bluuebunny/crossref_metadata_2025 huggingface dataset:
Journalists’ Response and Reporting of Public Emergencies in the Era of Artificial Intelligence
Authors: Lian Shaoying , Mi Ruoyu , Tang Runhua
Published: January 2022

In order to improve the response ability of journalists to public emergencies, this study uses the computer simulation research method, based on Shannon’s information theory and the basic theory of journalism and communication, constructs the general model of public emergencies based on the statistical results of big data, and constructs the irrational natural person game model of four types of news communication participants. In the simulation analysis, it is found that in the face of public emergencies, journalists, on the one hand, firmly implement the publicity caliber, strengthen the amount of creation, and improve the forwarding amount and approval amount of manuscripts under the artificial intelligence news system. On the other hand, they should achieve effective interaction with nonofficial news media such as we media, and the subjective news department should provide effective guidance and guidance to the media.
Predictive Ability of Visit-to-Visit Variability of HbA1c Measurements for the Development of Diabetic Kidney Disease: A Retrospective Longitudinal Observational Study
Authors: Yan Yunyi , Kondo Nozomi , Oniki Kentaro , Watanabe Hiroshi , Imafuku Tadashi , Sakamoto Yuki , Shigaki Takuro , Maruyama Akari , Nakazawa Hitomi , Kaneko Tetsuya , Morita Ayami , Yoshida Akira , Maeda Hitoshi , Maruyama Toru , Jinnouchi Hideaki , Saruwatari Junji
Published: January 2022

Aims. This study is aimed at clarifying the relationship between visit-to-visit variability of glycated hemoglobin (HbA1c) and the risk of diabetic kidney disease (DKD) and to identifying the most useful index of visit-to-visit variability of HbA1c. Methods. This clinic-based retrospective longitudinal study included 699 Japanese type 2 diabetes mellitus patients. Visit-to-visit variability of HbA1c was calculated as the internal standard deviation of HbA1c (HbA1c-SD), the coefficient of variation of HbA1c (HbA1c-CV), the HbA1c change score (HbA1c-HVS), and the area under the HbA1c curve (HbA1c-AUC) with 3-year serial HbA1c measurement data, and the associations between these indices and the development/progression of DKD were examined. Results. Cox proportional hazards models showed that the HbA1c-SD and HbA1c-AUC were associated with the incidence of microalbuminuria, independently of the HbA1c level. These results were verified and replicated in propensity score (PS) matching and bootstrap analyses. Moreover, the HbA1c-SD and HbA1c-AUC were also associated with oxidized human serum albumin (HSA), an oxidative stress marker. Conclusions. Visit-to-visit variability of HbA1c was an independent risk factor of microalbuminuria in association with oxidative stress among type 2 diabetes mellitus patients. HbA1c-AUC, a novel index of HbA1c variability, may be a potent prognostic indicator in predicting the risk of microalbuminuria.
Performance Evaluation of Cyclic Stability and Capacitance of Manganese Oxide Modified Graphene Oxide Nanocomposite for Potential Supercapacitor Applications
Authors: Kumar R. Ranjith , Thanigaivel S. , Dey Nibedita , Priya A. K. , Karthick Alagar , Mohanavel V. , Kannadhasan S. , Muhibbullah M. , Osman Sameh M.
Published: January 2022

Supercapacitors are a revolutionary type of energy storage device. They must be able to charge and discharge quickly while maintaining a high energy density. A storage material’s cyclic stability is a desirable feature. The type of electrode materials employed for the specific study design affects supercapacitor performance. Manganese dioxide has long been regarded as one of the best and most abundant materials in nature, having a potentially high specific capacitance. They also offer a wider potential range, more electroactivity, and are more environmentally friendly. However, because of its decreased volume expansion and low conductivity, it is difficult to use as a capacitor material. As a result, carbon‐based porous films and supports can be employed to produce critical composites to overcome the current shortcoming. These nanoparticle‐based materials will have improved electrical conductivity and a large surface area. Graphene oxide (GO) has a high surface area, thermal stability, and porosity. As an electrode material, many types of MnO2/carbon‐based materials have been widely used in supercapacitors. Their overall performance is influenced by their construction processes, metal ratios, electrolyte medium, and voltage factors. Microwave technology was chosen as a cost‐efficient and effective alternative to expensive and laborious techniques for fabricating MnO2/GO composites. The production procedure of a supercapacitor has been explored in this study using MnO2‐GO composite materials. Using the electrochemical deposition process, the nanocomposite materials of MnO2‐GO are significantly deposited on the stainless steel (SS) substrate material. Galvanostatic charge‐discharge techniques and cyclic voltammetry (CV) analytical methods were used to investigate the storage and cycle ability of supercapacitors. The composite MnO2‐GO supercapacitor has a higher electrochemical capacitance based on these findings.
Effect of Thiopental on Ischemic Stroke in Rat Brain in Spontaneously Hypertensive Rats
Authors: You Lu , Zhao Qian , Yan JianYong , Li Wen , Yang Ye , Qin Chenguang
Published: January 2022

Motivation and Problem Statement. Thiopental is an anesthetic drug related to the condition of controlling the area of neurological contexts. This study is related to the analysis of effectiveness for the condition of thiopental application on spontaneously hypertensive rats. Methodology. We have evaluated the thiopental induction as the anesthetic agent. The hypertensive rats were selected to administer thiopental in the form of anesthesia. The selection and application of hypertensive strokes are related to the derivation of an inducible model to assess the efficacy for analyzing the ischemic stroke parameters which relate to the human body. We used middle cerebral artery occlusion (MCAO) models related to spontaneous hypertension with the area of examining the complications in ischemic stroke. Results and Conclusion. The study focused on the experimental analysis based on the selection of spontaneously hypertensive rats associated with the incidence of ischemic stroke. Application of thiopental has reported the weak functionality and mechanism on the relaxation of neuronal activity in the case of rat brain. The considered population of the spontaneously hypertensive rats is evaluated based on the condition of effectiveness as well as the duration of the medication effects within the rat brain. Involvement of thiopental in the case of ischemic stroke has provided the area of risk development for high rate of death incidences after occurrence of acute ischemic stroke. A complication in the area of defining neuroprotective actions provides difficulty in drawing an appropriate conclusion of the study.
[Retracted] Discrete Dynamic Modeling Analysis of Rural Revitalization and Ecotourism Sustainable Prediction Based on Big Data
Authors: Tang Yao
Published: January 2022

With the development of modern rural tourism, it has become people’s spiritual demand to deeply tap the characteristic rural culture and continuously enhance the attraction of rural tourism. However, due to the complex tourism market environment, small changes in factors will affect the final result. Therefore, traditional methods cannot accurately predict the future tourism market. In view of this situation, this paper uses the mathematical algorithm of BP neural network to simulate the structure of brain neural network to deal with this kind of nonlinear relationship problem. Through the classification of complex and changeable factors, the modeling is completed systematically, and finally the effective prediction results are obtained. For the analysis of the time evolution of tourism resources development, it can be found from the policy development theory that the innovative development presents the characteristics of S‐shaped curve in time; that is, the number adopted in the initial stage of development is less, then enters the rapid development period, and finally develops slowly. This study will help to solve the primary problem of balancing the positive and negative effects of rural tourism development and realizing the sustainable development of coastal villages.
A Neural Network-Based Method for Fast Capture and Tracking of Laser Links between Nonorbiting Platforms
Authors: Li Bo , Yu Siyuan , Ma Jing , Tan Liying
Published: January 2022

In this paper, a neural network approach is used to conduct an in-depth study and analysis of the fast capture tracking method for laser links between nonorbiting platforms. The experimental platform of the convolutional neural network- (CNN-) based free-space optical communication (FSO) wavefront correction system is built indoors, and the wavefront distortion correction performance of the CNN-based wavefront correction method is investigated. The experimental results show that the coupling power loss can be reduced to small after the CNN method correction under weak and strong turbulence. The accuracy of the above model is verified by comparing the simulation data with the experimentally measured data, thus realizing the coordinate decoupling of the coarse aiming mechanism and weakening the influence of structural factors on the tracking accuracy of the system. The tracking correlation equation of the influence of beam far-field dynamic characteristics on the tracking stability of the link is established, and the correlation factor variance of beam far-field dynamic characteristics is used to provide a quantitative analysis method for the evaluation and prediction of the comprehensive performance of the link tracking stability. The influence of beam divergence angle, wavefront distortion, detector accuracy, and atmospheric turbulence disturbance on the correlation factor variance of beam far-field dynamic characteristics of laser link beacons is modelled, and the link tracking stability optimization method is proposed under the requirement of link tracking accuracy, which provides an effective solution analysis method to realize the improvement of laser link tracking stability.
Visual-Text Reference Pretraining Model for Image Captioning
Authors: Li Pengfei , Zhang Min , Lin Peijie , Wan Jian , Jiang Ming
Published: January 2022

People can accurately describe an image by constantly referring to the visual information and key text information of the image. Inspired by this idea, we propose the VTR-PTM (Visual-Text Reference Pretraining Model) for image captioning. First, based on the pretraining model (BERT/UNIML), we design the dual-stream input mode of image reference and text reference and use two different mask modes (bidirectional and sequence to sequence) to realize the VTR-PTM suitable for generating tasks. Second, the target dataset is used to fine tune the VTR-PTM. To the best of our knowledge, VTR-PTM is the first reported pretraining model to use visual-text references in the learning process. To evaluate the model, we conduct several experiments on the benchmark datasets of image captioning, including MS COCO and Visual Genome, and achieve significant improvements on most metrics. The code is available at https://github.com/lpfworld/VTR-PTM.
Universal cyber physical system, a prototype for predictive maintenance
Authors: Kee Keh-Kim , Lau Boung Yew Simon , Lim Yun Seng , Ting Yip Ping , Rashidi Ramli
Published: January 2022

Industrial 4.0 technology of cyber-physical system enables real-time monitoring, sensing and actuating of physical machinery for predictive maintenance that replaces the conventional labor-intensive approach. This paper presents the design and development of a universal, cost-effective and internet of thing (IoT)-based proof-of-concept prototype universal cyber-physical system (UniCPS) with a cloud platform with an open and modular-based design of three-tier system architecture. The prototype demonstrates promising precision and accuracy for predictive maintenance on a pilot use case with MAPE of 3.77%, and average RMSE of 0.50. Besides, real-time visualization and detection of anomaly were also demonstrated with a cloud-based solution. The maintenance alert sent out by the actuator serves to notify the authorized personnel immediately for corrective action. As an extension to this work, a wireless sensor network can be incorporated in future work to acquire various data from diverse locations to overcome the limitations of sensor data.
Enhanced SLM based OFDM-DCSK communication system for PAPR reduction
Authors: Abdulridha Sajjad R. , Hasan Fadhil S.
Published: January 2022

In this research, a selective mapping (SLM) technique using the Walsh Hadamard (WH) matrix, the Riemann matrix, and the new enhanced Riemann matrix were introduced to reduce the peak to average power ratio (PAPR) of orthogonal frequency division multiplexing based differential chaos shift keying (OFDM-DCSK). Using a new algorithm to reduce the size of the Riemann matrix, which in turn enhances the computational complexity of the SLM system without affecting the performance of PAPR in the main method. The simulation results show that the SLM technique using the Riemann matrix gives better PAPR performance than WH and conventional techniques by gaining about (6.3, 6.15) dB, respectively, for complementary cumulative distribution function (CCDF)=10-3 and the number of candidates U=16. Also, the results show that the SLM technique based enhanced Riemann matrix gives a reduction in computational complexity by reducing the number of candidates U to 4, while maintaining the same PAPR performance.
Digital watermarking image using three-level discrete wavelet transform under attacking noise
Authors: Lidyawati Lita , Darlis Arsyad Ramadhan , Jambola Lucia , Kristiana Lisa , Jayandanu Rea Ramada
Published: January 2022

The authentication, identification, and copyright protection can be obtained by constructing the digital image watermarking technique. Watermark robustness and imperceptibility account for the capability of the hidden watermark to survive the manipulation. The proposed paper is a robust algorithm for digital image watermarking with 3-level discrete wavelet transform (DWT) with some attacks method. The 3-level DWT method was used constants α=0.01 and 0.03 as a function of how depth the watermark inserts to the host image in the insertion and extraction process. The algorithm was evaluated using 8 bits per pixel (bpp) grayscale, 1024x1024 pixels for the host image, and 256x256 pixels for the watermark image. The method is also implemented some experimental with attacks such as gaussian, salt and pepper, blurring, and compression. The algorithm is relatively acceptable of good quality, achieves low-value mean squared error (MSE), high peak signals to noise ratio (PSNR), and structural similarity index metric (SSIM) value approach to 1. It is found that the highest image quality measurements by using α=0.03 with the attacking method of salt and pepper yield MSE=0.01, PSNR=45.6 dB and SSIM=0.95, respectively.
Image and video face retrieval with query image using convolutional neural network features
Authors: Hachchane Imane , Badri Abdelmajid , Sahel Aïcha , Elmourabit Ilham , Ruichek Yassine
Published: January 2022

This paper addresses the issue of image and video face retrieval. The aim of this work is to be able to retrieve images and/or videos of specific person from a dataset of images and videos if we have a query image of that person. The methods proposed so far either focus on images or videos and use hand crafted features. In this work we built an end-to-end pipeline for both image and video face retrieval where we use convolutional neural network (CNN) features from an off-line feature extractor. And we exploit the object proposals learned by a region proposal network (RPN) in the online filtering and re-ranking steps. Moreover, we study the impact of finetuning the networks, the impact of sum-pooling and max-pooling, and the impact of different similarity metrics. The results that we were able to achieve are very promising.
Dataset for classification of computer graphic images and photographic images
Authors: Basanth Kumar Halaguru Basavarajappa , Chennamma Haranahalli Rajanna
Published: January 2022

The recent advancements in computer graphics (CG) image rendering techniques have made it easy for the content creators to produce high quality computer graphics similar to photographic images (PG) confounding the most naïve users. Such images used with negative intent, cause serious problems to the society. In such cases, proving the authenticity of an image is a big challenge in digital image forensics due to high photo-realism of CG images. Existing datasets used to assess the performance of classification models are lacking with: (i) larger dataset size, (ii) diversified image contents, and (iii) images generated with the recent digital image rendering techniques. To fill this gap, we created two new datasets, namely, ‘JSSSTU CG and PG image dataset’ and ‘JSSSTU PRCG image dataset’. Further, the complexity of the new datasets and benchmark datasets are evaluated using handcrafted texture feature descriptors such as gray level co-occurrence matrix, local binary pattern and VGG variants (VGG16 and VGG19) which are pre-trained convolutional neural network (CNN) models. Experimental results showed that the CNN-based pre-trained techniques outperformed the conventional support vector machine (SVM)-based classifier in terms of classification accuracy. Proposed datasets have attained a low f-score when compared to existing datasets indicating they are very challenging.
Adaptive weight assignment scheme for multi-task learning
Authors: Huq Aminul , Pervin Mst. Tasnim
Published: January 2022

Deep learning based models are used regularly in every applications nowadays. Gen- erally we train a single model on a single task. However, we can train multiple tasks on a single model under multi-task learning (MTL) settings. This provides us many beneﬁts like lesser training time, training a single model for multiple tasks, reducing overﬁtting, and improving performances. To train a model in multi-task learning settings we need to sum the loss values from different tasks. In vanilla multi-task learning settings we assign equal weights but since not all tasks are of similar difﬁculty we need to allocate more weight to tasks which are more difﬁcult. Also improper weight assignment reduces the performance of the model. We propose a simple weight assignment scheme in this paper which improves the performance of the model and puts more emphasis on difﬁcult tasks. We tested our methods performance on both image and textual data and also compared performance against two popular weight assignment methods. Empirical results suggest that our proposed method achieves better results compared to other popular methods.
Smart pools of data with ensembles for adaptive learning in dynamic data streams with class imbalance
Authors: Kulkarni Radhika Vikas , Revathy S. , Patil Suhas Haribhau
Published: January 2022

Streaming data incorporates dynamicity due to a nonstationary environment where data samples may endure class imbalance and change in data distribution over the period causing concept drifts. In real-life applications learning in dynamic data streams, is vitally important and challenging. A combined solution to adapt to class imbalance and concept drifts in dynamic data streams is rarely addressed by researchers. With this motivation, the current communication presents the online ensemble model smart pools of data with ensembles for class imbalance adaptive learning (SPECIAL) to learn in skewed and drifting data streams. It employs an ageing-based G-mean maximization strategy to adapt to dynamicity in data streams. It employs smart data-pools with the local expertise ensemble to classify samples lying in the same data-pool. The empirical and statistical study on different evaluation metrics exhibits that SPECIAL is more adaptive to class imbalanced dynamic data streams than the state-of-the-art algorithms.
Automatic face recording system based on quick response code using multicam
Authors: Julham Julham , Lubis Muharman , Lubis Arif Ridho , Al-Khowarizmi Al-Khowarizmi , Kamil Idham
Published: January 2022

This research mainly talks about the use of quick response (QR) code reader in automating of recording the users' face. The applied QR code reader system is a dynamic type, which can be modified as required, such as adding a database, functioning to store or retrieve information in the QR code image. Since the QR code image is randomly based on its information, a QR code generator is required to display the image and store the information. While the face recorder uses a dataset available in the OpenCV library. Thus, only the registered QR code image can be used to record the user's face. To be able to work, the QR code reader should be 10 to 55 cm from the QR code image.
Identify tooth cone beam computed tomography based on contourlet particle swarm optimization
Authors: Younis Hiba Adreese , Hammadi Dhafar Sami , Younis Ansam Nazar
Published: January 2022

In this paper certain type of biometric measurements has been used to identify the cone beam computed tomography (CBCT) radiograph of the subject in a fast and reliable way. Where the CBCT radiograph of a person is used as a data and stored in database for later use in a person’s recognition process. The aim of this research is to use various stages of the preprocessing operations of the CBCT radiograph to obtain the clearest possible image that will help us in the identification process more easily and precisely. The contourlet transformation was used for feature extraction of each particular CBCT image and the results were processed by a new hybrid particle swarm optimization (PSO) named "contourlet PSO" algorithm (CPSO), which is faster and produce more precise (due to apply contourlet algorithm) than traditional PSO. The proposed algorithm (CPSO) gave a detection ratio of 98% after its application on 100 CBCT radiographs.
Bad Speech, Good Evidence: Content Moderation in the Context of Open-Source Investigations
Authors: Hubley Hillary
Published: January 2022

This article explores how content moderation on social media platforms impacts the work of open-source investigators through its routine removal of content having evidentiary value. These practices have rendered social media platforms susceptible to public criticism and scrutiny. However, these criticisms have largely been levied by a community who cares about content removal’s impact on free expression online. This swath of concerns does not comport with those of international criminal investigators who have increasingly turned to platforms for evidence gathering. Rather than confronting the issue, investigators have absorbed the costs by downplaying the impact of content removal on their work and by seeking to preserve the content on their own. I examine the disconnect between these two groups in their respective approaches to the problem of content removal and argue that both communities can stand to benefit from joining forces and taking notice of the convergence of their respective concerns.
Single-Incision Laparoscopic Complete Mesocolic Excision With Central Vascular Ligation for Descending Colon Cancer
Authors: Tei Mitsuyoshi , Suzuki Yozo , Ohtsuka Masahisa , Mizushima Tsunekazu , Akamatsu Hiroki
Published: January 2022

Background

Single-incision laparoscopic complete mesocolic excision with central vascular ligation for descending colon cancer is technically challenging. Standardization of the surgical procedures is therefore needed.

Methods

In a Trendelenburg position with left side elevated, the sigmoid mesocolon is mobilized using a medial-to-lateral approach, and the left colic artery and inferior mesenteric vein (IMV) are divided after radical lymphadenectomy along the inferior mesenteric artery, preserving the superior rectal artery. The descending mesocolon is mobilized from the retroperitoneal planes up to the dorsal surface of the pancreas using medial and lateral approaches. Next, changing the surgical position to a reverse Trendelenburg position with left side elevated, the omental bursa is opened, and the transverse mesocolon is separated from the inferior border of the pancreas. The splenocolic ligament and lateral attachment are then divided, matching the previous medial dissection of the retroperitoneum, and the splenic flexure is fully mobilized. The IMV is divided again at the inferior border of the pancreas. The left branch of the middle colic artery is also divided.

Results

Forty-seven consecutive patients with DCC underwent single-incision laparoscopic CME with CVL. One patient required an additional port. Median operative time, blood loss, and number of harvested lymph nodes were 240 min (interquartile range [IQR], 195-257 min), 5 mL (IQR, 5-52 mL), and 21 (IQR, 13-29), respectively. Morbidity rate was 5.9%. Median duration of hospitalization was 9 days (IQR, 7-11 days).

Conclusions

Single-incision laparoscopic CME with CVL is safe and feasible for DCC.
The Jungian Application of Therapeutic Folk Imagery With Frontline Workers in China During the Pandemic
Authors: Shi Congxin , Zhang Yancui
Published: January 2022

After the sudden outbreak of coronavirus disease 2019 (COVID-19) in China in 2020, the viral disease broke out in most countries around the world, becoming a worldwide health emergency. Throughout the pandemic, people have been compelled to simultaneously grapple with its external challenges as well as the psycho-spiritual consequences. This article focuses on a folk image “Sea-Stabilizing Secret Weapon1” and its clinical application to the frontline workers during the pandemic from Jungian perspective. “Sea-Stabilizing Secret Weapon” is a magical weapon used by the character Monkey King who wields it to subdue demons in his quest to retrieve and protect sacred Buddhist scriptures in the Chinese mythological novel Journey to the West. In this article, we analyze the psychological significance of the image of Sea-Stabilizing Secret Weapon as a psychic portal through which to bring contents of the unconscious into consciousness, and a medium to achieve balance between the I (consciousness) and the psychic world within (the unconscious). We posit that the Sea-Stabilizing Secret Weapon corresponds with Edinger’s ego-Self axis and can be used to unveil the unconscious. The process through which this magical weapon is discovered and used by Monkey King is analogous to the dynamic linking of the ego (the center of consciousness) to the Self (the center of the psyche). Two cases during the pandemic are used to illustrate the application of the image as a therapeutic intervention with the frontline medical staff at the individual and group levels.
Using Technology to Support Academic Learning
Authors: Kroesch Allison M. , Jozwik Sara , Douglas Karen H. , Chung Yun-Ching , Uphold Nicole M. , Baker Emilee
Published: January 2022

We conducted this systematic literature review to summarize single-case intervention studies in which academic instruction incorporated assistive and instructional technology for students with complex support needs. Thirty studies, published between 2012 and 2019, were included in the review and evaluated for methodological rigor. Of the 97 student participants across all studies, most received language arts instruction in self-contained elementary classrooms. The majority of interventions used instructional technology on mobile devices in conjunction with systematic instruction focusing on teaching word recognition or letter identification skills. We discuss the key findings with recommendations for future research, and implications for practice.
How Does the Central Nervous System Control Forthcoming Movement with Different Emotional Stimuli?
Authors: Chikh Soufien , Mguidich Hajer , Souissi Hichem , Watelain Eric
Published: January 2022

Maintaining postural balance is a key factor in human motor skills, based in part on emotional stimuli. Our objective in this study was to measure the effect of emotion on postural control as influenced by the direction of forthcoming movement. Eighteen right-handed women initiated a step forward or backward or remained in a static position after visualizing an emotional stimulus (positive, negative, or neutral). Center of pressure (COP) parameters (2D velocity, Medio-lateral (ML), and antero-posterior (AP) amplitude) were recorded for 3-second windows for movement direction and emotional stimulus. We observed a motion * direction effect on 2D velocity, characterized by a decrease in the emotional stimulus and static direction windows. The participants’ ML amplitude was influenced by direction, and their reduced amplitude was evident in the presence of emotions. AP amplitude was high in the direction versus emotion window. In the static position, the AP amplitude was high in the direction window and low in the emotion window. The participants’ movement planning and programming phase (direction window) was characterized by less oscillation for forward or backward movements and more oscillation before movement, suggesting anticipatory postural adjustments in the emotion window. Static direction was characterized by low oscillation, compared to forward and backward movement and in negative versus positive emotional context, proving the interactive impact of direction and emotion on COP amplitudes. Thus, postural control was influenced by both movement (direction) and emotional content (valence). This study provided insight regarding the interactive effect of emotion and direction on planning and programming forthcoming movement.
Trends in Health Care Access Disparities Among Asian and Pacific Islander Health Fair Participants in Los Angeles, 2011-2019
Authors: Dhanjani Suraj Avinash , Yang Hong-Ho , Goyal Shuchi , Zhang Kevin , Gee Gilbert , Cowgill Burton
Published: January 2022

Objectives:

Given several efforts to improve health care access in California and nationally, we studied whether linguistic and socioeconomic disparities in health care access changed from 2011 to 2019 among Asian and Pacific Islander American (APIA) people in Los Angeles, California.

Methods:

We analyzed survey responses from APIA health fair participants (n = 5032) in the Greater Los Angeles area from May 15, 2011, through October 20, 2019. To assess the effect of socioeconomic factors on and shifts in health care access (ie, health insurance status/regular doctor), we used a logistic regression model. Covariates included English proficiency, year, age, sex, ethnicity, income, employment, and education. We also ran an interaction analysis between English proficiency and year.

Results:

Health insurance access increased and doctor access remained stable throughout the study period; however, disparities in health insurance status widened by a factor of 1.08 per year between participants with high English proficiency (HEP) and participants with low English proficiency (LEP) ( P = .01). People with HEP were 2.02 times more likely to have a regular doctor than people with LEP ( P < .001), and this disparity persisted from 2011 to 2019 ( P = .58). Participants who were young ( P < .001) and male ( P = .005) were significantly less likely to have health insurance and a regular doctor ( P < .001) than participants who were older and female. Chinese participants were significantly more likely than Thai ( P = .002) and Korean ( P < .001) participants to be insured but not more likely to have a regular doctor, when controlling for health insurance.

Conclusions:

Policy changes targeting language and cultural barriers to care for APIA people with LEP may address the disparities observed.
Prescribed performance–based tracking control for quadrotor UAV under input delays and input saturations
Authors: Zhu Bing , Chen Mou , Li Tao
Published: January 2022

In this paper, a semi-global trajectory tracking control scheme is proposed for quadrotor unmanned aerial vehicle (UAV) under time-varying input delays, input saturations, and bounded disturbances. Initially, in order to ensure the desirable control performance that tracking error is limited in a prescribed bound, an error transformation function is presented to transform the constrained problem into a stabilization one. Then, under backstepping control scheme, a state prediction method combined with a dynamic surface control (DSC) is presented to compensate for the effects of input delays, and an auxiliary system is designed to tackle the input saturations, which are further to deal with input delays and input saturations in both position system and attitude system of quadrotor UAV. Particularly, the Euler angle is constrained to avoid the singular points of the attitude system. Besides, based on Lyapunov stability theory, it can be verified that all signals in the closed-loop system of the quadrotor UAV are semi-globally ultimately uniformly bounded (UUB) and the tracking errors are restrained in the prescribed bounds. Finally, by choosing some appropriate parameters, the simulation results based on quadrotor UAV model are given to verify the effectiveness of the proposed control scheme.
Relationship between the Children’s Visual Function Questionnaire and psychophysical measures of visual acuity and chromaticity discrimination in older visually impaired children
Authors: Lopes Marcia Caires Bestilleiro , Costa Marcelo Fernandes , Nakanami Célia Regina
Published: January 2022

The Children’s Visual Function Questionnaire (CVFQ) is an instrument to measure the impact of visual impairment in children and their families. It can be used as a research tool to verify the effectiveness of treatment, therapy, and different methods for visual stimulation and rehabilitation. The aim of this study is to describe the relationship between General Health, General Vision Health, Personality, Family Impact, and Treatment – subscales of the CVFQ and psychophysical measures of visual acuity (VA) and chromaticity discrimination (CV). This prospective, cross-sectional study was conducted at the Sensory Psychophysiology Laboratory – University of São Paulo in partnership with the Ambulatory of Visual Stimulation in the Sector of Low Vision and Visual Rehabilitation – Federal University of São Paulo. The children who participated in this study were divided into two groups: study group (SG), composed of 11 children with a diagnosis of visual impairment and mean age of 55.36 months ( SD = 16.88), and control group (CG), composed of 8 children with normal vision and mean age of 64.87 months ( SD = 13.22). Both groups underwent the application of CVFQ, were tested for VA using the Teller Acuity Cards (TAC) test, and CV using the Cambridge Colour Test program for children (CCT Kids). The result of applying the CVFQ to groups of children over 3 years, comparing SG and CG, differences were observed in the following subscales: General Vision Health ( F = 10.00, p < .001); Competence ( F = 7.03, p = .030); Personality ( F = 6.48, p = .010); Total Quality of Life ( F = 11.39, p = .010). These differences show a worse score for the SG. In the VA test using TAC, the data collected in groups of children over 3 years, comparing SG and CG, differences were observed in VA RE ( F = 19.25, p < .001); VA LE ( F = 25.99, p < .001); VA BE ( F = 15.45, p < .001). These differences show worse scores for the SG. In the CV using the CCT Kids, the data collected in groups of children over 3 years, comparing SG and CG, no statistically significant differences for protan, tritan, and deutan groups were observed. For the SG, while for children over 3 years, correlations were found for General Vision Health, Competence, Family Impact, and General Quality of Life. We conclude that there are statistically significant differences when comparing the SG with the CG for the visual function of visual acuity and chromaticity discrimination, and we also demonstrated the sensitivity in the use of CVFQ in reflect VA and CV impairments.
Evaluation of a nasopharyngeal stent in patients with obstructive sleep-related breathing disorders
Authors: Dellweg Alexander , Kampmann Martin , Tschopp Kurt
Published: January 2022

Objective

This study was performed to evaluate the therapeutic effect and diagnostic value of a novel nasopharyngeal stent (Naśtent; Corinium Medical Equipment Ltd., Cirencester, UK). The Naśtent is designed to stent palatal collapse in patients with sleep-related breathing disorders.

Methods

The study was conducted from 2018 to 2019. Patients who did not qualify for continuous positive airway pressure therapy underwent split-night examination with an inserted Naśtent for the first half of the night. The next morning, drug-induced sleep endoscopy (DISE) was performed.

Results

Of the 122 enrolled patients, 21 were excluded because of Naśtent intolerance (n = 14) or technically invalid examinations (n = 7). Among the remaining 101 patients, in correlation with DISE, the apnea–hypopnea index was significantly reduced in patients with palatal obstructions, mainly in those with anteroposterior collapse patterns. The Naśtent did not influence retrolingual or multilevel obstructions. Using a 40% reduction of the apnea–hypopnea index by the Naśtent as a cut-off value, 85.7% of soft palate obstructions were detected compared with DISE.

Conclusions

The Naśtent is a viable tool to reduce palatal obstructions, although it is not readily tolerated. It may also be helpful for diagnosis of sleep-related breathing disorders when DISE is unavailable.
Sustainable supplier selection and order allocation for multinational enterprises considering supply disruption in COVID-19 era
Authors: Shao Yifan , Barnes David , Wu Chong
Published: January 2022

The unprecedented outbreak of COVID-19 has left many multinational enterprises facing extremely severe supply disruptions. Besides considering triple-bottom-line requirements, managers now also have to consider supply disruption due to the pandemic more seriously. However, existing research does not take these two key objectives into account simultaneously. To bridge this research gap, based on the characteristics of COVID-19 and similar global emergency events, this article proposes a model that aims to solve the problem of sustainable supplier selection and order allocation considering supply disruption in the COVID-19 era. It does so by using a multi-stage multi-objective optimization model applied to the different stages of development and spread of the pandemic. Then, a novel nRa-NSGA-II algorithm is proposed to solve the high-dimensional multi-objective optimization model. The applicability and effectiveness of the proposed model is illustrated in a well-known multinational producer of shortwave therapeutic instruments.

JEL Classification: M11
Vehicle Detection and Tracking for 511 Traffic Cameras With U-Shaped Dual Attention Inception Neural Networks and Spatial-Temporal Map
Authors: Zhang Tianya , Jin Peter J. , Ge Yi , Moghe Ryhan , Jiang Xiaowen
Published: January 2022

This paper develops vehicle detection and tracking method for 511 camera networks based on the spatial-temporal map (STMap) as an add-on toolbox for the traveler information system platform. The U-shaped dual attention inception (DAIU) deep-learning model was designed, given the similarities between the STMap vehicle detection task and the medical image segmentation task. The inception backbone takes full advantage of diverse sizes of filters and the flexible residual learning design. The channel attention module augmented the feature extraction for the bottom layer of the UNet. The modified gated attention scheme replaced the skip connection of the original UNet to reduce irrelevant features learned from earlier encoder layers. The designed model was tested on NJ511 traffic cameras for different scenarios covering rainy, snowy, low illumination, and signalized intersections from a key, strategic arterial in New Jersey. The DAIU Net has shown better performance than other mainstream neural networks based on segmentation model evaluation metrics. The proposed scanline vehicle detection was also compared with the state-of-the-art solution for infrastructure-based traffic movement counting solution and demonstrates superior capability. The code for the proposed DAIU model and reference models has been made public with the labeled STMap data to facilitate future research.
Evaluating the Performance of Concrete Overlays in Missouri
Authors: Espinoza-Luque Arturo Francisco , Grogg Max , Smith Kurt , Vandenbossche Julie , Donahue John
Published: January 2022

The Missouri Department of Transportation (MoDOT) has used concrete overlays as a pavement rehabilitation method since at least the 1930s, with over 40 projects constructed in the last two decades alone. However, there has not been an integral effort to comprehensively evaluate the performance of those projects in relation to design parameters, as-built construction quality, traffic levels, or distress progression. The objective of this study was to undertake a critical analysis of concrete overlays in Missouri as a first step to recommend improvements to MoDOT’s overlay selection, design, and construction practices. MoDOT uses three types of concrete overlays: unbonded overlays (UBOL), big block overlays (BBOL), and bonded overlays (BOL). It was found that UBOL projects exhibited the lowest international roughness index values among all types of overlays. The most predominant distress for UBOL was longitudinal cracking, which appeared more often at the center of the slab or in the right wheelpath. Cracking in the right wheelpath was particularly evident on projects that used a slab width greater than 12 ft and asphalt shoulders. Although BBOL and BOL projects did not deviate from the standard slab size, the rightmost panels tended to exhibit more distress, which might also point to weak support around the mainline-shoulder area. Recommendations for future projects include revising the design thickness procedures to be site-specific, revising the thickness quality control practices, and the continued use of geotextiles as interlayers for projects that require a bond breaker.
Experimental Investigation of Piezoelectric Energy Harvesters Applied in Concrete Pavement
Authors: Li Chenchen , Zhao Hongduo , Tian Yu , Lin Zhongpu
Published: January 2022

This paper proposes the application and manufacturing of piezoelectric devices based on pile and arc-bridge transducers to harvest mechanical energy from concrete pavement. Multi-scale experiments are conducted to clarify the influence of electrical connection, load resistance, traffic speed, and loading times on the electrical properties of the harvesters. The reduced-scale test shows that the transducers should be connected to rectifiers before being connected as an array. Moreover, the output power of the arc-bridge transducer with resistance variations is unstable compared with that of the pile transducer. Accelerated pavement testing illustrates that the output power of the half pile array device increases to 1.7 mW with an optimal resistance of 10.0 MΩ; reducing the internal equivalent resistance is a potential way to increase the energy output. The results also show that the load speeds significantly influence the profile of the voltage and have a minor effect on the generated electric energy in the tested conditions. Furthermore, the electrical properties of the piezoelectric device exhibit no statistical degradation after the electrical fatigue test of 100,000 tire loads, indicating a novel electrical fatigue performance. The findings in this paper can further guide the application of such piezoelectric devices in concrete pavement.
A response to Martin Weimer’s ‘The Talmudic way of thinking cannot suddenly have disappeared from us: Death instinct, anti-Semitism and Jewish traditions in the foundation matrix of group analysis’
Authors: Tubert-Oklander Juan
Published: January 2022

The author of this article poses three inter-related themes. 1) The primacy of the death instinct that accounts for destructivity in groups and, especially, for anti-Semitism. 2) There is a blind spot in group analysis that conceals the importance of anti-Semitism in its inception and history, which he deems to be largely derived from Foulkes’s idealization of groups and denial of their destructive potential. Hence, anti-Semitism is part of the foundation matrix of group analysis. 3) Group analytical practice, right down to its clinical details, can be understood as a performative realization of the rabbinic Jewish tradition. The present reviewer disagrees with these three points and expounds the reasons for this. However, he welcomes the opportunity it provides to engage in a most needed critical discussion.
Disparities in Teachers’ Access to Schools’ Collective Social Assets Based on Role, Race, and Poverty
Authors: Mason-Williams Loretta , Bettini Elizabeth , Morris Mathews Hannah , Boveda Mildred , Rodgers Wendy
Published: January 2022

A schools’ collective social assets (i.e., school culture, administrative support, and satisfied colleagues) are especially important for beginning teachers at higher risk of attrition, including special educators, teachers of color, teachers in high-poverty schools, and teachers in schools serving predominantly students of color. These teachers often report experiencing less social support than general educators, White teachers, teachers in low-poverty schools, and teachers serving predominantly White students, respectively; we labeled this inequitable access to schools’ collective social assets intersectional professional vulnerability. Using data from the Schools and Staffing Survey and structural equation modeling, we examined how beginning teachers’ race/ethnicity and their students’ race/ethnicity, socioeconomic status, and disability status related to perceptions of their U.S. schools’ collective social assets and how those perceptions shaped intent to continue teaching. We found significant differences in access to collective social assets based on their race/ethnicity, role as special versus general educators, and students served within their school.
Using Simulated Video Analysis to Promote Special Education Teacher Candidates’ Professional Knowledge and Reflective Ability
Authors: Nagro Sarah A. , Monnin Kevin
Published: January 2022

The purpose of this study was to investigate the potential of simulated video analysis where candidates with differing educational backgrounds taught their peers prior to engaging in an authentic field experience. Teacher candidates’ special education professional knowledge, reflective ability, and instructional skills were tracked to understand if outcomes differed based on teacher candidates’ previous teaching experience or progress toward licensure. All 37 candidates participated in three simulated video analysis sessions by recording their instruction during role-play with peers, reviewing their video independently in class, and completing a reflection matrix. Finally, candidates completed a culminating field experience project with a P-12 focus student. Results indicated significant improvements in both special education professional knowledge and reflective ability regardless of previous teaching experience or progress toward licensure. Candidates with previous teaching experience demonstrated significantly greater instructional skills than candidates with no previous teaching experience. Implications and limitations discussed.