Miracle-dz/UniFAR-FTUs huggingface dataset:
The Speed of Swimming of Fish as Related to Size and to the Frequency and Amplitude of the Tail Beat

1. An apparatus is described in which it is possible to study and record the continuous swimming of fish at speeds up to 20 m.p.h. 2. Records made of the swimming at different speeds of dace, trout and goldfish measuring up to 30 cm. in length are reproduced. 3. Speed at any particular frequency of tail beat is shown to be directly related to the length of the specimen, measured from the tip of the snout to the most posterior extremity of the tail. 4. Above a frequency of 5 tail beats per second speed is directly dependent upon frequency up to the maximum values recorded. The results for all sizes and species recorded may be adequately expressed by the formula V = ¼{ L (3 f - 4)}, where V is the speed in cm. per sec. , f is the frequency in beats per sec. and L is the body length in cm. 5. The distance travelled per beat (and hence the speed) is directly dependent upon the amplitude of the tail beat. 6. The amplitude increases with increasing frequency up to a maximum reached at about beats per second. This maximum amplitude is the same for all fish tested and is about one-fifth of the body length. 7. The maximum frequency attainable decreases with increasing size of the specimen. This decrease is slight in the trout and more pronounced in the dace and goldfish. Estimation of the possible maximum frequencies of much bigger fish allows for prediction of the maximum speeds they may be able to attain. Such predicted speeds are in accord with the few measurements that have been made and are of the order of 10 body lengths per second up to a size of 1 m.
Biochemical composition and nutritional value analysis of Chinese mitten crab, Eriocheir sinensis, grown in pond

Chinese mitten crab ( Eriocheir sinensis ) is an importantly economic species farmed in China and is becoming a commonly worldwide food due to its increasing export. The nutritional compositions of Chinese mitten crab of commercial size grown in pond with different genders were analyzed in this study. The results showed that total edible yield were ~40% for both male and female crabs. Meat from muscle contributed as much as 80% of the total protein, and can be considered as a low-fat and high-protein food with relative well-balanced essential amino acids, especially that from female crabs. While the edible viscera counting ~ 99% of the total fat with rich n-3 fatty acids, especially EPA and DHA, which together with the higher n-3/n-6 PUFA ratios, proved that Chinese mitten crab grown in pond is undoubtedly an n-3 PUFA-rich food for human. No significant differences were found in all parameters tested between male and female crabs though male crab has lower values of essential amino acids score than female crabs, indicating that male and female Chinese mitten crabs have equally nutritional values.
A Hybrid Metaheuristic Method in Training Artificial Neural Network for Bankruptcy Prediction

Corporate bankruptcy prediction is an important task in the determination of corporate solvency, that is, whether a company can meet up to its financial obligations or not. It is widely studied as it has a significant effect on employees, customers, management, stockholders, bank lending assessments, and profitability. In recent years, machine learning techniques, particularly Artificial Neural Network (ANN), have widely been studied for bankruptcy prediction since they have proven to be a good predictor, especially in financial applications. A critical process in learning a network is weight training. Although the ANN is mathematically efficient, it has a complex weight training process, especially in computation time when involving a large training data. Many studies improved ANN’s weight training using metaheuristic algorithms such as Evolutionary Algorithms (EA), and Swarm Intelligence (SI) approaches for bankruptcy prediction. In this study, two metaheuristics algorithms, Magnetic Optimization Algorithm (MOA) and Particle Swarm Optimization (PSO), have been enhanced through hybridization to propose a new method MOA-PSO. Hybrid algorithms have been proven to be capable of solving optimization problems faster, with better accuracy. The MOA-PSO was used in training ANN to improve the performance of the ANN in bankruptcy prediction. The performance of the hybrid MOA-PSO was compared with that of four existing algorithms. The proposed hybrid MOA-PSO algorithm exhibits promising results with a faster and more accurate prediction, with 99.7% accuracy.
Bayesian Assessment of Diagnostic Strategy for a Thyroid Nodule Involving a Combination of Clinical Synthetic Features and Molecular Data

The use of machine learning has increased over the years, especially in the world of molecular data. Generally, the inference of relationships between features is determined by statistical models. The phenotype (observable clinical characteristics) can result from the expression of the genotype (genetic code) or environmental factors. Molecular datasets have limited information, while supporting clinical data is ambiguous. There are no well-established approaches for combining clinical information with genomic repositories. The genomic tests that are available only use molecular data and give physicians a result which can be integrated clinically. In this article, we present the strategy where clinical data, regardless of its limitations, is combined in one predictive model with molecular features. We predict the risk of malignancy in the thyroid nodules based on the results of fine-needle aspiration biopsy and expression of selected genes. We utilize a Bayesian network (BN) framework to discover relationships between molecular features and assess the impact of added clinical data quality on the performance of the chosen gene set. Bayesian network offering both prognostic and diagnostic perspectives is a perfect non-parametric technique for feature selection, feature extraction, and prediction purposes. We show that certain clinical factors could work as a synthetic feature and provide predictive abilities beyond what genes alone can offer. The experimental results demonstrate a higher performance of predictive models based on molecular and clinical data than when using only molecular data. We also explain why, one should consider the source of clinical data, but be aware of the quality of variables.
Hyperspectral Image Classification Method Based on 2D–3D CNN and Multibranch Feature Fusion

The emergence of a convolutional neural network (CNN) has greatly promoted the development of hyperspectral image (HSI) classification technology. However, the acquisition of HSI is difficult. The lack of training samples is the primary cause of low classification performance. The traditional CNN-based methods mainly use the 2-D CNN for feature extraction, which makes the interband correlations of HSIs underutilized. The 3-D CNN extracts the joint spectral–spatial information representation, but it depends on a more complex model. Also, too deep or too shallow network cannot extract the image features well. To tackle these issues, we propose an HSI classification method based on the 2D–3D CNN and multibranch feature fusion. We first combine 2-D CNN and 3-D CNN to extract image features. Then, by means of the multibranch neural network, three kinds of features from shallow to deep are extracted and fused in the spectral dimension. Finally, the fused features are passed into several fully connected layers and a softmax layer to obtain the classification results. In addition, our network model utilizes the state-of-the-art activation function Mish to further improve the classification performance. Our experimental results, conducted on four widely used HSI datasets, indicate that the proposed method achieves better performance than the existing alternatives.
Integrated nutrient management in rainy season groundnut (Arachis hypogaea)

A field experiment was conducted at Junagadh during the rainy season of 1996 and 1997 to study the effect of organic, inorganic and biological sources of nutrients on yield, quality, nutrient content and uptake of semi spreading groundnut (Arachis hypogaea L.) as well as nutrient status of soil. Combine application of FYM Q 20 tonneslha 100% recommended dose of fertilizer Azotobacter spp. Pseudomonas striata recorded significantly higher shelling (%), protein content and yield, oil yield, mean yield of pod and haulm as well as gross returns than the control, at application of only FYM Q 10 tonnestha, , Azotobacter spp. Pseudomonas striata, 50% N of recommended dose of fertilizer Pseudomonas striata, 50% P,O, of recommended dose of fertilizer Azotobacter spp. and 50% recommended dose of fertilizer, while net returns were obtained maximum when crop was fertilized with only 100% recommended dose of fertilizer. Similar trend was also observed for N, P, K content and uptake. Available nitrogen and phosphorus in soil was also improved with combined application of organic, inorganic and biofertilizers.
SMELL SPACE

The human sense of smell is powerful. However, the way we use smell as an interaction modality in human–computer interaction (HCI) is limited. We lack a common reference point to guide designers’ choices when using smell. Here, we map out an olfactory design space to provide designers with such guidance. We identified four key design features: (i) chemical, (ii) emotional, (iii) spatial, and (iv) temporal. Each feature defines a building block for smell-based interaction design and is grounded in a review of the relevant scientific literature. We then demonstrate the design opportunities in three application cases. Each application (i.e., one desktop, two virtual reality implementations) highlights the design choices alongside the implementation and evaluation possibilities in using smell. We conclude by discussing how identifying those design features facilitates a healthy growth of this research domain and contributes to an intermediate-level knowledge space. Finally, we discuss further challenges the HCI community needs to tackle.
NativeX: Native Executioner Freezes Android

Android is a Linux-based multi-thread open-source operating system that dominates 85% of the worldwide smartphone market share. Though Android has its established management for its framework layer processes, we discovered for the first time that the weak management of native processes is posing tangible threats to Android systems from version 4.2 to 9.0. As a consequence, any third-party application without any permission can freeze the system or force the system to go through a reboot by starving or significantly delaying the critical system services using Android commands in its native processes. We design NativeX to systematically analyze the Android source code to identify the risky Android commands. For each identified risky command, NativeX can automatically generate the PoC (Proof-of-Concept) application, and verify the effectiveness of the generated PoC. We conduct manual vulnerability analysis to reveal two root causes beyond the superficial attack consequences. We further carry out quantitative experiments to demonstrate the attack consequences, including the device temperature surge, the battery degeneration, and the computing performance decrease, based on which, three representative PoC attacks are engineered. Finally, we discuss possible defense approaches to improve the management of Android native processes.
The Influence Of UTAUT Model Factors On The Intension Of Millennials Generation In Using Mobile Wallets In Jakarta

This study was carried out to identify factors affecting the acceptance of mobile wallets by Millennials in Jakarta based on UTAUT (Unified Theory of Acceptance and Use of Technology) model. The respondents of this study were mobile wallet users within age ranging from 20–35 years old and living in Jakarta. Payment using cash is still the preferred mode of payment in Indonesia, 92% still choose to use cash as a payment option. Population aged 20 - 35 years, which in Jakarta alone amounted to 40% of the total population of Jakarta. The data was collected using questionnaires directly and also by using Google Form. The respondents in this study amounted to 407, which was using a random sampling technique. The analysis of this study was conducted using Modeling of structural equations-Partial Least Square (SEM-PLS). The result of this study shows that Millennials' Behavioral Intention to use mobile wallet in Jakarta was affected by Effort Expectancy, Age, Facilitating Condition, and Performance Expectancy.
Online teaching placement during the COVID-19 pandemic in Chile: challenges and opportunities

ABSTRACT The 2019 Coronavirus pandemic has triggered significant changes in education systems worldwide and Initial Teacher Education (ITE) programmes have been particularly affected by the associated challenges. Due to school closures, teaching placements have had to shift from the face-to-face lessons to an entirely virtual model. Twenty-seven Chilean English as a Foreign Language (EFL) teacher candidates participated in this interpretative case study aiming at exploring the challenges and opportunities of this virtual teaching experience. The results indicate that factors such as the lack of direct interaction with learners and the sudden change of setting were among those that most strongly affected the participants’ own learning process. Despite the challenges presented, student teachers suggested that this unique experience would contribute positively, at least to a certain extent, to their teacher education and their future careers. Based on the findings of this study, a series of recommendations for ITE programmes are provided.
Cartographic content analysis of compelling climate change communication

ABSTRACT Maps are a key way to communicate climate change. The goal of these maps is to make climate change relatable, tangible, and understandable. However, little research has assessed the content of these maps and the aspects of these maps which attract readers, reduce complexity, and make climate change tangible. One way to evaluate maps of climate change is through the concept of vividness, a term from the communication literature. This article examines the content and vividness of maps of climate change to answer the following: which media organizations publish these maps? What is the design and content of these maps? Did these maps convey climate change vividly? Using content analysis and multidimensional scaling (nMDS) this research showed that producers of climate change maps are often not the publishers of this same content. These maps primarily showed topics which were relevant to audiences in the United States. There was a wide variety of different cartographic designs used. And finally, maps were vivid when they employed the eight aspects of vividness presented in this paper: legend design, symbolization, layout, projections which were appropriate for the data, visual salience, visible change over time, color use which aligned with color connotations, and novel design styles.
Prognosis Analysis and Validation of m6A Signature and Tumor Immune Microenvironment in Glioma

Glioma is one of the most typical intracranial tumors, comprising about 80% of all brain malignancies. Several key molecular signatures have emerged as prognostic biomarkers, which indicate room for improvement in the current approach to glioma classification. In order to construct a more veracious prediction model and identify the potential prognosis-biomarker, we explore the differential expressed m6A RNA methylation regulators in 665 gliomas from TCGA-GBM and TCGA-LGG. Consensus clustering was applied to the m6A RNA methylation regulators, and two glioma subgroups were identified with a poorer prognosis and a higher grade of WHO classification in cluster 1. The further chi-squared test indicated that the immune infiltration was significantly enriched in cluster 1, indicating a close relation between m6A regulators and immune infiltration. In order to explore the potential biomarkers, the weighted gene co-expression network analysis (WGCNA), along with Least absolute shrinkage and selection operator (LASSO), between high/low immune infiltration and m6A cluster 1/2 groups were utilized for the hub genes, and four genes (TAGLN2, PDPN, TIMP1, EMP3) were identified as prognostic biomarkers. Besides, a prognostic model was constructed based on the four genes with a good prediction and applicability for the overall survival (OS) of glioma patients (the area under the curve of ROC achieved 0.80 (0.76–0.83) and 0.72 (0.68–0.76) in TCGA and Chinese Glioma Genome Atlas (CGGA), respectively). Moreover, we also found PDPN and TIMP1 were highly expressed in high-grade glioma from The Human Protein Atlas database and both of them were correlated with m6A and immune cell marker in glioma tissue samples. In conclusion, we construct a novel prognostic model which provides new insights into glioma prognosis. The PDPN and TIMP1 may serve as potential biomarkers for prognosis of glioma.
Correlates of Health-Protective Behavior During the Initial Days of the COVID-19 Outbreak in Norway

The coronavirus outbreak manifested in Norway in March 2020. It was met with a combination of mandatory changes (closing of public institutions) and recommended changes (hygiene behavior, physical distancing). It has been emphasized that health-protective behavior such as increased hygiene or physical distancing are able to slow the spread of infections and flatten the curve. Drawing on previous health-psychological studies during the outbreak of various pandemics, we investigated psychological and demographic factors predicting the adoption and engagement in health-protective behavior and changes in such behavior, attitudes, and emotions over time. We recruited a non-representative sample of Norwegians (n = 8676) during a 15-day period (March 12–26 2020) at the beginning of the COVID-19 outbreak in Norway. Employing both traditional methods and exploratory machine learning, we replicated earlier findings that engagement in health-protective behavior is associated with specific demographic characteristics. Further, we observed that increased media exposure, perceiving measures as effective, and perceiving the outbreak as serious was positively related to engagement in health-protective behavior. We also found indications that hygiene and physical distancing behaviors were related to somewhat different psychological and demographic factors. Over the sampling period, reported engagement in physical distancing increased, while experienced concern or fear declined. Contrary to previous studies, we found no or only small positive predictions by confidence in authorities, knowledge about the outbreak, and perceived individual risk, while all of those variables were rather high. These findings provide guidance for health communications or interventions targeting the adoption of health-protective behaviors in order to diminish the spread of COVID-19.
The Effect of Teachers’ Attitudes and Teacher Efficacy for Inclusive Education on Emotional Distress in Primary School Teachers in Japan

The purpose of this study is to examine the relationship between teachers’ attitudes toward and teacher efficacy in inclusive education, and the emotional distress in Japan. A survey of 158 primary school teachers in Yamaguchi prefecture, Japan measured the attitudes of regular and special education teachers for inclusive education and teacher efficacy toward inclusive education to assess the impact of these factors on teachers’ emotional distress. The results indicated that the teachers’ emotional distress was significantly and negatively correlated with attitudes toward integrated classroom management and perceived ability to teach students with disabilities. Furthermore, teachers’ emotional distress was significantly and negatively correlated with high teacher efficacy in inclusive instruction, collaboration, and managing behavior. A regression analysis was performed which further confirmed that efficacy in collaboration and managing behavior were unique predictors of emotional distress in primary school teachers. These findings can provide useful insights into the issue of emotional distress in primary school teachers.
Establishment of Design Hyetographs of 24-hour Duration Using a Bivariate Gumbel-Hougaard Copula

ABSTRACT Yang, X. ; Wang, J.; Weng, S.G. ; Hou, M. ; Zhang, X.Y. , and Wang, T.S. , 2020. Establishment of Design Hyetographs of 24-hour duration using a bivariate Gumbel-Hougaard copula. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 166–171. Coconut Creek (Florida), ISSN 0749-0208. Design hyetograph with a given return period and selected combinations of rainfall depth, peak intensity and duration, is widely used in engineering design. Recent hydrologic studies on multivariate stochastic analysis of extreme rainfall event have shown that these variables related to design hyetograph are partially correlated, and that copulas perform well for multivariate problems. Therefore, the main aim of the study is to develop a new method using Gumbel-Hougaard copula to construct design hyetograph. Firstly fixing the rainfall duration and rainfall return period, then the pairs total rainfall depth-the corresponding peak can be determined using a specified conditional risk probability, finally the dimensionless hyetograph is scaled to fit the specified design total rainfall depth and the corresponding peak. Shenzhen (China) was chosen for case study, and T-year (50-yr, 100-yr, 200-yr) design hyetographs of 24 h duration were discussed. The proposed method provides an effective rule to optimize the choices for the design hyetograph variables.
Varietal Differences of Rice in Differentiation and Degeneration of Secondary Rachis-branches and Spikelets in Terms of Their Nodal Distribution on a Rachis

The higher number of spikelets in modern rice varieties with higher yielding ability (MVs) results from the higher number of secondary rachis branches (SBs). It is conjectured that rice cultivar Takanari has higher ability to develop more spikelets at upper part of a panicle and that it realizes greater grain-filling ability. The experimental objective was to clarify the varietal difference in nodal distribution of SBs and spikelets on a rachis (ear type) between local japonica varieties (LJVs) and MVs. Eight cultivars different in the number and the size of spikelets were used. The cultivars were classified into three ear types with differentiated spikelets : Spikelets on middle modes superior-type, spikelets on middle and lower nodes superior-type and spikelets on lower nodes superior-type. The cultivars of higher spikelet number except Akenohoshi differentiated SBs mainly on lower nodes. The increased SBs on lower nodes were, however, easily degenerated. This made survival spikelet number at the middle part of a panicle increased more than that at upper and lower parts with the exception on Nanjin 11 and Arborio. There was little difference in ear type between local and modern japonica varieties. Spikelets at the upper part of panicle in LJVs could not supplement the loss of spikelets degenerated at the lower part. It was concluded that it is difficult to increase spikelets at the upper part, using the LJVs researched in this experiment.