7,213 research outputs found

    Stochastic maize production technology and production risk analysis in Dadar district, East Ethiopia

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    A stochastic production technology that allows risk effects of factor inputs was estimated for maize farmers in Ethiopia. The results suggested that the promoted improved maize technology exhibits constant returns to scale whereas non-adopters use decreasing returns to scale technology. The study showed that timely planting is critical for maize yield stability among both adopters and non-adopters and suggests the importance of using oxen and higher efforts to achieve that. Nevertheless, the results showed that most of the factors under the control of the farmers do not offer powerful explanation to maize yield variability compared to natural factors such as rainfall, frost, pests and diseases.Crop Production/Industries,

    On Strong Small Loop Transfer Spaces Relative to Subgroups of Fundamental Groups

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    Let HH be a subgroup of the fundamental group π1(X,x0)\pi_{1}(X,x_{0}). By extending the concept of strong SLT space to a relative version with respect to HH, strong HH-SLT space, first, we investigate the existence of a covering map for strong HH-SLT spaces. Moreover, we show that a semicovering map is a covering map in the presence of strong HH-SLT property. Second, we present conditions under which the whisker topology agrees with the lasso topology on X~H\widetilde{X}_{H}. Also, we study the relationship between open subsets of π1wh(X,x0)\pi_{1}^{wh}(X,x_{0}) and π1l(X,x0)\pi_{1}^{l}(X,x_{0}). Finally, we give some examples to justify the definition and study of strong HH-SLT spaces.Comment: 16 page

    Analytical and finite-element study of optimal strain distribution in various beam shapes for energy harvesting applications

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    Due to the increasing demand for harvesting energy from environmental vibration, for use in self-powered electronic applications, cantilever-based vibration energy harvesting has attracted great interest from various parties and become one of the most common approaches to convert redundant mechanical energy into electrical energy. As the output voltage produces from a piezoelectric material depends greatly on the geometric shape and the size of the beam, there is a need to model and compare the performance of cantilever beams of differing geometries. This paper presents the study of strain distribution in various shapes of cantilever beams, including a convex and concave edge profile elliptical beams that have been overseen in most of the prior literature. Both analytical and finite element models are derived and the resultant strain distributions in the beam are computed based on MATLAB solver and ANSYS finite element analysis tools. An optimum geometry for a vibration-based energy harvester system is verified. Lastly, experimental results comparing the power density for a triangular and rectangular piezoelectric beams are also presented to validate the finding of the study and the claim as suggested in the literature is verified

    Chiral transition in a magnetic field and at finite baryon density

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    We consider the quark-meson model with two quark flavors in a constant external magnetic field BB at finite temperature TT and finite baryon chemical potential μB\mu_B. We calculate the full renormalized effective potential to one-loop order in perturbation theory. We study the system in the large-NcN_c limit, where we treat the bosonic modes at tree level. It is shown that the system exhibits dynamical chiral symmetry breaking, i. e. that an arbitrarily weak magnetic field breaks chiral symmetry dynamically, in agreement with earlier calculations using the NJL model. We study the influence on the phase transition of the fermionic vacuum fluctuations. For strong magnetic fields, qB5mπ2|qB|\sim5m_{\pi}^2 and in the chiral limit, the transition is first order in the entire μBT\mu_B-T plane if vacuum fluctuations are not included and second order if they are included. At the physical point, the transition is a crossover for μB=0\mu_B=0 with and without vacuum fluctuations.Comment: 11 pages. 5figs. V2: fixed a few typos and added refs. Submitted to PRD. V3: Added refs and substantial revision of tex

    Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis

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    Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for disease diagnosis, where discriminating subjects with mild cognitive impairment (MCI) from normal controls (NC) is still one of the most challenging problems. Dynamic functional connectivity (dFC), consisting of time-varying spatiotemporal dynamics, may characterize "chronnectome" diagnostic information for improving MCI classification. However, most of the current dFC studies are based on detecting discrete major brain status via spatial clustering, which ignores rich spatiotemporal dynamics contained in such chronnectome. We propose Deep Chronnectome Learning for exhaustively mining the comprehensive information, especially the hidden higher-level features, i.e., the dFC time series that may add critical diagnostic power for MCI classification. To this end, we devise a new Fully-connected Bidirectional Long Short-Term Memory Network (Full-BiLSTM) to effectively learn the periodic brain status changes using both past and future information for each brief time segment and then fuse them to form the final output. We have applied our method to a rigorously built large-scale multi-site database (i.e., with 164 data from NCs and 330 from MCIs, which can be further augmented by 25 folds). Our method outperforms other state-of-the-art approaches with an accuracy of 73.6% under solid cross-validations. We also made extensive comparisons among multiple variants of LSTM models. The results suggest high feasibility of our method with promising value also for other brain disorder diagnoses.Comment: The paper has been accepted by MICCAI201

    Early Aspects at ICSE 2007: Workshop on Aspect-Oriented Requirements Engineering and Architecture Design

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    The “Early Aspects @ ICSE’07” is the 11th workshop in the series of Early Aspects workshops [1] which focuses on aspect identification during the requirements engineering and architecture derivation activities. The specific aim of the present workshop is twofold: (a) to initiate creation of an Early Aspects application demonstration and comparisons benchmark; and (b) to solicit submission of new research

    Quantum Nonlocal Boxes Exhibit Stronger Distillability

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    The hypothetical nonlocal box (\textsf{NLB}) proposed by Popescu and Rohrlich allows two spatially separated parties, Alice and Bob, to exhibit stronger than quantum correlations. If the generated correlations are weak, they can sometimes be distilled into a stronger correlation by repeated applications of the \textsf{NLB}. Motivated by the limited distillability of \textsf{NLB}s, we initiate here a study of the distillation of correlations for nonlocal boxes that output quantum states rather than classical bits (\textsf{qNLB}s). We propose a new protocol for distillation and show that it asymptotically distills a class of correlated quantum nonlocal boxes to the value 1/2(33+1)3.0980761/2 (3\sqrt{3}+1) \approx 3.098076, whereas in contrast, the optimal non-adaptive parity protocol for classical nonlocal boxes asymptotically distills only to the value 3.0. We show that our protocol is an optimal non-adaptive protocol for 1, 2 and 3 \textsf{qNLB} copies by constructing a matching dual solution for the associated primal semidefinite program (SDP). We conclude that \textsf{qNLB}s are a stronger resource for nonlocality than \textsf{NLB}s. The main premise that develops from this conclusion is that the \textsf{NLB} model is not the strongest resource to investigate the fundamental principles that limit quantum nonlocality. As such, our work provides strong motivation to reconsider the status quo of the principles that are known to limit nonlocal correlations under the framework of \textsf{qNLB}s rather than \textsf{NLB}s.Comment: 25 pages, 7 figure

    Role of non-timber forest products in sustaining forest-based livelihoods and rural households' resilience capacity in and around protected area- a Bangladesh study

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    People in developing world derive a significant part of their livelihoods from various forest products, particularly non-timber forest products. This article attempts to explore the contribution of NTFPs in sustaining forest-based rural livelihood in and around a protected area of Bangladesh, and their potential role in enhancing households resilience capacity. Based on empirical investigation our study revealed that, local communities gather a substantial amount of NTFPs from national park despite the official restrictions. 27 percent households of the area received at least some cash benefit from the collection, processing and selling of NTFPs, and NTFPs contribute as HHs primary, supplementary and emergency sources of income. NTFPs also constituted an estimated 19 percent of HHs net annual income, and were the primary occupation for about 18 percent of the HHs. HHs dependency on nearby forests for various NTFPs varied vis-a-vis their socio-economic condition as well as with their location from the park. Based on our case study the article also offers some clues for improving the situation in PA.Comment: To appear in Journal of Environmental Planning and Management, 201
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