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P/TGMS (Photo/thermo-sensitive genic male sterile) lines are crucial resources for two-line hybrid rice breeding. Previous studies revealed that slow development is a general mechanism for sterility-fertility conversion of P/TGMS in Arabidopsis. However, the difference in P/TGMS genes between rice and Arabidopsis suggests the presence of a distinct P/TGMS mechanism in rice. In this study, we isolated a novel P/TGMS line, ostms19, which shows sterility under high-temperature conditions and fertility under low-temperature conditions. OsTMS19 encodes a novel pentatricopeptide repeat (PPR) protein essential for pollen formation, in which a point mutation GTA(Val) to GCA(Ala) leads to ostms19 P/TGMS phenotype. It is highly expressed in the tapetum and localized to mitochondria. Under high temperature or long-day photoperiod conditions, excessive ROS accumulation in ostms19 anthers during pollen mitosis disrupts gene expression and intine formation, causing male sterility. Conversely, under low temperature or short-day photoperiod conditions, ROS can be effectively scavenged in anthers, resulting in fertility restoration. This indicates that ROS homeostasis is critical for fertility conversion. This relationship between ROS homeostasis and fertility conversion has also been observed in other tested rice P/TGMS lines. Therefore, we propose that ROS homeostasis is a general mechanism for the sterility-fertility conversion of rice P/TGMS lines.

This study examines the impact of regulatory frameworks on the firm value of cross-listed companies in Hong Kong and Mainland China, employing Institutional and Agency theories as analytical lenses. The research primarily utilizes quantitative methodologies, analysing secondary data sourced from financial databases and regulatory bodies. Key findings indicate that stringent regulatory compliance in Hong Kong correlates with higher firm values compared to Mainland China. Effective enforcement of regulations in Hong Kong also reduces information asymmetry, thereby increasing firm value. Conversely, regulatory discrepancies between the two regions increase perceived investment risks, negatively impacting firm value. These results underscore the importance of robust, consistent regulatory practices in enhancing corporate legitimacy and investor confidence. The study acknowledges limitations related to the reliance on secondary data and the dynamic nature of regulatory frameworks, which may affect the timeliness and applicability of the findings across different regions. Future research directions include conducting longitudinal studies to assess the temporal effects of regulatory changes, incorporating qualitative analyses to deepen understanding of corporate responses to regulatory environments, and expanding the geographical scope to include comparisons with other global markets. This research contributes to the existing literature by highlighting how regulatory alignment and enforcement influence the economic valuation of cross-listed firms, providing valuable insights for regulators and corporate managers aiming to optimize firm value in complex regulatory landscapes.

Polysaccharides are biomacromolecular widely applied in the food industry, as gelling agents, thickeners and health supplements. As hydrophobic groups, acetyls provide amphiphilicity to polysaccharides with numerous hydroxyl groups, which greatly expand the presence of polysaccharides in organic organisms and various chemical environments. Acetylation could result in diverseness and promotion of the structure of polysaccharides, which improve the physicochemical properties and biological activities. High efficient and environmentally friendly access to acetylated derivatives of different polysaccharides is being explored. This review discusses and summarizes acetylated polysaccharides in terms of synthetic methods, physicochemical properties and biological activities and emphasizes the structure-effect relationships introduced by acetyl groups to reveal the potential mechanism of acetylated polysaccharides. Acetyls with different contents and substitution sites could change the molecular weight, monosaccharide composition and spatial architecture of polysaccharides, resulting in differences among properties such as water solubility, emulsification and crystallinity. Coupled with acetyls, polysaccharides have increased antioxidant, immunomodulatory, antitumor, and pro-prebiotic capacities. In addition, their possible applications have also been discussed in green food materials, bioactive ingredient carriers and functional food products, indicating that acetylated polysaccharides hold a clear vision in food health and industrial development.

Implementation of fluorine-free electrolytes that are safer and more sustainable than the state-of-the-art highly fluorinated electrolytes requires a thorough understanding of the interphase formation process. This work investigates the effects of LiPF6- and lithium bis(oxalato)borate (LiBOB)-based electrolytes on the electrochemical performance and surface chemistry of graphite, silicon, and silicon-graphite composite electrodes. The LiBOB-based electrolyte degrades more with the presence of silicon in the electrode, and tends to form a thicker solid electrolyte interphase (SEI) layer compared to the LiPF6-based electrolyte. Different degradation distributions were also found in the graphite-silicon composite electrode: The LiPF6 degradation products tend to form on silicon, while the LiBOB degradation products preferentially form on carbon species. These results provide insights into the relationship between electrolytes and electrodes in terms of electrochemical performance, as well as SEI composition and morphology.

Ning Luo,1,* Yi-Chen Zeng,1,* Bai-Tian Fu,1 Je Wie Low,2 Jian-Qiao Fang1 1The Third Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China; 2Institute of International Education of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jian-Qiao Fang, The Third Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China, Email fangjianqiao7532@163.comIntroduction: Diabetic peripheral neuropathy (DPN) affects patients’ quality of life significantly. To date, selecting the appropriate treatment remains challenging. While electroacupuncture (EA) has shown promise as an effective adjunct therapy for DPN, and infrared thermography (IRT) has been considered as a potential predictor of treatment efficacy, the evidence for both remains inconclusive. As such, the objectives of this trial are twofold: to ascertain the efficacy of EA for DPN, and to explore the feasibility of IRT as an adjunctive objective tool for efficacy assessment.Methods: The study was designed as a randomized, parallel, controlled trial. It spanned over 6 weeks of treatment and an additional 4 weeks of follow-up. 104 eligible participants will be stratified for severity of disease: mild with Toronto clinical scoring system(TCSS) score 6– 8, moderate (TCSS score 9– 11), and severe (TCSS score 12– 19), and each level will be randomised in a 1:1 ratio into a EA group and waiting-list group. The waiting-list group received only the current conventional medication, while the EA group received an additional 12 EA sessions on top of the conventional medication. The primary outcome indicators is nerve conduction velocity (NCV), which will be tested at the baseline and week 6. Total clinical efficiency, TCSS, Clinical symptoms score of Traditional Chinese Medicine (TCM), Patient

In heterogeneous catalysis the surface-adsorbate bond strength is critical for the function of the system. Here we study a series consisting of multilayer, bilayer and monolayer N2O on Ni(111) and employ Auger-photoelectron coincidence spectroscopy (APECS) to study the interaction between the molecule and the substrate directly. We observe intensity in the nitrogen Auger spectra that arise from the interaction between molecule and surface (not observed in free molecules) whereas the oxygen spectra are thickness-independent. Since the two nitrogen atoms of N2O are chemically inequivalent we can assign the intensity present in the bilayer and monolayer cases to orbitals centered on the terminal nitrogen which is closest to the Ni(111) surface. Using ab initio, molecular dynamics and solid-state density functional theory calculations we infer a Blyholder model of the surface bond as consisting of donation from the terminal nitrogen lone-pair valence orbital with back-donation from the metal into the unoccupied orbitals on that nitrogen. This coincidence technique can readily be used to study substrate–adsorbate interactions directly with chemical and orbital specificity — this opens up prospects to study fundamental steps of molecular adsorption and heterogeneous catalysis with unprecedented detail.

Innovations in resistive switching devices constitute a core objective for the development of ultralow-power computing devices. Forming-free resistive switching is a type of resistive switching that eliminates the need for an initial high voltage for the formation of conductive filaments and offers promising opportunities to overcome the limitations of traditional resistive switching devices. Here, we demonstrate mixed charge state oxygen vacancy-engineered electroforming-free resistive switching in NiFe2O4 (NFO) thin films, fabricated as asymmetric Ti/NFO/Pt heterostructures, for the first time. Using pulsed laser deposition in a controlled oxygen atmosphere, we tune the oxygen vacancies together with the cationic valence state in the nickel ferrite phase, with the latter directly affecting the charge state of the oxygen vacancies. The structural integrity and chemical composition of the films are confirmed by X-ray diffraction and hard X-ray photoelectron spectroscopy, respectively. Electrical transport studies reveal that resistive switching characteristics in the films can be significantly altered by tuning the amount and charge state of the oxygen vacancy concentration during the deposition of the films. The resistive switching mechanism is seen to depend upon the migration of both singly and doubly charged oxygen vacancies formed as a result of changes in the nickel valence state and the consequent formation/rupture of conducting filaments in the switching layer. This is supported by the existence of an optimum oxygen vacancy concentration for efficient low-voltage resistive switching, below or above which the switching process is inhibited. Along with the filamentary switching mechanism, the Ti top electrode also enhances the resistive switching performance due to interfacial effects. Time-resolved measurements on the devices display both long- and short-term potentiation in the optimized vacancy-engineered NFO resistive switches, ideal for solid-state synaps

A limiting factor for solid polymer electrolyte (SPE)-based Li-batteries is the functionality of the electrolyte decomposition layer that is spontaneously formed at the Li metal anode. A deeper understanding of this layer will facilitate its improvement. This study investigates three SPEs – polyethylene oxide:lithium tetrafluoroborate (PEO:LiBF4), polyethylene oxide:lithium bis(oxalate)borate (PEO:LiBOB), and polyethylene oxide:lithium difluoro(oxalato)borate (PEO:LiDFOB) – using a combination of electrochemical impedance spectroscopy (EIS), galvanostatic cycling, in situ Li deposition photoelectron spectroscopy (PES), and ab initio molecular dynamics (AIMD) simulations. Through this combination, the cell performance of PEO:LiDFOB can be connected to the initial SPE decomposition at the anode interface. It is found that PEO:LiDFOB had the highest capacity retention, which is correlated to having the least decomposition at the interface. This indicates that the lower SPE decomposition at the interface still creates a more effective decomposition layer, which is capable of preventing further electrolyte decomposition. Moreover, the PES results indicate formation of polyethylene in the SEI in cells based on PEO electrolytes. This is supported by AIMD that shows a polyethylene formation pathway through free-radical polymerization of ethylene.

Engineering human enzymes for therapeutic applications is attractive but introducing new amino acids may adversely affect enzyme stability and immunogenicity. Here we used a mammalian membrane-tethered screening system (ECSTASY) to evolve human lysosomal beta-glucuronidase (hBG) to hydrolyze a glucuronide metabolite (SN-38G) of the anticancer drug irinotecan (CPT-11). Three human beta-glucuronidase variants (hBG3, hBG10 and hBG19) with 3, 10 and 19 amino acid substitutions were identified that display up to 40-fold enhanced enzymatic activity, higher stability than E. coli beta-glucuronidase in human serum, and similar pharmacokinetics in mice as wild-type hBG. The hBG variants were two to three orders of magnitude less immunogenic than E. coli beta-glucuronidase in hBG transgenic mice. Intravenous administration of an immunoenzyme (hcc49-hBG10) targeting a sialyl-Tn tumor-associated antigen to mice bearing human colon xenografts significantly enhanced the anticancer activity of CPT-11 as measured by tumor suppression and mouse survival. Our results suggest that genetically-modified human enzymes represent a good alternative to microbially-derived enzymes for therapeutic applications.

Jui-Jen Chang,1,2,* Yi-Chen Wang,3,4,* Shu-Hui Yang,5,6 Ju-Yu Wu,7 Ming-Wei Chang,8 Hui-Min David Wang5,9– 11 1Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40447, Taiwan; 2Graduate Institute of Integrated Medicine, China Medical University, Taichung, 40447, Taiwan; 3Division of Cardiology, Department of Internal Medicine, Kaohsiung Armed Forces General Hospital, Kaohsiung City, 802, Taiwan; 4Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung, 807, Taiwan; 5Graduate Institute of Biomedical Engineering, National Chung Hsing University, Taichung, 402, Taiwan; 6Bachelor Program of Biotechnology, National Chung Hsing University, Taichung, 402, Taiwan; 7Doctoral Program in Tissue Engineering and Regenerative Medicine, National Chung Hsing University, Taichung, 402, Taiwan; 8Nanotechnology and Integrated Bioengineering Centre, University of Ulster, Belfast, BT15 1AB, Northern Ireland, UK; 9Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; 10Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung, 404, Taiwan; 11Center of Applied Nanomedicine, National Cheng Kung University, Tainan, 701, Taiwan*These authors contributed equally to this workCorrespondence: Hui-Min David Wang, Graduate Institute of Biomedical Engineering, National Chung Hsing University, No. 145, Xingda Road, South Dist, Taichung City, 402, Taiwan, Tel +886-4-22840733#651 ; +886-935753718, Email davidw@dragon.nchu.edu.twBackground: Recently, the use of the tumor or its secretions as drug carriers has gradually become popular, with the advantages of high biocompatibility and enhanced drug delivery to specific cells. Melanoma is the most malignant tumor of all skin cancers; it is the most metastatic and, therefore, the most difficult to treat. The main purpose of this study is to develop na

Hsin-Ying Lin,1 Chung-Han Ho,2,3 Yu-Shiuan Lin,1 Shu-Chun Kuo,1,4 Yi-Chen Chen,2 Yung-Jen Cheng5 1Department of Ophthalmology, Chi Mei Medical Center, Tainan, Taiwan; 2Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan; 3Department of Information Management, Southern Taiwan University of Science and Technology, Tainan, Taiwan; 4Department of Optometry, Chung Hwa University of Medical Technology, Tainan, Taiwan; 5Department of Radiation Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, TaiwanCorrespondence: Yung-Jen Cheng, Department of Radiation Oncology, National Cheng Kung University Hospital, No. 138, Sheng Li Road, Tainan, 704, Taiwan, Email n052337@mail.hosp.ncku.edu.twPurpose: Continuous advancements in medical diagnostic technology and the growing availability of resources suggest a potential for fluctuations in the incidence rate of retinoblastoma (Rb). This study aimed to analyze incidence data of Rb patients in Taiwan from 1999 to 2018, utilizing the nationwide Taiwan Cancer Registry (TCR) database. Additionally, we investigated the treatment modalities used for these Rb patients and compared them with those observed in other countries.Patients and Methods: We conducted a retrospective cohort study utilizing data from the TCR database. The study cohort comprised individuals who were newly diagnosed with Rb between 1999 and 2018. The incidence of Rb was calculated as the number of patients with Rb per million live births, both for the entire population and for different gender groups and time periods. The trends in Rb incidence from 1999 to 2018 across various age groups and sexes were presented with the linear trend test.Results: From 1999 to 2018, a total of 248 cases of Rb were identified. The overall incidence rate over this 20-year period was 60.20 cases per million live births, corresponding to 1 case per 16,611 live births. Incidence rates for each 5-year period between

Flow-based super-resolution (SR) models have demonstrated astonishing capabilities in generating high-quality images. However, these methods encounter several challenges during image generation, such as grid artifacts, exploding inverses, and suboptimal results due to a fixed sampling temperature. To overcome these issues, this work introduces a conditional learned prior to the inference phase of a flow-based SR model. This prior is a latent code predicted by our proposed latent module conditioned on the low-resolution image, which is then transformed by the flow model into an SR image. Our framework is designed to seamlessly integrate with any contemporary flow-based SR model without modifying its architecture or pre-trained weights. We evaluate the effectiveness of our proposed framework through extensive experiments and ablation analyses. The proposed framework successfully addresses all the inherent issues in flow-based SR models and enhances their performance in various SR scenarios. Our code is available at: https://github.com/liyuantsao/BFSR, Comment: Accepted to CVPR2024

Offline meta-reinforcement learning (OMRL) proficiently allows an agent to tackle novel tasks while solely relying on a static dataset. For precise and efficient task identification, existing OMRL research suggests learning separate task representations that be incorporated with policy input, thus forming a context-based meta-policy. A major approach to train task representations is to adopt contrastive learning using multi-task offline data. The dataset typically encompasses interactions from various policies (i.e., the behavior policies), thus providing a plethora of contextual information regarding different tasks. Nonetheless, amassing data from a substantial number of policies is not only impractical but also often unattainable in realistic settings. Instead, we resort to a more constrained yet practical scenario, where multi-task data collection occurs with a limited number of policies. We observed that learned task representations from previous OMRL methods tend to correlate spuriously with the behavior policy instead of reflecting the essential characteristics of the task, resulting in unfavorable out-of-distribution generalization. To alleviate this issue, we introduce a novel algorithm to disentangle the impact of behavior policy from task representation learning through a process called adversarial data augmentation. Specifically, the objective of adversarial data augmentation is not merely to generate data analogous to offline data distribution; instead, it aims to create adversarial examples designed to confound learned task representations and lead to incorrect task identification. Our experiments show that learning from such adversarial samples significantly enhances the robustness and effectiveness of the task identification process and realizes satisfactory out-of-distribution generalization.

Developing policies that can adjust to non-stationary environments is essential for real-world reinforcement learning applications. However, learning such adaptable policies in offline settings, with only a limited set of pre-collected trajectories, presents significant challenges. A key difficulty arises because the limited offline data makes it hard for the context encoder to differentiate between changes in the environment dynamics and shifts in the behavior policy, often leading to context misassociations. To address this issue, we introduce a novel approach called Debiased Offline Representation for fast online Adaptation (DORA). DORA incorporates an information bottleneck principle that maximizes mutual information between the dynamics encoding and the environmental data, while minimizing mutual information between the dynamics encoding and the actions of the behavior policy. We present a practical implementation of DORA, leveraging tractable bounds of the information bottleneck principle. Our experimental evaluation across six benchmark MuJoCo tasks with variable parameters demonstrates that DORA not only achieves a more precise dynamics encoding but also significantly outperforms existing baselines in terms of performance.

Large language models (LLMs) have catalyzed a paradigm shift in natural language processing, yet their limited controllability poses a significant challenge for downstream applications. We aim to address this by drawing inspiration from the neural mechanisms of the human brain, specifically Broca's and Wernicke's areas, which are crucial for language generation and comprehension, respectively. In particular, Broca's area receives cognitive decision signals from Wernicke's area, treating the language generation as an intricate decision-making process, which differs from the fully auto-regressive language generation of existing LLMs. In a similar vein, our proposed system, the BWArea model, conceptualizes language generation as a decision-making task. This model has three components: a language world model, an inverse dynamics model, and a cognitive policy. Like Wernicke's area, the inverse dynamics model is designed to deduce the underlying cognitive intentions, or latent actions, behind each token. The BWArea model is amenable to both pre-training and fine-tuning like existing LLMs. With 30B clean pre-training tokens, we have trained a BWArea model, which achieves competitive performance with LLMs of equal size (1B parameters). Unlike fully auto-regressive LLMs, its pre-training performance does not degenerate if dirty data unintentionally appears. This shows the advantage of a decomposed structure of BWArea model in reducing efforts in laborious data selection and labeling. Finally, we reveal that the BWArea model offers enhanced controllability via fine-tuning the cognitive policy with downstream reward metrics, thereby facilitating alignment with greater simplicity. On 9 out of 10 tasks from two suites, TextWorld and BigBench Hard, our method shows superior performance to auto-regressive LLMs.

Model-based methods in reinforcement learning offer a promising approach to enhance data efficiency by facilitating policy exploration within a dynamics model. However, accurately predicting sequential steps in the dynamics model remains a challenge due to the bootstrapping prediction, which attributes the next state to the prediction of the current state. This leads to accumulated errors during model roll-out. In this paper, we propose the Any-step Dynamics Model (ADM) to mitigate the compounding error by reducing bootstrapping prediction to direct prediction. ADM allows for the use of variable-length plans as inputs for predicting future states without frequent bootstrapping. We design two algorithms, ADMPO-ON and ADMPO-OFF, which apply ADM in online and offline model-based frameworks, respectively. In the online setting, ADMPO-ON demonstrates improved sample efficiency compared to previous state-of-the-art methods. In the offline setting, ADMPO-OFF not only demonstrates superior performance compared to recent state-of-the-art offline approaches but also offers better quantification of model uncertainty using only a single ADM.

College completion, earning a degree or certificate, is considered to be a key college success outcome, supported by every educational policymaker. Yet, institutions and policymakers in the U.S. know surprisingly little about the rates of completion for students who follow all but the most traditional of postsecondary pathways. This is because traditional graduation rate calculations are institution based and only count students who finish at the same institution where they started. Building on findings from previous reports in the National Student Clearinghouse Research Center's "Signature Report" series, this new report measures this key college success outcome--rates of first completion--encompassing postsecondary credentials of all levels and types at any institution in any state, whether it is the first, second, third, or more, attended. This report draws on the Clearinghouse database's near-census national coverage of enrollments and awarded degrees to explore the six-year outcomes of a cohort of first-time-in-college degree-seeking students who started in fall 2006 (N=1,878,484). It enhances the traditional graduation rate by reporting in four key ways: (1) Student completion anywhere, beyond institutional boundaries, across state lines, and over time; (2) Persistence anywhere, not just at the starting institution, for those who have not yet completed but are still pursuing a degree; (3) College outcomes broken out by student age at first entry and enrollment intensity, thus addressing questions about the role of students' varied postsecondary pathways in progress toward national completion goals; and (4) Enrollment intensity based on the enrollment status in all terms of enrollment, and not just the first term. Specifically, this report examines: (1) Six-year college outcomes, including the first instance of degree or certificate completion (first completion), persistence, and stop-out. Outcomes are broken out by students' age at first entry, students' enrollment intensity, enrollment intensity within each age group, and type of starting institution; (2) Six-year college outcomes for students who started at four-year public institutions, at two-year public institutions, at four-year private nonprofit institutions, and at four-year private for-profit institutions; and (3) Patterns of completion across state lines, broken out by students' enrollment intensity, students' age at first entry, and enrollment intensity within each age group. The findings presented in this report show that within six years, 12.1 percent of first-time-in-college degree-seeking students who enrolled in fall 2006 completed a degree or certificate at an institution other than their starting institution, raising the overall completion rate from 42.0 percent to 54.1 percent. Mixed enrollment students completed at an institution other than their starting institution at a higher rate (14.6 percent) than exclusively full-time (10.6 percent) and exclusively part-time (3.1 percent) students. Appended are: (1) Methodological Notes; (2) Coverage Tables; and (3) Results Tables. (Contains 29 figures, 34 tables, and 5 footnotes.)

Colorectal cancer is among the most common cancers worldwide and a frequent cause of cancer related deaths. Oxaliplatin is the first line chemotherapeutics for treatment, but the development of resistance leads to recurrence of oxaliplatin insensitive tumors. To understand possible mechanisms of drug tolerance we developed oxaliplatin resistant derivatives (OR-LoVo) of the established LoVo cell line originally isolated from a metastatic colon adenocarcinoma. We compared the microRNA (miRNA) expression profile of the cell pair and found expression of miR-29a-3p significantly increased in OR-LoVo cells compared to parent cells. In addition, miR-29a-3p was significantly elevated in tumor tissue when compared to matched surrounding tissue in human, suggesting potential clinical importance. Ectopic miR-29-a-3p expression induced chemoresistance in a number of different cancer cell lines as well as colorectal tumors in mice. We further demonstrated that miR-29-a-3p downregulates expression of the ubiquitin ligase component FEM1B and that reduction of Fem1b levels is sufficient to confer oxaliplatin resistance. FEM1B targets the glioma associated oncogene Gli1 for degradation, suggesting that increased Gli1 levels could contribute to oxaliplatin tolerance. Accordingly, knockdown of GLI1 reverted chemoresistance of OR-LoVo cells. Mechanistically, resistant cells experienced significantly lower DNA damage upon oxaliplatin treatment, which can be partially explained by reduced oxaliplatin uptake and enhanced repair. These results suggest that miR-29-a-3p overexpression induces oxaliplatin resistance through misregulation of Fem1B and Gli1 levels. TCGA analyses provides strong evidence that the reported findings regarding induced drug tolerance by the miR-29a/Fem1B axis is clinically relevant. The reported findings can help to predict oxaliplatin sensitivity and resistance of colorectal tumors.

The conductivity of organic polymer heterojunction devices relies on the electron dynamics occurring along interfaces between the acceptor and donor moieties. To investigate these dynamics with chemical specificity, spectroscopic techniques are employed to obtain localized snapshots of the electron behavior at selected interfaces. In this study, charge transfer in blends (by weight 10, 50, 90, and 100%) of p-type polymer P(g(4)2T-T) (bithiophene-thiophene) and n-type polymer BBL (poly(benzimidazo-benzo-phenanthroline)) was measured by resonant Auger spectroscopy. Electron spectra emanating from the decay of core-excited states created upon X-ray absorption in the donor polymer P(g(4)2T-T) were measured in the sulfur KL2,3L2,3 Auger kinetic energy region as a function of the excitation energy. By tuning the photon energy across the sulfur K-absorption edge, it is possible to differentiate between decay paths in which the core-excited electron remained on the atom with the core-hole and those where it tunneled away. Analyzing the competing decay modes of these localized and delocalized (charge-transfer) processes facilitated the computation of charge-transfer times as a function of excitation energy using the core-hole clock method. The electron delocalization times derived from the measurements were found to be in the as/fs regime for all polymer blends, with the fastest charge transfer occurring in the sample with an equal amount of donor and acceptor polymer. These findings highlight the significance of core-hole clock spectroscopy as a chemically specific tool for examining the local charge tunneling propensity, which is fundamental to understanding macroscopic conductivity. Additionally, the X-ray absorption spectra near the sulfur K-edge in the P(g(4)2T-T) polymer for different polymer blends were analyzed to compare molecular structure, orientation, and ordering in the polymer heterojunctions. The 50% donor sample exhibited the most pronounced angular dependenc, QC 20240201

Crop varieties differing in architectural characteristics (AC) vary in their intra-canopy light distribution. To optimize canopy photosynthesis, we hypothesize that varieties with contrasting AC possess different photosynthetic acclimation strategy (PAS) with respect to photosynthetic nitrogen (Np) partitioning. We firstly used in silico experiments to test this hypothesis and suggested a trade-off in Np partitioning between carboxylation and light harvesting to achieve optimal coordination between PAS, AC and growing light environment. Then, two cucumber (Cucumis sativus L.) cultivars, Aramon and SC-50, which were bred under greenhouse vertical single-stem and field creeping multi-branch canopy, were selected for studying their differences in AC and PAS using greenhouse and growth chamber experiments, respectively. In the greenhouse, more horizontal leaves of SC-50 resulted in steeper intra-canopy light gradient and a higher degree of self-shading, especially in the upper canopy layer. In growth chamber experiments, Aramon invested more leaf nitrogen into photosynthesis than SC-50, and the proportion (pNp) increased as light was reduced. In contrast, pNp of SC-50 did not respond to light but SC-50 partitioned its limited Np between carboxylation and light harvesting functions more effectively, showing a strategy particularly advantageous for canopies with a high degree of self-shading. This is further confirmed by additional in silico experiments showing that Np partitioning of SC-50 coped better with the impact of strong light competition caused by low light and by leaf clumping under high planting density. These findings provide a comprehensive perspective of genotypic variation in PAS, canopy architectures and their optimal coordination., Peer Reviewed

Soybean [Glycine max(L.) Merr.] is a globally important crop due to its valuable seed composition, versatile feed, food, and industrial end-uses, and consistent genetic gain. Successful genetic gain in soybean has led to widespread adaptation and increased value for producers, processors, and consumers. Specific focus on the nutritional quality of soybean seed composition for food and feed has further elucidated genetic knowledge and bolstered breeding progress. Seed components are historical and current targets for soybean breeders seeking to improve nutritional quality of soybean. This article reviews genetic and genomic foundations for improvement of nutritionally important traits, such as protein and amino acids, oil and fatty acids, carbohydrates, and specific food-grade considerations; discusses the application of advanced breeding technology such as CRISPR/Cas9 in creating seed composition variations; and provides future directions and breeding recommendations regarding soybean seed composition traits.

Aim: This Study examines the influence of the American ESL Teacher Education Training Program on the qualifications of Chinese language educators. Due to the growing demand for English language teaching, there is an urgent need in China for trained and skilled second language teachers. Specialized training in pedagogical abilities, language proficiency, cultural awareness, and professional growth is available through the American ESL Teacher Education Training Program. Methodology: The impact of the American ESL Teacher Education Training Program on the qualifications of second language instructors in China was investigated using a systematic review methodology. Results: It is well known for its comprehensive strategy for teacher development. Conclusions: This publication examines how this training program has raised the bar for second-language teachers in China. Originality/Value: This study was conducted during teachers' education training. There is an urgent need for trained and skilled second language teachers in China due to the growing demand for English language education. Specialized training in educational skills, language skills, cultural awareness, and professional development is available through the American ESL Teacher Education Training Program.

Aim: This study aimed to investigate and evaluate the questioning strategies used in the classroom by middle school instructors. "What is the impact of dialogue-based questioning methods on middle school students' learning outcomes?" was the research question for the study. Methodology: A methodical search technique was used to find pertinent peer-reviewed papers written in English in order to meet the research objective. Key information regarding the different types of questioning techniques, impact on student engagement, improvement of critical thinking skills, student learning outcomes, teacher-student interaction, professional development, and teacher preparation was extracted from the studies that were chosen and synthesized. Results and conclusions: Results indicated that dialogue-based questioning techniques, such as open-ended inquiries, incisive inquiries, and Socratic inquiries, are successful in encouraging fruitful discussion, student participation, and the development of critical thinking abilities. Recommendations: Teachers should give priority to integrating different questioning strategies in order to promote discussion, stimulate active student participation, and improve critical thinking abilities. Practical Implications: The use of dialogue-based questioning techniques to improve student engagement, critical thinking, and learning outcomes, supported by efficient professional development programs, is one practical use.

Jian-Jun Xi,1,* Yu Cao,1,* Ruo-Yu He,1 Jian-Kang Zhang,2 Yan-Mei Zhao,1 Qiao Tong,1 Jian-Feng Bao,1 Yi-Chen Dong,3 Rang-Xiao Zhuang,1 Jin-Song Huang,1 Yongping Chen,4 Shou-Rong Liu1 1Department of Pharmacy, Hangzhou Xixi Hospital Affiliated to Zhejiang University School of Medicine, Hangzhou, People’s Republic of China; 2School of Medicine, Zhejiang University City College, Hangzhou, People’s Republic of China; 3Faculty of Chinese Medicine, Macau University of Science and Technology, Macau, People’s Republic of China; 4Department of Infectious Diseases, The First Affiliated Hospital of Wenzhou Medical University, Hepatology Institute of Wenzhou Medical University, Wenzhou Key Laboratory of Hepatology, Wenzou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yongping Chen, Department of Infectious Diseases, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou Key Laboratory of Hepatology, Hepatology Institute of Wenzhou Medical University, Wenzhou, Zhejiang Province, 325025, People’s Republic of China, Email 13505777281@163.com Shou-Rong Liu, Department of Infectious Diseases, Hangzhou Xixi Hospital Affiliated to Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310023, People’s Republic of China, Email lsr85463990@126.comObjective: Silibinin, a natural product extracted from the seeds of the Silybum marianum, is versatile with various pharmacological effects. However, its clinical application was strongly hampered by its low bioavailability and poor water solubility. Herein, a series of glycosylated silibinin derivatives were identified as novel anti-tumor agents.Materials and Methods: The cell viability was evaluated by CCK8 assay. Furthermore, cell apoptosis and cell cycle progression were tested by flow cytometry. In addition, the pharmacokinetic assessment of compound 15 and silibinin through intravenous administration (i.v., 2 mg/kg) to ICR mice were

Sheng-Te Hung,1 Yi-Chen Cheng,2 Chieh-Chen Wu,2 Chun-Hsien Su1,2 1Graduate Institute of Sports Coaching Science, College of Kinesiology and Health, Chinese Culture University, Taipei, 111396, Taiwan; 2Department of Exercise and Health Promotion, College of Kinesiology and Health, Chinese Culture University, Taipei, 111396, TaiwanCorrespondence: Chun-Hsien Su, Department of Exercise and Health Promotion, College of Kinesiology and Health, Chinese Culture University, 55, Hwa-Kang Road, Shilin Distract, Taipei City, 111396, Taiwan, Tel +886-2-28610511 ext.45001, Fax +886-2-28617084, Email chsu@ulive.pccu.edu.twAbstract: This review examines the impact of physical activity, nutrition, and sleep evaluations on the physical wellness (PW) and overall well-being of older individuals. A comprehensive search was conducted in databases like PubMed, Google Scholar, and EBSCO Information Services. The search spanned from January 2000 to December 2022, resulting in 19,400 articles, out of which 98 review articles met the inclusion criteria. Through the analysis of these articles, key characteristics of the literature were summarized, and opportunities to enhance the practical application of physical activity (PA), nutrition, and sleep evaluations in the daily lives of older persons were identified. Regular physical activity is crucial for older persons to maintain their physical, mental, and emotional well-being and prevent age-related health issues. Older persons have specific nutritional needs, including increased protein, vitamin D, calcium, and vitamin B12 intake. Poor sleep quality in older persons is associated with negative health outcomes such as cognitive decline, physical disability, and mortality. This review emphasizes the significance of considering physical wellness as a fundamental element for achieving holistic well-being in older persons and highlights the importance of physical activity, nutrition, and sleep evaluations in improving their overall health and well

'S17-2243C' (Reg. no. CV-557, PI 700003) is a semi-determinate, maturity group IV (relative maturity 4.9), non-genetically modified (non-GM) soybean [Glycine max (L.) Merr.] cultivar developed and released by the University of Missouri-Fisher Delta Research, Extension, and Education Center. S17-2243C was developed to meet the growing demands for new non-GM soybean cultivars with high yield and elevated seed oil content. S17-2243C is resistant to stem canker and charcoal rot and has tolerance to salinity conditions. Seed of S17-2243C has averaged 232 g kg(-1) of oil concentration on a dry weight basis, which was significantly higher than all check cultivars in the 2020 USDA Uniform Soybean Tests, Southern States. S17-2243C was tested against high-yielding private and public soybean cultivars from 2018 to 2021 in 80 locations across 12 states, including Alabama, Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Ohio, South Carolina, Tennessee, and Virginia. With high yield potential, broad adaptability, early maturity, elevated seed oil content, and non-GM traits, S17-2243C is an excellent cultivar choice for soybean growers adopting alternative growing systems and benefiting from premium prices offered for non-GM soybean products.

Flow-based methods have demonstrated promising results in addressing the ill-posed nature of super-resolution (SR) by learning the distribution of high-resolution (HR) images with the normalizing flow. However, these methods can only perform a predefined fixed-scale SR, limiting their potential in real-world applications. Meanwhile, arbitrary-scale SR has gained more attention and achieved great progress. Nonetheless, previous arbitrary-scale SR methods ignore the ill-posed problem and train the model with per-pixel L1 loss, leading to blurry SR outputs. In this work, we propose "Local Implicit Normalizing Flow" (LINF) as a unified solution to the above problems. LINF models the distribution of texture details under different scaling factors with normalizing flow. Thus, LINF can generate photo-realistic HR images with rich texture details in arbitrary scale factors. We evaluate LINF with extensive experiments and show that LINF achieves the state-of-the-art perceptual quality compared with prior arbitrary-scale SR methods., Comment: Accepted by CVPR 2023. Code: https://github.com/JNNNNYao/LINF

Transformers achieve promising performance in document understanding because of their high effectiveness and still suffer from quadratic computational complexity dependency on the sequence length. General efficient transformers are challenging to be directly adapted to model document. They are unable to handle the layout representation in documents, e.g. word, line and paragraph, on different granularity levels and seem hard to achieve a good trade-off between efficiency and performance. To tackle the concerns, we propose Fast-StrucTexT, an efficient multi-modal framework based on the StrucTexT algorithm with an hourglass transformer architecture, for visual document understanding. Specifically, we design a modality-guided dynamic token merging block to make the model learn multi-granularity representation and prunes redundant tokens. Additionally, we present a multi-modal interaction module called Symmetry Cross Attention (SCA) to consider multi-modal fusion and efficiently guide the token mergence. The SCA allows one modality input as query to calculate cross attention with another modality in a dual phase. Extensive experiments on FUNSD, SROIE, and CORD datasets demonstrate that our model achieves the state-of-the-art performance and almost 1.9X faster inference time than the state-of-the-art methods., Comment: IJCAI 2023

OBJECTIVES The current strategies to reconstruct lost peri-implant tissues due to the disease have been largely unpredictable. The aim of this conceptual review is to discuss relevant biological and biomechanical challenges of applying reconstructive means to treat peri-implantitis. Additionally, opportunities to improve treatment predictability are presented. MATERIAL AND METHODS A narrative review was conducted to fulfill the aim. RESULTS The four interrelated negative conditions hampering effective reconstruction are: inferior tissue perfusion, unfavorable bone topography, ineffective surface treatment, and unstable wound. First, peri-implant tissues resemble scars with reduced cellularity and vascularity, coupled with the absence of the periodontal ligament plexuses and the avascular implant and biomaterials, maintaining primary closure is a challenge, which is critical for regeneration. Second, defect morphology and bone topography surrounding implants determine the reconstructive potential. Unfortunately, noncontained defects are frequently encountered, with a combination of suprabony (horizontal bone loss) and infrabony (vertical usually involving circumferential bone loss) defects. Third, current attempts for implant surface decontamination are insufficient due to inaccessible macrostructure and rough surfaces in the micro-scale. Histologic evaluation has shown bacteria aggregation and calcified deposits around implants. Lastly, wound stability is difficult to achieve due to inherent soft tissue biomechanical quality and quantity deficiencies and mobile bone particulates. Opportunities to tackle the abovementioned challenges include the use of novel imaging technologies, such as high-frequency dental ultrasound and laser speckle imaging to evaluate tissue perfusion, soft tissue quality/quantity, and bone topography pre-surgically. The use of the operating microscope could allow better visualization and removal of etiologic factors. Strategies to improve soft

In this study, we introduce JarviX, a sophisticated data analytics framework. JarviX is designed to employ Large Language Models (LLMs) to facilitate an automated guide and execute high-precision data analyzes on tabular datasets. This framework emphasizes the significance of varying column types, capitalizing on state-of-the-art LLMs to generate concise data insight summaries, propose relevant analysis inquiries, visualize data effectively, and provide comprehensive explanations for results drawn from an extensive data analysis pipeline. Moreover, JarviX incorporates an automated machine learning (AutoML) pipeline for predictive modeling. This integration forms a comprehensive and automated optimization cycle, which proves particularly advantageous for optimizing machine configuration. The efficacy and adaptability of JarviX are substantiated through a series of practical use case studies.

This paper introduces the Cross-lingual Fact Extraction and VERification (XFEVER) dataset designed for benchmarking the fact verification models across different languages. We constructed it by translating the claim and evidence texts of the Fact Extraction and VERification (FEVER) dataset into six languages. The training and development sets were translated using machine translation, whereas the test set includes texts translated by professional translators and machine-translated texts. Using the XFEVER dataset, two cross-lingual fact verification scenarios, zero-shot learning and translate-train learning, are defined, and baseline models for each scenario are also proposed in this paper. Experimental results show that the multilingual language model can be used to build fact verification models in different languages efficiently. However, the performance varies by language and is somewhat inferior to the English case. We also found that we can effectively mitigate model miscalibration by considering the prediction similarity between the English and target languages. The XFEVER dataset, code, and model checkpoints are available at https://github.com/nii-yamagishilab/xfever., Comment: Accepted for an oral presentation at the 35th Conference on Computational Linguistics and Speech Processing (ROCLING 2023)

Imitation learning (IL) enables agents to mimic expert behaviors. Most previous IL techniques focus on precisely imitating one policy through mass demonstrations. However, in many applications, what humans require is the ability to perform various tasks directly through a few demonstrations of corresponding tasks, where the agent would meet many unexpected changes when deployed. In this scenario, the agent is expected to not only imitate the demonstration but also adapt to unforeseen environmental changes. This motivates us to propose a new topic called imitator learning (ItorL), which aims to derive an imitator module that can on-the-fly reconstruct the imitation policies based on very limited expert demonstrations for different unseen tasks, without any extra adjustment. In this work, we focus on imitator learning based on only one expert demonstration. To solve ItorL, we propose Demo-Attention Actor-Critic (DAAC), which integrates IL into a reinforcement-learning paradigm that can regularize policies' behaviors in unexpected situations. Besides, for autonomous imitation policy building, we design a demonstration-based attention architecture for imitator policy that can effectively output imitated actions by adaptively tracing the suitable states in demonstrations. We develop a new navigation benchmark and a robot environment for \topic~and show that DAAC~outperforms previous imitation methods \textit{with large margins} both on seen and unseen tasks.

While sentence simplification is an active research topic in NLP, its adjacent tasks of sentence complexification and same-level paraphrasing are not. To train models on all three tasks, we present two new unsupervised datasets. We compare these datasets, one labeled by a weak classifier and the other by a rule-based approach, with a single supervised dataset. Using these three datasets for training, we perform extensive experiments on both multitasking and prompting strategies. Compared to other systems trained on unsupervised parallel data, models trained on our weak classifier labeled dataset achieve state-of-the-art performance on the ASSET simplification benchmark. Our models also outperform previous work on sentence level targeting. Finally, we establish how a handful of Large Language Models perform on these tasks under a zero-shot setting., Comment: This arXiv version is a pre-MIT Press publication version, this paper has been accepted by TACL. 22 pages, 3 figures, 13 tables

We consider the problem of learning the best possible policy from a fixed dataset, known as offline Reinforcement Learning (RL). A common taxonomy of existing offline RL works is policy regularization, which typically constrains the learned policy by distribution or support of the behavior policy. However, distribution and support constraints are overly conservative since they both force the policy to choose similar actions as the behavior policy when considering particular states. It will limit the learned policy's performance, especially when the behavior policy is sub-optimal. In this paper, we find that regularizing the policy towards the nearest state-action pair can be more effective and thus propose Policy Regularization with Dataset Constraint (PRDC). When updating the policy in a given state, PRDC searches the entire dataset for the nearest state-action sample and then restricts the policy with the action of this sample. Unlike previous works, PRDC can guide the policy with proper behaviors from the dataset, allowing it to choose actions that do not appear in the dataset along with the given state. It is a softer constraint but still keeps enough conservatism from out-of-distribution actions. Empirical evidence and theoretical analysis show that PRDC can alleviate offline RL's fundamentally challenging value overestimation issue with a bounded performance gap. Moreover, on a set of locomotion and navigation tasks, PRDC achieves state-of-the-art performance compared with existing methods. Code is available at https://github.com/LAMDA-RL/PRDC, Comment: Accepted to ICML 2023

Despite the rise of social studies to address craft economy or production in modern society, how the value can be added to a craft-made product is poorly explained. By exploring the global context of the guitar-making industry in the 1960s and interviewing guitar makers in four different countries, in this dissertation, I argue that the rise of the craft-made guitar industry since the 1980s resulted from the invented tradition of "vintage" and the dependence on advanced technology. Additionally, by exploring various guitar builders' life stories, labor processes, and business networks, I create a concept, the ladder towards luthiers, to describe how an inexperienced apprentice may become an independent luthier in a hierarchical structure in the industry. Furthermore, I argue that the traditional definition of craft overvalues male luthiers' role in adding value to a craft-made guitar and overlooks female workers' contributions in the craft industry. In order to highlight different actors' contributions in the craft industry, we need a new definition of craft to help consumers understand that the value of a craft product is also made in a social process rather than by an independent luthier. Finally, this study also sheds light on the relationship between craft production and mass production and figures out that the rise of craft production could reflect a reskilling process of industrial capitalism rather than the opposite of the deskilled mass production.

The project is to transform Belgium National Bank into a working environment capable of accommodating diverse activities. Given its economic capacity and social responsibility, the bank also has a public attribute that allows it to accommodate specific public events. propose to open part of the bank's space as a financial culture center, mainly an exhibition and library related to financial themes. Since the bank is located on the border of the upper and lower town of Brussels, the financial culture center also undertakes the task of connecting the site with an 8 meters height difference. So I created a new public landscape circulation through ramps and three staircases, inviting people to enter the bank to experience the newly inserted public facilities and the existing delicate bank building. For the office space above the first floor, the existing atrium is very barren and unused. So I propose to put balconies with plants in the atrium to make them like hanging gardens. Employees can relax or chat on the balcony, providing an opportunity to relax from a busy work schedule., Architecture, Urbanism and Building Sciences | Interiors Buildings Cities

The perennial model species Arabis alpina exhibits various flowering behaviour amongst natural populations that range geographically from northern Spain to Norway. The Spanish population has previously been studied and the floral induction can only occur in response to winter cold (vernalization). However, the Norwegian population exhibits flowering behaviours that are not present in the Spanish population. In the absence of vernalization, the Norwegian population exhibits early- and late-flowering phenotypes, which are not due to variation in the timing of floral induction, but to differences in bud outgrowth. In the presence of vernalization, the flowering mechanisms of the early- and late-flowering accessions still differed. In the growth chamber, the activity of axillary meristems within the V1 zone is unique to the early-flowering. Genome-wide co-expression network analysis revealed that the majority of floral repressor genes in the early-flowering accession belonged to a single cluster, whereas in the late-flowering accession, these floral repressors were split between multiple clusters that showed similar qualitative expression patterns but asynchronous. The genetic basis of the variation in bud outgrowth was narrowed down to 759 Kb by analysing near-isogenic lines in the late-flowering genetic background that carried early flowering alleles on chromosome 8 that conferred early flowering. An in situ transplantation experiment in the natural environment also revealed that the early-flowering accession invests resources into growing numerous rosettes, ensuring that sufficient rosettes flower the subsequent year, whereas the late-flowering accession invests resources into producing a greater number of flowers, leading to more siliques, maximising offspring production. Taken together, the four research approaches in this study have facilitated a better understanding of the variation in the flowering behaviour within the Norwegian Riasten A. alpina population.

Just Transitions to Decarbonisation in the Asia-Pacific

Meng-Meng Zheng,1,* Ming-Xing Guo,2,* Li-Min Shang,1,* Jian Zhang,1 Jun Lin,1 Ye Tian,1 Xiang-Li Cui,2,* Yi-Chen Zhu1,* 1Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Pharmacy, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiang-Li Cui, Department of Pharmacy, Beijing Friendship Hospital, Capital Medical University, No. 95 Yong’an Road, Xicheng District, Beijing, 100050, People’s Republic of China, Email xianglicui@ccmu.edu.cn Yi-Chen Zhu, Department of Urology, Capital Medical University, Beijing Friendship Hospital, No. 95 Yong’an Road, Xicheng District, Beijing, 100050, People’s Republic of China, Email zhuyc@ccmu.edu.cnBackground: Carbapenem-resistant Klebsiella pneumoniae (CRKP) infection has proven to be difficult to control and typically presents with devastating effects.Methods: This retrospective study was conducted on the renal recipients at our institution between January 2021 to January 2022. Clinical data was collected to identify factors associated with CRKP infection and clinical outcomes.Results: There were 104 cases out of 186 total renal recipients who presented with at least one infection within 3 months after KT, and 14 cases developed unfavorable clinical outcomes. We identified 16 confirmed CRKP infected cases with the incidence of 8.60%. Possible donor derived infection (DDI) (OR = 6.743; 95% CI: 1.477– 30.786; P = 0.014) were independent risk factors for the occurrence of CRKP infection of renal recipients in our analysis, CRKP infection (OR = 20.723; 95% CI: 3.448– 124.547; P = 0.001) and pneumonia (OR = 28.458; 95% CI: 1.956– 413.984 P = 0.014) were independent risk factors for the occurrence of unfavorable clinical outcomes following KT, and the occurrence of unfavorable clinical out

Meng-meng Zheng,* Li-min Shang,* Chun-kai Du,* Lei Zhang, Wen Sun, Zhi-peng Wang, Yi-chen Zhu, Ye Tian Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yi-chen Zhu; Ye Tian, Department of Urology, Capital Medical University, Beijing Friendship Hospital, No. 95 Yong’an Road, Xicheng District, Beijing, 100050, People’s Republic of China, Email zhuyc82@sina.com; tianye166@126.comBackground: Potent immune-suppressive therapy has been demonstrated to increase the risk of infective endocarditis (IE) in renal recipients. Reports of Corynebacterium striatum (C. striatum) endocarditis in renal recipients are scarce, thus limiting understanding of the disease.Case Presentation: We describe a case of native valve endocarditis caused by C. striatum in a 35-year-old male patient. The young man with end-stage renal failure underwent kidney transplantation because of autosomal dominant polycystic kidney disease. Ceftazidime was administered after the surgery according to routine procedures, and the patient was discharged on the 14th day after the surgery without any evidence of infection. The patient experienced fever on the 56th day, and Corynebacterium was cultured from the patient’s blood, in agreement with the results of testing of the donor kidney preservation solution. On the 64th day, multiple thromboses were found in the right external iliac artery, particularly around the anastomotic orifice of the transplanted renal artery. Vegetation was found in the posterior mitral valve tip on the 65th day. The patient had symptoms of persistent angina pectoris and chest tightness and underwent mitral valve replacement and vegetative resection. The patient eventually died. C. striatum was detected in the mitral valve and vegetation tissue with metagenomic next-generation sequencing.Conclusion: C. striatum may cause en

Chien-Cheng Huang,1– 3 Tzu-Hao Chen,3,4 Chung-Han Ho,4,5 Yi-Chen Chen,4 Rong-Jane Chen,3,6 Ying-Jan Wang,3 Chien-Chin Hsu,1 Hung-Jung Lin,1,7 Jhi-Joung Wang,8,9 Ching-Ping Chang,4 How-Ran Guo3,10,11 1Department of Emergency Medicine, Chi Mei Medical Center, Tainan, Taiwan; 2Department of Emergency Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; 3Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; 4Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan; 5Department of Information Management, Southern Taiwan University of Science and Technology, Tainan, Taiwan; 6Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan, Taiwan; 7Department of Emergency Medicine, Taipei Medical University, Taipei, Taiwan; 8Department of Anesthesiology, Chi Mei Medical Center, Tainan, Taiwan; 9Department of Anesthesiology, National Defense Medical Center, Taipei, Taiwan; 10Department of Occupational and Environmental Medicine, National Cheng Kung University Hospital, Tainan, Taiwan; 11Occupational Safety, Health and Medicine Research Center, National Cheng Kung University Hospital, Tainan, TaiwanCorrespondence: Chien-Cheng Huang, Department of Emergency Medicine, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan, 710, Taiwan, Tel +886-6-281-2811, Fax +886-6-281-6161, Email cmher11001@mail.chimei.org.tw How-Ran Guo, Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 1 Daxue Road, Tainan, 701, Taiwan, Tel +886-6-235-3535, Fax +886-6-275-2484, Email hrguo@mail.ncku.edu.twPurpose: Carbon monoxide (CO) poisoning may damage the pancreas, but the effects of CO poisoning on the development of diabetes and on existing diabetes remain unclear. We conducted a study incorporating data from epidemiologic analyses and animal experiments to clarify these issues.Methods: Using

Chien-An Chen,1,2,* Chung-Han Ho,3– 5,* Yu-Cih Wu,3 Yi-Chen Chen,3 Jhi-Joung Wang,3 Kuang-Ming Liao6 1Division of Hepatogastroenterology, Department of Internal Medicine, Chi Mei Medical Center, Tainan, 71004, Taiwan; 2Division of Hospital Medicine, Department of Internal Medicine, Chi Mei Medical Center, Tainan, 71004, Taiwan; 3Department of Medical Research, Chi Mei Medical Center, Tainan, 71004, Taiwan; 4Department of Information Management, Southern Taiwan University of Science and Technology, Tainan, 71005, Taiwan; 5Cancer Center, Taipei Municipal Wanfang Hospital, Taipei Medical University, Taipei, 11696, Taiwan; 6Department of Internal Medicine, Chi Mei Medical Center, Chiali, Tainan, 72263, Taiwan*These authors contributed equally to this workCorrespondence: Kuang-Ming Liao, Department of Internal Medicine, Chi Mei Medical Center, Chiali, Tainan, 72263, Taiwan, Tel +886 6 726 3333, Email abc8870@yahoo.com.twPurpose: The incidence of aspergillosis is increasing, and the risk factors for infection include cancer, admission to the intensive care unit, chronic pulmonary diseases, immunocompromised status, and taking immunomodulatory drugs. There are limited data about the incidence of aspergillosis in patients with different types of cancer. The aim of our study was to survey the incidence of aspergillosis in different cancer types from 2006 to 2017.Patients and Methods: Data were collected from the Taiwan Cancer Registry database and International Classification of Diseases, 9th, 10th Revision, and Clinical Modification codes for diagnosing aspergillosis. Patients with a history of aspergillosis before cancer were excluded, and the secondary outcome was the risk of mortality in cancer patients with and without aspergillosis after 1 year.Results: Among 951 cancer patients with a diagnosis of aspergillosis, there were 614 hematopoietic and reticuloendothelial system patients, 100 lung cancer patients, and 73 lymphoma cancer patients. The

Many unsupervised domain adaptation (UDA) methods have been proposed to bridge the domain gap by utilizing domain invariant information. Most approaches have chosen depth as such information and achieved remarkable success. Despite their effectiveness, using depth as domain invariant information in UDA tasks may lead to multiple issues, such as excessively high extraction costs and difficulties in achieving a reliable prediction quality. As a result, we introduce Edge Learning based Domain Adaptation (ELDA), a framework which incorporates edge information into its training process to serve as a type of domain invariant information. In our experiments, we quantitatively and qualitatively demonstrate that the incorporation of edge information is indeed beneficial and effective and enables ELDA to outperform the contemporary state-of-the-art methods on two commonly adopted benchmarks for semantic segmentation based UDA tasks. In addition, we show that ELDA is able to better separate the feature distributions of different classes. We further provide an ablation analysis to justify our design decisions., Comment: Accepted by BMVC2022. Ting-Hsuan Liao and Huang-Ru Liao contributed equally to this work

Federated learning (FL) is a collaborative machine learning framework that requires different clients (e.g., Internet of Things devices) to participate in the machine learning model training process by training and uploading their local models to an FL server in each global iteration. Upon receiving the local models from all the clients, the FL server generates a global model by aggregating the received local models. This traditional FL process may suffer from the straggler problem in heterogeneous client settings, where the FL server has to wait for slow clients to upload their local models in each global iteration, thus increasing the overall training time. One of the solutions is to set up a deadline and only the clients that can upload their local models before the deadline would be selected in the FL process. This solution may lead to a slow convergence rate and global model overfitting issues due to the limited client selection. In this paper, we propose the Latency awarE Semi-synchronous client Selection and mOdel aggregation for federated learNing (LESSON) method that allows all the clients to participate in the whole FL process but with different frequencies. That is, faster clients would be scheduled to upload their models more frequently than slow clients, thus resolving the straggler problem and accelerating the convergence speed, while avoiding model overfitting. Also, LESSON is capable of adjusting the tradeoff between the model accuracy and convergence rate by varying the deadline. Extensive simulations have been conducted to compare the performance of LESSON with the other two baseline methods, i.e., FedAvg and FedCS. The simulation results demonstrate that LESSON achieves faster convergence speed than FedAvg and FedCS, and higher model accuracy than FedCS.