VIX AND VIX FUTURES: A TOOL OF RISK REDUCTION AND DOWNSIDE PROTECTION FOR HEDGE FUNDS

We analyze VIX, VIX futures and hedge funds. VIX is a measure of the implied volatility of S&P 500 index options. VIX futures performance is measured by the S&P 500 VIX Mid-Term Futures Index and the CBOE VIX Premium Strategy Index. Credit Suisse Hedge Fund Index and Hedge Fund Research Indices represent hedge funds performance. In our project, we expand Dash and Moran (2005) by expanding the end period of survey from December 2004 to May 2014 and including two hedge fund databases, Credit Suisse and Hedge Fund Research. In addition, we conduct analyses on both VIX index and VIX futures indices, which are not included in the Dash and Moran (2005). Not only we check the addition of VIX index or VIX futures indices to hedge fund portfolios for risk reduction or downside protection, but also our analysis pays more attention to the period of 2008 financial crisis. We find that broad-based hedge fund indices and most narrow hedge fund indices are negatively and asymmetrically correlated with VIX. Addition of VIX index as well as VIX futures indices protects hedge fund portfolios from major drawdowns and helps reduce risk

CryptOpt: Verified Compilation with Random Program Search for Cryptographic Primitives

Most software domains rely on compilers to translate high-level code to multiple different machine languages, with performance not too much worse than what developers would have the patience to write directly in assembly language. However, cryptography has been an exception, where many performance-critical routines have been written directly in assembly (sometimes through metaprogramming layers). Some past work has shown how to do formal verification of that assembly, and other work has shown how to generate C code automatically along with formal proof, but with consequent performance penalties vs. the best-known assembly. We present CryptOpt, the first compilation pipeline that specializes high-level cryptographic functional programs into assembly code significantly faster than what GCC or Clang produce, with mechanized proof (in Coq) whose final theorem statement mentions little beyond the input functional program and the operational semantics of x86-64 assembly. On the optimization side, we apply randomized search through the space of assembly programs, with repeated automatic benchmarking on target CPUs. On the formal-verification side, we connect to the Fiat Cryptography framework (which translates functional programs into C-like IR code) and extend it with a new formally verified program-equivalence checker, incorporating a modest subset of known features of SMT solvers and symbolic-execution engines. The overall prototype is quite practical, e.g. producing new fastest-known implementations for the relatively new Intel i9 12G, of finite-field arithmetic for both Curve25519 (part of the TLS standard) and the Bitcoin elliptic curve secp256k1

Research on the influence of a high proportion of wind power connected to the receiving power grid on the system power angle stability

With the increasing proportion of wind power integration, the effect on the stability of the system power angle cannot be ignored. In this paper, based on the different power characteristics of direct-drive wind generators before a fault and after its clearance, the system model of the receiving-end grid with thermal units replaced by wind turbines is simplified. The influence of the increase in the replacement ratio of wind power in the receiving-end grid on the transfer impedance between the sending end and receiving end is analyzed. Based on the equal area rule, the influence of the replacement ratio k within the receiving-end grid, power grid operation mode, and wind power integration point on the system power angle stability is analyzed. It is concluded that the stability of the system’s power angle will first get better and then deteriorate with the increase in the replacement ratio of wind power, the system can bear a larger proportion of wind turbines under the low-load operation mode, and the system’s power angle of the replacement of wind power with equal capacity in the load center region is relatively better. The aforementioned conclusions are verified by simulation with real data from a bulk power system in China. Therefore, the method and conclusion can also be used to study the power angle stability of other large-scale power grids

Impact of Digital Economy on Energy Supply Chain Efficiency: Evidence from Chinese Energy Enterprises

The global industrial chain and energy supply chain are being reconfigured at an accelerated pace, and the uncertainty of China’s energy supply security is growing significantly. Empowering energy supply chains through the digital economy (diec) has a positive effect on accelerating the transformation of China’s energy supply structure. This paper discusses the effect and mechanisms of the digital economy on energy supply chain efficiency (esce). Specifically, based on the panel data of 112 energy enterprises in China from 2011 to 2019, energy supply chain efficiency and digital economy at the enterprise level were evaluated through three-stage DEA and content analysis, respectively. A two-way fixed effects model and mediation effect mode were adopted to investigate the nexus of diec and esce. The results show that the digital economy improves energy supply chain efficiency, and the conclusion holds water even after a series of robustness tests and endogenous treatment. Meanwhile, its promotion effect is more significant among large enterprises, non-state enterprises and enterprises in high market-oriented regions. The main impact mechanisms are regional industrial agglomeration and technological innovation of enterprises. Based on the above conclusions, it is suggested to take advantage of the industrial aggregation effect and technological innovation effect of the digital economy to further improve the efficiency of the energy supply chain for the purpose of maintaining energy supply security

Predicting Lung Cancer in the United States: A Multiple Model Examination of Public Health Factors

In this research, we take a multivariate, multi-method approach to predicting the incidence of lung cancer in the United States. We obtain public health and ambient emission data from multiple sources in 2000–2013 to model lung cancer in the period 2013–2017. We compare several models using four sources of predictor variables: adult smoking, state, environmental quality index, and ambient emissions. The environmental quality index variables pertain to macro-level domains: air, land, water, socio-demographic, and built environment. The ambient emissions consist of Cyanide compounds, Carbon Monoxide, Carbon Disulfide, Diesel Exhaust, Nitrogen Dioxide, Tropospheric Ozone, Coarse Particulate Matter, Fine Particulate Matter, and Sulfur Dioxide. We compare various models and find that the best regression model has variance explained of 62 percent whereas the best machine learning model has 64 percent variance explained with 10% less error. The most hazardous ambient emissions are Coarse Particulate Matter, Fine Particulate Matter, Sulfur Dioxide, Carbon Monoxide, and Tropospheric Ozone. These ambient emissions could be curtailed to improve air quality, thus reducing the incidence of lung cancer. We interpret and discuss the implications of the model results, including the tradeoff between transparency and accuracy. We also review limitations of and directions for the current models in order to extend and refine them

Long non-coding RNA and Evolving drug resistance in lung cancer

Non-small cell lung cancer (NSCLC) is one of the most devastating cancers with a high incidence and mortality rates of all cancers. Locally advanced or metastatic NSCLC patients can benefit from platinum-based chemotherapy and targeted therapy drugs. Nevertheless, primary or acquired drug resistance will result in ineffective treatment, leading to tumor progression. The detailed mechanism underlying drug resistance to NSCLC are complicated and result from various factor. Among them, long noncoding RNAs (lncRNAs) have been found to be critically involved in NSCLC development and play a vital role in mediating therapy resistance. In this review, we attempt to systematically summarize the mechanisms underlying the lncRNA-mediated resistance to chemotherapy agents and targeted therapy drugs against lung cancer

Enhanced Hemostatic and Procoagulant Efficacy of PEG/ZnO Hydrogels: A Novel Approach in Traumatic Hemorrhage Management

Managing severe bleeding, particularly in soft tissues and visceral injuries, remains a significant challenge in trauma and surgical care. Traditional hemostatic methods often fall short in wet and dynamic environments. This study addresses the critical issue of severe bleeding in soft tissues, proposing an innovative solution using a polyethylene glycol (PEG)-based hydrogel combined with zinc oxide (ZnO). The developed hydrogel forms a dual-network structure through amide bonds and metal ion chelation, resulting in enhanced mechanical properties and adhesion strength. The hydrogel, exhibiting excellent biocompatibility, is designed to release zinc ions, promoting coagulation and accelerating hemostasis. Comprehensive characterization, including gelation time, rheological properties, microstructure analysis, and swelling behavior, demonstrates the superior performance of the PEG/ZnO hydrogel compared to traditional PEG hydrogels. Mechanical tests confirm increased compression strength and adhesive properties, which are crucial for withstanding tissue dynamics. In vitro assessments reveal excellent biocompatibility and enhanced procoagulant ability attributed to ZnO. Moreover, in vivo experiments using rat liver and tail bleeding models demonstrate the remarkable hemostatic performance of the PEG/ZnO hydrogel, showcasing its potential for acute bleeding treatment in both visceral and peripheral scenarios

The Epidemiology and Variation in Pseudorabies Virus: A Continuing Challenge to Pigs and Humans

Pseudorabies virus (PRV) can infect most mammals and is well known for causing substantial economic losses in the pig industry. In addition to pigs, PRV infection usually leads to severe itching, central nervous system dysfunction, and 100% mortality in its non-natural hosts. It should be noted that increasing human cases of PRV infection have been reported in China since 2017, and these patients have generally suffered from nervous system damage and even death. Here, we reviewed the current prevalence and variation in PRV worldwide as well as the PRV-caused infections in animals and humans, and briefly summarized the vaccines and diagnostic methods used for pseudorabies control. Most countries, including China, have control programs in place for pseudorabies in domestic pigs, and thus, the disease is on the decline; however, PRV is still globally epizootic and an important pathogen for pigs. In countries where pseudorabies in domestic pigs have already been eliminated, the risk of PRV transmission by infected wild animals should be estimated and prevented. As a member of the alphaherpesviruses, PRV showed protein-coding variation that was relatively higher than that of herpes simplex virus-1 (HSV-1) and varicella-zoster virus (VZV), and its evolution was mainly contributed to by the frequent recombination observed between different genotypes or within the clade. Recombination events have promoted the generation of new variants, such as the variant strains resulting in the outbreak of pseudorabies in pigs in China, 2011. There have been 25 cases of PRV infections in humans reported in China since 2017, and they were considered to be infected by PRV variant strains. Although PRV infections have been sporadically reported in humans, their causal association remains to be determined. This review provided the latest epidemiological information on PRV for the better understanding, prevention, and treatment of pseudorabies