Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Classiﬁcation Based On BERT

In recent years, social networks such as Weibo, social networks, forums, wikis, and online shopping platforms have gathered a large number of users. These users are not only the browsing and recipients of online information resources, but also the providers and transmitters of said resources. This information includes objective reports on people, things, and events, as well as subjective expressions of people, things, and events. How to automatically analyze and process subjective emotional expressions from different social networks has become a difﬁcult problem to be solved urgently. Among them, the theoretical basis of sentence-level text sentiment analysis technology involves many research ﬁelds such as natural language information processing, artiﬁcial intelligence, information retrieval, probability and statistics, and is used in practical applications for customer experience, market research, customer insight, and digital analysis. Even media evaluation is a key solution, closely related to Internet social media analysis such as blogs, Weibo and WeChat, and has become a current research hotspot. This article conducts in-depth research on sentence-level sentiment classiﬁcation. Under the framework of supervised learning, the Bert model is introduced, the improvement research of sentence-level sentiment analysis is carried out, and some novel sentiment clas-siﬁcation methods are proposed. And conducted experiments on the hotel review data set. Experiments show that the model has achieved good research results.
Vision Based Outdoor Localization of IIITD Campus

Localization problem is one of the most prominent problems of computer vision. Interests in solving these problems developed over the years as it had wide range of applications such as controlling the motion of a robot based on the visual inputs and navigating driverless vehicles. It is heavily used in oil pipeline inspection, ocean surveying and underwater navigation, mine exploration, coral reef inspection, military applications, crime scene investigation. The idea was popularised by the competition Where am I ? by ICCV, Computer Vision Contest.
An Empirical Investigation of the Random Walk Hypothesis in the Nigerian Stock Market

The Random Walk Hypothesis (RWH) states that stock prices move randomly in the stock market without following any regular or particular pattern and as such historical information contained in the past prices of stocks cannot be used to predict current or future stock prices. Hence, stock prices are unpredictable and that investors cannot usurp any available information in the market to manipulate the market and make abnormal profits. This study empirically examines the random walk hypothesis in the Nigerian stock market using the daily quotations of the Nigerian stock exchange from 2nd January, 1998 to 31st December, 2019. The study employs Augmented Dickey-Fuller unit root test, the random walk model, Ljung-Box Q-statistic test for serial dependence, runs test of randomness, and the robust variance ratio test as methods of analyses. The result of the study rejected the null hypotheses of a unit root and random walk in the stock returns. The null hypothesis of no serial correlation in the residuals of stock returns was also rejected indicating the presence of serial correlation/autocorrelation in the residual series. The result of the runs test rejected the null hypothesis of randomness in the Nigerian stock returns. The results of the variance ratio test under homoskedasticity and heteroskedasticity assumptions both strongly rejected the null hypothesis of a random walk for both joint tests and test of individual periods. Based on the results of the four tests applied in this study, it is concluded that the Nigerian daily stock returns under the period of investigation do not follow a random walk and hence the null hypothesis of a random walk is rejected. The results of the study further revealed that the Nigerian stock market is weak-form inefficient indicating that prices in the Nigerian stock market are predictable, dependable, consistently mispriced, inflated, liable to arbitraging and left unprotected to speculations and market manipulations. The study provided some policy recommendations
Management of Anthracnose Disease of Aloe vera in Bangladesh

Aims: To identify the causal organisms of anthracnose disease of Aloe vera in Bangladesh and to manage this disease in field condition. Study Design: The experiment was designed by Randomized Complete Block Design (RCBD) with three replications. Place and Duration of Study: The field experiments were conducted in Natore, Bangladesh and the laboratory experiments were carried out at the Department of Plant Pathology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh from January, 2017 to December, 2018. Methodology: The causal organism Colletotrichum gloeosporioides was isolated by tissue plating method and identified based on morphological and cultural characteristics and that was confirmed by pathogenicity test. Infested farmer’s fields were selected in rainy season under natural epiphytic condition to evaluate the efficacy of eleven treatments. Results: Among the treatments, Bordeaux mixture gave best result against this disease. Moreover, Tilt 250 EC and Folicur 25 EC and Garlic bulb extract showed better effect against the disease than the other treatments. Lime also has moderate effect against anthracnose disease of A. vera. In 2017, after 4th spray, the lowest incidence was recorded in Bordeaux mixture (58.33%) which was statistically identical with Folicur (64.58%), Tilt (64.58%) and Garlic bulb extract (66.67%). Similarly, the lowest disease severity was found in Bordeaux mixture (3.55) followed by Folicur (5.67%), Tilt (6.67%) and Garlic bulb extract (7.67%). Similar result also found in 2018. After 4th spray, the lowest incidence was recorded in Bordeaux mixture (38.58%) which was statistically identical with Lime (41.66%) and Garlic bulb extract (45.83%). Similarly, the lowest disease severity was found in Bordeaux mixture (0.20%) followed by Lime (0.25%) and Garlic bulb extract (0.36%). Conclusion: Garlic bulb extract could be used as eco-friendly approach. Moreover, use of Bordeaux mixture is better than the traditional use of lime. From chemical pesticides, Tilt 250 EC and Folicur 25 EC could be used for controlling the disease as the last option.
Methods of Reconstruction for Distal Aortic Dissection

The modern approach to the correction of aortic dissection involves the most complete reconstruction of the entire pathologically altered segment of the vessel, which is often impossible due to the vastness of the lesion and the associated severity of surgery. Reduction of intraoperative trauma can improve survival in the immediate postoperative period, and the completeness of reconstruction to reduce the number of complications and relapses in the long term. In this chapter, the methods of reconstruction of the aorta in case of distal dissection from a conventional open surgery to endovascular techniques, or usage of their combination for minimization of surgical trauma, are reviewed.
The role of geochemistry in organic carbon stabilization against microbial decomposition in tropical rainforest soils

Abstract. Stabilization of soil organic carbon (SOC) against microbial decomposition depends on several soil properties, including the soil weathering stage and the mineralogy of parent material. As such, tropical SOC stabilization mechanisms likely differ from those in temperate soils due to contrasting soil development. To better understand these mechanisms, we investigated SOC dynamics at three soil depths under pristine tropical African mountain forest along a geochemical gradient from mafic to felsic and a topographic gradient covering plateau, slope and valley positions. To do so, we conducted a series of soil C fractionation experiments in combination with an analysis of the geochemical composition of soil and a sequential extraction of pedogenic oxides. Relationships between our target and predicting variables were investigated using a combination of regression analyses and dimension reduction. Here, we show that reactive secondary mineral phases drive SOC properties and stabilization mechanisms together with, and sometimes more strongly than, other mechanisms such as aggregation or C stabilization by clay content. Key mineral stabilization mechanisms for SOC were strongly related to soil geochemistry, differing across the study regions. These findings were independent of topography in the absence of detectable erosion processes. Instead, fluvial dynamics and changes in soil moisture conditions had a secondary control on SOC dynamics in valley positions, leading to higher SOC stocks there than at the non-valley positions. At several sites, we also detected fossil organic carbon (FOC), which is characterized by high C/N ratios and depletion of N. FOC constitutes up to 52.0 ± 13.2 % of total SOC stock in the C-depleted subsoil. Interestingly, total SOC stocks for these soils did not exceed those of sites without FOC. Additionally, FOC decreased strongly towards more shallow soil depths, indicating decomposability of FOC by microbial communities under more fertile conditions. Regression models, considering depth intervals of 0–10, 30–40 and 60–70 cm, showed that variables affiliated with soil weathering, parent material geochemistry and soil fertility, together with soil depth, explained up to 75 % of the variability of SOC stocks and Δ14C. Furthermore, the same variables explain 44 % of the variability in the relative abundance of C associated with microaggregates vs. free-silt- and-clay-associated C fractions. However, geochemical variables gained or retained importance for explaining SOC target variables when controlling for soil depth. We conclude that despite long-lasting weathering, geochemical properties of soil parent material leave a footprint in tropical soils that affects SOC stocks and mineral-related C stabilization mechanisms. While identified stabilization mechanisms and controls are similar to less weathered soils in other climate zones, their relative importance is markedly different in the tropical soils investigated.
When are Iterative Gaussian Processes Reliably Accurate?

While recent work on conjugate gradient methods and Lanczos decompositions have achieved scalable Gaussian process inference with highly accurate point predictions, in several implementations these iterative methods appear to struggle with numerical instabilities in learning kernel hyperparameters, and poor test likelihoods. By investigating CG tolerance, preconditioner rank, and Lanczos decomposition rank, we provide a particularly simple prescription to correct these issues: we recommend that one should use a small CG tolerance ($\epsilon \leq 0.01$) and a large root decomposition size ($r \geq 5000$). Moreover, we show that L-BFGS-B is a compelling optimizer for Iterative GPs, achieving convergence with fewer gradient updates.
How American Attitudes about Race, Ethnicity, and Gender affect the Health and Wellbeing of Black-African Refugee Men in the United States

More than half of all refugees currently resettled in the United States are racial-ethnic-minority men. Yetrefugee health scholarship has not fully explored racial ethnic minority refugee men's encounters with resettlement environment norms about race, ethnicity and gender. This paper describes an intersectional-informed qualitative study of the daily stressors experienced by Black-African refugee men in the United States to explain how such experiences impact their health and wellbeing. These men’s life narratives illumi-nate how stigma and discrimination associated with race, ethnicity, gender affect their health and wellbeing during resettlement. These findings offer evidence that the realities of ethnic minority refugee men in the United States, while unique, can contribute to broader discourses about minority men’s health inequities.
AUDIO BASED BIRD SPECIES RECOGNITION USING NAÏVE BAYES ALGORITHM

— Small of the smallest living creature is the part of the whole ecosystem. Monitoring and maintaining this environmental health has become a task of prime importance, since human activity and climate change has placed the greater pressure on biodiversity. This helps in monitoring dangerous situations to planes caused by birds near airports and also in saving endangered species. Powerful audio signal processing techniques makes it possible to introduce automated methods for the detection of such vocalizations. The complete identification procedure essentially involves collection of recorded vocalizations of different species, audio pre-processing to remove the noise and silence, segmentation to select the most representative characterizing elements of the signal called syllable, extraction of different features commonly found in sound classification and speech recognition to obtain relevant characteristics, and decision procedures for identification, where Machine Learning (ML) algorithms are used to train employed classifiers using labelled database of previously known species of interest. Naïve Bayes algorithm is used for classification and hence recognition of bird species. The required class probabilities are found to be as good as 100% and as worst as 97% in some cases.
A Strategic Alignment Model for Knowledge Management

Copy right Idea Grou p Inc. Copy right Idea Grou p Inc. ABSTRACT With the growing awareness of the crucial role that knowledge can play in gaining competitive advantage, several issues with regard to knowledge management (KM) initiatives have challenged executives. The articulation of the relationship between an organizations competitive strategy and its knowledge strategy is the most eminent. Based on the premise that the realization of business value from KM investments requires alignment between business and knowledge strategies, the issue is addressed in this paper by developing a strategic alignment model for KM. This model, which provides alternative strategic perspectives of alignment, is used to study a KM initiative at Buckman Laboratories. A Strategic Alignment Model for Knowledge Management
DNA barcoding of the mesic adapted striped mouse, Rhabdomys dilectus in the Eastern Cape and KwaZulu-Natal provinces of South Africa

Abstract South African small mammals are under-represented in DNA barcoding efforts, particularly from the eastern forested regions of the country. This study reports DNA barcoding of Rhabdomys taxa from previously unsampled parts of the Eastern Cape and KwaZulu-Natal provinces of South Africa. The complete mitochondrial DNA cytochrome oxidase I (COI) gene was sequenced for 101 Rhabdomys sp. individuals from 16 localities from all three main forest groups (coastal, mistbelt, and scarp forests). Molecular data were supplemented with external morphological measurements, including those deemed potential taxonomically diagnostic characters. Findings indicate the area to be inhabited solely by Rhabdomys dilectus chakae. Haplotypes distributed across the three forest groups were separated by shallow sequence divergences ranging from 0.001–0.015 (Kimura 2-parameter model) and displayed very little population genetic structure (FST= 0.071787). Morphological data revealed some regional metric differences in external morphology, but all the head-and-body to tail (HB: tail) ratios match that of R. d. chakae, and consequently, molecular and morphological data are congruent. These data confirm a range extension of R. d. chakae, supporting the utility of COI barcodes in the identification of small mammalian species.
Redesign of a Biomechanical Energy Regeneration-based Robotic Ankle Prosthesis using Indonesian Gait Data

In this research, the robotic ankle design from Arizona State University (ASU) known as SPARKy was redesigned to accommodate the specific needs of Indonesian people. Most active prosthetic legs are designed based on gait parameters for people from Western countries, which may differ for people from other cultures that have a different anthropometry and economic background. Indonesians have smaller actuating power characteristics compared to people from Western cultures due to their smaller average weight and body height. Thus, the applied design strategy took advantage of a biomechanical energy regeneration scheme to reduce the actuator input power requirement and the relatively smaller mechanical power of the typical Indonesian ankle to create a potentially affordable robotic ankle with a smaller actuator that meets the technical specifications. The specifications of the powered prosthetic ankle were determined through the same methods used by SPARKy. Only one low-level control system, to actuate normal walking, was designed and tested on a fully assembled robotic ankle. The test results indicated a promising low-level control, where the robotic ankle can follow the predetermined trajectory required to actuate normal walking based on Indonesian gait data.
Radial variability of fibrovascular bundle properties of salacca (Salacca zalacca) fronds cultivated on Turi Agrotourism in Yogyakarta, Indonesia

Abstract. Hakim L, Widyorini R, Nugroho WD, Prayitno TA. 2021. Radial variability of fibrovascular bundle properties of salacca (Salacca zalacca) fronds cultivated on Turi Agrotourism in Yogyakarta, Indonesia. Biodiversitas 22: 3594-3603. Fibrovascular bundles have properties variability not only based on species and varieties but also parts of species. This study, therefore, aims to characterize the FVB fundamental properties (anatomical, chemical, physical and mechanical) of Salacca zalacca (Gaertn.) Voss fronds, based on radial direction. The salacca fronds were divided into three parts, outer, middle as well as inner positions. Then the FVB's anatomical and physical properties were observed by light microscope and gravimetry analysis, respectively. Meanwhile, the variability of chemical and mechanical properties was investigated based on the ASTM standard. According to the results, the outer position has a higher variability of diameter, density, cellulose, lignin, and mechanical properties than the inner position, but has a lower hemicellulose value than the middle and inner position. Furthermore, the relationships between the anatomical, physical, chemical, and mechanical properties were discovered to form a pattern where increasing the mechanical properties is influenced by density and ratio vascular tissue area to total transverse area. Based on the results, the fibrovascular bundle of S. zalacca frond was concluded to possess anatomical, physical, chemical, and mechanical properties variability on the radial direction. There was a correlation between anatomical properties and mechanical properties.
The impact of plants offering cover on female students’ perception of danger in urban green spaces in crime hot spots

Urban parks and forests are important for wellbeing, but feelings of insecurity limit their usage. Removal of vegetation from hotspots of fear is sometimes recommended as a means of boosting safety. However, such actions should be approached with caution. One explanation, based on prospect-refuge theory, is that plants increase perceptions of danger because of their contribution to a setting’s effectiveness in concealing criminals. It is also believed that people do not like urban parks containing trees and shrubs that can act as hiding places because of the sense of danger that this vegetation evokes. To test this explanation, participants (female students) rated 57 photos of urban parks settings in terms of perceived danger, effectiveness of concealment, and landscape preference. In addition, the effectiveness of concealment in the photos was measured, assuming that the value of this variable is expressed by the percentage of the pixels occupied by trees and shrubs offering concealment in a photograph. Results confirmed that concealment and danger are strongly correlated. Mediation analysis confirmed that the impact of concealment on preferences can be explained by perceived danger. When danger was controlled, the efficiency of concealment had no influence on preferences.
High-Selectivity Reflectionless Unbalanced-to-Balanced Filtering Power Combiner

A high-selectivity reflectionless unbalanced-tobalanced (UTB) filtering power combiner is proposed. The proposed power combiner composes of two absorbing branches, two filtering sections, two transmission lines, a grounded resistor, and a phase inverter. Two transmission zeros respectively located at the lower and upper sides of the passband are achieved by the filtering sections, resulting in high selectivity. The input-port reflectionless response in the bandstop region is obtained by the absorbing branch. A 1.0-GHz UTB filtering power combiner is designed and fabricated. Finally, the measurement performances are given in this paper. The input-reflection absorptive bandwidth and transmission bandwidth are measured as 545 MHz and 132 MHz, respectively. The absorptive bandwidth is 4.12 times the transmission bandwidth.
TremorSense: Tremor Detection for Parkinson's Disease Using Convolutional Neural Network

Parkinson's Disease (PD) hand tremors are common symptoms in all stages of PD. PD tremors have a severe influence on patients' daily quality of life. Wearable technology can be used to help detect, quantify, and mitigate these PD tremors. Among the wearable technology, PD tremor detection is the primary step for further analysis and treatment using wearable devices. Some researchers have explored PD rest tremor detection. However, less research has been done concerning postural tremor and action tremor detection, which are difficult to classify only using frequency-domain features. In this paper, we propose TremorSense, a PD tremor detection system to classify Parkinson's Disease hand tremors. TremorSense utilizes accelerometers and gyroscopes as wearable sensors on patients' wrists to collect data from 30 PD patients. We develop the TremorSense Android application that connects the sensors via Bluetooth to save the data. Furthermore, we design an 8-Layer Convolutional Neural Network (CNN) to classify PD rest, postural, and action tremors. We evaluate the CNN model with self-evaluation, cross-evaluation and leave-one-out evaluation, and the accuracies for all three evaluations are greater than 94%.
“Go, Vote, and Tweet It”: Interactivity in Online Protest-Related Discussions About the 2014 Catalan Referendum for Independence

While studies abound that examine protest-related citizen communicative behaviors taking place online, there is still a limited understanding of the factors associated with social media users’ engagement in 2-way interactive exchanges about the issue of protest. Using discussion threads as the unit of analysis, this study looks at potential predictors associated with users’ engagement in interactive discussions in the context of the 2014 Catalan Referendum of Independence. Results show low overall levels of interactivity in discussions, with user status, media content sharing, negative emotion, and linguistic and ideological heterogeneity being related to lower interactivity levels. Findings are discussed within the framework of collective expressive modes of online citizen participation.