206 research outputs found
Retrieving Top-N Weighted Spatial k-cliques
Spatial data analysis is a classic yet important topic because of its wide range of applications. Recently, as a spatial data analysis approach, a neighbor graph of a set P of spatial points has often been employed. This paper also considers a spatial neighbor graph and addresses a new problem, namely top-N weighted spatial k-clique retrieval. This problem searches for the N minimum weighted cliques consisting of k points in P, and it has important applications, such as community detection and co-location pattern mining. Recent spatial datasets have many points, and efficiently dealing with such big datasets is one of the main requirements of applications. A straightforward approach to solving our problem is to try to enumerate all k-cliques, which incurs O(nkk2) time. Since k ≥ 3, this approach cannot achieve the main requirement, so computing the result without enumerating unnecessary k-cliques is required. This paper achieves this challenging task and proposes a simple practically-efficient algorithm that returns the exact answer. We conduct experiments using two real spatial datasets consisting of million points, and the results show the efficiency of our algorithm, e.g., it can return the exact top-N result within 1 second when N ≤ 1000 and k ≤ 7.Taniguchi R., Amagata D., Hara T.. Retrieving Top-N Weighted Spatial k-cliques. Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022 , 4952 (2022); https://doi.org/10.1109/BigData55660.2022.10021071
Efficient Retrieval of Top-k Weighted Spatial Triangles
Due to the proliferation of location-based services and IoT devices, a lot of spatial points are being generated. Spatial data analysis is well known to be an important task. As spatial data analysis tools, graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, have been receiving much attention. We focus on triangles (one of the simplest sub-graph patterns) in such graphs and address the problem of retrieving the top-k weighted spatial triangles. This problem has important real-life applications, e.g., group search, urban planning, and co-location pattern mining. However, this problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To solve this challenge, we propose an efficient algorithm that returns the exact result. Our experimental results on real datasets show the efficiency of our algorithm.This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-00123-9_17
Efficient Retrieval of Top-k Weighted Triangles on Static and Dynamic Spatial Data
Due to the proliferation of location-based services, spatial data analysis becomes more and more important. We consider graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, as they have been receiving attention as spatial data analysis tools. We focus on triangles in such graphs and address the problem of retrieving the top- weighted spatial triangles. This problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To overcome this challenge, we propose an algorithm that returns the exact result efficiently. We moreover consider two dynamic data models: (i) fully dynamic data that allow arbitrary point insertions and deletions and (ii) streaming data in a sliding-window model. They often appear in location-based services. The results of our experiments on real datasets show the efficiency of our algorithms for static and dynamic data.Taniguchi R., Amagata D., Hara T.. Efficient Retrieval of Top-k Weighted Triangles on Static and Dynamic Spatial Data. IEEE Access 10, 55298 (2022); https://doi.org/10.1109/ACCESS.2022.3177620
Phosphorous Uptake from Organic Matter via AM fungi : Possible Involvement of Phytate-Degrading Bacteria
Poster Sessio
SlIAA9 Controls Tomato Elongation
Tomato INDOLE-3-ACETIC ACID9 (SlIAA9) is a transcriptional repressor in auxin signal transduction, and SlIAA9 knockout tomato plants develop parthenocarpic fruits without fertilization. We generated sliaa9 mutants with parthenocarpy in several commercial tomato cultivars (Moneymaker, Rio Grande, and Ailsa Craig) using CRISPR-Cas9, and null-segregant lines in the T1 generation were isolated by self-pollination, which was confirmed by PCR and Southern blot analysis. We then estimated shoot growth phenotypes of the mutant plants under different light (low and normal) conditions. The shoot length of sliaa9 plants in Moneymaker and Rio Grande was smaller than those of wild-type cultivars in low light conditions, whereas there was not clear difference between the mutant of Ailsa Craig and the wild-type under both light conditions. Furthermore, young seedlings in Rio Grande exhibited shade avoidance response in hypocotyl growth, in which the hypocotyl lengths were increased in low light conditions, and sliaa9 mutant seedlings of Ailsa Craig exhibited enhanced responses in this phenotype. Fruit production and growth rates were similar among the sliaa9 mutant tomato cultivars. These results suggest that control mechanisms involved in the interaction of AUX/IAA9 and lights condition in elongation growth differ among commercial tomato cultivars
Altered Islet Composition and Disproportionate Loss of Large Islets in Patients with Type 2 Diabetes
Human islets exhibit distinct islet architecture with intermingled alpha- and beta-cells particularly in large islets. In this study, we quantitatively examined pathological changes of the pancreas in patients with type 2 diabetes (T2D). Specifically, we tested a hypothesis that changes in endocrine cell mass and composition are islet-size dependent. A large-scale analysis of cadaveric pancreatic sections from T2D patients (n = 12) and non-diabetic subjects (n = 14) was carried out combined with semi-automated analysis to quantify changes in islet architecture. The method provided the representative islet distribution in the whole pancreas section that allowed us to examine details of endocrine cell composition in individual islets. We observed a preferential loss of large islets (>60 µm in diameter) in T2D patients compared to non-diabetic subjects. Analysis of islet cell composition revealed that the beta-cell fraction in large islets was decreased in T2D patients. This change was accompanied by a reciprocal increase in alpha-cell fraction, however total alpha-cell area was decreased along with beta-cells in T2D. Delta-cell fraction and area remained unchanged. The computer-assisted quantification of morphological changes in islet structure minimizes sampling bias. Significant beta-cell loss was observed in large islets in T2D, in which alpha-cell ratio reciprocally increased. However, there was no alpha-cell expansion and the total alpha-cell area was also decreased. Changes in islet architecture were marked in large islets. Our method is widely applicable to various specimens using standard immunohistochemical analysis that may be particularly useful to study large animals including humans where large organ size precludes manual quantitation of organ morphology
Changes in Behavior, Professionalism, and Views on Life and Death among Physical Therapists and Students during the COVID-19 Pandemic in Japan
Although the mental health disorders of healthcare workers during the coronavirus disease 2019 (COVID-19) pandemic have been examined, little is known about the psychological impact of the pandemic on physical therapists. In this study, an online questionnaire survey was conducted on physical therapists and students aspiring to become physical therapists, to investigate changes in behavior/values and related factors. Increased anxiety about COVID- 19, awareness of voluntary restraint, and reduced motivation were observed in comparison with usual levels in both physical therapists and students. The desire to resign and concerns about patients increased significantly, and the desire to resign tended to increase with increases in years of clinical experience. The subjects’ views of the profession did not change, but decreased motivation was related to damage to the professionalism. Views on life and death changed significantly in both groups, and change was greater in students than in physical therapists. Anxiety and/or awareness of voluntary restraint and/or experience caring for patients were associated with changes in views on life and death. These results indicate that the COVID-19 pandemic affected the behaviors and values of physical therapists and students through anxiety and reduced motivation
Genome editing in plants using CRISPR type I-D nuclease
Genome editing in plants has advanced greatly by applying the clustered regularly interspaced short palindromic repeats (CRISPRs)-Cas system, especially CRISPR-Cas9. However, CRISPR type I—the most abundant CRISPR system in bacteria—has not been exploited for plant genome modification. In type I CRISPR-Cas systems, e.g., type I-E, Cas3 nucleases degrade the target DNA in mammals. Here, we present a type I-D (TiD) CRISPR-Cas genome editing system in plants. TiD lacks the Cas3 nuclease domain; instead, Cas10d is the functional nuclease in vivo. TiD was active in targeted mutagenesis of tomato genomic DNA. The mutations generated by TiD differed from those of CRISPR/Cas9; both bi-directional long-range deletions and short indels mutations were detected in tomato cells. Furthermore, TiD can be used to efficiently generate bi-allelic mutant plants in the first generation. These findings indicate that TiD is a unique CRISPR system that can be used for genome engineering in plants
A novel COL4A1 variant associated with recurrent epistaxis and glioblastoma
COL4A1-related disorders are characterized by a higher incidence of cerebral hemorrhage than other hereditary cerebral small vessel diseases. Accumulating data have shown broad phenotypic variations, and extracerebral hemorrhages have been linked to these disorders. Moreover, the coexistence of neural tumors has been described. Here, we report a Japanese family with a novel COL4A1 variant, including a patient with recurrent epistaxis and glioblastoma
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