bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomics profiling reveals a distinct high-risk molecular subtype of hypertrophic cardiomyopathy
Authors: Liang Lusha W , Raita Yoshihiko , Hasegawa Kohei , Fifer Michael A , Maurer Mathew S , Reilly Muredach P , Shimada Yuichi J
Published: March 2022

Objective

Hypertrophic cardiomyopathy (HCM) is a heterogeneous disease, likely encompassing several subtypes of disease with distinct biological mechanisms (ie, molecular subtypes). Current models based solely on clinical data have yielded limited accuracy in predicting the risk of major adverse cardiovascular events (MACE). Our aim in this study was to derive molecular subtypes in our multicentre prospective cohort of patients with HCM using proteomics profiling and to examine their longitudinal associations with MACE.

Methods

We applied unsupervised machine learning methods to plasma proteomics profiling data of 1681 proteins from 258 patients with HCM who were prospectively followed for a median of 2.8 years. The primary outcome was MACE, defined as a composite of arrhythmia, heart failure, stroke and sudden cardiac death.

Results

We identified four molecular subtypes of HCM. Time-to-event analysis revealed significant differences in MACE-free survival among the four molecular subtypes (plogrank=0.007). Compared with the reference group with the lowest risk of MACE (molecular subtype A), patients in molecular subtype D had a higher risk of subsequently developing MACE, with an HR of 3.41 (95% CI 1.54 to 7.55, p=0.003). Pathway analysis of proteins differentially regulated in molecular subtype D demonstrated an upregulation of the Ras/mitogen-activated protein kinase and associated pathways, as well as pathways related to inflammation and fibrosis (eg, transforming growth factor-β pathway).

Conclusions

Our prospective plasma proteomics study not only exhibited the presence of HCM molecular subtypes but also identified pathobiological mechanisms associated with a distinct high-risk subtype of HCM.
Patient Reported Outcome Measures for Rheumatoid Arthritis Disease Activity: a systematic review following COSMIN guidelines
Authors: Pickles Tim , Macefield Rhiannon , Aiyegbusi Olalekan Lee , Beecher Claire , Horton Mike , Christensen Karl Bang , Phillips Rhiannon , Gillespie David , Choy Ernest
Published: March 2022

Background

The current standard of care in rheumatoid arthritis (RA) requires regular assessment of disease activity (DA). All standard RA DA measurement instruments require joint counts to be undertaken by a healthcare professional with/without a blood test. Few healthcare providers have the capacity to assess patients as frequently as stipulated by guidelines. Patient Reported Outcome Measures (PROMs) could be an efficient and informative way to assess RA DA, which is highlighted by the SARS-COV-2 pandemic, as most consultations are remote rather than face-to-face. We aimed to assess all PROMs for RA DA against the internationally recognised COSMIN guidelines to provide evidence‐based recommendations to select the most suitable PROMs.

Methods

Review registered on PROSPERO as CRD42020176176. The search strategy was based on a previous similar systematic review and expanded to include all articles up to January 2019. All identified articles were rated by two independent assessors following the COSMIN guidelines.

Results

668 abstracts were identified, with 10 articles included. A further 21 were identified from a previous review. Ten PROMs were identified. There was insufficient evidence to place any of the identified PROMs into recommendation for use category A due to lack of evidence for content validity, as stipulated by the COSMIN guidelines.

Conclusion

Lack of evidence of content validity limits suitable PROM selection, therefore none can be recommended for use. It is acknowledged that all included PROMs were developed before the COSMIN guidelines were published. Future research on PROMs for RA DA must provide evidence of content validity.
Multimodal imaging of the distal interphalangeal-joint synovio-entheseal complex in psoriatic arthritis (MIDAS): a cross-sectional study on the diagnostic accuracy of different imaging modalities comparing psoriatic arthritis to psoriasis and osteoarthritis
Authors: Guldberg-Møller Jørgen , Mogensen Mette , Ellegaard Karen , Zavareh Ali , Wakefield Richard J , Tan Ai Lyn , Boesen Mikael , Dehmeshki Jamshid , Kubassova Olga , Dreyer Lene , Henriksen Marius , Kristensen Lars Erik
Published: March 2022

Objective

Can ultrasound (US), MRI and X-ray applied to the distal interphalangeal (DIP)-joint and synovio-entheseal complex (SEC) discriminate between patients with psoriatic arthritis (PsA), skin psoriasis (PsO) and hand osteoarthritis (OA)?

Methods

In this prospective, cross-sectional study, patients with DIP-joint PsA and nail involvement (n=50), PsO with nail involvement (n=12); and OA (n=13); were consecutively recruited. Risk ratios (RR) were calculated for US, MRI and X-ray findings of the DIP-joint and SEC between diagnoses.

Results

New bone formation (NBF) in US and MRI was a hallmark of OA, reducing the risk of having PsA (RR 0.52 (95% CI 0.43 to 0.63) and 0.64 (95% CI 0.56 to 0.74). The OA group was different from PsA and PsO on all MRI and X-ray outcomes reflected in a lower RR of having PsA; RR ranging from 0.20 (95% CI 0.13 to 0.31) for MRI bone marrow oedema (BMO) to 0.85 (95% CI 0.80 to 0.90) in X-ray enthesitis. No outcome in US, MRI or X-ray was significantly associated with a higher risk of PsA versus PsO, although there was a trend to a higher degree of US erosions and NBF in PsA. 82% of PsA and 67% of PsO was treated with disease modifying antirheumatic drugs which commonly reflects the clinical setting.

Conclusion

High grade of US, MRI and X-ray NBF reduce the RR of having PsA compared with OA. In PsA versus PsO patients, there was a trend for US to demonstrate more structural changes in PsA although this did not reach significance.
On the velocity of a quantum particle in the de Broglie–Bohm quantum mechanics: the case of the bouncing ball
Authors: Feoli A. , Benedetto E. , Iannella A. L.
Published: March 2022

Starting from the dynamics of a bouncing ball in classical and quantum regime, we suggest a modification of the probability current in quantum mechanics. We consider the consequences of this generalization on the resulting velocity of a quantum particle in the de Broglie–Bohm interpretation of quantum mechanics.
Acceptance sampling to aid in the verification of computational simulations
Authors: Collins Andrew J. , Frydenlund Erika , Lynch Christopher J. , Robinson R. Michael
Published: March 2022

Advances in computing allow for the construction of increasingly large and complex models and simulations. Exhaustive error checking of these intricate, large computational simulation models is daunting and potentially impractical. This paper explores an approach to error-checking simulation model components using an Acceptance Sampling methodology from the field of industrial manufacturing. We propose a systematic process in which a simulation inspector examines only a fraction of the computational model elements to measure the errors present. Our proposed process could support established verification processes by sampling the simulation components to identify whether the model is acceptably error free and which components require correcting. The proposed methodology relies on several statistical constraints but serves the interests of simulation professionals as part of the overall verification process. We illustrate the application and usefulness of our methodology through a real-world case study of a citywide microscopic transportation model.
Differentially Private
k
-Nearest Neighbor Missing Data Imputation
Authors: Clifton Chris , Hanson Eric J. , Merrill Keith , Merrill Shawn
Published: March 2022

Using techniques employing
smooth sensitivity
, we develop a method for

\( k \)

-nearest neighbor missing data imputation with differential privacy. This requires bounding the number of data incomplete tuples that can have their data complete “donor” changed by making a single addition or deletion to the dataset. The multiplicity of a single individual’s impact on an imputed dataset necessarily means our mechanisms require the addition of more noise than mechanisms that ignore missing data, but we show empirically that this is significantly outweighed by the bias reduction from imputing missing data.
SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems
Authors: Chen Yuxuan , Zhang Jiangshan , Yuan Xuejing , Zhang Shengzhi , Chen Kai , Wang Xiaofeng , Guo Shanqing
Published: March 2022

With the wide use of Automatic Speech Recognition (ASR) in applications such as human machine interaction, simultaneous interpretation, audio transcription, and so on, its security protection becomes increasingly important. Although recent studies have brought to light the weaknesses of popular ASR systems that enable out-of-band signal attack, adversarial attack, and so on, and further proposed various remedies (signal smoothing, adversarial training, etc.), a systematic understanding of ASR security (both attacks and defenses) is still missing, especially on how realistic such threats are and how general existing protection could be. In this article, we present our systematization of knowledge for ASR security and provide a comprehensive taxonomy for existing work based on a modularized workflow. More importantly, we align the research in this domain with that on security in Image Recognition System (IRS), which has been extensively studied, using the domain knowledge in the latter to help understand where we stand in the former. Generally, both IRS and ASR are perceptual systems. Their similarities allow us to systematically study existing literature in ASR security based on the spectrum of attacks and defense solutions proposed for IRS, and pinpoint the directions of more advanced attacks and the directions potentially leading to more effective protection in ASR. In contrast, their differences, especially the complexity of ASR compared with IRS, help us learn unique challenges and opportunities in ASR security. Particularly, our experimental study shows that transfer attacks across ASR models are feasible, even in the absence of knowledge about models (even their types) and training data.
Workings of science
Authors: Yaffe Philip
Published: March 2022

Albert Einstein once said, "The whole of science is nothing more than a refinement of everyday thinking." This thought was echoed by Carl Sagan, who said, "Every kid starts out as a natural-born scientist, and then we beat it out of them." These observations, and those of numerous other intellectual luminaries, strongly suggest that the common distinction made between what is science and non-science, say between physics and history, is more apparent than real. These, of course, are personal opinions based on personal observations This essay explores the intriguing idea that virtually everything is science. It also provides some recent scientific evidence that trying to distinguish between science and non-science is not only fruitless but can also do real harm to individuals and society as a whole.
Recursive Sparse Representation for Identifying Multiple Concurrent Occupants Using Floor Vibration Sensing
Authors: Fagert Jonathon , Mirshekari Mostafa , Zhang Pei , Noh Hae Young
Published: March 2022

In this paper, we present a multiple concurrent occupant identification approach through footstep-induced floor vibration sensing. Identification of human occupants is useful in a variety of indoor smart structure scenarios, with applications in building security, space allocation, and healthcare. Existing approaches leverage sensing modalities such as vision, acoustic, RF, and wearables, but are limited due to deployment constraints such as line-of-sight requirements, sensitivity to noise, dense sensor deployment, and requiring each walker to wear/carry a device. To overcome these restrictions, we use footstep-induced structural vibration sensing. Footstep-induced signals contain information about the occupants' unique gait characteristics, and propagate through the structural medium, which enables sparse and passive identification of indoor occupants. The primary research challenge is that multiple-person footstep-induced vibration responses are a mixture of structurally-codependent overlapping individual responses with unknown timing, spectral content, and mixing ratios. As such, it is difficult to determine which part of the signal corresponds to each occupant. We overcome this challenge through a recursive sparse representation approach based on cosine distance that identifies each occupant in a footstep event in the order that their signals are generated, reconstructs their portion of the signal, and removes it from the mixed response. By leveraging sparse representation, our approach can simultaneously identify and separate mixed/overlapping responses, and the use of the cosine distance error function reduces the influence of structural codependency on the multiple walkers' signals. In this way, we isolate and identify each of the multiple occupants' footstep responses. We evaluate our approach by conducting real-world walking experiments with three concurrent walkers and achieve an average F1 score for identifying all persons of 0.89 (1.3x baseline improvement), and with a 10-person "hybrid" dataset (simulated combination of single-walker real-world data), we identify 2, 3, and 4 concurrent walkers with a trace-level accuracy of 100%, 93%, and 73%, respectively, and observe as much as a 2.9x error reduction over a naive baseline approach.
Design and Evaluation of a Clippable and Personalizable Pneumatic-haptic Feedback Device for Breathing Guidance
Authors: Choi Kyung Yun , ElHaouij Neska , Lee Jinmo , Picard Rosalind W. , Ishii Hiroshi
Published: March 2022

To assist people in practicing mindful breathing and regulate their perceived workload while not disturbing the ongoing foreground task during daily routines, we developed a mobile and personalizable pneumatic-haptic feedback device that provides programmable subtle tactile feedback. The device consists of three soft inflatable actuators embedded with DIY stretchable sensors. We introduce their simple and cost-effective fabrication method. We conducted a technical and user-based evaluation of the device. The user-based evaluation focused on the personalization of the tactile feedback based on users' experience assessed during three pilot studies. Different personalization parameters have been tested, such as two tactile patterns, different levels of intensity and frequency. We collected the participants' self-reports and physiological data. Our results show that the device has the potential of a breathing guide under certain conditions. We provide the main findings and design insights from each study and suggest recommendations for developing an on-body personalizable pneumatic-haptic feedback interface.
Toward Reliable Non-Line-of-Sight Localization Using Multipath Reflections
Authors: Zhang Xianan , Chen Lieke , Feng Mingjie , Jiang Tao
Published: March 2022

The past decade's research in RF indoor localization has led to technologies with decimeter-level accuracy under controlled experimental settings. However, existing solutions are not reliable in challenging environments with rich multipath and various occlusions. The errors can be 3-5 times compared to settings with clear LoS paths. In addition, when the direct path is completely blocked, such approaches would generate wrong location estimates. In this paper, we present NLoc, a reliable non-line-of-sight localization system that overcomes the above limitations. The key innovation of NLoc is to convert multipath reflections to virtual direct paths to enhance the localization performance. To this end, NLoc first extracts reliable multi-dimensional parameters by characterizing phase variations. Then, it models the relation between the target location and the geometric features of multipath reflections to obtain virtual direct paths. Finally, it incorporates novel algorithms to remove random ToF offsets due to lack of synchronization and compensate target orientation that determines the geometric features, for accurate location estimates. We implement NLoc on commercial off-the-shelf WiFi devices. Our experiments in multipath challenged environments with dozens of obstacles and occlusions demonstrate that NLoc outperforms state-of-the-art approaches by 44% at the median and 200% at 90% percentile.
Testing a Drop of Liquid Using Smartphone LiDAR
Authors: Chan Justin , Raghunath Ananditha , Michaelsen Kelly E. , Gollakota Shyamnath
Published: March 2022

We present the first system to determine fluid properties using the LiDAR sensors present on modern smartphones. Traditional methods of measuring properties like viscosity require expensive laboratory equipment or a relatively large amount of fluid. In contrast, our smartphone-based method is accessible, contactless and works with just a single drop of liquid. Our design works by targeting a coherent LiDAR beam from the phone onto the liquid. Using the phone's camera, we capture the characteristic laser speckle pattern that is formed by the interference of light reflecting from light-scattering particles. By correlating the fluctuations in speckle intensity over time, we can characterize the Brownian motion within the liquid which is correlated with its viscosity. The speckle pattern can be captured on a range of phone cameras and does not require external magnifiers. Our results show that we can distinguish between different fat contents as well as identify adulterated milk. Further, algorithms can classify between ten different liquids using the smartphone LiDAR speckle patterns. Finally, we conducted a clinical study with whole blood samples across 30 patients showing that our approach can distinguish between coagulated and uncoagulated blood using a single drop of blood.
Contextual Biases in Microinteraction Ecological Momentary Assessment (μEMA) Non-response
Authors: Ponnada Aditya , Li Jixin , Wang Shirlene , Wang Wei-Lin , Do Bridgette , Dunton Genevieve F. , Intille Stephen S.
Published: March 2022

Ecological momentary assessment (EMA) is used to gather in-situ self-report on behaviors using mobile devices. Microinteraction EMA (μEMA), is a type of EMA where each survey is only one single question that can be answered with a glanceable microinteraction on a smartwatch. Prior work shows that even when μEMA interrupts far more frequently than smartphone-EMA, μEMA yields higher response rates with lower burden. We examined the contextual biases associated with non-response of μEMA prompts on a smartwatch. Based on prior work on EMA non-response and smartwatch use, we identified 10 potential contextual biases from three categories: temporal (time of the day, parts of waking day, day of the week, and days in study), device use (screen state, charging status, battery mode, and phone usage), and activity (wrist motion and location). We used data from a longitudinal study where 131 participants (Mean age 22.9 years, SD = 3.0) responded to μEMA surveys on a smartwatch for at least six months. Using mixed-effects logistic regression, we found that all temporal, activity/mobility, and device use variables had a statistically significant (p<0.001) association with momentary μEMA non-response. We discuss the implication of these results for future use of context-aware μEMA methodology.
Integrating Handcrafted Features with Deep Representations for Smartphone Authentication
Authors: Song Yunpeng , Cai Zhongmin
Published: March 2022

Recent research demonstrates the potential of touch dynamics as a usable and privacy-preserving scheme for smartphone authentication. Most existing approaches rely on handcrafted features since deep models may be vulnerable to behavioral uncertainty due to the lack of consistent semantic information. Toward this end, we propose an approach to integrating handcrafted features into two phases of the deep learning process. On one hand, we present three fine-grained behavior representations by encoding semantic handcrafted features into the raw touch actions. On the other hand, we devise a deep Feature Regularization Net (FRN) architecture to combine the complementary information in both handcrafted and deep features. FRN involves handcrafted features as regularization to guide the learning process of deep features and selectively fuses these two feature types through a feature re-weighting mechanism. Experimental findings demonstrate that FRN outperforms the existing handcrafted or deep features even with smaller training and template sets. The framework also works for SOTA deep models and further boosts the accuracy. Results show that our approach is more reliable to alleviate behavioral variability and is competitively robust to statistical attacks compared with the most effective handcrafted features, suggesting a promising mechanism to improve the effectiveness and usability of behavioral authentication for multi-touch enabled mobile devices.
Down the rabbit hole: Revisiting etymology, epistemology, history and practice of instructional and learning design
Authors: Saçak Begüm , Bozkurt Aras , Wagner Ellen
Published: March 2022

There is a multitude of terminologies in the field of learning and training to refer to how we design and approach learning experiences: two of them being instructional design and learning design. Online searches and forum discussions among practitioners and researchers reveal the confusion surrounding the use of these terms. Both terms have sometimes been used interchangeably, but the fact that there is more than one term implies that both terms might be used to encompass different aspects of the learning and training discipline. The term instructional design has been a commonly used term until recently, but now learning design made its way to the literature and to our practices. But, what exactly do these terms refer to, and what do we mean when we use each of these terms? In this brief review paper, by adopting a holistic approach, the authors aim to ponder these questions from multiple dimensions: etymological, epistemological, historical, and practical perspectives.
Premature Ventricular Contraction Recognition Based on a Deep Learning Approach
Authors: Sarshar Nazanin Tataei , Mirzaei Mohammad
Published: March 2022

Electrocardiogram signal (ECG) is considered a significant biological signal employed to diagnose heart diseases. An ECG signal allows the demonstration of the cyclical contraction and relaxation of human heart muscles. This signal is a primary and noninvasive tool employed to recognize the actual life threat related to the heart. Abnormal ECG heartbeat and arrhythmia are the possible symptoms of severe heart diseases that can lead to death. Premature ventricular contraction (PVC) is one of the most common arrhythmias which begins from the lower chamber of the heart and can cause cardiac arrest, palpitation, and other symptoms affecting all activities of a patient. Nowadays, computer-assisted techniques reduce doctors' burden to assess heart arrhythmia and heart disease automatically. In this study, we propose a PVC recognition based on a deep learning approach using the MIT-BIH arrhythmia database. Firstly, 10 heartbeat and statistical features including three morphological features (RS amplitude, QR amplitude, and QRS width) and seven statistical features are computed for each signal. The extraction process of these features is conducted for 20 s of ECG data that create a feature vector. Next, these features are fed into a convolutional neural network (CNN) to find unique patterns and classify them more effectively. The obtained results prove that our pipeline improves the diagnosis performance more effectively.
Circulating ADAMTS13 Levels Are Associated with an Increased Occurrence of Obstructive Sleep Apnea
Authors: Huang Mengling , Liu Sheng , Liu Shuang , Wen Wanwan , Ning Yu , Jia Yifan , Yang Yunxiao , Jiao Xiaolu , Zheng Weiping , Zhang Ming
Published: March 2022

Background and Aims. Obstructive sleep apnea (OSA) is strongly associated with obesity, metabolic diseases, coronary artery disease (CAD), stroke, hypertension, and other disorders. This study assessed the relationship between circulating a disintegrin and metalloprotease with a thrombospondin type 1 motif, member 13 (ADAMTS13) levels and the presence of OSA. Materials and Methods. This cross-sectional study included a total of 223 patients. We used a powerful high-throughput multiplexed immunobead-based assay to detect circulating levels of ADAMTS13. The associations between circulating ADAMTS13 levels and OSA were evaluated by multivariate logistic regression analysis. Results. Circulating ADAMTS13 levels were significantly elevated in patients with OSA compared with controls (0.8 vs. 2.7 μg/mL, respectively,P<0.001). After adjusting for confounding factors, circulating ADAMTS13 levels were significantly independently associated with the presence of OSA (odds ratio=9.96, 95% confidence interval (CI) =4.11–24.13,P<0.001). Furthermore, circulating ADAMTS13 levels showed discriminatory accuracy in assessing the presence of OSA (area under the curve: 0.87, 95% CI 0.81–0.93,P<0.001). Conclusion. Circulating ADAMTS13 levels were significantly correlated with the presence of OSA. ADAMTS13 may therefore function as a novel biomarker for monitoring the development and progression of OSA.
Rg1 Protects Hematopoietic Stem Cells from LiCl-Induced Oxidative Stress via Wnt Signaling Pathway
Authors: Wang Ziling , Xia Jieyu , Li Jing , Chen Linbo , Chen Xiongbin , Zhang Yanyan , Wang Lu , Wang Yaping
Published: March 2022

Background. Ginsenoside Rg1 is a major component of ginseng with antioxidative and antiaging effects, which is a traditional Chinese medicine. In this study, we investigated the potential spillover and mechanism of action of Rg1 on LiCl-driven hematopoietic stem cell aging. Results. Collect the purified Sca-1+ hematopoietic cells for differentiation ability detection and biochemical and molecular labeling. The experiment found that Rg1 plays an antiaging role in reversing the SA-β-gal staining associated with LiCl-induced hematopoietic stem cell senescence, the increase in p53 and p21 proteins, and sustained DNA damage. At the same time, Rg1 protects hematopoietic cells from the reduced differentiation ability caused by LiCl. In addition, Rg1 increased the excessive inhibition of intracellular GSK-3β protein, resulting in the maintenance of β-catenin protein levels in hematopoietic cells after LiCl treatment. Then, the target gene level of β-catenin can be maintained. Conclusions. Rg1 exerts the pharmacological effect of maintaining the activity of GSK-3β in Sca-1+ hematopoietic cells, enhances the antioxidant potential of cells, improves the redox homeostasis, and thus protects cells from the decline in differentiation ability caused by aging. This study provides a potential therapeutic strategy to reduce stem cell pool failure caused by chronic oxidative damage to hematopoietic stem cells.
Three-Dimensional Optimization Development and Regulation of Land Space Based on Spatial Equilibrium Model
Authors: Zhai Guoliang , Wang Haibo , Zhai Yulu
Published: March 2022

The territorial space development pattern of the target construction should be able to help the full circulation and optimal allocation of social elements and resources, the society in the region is relatively fair, the development opportunities and welfare of people are equal, and the development of people, society, economy, and environment is coordinated and sustainable. This article aims to develop and control the three-dimensional optimization of the land space based on the spatial equilibrium model. This article first analyzes and introduces the spatial equilibrium model, then constructs an evaluation index model for the suitability of territorial spatial three-dimensional optimization development, and determines the index weights for the suitability of territorial spatial three-dimensional optimization development. Then, it analyzes the supply-demand relationship of the three-dimensional optimization development of the territorial space, discusses the imbalance of the supply and demand of the territorial service space, and finally summarizes the overall characteristics of the supply and demand of the three-dimensional optimization development of the territorial space based on the spatial equilibrium model. The research results show that under the conditions of rapid development, some development zones represented by the High-tech Zone in City B are seriously inadequate for industrial land use. In 2020, the proportion of industrial land in the high-tech zone of City B will exceed 17.69% of the 2015 plan. The demand for production space in the development zone is greater than the supply, which will inevitably bring certain pressure to industrial transformation.
RFID Data Analysis and Evaluation Based on Big Data and Data Clustering
Authors: Lv Lihua
Published: March 2022

The era people live in is the era of big data, and massive data carry a large amount of information. This study aims to analyze RFID data based on big data and clustering algorithms. In this study, a RFID data extraction technology based on joint Kalman filter fusion is proposed. In the system, the proposed data extraction technology can effectively read RFID tags. The data are recorded, and the KM-KL clustering algorithm is proposed for RFID data, which combines the advantages of the K-means algorithm. The improved KM-KL clustering algorithm can effectively analyze and evaluate RFID data. The experimental results of this study prove that the recognition error rate of the RFID data extraction technology based on the joint Kalman filter fusion is only 2.7%. The improved KM-KL clustering algorithm also has better performance than the traditional algorithm.
Design and Analysis of a Metamaterial-Inspired Miniaturized Quadband Antenna
Authors: Li Si , Sun Shitao , Mao Yunlong
Published: March 2022

A metamaterial-inspired miniaturized quadband antenna is designed and discussed with a transmission line model to study the theory of miniaturization and multiband in this paper. A conventional printed monopole antenna is assumed as a primary antenna and then surrounded by an array of 4 × 2 interdigital LHMs. The proposed antenna has a compact size of

36
mm
×
24
mm
×
1
mm

, and operates at 2.40–2.55 GHz, 3.02–3.38 GHz, 5.04–5.52 GHz, and 7.08–7.38 GHz. Good gain and omnidirectional radiation patterns are observed in simulations and measurements. A simplified transmission line modal was established to study the reasons for miniaturization and multiband that were brought about by the LHM array. Related results verified the theoretical analysis and indicated that the proposed antenna is a good candidate for wireless communication applications.
Dynamics of Hidden Attractors in Four-Dimensional Dynamical Systems with Power Law
Authors: Khan Zareen A. , Khan Javed , Saifullah Sayed , Ali Amir
Published: March 2022

Four-dimensional continuous chaotic models with Caputo fractional derivative are presented. Fixed point theory is used to investigate the existence and uniqueness of complex systems. The dynamical properties are studied, including the Lyapunov exponent, phase portrait, and time series analysis. The hyperchaotic nature of each system is revealed by the positive exponents. The numerical method is introduced to describe the influence of the order of the Caputo fractional derivative. The phase portraits are presented to investigate the behavior and effect of some key parameters and fractional orders on model dynamics. The systems approach fixed point attractors for fractional-order and increase the visibility of the attractor by decreasing fractional order. This means that a change in fractional order has a significant impact on the dynamics of the models. When the order of the derivative is equal to one, both systems oscillate frequently. However, as the fractional order is reduced, the system oscillations decrease as compared to the integer-order, and the system moves towards its fixed point, reveals the hidden attractors inherent in the system, and enabling it to develop to a stable state more efficiently.
Experimental Study on SHPB Dynamic Mechanical Response in Different Damage Zones of Rock under Blast Load
Authors: Tang Wenda , You Yuanyuan , Hu Feng , Bian Yuanyuan , Xiao Chenglong , Zhu Yijun
Published: March 2022

In this study, the damage characteristics of the slit charge pack along the rock slitting and the vertical slitting directions were investigated using green sandstone as the subject. Split-Hopkinson pressure bar (SHPB) experiments were performed on green sandstone, and the dynamic mechanical properties of rock specimen were analyzed in the slitting and vertical slitting directions. Based on the SHPB experiments of the rock specimens in different damage zones along the rock slitting and the vertical slitting directions combined with the fractal theory, the distribution pattern of rock fracture fragmentation was investigated at different positions in the kerf direction and vertical kerf direction. The results of this study show that the dynamic strength of the rock corresponds to the damage degree of the rock, which is greater in the direction of the slit than that in the perpendicular direction of the slit. In addition, the core at 150 mm distance from the blast hole perpendicular to the slit direction could easily bear the blast loads. The lumpiness distribution of rock specimens under impact load shows good statistical self-similarity. The evolution law of fractal dimension shows that with increasing distance from the core to the blast hole, the fractal dimension of the specimen after failure increases. The fractal dimension of the specimen perpendicular to the slit direction is greater than that of the specimen along the slit direction at the same distance.
Prediction of Pulmonary Fibrosis Based on X-Rays by Deep Neural Network
Authors: Li Da , Liu Zhuo , Luo Lin , Tian Siyu , Zhao Jingyuan
Published: March 2022

As a fatal lung disease, pulmonary fibrosis can cause irreversible damage to the lung, affect normal lung function, and eventually lead to death. At present, the pathogenesis of this kind of disease is not completely clear, and there is no radical cure. The main purpose of the treatment of this disease is to slow down the deterioration of pulmonary fibrosis. For this kind of disease, if it can be found early, it can be treated as soon as possible and the life of patients will be prolonged. Clinically, the diagnosis of pulmonary fibrosis depends on the relevant imaging examination, lung biopsy, lung function examination, and so on. Imaging data such as X-rays is a common examination means in clinical medicine and also plays an important role in the prediction of pulmonary fibrosis. Through X-ray, radiologists can clearly see the relevant lung lesions so as to make the relevant diagnosis. Based on the common medical image data, this paper designs related models to complete the prediction of pulmonary fibrosis. The model designed in this paper is mainly divided into two parts: first, this paper uses a neural network to complete the segmentation of lung organs; second, the neural network of image classification is designed to complete the process from lung image to disease prediction. In the design of these two parts, this paper improves on the basis of previous research methods. Through the design of a neural network with higher performance, more optimized results are achieved on the key indicators which can be applied to the real scene of pulmonary fibrosis prediction.
Performance Assessment of Reinforced Concrete Frame under Close‐In Blast Loading
Authors: Abebe Solomon , Mohammed Tesfaye Alemu
Published: March 2022

The need for assessing and retrofitting structures increased with time as terrorism‐induced explosion trends rose with time. This paper presents a numerical investigation on performance assessment of a two‐story, one‐bay seismic resistant reinforced concrete framed building under close‐in blast loading. ANSYS AUTODYN, an explicit nonlinear finite element software program, was used for 3D model development and analysis. The experimental results reported in the literature were used to validate proposed FE models. Furthermore, parametric studies on close‐in explosive story‐to‐story locations and charge masses were performed on both conventional and seismically detailed RC framed structures. FEA results showed that a decrease in scaled distance raised effective plastic strain and damage index values. Furthermore, simultaneous use of close‐spaced transverse steel reinforcement spacing in mid‐height and ends of reinforced concrete columns is found to be effective in reducing both effective plastic strains and damage index values.
Difference of Farmers’ Livelihood Capital before and after Rural Tourism Development
Authors: Yi Xiao , Xixi Tan , Lu Pan
Published: March 2022

Purpose. To compare the differences in rural household livelihood capital before and after the development of rural tourism to derive factors that affect rural household livelihood capital. Methodology. This study establishes a household livelihood capital index system to determine the total livelihood capital owned by rural households. Findings. After the development of rural tourism, regardless of farmers participating in rural tourism or not participating in rural tourism, their livelihood capital has increased, but the growth rate of livelihood capital of farmers participating in rural tourism is significantly higher than that of non-participating farmers, especially social capital and financial capital. Originality. This study is based on the sustainable livelihood analysis framework developed by DFID, analyzes the characteristics of farmers’ livelihood capital and livelihood activities, and discusses the differences of farmers’ livelihood capital before and after rural tourism development.
Design, Simulation, and Optimization of Polarization-Independent Four-Port Optical Waveguide Circulator Based on a Ferrite Material
Authors: Hashemi Babak , Alizadeh Amir Hamid
Published: March 2022

Optical circulators are used in optical devices such as multiplexers, demultiplexers, and optical routers. Usually, the magnetic material in the center of the circulator conducts light by interacting with the electromagnetic wave. In this research, a polarization-independent four-port optical waveguide circulator with the presence of a rhombus-shaped ferrimagnetic material has been designed, simulated, and optimized in the three-dimensional part of Comsol software. This designed circulator unlike the previous structures has four ports which use the transmission matrix method to conduct waves. By selecting the appropriate size and type of central ferrite, as well as the scale of input and output channels, the most optimal situation is obtained for power transmission with less than 1 dB loss when port 1 is input and port 2 is output.
Antiobesity and Hepatoprotective Effects of Protein Hydrolysates Derived from Protaetia brevitarsis in an Obese Mouse Model
Authors: Lee Eun Hye , Chun So Young , Yoon BoHyun , Han Man-Hoon , Chung Jae-Wook , Ha Yun-Sok , Lee Jun Nyung , Kim Hyun Tae , Kim Dae Hwan , Beik Gyung Yun , Jang Byung Ik , Kwon Tae Gyun , Park Chae-Eun , Lee In-Seon , Kim Bum Soo , Lee Syng-ook
Published: March 2022

Background. Obesity induced by excessive nutrients can cause fatty liver and metabolic dysfunction, which leads to hepatic dysfunction and local/systemic inflammatory responses. Previously, we analyzed the antioxidant, antilipotoxicity, and anti‐inflammatory effects of protein hydrolysates in vitro. The aim of the present study is to investigate the antiobesity and hepatoprotective effects of protein hydrolysates derived from Protaectia brevitas (PHPB) in an obese mouse model. Methods. For this in vivo study, 40 mice were included and divided into four groups: (1) normal diet group, (2) high‐fat‐diet (ctrl(–)) group, (3) high‐fat‐diet and silymarin‐treated (ctrl(+)) group, and (4) high‐fat‐diet and PHPB‐treated group. After 6 weeks of treatment, body weight and the amount of daily food intake were observed. Moreover, the major organs and blood of animals were collected for the analysis of serum chemistry, histopathological examination, and obesity‐ and inflammation‐related gene expressions. Results. The body weight and the amount of daily food intake significantly decreased in the PHPB‐treated group compared with those in the ctrl(–) group. The levels of serum ALT, AST, ALP, creatinine, blood urea nitrogen, glucose, bilirubin, total cholesterol, TG, low‐density lipoprotein, IL‐6, TNF‐α, and IGF‐1 significantly reduced in the PHPB‐treated group, whereas the serum free fatty acid, albumin, high‐density lipoprotein, and adiponectin concentrations increased. In the analysis of weight of the liver, kidney, lungs, spleen, and fat tissues (from epididymal, perirenal, and mesentery tissues), the PHPB‐treated group showed decreased values compared with the ctrl(–) group. In the histopathological analysis, the PHPB‐treated group showed significantly reduced macrovesicular fatty change and inflammatory cell infiltration in the liver, and the size of the adipocyte in the epididymis also significantly decreased. The obesity‐ and inflammation‐related gene (IL‐6, TNF‐α, IGF‐1, leptin, AP2/FABP4, AMPK‐α2, β3AR, and PPAR‐γ) expressions in the liver and epididymal adipose tissue were reduced in the PHPB‐treated group. Conclusions. Overall, the results of this study suggest that the protein hydrolysates that derived from Protaectia brevitas produce antiobesity and hepatoprotective effects via anti‐inflammatory activities.
The Predictability of Cystatin C for Peripheral Arterial Disease in Chinese Population with Type 2 Diabetes Mellitus
Authors: Liu Luna , Wang Hai , Ning Jing , Han Junming , Yu Chunxiao , Guan Qingbo
Published: March 2022

Objectives. Peripheral artery disease (PAD) in diabetic populations is a vital chronic disease all over the world due to its high morbidity and mortality. It is important to find early simple screening biomarkers and find residual risk factors that may provide a new target for prevention and treatment of PAD in diabetic patients besides traditional cardiometabolic risk factors. Methods. We performed a cross-sectional retrospective study, and a total of 1671 T2DM participants were recruited. Receiver operating characteristic analysis, stepwise logistic regression analysis, points score system, and decision curve analysis were performed to assess the risk factors for PAD. Results. The prevalence of PAD in the study was 7.18% (

n
=
120

). Compared to the participants with the lowest quartile of cystatin C (CysC), the risk of developing PAD in participants with the highest quartile of CysC increased 6.339-fold. The CysC was the superior indicators to distinguish participants with PAD from those without PAD, with an AUC of 0.716. Stepwise logistic regression analysis showed that CysC was independent risk factor for PAD besides traditional risk factors. Combined exposure to these traditional risk factors and CysC was associated with a stepwise increase in the risk of developing PAD and even increased 11.976-fold in participants with the highest quintiles of combined exposure score (CES) based on traditional risk factors and CysC compared to the participants with the lowest quintiles of CES. Conclusions. CysC was associated with PAD independent of potential risk factors in diabetic populations. The CysC was a reliable marker for the early screening of PAD in diabetic patients besides traditional cardiometabolic risk factors.
2‐Prime Hyperideals of Multiplicative Hyperrings
Authors: Anbarloei Mahdi
Published: March 2022

Multiplicative hyperrings are an important class of algebraic hyperstructures which generalize rings further to allow multiple output values for the multiplication operation. Let R be a commutative multiplicative hyperring. A proper hyperideal I of R is called 2‐prime if x∘y⊆I for some x, y ∈ R, then, x2⊆I or y2⊆I. The 2‐prime hyperideals are a generalization of prime hyperideals. In this paper, we aim to study 2‐prime hyperideals and give some results. Moreover, we investigate δ‐2‐primary hyperideals which are an expansion of 2‐prime hyperideals.
Bidding Strategy of a Wind-Thermal GENCO considering Piecewise Linear AC Power Flow and Correlated Uncertainties
Authors: Daealhaq Haitham , Falah Hassan Yasser , Ghanimi Hanan , Azimian Mahdi
Published: March 2022

In deregulated electricity markets, generation companies (GENCO) try to maximize their economic benefits considering the electricity demand, transmission network condition, and other participants’ behaviors. The increasing penetration of renewable sources such as wind power generation with intermittent nature poses several challenges to the participation of GENCOs in the electricity market. Thus, this paper presents a stochastic bilevel optimization model to determine the coordinated bidding strategy of a wind-thermal GENCO with the aim of maximizing its profit in the day-ahead and real-time balancing market. Herein, the model aims to maximize the profit of GENCO in the day-ahead and the balancing market in the upper-level problem while minimizing the operation cost of the system in the lower-level problem. The uncertainties of wind power generation and electricity demand are modeled by defining a set of scenarios considering their mutual correlation using the copula technique. Additionally, incorporating AC power flow constraints in the proposed optimization model offers a better solution to the coordinated bidding strategy of the wind-thermal GENCO. Further, the nonlinear AC power flow equations are linearized using the piecewise approximation technique to reduce the computational complexity and enhance the accuracy of the optimal solution. In the end, the developed algorithm is implemented on the IEEE 24-bus RTS, and the simulation results are provided to validate the efficiency and applicability of the proposed coordinated bidding strategy model. The results advocate that the participation of the thermal unit along with the wind farm might mitigate the risk of uncertainties, but it causes an intense increase in the locational marginal price of the system. Importantly, the simulation results indicate the computational efficiency of the model by developing an exact AC power flow model without compromising the results. Notably, it has been found that the profit of the wind-thermal GENCO would be increased by 35.2% employing the copula technique to model the mutual correlation of uncertain parameters.