bluuebunny/crossref_metadata_2025 huggingface dataset:
The Association between Asthma and OSA in Children
Authors: Garza Nicholas , Witmans Manisha , Salud Martina , Lagera Pamela Gail D. , Co Vince Aaron , Tablizo Mary Anne
Published: September 2022

Obstructive sleep apnea (OSA) and asthma are two of the most prevalent and commonly co-existing respiratory conditions seen in the pediatric population. Studies linking asthma and OSA in children are limited but indicate that there is a bi-directional relationship between them with significant overlap in the symptoms, risk factors, pathophysiology, comorbidities, and management. It is suggested that there is a reciprocal association between asthma predisposing to OSA, and OSA worsening symptom control and outcomes from asthma. It stands to reason that inflammation in the upper and/or lower airways can influence each other. Most of the pediatric literature that is available evaluates each aspect of this relationship independently such as risk factors, mechanisms, and treatment indications. This article highlights the relationship between OSA and asthma in the context of shared risk factors, pathophysiology, and available management recommendations in the pediatric population. Early recognition of the co-existence and association between OSA and asthma could ideally improve the treatment outcomes for these two conditions. Gaining a better understanding of the mechanism of this relationship can help identify nuances for medical management, optimize treatment and protect this population at risk from associated morbidity.
Physical Activity among U.S. Preschool-Aged Children: Application of Machine Learning Physical Activity Classification to the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey
Authors: Kwon Soyang , O’Brien Megan K. , Welch Sarah B. , Honegger Kyle
Published: September 2022

Early childhood is an important development period for establishing healthy physical activity (PA) habits. The objective of this study was to evaluate PA levels in a representative sample of U.S. preschool-aged children. The study sample included 301 participants (149 girls, 3–5 years of age) in the 2012 U.S. National Health and Examination Survey National Youth Fitness Survey. Participants were asked to wear an ActiGraph accelerometer on their wrist for 7 days. A machine learning random forest classification algorithm was applied to accelerometer data to estimate daily time spent in moderate- and vigorous-intensity PA (MVPA; the sum of minutes spent in running, walking, and other moderate- and vigorous-intensity PA) and total PA (the sum of MVPA and light-intensity PA). We estimated that U.S. preschool-aged children engaged in 28 min/day of MVPA and 361 min/day of total PA, on average. MVPA and total PA levels were not significantly different between males and females. This study revealed that U.S. preschool-aged children engage in lower levels of MVPA and higher levels of total PA than the minimum recommended by the World Health Organization.
Special Issue: Corrosion Effects and Smart Coatings of Corrosion Protection
Authors: Zhao Xiaoshuo , Jiang Dan , Ma Li , Zeng Xian , Li Zengying , Huang Guosheng
Published: September 2022

Materials that are capable of adapting their properties dynamically to an external stimulus are called stimuli-responsive or “smart materials” [...]
Wear Study of Coated Mills during Circumferential Milling of Carbon Fiber-Reinforced Composites and Their Influence on the Sustainable Quality of the Machined Surface
Authors: Knápek Tomáš , Dvořáčková Štěpánka , Knap Artur
Published: September 2022

Composite materials made of fiber-reinforced plastic laminates are highly susceptible to surface damage caused by wear during contour milling, especially with inappropriate tool and cutting material properties. Improper choice of tools and cutting conditions lead to delamination between applied layers, thermal damage of materials in the polymer matrix, and reduction of the edge quality of cutting tools. The study was devoted to circumferential milling of twill-bonded CFRP (carbon-fiber-reinforced polymer) sheets with a focus on cutting forces and tool flank face wear, including their effect on the machined surface structure, roughness, and topography of the laminate. The main objective of the study is to investigate the feasibility of applying conventional coated tools, which are not primarily designed for milling CFRP, in comparison to a dedicated DLC (diamond-like carbon) coated tool, due to economic and distribution availability and the possibility of providing suitable cutting conditions during milling. The study provides results confirming the possibility of using conventional tools for machining CFRP and provides relevant experimental results that can be implemented for optimal tool selection, tool life criteria, cutting conditions, and machining strategies including low energy consumption. The best values of the investigated parameters were obtained when using the ECSSF (instrument designation) tool with DLC coating.
Calcium Orthophosphate (CaPO4)-Based Bioceramics: Preparation, Properties, and Applications
Authors: Dorozhkin Sergey V.
Published: September 2022

Various types of materials have been traditionally used to restore damaged bones. In the late 1960s, a strong interest was raised in studying ceramics as potential bone grafts due to their biomechanical properties. A short time later, such synthetic biomaterials were called bioceramics. Bioceramics can be prepared from diverse inorganic substances, but this review is limited to calcium orthophosphate (CaPO4)-based formulations only, due to its chemical similarity to mammalian bones and teeth. During the past 50 years, there have been a number of important achievements in this field. Namely, after the initial development of bioceramics that was just tolerated in the physiological environment, an emphasis was shifted towards the formulations able to form direct chemical bonds with the adjacent bones. Afterwards, by the structural and compositional controls, it became possible to choose whether the CaPO4-based implants would remain biologically stable once incorporated into the skeletal structure or whether they would be resorbed over time. At the turn of the millennium, a new concept of regenerative bioceramics was developed, and such formulations became an integrated part of the tissue engineering approach. Now, CaPO4-based scaffolds are designed to induce bone formation and vascularization. These scaffolds are usually porous and harbor various biomolecules and/or cells. Therefore, current biomedical applications of CaPO4-based bioceramics include artificial bone grafts, bone augmentations, maxillofacial reconstruction, spinal fusion, and periodontal disease repairs, as well as bone fillers after tumor surgery. Prospective future applications comprise drug delivery and tissue engineering purposes because CaPO4 appear to be promising carriers of growth factors, bioactive peptides, and various types of cells.
Composition Engineering on the Local Structure and Viscosity of the CaO-SiO2-Al2O3-P2O5-FeO Slag by Machine Learning Methods
Authors: Lyu Ziyu , Gu Chao , Lyu Ziyang , Bao Yanping
Published: September 2022

Due to the high cost and low accuracy of high-temperature tests, the viscosity data for multicomponent slag systems is difficult to be obtained precisely. Therefore, it is important to fulfill the viscosity database of the multicomponent slag systems via reasonable methods with lower costs. In this study, a viscosity prediction method based on the machine learning method was proposed for the CaO-SiO2-FeO-Al2O3-P2O5 quinary slag system. To provide valid data for the machine learning model, the viscosity predicted by the molecular dynamic method and multiple semi-empirical models were compared to verify the applicability of these methods to the slag system. Different machine learning models were also developed. The results showed that the prediction results from the gradient boosting decision tree method were the most accurate for the CaO-SiO2-FeO-Al2O3-P2O5 quinary slag system. Based on this method, a color-map concerning the numerical effect of Al2O3 and P2O5 contents and slag viscosity is provided, which also provides assistance for the composition engineering to fulfill a certain demand on the viscosity design.
Rare and Insidious Toxicities from New Combination Therapies in Metastatic Renal Cell Cancer: Lessons Learned from Real-Practice
Authors: Dri Arianna , Garattini Silvio Ken , Cinausero Marika , Macerelli Marianna , Fanelli Martina , Puglisi Fabio , Fasola Gianpiero , Ermacora Paola
Published: September 2022

The advent of immune checkpoint inhibitors in combination with multitarget tyrosine kinase inhibitors has become a standard first-line treatment for metastatic renal cell cancer. Along with survival improvement, new toxicities have emerged. Such adverse events are still complex to be managed and some of them are rare and could be insidious or even fatal. Medical oncologists dispose of guidelines about the management of toxicities from immune checkpoint inhibitors but not for combinations. Therefore, it is still difficult to properly attribute and manage additive or overlapping adverse events. We report two clinical cases regarding rare treatment-related endocrine toxicities—hypophysitis and thyroiditis—with particular focus on their management. To this purpose, immune checkpoint-related toxicities guidelines represent the starting point. However, their implementation with additional measures is needed, considering the increasing complexity of current clinical scenarios. The goal is to correctly recognize adverse events and address side effects, so as not to discontinue effective treatments. We, therefore, aim at discussing the points of proper management of toxicities and individuating potential areas of improvement.
Prone Positioning Decreases Inhomogeneity and Improves Dorsal Compliance in Invasively Ventilated Spontaneously Breathing COVID-19 Patients—A Study Using Electrical Impedance Tomography
Authors: Pierrakos Charalampos , van der Ven Fleur L. I. M. , Smit Marry R. , Hagens Laura A. , Paulus Frederique , Schultz Marcus J. , Bos Lieuwe D. J.
Published: September 2022

Background: We studied prone positioning effects on lung aeration in spontaneously breathing invasively ventilated patients with coronavirus disease 2019 (COVID-19). Methods: changes in lung aeration were studied prospectively by electrical impedance tomography (EIT) from before to after placing the patient prone, and back to supine. Mixed effect models with a random intercept and only fixed effects were used to evaluate changes in lung aeration. Results: fifteen spontaneously breathing invasively ventilated patients were enrolled, and remained prone for a median of 19 [17 to 21] hours. At 16 h the global inhomogeneity index was lower. At 2 h, there were neither changes in dorsal nor in ventral compliance; after 16 h, only dorsal compliance (βFe +18.9 [95% Confidence interval (CI): 9.1 to 28.8]) and dorsal end-expiratory lung impedance (EELI) were increased (βFe, +252 [95% CI: 13 to 496]); at 2 and 16 h, dorsal silent spaces was unchanged (βFe, –4.6 [95% CI: –12.3 to +3.2]). The observed changes induced by prone positioning disappeared after turning patients back to supine. Conclusions: in this cohort of spontaneously breathing invasively ventilated COVID-19 patients, prone positioning decreased inhomogeneity, increased lung volumes, and improved dorsal compliance.
Pitfalls of Using Imaging Technique in the Presence of Eustachian Valve or Chiari Network: Effects on Right-to-Left Shunt and Related Influencing Factors
Authors: Zhang Han , Liu Weiwei , Ma Jie , Liu Huanling , Li Lin , Zhou Jinling , Wang Shanshan , Li Shanshan , Wang Wei , Wang Yueheng
Published: September 2022

When patent foramen ovale (PFO) combines with the prominent Eustachian valve or Chiari network (EV/CN), contrast transthoracic echocardiography (cTTE) may miss the diagnosis of PFO. We sought to determine the characteristics of right-to-left shunt (RLS) in PFO patients with prominent EV/CN on cTTE and identify the causal factors of missed diagnosis. We consecutively enrolled 98 patients who suffered from PFO-related stroke and with prominent EV/CN. All patients were divided into the delayed and non-delayed groups according to the characteristics of RLS on cTTE. The characteristics of RLS were compared with those of 42 intrapulmonary shunt patients. The anatomical characteristics of PFO and EV/CN were analyzed in the 98 PFO patients. Upon cTTE, significantly delayed occurrence and longer duration of the RLS in the delayed group were found both at rest and during the Valsalva maneuver, similar to the intrapulmonary shunt. Multivariate logistic analysis revealed that the length of EV/CN (>19 mm) and the diameter of PFO at the left atrium aspect (<1.2 mm) were high-risk factors for missed diagnosis. In conclusion, RLS showed delayed emergence and disappearance in some of the PFO patients with prominent EV/CN. The length of EV/CN and the diameter of PFO may have been related to the missed diagnosis of PFO.
Electrical Impedance Tomography (EIT) in a Patient Suffering from Post-COVID Syndrome with Dyspnea: A Case Report
Authors: Katzer Katrin , Gremme Yvonne , Moshmosh Alsabbagh Majd , Stallmach Andreas , Reuken Philipp , Lewejohann Jan-Christoph
Published: September 2022

Background: Long-term health consequences following COVID-19 disease constitute an increasing problem worldwide. A considerable number of patients still suffer from various symptoms, most commonly dyspnea, months or even years after the acute infection. In these patients, a classical pulmonary function test often yields no significant findings. Subsequently, treating those patients is a challenge for any physician as there are currently no evidence-based treatment plans. Case and methods: We reported the case of a 58-year-old patient who was still suffering from resting dyspnea six months after severe COVID-19 pneumonia. The dyspnea was so pronounced that the patient was supplied with home oxygen, which they used as needed. The regional distribution of ventilation in the lungs was studied twice utilizing noninvasive electrical impedance tomography (EIT). The first examination showed distinct inhomogeneities of regional ventilation, a regional ventilation delay (RVD) of 15%, and pronounced pendelluft phenomena. Seven weeks after treatment with budesonide and physical therapy, the patient reported a clear subjective improvement in complaints. Accordingly, the regional distribution of ventilation also improved. Conclusion: Electrical impedance tomography might be a promising method to assess lung function in post-COVID patients; however, controlled and larger studies are necessary.
Assessing, Testing and Estimating the Amount of Fine-Tuning by Means of Active Information
Authors: Díaz-Pachón Daniel Andrés , Hössjer Ola
Published: September 2022

A general framework is introduced to estimate how much external information has been infused into a search algorithm, the so-called active information. This is rephrased as a test of fine-tuning, where tuning corresponds to the amount of pre-specified knowledge that the algorithm makes use of in order to reach a certain target. A function f quantifies specificity for each possible outcome x of a search, so that the target of the algorithm is a set of highly specified states, whereas fine-tuning occurs if it is much more likely for the algorithm to reach the target as intended than by chance. The distribution of a random outcome X of the algorithm involves a parameter θ that quantifies how much background information has been infused. A simple choice of this parameter is to use θf in order to exponentially tilt the distribution of the outcome of the search algorithm under the null distribution of no tuning, so that an exponential family of distributions is obtained. Such algorithms are obtained by iterating a Metropolis–Hastings type of Markov chain, which makes it possible to compute their active information under the equilibrium and non-equilibrium of the Markov chain, with or without stopping when the targeted set of fine-tuned states has been reached. Other choices of tuning parameters θ are discussed as well. Nonparametric and parametric estimators of active information and tests of fine-tuning are developed when repeated and independent outcomes of the algorithm are available. The theory is illustrated with examples from cosmology, student learning, reinforcement learning, a Moran type model of population genetics, and evolutionary programming.
The Financial Sustainability of State-Owned Enterprises in an Emerging Economy
Authors: Lee Chee Loong , Ahmad Riayati , Lee Wing Shing , Khalid Norlin , Karim Zulkefly Abdul
Published: September 2022

When the government creates state-owned enterprises (SOEs), one of the primary purposes is to reduce its financial burden in the long run, also called financial sustainability. Nonetheless, previous research has pointed out that SOEs struggle to achieve financial sustainability due to government intervention. In this study, we examine the relationship between the financial sustainability of SOEs and government intervention in Malaysia. We take a novel approach, using share ownership to measure government intervention. Our results show that the threshold effect of government ownership on financial sustainability in Malaysia is around 27%. The findings prove that the SOEs of an emerging country could reach financial sustainability only if the government ownership is below the threshold. Finally, this study discusses the policy implications of our findings for SOEs. The government of Malaysia should propose a road map to gradually reduce its ownership of SOEs below the threshold.
Selective Layer Tuning and Performance Study of Pre-Trained Models Using Genetic Algorithm
Authors: Jeong Jae-Cheol , Yu Gwang-Hyun , Song Min-Gyu , Vu Dang Thanh , Anh Le Hoang , Jung Young-Ae , Choi Yoon-A , Um Tai-Won , Kim Jin-Young
Published: September 2022

Utilizing pre-trained models involves fully or partially using pre-trained parameters as initialization. In general, configuring a pre-trained model demands practitioners’ knowledge about problems or an exhaustive trial–error experiment according to a given task. In this paper, we propose tuning trainable layers using a genetic algorithm on a pre-trained model that is fine-tuned on single-channel image datasets for a classification task. The single-channel dataset comprises images from grayscale and preprocessed audio signals transformed into a log-Mel spectrogram. Four deep-learning models used in the experimental evaluation employed the pre-trained model with the ImageNet dataset. The proposed genetic algorithm was applied to find the highest fitness for every generation to determine the selective layer tuning of the pre-trained models. Compared to the conventional fine-tuning method and random layer search, our proposed selective layer search with a genetic algorithm achieves higher accuracy, on average, by 9.7% and 1.88% (MNIST-Fashion), 1.31% and 1.14% (UrbanSound8k), and 2.2% and 0.29% (HospitalAlarmSound), respectively. In addition, our searching method can naturally be applied to various datasets of the same task without prior knowledge about the dataset of interest.
Specially-Designed Out-of-Order Processor Architecture for Microcontrollers
Authors: Hu Yunhao , Chen Jie , Zhu Kaiben , Xing Qijun , Liu Wei , Shen Junfeng , Gao Ge
Published: September 2022

In very large-scale integration circuit (VLSI) systems, microcontrollers are often implanted to manage the whole system to complete the given computing tasks. They play an essential part as regulators, which should allocate resources steadily and issue instructions promptly to drive functional units. However, most of the recent research focuses on the operation at the software level or the scheduling at the SoC level, ignoring the impact of the microarchitecture and the features of controlled sub-modules. This paper analyzes the requirements of microcontrollers in the VLSI system with various constraints and conditions that should be considered in the hardware implementation of such microarchitecture. Furthermore, this paper takes an open-source design using RISC-V ISA as the prototype to implement hardware microarchitecture. This design integrates the techniques of out-of-order processing, which are usually used on superscalar processors. As a result, the design quadruples the number of pipelined instructions, greatly alleviating the stalling of the instruction stream with a maximum extra look up table utilization of 18.37% in FPGA implementation.
RISC-Vlim, a RISC-V Framework for Logic-in-Memory Architectures
Authors: Coluccio Andrea , Ieva Antonia , Riente Fabrizio , Roch Massimo Ruo , Ottavi Marco , Vacca Marco
Published: September 2022

Most modern CPU architectures are based on the von Neumann principle, where memory and processing units are separate entities. Although processing unit performance has improved over the years, memory capacity has not followed the same trend, creating a performance gap between them. This problem is known as the "memory wall" and severely limits the performance of a microprocessor. One of the most promising solutions is the "logic-in-memory" approach. It consists of merging memory and logic units, enabling data to be processed directly inside the memory itself. Here we propose an RISC-V framework that supports logic-in-memory operations. We substitute data memory with a circuit capable of storing data and of performing in-memory computation. The framework is based on a standard memory interface, so different logic-in-memory architectures can be inserted inside the microprocessor, based both on CMOS and emerging technologies. The main advantage of this framework is the possibility of comparing the performance of different logic-in-memory solutions on code execution. We demonstrate the effectiveness of the framework using a CMOS volatile memory and a memory based on a new emerging technology, racetrack logic. The results demonstrate an improvement in algorithm execution speed and a reduction in energy consumption.
An Empirical Comparison of Pen-Testing Tools for Detecting Web App Vulnerabilities
Authors: Albahar Marwan , Alansari Dhoha , Jurcut Anca
Published: September 2022

Today, one of the most popular ways organizations use to provide their services, or broadly speaking, interact with their customers, is through web applications. Those applications should be protected and meet all security requirements. Penetration testers need to make sure that the attacker cannot find any weaknesses to destroy, exploit, or disclose information on the Web. Therefore, using automated vulnerability assessment tools is the best and easiest part of web application pen-testing, but these tools have strengths and weaknesses. Thus, using the wrong tool may lead to undetected, expected, or known vulnerabilities that may open doors for cyberattacks. This research proposes an empirical comparison of pen-testing tools for detecting web app vulnerabilities using approved standards and methods to facilitate the selection of appropriate tools according to the needs of penetration testers. In addition, we have proposed an enhanced benchmarking framework that combines the latest research into benchmarking and evaluation criteria in addition to new criteria to cover more ground with benchmarking metrics as an enhancement for web penetration testers and penetration testers in real life. In addition, we measure the tool’s abilities using a score-based comparative analysis. Moreover, we conducted simulation tests of both commercial and non-commercial pen-testing tools. The results showed that Burp Suite Professional scored the highest out of the commercial tools, while OWASP ZAP scored the highest out of the non-commercial tools.
Experimental Characterization of Millimeter-Wave Substrate-Integrated Waveguide Interconnect with Slot Transition in Flexible Printed Circuit Boards
Authors: Kim Myunghoi , Bae Bumhee , Cheon Jeongnam
Published: September 2022

For high-speed communication services such as 5G technology, the use of millimeter-wave (mmWave) components substantially increases in mobile applications. The interconnect based on a substrate-integrated waveguide (SIW) is an efficient solution for connecting these devices. However, the SIW characteristics in the mmWave frequency range are not sufficiently presented from the practical viewpoint. In this paper, the experimental characterization of mmWave SIWs in flexible printed circuit boards (FPCBs) and their simulation results are presented. A practical method using balanced/single slot transition is proposed for microstrip-to-SIW transition. Using a full-wave simulation and genetic algorithm, the proposed slot technique is optimized. It is experimentally demonstrated that the cutoff frequency affects the operating band of the SIW differently. The per-unit-length losses of the full-mode and half-mode SIWs are obtained as 0.0375 dB/mm and 0.0609 dB/mm, respectively. Using the measurements, the SIW type effect on the transmission loss is quantitatively analyzed, and the loss is increased up to 62.4% at 39 GHz.
Advances in Ku-Band GaN Single Chip Front End for Space SARs: From System Specifications to Technology Selection
Authors: Scappaviva Francesco , Bosi Gianni , Biondi Andrea , D’Angelo Sara , Cariani Luca , Vadalà Valeria , Raffo Antonio , Resca Davide , Cipriani Elisa , Vannini Giorgio
Published: September 2022

In this paper, a single-chip front-end (SCFE) operating in Ku-band (12–17 GHz) is presented. It is designed exploiting a GaN on SiC technology featured by 150 nm gate length provided by UMS foundry. This MMIC integrates high power and low noise amplification functions enabled by a single-pole double-throw (SPDT) switch, occupying a total area of 20 mm2. The transmitting chain (Tx) presents a 39 dBm output power, a power added efficiency (PAE) higher than 30% and a 22 dB power gain. The receive path (Rx) offers a low noise figure (NF) lower than 2.8 dB with 25 dB of linear gain. The Rx port output power leakage is limited on chip to be below 15 dBm even at high compression levels. Finally, a complete characterization of the SCFE in the Rx and Tx modes is presented, also showing the measurement of the recovery time in the presence of large-signal interferences.
MFVC: Urban Traffic Scene Video Caption Based on Multimodal Fusion
Authors: Li Mingxing , Zhang Hao , Xu Cheng , Yan Chenyang , Liu Hongzhe , Li Xuewei
Published: September 2022

With the development of electronic technology, intelligent cars can gradually realize more complex artificial intelligence algorithms. The video caption algorithm is one of them. However, current video caption algorithms only consider single-visual information when applied to urban traffic scenes, which leads to the failure to generate accurate captions of complex sets. The multimodal fusion algorithm based on Transformer is one of the solutions to this problem. However, the existing algorithms have the difficulties of a low fusion performance and high computational complexity. We propose a new video caption Transformer-based model, the MFVC (Multimodal Fusion for Video Caption), to solve these issues. We introduce audio modal data and the attention bottleneck module to increase the available information to describe the generative model and improve the model effect with less operation costs through the attention bottleneck module. Finally, the experiment is conducted on the available datasets, MSR-VTT and MSVD. Meanwhile, to verify the effect of the model on the urban traffic scene, the experiment is carried out on the self-built traffic caption dataset BUUISE, and the evaluation index confirms the model. This model can achieve good results on both available datasets and urban traffic datasets and has excellent application prospects in the intelligent driving industry.
Semantic Segmentation of Side-Scan Sonar Images with Few Samples
Authors: Yang Dianyu , Wang Can , Cheng Chensheng , Pan Guang , Zhang Feihu
Published: September 2022

Underwater sensing and detection still rely heavily on acoustic equipment, known as sonar. As an imaging sonar, side-scan sonar can present a specific underwater situation in images, so the application scenario is comprehensive. However, the definition of side scan sonar is low; many objects are in the picture, and the scale is enormous. Therefore, the traditional image segmentation method is not practical. In addition, data acquisition is challenging, and the sample size is insufficient. To solve these problems, we design a semantic segmentation model of side-scan sonar images based on a convolutional neural network, which is used to realize the semantic segmentation of side-scan sonar images with few training samples. The model uses a large convolution kernel to extract large-scale features, adds a parallel channel using a small convolution kernel to obtain multi-scale features, and uses SE-block to focus on the weight of different channels. Finally, we verify the effect of the model on the self-collected side-scan sonar dataset. Experimental results show that, compared with the traditional lightweight semantic segmentation network, the model’s performance is improved, and the number of parameters is relatively small, which is easy to transplant to AUV.
UI dApps Meet Decentralized Operating Systems
Authors: Skowroński Rafał , Brzeziński Jerzy
Published: September 2022

The advent of Ethereum opened up a pandora box of decentralized possibilities. While allowing for the replicated, decentralized computation of Turing-complete instructions, platforms such as Ethereum do not offer the possibility of direct, interactive, real-time processing of users’ inputs that could later affect the decentralized state machine. They cannot directly observe, replicate and authenticate users’ actions performed in real-time while presenting the results of these. They lack mechanics that would incentivize full-nodes to provide low-latency-constrained services to users in-between epochs of a decentralized state machine, thus pushing dApps’ developers towards hybrid architectures—ones employing centralized servers while not even considering certain applications, due to the aforementioned limitations. In this research paper, we explore our results of an attempt to create a ‘decentralized operating system’ user experience a reality. We propose an architecture which solves the problems of the responsiveness and finalization of multiple actions performed by users in real-time—without the need for users to pre-authenticate but after having presented a single, unitary consent to commit—through the hereby proposed Deferred Authentication mechanism. To allow for this, we employ an in-house developed #GridScript programming language, used by our decentralized state machine, along with a computer-vision-enabled and AI-aided mobile app (available for both iOS and Android). We introduce the concept of Decentralized Processing Threads (DPTs) and see how these enable fascinating possibilities. In addition, we look into how Access-Control-Lists (ACLs)-enabled, incentivized storage, incentivized Sybil-proof communication, embedded firewall apparatus, integrated off-the-chain payments, and crypto-incentivized off-the-chain storage aid such a system and thus render it as feasible. We highlight various interesting troubles we have encountered, such as state recovery after disconnects of the UI and the replication of its state across both nodes maintaining the network and web browsers. We depict ‘off-the-chain’ mechanics, which we use to reward for real-time services provided to users by nodes maintaining the network. We tackle crypto-incentivized WebRTC swarms not needing centralized servers for signaling. We look into a user-friendly approach to Non-Fungible Tokens (NFTs). The test-bed is readily available with multiple functional UI dApps already in place. Indeed, the paper presents UI and UX design decisions we have undertaken based on conclusions from statistical research results on a group of 50,341 volunteers over 4 years, which we have used to formulate what we codenamed as the Venice UI/UX design paradigm. We extend upon the notion of Token Pools to allow for the Sybil-proof incentivization of multiple-peers from a single data structure stored on the decentralized state machine.
Approximate Floating-Point Multiplier based on Static Segmentation
Authors: Di Meo Gennaro , Saggese Gerardo , Strollo Antonio G. M. , De Caro Davide , Petra Nicola
Published: September 2022

In this paper a novel low-power approximate floating-point multiplier is presented. Since the mantissa computation is responsible for the largest part of the power consumption, we apply a novel approximation technique to mantissa multiplication, based on static segmentation. In our approach, the inputs of the mantissa multiplier are properly segmented so that a small inner multiplier can be used to calculate the output, with beneficial impact on power and area. To further improve performance, we introduce a novel segmentation-and-truncation approach which allows us to eliminate the shifter normally present at the output of the segmented multiplier. In addition, a simple compensation term for reducing approximation error is employed. The accuracy of the circuit can be tailored at the design time, by acting on a single parameter. The proposed approximate floating-point multiplier is compared with the state-of-the-art, showing good performance in terms of both precision and hardware saving. For single-precision floating-point format, the obtained NMED is in the range 10−5–7 × 10−7, while MRED is in the range 3 × 10−3–1.7 × 10−4. Synthesis results in 28 nm CMOS show area and power saving of up to 82% and 85%, respectively, compared to the exact floating-point multiplier. Image processing applications confirm the expectations, with results very close to the exact case.
Adversarial Image Colorization Method Based on Semantic Optimization and Edge Preservation
Authors: Gui Tingting , Zhan Weida , Gu Xing , Hu Jiahui
Published: September 2022

As a medium for transmitting visual information, image is a direct reflection of the objective existence of the natural world. Grayscale images lack more visual information than color images. Therefore, it is of great significance to study the colorization of grayscale images. At present, the problems of semantic ambiguity, boundary overflow and lack of color saturation exist in both traditional and deep learning methods. To solve the above problems, an adversarial image colorization method based on semantic optimization and edge preservation is proposed. By improving generative and discriminative networks and designing loss functions, deeper semantic information and sharper edges of images can be learned by our network. Our experiments are carried out on the public datasets Place365 and ImageNet. The experimental results show that the method in this paper can reduce the color anomaly caused by semantic ambiguity, suppress the color blooming in the image boundary area and improve the saturation of the image. Our work achieves competitive results on objective indicators of peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and learned perceptual image patch similarity (LPIPS), with values of 30.903 dB, 0.956 and 0.147 on Place365 and 30.545 dB, 0.946 and 0.150 on ImageNet, which proves that this method can effectively colorize grayscale images.
Analysis and Error Separation of Capacitive Potential in the Inductosyn
Authors: Liu Chengjun , Sun Jianfei , Zhang Yifei , Shang Jing
Published: September 2022

High-precision rotor position information is usually needed in permanent-magnet synchronous motors, which are critical to high-performance motor control based on vector algorithm. Therefore, inductosyn is the best choice for the permanent-magnet synchronous motor position sensor. Capacitive potential is an important component of the ineffective potential in the inductosyn angle measuring system. When the effective potential of the inductosyn approaches zero, the proportion of capacitive potential in the output potential will be greatly amplified. As a result, the zero-position accuracy will be seriously affected. Error potential and effective potential always exist at the same time, so it is difficult to measure and study quantitatively. In this paper, the capacitance network model of inductosyn was established and the analytical calculation method was proposed. The factors affecting the capacitive potential and the suppression strategy were studied through the combination of theoretical analysis and the finite element method. In addition, the error separation method of capacitive potential was also proposed in this paper, which realized the accurate measurement of this part of error. The accuracy of the theoretical calculation and finite element analysis was verified by the experimental results.
Bio-Waste as a Substitute for the Production of Carbon Dioxide Adsorbents: A Review
Authors: Sołtysik Marcelina , Majchrzak-Kucęba Izabela , Wawrzyńczak Dariusz
Published: September 2022

Bioadsorbent, obtained as a result of the processing of bio-waste, has recently gained popularity as a material that adsorbs greenhouse gases, mainly carbon dioxide. Bio-waste, mainly residues from food industry operations, is a waste to be landfilled or composted and can be a potential substrate for bioadsorbent production. Bioadsorbents used for carbon capture must, above all, have low production costs and high adsorption efficiency. This review covers popular bioadsorbents that have been tested for their ability to adsorb carbon dioxide. The paper compares bioadsorbent production methods, physicochemical properties, adsorption isotherms, surfaces, and their porosity. There is a lack of data in the literature on the topic of carbon dioxide adsorption on large-scale plants in the target environment. Therefore, further research needs to fill in the gaps to identify the promised potential of these bioadsorbents.
Development and Properties of a Similar Material to Coal
Authors: Zhan Keliang , Xue Junhua
Published: September 2022

In the mining process, protective-seam mining is one of the most effective measures to prevent and control coal and gas outburst accidents across the world. To accurately obtain the fracture development characteristics for protected coal in a similar physical simulation (to two-dimensional (2D) protective-seam mining), a novel and similar material to coal was developed. The similar material was prepared by mixing pulverized coal with a certain particle-size distribution and a water solution of sodium humate, which were separately taken as the aggregate and binder, followed by pressing and drying. Numerous orthogonal proportioning tests revealed that, under the molding pressure of 15 MPa, the unit weight and porosity of the similar material tended to be stable and approach that of raw coal. The similar material has a high compressive strength that is regulatable over a range as wide as 0.5~2.8 MPa and has an approximately linear direct proportional relation with the binder concentration. The adsorption and desorption tests revealed that the similar material features favorable adsorption properties, and its adsorption isotherm agrees with that of raw coal. The similar material is also characterized by a low price for its raw materials, no toxic or side effects, simple proportioning, stable properties, and the convenient regulation of various physical and mechanical parameters. Therefore, it can be used to simulate raw coal with different strengths.
Australia’s Energy Security and Statecraft in an Era of Strategic Competition
Authors: Vivoda Vlado
Published: September 2022

Previously published studies on Australia’s energy security did not examine the country’s domestic energy security situation in tandem with its international energy statecraft. This paper fills this research gap. In order to provide a robust analysis of a country’s strategic options in the energy sector, it is paramount to balance domestic and international dimensions, along with internal and external factors. The paper utilizes the strengths, weaknesses, opportunities, and threats (SWOT) method to review Australia’s strategic options by balancing the inward-looking, domestic risk minimization dimension (energy security), with the outward-looking, international power projection dimension (energy statecraft). The paper also applies the 4A framework (availability, accessibility, affordability, and acceptance) to assess Australia’s energy security performance. On the one hand, the results demonstrate that Australia has many strengths and opportunities as a reliable and stable energy supplier, endowed with traditional and renewable energy resources, and critical minerals. On the other hand, numerous internal weaknesses and external threats may affect Australia’s strategic options in the future. The most pressing issue is the historical lack of strategic government intervention in the energy market, which has, paradoxically, resulted in domestic energy accessibility and affordability crisis. The market-based approach is also the main reason why Australia has not transformed its energy resources into capabilities to be used as instruments of statecraft. The paper uses the SWOT analysis and the 4A assessment as the basis for discussion on how Australia can transform its energy sector weaknesses and threats into strengths and opportunities, to benefit the national interest.
The Effect of Dietary Inclusion of Microalgae Schizochytrium spp. on Ewes’ Milk Quality and Oxidative Status
Authors: Zisis Foivos , Kyriakaki Panagiota , Satolias Fotis F. , Mavrommatis Alexandros , Simitzis Panagiotis E. , Pappas Athanasios C. , Surai Peter F. , Tsiplakou Eleni
Published: September 2022

An unprecedented challenge for nutritionists arises during the 21st century in order to produce highly nutritious and functional food which promotes human health. Polyunsaturated fatty acids (PUFA) that are highly contained in microalgae have broadly been confirmed for preventing cardiovascular diseases and regulating immune-oxidative status. However, their optimum dietary inclusion level needs to be defined since PUFA are prone to oxidation. For this purpose, 24 cross-bred dairy ewes, were separated into four groups (n = 6) and were fed with different levels of microalgae Schizochytrium spp. [0 (CON, no microalgae), 20 (SC20), 30 (SC30) and 40 (SC40) g/ewe/day] for 60 days. The results showed that although the production parameters were not impaired, milk fat content was decreased in medium and high-level supplemented groups while protein content was suppressed only for the medium one. Concerning the fatty acids (FA) profile, the proportions of C14:0, trans C18:1, trans-11 C18:1, cis-9, trans-11 C18:2, trans-10, cis-12 C18:2, C20:5 (EPA), C22:5n-6 (DPA), C22:6n-3 (DHA), the total ω3 FA and PUFA were significantly increased, while those of C18:0, cis-9 C18:1 and C18:2n-6c were decreased in the milk of treated ewes. Additionally, in the S40 group an oxidative response was induced, observed by the increased malondialdehyde (MDA) levels in milk and blood plasma. In conclusion, the dietary inclusion of 20 g Schizochytrium spp./ewe/day, improves milks’ fatty acid profile and seems to be a promising way for producing ω3 fatty acid-enriched dairy products.
Targeting Virulence Factors of Candida albicans with Natural Products
Authors: Bu Qing-Ru , Bao Meng-Yuan , Yang Yue , Wang Tian-Ming , Wang Chang-Zhong
Published: September 2022

Natural products derived from natural resources, including nutritional functional food, play an important role in human health. In recent years, the study of anti-fungal and other properties of agri-foods and derived functional compounds has been a hot research topic. Candida albicans is a parasitic fungus that thrives on human mucosal surfaces, which are colonized through opportunistic infection. It is the most prevalent cause of invasive fungal infection in immunocompromised individuals, resulting in a wide variety of clinical symptoms. Moreover, the efficacy of classical therapeutic medications such as fluconazole is often limited by the development of resistance. There is an ongoing need for the development of novel and effective antifungal therapy and medications. Infection of C. albicans is influenced by a great quantity of virulence factors, like adhesion, invasion-promoting enzymes, mycelial growth, and phenotypic change, and among others. Furthermore, various natural products especially from food sources that target C. albicans virulence factors have been researched, providing promising prospects for C. albicans prevention and treatment. In this review, we discuss the virulence factors of C. albicans and how functional foods and derived functional compounds affect them. Our hope is that this review will stimulate additional thoughts and suggestions regarding nutritional functional food and therapeutic development for patients afflicted with C. albicans.
Enhancement of Polypeptide Yield Derived from Rapeseed Meal with Low-Intensity Alternating Magnetic Field
Authors: Guo Lina , Guo Yiting , Wu Ping , Liu Shiyi , Gu Chen , Yolandani  , Wu Mengdi , Ma Haile , He Ronghai
Published: September 2022

The application of physical processing technologies in fermentation is an effective way to improve the quality of substrates. The purpose of the study was to evaluate the feasibility of enhancing the polypeptides of rapeseed meal (RSM) by a low-intensity alternating magnetic field (LF-MF)-assisted solid-state fermentation. A protease-producing strain B16 from RSM was isolated and identified as Bacillus velezensis by analyzing its morphology and 16S rDNA sequencing. Then, it was employed in solid-state fermentation for polypeptide production. The results showed that the neutral protease activity could reach 147.48 U/mL when B.velezensis was cultured under suitable conditions. The protease activity increased rapidly on the 2.5th day of traditional fermentation, while the polypeptide yield reached the maximum on the third day. The highest polypeptides content was achieved by LF-MF-assisted fermentation at magnetic field intensity 140 Gs, treatment 4 h, magnetic field intervention after 16 h of inoculation, and rotation speed 50 rpm/min, which increased by 18.98% compared with traditional fermentation. Therefore, LF-MF-assisted fermentation effectively enhanced the polypeptide yield. The results suggested that LF-MF technology would be widely used to produce bioactive components from agro-industrial by-products.
Effect of Hydrothermal Treatment on the Structure and Functional Properties of Quinoa Protein Isolate
Authors: He Xingfen , Wang Bin , Zhao Baotang , Meng Yuecheng , Chen Jie , Yang Fumin
Published: September 2022

The aim of this study was to investigate the effects of hydrothermal treatment at different temperatures and times on the structure and functional properties of quinoa protein isolate (QPI). The structure of QPI was investigated by analyzing changes in the intrinsic fluorescence spectrum, ultra-violet (UV) spectrum, and Fourier transform infrared spectrum. The solubility, water/oil-holding capacity, emulsifying activity, and emulsion stability of QPI were studied, as were the particle size and the thermogravimetric properties of QPI. The results showed that the average particle size of QPI gradually increased with the increase in hydrothermal treatment time and temperature, and reached a maximum value of 121 °C for 30 min. The surface morphology also became rough and its thermal stability also increased. The endogenous fluorescence and UV spectral intensity at 280 nm decreased gradually with increasing hydrothermal treatment time and temperature, and reduced to the minimum values at 121 °C for 30 min, respectively. After hydrothermal treatment, the secondary structure of QPI tended to be disordered. The functional properties of QPI after treatment were all superior to those of the control. The results of this study might provide a basis for the processing and utilization of QPI.