Les femmes et l’incarcération, le temps n'arrange rien

Some of the issues related to the incarceration of women have long been denounced and are well documented in the current literature. This article attempts to report on the recommendations of the Task Force on federally sentenced women in Canada by indicating what were the underlying influences. Thus, the proposed policy is presented as deriving from a feminist analysis of the reality of the women in prison. It is also mentioned that, for various reasons, the implementation of such a policy may not follow the course initially intended, therefore it should be cautiously supervised

Refugee Youth Challenges and Unique Needs in Worcester Public Schools that are Satisfied by African Community Education

The influx of refugee youth in United States challenges the structure of the US formal school system, as it struggles to manage the unique needs of refugee youth. This research explores African refugee youth needs in the formal school system in Worcester, MA, and how some of these needs are better supported in a supplementary education institution, African Community Education (ACE). The research draws on individual interviews and focus group discussions with refugee youth and ACE’s staff to analyze the complexities and challenges refugee youth are confronted within formal schools and how they are motivated to seek supplementary education. The results suggest that while African refugee youth’s academic challenges in school are partly as a result of low English language skills, an even more important struggle is the residual trauma and sense of exclusion that they feel while in formal schooling. ACE provides the support system that helps these students with these challenges. This research paper also provides recommendations specifically tailored to ACE to strengthen their supplemental education provided to African refugee youth attending Worcester Public Schools

Algebraic analysis of quantum search with pure and mixed states

An algebraic analysis of Grover's quantum search algorithm is presented for the case in which the initial state is an arbitrary pure quantum state of n qubits. This approach reveals the geometrical structure of the quantum search process, which turns out to be confined to a four-dimensional subspace of the Hilbert space. This work unifies and generalizes earlier results on the time evolution of the amplitudes during the quantum search, the optimal number of iterations and the success probability. Furthermore, it enables a direct generalization to the case in which the initial state is a mixed state, providing an exact formula for the success probability.Comment: 13 page

Normal sleep bouts are not essential for C. elegans survival and FoxO is important for compensatory changes in sleep

Additional file 6: Decreased lag-2 function does not slow vulval development. The progeny of wild type and lag-2(q420) animals raised at 25.5 °C were selected at the L4 stage, prior to lethargus entry. Vulval eversion was scored after 3 h; the percentage of animals completing vulval eversion was recorded. Significance was assessed by student’s two-tailed t-test p value < 0.5; error bars represents SEM from 3 trials. Total number of animals: wild type n = 45 and lag-2(q420) n = 42

Molecular Model of the Contractile Ring

We present a model for the actin contractile ring of adherent animal cells. The model suggests that the actin concentration within the ring and consequently the power that the ring exerts both increase during contraction. We demonstrate the crucial role of actin polymerization and depolymerization throughout cytokinesis, and the dominance of viscous dissipation in the dynamics. The physical origin of two phases in cytokinesis dynamics ("biphasic cytokinesis") follows from a limitation on the actin density. The model is consistent with a wide range of measurements of the midzone of dividing animal cells.Comment: PACS numbers: 87.16.Ka, 87.16.Ac http://www.ncbi.nlm.nih.gov/pubmed/16197254 http://www.weizmann.ac.il/complex/tlusty/papers/PhysRevLett2005.pd

Theory of Initialization-Free Decoherence-Free Subspaces and Subsystems

We introduce a generalized theory of decoherence-free subspaces and subsystems (DFSs), which do not require accurate initialization. We derive a new set of conditions for the existence of DFSs within this generalized framework. By relaxing the initialization requirement we show that a DFS can tolerate arbitrarily large preparation errors. This has potentially significant implications for experiments involving DFSs, in particular for the experimental implementation, over DFSs, of the large class of quantum algorithms which can function with arbitrary input states

Nested quantum search and NP-complete problems

A quantum algorithm is known that solves an unstructured search problem in a number of iterations of order $\sqrt{d}$, where $d$ is the dimension of the search space, whereas any classical algorithm necessarily scales as $O(d)$. It is shown here that an improved quantum search algorithm can be devised that exploits the structure of a tree search problem by nesting this standard search algorithm. The number of iterations required to find the solution of an average instance of a constraint satisfaction problem scales as $\sqrt{d^\alpha}$, with a constant $\alpha<1$ depending on the nesting depth and the problem considered. When applying a single nesting level to a problem with constraints of size 2 such as the graph coloring problem, this constant $\alpha$ is estimated to be around 0.62 for average instances of maximum difficulty. This corresponds to a square-root speedup over a classical nested search algorithm, of which our presented algorithm is the quantum counterpart.Comment: 18 pages RevTeX, 3 Postscript figure

Discourse “Declaration of Love”: Problem of Automatic Identification (Works of A. P. Chekhov»)

The problem of revealing the “Declaration of Love” discourse in works of art is considered. The author’s development on the automatic detection of the situation of declaration of love, tested on the material of the work of A. P. Chekhov, is presented. The search was carried out on the basis of the Russian National Corpus. In total, more than 200 texts have been identified containing textual representations of the situation of declaration of love. 40 out of 200 texts are identified by the authors of the article as the most fully representative of the desired situation. The set of textual passages describing it is viewed as a cognitive-discursive set of declarations of love. The development of the algorithm was carried out based on the identification of the cognitive schemes of the writer and the statistical analysis of the lexical composition of the situation of declaration of love. Among the frequency components of the cognitive model, which A. P. Chekhov follows in describing the process of declaring love, an open space filled with plants, birds, etc. was revealed. In the general cognitive-discursive set of declarations of love, the nuclear and satellite zones were identified and analyzed, the lexical components of which belong to certain functional-semantic classes and functional-semantic groups

Automatic detection and classification of honey bee comb cells using deep learning

In a scenario of worldwide honey bee decline, assessing colony strength is becoming increasingly important for sustainable beekeeping. Temporal counts of number of comb cells with brood and food reserves offers researchers data for multiple applications, such as modelling colony dynamics, and beekeepers information on colony strength, an indicator of colony health and honey yield. Counting cells manually in comb images is labour intensive, tedious, and prone to error. Herein, we developed a free software, named DeepBee©, capable of automatically detecting cells in comb images and classifying their contents into seven classes. By distinguishing cells occupied by eggs, larvae, capped brood, pollen, nectar, honey, and other, DeepBee© allows an unprecedented level of accuracy in cell classification. Using Circle Hough Transform and the semantic segmentation technique, we obtained a cell detection rate of 98.7%, which is 16.2% higher than the best result found in the literature. For classification of comb cells, we trained and evaluated thirteen different convolutional neural network (CNN) architectures, including: DenseNet (121, 169 and 201); InceptionResNetV2; InceptionV3; MobileNet; MobileNetV2; NasNet; NasNetMobile; ResNet50; VGG (16 and 19) and Xception. MobileNet revealed to be the best compromise between training cost, with ~9 s for processing all cells in a comb image, and accuracy, with an F1-Score of 94.3%. We show the technical details to build a complete pipeline for classifying and counting comb cells and we made the CNN models, source code, and datasets publicly available. With this effort, we hope to have expanded the frontier of apicultural precision analysis by providing a tool with high performance and source codes to foster improvement by third parties (https://github.com/AvsThiago/DeepBeesource).This research was developed in the framework of the project “BeeHope - Honeybee conservation centers in Western Europe: an innovative strategy using sustainable beekeeping to reduce honeybee decline”, funded through the 2013-2014 BiodivERsA/FACCE-JPI Joint call for research proposals, with the national funders FCT (Portugal), CNRS (France), and MEC (Spain).info:eu-repo/semantics/publishedVersio