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A new 8,17-epoxybriarane, briastecholide O (1), was isolated from an encrusting algae-containing cultured octocoral Briareum stechei. Moreover, wild-type B. stechei collected from Okinawan waters yielded a new 8,17-epoxybriarane, briastecholide P (2), along with two known analogs, namely, briaexcavatins G (3) and X (4). Single-crystal X-ray diffraction was conducted to determine the absolute configurations of 2 – 4 , while the structure of 1 was established by spectroscopic elucidation. Briaranes 1 and 3 were active in enhancing the growth of MG-63 human mesenchymal stem cells. [Display omitted] • New briaranes, briastecholides O (1) and P (2), were isolated from Briareum stechei. • The absolute configuration of briarane 2 was determined via X-ray analysis. • Briarane 1 enhanced the growth of MG-63 human mesenchymal stem cells. [ABSTRACT FROM AUTHOR]

Purpose: To assess the effects of ceramic thickness, ceramic translucency, and light transmission on restorative composites used as luting cement for lithium disilicate-based ceramics. Methods: Four luting types of cement were tested (n=8); a dual-cured resin cement (Multilink N), a light-cured conventional flowable composite (Tetric N-Flow), and two light-cured bulk-fill flowable composites (Tetric N-Flow Bulk Fill and X-tra base). The 20 s- or 40 s-light (1000 mW/cm2) was transmitted through 1- or 2-mm-thick high- or low-translucency (HT- or LT-) ceramic discs (IPS e.Max press) to reach the 1-mm-thick luting cement. Light transmitted to cement without ceramic served as a control. Vickers hardness number (VHN), flexural strength (FS), fractography, and degree of conversion (DC) were evaluated. One-way and multi-way analysis of variance was conducted to determine the effects of factors on VHN and FS. Results: Ceramic thickness, light transmission time, and cement type significantly affected the VHN of the luting cement (P < .000). Only Multilink N (LT- and HT-1mm) and Tetric N-Flow (HT-1mm) reached 90% VHN of corresponding control by 20 s-light transmissions, but Tetric N-Flow exhibited lowest VHN and approximately 1/3-1/2 VHN of Multilink N (P < 0.05). X-tra base expressed superior physicochemical properties to Tetric N-Flow Bulk Fill (P < 0.05) and reached >90% VHN of control in all conditions with 40 s-light transmissions except for LT-2 mm. DC, FS, and fractography supported these findings. Conclusions: The light-cured bulk-fill composite served as a luting cement for lithium-disilicate-based ceramics in a product-dependent manner. Light transmission time is crucial to ensure sufficient luting cement polymerization. [ABSTRACT FROM AUTHOR]

In this paper, we improve the state-of-the-art ECAPA-TDNN model for speaker verification with CNN stem, self-calibration (SC) block, and deep layer aggregation. The proposed architecture is called Emphasized Channel Attention Propagation and Deep Layer Aggregation with Pre-activated CNN Stem in Time Delay Neural Network, which is abbreviated as ECAPDLA CNNv2-TDNN. First, we add a pre-activated stemming convolution layer in front of the main ECAPA-TDNN architecture. This ensures that the input to our main model architecture is a stable feature representation. Next, we change the multi-layer aggregation of ECAPA-TDNN to deep layer aggregation and replace the SE-Res2block in ECAPA-TDNN with SC block. Thus, the proposed implementation enhances feature extraction on multiple time scales and spectral channels and improves the overall training efficacy. On the VoxCelebl-O dataset, the proposed model achieves an equal error rate (EER) of 0.95%. This is significantly better than the EER of 1.23% achieved by the ECAPA-TDNN baseline. [ABSTRACT FROM AUTHOR]

Objectives: Hepatocellular carcinoma (HCC) is a common indication for hepatectomy that is often complicated by postoperative complication. The authors sought to investigate the relationship between the open with laparoscopic approach of hepatectomy and incidences of postoperative infectious complications. Patients and methods: Using a multicenter database, HCC patients who underwent laparoscopic hepatectomy (LH) or open hepatectomy (OH) were reviewed and analyzed. Propensity score matching (PSM), inverse probability of treatment weight (IPTW), and multivariate logistic regression analyses were utilized to assess the association of the operative approach with postoperative infectious complications, including incisional surgical site infection (SSI), organ/space SSI, and remote infection (RI). Results: Among 3876 patients, 845 (21.8%) and 3031 (78.2%) patients underwent LH and OH, respectively. The overall incidence of infectionwas 6.9 versus 14.6% among patients who underwent LH versus OH, respectively (P<0.001).Of note, the incidences of incisional SSI (1.8 vs. 6.3%, P<0.001), organ/space SSI (1.8 vs. 4.6%, P<0.001), and RI (3.8 vs. 9.8%, P<0.001) were all significantly lower among patients who underwent LH versus OH. After PSM (6.9, 1.8, 1.8, and 3.8%vs. 18.5, 8.4, 5.2, and 12.8%, respectively) and IPTW (9.5, 2.3, 2.1, and 5.5% vs. 14.3, 6.3, 4.5, and 9.8%, respectively), LH remained associated with statistically lower incidences of all types of infectious complications. After adjustment for other confounding factors on multivariate analyses, LH remained independently associated with lower incidences of overall infection, incisional SSI, organ/space SSI, and RI in the overall, PSM, and IPTW cohorts, respectively. Conclusion: Compared with open approach, laparoscopic approach was independently associated with lower incidences of postoperative infectious complications following hepatectomy for HCC. [ABSTRACT FROM AUTHOR]

Malware analysis has been extensively investigated as the number and types of malware has increased dramatically. However, most previous studies use end-to-end systems to detect whether a sample is malicious, or to identify its malware family. In this paper, we introduce a framework composed of two components, RasMMA and RasNN, accounting for common characteristics within a family. While RasMMA extracts the common behaviors of malware, RasNN is designed to pretrain a composition of the common behaviors as malware representation. Different from the end-to-end models, the pre-trained malware representation can be fine-tuned with one additional output layer to apply other malware applications, such as family classification. We conduct broad experiments to determine the influence of individual framework components and the feasibility of a task-specific extension model. The results show that the proposed framework outperforms the other baselines, and also demonstrates that learned malware representation can be applied to other cybersecurity application and outperform the existing system. [ABSTRACT FROM AUTHOR]

To investigate effect and mechanism of Ziqi Ruangan Decoction (ZQRGD) on hepatic fibrosis in rats. Rats were randomly assigned to blank group, model group, colchicine group, ZQRGD high-dose group, ZQRGD middle-dose group, and ZQRGD low-dose group. All groups except group A were intraperitoneally injected with 40% CCl4/olive oil for 8 weeks; group C was then given intragastric colchicine administration. Groups D, E, and F were intragastrically dosed with ZQRGD. Compared with the colchicine group, the superoxide dismutase (SOD) activity of each dose group of ZQRGD significantly increased. TNF-α and IL-6 concentration significantly decreased in each drug intervention group, while these significantly decreased in the high-dose and medium-dose ZQRGD groups. The expression of α-SMA and collagen I significantly decreased in the drug treatment group compared with the model group, as did the expression of PI3K, AKT, and mTOR. Ziqi Ruangan Decoction had a favorable anti-liver fibrosis effect and the mechanism is related to anti-oxidative stress, anti-inflammation, the inhibition of the PI3K/Akt/mTOR signaling pathway, and the inhibition of hepatic stellate cell activation. [ABSTRACT FROM AUTHOR]

Meiotic disturbances in F 1 hybrids and their progenies are still major problems in wide hybridization. To investigate the genome affinity reflected in chromosome pairing and segregation, we studied chromosome behaviors during meiosis in two interspecific F 1 hybrids [ O. minuta × O. australiensis (Om × Oa , BCE genome) and Oa × O. ridleyi (Or , EHJ genome)] by using both traditional staining methods and genomic in situ hybridization (GISH). GISH analysis has been successfully performed on mitotic chromosomes to distinguish different Oryza genomes, but relatively fewer systematic analyses of meiotic chromosomes of interspecific hybrids have been reported. In the hybrids, highly irregular chromosome behaviors through meiosis resulted in producing microspores with unbalanced genome. At diakinesis of these two hybrids, most chromosomes present as univalent, with low frequency as bivalents and occasionally as trivalents. In a pollen mother cell, 2 to 8 bivalents and 0 to 4 trivalents were observed in the hybrid Oa × Or , and 1 to 8 bivalents and 0 to 5 trivalents were observed in the hybrid Om × Oa. GISH results indicated that 51.52% bivalents in Oa × Or and 79.65% bivalents in Om × Oa involved allosyndetic association, which indicates that recombination and introgression should be possible if viable backcrosses can be recovered even from triploid hybrids. In this study, we revealed that the meiotic disturbance due to low affinities between parental genomes is the major reason for the sterility of these two triploid interspecific hybrids. The two hybrids showing vigor in reproductive growth are potential genetic resources in future breeding programs. A better understanding of genomic affinities between these distant Oryza species can facilitate planning an effective breeding program by using wide hybridization, and efficient and routine GISH analysis is helpful to monitor alien introgression in the process. [ABSTRACT FROM AUTHOR]

The article discusses plastic's benefits, the ever-increasing mass of unmanaged plastic waste is causing significant damage to the global ecosystem. Topics include a few key regulations, as well as recycling technologies, have helping to curb the threat; and produced in huge quantities, plastics have transformed world in countless ways.

In this paper, we report on our investigation of human-AI collaboration for mind-mapping. We specifically focus on problem exploration in pre-conceptualization stages of early design. Our approach leverages the notion of query expansion--the process of refining a given search query for improving information retrieval. Assuming a mind-map as a network of nodes, we reformulate its construction process as a sequential interaction workflow wherein a human user and an intelligent agent take turns to add one node to the network at a time. Our contribution is the design, implementation, and evaluation of algorithm that powers the intelligent agent (IA). This paper is an extension of our prior work (Chen et al., 2019, "Mini-Map: Mixed-Initiative Mind-Mapping Via Contextual Query Expansion," AIAA Scitech 2020 Forum, p. 2347) wherein we developed this algorithm, dubbed Mini-Map, and implemented a web-based workflow enabled by ConceptNet (a large graph-based representation of "commonsense" knowledge). In this paper, we extend our prior work through a comprehensive comparison between human-AI collaboration and human-human collaboration for mind-mapping. We specifically extend our prior work by: (a) expanding on our previous quantitative analysis using established metrics and semantic studies, (b) presenting a new detailed video protocol analysis of the mind-mapping process, and (c) providing design implications for digital mind-mapping tools. [ABSTRACT FROM AUTHOR]

In this paper, we report on our investigation of human-AI collaboration for mind-mapping. We specifically focus on problem exploration in pre-conceptualization stages of early design. Our approach leverages the notion of query expansion--the process of refining a given search query for improving information retrieval. Assuming a mind-map as a network of nodes, we reformulate its construction process as a sequential interaction workflow wherein a human user and an intelligent agent take turns to add one node to the network at a time. Our contribution is the design, implementation, and evaluation of algorithm that powers the intelligent agent (IA). This paper is an extension of our prior work (Chen et al., 2019, "Mini-Map: Mixed-Initiative Mind-Mapping Via Contextual Query Expansion," AIAA Scitech 2020 Forum, p. 2347) wherein we developed this algorithm, dubbed Mini-Map, and implemented a web-based workflow enabled by ConceptNet (a large graph-based representation of "commonsense" knowledge). In this paper, we extend our prior work through a comprehensive comparison between human-AI collaboration and human-human collaboration for mind-mapping. We specifically extend our prior work by: (a) expanding on our previous quantitative analysis using established metrics and semantic studies, (b) presenting a new detailed video protocol analysis of the mind-mapping process, and (c) providing design implications for digital mind-mapping tools. [ABSTRACT FROM AUTHOR]

The pandemic of avian influenza viruses (AIVs) in Asia has caused enormous economic loss in poultry industry and human health threat, especially clade 2.3.4.4 H5 and H7 subtypes in recent years. The endemic chicken H6 virus in Taiwan has also brought about human and dog infections. Since wild waterfowls is the major AIV reservoir, it is important to monitor the diversified subtypes in wildfowl flocks in early stage to prevent viral reassortment and transmission. To develop a more efficient and sensitive approach is a key issue in epidemic control. In this study, we integrate multiplex reverse transcription recombinase polymerase amplification (RT-RPA) and capillary electrophoresis (CE) for high-throughput detection and differentiation of AIVs in wild waterfowls in Taiwan. Four viral genes were detected simultaneously, including nucleoprotein (NP) gene of all AIVs, hemagglutinin (HA) gene of clade 2.3.4.4 H5, H6 and H7 subtypes. The detection limit of the developed detection system could achieve as low as one copy number for each of the four viral gene targets. Sixty wild waterfowl field samples were tested and all of the four gene signals were unambiguously identified within 6 h, including the initial sample processing and the final CE data analysis. The results indicated that multiplex RT-RPA combined with CE was an excellent alternative for instant simultaneous AIV detection and subtype differentiation. The high efficiency and sensitivity of the proposed method could greatly assist in wild bird monitoring and epidemic control of poultry. [ABSTRACT FROM AUTHOR]

One-dimensional boron-doped submicron diamond rods (SDRs) were fabricated on diamond/Si substrates by oxygen plasma etching. The SDRs are ∼4.5 μm in height and ∼383 nm in diameter. Iron oxide coated on SDRs is essential in the formation of one-dimensional SDRs. However, the as-etched SDRs suffer with high turn-on field (ETO) and low field emission current density (JFE) due to the iron oxide. A huge improvement in the field emission characteristics can be achieved by removing iron oxide using a wet-etch process in a diluted HCl (37%). After the wet-etch, the SDRs exhibit a low ETO value of 4.5 V/μm (at 10 μA/cm2) and a high JFE value of 30 mA/cm2 (at 8.5 V/μm). The FE emitter is only stable for a short period of time at high current stress owing to the rounding of the tips of SDRs. [ABSTRACT FROM AUTHOR]

The weight is one of the most useful tools to measure the attribute importance when individuals make a decision or evaluate the alternatives. Among the methods which measure the weight, fuzzy measures is are subjective scales for the degrees of fuzziness and widely used to determine the degrees of subjective importance of evaluation items in numerous studies for the time being. The purpose of this study is to use fuzzy number-valued fuzzy measures to determine the attribute importance. Several types of triangular fuzzy numbers and trapezoidal fuzzy numbers were applied in order to observe which type of fuzzy numbers had the best effects in the empirical study. In addition, we took advantage of distance measures to adjust the distance between attribute importance such as Euclidean distance, and Tran and Duckstein's distances. The results indicate that since using different types of fuzzy numbers and distance measures in fuzzy number-valued fuzzy measures have the similar performance, we suggest that triangular fuzzy numbers are better than trapezoidal fuzzy numbers, and Euclidean distance is preferred on account of their simple form to calculate. [ABSTRACT FROM AUTHOR]

Because of the reason that the individuals' thoughts have the complicated and uncertain characteristics in the field of social science, this study makes the most of the fuzzy sets, which solve uncertain and imprecise conditions, to transform the opinions belonging to human beings into the quantitative numbers. Advertising involvement is regarded as the object for this empirical study which comprehensively collects plenty of antecedents and consequences for advertising involvement. We take advantage of the fuzzy automata to develop an integrated model of advertising involvement. The results indicate that in addition to the selection of implications, a fitting model relies on the selection of compositions in the fuzzy automata. On the average, the standard composition, which is one of compositions in this study, is the most appropriate method for developing a model of advertising involvement. [ABSTRACT FROM AUTHOR]

Atanassov (Fuzzy Sets and Systems 20 (1986) 87-96) defined basic operations over the intuitionistic fuzzy sets. Here we shall introduce two operations, subtraction and division, derived from the deconvolution for equations using addition and multiplication operations, respectively. In addition, we shall give some conditions to examine the correctness regarding the defined operations. The remarks in this paper can be immediately expressed in terms of interval-valued fuzzy sets. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce a new method for measuring attribute salience in decision analysis. Fuzzy measures have been widely used to determine the degrees of subjective importance of evaluation items. We consider the value of fuzzy measures as a linguistic value and then convert linguistic terms to fuzzy numbers. The grades of attribute importance are correspondingly expressed by fuzzy number-valued fuzzy measures. However, the leniency error may exist when most attributes are assigned unduly high ratings. To reduce positive leniency in fuzzy measure ratings, we develop an importance-assessing method by comparison of fuzzy number-valued fuzzy measures using a fuzzy distance measure. An outcome-oriented approach is adopted to validate the proposed method. Several multiattribute evaluation cases in consumer decision-making reality are addressed to examine the feasibility and applicability of the current method. [ABSTRACT FROM AUTHOR]

This study employs evolutionary algorithms to effectively solve λ-fuzzy measures. In consideration of domain knowledge concerning λ-fuzzy measures, we develop an evolutionary algorithm by synthesizing important features of genetic algorithms and evolution strategies. Our proposed method includes selection, recombination and mutation acting on real-valued encodings that are evaluated for fitness. To make a legitimate inference in reliability and validity of the proposed method, 225 cases are generated through experimental design to cover the possible instances of the identification problem for λ-fuzzy measures. Then, we conduct an experimental analysis of solving the 225 cases by the proposed evolutionary algorithm. In each experimental case, we solve the inverse problem of λ-fuzzy measures. The experimental results show desirable performance in solution quality and efficiency. Moreover, there are only a few input data required by our proposed method, and this can reduce the difficulty of data collection in practice. [ABSTRACT FROM AUTHOR]

Due to the lack of resident physicians in medical institutions, nurse practitioners must assist in clinical care. However, the quality of training courses in training hospitals is varied and, currently, there is no theory to guide nurse practitioners to complete training. To develop a theory to guide nurse practitioners to accomplish training programme. This study adopted a qualitative grounded theory approach. A regional teaching hospital in Taiwan. Seventeen nurse practitioners, who had passed the oral test within the past six months, were recruited until data saturation was achieved. Data were collected using a semi-structured interview and data were collected between January 2018 and March 2019. Data were analysed using open, axial, and selective coding and using NVivo 11 to aid the process of coding. A substantive theory was formulated to help nurse practitioners complete their training programme. The core category was 'professional ability to improve nursing quality and excel'. Other important categories and subcategories were 'improving thinking ability' (improving critical thinking ability and differential diagnosis), 'improving clinical care ability' (improving clinical assessment and overall communication skills), and 'active learning' (multi-method learning, repeated practice, and self-improvement). The findings will facilitate the provision of guidance to nurse practitioner trainees in medical institutions. This will help them successfully complete their training, improve the passing rate for nurse practitioner selection, reduce the wastage of workforce training resources, and improve the quality of care that nurse practitioners provide. Hospitals could use this theory as a reference and create a warm and supportive training environment to help nurse practitioners complete their training programme and improve care quality. [ABSTRACT FROM AUTHOR]

In this paper, we report on our investigation of human-AI collaboration for mind-mapping. We specifically focus on problem exploration in pre-conceptualization stages of early design. Our approach leverages the notion of query expansion--the process of refining a given search query for improving information retrieval. Assuming a mind-map as a network of nodes, we reformulate its construction process as a sequential interaction workflow wherein a human user and an intelligent agent take turns to add one node to the network at a time. Our contribution is the design, implementation, and evaluation of algorithm that powers the intelligent agent (IA). This paper is an extension of our prior work (Chen et al., 2019, "Mini-Map: Mixed-Initiative Mind-Mapping Via Contextual Query Expansion," AIAA Scitech 2020 Forum, p. 2347) wherein we developed this algorithm, dubbed Mini-Map, and implemented a web-based workflow enabled by ConceptNet (a large graph-based representation of "commonsense" knowledge). In this paper, we extend our prior work through a comprehensive comparison between human-AI collaboration and human-human collaboration for mind-mapping. We specifically extend our prior work by: (a) expanding on our previous quantitative analysis using established metrics and semantic studies, (b) presenting a new detailed video protocol analysis of the mind-mapping process, and (c) providing design implications for digital mind-mapping tools. [ABSTRACT FROM AUTHOR]