Miracle-dz/UniFAR-FTUs huggingface dataset:
Theorizing Issue Selection in Advocacy Organizations: An Analysis of Human Rights Activism around Darfur and the Congo, 1998–2010

Why do advocacy organizations focus on some issues rather than others? Issue selection is an important area of study given that advocacy organizations have limited time and resources and thus many potentially important issues go ignored. Yet issue selection remains an understudied question in the scholarly study of advocacy organizations. In this article, the author draws on historical data, interviews, and a database of statements by major human rights advocacy organizations to examine one particular historical puzzle regarding issue selection: Why advocacy organizations have focused on the recent conflict in the Darfur region of Sudan rather than the conflict in the Democratic Republic of Congo, even though more people have died in the Congo. The author finds that advocacy organizations select issues not based on their severity but based on framing, political opportunities, and organizational resources.
Spatial moment models for collective cell behaviour

The ability of cells to undergo collective movement plays a fundamental role in tissue repair, development and cancer. Interactions occurring at the level of individual cells may give rise to spatial structure, such as clustering, in a moving population. In vitro cell culture studies have shown that the presence of such spatial structure can play an important role in determining the dynamics of migrating cells at a population level. However, mathematical models that consider population-level behaviour often take a mean-field approach, which assumes that individuals interact with one another in proportion to their average density and neglects the effects of spatial structure. In this work, we develop a lattice-free individual-based model (IBM) for collective movement in one-dimensional space. The IBM uses random walk theory to model the stochastic interactions occurring at the scale of individual migrating cells. In particular, our model allows an individual’s direction of movement to be affected by interactions with other cells in its neighbourhood, providing insights into how directional bias generates spatial structure. As an alternative to the mean-field approach, we employ spatial moment theory to develop a population-level model which accounts for spatial structure and predicts how these individual-level interactions propagate to the scale of the whole population. The IBM is used to derive an equation for dynamics of the second spatial moment (the average density of pairs of cells) which incorporates the neighbour-dependent directional bias and we solve this numerically for a spatially homogeneous case. Extending our model to consider cell behaviour in two-dimensional space makes it more amenable for use alongside experimental data. Using imaging data from in vitro experiments, we estimate parameters for the two-dimensional model and show that it can generate similar spatial structure to that observed in a 3T3 fibroblast cell population. Finally, we incorporate cell birth and death into our two-dimensional model to consider how these processes give rise to spatial structure and how, in turn, this spatial structure affects the collective dynamics.
On the importance of normalisation layers in deep learning with piecewise linear activation units

Deep feedforward neural networks with piecewise linear activations are currently producing the state-of-the-art results in several public datasets (e.g., CIFAR-10, CIFAR-100, MNIST, and SVHN). The combination of deep learning models and piecewise linear activation functions allows for the estimation of exponentially complex functions with the use of a large number of subnetworks specialized in the classification of similar input examples. During the training process, these subnetworks avoid overfitting with an implicit regularization scheme based on the fact that they must share their parameters with other subnetworks. Using this framework, we have made an empirical observation that can improve even more the performance of such models. We notice that these models assume a balanced initial distribution of data points with respect to the domain of the piecewise linear activation function. If that assumption is violated, then the piecewise linear activation units can degenerate into purely linear activation units, which can result in a significant reduction of their capacity to learn complex functions. Furthermore, as the number of model layers increases, this unbalanced initial distribution makes the model ill-conditioned. Therefore, we propose the introduction of batch normalisation units into deep feedforward neural networks with piecewise linear activations, which drives a more balanced use of these activation units, where each region of the activation function is trained with a relatively large proportion of training samples. Also, this batch normalisation promotes the pre-conditioning of very deep learning models. We show that by introducing maxout and batch normalisation units to the network in network model results in a model that produces classification results that are better than or comparable to the current state of the art in CIFAR-10, CIFAR-100, MNIST, and SVHN datasets.
The physical determinants of the DNA conformational landscape: an analysis of the potential energy surface of single-strand dinucleotides in the conformational space of duplex DNA

A multivariate analysis of the backbone and sugar torsion angles of dinucleotide fragments was used to construct a 3D principal conformational subspace (PCS) of DNA duplex crystal structures. The potential energy surface (PES) within the PCS was mapped for a single-strand dinucleotide model using an empirical energy function. The low energy regions of the surface encompass known DNA forms and also identify previously unclassified conformers. The physical determinants of the conformational landscape are found to be predominantly steric interactions within the dinucleotide backbone, with medium-dependent backbone-base electrostatic interactions serving to tune the relative stability of the different local energy minima. The fidelity of the PES to duplex DNA properties is validated through a correspondence to the conformational distribution of duplex DNA crystal structures and the reproduction of observed sequence specific propensities for the formation of A-form DNA. The utility of the PES is demonstrated through its succinct and accurate description of complex conformational processes in simulations of duplex DNA. The study suggests that stereochemical considerations of the nucleic acid backbone play a role in determining conformational preferences of DNA which is analogous to the role of local steric interactions in determining polypeptide secondary structure.
Syntactic and Semantic Structure for Opinion Expression Detection

We demonstrate that relational features derived from dependency-syntactic and semantic role structures are useful for the task of detecting opinionated expressions in natural-language text, significantly improving over conventional models based on sequence labeling with local features. These features allow us to model the way opinionated expressions interact in a sentence over arbitrary distances. While the relational features make the prediction task more computationally expensive, we show that it can be tackled effectively by using a reranker. We evaluate a number of machine learning approaches for the reranker, and the best model results in a 10-point absolute improvement in soft recall on the MPQA corpus, while decreasing precision only slightly.
Autologous mesenchymal stromal cells and kidney transplantation: a pilot study of safety and clinical feasibility.

BACKGROUND AND OBJECTIVES Mesenchymal stromal cells (MSCs) abrogate alloimmune response in vitro, suggesting a novel cell-based approach in transplantation. Moving this concept toward clinical application in organ transplantation should be critically assessed. DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS A safety and clinical feasibility study (ClinicalTrials.gov, NCT00752479) of autologous MSC infusion was conducted in two recipients of kidneys from living-related donors. Patients were given T cell-depleting induction therapy and maintenance immunosuppression with cyclosporine and mycophenolate mofetil. On day 7 posttransplant, MSCs were administered intravenously. Clinical and immunomonitoring of MSC-treated patients was performed up to day 360 postsurgery. RESULTS Serum creatinine levels increased 7 to 14 days after cell infusion in both MSC-treated patients. A graft biopsy in patient 2 excluded acute graft rejection, but showed a focal inflammatory infiltrate, mostly granulocytes. In patient 1 protocol biopsy at 1-year posttransplant showed a normal graft. Both MSC-treated patients are in good health with stable graft function. A progressive increase of the percentage of CD4+CD25highFoxP3+CD127- Treg and a marked inhibition of memory CD45RO+RA-CD8+ T cell expansion were observed posttransplant. Patient T cells showed a profound reduction of CD8+ T cell activity. CONCLUSIONS Findings from this study in the two patients show that MSC infusion in kidney transplant recipients is feasible, allows enlargement of Treg in the peripheral blood, and controls memory CD8+ T cell function. Future clinical trials with MSCs to look with the greatest care for unwanted side effects is advised.
Leave-One-Out Bounds for Kernel Methods

In this article, we study leave-one-out style cross-validation bounds for kernel methods. The essential element in our analysis is a bound on the parameter estimation stability for regularized kernel formulations. Using this result, we derive bounds on expected leave-one-out cross-validation errors, which lead to expected generalization bounds for various kernel algorithms. In addition, we also obtain variance bounds for leave-oneout errors. We apply our analysis to some classification and regression problems and compare them with previous results.
Is the panoramic mandibular index useful for bone quality evaluation?

Purpose The aim of this study was to determine whether the panoramic mandibular index (PMI) is useful for assessing bone mineral density. We also analyzed the potential correlations between PMI parameters and patient age. Materials and Methods Four observers measured the PMI of both sides of the mental foramen using a picture archiving and communication system and images in the Digital Imaging and Communications in Medicine format. They studied 300 panoramic radiographic images of patients belonging to the following age groups: 40–49 years, 50–59 years, 60–69 years, 70–79 years, and 80–89 years. The observers were allowed to zoom in or out and to adjust the contrast of the images. Further, they were instructed to record the reasons for any measurements that could not be made. Then, we conducted a reliability analysis of the measured PMI and assessed the correlations between different patient age groups and the 3 parameters used for determining the PMI from the available data. Results Among the 600 data items collected, 23 items were considered unmeasurable by at least 1 observer for the following 4 reasons: postoperative state, lesion, unidentified mental foramen, and alveolar bone loss. The intraobserver reproducibility of the measurable data was 0.611-0.752. The mandibular cortical width (MCW) decreased significantly as patient age increased. Conclusion PMI had limited usability when the margin of the mental foramen was not clear. In contrast, MCW, a parameter used for determining the PMI, had fewer drawbacks than the PMI with respect to bone mineral density measurements and exhibited a significant correlation with patient age.
Do parents lead their children by the hand?

The types of gesture+speech combinations children produce during the early stages of language development change over time. This change, in turn, predicts the onset of two-word speech and thus might reflect a cognitive transition that the child is undergoing. An alternative, however, is that the change merely reflects changes in the types of gesture+speech combinations that their caregivers produce. To explore this possibility, we videotaped 40 American child–caregiver dyads in their homes for 90 minutes when the children were 1;2, 1;6, and 1;10. Each gesture was classified according to type (deictic, conventional, representational) and the relation it held to speech (reinforcing, disambiguating, supplementary). Children and their caregivers produced the same types of gestures and in approximately the same distribution. However, the children differed from their caregivers in the way they used gesture in relation to speech. Over time, children produced many more REINFORCING (bike+point at bike), DISAMBIGUATING (that one+point at bike), and SUPPLEMENTARY combinations (ride+point at bike). In contrast, the frequency and distribution of caregivers' gesture+speech combinations remained constant over time. Thus, the changing relation between gesture and speech observed in the children cannot be traced back to the gestural input the children receive. Rather, it appears to reflect changes in the children's own skills, illustrating once again gesture's ability to shed light on developing cognitive and linguistic processes.
The thin-cap fibroatheroma: a type of vulnerable plaque: The major precursor lesion to acute coronary syndromes

While the concept of plaque `vulnerability' implies a propensity towards thrombosis, the term vulnerable was originally intended to provide a morphologic description consistent with plaques that are prone to rupture. It is now known that the etiology of coronary thrombi is diverse and can arise from entities of plaque erosion or calcified nodules. These findings have prompted the search for more definitive terminology to describe precursor lesions associated with rupture, now referred to as thin-cap fibroatheromas. This review focuses on the thin-cap fibroatheroma, as a specific cause of acute coronary syndromes. To put these issues into current perspective, we need to revisit some of the older literature describing plaque morphology in stable and unstable angina, acute myocardial infarction, and sudden coronary death. The morphology, frequency, and precise location of these thin-cap fibroatheromas are further discussed in detail. Potential mechanisms of fibrous cap thinning are also addressed, in particular emerging data, which suggests the role of cell death “apoptosis” in cap atrophy.
Adaptive Motion/Force Control of Mobile Under-Actuated Manipulators With Dynamics Uncertainties by Dynamic Coupling and Output Feedback

In this paper, adaptive motion/force control by dynamic coupling and output feedback is considered for nonholonomic mobile manipulators with an under-actuated joint, in the presence of parametric and functional uncertainties. It is obvious that the constraints of the system consist of kinematic constraints for the mobile platform and dynamic constraints for the under-actuated joint. Through using dynamic coupling property of nonholonomic mobile under-actuated manipulators, adaptive output feedback control is investigated for the system by using a high gain observer to reconstruct the system states, whose states and time derivatives of the output are unavailable. Moreover, the nonholonomic constraint force between the wheels and the ground is also considered in the control design such that the slipping or slippage is avoided during the motion. It is shown that output tracking errors of motion and force converge to adjustable neighborhoods of the origin for the output feedback control.
İlköğretim Sosyal Bilgiler Programında Yer Alan Değerler ve Değer Eğitimi Uygulamaları Konusunda Öğretmen Görüşleri

Bu arastirmanin amaci, ilkogretim sosyal bilgiler programinda yer alan degerler ve deger egitimi uygulamalari konusunda ogretmenlerin goruslerini belirlemektir. Arastirma 2006-2007 egitim ogretim yilinda, Mersin’de, 24 okuldan 152 sinif ve sosyal bilgiler ogretmeninin katilimiyla gerceklestirilmistir. Verilerin toplanmasinda ogretmenlerin sosyal bilgiler programinda bulunan degerlerin onem derecesi, degerlere hangi derslerde deginildigi ve hangi ara disiplinlerle iliski kuruldugu, deger ogretimi icin kullanilan yontemlerin etkililigi, degerlerin kazanim guclugu, deger egitiminde karsilasilan sorunlar ve bu sorunlara yonelik cozum onerileri ile ilgili goruslerini almak uzere hazirlanan bir anket kullanilmistir. Bulgulara gore ogretmenlerin sosyal bilgiler programinda belirtilen degerlerin tumunu cok onemli ve onemli bulduklari ve bu degerlerden “adil olma”, “baris”, “durustluk” ve “duygu ve dusuncelere saygi” degerlerinin ise onem derecesi acisindan ilk siralarda yer aldigi tespit edilmistir. Ogretmenlerin deger ogretiminde en etkili bulduklari yontemin ornek olay incelemesi, oldugu, en az etkili yontemin ise geleneksel telkin yontemi oldugu bulunmustur. Ogretmenlerin deger egitimine en cok degindikleri dersin sosyal bilgiler, en cok iliskilendirdikleri ara disiplinin rehberlik ve psikolojik danisma oldugu belirlenmistir. Ayrica ogretmenlerin degerlerin kazanilmasinin orta duzeyde guc oldugunu dusundukleri tespit edilmistir. Bunun yani sira, arastirmaya katilan ogretmenlerin deger egitiminde sorun kaynagi olarak ilk sirada “ailenin sosyal, kulturel ve ekonomik ozellikleri”ni gordukleri belirlenmistir. Bu sorunlarin cozumu ile ilgili onerilerinde ise “cocuga degerli oldugunu hissettirmek” gorusunun birinci sirada yer aldigi ortaya cikmistir
Deep Learning for Answer Sentence Selection

Answer sentence selection is the task of identifying sentences that contain the answer to a given question. This is an important problem in its own right as well as in the larger context of open domain question answering. We propose a novel approach to solving this task via means of distributed representations, and learn to match questions with answers by considering their semantic encoding. This contrasts prior work on this task, which typically relies on classifiers with large numbers of hand-crafted syntactic and semantic features and various external resources. Our approach does not require any feature engineering nor does it involve specialist linguistic data, making this model easily applicable to a wide range of domains and languages. Experimental results on a standard benchmark dataset from TREC demonstrate that---despite its simplicity---our model matches state of the art performance on the answer sentence selection task.
VLSI circuit placement with rectilinear modules using three-layer force-directed self-organizing maps

In this paper, a three-layer force-directed self-organizing map is designed to resolve the circuit placement problem with arbitrarily shaped rectilinear modules. The proposed neural model with an additional hidden layer can easily model a rectilinear module by a set of hidden neurons to correspond the partitioned rectangles. With the collective computing from hidden neurons, these rectilinear modules can correctly interact with each other and finally converge to a good placement result. In this paper, multiple contradictory criteria are accounted simultaneously during the placement process, in which, both the wire length and the module overlap are reduced. The proposed model has been successfully exploited to solve the time consuming rectilinear module placement problem. The placement results of real rectilinear test examples are presented, which demonstrate that the proposed method is better than the simulated annealing approach in the total wire length. The appropriate parameter values which yield good solutions are also investigated.
Retrospective evaluation of revised criteria for the diagnosis of Alzheimer's disease using a cohort with post‐mortem diagnosis

The criteria currently used to diagnose Alzheimer's disease (AD) require the presence of dementia, i.e. cognitive impairment sufficient to affect normal social and/or occupational function. Dubois et al. (Dubois et al., 2007 ) have recently proposed a set of revised criteria that may aid the diagnosis of the earlier stages of AD, and do not require the presence of dementia. We aimed to evaluate the new predementia‐AD criteria through their retrospective application to the OPTIMA cohort with post‐mortem (PM) confirmed diagnoses.
Value distribution of the Gauss map of improper affine spheres

We give the best possible upper bound for the number of exceptional values of the Lagrangian Gauss map of complete improper affine fronts in the affine three-space. We also obtain the sharp estimate for weakly complete case. As an application of this result, we provide a new and simple proof of the parametric affine Bernstein problem for improper affine spheres. Moreover, we get the same estimate for t ratio of canonical forms of weakly complete flat fronts in hyperbolic three-space.
Rapid Development of a Gamma Interferon-Secreting Glycolipid/CD1d-Specific Vα14+ NK1.1− T-Cell Subset after Bacterial Infection

ABSTRACT The phenotypic and functional changes of glycolipid presented by CD1d(glycolipid/CD1d) specific Vα14+ T cells in the liver of mice at early stages of bacterial infection were investigated. After Listeria monocytogenes infection or interleukin-12 (IL-12) treatment, α-galactosylceramide/CD1d tetramer-reactive (α-GalCer/CD1d+) T cells coexpressing natural killer (NK) 1.1 marker became undetectable and, concomitantly, cells lacking NK1.1 emerged in both euthymic and thymectomized animals. Depletion of the NK1.1+ subpopulation prevented the emergence of α-GalCer/CD1d+ NK1.1− T cells. Before infection, NK1.1+, rather than NK1.1−, α-GalCer/CD1d+ T cells coexpressing CD4 were responsible for IL-4 production, whereas gamma interferon (IFN-γ) was produced by cells regardless of NK1.1 or CD4 expression. After infection, IL-4-secreting cells became undetectable among α-GalCer/CD1d+ T cells, but considerable numbers of IFN-γ-secreting cells were found among NK1.1−, but not NK1.1+, cells lacking CD4. Thus, NK1.1 surface expression and functional activities of Vα14+ T cells underwent dramatic changes at early stages of listeriosis, and these alterations progressed in a thymus-independent manner. In mutant mice lacking all α-GalCer/CD1d+ T cells listeriosis was ameliorated, suggesting that the subtle contribution of the NK1.1− T-cell subset to antibacterial protection is covered by more profound detrimental effects of the NK1.1+ T-cell subset.
Paranormal belief and biases in reasoning underlying the formation of delusions

Some recent research suggests that psychological processes underlying the formation of paranormal beliefs have much in common with those underlying delusional beliefs. On this ground a survey was conducted to investigate the relationship between paranormal beliefs and distortions in reasoning known to be associated with the development of psychotic delusions. A convenience sample of 250 people completed an online inventory of questionnaires measuring the intensity of paranormal beliefs, schizotypal biases in reasoning, and the need for closure. Both dimensions of paranormal belief surveyed here were found to be predicted by reasoning biases.