118 research outputs found
Causal effects of stock market on corporate decisions, disclosure mandates, and informational feedback
No full textThe accounting literature has long recognized that maintaining or increasing stock prices isone of the most important factors for managers’ reporting and disclosure decisions, how-ever, the extant literature mainly examines the reverse causality (i.e., the effect of voluntaryearnings forecasts or earnings management on stock prices), due to endogeneity concerns.Chapter 1 examines managers’ decisions on information disclosure in response to stock-underpricing. Using mutual fund fire sales as an exogenous source of market-disruption,we find some managers increase frequency/precision of earnings guidance in response tostock-underpricing. Other managers, especially those in firms with poorer performanceand more short-term-oriented investors, engage in accrual-based earnings management.The passage of SOX, however, affects firms’ response to fire sales, with firms increasingtheir reliance on guidance as opposed to earnings management. The shift is associatedwith faster post-fire-sales price recovery, suggesting that enhancing information disclosurerather than information manipulation is effective in correcting stock-underpricing.The SEC promulgated Regulation Fair Disclosure (Reg FD) to establish a “level play-ing field”for investors through prohibiting the use of selective disclosure. In Chapter 2, weuse Reg FD as a plausibly natural experiment to evaluate links between disclosure, privateinformation production, and real efficiency. We find that the rule has an adverse impact onprice informativeness, investment-to-price sensitivity, and firm valuewith stronger effectsfor firms with greater prior reliance on selective disclosure. Analyst forecast quality alsoappears to decline following the rule change. Interestingly, the impact of Reg FD on priceinformativeness and the sensitivity of investment-to-price diminishes over time, while the deterioration in analyst forecasts tends to persist. Collectively, the results highlight unin-tended consequences of Reg FD in inhibiting private information acquisition and, thereby,the informational feedback from stock prices to real decisions.Ph.D.Includes bibliographical referencesby Jinglin Jian
Peptide-modified surfaces for enzyme immobilization.
No full textBACKGROUND: Chemistry and particularly enzymology at surfaces is a topic of rapidly growing interest, both in terms of its role in biological systems and its application in biocatalysis. Existing protein immobilization approaches, including noncovalent or covalent attachments to solid supports, have difficulties in controlling protein orientation, reducing nonspecific absorption and preventing protein denaturation. New strategies for enzyme immobilization are needed that allow the precise control over orientation and position and thereby provide optimized activity. METHODOLOGY/PRINCIPAL FINDINGS: A method is presented for utilizing peptide ligands to immobilize enzymes on surfaces with improved enzyme activity and stability. The appropriate peptide ligands have been rapidly selected from high-density arrays and when desirable, the peptide sequences were further optimized by single-point variant screening to enhance both the affinity and activity of the bound enzyme. For proof of concept, the peptides that bound to β-galactosidase and optimized its activity were covalently attached to surfaces for the purpose of capturing target enzymes. Compared to conventional methods, enzymes immobilized on peptide-modified surfaces exhibited higher specific activity and stability, as well as controlled protein orientation. CONCLUSIONS/SIGNIFICANCE: A simple method for immobilizing enzymes through specific interactions with peptides anchored on surfaces has been developed. This approach will be applicable to the immobilization of a wide variety of enzymes on surfaces with optimized orientation, location and performance, and provides a potential mechanism for the patterned self-assembly of multiple enzymes on surfaces
G-quadruplex: a multifunction DNA structure with great potential
No full textG-quadruplex DNA has great potential for use in many biochemical applications. In the field of nucleic acid nanotechnology, G-quadruplexes can facilitate chemical reactions, mimicking the function of an enzyme when bound to hemin, collectively referred to as G-quadruplex/hemin (abbv. GQH). However, in many published studies, GQH shows unstable and inconsistent catalytic activities, especially regarding the suicide inactivation of GQH, often observed when using it as a peroxidase replacement in reactions. The unstable catalysis of GQH limits its biotechnological applications. Here, we report how varied environmental conditions and the use of different substrates influence inactivation kinetics of GQH, while posing potential solutions to improve the catalytic stability of GQH over long reaction periods. These solutions include optimization of pH condition, protection of hemin through the utilization of polyhistidine chains, and generation of H2O2 utilizing enzyme cascades. Specifically in a cascade reaction of GOx – GQH, GOx converts glucose to H2O2, which can then be utilized by GQH for oxidation of Amplex Red, rather than using high concentration of H2O2. The residual activity of GQH is more stable over time in this cascade, presumably due to the low intermediate H2O2 concentration reducing oxidative damage done to hemin. We also report and confirm previously demonstrated results of protection of hemin from damage through utilization of polypeptide-DNAzyme aggregates. Interestingly, we demonstrate a trade-off in overall initial reaction rate with long-term catalytic activity. That is, unprotected GQH had higher initial velocities at the reaction onset than protected complexes, but protected complexes significantly outperformed the unprotected DNAzyme after only 15 minutes of incubation with H2O2. Overall, our results characterize the inherent inactivation kinetics of the peroxidase-mimicking GQH DNAzyme caused by product color depletion and hemin inactivation in the presence of H2O2 across a variety of environmental conditions. We also explored potential options as detailed above to improve the stability of GQH catalysis. With these results, we hope to provide potentially useful kinetic information for future applications of GQH in biomimetic systems, DNA-based nanotechnologies, and other future applications. We also report a potentially useful future application of the GQ structure in the assembly of DNA nanowires for the efficient transfer of photon energy across nanodevices.Presented at the annual Celebration of Undergraduate Research and Creative Activity while the author was an undergraduate student at Rutgers University-Camden
Genotypes of SNPs of Key Genes Regulate Susceptibility and Drug Sensitivity to Neovascular AMD
No full textAge-related macular degeneration (AMD), particularly its neovascular form, stands as a leading cause of blindness globally, with its prevalence in our country on a steady rise. This underscores the critical impact of neovascular AMD (nAMD) management on patient quality of life and societal burden. Current optimal treatments hinge on anti-vascular endothelial growth factor (anti-VEGF) therapies, though their efficacy varies across different drugs and individuals, highlighting the importance of precise drug selection in clinical outcomes. Research suggests that factors such as baseline vision, age, disease duration, lesion size, central retina thickness, neovascularization type, and demographic differences influence nAMD prognosis. In addition, Genetic predispositions and environmental factors also contribute to nAMD development, with increasing focus on molecular genetics to understand treatment responses. Single nucleotide polymorphisms (SNPs), as primary genomic variations, are linked to disease susceptibility and treatment sensitivity, including in nAMD. This study posits that SNP interactions within human genes may influence anti-VEGF drug’s efficacy, supported by evidence on the distinct molecular functions and pathways of VEGF family genes. We aimed to analyze nAMD susceptibility and sensitivity to VEGF inhibitors and explore gene polymorphisms at the molecular level, demonstrating that SNP presence could elucidate variances in anti-VEGF drug performance, thereby optimizing clinical drug selection and minimizing treatment failures. Given the high costs associated with anti-VEGF therapies, adopting a precision medicine approach, guided by genetic insights, is crucial for economic and clinical efficiency. This study provides a foundation for personalized treatment strategies, efficacy monitoring, individual variability assessment, biologic development, and etiological analysis in nAMD management. We investigated the presence of SNPs in nAMD patients, examining the correlation between gene SNPs, genetic susceptibility, and anti-VEGF drug efficacy. Selecting 30 SNP sites from 14 genes associated with nAMD, we analyzed their contribution to disease occurrence and treatment response, revealing significant SNP-related individual differences in drug sensitivity and cross-efficacy. Our research encompasses three main aspects: firstly, reviewing pathogenic factors of nAMD and anti-VEGF drug effects; secondly, conducting a retrospective study comparing the effectiveness and safety of conbercept and ranibizumab; thirdly, analyzing the association between gene SNPs and nAMD etiology and drug efficacy. Significant genotype differences were found, underscoring the potential of genotype-based personalized treatments for enhanced clinical outcomes in nAMD management
The jingling Geordie: community arts and the regional culture of the North East of England
No full textIn the light of the massive economic and social changes which have affected the North East of England over the last 25 years, the author assesses the vitality of the indigenous culture and reflects upon current cultural trends and the North East’s future, particularly in relation to a regional Europe. He traces the folk-tradition of the region and looks at ways in which this can be drawn upon to develop a meaningful link between past and present. He looks closely at the changing nature of class-relationships in the North East and reflects upon how a valid local culture can survive in a multi-cultural society. He draws upon his own extensive experience in Community Arts, looking at definitions of the term in the new political climate and arguing for its positive contribution to the cultural debate. He dwells on the issue of regionalism and devolution in a new Europe, comparing the situation in the North East of England with political and cultural changes in Scotland and other parts of the United Kingdom
Threshold voltage reliability and trap modelling in silicon carbide MOS capacitor under high temperature
No full textTo extend Moore’s law, silicon carbide devices attend the researcher’s attention due to their irreplaceable advantages such as high critical breakdown electrical field, wide bandgap and excellent thermal conductivity without sacrificing too much charge carrier mobility. However, the defects on the SiC-oxide interface degrades the performance of the device and even get worse at high temperature, such as the threshold voltage shifting problems, limiting the design of the integrated circuits. The thesis models, characterise, analyses, measures and extracts the traps of SiC MOSCAP, to understand the trapped charge transportation and unreliability mechanism under high temperature.Effectively using SiC materials necessitates the need to understand the physical properties itself. Due to the large bandgap, the inversion layer cannot be observable in low frequency C-V measurement. The electrical field, space charge region, surface potential and C-V curve in SiC devices all differ from Si devices. More importantly, the trapped charges fluctuate the surface potential of the SiC devices. To give insight into the mechanism governing the trapped charges, the mathematical solution of the trapped charges in the whole bandgap is solved.To be specific, the trap behaviour at a single energy level is then followed. A nonzero transient current is generated due only to the capture and release of the trapped charges when the equilibrium condition is broken. The trapped charges with high energy are thermalized and an equivalent admittance is obtained which further be split into a capacitance and a conductance.Rising temperature activates the dopant atoms that are not ionised, and the Fermi level shifts towards the midband. The variation of equivalent circuit components and physical parameters responds to the temperature. High temperature expands the SiC crystal and the trapped charges are easy to receive energy from phonons so that the interaction between traps and the conduction band is enhanced and more empty states are waiting for the recombination of the charge carriers.Electrical Engineerin
Volumetric Method of Moments: A Numerical Tool for High Frequency Problems Analysis
No full textIn this thesis a Volumetric Method of Moments (V-MoM) is developed to analyse accurately, and ease the design of small size lens antennas, and to estimate the power emitted by warm bodies constituted by realistic materials, and having arbitrary geometries. hanks to the application of the volume equivalence theorem and the use of a structured mesh, this method can be used in a design loop efficiently, since different geometries can be simulated with the sameevaluation of the projections, and the specific material arrangements are added at a negligible cost. Therefore, at every design iteration, differently from other integral equation methods, only the linear system has to be solved. Moreover, thanks to the use of a uniform sampling, a convolutional structure is obtained, implying that only a reduced number of projections are sufficient to characterize the entire matrix, reducing significantly the memory requirements, and allowing the solution of large scale systems. The linear system is then solved with an iterative solver, that, thanks to the convolutional properties, can be accelerated by fast matrix-vector products by using Fast Fourier Transform (FFT). The method is validated by studying the field scattered by a homogeneous and multilayer dielectric sphere, proving an accuracy within the discretizationtolerance, and the capability of handling inhomogeneous structures.A Graphical User Interface (GUI) based on the presented method has been developed, with the aim of easing and assisting the user experience on the electromagnetic analysis. The GUI allows to simulate complexgeometries combining elementary shapes, characterized by arbitrary materials, and excited by either plane waves or discrete ports. The solution can be post-processed in terms near-fields, far-fields, and network quantities. A representation in terms of impressed currents and incident voltage has been formulated to represent the incoherent radiometric sources in the V-MoM, used to analyse the power emitted by lossy semiconductors, characterized by a Drude’s dispersion for the conductivity. An experimental setup to verify the numerical and analytical model is then designedElectrical Engineerin
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning
No full textFederated Class Continual Learning (FCCL) merges the challenges of distributed client learning with the need for seamless adaptation to new classes without forgetting old ones. The key challenge in FCCL is catastrophic forgetting, an issue that has been explored to some extent in Continual Learning (CL). However, due to privacy preservation requirements, some conventional methods, such as experience replay, are not directly applicable to FCCL. Existing FCCL methods mitigate forgetting by generating historical data through federated training of GANs or data-free knowledge distillation. However, these approaches often suffer from unstable training of generators or low-quality generated data, limiting their guidance for the model. To address this challenge, we propose a novel method of data replay based on diffusion models. Instead of training a diffusion model, we employ a pre-trained conditional diffusion model to reverse-engineer each class, searching the corresponding input conditions for each class within the model’s input space, significantly reducing computational resources and time consumption while ensuring effective generation. Furthermore, we enhance the classifier’s domain generalization ability on generated and real data through contrastive learning, indirectly improving the representational capability of generated data for real data. Comprehensive experiments demonstrate that our method significantly outperforms existing baselines. Code is available at https://github.com/jinglin-liang/DDDR. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025
A quantitative study of the effects of solvent properties on crystal growth morphology
No full textIn this thesis, the effects of solvent properties on crystal formations are studied. The first section focuses on giving the reader an overview. It explains the context and the likely industrial application of the study outcome. In the second part, the author approaches the topic quantitatively by introducing the theoretical foundations for the significance of solvent selection. The reader will be able to walk through a few mathematical models that were built from previous scientific research and then get a general idea of how and why each factor matters from a mathematical perspective. To validate the mathematical prediction, experimental observations from various research labs, as well as the results obtained by the Smith College Pfizer Design team, are presented. They both demonstrate good agreements with the theoretical foundations discussed in the preceding sections. Both the theoretical discussions and the experimental interpretations have formed solid foundations for the author to design a recipe that can serve as a guideline for engineers to follow when making solvent selections before starting a crystallization. The author lists step by step recommendations which, if followed carefully, would facilitate the selection of good solvents, and ultimately optimize the formation process of good crystals. As the first step of all crystallization processes, solvent selection is critical for improving the operating efficiency. Therefore, the author is hoping that, after reading this thesis, the reader will achieve a better understanding of the following three aspects: 1) why solvent selection matters; 2) the important parameters associated with the process; 3) most importantly, a protocol to reference when making decisions
Co-aggregation studies of nucleic acid nanostructures with tetracycline molcules
No full textBiological systems have evolved complex macromolecular nanostructures to carry out cellular functions with high specificity and efficiency, such as mitochondrial electron transport chains, polymerase and transcription cofactors and light-harvesting antenna in photosynthesis. These organized nanostructures are formed inside cells by spontaneous self-assembly of individual molecular components. In the past few decades, researchers have taken advantage of the self-assembly of nucleic acids to construct various 1D – 3D nanostructures. Self-assembled DNA nanostructures have an inherent advantage of generating programmable nanostructures with controllable parameters of dimension, structural hierarchy and nanometer precision, which can be used for mediating drug release. In this thesis, we have studied single- or double-stranded DNA molecules for forming nanoparticles with minocycline (MH) in the presence of magnesium ions (bridging effect) and π-π stacking interaction. We evaluated multi-dimensional DNA nanostructures (e.g. ssDNA, dsDNA, DNA origami) to load and release MH with sufficient dose during an interval of two weeks. The entrapment efficiency of MH and iii DNA was found to depend on the Mg2+ concentration, DNA length, and types of DNA (i.e. as a function of nitrogen bases). The molecule ssDNA with length > 11-nucleotide (nt) was found to form aggregates with MH in the presence of Mg2+. The titration of Mg2+ concentration showed that the maximum particle formation yield was reached at ~ 4 mM. ssDNA also showed higher dimensional aggregate formation yield than dsDNA, due to the flexible structure of ssDNA allowing more aggregation with MH and Mg2+. In collaboration with Drexel University, we have applied DNA-Mg2+-MH particles to agarose gel encapsulation and release for maintaining the activity of MH during a long period release. This DNA-mediated MH release could be potentially used in the future spinal cord therapy for localized delivery of MH at the injury site.M.S.Includes bibliographical referencesby Nouf Alzahran
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