Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology of Calculating the Number of Trees Based on ALS Data for Forestry Applications for the Area of Samławki Forest District

Airborne Laser Scanning (ALS) is a technology often used to study forest areas. The main area of application of ALS in forests is collecting data to determine the height of individual trees and entire stands, tree density and stand biomass. The content of the ALS data is also classified, i.e., registered objects are identified, including the species affiliation of individual trees. Important information for forest districts includes other parameters related to the structure and share of stands and the number of trees in the forest district. The main goal of this study was to propose the new ALS data processing methodology for detecting single trees in the Samławki Forest District. The idea of the proposed methodology is to indicate a free and accessible solution for any user (at least in Poland). This new ALS data processing methodology contributes to research on the use of ALS data in forest districts to maintain up-to-date and accurate stand statistics. This methodology was based on free data from the geoportal.gov. pl portal and free software, which allowed to minimize the costs of preparing data for the needs of forestry activities. In cooperation with the Samławki Forest District, the proposed methodology was used to detect the number and heights of trees for two forest addresses 13b and 30a, and then to calculate the volume of stands. As a result, the volume of the analyzed stands was calculated, obtaining values differing from the nominal ones included in the FMP (Forest Management Plan) by about 25% and 5%, respectively, for larch and oak.
PRE-TRAINING AND FINE-TUNING ELECTRA MODELS FOR VARIOUS VIETNAMESE NATURAL LANGUAGE PROCESSING TASKS

: In recent years, the Natural Language Processing community was impacted greatly by models based on the BERT architecture (Devlin et al., 2018). The Transformer-based Masked Language Model (MLM) has yielded significant improvement on many Natural Language Processing problems. However, it requires huge computing power and makes pre-training models a resource-consuming process. To overcome this impediment, in March 2020, Clark et al. have published a new model named ELECTRA. It carries the same structural framework as BERT, but the pre-training task was essentially modified, which makes it effective while cost-saving. The English ELECTRA models have gained remarkable results on the GLUE Natural Language Understanding benchmark, compared to BERT and GPT. In this paper, we introduce our Vietnamese ELECTRA models (ViELECTRA). On a similar amount of text, the pre-training resource of ViELECTRA was around 1/5 to 1/2 of PhoBERT’s (Nguyen and Nguyen, 2020). We fine-tuned the models on various downstream tasks such as Dependency Parsing, Named Entity Recognition, Part of Speech Tagging, and Natural Language Inference. ViELECTRA-Base outperformed PhoBERT-Base on the Natural Language Inference task with an accuracy score of 79.1% over 78.5%. On the Dependency Parsing task, we achieved 83.66% UAS and 75.27% LAS which is on average 2.5% lower than PhoBERT. The evaluation results show that ELECTRA is promisingly applicable in the Vietnamese language and there is still room for further development.
Development of a Cryptocurrency IoT wallet with Automatic Authentication

The paper studies a practical implementation of Internet of Things device personalization. The solution of this problem greatly contributes to the creation of a system of devices that exchange trusted data. A fundamental architecture for a new information system that implements crypto wallets with automatic authentication of IoT devices, is proposed. The architecture provides a secure method of wallet initiation on a device. Internet of Things poses significant restrictions on hardware and software. The main problems are ensuring communication between IoT devices, optimizing the energy consumption of devices and small processing power. Changes in existing libraries and program code were required to implement the IoT wallet. The presence of a wallet makes it possible for the device to buy or sell data for crypto coins, for example, temperature readings of a video feed. This will contribute to the emergence of a new economic model in which the data collected is sold, not the devices themselves. Where seller IoT device transfers impersonal data to the customer and other IoT device validates integrity of data that is transferred. Based on integrous of data and its relevance other IoT device rates the seller and data costs.
The Experience of Evolution: Developments in Design Practice

Designers today have opportunities to design much more than simply static objects. We are designing integrated and dynamic interactions with objects, spaces and services and helping companies with more strategic decisions. Expanded opportunities have spawned developments in traditional design practice. First are developments relating to awareness of people's experience. Design- and user-research methods are evolving. Combinations of projective techniques and empathic exercises are more holistic in scope and yield results that can be more viscerally understood. A second development is in representing multiple dimensions of people's experience through modelling tools used to explore design ideas. Video scenarios and enactment enable explorations, in more dynamic ways, of what it will be like to interact with new designs. Finally, both design teams and client groups involve professionals from multiple disciplines and business functions. Tools such as experience prototyping are being developed to promote shared visions and to enable the communication of experiential design ideas in compelling ways.
An Object Detection and Scaling Model for Plastic Waste Sorting

Plastic waste sorting involves the separation of plastic into its individual plastic types. This research proposes an Object Detection and Scaling Model for plastic waste sorting to detect four types of plastics using the WaDaBa dataset. This research compares the Object Detection and Scaling Models Scaled-Yolov4 and EfﬁcientDet. Results demonstrate that Scaled-Yolov4-CSP outperforms the state of the art, Colour-Histogram based Canny-Edge-Gaussian Filter, by 21% accuracy.
Expression and mechanism of microRNA 195 in diabetic retinopathy.

We aimed to explore the role of microRNA 195 (miR-195) in diabetic retinopathy (DR). From January 2019 to July 2020, 50 patients with DR undergoing vitrectomy and 40 patients with idiopathic macular holes undergoing vitrectomy were selected as the observation group (OG) and control group (CG), respectively. The mRNA and protein expression levels of miR-195, SIRT1, BAX, and BCL-2 were detected in the retinal tissues obtained from the two groups during surgery. In addition, human retinal endothelial cells and human dermal microvascular endothelial cells were cultured in a high-glucose environment to detect the targeted relationship between miR-195 and SIRT1; determine the mRNA and protein expression levels of SIRT1, BAX, and BCL-2 after miR-195 knockdown; and assess the levels of cell proliferation and apoptosis. In OG, the mRNA and protein expression levels of miR-195 and BAX were high, whereas those of BCL-2 and SIRT1 were low. Moreover, we detected a targeted relationship between miR-195 and SIRT1. Conversely, miR-195 knockdown led to the downregulation of the mRNA and protein expression levels of BAX and the upregulation of the mRNA and protein expression levels of SIRT1 and BCL-2 as well as improvement in cell growth and a decrease in the apoptosis rate. miR-195 is ‍overexpressed in DR, and its targeted relationship with SIRT1 inhibits the growth of cells in the retina and accelerates ‍apoptosis.
Application of Max-Min Ant System Algorithm on IC Substrate Drilling Path Optimization

research studies the drilling path problem in the drilling process of IC substrate. Usually, tens of holes are to be drilled on an IC substrate and there are about 1,000 substrates on a piece of copper clad laminate. A drilling path that connects the tens of thousands of holes on a piece of copper clad laminate has to be laid out for the drilling process. A drilling path of shorter length is desired to reduce operation time. Thus, this problem is usually treated as a large scale traveling salesman problem. This research focuses on the drilling path problem with massive number of holes in IC substrate industry. Incorporating with the repeating design pattern on a panel, the Max-Min Ant System is applied to develop two methods: single-substrate-sequential and various-linkage. Numerical experiment with cases from (1) is conducted. Results are compared to those reported by (1) who proposed genetic algorithm approaches to the same problem. It is shown that single-substrate-sequential method is able to effectively obtain the approximate optimal value similar to the solutions of case company. Furthermore, the various-linkage method successfully improves execution time and solution stability.
Linear electric actuators and generators

Linear electric actuators and generators (LEAGs) are electromagnetic devices which develop directly short-travel progressive (or oscillatory) linear motion. Machine tool sliding tables, pen recorders, and free piston power machines are typical industrial applications for LEAGs. Their revival in applications in compressors, pumps, electromagnetic valve actuators, active shock absorbers, vibrators, etc. prompts this review, which presents main LEAGs configurations, their principles of operations, comparative performance evaluation, motion control and existing and potential applications.
The Relationship between Adverse Family Experiences during Childhood and Self-rated Health Outcome in Adulthood

ABSTRACT Although there is increasing evidence of a link between adverse family experiences (AFEs) and long-term health outcomes, few studies have investigated the role of educational attainment in the relationship between AFEs and adult health. The data of this study comes from the China Health and Retirement Longitudinal Study (CHARLS). Here, 15,359 samples were analyzed. Ordered logistic regression with interaction terms was used to explore the moderating effect of education on the relationship between AFEs in childhood and adult self-rated health. The self-rated health scores of people with childhood AFEs were significantly lower than of those without them, particularly in the categories of “parents divorced,” “parent died,” “physical abuse,” “domestic conflict,” “parental bias,” “physical and emotional neglect,” “parental physical illness,” ‘parental mental illness,” “family economic hardship,” “experience of starvation,” “lived in an insecure neighborhood,” and “lived in an unhygienic community. ” Increases in education level reduced the adverse effects of parental bias and neglect in childhood, but this did not eliminate the negative effect of community’s environment on adult health. This study highlighted the role of the level of education in eliminating health disparities, which can reduce the adverse effects of AFEs on health in adulthood.
Seasonal prediction of PM2.5 based on support vector machine model and multiple regression model

Air pollution, an issue that requires world-wide attention, has been a long-lasting problem, especially in north Asia. PM2.5 concentration that exceeds the standard value has been a main cause to people’s both mental and physical health. As the environment conservation is on going, prediction models need persistent emphasis to better forecast air quality with great accuracy so that citizens can better manage life schedule and impact of air pollution can be alleviated. This paper chose Xuhui District, Shanghai as the prediction area, collected year-round data accurate to hour, chose data from numerous dimensions which covers gaseous influents and meteorological factors, and set these input values with different weights when training data based on the degree these factors lead to air quality fluctuations. Besides, the research integrated polynomial regression model and Support Vector Machine models, which are two methods with great difference, so as to compensate for each other’s prediction of PM2.5 concentration disadvantages. when combining these two models and setting different weights to the results of these two models, the new result of predicted PM2.5 is closer to the real value.
Double negative media using interconnected ω‐type metallic particles

We report on broadband low‐loss properties of Ω‐based metamaterials. It is shown that interconnecting elementary current‐loops via their arms can yield to a relative bandwidth of around 70% for infinite arrays. Combining interconnected and disconnected sections permits one to engineer the left‐handed and right‐handed dispersion branches with the prospect of composite artificial media such as those initially proposed by Itoh and coworkers (IEEE Microwave Mag 34 (2004) 34–50) in the context of transmission lines. This typical behavior is interpreted through a lumped element model. At last, some guidelines to optimize the transmission properties of Ω‐shaped arrays are presented. These results are discussed on the basis of recently published data concerning Ω‐shaped and C‐shaped particles. © 2006 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 84–90, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22034
Equivalent Circuit Model of Top-Emitting OLED for the Designing of OLED-on-Silicon Microdisplay

In the commonly-used EDA software, there is no equivalent circuit model of top-emitting OLED for SPICE, so it is difficult while the OLED pixel driving circuits are designed such as in microdisplay applications. To solve the problem, its SPICE model of top-emitting OLED was studied in this paper. Three models including the diode-connected NMOS model, the single-diode model, and the double-diode paralleled model are discussed and their simulation results from EDA software HSPICE are compared. Results show that the fitted errors obtained from the diode-connected NMOS model is the smallest, but its simulated errors are the largest. The fitted errors and the simulated errors obtained from the single-diode model are also large. However, small fitted errors and simulated errors got from double-diode paralleled model show that this model satisfies the application of the designing for OLED pixel driving circuits.
Future Prospective of Oral Microbiome Research

Oral microbiome has complex structure. It consisted of more than 700 species of bacteria. These bacteria contains pathogens for human health. In contrast, some beneficial bacteria were included. Perspective of oral microbiome is not still elucidated. In this paper, information regarding oral microbiome of health older adults and oral diseases are included. Additionally, concise review of oral microbiome are presented.
OPTIMISATION OF REACTION PARAMETERS FOR THE SYNTHESIS OF SOLKETAL LEVULINATE AS POTENTIAL BIODIESEL ADDITIVE

Glycerol is a major by-product of biodiesel production and finding new uses for glycerol is crucial to ensure the sustainability and continuance of the biodiesel industry. Thus, the transformation of glycerol into ketal compounds that have potential as additive to improve biodiesel properties, could be an option to provide an outlet for increasing glycerol stock. This study aims to optimise the transesterification reaction to afford solketal levulinate ester (SoLE) in highest yield by reacting solketal with methyl levulinate (ML). The reaction parameters varied are type of base catalyst, catalyst concentration, reaction temperature, reaction time and reactants molar ratio. Under optimised reaction conditions: 1.5% sodium carbonate (Na 2 CO 3 ) catalyst loading, reaction temperature of 140°C, reaction time of 4 hr and molar ratio of 3:1 (solketal:ML), as high as 74.5% yield and 95.0% purity of SoLE was obtained.
Numerical Study on Mixing Performance of Straight Groove Micromixers

Numerical analyses have been performed to investigate the effects of geometric parameters of a straight groove micromixer on mixing performance and pressure drop. Three-dimensional Navier-Stokes equations with two working fluids, water and ethanol have been used to calculate mixing index and pressure drop. A parametric study has been carried out to find the effects of the number of grooves per cycle, arrangement of patterned walls, and additional grooves in triangular dead zones between half cycles of grooves. The three arrangements of patterned walls in a micromixer, i.e., single wall patterned, both walls patterned symmetrically, and both walls patterned asymmetrically, have been tested. The results indicate that as the number of grooves per cycle increases the mixing index increases and the pressure drop decreases. The microchannel with both walls patterned asymmetrically shows the best mixing performance among the three different arrangements of patterned walls. Additional grooves confirm the better mixing performance and lower pressure drop.
From gearstick to joystick – Challenges in designing new interventions for the safety-critical driving context

Consumer electronics increasingly find their way into cars and are often portrayed as unwanted distractions. As part of our endeavour to capitalise on these technologies as safety tools rather than safety threats, we suggest to use smartphones, head-up displays, vehicle interfaces, and other digital gadgets: a) as readily available and lightweight sensing devices, and b) as platforms for engaging interventions that provide safe stimuli in real- time while driving. In our effort to make safe driving behaviours more fun, we explore ways to apply gamification to driving. In this paper, we illustrate the need for a careful balance between fun and safety and reveal ethical issues that arise when introducing new technology interventions into this complex and safety- critical design space.
Subsonic roll oscillation experiments on the Standard Dynamics Model

The experimental determination of the subsonic roll derivatives of the Standard Dynamics Model, which is representative of a current fighter aircraft configuration, is described. The direct, cross and cross-coupling derivatives are presented for angles of attack up to 41 deg and sideslip angles in the range from -5 deg to 5 deg, as functions of oscillation frequency. The derivatives exhibited significant nonlinear trends at high incidences and were found to be extremely sensitive to sideslip angle at angles of attack near 36 deg. The roll damping and dynamic cross derivatives were highly frequency dependent at angles of attack above 30 deg. The highest values measured for the dynamic cross and cross-coupling derivatives were comparable in magnitude with the maximum roll damping. The effects of oscillation amplitude and Mach number were also investigated, and the direct derivatives were correlated with data from another facility.
Coupled Self-Exciting Process for Information Diffusion Prediction

The forwarding behavior of each individual at microscopic level determines the final morphology of macroscopic cascades. Fully grasping the inner relationship between forwarding events is essential for understanding the intrinsic diffusion mechanisms, which has proven to offer decisive references in many applications, e.g., viral marketing and innovation diffusion. Conventional approaches generally constrain the occurrence of forwarding events to a specific priori based on expert experience. However, excessive parameterization will limit the learning ability of these models. As a typical stochastic process that can characterize the mutual excitation phenomenon, the Hawkes process merely assumes that the influence between users must satisfy the mode of "excitation first, then decay". In this paper, we propose the Coupled Self-Exciting Process (CoSEP) to achieve a generalized stochastic process for information diffusion prediction. Concretely, we design a coupling strategy based on the shifted Bi-LSTM, which simultaneously considers the instantaneous excitation generated by history and the subsequent evolution while modeling the change of intensity function corresponding to each participant. Extensive experiments on real-world datasets, Sina Weibo and Open Academic Graph 2.0, demonstrate that the proposed CoSEP significantly outperforms state-of-the-art approaches, suggesting the effectiveness of the coupled self-exciting process for social applications.
Surface defect detection of vehicle light guide plates based on an improved RetinaNet

Aiming at the vehicle navigation light guide plate (LGP) image characteristics, such as complex and gradient textures, uneven brightness, and small defects, this paper proposes a visual inspection method for LGP defects based on an improved RetinaNet. First, we use ResNeXt50 with higher accuracy under the same parameters as the backbone network, and propose the lightweight module Ghost_module to replace the 1 × 1 convolution in the lower half of the ResNeXt_block. This can reduce the resource parameters and consumption, and speed up training and inference. Second, we propose and use an improved feature pyramid network module to improve the feature fusion network in RetinaNet. It can more effectively fuse the shallow semantic information and high-level semantic information in the backbone feature extraction network, and further improve the detection ability of small target defects. Finally, the defect detection dataset constructed based on the vehicle LGP images collected at a industrial site, and experiments are performed on the vehicle LGP dataset and Aluminum Profile Defect Identification dataset (Aluminum Profile DID). The experimental results show that the proposed method is both efficient and effective. It achieves a better average detection rate of 98.6% on the vehicle LGP dataset. The accuracy and real-time performance can meet the requirements of industrial detection.
Diet and Consumer Behavior in U.S. Vegetarians: A National Health and Nutrition Examination Survey (NHANES) Data Report

An increasing number of individuals adopt plant-based diets for their potential health benefits. Understanding vegetarians’ dietary behavior in the context of their socioeconomic background is essential for pro-vegetarian messaging and to influence public beliefs about plant food consumption. Thus, this study sought to investigate diet and consumer behaviors in U.S. vegetarians. This is a cross-sectional, population-based study with data from the Nutrition and Health Examination Surveys (2007–2010). Selected items from three modules (diet and nutrition behavior, consumer behavior, and food security) were compared between vegetarians (n = 352) and the general population (n = 14,328). U.S. vegetarians consumed significantly fewer calories and less cholesterol but more fiber than their omnivorous counterparts. Moreover, vegetarians had significantly fewer soft drinks and salty snacks available at home. We also observed significant intergroup differences with regard to the availability of fruit and dark green vegetables. Vegetarians spent less money on eating out and indicated a lower number of not-home-prepared meals and ready-to-eat foods. We found no differences regarding money spent at supermarkets or grocery stores. Our study contributes to a better understanding of dietary and consumer behaviors in vegetarians. We shed a new light on the economic feasibility of vegetarian diets, highlighting that these diets are not necessarily more expensive than an omnivorous diet.