Miracle-dz/UniFAR-FTUs huggingface dataset:
Inter-annual variability in the breeding performance of seabirds in relation to oceanographic anomalies that affect the Crozet and the Kerguelen sectors of the Southern Ocean

Global warming is expected to increase the frequency and intensity of inter-annual variation in Sea-Surface Temperatures (SST) associated with a latitudinal shift of frontal structures in the Southern Ocean. However, the long-term consequences of these major climatic events on the biotic environment remain poorly understood. We studied the effect of SST anomalies in the southern Indian Ocean on the breeding success of eight seabird species, and found these temperature anomalies to have different effects depending on the foraging habitat of the species. The breeding success of four seabird species foraging mainly south of the Polar Front in Antarctic waters was significantly depressed by warm SST occurring mainly in winter and spring, prior to breeding. Conversely, warm SST anomalies were associated with a higher breeding success for species foraging mainly north of the Polar Front, while no significant effect was found for two species that forage on the Kerguelen plateau. These different responses to changes in the SST were also observed for two closely related species (sooty albatross Phoebetria fusca and light-mantled sooty albatross P. palpebrata) breeding at Kerguelen. These observations highlight the importance of multi-species long-term monitoring programs for understanding the ecological consequences of environmental variability. Our results suggest that the predicted southward shift of the Polar Front caused by oceanic warming could lead to an important decrease in the breeding performance of top predator seabirds depending on the location and changes of their foraging habitat in relation the Polar Front.
Estimation of cardiac preload changes by systolic pressure variation in pigs undergoing pneumoperitoneum

Background: Variations in systolic pressure arterial waveform (SPV) and its component have been shown to be a reasonable indicator of left ventricular preload. Creation of a pneumoperitoneum (PMOP) by insufflation of CO2 increases intrathoracic pressure, leading to overestimation of preload as assessed by pressure methods. The purpose of this study was to compare SPV with other standard methods in anaesthetized pigs.
Hospital to Community Transitions for Adults: Discharge Planners and Community Service Providers’ Perspectives

Discharges from the hospital to community-based settings are more difficult for older adults when there is lack of communication, resource sharing, and viable partnerships among service providers in these settings. The researchers captured the perspectives of three different groups of participants from hospitals, independent living centers, and Area Agencies on Aging, which has rarely been done in studies on discharge planning. Findings include identification of barriers in the assessment and referral process (e.g., timing of discharge, inattention to client goals, lack of communication and partnerships between hospital discharge planners and community providers), and strategies for overcoming these barriers. Implications are discussed including potential for Medicaid and Medicare cost reductions due to fewer re-hospitalizations.
COSMIC REIONIZATION ON COMPUTERS: NUMERICAL AND PHYSICAL CONVERGENCE

In this paper I show that simulations of reionization performed under the Cosmic Reionization On Computers project do converge in space and mass, albeit rather slowly. A fully converged solution (for a given star formation and feedback model) can be determined at a level of precision of about 20%, but such a solution is useless in practice, since achieving it in production-grade simulations would require a large set of runs at various mass and spatial resolutions, and computational resources for such an undertaking are not yet readily available. In order to make progress in the interim, I introduce a weak convergence correction factor in the star formation recipe, which allows one to approximate the fully converged solution with finite-resolution simulations. The accuracy of weakly converged simulations approaches a comparable, ~20% level of precision for star formation histories of individual galactic halos and other galactic properties that are directly related to star formation rates, such as stellar masses and metallicities. Yet other properties of model galaxies, for example, their H i masses, are recovered in the weakly converged runs only within a factor of 2.
The Pragmatics of Cooperation and Relevance for Teaching and Learning

This study aims at investigating first language attrition in Persian speakers of English as L2. Three groups are compared: Persian monolinguals, early bilinguals and late bilinguals. An acceptability judgment test is used in which the test sentences consist of pairs of sentences each of which follow either the English structure or the Persian structure in three syntactic areas of relative clause, adverb position and pro-dropping which constitute three main areas of syntactic differences between Persian and English. The results revealed that the type and degree of L1 attrition that early bilingual speakers undergo is different compared to late bilinguals and the degree of L1 education conditions attrition. The implication is that age of L2 acquisition has a major influence on how bilinguals represent their L1: late bilinguals often retain a large amount of underlying competence in their first language while early bilinguals lose it more quickly. Introduction The notion of language attrition has been a topic of investigation for more than three decades. It attracted the attention of language researchers in the late 1970’s and subsequently the inaugural conference on Attrition of Language Skills at the University of Pennsylvania (Upenn) in 1980 was a turning point for research in this field. Before the conference, ‘language loss’ was used to refer to pathological disorders such as aphasia, or language disorders caused by tumors, strokes, or traumas to the head (Smith & Wilson, 1979, Yağmur, 2004). This conference was a starting point for further research and conferences that probed into the process of language loss as a non-pathological disorder from many other perspectives. From a non-pathological perspective, the idea of language loss first rose with reference to foreign language students who had spent an enormous amount of time learning a second language but subsequently lost it as time passed. The study of first language attrition began in the early 1980’s with Richard D. Lambert’s interest in language loss. As one of the organizers of the inaugural UPenn conference and coeditor of the following conference volume by Lambert & Freed (1982), Lambert was a pioneer in steering attention to the language loss that happens so often among
Software Engineering 2010 - Fachtagung des GI-Fachbereichs Softwaretechnik, 22.-26.2.2010 in Paderborn

This paper describes various techniques for improving productivity in the development of software-based systems. These build on having a strong foundation regarding people and processes. On this solid foundation, it is important to do requirements engineering well so that you develop the right functionality, elicit also the non-functional requirements, and have testable requirements. Structure the system to avoid unnecessary complexity and to take advantage of reuse. During the development use an iterative and lean approach to ensure that the product is realized as efficiently as possible. Finally, work at a higher level of abstraction through model-driven approaches and take advantage of automation provide additional improvements to productivity.
A proposed new model for maintainability index of open source software

Software metrics play a key role in measuring attributes that are important for the success of a software project. Measurements of these metrics tell us various key aspects of system. This in turn supports knowledgeable decision making by which we can enhance the quality of system. Maintenance is a process of revisions or corrections made to software systems after their first release. The key feature of software development is change. Hence it is important to develop software that is easy to modify and is thus maintainable. This paper evaluates the existing Oman and Hagemeister maintainability index model which calculates maintainability index (MI) based on Cyclomatic Complexity, Lines of code and Halsted volume. For this purpose, software metric datasets of Lucene, which is open source software of 163085 lines of code are used, and it is shown that the existing Oman and Hagemeister maintainability index mode model is not a good a predictor of maintainability. A new maintainability index model is proposed with a new set of predictor metrics. The new proposed model is a marked improvement over the existing Oman and Hagemeister maintainability index model. The coefficient of determination (R2) of the new proposed maintainability model is 0.984 and correlation coefficient(R) is 0.992 as compared to the Oman and Hagemeister model whose correlation coefficient(R) is 0.320.
Experiments showing an improvement of angular resolution by LMMSE-based processing

Azimuth target resolution is of crucial importance in many applications of radar. The primary radar parameter affecting the azimuth resolution is the antenna beamwidth. However, in practice, standard signal processing techniques require the distance between targets to be more than one resolution cell. This can prove inadequate for several relevant applications. This paper describes the results obtained from experiments aimed at testing the capabilities of angular resolution between targets separated by less than the beamwidth in azimuth by means of linear minimum mean square error, LMMSE, -based processing. Results show the capabilities of this technique of separating targets in such a scenario. The processing scheme shows a strong improvement in the resolution capability with respect to standard techniques.
Building Green with Nanotechnology

Nanotechnology, the manipulation of matter at the molecular scale, is opening new possibilities in green building through products like solar energy collecting paints, high-insulating translucent panels, and heatabsorbing windows. Even more dramatic breakthroughs are now in development such as spray-on solar collecting paint, windows that shift from transparent to opaque with the flip of a switch, and environmentally friendly biocides for preserving wood. These breakthrough materials are opening new frontiers in green building, offering unprecedented performance in energy efficiency, durability, economy and sustainability. This paper provides an overview of nanotechnology applications for green building, with an emphasis on the energy conservation capabilities of architectural nanomaterials in green building.
Subacute ruminal acidosis: prevalence and risk factors in Greek dairy herds

Summary Subacute ruminal acidosis (SARA) represents one of the most important metabolic subclinical disorders of high producing dairy cows, having serious impact in both animal health and herd profitability. The aim of this study was to confirm the presence of SARA in Greek dairy herds and record its prevalence and risk factors. Ruminal fluid samples, via rumenocentesis, were obtained from a total of 153 Holstein dairy cows, from 12 herds (≥12 cows per herd). Rumen pH was measured on-site with a portable pH-meter in order to establish a SARA diagnosis. Almost sixteen percent (24/153) of the sampled cows were found with rumen pH ≤5.5, which is indicative of SARA. Thirty three percent (4/12) of the herds were SARA-positive, 8.33% (1/12) of the herds were SARA-marginal, and 58.33% (7/12) were SARA-negative. Number of lactating cow groups, order in which the feeds were added into the mixing wagon, particle length size, ration composition, housing type (free stall or bedded pack) and stocking density significantly influenced the presence of SARA.
Evaluation of Buccal Infiltration with Articaine and Inferior Alveolar Nerve Block with Lignocaine for Pulp Therapy in Mandibular Primary Molars.

OBJECTIVE Failure of inferior alveolar nerve block in achieving profound anesthesia of the pulp due to various reasons has led to the introduction of more potent local anesthetic agents like articaine. This study was conducted to compare the efficacy of buccal infiltration with articaine in achieving pulpal anesthesia of primary molars as compared to inferior alveolar nerve block with lignocaine. STUDY DESIGN 30 patients (4-8 years) with indication of pulp therapy in at least two mandibular primary molars were selected. Patients were randomly assigned to receive nerve block with lignocaine or infiltration with articaine on first appointment and the other solution on second appointment. All the pulpotomies and pulpectomies were performed by a pediatric dentist. Two researchers standing at a distance of 1.5 m recorded the Pain Scores and Sound, Eye, Motor (SEM) scores. After the completion of procedure, the patient was asked to record the Facial Image score and Heft-Parker Visual Analogue Score (HP-VAS). RESULTS Pain Score recorded at the time of injection showed significantly more movements with block as compared to infiltration (p<0.001). SEM scores at time of pulp extirpation were also higher for block than infiltration (p<0.001). CONCLUSION Articaine infiltration has the potential to replace inferior alveolar nerve block for primary mandibular molars.
Membrane-Associated TGF-β1 Inhibits Human Memory T Cell Signaling in Malignant and Nonmalignant Inflammatory Microenvironments1

TGF-β1 is present on cells derived from the microenvironment of human lung tumors and nonmalignant inflammatory tissues. We establish that this cell-associated cytokine mediates hyporesponsiveness of the memory T cells in these microenvironments in situ by blocking TCR signaling. T cells derived from these tissues failed to translocate NF-κB to the nucleus in response to CD3 + CD28 cross-linking. This nonresponsiveness was reversed by an anti-TGF-β1-neutralizing Ab. Refractoriness of the memory T cells to TCR activation was also reversed by the removal of TGF-β1 by briefly pulsing the cells in a low pH buffer. Addition of exogenous TGF-β1 to eluted T cells re-established their nonresponsive state. Neither TGF-β1, anti-TGF-β1 Ab, nor low pH affected TCR signaling potential of peripheral blood T cells. We conclude that TGF-β1 mediates a physiologically relevant regulatory mechanism, selective for memory T cells present in the tumor microenvironment and nonmalignant chronic inflammatory tissues.
Review: Autophagy: Definition, Molecular Machinery, and Potential Role in Myocardial Ischemia-Reperfusion Injury

Autophagy is the endogenous, tightly regulated cellular "housekeeping" process responsible for the degradation of damaged and dysfunctional cellular organelles and protein aggregates. There is a growing consensus that autophagy is upregulated in the setting of myocardial ischemia-reperfusion. Moreover, emerging data suggest that autophagy may serve as an adaptive process and confer increased resistance to ischemia-reperfusion injury. Our aims in this review are to (1) provide a brief synopsis of process of autophagy (including an overview of the key molecular mediators of this catabolic process and its relationship with other cardiac signaling pathways) and (2) most importantly, summarize the current evidence for versus against the intriguing concept of autophagy-mediated cardioprotection.
Human Immunodeficiency Virus Type 1 Nef Expression Prevents AP-2-Mediated Internalization of the Major Histocompatibility Complex Class II-Associated Invariant Chain

ABSTRACT The lentiviral Nef protein has been studied extensively for its ability to induce the downregulation of several immunoreceptors on the surfaces of infected cells. However, Nef expression is unique in inducing highly effective upregulation of the major histocompatibility complex class II-associated chaperone invariant (Ii) chain complexes in different cell types. Under normal conditions, endocytosis of the Ii chain and other molecules, like the transferrin receptor and CD4, is rapid and AP-2 dependent. Human immunodeficiency virus type 1 (HIV-1) Nef expression strongly reduces the internalization of the Ii chain, enhances that of CD4, and does not modify transferrin uptake. The mutation of AP-2 binding motifs LL164 and DD174 in Nef leads to the inhibition of Ii chain upregulation. In AP-2-depleted cells, surface levels of the Ii chain are high and remain unmodified by Nef expression, further indicating that Nef regulates Ii chain internalization via the AP-2 pathway. Immunoprecipitation experiments revealed that the Ii chain can interact with Nef in a dileucine-dependent manner. Importantly, we have shown that Nef-induced CD4 downregulation and Ii chain upregulation are genetically distinguishable. We have identified natural nef alleles that have lost one of the two functions but not the other one. Moreover, we have characterized Nef mutant forms possessing a similar phenotype in the context of HIV-1 infection. Therefore, the Nef-induced accumulation of Ii chain complexes at the cell surface probably results from a complex mechanism leading to the impairment of AP-2-mediated endocytosis rather than from direct competition between Nef and the Ii chain for binding AP-2.
Control of the size and shape of TiO2 nanoparticles in restricted media

Template-capped TiO2 nanostructures have been synthesized. In certain template conditions, TiO2 hexagons are found to form. These hexagonal structures can be effectively sensitized by fluorescein dye without any change in the protonation state of the dye. Bare TiO2 nanoparticles are not so useful for sensitization with dyes like fluorescein as they alter the dye protonation state. The novelty of this work is twofold—the hitherto elusive hexagonal phase of TiO2 nanoparticles has been stabilized and the synthesis of TiO2 in the rutile phase has been achieved under mild conditions.
MA-SSR: A Memetic Algorithm for Skyline Scenic Routes Planning Leveraging Heterogeneous User-Generated Digital Footprints

Most existing trip planning work ignores the issue of planning detailed travel routes between points of interest, leaving the task to online map services or commercial Global Poisioning System (GPS) navigators. However, such a service or navigator cannot meet the diverse requirements of users. Particularity, in this paper, we aim at planning travel routes that not only minimize the distance but provide high-quality sceneries along the way as well. To this end, we propose a novel two-phase framework to plan travel routes efficiently in a large road network considering multiple criteria, i.e., both the quality of the scenic view and the travel distance. In the first phase, we enrich the edges and assign a proper scenic view score for each of them by extracting relevant information from heterogeneous digital footprints of geotagged images and check-ins. In the second phase, on the top of the enriched road network, given users’ trip queries, we employ the concept of skyline operator and propose a memetic algorithm (MA) to discover a set of equally optimal routes with diverse travel distances for users to pick from. Finally, to validate the efficiency and effectiveness of the proposed framework, we conduct extensive experiments on three real-world datasets from the Bay Area in the city of San Francisco, CA, USA, which contain a road network with 3771 nodes and 5940 edges crawled from OpenStreetMap, more than 31 000 geotagged images generated by 1571 Flickr users in one year; and 110 214 check-ins left by 15 680 Foursquare users in six months. Results demonstrate that the MA yields high-quality solutions that are reasonably close to the optima but within desirable computation time and considerably better than the baseline solutions obtained by genetic algorithms.
Inhibition of class II phosphoinositide 3-kinase γ expression by p185Bcr–Abl contributes to impaired chemotaxis and aberrant homing of leukemic cells

The expression of p185Bcr–Abl in Ba/F3 cells inhibits the chemotactic response of these cells to SDF1α. A mutant p185Bcr–Abl with deletion of amino acids from 176 to 426 (p185Δ176–426) is deficient in suppressing SDF1α-stimulated chemotaxis. Comparison of the gene expression profiles among parental Ba/F3 cells and cells transformed by p185Bcr–Abl and p185Δ176–426 reveals that class II phosphoinositide 3-kinase γ (PI3KC2γ) expression is markedly down-regulated by p185Bcr–Abl but not p185Δ176–426. Furthermore, knockdown of PI3KC2γ expression in p185Δ176–426 cells is sufficient to suppress SDF1α-stimulated chemotaxis and to promote infiltration of these cells into the liver. Together, these studies suggest that inhibition of PI3KC2γ expression may represent a mechanism by which Bcr–Abl suppresses SDF1α-induced chemotaxis and induces abnormal homing of leukemic cells.
Resource Constrained Exploration in Reinforcement Learning

This paper examines temporal difference reinforcement learning (RL) with adaptive and directed exploration for resource-limited missions. The scenario considered is for an energy-limited agent which must explore an unknown region to find new energy sources. The presented algorithm uses a Gaussian Process (GP) regression model to estimate the value function in an RL framework. However, to avoid myopic exploration we developed a resource-weighted objective function which combines an estimate of the future information gain using an action rollout with the estimated value function to generate directed explorative action sequences. The results show that under this objective function, the learning agent is able to continue exploring for better state-action trajectories when platform energy is high and follow conservative energy gaining trajectories when platform energy is low.
Semantics in Deep Neural-Network Computing

Artificial Intelligence development is stepping into a new era due to the recent exciting achievements from neural network and statistical machine learning research communities. Statistic neural-computing based machine learning has been deemed as one of promising roads towards realizing the ideal of Artificial Intelligence promoted since last century. Learning is the key in making progress. Statistic machine learning is to obtain a probability distribution or a function from a set of training samples according to a certain optimization target over the training cost based on a predefined model. While there are many significant improvements in image, sound and text recognition and analyzing using neural network based learning strategies, a new open question emerges, that is, what is the next? To ask this question is to mean that the neural network solution is not an ultimate solution, and there will be more challenges to meet in coming future. We discussed these aspects of deep neural network research work in this paper and focused on semantics in deep neural-network computing models. We try to browse how semantics or knowledge are to be involved in deep neural network models and how the semantics and knowledge will be a key factor towards making more intelligent machines. We argue that priori semantics and knowledge in modelling a neural network is important, which could be the key for researchers to design intelligent machine models to perform complex tasks.