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1-2.2, 0.2-0.5, and 0.5-1.0 under blue, R630, and R680 light conditions, respectively. The predicted linear and cyclic electron flow ratios were consistent with the excitation ratio between photosystems I and II, as observed in the steady-state fluorescence spectra.In the first selection stage of iron ore, the ore classification accuracy plays a decisive role in subsequent work. Therefore, how to identify iron ore quickly and accurately is an important task. Traditional chemical, physical and manual identification methods have the disadvantages of high costs and high time consumption. This research proposes a new iron ore identification method, that combines deep learning with visible-infrared reflectance spectroscopy to establish an iron ore classification model. We collected iron ore samples from the Anshan iron ore area and measured the spectral data with a spectrometer. Then, a deep neural network framework is proposed based on the convolution neural network and the improved extreme learning machine algorithm, and an iron ore classification model is established based on the framework. The results show that the proposed model can effectively identify the types of iron ore, and the overall accuracy reaches 98.11%.The Academy of Nutrition and Dietetics, as the largest member-based nutrition organization in the world, is dedicated to advancing the world of nutrition and dietetics through research. It is essential for the Academy to identify both current and future research priorities for nutrition and dietetics professionals. To address this, the Academy convened a task force charged with developing research priorities relevant for its members. Specifically, it would define key issues of the nutrition and dietetics profession going into the second century and identify relevant research topics and questions related to the defined issues. The task force leveraged multiple data sources to develop the research priorities. These data sources included existing interviews from a previous Academy event (Nutrition Impact Summit) held in 2016 and answers from an Academy Member Engagement Zone survey. This led to the development of draft research priorities that were included in a more extensive survey e-mailed to all Academy members. Results of this member-wide survey, in addition to multiple stakeholder checks, informed the final Academy research priorities. SCH58261 Thirteen final priorities were established across 4 domains nutrition-related discovery, clinical nutrition research, implementation science, and public health. These priorities have relevance for all nutrition and dietetics professionals across diverse areas of practice and will be used internally to prioritize research efforts, inform the allocation of resources across Academy units, and guide Academy advocacy for national nutrition research agendas and initiatives. This article will summarize the task force's updated research priorities and detail the 9-step process used to generate them.As nutrition-related diseases contribute to rising health care costs, food retail settings are providing a unique opportunity for registered dietitian nutritionists (RDNs) to address the nutritional needs of consumers. Food as Medicine interventions play a role in preventing and/or managing many chronic conditions that drive health care costs. The objective of this scoping review was to identify and characterize literature examining Food as Medicine interventions within food retail settings and across consumer demographics. An electronic literature search of 8 databases identified 11,404 relevant articles. Results from the searches were screened against inclusion criteria, and intervention effectiveness was assessed for the following outcomes improvement in health outcomes and cost-effectiveness. One-hundred and eighty-six papers and 25 systematic reviews met inclusion criteria. Five categories surfaced as single interventions prescription programs, incentive programs, medically tailored nutrition, path-to-purchase marketing, and personalized nutrition education. Multiple combinations of intervention categories, reporting of health outcomes (nutritional quality of shopping purchases, eating habits, biometric measures), and cost-effectiveness (store sales, health care dollar savings) also emerged. The intervention categories that produced both improved health outcomes and cost-effectiveness included a combination of incentive programs, personalized nutrition education, and path-to-purchase marketing. Food as Medicine interventions in the food retail setting can aid consumers in navigating health through diet and nutrition by encompassing the following strategic focus areas promotion of health and well-being, managing chronic disease, and improving food security. Food retailers should consider the target population and desired focus areas and should engage registered dietitian nutritionists when developing Food as Medicine interventions.Sigma (σ) factors are key regulatory proteins that control the transcription initiation in prokaryotes. In response to environmental or developmental cues, σ factors initiate the transcription of necessary genes responsible for maintaining a life-sustaining metabolic balance. Due to the significant role of σ factors in bacterial metabolism, their rational engineering for commercial metabolite production in photoautotrophic, cyanobacterial cells is a desirable venture. As cyanobacterial genomes typically encode multiple σ factors, effective execution of metabolic engineering efforts largely relies on uncovering the complicated gene regulatory network and further characterization of the members of σ factor regulatory circuits. This review outlines the prospects of σ factor in metabolic engineering of cyanobacteria, summarizes the challenges in the path towards an efficient strain construction and highlights the genomic context of putative regulators of cyanobacterial σ factors.Oral cavity metastases are considered rare and represent approximately 1% of all oral malignancies. Due to their rarity and atypical clinical and radiographic appearance, metastatic lesions are considered a diagnostic challenge. In this article we present a rare, unusual & exceptional case of left maxillary mass which on further evaluation leading to diagnosis of left breast carcinoma with metastasis to isolated left maxillary bone. Sixty five year old postmenopausal woman of low socioeconomic status with good performance status presented with a 3 months history of progressive pain and swelling in the left maxillary region. Fine Needle Aspiration Cytology (FNAC) from the maxillary mass shows invasive ductal carcinoma. On further clinical, radiographic, and histopathological examination findings from the breast lesion confirmed the diagnosis of hormone receptor positive metastatic breast carcinoma. In view of painful metastatic maxillary lesion with breast disease she was managed with a palliative radiotherapy to the maxillary lesion and palliative chemotherapy with Doxorubicin-Cyclophosphamide and bhisphosphonate-Zolendronic acid.