Fluorinated semi-interpenetrating polymer networks for enhancing the mechanical performance and storage stability of polymer-bonded explosives by controlling curing and phase separation rates

Herein, the effect of fluoropolymer binders on the properties of polymer-bonded explosives(PBXs) was comprehensively investigated. To this end, fluorinated semi-interpenetrating polymer networks(semiIPNs) were prepared using different catalyst amounts(denoted as F23-CLF-30-D). The involved curing and phase separation processes were monitored using Fourier-transform infrared spectroscopy, differential scanning calorimetry, a haze meter and a rheometer. Curing rate constant and activation energy were calculated using a theoretical model and numerical method, respectively. Results revealed that owing to its co-continuous micro-phase separation structure, the F23-CLF-30-D3 semi-IPN exhibited considerably higher tensile strength and elongation at break than pure fluororubber F2314 and the F23-CLF-30-D0 semi-IPN because the phase separation and curing rates matched in the initial stage of curing.An arc Brazilian test revealed that F23-CLF-30-D-based composites used as mock materials for PBXs exhibited excellent mechanical performance and storage stability. Thus, the matched curing and phase separation rates play a crucial role during the fabrication of high-performance semi-IPNs;these factors can be feasibly controlled using an appropriate catalyst amount.

Rock Mass Quality Rating Based on the Multi-Criteria Grey Metric Space

Assessment of rock mass quality significantly impacts the design and construction of underground and open-pit mines from the point of stability and economy.This study develops the novel Gromov-Hausdorff distance for rock quality(GHDQR)methodology for rock mass quality rating based on multi-criteria grey metric space.It usually presents the quality of surrounding rock by classes(metric spaces)with specified properties and adequate interval-grey numbers.Measuring the distance between surrounding rock sample characteristics and existing classes represents the core of this study.The Gromov-Hausdorff distance is an especially useful discriminant function,i.e.,a classifier to calculate these distances,and assess the quality of the surrounding rock.The efficiency of the developed methodology is analyzed using the Mean Absolute Percentage Error(MAPE)technique.Seven existing methods,such as the Gaussian cloud method,Discriminant method,Mutation series method,Artificial neural network(ANN),Support vector machine(SVM),Grey wolf optimizer and Support vector classification method(GWO-SVC)and Rock mass rating method(RMR)are used for comparison with the proposed GHDQR method.The share of the highly accurate category of 85.71%clearly indicates compliance with actual values obtained by the compared methods.The results of comparisons showed that the model enables objective,efficient,and reliable assessment of rock mass quality.

Comparative Analysis of Building Rating Systems and Occupant Rating Systems

To begin with, rating systems are a beneficial tool in determining the efficiency of a building’s ability to utilise its resources effectively. In this study, the two elements under comparison are the Building Rating Systems (BRSs) and Occupant Rating Systems (ORSs). The main objective of this paper is to be able to examine the most commonly applied international and national BRS and ORS and, based on that, discover the possibility of developing an integration of both the BRS and ORS into one rating system. Quite simply, a BRS is a method by which buildings are assessed and given a score based on numerous features such as the efficiency of each of the services, total energy consumption, and alternate options of consumption. There are various BRSs that are implemented globally, each with its own set of criteria and specifications. Thus, based on the analysis of the benefits and drawbacks of both types of rating systems, it could be deduced that a well-rounded rating system with all technical and non-technical aspects combined would be beneficial to both the efficiency of the building as well as the building occupants’ health and well-being.

Aspect Level Songs Rating Based Upon Reviews in English

With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after the use of the item.The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items.Sentiment Analysis(SA)is a technique that performs such decision analysis.This research targets the ranking and rating through sentiment analysis of these reviews,on different aspects.As a case study,Songs are opted to design and test the decision model.Different aspects of songs namely music,lyrics,song,voice and video are picked.For the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a dataset.Different machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are applied.ANN performed the best with 74.99%accuracy.Results are validated using K-Fold.

Exploring the thermal stability of lithium-ion cells via accelerating rate calorimetry:A review

Given the importance of lithium-ion cell safety,a comprehensive review on the thermal stability of lithium-ion cells investigated by accelerating rate calorimetry(ARC),is provided in the present work.The operating mechanism of ARC is discussed first,including the usage and the reaction kinetics.Besides that,the thermal stability of the cathode/anode materials at elevated temperatures is revealed by examining the impacts of some significant factors,i.e.,the lithium content,particle size,material density,lithium salt,solvent,additive,binder and initial heating temperature.A comparison of the common cathode materials indicates that the presence of Mn and polyanion could significantly enhance the thermal stability of cathode materials,while the doping of Al also helps to restrain the reactivity.Except for their high capacity,some alloy materials demonstrate more competitive safety than traditional carbon anode materials.Furthermore,the thermal behaviors of full cells under abusive conditions are reviewed here.Due to the sensitivity of ARC to the kinetic parameters,a reaction kinetic modeling can be built on the basis of ARC profiles,to predict the thermal behaviors of cell components and cells.Herein,a shortcircuit modeling is exampled.

Prediction of film ratings based on domain adaptive transfer learning

This paper examines the prediction of film ratings.Firstly,in the data feature engineering,feature construction is performed based on the original features of the film dataset.Secondly,the clustering algorithm is utilized to remove singular film samples,and feature selections are carried out.When solving the problem that film samples of the target domain are unlabelled,it is impossible to train a model and address the inconsistency in the feature dimension for film samples from the source domain.Therefore,the domain adaptive transfer learning model combined with dimensionality reduction algorithms is adopted in this paper.At the same time,in order to reduce the prediction error of models,the stacking ensemble learning model for regression is also used.Finally,through comparative experiments,the effectiveness of the proposed method is verified,which proves to be better predicting film ratings in the target domain.

The laparoscopic rating scale for the evaluation of working conditions for surgical treatment of super-obesity

In this technical note,a novel rating scale(abdominal integral index)was introduced for assessing the conditions of the working laparoscopic space based on linear measurements to select the optimal one or two-stage surgical treatment for super-obesity.Patients with the same height and similar BMI values had different rating scale scores,reflecting different conditions of laparoscopic bariatric surgery.The rating scale helps surgeons and patients make a safe option for surgery,depending on the experience of the surgeon and technical laparoscopic conditions.

The Impact of Credit Ratings on Financial Performance (ROA) and Value Creation (Tobin’s Q)

This study employs a bibliometric and systematic approach to examine the impact of credit ratings as a measure of financial performance for companies listed in the S&P 500 index.The study identified a knowledge gap as only two researches were found,one suggesting and another using credit ratings to measure financial performance.Most researches use leverage,profitability,liquidity,and Share Return measures to explain financial performance.The empirical analysis uses the data of 2,398 observations of 240 companies rated by S&P Global Ratings for the period 2009-2013,applying a Generalized Method of Moments(GMM)methodology to estimate the models due to its ability to address potential endogeneity issues.The study considers Return on Assets(ROA)and Tobin’s Q as dependent variables.It incorporates credit ratings(CRWLTA)along with variables such as Total Debt to Total Assets(TDTA),Total Shareholder Return(TSR),EBITDA Interest coverage(EBITDAICOV),Quick Ratio(QR),Altman’s Z-Score(AZS),as well as macroeconomic factors like Gross Domestic Product(GDP)growth,inflation(Consumer Price Index-CPI),and the Federal Reserve Interest Rate(FDRI)as independent variables.The study argues that credit ratings,which incorporate historical data and confidential information about companies’strategies,provide reliable forward-looking creditworthiness assessments to the market.It is supported by specialized rating agencies that employ their methodologies.However,the findings suggested that CRWLTA,had a negative relationship with Q Tobin,although it was not statistically significant,and a negative relationship with ROA that was on the verge of significance.

Detecting conflicts of interest in credit rating changes:a distribution dynamics approach

In this study,we compare the adjustments of credit ratings by an investor-paid credit rating agency(CRA),represented by Egan-Jones Ratings Company,and an issuer-paid CRA,represented by Moody’s Investors Service,vis-à-vis conflict of interest and reputation.A novel distribution dynamics approach is employed to compute the probability distribution and,hence,the downgrade and upgrade probabilities of a credit rating assigned by these two CRAs of different compensation systems based on the dataset of 750 U.S.issuers between 2011 and 2018,that is,after the passage of the Dodd–Frank Act.It is found that investor-paid ratings are more likely to be downgraded than issuerpaid ratings only in the lower rating grades,which is consistent with the argument that investor-paid agencies have harsher attitudes toward potentially defaulting issuers to protect their reputation.We do not find evidence that issuer-paid CRAs provide overly favorable treatments to issuers with threshold ratings,implying that reputation concerns and the Dodd–Frank regulation mitigate the conflict of interests,while issuerpaid CRAs are more concerned about providing accurate ratings.

SCIM: Incorporating secure communication and interference management in one operation

Due to the broadcast nature of wireless communications,users’data transmitted wirelessly is susceptible to security/privacy threats.Meanwhile,as a result of the limitation of spectrum resources,massive wireless connections will incur serious interference,which may damage the efficiency of data transmission.Therefore,improving both efficiency and secrecy of data transmission is of research significance.In this paper,we propose a wireless transmission scheme by taking both Secure Communication(SC)and Interference Management(IM)into account,namely SCIM.With this scheme,an SCIM signal is generated by the legitimate transmitter(Tx)and sent along with the desired signal,so that the SCIM signal can interact with and suppress the environmental interference at the legitimate receiver(Rx).Meanwhile,the SCIM signal may interfere with the eavesdropper in the coverage of legitimate transmission so as to deteriorate the eavesdropping performance.Therefore,the secrecy of desired transmission is improved.In this way,both the transmission efficiency and privacy are enhanced.Then,by taking various transmission preferences into account,we develop different implementations of SCIM,including Interference Suppression First SCIM(ISF-SCIM),Data Transmission First SCIM(DTF-SCIM),Anti-Eavesdropping First SCIM(AEF-SCIM),and Secrecy Rate Maximization SCIM(SRM-SCIM).Our in-depth simulation results have shown the proposed methods to effectively improve the efficiency and secrecy of the legitimate transmission.

Design of Online Vitals Monitor by Integrating Big Data and IoT

In this work,we design a multisensory IoT-based online vitals monitor(hereinafter referred to as the VITALS)to sense four bedside physiological parameters including pulse(heart)rate,body temperature,blood pressure,and periph-eral oxygen saturation.Then,the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery.The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment,a powerful microcontroller,a reliable wireless communication module,and a big data analytics system.It extracts human vital signs in a pre-programmed interval of 30 min and sends them to big data analytics system through the WiFi module for further analysis.We use Apache Kafka(to gather live data streams from connected sen-sors),Apache Spark(to categorize the patient vitals and notify the medical pro-fessionals while identifying abnormalities in physiological parameters),Hadoop Distributed File System(HDFS)(to archive data streams for further analysis and long-term storage),Spark SQL,Hive and Matplotlib(to support caregivers to access/visualize appropriate information from collected data streams and to explore/understand the health status of the individuals).In addition,we develop a mobile application to send statistical graphs to doctors and patients to enable them to monitor health conditions remotely.Our proposed system is implemented on three patients for 7 days to check the effectiveness of sensing,data processing,and data transmission mechanisms.To validate the system accuracy,we compare the data values collected from established sensors with the measured readouts using a commercial healthcare monitor,the Welch Allyn®Spot Check.Our pro-posed system provides improved care solutions,especially for those whose access to care services is limited.

一种新的P2P系统中基于双ratings的声誉管理机制

声誉系统的效率取决于回馈的质量,现有P2P系统中的声誉模型不能处理合谋、不递交ratings等攻击,并且对无过失节点还存在不公平性.针对这些问题,提出了一个新的基于双ratings的声誉管理机制.采用两个度量来评价节点:服务信任和回馈信任.服务信任反映server提供服务的可靠性;回馈信任反映consumer汇报ratings的可信度.一次交易后,要求服务双方都递交ratings,依据这两个ratings对server的服务信任和consumer的回馈信任进行更新,并且server的服务信任更新与consumer的回馈信任紧密相关.为了防止恶意节点反复实施恶意行为或不递交rating,还提出了一个惩罚机制,作为对声誉模型的补充.仿真表明,提出的声誉管理机制能够抵制上述恶意攻击,减少不公平性.

基于主题模型的(Aspect,Rating)摘要生成方法研究

提出基于短语参数学习的主题模型TMPP(Topic Model based on Phrase Parameter)对在线评论中被评价实体的aspect和与之对应的rating进行抽取.TMPP具有三个特点:1)评论用"短语袋"表示;2)将标准的LDA中表示文档-主题的参数扩展为(aspect,rating)集;3)融合了先验知识.介绍了TMPP模型参数的物理含义、模型的生成过程以及先验知识的获取和表示方法;阐述了在TMPP模型中引入方面集聚类使用先验知识的原因与好处、TMPP模型提取(方面,等级)对形成(aspect,rating)摘要的原理.以真实的在线产品评论数据集为实验对象,在实验过程中引入先验知识的方面识别分析和等级预测精度分析,列出了五类产品相关方面和对立的情感词的实验结果.通过与已有的基线方法比较,实验表明若评论集中每篇评论有一个总体等级,TMPP能产生高质量的(aspect,rating)摘要.

Structure design and simulation of MEMS vibrating ring gyroscope

MEMS gyroscope is a new inertial navigation sensor,which can measure the input angular rate of sensitive axis using Coriolis effect.Compared to the conventional gyroscope,it owns many unique advantages.A novel structure of vibrating ring gyroscope is proposed and the finite element model of the oscillator is established based on MEMS technology.Through the modal analysis,the natural frequency and mode shapes of the oscillator are obtained.By analyzing the effects of the structural parameters on the mode shapes and frequency of the harmonic oscillator,the optimal design parameters are got.The frequency difference between the operating mode and the other modes is greater than 1kHz after optimization,which can avoid the frequency coupling of the operating mode and other vibrating modes of the oscillator.The simulation results show that the performance parameters of the ring structure meet the design requirements and have obvious advantages.

Study of the Effect of Operating Temperatures (1320 K, 1420 K and 1520 K) on the Vacant Sites of TiN Alloy in B2 Structure at 45%, 50% and 55% N by MEAM Method

In this work, we have studied the vacancy formation energy of TiN alloy of structure B2 of size 10 × 10 × 10 for nitrogen percentages of 45%, 50% and 55% under the influence of temperature at 1320 K, 1420 K and 1520 K using the Modified Embedded Atom Method MEAM under the calculation code LAMMPS version 2020. This study has enabled us to understand the behavior of the TiN alloy under different nitrogen percentages in terms of total energy, vacancy formation energy, crystalline parameter, occupancy rate and order parameter. For total energy, we have shown that as temperature increases, total energy decreases, making it easier to obtain TiN at higher temperatures;reaching the value of -7344.9169 eV for the 55% nitrogen structure for the temperature of 1420 K. For the energy of formation, we have shown that the compounds obtained at 1320 K and 1520 K have a more considerable energy of formation than that obtained at 1420 K. The study of fractions and the order parameter showed us that the structure of TiN with 55% nitrogen is less likely, as the composition obtained is at most 53.35%.

Strategic Planning for Equitable RWIS Implementation:A Comprehensive Study Incorporating a Multi-variable Semivariogram Model

This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.

Comparison of diagnostic validity of two autism rating scales for suspected autism in a large Chinese sample

BACKGROUND Autism is the most common clinical developmental disorder in children.The childhood autism rating scale(CARS)and autistic autism behavior checklist(ABC)are the most commonly used assessment scales for diagnosing autism.However,the diagnostic validations and the corresponding cutoffs for CARS and ABC in individuals with suspected autism spectrum disorder(ASD)remain unclear.Furthermore,for suspected ASD in China,it remains unclear whether CARS is a better diagnostic tool than ABC.Also unclear is whether the current cutoff points for ABC and CARS are suitable for the accurate diagnosis of ASD.AIM To investigate the diagnostic validity of CARS and ABC based on a large Chinese sample.METHODS A total of 591 outpatient children from the ASD Unit at Beijing Children’s Hospital between June and November 2019 were identified.First,the Clancy autism behavior scale(CABS)was used to screen out suspected autism from these children.Then,each suspected ASD was evaluated by CARS and ABC.Receiver operating characteristic(ROC)curve analysis was used to compare diagnostic validations.We also calculated the area under the curve(AUC)for both CARS and ABC.RESULTS We found that the Cronbach alpha coefficients of CARS and ABC were 0.772 and 0.426,respectively.Therefore,the reliability of the CARS was higher than that of the ABC.In addition,we found that the correlation between CARS and CABS was 0.732.Next,we performed ROC curve analysis for CARS and ABC,which yielded AUC values of 0.846 and 0.768,respectively.The cutoff value,which is associated with the maximum Youden index,is usually applied as a decision threshold.We found that the cutoff values of CARS and ABC were 34 and 67,respectively.CONCLUSION This result indicated that CARS is superior to ABC in the Chinese population with suspected ASD.

Development of Jacket Platform Tsunami Risk Rating System in Waters Offshore North Borneo

This work details the simulation of tsunami waves generated by seaquakes in the Manila Trench and their effect on fixed oil and gas jacket platforms in waters offshore North Borneo. For this study, a four-leg living quarter jacket platform located in a water depth of 63 m is modelled in SACS v5.3. Malaysia has traditionally been perceived to be safe from the hazards of earthquakes and tsunamis. Local design practices tend to neglect tsunami waves and include no such provisions. In 2004, a 9.3Mw seaquake occurred off the northwest coast of Aceh, which generated tsunami waves that caused destruction in Malaysia totalling US$ 25 million and 68 deaths. This event prompted an awareness of the need to study the reliability of fixed offshore platforms scattered throughout Malaysian waters. In this paper, we present a review of research on the seismicity of the Manila Trench, which is perceived to be high risk for Southeast Asia. From the tsunami numerical model TUNA-M2, we extract computer-simulated tsunami waves at prescribed grid points in the vicinity of the platforms in the region. Using wave heights as input, we simulate the tsunami using SACS v5.3 structural analysis software of offshore platforms, which is widely accepted by the industry. We employ the nonlinear solitary wave theory in our tsunami loading calculations for the platforms, and formulate a platform-specific risk quantification system. We then perform an intensive structural sensitivity analysis and derive a corresponding platform-specific risk rating model.

Debt Rating Initiations： Natural Evolution or Opportunistic Behavior？

The authors examine a firm＇s decision to begin issuing debt in public bond markets and find that it is a function of both life cycle influences and opportunistic timing. Defining life cycle factors to encompass both a firm＇s age in years and its underlying characteristics, the authors confirm that bond market participation is generally restricted to large, mature firms. Summary statistics show that finns obtain their initial bond ratings on average 9.5 years after their equity initial public offering （IPO） and 11.8 years after initiating dividend payments. Growth rates, capital expenditures, and cash flow volatility all decline as the firm accesses public debt markets, consistent with entry into the mature phase of its life cycle. With respect to opportunistic timing, it is asked whether entry into public bond markets follows strong performance （or precedes weak performance） at both the firm and market levels. At the firm level, the authors find that the debt IPO occurs following periods of strong operating performance and high excess stock returns. At the market level, entry coincides with favorable interest rates and default spreads. The benefits of careful timing result in firms receiving initial bond ratings that are stronger than what would be predicted; however, there is no evidence of abnormal numbers of downgrades for these firms in subsequent years.

Positional statement of companies＇ corporate governance rating reports： Evidence from Turkey

The Organisation for Economic Cooperation and Development （OECD） defines corporate governance as, ＂the way in which boards oversee the running of a company by its managers, and how board members are in turn accountable to shareholders and the company.＂ In recent years the issue of corporate governance and committees related to it and their impacts on corporate performance have continued to gain widespread prominence in the capital market economy. Corporate Governance Rating is meant to indicate the relative level to which an organisation accepts and follows the codes and guidelines of corporate governance practices. The purpose of the paper is to examine the rating reports of 27 companies which have obtained the corporate governance rating by rating agencies. The study highlights that the ＂stakeholders＂ sections of the reports are the most powerful part of the reports whereas the ＂board of directors＂ sections are the weakest. Potential areas for improvements are also identified.