Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simple Model of Replenishable Natural Resource Exploitation

The purpose of this paper is to consider maximum sustained yield programs of replenishable natural resource exploitation and to question the validity of these programs in satisfying social goals. In the treatment of such programs, two fundamental problems arise. The first is that the existence of a social discount factor (or interest rate) may cause the maximum sustained yield program to be nonoptimal.1 The second problem, considered recently in the literature, relates to the many externalities which may be present in harvesting resources.2 The most significant of these externalities is the 'stock' externality in production. That is, there is a potential misallocation of inputs in the production of natural resource product due to the fact that one input, the natural resource itself, contributes to production but may not receive payment (for example, its marginal product) because no one owns the resource. Recently, research in this area has been directed at finding optimal taxing schemes which will have the effect of assigning to an unappropriated natural resource its imputed rent.3 In this paper, a simple model will be developed which will illustrate the nature of the first of these problems in a case where the second problem is not present. To accomplish this, production will be assumed 'costless' in the sense that no inputs are used. (Production, which will be the same as consumption, has a 'cost' in the sense that it diminishes the stock of resource available for consumption in all subsequent periods.) The use of a natural resource in this model is parallel in theory to the use of capital, and the term 'investment' will be used here to indicate simply 'foregone consumption. ' The intertemporal aspect of the problem suggests a dynamic model, and the model is formulated as an optimal control question. The approach parallels Kenneth Arrow in his treatment of the Reversible Ramsey Problem.
Discriminative Robust Transformation Learning

This paper proposes a framework for learning features that are robust to data variation, which is particularly important when only a limited number of training samples are available. The framework makes it possible to tradeoff the discriminative value of learned features against the generalization error of the learning algorithm. Robustness is achieved by encouraging the transform that maps data to features to be a local isometry. This geometric property is shown to improve (K, ∊)-robustness, thereby providing theoretical justification for reductions in generalization error observed in experiments. The proposed optimization framework is used to train standard learning algorithms such as deep neural networks. Experimental results obtained on benchmark datasets, such as labeled faces in the wild, demonstrate the value of being able to balance discrimination and robustness.
Accuracy of the Kirchhoff-Approximation and Kirchhoff-Ray-Mode Fish Swimbladder Acoustic Scattering Models

The acoustic backscatter from pressure release prolate spheroids and a three-dimensional representation of a fish swimbladder (Chilean jack mackerel, Trachurus symmetricus murphyi) was calculated using four target strength models (Kirchhoff-approximation, Kirchhoff-ray-mode, finite element solution of the Helmholtz equation, and prolate-spheroid-modal-series). Smoothly varying errors were found in the Kirchhoff-approximation and Kirchhoff-ray-mode model results when compared to the other models, and provide objective criteria for constraining the use of the KA and KRM models. A generic correction technique is also proposed for the prolate spheroid estimates and tentatively tested on a jack mackerel swimbladder, resulting in improvements to the target strength estimates from the Kirchhoff-approximation and Kirchhoff-ray-mode models.
Gastric carcinoma: imaging diagnosis, staging and assessment of treatment response

Abstract Gastric carcinoma (GC) is one of the most common causes of cancer-related death worldwide. Surgical resection is the only cure available and is dependent on the GC stage at presentation, which incorporates depth of tumor invasion, extent of lymph node and distant metastases. Accurate preoperative staging is therefore essential for optimal surgical management with consideration of preoperative and/or postoperative chemotherapy. Multidetector computed tomography (MDCT) with its ability to assess tumor depth, nodal disease and metastases is the preferred technique for staging GC. Endoscopic ultrasonography is more accurate for assessing the depth of wall invasion in early cancer, but is limited in the assessment of advanced local or stenotic cancer and detection of distant metastases. Magnetic resonance imaging (MRI), although useful for staging, is not proven to be effective. Positron emission tomography (PET) is most useful for detecting and characterizing distant metastases. Both MDCT and PET are useful for assessment of treatment response following preoperative chemotherapy and for detection of recurrence after surgical resection. This review article discusses the usefulness of imaging modalities for detecting, staging and assessing treatment response for GC and the potential role of newer applications including CT volumetry, virtual gastroscopy and perfusion CT in the management of GC.
Randomised Controlled Feasibility Trial of an Evidence-Informed Behavioural Intervention for Obese Adults with Additional Risk Factors

Background Interventions for dietary and physical activity changes in obese adults may be less effective for participants with additional obesity-related risk factors and co-morbidities than for otherwise healthy individuals. This study aimed to test the feasibility and acceptability of the recruitment, allocation, measurement, retention and intervention procedures of a randomised controlled trial of an intervention to improve physical activity and dietary practices amongst obese adults with additional obesity related risk factors. Method Pilot single centre open-labelled outcome assessor-blinded randomised controlled trial of obese (Body Mass Index (BMI)≥30 kg/m2) adults (age≥18 y) with obesity related co-morbidities such as type 2 diabetes, impaired glucose tolerance or hypertension. Participants were randomly allocated to a manual-based group intervention or a leaflet control condition in accordance to a 2∶1 allocation ratio. Primary outcome was acceptability and feasibility of trial procedures, secondary outcomes included measures of body composition, physical activity, food intake and psychological process measures. Results Out of 806 potentially eligible individuals identified through list searches in two primary care general medical practices N = 81 participants (63% female; mean-age = 56.56(11.44); mean-BMI = 36.73(6.06)) with 2.35(1.47) co-morbidities were randomised. Scottish Index of Multiple Deprivation (SIMD) was the only significant predictor of providing consent to take part in the study (higher chances of consent for invitees with lower levels of deprivation). Participant flowcharts, qualitative and quantitative feedback suggested good acceptance and feasibility of intervention procedures but 34.6% of randomised participants were lost to follow-up due to overly high measurement burden and sub-optimal retention procedures. Participants in the intervention group showed positive trends for most psychological, behavioural and body composition outcomes. Conclusions The intervention procedures were found to be acceptable and feasible. Attrition rates were unacceptably high and areas for improvements of trial procedures were identified. Trial Registration Controlled-Trials.com ISRCTN90101501
Freezing or supercooling: how does an aquatic subterranean crustacean survive exposures at subzero temperatures?

SUMMARY Crystallization temperature (Tc), resistance to inoculative freezing (IF), ice contents, bound water, protein and glycogen body contents were measured in the aquatic subterranean crustacean Niphargus rhenorhodanensis and in the morphologically close surface-dwelling aquatic crustacean Gammarus fossarum, both acclimated at 12°C, 3°C and -2°C. Cold acclimation induced an increase in the Tc values in both species but no survival was observed after thawing. However, after inoculation at high sub-zero temperatures, cold-acclimated N. rhenorhodanensis survived whereas all others, including the 3°C and -2°C acclimated G. fossarum died. In its aquatic environment, N. rhenorhodanensis is likely to encounter inoculative freezing before reaching the Tc and IF tolerance appears as a highly adaptive trait in this species. Bound water and glycogen were found to increase in the 3°C and -2°C acclimated N. rhenorhodanensis, whereas no variation was observed in G. fossarum. Considering the hydrophilic properties of glycogen, such a rise may be correlated with the increased bound water measured in cold-acclimated N. rhenorhodanensis, and may be linked to the survival of this species when it was inoculated. The ecological significance of the survival of the aquatic subterranean crustacean to inoculative freezing is paradoxical, as temperature is currently highly buffered in its habitat. However, we assume that past geographical distribution and resulting life history traits of N. rhenorhodanensis are key parameters in the current cold-hardiness of the species.
High Schools That Work: Program Description, Literature Review, and Research Findings. Research Report. ETS RR-11-33.

Interest in setting high educational standards is at the forefront of many school reform programs in the United States. States' pursuit of high standards can be advanced through implementation of programs such as High Schools That Work (HSTW), which emphasizes high expectations and rigorous academics for all students, including Career and Technical Education students. High Schools That Work is the largest comprehensive school reform program for high schools in the United States, with over 1,000 schools in more than 30 states currently participating. This report describes the program, previous research, and recent research studies conducted by ETS to ensure validity for the HSTW program.
Organic BMPs Used for Storm Water Management

Recent university research has shown that a compost system can reduce storm runoff, sediment and nutrient loss, and increase vegetation and soil quality parameters relative to industry standard best management practices. State departments of transportation and construction companies have reported positive results in using compost as a filter media within filter socks. Compost used as a sediment retention or storm water filtration device has shown empirical success in perimeter control on construction sites, check dams in channels, channel protection, stormwater inlet and outlet protection, streambank stabilization, sediment pond alternative, slope stabilization, temporary and permanent vegetation establishment, flood control, green roof growing media, stormwater gardens, bioretention ponds, and hydrocarbon filtration of runoff. Independent laboratory testing evaluated compost filter media for sediment, nutrient, and hydrocarbon removal from storm water runoff on a 3:1 slope. Total solids and petroleum hydrocarbon reduction from filtration of storm runoff were consistently over 95%. Reduction in nitrate nitrogen and total phosphorus concentrations from storm runoff were observed. Additionally, increased reduction of total suspended solids and turbidity, in addition to consistently high removal percentages of petroleum hydrocarbons over three consecutive storm runoff events were also reported.
New constraints on the chemical evolution of the dwarf spheroidal galaxy Leo I from VLT spectroscopy

We present the spectroscopy of red giant stars in the dwarf spheroidal galaxy Leo I, aimed at further constraining its chemical enrichment history. Intermediate-resolution spectroscopy in the Ca ii triplet spectral region was obtained for 54 stars in Leo I using FORS2 at the ESO Very Large Telescope. The equivalent widths of Ca ii triplet lines were used to derive the metallicities of the target stars on the [Fe/H] scale of Carretta & Gratton, as well as on a scale tied to the global metal abundance, [M/H]. The metallicity distribution function for red giant branch (RGB) stars in Leo I is confirmed to be very narrow, with mean value [M/H] �− 1.2 and dispersion σ[M/H] � 0.2. By evaluating all contributions to the measurement error, we provide a constraint to the intrinsic metallicity dispersion, σ[M/H],0 = 0.08. We find a few metal-poor stars (whose metallicity values depend on the adopted extrapolation of the existing calibrations), but in no case are stars more metal-poor than [Fe/H] = −2.6. Our measurements provide a hint of a shallow metallicity gradient of −0.27 dex Kpc −1 among Leo I red giants. The gradient disappears if our data are combined with previous spectroscopic datasets in the literature, so that any firm conclusions about its presence must await new data, particularly in the outer regions. By combining the metallicities of the target stars with their photometric data, we provide age estimates and an age-metallicity relation for a subset of red giant stars in Leo I. Our age estimates indicate a rapid initial enrichment, a slowly rising metal abundance – consistent with the narrowness of the metallicity distribution – and an increase of ∼0.2 dex in the last few Gyr. The estimated ages also suggest a radial age gradient in the RGB stellar populations, which agrees with the conclusions of a parallel study of asymptotic giant branch stars in Leo I from near-infrared photometry. Together, these studies provide the first evidence of stellar population gradients in Leo I.
Planar graphs, negative weight edges, shortest paths, and near linear time

The authors present an O(n log/sup 3/ n) time algorithm for finding shortest paths in a planar graph with real weights. This can be compared to the best previous strongly polynomial time algorithm developed by R. Lipton et al., (1978 )which ran in O(n/sup 3/2/) time, and the best polynomial algorithm developed by M. Henzinger et al. (1994) which ran in O/spl tilde/(n/sup 4/3/) time. We also present significantly improved algorithms for query and dynamic versions of the shortest path problems.
Alzheimer Disease National Registry System in Prevention and Treatment Management

Alzheimer is a kind of brain disorder in which death of brain cells leads to dysfunction of memory, thought, judgment, language, and other nervous activities which can subsequently change individual behavior and personality. Collection of proper data and access to sufficient information regarding causes of Alzheimer can help to develop preventive programs and manage treatment. The most important part of information management system is data collection which is considered as the basic tool for a detailed description of the health care process, evaluation, diagnosis, interventions, outcomes, and documentation. Managers need reliable and accurate data for resource allocation and management. The first step toward data standardization in order to facilitate, share, and compare it among different centers is the establishment of a minimum data set (MDS). MDS is a minimum set of agreed data elements collected at national or regional level and reported to related organizations. In this regard, the present study aims to investigate the role of the Alzheimer national registry system in the prevention treatment and management. The study was a narrative survey, which was done through searching in Google search engine as well as sites associated with Alzheimer with the help of some key words such as “minimum data set”, “advantages”, “treatment”, “prevention” “Alzheimer”, and “registry” in journal articles (abstracts and texts), books, conference abstracts, and other online documents from 2006 to 2015. Approximately, 70 articles, books, theses, and conference abstracts were obtained of which 50 cases were selected. Designing and development of MDS for Alzheimer seems necessary at the national level in Iran, so that data collection and analysis can help in designing of preventive programs.
Integrating a Suicide Prevention Program into the Primary Health Care Network: A Field Trial Study in Iran

Objective. To describe and evaluate the feasibility of integrating a suicide prevention program with Primary Health Care services and evaluate if such system can improve screening and identification of depressive disorder, reduce number of suicide attempters, and lower rate of suicide completion. Methodology. This was a quasi-experimental trial in which one community was exposed to the intervention versus the control community with no such exposure. The study sites were two counties in Western Iran. The intervention protocol called for primary care and suicide prevention collaboration at different levels of care. The outcome variables were the number of suicides committed, the number of documented suicide attempts, and the number of identified depressed cases. Results. We identified a higher prevalence of depressive disorders in the intervention site versus the control site (χ 2 = 14.8, P < 0.001). We also found a reduction in the rate of suicide completion in the intervention region compared to the control, but a higher prevalence of suicide attempts in both the intervention and the control sites. Conclusion. Integrating a suicide prevention program with the Primary Health Care network enhanced depression and suicide surveillance capacity and subsequently reduced the number of suicides, especially in rural areas.
Rediscovering the Democratic Purposes of Education

Why do America's public schools seem unable to meet today's social challenges? As competing interest groups vie over issues like funding and curricula, we seem to have lost sight of the democratic purposes originally intended for public education. Public schools were envisioned by the Founders as democratically run institutions for instilling civic values, but today's education system seems more concerned with producing good employees than good citizens. Meanwhile, our country's diversity has eroded consensus about citizenship, and the professionalization of educators has diminished public involvement in schools. This volume seeks to demonstrate that the democratic purposes of education are not outmoded ideas but can continue to be driving forces in public education. Nine original articles by some of today's leading education theorists cut a broad swath across the political spectrum to examine how those democratic purposes might be redefined and revived. It both establishes the intellectual foundation for revitalizing American schools and offers concrete ideas for how the educational process can be made more democratic. The authors make a case for better empirical research about the politics of education in order to both reconnect schools to their communities and help educators instill citizenship. An initial series of articles reexamines the original premise of American education as articulated by important thinkers like Jefferson and Dewey. A second group identifies flaws in how schools are currently governed and offers models for change. A final section analyzes the value conflicts posed by the twin strands of democratic socialization and governance, and their implications for education policy. Spanning philosophy, history, sociology, and political science, this book brings together the best current thinking about the specifics of education policy vouchers, charter schools, national testing and about the role of deliberation in a democracy. It offers a cogent alternative to the exchange paradigm and shows how much more needs to be understood about an issue so vital to America's future. "
How is luminance information passed into the cortex: emergent multifunctional behavior of a simple cell model

In modeling brightness perception, one problem of high biological relevance is how luminance information is transmitted into the primary visual cortex. This is especially interesting in the light of recent neurophysiological studies, which suggest that simple cells are responding shallowly to homogeneous illuminated surfaces. This indicates that simple cells possess far more functional complexity as the wide-spread notion of mere line and edge detectors. Here we present new neural circuits for modeling even and odd simple cells, capable of transmitting brightness information without using an extra `luminance- channel'. Although these circuits taken for themselves can not be regarded yet as a full brightness model, however, they might gain some insight in why the visual system is using certain processing strategies. These include e.g. the segregation in ON and OFF channels and the mutual inhibition of simple cell pairs which are in anti-phase relation. These simple cell circuits turn out to be robust against noise, and thus might find its application in a border detection scheme, beside of being a building block for a more sophisticated brightness-model.
Toward optimal LES on unstructured meshes

A new approach for determining the correlation data required by the optimal-LES procedure of Langford and Moser (Optimal LES formulations for isotropic turbulence, J. Fluid Mech., 398, 321–346, 1999) is presented. Based on Kolmogorov’s theory for isotropic turbulence, the new approach leads to stencil coefficients in terms of integrated multi-point correlations. The explicit dependence of the optimal-LES method on DNS data is thus eliminated, and its applicability is extended to high Reynolds-number flows in complex geometries. A preliminary verification of the new optimal-LES method for decaying isotropic turbulence showed good results for decay rates.
Small Trades and ADR Premiums : The Case of Indian ADRs

There is a growing literature on the impact of small trades/retail investors on stock prices, with some studies suggesting that strong buying by retail investors leads to overvaluation of stocks. We examine the impact of small trades in the U.S. on Indian ADR prices relative to the underlying stock. These ADRs trade at significant premiums that cannot be arbitraged due to Indian government regulations. The existence of two market prices for claims to the same set of underlying cash flows closely resembles the closed-end fund (CEF) discount puzzle. In the case of ADRs, we can rule out the tax, and agency cost explanations. Hence, Indian ADRs provide a better setting to examine the evidence for investor sentiment influencing market prices. Consistent with such an influence, we find that ADR premiums are positively related to orderimbalance of small ADR trades. The premiums associated with the small trades are reversed in two weeks. We control for price pressure effects by including order-imbalance of all trades. Also, premiums are negatively related to the volatility implied by S&P500 index option prices (VIX).