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Research on soil microplastics is currently at an early stage, and there is no widely approved sampling protocol. Even so, any basic research should minimize errors to ensure that they are not amplified in future research. This paper examines some weaknesses of the original research paper 'Soil microplastic pollution under different land uses in tropics, southwestern China' recently published in this journal. The authors neglected to report the equipment used for soil sampling and did not use field blank samples. There is also a soil layer that was incorrectly named. The type and pore size of filter paper used for filtration during pre-analytical soil sample preparation is very important. In this paper the nature of the filter paper used, and its larger pore sizes are questionable by today's scientists. In addition, the authors in the original paper also overlooked reporting the statistical package used for statical analysis and ensuring if all data sets obey normality, homogeneity, and equality before running the one-way ANOVA test. This statistical step is widely considered mandatory, especially in the soil science community. So, this makes it difficult to trust the results documented. Furthermore, in the original paper, the needle and stereo microscope instruments used to sort microplastic-like materials prior to proper analysis are not reliable. [Display omitted] • A dissecting needle and stereo microscope shouldn't be used to sort out soil microplastics. • Gold-coated filter paper with smaller pore size is better than nitrocellulose filter paper. • The 0–10cm is the top soil layer and 10–20cm is the subsoil layer not a deep soil layer. • The statistical package used for analysis must be documented accordingly. • If the dataset is a normal distribution prior to ANOVA testing, it must be confirmed and reported. [ABSTRACT FROM AUTHOR]

Each year, researchers publish an immense number of scientific papers. While some receive many citations, others receive none. Here we investigate whether any of this variance can be explained by the choice of words in a paper's abstract. We find that doubling the word frequency of an average abstract increases citations by 0.70%. We also find that journals which publish papers whose abstracts are shorter and contain more frequently used words receive slightly more citations per paper. Specifically, adding a 5 letter word to an abstract decreases the number of citations by 0.02%. These results are consistent with the hypothesis that the style in which a paper's abstract is written bears some relation to its scientific impact. [ABSTRACT FROM AUTHOR]

Unimodal biometric systems are susceptible to a variety of problems such as noisy data, intra-class variations, limited degrees of freedom, non-universality, spoof attacks and unacceptable error rates. Some of these limitations can be addressed by deploy multimodal biometric systems that integrates the evidence presented by multiple sources of information The proposed system provides effective fusion scheme that combines information presented by the multiple domain experts based on the Rank level fusion integration method, thereby increasing the efficiency of the system which is not possible by the unimodal biometric system. The proposed multimodal biometric system has a number of unique qualities, including principal component analysis and fisher's linear discriminate methods for individual matchers authentication. The novel rank level fusion method is used in order to consolidate the results obtained from different biometric matchers. [ABSTRACT FROM AUTHOR]

Telomerase is extensively expressed in various cancer cells and recognized as a target for cancer drug discovery. In the present study, a simple and amplification-free fluorescence assay based on polyamidoamine starburst dendrimer (PAMAM dendrimer)-activated paper device is proposed for sensitive detection of telomerase activity through hybridization of Cy5 modified single strand DNA probes with telomerase extension products. The paper substrate is fabricated by hand drawing according to a template, which is low cost, instrument free and easy operation. PAMAM is rich in amino groups on its surface and employed to immobilize the telomerase substrate (TS) primer. Highly sensitive detection of telomerase activity in HeLa cell lysate of 10 cells is achieved since the PAMAM dendrimer-activated paper surface can provide high density of binding sites for immobilization of TS primer. The experimental results also demonstrate that the assay can be employed to evaluate telomerase activity levels of various cell lines and screen telomerase inhibitors. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the application of two-step nanofiltration (NF) process was investigated in the purification of biologically treated pulp and paper wastewater for the purpose of reuse. In the first step, the effect of operating conditions such as pH, temperature, transmembrane pressure and volume reduction factor (VRF) on the membrane fouling was investigated using FM NP010 membrane. Membrane fouling was minimized by optimizing the operating conditions using Taguchi experimental design method. The smaller-the-better signal-to-noise (S/N) ratio was used to analyze the results of experiments. Flux decline caused by fouling was selected as response parameter. The best results were obtained at third level of pH (10), first level of temperature (25°C), first level of transmembrane pressure (12bar) and third level of VRF (4) which provided minimum flux decline caused by fouling (11%). Based on the analysis of variance (ANOVA), the results indicated that transmembrane pressure has significant effect on membrane fouling, while VRF shows very little effect on membrane fouling. Membrane fouling was further examined in terms of atomic force microscopy (AFM) and scanning electron microscopy (SEM) analysis. Under the optimized conditions, 91% chemical oxygen demand (COD), 92% total hardness and 98% sulphate removal were achieved using FM NP010 membrane. Also the obtained permeate is colorless and free from suspended solids. However, chloride and conductivity were partially removed. In the second step, FM NP030 membrane was used to provide better permeate quality like actual process water. Membrane fouling was also investigated in terms of flux decline, contact angle measurements and SEM analysis in this step. As a conclusion, the water produced by two step NF treatment of biologically treated pulp and paper industry meets the quality of actual process water. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to evaluate the potential of inorganic analysis techniques for the discrimination of document (multipurpose office) paper. A set of 25 different multipurpose office papers from the European market was used for comparison. It appeared that for the single techniques LA–ICP–MS had the highest overall discriminating power. Despite its lower sensitivity, XRF also showed good discriminating power but the correlation with LA–ICP–MS is high. The combination of LA–ICP–MS and IRMS provides a powerful and strongly discriminating set of techniques. [Copyright &y& Elsevier]

Abstract: With a sample of Grade 4 Chinese students, the present study examined whether the electronic version was comparable to the paper-and-pencil version of the Wallach–Kogan Creativity Tests (WKCT). It was found that the two versions generated similar patterns of reliability coefficients and inter-correlation coefficients for the eight creativity measures (verbal and figural fluency, flexibility, uniqueness, and unusualness). Results of MANOVA and subsequent ANOVA revealed that there were no significant differences in the means of all the eight creativity measures assessed by the two versions. These results provided some preliminary evidences for the comparability of the two versions of the WKCT. The availability of the electronic version of the WKCT is in step with the rapid advances in test computerization and it will definitely facilitate creativity research and theorization. [ABSTRACT FROM AUTHOR]

The purpose of this study was to compare student performance on two proctored quizzes and one practice test taken in paper-based or computer-based testing mode using an equal number of algorithmic, conceptual, and definition questions to examine the effect of testing mode when students take multiple tests in class. Data were collected from 221 students enrolled in a general chemistry course at a Midwestern university. After learning the material in lecture, students completed two quizzes: Quiz 1 and Quiz 2. One quiz was delivered on paper and another quiz was taken on computer. Each quiz tested student understanding of different chemistry concepts and the quizzes were proctored on different days. Several days after Quiz 2, students took a practice test that tested the knowledge of Quiz 1 and Quiz 2 with different yet similar questions, and again, the testing mode of the practice test was either paper-and-pencil or computer. After each quiz and the practice test, students received feedback on their performance. Differences in performance between the quizzes and the practice test were measured with normalized gains and the differences between the normalized gains for each condition were analyzed using an Analysis of Variance. The results showed no significant testing mode effects among the four conditions overall, or for algorithmic, conceptual, or definition type of questions. Altogether, the results of the present study do not provide evidence to suggest that instructors need to be concerned about testing mode (paper versus computer) when designing and administering chemistry tests. [ABSTRACT FROM AUTHOR]

Abstract: This study compared the measurement invariance of paper-and-pencil (PP) and web-based (WB) administration formats through a humor survey. Participants were 401 undergraduate students divided into four groups (A, B, C, and D), and each group completed one of the four testing conditions (group A: PP→PP, group B: PP→WB, group C: WB→PP, and group D: WB→WB). The WB and PP versions of the revised Multidimensional Sense of Humor Scale (Wang, Cheng, Liu, & Ho, 2011), which measure humor production, attitudes toward humor, and humor coping, were administered to the participants. The results indicated that both of the PP and WB survey formats were practically invariant. No significant differences across administration situations were found for humor production or humor coping. Interestingly, the mean score of the WB format was significantly higher than that of PP format on attitudes toward humor. The findings suggest that researchers should carefully examine the measurement invariance and the effect of characteristics of the construct on measurement results when using a WB-format instrument. [Copyright &y& Elsevier]

This study explored the relationship between syntactic complexity and rhetorical functions and the relationship between syntactic complexity and level of move/step realization in learner-generated research paper introductions. We created a corpus of 79 introductions written by undergraduate L2 students at intermediate to high-intermediate levels. We annotated the introductions for moves and steps, measured their syntactic complexity at the global, clausal, and phrasal levels, and rated their level of move/step realization across four levels (no, low, intermediate, and high). We conducted one-way MANOVA, one-way ANOVA, Pearson correlation, and stepwise multiple linear regression analyses. We found sentences realizing Reviewing items of previous research function to be significantly longer than other steps in Move 1 and to contain significantly more clausal and phrasal complexity features. Sentences performing Claiming c entrality function also demonstrated significantly more phrasal complexity features as measured by complex nominals per clause. We also found a higher level of phrasal complexity in introductions with a higher level of move/step realization, which can be attributed to introductions including Step1 and Step3 , rather than containing all steps. Our findings imply that there is value in developing explicit instructions on how to use complex structures in performing rhetorical steps in research paper introductions. [ABSTRACT FROM AUTHOR]

Many current standardized testing and teaching practices approach media for composition with the assumption that media do not influence the writing process in significant ways. This study seeks to determine whether emergent media used for student writing influence essay composition (in terms of quantifiable text indicators) and compares a set of eighth-grade student essays composed via Chromebooks ( n = 139) to those written by hand ( n = 319). Essays were collected from students across three (3) schools, and descriptive results corroborate previous findings that Chromebook essays were generally longer than handwritten essays. ANOVA hypothesis testing on Flesch-Kincaid reading ease and grade level scores yielded new knowledge with regard to writing complexity as they indicated that Chromebook essays exhibited a significantly higher grade-level of writing and greater reading difficulty. This suggests greater complexity in word usage and sentence composition among Chromebook essays when compared to handwritten essays and also suggests that the medium itself may have an effect upon the complexity of student writing. [ABSTRACT FROM AUTHOR]

• International mathematical contest papers are an emerging type of research paper. • Metadiscourse analysis showed variances in use in winning papers across cultures. • Clear writing was more important than native-like writing in math contest papers. • Using IR and text analysis in an EAP course may increase contest competitiveness. Practitioners of English for Academic Purposes (EAP) are responsible for preparing students to fulfill the expectations of an ever-growing number of written genres. One emerging application of the research paper genre is found in a related pair of highly competitive international contests, the Mathematical Contest in Modeling (MCM) and Interdisciplinary Contest in Modeling (ICM). Through a lens of intercultural rhetoric (IR) and English as a lingua franca (ELF), this paper examines a metadiscourse analysis of 38 summary and 38 conclusion sections of MCM/ICM Outstanding Winner papers, half of which were written by Chinese teams and the other half by American teams. The study found that while both Chinese and American writing depended heavily on the use of metadiscourse in the two sections, there are distinct differences in the frequency and linguistic realization of metadiscourse across cultures. The paper concludes with proposed pedagogical applications of findings in designing an EAP course to prepare international student teams to be more competitive in their MCM/ICM writing. In line with recent research in IR and ELF, the current research demonstrates that the MCM/ICM contests do not require students to hold strictly to "native-speaker" levels of writing as long as the contest papers are mathematically and logically sound. [ABSTRACT FROM AUTHOR]

• Gift-wrapping paper made fragrant by screen-printing with UV-curable varnish mixed with encapsulated lavender essential oil. • Encapsulate lavender essential oil with Gelatin and gum-arabic complex coacervate. • Optimize encapsulation for strengths, releases and morphologies of microcapsules. • Optimize fragrant varnish for strengths, releases, and encapsulation capacity. • Make paper fragrant without modifying or interfering with the actual printing. The applicability of making a gift-wrapping paper fragrant by screen-printing with a varnish that contained microencapsulated fragrance were assessed. Experiments were conducted on a commercially available, general use, Lavender (Lavandula Angustifolia) essential oil. The encapsulation was made by a complex coacervating technique, with gelatin and gum-arabic as the wall materials. Factors in the encapsulating process were studied with the attempts to control the strength, the release and the morphologies of microcapsule. The statistical tools including the analysis of variance, the main effect plot, and the rolled throughput yield were used in identifying the controlling factors and the best performing conditions for encapsulation. Fragrant varnishes made by mixing the microcapsule into a commercially available UV-curable varnish were evaluated and optimized for the essential oil loading capacity, the release by rubbing with fingers, the protection against untimely release, and the load withstanding in handling, storage and transportation. All the practices specifically required to produce a fragrant gift-wrapping paper were done without the need to modify or to interfere with the actual screen-printing process. The overall results signified its potential in applications like special ordered or customized, small volume gift-wrapping papers, and the likes. [ABSTRACT FROM AUTHOR]

Abstract: Background: Paper based simulated patients are widely used to analyse nurses’ clinical judgements. However, developments in the physical simulation of clinical environments offer exciting, but relatively underexploited, opportunities for exploring nurses’ judgements. Critical event risk assessment is an element of acute care practice which lends itself well to simulation and in which more clinical experience is often assumed to lead to better quality judgements. Objectives: To model nurses’ judgements of critical event risk using physical and paper simulation and to examine whether improving fidelity via physical clinical simulation impacts on the apparent benefits of clinical experience on nurses’ judgement performance. Design: A comparative clinical judgement analysis. Setting: A university in Northern England. Methods: Sixty-three nursing students and 34 experienced nurses made dichotomous risk assessment judgements (“at risk” or “not at risk”) in response to 25 paper and physical simulated scenarios. These were randomly generated from a dataset of real patient case records. Clinical outcomes (the judgement criteria) for a ‘correct’ judgement were derived from the same case records. Logistic regression models were constructed to derive statistics for each nurse representing various measures of judgement performance: achievement (r a ), consistency (R s ) and clinical information use (G). These statistics were known as Lens Model statistics (from the psychological theory of Brunswik''s Lens Model of judgement). Performance measures for novice and experienced nurses were compared. Results: No significant differences in judgemental achievement (r a ) between experienced nurses and students were observed in either paper or high fidelity clinical simulations. Similarly, there were no significant differences in the nurses’ abilities to correctly match the ways they synthesised clinical information with the optimum synthesis required by the task (policy matching) (G). When faced with “paper patients” experienced nurses exercised more cognitive control/consistency (R s ) than students (P =0.04). However, this heightened control in experienced nurses was absent when those same nurses made judgements in the higher fidelity clinical simulation environment. Conclusion: Clinical experience made no difference to nurses’ judgement achievement (accuracy) in either the lower fidelity paper scenarios or the higher fidelity setting of the clinical simulation unit. The significant impact of clinical experience on judgement consistency was negated by the increases in fidelity offered through clinical simulation. [Copyright &y& Elsevier]

Objective: The aim of this study was to compare the effects of medium light roast (MLR) and medium roast (MR) paper-filtered coffee on cardiovascular risk factors in healthy volunteers. Methods: This randomized crossover trial compared the effects of consuming three or four cups (150 mL) of MLR or MR coffee per day for 4 wk in 20 healthy volunteers. Plasma lipids, lipoprotein( a) (Lp[a]), total homocysteine, and endothelial dysfunction-related inflammation biomarkers, serum glycemic biomarkers, and blood pressure were measured at baseline and after each intervention. Results: Both roasts increased plasma total cholesterol, low-density lipoprotein-cholesterol, and soluble vascular cell adhesion molecule-1 (sVCAM-1) concentrations (10%, 12%, and 18% for MLR; 12%, 14%, and 14% for MR, respectively) (P < 0.05). MR also increased high-density lipoporteincholesterol concentration by 7% (P = 0.003). Plasma fibrinogen concentration increased 8% after MR intake (P = 0.01), and soluble E-selectin increased 12% after MLR intake (P = 0.02). No changes were observed for Lp(a), total homocysteine, glycemic biomarkers, and blood pressure. Conclusion: Moderate paper-filtered coffee consumption may have an undesirable effect on plasma cholesterol and inflammation biomarkers in healthy individuals regardless of its antioxidant content. [ABSTRACT FROM AUTHOR]

Abstract: presented a bias adjustment to the jackknife variance estimator of in the presence of non-response. In their paper, they obtained a second-order approximation of the bias of the Rao-Sitter variance estimator and then proposed a bias-adjusted estimator based on this approximation. To compare their proposed variance estimator to various other variance estimators, they performed a simulation study and showed that their variance estimator is superior to the Rao-Sitter variance estimator. In fact they showed that the Rao-Sitter variance estimator suffers from severe underestimation. These results contradict those in the literature, which indicate that the Rao-Sitter variance estimator suffers from a positive bias if the sampling fractions are not negligible; see , and . Because of this contradiction, we felt that a further investigation was warranted. In this paper, we attempt to recreate the results of and, in fact, show that their second order approximation to the bias of the Rao-Sitter variance estimator is incorrect and that their simulation results are also questionable. [Copyright &y& Elsevier]

Abstract: Computer-based interventions are being used more in the classroom. Student responses to these interventions often contribute to decisions making regarding important outcomes. It is important to understand the effect of these interventions within the context of the intervention as well as across related context. The current study examined the generalization of math fact fluency gains resulting from a computer-based intervention to paper-and-pencil performance. A total of 31 second grade students completed fluency drills on the computer or with paper and pencil. Pretest–posttest performance on both computer and paper and pencil for all students was evaluated using a doubly multivariate repeated measure ANOVA. Results indicated that gains achieved on the computer did not generalize to paper-and-pencil performance. [Copyright &y& Elsevier]

Abstract: Objective: To assess the measurement equivalence of an interactive voice response (IVR) version of the EQ-5D with the original paper version. Methods: Subjects were randomly assigned to: 1) paper then IVR, or 2) IVR then paper and asked to complete the questionnaire two days apart. The analyses tested mean differences (repeated measures analysis of variance) and reliability (intraclass correlation coefficient [ICC]). Equivalence of the means was established if the 95% confidence interval (CI) of the mean difference was within the minimally important difference interval: −0.035 to 0.035 for the EQ-5D index and −3 to 3 for the visual analog scale (EQ VAS). ICC adequacy was tested by comparing the ICC 95% lower CI with a critical value of 0.70. Results: The analyses included 113 subjects for the index and 109 subjects for the EQ VAS. For the index, the adjusted means of the paper and IVR versions were 0.789 ± 0.016 and 0.798 ± 0. 017, respectively. The 95% CI of the mean difference was −0.024 to 0.006, within the equivalence interval. The ICC was 0.894 (95% lower CI 0.857), significantly greater than 0.70. For the EQ VAS, the adjusted means were 71.94 ± 1.87 for paper and 74.63 ± 1.79 for IVR. The 95% CI of the mean difference was −4.347 to −1.049, partially within the equivalence interval. The ICC was 0.887 (95% lower CI 0.840), significantly greater than 0.70. Conclusions: The results provide evidence that the EQ-5D scores on the IVR version were sufficiently equivalent to those obtained on the paper version. [Copyright &y& Elsevier]

Abstract: Self-monitoring has traditionally been done using a paper record, which can be tedious and burdensome. A personal digital assistant (PDA) with dietary software can provide an alternative to a paper record. The study aimed to describe the differences in dietary changes at 6 months between participants randomly assigned to use a paper record or PDA for self-monitoring in a clinical trial of weight-loss treatment. Self-monitoring adherence and changes in weight and diet were assessed between 2006 and 2009. The sample (n=192) was 84% female and 78% white, with a mean age of 49 years and body mass index (calculated as kg/m2) of 34.1. At baseline, the groups did not differ in energy intake, percent calories from fat, and number of servings of the examined food groups. At 6 months, both groups had significant reductions in weight, energy intake, and percent calories from total fat and saturated fatty acids (P<0.001); no between-group differences were found. Compared to the paper record group, the PDA group significantly increased consumption of fruit (P=0.02) and vegetables (P=0.04) and decreased consumption of refined grains (P=0.02). Interactions among self-monitoring and the two groups were found in relation to changes in percent calories from total fat (P=0.02), monounsaturated fatty acids (P=0.002), and trans-fatty acids (P=0.04). Frequent self-monitoring was significantly associated with total sugar (P=0.02) and added sugar (P=0.01) intake in both groups. Our findings suggest that use of a PDA for self-monitoring might improve self-awareness of behavior and dietary changes. [Copyright &y& Elsevier]

Abstract: Wood extractives present in pulp and paper mill effluents may cause reproductive disturbances in fish. A chronic-exposure toxicity experiment using immature rainbow trout (Oncorhynchus mykiss) was conducted in order to assess the endocrine disrupting effects of two Chilean pulp and paper mill specific extracts (solid phase extraction, SPE) obtained from primary and secondary treated effluents. The (anti)estrogenic potencies and toxicity of the wood extractives regularly present in pulp mill effluent such as dehydroabietic acid (DHAA), β-sitosterol (BS), and model estrogen 17β-estradiol (E2) were evaluated by analysis of plasma vitellogenin (VTG) levels, gonadal somatic index (GSI) and liver ethoxyresorufin-O-deethylase (EROD) activity, respectively. The protocol involved the use of multiple intra-peritoneal injections (1 injection every 7 days for a total exposure period of 28 days). Analysis of variance/covariance, demonstrated no differences associated with fish gender other than GSI. The phytosterol BS, E2 and both pulp mill effluent extracts showed significant inductions of EROD and increased VTG levels after 4, 7, 14, 21 and 28 of exposure. While fish injected with secondary treated effluent extract showed a delayed induction in VTG levels compared to primary effluent injected fish, no effects on VTG and EROD levels were observed in DHAA injected fish. Moreover simultaneous injection of DHAA+E2 reduced the VTG levels found in E2 injected fish, indicating a potential indirect anti-estrogenic effect of this resin acid. The results of this study indicate that Chilean pulp and paper mill effluent extracts are estrogenic in rainbow trout males and females. [Copyright &y& Elsevier]

Abstract: This paper proposes an alternative analytical method using energy dispersive X-ray fluorescence (EDXRF) to determine Fe and Cu in gasoline samples. In the proposed procedure, samples were distilled and the distillation residues were spotted on cellulose paper disk to form a uniform thin film and to produce a homogeneous and reproducible interface to the XRF instrument. The disks were dried at 60°C for 20min and copper and iron were determined directly in the solid phase at 6.40 and 8.04keV, respectively. The calibration curves showed linear response in the 20–800μgL−1 concentration range of each metal. The precisions (repeatability) calculated from 15 consecutive measurements and defined as the coefficient of variation of solutions containing 100μgL−1 of Fe and Cu were 7.8 and 8.1%, respectively. The limits of detection (LOD), defined as the analyte concentration that gives a response equivalent to three times the standard deviation of the blank (n =10), were found to be 10 and 15μgL−1 for Fe and Cu, respectively. The proposed method was applied to copper and iron determination in gasoline samples collected from different gas stations. [Copyright &y& Elsevier]

This is the first in a short series of papers on measurement theory and practice with particular relevance to intervention research in nursing, midwifery, and healthcare. In this article I discuss reliability, its origins in classic measurement theory, important issues to consider when operationally defining reliability for a particular study, correlational procedures for assessing the reliability of data once collected, including test-retest reliability, split-half reliability, and Cronbach's coefficient a. Some important insights into reliability provided by attenuation theory are also offered. [ABSTRACT FROM AUTHOR]

Abstract: This paper promotes the concept of active models in image-guided interventions. We outline the limitations of the rigid body assumption in image-guided interventions and describe how intraoperative imaging provides a rich source of information on spatial location of anatomical structures and therapy devices, allowing a preoperative plan to be updated during an intervention. Soft tissue deformation and variation from an atlas to a particular individual can both be determined using non-rigid registration. Established methods using free-form deformations have a very large number of degrees of freedom. Three examples of deformable models – motion models, biomechanical models and statistical shape models – are used to illustrate how prior information can be used to restrict the number of degrees of freedom of the registration algorithm and thus provide active models for image-guided interventions. We provide preliminary results from applications for each type of model. [Copyright &y& Elsevier]

Results from animal studies show that hearing loss can result in increased neural responsiveness within the central auditory system. This study employed auditory middle latency evoked responses to compare central auditory responsiveness in human males with and without hearing loss. Measurements of auditory middle latency responses (MLRs) recorded from 14 normal hearing males were compared with MLR measures from 14 males with high-frequency, sensorineural hearing loss. Sixteen toneburst stimuli (four frequencies×four intensities) were used. Slopes of the amplitude–intensity functions for the several components of the MLR were obtained for each subject at frequencies below, near, and above the audiometric edge. Analysis of variance (ANOVA) revealed a significant group effect for MLR component Pa–Na, with less steep slopes at all frequencies for the hearing-impaired group. The ANOVA also showed a trend towards a significant group effect for Pb–Nb. Two-sample t-tests performed for Pb–Nb for each of the four tonebursts showed a frequency-specific effect. For Pb–Nb there was a statistically greater mean slope for the hearing-impaired group at the toneburst frequency associated with the audiometric edge. [Copyright &y& Elsevier]

Analysis of variance (ANOVA) may be required by researchers as an inferential statistical test when more than two means require comparison. This paper explains how to perform ANOVA in Microsoft Excel. [ABSTRACT FROM AUTHOR]

Data may be normally distributed in which case standard and relatively familiar tests may be used for inferential testing. Or data may be non-normally distributed, such as ordinal data, in which case, non-parametric tests are usually advocated. This paper will review current thinking with regard to these tests, and the appropriateness of their application/s. [ABSTRACT FROM AUTHOR]

The grinding process of the angle grinder generates a large amount of dust, which present hazards to the environment and workers' health. In order to capture the grinding dust more efficiently, this paper optimizes the performance of the dust collection hood of the angle grinder by building a grinding experimental platform and using the response surface method (RSM). Using the Box-Behnken design method, the collection quantity M total of all dust particles generated by grinding and the collection quantity M PM10 of PM10 are used as the main performance indicators of the dust collector. Four independent factors such as grinding wheel diameter, suction pipe diameter, mounting angle, and grinding wheel speed of the dust collection hood were optimized to arrive at the best combination of parameters. Through response surface analysis, a quadratic polynomial regression model between each influencing factor and performance indicator is established, and significance test and variance analysis are performed to verify the validity and applicability of the model. Finally, through three-dimensional response surface plots and contour plots, the interactions between each influencing factor are analyzed, and the predicted values of performance indicators under optimal experimental conditions are determined. The experimental results show that the mounting angle has the greatest impact on M total , and the grinding wheel speed has the greatest impact on M PM10. The field engineering application shows that the optimized dust collection hood can effectively prevent dust from escaping. The reduction efficiency of total dust concentration in the grinding place is over 83.6 %, and the reduction efficiency of respirable dust concentration is over 90.0 %. The research results of this paper provide some reference value for the research and application in the field of dust control. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper we consider an orthonormal basis, generated by a tensor product of Fourier basis functions, half period cosine basis functions, and the Chebyshev basis functions. We deal with the approximation problem in high dimensions related to this basis and design a fast algorithm to multiply with the underlying matrix, consisting of rows of the non-equidistant Fourier matrix, the non-equidistant cosine matrix and the non-equidistant Chebyshev matrix, and its transposed. Using this, we derive the ANOVA (analysis of variance) decomposition for functions with partially periodic boundary conditions through using the Fourier basis in some dimensions and the half period cosine basis or the Chebyshev basis in others. We consider sensitivity analysis in this setting, in order to find an adapted basis for the underlying approximation problem. More precisely, we find the underlying index set of the multidimensional series expansion. Additionally, we test this ANOVA approximation with mixed basis at numerical experiments, and refer to the advantage of interpretable results. [ABSTRACT FROM AUTHOR]

The paper presents a novel low power, low noise and high CMRR current feedback instrumentation amplifier (CFIA) design for biomedical signal acquisition i.e. EEG/ECG applications is presented. The proposed instrumentation amplifier performance is evaluated using 0. 18 μ m , CMOS technology with 1.8 V supply and results are obtained in Cadence EDA tool. The proposed CFIA is implemented using a dual output bandwidth boosted folded cascode operational amplifier (BBFC OP-AMP) active block. In this paper the proposed CFIA performance parameters has been considered for optimization to get better results by using the idea of signal to noise ratio (SNR) with Taguchi design of experiments (Taguchi DoE) and analysis of variance (ANOVA) to estimate the most important independent variable which control the performance of the design. The bias voltage, channel length and width of input MOS transistors have been selected to optimize the proposed circuit performance. The proposed CFIA structure have 50.33 to 69.67 dB tunable differential gain, common mode rejection ratio (CMRR) of 143.19 dB, tunable bandwidth of 148.24 kHz to 1.31 MHz, dynamic range (DR) of 74.31 dB and 297.73 dB of figure of merit (FoM). The CFIA shows an equivalent input referred noise (IRN) of 0.586 μ V at 0.1 Hz to 148.24 kHz frequency range, with total power dissipation of 102.73 μ W and occupies 8194 μ m 2 of core area. The simulation results of the proposed CFIA are close to the predicted solution obtained from ANOVA. The PVT analysis and post layout simulation has been performed to check the robustness of the proposed design. The proposed design has been compared with the other existing literature which shows the competence of the design. • The BBFC OP-AMP avoids external R, C elements to achieve improved compensation. • Feedback for offset, noise minimization and self-biasing in load, tail source. • BBFC OP-AMP based CFIA offers wide BW without degrading gain, improves NEF and FoM. • Taguchi DoE and ANOVA provide sizes of MOS transistors to achieve optimized results. • High tunable gain, high CMRR and low power promising for the biomedical applications. [ABSTRACT FROM AUTHOR]

• The emissivity of ultra-thin graphene based films (G-paper) were assessed. • Two different measurement technique were adopted. • The effect of graphene content (%) and temperature on the emissivity were also investigated. • Design Of Experiment and ANalysis Of VAriance, were adopted. • The factors affecting the emissivity were identified. In the present paper, an experimental procedure to measure the emissivity of ultra-thin graphene based films (G-paper) is presented, with the aim to determine the effect of measuring temperature and graphene concentration on the G-papers emissivity. To this end, two methods were adopted, both according to the ASTM E1933 Standard: Contact Thermometer Method (CTM) and Noncontact Thermometer Method (NTM). The latter was modified in order to take in account the specimens characteristics. In both the cases an IR camera, with a spectral range of 7.5–14 μm, was adopted. The experimental tests were performed by heating 50 μm thick G-papers, with different graphene contents (in the range 70–100%). The tests were carried out in the temperature range of 80–200 °C. During the NTM tests, a conductive paint was adopted as reference materials for the temperature measuring. Before the tests, the paint calibration curve was obtained. Statistical methodologies, Design Of Experiment and ANalysis Of VAriance, were adopted in order to identify the factors affecting the emissivity. Results show that the measuring temperature and the test methods do not affect the emissivity. The latter decreases at the graphene content increase and vary in the range of 0.38–0.51, minimum and maximum values measured for a graphene content of 100% and 70% respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • Analytical error variance propagation. • Analysis of white noise, bias instability, rate random walk, and correlated noise. • Comparison of the relative importance of each error factor. • Using a more suitable model for bias instability. Understanding and mitigating the various stochastic errors in gyroscope measurements is crucial for accurate attitude determination. White noise and bias instability can introduce drift errors, reducing the system's accuracy. Efficient sensor selection and algorithm design necessitate a thorough understanding of these influences and how they propagate throughout the system. This paper addresses the propagation of significant stochastic errors in the attitude determination system, including white noise (angle random walk), bias instability, rate random walk, and correlated noise. The paper discusses the modeling strategy and statistical characteristics of these error contributors. It then evaluates the variance propagation of these errors within the output of a single-axis attitude determination system. The presented analysis calculates and compares the impact of each source of error on the system's precision over time. Experiments with the MPU6050 and L3G4200D sensors are conducted to validate the analytical results. [ABSTRACT FROM AUTHOR]

Analyzing vibration of rotating machinery signals is a popular methodology derived on the potent tools provided by cyclostationary process theory. Among them, the autocorrelation function (ACF), the Fourier transform (FT), the short-time Fourier transform (STFT), and the time synchronous average (TSA) are widely used for enhancing and analyze random cyclostationary components, i.e., repetitive impulses. This paper aims to thoroughly investigate these techniques through a comprehensive scientific research process. Initially, theoretical analyses are conducted to discuss their noise suppression principles, on the foundation of mean and variance analysis. Results indicate that for Gaussian random noise, the variance of the noise linked to the ACF, the FT, and TSA almost decreases linearly with signal length, while the noise variance of the short-time Fourier transform does so with window length. Therefore, longer signal lengths for the ACF, the FT, and the TSA, or extended window lengths for the STFT, improve their denoising performance. Subsequently, a series of simulated signals are generated to validate these findings, complemented by public datasets for further verification. Finally, the paper discusses and concludes with enhancement approaches derived from these four methodologies. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of stochastic modeling of atomic ensembles under multi-source noise and makes the model interpretable. First, based on Itô's lemma and Allan variance analysis (ITÔ-AVAR), an approach is proposed to model nonstationary stochastic submodels of atomic ensembles. On this basis, the variance decomposition and nonlinear optimization algorithms are utilized to hybridize modeling atomic ensembles with nonlinear and nonstationary properties. Second, an Itô's lemma dynamic allan variance analysis (ITÔ-DAVAR) approach is developed for online modeling of atomic ensembles. Further, an atomic ensembles sensitivity enhancement scheme based on the proposed approach is given, which effectively promotes the progress of quantum instrument engineering. Finally, the proposed scheme are deployed in the optical pumping magnetometer and spin-exchange relaxation-free comagnetometer, respectively, while experimentally verifying the sensitivity of the spin-exchange relaxation-free comagnetometer reaches 5. 36 × 1 0 − 6 deg s − 1 Hz − 1 / 2 . • An approach is proposed for modeling nonstationary stochastic submodels of atomic ensembles using Itô's lemma and Allan variance analysis. • Combining the variance decomposition and the nonlinear optimization algorithm to hybrid model the atomic ensembles. • A sliding-window technique is employed to realize real-time online modeling of the atomic ensembles, ensuring adaptability and practicality. • An atomic ensembles sensitivity improvement scheme is proposed to promote its engineering progress. • The effectiveness of the proposed approach is verified through numerical simulations and practical experiments. [ABSTRACT FROM AUTHOR]

The urgency of addressing climate change and reducing carbon emissions necessitates the establishment of effective carbon markets. Our paper focuses on assessing and interpreting the efficiency of carbon markets, which is a crucial aspect of their successful implementation. We selected Hubei, Shenzhen, and Guangdong carbon pilots as examples to measure their dynamic information efficiency by combining the rolling time window and wild-bootstrap variance ratio test. Furthermore, we combined SHapley Additive exPlanations (SHAP) and Extra Trees (ET) regressor to reveal the nonlinear relationship between market performance and efficiency. Our findings highlight the time-varying nature of carbon market efficiency and reveal that China's carbon market has not yet achieved stable weak-form efficiency. Additionally, we identified excessive trading volume volatility as a significant constraint on market efficiency, while the trading volume itself exhibits weak explanatory power. Our proposed hybrid model demonstrates superior predictive and explanatory capabilities, offering regulators a valuable tool for continuously monitoring and interpreting carbon market efficiency. Finally, we suggested that reducing trading volume volatility should be a major concern for regulators to optimize market operations at present. [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia has developed rigorous strategies to control and prevent the spread of COVID-19. However, the effectiveness of these measures in containing and mitigating the epidemic has yet to be studied. This paper aims to assess the efficiency of preventive policy initiatives that Saudi Arabia has taken to reduce the spread of COVID-19, which was rapid and progressive in nature. Information on the effectiveness of measures applies to help the Saudi government adjust policy responses when considering which measures to relax once the epidemic is controlled. Data for this study were retrieved via publicly available data sources such as the Saudi Arabia Ministry of Health and the government's official news agency—Saudi Press Agency (SPA) websites. Other datasets, such as prevention measures, were gathered from the Country Policy Tracker website. Our dataset's time component extends over 590 consecutive days from 20 January 2020–31 August 2021. Moreover, a mixed-method approach combining COVID-19 data and prevention measures was adopted to assess preventative measures practice. We compiled the dataset used in this study in a Microsoft Excel database. The significance of observed differences among implementing effective strategies was determined using ANOVA and Mixed methods approach. Noticeably, the statistical analysis was performed using the open-source statistical system R version 4.2 (available at http://cran.r-project.org). Our analysis showed that only three out of the 32 (9.4%) measures significantly reduced the spread of COVID-19. Our results also show substantial variations in the spread of COVID-19 associated with preventive measures in Saudi Arabia. There was a significant positive correlation between activating and massive testing in communities and cases of COVID-19 (measure effect = 923.086 and p < 0.05). A similar result was found for complete curfew across the Kingdom and cases of COVID-19 (measure effect = 621.389 and p < 0.10). Removing slum areas interrupted the spread of Covid-19 (measure effect = 305.689 and p < 0.01). The other preventive measures did not significantly affect the COVID-19 pandemic distribution. These findings consistently concluded that activating and massive testing in communities, complete curfew across the Kingdom, and removal of slum areas were the most effective measures for reducing the impact of the COVID-19 pandemic. Only by understanding these correlations will it be possible to control and reduce the rate of COVID-19 spread and, therefore, suggest a possible exit strategy once the epidemic is controlled. [ABSTRACT FROM AUTHOR]

• Functional data analysis (FDA) for Rating Scale (RS) Time-Intensity (T-I) data. • The mean RS functional curves and their 1st and 2nd derivative curves. • The index of efficiency (A.RS) based on area under curve for percentage (%) relief. • Functional analysis of variance (FANOVA) for detection of group effects. A longitudinal study was undertaken recently in the USA to investigate the perceptual efficacy of a supplement tablet. Efficacy was assessed using an 11-attribute 5-point Rating Scale (RS). The RS diary time-intensity data were analyzed using functional data analysis (FDA). The mean RS functional curves and their 1st and 2nd derivative curves are produced. Attribute intensities (symptom relief) are compared to baseline measures. Two indices of efficacy were used to measure reduction in symptom severity. Results show symptoms decreased over the 12-week study with use of the tablet. The focus of this paper is on applied use of FDA and the new index A.RS which shows advantages by providing examination of the full range of longitudinal data (0–84 days) and a percentage efficacy index versus a traditional efficacy index that is based on the difference between just two time points (day 0 and day 84). The analytic methods in this paper have relevancy for sensory and consumer time-intensity research and longitudinal study. [ABSTRACT FROM AUTHOR]

Toxic organic chemicals present in industrial effluents were screened to design mixtures for examining the significant main and interaction effects among mixture components. A set of five four-component mixtures was selected by examining effluents from organic chemical, textile-dye, pulp-paper and petroleum refinery industries. The screening was based on their discharge, solubility, toxicity and volatility. A 2 n full factorial approach was used in designing the mixtures, containing components at two dose levels, EC10(−) and EC40(+). Each mixture resulted in 16 combinations. Mixture toxicity was measured using the Vibrio fischeri bioluminescence inhibition assay. The main effects and binary, ternary and quaternary interaction effects were determined and the significance of effects was evaluated using normal order score and multifactor ANOVA. The organic chemicals retained after screening included, acetaldehyde, aniline, n-butanol, p-cresol, catechol, ethylbenzene, naphthalene, phenol, 1,2,4 trimethylbenzene and o-xylene. In all mixtures, the magnitude of main effects was more significant than the interaction effects. The trend in the main effect of components in any mixture was affected by the trends in the physico-chemical properties of the components, i.e., partition coefficient, molecular size and polarity. In some mixtures, a component with significantly higher concentration and significantly lower toxicity was found to depict a relatively high main effect, as observed for acetaldehyde in mixture I and n-butanol in mixture III. Normal order score approach failed to identify the significant interaction effects that could be identified using multifactor ANOVA. In general, the binary interactions were more significant than the ternary and quaternary interactions. [Copyright &y& Elsevier]

Reflection is a key activity in self-regulated learning (SRL) and a critical part of health professions education that supports the development of effective lifelong-learning health professionals. Despite widespread use and plentiful theoretical models, empirical understanding of and support for reflection in health professions education remains limited due to simple manual assessment and rare feedback to students. Recent moves to digital reflection practices offer opportunities to computationally study and support reflection as a part of SRL. The critical task in such an endeavor, and the goal of this paper, is to align high-level reflection qualities that are valued conceptually with low-level features in the data that are possible to extract computationally. This paper approaches this goal by (a) developing a unified framework for conceptualizing reflection analytics in health professions education and (b) empirically examining potential data features through which these elements can be assessed. Synthesizing the prior literature yields a conceptual framework for health professions reflection comprised of six elements: Description, Analysis, Feelings, Perspective, Evaluation, and Outcome. These elements then serve as the conceptual grounding for the computational analysis in which 27 dental students' reflections (in six reflective statement types) over the course of 4 years were examined using selected LIWC (Linguistic Inquiry and Word Count) indices. Variation in elements of reflection across students, years, and reflection-types supports use of the multi-dimensional analysis framework to (a) increase precision of research claims; (b) evaluate whether reflection activities are engaged in as intended; and (c) diagnose aspects of reflection in which specific students need support. Implications for the development of health professions reflection analytics that can contribute to SRL and promising areas for future research are discussed. • Presentation of synthesized theoretical framework for reflection analytics. • Conceptualization of reflection quality through six components. • Alignment of textual linguistic markers with conceptual elements of reflection. • Analytic detection of reflection variation across students and over time. • Identification of applications for actionable feedback to support self-regulated learning (SRL). [ABSTRACT FROM AUTHOR]

Cyber security has been drawing massive attention in recent years due to human reliance on new technology, and systems. Therefore, securing these systems against cyber-attacks has become an essential task nowadays. The advanced persistent threat is one of the most sophisticated cyber-attacks in which malicious actors gain unauthorized access to a network and remain undiscovered for a lengthy period of time. The number of recorded advanced persistent threat attacks and threats to organizations intensifies. One method used in detecting advanced persistent threat attacks is machine learning. However, this method has not been covered in many previous kinds of research due to the lack of datasets covering an entire advanced persistent threat attack lifecycle. Thus, this paper aims to build a new dataset that covers the complete life cycle of an advanced persistent threat attack to detect them in different stages such as normal, reconnaissance, initial compromise, lateral movement, and data exfiltration activities. The newly collected dataset is based on advanced persistent threat attacks using tactics, techniques, procedures, and indicators of compromise. Then, it is applied to a proposed machine learning model employing eXtreme gradient boosting and analysis of variance feature selection method. The model was compared to other traditional classifiers: random forest, decision tree, and K-nearest neighbor. Based on the accuracy score of the proposed model 99.89% using only 12 features, it proved to be more powerful and efficient than the other classifiers in detecting advanced persistent threat attacks. The dataset used in this research is newly built based on advanced persistent threat attack behaviors, which will aid organizations in detecting advanced persistent threat attack activity efficiently. The experimental evaluation proved that the proposed method effectively detects advanced persistent threat attacks at different stages. [ABSTRACT FROM AUTHOR]

This paper elaborates experimental analysis of cardboard/sawdust briquettes as a viable option for biomass fuel. Physical–mechanical and thermal characteristics of cardboard/sawdust briquettes were investigated. The influence of the main parameters on heating content was also examined through an ANOVA and regression analysis, i.e. pressure influence (that was applied in a punch-and-die process), cardboard/sawdust ratio influence and finally drying temperature influence. In order to find the maximum heating value, minimum ash content and maximum compressive strength optimization were done. The optimal values obtained for the studied briquetting process parameters are a compression force of 588.6 kN, a sawdust mass of 46.66% and a drying temperature of 22 °C. According to the mathematical model obtained, these optimal values give a maximum higher heating value of 17.41 MJ/kg, a minimum ash content of 6.62% and a maximum compressive strength of 149.54 N/mm. Finally, Cardboard/sawdust briquettes showed potential for application as viable biomass fuel. [ABSTRACT FROM AUTHOR]

Introduction: Given the centrality of insight in promoting change, the relevance of measures for assessing this construct has become increasingly clear. This paper describes a new self-report measure for assessing some of the characteristics of insight, the insight orientation scale (IOS).Aims: In study 1, we evaluated the factor structure and the reliability of the scale. In study 2, we analyzed the concurrent and discriminant validity of the scale in patients with different clinical diagnoses.Methods: In study 1 participants were 600 individuals (41.1% male, 58.9% female) with a mean age of 33.95 years (SD = 13.04). In study 2 participants were 136 individuals divided into the following groups: 1) schizophrenia spectrum and other psychotic disorders (n = 26); 2) substance-related disorders (n = 55); 3) depressive disorders (n = 27); and 4) personality disorders (n = 28).Instruments: Instruments are the insight orientation scale (IOS) and the Beck cognitive insight scale.Results: The goodness-of-fit indices showed a satisfactory fit of a one factor model. We found also a good internal consistency (α = .77).Conclusions: These findings support the dimensionality of the IOS and suggest that it may be useful as an assessment tool for use in guiding psychotherapy. [ABSTRACT FROM AUTHOR]

Electro-mechanical brake units (EMBUs) have complex degradation process. There are challenges such as component fault coupling, unclear degradation characteristics, random disturbance and so on. A remaining useful life (RUL) framework for EMBUs is developed in this paper. To eliminate the issue of time lag, a data pre-processing method based on zero-phase filtering is proposed for health indicator (HI) construction. Then, the 3 health stages (HSs) characteristics of degradation process is proposed, and is modeled using the Wiener process. To overcome perturbation of large diffusion coefficient and random fluctuation, the change point (CP) detection methods based on the variance ratio hypothesis test and maximal overlap discrete wavelet transform — multi-resolution analysis (MODWT-MRA) are developed. Besides, a consecutive anomaly window detection strategy using sliding windows is employed. Finally, the MODWT-MRA-based RUL prediction methods is proposed. The proposed methods are verified by the durability test data. The proposed data pre-processing method can avoid 10% time error compared to the common difference method. The proposed MODWT-MRA-based CP detection and RUL prediction method can overcome the interference of large random fluctuations in the non-healthy state of EMBU. • Multi-HS characteristics of the degradation process of EMBU is proposed, providing a basis for accurate RUL prediction and avoid overfitting predictions. • A RUL prediction framework including multi-CP detection of multi-HS with hypothesis test and Maximal Overlap Discrete Wavelet Transform —Multi-Resolution Analysis is introduced. • A data pre-processing for HIs construction based on zero-phase filtering is proposed, which is able to address the issue of signal noise and time delay encountered in traditional filters. [ABSTRACT FROM AUTHOR]

This paper aims to optimize the crashworthiness capability of glass-reinforced epoxy composites (GFRE) over wrapped polyvinyl chloride (PVC) circular tubes with cutouts. The intended tubes were prepared by a wet wrapping method; then subjected to quasi-static axial compression. To compute crashworthiness indications, three design parameters, each at three levels, were used. The design parameters are the hole diameter (d), the hole's number (n), and the hole position (L). A few runs were accompanied by the L9 orthogonal array based on the Taguchi technique. With the lowest initial peak crash force (F ip) and the largest absorbed energy (U), the optimal parameters were found. Furthermore, the main effect, signal-to-noise ratio (S/N), as well as the analysis of variance (ANOVA), have been studied using the commercial software program MINITAB 18. Furthermore, to optimize the process parameters in terms of the crashworthiness indicators, desirability function analysis (DFA) was applied. Lastly, tests for confirmation were performed to verify the predicted values in light of the experimental results and compare them with the intact tubes. Regarding the single optimization, the optimum F ip tube is smaller than the intact PVC tube and intact hybrid tube, at 24.01 and 72.85 %, respectively. Nonetheless, the optimal U was 21.43 % lower than the intact hybrid tube and 152.75 % greater than the intact PVC tube. While, for F ip and U, the multi-objective optimization specimen achieves 5.13 and 70.02 % greater than the intact PVC tube. But it was 62.44 % and 47.14 % less than what the intact hybrid tube had accomplished. [ABSTRACT FROM AUTHOR]

The methane steam reforming to produce hydrogen under concentrated irradiation was proposed and the novel thermodynamic analysis interaction effects on the conversion of methane via Design Expert software was utilized in this paper. The four parameters (material porosity, inlet gas temperature, steam-to-methane ratio, inlet gas velocity) and three levels (low, center and high) were designed via the Box-Behnken Design in Response Surface Methodology. The response model was established to optimize and analyze the condition parameters, which showed effects on the methane conversion under concentrated irradiation. The results showed that the value of material porosity, inlet gas temperature and S/C had a positive effect on the methane conversion rate, while the value of inlet gas velocity had a negative effect on it. The analysis of variance of the methane conversion in the Response Surface Methodology was 0.9914. When the material porosity, gas inlet temperature, S/C and gas inlet velocity were 0.770, 579.925 K, 2.996 and 0.031, respectively, methane conversion was 94.03%; Among the above four factors, material porosity had the most significant effect on the reaction of methane steam reforming to produce hydrogen under concentrated irradiation. These results provided theoretical guidance for application of methane steam reforming under concentrated irradiation. • Methane steam reforming under concentrated irradiation were carried out via response surface methodology. • The influence order was material porosity > steam-to-methane ratio > inlet gas temperature > inlet gas velocity. • The optimal condition of material porosity, inlet gas temperature, S/C and inlet gas velocity was obtained. • The optimal conversion of methane was 94.03%. [ABSTRACT FROM AUTHOR]

In the evaluation of measurements on characteristics of forensic trace evidence, Aitken and Lucy (2004) model the data as a two-level model using assumptions of normality where likelihood ratios are used as a measure for the strength of evidence. A two-level model assumes two sources of variation: the variation within measurements in a group (first level) and the variation between different groups (second level). Estimates of the variation within groups, the variation between groups and the overall mean are required in this approach. This paper discusses three estimators for the overall mean. In forensic science, two of these estimators are known as the weighted and unweighted mean. For an optimal choice between these estimators, the within- and between-group covariance matrices are required. In this paper a generalization to the latter two mean estimators is suggested, which is referred to as the generalized weighted mean. The weights of this estimator can be chosen such that they minimize the variance of the generalized weighted mean. These optimal weights lead to a "toy estimator", because they depend on the unknown within- and between-group covariance matrices. Using these optimal weights with estimates for the within- and between-group covariance matrices leads to the third estimator, the optimal "plug-in" generalized weighted mean estimator. The three estimators and the toy estimator are compared through a simulation study. Under conditions generally encountered in practice, we show that the unweighted mean can be preferred over the weighted mean. Moreover, in these situations the unweighted mean and the optimal generalized weighted mean behave similarly. An artificial choice of parameters is used to provide an example where the optimal generalized weighted mean outperforms both the weighted and unweighted mean. Finally, the three mean estimators are applied to real XTC data to illustrate the impact of the choice of overall mean estimator. [ABSTRACT FROM AUTHOR]

Abstract The importance, benefits, and impact of integration of decisions within supply chains have long been investigated by many researchers. Order acceptance and supplier selection are two of the most critical decisions for supply chain managers. Throughout the process of order acceptance, a manufacturer has to decide which orders to be accepted and processed and based on the accepted orders, the volume of required raw material is determined. On the other hand, a manufacturer aims to choose one or several suppliers among all possible choices to provide sufficient raw material for the accepted orders, subject to different criteria such as list price, transportation cost, etc. This paper addresses an integrated framework for profit maximization in an integrated supplier selection, order acceptance and scheduling problem in a single-machine environment with multiple customers. There is substantial literature on the problems of supplier selection and order acceptance; however, to the best of our knowledge, this paper is the first research that integrates these essential decisions in the form of a mathematical model to maximize the total profit. The problem is NP-hard in nature; therefore, solving to optimality is not practically possible for problems with medium and large size. For that purpose, we developed a Heuristic Algorithm (HA) to solve the problem above in a reasonable time, with proper accuracy. Results from this heuristic algorithm are compared with that of a commercial solver (GAMS) and the well-known Genetic Algorithm (GA) and Variable Neighborhood Search (VNS). Computational experiments demonstrate that the developed heuristic algorithm is more efficient in comparison with other tested methods. Highlights • A model is developed to integrate order acceptance, order scheduling, due date assignment, and supplier selection decisions. • A heuristic algorithm is developed to solve the problem promptly with great accuracy. • Extensive computational experiments and analysis demonstrate the outperformance of the developed heuristic algorithm. [ABSTRACT FROM AUTHOR]