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关键词： Computational models   Computer science   Gene expression  

摘要： Spatial transcriptomics enables the simultaneous measurement of morphological features and transcriptional profiles of the same cells or regions in tissues. Here we present multi-modal structured embedding (MUSE), an approach to characterize cells and tissue regions by integrating morphological and spatially resolved transcriptional data. We demonstrate that MUSE can discover tissue subpopulations missed by either modality as well as compensate for modality-specific noise. We apply MUSE to diverse datasets containing spatial transcriptomics (seqFISH+, STARmap or Visium) and imaging (hematoxylin and eosin or fluorescence microscopy) modalities. MUSE identified biologically meaningful tissue subpopulations and stereotyped spatial patterning in healthy brain cortex and intestinal tissues. In diseased tissues, MUSE revealed gene biomarkers for proximity to tumor region and heterogeneity of amyloid precursor protein processing across Alzheimer brain regions. MUSE enables the integration of multi-modal data to provide insights into the states, functions and organization of cells in complex biological tissues.

关键词： computer science education   high schools   california   leadership   course taking  

摘要： Purpose: We aim to better understand the curricular, staffing, and achievement trade-offs entailed by expansions of high-school computer science (CS) for students, schools, and school leaders. Methods: We use descriptive, correlational, and quasi-experimental methods to analyze statewide longitudinal course-, school-, and staff-level data from California, where CS course taking has expanded rapidly. Findings: We find that these rapid CS course expansions have not come at the expense of CS teachers' observable qualifications (namely certification, education, or experience). Within-school course taking patterns over time suggest that CS enrollment growth has come at the expense of social studies, English/language arts (ELA), and arts courses, as well as from other miscellaneous electives. However, we find no evidence that increased enrollment of students in CS courses at a school has a significant effect on students' math or ELA test scores. Implications: Flexible authorization requirements for CS teachers appear to have allowed school leaders to staff new CS courses with teachers whose observable qualifications are strong, though we do not observe teachers' CS teaching skill. Increasing CS participation is unlikely to noticeably improve school-level student test scores, but administrators also do not need to be overly concerned that test scores will suffer. However, school leaders and policymakers should think carefully about what courses new CS courses will replace and whether such replacements are worthwhile.

关键词： Climate change   Computer science   Machine learning  

摘要： Emissions data for different locations could help researchers to reduce the environmental cost of machine-learning experiments.

摘要： The present situation is investigated and the relevance of the stage of prototyping of user interfaces as intermediary of human-machine interaction in the process of software development is substantiated. The necessity of improving the methodology of teaching graphic disciplines and the relevance of studying the technologies of «UX/UI Design» in the process of professional training of future bachelor’s in computer science as a perspective direction in view of the demands of the labor market and as a factor that raises the level of motivation of students for professional activity in general and on the formation of graphic competence. The methodical provision of the course is described, the structure and content of the theoretical and practical part of the course are presented, which is focused on the study of the technology of «UX/UI Design». The mathematical modeling of the discipline learning process «UX/UI Design» is described. The use of mathematical modeling to develop a model for training the discipline «UX/UI Design» provided the basis for the creation of a system of scientific-methodical and computer support of pedagogical activities and outlined the perspectives of designing a pedagogical technology for the formation of graphic competence of future Bachelor of Computer Sciences in the course of studying the discipline «UX/UI Design».

关键词： Computer science   Electrical and electronic engineering   Computational science  

摘要： Designing energy-efficient computing solution for the implementation of AI algorithms in edge devices remains a challenge. Yang et al. proposes a decentralized brain-inspired computing method enabling multiple edge devices to collaboratively train a global model without a fixed central coordinator. In order to realize the full potential of wireless edge artificial intelligence (AI), very large and diverse datasets will often be required for energy-demanding model training on resource-constrained edge devices. This paper proposes a lead federated neuromorphic learning (LFNL) technique, which is a decentralized energy-efficient brain-inspired computing method based on spiking neural networks. The proposed technique will enable edge devices to exploit brain-like biophysiological structure to collaboratively train a global model while helping preserve privacy. Experimental results show that, under the situation of uneven dataset distribution among edge devices, LFNL achieves a comparable recognition accuracy to existing edge AI techniques, while substantially reducing data traffic by >3.5x and computational latency by >2.0x. Furthermore, LFNL significantly reduces energy consumption by >4.5x compared to standard federated learning with a slight accuracy loss up to 1.5%. Therefore, the proposed LFNL can facilitate the development of brain-inspired computing and edge AI.

关键词： Students  

摘要： Teaching assistants (TAs) are heavily used in computer science courses as a way to handle high enrollment and still being able to offer students individual tutoring and detailed assessments. TAs are themselves students who take on this additional role in parallel with their own studies at the same institution. Previous research has shown that being a TA can be challenging but has mainly been conducted on TAs from a single institution or within a single course. This paper offers a multi-institutional, multi-national perspective of challenges that TAs in computer science face. This has been done by conducting a thematic analysis of 180 reflective essays written by TAs from three institutions across Europe. The thematic analysis resulted in five main challenges: becoming a professional TA, student focused challenges, assessment, defining and using best practice, and threats to best practice. In addition, these challenges were all identified within the essays from all three institutions, indicating that the identified challenges are not particularly context-dependent. Based on these findings, we also outline implications for educators involved in TA training and coordinators of computer science courses with TAs. © 2022, CC BY.

关键词： Computer science   Optics and photonics   Physics   Theory and computation  

摘要： Deep learning techniques usually require a large quantity of training data and may be challenging for scarce datasets. The authors propose a framework that involves contrastive and transfer learning and reduces data requirements for training while keeping the prediction accuracy. Deep learning techniques have been increasingly applied to the natural sciences, e.g., for property prediction and optimization or material discovery. A fundamental ingredient of such approaches is the vast quantity of labeled data needed to train the model. This poses severe challenges in data-scarce settings where obtaining labels requires substantial computational or labor resources. Noting that problems in natural sciences often benefit from easily obtainable auxiliary information sources, we introduce surrogate- and invariance-boosted contrastive learning (SIB-CL), a deep learning framework which incorporates three inexpensive and easily obtainable auxiliary information sources to overcome data scarcity. Specifically, these are: abundant unlabeled data, prior knowledge of symmetries or invariances, and surrogate data obtained at near-zero cost. We demonstrate SIB-CL's effectiveness and generality on various scientific problems, e.g., predicting the density-of-states of 2D photonic crystals and solving the 3D time-independent Schrodinger equation. SIB-CL consistently results in orders of magnitude reduction in the number of labels needed to achieve the same network accuracies.

关键词： Application programs  

摘要： Possible for science itself, conceptually, to have and will understand differently, let alone science also seen as technology, such as computer science. After all, science and technology are viewpoints diverse by either individual, community, or social. Generally, it depends on socioeconomic capabilities. So it is with computer science has become a phenomenon and fashionable, where based on the stream of documents, various issues arise in either its theory or implementation, adapting different communities, or designing curriculum holds in the education system. Generally, there are gaps between rich and poor, masculine and feminine, and basic sciences, engineering, and social sciences in accessing and using computer science. In particular, there have been various developments in hardware, software, and brain-ware from computer science in the application. There are recurring problems shortly, in the same or different places, both in developed and technologically lagging countries. Although computer science is still new, it has provided various innovations through research, which is proven by many documents. Therefore, following the growth of computer science - documents in the reputable indexed database, Scopus - there are clues for showing the trends. That is, dividing documents into three-time sessions: sloping, increasing and decreasing. That is by using a growth graphic. Then equip it with some parameters: topics and the weights from hit counts of databases. It gives the meaning as an interpretation to support the reviews. Therefore, this paper will provide a commentary related to that growth. It is for showing that despite the spread of studies, at the last time-session, the issues were always present simultaneously at the same time in accumulation. That is for describing a study title of computer science about what the world already has, going, and will understand about computer science. It is a view regarding its philosophy, basic science, applications, and tec

关键词： Computer science   Mechanical engineering  

摘要： Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsupervised learning problem. Current machine learning methods process new sensory data using prior knowledge defined by either domain knowledge or datasets. When datasets are not available, data acquisition is needed, though automating exploration in support of learning is still an unsolved problem. Here we develop a method that enables agents to efficiently collect data for learning a predictive sensor model-without requiring domain knowledge, human input, or previously existing data-using ergodicity to specify the data acquisition process. This approach is based entirely on data-driven sensor characteristics rather than predefined knowledge of the sensor model and its physical characteristics. We learn higher quality models with lower energy expenditure during exploration for data acquisition compared to competing approaches, including both random sampling and information maximization. In addition to applications in autonomy, our approach provides a potential model of how animals use their motor control to develop high quality models of their sensors (sight, sound, touch) before having knowledge of their sensor capabilities or their surrounding environment. Information-based search strategies are relevant for the learning of interacting agents dynamics and usually need predefined data. The authors propose a method to collect data for learning a predictive sensor model, without requiring domain knowledge, human input, or previously existing data.