Selection Method for Kernel Function in Nonparametric Extrapolation Based on Multicriteria Decision-Making Technology

Selecting the most appropriate kernel function to extrapolate a load set is the paramount step in compiling load spectrum, as it affects the results of nonparametric extrapolation largely. Aiming at this issue, this paper provides a new approach in selecting kernel function for the nonparametric extrapolation. To solve the complexity and uncertainty of nonparametric extrapolation, characteristics of four kernel functions and their effects on the results are explained in the “from-to” diagram obtained by rainflow counting. Multicriteria decision-making (MCDM) is then applied to solve the selection problem of kernel function. To evaluate the dispersion degrees of the mean and amplitude of a load set accurately, their range, standard deviation, and interquartile range are selected as the evaluation criteria. The weight of each criterion, which represents the impact degree on the selection of the kernel function, is calculated separately using the eigenvector and entropy method. The comprehensive weights are obtained by applying the optimization theory and Jaynes’ maximum entropy principle. Finally, the importance of each criterion is discussed according to their calculated comprehensive weights, and the selection method for kernel functions is obtained, which is illustrated by extrapolating the output torque of the power split device of hybrid electrical vehicles

Heptaaqua­(3,4,5,6-tetra­chloro­phthalato-κO 1)erbium(III) 2-carb­oxy-3,4,5,6-tetra­chloro­benzoate–3,4,5,6-tetra­chloro­phthalic acid–water (1/1/1)

In the three-dimensional tetra­chloro­phthalate-bridged title complex [Er(C8Cl4O4)(H2O)7](C8HCl4O4)·C8H2Cl4O4·H2O, the ErIII ion is coordinated in form of a distorted square antiprism by an O atom of a tetra­chloro­phthalate ligand and by seven water O atoms. Extensive hydrogen bonds establish a layered network structure extending parallel to (001)

Amorphous Iron Oxyhydroxide Nanosheets: Synthesis, Li Storage, and Conversion Reaction Kinetics

We present a facile approach to synthesize amorphous iron oxyhydroxide nanosheet from the surfactant-assisted oxidation of iron sulfide nanosheet. The amorphous iron oxyhydroxide nanosheet is porous and has a high surface area of 223 m(2) g(-1). The lithium storage properties of the amorphous iron oxyhydroxide are characterized: it is a conversion-reaction electrode material, and it demonstrates superior rate capabilities (e.g., discharge capacities as high as 642 mAh g(-1) are delivered at a current density of 2 C). The impedance spectroscopy analysis identifies a RC series subcircuit originated by the conversion-reaction process. Investigation of the conversion-reaction kinetics through the RC subcircuit time constant reproduces the hysteresis in the discharge/charge voltage profile. Hysteresis is then connected to underlying thermodynamics of the conversion reaction rather than to a kinetic limitation.We thank financial support from Generalitat Valenciana (ISIC/2012/008 Institute of Nanotechnologies for Clean Energies) and FP7 European project ORION (Large CP-IP 229036-2). We thank the financial support by the Singapore National Research Foundation (NRF) through its Campus for Research Excellence and Technological Enterprise (CREATE) program

A feasibility study on using smartphones to conduct short-version verbal autopsies in rural China

Background: Currently there are two main sources of mortality data with cause of death assignments in China. Both sources-the Ministry of Health-Vital Registration system and the Chinese Disease Surveillance Point system-present their own challenges. A new approach to cause of death assignment is a smartphone-based shortened version of a verbal autopsy survey. This study evaluates the feasibility and acceptability of this new method conducted by township health care providers (THP) and village doctors (VD) in rural China, where a large proportion of deaths occur in homes and cause of death data are inaccurate or lacking. Methods: The Population Health Metrics Research Consortium mobile phone-based shortened verbal autopsy questionnaire was made available on an Android system-based application, and cause of death was derived using the Tariff method (Tariff 2.0); we called this set of tools "msVA." msVA was administered to relatives of the deceased by six THPs and six VDs in 24 villages located in six townships of Luquan County, Hebei Province, China. Subsequently, interviews were conducted among 12 interviewers, 12 randomly selected respondents, and five study staff to assess the feasibility and acceptability of using msVA for mortality data collection. Results: Between July 2013 and August 2013, 268 deaths took place in the study villages. Among the 268 deaths, 227 VAs were completed (nine refusals, 31 migrations and one loss of data due to breakdown of the smartphone). The average time for a VA interview was 21.5 +/- 3.4 min (20.1 +/- 3.5 min for THP and 23.2 +/- 4.1 min for VD). Both THPs and VDs could be successful interviewers; the latter needed more training but had more willingness to implement msVA in the future. The interviews revealed that both interviewers and relatives of the deceased found msVA to be feasible, acceptable, and more desirable than traditional methods. The cost of conducting a new VA was $ 8.87 per death. Conclusions: Conduction of msVA by VDs in their own villages was feasible and acceptable in rural northern China. Broader implementation of msVA across rural China could potentially improve the coverage and quality of cause of death data, allowing for better national health evaluation and program planning.National Heart, Lung and Blood Institute, National Institutes of Health, Department of Health and Human Services [HHSN268200900034C]; NHLBI-UHG Trainee Seed [email protected]

Inhibition of phosphorylated c-Met in rhabdomyosarcoma cell lines by a small molecule inhibitor SU11274

<p>Abstract</p> <p>Background</p> <p>c-Met is a receptor tyrosine kinase (RTK) that is over-expressed in a variety of cancers and involved in cell growth, invasion, metastasis and angiogenesis. In this study, we investigated the role of c-Met in rhabdomyosarcoma (RMS) using its small molecule inhibitor SU11274, which has been hypothesized to be a potential therapeutic target for RMS.</p> <p>Methods</p> <p>The expression level of phosphorylated c-Met in RMS cell lines (RD, CW9019 and RH30) and tumor tissues was assessed by phospho-RTK array and immunohistochemistry, respectively. The inhibition effects of SU11274 on RMS cells were studied with regard to intracellular signaling, cell proliferation, cell cycle and cell migration.</p> <p>Results</p> <p>A high level of phosphorylated c-Met was detected in 2 alveolar RMS cell lines (CW9019 and RH30) and 14 out of 24 RMS tissue samples, whereas relatively low levels of phospho-c-Met were observed in the embryonic RMS cell line (RD). The small molecule SU11274 could significantly reduce the phosphorylation of c-Met, resulting in inhibition of cell proliferation, G1 phase arrest of cell cycle and blocking of cell migration in CW9019 and RH30 cell lines.</p> <p>Conclusion</p> <p>These results might support the role of c-Met in the development and progression of RMS. Furthermore, the inhibitor of c-Met, SU11274, could be an effective targeting therapy reagent for RMS, especially alveolar RMS.</p

Recent progress in carbon-based electrochemical catalysts: From structure design to potential applications

Advances in research and development of carbon-based metal-free electrocatalysts (C-MFECs) have provided potential alternatives to precious metal catalysts for various reactions important to renewable energy and environmental remediation. This timely but critical review provides an overview of recent breakthroughs (within the past 5 years or so) on C-MFECs in all aspects, including the design and regulation of intrinsic catalytic active sites, design and synthesis of carbon composite and hybrid carbon catalysts, mechanism understanding, and potential applications in clean energy storage and energy/chemical conversion. Current challenges and future opportunities in the field of metal-free carbon electrocatalysis are also discussed to provide forward-looking opportunities for their potential applications in various catalytic processes of practical significance

Advancing microbial production through artificial intelligence-aided biology

Microbial cell factories (MCFs) have been leveraged to construct sustainable platforms for value-added compound production. To optimize metabolism and reach optimal productivity, synthetic biology has developed various genetic devices to engineer microbial systems by gene editing, high-throughput protein engineering, and dynamic regulation. However, current synthetic biology methodologies still rely heavily on manual design, laborious testing, and exhaustive analysis. The emerging interdisciplinary field of artificial intelligence (AI) and biology has become pivotal in addressing the remaining challenges. AI-aided microbial production harnesses the power of processing, learning, and predicting vast amounts of biological data within seconds, providing outputs with high probability. With well-trained AI models, the conventional Design-Build-Test (DBT) cycle has been transformed into a multidimensional Design-Build-Test-Learn-Predict (DBTLP) workflow, leading to significantly improved operational efficiency and reduced labor consumption. Here, we comprehensively review the main components and recent advances in AI-aided microbial production, focusing on genome annotation, AI-aided protein engineering, artificial functional protein design, and AI-enabled pathway prediction. Finally, we discuss the challenges of integrating novel AI techniques into biology and propose the potential of large language models (LLMs) in advancing microbial production

Research Progress on the Effect of Dissolved Organic Matter on the Environmental Behavior of Cadmium in Environmental Remediation

With the rapid development of the economy and society and the continuous emission of cadmium (Cd), Cd pollution has become a major environmental problem faced by China and the rest of the world. As the most active component in organic matter, molecular weight of DOM is usually between several Da and several hundred kDa. The various active functional groups contained in DOM, such as carboxyl, hydroxyl, and phenolic groups, are ligands and migration carriers for many heavy metals in the environment. The interaction between DOM and Cd significantly affects the morphology, bioavailability, toxicity, and migration transformation of Cd in the environment through physical adsorption, ligand exchange, and surface complexation. However, from the perspective of cadmium pollution remediation, the complexation between Cd and DOM is a key factor controlling the effectiveness of Cd remediation. DOM can directly form DOM-Cd binary complexes through ligand exchange. According to the different bridging positions of DOM, Cd(Ⅱ), and mineral/metal surface cations (Mi/Me), two types of ternary complexes can also be formed: A or B. DOM has complex and diverse sources, components, and structures, under different conditions, DOM exhibits two effects on Cd: passivation or activation, which has been widely used in in situ passivation remediation, leaching remediation, or phytoremediation of Cd pollution. Based on the review of relevant research results in recent years, this review evaluates the complexation types between Cd and DOM, and analyzes the effects of factors such as DOM molecular weight, pH, ion strength, and temperature on Cd-DOM complexation and the mechanism of Cd adsorption and desorption. On this basis, the application research of DOM in in situ passivation remediation and ex situ remediation of soil/sediment Cd pollution was summarized. These methods help to reduce environmental risks and remediation costs of Cd pollution remediation. Under normal circumstances, small molecular weight DOM contains richer functional groups and more complex coordination sites, making it easy to form soluble DOM-Cd complexes. Especially for DOM components with molecular weight 30kDa) with higher humification degree and applying inorganic passivators such as iron oxides can significantly improve the in situ passivation and remediation effect of Cd pollution. In the chemical leaching or phytoremediation of Cd, small molecular weight DOM (<5kDa) is selected to improve the effectiveness of pollution remediation. It is recommended to conduct research in the following three areas in the future: (1) Study the complexation between different molecular weights of DOM and Cd, and accurately analyze the complexation between functional groups of different components inside DOM and Cd. (2) Strengthen the research on the adsorption, desorption, migration, transformation, and bioavailability of Cd by DOM under the influence and control of multiple factors. (3) Strengthen the research on DOM in Cd pollution remediation technology, improve the numerical simulation model of the interaction between DOM and Cd, provide path guidance and data support for long-term observation of Cd pollution, and more accurately determine the migration and transformation process of Cd in the environment

Functional proteomic analysis reveals the involvement of KIAA1199 in breast cancer growth, motility and invasiveness.

BACKGROUND: KIAA1199 is a recently identified novel gene that is up-regulated in human cancer with poor survival. Our proteomic study on signaling polarity in chemotactic cells revealed KIAA1199 as a novel protein target that may be involved in cellular chemotaxis and motility. In the present study, we examined the functional significance of KIAA1199 expression in breast cancer growth, motility and invasiveness. METHODS: We validated the previous microarray observation by tissue microarray immunohistochemistry using a TMA slide containing 12 breast tumor tissue cores and 12 corresponding normal tissues. We performed the shRNA-mediated knockdown of KIAA1199 in MDA-MB-231 and HS578T cells to study the role of this protein in cell proliferation, migration and apoptosis in vitro. We studied the effects of KIAA1199 knockdown in vivo in two groups of mice (n = 5). We carried out the SILAC LC-MS/MS based proteomic studies on the involvement of KIAA1199 in breast cancer. RESULTS: KIAA1199 mRNA and protein was significantly overexpressed in breast tumor specimens and cell lines as compared with non-neoplastic breast tissues from large-scale microarray and studies of breast cancer cell lines and tumors. To gain deeper insights into the novel role of KIAA1199 in breast cancer, we modulated KIAA1199 expression using shRNA-mediated knockdown in two breast cancer cell lines (MDA-MB-231 and HS578T), expressing higher levels of KIAA1199. The KIAA1199 knockdown cells showed reduced motility and cell proliferation in vitro. Moreover, when the knockdown cells were injected into the mammary fat pads of female athymic nude mice, there was a significant decrease in tumor incidence and growth. In addition, quantitative proteomic analysis revealed that knockdown of KIAA1199 in breast cancer (MDA-MB-231) cells affected a broad range of cellular functions including apoptosis, metabolism and cell motility. CONCLUSIONS: Our findings indicate that KIAA1199 may play an important role in breast tumor growth and invasiveness, and that it may represent a novel target for biomarker development and a novel therapeutic target for breast cancer