Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Consumption- Growth Nexus in SAARC Countries: Using Cointegration and Error Correction Model

The paper explores the nexus between energy consumption (oil and electricity) and economic growth in the five SAARC countries over the period 1970-2006. Using cointegration and Error Correction Model (ECM), the paper finds a unidirectional short run and long run causality from oil consumption to economic growth in Bangladesh and Nepal, a unidirectional short run and long run causality from electricity consumption to economic growth in Pakistan and Sri Lanka, a unidirectional short run and long run causality from economic growth to oil consumption in India and Sri Lanka, and a unidirectional causality from economic growth to electricity consumption in India and Nepal. It also finds the bidirectional causality between electricity consumption and economic growth in Bangladesh and between oil consumption and economic growth in Pakistan. The paper at the end suggests that energy and environmental policies should recognize the differences in the energy consumption-growth nexus in order to maintain sustainable economic growth in the region.
Content Based Image Retrieval System using K-means and KNN approach by Feature Extraction

The last decade is evidenced that there is a great interest in research on contentbased image retrieval (CBIR). This has paved the way for a large number of new techniques and systems, and a growing interest in associated fields to support such systems. There are different system designs for content based image retrieval (CBIR) system. This paper propose a novel system architecture for CBIR system which combines techniques include content-based image and color analysis, as well as data mining techniques. To our best knowledge, this is the first time to propose segmentation and grid module, feature extraction module, K-means and k-nearest neighbor clustering algorithms and bring in the neighborhood module to build the CBIR system. Concept of neighborhood color analysis module which also recognizes the side of every grids of image is first contributed in this paper. The results show the CBIR systems performs well in the training and it also indicates there contains many interested issue to be optimized in the query stage of image
Targeting, bias, and expected impact of complex innovations on developing‐country agriculture: evidence from Malawi

Agronomic analyses of new technologies are often conducted under carefully controlled research station programs or trials managed by self-selected farmers. Oftentimes, the technologies are then scaled up with minimal evaluation under real-world conditions. Yet, the interim step between agronomic trials and large-scale promotion is crucial to generate evidence on the social and economic impact of technologies that is both internally valid and generalizable. The article focuses on a participatory action research program in Malawi designed to test and identify scalable technology options to intensify the smallholder sector and contribute to poverty reduction and food and nutrition security. We examine the socioeconomic characteristics of farmers testing technologies and find evidence of systematic targeting of better-endowed farmers. After controlling for observable differences using matching and a doubly robust estimator, we find evidence of early positive effects on maize yield and harvest value, although placebo tests suggest possible selection on unobservables. We note that attention should be given to program design and household characterization to better define and improve targeting criteria, technology selection, and external validity.
Power transfer in non-linear gravitational clustering and asymptotic universality

We study the non-linear gravitational clustering of collisionless particles in an expanding background using an integro-differential equation for the gravitational potential. In particular, we address the question of how the non-linear mode‐mode coupling transfers power from one scale to another in the Fourier space if the initial power spectrum is sharply peaked at a given scale. We show that the dynamical equation allows self-similar evolution for the gravitational potential φ k(t) in Fourier space of the form φ k(t) = F(t)D(k) where the function F(t) satisfies a second-order non-linear differential equation. We analyse the relevant solutions of this equation, thereby determining the asymptotic time evolution of the gravitational potential and density contrast. The analysis suggests that both F(t) and D(k) have well-defined asymptotic forms indicating that the power transfer leads to a universal power spectrum at late times. The analytic results are compared with numerical simulations, showing good agreement over the range at which we could test them.
Distinguishing dynamics of dissolved organic matter components in a forested stream using kinetic enrichments

Traditional methods for investigating stream solute biogeochemistry measure longitudinal rates of uptake by increasing either the concentration or isotopic composition of solutes. These methods cannot be applied to dissolved organic matter (DOM) because we cannot replicate the heterogeneous native DOM pool. We explored an alternative approach, attempting to displace or enhance benthic uptake of native DOM by supplying an exogenous source of labile carbon or by enriching the stream with inorganic nitrogen. This approach allows us to measure uptake rates of enriched solutes, as well as changes in the concentration and composition of native DOM resulting from the experimental manipulations. We examined DOM composition using fluorescence characterization. We were able to elicit changes in the chemical composition of native DOM by differentially altering the dynamics of autotrophic production and heterotrophic uptake within the second‐order reach of Walker Branch, a well‐studied stream in eastern Tennessee. Supplying heterotrophs with labile carbon resulted in an increase in fluorescence associated with terrestrially derived DOM. Stimulating algae by adding inorganic nitrogen increased autochthonous production and indirectly displaced heterotrophic demand for terrestrial DOM due to increased in‐stream production of bioavailable DOM. While we were able to alter the composition of the native DOM pool, we observed little change in DOM concentrations. The ability to differentiate between DOM subcomponents provides insight into processes controlling DOM production and consumption that cannot be gained by treating DOM as a single bulk pool.
The role of muscle in disease-related malnutrition . Decalogue of Good Practices

José Manuel García Almeida, Helena Bascuñana Ambrós, Nicolás Terrados, Rebeca Sanz Barriuso, José María López Pedrosa, Nefertiti Campos Gorgona, Daniel de Luis Román 1 Endocrinología y Nutrición, Hospital Virgen de la Victoria, Campus de Teatinos, Málaga, Spain E-mail: jgarciaalmeida@ gmail.com; 2 Medicina física y rehabilitación, Hospital Universitario Sant Pau, Barcelona, Spain; 3 Unidad Regional de Medicina Deportiva del Principado de Asturias y Dpto de Biología Funcional de la Universidad de Oviedo, Complejo Deportivo Avilés, Avilés, Asturias, Spain; 4 Abbott Nutrition Medical Affairs, Madrid, Spain; 5 Abbott Nutrition R&D, Discovery, Granada, Spain; 6 Abbott Nutrition Partner Developer, Singapore; 7 Centro de Investigación de Endocrinología y Nutrición Clínica Facultad de Medicina, Servicio de Endocrinología y Nutrición Hospital Clínico Valladolid, Valladolid, Spain
CRANIOFACIAL AGING

Face recognition is one of the most favored techniques used in the field Q1 of biometrics. Despite many of the advanced methods that have been developed, face recognition is still challenged by many factors such as illumination, pose, and other real-world conditions such as a temporal difference in training and classification data (mainly images). As such, normal adult aging is an important factor to be considered in the development and evaluation of face-recognition systems. To date, little progress has been made in developing techniques that are robust to age-progression in individuals. Two of the main reasons for minimal development in this area are an incomplete understanding of the factors that influence the changing appearance of the face during aging and a lack of relevant longitudinal face corpora required for development and evaluation. This article provides a summary understanding of the factors and process innate to craniofacial morphology of the face during the period of adult aging and also reviews recent biometric-related work on aging of the human face. Additionally, this work can be used to inform practitioners who conduct human-based analysis on longitudinal face images for identity verification.
Thermal emission spectroscopy of microcrystalline sedimentary phases: Effects of natural surface roughness on spectral feature shape

Distinguishing between microcrystalline and macrocrystalline mineral phases can help constrain the conditions under which those minerals formed or the degree of postdepositional alteration. This study demonstrates the effects of crystal size and surface roughness on thermal infrared emission spectra of micro and macrocrystalline phases of the two most common minerals on Earth, quartz and calcite. Given the characteristic depositional and environmental conditions under which microcrystalline minerals form, and the recent observations of high‐silica deposits on Mars, it is important to understand how these unique materials can be identified using remote infrared spectroscopy techniques. We find that (a) microcrystalline minerals exhibit naturally rough surfaces compared to their macrocrystalline counterparts at the 10 µm scale; and that (b) this roughness causes distinct spectral differences within the Reststrahlen bands of each mineral. These spectral differences occur for surfaces that are rough on the wavelength scale, where the absorption coefficient (k) is large. Specifically, the wavelength positions of the Reststrahlen features for microcrystalline phases are narrowed and shifted compared to macrocrystalline counterparts. The spectral shape differences are small enough that the composition of the material is still recognizable, but large enough such that a roughness effect could be detected. Petrographic and topographic analyses of microcrystalline samples suggest a relationship between crystal size and surface roughness. Together, these observations suggest it may be possible to make general inferences about microcrystallinity from the thermal infrared spectral character of samples, which could aid in reconstructions of sedimentary rock diagenesis where corresponding petrographic or microimaging is not available.
GROWTH AND VARIABILITY OF STATE INDIVIDUAL INCOME AND GENERAL SALES TAXES

Two important characteristics of state tax systems are the trend growth rate and cyclical variability of tax revenues. We use national aggregate time series data to estimate the trend rate of growth and the deviation from trend for several components of state general sales and individual income tax bases. The results indicate great variety in growth and variability characteristics across tax base components. One important finding is that growth and variability are sometimes inversely related. Another interesting finding is that, depending on structural design, income taxes can be more stable than sales taxes.
Precautionary Pulp: Pulp Mills and the Evolving Dispute between International Tribunals over the Reach of the Precautionary Principle

While the term "precautionary principle" is much used, its status, its applicability, and even its definition are not clear. The International Tribunal for the Law of the Sea has applied the precautionary principle in environmental cases. The World Trade Organization has refused to apply the principle, but, in dicta, has suggested that it should be applied in environmental cases. The International Court of Justice has traditionally been reticent on the issue. However, in its recent Pulp Mills decision, the court strongly limited, if not eviscerated, the principle. The court did not allow the precautionary principle to reverse the burden ofproof or even to affect the standards ofproof
Ontology Based Image Recognition : A Review

Due to lack of domain knowledge about the semantics of the image, image retrieval rate is usually unsatisfying. To improve this, image labels must be provided by the author of the dataset. Applying ontology in digital image recognition to extract relevant information such as timeline, features, visualization to help understand and interpret it, so that we can focus on the most relevant information.
Explaining the persistence of low income and environmentally degrading land uses in the Brazilian Amazon

Tropical forests continue to be plagued by the dual sustainability challenges of deforestation and rural poverty. We seek to understand why many of the farmers living in the Brazilian Amazon, home to the world’s largest tropical agricultural-forest frontier, persist in agricultural activities associated with low incomes and high environmental damage. To answer this question, we assess the factors that shape the development and distribution of agricultural activities and farmer well-being in these frontiers. Our study utilizes a uniquely comprehensive social-ecological dataset from two regions in the eastern Brazilian Amazon and employs a novel conceptual framework that highlights the interdependencies between household attributes, agricultural activities, and well-being. We find that livestock production, which yields the lowest per hectare incomes, remains the most prevalent land use in remote areas, but many examples of high income fruit, horticulture, and staple crop production exist on small properties, particularly in peri-urban areas. The transition to more profitable land uses is limited by lagging supply chain infrastructure, social preferences, and the fact that income associated with land use activities is not a primary source of perceived life quality. Instead subjective well-being is more heavily influenced by the nonmonetary attributes of a rural lifestyle (safety, tranquility, community relations, etc.). We conclude that transitions away from low-income land uses in agricultural-forest frontiers of the Brazilian Amazon need not abandon a land-focused vision of development, but will require policies and programs that identify and discriminate households based on a broader set of household assets, cultural attributes, and aspirations than are traditionally applied. At a broader scale, access to distant markets for high value crops must be improved via investments in processing, storage, and marketing infrastructure.
Error and Generalization in Discrete Choice Under Risk

I compare the generalization ability, or out-of-sample predictive success, of four probabilistic models of binary discrete choice under risk. One model is the conventional homoscedastic latent index model—the simple logit—that is common in applied econometrics: This model is “context-free” in the sense that its error part is homoscedastic with respect to decision sets. The other three models are also latent index models but their error part is heteroscedastic with respect to decision sets: In that sense they are “context-dependent” models. Context-dependent models of choice under risk arise from several different theoretical perspectives. Here I consider my own “contextual utility” model (Wilcox 2011), the “decision field theory” model of Busemeyer and Townsend (1993) and the “Blavatskyy-Fishburn” model (Fishburn 1978; Blavatskyy 2014). In a new experiment, all three context-dependent models outperform the context-free model in prediction, and significantly outperform a linear probability model (suggested by contemporary applied practice a la Angrist and Pischke 2009) when the latent preference structure is rank-dependent utility (Quiggin 1982). All of this holds true for function-free estimations of outcome utilities and probability weights as well as parametric estimations. Preoccupation with theories of the deterministic structure of choice under risk, to the exclusion of theories of error, is a mistake.
Equivalent medium representation of fractured rock

A similarity may be found between various approaches for determining the effects of parallel fractures or aligned cracks on seismic wave propagation at wavelengths that are long compared with the scale length of the cracks. Fractures can be modeled using an empirical linear slip condition; however, natural fracture surfaces can also be simulated directly as planar distributions of small isolated areas of slip (cracks) (model 1) or, conversely, as planar distributions of imperfect interfacial contacts (model 2). An alternative is plane surfaces separated by thin continuous layers of viscous fluid or a soft material (model 3). We present analytic expressions for the fracture compliances for these three models and, using these analytic results, compute the effective compliances and stiffnesses of the fractured material. As a result, it is possible to relate the measured compliances or stiffnesses directly to the statistics of the microstructural details of a fracture, given appropriate a priori information on the fracture surfaces. The results for model 1 are equivalent to a volume distribution of cracks as studied by Hudson [1980, 1981] for small crack density; the results for model 2 are basically the same as those given by White [1983] for a packing of spheres; and finally, the results for model 3 are in agreement with those given by Backus [1962] for combinations of two constituent layers. These results can be extended to the case of nonaligned fractures and to allow for fluid flow between cracks and into a porous matrix rock. Finally, it is shown that the ratio of the normal to shear fracture compliance is a good indicator of the properties of the fracture infill.
Modeling of an Ultrasonic Transducer for Cardiac Imaging

Within Philips Research, ultrasonic transducers are integrated into the minimally invasive needles and catheters for cardiac imaging. The existing ultrasonic transducers have a low signal to noise ratio (SNR) and a low bandwidth of the received echo and, therefore, the transducer does not perform well for the cardiac imaging application. A high SNR is needed to increase penetration depth into heart tissue and an increased bandwidth is required to improve resolution. Therefore, there is a need for a model that can predict the behavior of the ultrasonic transducer. In this report, a model is developed and implemented for the complete ultrasonic measurement system. This model is used for the improvement of the design of a transducer and can also be used for design of ultrasonic transducer for various applications. Various parameters needed for the simulation are estimated experimentally. The comparison between the response of an ultrasonic transducer and obtained model indicates the high accuracy of the model to predict the behavior of an ultrasonic transducer.
Minimizing the average cost of paging under delay constraints

Efficient paging procedures help minimize the amount of bandwidth expended in locating a mobile unit. Given a probability distribution on user location, it is shown that the optimal paging strategy which minimizes the expected number of locations polled EL is to query each location sequentially in order of decreasing probability. However, since sequential search over many locations may impose unacceptable polling delay, D, optimal paging subject to delay constraints is considered. It is shown that substantial reductions in EL can be had even after moderate constraints are imposed on acceptableD (i.e., D 3). Since all methods of mobility management eventually reduce to considering a time-varying probability distribution on user location, this work should be applicable to a wide range of problems in the area. most notably those with additive cost
A method is described for the generation of multivariate stochastic climate sequences for the Berg and Breede Water Management Areas in the Western Cape province of South Africa

[1] A method is described for the generation of multivariate stochastic climate sequences for the Berg and Breede Water Management Areas in the Western Cape province of South Africa. The sequences, based on joint modeling of precipitation and minimum and maximum daily temperatures, are conditioned on annualized data, the aim being to simulate realistic variability on annual to decadal time scales. A vector autoregressive (VAR) model is utilized for this purpose and reproduces well those statistical attributes, including intervariable correlation and serial autocorrelation in individual variables, most relevant for the regional climate in this setting. The sequences incorporate nonlinear climate change trends, inferred using an ensemble of global climate models from the Coupled Model Intercomparison Project (CMIP5). Subannual variability is simulated using a block resampling scheme based on the k-nearest-neighbor approach, preserving both temporal patterns and spatial correlations. Downscaling to a network of quinary-level catchments enables distributed runoff, streamflow, and crop simulations and the assessment and integration of impacts. Final output takes the form of daily sequences, structured for driving the ACRU agrohydrological model of the University of KwaZulu-Natal, South Africa.
Automated Detection of Significant Deviations in a Spatial Position of Oil Pipelines

Selective comparison of the oil pipeline sections based upon datasets of multiple in-line inspections [1] showed that there is a significant group of sections with 3d position changed again and again after repairs. At the same time, increasing volume of in-line inspections makes it impossible to analyze a spatial position of each pipeline section over time. It provokes adapting methods of multidimensional data analysis for automating detection of significant deviations in a spatial position of the pipeline. First phase of data preparation algorithm includes checking the uniqueness headers of dataset, lack of duplicates and gaps, lack of special characters, unprintable characters and extra spaces. The second phase includes checking misses, as well as significant and rapid changes in trends. Method of detecting significant deviations in a spatial position of the oil pipeline consists of four main steps: evaluating correlation coefficients of datasets, selecting the grouping method [2], analyzing intra-group statistics and assigning compensating activities for each group of pipeline sections.
Exploring the Link between Motivation for Course-Choice and Retention in the Architectural Profession: Students’ Perspectives

Studies have identified positive links between students’ commitment to the learning process and career aspirations. This paper explored the link between students’ commitment to architectural education and their subsequent willingness to remain within the profession. A questionnaire which focused on students’ experience of architectural education, experiences in professional offices and intention to practice after graduation was administered to students on the architecture programme in a Nigerian private university in addition to earlier personal statements from the students on why they embarked on the programme. Quantitative data were analysed using descriptive statistics while qualitative data were content analysed. Results indicated a correlation between reasons for choosing architecture and decisions to practice architecture. A gradual drop in desire to practice architecture was observed at higher levels of study compared to the lower levels. To improve retention rate in professional practice, admission process should include a request for a detailed personal statement from applicants, to establish strong congruence between course/major choice and career aspirations. DOI: 10.5901/mjss.2015. v6n6s1p191