bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting the Pore-Pressure and Temperature of Fire-Loaded Concrete by a Hybrid Neural Network
Authors: Zhang Yiming , Gao Zhiran , Wang Xueya , Liu Qi
Published: March 2022

Fire-loaded concrete structures may experience explosive spalling, i.e., violent splitting of concrete pieces from the heated surfaces, greatly jeopardizing the load carrying capacity and durability. Spalling is closely correlated with the evolution and distribution of pore-pressure [Formula: see text] and temperature [Formula: see text] in heated concrete. Conventionally complicated thermo-hydro-chemical (THC) models are necessary for capturing this information. In this work, we proposed a hybrid neural network for quickly obtaining [Formula: see text], [Formula: see text] of heated concrete. The neural network includes two parts: (i) a well-established autoencoder (AE) and (ii) a fully connected neural network (FNN). A strongly coupled THC model was first used to provide large amounts of results represented by thousands RGB images. The AE was used to condense the images into characteristic vectors, which were used for training the FNN. After training, the FNN can be used for predicting the corresponding characteristic vectors considering different concrete properties, moisture and fire loadings. Then the decoder of the AE is used to translate the characteristic vectors into RGB images, storing the information of [Formula: see text] and [Formula: see text]. Numerical tests indicate the effectiveness and reliability of the proposed model.
QUO VADIS BUSINESS MODEL INNOVATION? BMI STATUS, DEVELOPMENT, AND RESEARCH IMPLICATIONS
Authors: WIRTZ BERND , MÜLLER WILHELM M. , LANGER PAUL F.
Published: March 2022

Driven by technological progress, new market trends, and deregulation, business model innovations (BMI) are becoming increasingly important for entrepreneurs, established companies, and corresponding researchers. Against the background of the vast number of current studies and research reviews and a resulting lack of oversight, this study aims to systematically analyse previous literature studies on BMI to find out which and to what extent specific BMI research topics are considered. This novel meta-literature study provides a systematic analysis of 34 selected review studies by comparing their research approach, focus and findings, citation success, and open research questions. In this context, 12 key areas could be derived, which can be grouped under the following headings: BMI definitions and terminology, BMI determinants, BMI configurations and processes, and BMI outcomes and impacts. The systematic and detailed analysis of the studies allows conclusions to be drawn about identified research gaps and helps to derive recommendations for future research and practical developments in the field of BMI.
Online shopping behavior analysis for smart business using big data analytics and blockchain security
Authors: Wei Weiwei , Sivaparthipan C. B. , Kumar Priyan Malarvizhi
Published: March 2022

Technological advancement in a modern environment is approaching universality. The realm and uses of information technology (IT) and Blockchain Security have been extensively broadened. Any business wishing to boost its market prospects would certainly keep records of the perspectives and behaviors of its consumers. The firms employ advanced technological concepts, skills, and methods to comprehend their applicants. Additional information and facts are analyzed to improve judgment. Business analytics and Blockchain Security professionals have a positive opinion. Online shopping behavior analysis (OSBA) is proposed in this research. It addresses a smooth transition from a prediction method to a gradual information strategy that learns the clients’ needs and achieves their electronic trading revenues. Any commercial enterprise must have limitless entry to information. That contains population revenues, industrial patterns, competition and customer information, productivity measurements, computations, and much more. Corporate information has a significant role in this undertaking. Experimental information is collected periodically to evaluate the evidence and provide fresh discoveries and operations that provide fresh perspectives. The major consideration principal element assessment approach is utilized with big data analytics, Blockchain Security, and fuzzy interference system to assess the essential purchasing variables for customers. It achieves an accuracy of 89% and an [Formula: see text] score of 87%. Models like support vector machine, convolutional neural network, deep neural network, random forest, fuzzy logic, and decision tree (DT) are compared with the OSBA model’s simulation results (DT). Fuzzy interference, big data, and Blockchain Security analytics improve the OSBA model’s performance.
Doing More with Less: Overcoming Data Scarcity for POI Recommendation via Cross-Region Transfer
Authors: Gupta Vinayak , Bedathur Srikanta
Published: March 2022

Variability in social app usage across regions results in a high skew of the quantity and the quality of check-in data collected, which in turn is a challenge for effective location recommender systems. In this article, we present

Axolotl

(
Automated
cross
Location-network Transfer Learning
), a novel method aimed at transferring location preference models learned in a data-rich region to significantly boost the quality of recommendations in a data-scarce region.
Axolotl
predominantly deploys two channels for information transfer: (1) a
meta-learning
based procedure learned using location recommendation as well as social predictions, and (2) a
lightweight
unsupervised cluster-based transfer across users and locations with similar preferences. Both of these work together synergistically to achieve improved accuracy of recommendations in data-scarce regions without any prerequisite of overlapping users and with minimal fine-tuning. We build
Axolotl
on top of a
twin graph-attention
neural network model used for capturing the user- and location-conditioned influences in a user-mobility graph for each region. We conduct extensive experiments on 12 user mobility datasets across the US, Japan, and Germany, using three as
source
regions and nine of them (that have much sparsely recorded mobility data) as
target
regions. Empirically, we show that
Axolotl
achieves up to 18% better recommendation performance than the existing state-of-the-art methods across all metrics.
Toward Understanding Playful Beverage-based Gustosonic Experiences
Authors: Wang Yan , Li Zhuying , Khot Rohit Ashok , Mueller Florian 'Floyd'
Published: March 2022

Recent advances in interactive technology are being used to enrich our interactions around food and drinks. Making use of sound to enrich dining - providing "gustosonic" experiences - has recently garnered interest as an exciting area of ubiquitous computing. However, these experiences have tended to focus on eating. In response to the lack of drinking-focused experiences, we explore the combining playful design and drinking activities so as to allow users to experience playful personalized sounds via drinking through "Sonic Straws". We present the findings of an in-the-wild study that highlights how our system supported self-expression via playful drinking actions, facilitated pleasurable social drinking moments, and promoted reflection on drinking practices. We discuss the implications of this work for designers of future gustosonic experiences, including how to amplify entertainment experiences around drinking/eating, how to highlight the joy coming from multisensory experiences, and how to facilitate mindful engagement with what one drinks. Ultimately, we aim to contribute to the enrichment of dining experiences through playful design.
SkillFence
Authors: Hooda Ashish , Wallace Matthew , Jhunjhunwalla Kushal , Fernandes Earlence , Fawaz Kassem
Published: March 2022

Voice assistants are deployed widely and provide useful functionality. However, recent work has shown that commercial systems like Amazon Alexa and Google Home are vulnerable to voice-based confusion attacks that exploit design issues. We propose a systems-oriented defense against this class of attacks and demonstrate its functionality for Amazon Alexa. We ensure that only the skills a user intends execute in response to voice commands. Our key insight is that we can interpret a user's intentions by analyzing their activity on counterpart systems of the web and smartphones. For example, the Lyft ride-sharing Alexa skill has an Android app and a website. Our work shows how information from counterpart apps can help reduce dis-ambiguities in the skill invocation process. We build SkilIFence, a browser extension that existing voice assistant users can install to ensure that only legitimate skills run in response to their commands. Using real user data from MTurk (N = 116) and experimental trials involving synthetic and organic speech, we show that SkillFence provides a balance between usability and security by securing 90.83% of skills that a user will need with a False acceptance rate of 19.83%.
ARticulate
Authors: Clark Meghan , Newman Mark W. , Dutta Prabal
Published: March 2022

Smart space technologies have entered the mainstream home market. Most users currently interact with smart homes that they (or an acquaintance) have set up and know well. However, as these technologies spread to commercial or public environments, users will need to frequently interact with unfamiliar smart spaces where they are unaware of the available capabilities and the system maintainer will not be present to help. Users will need to quickly and independently 1) discover what is and is not possible, and 2) make use of available functionality. Widespread adoption of smart space systems will not be possible until this discoverability issue is solved. We design and evaluate ARticulate, an interface that allows users to have successful smart space interactions with an intelligent assistant while learning transferable information about the overall set of devices in an unfamiliar space. Our method of using Snapchat-like contextual photo messages enhanced by two technologies---augmented reality and autocomplete---allows users to determine available functionality and achieve their goals in one attempt with a smart space they have never seen before, something no existing interface supports. The ability to easily operate unfamiliar smart spaces improves the usability of existing systems and removes a significant obstacle to the vision of ubiquitous computing.
Battery-free MakeCode
Authors: Kraemer Christopher , Guo Amy , Ahmed Saad , Hester Josiah
Published: March 2022

Hands-on computing has emerged as an exciting and accessible way to learn about computing and engineering in the physical world for students and makers of all ages. Current end-to-end approaches like Microsoft MakeCode require tethered or battery-powered devices like a micro:bit, limiting usefulness and applicability, as well as abdicating responsibility for teaching sustainable practices. Unfortunately, energy harvesting computing devices are usually only programmable by experts and require significant supporting toolchains and knowledge across multiple engineering and computing disciplines to work effectively. This paper bridges the gap between sustainable computing efforts, the maker movement, and novice-focused programming environments with MakeCode-Iceberg, a set of compiler extensions to Microsoft's open-source MakeCode project. The extensions automatically and invisibly transform user code in any language supported (Blocks, JavaScript, Python)into a version that can safely and correctly execute across intermittent power failures caused by unreliable energy harvesting. Determining where, when, and what to save in a checkpoint on limited energy, time, and hardware budget is challenging. We leverage the unique intermediate representation of the MakeCode source-to-source compiler to design and deploy various checkpointing techniques. Our approach allows us to provide, for the first time, a fully web-based and toolchain-free environment to program intermittent computing devices, making battery-free operation accessible to all. We demonstrate new use cases with multiple energy harvesters, peripherals, and application domains: including a Smart Terrarium, Step Counter, and Combination Lock. MakeCode-Iceberg provides sustainable hands-on computing opportunities to a broad audience of makers and learners, democratizing access to energy harvesting and battery-free embedded systems.
Placement Matters
Authors: Wang Xuanzhi , Niu Kai , Xiong Jie , Qian Bochong , Yao Zhiyun , Lou Tairong , Zhang Daqing
Published: March 2022

WiFi-based contactless sensing has found numerous applications in the fields of smart home and health care owning to its low-cost, non-intrusive and privacy-preserving characteristics. While promising in many aspects, the limited sensing range and interference issues still exist, hindering the adoption of WiFi sensing in real world. In this paper, inspired by the SNR (signal-to-noise ratio) metric in communication theory, we propose a new metric named SSNR (sensing-signal-to-noise-ratio) to quantify the sensing capability of WiFi systems. We theoretically model the effect of transmitter-receiver distance on sensing coverage. We show that in LoS scenario, the sensing coverage area increases first from a small oval to a maximal one and then decreases. When the transmitter-receiver distance further increases, the coverage area is separated into two ovals located around the two transceivers respectively. We demonstrate that, instead of applying complex signal processing scheme or advanced hardware, by just properly placing the transmitter and receiver, the two well-known issues in WiFi sensing (i.e., small range and severe interference) can be greatly mitigated. Specifically, by properly placing the transmitter and receiver, the coverage of human walking sensing can be expanded by around 200%. By increasing the transmitter-receiver distance, a target's fine-grained respiration can still be accurately sensed with one interferer sitting just 0.5 m away.
Estimating 3D Finger Angle via Fingerprint Image
Authors: He Ke , Duan Yongjie , Feng Jianjiang , Zhou Jie
Published: March 2022

Touchscreens are the primary input devices for smartphones and tablets. Although widely used, the output of touchscreen controllers is still limited to the two-dimensional position of the contacting finger. Finger angle (or orientation) estimation from touchscreen images has been studied for enriching touch input. However, only pitch and yaw are usually estimated and estimation error is large. One main reason is that touchscreens provide very limited information of finger. With the development of under-screen fingerprint sensing technology, fingerprint images, which contain more information of finger compared with touchscreen images, can be captured when a finger touches the screen. In this paper, we constructed a dataset with fingerprint images and the corresponding ground truth values of finger angle. We contribute with a network architecture and training strategy that harness the strong dependencies among finger angle, finger region, finger type, and fingerprint ridge orientation to produce a top-performing model for finger angle estimation. The experimental results demonstrate the superiority of our method over previous state-of-the-art methods. The mean absolute errors of the three angles are 6.6 degrees for yaw, 7.1 degrees for pitch, and 9.1 degrees for roll, markedly smaller than previously reported errors. Extensive experiments were conducted to examine important factors including image resolution, image size, and finger type. Evaluations on a set of under-screen fingerprints were also performed to explore feasibility in real-world applications. Code and a subset of the data are publicly available.
ColloSSL
Authors: Jain Yash , Tang Chi Ian , Min Chulhong , Kawsar Fahim , Mathur Akhil
Published: March 2022

A major bottleneck in training robust Human-Activity Recognition models (HAR) is the need for large-scale labeled sensor datasets. Because labeling large amounts of sensor data is an expensive task, unsupervised and semi-supervised learning techniques have emerged that can learn good features from the data without requiring any labels. In this paper, we extend this line of research and present a novel technique called Collaborative Self-Supervised Learning (ColloSSL) which leverages unlabeled data collected from multiple devices worn by a user to learn high-quality features of the data. A key insight that underpins the design of ColloSSL is that unlabeled sensor datasets simultaneously captured by multiple devices can be viewed as natural transformations of each other, and leveraged to generate a supervisory signal for representation learning. We present three technical innovations to extend conventional self-supervised learning algorithms to a multi-device setting: a Device Selection approach which selects positive and negative devices to enable contrastive learning, a Contrastive Sampling algorithm which samples positive and negative examples in a multi-device setting, and a loss function called Multi-view Contrastive Loss which extends standard contrastive loss to a multi-device setting. Our experimental results on three multi-device datasets show that ColloSSL outperforms both fully-supervised and semi-supervised learning techniques in majority of the experiment settings, resulting in an absolute increase of upto 7.9% in F1 score compared to the best performing baselines. We also show that ColloSSL outperforms the fully-supervised methods in a low-data regime, by just using one-tenth of the available labeled data in the best case.
Layer by Layer, Patterned Valves Enable Programmable Soft Surfaces
Authors: Gonzalez Jesse T. , Hudson Scott E.
Published: March 2022

Programmable surfaces, which can be instructed to alter their shape or texture, may one day serve as a platform for tangible interfaces and adaptive environments. But so far, these structures have been constrained in scale by a challenging fabrication process, as the numerous constituent actuators must be built and assembled individually. We look towards emerging trends in mechanical engineering and consider an alternate framework --- layer-driven design, which enables the production of dynamic, discretely-actuated surfaces at multiple scales. By centering the construction around patterning and stacking, forgoing individual assembly in favor of bulk processes such as photo-etching and laser cutting, we avoid the need for multiple manufacturing steps that are repeated for each of the many actuators that compose the surface. As an instance of this layer-driven model, we build an array of electrostatic valves, and use this composite material (which we refer to as Stoma-Board) to drive four types of pneumatic transducers. We also show how this technique may be readily industrialized, through integration with the highly mature and automated manufacturing processes of modern electronics.
LASense
Authors: Li Dong , Liu Jialin , Lee Sunghoon Ivan , Xiong Jie
Published: March 2022

Acoustic signals have been widely adopted in sensing fine-grained human activities, including respiration monitoring, finger tracking, eye blink detection, etc. One major challenge for acoustic sensing is the extremely limited sensing range, which becomes even more severe when sensing fine-grained activities. Different from the prior efforts that adopt multiple microphones and/or advanced deep learning techniques for long sensing range, we propose a system called LASense, which can significantly increase the sensing range for fine-grained human activities using a single pair of speaker and microphone. To achieve this, LASense introduces a virtual transceiver idea that purely leverages delicate signal processing techniques in software. To demonstrate the effectiveness of LASense, we apply the proposed approach to three fine-grained human activities, i.e., respiration, finger tapping and eye blink. For respiration monitoring, we significantly increase the sensing range from the state-of-the-art 2 m to 6 m. For finer-grained finger tapping and eye blink detection, we increase the state-of-the-art sensing range by 150% and 80%, respectively.
WearSign
Authors: Zhang Qian , Jing JiaZhen , Wang Dong , Zhao Run
Published: March 2022

Sign language translation (SLT) is considered as the core technology to break the communication barrier between the deaf and hearing people. However, most studies only focus on recognizing the sequence of sign gestures (sign language recognition (SLR)), ignoring the significant difference of linguistic structures between sign language and spoken language. In this paper, we approach SLT as a spatio-temporal machine translation task and propose a wearable-based system, WearSign, to enable direct translation from the sign-induced sensory signals into spoken texts. WearSign leverages a smartwatch and an armband of ElectroMyoGraphy (EMG) sensors to capture the sophisticated sign gestures. In the design of the translation network, considering the significant modality and linguistic gap between sensory signals and spoken language, we design a multi-task encoder-decoder framework which uses sign glosses (sign gesture labels) for intermediate supervision to guide the end-to-end training. In addition, due to the lack of sufficient training data, the performance of prior studies usually degrades drastically when it comes to sentences with complex structures or unseen in the training set. To tackle this, we borrow the idea of back-translation and leverage the much more available spoken language data to synthesize the paired sign language data. We include the synthetic pairs into the training process, which enables the network to learn better sequence-to-sequence mapping as well as generate more fluent spoken language sentences.

We construct an American sign language (ASL) dataset consisting of 250 commonly used sentences gathered from 15 volunteers. WearSign achieves 4.7% and 8.6% word error rate (WER) in user-independent tests and unseen sentence tests respectively. We also implement a real-time version of WearSign which runs fully on the smartphone with a low latency and energy overhead.
Unilateral Sciatic Nerve Crush Induces White Blood Cell Infiltration of the Contralateral Nerve
Authors: Cheng Jia , Ding Lingtao , Yang Minlie , Zhu Yugang , Gu Zaiqiu , Lv Guozhong
Published: March 2022

Nerve injury leads to the accumulation of white blood cells derived from the bone marrow in the lesioned nerve, but it is still unknown whether there are similar responses in unlesioned nerves. To address this question, sciatic nerves of mice expressing enhanced green fluorescent protein (EGFP) in their bone marrow were crushed unilaterally to observe the invasion of bone marrow-derived cells into the contralateral unlesioned nerve. Two days after surgery, EGFP+ cells began to infiltrate both the damaged and undamaged nerves. These cells gradually amplified to the highest point within 14 days and slowly lowered. In ipsilateral (lesioned) and contralateral (unlesioned) nerves, the time course of infiltration of EGFP+ cells was similar, but the magnitude was much less for the unlesioned one. Through CD68 staining, some cells were identified as macrophages. Transmission electron microscopy revealed slight demyelination and phagocytosing macrophages in the contralateral nerve. The data showed that infiltration by white blood cells is a response to nerve injury, even in uninjured nerves.
Interrogative Sentences Recognition Based on the GRU Multiattentive Layer Model
Authors: Liu Liu
Published: March 2022

Understanding the question is the key point in the question answering system. Therefore, this paper designs a multi attention layer model, extracts some missing features from the storage module, and uses Gru unit to organize them reasonably. By using non-linear operations to combine the results of different attention layers, we can avoid extracting only the linear combination of memory modules. Effectively combine the process of problem understanding, including the classification of problem words, the vocabulary annotation of problem sentences, the identification of problem sentence patterns, the classification of problems and the identification of problem centers, the grammatical analysis of question sentences and the identification of question sentence patterns, so as to achieve problem understanding. Experimental results show that this method improves the accuracy of problem understanding.
Experimental Study on Lateral Resolution of Phased Array Ultrasonic Testing of Irregular Structure Weld Defects
Authors: Liu Wenjing , Wen Zechun , Wang Jianguo , Wang Shaofeng , Wang Hailing , Zhang Wenliang , Huang Shunzhou , Hong Jun
Published: March 2022

Irregular structure welds are used in numerous military industries. This paper is interested in how to utilize phased array ultrasonic testing (PAUT) to identify and locate irregular structure weld defects. In this paper, CIVA simulation results were compared with inspection results of known defects and were found to be in very good agreement. This shows the feasibility of CIVA simulations. The coupling, among process parameters, affects the amplitude drop value from the peak to the trough of defects signal response, which represents the lateral resolution of internal weld defects and affect the imaging quality directly. Thus, the proper setting of detection parameters is critical to improve the testing efficiency and the imaging quality. This paper uses the response surface methodology (RSM) to design the test and conduct a factorial test to analyze the effect of each parameter. Modelling of the parameters and the response is conducted through center composite design (CCD) to analyze the coupling among multiple parameters and the reliability of the model. In the process of PAUT, the response surface plot, contour plot and the initial design domain of process parameters were combined for weld defects to determine the optimal parameters rapidly and correctly. Besides, CIVA simulation could further verify optimized detection parameters and position in industry site. Finally, irregular structure weld defects were identified accurately with PAUT imaging.
Hepatoprotective Effects of Crude Stem Bark Extracts and Solvent Fractions of Cordia africana against Acetaminophen-Induced Liver Injury in Rats
Authors: Geresu Gudeta Duga , Umer Shemsu , Arayaselassie Mahlet , Ashebir Genet , Makonnen Eyasu
Published: March 2022

Cordia africana Lam (Boraginaceae) is widely used in Ethiopian folk medicine for the treatment of different types of liver disorders. Thus, this study aimed to investigate the hepatoprotective effects of an aqueous (CAAE), 80% methanol extracts of C. africana stem bark (CAME), and the solvent fractions of the methanol extract against acetaminophen (APAP)-induced liver injury in rats. Acute toxicity test and APAP-induced lethality test were done on mice of either sex, while APAP dose selection test was done on female rats. Male rats were used for hepatoprotective experiments and the liver injury was induced using 2 g/kg APAP given orally. Serum levels of the liver enzymes and total bilirubin (TB), as well as lipid profiles, were determined. Histopathological examination of the liver tissues was also conducted to confirm the findings of biochemical analysis. Intraperitoneal (i.p.) sodium pentobarbital (SPB)-induced sleeping duration was also used to determine the protective effect of the test substances. Oral administration of APAP resulted in a significant increase in serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), TB, low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides (TGs) and decrease in serum high-density lipoprotein (HDL). Administration of the standard drug, silymarin 100 mg/kg, extracts at doses of 100, 200, and 400 mg/kg and fractions at the dose of 400 mg/kg reversed the serum levels of all parameters to normal. CAME exerted a significant dose-dependent hepatoprotective effect in terms of ALT and AST, while CAAE significant dose-dependent hepatoprotective effect was in terms of AST, ALP, and TGs. The protective effect of the extracts and fractions was also confirmed by histopathological investigations and SPB-induced sleeping time. From the results of the present study, it can be concluded that C. africana stem bark aqueous, 80% methanol crude extracts, and solvent fractions of the methanol extract showed hepatoprotective effects.
Study on the Microstructure and Mechanical Properties of As-Extruded AZ Magnesium Alloys by Micro-Adding La Rare-Earth Element
Authors: Fu Li , Guo Chunrong , Zhang Zhiqian , Jia Zheng , Lu Lin , Le Qichi
Published: March 2022

Changes of precipitates, dynamic recrystallization, texture, and properties at room temperature in the as-extruded AZ alloys (Al =  0, 3, 6, 8, wt.%) with 0.3% La addition were systematically investigated in this work. The analysis results suggest that new Mg12La with lamellar-structure precipitates in AZ01-0.3La alloy and new Al11La3 with needlelike structure precipitates in AZ-0.3La alloy with 3%–8% Al. Crashed Mg17Al12 could decrease the recrystallization temperature. Proper-sized Mg12La and Al11La3 could promote the dynamic recrystallization nucleation, leading to the reduction of grains in the as-extruded AZ-0.3La alloy, except for 6% Al. At room temperature, the strength of as-extruded AZ-0.3La alloys increases as Al increases, and the elongation first increases and then decreases, while the elongation is greater than 20% with 3%–8% Al. Due to the refined average grain size of 12.2 μm, the scattered and wakened

0002

base texture, the as-extruded AZ31-0.3La shows the best comprehensive tensile property compared with other AZ-0.3La alloys and AZ alloys, of which the Rp0.2 is 162 MPa, the Rm is 252 MPa, and the A is 21.7%.
Experimental Analysis of Recycled Aggregate Concrete Beams and Correction Formulas for the Crack Resistance Calculation
Authors: Chen Xuyong , Zhang Zhixin , Xu Zhifeng , Wu Qiaoyun , Fan Jianping , Zhao Xuri
Published: March 2022

This paper studies the similarities and the differences between natural aggregate concrete (NAC) beams and recycled aggregate concrete (RAC) beams in terms of concrete material properties, bearing capacity, and crack resistance and further proposes correction formulas for cracking moment calculation of RAC beams that consider different recycled aggregate substitution ratios. First, the basic mechanical properties (e.g., cube compressive strength, axial compressive strength, and elastic modulus) of RAC blocks were tested; second, comparative bending tests of RAC beams and natural aggregate concrete beams were conducted, in order to obtain the cracking moments, yield bending moments, ultimate bending moments, mid-span deflections and crack development forms; finally, numerical simulations were performed to investigate the cracking performances of RAC beams. Through analyzing the experimental results, it is found that the crack development pattern of RAC beams resembles that of natural aggregate concrete beams, while the cracking performance of RAC beams significantly deviates from that of NAC beams. Finally, the correction formulas for the cracking moment calculation of RAC beams are proposed based on the numerical simulation results and verified by data from other researchers, which can be regarded as a correction for the cracking moment calculation formulas in the current code for RAC beams with respect to varied recycled concrete aggregate substitution ratios.
Causes of Emergency Bleeding after Nonsurgical Periodontal Therapy in Adult Periodontitis Patients: A Retrospective Analysis
Authors: Lu Fei , Qi Gang-Gang , Fang Wen , Zhang Xin , Zhou Jing , Yu Xue-Fen , Li Xiao-Jun
Published: March 2022

Background. Emergency gingival uncontrollable bleeding after nonsurgical periodontal therapy (NSPT) could be caused by a variety of factors; local oral factors are the main cause of gingival bleeding in most patients. Because the doctor will do a good job of evaluating the patient’s physical condition before nonsurgical periodontal therapy. This study is subjected to evaluate the possible factors associated with emergency uncontrollable bleeding within 24-48 hours after NSPT. Material and Methods. A total of fifty-eight patients with emergency bleeding after NSPT in the past four years were enrolled. The related factors in patients, such as age, gender, clotting function, systemic diseases, and baseline periodontitis severity, were analyzed. The site-related factors, such as tooth type, tooth distribution, and alveolar bone resorption at the bleeding site, were compared. The possible relationship of the parameters to the causes of emergency bleeding with NSPT was also evaluated. Results. Gingival bleeding after NSPT was registered. In this retrospective study, a total of 58 patients were selected. There were 29 males and 29 females, aged from 20 to 67 years old, with an average age of

35.21
±
10.09

years. Among them, 8.6% were over 50 years old, and 91.4% were under 50 years old. Completed evaluations were performed in 15.5% gingivitis and 84.5% periodontitis. The causes of emergency bleeding after nonsurgical periodontal therapy in this study were residual subgingival calculus or granulation tissue in 63.79% of cases: severe gingival inflammation, 29.32%; gum trauma, 3.45%; and poor compliance, 3.45%. The therapy method before bleeding includes supragingival scaling accounted for 72.4% and subgingival scaling accounted for 27.6%. 23 cases of horizontal absorption at the bleeding site accounted for 39.66%, and 35 cases of angular absorption accounted for 60.34%. Bleeding of maxillary posterior teeth accounted for 34.48%; mandibular anterior teeth accounted for 15.52%; mandibular anterior teeth accounted for 8.62%; and mandibular posterior teeth accounted for 18.97%; multiple sites accounted for 22.41%; eliminating residual subgingival calculus and granulation tissue were the main and most effective hemostatic methods, 86.21%. Conclusion. Residual subgingival calculus or granulation tissue and severe gingival inflammation were the main causes of emergency gingival bleeding after nonsurgical periodontal therapy. Severe gingival inflammation causing emergency bleeding was more common in maxillary posterior teeth areas. Angular alveolar bone resorption was more likely to cause bleeding than horizontal resorption. Careful debridement of residual subgingival calculus and granulation tissue was the main hemostatic method.
A Paradigmatic Approach to Find Equal Sum Partitions of Zero-Divisors via Complete Graphs
Authors: Mateen M. Haris , Mahmood M. Khalid , Ahmad Daud , Ali Shahbaz , Ali Shajib
Published: March 2022

In computer science and mathematics, a partition of a set into two or more disjoint subsets with equal sums is a well-known NP-complete problem. This is a hard problem and referred to as the partition problem or number partitioning. In this paper, we solve a particular type of NP-complete problem on the set of all zero-divisors of

Z

n

including zero, where

Z

n

is the ring of residue classes of a positive integer

n

. In this regard, we introduce and investigate quadratic zero-divisor graph in which we build an edge between zero-divisors

z

i

and

z

j

if and only if

z

i

2

≡

z

j

2

 

mod
 
n

,
i
≠
j

. This is denoted as

G

⏞

2

,

n

. We characterize these graphs in term of complete graphs for classes of integers

2

α

,

p

α

,

2

α

p
,
2

p

α

and

p
q

, where

α

is any positive integer and

p
,
q

are odd primes.
The Effect of the NFκB-USP9X-Cx43 Axis on the Dynamic Balance of Bone Formation/Degradation during Ossification of the Posterior Longitudinal Ligament of the Cervical Spine
Authors: Yuan Xiaoqiu , Guo Yongfei , Liu Jilu , Sun Jingchuan , Shi Lei , Miao Jinhao , Shi Jiangang , Chen Yu
Published: March 2022

Connexin 43- (Cx43-) mediated nuclear factor kappa-light-chain-enhancer of activated B cell (NF-κB) signaling has been found involved in the ossification of the posterior longitudinal ligament (OPLL). However, the underlying mechanism how OPLL is regulated has not been elucidated. In the present study, primary ligament fibroblast were isolated; immunoprecipitation (IP) and liquid chromatography-mass spectrometry (LC-MS) assays were applied to identify potential binding proteins of Cx43. Protein interaction was then confirmed by co-IP assay. Alkaline phosphatase (ALP) activity and alizarin red staining were used to evaluate ossification. Luciferase reporter assay and chromatin immunoprecipitation (ChIP) assay were employed to assess the binding between NF-κB p65 and target gene. Lipoxygenase inhibitor (5,8,11-eicosatriynoic acid, EPA) was applied to induce endoplasmic reticulum (ER) stress, and 4-phenylbutyrate (4-PBA) was used as an ER-stress inhibitor. Expression of USP9X, Cx43, and nuclei p65 in ligaments from patients and controls was detected by Western blotting. The results showed that ubiquitin-specific protease 9 X-chromosome (USP9X), a deubiquitylating enzyme, was a candidate of Cx43 binding proteins, and USP9X inhibited Cx43 ubiquitination. In vitro experiments showed that USP9X promoted ossification of primary ligament fibroblasts and nuclear translocation of NF-κB p65 by regulating Cx43 expression. Moreover, NF-κB can bind to the USP9X promoter to promote its transcription. When ER stress was inhibited by 4-PBA, USP9X levels, NF-κB nuclei translocation, and ALP activity were decreased. Reverse results were obtained when ER stress was induced by EPA. PDTC, an NF-κB inhibitor, could abolish the effects of EPA. Furthermore, USP9X, Cx43, and nuclei p65 were significantly upregulated in ligaments from OPLL patients than non-OPLL controls. USP9X was positively correlated with CX43 and nuclei p65 in OPLL samples. Overall, the findings suggest that the ER stress–NFκB-USP9X-Cx43 signaling pathway plays an important role in OPLL progression.
Biological Deciphering of the “Kidney Governing Bones” Theory in Traditional Chinese Medicine
Authors: Zhu Hanmin , Liu Qi , Li Wei , Huang Shuming , Zhang Bo , Wang Yumei
Published: March 2022

The description of the “kidney” was entirely different from modern medicine. In traditional Chinese medicine (TCM), the kidney was a functional concept regulating water metabolism, which was closely related to the urinary system, reproductive system, nervous system, endocrine, skeleton, hearing, metabolism, immunity, etc. In particular, the kidney in TCM plays an important regulatory role in the processes of growth, development, prime, aging, and reproduction. Hence, “Kidney Governing Bone” (KGB) was a classical theory in TCM, which hypothesized that the function of the kidney was responsible for bone health. However, the related modern physiological mechanisms of this TCM theory are unclear. This present paper proposed a new understanding and explored the biological basis of the KGB theory. After searching through plenty of reported literature, we discovered that the functions of the kidney in TCM were closely associated with the hypothalamic-pituitary-gonadal (HPG) axis in modern science. The physiological mechanism of the KGB was regulated by sex hormones and their receptors. This review deciphered the connotation of the KGB theory in modern medicine and further verified the scientificity of the basic TCM theory.
Association between Interleukin-4-590C>T Polymorphism and the Susceptibility to Asthma: A Meta-Analysis of Case-Control Study
Authors: Liu Tong , Yin Weimou , Luo Ling , Wu Yankui , Qin Songmei , Qin Xuejun
Published: March 2022

This study was aimed to investigate the relationship between the interleukin-4-590C > T gene polymorphism and the susceptibility to asthma by meta-analysis. To explore the underlying relationship between the polymorphism of IL-4-590C > T and the susceptibility to asthma, this study systematically retrieved the literature including cohort studies and case-control studies published before June 2019 in PubMed, Embase, and Cochrane Library. Data on the odds ratio (OR) and 95% confidence interval (CI) of the literature were included in the relative studies. Subsequently, the included data were weighted by an inverse variance and then analyzed by the fixed or random effects model. Overall, 818 asthma patients and 831 healthy individuals participated in the 8 independent case-control studies in the current meta-analysis. There was no correlation between IL-4-590C > T TT genotype and the increased susceptibility to asthma (dominant model: OR = 1.31, 95% CI = 0.68–2.53). Subgroup analysis by ethnicity showed no significant results in the Asians (OR = 1.28, 95% CI = 0.24–6.80); however, IL-4-590C > T TT genotype significantly elevated the susceptibility to asthma in the Caucasians (OR = 1.43, 95%CI = 1.03–1.98). Meanwhile, subgroup analysis was performed by source of control. A statistically significant result was found in the population-based control group (OR = 1.33, 95% CI = 1.01–1.76), but not in the hospital-based control group (OR = 1.22, 95% CI = 0.27–5.46). The results demonstrated that IL-4-590C > T TT genotype could significantly enhance the susceptibility to asthma in Caucasians without increasing that in Asian populations. However, it still required a large sample of high-quality studies in multicentral hospital to further confirm its reliability.
Feasibility of Constructing an Automatic Meniscus Injury Detection Model Based on Dual-Mode Magnetic Resonance Imaging (MRI) Radiomics of the Knee Joint
Authors: Wang Yi , Li Yuanzhe , Huang Meiling , Lai Qingquan , Huang Jing , Chen Jiayang
Published: March 2022

Objective. To explore the feasibility of automatically detecting the degree of meniscus injury by radiomics fusion of dual-mode magnetic resonance imaging (MRI) features of sagittal and coronal planes of the knee joint. Methods. This retrospective study included 164 arthroscopically confirmed meniscus injuries in 152 patients admitted to the Department of Orthopaedics of our hospital from July 2018 to March 2021. A total of 1316-dimensional radiomics signatures were extracted from single-mode sagittal and coronal plane images of menisci, respectively. Then, the sagittal and coronal plane features were fused to form a dual-mode joint feature group with a total of 2632-dimensional radiomics signatures. The minimum redundancy maximum relevance (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression were used to select features and generate optimal radiomics signatures. The single-mode sagittal plane feature model (Model 1), single-mode coronal plane feature model (Model 2), and the combined sagittal and coronal plane feature model (Model 3) performance were tested by receiver operating characteristic (ROC) curves and Delong test. The calibration curve test was used to verify the reliability of radiomics signatures of the three models. Results. The average intra- and interobserver intraclass correlation coefficients (ICCs) of the most significant 8-dimensional radiomics signatures of Model 1 and Model 2 were 0.935 (range 0.832-0.998) and 0.928 (range 0.845-0.998), respectively. All the three models had good detection performance; Model 3 had the most significant performance (the areas under the curve (AUCs) of training, and validation sets were 0.947 and 0.923, respectively), which was superior to Model 1 (AUCs of training set and validation set were 0.889 and 0.876, respectively) and Model 2 (AUCs of training set and validation set were 0.831 and 0.851, respectively). The detection probability of training and validation sets in the three models was highly consistent with the actual clinical probability. Conclusions. It is feasible to establish a model for automatic detection of meniscus damage by means of radiomics. The detection performance of the dual-mode knee MRI model is better than that of any single-mode model, showing potent feature analysis ability and outstanding detection performance.
An Efficient Authentication and Key Distribution Protocol for Multicast Service in Space-Ground Integration Network
Authors: Kou Wenlong , You Wei , Li Sheng , Shi Xiaoping , Ma Ruhui , Guo Chao
Published: March 2022

Satellite communication technology has attracted the attention of researchers in the study of the sixth-generation (6G) mobile communication network because of its advantages of achieving global coverage with high cost-effectiveness and not being affected by terrain factors and human activities. In order to achieve efficient interconnection between terminals and networks, it is a new development trend of communication technology to integrate satellite communication networks and ground communication networks to construct the Space-Ground Integration Network (SGIN). Multicast service is widely used by network service providers to provide business services to users. Due to the characteristics of higher delay of space communication and unstable link compared with the ground network, if the ground multimedia multicast security protocol is directly applied to the space communication, it is difficult to guarantee the efficiency of the corresponding business service. The existing security protocols in the space information network are usually designed to ensure the security of end-to-end communication, and there are few studies on the security of multimedia multicast services. In view of the above situation, we design a new multicast service security protocol for the SGIN to realize the secure and efficient transmission in multicast services. In the protocol, we first design a key derivation scheme for the shared key between UE and BM-SC based on the existing 5G-AKA mechanism. Then, we propose a group-based multicast service registration mechanism. Finally, we propose a secure and efficient key distribution and update process of multicast service group key based on China Remainder Theorem (CRT). The formal verification tool Scyther is employed to analyze the security of the proposed protocol, and the results show that our scheme has valid security properties. We analyze the performance of the scheme by comparing it with the existing schemes in three aspects, such as signaling overhead, computational overhead, and bandwidth overhead. The comparison results show that our scheme is superior to other existing schemes. Finally, we build an experimental environment and test the delay, transmission rate, and CPU usage of the proposed system. The results show that our scheme improves the efficiency of multicast services while ensuring network security.