Wi-Fi Coexistence with Duty Cycled LTE-U

Coexistence of Wi-Fi and LTE-Unlicensed (LTE-U) technologies has drawn significant concern in industry. In this paper, we investigate the Wi-Fi performance in the presence of duty cycle based LTE-U transmission on the same channel. More specifically, one LTE-U cell and one Wi-Fi basic service set (BSS) coexist by allowing LTE-U devices transmit their signals only in predetermined duty cycles. Wi-Fi stations, on the other hand, simply contend the shared channel using the distributed coordination function (DCF) protocol without cooperation with the LTE-U system or prior knowledge about the duty cycle period or duty cycle of LTE-U transmission. We define the fairness of the above scheme as the difference between Wi-Fi performance loss ratio (considering a defined reference performance) and the LTE-U duty cycle (or function of LTE-U duty cycle). Depending on the interference to noise ratio (INR) being above or below -62dbm, we classify the LTE-U interference as strong or weak and establish mathematical models accordingly. The average throughput and average service time of Wi-Fi are both formulated as functions of Wi-Fi and LTE-U system parameters using probability theory. Lastly, we use the Monte Carlo analysis to demonstrate the fairness of Wi-Fi and LTE-U air time sharing

Fermentation Control and Ethanol Production of Total Mixed Ration Prepared with Apple Pomace and Microbial and Chemical Additives

The objective of this study is to evaluate the impacts of moisture adjustment, lactic acid bacteria (LAB) inoculant and chemical additives on fermentation characteristics and ethanol production of a total mixed ration (TMR) containing apple (Malus domestica) pomace. The TMR was prepared with apple pomace, corn, wheat bran, soybean meal, timothy, and alfalfa hay. In Experiment 1, the proportion of apple pomace was 150 g/kg of dry matter (DM), and the moisture of the TMR was unadjusted (control) or adjusted to 450, 500, and 550 g/kg, respectively. In Experiment 2, the same ingredient proportions as in experiment 1 were used and the TMR moisture was adjusted to 550 g/kg. The treatments were no additive (Control), homo-fermentative LAB (Lactobacillus plantarum, LP), hetero-fermentative LAB (Lactobacillus buchneri, LB) and calcium propionate (CP). The small-scale fermentation system was used to prepare the TMR, and their fermentation characteristics were analyzed after 60 days of ensiling. In Experiment 1, the pH of various TMRs was around 4.1. With the moisture decrease, the lactic acid increased (P \u3c 0.05), and the ammonia nitrogen decreased (P \u3c 0.05). The ethanol decreased significantly with moisture adjustment compared to the control, and the TMR with moisture of 500g/kg showed the lowest ethanol concentration (P \u3c 0.05). In Experiment 2, LP treatment increased lactic acid and decreased acetic acid and ammonia nitrogen significantly (P \u3c 0.05), while LB treatment had no effect on fermentation. Both LP and LB had no effect on the ethanol concentration. The TMR treated with CP significantly decreased the ethanol and acetic acid concentrations (P \u3c 0.05) but did not inhibit the lactic acid production compared to control. The results confirmed that adjusting moisture to 500 g/kg and adding CP could effectively inhibit the excessive production of ethanol in TMR containing apple pomace. Homo-fermentative LAB can better improve the fermentation quality of TMR than hetero-fermentative LAB, but neither can inhibit the production of ethanol

Measurement of the extinction coefficients of magnetic fluids

A novel spectral transmittance approach for measuring the extinction coefficient of magnetic fluids is proposed. The measuring principle and accuracy of the approach are analysed. Experiments are conducted to measure the extinction coefficient of magnetic fluids with different particle volume fractions. The relative uncertainty of experimental data is less than 1.8%. The experimental results indicate that the extinction coefficient of magnetic fluids increases with increase of the volume fraction of suspended magnetic nanoparticles and the optical properties of the particle material have a significant effect on the extinction coefficient of the magnetic fluids

Data-driven model construction for anisotropic dynamics of active matter

The dynamics of cellular pattern formation is crucial for understanding embryonic development and tissue morphogenesis. Recent studies have shown that human dermal fibroblasts cultured on liquid crystal elastomers can exhibit an increase in orientational alignment over time, accompanied by cell proliferation, under the influence of the weak guidance of a molecularly aligned substrate. However, a comprehensive understanding of how this order arises remains largely unknown. This knowledge gap may be attributed, in part, to a scarcity of mechanistic models that can capture the temporal progression of the complex nonequilibrium dynamics during the cellular alignment process. The orientational alignment occurs primarily when cells reach a high density near confluence. Therefore, for accurate modeling, it is crucial to take into account both the cell-cell interaction term and the influence from the substrate, acting as a one-body external potential term. To fill in this gap, we develop a hybrid procedure that utilizes statistical learning approaches to extend the state-of-the-art physics models for quantifying both effects. We develop a more efficient way to perform feature selection that avoids testing all feature combinations through simulation. The maximum likelihood estimator of the model was derived and implemented in computationally scalable algorithms for model calibration and simulation. By including these features, such as the non-Gaussian, anisotropic fluctuations, and limiting alignment interaction only to neighboring cells with the same velocity direction, this model quantitatively reproduce the key system-level parameters--the temporal progression of the velocity orientational order parameters and the variability of velocity vectors, whereas models missing any of the features fail to capture these temporally dependent parameters.Comment: 20 pages, 14 figure

Construction of Innovation Platform for CEEUSRO

On the basis of differentiating the meaning and function of platform of CEEUSRO, the contracture and the factors are discussed, and the approaches of organization and the administrative mechanism of the platform are put forward to supply specific thoughts to construct the platform of CEEUSRO

Alterations in oxidative, inflammatory and apoptotic events in short-lived and long-lived mice testes

Aged testes undergo profound histological and morphological alterations leading to a reduced functionality. Here, we investigated whether variations in longevity affect the development of local inflammatory processes, the oxidative state and the occurrence of apoptotic events in the testis. To this aim, well-established mouse models with delayed (growth hormone releasing hormone-knockout and Ames dwarf mice) or accelerated (growth hormone-transgenic mice) aging were used. We hereby show that the testes of short-lived mice show a significant increase in cyclooxygenase 2 expression, PGD2 production, lipid peroxidation, antioxidant enzymes expression, local macrophages and TUNEL-positive germ cells numbers, and the levels of both pro-caspase-3 and cleaved caspase-3. In contrast, although the expression of antioxidant enzymes remained unchanged in testes of long-lived mice, the remainder of the parameters assessed showed a significant reduction. This study provides novel evidence that longevity confers anti-inflammatory, anti-oxidant and anti-apoptotic capacities to the adult testis. Oppositely, short-lived mice suffer testicular inflammatory, oxidative and apoptotic processes.Fil: Matzkin, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; ArgentinaFil: Miquet, Johanna Gabriela. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; ArgentinaFil: Fang, Yimin. Southern Illinois University. School Of Medicine; Estados UnidosFil: Hill, Cristal Monique. Southern Illinois University; Estados UnidosFil: Turyn, Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Físico-Química Biológicas "Prof. Alejandro C. Paladini". Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Físico-Química Biológicas; ArgentinaFil: Calandra, Ricardo Saul. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Bartke, Andrzej. Southern Illinois University; Estados UnidosFil: Frungieri, Monica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; Argentin

Lifespan of long-lived growth hormone receptor knockout mice was not normalized by housing at 30°C since weaning

Growth hormone receptor knockout (GHRKO) mice are remarkably long-lived and have improved glucose homeostasis along with altered energy metabolism which manifests through decreased respiratory quotient (RQ) and increased oxygen consumption (VO2 ). Short-term exposure of these animals to increased environmental temperature (eT) at 30°C can normalize their VO2 and RQ. We hypothesized that increased heat loss in the diminutive GHRKO mice housed at 23°C and the consequent metabolic adjustments to meet the increased energy demand for thermogenesis may promote extension of longevity, and preventing these adjustments by chronic exposure to increased eT will reduce or eliminate their longevity advantage. To test these hypotheses, GHRKO mice were housed at increased eT (30°C) since weaning. Here, we report that contrasting with the effects of short-term exposure of adult GHRKO mice to 30°C, transferring juvenile GHRKO mice to chronic housing at 30°C did not normalize the examined parameters of energy metabolism and glucose homeostasis. Moreover, despite decreased expression levels of thermogenic genes in brown adipose tissue (BAT) and elevated core body temperature, the lifespan of male GHRKO mice was not reduced, while the lifespan of female GHRKO mice was increased, along with improved glucose homeostasis. The results indicate that GHRKO mice have intrinsic features that help maintain their delayed, healthy aging, and extended longevity at both 23°C and 30°C

GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals

Towards developing effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by electroencephalogram (EEG), is highly demanded. Traditional works classify EEG signals without considering the topological relationship among electrodes. However, neuroscience research has increasingly emphasized network patterns of brain dynamics. Thus, the Euclidean structure of electrodes might not adequately reflect the interaction between signals. To fill the gap, a novel deep learning framework based on the graph convolutional neural networks (GCNs) was presented to enhance the decoding performance of raw EEG signals during different types of motor imagery (MI) tasks while cooperating with the functional topological relationship of electrodes. Based on the absolute Pearson's matrix of overall signals, the graph Laplacian of EEG electrodes was built up. The GCNs-Net constructed by graph convolutional layers learns the generalized features. The followed pooling layers reduce dimensionality, and the fully-connected softmax layer derives the final prediction. The introduced approach has been shown to converge for both personalized and group-wise predictions. It has achieved the highest averaged accuracy, 93.056% and 88.57% (PhysioNet Dataset), 96.24% and 80.89% (High Gamma Dataset), at the subject and group level, respectively, compared with existing studies, which suggests adaptability and robustness to individual variability. Moreover, the performance was stably reproducible among repetitive experiments for cross-validation. To conclude, the GCNs-Net filters EEG signals based on the functional topological relationship, which manages to decode relevant features for brain motor imagery