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Teacher motivation is considred as one of the most decisive factorts infulencing teacher functioing as well as students' achievement. Many variable can develop teacher motoivation. In this study, it is presumed that teacher engagement, comprising three facets of emotional, behavioral, and cognitive influence teacher motivation. To examine this hypothesis, this study takes the initiative to utiliuze an innovative artificial intelliengce (AI)-inspired approach called Ant Colony Optimization (ACO) technique. ACO is an artificial intelligence (AI) algorithm originating from natural phenomena. The concept originates from biology and physics and specifically from ants' movements. ACO has the ability to find the connections between inputs and outputs, and it can find the most influencing inputs. Motivation was the output of the study, and the inputs were three different engagement factors. Based on the results, ACO reached a high R-value meaning that it could predict the output with a high accuracy. The findings of this study substantiate the wide-ranging and multifacsted potentials of AI, in particular ACO, in studying and predicting human functioning in academic settings. [ABSTRACT FROM AUTHOR]

The present research scrutinized the nexus between English as a Foreign Language (EFL) learners' metacognitive awareness (MCA), personal best goals (PBs), the positive dimension of self-critical rumination (PSCR) and language achievement (LA) via a quantitative approach. To accomplish this aim, 526 EFL students studying at different private English institutes and a university were asked to take part in a questionnaire survey and fill in three questionnaires. The first questionnaire was L2 Self-Critical Rumination Questionnaire (Ghanizadeh & Jahedizadeh, forthc.). It included 11 items and evaluated positive and negative metacognitions. In this study, positive metacognition was employed. To measure the metacognitive awareness in this study, the scale developed by Schraw and Dennison (1994) was used. It comprised 52 statements measuring two broad classifications of knowledge of cognition (two subcomponents), and regulation of cognition (five subcomponents). To measure student PB goals, the Persian version of 'Personal Best Goals Scale' developed by Martin (2006) and translated to Persian and validated by Najafzadeh et al. (2019) was considered. The 16 statements that made up the personal best scale assessed challenging goals, specific goals, competitively self-referenced goals, and self-improvement goals. The results computed via Structural Equation Modeling (SEM) demonstrated that MCA positively predicted PSCR (β = 0.45, t = 6.05), PB (β = 0.51, t = 6.48), and LA (β = 0.61, t = 7.87). A further finding was that both PB (β = 0.63, t = 8.08) and PSCR (β = 0.31, t = 3.18) positively predicted LA. Taken together, the highest impact on LA was exerted by PB, followed by MCA. The association between the subscales of MCA and PB demonstrated that the highest correlation is between MCA and information management strategies (r = 0.71, p < 0.05) followed by monitoring (r = 0.70, p < 0.05), planning (r = 0.69, p < 0.05), and evaluation (r = 0.67, p < 0.05). The outcomes of this study can be significant for teachers, education policymakers, and material developers. They should understand that enhancing metacognitive awareness helps students be more mindful in their learning and set more ideal goals, resulting in greater academic achievement. [ABSTRACT FROM AUTHOR]

The use of ensemble learning (EL) has grown due to its ability to enhance precision in predictions compared to typical machine learning (ML) algorithms. EL-based approaches are expected to be more accurate and efficient in simulating green engineering materials like sustainable concretes. In this study, three novel EL methods predict the compressive strength (CS) of concrete containing rice husk ash (CCRHA) using hybridizations of adaptive boosting (AdaBoost), gradient boosting regression trees (GBRT), random forests (RF), and teaching-learning-based optimisation algorithms (TLBO). Data for the CS of CCRHA (1212 instances) were collected from 42 published journal papers. Input variables included the amount of water, cement, fine aggregate, coarse aggregate, rice husk ash, superplasticizer, and curing time. Generally, GBRT-TLBO outperformed other approaches in testing with R2, RMSE, and MAE values of 0.976, 3.299, and 2.419 MPa, respectively. GBRT-TLBO models had superior capabilities in the testing phase with interquartile ranges of absolute error boxes equal to 1.0 MPa. A comparison with literature models showed that GBRT-TLBO was correctly tuned. Sensitivity analysis indicated cement and age as the most significant variables, while RHA was the least significant. Surface plots from parametric studies identified the interaction of input variables with concrete CS. HIGHLIGHTS: Using ensemble learning (EL), the compressive strength (CS) of concrete composed of rice husk ash (CCRHA) is modelled. Three novel hybrid ensemble learning methods including AdaBoost, GBRT, RF, and teaching-learning-based optimisation algorithm (TLBO) are employed. The contents of water, cement, fine aggregate, coarse aggregate, rice husk ash, superplasticizer, and curing age were considered as inputs. Sensitivity analysis and parametric studies were performed to evaluate model feature importance and efficiency. For the same number of data records, the proposed models are superior to those developed via the research literature. [ABSTRACT FROM AUTHOR]

Let E be a sublattice of a vector lattice F. A continuous operator T from E into a normed vector space X is said to be õrder-norm continuous if ... implies ... for every (xα)α∈A ⊆ E. This paper aims to investigate the properties of this new class of operators and explore their relationships with existing classifications of operators. We introduce a new class of operators called õrder weakly compact operators. A continuous operator T : E → X is considered õrder weakly compact if T(A) in X is a relatively weakly compact set for every Fo-bounded A ⊆ E. In this manuscript, we examine various properties of this class of operators and explore their connections with õrder-norm continuous operators. [ABSTRACT FROM AUTHOR]

The current study is delved into English as a Foreign Language (EFL) students' academic procrastination, learning approach, burnout, and language achievement. To do so, 203 EFL students studying in three universities in Iran were asked to complete three questionnaires, including Academic Procrastination Scale, Revised Study Process Questionnaire, and Maslach Burnout Inventory Student-Survey. Structural Equation Modeling was employed to verify the causal model. The results revealed that students' procrastination predicted their burnout positively and significantly. Moreover, academic procrastination was found to correlate positively with surface learning approach. The results also indicated that procrastination had a negative impact on deep learning approach. Another finding was that procrastination influenced language achievement indirectly and negatively. Finally, these findings were discussed in the light of prior research. [ABSTRACT FROM AUTHOR]

Background: It seems that children's anxiety is affected by parental factors and the child's personality characteristics. The objective of this study was to develop a model of child anxiety based on maternal overprotection, anxious beliefs, and the mediating role of child inhibition in clients referred to the Urmia Police Force Counseling Center, Urmia, Iran. Methods: In this modeling type of correlational study, among the clients referring to the Urmia Police Force Counseling Center in 2021-2022, 218 mothers with children aged 2 to 8 years were selected using a convenience sampling method. Mothers completed the Roth Manual of Mother-Child Relationship Evaluation (MCRE), Spence et al. Preschool Anxiety Scale (PAS), Francis and Chorpita Parental Beliefs about Anxiety Questionnaire (PBA-Q), and Bishop et al. Behavioral Inhibition Questionnaire (BIQ). The obtained data were analyzed in SPSS [mean, standard deviation (SD), and correlation] and Amos software using the path analysis method. Results: A significant positive relationship was found between maternal overprotection (r = 0.49, P < 0.001), anxious beliefs (r = 0.54, P < 0.001), child inhibition (r = 0.48, P < 0.001), and child anxiety. Moreover, overprotection had an indirect and positive effect (p = 0.41, P < 0.02) on the child's anxiety given the mediating role of the child's inhibition (p = 0.073, P < 0.01). Anxious beliefs directly (p = 0.41, P < 0.01), indirectly, and positively affected a child's anxiety given the mediating role of the child's inhibition (p = 0.098, P < 0.001). It should be noted that the root mean square error of approximation (RMSEA) index was 0.09 and the comparative fit index (CFI) was 0.987, which were acceptable. Conclusion: Based on the results, the mother's cognitive and behavioral characteristics can affect anxiety through the child's behavioral inhibition characteristic. In addition to parents' cognitive and behavioral characteristics, the child's temperament and parents' response based on the children's temperament should be also considered in the diagnosis and treatment of children's anxiety disorders. [ABSTRACT FROM AUTHOR]

Identifying characteristics of invasive species or growth forms that facilitate their range expansion is critical for management. Clematis vitalba L. (old man's beard) is an invasive temperate liana in many areas of its introduction, yet its seedlings do not thrive in circumstances where resources are limited. Although some lianas in both tropical and temperate climates have been shown to spread by clonal stems along the ground, the bulk of previous research on C. vitalba reproduction has focused largely on aspects of seed ecology. The vegetative growth of the species is poorly understood. The first objective of our study was to evaluate the use of vegetative spread by C. vitalba as a means of local dispersal and population growth. We excavated ten 1‐m2 plots in infested riparian zones and found an extensive, branching network of creeping stems, both above and below ground. Our second objective was to test the ability of C. vitalba stem fragments to act as vegetative propagules. After 4 months, ~50% of two‐node fragments had regenerated, from both creeping and climbing stems. These studies help explain how a temperate liana forms populations and dominate ecological communities. The findings provide good evidence that C. vitalba may rely quite heavily on asexual reproduction. In addition, the results document liana stem phenotypic plasticity; fragmented climbing stems are just as likely as fragmented creeping stems to reprogram shoot tissue systems, generate roots and regrow as independent plants. [ABSTRACT FROM AUTHOR]

An innovative approach for creating customized dosage forms and supporting patient populations with specific requirements who need additional support to improve drug adherence is 3D printing. This work introduces liquid crystal display (LCD) 3D printing as a means of developing melatonin (MLT) tablets. For patients who are blind or visually challenged, Braille patterns were displayed on the tablet surface in addition to the optimization of printing hydrogel inks. Owing to the great printing accuracy, blind patients could validate the Braille patterns that provided the required information. Upon further examination MLT was found to be present in the photopolymerized resins in an amorphous state. The choice of poly(ethylene glycol)-diacrylate (PEGDA) with varying molecular weights and the inclusion of surfactants or solubilizers interfered with the photopolymerization of the resin, hence controlling the rates of MLT dissolution towards the sought sustained release. Nuclear magnetic resonance (NMR) analysis showed that photopolymerization of the PEGDA resins in the printed dosage forms has taken place. A small batch scale-up investigation showed that LCDs could print a significant number of tablets quickly—about twenty-four minutes. [ABSTRACT FROM AUTHOR]

BACKGROUND: Resistance to dicamba in Chenopodium album was first documented over a decade ago, however, the molecular basis of dicamba resistance in this species has not been elucidated. In this research, the resistance mechanism in a dicamba‐resistant C. album phenotype was investigated using a transcriptomics (RNA‐sequence) approach. RESULTS: The dose–response assay showed that the resistant (R) phenotype was nearly 25‐fold more resistant to dicamba than a susceptible (S) phenotype of C. album. Also, dicamba treatment significantly induced transcription of the known auxin‐responsive genes, Gretchen Hagen 3 (GH3), small auxin‐up RNAs (SAURs), and 1‐aminocyclopropane‐1‐carboxylate synthase (ACS) genes in the susceptible phenotype. Comparing the transcripts of auxin TIR/AFB receptors and auxin/indole‐3‐acetic acid (AUX/IAA) proteins identified from C. album transcriptomic analysis revealed that the R phenotype contained a novel mutation at the first codon of the GWPPV degron motif of IAA16, resulting in an amino acid substitution of glycine (G) with aspartic acid (D). Sequencing the IAA16 gene in other R and S individuals further confirmed that all the R individuals contained the mutation. CONCLUSION: In this research, we describe the dicamba resistance mechanism in the only case of dicamba‐resistant C. album reported to date. Prior work has shown that the dicamba resistance allele confers significant growth defects to the R phenotype investigated here, suggesting that dicamba‐resistant C. album carrying this novel mutation in the IAA16 gene may not persist at high frequencies upon removal of dicamba application. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Soil pollution by heavy metals is a serious environmental concern globally. Hexavalent (VI) chromium (Cr) is one of the main pollutants causing groundwater and soil heavy metal pollution. Miscanthus sinensis is a C4 perennial grass species with a high level of heavy metal tolerance. This species can effectively remove Cr from soils and maintain desirable biomass production under Cr stress. This research aimed to characterize and compare Cr accumulation in 58 genotypes of M. sinensis and to develop Expressed Sequence Tag–Simple Sequence Repeat (EST-SSR) markers associated with Cr tolerance. The results show that the pattern of translocation of Cr in plants differed among the 58 M. sinensis genotypes following treatment of 200 mg/L of Cr6+; however, in most genotypes, the Cr was primarily accumulated in roots. A total of 43,367 EST-SSRs were identified, and 88 EST-SSR primer pairs corresponding to candidate genes involved in Cr accumulation in M. sinensis were selected for validation. Subsequently, 170 polymorphic loci generated from 24 validated EST-SSRs were used for the population structure and marker–trait association analysis. Based on a general linear model (GLM), a total of 46 associations were identified (p < 0.05), with 14 EST-SSRs markers associated with target traits. Among them, four genes related to ABC transporters, wall-associated receptor kinases, as well as two high-affinity sulfate transporters (ST), were identified under Cr stress (p < 0.05). The results of this study help to accelerate the screening across M. sinensis genotypes for desirable traits under Cr stress and provide a platform for M. sinensis genetic improvement and molecular-marker-assisted breeding. [ABSTRACT FROM AUTHOR]

Introduction: With the approach of attention to the environment, the use of natural materials can be effective in reducing the harmful effects of chemical fertilizers and artificial growth regulators. Drought stress is one of the main limitations of food production around the world, and due to increasing population and water deficiency, there is a global attention for using some materials to increase resistant of plant to drought stress. Chemical stimulants are currently used for decreasing negative effects of water stress in plant. Now a days, use of natural materials, such as plant extract is recommended by researchers. Garlic extract is one of the natural extracts that contains many enzymes and more than 200 biochemical compounds that, due to its richness in minerals and plant hormones, causes cell enlargement, cell division and, plant growth. Humic acid is created from the decomposition of organic matter and is beneficial to plant growth and development. Therefore, the aims of this research were to study the effects of using natural substances of humic acid and garlic extract on nutrients uptake (NPK) and growth of wheat plant under drought stress. Materials and methods: This study was performed during 2018 in a completely randomized design with factorial arrangement in three replications under greenhouse conditions. The studied soil with texture class of loam had pH = 8.11 and EC = 1.28 dS m-1. Experimental factors include drought stress at three levels of 95%, 65% and 45% of field capacity, garlic extract at three levels of foliar application of 0, 2% and 4% and humic acid at two levels of foliar application of 0 and 300 mg l-1. Drought stress were treated by the weight method, 17 days after sowing. Foliar application of humic acid (twice, 13 and 20 days after threating the drought stress) and garlic extract (three times, 18, 24 and 27 days after threating the drought stress) were performed by spraying 150 ml pot-1 of the solutions in each time. The plants were harvested 54 days after sowing and the parameters of shoot dry weight and uptake of nitrogen, phosphorus and potassium in plant were measured. Statistical analysis was done using SAS 9.4 software and the comparison of means was done using Tukey's test at the 5% probability level. [ABSTRACT FROM AUTHOR]

During iron ore process, a substantial amount of iron ore tailings (IOT) are generated, which can be caused environmental challenges. To mitigate this issue, the stabilised IOT can be repurposed as road material. The unconfined compressive strength (UCS) parameter is typically used to assess the quality control and mix designing of stabilised materials, which its measurement is time-consuming due to the required curing time (CT). Consequently, implementing machine learning techniques to determine and predict UCS values can significantly streamline the process and reduce mix design as well as quality control costs. This research aims to evaluate various machine learning models to predict the UCS of cement-stabilised IOT. Four input variables including cement percentage, CT, compaction moisture content (MC) and compaction energy were considered for UCS modelling. A comparison of the statistical results from the developed models revealed that the artificial neural network (ANN) method exhibited superior accuracy for both training and testing data, with R2 values of 0.96 and 0.97, respectively. Moreover, a sensitivity analysis of the ANN model demonstrated that cement percentage had the most significant impact on the UCS, while compaction MC had the least. Lastly, a parametric study was conducted to evaluate the influence of various variables on the UCS. [ABSTRACT FROM AUTHOR]

Sepiolite is a fibrous clay mineral, which is mostly associated with a semi-arid to arid climate, with characteristics intermediate between kaolinite and montmorillonite minerals. An experimental study was conducted, with the goal of creating a substantial database of physical, microstructural, and geotechnical characteristics of sepiolite to develop its applications as a natural resource that is explored as the main deposit of Iran. It has been found that sepiolite soils were lightweight, porous, and cohesive with negligible settlement and swelling properties and almost high UCS values. Various analysis were performed to characterise the macroscopic behaviour (Atterberg limit, physical, and compressibility tests), microstructural, chemical, and mineralogical characterisations by chemical analysis, X-Ray diffraction, and Scanning Electron Microscopy. At first glance, sepiolite soils showed high liquid limits with medium to high plastic indices which can result in problems including creation of up and down movements in foundations. After mixing with silt and fine sand to decrease high liquid limit and optimum moisture amounts, sepiolite is suitable candidate for engineering applications (including clay liners, clay cores, etc.) due to its compressibility and strength characteristics. In conclusion, sepiolite soils are strongly recommended for geo-environmental structures due to their adsorption capacity, low permeability coefficient, and suitable strengths. [ABSTRACT FROM AUTHOR]

There are four critical factors that affect air voids (VA) of asphalt concrete over time: traffic loads and repetitions, environmental regimes, compaction, and asphalt mix composition. Because of the high as-construct VA content of the material, it is expected that voids will reduce over time, causing rutting during initial traffic periods. Eventually, the material will undergo shear flow when it reaches its most dense state with optimum aggregate interlock or refusal VA content. Furthermore, to accurately model the performance of an asphalt mixture, the VA must be predicted over time. This study aims to implement two ensemble learning methods namely Cubist and gradient boosting regression tree (GBRT) hybridized with equilibrium optimizer algorithm (EOA) to predict the VA percentage of asphalt concrete during the service life of flexible pavements. For this purpose, 324 data records of VA were collected from the literature. The variables selected as inputs were original as-constructed air voids, VAorig (%); mean annual air temperature, MAAT (°F); original viscosity at 77°F (25°C) , ηorig,77 (Mega-Poises); and time (months). GBRT-EOA and Cubist-EOA were found to be superior to other classical single ML approaches [for instance, artificial neural network (ANN), support vector machine (SVM), and Gaussian process regression (GPR) and M5Tree] and existing nonlinear regression models. In the training phase, the GBRT-EOA had R2 , root mean square error (RMSE), mean absolute error (MAE), and mean of absolute percent error (MAPE) values of 99.8%, 0.136%, 0.093%, and 1.324%, respectively, while these values changed to 95.1%, 0.701%, 0.53%, and 7.825% in the testing phase. Also, only less than 5% of the records were predicted using this model with more than 20% deviation from the observed values. As determined by the sensitivity analysis, time (months) is the most significant of the four input variables, while MAAT (°F) is the least one. A parametric study showed that regardless of the MAAT, the ηorig,77 of 1.0 Mega-Poises, and the VAorig above 6% can be ideal for improving the pavement service life in terms of the VA of the asphalt concrete layer during service life. [ABSTRACT FROM AUTHOR]

Amidst COVID-19, most of the students of higher education faced with different adversities and challenges when learning via Virtual Education (VE). Resilience in virtual education (RVE) seems of high importance in this regard, and its association with other psychological constructs can be of value for educationalists. Therefore, this research is aimed at elucidating on the role of English as a foreign language (EFL) university students' RVE in personal best (PB) goals and second language (L2) anxiety. Moreover, it examined whether these constructs act as factors contributing to language achievement. To do so, a total number of 611 university students from three universities in Mashhad, an Iranian city, in December 2022 and August 2023 were requested to answer three questionnaires. To measure participants' RVE, resilience in virtual education scale (RVES) designed and validated by Ghanizadeh and Majidi (forthc.) was utilized. Learners' PB goals were assessed via the Scale developed by Martin (2006). To evaluate L2 anxiety, six items out of the Dörnyei's L2 Motivational Self System (2005) were employed. The results yeided via structural equation modeling (SEM) indicated that RVE can predict all three constructs, though negatively with reference to L2 anxiety and positively for PB and language achievement. Language achievement was influenced positively by PB goals and negatively by L2 anxiety. It was also demonstrated that RVE can predict language achievement indirectly via its impact on L2 anxiety and PB in addition to the direct effect. Therefore, it was affirmed that EFL university students' RVE plays key role in predicting learners' psychological factors and their academic success. [ABSTRACT FROM AUTHOR]

Background: COVID-19 had a destructive effect on human's life. People with COVID-19 experienced high levels of depression, anxiety, and low Quality of Life (QOL). The aim of this study was to investigate the effect of the cognitive-behavioral intervention package on reducing stress, depression, and anxiety, as well as improving the QOL of patients with COVID-19. Methods: In this randomized controlled trial, 60 patients with COVID-19 who entered the isolation ward were included and randomly divided into control and experimental groups. The experimental group entered the intervention sessions once a week for 45 minutes for eight consecutive weeks. The intervention consisted of 8 sessions of CBT which was implemented for the experimental group. Patients in the control group received routine care during this period. DASS21, the Symptom Checklist (SCL-90), Fear of COVID-19 Scale (FCV-19S), and WHO-QOL were used to measure patients' mental health and QOL. Data analysis was performed with ANCOVA using SPSS24 software. Results: There was no significant difference between groups in terms of DASS21, SCL-90 and QOL before intervention (p<0.05). After intervention, depression symptom and QOL were significantly improved in the experimental group compared to control group (p< 0.05). Accordingly, the findings stated the session of intervention was effective in improving the QOL (p<0.05) and mental illnesses (p<0.05) in patients with COVID-19. Conclusion: Our designed cognitive-behavioral intervention package can enhance the awareness and mental health of patients with COVID-19. This package as an auxiliary treatment can reduce anxiety/depression and improve QOL in patients with COVID-19. Therefore, our intervention package can serve as a useful solution for clinical settings to reduce mental health problems during crisis. [ABSTRACT FROM AUTHOR]

Old man's beard (Clematis vitalba L.) is a liana species that has become invasive in many areas of its introduced range. Seeds are produced in abundance and are both physiologically and morphologically dormant upon maturity. To understand the importance of seeds to its invasiveness, changes in viability and dormancy of the aerial seed bank were tracked throughout the after‐ripening period and during storage.Seeds collected every second month for 2 years were subjected to germination tests. Other seeds stored in outdoor ambient conditions or in a dry, chilled state were dissected before, during, and after imbibition, as well as during incubation, to measure embryo size.Less than 72% of seeds on the mother plant were viable. Viable seeds remained completely morpho‐physiologically dormant throughout autumn, even when treated with nitrate. Physiological dormancy declined in response to seasonal changes, yet morphological dormancy did not change until seeds had been exposed to appropriate germination conditions for several days. Fully dormant autumn seeds decayed at higher rates during incubation than partially or fully after‐ripened seeds, which were also more germinable and less dormant. Furthermore, seeds incubated in complete darkness were more likely to decay or remain dormant than those exposed to light.This study demonstrates that fewer than three‐quarters of seeds produced are viable and further decay occurs after dispersal, yet total fertility is still very high, with enormous propagule pressure from seeds alone. Viable seeds are protected with two forms of dormancy; morphological dormancy requires additional germination cues in order to break after seasonal changes break physiological dormancy. [ABSTRACT FROM AUTHOR]

Background: Microarray technology enables the examination of gene expression in thousands of genes and can be highly effective in identifying various types of cancers, including leukemia. However, many genes in microarray data are redundant and lack useful information for cancer diagnosis. The main objective of this study is to identify relevant and effective genes in classification of leukemia microarray data using a spline regressionbased method, taking into account the correlation between genes. Materials and Methods: In this analytical study, leukemia microarray data are used to identify relevant genes in classification of leukemia into Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) using a spline regression-based gene selection method, called SRS3FS based on l2, p-norm (0 < p = 1). Subsequently, the support vector machine (SVM) algorithm is employed to classify leukemia data into AML and ALL. Results: In this study, the classification results of SVM algorithm for 5, 10, 15, and 20 genes reveal that the SRS3FS method, employing l2,1/4-norm, l2,1/2-norm and l2,3/4-norm, exhibited the highest accuracy of 97.06% when identifying 10 genes for distinguishing between AML and ALL. Moreover, the leukemia data was classified into AML and ALL with an accuracy of 100%, using a gene identified by the SRS3FS method based on l2,3/4-norm and l2,1-norm. The gene labeled as number 3252, annotated as GLUTATHIONE STRANSFERASE, MICROSOMAL, is recognized as the most important gene. Conclusion: The experimental results on leukemia microarray data demonstrate that the spline regression-based gene selection method can effectively identify relevant genes in classification and prediction of leukemia. [ABSTRACT FROM AUTHOR]

Removing organic pollutants from wastewater is crucial to prevent environmental contamination and protect human health. Immobilized enzymes are increasingly being explored for wastewater treatment due to their specific catalytic activities, reusability, and stability under various environmental conditions. Peroxidases, such as horseradish peroxidase (HRP) and myoglobin (Mb), are promising candidates for immobilized enzymes utilized in wastewater treatment due to their ability to facilitate the oxidation process of a wide range of organic molecules. However, the properties of the carrier and support materials greatly influence the stability and activity of immobilized HRP and Mb. In this research, we developed immobilized HRP and Mb using support material composed of sodium alginate and CaCl2 as carriers and glutaraldehyde as a crosslinking agent. Following this, the efficacy of immobilized HRP and Mb in removing aniline, phenol, and p-nitrophenol was assessed. Both immobilized enzymes removed all three organic pollutants from an aqueous solution, but Mb was more effective than HRP. After being immobilized, both enzymes became more resilient to changes in temperature and pH. Both immobilized enzymes retained their ability to eliminate organic pollutants through eight treatment cycles. Our study uncovered novel immobilized enzyme microspheres and demonstrated their successful application in wastewater treatment, paving the way for future research. [ABSTRACT FROM AUTHOR]

Johne's disease, caused by Mycobacterium avium subspecies paratuberculosis (MAP), is a chronic inflammatory bowel disease affecting ruminants worldwide. Early detection of MAP-infected animals is crucial for disease control. This study aimed to investigate the presence of MAP in saliva and urine samples of cows with subclinical Johne's disease, as a non-invasive and easily accessible diagnostic approach. Saliva samples were collected from 40 seropositive cows with subclinical Johne's disease, confirmed through fecal PCR. An additional 40 seronegative cows were included as controls. PCR testing was conducted on the selected samples to check for MAP contamination. Out of the 40 seropositive cows with subclinical Johne's disease, 30 (75%) tested positive for MAP in saliva samples. In the control group, only four cows (10%) tested positive for MAP in saliva. The difference in MAP detection between the diseased and control groups was statistically significant (p≤0.05). Until now, it has been widely believed among researchers that MAP, primarily transmits through the fecaloral route. However, the findings of the current study indicate the potential for contamination through saliva, which is an important factor to consider. The high prevalence of MAP in these samples suggests that they may also serve as valuable alternatives to fecal samples for early disease detection. [ABSTRACT FROM AUTHOR]

Objectives: The current study devised a mindfulness intervention program, integrating face-to-face and group training with individualized technology-accessible practices. It aimed at investigating the role of Blended Mindfulness Intervention (BMI), which combines mainstream mindfulness practices with digital tools, in university students' sustained attention, working memory, academic achievement, and electroencephalogram (EEG) asymmetry. Method: Sixty junior university students, selected from a pool of 72 candidates, were randomly assigned into two groups. Mindfulness training (MT) was incorporated into class activities of experimental group in a course of eight sessions. The participants of experimental group were also assigned to do some weekly follow-up activities offered via a smartphone-based mindfulness meditation application (Smiling Mind). The homogeneity of the two groups was ascertained prior the study on mindfulness, working memory (determined via Automated Operation Span [AOSPAN] task), and sustained attention. The tripartite mindfulness instruction encompassed these activities: (1) in-class general MT practices, (2) in-class educational-inspired practices, and (3) at-home practices via Smiling Mind. Results: The results of statistical analysis via independent samples t-tests verified the efficiency of BMI in enhancing university students' sustained attention, working memory, and academic achievement. The analysis of EEG measurements via a 19-channel device demonstrated reduction in the theta/beta ratio (TBR) values in all brain regions, including frontal, parietal, occipital, and central in posttest. The ratio is a measure often used in EEG studies to assess brain activity. Conclusions: This study substantiated that promoting state mindfulness in MT programs develops trait mindfulness, which brings about a host of cognitive, emotional, social, and metacognitive benefits. It also demonstrated that supplementing face-to-face and group interventions with individualized and easily accessible and affordable ones seem to cater for all styles and preferences and ultimately augment the efficiency of these programs. Preregistration: This study is not preregistered. [ABSTRACT FROM AUTHOR]

Utilizing the aggregate piers is one of the methods to improve and increase the bearing capacity of soft soils. The ultimate bearing capacity of these piers is affected by parameters such as the physical properties of the piers, structural conditions, the embedment depth and replacement ratio of piers, which complicates the estimation of bearing capacity. In this study, the Gene Expression Programming method was used for the prediction of the ultimate bearing capacity of clay soils reinforced with aggregate piers. For this purpose, two different models were developed, of which the first model (GEP2) utilized two input variables, the undrained shear strength of clay (Su) and replacement ratio (ar), while the second model (GEP4) used four input variables including the undrained shear strength of clay (Su), replacement ratio (ar), slenderness ratio (Sr), and embedment depth of piers (df). The coefficient of determination of the GEP2 model, and the GEP4 model is 0.921 and 0.942, respectively. Besides, comparing the GEP4 model of this research with the developed models of previous studies confirms the superior performance of the GEP4 model, considering both the accuracy and number of input parameters. The results of sensitivity analysis showed that the undrained shear strength of clay (Su), replacement ratio (ar), slenderness ratio (Sr), and embedment depth of piers (df) have the highest impact on the prediction of bearing capacity, respectively. Furthermore, the parametric analysis demonstrated that increasing the Su, ar, Sr, and df would improve the bearing capacity of the aggregate piers reinforced clay. [ABSTRACT FROM AUTHOR]

Multiple Kernel Learning (MKL) is a conventional way to learn the kernel function in kernel-based methods. MKL algorithms enhance the performance of kernel methods. However, these methods have a lower complexity compared to deep models and are inferior to them regarding recognition accuracy. Deep learning models can learn complex functions by applying nonlinear transformations to data through several layers. In this paper, we show that a typical MKL algorithm can be interpreted as a one-layer neural network with linear activation functions. By this interpretation, we propose a Neural Generalization of Multiple Kernel Learning (NGMKL), which extends the conventional MKL framework to a multi-layer neural network with nonlinear activation functions. Our experiments show that the proposed method, which has a higher complexity than traditional MKL methods, leads to higher recognition accuracy on several benchmarks. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of subgrade soil stabilization on the performance and life extension of flexible pavements. Several variables affecting soil stabilization were considered, including subgrade soil type (CL or CH), additive type and content (3, 6, and 9% of hydrated lime, 5, 10, and 15% of class C fly ash (CFA), and 5, 10, and 15% of cement kiln dust (CKD)), three stabilization thicknesses (15, 30, and 45 cm), and four pavement sections with varying thicknesses. The effects of these variables were investigated using four different damage mechanisms, including the fatigue life of the asphalt concrete (AC) and stabilized subgrade layers, the crushing life of the stabilized subgrade soil, and the rutting life of the pavement, using a non-linear mechanistic-empirical methodology. The results suggest that the optimum percentage that maximizes the pavement life occurs at 3% of lime for subgrade soil type CL, 6% of lime for subgrade type CH, and 15% of CFA and CKD for both subgrade soil types. The maximum pavement life increase occurred in the section with the lowest thickness and the highest stabilization thickness, which was 1890% for 3% of lime in the CL subgrade and 568% for 6% of lime in the CH subgrade. The maximum increase in the pavement life of subgrade stabilization with 15% of CFA was 2048% in a CL subgrade, and 397% in a CH subgrade, and life extension due to subgrade stabilization with 15% of CKD was 2323% in a CL subgrade and 797% in a CH subgrade. [ABSTRACT FROM AUTHOR]

For decades, herbicides have provided easy-to-use, cost-effective weed management, but alternatives are desired. Consumer preference for chemical-free food, awareness of environmental impacts, regulation increasingly restricting agrichemical use, and increasing prevalence of herbicide resistance are forcing changes to weed management strategies. New Zealand farming must remain sustainable and profitable while responding to changes in its overseas markets, among which are increasing demands for regeneratively grown, safe, high-quality produce. Current reliance on herbicides should be reduced, with more emphasis on preventative management by cultural means, and weed suppression by alternative technologies. The emergence of agritechnologies incorporating automation, machine vision and artificial intelligence, and development of new techniques for weed destruction, offer alternatives that minimise or avoid the requirement for herbicides, avoid soil disturbance and can work effectively in high crop or crop-residue conditions. We have identified electric weeding as a feasible alternative and pulsed electric microshocks as a very low-energy option requiring a fraction of the energy of any other system. Pulsed microshocks enable an integrated weed management system for vegetable and arable crop production combining cultural controls and inexpensive pre-planting treatments with automated application of chemical-free in-crop weed control. Open-source software enables community development of autonomous deployment for niche crops. [ABSTRACT FROM AUTHOR]

Rapid identification of herbicide-resistant weeds plays a crucial role in their management. Glyphosate resistance in Lolium perenne is a growing issue in New Zealand and can be conferred by a single nucleotide polymorphism (SNP) causing amino acid substitutions at codon 106 in the 5-enolpyruvoylshikimate-3-phosphate synthase (EPSPS) gene. High-throughput molecular (HTM) methodologies that can detect such SNPs include high-resolution melting and real-time quantitative PCR probe assays. Here, we compare the effectiveness of both assays with a more labour-intense derived cleaved amplified polymorphic sequence (dCAPS) test for detecting SNPs at codon 106. The results showed that both HTM assays detected mutations at this codon, and their results were consistent with those of the dCAPS. Unlike dCAPS, however, the HTM assays over-estimated homozygosity for the glyphosate resistance allele. Nevertheless, cost-effective high-throughput detection of resistance is more important than the zygosity status when initiating an on-farm management response. In summary, both HTM assays successfully identified glyphosate resistance alleles at codon 106 in the EPSPS gene. Given that both assays are more cost-effective and can screen a larger number of samples in a timely manner compared to the dCAPS method, they can be used as quick tests for detecting glyphosate resistance in L. perenne. [ABSTRACT FROM AUTHOR]

A government research grant and industry co-funding allowed us to briefly provide free tests of suspected cases of herbicide resistance using traditional seedling-based assays. Information about the service was disseminated through the Foundation for Arable Research and other weed management professionals. Between 2019 and 2022 we received 248 seed samples collected by rural professionals from individual plants suspected of resistance. We successfully tested 195 samples from eight species from 57 farms. Rural professionals were good at recognising cases of resistance; 77% of these seed samples from 40 farms (70%) had resistance confirmed. We gained insights into contextually unique cases of resistance previously undescribed in the literature in New Zealand, including ryegrass resistance to glyphosate in a barley crop, Poa annua resistance to iodosulfuron in wheat, and Phalaris minor resistance to iodosulfuron in wheat. Resistance was typically confirmed 6–8 weeks after planting seed samples, though for species with seed after-ripening requirements to ensure consistent germination, results took as long as 6 months. The results facilitated conversations about long-term resistance avoidance strategies. Future costs of an independent resistance testing service would ideally be shared by the stakeholders benefitting from the crop protection product value chain, from herbicide producers to land managers. [ABSTRACT FROM AUTHOR]

Although New Zealand is developing an increasing number of herbicide-resistant weed populations, it has a much lower incidence of herbicide resistance than Australia. Understanding the reasons for these differences may help with future management of herbicide resistance in both countries. Australia is much larger than New Zealand so greater areas of weeds are exposed to herbicides annually in Australia. Another difference is the high frequency of Lolium rigidum in Australian agricultural systems, a species almost absent in New Zealand, and many of the cases of resistance in Australia involve this species. However, species closely related to L. rigidum are increasingly being found resistant to herbicides in New Zealand. Higher rainfall in most parts of New Zealand allows much more crop rotation than is possible in Australia, and greater crop yields give New Zealand farmers more flexibility to use higher application rates and more expensive herbicides in rotation than is feasible in Australia. Dry conditions result in more use of summer fallows in Australia using glyphosate which has caused some of the problems. Selection pressure for resistance still occurs in New Zealand, so herbicide and crop rotation may just be delaying the appearance of resistance in this country. [ABSTRACT FROM AUTHOR]

Resistance to iodosulfuron, a herbicide targeting acetolactate synthase (ALS), was identified and characterised in a population of Lolium perenne L. from Canterbury, New Zealand. The resistant population was 264 times more resistant to iodosulfuron than a susceptible population, based on a ratio of the rate corresponding to a 50% reduction in resistant and susceptible plant survival (R/S LD50). The resistant population was also 14-times more resistant to nicosulfuron, another ALS-inhibitor of the same class. However, no resistance to imazapyr, an ALS-inhibitor from a different chemical class, was detected in the resistant population. Pre-treatment with an inhibitor of cytochrome P450 reduced the level of iodosulfuron resistance to 46-fold in the resistant population, suggesting enhanced herbicide metabolism, a non-target site mechanism, contributed to resistance of this herbicide. In addition, a proline to leucine substitution at codon 197 was detected, suggesting a target-site-based mechanism was also associated with resistance to iodosulfuron. This is the first report on the resistance mechanisms to ALS-inhibiting herbicides identified in Lolium perenne in New Zealand and highlights the importance of integrated weed management approaches to reduce the likelihood of ALS-inhibitor herbicide resistance becoming more widespread. [ABSTRACT FROM AUTHOR]

Purpose: Storytelling is a method for training essential life issues as storytelling can assist learners to consider the story not just as a source of entertainment but as a practical lesson. In fact, teachers can encourage even the most unwilling students by engaging the students in storytelling while maintaining students' attention through narration using sounds and gestures. The present study aims to examine the effect of the university instructor's narrative on English as a Foreign Language (EFL) student's sustained attention, emotional involvement and cognitive learning. Design/methodology/approach: To do so, the study adopted a quasi-experimental research design with the aim of focusing on the students' performance within two different virtual classes. University students' sustained attention, emotional involvement and cognitive learning were assessed in control and experimental groups before and after the treatment. To measure students' sustained attention, Wei et al.'s (2012) scale, which comprises six items, was used. Besides, emotional involvement was assessed through Golestani's (2017) engagement questionnaire. To check students' cognitive learning, the scale designed by Richmond et al. (1987) was utilized. The summaries and conclusions in the experimental class were ingrained in instructors' pedagogical repertoires, as the repertoires offer students an alternative way to understand course material beyond a straight lecture. Students in the experimental group were also asked to ponder over the materials presented to the students each session, and the students were supposed to present a one to two-paragraph note on the possible implications of the materials instructed at each session. Findings: The results of independent samples t-test indicated that there was a statistically significant difference between the two groups regarding the degree of their sustained attention, emotional involvement and cognitive learning. The findings of the present study can raise instructors' awareness toward the application of narratives in their instructional methodologies, as well as putting forth significant strategies to enhance students' sustained attention, emotional involvement and cognitive learning through narratives. Originality/value: The theoretical framework of the study derives from Kromka and Goodboys (2018) conceptualization of instructor narrative (IN), defined as the explicit presentation of the lessons conclusion at the end of each session. Previous studies on narrative have primarily focused on learners' narrative as an educational tool. Later studies on teacher narratives conceive this as the teachers' personal anecdotes and story-like accounts of others' experiences; nonetheless, the position which is taken in this study is more academically laden and is based on the information instructed in each session. [ABSTRACT FROM AUTHOR]

Pastures represent about half of the global agricultural area and productivity losses from weeds are significant. The complex interactions between them and other pasture plants, livestock and the environment imply a need for innovative research that transforms pasture management. To this end, a horizon scan was conducted to identify relevant issues, questions, opportunities, and drivers. The drivers were ranked using three criteria: (1) is this a horizon (is the driver likely to become important in 10–20 years?); (2) will the research require stretchy science (is it currently not well addressed by the science community?); (3) is the research transformative (will successful scientific research in this area lead to significant changes to weed management in pastures?). We identified 11 major issues and 46 subordinate ones. The three highest ranked major issues were: (1) anticipated reductions in access to herbicides; (2) rethinking weed management under an ecosystem services paradigm; (3) responding to shifts in best practice and the regulations that are altering farm system planning to reduce farming's environmental impacts. We conclude that fundamental interdisciplinary research is needed that addresses biosecurity and weed management issues, while reducing the environmental footprint of farming and maintaining productivity. [ABSTRACT FROM AUTHOR]

This study presents a new single-phase transformer-less grid-connected inverter based on a six-phase interleaved dc/dc converter as a suitable topology for PV applications. The proposed topology consists of a dc input and multi-output in the dc-link side which results in production of six levels per half cycle. The voltage of the inverter at output side is 7-level that is injected into the network. The voltage of PV panels is low and this problem is solved by increasing the voltage level in the interleaved converter. Besides, the input current ripple of the interleaved dc/dc converter is very low which causes to improve the quality of the injected current into the grid through a PV panel. For control of the power switches and active/reactive power flows, the model predictive control (MPC) method is applied. The proposed system is capable of creating different voltage levels in step-up/down at the dc-link side and this will make it suitable for working in a wide range of power in the grid-tied. Besides, the total voltage blocking (TVB) of the power switches at the inverter side is greatly decreased. Consequently, the efficiency of the proposed system is high. To prove the accuracy of theoretical calculations, the proposed topology for a 900 W prototype at an operation of 50 Hz is built and tested in the laboratory. [ABSTRACT FROM AUTHOR]

Botrytis cinerea is a common pathogenic agent, causing a significant reduction in tomato quality and yield. In this study, the potential of two biocontrol fungal agents, Trichoderma harzianum and Clonostachys rosea to prevent and alleviate B. cinerea infection was assessed. To this end, the fungicidal effects of both biocontrol fungi were evaluated on ten common phytopathogens, including B. cinerea. Then, various ratios of T. harzianum and C. rosea mixtures were assessed to find the ratio that best promotes the growth of tomato seedlings and prevents the establishment of B. cinerea. The results showed that T. harzianum and C. rosea had significant fungicidal effects on all tested phytopathogens. Also, both biocontrol agents reduced the establishment of B. cinerea, in vitro assays, indicating they had significant fungicidal effects against this phytopathogen. However, when applied as a biofungicide to tomato plants, a combination of both biocontrol agents gave better control of B. cinerea. Investigating the molecular basis of resistance to B. cinerea induced by the mixture of T. harzianum and C. rosea revealed that the salicylic acid signaling pathway plays an important role in modulating the antioxidant enzyme activity. Taken together, the results of this research confirmed that both biocontrol fungal agents could induce the mechanism of B. cinerea resistance in tomato plants and shed light on the regulatory pathways associated with the resistance mechanism. [ABSTRACT FROM AUTHOR]

Alkali‐silica reaction continues to be a challenging durability issue for portland cement‐based concrete. While myriad of preventive options is known to reduce the risk of ASR, changes in availability and consistency of materials make either prescriptive or performance‐based approaches difficult to develop and then quickly adapt. In general, the research community has supported industry with practical solutions based on empirically derived relationships, mostly from accelerated test methods and to a lesser extent realistic exposure/field structures. It is time to increase the level of science behind our approach. The research team represented in this talk is investigating a new methodology that combines the alkali availability needed to initiate ASR (aggregate specific) with the available alkali from the total cementitious blend. The relationship between reactivity of a supplementary cementitious material and the ASR expansion is also explored. This keynote lecture will: 1) Explore performance‐based testing versus prescriptive approaches and why a hybrid approach should be considered ASR prevention; 2) Evaluate the relationship between accelerated laboratory tests, outdoor exposure blocks and field structures; 3) Examine the use of "non‐traditional" supplementary cementitious materials and/or chemical admixtures to prevent alkali‐silica reaction; 4) Propose future research needs and; 5) Make recommendations for how best to prevent alkali‐silica reactivity following the proposed approach. [ABSTRACT FROM AUTHOR]

Seeking an easy-to-deploy, energy-efficient, non-herbicide weed control method, we tested a flat-plate electrode to apply pulsed electric microshocks (PMS) to a grass and four broadleaf weed species. The method can be deployed via a hand-held unit or as part of a fully automated system to control escape weeds in field crops. The effectiveness of the treatments and the relative energy discharges when applying similar electric doses to the plant leaves or to the plant when pressed to the soil with a flat-plate electrode were compared. The method killed only half of the treated Lolium multiflorum "Winter Star" plants, well below our target rate, but significantly reduced growth rates and indicated that effective treatment of <1.0 MJ ha−1 for treating five plants m−2 is possible. Polygonum aviculare L., Amaranthus powellii S. Wats., Amaranthus deflexus, and Solanum nitidibaccatum Bitter plants were successfully controlled, with the energy required to kill 100% of seedlings varying from 0.1 to 0.9 MJ ha−1, indicating that broadleaf weeds are more susceptible. This easily met our target effectiveness and efficiency goals. The discharged energy increased when the electrode pressed the plant to a dry soil surface rather than to the leaves only and increased further when the electrode pressed the plant to a wet soil surface. [ABSTRACT FROM AUTHOR]

Given that marketing and its new methods play essential roles in survival in the current competitive market, the development of new marketing methods is considered the key to the survival of small businesses, and it has thus created guerilla marketing. Therefore, the present research aimed to synthesize extensive literature on guerrilla marketing. The research had an exploratory sequential mixed-methods type in terms of the nature of data analysis methods: In the first step, it was based on the meta-synthesis qualitative approach; in the second step, it determined the indices of the guerilla marketing model and screened them using the binomial t-test, and the fuzzy Delphi method (quantitative method); and in the third step, it introduced the indices agreed upon by the experts and offered a model. The statistical population consisted of studies from 2000 and 2021. In this regard, 250 studies on the target subject were evaluated, and finally, 26 studies were selected purposefully. Using the content analysis and synthesis of the relevant literature, 7 concepts and 5 key categories were selected from a total of 68 codes during the search process and systematic synthesis and were then analyzed and their validity was confirmed using Kaufman's kappa test. After the survey of experts, 61 codes were approved employing binomial test and fuzzy Delphi method. The results indicated that the most important key categories identified included technological tools, human tools, cultural tools, relational tools, and advertising weapons. The present research provided a deep understanding of the existing literature on guerrilla marketing. [ABSTRACT FROM AUTHOR]

This article discusses the issue of herbicide-resistant weeds in New Zealand's agricultural sectors. The number of cases of herbicide resistance has increased in New Zealand since the late 1970s, although the incidence is lower compared to other countries like Australia. The article highlights the importance of improved weed control and vegetation management to minimize future herbicide resistance. It also presents recent research on herbicide resistance and weed management, including the development of a machine-learning tool to assess the risk of herbicide resistance in different weed species. The article emphasizes the need for proper reporting and monitoring of herbicide resistance and explores alternative non-chemical approaches to weed management. Overall, the article provides valuable insights into the current focus of herbicide resistance research in New Zealand. [Extracted from the article]

A successful teacher manages the classroom in a way to meet all the potential challenges. In effect, classroom management skills are the cornerstone of the whole process of successful teaching. This survey-based study assessed the interrelationship among EFL teachers' smart classroom management (SCM), their students' learning approach, positive orientation (PO), and language achievement (LA). SCM implies using different strategies including appropriate planning, organization, leadership, and control based on humanistic approaches to education. The population of the study consisted of about 307 Iranian university, institute, and public school students, out of which 279 were sampled. This study used the Persian forms of three questionnaires: Smart Classroom Management Questionnaire (SCMQ), Revised Study Process Questionnaire (R-SPQ-2F) measuring deep approach (D), surface approach (SA), and Positivity Scale (PS). The results obtained via Structural Equation Modeling (SEM) demonstrated that the expected model including the variables under study had a good fit with the data. The results demonstrated that EFL teachers' SCM positively and significantly influenced the three student-related factors: DA. LA, and PO. LA was positively predicted by DA, while SA had no significant influence on LA. PO positively and significantly impacted LA. It can also be concluded that LA is positively predicted by SCM via its influence on DA and PO. The major implication of the present study should inform teacher educators to incorporate SCM strategies in their programs. [ABSTRACT FROM AUTHOR]

Human-caused nitrogen (N) deposition is a global environmental issue that can change community composition, functions, and ecosystem services. N deposition affects plants, soil, and microorganisms regionally and is linked to ecosystem, soil, and climate factors. We examined the effects of six N addition levels (0, 2.34 g, 4.67, 9.34,18.68, and 37.35 g N m−2 yr−1) on aboveground vegetation, surface soil properties, and microbial community. Alterations in microbial communities in response to N addition were monitored using 16S rRNA (16S ribosomal ribonucleic acid, where S donates a sedimentation coefficient) and ITS (internal transcribed spacer) regions for bacterial and fungal communities, respectively. N addition positively affected aboveground vegetation traits, such as biomass and community weighted mean of leaf nitrogen. N addition also limited phosphorus (P) availability and altered the microbial community assembly process from random processes to deterministic processes. The microbial community diversity and composition, however, were not sensitive to N addition. Partial least squares structural equation models showed that the composition of bacterial communities was mainly driven by the composition of plant communities and total nitrogen, while the composition of fungal communities was driven by soil pH and community weighted mean of leaf nitrogen. Taken together, the results of this research improved our understanding of the response of grassland ecosystems to N deposition and provided a theoretical basis for grassland utilization and management under N deposition. [ABSTRACT FROM AUTHOR]

Chemical stabilization is used to enhance and increase the strength characteristics of soft and problematic soils. In this research, Gaussian Process Regression (GPR) is employed to estimate the unconfined compressive strength (UCS) and the Young's modulus (E) of lean clay soils stabilized with iron ore mine tailing (IOMT) and hydrated lime (HL) percentage. In this regard, four inputs including the moisture content (MC), IMOT percentage, HL percentage, and curing time (CT) were used. The value of R2 for estimating the UCS and the E were 0.9825 and 0.9633 for all data, respectively. The RMSE for predicting the UCS and the E were 0.1875 and 19.868 for all data, respectively. The result of the sensitivity analysis demonstrated that MC, CT, HL, and IOMT percentage have the highest contribution to the UCS of the stabilized lean clay, respectively. Also, MC, HL, IOMT percentage, and CT have the highest impact on the E of the stabilized lean clay, respectively. The parametric study also revealed that increasing the HL content and the curing time led to an increase in the UCS and the E of stabilized lean clay, while IOMT content and the moisture content has an inverse relationship with the UCS and the E of stabilized lean clay soils. [ABSTRACT FROM AUTHOR]

The structure complexity and the extended geographical area are among the factors that create challenges in accurate fault location and detection in distribution networks. The single‐phase to ground (SPG) faults are considered as most frequent reasons for distribution network interruption, which can threaten the network's reliability. Signal processing methods are usually used as common approaches to distinguish and locate faults in distribution networks. This paper proposes a novel scenario to select optimal wavelet packet transform (WPT) coefficients for SPG fault location and a method based on superimposed voltage energy to distinguish the faulty phase according to these coefficients. Furthermore, employing the energies of the superimposed voltages helps to minimize the effects of high resistance faults (HRFs) and load encroachment on the efficiency of the faulty phase detection part. Comparing the obtained results with other scenarios demonstrates the considerable efficiency of the proposed scenario. Finally, with the help of general regression neural networks (GRNN) as machine‐learning tools, a new algorithm is derived for detecting and locating the SPG fault and capacitor bank switching overvoltage (COV). Simulation results are implemented on the IEEE 34‐bus standard distribution network, demonstrating the efficiency and superiority of the suggested method. [ABSTRACT FROM AUTHOR]

The present study aimed at investigating the effect of Teacher Technology Enhanced Scaffolding (TTES) on English as a Foreign Language (EFL) learners' grammar achievement, Directed Motivational Currents (DMCs), and mastery goal. This investigation was conducted among 50 participants in two classes, with a population of 25 EFL students for each group (control and experimental). The participants were all female junior high school students. They were administered a grammar test and two questionnaires once at the beginning and once at the end of the course. To gauge students' DMC, the Persian version of the DMC Disposition Questionnaire which was designed and validated by Muir (2016) and translated into Persian and revalidated by Ghanizadeh and Jahedizadeh(2017) was utilized. To assess the students' mastery goal, six items of the translated version of Achievement Goal Orientation Inventory designed by Midgley et al. (1998) was employed. Teaching in both groups was provided through Eitaa messenger. The treatment was presented in accordance with the principles of the process approach comprising three stages, noticing, retrieval, and generation. These are the three basic principles in the process approach adapted from Nation (2001). However, in the control group, the grammar was taught in the traditional method in the way that the same structure was presented to the learners, and then they did some exercises. The results of independent samples t-test demonstrated that using TTES had a significant impact on learners' grammar learning, DMC, and mastery goal. [ABSTRACT FROM AUTHOR]

Three-dimensional printing technologies can be implemented for the fabrication of personalized vaginal rings (VRs) as an alternative approach to traditional manufacturing. Although several studies have demonstrated the potential of additive manufacturing, there is a lack of knowledge concerning the opinions of patients and clinicians. This study aimed to investigate the perception of women and gynecologists regarding VRs with personalized shapes. The devices were printed with different designs (traditional, "Y", "M", and flat circle) by Fused Deposition Modeling for a cross-sectional survey with 155 participants. Their anticipated opinion was assessed through a questionnaire after a visual/tactile analysis of the VRs. The findings revealed that most women would feel comfortable using some of the 3D-printed VR designs and demonstrated good acceptability for the traditional and two innovative designs. However, women presented multiple preferences when the actual geometry was assessed, which directly related to their age, previous use of the vaginal route, and perception of comfort. In turn, gynecologists favored prescribing traditional and flat circle designs. Overall, although there was a difference in the perception between women and gynecologists, they had a positive opinion of the 3D-printed VRs. Finally, the personalized VRs could lead to an increase in therapeutic adherence, by meeting women's preferences. [ABSTRACT FROM AUTHOR]

Selective laser sintering (SLS) has drawn attention for the fabrication of three-dimensional oral dosage forms due to the plurality of drug formulations that can be processed. The aim of this work was to employ SLS with a CO2 laser for the manufacturing of carvedilol personalised dosage forms of various strengths. Carvedilol (CVD) and vinylpyrrolidone-vinyl acetate copolymer (Kollidon VA64) blends of various ratios were sintered to produce CVD tablets of 3.125, 6.25, and 12.5 mg. The tuning of the SLS processing laser intensity parameter improved printability and impacted the tablet hardness, friability, CVD dissolution rate, and the total amount of drug released. Physicochemical characterization showed the presence of CVD in the amorphous state. X-ray micro-CT analysis demonstrated that the applied CO2 intensity affected the total tablet porosity, which was reduced with increased laser intensity. The study demonstrated that SLS is a suitable technology for the development of personalised medicines that meet the required specifications and patient needs. [ABSTRACT FROM AUTHOR]

Fertilization could influence ecosystem structure and functioning through species turnover (ST) and intraspecific trait variation (ITV), especially in nutrient limited ecosystems. To quantify the relative importance of ITV and ST in driving community functional structure and productivity changes under nitrogen (N) and phosphorous (P) addition in semiarid grasslands. In this regard, we conducted a four-year fertilizer addition experiment in a semiarid grassland on the Loess Plateau, China. We examined how fertilization affects species-level leaf and root trait plasticity to evaluate the ability of plants to manifest different levels of traits in response to different N and P addition. Also, we assessed how ITV or ST dominated community-weighted mean (CWM) traits and functional diversity variations and evaluated their effects on grassland productivity. The results showed that the patterns of plasticity varied greatly among different plant species, and leaf and root traits showed coordinated variations following fertilization. Increasing the level of N and P increased CWM_specific leaf area (CWM_SLA), CWM_leaf N concentration (CWM_LN) and CWM_maximum plant height (CWM_Hmax) and ITV predominate these CWM traits variations. As a results, increased CWM_Hmax, CWM_LN and CWM_SLA positively influenced grassland productivity. In contrast, functional divergence decreased with increasing N and P and showed negative relationships with grassland productivity. Our results emphasized that CWM traits and functional diversity contrastingly drive changes in grassland productivity under N and P addition. [ABSTRACT FROM AUTHOR]

Earthquake-induced soil liquefaction (EISL) can cause significant damage to structures, facilities, and vital urban arteries. Thus, the accurate prediction of EISL is a challenge for geotechnical engineers in mitigating irreparable loss to buildings and human lives. This research aims to propose a binary classification model based on the hybrid method of a wavelet neural network (WNN) and particle swarm optimization (PSO) to predict EISL based on cone penetration test (CPT) results. To this end, a well-known dataset consisting of 109 datapoints has been used. The developed WNN-PSO model can predict liquefaction with an overall accuracy of 99.09% based on seven input variables, including total vertical stress ( σ v ), effective vertical stress ( σ v ′ ), mean grain size (D50), normalized peak horizontal acceleration at ground surface (αmax), cone resistance (qc), cyclic stress ratio (CSR), and earthquake magnitude (Mw). The results show that the proposed WNN-PSO model has superior performance against other computational intelligence models. The results of sensitivity analysis using the neighborhood component analysis (NCA) method reveal that among the seven input variables, qc has the highest degree of importance and Mw has the lowest degree of importance in predicting EISL. [ABSTRACT FROM AUTHOR]