Miracle-dz/UniFAR-FTUs huggingface dataset:
“When to Hold and When to Fold”: Simulating Portfolio Returns to Angel Investing in Early Stage Ventures

We use a large scale simulation to explore returns to angel investing in the context of real-world constraints in the first empirical examination of investment timing, termination and re- investment. Prior studies calculate angel returns as a single portfolio of investments, as if angels make hundreds of investments simultaneously and hold them all until exit or failure. We sample the largest available angel returns data set while varying portfolio size, investing window and portfolio hold time. Our Monte Carlo analysis simulates more than 11 million portfolios with over 240 million hypothetical investments. The results suggest that angel investing presents more variability and lower returns than reported in prior studies. Low returns are also associated with follow-on investment, which suggests that angels may tend to escalate commitment to poorly performing investments. The study highlights the importance of examining angel investing returns in the context of real-world constraints.
MULTISCALE MODELING OF BIOLOGICAL AND SOFT MATTER

The large range of spatial and temporal scales inherent in biological and soft matter is a challenge to modeling. To understand the physics of a cell membrane, one needs to start from Ångström-sized atoms and their motions in the femtosecond range, and go all the way to whole cells, whose diameters can be tens of micrometers and lifetimes of the order of days. All these scales can neither be probed by a single experimental technique, nor modeled using one simulation approach. What is needed is a range of techniques. Describing matter by a hierarchy of computational models, systematically linking the models at lower resolution to those at higher resolution, is termed multiscale modeling. Depending on the phenomenon one wishes to study, one may choose atomic-level models and algorithms, opt for a simplified or coarse-grained description, or decide on a combination of these. The aim of this Thesis is to describe modeling at atomic scale and mesoscale, i.e., at scales in the range 1–1000 nm and 1–1000 ns. We also focus on the systematic linking; how to reduce the degrees of freedom in an atomicscale model to arrive at a coarse-grained description. Further, use of hybrid models that combine atomic and coarse-grained descriptions is discussed. We approach multiscale modeling through examples from biological and soft matter physics. Atomic-scale modeling is illustrated through molecular dynamics simulations of phospholipid/cholesterol bilayers. The effect of cholesterol on the free volume, packing, and diffusive properties of bilayers is investigated. We then link the atomic-scale model to one allowing us to reach length scales significantly larger than those reached in current-day state-of-the-art atomic-level simulations: the new model offers an eightorder-of-magnitude speed-up, enabling us to study the lateral structure of bilayers at length scales up to hundreds of nanometers at a modest computational cost. The simulation results point at the existence of cholesterol-rich domains with sizes in the ten-nanometer-range. From membrane systems we move to the realm of complex fluids. We use polymer chains and colloids in solution as examples of systems where hybrid models should be used. The solutes are modeled in microscopic detail, while the solvent is coarse-grained. The solvent model is cost-effective, yet correctly describes the hydrodynamic interactions between the solute particles. Using these models we are able to resolve a long-standing debate about dynamic scaling of two-dimensional polymers in solution, and obtain interesting results for collective diffusion in colloidal suspensions.
Front-End Electronics of CXPD for Measuring Transient X-Ray Sources

The low-energy polarization detector (LPD), a payload of the POLAR-2 mission, is a soft X-ray polarization detector with a wide field of view and a large array aimed at measuring X-ray transients. These transients exhibit rapid intensity changes of several orders of magnitude, making it crucial for polarization detectors to have front-end electronics with low dead time, fast readout capabilities, high time resolution, and good energy resolution. In this article, we present the design of the front-end electronics, which consist of a rolling shutter CMOS pixel charge sensor (Topmetal-<inline-formula> <tex-math notation="LaTeX">$II^{-}$ </tex-math></inline-formula>) and a gas microchannel plate (GMCP) bottom amplifier circuit. Topmetal-<inline-formula> <tex-math notation="LaTeX">$II^{-}$ </tex-math></inline-formula>’s rolling shutter readout provides fast scanning of large pixel arrays without dead time and acquires 2-D images of photoelectron tracks. Meanwhile, the GMCP’s bottom amplifier circuit measures the energy and time of the X-ray. The front-end electronics are employed by the CubeSat cosmic X-ray polarization detector (CXPD), a proto-flight model of the LPD, achieving a timing resolution of 19 ns, and an energy resolution of 16.5% for linearly polarized X-rays at 8 keV.
A new Monte Carlo technique: antithetic variates

As we have stressed in a previous paper (9), the main concern in Monte Carlo work is to achieve without inordinate labour a respectably small standard error in the final result. Mere replication of the Monte Carlo results is unrewarding; for, to reduce a standard error by a factor k, the labour must be increased k2-fold, and this will be beyond the resources of even electronic computers when k = 1000, say. The remedy lies in a skilful choice of sampling technique and the substitution of analytical methods for random processes wherever possible. The efficiency of a Monte Carlo process may be taken as inversely proportional to the product of the sampling variance of the final estimate and the amount of labour expended in obtaining this estimate; and it is profitable to allow some increase in the labour if that produces an overwhelming decrease in the variance. For instance, in the last example quoted below (Table 2), we reduce the variance by a factor of four million at the expense of only multiplying the labour sixteenfold, thereby attaining a 250,000-fold gain of efficiency.
How satisfactory are empathetic care and robotic assistance in telemedicine services?

ABSTRACT Telemedicine healthcare and assistive robotic technologies are gaining popularity as support systems for traditional healthcare practices. However, there are concerns regarding the use of these digital services due to their lack of empathy and intimacy. This paper investigates the impact of physicians’ empathetic care and telepresence robot assistance on patients’ intimate experience and satisfaction. We employ a multi-method design to achieve our research objective. The first study utilizes a 2 (digital empathetic care: high vs. low) × 2 (telepresence robot assistance: present vs. absent) × 2 (severity of illness: high vs. low) between-subject experimental design involving 287 participants who have used robotic assistance and telemedicine services. The findings from this study confirm that the telepresence robotic assistance and empathetic care by physicians positively impact intimate experience and patient satisfaction significantly more for patients with low severity of illness, thus confirming the significant moderated-moderated mediation effect. The second study employs field data (n = 4629 reviews) to further validate the telepresence robots’ usability in establishing intimate patient experiences in digital settings. The study recommends to healthcare practitioners that empathetic care and robotic assistance are essential factors for building intimate experience and patient satisfaction in telehealthcare services.
Generation of mutants for boolean expression

Abstract Fault based testing suffers from biases of the programmer in seeding the faults. There is no formal approach to determine the maximum number of mutants that can be generated for a specific faults type. In this paper, we will examine the various fault categories for Boolean expressions in irreducible Disjunctive Normal Form (DNF) and Canonical DNF and estimate the maximum number of faults that can be seeded in a Boolean expression. The results obtained provide a mechanism for the generation of mutants that are not equivalent to the original Boolean expression in irreducible disjunctive normal form.
Perfluorocarbon Nanoemulsions with Fluorous Chlorin-Type Photosensitizers for Antitumor Photodynamic Therapy in Hypoxia

The efficacy of photodynamic therapy (PDT) strictly depends on the availability of molecular oxygen to trigger the light-induced generation of reactive species. Fluorocarbons have an increased ability to dissolve oxygen and are attractive tools for gas delivery. We synthesized three fluorous derivatives of chlorin with peripheral polyfluoroalkyl substituents. These compounds were used as precursors for preparing nanoemulsions with perfluorodecalin as an oxygen depot. Therefore, our formulations contained hydrophobic photosensitizers capable of absorbing monochromatic light in the long wavelength region and the oxygen carrier. These modifications did not alter the photosensitizing characteristics of chlorin such as the generation of singlet oxygen, the major cytocidal species in PDT. Emulsions readily entered HCT116 colon carcinoma cells and accumulated largely in mitochondria. Illumination of cells loaded with emulsions rapidly caused peroxidation of lipids and the loss of the plasma membrane integrity (photonecrosis). Most importantly, in PDT settings, emulsions potently sensitized cells cultured under prolonged (8 weeks) hypoxia as well as cells after oxygen depletion with sodium sulfite (acute hypoxia). The photodamaging potency of emulsions in hypoxia was significantly more pronounced compared to emulsion-free counterparts. Considering a negligible dark cytotoxicity, our materials emerge as efficient and biocompatible instruments for PDT-assisted eradication of hypoxic cells.
Circle-Net: An Unsupervised Lightweight-Attention Cyclic Network for Hyperspectral and Multispectral Image Fusion

Hyperspectral image (HSI) and multispectral image (MSI) fusion has the potential to significantly improve the quality and usefulness of data, leading to better decision-making and a more complete understanding of the observed scene. For HSI and MSI fusion, capturing matched pairs of HSI and MSI images is challenging. This hampers the pretraining of neural-network-based HSI–MSI fusion methods and yields unsatisfactory fusion results. A lightweight-attention (LA) cyclic network (Circle-Net) without pretraining using labeled data is constructed and applied to HSI–MSI fusion to alleviate this issue. Circle-Net consists of a coordinate feature fusion (CFF) network and a dual-attention decoder (DAD) network. Multiscale features collected from the DAD network are fused by the CFF network to derive a high-resolution HSI. Specifically, in the DAD network, skip connections in the encoder–decoder network are replaced by LAs, while polarized attention is used to guarantee efficient transfer of features between the encoder and decoder. In comparison with other methods, the experimental performance shows the superiority of the Circle-Net in both visual and quantitative performance.
The role of governmental stakeholder engagement in the sustainability of industrial engineering projects

PurposeThe aim of this research was to understand how governmental stakeholder engagement facilitates the sustainability of industrial engineering (IE) projects. A model for governmental stakeholder engagement activities is presented.Design/methodology/approachThe authors relied on a single-case study of a mining project in Northern Europe, where a novel collaboration and engagement approach with governmental stakeholders was piloted in the project's front-end phase. The analysis focused on the collaborative practices through which the IE project investor engaged governmental stakeholders during the project's front-end phase and how the engagement contributed to solving challenges in the early planning and permitting process and achieving project plans that balanced economic, social and environmental aspects.FindingsThe findings show how four collaborative engagement practices reduced uncertainty and equivocality related to the legal sustainability requirements, enabled the development of sustainable design solutions and overall accelerated the permitting process without compromising the quality of final project plans.Practical implicationsThe findings can be used to plan governmental stakeholder engagement and understand related challenges that need to be overcome. The study highlights the need to develop established practices and guidelines for governmental stakeholder engagement.Originality/valueThis study complements prior research on stakeholder engagement and project sustainability by developing an understanding of how governmental stakeholder engagement can be a key mechanism enabling the sustainability of IE project's end product. This research contributes to stakeholder theory by elaborating on a new stakeholder role, intermediary stakeholder.
An Electromechanical Matching Design Method for Faceted Surface of Mesh Reflector

The faceted surface is used in mesh reflectors to reflect electromagnetic (EM) signals. The matching design method of surface geometry is developed by considering EM performance. The geometrical model of faceted surface is established to avoid the facets overlapping by using the force density method, and the far field scattered by the mesh reflector is derived to reveal the relationship between the faceted surface and EM performance. To improve the computational efficiency, the double integral of the far field is derived in a closed-form expression, and a refinement procedure of EM grids for facets is proposed to homogenize the grids. The electromechanical coupling optimization model is established, and the comparative analysis is carried out, respectively. Numerical results show that the proposed method can obtain a higher gain with a larger surface error of the mesh reflector by adjusting the distribution of the surface-faceted error.
Significance of antinuclear antibodies in patients with COVID-19

© 2023 The Korean Association of Internal Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. pISSN 1226-3303 eISSN 2005-6648 http://www.kjim. org Editorial
Practical challenges of fiscal/monetary response to COVID-19 situation in the USA

The article’s main objective was to analyze sentiment, financial markets, and Consumer Price Index (CPI) emotional impact. It narrates and summarizes the changes that have occurred since the onset of the financial crisis and financial recession in 2003. Data document review is the main method used to collect data for the article. The article borrows concepts and theories from the cited sources. As per the article, it is hard for the government to target specific parts of the economy. The mainstream economic limits in the covid-19 era disproved several theoretical pillars of the mainstream economy. According to studies, conventional economic theory holds that people are constantly eager to adapt their requirements and satisfactions to better their balance sheets for increased utility. The demand and supply rules serve as the foundation for modern economics models. It demonstrates how the market continually seeks equilibrium. One of the key tenets of orthodox economics is that since economists are practical by nature, it follows that everyone wants their unique needs to be satisfied. People occasionally judge and make decisions, which is the limitation of contemporary mainstream economics in addressing real-world issues. The key dangers are that these markets could cause the real economy to suffer from risk re-pricing, decreased confidence, falling asset values, and tighter financial conditions. Mainstream economics influences most people’s lives aspects. Its majority dealings are at the house level and are deeply flawed in terms of their real-life impact. Individuals commonly follow market trends and predictions, and any shift will undoubtedly impact the individual.
#Sponsored: Understanding the Boundary Conditions of Resistance Coping Activation in Influencer Advertising

Abstract Influencer advertising has sparked controversy among both consumers and regulators, in that influencer advertising’s very effectiveness is built on deceit, because consumers are often unaware of the persuasive intent. Empirical evidence on influencer advertising is built largely on the premise that disclosure will activate consumers’ reactance, as consumers will recognize the persuasive intent. Using a mixed-method approach (focus groups and survey), we contribute to the growing body of research on influencer advertising by demonstrating the role of three important boundary conditions in the relationship between knowledge of persuasive intent and activation of “resistant coping” mechanisms: trust, overconfidence, and transparency. Based on our focus-group results, we propose that two groups of outcome variables need further research attention: (1) consumers’ moral and affective advertising literacy and (2) other individual-level psychological outcomes, such as cognitive dissonance and reduced control over one’s time and productivity. In our further empirical test, we focus more specifically on perceptions of moral appropriateness of advertising, and we illustrate its importance for understanding how influencer advertising works.
NGS Technology in Monitoring the Genetic Diversity of Cytomegalovirus Strains

Modern molecular genetic methods, massive parallel sequencing in particular, allow for genotyping of various pathogens with the aim of their epidemiological marking and improvement of molecular epidemiological surveillance of actual infections, including cytomegalovirus infection. The aim of the study is to evaluate the next-generation sequencing (NGS) technology for genotyping clinical isolates of cytomegalovirus (CMV). Materials and Methods The object of the study were samples of biological substrates (leukocyte mass, saliva, urine) taken from patients who underwent liver and kidney transplantation. Detection of CMV DNA was carried out by a real-time PCR using commercial diagnostic AmpliSense CMV-FL test systems (Central Research Institute for Epidemiology, Moscow, Russia). DNA extraction was performed using DNA-sorb AM and DNA-sorb V kits (Central Research Institute for Epidemiology) in accordance with manufacturer’s manual. The quality of the prepared DNA library for sequencing was assessed by means of the QIAxcel Advanced System capillary gel electrophoresis system (QIAGEN, Germany). Alignment and assembly of nucleotide sequences were carried out using CLC Genomics Workbench 5.5 software (CLC bio, USA). The sequencing results were analyzed using BLAST of NCBI server. Results CMV DNA samples were selected for genotyping. The two variable genes, UL55(gB) and UL73(gN), were used for CMV genotype determination, which was performed using NGS technology MiSeq sequencer (Illumina, USA). Based on the exploratory studies and analysis of literature sources, primers for genotyping on the UL55(gB) and UL73(gN) genes have been selected and the optimal conditions for the PCR reaction have been defined. The results of sequencing the UL55(gB) and UL73(gN) gene fragments of CMV clinical isolates from recipients of solid organs made it possible to determine the virus genotypes, among which gB2, gN4c, and gN4b were dominant. In some cases, association of two and three CMV genotypes has been revealed. Conclusion The application of the NGS technology for genotyping cytomegalovirus strains can become one of the main methods of CMV infection molecular epidemiology, as it allows for obtaining reliable results with a significant reduction in research time.
Genome-Wide Analysis of the Rad21/REC8 Gene Family in Cotton (Gossypium spp.)

Cohesin is a ring-shaped protein complex and plays a critical role in sister chromosome cohesion, which is a key event during mitosis and meiosis. Meiotic recombination protein REC8 is one of the subunits of the cohesion complex. Although REC8 genes have been characterized in some plant species, little is known about them in Gossypium. In this study, 89 REC8 genes were identified and analyzed in 16 plant species (including 4 Gossypium species); 12 REC8 genes were identified in Gossypium. hirsutum, 11 in Gossypium. barbadense, 7 in Gossypium. raimondii, and 5 in Gossypium. arboreum. In a phylogenetic analysis, the 89 RCE8 genes clustered into 6 subfamilies (I–VI). The chromosome location, exon-intron structure, and motifs of the REC8 genes in the Gossypium species were also analyzed. Expression patterns of GhREC8 genes in various tissues and under abiotic stress treatments were analyzed based on public RNA-seq data, which indicated that GhREC8 genes might have different functions in growth and development. Additionally, qRT-PCR analysis showed that MeJA, GA, SA, and ABA treatments could induce the expression of GhREC8 genes. In general, the genes of the REC8 gene family of cotton were systematically analyzed, and their potential function in cotton mitosis, meiosis, and in response to abiotic stress and hormones were preliminary predicted, which provided an important basis for further research on cotton development and resistance to abiotic stress.
Passive Flow Control in Boundary Layer Ingesting Semi Submerged Inlet

In this study, effect of vortex generators used as passive flow control devices in a boundary layer ingesting semi submerged inlet is computationally investigated with the commercially available flow solver Fluent 14.0. Studied intake duct exposed to high level of boundary layer ingestion such that ingested boundary layer thickness corresponds to the 40% of the intake throat height. Four design variables used for vortex generator sets are taken as vortex generator height relative to local boundary layer thickness, angle of incidence, number of vortex generators and the distance between separation point and the vortex generator set. Effect of each design variable on intake performance is discussed in detail. Best vortex generator set provides 80% reduction in total pressure distortion with negligible amount of reduction in total pressure recovery at the design condition. Moreover, it is shown that, passive flow control ensure sufficiently uniform flow at the engine face for not only design angle of attack but also for the whole angle of attack range encountered in flight envelope.
USING NONPARAMETRIC BOOTSTRAPPING TO ASSESS KAPPA STATISTICS

The kappa statistic has a long history of use as an index of interrater agreement. Methods for estimating kappa and finding the standard error of the estimate have been well established when there are two raters, and/or when the population value of kappa is assumed to be 0. Estimating the variance of the kappa statistic is more difficult when there are multiple raters and a non-zero population kappa or when there are unequal numbers of raters for different items. Although some formulas for the standard error have been proposed in these situations, the resulting estimates are not necessarily consistent (Myers, 2000). In the current study, nonparametric bootstrapping methods were used to compute the standard error of estimated kappas and to construct 95% confidence intervals under conditions of both 0 and nonzero population kappas, with equal numbers of raters. Results are compared to existing formulas and assessed in terms of coverage probabilities. Nonparametric bootstrapping appears to be a viable option for assessing the variability of the kappa statistic when there are multiple raters and multiple items.