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As Artificial Intelligence (AI) is becoming ubiquitous in many applications, serverless computing is also emerging as a building block for developing cloud-based AI services. Serverless computing has received much interest because of its simplicity, scalability, and resource efficiency. However, due to the trade-off with resource efficiency, serverless computing suffers from the cold start problem, that is, a latency between a request arrival and function execution. The cold start problem significantly influences the overall response time of workflow that consists of functions because the cold start may occur in every function within the workflow. Function fusion can be one of the solutions to mitigate the cold start latency of a workflow. If two functions are fused into a single function, the cold start of the second function is removed; however, if parallel functions are fused, the workflow response time can be increased because the parallel functions run sequentially even if the cold start latency is reduced. This study presents an approach to mitigate the cold start latency of a workflow using function fusion while considering a parallel run. First, we identify three latencies that affect response time, present a workflow response time model considering the latency, and efficiently find a fusion solution that can optimize the response time on the cold start. Our method shows a response time of 28–86% of the response time of the original workflow in five workflows.

We demonstrate a novel approach for the direct formation of nitrogen dioxide (NO ) in a supercritical nitrogen–oxygen mixture using laser-produced plasma. By tightly focusing a nanosecond laser pulse into the dense fluid, we generate a high electron density plasma that enables chemical reactions not accessible under ambient conditions. Optical emission and absorption spectroscopy confirm the in-situ formation of NO , and parametric investigations reveal that the yield is highly sensitive to the plasma characteristics and gas composition. These findings demonstrate the potential of using plasma as a compact and selective chemical microreactor in dense media, opening new possibilities for on-demand molecular synthesis in extreme environments such as space exploration.

Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA.

This study reinterprets Father Rodrigues’s apostasy in Endō Shūsaku’s Silence not as a religious failure, but as a process of Christianity’s “Japanization,” analyzed within the context of postwar Japanese intellectual history. Where existing criticism often falls into the binary opposition between martyrdom and betrayal, this study introduces the perspective of individual conviction versus organizational authority. First, Rodrigues’s act resonates with Yoshimoto Takaaki’s tenkō (ideological conversion) theory, specifically defined as the “third form of tenkō.” This form represents the choice to pursue the integrity of personal conviction over obedience to an organization. This links Rodrigues’s action to the spiritual continuity of the Kakure Kirishitan (Hidden Christians), arguing that the essence of his apostasy is a betrayal of the Church institution, not of faith itself. Furthermore, through the theme of the dialectic of everyday life, the study demonstrates that salvation is discovered not in the glorious death of martyrdom, but within the secular fabric of daily existence. Rodrigues’s paradoxical condition of being both weak and strong as Okada San’emon after the fumie is an extension of the Kakure Kirishitan’s survival, who maintained their faith amid secular labor. In conclusion, Endō’s literature serves as a testimony for the “cowards” and a plea for the grace to go on living. It illuminates the process through which individual faith transcends institutional authority and takes root in the indigenous Japanese way of life, thereby completing the vision of Christianity’s “Japanization.”

The success of Transformer architecture has seen increased interest in machine translation (MT). The translation quality of neural network-based MT transcends that of translations derived using statistical methods. This growth in MT research has entailed the development of accurate automatic evaluation metrics that allow us to track the performance of MT. However, automatically evaluating and comparing MT systems is a challenging task. Several studies have shown that traditional metrics (e.g., BLEU, TER) show poor performance in capturing semantic similarity between MT outputs and human reference translations. To date, to improve performance, various evaluation metrics have been proposed using the Transformer architecture. However, a systematic and comprehensive literature review on these metrics is still missing. Therefore, it is necessary to survey the existing automatic evaluation metrics of MT to enable both established and new researchers to quickly understand the trend of MT evaluation over the past few years. In this survey, we present the trend of automatic evaluation metrics. To better understand the developments in the field, we provide the taxonomy of the automatic evaluation metrics. Then, we explain the key contributions and shortcomings of the metrics. In addition, we select the representative metrics from the taxonomy, and conduct experiments to analyze related problems. Finally, we discuss the limitation of the current automatic metric studies through the experimentation and our suggestions for further research to improve the automatic evaluation metrics.

Near-perfect light absorbers (NPLAs), with absorbance, A , of at least 99%, have a wide range of applications ranging from energy and sensing devices to stealth technologies and secure communications. Previous work on NPLAs has mainly relied upon plasmonic structures or patterned metasurfaces, which require complex nanolithography, limiting their practical applications, particularly for large-area platforms. Here, we use the exceptional band nesting effect in TMDs, combined with a Salisbury screen geometry, to demonstrate NPLAs using only two or three uniform atomic layers of transition metal dichalcogenides (TMDs). The key innovation in our design, verified using theoretical calculations, is to stack monolayer TMDs in such a way as to minimize their interlayer coupling, thus preserving their strong band nesting properties. We experimentally demonstrate two feasible routes to controlling the interlayer coupling: twisted TMD bi-layers and TMD/buffer layer/TMD tri-layer heterostructures. Using these approaches, we demonstrate room-temperature values of A =95% at λ =2.8 eV with theoretically predicted values as high as 99%. Moreover, the chemical variety of TMDs allows us to design NPLAs covering the entire visible range, paving the way for efficient atomically-thin optoelectronics. The authors demonstrate near-perfect light absorption using only two atomic layers of transition metal dichalcogenides. This is achieved by reducing interlayer interaction which optimizes band nesting, and does not require the use of complex metasurfaces.

Debris flow hazards are often interpreted through back-calculated simulation analysis or empirical methods. The mobility of a debris flow is greatly influenced by mechanical and hydrological parameters. The strength parameters play important roles in the debris flow initiation and flow stages. In particular, the rheological parameters of yield strength and plastic viscosity directly affect the debris flow runout distance and velocity. One of the most important parameters to consider when evaluating debris flow hazards is the shear strength. This strength is called the residual shear strength in the failure stage and the yield strength in the post-failure stage. The residual shear strength obtained from ring shear tests can be related to the initiation of mass movements; the yield strength obtained from rheological tests can be related to the mobilization of debris flows. The residual shear stresses obtained from ring shear tests of weathered soils typically range between 10 and 100 kPa and strongly depend on the normal stress and shear velocity. When progressive slope failure (i.e., strain-softening behavior) occurs at a relatively shallow slope depth (e.g., < 1 m), the soil strength ranges from approximately 5–10 kPa. If the liquid limit state (i.e., solid‒liquid transition) is reached, the shear strength of the soil is approximately 2 kPa. Once the soil fails and mixes with ambient water along the slip surface, the yield strength decreases dramatically, resulting in high mobilization. A suggestion on how strength parameters can be applied to estimate debris flow mobility is presented by considering the 2011 Miryang debris flow, which occurred in weathered soil deposits in Miryang city, Republic of Korea. The best approach for debris flow yield strength estimation would be to consider the residual shear strength in the initiation stage, the yield strength in the flow stage, and the reduction in yield strength with the entrainment effect of the flow in the rapid fluidization stage.

Background Early life plays a vital role in the development of the gut microbiome and subsequent health. While many factors that shape the gut microbiome have been described, including delivery mode, breastfeeding, and antibiotic use, the role of household environments is still unclear. Furthermore, the development of the gut antimicrobial resistome and its role in health and disease is not well characterized, particularly in settings with water insecurity and less sanitation infrastructure. Results This study investigated the gut microbiome and resistome of infants and young children (ages 4 days-6 years) in rural Nicaragua using Oxford Nanopore Technology’s MinION long-read sequencing. Differences in gut microbiome diversity and antibiotic resistance gene (ARG) abundance were examined for associations with host factors (age, sex, height for age z-score, weight for height z-score, delivery mode, breastfeeding habits) and household environmental factors (animals inside the home, coliforms in drinking water, enteric pathogens in household floors, fecal microbial source tracking markers in household floors). We identified anticipated associations of higher gut microbiome diversity with participant age and vaginal delivery. However, novel to this study were the significant, positive associations between ruminant and dog fecal contamination of household floors and gut microbiome diversity. We also identified greater abundance of potential pathogens in the gut microbiomes of participants with higher fecal contamination on their household floors. Path analysis revealed that water quality and household floor contamination independently and significantly influenced gut microbiome diversity when controlling for age. These gut microbiome contained diverse resistome, dominated by multidrug, tetracycline, macrolide/lincosamide/streptogramin, and beta-lactam resistance. We found that the abundance of ARGs in the gut decreased with age. The bacterial hosts of ARGs were mainly from the family Enterobacteriaceae , particularly Escherichia coli . Conclusions This study identified the role of household environmental contamination in the developing gut microbiome and resistome of young children and infants with a One Health perspective. We found significant relationships between host age, gut microbiome diversity, and the resistome. Understanding the impact of the household environment on the development of the resistome and microbiome in early life is essential to optimize the relationship between environmental exposure and human health. 92Jf2w8Y_xc1zDLBRpWCqW Video Abstract Graphical Abstract

This paper presents a small-sized, low-power gas sensor system combining a high-electron-mobility transistor (HEMT) device and readout integrated circuit (ROIC). Using a semiconductor-based HEMT as a gas-sensing device, it is possible to secure high sensitivity, reduced complexity, low power, and small size of the ROIC sensor system. Unlike existing gas sensors comprising only HEMT elements, the proposed sensor system has both an ROIC and a digital controller and can control sensor operation through a simple calibration process with digital signal processing while maintaining constant performance despite variations. The ROIC mainly consists of a transimpedance amplifier (TIA), a negative-voltage generator, and an analog-to-digital converter (ADC) and is designed to match a minimum target detection unit of 1 ppm for hydrogen. The prototype ROIC for the HEMT presented herein was implemented in a 0.18 µm complementary metal–oxide–semiconductor (CMOS) process. The total measured power consumption and detection unit of the proposed ROIC for hydrogen gas were 3.1 mW and 2.6 ppm, respectively.

Floor materials in indoor environments are known to be reservoirs of microbes. We focused on examining bacterial community composition, antibiotic resistance (AR) and microbial source tracking (MST) of fecal bacteria on the floor surfaces. Swab samples were collected from carpet and vinyl floors in three different buildings (medical, veterinary, and office buildings) from high and low traffic areas. Bacterial communities were determined with 16S rRNA sequencing, and AR (tetracycline (tetQ), sulfonamide, and carbapenem (KPC)) and MST (human-, canine-, avian-, and ruminant-specific fecal bacteria) were examined with quantitative polymerase chain reaction (PCR). The results show that Proteobacteria and Actinobacteria were the most abundant phyla. Traffic level significantly affected the number of operational taxonomic units. Traffic level was a key factor for distinctive bacterial community in the medical center. Targeted ARGs were detected from all buildings and tetQ concentration was related with traffic level, and KPC was only detected from the medical center. Most of the floor surfaces showed the presence of dog-specific fecal bacteria (83%) followed by bird-specific fecal bacteria (75%). The results suggest that traffic levels affected the bacterial levels and fecal contamination is prevalent on the floor surfaces. This is the first study that reports KPC presence on the floor surfaces.