Miracle-dz/UniFAR-FTUs huggingface dataset:
An annotated checklist of amphibians in and around Dampa Tiger Reserve, Mizoram, India

Amphibians are an integral part of the ecosystem and act as an ecological indicator. As several species are added to the list of threatened species every year due to loss of habitat, it is important to understand the role of unmanaged landscape for sustenance of amphibian diversity. In this study, 28 amphibian species were recorded from different modified habitat including 19 new records for Dampa Tiger Reserve (DTR) and its surrounding areas. Further, six species, Amolops indoburmanensis, Limnonectes khasianus, Microhyla mukhlesuri, M. mymensinghensis, Raorchestes rezakhani, and Sylvirana lacrima are new distribution records for the state of Mizoram and out of these, two species, Raorchestes rezakhani and Sylvirana lacrima, are new country records for India. Amongst the recorded species, four species are Data Deficient, two Vulnerable, 14 Least Concern, and eight species are not assessed as per the IUCN Red List. Within the core and buffer areas of DTR, we found that natural perennial stream, puddles, canals, natural ponds, fish ponds, roadside, primary forest, secondary forest, paddy fields, and human settlement areas are excellent microhabitats for amphibian population and need to be conserved for their rich ecological niches.
Innovative Aspects in the System of Labor Relations of a Modern Enterprise

The article is devoted to the problems of innovation implementation in a modern enterprise. The article reflects human resources' effective use in the conditions of instability of the external environment and personnel's irrational behaviour. The paper offers some psychological tools and principles of modern personnel policy of innovation implementation at the enterprise. The article proposes to use a new wage system based on the model of competencies with specific indicators of manifestation in professional activity, as a means of material stimulation of innovative activity at the enterprise. To effectively introduce innovations at the enterprise, the article suggests several areas of personnel work with personnel: training seminars on revealing to personnel the validity and practicality of innovative transformations taking place at the enterprise; identification of innovative generators among the staff, mentors who have an active, innovative work position, can promote the ideas of new innovative competencies, etc. The study results can be used by managers and employees of the HR management Department in practice when developing strategic and tactical measures for implementing and stimulating innovative processes at the enterprise.
One-Shot Image Segmentation with U-Net

Image segmentation is an important task in the field of computer vision research. Many applications need accurate and efficient segmentation mechanisms. However, most existing methods need a large support set and have struggled with dealing with new classes in solving computer vision problems. In order to deal with the problem, this paper modified the traditional model to adapt it to the task of few-shot segmentation. Especially, the part of encoders was changed into a Siamese neural network for support branch and query branch. Then, the decoded query image is compared with different levels of features from the encoded support image. Experimental results show that this proposed model achieved the best performance compared with several baseline methods, and the improvement is more than 8%.
Enablers and Inhibitors of E-tax System Use:The Perspective of Dual-Factor Concepts

The aim of this study is to investigate the acceptance and rejection behavior of electronic tax system at the same time. This study applied a conceptual framework focused on the dual-factor concepts of "enablers" and "inhibitors" to illustrate users' desire to exercise the e-tax system. In the dual model the Theory of Consumption Value (TCV) and Status Quo Bias (SQB) have been used to describe the reason behind consumers' accepting or rejecting the e-tax system through perceived enablers and deliberate inhibitors. A survey has been conducted in Bangladesh to collect data from 422 taxpayers, and the structural equation model was used to validate the proposed model. We find that functional value, social value, and emotional value are seen to have positive and direct impacts on the user's preference to use the e-tax system, while user’s resistance to use adversely impacts the use of the e-tax system. The results also signify that the user's resistance to using the e-tax is due to switching costs, inertia, and perceived risk. Several suggestions are provided for the practitioners to implement the e-tax system successfully by eliminating resistance factors.
Multi-objective Optimization Based Deep Reinforcement Learning for Autonomous Driving Policy

End-to-end autonomous driving approach seeks to solve the problems of perception, decision and control in an integrated way, which can better adapt to the new traffic scene. Due to the diversity of traffic scenes and the uncertainty of the interaction among surrounding vehicles, the design of autonomous driving policy is challenging. Many current methods manually design the corresponding driving policy for different traffic scene, resulting in suboptimal solutions and the maintaining is hard. Most of the existing deep reinforcement learning (DRL) methods can’t work well in the complex urban traffic scenes because of the sensing and simple driving policy. In this paper, to extend the adaptability of the SAC-based method, we proposed to take the multiple sensor data as input, and a VAE network was used to enhance the quality of training data for SAC-based DRL method. A multi-constraints reward function for SAC-based driving policy training is designed, which account for the errors of transverse distance, longitudinal distance, heading, velocity and the possibility of collision. The multiple sensor data include the original RGB image captured by forward-view camera, a 3D LiDAR and the bird’s-eye view map resulted from the perception processing, the mixed inputs could enrich the capability of scene perception. The proposed approach is validated with the multi-vehicle traffic simulation built with CARLA[1]. The results showed that the simulated vehicle could adapt to more challenging traffic scenes, like passing intersections and turning in crowded urban scenes, etc with the driving policy generated by the proposed method, and its performances are obviously outperformed against the existing similar methods.
Attention Relational Graph Convolution Networks for Relation Prediction in Knowledge Graphs

Recently, the tasks based on knowledge graph (KG), such as question answering, information retrieval, are more and more widely used. However, due to the incompleteness of the relations (links) between entities, it is very important to study the relations prediction based on KG to complete the missing relations between entities. In recent years, graph convolution networks (GCNs) have been a new method to solve the reasoning of knowledge graph. However, the existing knowledge graph relation prediction model based on GCNs fails to consider the importance between nodes. In order to obtain more abundant relations information between entities (nodes), inspired by the graph attention network (GAT), we propose an attention weighted relational graph convolutional network (denoted as AWR-GCN), which is used as an encoder of the encoder-decoder model for relationship prediction, and the decoder is a linear model. Compared with the advanced methods in the commonly used relational prediction data sets, our model has a certain performance improvement and reached advanced level.
Artificial Intelligence Path Planning for Marine Environment

Artificial intelligence path planning and its optimization method is an important topic of the times, but the research of path planning for marine environment is less. Under the background of the popularization of offshore operation platform and the urgent development of marine resources, it is very important to analyze the artificial intelligence marine path planning and study the multi strategy path planning optimization algorithm. In view of this, this study proposes a multi strategy optimization ant colony algorithm (ACA-Mso), and realizes the artificial intelligence path planning of marine environment by updating the population pheromone strategy, implementing the preview strategy of local forced exchange optimization, and the symmetric path optimization strategy. Its main advantage is that it not only overcomes the shortcomings of the basic ant colony algorithm, such as long convergence time, too many iterations of the optimal solution, and the limitations of fuzzy symmetric path selection rules, but also ensures the enhancement of pheromone among nodes, the optimization of local search path potential, and the improvement of search ability of path planning algorithm, so as to realize the comprehensive path planning of marine environment Optimization.
Controlled Synthesis of Monodisperse CeO2 Nanoplates Developed from Assembled Nanoparticles

Surfactant-mediated synthesis of monodisperse CeO2 nanoplates (15 nm × 50 nm, 2 nm thick) was conducted by the thermal decomposition of cerium acetate in 1-octadecene. X-ray diffraction patterns indicated selective (200) plane growth of fluorite cubic CeO2 in the CeO2 nanoplates, and transmission electron microscopy revealed that most of the side surfaces exhibited {200} lattice fringes. Smaller amounts of surfactants resulted in larger nanoplates composed of assemblies of small CeO2 nanoparticles (NPs). The formation of this polycrystalline structure of assembled NPs is preferable to induce stability by decreasing the surface energy and positive charge of the NPs. The bandgap energy of CeO2 nanoplates for direct transitions was larger than that for polyhedral CeO2 NPs.
Estimation of leaf area by mobile application: Fast and accurate method

There are numerous techniques for the estimation of leaf area. Every technique has some advantages and disadvantages over one another. This study proposed a new technique for the leaf area estimation i.e. mobile application (Petiole). It is a free of cost mobile application. The mobile application was used for the estimation of the leaf area of six different plant species. It was observed that error percentage for the leaf area estimation was recorded less than 4% in case of banyan, Jamun and lemon plant leaf. It was also concluded that less than 3 cm 2 area error was present for all the cases. This study confirmed the reliability, correctness and robustness of the mobile application for leaf area estimation. This study ensures the accuracy and capability of the petiole app to mitigate the problems of laborious, cumbersome and expensive experiments for the leaf area estimation and the method also saved a lot of time as compared to the other methods. It has the potential to avoid the complex coding algorithm for the program based techniques, usually adopted for the measurement of the leaf area.
Tri-State: From Shannon to Galois Fields in Communication Systems

Communication, compression of information, transmission of information through noisy channels, interconnecting different information systems, cryptography, gate construction –– these areas all depend on classical information theory. We show that, in classical terms, semantic aspects of communication are not at all irrelevant to the engineering problem, contrary to Shannon, and affect the message intended to be transmitted. This is revisited and captured by an analogy to trust, in that they are essential to the channel (for proper use), but cannot be transferred (under risk of flaws) through that same channel. Information is also described by, at least, a tri-state system — not by binary logic. The trust analogy semantics can be coded as the Curry-Howard relationship, connecting computer code with structural logic, by way of different categories. Two-state and Boolean logic (aka Shannon semantics) was used classically before, with Shannon theory, but without trust analogy semantics – found to be a sine qua non condition. This is now familiar in classical gate construction with physical systems with, e.g., Verilog and SystemVerilog. The applications to computation and quantum theory are further explored. The most fundamental entity in today`s theory of information is proposed to use at least three logical states, not bits, in all applications, including: cyber-physical systems, devices, in computation, and in quantum theory.
The effect of school-family collaboration and parents behavior on students ethical behavior

The aim of this study is to provide opinions on the evaluation of parents' attitudes and behaviors in developing cooperation in ethical education. Although the research is a qualitative study, the study group consists of 10 participants, 5 principals and 5 teachers. A semi-structured interview form was prepared and interview technique was used to collect data. The data were analyzed using the content analysis technique. According to the results of the research, to increase children's awareness of ethical principles and moral virtues, to support each other between family and school so that children can become good people, to transform the understanding of school-family cooperation to contribute to moral education, to the moral maturation of children in order to cooperate with the child and school, effective and new ways should be developed and various and different measures should be taken to carry out these actions. To be positive, desirable and morally mature for children, the school and family must be able to collaborate with the child and find effective and new ways to do this. In the field of moral education, it is essential to provide the measures that families and all collaborators should take, by revealing the need and understanding of cooperation. It is necessary to provide follow-up and support that can ensure very carefully school-family-child cooperation for maximum implementation. Key words: School-family cooperation, moral education, ethics, opinions.
Laboratory-based nitrogen mineralization and biogeochemistry of two soils used in oil sands reclamation

MacKenzie, M. D. and Quideau, S. A. 2012. Laboratory-based nitrogen mineralization and biogeochemistry of two soils used in oil sands reclamation. Can. J. Soil Sci. 92: 131-142. In the Athabasca oil sands region of Alberta, Canada, peat mineral and upland forest floor mineral soils are salvaged and stockpiled for reclamation. Previous work showed that sites reclaimed with forest floor mineral soil had better understory regeneration and nitrogen dynamics more similar to naturally disturbed ecosystems. Both soils and a mixture of the two were compared in laboratory incubations by examining nitrogen mineralization (over 45 wk) and factorial fertility additions (4 wk trial with NPK) on microbial community structure and nutrient availability. Nitrogen mineralization indicated forest floor mineral soil had lower release rates and a higher estimated labile nitrogen pool than peat mineral soil. Nitrogen mineralization in mixed soil started like peat mineral soil and finished like forest floor mineral soil. Fertility additions influenced microbial community structure less than soil type. Multi-response permutation procedure indicated the forest floor mineral soil microbial community was significantly different from peat mineral and mixed soil communities. Control nutrient profiles differed from those with added NPK. Forest floor mineral soil retained nitrogen as ammonium, while peat mineral and mixed soils were nitrate dominated. Reclamation will require all soil types to be used and these data will help determine soil placement prescriptions.
The development of harmonic oscillation e-module based on problem based learning (pbl) for helping improvement of students’ higher order thinking skills (hots)

This study aims to develop a harmonic oscillation e-module based on pbl for helping hots improvement of senior high school students at SMA N 23 Jakarta. The ADDIE Model of research and development was applied in developing such e-module prior to measure improvement of students’ hots. The validation results of experts indicated the values of 78.1%, 77.7% and 93.8% for media, learning model and content, respectively. The trial result of teachers and a small and big groups of students respectively indicated an average score of 93.95% and 95.1% and 86.5% for all aspects of content eligibility, presentation, language and graphical eligibilities. Furthermore, The tgain test calculation shown that the tgain count (2.58) was bigger than tgain table (1.67) with 5% significance level. The analyzed result indicated that the improvement of hots of students which was taught with the pbl based e-module was better than those who utilized the non pbl based e-module of the harmonic oscillation. Whiles, the result of d’Cohen test indicated that the developed e-module was very decent to be utilized as learning media with contribution category of medium (based on d’Cohen test result of 0.64) for improving hots of senior high school students.
Dampak Pembelajaran Jarak Jauh terhadap Tingkat Stres dan Kecemasan Mahasiswa selama Pandemi COVID-19

WHO telah menyatakan bahwa COVID-19 sebagai pandemi global, untuk mencegah penyebarannya maka kegiatan akademis di Indonesia dialihkan menjadi metode pembelajaran jarak jauh. Perubahan ini mengakibatkan mahasiswa harus beradaptasi dengan metode baru dan salah satu dampak dari hal tersebut adalah munculnya masalah kesehatan mental seperti stres dan kecemasan pada mahasiswa. Penelitian ini bertujuan untuk menunjukkan adanya peningkatan stres dan kecemasan pada mahasiswa sebagai dampak pembelajaran jarak jauh selama masa pandemi COVID-19. Metode yang digunakan adalah kajian pustaka dari jurnal nasional dan internasional yang meneliti tentang pengaruh pandemi COVID-19 terhadap stres dan kecemasan yang dialami mahasiswa. Penelusuran jurnal ini menggunakan database Google Scholar, ResearchGate, dan Pubmed. Hasil penelitian dari 10 jurnal menunjukkan peningkatan stres dan kecemasan yang dialami mahasiswa selama pandemi COVID-19 yang disebabkan oleh berbagai faktor. Angka stres pada mahasiswa di Indonesia selama perkuliahan jarak jauh rata-rata sebesar 55,1%, sedangkan pada mahasiswa di luar Indonesia sebesar 66,3%. Angka kecemasan mahasiswa di Indonesia selama perkuliahan jarak jauh rata-rata sebesar 40%, sedangkan pada mahasiswa di luar Indonesia sebesar 57,2%. Sebagai saran, beberapa upaya dapat dilakukan seperti olahraga atau aktivitas fisik, istirahat yang cukup, melakukan hobi, sosialisasi secara virtual serta menerapkan lingkungan yang sehat baik secara fisik maupun psikologis untuk mengurangi stres dan kecemasan.
On the origins of near-surface stresses in silicon around Cu-filled and CNT-filled through silicon vias

Micro-Raman spectroscopy was employed to study the near-surface stress distributions and origins in Si around through silicon vias (TSVs) at both room temperature and elevated temperatures for Cu-filled and carbon nanotube (CNT)-filled TSV samples. From observations, we proved that the stresses near TSVs are mainly from two sources: (1) pre-existing stress before via filling, and (2) coefficients of thermal expansion (CTE) mismatch-induced stress. CTE-mismatch-induced stress is shown to dominate the compressive regime of the near-surface stress distribution around the two types of Cu-filled TSV structures in this work and in previous work, while pre-existing stress dominates the full range of the stress distribution in the CNT-filled TSV structures studied. These results show the importance of the pre-existing stress and support the use of a liner technology with lower stress introduction such as deposited oxide instead of thermal oxide. It is specifically important for CNT-filled TSVs, where the pre-existing stress is much larger than the CTE-mismatch-induced stress as observed in this work.
Digital technology for removable partial denture realization. Case report

The conventional fabrication of removable partial dentures is a complex process, which involves a lot of clinical and technological steps. The design of the elements must be performed in order to maintain the homeostasis and to rehabilitate, in optimal conditions, the functions of the stomatognathic system. Digital technology-Computer-aided design/computer-aided manufacturing (CAD/CAM) method for partial denture fabrication brings a lot of advantages: high accuracy of the denture, increases the strength and durability, avoid changes of the volume and, time working economy. This clinical report aims to illustrate the stages of getting a removable prosthesis, using the computerized method and to emphasize that digital prosthesis can be effective and accurate, eliminating or replacing steps that can lead to complications.
A Comparative Study of Various Human Activity Recognition Approaches

Human Activity Recognition (HAR) is a vast and exciting topic for researchers and students. HAR aims to recognize activities by observing the actions of subjects and surrounding conditions. This topic also has many significant and futuristic applications and a basis of many automated tasks like 24*7 security surveillance, healthcare, laws regulations, automatic vehicle controls, game controls by human motion detection, basically human-computer interaction. This survey paper focuses on reviewing other research papers on sensing technologies used in HAR. This paper has covered distinct research in which researchers collect data from smartphones; some use a surveillance camera system to get video clips. Most of the researchers used videos to train their systems to recognize human activities collected from YouTubes and other video sources. Several sensor-based approaches have also covered in this survey paper to study and predict human activities, such as accelerometer, gyroscope, and many more. Some of the papers also used technologies like a Convolutional neural network (CNN) with spatiotemporal three-dimensional (3D) kernels for model development and then using to integrate it with OpenCV. There are also work done for Alzheimer’s patient in the Healthcare sector, used for their better performance in day-to-day tasks. We will analyze the research using both classic and less commonly known classifiers on distinct datasets available on the UCI Machine Learning Repository. We describe each researcher’s approaches, compare the technologies used, and conclude the adequate technology for Human Activity Recognition. Every research will be discussed in detail in this survey paper to get a brief knowledge of activity recognition.
Recognition of Human Activities using Machine Learning Algorithms

: Human activity recognition via wearable devices has been actively investigated during a huge variety of applications. Most of them, however, either target easy activities whereby whole-body movement is concerned or need a range of sensors to spot daily activities. During this study, we have a tendency to propose a personality's activity recognition system that collects information from associate off-the-peg smartwatch and uses a man-made neural network for classification. The planned system is additional increased victimization location data. We consider 6 activities, including both simple and dynamic activities.