Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Green Technology in Transportation

The transportation industry, is the carrier of goods and passengers, it is undeniably one of the most important industries in the world. Global warming, environmental pollution, health consequences (physical, physiological, behavioral, spiritual), and greenhouse gas emissions are all problems that current transportation systems face. Urban traffic congestion is becoming more severe as the urbanization process accelerates, and the conflict is growing. Populace, resources, and the atmosphere are all becoming more important, according to the estimated data, all the road transportation is reliant on the oil as a source of transportation and uses about 90% of the oil. Green transport is a less polluting and environmentally sustainable form of transportation. Implementation of green transport system is beneficial not only for efficient utilization of street resources, reduced transportation jamming, lower energy expenditure, and improved air eminence, but too as a reappearance to the past. present paper identifies the cause and effects of conventional transportation sector on environment, importance of green technology, benefits and contribution of green transportation to flora and faunas. Further, in the present study various modes of green transportation approaches is been discussed.
Bayesian Joint Modelling of Disease Progression and Time to Death Event of HIV/AIDS Patients under ART Follow up at Shashemene Referral Hospital, Ethiopia

Longitudinal data and survival data frequently arise together in practice. Joint modelling refers to the statistical analysis of the longitudinal and survival data while taking account of any association between the repeated measurement and time to event outcomes. The population of our study is all HIV/AIDS patients who were under the follow up of ART at Shashemene referral hospital from January, 2006 to December, 2012. The purpose of this study is to develop separate and joint statistical models in Bayesian framework for longitudinal and survival data of HIV/AIDS patients under ART follow up at Shashemene referral hospital. The WinBUGS software was used to produce MCMC samples from the posterior distribution of the parameters of a desired model. The results of both the separate and joint analyses are consistent. The overall performance of separate model in terms of model goodness of fit is better than joint model. The joint model M9 is somehow the simpler (less complex) model as compared to the separate model for this study. Both in joint and separate model linear and quadratic time, sex and tobacco addiction are statistically significant at 0.05 level of significance. Out of the covariates included in the survival submodel of the joint model, knowledge of ART and condom use are found to be significantly associated with time to death at 0.05 level of significance. Also, the results show that the patients’ survival in the ART treatment is not significantly associated with patient specific CD4 fluctuations.
Phenolic compounds and in vitro antioxidant activity of six accessions of mashua (Tropaeolum tuberosum R. & P.) from Puno Region, Peru

Mashua (Tropaeolum tuberosum R. & P.) is an Andean crop of high nutritional value and medicinal properties, which presents a great diversity in morphology and color. The aim of the study was to evaluate the content of phenolic compounds and in vitro antioxidant activity of the most economically important mashua accessions in the Puno Region, Peru. Six accessions of mashua (three purplecolored and three yellow-colored) were evaluated. The content of total polyphenols, total flavonoids and identification of phenolic compounds was determined by the Folin-Ciocalteu assay, aluminum chloride colorimetric method and HPLC-DAD, respectively. In vitro antioxidant activity was evaluated using the FRAP and DPPH assays. In general, the purple-colored mashua had a significantly higher content of total polyphenols, total flavonoids, and in vitro antioxidant activity compared to the yellowcolored mashua; being the Tt-23 accession purple-colored (peel/pulp, purple/purple), which presented a significantly higher content of phenolic compounds and in vitro antioxidant activity compared to the other accessions evaluated (P<0.05). Furthermore, a significant correlation was observed between FRAP and DPPH activities with the total content of polyphenols and flavonoids (P<0.01), as well as between FRAP activity and the caffeic acid and rutin levels (P<0.05). These results suggest that purple-colored mashua, particularly the Tt-23 accession (peel/pulp, purple/purple), has better nutraceutical and antioxidant properties due to its higher content of phenolic compounds.
Site-specific millimeter-wave compressive channel estimation algorithms with hybrid MIMO architectures

In this paper, we present and compare three novel model-cum-data-driven channel estimation procedures in a millimeter-wave Multi-Input Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) wireless communication system. The transceivers employ a hybrid analog-digital architecture. We adapt techniques from a wide range of signal processing methods, such as detection and estimation theories, compressed sensing, and Bayesian inference, to learn the unknown virtual beamspace domain dictionary, as well as the delay-and-beamspace sparse channel. We train the model-based algorithms with a site-specific training dataset generated using a realistic ray tracing-based wireless channel simulation tool. We assess the performance of the proposed channel estimation algorithms with the same site's test data. We benchmark the performance of our novel procedures in terms of normalized mean squared error against an existing fast greedy method and empirically show that model-based approaches combined with data-driven customization unanimously outperform the state-of-the-art techniques by a large margin. The proposed algorithms were selected as the top three solutions in the "ML5G-PHY Channel Estimation Global Challenge 2020" organized by the International Telecommunication Union.
Nanoparticles in traumatic spinal cord injury: therapy and diagnosis

Nanotechnology has been previously employed for constructing drug delivery vehicles, biosensors, solar cells, lubricants and as antimicrobial agents. The advancement in synthesis procedure makes it possible to formulate nanoparticles (NPs) with precise control over physico-chemical and optical properties that are desired for specific clinical or biological applications. The surface modification technology has further added impetus to the specific applications of NPs by providing them with desirable characteristics. Hence, nanotechnology is of paramount importance in numerous biomedical and industrial applications due to their biocompatibility and stability even in harsh environments. Traumatic spinal cord injuries (TSCIs) are one of the major traumatic injuries that are commonly associated with severe consequences to the patient that may reach to the point of paralysis. Several processes occurring at a biochemical level which exacerbate the injury may be targeted using nanotechnology. This review discusses possible nanotechnology-based approaches for the diagnosis and therapy of TSCI, which have a bright future in clinical practice.
Audio-Visual Speech Emotion Recognition by Disentangling Emotion and Identity Attributes

In this paper, we propose an audio-visual speech emotion recognition (AV-SER) that can suppress the disturbance from an identity attribute by disentangling an emotion attribute and an identity one. We developed a model that ﬁrst disentangles both attributes for each modality. In order to achieve the disentangle-ment, we introduce a co-attention module to our model. Our model disentangles the emotion attribute by giving the identity attribute as conditional features to the module. Conversely, the identity attribute is also obtained with the emotion attribute as a condition. Our model then makes a prediction for each attribute from these disentangled features by considering both modalities. In addition, to ensure the disentanglement capacity of our model, we train the model with an identiﬁcation task as the auxiliary task and an SER task as the primary task alternately, and we update only the part of parameters responsible for each task. The experimental result shows the effectiveness of our method with the wild CMU-MOSEI dataset.
A CROSS DOMAIN APPROACH TO ANALYSE SENTIMENTS FROM OPINIONS ON SOCIAL MEDIA

: Data is generated from versatile sources and in large quantities. The rate of data generation is increasing with time. This data is related to a large range of fields. Also this data contains hidden information which can be extracted. This information can prove beneficial to multiple organizations and institutions. Data from Social Networks mostly contains opinions of general public. Twitter is one such application where people express their opinions regarding every issue, development, product etc. In this paper we have tried to To store and organize unstructured datasets from twitter into HDFS of Hadoop using Flume and extract data from HDFS through Apache Hive. The design and implement hybrid classification algorithm comprising of Naïve bayes based on probability and Decision Tree based on decision rules is done and along with it analysis and comparison of performance of the proposed approach based on accuracy with the existing naïve bayes.
Friend Recommendation System for Social Network a Semantic Approach

: Existing social networking services recommend friends to users based on their social graphs, which may not be the most appropriate to reflect a user’s preferences on friend selection in material life.In this report, we present Friendbook, a novel semantic-based friend recommendation system for social networks, which recommends friends to users based on their lifestyles instead of social graphs. By advantage of sensor-rich smartphones, Friendbook discovers life styles of users from user-centric sensor data, measures the similarity of life styles between users, and recommends friends to users if their lifestyles have high similarity. Inspired by text mining, we model a user’s daily life as life documents, from which his/her life styles are taken out by using the Latent Dirichlet Allocation algorithm. We further propose a similarity metric to evaluate the similarity of life styles between users, and calculate users’ impact in terms of lifestyles with a friend-matching graph. Upon getting a request, Friendbook returns a list of people with highest recommendation scores to the query user.Finally, Friendbook integrates a feedback mechanism to further amend the recommendation accuracy. We have implemented Friend book on the Android-based smartphones, and assessed its performance on both small-scale experiments and large-scale simulations. The outcomes indicate that the recommendations accurately reflect the preferences of users in choosing allies.
Re-Examining IT Investments: Measuring Long-Term Payback in the E-Commerce Era

Traditional return on investment (ROI) metrics have been used in organisations to evaluate the feasibility of investments in information technology (IT) during the pre electronic-commerce era. However, with the advent of e-commerce, some organisations are still utilising this formal measure while others are searching for alternative methods that will prove to be better instruments. The problem with ROI methods lies in the lack of attention paid to internal and external changes in organisations and the changing role of IT. This paper compares the key underlying factors that define pre and post e-commerce IT eras, and argues that many of the IT investment metrics still in use today are derived from the pre e-commerce era of controllable procedures, products and customer bases. It proposes that only a closer study of the strategic organisational changes brought about by e-commerce and carried out from a long term perspective will lead to the development of more pertinent methods to evaluate IT. An investment banking group case study is presented to support this view and demonstrate the importance of adopting a strategic long-term outlook in evaluating e-commerce investments.
Mobile Computational Vision System in the Identification of White Quinoa Quality

Quinoa is currently in high commercial demand due to its large benefits and vitamin components. The process of selecting this grain is mostly done manually, being prone to errors, because many times this work is subject to fatigue and to subjective criteria of those in charge, causing the quality to decrease due to not making an adequate selection subject to standards. For this reason, a study focused on determining the influence of the computer vision system for the identification of the quality of white quinoa, based on the standards and techniques for the development of a computer vision system through the phases of PDI. Managing to determine the influence of this, concluding that it is possible to ensure the implementation of robust systems to solve problems by applying computer vision thanks to technological advances for mobile devices. Keywords—Computer vision system; quinoa quality; digital image processing
DEVELOPING A TOTAL BUILDING PERFORMANCE INDEX FOR ASSESSING OFFICE BUILDINGS IN NIGERIA

Building performance is a function of a number of variables each of which is important to analyse concurrently when conducting a POE study. The development of framework for assessing buildings is significant as it will provide an evaluation tool for ensuring sustainable buildings. This study developed an index for assessing the overall performance of office buildings in Nigeria. A Total of 51 professionals in the built environment were surveyed. The data obtained were analysed using content analysis technique, pair wise comparison (one sample t-test) and regression analysis. The results showed that; the performance criteria which are relevant to the performance of office building in order of their importance were building integrity (54.54), indoor air quality (53.69), safety and security (64.04), thermal (46.77), spatial (7.27%), visual (44.01), spatial (43.33) and acoustic performance (43.62); priority placed by individual professional, architects rated safety and security and building integrity (18) most important and acoustic least (9) important, builders rated IAQ and visual performance (20) most important and building integrity (8) least important, estate surveyors rated safety (21) and building integrity (17) performance most important and acoustic performance (7) least important, mechanical engineers rated safety (22) and building integrity (0) performance most important and acoustic performance (7) least important. A regression model based on the TBP criteria identified was developed (TBP Index = 13.36ð+12.57ŋ+12.46Ɣ+15.34ω+12.38ɸ+15.58φ+18.30ψ). It was concluded that safety and security was rated most important of all the performance mandates, followed by indoor air quality, building integrity, thermal performance, spatial performance, visual performance and acoustic performance.
Effect of solvent types on the antioxidant activity and total flavonoids of some Bangladeshi legumes

In this study, an attempt was made to estimate the antioxidant activity of some popular Bangladeshi legumes by employing DPPH radical scavenging assay, total phenolic content (TPC), and ferric reducing antioxidant assay (FRAP). The extraction efficiency and total flavonoid content (TFC) of hyacinth bean (Lablab niger), kidney bean (Phaseolus vulgaris), black gram (Vigna radiate), mung bean (Vigna mungo), and green pea (Pisum sativam) by different solvents were also examined. Extraction was done using 80% acetone, ethanol, and methanol as solvent. The maximum and minimum DPPH scavenging activity was shown by mung bean (27.67±1.53%) and Hyacinth bean (4.33±1.53%), respectively using ethanol as solvent. The highest and lowest FRAP value was recorded 89.60±0.80 μg AAE/mL for green pea and 35.11±1.39 μg AAE/mL for mung bean, respectively with ethanol solvent. For TPC, green pea with ethanol solvent showed the highest value (1045.92±21.30 mg GAE/100 g), and mung bean with ethanol solvent exhibited the lowest value (415.92±1.44 mg GAE/100 g). For TFC, black gram with ethanol solvent exhibited the highest value (342.21±3.05 mg QE/100 g), while mung bean with acetone solvent exhibited the lowest value (77.38±0.80 mg QE/100 g).
Final Author Comments-responses to Reviewer 2 comments

Reviewer 2 commented generally that the breaking mechanism of fast ice was not discussed adequately in the manuscript. As noted in our Final Author Comments on Reviewer 1’s comments, we agree with both reviewers that further discussion of fast ice break out mechanisms would be valuable additions to the manuscript and we will look to include an expanded discussion on breakout mechanisms in the revised manuscript. We have responded to the general comments of both reviewers in our Final Author Comments on Reviewer 1’s comments, and included our responses here for completeness.
Hardware SYN Attack Protection For High Performance Load Balancers

SYN flooding is a simple and effective denial-of-service attack, in which an attacker sends many SYN requests to a target's server in an attempt to consume server resources and make it unresponsive to legitimate traffic. While SYN attacks have traditionally targeted web servers, they are also known to be very harmful to intermediate cloud devices, and in particular to stateful load balancers (LBs). We propose LB schemes that guarantee high throughput of one million connections per second, while supporting a high pool update rate without breaking connections, and fighting against a high rate SYN attack, of up to 10 million fake SYNs per second.
CUNI-MTIR at COVID-19 MLIA @ Eval Task 2

This paper describes the participation of CUNI-MTIR team in the COVID-19 MILA Multilingual Semantic Search task. We participate in the monolingual and the bilingual task and its subtasks. In both cases, we use the English document collection. As for queries, we use the English for the monolingual system, and queries in French, German, Spanish and Swedish for the bilingual task. We follow query-translation approach to reduce the bilingual search task into a monolingual one, and we adopt neural machine translation systems that are deployed for the purpose of this task for the translation process. We also study the effect of the morphological analysis (lemmatisation) of the documents and queries on the recall performance of the retrieval.
miR-515-5p inhibits the proliferation, migration and invasion of human breast cancer cells by targeting CBX4

microRNA (miR)-515-5p has been previously suggested to function as a tumor suppressor in various types of human cancer. Therefore, the role of miR-515-5p in breast cancer (BC) was explored in the present study. A series of assays were performed to study the function of miR-515-p in BC cells, including Cell Counting Kit-8, TUNEL, flow cytometric and colony formation to detect cell viability and apoptosis, wound healing and Transwell assays to measure cell motility. In addition, reverse transcription quantitative PCR and western blot analysis were used to assess miR-515-5p, CBX4, Cox-2, MMP2, MMP9, CDK2, p21 and Cyclin D1 respectively. Bioinformatics and dual-luciferase reporter assays were used to analyze the target genes of miR-515-5p, which confirmed the direct binding between miR-515-5p and polycomb chromobox 4 (CBX4). It was found that the expression of miR-515-5p is lower in BC cells compared with that in normal breast cells (MCF10A). Overexpression of miR-515-5p using the miR-515 mimic was found to reduce cell viability, facilitate cell apoptosis, inhibit cell proliferation and arrest cell cycle progressio at G1 phase. In addition, miR-515-5p overexpression could inhibit cell migration and invasion, whilst decreasing the expression levels of prostaglandin-endoperoxide synthase 2, MMP2 and MMP9 proteins. In addition, miR-515-5p overexpression could reduce the expression levels of CBX4 in MCF7 and ZR-75-30 cells. By contrast, overexpression of CBX4 reversed the effects of the miR-515-5p mimic transfection on cell proliferation, migration and invasion in MCF7 and ZR-75-30 cells. In combination, these results suggest that miR-515-5p inhibits BC cell proliferation, migration and invasion by directly targeting CBX4.
Modeling Dialectal Variation for Swiss German Automatic Speech Recognition

We describe a speech recognition system for Swiss German, a dialectal spoken language in German-speaking Switzer-land. Swiss German has no standard orthography, with a signiﬁcant variation in its written form. To alleviate the uncertainty associated with this variability, we automatically generate a lexicon from which multiple written forms of a given word in any dialect can be generated. The lexicon is built from a small (incomplete) handcrafted lexicon designed by linguistic experts and contains forms of common words in various Swiss German dialects. We exploit the powerful speech representation of self-supervised acoustic pre-training (wav2vec) to address the low-resource nature of the spoken dialects. The proposed approach results in an overall relative improvement of 9% word error rate compared to one based on an expert-generated lexicon for our TV Box voice assistant application.
Cluster Headache Pathophysiology—A Disorder of Network Excitability?

Patients’ accounts of cluster headache attacks, ictal restlessness, and electrophysiological studies suggest that the pathophysiology involves Aδ-fibre nociceptors and the network processing their input. Continuous activity of the trigeminal autonomic reflex throughout the in-bout period results in central sensitization of these networks in many patients. It is likely that several factors force circadian rhythmicity upon the disease. In addition to sensitization, circadian changes in pain perception and autonomic innervation might influence the excitability of the trigeminal cervical complex. Summation of several factors influencing pain perception might render neurons vulnerable to spontaneous depolarization, particularly at the beginning of rapid drops of the pain threshold (“summation headache”). In light of studies suggesting an impairment of short-term synaptic plasticity in CH patients, we suggest that the physiologic basis of CH attacks might be network overactivity—similarly to epileptic seizures. Case reports documenting cluster-like attacks support the idea of distinct factors being transiently able to induce attacks and being relevant in the pathophysiology of the disorder. A sustained and recurring proneness to attacks likely requires changes in the activity of other structures among which the hypothalamus is the most probable candidate.
Abstract. Despite the success of anti‐HER2 therapy in patients with breast cancer with HER2 amplification or HER2 overexpression, the results of clinical trials on anti‐HER2

Despite the success of anti‐HER2 therapy in patients with breast cancer with HER2 amplification or HER2 overexpression, the results of clinical trials on anti‐HER2 therapy for lung cancer have not been satisfactory. The aim of the present study was to report a case of a non‐smoker, female patient diagnosed with stage IIIA lung adenocarcinoma harboring HER2 amplification. The disease progressed despite surgery and multiple lines of chemotherapy, plus trastuzumab or lapatinib. The pan‐ErbB inhibitor pyrotinib (400 mg/day) was commenced as a fourth‐line regimen, and the patient achieved complete response with a time to progression (TTP) of 6 months. After the lung adenocarcinoma progressed, pyrotinib was continued, along with anlotinib and nivolumab. The patient achieved stable disease (SD) status with another 6 months of TTP. The overall survival of the patient was 28 months. Therefore, the present case suggests that the development of novel drugs may provide new and effective therapeutic regimens for lung cancer with HER2 amplification.