bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of mindful acceptance and lucid dreaming in nightmare frequency and distress
Authors: Tzioridou Sofia , Dresler Martin , Sandberg Kristian , Mueller Erik M. 
Published: September 2022

AbstractA theoretical and empirical association between lucid dreaming and mindfulness, as well as lucid dreaming and nightmares has previously been observed; however, the relationship between nightmares and mindfulness has received surprisingly little attention. Here, we present the findings of two studies exploring the relation of nightmare frequency and distress with two components of mindfulness, termed presence and acceptance, as well as lucid dreaming. Study 1 (N = 338) consisted of a low percentage of frequent lucid dreamers whereas Study 2 (N = 187) consisted primarily of frequent lucid dreamers that used lucid dream induction training techniques and meditation. Across studies, nightmare-related variables showed a more robust association with mindful acceptance as opposed to mindful presence. Moreover, individuals with high levels of meditation expertise and practice of lucid dreaming induction techniques reported lower nightmare frequency. Finally, in Study 2, which consisted of frequent lucid dreamers, a positive correlation between lucid dreaming frequency and mindfulness was apparent. The present findings support the notion that wakeful mindfulness is associated with the quality of dreams and extend previous research by suggesting a disentangled role of the two facets of mindfulness in dream variation. This association remains open for experimental manipulation, the result of which could have clinical implications.
Development and application of an environment monitoring system based on IPv6
Authors: Li Xiuhong , Hao Xuejie , Yin Lizeyan , Ma Yushuang , Sun Meiying , Yang Rongjin 
Published: September 2022

AbstractThe widespread use of the Internet of Things (Iot) makes it possible to connect everything but having enough IP addresses is a fundamental requirement of this paradigm. All previous environmental monitoring systems in China are based on IPv4. In combination with the characteristics and requirements of China's atmospheric environment monitoring system, this paper develops a monitoring system based on IPv6 technology. Users can directly access the monitoring equipment through the IPv6 website to view data and configure operations. This paper first introduces the design and implementation of the software and hardware of the system, then introduces the simplification of IPv6 protocol, the transplantation of IPv6 protocol on ARM and the design and implementation of embedded Web server system. The experimental results show that the developed atmospheric environment monitoring system can realize continuous data acquisition based on IPv6 and provide data-driven support for environmental protection management and decision-making.
Developing a hybrid time-series artificial intelligence model to forecast energy use in buildings
Authors: Ngo Ngoc-Tri , Pham Anh-Duc , Truong Thi Thu Ha , Truong Ngoc-Son , Huynh Nhat-To 
Published: September 2022

AbstractThe development of a reliable energy use prediction model is still difficult due to the inherent complex pattern of energy use data. There are few studies developing a prediction model for the one-day-ahead energy use prediction in buildings and optimizing the hyperparameters of a prediction model is necessary. This study aimed to propose a hybrid artificial intelligence model for forecasting one-day ahead time-series energy consumption in buildings. The proposed model was developed based on the integration of the Seasonal Autoregressive integrated Moving average, the Firefly-inspired Optimization algorithm, and the support vector Regression (SAMFOR). A large dataset of energy consumption in 30-min intervals, temporal data, and weather data from six real-world buildings in Vietnam was used to train and test the model. Sensitivity analyses were performed to identify appropriate model inputs. Comparison results show that the SAMFOR model was more effective than the others such as the seasonal autoregressive integrated moving average (SARIMA) and support vector regression (SVR), SARIMA-SVR, and random forests (RF) models. Evaluation results on real-world building depicted that the proposed SAMFOR model achieved the highest accuracy with the root-mean-square error (RMSE) of 1.77 kWh in, mean absolute percentage error (MAPE) of 9.56%, and correlation coefficient (R) of 0.914. The comparison results confirmed that the SAMFOR model was effective for forecasting one-day-ahead energy consumption. The study contributes to (1) the knowledge domain by proposing the hybrid SAMFOR model for forecasting energy consumption in buildings; and (2) the state of practice by providing building managers or users with a powerful tool for analyzing and improving building energy performance.
MISPR: an open-source package for high-throughput multiscale molecular simulations
Authors: Atwi Rasha , Bliss Matthew , Makeev Maxim , Rajput Nav Nidhi 
Published: September 2022

AbstractComputational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.
Assessment of video see-through smart glasses for augmented reality to support technicians during milking machine maintenance
Authors: Sara Gabriele , Todde Giuseppe , Caria Maria 
Published: September 2022

AbstractSmart glasses for augmented reality are digital technology under investigation in the agricultural sector. The potential of augmented reality was underlined, in some scientific contributions, as a support tool for farmers' activities and for the decision-making process. One of the most practical applications studied for augmented reality was in maintenance operations, where the use of smart glasses showed high capability. This work focuses on the evaluation of the performance and applicability of smart glasses with a video see-through display system and testing the device's available functions in agricultural frameworks. In addition, an augmented assistance scenario describing the main steps involved in the functioning of the maintenance operation was developed for milking machine inspection. The audio–video quality, battery life, detection capabilities of markers, and voice control interaction system were evaluated. The results showed the capabilities of smart glasses to reach augmented information from a long distance in a short time interval and to transmit audio and video with a high level of detail, allowing discrimination of small objects during remote assistance with reduced delay. The built maintenance scenario represents an example of augmented reality digital assistance application in the inspection and maintenance of the milking machine. The device performance and the proposed maintenance scenario underline the potential that augmented reality could have in the agricultural sector to assist and guide both farmers and technicians to timely problem solving. This solution fits into the agriculture 4.0 perspective, which is increasingly focused on digital transformation to improve farms’ efficiency and sustainability.
3D optical illusion as visualisation tools in spatial planning and development
Authors: Kaźmierczak Rafał , Szczepańska Agnieszka 
Published: September 2022

AbstractSpatial planning and development use various visualisation methods. Technological advancements in visualisation techniques have allowed imaging to shift from 2 to 3D dimensions. 3D optical illusion, which converts information recorded in the digital form into a three-dimensional presentation, can be a new tool for presenting spatial development solutions. Since a optical illusion is a direct spatial presentation, it requires neither specialist preparation nor spatial imagination. For this reason, it can become an effective means of visual communication with the public in the area of spatial planning and development. This article shows an example of the imaging of a model element of spatial development (a building) using the 3D illusion technique. Collected opinions of the test group of viewers confirm the usefulness of this tool. The presented 3D visualisation effect evoked positive reactions among the viewers. The use of the hologram technique in spatial planning and development appears to be justified and is an interesting research trend.
A hybrid data-driven solution to facilitate safe mud window prediction
Authors: Gowida Ahmed , Ibrahim Ahmed Farid , Elkatatny Salaheldin 
Published: September 2022

AbstractSafe mud window (SMW) defines the allowable limits of the mud weights that can be used while drilling O&G wells. Controlling the mud weight within the SMW limits would help avoid many serious problems such as wellbore instability issues, loss of circulation, etc. SMW can be defined by the minimum mud weight below which shear failure (breakout) may occur (MWBO) and the maximum mud weight above which tensile failure (breakdown) may occur (MWBD). These limits can be determined from the geomechanical analysis of downhole formations. However, such analysis is not always accessible for most drilled wells. Therefore, in this study, a new approach is introduced to develop a new data-driven model to estimate the safe mud weight range in no time and without additional cost. New models were developed using an artificial neural network (ANN) to estimate both MWBO and MWBD directly from the logging data that are usually available for most wells. The ANN-based models were trained using actual data from a Middle Eastern field before being tested by an unseen dataset. The models achieved high accuracy exceeding 92% upon comparing the predicted and observed output values. Additionally, new equations were established based on the optimized ANN models’ weights and biases whereby both MWBO and MWBD can be calculated without the need for any complicated codes. Finally, another dataset from the same field was then used to validate the new equations and the results demonstrated the high robustness of the new equations to estimate MWBO and MWBD with a low mean absolute percentage error of 0.60% at maximum. So, unlike the costly conventional approaches, the newly developed equations would facilitate determining the SMW limits in a timely and economically effective way, with high accuracy whenever the logging data are available.
Speech-Evoked Envelope Following Responses in Children and Adults
Authors: Easwar Vijayalakshmi , Purcell David , Lasarev Michael , McGrath Emma , Galloy Mary 
Published: September 2022

Purpose:
Envelope following responses (EFRs) could be useful for objectively evaluating audibility of speech in children who are unable to participate in routine clinical tests. However, relative to adults, the characteristics of EFRs elicited by frequency-specific speech and their utility in predicting audibility in children are unknown.

Method:
EFRs were elicited by the first (F1) and second and higher formants (F2+) of male-spoken vowels /u/ and /i/ and by fricatives /ʃ/ and /s/ in the token /suʃi/ presented at 15, 35, 55, 65, and 75 dB SPL. The F1, F2+, and fricatives were low-, mid-, and high-frequency dominant, respectively. EFRs were recorded between the vertex and the nape from twenty-three 6- to 17-year-old children and 21 young adults with normal hearing. Sensation levels of stimuli were estimated based on behavioral thresholds.

Results:
In children, amplitude decreased with age for /ʃ/-elicited EFRs but remained stable for low- and mid-frequency stimuli. As a group, EFR amplitude and phase coherence did not differ from that of adults. EFR sensitivity (proportion of audible stimuli detected) and specificity (proportion of inaudible stimuli not detected) did not vary between children and adults. Consistent with previous work, EFR sensitivity increased with stimulus frequency and level. The type of statistical indicator used for EFR detection did not influence accuracy in children.

Conclusions:
Adultlike EFRs in 6- to 17-year-old typically developing children suggest mature envelope encoding for low- and mid-frequency stimuli. EFR sensitivity and specificity in children, when considering a wide range of stimulus levels and audibility, are ~77% and ~92%, respectively.

Supplemental Material:

https://doi.org/10.23641/asha.21136171
Low complexity duty cycle modulation model predictive current control of permanent magnet synchronous motor
Authors: Yu Deliang , Zhang Chuanchang , Guo Qingbo , Zhou Minghao 
Published: September 2022

AbstractThis study proposes a model predictive current control algorithm for the synchronous permanent magnet motor with low complexity duty cycle modulation. Three single‐phase voltage vectors are simulated to synthesize the target voltage vector that enables the current to achieve deadbeat control. The algorithm can change the amplitude and direction of the synthesized vector and extend the selection range of the synthesized vector to the whole hexagonal region. That is to say, this method can realize the deadbeat control of the d‐axis and q‐axis currents, and reduce the current pulsation. Moreover, this method only needs one action time operation, which can directly convert the action time of the voltage vector into a three‐phase duty cycle after equivalent processing and over‐modulation of the action time of the voltage vector. It is not necessary to traverse multiple sectors for optimization, which simplifies the modulation method and reduces the computational complexity. The effectiveness and reliability of the proposed method are verified by theoretical derivation and experimental results.
Fast diagnosis strategy for open‐circuit fault of switch devices in open‐winding PMSM system based on voltage error estimation
Authors: Yuan Guofeng , Zhang Chenguang , Zhang Xiaoguang , Xu Chi 
Published: September 2022

AbstractIn the dual inverter topology of open‐winding permanent magnet synchronous motor system, due to the symmetry of the topology, switch devices have high similarity in working characteristics, which undoubtedly increases the difficulty in locating faulty devices. In this paper, by analysing the difference of inverter output characteristics before and after switch devices open‐circuit fault, the relationship between the inverter output voltage error and fault location is found, and a fault diagnosis strategy is proposed. In this strategy, a construction method of fault phase characteristic current and the estimation equation of inverter output‐voltage error are designed. Then, the real‐time diagnosis of single device fault and two devices with the same characteristics fault at the same time is realized. Since the strategy proposed in this paper does not need additional voltage sensors, it has the same applicability as the traditional current method. In addition, the diagnosis method based on voltage information reduces the diagnosis time. Besides, this method is independent of the PWM strategy and is not sensitive to the phenomena of dead time and delayed insulated gate bipolar transistors switching. Finally, experimental results demonstrate the effectiveness of the proposed fault diagnosis strategy.
Wind power forecast based on broad learning system and simplified long short term memory network
Authors: Han Li , Li Mengjie , Wang Xiaojing , Lu Panpan 
Published: September 2022

AbstractDue to its strong randomness and volatility, the modes of wind power are complex. After decomposing wind power time series into three subseries, the complex modes are deconstructed and each subseries maintain unique characteristics. Aiming at the characteristics of each subseries, a wind power forecast method based on Broad Learning System (BLS) and Simplified Long Short Term Memory (SLSTM) is proposed. Firstly, the decomposed subseries is analysed. The first layer subseries reflects the main amplitude changes caused by ramp events and the second represents the local fluctuations accompanying ramp events. Due to the randomness of ramp events, new modes appear frequently in the two subseries. The third layer subseries consists of continuous irregular jitter. Then, the BLS is introduced to forecast the first and second layer subseries. By adjusting its structure dynamically, various modes of ramp events can be learned from amplitude change and accompanying fluctuation. Additionally, according to the characteristics of the third layer subseries, continuous jitter needn't be transmitted in long‐term memory. Setting the forget gate to 0, SLSTM is proposed to forecast the third layer subseries. Finally, the wind power data from the Belgian ELIA website is used to verify the superiority of the proposed method.
Satellite shadows through stellar occultations
Authors: Groot Paul J. 
Published: September 2022

Aims. The impact of mega-constellations of satellites in low-Earth orbit during nighttime optical observations is assessed.
Methods. Orbital geometry is used to calculate the impact of stellar occultations by satellites on the photometry of individual stars as well as the effect on the photometric calibration of wide-field observations.
Results. Starlink-type satellites will have occultation disks several arcseconds across. Together with occultation crossing times of 0.1−100 ms, this will lead to photometric ‘jitter’ on the flux determination of stars. The level of impact for a given star depends on the ratio of the integration time of the frame over the occultation crossing time. In current-day CCD-based synoptic surveys, this impact is negligible (≪1%), but with future CMOS-based wide-field surveys obtaining data at frequencies >1 Hz, the impact will grow towards complete dropouts. At integration times similar to the occultation crossing time, the orbit of a satellite can be traced using the occultation method. At even shorter integration times, the shape of the occulting satellite can be deduced.
Conclusions. Stellar occultations by passing satellites, enabled by high-speed CMOS technology, will be a new method for studying orbiting satellites. Large-scale monitoring programs will be needed to independently determine and update the orbits of satellites.
Uncovering Discrepancies in IV Vancomycin Infusion Records between Pump Logs and EHR Documentation
Authors: Tung Tsan-Hua , DeLaurentis Poching , Yih Yuehwern 
Published: September 2022

Abstract
Background Infusion start time, completion time, and interruptions are the key data points needed in both area under the concentration–time curve (AUC)- and trough-based vancomycin therapeutic drug monitoring (TDM). However, little is known about the accuracy of documented times of drug infusions compared with automated recorded events in the infusion pump system. A traditional approach of direct observations of infusion practice is resource intensive and impractical to scale. We need a new methodology to leverage the infusion pump event logs to understand the prevalence of timestamp discrepancies as documented in the electronic health records (EHRs).
Objectives We aimed to analyze timestamp discrepancies between EHR documentation (the information used for clinical decision making) and pump event logs (actual administration process) for vancomycin treatment as it may lead to suboptimal data used for therapeutic decisions.
Methods We used process mining to study the conformance between pump event logs and EHR data for a single hospital in the United States from July to December 2016. An algorithm was developed to link records belonging to the same infusions. We analyzed discrepancies in infusion start time, completion time, and interruptions.
Results Of the 1,858 infusions, 19.1% had infusion start time discrepancy more than ± 10 minutes. Of the 487 infusion interruptions, 2.5% lasted for more than 20 minutes before the infusion resumed. 24.2% (312 of 1,287) of 1-hour infusions and 32% (114 of 359) of 2-hour infusions had over 10-minute completion time discrepancy. We believe those discrepancies are inherent part of the current EHR documentation process commonly found in hospitals, not unique to the care facility under study.
Conclusion We demonstrated pump event logs and EHR data can be utilized to study time discrepancies in infusion administration at scale. Such discrepancy should be further investigated at different hospitals to address the prevalence of the problem and improvement effort.