Miracle-dz/UniFAR-FTUs huggingface dataset:
CEO Overconfidence and Corporate Innovation Outcomes: Evidence From China

This study examines how chief executive officer (CEO) overconfidence can influence the quantity, quality and direction of corporate innovation using Chinese firms for the period 2009–2016. Our results suggest that overall, CEO overconfidence has a positive impact on firm innovation productivity. Furthermore, this effect is significant for Chinese non-SOEs but not for Chinese SOEs. Specifically, an overconfident CEO can facilitate firm innovation in new technological areas but not in the firm’s existing areas. Additionally, we find that internal controls can regulate the relationship between CEO overconfidence and innovation. Interestingly, when the internal control level is too high or too low, the correlation between CEO overconfidence and innovation productivity is not significant.
Robust Prediction of Prognosis and Immunotherapeutic Response for Clear Cell Renal Cell Carcinoma Through Deep Learning Algorithm

It is of great urgency to explore useful prognostic markers and develop a robust prognostic model for patients with clear-cell renal cell carcinoma (ccRCC). Three independent patient cohorts were included in this study. We applied a high-level neural network based on TensorFlow to construct the robust model by using the deep learning algorithm. The deep learning-based model (FB-risk) could perform well in predicting the survival status in the 5-year follow-up, which could also significantly distinguish the patients with high overall survival risk in three independent patient cohorts of ccRCC and a pan-cancer cohort. High FB-risk was found to be partially associated with negative regulation of the immune system. In addition, the novel phenotyping of ccRCC based on the F-box gene family could robustly stratify patients with different survival risks. The different mutation landscapes and immune characteristics were also found among different clusters. Furthermore, the novel phenotyping of ccRCC based on the F-box gene family could perform well in the robust stratification of survival and immune response in ccRCC, which might have potential for application in clinical practices.
Has the COVID-19 Pandemic Affected Breast Cancer Stage and Surgical Volume?

Background This study investigates the effects of COVID-19 on the breast cancer stage and the volume of breast cancer surgery in a specialized breast institute. Methods Data of 332 patients who were diagnosed and treated for breast cancer between December 2019 and November 2020 were evaluated retrospectively according to periods of pandemic. Results A significant decrease in the number of operations, especially upfront surgeries rather than surgeries after neoadjuvant chemotherapy, was detected in the early period of the COVID-19 pandemic. It was found that patients with complaints were mostly admitted during this period (p = 0.024). No statistical significance was found for age, sex, side of the tumor, type of tumor, surgery to breast, and axilla. Following the early period of the pandemic, it was observed that patients with mostly luminal, early-stage, and less axillary nodal involvement (p < 0.05) were admitted, and as a result, it was founded that upfront surgeries increased, although no change in TNM staging was observed. However, it did affect the decision of initial treatment. Thus, the number of upfront surgeries was significantly higher than the NCT group (p = 0.027) following the early period. Conclusion Surgical volume is significantly affected in the early period of the COVID-19 pandemic. To overcome overload due to delayed surgeries related to pandemics, some hospitals should be spared for oncological treatments. Following the early period, mostly luminal type, early-stage patients were admitted, probably because of increased self-awareness and short wave duration, but the breast cancer stage was not affected.
Plasma Metabolomics Reveals Diagnostic Biomarkers and Risk Factors for Esophageal Squamous Cell Carcinoma

Esophageal squamous carcinoma (ESCC) has a high morbidity and mortality rate. Identifying risk metabolites associated with its progression is essential for the early prevention and treatment of ESCC. A total of 373 ESCC, 40 esophageal squamous dysplasia (ESD), and 218 healthy controls (HC) subjects were enrolled in this study. Gas chromatography-mass spectrometry (GC/MS) was used to acquire plasma metabolic profiles. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate the potential diagnosis and prediction ability markers. The levels of alpha-tocopherol and cysteine were progressively decreased, while the levels of aminomalonic acid were progressively increased during the various stages (from precancerous lesions to advanced-stage) of exacerbation in ESCC patients. Alpha-tocopherol performed well for the differential diagnosis of HC and ESD/ESCC (AUROC>0.90). OR calculations showed that a high level of aminomalonic acid was not only a risk factor for further development of ESD to ESCC (OR>13.0) but also a risk factor for lymphatic metastasis in ESCC patients (OR>3.0). A low level of alpha-tocopherol was a distinguished independent risk factor of ESCC (OR< 0.5). The panel constructed by glycolic acid, oxalic acid, glyceric acid, malate and alpha-tocopherol performed well in distinguishing between ESD/ESCC from HC in the training and validation set (AUROC>0.95). In conclusion, the oxidative stress function was impaired in ESCC patients, and improving the body’s antioxidant function may help reduce the early occurrence of ESCC.
Title: Cyclic, condition-independent activity in primary motor cortex predicts corrective movement behavior Abbreviated Title: Cyclic neural activity in corrective movements

1 Reaching movements are known to have large condition-independent neural activity and cyclic 2 neural dynamics. A new precision center-out task was performed by rhesus macaques to test the 3 hypothesis that cyclic, condition-independent neural activity in the primary motor cortex (M1) occurs not 4 only during initial reaching movements but also during subsequent corrective movements. Corrective 5 movements were observed to be discrete with time courses and bell-shaped speed profiles similar to the 6 initial movements. Condition-independent cyclic neural trajectories were similar and repeated for initial 7 and each additional corrective submovement. The phase of the cyclic condition-independent neural 8 activity predicted the time of peak movement speed more accurately than regression of instantaneous 9 firing rate, even when the subject made multiple corrective movements. Rather than being controlled as 10 continuations of the initial reach, a discrete cycle of motor cortex activity encodes each corrective 11 submovement. 12 Significance Statement 13 During a precision center-out task, initial and subsequent corrective movements occur as discrete 14 submovements with bell-shaped speed profiles. A cycle of condition-independent activity in primary 15 motor cortex neuron populations corresponds to each submovement, such that the phase of this cyclic 16 activity predicts the time of peak speeds—both initial and corrective. These submovements accompanied 17 by cyclic neural activity offer important clues into how we successfully execute precise, corrective 18 reaching movements and may have implications for optimizing control of brain-computer interfaces. 19
Single-Photon Camera Guided Extreme Dynamic Range Imaging

Reconstruction of high-resolution extreme dynamic range images from a small number of low dynamic range (LDR) images is crucial for many computer vision applications. Current high dynamic range (HDR) cameras based on CMOS image sensor technology rely on multi-exposure bracketing which suffers from motion artifacts and signal-to-noise (SNR) dip artifacts in extreme dynamic range scenes. Recently, single-photon cameras (SPCs) have been shown to achieve orders of magnitude higher dynamic range for passive imaging than conventional CMOS sensors. SPCs are becoming increasingly available commercially, even in some consumer devices. Unfortunately, current SPCs suffer from low spatial resolution. To overcome the limitations of CMOS and SPC sensors, we propose a learning-based CMOS-SPC fusion method to recover high-resolution extreme dynamic range images. We compare the performance of our method against various traditional and state-of-the-art baselines using both synthetic and experimental data. Our method outperforms these baselines, both in terms of visual quality and quantitative metrics.
Morphology Filter for Infrared Dim and Small Target Background Suppression

This research is conducted on the background suppression in detecting infrared small dim target.First,a combinatorial structure is proposed to improve the structure of morphology filter.Combining linear filtering with nonlinear filtering technique,then,lowpass and morphology filter are used to remove the background clutter for the image under the influence of background clutter and random noise.Compared with the lowpass filter and the morphology filter,the new approach's performance is much better in the case of low signal noise ratio.The algorithm effectively filters the intense clutter and preserves the target signal,and the SNR is improved effectively.
Economic analysis of TQM adoption in the construction sector

Researchers have dedicated considerable efforts to examining and explaining the capacity of total quality management (TQM) to generate wealth, from the conceptual framework of the resource-based view. From this approach, TQM is basically an inimitable resource that generates competitive advantages. This analytical perspective can help justify and explain the behaviour of the firms that have adopted TQM, but not that of the firms that do not intend to adopt this management approach in the future. In the current work, we aim to make progress in this direction. We offer arguments, from an economic and organisational perspective, that help explain how TQM's capacity to generate wealth is not uniform in all firms but is contingent on variables such as the firm's size and subsector. The results of the empirical analysis, involving a sample of Spanish construction firms, provide support for two hypotheses postulating relations between the firm's optimum level of TQM adoption and its size and subsector.
Green Development Path of South Korean Foreign Trade

Purpose – This paper aims to examine the environmental effects of South Korean foreign trade, and the changing relationship between industrial “three wastes” emissions and foreign trade. Design/methodology – Based on time series data of South Korean foreign trade and industrial “three wastes” from 2009 to 2019, a VAR model was used to analyze the long-term internal links and dynamic changes between foreign trade and environmental pollution. Findings – Variance decomposition analysis shows that for the three types of pollutants, self-impact contributes the most to the variance decomposition. It follows that South Korean foreign trade has a certain negative impact on the environment, and this impact has a certain sustainability. Originality/value – This paper contributes to the study on the relationship between foreign trade and environmental pollution. It theoretically proposes a coordinated development path for foreign trade development and green development based on the environmental impact of foreign trade, to provide a reference for the development of collaborative promotion.
Synchronization of rumen degradable protein with non-fiber carbohydrate on microbial protein synthesis and dairy ration digestibility

Background and Aim: Dairy ration formulations should consider the synchronization of the rumen degradable protein (RDP) to rumen undegradable protein (RUP) ratio (RDPR) with non-fiber carbohydrate (NFC) to achieve optimum microbial protein synthesis (MPS), reduce feed costs, and reduce N excretion to the environment. This study aimed to investigate the effect of RDPR and NFC synchronization on in vitro digestibility, fermentability, and MPS. Materials and Methods: The experiment used a 3×3 factorial randomized block design with four replications. The first factor was RDPR (RDPR1=50:50; RDPR2=55:45; RDPR3=60:40) and the second factor was NFC levels (NFC1=30%, NFC2=35%, NFC3=40%). The experimental diets were evaluated using a two-stage in vitro method. The examined parameters included rumen pH, NH3 concentration, total volatile fatty acid (VFA) concentration, the molar proportion of VFAs, rumen microbes (protozoa and total bacteria population), and MPS. Data were analyzed using ANOVA, followed by the Duncan test. Results: The results show that neither RDPR nor NFC affected rumen pH, NH3, total VFA, and the rumen microbe population. The interaction between RDPR and NFC affected the molar proportion of acetate, iso-butyrate, and n-valerate. The combination of RDPR1 and NFC1 produced a lower molar proportion of acetate (49.73%) than the other treatment combinations (>54%). The acetate to propionate ratio was influenced by the NFC levels, in which NFC2 and NFC3 produced the highest ratio (p<0.05). MPS was affected by RDPR and NFC, but not by their interaction. Treatments NFC2 and RDPR3 produced the highest MPS. NFC affected the dry matter and organic matter digestibility (DMD and OMD), with treatment NFC3 resulting in the highest DMD and OMD. Conclusion: The combination of a 60:40 RDPR with 35% NFC resulted in the best synchronization of protein and energy available for MPS and digestion activity in the rumen.
Effect of Pollution Non-uniformity on Electric Field of Contaminated Insulator

The three-dimension electric field and potential distribution of several typical non-uniform polluted insulators are calculated by use of the finite element analysis software——ANSYS.According to the mechanism of pollution flashover,the variation of electrical field after formation of dry bands and effect of their location are calculated.Results are analyzed by surface resistor model of contaminated insulator which has been established.The results show that all kinds of non-uniform pollution have considerable effects on the electric field distribution of insulator and space around.The wet pollution layer connecting the metal cap or pin would deduce the electric field around HV electrodes.The pollution non-uniformity on upper and lower surface has significant effect,however that in radial direction has weak effect.The maximum electric field on dry band is related to the location and has a "U"shape.
RETROREFLECTIVITY REQUIREMENTS FOR PAVEMENT MARKINGS

Subjective evaluations by 59 observers and quantitative measurements of in-place roadway markings were made in order to determine minimum field luminance and retroreflectivity levels for pavement markings. A minimum luminance value was also determined for the same observers through subjective evaluations and quantitative measurements under controlled and repeatable laboratory conditions. For the field test, more than 90% of the subjects rated a marking retroreflectance of 93 mcd/sq m/lx as adequate or more than adequate for night conditions. More than 98% of the subjects rated all locations having a marking luminance of 3.84 cd/sq m or greater as adequate or more than adequate, corresponding to a measured retroreflectivity of 94 mcd/sq m/lx. For the laboratory study, more than 90% of the subjects rated the simulated markings with a luminance of 0.38 cd/sq m as adequate or more than adequate. Subjects used in this research represented a relatively young population, and the study was conducted under the ideal field conditions. It is likely that an older driver, operating in a real-world driving situation, would require a retroreflectivity value higher than 93 mcd/sq m/lx.
Estimating Remaining Useful Life Under Uncertain Degradation Measurements

Remaining useful lifetime( RUL) estimation is a key issue in prognosis and health management for industrial systems. Currently,the use of the observed degradation data of a system holds promise to estimate its RUL. Due to the effect of system 's stochastic deterioration and uncertain measurements,the measured data are inevitably contaminated by the stochasticity of the degradation and measurement uncertainty. How ever,in current studies of the RUL estimation based on the measured data,there is no report considering the effect of the degradation stochasticity and measurement uncertainty on the estimated RUL distribution. In this paper,a new degradation modeling approach is proposed based on Wiener process,w hich considers system 's stochastic deterioration and uncertain measurements simultaneously,and the Kalman filtering technique is utilized to estimate the underlying degradation state. On the basis of the estimated degradation state,the analytical RUL distribution is derived w hich accounts for the uncertainties in the estimated degradation state and measurements. Additionally,a parameter estimation method for the developed model is presented based on the maximum likelihood method. Finally,a case study for gyros verifies the proposed method and the results indicate that the proposed method is superior to the method w ithout considering uncertain measurements and can improve the accuracy of the estimated RUL.
ON THE PAVEMENT PERFORMANCE TEST OF STABILIZED UNIFORMLY-GRADED GRAVEL SOIL WITH LIME

The problem of stabilized uniformly-graded gravel soil with lime used in the top layer of subgrade of highway with semi-rigid basement and pitched road surface is discussed.The material property and basic physical-mechanical property of uniformly-graded gravel soil and its swelling-shrinkage behavior are performed on the spot.The reasonable construction distribution ratio is presented,which provides reference to the construction of highway in similar project.
Hydra : Resilient and Highly Available Remote Memory

We present Hydra, a low-latency, low-overhead, and highly available resilience mechanism for remote memory. Hydra can access erasure-coded remote memory within a single-digit microsecond read/write latency, significantly improving the performance-efficiency trade-off over the state-of-the-art -- it performs similar to in-memory replication with 1.6X lower memory overhead. We also propose CodingSets, a novel coding group placement algorithm for erasure-coded data, that provides load balancing while reducing the probability of data loss under correlated failures by an order of magnitude. With Hydra, even when only 50% of memory is local, unmodified memory-intensive applications achieve performance close to that of the fully in-memory case in the presence of remote failures and outperform the state-of-the-art solutions by up to 4.35X.
Bioactive Amines

patients are interviewed by a whole team. Firstly it avoids the sort of intimidation thatâ€¢an individual patient might feel when confronted by several members of staff en masseâ€”'much worse than vivas' according to your correspondent (Journal, January 1978, 132, 112). The group setting seems to enabl@ patientsto questionstaffin a way which isseldom seen in the traditional ward round. We feel that thisi approach is conducive to the sharing of decision making with patients and therefore therapeutic in itself; patients seem to be able to feel their way towards participating in making decisions without arousing too much staff anxiety, or insecurity in themselves. Secondly our type of approach is a way of enforcing rather than undermining the therapeutic momentum of self-help among patientsâ€”a force which I believe is potentially a highly effective tool in the treatment of psychiatric illness. Finally our ward round provides a suitable framework in which members of staff can examine their own motives and wishes during decision-making, thereby improving the quality of decisions.
Advances in working fluids for Organic Rankine cycle

Organic Rankine cycle(ORC)is an effective method for low-grade heat energy recovery,and its working fluid option is a key factor for the cycle performance.After a brief introduction of ORC and characteristics of ideal organic working fluids,the advances in ORC working fluids for five typical heat sources,i.e.industry waste heat,geothermal heat,solar energy,biomass energy and LNG cold energy were presented.Furthermore,based on an analysis of pending problems,the future research efforts on ORC working fluids were also discussed.
Editorial Preface

The introduction of neuroimaging techniques for the study of brain structure and function has revolutionised the endeavour to elucidate the pathology of psychiatric disorder, the Holy Grail in psychiatry (Krishnan, 1990). Emil Kraepelin discovered the two major mental disorders, dementia praecox and manic-depression, and conceived their aetiology in brain pathology. It was Alois Alzheimer, however, his most successful student, who discovered the neuropathology of Alzheimer's disease. Sigmund Freud, who started his inquiries in brain science, lost faith and shifted to the study of the mind. Brain science and mind ‘science’ rapidly became odd bed fellows and parted company. The breakdown in communication fostered a mistrust in both parties, aborting endeavours of reconciliation. The evidence for the neuropathology of the ‘functional’ psychoses has, however, been inconclusive. It was the advent of brain-imaging techniques that rejuvenated brain sciences and modern neurosciences. The introduction of neuroimaging techniques, such as the electroencephalogram (EEG) in the 1920s and the whole-brain blood-flow techniques (Berger, 1929; Kety & Schmidt, 1948), antedated the discovery of psychotropic drugs. Pneumoencephalography was also applied to study brain structure in schizophrenia (Storey, 1966). The true methodological leap, however, was the introduction of computerised methods to construct three-dimensional images from two-dimensional data, enabling the development of computerised tomography (CT), magnetic resonance imaging (MRI), positron-emission tomography (PET) and single-photon emission computerised tomography (SPECT).
Three-dimensional routed manifolds with externally inserted cables

The Automatic Test Equipment industry must maintain a tester accuracy of roughly one tenth the pulsewidth of the device under test (DUT). Funneling a vast number of electrical signals into a very tiny area to contact the DUT while still maintaining good signal fidelity is a problem not only in the ATE industry, but also for personal computers, network servers and supercomputers. As the speed of processors increase, ATE companies must find new ways to achieve the required accuracy. A solution to this problem is investigated whereby a large number of semi-rigid coaxial wires are routed in 3D space from a low-density array (the tester side) to a highdensity array (the DUT side). The three dimensional paths are subject to bend constraints and cannot intersect with any other paths. A software program has been written and tested that is able to find solutions to this 3D routing problem for many test cases. For relatively simple test cases with less than 15 wires, solutions can typically be found in under a minute. Once the geometries of the paths are determined, a block is made with 3D tunnels transversing through it. This part is created using a 3D additive process (e.g. stereolithography), and the coaxial wires are pushed into each tunnel. The maximum force used to insert a wire into a tunnel is limited by the force at which buckling occurs. Uncontrolled buckling of the coaxial wire will compromise electrical signal fidelity or cause opens and must therefore be prevented. To this end, models have been developed to predict the force required to push wires into a predetermined path. Relatively good experimental agreement, within 20% in many cases, was achieved for paths with radii of curvature to wire diameter ratios between 200:1 and 10:1. A perfectly elastic beam model is developed as well as an elastic-plastic beam model. Additional models are developed which account for the friction and the effect of clearance between the tunnel