A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data

Clustering analysis is widely utilized in single-cell RNA-sequencing (scRNA-seq) data to discover cell heterogeneity and cell states. While many clustering methods have been developed for scRNA-seq analysis, most of these methods require to provide the number of clusters. However, it is not easy to know the exact number of cell types in advance, and experienced determination is not always reliable. Here, we have developed ADClust, an automatic deep embedding clustering method for scRNA-seq data, which can accurately cluster cells without requiring a predefined number of clusters. Specifically, ADClust first obtains low-dimensional representation through pre-trained autoencoder, and uses the representations to cluster cells into initial micro-clusters. The clusters are then compared in between by a statistical test, and similar micro-clusters are merged into larger clusters. According to the clustering, cell representations are updated so that each cell will be pulled toward centres of its assigned cluster and similar clusters, while cells are separated to keep distances between clusters. This is accomplished through jointly optimizing the carefully designed clustering and autoencoder loss functions. This merging process continues until convergence. ADClust was tested on eleven real scRNA-seq datasets, and shown to outperform existing methods in terms of both clustering performance and the accuracy on the number of the determined clusters. More importantly, our model provides high speed and scalability for large datasets.

Merger of Private Universities: Empirical Study STAI Become FAI of Muhammadiyah University Bandung

The number of private universities in Indonesia is more than universities in the most populous country in the world, but it is not accompanied by good quality. This research is an empirical study with a descriptive, qualitative research approach. Technical data collection through documents, and observations of the process of unification of STAI and Muhammadiyah University. The unification of these two institutions is in one foundation, namely Muhammadiyah. In this merger process, the Ministry of Education and Culture and the Ministry of Religion are involved. The Chairperson of the Association of Indonesian Private Universities strongly supports the merging of two or more universities to reduce the number, facilitate coaching, and improve the quality of higher education. The first merger process was carried out by the Ministry of Education and Culture after the filing and visitation procedures were completed in writing and the visit of the LLDIKTI chairman followed by submission to DIKTIS (Directorate of Islamic Higher Education). This article aims to prove empirically about the implementation of the Ministry of Education and Culture's policies and the Decree of the Directorate of Islamic Higher Education regarding the merger of two or more universities, 2) information that the merging process of PTKAI and PTU is not easy.

Cold Molecular Gas in Merger Remnants. II. The Properties of Dense Molecular Gas

We present the 3 mm wavelength spectra of 28 local galaxy merger remnants obtained with the Large Millimeter Telescope. Sixteen molecular lines from 14 different molecular species and isotopologues were identified, and 21 out of 28 sources were detected in one or more molecular lines. On average, the line ratios of the dense gas tracers, such as HCN (1–0) and HCO+(1–0), to 13CO (1–0) are 3–4 times higher in ultra/luminous infrared galaxies (U/LIRGs) than in non-LIRGs in our sample. These high line ratios could be explained by the deficiency of 13CO and high dense gas fractions suggested by high HCN (1–0)/12CO (1–0) ratios. We calculate the IR-to-HCN (1–0) luminosity ratio as a proxy of the dense gas star formation efficiency. There is no correlation between the IR/HCN ratio and the IR luminosity, while the IR/HCN ratio varies from source to source ((1.1–6.5) × 103 L ☉/(K km s−1 pc2)). Compared with the control sample, we find that the average IR/HCN ratio of the merger remnants is higher by a factor of 2–3 than those of the early/mid-stage mergers and nonmerging LIRGs, and it is comparable to that of the late-stage mergers. The IR-to-12CO (1–0) ratios show a similar trend to the IR/HCN ratios. These results suggest that star formation efficiency is enhanced by the merging process and maintained at high levels even after the final coalescence. The dynamical interactions and mergers could change the star formation mode and continue to impact the star formation properties of the gas in the postmerger phase.

Spontaneous Generated Convective Anticyclones in Low Latitude --- A Model for the Great Red Spot

The Great Red Spot at about latitude 22oS of Jupiter has been observed for hundreds of years, yet the driving mechanism on the formation of this giant anticyclone still remains unclear. Two scenarios were proposed to explain its formation. One is a shallow model suggesting that it might be a weather feature formed through a merging process of small shallow storms generated by moist convection, while the other is a deep model suggesting that it might be a deeply rooted anticyclone powered by the internal heat of Jupiter. In this work, we present numerical simulations showing that the Great Red Spot could be naturally generated in a deep rotating turbulent flow and survive for a long time, when the convective Rossby number is smaller than a certain critical value. From this critical value, we predict that the Great Red Spot extends at least about 500 kilometers deep into the Jovian atmosphere. Our results demonstrate that the Great Red Spot is likely to be a feature deep-seated in the Jovian atmosphere.

Spontaneous Generated Convective Anticyclones in Low Latitude --- A Model for the Great Red Spot

The Great Red Spot at about latitude 22oS of Jupiter has been observed for hundreds of years, yet the driving mechanism on the formation of this giant anticyclone still remains unclear. Two scenarios were proposed to explain its formation. One is a shallow model suggesting that it might be a weather feature formed through a merging process of small shallow storms generated by moist convection, while the other is a deep model suggesting that it might be a deeply rooted anticyclone powered by the internal heat of Jupiter. In this work, we present numerical simulations showing that the Great Red Spot could be naturally generated in a deep rotating turbulent flow and survive for a long time, when the convective Rossby number is smaller than a certain critical value. From this critical value, we predict that the Great Red Spot extends at least about 500 kilometers deep into the Jovian atmosphere. Our results demonstrate that the Great Red Spot is likely to be a feature deep-seated in the Jovian atmosphere.

Architectural and urban identity of Homs city

Introduction. The article aims to determine the architectural and urban planning elements that give buildings and residential neighborhoods their identity in Homs city in Syria. During the last century, environmental and social problems have accumulated. The city’s parts have subjected to many violations in the construction processes and the weak construction laws. Within the past ten years, the war crisis in Syria caused massive destruction in the old city too. Together, all these factors contributed to losing an important and essential part of the city’s structure. Materials and methods. Throughout retrospective and comparative analysis, in addition to observations and photographic recordings, the basic architectural and planning features in the city of Homs have been identified. These features distinguish Homs from the rest of the Syrian cities. The merging process of social and environmental characteristics and their interconnectedness shaped the so-called “Homsi” identity. Results. The research concluded that Homs’ city possesses unique planning and architectural characteristics that distinguish it from other Syrian towns despite the historical connection between the Syrian cities. Thus, the character and the city’s architectural and urban identity have developed, so architects and urban planners should not ignore this identity in the next stage of recovery and reconstruction. Conclusions. This lost identity of Homs must be reintroduced creatively in the next stage of reconstruction because it carries the meanings of environmental sustainability in addition to being a historical and cultural legacy that cannot be neglected in the future if we ignored it now, all the attempts to revive only the visual image of the city will not save the identity and will generate a fake and weak personality of the city.

ONTOLOGY MERGING USING PROTÉGÉ – A CASE STUDY

The exponential growth of data and the boom of online businesses necessitates the need for data to be machine-readable, as humans are no longer able to manually manage the vast amounts of data. Ontologies can define concepts and relations that are amenable to processing by machines. Ontologies are created in silos and pockets of domains, and the need to merge these resources is key to universal access to multi-domain knowledge. Merging of ontologies has been explored to an extent over the last two decades, and this paper explores the extent of the tools and techniques available with a case study of merging two ontologies which are publicly available, the Person ontology and Institutional ontology, using the latest tools available on the most popular ontology editor, Protégé. It is found that automated merging tools have not been improved much over the last two decades, and the most current merging tools provided combine the two ontologies into one but do not unite or merge any of the classes or axioms which are equivalent. This can be seen in the axiom count, which does not decrease in the merged ontology, showing that no similar classes or actual axioms were merged. Protégé plugins which used to provide the semi-automatic mapping of similar classes to assist the merging process were found to be no longer available, and manual mapping by the knowledge engineer was required. This supports further research in automated ontology merging techniques.

Performance Comparison of Feature Generation Algorithms for Mosaic Photoacoustic Microscopy

Mosaic imaging is a computer vision process that is used for merging multiple overlapping imaging patches into a wide-field-of-view image. To achieve a wide-field-of-view photoacoustic microscopy (PAM) image, the limitations of the scan range of PAM require a merging process, such as marking the location of patches or merging overlapping areas between adjacent images. By using the mosaic imaging process, PAM shows a larger field view of targets and preserves the quality of the spatial resolution. As an essential process in mosaic imaging, various feature generation methods have been used to estimate pairs of image locations. In this study, various feature generation algorithms were applied and analyzed using a high-resolution mouse ear PAM image dataset to achieve and optimize a mosaic imaging process for wide-field PAM imaging. We compared the performance of traditional and deep learning feature generation algorithms by estimating the processing time, the number of matches, good matching ratio, and matching efficiency. The analytic results indicate the successful implementation of wide-field PAM images, realized by applying suitable methods to the mosaic PAM imaging process.

Spontaneous Generated Convective Anticyclones in Low Latitude --- A Model for the Great Red Spot

The Great Red Spot at about latitude 22oS of Jupiter has been observed for hundreds of years, yet the driving mechanism on the formation of this giant anticyclone still remains unclear. Two scenarios were proposed to explain its formation. One is a shallow model suggesting that it might be a weather feature formed through a merging process of small shallow storms generated by moist convection, while the other is a deep model suggesting that it might be a deeply rooted anticyclone powered by the internal heat of Jupiter. In this work, we present numerical simulations showing that the Great Red Spot could be naturally generated in a deep rotating turbulent flow and survive for a long time, when the convective Rossby number is smaller than a certain critical value. From this critical value, we predict that the Great Red Spot extends at least about 500 kilometers deep into the Jovian atmosphere. Our results demonstrate that the Great Red Spot is likely to be a feature deep-seated in the Jovian atmosphere.

The Hybrid of Jaro-Winkler and Rabin-Karp Algorithm in Detecting Indonesian Text Similarity

The String-matching technique is part of the similarity technique. This technique can detect the similarity level of the text. The Rabin-Karp is an algorithm of string-matching type. The Rabin-Karp is capable of multiple patterns searching but does not match a single pattern. The Jaro-Winkler Distance algorithm can find strings within approximate string matching. This algorithm is very suitable and gives the best results on the matching of two short strings. This study aims to overcome the shortcomings of the Rabin-Karp algorithm in the single pattern search process by combining the Jaro-Winkler and Rabin-Karp algorithm methods. The merging process started from pre-processing and forming the K-Gram data. Then, it was followed by the calculation of the hash value for each K-Gram by the Rabin-Karp algorithm. The process of finding the same hash score and calculating the percentage level of data similarity used the Jaro-Winkler algorithm. The test was done by comparing words, sentences, and journal abstracts that have been rearranged. The average percentage of the test results for the similarity level of words in the combination algorithm has increased. In contrast, the results of the percentage test for the level of similarity of sentences and journal abstracts have decreased. The experimental results showed that the combination of the Jaro-Winkler algorithm on the Rabin-Karp algorithm can improve the similarity of text accuracy.