Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Hybrid Model Predictive Controller Design for Adaptive Cruise of Autonomous Electric Vehicles

Autonomous driving is an appealing research topic for integrating advanced intelligent algorithms to transform automotive industries and human commuting. This paper focuses on a hybrid model predictive controller (MPC) design for an adaptive cruise. The driving modes are divided into following and cruising, and the MPC algorithm based on simplified dual neural network (SDNN) and proportional-integral-derivative (PID) based on single neuron (SN) are applied to the following mode and the cruising mode, respectively. SDNN is used to accelerate the solution of the quadratic programming (QP) problem of the proposed MPC algorithm to improve the computation efficiency, while PID based on SN performs well in the nonlinear and time-varying conditions in the ACC system. Moreover, lateral dynamics control is integrated into the designed system to fulfill cruise control in the curved road conditions. Furthermore, to improve the energy efficiency of the electric vehicle, an energy feedback strategy is proposed. The simulation results show that the proposed ACC system is effective on both straight roads and curved roads.
Implication of classification of land types on the river banks on the layout of settlements planning (A case of the Ogan Ulu community, in South Sumatera, Indonesia)

ABSTRACT This article analyses the implications of the knowledge of the Ogan community in South Sumatra (Indonesia) about the types of land on the banks of the river on the layout of their settlements. Living on the river bank is an important identity for the Ogan Ulu community, but the condition of their rivers which tend to run watery and the inappropriate land use, of course, will have an impact on the destruction of settlements and their natural environment. Through anthropological studies, the results of the study show that the use of land on the river banks are not arbitrary, but it is based on how the community interprets the classification of soil types and the river’s behaviour in the river environment. This article confirms that the river's behaviour and classification of soil types have implications for the community's struggle to maintain settlements as their identity while preserving the river's environment.
Interactive Effects of Nitrogen and Water Addition on Soil Microbial Metabolic Limitation in Temperate Desert Shrublands

Aims Soil microbes play critical roles in regulating the turnover of soil organic carbon (SOC) and nutrients, and microbial metabolic limitation should draw more attention in desert ecosystems. However, soil extracellular enzymes activity (EEA) response and microbial metabolic limitation to atmospheric N deposition and increased precipitation in desert-shrubland are still poorly understood. Methods The study examined the effects of long-term (9 year) N and water additions (i.e., 5 g N m−2 yr−1, 30% ambient precipitation increase and their combination) on EEAs and soil microbial resource limitation, as well as explored their controlling factors in the Gurbantunggut Desert in northwestern China. Results The results showed that N and water additions significantly enhanced soil EEAs and considerably aggravated microbial phosphorous (P) limitation. Water addition and the N-water combination addition alleviated carbon (C) limitation, but N addition alone strengthened microbial C limitation. The interaction of N and water additions relieved the negative impact of N addition on soil microbial C limitation, and positively aggravated microbial P limitation. Soil microbial C limitation was primarily driven by soil moisture and organic C concentration, while the soil microbial N/P limitation was chiefly controlled by soil water and available P contents. Conclusions The influences of either N- or water addition alone on desert ecosystem biogeochemical processes may be altered by their concurrent occurrence. Overall, these findings highlight water availability is more effective at modifying microbial metabolisms than N accumulation in desert ecosystems. Altogether, this may help to predict how terrestrial C and nutrient flow could be induced by global change factors.
Relational turbulence from the COVID-19 pandemic: Within-subjects mediation by romantic partner interdependence

Relational turbulence theory posits that external changes to the relational environment compel romantic partners to navigate transitions by establishing new daily routines as interdependent couples. The COVID-19 pandemic is an unprecedented transition fraught with difficult changes that have the potential to be especially disruptive to romantic partners’ daily routines as couples alter their patterns of interdependence and adapt their everyday lives. To study the pandemic’s effect as a relational transition, college students in romantic relationships (N = 314) completed measures of partner facilitation and interference, negative emotions, and relational turbulence as they recalled what their relationships were like prior to the pandemic (January, 2020) and then reported on their relationships during the peak of the first wave of the pandemic in the U.S. (April, 2020). On average, negative emotions (i.e., anger, fear, sadness) toward interacting with partners and relational turbulence both increased from before to during the pandemic, and partner interference was positively correlated, whereas facilitation was inversely correlated, with negative emotions during the pandemic. Results of a within-subjects mediation model revealed that changes in relational turbulence were explained, in part, by a decrease in partner interdependence due to the pandemic. A direct effect of the pandemic on increases in relational turbulence was also discovered.
Modeling and analysis of hydrogen storage wind and gas complementary power generation system

In view of the uncertainty and volatility of wind power generation and the inability to provide stable and continuous power, this paper proposes a hydrogen storage wind-gas complementary power generation system, using Matlab/Simulink to simulate and model wind generators and gas turbines. Considering the economy and power supply reliability of the wind-gas complementary power generation system, and taking the economic and environmental cost of the system as the objective function, the capacity optimization model of the wind-gas complementary power generation system is established. The brain storming algorithm (BSO) is used to solve the optimization problem, and the BSO algorithm is used to optimize the BP neural network, which improves the accuracy of the BP neural network for load forecasting. Finally, a simulation is carried out with load data in a certain area, and the simulation verification verifies that BSO-BP can improve the accuracy of load forecasting and reduce the error of load forecasting. Multi-objective optimization of system economic cost and environmental cost through BSO algorithm can make the system cost reach the most reasonable level. Through the analysis of the calculation examples, it is verified that gas-fired power generation can effectively alleviate the volatility of wind power generation, showing the role and advantages of energy complementary power generation. Therefore, the wind-gas complementary system can effectively increase energy utilization and reduce wind curtailment.
Searching for Flexibility in Corporate Real Estate Portfolio: Six Co-Working Strategies for User Corporations

The increasing competitive pressures and dynamic user preferences have resulted in a fast-paced and uncertain business environment. In the face of these circumstances, organizations are looking into alternatives to incorporate flexibility to become more adaptive and responsive to change. In this line, co-working, typically associated with freelancers, entrepreneurs, and startups, has become a particularly interesting alternative in the market that has caught the attention of corporate occupiers. Therefore, the aim of this paper is to identify co-working strategies that can be implemented as part of the corporate real estate portfolio, in alignment with the flexibility demands of the organization. This nascent research topic is studied through 5 qualitative case studies including in-depth, semi-structured interviews with corporate real estate managers and related case documentation. The results evidence the different motivations that the organizations have when incorporating co-working in their property portfolio. As seen across the cases, organizations in different stages of maturity are implementing co-working as the main office location or as a temporary or complementary space solution, through six different strategies: (1) Swing Space, (2) Expansion Space, (3) Core and Flex, (4) Touchdown Space, (5) Testing Market, and (6) Temporary Projects and Staff. This research evidences that each strategy plays a specific role in the corporate real estate portfolio and implies different sources of flexibility that support the physical, functional, and financial flexibility demands of the organization.
Learning from mistakes: Improving spelling correction performance with automatic generation of realistic misspellings

Sequence to sequence models (seq2seq) require a large amount of labelled training data to learn the mapping between the input and output. A large set of misspelled words together with their corrections is needed to train a seq2seq spelling correction system. Low‐resource languages such as Turkish usually lack such large annotated datasets. Although misspelling‐reference pairs can be synthesized with a random procedure, the generated dataset may not well match to genuine human‐made misspellings. This might degrade the performance in realistic test scenarios. In this paper, we propose a novel procedure to automatically introduce human‐like misspellings to legitimate words in Turkish language. Generated human‐like misspellings are used to improve the performance of a seq2seq spelling correction system. The proposed system consists of two separate models; a misspelling generator and a spelling corrector. The generator is trained using a relatively small number of human‐made misspellings and their manual corrections. Reference words and their misspellings are used as inputs and outputs of the generator, respectively. As a result, it is trained to add realistic spelling errors to the valid words. Training data of the spelling corrector is augmented by the generator's human‐like misspellings. In the experiments, we observe that the data augmentation significantly improves the spelling correction performance. Our proposed method yields 5% absolute improvement over the state‐of‐the‐art Turkish spelling correction systems in a test set which contains human‐made misspellings from Twitter messages.
Accessibility and Connectivity Criteria for Assessing Walkability: An Application in Qazvin, Iran

Distance is a recognized key determinant of walking. Pedestrians tend to choose the shortest route between two points. Shortest routes can be spatially described in terms of distances between two points or topologically described as the number of turns/directional changes between these points. This paper presents a methodology to evaluate the conditions provided by a street network to pedestrians, by using two space syntax measures. Accessibility was calculated through Angular Segment Analysis by Metric Distance (ASAMeD), a measure of street integration and choice strongly correlated with pedestrian movement pattern. Street Connectivity was calculated by using the space syntax measure of connectivity, which shows the direct connection of street nodes to each individual nodes. The streets criterion values of both approaches were normalized by using fuzzy logic linear functions. The method was applied in the city center of Qazvin, Iran. Results showed that the urban structure of Qazvin has a strong impact on the performance of the network. The old neighborhood centers widespread in the city center presented a high topological accessibility, while the most connected street are those streets crossing and surrounding the neighborhood areas. The method can be used to evaluate and improve pedestrian networks, as it can distinguish the most and least attractive streets according to the criteria used. These findings can be used to guide policies towards improving walkability and to create more walkable and sustainable cities.
Late Pleistocene–Holocene stress in the South American intraplate evidenced by tectonic instability in central Amazonia

Abstract Documenting neotectonic instabilities and determining the style and time of deformation in the vast and difficult to access central Amazonia region is challenging. We focus on these issues by investigating a large area of the Negro River drainage basin, applying morphostructural analysis based on synthetic aperture radar data. The digital elevation models of the C-band Shuttle Radar Topography Mission and the L-band Protection System of Amazonia were used as the database. We also used subsurface magnetic information from the Earth Magnetic Anomaly Grid global model to validate the morphostructures. The results revealed NW-oriented morphostructural lineaments bounding multiple depositional valley fills. These were extensively fragmented to form regularly distributed en échelon rectangular blocks commonly offset horizontally by several kilometers. Strike-slip faults and oblique, either normal or reverse, faults are present. These structures were reactivated along the main NE- and SW-oriented regional structural trends due to N-S-oriented horizontal compression and E-W-oriented horizontal extension in the late Pleistocene and Holocene. The extensive neotectonic faulting results from the interplay of plate motion and Andean uplifting since the late Pleistocene, combined with local stresses.
Smart release of corrosion inhibitors by a novel encapsulation method

The objective of this project is to explore the feasibility of atomic layer deposition (ALD) and molecular layer deposition (MLD) as methods for the encapsulation of corrosion inhibitor. It is desirable to encapsulate the inhibitors before incorporation into the coating in order to provide a smart release only at specific conditions (acidic and alkaline pH in this case). ALD and MLD are processes to deposit conformal thin films with atomic and molecular level control, which leads to excellent step coverage and conformal deposition on complex micro- and nano-encapsulate structures. In this project, ALD and MLD process in different conditions were applied to three environmentally friendly inhibitors, namely 2-mercaptobenzothiazole (2-MBT), Ce(NO3)3 and Li2CO3, which present high protection performance against corrosion of aluminum alloys. After MLD and ALD, coverage of the coatings were characterized by scanning electron microscopy (SEM), coupled with energy dispersive x-ray spectroscopy (EDS) and Fourier transform infrared spectroscopy (FTIR). Leaching of coated inhibitors in solutions was studied by inductively coupled plasma-optical emission spectroscopy (ICP-OES) and ultraviolet-visible spectroscopy (UV-vis). Finally, the encapsulated inhibitors were incorporated into epoxy coating and applied on Al substrate. Inhibition efficiency was studied by electrochemical impedance spectroscopy (EIS). The results demonstrate that for the lithium carbonate, alumina shell can be formed in the surface via ALD process and a reduced leaching can be observed in the case of coated Li2CO3; healing effect can be observed in the encapsulated Li2CO3 doped coating, indicating the feasibility of this encapsulation concept on lithium carbonate. For the cerium nitrate, the inhibitor was coated with organic coating via MLD process but not well coated via ALD process; reduced leaching was not observed in this case and healing effect was not observed, neither. Organic shell can be well formed in the surface of 2-MBT, but the coating was not stable enough in solution to reduce leaching of the inhibitor; inhibition efficiency was not increased by doping the encapsulated 2-MBT into epoxy coating, possibly due to the reaction between shell material and epoxy coating.
Kernel Partial Least Square Regression with High Resistance to Multiple Outliers and Bad Leverage Points on Near-Infrared Spectral Data Analysis

Multivariate statistical analysis such as partial least square regression (PLSR) is the common data processing technique used to handle high-dimensional data space on near-infrared (NIR) spectral datasets. The PLSR is useful to tackle the multicollinearity and heteroscedasticity problem that can be commonly found in such data space. With the problem of the nonlinear structure in the original input space, the use of the classical PLSR model might not be appropriate. In addition, the contamination of multiple outliers and high leverage points (HLPs) in the dataset could further damage the model. Generally, HLPs contain both good leverage points (GLPs) and bad leverage points (BLPs); therefore, in this case, removing the BLPs seems relevant since it has a significant impact on the parameter estimates and can slow down the convergence process. On the other hand, the GLPs provide a good efficiency in the model calibration process; thus, they should not be eliminated. In this study, robust alternatives to the existing kernel partial least square (KPLS) regression, which are called the kernel partial robust GM6-estimator (KPRGM6) regression and the kernel partial robust modified GM6-estimator (KPRMGM6) regression are introduced. The nonlinear solution on PLSR was handled through kernel-based learning by nonlinearly projecting the original input data matrix into a high-dimensional feature mapping that corresponded to the reproducing kernel Hilbert spaces (RKHS). To increase the robustness, the improvements on GM6 estimators are presented with the nonlinear PLSR. Based on the investigation using several artificial dataset scenarios from Monte Carlo simulations and two sets from the near-infrared (NIR) spectral dataset, the proposed robust KPRMGM6 is found to be superior to the robust KPRGM6 and non-robust KPLS.
Smoking among High School Students in Iran: A Meta-Analysis Study

Objective: Cigarette smoking is an important and preventable risk factor, especially for adolescents and high school students. This issue has become one of the challenges for health system. Thus, the present study aimed to investigate the prevalence of smoking among Iranian high school students. Method : This systematic review and meta-analysis study was done by searching PubMed, Scopus, Web Science (WOS), Science Direct, SID, and Google Scholar using the following keywords: “student” and “smoking” from 2000 to March 2018. After initial and critical appraisal, data were entered into a checklist and analyzed by a comprehensive meta-analysis software. Results: The prevalence of smoking was 7.9% by combining the results of 49 articles. Males and females had 10.6% and 4.5% smoking prevalence, respectively. The overall prevalence of smoking was higher in northern areas in Iran (22.4%). Males in the northern (22.4%) and females in western regions (5.3%) were more smokers. There was a significant relationship between the prevalence of smoking with the year of publication, sample size, and age (P < 0.001). Conclusion: In this study, Students' tendency to smoke was different in various regions of Iran, and had a high rate (7.9%). This figure indicates the necessity for planning some coherent educational programs for the public.
Callogenesis and in vitro Regeneration of Baru (Dipteryx alata Vog.) Esprouts

The aim of this study was to evaluate the effect of different concentrations of 6-benzylaminopurine (BAP) and naphthalene acetic acid (ANA) on calogenesis and regeneration from baru leaf and apex segments. The explants were obtained from baru plants previously established in vitro from almonds and cauline apices. The leaf segments were placed in Petri dishes containing MS medium (Murashige & Skoog, 1962) with concentrations (0.0, 2.0, 3.0, 4.0 and 5.0 mg L) BAP combined with ANA (0.0 and 2.0 mg L). The shoot apices were inoculated in test tubes with the same medium using the concentrations (0.0, 0.5, 1.0 and 1.5 mg L) BAP combined (0.0 and 0.1 mg L) ANA. After 25 days of inoculation, the percentages of callus and texture in leaf explants and apices were evaluated. The number of shoots was also evaluated by the Scott-Knott test at 5% of probability. The most efficient concentration in the formation of callus in leaves was 3.0 mg L BAP + 2.0 mg L ANA (68.88%), at apexes the most efficient concentration was 1.0 mg L BAP without ANA with 100% calogenesis. The most effective concentration was 1.0 mg L BAP without ANA with an average of 1.90 of shoots in relation to the concentrations evaluated.
Screening for Cold Tolerance during Germination within Sweet and Fiber Sorghums [Sorghum bicolor (L.) Moench] for Energy Biomass

Within the project “BIOSEA” funded by the Italian Ministry of Agriculture and Forestry, a preliminary laboratory test was conducted to assess the variability for cold tolerance during germination in 30 cultivars of biomass sorghum, among fiber and sweet types. Seed germination (%) and mean germination time (MGT) were examined at seven constant temperatures (from 8 °C to 35 °C) and base temperature (Tb) and thermal time (θT) for 50% germination were calculated. A wide genetic diversity in the germination response of sorghum was ascertained at 8 °C (CV 45%) and 10 °C (CV 25.4%). At 8 °C, in cultivars of ‘Padana 4’, ‘PR811F’, ‘PSE24213’, ‘PR849’ and ‘Zerberus’, seed germination exceeded 80%. Seeds of ‘Zerberus’ were also the fastest, requiring less than 13 days for final germination at this low temperature. Great differences were found in Tb and θT among cultivars. Tb varied between 7.44 °C (‘PR811F’) and 13.48 °C (‘Nectar’). Thermal time (θT) was, on average, 24.09 °Cd−1, and ranged between 16.62 (‘Nectar’) and 33.42 °Cd−1 (‘PSE24213’). The best combination of the two germination parameters (i.e., low Tb and θT) corresponded to ‘Zerberus’, ‘Sucrosorgo 506’, ‘Jumbo’ and ‘PR811F’. Accordingly, these cultivars are more tolerant to cold stress during germination and, thus, more adapt to early spring sowings in Mediterranean areas (March-April). Cultivars ‘PR811F’ (fiber type) and ‘Sucrosorgo 506’ (sweet type) also combine high cold tolerance with good productivity in terms of final dry biomass, as assessed in open-field conditions (late spring sowing). The genetic variation in the germination response to a low temperature is useful for the identification of genotypes of sorghum suitable to early sowings in semi-arid areas. Selection within existing cultivars for cold tolerance during germination may also contribute to the expansion of biomass sorghum into cooler cultivation areas, such as those of Northern Europe, which are less suitable to this warm season crop.