Yield Performance of Locally Selected Cocoa Clones in North Luwu

Participatory selection in North Luwu District selected some locally cocoa clones, of which MCC 01 and MCC 02 the most promising to be developed as clonal material. This research has objectives to observe the stability performance of yield of these clones that enable be characterized of the potency as the basis for recommendation. Observation were carried out in 35 selected-farms be differentiated according to clone\u27s type, namely MCC 01, MCC 02 and Sulawesi 01 (control) and the year of planting (age). These farms were establised at the main area of cocoa in North Luwu. The assessed variables were the number of pod, yield components, the resistance to cocoa pod borer (CPB), vascular-streak dieback (VSD) and phytophthora pod rot (PPR). Data were recorded through 20 sampled-trees per farm in the period of April 2013 to April 2014 with monthly basis assessment. Data were analyzed refer to Eberhart & Russel method to perform stability parameters of the yield. The results indicate that these clones stable performing yield potency among plant age. MCC 01 and MCC 02 performed yield potency in amount of 3,682 kg/ha and 3,132 kg/ha respectively higher than Sulawesi 01 of 2,772 kg/ha. Evaluation of the resistance, MCC 01 having moderate resistance to CPB and VSD and resistance to PPR, however MCC 02 having resistance to CPB, VSD and PPR. Referring to the potency thus MCC 01 and MCC 02 were legally recommended as clonal material for farmers, restricted at the agroclimatic area similar to the condition in North Luwu

Parameterized Complexity and Approximation Issues for the Colorful Components Problems

The quest for colorful components (connected components where each color is associated with at most one vertex) inside a vertex-colored graph has been widely considered in the last ten years. Here we consider two variants, Minimum Colorful Components (MCC) and Maximum Edges in transitive Closure (MEC), introduced in 2011 in the context of orthology gene identification in bioinformatics. The input of both MCC and MEC is a vertex-colored graph. MCC asks for the removal of a subset of edges, so that the resulting graph is partitioned in the minimum number of colorful connected components; MEC asks for the removal of a subset of edges, so that the resulting graph is partitioned in colorful connected components and the number of edges in the transitive closure of such a graph is maximized. We study the parameterized and approximation complexity of MCC and MEC, for general and restricted instances. For MCC on trees we show that the problem is basically equivalent to Minimum Cut on Trees, thus MCC is not approximable within factor $1.36 - \varepsilon$, it is fixed-parameter tractable and it admits a poly-kernel (when the parameter is the number of colorful components). Moreover, we show that MCC, while it is polynomial time solvable on paths, it is NP-hard even for graphs with constant distance to disjoint paths number. Then we consider the parameterized complexity of MEC when parameterized by the number $k$ of edges in the transitive closure of a solution (the graph obtained by removing edges so that it is partitioned in colorful connected components). We give a fixed-parameter algorithm for MEC paramterized by $k$ and, when the input graph is a tree, we give a poly-kernel

Mad2, Bub3, and Mps1 regulate chromosome segregation and mitotic synchrony in Giardia intestinalis, a binucleate protist lacking an anaphase-promoting complex.

The binucleate pathogen Giardia intestinalis is a highly divergent eukaryote with a semiopen mitosis, lacking an anaphase-promoting complex/cyclosome (APC/C) and many of the mitotic checkpoint complex (MCC) proteins. However, Giardia has some MCC components (Bub3, Mad2, and Mps1) and proteins from the cohesin system (Smc1 and Smc3). Mad2 localizes to the cytoplasm, but Bub3 and Mps1 are either located on chromosomes or in the cytoplasm, depending on the cell cycle stage. Depletion of Bub3, Mad2, or Mps1 resulted in a lowered mitotic index, errors in chromosome segregation (including lagging chromosomes), and abnormalities in spindle morphology. During interphase, MCC knockdown cells have an abnormal number of nuclei, either one nucleus usually on the left-hand side of the cell or two nuclei with one mislocalized. These results suggest that the minimal set of MCC proteins in Giardia play a major role in regulating many aspects of mitosis, including chromosome segregation, coordination of mitosis between the two nuclei, and subsequent nuclear positioning. The critical importance of MCC proteins in an organism that lacks their canonical target, the APC/C, suggests a broader role for these proteins and hints at new pathways to be discovered

Approximate Clustering via Metric Partitioning

In this paper we consider two metric covering/clustering problems - \textit{Minimum Cost Covering Problem} (MCC) and $k$-clustering. In the MCC problem, we are given two point sets $X$ (clients) and $Y$ (servers), and a metric on $X \cup Y$. We would like to cover the clients by balls centered at the servers. The objective function to minimize is the sum of the $\alpha$-th power of the radii of the balls. Here $\alpha \geq 1$ is a parameter of the problem (but not of a problem instance). MCC is closely related to the $k$-clustering problem. The main difference between $k$-clustering and MCC is that in $k$-clustering one needs to select $k$ balls to cover the clients. For any \eps > 0, we describe quasi-polynomial time (1 + \eps) approximation algorithms for both of the problems. However, in case of $k$-clustering the algorithm uses (1 + \eps)k balls. Prior to our work, a $3^{\alpha}$ and a ${c}^{\alpha}$ approximation were achieved by polynomial-time algorithms for MCC and $k$-clustering, respectively, where $c > 1$ is an absolute constant. These two problems are thus interesting examples of metric covering/clustering problems that admit (1 + \eps)-approximation (using (1+\eps)k balls in case of $k$-clustering), if one is willing to settle for quasi-polynomial time. In contrast, for the variant of MCC where $\alpha$ is part of the input, we show under standard assumptions that no polynomial time algorithm can achieve an approximation factor better than $O(\log |X|)$ for $\alpha \geq \log |X|$.Comment: 19 page

Towards offering more useful data reliably to mobile cloudfrom wireless sensor network

The integration of ubiquitous wireless sensor network (WSN) and powerful mobile cloud computing (MCC) is a research topic that is attracting growing interest in both academia and industry. In this new paradigm, WSN provides data to the cloud, and mobile users request data from the cloud. To support applications involving WSN-MCC integration, which need to reliably offer data that are more useful to the mobile users from WSN to cloud, this paper first identifies the critical issues that affect the usefulness of sensory data and the reliability of WSN, then proposes a novel WSN-MCC integration scheme named TPSS, which consists of two main parts: 1) TPSDT (Time and Priority based Selective Data Transmission) for WSN gateway to selectively transmit sensory data that are more useful to the cloud, considering the time and priority features of the data requested by the mobile user; 2) PSS (Priority-based Sleep Scheduling) algorithm for WSN to save energy consumption so that it can gather and transmit data in a more reliable way. Analytical and experimental results demonstrate the effectiveness of TPSS in improving usefulness of sensory data and reliability of WSN for WSN-MCC integration

SAMI: Service-Based Arbitrated Multi-Tier Infrastructure for Mobile Cloud Computing

Mobile Cloud Computing (MCC) is the state-ofthe- art mobile computing technology aims to alleviate resource poverty of mobile devices. Recently, several approaches and techniques have been proposed to augment mobile devices by leveraging cloud computing. However, long-WAN latency and trust are still two major issues in MCC that hinder its vision. In this paper, we analyze MCC and discuss its issues. We leverage Service Oriented Architecture (SOA) to propose an arbitrated multi-tier infrastructure model named SAMI for MCC. Our architecture consists of three major layers, namely SOA, arbitrator, and infrastructure. The main strength of this architecture is in its multi-tier infrastructure layer which leverages infrastructures from three main sources of Clouds, Mobile Network Operators (MNOs), and MNOs' authorized dealers. On top of the infrastructure layer, an arbitrator layer is designed to classify Services and allocate them the suitable resources based on several metrics such as resource requirement, latency and security. Utilizing SAMI facilitate development and deployment of service-based platform-neutral mobile applications.Comment: 6 full pages, accepted for publication in IEEE MobiCC'12 conference, MobiCC 2012:IEEE Workshop on Mobile Cloud Computing, Beijing, Chin

Does Conditionality Work? A Test for an Innovative US Aid Scheme

Performance-based aid has been proposed as an alternative to the failed traditional approach whereby donors make aid conditional on the reform promises of recipient countries. However, hardly any empirical evidence exists on whether ex post rewards are effective in inducing reforms. We attempt to fill this gap by investigating whether the Millennium Challenge Corporation (MCC) was successful in promoting better control of corruption. We employ a difference-in-difference-in-differences (DDD) approach, considering different ways of defining the treatment group as well as different time periods during which incentive effects could have materialized. We find evidence of strong anticipation effects immediately after the announcement of the MCC, while increasing uncertainty about the timing and amount of MCC aid appear to weaken the incentive to fight corruption over time.foreign aid, corruption, Millennium Challenge Corporation, MCC effect