Miracle-dz/UniFAR-FTUs huggingface dataset:
Five Decades of Structural and Compositional Changes in Managed and Unmanaged Montane Stands: A Case Study from South-East Europe

The recent research has indicated that restoration of old-growth attributes such as large-sized living trees and snags contributes to sustaining biodiversity on the landscape level. The extent to which these attributes are restored, maintained, or diminished by total salvage logging, selection silviculture, and strict protection has been partly investigated in the past. However, studies examining the influence of partial salvage logging are largely absent. Thus, we compared long-term structural and compositional changes in three montane beech-fir-spruce stands in Serbia that were exposed to different management regimes for five decades (partial salvage logging, selection silviculture, and strict protection). Tree species composition of partly salvaged stand and selection stand significantly differed from that in the adjacent unmanaged stand. However, the diameter distributions of compared stands often exhibited the same structural forms in certain periods, despite the greater share of large-size trees in the unmanaged stand. The study indicated that managing for old-growth attributes such as large trees may be possible by applying not only rotated sigmoid and negative exponential structures, but also the increasing-q diameter structure as high basal areas in studied beech-fir-spruce stands did not impair the ingrowth of young trees when conifers dominated the upperstory. The study further revealed that partial salvaging may serve as a sound alternative to promoting old-growth attributes such as large veteran trees and snags.
On the Transportability of Laboratory Results

The “transportability” of laboratory findings to other instances than the original implementation entails the robustness of rates of observed behaviors and estimated treatment effects to changes in the specific research setting and in the sample under study. In four studies based on incentivized games of fairness, trust, and reciprocity, we evaluate (1) the sensitivity of laboratory results to locally recruited student-subject pools, (2) the comparability of behavioral data collected online and, under varying anonymity conditions, in the laboratory, (3) the generalizability of student-based results to the broader population, and (4) with a replication at Amazon Mechanical Turk, the stability of laboratory results across research contexts. For the class of laboratory designs using incentivized games as measurement instruments of prosocial behavior, we find that rates of behavior and the exact behavioral differences between decision situations do not transport beyond specific implementations. Most clearly, data obtained from standard participant pools differ significantly from those from the broader population. This undermines the use of empirically motivated laboratory studies to establish descriptive parameters of human behavior. Directions of the behavioral differences between games, in contrast, are remarkably robust to changes in samples and settings. Moreover, we find no evidence for either anonymity effects nor mode effects potentially biasing laboratory measurement. These results underscore the capacity of laboratory experiments to establish generalizable causal effects in theory-driven designs.
A business-cycle-model with monopolistically-competitive intermediary firms and sticky nominal wages: the case of Bulgaria after the introduction of the currency board (1999-2016)

We augment an otherwise standard business cycle model with a richer government sector, and add monopolistic competition in the product market, and rigid prices, as well as rigid wages a la Calvo (1983) in the labor market. This specification with the nominal wage rigidity, when calibrated to Bulgarian data after the introduction of the currency board (1999-2016), allows the framework to reproduce better observed variability and correlations among model variables, and those characterizing the labor market in particular. As nominal wage frictions are incorporated, the variables become more persistent, especially output, capital stock, investment and consumption, which helps the model match data better.
Local Hamiltonians for one-dimensional critical models

Conformal field theory has turned out to be a powerful tool to derive interesting lattice models with analytical ground states. Here, we investigate a class of critical, one-dimensional lattice models of fermions and hardcore bosons related to the Laughlin states. The Hamiltonians of the exact models involve interactions over long distances that are difficult to realize experimentally. This motivates us to study the properties of models with the same type of interactions, but now only between nearest and possibly next-nearest neighbor sites. Based on computations of wavefunction overlaps, entanglement entropies, and two-site correlation functions for systems of up to 32 sites, we find that the ground state is close to the ground state of the exact model. There is also a high overlap per site between the lowest excited states for the local and the exact models, although the energies of the low-lying excited states are modified to some extent for the system sizes considered. We also briefly discuss possibilities for realizing the local models in ultracold atoms in optical lattices.
Integrated Pest Management for Turf

One of the “buzz words” today in commercial agriculture and urban horticulture is integrated pest management (IPM), a concept that amounts to more than just the same old method of pest control wrapped up in a new package. IPM is defined as multiple tactics used in a compatible manner in order to maintain pest population below levels that cause economic or unacceptable aesthetic “injury without posing a hazard to humans, domestic animals, or other nontarget life forms. Integrated means that a broad interdisciplinary approach is taken, using scientific principles of plant protection, to fuse into a single system a variety of management strategies and tactics. This integration of techniques must be compatible with sound turf management practices, and it must be economically feasible. Pests include all biotic agents (that is, insects, nematodes, weeds, fungi, viruses, and vertebrates) that adversely affect turf species. Tactics include regulatory, genetic, cultural, biological, physical, and chemical procedures.
A Citizen-Contributed GIS Approach for Evaluating the Impacts of Land Use on Hurricane-Harvey-Induced Flooding in Houston Area

Hurricane Harvey (2017) caused widespread flash flooding by extremely heavy rainfall and resulted in tremendous damage, including 82 fatalities and huge economic loss in the Houston, Texas area. To reduce hazards, loss, and to improve urban resilience, it is important to understand the factors that influence the occurrence of flooding events. People rely on natural resources and different land uses to reduce the severity of flood impacts and mitigate the risk. In this study, we focused the impacts of land use on Hurricane-Harvey-induced flooding inside and outside the Houston city center. With the recent trend that more citizen scientists serve in delivering information about natural disaster response, local residents in Houston areas participated in delineating the flooded areas in Hurricane Harvey. The flooding information used here generated a published map with citizen-contributed flooding data. A regional model framework with spatial autocovariates was employed to understand those interactions. Different land use patterns and types affected the potential of flooding events differently inside and outside Houston’s city center. Explicitly, we found agricultural and open space were associated with high risk of flooding outside the city center, industrial lands increased the high risk of flooding in city center, and residential areas reduced the potential of flooding both inside and outside the city center. The results can assist with future land use strategy in Houston and other areas, and mitigate potential flash flooding. This study also highlighted the contribution of citizen science to responses to natural hazards.
Design of a New Knee Modular Orthotic Device from Cinematic Considerations

IFFERENT human locomotion system cinematic analyses have been developed through diverse methods [1], [2], [3], [5], [12] and [14]. In this paper a human locomotion system cinematic analysis is performed in the walking case of a 4 years old child. The research aim is to design a new knee orthosis which will be used by children that needs a temporal recovery through therapeutic procedures only for walking activity. The children are permanently in growth and that is the main fact that restricts the orthosis design research area. For this we propose here the development of a new orthosis type which consists in modules that can be modified by depending the chidrens age, sex, weight, height, etc. For this is necessary to study the whole locomotion system from a cinematic viewpoint when perform a single gait. A cinematic analysis of a mechanical model consists in solving two important problems: cinematic direct problem and cinematic inverse problem. The cinematic direct problem’s frame, the displacements from cinematic joint are known, and it will be determined the positions – orientation, speeds and accelerations of the mechanism elements or some characteristic points onto the analyzed mechanism. The cinematic inverse problem, cinematic parameters for some characteristic points motion are known, and it will be determined the cinematic joints relative motions parameters. With these, in the cinematic analysis context, we identify many problems such as: positional problem, speed problem, accelerations problem. Each of these problems presents a direct or inverse aspect.
Heat Shock Proteins in Exercise : A Review

This review has attempted to highlight some of the most recent and original studies involving the stress response. It is clear that, especially regarding in vivo human studies, there is a paucity of research regarding the SPR stimulus, it‟s signalling system, measurement concepts, chronic adaptations, and it‟s practical use in both the health and elite sporting performance fields. In addition, the differences in exercise intensity, mode duration, subjects, training status etc. contribute to disparity in findings from previous studies.
Cross Corpus Emotion Classification Using Survey Data

Although semantic analysis and machine learning are becoming well established parts of Natural Language Processing (NLP), extraction of discrete emotions from text remains an under-developed area. Even less frequently do we see application of these technologies to open-ended survey questions in fields such as political science, psychology, public policy and sociology. In these domains, the need for more fined-grained emotion analysis of text responses has become apparent, particularly for assessing nuanced responses of the population to unexpected high impact events or incidents. Doing such assessments in real time is even more difficult. We report preliminary results on an ambitious attempt to perform a cross-corpus emotion classification that applies data gathered in one survey to text collected at a different time from different sources. This research is one step in a broader agenda to create new NLP methods to code large-scale text data from surveys and social media to improve studies of emotion contagion through social media networks. Our report is based on a medium-scale experiment from a survey conducted in the Fall of 2016 during a crisis event. Preliminary evidence suggests that with careful calibration of survey instruments, and proper understanding of natural language expressions (encoded as machine learning features), a transfer of classification code should be possible for some strongly expressed and potentially actionable emotions, like anger. 12
A retrospective and prospective look at inclined heterolithic stratification of tidal-fluvial point bars of the middle McMurray Formation of Northeastern Alberta, Canada

Within academia and industry, there is a renaissance occurring, reforming our understanding of point bars and more specifically tidal-fluvial point bars of the fluvial-to-marine transition zone. Though early workers (Jackson 1975; 1976;1981; Bridges and Leeder, 1976; Allen et al.,1980, Reineck and Singh, 1980; Mossop and Flach, 1983; Miall, 1985; Thomas et al., 1987; Smith 1988; Wightman and Pemberton, 1997; Hein et al., 2000; Ranger and Gingras, 2001; etc.) of point bars and bars within the fluvial-marine transition provided fundamental insights which guide current thinking, in the past five years, marked advancements have reshaped our understanding of the processes (Willis and Tang, 2010; Dalrymple et al., 2011; Martinius and Van den Berg, 2011; Nittrouer et al., 2012; Ashworth and Lewin, 2012; Sisulak and Dashtgard, 2012; Blum et al., 2013); geomorphological elements (Smith et al.,2009; Hubbard et al., 2011; Musial et al., 2011; Fustic et al., 2012); architectural elements (Labreque et al., 2011; Jablonski 2012; Nardin et al., 2012;) and ultimately the deposits of tidal-fluvial point bars. This renaissance in tidal-fluvial understanding has largely been spurred by great interest in the bituminous Lower Cretaceous (Aptian-Albian) McMurray Formation which is interpreted to be deposited within the fluvial-marine transition zone. Furthermore, a large proportion of the middle McMurray Formation was deposited within tidal-fluvial point bar environments, which can be dominantly composed of inclined heterolithic stratification (IHS; Thomas et al., 1987). In Situ bitumen extraction techniques (i.e., SAGD) appear to be extremely sensitive to reservoir heterogeneity associated with the distribution of this IHS, particularly the silt beds (Strobl et al., 1997; Nardin et al., 2012; Strobl, 2012). This prompted current and ongoing research into the developing a better understanding of 3-dimensional architecture, spatial distribution and depositional processed related to these IHS packages of tidal-fluvial point bars. During two field campaigns within the Fort McMurray area, insight into seasonal IHS development was established. The Type Section, Abasand, Mackay Gauging Station, Steepbank River outcrops and the CNRL Bridge Section are all areas of current study for their diversity in form and diversity of IHS (Fig. 1). Fustic et al., (2012) synthesized previously established models (Smith, 1985; Wood, 1989, Wightman and Pemberton, 1997) to suggest that tidal-fluvial point bars have a general trend “around the bend” (i.e., sand -dominated to sandy IHS to muddy IHS both laterally and downstream; Fig 2A) and that the proportion of upper point bar versus lower point bar deposits increases in progressively younger point bar layers, resulting in a wedge shaped geometry of the lower
DYADIC RELATIONS OF PERSONS WITH DISABILITIES: COPING AND PSYCHOLOGICAL WELL-BEING

Studying the close relations of people with disabilities seems to us an important and socially acute problem with practical significance and meeting the social demand of the society. The study is devoted to the study of coping and psychological well-being of the dyad of persons with disabilities. Dyad groups of partners with normative and impaired development differ significantly in their main indicators (dyadic coping strategies, aspects of dyadic relations, level of well-being).
Interactions between Democracy and Environmental Quality: Toward a More Nuanced Understanding

This paper seeks to contribute to existing debates on the relationship between democracy and environmental quality. More specifically, we aim to provide nuance and insight into the question as to whether democratic regimes are better equipped to protect the environment. After critically reviewing theoretical arguments and providing an overview of existing empirical studies, the paper proposes an approach which consists of the use of non-parametric correlations between democracy and environmental quality, and a consideration of the interactions between democracy, government effectiveness, economic prosperity, and perceptions of corruption. Crucially, we show that, although a positive correlation can be found between levels of democracy and environmental quality, the picture is somewhat blurred if data are stratified using criteria such as government effectiveness and corruption perceptions. Consequently, the main argument the paper pursues is that, to assess the relationship between democracy and environmental quality, intervening factors and their effects need to be acknowledged and taken into account.
Deep learning for improved prediction of late-onset cardiomyopathy among childhood cancer survivors: A report from the St. Jude Lifetime Cohort (SJLIFE).

10545 Background: Early identification of survivors at high risk for treatment-induced cardiomyopathy may allow for prevention and/or early intervention. We utilized deep learning methods using COG guideline-recommended baseline electrocardiography (ECG) to improve prediction of future cardiomyopathy. Methods: SJLIFE is a cohort of 5-year clinically assessed childhood cancer survivors including baseline ECG measurements. Development of cardiomyopathy was identified from clinical and echocardiographic measurement using CTCAE criteria (grade 3-4). We applied deep learning approaches to ECG, treatment exposure and demographic data obtained at baseline SJLIFE assessment. We trained a cascaded model combining a 12-layer 1D convolutional neural network to extract features from waveform ECG signals with a 2-layer dense neural network to embed features from other phenotypic data in tabular format to determine if use of deep learning with ECG data could improve prediction of cardiomyopathy. Results: Among 1,218 subjects (median age 31.7 years, range 18.4-66.4) without cardiomyopathy at baseline evaluation, 616 (51%) were male, 1,041 (85%) white, 157 (13%) African American and 792 (65%) were survivors of lymphoma/leukemia. Follow-up averaged 5 (0.5 to 9) years from baseline examination. Mean chest radiation dose was 1350 cGy (range 0 to 6,200 cGy) and mean cumulative anthracycline dose was 191 mg/m2 (range o to 734 mg/m2). A total of 114 (9.4%) survivors developed cardiomyopathy after baseline. A cascaded deep learning model built on a training set (N = 974 participants) classified cardiomyopathy in the test set (N = 244 participants) using both clinical and ECG data with a sensitivity of 70%, specificity of 73%, and AUC of 0.74 (95% CI 0.63-0.85), compared to a model using clinical data alone (sensitivity 61%, specificity 62%, and AUC 0.67, 95% CI 0.56-0.79). In subgroup analyses, models predicting cardiomyopathy within 0-4 years following baseline had a sensitivity, specificity, and AUC of 77%, 78%, and 0.78 (0.65-0.91), respectively. When predicting cardiomyopathy 5-9 years following baseline, model performance dropped to a sensitivity, specificity, and AUC of 70%, 70%, and 0.68 (0.50-0.87), respectively. Conclusions: Deep learning using ECG at baseline evaluation significantly improved prediction of cardiomyopathy in childhood cancer survivors at high risk for cardiomyopathy. Future directions will incorporate deep learning approaches to echocardiography to further improve prediction.
Learning Search Policies in Large Commonsense Knowledge Bases by Randomized Exploration

Deep deductive reasoning is a critical problem for cognitive systems. Very large knowledge bases have millions of axioms, of which relatively few are relevant for answering any given goal query. A large number of irrelevant axioms overwhelm theorem provers, and even simple queries cannot be answered in reasonable time. Therefore, heuristics which help in identifying useful inference paths are an essential component of cognitive systems. In this paper, we learn search control knowledge by taking random samples in the search space and evaluating the quality of resulting paths. These random probes help us to identify relevant inference paths for queries. Experimental results on difficult queries from the Cyc KB show that this approach can be applied effectively to reduce inference time.
ENHANCING THE STACK SMASHING PROTECTION IN THE GCC

The paper addresses the problem of stack smashing or stack overflows in modern operating systems. We focus on a security solution for this problem, namely compiler generated canary protection and, to be more specific, we consider the Stack Smashing Protector (SSP) present in the most popular C compiler, the GCC. We first analyze the limitations of the GCCs SSP and then present three improvements that will harden the security offered by the SSP making an attackers attempt more difficult. All improvements refer to the most recent version of GCC, 4.6. 2.
THE ROLE OF COMMUNICATION AND COLLABORATION INFLUENCING TEACHERS’ PROFESSIONAL MOTIVATION

The article addresses one of the most important factors of teachers’ professional motivation, communication and collaboration, in the context of the education process understood as a system of interaction of all members of the education process. The main idea of the empirical research introduced in this article is to reveal and generalise aspects of communication and collaboration in Lithuanian non-formal music education (in music schools), while thoroughly analysing the aspect of relationships between an educator and students, an educator and parents, an educator and an educator, an educator and a school principal. The research shows that the relation between teacher and student in the process of music education is clearly characteristic of manifestations of authoritarianism in education. When evaluating manifestation of the relationship between a teacher and parents, a teachers’ positive attitudes towards mutual collaboration have been found out; nevertheless, interrelations among teachers in school are based on competitiveness. The relationship between a school principal and teachers is ambiguously evaluated by teachers themselves: in some cases, it is characterised as positive, whereas in other cases it is perceived as negative; nevertheless, in all cases it is considered as making an impact on the entire education process.
Keeping up with the Neighbors: Social Interaction in a Production Economy

It is well-documented that individuals care about how others around them are doing. This paper studies a production economy in which consumers provide labor supply to a representative firm to earn income for consumption, and their utility depends on their own leisure time, their own consumption level, as well as their neighbors’ consumption levels. We characterize the unique equilibrium for such an economy, allowing for three different types of effects of the neighborhood size: linear effect, zero effect, and nonlinear effect. Four network structures (empty network, ring network, star network, and core-periphery network) with different production technologies are analyzed. Our work contributes to a better understanding of the general equilibrium effect of social preferences and network structures.
Private Litigation Costs and Voluntary Disclosure: Evidence from the Morrison Ruling

We examine the causal effect of expected private litigation costs on voluntary disclosure using a natural experiment, the Supreme Court ruling in Morrison v. National Australia Bank. Even though this ruling had no effect on what constituted fraudulent conduct for the purpose of securities litigation, it significantly reduced the expected private litigation costs for foreign cross-listed firms by reducing the pool of potential claimants. It did so by eliminating the right of shareholders who purchased shares on non-U.S. exchanges from seeking compensation in U.S. courts. In the post-Morrison period, we find consistent evidence showing a decrease in voluntary disclosure using analyses that exploit the varying impact of the ruling based on both firm- and country-level attributes. Unlike a number of prior studies, we find that the positive relation between litigation and disclosure does not depend on the direction of the news. JEL Classifications: G15; G18; M41. Data Availability: Data are available from the public sources cited in the text.