Inclusion and Equity Committee Diverse Recruitment Task Force 2 “Current University Libraries and UNLV Practices”

The Diverse Recruitment Task Force 2 was charged with reviewing current UNLV and UNLV University Libraries best practices and making recommendations to recruit and hire faculty and staff from underrepresented groups. This report is organized into several sections. First, the task force offers specific recommendations for classified staff as the hiring process for classified staff is so different from the process for academic and administrative faculty. Second, the task force would like to point out that if it is the goal of the Libraries to have a staff that more closely resembles the local student population, then the Libraries should focus on local student and staff populations for recruitment and hiring. Finally, the task force offers recommendations that may improve the processes of recruiting, hiring, and retaining academic and administrative faculty

Efficient architecture for discrete wavelet transform using daubechies

Thesis (M.Eng., Electrical Engineering)--Prince of Songkla University, 201

Backdoor Attack with Mode Mixture Latent Modification

Backdoor attacks become a significant security concern for deep neural networks in recent years. An image classification model can be compromised if malicious backdoors are injected into it. This corruption will cause the model to function normally on clean images but predict a specific target label when triggers are present. Previous research can be categorized into two genres: poisoning a portion of the dataset with triggered images for users to train the model from scratch, or training a backdoored model alongside a triggered image generator. Both approaches require significant amount of attackable parameters for optimization to establish a connection between the trigger and the target label, which may raise suspicions as more people become aware of the existence of backdoor attacks. In this paper, we propose a backdoor attack paradigm that only requires minimal alterations (specifically, the output layer) to a clean model in order to inject the backdoor under the guise of fine-tuning. To achieve this, we leverage mode mixture samples, which are located between different modes in latent space, and introduce a novel method for conducting backdoor attacks. We evaluate the effectiveness of our method on four popular benchmark datasets: MNIST, CIFAR-10, GTSRB, and TinyImageNet

An Expert System for Local Flood Response Coordination and Training

Flood response is an essential component of flood management to rescue people, reduce property loss, and limit the impact to the environment. Effective flood response depends on a sound coordination structure with unified responsibilities, smooth communications, and scalable response plans. An efficient coordination system, including command and management structures, is built on a thorough understanding of the responsibilities and actions of each role for delivering the response core capabilities. Collecting, sharing, using, and handling the knowledge require great efforts in knowledge management. To further enhance such efforts, an expert system for local flood response coordination and training (LFRS) was developed and introduced in this paper. LFRS can help emergency managers construct scalable, flexible, and adaptable coordination structures and support educating flood response entities, such as individuals, communities, nongovernmental organizations, private sector entities, and local governments. The output of the prototype expert system contains two CSV formatted reports as well as prompt screens. The operational structure report hierarchically depicts the crisscross linkages among all responders, their primary functions, and contact information. Another report summarizes the responsibilities and actions of a certain role of flood responders from commanders to individuals

Performance Regulation of Thieno[3,2-b]benzothiophene π-Spacer-Based D-π-A Organic Dyes for Dye-Sensitized Solar Cell Applications: Insights From Computational Study

Dye-sensitized solar cells (DSSCs) have been widely investigated; however, the development of promising dye sensitizers is still appealing. In this work, we perform a detailed theoretical search for high-efficiency D-π-A organic dyes using density functional theory and time-dependent density functional theory calculations. Specifically, we perform geometric optimization, and electronic structure and absorption spectra calculations for isolated dyes for two thieno[3,2-b]benzothiophene π-spacer-based D-π-A organic dyes SGT129 and SGT130, which show significant efficiency difference, before and after binding to a TiO2 semiconductor. The calculation results reveal that the coplanar configuration between the electron donor and the π-spacer can enhance electronic communication efficiently, thus facilitating intra-molecular charge transfer from the electron donor to the acceptor groups in SGT130. The absorption spectrum of SGT130 broadens and is red-shifted owing to the decreased bandgap. The higher light-harvesting efficiency, favorable intra-molecular charge transfer, larger shift of the conduction band edge in the TiO2 semiconductor, and slower charge recombination between the injected electrons in the TiO2 conduction band and the electrolyte explain the superior efficiency of SGT130 over that of SGT129. Using SGT130 as the reference dye, we further design four novel dyes 1–4 by modifying the π-spacer with electron-rich and electron-withdrawing moieties. Judging from the theoretical parameters influencing the short-circuit current and open-circuit voltage, we found that all dyes would perform better than SGT130 in terms of the favorable interfacial charge transfer (ICT) and light-harvesting efficiency, as well as the larger shift of the TiO2 conduction band edge. Our theoretical research is expected to provide valuable insights into the molecular modification of TBT-based D-π-A organic dyes for DSSC applications

PPARα: A potential therapeutic target of cholestasis

The accumulation of bile acids in the liver leads to the development of cholestasis and hepatocyte injury. Nuclear receptors control the synthesis and transport of bile acids in the liver. Among them, the farnesoid X receptor (FXR) is the most common receptor studied in treating cholestasis. The activation of this receptor can reduce the amount of bile acid synthesis and decrease the bile acid content in the liver, alleviating cholestasis. Ursodeoxycholic acid (UDCA) and obeticholic acid (OCA) have a FXR excitatory effect, but the unresponsiveness of some patients and the side effect of pruritus seriously affect the results of UDCA or OCA treatment. The activator of peroxisome proliferator-activated receptor alpha (PPARα) has emerged as a new target for controlling the synthesis and transport of bile acids during cholestasis. Moreover, the anti-inflammatory effect of PPARα can effectively reduce cholestatic liver injury, thereby improving patients’ physiological status. Here, we will focus on the function of PPARα and its involvement in the regulation of bile acid transport and metabolism. In addition, the anti-inflammatory effects of PPARα will be discussed in some detail. Finally, we will discuss the application of PPARα agonists for cholestatic liver disorders

Matching dependence-related queries in the system dependence graph.

In software maintenance and evolution, it is common that develop-ers want to apply a change to a number of similar places. Due to the size and complexity of the code base, it is challenging for develop-ers to locate all the places that need the change. A main challenge in locating the places that need the change is that, these places share certain common dependence conditions but existing code searching techniques can hardly handle dependence relations satisfactorily. In this paper, we propose a technique that enables developers to make queries involving dependence conditions and textual condi-tions on the system dependence graph of the program. We carried out an empirical evaluation on four searching tasks taken from the development history of two real-world projects. The results of our evaluation indicate that, compared with code-clone detection, our technique is able to locate many required code elements that code-clone detection cannot locate, and compared with text search, our technique is able to effectively reduce false positives without losing any required code elements

First realization of macroscopic Fourier ptychography for hundred-meter distance sub-diffraction imaging

Fourier ptychography (FP) imaging, drawing on the idea of synthetic aperture, has been demonstrated as a potential approach for remote sub-diffraction-limited imaging. Nevertheless, the farthest imaging distance is still limited around 10 m even though there has been a significant improvement in macroscopic FP. The most severely issue in increasing the imaging distance is FoV limitation caused by far-field condition for diffraction. Here, we propose to modify the Fourier far-field condition for rough reflective objects, aiming to overcome the small FoV limitation by using a divergent beam to illuminate objects. A joint optimization of pupil function and target image is utilized to attain the aberration-free image while estimating the pupil function simultaneously. Benefiting from the optimized reconstruction algorithm which effectively expands the camera's effective aperture, we experimentally implement several FP systems suited for imaging distance of 12 m, 90 m, and 170 m with the maximum synthetic aperture of 200 mm. The maximum imaging distance and synthetic aperture are thus improved by more than one order of magnitude of the state-of-the-art works with a fourfold improvement in the resolution. Our findings demonstrate significant potential for advancing the field of macroscopic FP, propelling it into a new stage of development