Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil organic carbon stocks in Laos: spatial variations and controlling factors

Surface soils, which contain the largest pool of terrestrial organic carbon (C), may be able to sequester atmospheric C and thus mitigate climate change. However, this remains controversial, largely due to insufficient data and knowledge gaps in respect of organic C contents and stocks in soils and the main factors of their control. Up to now and despite numerous evaluations of soil organic carbon (SOC) stocks worldwide, the sloping lands of southeast Asia, one of the most biogeochemically active regions of the world, remain uninvestigated. Our main objective was to quantify SOC stocks and to evaluate the impact of various environmental factors. We, therefore, selected Laos with 230 566 km2 of mostly forested steep slopes, and where cultivation is still mainly traditional, i.e. a system of shifting cultivation without fertilization or mechanical tillage. Analytical data from 3471 soil profiles demonstrated that the top 1 m of soil depth holds an estimated 4.64 billion tons of SOC, 65% of which is in the first 0.3 m. SOC stocks to 0.3 m exhibit a high coefficient of variation (CV=62%) with values from 1.8 to 771 Mg C ha−1 and a mean at 129 Mg C ha−1. Furthermore, these stocks are significantly (at P<0.05 level) affected by land use as shown by principal components analysis and t‐tests with the largest amount being found under forest, less under shifting cultivation and the smallest under continuous cultivation. Moreover, SOC stocks correlated regionally to total annual rainfalls and latitude, and locally at the hill‐slope level to the distance to the stream network and the slope angle. It is hypothesized that this correlation is through actions on mineral weathering, soil clay content, soil fertility and SOC redistributions in landscapes. These relationships between SOC stocks and environmental factors may be of further use in (1) predicting the impact of global changes on future SOC stocks; and (2) identifying optimal strategies for land use planning so as to minimize soil C emissions to the atmosphere while maximizing carbon sequestration in soils.
Using PseudoGravity to Attract People: An Automated Approach to Engaging a Target Audience using Twitter

We introduce the PseudoGravity tool, an automated social media system that establishes a social media presence in the area of interest of a target audience, identifies target users that are open to connect, engages with them, and elicits a complex response and time investment from them. In this work, we use Twitter as the social media platform and an extensive survey as the activity requiring time investment. We evaluate the tool by using it to find and survey a challenging target – science fiction authors – and compare its results with other methods of automated online surveys. In 28 months, the Twitter account managed by the tool achieved more than 12,000 followers, and achieved monthly Tweet Impressions of more than 250,000. The tool also achieved a high survey response rate of 71% and a completion rate of 83% compared to 30% and 47% achieved by typical online surveys, and high numbers of words and characters entered for questions that required free text input. In addition, this work successfully surveyed more than 500 science fiction writers and gained new understandings of the challenges that e-publishing is bringing to their profession.
Acquisition and Analysis of a Meme Corpus to Investigate Web Culture

Memes are a popular part of today’s online culture reflecting current developments in pop-culture, politics or sports and are created and shared in large scale on a daily basis. We present first results of an ongoing project about the study of online-memes via computational Distant Reading methods. We focus on the meme type of image macros. Image macros memes consists of a reusable image template with a top and/or bottom text and are the most common and popular meme types. We gather a corpus for 16 of the most popular image macros memes by crawling the platform knowyourmeme.com thus creating a corpus consisting of 7840 memes incarnations and their corresponding metadata. Furthermore, we gather the text of the memes via OCR and make this corpus publicly available for the research community. We explore the application of various text mining methods like Topic Modeling and Sentiment Analysis to analyze the language, the topics and the moods expressed via online memes.
A Coupling Dynamic Model for Studying the Physical Interaction Between a Finger Exoskeleton and a Human Finger

This paper presents a coupling dynamic model that is based on a spring-damping contact for modeling and analyzing the physical interaction between the soft exoskeleton and the finger. The physiological structure and biomechanical model of the finger were introduced. According to the movement mechanism of the finger, a bionic prototype of the single-finger model, which is driven by shape memory alloy (SMA) wire, was designed, and its mechanical model was established. A spring-damping model was used to expound an interaction force of a human-robot with a coupling dynamic model. The experiment was carried out to verify the exoskeleton mechanical model and determine the bending angle trajectory of each joint. The inverse solution of the coupling dynamic model was verified by using angle data and driving parameters as input. According to the torque relationship, the actual active shrinkage torque of SMA wire was compared with the simulation data for the circumstances with or without consideration of the interaction contact force. The results confirm that the actual values are consistent with the simulation values. After comparing the actual active shrinkage torque and simulation curve without considering the interaction contact force, the error range is between 0 and $19.57~\text {N}\cdot \text {mm}$ . The comparison that considers the interaction contact force model yields an error range between −0.74 and $10.89~\text {N}\cdot \text {mm}$ . The accuracy of the model is increased by an average of 7.05%.
Prototype Development of a Nano-fiber based Portable Solar Water Purifier System

This proposed system can purify the dirtiest or even badly odoured water into a usable form, meant for drinking purposes using the Solar energy. It is small in size, light in weight, and also affordable. This system can complete the process of purification within a shorter period. The sediments, minute particles, and even the odour are removed using an activated carbon filter. The bacteria, including the smallest microorganisms and even all forms of chemicals, are expelled using a nanofiber material. The water then undergoes the process of Solar distillation for further purification, where the water is heated in a Solar chamber and is then condensed. The last stage is UV sterilization of the water, thereby fulfilling its purpose for drinking. This device is easily accessible by the ordinary villagers. It is very helpful, even during situations causing disasters like floods, and drought. This system uses a different type of technology, that is, activated carbon filters that have emerged from the charcoal, and also a thin nanofiber membrane emerged from the advanced Nano-technology. This device is a portable system, that is it can be transported to any other place without the need for any external help.
Impatiens shimianensis sp. nov. (Balsaminaceae): A New Species from Sichuan, China, Based on Morphological and Molecular Evidence

Abstract A new species, Impatiens shimianensis (Balsaminaceae), is described and illustrated. Impatiens shimianensis is morphologically most similar to I. delavayi in having ovate or ovate-orbicular leaves, crenate leaf margins, and bilobed spurs. The two species differ in that I. shimianensis has an orbicular upper petal of lateral united petals and shortly clawed lateral united petals while I. delavayi has a subtetragonous upper petal of lateral united petals and conspicuously clawed lateral united petals. The upper portion of the lower sepal of I. shimianensis is yellow and the lower portion of the lower sepal has brown stripes, whereas the whole lower sepal of I. delavayi is dark purple or pink. In addition, the petals of I. shimianensis are yellow or whitish yellow, whereas those of I. delavayi are dirty yellow or pink. Phylogenetic analyses based on DNA sequences from the nuclear internal transcribed spacer (ITS) and the chloroplast atpB-rbcL intergenic spacer showed that I. shimianensis fell within a well-supported clade composed of I. barbata, I. corchorifolia, I. delavayi, and I. poculifer. In addition to these species, a few other morphologically similar species that were not sampled for the molecular phylogenetic component of this study were compared with the species newly discovered. Impatiens shimianensis can easily be distinguished morphologically from all these species by its yellowish white flowers, dark red spur tip, and purple abaxial leaf surface.
Comparison of Effects of Ethylene-Based and Propylene-Based Copolymer on Tailoring the Properties of Polypropylene

Recently, polypropylene (PP) is considered as the potential recyclable HVDC cable insulation material. Ethylene-based copolymer (EBC) and propylene-based copolymer (PBC) were introduced into PP to tailor the properties of PP and make it more capable for HVDC cable insulation application. This paper focused on the effects of two additions on those propertied such as microstructure, thermal properties, electrical properties and space charge accumulation of PP. The results indicated that PBC was uniformly dispersed in the matrix of PP without adhesion, and its particle size did not increase with the increase of its content in the matrix. With the increase of PBC, the glass transition peak of polypropylene decreased slowly, indicating a better performance on flexibility at low temperature. With the increase of content of copolymer, the DC volume resistivity of the composite material decreased gradually, but samples with PBC had higher resistivity than samples with EBC. In the term of space charge, the addition of PBC could help suppressing the accumulation of space charge better. To sum up, PP/PBC composite material could be an option for recyclable DC cable insulation material.
A Cu–Mn complex of a Schiff base containing alanylglycine: hexa­aqua­manganese(II) bis­{[N‐(2‐oxidobenzyl­idene)alanylglycinato]cuprate(II)} dodeca­hydrate

In the title compound, [Mn(H2O)6][Cu(C12H11N2O4)]2·12H2O, the Cu atom has a square-planar coordination with two N and two O atoms of the tetra­dentate Schiff base ligand. The centrosymmetric cation [Mn(H2O)6]2+ and anion [CuL]− (L is a Schiff base derived from alanylglycine and salicylaldehyde) occupy a stacking structure within well separated columns along the c axis.
Design and Simulation of Special Hexapod Robot with Vertical Climbing Ability

This paper presented an novel design of hexapod robot, given out the mechanical structure of the hexapod robot and the design of the legs in detail, and then performed step climbing and steep slopes climbing experiment on the MATLAB and VREP simulation platform. Several simulation experiments was performed to verify the proposed design. The experimental results show that the robot has the possibility to climb vertical walls, which has important theoretical and practical significance for further improvement and research on the hexapod robot climbing vertical walls in the future. At last, there is no doubt that this hexapod robot can be equipped with some special detectors to achieve some difficult tasks.
Recommended System: Attentive Neural Collaborative Filtering

In recent years, neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation — collaborative filtering — on the basis of implicit feedback. Although some recent work has employed deep learning for recommendation, they primarily used it to model auxiliary information, such as textual descriptions of items and acoustic features of music. When it comes to model the key factor in collaborative filtering — the interaction between users and item features, they still resorted to matrix factorization and applied an inner product on the latent features of users and items. And the collaboration signal hidden in the user-item interaction is not encoded during the embedding process. Therefore, the resulting embedding may not be sufficient to capture the collaborative filtering effect. By replacing the inner product with a neural architecture that can learn an arbitrary function from data, we present a general method named ANCF(Attention Neural network Collaborative Filtering). ANCF captures collaborative filtering signals and refines the embedding of users and items according to the structure of the graph. By introducing an attention mechanism, the user vector and the item vector are learned on the user-item interaction graph, neighbor interaction information is aggregated to encode, and the embedding is propagated on the user-item interaction graph. This makes it possible to explicitly inject user-item collaboration signals into the embedding process. Extensive experiments conducted on two real world datasets show that ANCF’s recall and ndcg have increased by 30% and 35%, so our proposed ANCF method has been significantly improved over the state-of-the-art method. Empirical evidence shows that using deeper layers of neural networks offers better recommendation performance.
Introgressive Hybridization of Redband Trout in the Upper McCloud River Watershed

Abstract Introgressive hybridization is an obstacle to the conservation of many species and subspecies. Diagnostic genetic markers or markers with high allele frequency differentials, such as single-nucleotide polymorphisms (SNPs), are becoming increasingly useful for detecting introgression between species or subspecies, such as subspecies of rainbow trout Oncorhynchus mykiss known as redband trout in the upper McCloud River watershed. Using a diagnostic mitochondrial SNP as well as nine nuclear SNPs, we quantified introgression levels between native redband trout and nonnative rainbow trout at 14 locations in the upper McCloud watershed and two locations in the lower McCloud region. Our analyses suggest that Sheepheaven, Edson, Moosehead, and Swamp creeks contain a large portion of the nonintrogressed redband trout individuals remaining in the upper McCloud watershed, implying a dramatic loss of populations free from introgressive hybridization. The results of this study have key management implications.
SABES: Statistical Available Bandwidth EStimation from passive TCP measurements

Estimating available network resources is fundamental when adapting the sending rate both at the application and transport layer. Traditional approaches either rely on active probing techniques or iteratively adapting the average sending rate, as is the case for modern TCP congestion control algorithms. In this paper, we propose a statistical method based on the inter-packet arrival time analysis of TCP acknowledgments to estimate a path available bandwidth. SABES first estimates the bottleneck link capacity exploiting the TCP flow slow start traffic patterns. Then, an heuristic based on the capacity estimation, provides an approximation of the end-to-end available bandwidth. Exhaustive experimentation on both simulations and real-world scenarios were conducted to validate our technique, and our results are promising. Furthermore, we train an artificial neural network to improve the estimation accuracy.
Role of Interface Design and Experience in Mobile Service Applications Acceptance: an Empirical Study

For progressive development and dissemination of mobile service applications, the most important thing is the satisfaction and consolation of users. The theoretical model proposed in this study is based on revised technology acceptance model that comprises of the distinct features from mobile service, information systems domain. It helps to enlarge our comprehension of the application, implication, utility and usage of mobile service applications. This study adopted the quantitative method. A cross-sectioned quantitative approach using a survey tool was used to collect data. The proposed model was tested on the 171 mobile service users in Hyderabad Region, Pakistan. The structural modeling using with PLS software, data analysis has provided significant support for the extended hypothetical model. The extended model achieved acceptable fit and most of the hypothesis paths were significant. The result, according to the degree of importance, perceived usefulness shared the largest variance 68% followed by mobile service acceptances 64% and perceived ease of use 41%. Interface design and Experience were found to be a more significant factor of perceived ease of use than perceived usefulness.
Design of Wearable Wrist Haptic Device for Blind Navigation using Microsoft Kinect for Xbox 360

This paper considers issue relevant for the study and use of haptic technology for assistive devices for individuals who are blind and visually impaired in some of the major areas of importance: enhanced coverage of the direction, algorithm to be used and accuracy of the device in navigating. With all the gathered studies and considerations in designing a wearable haptic device, and with the aim to enhance the coverage of the direction it provides to the user while the device being wearable and not impairing the movement of the user, which is suitable for the blind and visually impaired person, the proponents designed a wearable wrist haptic device that provides the angle of direction to the user. Using solenoids' mechanical motion which is responsible for giving haptic feedback to the skin of the user and the concept of binary system or notation to provide the angle of direction to the user through touch. 7 solenoids which represents; left and right for the side of direction, 1, 2, 4, 8, and 16 for the binary notation. This can serve as a reference for the implementation to actual scenarios integrated with sensors. The created device is applied in real-time blind navigation using Canny Edge detector in obstacle detection system using Microsoft Kinect for XBOX 360.
Smart Hand Rehabilitation Tool for Hypertonia Patients

Hypertonia is a state in which there is extreme muscle tone so that the limbs are stiff and heavy to move. Hypertonia patients are not able to move their affected hand without any aid. Because of this disablement, hand recuperation is absolutely necessary for re-establishment of hand functionality. The objective of the study is to develop an exoskeleton for Hypertonia patients to assist them with their hand functions. The smart hand rehabilitation tool assists the patients suffering from Hypertonia to move their hand using a series of servomotors fitted at wrist and elbow joints of the exoskeleton. The angle, speed and the number of times of the movement of wrist or elbow joints exoskeleton can be controlled using ATMEGA328P microcontroller. The servomotors at wrist and elbow joints of the exoskeleton will apply extension torques and compensates for the Hypertonia.
Optimizing Spectrum Use in Wireless Networks by Learning Agents

paper examines several distributed mechanisms that can be used in wireless networks consisting of base stations transmitting onto a population of receivers. The overall goal of the algorithms is to optimize a global measure: the sum of capacities of the channels formed between transmitters and receivers in the presence of interference. We introduce a mathematical model of the operation of an OFDM-based wireless network and on this premise we pose the problem of interference in a game theoretic setting. We propose a simple but expressive way of modeling “smart devices” as learning and executing agents and introduce three types of such agents. This part of the work is carried out in the scope of the multi-armed bandit framework. One of the three algorithms we propose is well known and widely studied and two others are new variants of known algorithms seemingly not yet studied. By numerical simulations we show that these mechanisms improve network performance in the considered model. We offer some basic heuristic explanations of this improvement and identify future work.
Scheduling for Heterogeneous Computing Platforms using a Genetic Algorithm

In heterogeneous computing platform interconnected by high-speed networks, the task scheduling problem has been extensively studied. Such systems promise to quickly handle computationally intensive applications with different computing needs. The HEFT algorithm is proposed to solve the task scheduling problem of such a system. The HEFT algorithm is simple but its efficiency needs to be improved. The basic idea of our method is to take advantage of genetic algorithms and HEFT algorithms while avoiding their disadvantages. The algorithm uses the HEFT algorithm to assign priorities to each subtask, while using a genetic algorithm to search for a task-to-processor mapping solution. The GHEFT method also designs crossover, mutation, and fitness functions suitable for directed acyclic graph (DAG) scheduling. Experimental results show that the GHEFT algorithm is superior to a non-evolutionary heuristic algorithm and a random search method in terms of scheduling quality.
Investigation of a Hybrid Kinematic Calibration Method for the “Sina” Surgical Robot

Calibrating the inverse kinematics of complex robots is often a challenging task. Finding analytical solutions is not always possible and the convergence of numerical methods is not guaranteed. The model-free approaches, based on machine learning and artificial intelligence, are fast and easy to work, however, they need a huge amount of experimental training data to provide acceptable results. In this article, we proposed a hybrid method to benefit the advantage of both model-based and model-free approaches. The forward kinematics of the robot is calibrated using a model-based approach, and its inverse kinematics using a neural network. Hence, while there is no need to solve the nonlinear inverse kinematic equations, the training data of the neural network is generated artificially by the calibrated forward kinematic model. The implementation of the proposed methodology on slave robot of the “Sina” surgical system revealed reasonably good results. The accuracy improved by <inline-formula><tex-math notation="LaTeX">${\bf 53\%}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${\bf 43\%}$</tex-math></inline-formula> for position and orientation, respectively, after calibration.
A Building Block Assembly Dualband Dual-Polarized Antenna With Dual Wide Beamwidths for 5G Microcell Applications

A dualband dual-polarized antenna element with dual wide beamwidths for 5G microcell applications is initially proposed and investigated in this paper. To achieve very low manufacturing cost, an unprecedented method is applied to the antenna element, in which the antenna components are printed separately on F-4B substrates, follow by assembling them to form the antenna element (similar to building block assembly). To further achieve high gain, an $1\times 4$ antenna array is also designed. Measured results show that the half power beamwidths (HPBWs) in H- and E-planes are 112±1° and 105±3° in the lower frequency band of 3.22-3.88 GHz, respectively, and 99±3° and 106±4° in the upper frequency band of 4.52-5.02 GHz, respectively. In addition, high front-to-back ratio (FBR) of approximately 19 dB and high isolation of 33.6 dB can also be achieved.