Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comprehensive Review of the Different Methods and Materials for the Construction of MFCs and their Effect on the Performance of MFC

The use of fossil fuels has increased exponentially to meet the increasing global energy demand caused by rapid industrialization and urbanization. The continuous use of fossil fuels leads to its depletion and environmental degradation, which leads to a global focus on renewable energies. Microbial Fuel Cell (MFC) is a relatively recent concept in the quest for renewable energy sources. It is steadily gaining traction as a viable "green and renewable" energy source. An MFC is an electro-biochemical system that exploits the oxidative ability of microorganisms especially bacteria to produce bioelectricity from organic waste matter. Organic-rich waste streams are being regarded as potential substrates for bio-energy production using MFC technology. MFC technology is an interesting and rapidly evolving interdisciplinary field that needs contributions from a wide range of disciplines, including microbiology, electrochemistry, electronics, and environmental engineering. The technology is gaining attention and is becoming increasingly important in the field of renewable energy. In recent decades a lot of the work has been done primarily to minimize electrode material costs and to configure MFCs so that current densities are maximized. In this paper, we present a comprehensive review of the performance of MFC. A critical analysis of different electrode materials has been done for dual-chamber MFC and single chamber MFC. We have presented a comparative analysis for different electrode materials. Various advancements from pure electrode material to the composite material for anode and cathode and their impact on output power density have been discussed. The analysis has been focused on bio-electricity production. We tried to analyze the factors affecting the change in the output power density of MFC. We also focus to obtain optimized parameters for high electricity production. The review also highlights the use of MFC technology in wastewater treatment along with bio-electricity
SOCIAL SUPPORT, LONELINESS AND PERCEIVED STRESS IN GERIATRIC PATIENTS OF DEPRESSION

Background: Ageing is a universal process which is considered as associated with declining health status. With a rapidly aging society, Geriatric Mental Health is becoming an important public health concern. Depression is a common cause of distress among older adults that leads to physical, mental and social dysfunction and significantly decreases quality of life. Objective: This study aimed to examine the Social Support, Loneliness and Perceived Stress in Geriatric Patients of Depression. Methodology: It was a cross-sectional and comparative study in nature, in which 30 geriatric (Age = 60 or above) patients with Depression were compared with 30 geriatric Non-Depressive of same age group on Social Support, Loneliness and Perceived Stress. Measures: Socio-demographic details and clinical details were recorded with the help of socio-demographic and clinical data sheets designed separately for both groups. Thereafter MMSE was administered. University of California Los Angeles Loneliness Scale, Perceived Stress Scale, Social Support Questionnaire, Geriatric Depression Scale and General Health Questionnaire (only on control group) were administered on those who fulfilled the inclusion criteria after screening by MMSE to rule out any neuro-cognitive disorders. Results: No significant difference between two groups on various sociodemographic variables such as education, domicile and family background etc was found as they were comparable groups. It was analyzed that Depression co-related positively with Loneliness and Perceived Stress whereas Social Support is inversely correlated with Depression. Statistically significant differences were found in Social Support, Loneliness and Perceived Stress between Depressive and Non-Depressive groups. Conclusion: Lack of Social Support, Loneliness and high level of Perceived Stress are the risk factor for Geriatric Depression.
Extractive Text Summarization Techniques

1B.Tech. student, Dept. of Computer Science and Engineering, Acropolis Institute of Technology & Research, Indore, (M.P), India 2Senior Assistant Professor, Dept. of Computer Science and Engineering, Acropolis Institute of Technology & Research, Indore, (M.P), India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract – Text summarization is a process of retrieving crucial information in a concise and precise manner from original and voluminous texts while maintaining the overall meaning of the text. Data is growing exponentially day by day and so the textual data, which may be structured or unstructured, and the best way to use them is by skimming the results. We can access an immense amount of information, however, most of it is redundant, trivial, and may not deliver intended results. Using text summarization techniques can amplify the readability of text documents, reduce the investment of time in scrutinizing the information, and can increase the amount of information to be inserted in a particular domain.
DFT calculation of intrinsic properties of magnetically hard phase L1 0 FePt

Due to its strong magnetocrystalline anisotropy, FePt L1 0 phase is considered as a promising magnetic recording media material. Although the magnetic properties of this phase have already been analyzed many times using density functional theory (DFT), we decided to study it again, emphasizing on full potential methods, including spin-polarized relativistic Korringa-Kohn-Rostoker (SPR-KKR) and full-potential local-orbital (FPLO) scheme. In addition to the determination of exact values of the magnetocrystalline anisotropy constants K 1 and K 2 , the magnetic moments, the Curie temperature, and the magnetostriction coeﬃcient, we focused on the investigation of the magnetocrystalline anisotropy energy (MAE) dependence on the magnetic moment values using the fully relativistic ﬁxed spin moment (FSM) method with various exchange-correlation potentials. We present nearly identical MAE( m ) curves near the equilibrium point, along with diﬀerent equilibrium values of MAE and magnetic moments. For a magnetic moment reduced by about 10%, we determined a theoretical MAE maximum in the ground state (0 K) equal to about 20.3 MJ m − 3 and independent of the choice of the exchange-correlation potential form. These calculations allow us to understand the discrepancies between the previous MAE results for diﬀerent exchange-correlation potentials.
Sentiment Analysis on Customer's Comments of Myanmar Cosmetic Products

Today, people don’t necessarily go outside for buying their daily use products. There are many doorto-door delivery services and online shopping to fulfill their needs. However, the expectation of the products and the reality will not be the same every time. In such cases, honest reviews comments of real customers will help to avoid buying poor quality products. This paper emphasizes classifying the customer’s sentiment on Myanmar cosmetic products and we identified three sentiment polarities: positive, negative, and neutral. We collected and annotated the customer’s comments from Facebook pages of the most popular cosmetic products in Myanmar. The experiment is performed by Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) model on the customer’s comments datasets. According to the experiment, the LSTM model performs better than the RNN model. The average accuracy of the LSTM model is 91% and the RNN model is 89%.
A spatial-temporal Deep Learning Framework for Network-wide Bus Passenger Flow prediction

1 Bus system is one of the most important components of an integrated public transit system that 2 shares a large proportion of daily trips. The accurate short-term bus passenger flow prediction is of 3 great significance for public agencies and operators to ensure the quality and reliability of the ser4 vices. In this paper, we propose a novel end-to-end deep learning framework that aims at making 5 multi-step collective prediction for different types of bus passenger flow (boarding and alighting) 6 in a network-wide region level. The proposed framework has a deep structure comprising stacks 7 of spatial-temporal blocks, which can effectively learn long-range spatial-temporal dependencies. 8 The large quantities of real-world data from Singapore are used to evaluate the proposed model, 9 according to which we find that our proposed model is capable of making reliable prediction and 10 outperforms a set of commonly used baselines. 11 12
Review of Secure Software Development in Various Agile Models

Software whether application or system are most valuable assets of a computer system. Hardware of computer is also dependent upon software. Initially software requirements, size, complexities and operating environment were limited. There are multiple development methodologies such as waterfall, spiral, rational unified process and now the most common agile. Scrum, XP, DSDM, FDD, and Crystal are some of commonly used agile software development methodologies being used for development of software in increments. Agile facilitates quick releases, iterations and customer involvement. Weak coding practices are major cause of software vulnerabilities. Secure programming rules should be followed for writing programs in order to manage security. Interactive Static Analysis integrates static analysis in Integrated Development Environment (IDE) it assists and indicate programmer such coding mistakes.
Survey of Spatial Audio Enhancement for Digital Hearing Aid

A multi microphone array technique for hearing aid noise reduction is described. This study evaluates a spatial-filtering algorithm as a method to improve speech reception for monaural and binaural hearing impaired users in reverberant environments with multiple noise sources. The system has to filter sounds using phase differences between two microphones situated some distance apart in a behind-the-ear hearing-aid capsule. The approach is to linearly combine microphone signals after amplitude scaling and phase shifting. This approach is linear and time-invariant and can be used to generate known directional responses. Such approaches are generally referred to as beamforming algorithms. Beamformers can be implemented in analog, multiport, microphone circuitry to produce directional microphones. These techniques help to filter sounds using phase differences between microphones and provide improvements in speech signal across listening conditions compared with the omnidirectional response also spatial filtering can improve speech reception for hearing impaired users even in highly reverberant conditions with multiple noise sources.
Proposal for the Volition Subcategories of the ARCS-V Model

In this paper, the authors propose and discuss the significance of subcategories for Volition in the ARCS-V model. This model is an expansion of the ARCS model developed by John M. Keller. Three subcategories for the element of Attention, Relevance, Confidence and Satisfaction that provide hints for instructors and learners were identified in the ARCS model, but subcategories for Volition of the ARCS-V model have not been identified. Through volition-related research reviews, the authors identified keywords to classify subcategories for Volition for the ARCS-V model. The authors discuss whether the proposed subcategories can make the ARCS-V model more persuasive in the volitional phase of learning. The implications of the proposed subcategories are also discussed.
FINGERPRINT IMAGE ENHANCEMENT BASED ON THE GABOR FILTER

Fingerprints were one of the first forms of biometric authentication to be used for law enforcement and civilian applications. Contrary to popular belief, despite decades of research in fingerprints, reliable fingerprint recognition is an open problem. Extracting features out of poor quality prints is the most challenging problem faced in this area. So it is essential to enhance the prints prior to feature extraction. This paper proposes an approach for fingerprint image enhancement based on the Gabor Filter. Ridge orientation, one of the important parameters of the filter, is estimated using the Sobel operator. But, the estimation of ridge frequency, which is another important parameter, is eliminated by giving a fixed value that leads to a fast enhancement process.
Secure IoT Based on Blockchain: Quantitive Evaluation and Analysis of the Correlation Between Block Mining Time and Blockchain Efficiency

This research study aims to quantitively analyze the correlation between block mining time and blockchain efficiency with the integrity and scalability aspects under different parameters. The results showed that, hash difficulty value has strongest positive relationship with block mining time, while the data length has weakest positive correlation. Also, this study shows that, block mining time has correlation with the data length, number of blocks, and hash difficulty, while its efficiency corollate only with the hash difficulty.
A Neural Probabilistic Language Model for Joint Segmentation and POS tagging

Myanmar Language being morphologically rich and complex language, morphological analysis is an essential preprocessing phrase for effective and efficient Myanmar language processing tasks and information retrieval. As a part of Myanmar Language Analysis project, a language model that can represent the morphological feature based on the recurrent neural network (RNN) is developed. Two other models, tri-gram with KN and baseline model using the current available systems are also developed. The language models are trained and tested their performance in segmentation and tagging using three different testing
Hardware Aware Sparsity Generation for Convolutional Neural Networks

Weight sparsity has gained a lot of attention as a compression method in recent years with the increasing demand of hardware containing sparse accelerators. Among all the methods of weight sparsity, AutoML leads to the best performance in terms of compression ratio and accuracy. However, the compression ratio cannot guarantee such network to perform the best on target hardware. Therefore, in this work we introduce hardware aware method of weight sparsity targeting optimal performance on the given hardware. Using our method, ResNets and MobileNetv2 can be reduced to 45% and 70% of original cycles respectively with almost no Top 1 accuracy loss which the other weight sparsity methods cannot achieve. Our work also bring insights of sparse weight distribution on hardware which contains sparse accelerators.
The Influence of Brand Communication, Brand Image, and Brand Trust on Brand Loyalty At University In Jakarta

Institutions in the education industry, including higher educations, need to have the right strategy in creating a brand with the appropriate quality. Besides, universities need to have different values with the high quality of products and services. An institution such as a university must be able to communicate its brand-related products well to consumers. Therefore this study aims to see the effect of brand communication, brand image, and brand trust on brand loyalty at the university in Jakarta. The sample of this study was 210 university students in Jakarta. This research is deductive. Data were collected using a questionnaire. The analytical method used is the Structural Equation Model (SEM). The results showed that: Firstly, there is an influence between brand communication on brand image. Secondly, there is an influence of brand communication on brand trust. Thirdly, there is an influence between brand image and brand trust. Fourth, there is an influence between the brand image on brand loyalty.
UAV Swarm Co-Ordination and Control Using Grossberg Neural Network

A UAV swarm (Swarm) has multiple unmanned aerial vehicles (UAV) working in synchronization towards achieving a unified/ universal task. Swarm Co-ordination, primarily deals with communicating with each individual UAV independently from the Ground Control Station (GCS) and negotiation based [8] information exchange between UAVs themselves. The most common type of flight formations are behavioural formations. Leader – follower formation types are the most closely associated with hierarchical class schemes. In the Leader – Follower formation, it is enough to specify a path for the leader to fly as in order to dictate the path taken by formation. The architecture of a system supporting a hierarchical Leader/follower formation scheme for Swarm of Quad copters. One Quad copter acts as a leader, while other acts as follower/ (s).
Application of Aloe vera gel and olive oil coatings to enhance fruit quality and shelf-life of ber (Ziziphus mauritiana L.)

Ber (Zizyphus maritiana Lamk) is an important tropical fruit. Ber fruit is known as “fruit of poor” because of low price in the market. This work was planned to evaluate Aloe vera gel and olive oil edible coating to enhance its shelf life and minimize post-harvest losses. The treatments included were T1= (control), T2= Olive oil (2%), T3= Olive oil (2.5%), T4= Olive oil (3%), T5 = Aloe vera gel (2%), T6 = Aloe vera gel (2.5%) and T7= Aloe vera gel (3%). Physico-chemical parameters of fruits were analyzed and recorded 12 day of storage. The study revealed that both olive oil and Aloe vera gel coatings were effective in maintaining quality of Ber fruit during storage period of 12 days. Minimum physiological weight loss, lesser loss in acid contents were observed in Aloe vera gel treated fruits along with maximum color retention compared to uncoated fruits. Coatings delayed ripening. Ascorbic acid loss and decay percentage were reduced by using different concentrations of olive oil and Aloe vera gel. Based on results deduced from the present study, it is concluded that application of Aloe vera gel was at par with olive oil coating but olive oil 3% and Aloe vera 3% proved best so, these coatings could be applied to enhance fruit shelf life and quality.
Research Article: Comparison of free and nano-encapsulated Safran (Crocus sativus L.) petal extract effects on some quality indexes of rainbow trout (Oncorhynchus mykiss) fillets

Fish as a main source of omega-3 and protein is widely consumed across the world. However, fish muscle is susceptible to putrefaction during storage. The aims of this study were to compare the effect of free and nano capsulated saffron petal extract on (bio) chemical, microbial and sensory properties of rainbow-trout fillet. Free saffronpetal extract (FSPE) and its nano capsulate (NSPE) were prepared by enzymatichydrolysis and coating with the core (FSPE), wall (50:50 maltodextrin/whey-protein concentrates MD/WPC) ratio of 1:4 respectively. The fillets were soaked into three solutions of FSPE and NSPE at 10% w/v as well as ionized water (control), dried with ambient-air, packed in aerobic condition and polyethylene bags and kept in refrigerator (15-day at 4±1oC). Scanning-electron microscopy and Fourier-transform infra-red spectroscopy of NSPE confirmed the successful coating of particles and interactions between the FSPE and MD/WPC. The total-viable and psychrophilic bacteria-count of samples treated with saffron-petal extract was significantly lower than those of control samples. The difference between NSPE and FSPE samples was not significant (p>0.05). The lowest thiobarbituric-acid reactive substances (TBARS) and total-volatile basic nitrogen (TVB-N) value obtained in NSPE samples was 1.44 mg MDA/kg and 16.44 mgN2/100g after 9 days at 4oC storage (p<0.05). The best sensory score was obtained for NSPE samples. The shelf-life of control fish was 5-8 days, while this time for NSPE and FSPE samples were 9-13 and 8-13 respectively. Overall, encapsulation of free saffron petal extract with maltodextrin/whey prr neco nrcnnc oc no eto onnrnnnccncotrooe toeetenoooor nn ercoctcect onennencoocc conenorieco degradation.
Implications of the fretting phenomenon on the stability of the total hip prosthesis-A review

The paper presents a review of three of the studies undertaken by the authors regarding the implications of the fretting phenomenon that can manifest in a total hip prosthesis, on its stability. Experimental investigations have been made on Ti6Al4V / UHMWPE prostheses with cemented stem Failure to fix the cemented stem of the prosthesis occurred at 2450000 cycles, after which visual inspection was done and photographic recordings were made. Two different conditions were considered for the normal force N between the contact surfaces: constant or proportional to the axial force P. Determination of the stresses induced in the fretting process required the preliminary characterization of the relationship between the friction force F and the axial force P produced during the loading cycles. Hereafter, experimental studies were carried out to detect the early stage when fretting wear of the Ti-6Al-4V alloy, used for the hip prostheses, appears. Wear is a critical aspect for estimating the fretting fatigue. It was taken into account the unanimous finding that the surface roughness of the testing sample has a significant influence on the occurrence and evolution of the fretting scar. Studies were realized on samples of special shape presented in this paper.
Atmospheric mineral dust and its role in ice formation

Water can supercool below -350C without the presence of Ice Nucleating Particles (INP’s) which makes INPs important for the development of mixed phase clouds. Mineral dust is known to be a substantial source of active INPs in the atmosphere. At present our ability to accurately predict the global distribution of atmospheric mineral dust INP is limited by both a fundamental understanding of which specific components nucleate ice, how efficiently they do so and how they are processed or altered while in the atmosphere, as well as the lack of instrumentation to reliably and routinely quantify INP concentrations in the atmosphere. In my PhD project I have already begun to address questions around which feldspars are most important at nucleating ice and in the longer term I propose to build a new instrument to make direct field measurements to increase datasets for global distributions of INP. A major topic of this essay is my investigation of the role of feldspar composition and structure on its ice nucleating efficiency. We find that alkali feldspars are the most active group of feldspars, with plagioclases being the least active. There is also a wide range of activities within each group and the stability of active sites on each feldspar can vary. I also briefly discuss the concept for the new field instrument and where I hope to measure INP concentrations. Alex Harrison January 2016