Determining the Effects of Thermal Decay on Pig Femur Bone Composition Through DNA Extraction and ATR FT-IR Spectroscopy

This research was designed to determine the effect of thermal decay on the chemical composition of pig femur bones. Two methods were utilized to observe the effect of thermal exposure on burnt samples: ATR FT-IR spectroscopy and DNA extraction with PCR quantitation. The former utilizes infrared spectroscopy with an attenuated total reflectance sampling method to measure a sample’s absorption of IR light. This allows for a better understanding of a material’s composition by providing information about its chemical bonds and functional groups. DNA extraction from samples can also provide information through PCR quantitation, in which the amount of genetic material present within a sample is amplified. It was hypothesized that as the temperature at which the samples were exposed increased, the bone composition would exhibit higher levels of decay due to dehydration, denaturation, and degradation of organic compounds. It was therefore expected that as temperature increased, a decrease would be observed in CO/P ratio calculated from ATR FT-IR peak intensities as well as the quantity of DNA able to be recovered through PCR. Four pig femur bones were utilized in this experiment and cut into three cross sections prior to burning. One cross section each from bones 1-3 were burned at three temperatures, ranging from 100˚ to 280˚C. Cross sections from Bone 4 were left untouched as unburned control samples. Powdered bone samples were collected from each cross section, which were then used for ATR FT-IR spectroscopy and DNA extraction. Both methods of information collection were completed successfully and indicated that an increase of temperature resulted in a slight increase in CO/P ratio and quantity of DNA extraction from 100˚C to 200˚C, before a significant decrease in each from 200˚C to 280˚C. It was also found through analysis of control samples that natural variation has a large effect on the data and should be minimized in future studies. Natural variation acts as a random variable, and when controlled, will allow for a greater understanding of the effects of temperature on the samples

America’s Criminal Justice System Interaction, Housing Opportunities, and Job Sustainability: Perceptions from Residents of the Greater New Haven Area

This study explored the perceived relationship between criminal justice system (CJS) involvement and housing and employment outcomes among residents of the Greater New Haven area. Prior research has demonstrated that individuals with criminal records or histories of incarceration often face significant obstacles when attempting to secure stable housing or employment. Through qualitative analysis of survey responses from 47 participants, this study highlights how increased contact with the justice system is perceived to negatively impact job sustainability and housing opportunities, while limited or no contact appears to serve as a form of privilege. Using an inductive coding method, recurring themes were identified and analyzed to examine how individuals with different levels of CJS involvement perceive the long-term consequences of legal system contact. The findings emphasize the compounding nature of these challenges, particularly for low-income residents, and ultimately contribute to broader conversations on the structural barriers that persist in reentry and poverty-alleviation efforts. To conclude, this research emphasizes the need for equitable policy reforms that address housing and employment barriers tied to criminal justice involvement

Soil Discrimination by Particle-Correlated Raman Spectroscopy

Forensic soil analysis has had a rich history of providing valuable information for investigating criminal events. However, many modern forensic laboratories have stopped performing this analysis due to the perception that it is either too time-consuming or labor­ intensive. Further complicating the issue is the view that many forensic soil analytical methods are subjective due to their reliance on feature comparisons. Particle Correlated Raman Spectroscopy (PCRS) is a new method that was proposed to address both concerns by providing automated and objective analysis and comparison of sample mixtures. PCRS is an integrated technique that combines automated image analysis with Raman spectroscopy. Particle imaging determines particle size and shape distributions for each component in a sample, yielding detailed morphological information (e.g., circularity, area). At the same time, Raman spectroscopy can probe the molecular chemistry of specific particles of interest. Particle size distributions can be generated for the entire sample or for each mineral present, along with quantitative information on the relative amount of each type of particle. Mineral counts and morphological properties are used as the basis for the classification and comparison of Raman-identified particles. The discrimination potential of PCRS was explored using various statistical methods from data collected from topsoil samples collected in triplicate from 30 different locations in the Northeast United States. Following analysis of the particle sets within each sample, applicable mineral sets were subject to statistical analysis via Analysis of Variance (ANOVA) and Kruskal-Wallis. While the process was plagued with technological obstacles during data collection, physical and chemical data were still collected for all samples and statistical analysis showed promising results. Ultimately, this research provides statistical evidence for the discriminatory power of minerals and their morphologies for the classification and source identification of soil samples

Information Content of an Open Limit-Order Book: Indian Evidence

Using the 5-year period (2014-18) limit-order book and trade book data from NSE, this paper investigates the contribution of an open limit-order book towards price discovery and market efficiency. In particular, the paper examines two interesting questions: (a) the information content of the limit-order book beyond the best prices and (b) the order submission choices of informed traders. The results indicate that the deeper levels of the order book significantly contribute to short-term return predictability, even after controlling for the return autocorrelations, volume, and trade imbalances. Furthermore, this return predictability is time-varying and relatively high around lower quantiles of the return distribution. There is evidence to suggest that informed trading is more pronounced during the environments characterized by low liquidity and high uncertainty. The information share (Hasbrouck, 1995) and component share (Gonzalo & Granger, 1995) measures show that, out of the total contribution of the limit-order book to price discovery, the deeper levels’ share is nearly 50%

Effects of Adhesives on the Subsequent Instrumental Analysis of Various Trace Evidence

A central pillar of forensic science is the proper collection and containment of evidence. Technicians at both crime scenes and within the labs are reliant on a variety of adhesives to accomplish this task. As collection devices, adhesives come into direct contact with evidence such as fibers and paint. This contact introduces a possible risk of either physical or chemical interference. Contamination may have dire consequences in the courtroom therefore, any area of risk must be investigated with the utmost sincerity. The idea that these adhesives may alter paint evidence, and paint evidence alone, during collection from a scene and subsequent storage has been codified into both NIST and SWGMAT standards. Neither committee, however, has concerns regarding adhesive use during fiber or other trace evidence collection and no articles have thus far been discovered that prove any chemical or physical interactions between trace evidence and adhesives. This thesis\u27 goal was to investigate if adhesives have a chemical or physical impact on the trace evidence, and whether these differences can be observed during laboratory examination. In this study, six distinct adhesives were utilized to test for their potential chemical or physical impacts on trace evidence. To simulate common trace evidence three diverse types of fiber evidence, as well as three different types of paint evidence were collected. All adhesive and evidence combinations were stored at four different storage intervals, 1 week, 4 weeks, 14 weeks, and 24 weeks and chemical and physical changes were documented by Fourier Transform Infrared Spectrophotometry (FTIR) using an Attenuated Total Reflectance (ATR) objective. The results showed that the rate of physical alterations and chemical contamination created two groups. One with a larger amount of both physical damage and chemical contamination: forensic tape, packing tape, and hinge lifters. The other group with less: gelatin lifters, sticky notes, and lint rollers. Overall, between the fiber and paint samples there does not seem to be an experimental reason why adhesives should not be used on paint trace evidence. These results could open the door for practitioners to use weaker adhesives for both collection and storage of trace paint evidence

Determination of Accuracy in Forensic Phenotyping With Implementation of Microspectrophotometry and SNP Testing

Forensic DNA phenotyping and single nucleotide polymorphisms (SNP) testing has been a recent tool practiced in the field of forensic science, especially for identification purposes. DNA phenotyping had drawn debate in terms of its legislation and use, as it is practiced more in private sectors compared to local, state and federal laboratories (Schneider et al., 2019). When looking at specific SNPs, some are better associated in accurately predicating phenotypes for hair and eye color than others. Microspectrophotometry was combined with SNP testing in this study to determine if there was an improved accuracy in determination of genetic hair color vs dyed hair samples. Forty-one samples comprised of European descent participants who selfidentified their hair color to be red, blond, brown or dyed red were collected and analyzed. SNP rs1805007 associated with the red hair phenotype and genotypes TT, CT and CC were examined, along with the various transmission spectra produced for each hair sample from a microspectrophotometer. Through the use of instrumentation and color examination, the phenotypic determination of hair was predicted using obtained data and compared amongst a SNP test. The SNP results, microspectrophotomoter spectra transmission results, microscopic images of each hair sample and the participant’s self-identification photograph were compared for phenotype prediction and classification accuracy

How Does Moral Hazard Impact Critical Market Banking Performance?

The degree to which financial institutions form expectations of policy intervention despite their own risk appetites lies at the heart of macrofinancial regulations such as the Dodd-Frank and Consumer Protection Acts. The effectiveness of these policies hinge on the assumption that large banks are the only banks that are too-big-to-fail (TBTF). However, alternative perspectives posit that banks may be too-complex-to-fail, regardless of their size. To remedy competing TBTF definitions, we propose a new criterion to identify potential TBTF banks by their relative involvement in so-called critical markets, considerate of both bank size and complexity. We estimate a restricted translog semiparametric smooth coefficient seemingly unrelated regressions model (SPSC SUR) wherein model elasticities are functions of nonperforming assets, a proxy for moral hazard, to derive nonperformance-adjusted returns-to-scale estimates for critical market banks from 2001 through 2023. Over our full sample, the median critical market bank tends to operate under increasing returns-to-scale while most critical market banks exhibit decreasing or constant returns-to-scale. Results taken over the past two decades suggest that most TBTF banks have exhausted their economies of scale concurrently alongside the shrinking competitive landscape

Total Factor Productivity (TFP) and Financial Markets

The dynamic interplay between real firms and the financial markets remains under continuous government scrutiny, reflecting the evolving diversity that accompanies the expansion of financial markets. Given the financial market\u27s critical role in capital provision, it is essential to understand how different funding relationships influence firm performance. This study focuses on A-share listed companies in China from 2013 to 2023, categorizing their funding relationships into two distinct types: net investment and net financing. The analysis reveals a significant dampening effect on Total Factor Productivity (TFP) associated with net investment-based funding relationships. Mechanistic investigations indicate that this suppression is due to the diversion of capital from core business activities towards net investment activities, ultimately hindering productivity. These findings offer valuable insights into the complex relationship between real firms and the financial markets, highlighting the varied mechanisms through which the financial markets can either enhance or impede firm value. Additionally, the study provides practical policy recommendations for regulatory authorities aimed at optimizing the real economy\u27s access to financial services by refining the funding relationships between real firms and the financial markets

Yemaya

Created 2025. This work of art is shells, epoxy, and mixed media on board. Yemaya, the orisha of the sea, considered a mother figure in Yoruba mythology.https://digitalcommons.newhaven.edu/digital-exhibits/1069/thumbnail.jp

Two General Data Protection Regulation (GDPR) Compliant Approaches to Scoring Firm Financial Frailty in Business Litigation

A litany of data artifacts, including the possibility of source data drift, lack of generalizability, and imprecise risk categories, all weaken—and may even impugn—estimates of a firm\u27s economic frailty when using the Altman Z-score as a formulaic measure of risk in business litigation. These limitations constitute potential veto points which may be exploited by opposing counsel in court proceedings. We offer two possibly complementary approaches to obtaining estimates of the probability of a firm’s likelihood of business failure. To illustrate these approaches, we use the case study data in O\u27Haver (1993) and Local Outlier Probabilities (Breunig et al., 2000; Kriegel et al., 2009) and PRIDIT (Brockett, et al., 2002; Lieberthal, 2008) to first order the outcomes in terms of a numeric score. Once ordered, the scores represent either probability-of-insolvency measure or an insolvency ranking. We then map the scores onto bivariate classes using Fisher-Jenks clustering. Each algorithm’s accuracy is obtained by comparing its predictions of either failure of viability to those of the labeled data in O\u27Haver (1993). Both procedures are sound and with equal accuracy to the original discriminant analysis featured in O\u27Haver (1993). We hold that these competing approaches are capable of navigating opposing counsel objections. Importantly, our approach also falls well within the interpretability criteria demanded by the EU General Data Protection Regulation (“GDPR”) and other regulations taking aim at black-box algorithms