Miracle-dz/UniFAR-FTUs huggingface dataset:
Holistic Parenting Scale: Developing a Holistic Parenting Scale Model based on Islamic Values

Islamic treasures have a parenting concept originating from the Holy Qur’an and the Hadith. I call this Islamic parenting concept a Holistic Parenting. Samples used in this study were as follows: five parents during the data elicitation stage, 228 male and female teenagers during the try-out stage and 616 16-to-17-year-old teenagers during the primary data collection stage. Based on the internal consistency test and construct validity test, the holistic parenting scale has a good validity and reliability. This scale is capable of measuring the same construct consistently, and is valid to measure the construct holistic parenting consisting of five dimensions namely: qudwah hasanah (integrated role model), al addah (habituation), al mauidzah (effective advice), al mulahadzah (fairness in care and control), and uqubah wa ujaroh (proportional consequences). Through the psychometric standard procedure that has been undergone, the holistic parenting scale presented in this study has been able to be employed to measure parents’ parenting capability over their sons and daughters in the Muslim family in Indonesia.
Data-driven Optimal Control Strategy for Virtual Synchronous Generator via Deep Reinforcement Learning Approach

This paper aims at developing a data-driven optimal control strategy for virtual synchronous generator (VSG) in the scenario that no expert knowledge and no requirement for system model are available. Firstly, the optimal and adaptive control problem for VSG is transformed into a reinforcement learning task. Specifically, the control variables, i. e. , virtual inertia and damping factor are defined as the actions. Mean-while, the active power output, angular frequency and its derivative are seen as the observations. Moreover, the reward mechanism is designed based on three preset characteristic functions to quantify the control targets: 1) Maintaining the deviation of angular frequency within special limits; 2) Preserving well-damped oscillations for both the angular frequency and active power output; 3) Obtaining slow frequency drop in the transient process. Next, to maximize the cumulative rewards, a decentralized deep policy gradient algorithm, which features model-free and faster convergence, is developed and employed to find the optimal control policy. With this effort, a data-driven adaptive VSG controller can be obtained. By using the proposed controller, the inverter-based distributed generator can adaptively adjust its control variables based on current observations to fulfill the expected targets in model-free fashion. Finally, simulation results validate the feasibility and effectiveness of the proposed methodology.
A guaranteed collision‐free trajectory planning method for autonomous parking

Planning a feasible, and safe trajectory is a crucial procedure for autonomous parking which remains to be fully solved. Generally, a trajectory is depicted by a sequence of conﬁgu-rations which include positions, and orientations. However, existing approaches usually design parking trajectories without considering the evolution from one conﬁguration to the next. Hence, these trajectories are practically infeasible in some scenarios, and safety risks may exist. In this paper, a guaranteed collision-free trajectory planning method is proposed for autonomous parking. A dynamic optimisation problem is built, which includes vehicle kinematics, collision avoidance constraints, and physical restraints. Then the dynamic optimisation problem is discretised into a ﬁnite-dimensional nonlinear programming problem. To describe collision avoidance constraints, the concepts of the virtual protection frame, and the magniﬁcation parameter are introduced. It is highlighted that a novel collision detection criterion is raised from the view of geometry. Tests in three common scenarios, and a complex scenario illustrate the effectiveness of the proposed approach. Moreover, the stability of the algorithm is discussed in this paper. Via the proposed approach, an integrated design of planning, and control is possible.
A Multiyear Constraint on Ammonia Emissions and Deposition Within the US Corn Belt

The US Corn Belt is a global hotspot of atmospheric ammonia (NH3), a gas known to adversely impact the environment and human health. We combine hourly tall tower (100 m) measurements and bi‐weekly, spatially distributed, ground‐based observations from the Ammonia Monitoring Network with the US National Emissions Inventory (NEI) and WRF‐Chem simulations to constrain NH3 emissions from April to September 2017–2019. We show that: (1) NH3 emissions peaked from May to July and were 1.6–1.7 times the annual NEI average; (2) average growing season NH3 emissions from agricultural lands were remarkably similar across years (3.27–3.64 nmol m−2 s−1), yet showed substantial episodic variability driven by meteorology and land management; (3) dry deposition was 40% of gross emissions from agricultural lands and exceeded 100% of gross emissions in natural lands. Our findings provide an important benchmark for evaluating future NH3 emissions and mitigation efforts.
Analysis of Lyα Dielectronic Satellites to Characterize Temporal Profile of Intense Femtosecond Laser Pulses

In the paper, an X-ray spectroscopy-based approach on laser pulse temporal profile characterization is described. The structure of dielectronic satellites to H-like Lyα lines strongly depends on a plasma electron density, so it can be applied for diagnostics. These spectral lines are mainly emitted during initial stage of laser plasma expansion. It means that plasma parameters obtained via them characterizes matter conditions in a region surrounding a spot of laser-matter interaction. In the case when a laser contrast is high enough, the radiation interacts with cold matter, which had not been preliminary perturbed by a laser prepulse, and the satellites structure shape corresponding to high densities should be observed. It allows us to consider the satellites as a diagnostic tool for the laser temporal profile quality. In the paper dependencies of the dielectronic satellites structure on electron densities obtained from detailed kinetic calculations in the wide range of plasma parameter for different elements are under discussion. Fundamental theoretical aspects of plasma diagnostic based on the feature of satellite structures shape in hot dense plasma, which led to development of the proposed method, are also explained.
Performance Enhancement of Massive MIMO Using Deep Learning-Based Channel Estimation

Massive Multiple-Input Multiple-Output (massive MIMO) system relies on channel state information (CSI) feedback to perform precoding and achieve performance gain in frequency division duplex (FDD) networks. However, transmission of massive MIMO system is subject to excessive feedback overhead. In this paper, we propose a Deep Learning (DL) approach-based channel estimation technique to enhance the performance of massive MIMO system. This technique is used to enhance recovery quality and improve trade-off between compression ratio (CR) and complexity of massive MIMO system. The proposed technique is based upon using the Channel State Information Network combined with gated recurrent unit (CsiNet-GRU). Moreover, the dropout method is used in the proposed technique to reduce overfitting during the learning process. The simulation results demonstrate that the proposed CsiNet-GRU technique results in a significant improvement in performance when compared with existing techniques used in conjunction with massive MIMO systems.
Research on Enterprises’ Intention to Adopt Green Technology Imposed by Environmental Regulations with Perspective of State Ownership

Environmental regulations (ER) affect enterprise behaviors. Nevertheless, whether the state ownership influences the relationship between environmental regulations and enterprises’ green intentions and behaviors need to be explored further. In this paper, the effects of environmental regulations on enterprises’ intentions to adopt green technologies, especially the moderating role of state ownership between environmental regulations and green technologic adoption intentions (GTAI), are proposed. An empirical study is carried out with the questionnaire data collected from 207 Chinese managers and executives in order to explore the influence of environmental regulations. With the perspective of ownership, the results confirm that the three kinds of environmental regulations (command-and-control (CAC), market-based incentives (MBI) and voluntary environmental (VER) regulations) have positive effects on enterprise green technology adoption intention. Furthermore, the state ownership of enterprise plays a positive moderating role in the relationship between command-and-control environmental regulations and green technology adoption intentions, but plays a negative moderating role in the relationship between voluntary environmental regulations and green technology adoption intentions. It generates no significant moderate effect on the relationship between market-based incentives environmental regulations and green technology adoption intentions. The work verifies that the differences of ownership would lead to varying effects on the intentions of enterprise green technology adoption imposed by regulations. Managerial implications, as well as the limitation of the work, are concluded at the end of this paper.
Reparative Regeneration by Substitution of Bone Tissue Defects with Bioglass, Using Regeneration Technologies

Bioactive glass (BG) induces osteogenesis of damaged bone, causing excessive bone formation. This study included a morphological and morphometrical data of the bone tissue regeneration by filling bone defects with BG with autologous native platele rich plasma (PRP) or fibrin (PRF) and aspirate of bone marrow (ABM). The parameters of newly formed bone in rabbits bone defect were analyzed and compared with terms 4th and 12th week. The groups with ABM-BG, PRF-BG and PRP-BG have shown common tendency: development of newly formed bone tissue, the external contour of the bone has been enlarged; an additional trabecular bone has been formed under the cortical layer, which has often been limited by a solid compact bone from the bone marrow. The induced osteoge nesis resulted in the appearance of a significant amount of bone tissue exceeding the original size of the defect. Increased density of the newl formed tissue at the defect level relative to ABM-BG was detected in the PRF-BG group at 12 weeks and PRP-BG at 4 and 12 weeks (p<0.05). In this case, the bone thickness in the substituted defect was greater in the ABM-BG group. The number of newly forme d bone tissue in the ABM-BG group at 4 weeks also exceeded the value of the BG group, but the density of such bone did not differ betw een the groups. That is, ABM-BG stimulated greater trabecular bone formation and fibrous reticular tissue was located in the lacunae be twee trabeculae. These results indicate that the additional use of tissue technology (ABM, platelet plasma) facilitated osteogenesis , and th newly formed bone tissue was tightly coupled and remodeled to the cortical bone layer in the form of compact bone tissue. PRP, to a greater extent than ABM, promoted the formation of compact bone tissue.
Spatial-Temporal Characteristics and Factors
of Agricultural Carbon Emissions in the Belt
and Road Region of China

The implementation of the “Belt and Road” strategy not only promotes the coordinated development of China’s regional economy but also generates a large amount of greenhouse gas emissions. The research and policy recommendations on agricultural carbon emissions are of great significance for China toward engendering sustainable agricultural development and appreciably contributing to the alleviation of global climate change. In this paper, agricultural carbon emissions in the Belt and Road region of China from 2003–2018 are calculated, and its spatial-temporal characteristics are analyzed. Then, we modified the logarithmic mean Divisia index model from the original four factors to six to analyze the drivers of agricultural carbon emissions. The research results obtained are as follows: (1) Total carbon emission reached a peak of 26.6326 million tons in 2016, representing a 54.53% increase from the 17.2342 million tons in 2003. Moreover, it indicated a downward trend in 2017 and dropped by approximately 4% to 25.5685 million tons in 2018. (2) Spatially, agricultural carbon emission varies greatly, with the highest value recorded in Heilongjiang and the lowest in Tibet, thereby exhibiting the characteristics of "northwest>northeast>southwest>southeast. " (3) Overall, the economic factor was the most important driving factor, whereas the subsidy factor was the strongest inhibiting factor for the growth of agricultural carbon emissions. Notably, the foreign trade factor had both promoting and inhibiting effects on it.
Why is the Application Programming Interface the backbone of a Smart City?

Improved informatiAbstractcommunication technology, causing smart city initiatives have developed in major cities in the world since the last decade. Smart cities aim to create sustainable urban development. Through the Ministry of Communication and Information of the Republic of Indonesia implemented the “100 cities to smart city” program, which began in 2017. The purpose of this article is to analyze the Application Programming Interface (API) as the Smart City backbone in Samarinda as a buffer city for the capital of the Republic of Indonesia in 2024 This study uses a qualitative approach with data collection techniques through in-depth interviews, FGD, observation and emphasizes on document analysis. This study provides the following conclusions. First, Samarinda City Government has carried out various transformations and innovations so that the city of Samarinda is competitive and ready to become a buffer city for the Republic of Indonesia’s capital in 2024. Second, infrastructure development is necessary as a means of supporting smart cities. To facilitate the implementation of API in Samarinda City. Recommendations from this research for the successful implementation of API in Samarinda City as a buffer for the nation’s capital in 2024 are as follows. First, there needs to be a more comprehensive strengthening of policies and regulations because there are regional apparatus of the Samarinda City Government that have an information system that is not integrated with the API. Second, there needs to be an increase in human resources, especially the State Civil Apparatus and / or Civil Servants, directly related to API. This study proves that there are no consolidated standards or best practices for smart governance because each city can implement different governance frameworks and models in achieving smart cities according to their local wisdom and city resources.
Observations of canopy storage capacity and wet canopy evaporation in a humid boreal forest

Evaporation of intercepted rain by a canopy is an important component of evapotranspiration, particularly in the humid boreal forest, which is subject to frequent precipitation and where conifers have a large surface water storage capacity. Unfortunately, our knowledge of interception processes for this type of environment is limited by the many challenges associated with experimental monitoring of the canopy water balance. The objective of this study is to observe and estimate canopy storage capacity and wet canopy evaporation at the sub‐daily and seasonal time scales in a humid boreal forest. This study relies on field‐based estimates of rainfall interception and evapotranspiration partitioning at the Montmorency Forest, Québec, Canada (mean annual precipitation: 1600 mm, mean annual evapotranspiration: 550 mm), in two balsam fir‐white birch forest stands. Evapotranspiration was monitored using eddy covariance sensors and sap flow systems, whereas rainfall interception was measured using 12 sets of throughfall and six stemflow collectors randomly placed inside six 400‐m2 plots. Changes in the amount of water stored on the canopy were also directly monitored using the stem compression method. The amount of water intercepted by the forest canopy was 11 ± 5% of the total rainfall during the snow‐free (5 July–18 October) measurement periods of 2017 and 2018. The maximum canopy storage estimated from rainfall interception measurements was on average 1.6 ± 0.7 mm, though a higher value was found using the stem compression method (2.2 ± 1.6 mm). Taking the average of the two forest stands studied, evaporation of intercepted water represented 21 ± 8% of evapotranspiration, while the contribution of transpiration and understory evapotranspiration was 36 ± 9% and 18 ± 8%. The observations of each of the evapotranspiration terms underestimated the total evapotranspiration observed, so that 26 ± 12% of it was not attributed. These results highlight the importance to account for the evaporation of rain intercepted by humid boreal forests in hydrological models.
Measuring Similarity for Data-Aware Business Processes

Business process similarity measures are of vital importance for process repository management applications, such as process query, process recommendation, and process clustering. Most existing approaches measure process similarity by relying on control-flow structures only. This article investigates the role of data in process similarity measure. To incorporate data-flow information into business process control flow, it proposes a data-aware workflow net (DWF-net) by extending the classical workflow net with data reading and writing semantics. Then, we introduce three types of similarity measures, i.e., data item set-based similarity, data operation set-based similarity, and data-aware behavior-based similarity, to quantify the similarity of data-aware business processes from different perspectives. Next, a methodology is introduced to help process analysts apply these three measures in a systematical way. Finally, we evaluate the effectiveness and applicability of the proposed similarity measures by a group of comparative experiments. Note to Practitioners—Business process similarity measures play an increasingly important role in business process repository management. This work addresses the role of data for process similarity measures. To this end, three types of similarity measures, i.e., data item set-based similarity, data operation set-based similarity, and data-aware behavior-based similarity, are introduced to quantify the similarity of data-aware business processes from different perspectives. By comparative evaluation, the effectiveness and applicability are demonstrated. The proposed methodology is readily applicable to enterprise process repository management problems.
Soft robotic fabric design, fabrication, and thermoregulation evaluation

Usually, traditional insulation materials have a constant thermal resistance value that cannot change within the ambient temperature and will decrease as ambient humidity or external stress increases. Humans heavily rely on heating, ventilation, and air conditioning (HVAC) systems to meet the thermal comfort requirements of their bodies, giving rise to energy waste and global warming. As an infinitely available natural resource, air is one of the most efficient thermal retaining substances known to science. Inspired by soft pneumatic robotics, we propose an architecture for air-driven thermoregulation fabrics called soft robotic fabrics (SRF). By changing the thickness of trapped air layer in fabric system through SRF, wearers could modify garments’ thermal insulation performance. A fabrication method is introduced to rapidly manufacture low-cost pneumatic structures using various types of construction and dimensions. With excellent ductility, elasticity, and compression resistance, the thickness of SRF increases by 12 times or more after inflation, and the fabric even can lift an object 270 times heavier than its weight. The excellent deformability can effectively increase stable air layer between clothing and skin. Based on the Predicted Mean Vote–Predicted Percentage of Dissatisfied model, the thermoregulation capability of SRF helps HVAC expand the temperature setpoint range by 3–8 times when compared with traditional fabrics, and has far-reaching significance in saving energy.
A numerical investigation of a thermal storage water heating system using phase change materials

In this paper, the process of thermal heat storage within a water heating system utilizing phase change materials was numerically investigated using a CFD simulation. A two-dimensional model of the water-PCM energy storage system was designed and modelled using ANSYS Fluent. Two cases of without and with PCM were studied to investigate the possibility of using PCM materials in water storage heating systems. Paraffin wax with a melting temperature of 52 °C is used as the PCM material. Results showed that PCM (can maintain the water temperature at a higher level than that of without using PCM that meets the thermal requirements of water heating storage systems for domestic application. Also, results showed that the water temperature at the end of the simulation reaches 39.7 and 48.2 °C for the cases of without and with using PCM respectively. This means the final temperature of with PCM case is 8.5 °C higher than that of without PCM case and a temperature increase of about 21.46% can be achieved. This study highlighted the advantage of using PCM materials in water storage heating systems.
Sequence and Regularity Controlled Coordination Copolymerization of Butadiene and Styrene: Strategy and Mechanism

The stereoselective and sequence controlled coordination copolymerizations of butadiene (BD) and styrene (St) with diblock, tapered, gradient, and random sequence distributions were achieved for the first time through varying the central metals of the rare-earth metal bis(alkyl) catalyst precursors (Flu-CH2-Py)Ln(CH2SiMe3)2(THF)x (Flu = fluorenyl, Py = pyridyl, x = 1: Ln = Nd(1), Y(2), Tm(3); x = 0, Ln = Sc(4)). The thermal behavior, morphology, and the mechanical property of these copolymers were analyzed, and their relationships were established for the first time. The mechanism of central metal size tuning the sequence distribution was discussed based on DFT calculations.
Diets, Food Choices and Environmental Impacts across an Urban-Rural Interface in Northern Vietnam

Human diets and their associated environmental impacts differ across segments of the population. There is evidence that consumer choices of food intake can also affect the overall environmental impacts of a food system. This paper analyzes the environmental impact of diets and food choices across a rural–urban transect in Northern Vietnam by using mixed survey data from 619 adult respondents. The average greenhouse gas emissions (GHGE) resulting from producing the daily food intake of adults in the urban and peri-urban districts were similar, while the average in the rural district was lower. Although starchy staples contributed the most to energy intake, pork and beef were the largest contributors to GHGE. Metrics of blue water use were higher for diets of males than those of females in all three districts. Interestingly, the difference in mean diet diversity score between urban and rural households was significant, and females’ diets were more diverse than those of males. As expected, urban households were more likely to buy food, while rural households often produced their own foods. Urban households reported prioritizing personal health and the natural content of food and would increase seafood and fruits if their income were to increase. In rural regions, interventions aimed at reducing undernutrition should address improving diet quality without significant increases to diet-related environmental impacts.