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Food redistribution systems do not currently address access to sustainably sourced foods that are also nutrient-dense for lower-income communities. Opportunities for future research and practice include aligning food waste, plastic waste, and nutrition priorities together and developing better food redistribution systems to limit wastage of high-quality foods.As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices.In order to accurately diagnose the health of high-order statically indeterminate structures, most existing structural health monitoring (SHM) methods require multiple sensors to collect enough information. However, comprehensive data collection from multiple sensors for high degree-of-freedom structures is not typically available in practice. We propose a method that reconciles the two seemingly conflicting difficulties. Takens' embedding theorem is used to augment the dimensions of data collected from a single sensor. Taking advantage of the success of machine learning in image classification, high-dimensional reconstructed attractors were converted into images and fed into a convolutional neural network (CNN). Attractor classification was performed for 10 damage cases of a 3-story shear frame structure. Numerical results show that the inherently high dimension of the CNN model allows the handling of higher dimensional data. Information on both the level and the location of damage was successfully embedded. The same methodology will allow the extraction of data with unsupervised CNN classification to be consistent with real use cases.Hepatitis B virus (HBV) infection is one of the important risk factors for hepatocellular carcinoma (HCC) worldwide, accounting for around 50% of cases. Chronic hepatitis B infection generates an inflammatory microenvironment, in which hepatocytes undergoing repeated cycles of damage and regeneration accumulate genetic mutations predisposing them to cancer. A striking male dominance in HBV-related HCC highlights the influence of sex hormones which interact with viral factors to influence carcinogenesis. HBV is also considered an oncogenic virus since its X and surface mutant proteins showed tumorigenic activity in mouse models. The other unique mechanism is the insertional mutagenesis by integration of HBV genome into hepatocyte chromosomes to activate oncogenes. HCC survival largely depends on tumor stages at diagnosis and effective treatment. However, early diagnosis by the conventional protein biomarkers achieves limited success. A new biomarker, the circulating virus-host chimera DNA from HBV integration sites in HCC, provides a liquid biopsy approach for monitoring the tumor load in the majority of HBV-HCC patients. To maximize the efficacy of new immunotherapies or molecular target therapies, it requires better classification of HCC based on the tumor microenvironment and specific carcinogenic pathways. An in-depth study may benefit both the diagnosis and treatment of HBV-related HCC.Megalin has been proposed as an endocytic receptor for aminoglycosides as well as estrogen and androgen. learn more We aimed to investigate the otoprotective effects of antiandrogens (flutamide, FM) on kanamycin (KM)-induced hearing loss in rats. Rats were divided into four groups. The KM group was administered KM (20 mg/kg/day) for 5 days, while the FM group received FM (15 mg/kg/day) for 10 days. In the KM + FM group, KM and FM (15 mg/kg/day) were simultaneously injected for 5 days and then FM was injected for 5 days. Auditory brainstem responses were measured. Western blotting and/or quantitative reverse transcriptase-polymerase chain reaction were performed for megalin, cytochrome P450 1A1 (Cyp1a1), Cyp1b1, metallothionein 1A (MT1A), MT2A, tumor necrosis factor (TNF)-α, caspase 3, and cleaved caspase 3. The FM + KM group showed attenuated auditory thresholds when compared with the KM group at 4, 8, 16, and 32 kHz (all p less then 0.05). The KM + FM group showed lower megalin and Cyp1b1 levels than the KM group (all p less then 0.05). The KM + FM group revealed lower MT1A, TNFα, and caspase 3 protein levels, compared with those in the KM group (all p less then 0.05). Androgen receptor inhibition protects against cochlear injuries in KM-induced hearing loss rats by attenuating megalin expression, revealing anti-inflammatory and anti-apoptotic effects.Orange peel is the main by-product from orange juice industry. It is a known source of bioactive compounds, mostly phenolic compounds, and it has been widely studied for its healthy activities. Thus, this research focuses on the establishment of ultrasound-assisted extraction of phenolic compounds in orange peel using a sonotrode. For this purpose, a Box-Behnken design of 27 experiments was carried out with four independent factors-ratio ethanol/water (v/v), time (min), amplitude (%), and pulse (%). Quantitative analyses of phenolic compounds were performed and the antioxidant activity was measured by ABTS and DPPH methods. The validity of the experimental design was confirmed by ANOVA and the optimal sonotrode extraction conditions were obtained by response surface methodology (RSM). The extracts obtained in the established conditions were analyzed by High Performance Liquid Chromatography (HPLC) coupled to mass spectrometer detector and 74 polar compounds were identified. The highest phenolic content and antioxidant activity were obtained using 45/55 ethanol/water (v/v), 35 min, amplitude 90% (110 W), and pulse 100%.

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