bluuebunny/crossref_metadata_2025 huggingface dataset:
Overflush and Hydraulic Fracturing: Playing Poker with Your Completion
Authors: Rylance Martin
Published: August 2023

Since the inception of hydraulic fracturing, the industry has wrestled with the concept of over-/underflushing and has always pitched this as a binary philosophy, attempting to determine/define whether this is either a fundamentally good or a bad approach. This schism simply grew with the extensive development of unconventionals; the use of overflush being an inherent and fundamental requirement for an effective and economic unconventional completion sequence. This paper will demonstrate that the true answer, as any engineer would expect, is that a detailed assessment is what is required on a case-by-case basis.

The paper will describe and reference several fracturing case histories in both the conventional and unconventional environments where the application of an overflush, an underflush, or an engineered approach has been assessed or applied. Rather than taking an easy headline grabbing route to perpetuate the myth that the process is a major paradigm or simply either a good or a bad thing, this paper will discuss some of the key aspects that impact the suitability of one approach over another and how engineering the implementation can lead to a broader range of applicability/suitability for the most economically effective outcome. This includes an appreciation of the production/economic profile and exposure to risk, which are hugely different in, say, an ultradeep-water five well offshore development vs. a field development with some 100s to 1,000s of wells in a lower-cost onshore environment.

The paper will describe and demonstrate some of the fundamental variables that need to be considered, attempting to elaborate on a few of the key parameters that can influence the effective outcome. The paper will also indicate that there are several different scenarios whereby any form of overflush can result in a detrimental impact on the production rate and estimated ultimate recovery (EUR) and that these must be fully appreciated. Subtleties, related to reservoir characteristics and fracture geometry, should be examined and appreciated. Additional aspects such as how production, drawdown, and pore pressure will be managed can also have an impact. All these considerations, and more, will be discussed, described, and referenced.

While there is no doubt that the overflush debate will continue unabated, the intent of this paper is to reduce the damage (or uncertainty), one way or the other, that will result. It is an attempt, at a minimum, to ensure that the debate becomes solely a technical one related to the approaches to be taken rather than a black and white one of right or wrong. Ultimately, the paper will advise, and inform, that the approach should be fully considered, engineered in detail and tailored to each, and every application and that as a result is no longer simply considered a binary question.
Multiparameter Inversion of Reservoirs Based on Deep Learning
Authors: Liu Zhi , Hao Yuxiang , Li Daolun , Zha Wenshu , Shen Luhang
Published: August 2023

Reservoir parameter inversion is an important technique in oil and gas exploration and development that can estimate the reservoir physical properties, such as skin factor and permeability, using observed data, such as well test data and production data. In this paper, we propose a physical accelerated neural network with multiple residual blocks (PRNN-Acc) for multiple parameter inversion of the seepage equation with a source term and a sink term. PRNN-Acc is based on the idea of physical residual neural network (PRNN), which uses deep neural networks to approximate the solution and parameter spaces of partial differential equations. PRNN-Acc adds multiple residual blocks to enhance the expression ability and flexibility of the network and avoid gradient explosion or degeneration phenomena. In addition, the input of PRNN-Acc is multiplied by three adaptive parameters, which can adjust the network training process according to the characteristics of the data and loss function and improve the accuracy and stability of the inversion. We use bottomhole pressure (BHP) data before and after shut-in as labels to invert multiple parameters for homogeneous and heterogeneous reservoirs. In this paper, three numerical experiments are designed. For homogeneous and heterogeneous reservoirs, the inversion results of this method are up to 36 times more accurate than those of PRNN. It is fully proven that the inversion effect of this method is better than that of PRNN.
Rapid sea level rise causes loss of seagrass meadows
Authors: Capistrant-Fossa Kyle , Dunton Kenneth
Published: August 2023

As global declines in seagrass populations continue to cause great concern, long-term assessment of seagrass meadows show promise in providing valuable insights into fundamental causes of seagrass loss and drivers of environmental change. Here we report two long-term records of seagrass presence in western Gulf of Mexico coastal waters that provided insight into their rapid decline in a relatively pristine ecosystem. Coincident with unprecedented increases in water depth starting in 2014 (14-25 mm y-1), monthly measurements at a “deep edge” fixed station revealed that two ubiquitous seagrass species (Halodule wrightii and Syringodium filiforme) vanished altogether in just five years; a subsequent basin wide assessment revealed that seagrasses disappeared at 23% of 144 sentinel stations. Models that incorporate differing sea level rise scenarios and water depth thresholds reveal additional global losses of seagrass habitat (14,000 km2), with expansion into newly created shallow habitats further exacerbated by hardened shorelines
SNM1A (DCLRE1A) is crucial for efficient repair of complex DNA breaks in human cells
Authors: McHugh Peter , Swift Lonnie , Lagerholm B. Christoffer , Baddock Hannah , Henderson Lucy , Ratnaweera Malitha , Sengerova Blanka , Lee Sook , Cruz-Migoni Abimael , Waithe Dominic , Renz Christian , Ulrich Helle , Newman Joseph , Schofield Christopher
Published: August 2023

DNA double-strand breaks (DSBs), such as those produced by radiation and radiomimetics, are amongst the most toxic forms of cellular damage, in part because they involve extensive oxidative modifications at the break termini. Prior to completion of DSB repair, the chemically modified termini must be removed. Various DNA processing enzymes have been implicated in the processing of these ‘dirty ends’, but molecular knowledge of this process is limited. Here, we demonstrate a role for the metallo-β-lactamase fold 5′-3′ exonuclease SNM1A in this vital process. Cells disrupted for SNM1A manifest increased sensitivity to radiation and radiomimetic agents and show defects in DSB damage repair. SNM1A is recruited and is retained at the sites of DSB damage via the concerted action of its three highly conserved PBZ, PIP box and UBZ interaction domains, which mediate interactions with poly-ADP-ribose chains, PCNA and the ubiquitinated form of PCNA, respectively. SNM1A can resect DNA containing oxidative lesions induced by radiation damage at break termini. The combined results reveal a crucial role for SNM1A to digest chemically modified DNA during the repair of DSBs and imply that the catalytic domain of SNM1A is an attractive target for potentiation of radiotherapy.
Carcass Yield and Haematological Response of Broiler Chickens to Spotted Pumpkin (Lagenaria Breviflora Robert) Fruit Extract
Authors: ADELEYE OLUWAGBEMIGA , ABATAN MUNIRAT , OLORUNSOGBON BERNARD , KOLAWOLE AMOS , SONIBARE A. O. , EGBEYALE L. T.
Published: August 2023

BACKGROUND
Over the years, therapeutic application of plants has been used in folkloric medicine to explore natural alternatives to usage of antibiotic growth promoters due to the development of resistant bacteria strains and presence of drug residues in poultry meat. This study investigated the effects of concentrations and frequencies of administration of Lagenaria breviflora fruit extract (LBFE) on the haematological indices and carcass yield of broiler chickens. 390 birds were randomly distributed into 8 treatments; T1: control, T2: 75 g of LBFE/litre as synthetic antibiotic replacer (SAR) when necessary, T3: 75 g of LBFE/litre for 3days/week, T4: 75 g of LBFE/litre for 5days/week, T5: control, T6: 125 g of LBFE/litre as SAR, T7: 125 g of LBFE/litre for 3days/week and T8: 125 g of LBFE/litre for 5days/week. The experiment was laid out in a 2×4 factorial and data were subjected to Completely Randomized Design. Packed cell volume (PCV), red blood cell count (RBC), white blood cell count (WBC) and haemoglobin (HB) were determined using improved Neubaur Haemycytometer after dilution and Cyanomethamoglobin methods. Dressing percentage for the carcass yield were also obtained.
RESULTS
Eosinophil counts and Uric acid were significantly (p < 0.05) highest in birds administered 75 g of LBFE/ litre of water 5days/week. At the finisher phase, Packed cell volume was significantly (P < 0.05) highest (32.25) in birds administered 75 g of LBFE/ litre of water 5days/week, while birds administered 125 g of LBFE/ litre of water as antibiotic replacement had significantly (P < 0.05) highest (5.00) red blood cell count. The thigh and liver of birds administered LBFE 3 days/week had the highest values (P < 0.5) of 10.79% and 2.84% respectively.
CONCLUSION
The study infers that administration of LBFE to broilers enhances the haematological indices as well as carcass yield which ultimately promotes healthy living of the birds.
Bevel gear transmission error test method based on strain method
Authors: zhang jian , Lv ChuanMao , li ZhengMinQing
Published: August 2023

The testing and measurement of dynamic transmission error in cone gears is highly challenging in oil-based environments, where conventional testing methods are often limited in scope. To address this issue, a testing method utilizing strain sensors was proposed to measure dynamic transmission error in cone gears. To verify the feasibility of this testing method, a testing platform was designed and constructed specifically for cone gear transmission error testing. During the testing process, temperature-induced interference was compensated using a quarter-bridge configuration to enhance the reliability of test data. Additionally, a magnetic grid method was used to synchronously measure dynamic transmission error in cone gears. Comparative analysis of test results from the two different testing methods was conducted under various operational conditions of the cone gears. The comparison successfully verified the feasibility of the stress-strain-stiffness method in measuring dynamic transmission error in cone gears. This study provides a new, quick, simple, and practical testing method for measuring dynamic transmission error in cone gears, which can be valuable for academic research and practical applications.
Geochemical Modeling of the Mantle Partial Melting using Heuristic Exploration: An Optimization Model Applied to Earth Sciences
Authors: Soto-Villalobos Roberto , López Mario A. Aguirre , Walle-García Otoniel , Benavides-Bravo Francisco Gerardo , Almaguer-Martínez F-Javier , Méndez-Delgado S. , Velasco-Tapia Fernando
Published: August 2023

An evolution strategy-type heuristic simulation tool was developed to optimize the mantle partial melting inverse modeling. An objective or fitness function was derived from the batch equation to model the source composition and the partial melting degree from the chemistry of near primary liquids. In the search algorithm structure was considered: (a) the geochemical system constraints, (b) an initialization step, and (c) a procedure of mutation and heuristic individual selection. The heuristic simulation was successfully applied in four study cases, as mineralogical and rare earth element (REE) composition of known peridotitic sources. Partial melting conditions were reproduced with a deviation ≤ 10−6 in a reasonably practical time (∼ 2 hours) by using a desktop computer.
Phylogeny and Molecular evolution of the first local Monkeypox virus cluster in Guangdong Province, China
Authors: Zhao Wei , Yu Jianhai , Zhang Xin , Liu Jiajun , Xiang Linlin , Huang Shen , Xie Xiaoting , Fang Ling , Lin Yifan , Zhang Meng , Wang Linqing , He Jianfeng , Zhang Bao , Di Biao , Peng Bo , Liang Jingtao , Sheng Chenguang , Li Baisheng
Published: August 2023

The first local monkeypox (MPX) outbreak in Guangdong Province, China occurred in June 2023. However, epidemiological data failed to quickly identify the import source and transmission of the outbreak. In this study, phylogenetic and molecular evolutionary of 10 monkeypox virus (MPXV) genome sequences from Guangdong outbreak were rapidly characterized, revealing that local hidden transmissions may have occurred in Guangdong, and showing molecular epidemiological correlation of MPX outbreaks in several regions of China at the same period. The Guangdong MPXV cluster showed a further evolutionary distance than that of Japan, separated 39 single-nucleotide polymorphisms from B.1 lineage comprising 23 non-synonymous mutations in genes linked to host regulation, virus infection and virus life cycle, and displayed a unique mutation spectrum related to APOBEC3 editing, promoting the rapid viral evolution and diversification. All these findings contribute to understanding of the ongoing MPX outbreak in China, offer insights for Joint prevention and control strategies.
Digitally-Enhanced Dog Behavioral Testing: Getting Help from the Machine
Authors: Farhat Nareed H. , Lazebnik Teddy , Monteny Joke , Moons Christel Palmyre Henri , Wydooghe Eline , Linden Dirk van der , Zamansky Anna
Published: August 2023

The assessment of behavioral traits in dogs is a well-studied challenge due to its many practical applications such as selection for breeding, prediction of working aptitude, chances of being adopted, etc. Most methods for assessing behavioral traits are questionnaire or observation-based, which require a significant amount of time, effort and expertise. In addition, these methods are also susceptible to subjectivity and bias, making them less reliable. In this study, we proposed an automated computational approach that may provide a more objective, robust and resource-efficient alternative to current solutions. Using part of a Stranger Test protocol, we tested (n=53) dogs for their response to the presence and benign actions of a stranger. Dog coping styles were scored by three experts. Moreover, data were collected from their handlers using the Canine Behavioral Assessment and Research Questionnaire (C-BARQ) . An unsupervised clustering of the dogs' trajectories revealed two main clusters showing a significant difference in the stranger-directed fear C-BARQ factor, as well as a good separation between (sufficiently) relaxed dogs and dogs with excessive behaviors towards strangers based on expert scoring. Based on the clustering, we obtained a machine learning classifier for expert scoring of coping styles towards strangers, which reached an accuracy of 78%. We also obtained a regression model predicting C-BARQ factor scores with varying performance, the best being Owner-Directed Aggression (with a mean average error of 0.108) and Excitability (with a mean square error of 0.032). This case study demonstrates a novel paradigm of digitally enhanced canine behavioral testing.
Assessment of Dietary Patterns in Celiac Disease Patients Using Factor Analysis Method and Its Relationship with Dietary Intake and Anthropometric Measurements in Iran
Authors: Morvaridi Mehrnaz , Sadeghi Narges , Alavinejad Pezhman , Sadeghian Mehdi , Tahvilian Negin , Behbahani Hossein Bavi , Farsi Farnaz
Published: August 2023

Background/Objectives:
Celiac disease (CD) is a systemic and autoimmune enteropathy of the gastrointestinal tract with malabsorption characteristics. The only effective treatment for CD is to strict adherence a gluten-free diet (GFD) throughout life. the objective of this study was evaluated the dietary patterns in celiac disease patients and its relationship with dietary intake and anthropometric measurements in Iran.
Subjects/Methods:
This is a case control study on 110 patients with celiac disease who were referred to the Celiac Association of Khuzestan, Iran. Nutritional information was collected using a validated 147-item semi-quantitative food frequency questionnaire (FFQ). The software Stata (StataCorp, Version 14.0) was used to analyze the data. Principal component analysis (PCA) was used to obtain patients' dietary patterns.
Results
There was a significant relationship between age, BMI, and total energy intake with quartiles of healthy dietary pattern score (P < 0.001, P = 0.001, and P = 0.001, respectively). Also, there was a significant relationship between total energy intake with quartiles of unhealthy dietary pattern score and traditional dietary pattern (P < 0.001 and p = 0.005 respectively). Moreover, there was a significant association of odd ratio for celiac disease and traditional dietary pattern score.
Conclusions
The main findings of our study revealed that the patients who consumed healthy dietary patterns had lower odds ratio of the celiac disease incidence. Although, the rate of adhere to healthy eating pattern was related to increase BMI and daily calorie intake with rising age of participants.
Quantum scaling atomic superheterodyne receiver
Authors: Zhang Peng , Jing Mingyong , wang Zheng , Peng Yan , Yuan Shaoxin , Zhang Hao , Xiao Liantuan , Jia Suotang , Zhang Linjie
Published: August 2023

Measurement sensitivity is one of the critical indicators for Rydberg atomic radio receivers. This work quantitatively studies the relationship between the atomic superheterodyne receiver's sensitivity and the number of atoms involved in the measurement. The atom number is changed by adjusting the length of the interaction area. The results show that for the ideal case, the sensitivity of the atomic superheterodyne receiver exhibits a quantum scaling: the amplitude of its output signal is proportional to the atom number, and the amplitude of its read-out noise is proportional to the square root of the atom number. Hence, its sensitivity is inversely proportional to the square root of the atom number. This work also gives a detailed discussion of the properties of transit noise in atomic receivers and the influence of some non-ideal factors on sensitivity scaling. This work is significant in the field of atom-based quantum precision measurements.
Failure patterns of locoregional recurrence after reducing target volumes in patients with nasopharyngeal carcinoma receiving adaptive replanning during intensity-modulated radiotherapy: A single-center experience in China
Authors: Zhou Xiate , Zhu Jian , Zhou Chao , Wang Wei , Ding Weijun , Chen Meng , Chen Kuifei , Li Shuling , Chen Xiaofeng , Yang Haihua
Published: August 2023

Background
Previous researches have demonstrated that adaptive replanning during intensity-modulated radiation therapy (IMRT) could enhance the prognosis of patients with nasopharyngeal carcinoma (NPC). However, the delineation of replanning target volumes remains unclear. This study aimed to evaluate the feasibility of reducing target volumes through adaptive replanning during IMRT by analyzing long-term survival outcomes and failure patterns of locoregional recurrence in NPC.
Methods
This study enrolled consecutive NPC patients who received IMRT at our hospital between August 2011 and April 2018. Patients with initially diagnosed, histologically verified, non-metastatic nasopharyngeal cancer were eligible for participation in this study. The location and extent of locoregional recurrences were transferred to pretreatment planning computed tomography for dosimetry analysis.
Results
Among 274 patients, 100 (36.5%) received IMRT without replanning and 174 (63.5%) received IMRT with replanning. Five-year rates of locoregional recurrence-free survival (LRFS) were 90.1% (95%CI, 84.8–95.4%) and 80.8% (95%CI, 72.0–89.6%) for patients with and without replanning, p = 0.045. There were 17 locoregional recurrences in 15 patients among patients with replanning, of which 1 (5.9%) was out-field and 16 (94.1%) were in-field. Among patients without replanning, 19 patients developed locoregional recurrences, of which 1 (5.3%) was out-field, 2 (10.5%) were marginal, and 16 (84.2%) were in-field.
Conclusions
In-field failure inside the high dose area was the most common locoregional recurrent pattern for non-metastatic NPC. Adapting the target volumes and modifying the radiation dose prescribed to the area of tumor reduction during IMRT were feasible and would not cause additional recurrence in the shrunken area.
Origin of filaments in finite-time in Newtonian and non-Newtonian thin-films
Authors: Sharma Saksham , Wilson D. Ian
Published: August 2023

The sticky fluids found in pitcher plant leaf vessels can leave fractal-like fil- aments behind when dewetting from a substrate. To understand the origin of these filaments, we investigate the dynamics of a retreating thin-film of aqueous polyethylene oxide (PEO) solutions which partially wet polydimethyl siloxane (PDMS) substrates. Under certain conditions the retreating film gen- erates regularly-spaced liquid filaments. The early-stage thin-film dynamics of dewetting are investigated to identify a theoretical criterion for liquid fil- ament formation. Starting with a linear stability analysis of a Newtonian or simple non-Newtonian (power-law) thin-film, a critical film thickness is iden- tified which depends on the Hamaker constant for the fluid-substrate pair and the surface tension of the fluid. When the measured film thickness is smaller than this value, the film is unstable and forms filaments as a result of van der Waals forces dominating its behaviour. This critical film-height is compared with experimental measurements of film thickness obtained for receding films of Newtonian (glycerol-water mixtures) and non-Newtonian (PEO) solutions generated on substrates inclined at angles 0°, 30°, and 60° to the vertical. The observations of filament and its absence show good agreement with the theory. Further analysis of the former case, involving a stability analysis of the con- tact line, yields a prediction of the spacing (wavelength) λˆf between filaments as λˆηˆ/ϒˆ∝Ca, where ˆCa is the capillary number for contact line motion: our experiments yield λˆηˆ/ϒˆ∝Ca1.08 and earlier studies in the literature reported λˆηˆ/ϒˆ∝Ca0.945. The evolution of the thin-film shape is modelled numerically to show that the formation of filaments arises because the thin-film equation features a singular solution after a finite-time, hence termed a “finite-time sin- gularity”.
Smoothing Randomized Block-coordinate Proximal Gradient Algorithms for Nonsmooth Nonconvex Composite Optimization
Authors: Bian Wei , Li Xue
Published: August 2023

In this paper, we propose a smoothing randomized block-coordinate proximal gradient (S-RBCPG) algorithm and a Bregman randomized block-coordinate proximal gradient (B-RBCPG) algorithm for minimizing the sum of two nonconvex nonsmooth functions and one of which is separable. The pivotal tool of our analysis is the connection of the proximal gradient mapping with V-proximal mapping and Bregman proximal mapping. S-RBCPG algorithm overcome the non-smoothness issue of the objective function by utilizing the smoothing technique and we establish its subsequential convergence. Further, B-RBCPG algorithm is designed for cases where the separable function is separately relative smooth (that is, each separation part is relative smooth). Then, we establish the global convergence and R-linear convergence rate of the B-RBCPG algorithm under expectation by assuming the Kurdyka-Łojasiewicz property on the objective function without any convexity assumption. Finally, we use numerical experiments to illustrate the effectiveness and convergence of the proposed algorithms.
MSC Classification: 90C30 , 90C26 , 65K05
Twin chain: A Blockchain based Federated Learning Intrusion Detection System usingOptimized Backpropagation based Neural Network for Edge Assisted IoT Networks
Authors: Narayanan Uma , Paul Varghese
Published: August 2023

Ensuring security and privacy in IoT environments is a critical concern due to the prevalence of intrusions. Federated learning (FL) has emerged as a prominent technology for intrusion detection without compromising data privacy. This study proposes a novel model called BlockFL-IDS (Blockchain-based Federated Learning for Intrusion Detection System) that combines blockchain and deep learning approaches for effective intrusion detection. The BlockFL-IDS model consists of three key processes: efficient client selection, secure channel selection, and federated learning-based IDS. To streamline the complexity of federated learning, we employ Auction game theory to select efficient clients based on metrics such as trust, energy, bandwidth, and network conditions. Furthermore, we employ the Base Criterion Method (BCM), a multicriteria decision-making algorithm, for secure channel selection. BCM evaluates multiple criteria, including noise, path loss, channel quality, stability, trust, and fading, resulting in improved accuracy and reduced data loss in intrusion detection. For federated learning, we utilize the Optimized Back Propagation-based Deep Belief Network (OB-DBN), enabling the generation of both local and global models. The edge server generates local models, extracting packet-based features from client data for intrusion detection. Cloud servers aggregate these local models to create global models stored in a circular-based regression tree structure to enhance scalability and reduce retrieval time. The proposed OB-DBN algorithm calculates backpropagation error, facilitating loss reduction and weight updates. To evaluate the performance of the BlockFL-IDS model, we implement it using the NS-3.26 network simulator and assess its effectiveness using various performance metrics. Through our research, we aim to address security and privacy concerns in IoT environments, providing an innovative solution that enhances intrusion detection while preserving data privacy.
Study of India stock prices (2023) of Banks and prediction based on ARIMA models
Authors: Bhuvaneshwari S. , Rajini S. Nirmala Sugirtha
Published: August 2023

Many investors, both novice and seasoned, have made considerable profits by strategizing and investing in stocks over the years. The study described in this paper uses a time series approach to model and forecast the stock values of the State Bank of India and the Indian Bank in India. From the Yahoo Finance web-site, we retrieved the stock prices for SBIN.NS and INDIANB.NS. This article’s primary goal is the Hampel filter-based outlier detection of stock prices. We used the Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test to check the time series of stock prices for stationarity. We also discovered the (partial) autocorrelation function graphs (PACF/ACF). Finally, we used the AutoRegressive Integrated Moving Average (ARIMA) models to forecast the stock values of Indian banks.
Structural, Electronic, Elastic, Magnetic and Optical Properties of BaXN3(X=K, Rb) perovskites: An Ab-initio DFT Study
Authors: benatmane saadiya
Published: August 2023

The full-potential linearized augmented plane waves (FP-LAPW) method, which is based entirely on functional density theory (DFT), is used to investigate the structural, electronic, magnetic, optical, and elastic properties of BaXN3(X = K, Rb). This method also employs the Generalized Gradient Approximation (GGA) and a modified Beck Johnson TB-mBJ potential in the exchange correlation term. When the resulting structural properties were examined, the findings showed that our compounds are best stable when they are configured as ferromagnetic materials. The formation energy value demonstrated that these chemicals could be produced experimentally. Additionally, the estimated band structures show that BaXN3(X = K, Rb) exhibits half-metallic behavior with an indirect band gap. The total and partial density of state curves were used to assess the contributions of the various bands. Additionally, we discovered that the total magnetic moment is an integer of 6 µB, confirming the half-metallic nature. The primary source of the magnetic moment is the spin-polarization of the p electrons in N atoms. The mechanical stability of these compounds has been discovered. The elastic parameters are obtained, including the elastic constants, bulk modulus, anisotropy factor, Poisson's ratio, and Pugh's ratio. The optical spectra are calculated for the energy range of 0 to 30 eV, including the real and imaginary components of the dielectric function, extinction coefficient, and refractive index.
Corrosion of 9Cr steel by hot CO2 gas: effects of O2 and H2O
Authors: Rouillard F. , Jomard F. , Latu-Romain L. , Martinelli L. , Miserque F. , Young D. J.
Published: August 2023

The initial stages of oxidation of 9Cr steel in CO2, O2, CO2-O2 and CO2-O2-H2O is studied by Gas Phase Analysis (GPA) at 550°C using 13C16,16O2, 18,18O2 and 2H216O isotopic molecules in order to discriminate the reactions of all gas molecules. Protective and non-protective oxide scales are formed on 9Cr steel depending on the exact composition of the gas mixture. In pure CO2, 9Cr steel forms a slow growing chromium rich oxide scale without any carburization. Adding O2 impurities in CO2 favors the formation of fast growing iron rich duplex oxide scale coupled to strong carburization. Adding several % of O2 in CO2 favors again the formation of slow growing oxide scale but with different structure and composition than in pure CO2. GPA analyses combined with oxide scale analyses demonstrate that the composition and structure of the transient oxide scale formed on 9Cr surface is determined by the rate at which surface adsorbed oxygen atoms are supplied by the gas phase in the first minutes of exposure. The presence of the very oxidizing O2 molecules in CO2 increases drastically the surface oxidation rate and favors the formation of non-protective duplex oxide scale against carburization. Adding water vapor to a CO2 gas environment slows carburization. Preferential adsorption of water vapor molecules over CO2/CO molecules in the inner oxide scale is proposed to explain this result. A unified mechanism for the formation of the transient oxide scale on 9Cr steel in CO2/O2/H2O gas mixtures is described.
Grid convergence study for the prediction of hemolysis in blood circulatory devices: sensitivity to the form of equivalent stress and turbulence simulation methods
Authors: Zhang Ke-Jia , Wu Peng
Published: August 2023

Hemolysis and related complications induced by non-physiological stress are major concerns during the development and clinical applications of blood circulatory devices. Turbulence is one of the primary causes of hemolysis. To consider turbulence effects on hemolysis, various turbulence simulation methods and stress forms were employed or proposed. Nonetheless, the results showed significant divergence for different stress forms and turbulence simulation methods, discrediting hemolysis prediction as an important tool for the design, optimization and evaluation of blood circulatory devices. This study aims at quantitatively investigating the grid convergence for the prediction of hemolysis in blood circulatory devices, with a focus on its sensitivity to the stress forms and turbulence simulation methods. We revealed the integral of equivalent stress has very different characteristics of grid convergence. For Reynolds-averaged Navier-Stokes (RANS) method, grid convergence was less demanding on grid size and insensitive to stress forms. For large eddy simulation (LES), grid convergence was demanding and sensitive to stress forms, with highest uncertainty for the “total scalar stress”, followed by “viscous stress”. The “energy-dissipation stress” showed the best grid convergence for both RANS and LES. We also observed a significant divergence for metrics based on “total scalar stress” under different turbulence simulation methods, while the “energy-dissipation stress” showed a much higher consistency. We show the combination of energy-dissipation stress and LES can better capture the trend of hemolysis and has the best grid convergence. This study provides insights for a better prediction of hemolysis in turbulent flows in blood circulatory devices.
Substitution Analytical Model for Finite Element Method to Predict Distribution of Flux density for Flux Switching Permanent Magnet with E-Core Shape of Stator at no load
Authors: Shirzad Ehsan
Published: August 2023

In this essay, a two-dimensional analytical model for switched flux machines without permanent magnet brushes with E-shape of stator is presented. This machine is a suitable choice for use in hybrid vehicles, due to high power density of this configuration. The radial and tangential components of the magnetic flux density in the presence of only magnets are calculated based on Maxwell's equations and the subdomain method for different areas of the machine, including air gaps. Finally, in order to validate the proposed model of the essay, the results extracted from the analytical model are compared with the results obtained from the finite element method
The predictive role of frontoparietal network in clinical symptoms and treatment response in anorexia nervosa
Authors: He Qianqian , Zheng Hui , Zhang Jialin , Yue Ling , Kang Qing , Lian Cheng , Guo Lei , Chen Yan , Hu Yanran , Wang Yuping , Peng Sufang , Wang Zhen , Chen Jue
Published: August 2023

Objective
Anorexia nervosa (AN) has been characterized as an over-control disorder with increased resting-state functional connectivity (RSFC) in the frontoparietal control network (FPCN). However, there has been limited exploration of neuroimaging biomarkers for predicting treatment response in AN. The study aimed to investigate the role of FPCN in predicting clinical symptoms and treatment response in AN patients.
Method
Seventy-nine female AN patients who had not received prior treatment and forty matched healthy controls (HCs) were recruited for this study. All participants completed the Questionnaire Version of the Eating Disorders Examination (version 6.0) to assess the severity of AN. Additionally, RSFC data were obtained from all participants at baseline. AN patients then underwent outpatient treatment for four and twelve weeks, during which time their clinical symptoms were evaluated using the same measures as at baseline.
Results
After controlling for depression and anxiety symptoms, the AN group still exhibited increased RSFC in the right posterior parietal cortex (PPC) and dlPFC compared to HCs. Moreover, RSFC in the PPC to inferior frontal gyrus (IFG) was found to be an important predictor or tend to be an important predictor for the clinical symptoms after controlling for age, and treatment response of AN after controlling for age, age of onset and BMI.
Conclusion
Alterations in RSFC of FPCN may provide a possible neural marker to assist in predicting clinical symptoms and treatment response in AN patients, providing new insight into the pathogenesis of AN and allowing for early prevention and treatment.
Prognostic value of different surgical treatment strategies in patients with colorectal cancer liver metastases: Analysis of SEER Data
Authors: Luo MingPeng , Yuan Li , Gao Xin , Cao Qiaochang , Zhou Jichun , Ruan Shanming , Zhang Bo
Published: August 2023

Objective: This study aimed to evaluate the prognostic value of different surgical treatment options selected based on the clinical and pathological characteristics of colorectal liver metastasis (CLM) patients through a retrospective study.
Materials and Methods: A retrospective analysis was conducted on CLM patients from 2000 to 2018 based on the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate regression analysis and propensity score matching were used to evaluate the survival outcomes and risk factors of different surgical treatment strategies.
Results: A total of 32,308 eligible CLM patients were included in this study, with 15,409 (47.69%) patients receiving no surgery, 469 (1.45%) patients undergoing liver cancer surgery only without colorectal cancer surgery, 11,559 (35.78%) patients undergoing colorectal cancer surgery only without liver cancer surgery, and 4,871 (15.08%) patients undergoing both liver cancer and colorectal cancer surgery. Multivariate survival analysis showed that patients who underwent both surgeries had the best prognosis, while patients who underwent only liver cancer surgery or only colorectal cancer surgery had similar survival curves, indicating similar prognostic outcomes. Patients who did not undergo surgery had the worst prognosis (P<0.001). Propensity score matching eliminated potential confounding factors and verified the aforementioned findings.
Conclusion: In all conditions, even when only partial conditions meet the indications for surgery, proactive surgical treatment remains the primary choice with adequate consideration for safety. Personalized surgical resection strategies contribute to improved survival rates for patients.
Enhancing Stance Detection through Sequential Weighted Multi-task Learning
Authors: Alturayeif Nora , Luqman Hamzah , Ahmed Moataz
Published: August 2023

The exponential growth of user-generated content on social media platforms, online news outlets, and digital communication has necessitated the development of automated tools for analyzing opinions and attitudes expressed in text. Stance detection, a critical task in Natural Language Processing (NLP), aims to identify the underlying perspective or viewpoint of an individual or group towards a specific topic or target. This paper explores the challenges of stance detection, particularly in the context of social media, where brevity, informality, and limited contextual information prevail. While sentiment analysis focuses on explicit sentiment polarity, stance detection classifies the stance or viewpoint of a text towards a target, often of an abstract nature. This study introduces two multi-task learning (MTL) models that integrate sentiment analysis and sarcasm detection tasks to enhance stance detection performance. Four task weighting techniques are proposed and evaluated, and their effectiveness in the MTL models is demonstrated. Extensive evaluations on English and Arabic benchmark datasets highlight the advantages of the proposed models. Among them, the multi-target sequential MTL model stands out with its hierarchical weighting approach, as it achieves state-of-the-art performance. The study underscores the potential of MTL in improving stance detection and provides insights into the interaction between sentiment and stance, while considering the impact of sarcasm.
Semantic Feature Integration network for Fine-grained Visual Classification
Authors: Li Yueyang , Wang Hui , Luo Haichi
Published: August 2023

Fine-Grained Visual Classification (FGVC) is known as a challenging task due to subtle differences among subordinate categories. Many current FGVC approaches focus on identifying and locating discriminative regions, but neglect the presence of unnecessary features that impair the understanding of object structure. These unnecessary features, including 1) ambiguous parts resulting from the visual similarity in object appearances and 2) noninformative parts (e.g., background noise), can have a significant adverse impact on classification results. To address this limitation, we propose the Semantic Feature Integration network (SFI-Net) to eliminate unnecessary information and reconstructing the semantic relations among discriminative features. The network consists of two modules: 1) the multi-level feature filter (MFF) module is proposed to remove unnecessary features with different receptive field, and then concatenate the preserved features on pixel level for subsequent disposal; 2) the semantic information reconstitution (SIR) module is presented to further establish semantic relations among discriminative features obtained from the MFF module. These two modules are carefully designed and can be trained end-to-end in a weakly-supervised way. Extensive experiments on four challenging fine-grained benchmarks demonstrate that our proposed SFI-Net achieves the state-of-the-arts performance. Especially, the classification accuracy of our model on CUB-200-2011 and Stanford Dogs reaches 92.64% and 93.03%, respectively.
Exact Mathematical Analysis of DC-DC Converters Employing Type 3 Controllers
Authors: Gurbina Mircea , Lascu Dan , Lica Septimiu , Sirbu Cristina Laura
Published: August 2023

A new method for analysing the stability of dc-dc converters in closed-loop operation is developed. A generalized discrete model is proposed consisting of two nonlinear vector equations: the state equation and the nondynamic constraint. After model linearization, the classical technique of using characteristic multipliers can be applied. Several problems were solved regarding: the nondynamic constraint derivation; the steady-state operation point calculation; verifying that the parameters defining the steady-state operation point are located in the linear region and are not in the proximity of a saturated vicinity; partial derivatives determination and Jacobian calculation. The above concepts have been easily implemented in Matlab, allowing: determination of the parameter value for which instability occurs; to demonstrate that instability is installed with a Neimark-Sacker bifurcation; to prove that the proposed exact method predicts a much larger stable region, 327% higher compared to that predicted by the traditional approach. The theoretical considerations were accurately validated by computer simulation.
PHYTOREMEDIATION CAPACITY OF MAIZE (ZEA MAYS) ON DIESEL OIL POLLUTED SOIL
Authors:   Department of Biological Science, Federal University of Technology Owerri, Nigeria., A. Ukaoma , I. Iwu ,   Department of Chemistry, Federal University of Technology Owerri, Nigeria., N. Nwachukwu ,   Department of Biological Science, Federal University of Technology Owerri, Nigeria., C. Anyanwu ,   Department of Biotechnology, Federal University of Technology Owerri, Nigeria., I. Adamu ,   Department of Biological Science, Federal University of Technology Owerri, Nigeria.
Published: August 2023

The potential of maize plants in the remediation of diesel oil-polluted soil was evaluated. Soil samples were polluted with diesel oil in concentrations of 100ml, 200ml, 300ml, and 400ml and amendedseparately with poultry droppings. Samples wereanalyzed at two weeks intervals for 9 weeks. Results show a significant reduction of diesel oil in polluted soil.The effect was concentration dependent. Agromorphological parameters that were observed were Petiole Length, Plant Height, Leaf Length, Leaf Width, and Number of Leaves. Results obtained showed that as the concentration increased the more it reduced the growth of the plant. TPH content of diesel oil showed a significant reduction through the growth period, reducing from a baseline data of 8502mg/kg to 2843mg/kg. Hence, theplants have a higher potential for phytoremediation of diesel-contaminated soils.
CLASSIFICATION OF THERAPEUTIC PLANTS OF IVORY COAST BASED ON THE ARTIFICIAL IMMUNE SYSTEM AND WAVELET TRANSFORMATION
Authors:   LASTIC, Ecole SupÃ©rieure Africaine des TIC (ESATIC), Abidjan, Cote dIvoire., Adles Francis KOUASSI , Hyacinthe Kouassi KONAN ,   LASTIC, Ecole SupÃ©rieure Africaine des TIC (ESATIC), Abidjan, Cote dIvoire., Narcisse TAHI ,   EDP-INPHB, Yamoussoukro, Cote dIvoire., Olivier ASSEU ,   LASTIC, Ecole SupÃ©rieure Africaine des TIC (ESATIC), Abidjan, Cote dIvoire.,   EDP-INPHB, Yamoussoukro, Cote dIvoire.
Published: August 2023

Leaf recognition plays an important role in plant classification. Its main problem is whether the selected features are stable and have a good ability to distinguish between different leaf types. In this paper, we propose a new method for plant classification from a set of leaf images based on artificial immune system (AIS) and wavelet transforms. AIS are a type of intelligent algorithm they imitate the human defense mechanism and they use its principles, to give them the power to be applied as a classifier. Moreover, the wavelet transform offers fascinating features for texture classification. The experimental results show that it is possible to use the artificial immune system and the wavelet transform to recognize the image of the leafy plant, and the recognition accuracy is encouraging.
A COMPARATIVE STUDY OF RAPID SARS COV 2 ANTIGEN DETECTION TEST & REAL TIME PCR TEST FOR DIAGNOSIS OF COVID-19 IN TERTIARY CARE INSTITUTE AT KOTA, SOUTH-EAST RAJASTHAN, INDIA
Authors:   Senior Demonstrator, Department of Microbiology and Immunology, Government Medical College-Kota, Kota, Rajasthan, INDIA., Singh Naruka Harshad , Verma Dinesh ,   Professor, Department of Microbiology and Immunology, Government Medical College-Kota, Kota, Rajasthan, INDIA., Singh Mandawat Preetam ,   Senior Demonstrator,Department of Pathology,Government Medical College-Kota, Kota Rajasthan, INDIA., Kumar Mandawat Bhupendra ,   Professor, Department of Microbiology and Immunology, Government Medical College- Kota, Kota, Rajasthan, INDIA.
Published: August 2023

Background:The 2019 (Covid19) pandemic of coronavirus disease was caused by SARS Cov 2 Virus. The emergence of the disease was started from the Wuhan city of China in December 20191. This infection causes asymptomatic and mild diseases more than severe pneumonia. A Rapid Lateral flow immunoassays using monoclonal anti-SARS CoV- 2 antibodies, targeting SARS-CoV-2 antigens, can be used as complementary screening tests if their accuracy comes comparable to that of gold standard real-time RT-PCR assays. Objective:The present study has been conducted retrospectively on the data of patients who underwent for Covid 19 diagnosis by RAT at the Microbiology Department Central Laboratory, Maharao Bhim Singh Hospital Nayapura Kota. Material and Method: Respiratory samples from suspected 5219 COVID-19 patients, mainly nasopharyngeal and throat swabs were collected. COVID-19 Ag ConfirmitÃƒÂƒÃ‚Â¢ÃƒÂ‚Ã‚Â„ÃƒÂ‚Ã‚Â¢ kit (Alpine biomedicals) is a rapidchromatographic immunoassay for the detection ofSARS-CoV-2 nucleoprotein (N) antigen in respiratoryspecimens. Multiplex Real-time RT-PCR kit (TRIVITRON healthcare) was used, whichtargets envelope gene (E), and Orf1ab gene of SARS-CoV-2 genome and RPP30 Human gene as internal control, was used for SARS-CoV-2RNA detection. Descriptive statistics were used to describe the usefulness of rapid diagnostic tests. For that online MedCalcs Diagnostic test evaluation statistical tool10. Result: Among all 5219 samples (n=5219) tested by RT-PCR 785 (15.4%) samples were positive and 4434 (84.95%) were negative. Samples tested by RAT 813 (15.57%) samples were positive & 4406 (84.42%) were negative, in our study we found discordant results in 36 samples. The sensitivity and specificity of the COVID-19 Ag ConfirmitÃƒÂƒÃ‚Â¢ÃƒÂ‚Ã‚Â„ÃƒÂ‚Ã‚Â¢ kit (Alpine biomedicals) were 99.49% and 99.28% respectively. Discussion: Out of 785 RT-PCR-positive samples in our study, the 4 false negative results were tested for SARS-CoV-2 antigen seven days after disease onset. The RT-PCR result of these samples had relatively high Ct-values. Without the present population prevalence of COVID-19, the positive and negative predictive values (PPV and NPV) of the assay could not be accurately calculated. Conclusions: There is comparable Sensitivity and Specificity between Rapid assay for SARS-CoV-2 antigen detection (COVID-19 Ag ConfirmitÃƒÂƒÃ‚Â¢ÃƒÂ‚Ã‚Â„ÃƒÂ‚Ã‚Â¢ kit) and real-time RT-PCR assay.