Towards Rewriting Semantics of Software Architecture Specification

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A Cluster-Based Statistical Channel Model for Integrated Sensing and Communication Channels

The emerging 6G network envisions integrated sensing and communication (ISAC) as a promising solution to meet growing demand for native perception ability. To optimize and evaluate ISAC systems and techniques, it is crucial to have an accurate and realistic wireless channel model. However, some important features of ISAC channels have not been well characterized, for example, most existing ISAC channel models consider communication channels and sensing channels independently, whereas ignoring correlation under the consistent environment. Moreover, sensing channels have not been well modeled in the existing standard-level channel models. Therefore, in order to better model ISAC channel, a cluster-based statistical channel model is proposed in this paper, which is based on measurements conducted at 28 GHz. In the proposed model, a new framework based on 3GPP standard is proposed, which includes communication clusters and sensing clusters. Clustering and tracking algorithms are used to extract and analyze ISAC channel characteristics. Furthermore, some special sensing cluster structures such as shared sensing cluster, newborn sensing cluster, etc., are defined to model correlation and difference between communication and sensing channels. Finally, accuracy of the proposed model is validated based on measurements and simulations

RACE: An Efficient Redundancy-aware Accelerator for Dynamic Graph Neural Network

Dynamic Graph Neural Network (DGNN) has recently attracted a significant amount of research attention from various domains, because most real-world graphs are inherently dynamic. Despite many research efforts, for DGNN, existing hardware/software solutions still suffer significantly from redundant computation and memory access overhead, because they need to irregularly access and recompute all graph data of each graph snapshot. To address these issues, we propose an efficient redundancy-aware accelerator, RACE, which enables energy-efficient execution of DGNN models. Specifically, we propose a redundancy-aware incremental execution approach into the accelerator design for DGNN to instantly achieve the output features of the latest graph snapshot by correctly and incrementally refining the output features of the previous graph snapshot and also enable regular accesses of vertices\u27 input features. Through traversing the graph on the fly, RACE identifies the vertices that are not affected by graph updates between successive snapshots to reuse these vertices\u27 states (i.e., their output features) of the previous snapshot for the processing of the latest snapshot. The vertices affected by graph updates are also tracked to incrementally recompute their new states using their neighbors\u27 input features of the latest snapshot for correctness. In this way, the processing and accessing of many graph data that are not affected by graph updates can be correctly eliminated, enabling smaller redundant computation and memory access overhead. Besides, the input features, which are accessed more frequently, are dynamically identified according to graph topology and are preferentially resident in the on-chip memory for less off-chip communications. Experimental results show that RACE achieves on average 1139× and 84.7× speedups for DGNN inference, with average 2242× and 234.2× energy savings, in comparison with the state-of-the-art software DGNN running on Intel Xeon CPU and NVIDIA A100 GPU, respectively. Moreover, for DGNN inference, RACE obtains on average 13.1×, 11.7×, 10.4×, and 7.9× speedup and 14.8×, 12.9×, 11.5×, and 8.9× energy savings over the state-of-the-art Graph Neural Network accelerators, i.e., AWB-GCN, GCNAX, ReGNN, and I-GCN, respectively

Spatiotemporal consistency analysis of cerebral small vessel disease: an rs-fMRI study

IntroductionCerebral small vessel disease (SVD) affects older adults, but traditional approaches have limited the understanding of the neural mechanisms of SVD. This study aimed to explore the effects of SVD on brain regions and its association with cognitive decline using the four-dimensional (spatiotemporal) consistency of local neural activity (FOCA) method.MethodsMagnetic resonance imaging data from 42 patients with SVD and 38 healthy controls (HCs) were analyzed using the FOCA values. A two-sample t test was performed to compare the differences in FOCA values in the brain between the HCs and SVD groups. Pearson correlation analysis was conducted to analyze the association of various brain regions with SVD scores.ResultsThe results revealed that the FOCA values in the right frontal_inf_oper, right temporal_pole_sup, and default mode network decreased, whereas those in the temporal_inf, hippocampus, basal ganglia, and cerebellum increased, in patients with SVD. Most of these varying brain regions were negatively correlated with SVD scores.DiscussionThis study suggested that the FOCA approach might have the potential to provide useful insights into the understanding of the neurophysiologic mechanisms of patients with SVD

Influence of D-Amino Acids in Beer on Formation of Uric Acid

Prekomjerna konzumacija piva može dovesti do povećanja koncentracije mokraćne kiseline u serumu, čime se povećava rizik nastanka uričnog artritisa (gihta), što se prethodno dovodilo u vezu s velikim udjelom purina u pivu. Međutim, novija istraživanja pokazuju da konzumacija povrća bogatog purinima i grahorica ne povećava koncentraciju mokraćne kiseline, što opovrgava tu tvrdnju. Još uvijek nije objašnjeno zašto povećana konzumacija piva može povećati rizik nastanka gihta, pa su ispitani drugi uzročnici nakupljanja mokraćne kiseline u krvi. Pivo sadržava relativno velike koncentracije D-aminokiselina koje nastaju racemizacijom L-aminokiselina tijekom prerade hrane. Katalizom pomoću D-aminokiselinske oksidaze iz D-aminokiselina nastaje H2O2, čijom oksidacijom u prisutnosti Fe2+ nastaju hidroksilni radikali. Pritom dolazi do oštećenja DNA i nastanka purinskih baza u većoj količini, iz kojih djelovanjem različitih enzima nastaje mokraćna kiselina. Neki dodaci hrani, kao što su vitamini i ioni joda, potiču nastanak mokraćne kiseline iz D-aminokiselina. D-aminokiseline u pivu imaju ključnu ulogu u povećanju koncentracije mokraćne kiseline. Biološka uloga D-aminokiselina može objasniti pojavu gihta kod osoba koje učestalo konzumiraju pivo.Excessive intake of beer could increase serum uric acid levels, leading to high risk of gout, which was previously attributed to high purine content in beer. Recent reports that purine-rich vegetables and bean products do not cause higher uric acid levels do not support this theory. Why excessive intake of beer could increase a high risk of gout has been unclear. Other factors affecting the accumulation of uric acid in the blood have been explored. Beer contains relatively high levels of D-amino acids due to the racemization of l-amino acids induced by food processing. D-amino acid was catalyzed by D-amino acid oxidase to produce H2O2, which is further oxidized in the presence of Fe2+ to produce hydroxyl radicals, resulting in DNA damage and formation of a large amount of purine bases, which are oxidized to uric acid by a series of enzymes. Some food ingredients, such as vitamins and I–, prompt D-amino acids to form uric acid. D-amino acids in beer are one of the key factors responsible for the increase in uric acid levels. The biological response of D-amino acids could explain gout occurrence in beer drinkers

Dynamic Distribution of Gut Microbiota in Goats at Different Ages and Health States

The importance of the gut microbiota (GM) of animals is widely acknowledged because of its pivotal roles in metabolism, immunity, and health maintenance. The level of health can be reflected by the dynamic distribution of GM. In this study, high-throughput sequencing of the bacterial 16S rRNA gene was used to compare the microbial populations from feces in healthy and diarrheic kids, which reflected the dynamic shift of microbiota in kids and investigated differences from adult healthy goats. Healthy kids and goats not only displayed higher species richness but also exhibited higher bacterial diversity than diarrheic kids based on the results of the operational taxonomic unit analysis, alpha diversity, and beta diversity. Firmicutes and Bacteroidetes were the most dominant phyla in all samples. At the genus level, the differences in diversity and abundance between diarrheic kids and the other two groups were gradually observed. In the diarrheic kid intestine, Bacteroides remained the dominant species, and the proportion of Clostridium_sensu_stricto_1 and Paeniclostridium increased, whereas Rikenellaceae_RC9_gut_group, Ruminococcaceae_UCG-005, and Christensenellaceae_R-7_group were significantly reduced. The results showed the differences of GM in diarrheic kids and healthy kids were significant while in kids and goats were not obvious. Differences in the composition of intestinal microbiota may not be the cause of diarrhea, and some changes of bacterial richness may guide our interpretation of diarrhea. This study is the first to investigate the distribution of GM in Boer goats with different ages and health states. Furthermore, this study will provide a theoretical basis for the establishment of a prevention and treatment system for goat diarrhea

Studies on the interaction of achiral cationic pseudoisocyanine with chiral metal complexes

The effect of chiral metal complexes ([Co(en)(3)]I(3)center dot H(2)O, cis-[CoBr(NH(3))(en)(2)]Br(2), K[Co(edta)]center dot 2H(2)O and [Ru(phen)(3)](PF(6))(2)) on the polymer-bound J-aggregates in aqueous mixtures of pesudoisocyanine (PIC) iodine and poly(acrylic acid, sodium)(PAAS) have been studied by UV-vis absorption, circular dichroism (CD) and fluorescence spectra. At low concentration, the PIC monomers could self-assemble to form supermolecules by binding to each of the COO(-) groups on the polymer chains through electrostatic interactions. After the addition of chiral metal complexes to the formed PIC-PAAS J-aggregates, we found that only the chiral multiple pi-conjugated phenanthroline metal complexes could transfer their metal-centered chiral information to the formed J-aggregates. The chiral J-aggregates showed a characteristic induced circular dichroism (ICD) in the visible region of J-band chromophore, and the ICD signals depend on the absolute configuration, concentration of the chiral multiple pi-conjugated metal complexes, as well as temperature. More interestingly, the supramolecular chirality of the polymer supported PIC J-aggregates could be memorized even after the addition of an excess opposite chiral complex enantiomers. This is in sharp contrast to the behavior in the high concentrated NaCl induced PIC-J aggregates, in which the optical rotation of a mixture of two enantiomers varies linearly with their ratio.National Natural Science Foundation of China[20773098, 20877099, 20972183]; State Key Laboratory of Natural and Biomimetic Drugs[20080208]; GUCAS (A B); Ministry of Science and Technology of China[2008AA100801]; CAS[2010B090300031]; Guangdong Provinc