bluuebunny/crossref_metadata_2025 huggingface dataset:
APIGAN: Learning to Recommend Java API in Real-Time Using Generative Adversarial Networks
Authors: Zhang Qinhe , Zhang Jiachen , Feng Tie , Xue Jialang , Huang Pengyu
Published: December 2022

In order to improve the accuracy of API recommendations, this paper proposes a novel API recommendation approach of APIGAN fully leveraging structural and textual information based on Generative Adversarial Networks, in which a Long Short-Term Memory (LSTM) is used as a generator while a Convolutional Neural Network (CNN) is used as a discriminator. The structural and semantic information of a source code extracted from an abstract syntax tree is used to construct a program dependence graph (PDG) which is also the input of the generator and the discriminator. By evaluating the difference in outputs of them, LSTM is evolved gradually till an optimized program dependence network is obtained to recommend top-k APIs. The results of the experiments show that APIGAN outperforms state-of-the-art research such as APIREC, GraLan, and n-gram in the aspect of top-k accuracy.
Encrypted Traffic Classification Based on a Convolutional Neural Network
Authors: Ma Zhuhong , Li Kunyang , Li Zongyu , Yao Liu
Published: December 2022

To resolve the issues of low accuracy, weak universality, and easy invasion of privacy in traditional encryption traffic classification methods, an encryption traffic classification method based on a convolutional neural network is offered. Firstly, according to the packet size and time message of the net traffic, the original traffic is transformed into a two-dimensional picture to avoid relying on the packet payload to violate privacy, and then the model is embedded. The Inception module performs feature fusion to improve the classification accuracy. Finally, the average pooling layer and the convolution layer are used to replace the fully connected layer, increasing the calculation speed and avoiding overfitting. Experimental results show that the algorithm achieves an accuracy of more than 95% for application traffic classification tasks.
Fault diagnosis of Rolling Bearing Based on One-dimensional Residual Convolution Recurrent Neural Network
Authors: Zhao Yao , Zhong Zhidan , Zhang Haobo , Zhang ZhiHui , Yang AoYu
Published: December 2022

To resolve the issue that conventional rolling bearing fault diagnosis technology are incapable of extracting features adaptively, a one-dimensional residual convolutional recurrent neural network (1DRCRNN-LSTM) is proposed to obtain signal characteristics directly from the original signal. Firstly, a train-valid-test paradigm dataset with sample overlap is created by data augmentation and one-hot coding. Secondly, a convolutional neural network (CNN) and a long short-term memory neural network (LSTM) are fused and a residual learning mechanism is introduced to build a network model for the extraction of signal characteristics. Finally, a softmax classification layer is implemented to classify ten types of faults and output diagnostic results. The proposed network model is verified using the Case Western Reserve University (CWRU) Rolling Bearing Dataset and the results show that the 1DRCRNN-LSTM model has a fault diagnosis accuracy of 0.987, which is better than that of multilayer perceptron (MLP) and convolutional neural network and other methods. Meanwhile, through t-sne visualization techniques, it is proved that this method has superior feature extraction and fault diagnosis capabilities.
Research on Ensemble Convolutional Neural Networks in Digital Image Course experiments
Authors: Zhang Jiawei , Liu Huan , Ge Junwei , Mei Hao , Yan Xiaojun , Cao Yifan , Luo Yaoyao
Published: December 2022

In various digital image processing courses, the accuracy of traditional expression recognition algorithms cannot meet practical needs. This paper studies facial expression recognition using a convolutional neural network and ensemble learning. We develop three subnetwork models based on the classical convolutional neural network, using the BN layer to increase the network convergence rate and regularization is used to prevent subnetwork overfitting. The optimization idea used in this paper is applicable to most experimental improvements and raises the standard of the experiments.
Robust Map Merging Method for Collaborative LiDAR-based SLAM Using GPS Sensor
Authors: Wu Jianbin , Wang Jiaqin , Wei Changyun
Published: December 2022

Typical lidar-based mappings need to cover the entire environment alone, which often leads to long build cycles and large computational resource requirements. Collaborative simultaneous localization and mapping have been applied to explore large and complex scenarios. However, merging local maps from multiple robots remains a challenge. It is crucial for Collaborative SLAM to identify overlapping areas and obtain the transformation matrix for map merging. To this end, this paper proposes a map merging method for collaborative lidar-based SLAM based on GPS measurements and improved Iterative Closest Point (ICP). We add a GPS sensor to the traditional robot configuration and use a simplified model to convert latitude and longitude data into plane coordinate data. According to Euclidean geometry, we determine the overlapping regions scanned by robots and calculate the initial pose transformation matrix between different robots. Based on the traditional ICP algorithm, KD-tree and normal vectors are used to register point clouds in overlapping regions accurately. The transformation matrix obtained by precise registration is used to rotate and translate the source local point cloud, so as to obtain the global point cloud map. In the real-world experiment, the initial transformation matrix is successfully obtained based on GPS measurements, which provides a good initial pose for the ICP algorithm. Compared with the ICP algorithm, the time consumption and RMSE of the improved ICP algorithm are reduced by 26.3% and 7.94%, respectively. Experimental results demonstrate that the proposed method can achieve accurate and efficient map fusion for multi-robot collaborative SLAM.
Research on a Real-time Job-shop Scheduling Method Based on Reinforcement Learning
Authors: Zhu Haihua , Gui Yong , Xu Hui , Tao Shuai , Zheng Kun
Published: December 2022

At present, manufacturing models are characterized by multi-variety, small batch, and diversification. It is insufficient to use traditional scheduling methods for production management with high performance. A real-time production scheduling system based on reinforcement learning (RL) is suggested in an effort to address the aforementioned issues. A brand-new manufacturing neural network is created to learn the state-action values for production scheduling in real time using high-dimensional data as the input. The detailed setup of network inputs, neural network, action, and reward are also designed. Then, a policy-based reinforcement learning algorithm is proposed to achieve the optimum objective. Finally, By contrasting the proposed scheduling strategy with rule-based approaches in a smart manufacturing environment, its efficacy is demonstrated. according to experimental data, the suggested algorithm can successfully improve performance in the dynamic job-shop environment.
Mechanism design of elbow joint rehabilitation robot
Authors: Mao Kefu , Pei Fengque , Yuan Minghai , Zheng Liang
Published: December 2022

Aiming at the problems of low mechanism precision, large motion inertia, and ease of secondary patient damage in the elbow joint rehabilitation robot, an exoskeleton parallel robot that can realize two degrees of freedom (2-PRR-S) motion of the elbow joint is designed. First, use Solidworks to complete the design and modeling of each component, and use ANSYS to perform finite element analysis on some important components to check the strength of the components. Finally, Adams is used to performing kinematic analysis in order to verify the kinematic properties of the forearm support, and the check analysis of the whole mechanism’s kinematic properties is completed. The simulation results show that the designed elbow joint rehabilitation robot meets the design requirements.
Design of a small material handling robot gripping and storage system
Authors: Liu Zhuoran , Li Chunxu , Wang Li , Li Shaoxiang
Published: December 2022

This paper completed the development status and working principle of the handling robot, analyzed the performance index parameters and system functional requirements of the robot, and proposed an overall design scheme of the handling robot control system. The mechanical structure design of the handling robot was developed, and the selection of the core components of the system was studied and designed in detail based on theoretical analysis and calculation. Secondly, this paper selected the STM32 microcontroller as the core of the handling robot. It completed the circuit schematic diagram of the systems, and investigated the selection of core sensors for the navigation and positioning module, obstacle avoidance module, and wireless communication module. Finally, this paper studied the automatic control part of the handling robot, which mainly included the modeling of the robot’s manipulator, PID control, and MATLAB simulation verification. In addition, the application prospect of the handling robot was explored. It had the advantages of high efficiency, strong practicability, and perfect function, and had certain practical significance in the application of the logistics industry.
Modular-based test system for proportional valves
Authors: Xu Dingan , Xing Keli , Jin Xiajie
Published: December 2022

Based on the dynamic and static test performance requirements of a company for proportional valves, a hydraulic schematic and electrical control system for a proportional valve test bench was designed, on the basis of which a LabVIEW-based proportional valve test system was developed. The test and control software is based on a modular design, which allows the required functions to be handled in a modular way, greatly reducing the development cycle of the test software and facilitating later improvements and maintenance. The test results show that the test bench has high accuracy and stable performance, and can provide a reliable test basis and test means for the development and online inspection of proportional valves.
Design and Verification of a Penetration System Used for Constructing the Sampling Channel
Authors: Ma Ruqi , Ma Rulin , Sun Kang , Chao Ma , Jiang Shuiqing
Published: December 2022

Based on the analysis of the water ice sampling system design at the lunar permanent shadow region(PSR), a rapid sampling channel construction method based on kinetic energy penetration was proposed, and an engineering prototype of the penetrator system based on the conversion of chemical energy and kinetic energy was developed, which can solve the problem that the subsurface lunar water ice is too difficult to sample quickly due to its significantly enhanced mechanical properties. Based on the mechanical properties boundary of lunar soil water ice, the performance of the engineering prototype was tested and verified. The test results show that the penetrating system developed in this paper can achieve rapid penetration into the lunar soil with uniaxial compressive strength of about 30MPa without consuming power consumption; the penetrating depth can reach 234mm, and the penetrating time is less than 1s. The penetrating system can rapidly construct sampling channels, which can effectively solve the problem of the high-hardness water ice samples located at the subsurface layer of the lunar soil that can be efficiently exposed faced by in-situ water ice sampling in the permanent shadow region.
Buckling and Post-buckling Characteristics of Stiffened Panels Under Compression-Shear Load
Authors: Chen Limin , Zhuo Yi , Xu Rongzhang , Wang Houbing
Published: December 2022

Experiments have been conducted to investigate the buckling and post-buckling behavior of a T-the stiffened composite panel in size of 2412 by 1420mm under a compression-shear load. DIC was used to monitor the local buckling and post-buckling, and the results were compared with that of strain gauges. The results show that DIC can accurately capture the displacement field and the whole progress of the buckling mode transition, and the buckling modes at different times are clearly and intuitively, the error of the initial buckling load is less than 5% compared with the load measured by the strain gauge. Four different buckling determination methods based on strain gauge measurement and DIC measurement are presented, and a more accurate and convenient method for judging buckling load is obtained. The initial principal strain angle is related to the ratio of shear stress to compressive stress and changes greatly after the buckling, and the fracture angle approaches 45 degrees. The experimental results show that the hole with 6mm in the weighted middle of the web has a slight effect on the buckling load but has an obvious effect on the load capacity.
Analysis of Wet Modal Vibration of Shell Structure
Authors: Li Panfei
Published: December 2022

Modal analysis is very important for structural dynamics research. However, the simulation results have certain limitations and cannot be fully applied to engineering applications.Using LMS (LMS Test.lab) data analysis equipment, modal experiments were carried out on the pressure shell in air and water respectively. The natural frequency and damping ratio of each order mode of the pressure shell are calculated using the polyMAX(poly referene least square complex frequencydomain) algorithm. Comparing with the simulated data, the difference between the experimental state and the simulated state is obtained, and the variation rules of the underwater modal vibration frequency and damping ratio changing with the water depth are obtained. According to this conclusion, an effective reference for the simulation method is put forward.
Wear analysis of elevator brake shoe
Authors: Ren Facai
Published: December 2022

The brake is the key equipment to ensure the safe operation of the elevator. Failure of the elevator brake will lead to a slide accident. This paper takes the elevator brake shoe, which has been used for more than 15 years, as the research object, and systematically analyzes its wear characteristics. The research results show that most of the brake shoes have obvious scratches, and some of them even have cracks. Therefore, in the daily maintenance of the elevator, pay special attention to the wear state of the brake shoe to ensure the safe operation of the elevator brake.
GPF Design Based on Sierpinski Triangle
Authors: Zhang Jian , Chen Wenhao , Liu Xiaoying , Liu Jiaoyan
Published: December 2022

In order to adapt to strict emission regulations and reduce particulate emissions from gasoline engines, continuous research on GPF is needed to improve particulate capture efficiency. The structure and working principle of gasoline engine particle catchers are studied. A new type of GPF is designed based on the Sierpinski triangle structure. The GPF shell is designed according to the structure of the filter body, and the flow guide plate is designed to make the gas flow rate uniform. The model and accessories of the filter body are modeled in Solid Works. Based on the repeated characteristics of the filter body structure, a unit body is extracted to simplify the analysis. The simulation was performed using the filter unit. The flow rate of exhaust gas between the new filter structure and the traditional filter body was compared in addition to the pressure of the filter body and the trapping effect of small molecular particles in the exhaust gas. Through analysis and comparison, it can be concluded that the new GPF filter structure has better trapping efficiency than the traditional filter structure.
Smart driving of a bilayered composite tape-spring structure
Authors: Lin Xueqi , Wang Bing , Zhong Shuncong , Chen Hui , Liu Dianzi
Published: December 2022

Composite tape-springs (CTS) structure has been applied to spatial developable structures due to its bistability. There is growing interest in smart driving of the CTS-based structures because of the limitations on the working environment. Here, we propose a detailed analysis of the smart driving of the CTS structure. This is achieved by using smart materials to develop a bilayered CTS intelligent structure: the smart material forms the active layer to generate stress/strain to drive the structure; the CTS layer acts as a passive layer where its intrinsic bistability, designability further enriches the diversity of intelligent morphing structures. A theoretical analytical model is developed to anticipate the bistability; the stability criteria are then determined to guide the intelligent morphing design. These will facilitate the future smart driving design of aerospace deployable structures.
Modeling and Simulation of Combined Bending-torsion Experiment Based on ABAQUS
Authors: Li Xiaozhan , Wang Shang , Liang Meiqin
Published: December 2022

Hollow shaft is widely used in aviation, vehicle, construction, electrician, and other fields. Bending-torsional resistance is one of the most important mechanical properties of the hollow shaft. The traditional test has a long testing time, high cost, and strict requirements on the sample size. In addition, it is difficult to measure the stress in special areas, such as the inner diameter of the hole and narrow gaps, because the strain gauge has a certain size. To solve this problem, a three-dimensional finite element model was established to study the bending-torsional resistance of the hollow shaft. The color stress nephograms and rich data are obtained by simulation. The results showed that Mises stress of the hollow shaft increased with the indenter pressure. However, this increase is slowing down. The maximum Mises stress of the shaft reached 497.6 MPa when the pressure was 40 kN. The maximum Mises stress occurred at the position where the shaft contacted the base. Using simulation techniques to study the bending and twisting resistance of the hollow shaft is feasible.
Research on Water System Inline Heater Heating Performance Simulation of Civil Aircraft
Authors: Zhu Chong
Published: December 2022

The water system in civil aircraft is indispensable and important. During the design of the water system, cold weather is a severe working condition, which will cause the water system to freeze and lose water supply function, so the heating and anti-freezing design of the water system is necessary. An inline heater is a new heating and anti-freezing equipment for water system pipelines, with the advantage of convenient installation and high heating efficiency. In this paper, the fluid-solid coupling heat transfer simulation is used to study the heating and anti-freezing effect of the inline heater, considering the influence of the water flow rate and the heater power. Through analysis, increasing the water flow rate can improve the heating efficiency of the inline heater, but it also puts forward a higher heater requirement for the inline heater. With the increase of the heating power of the inline heater, its heat utilization rate is constantly decreasing, so blindly increasing the heating power can not significantly improve the heating and anti-freezing performance. This study can guide the water system inline heater design of civil aircraft.
Design of Electric Power System for Xinhangcheng Station on Intercity Railway Connecting Line
Authors: Yu Guo
Published: December 2022

At present, the intercity railway station is getting bigger and bigger, represented by the Intercity Railway Xinhangcheng Station. Xinhangcheng Station of the Intercity Railway Link Line is a key station for the national railway underground passenger transport, the scale of the building is larger than that of ordinary subway stations, with a total of 6 floors, including communication, signal, information, escalator, screen door and other equipment. The layout and design of ventilation, water supply, and fire-fighting equipment are more complicated than subways. The station also includes areas related to station support and integrated development, therefore, new requirements are put forward for the design of the station power system. Therefore, it is very important to study a reasonable and feasible power design scheme. In this paper, to meet the needs of the intercity railway tie line underground station building, station supporting and integrated development of electricity consumption and electricity consumption independent of each other, a 10KV/0.4KV substation is set up on the ground floor and on the second floor of the station building to supply power to the station, a 10KV/0.4KV substation is set up on the east and west sides of the supporting area to supply power to the municipal supporting area, and integrated development of a 10KV/0.4KV substation is set up to supply power for integrated commercial development, meeting the needs of all parties.
Research on measurement technology of action characteristics of double-ended grounding switch based on flexible sensing
Authors: Xiao Yang , Huang Yuzhong , He Zhenxiang , Zhan Jinte
Published: December 2022

In order to solve the problems of high voltage switches’ operation characteristic tests, such as no double end grounding measurement, the inconvenient opening of grounding switch, easy injury, and equipment damage due to induced high voltage, a new measurement method is proposed in this paper, which adopts frequency conversion technology, time coding technology, and contactless flexible sensor technology, which can accurately measure the action characteristics of high voltage switch equipment under the condition of double terminal grounding. This method can effectively reduce the influence of field measurement factors and improve the accuracy, safety, and convenience of field measurement of high voltage switch action characteristics.
Theoretical Integrated Electric Quantity of Primary Frequency Control
Authors: Wang Chun
Published: December 2022

At present, the qualification rate of primary frequency control of hydropower units in the southwest power grid is low. The current grid has defects in the calculation method of the theoretical integral power of primary frequency control of hydropower units. The theoretical power of primary frequency control is proportional to the frequency difference. The adjustment rate is slow, and the deviation between the theoretical value and the actual value is large, which leads to a significant increase in the failure rate; by modeling the entire hydro-generator set adjustment system and performing the inverse Laplace transform of the simplified and reduced transfer function to obtain an exponential function, the theoretical integral power of Primary Frequency Control is calculated by this function, and the accuracy of the measured comparison is significantly higher, which is in line with the actual regulation law.
Analysis of energy storage operation on the power supply side under a high proportion of wind power access based on system dynamics
Authors: Huang Haoyang , Yang Ying , Yu Bangdong , Jiang Leilei , Liu Zhi , Song Dongming
Published: December 2022

With the rapid development of renewable energy sources such as wind energy and solar energy in China, structural problems such as wind and light abandonment, system operation imbalance, and insufficient energy supply have arisen in the process of accelerating the energy transformation process. Given the above problems, this paper uses the system dynamics method for modeling. First, the key variables are selected from the perspective of influencing the economic reliability of the power system. Second, the energy storage operation model of the power supply side under the high proportion of wind power access is established, and the impact of new energy access on the system balance and energy storage configuration is explored. Finally, the cost connection of each module body is used to optimize the allocation of energy storage resources, thereby improving the efficiency of the enterprise itself and providing a new idea for the power generation enterprise to participate in the operation and scheduling of the system.
Electric power dispatching of virtual power plant with electric vehicle
Authors: Sun Weibin , Liu Sanming , Dong Hao , Huang Qifan
Published: December 2022

Because electric vehicles have many advantages such as low carbon, environmental protection, and low cost compared with fuel vehicles, electric vehicles have developed rapidly in recent years, which will lead to large-scale impact load. In this paper, the electric vehicle is regarded as an energy storage device, a multi-energy VPP electric thermal scheduling model including electric vehicles is established, and a scheduling strategy for electric vehicles to participate in the power system scheduling is proposed. With the minimum cost of VPP and the minimum carbon dioxide emissions as the optimization objectives, the relevant objective functions are described, and equality constraints and inequality constraints are applied to them. Then, the improved algorithm is applied to solve the model. The results of the example analysis show that the virtual power plant system model with electric vehicles established in this paper can reduce the operating cost of the VPP system, reduce carbon emissions, and be conducive to the safe, low-carbon, and economic operation of the power system.
Study on Simulation Model of Power Electronic Transformer (PET)
Authors: Sun Jingbo
Published: December 2022

The thesis has completed the following research work: 1. After reviewing the development process, research background, and application field of PET, the advantages of PET are summarized, and then the research object of this paper is AC/DC/AC including DC port and the key technical problems that need to be solved. 2. This thesis has established the mathematical model of PET at all levels of AC/DC/AC type structure. The input stage is composed of a PWM rectifier circuit, and the circuit working principle, mathematical model, and control strategy are analyzed in detail. The isolation stage theoretically analyzes the working modes of the circuit topology in each time period. The output stage consists of a unipolar inverter circuit and an LC filter. 3. In the simulation environment of Matlab/Simulink, according to the design parameters, the simulation model of the main circuit of the PET rectifier stage, isolation stage, and inverter stage, as well as the simulation model of the whole machine system are built under the 1kv voltage level.
VSC-HVDC Fault Location Method Based on Effective Feature and Depth Belief Network
Authors: Zhai Shaolei , Cui Ye , Li Fangqing , Wang Ren , Su Wenjing , Tang Hansong
Published: December 2022

Aiming at the problems that most fault location methods are applied to the high voltage direct current (HVDC) transmission system, such as low location accuracy and vulnerability to noise, a voltage source converter (VSC)-HVDC fault location method based on effective feature and deep belief network is proposed. Firstly, the Karenbauer phase mode transform is used to decouple the original fault current data to eliminate the coupling effect between positive and negative lines. Then, Hilbert Huang (HH) transform is used to obtain six effective features of information from frequency domain and time domain analysis to fully characterize the system fault current signal. Finally, the extracted effective features are input into the depth belief network for learning, so as to estimate the fault location in the transmission line. VSC-HVDC system is built based on the MATLAB platform for experimental analysis. The results show that the fault location obtained by the proposed method has the smallest overall fault location error, and the maximum and minimum errors are divided into about 0.52 km and -0.95 km. Compared with other methods, it has certain advantages in fault location.
Research on configuration optimization of distributed energy storage system based on multi-objective genetic algorithm
Authors: Yin Shuo , Chai Zhe , Yang Meng , Chen Xing , Jin Man , Liu Junhui
Published: December 2022

In view of some problems existing in China’s power market, this paper uses the multi-objective genetic algorithm to analyze the problems in the power market. The equivalent mathematical model of energy distribution is established and optimized, and its performance is optimized. The results indicates that the scheme can significantly improve the new energy consumption rate of the distribution network and the security of the distribution network and achieve the design purpose.
Study of peat-mangrove ecosystem in East Kalimantan Province
Authors: Surahman S , Ahmad A , Butarbutar T , Palgunadi M A
Published: December 2022

Indonesia's peatland cover is about 11 million ha of land in tidal swamp areas and 3.9 million hectares in swamp and coastal areas. Based on these data, there are possibility interconnection between peat and mangrove ecosystems in the one landscape. Therefore, the purpose of this study is to analyze the characteristics of interconnection between the peat and mangrove ecosystems in Indonesia, specifically in East Kalimantan. Vegetation characteristics such as structure and species composition will be measured, as well as soil physical characteristics including analysis of water content, bulk density, particle density and porosity. characteristics of soil chemical properties include analysis of pH, EC, ash content, bases (K, Na, Ca, Mg), micro elements (Fe, Mn, Cu, Zn), C-total, N-total and S-total. The results obtained are East Kalimantan is located in the coastline area which is still influenced by high salinity tides. The level of species diversity and community stability in the transition area is in the low to moderate limit with a Shannon index value of 2.24. Species with high salinity tolerance dominate the transition area (true mangrove vegetation species).
Comparison of microwave assisted extraction and ultrasound assisted extraction on recovery of residual palm oil from spent bleaching earth
Authors: Taslim  , Manurung R , Iriany  , Bani O , Pranata A , Nugraha A
Published: December 2022

Recovery of oil contained in spent bleaching earth (SBE) will have a good impact on the environment and economy. The process can be carried out using Microwave Assisted Extraction (MAE). This study aimed to determine best operation parameters for residual palm oil recovery using MAE and compare it to Ultrasound Assisted Extraction (UAE). The oil extraction was carried out using hexane as solvent at variable microwave power (100, 180, and 300 W), SBE to solvent ratio (1:4, 1:5, 1:6), and extraction time (50,70 and 80 min). The highest oil yield was achieved at microwave power of 300 W, SBE to solvent ratio of 1:5 and extraction time of 80 min at 20.97%. The main components of the oil produced were C16 (56.65 %wt) and C18.1 (28.35 %wt). The free fatty acid content, moisture, iodine value, deterioration of bleachability index (DOBI) and peroxide value of the resulting oil were 10.91%, 1.52%, 56.71 g I2/100 g, 1.372 and 7.419 meq/kg respectively.
Characteristics of instant porridge from cassava flour fortified anchovy flour, and yellow pumpkin flour from Indonesian Local Resources
Authors: Nurminah M , Pratiwi Y , Lubis Z
Published: December 2022

This study aimed to produce modern functional food products, obtain the bestquality instant porridge formula, and determine the effect of the formulation of cassava flour and anchovy flour and the addition of yellow pumpkin flour for health. This study used a completely randomized design (CRD) with 2 factors, namely the ratio of cassava flour to anchovy flour (Factor I) which was 97.5%: 2.5%; 95%:5%; 92.5%:7.5%; 90%:10% and the addition of yellow pumpkin flour (Factor II) ie 0%; 5%; 10%; 15%. Several parameters carried out in this study consisted of proximate tests (moisture content, ash content, fiber content, fat content, protein content, carbohydrates) and organoleptic tests (color, aroma, taste, texture, and general acceptance). Results obtained on all test parameters, it can be determined that instant porridge with a ratio of cassava flour and anchovy flour (90%: 10%) and the addition of yellow pumpkin flour (15%) was the best treatment of instant porridge product.
Anatomical properties of branches and twigs mangrove woods
Authors: Panggabean L E , Nuryawan A , Risnasari I , Susilawati
Published: December 2022

In order to optimize the utilization of mangrove woods, particularly branches and twigs parts, this research was conducted to investigate anatomical properties of three species of mangrove woods, namely api-api (Avicennia marina), bakau minyak (Rhizopora apiculata), and berembang (Sonneratia caseolaris). The properties were comprised of both microtome sections and macerations dimensions. Procedure for microtome followed Sass method, resulted in three sections for each part, namely cross-section (L/longitudinal), radial/R section, and tangential/T section. Technical procedure for maceration based on Forest Product Laboratory (FPL) method, resulted in measurement of fiber dimension and derivative of fiber dimension. In term of microtome, the anatomical features between branches and twigs for each species in L, R, T sections are similar, but their quantitative anatomical observations between twigs and branches have differences in the vessel, rays and fiber parameters statistically. In term of fiber dimension and its derivatives (Runkel Ratio, Felting Power, Mulhstep Ratio, Coefficient Rigidity, Flexibility Ratio) both branches and twigs showed same quality class, namely 3rdclass with scored 150-175 points.
Literature Review: Identification Of Sustainable Ecotourism In Tangkahan
Authors: Siregar Onan Marakali , Siregar Afrila Mulyati , Andriansyah
Published: December 2022

Ecotourism development is an effort to develop sustainable and environmentally friendly tourism so that it can be enjoyed for a more extended period. Ecotourism does not only offer travel but creates an element of learning in it. As a result, managing sustainable tourism destinations related to governance in carrying out tourism activities is increasingly important. In this paper, the approach used in the literature review is collected from several publishers such as emerald, Wiley, research gate, science direct, and Thomson and then studied systematically, which is related to this paper, totalling 50 articles. The purpose of this paper is to present a conceptual framework for ecotourism that combines the concept of 4a's tourism as a framework for identifying and developing tourist destinations. This paper explores the essence of ecotourism related to sustainable tourism through the 4A component of tourism. The findings show that ecotourism contributes differently to other tourism depending on the sub-topics raised. It can be underlined that the literature review is long-term research integrated between ecotourism management and stakeholders such as the government, residents and consumers needed to carry out ecotourism literacy for the environment.
Utilization of UAV (Unmanned Aerial Vehicle) technology for mangrove species identification in Belawan, Medan City, North Sumatera, Indonesia
Authors: Thoha A S , Lubis O A , Hulu D L N , Sari T Y , Ulfa M , Mardiyadi Z
Published: December 2022

The mangrove forests in Indonesia are starting to decrease over time because there is still a lack of knowledge among people around the coast about the importance of mangroves. Kampung Nelayan, Medan Belawaan, is a coastal community area whose life is very dependent on coastal, mangrove, and water resources. Unmanned Aerial Vehicle (UAV) technology has the potential to provide a fast, cost-effective, and efficient mangrove mapping technique. It is very useful because mangrove areas are located in remote areas, where field measurements are difficult, time-consuming, and expensive. The objective of this study is to analyze mangrove species using UAV imagery with Object-Based Image Analysis (OBIA) classification. The object-based classification result for the overall accuracy is 82.94% where there are 7 classes of mangrove species based on the classification process, including: Avicennia alba, Avicennia officinialis, Avicennia Marina, Rhizopora apiculata, Nypah fruticans, Scyphipora hydrophylacea, Bruguiera gymnorriza. There are also two classes for non-mangrove, consisting of the water body and non-mangrove. The largest area of mangrove species in the research site is Avicennia Marina with a percentage of 33.86% covering an area of 7.80 Ha. The second-largest mangrove species with a percentage of 21.88% is Avicennia officinalis with an area of 5.04 Ha.
Highly elastic and self-healing nanostructured gelatin/clay colloidal gels with osteogenic capacity for minimally invasive and customized bone regeneration
Authors: Dou Zhenzhen , Tang Han , Chen Kaiwen , Li Dize , Ying Qiwei , Mu Zhixiang , An Chuanfeng , Shao Fei , Zhang Yang , Zhang Yonggang , Bai Haoliang , Zheng Guoshuang , Zhang Lijun , Chen Tao , Wang Huanan
Published: December 2022

Extrusible biomaterials have recently attracted increasing attention due to the desirable injectability and printability to allow minimally invasive administration and precise construction of tissue mimics. Specifically, self-healing colloidal gels are a novel class of candidate materials as injectables or printable inks considering their fascinating viscoelastic behavior and high degree of freedom on tailoring their compositional and mechanical properties. Herein, we developed a novel class of adaptable and osteogenic composite colloidal gels via electrostatic assembly of gelatin nanoparticles and nanoclay particles. These composite gels exhibited excellent injectability and printability, and remarkable mechanical properties reflected by the maximal elastic modulus reaching ∼150 kPa combined with high self-healing efficiency, outperforming most previously reported self-healing hydrogels. Moreover, the cytocompatibility and the osteogenic capacity of the colloidal gels were demonstrated by inductive culture of MC3T3 cells seeded on the three-dimensional (3D)-printed colloidal scaffolds. Besides, the biocompatibility and biodegradability of the colloidal gels was proved in vivo by subcutaneous implantation of the 3D-printed scaffolds. Furthermore, we investigated the therapeutic capacity of the colloidal gels, either in form of injectable gels or 3D-printed bone substitutes, using rat sinus bone augmentation model or critical-sized cranial defect model. The results confirmed that the composite gels were able to adapt to the local complexity including irregular or customized defect shapes and continuous on-site mechanical stimuli, but also to realize osteointegrity with the surrounding bone tissues and eventually be replaced by newly formed bones.
Convolutional neural network analysis of x-ray diffraction data: strain profile retrieval in ion beam modified materials
Authors: Boulle A , Debelle A
Published: December 2022

This work describes a proof of concept demonstrating that convolutional neural networks (CNNs) can be used to invert x-ray diffraction (XRD) data, so as to, for instance, retrieve depth-resolved strain profiles. The determination of strain distributions in disordered materials is critical in several technological domains, such as the semiconductor industry for instance. Using numerically generated data, a dedicated CNN has been developed, optimized, and trained, with the ultimate objective of inferring spatial strain profiles on the sole basis of XRD data, without the need of a priori knowledge or human intervention. With the example ZrO2 single crystals, in which atomic disorder and strain are introduced by means of ion irradiation, we investigate the physical parameters of the disordered material that condition the performances of the CNN. Simple descriptors of the strain distribution, such as the maximum strain and the strained depth, are predicted with accuracies of 94% and 91%, respectively. The exact shape of the strain distribution is predicted with a 82% accuracy, and 76% for strain levels <2% where the amount of meaningful information in the XRD data is significantly decreased. The robustness of the CNN against the number of predicted parameters and the size of the training dataset, as well as the uniqueness of the solution in some challenging cases, are critically discussed. Finally, the potential of the CNN has been tested on real, experimental, data. Interestingly, while the CNN has not been trained to operate on experimental data, it still shows promising performances with predictions achieved in a few seconds and corresponding root-mean-square errors in the 0.12–0.17 range for a fully automated approach, vs. a 0.06–0.12 range for a classical, human-based, approach that, in turn, requires several tens of minutes to optimize the solution. While the overall accuracy of the CNN has to be improved, these results pave the way for a fully automated XRD data analysis.
Friar Lawrence’s Confessional: Shakespeare through the lens of a webcam
Authors: Paton Emma
Published: December 2022

A review of Friar Lawrence’s Confessional, a digital adaptation produced by Creation Theatre, discusses how the adaptation utilises the Zoom online conferencing platform as both a stage and setting for the performance, varying between ‘showing’ and ‘telling’ modes to retain both the narrative of the source text (William Shakespeare’s Romeo and Juliet) and the central conceit of the production: that the audience is viewing the Friar through his webcam.
Target Trial Emulation and Bias Through Missing Eligibility Data: An Application to a Study of Palivizumab for the Prevention of Hospitalization Due to Infant Respiratory Illness
Authors: Tompsett Daniel , Zylbersztejn Ania , Hardelid Pia , De Stavola Bianca
Published: December 2022

Target trial emulation (TTE) applies the principles of randomized controlled trials to the causal analysis of observational data sets. One challenge that is rarely considered in TTE is the sources of bias that may arise if the variables involved in the definition of eligibility for the trial are missing. We highlight patterns of bias that might arise when estimating the causal effect of a point exposure when restricting the target trial to individuals with complete eligibility data. Simulations consider realistic scenarios where the variables affecting eligibility modify the causal effect of the exposure and are missing at random or missing not at random. We discuss means to address these patterns of bias, namely: 1) controlling for the collider bias induced by the missing data on eligibility, and 2) imputing the missing values of the eligibility variables prior to selection into the target trial. Results are compared with the results when TTE is performed ignoring the impact of missing eligibility. A study of palivizumab, a monoclonal antibody recommended for the prevention of respiratory hospital admissions due to respiratory syncytial virus in high-risk infants, is used for illustration.
Health and Safety Regulations for COVID-19: A Policy Analysis
Authors: Brosseau Lisa M , Jones Rachael M , Gardner Kate , Williams Spencer C , Henry Kimberly P , Sanders Denali
Published: December 2022

The COVID-19 pandemic spurred some regulators in the USA to require occupational health and safety programs to prevent COVID-19 transmission in workplaces. The objective of this study was to describe such state and federal regulations enacted between January 2020 and January 2022. Regulations, including emergency temporary standards (ETS) and permanent standards, were identified through a search of Nexis Uni and Bloomberg Law and review of US OSHA websites and the Federal Register. Full texts were reviewed for regulatory scope, hazard and exposure definitions, determination of exposure or risk levels, and control strategies. Four state (California, Michigan, Virginia, and Oregon) and two federal regulations were identified. All regulations described respiratory aerosols as the primary source of SARS-CoV-2 and recognized person-to-person transmission by droplet, airborne, and contact routes. Only the US OSHA ETS for healthcare explicitly stated that inhalation of respiratory particles was the most likely method of COVID-19 transmission. The Virginia, Michigan, and Oregon regulations described different categories of risk defined by exposure frequency and duration or specific workplace activities. California described exposure as places and times when employees come into contact or congregate with other people. The US OSHA ETS for healthcare described exposure as involving close contact with suspected or confirmed COVID-19 patients. While all of the state regulations required strategies from across the hierarchy, only the Virginia regulations specifically incorporated the hierarchy of controls. Only the California and Virginia regulations explicitly linked control strategies to the transmission route, while Virginia demarcated control strategies by risk level. Oregon linked risk level to occupancy levels and physical distancing requirements and referred to the use of a layered approach for transmission control. The US OSHA ETS for healthcare defined droplet and airborne precautions but made no mention of the hierarchy of controls or risk levels. Respirators were discussed in most of the regulations. The first Michigan regulation explicitly required respirators appropriate to exposure risk. The California regulations noted that respirators protect the wearer while face coverings protect people around the wearer. These regulations offer insights for a permanent US OSHA infectious disease regulation, such as the need to consider a range of transmission modes including near- and far-range aerosol inhalation, endemic and novel pathogens, workplaces beyond healthcare settings, factors that contribute to exposure and risk, the hierarchy of controls, the role of vaccination, and the importance of written exposure assessment and infection prevention plans.
Inference after latent variable estimation for single-cell RNA sequencing data
Authors: Neufeld Anna , Gao Lucy L , Popp Joshua , Battle Alexis , Witten Daniela
Published: December 2022

In the analysis of single-cell RNA sequencing data, researchers often characterize the variation between cells by estimating a latent variable, such as cell type or pseudotime, representing some aspect of the cell’s state. They then test each gene for association with the estimated latent variable. If the same data are used for both of these steps, then standard methods for computing p-values in the second step will fail to achieve statistical guarantees such as Type 1 error control. Furthermore, approaches such as sample splitting that can be applied to solve similar problems in other settings are not applicable in this context. In this article, we introduce count splitting, a flexible framework that allows us to carry out valid inference in this setting, for virtually any latent variable estimation technique and inference approach, under a Poisson assumption. We demonstrate the Type 1 error control and power of count splitting in a simulation study and apply count splitting to a data set of pluripotent stem cells differentiating to cardiomyocytes.