Spatial aspects of the design and targeting of agricultural development strategies:

Two increasingly shared perspectives within the international development community are that (a) geography matters, and (b) many government interventions would be more successful if they were better targeted. This paper unites these two notions by exploring the opportunities for, and benefits of, bringing an explicitly spatial dimension to the tasks of formulating and evaluating agricultural development strategies. We first review the lingua franca of land fragility and find it lacking in its capacity to describe the dynamic interface between the biophysical and socioeconomic factors that help shape rural development options. Subsequently, we propose a two-phased approach. First, development strategy options are characterized to identify the desirable ranges of conditions that would most favor successful strategy implementation. Second, those conditions exhibiting important spatial dependency – such as agricultural potential, population density, and access to infrastructure and markets – are matched against a similarly characterized, spatially-referenced (GIS) database. This process generates both spatial (map) and tabular representations of strategy-specific development domains. An important benefit of a spatial (GIS) framework is that it provides a powerful means of organizing and integrating a very diverse range of disciplinary and data inputs. At a more conceptual level we propose that it is the characterization of location, not the narrowly-focused characterization of land, that is more properly the focus of attention from a development perspective. The paper includes appropriate examples of spatial analysis using data from East Africa and Burkina Faso, and concludes with an appendix describing and interpreting regional climate and soil data for Sub-Saharan Africa that was directly relevant to our original goal.Spatial analysis (Statistics), Agricultural development., Burkina Faso., Africa, Sub-Saharan.,

GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction

In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we observe that there exists another type of features introduced during the preprocessing steps and we call them "\textbf{Procedural Bias}". Besides, such bias can be leveraged to improve classification accuracy. Nevertheless, most existing models suffer from either under-fit without considering procedural bias or poor interpretability without differentiating such bias from lesion ones. In this paper, a novel dual-task algorithm namely \emph{GSplit LBI} is proposed to resolve this problem. By introducing an augmented variable enforced to be structural sparsity with a variable splitting term, the estimators for prediction and selecting lesion features can be optimized separately and mutually monitored by each other following an iterative scheme. Empirical experiments have been evaluated on the Alzheimer's Disease Neuroimaging Initiative\thinspace(ADNI) database. The advantage of proposed model is verified by improved stability of selected lesion features and better classification results.Comment: Conditional Accepted by Miccai,201

Phase Structure of Kerr-AdS Black Hole

We study the critical phenomena of Kerr-AdS black hole. Phase structures are observed at different temperatures, $T_{L}$, $T_{c1}$ and $T_{c2}$ with various features. We discuss the thermal stability considering the isothermal compressibility and how phase transitions related to each other. The asymptotic value of the angular momentum also has an implication on separating stable and unstable part. Near critical temperature $T_{c1}$, the order parameter is determined to calculate the critical exponents. All the critical exponents ($\alpha$,$\beta$,$\gamma$,$\delta$)=(0,1/2,1,3) are identical to that of mean field systems. We plot the phase diagram near this critical point, and discuss the scaling symmetry of the free energy.Comment: 21 pages, 6 figures, contents revise

Analisa Dan Perancangan Sistem Informasi Pemetaan Sekolah Dasar Kota Manado

Sekolah merupakan salah satu halpenting dalam kehidupan masyarakat KotaManado. Sekolah dasar negeri merupakantanggung jawab data dari Dinas Pendidikan yangmemiliki kesulitan dalam mengelolah data di KotaManado yang begitu banyak. Sistem InformasiPemetaan Sekolah Dasar di Kota Manado inidapat memberikan gambaran pemetaan daninformasi secara keseluruhan tentang SekolahDasar di Kota Manado. Sistem informasi ini dilengkapi dengan menggunakan metodologipengembangan sistem perangkat lunak RapidApplication Development Sistem InformasiPemetaan Sekolah Dasar di Kota Manado dibuatdengan bahasa pemograman Perl HypertextPreprocessor dan Google Maps API. Hasil daripenelitian ini adalah sebuah aplikasi SistemInformasi Pemetaan Sekolah Dasar di KotaManado berbasis web

Open Biomedical Ontology-based Medline exploration

Abstract Background Effective Medline database exploration is critical for the understanding of high throughput experimental results and the development of novel hypotheses about the mechanisms underlying the targeted biological processes. While existing solutions enhance Medline exploration through different approaches such as document clustering, network presentations of underlying conceptual relationships and the mapping of search results to MeSH and Gene Ontology trees, we believe the use of multiple ontologies from the Open Biomedical Ontology can greatly help researchers to explore literature from different perspectives as well as to quickly locate the most relevant Medline records for further investigation. Results We developed an ontology-based interactive Medline exploration solution called PubOnto to enable the interactive exploration and filtering of search results through the use of multiple ontologies from the OBO foundry. The PubOnto program is a rich internet application based on the FLEX platform. It contains a number of interactive tools, visualization capabilities, an open service architecture, and a customizable user interface. It is freely accessible at: http://brainarray.mbni.med.umich.edu/brainarray/prototype/pubonto .http://deepblue.lib.umich.edu/bitstream/2027.42/112693/1/12859_2009_Article_3295.pd

Microbiota dynamics, metabolic and immune interactions in the cervicovaginal environment and their role in spontaneous preterm birth

Differences in the cervicovaginal microbiota are associated with spontaneous preterm birth (sPTB), a significant cause of infant morbidity and mortality. Although establishing a direct causal link between cervicovaginal microbiota and sPTB remains challenging, recent advancements in sequencing technologies have facilitated the identification of microbial markers potentially linked to sPTB. Despite variations in findings, a recurring observation suggests that sPTB is associated with a more diverse and less stable vaginal microbiota across pregnancy trimesters. It is hypothesized that sPTB risk is likely to be modified via an intricate host-microbe interactions rather than due to the presence of a single microbial taxon or broad community state. Nonetheless, lactobacilli dominance is generally associated with term outcomes and contributes to a healthy vaginal environment through the production of lactic acid/ maintenance of a low pH that excludes other pathogenic microorganisms. Additionally, the innate immunity of the host and metabolic interactions between cervicovaginal microbiota, such as the production of bacteriocins and the use of proteolytic enzymes, exerts a profound influence on microbial populations, activities, and host immune responses. These interplays collectively impact pregnancy outcomes. This review aims to summarize the complexity of cervicovaginal environment and microbiota dynamics, and associations with bacterial vaginosis and sPTB. There is also consideration on how probiotics may mitigate the risk of sPTB and bacterial vaginosis

catena-Poly[1-butyl-3-methyl­imidazolium [[dichlorido(methanol-κO)(propan-2-ol-κO)lanthanate(III)]-di-μ-chlorido]]

The title compound, (C8H15N2)[LaCl4(CH3OH)(C3H7OH)], consists of one 1-butyl-3-methyl­imidazolium (BMI+) cation and one hexa­hedral tetra­chlorido(methanol)(propan-2-ol)lanthanate anion. The LaIII ion is eight-coordinate, with the LaIII ion bridged by a pair of Cl atoms, so forming chains propagating along the a-axis direction. Each LaIII ion is further coordinated by two isolated Cl atoms, one methanol and one propan-2-ol mol­ecule. The coordinated methanol and propan-2-ol mol­ecules of the anion form O—H⋯Cl hydrogen bonds with the Cl atoms of inversion-related anions. The BMI+ cation froms C—H⋯Cl hydrogen bonds with the Cl atoms of the anion. The anions are located in the C faces of the triclinic unit cell, with an inversion center in the middle of the La2Cl2 ring of the polymeric chain

Quality-Diversity through AI Feedback

In many text-generation problems, users may prefer not only a single response, but a diverse range of high-quality outputs from which to choose. Quality-diversity (QD) search algorithms aim at such outcomes, by continually improving and diversifying a population of candidates. However, the applicability of QD to qualitative domains, like creative writing, has been limited by the difficulty of algorithmically specifying measures of quality and diversity. Interestingly, recent developments in language models (LMs) have enabled guiding search through AI feedback, wherein LMs are prompted in natural language to evaluate qualitative aspects of text. Leveraging this development, we introduce Quality-Diversity through AI Feedback (QDAIF), wherein an evolutionary algorithm applies LMs to both generate variation and evaluate the quality and diversity of candidate text. When assessed on creative writing domains, QDAIF covers more of a specified search space with high-quality samples than do non-QD controls. Further, human evaluation of QDAIF-generated creative texts validates reasonable agreement between AI and human evaluation. Our results thus highlight the potential of AI feedback to guide open-ended search for creative and original solutions, providing a recipe that seemingly generalizes to many domains and modalities. In this way, QDAIF is a step towards AI systems that can independently search, diversify, evaluate, and improve, which are among the core skills underlying human society's capacity for innovation.Comment: minor additions to supplementary result

Selfishness, fraternity, and other-regarding preference in spatial evolutionary games

Spatial evolutionary games are studied with myopic players whose payoff interest, as a personal character, is tuned from selfishness to other-regarding preference via fraternity. The players are located on a square lattice and collect income from symmetric two-person two-strategy (called cooperation and defection) games with their nearest neighbors. During the elementary steps of evolution a randomly chosen player modifies her strategy in order to maximize stochastically her utility function composed from her own and the co-players' income with weight factors $1-Q$ and Q. These models are studied within a wide range of payoff parameters using Monte Carlo simulations for noisy strategy updates and by spatial stability analysis in the low noise limit. For fraternal players ($Q=1/2$) the system evolves into ordered arrangements of strategies in the low noise limit in a way providing optimum payoff for the whole society. Dominance of defectors, representing the "tragedy of the commons", is found within the regions of prisoner's dilemma and stag hunt game for selfish players (Q=0). Due to the symmetry in the effective utility function the system exhibits similar behavior even for Q=1 that can be interpreted as the "lovers' dilemma".Comment: 7 two-column pages, 8 figures; accepted for publication in J. Theor. Bio