Best Practices to Increase Efficacy of Graduate School Admissions Communications at Clark University

Within the period of time that a graduate student deposits and subsequently arrives at their academic institution, receiving timely information is important for their preparation. This process has been deemed by the Deans of the Enterprise Schools at Clark University as one that needs further investigation. As such, this Capstone looks at the array of communication that goes out to each graduate student during this four-month period. The purpose of examining this communication is to analyze its effectiveness in engaging students. To analyze the effectiveness of this communication, surveys were distributed to current students in these schools to gather data surrounding their experience after applying to Clark. In addition to looking at Clark University’s current process, we conducted an analysis of trends and best practices from colleges and universities across the country. Based on findings from this research and our firsthand interviews of the aforementioned Deans and involved staff members, we have provided recommendations to improve this process. Ultimately, in order to improve student engagement our group has created recommendations that could improve some of the challenges in engaging and retaining students during this period of time

Facile Fabrication of a Hierarchical Superhydrophobic Coating with Aluminate Coupling Agent Modified Kaolin

A superhydrophobic coating was fabricated from the dispersion of unmodified kaolin particles and aluminate coupling agent in anhydrous ethanol. Through surface modification, water contact angle of the coating prepared by modified kaolin particles increased dramatically from 0° to 152°, and the sliding angle decreased from 90° to 3°. Scanning electron microscopy was used to examine the surface morphology. A structure composed of micro-nano hierarchical component, combined with the surface modification by aluminate coupling agent which reduced the surface energy greatly, was found to be responsible for the superhydrophobicity. The method adopted is relatively simple, facile, and cost-effective and can potentially be applied to large water-repellent surface coatings

Understanding PRRSV Infection in Porcine Lung Based on Genome-Wide Transcriptome Response Identified by Deep Sequencing

Porcine reproductive and respiratory syndrome (PRRS) has been one of the most economically important diseases affecting swine industry worldwide and causes great economic losses each year. PRRS virus (PRRSV) replicates mainly in porcine alveolar macrophages (PAMs) and dendritic cells (DCs) and develops persistent infections, antibody-dependent enhancement (ADE), interstitial pneumonia and immunosuppression. But the molecular mechanisms of PRRSV infection still are poorly understood. Here we report on the first genome-wide host transcriptional responses to classical North American type PRRSV (N-PRRSV) strain CH 1a infection using Solexa/Illumina's digital gene expression (DGE) system, a tag-based high-throughput transcriptome sequencing method, and analyse systematically the relationship between pulmonary gene expression profiles after N-PRRSV infection and infection pathology. Our results suggest that N-PRRSV appeared to utilize multiple strategies for its replication and spread in infected pigs, including subverting host innate immune response, inducing an anti-apoptotic and anti-inflammatory state as well as developing ADE. Upregulation expression of virus-induced pro-inflammatory cytokines, chemokines, adhesion molecules and inflammatory enzymes and inflammatory cells, antibodies, complement activation were likely to result in the development of inflammatory responses during N-PRRSV infection processes. N-PRRSV-induced immunosuppression might be mediated by apoptosis of infected cells, which caused depletion of immune cells and induced an anti-inflammatory cytokine response in which they were unable to eradicate the primary infection. Our systems analysis will benefit for better understanding the molecular pathogenesis of N-PRRSV infection, developing novel antiviral therapies and identifying genetic components for swine resistance/susceptibility to PRRS

The impact of the winter North Atlantic Oscillation on the frequency of spring dust storms over Tarim Basin in northwest China in the past half-century

The relationship between the frequency of spring dust storms over Tarim Basin in northwest China and the winter North Atlantic Oscillation (NAO) is investigated by using the observed dust storm frequency (DSF) and the 10 m wind velocity at 36 stations in Tarim Basin and the National Centers for Environment Prediction/National Center for Atmospheric Research reanalysis data for the period 1961–2007. The spring DSF (winter NAO) index shows a clear decreasing (increasing) linear trend over 1961–2007. The winter NAO correlates well with the subsequent spring DSF over Tarim Basin on both interannual and interdecadal time scales and its interannual to interdecadal variation plays an important role in the spring DSF. Two possible physical mechanisms are identified. One is related to the large scale anomalous circulations in spring in the middle to high troposphere modulated by the winter NAO, providing the background of dynamical conditions for the dust storm occurrences. The other is related to the shifts in the local horizontal sea level pressure (SLP) gradients and 10 m wind speed, corresponding to changes in the large scale circulations in spring. The decrease in the local 10 m wind speed due to the reduced horizontal SLP gradients over Tarim Basin during the strong winter NAO years contributes to the decline of the DSF in the subsequent spring

A Fault Feature Extraction Method Based on Improved VMD Multi-Scale Dispersion Entropy and TVD-CYCBD

In modern industry, due to the poor working environment and the complex working conditions of mechanical equipment, the characteristics of the impact signals caused by faults are often submerged in strong background signals and noises. Therefore, it is difficult to effectivelyextract the fault features. In this paper, a fault feature extraction method based on improved VMD multi-scale dispersion entropy and TVD-CYCBD is proposed. First, the marine predator algorithm (MPA) is used to optimize the modal components and penalty factors in VMD. Second, the optimized VMD is used to model and decompose the fault signal, and then the optimal signal components are filtered according to the combined weight index criteria. Third, TVD is used to denoise the optimal signal components. Finally, CYCBD filters the de-noised signal and then envelope demodulation analysis is carried out. Through the simulation signal experiment and the actual fault signal experiment, the results verified that multiple frequency doubling peaks can be seen from the envelope spectrum, and there is little interference near the peak, which shows the good performance of the method

A Fault Feature Extraction Method Based on Improved VMD Multi-Scale Dispersion Entropy and TVD-CYCBD

In modern industry, due to the poor working environment and the complex working conditions of mechanical equipment, the characteristics of the impact signals caused by faults are often submerged in strong background signals and noises. Therefore, it is difficult to effectivelyextract the fault features. In this paper, a fault feature extraction method based on improved VMD multi-scale dispersion entropy and TVD-CYCBD is proposed. First, the marine predator algorithm (MPA) is used to optimize the modal components and penalty factors in VMD. Second, the optimized VMD is used to model and decompose the fault signal, and then the optimal signal components are filtered according to the combined weight index criteria. Third, TVD is used to denoise the optimal signal components. Finally, CYCBD filters the de-noised signal and then envelope demodulation analysis is carried out. Through the simulation signal experiment and the actual fault signal experiment, the results verified that multiple frequency doubling peaks can be seen from the envelope spectrum, and there is little interference near the peak, which shows the good performance of the method

A Kitchen Standard Dress Detection Method Based on the YOLOv5s Embedded Model

In order to quickly and accurately detect whether a chef is wearing a hat and mask, a kitchen standard dress detection method based on the YOLOv5s embedded model is proposed. Firstly, a complete kitchen scene dataset was constructed, and the introduction of images for the wearing of masks and hats allows for the low reliability problem caused by a single detection object to be effectively avoided. Secondly, the embedded detection system based on Jetson Xavier NX was introduced into kitchen standard dress detection for the first time, which accurately realizes real-time detection and early warning of non-standard dress. Among them, the combination of YOLOv5 and DeepStream SDK effectively improved the accuracy and effectiveness of standard dress detection in the complex kitchen background. Multiple sets of experiments show that the detection system based on YOLOv5s has the highest average accuracy of 0.857 and the fastest speed of 31.42 FPS. Therefore, the proposed detection method provided strong technical support for kitchen hygiene and food safety