Miracle-dz/UniFAR-FTUs huggingface dataset:
A two-dimensional hot-spot mixer model for phonon-cooled hot electron bolometers

A hot spot model for superconducting hot electron bolometers is presented based on a two-dimensional heat transport equation for electrons and phonons including heat trapping due to quasiparticle bandgap gradients. Skin effect concentrates the RF heating in lateral regions of the bridge and the bias current in the center. A reduction in conversion gain compared to a one-dimensional hot spot model is explained by the RF and bias heating profiles not being identical. An experimentally verified increase of the IF bandwidth from 3.5 GHz to 8 GHz when increasing bias voltage is predicted. IV curves, gain and noise are in very good agreement with measurements.
Efficient Clustering Based Routing for Energy Management in Wireless Sensor Network-Assisted Internet of Things

Wireless sensor networks (WSNs) play a huge part in arising innovations like smart applications, the Internet of Things, and numerous self-designed, independent applications. Energy exhaustion and efficient energy consumption are principal issues in wireless sensor networks. Energy is a significant and valuable asset of sensor nodes; early energy depletion ultimately leads to a shorter network lifetime and the replacement of sensor nodes. This research proposes a novel Power-Efficient Cluster-based Routing (PECR) algorithm. It takes in clustering using K-Means, the arrangement of Cluster Heads (CHs) and a Main Cluster Head (MCH), the optimal route choice, communication in light of the energy utilization model, cluster heads, and main cluster head alternation based on residual energy and relative location. PECR decreases traffic overburden, restricts energy usage, and at last, expands the network lifetime. Sensor nodes sense the information and transmit traffic to a Base Station (BS) through a legitimate channel. The results confirm it decreases the traffic overhead and effectively utilizes the energy assets. The simulation results show that PECR’s performance is 44% more improved than LEACH, EC, EECRP, and EECA algorithms. It is suitable for networks that require a stretched life.
A simulation study of statistical tests in logistic measurement error models

Measurement error models in logistic regression have been subject to much research during the last 10–15 years. In this work, we will focus on statistical testing in these models. We will compare the measurement error likelihood ratio test with a Wald-type test based on the so-called regression calibration method with both asymptotic- and bootstrap standard errors, and the score test, in some finite sample situations. We find that all tests perform approximately equally with regard to empirical power. With regard to the empirical test size, the Wald-type test based on the asymptotic standard error was too conservative, whereas the Wald-type test based on a trimmed boostrap standard error performed quite unstably. In summary, we will recommend the use of likelihood ratio tests or score tests in logistic measurement error situations.
Prognostic value of low-density lipoprotein cholesterol in IgA nephropathy and establishment of nomogram model

Background Dyslipidemia is closely related to kidney disease. We aimed to investigate the relationship between low-density lipoprotein cholesterol (LDL-C) and prognosis of IgA nephropathy (IgAN) and build a nomogram prognostic model. Methods 519 IgAN patients with 61 months median follow-up were enrolled and divided into two groups based on the cut-off value of baseline LDL-C (2.60 mmol/L): the high group (n=253) and the low group (n=266). Renal survival was assessed by Kaplan⁃Meier (KM) survival curve. Risk factors were identified by COX regression analysis. The area under the receiver operating characteristic (ROC) curves (AUC), concordance index (C-index), and calibration curves were applied to evaluate the nomogram model. Results KM survival curve analysis showed that the high LDL-C group had worse renal survival than the low LDL-C group (χ2 = 8.555, p=0.003). After adjusting for confounding factors, Cox regression analysis showed the baseline LDL-C level was an independent risk factor of end-stage renal disease (ESRD) in IgAN (HR=3.135, 95% CI 1.240~7.926, p =0.016). LDL-C, segmental sclerosis, tubular atrophy/interstitial fibrosis, the prevalence of cardiovascular disease, 24-hour proteinuria were identified and entered into the nomogram models, with AUC of 0.864, 0.827, and 0.792 respectively to predict the 5-, 8-, and 10-year risk of ESRD in IgAN. The C-index of this prediction model was respectively 0.862, 0.838, and 0.800 and was well-calibrated. Conclusion Elevated LDL-C level is a predictive factor for the prognosis of IgAN. We developed a nomogram model that can predict the risk of ESRD in IgAN by using LDL-C ≥ 2.60 mmol/L.
Displacement damage equivalent to dose in silicon devices

Particle‐induced displacement damage effects in silicon bipolar transistors, including those due to electrons and to fission neutrons, are correlated on the basis of the nonionizing energy deposited in the lattice by the primary knock‐on atoms. Deviations from linearity between damage effects and energy deposition are in a direction opposite to those expected from defect cluster models but can be accounted for in terms of the fraction of vacancy‐interstitial pairs initially formed that survive recombination.
Predicting the subcellular location of apoptosis proteins based on recurrence quantification analysis and the Hilbert—Huang transform

Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of programmed cell death. In this paper, the recurrent quantification analysis, Hilbert—Huang transform methods, the maximum relevance and minimum redundancy method and support vector machine are used to predict the subcellular location of apoptosis proteins. The validation of the jackknife test suggests that the proposed method can improve the prediction accuracy of the subcellular location of apoptosis proteins and its application may be promising in other fields.
Enhancing the performance of green GaN-based light-emitting diodes with graded superlattice AlGaN/GaN inserting layer

Green InGaN/GaN multiple quantum wells light-emitting diodes with graded superlattice (GSL) AlGaN/GaN inserting layer are investigated numerically and experimentally. Our simulation results indicate that GSL inserting layer can decrease the effective barrier height of holes by 57 meV, which makes holes more easily inject into the quantum wells. The piezoelectric polarization field near the last barrier is suppressed effectively by introducing of the GSL inserting layer. As a result, the efficiency droop radio is improved from 35.8% to 19.4% at current density of 100 A/cm−2.
Equine osteoarthritis: Strategies to enhance mesenchymal stromal cell-based acellular therapies

Osteoarthritis (OA) is a degenerative disease that eventually leads to the complete degradation of articular cartilage. Articular cartilage has limited intrinsic capacity for self-repair and, to date, there is no curative treatment for OA. Humans and horses have a similar articular cartilage and OA etiology. Thus, in the context of a One Health approach, progress in the treatment of equine OA can help improve horse health and can also constitute preclinical studies for human medicine. Furthermore, equine OA affects horse welfare and leads to significant financial losses in the equine industry. In the last few years, the immunomodulatory and cartilage regenerative potentials of mesenchymal stromal cells (MSCs) have been demonstrated, but have also raised several concerns. However, most of MSC therapeutic properties are contained in their secretome, particularly in their extracellular vesicles (EVs), a promising avenue for acellular therapy. From tissue origin to in vitro culture methods, various aspects must be taken into consideration to optimize MSC secretome potential for OA treatment. Immunomodulatory and regenerative properties of MSCs can also be enhanced by recreating a pro-inflammatory environment to mimic an in vivo pathological setting, but more unusual methods also deserve to be investigated. Altogether, these strategies hold substantial potential for the development of MSC secretome-based therapies suitable for OA management. The aim of this mini review is to survey the most recent advances on MSC secretome research with regard to equine OA.
New semiconductor alloy GaNAsBi with temperature‐insensitive bandgap

GaNyAs1–x–yBix alloys were grown by molecular beam epitaxy (MBE). Successful incorporation of N and Bi atoms was confirmed and their concentration was evaluated by Rutherford backscattering spectroscopy (RBS) and secondary ion mass spectroscopy (SIMS). Single‐peak photoluminescence (PL) spectra were observed in the temperature range of 10–300 K. The PL peak energy of GaNyAs1–x–yBix alloy decreased with increasing GaBi and GaN molar fractions with redshift coefficients of ∼62 meV/%Bi and ∼130 meV/%N, respectively, at room temperature. The temperature dependence of the PL peak energy in the temperature range of 150–300 K is much smaller than the temperature dependence of the bandgap for InGaAsP. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Laparoscopic Video Analysis Using Temporal, Attention, and Multi-Feature Fusion Based-Approaches

Adapting intelligent context-aware systems (CAS) to future operating rooms (OR) aims to improve situational awareness and provide surgical decision support systems to medical teams. CAS analyzes data streams from available devices during surgery and communicates real-time knowledge to clinicians. Indeed, recent advances in computer vision and machine learning, particularly deep learning, paved the way for extensive research to develop CAS. In this work, a deep learning approach for analyzing laparoscopic videos for surgical phase recognition, tool classification, and weakly-supervised tool localization in laparoscopic videos was proposed. The ResNet-50 convolutional neural network (CNN) architecture was adapted by adding attention modules and fusing features from multiple stages to generate better-focused, generalized, and well-representative features. Then, a multi-map convolutional layer followed by tool-wise and spatial pooling operations was utilized to perform tool localization and generate tool presence confidences. Finally, the long short-term memory (LSTM) network was employed to model temporal information and perform tool classification and phase recognition. The proposed approach was evaluated on the Cholec80 dataset. The experimental results (i.e., 88.5% and 89.0% mean precision and recall for phase recognition, respectively, 95.6% mean average precision for tool presence detection, and a 70.1% F1-score for tool localization) demonstrated the ability of the model to learn discriminative features for all tasks. The performances revealed the importance of integrating attention modules and multi-stage feature fusion for more robust and precise detection of surgical phases and tools.
Semiparametric estimation for inverse density weighted expectations when responses are missing at random

When responses are missing at random, we consider semiparametric estimation of inverse density weighted expectations, or equivalently, integrals of conditional expectations. An inverse probability weighted estimator and a full propensity score weighted estimator are proposed and shown to be asymptotically normal. The two estimators are asymptotically equivalent and achieve the semiparametric efficiency bound. The performances of the estimators are investigated and compared with simulation studies and a real data example.
The Effect of Stress of COVID-19 on Chinese Adults’ Work-Family Conflict: Testing a Moderated Mediation Model

Purpose The current study examined the effect of stress of COVID-19 on work-family conflict, how perceived work ability may mediate this effect, and lastly how perceived social support may moderate the various indirect pathway during COVID-19 pandemic. Methods A total of 2558 Chinese adults were recruited from the first author’s university completed the questionnaire including stress of COVID-19 scale, work-family conflict, perceived social support and perceived work ability scale. Results The present study showed that stress of COVID-19 was positively associated with work-family conflict while negatively associated with perceived work ability, which in turn, was negatively associated with work-family conflict. Perceived social support magnified the effects of perceived work ability on work-family conflict. Conclusion Findings of this study shed light on a correlation between stress of COVID-19 and work-family conflict. Moreover, this study emphasizes the value of intervening individuals’ perceived work ability and increasing the ability of perceived social support in the context of COVID-19.
The Rotation of the G0 Dwarf β Comae

The rotation of β Comae (HR 4983, HD 114710, G0 V) is studied using the available information from spectral line broadening and from rotational modulation. The line broadening yields v sin i = 4.10 ± 0.06 km s-1, which agrees with previous values. Rotational modulation was looked for but not seen in the photospheric parameters of temperature and granulation, although this might be a result of data sampling not being well suited for modulation studies. Rotational modulation is seen in the S index of the Ca II chromospheric emission. Two period sequences characterize β Comae between 1981 and 1994. The periods decline monotonically with time, paralleling the decline in magnetic activity as indicated by the average strength of the Ca II emission. We interpret the decrease in period as differential rotation coupled with systematic migration in latitude of the active regions. It is not possible to separate the differential rotation profile of β Comae from its rate and sense of latitude migration. We compare the changes of β Comae with the Sun's and point out similarities and differences.
Debt and Financial Fragility: Italian Non-Financial Companies after the Pandemic

This paper analyses the evolution of debt of Italian firms from 2010 to 2020 with special focus on the first year of the Covid-19 pandemic. By means of quantile regressions, our approach investigates several heterogeneities to assess the vulnerabilities of the most fragile firms. We find that, on average, Italian non-financial companies (NFCs) reduced their indebtedness over the sample period, a trend which did not get interrupted during the first year of the pandemic. By exploiting the high heterogeneity in the data, however, we find that the turmoil affected the most indebted firms and the trend of declining indebtedness for these firms was reversed. Moreover, sectors that were suspended ex lege during the first lockdown: i) already had the highest levels of the debt-to-assets ratios over our sample period, and ii) experienced the steepest increase in debt in 2020 relative to the previous year. Finally, our results show that highly indebted firms exhibit a qualitative different behaviour compared to the rest of the sample and that excessively piling up debt severely increases the likelihood of exiting the market.
GA-OH enhances the cytotoxicity of photon and proton radiation in HPV+ HNSCC cells

Introduction Treatment-related toxicity following either chemo- or radiotherapy can create significant clinical challenges for HNSCC cancer patients, particularly those with HPV-associated oropharyngeal squamous cell carcinoma. Identifying and characterizing targeted therapy agents that enhance the efficacy of radiation is a reasonable approach for developing de-escalated radiation regimens that result in less radiation-induced sequelae. We evaluated the ability of our recently discovered, novel HPV E6 inhibitor (GA-OH) to radio-sensitize HPV+ and HPV- HNSCC cell lines to photon and proton radiation. Methods Radiosensitivity to either photon or proton beams was assessed using various assays such as colony formation assay, DNA damage markers, cell cycle and apoptosis, western blotting, and primary cells. Calculations for radiosensitivity indices and relative biological effectiveness (RBE) were based on the linear quadratic model. Results Our results showed that radiation derived from both X-ray photons and protons is effective in inhibiting colony formation in HNSCC cells, and that GA-OH potentiated radiosensitivity of the cells. This effect was stronger in HPV+ cells as compared to their HPV- counterparts. We also found that GA-OH was more effective than cetuximab but less effective than cisplatin (CDDP) in enhancing radiosensitivity of HSNCC cells. Further tests indicated that the effects of GA-OH on the response to radiation may be mediated through cell cycle arrest, particularly in HPV+ cell lines. Importantly, the results also showed that GA-OH increases the apoptotic induction of radiation as measured by several apoptotic markers, even though radiation alone had little effect on apoptosis. Conclusion The enhanced combinatorial cytotoxicity found in this study indicates the strong potential of E6 inhibition as a strategy to sensitize cells to radiation. Future research is warranted to further characterize the interaction of GA-OH derivatives and other E6-specific inhibitors with radiation, as well as its potential to improve the safety and effectiveness of radiation treatment for patients with oropharyngeal cancer.
Observations of A4059 with Chandra, Hubble Space Telescope, and the Very Large Array: Unraveling a Complex Cluster/Radio Galaxy Interaction

We present a detailed reanalysis of Chandra data for the galaxy cluster A4059 and its central radio galaxy, PKS 2354-35. We also present new 1.4 and 4.7 GHz CnB-array radio data from the Very Large Array, as well as a short archival WFPC2 image from the Hubble Space Telescope. The presence of a strong interaction between this radio galaxy and the intracluster medium (ICM) was suggested by Huang & Sarazin on the basis of a short observation by the High Resolution Imager on ROSAT and confirmed in our preliminary analysis of the Chandra ACIS-S data. In particular, X-ray imaging clearly shows two cavities within the ICM that are approximately aligned with the radio galaxy axis. However, using our new radio maps (which are at lower frequencies and better matched to searching for ~1' structures than the previous high-quality maps), we fail to find a detailed correspondence between the ~1' scale radio lobes and the ICM cavities. This suggests that the cavities are "ghosts" of a previous burst of powerful activity by PKS 2354-35. This is supported by detailed, spatially resolved X-ray spectroscopy that fails to find any shock-heated ICM, suggesting that the cavities are evolving subsonically. We also examine the nature of the central asymmetric ridge (or bar) of X-ray emission extending for ~30 kpc southwest of the cluster center that has been noted in these previous analyses. We find the ridge to be denser and cooler than, but probably in pressure balance with, its surroundings. The thermal evolution of this structure seems to be dominated by radiative cooling, possibly enhanced by the radio galaxy-ICM interaction. We discuss several possible models for the formation of this southwest ridge and find none of them to be entirely satisfactory. In our preferred model, the southwest ridge is due to radiative cooling induced by an interaction between a radio galaxy-driven disturbance and a preexisting bulk ICM flow. The presence of such a bulk flow (with a velocity of ~500 km s-1 projected on the plane of the sky) is suggested by the off-center nature of the pair of X-ray cavities. Such a bulk flow can be created during a cluster/subcluster merger—the presence of a prominent dust lane in the cD galaxy of A4059, ESO 349-G010, is circumstantial evidence for just such a merger.
Exploring the influence of individual daily activity patterns on activity-space segregation

Activity-space segregation is a new topic in urban segregation studies. The existing literature did not fully explain its mechanisms. In this study, we tested the hypothesis whether activity-space segregation is influenced by individual daily activity patterns. The dynamic ambient population that individuals interact with was identified with mobile phone big data and the individuals’ experienced segregation at the activity space was measured with travel survey small data. This study compared the differences in individuals’ daily activity patterns by different social-economic groups and examined the influence of the spatiotemporal pattern on the activity-space segregation. It has found that: (1) The degree of segregation in non-mandatory activity spaces during the day is less than that in mandatory activity spaces, and the degree of segregation in residence is the highest. (2) Disadvantaged populations have less leisure time and smaller activities space, and they are subject to greater time and space constraints. Spatiotemporal patterns affect the degree of an individual’s segregation. Those who have less leisure time and shorter travel distances experience higher activity-space segregation. This study has both theoretical and practical significance. The social interaction in non-mandatory activities is very important for decreasing activity-space segregation. It facilitates scientific decision-making for the government.
GaN and InGaN Metal-Semiconductor-Metal Photodetectors with Different Schottky Contact Metals

The characterizations of n-type doped GaN, p-type doped GaN and n-type doped In0.2Ga0. 8N Schottky metal-semiconductor-metal (MSM) photodetectors were reported. The epilayers were grown on sapphire by metalorganic chemical vapor deposition (MOVCD). Schottky contacts were fabricated using Au, Ti, Ni and Pt metals. The dark and illuminated current–voltage characteristics of GaN and InGaN MSM photodetectors with different Schottky metals were studied. The n-GaN MSM photodetectors with Au Schottky contacts showed better responsivity than those with other metals and they were also better than Au/p-GaN and Ti/n-In0.2Ga0. 8N MSMs. The effects of the pitch width between the interdigitate fingers and the thickness of Schottky metals on the characteristics of photocurrents were also studied.
Nonlinear Analysis of Masonry Arches Strengthened with Composite Materials

The nonlinear behavior of masonry arches strengthened with externally bonded composite materials is investigated. A finite-element (FE) formulation that is specially tailored for the nonlinear analysis of the strengthened arch is developed. The FE formulation takes into account material nonlinearity of the masonry construction and high-order kinematic relations for the layered element. Implementation of the above concept in the FE framework reduces the general problem to a one-dimensional nonlinear formulation in polar coordinates with a closed-form representation of the elemental Jacobian matrix (tangent stiffness). A numerical study that examines the capabilities of the model and highlights various aspects of the nonlinear behavior of the strengthened masonry arch is presented. Emphasis is placed on the unique effects near irregular points and the nonlinear evolution of these effects through the loading process. A comparison with experimental results and a discussion of the correlating aspects and the ones that designate needs of further study are also presented.