Miracle-dz/UniFAR-FTUs huggingface dataset:
Literature Review of Innovation and Entrepreneurship Management

Innovation management is the industrial implementation and exploitation of unique thoughts and examinations and innovation practice in an association to promote and make new ideas and business possibilities possible. It consists of innovation strategy, culture, thoughts management, and implementation of innovation processes. This paper analyses the management innovation and entrepreneurship of innovation management through literature research. Innovation management in the hotel industry, education, manufacturing, government, and finance innovation management of the banking industry have carried out a comprehensive theoretical review. And hope to provide a general appearance of innovation, management, creativity, and reliable systems.
Effects of climate and soil properties on regional differences in nitrogen use efficiency and reactive nitrogen losses in rice

Nitrogen (N) use efficiency worldwide varies greatly due to climate, agronomic, and soil factors. However, the information on individual effects of these factors on N use efficiency is crucial but has remained scanty. Given that climate cannot be regulated, understanding the relative importance of fertilizer and soil variations on regional differences in N use efficiency is critical. Here, we constructed a database of 302 studies from 1986 to 2020 in East and Northeast China to determine the effects of climate, soil properties, and fertilizer N (FN) rate on variations in N use efficiency (agronomic efficiency (AE), apparent recovery efficiency (RE), physiological efficiency (PE), N harvest index, partial factor productivity), N surplus, grain N content, and reactive N (Nr) losses (N2O emissions, NH3 volatilization, Nr leaching, and runoff). Rice yield was comparable between two regions under farmers’ N practices, yet the N input was considerably higher in East China. All indices of N use efficiency, except RE, are higher in Northeast China. Differences in AE were dominated by the ability of the plant to mobilize N (PE) rather than N uptake (RE), FN, or Nr loss. Soil properties and FN related to optimizable N management accounted for 29% (RE), 39% (PE), and 43% (Nr losses) of the variations, of which key factors as pH showed a negative effect while available N (AN) correlated positively to the N use efficiency. To realize high N use efficiency, pivotal effects of pH, AN, and FN on N use efficiency under certain climate zone should be considered.
The Analysis of Capital Structure Based on Two Hypothetical Firms

A corporate’s financing of its real investments has recently attracted considerable attention from academics who have proposed various theories. This paper firstly studies the Gordon growth model and the weighted average cost of capital formula with the empirical tests and the sensitivity analysis. Then, we exam changes in a company’s market value concerning different combinations of capital structures and identify an arbitrage opportunity based on the Modigliani-Miller propositions. Finally, we investigate the relationship between a firm’s funding sources and its profit using panel data regression to figure out the optimal way to financing. These studies enable us to realize the fundamental relationship between a corporate’s price and its capital structure. In light of those studies, we could have some insightful ideas regarding funding decision-making in reality.
Transformer-based Face Anti-Spoofing Algorithm

For the face anti-spoofing tasks, most scholars at this stage use a convolutional neural network framework.In this paper, We rely on the powerful feature extraction capability of transformer and deepen the transformer network loop depth by improving it.And achieved good proformace on CASIA-SURF datasets,reduced the EER to 0.025 on the CASIA-SURF dataset and improved accuracy to the 99.6%.
UTILIZATION POSSIBILITIES OF UNMANNED AERIAL SYSTEMS IN POSTAL AND PARCEL SERVICES

This article deals with the use of unmanned aerial systems in postal and delivery services. Unmanned systems are characterized by their classification and briefly closer to the possibility of using unmanned equipment are presented. An overview of the current state is created in the transport of mail and parcels and types of consignments. The achievements resulting from the choice of an appropriate UAV classification and financial analysis are applied in the design of the most appropriate options for the carriage of mail and mail systems.
Evidence synthesis Timing of sedentary behaviour and access to sedentary activities in the bedroom and their association with sleep quality and duration in children and youth: a systematic review

frequencies of screen time were associated with unfavourable body com-position, behavioural conduct, fitness, self-esteem and clustered cardiometabolic risk. In contrast, reading and homework were positively associated with academic achievement. 4 Other recent systematic reviews and meta-analyses report that higher levels of screen-based sedentary behaviours are also associated with increased risk of depression, 5,6 although questions remain regarding the magnitude of this relationship. 7 Abstract Background: The purpose of this study was to systematically review the relationship between the timing of sedentary behaviours and access to sedentary activities in the bedroom with sleep duration and quality in children and youth. A secondary purpose was to examine whether these relationships differ when comparing screen-based and non-screen-based sedentary activities. Methods: We searched four databases for peer-reviewed studies published between 1 January 2010 and 19 January 2021. Risk of bias assessment for each study and certainty of evidence were assessed using the GRADE framework. Results: We identified 44 eligible papers reporting data from 42 separate datasets and including 239 267 participants. Evening participation in screen-based sedentary behaviours and access to screen-based devices in the bedroom were associated with reduced sleep duration and quality. Daytime screen use was also associated with reduced sleep duration, although this was examined in relatively few studies. Whether performed during the day or night, non-screen-based sedentary behaviours were not consistently associated with sleep duration or quality. The quality of evidence was rated as low to very low for all outcomes. Conclusion: In order to maximize sleep duration and quality, children and youth should be encouraged to minimize screen time in the evening and remove screens from bedrooms. (PROSPERO registration no.: CRD42020189082)
CORPORATE SOCIAL RESPONSIBILITY DISCLOSURE: EFFECTS ON COMPANIES ECONOMIC PERFORMANCE AND RISK

We investigated the corporate social responsibility (CSR) disclosure effect on corporate economic performance (CEP) and risk on Brazilian companies, under the (in)consistent CSR disclosure point of view. To distinguish consistent CSR disclosure from inconsistent CSR disclosure, we made use of a premises pool based on CSR disclosure continuity and standardization to indicate consistent CSR disclosure signaling. We used the non-financial disclosure of the Global Reporting Initiative (GRI) repository as a proxy for CSR disclosure and the Corporate Sustainability Index (CSI) as a proxy for CSR. We address the mutual causality between CSR, CSR disclosure and CEP and selection bias problems by controlling a second stage for the CSI and the GRI Inverse Mills Ratio (IMR), whose scores associated with the probability of companies to make part of the CSI or to do GRI disclosure were calculated in two first-stage probits. We found that when companies make CSR disclosures via GRI there are, on average, reductions in the three studied indicators? book and market performances and risk? and that in cases where the CSR disclosure is more consistent, the reductions in the three indicators are even larger. ABSTRACT We investigated the corporate social responsibility (CSR) disclosure effect on corporate economic performance (CEP) and risk on Brazilian companies, under the (in)consistent CSR disclosure point of view. To distinguish consistent CSR disclosure from inconsistent CSR disclosure, we made use of a premises pool based on CSR disclosure continuity and standardization to indicate consistent CSR disclosure signaling. We used the non-financial disclosure of the Global Reporting Initiative (GRI) repository as a proxy for CSR disclosure and the Corporate Sustainability Index (CSI) as a proxy for CSR. We address the mutual causality between CSR, CSR disclosure and CEP and selection bias problems by controlling a second stage for the CSI and the GRI Inverse Mills Ratio (IMR), whose scores associated with the probability of companies to make part of the CSI or to do GRI disclosure were calculated in two first-stage probits. We found that when companies make CSR disclosures via GRI there are, on average, reductions in the three studied indicators—book and market performances and risk—and that in cases where the CSR disclosure is more consistent, the reductions in the three indicators are even larger.
Distraction osteogenesis ​ for treatment of a shortened first metatarsal after failed first metatarsophalangeal joint

Foot and Ankle Online Journal 13 (3): 9 Distraction osteogenesis is well documented in the literature as a viable treatment option for large bony defects and brachymetatarsia. Few studies have examined the use of this technique after failed arthrodesis or arthroplasty of the 1st metatarsophalangeal joint (MPJ). Acute correction with autograft is typically the procedure of choice for treatment of defects of the 1st MPJ. However, the amount of length that can be achieved is limited in acute correction and distraction osteogenesis should be considered for larger defects. This case study presents our treatment of a failed first MPJ arthroplasty that resulted in a defect at the 1 ​ st MPJ of greater than 2 centimeters and our technique of using external fixation followed by internal fixation to regain
SECOM: Towards a convention for security commit messages

One way to detect and assess software vulnerabilities is by extracting security-related information from commit messages. Automating the detection and assessment of vulnerabilities upon security commit messages is still challenging due to the lack of structured and clear messages. We created a convention, called SECOM, for security commit messages that structure and include bits of security-related information that are essential for detecting and assessing vulnerabilities for both humans and tools. The full convention and details are available here: https://tqrg.github. io/secom/.
dPRO: A Generic Performance Diagnosis and Optimization Toolkit for Expediting Distributed DNN Training

Distributed training using multiple devices (e.g., GPUs) has been widely adopted for learning DNN models over large datasets. However, the performance of large-scale distributed training tends to be far from linear speed-up in practice. Given the complexity of distributed systems, it is challenging to identify the root cause(s) of inefficiency and exercise effective performance optimizations when unexpected low training speed occurs. To date, there exists no software tool which diagnoses performance issues and helps expedite distributed DNN training, while the training can be run using different deep learning frameworks. This paper proposes dPRO, a toolkit that includes: (1) an efficient profiler that collects runtime traces of distributed DNN training across multiple frameworks, especially fine-grained communication traces, and constructs global data flow graphs including detailed communication operations for accurate replay; (2) an optimizer that effectively identifies performance bottlenecks and explores optimization strategies (from computation, communication, and memory aspects) for training acceleration. We implement dPRO on multiple deep learning frameworks (TensorFlow, MXNet) and representative communication schemes (AllReduce and Parameter Server). Extensive experiments show that dPRO predicts the performance of distributed training in various settings with<5% errors in most cases and finds optimization strategies with up to 3.48x speed-up over the baselines.
Development and Psychometric Characteristics Evaluation of Preconception Knowledge and Attitude Scale

Background: Maternal knowledge, attitudes and health status before conception is an important determinant of fetal health. However, there are no scales in the literature to evaluate for preconception health, knowledge, and attitudes of women before pregnancy. Aim: The aim of the study was to develop a valid and reliable measurement tool that can measure the preconceptional knowledge and attitudes of reproductive age women. Methodology: A methodological design was used in this research. The sample consists of 913 women (402 married, 511 single) aged 18 ‒ 45 years. Preconception Knowledge and Attitude Scale’s item pool is based on literature and expert opinions. Psychometric characteristics evaluation of the scale included the content, face and construct validity, internal consistency reliability, item-total correlation, test-retest method. The data were analyzed using LISREL 8.54 and SPSS 18.0 package programs. Results: Principal component analysis and varimax rotation revealed that the reduced scale was 43 items and 7-factor which have eigenvalues more than >1 and explain 40% of the total variance. Cronbach’s Alpha coe ﬃ cient was found to be 0.86 for the total scale and between 0.44 and 0.82 for the subscales. Confirmatory factor analysis results showed that the model fit index values were acceptable. The test-retest reliability of the scale was found as 0.98 (p<0.001). Conclusions: The study showed that Preconceptional Knowledge and Attitude Scale was a reliable and valid scale. The scale can be use to assess preconceptional knowledge and attitudes of women by health professionals.
How Businesses Might Prevent Issues Arising from Cultural Differences in Online Negotiations

In this work talking about when foreign trade happening, which is a form of trade with great cultural differences, changes online, what kind of online cultural differences and communication difficulties will be caused is the main goal of research. Many cultural differences caused by online business negotiation have been found in the research. Therefore, business negotiations are divided into four different parts of the analysis: (1) non-task sounding (2) task-related exchange of information (3) persuasion and dissuasion (4) concessions and Agreement. In the four processes, five symbolic problems of cultural differences are selected for analysis, and corresponding solutions to relevant problems are proposed.
Prevalence of Mycobacterium tuberculosis in Sputum and Reported Symptoms Among Clinic Attendees Compared With a Community Survey in Rural South Africa

Abstract Background Tuberculosis (TB) case finding efforts typically target symptomatic people attending health facilities. We compared the prevalence of Mycobacterium tuberculosis (Mtb) sputum culture-positivity among adult clinic attendees in rural South Africa with a concurrent, community-based estimate from the surrounding demographic surveillance area (DSA). Methods Clinic: Randomly selected adults (≥18 years) attending 2 primary healthcare clinics were interviewed and requested to give sputum for mycobacterial culture. Human immunodeficiency virus (HIV) and antiretroviral therapy (ART) status were based on self-report and record review. Community: All adult (≥15 years) DSA residents were invited to a mobile clinic for health screening, including serological HIV testing; those with ≥1 TB symptom (cough, weight loss, night sweats, fever) or abnormal chest radiograph were asked for sputum. Results Clinic: 2055 patients were enrolled (76.9% female; median age, 36 years); 1479 (72.0%) were classified HIV-positive (98.9% on ART) and 131 (6.4%) reported ≥1 TB symptom. Of 20/2055 (1.0% [95% CI, .6–1.5]) with Mtb culture-positive sputum, 14 (70%) reported no symptoms. Community: 10 320 residents were enrolled (68.3% female; median age, 38 years); 3105 (30.3%) tested HIV-positive (87.4% on ART) and 1091 (10.6%) reported ≥1 TB symptom. Of 58/10 320 (0.6% [95% CI, .4–.7]) with Mtb culture-positive sputum, 45 (77.6%) reported no symptoms. In both surveys, sputum culture positivity was associated with male sex and reporting >1 TB symptom. Conclusions In both clinic and community settings, most participants with Mtb culture-positive sputum were asymptomatic. TB screening based only on symptoms will miss many people with active disease in both settings.
Research on Adaptive Machine Learning Algorithms Based on Cognitive Simulation

: According to the theory of cognitive science and guided by the latest research results of neuroscience and brain science, an adaptive machine learning method is proposed by using the methods of computer science, mathematics and engineering science. This method is based on the learning mechanism model of human brain from the micro-neuron level, the middle level and the macro level. The automatic acquisition system of ECG classification knowledge based on this method can well simulate the functions of ECG experts' perception, cognition and thinking.
Investment Slumps during Financial Crises: The Role of Credit Constraints

How much do credit constraints contribute to investment slumps during ﬁnancial crises? For the Greek crisis that erupted in 2010, we ﬁnd that tightened credit constraints contributed to about half of the observed collapse in investment rates. The remainder is explained by diminished demand and productivity ﬁrms faced. We use a novel ﬁrm-level dataset of manufacturing ﬁrms and show that standard dynamic investment models abstracting from credit constraints cannot reproduce the observed investment dynamics. Enhanced with borrowing constraints subject to an aggregate shock to eligible collateral, such models can account for the observed collapse in investment rates. In this table we explore the role of external-ﬁnancing dependence in investment during the crisis. To do so, we construct an index of external-ﬁnancial dependence, similar to that of Rajan and Zingales (1998), at the industry level using the pre-crisis microdata. The estimated coeﬃcient of this index interacted with a crisis dummy variable in several investment regressions shows that ﬁrms in industries with higher dependence on external ﬁnancing invested less than did similar ﬁrms in industries less dependent on external funds. These results suggest that credit conditions may have played a role in ﬁrms’ investment decisions during the crisis.
Lethe: Practical Data Breach Detection with Zero Persistent Secret State

Honeywords are false passwords associated with each user account. Using a honeyword to login sets off an alarm as a data breach has been detected. Existing approaches for detecting data breaches using honeywords suffer from the need of a trusted component to tell honey-words from the valid password. Once this trusted component is compromised, then honeywords can offer no assistance for mitigating or detecting a data breach. In this paper, we present Lethe, a honeywords-based data-breach detection system that requires no trusted components, other than a trusted bootstrap, and keeps limited transient state for verifying login attempts. Lethe is based on two fundamental principles. First, Lethe generates honeywords using a Machine Learning (ML) model, which constantly evolves. This means that an attacker that compromises the Honeyword Generation Technique (HGT) cannot reproduce the same set of honeywords, and thus cannot tell which password was used as the initial generator. In particular, Lethe is the first system that allows an attacker to fully compromise the HGT without affecting the security of already generated honeywords. Second, Lethe is not aware of the valid password. In fact, for Lethe the only one that knows the actual password is the user that selected it in the first place. Lethe records login events, but without storing anywhere the password used. These login events can be further replayed in another server, which can check if, for a particular user, there were at least two different passwords used and therefore detect a data breach. Lethe allows the detection of a data breach deterministically and not probabilistically as similar approaches do. Additionally, Lethe allows detecting data breaches that are associated with rarely used accounts. Lethe can signal an alarm even if a user account that has logged in just once with the system is compromised. This is in contrast to other efforts that require legitimate users to authenticate with the system, after the attacker has done so, for detecting the breach. To demonstrate the effectiveness of Lethe, we provide a fully functional prototype, along with the ML-based HGT, and assess the provided security with a set of diverse attackers.
The Determinants of Green Purchasing: The Perspectives of Brand Knowledge, Perceived Quality and Country of Origin

Driven by social responsibility, firms have realized the importance to reconcile the interests of the environments, community, and business. The soaring of environmental conscious leads consumers to consider purchasing green products. However, the prior studies on purchase willingness of green products have mixed research results. In order to verify the determinants of green purchasing, this paper investigated the dimensions of brand knowledge, quality perception, and country of origin image in green products. This paper was conducted by a survey of 568 valid respondents for three green skincare brands including L'OCCITANE, DHC, and ORIGINS. Specifically, these brands stand for different country of origin image including the U.S., France, and Japan. Through a LISREL analysis, the findings indicated that the augmented consumers’ brand knowledge can enhance purchase willingness. Specifically, consumers’ perceived quality was able to bridge brand knowledge and purchase willingness. Moreover, country image of green brand moderates the relationship between brand knowledge and perceived quality. This paper contributed to enhance the understanding of consumers’ purchase willingness and provides the insights of firms’ effective marketing in green skincare products.
Tri-iterative STAP for transmit beamspace-based MIMO radar

ABSTRACT Because of the transmit power dispersion, the output signal-to-clutter-plus-noise ratio (SCNR) of the traditional airborne multiple-input multiple-output (MIMO) radar space-time adaptive processing (STAP) is severely restricted. To address this problem, a transmit beamspace (TB)-based tri-iterative MIMO-STAP method is proposed. First, the signal model of the TB-based MIMO radar STAP is established, and the TB matrix is designed based on spheroidal sequences to focus the transmit power within the spatial sector of desired targets. Then, the clutter-to-noise ratio (CNR) of the TB-based MIMO radar is analysed to show its relationship with the total transmit power. The calculated value is provided to illustrate that the CNR of the TB-based MIMO radar is reduced compared with the traditional MIMO radar with uniform omnidirectional transmission. Next, in order to decrease the training sample requirement and the computational complexity of the TB-based MIMO-STAP, the tri-iterative algorithm (TRIA) is employed to resolve the reduced-dimension weight vectors. The proposed TB-based tri-iterative MIMO-STAP method can achieve superior SCNR performance at lower computational cost, compared with the tri-iterative STAP for the traditional MIMO radar. Simulation results demonstrate the effectiveness and superiority of the proposed TB-based tri-iterative MIMO-STAP method, which is valuable for engineering application.