Search

Ionic liquids (ILs) are increasingly used, e.g. as solvents, electrolytes, active pharmaceutical ingredients and herbicides. If ILs enter the environment due to their use or accidental spills at industry sites, they can pollute the environment. To avoid adverse side effects of persistent ILs in the environment, they should be designed to fully mineralise in the environment after they fulfilled their function during application. (Quantitative) structure–biodegradability relationship models ((Q)SBRs) have been successfully applied in the design of benign chemicals. However, (Q)SBR models have not been widely applied to design mineralising ILs. Therefore, in this study we developed five quantitative structure–biodegradability relationship (QSBR) models based on OECD 301D data from the literature and our own in-house biodegradation experiments. These models can potentially be part of a test battery for designing fully mineralising ILs to increase the overall reliability of the biodegradability assessment and reduce uncertainties. Two datasets were formed and randomly divided into a training set with 233 and 321 compounds and a test set with 26 and 36 compounds, respectively. Both classification and regression models were built using molecular fragments with the aim to predict the classification and continuous biodegradation rate, respectively. The internal and external validations produced a R2 of 0.620–0.854 for the regression models and accuracy, true positive rate, and true negative rate were between 62 and 100% for the classification models indicating an adequate performance but also a need for improvement. For the models and the test battery presented in this study, further research is needed to demonstrate their applicability. [ABSTRACT FROM AUTHOR]

High throughput screening (HTS) methods of enzyme variants are essential for the development of robust biocatalysts suited for low impact, industrial scale, biobased synthesis of a myriad of compounds. However, for the majority of enzyme classes, current screening methods have limited throughput, or need expensive substrates in combination with sophisticated setups. Here, we present a straightforward, high throughput selection system that couples sucrose synthase activity to growth. Enabling high throughput screening of this enzyme class holds the potential to facilitate the creation of robust variants, which in turn can significantly impact the future of cost effective industrial glycosylation. [ABSTRACT FROM AUTHOR]

Quasi-zero stiffness (QZS) vibration isolators are widely used for vibration isolation due to their high performance, but their low load-carrying capacity limits their applications. In this paper, a heavy-load-bearing QZS vibration isolator consisting of three compression springs is investigated for isolating ultra-low frequency vibrations. From the theoretical aspect, parameter optimization considering both load mass and isolation performance metric (IPM) is implemented, and a parameter guidance diagram is proposed for parameter design. From the practical point of view, two innovative springs are designed and fabricated by wire-electrical discharge machining (W-EDM), referring to the idea of compliant mechanism. These creative designs are endowed with precise stiffness, large compression and buckling avoidance, which further improve the system properties. Finally, a prototype is made and experiments are carried out to verify the effectiveness of the design. Compared with linear isolators, the experimental results of QZS isolator show better isolation performances in a wider frequency range. • A quasi-zero stiffness isolator is proposed to isolate ultralow frequency vibrations. • Guidance graphs considering isolation and load-bearing performances are developed. • Machinable springs are designed to avoid buckling and thus achieve large compression. • Machinable springs avoid introducing damping and thus enhance system properties. [ABSTRACT FROM AUTHOR]

There is growing interest in multicancer detection tests, which identify molecular signals in the blood that indicate a potential preclinical cancer. A key stage in evaluating these tests is a prediagnostic performance study, in which investigators store specimens from asymptomatic individuals and later test stored specimens from patients with cancer and a random sample of controls to determine predictive performance. Performance metrics include rates of cancer-specific true-positive and false-positive findings and a cancer-specific positive predictive value, with the latter compared with a decision-analytic threshold. The sample size trade-off method, which trades imprecise targeting of the true-positive rate for precise targeting of a zero-false-positive rate can substantially reduce sample size while increasing the lower bound of the positive predictive value. For a 1-year follow-up, with ovarian cancer as the rarest cancer considered, the sample size trade-off method yields a sample size of 163 000 compared with a sample size of 720 000, based on standard calculations. These design and analysis recommendations should be considered in planning a specimen repository and in the prediagnostic evaluation of multicancer detection tests. [ABSTRACT FROM AUTHOR]

Sex differences in mental rotation performance are one of the largest in cognitive psychology. Men outperform women by up to 1 SD in psychometric mental rotation tests, but it is often neglected that there are no or only small sex differences for chronometric tests. As both tests are supposed to measure the same ability, we suspect some features of the tests themselves to affect sex differences in performance. Following a theoretical review of the test features, we evaluate the effects of the number of possible answer alternatives, whether they are presented as pairwise mirrored, and their interaction on sex differences in mental rotation performance. In an online experiment, 838 German-speaking participants, 421 women, 417 men, M age = 42.58 (SD = 12.54) years, solved four blocks of mental rotation trials with two or eight alternatives, which were either pairwise mirrored or not. The results show that that the overall performance was lower for more alternatives and for mixed alternatives but not for their interaction. We could not determine explanations for sex differences as we did not observe meaningful sex differences at all. Possible reasons include the differences between men and women in age and education. This study suggests that the differences between tests affect performance. Sex differences, however, need more investigation, including possible effects and interactions of the test design, education, and age. [ABSTRACT FROM AUTHOR]

Background: A practical test that measures the information and communication technology (ICT) skills students need for effectively using ICT in primary education has yet to be developed (Oh et al., 2021). This paper reports on the development, validation, and reliability of a test measuring primary school students' ICT skills required for effectively using ICT (the ECC‐ICT test). Objectives: Based on existing literature, three ICT use domains were identified for effectively using ICT: Effective, collaborative, and creativeuse of ICT. For these three domains, 24 corresponding teaching objectives were identified from a widely used digital literacy framework. Thirty‐four test items cover these teaching objectives in an online test. Methods: A mixed‐method approach was used for the ECC‐ICT test. Four pilot rounds (n=25) implemented qualitative interviews for cognitive validity and refining the test items, followed by a qualitative usability study(n=6). Confirmatory factor analysis and ANOVA provided quantitative insight into the large‐scale test administration(n=575). Results and Conclusions: Composite reliability of our conceptual 3‐factor confirmatory model showed that the test reliably measured primary school effective use of ICT (ω = 0.82), collaborative use of ICT (ω = 0.80) and creative use of ICT (ω = 0.64). Convergent validity (ranging from 0.41 to 0.46) was acceptable. Internal consistency (ranging from 0.84 to 0.91) and discriminant validity (HTMT values below 0.90) are good. ANOVA results show that mean test scores are higher for students in higher grade levels (p < 0.001). The post hoc Bonferroni results show that most grade‐by‐grade comparisons are significant (p < 0.001). Lay Description: What is already known about this topic: Information and communication technology (ICT) skills are finding their way into national curriculums as teachers implement more digital learning environments.Teachers currently do not have a measurement instrument for the ICT skills primary education students need to learn in a personalised way. What this paper adds: This paper gives teachers a test that reliably measures the effective, collaborative, and creative ICT skills required for primary school students to learn using ICT.To our knowledge, this test is the first of its kind.Al materials to reproduce the test are available digitally for teachers. The implications of study findings for practitioners: For policy, this test can be used to check if a student is ready to use ICT in a self‐regulated setting.With this test, teachers can assess and support students' growth on the effective, collaborative, and creative ICT skills required for primary school students using ICT. [ABSTRACT FROM AUTHOR]

• Create a prediction model based on anti-angiogenesis for patients with locally advanced cervical cancer. • The level of benefit of targeted therapy could be predicted before treatment, and the model validation was good. This study aimed to develop and evaluate an anti-angiogenesis-based model for predicting the survival and the potential benefits of targeted therapy for patients with localized advanced cervical cancer. We collected clinical data from 163 patients with cervical cancer who received paclitaxel and cisplatin (TP) or TP plus bevacizumab during or after radiotherapy from June 2017 to February 2023. We analyzed the clinical measures of recent efficacy and overall survival (OS) using univariate and logistic multivariate and Cox regression methods, respectively. We constructed a nomogram model and evaluated its efficacy using the c-index, the area under the curve (AUC), a calibration curve, and the clinical decision curve (DCA). We found that targeted agents and hemoglobin were independent determinants of near-term efficacy (P < 0.05), while targeted agents and stage were independent factors of OS (P < 0.05). We developed a predictive model for an OS prognostic nomogram and performed internal validation 1000 times using the Bootstrap re-sampling method. The c-index was 0.81, and the AUC was 0.84 (P < 0.01).The calibration curves showed a good agreement between the projected and actual values. The DCA curve indicated that the model had a high positive predictive accuracy. We developed a novel anti-angiogenesis-based survival prediction model for patients with locally advanced cervical cancer. This model could estimate the benefit of targeted therapy before treatment, and it had good validation. [ABSTRACT FROM AUTHOR]

It is well documented that survey overreporting of voter turnout due to social desirability bias threatens inference about political behavior. This paper reports four studies that contained question wording experiments to test questions designed to minimize that bias using a "pipeline" approach. The "pipeline" informs survey participants that researchers can perform vote validation to verify turnout self-reports. This approach reduced self-reported turnout by 5.7 points in the 2020 American National Election Study, which represents a majority of the estimated overreporting bias. It reduced reported turnout by 4 points in two nonprobability samples. No effect was found in a third nonprobability study with Amazon Mechanical Turk workers. Validated vote data also confirm that the pipeline approach reduced overreporting. We tested heterogeneous effects for sophistication and several other variables, but results were inconclusive. The pipeline approach reduces overreporting of voter turnout and produces more accurate estimates of voters' characteristics. [ABSTRACT FROM AUTHOR]

The integration of inserts into sandwich panel constructions is a complex multi-step process with significant human intervention that also limits the geometrical freedom of the insert design. In a standard sandwich construction, the panel core is made up of multiple materials across its main components: insert, potting and core. This multi-material assembly is not only difficult to manufacture, but it also promotes stress jumps at the insert-core interface, leading to a sub-optimal load distribution from the bolt to the panel core. Additive manufacturing (AM) can lead to a single-part core and insert assembly with more optimised insert geometries that can better transmit the loads applied to the panel. Previous work by the authors has explored the manufacturing limits and the failure modes of AM inserts integrated in cores printed out of sintered AlSi10Mg. The conclusions were that the core walls and insert elements should have a minimum design thickness of 0.5 mm to survive the tapping process without facesheets attached and it was found that the main failure mode of the geometries tested in pull-out was buckling of the insert walls. Based on these results, the paper proposes a novel insert design philosophy that can delay the buckling of 3D printed inserts and move the failure point of the insert away from the bolt. A set of inserts that follow this design direction is manufactured and tested under normal pull-out loads and the optimised designs outperform standard printed insert geometries by a factor of three. The design philosophy can be further developed to offer a suitable alternative to the current insert standard. [ABSTRACT FROM AUTHOR]

We describe the construction and testing of an in situ cloud particle imager based on digital holography. The instrument was designed to be low cost and lightweight for vertical profiling of clouds with an untethered weather balloon. This capability is intended to address the lack of in situ cloud microphysical observations that are required for improving the understanding of cloud processes, calibration of climate and weather models, and validation of remote sensing observation methods. From a balloon sounding through multiple bands of cloud, we show that we can retrieve shape information and size distributions of the cloud particles as a function of altitude. Microphysical retrievals from an imaging satellite are compared to these in situ observations, and significant differences are identified, consistent with those identified in prior evaluation campaigns. [ABSTRACT FROM AUTHOR]

Background: The selection of primer pairs in sequencing-based research can greatly influence the results, highlighting the need for a tool capable of analysing their performance in-silico prior to the sequencing process. We therefore propose PrimerEvalPy, a Python-based package designed to test the performance of any primer or primer pair against any sequencing database. The package calculates a coverage metric and returns the amplicon sequences found, along with information such as their average start and end positions. It also allows the analysis of coverage for different taxonomic levels. Results: As a case study, PrimerEvalPy was used to test the most commonly used primers in the literature against two oral 16S rRNA gene databases containing bacteria and archaea. The results showed that the most commonly used primer pairs in the oral cavity did not match those with the highest coverage. The best performing primer pairs were found for the detection of oral bacteria and archaea. Conclusions: This demonstrates the importance of a coverage analysis tool such as PrimerEvalPy to find the best primer pairs for specific niches. The software is available under the MIT licence at https://gitlab.citius.usc.es/lara.vazquez/PrimerEvalPy. [ABSTRACT FROM AUTHOR]

AbstractTraditional analyses of pretest-posttest designs draw inferences about learning using linear models that predict posttest performance by accounting for pretest scores. These analyses allow inferring student growth effects but prior research has pointed out some conceptual problems, such as its meaningful interpretation as learning. By drawing on research about physics teaching, this study introduces the Learning Rate Model (LR-Model) to describe learning as a non-linear process of knowledge acquisition. Analysis of data gathered from two real-world math learning interventions indicates that the model can provide adequate interpretations of math learning phenomena observed in pretest-posttest study designs. The model seems well suited to assess math learning interventions that teach unfamiliar knowledge to learners, where the pretest and posttest measures are designed to evaluate the content delivered during the intervention. Under these conditions, the LR-Model shows advantages to alternative linear models as (1) it describes learning more accurately, (2) it delivers more meaningful learning estimators, and (3) it provides higher statistical power for hypothesis testing aimed at determining learning effects. [ABSTRACT FROM AUTHOR]

Training deep learning models for vision-based monitoring of construction sites usually requires a large amount of labeled data. Semisupervised learning methods can efficiently obtain unlabeled data with substantial cost savings. Thus, this paper proposes a semisupervised object detection method for construction site monitoring. Weather as well as strong and weak data augmentation are integrated to cope with the complex construction site conditions (weather changes, camera view shifts, and so on) by integrating semisupervised learning to leverage the valid information in unlabeled construction site images. To validate its effectiveness, the proposed method was tested on the Alberta Construction Image Data Set (ACID), a public data set for the construction research community. The experimental results revealed that the proposed method achieves an average accuracy [mean average precision (mAP)] of 81.1% when trained on only 3% of the labeled images. This study helps to significantly reduce the development cost of vision-based object detection models for construction sites. [ABSTRACT FROM AUTHOR]

After two phases of on-site construction and testing (2010–2013 and 2013–2017), the Shanghai Tianma Radio Telescope (TMRT) can work well, with efficiencies better than 50% from 1.3 to 50.0 GHz, mainly benefiting from its low-noise cryogenic receivers and active surface system. Pulsars were chosen as important targets of research at the TMRT because of their important scientific and applied values. To meet the demands of pulsar-related observations, TMRT is equipped with some necessary backends, including a digital backend system (DIBAS) supporting normal pulsar observation modes, a real-time fast-radio-burst-monitoring backend, and baseband backends for very-long-baseline interferometry (VLBI) observations. Utilizing its high sensitivity and simultaneous dual-frequency observation capacity, a sequence of pulsar research endeavors has been undertaken, such as long-term pulsar timing, magnetar monitoring, multi-frequency (or high-frequency) observations, interstellar scintillation, pulsar VLBI, etc. In this paper, we give a short introduction about pulsar observation systems at the TMRT and briefly review the results obtained by these pulsar research projects. [ABSTRACT FROM AUTHOR]

Zero-shot learning (ZSL) refers to the design of predictive functions on new classes (unseen classes) of data that have never been seen during training. In a more practical scenario, generalized zero-shot learning (GZSL) requires predicting both seen and unseen classes accurately. In the absence of target samples, many GZSL models may overfit training data and are inclined to predict individuals as categories that have been seen in training. To alleviate this problem, we develop a parameter-wise adversarial training process that promotes robust recognition of seen classes while designing during the test a novel model perturbation mechanism to ensure sufficient sensitivity to unseen classes. Concretely, adversarial perturbation is conducted on the model to obtain instance-specific parameters so that predictions can be biased to unseen classes in the test. Meanwhile, the robust training encourages the model robustness, leading to nearly unaffected prediction for seen classes. Moreover, perturbations in the parameter space, computed from multiple individuals simultaneously, can be used to avoid the effect of perturbations that are too extreme and ruin the predictions. Comparison results on four benchmark ZSL data sets show the effective improvement that the proposed framework made on zero-shot methods with learned metrics. [ABSTRACT FROM AUTHOR]

The public‐elite policy feedback mechanism of the Social Construction Framework (SCF) postulates that the public rewards policymakers for the appropriate distribution of benefits and burdens to target populations. In this article we test a key part of this dynamic by examining public receptivity to policy design features as a function of target population choice. We conduct a national survey experiment of approximately 3350 Americans. Our instrument asks respondents to indicate support or opposition to a range of policy tools in a suite of six climate change policies, but varies who would be responsible for options based upon Schneider and Ingram's idealized types. Our research design tests the independent effects of deservingness and power foundational to the construction of target populations in the SCF. We find, in general, deservingness to be a stronger predictor of support for policy tools than notions of power. We also identify situations where deservingness acts independently of power in ways not anticipated by the SCF—notably public favor for burdens on powerful groups. Our findings offer implications for theoretical and empirical development of the SCF regarding the influence of policymakers' perceptions of public acceptance of policy design in crafting public policies. [ABSTRACT FROM AUTHOR]

This study proposed a modified lift-off test that enables evaluation of the anchoring condition (anchored capacity or creep ratio) during the investigation of the residual anchor load and facilitates the restressing of anchors. To verify the applicability of the proposed measure in practice, a case study of the rehabilitated landslide slope of the T16 support tower of the Taipei Maokong Gondola System was conducted, a two-stage procedure that simultaneously facilitated the investigation and rehabilitation of an anchored slope with load loss. Results of an investigation of the residual load acting on 619 anchors indicated that the average load loss of the anchors was approximately 36% compared with the design load. In conventional design, approximately 223 extra anchors must be installed in the study area. However, the corresponding number in the proposed measure is about one-fifth the number of anchors required in the conventional approach. This paper emphasizes the merit of using the modified lift-off test in reducing construction time and construction costs in slope rehabilitation. Furthermore, the proposed rehabilitation measure adopted in this study did not involve adding many concrete structures to the original anchored slope. Thus, these measures are environmentally friendly and contribute to sustainable development. [ABSTRACT FROM AUTHOR]

Various geometric and mechanical conditions for soil–foundation interfaces affect the superstructure and foundation responses against earthquake. As one of these conditions, 2D asymmetry of soil around the embedded rigid foundation is emphasized in the present paper. Accordingly, a reduced-scaled embedded foundation bearing SDOF superstructure is considered under slow lateral cyclic and dynamic shake table tests in design and service levels at 1 g state, and the system response is compared to those of systems containing surface and embedded foundations with symmetric condition. Test results show the asymmetry in the moment–rotation response curve for system with asymmetric soil condition in static state. While for dynamic response, the behavior under harmonic excitation with the design amplitude level is close to one of system with surface foundation. In addition, the foundation moment capacity of nonlinear dynamic response can be estimated properly through theoretical expression for foundation with asymmetric condition. Moreover, the rocking behavior in two-way excitation causes significant loss of superstructure response relative to the foundation in all three cases. [ABSTRACT FROM AUTHOR]

Hypothesis testing is a valuable method used to investigate ideas and test predictions arising from theories based on available data. In the context of critical system architecture, there is a need to effectively utilize hypothesis testing to identify faulty paths and improve system safety. This research aims to propose guidelines and best practices for presenting hypothesis testing in critical system architecture. The problem addressed in this study is the underutilization of hypothesis testing in life-critical system methods, resulting in a lack of identification of faulty paths. To address this challenge, we propose an enhanced pathway analysis technique that integrates error-derived information from a system's architectural description, thereby augmenting traditional hypothesis testing methods. By investigating various paths, we aim to identify false positive and false negative errors in life-critical system architecture. Furthermore, the proposed method is validated based on specific validation criteria for each step such as system boundary, assumption, content/architecture, and traceability validations. Also, the method is evaluated based on our claims. The results of our research highlight the significance of tracing errors in early system knowledge. By leveraging the augmented hypothesis testing method, we are able to identify hazards, safety constraints, and specific causes of unsafe actions more effectively. The findings emphasize the importance of integrating early design knowledge into hypothesis testing for enhanced hazard identification and improved system safety. [ABSTRACT FROM AUTHOR]

A wireless monitoring system based on piezoelectric energy harvesting (PEH) is presented to provide fatigue data of wind turbine blades in operation. The system comprises three subsystems, each respectively providing the following functions: (i) the conversion of mechanical to electric energy by exploiting the bistable vibration of a composite beam with piezoelectric patches in post-buckling, (ii) harvesting the converted energy by means of a modified, commercial, off-the-shelf (COTS) circuit to feed a LiPo battery and (iii) the battery-powered acquisition and wireless transmission of sensory signals to the cloud to be elaborated upon by the end-user. The system was verified with ground tests under representative operation conditions, which demonstrated the fulfillment of the design requirements. The measurements indicated that the system provided 23% of the required power for fully autonomous operation when subjected to white noise base excitation of 1 g acceleration in the range of 1–20 Hz. [ABSTRACT FROM AUTHOR]

In many geological hazards, such as landslides, a large number of irregular blocks start moving. Their interaction on the way down renders prediction of disaster scopes difficult. To study this process and to provide a novel method for validation and calibration of numerical tools for its simulation, a cube movement test is designed. The goal of this research is to obtain patterns of movement of cubes, starting from different initial stacking arrangements. Cubes of four sizes are inserted into a hollow cylinder. Their distribution after lifting the cylinder is determined. Three categories of tests refer to three different strategies of filling the cubes into the cylinder. In order to simulate cube movement tests, a numerical tool is developed in the framework of the continuum–discontinuum element method (CDEM). The contact between the individual cubes is modeled by the contact‐pairs‐based algorithm. Both the contact state and type are detected by determining the half‐space relation between contact pairs. The final positions of the cubes are strongly related to their initial arrangement. The latter is different in every test, even if the same strategy is used to fill the cubes into the cylinder. It is found that at least 20 experiments/simulations are required to obtain statistically representative results. The new test provides valuable data for validation of numerical tools used for the simulation of mass movement processes. The proposed numerical method captures the complicated movements of blocks. [ABSTRACT FROM AUTHOR]

During the harvesting process, rigid materials are prone to causing damage to the cotton stalks, which will increase the risk of stalk breakage. A cotton stalk pulling component that blends stiff and flexible materials was devised to lower the breaking rate. The cotton stalk pulling component was made up of rollers and flexible belts that pull the stalks using clamping force and the forward speed of the tractor. The influence of various factors in the equipment on the harvesting effect of cotton stalks were analyzed through response surface experiments, and a multiple quadratic regression response surface model with missing pulling rate and breakage rate as response values was established. The significant of influencing factors on the breaking rate of cotton stalks are in a descending order as: the angle of cotton stalk pulling, tractor's forward speed, and the clamping speed of the cotton stalk component. The working parameters of the wheel-belt type cotton stalk pulling machine have been optimized using the response surface combination experimental method, and the optimal parameter combination was obtained as: tractor forward speed of 4.5 km/h, cotton stalk pulling angle of 60°, and clamping speed of the cotton stalk pulling component of 349 r/min. The results of validation experiments showed that the missing pulling rate of cotton stalks was 5.06% and the breakage rate was 13.12%, indicating a good harvesting effect of the cotton stalks. The model was reasonable and the performance parameters could meet the relevant inspection requirements. The results can provide a reference for further research on the technology of flexible cotton stalk pulling. [ABSTRACT FROM AUTHOR]

Model testing is common in coastal and offshore engineering. The design of such model tests is important such that the maximal information of the underlying physics can be extrapolated with a limited amount of test cases. The design of experiments also requires considering the previous similar experimental results and the typical sea-states of the ocean environments. In this study, we develop a model test design strategy based on Bayesian sampling for a classic problem in ocean engineering--nonlinear wave loading on a vertical cylinder. The new experimental design strategy is achieved through a GP-based surrogate model, which considers the previous experimental data as the prior information. The metocean data are further incorporated into the experimental design through a modified acquisition function. We perform a new experiment, which is mainly designed by data-driven methods, including several critical parameters such as the size of the cylinder and all the wave conditions. We examine the performance of such a method when compared to traditional experimental design based on manual decisions. This method is a step forward to a more systematic way of approaching test designs with marginally better performance in capturing the higher-order force coefficients. The current surrogate model also made several "interpretable" decisions which can be explained with physical insights. [ABSTRACT FROM AUTHOR]

The electric wheel loader is a new prototype in powertrains and drivetrains that saves energy consumption and diminishes emissions as earthmoving machinery. Dual-motor drive in the front and rear axles of electric wheel loaders helps the distribution of drive torque. However, challenges arise during shoveling conditions, particularly when one motor generates torque exceeding the ground's adhesion force, leading to tire slippage. This study thoroughly examines the mechanical structure of the working unit and elucidates the correlation between wheel load and hydraulic pressure in the base chamber of the tilt cylinder. This analysis is accomplished through a combination of theoretical derivations and experimental tests. The experiments involve a 5 ton rated load electric wheel loader tested across five running cases as well as weighing tests on a 15 ton rated load electric wheel loader. Based on the experiment discoveries, a dual-motor drive electric wheel loader is designed with specific transmission ratios for the front and rear drivetrains, and a torque distribution strategy is proposed based on wheel load during shoveling. Running condition tests demonstrate sufficient drive force for the new electric wheel loader, and shoveling tests reveal a significant reduction in tire slippage when employing the proposed torque distribution strategy compared to evenly distributed torque in the front and rear axles. Moreover, the driving force during the shoveling process remains undiminished. This indicates that the newly designed loader, in conjunction with the proposed strategy, exhibits excellent shoveling efficiency. [ABSTRACT FROM AUTHOR]

Item response theory (IRT) has evolved as a standard psychometric approach in recent years, in particular for test construction based on dichotomous (i.e., true/false) items. Unfortunately, large samples are typically needed for item refinement in unidimensional models and even more so in the multidimensional case. However, Bayesian IRT approaches with hierarchical priors have recently been shown to be promising for estimating even complex models in small samples. Still, it may be challenging for applied researchers to set up such IRT models in general purpose or specialized statistical computer programs. Therefore, we developed a user-friendly tool – a SAS macro called HBMIRT – that allows to estimate uni- and multidimensional IRT models with dichotomous items. We explain the capabilities and features of the macro and demonstrate the particular advantages of the implemented hierarchical priors in rather small samples over weakly informative priors and traditional maximum likelihood estimation with the help of a simulation study. The macro can also be used with the online version of SAS OnDemand for Academics that is freely accessible for academic researchers. [ABSTRACT FROM AUTHOR]

The computerized adaptive form of cognitive diagnostic testing, CD-CAT, has gained increasing attention in the domain of personalized measurements for its ability to categorize individual mastery status of fine-grained attributes more accurately and efficiently through administering items tailored to one's ability progressively. How to select the next item based on previous response(s) is crucial for the success of CD-CAT. Previous item selection strategies for CD-CAT have often followed a greedy or semi-greedy approach, which makes it difficult to strike a balance between diagnostic performance and item bank utilization. To address this issue, this study takes a graph perspective and transforms the item selection problem in CD-CAT into a path-searching problem, in which paths refer to possible test construction and nodes refer to individual items. A heuristic function is defined to predict the prospect of a path, indicating how well the corresponding test can diagnose the current examinee. Two search mechanisms with different biases towards item exposure control are proposed to approximate the optimal path with the best prospect. The first unused item on the resulting path is selected as the next item. The above components compose a novel CD-CAT item selection framework based on heuristic search. Simulation studies are conducted under a variety of conditions regarding bank designs, bank-quality conditions, and testing scenarios. The results are compared with different types of classic item selection strategies in CD-CAT, showing that the proposed framework can enhance bank utilization at a smaller cost of diagnostic performance. [ABSTRACT FROM AUTHOR]

A miniaturised high‐isolation K‐/Ka‐band diplexer with exceeding adjacent channels using 3D antarafacial channel integration and vertical‐quasi‐coaxial‐based matching network is proposed. For smaller size, lower loss and lower channel interference, the high‐order low‐pass filter for the K‐band channel and the four‐line‐interdigital‐coupled wideband bandpass filter for the Ka‐band channel are respectively designed on two low‐loss glass‐based substrates, and these two substrates are integrated on the two antarafacial surface of the mounting board. The vertical‐quasi‐coaxial (VQC) embedded in the mounting board is not only used as three‐dimensional (3D) interconnection of the two antarafacial channels but also designed as the constituent part of the matching/isolation network, and this can effectively decrease the impedance traction caused by the Ka‐band filter for the K‐band channel of the diplexer. In addition, four transmission zeros of the K‐band filter are designed at the whole passband of the Ka‐band channel to improve the isolation to the K‐band channel for guaranteeing the performance of the diplexer at the Ka‐band channel. Furthermore, working principle, design method and test solution of this proposed K‐/Ka‐band diplexer are well illustrated, and the high‐isolation (>40 dB) in very adjacent wideband channels at K‐band (18–23.5 GHz) and Ka‐band (25.8–31.6 GHz) is achieved within a tiny size of 9 × 4 × 0.87 mm. [ABSTRACT FROM AUTHOR]

The unmanned farm control platform is of great significance in promoting the supervision of farm production with less manpower or autonomous operation of farm machinery and the construction of farm informatization. Addressing the existing control platform for farm location information acquisition is time-consuming, labor-intensive, and lacks the whole process control of multiple types of farm machinery. In this paper, we propose an Internet of Things (IoT) control scheme for intelligent farm machinery operation of unmanned farms and design the access standards for multiple types of farm machinery, as well as realize the remote control of intelligent farm machinery operation by constructing a remote control model. A high-precision map construction method is designed to improve the DeepLabV3+ algorithm to identify fields and roads. The control models of path planning, remote task, remote control, and safety system are built to achieve the remote control of intelligent agricultural machinery operation. The proposed technology is implemented in the platform integration and application tests are carried out. The error of the constructed high-precision map is less than 3 cm, the completeness rate of the automatic boundary extraction rate is 96.71%, and the correctness rate is 95.63%, which can be used to obtain the boundary instead of manual labeling or on-site point picking. The use of the platform for the simultaneous control of three farm machinery operations reduces the number of people in operation and production and reduces the professional requirements of the personnel, which will promote the management of the entire farm by one person or even by no one in the future. [ABSTRACT FROM AUTHOR]

Internet‐scale distributed systems often replicate data at multiple geographic locations to provide low latency and high availability, despite node and network failures. According to the CAP theorem, low latency and high availability can only be achieved at the cost of accepting weak consistency. The conflict‐free replicated data type (CRDT) is a framework that provides a principled approach to maintaining eventual consistency among data replicas. CRDTs have been notoriously difficult to design and implement correctly. Subtle deep bugs lie in the complex and tedious handling of all possible cases of conflicting data updates. We argue that the CRDT design should be formally specified and model checked, to uncover deep bugs which are beyond human reasoning. The implementation further needs to be systematically tested. On the one hand, the testing needs to inherit the exhaustive nature of the model checking and ensures the coverage of testing. On the other hand, the testing is expected to find coding errors which cannot be detected by design level verification. Toward the challenges above, we propose the model‐checking‐driven explorative testing (MET) framework. At the design level, MET uses TLA+ to specify and model check CRDT designs. At the implementation level, MET conducts model‐checking‐driven explorative testing, in the sense that the test cases are automatically generated from the model‐checking traces. The system execution is controlled to proceed deterministically, following the model‐checking trace. The explorative testing systematically controls and permutes all nondeterministic choices of message reorderings. We apply MET in our practical development of CRDTs. The bugs in both designs and implementations of CRDTs are found. As for bugs which can be found by traditional testing techniques, MET greatly reduces the cost of fixing the bugs. Moreover, MET can find subtle deep bugs which cannot be found by existing techniques at a reasonable cost. Based on our practical use of MET, we discuss how MET provides us with sufficient confidence in the correctness of our CRDT designs and implementations. Conflict‐free replicated data type (CRDT) is a framework that provides a principled approach to maintaining eventual consistency among data replicas in distributed systems. CRDTs have been notoriously difficult to design and implement correctly. We propose model‐checking‐driven explorative testing (MET) framework for dealing with such problem. We apply MET in our practical development of CRDTs. MET successfully finds subtle deep bugs and provides us with sufficient confidence in the correctness of our CRDT designs and implementations. [ABSTRACT FROM AUTHOR]

Psychometrics is the field of designing tests and assessments to measure certain psychological concepts. It is chiefly concerned with two fundamental properties: reliability and validity. These properties are often influenced by confounding variables: other things that can influence performance but are not what you are trying to measure. Here, I describe how teaching an undergraduate course on psychometrics has reframed my views of assessments in teaching. The goal of any assessment is to accurately, or validly, measure students' knowledge and learning. This raises three questions that can influence assessment design, course structure, and teaching style: 1) Do deadlines really matter? 2) Should all assessments be offered multiple times? 3) How much do my assessments really measure student knowledge on this topic? In discussing each of these, I consider the ways in which evaluating how validity plays a role in our assessment design and teaching style can help us minimize confounding variables and ensure that students' grades reflect their learning. [ABSTRACT FROM AUTHOR]

The robust control of genotoxic N -nitrosamine (NA) impurities is an important safety consideration for the pharmaceutical industry, especially considering recent drug product withdrawals. NAs belong to the 'cohort of concern' list of genotoxic impurities (ICH M7) because of the mutagenic and carcinogenic potency of this chemical class. In addition, regulatory concerns exist regarding the capacity of the Ames test to predict the carcinogenic potential of NAs because of historically discordant results. The reasons postulated to explain these discordant data generally point to aspects of Ames test study design. These include vehicle solvent choice, liver S9 species, bacterial strain, compound concentration, and use of pre-incubation versus plate incorporation methods. Many of these concerns have their roots in historical data generated prior to the harmonization of Ames test guidelines. Therefore, we investigated various Ames test assay parameters and used qualitative analysis and quantitative benchmark dose modelling to identify which combinations provided the most sensitive conditions in terms of mutagenic potency. Two alkyl-nitrosamines, N -nitrosodimethylamine (NDMA) and N -nitrosodiethylamine (NDEA) were studied. NDMA and NDEA mutagenicity was readily detected in the Ames test and key assay parameters were identified that contributed to assay sensitivity rankings. The pre-incubation method (30-min incubation), appropriate vehicle (water or methanol), and hamster-induced liver S9, alongside Salmonella typhimurium strains TA100 and TA1535 and Escherichia coli strain WP2uvrA(pKM101) provide the most sensitive combination of assay parameters in terms of NDMA and NDEA mutagenic potency in the Ames test. Using these parameters and further quantitative benchmark dose modelling, we show that N -nitrosomethylethylamine (NMEA) is positive in Ames test and therefore should no longer be considered a historically discordant NA. The results presented herein define a sensitive Ames test design that can be deployed for the assessment of NAs to support robust impurity qualifications. [ABSTRACT FROM AUTHOR]

It is known that the Metronome Response Task (MRT)—one of the most used mind-wandering sampling paradigms, struggles to differentiate between spontaneous mind-wandering (wherein one's attention is uncontrollably shifted away from the task at hand) and deliberate mind-wandering (wherein one's attention is purposefully shifted away). Thus, we endeavoured to design and test a new mind-wandering measure, called the In Sync Task (IST), that can achieve such differentiation more readily. Unlike the MRT, which involves having participants click in sync (using a mouse) with rhythmically presented, auditory monotones, the IST requires participants to (1) click in sync with tone triplets that increase incrementally in loudness and (2) modulate their clicking force to the presented tone's loudness. Here, we measured (1) participants' variabilities in their rhythmic response times (as is the MRT) and (2) their consistency in appropriately modulating their clicking force. Across two separate samples of university students (n = 119 and n = 121) collected between June 2022 to February 2023, we showed performance differences between the mind-wandering subtypes. Specifically, participants were better able to modulate their clicking force during epochs of spontaneous, compared with deliberate, mind-wandering, whereas the MRT was unable to differentiate between these conditions. In sum, we show that there appear to be greater costs to performance when one deliberately mind-wanders, as opposed to spontaneously mind-wandering. [ABSTRACT FROM AUTHOR]

Glass sagging is a subsequent process to the CVD process used for large‐size and high‐purity silica glass synthesis. Physical phenomena taking place in this process are complicated which need an in‐depth understanding for better control. In this paper, a comprehensive study is conducted for the sagging process using a level‐set and enthalpy‐porosity coupled model. With this model, the deforming behavior of glass ingot and evolution of OH uniformly distributed region are well predicted. Then, two performance indices (the effective yield rate and maximum extension radius of OH uniformly distributed region) are proposed based on different applications, and important factors, including geometrical parameters (the ingot initial length, crucible diameter and pedestal height) and operating parameter (the heater power allocation scheme), are explored for their effects on the two indices. The orthogonal test design method is adopted to further determine the collective effects of the four factors. According to the range analysis results, the initial ingot length has the greatest effect, while the crucible diameter has the least effect on the effective yield rate; and for the maximum extension radius, the crucible diameter becomes the major factor, while the pedestal height is the most insensitive factor. The corresponding optimal schemes are proposed for the two indices finally, which are believed to provide useful guidance for improving the sagging process. [ABSTRACT FROM AUTHOR]

China's college entrance examination reforms necessitate a new view of adolescent career development along with suitable assessment instruments for career intervention with secondary school students. We conducted two studies to address this need. The first study examined the evidence for the validity and reliability of the Student Career Construction Inventory (SCCI). The results of the Confirmatory Factor Analysis (CFA) supported the four-factor structure of the SCCI. The findings suggest that the SCCI is an effective measure of career-construction behaviors among Chinese secondary school students. The second study evaluated the applicability of the career construction model of adaptation (CCMA). The model was empirically tested using the validated SCCI. The results of the serial mediation analysis confirmed that adaptive readiness indirectly influences adaptability resources, adapting responses, and adaptation results in the CCMA model. [ABSTRACT FROM AUTHOR]

Progress in satellite technology places higher expectations on the design period and reliability of thermal control systems, especially for small satellites with high intensification. Here, a thermal analysis is conducted throughout the satellite development process, with thermal modeling serving as the foundation for thermal analysis in the early and formal design and test verification stages. As a result, designers are required to appreciate, penetrate, and properly apply thermal models for the development of satellite thermal systems. Thus, in this article, we reviewed the research and development of thermal model techniques, as well as the preparation of crucial parameters and means of simplification for accurate and fast solutions. In addition, a summary of the relevant application and state-of-the-art technologies such as uncertainty and sensitivity analysis, intelligent optimization design, and parameter correlation, was dedicated to promoting the comprehensive development and innovation of thermal analysis of satellites. [ABSTRACT FROM AUTHOR]

In the dense-medium coal preparation process magnetite powder is used, however, due to poor recovery of the magnetite, the consumption of magnetite increases which ultimately reflects in the economics. In order to continuously and efficiently recover the magnetite, a novel three-phase conical magnetic separator based on the principle of an alternating magnetic field generated by a three-phase linear motor, was developed. The distribution law of the magnetic field in the separation chamber was studied, and the magnetic separator's basic structure and parameters were determined. By varying the feed rate, coil current, coil turns, and particle size, magnetic separation experiments were conducted and compared with traditional magnetic separators. The results confirmed the excellent sorting performance of the conical AC magnetic separator. [ABSTRACT FROM AUTHOR]

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultrasonography technician who is likely unavailable at the point of injury where resources are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics platform. The ability of four probe adapter technologies to precisely capture images at anatomical locations, repeatedly, and with different ultrasound transducer types were evaluated across more than five scoring criteria. Testing demonstrated two of the adapters outperformed the traditional robot gripper and manual image capture, with a compact, rotating design compatible with wireless imaging technology being most suitable for use at the point of injury. Next steps will integrate the robotic platform with computer vision and deep learning image interpretation models to automate image capture and diagnosis. This will lower the skill threshold needed for medical imaging-based triage, enabling this procedure to be available at or near the point of injury. [ABSTRACT FROM AUTHOR]

Key digested message This article examines the expansive growth of ChatGPT and the implications for large-scale test design. The authors contend that the impressive test simulation results observed by Chat-GPT undergird ongoing construct validity concerns with student testing. In order to address these challenges, a set of strategies is proposed that emphasises authentic assessment, the importance of human elements in traditional paper-and-pencil questions, and the controversial issue of the stakes ascribed to test results. Collectively, these approaches are meant to help test developers more carefully consider existing limitations within traditional standardised and large-scale assessment programs. Ultimately, test design reforms that enhance validity are increasingly needed to address the challenges posed by AI applications. [ABSTRACT FROM AUTHOR]