Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesoporous Methyl-Functionalized Titanosilicate Produced by Aerosol Process for the Catalytic Epoxidation of Olefins

Titanosilicates (Ti-SiO2) are well-known catalysts for the epoxidation of olefins. Isolated Ti inserted in the silica framework in tetrahedral coordination are the active species. Recently, adjusting the hydrophobic/hydrophilic balance of such catalysts’ surfaces has appeared as a promising tool to further boost their performance. However, adjusting the hydrophobic/hydrophilic balance via a one-pot classical sol-gel generally leads to a decrease in the Ti dispersion and/or collapse of the pore network. To overcome this limitation, hydrophobic mesoporous Ti-SiO2 were here synthesized by aerosol-assisted one-pot sol–gel, which allowed the simultaneous control of their Ti loading, degree of methyl-functionalization, and textural properties. Methyl-functionalization was achieved by a partial substitution of tetraethoxy silane (TEOS) by methyltriethoxy silane (MTES) in different ratios. Solid-state 29Si-NMR, FTIR, TGA, and vapor-phase water adsorption showed that methyl moieties were effectively incorporated, conferring a hydrophobic property to the Ti-SiO2 catalysts. ICP-AES, DRUV, XPS, and N2 physisorption demonstrated that Ti dispersion and textural properties were both successfully preserved upon the incorporation of the methyl moieties. In the epoxidation of cyclooctene with tert-butyl hydroperoxide as oxidant, the hydrophobic Ti-SiO2 showed higher catalytic performance than pristine Ti-SiO2 prepared without MTES. In addition to disentangling the positive effect of adjusting the hydrophobic/hydrophilic balance of epoxidation catalysts on their performance, this contribution highlights the advantages of the aerosol procedure to synthesize mesoporous functionalized catalysts with very high dispersion of active sites.
Increasing Efficiency of a Finned Heat Sink Using Orthogonal Analysis

As the heat flux of electronic components is increasing rapidly, the traditional air-cooling technique is gradually not meeting the requirements of thermal management. The immersion liquid-cooling technique shows great potential, and has attracted increasing attention due to its excellent performance in recent years. The finned heat sink is common and essential for cooling electric components. To analyze the influences of its structural parameters on heat dissipation and improve its efficiency while using a dielectric coolant, this study used the orthogonal analysis method to obtain the optimal structure via the numerical simulation method. The maximum temperature of the heat sink was selected as the evaluation criteria. The results showed that the parameters that affect the maximum temperature, in order of importance, are fin thickness, the number of fins, the height of the fins, and substrate thickness. Finally, taking the maximum temperature and mass as indexes obtained the optimal structure of the heat sink. The mass was reduced by 19%, while the temperature only increased by 4.5% when considering the mass index.
Applying process analytical technology to biotech unit operations

Case studies were run to test Process Analytical Technology applications for protein refolding, diafiltration, and cation exchange chromatography. It is shown that it is feasible to design control schemes that rely on measurement of product quality attributes and thereby enable real-time decisions. Implementation of these schemes should result in consistent product quality and high operational efficiency. However, these advantages are balanced by requirements of a higher level of process understanding for designing these schemes, and increased operational complexity during implementation. Increased consistency in product quality is likely to increase variability in step recovery, a parameter that is commonly considered an indicator of process consistency.
Hot question prediction in Stack Overflow

National Key Research and Development Program of China No: 2018AAA0102304; State Key Laboratory of Software Development Environment, Grant/Award Number: SKLSDE‐2019ZX‐05; National Natural Science Foundation of China, Grant/Award Number: 61732019; National Basic Research Program of China (973 Program) , Grant/ Award Number: 2018YFB1004202; Fundamental Research Funds for the Central Universities, Grant/ Award Number: No.YWF‐20‐BJ‐J‐1018 Abstract Stack Overflow is a very popular programming question and answer community. Some questions become hot, and receive high views, which are of widespread concern to developers. Finding hot questions early can give priority to recommend potential hot questions to answers, thereby shortening the response time. Besides, the hot question prediction is also helpful for making advertising plan, planning advertising campaigns and estimating costs. Therefore, it is important to predict hot questions. The authors propose the VSAF method which analyses the View amount changes, Answer amount changes and Score changes soon after questions' creation based on Fully convolutional neural network. The performance of the VSAF method based on a training set and two different test sets has been evaluated. The training set has 1600 hot questions and 1600 cold questions. The random test set has 381 hot questions and 2819 cold questions, while the balanced test set has 400 hot questions and 400 cold questions. The experimental results show that using the balanced test set, VSAF achieves Accuracy, F1hot and F1cold of 80%, 77.77% and 81.81%, which outperforms the baseline approach by 25.59%, 21.52% and 29.04%, respectively. Using the random test set for evaluation, VSAF achieves Accuracy, F1hot and F1cold of 84.91%, 53.96% and 90.97%, which outperforms the baseline approach by 31.83%, 84.16% and 19.35%, respectively. The VSAF method significantly outperforms the state‐of‐the‐art approach on hot question prediction.
Green bridges in a re‐colonizing landscape: Wolves (Canis lupus) in Brandenburg, Germany

Gray wolves (Canis lupus) are recolonizing many parts of central Europe and are a key part of international conservation directives. However, roads may hinder the reestablishment of gray wolves throughout their historic range by reducing landscape connectivity and increasing mortality from wildlife‐vehicle collisions. The impact of roads on wolves might be mitigated by the construction of green bridges (i.e., large vegetated overpasses, designed to accommodate the movement of wildlife over transportation corridors). In this study, we investigated the seasonal and diurnal use of a green bridge by wolves and three of their main prey species: red deer (Cervus elaphus), roe deer (Capreolus capreolus), and wild boar (Sus scrofa). We found that all four species used the green bridge. Wolves were most active in winter, whereas prey species were most active in spring and summer. All species were more active at dusk and during the night than at dawn and during the day. We found no evidence that wolf presence influenced bridge‐use by prey species, consistent with other tests of the prey‐trap hypothesis. Our results suggest that green bridges are used by wolves and prey species alike, and may foster connectivity and recolonization for these species in rewilding landscapes.
Optimization of the CNN model for smart agriculture

Artificial intelligence is a branch of computer science that has advanced quite rapidly and is very useful in helping to alleviate human tasks. One of the models or algorithms part of artificial intelligence is the Convolutional Neural Network (CNN). This model is proven to be very accurate in image data processing. CNN has been used for facial recognition and image data detection systems. In this study, researchers will optimize CNN to obtain a faster and more accurate model for processing plant disease image data in this study using oil palm plant sample data. With the Research and Development method and FGD (Focus Group Discussion) with various experts, this research is expected to produce a CNN model that is faster and more accurate.
Efficacy and Effectiveness of Physical Agent Modalities in Complex Regional Pain Syndrome Type I: A Scoping Review

Complex regional pain syndrome type I (CRPS-I) is a rare condition with huge variability in triggering factors and clinical scenarios. The complexity of the pathophysiology of this condition fosters the proposal of several therapeutic options with different mechanisms of action in both research and clinical practice. An interdisciplinary and multimodal approach, including pharmacological and non-pharmacological interventions, particularly physical therapy, is recommended by international guidelines, but the benefits and harms of available interventions are poorly known. In this scoping review, the clinical rationale for use of physical agent modalities for patients with CRPS-I will be presented. We found 10 studies addressing the role of electromagnetic field therapy, electrotherapy, and laser therapy. Our findings suggest that physical therapy modalities, in particular transcutaneous electrical nerve stimulation (TENS) and pulsed electromagnetic field therapy (PEMF), may contribute to reduce pain and improve function in patients with CRPS-1.
Evidence of Climate Change Coping and Adaptation Practices by Smallholder Farmers in Northern Ghana

Evidence on how coping practices for immediate climate variations can transform into long-term adaptive capacity are relatively limited. This study addressed this gap by identifying the coping practices for short-term climate variations and the adaptation measures used by smallholder farmers to address future climate change in northeast Ghana. The paper used a mixed-methods approach, including household surveys, focus group discussions and key informant interviews. Data were collected from 555 households located in six communities across three districts in northeast Ghana. Results indicated that smallholder farmers were employing a host of practices to address the threats posed by climate change. Key adaptation practices included the planting of drought-tolerant crop varieties, the use of indigenous knowledge, intensification of irrigation, migration, adjusting the planting calendar, crop diversification, mixed farming, and sustainable land management practices. On the contrary, short-term coping practices reported by the study participants included the sale of non-farm assets, complementing agriculture with non-farm jobs, selling livestock, engaging in wage labor, charcoal burning and reliance on social networks. The results further revealed that barriers to climate change adaptation and coping practices differed by gender. The paper recommends that capacities of smallholder farmers in vulnerability hotspots should be enhanced to address immediate climate variations, as well as future climate changes. Ghana’s climate change and agricultural policies should prioritize adaptations by smallholder farmers in addressing threats posed by climate change.
On Fast Jerk-, Acceleration- and Velocity-Restricted Motion Functions for Online Trajectory Generation

Finding fast motion functions to get from an initial state (distance, velocity, acceleration) to a final one has been of interest for decades. For a solution to be practically relevant, restrictions on jerk, acceleration and velocity have to be taken into account. Such solutions use optimization algorithms or try to directly construct a motion function allowing online trajectory generation. In this contribution, we follow the latter strategy and present an approach which first deals with the situation where initial and final accelerations are 0, and then relates the general case as much as possible to this situation. This leads to a classification with just four major cases. A continuity argument guarantees full coverage of all situations which is not the case or is not clear for other available algorithms. We present several examples that show the variety of different situations and, thus, the complexity of the task. We also describe an implementation in MATLAB® and results from a huge number of test runs regarding accuracy and efficiency, thus demonstrating that the algorithm is suitable for online trajectory generation.
Event‐triggered guaranteed cost fault‐tolerant optimal tracking control for uncertain nonlinear system via adaptive dynamic
 programming

In this article, an event‐triggered guaranteed cost optimal tracking control problem is investigated for a class of uncertain nonlinear system with partial loss of actuator effectiveness faults. To begin with, an augmented system consisted of error system and reference system is constructed to simplify the tracking controller design. Then, in order to consider both actuator faults and system uncertainties in optimal tracking control, an improved discounted cost function is developed. Furthermore, a single critic neural network adaptive dynamic programming algorithm is utilized to implement the event‐based approximate optimal controller design. Different from static event‐triggered mechanism, the dynamic event‐triggered mechanism proposed in this article with an internal dynamic signal can further improve execution efficiency. A Lyapunov‐based stability analysis is given to demonstrate the uniformly ultimately bounded stability of the closed‐loop system. Finally, two typical nonlinear simulations are presented to verify the developed control method.
Computation offloading game in multiple unmanned aerial vehicle-enabled mobile edge computing networks

Because of extreme sensitivity to time and energy consumption, many computation- and data-intensive tasks are difﬁcult to implement on mobile terminals and cannot meet the needs of the rapid development of mobile networks. To solve this problem, mobile edge computing (MEC) appears to be a promising solution. In this study, we propose two ofﬂoading schemes in the multiple unmanned aerial vehicles (UAVs) enabled MEC network. Their optimisation goals are to minimise the global computing time and energy consumption of all UAVs, respectively. Different from previous research, the UAV can perform tasks locally or ofﬂoad an appropriate percentage to the desired MEC server in the two proposed schemes. In order to get the minimum global computing time, we prove the existence condition and obtain the optimal ofﬂoading proportion. In addition, in order to minimise global energy consumption, we also obtain the optimal ofﬂoading proportion and present the optimal transmission power through solving Karush–Kuhn–Tucker conditions. Finally, because UAVs are selﬁsh, we adopt the game theory to get optimal solutions of the proposed ofﬂoading strategies. Numerical results verify that the proposed schemes can effectively decrease the global computing time and energy consumption, especially for a large number of UAVs.
Influence of Ethical Leadership on Employees’ Innovative Behavior: The Role of Organization-Based Self-Esteem and Flexible Human Resource Management

Employees’ innovative behavior is a vital source for promoting the sustainable survival and development of enterprises. Innovation is a complicated and high-risk mental process, where in each stage employees’ innovative attitude and behavior will be affected by the varying behaviors of their direct leaders. Therefore, exploring the intricate relationship between leadership behavior and employees’ innovative behavior is necessary. Based on social exchange theory, this study builds a cross-level moderation model to investigate the impact of ethical leadership on employees’ innovative behavior and the mediating role of organization-based self-esteem and the moderating role of flexible human resource management. On the basis of a questionnaire survey of 146 supervisors and 365 subordinates in the mainland of China, the empirical results show that: (a) Ethical leadership positively affects employees’ innovative behavior significantly; (b) Organization-based self-esteem has a partial mediating relationship between ethical leadership and employees’ innovative behavior; and (c) flexible human resource management plays a positive moderating role in the relationship between organization-based self-esteem and employees’ innovative behavior, and it also positively moderates the mediating effect of organization-based self-esteem on the relationship between ethical leadership and employees’ innovative behavior. The findings reveal the internal mechanism and boundary condition of ethical leadership influencing employees’ innovative behavior, which provide a reference for enterprises to encourage employees to innovate, and have important practical significance for employees to actively pursue innovative activities in the workplace.
Predicting User’s Web Navigation behaviour using AMD and HMM Approaches

The academics were introducing various techniques in web usage mining to reduce user latency time to improve their web performance. The server-side web log data helps to identify the most appropriate pages, based on the user’s request. Analyzing web log data creates difficulties since it comprises exhaustive web page data. This paper proposes a new technique in which the web log data we can preprocess in order to extract sequence and navigation patterns useful to predict. In this paper, we cluster users into communities labelled by the websites most frequently visited, to discover their preferences and to describe website reorganisation. The URL sequence navigated by a user during a session. Session denotes a user’s browsing pattern. Multiple users’ sessions are clustered using the hierarchical clustering technique to analyse the sequence in their navigation patterns. The two model predictions are Adaptive Mahanabolis Distance (AMD) and Hidden Markov model (HMM), providing a list of web pages of interest to the user. We validate the proposed framework on NASA, Clarknet and serc datasets web log files.
Research on intergenerational transmission of Chinese residents’ income: Based on data from ten surveys of Chinese Family Tracking Survey from 1989 to 2015

Abstract This article uses the rank-ordered probit estimation method and data from the 10 Chinese Family Tracking Survey from 1989 to 2015 to systematically study how the family background, especially the parental income, of urban and rural residents in China since its opening affects the intergenerational transmission of income and income inequality. The results show the following: ① The higher the income of parents is, the higher the income of their offspring. When parents are middle income or above, the probability of their children earning an upper-middle or high income increases significantly. ② Although the income of mothers is low, its impact on children’s income is greater than that of the father’s income. If the mother’s income is middle, upper-middle, or high income, it will increase the probability of her children earning a high income by 12.17%, 28.16% and 45.90%, respectively, while the corresponding influence from the father’s income is 9.62%, 20.69% and 43.82%. ③ For children, the degree of intergenerational income inequality is greater for women than for men, and it is higher in cities than in rural areas. ④ The intergenerational transmission of income is persistent across multiple generations, but the transmission from parents is much higher than from grandparents. It is also difficult for the offspring of a lower-income couple to obtain a higher income. These conclusions are robust to examining different samples and examining the predicted impact of various measures of family background on the income of offspring. Based on the results, this article puts forward policy recommendations to improve intergenerational income consolidation and reduce income inequality.
Smart Shoe Sanitizing Device

People of our country are searching for all kind of protection against the virus which has been spread in all countries, according to surveys it is known that coronavirus keep active on the metallic grounds but on the other hand it can remain on shoe for three to five days. As plastic, leather, and rubber are the good transporter of viruses so daily requirements made by these materials are needed to be sanitized. If a person goes to an infected place or sneezes or speaks in front of another person can be infected easily by the globules spread over the shoes. Also, as our shoes come in contact with most of the dirt and germs, it is another reason for growing corona along with another virus. For this which virus and bacteria stay stick with the sole of the shoes can be carried to home. So, to fight against this situation, this paper proposed a smart IoT based Shoe Sanitizing System. Our proposed system will detect and remove the bacteria or virus by liquid spraying sanitizer along with the light of UV and at last, the shoes are dried with the air of DC. We can monitor and control the system over the Wi-Fi or internet by the implementation of the Node MCU and 4G GSM module. We have constructed this system to be carried out on the entry gates and doors. Through this device, a passer-by can avoid destroying the pandemic and also lower cost.
Thick GaN growth via GaN nanodot formation by HVPE

We demonstrate a 400 μm-thick GaN layer on 4 inch (0001) Al2O3 substrates through GaN nanodot formation as a seed for stress relaxation layers, which were formed by an in situ special surface treatment using HVPE. The size and density of the GaN nanodots determined the thickness of the stress relaxation layers and the structural properties of thick GaN. The 400 μm-thick GaN layer exhibits a smooth surface and high crystal quality with FWHM of 104 arcsec and 163 arcsec in the (002) and (102) X-ray rocking curves, respectively. The dislocation density estimated via micro-PL measurements was 2 × 106 cm−2. This can provide an efficient and simple way to fabricate thick GaN layers on an Al2O3 substrate without ex situ buffer layer formation or additional complicated processes.
Effects of an emotional regulation program on maladaptive cognitive emotion regulation, stress, anxiety, and postpartum depression among South Korean mothers of premature infants in the neonatal intensive care unit

Purpose This study aimed to evaluate the effects of a rational emotive behavior therapy (REBT)-based emotional regulation program for mothers of premature infants in the neonatal intensive care unit (NICU). Methods The study utilized a nonequivalent control group pretest-posttest design. Seventeen mothers were recruited for the experimental group and 21 mothers for the control group. Data were collected from July 9, 2018, to Oct 12, 2018 from mothers of premature infants in the NICU regarding parental stress, state anxiety, depression, and maladaptive cognitive emotion regulation. The experimental group received eight sessions of the REBT-based emotional regulation program for 3-4 weeks, and the control group only received standard nursing care. Results Significant differences were found between the two groups in maladaptive cognitive emotion regulation (Z=−3.88, p<.001), stress (Z=−2.76, p=.006), state anxiety (Z=−3.72, p<.001), and postpartum depression(Z=−2.62, p=.009) after the intervention in the experimental group. Conclusion The REBT-based emotional regulation program for mothers of premature infants was effective for reducing maladaptive cognitive emotion regulation, stress, anxiety, and postpartum depression. Therefore, it may be necessary to provide an REBT-based emotional regulation program for mothers of premature infants in the NICU in clinical practice.
Metal–Organic Frameworks (MOFs) Based Analytical Techniques for Food Safety Evaluation

1State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR 999078, China 2School of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China 3Sichuan Institute for Food and Drug Control, NMPA Key Laboratory for Quality Evaluation of Traditional Chinese Medicine (Traditional Chinese Patent Medicine), Chengdu, Sichuan 610000, China