Miracle-dz/UniFAR-FTUs huggingface dataset:
The Development Mode of Regional Science and Technology Innovation Center Based on the Experience of China and the United States

It is necessary to explore the new development mode of regional science and technology innovation center in order to boost the high-quality development. In this paper, data analysis method is used to describe the development mode and existing issues in detail based on the development experience of three high-tech innovation regions. Specifically, three regions are selected as investigation cases containing Z-Park, Silicon Valley and North Carolina's Research Triangle Park. According to the results, the establishment of a science and technology innovation center needs a perfect ecosystem, sound social network, efficient organization, strong innovation, and R&D ability. Meanwhile, in the process of development, regional science and technology innovation center should combine with their own development reality. On this basis, they can obtain local government policy support, pay attention to the cultivation of scientific research talents, realize the integration of industry and city, and establish a livable urban community. It is of practical significance to further strengthen the construction of regional science and technology innovation center with global influence. These results shed light for the country establish a better innovation center.
Metabolic Syndrome is an Independent Risk Factor for Fuhrman Grade and TNM Stage of Renal Clear Cell Carcinoma

Background More and more evidences show that metabolic syndrome (MS) is closely related to clear cell renal cell carcinoma (ccRCC), but the impact of MS on Fuhrman grade and TNM stage of ccRCC is rarely reported. Purpose To explore the relationship between MS and its components of Fuhrman grade and TNM stage in ccRCC. Objective The clinical data of 247 patients with ccRCC diagnosed in our hospital from January 2016 to November 2020 were retrospectively collected and analyzed. Based on diagnostic criteria of MS, the patients were divided into MS and non-MS group. Logistic regression analysis was used to analyze the independent risk factors of ccRCC. Results The incidence of MS was 32.79% (81/247). There was no significant difference in age, gender, smoking and drinking between MS group and non-MS group (P > 0.05). In MS group, BMI ≥25kg/m2, hypertension, diabetes, hyperlipidemia, tumor diameter, poorly differentiated renal cancer, high-stage renal cancer, triglyceride, fasting blood glucose, glycated hemoglobin, fasting insulin and homeostasis model assessment index were significantly higher than those in non-MS group (P < 0.001), while in high density lipoprotein cholesterol (p < 0.005), islet beta cell secretory index (P < 0.001), well-differentiated renal cell carcinoma (P= 0.009), and low-stage renal cell carcinoma (P = 0.019) were significantly lower than that of non-MS group. Logistic regression analysis showed that hypertension (P = 0.005), diabetes (P = 0.012), hyperlipidemia (P = 0.021) are independent risk factors for Fuhrman grade of ccRCC, while diabetes (P = 0.002), hyperlipidemia (P = 0.007) are independent risk factors for TNM staging of ccRCC. Conclusion The patients with ccRCC and MS had higher Fuhrman grade and TNM stage. MS is an independent risk factor for Fuhrman grade and TNM stage of ccRCC.
Lean Quality in Construction Project Delivery—A New Model and Principles

All industries are undergoing rapid change under the pressure of technological innovation and changing client needs. The construction sector is no exception, the past 10 years has seen accelerating globalisation, a demand for larger and more complex projects, and a requirement for them to be delivered in ever shorter timeframes. Meanwhile clients of the industry are increasingly concerned that this sector is not keeping pace with the rates of improvement seen in other sections of the economy. In addition, in this sector, the rate and cost of errors in quality and safety have been too slow to improve.
The Effectiveness of Brand Culture on Customer Engagement

Spotify is a Swedish digital music streaming service and technology company founded in 2006 by Daniel Ek. In the US market, Spotify is the most predominant audio streaming service among its competitors. The primary purpose of this research was to explore how Spotify took advantage of its branding culture to deliberately orient or mediate its customer engagement. This research would develop preceding case studies related to customer engagement and Spotify's branding strategies to draw a general correlation. Although psychological factors of the consumers might affect their engagement to a certain extent, the research concludes the personalized customer experience of Spotify has strengthened the relationship between the application and consumers, attracting more non-members to subscribe to the premium service offered by Spotify. From Spotify's data-driven service, a particular customized playlist would be recommended to the users. People tend to be touched by music and such emotional interactions, leading to a sense of resonation and inspiration to them. Besides, artists and other music content creators could better comprehend the streaming media data of their works through the analytic database from Spotify. The adhesiveness of users would be valued. Thus, Spotify's brand culture and marketing tactics have to render part of its consumers become advocates, extensively spreading word-of-mouth recommendations of Spotify's benefits. In short, this research aims to provide an enlightening indication of Spotify's prospective developing orientation, which might be facilitated customer-oriented
A new pattern recognition method of gas sensor array detection

BP neural network based gas sensor array detection pattern recognition has some disadvantages,such as slow convergence and local minimum problem.A modified immune neural network model which combines BP algorithm and immune algorithm is proposed to enhance global search capability and improve the performance of the neural network model.Orthogonal test is adopted to design the study samples of neural network.This ensures the accuracy of neural network while reducing the number of samples.The simulation results show that the proposed pattern recognition method solves the cross sensitivity of gas sensor effectively,overcomes the disadvantages of traditional BP neural network and improves the learning speed and detection accuracy.
Treatment of C1.1 (AO-41) tibial plateau fracture: A finite element analysis of single medial, lateral and dual plating

Bicondylar tibial plateau fractures pose many challenges in surgical treatment. The aim of the present study was to analyze three methods of reduction, single medial, single lateral, and dual plating, for the treatment of a bicondylar tibial plateau fracture, through finite element analysis (FEA). A simple metaphyseal fracture, type C1.1 (AO-41) was modeled on a CT-derived 3D model of the knee. Lateral and medial proximal tibial polyaxial plates with screws were modeled and placed accordingly for the three methods of reduction. Simulation of physiological type loading corresponding to the maximal weight acceptance phase during a slow walking gait cycle was performed using FEA. Values of stress and strain were recorded near the fracture lines. Dual plating provided a decrease of stress and strain in the tibial plateau area. However, the differences in the values among the three cases were small. The stress concentration areas were located in the vicinity of the fracture, predominantly in the area of the tibial plateau. Considering the limitations of the present study, the results revealed that dual plating leads to smaller stress and strain values near the fracture lines in the tibial plateau area. However, values obtained for single lateral plating are close in range. Considering the complexity of the surgical approach for dual plating, single lateral plating may be a solution for good reduction with fewer surgical risks and complications. Further studies on the C1.1 fracture (AO-41) are needed to analyze the complex issue of reducing and stabilizing such a fracture and to characterize the postoperative state while providing predictable parameters for an optimal result.
Neuroprotective Effects of Probiotic-Supplemented Diet on Cognitive Behavior of 3xTg-AD Mice

Alzheimer's disease (AD) is recognized as one of the most common types of senile dementia. AD patients first suffer memory loss for recent events (short-term memory impairment). As the disease progresses, they are deprived of self-awareness. This study aims to explore the effects of a probiotic-supplemented diet on the cognitive behaviors and pathological features of mouse models of Alzheimer's disease (AD). Mice in the control group and the 3xTg-AD group were fed a regular diet and a probiotic-supplemented diet, respectively, for 20 weeks. Behavioral experiments like Morris's water maze and Y maze were conducted. Then, feces of mice were collected for 16S sRNA gene sequencing for microorganisms. In the end, soluble and insoluble Aβ40 and Aβ42 in the hippocampus and cortex of mice in each group were quantitatively analyzed with a double-antibody Sandwich ELISA. The expression levels of tau protein and gliocyte in the hippocampus and cortex were detected using the Western Blot method. The result of the Morris water maze experiment indicated that, in the place navigation test, the mice in the 3xTg-AD group experienced a significant decline in the learning ability and a longer escape latency and in the space exploration test, the swimming time of mice in the 3xTg-AD group in the target quadrant decreased and after being treated with the probiotic diet, mice in the 3xTg-AD group had improved learning and memory ability. The result of Y maze showed that the probiotic diet can improve the spontaneous alternation accuracy of mice in the 3xTg-AD group. The result of 16s rRNA gene sequencing showed that, compared with mice in the WT group, those in the 3xTg-AD group experienced a change in the intestinal flora. The Western Blot result displayed a decreased expression level of tau (pS202) (P < 0.05) and decreased expression levels of Iba-1 and GFAP (P < 0.05). The result of the ELISA experiment showed decreased levels of soluble and insoluble Aβ40 and Aβ42 in 3xTg-AD mice (P < 0.05). In conclusion, a probiotic diet can prevent and treat AD by improving the intestinal flora of 3xTg-AD.
Credit card fraud detection using moth-flame earth worm optimisation algorithm-based deep belief neural network

: Nowadays, credit card fraud actions happen commonly, which results in vast financial losses. Fraudulent transactions can take place in a variety of ways and can be put into various categories. Hence, financial institutions and banks put forward credit card fraud detection applications. To detect fraudulent activities, this paper proposes a credit card fraud detection system. The proposed system uses the database with the credit card transaction information and sends it to the pre-processing. The log transformation is applied over the database for data regulation in the pre-processing step. After, the appropriate features are selected by the information gain criterion, and the selected features are utilised to train the classifier. Here, a novel classifier, namely moth-flame earth worm optimisation-based deep belief network (MF-EWA-based DBN) is proposed for the fraud detection. The weights for the classifier are selected by the newly developed moth-flame earth worm optimisation algorithm (MF-EWA). The proposed classifier carries out the training and detects the fraud transactions in the database. The proposed MF-EWA-based DBN classifier has improved detection performance and outclassed other existing models with 85.89% accuracy.
The development of mathematics teacher professional competencies through social media

One of the competencies for mathematics teachers that needs to be developed continuously is professional competence. However, even if efforts for developing teachers’ competencies have been made formally by the government, it seems still lacking. This study, therefore, aims to develop mathematics teacher professional competencies through an informal development model using social media. This research used a qualitative method, a case study design, involving 19 mathematics teachers from various regions in Indonesia in the informal development process in the range of 2019-2021. The informal approach was carried out using question-and-answer techniques and guided discussions on mathematical problems. From the teacher development processes, 30 mathematics problems and their solutions were collected. As an illustration of this development process, this article presents five problems and their solutions, including solutions for two mathematics problems on conceptual understanding and three mathematics problems on problem-solving. We conclude that this informal approach is fruitful in helping mathematics teachers solve mathematics problems. This study implies that the teacher development process carried out in this study can be used as a model for informal teacher development by other higher education academics in their respective places.
Out-of-the-ICU Mobilization in Critically Ill Patients: The Safety of a New Model of Rehabilitation

OBJECTIVES: Early mobilization of ICU patients has been reported to be safe and feasible. Recently, our ICU implemented out-of-the-ICU wheelchair excursions as a daily rehabilitation practice. The aim of this study is to investigate the safety of participation in the out-of-the-ICU program for early mobilization. DESIGN: Retrospective cohort study. SETTING: Single general ICU in a tertiary teaching hospital. PATIENTS: Adult patients who were admitted to the ICU and underwent the out-of-the-ICU program as an early mobilization intervention was investigated. INTERVENTIONS: The out-of-the-ICU activities include visiting indoor area, visiting our outdoor garden, and bathing. MEASUREMENTS AND MAIN RESULTS: Medical records of ICU patients who participated in the out-of-the-ICU program were reviewed. The primary outcome was the occurrence rate of physical safety events, defined as unintentional removal of medical devices, patient agitation, a fall, or an injury. The secondary outcome was the occurrence rate of adverse physiologic changes, defined as hypotension, hypertension, bradycardia, tachycardia, desaturation, bradypnea, tachypnea, an increase in Fio2, or an increase in doses of vasoactive drugs. In total, 99 adult patients participated in the program, comprising a total of 423 out-of-the-ICU sessions. Among them, one session resulted in a physical safety event, the dislodgement of a tracheostomy tube. In 23 sessions, one or two adverse physiologic changes occurred. None of these events required additional treatment nor resulted in serious sequelae. CONCLUSIONS: An out-of-the-ICU program can be provided safely to adult ICU patients, provided that it is supervised by a dedicated intensivist with an appropriately trained multiprofessional staff and equipment on-site. It appears to contribute to the promotion of humanizing intensive care.
Analysis of cerebral glucose metabolism following experimental subarachnoid hemorrhage: an [18F]FDG-PET study over 7 days using an MRI-template based analysis tool

Little is known about changes in brain metabolism following SAH, possibly leading towards secondary brain damage. Despite sustained progress in the last decade, analysis of in vivo acquired data still remains challenging. The present interdisciplinary study uses a semi-automated data analysis tool analyzing imaging data independently from the administrated radiotracer. The uptake of 2-[18F]Fluoro-2-deoxy-glucose ([18F]FDG) was evaluated in different brain regions in 14 male Sprague-Dawley rats, randomized into two groups: (1) SAH induced by the endovascular filament model and (2) sham operated controls. Serial [18F]FDG-PET measurements were performed. Quantitative image analysis was performed by uptake ratio using a self-developed MRI-template based data analysis tool. SAH animals showed significantly higher [18F]FDG accumulation in gray matter, neocortex and olfactory system as compared to animals of the sham group, while white matter and basal forebrain region showed significant reduced tracer accumulation in SAH animals. All significant metabolic changes were visualized from 3 hours, over 24 hours, day 4 and day 7 following SAH/sham operation. This [18F]FDG-PET study provides important insights into glucose metabolism alterations following SAH - for the first time in different brain regions and up to day 7 during course of disease. The present tool improves PET image quantification and provides more flexible data analysis advocating its clinical application.
Do Attitudes Toward Violence Affect Violent Behavior?

ABSTRACT Attitudes toward violence are important in theoretical explanations of violent behavior and efforts to reduce violent behavior. Though an association between attitudes and violent behavior has been demonstrated, most studies have used correlational/observational research designs. We conducted a randomized experiment to test the effect of attitudes toward violence on violent behavior with 285 men from the community. Participants were randomly assigned to receive material to make attitudes toward violence more negative or to a control condition. Violent behavior was then approximated by asking participants to select from a range of violent and nonviolent options in response to a series of interpersonal conflict vignettes. Participants in the negative attitude condition responded with less violence on the vignette questionnaire than did participants in the control condition (Cohen’s d = −0.23, 95% CI [−0.46, 0.01]). Participants also completed a measure of attitudes toward violence at the end of the experiment; more positive attitudes toward violence showed a strong association with more violent responding on the vignette questionnaire (r = .62, 95% bootstrapped CI [.54, .69]). Consistent with theory and practice, our findings suggest that attitudes toward violence may play a role in violent behavior.
A Quality-Related Fault Detection Method Based on the Dynamic Data-Driven Algorithm for Industrial Systems

For nearly a decade, quality-related fault detection algorithms have been widely used in industrial systems. However, the majority of these detection strategies rely on static assumptions of the operating environment. In this paper, taking the time series of variables into consideration, a dynamic kernel entropy component regression (DKECR) framework is proposed to address the instability of quality-related fault detection due to the existing dynamic characteristics. Compared with the typical kernel entropy component analysis method, the proposed method constructs the relationship between process states and quality states to further interpret the direct effect on the product taken by the fault. In the proposed approach, process measurements are converted to a lower-dimensional subspace with a specific angular structure that is more comprehensive than traditional subspace approaches. In addition, the angular statistics and their relevant thresholds are exploited to enhance the quality-related fault detection performance. Finally, the proposed method will be compared with three methods by means of a numerical example and two industrial scenarios to demonstrate its practicality and effectiveness. Note to Practitioners—This paper studies a quality-related fault detection problem for the dynamic nonlinear industrial system. Controlling and measuring the quality state is challenging for the high-level monitoring system of the manufacturing process due to the nonlinear dynamic feature in states. This paper proposes a new data-driven method based on the kernel entropy component analysis method to assess the correlation between the quality and fault in the industrial system, reducing unnecessary overhaul and maintenance. Based on the autoregressive moving average exogenous algorithm, the proposed method captures the dynamic interaction between the process states to decrease false alarms. In the experimental section, the DKECR method outperforms the compared approaches, which can provide stable fault detection results. Additionally, the unique angle structure of the proposed method can supply more information for engineers’ monitoring needs.
Strategic conception of future synchronous power network in China

Power network is the infrastructure of national economy and the carrier of power market, which undertakes optimization of energy resource disposition and plays an important role in ensuring the national energy safe and satisfying the development of national economy. Based on the present situation analysis of synchronous power network in China and combined with the development tendency of power network in the future, the strategic conception of forming North China-Central China-East China synchronous power network with UHVAC link was put forward, and its scientific reasonability and technical feasibility were discussed. It is pointed out that to enforce the pilot project firmly is the key of verifying UHVAC technology.
Prior-Knowledge-Guided Deep-Learning-Enabled Synthesis for Broadband and Large Phase Shift Range Metacells in Metalens Antenna

A prior-knowledge-guided deep-learning-enabled (PK-DL) synthesis method is proposed for enhancing the transmission bandwidth and phase shift range of metacells used for the design of metalens antennas. The algorithm of conditional deep convolutional generative adversarial network (cDCGAN) is utilized in the proposed deep-learning (DL) method. Prior knowledge, including well-known fundamental electromagnetic theorems and experience in antenna design, is purposely applied at the early stage of the proposed method to strategically guide and speed up the synthesis. The proposed intelligent method provides the design of pixelated metacells with high degrees of freedom so that the key performance of the synthesized metacells exceeds the existing limit of conventional design methods by generating a rich profusion of cell patterns. For example, the synthesized triple-layer metacell achieves the −1 dB phase shift range of 330° breaking the limit of 308° derived by existing techniques. The proposed synthesis method also provides the additional capability to flexibly control the phase shift not only at the center frequency but also over a frequency range of interest. A Ku-band metalens antenna formed with the synthesized metacells demonstrates the achieved 1 and 3 dB gain bandwidths increase by 52.2% and 42.6%, respectively, compared to the metalens antenna using the well-known Jerusalem cross (JC) metacells. The proposed method extends the capability for the synthesis of metacells and metalens antennas with enhanced performance.