Miracle-dz/UniFAR-FTUs huggingface dataset:
IRDDS: Instance reduction based on Distance-based decision surface

In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, which is an important task for classifiers since through this process the time for classification or training could be reduced. Instance-based learning methods are often confronted with the difficulty of choosing the instances, which must be stored to be used during an actual test. Storing too many instances may result in large memory requirements and slow execution speed. In this paper, first, a Distance-based Decision Surface (DDS) is proposed and is used as a separate surface between the classes, and then an instance reduction method, which is based on the DDS is proposed, namely IRDDS (Instance Reduction based on Distance-based Decision Surface). Using the DDS with Genetic algorithm selects a reference set for classification. IRDDS selects the most representative instances, satisfying both of the following objectives: high accuracy and reduction rates. The performance of IRDDS is evaluated on real world data sets from UCI repository by the 10-fold cross-validation method. The results of the experiments are compared with some state-of-the-art methods, which show the superiority of the proposed method, in terms of both classification accuracy and reduction percentage.
A Dynamic Model of the Housing Market ∗

We use a unique dataset linking information about buyers and sellers to the complete census of housing transactions in the San Francisco metropolitan area for a period of 15 years to examine the microfoundations of housing market dynamics. We develop a tractable model of neighborhood choice in a dynamic setting along with a computationally straightforward estimation approach. This approach allows the observed and unobserved features of each neighborhood to evolve in a completely flexible way and uses information on neighborhood choice and the timing of moves to recover semi-parametrically: (i) preferences for housing and neighborhood attributes, (ii) preferences regarding the performance of the house as a financial asset (e.g., expected appreciation, volatility), and (iii) moving costs. This model and estimation approach is potentially applicable to the study a wide set of dynamic phenomena in housing markets and cities. In this paper, we use the model to develop testable implications of housing market efficiency and in particular rational expectations on the part of home buyers. We begin by showing that when the model is restricted so that all households have identical preferences, rational expectations implies the absence of predictable returns, i.e., the absence of the positive persistence in housing prices shown in the literature following Case and Shiller (1989). Thus, as the houses considered in an analysis are closer substitutes for one another, the predictability of returns should fall to zero. We examine this hypothesis empirically by studying the dynamics of housing prices at various levels of aggregation across both geographic and ∗PRELIMINARY AND INCOMPLETE
Returns to Education Revisited and Effects of Education on Household Welfare in Nigeria

Human capital development, especially higher educational attainment attaches high premium to human skills as an important factor of production. In view of this, the objective of the study is defined in two folds; first, to revisit returns to education in Nigeria and second, to investigate effects of education on the economic welfare of households in Nigeria. The study uses Double Hurdle (DH) model and Quantile Regression (QR), respectively for the objective one and two. Thus, our findings show that returns to schooling (i.e., labour market earnings) at primary, secondary and postgraduate levels are very low relative to schooling at the tertiary education in Nigeria. Also, we find the effects of primary, secondary and postgraduate education on household economic welfare to be substantially lower compared with that of tertiary education in the country. The implication of these findings is that investment up to completing tertiary education is vital for higher welfare through increasing labour market earnings among households in Nigeria.
Rethinking the Camera Pipeline for Computer Vision

Computer vision is undergoing a revolution that is enabling new categories of visual applications for consumers, but it still incurs costs that prevent energy-strapped mobile devices from deploying these new capabilities. Part of the problem is the camera system itself: smartphone cameras and their associated signal processing hardware are designed to capture high-quality images for human consumption, not to efficiently feed a computer vision algorithm. In ongoing work, we propose to redesign the imaging systems in mobile devices from the ground up for computer vision. The key finding is that much of the work that makes up a traditional camera pipeline is unnecessary when feeding a vision algorithm. We propose a programmable design for a camera sensor and the associated image signal processor (ISP) chip that can switch into an efficient vision mode, which delivers raw signal data instead of high-quality photographs. Using experiments with both classical vision algorithms and deep convolutional neural networks, we find significant energy savings are possible with only minor degradation in vision accuracy: where humans see low-quality photographs, computer vision algorithms see usable data.
Separate measures of ATP utilization and recovery in human skeletal muscle.

1. The chemical changes during contractile activity were separated from recovery metabolism in the forearm flexor musculature in normal human subjects using 31P nuclear magnetic resonance (NMR) spectroscopy. Percutaneous, supramaximal twitch stimulation of the median and ulnar nerves was used in combination with temporary ischaemia of the forearm to characterize the summed ATPase activity. The recovery following restoration of blood flow provided a measure of oxidative ATP synthesis activity. These processes were measured based on the dynamics of creatine phosphate (PCr) content. 2. Muscle oxygen stores were depleted using ischaemia without stimulation as indicated by PCr breakdown after 250 +/‐ 33 s (mean +/‐ S.D.; n = 5), which provided a measure of the basal metabolic rate (0.008 +/‐ 0.002 mM s‐1, n = 5). 3. The PCr breakdown rate during twitch stimulation of the oxygen‐depleted muscle was constant at 1 Hz at 0.15 +/‐ 0.03 mM PCr per second or per twitch (n = 8). A constant cost per twitch was found from 0.5 to 2 Hz stimulation (depletion of PCr per twitch = 0.15 mM per twitch). 4. No net anaerobic recovery of PCr was found during a 2 min post‐stimulation ischaemia. 5. Upon restoration of blood flow, PCr recovery followed an exponential time course with a time constant of 63 +/‐ 14 s (n = 8). From these recovery rates, the capacity for oxidative phosphorylation was estimated to be 0.4 mM s‐1. 6. This experimental approach defines a non‐invasive and quantitative measure of human muscle ATPase rate and ATP synthetase rate.
Water supply system decision making using multicriteria analysis

Sound decision-making processes for investments in water supply systems need to be developed. This need arises from the problem observed in developing countries of a growing demand for water supply projects coupled with a lack of financial resources available to invest in them. A second problem is the selection of a locality that is most in need of assistance for the implementation of the water supply system. This study describes the application of multicriteria decision aid for choosing the priority city to receive a water supply system, using the ELECTRE methodology. It was found that this type of methodology accommodates the decision-making in selecting a locality, with the capacity to integrate weighted qualitative judgment criteria, incorporating the concordance and discordance indices, specifying an efficient allocation of resources available and thus maximising gains.
Finding the Edgeworth-Pareto hull and its application to optimization over the efficient set of multiple objective discrete linear programs

We propose a new algorithm for finding the Edgeworth-Pareto hull for multiple objective linear mathematical programming problems, where the constraint set is given by a finite number of points. We apply the proposed algorithm to minimizing an increasingly quasiconcave function over the efficient set by using the Edgeworth-Pareto hull in outcome space. When the cardinality of the discrete constrained set is large, one can replace this set by the vertices of its convex hull. Application to minimization problems of an increasingly quasiconcave function over the efficient set by using the Edgeworth-Pareto hull is discussed. The obtained computational results on a lot number of randomly generated problems show the efficiency of the proposed algorithm for some cases.
Efficient nonintrusive distinguisher of small nonlinear electrical loads

The work contributes to the identification of small nonlinear appliances which are hardly distinguished by existing noninvasive load monitoring methods. It improves the steady load monitoring by introducing distortion power as an additional parameter to the widely used Hart's algorithm based on measurement of active and reactive power. The results show that the method efficiently distinguishes the variety of nonlinear appliances whose usage is fast growing nowadays. Furthermore, this approach is advantageous in comparison with other approaches, which use three parameters to precisely identify the appliances, due to its simplicity. Namely, distortion power can be easily determined using only smart meters and thus no any additional measuring equipment is required.
Behavioral Modulation of Gustatory Cortical Activity

Our perception of the sensory world is constantly modulated by the environment surrounding us and by our psychological state; each encounter with the same stimulus can in fact evoke very different perceptions. This phenomenological richness correlates well with the plasticity and the state‐dependency observed in neural responses to sensory stimuli. This article reviews recent results on how the processing of sensory inputs varies depending on the internal state of the animal. Specifically it focuses on the gustatory system and on data showing that levels of attention and expectation modulate taste processing and gustatory cortical activity in meaningful ways. Mounting experimental evidence suggesting that expectation‐dependent changes in gustatory cortical activity result from changes in the coupling between the amygdala and the cortex will also be discussed. The results presented here begin to paint a complex picture of taste, which goes beyond the framework of classical coding theories.
Creating technological knowledge in vintage communities of practice

Purpose – The purpose of this paper is to show how members of a “vintage community of practice” (CoP) – the Multiple Arcade Machine Emulator (MAME) community – recombine old technological knowledge with new technological knowledge. A vintage CoP is a group of aficionados of old technology who keep using it even after superior new technologies have emerged and technological change has taken place. This paper presents mechanisms through which developers and gamers in the MAME community and its subcommunities or hubs select and recombine old and new technology to update old arcade videogames in a format that is playable on current personal computers (PCs). Design/methodological approach – An inductive single-case exploratory case study was conducted in the MAME community. Semi-structured interviews were conducted with core community members to uncover mechanisms through which old technology-related knowledge (T-RK) was combined with new T-RK to update old versions of arcade video games into software versions.
Cell surface properties and flocculation behaviour of industrial strains of Saccharomyces cerevisiae

Received 25 September, 2014 Received in revised form 20 October, 2014 Accepted 24 October, 2014 Cellular adhesion properties of yeasts depend on the characteristics of the outer layer of the cell wall. In this study, the flocculation behaviour of four industrial strains of Saccharomyces cerevisiae used for production of beer, champagne, wine and fuel alcohol was evaluated; their flocculation abilities being, 42.5, 14.8, 13.8 and 11.6%, respectively. The brewing yeast strain was found to be the most flocculent. Very little flocculation was observed during the lag and logarithmic phases of growth (1-15%), while during the early and late stationary phases, different strains exhibited variable flocculation patterns. Cell surface hydrophobicity (assayed using hydrophobicity microsphere assay (HMA) and microbial adhesion to solvent (MATS)) and surface charge (assayed by Alcian Blue dye retention) played important roles in dictating flocculation behaviour in different yeast strains, as did the yeast growth phase. Percentage hydrophobicity index (HI) and % hydrophobicity of the four strains followed, respectively the same order, viz Beer (66.6, 21.5) > Champagne (33, 10.5) > fuel alcohol (22.4, 7.4) > wine (20.5, 2.7). Our findings provide new insight into yeast cell surface properties and how these relate to behavioural characteristics of yeasts employed in industrial fermentations.
Silver nanoparticles: the powerful nanoweapon against multidrug‐resistant bacteria

In the present scenario, pharmaceutical and biomedical sectors are facing the challenges of continuous increase in the multidrug‐resistant (MDR) human pathogenic microbes. Re‐emergence of MDR microbes is facilitated by drug and/or antibiotic resistance, which is acquired way of microbes for their survival and multiplication in uncomfortable environments. MDR bacterial infections lead to significant increase in mortality, morbidity and cost of prolonged treatments. Therefore, development, modification or searching the antimicrobial compounds having bactericidal potential against MDR bacteria is a priority area of research. Silver in the form of various compounds and bhasmas have been used in Ayurveda to treat several bacterial infections since time immemorial. As several pathogenic bacteria are developing antibiotic resistance, silver nanoparticles are the new hope to treat them. This review discusses the bactericidal potential of silver nanoparticles against the MDR bacteria. This multiactional nanoweapon can be used for the treatment and prevention of drug‐resistant microbes.
Organochlorine pesticides and polychlorinated biphenyls in fin whales (Balaenoptera physalus) from the Gulf of California

The present study reports unique data on concentrations of several classes of organochlorine pesticides and polychlorinated biphenyls in blubber biopsies from healthy living fin whales (Balaenoptera physalus) from the Gulf of California, Mexico, one of the most isolated and unstudied population in the world. OC levels in this population were generally lower than levels reported in fin whales from other regions. The rank order of OCs were ∑DDTs (range from 300 to 2400 ng g−1 lw) > ∑PCBs (range from 40 to 290 ng g−1 lw) > ∑HCHs (range from
Groups in bulk synchronous parallel computing

An extension to the Bulk Synchronous Parallel Model (BSP) to allow the use of asynchronous BSP groups of processors is presented. In this model, called Nested BSP, processor groups can be divided and processors in a group synchronize through group dependent collective operations generalizing the concept of barrier synchronization. A classification of problems and algorithms attending to their parallel input-output distribution is provided. For one of these problem classes, the called common-common class, we present a general strategy to derive efficient parallel algorithms. Algorithms belonging to this class allow the arbitrary division of the processor subsets, easing the opportunities of the underlying BSP software to divide the network in independent sub networks, minimizing the impact of the traffic in the rest of the network in the predicted cost. The expressiveness of the model is exemplified through three divide and conquer programs. The computational results for these programs in six high performance supercomputers show both the accuracy of the model and the optimality of the speedups for the class of problems considered.
Low-k interconnect stack with metal-insulator-metal capacitors for 22nm high volume manufacturing

We describe interconnect features for Intel's 22nm high-performance logic technology, with metal-insulator-metal capacitors and nine layers of interconnects. Metal-1 through Metal-6 feature a new ultra-low-k carbon doped oxide (CDO) and a low-k etch stop. Metal-7 and Metal-8 use a low-k CDO. New materials and process optimization provide 13-18% capacitance improvement. Single-exposure patterning for 80nm pitch layers makes the process cost-effective.
Enhanced Antibody Lymphatic Delivery of Monoclonal Following 0 K 432 Pretreatment

KITAMURA, K. , TAKAHASHI, T. , YAMAGUCHI, T. , NOGUCHI, A. , OTSUJI, E. , TSURUMI, II. , YAMAOKA, N. , MIYAGAKI, T. and KOTANI, T. Enhanced Lymphatic Delivery of Monoclonal Antibody Following OK432 Pretreatment. Tohoku J. Exp. Med., 1993, 169 (4), 319-323 The effect of 0K432 on the lymphatic delivery of monoclonal antibody (Mab) was investigated by injecting [125I1-Mab A7 into BALB/c mice pre-treated with OK432, and measuring the radioactivity in the regional lymph nodes. The [125I]-Mab A7, when administered subcutaneously to the foot pad, preferentially accumulated in the ipsilateral popliteal and para-aortic lymph nodes. Treatment with OK432 prior to antibody injection significantly enhanced the accumulation of Mab A7 in these regional lymph nodes. These findings suggest that pretreatment with OK432 may constitute a promising method of enhancing the lymphatic delivery of Mab, and improving the efficacy of therapy directed against lymphatic malignancies. monoclonal antibody A7; OK432; lymphatic delivery
NOD / SCID / cnull mouse : an excellent recipient mouse model for engraftment of human cells

c null mice and NOD/Shi-scid mice. When human CD34 cells from umbilical cord blood were transplanted into this strain, the engraftment rate in the peripheral circulation, spleen, and bone marrow were significantly higher than that in NOD/Shiscid mice treated with anti-asialo GM1 antibody or in the 2-microglobulin– deficient NOD/LtSz-scid (NOD/SCID/ 2mnull) mice, which were as completely defective in NK cell activity as NOD/SCID/
GRFM: an efficient grid-based replication and fault tolerant middleware

Grid computing provides geographically distributed resources for large-scale complex applications which involve huge data management services. There is a need for availability, fault tolerance, scalability and high-performance in a service-oriented environment as grid. The proposed grid-based replication and fault tolerant middleware GRFM is a solution for data availability by eliminating faults in grids. GRFM is an adaptive replication grid middleware framework especially designed for high-performance applications. It enables data synchronisation between multiple heterogeneous databases located remotely in a grid. The proposed framework offers: an effective replicating strategy, mechanism to handle faulty nodes, totally ordered communication mechanism, improved membership service, hash-based replica locating service, and support for scalability and security features. GRFM reduces the system overhead by reducing the traffic in the grid and thereby improving the performance of data management for large-scale complex grid applications. Experiments are carried out on well-known grid computing tool kit Aneka Chu et al., 2007. The experimental results show that GRFM performs better when compared to universal description, discovery and integration framework UDDI lazy replication Sun et al., 2004, WS-based ring replication protocol WS-RRP Luckow and Schnor, 2008, and JGroups Ban, 1998 total ordering and group communication service approaches on real-time transaction databases.
Childhood obesity in United Arab Emirates schoolchildren: A national study

Objective: The study assessed the national prevalence of obesity among schoolchildren in the United Arab Emirates (UAE). Subjects: A stratified 10% random sample of 16 391 children was drawn from 145 492 pupils in the UAE. Methods: Height and weight were measured by physicians and trained nurses, and the body mass index (BMI; weight (kg)/height (m)2) was computed. BMIs for UAE were compared to recently published international standards. Results: Comparison of BMIs to international reference data revealed that UAE children are at increased risk for overweight (>25 kg m−2 and ≤30 kg m−2) and obesity (≥30 kg m−2). For example, 10-year-old male UAE children had 1.7 times the rate of overweight compared to international standards and 1.9 times at 18 years. Similarly, female UAE children have 1.8 times the rate of overweight compared to international standards at 10 and 18 years of age. Obesity was 2.3-fold higher among UAE males at 14 years compared to international standards, and increased to 3.6 times at 18 years of age. Among UAE female children, obesity was same as males at 14 years, 2.3 times than the international standards. At 18 years of age, UAE female obesity was 1.9-fold higher than the international standard, nearly one-half the rate of obesity among UAE males at the same age. Conclusion: The frequency of obesity among UAE youth is two to three times greater than the recently published international standard. Profound public health implications of childhood obesity for UAE children and young adults are seriously increased because of adult chronic disease processes (e.g. cardiovascular disease, diabetes) normally attendant to increased obesity rates.
SUPPORT VECTOR MACHINE AND MAXIMUM LIKELIHOOD APPROACHES TO F-MEASURE OPTIMIZATION

Most standard methods of classifying data are designed to optimize accuracy. In this thesis, we consider classifiers that are adjusted instead to optimize the F -measure, allowing a more flexible approach to classification, and in particular, providing a more reliable assessment in the presence of class imbalance. We formulate both the F -measure optimizing support vector machine with a new method of implementation, and the F -measure optimizing maximum entropy classifier, as well as adapting the latter to a new framework of uncertainty, where classes are not necessarily deterministic but observed with some noise given by a probability distribution. Our theoretical findings are put into practice on some synthetic and real-world datasets.
1 Dynamic and Long-term Linkages among Agricultural and Non-Agricultural Growth , Inequality and Poverty in Developing Countries

Drawing upon cross-country panel data for developing countries, the present study examines the role of agricultural growth in reducing inequality and poverty by modelling the dynamic linkage between agricultural and non-agricultural sectors. For this purpose, we have compared the role of agricultural growth and that of non-agricultural growth and have found that agricultural growth is more important in reducing poverty, while the negative effect of agricultural growth on inequality is found in a few models where specific definitions of inequality are adopted. Our analysis generally reinforces the case for revival of agriculture in the post-2015 discourse, contrary to the much emphasised roles of rural-urban migration and urbanisation as main drivers of growth and elimination of extreme poverty.