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Members of the IQ Consortium ″Working Group on Characterization on Amorphous Solid Dispersions″ shares here a perspective on the analytical challenges, and limitations of detecting low levels of crystalline drug substance in amorphous solid dispersions (ASDs) and associated drug products. These companies aim to employ highly sensitive commercially available analytical technologies to guide development, support control strategies, and enable registration of quality products. We hope to promote consistency in development and registration approaches and guide the industry in development of "characterization best practices" in the interest of providing high quality products for patients. The first half of this perspective highlights the unique challenges of analytical methodologies to monitor crystalline drug substance in ASDs and their associated drug products. Challenges around use of limit tests, analyte spiking experiments, and method robustness are also underscored. The latter half describes the merits and limitations of the diverse analytical "toolbox" (such as XRPD, NIR and DSC), which can be readily applied during development and, in some cases, considered for potential application and validation in the commercial QC setting when necessary. [ABSTRACT FROM AUTHOR]

Abstract To reduce pollution emissions and achieve a cleaner production in paper industry, it is essential to understand the inner links between concentrations of gaseous pollutants, types of final products and production techniques. In this study, the concentrations of four potential gaseous pollutants, total volatile organic compounds (TVOC), formaldehyde (HCHO), hydrogen sulfide (H 2 S), and hydrocarbon compounds (C x H y), in the ambient air on thirty sampling points of five pulp and paper mills were detected and analyzed. The results were summarized with respect to the following aspects: (1) Levels of four gaseous pollutants on all the sampling points in five mills. It was obvious that the situation of gaseous pollution from pulp mill was much more serious than those from paper mills. (2) Gaseous pollutant distinctions due to different production processes. The levels of gaseous pollutants from five mills were greatly influenced by the utilized raw materials and the applied paper chemical agents (flavor, coating materials and additives) in mills. (3) Gaseous pollution comparisons at common points. At the two common points in five mills, i.e. the wet end of paper machine and the wastewater treatment process, TVOC and HCHO, C x H y and H 2 S were the main gaseous pollutants, respectively. In addition, some feasible measures to realize a cleaner production in pulping and papermaking process were also put forward in the article. Highlights • We analyze the levels of 4 gaseous pollutants on 30 sites of 5 pulp & paper mills. • Gaseous pollution distinctions due to different production processes are studied. • Feasible measures to realize the cleaner production in the processes are suggested. • Gaseous pollution are greatly affected by raw materials and added paper chemicals. [ABSTRACT FROM AUTHOR]

Rapid screening of bacteria by low-cost and eco-friendly material-based approaches is still a major challenge. Herein, a colorimetric biosensor was designed for the ultrasensitive and rapid detection of Gram-positive bacteria. The biosensor exploited polydopamine and polyethyleneimine (PDA-PEI)-modified papers for separating bacteria and carbon dots (CDs) for selective colorimetric detection of Gram-positive bacteria. Noble metal-free CDs can target Gram-positive bacteria by binding with peptidoglycan and possess peroxidase-like activity. Thus, they can avert the step of modifying recognition probes, facilitating biosensor fabrication, and reducing the cost. This biosensor can detect S. aureus as low as 1 cfu mL−1, L. monocytogenes as low as 5 cfu mL−1, and B. subtilis as low as 9 cfu mL−1 within 55 min. In addition, a portable device was constructed to enable convenient and on-site quantitative detection of Gram-positive bacteria. The feasibility of the biosensor was verified by detecting Gram-positive bacteria in eggshell and sausage samples with recoveries ranging from 91.2% to 110%. [Display omitted] • A colorimetric biosensor was developed based on PDA-PEI@paper and CDs. • The biosensor can selectively detect Gram-positive bacteria. • PDA-PEI@paper can enrich bacteria to improve sensitivity. • CDs with peroxidase-like activity can target Gram-positive bacteria. • The LODs of the biosensor for Gram-positive bacteria were less than 10 cfu mL−1. [ABSTRACT FROM AUTHOR]

A vast amount of articles centered on brain metastases have been published. To present the 100 most-cited articles dedicated to brain metastasis and to accomplish a broad literature review. In December 2019, we performed a title-focused search using the Thomson Reuters Web of Science database to identify the most cited articles centered on brain metastatic disease. Our search query term was based on using the following algorithm: "brain metastases" OR "brain metastasis" OR "brain metastatic disease" OR "cerebral metastases" OR "cerebral metastasis" OR "cerebral metastatic disease." Afterward, we reviewed the results to certify that they were relevant to the purposes of our research protocol. The 100 most cited papers were chosen and further analyzed. Our search resulted in 11,579 articles, published from 1975 until the completion of our survey. The most cited article, by Patchell et al., was published in 1990, with 1862 citations, and an average of 62.07 citations per year, whereas the last in our list, by Gaspar et al., was published in 2010, with 195 total citations, and an average of 19.50 citations per year. Countries with the highest-cited articles included the United States (75 records), followed by Canada (16 records). We discovered the top 100 most-cited articles centered on brain metastasis, all of which show a potentially increased level of interest, because they are meaningful scientific reports. In addition, we reviewed the historical development and advances in brain metastasis research and relevant points of interest, alongside the relevant contributions of different authors, fields of special interest, and countries. Many of the most cited articles were written by authors whose specialty was not neurosurgery or by neurosurgeons who were supported by colleagues from other medical fields. As a consequence, many of these articles were not published in neurosurgery-dedicated journals. [ABSTRACT FROM AUTHOR]

The infrastructure of the Heliophysics discipline has promising components but with several missing gaps, drastically reducing research and development efficiency. Developing an online discovery and analysis software ecosystem will close several of these gaps. The five main focuses on this ecosystem should be Discovery, Implementation, Analysis, Reproducibility, and Sharing of results (DIARieS). In this paper, we give a detailed description of how the proposed software ecosystem should operate, and point out the large range of possible applications to benefit many disparate groups, such as researchers, operational staff, decision-makers, and educators. The infrastructure components and technological capabilities necessary for its completion are either currently available or in development, making such an ecosystem possible for the first time. One main focus of current infrastructure investments must be to adapt and connect these pieces together into a cohesive whole to increase our research and development efficiency. [ABSTRACT FROM AUTHOR]

• Review with more than 100 references on cationic starches. • Overview on industrially relevant cationic starches. • Summary on analytical techniques for cationic starches. • Identification of challenges in the analysis of cationic starches. This review focuses on cationic starches with a low degree of substitution (<0.06) which are mainly used for production of paper-based products. After a brief introduction on starch in general, cationization pathways and importance of cationic starches in paper production, this review emphasizes on the analytical challenges from different perspectives. These include the different length scales of starches when in solution: the macromolecular level, their assembly into nm aggregates and finally hydrocolloids with hundreds of nanometers of diameter. We give an overview on the current state of the art on the analysis of such challenging samples and aim at providing a guideline for obtaining and presenting reliable analytical data. [ABSTRACT FROM AUTHOR]

In today's email dependent world, cyber criminals often target organizations using a variety of social engineering techniques and specially crafted malicious emails. When successful, such attacks can result in significant harm to physical and digital systems and assets, the leakage of sensitive information, reputation damage, and financial loss. Despite the plethora of studies on the detection of phishing attacks and malicious links in emails, there are no solutions capable of effectively, quickly, and accurately coping with more complex email-based attacks, such as malicious email attachments. This paper presents the first fully automated malicious email detection framework using deep ensemble learning to analyze all email segments (body, header, and attachments); this eliminates the need for human expert intervention for feature engineering. In this paper, we also demonstrate how an ensemble framework of deep learning classifiers each of which are trained on specific portions of an email (thereby independently utilizing the entire email) can generalize better than popular email analysis methods that analyze just a specific portion of the email for analysis. The proposed framework is evaluated comprehensively and with an AUC of 0.993, the proposed framework's results surpass state-of-the-art malicious email detection methods, including human expert feature-based machine learning models by a TPR of 5%. [ABSTRACT FROM AUTHOR]

• A mathematical model of submerged floating tunnel(SFT) with elastic boundary and flexible joints under moving load was proposed. • The different cable support stiffness and joint flexural stiffness in SFT was considered in this model. • The factors affecting the maximum displacement and moment response of SFT were discussed. This paper proposed a new theoretical model for analyzing the submerged floating tunnel(SFT) under moving load, whose boundary at two ends was regarded as elastic constraint, and the anchor cable was simplified as the discrete spring support. Besides, the tunnel joint was simulated as a flexural spring to connect two adjacent tube segments. The modes and natural frequencies of the model were solved by transfer matrix method, and the dynamic response of the SFT under moving load was investigated by the modal superposition method, which was verified by comparing with the results obtained by the general FEM software. The influence of boundary conditions, dissimilarity of cable stiffness and joint flexural stiffness on the dynamic response of the SFT was analyzed. The difference of the response between the beam on elastic supports (BOES) and the beam on elastic foundation (BOEF) was compared. The results showed that the boundary conditions had little influence on the vibration response of SFT's intermediate spans, but had great influence on the displacement and bending moment of the side span. Besides, even in the case when the frequency differentials of the BOES and the BOEF were small (1.84%), the displacements of the two models also had significant difference. The disparity of the cable stiffness and joint flexural stiffness had great influence on the distribution of displacement and bending moment of SFT. [ABSTRACT FROM AUTHOR]

• Behavior of the diffusion LMS algorithm is analyzed in the presence of delays in probing the unknown system. • Cyclostationary white Gaussian and non-Gaussian nodal inputs are considered. • The types of input distribution and the probing delays can be different for different nodes. • The derived models facilitate the understanding of the algorithm dependence upon the network parameters. • Significant differences are found between the algorithm behavior for equal and unequal probing delays. The paper studies the behavior of the diffusion least mean square (DLMS) algorithm in the presence of delays in probing the unknown system by the nodes. The types of input distribution and the probing delays can be different for different nodes. The analysis is done for a network having a central combiner. This structure reduces the dimensionality of the resulting stochastic models while preserving important diffusion properties. Communication delays between the nodes and the central combiner are also considered in the analysis. The analysis is done for system identification for cyclostationary white nodal inputs. Mean and mean-square behaviors of the algorithm are analyzed. The derived models consist of simple scalar recursions. These recursions facilitate the understanding of the algorithm mean and mean-square dependence upon the 1) nodal input kurtosis, 2) nodal probing delays, 3) communication delays between the nodes and the central combiner, 4) nodal noise powers, and 5) nodal weighting coefficients. Significant differences are found between the algorithm behavior for equal probing delays and that for unequal probing delays. Results for unequal probing delays are surprising. Simulations are in excellent agreement with the theory. [ABSTRACT FROM AUTHOR]

Antibiotic resistance is increasingly seen as a future concern, but antibiotics are still commonly used in animals, leading to their accumulation in humans through the food chain and posing health risks. The development of nanomaterials has opened up possibilities for creating new sensing strategies to detect antibiotic residues, resulting in the emergence of innovative nanobiosensors with different benefits like rapidity, simplicity, accuracy, sensitivity, specificity, and precision. Therefore, this comprehensive review provides pertinent and current insights into nanomaterials-based electrochemical/optical sensors for the detection of antibitic residues (ANBr) across milk and dairy products. Here, we first discuss the commonly used ANBs in real products, the significance of ANBr, and also their binding/biological properties. Then, we provide an overview of the role of using different nanomaterials on the development of advanced nanobiosensors like fluorescence-based, colorimetric, surface-enhanced Raman scattering, surface plasmon resonance, and several important electrochemical nanobiosensors relying on different kinds of electrodes. The enhancement of ANB electrochemical behavior for detection is also outlined, along with a concise overview of the utilization of (bio)recognition units. Ultimately, this paper offers a perspective on the future concepts of this research field and commercialized nanomaterial-based sensors to help upgrade the sensing techniques for ANBr in dairy products. [Display omitted] • Food safety, security and quality are significant issues in today's world. • Antibiotics are known as one of the persistent organic pollutants in dairy products. • Using of the bio−/nano-sensors to detect antibiotics has progressed. • Different nanosensors for detection of antibiotics in dairy products are discussed. [ABSTRACT FROM AUTHOR]

• A new platform for the integrated assessment of waste heat recovery is presented. • The platform assesses physical, techno-economic, market and business dimensions. • The platform achieves robust results within a short time-frame. • The new platform aims to help untapping the large waste heat potential. At a time when European countries try to cope with escalating energy prices while decarbonizing their economies, waste heat recovery and reuse arises as part of the solution for sustainable energy transitions. The lack of appropriate assessment tools has been pointed out as one of the main barriers to the wider deployment of waste heat recovery projects and as a reason why its potential remains largely untapped. The EMB3Rs platform emerges as an online, open-source, comprehensive and novel tool that provides an integrated assessment of different types of waste heat recovery solutions, (e.g. internal or external) and comprises several analysis dimensions (e.g. physical, geographical, technical, market, and business models). It has been developed together with stakeholders, and tested in a number of representative contexts, covering both industrial and heat network applications. This has demonstrated the enormous potential of the tool in dealing with complex simulations, while delivering accurate results within a significantly lower time-frame than traditional analysis. The EMB3Rs tool removes important barriers such as analysis costs, time and complexity for the user, and aims at supporting a wider investment in waste heat recovery and reuse by providing an integrated estimation of the costs and benefits of such projects. This paper describes the tool and illustrates how it can be applied to help unlock the potential of waste heat recovery across European countries. [ABSTRACT FROM AUTHOR]

Exposure to trace levels of toxic disinfection byproducts (DBPs) can pose significant environmental security risks and adversely impact human health. Recent advancements in efficient sample preparation and sensitive analytical methods have significantly supported the high-throughput identification, accurate determination, and rapid sensing of water DBPs. These advancements facilitate studies on formation mechanism study, toxicity evaluation, and risk management of DBPs. In this paper we systematically reviewed the advance on the sample preparation and analytical methods for analyzing trace and diverse DBPs across various aquatic environments. Efficient sample preparation methods introduced for DBPs analysis significantly enhance the separation and preconcentration efficiency, thereby improving the analytical sensitivity and accuracy when coupled with adaptable analytical techniques. Moreover, we summarized the application of these methods in monitoring water quality, investigating DBPs formation mechanism and evaluating DBPs removal efficiency. Finally, the challenges and future perspectives were discussed to provide readers with insightful trends in the field. [Display omitted] • Advance on the sample preparation methods for disinfection byproducts. • Advance on the analytical methods for disinfection byproducts. • Analytical applications of water disinfection byproducts. [ABSTRACT FROM AUTHOR]

This paper analyzes the effect of a processing delay on the Least Mean Squares (LMS) algorithm for a system identification problem when the processing delay is in the adaptive arm of the filter. Thus the sensing of the input signal is delayed. The input is assumed to be a zero mean stationary Gaussian process. The theoretical mean and mean square behavior of the adaptive weight vector is analyzed. The weight vector is shown to be biased and significantly affects the mean square deviation (MSD). Monte Carlo simulations are presented in support of the assumptions used to derive the theoretical model as a function of the delay, bandwidth and step-size for the LMS algorithm. The results suggest bias problems with other more complicated adaptive filtering algorithms such as Normalized LMS and Recursive Least Squares. • We study the stochastic behavior of the LMS algorithm for a system identification framework when the input signal is a cyclostationary colored Gaussian process. • Well-known results for the LMS algorithm are extended to the cyclostationary case and used for predicting the mean-square weight deviation (MSD) and excess mean-square error (EMSE) behavior of the algorithm. • The analysis is performed for cyclostationary input signals modeled as colored Gaussian random processes with periodically time-varying power. • A new model is proposed for the autocorrelation matrix of an input vector of samples of a second order wide sense cyclostationary signal. • It is shown that the proposed model is a good approximation of the autocorrelation matrix of an autoregressive signal with periodically varying power. • Simulation results show excellent agreement with the theoretically predicted behavior, confirming the usefulness of the analytical model to study the adaptive filter behavior. [ABSTRACT FROM AUTHOR]

This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can be split into two categories. First, algorithms based on data mining and knowledge discovery, which study the different correlation among human behavioral data, and identify the collective abnormal human behavior from knowledge extracted. Secondly, algorithms exploring convolution deep neural networks, which learn different features of historical data to determine the collective abnormal human behaviors. Experiments on an actual human behaviors database have been carried out to demonstrate the usefulness of the proposed algorithms. The results show that the deep learning solution outperforms both data mining as well as the state-of-the-art solutions in terms of runtime and accuracy performance. In particular, for large datasets, the accuracy of the deep learning solution reaches 88%, however other solutions do not exceed 81%. Additionally, the runtime of the deep learning solution is below 50 seconds, whereas other solutions need more than 80 seconds for analyzing the same database. • We formally define the group trajectory outlier detection problem. • We propose several solutions based on data mining and deep learning models to identify outliers. • We evaluate various algorithms using human-behavioral databases to identify the performance of two different models. [ABSTRACT FROM AUTHOR]

Tremendous progress has been made in facial Micro-Expression (ME) spotting and recognition; however, most works have focused on either spotting or recognition tasks on the 2D videos. Until recently, the estimation of the 3D motion field (a.k.a scene flow) for the ME has only become possible after the release of the multi-modal ME dataset. In this paper, we propose the first Scene Flow Attention-based Micro-expression Network, namely SFAMNet. It takes the scene flow computed using the RGB-D flow algorithm as the input and predicts the spotting confidence score and emotion labels. Specifically, SFAMNet is an attention-based end-to-end multi-stream multi-task network devised to spot and recognize the ME. Besides that, we present a data augmentation strategy to alleviate the small sample size problem during network learning. Extensive experiments are performed on three tasks: (i) ME spotting; (ii) ME recognition; and (iii) ME analysis on the multi-modal CAS(ME) 3 dataset. Empirical results indicate that depth is vital in capturing the ME information and the effectiveness of the proposed approach. Our source code is publicly available at https://github.com/genbing99/SFAMNet. • First study to spot and recognize micro-expressions on the multi-modal dataset. • A scene flow attention-based end-to-end multi-stream multi-task network is proposed. • Scene flow is extracted to estimate the 3D motion using color and depth modalities. • This work leverages data augmentation and improves the pseudo-labeling technique. • Encouraging results in micro-expression spotting, recognition, and analysis. [ABSTRACT FROM AUTHOR]

Most food samples are detected positive for neonicotinoid insecticides, posing a severe threat to human health. Electrochemical sensors have been proven effective for monitoring the residues to guarantee food safety, but there needs to be more review to conclude the development status comprehensively. On the other hand, various modified materials were emphasized to improve the performance of electrochemical sensors in relevant reviews, rather than the reasons why they were selected. Therefore, this paper reviewed the electrochemical sensors of neonicotinoid insecticides according to bases and strategies. The fundamental basis is the molecular structure of neonicotinoid insecticides, which was disassembled into four functional groups: nitro group, saturated nitrogen ring system, aromatic heterocycle and chlorine substituent. Their relationships were established with strategies including direct sensing, enzyme sensors, aptasensors, immunosensors, and sample pretreatment, respectively. It is hoped to provide a reference for the effective design of electrochemical sensors for small molecule compounds. [Display omitted] • Four functional groups of neonicotinoids are basis for their electrochemical sensors. • Electro-active of nitro group is beneficial for direct sensing. • Saturated nitrogen ring systems results in the absence of enzyme sensors. • Aromatic heterocyclics and saturated nitrogen ring systems are vital in aptasensors recognition. • Chlorine substituent is crucial to synthesize antibodies applied in immunosensors. [ABSTRACT FROM AUTHOR]

• Assessing the strengths and drawbacks of FTIR techniques for microplastic identification and quantification. • Highlights on some current research and development efforts to enhance FTIR techniques for microplastic analysis. • Concise comparison of FTIR to other viable analytical tools was presented. • FTIR was identified to be the best analytical tool for detecting functional groups. Microplastics (MPs) have become the talk of the century globally and hence taken the center stage of major research works especially in the environmental sector. In this study, the sources, types, and effects of microplastics are examined. The paper also reviews the Fourier transform infrared (FTIR) spectroscopy and its use in identifying and quantifying microplastics in environmental samples compared with other analytical techniques. There is also a critical look at the advantages and drawbacks of FTIR for microplastic analysis, including its ability to identify and describe microplastics in a variety of environmental matrices compared with other viable analytical methods commonly used for microplastics identification. There was also a highlight on the current research and development efforts aimed at improving FTIR techniques for microplastic analysis, particularly low-concentration quantification. However, of all the techniques, the FTIR method is seen as an excellent tool especially in detecting functional groups in environmental samples and assessing microplastics amounting to several studies either using it solely or in addition with other techniques. [ABSTRACT FROM AUTHOR]

This paper presents an axial flux eddy current sensor with a compact and simple structure for measuring the rotating speed of iron shafts. The sensor structure is optimized for high sensitivity with a novel configuration of the coils positioned perpendicularly to each other. The sensor comprises two D-shaped excitation coils and two D-shaped pick-up coils in a double-layer structure. A disc-shaped magnetic shield or core shields the coils. Two iron shafts with different material properties are considered. A new cup-shaped configuration of nonmagnetic copper and aluminum caps mounted on iron shafts improves sensitivity and suppresses susceptibility to shaft material properties and airgap variation. 2D and 3D finite element methods are utilized for the performance analysis of the sensor. The measurements are performed at speeds up to ± 3000 rpm and different excitation frequencies from 400 Hz to 4 kHz. The eddy current speed sensor has excellent linearity characteristics with a nonlinearity error of 0.15%. The geometry of the coils is further optimized and improved for maximum sensitivity and compactness. The fault-tolerant capability of the sensor is also evaluated. [Display omitted] • Axial flux eddy current speed sensor for rotating speed measurement. • Novel configuration of perpendicular coils. • Optimization of the eddy current speed sensor. • 2D and 3D finite element method analysis. [ABSTRACT FROM AUTHOR]

Linseed or flaxseed (Linum usitatissimum L) is an ancient perennial plant species regarded as a multipurpose plant mostly due to its seed unique richness in omega-3 fatty acids. The extensive biochemical analysis of linseed further resulted in the identification of its other components i.e., lignans with potential applications in the improvement of human health. Linseed oil that amount for 40% of its seed weight is an edible oil in demand as a dietary supplement owing to its several health benefits. This comprehensive review based on research papers and patents capitalizes on linseed oil, the major product of linseed with emphasis on the interrelationship between extraction methods, holistic chemical composition, sensory characters, and nutritional value. Overview of the different analytical approaches for linseed oil analysis and its quality control assessment is presented i.e., adulteration detection highlighting for each application advantages and limitations. Different oil extraction as well as processing methods are reviewed and in context to their influence on the final oil quality and/or biological effects. The review recapitulates on the rancidity prevention approaches to ensure best oil quality and shelf life. The extraction method as well as the pretreatments appeared to dramatically affect the yield and the quality of the oil. • Details on the main classes of compounds in linseed oil. • Oil rancid products mechanisms of formation is presented highlighting factors. • Analytical methods used for ensuring oil quality and adulteration are described. • Formulation of linseed oil in nutraceuticals to improve its stability. • This review provides data to improve health value, safety and consumer acceptance of linseed oil. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a comprehensive review of literature on most widely used urban sustainability assessment tools. The aim of this paper is to understand the similarities and differences in existing urban sustainability assessment tools and identify the gaps so as to find out whether these are capable of and suitable for addressing multiple issues of urban sustainability in multiple contexts, including settlements in diverse geo-climatic and ecologically sensitive regions such as the Himalayan hill regions of India. Qualitative Content Analysis (QCA) is employed in this study to identify various themes/categories associated with various dimensions of sustainability. A total of 2594 articles were selected, of which 105 have been analysed in detail. The research reviews six most widely used urban sustainability assessment tools i.e., Building Research Establishment Environmental Assessment Method (BREEAM)for Communities, Comprehensive Assessment System for Built Environment Efficiency (CASBEE) for Urban Development, Green Building Index (GBI)for Township, Leadership in Energy and Environmental Design (LEED) for Neighbourhood Development that are used in other countries, and Indian Green Building Council (IGBC)for Green Townships and Green Rating for Integrated Habitat Assessment (GRIHA) for Large Development which are used in India. Analysis of these assessment tools reveals that most of them view sustainability from different perspectives by laying more emphasis on some aspects like infrastructure and resource management while ignoring others like cultural, business and innovation. The findings of the analysis highlight that certain aspects are given more importance in all the urban sustainability assessment tools reviewed and certain other aspects are given much lower or no consideration in all tools reflecting an incomprehensive understanding of urban sustainability on one hand; most tools reviewed do not address all context-specific aspects on the other. Further, it is observed that these tools are unable to address the complex relationships among various criteria and categories and each criterion is assessed in isolation irrespective of the fact that it can influence or be influenced by other criteria. [ABSTRACT FROM AUTHOR]

Highlights • SOFC system models are validated with experimental data from a real system. • A novel SOFC/SOEC combined system is analyzed based on a physical model. • Performance of four classic SOFC systems are optimized and compared systematically. • Suitable application scenarios of four typical SOFC systems are investigated. • The performance index system supplies the gap of the comparison for SOFC systems. Abstract With the development of SOFC (solid oxide fuel cell) technology, especially in terms of cell manufacture and stack assembly, recent SOFC research has focused on system integration and control. Various SOFC system configurations presented in the literature can be applied to various application scenarios for their unique advantages. A thorough evaluation and comparison of those SOFC systems in terms of performance, cost and efficiency is very important for optimal system design, taking the environment and conditions into consideration. In this paper, four typical 10 kW-scale SOFC-based systems are investigated, a hydrogen-fueled SOFC system, an external steam-reforming SOFC system, an SOFC/gas turbine hybrid system and SOFC/SOEC (solid oxide electrolysis cell) combined system. First, physical system models were constructed according to physical conservation laws and chemical kinetics and validated using experimental data. In addition, an exergoeconomic analysis was carried out based on these models. Then the optimal operating points of the four systems, which can be used for system performance comparison under the same operating conditions, are acquired through a multiple-objective optimization process based on an improved genetic particle swarm optimization algorithm. Then the systems were compared in aspects of technical and exergoeconomic performance under the same net output power, and comprehensive system marking was performed. Finally, analysis and predictions of application scenarios for these systems were proposed based on the scores. This paper provides a theoretical foundation for the design, analysis and application of SOFC systems. [ABSTRACT FROM AUTHOR]

Solute analysis of bauxite residue filter cakes is an important but not very well understood operation carried out at refineries and in scientific research. As more and more refineries rely currently on dry cake disposal after filtration, washing and deliquoring of the cakes, the importance of correctly performed cake analysis will increase. Chemical analysis of bauxite residue filter cakes regarding their soluble compounds, such as the total caustic, soda and aluminate, is performed after forming a slurry from the cake and pure water by using a selected liquid/solid (L/S) ratio. This paper shows that there is currently no cake analysis procedure which could be used without unexpected variation in the results. This is because several factors affect the analysis result at the filtration and sample preparation stages. The factors discussed in this paper are divided into two groups, including the filtration and washing conditions and the sample preparation procedures. In the filtration stage, the filtration temperature and pressure were found to have a considerable effect on the solute recovery. On the other hand, the sample preparation procedure was observed to be affected by factors like the L/S ratio, the composition of the diluting liquid (with respect to its Na 2 CO 3 concentration), the temperature, and the cake leaching time. In addition to the cake solute analysis, particle size measurements and calculation of alkali recovery for the solid-liquid separation stage are discussed as well. To summarize the main findings, it can be stated that significant differences in the results can be seen when any detail in the sample preparation procedure is changed. [ABSTRACT FROM AUTHOR]

Low mass compact rovers provide cost effective means to explore extra-terrestrial terrains. Use of flexible wheels in such applications where the wheel size is restricted, improves traction at reduced slip and sinkage. Design of a flexible wheel for a given mission is a challenging task requiring consideration of stiffness of rim and spokes, stress induced in the wheel, chassis movement during wheel rotation and the operating mode of the wheel. Also, accurate mathematical models are required to save design and development time and reduce the number of prototypes for selection. It is observed that most of the research papers deal with performance testing of flexible wheels and information on analytical formulation is scarce. Therefore, in the present work, a methodology has been formulated to systematically design a flexible wheel for a low mass lunar rover. The prototype performance is tested and compared with analytical estimates and reasons for difference are investigated. Paper contains details of design criteria, mathematical modelling, realisation of wheel prototype, test fixture and analysis test comparison. Authors believe that this work provides a useful aid to the designer to systematically design flexible wheels for low mass lunar rovers. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of identification of injection duration of common rail (CR) diesel pilot injectors of dual-fuel engines. In these pilot injectors, the injected volume is small and the repeatability of injections and identification of drifts of injectors are important factors, which need to be taken into account in order to achieve good repeatability (shot-to-shot with every cylinder) and therefore a well-balanced engine and furthermore reduced overall wear. This information can then be used for calibration and diagnostics purposes to guarantee engine longevity facilitated by consistent operating conditions throughout the life of the unit. A diagnostics method based on analysis of CR pressure with experimental results is presented in this paper. Using the developed method, the relative duration of injection events can be identified for multiple injectors. We use the phenomenon of drop in rail pressure due to an injection event as a feature of the injection process. The method is based on filtered CR pressure data during and after the injection event. First, the pressure signal during injection is extracted after control of each injection event. After that, the signal is normalized and filtered. Then a derivative of the filtered signal is calculated. Change in the derivative of the filtered signal larger than a predefined threshold indicates an injection event that can be detected and its relative duration can be identified. We present the experimental results and demonstrate the efficacy of the proposed methods using two different types of pressure sensors. We are able to properly identify a change of ≥10 µs (2%, 500 µs) in injection time. This shows that the developed method detects drifts in injection duration and the magnitude of drift. This information can be used for adaptive control of injection duration, so that finally the injected fuel volume is the same as the original. [ABSTRACT FROM AUTHOR]

Knowledge cannot be bound, restricted or categorized. Knowledge is precisely an intangible strength that has a definite economic importance if well utilized and commercialized. Knowledge spillover is an occurrence, which is imaginable but difficult to have an effective measurement of it. Patents citation is a developing concept and has gained momentum in recent past. Patents citation contains valuable data and if analyzed well, may sometimes reveal concealed mysteries of the information flow between countries, laboratories, companies, and universities. Profuse technical research has been conducted on this topic by many scientists. Through these experiments, scientists have tried to show that the innovative information hidden in patents crosses every barrier and is taken by the research labs for its further expansion. Patents citation reveals the diffusion of information and its applicability into many other technical fields which give birth to a new technology. This paper presents a comprehensive survey of patents citation analysis covering and promoting the landmark research done in the field of patents citation, informing readers to consider this important segment of patent document as a field for analysis. Also, this paper presents an innovative methodology for generating patent citation network with the help of techniques of Information Retrievals. [ABSTRACT FROM AUTHOR]

Background This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. New method The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Results Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. Comparison with existing methods The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. Conclusions The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. [ABSTRACT FROM AUTHOR]

This work describes the creation of a new method to choose a suitable Multi-Criteria Decision Making (MCDM) method for a Boeing strategic decision. The decision involved four global market regions being ranked based on their market attractiveness and competitive strength when risk and uncertainty were anticipated. Following an analysis of MCDM problems and methods, a new organized approach was created to provide a decision maker with a sub-group of suitable MCDM methods. Sensitivity analysis was used to investigate the robustness of the outputs from the various candidate methods. A MCDM method is recommended automatically. The recommended candidate method is the one that provided the most robust output (solution to the problem). Only methods that deal with a discrete set of choices were considered. In the Boeing strategic decision presented in this paper, two MCDM methods were compared and a recommendation was made after calculating the minimum percentage change in performance measures and criteria weights required to change the ranking of any two alternatives. An MCDM method was recommended based on a compromise between the minimum percentage change that was required in the inputs to change the ranking of alternatives. Some propositions are discussed based on general scenarios concerning MCDM problems. [ABSTRACT FROM AUTHOR]

Successful development of stable solid protein formulations usually requires the addition of one or several excipients to achieve optimal stability. In these products, there is a potential risk of an inhomogeneous distribution of the various ingredients, specifically the ratio of protein and stabilizer may vary. Such inhomogeneity can be detrimental for stability but is mostly neglected in literature. In the past, it was challenging to analyze inhomogeneous component distribution, but recent advances in analytical techniques have revealed new options to investigate this phenomenon. This paper aims to review fundamental aspects of the inhomogeneous distribution of components of freeze-dried and spray-dried protein formulations. Four key topics will be presented and discussed, including the sources of component inhomogeneity, its consequences on protein stability, the analytical methods to reveal component inhomogeneity, and possible solutions to prevent or mitigate inhomogeneity. [ABSTRACT FROM AUTHOR]

• Provide quick sorting of patients using Alzheimer Disease Intensity Number (ADIN). • Enable estimation of the progression of disease and within a patient's context. • Achieve sufficient expressiveness in understanding patients' disease information. • Knowing the context suggest related treatment(s) or an estimated life expectancy. Modern neuroscience imaging technologies considerably affect diagnostic and prognostic accuracy and facilitate progress towards the cure of brain diseases. The benefits largely depend on the practicalities by which the large-scale imaging and clinical data can be integrated, examined and understood. In EU neuGRID4You (N4U) project, many datasets were generated from research centres and hospitals. In order to perform effective analyses, these datasets and their metadata along with a number of pre-computed parameters are stored in a big data repository. This paper focuses on the patient identification using big data and Fuzzy Logic, which has been achieved through fuzzy processing where a reference number called Alzheimers Disease Identification Number (ADIN) is calculated. It has enabled patients sorting for a particular intensity of Alzheimers disease, short-term estimation of the progression of that disease and context of individual patients with respect to other patients such as appropriate treatment, estimated life expectancy etc. The generated rules define the necessary knowledge base for the inference engine to generate output sets and an aggregate membership function of each rule is formed. Using this function, a most representative value of the total output set is obtained which represents the disease intensity. The implemented system and its evaluation are based on realistic datasets, demonstrators and making use of real-life neuroscience case studies. The presented results of four selected case studies show that this approach have provided sufficient expressiveness in understanding patients' disease information. Finally, a discussion and conclusions are presented on the opportunities offered by the calculation of ADIN to manage Alzheimers disease along with potential future extensions or applications of this work. [ABSTRACT FROM AUTHOR]

Failure analysis construction of car tyres is a highly demanding process requiring very specific methods of analysis. Industrial metrotomography is one of suitable analytical tool in this area. However, the method used for failure analysis construction of car tyres may have its limits. The paper provides a detailed research for the analysis of 5 typical types of damage occurring in car tyres, analysing the possibilities of such a technology as well as occurrence of undesirable phenomena. Results provided further on refer to occurrence of undesirable phenomenon such as various artifacts due to their construction, but also confirm suitability of application of the method for car tyres research of failure analysis. • The analysis of 5 typical types of damage occurring in car tyres. • Analysing the possibilities of a technology industrial metrotomography. • Investigation of processes of car tyres damaging. [ABSTRACT FROM AUTHOR]

Cryogenic distillation (CD) of hydrogen in combination with Liquid Phase Catalytic Exchange (LPCE) or Combined Electrolytic Catalytic Exchange (CECE) process is used for tritium removal/recovery from tritiated water from fission rectors like CANDU and is the proposed technology for ITER/DEMO. Tritiated water is being obtained after long time operation of CANDU reactors, or in case of ITER mainly by the Detritiation System. The cryogenic system of the Experimental Pilot plant for tritium and deuterium separation from ICSI Rm. Valcea consists of four distillation columns and significant effort is required in various batch mode operations for achieving high tritium concentration. Some problems have been experienced with the fourth column of the cascade regarding the heat transient transfer during start-up. This paper intent is to present a CAE/FEA (Computer Aided Engineering/Finite Element Analysis) thermal simulation of the column during the transitory thermal regime in order to investigate the temperature distribution along the column and its connections to other equipment. The simulation is done on the as-built design of the column and takes in consideration the actual configuration. This work provides an important platform to understand the thermal phenomena during cool down of a cryogenic distillation column besides finding the failures in thermal insulation or design flaws. The results of the simulation can be used as lessons-learned for future design work of cryogenic systems like Tritium Removal Facility from Cernavoda Nuclear Power Plant or ITER/DEMO Isotope Separation System. [ABSTRACT FROM AUTHOR]

• Field homogeneity analysis for the optimization of coil system. • Theoretical and FEM analysis for cooling system design. • The largest coil system for magnetic field immunity test. For the safety and reliability concerns for the Chinese Fusion Engineering Test Reactor (CFETR) and future tokamak devices, a large-scale high-intensity static magnetic field immunity test platform is planned in Chinese Academy of Sciences, Institute of Plasma Physics (ASIPP). This paper presents the preliminary design of the coil system which is used to generate a high-strength uniform magnetic field in a large test zone. At first, a magnetic field homogeneity analysis is performed to determine the structural parameters of the test coil which satisfies the test requirement at a low power loss. The electrical parameters of the coil are then determined based on the structural parameters. In addition, the design of cooling system for the test coil is performed based on theoretical analysis, and then verified by a CFD analysis. The square-shaped designed coil system is able to continuously generate a uniform magnetic field with a field strength over 700 m T in a test zone with a side-length of 2.1 m, which enables the immunity test for large devices at a nominal test level up to 500 m T. It is of great value to ensure the reliable operation of electrical and electronic equipment in CFETR and future devices. [ABSTRACT FROM AUTHOR]

Abstract The research project INFINITY focuses on design improvements for PV system components operating in different climatic regions. This topic gained pertinence in recent years due to increased installation rates worldwide with the highest growth rates in non-moderate climates. As PV components are not optimized to the respective climate zone, the target of the project is to gather failure data from PV installations in various climate zones. A standardized data input was achieved by using an extended format of the IEA PVPS Task 13 failure survey, allowing to enter PV system and failure information in rich detail. The components' and failure structure were elaborated by combining input from reliability workshop proceedings, PVPS Task 13 and project partners' experience in PV reliability testing. These structures were mapped into a database to collect and prepare the input for further statistical analysis. Collected data was filtered, offering a tidy data set of 1048 samples from 340 sub-systems from 45 countries worldwide. After data filtering, a power loss evaluation, a cluster analysis and a trend analysis were performed. This paper presents results of comparing PV module failures in different climate zones starting with a range of PV systems installed in the 1970s, to recently installed systems. Highlights • Comparison of PV module failures in different climate zones. • 1048 failures from 340 sub-systems in 45 countries all over the world. • Prevailing failures in the main climate zones (A-D) were identified. • A cluster analysis shows typical combinations of failures in various climate zones. • A trend analysis indicates different time to failure in individual climate zones. [ABSTRACT FROM AUTHOR]

In recent years, according to the survey, college students have frequent psychological problems, anxiety, depression, inferiority, interpersonal sensitivity and other psychological problems, and even more, even the idea of suicide. It has a very serious negative impact on the family and society. Children are the flowers of the motherland, and college students are the important cornerstone of the country's future development. Therefore, the mental health problems of college students are particularly important. Based on the research of cognitive computing, this paper combines the research data to analyze the influencing factors of mental health, analyzes the shortcomings of mental health education, and proposes corresponding ideas and solutions. [ABSTRACT FROM AUTHOR]

Highlights • We study the stochastic behavior of the LMS algorithm when the input signal is a cyclostationary colored Gaussian process. • The analysis is performed for cyclostationary input signals modeled as colored Gaussian random processes with periodically time-varying power. • A new model is proposed for the autocorrelation matrix of an input vector of samples of a second order wide sense cyclostationary signal. • The proposed model is a good approximation of the autocorrelation matrix of an autoregressive signal with periodically varying power. • Simulation results show excellent agreement with the theoretically predicted behavior. Abstract This paper studies the stochastic behavior of the LMS algorithm for a system identification framework when the input signal is a cyclostationary colored Gaussian process. The unknown system is modeled by the standard random walk model. Well-known results for the LMS algorithm are extended to the cyclostationary case and used for predicting the mean-square weight deviation (MSD) and excess mean-square error (EMSE) behavior of the algorithm. Monte Carlo simulations provide strong support for the theory. [ABSTRACT FROM AUTHOR]

[Display omitted] • Microplastics are fragments of synthetic particles of size from 0.1 to 5000 µm. • Microplastics have been detected in beverages, food from animals, plants and spices. • Isolation of MP is performed using filtration, digestion and density separation. • Spectroscopic techniques are commonly used for the identification of microplastic. • Determination of size, shape, and colour is possible due to the usage of microscopy. The ubiquity of microplastics (MPs) is a more and more frequently brought up topic. The fact that such particles are present in food raises particular concern. Information regarding the described contamination is incoherent and difficult to interpret. Problems appear already at the level of the definition of MPs. This paper will discuss ways of explaining the concept of MPs and methods used for its analysis. Isolation of characterised particles is usually performed using filtration, etching and/or density separation. Spectroscopic techniques are commonly applied for analysis, whereas visual evaluation of the particles is possible thanks to microscopic analysis. Basic information about the sample can be obtained by the combination of Fourier Transform Infrared spectroscopy or Raman spectroscopy and microscopy or using the thermal method combined with spectroscopy or chromatography. The unification of the research methodology will allow a credible assessment of the influence of this pollution coming from food on health. [ABSTRACT FROM AUTHOR]

There is an increasing demand to optimize performance and profit of comminution circuits. Research in this area has resulted in the development of numerous optimization tools, and recent research has shown that the quality aspects of the production have a great influence on the optimization results. The quality, cost, profit and capacity of a product are influenced by several parameters, and in order to control all of these parameters it is necessary to use some sort of optimization algorithm. In this paper, a novel approach to apply e.g. cost, revenue, capacity and quality in order to perform a multi objective optimization with the ability to handle dynamic variations of a comminution is presented. The problem with optimizations in general is that the objective function used for optimization is reduced in complexity in order to save computational time. In a comminution process performance varies with time and in order to perform a correct optimization the objective function used must be able to handle this type of dynamic behavior. The process has a given set of constraints that represents the conditions normal in these type of comminution applications. The first step in this paper is to identify if the range of the constraints can cause undesirable production costs when reaching for a given product property. In this step a dynamic response model is described that will be able to address the difficulties with optimizing dynamic systems. The next step in the optimization is the definition of the multi-objective optimization formulation including constraints for the optimization. Evaluating the result of the optimization in combination with a strategy for relaxing constraint can show how to increase overall productivity and still reach certain product properties. The conclusions made in this work are that multi objective optimization is essential when optimizing a comminution circuit against multiple objectives. [ABSTRACT FROM AUTHOR]

The carried scientific research regarding evaluation the hygrothermal effects of integration the vegetation into the building envelope was influenced with the differences in necessity to use air-conditioning in the houses, which are not surrounded with vegetation in horizontal structure and which have such vegetation during the summer time. The experimental testing is based on the precise measurements of the relative humidity and temperature, which were carried close to the building plaster in the place without influence of vegetation and between the wall and vegetation. Vegetation on the house, which was used for experimental purposes, is made up of the vine species with a thickness of 40 cm in the place where measurement was carried. Although the investigation takes longer, the paper aims to one month to show the summer time. The mathematical modelling of the obtained data was realized using the numerical as well as the statistical methods The paper aims especially on modelling the differences in relative humidity and temperature of the air and between the wall and vegetation. The dependence of temperature differences was expressed as a piecewise function using the method of Least squares of multiple regression as statistical method. Also the proportional energy to that which might be saved daily instead of its use for air-conditioning in the house was determined. The measurements as well as the used methods: showed sufficient accuracy. [ABSTRACT FROM AUTHOR]

• Two samples of ABS building material were produced with the use of FDM technology. • Surface and internal structure of samples were examined by computed tomography. • Individual samples were subjected to microCT scanning. • Basic requirement of research was to determine surface for software reconstruction. • The porosity analysis of samples was created by use of VGStudio MAX software. This research examined the surface and internal structure of lattice samples with the use of computed tomography. The CAD system PTC Creo Parametric 8 was used to create a 3D model of a lattice structure. For research within this paper, two samples of ABS building material were produced with the use of FDM technology. One of them was destructively tested, i.e., deformed by pressure. The untested sample contained, in addition to base material, P400SR supporting material while the tested sample only contained ABS construction material. Individual samples were subjected to microCT scanning to perform samples' analysis of dimensional and shape characteristics and their porosity. The paper describes the procedure and methodology of individual problem-solving steps. Our basic requirement was to determine surface for software reconstruction as it affects all analyzes being performed. Since the unloaded sample also contains support material, the surface area for the base material only had to be determined and support material, while reconstructing the sample, be removed. Due to higher support material density, direct segmentation of base material was impossible. In the end, the porosity analysis of samples was created with the use of VGStudio MAX software. [ABSTRACT FROM AUTHOR]

Abstract Ethnopharmacological relevance Panax notoginseng (Burk.) F. H. Chen, also called Sanqi, is a widely used traditional Chinese medicine, which has long history used as herbal medicines. It is currently an important medicinal material in China, holding the first place in the sale volume of the whole patent medicines market in China, and the market size of the single species has exceeded 10 billion yuan. In addition, P. notoginseng is an important constituent part of many famous Chinese patent medicines, such as Compound Danshen Dripping Pills and Yunnan Baiyao. P. notoginseng saponins (PNSs), which are the major active components of P. notoginseng , are a kind of chemical mixture containing different dammarane-type saponins. Many studies show that PNSs have been extensively used in medical research or applications, such as atherosclerosis, diabetes, acute lung injury, cancer, and cardiovascular diseases. In addition, various PNS preparations, such as injections and capsules, have been made commercially available and are widely applied in clinical practice. Aim of the review Since the safety and efficacy of compounds are related to their qualitative and quantitative analyses, this review briefly summarizes the analytic approaches for PNSs and their biological effects developed in the last decade. Methodology This review conducted a systematic search in electronic databases, such as Pubmed, Google Scholar, SciFinder, ISI Web of Science, and CNKI, since 2009. The information provided in this review is based on peer-reviewed papers and patents in either English or Chinese. Results At present, the chromatographic technique remains the most extensively used approach for the identification or quantitation of PNSs, coupled with different detectors, among which the difference mainly lies in their sensitivity and specificity for analyzing various compounds. It is well-known that PNSs have traditionally strong activity on cardiovascular diseases, such as atherosclerosis, intracerebral hemorrhage, or brain injury. The recent studies showed that PNSs also responded to osteoporosis, cancers, diabetes, and drug toxicity. However, some other studies also showed that some PNSs injections and special PNS components might lead to some biological toxicity under certain dosages. Conclusion This review may be used as a basis for further research in the field of quantitative and qualitative analyses, and is expected to provide updated and valuable insights into the potential medicinal applications of PNSs. [ABSTRACT FROM AUTHOR]

• During attaining restoration in repeated experiments, the contact force varies. • The contact force has increasing, steady or decreasing behaviour. • Area ellipses confirms the consistency of measurements. • Models are suitable for predicting the contact force with a constant increment. Operating conditions of rubber-textile conveyor belts represent a source of information providing a wide spectrum of operating characteristics. Various theoretical and experimental methods, mostly based on ex post approach, have been recently employed for the identification of such operating characteristics. However, this approach is not very effective and is used as a source of data for various follow-up analyses. On the other hand, the operation of conveyors requires the prediction of needed forces and adjustments of operation based on such forces. This is called ex ante approach. The paper covers an introduction of the option allowing operating characteristics to be predicted based on a tool basis determined by experimental measurements. The whole procedure is demonstrated by a specific example focusing on the prediction of the contact force – tension force relationship. The presented results have been derived using the tools of statistical analysis. The article presents only the first part of the research in which data was recorded without the material being transported, there are two reasons for this: 1. Finding information about the behaviour of the conveyor belt when it has been implemented and started without the material being transported, 2. Detection of changes occurring in the conveyor belt when burdening it with conveyed material. [ABSTRACT FROM AUTHOR]

Highlights • Analysis of fresh fruit and vegetables by FT-MIR spectroscopy is reviewed. • The review covers more than 40 genera and more than 40 different crop attributes. • Best-practice chemometric approaches for analysing these samples are outlined. • Applications are described for portable, lab-based and FT-microscope systems. • Issues impeding uptake of this novel technique are identified in future directions. Abstract In recent years, decreased cost, miniaturisation and advances in computing power and data processing software have led to widespread introduction of Fourier-transform (FT) spectrometers across different disciplines. In this review, applications of FT mid infrared (FT-MIR) spectroscopy are summarised covering the analysis of fresh fruit and vegetables, and some of their processed products (juices, jam, oil, wine). The paper also outlines basic principles of vibrational spectroscopy in the MIR region, using sugars and acids in fruit juices as exemplars of spectral interpretation. Laboratory-based spectrometers, FT-MIR microspectroscopy for high-resolution mapping, and portable, hand-held units for field work are described. Applications involving these systems, which extend to more than 40 genera, and more than 40 different crop attributes, include; assessing the maturity or quality attributes of produce, screening progeny from breeding programmes, determination of bioactive contents and plant metabolites, determining the extent of adulteration and authenticating products for type or geographic location, and localisation of metabolites within plant cells. Principles outlining best-practice for developing calibration models in fruit and vegetable-based systems are also included. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a physically acceptable analysis of stress intensity factor (SIF) for a two-tip web crack in the wide-flange (W shape) steel member widely used in steel construction subjected to the linear distribution loading. The analysis includes the effect of crack surface interference, i.e., crack surfaces are not allowed to overlap, that magnifies the SIF and crack opening displacement (COD) in an opened portion of the crack. For a range of possible web cracks in typical hot-rolled W shapes listed in the AISC Steel Construction Manual, the effective mode-I SIF is a function of applied stress, web crack length, crack eccentricity, and flange-to-web area ratio of the W shape. The depth-to-width ratio of W shape is not a significant parameter in the calculation of SIF. The analysis results show that the conventional (overlapping) solution underestimates the SIF at the tension-side crack tip under bending up to 12%. The effect of crack surface interference only exists between the conditions for complete crack opening and complete crack closure. Both conditions are governed by axial-to-bending stress ratio. Highlights • The effect of crack surface interference on magnifying the mode-I stress intensity factor (SIF) is quantified by analysis • The analysis is based on superposition of conventional (overlapping) SIF solution. • The analysis results are verified with the 3D finite element analysis using contact elements. • For typical AISC W-shapes, the conventional SIF solution underestimates SIF of two-tip web cracks under bending up to 12%. • Conditions for complete crack opening and closure, which eliminate the effect of crack surface interference, are described. • The non-overlapping analysis is applicable to polynomial loadings. [ABSTRACT FROM AUTHOR]

Abstract The role of the ITER Tokamak thermal shield system is to minimize heat loads transferred from the hot tokamak components to the cooled superconducting components. The system consists of two single wall structures fabricated from 304L-(N) stainless steel. Both structures are actively cooled with pipes permanently welded to the structure and filled with pressurized helium gas at 80K. One structure is the Vacuum Vessel Thermal Shield (VVTS), which protects magnet components from Vacuum Vessel (VV) radiation. The second structure is the Cryostat Thermal Shield (CTS), which protects magnet components from in-Cryostat components' radiations such as the Cryostat (at 293K), the VV Ports (at 393K), and the water cooling system (at 350K). In 2012, thermal analyses were performed in order to verify the thermal integrity of the ITER CTS 2010 baseline design. The heat loads to the CTS were estimated according to load specification as a homogeneous distribution based on cryostat temperature at 293K. Following this study, in order to determine a more realistic heat load distribution on the CTS panels, we performed a detailed 3D analysis of the Cryostat-CTS interspace. This paper describes the methodology used, based on view factors combined with Kirchhoff's law, to define the heat flux deposition on the CTS from its surrounding components via radiation. The previous thermo-hydraulic analysis models have been adapted using this method to define the temperature distribution and total power transmitted to the magnets. Despite an increase of 30% of the CTS total power deposition on the superconducting components in comparison to the previous analysis, we found the total heat power deposition onto the superconducting components at 4K to be within the limit of the design requirement (P≤1900W). [ABSTRACT FROM AUTHOR]

Abstract A design method for cylindrical mixing chamber ejector according to performance analyses is proposed based on the real gas properties. Compared with the experimental data, the entrainment ratio and critical back pressure calculated by the proposed method have errors within ±17% and ±6%, respectively. Ejectors with common characteristic sizes using steam, ammonia, R290 and R134a as working fluids are analyzed by this method. Consequently, design curves and regressive expressions are provided to describe the relations between entrainment ratios, ejector area ratios and expansion and compression ratios, as well as the relations between nozzle area ratios and expansion ratios. The expressions of nozzle throat areas are regressed for steam ejectors at 75–130 °C, as well as for ammonia, R290 and R134a ejectors at 75–95 °C. The design curves and regressive expressions provided by this paper can be used to design ejectors with cylindrical mixing chamber accurately and conveniently. Highlights • A performance analysis method for cylindrical mixing chamber ejector is proposed. • Ejectors using steam, ammonia, R290 and R134a as working fluids are analyzed. • The concise design method of cylindrical mixing chamber ejector is put forward. [ABSTRACT FROM AUTHOR]

In recent years, cyber-attacks against businesses and organizations have increased. Such attacks usually result in significant damage to the organization, such as the loss and/or leakage of sensitive and confidential information. Because email communication is an integral part of daily business operations, attackers frequently leverage email as an attack vector in order to initially penetrate the targeted organization. Email message allows the attacker to deliver dangerous content to the victim, such as malicious attachments or links to malicious websites. Existing email analysis solutions analyze only specific parts of the email using rule-based methods, while other important parts remain unanalyzed. Existing anti-virus engines primarily use signature-based detection methods, and therefore are insufficient for detecting new unknown malicious emails. Machine learning methods have been shown to be effective at detecting maliciousness in various domains and particularly in email. Previous works which used machine learning methods suggested sets of features which offer a limited perspective over the whole email message. In this paper, we propose a novel set of general descriptive features extracted from all email components (header, body, and attachments) for enhanced detection of malicious emails using machine learning methods. The proposed features are extracted just from the email itself; therefore, our features are independent, since the extraction process does not require an Internet connection or the use of external services or other tools, thereby meeting the needs of real-time detection systems. We conducted an extensive evaluation of our new novel features against sets of features suggested by previous academic work using a collection of 33,142 emails which contains 38.73% malicious and 61.27% benign emails. The results show that malicious emails can be detected effectively when using our novel features with machine learning algorithms. Moreover, our novel features enhance the detection of malicious emails when used in conjunction with features suggested by related work. The Random Forest classifier achieved the highest detection rates, with an AUC of 0.929, true positive rate (TPR) of 0.947, and false positive rate (FPR) of 0.03. We also present the IDR (integrated detection rate), a new measure which helps calibrate the threshold of a machine learning classifier in order to achieve the optimal TP and FP rates, which are the most important measures for a real-time and practical cyber-security application. [ABSTRACT FROM AUTHOR]

Highlights • Multi-salt sorbent of CaCl 2 /MnCl 2 is developed for a gas heating/cooling system. • The pressure drop for the sorption bed at the outlet of engine is only 380 Pa. • The volumetric heat transfer capacity is 2.3 times that of the conventional system. • The system generates the cooling power of 19 kW m−3 stably when heated at 200 °C. Abstract Multi-salt sorbents were reported with better performance than single salt sorbents because they could reduce the sorption hysteresis phenomena, but such type of sorbents have not been utilized in the refrigeration systems. In this paper, a gas heating/cooling sorption refrigeration system with multi-salt sorbent of CaCl 2 /MnCl 2 is designed and analyzed, and the results show the maximum SCP gets to about 330 W kg−1. The system is proposed for refrigerated truck transport and it makes the structure much simpler than the previous two-stage refrigeration system because only one sorption bed is required. The critical conditions, such as low heat transfer coefficient of exhaust gas and cooling air as well as high cooling temperature in hot summer, are considered. The sorption bed with a tri-pass structure for exhaust gas is compared with the tetra-pass design, and it shows better performance for that the pressure drop of the modularized sorption bed is only about 380 Pa when the air flow rate is 600 m3 h−1, and the engine performance won’t be affect if such a bed is installed at the outlet of exhaust pipe of the truck. The heat transfer performance of the bed with tri-pass for exhaust gas is analyzed by the experimental system set up in the lab, and it has a heat transfer rate of about 60 kW/m3 sorption bed during the desorption process, which is about 2.3 times that of the conventional liquid heating/cooling system. The preliminary test results show that the volumetric refrigeration capacity gets to about 19 kW m−3, increasing by almost 30% when compared with the liquid heating/cooling system. [ABSTRACT FROM AUTHOR]

Abstract Pectins are defined as a group of widely distributed plant cell wall polysaccharides that contain galacturonic acid linked at both the 1 and 4 positions. The wide use of pectin as an ingredient which imparts rheological and textural properties to various food products and the development of applications beyond the food industry have brought about its increase in production and influenced research towards alternative sources and improving the overall isolation process of pectic polysaccharides. In this context, this paper aims to give a complete perspective on the current state of pectin research by mainly focusing on recent research on the extraction of pectin from other feasible sources, on the post-extraction stages of pectin recovery from plant materials (purification and fractionation), and, finally, on the advancements in the study of the physical, chemical, rheological, and functional properties of pectin. Graphical abstract Unlabelled Image Highlights • Recently, an increasing number of studies proposed new sources for pectin extraction. • The potential of these plant wastes needs to be reviewed in order to establish sustainability. • Purification and fractionation of extracted pectin are essential steps of the isolation process. • An overview of the methods used for the analysis of pectin composition and properties is provided. [ABSTRACT FROM AUTHOR]

Abstract The complexity and vulnerability of the pediatric population make them unique to risk management. Risk analysis is particularly demanding here and requires comprehensive identification of hazardous situations. Few data are published on methods to prevent medication errors in pediatric inpatients, reducing the possibility for healthcare institutions to prioritize the actions to take. This paper summarizes the proactive risk analysis methods described in the literature, the failures identified, and the corrective actions applied to reduce the risks in pediatrics. [ABSTRACT FROM AUTHOR]

Rapid grow of biogas stations numbers across the Europe could be seen in recent past. This is also associated with an increase in the absolute number of operational accidents. In the opinion of experts who deal with safety engineering in the field of bioenergy installations, the number of accidents on biogas stations is growing faster than energy production from these stations. The aim of this paper is to open a discussion about interpretation and uncertainty of quantitative accidents assessment. For this purpose, 208 accidents of biogas stations were collected across Europe from 2006 to 2016. These data were statistically analysed. An integral part of the work is also the calculation of event frequencies for selected scenarios, which in the future can facilitate the decision making of risk experts in similar installations. The work also addresses issues related to the reduction of the risk level in the biogas station operations. [ABSTRACT FROM AUTHOR]