach will run all those simulation/ scenarios and adjust itself automatically with almost no manual interference. Leading to self-data-driven data-quality model.
Scattering of Quantum Light by a Perfectly Conducting Cylinder (2021)

We consider transformation of quantum states of electromagnetic field by scattering from a perfectly conducting cylinder with a circular cross-section. We introduce a quantization technique for the scattered field, and demonstrate how quantumness (in particular, entanglement) of field states is transferred to the scattered field. The obtained results may be useful for designing quantum antennas and for quantum-enhanced far-field sensing, i.e., quantum lidars/radars.
ZnBr2‐catalyzed chemical effects in poly(acrylonitrile‐ co‐butadiene) (2003)

Abstract The excellent chemical properties and resistance to oil of poly(acrylonitrile‐ co ‐butadiene), or nitrile–butadiene rubber (NBR), has led to the extensive use of these elastomers as O‐ring material in the oil extraction industry. The degradation of NBR gaskets is known to occur during the well completion and oil extraction process when they are exposed to bromide fluids such as ZnBr 2 ‐based completion fluid. Samples of NBR, polyacrylonitrile, and polybutadiene were exposed to ZnBr 2 ‐based completion fluid and analyzed by attenuated total reflectance (ATR) and diffuse reflectance IR. These analyses showed that the ZnBr 2 completion fluid promoted the hydrolysis of the nitrile group to form amides and carboxylic groups. The carbon–carbon double bonds in NBR were unaffected after short exposure to ZnBr 2 ‐based completion fluid but were quickly hydrated in acidic bromide mixtures. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 1250–1257, 2003
Tell me what i don't know - Making the most of social health forums (2013)

We describe a novel approach to helping patients learn about their condition using social health forums. We infer a patient's condition based on her clinical data, and assign her to a clinical state pertaining to that condition. Our system presents the patient with forum posts that are most relevant to her current state. By adjusting a Like Me dial, the patient can modify the results from those that are most popular with patients in the same condition to the most general that apply to patients that map to other states for the condition. The posts are ranked in order of importance to the patient condition and the dial settings and the Top-N results are shown to the patient. The initial rankings of posts for different states are obtained by weights assigned by a medical expert. The patients can also give feedback with a LIKE or a DISLIKE button on whether the post is useful to them. This is incorporated into our method to dynamically change the initial weights. As the system is used in practice the initial rankings are subsumed by the feedback provided by users of the system. Our approach is general but we give results in the context of a diabetes social health forum. The algorithms are given along with preliminary results and an illustration of the user interface. We view this effort as a component of a larger patient navigation and engagement system that can help patients gain a better understanding of their condition.
Model predictive control for treating cancer with ultrasonic heating (2015)

This paper investigates thermal ablation of cancer tissue as a controls problem. The objective is to deliver a lethal dose of thermal energy to the cancer tissue without damaging critical nearby healthy tissue. This paper proposes a model predictive controller (MPC) to regulate thermal dose. The model predictive controller guarantees the safety of the healthy tissue surrounding the tumor. The cost function rewards killing cancer cells. Simulations comparing the proposed controller with the bang-bang controller used in practice demonstrate that the MPC controller kills more of the cancer tissue and requires less time than the bang-bang controller, while damaging less healthy tissue.
Effects of diltiazem, dipyridamole, and their combination on hemostasis (1984)

Calcium channel blockers and antiplatelet agents, alone and in combination, have been reported to induce bleeding in patients undergoing surgery. Since diltiazem and dipyridamole influence platelet function in vitro and in vivo, their influence on hemostasis was examined in five normal men given diltiazem, 90 mg by mouth, followed by 60 mg every 6 hr for 48 hr, or dipyridamole, 75 mg by mouth every 8 hr for 48 hr. At 24 hr, the alternate drug was added to the regimen to assess effects of the combination on hemostasis. Platelet aggregation, serum thromboxane B2 and 6-keto-PGF1 alpha concentrations (stable metabolites of thromboxane A2 and prostacyclin), bleeding time, prothrombin time, partial thromboplastin time, and serum diltiazem concentrations were measured. Diltiazem and dipyridamole alone and in combination had no significant effect on bleeding time, prothrombin time, or partial thromboplastin time. Platelet aggregation induced by threshold concentrations of adenosine diphosphate, epinephrine, and calcium ionophore A 23187 were inhibited by diltiazem and dipyridamole alone and in combination. The only change in prostaglandin concentrations was a slight increase in serum 6-keto-PGF1 alpha after diltiazem. Despite influences on platelet function, neither diltiazem nor dipyridamole alone or in combination induced clinically relevant changes in hemostasis.
Knotless anchors with sutures external to the anchor body may be at risk for suture cutting through osteopenic bone (2016)

Anchors with sutures external to the anchor body are at risk for suture cutting through bone since the suture eyelet is at the distal tip of the implant and the suture directly abrades against the bone edge during cyclic loading. Suture cutting through bone may be a significant source of fixation failure, particularly in osteopenic bone.Cite this article: Y. Ono, J. M. Woodmass, A. A. Nelson, R. S. Boorman, G. M. Thornton, I. K. Y. Lo. Knotless anchors with sutures external to the anchor body may be at risk for suture cutting through osteopenic bone. Bone Joint Res 2016;5:269-275. DOI: 10.1302/2046-3758.56.2000535.
Supplementary Data 1 from Identification of Epigenetically Silenced Genes in Tumor Endothelial Cells (2023)

Supplementary Data 1 from Identification of Epigenetically Silenced Genes in Tumor Endothelial Cells
Lepidocrocite Titanate–Graphene Composites for Sodium-Ion Batteries (2022)

To overcome electronic transport issues of layered titanates in sodium-ion batteries, we have designed and synthesized composites of lepidocrocite titanates with reduced graphene oxide through a solution-based self-assembly approach. The parent lepidocrocite titanate (K0.8[Ti1.73Li0.27]O4) was exfoliated by a soft-chemical approach and mechanical shaking. Exfoliated layered titania sheets (LTO) were then combined with reduced graphene oxide (rGO) layers to assemble into composites through flocculation. Countercations (i.e., Mg2+) were used for the self-assembly of negatively charged titania and rGO nanosheets via flocculation. The carbon content in the composites was tuned from 1 to 17% by changing the ratio of titania and rGO sheets in the mixed colloidal suspensions. Electrodes were processed with as-prepared LTO–rGO composites without any carbon additives and tested in sodium half-cell configurations. Mg+-coagulated LTO–rGO composite electrodes deliver higher capacities than electrodes prepared with coagulated titania sheets and 10% acetylene black in sodium half-cells and display good capacity retention after 50 cycles. Electrochemical impedance spectroscopy results indicate lower charge transfer resistance for LTO–14.5%rGO composites than that of coagulated titania sheets with 10% acetylene black. A power law analysis of cells containing the composites indicate a hybrid mechanism consisting of both surface and diffusional processes. A comparison with a similar system, that of dopamine-derived LTO-C heterostructures, reveal significant differences. While capacities showed a strong dependence on carbon content for the dopamine-derived materials, this was not true for the LTO–rGO composites. Instead, the highest capacity was obtained for the 14.5% rGO sample, with a lower value obtained for the 17% rGO sample. A greater proportion of the redox processes were surface rather than diffusional in nature for the LTO–rGO composites as well.
A systematic investigation to obtain physical assets on the moon through self-propagating high-temperature reactions (2013)

Future space missions on the Moon, Mars and near Earth asteroids, etc., are expected to be strongly facilitated and time extended by the possibility of "In-Situ Fabrication and Repair" (ISFR) the required equipments and infrastructures. In addition, the combination of the latter approach with the "In-Situ Resources Utilization" (ISRU) paradigm contributes to overcome drawbacks related to the transportation of the needed material from the Earth. In this regard, various technologies have been recently proposed with the aim of developing suitable structures to be placed on the Moon surface for the protection against cosmic rays, solar wind, meteoroids, etc. Specifically, the possibility of exploiting combustion synthesistype reactions using Lunar resources for the fabrication of ceramic-based products was considered. Along these lines, by taking advantage of the fact that Lunar soil contains up to 20 wt.% of ilmenite (FeTiO3), the highly exothermic thermite reduction of the latter oxide with Al is systematically investigated in this work. A self-propagating (SHS) behavior is displayed only above a certain Al/FeTiO 3 molar ratio (0.9). In addition, as the amount of Al in the mixture is increased, the reactive process proceeds faster and the combustion temperature becomes higher, due to the increased system exothermicity. Correspondingly, the maximum amount of Lunar regolith to be possibly reacted with additional FeTiO3 and Al is identified. The obtained products (a mixture of Al-, Ti-, Mg-, and Ca-oxides, and metallic phases) exhibit satisfactory compressive strength properties (≥ 25.8 MPa) that make them promising as construction materials. Parabolic flight experiments evidenced that SHS process dynamics and product characteristics are barely affected by gravity. The obtained findings allow us to conclude that the optimal conditions identified during terrestrial experiments are still valid for in-situ applications in Lunar environment
Pipeline Embolization Device for treatment of high cervical and skull base carotid artery dissections: clinical case series (2015)

Our initial experience with treatment of high cervical and skull base dissections with the PED appears to show that this technique may be a safe and viable treatment option. However, long-term results are needed to fully evaluate the efficacy of such treatment.
Mixing performance comparison of milliscale continuous high‐shear mixers (2015)

Mixing performance of two continuous flow millilitre‐scale reactors (volumes 9.5 mL and 2.5 mL) equipped with rotor‐stator mixers was studied. Cumulative residence time distributions (RTD) were determined experimentally using a step response method. Distributions were measured for both reactors by varying impeller speed and feed flow rate. The mixing effect was determined by measured RTDs. Computational fluid dynamics (CFD) were used to verify that the residence time distribution in the measurement outlet agreed with the outlet flow. The mixing power of both reactors was determined using a calorimetric method. The reactor inlet flow rate was found to affect mixing performance at 1–13 s residence times but the effect of impeller speed could not be noted. Both milliscale reactors are close to an ideal continuous stirred‐tank reactor (CSTR) at the studied impeller speed and flow rate ranges. The specific interfacial area was found to depend on the reactor inlet flow rate at constant impeller speed for the case of copper solvent extraction.
Creatine Kinase, a Magnetic Resonance-Detectable Marker Gene for Quantification of Liver-Directed Gene Transfer (2005)

We reported previously the in vivo detection of ectopic and transient expression of creatine kinase gene (ck) in the liver by phosphorus-31 magnetic resonance spectroscopy ((31)P MRS). Here we demonstrate the feasibility of using ck as a reporter gene to monitor the transfer of low-density lipoprotein receptor (LDLr) gene to LDLr(/) mice, a preclinical model for familial hypercholesterolemia. A recombinant adenovirus was generated that carries the creatine kinase gene (ck) and human LDL receptor gene (hLDLr) linked by an internal ribosomal entry site sequence. Intravenous injection of the adenovirus into LDLr(/)mice (1 x 10(11) viral particles/mouse) resulted in transduction of more than 90% of hepatocytes in the liver. Simultaneous expression of ck and LDLr was confirmed by Western analysis of the transduced livers. Through precise regulation of transgene expression in hepatocytes in vitro, an excellent correlation (R(2) = 0.96) between LDLr and ck expression was demonstrated over a wide range of viral dose. In vivo 31P MRS was employed to detect the metabolic product (i.e., phosphocreatine) of the creatine kinase protein (CK) reaction. CK activity, which is a true measure of ck gene expression, was quantified in vivo by magnetization transfer. Because ck is expressed abundantly in human muscle and brain but is absent from the liver, ck is useful to monitor any liver directed gene transfer. Use of the ck reporter would facilitate the clinical translation of gene therapy by providing a nondestructive readout of the level and duration of therapeutic gene expression.
Algorithm-data driven optimization of adaptive communication networks (2017)

This paper is motivated by the emerging vision of an automated and data-driven optimization of communication networks, making it possible to fully exploit the flexibilities offered by modern network technologies and heralding an era of fast and self-adjusting networks. We build upon our recent study of machine-learning approaches to (statically) optimize resource allocations based on the data produced by network algorithms in the past. We take our study a crucial step further by considering dynamic scenarios: scenarios where communication patterns can change over time. In particular, we investigate network algorithms which learn from the traffic distribution (the feature vector), in order to predict global network allocations (a multi-label problem). As a case study, we consider a well-studied fc-median problem arising in Software-Defined Networks, and aim to imitate and speedup existing heuristics as well as to predict good initial solutions for local search algorithms. We compare different machine learning algorithms by simulation and find that neural network can provide the best abstraction, saving up to two-thirds of the algorithm runtime.
Understanding Preanalytical Factors Affecting INR Results in Egyptian Patients on Maintenance Warfarin Therapy (2018)

International normalized ratio (INR) is routinely monitored during warfarin (WRN) therapy. WRN response is affected by preanalytical variations, which may affect the accuracy of the assay, resulting in poor clinical management. The aim of this study is to investigate the most common preanalytical variations that affect INR measurements in patients under warfarin maintenance therapy. INR was recorded in 106 patients under WRN maintenance therapy. Hemoglobin, PCV, and serum albumin were measured for all patients. There was significant differences in hemoglobin, PCV, and serum albumin between patients who reached their target INR (n = 56) and those who did not (n = 50). Among patients who did not achieve adequate coagulation, 42% suffered from severe anemia (7 males and 17 females) while 46.4% had low PCV (6 males and 20 females), and 40% had hypoalbuminemia (6 males and 14 females). Low hemoglobin, PCV, and/or albumin levels were prevalent among patients who did not achieve their target INR values (n = 50). It is recommended to measure hemoglobin, PCV, and albumin levels in patients under WRN maintenance therapy who did not achieve their target INR values. Poor nutrition and health status as reflected by high prevalence of anemia or hypoalbuminemia may contribute to poor WRN coagulation control among Egyptians. Thus, monitoring anemia as well as albumin level may enhance the therapeutic effectiveness.
Advanced RMG module to improve AC/DC performance for 14nm FinFETs and beyond (2014)

An advanced Replacement Metal Gate (RMG) module was developed for 14nm node FinFETs and beyond. STI oxide extra recess increases on-current without any dedicated Source and Drain (SD) optimization. Tungsten (W) selective etch recesses work function metal (WFM), which reduces gate-contact capacitance, and improves AC performance and yields by increasing gate-contact space. Combination of work function (WF) adjust treatment and WFM optimization was applied to achieve wide range of threshold voltage (Vt) control for multiple Vt (multi-Vt) devices without any performance penalty.
Generation of a Space-Time Pulse with a Controllable Group Velocity as a Function of Distance Utilizing Classical Entanglement by Combining Multiple Frequencies Each Containing Multiple Laguerre Gaussian Modes (2020)

We simulate the generation of a space-time pulse with a controllable group velocity by classical entanglement of frequencies and multiple LG modes. Group velocities greater and smaller than the speed of light are achieved.
Rapid high-resolution cranial bone MRI using deep-learning prior image reconstruction (2023)

A high-resolution (HR) MRI capable of resolving the detail of bony structures at sub-millimeter resolution is desired. A short MR acquisition results in under-sampled k-space data below the Nyquist rate, leading to artifacts and high noise. We developed an HR reconstruction method regularized by a complex deep-learning prior (RECD). We achieved high-resolution MR (0.6x0.6x0.8mm3) with a one-minute acquisition time. Using images reconstructed from a 5-minute MR scan as the gold standard, we compared the peak signal to noise ratio (PSNR) and similarity index (SSIM) for 1-min RECD and 1-min compressed sensing (CS) reconstructed images. RECD outperformed CS.