Miracle-dz/UniFAR-FTUs huggingface dataset:
Gastropod Seed Dispersal: An Invasive Slug Destroys Far More Seeds in Its Gut than Native Gastropods

Seed dispersal is one of the most important mechanisms shaping biodiversity, and animals are one of the key dispersal vectors. Animal seed dispersal can directly or indirectly be altered by invasive organisms through the establishment of new or the disruption of existing seed dispersal interactions. So far it is known for a few gastropod species that they ingest and defecate viable plant seeds and consequently act as seed dispersers, referred to as gastropodochory. In a multi-species experiment, consisting of five different plant species and four different gastropod species, we tested with a fully crossed design whether gastropodochory is a general mechanism across native gastropod species, and whether it is altered by the invasive alien slug species Arion lusitanicus. Specifically, we hypothesized that a) native gastropod species consume the seeds from all tested plant species in equal numbers (have no preference), b) the voracious invasive alien slug A. lusitanicus – similarly to its herbivore behaviour – consumes a higher amount of seeds than native gastropods, and that c) seed viability is equal among different gastropod species after gut passage. As expected all tested gastropod species consumed all tested plant species. Against our expectation there was a difference in the amount of consumed seeds, with the largest and native mollusk Helix pomatia consuming most seeds, followed by the invasive slug and the other gastropods. Seed damage and germination rates did not differ after gut passage through different native species, but seed damage was significantly higher after gut passage through the invasive slug A. lusitanicus, and their germination rates were significantly reduced.
NEURAghe

Deep convolutional neural networks (CNNs) obtain outstanding results in tasks that require human-level understanding of data, like image or speech recognition. However, their computational load is significant, motivating the development of CNN-specialized accelerators. This work presents NEURAghe, a flexible and efficient hardware/software solution for the acceleration of CNNs on Zynq SoCs. NEURAghe leverages the synergistic usage of Zynq ARM cores and of a powerful and flexible Convolution-Specific Processor deployed on the reconfigurable logic. The Convolution-Specific Processor embeds both a convolution engine and a programmable soft core, releasing the ARM processors from most of the supervision duties and allowing the accelerator to be controlled by software at an ultra-fine granularity. This methodology opens the way for cooperative heterogeneous computing: While the accelerator takes care of the bulk of the CNN workload, the ARM cores can seamlessly execute hard-to-accelerate parts of the computational graph, taking advantage of the NEON vector engines to further speed up computation. Through the companion NeuDNN SW stack, NEURAghe supports end-to-end CNN-based classification with a peak performance of 169GOps/s, and an energy efficiency of 17GOps/W. Thanks to our heterogeneous computing model, our platform improves upon the state-of-the-art, achieving a frame rate of 5.5 frames per second (fps) on the end-to-end execution of VGG-16 and 6.6fps on ResNet-18.
Engaged Scholarship: A Guide for Organizational and Social Research

1. Engaged Scholarship in a Professional School 2. Philosophy of Science Underlying Engaged Scholarship 3. Formulating the Research Problem 4. Building a Theory 5. Process and Variance Models 6. Designing Variance Studies 7. Designing Process Studies 8. Communicating and Using Research Knowledge 9. Practicing Engaged Scholarship
Iterative evolution of digitate planktonic foraminifera

Abstract Digitate shell morphologies have evolved repeatedly in planktonic foraminifera throughout the Cretaceous and Cenozoic. Digitate species are usually rare in fossil and modern assemblages but show increased abundance and diversity at times during the Cretaceous and middle Eocene. In this paper we discuss the morphology and stratigraphic distribution of digitate planktonic foraminifera and establish the isotopic depth ecology of fossil ones to draw parallels with modern counterparts. δ18O and δ13C values of six extinct and two modern digitate species, from six time slices (Cenomanian, Turonian, Eocene, Miocene, Pleistocene and Holocene) have similar isotopic depth ecologies, consistently registering the most negative δ13C and usually the most positive δ18O compared to coexisting species. These results indicate a similar deep, subthermocline (>150 m) habitat, characterized by lower temperatures, reduced oxygen, and enrichment of dissolved inorganic carbon. This is consistent with water-column plankton studies that provide insight into the depth preferences of the three modern digitate species; in over 70% of observations digitates occurred in nets below 150 m, and down to 2000 m. The correlation between digitate species and subsurface habitats across multiple epochs suggests that elongated chambers were advantageous for survival in a deep mesopelagic habitat, where food is usually scarce. Increased abundance and diversity of digitates in association with some early and mid-Cretaceous oceanic anoxic events, in middle Eocene regions of coastal and equatorial upwelling, and occasionally in some modern upwelling regions, suggests an additional link with episodes of enhanced ocean productivity associated with expansion of the oxygen minimum zone (OMZ). We suggest that the primary function of digitate chambers was as a feeding specialization that increased effective shell size and food gathering efficiency, for survival in a usually food-poor environment, close to the OMZ. Episodes of increased digitate abundance and diversity indicate expansion of the deep-water ecologic opportunity under conditions that were unfavorable to other planktonic species. Our results provide evidence of iterative evolution reflecting common functional constraints on planktonic foraminifera shell morphology within similar subsurface habitats. They also highlight the potential of digitate species to act as indicators of deep watermasses, especially where there was expansion of the OMZ.
Multicast Scheduling for Input-Queued Switches

We design a scheduler for an M/spl times/N input-queued multicast switch. It is assumed that: 1) each input maintains a single queue for arriving multicast cells and 2) only the cell at the head of line (HOL) can be observed and scheduled at one time. The scheduler needs to be: 1) work-conserving (no output port may be idle as long as there is an input cell destined to it) and 2) fair (which means that no input cell may be held at HOL for more than a fixed number of cell times). The aim is to find a work-conserving, fair policy that delivers maximum throughput and minimizes input queue latency, and yet is simple to implement. When a scheduling policy decides which cells to schedule, contention may require that it leave a residue of cells to be scheduled in the next cell time. The selection of where to place the residue uniquely defines the scheduling policy. Subject to a fairness constraint, we argue that a policy which always concentrates the residue on as few inputs as possible generally outperforms all other policies. We find that there is a tradeoff among concentration of residue (for high throughput), strictness of fairness (to prevent starvation), and implementational simplicity (for the design of high-speed switches). By mapping the general multicast switching problem onto a variation of the popular block-packing game Tetris, we are able to analyze various scheduling policies which possess these attributes in different proportions. We present a novel scheduling policy, called TATRA, which performs extremely well and is strict in fairness. We also present a simple weight-based algorithm, called WBA.
An empirical study on clone stability

Code cloning is a controversial software engineering practice due to contradictory claims regarding its effect on software maintenance. Code stability is a recently introduced measurement technique that has been used to determine the impact of code cloning by quantifying the changeability of a code region. Although most existing stability analysis studies agree that cloned code is more stable than non-cloned code, the studies have two major flaws: (i) each study only considered a single stability measurement (e.g., lines of code changed, frequency of change, age of change); and, (ii) only a small number of subject systems were analyzed and these were of limited variety. In this paper, we present a comprehensive empirical study on code stability using four different stability measuring methods. We use a recently introduced hybrid clone detection tool, NiCAD, to detect the clones and analyze their stability in different dimensions: by clone type, by measuring method, by programming language, and by system size and age. Our in-depth investigation on 12 diverse subject systems written in three programming languages considering three types of clones reveals that: (i) cloned code is generally less stable than non-cloned code, and more specifically both Type-1 and Type-2 clones show higher instability than Type-3 clones; (ii) clones in both Java and C systems exhibit higher instability compared to the clones in C# systems; (iii) a system's development strategy might play a key role in defining its comparative code stability scenario; and, (iv) cloned and non-cloned regions of a subject system do not follow any consistent change pattern.
Sleep duration and overweight among Australian children and adolescents

Aim: To examine the association between sleep and overweight and waist circumference (WC) in children and adolescents. Methods: Data were from a nationally representative sample of 6324 7–15‐y‐old males and females from the Australian Health and Fitness Survey. Associations between sleep duration and body mass index (BMI) and WC were examined by analysis of covariance, linear regression, and logistic regression. Results: In the total sample, there was a significant main effect across sleep‐duration categories (≤8 h, 8–9 h, 9–10 h, and ≥10 h) for BMI. Linear regression showed significant age, sex, age‐sleep, and age‐sex‐sleep interactions in the total sample. There was an inverse graded relationship between sleep and BMI and WC in boys. In boys, there was a 1.6–1.8 times greater odds of overweight for those who reported 8–9 h or 9–10 h of sleep compared to those reporting ≥10 h of sleep. For boys reporting ≤8 h of sleep, there was about 3.1 times greater odds of overweight compared to those reporting ≥10 h of sleep. In contrast, no significant associations between sleep and overweight were found in girls.
Distribution Strategies for Durable Goods with Indirect Network Effects

In this paper we examine the influence that indirect network effects have on a durable goods manufacturer’s distribution strategy to lease or sell her product. Previous research has identified that a durable goods manufacturer can mitigate the potential for its own opportunistic behavior with respect to consumers by leasing instead of selling its product. However, we show that leasing creates an opportunity for a durable goods manufacturer to exploit firms that generate indirect network benefits by providing complementary products. As a result, the durable goods manufacturer faces a trade-off between leasing, which mitigates its potential to exploit consumers, and selling, which mitigates its potential to exploit producers of complementary products. In this paper, we examine this trade-off and show how a durable goods manufacturer can use a combination of leasing and selling to balance its strategic commitment across both its own market as well as the complementary market. We also analyze the impact of leasing with an optionto-buy contracts under these situations. (complementary markets, selling versus leasing, leasing with an option-to-buy) ∗The authors are listed in alphabetical order †University of Texas at Austin, Management Department CBA 4.202, Austin, Tx-78712, Sreekumar.Bhaskaran-Nair@phd.mccombs.utexas.edu ‡University of Texas at Austin, Management Department CBA 4.202, Austin, Tx-78712, steve.gilbert@mccombs.utexas.edu
Detection of feline Mycoplasma species in cats with feline asthma and chronic bronchitis

Little is known about the aetiology of inflammatory lower airway disease in cats. The aim of this study was to investigate the role of Mycoplasma species in cats with feline asthma (FA) and chronic bronchitis (CB). The study population consisted of 17 cats with FA/CB, and 14 sick cats without clinical and historical signs of respiratory disease, which were euthanased for various other reasons. Nasal swabs, nasal lavage and bronchoalveolar lavage fluid (BALF) samples were taken from patients from both groups. Mycoplasma species culture with modified Hayflick agar and Mycoplasma polymerase chain reaction (PCR) were performed on all samples followed by sequencing of all Mycoplasma species-positive samples for differentiation of subspecies. PCR testing detected significantly more Mycoplasma species-positive BALF samples than Mycoplasma culture (P = 0.021). When cats with oropharyngeal contamination were excluded from comparison, the numbers of Mycoplasma species-positive BALF samples in the group with FA/CB (6/17) and the control group (4/9) were not significantly different (P = 0.6924). While all nasal samples of the cats with FA/CB were negative for Mycoplasma organisms, five samples in the control group (P = 0.041) were positive on PCR. Sequencing revealed Mycoplasma felis in all PCR-positive samples. Mycoplasma species can be detected in the lower airways of cats with FA/CB, as well as in the BALF of sick cats without respiratory signs. Further studies are warranted to investigate the possibility that Mycoplasma species represent commensals of the lower respiratory tract of cats.
Risk Management and Healthcare Policy Dovepress Improving Health Outcomes with Better Patient Understanding and Education Specific Conditions or Problems Risk Management and Healthcare Policy 2010:3 Types of Interventions Risk Management and Healthcare Policy 2010:3 Information Provision Alone Healt

A central plank of health care reform is an expanded role for educated consumers interacting with responsive health care teams. However, for individuals to realize the benefits of health education also requires a high level of engagement. Population studies have documented a gap between expectations and the actual performance of behaviours related to participation in health care and prevention. Interventions to improve self-care have shown improvements in self-efficacy, patient satisfaction, coping skills, and perceptions of social support. Significant clinical benefits have been seen from trials of self-management or lifestyle interventions across conditions such as diabetes, coronary heart disease, heart failure and rheumatoid arthritis. However, the focus of many studies has been on short-term outcomes rather that long term effects. There is also some evidence that participation in patient education programs is not spread evenly across socio economic groups. This review considers three other issues that may be important in increasing the public health impact of patient education. The first is health literacy, which is the capacity to seek, understand and act on health information. Although health literacy involves an individual's competencies, the health system has a primary responsibility in setting the parameters of the health interaction and the style, content and mode of information. Secondly, much patient education work has focused on factors such as attitudes and beliefs. That small changes in physical environments can have large effects on behavior and can be utilized in self-management and chronic disease research. Choice architecture involves reconfiguring the context or physical environment in a way that makes it more likely that people will choose certain behaviours. Thirdly, better means of evaluating the impact of programs on public health is needed. The Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework has been promoted as one such potential approach. Chronic disease self-management and preventive health programs mainly focus on promoting informed lifestyle choices, risk-factor modification, and active patient self-management of chronic diseases. 1 Such a process relies heavily on better information and communication practices. The logic of health reform that emphasizes preventive and enhanced primary models of care is an expanded role for informed, active consumers interacting with responsive health care teams. 1 Most observers agree that this central role demands improved education and understanding of health behavior and chronic disease management. However, for individuals to realize the benefits of health education also requires a high level of participation and engagement, ie, action or behavior …
Characteristics of Child Maltreatment and Their Relation to Dissociation, Posttraumatic Stress Symptoms, and Depression in Adult Psychiatric Patients

Abstract Little is known about the influence of particular characteristics of childhood maltreatment, such as developmental stage, relationship to the perpetrator, and nature of the trauma, on adult psychopathology. The effects of childhood maltreatment were assessed in adult psychiatric patients (N = 287) using self-rating scales and diagnostic checklists. Maltreatment was strongly associated with dissociation. This relationship was observed for all childhood developmental stages and was strongest when the perpetrator was outside the family. Dissociation was more strongly correlated with childhood emotional abuse and sexual harassment than with sexual or physical abuse. Childhood sexual abuse was found to be associated with symptoms of posttraumatic stress. The findings suggest that dissociation is a relatively specific consequence of childhood maltreatment that is largely independent of the familial relationship to the perpetrator or the child’s developmental stage.
Comparison of quality of life among cardiac, hepatic, cancer, and dermatological patients.

OBJECTIVE To assess the level of quality of life (QOL) in patients suffering from various cardiac, cancer, hepatic, and dermatological diseases. METHOD A total of 339 patients of cardiac, cancer, hepatic, and dermatological diseases from DHQ/Allied hospitals of Faisalabad participated in this study through purposive convenient sampling technique. Quality of life was measured by WHO QOL-BREF (Validated Urdu Version) while demographic variables were recorded on a demographic sheet. The results were obtained by using analysis of variance (ANOVA) on SPSS 13. RESULTS Out of 339, 156 (46%) patients were males while 183 (54%) patients were females. Of the total, 99 (29.2%) belonged to the lower socio economic status, 113 (33.3%) belonged to the lower middle, 62 (18.3%) belonged to the middle, and 65 (19.2%) belonged to the upper middle socio economic status. In terms of education, 49 (14.5%) were illiterate, 110 (32.3%) had primary level education, 118 (34.8%) had middle level education, 21 (6.2%) had done matriculation, 17 (5%) had intermediate, 14 (4.1%) were graduates, 8 (2.4%) had done masters. Of the whole lot, only 2 (0.6%) patients were professionals. Results showed that the quality of life was most deteriorated in the domain of physical health; while psychological health was the second most deteriorated domain. Social relationship was the least affected domain, while environment was the second least affected area. Quality of life of hepatic patients was significantly lower than dermatological patients with respect to physical health and environment, lower than cancer patients in relation to psychological health, and lower than cardiac patients in the social relationship domain. The quality of life of cardiac patients was noted to be significantly higher than the other three categories in the domains of psychological health and environment. CONCLUSION In the face of the evidence of high deterioration in the quality of life of the patients in terms of physical and psychological health, medical units should be better equipped with facilities to enhance a sense of betterment in patients. The treating doctors should be better trained to give due consideration to this important aspect of management. Moreover, the role of liaison psychiatry should also be incorporated.
Evolutionary Computation in Financial Engineering: A Roadmap of GAs and GP

In this and previous issues, R. Baker and S. Smith has introduced the techniques of evolutionary computation and their application to nancial engineering. In this article, we would like to rst summarize a few major insights revealed in those two articles and then provide a roadmap for readers to initialize their own trails. First of all, why evolutionary computation? Where is the motivation? In engineering or applied mathematics, evolutionary computation has been extensively applied to problems whose solution space is irregular, i.e., too large and highly complex, so that it is di cult to employ conventional optimization procedures to search for the global optimum. For those who are interested in nancial econometrics, Dorsey and Mayer (1995) is a good reference to help one have a taste of this kind of solution space. In this study, Dorsey and Mayer listed several irregular features of the likelihood function (the search space) frequently encountered in econometrics. They selected 11 test problems, and showed the advantages of genetic algorithms over many general-purpose direct-search algorithms such as simplex, adaptive random search, and simulated annealing. Now, are solution spaces for most nancial optimization problems irregular? My answer is yes, and I am not alone to entertain such a view. General acceptance of this property has in fact fostered the growth of the eld nancial engineering. Take nancial forecasting for example. There is a tendency to jettison the early well-accepted random walk hypothesis or the unpredictability of nancial time series. In the literature, nonlinear models such as arti cial neural networks have proved to be capable of beating random walks not only statistically signi cantly but also economically signi cantly (Rauscher, 1997). Su ce it to say, many nonlinear models have the potential to beat the random walk but the search space of nonlinear models is doubtlessly large and complex. Similarly, in technical analysis, search over the space of trading rules is obviously a daunting task. But, is evolutionary computation the only choice for us to cope with the irregular search space? Of course not. There are many equally promising tools available in the machine learning literature. However, evolutionary computation should not be considered as a kind of optimization technique to compete with other alternative techniques but an optimization principle to be incorporated with existing techniques. It is more a complement to than a substitute for many existing techniques. For example, the application of evolutionary computation to arti cial neural networks has generated one of most promising research areas known as evolutionary articial neural networks, (EANNs) (Yao, 1993), to which we shall come back later. For now let me introduce evolutionary computation as an optimization principle.