Sustainability of Small Scale Farming in a Mountain Region: Case Study of the Khaling Rai Population of the Solukhumbu, Nepal

The Khaling Rai live in a remote area of the mountain region of Nepal. Subsistence farming is central to their livelihood strategy, the sustainability of which was examined in this study. The sustainable livelihood approach was identified as a suitable theoretical framework to analyse the assets of the Khaling Rai. A baseline study was conducted using indicators to assess the outcome of the livelihood strategies under the three pillars of sustainability – economic, social and environmental. Relationships between key factors were analysed. The outcome showed that farming fulfils their basic need of food security, with self-sufficiency in terms of seeds, organic fertilisers and tools. Agriculture is almost totally non-monitized: crops are grown mainly for household consumption. However, the crux faced by the Khaling Rai community is the need to develop high value cash crops in order to improve their livelihoods while at the same time maintaining food security. Institutional support in this regard was found to be lacking. At the same time there is declining soil fertility and an expanding population, which results in smaller land holdings. The capacity to absorb risk is inhibited by the small size of the resource base and access only to small local markets. A two-pronged approach is recommended. Firstly, the formation of agricultural cooperative associations in the area. Secondly, through them the selection of key personnel to be put forward for training in the adoption of improved low-cost technologies for staple crops and in the introduction of appropriate new cash crops.

Technical and scale efficiency of cassava production system in Delta State, Nigeria: an application of Two-Stage DEA approach

The present study examines the level of pure technical and scale efficiencies of cassava production system including its sub-processes (that is production and processing stages) of 278 cassava farmers/processors from three regions of Delta State, Nigeria by applying Two-Stage Data Envelopment Analysis (DEA) approach. Results reveal that pure technical efficiency (PTE) is significantly lower at the production stage 0.41 vs 0.55 for the processing stage, but scale efficiency (SE) is high at both stages (0.84 and 0.87), implying that productivity can be improved substantially by reallocation of resources and adjusting operation size. The socio-economic determinants exert differential impacts on PTE and SE at each stage. Overall, education, experience and main occupation as farmer significantly improve SE while subsistence pressure reduces it. Extension contact significantly improves SE at the processing stage but reduces PTE and SE overall. Inverse size-PTE and size-SE relationships exist in cassava production system. In other words, large/medium farms are technically and scale inefficient. Gender gap exists in performance. Male farmers are technically efficient at processing stage but scale inefficient overall. Farmers in northern region are technically efficient. Investments in education, extension services and infrastructure are suggested as policy options to improve the cassava sector in Nigeria.

Transport magnetischer Partikel durch maßgeschneiderte magnetische Feldlandschaften zur Anwendung in mikrofluidischen Mischprozessen

Die Miniaturisierung von konventioneller Labor- und Analysetechnik nimmt eine zentrale Rolle im Bereich der allgemeinen Lebenswissenschaften und medizinischen Diagnostik ein. Neuartige und preiswerte Technologieplattformen wie Lab-on-a-Chip (LOC) oder Mikrototalanalysesysteme (µTAS) versprechen insbesondere im Bereich der Individualmedizin einen hohen gesellschaftlichen Nutzen zur frühzeitigen und nichtinvasiven Diagnose krankheitsspezifischer Indikatoren. Durch den patientennahen Einsatz preiswerter und verlässlicher Mikrochips auf Basis hoher Qualitätsstandards entfallen kostspielige und zeitintensive Zentrallaboranalysen, was gleichzeitig Chancen für den globalen Einsatz - speziell in Schwellen- und Entwicklungsländern - bietet. Die technischen Herausforderungen bei der Realisierung moderner LOC-Systeme sind in der kontrollierten und verlässlichen Handhabung kleinster Flüssigkeitsmengen sowie deren diagnostischem Nachweis begründet. In diesem Kontext wird der erfolgreichen Integration eines fernsteuerbaren Transports von biokompatiblen, magnetischen Mikro- und Nanopartikeln eine Schlüsselrolle zugesprochen. Die Ursache hierfür liegt in der vielfältigen Einsetzbarkeit, die durch die einzigartigen Materialeigenschaften begründet sind. Diese reichen von der beschleunigten, aktiven Durchmischung mikrofluidischer Substanzvolumina über die Steigerung der molekularen Interaktionsrate in Biosensoren bis hin zur Isolation und Aufreinigung von krankheitsspezifischen Indikatoren. In der Literatur beschriebene Ansätze basieren auf der dynamischen Transformation eines makroskopischen, zeitabhängigen externen Magnetfelds in eine mikroskopisch veränderliche potentielle Energielandschaft oberhalb magnetisch strukturierter Substrate, woraus eine gerichtete und fernsteuerbare Partikelbewegung resultiert. Zentrale Kriterien, wie die theoretische Modellierung und experimentelle Charakterisierung der magnetischen Feldlandschaft in räumlicher Nähe zur Oberfläche der strukturierten Substrate sowie die theoretische Beschreibung der Durchmischungseffekte, wurden jedoch bislang nicht näher beleuchtet, obwohl diese essentiell für ein detailliertes Verständnis der zu Grunde liegenden Mechanismen und folglich für einen Markteintritt zukünftiger Geräte sind. Im Rahmen der vorgestellten Arbeit wurde daher ein neuartiger Ansatz zur erfolgreichen Integration eines Konzepts zum fernsteuerbaren Transport magnetischer Partikel zur Anwendung in modernen LOC-Systemen unter Verwendung von magnetisch strukturierten Exchange-Bias (EB) Dünnschichtsystemen verfolgt. Die Ergebnisse zeigen, dass sich das Verfahren der ionenbe-schussinduzierten magnetischen Strukturierung (IBMP) von EB-Systemen zur Herstellung von maßgeschneiderten magnetischen Feldlandschaften (MFL) oberhalb der Substratoberfläche, deren Stärke und räumlicher Verlauf auf Nano- und Mikrometerlängenskalen gezielt über die Veränderung der Materialparameter des EB-Systems via IBMP eingestellt werden kann, eignet. Im Zuge dessen wurden erstmals moderne, experimentelle Verfahrenstechniken (Raster-Hall-Sonden-Mikroskopie und rastermagnetoresistive Mikroskopie) in Kombination mit einem eigens entwickelten theoretischen Modell eingesetzt, um eine Abbildung der MFL in unterschiedlichen Abstandsbereichen zur Substratoberfläche zu realisieren. Basierend auf der quantitativen Kenntnis der MFL wurde ein neuartiges Konzept zum fernsteuerbaren Transport magnetischer Partikel entwickelt, bei dem Partikelgeschwindigkeiten im Bereich von 100 µm/s unter Verwendung von externen Magnetfeldstärken im Bereich weniger Millitesla erzielt werden können, ohne den magnetischen Zustand des Substrats zu modifizieren. Wie aus den Untersuchungen hervorgeht, können zudem die Stärke des externen Magnetfelds, die Stärke und der Gradient der MFL, das magnetfeldinduzierte magnetische Moment der Partikel sowie die Größe und der künstlich veränderliche Abstand der Partikel zur Substratoberfläche als zentrale Einflussgrößen zur quantitativen Modifikation der Partikelgeschwindigkeit genutzt werden. Abschließend wurde erfolgreich ein numerisches Simulationsmodell entwickelt, das die quantitative Studie der aktiven Durchmischung auf Basis des vorgestellten Partikeltransportkonzepts von theoretischer Seite ermöglicht, um so gezielt die geometrischen Gegebenheiten der mikrofluidischen Kanalstrukturen auf einem LOC-System für spezifische Anwendungen anzupassen.

Determinants of technical efficiency of freshwater prawn farming in southwestern Bangladesh

This paper estimates a translog stochastic production function to examine the determinants of technical efficiency of freshwater prawn farming in Bangladesh. Primary data has been collected using random sampling from 90 farmers of three villages in southwestern Bangladesh. Prawn farming displayed much variability in technical efficiency ranging from 9.50 to 99.94% with mean technical efficiency of 65%, which suggested a substantial 35% of potential output can be recovered by removing inefficiency. For a land scarce country like Bangladesh this gain could help increase income and ensure better livelihood for the farmers. Based on the translog production function specification, farmers could be made scale efficient by providing more input to produce more output. The results suggest that farmers’ education and non-farm income significantly improve efficiency whilst farmers’ training, farm distance from the water canal and involvement in fish farm associations reduces efficiency. Hence, the study proposes strategies such as less involvement in farming-related associations and raising the effective training facilities of the farmers as beneficial adjustments for reducing inefficiency. Moreover, the key policy implication of the analysis is that investment in primary education would greatly improve technical efficiency.

A Detailed Look at Scale and Translation Invariance in a Hierarchical Neural Model of Visual Object Recognition

The HMAX model has recently been proposed by Riesenhuber & Poggio as a hierarchical model of position- and size-invariant object recognition in visual cortex. It has also turned out to model successfully a number of other properties of the ventral visual stream (the visual pathway thought to be crucial for object recognition in cortex), and particularly of (view-tuned) neurons in macaque inferotemporal cortex, the brain area at the top of the ventral stream. The original modeling study only used ``paperclip'' stimuli, as in the corresponding physiology experiment, and did not explore systematically how model units' invariance properties depended on model parameters. In this study, we aimed at a deeper understanding of the inner workings of HMAX and its performance for various parameter settings and ``natural'' stimulus classes. We examined HMAX responses for different stimulus sizes and positions systematically and found a dependence of model units' responses on stimulus position for which a quantitative description is offered. Interestingly, we find that scale invariance properties of hierarchical neural models are not independent of stimulus class, as opposed to translation invariance, even though both are affine transformations within the image plane.

Global Depth Perception from Familiar Scene Structure

In the absence of cues for absolute depth measurements as binocular disparity, motion, or defocus, the absolute distance between the observer and a scene cannot be measured. The interpretation of shading, edges and junctions may provide a 3D model of the scene but it will not inform about the actual "size" of the space. One possible source of information for absolute depth estimation is the image size of known objects. However, this is computationally complex due to the difficulty of the object recognition process. Here we propose a source of information for absolute depth estimation that does not rely on specific objects: we introduce a procedure for absolute depth estimation based on the recognition of the whole scene. The shape of the space of the scene and the structures present in the scene are strongly related to the scale of observation. We demonstrate that, by recognizing the properties of the structures present in the image, we can infer the scale of the scene, and therefore its absolute mean depth. We illustrate the interest in computing the mean depth of the scene with application to scene recognition and object detection.

A Multi-scale Model for Copper Dishing in Chemical-Mechanical Polishing

The present success in the manufacture of multi-layer interconnects in ultra-large-scale integration is largely due to the acceptable planarization capabilities of the chemical-mechanical polishing (CMP) process. In the past decade, copper has emerged as the preferred interconnect material. The greatest challenge in Cu CMP at present is the control of wafer surface non-uniformity at various scales. As the size of a wafer has increased to 300 mm, the wafer-level non-uniformity has assumed critical importance. Moreover, the pattern geometry in each die has become quite complex due to a wide range of feature sizes and multi-level structures. Therefore, it is important to develop a non-uniformity model that integrates wafer-, die- and feature-level variations into a unified, multi-scale dielectric erosion and Cu dishing model. In this paper, a systematic way of characterizing and modeling dishing in the single-step Cu CMP process is presented. The possible causes of dishing at each scale are identified in terms of several geometric and process parameters. The feature-scale pressure calculation based on the step-height at each polishing stage is introduced. The dishing model is based on pad elastic deformation and the evolving pattern geometry, and is integrated with the wafer- and die-level variations. Experimental and analytical means of determining the model parameters are outlined and the model is validated by polishing experiments on patterned wafers. Finally, practical approaches for minimizing Cu dishing are suggested.

A Multi-scale Model for Copper Dishing in Chemical-Mechanical Polishing

The present success in the manufacture of multi-layer interconnects in ultra-large-scale integration is largely due to the acceptable planarization capabilities of the chemical-mechanical polishing (CMP) process. In the past decade, copper has emerged as the preferred interconnect material. The greatest challenge in Cu CMP at present is the control of wafer surface non-uniformity at various scales. As the size of a wafer has increased to 300 mm, the wafer-level non-uniformity has assumed critical importance. Moreover, the pattern geometry in each die has become quite complex due to a wide range of feature sizes and multi-level structures. Therefore, it is important to develop a non-uniformity model that integrates wafer-, die- and feature-level variations into a unified, multi-scale dielectric erosion and Cu dishing model. In this paper, a systematic way of characterizing and modeling dishing in the single-step Cu CMP process is presented. The possible causes of dishing at each scale are identified in terms of several geometric and process parameters. The feature-scale pressure calculation based on the step-height at each polishing stage is introduced. The dishing model is based on pad elastic deformation and the evolving pattern geometry, and is integrated with the wafer- and die-level variations. Experimental and analytical means of determining the model parameters are outlined and the model is validated by polishing experiments on patterned wafers. Finally, practical approaches for minimizing Cu dishing are suggested.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Central notations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform. In this way very elaborated aspects of mathematical statistics can be understood easily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating, combination of likelihood and robust M-estimation functions are simple additions/ perturbations in A2(Pprior). Weighting observations corresponds to a weighted addition of the corresponding evidence. Likelihood based statistics for general exponential families turns out to have a particularly easy interpretation in terms of A2(P). Regular exponential families form finite dimensional linear subspaces of A2(P) and they correspond to finite dimensional subspaces formed by their posterior in the dual information space A2(Pprior). The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P. The discussion of A2(P) valued random variables, such as estimation functions or likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

Composición factorial de la versión española de la Spence Children Anxiety Scale (SCAS).

Resumen tomado de la publicación

An??lisis de la estructura factorial de las puntuaciones de la 'Preschool and Kindergarten Behavior Scale' en poblaci??n espa??ola

Resumen tomado de la publicaci??n

Evaluación de la equivalencia factorial y métrica de la Sexual Assertiveness Scale (SAS) por sexo.

Resumen tomado de la publicación