Failure to attract external financing is a common puzzle for start-up firms and often leads to the use of entrepreneurs' personal funding, typically with the help of their family. With little entrepreneurial experience, nascent entrepreneurs will have no factual signals to show external investors, except their characteristics or those of their family. The literature mainly focuses on the net effects of entrepreneurs' personal capital endowments in isolation on start-up capital structure despite emerging appreciation of the importance of family-related factors. However, little is known about which combinations of capital endowments across capital dimensions (i.e., human, social, and financial capital) or generations (i.e., parent and child) will likely affect the level of external funding. Drawing on signaling theory, we adopt a configurational approach to examine the compositions of intergenerational capital endowments that are sufficient to shape external funding. Conducting a fuzzy-set qualitative comparative analysis of Chinese privately owned enterprises of nascent entrepreneurs, we identify four typical family prototypes that feature intergenerational capital endowments for low external funding. Findings highlight the significance of family dynamics in China and their role in shaping new venture financing by displaying intergenerational signals.

Yellow nutsedge (Cyperus esculentus L.) is one of the most problematic weeds in turfgrass due to its fast growth rate and high tuber production. Effective long-term control relies on translocation of systemic herbicides to underground tubers. Two identical trials were conducted simultaneously in separate greenhouses to evaluate the effect of several acetolactate synthase (ALS) and protoporphyrinogen oxidase (PPO) inhibiting postemergence herbicides on C. esculentus tuber production and viability. Seven tubers were planted into 1 L pots, and plants were allowed to mature for 6 weeks before trial initiation. Treatments included pyrimisulfan at 73 g ai ha-1 once or 49 g ai ha-1 twice, imazosulfuron at 736 g ai ha-1 once or 420 g ai ha-1 twice, carfentrazone-ethyl + sulfentrazone at 22 + 198 g ai ha-1 once or 14 + 127 g ai ha-1 twice, halosulfuron at 70 g ai ha-1 once or 35 g ai ha-1 twice, and a non-treated control. Sequential applications were made 3 weeks after initial treatment (WAIT) for both trials. Both single and sequential applications of carfentrazone-ethyl + sulfentrazone exhibited the quickest control (80 to 83% 4 WAIT). Two applications of imazosulfuron resulted in the greatest reduction in tuber number (81%) and tuber dry biomass (85%), while one application of carfentrazone-ethyl + sulfentrazone resulted in the greatest reduction in shoot biomass (71%). The viability of tubers that were recovered from each pot was reduced 48 to 70%, with the greatest reduction in response to carfentrazone-ethyl + sulfentrazone. Although two applications of pyrimisulfan only resulted in tuber number and shoot biomass reductions of 66% and 38%, respectively, tuber dry biomass reduction was 80%. Therefore, pyrimisulfan, imazosulfuron, halosulfuron, and carfentrazone-ethyl + sulfentrazone are all viable options for long-term C. esculentus control in turfgrass.

We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839 $-$10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect $10\times$ more FRBs than the current CRAFT incoherent sum system (i.e. 0.5 $-$2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.

This study addresses a significant knowledge gap in the literature by examining the relationship between religious involvement and subjective wellbeing (SWB) among older adults in Taiwan, a cultural context that has been underrepresented in existing research, with a focus on gender and age differences. Using data collected in Taichung City in 2017 (N = 645), this study measured religious involvement through religious affiliation, religiosity and frequency of religious participation, and assessed SWB via life satisfaction and happiness. Findings revealed no significant association between religious involvement and life satisfaction. However, religious participation was positively correlated with happiness. Gender differences were observed: Buddhism and Taoism were positively associated with life satisfaction among males, whereas religiosity and religious participation were significantly related to life satisfaction and happiness among females. Age disparities were also found, with religiosity significantly relating to both life satisfaction and happiness in the old-old group (70–89 years) but not in the young-old group (60–69 years). These findings highlight the nuanced associations between religious involvement and SWB, emphasising the importance of considering gender and age variations in future research. Future studies should further explore the cultural contexts that shape these relationships and examine other potential mediating factors to provide a more comprehensive understanding of how religious involvement influences wellbeing across different demographic groups.

A careful theoretical analysis of the excitation of Alfvén eigenmodes (AEs), such as TAE (toroidicity-induced AE) and RSAE (reversed shear AE), by superalfvenic energetic particles is required for reliable predictions of energetic ion relaxation in present day fusion experiments. This includes the evaluation of different AE damping mechanisms including radiative and continuum dampings which are the focus of this study. A recent comprehensive benchmark of different eigenmode solvers including gyrokinetic, gyrofluid and hybrid magenetohydrodynamics (MHD) has shown that employed models may have deficiencies when addressing some of them (Taimourzadeh et al., Nucl. Fusion, vol. 59, 2019, 066006). In this paper, we are studying the radiative and continuum dampings of RSAEs in details which were missing in hybrid NOVA/NOVA-C calculations to prepare a NOVA-C package with a substantial upgrade. Both dampings require the finite Larmor radius (FLR) corrections to AE mode structures to be accounted for. Accurately calculating different damping rates and understanding their parametric dependencies, we resolve the limitation coming out of the perturbative approach. In particular, here, the radiative damping is included perturbatively, whereas the continuum damping is computed non-perturbatively. Our comparison leads to the conclusion that the non-perturbative treatment of the unstable RSAE modes is needed to find the agreement with the gyrokinetic calculations. We expect that the RSAE mode structure modification plays a dominant role in determining the RSAE stability.

The axisymmetric nozzle mechanism is the core part for thrust vectoring of aero engine, which contains complex rigid-flexible coupled multibody system with joints clearance and significantly reduces the efficiency in modeling and calculation, therefore the kinematics and dynamics analysis of axisymmetric vectoring nozzle mechanism based on deep neural network is proposed. The deep neural network model of the axisymmetric vector nozzle is established according to the limited training data from the physical dynamic model and then used to predict the kinematics and dynamics response of the axisymmetric vector nozzle. This study analyses the effects of joint clearance on the kinematics and dynamics of the axisymmetric vector nozzle mechanism by a data-driven model. It is found that the angular acceleration of the expanding blade and the driving force are mostly affected by joint clearance followed by the angle, angular velocity and position of the expanding blade. Larger joint clearance results in more pronounced fluctuations of the dynamic response of the mechanism, which is due to the greater relative velocity and contact force between the bushing and the pin. Since axisymmetric vector nozzles are highly complex nonlinear systems, traditional numerical methods of dynamics are extremely time-consuming. Our work indicates that the data-driven approach greatly reduces the computational cost while maintaining accuracy, and can be used for rapid evaluation and iterative computation of complex multibody dynamics of engine nozzle mechanism.

Efficient evidence generation to assess the clinical and economic impact of medical therapies is critical amid rising healthcare costs and aging populations. However, drug development and clinical trials remain far too expensive and inefficient for all stakeholders. On October 25–26, 2023, the Duke Clinical Research Institute brought together leaders from academia, industry, government agencies, patient advocacy, and nonprofit organizations to explore how different entities and influencers in drug development and healthcare can realign incentive structures to efficiently accelerate evidence generation that addresses the highest public health needs. Prominent themes surfaced, including competing research priorities and incentives, inadequate representation of patient population in clinical trials, opportunities to better leverage existing technology and infrastructure in trial design, and a need for heightened transparency and accountability in research practices. The group determined that together these elements contribute to an inefficient and costly clinical research enterprise, amplifying disparities in population health and sustaining gaps in evidence that impede advancements in equitable healthcare delivery and outcomes. The goal of addressing the identified challenges is to ultimately make clinical trials faster, more inclusive, and more efficient across diverse communities and settings.

A set of 68 simple sequence repeat (SSR) markers were selected from existing databases (including Medicago, soybean, cowpea and peanut) for the purpose of exploiting the transferability of SSRs across species and/or genera within the legume family. Primers were tested for cross-species and cross-genus fragment amplification with an array of 24 different legume accessions. Nearly one-third (30.78%) of the SSR primers screened generated reproducible and cross-genus amplicons. One hundred and seventeen cross-species polymorphic amplicons were identified and could be used as DNA markers. These polymorphic markers are now being used for characterization and evaluation of our collected and donated legume germ- plasm. The transferability of SSRs, mis-/multiple-primings, homologous/heterologous amplifications, single/multiple-amplicons and application of these amplicons as DNA markers are discussed. The transfer of SSR markers across species or across genera can be a very efficient approach for DNA marker development, especially for minor crops.

Cryogenic carbon capture (CCC) is an innovative technology to desublimate $\text {CO}_2$ out of industrial flue gases. A comprehensive understanding of $\text {CO}_2$ desublimation and sublimation is essential for widespread application of CCC, which is highly challenging due to the complex physics behind. In this work, a lattice Boltzmann (LB) model is proposed to study $\text {CO}_2$ desublimation and sublimation for different operating conditions, including the bed temperature (subcooling degree $\Delta T_s$), gas feed rate (Péclet number $Pe $) and bed porosity ($\psi$). The $\text {CO}_2$ desublimation and sublimation properties are reproduced. Interactions between convective $\text {CO}_2$ supply and desublimation/sublimation intensity are analysed. In the single-grain case, $Pe $ is suggested to exceed a critical value $Pe _c$ at each $\Delta T_s$ to avoid the convection-limited regime. Beyond $Pe _c$, the $\text {CO}_2$ capture rate ($v_c$) grows monotonically with $\Delta T_s$, indicating a desublimation-limited regime. In the packed bed case, multiple grains render the convective $\text {CO}_2$ supply insufficient and make CCC operate under the convection-limited mechanism. Besides, in small-$\Delta T_s$ and high-$Pe $ tests, $\text {CO}_2$ desublimation becomes insufficient compared with convective $\text {CO}_2$ supply, thus introducing the desublimation-limited regime with severe $\text {CO}_2$ capture capacity loss ($\eta _d$). Moreover, large $\psi$ enhances gas mobility while decreasing cold grain volume. A moderate porosity $\psi _c$ is recommended for improving the $\text {CO}_2$ capture performance. By analysing $v_c$ and $\eta _d$, regime diagrams are proposed in $\Delta T_s$–$Pe $ space to show distributions of convection-limited and desublimation-limited regimes, thus suggesting optimal conditions for efficient $\text {CO}_2$ capture. This work develops a viable LB model to examine CCC under extensive operating conditions, contributing to facilitating its application.

Background: We recently identified four molecular subgroups of meningioma with distinct biology and outcomes. While two (MG3/MG4) are associated with poor outcome, they display divergent transcriptional profiles (enriched in metabolic and cell cycling pathways, respectively) and therapeutic vulnerabilities (MG3 has no clear treatment target). We sought to understand drivers of these key differences at a chromatin level. Methods: We profiled MG3/MG4 meningiomas for common histone marks H3K27me3, H3K27Ac, H3K4me1, H3K4me3, H3K9me3, and H3K36me3. Multiple computational approaches were used to compare MG3 and MG4 tumours including superenhancer ranking, differential binding analysis, and unsupervised clustering. Results: Our cohort includes 11-20 meningiomas per histone mark. Clustering revealed striking separation of subgroups based on multiple histone marks, particularly H3K36me3. FOXC1, a known driver of the epithelial to mesenchymal transition, was identified as a recurrent superenhancer in both groups, whereas MG3-specific superenhancers mapped to immune regulatory networks. Integrated differential binding analysis confirmed an immune-rich microenvironment in MG3 tumours driven by multiple histone marks, suggesting a role for targeting novel immune checkpoint genes CD84 and CD48. Conclusions: This study is the first to apply integrated analysis of multiple histone modifications to aggressive meningioma. We further characterize MG3 tumours by identifying an epigenetically-driven immune phenotype and propose novel treatment targets.

Background: Meningiomas are the most common intracranial tumor with surgery, dural margin treatment, and radiotherapy as cornerstones of therapy. Response to treatment continues to be highly heterogeneous even across tumors of the same grade. Methods: Using a cohort of 2490 meningiomas in addition to 100 cases from the prospective RTOG-0539 phase II clinical trial, we define molecular biomarkers of response across multiple different, recently defined molecular classifications and use propensity score matching to mimic a randomized controlled trial to evaluate the role of extent of resection, dural marginal resection, and adjuvant radiotherapy on clinical outcome. Results: Gross tumor resection led to improved progression-free-survival (PFS) across all molecular groups (MG) and improved overall survival in proliferative meningiomas (HR 0.52, 95%CI 0.30-0.93). Dural margin treatment (Simpson grade 1/2) improved PFS versus complete tumor removal alone (Simpson 3). MG reliably predicted response to radiotherapy, including in the RTOG-0539 cohort. A molecular model developed using clinical trial cases discriminated response to radiotherapy better than standard of care grading in multiple cohorts (ΔAUC 0.12, 95%CI 0.10-0.14). Conclusions: We elucidate biological and molecular classifications of meningioma that influence response to surgery and radiotherapy in addition to introducing a novel molecular-based prediction model of response to radiation to guide treatment decisions.

Background: Liquid biopsy represents a major development in cancer research, with significant translational potential. Similarly, the integration of multiple molecular platforms has yielded novel insights into disease biology and heterogeneity. We hypothesise that applying contemporary multi-omic approaches to liquid biopsies will improve the power of current models. Methods: We have compiled a cohort of 51 patients with glioblastoma, brain metastasis, and primary CNS lymphoma who underwent CSF sampling as part of clinical care. Cell free methylated DNA and shotgun proteomic profiling was obtained from the CSF of each patient and used to build tumour-specific classifiers. Integrated classifiers were compared with single platform classifiers using multiple approaches. Results: In this study, we show that the DNA methylation and protein profiles of cerebrospinal fluid can be combined to fully discriminate lymphomas from their major diagnostic counterparts with perfect AUCs of 1 (95% confidence interval 1-1) and 100% specificity. Each integrated lymphoma classifier significantly outperforms single-platform classifiers, suggesting synergistic biology is obtained using multiple molecular platforms. Conclusions: We present the most specific and accurate CNS lymphoma classifier to date by integrating the methylome and proteome of CSF. This has important implications for the future of cancer diagnostics and generates immediate utility for patients with CNS lymphoma.

Background: Meningiomas have significant heterogeneity between patients, making prognostication challenging. For this study, we prospectively validate the prognostic capabilities of a DNA methylation-based predictor and multiomic molecular groups (MG) of meningiomas. Methods: DNA methylation profiles were generated using the Illumina EPICarray. MG were assigned as previously published. Performance of our methylation-based predictor and MG were compared with WHO grade using generalized boosted regression modeling by generating time-dependent receiver operating characteristic (ROC) curves and computing area under the ROC curves (AUCs) along with their 95% confidence interval using bootstrap resampling. Results: 295 meningiomas treated from 2018-2021 were included. Methylation-defined high-risk meningiomas had significantly poorer PFS and OS compared to low-risk cases (p<0.0001). Methylation risk increased with higher WHO grade and MG. Higher methylome risk (HR 4.89, 95%CI 2.02-11.82) and proliferative MG (HR 4.11, 95%CI 1.29-13.06) were associated with significantly worse PFS independent of WHO grade, extent of resection, and adjuvant RT. Both methylome-risk and MG classification predicted 3- and 5-year PFS and OS more accurately than WHO grade alone (ΔAUC=0.10-0.23). 42 cases were prescribed adjuvant RT prospectively although RT did not significantly improve PFS in high-risk cases (p=0.41). Conclusions: Molecular profiling outperforms conventional WHO grading for prognostication in an independent, prospectively collected cohort of meningiomas.

Multivariate regular variation is a key concept that has been applied in finance, insurance, and risk management. This paper proposes a new dependence assumption via a framework of multivariate regular variation. Under the condition that financial and insurance risks satisfy our assumption, we conduct asymptotic analyses for multidimensional ruin probabilities in the discrete-time and continuous-time cases. Also, we present a two-dimensional numerical example satisfying our assumption, through which we show the accuracy of the asymptotic result for the discrete-time multidimensional insurance risk model.

Let G be a finite group. A subgroup A of G is said to be S-permutable in G if A permutes with every Sylow subgroup P of G, that is, $AP=PA$. Let $A_{sG}$ be the subgroup of A generated by all S-permutable subgroups of G contained in A and $A^{sG}$ be the intersection of all S-permutable subgroups of G containing A. We prove that if G is a soluble group, then S-permutability is a transitive relation in G if and only if the nilpotent residual $G^{\mathfrak {N}}$ of G avoids the pair $(A^{s G}, A_{sG})$, that is, $G^{\mathfrak {N}}\cap A^{sG}= G^{\mathfrak {N}}\cap A_{sG}$ for every subnormal subgroup A of G.