Miracle-dz/UniFAR-FTUs huggingface dataset:
Small Ruminant Production System Efficiency under Abu-Dhabi, United Arab Emirates Arid Land Conditions

Sheep and goat production systems in the United Arab Emirates (UAE) operate under scarce natural resource constraints. A cross-sectional survey that covered 661 mixed farms, including major sheep and goat production, was conducted in the three regions of Abu Dhabi Emirate (Al-Ain, Western Region and Abu Dhabi city) during 2012. A Cobb-Douglas, double-logarithmic stochastic frontier production function and maximum likelihood estimation were applied to estimate important economic derivatives and the associated risk of small ruminant production in this arid area. The highest impact of an input on the output level was found to be labor for raising sheep and alfalfa grass for raising goats. Both labor and alfalfa variables were found to be overutilized for sheep and goat production, respectively. Overall, the results indicate that average technical efficiency is 0.62 for raising sheep and only 0.34 for raising goats in the study area. Technical efficiency analysis included measuring the frequency of farms at each level of estimated technical efficiency in the range between zero and one. Zero for the technical efficiency coefficient indicates a lack of technical efficiency in resource use. The results of this study indicated that only 1% of the sheep farms show a technical efficiency coefficient of 0.25 or less; the same can be said for 41% of goat producers. However, these technical efficiencies were found to be more than 0.75 for 12% and 5% of the sheep and goat farms, respectively. Overall, goat farming in the UAE was found to be less efficient than sheep production. The results also indicated that flock size and type of breed were the most influential factors relative to other factors, and both show a positive relationship with technical efficiency. Other than flock size, factors, such as owners’ years of experience and management practices, were found to be more influential on goat farming system efficiency relative to sheep farming.
Stationary Deterministic Policies for Constrained MDPs with Multiple Rewards, Costs, and Discount Factors

We consider the problem of policy optimization for a resource-limited agent with multiple time-dependent objectives, represented as an MDP with multiple discount factors in the objective function and constraints. We show that limiting search to stationary deterministic policies, coupled with a novel problem reduction to mixed integer programming, yields an algorithm for finding such policies that is computationally feasible, where no such algorithm has heretofore been identified. In the simpler case where the constrained MDP has a single discount factor, our technique provides a new way for finding an optimal deterministic policy, where previous methods could only find randomized policies. We analyze the properties of our approach and describe implementation results.
How a consumer can measure elasticity for cloud platforms

One major benefit claimed for cloud computing is elasticity: the cost to a consumer of computation can grow or shrink with the workload. This paper offers improved ways to quantify the elasticity concept, using data available to the consumer. We define a measure that reflects the financial penalty to a particular consumer, from under-provisioning (leading to unacceptable latency or unmet demand) or over-provisioning (paying more than necessary for the resources needed to support a workload). We have applied several workloads to a public cloud; from our experiments we extract insights into the characteristics of a platform that influence its elasticity. We explore the impact of the rules used to increase or decrease capacity.
Synthesis, Characterization and Biological Studies of Metal(II) Complexes of (3E)-3-[(2-{(E)-[1-(2,4-Dihydroxyphenyl)ethylidene]amino}ethyl)imino]-1-phenylbutan-1-one Schiff Base

Co(II), Ni(II), Zn(II) and Cu(II) complexes of (3E)-3-[(2-{(E)-[1-(2,4-dihydroxyphenyl)ethylidene]amino}ethyl)imino]-1-phenylbutan-1-one (DEPH2) derived from ethylenediamine, 2′,4′-dihydroxyacetophenone and 1-phenylbutane-1,3-dione have been synthesized and characterized by elemental analysis, FTIR, UV-Visible spectroscopy, and screened to establish their potential as antibacterial agents, antioxidants and DPPH radical scavengers. The FTIR spectra showed that the ligand behaves as a dibasic tetradentate ligand with the dioxygen-dinitrogen donor atom system oriented towards the central metal ion. The analytical and spectroscopic data suggest a square planar geometry for Cu(II) and Ni(II) complexes and an octahedral geometry for the Co(II) complex. The ligand and their metal complexes were screened for antibacterial activity against Gram (+) and Gram (−) bacteria by the agar well diffusion method. In addition, the antioxidant activities of the complexes were also investigated through their scavenging effect on DPPH and ABTS radicals. The obtained IC50 value of the DPPH activity for the copper complex (2.08 ± 0.47 µM) and that of the ABTS activity for the copper complex (IC50 = 2.11 + 1.69 µM) were higher than the values obtained for the other compounds.
Volatility time Option Price Call Black Scholes Response Option Price Call Black Scholes Result Option Price Delta Call Black

In this work we provide an initial analysis of service categorization, the process of associating services with ontologies. Service categorization is an important pre-processing step to tasks such as service composition. The absence of semantic understanding of services may yield erroneous compositions and therefore, service categorization can assist in determining the correctness of a composition. We analyze two common methods for text processing, TF/IDF and context analysis. We also test two types of service description, textual and WSDL. Our initial results indicate that context analysis is more useful than TF/IDF and that WSDL description provides better categorization than textual description.
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets

In this paper, we consider the problem of predicting demographics of geographic units given geotagged Tweets that are composed within these units. Traditional survey methods that offer demographics estimates are usually limited in terms of geographic resolution, geographic boundaries, and time intervals. Thus, it would be highly useful to develop computational methods that can complement traditional survey methods by offering demographics estimates at finer geographic resolutions, with flexible geographic boundaries (i.e. not confined to administrative boundaries), and at different time intervals. While prior work has focused on predicting demographics and health statistics at relatively coarse geographic resolutions such as the county-level or state-level, we introduce an approach to predict demographics at finer geographic resolutions such as the blockgroup-level. For the task of predicting gender and race/ethnicity counts at the blockgroup-level, an approach adapted from prior work to our problem achieves an average correlation of 0.389 (gender) and 0.569 (race) on a held-out test dataset. Our approach outperforms this prior approach with an average correlation of 0.671 (gender) and 0.692 (race).
Menthol-Induced Ca2+ Release from Presynaptic Ca2+ Stores Potentiates Sensory Synaptic Transmission

Menthol and many of its derivatives produce profound sensory and mental effects. The receptor for menthol has been cloned and named cold- and menthol-sensitive receptor-1 (CMR1) or transient receptor potential channel M8 (TRPM8) receptor. Using a dorsal root ganglion (DRG) and dorsal horn (DH) coculture system as a model for the first sensory synapse in the CNS, we studied menthol effects on sensory synaptic transmission and the underlying mechanisms. We found that menthol increased the frequency of miniature EPSCs (mEPSCs). The effects persisted under an extracellular Ca2+-free condition but were abolished by intracellular BAPTA and pretreatment with thapsigargin. Menthol-induced increases of mEPSC frequency were blocked by 2-aminoethoxydiphenylborane (2-APB) but not affected by the phospholipase C inhibitor U73122 or by the cADP receptor inhibitor 8-bromo-cADPR (8Br-cADPR). Double-patch recordings from DRG-DH pairs showed that menthol could potentiate evoked EPSCs (eEPSCs) and change the paired-pulse ratio of eEPSCs. A Ca2+ imaging study on DRG neurons demonstrated that menthol could directly release Ca2+ from intracellular Ca2+ stores. Menthol-induced Ca2+ release was abolished by 2-APB but not affected by U73122 or 8Br-cADPR. Taken together, our results indicate that menthol can act directly on presynaptic Ca2+ stores of sensory neurons to release Ca2+, resulting in a facilitation of glutamate release and a modulation of neuronal transmission at sensory synapses. Expression of TRPM8 receptor on presynaptic Ca2+ stores, a novel localization for this ligand-gated ion channel, is also strongly suggested.
Measuring the Genotype Diversity of Evolvable Neural Networks

Studying the diversity of genetic algorithms is the most important topic to prevent the problem of premature convergence of the population. In general diversity study can be divided into, measuring diversity of the population and maintaining the diversity of the population. This paper is interested in measuring the diversity. Measuring population diversity can be categorised into genotype diversity measure and phenotype diversity measure. Most of the previous research was devoted to measure diversity of genetic programming and genetic algorithms in general. The present paper introduces a dedicated study to measure and analyse the genotype or structure diversity of evolvable neural networks. A new metric is introduced to measure the genotype diversity of evolvable neural networks based on genetic operations required to transform one neural network to another one. This method is called neuro-edit, it is inspired on edit distance measure and genetic operations used to evolve neural networks. This metric measures the distance between neural networks in terms of connection genes addition, deletion, and substitution.
MINT: a front end for efficient simulation of shared-memory multiprocessors

MINT is a software package designed to ease the process of constructing event-driven memory hierarchy simulators for multiprocessors. It provides a set of simulated processors that run standard Unix executable files compiled for a MIPS R3000 based multiprocessor. These generate multiple streams of memory reference events that drive a user-provided memory system simulator. MINT uses a novel hybrid technique that exploits the best aspects of native execution and software interpretation to minimize the overhead of processor simulation. Combined with related techniques to improve performance, this approach makes simulation on uniprocessor hosts extremely efficient. <<ETX>>
Compositional specification of event-based software architectural styles

Architectural style constitutes a mean to put in practice design approaches based on pattern refinement, adaptation and reuse. Our objective is to support such approaches. In this work, we focus on real-life architectural styles and more particularly on the event-based style. We provide a set of basic styles and we describe a formal approach to specify them and to compose them to generate more complex patterns. In this way, we help the architect to design correct and elaborated architectural styles that can serve as a starting point for a more correct and successful refinement process.
Assessment of Basic Fitness Related Performance Components between Three Essential Co-Curriculum Units of University Sultan Zainal Abidin Malaysia

Uniform arm units are set up to serve as the first line defence and to assist the university members for any emergency that might arise. To discharge their duties effectively, they need to meet up to the requirement of highest physical fitness level. This study aims to examine the physical fitness levels among armed uniform package unit of UniSZA and to investigate the components that distinguish their level of physical fitness. A total of 120 participants within the age range of (±20.45) male and (±20.63) female took part in this study 60 from each group. Standard physical fitness tests were conducted, and Multivariate Analysis of Variance (MANOVA) was used to analyse their performance on the physical fitness with the performance of physical fitness as the dependent variable (DV), while the categories of the uniform units as the independent variables (IV). Pairwise Comparison follow-up test was conducted to determine the significant parameters that differentiate the groups. The finding shows that there is a significant difference in the performance of physical fitness tests for both male and female F (20, 98) = 1.68, p
How to make ad-hoc polymorphism less ad hoc

This paper presents type classes, a new approach to ad-hoc polymorphism. Type classes permit overloading of arithmetic operators such as multiplication, and generalise the “eqtype variables” of Standard ML. Type classes extend the Hindley/Milner polymorphic type system, and provide a new approach to issues that arise in object-oriented programming, bounded type quantification, and abstract data types. This paper provides an informal introduction to type classes, and defines them formally by means of type inference rules.
NBER WORKING PAPER SERIES ENDOGENOUS SKILL ACQUISITION AND EXPORT MANUFACTURING IN MEXICO

This paper presents empirical evidence that the growth of export manufacturing in Mexico during a period of major trade reforms, the years 1986-2000, altered the distribution of education. I use variation in the timing of factory openings across commuting zones to show that school dropout increased with local expansions in export manufacturing. The magnitudes I find suggest that for every twenty-five jobs created, one student dropped out of school at grade 9 rather than continuing through to grade 12. These effects are driven by less-skilled export-manufacturing jobs which raised the opportunity cost of schooling for students at the margin. David Atkin Department of Economics MIT 77 Massachusetts Avenue E19-750 Cambridge, MA 02139 and NBER atkin@mit.edu
Competition and Technical Progress in Marx : Two Different Perspectives

Competition and Technical Progress in Marx: Two Different Perspectives Maria Daniela Giammanco University of Catania (ITALY)-Facoltà di Scienze Politiche Dipartimento di Analisi dei Processi Politici, Sociali e Istituzionali Starting from Marx's twofold idea of competition, this work focuses on the two different but consistently interrelated ways in which it is possible to envisage technical progress in Marx's work. During the emergence of capitalism, competition is a negative force, leading to the destruction of pre-capitalistic modes of production, therefore technical progress can be seen as supporting capital in establishing complete command over labour. In a fully developed capitalistic society, competition is a process allowing the development and reproduction of the capitalistic mode of production, and technical progress is a powerful instrument in the struggle among capitals.
The marginalized likelihood ratio test for detecting abrupt changes

The generalized likelihood ratio (GLR) test is a widely used method for detecting abrupt changes in linear systems and signals. In this paper the marginalized likelihood ratio (MLR) test is introduced for eliminating three shortcomings of GLR while preserving its applicability and generality. First, the need for a user-chosen threshold is eliminated in MLR. Second, the noise levels need not be known exactly and may even change over time, which means that MLR is robust. Finally, a very efficient exact implementation with linear in time complexity for batch-wise data processing is developed. This should be compared to the quadratic in time complexity of the exact GLR.
Portfolio optimization with Markov-modulated stock prices and interest rates

A financial market with one bond and one stock is considered where the risk free interest rate, the appreciation rate of the stock and the volatility of the stock depend on an external finite state Markov chain. We investigate the problem of maximizing the expected utility from terminal wealth and solve it by stochastic control methods for different utility functions. Due to explicit solutions it is possible to compare the value function of the problem to one where we have constant (average) market data. The case of benchmark optimization is also considered.
Passive Immunization Reduces Behavioral and Neuropathological Deficits in an Alpha-Synuclein Transgenic Model of Lewy Body Disease

Dementia with Lewy bodies (DLB) and Parkinson's Disease (PD) are common causes of motor and cognitive deficits and are associated with the abnormal accumulation of alpha-synuclein (α-syn). This study investigated whether passive immunization with a novel monoclonal α-syn antibody (9E4) against the C-terminus (CT) of α-syn was able to cross into the CNS and ameliorate the deficits associated with α-syn accumulation. In this study we demonstrate that 9E4 was effective at reducing behavioral deficits in the water maze, moreover, immunization with 9E4 reduced the accumulation of calpain-cleaved α-syn in axons and synapses and the associated neurodegenerative deficits. In vivo studies demonstrated that 9E4 traffics into the CNS, binds to cells that display α-syn accumulation and promotes α-syn clearance via the lysosomal pathway. These results suggest that passive immunization with monoclonal antibodies against the CT of α-syn may be of therapeutic relevance in patients with PD and DLB.
When Should Leaders Share Information with their Subordinates?

We show that when leaders share some of their information with subordinates, decision making is subject to a motivational bias; leaders make the decisions their subordinates want to see. As this bias increases with the quality of the shared information, an improvement of an organization's information might even decrease its efficiency. As a consequence, information sharing is not always optimal. We show however that self-confidence can help the leader to overcome his motivational bias, thus making information sharing more attractive. Conversely, we find that information sharing can help to curb the autocratic tendencies of a self-confident leadership. We conclude that a policy of information sharing and the appointment of a self-confident leadership are most effective when they go hand in hand.
Exploiting Run-Time Information for Efficient Processing of Queries

Information agents answer user queries using a large number of diverse information sources. The key issue in their perfomance is finding the set of information sources relevant to a query. Previous work has considered determining relevance soley based on compile-time analysis of the query. We argue that at compile-time, it is often not possible to significantly prune the set of sources relevant to a query, and that run-time information is needed. We make the following contributions. First, we identify the different types of information that can be obtained at run-time, and how they can be used to prune information sources. Second, we describe an algorithm which naturally extends query planning algorithms to exploit run-time information. Third, we describe the discrimination matrix, which is a data structure that identifies the information that can be used to help discriminate between different possible sources.
Recommending topics for self-descriptions in online user profiles

Traditional social networking sites allow users to enter responses to a set of predefined fields when populating their personal profiles. In the system discussed in this work, freeform 'About You' entries allow users to craft their own questions / topics. We found that this kind of flexibility often leads to low content contributions and infrequent updates. The 'About You' recommender system described in this paper differs from many recommender systems in that it recommends content for users to create, rather than consume. We present empirical data from an experiment with 2,000 users of a social networking site during a one month period. Our findings suggest that users who receive recommendations create more entries and update them more over time. Further, using articulated social network information for recommendations performed better than content-based matching.
Load Balanced and Constant Stretch Hole Bypassing Protocol for Wireless Sensor Networks

Recent years have witnessed the emergence of wireless sensor networks (WSNs) which consist of tiny sensor nodes deployed over a region of interest to monitor and control the physical environment. Wireless sensor networks have been widely used in various domains such as military target tracking and surveillance, natural disaster relief, agricultural and environmental monitoring, biomedical health monitoring, etc. In this dissertation, we focus on large-scale WSNs which are based on the cooperation of a large number of sensor nodes. Typically, large-scale WSNs are used in monitoring applications such as agricultural monitoring, climate monitoring, forest monitoring, weather monitoring, etc. Due to the short-range communication nature of sensor nodes, data transfer in WSNs is usually performed in the multi-hop communication paradigm. Hence, routing becomes one of the most important issues which has received intensive research attention. As sensor nodes are equipped with only limited and non-rechargeable batteries, conserving energy consumption is an important factor in designing routing protocol. Energy conservation can be achieved by shortening the routing path and reducing the overhead caused by control packets. In many applications, the network can’t achieve its objective if all the nodes can’t sense or report the sensed data, thus the death of even only one node may cause the network to operate un-functionally. Accordingly, balancing traffic over the network to extend the network lifetime is another important designing factor of routing protocol in WSNs. Geographic routing has been widely used in wireless sensor networks because of its simplicity and efficiency resulted from its local and stateless nature. However, when subjected to routing holes (i.e., regions without sensor nodes that have communication capability), geographic routing suffers from the so-called local minimum phenomenon, where packets are stopped at the hole boundaries. The traditional scheme (named as
Adaptation of Bayesian Models for Single-Channel Source Separation and its Application to Voice/Music Separation in Popular Songs

Probabilistic approaches can offer satisfactory solutions to source separation with a single channel, provided that the models of the sources match accurately the statistical properties of the mixed signals. However, it is not always possible to train such models. To overcome this problem, we propose to resort to an adaptation scheme for adjusting the source models with respect to the actual properties of the signals observed in the mix. In this paper, we introduce a general formalism for source model adaptation which is expressed in the framework of Bayesian models. Particular cases of the proposed approach are then investigated experimentally on the problem of separating voice from music in popular songs. The obtained results show that an adaptation scheme can improve consistently and significantly the separation performance in comparison with nonadapted models.