Miracle-dz/UniFAR-FTUs huggingface dataset:
Total Phenolic Content and Antioxidant Activities of Palm Puree Prepared From Various Tenera Varieties

Four palm puree samples were used in this study namely Palm Puree 1 (PP1), Palm Puree 2 (PP2), Palm Puree 3 (PP3) and Palm Puree 4 (PP4). All samples were prepared from the combination of mesocarp fiber and crude palm oil of Tenera varieties. Total Phenolic Content (TPC) OF Palm Puree was determined by Folin-Ciaocalteu assay while antioxidant activities were determined by Ferric Reducing Antioxidant Power (FRAP), beta-carotene content and 1,1- Diphenyl-2-2picrylhydrazyl (DPPH) assays. Palm Puree 4 (PP4) showed highest TPC and FRAP values of 412.194 mg GAE/100 g extract and 282.03 x 10 3 µM Trolox/g dry weight respectively as compared to other samples. Palm Puree 3 (PP3) exhibited the highest percentage of free radical scavenging (DPPH) (95.48%) and the beta-carotene content (1116.61 mg/kg) among all Palm Puree samples studied.
Locality in Language and Locality in Brain Oscillatory Structures

From the perspective of brain oscillations, an explanation is offered as to why external systems of language cannot deal with identical categorial elements in certain local domains. An equivalent locality effect in brain structure is argued for which causes a (cognitively problematic and ambiguous) synchronization of rhythms in the gamma, beta1, and beta2 bands. These rhythms can be related to different categories, and their limited patterns and interactions may explain syntactic constraints on phrases, phases, and Internal Merge.
Anomalous Transport Behavior in Quantum Magnets

Transport behavior that is characterized by a low-temperature electrical resistivity that displays a power law behavior ( ρ ( T → 0 ) ∝ T s ) with an exponent of s < 2 is commonly observed in magnetic materials in both the magnetic and non-magnetic phases. We give a pedagogical overview of this phenomenon that summarizes both the experimental situation and the state of its theoretical understanding. We also put it in context by drawing parallels with unusual power law transport behavior in other systems.
Summer and winter variations of dicarboxylic acids, fatty acids and benzoic acid in PM 2.5 in Pearl Delta River Region, China

Ground-based PM2.5 samples collected at four different sites in Pearl River Delta region (PRD) during win- ter and summer (from 14 December 2006 to 28 January 2007 in winter and from 4 July to 9 August 2007 in sum- mer) were analyzed for 30 water-soluble organic species, including dicarboxylic acids, ketocarboxylic acids and di- carbonyls, nine fatty acids, and benzoic acid. Molecu- lar distributions of dicarboxylic acids demonstrated that ox- alic acid (C2) was the most abundant species followed by phthalic acid (Ph) in PRD region. The concentrations of total dicarboxylic acids ranged from 99 to 1340 ng m 3 , with an average of 438± 267 ng m 3 in PRD. The con- centrations of total ketocarboxylic acids ranged from 0.6 to 207 ng m 3 (43± 48 ng m 3 on average) while the con- centrations of total -dicarbonyls, including glyoxal and methylglyoxal, ranged from 0.2 to 89 ng m 3 , with an av- erage of 11± 18 ng m 3 in PRD. The total quantified water- soluble compounds (TQWOC) (organic carbon) accounted for 3.4± 2.2% of OC and 14.3± 10.3% of water-soluble OC (WSOC). Hexadecanoic acid (C16:0), octadecanoic acid (C18:0) and oleic acid (C18:1) were the three most abundant fatty acids in PRD. The distributions of fatty acids were char- acterized by a strong even carbon number predominance with a maximum (Cmax) at hexadecanoic acid (C16:0). Ratio of C18:1 to C18:0 acts as an indicator for aerosol aging. In PRD, an average of C18:1/C18:0 ratio was 0.53± 0.39, sug- gesting an enhanced photochemical degradation of unsatu- rated fatty acid. Moreover, the concentrations of benzoic acid ranged from 84 to 306 ng m 3 , (165± 48 ng m 3 on av-
Modeling Gross Primary Production by Integrating Satellite Data and Coordinated Flux Measurements in Arid and Semi-Arid China

Abstract Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes. Remote sensing-based models, which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics, improve spatially extended estimates of vegetation productivity with high accuracy. In this study, the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM), which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types. The field data were collected by coordinating observations at nine stations in 2008. The results indicate that in the region during the growing season GPP was highest in cropland sites, second highest in woodland sites, and lowest in grassland sites. VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas. Further, Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas, while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation. This study demonstrates the potential of satellite-driven models for scaling-up GPP, which is a key component for studying the carbon cycle at regional and global scales.
The effect of span length to height ratio of reinforced concrete slabs on pressure-impulse diagram with multiple failure modes under blast loading

In this paper, two loosely coupled single degree of freedom (SDOF) systems are used to generate pressure-impulse diagrams (P-I) with the flexural and direct shear responses of one-way reinforced concrete slabs subjected to blast loading. The effect of span length to height ratio in P-I diagrams is investigated. The numerical calculation results indicate that a slab tends to fail in a direct shear mode if the blast load amplitude is high but of short duration. It tends to fail in flexural failure mode if load amplitude is relatively low and duration is relatively long. And the failure of the slab might be a combination of shear and flexural damage in the dynamic loading region. Based on numerical results, different failure modes are got with different the span length to height ratio on the P-I diagrams. Results indicate that there is only shear failure mode in the P-I diagrams when L/h 24.89, there are two damage mode in the P-I diagrams with flexure failure mode and flexure-shear failure mode. When 10.9 < L/h < 24.89, there are three damage modes in the P-I diagrams: shear failure mode, flexure failure mode and flexure-shear failure mode.
UvA-DARE (Digital Academic Repository) What Should We Teach in Information Retrieval?

Modern Information Retrieval (IR) systems, such as search engines, recommender systems, and conversational agents, are best thought of as interactive systems. And their development is best thought of as a two-stage development process: oﬄine development followed by con-tinued online adaptation and development based on interactions with users. In this opinion paper, we take a closer look at existing IR textbooks and teaching materials, and examine to which degree they cover the oﬄine and online stages of the IR system development process. We notice that current teaching materials in IR focus mostly on search and on the oﬄine development phase. Other scenarios of interacting with information are largely absent from current IR teaching materials, as is the (interactive) online development phase. We identify a list of scenarios and a list of topics that we believe are essential to any modern set of IR teaching materials that claims to fully cover IR system development. In particular, we argue for more attention, in basic IR teaching materials, to scenarios such as recommender systems, and to topics such as query and interaction mining and understanding, online evaluation, and online learning to rank.
Bank size, relationship lending and SME financing: Evidence from Bangladesh

BANK SIZE, RELATIONSHIP LENDING AND SME FINANCING: EVIDENCE FROM BANGLADESH This paper examines the effect of bank size on relationship lending and how relationship lending can affect credit availability, interest rates and collateral to SMEs in the context of Bangladesh. Our empirical results suggest that SMEs with a long-term relationship with small banks have more access to finance than from large banks. However, we did not find any evidence that long-term relationship with small banks can reduce interest rates or collateral requirements for SMEs. We find evidence though that a stronger and much more exclusive relationship with a small bank can reduce the interest rates for SMEs. This mixed evidence suggests that small banks do not have full comparative advantage in processing soft information, but large banks in Bangladesh may have different lending techniques to extend loans to SMEs with similar interest rates and collateral requirements as like as small banks. Furthermore, we find evidence that small banks are giving priority to both long-term relationship and collateral requirement for SME credit risk than large banks.
Reply to Comment on ‘Molecular structure-dependent deformations in boron nitride nanostructures subject to an electrical field’

A large scattering of effective atomic charge distribution was found in the literature for hexagonal boron nitride nanostructures (BNNSs). In our paper (Zhang J, Wang C Y and Sondipon A 2013 J. Phys. D: Appl. Phys. 46 235303) ‘±3e’ was chosen as a rough approximation for the effective atomic charge in BNNSs as it gave the piezoelectric coefficient of BNNSs close to the values in the literature.
Linking Taxonomic Diversity and Trophic Function: A Graph-Based Theoretical Approach

The purpose of this study is to develop a novel, visual method in analyzing complex functional trait data in freshwater ecology. We focus on macroinvertebrates in stream ecosystems under a gradient of habitat degradation and employ a combination of taxonomic and functional trait diversity analyses. Then we use graph theory to link changes in functional trait diversity to taxonomic richness and habitat degradation. We test the hypotheses that: 1) taxonomic diversity and trophic functional trait diversity both decrease with increased habitat degradation; 2) loss of taxa leads to a decrease in trophic function as visualized using a bipartite graph; and 3) loss of taxa will result in loss of redundancy. The first hypothesis was supported by the similarity of ShannonWiener diversity values for taxa and trophic function, correlated at r = 81%. The bipartite graph theoretic approach we developed clearly was effective in showing the linkages between taxonomic diversity and trophic functional traits related to habitat condition. In the most impaired site, loss of taxa led to the complete loss of some trophic functions and significantly less overall redundancy, supporting the third hypothesis. The implications are that taxa loss directly affects trophic function and that loss of taxonomic diversity may affect ecosystem function.
Assessing the use of function based assessments in Massachusetts among professionals working with individuals with developmental disabilities

There has been an emphasis placed on conducting function-based assessments (FBA) prior to selecting treatment for challenging behaviors for individuals with developmental disabilities (IDD). Research has demonstrated that treatment that first identifies the function of behavior is more effective for reducing challenging behavior than treatment not based on FBAs. There is little information regarding whether the practitioners responsible for behavior modification are employing FBA in applied settings. The purpose of the current study was to distribute a survey to assess the degree to which FBA are implemented in agencies serving IDD in the state of Massachusetts. The survey asked practitioners to indicate their perception about and use of the various categories of functional assessment (e.g., indirect assessment [IA], descriptive analysis, and functional analysis [FA]). From the 275 responses, the most frequently used FBA was descriptive assessments, which involves direct observation of behavior but no manipulation of environmental events. Results suggest that even though the majority (68.2%) of practitioners believe FA to be the more informative assessment tool for selecting behavioral treatment, only 26.1% of respondents indicate that they typically use FA (alone or in combination with IA or DA) to inform the development of a behavior plan. Board certified behavior analysts (BCBA) were no more likely to use FAs than were individuals without BCBA-certification. In fact, contrary to published research questioning the validity of DA for identifying function, 52.8% of BCBAs believe that descriptive assessments alone are sufficient for determining behavior function. Barriers to conducting FAs are discussed.
Ways to Reach Lower Detection Limits of Lateral Flow Immunoassays

This chapter considers factors influencing sensitivity of lateral flow immunoassay and modern developments that are focused on reaching lower detection limits. The exist ing variety of proposed approaches is classified in accordance with the “big five rules” for these assays, including proper sample, receptor, interaction, response, and output. The solutions for rapid extraction of target analytes and preventing negative influence of extractants are considered. Role to antibodies affinity and specificity is characterized. Potential of alternate bioreceptor molecules is discussed. Immunoreactants’ composi - tions, concentrations, and locations on the test strip are characterized as factors deter mining assay parameters. The existing variety of labels is compared in terms of their optical and alternate registration. Tools to modulate a sequence of analytical reactions and to form aggregates of the detected labels are considered. The discussed approaches are illustrated through developments of test strips for detection of mycotoxins, veteri nary drugs, and other analytes. Main research and development tasks to obtain proper receptors for LFIA. and sizes, carbon nanoparticles, selenium nanoparticles, iron oxide nanoparticles, fluorescent dyes, fluorescent dye-doped nanoparticles, quantum dots, infrared emitters, up-converting emitters, nanoparticles with long-lived emission, liposomes, and enzymes used for
Forecasting Daily Demand in Cash Supply Chains

Problem statement: Previous studies focused on explaining the long ru n determinants of currency demand offering limited insight into the s hort-run determinants and co-variability of daily demand in cash supply chains. Approach: This study contrasted competing techniques of fore casting daily demand in cash supply chains in order to dete rmine the overall performance and the potential of joint forecasting for integrated planning. A joint forecasting approach was compared with well- established causal forecasting techniques, namely, a vector time series model and a seasonal ARIMA model using simple methods as benchmarks. Evaluation was based on multiple time series obtained from mid-size European bank with forecasting horizons of up to 28 days. Forecasting accuracy was measured using the mean absolute percentage error. Results: The seasonal ARIMA model resulted in a higher forecasting accuracy compared to the vector time series model. Variability in demand was mainly attributed to the day-of-the-week effect. Co -variability is captured by seasonality and calenda r effects limiting the potential of joint forecasting . Cumulative forecasts for periods of 14 days are v ery robust with mean percentage errors of approximately two percent. Conclusion: The results confirmed the benefit of advanced forecasting techniques for daily forecasts. However, the study suggested that the role of information sharing is limited to coord ination of replenishments across the cash supply chain and does not yield more accurate forecasts ba sed on joint forecasting.
Rolling bearing fault identification using multilayer deep learning convolutional neural network

The vibration signal of rolling bearing is usually complex and the useful fault information is hidden in the background noise, therefore, it is a challenge to identify rolling bearing faults from the complex vibration environment. In this paper, a novel multilayer deep learning convolutional neural network (CNN) method to identify rollings bearing fault is proposed. Firstly, in order to avoid the influence of different characteristics of the input data on the identification accuracy, a normalization preprocessing method is applied to preprocess the vibration signals of rolling bearings. Secondly, a multilayer CNN based on deep learning is designed in this paper to improve the fault identification accuracy of rolling bearing. Simulation data and experimental data analysis results show that the proposed method has better performance than SVM method and ANN method without any manual feature extractor design.
Quantum error correction via robust probe modes

We propose a scheme for quantum error correction using robust continuous variable probe modes, rather than fragile ancilla qubits, to detect errors without destroying data qubits. The use of such probe modes reduces the required number of expensive qubits in error correction and allows efficient encoding, error detection, and error correction. Moreover, the elimination of the need for direct qubit interactions significantly simplifies the construction of quantum circuits. We will illustrate how the approach implements three existing quantum error correcting codes: the three-qubit bit-flip (phase-flip) code, the Shor code, and an erasure code.
Systematic Design of Attitude Control Systems for a Satellite in a Circular Orbit with Guaranteed Performance and Stability

In this paper two nonlinear control techniques are developed and compared for the satellite attitude control problem. The first technique is a robust recursive nonlinear method using Euler angle formulation. This method is related to integrator backstepping as well as feedback linearization techniques. However, in this paper a different formulation is presented which overcomes some of the previous difficulties in applying backstepping to this problem by treating the three axis satellite system as a fully coupled set of second order systems. The technique produces a robustly stable controller, which meets desired performance, accounts for system nonlinear behavior, and is easily implementable in a set of feedback equations that can be computed in real time. The second technique is a learning control that updates the control input iteratively in order to enhance the transient performance of systems that are repeatedly executed over a fixed finite duration. It updates the control input by learning laws without the computation of system parameters and inverse dynamics of systems. The advantage of utilizing learning control schemes for attitude control systems is the enhancement of transient performance from trial to trial by taking advantage of the periodicity of the repeated system operation. By learning unknown parameters or time functions, the learning control can compensate nonlinear dynamics so that the desired performance can be achieved. The performance of both techniques is demonstrated for a satellite attitude tracking maneuver which represents a satellite in a circular orbit maintaining one face toward the earth while tracking simultaneous sinusoidal pointing commands in the other two axes. It is shown that the recursive controller provides the desired tracking performance with reasonable control effort, and that the learning control technique can be used to compensate for periodic external disturbances. Corresponding author, Coleman Aerospace Company, 7675 Municipal Drive, Orlando, Florida 32819 tel: (407) 354-0047, fax: (407) 354-1113, e-mail: Richard_Hull@mail.crc. com Florida Space Institute / Department of Mechanical, Materials and Aerospace Engineering, University of Central Florida, Orlando, Florida Reference No: SSC00-VIII-5 Session: VIII (Advanced Subsystems & Components 1) 2
New Spectrophotometric Method for the Determination of Desloratadine in Pharmaceutical Formulations

An Economic, precise, accurate, sensitive and simple spectrophotometric method developed for the quantitative estimation of desloratadine in pharmaceutical formulations. The method was based on the formation of ferric chloride and potassium ferricyanide, which forms a coloured chromgen exhibit the absorbance at λmax 710 nm and obeyed Beer’s law in the concentration ranges 1-5 µg/mL. Spectrophotometric parameters were established for standardization of the method including statistical analysis of data. The method has been successfully extended to the Pharmaceutical formulations
Intangible Capital and U.S. Economic Growth

Published macroeconomic data traditionally exclude most intangible investment from measured GDP. This situation is beginning to change, but our estimates suggest that as much as $800 billion is still excluded from U.S. published data (as of 2003), and that this leads to the exclusion of more than $3 trillion of business intangible capital stock. To assess the importance of this omission, we add intangible capital to the standard sources-of-growth framework used by the BLS, and find that the inclusion of our list of intangible assets makes a significant difference in the observed patterns of U.S. economic growth. The rate of change of output per worker increases more rapidly when intangibles are counted as capital, and capital deepening becomes the unambiguously dominant source of growth in labor productivity. The role of multifactor productivity is correspondingly diminished, and labor's income share is found to have decreased significantly over the last 50 years.
ASSESSING THE DEVELOPMENT OF SHOREBIRD EGGS USING THE FLOTATION METHOD: SPECIES-SPECIFIC AND GENERALIZED REGRESSION MODELS

Abstract ABSTRACT We modeled the relationship between egg flotation and age of a developing embryo for 24 species of shorebirds. For 21 species, we used regression analyses to estimate hatching date by modeling egg angle and float height, measured as continuous variables, against embryo age. For eggs early in incubation, we used linear regression analyses to predict hatching date from logit-transformed egg angles only. For late incubation, we used multiple regression analyses to predict hatching date from both egg angles and float heights. In 30 of 36 cases, these equations estimated hatching date to within four days of the true hatching date for each species. After controlling for incubation duration and egg size, flotation patterns did not differ between shorebirds grouped by mass (≥100 g or <100 g) or taxonomy (Scolopacidae versus Charadriidae). Flotation progressed more rapidly in species in which both adults incubate the clutch versus species in which only one adult incubates the clutch, although this did not affect prediction accuracy. We also pooled all continuous data and created a generalized regression equation that can be applied to all shorebird species. For the remaining three species, we estimated hatching date using five float categories. Estimates of hatching date using categorical data were, overall, less accurate than those generated using continuous data (by 3%–5% of a given incubation period). Our equations were less accurate than results reported in similar studies; data collected by multiple observers and at multiple sites, as well as low sample sizes for some species, likely increased measurement error. To minimize flotation method prediction error, we recommend sampling in early incubation, collecting both egg angle and float height data in late incubation, and developing site- and species-specific regression models where possible.