Estimates of Quarterly and Monthly Episodes of Global Recessions: Evidence from Markov-switching Dynamic Factor Models

An important issue in identifying global recessions is the limited availability of output data at the quarterly and monthly frequencies over longer time horizons. A related issue is the heterogeneity in evidence about specific recessionary episodes. We utilize the context that commodity prices are determined in the global markets, and four base metals have flexible nominal prices at the monthly frequency from the 1960s, providing crucial information about the global economy. We use the base metal prices to account for the global dimension of the analysis and to complement the information about the global economy in the GDP data of G7 and 25 other countries, and in the World Industrial Production index. We estimate the quarterly episodes of global recessions from the 1960s using extended Markov-switching dynamic factor models with multiple indicators. We also further adapt the quarterly models to a mixed-frequency Markov-switching dynamic factor model to estimate the monthly episodes. Our estimates show eight episodes of global recessions at the quarterly frequency. Monthly estimates also capture the eight quarterly episodes of global recessions. The results are robust to inclusion of oil prices in a subsample. Regressions using 32 countries show reductions in GDP growth for all countries during the global recession episodes. Further analysis shows that the four global recessions that are common with other studies are deeper and more widespread recessions than the other four downturns. The analysis highlights heterogeneity in the size and the spread of global recessions while providing empirical evidence in favor of four specific recessions with mixed support in the past literature

Immunity Through Bankruptcy for the Sackler Family

In August 2023, the Supreme Court of the United States temporarily blocked one of the largest public health settlements in history: that of Purdue Pharma, L.P., reached in bankruptcy court. The negotiated bankruptcy settlement approved by the court would give a golden parachute, in the form of immunity from liability, to the very people thought to have ignited the opioid crisis: the Sackler family. As the Supreme Court considers the propriety of immunity through bankruptcy, the case has raised fundamental questions about whether bankruptcy is a proper refuge from tort liability and whether law checks power or law serves power. Of course, bankruptcy courts often limit liability against a distressed company, but here, the Sacklers did not themselves declare bankruptcy. Instead, they added about $6 billion to the pot—compared with$600 billion in annual costs from the opioid crisis, by some estimates—and were allowed to keep any remaining profits. The bankruptcy court justified immunity on the grounds that the Sacklers’ money was protected in offshore accounts and trusts and, therefore, could not be reached through tort liability—all the better to have them participate voluntarily. In other words, the Sacklers laid the groundwork for their own immunity by sheltering the money they withdrew from Purdue. This article explores the public health ramifications of the bankruptcy plan. We have doubts that a single court should have the enormous power of shielding the Sackler family from all future civil liability for the opioid crisis, simply to enlarge a settlement. Public health litigation has the power to address root causes of public health crises by disincentivizing unscrupulous actors. Granting these actors immunity may insulate them from public criticism while undermining the important role of courts as an avenue of recourse. Upholding immunity for the Sackler family would lay the groundwork for future executives to ride a company into the ground at the expense of public health, golden parachute ready and waiting

Positive Responses of Solanum lycopersicum Growth to Additions of Gibberellin in the Presence of Wounding Stress

Herbivory poses significant challenges to many economically valued crop plants. Plant growth hormones such as gibberellins are known to influence plant growth mechanisms especially at times of stress such as herbivory. To investigate, we set up a two-factorial design with 60 Solanum lycopersicum plants and subjected 15 plants each to four treatment groups: reference control, 0.187M gibberellin, wounding, and 0.187M gibberellin+wounding. We found that addition of gibberellin significantly influenced plant height and chlorophyll fluorescence, but not biomass or root-to-shoot ratios. Mechanical wounding showed significant effects on chlorophyll fluorescence but did not significantly impact other tested plant factors. The interaction between gibberellin and wounding interestingly influenced root-to-shoot ratios. Our experiment allows us to conclude that gibberellin will impact plant growth factors and resource allocation under wounding stress. This conclusion highlights the importance of further studying plant growth hormone regulation and agricultural implications relating overall plant growth and yield to environmental challenges and stressors

An Evaluation of a Human-Operant Effort Manipulation and Effects of Effort Disparity on Renewal

The relative effort of target and alternative responses during treatments using differential reinforcement of alternative behavior may impact the likelihood that a previously reduced target response will reemerge following a context change (i.e., “renewal”). The purpose of this study was to evaluate the role of an effort disparity between target and alternative responses in a human-operant arrangement. Eighteen college students clicked on one (Experiment 1) or two (Experiment 2) circles moving on a computer screen for points. In Experiment 1, the speed of the circle was manipulated as an index of effort such that three circle speeds (i.e., 50, 100, 200 mm/s) were used across conditions. Nearly all participants engaged in differential response rates, depending on the speed of the available circle. Criterion response rates (clicks on the target circle) were highest when the speed was slow. Subcriterion response rates (clicks on the background of the computer screen) were inversely related to the speed of the circle. In Experiment 2, a three-phase renewal arrangement was executed across three experimental conditions in which the target response was either the same, easier, or more difficult than the alternative response. The effects of the relative effort of the target response to the alternative response on the occurrence and magnitude of renewal were mixed across participants. The clinical and conceptual relevance regarding the relative effort of target and alternative responses will be discussed

ENDOGENOUS GLUCOCORTICOID SIGNALING IS REQUIRED FOR NORMAL MACROPHAGE RESPONSE TO H. pylori INFECTION

Gastric cancer is the fifth leading cause of cancer-related deaths worldwide, affecting millions of people. H. pylori is the strongest risk factor for gastric cancer, with about 90% of the cases strongly associated with H. pylori infection. Half of the world\u27s population is infected with this bacterium. However, only a small subset of the infected population (1-3 %) go on to develop gastric cancer. Diagnosis of the disease at an early stage is the biggest challenge because of the widespread prevalence of H. pylori infection and a long asymptomatic phase before the advanced stages. Patients are left with limited treatment options when the infection progresses to an advanced form of pathology. Chronic inflammation is a necessary driving factor for advancing the infection and development of cancer. H. pylori triggers the infiltration of different types of immune cells, among which the neutrophils, macrophages, dendritic cells, and eosinophils are the primary responders. T cells are also necessary for adequate bacterial clearance. Among these, macrophages are critical to phagocytose bacteria and present antigens to the cells of the adaptive immune system. Previous studies from our lab showed that in the absence of circulating glucocorticoids, macrophages promote gastritis and the development of metaplasia, a pre-neoplastic lesion, in mice. Glucocorticoid signaling is critical for the innate immune sensitization and resolution of inflammation. Although glucocorticoids are popularly known as immunosuppressive compounds, there is an abundance of literature on the immune-sensitizing role of glucocorticoid signaling. Glucocorticoids are known to regulate a large number of gene sets in monocytes during differentiation and dictate macrophage transcriptome. Here, we hypothesize that loss of the endogenous glucocorticoid signaling during differentiation impairs the macrophage\u27s immune response to the bacterium H. pyloriand affects the development of gastric cancer. Using ATAC and RNA sequencing, we elucidated that loss of the glucocorticoid receptor (GR) during differentiation blunts the macrophage immune responses towards H. pylori and skews them to cancer pathways. Further, we investigate the role of glucocorticoids within the myeloid compartment during gastric carcinogenesis using the model of Helicobacter pylori and Helicobacter felis infection in mice. We observed that loss of GR signaling impairs gastric leukocyte infiltration and T-cell homing in H. pylori-infected myGRKO mice. Additionally, myGRKO mice were protected from robust gastric inflammation and metaplasia in the chronic H. felis infection model. Our findings suggest that glucocorticoid signaling has an immunomodulatory role in the immune compartment and is required for a normal immune response to H. pylori infectio

Pilot Quality Improvement Project to Update Surgeon Preference Cards of a Community Hospital\u27s Orthopedic Service

Abstract Implementation of a Pilot Quality Improvement Project to Update Surgeon Preference Cards of a Community Hospital’s Orthopedic Service Jessica R. Mitchell Problem Statement: Over time, surgeons change preferences for surgical equipment, and their preference cards need updating. Failure to update preference cards leads to impaired staff communication, opening of unnecessary equipment, excess waste, increased cost to patients and facilities, and potential threats to patient safety. Background: Members of the orthopedic surgical team in a community hospital in suburban West Virginia wanted to establish a process to regularly update outdated surgeon preference cards (SPC) for several common orthopedic procedures. The preference cards convey important information to operating room (OR) staff to promote efficient and safe intraoperative care of patients. Outdated or inaccurate information may increase wasting of supplies, decrease efficiency of OR time, increase costs, and potentially decrease safety for patients. Project Goal: The purpose of this project was to establish a process for reviewing and updating surgeon preference cards for the orthopedic service in the operating room of a community hospital in suburban West Virginia. Project Aims: 1) Evaluate the current process for updating surgeon preference cards 2) Implement a pilot project to update and standardize surgeon preference cards 3) Evaluate the usefulness of the pilot project to update and standardize surgical preference cards Methods: The project director met with three orthopedic surgeons, physician assistants, and service line coordinators to review and update surgeon preference cards to implement and standardize their preferences for knee arthroplasty, hip arthroplasty, and shoulder arthroscopy. Pre and post intervention costs of each procedure were compared, and surveys administered to OR registered nurses, surgical technicians, physician assistants, and surgeons were analyzed. Results: Pre and post intervention mean cost analysis was completed per surgeon evaluating each surgical procedure using a paired t-test for evaluation of post intervention savings. Surgeon A results indicated that there was no significant difference when the SPCs were updated (p = 0.476). Surgeon B results indicated that there was a significant difference with cost post implementation (p = 0.022). Surgeon C results indicated that there was not significant difference in cost post implementation (p = 0.405). Survey results were analyzed using a Likert scale to evaluate sense of preparedness with updated SPCs. The participants (n=25) all felt very prepared for the surgical case post implementation. Conclusion: Evidence suggests costs savings when SPCs are maintained with input from providers. This quality improvement project did not demonstrate consistent cost savings for all procedures and surgeons, however there were cost savings associated with surgeon B for all three procedures that were updated. Surgeon A had a cost savings for knee arthroplasty. Surgeon C had a cost savings for hip arthroplasty, and shoulder arthroscopy. Staff that completed post implementation surveys felt satisfied with the updates to SPCs and felt prepared to perform the surgical cases

A Domain Adaptation Approach for Morphology-Independent Cell Instance Segmentation

In recent years, there has been an upward trend of utilizing deep learning to automate cell segmentation processes. As global storage capacities grow exponentially, so have microscopy data collections become larger and more frequent. To benefit from them, accurate and precise quantitative analysis tools like cell instance segmentation have become necessary. However, the highly variable nature of these data collections necessitates retraining segmentation models to maintain high accuracy on new data collections. This process is time-consuming and labor-intensive since a user must annotate much of the new data, usually under the supervision of a medical professional. The problem is further exacerbated when segmenting cells with elongated and non-convex morphology, like bacteria cells. In mitigating these concerns, we propose reducing the amount of annotation and compute power needed to retrain the model by introducing a few-shot domain adaptation approach that requires the annotation of only one to five cells of the new data. First, we rely on a robust and precise segmentation method trained on extensive source data and capable of handling highly diverse cell morphologies. Second, we take a few-shot learning approach, where given a target dataset that is distributed differently from source data, we require a user to label only a minimal amount of target data. We then set up a contrastive prediction task by introducing new losses that pull the representation of positive samples in a target domain closer to samples of the same class in a source domain while simultaneously pushing them apart from negative source samples using kernels as a similarity measure. Furthermore, we comprehensively studied the best kernel composition method for combining kernels defined on two inhomogeneous pairs of quantities. Our approach quickly adapts the model to maintain high accuracy, and our results show a significant boost in accuracy after adaptation to very challenging bacteria datasets

UNG: A Diagnostic Standard C Library

Undefined behavior in C programs is a major source of unreliable software. Many of the most common exploitable software vulnerabilities can be traced directly to undefined behavior. In the increasingly connected world, a successful attack can cost the victim millions of dollars to recover from. While static program analysis aids in identifying undefined behavior, testing indicates that even the best static analysis tools correctly identifies about 35% of these defects. This dissertation introduces UNG’s Not GNU (UNG), a standard C library designed to mitigate undefined behavior. Where others have seen opportunities for optimization, UNG makes every effort to identify undefined behavior at run time and, when encountered, prevent it from becoming an exploit vector by terminating the program with a detailed diagnostic message. It can be used to protect and diagnose existing programs without recompilation, or it can provide more details by recompiling programs to use it directly. In tests, UNG reliably diagnoses 59 of the 110 types of undefined behavior related to the standard library. This is 14750% more than the average of 0.4 identified by existing implementations, or 5900% more than the next best result of 1. Compared to static analysis tools, UNG correctly identifies 55% more samples than the best performer (38), and 178% more than the average of 21.25. Testing against exploitable Common Vulnerabilities and Exposures (CVE)s also shows that UNG is capable of preventing known attacks from succeeding, providing confidence that it will also prevent future unknown attacks of a similar nature