bluuebunny/crossref_metadata_2025 huggingface dataset:
Chinese English as a Foreign Language Teachers’ Immunity and Mindfulness as Predictors of Their Work Engagement
Authors: Li Shengji
Published: April 2022

Considering the significant contribution of teachers’ professional triumph in the prosperity of students, the current study aims to investigate the existence of any relationship among three factors influencing teachers’ success: immunity, mindfulness, and engagement. Furthermore, we attempt to investigate whether English as a foreign language (EFL) teachers’ immunity and mindfulness can predict their work engagement. To this end, a Likert-scale questionnaire including items on teacher immunity, mindfulness, and work engagement was distributed to 582 EFL teachers in China through the WeChat application by employing a convenient sampling. To analyze the collected data, the Spearman Rho correlation index and linear multiple regression analysis are employed. The findings are that there does exist an indication of a direct relationship among EFL teachers’ immunity, mindfulness, and work engagement. Also, it is found that immunity and mindfulness can predict EFL teachers’ work engagement. The current study’s findings support the necessity of training language teachers to cope with the EFL context adversities.
The Impact of Language Diversity on Knowledge Sharing Within International University Research Teams: Evidence From TED Project
Authors: Canestrino Rossella , Magliocca Pierpaolo , Li Yang
Published: April 2022

In today’s knowledge economy, knowledge and knowledge sharing are fundamental for organizations to achieve competitiveness and for individuals to strengthen their innovation capabilities. Knowledge sharing is a complex language-based activity; language affects how individuals communicate and relate. The growth in international collaborations and the increasing number of diverse teams affect knowledge sharing because individuals engage in daily knowledge activities in a language they are not native speakers. Understanding the challenges they face, and how they manage the emerging difficulties is the main aim of this manuscript. For this purpose, an explorative case study was conducted in an international university research project, namely the TED project. Both interviews and direct observations were employed to understand the phenomenon better and deliberately triangulate data and improve validity. Results show that non-native language use determines the emergence of different language proficiency, depending on the nature of the knowledge domain–job-related vs. non-job-related. Within non-job-related knowledge domains, the lack of linguistic abilities, summed to the perceived cultural diversities, mainly affects people’s propensity to engage in personal and more intense social relationships. Under such circumstances, tacit knowledge sharing is reduced with negative consequences on the project’s long-term innovative performance. Since the project is still running, detecting language challenges will allow the partners to design and apply effective measures to support cooperation with language and cultural barriers. Among them,code switching, adopted by “bridge” actors, already emerges as tool supporting communication and knowledge exchange.
Effect of -NBOMe Compounds on Sensorimotor, Motor, and Prepulse Inhibition Responses in Mice in Comparison With the 2C Analogs and Lysergic Acid Diethylamide: From Preclinical Evidence to Forensic Implication in Driving Under the Influence of Drugs
Authors: Tirri Micaela , Bilel Sabrine , Arfè Raffaella , Corli Giorgia , Marchetti Beatrice , Bernardi Tatiana , Boccuto Federica , Serpelloni Giovanni , Botrè Francesco , De-Giorgio Fabio , Golembiowska Krystyna , Marti Matteo
Published: April 2022

In the last decade, the market for new psychoactive substances has been enriched by numerous psychedelic phenethylamines, which mimic the psychoactive effect of lysergic acid diethylamide (LSD). In particular, the -NBOMe series, which are more potent than their 2C compounds analogs, are considered worthy substitutes for LSD by users. The purpose of this study was to assess the effects of 25H-NBOMe and its halogenated derivatives (25I-NBOMe and 25B-NBOMe) in comparison to their 2C compounds analogs and LSD on the sensorimotor (visual, acoustic, and overall tactile), reaction time, spontaneous (total distance traveled) and stimulated (drag, accelerod test) motor activity, grip strength test, and prepulse inhibition (PPI) responses in mice. Systemic administration of -NBOMe, 2C compounds analogs, and LSD (0.001–10 mg/kg) differently impaired the sensorimotor, reaction time, motor, and PPI responses in mice. In particular, halogenated (25I and 25B)-NBOMe derivatives appear to be more effective than the entire class of 2C compounds analogs in altering visual and acoustic responses, affecting reaction time, and motor and sensory gating in PPI test. In fact, the specific rank order of compounds potency for nearly all of the experiments showed that (25I and 25B)-NBOMe were more potent than 2C compounds analogs and LSD. -NBOMe and 2C compounds analogs impaired not only the reception of incoming sensory stimuli (visual and acoustic), but their correct brain processing (PPI) in an equal and sometimes stronger way than LSD. This sensory impairment directly affected the spontaneous motor response and reaction time of mice, with no change in performance in stimulated motor activity tests. These aspects should be carefully considered to better understand the potential danger that psychedelic phenethylamines, in particular -NBOMe, may pose to public health, with particular reference to decreased performance in driving and hazardous works that require special sensorimotor skills.
Guidelines for Treatment of Umbilical and Epigastric Hernias From the European and Americas Hernia Societies–A Web-Based Survey on Surgeons’ Opinion
Authors: Henriksen N. A. , Nazari T. , Simons M. P. , Hope W. , Montgomery A.
Published: April 2022

Background and aims: The European and Americas Hernia Society’s (EHS and AHS) Guidelines on the treatment of primary midline ventral hernias were launched to guide surgeons. As a part of a dissemination plan of the guideline, this study aimed to evaluate the level of consensus between recommendations and the current surgical practices of EHS and AHS members before implementation.

Material and methods: A questionnaire was constructed including questions on the current practice of the members and nine selected key recommendations from the guidelines. An on-stage consensus voting was performed at the EHS Congress in Hamburg 2019 followed by a SurveyMonkey sent to all EHS and AHS members. Consensus with a recommendation was defined as an agreement of ≥70%.

Results: A total of 178 votes were collected in Hamburg. A further 499/1,754 (28.4%) of EHS and 150/1,100 (13.6%) of AHS members participated in the SurveyMonkey. A consensus was reached for 7/9 (78%) of the recommendations. The two recommendations that did not reach consensus were on indication and the technique used for laparoscopic repair. In current practice, more AHS participants used a preformed patch; 50.7% (76/150) compared with EHS participants 32.1% (160/499), p < 0.001.

Conclusion: A consensus was achieved for most recommendations given by the new guideline for the treatment of umbilical and epigastric hernias. Recommendations that did not reach consensus were on indication and technique for laparoscopic repair, which may reflect the lack of evidence on these topics.
Implementation and Validation of a Novel and Inexpensive Training Model for Laparoscopic Inguinal Hernia Repair
Authors: Hanssen Andres , Hanssen Diego A. , Hanssen Rafael A. , Plotnikov Sergio , Haddad Jose , Daes Jorge E.
Published: April 2022

Purpose: The aim of this study was to develop and validate a reproducible low-cost model useful for the development and acquisition of skills and competencies required for endoscopic hernia repairs.

Methods: Ten general surgery residents (PGY3) were instructed to construct the model and perform the maneuvers necessary for the simulation of laparoscopic inguinal hernioplasty by the trans-abdominal pre-peritoneal (TAPP) technique. They practiced for 4 weeks in the model, and the time required to perform simulated hernioplasty by the laparoscopic TAPP technique in the initial session was compared to the time required after 4 weeks of training.

Results: The time required to perform the exercise was significantly lower than in the initial session (p < 0.01). The time required by residents to complete the exercise in the initial session was significantly longer than that used by expert surgeons in the same task (p < 0.01), and although a significant difference persisted, this difference was substantially reduced to 3.60 min after the residents completed 4-week training in the model (p < 0.01). An independent expert, blinded to the level of training of the person who performed the exercise, could recognize all residents as novices and all experienced surgeons as experts in the initial session of the exercise with the model, but after 4 weeks of training, they did not recognize 4 of the 10 residents as novices (p < 0.05).

Conclusion: The routine implementation of training in this model could be very useful in the laparoscopic inguinal hernioplasty teaching-learning process.
Hysteresis Modeling and Compensation of Piezoelectric Actuators Using Gaussian Process with High-Dimensional Input
Authors: Meng Yixuan , Wang Xiangyuan , Li Linlin , Huang Weiwei , Zhu Limin
Published: April 2022

Rate-dependent hysteresis seriously deteriorates the positioning accuracy of the piezoelectric actuators, especially when tracking high-frequency signals. As a widely-used nonparametric Bayesian method, the Gaussian process (GP) has proven its effectiveness in nonlinear hysteresis modeling. In this paper, the dimension of the input to the GP model is extended to consider more dynamic features of the tracking signal so as to improve the rate-dependent hysteresis modeling accuracy. In contrast with the traditional training set containing only the position and speed information, the acceleration and jerk information, as well as their temporal distribution information, is also included in the input of the model. An inverse hysteresis compensator (IHC) is established in the same way, and open-loop and closed-loop controllers are developed by using the IHC. Experimental results on a PEA stage show that with the increase in the input dimension, the hysteresis modeling accuracy improves greatly and, thus, the controllers based on IHC can achieve a better tracking performance.
Impact of Soil Characteristics and Weed Management Practices on Glyphosate and AMPA Persistence in Field Crops Soils from the St. Lawrence Lowlands (Quebec, Canada)
Authors: Maccario Sophie , Lucotte Marc , Moingt Matthieu , Samson-Brais Émile , Smedbol Élise , Labrecque Michel
Published: April 2022

The use of glyphosate-based herbicides (GBHs) in industrial agriculture has intensified in the past decades, causing a growing concern about the occurrence and spatial distribution of glyphosate and its principal metabolite, aminomethylphosphonic acid (AMPA), in the environment. In 2014, glyphosate and AMPA content was measured in 45 soils from the St. Lawrence Lowlands (Quebec, Canada) before seeding and at harvest in soybean field crops using various weed management practices with or without GBH applications. At the same time, a recent history of agricultural practices and soil conditions was compiled for the sampled sites. The results of the study show that 91% of the samples contained detectable amount of either glyphosate or AMPA, with maximum values of 0.47 mg·kg−1 and 1.16 mg·kg−1 for glyphosate and AMPA, respectively. Surprisingly, detectable amounts of AMPA were measured in fields not treated with GBHs in 2014, whereas traces of both glyphosate and AMPA were detected in organic field crops, highlighting the potential spreading and/or persistence of both compounds in the environment. Glyphosate content was significantly higher in clay soils rich in exchangeable cations, such as Mg2+, K+ and Ca2+, which can contribute to the retention of glyphosate in soil via complexation processes.
How Can We Do Citizen Science Better? A Case Study Evaluating Grizzly Bear Citizen Science Using Principles of Good Practice in Alberta, Canada
Authors: Hughes Courtney , Tremblett Krista , Kummer Justine , Lee Tracy S. , Duke Danah
Published: April 2022

Citizen science offers an excellent opportunity to engage the public in scientific data collection, educational opportunities, and applied management. However, the practicalities of developing and implementing citizen science programming are often more complex than considered. Some challenges to effective citizen science include scientists’ skepticism about the ability of public participants to rigorously collect quality data; a lack of clarity on or confidence in the utility of data; scientists’ hesitancy in engaging the public in projects; limited financial commitments; and challenges associated with the temporal and geographic scales of projects. To address these challenges, and provide a foundation upon which practitioners, scientists, and the public can credibly engage in citizen science, the Government of Alberta developed a set of citizen science principles. These principles offer a framework for planning, designing, implementing, and evaluating citizen science projects that extend beyond Alberta. Here, we present a case study using these principles to evaluate GrizzTracker, a citizen science program developed to help inform provincial species-at-risk recovery efforts. While we found that GrizzTracker applied each of the six principles in some way, including successful public engagement, strengthened relationships, and raising public awareness about northwest Alberta’s grizzly bears, we also identified a number of challenges. These included ongoing skepticism from the traditional scientific community about the utility of citizen science and governance challenges related to program leadership, staff capacity, and funding. By using the principles as a guideline, we provide policy recommendations for future citizen science efforts, including considerations for program design, implementation, and evaluation.
Fatty Acids Composition of Stomach Oil of Scopoli’s Shearwater (Calonectris diomedea) from Linosa’s Colony
Authors: Galluzzo Francesco Giuseppe , Cumbo Valentina , Cammilleri Gaetano , Calabrese Vittorio , Pulvirenti Andrea , Cicero Nicola , Pantano Licia , Mascetti Antonietta , Lo Cascio Giovanni , Bacchi Emanuela , Macaluso Andrea , Vella Antonio , Seminara Salvatore , Ferrantelli Vincenzo
Published: April 2022

Calonectris diomedea is a Procellariforms seabird having a very representative colony in Linosa Island (Southern Italy). The adult forms of C. diomedea produce a pasty oil from their proventriculus to feed their chicks during the rearing period. In this work, we examined the fatty acids composition of the stomach oil of C. diomedea from Linosa Island by gas chromatography with flame ionization detection (GC-FID). The samples were collected at 20 and 70 days after hatching. Twenty different fatty acids (FAs) were identified. Saturated fatty acids (SFA) were the most abundant in percentage (41.6%) at day 20 followed by polyunsaturated fatty acids (PUFA, 38.7%) and monounsaturated fatty acids (MUFA, 19.7%). MUFAs were the most abundant in samples collected at day 70 (53.8%), followed by SFAs (36.6%) and PUFAs (9.8%). Oleic acid (C18:1ω9) in the samples on day 70 was 4 times higher than that in the samples on day 20. The Principal Component Analysis (PCA) verified a clear separation of the stomach oil samples in two groups, according to the day of sampling. The results obtained confirm the role of FAs analysis of stomach oil to understand the ecology and breeding behaviour of C. diomedea, highlighting a resemblance with signatures recorded in marine organisms of Linosa Island.
Suppression of Harmonic Current in Magnetic Bearing–Rotor System with Redundant Structure
Authors: Cheng Baixin , Cheng Xin , Song Shao , Zhou Rougang , Deng Shuai
Published: April 2022

The magnetic bearing–rotor system has the advantages of no mechanical friction and active vibration control. A magnetic bearing with redundant structures provides an effective method to apply fault-tolerant control to the magnetic bearing–rotor system. In this paper, in order to improve the robustness of a rotor suspended by a magnetic bearing with redundant structures, the harmonic current suppression approach is proposed. Firstly, the generation mechanism of harmonic current in the magnetic bearing–rotor system is analyzed. Secondly, on the basis of the current distribution theory of magnetic bearing with redundant structures, the linearization model of electromagnetic force is established. Then, the eight-pole symmetrical radial magnetic bearing is taken as the research object, and the control system model with a multi-excitation disturbance source is established under the condition of no coil failure. Lastly, considering the periodicity of disturbance signals, a repetitive controller that is suitable for magnetic bearing with redundant structures is proposed in this paper, Moreover, in order to verify the effectiveness of the proposed control strategy, we inserted the repetitive controller into the original controller applied to the magnetically levitated rotor with redundant structures, and the corresponding simulation was carried out. The results demonstrate that the repetitive control method proposed in this paper can effectively suppress the harmonic current and improve the suspension accuracy of the rotor supported by the magnetic bearing with redundant structures.
Influence of Vegetation Filter Strip on Slope Runoff, Sediment Yield and Nutrient Loss
Authors: Zhang Huayong , Meng Qiang , You Qinjing , Huang Tousheng , Zhang Xiumin
Published: April 2022

It is an important branch of erosion research to control soil erosion on eroded gullies and slopes by using vegetation filter strip. Several simulated rainfall experiments were carried out in soil tanks filled with loess sandy loam taken from a typical eroded gully area with less vegetation coverage in Yanghe hilly basin in Xuanhua District, Zhangjiakou City, Hebei Province. The soil and water conservation effects of two different vegetation setting modes were compared under the same vegetation strip width and different rainfall intensities and slopes. During the rainfall process, the changes of runoff and sediment yield and nutrient loss were not stable, but the same erosion index had similar variation trends under different combinations of rainfall intensity, slope and vegetation coverage. Multiple regression results showed that runoff and sediment production in eroded gully can be effectively reduced through vegetation filter strips, which are jointly affected by rainfall intensity and slope. There was no significant difference in the amount of runoff and sediment yield between the two vegetation setting modes. Rainfall intensity and slope gradient showed different strengths of impact on nutrient loss. Through cluster analysis, the results showed that the impacts of rainfall intensity, slope gradient and vegetation setting modes on soil and water loss on slope can be equal or offset. In general, setting vegetation filter strips can offset the effects of rainfall intensity and slope, but vegetation regulation of erosion was not obvious under extreme rainfall and steep slope conditions. What’s more, rainfall intensity had a dominant effect on erosion. The results in this research may provide reference for practical application of vegetation filter strips on eroded slopes.
Multi-Scale Factor Image Super-Resolution Algorithm with Information Distillation Network
Authors: Cheng Yu , Chen Shuai , Liao Zeyu , Zhou Niujun
Published: April 2022

Deep convolutional neural networks with strong expressive ability have achieved impressive performances in single-image super-resolution algorithms. However, excessive convolutions usually consume high computational cost, which limits the application of super-resolution technology in low computing power devices. Besides, super-resolution of arbitrary scale factor has been ignored for a long time. Most previous researchers have trained a specific network model separately for each factor, and taken the super-resolution of several integer scale factors into consideration. In this paper, we put forward a multi-scale factor network (MFN), which dynamically predicts the weights of the upscale filter by taking the scale factor as input, and generates HR images with corresponding scale factors from the weights. This method is suitable for arbitrary scale factors (integer or non-integer). In addition, we use an information distillation structure to gradually extract multi-scale spatial features. Extensive experiments suggest that the proposed method performs favorably against the state-of-the-art SR algorithms in term of visual quality, PSNR/SSIM evaluation indicators, and model parameters.
Wireless Lan Performance Enhancement Using Double Deep Q-Networks
Authors: Asaf Khizra , Khan Bilal , Kim Ga-Young
Published: April 2022

Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access Control) protocol was not specially designed. Although 802.11ax aims to improve Wi-Fi performance in dense scenarios due to modifications in the physical layer (PHY), however, MAC layer operations remain unchanged, and are not capable enough to provide stable performance in dense scenarios. Potential applications of Deep Learning (DL) to Media Access Control (MAC) layer of WLAN has now been recognized due to their unique features. Deep Reinforcement Learning (DRL) is a technique focused on behavioral sensitivity and control philosophy. In this paper, we have proposed an algorithm for setting optimal contention window (CW) under different network conditions called DRL-based Contention Window Optimization (DCWO). The proposed algorithm operates in three steps. In the initial step, Wi-Fi is being controlled by the 802.11 standards. In the second step, the agent makes the decisions concerning the value of CW after the TRAIN procedure for the proposed algorithm. The final phase begins after the training, defined by a time duration specified by the user. Now, the agent is fully trained, and no updates will be no longer received. Now the CW is updated via the OPTIMIZE process of DCWO. We have selected total network throughput, instantaneous network throughput, fairness index, and cumulative reward, and compared our proposed scheme DCWO with the Centralized Contention window Optimization with DRL (CCOD). Simulation results show that DCWO with Double Deep Q-Networks (DDQN) performs better than CCOD with (i) Deep Deterministic Policy Gradient (DDPG) and (ii) Deep Q-Network (DQN). More specifically, DCWO with DDQN gives on average 28% and 23% higher network throughput than CCOD in static and dynamic scenarios. Whereas in terms of instantaneous network throughput DCWO gives around 10% better results than the CCOD. DCWO achieves almost near to optimal fairness in static scenarios and better than DQN and DDPG with CCOD in dynamic scenarios. Similarly, while the cumulative reward achieved by DCWO is almost the same with CCOD with DDPG, the uptrend of DCWO is still encouraging.
Model Predictive Traffic Control by Bi-Level Optimization
Authors: Stoilova Krasimira , Stoilov Todor
Published: April 2022

A bi-level model for traffic signal optimization is developed. The model predictive framework is applied for traffic control in an urban traffic network. The potential of the bi-level formalization is used to increase the space of control influences with simultaneous evaluation of the green light and cycle durations. Thus, the increased control space allows more traffic parameters to be considered, such as vehicles queues and traffic flows. A particular modification of the bi-level control is applied for the synchronization of the traffic lights in the network. The model predictive approach is used for the real-time management of the traffic in the network. The control implementations are constrained by the shortest evaluated cycle. Thus, a synchronization of the traffic lights is applied for the minimization of the queues and maximization of the outgoing flows from the network. The bi-level model has been numerically tested on a set of intensive crossroads in Sofia. The numerical simulations prove the superiority of the developed bi-level control in comparison with the classical optimization of queue lengths.
Automated Classification of Left Ventricular Hypertrophy on Cardiac MRI
Authors: Budai Adam , Suhai Ferenc Imre , Csorba Kristof , Dohy Zsofia , Szabo Liliana , Merkely Bela , Vago Hajnalka
Published: April 2022

Left ventricular hypertrophy is an independent predictor of coronary artery disease, stroke, and heart failure. Our aim was to detect LVH cardiac magnetic resonance (CMR) scans with automatic methods. We developed an ensemble model based on a three-dimensional version of ResNet. The input of the network included short-axis and long-axis images. We also introduced a standardization methodology to unify the input images for noise reduction. The output of the network is the decision whether the patient has hypertrophy or not. We included 428 patients (mean age: 49 ± 18 years, 262 males) with LVH (346 hypertrophic cardiomyopathy, 45 cardiac amyloidosis, 11 Anderson–Fabry disease, 16 endomyocardial fibrosis, 10 aortic stenosis). Our control group consisted of 234 healthy subjects (mean age: 35 ± 15 years; 126 males) without any known cardiovascular diseases. The developed machine-learning-based model achieved a 92% F1-score and 97% recall on the hold-out dataset, which is comparable to the medical experts. Experiments showed that the standardization method was able to significantly boost the performance of the algorithm. The algorithm could improve the diagnostic accuracy, and it could open a new door to AI applications in CMR.
Multi-Criteria Usability Evaluation of mHealth Applications on Type 2 Diabetes Mellitus Using Two Hybrid MCDM Models: CODAS-FAHP and MOORA-FAHP
Authors: Gupta Kamaldeep , Roy Sharmistha , Poonia Ramesh Chandra , Kumar Raghvendra , Nayak Soumya Ranjan , Altameem Ayman , Saudagar Abdul Khader Jilani
Published: April 2022

People use mHealth applications to help manage and keep track of their health conditions more effectively. With the increase of mHealth applications, it has become more difficult to choose the best applications that are user-friendly and provide user satisfaction. The best techniques for any decision-making challenge are multi-criteria decision-making (MCDM) methodologies. However, traditional MCDM methods cannot provide accurate results in complex situations. Currently, researchers are focusing on the use of hybrid MCDM methods to provide accurate decisions for complex problems. Thus, the authors in this paper proposed two hybrid MCDM methods, CODAS-FAHP and MOORA-FAHP, to assess the usability of the five most familiar mHealth applications that focus on type 2 diabetes mellitus (T2DM), based on ten criteria. The fuzzy Analytic Hierarchy Process (FAHP) is applied for efficient weight estimation by removing the vagueness and ambiguity of expert judgment. The CODAS and MOORA MCDM methods are used to rank the mHealth applications, depending on the usability parameter, and to select the best application. The resulting analysis shows that the ranking from both hybrid models is sufficiently consistent. To assess the proposed framework’s stability and validity, a sensitivity analysis was performed. It showed that the result is consistent with the proposed hybrid model.
Additive Manufacturing Technology for Spare Parts Application: A Systematic Review on Supply Chain Management
Authors: Mecheter Asma , Pokharel Shaligram , Tarlochan Faris
Published: April 2022

Additive manufacturing (AM) is gaining interest among researchers and practitioners in the field of manufacturing. One major potential area of AM application is the manufacturing of spare parts, which affects the availability of the operation and supply chain. The data show that the application and adoption of AM has contributed to a reduction in lead times and inventory, which also contributes to a reduction in holding costs. This paper provides a review of recent work on the application of AM technology specifically for spare parts. The review shows that there are supply chain opportunities and challenges to the adoption of AM in spare parts within various application sectors. Our research reviews both the quantitative and qualitative models used for analysis to meet the emerging needs of the industry. The review also shows that the development of technology and its application is still emerging; therefore, there will be further opportunities to develop better spare parts supply chains to support AM applications. This paper concludes with future research directions.
Effect of Different pH Beverages on the Color Stability of Smart Monochromatic Composite
Authors: Ahmed Muhammad Adeel , Jouhar Rizwan , Vohra Fahim
Published: April 2022

Omnichroma is a smart monochromatic material and is believed to attain the shade of the surrounding tooth structure in which it is placed. However, the color stability of this material is unknown. Therefore, this study was conducted to evaluate the effect of different pH beverages on the color stability of the Omnichroma composite and its comparison with micro-hybrid composite resin. Sixty extracted human maxillary premolars of different shades, viz. A2, A3, B2 and B3, were selected in equal numbers. A Class V cavity was prepared on the buccal and palatal sides of each tooth. After the cavity preparation, etching of the cavity was performed with 35% phosphoric acid followed by bonding. The prepared cavities were then filled with Omnichroma composite resin on the buccal side and Filtek Z250 composite on the palatal side. The baseline color measurements of all tooth samples were performed by a spectrophotometer. The teeth were then divided into three groups, the Pepsi group, coffee group and milk tea group. Five teeth from each shade, viz. A2, A3, B2 and B3, were immersed in 10-mL of Pepsi, coffee, and milk tea for 14 days. After the completion of the 14 days, the teeth were rinsed and kept in distilled water for 24 h. Finally, a spectrophotometer was used to calculate the color alteration value ΔE. Mean difference in ΔE values of the samples before and after immersion in different beverages was calculated and analysed by SPSS 25. One-way ANOVA test was applied to compare groups. Further stratification was performed using the Post-Hoc Tukeys test. Samples immersed in milk tea showed a statistically significant difference (p < 0.05) in A2, A3, and B2 shades of the OM-milk tea group in comparison with the FT-milk tea group. In summary, the immersion of teeth in beverages with a different pH and colorants showed an apparent alteration in the color of both the smart monochromatic and micro-hybrid composites. Hence, the type of resin composite material should be selected wisely depending on the patient’s drinking and social habits.
Deep Learning-Based Human Action Recognition with Key-Frames Sampling Using Ranking Methods
Authors: Tasnim Nusrat , Baek Joong-Hwan
Published: April 2022

Nowadays, the demand for human–machine or object interaction is growing tremendously owing to its diverse applications. The massive advancement in modern technology has greatly influenced researchers to adopt deep learning models in the fields of computer vision and image-processing, particularly human action recognition. Many methods have been developed to recognize human activity, which is limited to effectiveness, efficiency, and use of data modalities. Very few methods have used depth sequences in which they have introduced different encoding techniques to represent an action sequence into the spatial format called dynamic image. Then, they have used a 2D convolutional neural network (CNN) or traditional machine learning algorithms for action recognition. These methods are completely dependent on the effectiveness of the spatial representation. In this article, we propose a novel ranking-based approach to select key frames and adopt a 3D-CNN model for action classification. We directly use the raw sequence instead of generating the dynamic image. We investigate the recognition results with various levels of sampling to show the competency and robustness of the proposed system. We also examine the universality of the proposed method on three benchmark human action datasets: DHA (depth-included human action), MSR-Action3D (Microsoft Action 3D), and UTD-MHAD (University of Texas at Dallas Multimodal Human Action Dataset). The proposed method secures better performance than state-of-the-art techniques using depth sequences.
Optimal Spatial Coherence of a Light-Emitting Diode in a Digital Holographic Display
Authors: Lim Sungjin , Jeon Hosung , Ahn Sunggyun , Hahn Joonku
Published: April 2022

The coherence of a light source is a vital aspect regarding the image quality of holographic contents. Generally, the coherence of the light source is the reason for speckle noise in a holographic display, which degrades the image quality. To reduce the speckle noise, partially coherent light sources such as light-emitting diodes (LED) have been studied. However, if the coherence of the light source is too low, the reconstructed image will blur. Therefore, using a spatial filter to improve the spatial coherence of LEDs has been proposed. In this study, we analyze the effect of the spatial and temporal coherence of the LED light source in a digital holographic display, and the optimal spatial coherence is determined. For this purpose, we devised an optical structure to control the spatial coherence in a holographic display system using a digital micro-mirror device (DMD). Here, the DMD functions as a dynamic spatial filter. By evaluating the change in the holographic image quality according to the spatial filter size, we obtained an optimal spatial filter size of 270 µm in our system. The proposed method is expected to be useful for selecting the optimal coherence of the light source for holographic displays.
Influence of Ambient Atmospheric Environments on the Mixing State and Source of Oxalate-Containing Particles at Coastal and Suburban Sites in North China
Authors: Zhao Yunhui , Zhang Yanjing , Li Xiaodong , Li Lei , Feng Limin , Xie Huan , Li Wenshuai , Liu Xiaohuan , Zhu Yujiao , Sheng Lifang , Qi Jianhua , Gao Huiwang , Zhou Zhen , Zhou Yang
Published: April 2022

Photodegradation is a key process impacting the lifetime of oxalate in the atmosphere, but few studies investigated this process in the field due to the complex mixing and sources of oxalate. Oxalate-containing particles were measured via single-particle aerosol mass spectrometry at coastal and suburban sites in Qingdao, a coastal city in North China in the summer of 2016. The mixing state and influence of different ambient conditions on the source and photodegradation of oxalate were investigated. Generally, 6.3% and 12.3% of the total particles (by number) contained oxalate at coastal and suburban sites, respectively. Twelve major types of oxalate-containing particles were identified, and they were classified into three groups. Biomass burning (BB)-related oxalate–K and oxalate–carbonaceous particles were the dominant groups, respectively, accounting for 68.9% and 13.6% at the coastal site and 72.0% and 16.8% at the suburban site. Oxalate–Heavy metals (HM)-related particles represented 14.6% and 9.3% of the oxalate particles at coastal and suburban sites, respectively, which were mainly from industrial emissions (Cu-rich, Fe-rich, Pb-rich), BB (Zn-rich), and residual fuel oil combustion (V-rich). The peak area of oxalate at the coastal site decreased immediately after sunrise, while it increased during the daytime at the suburban site. However, the oxalate peak area of Fe-rich particles at both sites decreased after sunrise, indicating that iron plays an important role in oxalate degradation in both environments. The decay rates (k) of Fe-rich and BB-Fe particles at the coastal site (−0.978 and −0.859 h−1, respectively), were greater than those at the suburban site (−0.512 and −0.178 h−1, respectively), owing to the high-water content of particles and fewer oxalate precursors. The estimated k values of oxalate peak area for different ambient conditions were in the same order of magnitude, which can help establish or validate the future atmospheric models.
Long-Term Studies of Biological Components of Atmospheric Aerosol: Trends and Variability
Authors: Safatov Alexandr S. , Andreeva Irina S. , Buryak Galina A. , Olkin Sergei E. , Reznikova Irina K. , Belan Boris D. , Panchenko Mikhail V. , Simonenkov Denis V.
Published: April 2022

Background: Biological components of atmospheric aerosol affect the quality of atmospheric air. Long-term trends in changes of the concentrations of total protein (a universal marker of the biogenic component of atmospheric aerosol) and culturable microorganisms in the air are studied. Methods: Atmospheric air samples are taken at two locations in the south of Western Siberia and during airborne sounding of the atmosphere. Sample analysis is carried out in the laboratory using standard culture methods (culturable microorganisms) and the fluorescence method (total protein). Results: Negative trends in the average annual concentration of total protein and culturable microorganisms in the air are revealed over more than 20 years of observations. For the concentration of total protein and culturable microorganisms in the air, intra-annual dynamics is revealed. The ratio of the maximum and minimum values of these concentrations reaches an order of magnitude. The variability of concentrations does not exceed, as a rule, two times for total protein and three times for culturable microorganisms. At the same time, for the data obtained in the course of airborne sounding of the atmosphere, a high temporal stability of the vertical profiles of the studied concentrations was found. The detected biodiversity of culturable microorganisms in atmospheric air samples demonstrates a very high variability at all observation sites. Conclusions: The revealed long-term changes in the biological components of atmospheric aerosol result in a decrease in their contribution to the atmospheric air quality index.
Design and Optimization of All-Dielectric Fluorescence Enhancing Metasurfaces: Towards Advanced Metasurface-Assisted Optrodes
Authors: Alhalaby Hiba , Principe Maria , Zaraket Haitham , Vaiano Patrizio , Aliberti Anna , Quero Giuseppe , Crescitelli Alessio , Di Meo Valentina , Esposito Emanuela , Consales Marco , Cusano Andrea
Published: April 2022

The need for miniaturized biological sensors which can be easily integrated into medical needles and catheters for in vivo liquid biopsies with ever-increasing performances has stimulated the interest of researchers in lab-on-fiber (LOF) technology. LOF devices arise from the integration of functional materials at the nanoscale on the tip of optical fibers, thus endowing a simple optical fiber with advanced functionalities and enabling the realization of high-performance LOF biological sensors. Consequently, in 2017, we demonstrated the first optical fiber meta-tip (OFMT), consisting of the integration of plasmonic metasurfaces (MSs) on the optical fiber end-face which represented a major breakthrough along the LOF technology roadmap. Successively, we demonstrated that label-free biological sensors based on the plasmonic OFMT are able to largely overwhelm the performance of a standard plasmonic LOF sensor, in view of the extraordinary light manipulation capabilities of plasmonic array exploiting phase gradients. To further improve the overall sensitivity, a labelled sensing strategy is here suggested. To this end, we envision the possibility to realize a novel class of labelled LOF optrodes based on OFMT, where an all-dielectric MS, designed to enhance the fluorescence emission by a labelled target molecule, is integrated on the end-face of a multimode fiber (MMF). We present a numerical environment to compute the fluorescence enhancement factor collected by the MMF, when on its tip a Silicon MS is laid, consisting of an array of cylindrical nanoantennas, or of dimers or trimers of cylindrical nanoantennas. According to the numerical results, a suitable design of the dielectric MS allows for a fluorescence enhancement up to three orders of magnitudes. Moreover, a feasibility study is carried out to verify the possibility to fabricate the designed MSs on the termination of multimode optical fibers using electron beam lithography followed by reactive ion etching. Finally, we analyze a real application scenario in the field of biosensing and evaluate the degradation in the fluorescence enhancement performances, taking into account the experimental conditions. The present work, thus, provides the main guidelines for the design and development of advanced LOF devices based on the fluorescence enhancement for labelled biosensing applications.
Cerebellum-Cortical Interaction in Spatial Navigation and Its Alteration in Dementias
Authors: Mirino Pierandrea , Pecchinenda Anna , Boccia Maddalena , Capirchio Adriano , D’Antonio Fabrizia , Guariglia Cecilia
Published: April 2022

The cerebellum has a homogeneous structure and performs different computational functions such as modulation/coordination of the communication between cerebral regions, and regulation/integration of sensory information. Albeit cerebellar activity is generally associated with motor functions, several recent studies link it to various cognitive functions, including spatial navigation. In addition, cerebellar activity plays a modulatory role in different cognitive domains and brain processes. Depending on the network involved, cerebellar damage results in specific functional alterations, even when no function loss might be detected. In the present review, we discuss evidence of brainstem degeneration and of a substantial reduction of neurons in nuclei connected to the inferior olivary nucleus in the early stages of Alzheimer’s disease. Based on the rich patterns of afferences from the inferior olive nucleus to the cerebellum, we argue that the subtle alterations in spatial navigation described in the early stages of dementia stem from alterations of the neuromodulatory functions of the cerebellum.
A High Methylation Level of a Novel −284 bp CpG Island in the RAMP1 Gene Promoter Is Potentially Associated with Migraine in Women
Authors: Carvalho Estefânia , Dias Andreia , Sousa Alda , Lopes Alexandra M. , Martins Sandra , Pinto Nádia , Lemos Carolina , Alves-Ferreira Miguel
Published: April 2022

Migraine is a complex neurovascular disorder affecting one billion people worldwide, mainly females. It is characterized by attacks of moderate to severe headache pain, with associated symptoms. Receptor activity modifying protein (RAMP1) is part of the Calcitonin Gene-Related Peptide (CGRP) receptor, a pharmacological target for migraine. Epigenetic processes, such as DNA methylation, play a role in clinical presentation of various diseases. DNA methylation occurs mostly in the gene promoter and can control gene expression. We investigated the methylation state of the RAMP1 promoter in 104 female blood DNA samples: 54 migraineurs and 50 controls. We treated DNA with sodium bisulfite and performed PCR, Sanger Sequencing, and Epigenetic Sequencing Methylation (ESME) software analysis. We identified 51 CpG dinucleotides, and 5 showed methylation variability. Migraineurs had a higher number of individuals with all five CpG methylated when compared to controls (26% vs. 16%), although non-significant (p = 0.216). We also found that CpG −284 bp, related to the transcription start site (TSS), showed higher methylation levels in cases (p = 0.011). This CpG may potentially play a role in migraine, affecting RAMP1 transcription or receptor malfunctioning and/or altered CGRP binding. We hope to confirm this finding in a larger cohort and establish an epigenetic biomarker to predict female migraine risk.
Psychometric Investigation of the Workplace Social Courage Scale (WSCS): New Evidence for Measurement Invariance and IRT Analysis
Authors: Magnano Paola , Faraci Palmira , Santisi Giuseppe , Zammitti Andrea , Zarbo Rita , Howard Matt C.
Published: April 2022

This study, after presenting a review of the existent literature on courage and social courage in the workplace, has the purpose of providing new evidence about the psychometric properties of an Italian-language version of the Workplace Social Courage Scale (WSCS), verifying its measurement invariance across gender and the discrimination properties of its items through IRT analysis. The aim of the research is testing the Italian version of the WSCS; for this scope, four studies have been conducted on four different samples analyzing the factorial structure, the internal consistency, the measurement invariance across gender, and the convergent and concurrent validity. The results support the psychometric properties in terms of factor structure, reliability, validity, and utility, showing positive relationships with the criterion variables: satisfaction of work-related basic needs, prosocial rule breaking and work performance. The current study extends prior findings by providing further insights about the construct of courage and social courage in the workplace, especially in the Italian context. As, to date, little is known about the impact of social courage on work and organizational outcomes, the availability of a reliable, valid, and cross-culturally supported instrument can promote the role of this construct in positive organizational behavior research.
Ultrasonic Coda Wave Experiment and Simulation of Concrete Damage Process under Uniaxial Compression
Authors: He Yameng , Song Lei , Xue Keke , Liu Shukui , Li Haipeng , Yang Weihao , Huang Jiahui
Published: April 2022

Using the coda wave interferometry (CWI) method to obtain the ultrasonic coda wave characteristics of loaded concrete is an important method to evaluate the mechanical response of concrete. In this paper, the ultrasonic coda wave characteristics of C40–C70 concrete specimens (four strengths of concrete) under uniaxial compression were tested by laboratory experiments. Furthermore, to clarify the relationship between the internal damage process of concrete and the change rate of coda wave velocity, an ultrasonic coda wave discrete element simulation model combined with digital image processing technology was established. The results show that the coda wave is very sensitive to small changes in the compressive damage to concrete, and the change in coda wave velocity can correspond to the development process of concrete damage. This research is conducive to a better understanding of the complex material behavior of compressive concrete and proves the feasibility of ultrasonic field simulation and processing by using numerical simulation images of concrete damage.