Miracle-dz/UniFAR-FTUs huggingface dataset:
NPP VIIRS geometric performance status

Visible Infrared Imager Radiometer Suite (VIIRS) instrument on-board the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) satellite is scheduled for launch in October, 2011. It is to provide satellite measured radiance/reflectance data for both weather and climate applications. Along with radiometric calibration, geometric characterization and calibration of Sensor Data Records (SDRs) are crucial to the VIIRS Environmental Data Record (EDR) algorithms and products which are used in numerical weather prediction (NWP). The instrument geometric performance includes: 1) sensor (detector) spatial response, parameterized by the dynamic field of view (DFOV) in the scan direction and instantaneous FOV (IFOV) in the track direction, modulation transfer function (MTF) for the 17 moderate resolution bands (M-bands), and horizontal spatial resolution (HSR) for the five imagery bands (I-bands); 2) matrices of band-to-band co-registration (BBR) from the corresponding detectors in all band pairs; and 3) pointing knowledge and stability characteristics that includes scan plane tilt, scan rate and scan start position variations, and thermally induced variations in pointing with respect to orbital position. They have been calibrated and characterized through ground testing under ambient and thermal vacuum conditions, numerical modeling and analysis. This paper summarizes the results, which are in general compliance with specifications, along with anomaly investigations, and describes paths forward for characterizing on-orbit BBR and spatial response, and for improving instrument on-orbit performance in pointing and geolocation.
Physicians’ Adherence to Asthma Guidelines: A Prospective Prescription Review from Tertiary Care Hospital, Malaysia

RESEARCH ARTICLE Physicians’ Adherence to Asthma Guidelines: A Prospective Prescription Review from Tertiary Care Hospital, Malaysia Raja Ahsan Aftab, Amer Hayat Khan, Syed Azhar Syed Sulaiman and Irfhan Ali Department of Clinical Pharmacy, School of Pharmaceutical Sciences Universiti Sains Malaysia, 11800 Penang, Malaysia School Of Pharmacy, Taylor’s University, Subang Jaya, Selangor, Malaysia Department of Respiratory Medicine, Penang General Hospital, Penang, Malaysia
Concordance of Serum Creatinine to Estimated Glomerular Filtration Rate in Determining Early Chronic Kidney Disease in Malaysia

Little is known about the accuracy of serum creatinine (SCr) in identifying early chronic kidney disease (CKD) in the primary care setting. Thus, this study aims to examine the concordance of SCr to estimated glomerular filtration rate (eGFR) in detecting early CKD. This is part of a randomly selected 10-year retrospective, observation cohort study of patients registered with the Department of Primary Care Medicine Clinic at the University of Malaya Medical Centre. A SCr ≥ 132μmol/L and eGFR < 60 ml/min are used as the cut-off points for impaired renal function. Kappa statistic is used to test the inter-rater agreement of SCr with eGFR. A total of 1100 subjects were recruited. The mean age, SCr and eGFR were 66±9 years, 86±42 μmol/L and 70±30 ml/min respectively. The concordance between SCr and eGFR was poor as 363 (35.5%) patients had normal SCr but abnormal eGFR. Kappa value was 0.022 (p<0.001). Screening for CKD using SCr fails to detect an additional third of patients with impaired renal functions. Hence using eGFR is a better way to identify early CKD.
Open-economy Distribution Forecast Targeting, Macroeconomic Volatility and Financial Implication

In an open-economy faced with model uncertainty, this paper uses distribution forecasts to investigate the impact of alternative inflation targeting policies on macroeconomic volatility and their potential implications on financial stability. Theoretically, Domestic Inflation Targeting (DIT) leads to less volatility than Consumer Price index Inflation Targeting (CPIIT) for several macroeconomic variables and, in particular, for the interest rate. Empirically, a positive relationship between interest rate volatility and financial instability emerges for the US, UK and Sweden since the early 1990s. Bridging theory and empirical evidence, we conclude that the choice of the inflation targeting regime has an important impact on macroeconomic volatility and potential implications for financial stability.
Influence of System Behavior on Success of Public Infrastructural Megaprojects in Kenya

The main objective of this study was to investigate the influence of system behavior on the success of public infrastructural megaprojects in Kenya. The need for this study arose from the thesis that complexity is the main cause of waste and failure that results in infrastructural megaprojects being delivered over budget, behind schedule, with benefit shortfalls, over and over again; and that system behavior is a key cause of this complexity. The study was designed as quantitative research, based on virtual constructionist ontology. A cross-sectional census survey of completed public infrastructural megaprojects was conducted using two interlinked questionnaires. Data analysis was conducted using both descriptive and inferential statistics. The results showed that system behavior had a significant negative influence on the success of public infrastructural megaprojects. System dynamics arising from the interaction of connectedness and dependency influenced success in such a way that the relative variability in cost and schedule performance was lower in cases where project components were pre-fabricated, pre-assembled and tested offsite; and projects in which materials were only brought on site when the site was ready to receive them recorded superior performance in both cost and schedule. As such, this study recommends that the design of these projects should provide for a delivery model in which project components are pre-fabricated, pre-assembled and tested offsite before their actual use on the project. It is also recommended that procurement practices for these projects be streamlined to allow for Just-In-Time (JIT) procurement
Similarity Measures for Content-Based Audio Retrieval

Personal multimedia databases contain thousands of items and other databases on the Internet may contain even billions of items. Finding a particular item manually from such databases becomes overwhelming and thus automatic search engines are required to lighten the job. Query by example refers to automatically finding multimedia items from a database, which are similar to the example provided by the user. This is an important task in modern multimedia databases. This thesis deals with automatic query by example of audio samples. The emphasis is on representation and distance measures between two audio signals, which are used to estimate the similarity between these two signals. The thesis also covers computational issues, which are highly important when it comes to practical implementation of the algorithms. Two different audio signal representations are proposed. These representations are interconnected, since the first separates drums from a polyphonic music signal although the same approach could be used to separate other parts of the original signal as well, for example, harmonic instruments. The second representation models the harmonic sound using only a few parameters. The proposed method is based on Mel frequency cepstral coefficients, which are further modeled using attack-decay-sustain-release curves with temporal evolution of harmonic instruments. Most distance measures, used in audio signal processing, are based on dividing a signal into frames, extracting perceptually motivated features from each frame, and calculating the distance between the features. Most of the proposed distance measures use Gaussian mixture models to estimate the probability density functions of the framewise features and calculate the distance between the Gaussian mixture models. However, the thesis also introduces a parameter free distance measurement. This is based on compression ratios of audio signals and
Carbon Nanotube Length Governs the Viscoelasticity and Permeability of Buckypaper

The effects of carbon nanotube (CNT) length on the viscoelasticity and permeability of buckypaper, composed of (5,5) single-walled CNTs (SWCNTs), are systematically explored through large-scale coarse-grained molecular dynamics simulations. The SWCNT length is found to have a pronounced impact on the structure of buckypapers. When the SWCNTs are short, they are found to form short bundles and to be tightly packed, exhibit high density and small pores, while long SWCNTs are entangled together at a low density accompanied by large pores. These structure variations contribute to distinct performances in the viscoelasticity of buckypapers. The energy dissipation for buckypapers with long SWCNTs under cyclic shear loading is dominated by the attachment and detachment between SWCNTs through a zipping-unzipping mechanism. Thus, the viscoelastic characteristics of buckypapers, such as storage and loss moduli, demonstrate frequency- and temperature-independent behaviors. In contrast, the sliding-friction mechanism controls the energy dissipation between short SWCNTs when the buckypaper is under loading and unloading processes. Friction between short SWCNTs monotonically increases with rising length of SWCNTs and temperature. Therefore, the tanδ, defined as the ratio of the loss modulus over the storage modulus, of buckypaper with short SWCNTs also increases with the increment of temperature or SWCNT length, before the SWCNTs are entangled together. The permeability of buckypapers is further investigated by studying the diffusion of structureless particles within buckypapers, denoted by the obstruction factor (β). It is found to be linearly dependent on the volume fraction of SWCNTs, signifying a mass-dominated permeability, regardless of the structure variations induced by different SWCNT lengths. The present study provides a comprehensive picture of the structure-property relationship for buckypapers composed of SWCNTs. The methodology could be used for designing multifunctional buckypaper-based devices.
Electronic Government as a Paradigm Shift for Efficient Public Services: opportunities and challenges for Nigerian government

Purpose – Nigeria has set up an e‐government initiative termed the “National e‐Government Strategy” (NeGSt) for the purpose of using ICT infrastructure to enhance public services. It was expected that e‐government would enable the Nigerian government at all levels to render efficiencies in the public sector, ensure higher productivity and economic growth, foster national competitiveness and lead to the attainment of the vision 20‐2020. Regrettably, the e‐services envisaged seem not to be impacting much on public service delivery in the country. The aim of this paper is to examine the benefits and the status of e‐government in Nigeria, the barriers to the accomplishment of the goal, and some ways out.Design/methodology/approach – A total of ten federal government ministries in Nigeria that have an official website were sampled. The study population was 100 randomly drawn employees in the ministries, and a structured questionnaire and oral interviews were used. Data were analyzed using frequency tables, sim.
Forecasting Chinese Stock Market Volatility With Economic Variables

ABSTRACT This article investigates the forecasting power of economic variables for the Chinese stock market volatility. We find that several economic variables strongly forecast the future monthly volatilities for the aggregate Chinese stock market and a number of industry portfolios. The forecasting power of economic variables remains strong in out-of-sample setting. The predictability of Chinese stock market volatility can be further improved when combining information in all economic variables together.
Quantitative Assay for Measurement of HER2 Total Protein Expression and HER2 Dimers

Genetic Counseling Experts recommend formal genetic counseling for patients who are at risk for inherited disorders and who wish to undergo genetic testing. Interpreting the results of genetic tests and understanding risk factors can be difficult for some patients; genetic counseling helps individuals understand the impact of genetic testing, including the possible effects the test results could have on the individual or their family members. It should be noted that genetic counseling may alter the utilization of genetic testing substantially and may reduce inappropriate testing; further, genetic counseling should be performed by an individual with experience and expertise in genetic medicine and genetic testing methods.
FPDeep: Acceleration and Load Balancing of CNN Training on FPGA Clusters

FPGA-based CNN accelerators have advantages in flexibility and power efficiency and so are being deployed by a number of cloud computing service providers, including Microsoft, Amazon, Tencent, and Alibaba. Given the increasing complexity of neural networks, however, it is becoming challenging to efficiently map CNNs to multi-FPGA platforms. In this work, we present a scalable framework, FPDeep, which helps engineers map a specific CNN's training logic to a multi-FPGA cluster or cloud and to build RTL implementations for the target network. With FPDeep, multi-FPGA accelerators work in a deeply-pipelined manner using a simple 1-D topology; this enables the accelerators to map directly onto many existing platforms, including Catapult, Catapult2, and almost any tightly-coupled FPGA cluster. FPDeep uses two mechanisms to facilitate high-performance and energy-efficiency. First, FPDeep provides a strategy to balance workload among FPGAs, leading to improved utilization. Second, training of CNNs is executed in a fine-grained inter- and intra-layer pipelined manner, minimizing the time that features need to remain available while waiting for back-propagation. This reduces the storage demand to where only on-chip memory is required for convolution layers. Experiments show that FPDeep has good scalability to a large number of FPGAs, with the limiting factor being the FPGA-to-FPGA bandwidth. Using six transceivers per FPGA, FPDeep shows linearity up to 60 FPGAs. We evaluate energy efficiency in GOPs/J and find that FPDeep provides up to 3.4 times higher energy efficiency than the Tesla K80 GPU.
G T ] 2 8 O ct 2 01 8 Bounded-Loss Private Prediction Markets

Prior work has investigated variations of prediction markets that preserve participants’ (differential) privacy, which formed the basis of useful mechanisms for purchasing data for machine learning objectives. Such markets required potentially unlimited financial subsidy, however, making them impractical. In this work, we design an adaptively-growing prediction market with a bounded financial subsidy, while achieving privacy, incentives to produce accurate predictions, and precision in the sense that market prices are not heavily impacted by the added privacypreserving noise. We briefly discuss how our mechanism can extend to the datapurchasing setting, and its relationship to traditional learning algorithms.
Analyzing Big Data Problem Using Hadoop and Cloud Technology

: In any kind of industry sector networks they used to share collaboration information which facilitates common interests based information sharing. As this method decreases costs and increases incomes thus by sharing and processing data management challenges they develop their performance and security. We have developed a data intensive technique which is a method of service sharing in corporate networks through cloud based peer to peer data management platform. Already existing method Data Integration in Bigdata (DIB) integrates database management system, cloud computing and peer to peer technologies and found a flexible and scalable data sharing service network applications. There are many different areas need to be included and concentrated the split up of data to be dealt whenever user includes new set of data. As it have several split ups data should be properly fetched without any loss of information. Corporate network eliminates less efficient hadoop tool thus reduced total intercompany costs. In our proposed system Data Integration in Bigdata (DIB) is used for integrating data and enhances the model pay for efficient storage. Robustness of data, performance upgrade for size of data increase for prolonged storage use. The benchmarking results show that our method outperforms HadoopDB, a recently proposed large-scale data processing system, in performance when both systems are employed to handle typical corporate network workloads. The benchmarking results also demonstrate that our method achieves near linear scalability for throughput with respect to the number of peer nodes
Low Molecular Weight Protein Tyrosine Phosphatases Control Antibiotic Production in Streptomyces coelicolor A3(2)

Streptomyces coelicolor A3(2) possesses a low molecular weight protein tyrosine phosphatase (LMW-PTP), PtpA, that affects the production of undecylprodigionsin (RED) and actinorhodin (ACT). In this study we identified another LMW-PTP called sco3700. Tyrosine phosphatase activity of the purified Sco3700 was established using para-nitrophenyl phosphate and the tyrosine-phosphorylated protein PtkA from Bacillus subtilis as substrates. The optimum pH for the Sco3700 phosphatase activity was 6.8, and KM for pNPP was 14.3 mM compared to pH 6.0 and KM0.75 mM for PtpA. The potential of Sco3700 to participate, alongside PtpA, in the regulation of S. coelicolor antibiotic production was investigated. Hence, S. coelicolor A3(2) strains with ptpA and sco3700 overexpression were constructed and characterized for growth, RED and ACT production. We did observe an increase in volumetric productivity of ACT in the ptpA over expression strain. Furthermore, a significantly earlier onset of ACT production was observed when ptpA was over expressed. Sco3700 overexpression had a pleiotropic effect on the cell, and the strain exhibited lower productivities and final concentrations of antibiotics. We conclude that Sco3700 is indeed a tyrosine phosphatase, and it contributes to regulation of antibiotic production in S. coelicolor affecting the timing of onset of the antibiotic production.
Winners and Losers in Area-Based Management of a Small-Scale Fishery in the Colombian Pacific

The Pacific coast of Colombia has some of the most extensive mangrove forests in South America. As an isolated region and one of the country’s poorest, coastal communities rely on fishing as a main source of animal protein and income. In an attempt to reverse declining trends of fisheries resources, in 2008, an Exclusive Zone of Artisanal Fishing closed to industrial fishing, was established by stakeholders in the Northern Choco region. Here we present a case study to investigate the effects of this area-based management on fisheries productivity and catch composition. Fishery landings data from 2010 to 2013 are compared to those of a neighbouring region with no fisheries management. Catch per unit effort, mean weight landed, and number of landed individuals were calculated for mangrove and non-mangrove associated species by boat type and fishing gear. A set of mixed effects models were used to unpack the effects of multiple factors and their interactions on response variables. Results show that across fishing gears and time, mean catch per unit effort increased by 50% in the Exclusive Zone of Artisanal Fishing within 3 years. Fisheries here focused on offshore resources with 61% more fishing trips associated with motorized boats than in the unmanaged region, where fishing was predominantly in mangroves and close to the coast. This suggests that fisheries management, may have played a role in reducing pressure on mangrove resources. However, area-based management may have also driven the displacement of fishing effort by excluding industrial trawlers, which then concentrated their activity in neighbouring areas.
Extraction of Aspects from Customer Reviews using Life Long Learning

Aspect extraction is a challenging task of opinion mining. This paper proposes a novel statistical approach to make a major improvement in sentiment analysis of customer reviews. The approach is based on identification of customer opinions along with the framework of lifelong learning. It is implemented with LSA and Association rule mining. Experimental results show the effectiveness of the proposed approach.
An Event-Related Potentials Study of Mental Rotation in Identifying Chemical Structural Formulas.

The purpose of this study was to investigate how mental rotation strategies affect the identification of chemical structural formulas. This study conducted event-related potentials (ERPs) experiments. In addition to the data collected in the ERPs, a Chemical Structure Conceptual Questionnaire and interviews were also administered for data collection. Eighteen university students majoring in chemistry were recruited. In the ERP experiments, the participants were required to identify 2D figures, 2D chemical structural formulas, 3D objects and 3D chemical structural formulas. The contours of 2D figures are similar to those of 2D chemical structural formulas, but they contain no content knowledge. Likewise, the contours of 3D objects are similar to 3D chemical structural formulas without content knowledge. The results showed that all students used similar strategies of mental rotation in identifying 2D figures, 3D objects and 3D chemical structural formulas. However, the high-achieving students used different strategies in identifying 2D figures and chemical structural formulas, while the low-achieving students tended to use similar strategies of mental rotation in identifying both 2D figures and chemical structural formulas. The results indicate that some of the difficulties in identifying 2D chemical structural formulas that students encounter are due to their inappropriate strategies of mental rotation.
A Review of Embedded Base Power Management Unit

: This paper Power-efficient design requires reducing power dissipation in all parts of the design and during all stages of the design process subject to constraints on the system performance and quality of service (QoS). Power-aware high-level language compilers, dynamic power management policies, memory management schemes, bus encoding techniques, and hardware design tools are needed to meet these often-conflicting design requirements. Power consumption by embedded devices is a critical issue. There is always a need to extend battery life and/or reduce the environmental impact of a system. Historically, this was purely a hardware issue, but those days are past. In modern embedded systems software takes an increasing responsibility for power management. This article reviews how power management is achieved while a device is operating and looks at the techniques employed to minimize power consumption when a device is inactive.
Exploiting Convolutional Neural Networks for Phonotactic Based Dialect Identification

In this paper, we investigate different approaches for Dialect Identification (DID) in Arabic broadcast speech. Dialects differ in their inventory of phonological segments. This paper proposes a new phonotactic based feature representation approach which enables discrimination among different occurrences of the same phone n-grams with different phone duration and probability statistics. To achieve further gain in accuracy we used multi-lingual phone recognizers, trained separately on Arabic, English, Czech, Hungarian and Russian languages. We use Support Vector Machines (SVMs), and Convolutional Neural Networks (CNN s) as backend classifiers throughout the study. The final system fusion results in 24.7% and 19.0% relative error rate reduction compared to that of a conventional phonotactic DID, and i-vectors with bottleneck features.