bluuebunny/crossref_metadata_2025 huggingface dataset:
The management of innovative processes in organizations.
System-transdisciplinary approach
Authors: Mokiy Michael , Gureev Paul
Published: April 2021

The article justifies the application of a system-interdisciplinary approach to solving problems of managing innovative processes, especially in the field of planning, organizing and controlling innovative events. Such problems are the justification of innovative events and
the selection of their dates. The article describes the principles of innovation classification based on the interdisciplinary model of the information unit of order. The development of the system can be represented as a multiplex of waves or as a set of M-waves. It is shown that the system at each stage of its development is predisposed to changes in a certain trait. The article describes the methodological principles for justifying the dates for planning, conducting and monitoring the implementation of measures in the innovation process.
Development of textual analytics tools for analysis of public and specialized sources in the tasks of foresight and system analysis
Authors: Savastiyanov Volodymyr
Published: April 2021

A combined approach to extracting concepts and constructing classifiers and ontologies using open and proprietary software packages has been developed. Modern approaches, methods and models of storing large amounts of poorly structured information from Open Source software sets are studied. An ontology was built, in the leaves of which a classifier based on Boolean rules was implemented using SAS(R) Content Categorization Software. To build the ontology, the approach of constructing vectors of related concepts is employed using the Open Source library of Gensim software, namely the Word2Vec model. A typical algorithm for constructing a classifying ontology has been developed. The results of the research
can be used to build an ontology of subject areas, create classification ontologies and mark corpora of texts.
Using cognitive maps to study issues concerning the improvement of the quality of life of population in the frame of interregional disparities
Authors: Tyushnyakov Vitaly , Tkachenko Yulia
Published: April 2021

This paper studies issues of the rise in the standards of living and improvement of the quality of life of the population in the
frame of intermunicipal disparities. Simulation and modelling are examined in relation to research of standards of living and quality of life. Tools of cognitive modelling and simulation are used to acquire new knowledge on the regional social and economic, ecological, and political system which determines the standards of living and quality of life. A cognitive model studying the quality of life was designed and its structural properties were analyzed. Scenarios were created to model possible developments
of the situation under the influence of various factors. The novelty of the work is in applying a new informational technology of cognitive modelling to studying the improvement of the quality of life in the frame of intermunicipal disparities.
Generalized solutions of optimal control problems
Authors: Beyko Ivan , Furtel Olesya , Spivak Julia
Published: April 2021

The problems of optimal control of systems of algebraic-integro-differential equations and partial differential equations are considered, which describe controlled processes with concentrated and distributed parameters. Generalized optimal solutions that exist for a wide range of optimal control applications are identified. Methods for constructing approximate generalized solutions are considered.
Effects of transport conditions on the stability and sensory quality of wines
Authors: Tchouakeu Betnga Prudence Fleur , Longo Edoardo , Poggesi Simone , Boselli Emanuele
Published: April 2021

The quality of wine can be affected by several factors after bottling: temperature changes, shipment time, type and amount of mechanical stress (vibrations) and environmental conditions, such as light exposure and relative humidity. The effects of delivery using different packaging systems (boxes, bottles, containers) and the impacts of mode of shipment (car, truck, airplane and cargo ship) are reviewed, along with compositional markers, the reactions leading to off-odours and/or off-flavours and the approaches to monitoring transportation conditions (temperature, relative humidity and type and entity of vibration) and their impacts on the sensory profile of the wine. Temperature fluctuations are more prevalent during the transport of wine over land than by sea, and may lead to a decrease in the fresh, fruity and floral aromas of the wine and to premature aging due to the ‘pump’ effect (repeated expansion and contraction cycles). Trans-shipment phases should be reduced to a minimum, especially in hot climates. Vibrations, even for a short period of time (15 days), can alter the overall quality of the product.
Anesthesia Management in Patient with Placenta Percreta Performed Intra-aortic Ballooning Caesarean Section
Authors: Supraptomo RTh. , Allan Alma Hepa
Published: April 2021

Placenta accreta spectrum is one of maternal mortality’s causes which is related with severe obstetric bleeding that requires hysterectomy. The incidence rate of the spectrum placenta increases with increasing caesarean section. Placenta accreta spectrum is also close-related to placenta previa. The aim of this study is to  understand perioperative management in patient with placenta percreta performed with intra-aortic ballooning in caesarean section. We are following a case on a 36 year old female patient, multigravida at term pregnant with placenta percreta and history of caesarean section 5 and 2 years ago. The surgeries performed were caesarean section surgery as well as intra-aortic ballooning. Anesthetic technique used was general anesthesia. Operation duration approximately ± 180 minutes, bleeding 1500 cc. After the operation, the patient was admitted to the ICU. The patient going well and discharged from ICU to ward on the second day. After three days in ward, the patient discharged to home. Hemodynamic changes during balloon intra-aortic procedures are of particular concern to anesthetists. This is because the stopping of blood flow to the aorta in this case can cause an increase in blood vessel pressure, where the administration of nitroglycerin at low doses can reduce venous tone resulting in venous vasodilation which will maintain hemodynamic stability during the process of blocking blood vessels with a balloon. From the case we may conclude that anesthesia in pregnant women with placenta accreta spectrum should be carried out with caution and involve a multidisciplinary specialist given its high risk of bleeding. The intra-aortic balloon insertion technique can be an option used to reduce the risk of bleeding in patients with placenta accreta spectrum.
Oil Companies Demand Digital Their Way
Authors: Rassenfoss Stephen
Published: April 2021

Oil industry executives surveyed last year ranked the potential positive impact of big data analytics at the top of the list of trends, higher than even changes in oil demand.

That bold conclusion was from a survey by accounting firm Ernst and Young (EY), putting big data analytics among the top trends that could aid business growth in the next 3 years, even above the demand swings that move oil prices.

The survey may have reflected the mood last summer when the outlook for oil consumption looked so weak that cost saving was the only path to better results.

“The survey speaks to a high-level ambition across the operator community to use digital as a mechanism to drive down costs,” said Toby Summers executive director for EY. The promise there is that digital can allow them to scale up operations with fewer hires in good times and scale back with fewer layoffs when the cycle turns down.

These projects also cost less than other cost-cutting options.

“Digitization is one of the cheapest ways to get the business more resilient,” said Patrick von Pattay, a vice president for Wintershall Dea, a Germany-based independent, and chairman of the Digital Transformation Committee of SPE’s Digital Energy Technical Section.

Process changes supported by digital analysis can cost a couple hundred thousand dollars; that is not a lot of money in a business where a single offshore well often costs hundreds of millions.

What is not obvious is who does the work.

The rush to digital has scrambled traditional relationships with oilfield service companies and brought in new players, from Silicon Valley giants to a flurry of startups in the oil business, a few of which have become established players.

As a result of the change in the technology, and the business models of the upstarts, oil company technical teams can and do play a more active role in digital technology development and use than in the past.

Changes began in 2014, when the sudden end of $100/bbl oil forced oil companies to drop their long-time reliance on owning their own computer systems. Oil companies finally joined the decade-old shift to buying data storage and processing as a service from giants such as Amazon and Google. That facilitated digital innovations by centralizing their data, eliminating splintered storage systems that hindered analysis.

The giant looming over the service business now is Amazon Web Services (AWS). The cloud storage arm of the online retail and logistics giant has grown exponentially, doing everything from selling an array of digital tools to promoting a list of preferred energy providers.

Digital newcomers disrupted relations with service companies that had built software solutions and sold equipment programmed using proprietary coding.

Increasingly user-friendly tools for visualizing and analyzing data, plus the ability for smaller companies to buy data capacity, allowed engineers to do more and allowed midsized companies to act like big ones.

“There has been a shift now; the independents have access to the same tech as the big guys,” Summers said.
Technology Focus: Production Monitoring (March 2021)
Authors: Mata Carlos
Published: April 2021

Last year, events accelerated several trends in the energy landscape. Oil and gas prices have remained low, and the industry is focusing more strongly on reducing costs and increasing operational efficiency. Reducing costs is not only about cutting costs today but also about reducing the life-cycle cost per barrel. Implementing innovative technologies that increase recovery requires a small investment but can bring large rewards.

Advances in sensor accuracy, computing power, and data analytics unlock innovative use cases for technology for mapping subsurface movements of fluids. Very different technologies provide independent insights into the displacement process in the reservoir—for example, distributed acoustic sensing (DAS) used for periodic 4D seismic, time-lapse borehole microgravity surveys for 4D reservoir fluid mapping, DNA analytics to map interwell connectivity and zonal contributions, and interpreting downhole gauge pressure fluctuations caused by tidal forces to map fluid fronts.

The aggregation of these uncorrelated insights helps geologists and reservoir engineers narrow down the number of possible realizations of the reservoir model, better map bypassed resources, and provide forecasts that are more realistic.

On the production side, well instrumentation continues to become more affordable over time. For example: distributed temperature sensing, DAS, and downhole gauge lines can be run in a single optoelectric cable, which reduces well complexity and instrumentation costs. Wells can be instrumented at surface for less than $5,000 using wireless technologies. Wireless downhole gauges also can be retrofitted in older completions. There are many ways to leverage technology for improving production and reservoir monitoring and unlocking potential.

The OnePetro online library offers a large collection of novel use cases for technology and algorithms applied to production and reservoir monitoring. The challenge now is to transform the way we work to realize the maximum value from such technology.
Laboratory Formation Damage Test Data Upscaled With Computational Fluid Dynamics
Authors: Feder Judy
Published: April 2021

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 199268, “Upscaling Laboratory Formation Damage Laboratory Test Data,” by Michael Byrne, SPE, Lesmana Djayapertapa, and Ken Watson, SPE, Lloyd’s Register, et al., prepared for the 2020 SPE International Conference and Exhibition on Formation Damage Control, Lafayette, Louisiana, 19-21 February. The paper has not been peer reviewed.

Through several case histories, the complete paper demonstrates applications of computational fluid dynamics (CFD) modeling to upscaling of laboratory-measured formation damage and reveals implications for well and completion design. The value of laboratory testing is quantified and interesting challenges to conventional wisdom are highlighted.

Introduction

Laboratory formation damage testing is often used to help select optimal drilling and completion fluids. Test procedures such as sand retention and return permeability represent an attempt to simulate near-wellbore conditions during well construction and production.

To determine what degree of permeability impairment is allowable, further interpretation that cannot be provided using classical nodal analysis or reservoir simulation methods is required. The complete paper describes the evolution of, and potential for, more-comprehensive upscaling and outlines the importance of consideration of full well geometry when designing and interpreting coreflood tests for formation damage. CFD simulations provide a means to upscale suitable laboratory test data to predict effect on well performance.

Methods

CFD simulations use a relatively simple, steady-state, static damage model that takes endpoint data from laboratory core tests and translates the data into parameters that are used for input into well geometry. Although this method has its merits and is a considerable advance on previous, more-simplistic upscaling attempts, it does not necessarily present the full picture of damage evolution in the near-wellbore. A transient model of damage with data again derived from laboratory coreflood data could reveal more about well cleanup and progressive damage removal.

Steady-State Modeling. No API recommended practice for return permeability testing exists. Laboratories have their own procedures that comply broadly with recommended procedures developed some time ago. Operators and consultants, too, have their own procedures, which they often ask laboratories to follow. Although no recommended practice exists, evaluation of drilling and completion fluids usually involves measurement of a base permeability and remeasurement of a return permeability—or several—after application of the test fluid or fluids. In many cases, the laboratory removes the external mud cake or trims a slice of the end of the plug to measure return permeability without mud cake (Fig. 1).
In-Situ Combustion Frontal Stability Analysis
Authors: Zhu Zhouyuan , Liu Yanni , Liu Canhua , Kovscek Anthony R.
Published: April 2021

Because of complex chemical reactions and multiphase flow physics, the displacement front stability for in-situ combustion (ISC) enhanced oil recovery (EOR) processes are not well understood. In this work, theory and numerical simulation validation are presented to establish an analytical frontal stability criterion for ISC processes.

First, the four influencing factors for ISC displacement stability are analyzed: viscous force, heat conduction, matrix permeability changes caused by coke deposition, and gravity. A thorough analysis of the different zones and displacement fronts in a typical ISC process is conducted, and the most unstable front with the strongest tendency for gravity override is identified. Second, analytical solutions for judging the frontal stability and gravity override are established. Third, numerical reservoir simulation is performed to study the frontal stability and gravity override to validate the analytical theory. Carefully selected numerical schemes, as well as spatial and temporal discretization, are used to ensure the accuracy of these simulations.

The four major zones and three displacement fronts (combustion front, leading edge of steam plateau, and oil bank leading edge) are identified in a typical 1D ISC process. The most unstable front with the largest pressure gradient contrast is the leading edge of the steam plateau. Gravity override also first takes place here with large fluid density differences across the front. By establishing material and energy balances and solving the wavy perturbation of the steam front, an analytical equation for deciding the ISC flood front stability in a 2D horizontal plane is achieved. Furthermore, the analytical solution for ISC gravity override is established. In numerical simulations, we are able to obtain results with sufficient accuracy to capture unstable ISC displacements and show fingering behavior under different conditions. The matrix permeability reduction caused by coke deposition has minimal impact on frontal stability. The simulation results are successfully validated with the analytical work for conditions in which the ISC process is stable or unstable and also for the degree of ISC gravity override. This demonstrates the predictive capability of the analytical method.

In summary, a theoretical framework to analyze whether the displacement front of an ISC process is stable or not has been established. Numerical simulations confirm its predictive capability. This serves as a new reservoir engineering tool to aid the implementation and design of practical ISC projects.
Preparation of fluorescent beads under C. elegans for fluorescence microscopy with adaptive optics
Authors: Lin Ruizhe , Kipreos Edward T. , Kner Peter
Published: April 2021

We describe a protocol for the preparation of a sample of fluorescent beads under C. elegans. This type of sample is useful for research into the use of adaptive optics to correct sample-induced optical aberrations in fluorescence microscopy.
Efﬁcacy and Safety of Nepa in Preventing Nausea and Vomiting Induced by Multiple-day Chemotherapy in Patients With Refractory/relapsed Aggressive Non-hodgkin’s Lymphoma Undergoing Stem Cell Mobilization Prior to Autologous Hematopoietic Stem Cell Transplantation
Authors: Renzo Nicola Di , Musso Maurizio , Scimè Rosanna , Cupri Alessandra , Perrone Tommasina , De Risi Clara , Pastore Domenico , Guarini Attilio , Mengarelli Andrea , Benedetti Fabio , Mazza Patrizio , Capria Saveria , Chiusolo Patrizia , Cupelli Luca , Federico Vincenzo , Bozzoli Valentina , Messa Anna Rita , Matera Rosella , Seripa Davide , Codega Paolo , Bonizzoni Erminio , Specchia Giorgina
Published: April 2021

PurposePrevention of chemotherapy-induced nausea and vomiting (CINV) is particularly challenging for patients receiving highly emetogenic preparative regimens before autologous stem cell transplantation (ASCT) due to the daily and continuous emetogenic stimulus of the multiple day chemotherapy (MD-CT). While studies have shown effective prevention of CINV during the conditioning phase with NK1 receptor antagonist (NK1RA)-containing regimens, there have been no studies evaluating antiemetic use with MD-CT administered for mobilization of hematopoietic stem cells prior to ASCT. MethodsThis multicenter, open-label, phase IIa study evaluated the efﬁcacy of every-other-day dosing of NEPA administered during MD-CT being given for mobilization of stem cells prior to ASCT in patients with relapsed-refractory aggressive non-Hodgkin’s lymphoma. Eighty-one patients participated. ResultsResponse rates were 77.8% for complete response (no emesis and no rescue use), 72.8% for complete control (complete response and no more than mild nausea), 86.4% for no emesis, and 82.7% for no rescue use during the overall phase (duration of MD-CT through 48 hours after). NEPA was well tolerated with no treatment-related adverse events reported. ConclusionNEPA, administered with a simplified every-other-day schedule, show to be very effective in preventing CINV in patients at high risk of CINV undergoing MD-CT for mobilization of hematopoietic stem cells prior to ASCT.
Predicting ground subsidence due to long term oil/gas production in a Niger Delta basin, Nigeria: implications for CO2 EOR and geosequestration
Authors: Abija Fidelis Ankwo , Abam Tamunoene. K. S.
Published: April 2021

Reservoir pressure depletion with production leading to porosity loss, compaction and surface subsidence are the effect of effective stress changes and the imposition of the overburden stress which was partly supported by the fluids on the rock grain skeleton. Ground subsidence is associated with environmental hazards, failure of operational facilities and damages to infrastructures amounting to huge economic losses. In this studies, subsidence has been assessed using the Geertsma nucleus of strain based on predicted reservoir pressure. Depletion was estimated as percentage pore pressure dissipation and dynamically derived geomechanical and petrophysical rock properties determined. Reservoir porosity vary from 15% – 32%, shale volume from 11.2% − 88%, bulk compressibility range from 2.52–2.53 x 10− 6 /mPa, and uniaxial compaction coefficient 1.15–1.8 x 10− 6/mPa. The vertical compaction in a typical reservoir interval with a thickness of 31.0m varies from 0.002mm to 0.05mm at 10% formation pressure depletion, − 0.005mm to 0.27mm at 50% formation pressure drawdown and 0.007 to 0.53mm at 99% production and reservoir pressure dissipation. surface subsidence would range from 0.045mm to 0.35mm at 10% pressure depletion, 0.058mm to 1.8mm at 50% pressure depletion and 0.045mm to -3.47mm at full reservoir pressure drawdown. At a distance of 92.45km from the Niger Delta coastline, subsidence in the oilfield can still spread to the coastline, the deformation causing damages to the environment, operational facilities and infrastructures that amount to huge economic losses to the operators and government. We recommend the use of CO2 in EOR to maximize production, mitigate subsidence through ground rebound and keep carbon securely sequestered.
Antibacterial potential of new active compounds with biological performances with drugs modeling of pharmacokinetics study as source of bacterial drugs manufacture process and preparations
Authors: ahmed waseem , Azmant Rafia , Qayyum Abdul , Khan Shah Masaud , Ahmed Rasheed , Naz Saima
Published: April 2021

Adhatoda vasica and Calotropis procera was popular plants for its traditional medicinal materials as treatment of many bacterial diseases and skin disorders the class of group of chemicals were present in these medical plants as used of various medicines the new bioactive compounds as sources of various medicines the currently study was aim to obtained the higher antibacterial resilient biomolecules were measured through several advanced analytical techniques. The results showed that methanolic extracts and supercritical fluid extraction methods were best for higher yield of new compounds measurement process, after extraction the four structural compounds b-Sitosteryl linoleate, Myristyl diglucoside, D-Triglucopyranoside and S-allylcysteine acid were isolated in herbal plants, while the complete HPLC-DAD analyzed process with accuracy ,precision inter and intraday process all four compounds were done. The new drug design with apply of compartmental modelling of pharmacokinetics were apply on these four compounds check their potential level and capacity of measurements. The cytotoxicity test was analyzed in both plants at three concentrations (1, 0.4 and 8) in which 0.4 % showed the higher activity of LD which was 8 % in Calotropis procera extracts. The best activity of LD was recorded in methanol extracts over other six solvents (Methanol, Ethyl acetate, Chloroform, Hexane, Aqueous, and Ascorbic acid). It was concluded that the both species may act as the best resources of medicines in future uses an efficient and precise combinatorial quantitative analysis method and provided insight into the chemical constituents and development of various antibacterial drugs and explore this medical plants
Using Transfer Learning for Diabetic Retinopathy Stages Classification
Authors: Houby Enas M.F. El
Published: April 2021

Purpose – Diabetes is a chronic disease, that leads to damage of many systems of the body. One of the dangerous complications of diabetes is diabetic retinopathy. Frequent inspection for diabetic retinopathy is essential to recognize patients at risk of visual impairment. The disease grade level must be tracked to manage its progress and to start the appropriate decision for treatment in time. Effective automated methods for the detection of diabetic retinopathy and the classification of its severity stage are necessary. It also helps to decrease the burden on ophthalmologists and reduce diagnostic contradictions among manual readers. Methods– In this research, a convolutional neural network (CNN) is used based on color retinal fundus images for the detection of diabetic retinopathy (DR) and classification of its stages. CNN can recognize sophisticated features on the retina and so provide an automatic diagnosis. The pre-trained CNN model Visual Geometry Group (VGG) is applied on DR data using a transfer learning approach to utilize the already learnt parameters based on 1,000,000 images of ImageNet with 1000 classes.Results – By conducting different experiments with different classes setting the built models achieved promising results. The best achieved accuracies for 2-ary, 3-ary, 4-ary, and 5-ary classification are 85.99, 80.5, 61.28, and 71, respectively.
Optimized MLCNN for Personalized News Recommendation Based on Social Media Harnessing Using Modified Genetic Algorithm
Authors: Manoharan Saravanapriya , senthilkumar radha , J Saktheewaran , A Kannan
Published: April 2021

Classification of label-specific users’ diversified interests is the most formidable task in personalized news recommendation systems (PNRS). To bring personalization to PNRS, many remarkable features have to be considered from their user profile to classify their interest. In this paper, 13, 346 features are considered per user to classify their interest for 15 labels using Multi-label Convolution Neural Network (MLCNN). The efficiency of MLCNN highly depends on its architecture through the tuning of its hyper parameters. Generally, researchers have manually designed a constant CNN architecture for each label and every label and verified the effectiveness, but this leads to additional complexity as well as large computational resources were consumed. Moreover, Designing the structure for all 15 labels leads to an increase in network structure exponentially with an increase in labels. Hence, in this paper, MLCNN architectures are optimized by implementing a novel approach Modified Genetic Algorithm (MGA) with the help of introducing four novel crossover operators to strengthen CNN performance for users interest classification. Further, for the recommendation process, the label-specific news articles were clustered from social media Facebook and Twitter feeds, and then most popular news articles were determined along with label-specific breaking news articles rendered from news feeds concerning users’ interest. The experimental result precisely proves that the proposed approach MGA attained an accuracy of 89.64%, 90.56%, 90.41%, and 91.79% for classifying users label specific interest and label-wise recommendation accuracy attained 93.3%, 90%, 90% from Twitter, Facebook, and also from Newsfeed respectively.
Conditional Survival After Surgical Resection of Appendiceal Tumors: a Population-based Study
Authors: Zhao Shutao , Lu Chang , Li Junan , Zhang Chao , Wang Xudong
Published: April 2021

Background: This study aimed to evaluate the conditional survival (CS) of appendiceal tumors (ATs) after surgery.Methods: A total of 3,031 patients with ATs who underwent surgery were included in the Surveillance Epidemiology and End Results (SEER) database from 2004 to 2016. A multivariate Cox regression model was used to analyze the prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). CS was used to calculate the probability of survival for another 3 years after the patient had survived x years. The formulas were COS3 = OS (x + 3) /OS (x), and CCS3 = CSS (x + 3)/CSS (x).Results: The 1-year, 3-year, and 5-year OSs for all patients were 95.6%, 83.3%, and 73.9%, respectively, while the 1-year, 3-year, and 5-year CSSs were 97.0%, 87.1%, and 79.9%, respectively. Age, grade, histology, N stage, carcinoembryonic antigen (CEA), and radiation were independent prognostic factors for OS and CSS. For patients that survived for 1 year, 3 years, and 5 years, their COS3s were 81.7%, 83.9%, and 87.0%, respectively. The CCS3s were 85.5%, 88.3%, and 92.0% respectively. In patients with poor clinicopathological factors, COS3 and CCS3 increased significantly, and the survival gap between OS and COS3, CSS and CCS3 was more obvious.Conclusions: CS for appendiceal tumors were dynamic and increased over time, especially in patients with poor prognosis.
A Design Approach Of Mechanical Assemblies Based On MBSE And CAD Models Interoperability
Authors: Brahmi Rihab , Belhadj Imen , Hammadi Moncef , Aifaoui Nizar , Choley Jean-Yves
Published: April 2021

The technological development of the last decades have been able to push human to develop their needs, so a way to new demands were opened and this can lead to a complexity problem. Thereby, a good interoperability between the product design activities can lead to the possibility of ensuring a promising satisfaction to all requirements. However, the major problem is the enormous discontinuity between them. Indeed, each one treats the product from its point of view without recourse to the requirements defined by others. This paper is interested in the collaborative work that brings together the system engineer, who deals with the system from a global view, and the designer, who is a specialist in the detailed design, in order to validate requirements. A new methodology has been proposed to define the role of each one in the design process. This methodology focuses on the product development cycle from the analysis of needs to the validation phase. This obviously requires interoperability between the two domains of Model Based System Engineering (MBSE) and Computer Aided Design (CAD). Based on a pedal bicycle case study which is an industrial mechatronic product, the proposed methodology will be illustrated for validation and highlighting its advantages and limitations.
Atomistic mechanisms for frictional energy dissipation during continuous sliding
Authors: Krylov Sergei , Frenken Joost
Published: April 2021

From a first-principles-based analysis, atomistic mechanisms of frictional energy dissipation are established. For a rigid object moving continuously in the periodic surface potential landscape of a solid that has vibrational degrees of freedom, they can be viewed as (i) the continuous pumping of energy into the resonant modes, if these exist, and (ii) the destructive interference of the force contributions introduced by all excited phonon modes. We report a surprising, mutual compensation between these two basic effects, which leads to very regular oscillations of the dissipative force, with a period determined by half the period of the solid lattice, while the mean friction force experienced by the sliding object hardly depends on time and varies in a straightforward manner with the sliding velocity. These mechanisms act already in a purely dynamic system that includes independent, non-interacting phonon modes, and they manifest irreversibility as a kind of "dynamical stochastization". In contrast to wide-spread views, we show that transformation of mechanical energy into heat, that always takes place in real systems due to the coupling between phonon modes, can play only a minor role in the appearance of friction, if any. This insight into the microscopic mechanisms of energy dissipation opens a new, direct way towards true control over friction.
Segmentation of Biventricle in Cardiac Cine MRI via Nested Capsule Dense Network
Authors: Hu Yuhang , Zhang Yajuan , Zhang Hongyang , Shen Weihao , Zhou Shoujun , Guo Shijie , Wang Yuanquan
Published: April 2021

Cardiac magnetic resonance image (MRI) has been widely used in diagnosis of cardiovascular diseases because of its noninvasive nature and high image quality. The evaluation standard of physiological indexes in cardiac diagnosis is essentially the accuracy of segmentation of left ventricle (LV) and right ventricle (RV) in cardiac MRI. In this paper, we propose a novel Nested Capsule Dense Network (NCDN) structure based on the FC-DenseNet model and capsule convolution-capsule deconvolution. Different from the traditional symmetric single codec network structure such as U-net, NCDN uses multiple codecs instead of a single codec to achieve multi-resolution, which makes it possible to save more spatial information and improve the robustness of the model. The proposed model is tested on three datasets that includes York University Cardiac MRI dataset, Automated Cardiac Diagnosis Challenge (ACDC-2017), and local dataset. The results show that the proposed NCDN outperforms the state-of-the-art methods.
Implementation of Non Destructive FTNIR Method for Quick Estimation of Peanut Quality Based on FFA and Peroxide Value
Authors: Raigar Rakesh Kumar Kumar , Srivast Shubhangi , Mishra Hari Niwas
Published: April 2021

The possibility of rapid estimation of moisture, protein, fat, free fatty acid (FFA), and peroxide value (PV) content in peanut kernel was studied by Fourier transform near-infrared spectroscopy (FTNIR) in the diffuse reflectance mode along with chemometric technic. The moisture, fat and protein of fresh and damaged seeds of peanuts ranging from 3 to 9 %, 45 to 57 % and 23 to 27 % respectively, were used for the calibration model building based on partial least squares (PLS) regression. The peanut samples had major peaks at wavenumbers 53.0853, 4954.98, 4464.03, 4070.85, 74.75.63, 8230.21, and 6178.13 in per cm. First and second derivate mathematical preprocessing was also applied in order to eliminate multiple baseline for different chemical quality parameters of peanut. The FFA had the lowest value of calibration and validation errors (0.579 and 0.738) followed by the protein (0.736 and 0.765). The quality of peanut seeds with lowest root mean square error of cross validation of 0.76 and maximum correlation coefficient (R2) of 96.8 was obtained. The comprehensive results signify that FT-NIR spectroscopy can be used for rapid, non destructive quantification of quality parameters in peanut.
Complexation Of Amino Acid With Cadmium And Its Application To Remove Cadmium From Contaminated Soil
Authors: Yao Wenbin , Yang Zhihui , Huang Lei , Su Changqing
Published: April 2021

Low molecular organic acids, such as amino acid, play an important role in cadmium (Cd) mobility. However, its complexation ability with Cd was not well studied. The complexation structure of amino and cadmium was investigated by theory calculation based on B3ly/SDD and detecting by FTIR spectrum. The conformers were found to be [COc, COc] for fatty amino-cadmium and PheCd2+, [COc, COc, COs] for GluCd2+and ThrCd2+, respectively. The complex energy of these conformers was calculated in water phase by SMD model and the order of chelation energy was; PheCd2+> AlaCd2+ > LeuCd2+ > GluCd2+ > GlyCd2+ > ThrCd2+. All the dissolving energy of complexes was below zero, indicating these complexes was easily dissolved in water. In aqueous solution experiment, the Cd2+ concentration decreased with increasing amino acid concentration. The order of logβ (Complex stability constant) was: PheCd2+> AlaCd2+ > LeuCd2+ > GluCd2+ > GlyCd2+ > ThrCd2+, consisting with the order of calculated chelation energy. The Cd removal efficiency by Thr, Glu, Gly, Ala, Leu and Phe were 38.88%, 37.47%, 35.5%, 34.72%, 34.04% and 31.99%, respectively. From soil batch experiment, the total Cd in soil was decreased in present of amino acid with the concentration of Cd in water increased from 231.97 µg/L to 652.94-793.51 µg/L. The results of BCR sequential extraction showed that the Cd in acid soluble and reducible fraction sharply decreased. From all the results, the amino acid has potential to be used as a chelation to remedy the Cd contaminated soil.
Physical functioning and perceived health status after surviving the first COVID-19 wave. A long-term observational perspective
Authors: Ferrarello Francesco , Iacopino Carmela , Pierinelli Catia
Published: April 2021

After the COVID-19 infection, individuals can experience impairment, activity limitation and participation restriction. Little information is available on range and frequency of individual problems arising after COVID-19 and its sequelae and long-term outcomes. In June and July 2020, nineteen individuals previously hospitalized with COVID-19 were referred to our outpatient physiotherapy unit. We monitored their level of independence in activities of daily living, mobility, and perceived health status for 7.4–9.5 months (median, 8.6) after healing. At baseline, our cohort showed substantial independence in activities of daily living, some mobility limitations, and below average perceived health status. Measures improved over time. Limitations of physical functioning were mostly moderate to slight and tending to improve; if present, severe limitations were probably related to pre- COVID-19 conditions. However, individuals in some cases may not have fully recovered their premorbid functioning seven to nine months after healing.
Total flavone of Abelmoschus Manihot improves colitis by promoting growth of Akkermansia in mice
Authors: Bu Fan , Ding Yang , Chen Tuo , Wang Rong , Wang Qiong , Zhou Jin-Yong , Jiang Feng , Zhang Dan , Xu Minmin , Shi Guoping , Chen Yugen
Published: April 2021

The total flavone of Abelmoschus manihot (TFA), a compound extracted from the flowers of Abelmoschus manihot (L.) Medic, has been widely used for the treatment of Crohn's disease, chronic glomerulonephritis and other diseases. The aim of this study was to investigate the effect of TFA on gut microbiota and intestinal barrier in dextran sulfate sodium (DSS) induced experimental colitis. C57BL/6J mice were treated with 2.5% DSS in drinking water to induce colitis. Mice were orally administrated with TFA (62.5mg/kg, 125mg/kg) or prednisone acetate (PAT, 2.5mg/kg) once daily for 7 days. Biological samples were collected for analysis of inflammation cytokines, gut microbiota and intestinal barrier integrity. TFA-H (125mg/kg) markedly attenuated DSS-induced colon shortening and histological injury in experimental colitis. The therapeutic effect was similar with PAT administration. TFA-H notably modulated the dysbiosis of gut microbiota induced by DSS and greatly enriched the Akkermansia muciniphila (A. muciniphila). Moreover, TFA-H remarkably ameliorated colonic inflammatory response and intestinal epithelial barrier dysfunction. Interestingly, TFA directly promotes the growth of A. muciniphila in vitro. Taken together, the results for the first time revealed that TFA, as a prebiotic of A. muciniphila, improved DSS-induced experimental colitis, at least partly through modulating gut microflora profile to maintain the colonic integrity and inhibit inflammation response.
Pharmacological Interventions on The Dopamine Motivation System Effectively Disturbed Cue-Induced Memory Reconsolidation Cocaine-Seeking Behavior for Rats
Authors: Li Yang , Li Nan , Qu Liang , Wang Xin , Wang Ping , Fu Jian , Chen Yu-kun , Wang Jian-cai , Ge Shun-nan , Wang Xue-lian
Published: April 2021

Drug addiction is a disorder related to dysfunction in the neural reward memory circuits, and it is characterized by compulsive drug use despite terrible negative consequences. Memory reconsolidation, during which aroused memory is easy to strengthening, weakening or updating, plays an extremely important role in drug addiction. Effectively interfering with the drug memory reconsolidation process would be key in treating drug addiction, but this intervention currently remains impossible. The dopamine motivation system has been widely recognized as an important system for reward, but whether the dopamine motivation system participates in drug memory reconsolidation is unclear. We aimed to explore the role of the dopamine motivation system during the cue-induced cocaine memory reconsolidation process by examining the effect of different pharmacological interventions on the dopamine motivation system during cue-induced cocaine self-administration-related memory reconsolidation drug-seeking behavior. Using a combined behavioral and biological method, our results showed that high concentrations of SCH 23390 and raclopride, or VTA lesions, could effectively disturb subsequent cue-induced cocaine self-administration-related memory reconsolidation drug-seeking behavior in rats. However, low concentrations of SCH 23390 and raclopride could not block this behavior. In summary, only a high dose of dopamine D1 and D2 receptor antagonists, or VTA lesions, could effectively disturb subsequent cue-induced cocaine self-administration-related memory reconsolidation drug-seeking behavior. These findings indicated that pharmacological interventions in the dopamine motivation system could effectively disturb subsequent cue-induced drug memory reconsolidation. Thus, pharmacological interventions on the dopamine motivation system might have therapeutic potential for drug addiction.
Dynamic Pricing Game in a Dual-channel Closed-loop Supply Chain with Heterogeneous Players and Delay Decision
Authors: Zhang Yuhao , Zhang Tao
Published: April 2021

In this paper, we study a dual-channel closed-loop supply chain(CLSC), where the manufacturer wholesales the new product through the traditional retail channel and distributes the remanufactured product via a direct channel established by himself. We focus on developing two dynamic Stackelberg game models under the assumption of the retailer is an adaptive agent and the manufacturer is a bounded rational player with non-delay and delay decisions. The existence and locally asymptotic stability of Nash equilibrium is investigated, and also the complex dynamics of each model is illustrated including period-doubling bifurcation, Neimark-Sacker bifurcation, strange attractor and chaotic phenomena. Numerical simulations are conducted to examine the impacts of key parameters on the complex behaviors of the long-run dynamic Stackelberg game and the performance of chain members under various scenarios. The results reveal that the excessively high value of the price adjustment speed of the manufacturer, the consumer discount perception for the remanufactured product as well as the consumer preference degree to the direct channel have adestabilization effect on the Nash equilibrium. Besides, the delay decision adopted by manufacturer no matter in the traditional or direct channel does not always necessarily make the system more stable, but the appropriately delay weights can expand the stability domain of the system. Moreover, the manufacturer would suffer a significant profit loss while the retailer can capture more profits when the dual-channel CLSC system falls into periodic cycles and chaos motions. At last, the variable feedback control method is utilized to eliminate the delayed system chaos.
A Smart IoT System for Remote Refrigeration Monitoring
Authors: Padmaja B , Ch Vijayakumar , Patro E Krishna Rao , Shashirekha B
Published: April 2021

The realm of refrigeration industry has marked its significance for storing food and beverages. Refrigeration warehouses are extensively used to store various combinations of large fresh food stock at favourable temperatures to maintain its quality. Any deviations from these favourable temperatures pose negative impacts on the cold stock. Hence, it is essential to minimize the margin of these potential risks that can incur huge loss to the cold-storage industries. On-site evaluation can be reliable to address these risks, but it is time consuming and an inefficient process as human intervention can be prone to manual errors. The paper, therefore, proposes a methodology to build a smart IoT system to remotely monitor and evaluate the refrigeration warehouses seamlessly at one’s fingertips using a mobile or laptop through dashboards. Furthermore, this paper addresses the difficulties in managing and analysing the large sensory data which are the result of seamless monitoring by unleashing the power of edge computing and cloud computing.
A New Model for Early Prediction of Persistent Low-Lying Placenta
Authors: Farladansky-Gershnabel Sivan , Gluska Hadar , Sharon-Weiner Maya , Shechter-Maor Gil , Schreiber Hanoch , Weitzner Omer , Biron-Shental Tal , Markovitch Ofer
Published: April 2021

Objective

Finding a predictive model for persistent low lying placenta (LLP) based on early clinical and laboratory parameters.
Methods

This retrospective cohort study included patients with LLP detected during early anatomy scan. Additional transvaginal ultrasound exams assessed for resolution at 22–24 weeks and 36–39 weeks. Patients were categorized as: Group 1–LLP resolved by the second trimester scan, Group 2- LLP resolved by the third, and Group 3–LLP persisted to delivery. Clinical and laboratory parameters were compared between groups. A linear support vector machine classification was used to define a prediction model for persistence.
Results

Among 236 pregnancies with LLP, 80% resolved by 22–24 weeks, 10.5% resolved by 36–39 weeks and 9.5% persisted until delivery. Second trimester hCG levels were higher the longer the LLP persisted (0.8MoM + 0.7 vs. 1.13MoM + 0.4 vs. 1.7MoM + 1.5, P = 0.03, respectively) and Cervical length was shorter (P = 0.008, P = 0.02, respectively). A linear SVM classification model was calculated based on these parameters. The predictive accuracy of this model was 90.3%.
Conclusion

LLP persistence can be predicted with an accuracy of 90.3%, as early as the beginning of the second trimester. Persistence vs. resolution of LLP may represent different entities and not a spectrum of the same condition over time.
Subcellular Receptor Localization in the Substantia Nigra in a Superecliptic pHlourin-Tagged D2 Receptor Knockin Mouse
Authors: Trinkle Mason , Lebowitz Jospeph J. , Robinson Brooks , Balcita-Pedicino Judith Joyce , Hetelekides Savas , Bunzow James R. , Aicher Sue , Williams John T. , Sesack Susan R.
Published: April 2021

Dopamine neurons use autoregulation for appropriate modulation of goal-directed behaviors, and yet the mechanisms for D2 receptor (D2R)-mediated autoregulation are not fully understood. Electrophysiology suggests close proximity between dopamine release and receipt, but actual dendro-dendritic synapses are rare. This ultrastructural study used transgenic mice with a knockin of superecliptic green fluorescent protein (SEP) on the D2R (SEP-D2R) to determine how often autoreceptors are localized at directly apposed dendrites in the substantia nigra pars compacta (SNc). Silver-enhanced immunogold labeling for SEP-D2R was observed within dendrites, axon varicosities, astrocytes, and soma. Although most gold particles were intracellular, 28% of SEP-D2R gold was irregularly distributed along the plasma membrane. Structures immediately adjacent to dendritic membrane gold particles were axons (40%), astrocytes (19%), and other dendrites (7%), with the remaining structures unidentified in single sections. Known limitations in antibody penetration suggest the actual incidence of D2R localization at apposed dendrites is probably greater than 7%. Nevertheless, these results indicate that intercellular dopamine communication in the SNc is primarily extrasynaptic. The thin astrocytic processes often seen separating adjacent dendrites may provide channels along which transmitter diffuses to access dendritic D2Rs. Expression of D2Rs by the astrocytes themselves suggests they may participate in dopamine autoregulation. A novel finding of SEP-D2R on the axon initial segments (AISs) of SNc neurons was confirmed by immunofluorescence to involve dopamine cells. While some of this may represent axonal trafficking, membrane D2Rs might serve an autoregulatory function at the AIS yet to be physiologically characterized for dopamine neurons.