Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversity of the edible fishes of the Lagos Lagoon, Nigeria and the public health concerns based on their Lead (Pb) content

In this study, a total of eighteen fish species were recorded in the Lagos Lagoon, Nigeria during a one year survey. Among the animals species recorded, the following, Galeoidesdecadactylus, Dentex gibbosus, Elops lacerta, Scomber japonicus, Ethmalosa fimbriata, Lutjanus agennes, Caranx senegallus, Callinectes amnicola, Paeneus notialis and Mytilus edulis were considered to be abundant in the Lagos lagoon based on the frequency of occurrence in fishermen catches. The analysis of the lead content in muscles of the edible fisheries revealed that the animals accumulated measurable quantity of lead in the edible parts. The level of lead detected in most (12 out of 18 species) of the fisheries species were found to be lower than the daily allowable concentration of 2.0 µg/g standard recommended by the World Health Organisation (WHO). Fishes species with high level of lead in their edible parts include Senegal jack, C. senegallus (2.188 µg/g), Bobo croaker, Pseudotolithus elongatus (2.024 µg/g), Cassava croaker, Pseudotolithus senegalensis (3.157 µg/g), crayfish, Penaeus notialis (25.46µg/g), edible mussel, Mytilus edulis (17.69 µg/g) and crab,Callinectes amnicola (10.19 µg/g). The mean levels of lead in Mytilus edulis, Penaeus notialis, and Callinectes amnicola collected from the Lagos lagoon were about 8 to 24 times higher than the WHO daily allowable standards for lead in sea foods and are therefore unsafe for human consumption. The need for regular monitoring of the levels of metals and other contaminants in edible fisheries resources and collaboration between environmental, health and food agencies to avert human tragedies due to lead accumulation are discussed. Key words: Bioaccumulation, lead, industrial pollution, aquatic ecosystem, biomonitoring.
Tracing value-added and double counting in sales of foreign affiliates and domestic-owned companies

In this paper, we propose a new accounting framework for the decomposition of value-added into domestic, foreign and double counting terms in domestic sales. In this framework, we show where the value-added double counting is derived from and give an explicit expression of domestic and foreign double counting terms based on the Inter-Country Input-Output (ICIO) tables’ Ghosh insight. We can distinguish domestic sales from exports and trace the value added and double counting in sales of foreign affiliates and domestic-owned enterprises. Based on this framework, we then calculate the value-added by foreign-owned and domestic-owned firms in exports and in domestic sales by using an Inter-Country Input-Output table split according to ownership. Preliminary results suggest that there is much more double counting in sales of foreign affiliates than in exports and that more value-added is created through exports than through sales of foreign affiliates in world GDP.
THE USE OF SEWAGE SLUDGE ASH (SSA) AS PARTIAL REPLACEMENT OF CEMENT IN CONCRETE

The production of sewage sludge from waste water treatment plant is increasing all over the world. Disposal of sewage sludge is becoming a serious environmental problem. Another alarming issue is attributed to the high usage of concrete in the construction industry where concrete is one of its main material. This will lead to increased cement production and emission of carbon dioxide because the cement industry one of the major contributor of carbon dioxide emission. Hence, the research for replacement of cement by sewage sludge ash is essential to reduce both the emissions of carbon dioxide and the disposal problem of sewage sludge ash. An attempt has been made to investigate the use of sewage sludge ash as partial cement replacement in concrete. The sewage sludge is incinerated at the temperature of 600°C and a duration of 3 hours. The incinerated sewage sludge ash is sieved through size of 150 µm. Four different percentages of 5%, 10%, 15% and 20% of sewage sludge ash (SSA) is used to replace the cement in the concrete. XRD and XRF tests were carried out to determine the similarity component present in the SSA. Water absorption test and slump test has also been carried out to check the capacity of water absorption, durability and workability of the SSA concrete. The compressive strength of SSA concrete is also determined through rebound hammer and compression test. Results show that SSA has the potential to replace cement as the major chemical component of SSA is similar to that of cement.5% of SSA concrete shows a lower absorption value than the control sample which shows that 5% SSA would have a better durability. However, an increase in the percentage of SSA decreases the workability and compressive strength and yet, the 5% SSA concrete possesses compressive strength higher than 25 N/mm 2 which can be applied in structural applications. The findings suggested that the suitability of sewage sludge ash concrete in different cement replacement ratio is applicable for different usage. The application of sewage sludge ash in concrete will directly reduce the quantity of the cement used which also decreases the emissions of carbon dioxide and solving the disposal problem of sewage sludge.
LATUX: an Iterative Workflow for Designing, Validating and Deploying Learning Analytics Visualisations

Designing, validating and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design and psychology. Whilst each of these disciplines has established its own design methodologies, there is a need for methodological frameworks that meet the specific demands of the cross-disciplinary space defined by learning analytics. In particular there is no systematic workflow for producing learning analytics tools that are both technologically feasible and truly underpin the learning experience. In this paper, we present a set of guiding principles and recommendations derived from the LATUX workflow. LATUX is a five-stage workflow to design, validate and deploy awareness interfaces in technology-enabled learning environments. LATUX is grounded on a well-established design process for creating, testing and re-designing user interfaces. We extend this process by integrating the pedagogical requirements, to guide the design of learning analytics visualisations that can inform instructors’ pedagogical decisions or intervention strategies. The workflow is illustrated with a case study in which collaborative activities were deployed in a real classroom. Finally, the paper proposes a research agenda to support designers and implementers of learning analytics interfaces.
Using machine learning techniques for sentiment analysis

The Natural language processing is the discipline that studies how to make the machines read and interpret the language that the people use, the natural language. But in the machines world, the words not exist and they are represented by sequences of numbers that the machine represents with a character when displaying them on screen. The Sentiment Analysis is the name of the problem that with a sentence or text the machine gets capable to analyze and predict with the maximum precision possible the sentiment that will be obtained by a person when reads it or the contextual opinion related to something. This document wants to show what we can obtain using the most used machine learning tools.
Effects of telmisartan on serum adiponectin and left ventricular remodeling in patients with essential hypertension

The aim of this study was to observe the changes in the serum Adiponectin (APN) levels and Left Ventricular Hypertrophy (LVH) in hypertensive patients before and after telmisartan treatment. Two hundred and forty hypertensive patients complicated with LVH were divided into a telmisartan group and an amlodipine group. The changes of these patients’ blood pressure, APN, and Left Ventricular Mass index (LVMI) treatment before and 12 w after treatment were compared. The systolic and diastolic blood pressures in both groups were significantly lower than those before treatment (P 0.05). Serum APN levels in the telmisartan group were significantly higher than those before treatment (P 0.05). Compared with amlodipine, telmisartan significantly increased the serum APN levels and significantly reversed the Left Ventricular Remodeling (LVRM) while reducing the blood pressure.
The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the Lendingclub Consumer Platform

Supersedes Working Paper 17-17. Fintech has been playing an increasing role in shaping financial and banking landscapes. There have been concerns about the use of alternative data sources by fintech lenders and the impact on financial inclusion. We compare loans made by a large fintech lender and similar loans that were originated through traditional banking channels. Specifically, we use account-level data from LendingClub and Y-14M data reported by bank holding companies with total assets of $50 billion or more. We find a high correlation with interest rate spreads, LendingClub rating grades, and loan performance. Interestingly, the correlations between the rating grades and FICO scores have declined from about 80 percent (for loans that were originated in 2007) to only about 35 percent for recent vintages (originated in 2014? 2015), indicating that nontraditional alternative data have been increasingly used by fintech lenders. Furthermore, we find that the rating grades (assigned based on alternative data) perform well in predicting loan performance over the two years after origination. The use of alternative data has allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into ? better? loan grades, which allowed them to get lower priced credit. In addition, for the same risk of default, consumers pay smaller spreads on loans from LendingClub than from credit card borrowing.
Status and Pancreatic Cancer Risk in Male Smokers A Prospective Nested Case-Control Study of Vitamin D Updated

Sun exposure is associated with lower death rates for pancreatic cancer in some ecological studies. Skin exposure to UVB light induces cutaneous production of precursors to 25-hydroxyvitamin D [25(OH)D]. Pancreatic islet and duct cells express 25(OH)D3-1A-hydroxylase that generates the biologically active 1,25(OH)2 vitamin D form. Thus, 25(OH)D concentrations could affect pancreatic function and possibly pancreatic cancer etiology. We conducted a prospective nested case-control study in the Alpha-Tocopherol, BetaCarotene Cancer Prevention cohort of male Finnish smokers, ages 50 to 69 years at baseline, to test whether more adequate vitamin D status, as determined by prediagnostic serum 25(OH)D concentrations, was associated with lower pancreatic cancer risk. Two hundred incident exocrine pancreatic cancer cases that occurred between 1985 and 2001 (up to 16.7 years of follow-up) were matched by age and date of blood draw to 400 controls who were alive and free of cancer at the time the case was diagnosed. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using conditional logistic regression. Higher vitamin D concentrations were associated with a 3-fold increased risk for pancreatic cancer (highest versus lowest quintile, >65.5 versus <32.0 nmol/L: OR, 2.92; 95% CI, 1.56-5.48, P trend = 0.001) that remained after excluding cases diagnosed early during followup. Contrary to expectations, subjects with higher prediagnostic vitamin D status had an increased pancreatic cancer risk compared with those with lower status. Our findings need to be replicated in other populations and caution is warranted in their interpretation and implication. Our results are intriguing and may provide clues that further the understanding of the etiology of this highly fatal cancer. (Cancer Res 2006; 66(20): 10213-9)
Tendermint : Consensus without Mining

Cryptocurrencies such as Bitcoin enable users to submit payment transactions without going through a centralized trusted organization. Bitcoin relies on proof-of-work mining to secure consensus which is problematic; mining requires a massive expenditure of energy, confirmation of transactions is slow, and security is difficult to quantify. We propose a solution to the blockchain consensus problem that does not require mining by adapting an existing solution to the Byzantine Generals Problem.
Ventilator-Associated Pneumonia and the Effectiveness of Endotracheal Tubes Coated with Silver Sulfadiazine

Ventilator-associated pneumonia (VAP) is a consequence of intubation and mechanical ventilation. Bacteria colonize the inner-lumen of endotracheal tubes (ETT) and develop into a biofilm. One method to reduce/eliminate the develop of biofilms within the ETT is lining the inner-lumen with silver-sulfadiazine. A systematic review was conducted to evaluate the effectiveness of silver-coated ETTs for patients that develop VAP. Multiple databases were searched to identify key literature related to silver-coated ETTs and VAP. Inclusion and exclusion criteria were identified to finalize the studies that were included in this systematic review. Five key studies were included in this review. Studies were further evaluated with PRISMA, a data collection table, the Critical Appraisal Skills Programme (CASP) and the Critical Appraisal for Summaries of Evidence (CASE) worksheet. All studies found either a reduction or elimination of bacteria within the ETT, breathing circuit, or lungs of the study subjects. In addition to the reduced colonization found across the studies, one study found a reduction in the mortality rate for the intervention group following a diagnosis of VAP. Certified Registered Nurse Anesthetists (CRNA) play an important role in educating staff about the impact silver-coated ETTs have on patient outcomes throughout periods of intubation and mechanical ventilation. Additionally, CRNAs are well positioned to identify patients pre-operatively that may require prolonged intubation following surgery. By advocating for silver-coated ETTs for these patients, CRNAs can improve patient outcomes by reducing the likelihood of these patients developing VAP.
Complex Variability within the THCA and CBDA Synthase Genes in Cannabis Species

The genes encoding the enzymes THCA and CBDA synthase, enzymes catalyzing the final biosynthetic steps in the production of the cannabinoids Δ-9-tetrahydrocannabinolic acid (THCA) and cannabidiolic acid (CBDA), have been subjected to DNA sequencing to better understand the variability of gene structure in different strains of marijuana (Cannabis sp.) and to begin to explore how this variability may have consequences in cannabinoid synthesis. Genomic DNA was extracted from a collection of marijuana samples seized by local law enforcement and made available for molecular analysis. Massively parallel sequencing as well as Sanger sequencing were used to elucidate the sequence of the synthase gene from different seized samples. The sequences were compared with THCA and CBDA synthase gene sequences contained within the GenBank database of NCBI to investigate the variability of these genes and to try and differentiate active from inactive synthase genes known to exist in Cannabis sp. Results suggest the existence of numerous copies of THCA and CBDA synthase gene sequences in the genome of Cannabis. THCA synthase sequences are less variable than CBDA sequences in terms of SNP polymorphisms visualized and SNPs visualized in THCA synthase are more highly conserved among the seized samples analyzed. Our results suggest the existence of multiple synthase genes that exist combinations of functional and non-functional combinations of genes. It may be difficult to design a simple molecular assay that will distinguish between active and inactive synthase genes in a way that would be useful to growers desiring to propagate plants selected to produce only one or the other of the principal cannabinoids useful for medicinal purposes.
A framework for testing isotropy with the cosmic microwave background

We present a new framework for testing the isotropy of the Universe using cosmic microwave background data, building on the nested-sampling ANICOSMO code. Uniquely, we are able to constrain the scalar, vector and tensor degrees of freedom alike; previous studies only considered the vector mode (linked to vorticity). We employ Bianchi type VII$_h$ cosmologies to model the anisotropic Universe, from which other types may be obtained by taking suitable limits. In a separate development, we improve the statistical analysis by including the effect of Bianchi power in the high-$\ell$, as well as the low-$\ell$, likelihood. To understand the effect of all these changes, we apply our new techniques to WMAP data. We find no evidence for anisotropy, constraining shear in the vector mode to $(\sigma_V/H)_0 < 1.7 \times 10^{-10}$ (95% CL). For the first time, we place limits on the tensor mode; unlike other modes, the tensor shear can grow from a near-isotropic early Universe. The limit on this type of shear is $(\sigma_{T,\rm reg}/H)_0 < 2.4 \times 10^{-7}$ (95% CL).
Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking

Offline training for object tracking has recently shown great potentials in balancing tracking accuracy and speed. However, it is still difficult to adapt an offline trained model to a target tracked online. This work presents a Residual Attentional Siamese Network (RASNet) for high performance object tracking. The RASNet model reformulates the correlation filter within a Siamese tracking framework, and introduces different kinds of the attention mechanisms to adapt the model without updating the model online. In particular, by exploiting the offline trained general attention, the target adapted residual attention, and the channel favored feature attention, the RASNet not only mitigates the over-fitting problem in deep network training, but also enhances its discriminative capacity and adaptability due to the separation of representation learning and discriminator learning. The proposed deep architecture is trained from end to end and takes full advantage of the rich spatial temporal information to achieve robust visual tracking. Experimental results on two latest benchmarks, OTB-2015 and VOT2017, show that the RASNet tracker has the state-of-the-art tracking accuracy while runs at more than 80 frames per second.
Risk factors associated with the frequency of antibodies against Babesia bovis and Babesia bigemina in cattle in southern Mozambique 1

Tembue A.A.M., Silva F.J.M. , Silva J.B. , Santos T.M. , Santos H.A. , Soares C.O. & Fonseca A.H. 2011. Risk factors associated with the frequency of antibodies against Babesia bovis and Babesia bigemina in cattle in southern Mozambique. Pesquisa Veterinária Brasileira 31(8):663-666. Laboratório de Doenças Parasitárias, Departamento de Parasitologia Animal, Universidade Federal Rural de Rio de Janeiro, Seropédica, RJ 23890000, Brazil. E-mail: adivaldo@ufrrj.br The study aimed to evaluate the risk factors associated with the frequency of IgG antibodies against Babesia bovis and B. bigemina in cattle in southern Mozambique. Eight hundred and nine serum samples were collected from cattle in three provinces namely Maputo, Gaza and Inhambane, and tested by indirect enzyme-linked immunosorbent assay (i-ELISA) to assess the humoral immune response towards B. bovis and B. bigemina. The chi-square test at 5% significance was used to determine whether there was an association between gender, age and geographic origin of seropositive animals. The overall prevalence was 78.8% (548/695) for B. bovis and 76.0% (528/695) for B. bigemina. The origin of the animals showed a significant association (p<0.05) with seropositivity to both agents, while gender and age was not associated (p>0.05). Maputo province had the highest rate of positive animals, with 93.7% (118/126) for B. bovis and 97.6% (123/126) for B. bigemina. In Gaza province 77.3% (321/415) of the animals were positive for B. bovis and 67.5% (280/415) for B. bigemina, while in the province of Inhambane the levels of seropositivity were 70.8% (109/154) and 81.2% (125/154) for B. bovis and B. bigemina respectively. In the present study, the frequency of cattle positive for B. bovis and B. bigemina was shown to increase among older age groups, suggesting that infection and re-infection persisted even after the primary infection. Thus, this region is considered to be in a state of enzootic stability with regards to B. bovis and B. bigemina.
Level of disability among individuals with Adhesive Capsulitis visiting Dhulikhel Hospital using Quick-DASH

Adhesive capsulitis affects shoulder joint with pain and mobility deficits. It has been termed as a self-limiting condition but recent evidences have shown patients facing long term disability for years due to this condition. Pain and stiffness are the factors defining disability with early pain or late stiffness in this condition. The level of disability is a component defining clinical state of adhesive capsulitis by which interventions can be planned out. Method: This is a cross-sectional study of 30 individuals with Adhesive Capsulitis visiting Dhulikhel Hospital in Nepal. Socio demographic factors, pain intensity and level of disability were recorded. Numeric Pain Rating Scale (NPRS) and Quick-Disability of arm shoulder and hand (Q-DASH) were the two outcome tools used to measure pain intensity and disability levels. Descriptive analysis was used for the sociodemographic findings and Chi-square test was used to observe the association between Pain and Disability. Results: The study found that majority of individuals had moderate level of disability (70%) followed by mild (23.3%) and severe level (6.7%). There was an association between pain and disability (p <0.05). Conclusion: Maximum number of individuals had moderate level of disability affecting their functional task due to pain and stiffness.
PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.