Entropic singularities give rise to quantum transmission

When can noiseless quantum information be sent across noisy quantum devices? And at what maximum rate? These questions lie at the heart of quantum technology, but remain unanswered because of non-additivity— a fundamental synergy which allows quantum devices (aka quantum channels) to send more information than expected. Previously, non-additivity was known to occur in very noisy channels with coherent information much smaller than that of a perfect channel; but, our work shows non-additivity in a simple low-noise channel. Our results extend even further. We prove a general theorem concerning positivity of a channel’s coherent information. A corollary of this theorem gives a simple dimensional test for a channel’s capacity. Applying this corollary solves an open problem by characterizing all qubit channels whose complement has non-zero capacity. Another application shows a wide class of zero quantum capacity qubit channels can assist an incomplete erasure channel in sending quantum information. These results arise from introducing and linking logarithmic singularities in the von-Neumann entropy with quantum transmission: changes in entropy caused by this singularity are a mechanism responsible for both positivity and non-additivity of the coherent information. Analysis of such singularities may be useful in other physics problems.

Hospital Childbirth: Perspectives of Women and Professionals for a Positive Experience—A Qualitative Study

The perception and interpretation of childbirth are changing as values change. This requires women and professionals to adapt to new circumstances. The objective of this study was to analyze the perspectives of women and professionals on hospital birth and to identify improvement areas in order to achieve a positive perinatal experience. A qualitative prospective study with a phenomenological approach was conducted using semi-structured interviews with women, two and eight months after childbirth, participant observation, and professional focus groups. The analysis of the transcribed texts involved a thematic inductive approach. Four improvement areas emerged from the analysis: (a) strengthening communication and the therapeutic relationship; (b) unifying criteria between hospitals and primary care centers to provide coordinated and coherent information; (c) involvement of the partner in the whole process of pregnancy-childbirth-puerperium; (d) improvement of the spaces used in prenatal care and births. The need for a continuity of care from the beginning of pregnancy to the postpartum period is emphasized, which requires an improvement in information, participation, and the promotion of shared decision-making. To this end, coordinated interdisciplinary work, involvement of the partner and the improvement of the spaces used in prenatal care and births are essential.

Writing strategies and difficulties to publish the scientific paper in effective English language

Klimova, B. (2020). This paper focus on that abstract of the paper is very important that should grab the attention of the reader if it doesn’t the rest of the paper will be omitted. We have to provide the clear, systematic, coherent information about the paper to attract the readers. The non native English students are difficult to form the abstract in systematic manner

Obstacles to Using Assistive Technology for Older Adults – Results from a Focus Group Analysis

Much hope is placed in the use of assistive technologies (AT) to support older adults and retain their independence and quality of life. AT could also be a way to help fulfill the increasing requirements of caring for an aging population. While many devices are freely available, successful and broad adoption is progressing slowly. In a qualitative analysis, we investigated the popularity of AT and the willingness to and obstacles for use. Eleven older adults aged 62–85 participated in three groups, each focusing on a specific age-related case example. Using content analysis, statements have been categorized into three levels: the affected person, their surroundings, and supportive devices. Information (knowledge, consultation) was the topic spoken about the most (n=101), followed by statements focusing on everyday life and the use of assistive devices (n=99). Comments on economic topics carried the least weight (n=28). The biggest obstacles for the reluctant adoption of AT don’t seem to be acceptance issues but rather a lack of knowledge of AT and where to get counseling. Thus, the provision and promotion of coherent information material and accessible consultation for users and relatives should be prioritized. AT training for healthcare professionals can provide further opportunities.

Text Detection Based on Faster R-CNN Algorithm with Skip Pooling and Fusion of Hindi Handwritten Characters

Significant learning is at present the standard system for object disclosure. Speedier territory based convolutional neural association (Faster R-CNN) has a basic circumstance in significant learning. It has stunning area impacts in standard scenes. Regardless, under unprecedented conditions, there can even now be inadmissible acknowledgment execution, for instance, the thing having issues like hindrance, contorting, or little size. This paper proposes a novel and improved estimation reliant on the Faster R-CNN framework got together with the Faster R-CNN figuring with skip pooling and mix of consistent information. This computation can improve the revelation execution under uncommon conditions dependent on Faster R-CNN. The improvement basically has three segments: The underlying portion adds a setting information incorporate extraction model after the conv5_3 of the convolutional layer; the resulting part adds skip pooling so the past can totally secure the coherent information of the article, especially for conditions where the thing is hindered and distorted; and the third part replaces the area recommendation association (RPN) with a more capable guided anchor RPN (GA-RPN), which can keep up the survey rate while improving the revelation execution. The last can get more positive information from different segment layers of the significant neural association figuring, and is especially centered around scenes with little articles. Differentiated and Faster R-CNN, you simply look once plan, (for instance, YOLOv3), single shot pointer, (for instance, SSD512), and other article revelation computations, the estimation proposed in this paper has an ordinary improvement of 6.857% on the mean typical precision (mAP) appraisal list while keeping up a particular audit rate. This unequivocally exhibits that the proposed methodology has higher ID rate and disclosure efficiency for this circumstance.

A novel image inpainting framework based on multilevel image pyramids

Image inpainting is the art of manipulating an image so that it is visually unrecognizable way. A considerable amount of research has been done in this area over the last few years. However, the state of art techniques does suffer from computational complexities and plausible results. This paper proposes a multi-level image pyramid-based image inpainting algorithm. The image inpainting algorithm starts with the coarsest level of the image pyramid and overpainting information is transferred to the subsequent levels until the bottom level gets inpainted. The search strategy used in the algorithm is based on hashing the coherent information in an image which makes the search fast and accurate. Also, the search space is constrained based on the propagated information thereby reducing the complexity of the algorithm. Compared to other inpainting methods; the proposed algorithm inpaints the target region with better plausibility and human vision conformation. Experimental results show that the proposed algorithm achieves better results as compared to other inpainting techniques.