bluuebunny/crossref_metadata_2025 huggingface dataset:
Prescribed Performance Rotating Formation Control of Multi-Spacecraft Systems with Uncertainties
Authors: Liu Yan , Qin Kaiyu , Li Weihao , Shi Mengji , Lin Boxian , Cao Lu
Published: November 2022

This paper investigates the problem of rotating formation control for multi-spacecraft systems with prescribed performance in the presence of model uncertainties. Firstly, The spacecraft dynamics containing unmodelled parts is described in a polar coordinate system, which is to solve the problem of the controllable angular velocity of rotating formation. Then, the prescribed performance control method is improved by developing new prescribed performance functions. Based on the improved prescribed performance control method, the distributed controller is designed for multi-spacecraft systems to achieve rotating formations with prescribed performance, i.e., the formations error converges to a predefined arbitrarily small residual set, with convergence time no less than a prespecified value. And an RBF neural network is used to fit the unmodelled components of the spacecraft dynamics. Compared with the existing works of literature, this paper not only solves the robust prescribed performance rotating formation control of multi-spacecraft system, but also acheives rotating formation with adjustable angular velocity. Finally, the Lyapunov approach is employed for convergence analysis, and simulation results are provided to illustrate the effectiveness of the theoretical results.
Design and Validation of a Test for the Types of Mathematical Problems Associated with Reading Comprehension
Authors: Díaz Verónica
Published: November 2022

Being able to understand a written text is an essential life skill, as is solving a problem, which configures a bidirectional relationship between both skills. With regard to reading comprehension, at least three specific levels are required to achieve a full understanding of a text: literal, inferential, and critical. For its part, mathematics has changed substantially in recent decades, prioritizing problem-solving as the central axis of the teaching process as it constitutes a resource for learning. This study connects both skills and aims to design and validate a mathematical problem-solving test contextualized to the quadratic function, to assess the level of reading comprehension of secondary school students. The study is nonexperimental, cross-sectional, and focused on psychometric aspects since it aims to validate a measurement instrument. It was applied on a pilot basis to three municipal secondary education courses in Chile. The content, construct, discrimination, and reliability validation tests carried out allowed us to demonstrate that the problem-solving test contextualized to the quadratic function is a reliable instrument to produce knowledge in educational research.
Exploring the Learning Experience of High-Performing Preclinical Undergraduate Dental Students: A Qualitative Study
Authors: Lin Galvin Sim Siang , Tan Wen Wu , Afrashtehfar Kelvin I.
Published: November 2022

The current study aimed to explore the perceptions of high-performing undergraduate dental students in learning dental materials science. One-on-one semi-structured interviews with high-performing students who scored 80 marks and above in dental materials were conducted using an online video-chat platform. A purposeful sampling method was employed, and six students fulfilled the criteria. The interviews were audio-recorded, transcribed verbatim, and analyzed qualitatively using a thematic approach. Three major themes were identified: (1) Learning strategies, (2) Learning enablers and barriers, and (3) Coping with learning challenges. Six sub-themes emerged from the “learning strategies” theme: memorizing and repeating, peer learning, seeking learning resources, study planning, paying attention during class, and mnemonics. The enabler sub-themes include motivation, lecture notes, teachers, and hands-on, whereas the barrier sub-theme is content understanding. Moreover, family support and de-stress appeared as the sub-themes in coping with learning challenges. In short, the present exploratory study identified several major themes and sub-themes that can help dental educators comprehend the complexity of learning dental materials science and how it affects students’ academic performances. The current findings also offer learning recommendations for low-performing students to improve their academic achievements in the dental materials science course.
An Ultra-Low Power Fast Transient LDO with Dynamic Bias
Authors: Liu Kun , Xie Yaoming , Li Xiaoran , Zhang Lei
Published: November 2022

A low-dropout linear regulator (LDO) without external capacitors is designed, combining ultra-low power consumption and ultra-fast transient response. The common support voltage of the LDO is 2.5 V to 3.6 V with a stable output voltage of 1.2 V and an output current dynamic range of 10 μA to 20 mA to supply power to other circuit modules. A Rail-to-Rail Input-Output (RRIO) Class AB push-pull output amplifier and a dynamic bias circuit are also designed. Meanwhile, a dynamic bias circuit which can regulate the operating current of error amplifier is proposed by monitoring output voltage variation in order to provide a larger compensation current to the operational amplifier when the load current changes are at high frequency and maintain ultra-low operating current at low clock frequency. The LDO is designed without resistors, and the deep well NMOS is applied in the output stage in order to reduce the difficulty of loop compensation. Designed in a 180 nm CMOS process, the post-simulation results show that under the condition of 40 °C and 3 V input voltage, the static power consumption is 31.7 nA with a settling time (±5%) of less than 35 ns.
Optimizable Control Barrier Functions to Improve Feasibility and Add Behavior Diversity while Ensuring Safety
Authors: Li Shilei , Yuan Zhimin , Chen Yun , Luo Fang , Yang Zhichao , Ye Qing , Fu Wei , Fu Yu
Published: November 2022

Ensuring safety while retaining maximum performance is a basic requirement for automatic cyber-physical systems, especially for safety-critical applications. A quadratic programming optimization framework called MPC-CBF has recently been presented, which directly unifies model predictive control (MPC) with control barrier functions (CBFs) over the prediction time horizon. However, the conservative nature of CBFs can lead to feasibility problems in real applications. Based on the analysis of the role of the decay rate and the conservative accumulation phenomenon in standard CBF formulations, this paper proposes to directly optimize CBF constraints within the MPC framework. By regarding CBFs as a safety restriction level indicator and an optimizable constraint within the MPC framework, the trade-off between feasibility and safety can be adaptively optimized. The proposed Optimizable CBF (OCBF) model removes the hyper-parameters selection problem in standard CBFs and can adaptively adjust the safety restriction level and increase behavior diversity by adding the corresponding objects in the cost function in MPC. To eliminate the accumulation effects of actual values of the CBF constraints in previous time steps, this paper further proposes a General OCBF (GOCBF) formulation. Compared with existing formulations, the safety margin defined in our GOCBF has intuitive physical meanings and thus provides a more flexible and intuitive mechanism to compromise different objects in terms of ensuring safety while not undermining basic feasibility. Experimental results demonstrate that our algorithm provides a more flexible and intuitive mechanism to achieve this, thus improving feasibility and adding behavior diversity in the MPC-CBF framework.
A Low-Power, Fully Integrated SC DC–DC Step-Up Converter with Phase-Reduced Soft-Charging Technique for Fully Implantable Neural Interfaces
Authors: Song Sangmin , Kim Minsung , Park Sung-Yun
Published: November 2022

We present a high-power conversion efficiency (PCE) on-chip switched-capacitor (SC) DC–DC step-up converter for a fully implantable neural interface operating with less than a few tens µW from energy harvesting. To improve the PCE in such light loads and wide variations of voltage-conversion ratio (VCR), which is a typical scenario for ultra-low-power fully implantable systems depending on energy harvesting, a phase-reduced soft-charging technique has been implemented in a step-up converter, thereby achieving very low VCR-sensitive PCE variation compared with other state-of-the-art works. The proposed DC–DC converter has been fabricated in a standard 180 nm CMOS 1P6M process. It exhibits high PCE (~80%) for wide input and output ranges from 0.5 V to 1.2 V and from 1.2 V to 1.8 V, respectively, with switching frequencies of 0.3–2 MHz, achieving a peak efficiency of 82.6% at 54 µW loads.
Cooperative Content Precaching Scheme Based on the Mobility Information of Vehicles in Intermittently Connected Vehicular Networks
Authors: Nam Youngju , Bang Jaejeong , Choi Hyunseok , Shin Yongje , Lee Euisin
Published: November 2022

Intermittently connected vehicular networks (ICVNs) consist of vehicles moving on roads and stationary roadside units (RSUs) deployed along roads. In ICVNs, the long distances between RSUs and the large volume of vehicular content lead to long download delays to vehicles and high traffic overhead on backhaul links. Fortunately, the improved content storage size and the enhanced vehicular mobility prediction afford opportunities to ameliorate these problems by proactively caching (i.e., precaching) content. However, existing precaching schemes exploits RSUs and vehicles individually for content precaching, even though the cooperative precaching between them can reduce download delays and backhaul link traffic. Thus, this paper proposes a cooperative content precaching scheme that exploits the precaching ability of both vehicles and RSUs to enhance the performance of content downloads in ICVNs. Based on the trajectory and velocity information of vehicles, we first select the optimal relaying vehicle and the next RSUs to cache the requested content proactively and provide it to the requester vehicle optimally. Next, we calculate the optimal content precaching amount for each of the relaying vehicle and the downloading RSUs by using a mathematical model that exploits both the dwell time in an RSU and the contact time between vehicles. To compensate for the error of the mobility prediction in determining both the dwell time and the contact time, our scheme adds a guardband to the optimal content precaching amount by considering the expected reduced delay. Finally, we evaluate the proposed scheme in various simulation environments to prove the achievement of efficient content download performance by comparing with the existing schemes.
Siamese Neural Networks on the Trail of Similarity in Bugs in 5G Mobile Network Base Stations
Authors: Zarębski Sebastian , Kuzmich Aleksander , Sitko Sebastian , Rusek Krzysztof , Chołda Piotr
Published: November 2022

To improve the R&D process by reducing duplicated bug tickets, we used the idea of composing a BERT encoder as a Siamese network to create a system for finding similar existing tickets. We proposed several different methods of generating artificial ticket pairs to augment the training set. Two phases of training were conducted. The first showed that only approximately 9% of pairs were correctly identified as certainly similar. Only 48% of the test samples were found to be pairs of similar tickets. With fine-tuning, we improved that result to 81%, which is a number describing a set of common decisions between the engineer in the company and the solution presented. With this tool, engineers in the company receive a specialized instrument with the ability to evaluate tickets related to a security bug at a level close to an experienced company employee. Therefore, we propose a new engineering application in corporate practice in a very important area with Siamese network methods that are widely known and recognized for their efficiency.
Design of Portable Self-Oscillating VCSEL-Pumped Cesium Atomic Magnetometer
Authors: Jin Kai , Geng Xuxing , Liang Zhi , Tang Wangwang , Xiao Jianfeng , Hu Heng , Huang Guangming , Li Gaoxiang , Yang Guoqing , Liang Shangqing
Published: November 2022

With the demand for fast response of magnetic field measurement and the development of laser diode technology, self-oscillating laser-pumped atomic magnetometers have become a new development trend. In this work, we designed a portable self-oscillating VCSEL-pumped Cs atom magnetometer, including the probe (optical path) and circuits. The signal amplification and feedback loop of the magnetometer, VCSEL laser control unit, and atomic cell temperature control unit were realized. We tested the performance of the magnetometer in the metering station. Finally, The performance of the VCSEL-pumped magnetometer designed in this work was compared with that of a CS-3 lamp-pumped self-oscillating atomic magnetometer; their performance was found to be mostly in the same order of magnitude, while the power consumption of our magnetometer was 3 W less than that of the CS-3. This work represents an exploratory attempt to integrate and miniaturize a portable self-oscillating VCSEL-pumped Cs atomic magnetometer.
Timing Analysis and Optimization Method with Interdependent Flip-Flop Timing Model for Near-Threshold Design
Authors: Cao Peng , Qin Yuan , Jiang Haiyang
Published: November 2022

Near-threshold Voltage (NTV) design is receiving wide attention due to remarkable energy efficiency improvement at the cost of performance degradation. The interdependency between the setup–hold time and clock-to-q delay of flip-flops has been exploited in the Super-threshold Voltage (STV) domain to improve circuit performance but faces the severe challenge of nonlinear relationship and wider effective coverage in the NTV region, which prevents the application of interdependent flip-flop model for timing analysis and optimization for NTV design. In this paper, a novel interdependent flip-flop timing model is proposed by Artificial Neural Network (ANN) to predict the clock-to-q delay with training data generated by SPICE simulation in a restricted hexagonal area of the two-dimensional setup-hold time space. By integrating the proposed model into Static Timing Analysis (STA) flow, a novel iterative optimization method is proposed to improve performance for NVT circuits based on a Genetic Algorithm (GA). The proposed timing analysis and optimization method were validated under Semiconductor Manufacturing International Corporation (SMIC) 40 nm process at the voltage of 0.6 V with the International Symposium on Circuits and Systems (ISCAS)’89 benchmark circuits. Experimental results demonstrate that the ANN-based interdependent timing model for flip-flop achieves considerable accurate prediction with the Mean Absolute Relative Error (MARE) of less than 0.69%. The minimum clock periods for ISCAS’89 benchmark circuits are reduced by 1.70~6.28% compared to traditional STA results without any setup and hold violations and hardware cost, which achieves at most 6.7% performance improvement for NTV design.
Motor Imaging EEG Signal Recognition of ResNet18 Network Based on Deformable Convolution
Authors: Du Xiuli , Li Kai , Lv Yana , Qiu Shaoming
Published: November 2022

EEG signals with a weak amplitude, complex background noise, randomness, significant individual differences, and small data volume lead to insufficient feature extraction and low classification accuracy. Spurred by these concerns, this paper proposes a motor imaging EEG signal classification method based on fusing the improved ResNet18 network with the deformable convolutional network (DCN). Specifically, the original signal’s local airspace characteristics are enhanced by the common spatial patterns (CSP), and the time-frequency domain characteristics are displayed using the short-time Fourier transform (STFT). Then, the signal is converted into a time-frequency map, where a deformable convolution is applied to capture the contour characteristics of the time-frequency map. This strategy solves the problems of traditional convolution related to hard rules, i.e., the convolutional kernel shape can only be a square or rectangular core and cannot be dynamically changed according to the recognition target, resulting in a low recognition rate, prohibiting the network from extracting hidden features and affording enhanced identification and classification. Experimental results demonstrate that our method attains an average classification accuracy on a two-classification and two four-classification motor imaging EEG signals of 90.30%, 86.50%, and 88.08%, respectively, which is much higher than current work, proving our method’s effectiveness.
Multi-Objective Computational Aided Design Tool Using Pareto Analysis
Authors: de Castro e Castro Pedro Augusto , Morais Lenin Martins Ferreira , de Oliveira Thiago Ribeiro
Published: November 2022

Due to commercial restrictions, aiming for greater product competitiveness, uninterruptible power supplies (UPS) must exhibit optimal design in order to reduce losses, volume, and noise, as well as increase power density. However, the optimal design of a power electronic converter is a complex and repetitive task, often requiring the use of a computational tool. The main objective of this work is to present a unified computational tool capable of helping the designer to find the optimal design for a given power electronic converter. This paper will show a comparison between two power converter design techniques: the traditional industrial design approach and a multi-objective optimization approach using Pareto analysis. For this purpose, the total performance of a 10 kVA UPS was compared in terms of losses and volumes. The use of the proposed computational tool to optimize the design resulted in a UPS with better power density and efficiency.
Mixed Electric Field of Multi-Shaft Ship Based on Oxygen Mass Transfer Process under Turbulent Conditions
Authors: Wang Xiangjun , Wang Shichuan , Hu Yucheng , Tong Yude
Published: November 2022

The theoretical basis for a multi-physics coupling modeling involving a turbulence flow field and a ship’s electric field was analyzed using the principles of electrochemistry and hydrodynamics. Considering the mass transfer of oxygen in the cathode reaction of electrochemical corrosion, the boundary element method was adopted to construct a corrosion electric field model for a multi-shaft ship under navigation. After dissecting the equivalent circuit resistance of the mechanical structure of a ship’s shaft, the initial phase difference of the equivalent resistance between different shafting systems of a multi-shaft ship was analyzed to reveal the regularity of variation of the ship corrosion mixed electric field, when the contact positions of the shaft grounding device were different. A ship model experiment was conducted to verify the correctness of the simulation model. As shown in the results, when the initial phase difference of two-shaft ship shafting equivalent resistance increased from 0° to 45°, 90°, 135°, and 180°, the amplitude of the ship’s mixed electric field varied by less than 3.7%, which was practically negligible. However, the amplitude of the ship’s shaft-rate electric field decreased by 8.30%, 25.4%, 50.2%, and 88.0%, respectively. Moreover, the minimum value of the shaft-rate electric field accounted for 4.11% of the maximum value. This significantly increased the difficulty of marine target detection based on electric field sensors.
Emerging Spiral Waves and Coexisting Attractors in Memductance-Based Tabu Learning Neurons
Authors: Sriram Balakrishnan , Tabekoueng Zeric Njitacke , Karthikeyan Anitha , Rajagopal Karthikeyan
Published: November 2022

Understanding neuron function may aid in determining the complex collective behavior of brain systems. To delineate the collective behavior of the neural network, we consider modified tabu learning neurons (MTLN) with magnetic flux. Primarily, we explore the rest points and stability of the isolated MTLN, as well as its dynamical characteristics using maximal Lyapunov exponents. Surprisingly, we discover that for a given set of parameter values with distinct initial conditions, the periodic and the chaotic attractors may coexist. In addition, experimental analysis is carried out using a microcontroller-based implementation technique to support the observed complex behavior of the MTLN. We demonstrate that the observed numerical results are in good agreement with the experimental verification. Eventually, the collective behaviors of the considered MTLN are investigated by extending them to the network of the lattice array. We discover that when the magnetic flux coupling coefficient is varied in the presence of an external stimulus, the transition from spiral waves to traveling plane waves occurs. Finally, we manifest the formation of spiral waves in the absence of an external stimulus in contrast to previous observations.
Eight-Wavelength-Switchable Narrow Linewidth Erbium-Doped Fiber Laser Based on Cascaded Superimposed High-Birefringence Fiber Bragg Grating
Authors: Li Dongyuan , Feng Ting , Sun Weiwei , Wu Shengbao , Yan Fengping , Li Qi , Yao Xiaotian Steve
Published: November 2022

A narrow-linewidth eight-wavelength-switchable erbium-doped fiber laser is proposed, and its performance is demonstrated. A cascaded superimposed high-birefringence fiber Bragg grating is used to determine the lasing wavelengths. The combination of a Fabry–Pérot filter and a single-coupler ring is adopted to achieve the single-longitudinal-mode (SLM) oscillation. By introducing the enhanced polarization-hole-burning effect to suppress the gain competition between different wavelength lasers, the stable lasing output is guaranteed. When the pump power is 200 mW, by adjusting the polarization controller to balance the gain and loss in the laser cavity, 24 switchable lasing modes are achieved, including 8 single-wavelength operations and 16 dual-wavelength operations with orthogonal polarization states. For single-wavelength operations, every laser is in the SLM lasing state, with a high stabilized optical spectrum, a linewidth of approximately 1 kHz, an optical signal-to-noise ratio (OSNR) as high as 73 dB, a relative intensity noise of less than −150 dB/Hz, and very good polarization characteristics. For dual-wavelength operations, the lasers also have a stable spectrum and an OSNR as high as 65 dB. The proposed fiber laser has a wide range of applications, including long-haul coherence optical communication, optical fiber sensing, and dense wavelength-division-multiplexing.
Study on the Impact of Clean Power Investment on Regional High-Quality Economic Development in China
Authors: Zhuang Xianrong , Pan Lingying
Published: November 2022

In 2017, the 19th CPC National Congress proposed to “establish a sound economic system of green, low-carbon and circular development”, which indicates the direction of high-quality economic development in the new era of China. Clean power investment is a powerful way to promote high-quality economic development by adopting non-fossil-energy utilization and low-emission technologies, as well as creating new jobs. Meanwhile, large-scale investment and a long investment return period result in negative effects on local economies. To better understand the effect of clean power investment, this paper selects panel data of thirty provinces in China from 2010 to 2019 to establish a spatial Durbin model to explore the impact of clean power investment on regional high-quality economic development. The results show that inter-regional high-quality economic development shows significant spatial auto-correlation characteristics. Clean power investment has not only a positive direct effect on high-quality economic development but also generates positive spatial spillover effects. Human capital, degree of government intervention, and urbanization rate have positive effects on regional high-quality economic development, while they play a suppressed role on neighboring regions.
Effects of Microplastic on Human Gut Microbiome: Detection of Plastic-Degrading Genes in Human Gut Exposed to Microplastics—Preliminary Study
Authors: Nugrahapraja Husna , Sugiyo Pramudya Wisnu Wicaksono , Putri Balqis Qonita , Ni’matuzahroh Ni’matuzahroh , Fatimah Fatimah , Huang Li , Hafza Nourhane , Götz Friedrich , Santoso Heri , Wibowo Anjar Tri , Luqman Arif
Published: November 2022

Microplastics are major pollutants in the environment, and it is currently established that microplastics have already entered human food chains and been incorporated into the human body through ingestion and inhalation. Several works in animal models have already reported the adverse effect of microplastic exposure on biological systems; however, the effect of microplastic contamination on human health is still far from understood. In previous work, we reported microplastic contamination in the digestive tract of the Indonesian coastal and highland population. Using the same stool samples, we extended our previous work by investigating gut microbial composition in samples with and without microplastic contamination using next-generation sequencing. We found that microplastic contamination does not affect overall gut microbial composition and the abundance of gut-health-related genes. However, we found a negative and positive correlation between specific types of microplastics with certain bacterial taxa, especially from the genera Roseburia, Clostridium, and Prevotella. Despite the lack of a profound effect on the gut microbiome, we detected for the first time the presence of genes encoding plastic-degrading enzymes in the human gut microbiome, suggesting an adaptation of gut microbiome to microplastic contamination.
Prediction of Primary Deformation Modulus Based on Bearing Capacity: A Case on Forest Road with a Light Falling Weight Deflectometer Zorn ZFG 3000 GPS
Authors: Grajewski Sylwester M.
Published: November 2022

Bearing capacity and compaction are among the most important and frequently used geotechnical parameters in road construction. The aim of this study was to determine the possibility of predicting the value of the primary deformation modulus E1 (obtained from measurements using a static plate load test—PLT) based on measurements with a Zorn light falling weight deflectometer (LFWD), type ZFG 3000 GPS, with a drop weight of 10 kg. A regression analysis was performed on 245 bearing capacity measurements that were taken on 46 forest road sections with various road surfaces. Different regression models were tested, from linear to logarithmic, polynomial, exponential and power models, but excluding polynomials of fourth and higher degree. The results showed that the prediction of E1 values (PLT) from the dynamic deformation modulus values Evd (LFWD) was possible. However, the reported unsatisfactory strength of the relationship between the two parameters was associated with a high risk of error (r = 0.64, R2 = 0.41, Se = 49.78). Neither the use of more complex non-linear regression models, nor the use of multiple regression by introducing an additional estimator in the form of the s/v ratio, significantly improved estimation results. The quality of the prediction of the E1 value was not constant. It varied, depending on the type of forest road, the use of geosynthetic reinforcement and the type of road subgrade. During the study, it was also found that the quality of the prediction of the E1 value could be improved by limiting the range of Evd values tested from above. It is advisable to continue this type of research, as the obtained results could form the basis for future development of national standards for the use of LFWDs to control the bearing capacity and compaction of forest road pavements.
A Detection Method for Individual Infected Pine Trees with Pine Wilt Disease Based on Deep Learning
Authors: Zhou Yan , Liu Wenping , Bi Haojie , Chen Riqiang , Zong Shixiang , Luo Youqing
Published: November 2022

Pine wilt disease (PWD) can cause destructive death in many species of pine trees within a short period. The recognition of infected pine trees in unmanned aerial vehicle (UAV) forest images is a key technology for automatic monitoring and early warning of pests. This paper collected UAV visible and multispectral images of Korean pines (Pinus koraiensis) and Chinese pines (P. tabulaeformis) infected by PWD and divided the PWD infection into early, middle, and late stages. With the open-source annotation tool, LabelImg, we labeled the category of infected pine trees at each stage. After coordinate-correction preprocessing of the ground truth, the Korean pine and Chinese pine datasets were established. As a means of detecting infected pine trees of PWD and determining different infection stages, a multi-band image-fusion infected pine tree detector (MFTD) based on deep learning was proposed. Firstly, the Halfway Fusion mode was adopted to fuse the network based on four YOLOv5 variants. Simultaneously, the Backbone network was initially designed as a dual branching network that includes visible and multispectral subnets. Moreover, the features of visible and multispectral images were extracted. To fully utilize the features of visible and multispectral images, a multi-band feature fusion transformer (MFFT) with a multi-head attention mechanism and a feed-forward network was constructed to enhance the information correlation between visible and multispectral feature maps. Finally, following the MFFT module, the two feature maps were fused and input into Neck and Head to predict the categories and positions of infected pine trees. The best-performing MFTD model achieved the highest detection accuracy with mean average precision values (mAP@50) of 88.5% and 86.8% on Korean pine and Chinese pine datasets, respectively, which improved by 8.6% and 10.8% compared to the original YOLOv5 models trained only with visible images. In addition, the average precision values (AP@50) are 87.2%, 93.5%, and 84.8% for early, middle, and late stages on the KP dataset and 81.2%, 92.9%, and 86.2% on the CP dataset. Furthermore, the largest improvement is observed in the early stage with 14.3% and 11.6%, respectively. The results show that MFTD can accurately detect the infected pine trees, especially those at the early stage, and improve the early warning ability of PWD.
Elucidation of the Taxonomy of Three Problematic East Asian Nola Leach, 1815, with Description of a New Species (Lepidoptera, Nolidae, Nolinae)
Authors: Cha Yeong-Bin , Bayarsaikhan Ulziijargal , László Gyula M. , Ronkay Gábor , Ronkay László , Bae Yang-Seop
Published: November 2022

The paper discusses the taxonomy of three East Asian Nola Leach, 1815 taxa, N. costimacula Staudinger, 1887, N. japonibia (Strand, 1920) and N. innocua Butler, 1880. We describe a new species N. galliphaga sp. nov. from Japan and South Korea and synonymize N. japonibia syn. nov. with N. costimacula. Type specimens, additional adults, and their genitalia are illustrated.
Anaerobic Digestion of Cereal Rye Cover Crop
Authors: Yang Liangcheng , Lamont Lucas D. , Sedbrook John C. , Heller Nicholas J. , Kopsell David E.
Published: November 2022

The rapid growth of cover crop planting area in the U.S. helps with erosion control, soil health, control of greenhouse gases, and also provides abundant biomass for the production of bioenergy and bioproducts. Given the cover crops’ compositional heterogeneity and variability, a tolerate platform technology such as anaerobic digestion (AD) is preferred but has not been widely used for cover crop biorefining. This study evaluated the biogas and methane yields from six cereal rye (Secale cereale L.) cover crops grown in the Midwest, using both bench- and pilot-scale anaerobic digesters. The effects of two critical factors, the total solids (TS) content and ensiling, on digester performance were also investigated. Methane yields of 174.79–225.23 L/kg-VS were obtained from the bench-scale tests using cereal rye as the mono feedstock. The pilot-scale test with no pH adjustment showed a slightly higher methane yield. Ensiling increased the methane yield by 23.08% at 6% TS, but disturbed AD at 8% TS, and failed AD at 10% and 15% TS. Findings from this study would help farmers and the biorefining industry to determine the baseline performance and revenue of cereal rye AD and to develop strategies for process control and optimization.
Superficial Velocity in Heterogeneous Two-Phase Systems with Truncated Fractal Distribution of Particle Concentration
Authors: Zhu Jianting
Published: November 2022

The interplay of particles in a heterogeneous multiparticle two-phase system and its effect on superficial velocity have not been well quantified. In this study, a new model is developed to examine the superficial velocity in a heterogeneous multiparticle two-phase system. To examine the heterogeneous effects to the potentially maximum extent, the particle concentration is assumed to follow a truncated fractal distribution, which is integrated into the free surface cell model. In a statistical sense, the multiparticle two-phase system is stationary, so the mean of spatial heterogeneity can be replaced by the ensemble mean. Since the underlying physical concept is rooted in the free surface cell model, the validity of the model should be, therefore, limited to the low-Reynolds number conditions. The developed model is compared to data from three representative experimental studies in the literature and it is found that the model can better capture the scatters in experimental data than the original free surface cell model. The model is also compared with three representative models and demonstrates reasonable results. While the deterministic free surface cell model underestimates the velocity, the cell model with truncated fractal distribution being incorporated can predict high velocity with a wide range of particle concentration heterogeneity.
Enhanced Energy Storage Using Pin-Fins in a Thermohydraulic System in the Presence of Phase Change Material
Authors: Saghir Mohamad Ziad
Published: November 2022

Energy storage has been an essential topic in thermal management. With the low conductivity of phase change material, the effort is to propose the best mechanism for heat transfer. In the present paper, pin-fins are used in the hydraulic system to transfer the heat coming from wastewater management into phase change material. Different flow rates have been tested, and it was found that pin-fins can create mixing in the flow chamber allowing a large convective heat flux to move heat into the phase change material. In the present design, it was found that natural convection assists in heat transfer. Additional findings suggested that the pin-fins height influence the heat transfer process. In the current configuration, 5 mm in height pin-fins demonstrated the best heat transfer when compared to pin-fins varying from 1 mm to 6 mm, respectively.
Extraction and Characterization of Lysozyme from Salted Duck Egg White
Authors: Yao Xinjun , Du Tianyin , Guo Jun , Lv Weiqiao , Adhikari Benu , Xu Jicheng
Published: November 2022

Salted duck egg white (SDEW), as the main by-product in the production process of salted egg yolk, has not been effectively used as a food resource because of its high salt concentration. This study creatively used isoelectric point precipitation, ultrafiltration, and cation exchange to separate and purify lysozyme from SDEW and preliminarily explored the enzymatic properties of lysozyme. The results showed that the relative molecular weight of lysozyme was about 14 KDa, and the specific activity of lysozyme reached 18,300 U/mg. Lysozyme had good stability in the temperature range of 30 °C to 60 °C and pH of 4 to 7. Metal ions, Fe2+, Cu2+, and Zn2+, strongly inhibited lysozyme activity. Different surfactants showed certain inhibition effects on lysozyme from SDEW, among which glycerin had the strongest inhibitory effect. This study aimed to provide a theoretical reference for industrial purification and production of lysozyme from SDEW.
An Innovative Approach in the Baking of Bread with CO2 Gas Hydrates as Leavening Agents
Authors: Srivastava Shubhangi , Kollemparembil Ann Mary , Zettel Viktoria , Claßen Timo , Mobarak Mohammad , Gatternig Bernhard , Delgado Antonio , Jekle Mario , Hitzmann Bernd
Published: November 2022

Gas (guest) molecules are trapped in hydrogen-bonded water molecules to form gas hydrates (GH), non-stoichiometric solids that resemble ice. High pressure and low temperature are typical conditions for their development, with van der Waals forces joining the host and guest molecules. This article study investigates the application of CO2 gas hydrates (CO2 GH) as a leavening agent in baking, with particular reference to the production of wheat bread. The main intention of this study is to better understand the complex bread dough formed by CO2 GH and its impact on product quality. This may enable the adaptation of CO2 GH in baking applications, such as those that can specifically influence wheat bread properties, and so the final bread quality. The present research further examines the comparative evaluation of yeast bread with the GH bread’s impact on bread quality parameters. The amount of GH was varied from 10 to 60%/amount of flour for the GH breads. The GH breads were compared with the standard yeast bread for different quality parameters such as volume, texture, and pore analysis. The results show that the bread with 20% and 40% GH obtained the best results in terms of volume and pore size. Moreover, this article also sheds some light on the future applications of the use of CO2 GH as leavening agents in foods. This knowledge could help to create new procedures and criteria for improved GH selection for applications in bread making and other bakery or food products.
The Role of Alternative Crops in an Upcoming Global Food Crisis: A Concise Review
Authors: Mavroeidis Antonios , Roussis Ioannis , Kakabouki Ioanna
Published: November 2022

Achieving Food Security (FS) is perhaps our most challenging aspiration. Despite our best efforts, millions of people around the globe are malnourished or live with hunger. The state of the geo-political scene, as well as the COVID-19 pandemic, have recently brought forth fears of a Global Food Crisis (GFC). Here, we present the factors that threaten FS and could trigger a GFC, examine the potential of alternative crops (ACs) as a measure against an upcoming GFC, and highlight the key aspects of the ACs introduction process in new regions. ACs could enhance FS, yet their success is premised on the adoption of sustainable practices and the implementation of food strategies that aim to promote healthy consumer behaviours.
Boundedness of Fractional Integrals on Grand Weighted Herz–Morrey Spaces with Variable Exponent
Authors: Sultan Babar , Azmi Fatima M. , Sultan Mehvish , Mahmood Tariq , Mlaiki Nabil , Souayah Nizar
Published: November 2022

In this paper, we introduce grand weighted Herz–Morrey spaces with a variable exponent and prove the boundedness of fractional integrals on these spaces.
Small Non-Coding RNAs in Human Cancer
Authors: Xiong Qunli , Zhang Yaguang , Li Junjun , Zhu Qing
Published: November 2022

Small non-coding RNAs are widespread in the biological world and have been extensively explored over the past decades. Their fundamental roles in human health and disease are increasingly appreciated. Furthermore, a growing number of studies have investigated the functions of small non-coding RNAs in cancer initiation and progression. In this review, we provide an overview of the biogenesis of small non-coding RNAs with a focus on microRNAs, PIWI-interacting RNAs, and a new class of tRNA-derived small RNAs. We discuss their biological functions in human cancer and highlight their clinical application as molecular biomarkers or therapeutic targets.
The Truth of Unusual Deaths under Military Expansion: Evidence from the Stable Isotopes of a Human Skull Ditch in the Capital City of the Early Shang Dynasty
Authors: Fang Fang , Liao Jingwen , Zeng Xiaomin , Zhang Juzhong
Published: November 2022

The site of Zhengzhou Shang City (ca. 1509-1315 cal. BC) was the capital of the early Shang Dynasty in China. Archaeological excavations have unearthed a ditch containing approximately one hundred unusual dead human skulls in the rammed-earth foundations of the palace area. The identity and origin of the skulls have long been disputed. In this work, strontium, carbon and nitrogen stable isotope analyses were carried out on 11 human skulls and 1 tooth from the ditch, as well as on 11 human bones, 11 human teeth from the ordinary tombs and 10 pig teeth from the Zhengzhou Shang City site. We determined that, in Zhengzhou Shang City, the local strontium isotope ratio ranges from 0.711606 to 0.711884, and ordinary inhabitants consumed mainly C4 plants supplemented by C3 plants. Moreover, humans buried in the ditch have 87Sr/86Sr values from 0.711335 to 0.711741 and consumed only C4 plants. Combining the isotopic data with the archaeological and cultural context, it is concluded that the unusual human skulls in the ditch are most likely those of prisoners of war captured by the central forces conquering the Xiaomintun area of Anyang in the early Shang Dynasty. The results provide valuable insight into the history of violence and military warfare in the early Chinese dynasty.
RNA Interference Analysis of the Functions of Cyclin B in Male Reproductive Development of the Oriental River Prawn (Macrobrachium nipponense)
Authors: Zhang Wenyi , Wang Pengchao , Xiong Yiwei , Chen Tianyong , Jiang Sufei , Qiao Hui , Gong Yongsheng , Wu Yan , Jin Shubo , Fu Hongtuo
Published: November 2022

Cyclin B (CycB) plays essential roles in cell proliferation and promotes gonad development in many crustaceans. The goal of this study was to investigate the regulatory roles of this gene in the reproductive development of male oriental river prawns (Macrobrachium nipponense). A phylo-genetic tree analysis revealed that the protein sequence of Mn-CycB was most closely related to those of freshwater prawns, whereas the evolutionary distance from crabs was much longer. A quantitative PCR analysis showed that the expression of Mn-CycB was highest in the gonad of both male and female prawns compared to that in other tissues (p < 0.05), indicating that this gene may play essential roles in the regulation of both testis and ovary development in M. nipponense. In males, Mn-CycB expression in the testis and androgenic gland was higher during the reproductive season than during the non-reproductive season (p < 0.05), implying that CycB plays essential roles in the reproductive development of male M. nipponense. An RNA interference analysis revealed that the Mn-insulin-like androgenic gland hormone expression decreased as the Mn-CycB expression decreased, and that few sperm were detected 14 days after the dsCycB treatment, indicating that CycB positively affects testis development in M. nipponense. The results of this study highlight the functions of CycB in M. nipponense, and they can be applied to studies of male reproductive development in other crustacean species.
Using Machine Learning to Explore the Crucial Factors of Assistive Technology Assessments: Cases of Wheelchairs
Authors: Fang Kwo-Ting , Ping Ching-Hsiang
Published: November 2022

The global population is gradually entering an aging society; chronic diseases and functional disabilities have increased, thereby increasing the number of people with limitations. Therefore, the demand for assistive devices has increased substantially. Due to numerous and complex types of assistive devices, an assessment by a professional therapist is required to help the individual find a suitable assistive device. According to actual site data, the assessment needs of “wheelchairs” accounted for most of the cases. Therefore, this study identified five key evaluation characteristics (head condition, age, pelvic condition, cognitive ability, and judgment) for “transit wheelchairs” and “reclining and tilting wheelchairs” from the diagnostic records of “wheelchairs” using the classification and regression trees (CART) decision tree algorithm. Furthermore, the study established an evaluation model through the Naïve Bayes classification method and obtained an accuracy rate of 72.0% after a 10-fold cross-validation. Finally, the study considered users’ convenience and combined it with a LINE BOT to allow the user or the user’s family to engage in self-evaluation. Preliminary suggestions for wheelchair types were given through the assessment model so that evaluators could not only determine a case’s situation in advance and reduce the time required for fixed-point or home assessments, but also help cases find the appropriate wheelchair type more easily and quickly.
Changes in Barriers That Cause Unmet Healthcare Needs in the Life Cycle of Adulthood and Their Policy Implications: A Need-Selection Model Analysis of the Korea Health Panel Survey Data
Authors: Chung Woojin
Published: November 2022

Using 68,930 observations selected from 16,535 adults in the Korea Health Panel survey (2014–2018), this study explored healthcare barriers that prevent people from meeting their healthcare needs most severely during adulthood, and the characteristics that are highly associated with the barrier. This study derived two outcome variables: a dichotomous outcome variable on whether an individual has experienced healthcare needs, and a quadchotomous outcome variable on how an individual’s healthcare needs ended. An analysis was conducted using a multivariable panel multinomial probit model with sample selection. The results showed that the main cause of unmet healthcare needs was not financial difficulties but non-financial barriers, which were time constraints up to a certain age and the lack of caring and support after that age. People with functional limitations were at a high risk of experiencing unmet healthcare needs due to a lack of caring and support. To reduce unmet healthcare needs in South Korea, the government should focus on lowering non-financial barriers to healthcare, including time constraints and lack of caring and support. It seems urgent to strengthen the foundation of “primary care”, which is exceptionally scarce now, and to expand it to “community-based integrated care” and “people-centered care”.
Association between Dietary Carbohydrate Intake and Control of Blood Pressure in Patients with Essential Hypertension
Authors: Jiang Yiqing , Shen Qin , Tang Haiying , Liu Yuanyuan , Ju Yang , Liu Ting , Cui Lingling , Li Jingjing , Wang Xiaohua
Published: November 2022

Background: Both high and low percentages of carbohydrate diets were associated with increased mortality and new-onset hypertension. However, few studies have aggregated to explore the association between carbohydrate intake and blood pressure (BP) control in patients with hypertension. This study aimed to explore the association between carbohydrate-to-energy proportion (CEP) and the rate of poorly controlled BP in patients with hypertension. Methods: A cross-sectional survey was conducted in one comprehensive hospital and one community clinic in China. Dietary CEP was obtained through two-24 h dietary recalls. According to the quintiles of CEP, the participants were divided into Q1–Q5 groups. The average of two BP values was adopted as the final BP value, and poorly controlled BP was defined as systolic BP (SBP) ≥140 mmHg and/or diastolic BP (DBP) ≥ 90 mmHg. Results: A total of 459 hypertensive patients were recruited. In univariate analyses, CEP was associated with the control of SBP and DBP. After the covariates were adjusted for, fewer CEPs in Q1 (OR, 4.335; 95% CI, 1.663, 11.299) and Q2 (OR, 2.482; 95% CI, 1.234, 4.989) were significantly associated with higher rates of poor SBP control. Conclusions: A lower dietary CEP is a risk factor for SBP control, whereas an appropriate CEP of 56% to 66% is beneficial for BP control in patients with essential hypertension.