bluuebunny/crossref_metadata_2025 huggingface dataset:
AI-Based Vehicular Network toward 6G and IoT: Deep Learning Approaches
Authors: Chen Mu-Yen , Fan Min-Hsuan , Huang Li-Xiang
Published: October 2021

In recent years, vehicular networks have become increasingly large, heterogeneous, and dynamic, making it difficult to meet strict requirements of ultralow latency, high reliability, high security, and massive connections for next generation (6G) networks. Recently,
deep learning (DL
) has emerged as a powerful
artificial intelligence (AI
) technique to optimize the efficiency and adaptability of vehicle and wireless communication. However, rapidly increasing absolute numbers of vehicles on the roads are leading to increased automobile accidents, many of which are attributable to drivers interacting with their mobile phones. To address potentially dangerous driver behavior, this study applies deep learning approaches to image recognition to develop an AI-based detection system that can detect potentially dangerous driving behavior. Multiple
convolutional neural network (CNN
)-based techniques including VGG16, VGG19, Densenet, and Openpose were compared in terms of their ability to detect and identify problematic driving.
A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling
Authors: Zhang Weijia , Li Jiuyong , Liu Lin
Published: October 2021

A central question in many fields of scientific research is to determine how an outcome is affected by an action, i.e., to estimate the causal effect or treatment effect of an action. In recent years, in areas such as personalised healthcare, sociology, and online marketing, a need has emerged to estimate heterogeneous treatment effects with respect to individuals of different characteristics. To meet this need, two major approaches have been taken: treatment effect heterogeneity modelling and uplifting modelling. Researchers and practitioners in different communities have developed algorithms based on these approaches to estimate the heterogeneous treatment effects. In this article, we present a unified view of these two seemingly disconnected yet closely related approaches under the potential outcome framework. We provide a structured survey of existing methods following either of the two approaches, emphasising their inherent connections and using unified notation to facilitate comparisons. We also review the main applications of the surveyed methods in personalised marketing, personalised medicine, and sociology. Finally, we summarise and discuss the available software packages and source codes in terms of their coverage of different methods and applicability to different datasets, and we provide general guidelines for method selection.
Towards Augmented Reality Driven Human-City Interaction: Current Research on Mobile Headsets and Future Challenges
Authors: Lee Lik-Hang , Braud Tristan , Hosio Simo , Hui Pan
Published: October 2021

Interaction design for Augmented Reality (AR) is gaining attention from both academia and industry. This survey discusses 260 articles (68.8% of articles published between 2015–2019) to review the field of human interaction in connected cities with emphasis on augmented reality-driven interaction. We provide an overview of Human-City Interaction and related technological approaches, followed by reviewing the latest trends of information visualization, constrained interfaces, and embodied interaction for AR headsets. We highlight under-explored issues in interface design and input techniques that warrant further research and conjecture that AR with complementary Conversational User Interfaces (CUIs) is a crucial enabler for ubiquitous interaction with immersive systems in smart cities. Our work helps researchers understand the current potential and future needs of AR in Human-City Interaction.
Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey
Authors: Roy Satyaki , Ghosh Preetam , Ghosh Nirnay , Das Sajal K.
Published: October 2021

The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.
Machine Learning at the Network Edge: A Survey
Authors: Murshed M. G. Sarwar , Murphy Christopher , Hou Daqing , Khan Nazar , Ananthanarayanan Ganesh , Hussain Faraz
Published: October 2021

Resource-constrained IoT devices, such as sensors and actuators, have become ubiquitous in recent years. This has led to the generation of large quantities of data in real-time, which is an appealing target for AI systems. However, deploying machine learning models on such end-devices is nearly impossible. A typical solution involves offloading data to external computing systems (such as cloud servers) for further processing but this worsens latency, leads to increased communication costs, and adds to privacy concerns. To address this issue, efforts have been made to place additional computing devices at the edge of the network, i.e., close to the IoT devices where the data is generated. Deploying machine learning systems on such edge computing devices alleviates the above issues by allowing computations to be performed close to the data sources. This survey describes major research efforts where machine learning systems have been deployed at the edge of computer networks, focusing on the operational aspects including compression techniques, tools, frameworks, and hardware used in successful applications of intelligent edge systems.
Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality
Authors: Lan Guohao , Liu Zida , Zhang Yunfan , Scargill Tim , Stojkovic Jovan , Joe-Wong Carlee , Gorlatova Maria
Published: October 2021

Mobile Augmented Reality (AR), which overlays digital content on the real-world scenes surrounding a user, is bringing immersive interactive experiences where the real and virtual worlds are tightly coupled. To enable seamless and precise AR experiences, an image recognition system that can accurately recognize the object in the camera view with low system latency is required. However, due to the pervasiveness and severity of image distortions, an effective and robust image recognition solution for “in the wild” mobile AR is still elusive. In this article, we present CollabAR, an edge-assisted system that provides
distortion-tolerant image recognition
for mobile AR with
imperceptible system latency
. CollabAR incorporates both
distortion-tolerant
and
collaborative
image recognition modules in its design. The former enables distortion-adaptive image recognition to improve the robustness against image distortions, while the latter exploits the spatial-temporal correlation among mobile AR users to improve recognition accuracy. Moreover, as it is difficult to collect a large-scale image distortion dataset, we propose a Cycle-Consistent Generative Adversarial Network-based data augmentation method to synthesize realistic image distortion. Our evaluation demonstrates that CollabAR achieves over 85% recognition accuracy for “in the wild” images with severe distortions, while reducing the end-to-end system latency to as low as 18.2 ms.
A Deamortization Approach for Dynamic Spanner and Dynamic Maximal Matching
Authors: Bernstein Aaron , Forster Sebastian , Henzinger Monika
Published: October 2021

Many dynamic graph algorithms have an
amortized
update time, rather than a stronger
worst-case
guarantee. But amortized data structures are not suitable for real-time systems, where each individual operation has to be executed quickly. For this reason, there exist many recent randomized results that aim to provide a guarantee stronger than amortized expected. The strongest possible guarantee for a randomized algorithm is that it is always correct (Las Vegas) and has
high-probability worst-case
update time, which gives a bound on the time for each individual operation that holds with high probability.

In this article, we present the first polylogarithmic high-probability worst-case time bounds for the dynamic spanner and the dynamic maximal matching problem.

(1)

For dynamic spanner, the only known
o
(
n
) worst-case bounds were
O
(
n
3/4
) high-probability worst-case update time for maintaining a 3-spanner and
O
(
n
5/9
) for maintaining a 5-spanner. We give a
O
(1)
k
log
3
(
n
) high-probability worst-case time bound for maintaining a (
2k-1
)-spanner, which yields the first worst-case polylog update time for all constant
k
. (All the results above maintain the optimal tradeoff of stretch
2k-1
and Õ(
n
1+1/k
) edges.)

(2)

For dynamic
maximal
matching, or dynamic 2-approximate maximum matching, no algorithm with
o(n)
worst-case time bound was known and we present an algorithm with
O
(log
5
(
n
)) high-probability worst-case time; similar worst-case bounds existed only for maintaining a matching that was (2+ϵ)-approximate, and hence not maximal.

Our results are achieved using a new approach for converting amortized guarantees to worst-case ones for randomized data structures by going through a third type of guarantee, which is a middle ground between the two above: An algorithm is said to have
worst-case expected
update time ɑ if for
every
update σ, the expected time to process σ is at most ɑ. Although stronger than amortized expected, the worst-case expected guarantee does not resolve the fundamental problem of amortization: A worst-case expected update time of
O(1)
still allows for the possibility that every 1/
f(n)
updates requires ϴ (
f(n)
) time to process, for arbitrarily high
f(n)
. In this article, we present a
black-box
reduction that converts any data structure with worst-case expected update time into one with a high-probability worst-case update time: The query time remains the same, while the update time increases by a factor of
O
(log
2(n)
).

Thus, we achieve our results in two steps: (1) First, we show how to convert existing dynamic graph algorithms with
amortized
expected polylogarithmic running times into algorithms with
worst-case expected
polylogarithmic running times. (2) Then, we use our black-box reduction to achieve the polylogarithmic high-probability worst-case time bound. All our algorithms are Las-Vegas-type algorithms.
Online Resource Provisioning for Wireless Data Collection
Authors: Liu Yu , Comden Joshua , Liu Zhenhua , Yang Yuanyuan
Published: October 2021

Wireless data collection requires a sequence of resource provisioning decisions due to the limited battery capacity of wireless sensors. The corresponding online resource provisioning problem is challenging. Recently, many prediction methods have been proposed that can be used to benefit the performance of various systems through their incorporation. Therefore, in this article, we focus on online resource provisioning problems with short-term predictions motivated by the wireless data collection problem. Specifically, we design separate online algorithms for systems in which the state evolves in either a stationary manner or an arbitrarily determined manner and prove their performance bounds where their bounds improve as the amount of available predictions increases. Additionally, we design a meta-algorithm that can choose which online algorithm to implement at each point in time, depending on the recent behavior of the system environment. The practical performances of the proposed algorithms are corroborated in trace-driven numerical simulations of data collection of shared bikes. Additionally, we show that the performance of our meta-algorithm in various system environments can be better than that of the single best algorithm chosen in hindsight.
A Survey on Blockchain Interoperability: Past, Present, and Future Trends
Authors: Belchior Rafael , Vasconcelos André , Guerreiro Sérgio , Correia Miguel
Published: October 2021

Blockchain interoperability is emerging as one of the crucial features of blockchain technology, but the knowledge necessary for achieving it is fragmented. This fact makes it challenging for academics and the industry to achieve interoperability among blockchains seamlessly. Given this new domain’s novelty and potential, we conduct a literature review on blockchain interoperability by collecting 284 papers and 120 grey literature documents, constituting a corpus of 404 documents. From those 404 documents, we systematically analyzed and discussed 102 documents, including peer-reviewed papers and grey literature. Our review classifies studies in three categories: Public Connectors, Blockchain of Blockchains, and Hybrid Connectors. Each category is further divided into sub-categories based on defined criteria. We classify 67 existing solutions in one sub-category using the Blockchain Interoperability Framework, providing a holistic overview of blockchain interoperability. Our findings show that blockchain interoperability has a much broader spectrum than cryptocurrencies and cross-chain asset transfers. Finally, this article discusses supporting technologies, standards, use cases, open challenges, and future research directions, paving the way for research in the area.
Attack-aware Synchronization-free Data Timestamping in LoRaWAN
Authors: Gu Chaojie , Jiang Linshan , Tan Rui , Li Mo , Huang Jun
Published: October 2021

Low-power wide-area network technologies such as long-range wide-area network (LoRaWAN) are promising for collecting low-rate monitoring data from geographically distributed sensors, in which timestamping the sensor data is a critical system function. This article considers a synchronization-free approach to timestamping LoRaWAN uplink data based on signal arrival time at the gateway, which well matches LoRaWAN’s one-hop star topology and releases bandwidth from transmitting timestamps and synchronizing end devices’ clocks at all times. However, we show that this approach is susceptible to a
frame delay attack
consisting of malicious frame collision and delayed replay. Real experiments show that the attack can affect the end devices in large areas up to about 50,000, m
2
. In a broader sense, the attack threatens any system functions requiring timely deliveries of LoRaWAN frames. To address this threat, we propose a LoRaTS gateway design that integrates a commodity LoRaWAN gateway and a low-power software-defined radio receiver to track the inherent frequency biases of the end devices. Based on an analytic model of LoRa’s chirp spread spectrum modulation, we develop signal processing algorithms to estimate the frequency biases with high accuracy beyond that achieved by LoRa’s default demodulation. The accurate frequency bias tracking capability enables the detection of the attack that introduces additional frequency biases. We also investigate and implement a more crafty attack that uses advanced radio apparatuses to eliminate the frequency biases. To address this crafty attack, we propose a pseudorandom interval hopping scheme to enhance our frequency bias tracking approach. Extensive experiments show the effectiveness of our approach in deployments with real affecting factors such as temperature variations.
Zip Trees
Authors: Tarjan Robert E. , Levy Caleb , Timmel Stephen
Published: October 2021

We introduce the
zip tree
,
1
a form of randomized binary search tree that integrates previous ideas into one practical, performant, and pleasant-to-implement package. A zip tree is a binary search tree in which each node has a numeric rank and the tree is (max)-heap-ordered with respect to ranks, with rank ties broken in favor of smaller keys. Zip trees are essentially treaps [8], except that ranks are drawn from a geometric distribution instead of a uniform distribution, and we allow rank ties. These changes enable us to use fewer random bits per node.

We perform insertions and deletions by unmerging and merging paths (
unzipping
and
zipping
) rather than by doing rotations, which avoids some pointer changes and improves efficiency. The methods of zipping and unzipping take inspiration from previous top-down approaches to insertion and deletion by Stephenson [10], Martínez and Roura [5], and Sprugnoli [9].

From a
theoretical
standpoint, this work provides two main results. First, zip trees require only
O
(log log
n
) bits (with high probability) to represent the largest rank in an
n
-node binary search tree; previous data structures require
O
(log
n
) bits for the largest rank. Second, zip trees are naturally isomorphic to skip lists [7], and simplify Dean and Jones’ mapping between skip lists
Approximation Algorithms for the Bottleneck Asymmetric Traveling Salesman Problem
Authors: An Hyung-Chan , Kleinberg Robert , Shmoys David B.
Published: October 2021

We present the first nontrivial approximation algorithm for the
bottleneck asymmetric traveling salesman problem
. Given an asymmetric metric cost between
n
vertices, the problem is to find a Hamiltonian cycle that minimizes its
bottleneck
(or maximum-length edge) cost. We achieve an
O
(log
n
/ log log
n
) approximation performance guarantee by giving a novel algorithmic technique to shortcut Eulerian circuits while bounding the lengths of the shortcuts needed. This allows us to build on a related result of Asadpour, Goemans, Mądry, Oveis Gharan, and Saberi to obtain this guarantee. Furthermore, we show how our technique yields stronger approximation bounds in some cases, such as the bounded orientable genus case studied by Oveis Gharan and Saberi. We also explore the possibility of further improvement upon our main result through a comparison to the symmetric counterpart of the problem.
Better Distance Preservers and Additive Spanners
Authors: Bodwin Greg , Williams Virginia Vassilevska
Published: October 2021

We study two popular ways to sketch the shortest path distances of an input graph. The first is
distance preservers
, which are sparse subgraphs that agree with the distances of the original graph on a given set of demand pairs. Prior work on distance preservers has exploited only a simple structural property of shortest paths, called
consistency
, stating that one can break shortest path ties such that no two paths intersect, split apart, and then intersect again later. We prove that consistency alone is not enough to understand distance preservers, by showing both a lower bound on the power of consistency and a new general upper bound that polynomially surpasses it. Specifically, our new upper bound is that any
p
demand pairs in an
n
-node undirected unweighted graph have a distance preserver on O(
n
2/3
p
2/3
+
np
1/3
edges. We leave a conjecture that the right bound is
O
(
n
2/3
p
2/3
+
n
) or better.

The second part of this paper leverages these distance preservers in a new construction of
additive spanners
, which are subgraphs that preserve all pairwise distances up to an additive error function. We give improved error bounds for spanners with relatively few edges; for example, we prove that all graphs have spanners on
O(n)
edges with +
O
(
n
3/7 + ε
) error. Our construction can be viewed as an extension of the popular path-buying framework to clusters of larger radii.
Dynamic Mode Decomposition and Its Variants
Authors: Schmid Peter J.
Published: October 2021

Dynamic mode decomposition (DMD) is a factorization and dimensionality reduction technique for data sequences. In its most common form, it processes high-dimensional sequential measurements, extracts coherent structures, isolates dynamic behavior, and reduces complex evolution processes to their dominant features and essential components. The decomposition is intimately related to Koopman analysis and, since its introduction, has spawned various extensions, generalizations, and improvements. It has been applied to numerical and experimental data sequences taken from simple to complex fluid systems and has also had an impact beyond fluid dynamics in, for example, video surveillance, epidemiology, neurobiology, and financial engineering. This review focuses on the practical aspects of DMD and its variants, as well as on its usage and characteristics as a quantitative tool for the analysis of complex fluid processes.
Learning Through Processing: Toward an Integrated Approach to Early Word Learning
Authors: Meylan Stephan C. , Bergelson Elika
Published: October 2021

Children's linguistic knowledge and the learning mechanisms by which they acquire it grow substantially in infancy and toddlerhood, yet theories of word learning largely fail to incorporate these shifts. Moreover, researchers’ often-siloed focus on either familiar word recognition or novel word learning limits the critical consideration of how these two relate. As a step toward a mechanistic theory of language acquisition, we present a framework of “learning through processing” and relate it to the prevailing methods used to assess children's early knowledge of words. Incorporating recent empirical work, we posit a specific, testable timeline of qualitative changes in the learning process in this interval. We conclude with several challenges and avenues for building a comprehensive theory of early word learning: better characterization of the input, reconciling results across approaches, and treating lexical knowledge in the nascent grammar with sufficient sophistication to ensure generalizability across languages and development.
Study on Influence of Cavity and Water Mist on Flame Propagation of Gas Explosion in a Pipeline
Authors: Gu Shicheng , Yuan Shujie , Yan Zhuo , Xu Xiaoxue
Published: October 2021

For studying the influence of the cavity and water mist on the flame propagation of gas explosion, a rectangular steel cavity of size of length

80
 
cm
×
width
 
50
 
cm
×
height
 
20
 
cm

was designed. The influence of the cavity and it with water mist on explosion flame propagation in a large circular gas explosion system with a length of 34 m was studied. The change of gas explosion flame in the pipeline was analyzed. The results showed that the intensity and flame propagation velocity increase after the explosion flame passes through the straight pipeline, and the attenuation rates are 4.93% and -2.48%, respectively. After the explosion flame passes through a rectangular cavity of length

80
 
cm
×
width
 
50
 
cm
×
height
 
20
 
cm

, its intensity and propagation speed are inhibited, and the attenuation rates are 66.58% and 45.26%, respectively. After the explosion flame passes through the rectangular cavity of the size of length

80
 
cm
×
width
 
50
 
cm
×
height
 
20
 
cm

with water mist, the intensity and propagation speed are inhibited much more, and the attenuation rates are 85.09% and 65.85%, respectively. The influence of the cavity with water mist on flame attenuation of gas explosion is better than that of the cavity alone. Based on theoretical analysis, it is concluded that the inhibition influence of the cavity on explosion flame propagation is mainly due to repeated reflection of flame in the cavity, which results in the attenuation of its energy. The inhibition influence of water mist is mainly due to its heat absorption by vaporization.
Preparation of Mesoporous Biochar from Cornstalk for the Chromium (VI) Elimination by Using One-Step Hydrothermal Carbonation
Authors: Wang Chao , Xie Jun , Zheng Mingdong , Zhu Jinbo , Shi Changliang
Published: October 2021

Hydrothermal carbon (HTC) was prepared by the one-step hydrothermal method for Cr (VI) removal from wastewater, which was considered a “green chemistry” method. The specific surface area (SBET) of HTC was 85 m2/g with the pore size in range of 2.0–24.0 nm. FT-IR spectra analysis showed that the HTC had abundant chemical surface functional groups. The influence of adsorption parameters such as pH, HTC dosage, Cr (VI) concentration, and contact time on the removal efficiency of Cr (VI) had been investigated. When the initial concentration was 50 mg/L, pH = 6, amount of adsorbent was 0.2 g/50 ml, and adsorption time was 90 min; the Cr (VI) absorbed rate of HTC reached 98%. Batch adsorption experiments indicated that Cr (VI) adsorption data of HTC fitted the Freundlich isothermal and pseudo-second-order kinetic models. Overall, our findings provide a promising material in treatment of Cr (VI)-rich wastewater and give a clear picture of its application, which is worthy of further study.
Fecal Impaction in the Rectum and Rectosigmoid Colon Secondary to Sunflower Seed Ingestion
Authors: Lyons Alexander , Lee Jamie , Cares Kristen
Published: October 2021

A 35-month-old male who had eaten a bag of sunflower seeds initially presented to the emergency department (ED) with visible seeds in the anus and was discharged home with a stool softener after manual disimpaction. He then returned to the hospital 2 days later, and abdominal radiographs confirmed significant fecal material within the rectum and rectosigmoid colon. After failed oral and rectal laxative therapy attempts, subsequent disimpaction under anesthesia revealed an undigested sunflower seed bezoar in the rectum extending to the distal segment of his sigmoid colon. This case highlights the dangers and possible complications of seed ingestion even in small quantities in children along with the pathophysiology of impaction. This is one of the youngest cases reported in the United States involving the rectum and rectosigmoid colon with a sunflower bezoar.
Experimental Study on the Mining‐Induced Water‐Resistance Properties of Clay Aquicludes and Water Conservation Mining Practices
Authors: Fan Zhenli , Fan Kesong , Liu Zhiguo , Feng Yutong , Wei Hua , Zhou Yunsen
Published: October 2021

The Yushen mining area contains thin bedrock and a shallow buried coal seam, where JingLe group Hipparion clay and Lishi loess serve as a high‐quality cement insulation cover. This study investigates the properties of the clay layer to determine the effect of the clay aquiclude on the mining water variation and fracture characteristics. Unloading hydraulic jack experiments were performed to test the physical and mechanical properties of the clay layer and the structure was analyzed in detail. The experimental results show that mining affects the soil cracks, leading to crack opening and subsequent bridging. The permeability coefficient of the soil layer initially increases with increased unloading and then decreases. A theoretical model is developed to determine the recovery mechanism of the clay layer water insulation based on the spatial movement of the clay. The results indicate the formation of a waterproof cover type of coal mud protection. Design methods are proposed to optimize the coal pillar size. Mining damage leads to the formation of a mud‐covered bridge belt, which can be designed to appropriately reduce the protective layer thickness. The model is applied to the Hao Jialiang 2301 working face. The results provide important insight on the variation characteristics of the mining water insulation in clay layers and an important reference for accurately calculating the size parameters of waterproof protective coal pillars under mud‐cap conditions to increase the upper mining limit of the working face.
Assessment of the Temporal and Spatial Variation of the Mercury Content of Lake Nokoué in Southern Benin Republic (West Africa)
Authors: Adounkpe Julien G. , Azon N. B. Nadia , Dégila Hermione W. , Hounkpe Peace , Amoussou Robertson
Published: October 2021

Anthropogenic input of mercury into watersheds is becoming increasingly noticeable and is the cause of fishery products contamination. This had led to the Convention of Minamata signed and ratified by the vast majority of the countries in the world. Lake Nokoué in Benin Republic, the most fishery products provider in West Africa, is subject to mercury pollution. The health threat to both the benthic and the consumers of the fishery products from this lake has to be anticipated by precisely determining the dynamics of mercury contamination of the waters and sediments of Lake Nokoué, taking into account the anthropogenic contribution. Water and sediment samples were collected on 23 sites twice a month for four sampling campaigns. Parameters such as pH, salinity, COD, and SS are evaluated in the water. The assessment of total mercury is conducted by cold vapor atomic absorption according to the US EPA 7473 method, using a direct mercury analyzer (DMA-80). On average, the mercury content in Lake Nokoué water is 0.43 ± 0.57 μg/kg. Its variation is linked not only to the seasonal variation but also to that of the suspended matter. South of the lake, the sediments are extremely polluted (5 ≤ Igeo) and present a risk of frequent effects for the benthic species present.
A Nonlinear Calibration Method Based on Sinusoidal Excitation and DFT Transformation for High‐Precision Power Analyzers
Authors: Zhou Wenjian , Yang Sheng , Wang Li , Sheng Hanmin , Deng Yang
Published: October 2021

For most high‐precision power analyzers, the measurement accuracy may be affected due to the nonlinear relationship between the input and output signal. Therefore, calibration before measurement is important to ensure accuracy. However, the traditional calibration methods usually have complicated structures, cumbersome calibration process, and difficult selection of calibration points, which is not suitable for situations with many measurement points. To solve these issues, a nonlinear calibration method based on sinusoidal excitation and DFT transformation is proposed in this paper. By obtaining the effective value data of the current sinusoidal excitation from the calibration source, the accurate calibration process can be done, and the calibration efficiency can be improved effectively. Firstly, through Fourier transform, the phase value at the initial moment of the fundamental frequency is calculated. Then, the mapping relationship between the sampling value and the theoretical calculation value is established according to the obtained theoretical discrete expression, and a cubic spline interpolation method is used to further reduce the calibration error. Simulations and experiments show that the calibration method presented in this paper achieves high calibration accuracy, and the results are compensation value after calibration with a deviation of ±3 × 10−4.
circFAM160A2 Promotes Mitochondrial Stabilization and Apoptosis Reduction in Osteoarthritis Chondrocytes by Targeting miR‐505‐3p and SIRT3
Authors: Bao Jiapeng , Lin Changjian , Zhou Xing , Ma Diana , Ge Lujie , Xu Kai , Moqbel Safwat Adel Abdo , He Yuzhe , Ma Chiyuan , Ran Jisheng , Wu Lidong
Published: October 2021

Competitive endogenous RNAs (ceRNAs), as a newly identified regulating mechanism, have been demonstrated to play a crucial role in various human diseases. An increasing number of recent studies have revealed that circular RNAs (circRNAs) can function as ceRNAs. However, little is known about the role of circFAM160A2 in the pathological process of osteoarthritis (OA). This study is the first to examine the crucial role of the circFAM160A2‐miR‐505‐3p‐SIRT3 axis in osteoarthritis progression. miR‐505‐3p was selected from the interaction of a microRNA (miRNA) microarray comparing chondrocytes in OA and normal conditions and prediction results from TargetScan. RT‐qPCR was performed to assess the expression of circFAM160A2, miR‐505‐3p, and SIRT3. A dual luciferase assay was used to validate the binding of circFAM160A2, miR‐505‐3p, and SIRT3. We used lentivirus and adeno‐associated virus to establish in vitro and in vivo overexpression models. Western blotting, apoptosis assay, ROS detection assay, Safranin O staining, and CCK‐8 assay were employed to assess the role of circFAM160A2, miR‐505‐3p, and SIRT3. We found that miR‐505‐3p was upregulated and circFAM160A2 was downregulated in OA. While overexpression of circFAM160A2 decreased the production of extracellular matrix (ECM) degrading enzymes and ameliorated chondrocyte apoptosis and mitochondrial dysfunction, inhibition of miR‐505‐3p could reverse the protective effect of circFAM160A2 on the OA phenotype both in vitro and in vivo. In conclusion, circFAM160A2 can promote mitochondrial stabilization and apoptosis reduction in OA chondrocytes by targeting miR‐505‐3p and SIRT3, which might be a potential therapeutic target for OA therapy.
Network Pharmacology-Based Study of the Underlying Mechanisms of Huangqi Sijunzi Decoction for Alzheimer’s Disease
Authors: Zhang Wei , Lv Mingti , Shi Yating , Mu Yonghui , Yao Zhaoyang , Yang Zhijun
Published: October 2021

Background. Huangqi Sijunzi decoction (HQSJZD) is a commonly used conventional Chinese herbal medicine prescription for invigorating Qi, tonifying Yang, and removing dampness. Modern pharmacology and clinical applications of HQSJZD have shown that it has a certain curative effect on Alzheimer’s disease (AD). Methods. The active components and targets of HQSJZD were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The genes corresponding to the targets were retrieved using UniProt and GeneCard database. The herb-compound-target network and protein-protein interaction (PPI) network were constructed by Cytoscape. The core targets of HQSJZD were analysed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HQSJZD were docked with acetylcholinesterase (AChE). In vitro experiments were conducted to detect the inhibitory and neuroprotective effects of AChE. Results. Compound-target network mainly contained 132 compounds and 255 corresponding targets. The main compounds contained quercetin, kaempferol, formononetin, isorhamnetin, hederagenin, and calycosin. Key targets contained AChE, PTGS2, PPARG, IL-1B, GSK3B, etc. There were 1708 GO items in GO enrichment analysis and 310 signalling pathways in KEGG, mainly including the cAMP signalling pathway, the vascular endothelial growth factor (VEGF) signalling pathway, serotonergic synapses, the calcium signalling pathway, type II diabetes mellitus, arginine and proline metabolism, and the longevity regulating pathway. Molecular docking showed that hederagenin and formononetin were the top 2 compounds of HQSJZD, which had a high affinity with AChE. And formononetin has a good neuroprotective effect, which can improve the oxidative damage of nerve cells. Conclusion. HQSJZD was found to have the potential to treat AD by targeting multiple AD-related targets. Formononetin and hederagenin in HQSJZD may regulate multiple signalling pathways through AChE, which might play a therapeutic role in AD.
Elevated Natural Killer Cell-Mediated Cytotoxicity Is Associated with Cavity Formation in Pulmonary Tuberculosis Patients
Authors: Li Shanshan , Wang Dongpo , Wei Panjian , Liu Rongmei , Guo Jidong , Yang Bin , Zhang Hongtao , Lu Jie , Gao Mengqiu , Pang Yu
Published: October 2021

Cavitation is a major pathological feature of pulmonary tuberculosis (TB). The study is aimed at investigating the mechanism of natural killer (NK) cells participating the cavity formation during Mycobacterium tuberculosis (MTB) infection. Human peripheral blood samples were donated by pulmonary TB patients with cavity or not. Real-time quantitative PCR and enzyme-linked immunosorbent assay were performed to analyze the expression of cytokines secreted by NK cells. And the cytotoxicity of NK cells was compared between two groups. Our data showed that NK cells were more abundant in cohorts of cavity. Increased abundance of granzyme A and granzyme B was observed in culture supernatants of NK cells isolated from cavitary TB patients, which also resulted in a higher level of nonviable MTB-infected monocytes. Our data firstly demonstrates that NK cells participate in cavity formation in pulmonary TB patients. The elevated level and increased cytotoxicity of NK cells accelerate the cavitary formulation.
Genomic and Transcriptomic Analysis of Relapsed and Refractory Childhood Solid Tumors Reveals a Diverse Molecular Landscape and Mechanisms of Immune Evasion
Authors: Byron Sara A. , Hendricks William P.D. , Nagulapally Abhinav B. , Kraveka Jacqueline M. , Ferguson William S. , Brown Valerie I. , Eslin Don E. , Mitchell Deanna , Cornelius Albert , Roberts William , Isakoff Michael S. , Oesterheld Javier E. , Wada Randal K. , Rawwas Jawhar , Neville Kathleen , Zage Peter E. , Harrod Virginia L. , Bergendahl Genevieve , VanSickle Elizabeth , Dykema Karl , Bond Jeffrey , Chou Hsien-Chao , Wei Jun S. , Wen Xinyu , Reardon Hue V. , Roos Alison , Nasser Sara , Izatt Tyler , Enriquez Daniel , Hegde Apurva M. , Cisneros Faith , Christofferson Austin , Turner Bryce , Szelinger Szabolcs , Keats Jonathan J. , Halperin Rebecca F. , Khan Javed , Saulnier Sholler Giselle L. , Trent Jeffrey M.
Published: October 2021

Children with treatment-refractory or relapsed (R/R) tumors face poor prognoses. As the genomic underpinnings driving R/R disease are not well defined, we describe here the genomic and transcriptomic landscapes of R/R solid tumors from 202 patients enrolled in Beat Childhood Cancer Consortium clinical trials. Tumor mutational burden (TMB) was elevated relative to untreated tumors at diagnosis, with one-third of tumors classified as having a pediatric high TMB. Prior chemotherapy exposure influenced the mutational landscape of these R/R tumors, with more than 40% of tumors demonstrating mutational signatures associated with platinum or temozolomide chemotherapy and two tumors showing treatment-associated hypermutation. Immunogenomic profiling found a heterogenous pattern of neoantigen and MHC class I expression and a general absence of immune infiltration. Transcriptional analysis and functional gene set enrichment analysis identified cross-pathology clusters associated with development, immune signaling, and cellular signaling pathways. While the landscapes of these R/R tumors reflected those of their corresponding untreated tumors at diagnosis, important exceptions were observed, suggestive of tumor evolution, treatment resistance mechanisms, and mutagenic etiologies of treatment.

Significance:

Tumor heterogeneity, chemotherapy exposure, and tumor evolution contribute to the molecular profiles and increased mutational burden that occur in treatment-refractory and relapsed childhood solid tumors.
Oncogenic Activity of Glucocorticoid Receptor β Is Controlled by Ubiquitination-Dependent Interaction with USP49 in Glioblastoma Cells
Authors: Hu Yaling , Jiang Yingdi , Zhang Zhenhao , Wang Jingjing , Zhang Bo , Gong Lingli , Ji Li , Pu Zhening , Yang Xusheng , Zou Jian , Yin Ying
Published: October 2021

Previous studies have demonstrated that glucocorticoid receptor β (GRβ) functions as an oncoprotein, regulating the malignant phenotypes and stem-like cell maintaining in human glioblastoma (GBM). Of the glucocorticoid receptor (GR) isoforms, GRβ and GRα are highly homologous, though the mechanism underlying the distinct functions of these two isoforms in GBM has not been clarified. Here by establishing a carboxyl-terminal (COOH-terminal) deletion mutant, we determined that GRβ can be ubiquitinated. We also found that its COOH terminal is essential for this ubiquitination. The mutation of a lysine to arginine at residue 733 (K733R) blocked the ubiquitination of GRβ, indicating that K733 is a key site for ubiquitination. Using K733R to establish nonubiquitinated GRβ, we demonstrated that ubiquitination not only regulates the stability and nuclear translocation of GRβ, but is also a vital mechanism for its oncogenic functions in vitro and in vivo. Protein interaction assay further indicated that ubiquitin-specific protease 49 (USP49) is a GRβ-binding protein and the interaction depends on GRβ ubiquitination. USP49 knockdown resulted in a decrease of cell proliferation, invasion, and an increase of cell apoptosis. More importantly, USP49 knockdown increased ubiquitination and amplified the oncogenic effects of GRβ, confirming the decisive role of ubiquitination on GRβ carcinogenicity. Taken together, these findings established that ubiquitination is a vial process for GRβ the execution of oncogenic functions in GBM and that the K733 site is crucial for ubiquitination of GRβ.

Implications:

This work is the first identify of the activation GRβ by a single lysine point-mediated ubiquitination and proteasome degradation, which determines its oncogenic functions in GBM.
GLI3 Is Stabilized by SPOP Mutations and Promotes Castration Resistance via Functional Cooperation with Androgen Receptor in Prostate Cancer
Authors: Burleson Marieke , Deng Janice J. , Qin Tai , Duong Thu Minh , Yan Yuqian , Gu Xiang , Das Debodipta , Easley Acarizia , Liss Michael A. , Yew P. Renee , Bedolla Roble , Kumar Addanki Pratap , Huang Tim Hui-Ming , Zou Yi , Chen Yidong , Chen Chun-Liang , Huang Haojie , Sun Lu-Zhe , Boyer Thomas G.
Published: October 2021

Although the Sonic hedgehog (SHH) signaling pathway has been implicated in promoting malignant phenotypes of prostate cancer, details on how it is activated and exerts its oncogenic role during prostate cancer development and progression is less clear. Here, we show that GLI3, a key SHH pathway effector, is transcriptionally upregulated during androgen deprivation and posttranslationally stabilized in prostate cancer cells by mutation of speckle-type POZ protein (SPOP). GLI3 is a substrate of SPOP-mediated proteasomal degradation in prostate cancer cells and prostate cancer driver mutations in SPOP abrogate GLI3 degradation. Functionally, GLI3 is necessary and sufficient for the growth and migration of androgen receptor (AR)–positive prostate cancer cells, particularly under androgen-depleted conditions. Importantly, we demonstrate that GLI3 physically interacts and functionally cooperates with AR to enrich an AR-dependent gene expression program leading to castration-resistant growth of xenografted prostate tumors. Finally, we identify an AR/GLI3 coregulated gene signature that is highly correlated with castration-resistant metastatic prostate cancer and predictive of disease recurrence. Together, these findings reveal that hyperactivated GLI3 promotes castration-resistant growth of prostate cancer and provide a rationale for therapeutic targeting of GLI3 in patients with castration-resistant prostate cancer (CRPC).

Implications:

We describe two clinically relevant mechanisms leading to hyperactivated GLI3 signaling and enhanced AR/GLI3 cross-talk, suggesting that GLI3-specific inhibitors might prove effective to block prostate cancer development or delay CRPC.
Coletânea de discursos de Malcolm X
Authors: Little Malcolm X
Published: October 2021

Em tempos em que a luta contra o Racismo é imprescindível e urgente, os discursos de Malcolm X demarcam um período de luta importante de um homem revertido ao Islam, que após o seu Hajj (peregrinação a Meca) amplia sua perspectiva sobre o humano e sobre a sua luta que não era contra homens brancos, e sim, contra homens que exploram outros homens. Passou a ser conhecido entre os muçulmanos como Al Hajj Malik Al-Shabazz (1925-1965), distinção dada a toda pessoa que faz o Hajj. Mais conhecido como Malcolm X, foi um ativista norte-americano, um dos mais polêmicos e populares líderes do movimento pelos direitos civis dos negros nos Estados Unidos. Fundou a Organização para a Unidade Afro-Americana, de inspiração separatista. Defensor dos direitos dos afro-americanos, conseguiu mobilizar brancos e negros na conscientização sobre os crimes cometidos contra a população afro-americana. Em 1998, Paul Gray, da revista Time, colocou a Autobiografia de Malcolm X entre os 10 livros de não-ficção mais importantes do século XX.
Worsened Tricuspid Regurgitation Following Pericardiectomy for Constrictive Pericarditis
Authors: Tabucanon Ray S. , Wang Tom Kai Ming , Chetrit Michael , Furqan Muhammad M. , Chan Nicholas , Pande Amol , Jellis Christine L. , Cremer Paul C. , Kwon Deborah H. , Johnston Douglas , Klein Allan L.
Published: October 2021

Background:

Worsening tricuspid regurgitation (TR) severity may occur after pericardiectomy surgery for constrictive pericarditis patients; however, its mechanisms and predictors are not well established. We evaluated the clinical characteristics, associated factors, and outcomes of worsening TR after pericardiectomy.

Methods:

Consecutive patients undergoing pericardiectomy for constrictive pericarditis without tricuspid valve surgery and with pre- and postoperative echocardiography available during 2000 to 2017 were retrospectively studied. Clinical, imaging, hemodynamic, and mortality characteristics were analyzed by those with and without worsening TR by at least one grade.

Results:

Among 381 patients (age 61 [17] years, 318 [83.5%] male), 193 (50.7%) had worsening TR post-operatively, and 75 died during the 2.5 (5.4) years follow-up. In univariable analysis, worsening TR was associated with a history of congestive heart failure (47.2% versus 31.9%,
P
=0.003), increased left atrial volume indexed (23 versus 20 mL/m
2
,
P
=0.020), reduced right ventricular fractional area change (47% versus 54%,
P
<0.001), and worsening mitral regurgitation (39.7% versus 16.6%,
P
<0.001). Worsened TR had a trend toward reduced survival during follow-up (log-rank
P
=0.080), especially those with worsened TR but no recovery of TR grade on subsequent echocardiography within the first year compared with those without worsened TR (log-rank
P
=0.02). In multivariable analysis, right ventricular fractional area change, left atrial volume indexed, left ventricular mass indexed, pulmonary artery systolic pressure, and right atrial pressure/pulmonary capillary wedge pressure ratio were most associated with worsened TR, while blood urea nitrogen, hematocrit, lateral and medial e’ tissue Doppler and heart rate were most associated with mortality during follow-up.

Conclusions:

Worsening TR severity was prevalent after pericardiectomy and had a trend toward reduced survival, especially if TR severity did not recover on subsequent echocardiography. Presence of parameters associated with worsened TR and reduced survival should alert clinicians to carefully manage these patients during follow-up.
A new species Lappula botschantzevii (Boraginaceae) from the Northern Africa
Authors: OVCZINNIKOVA SVETLANA
Published: October 2021

A new species, Lappula botschantzevii, is described from the desert zone of North-Western Africa. The new species belongs to the section Lappula and is close to the species L. patula, from which it differs in a smaller corolla, a scorpioid inflorescence (bilateral flowers) with loosely spaced flowers, a heteromorphic coenobium with two types of eremocarps: A) winged with glochids and a large number of spines along the edges of the disc of eremocarps and B) with a second short row of spines. The species is described based on samples from collections housed in three herbaria: Herbarium of the Komarov Botanical Institute RAS, Sankt-Peterburg (LE, Russia) and Muséum National d ‘Histoire Naturelle, Paris (P, France), Université de Montpellier (MPU). It is named after the Russian botanist Viktor Petrovich Botschantzev, who spent many years studying the flora of Africa and who collected samples of the new species. The absence of holotypes required the typification of the names of the studied species Lappula patula, L. capensis and L. eckloniana.