Miracle-dz/UniFAR-FTUs huggingface dataset:
Access to credit and the determinants of technical inefficiency among specialized small farmers in Chile

The influence on technical efficiency of access to credit and public support policies is studied for two groups of specialized small farmers in Chile. Using 2004 data, translog stochastic frontier production functions for 109 livestock and 342 crop producers are estimated. Mean technical efficiency is 89% and 78% for crop and livestock producers, respectively. Technical efficiency increases with decreasing use of inputs, dependence on on-farm income, farmer education, family size and the age of the family head. Extension services do not appear to help farms become more efficient, and even reduce efficiency among specialised crop pro-ducers. The volume of credit increases efficiency in crop production and reduces it in live-stock production. Correspondingly, credit constrained farmers are less efficient in crop pro-duction and more efficient in livestock. These results may reflect the fact that investments in livestock production can involve considerable adjustment costs in the short run. For livestock producers, credit volume and credit constraints are found to be endogenous to technical effi-ciency. A possible explanation is the organisation of public support for small livestock pro-ducers in Chile, which provides lenders with information about individual livestock produc-ers. This might enable lenders to target loans on the basis of efficiency. Correcting for this endogeneity does not lead to qualitatively different results, but does influence point estimates of parameters in the production function and inefficiency models. This highlights the impor-tance of testing for endogeneity in the variables used to model inefficiency effects.
Encoding Crowd Interaction with Deep Neural Network for Pedestrian Trajectory Prediction

Pedestrian trajectory prediction is a challenging task because of the complex nature of humans. In this paper, we tackle the problem within a deep learning framework by considering motion information of each pedestrian and its interaction with the crowd. Specifically, motivated by the residual learning in deep learning, we propose to predict displacement between neighboring frames for each pedestrian sequentially. To predict such displacement, we design a crowd interaction deep neural network (CIDNN) which considers the different importance of different pedestrians for the displacement prediction of a target pedestrian. Specifically, we use an LSTM to model motion information for all pedestrians and use a multi-layer perceptron to map the location of each pedestrian to a high dimensional feature space where the inner product between features is used as a measurement for the spatial affinity between two pedestrians. Then we weight the motion features of all pedestrians based on their spatial affinity to the target pedestrian for location displacement prediction. Extensive experiments on publicly available datasets validate the effectiveness of our method for trajectory prediction.
An Android Security Policy Enforcement Tool

The Android operating system (OS) has become the dominant smart phone OS in recent years due to its accessibility, usability and its open-source philosophy. Consequently, this has also made it a popular target for attackers who aim to install malware on Android devices and take advantage of Android’s coarse-grained, non-revoking permission system. This project designs, implements and evaluates a security tool named COMBdroid, which addresses these security concerns in Android by enforcing fine-grained, user-defined policies. COMBdroid modifies an application before installation, allowing it to override points of security vulnerabilities at run-time. As a proof of concept we have implemented three policies in COMBdroid. This paper documents the development process of COMBdroid, deriving design decisions from the literature review, detailing the design and implementation, and proving the program’s effectiveness through evaluation.
IMPROVED DISTRIBUTION GRID HOSTING CAPACITY WITH OPTIMISED PV DEPLOYMENT

Nowadays in Europe, the production from variable renewable energy sources (vRES) has seen a significant growth and the photovoltaic (PV) generation plays a central role. The unplanned proliferation of PV generators in different points of the distribution grid has caused different kind of disturbances that might compromise the correct operation and reliability of the grid. In particular, possible overvoltages caused by PV generation limit the amount of PV that can be installed in a certain node of a distribution system. In this respect, the aim of this work is twofold. First, the hosting capacity of a specific distribution network is analysed based on voltage buses, current branch and power at transformer level. Then, a suboptimal PV placement algorithm is proposed in order to reduce the overvoltage effect, thus mitigating the issues related to limited hosting capacity.
Energetic Order for Optimization on Hierarchies of Partitions: Continuous hierarchy and Lagrange optimization

In the current technical note we provide a topological generalization of hierarchy of partitions(HOP) structure, and the implications over the axioms of h-increasingness and scale increasingness [13]. Further in this study we will explicit the Lagrange optimization in the optimal cuts problem and the conditions necessary on the energy to obtain a global optimum using the a dynamic program. Further a general multi-constraint optimization problem is considered with multiple Lagrangian multipliers, leading to a general version of scale increasingness that orders cuts, by ordered tuples of multipliers. The report also differentiates Inf-Modularity and Submodularity and their space of application. The final demonstration on wavering hierarchies show how one can relax conditions on the hierarchical structure.
Accounting for User Diversity in the Design for Sustainable Behaviour in Smart Offices

Human factors are essential in the promotion and success of energy efficiency initiatives in the workplace. The existing literature on the field has demonstrated that ‘one-size-fits-all’ solutions tend to fail because they overlook addressing user diversity and the different motivations to behave pro-environmentally. Thus, accounting for user heterogeneity appears to be a successful approach to improve the accuracy selecting and developing behaviour change strategies for different user profiles and work-contexts. This paper addresses the ideation and design process of an Internet of Things (IoT)-based physical object, a coaster, to foster energy awareness in an office-based workplace. Putting the diversity of users in the centre of the process, the Iot-design proposal links persuasive principles with user profiles in order to give personalised eco-feedback for each different user type. Insights on the inclusion of user diversity on the Design for Sustainable Behaviour (DfSB) theories are provided after conducting qualitative research to evaluate the relationship between users and the designed interactive coaster.
Dynamic Market Selection in EU Business Services

European business services has witnessed about two decades of virtual productivity stagnation. The paper investigates whether this is caused by weak dynamic market selection. The time pattern of scale-related inefficiencies is used as an indicator for the effectiveness of market selection. We use a DEA method to construct the productivity frontier by sub-sector and size class, for business services in 13 EU countries. From this we derive scale economies and their development over time. Between 1999 and 2005 we observe a persistence of scale inefficiencies and X-inefficiencies , with scale efficiency falling rather than growing over time. This indicates malfunctioning competitive selection. The time pattern of inefficiencies is significantly explained by regulatory policies that hamper entry and exit dynamics and labour adjustment, and by a lack of import penetration. The results suggest that policy reform and more market openness will have positive productivity effects. This holds for business services itself, but also wider, because of business services’ products are widely used as intermediary inputs in other parts of the European economy.
The river absorption capacity determination as a tool to evaluate state of surface water

Abstract. In order to complete a thorough and systematic assessment of water quality, it is useful to measure the absorption capacity of a river. Absorption capacity is understood as a pollution load introduced into river water that will not cause permanent and irreversible changes in the aquatic ecosystem and will not cause a change in the classification of water quality in the river profile. In order to implement the method, the Macromodel DNS/SWAT basin for the Middle Warta pilot (central Poland) was used to simulate nutrient loads. This enabled detailed analysis of water quality in each water body and the assessment of the size of the absorption capacity parameter, which allows the determination of how much pollution can be added to the river without compromising its quality class. Positive values of the calculated absorption capacity parameter mean that it is assumed that the ecosystem is adjusted in such a way that it can eliminate pollution loads through a number of self-purification processes. Negative values indicate that the load limit has been exceeded, and too much pollution has been introduced into the ecosystem for it to be able to deal with through the processes of self-purification. Absorption capacity thus enables the connection of environmental standards of water quality and water quality management plans in order to meet these standards.
Random sampling and model competition for guaranteed multiple consensus sets estimation

Robust extraction of consensus sets from noisy data is a fundamental problem in robot vision. Existing multimodel estimation algorithms have shown success on large consensus sets estimations. One remaining challenge is to extract small consensus sets in cluttered multimodel data set. In this article, we present an effective multimodel extraction method to solve this challenge. Our technique is based on smallest consensus set random sampling, which we prove can guarantee to extract all consensus sets larger than the smallest set from input data. We then develop an efficient model competition scheme that iteratively removes redundant and incorrect model samplings. Extensive experiments on both synthetic data and real data with high percentage of outliers and multimodel intersections demonstrate the superiority of our method.
A User Study on the Effect of Aggregating Explanations for Interpreting Machine Learning Models

Recently, there is growing consensus of the critical need to have better techniques to explain machine learning models. However, many of the popular techniques are instance-level explanations, which explain the model from the point of view of a single data point. While local explanations may be misleading, they are also not human-scale, as it is impossible for users to read explanations for how the model behaves on all of their data points. Our work-in-progress paper explores the e ff ectiveness of providing instance-level explanations in aggregate, by demonstrating that such aggregated explanations have a significant impact on users’ ability to detect biases in data. This is achieved by comparing meaningful subsets, such as di ff erences be-tween ground truth labels, predicted labels, and correct and incorrect predictions, which provide necessary navigation to explain machine learning models.
Large-Scale Traffic Signal Offset Optimization

The offset optimization problem seeks to coordinate and synchronize the timing of traffic signals throughout a network in order to enhance traffic flow and reduce stops and delays. Recently, offset optimization was formulated into a continuous optimization problem without integer variables by modeling traffic flow as sinusoidal. In this article, we present a novel algorithm to solve this new formulation to near-global optimality on a large scale. Specifically, we solve a convex relaxation of the nonconvex problem using a tree decomposition reduction, and use randomized rounding to recover a near-global solution. We prove that the algorithm always delivers solutions of expected value at least 0.785 times the globally optimal value. Moreover, assuming that the topology of the traffic network is “tree-like,” we prove that the algorithm has near-linear time complexity with respect to the number of intersections. These theoretical guarantees are experimentally validated on the Berkeley, Manhattan, and Los Angeles traffic networks. In our numerical results, the empirical time complexity of the algorithm is linear, and the solutions have objectives within 0.99 times the globally optimal value.
Risk assessment of fixed defects in GIS under different voltage wave shapes

SF 6 gas has nowadays established itself as a reliable insulating medium for gas-insulated switchgear (GIS). In GIS however different kind of defects may occur, such as protrusions fixed to the conductors. Such defects locally enhance the electric field, which can result in partial discharge (PD) activity or even breakdown. For the application of condition based maintenance (CBM) on GIS, it is important to be able to assess its insulation condition. Aspects, which have to be taken into account, are sensitive detection of partial discharge activity, identification and location of the discharging source and probability for breakdown. In this paper, the criticality or probability for breakdown of fixed defects has been investigated. For this purpose, AC voltages have been applied to study the breakdown probabilities under pure AC condition. Secondly, the defects have been tested with standard lightning impulses (LI) and switching impulses (SI) and finally a bias-test was performed. Based on above-mentioned results, knowledge rules for risk assessment tools have been defined.
Student and Employee Wellness in Higher Education: A Literature Review.

This paper reviews the literature related to wellness. Wellness is reviewed in terms of definitions, theoretical perspectives, and research approaches. The definitions of wellness by six theorists are outlined. Regardless of definition chosen, today's conception of wellness has been fostered by disillusion with traditional medicine and the growing self-care movement. Recent interest in a holistic approach to life supports concerns with wellness and wellness readiness. Both qualitative and quantitative measures of wellness can be found in the literature, and both research approaches tend to focus on the wellness activities of employees and students, especially college students. Wellness centers and associated facilities are becoming more common on college and university campuses. (Contains 92 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. Student and Employee Wellness in Higher Education: A Literature Review PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) 1
Insights into Earth’s Energy Imbalance from Multiple Sources

AbstractThe current Earth’s energy imbalance (EEI) can best be estimated from changes in ocean heat content (OHC), complemented by top-of-atmosphere (TOA) radiation measurements and an assessment of the small non-ocean components. Sustained observations from the Argo array of autonomous profiling floats enable near-global estimates of OHC since 2005, which reveal considerable cancellation of variations in the upper 300 m. An analysis of the monthly contributions to EEI from non-ocean components (land and ice) using the Community Earth System Model (CESM) Large Ensemble reveals standard deviations of 0.3–0.4 W m−2 (global); largest values occur in August, but values are below 0.75 W m−2 greater than 95% of the time. Global standard deviations of EEI of 0.64 W m−2 based on top-of-atmosphere observations therefore substantially constrain ocean contributions, given by the tendencies of OHC. Instead, monthly standard deviations of many Argo-based OHC tendencies are 6–13 W m−2, and nonphysical fluctuations are .
Content-Centric and Named-Data Networking Security: The Good, The Bad and The Rest

Named Data Networking and Content-Centric Networking (NDN and CCN, respectively) are closely related networking architectures which, unlike host-centric IP, emphasize content by explicitly naming it, and by making content names addressable and routable in the network. They support innetwork (router-side) content caching, thus facilitating efficient and scalable content distribution, for which IP is comparatively poorly suited. These architectures also include new network-layer security features, such as signed content. While avoiding certain security problems of today’s Internet, NDN and CCN trigger some new security and privacy issues. This paper overviews the security landscape of NDN/CCN, and focuses on two main areas of concern: (1) Interest Flooding Attacks, and (2)Producer, Consumer, and Content Privacy. We argue that, despite many attempts to fix these problems, they have not been fully addressed, and discuss the challenges that inhibit comprehensive solutions.
Rapid climate change: an overview for economists

The possibility of future rapid climatic changes is a pressing concern amongst climate scientists. For example, an abrupt collapse of the ocean's Thermohaline Circulation (THC) would rapidly cool the northern hemisphere and reduce the net global primary productivity of vegetation, according to computer models. It is unclear how to incorporate such low-probability, high-impact events into the development of economics policies. This paper reviews the salient aspects of rapid climate change relevant to economists and policy makers. The main scientific certainties and uncertainties are clearly delineated, with the aim of guiding economics goals and ensuring that they retain fidelity to their scientific underpinnings.
The impact of food price shocks on weight loss: Evidence from the adult population of Tanzania

Undernourishment is still widespread in Tanzania, while obesity is becoming an issue of magnitude similar to undernutrition in the country. In this paper we examined the impact of an increase in maize prices on the nutritional status of Tanzania's adult population. We found that undernutrition increases as a result of increased prices, while the overweight and obese decrease their energy intake. The study presents evidences of the so called early stage of the nutritional transition that characterize developing countries. All in all, these findings are suggestive of the fact that food price shocks should be taken into consideration when designing policy and programmes aiming at addressing malnutrition in low income countries.
Solution Behavior of Double-Hydrophilic Block Copolymers in Dilute Aqueous Solution

The self-assembly of double-hydrophilic poly(ethylene oxide)–poly(2-methyl-2-oxazoline) diblock copolymers in water has been studied. Isothermal titration calorimetry, small-angle X-ray scattering, and analytical ultracentrifugation suggest that only single polymer chains are present in solution. In contrast, light scattering and transmission electron microscopy detect aggregates with radii of ca. 100 nm. Pulsed field gradient NMR spectroscopy confirms the presence of aggregates, although only 2% of the polymer chains undergo aggregation. Water uptake experiments indicate differences in the hydrophilicity of the two blocks, which is believed to be the origin of the unexpected aggregation behavior (in accordance with an earlier study by Ke et al. [Macromolecules2009, 42, 5339–5344]). The data therefore suggest that even in double-hydrophilic block copolymers, differences in hydrophilicity are sufficient to drive polymer aggregation, a phenomenon that has largely been overlooked or ignored so far.
Relationship between Phosphorus Levels in Three Ultisols and Phosphorus Concentrations in Runoff

Soils that contain high P levels can become a primary source of dissolved reactive P (DRP) in runoff, and thus contribute to accelerated eutrophication of surface waters. In a previous study on Captina soil, several soil test P (STP) methods gave results that were significantly correlated to DRP levels in runoff, but distilled H 2 O and NH 4 -oxalate methods gave the best correlations. Because results might differ on other soils, runoff studies were conducted on three additional Ultisols to identify the most consistent STP method for predicting runoff DRP levels, and determine effects of site hydrology on correlations between STP and runoff DRP concentrations. Surface soil (0-2 cm depth) of pasture plots was analyzed by Mehlich III, Olsen, Morgan, Bray-Kurtz P1, NH 4 -oxalate, and distilled H 2 O methods. Also, P saturation of each soil was determined by three different methods. Simulated rain (75 mm h - ') produced 30 min of runoff from each plot. All correlations of STP to runoff DRP were significant (P 0.90) on all three soils. For a given level of H 2 O-extractable STP, low runoff volumes coincided with low DRP concentrations. Therefore, when each DRP concentration was divided by volume of plot runoff, correlations to H 2 O-extractable STP had the same (P < 0.05) regression line for every soil. This suggests the importance of site hydrology in determining P loss in runoff, and may provide a means of developing a single relationship for a range of soil series.
Orthognathic Surgery Combined with Partial Lipectomy of the Buccal Fat Pad: Case Report on Optimization of Esthetic Outcome

Orthognathic surgery involves correction of functional and often esthetic disharmonies. The purpose of this case report is to present the case of a 22 years-old female with class III dentofacial deformity that required orthognathic surgery to treat her malocclusion and buccal fat pad excision for optimizing soft-tissue facial contour. Treatment planning involved a counterclockwise rotation of the maxilomandibular complex with genioplasty based on digital 3D surgical planning using the Dolphin Imaging 11.7 3D Premium software. Prototyping splints allowed surgical procedures (bilateral sagital mandibular osteotomy associated to a Le fort I osteotomy) that corrected position of the gnathic bones. In the same surgical procedure, the buccal fat pad was partially removed for a sharp cheek contour giving a slimmer appearance to her face. After 5 months, the patient was reassessed and reported no complaints regarding esthetics or function. This case illustrates that a combination of orthognathic surgery and an esthetic procedure can result in a stable and harmonious facial as well as occlusal outcomes.