Miracle-dz/UniFAR-FTUs huggingface dataset:
Using CERES-Maize and ENSO as Decision Support Tools to Evaluate Climate-Sensitive Farm Management Practices for Maize Production in the Northern Regions of Ghana

Maize (Zea mays) has traditionally been a major cereal staple in southern Ghana. Through breeding and other crop improvement efforts, the zone of cultivation of maize has now extended to the northern regions of Ghana which, hitherto, were the home to sorghum and millet as the major cereals. Maize yield in the northern Ghana is hampered by three major biophysical constraints, namely, poor soil fertility, low soil water storage capacity and climate variability. In this study we used the DSSAT crop model to assess integrated water and soil management strategies that combined the pre-season El-Niño-Southern Oscillation (ENSO)-based weather forecasting in selecting optimal planting time, at four locations in the northern regions of Ghana. It could be shown that the optimum planting date for a given year was predictable based on February-to-April (FMA) Sea Surface Temperature (SST) anomaly for the locations with R2 ranging from 0.52 to 0.71. For three out of four locations, the ENSO-predicted optimum planting dates resulted in significantly higher maize yields than the conventional farmer selected planting dates. In Wa for instance, early optimum planting dates were associated with La Nina and El Niño (Julian Days 130-150; early May to late May) whereas late planting (mid June to early July) was associated with the Neutral ENSO phase. It was also observed that the addition of manure and fertilizer improved soil water and nitrogen use efficiency, respectively, and minimized yield variability, especially when combined with weather forecast. The use of ENSO-based targeted planting date choice together with modest fertilizer and manure application has the potential to improve maize yields and also ensure sustainable maize production in parts of northern Ghana.
DOT4 Links Silencing and Cell Growth inSaccharomyces cerevisiae

ABSTRACT Transcriptional silencing in Saccharomyces cerevisiaeoccurs at specific loci and is mediated by a multiprotein complex that includes Rap1p and the Sir proteins. We studied the function of a recently identified gene, DOT4, that disrupts silencing when overexpressed. DOT4 encodes an ubiquitin processing protease (hydrolase) that is primarily located in the nucleus. By two-hybrid analysis, the amino-terminal third of Dot4p interacts with the silencing protein Sir4p. Cells lacking DOT4 exhibited reduced silencing and a corresponding decrease in the level of Sir4p. Together, these findings suggest that Dot4p regulates silencing by acting on Sir4p. In strains with several auxotrophic markers, loss ofDOT4 ubiquitin hydrolase activity also results in a slow-growth defect. The defect can be partially suppressed by mutations in a subunit of the 26S proteasome, suggesting that Dot4p has the ability to prevent ubiquitin-mediated degradation. Furthermore, wild-type SIR2, SIR3, and SIR4 are required for full manifestation of the growth defect in adot4 strain, indicating that the growth defect is caused in part by a silencing-related mechanism. We propose that Dot4p helps to restrict the location of silencing proteins to a limited set of genomic loci.
Graph Algorithms for Massive Data-Sets

In this dissertation we face a number of fundamental graph problems which, on the one hand, share applications to the state explosion problem in model checking, and, on the other hand, pose interesting algorithmic questions when very large graphs are dealt with. In more detail, this thesis is divided into three main parts. Part I (Symbolic Graph Algorithms) deals with the algorithmic solution of fundamental graph problems (especially graph connectivity problems) assuming a symbolic OBDD-based graph representation. Working on symbolically represented data has potential: the standards achieved in graph sizes (playing a crucial role, for example, in verification, VLSI design, and CAD) are definitely higher. On the other hand, symbolic algorithm’s design generates constraints as well. For example, Depth First Search is not feasible in the symbolic setting and our approach suggests a symbolic framework to tackle those problems which, in the standard case, are naturally solved by a DFS-based algorithm. Part II (Equivalence Based Graph Reduction) deals with well known bisimulation and simulation graph reductions. In particular, our purpose is to show a fil rouge connecting such notions, which consists in casting them into partition refinement problems (coarsest partition problems). Such a formulation is well known to be the engine of efficient computational strategies for bisimulation. In this thesis, we extend the picture to the, computationally more challenging, notion of simulation. Besides (we hope) a deeper understanding of the algebraic nature of simulation equivalence, the final byproduct is the definition of a new space efficient simulation algorithm refining a partition rather than a relation. Part III discusses some applications to model checking and builds connecting bridges among the material introduced in the first two parts of the dissertation. In particular, the strongly connected components symbolic algorithm defined in Part I is used to obtain a symbolic version of an efficient rank -based bisimulation reduction, recently defined in [39]. Finally, our symbolic procedure for strongly connected components turns out to be the key to cut down from O(V log V ) to O(V ) the number symbolic steps necessary to perform a number of tasks in model checking as bad cycle detection and Büchi as well as Streett automata language emptiness problems.
A coalitional game framework for cooperative secondary spectrum access

We consider a framework in which several service providers offer downlink wireless data access service in a certain area. Each provider serves its end-users through opportunistic secondary spectrum access of licensed spectrum, and needs to pay primary license holders of the spectrum usage based and membership based charges for such secondary spectrum access. In these circumstances, if providers pool their resources and allow end-users to be served by any of the cooperating providers, the total user satisfaction as well as the aggregate revenue earned by providers may increase. We use coalitional game theory to investigate such cooperation among providers, and show that the optimal cooperation schemes can be obtained as solutions of convex optimizations. We next show that under usage based charging scheme, if all providers cooperate, there always exists an operating point that maximizes the aggregate revenue of providers, while presenting each provider a share of the revenue such that no subset of providers has an incentive to leave the coalition. Furthermore, such an operating point can be computed in polynomial time. Finally, we show that when the charging scheme involves membership based charges, the above result holds in important special cases.
Does anti-thymocyte globulin have a place in busulfan/fludarabine conditioning for matched related donor hematopoietic stem cell transplantation?

Background/Aims: There is controversy about the prophylactic effect of anti-thymocyte globulin (ATG) on graft versus host disease (GVHD) in the setting of matched related-donor hematopoietic stem cell transplantation (HSCT). This study assessed the inf luences of ATG on the incidences of acute and chronic GVHD and other clinical outcomes in matched related-donor HSCT. Methods: Sixty-one patients received allogeneic HSCT from human leukocyte antigen-matched, related donors. Patients received busulfan/fludarabine conditioning regimens and standard GVHD prophylaxis with or without additional ATG. Results: There was no significant difference in the cumulative incidences of overall acute GVHD, grade II to IV acute GVHD at day 100, and chronic GVHD during the follow-up period between the ATG and non-ATG groups. Three-year overall survival rates were very similar, but three year disease-free survival of the non-ATG group was higher than that of the ATG group (56.2% for ATG vs. 63.1% for non-ATG, p = 0.597). Relapse rate at 3 years in the ATG group was slightly higher than that of the non-ATG group (37.5% vs. 20%, p = 0.29). Non-relapse mortality rate at 3 years was lower in the ATG group (6.25% vs. 15.6%, p = 0.668). Conclusions: Although the addition of ATG doesn’t guarantee a reduction in the incidences of acute and chronic GVHD, pre-transplantation ATG may result in lower non-relapse mortality in the context of matched related-donor HSCT with a busulfan/fludarabine conditioning regimen. However, caution is needed when using ATG because of a possibility to increase relapse rate.
The normal distributions transform: a new approach to laser scan matching

Matching 2D range scans is a basic component of many localization and mapping algorithms. Most scan match algorithms require finding correspondences between the used features, i.e. points or lines. We propose an alternative representation for a range scan, the normal distributions transform. Similar to an occupancy grid, we subdivide the 2D plane into cells. To each cell, we assign a normal distribution, which locally models the probability of measuring a point. The result of the transform is a piecewise continuous and differentiable probability density, that can be used to match another scan using Newton's algorithm. Thereby, no explicit correspondences have to be established. We present the algorithm in detail and show the application to relative position tracking and simultaneous localization and map building (SLAM). First results on real data demonstrate, that the algorithm is capable to map unmodified indoor environments reliable and in real time, even without using odometry data.
Working with Volunteers in Sport: Theory and Practice

The contribution of volunteers in terms of time and expertise is integral to sport development and delivery from 'sport for all' to elite levels. Good volunteer management and a clear understanding of the way volunteers work in sport is essential to protect and nurture this valuable group of individuals. This is the first book of its kind to examine the role of volunteers in sport, and links theory and research to provide clear guidelines for implementing good volunteer management practice. The authors are well known for their research in this subject and cover the key issues including: * developing sport through volunteers * recruiting and retaining volunteers * government policy and international comparisons * specialist volunteers - coaches, officials, administrators * relationships with paid staff * volunteers and the law. With nearly six million adult volunteers working in sport in the UK alone, and there being no other books currently on the market addressing this issue, Working with Volunteers is a valuable read for students and professionals working in sports management, sport development and sports policy.
The C4 Clustering Algorithm: Clusters of Galaxies in the Sloan Digital Sky Survey

We present the C4 Cluster Catalog, a new sample of 748 clusters of galaxies identified in the spectroscopic sample of the Second Data Release (DR2) of the Sloan Digital Sky Survey (SDSS). The C4 cluster-finding algorithm identifies clusters as overdensities in a seven-dimensional position and color space, thus minimizing projection effects that have plagued previous optical cluster selection. The present C4 catalog covers ∼2600 deg2 of sky and ranges in redshift from z = 0.02 to 0.17. The mean cluster membership is 36 galaxies (with measured redshifts) brighter than r = 17.7, but the catalog includes a range of systems, from groups containing 10 members to massive clusters with over 200 cluster members with measured redshifts. The catalog provides a large number of measured cluster properties including sky location, mean redshift, galaxy membership, summed r-band optical luminosity (Lr), and velocity dispersion, as well as quantitative measures of substructure and the surrounding large-scale environment. We use new, multicolor mock SDSS galaxy catalogs, empirically constructed from the ΛCDM Hubble Volume (HV) Sky Survey output, to investigate the sensitivity of the C4 catalog to the various algorithm parameters (detection threshold, choice of passbands, and search aperture), as well as to quantify the purity and completeness of the C4 cluster catalog. These mock catalogs indicate that the C4 catalog is ≃90% complete and 95% pure above M200 = 1 × 1014 h-1 M⊙ and within 0.03 ≤ z ≤ 0.12. Using the SDSS DR2 data, we show that the C4 algorithm finds 98% of X-ray–identified clusters and 90% of Abell clusters within 0.03 ≤ z ≤ 0.12. Using the mock galaxy catalogs and the full HV dark matter simulations, we show that the Lr of a cluster is a more robust estimator of the halo mass (M200) than the galaxy line-of-sight velocity dispersion or the richness of the cluster. However, if we exclude clusters embedded in complex large-scale environments, we find that the velocity dispersion of the remaining clusters is as good an estimator of M200 as Lr. The final C4 catalog will contain ≃2500 clusters using the full SDSS data set and will represent one of the largest and most homogeneous samples of local clusters.
Fetal macrosomia related to maternal poorly controlled type 1 diabetes strongly impairs serum lipoprotein concentrations and composition

Aims—To determine the effects of fetal macrosomia related to maternal type 1 diabetes on the lipid transport system. Methods—Serum lipoprotein concentrations and composition and lecithin:cholesterol acyltransferase (LCAT) activity were investigated in macrosomic newborns (mean birth weight, 4650 g; SEM, 90) and their mothers with poorly controlled type 1 diabetes, in appropriate for gestational age newborns (mean birth weight, 3616 g; SEM, 68) and their mothers with well controlled type 1 diabetes, and macrosomic (mean birth weight, 4555 g; SEM, 86) or appropriate for gestational age (mean birth weight, 3290 g; SEM, 45) newborns and their healthy mothers. Results—In mothers with well controlled type 1 diabetes, serum lipids, apolipoproteins, and lipoproteins were comparable with those of healthy mothers. Similarly, in their infants, these parameters did not differ from those of appropriate for gestational age newborns. Serum triglyceride, very low density lipoprotein (VLDL), apolipoprotein B100 (apo B100), and high density lipoprotein (HDL) triglyceride concentrations were higher, whereas serum apo A-I and HDL3 concentrations were lower in mothers with diabetes and poor glycaemic control than in healthy mothers. Their macrosomic newborns had higher concentrations in all serum lipids and lipoproteins, with high apo A-I and apo B100 values compared with appropriate for gestational age newborns. In macrosomic infants of healthy mothers, there were no significant differences in lipoprotein profiles compared with those of appropriate for gestational age infants. LCAT activity was similar in both groups of mothers and newborns. Conclusion—Poorly controlled maternal type 1 diabetes and fetal macrosomia were associated with lipoprotein abnormalities. Macrosomic lipoprotein profiles related to poor metabolic control of type 1 diabetes appear to have implications for later metabolic diseases.
Reperfusion-triggered stress protein response in the myocardium is blocked by post-conditioning. Systems biology pathway analysis highlights the key role of the canonical aryl-hydrocarbon receptor pathway.

AIMS Ischaemic post-conditioning (IPost-Co) exerts cardioprotection by diminishing ischaemia/reperfusion injury. Yet, the mechanisms involved in such protection remain largely unknown. We have investigated the effects of IPost-Co in cardiac cells and in heart performance using molecular, proteomic and functional approaches. METHODS AND RESULTS Pigs underwent 1.5 h mid-left anterior descending balloon occlusion and then were sacrificed without reperfusion (ischaemia; n= 7), subjected to 2.5 h of cardiac reperfusion and sacrificed (n= 5); or subjected to IPost-Co before reperfusion and sacrificed 0.5 h (n= 4) and 2.5 h (n= 5) afterwards. A sham-operated group was included (n= 4). Ischaemic and non-ischaemic myocardium was obtained for molecular/histological analysis. Proteomic analysis was performed by two-dimensional electrophoresis followed by matrix-assisted laser desorption/ionization-time-of-flight identification. Potential protein networks involved were identified by bioinformatics and Ingenuity Pathway Analysis (IPA). Cardiac function was assessed by echocardiography. IPost-Co diminished (up to 2.5 h) reperfusion-induced apoptosis of both the intrinsic and extrinsic pathways whereas it did not affect reperfusion-induced Akt/mammalian target of rapamycin (mTOR)/P70S6K activation. Proteomic studies showed that IPost-Co reverted 43% of cardiac cytoplasmic protein changes observed during ischaemia and ischaemia + reperfusion. Systems biology assessment revealed significant changes in the aryl-hydrocarbon receptor (AhR) pathway (cell damage related). Bioinformatic data were confirmed since the expression of HSP90, AhR, ANRT, and β-tubulin (involved in AhR-signalling transduction) were accordingly modified after IPost-Co. IPost-Co rescued 52% of the left ventricle-at-risk compared with reperfusion alone and resulted in a ≈30% relative improvement in left ventricular ejection fraction (P <0.05). CONCLUSION IPost-Co improves cardiac function post-myocardial infarction and reduces reperfusion-induced cell damage by down-regulation of the AhR-signalling transduction pathway ultimately leading to infarct size reduction.
Hybrid Evolutionary Optimisation Methods for the Clearance of Nonlinear Flight Control Laws

The application of two evolutionary optimisation methods, namely differential evolution and genetic algorithms, to the clearance of nonlinear flight control laws for highly augmented aircraft is described. The algorithms are applied to the problem of evaluating a nonlinear handling qualities clearance criterion for a simulation model of a high performance aircraft with a delta canard configuration and a full-authority flight control law. Hybrid versions of both algorithms, incorporating local gradient-based optimisation, are also developed and evaluated. Statistical comparisons of computational complexity and global convergence properties reveal the benefits of hybridisation for both algorithms. The differential evolution approach in particular, when appropriately augmented with local optimisation methods, is shown to have significant potential for improving both the reliability and efficiency of the current industrial flight clearance process.
User Mode Memory Page Management: An old idea applied anew to the memory wall problem

It is often said that one of the biggest limitations on computer performance is memory bandwidth (i.e."the memory wall problem"). In this position paper, I argue that if historical trends in computing evolution (where growth in available capacity is exponential and reduction in its access latencies is linear) continue as they have, then this view is wrong - in fact we ought to be concentrating on reducing whole system memory access latencies wherever possible, and by "whole system" I mean that we ought to look at how software can be unnecessarily wasteful with memory bandwidth due to legacy design decisions. To this end I conduct a feasibility study to determine whether we ought to virtualise the MMU for each application process such that it has direct access to its own MMU page tables and the memory allocated to a process is managed exclusively by the process and not the kernel. I find under typical conditions that nearly scale invariant performance to memory allocation size is possible such that hundreds of megabytes of memory can be allocated, relocated, swapped and deallocated in almost the same time as kilobytes (e.g. allocating 8Mb is 10x quicker under this experimental allocator than a conventional allocator, and resizing a 128Kb block to 256Kb block is 4.5x faster). I find that first time page access latencies are improved tenfold; moreover, because the kernel page fault handler is never called, the lack of cache pollution improves whole application memory access latencies increasing performance by up to 2x. Finally, I try binary patching existing applications to use the experimental allocation technique, finding almost universal performance improvements without having to recompile these applications to make better use of the new facilities.
Back-off as Parameter Estimation for DOP models

Data-Oriented Parsing (DOP) is a probabilistic performance approach to parsing natural language. Several DOP models have been proposed since it was introduced by Scha (1990), achieving promising results. One important feature of these models is the probability estimation procedure. Two major estimators have been put forward: Bod (1993) uses a relative frequency estimator; Bonnema (1999) adds a rescaling factor to correct for tree size effects. Both estimators, however, present biases. Moreover, Bod’s estimator has been shown to be inconsistent (Johnson, 2002), meaning that the probability estimates hypothesized by the model do not approach the true probabilities that generated the data as the sample size grows. In this thesis, we implement a new estimation procedure that tackles the shortcomings of the two previous methods. The main idea is to treat derivation events not as disjoint, but as interrelated in a hierarchical cascade of parse tree derivations. We show that this new estimator – called the Back-Off DOP (BO-DOP) estimator – outperforms both previous models. We tested it on the OVIS treebank, a Dutch language, speech-based system, and report error reductions of up to 11.4% and 15% when compared to, respectively, Bod’s and Bonnema’s estimators.
Research on Financial Subsidy Mode for Agricultural Water Fees Based on Incentive Mechanism of Water-Saving

Based on the analysis of two current representative modes of financial subsidy to agricultural water by introducing the theory of economics, this paper, set up an incentive model of water-saving in the premise of financial subsidy, in order to explore a financial subsidy mode on agricultural water and agriculture water price mechanism suitable for present situation. The research shows that direct subsidy is more efficient comparing to indirect subsidy, while the market's regulatory function was limited because of current low water price. From the angle of encouraging water saving, the paper put forward that direct financial subsidy of agricultural water based on increasing water price may not only reduce the farmers’ burden on water fees, but also generate water-saving incentives to both water supply unit and farmers, then help promoting the sustainable development of China's agriculture.
A Hardware System of Active Learning Method

The active learning method (ALM), proposed as a methodology of soft computing, simulates human learning and inferencing processes on the basis of fuzzy concepts. This paper presents a hardware implementation of ALM. ALM has processing engines called IDS, which are tasked with extracting useful information from a system subject to modeling. In realizing ALM in hardware, it will be desirable in terms of processing nature, performance, and scalability to utilize dedicated hardware for IDS. This paper primarily describes the actual hardware design of an IDS module, and shows modeling results using an ALM system that implemented the IDS module.
A Review on Personalized Information Recommendation System Using Collaborative Filtering

The term Collaborative Filtering is used as a backbone in almost all Commercial Recommendation Systems today. This paper attempts to review all major developments in area of Collaborative Filtering. Main application area is outlined and examples of applications of Collaborative Filtering are presented. KeywordsCollaborative filtering, Recommendation system, Concept drift, Trust, Cold-start, Hybrid model