Soil Chemical Properties of Sand-based C,olf Putting Green at Different Depths

USGA-specified golf putting green rootzone is a highly managed. sand dominated turf system. As putting greens age. organic matter accumulation in the form or thatch and mat in the upper rootzone profile causes temporal and spatial changes in soil chemical properties. The objective of the first study was to characterize soil chemical properties in aging putting green rootzones. Four USGA-specified putting greens treated with l\VO rootzone mixtures (sand/peat at 80:20: sand/peat/soil at 80: 15:5) and two establishment fertilization regimes (controlled and accelerated) were constructed in sequential years. Samples were collected to a depth of 7.62 cm when the four putting greens were 6. 7. 8. and 9 years old. and were subdivided into 12 layers. The effects or root zone mixture. establishment fertilization regime. putting green age. and soil depth on total organic C. total N. potentially mineralizable N (PMN). cation exchange capacity (CFC). Electrical conductivity (EC). and pH were evaluated. The rootzone mixtures and establishment fcrtili1.ation regimes had no effect on soil chemical properties investigated saving EC. which was higher in sand/peat/soil rootzones. Total organic C. total N. PMN CEC. and EC decreased with soil depth whereas soil PH increased with soil depth. The interaction between putting green age and soil depth was significant for t'1tal N. CFC. and EC. The initial differences or soil chemical properties disappeared due to topdressing practice over a period 0!'<1 yc,1rs at the top or the rootzones especially in the Oto 2 cm layer. The chemical properties of the original rootzone layers are affected by both the age of the putting greens and cultural practices. Diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy in the near infrared (NIR) (4000-10000 cm- 1) and mid -infrared (MIR) (600-4000 cm- 1) region in conjunction with partial least square regression (PLSR) is able to rapidly predict multiple soil properties from a single spectral scanning and is deemed as a promising surrogate for conventional analytical methods. In the second study. by using samples collected in the first study. calibration models were developed for total organic C. total N. CEC. EC. And pl I by regressing spectral results of DRIFT-NIR and -MIR with values determined by conventional methods. Results fix total organic C, total N, CFC and EC achieved R2 > 0.80. Mid infrared and NIR spectroscopy gave similar calibration accuracy for soil properties investigated. Based on rootzone mixture (sand/peat vs sand/peat/soil). Putting green age (6-yr-old vs 9-yr-old). and sampling depth (0-3.81 cm vs 3.81-7.62 cm). the whole sample set was further grouped into subsets. Satisfactory accuracy of MIR calibrations and mutual predictions was achieved with subsets of different rootzone mixtures and putting green ages. However. subsets separated by soil depth failed to be predicted with sufficient accuracy within the group. Results of the study verified the potential of using DRIFT-NIR and -MIR to predict soil chemical properties of sand-based turf soil through PLSR modeling: however. model robustness might be affected by sampling depth

LEAKAGE CURRENT REDUCTION OF MOS CAPACITOR INDUCED BY RAPID THERMAL PROCESSING

With the MOSFET scaling practice, the performance of IC devices is improved tremendously as we experienced in the last decades. However, the small semiconductor devices also bring some drawbacks among which the high gate leakage current is becoming increasingly serious. This thesis work is focused on the of gate leakage current reduction in thin oxide semiconductor devices. The method being studied is the Phonon Energy Coupling Enhancement (PECE) effect induced by Rapid Thermal Processing (RTP). The basic MOS capacitors are used to check improvements of leakage current reduction after appropriate RTP process. Through sets of experiments, it is found that after RTP in Helium environment could bring about four orders reduction in gate leakage current of MOS capacitors

INVESTOR ATTENTION AND SENTIMENT

Investor sentiment and attention are often linked to the same non-economic events making it difficult to understand why and how asset prices are affected. This thesis disentangles these two potential drivers of market behaviour by studying how investors react to sports outcomes, weather conditions and merger and acquisition announcements. Firstly, a new dataset of medals for major participating countries and sponsor firms over four Summer Olympic Games is analysed. Results show that although Olympic success does not lead to abnormal stock returns, subsequent market activity is reduced substantially. In the US, for example, trading volume (realised volatility) during Olympics is over 24% (46%) lower than usual while gold medal awards lead to a further decrease over the next trading day. These findings are in line with recent theories and evidence related to investor inattention but cannot easily be explained on the basis of sentiment. Analysis of data from online search volumes and surveys measuring investor sentiment, also suggest that the market impact of the Olympics is linked to changes in attention. I demonstrate that the statistical regularities can be exploited by simple volatility trading strategies in the US to produce significant risk adjusted profits. Secondly, I study the relationship between weather and stock market activity using a new perspective that does not rely solely on investor mood. I argue that bad weather can increase the productivity of investors by making them more focused on trading and less concerned about other leisure activities. This allows me to explain the empirical finding of higher trading activity on rainy days for a sample of 33 international stock markets. In line with previous literature, I confirm that particularly bad weather conditions which create inconvenience to market participants, such as snow, have the opposite effect by reducing productivity and trading volume. Finally, I find evidence that weather has a nonlinear effect on market activity. Thirdly, I explore if the market reaction to M&As in the US is governed by attention or sentiment. I find that attention, as proxied by online abnormal search volume, decreases significantly before announcements and then increases dramatically on the event date. The high level of attention diminishes shortly after. I also investigate whether the abnormal search volume surrounding the event date affects stock prices. The results suggest that the resolved uncertainty before the announcement date is incorporated into price discovery shortly after the announcement as the learning capacity of investors constrains the information processing speed in a bid to adjust the investment decisions

LncRNA PFAL suppresses TNF-α-induced inflammation by upregulating miR-18a in WI-38 cells

Purpose: Pneumonia is a serious respiratory disease among children with high mortality and morbidity all over the world. Long non-coding RNAs have been proven to play a vital role in many inflammatory diseases including pneumonia. In the present study, the protective impact of lncRNA PFAL on cell viability, cell apoptosis and secretion of inflammatory cytokines, as well as the underlying molecular mechanism in TNF-α-induced inflammatory injury model of pneumonia were investigated.Methods: WI-38 cell line was treated with 20 ng/ml TNF-α to establish an inflammatory injury model of pneumonia. LncRNA PFAL or miR-18a was up- or down-regulated in the WI-38 cells by transfection procedure. Cell viability was assessed using CCK-8 assay, while the rate of cell apoptosis was measured by utilizing flow cytometry. The mRNA expression levels of lncRNA PFAL, miR-18a, apoptosis-related and JNK pathway genes were determined with RT-qPCR. Moreover, the production of inflammatory cytokines such as IL-6 and MCP-1 were detected by using Western blot analysis.Results: The results indicated that cell viability was significantly (P&lt;0.05) reduced, while the rate of cell apoptosis was increased in the TNF-α-induced WI-38 cells. Also, TNF-α treatment enhanced the expression of inflammatory cytokines that included IL-6 and MCP-1 in WI-38 cells. Overexpression of PFAL suppressed the injury induced by TNF-α and miR-18a was positively regulated by PFAL. Moreover, the inhibition of miR-18a weakens the effect of PFAL overexpression in TNF-α-induced cell injury. Furthermore, PFAL and miR-18a were involved in the regulation of JNK pathway.Conclusion: Overexpression of PFAL suppresses TNF-α-induced WI-38 cell injury by up-regulating miR-18a via the inactivation of JNK signaling pathway. Keywords: Inflammation, JNK pathway, miR-18a, PFAL, Pneumonia, TNF-

Three Dimensional Cell Culture: A Window into Transport of Nanomedicine in Tumor Tissue.

Recent growth in nanotechnology has been accelerating the identification and evaluation of new drug candidates. The development, optimization of nanomedicine and preclinical drug screening is critical but long and expensive. These studies are challenging due to the lack of test platforms that can incorporate sufficient human-relevant physiological complexity for reliable and standardized prediction. Current preclinical models based on animals are expensive and has poor predictivity due to the variety of animals and limitation of imaging technologies. Two-dimensional (2D) cell cultures used in the preclinical phase drug screening cannot adequately restore original cellular behaviors to nanomedicine in three-dimensional (3D) tissues. 3D cell culture models with the ability to independently manipulate microenvironmental factors can be used as a platform, to explore fundamental biological response to novel therapeutic nanoparticles. Transport of nanomedicine through solid tumors can be adequately evaluated in specially prepared 3D cell culture as platform. This is important for validating drug doses and administration regimens required to achieve desired therapeutic effects. In coupling with Monte-Carlo sampling and analysis of conditioned microenvironment, the standardized and uniform-sized liver tumor spheroids culture model in Inverted Colloidal Crystal (ICC) scaffolds can be used to quantitatively identify or validate predictive nanoparticle (NP) transport, while transparency of the platform allowed convenient real-time monitoring with high resolution. This dissertation established the experimental and conceptual framework for quantitative evaluation of NP transport in the tumor tissue ex vivo as a part of drug discovery, and explored a new opportunity of carbon nanotubes as a promising nano-sized carrier for drug delivery. Beside, this platform has been improved to develop patient/disease-specific model for individualized study of drug safety and efficacy or drug–drug interactions with 3D stem cell culture. In this part of dissertation, ICC scaffolds with uniform, controllable porous structure combined with a layer-by-layer (LBL) bone mimetic modification technique served as a platform for engineered stem cells. Overall, this dissertation introduces a promising and standardized 3D cell culture platform as a window to fundamental understanding of nanomedicine, as well as a practical and valuable tool for drug discovery regarding drug delivery and transport through complex 3D tissues.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/120907/1/yichunw_1.pd

Retinal oscillations carry visual information to cortex

Thalamic relay cells fire action potentials that transmit information from retina to cortex. The amount of information that spike trains encode is usually estimated from the precision of spike timing with respect to the stimulus. Sensory input, however, is only one factor that influences neural activity. For example, intrinsic dynamics, such as oscillations of networks of neurons, also modulate firing pattern. Here, we asked if retinal oscillations might help to convey information to neurons downstream. Specifically, we made whole-cell recordings from relay cells to reveal retinal inputs (EPSPs) and thalamic outputs (spikes) and analyzed these events with information theory. Our results show that thalamic spike trains operate as two multiplexed channels. One channel, which occupies a low frequency band (<30 Hz), is encoded by average firing rate with respect to the stimulus and carries information about local changes in the image over time. The other operates in the gamma frequency band (40-80 Hz) and is encoded by spike time relative to the retinal oscillations. Because these oscillations involve extensive areas of the retina, it is likely that the second channel transmits information about global features of the visual scene. At times, the second channel conveyed even more information than the first.Comment: 21 pages, 10 figures, submitted to Frontiers in Systems Neuroscienc

Particle Swarm Algorithm to Optimize LSTM Short-Term Load Forecasting

Accurate load forecasting is of great significance for national and grid planning and management. In order to improve the accuracy of short-term load forecasting, an LSTM prediction model based on particle swarm optimization (PSO)algorithm is proposed. LSTM has the characteristics of avoiding gradient disappearance and gradient explosion, but there is a problem that parameters are difficult to select. Therefore, particle swarm optimization algorithm is used to help it select parameters. The experimental results show that the optimized LSTM has higher prediction accuracy

SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenes

Multi-object tracking in sports scenes plays a critical role in gathering players statistics, supporting further analysis, such as automatic tactical analysis. Yet existing MOT benchmarks cast little attention on the domain, limiting its development. In this work, we present a new large-scale multi-object tracking dataset in diverse sports scenes, coined as \emph{SportsMOT}, where all players on the court are supposed to be tracked. It consists of 240 video sequences, over 150K frames (almost 15\times MOT17) and over 1.6M bounding boxes (3\times MOT17) collected from 3 sports categories, including basketball, volleyball and football. Our dataset is characterized with two key properties: 1) fast and variable-speed motion and 2) similar yet distinguishable appearance. We expect SportsMOT to encourage the MOT trackers to promote in both motion-based association and appearance-based association. We benchmark several state-of-the-art trackers and reveal the key challenge of SportsMOT lies in object association. To alleviate the issue, we further propose a new multi-object tracking framework, termed as \emph{MixSort}, introducing a MixFormer-like structure as an auxiliary association model to prevailing tracking-by-detection trackers. By integrating the customized appearance-based association with the original motion-based association, MixSort achieves state-of-the-art performance on SportsMOT and MOT17. Based on MixSort, we give an in-depth analysis and provide some profound insights into SportsMOT. The dataset and code will be available at https://deeperaction.github.io/datasets/sportsmot.html