Pay-as-You-Go Financing and Capital Outlay Volatility: Evidence from the States over Two Recent Economic Cycles

Pay-as-you-go (pay-go or cash) and pay-as-you-use (pay-use or debt) are two mechanisms to finance capital projects. While pay-go faces multiple constraints, pay-use smoothes outlays, stabilizes tax rates, and improves inter-generational equity. Thus, pay-use has dominated infrastructure financing for decades. In recent years, there has been revived academic interest in pay-go as an alternate financing mechanism; however, there is a large gap in the literature and inadequate evidence on the effects of pay-go, especially its effects on capital outlay volatility. This paper fills in the niche. Examining state experience over the two recent economic cycles, this paper finds evidence that suggests that pay-go is associated with lower volatility in capital spending in the long run, but may increase short-run variability. We recommend that states couple pay-go in boom years with pay-use in lean years. In unison, the two mechanisms can reduce aggregate volatility and increase long-run stability of capital expenditures

Do Local Governments Save and Spend across Budget Cycles? Evidence from North Carolina

The fiscal crisis encountered by state-local governments since 2008 has again made prominent the issue of how to better prepare for and stabilize expenditures during recessions. Does the stabilization function of government, and its theory, still hold? Previous studies focus on federal and state levels; only a few look at local governments. This article explores whether localities save and spend across the boom-bust cycle; we intend to identify the determinants of local government savings and estimate the impact of savings on stabilizing expenditures. Unlike some early evidence that shows countercyclical stabilization properties of local unreserved general fund balance, the empirical results of our study on North Carolina counties do not support the stabilization role by localities. This study carries timely and important implications for state/local policy making and financial operations; it also adds to the literature on the stabilization function of government

Risk factors associated with infection of blood-borne virus among people who used methamphetamine

Background The surge of methamphetamine use has been a complicating factor compounding the steeply increasing number of drug overdose deaths in the U.S. Infection from blood-borne viruses including hepatitis B virus (HBV), hepatitis C virus (HCV) and HIV, related to methamphetamine use continue to grow. This study aims to examine the risk factors associated with HBV, HCV and HIV among people who used methamphetamine. Methods People who ever used methamphetamine were identified from five National Health and Nutrition Examination Survey (NHANES) cohorts, 2007 to 2016. The outcome was either positive or negative for blood-borne viruses as identified from laboratory tests. Weighted statistics for the combined ten years of data were calculated by multiplying the weighted variable for laboratory measurements by 0.2. We examined the association of sexual activities (sexual partners, sexual identity), drug use behaviors (poly-drug use, injection drug use, frequency of drug use, age started using methamphetamine), demographics, and socio-economic status with blood-borne viruses using bivariate and multivariable logistic regression models. Results There were 1132 participants representing approximately 11,996,319 persons who ever used methamphetamine in the U.S. Blood-borne viruses’ positive rate was 13.0 per 100,000. Multivariable logistic regression analyses showed significant associations of blood-borne infections with age 40–49 years (vs. age 20–29 years, adjusted odds ratio 4.77, 95% CI 1.11–20.55), age 50–59 years (vs. age 20–29 years, 10.25, 2.40–43.82), living within poverty index 1–1.9 (vs. poverty index \u3e = 2, 2.55; 1.19–5.49), living below the poverty threshold (vs. poverty index \u3e = 2, 2.55; 1.11–5.86), having lower than high school education (vs. equal or higher than high school education, 3.13; 1.51–6.46), sexual identity as other than heterosexual (vs. heterosexual, 5.60; 1.72–18.28), using methamphetamine and heroin and cocaine (vs. using methamphetamine alone, 4.24; 1.06–16.92), injection drug use (vs. no injection drug use, 3.15; 1.61–6.16), and started using methamphetamine at age above 25 (vs. started using methamphetamine at age between 10 and 17, 2.09; 1.01–4.35). Conclusions Among people who use methamphetamine, those who use polysubstance, or who inject substances, are in urgent need for vaccination and interventions to avoid further harm from blood borne infections

Volumetric Efficiency Improvement by Overflow in Rolling Piston Compressor

The rotary compressor with rolling piston is a widely used compressor with less clearance volume, while it is minimized from normal scale to meso or micro scale, the input and exit ports dimension is limited by port requirement and lead to a certain clearance volume, therefore, keeping or improving its volume efficiency is an important issue. Although rolling piston compressor is a kind of compact structure compressor, the existence of the clearance volume is inevitable in a compressor, the more the clearance volume, the lower the volumetric efficiency of compressor. The overflow is a method to improve the volumetric efficiency of a compressor which had been discussed in wankel compressor, in the overflowing process the clearance space with high pressure is connected directly with the space with lower pressure, mostly that is in the moment, one of the chambers in the rotary compressor is at the end of the exhaust process, and another chamber is at the sucking stage or the initial compression process. The gas pressure in the clearance volume is visibly higher than that in the compression chamber. The high-pressure gas in the clearance volume flows into the compression cylinder via a certain way; this flow considerably increases the pressure in the compression cylinder and decreases the pressure in the clearance volume. Thus, the intake and exhaust times means to be extended, and the volumetric efficiency and the cooling capacity of the compressor can be substantially enhanced. In this paper, we introduce the effect of input and exit dimensions on the volume efficiency of rolling piston compressor, and the overflow design on a rolling piston compressor that fully uses the high-pressure gas in the clearance volume, and discuss its effect on the performance of a compressor by theoretical analyses. Usually, the coefficient of performance of a vapor refrigeration cycle with the compressor overflow has a certain decrease compared with the conventional compressor, but the volumetric efficiency of the compressor with overflow and the cooling capacity of the thermodynamic cycle recesses are visibly higher than those of the conventional compressor in terms of the same operation and dimension parameters. The overflow has beneficial effect on miniaturizing the compresso

Why Do Acquisitions Negatively Affect Patient Outcomes at Target Hospitals: Quiet Life Hypothesis or Disruptions Caused by Acquisition Integrations?

Care quality declines at target hospitals following mergers and acquisitions (M&A) by multihospital health systems (MHSs). The declines have been attributed to the M&A’s consolidation and competitive intensity reduction effects. Insulated from competition, managers may choose to enjoy the “quiet life” instead of taking on difficult tasks to improve care quality. In addition to subjecting this hypothesis to empirical scrutiny, we propose and test a disruption hypothesis: IT M&A integrations and medical service integrations between an MHS and a target could cause disruptions to the target’s care processes and reduce the quality of patient outcomes. We find support for both hypotheses in a sample of 629 M&A transactions conducted by 179 unique MHSs and 579 unique target hospitals in the U.S. hospital industry during 2009-2017. Reduced competitive intensity increases mortality rates. IT M&A integrations increase readmission and mortality rates whereas service integrations increase only readmission rates in target hospitals

MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models

LLMs usually exhibit limitations in their ability to incorporate new knowledge, the generation of hallucinations, and the transparency of their decision-making process. In this paper, we explore how to prompt LLMs with knowledge graphs (KG), working as a remedy to engage LLMs with up-to-date knowledge and elicit the reasoning pathways from LLMs. Specifically, we build a prompting pipeline that endows LLMs with the capability of comprehending KG inputs and inferring with a combined implicit knowledge and the retrieved external knowledge. In addition, we investigate eliciting the mind map on which LLMs perform the reasoning and generate the answers. It is identified that the produced mind map exhibits the reasoning pathways of LLMs grounded on the ontology of knowledge, hence bringing the prospects of probing and gauging LLM inference in production. The experiments on three question & answering datasets also show that MindMap prompting leads to a striking empirical gain. For instance, prompting a GPT-3.5 with MindMap yields an overwhelming performance over GPT-4 consistently. We also demonstrate that with structured facts retrieved from KG, MindMap can outperform a series of prompting-with-document-retrieval methods, benefiting from more accurate, concise, and comprehensive knowledge from KGs.Comment: 7 pages, 8 figures, 9 table

Improved Inner Approximation for Aggregating Power Flexibility in Active Distribution Networks and its Applications

Concise and reliable modeling for aggregating power flexibility of distributed energy resources in active distribution networks (ADNs) is a crucial technique for coordinating transmission and distribution networks. Our recent research has successfully derived an explicit expression for the exact aggregation model (EAM) of power flexibility at the substation level under linearized distribution network constraints. The EAM, however, is impractical for decision-making purposes due to its exponential complexity. In this paper, we propose an inner approximation method for aggregating flexibility in ADNs that utilizes the properties of the EAM to improve performance. Specifically, the geometric prototype of the inner approximation model is defined according to a subset of the coefficient vector set of the EAM, which enhances the accuracy. On the other hand, the computation efficiency of the inner approximation is also significantly improved by exploiting the regularity of coefficient vectors in the EAM in the parameter calculation process. The inner approximated flexibility model of ADNs is further incorporated into the security-constrained unit commitment problem as an application. Numerical simulations verify the effectiveness of the proposed method.Comment: 10 page