Three-dimensional topological relationships serve as a theoretical foundation for quality control, update processing, and spatial analysis of three-dimensional spatial data in real-world three-dimensional GIS. The existing 3D topological relationship models are all basic relationship models that cannot distinguish the refined topological relationship between the line and the body with multiple intersections. In this study, we develop a 3D refined topological relationship description framework that draws from the two-dimensional refined topological relationship model, defines the unit intersection between the line and the body based on manifold topology, and proposes a method for describing the unit intersections between the line and the body considering Euler numbers and adjacency types. In total, 23 basic types between the line and the body are deduced. An example is provided to illustrate the distinguished refined topological relationship between the line and the body with multiple intersections. Subsequently, an algorithm for determining the basic type of line/body is developed. Finally, a line/body refined topological relationship computation prototype system is developed using the Nef polyhedron model, C++ language, and an open-source geometric algorithm library, and the effectiveness of our method is verified using actual building and pedestrian data. Full article

Stuttering, affecting approximately 1% of the global population, is a complex speech disorder significantly impacting individuals’ quality of life. Prior studies using electromyography (EMG) to examine orofacial muscle activity in stuttering have presented mixed results, highlighting the variability in neuromuscular responses during stuttering episodes. Fifty-five participants with stuttering and 30 individuals without stuttering, aged between 18 and 40, participated in the study. EMG signals from five facial and cervical muscles were recorded during speech tasks and analyzed for mean amplitude and frequency activity in the 5–15 Hz range to identify significant differences. Upon analysis of the 5–15 Hz frequency range, a higher average amplitude was observed in the zygomaticus major muscle for participants while stuttering (p < 0.05). Additionally, when assessing the overall EMG signal amplitude, a higher average amplitude was observed in samples obtained from disfluencies in participants who did not stutter, particularly in the depressor anguli oris muscle (p < 0.05). Significant differences in muscle activity were observed between the two groups, particularly in the depressor anguli oris and zygomaticus major muscles. These results suggest that the underlying neuromuscular mechanisms of stuttering might involve subtle aspects of timing and coordination in muscle activation. Therefore, these findings may contribute to the field of biosensors by providing valuable perspectives on neuromuscular mechanisms and the relevance of electromyography in stuttering research. Further research in this area has the potential to advance the development of biosensor technology for language-related applications and therapeutic interventions in stuttering. Full article

In order to explore the influence of dip angles on the deformation and failure of a coal–rock combination, uniaxial compression experiments were carried out on a coal–rock combination with different dip angles, and the acoustic emissions (hereinafter referred to as AE) responses during loading were collected. Based on the damage mechanics theory and fractal theory, the fractal dimensions of different damage degrees were calculated. The results show that, with the increase in the inclination angle, the compressive strength and elastic modulus of the coal–rock combination gradually decreased, while the AE ringing count gradually increased first and then decreased. At the initial loading stage of the specimen, the greater the damage degree of the coal–rock combination under the same strain condition, the larger the value of its overall fractal dimension. The AE fractal dimension of the coal–rock combination increases gradually between 10% and 20% of the damage degree. It suddenly decreased between 50% and 60%, then increased slightly before gradually decreasing to the minimum between 80% and 100%. The sudden decrease in fractal dimension, a slight increase, and then a continuous decrease can be used as the precursor information for the instability and failure of the coal–rock combination. Full article

The growing interest in low-impact mobility technologies has elevated the significance of fuel cell electric vehicles (FCEVs) in the automotive sector. Given the complexity of the resulting powertrain, the need for an effective energy management strategy (EMS) becomes essential to optimize efficiency and energy consumption in vehicles with diverse energy sources. Model-based control is the main approach to address the EMS in electrified vehicles. In particular, fuel cell power is commonly represented through a 1D look-up table using the current demand as input to simplify the implementation in a vehicle control unit. Uncertainties that may be implemented in maps due to simplifying hypotheses, dynamics, ageing, etc., can be propagated to powertrain control, motivating the adoption of adaptive look-up tables for FC modelling. In this study, an extended Kalman filter (EKF) is proposed to adapt the look-up table to actual FC behaviour by measuring its power and gradually correcting calibration errors, drift, and ageing. Subsequently, a standard equivalent consumption minimization strategy (ECMS) is employed to control the FCEV. The fuel cell model is calibrated with experimental data from an FCEV. The results demonstrate that the adaptive strategy outperforms the base calibration. Following an extensive simulation campaign, an improvement of 1.1% in fuel consumption was observed. Remarkably, after just one hour of operation, there was a notable 85% reduction in fuel cell power estimation error, even when the EMS was initially fed a biased look-up table. Full article

Urban areas generate more than 70% of the world’s climate change emissions, mainly CO₂, produced by the combustion of fossil fuels. Climate change is increasing cities’ exposure to climate hazards, such as heat waves or floods. Therefore, there is a need to improve risk management with the inclusion of climate resilience in urban policy design. Despite improved urban climate monitoring, there are still relatively few scientific publications on climate change adaptation in urban areas. Adaptation to climate change is not achieved through specific action, but rather through the adoption and continuous implementation of adaptation actions such as housing rehabilitation, green space management and protection measures for vulnerable groups. This variety of actions makes it difficult not only to identify different indicators, but also to use common benchmarks. Considering the role of municipalities in adapting to climate change, it is crucial to identify adaptation indicators that serve as a basis for decision making, as well as evaluation methods that allow the effectiveness of planned and implemented measures in municipalities. It can be used to determine which measures increase the level of adaptation or lead to poor adaptation. Therefore, monitoring indicators makes it possible to evaluate the effectiveness of the measures, in addition to formulating new ones. This paper includes a literature review of existing index designed to address climate hazards and mitigate their impacts in urban areas. Full article

The serious problem of soil erosion not only has a profound impact on people’s lives but also results in a series of ecological and environmental challenges. To determine the impact of changes in land use type on soil erosion in the urban agglomeration on the northern slopes of the Tianshan Mountains, this study commences by employing the InVEST-SDR (integrated valuation of ecosystem services and tradeoffs–sediment delivery ratio) model to calculate soil erosion levels spanning from 2000 to 2020. Subsequently, it forecasts land use and land cover (LULC) conditions for the year 2030 under three scenarios: Q1 (natural development), Q2 (ecological protection), and Q3 (economic priority). This projection is accomplished through the integration of a coupled Markov chain and multi-objective planning model (MOP) alongside patch-generating land use simulation (PLUS) models. Ultimately, based on these outcomes, the study predicts soil erosion levels for the year 2030. There has been a consistent decline in soil erosion from 2000 to 2020 with high-intensity erosion concentrated in the Tianshan Mountain region. Grasslands, glaciers, and permafrost are identified as the most erosion-prone land types in the study area, with forests exhibiting the highest capacity for soil retention. Converting from grassland and barren land to forest within the same area results in a substantial reduction in soil erosion, specifically by 27.3% and 46.3%, respectively. Furthermore, the transformation from barren land to grassland also leads to a noteworthy 19% decrease in soil erosion. Over the past two decades, the study area has witnessed a significant decline in the area of grasslands, with a notable shift towards barren and impervious surfaces due to economic development and mining activities. The three predicted scenarios depict significant expansion towards barren land, grassland, and impervious area, respectively. Soil erosion decreases under different shared socio-economic pathway (SSP) scenarios relative to 2020. There is an increase in soil erosion in the Q1 scenario and in the Q3 scenario, whereas the amount of soil erosion in the Q2 scenario exhibits a continued decrease when only the effect of land change on soil erosion is considered. Persistently rapid economic development can exacerbate soil erosion problems, underscoring the need to find a balance between economic growth and ecological conservation. As economic expansion slows down, greater emphasis should be placed on environmental protection to maintain ecological stability. Full article

The increasing demand for sustainable alternatives underscores the critical need for a shift away from traditional hydrocarbon-dependent processes. In this landscape, biomanufacturing emerges as a compelling solution, offering a pathway to produce essential chemical materials with significantly reduced environmental impacts. By utilizing engineered microorganisms and biomass as raw materials, biomanufacturing seeks to achieve a carbon-neutral footprint, effectively counteracting the carbon dioxide emissions associated with fossil fuel use. The efficiency and specificity of biocatalysts further contribute to lowering energy consumption and enhancing the sustainability of the production process. Within this context, cell-free synthesis emerges as a promising approach to accelerate the shift towards biomanufacturing. Operating with cellular machinery in a controlled environment, cell-free synthesis offers multiple advantages: it enables the rapid evaluation of biosynthetic pathways and optimization of the conditions for the synthesis of specific chemicals. It also holds potential as an on-demand platform for the production of personalized and specialized products. This review explores recent progress in cell-free synthesis, highlighting its potential to expedite the transformation of chemical processes into more sustainable biomanufacturing practices. We discuss how cell-free techniques not only accelerate the development of new bioproducts but also broaden the horizons for sustainable chemical production. Additionally, we address the challenges of scaling these technologies for commercial use and ensuring their affordability, which are critical for cell-free systems to meet the future demands of industries and fully realize their potential. Full article

Fingerprint recognition systems have achieved widespread integration into various technological devices, including cell phones, computers, door locks, and time attendance machines. Nevertheless, individuals with worn fingerprints encounter challenges when attempting to unlock original fingerprint systems, which results in disruptions to their daily activities. This study explores two distinct methods for fingerprint backup: traditional fingerprint impression and 3D printing technologies. Unlocking tests were conducted on commonly available optical fingerprint lock-equipped cell phones to assess the efficacy of these methods, particularly in unlocking with worn fingerprints. The research findings indicated that the traditional fingerprint impression method exhibited high fidelity in reproducing fingerprint patterns, achieving an impressive unlocking success rate of 97.8% for imprinting unworn fingerprints. However, when dealing with worn fingerprints, the traditional fingerprint impression technique showed a reduced unlocking success rate, progressively decreasing with increasing degrees of finger wear. In contrast, 3D-printed backup fingerprints, with image processing and optimization of ridge height, mitigated the impact of fingerprint wear on the unlocking capability, resulting in an unlocking success rate of 84.4% or higher. Thus, the utilization of 3D printing technology proves advantageous for individuals with severely worn or incomplete fingerprints, providing a viable solution for unforeseen circumstances. Full article

Combining multiple devices for localization has important applications in the military field. This paper exploits the land-based short-wave platforms and satellites for fusion localization. The ionospheric reflection height error and satellite position errors have a great impact on the short-wave localization and satellite localization accuracy, respectively. In this paper, an iterative constrained weighted least squares (ICWLS) algorithm is proposed for these two kinds of errors. The algorithm converts the nonconvex equation constraints to linear constraints using the results of the previous iteration, thus ensuring convergence to the globally optimal solution. Simulation results show that the localization accuracy of the algorithm can reach the corresponding Constrained Cramér–Rao Lower Bound (CCRLB). Finally, the localization results of the two methods are fused using Kalman filtering. Simulations show that the fused localization accuracy is improved compared to the single-means localization. Full article

Background: In recent years, whole blood parameters and derivatives have been used as prognostic criteria in the course of various diseases. The aim of this study was to evaluate the relationship between parameters such as the neutrophil–lymphocyte ratio (NLR), the systemic immune-inflammation index (SII), the prognostic nutritional index (PNI), controlling nutritional status (CONUT) score, nutritional risk index (NRI) and immunonutrition status and disease activity in patients with ischemic stroke of the small-vessel, large-vessel and other etiologies. Methods: We retrospectively evaluated the records of 1454 consecutive ischemic stroke patients hospitalized in the emergency department of Gaziosmanpasa Education and Research Hospital from 2019 to 2023. Results: Of the 1350 patients with ischemic stroke included in the study, 58.8% had small-vessel disease, 29.3% had large-vessel disease and 11.9% had other etiologies. There was a significant difference between the three etiology groups for PNI and CONUT. The mean of PNI was 47.30 ± 8.06 in the other etiology group, 37.25 ± 7.23 in the small-vessel group, and 34.78 ± 8.16 in the large-vessel disease group. The mean of CONUT was 5.49 ± 1.20 in the small-vessel group, 5.12 ± 1.46 in the large-vessel group and 4.22 ± 1.11 in the other etiology group. In addition, CONUT and PNI were also found to be independent risk factors for mortality. A negative significant correlation was observed between PNI and NLR (r: −0.692), SII (r: −0.591), and CONUT (r: −0.511). Significant correlations were observed between CONUT and NLR (r: 0.402), SII (r: 0.312). Conclusions: PNI, CONUT and NRI were found as more accurate prognostic indicators of nutritional status in patients with ischemic stroke. NLR and SII may be important predictive markers in the course and prognosis of stroke. Full article

In 2023, China’s crude steel production amount reached 1.019 billion tons, and the energy consumption of China’s steel industry amount reached 561 million tons of coal. China’s steel industry, with its dominant reliance on coal for energy and the primary use of blast furnaces and converters in production processes, as well as its massive output, has become the main field for achieving China’s “carbon peaking” and “carbon neutrality” goals. Firstly, this article summarizes the current production status of the steel industry and the situation of carbon emissions in the steel industry. Secondly, it discusses the dual-carbon policies based on the national and steel industry levels and outlines the future directions for China’s steel industry. Subsequently, it analyzes the current state of research and application of mature and emerging low-carbon technology in China’s steel industry and details the low-carbon plans of China’s steel companies using the low-carbon technology roadmaps of two representative steel companies as examples. Finally, the article gives policy suggestions for the further carbon reduction of China’s steel industry. The purpose of this paper is to show the efforts and contributions of China’s steel industry to the early realization of its “carbon peaking” and “carbon neutrality” goals. Full article

Fish health is of significant ecological and economic importance. In response to public observations of parasite-like structures in a popular edible fish, this study aimed to characterize nematode larvae commonly found in the muscle and body cavity of Saurida tumbil (Bloch, 1795), a commercially important fish species inhabiting the Persian Gulf and Oman Sea. This fish, locally known as Hasoom, holds substantial culinary importance, being a staple in the diets of millions residing in countries around the Persian Gulf. A total of 458 Saurida tumbil specimens were obtained from fish markets between June 2022 and May 2023. Subsequent examination revealed the presence of a total of 6132 nematode larvae. Nematodes found in the body cavity were identified as belonging to the genus Hysterothylacium sp., family Raphidascarididae, while those in the muscle were identified as Anisakis sp. larval type, family Anisakidae. Histopathology results suggested that these parasites may have adverse health impacts on their fish host. Notably, both nematode genera were found in the third larval stage, which is known to be the infective stage for anisakidosis. Given the reported cases of anisakidosis among people living in the study region, it is strongly recommended that fish be properly cooked before consumption to mitigate health risks. Full article

To solve the problem that zinc oxide nanorods (ZnO NRs)-based self-powered ultraviolet (UV) photodetectors cannot obtain both higher responsiveness and shorter response time, P(EDOS-TTh) was prepared using 3,4-ethylenedioxyselenphene (EDOS) and terthiophene (TTh) as copolymers, which modify the ZnO NRs surface, and the ZnO/P(EDOS-TTh) P-N junction self-powered UV device is assembled. The effect of the number of electrochemical polymerization cycles on the UV photodetection performance of ZnO/P(EDOS-TTh) P-N heterojunction was studied by adjusting the number of electrochemical polymerization cycles at the monomer molar ratio of 1:1. Benefiting from the enhanced built-in electric field of the ZnO/P(EDOS-TTh) interface, balancing photogenerated carriers, and charge separation and transport. The results show that the contact between N-type ZnO NRs and P-type P(EDOS-TTh) is best when the number of polymerization cycles is 3, due to the fact that EDOS-TTh and ZnO NRs form excellent P-N heterojunctions with strong internal electric fields, and the devices show good pyroelectric effect and UV photodetection performance. Under 0 V bias and 0.32 mW/cm² UV irradiation, the responsivity (R) of ZnO/P(EDOS-TTh) reaches 3.31 mA/W, the detectivity (D*) is 7.25 × 10¹⁰ Jones, and the response time is significantly shortened. The rise time is 0.086 s, which exhibited excellent photoelectric properties and stability. UV photodetection performance with high sensitivity and fast response time is achieved. Full article

Background: climate change is a reality, and more and more people are becoming aware of this global problem, which has generated anxiety in some populations. To validate a short survey to assess eco-anxiety in adults in South America. Methods: It is an instrumental study, and the validation was based on a previous survey, which had six questions and was generated by 217 respondents in the USA in 2021. These questions were subjected to a validation process with expert judgment, pilot and application, and then statistics were obtained. It was validated with 1907 people in six countries in South America, where the mean, standard deviation, skewness and kurtosis were adequate. Results: The initial confirmatory factorial model obtained unsatisfactory goodness-of-fit indices, so the indices were modified through a re-specification, where two items were eliminated, after which adequate values were obtained (χ² = 22.34, df = 2, p = 0.00; RMR = 0.020; GFI = 0.990; CFI = 0.990; TLI = 0.990; and RMSEA = 0.070). Finally, the overall Cronbach’s α was calculated to be 0.88 (95% CI = 0.86–0.89). Conclusions: The test was validated in a large South American population and found that only four questions can efficiently measure anxiety about the effects of climate change. The instrument can be used with other tests to screen different age groups, ethnicities and realities. Full article

Because of their stochastic nature, the high penetration of electric vehicles (EVs) places demands on the power system that may strain network reliability. Along with increasing network voltage deviations, this can also lower the quality of the power provided. By placing EV fast charging stations (FCSs) in strategic grid locations, this issue can be resolved. Thus, this work suggests a new methodology incorporating an effective and straightforward Red-Tailed Hawk Algorithm (RTH) to identify the optimal locations and capacities for FCSs in a real Aljouf Transmission Network located in northern Saudi Arabia. Using a fitness function, this work’s objective is to minimize voltage violations over a 24 h period. The merits of the suggested RTH are its high convergence rate and ability to eschew local solutions. The results obtained via the suggested RTH are contrasted with those of other approaches such as the use of a Kepler optimization algorithm (KOA), gold rush optimizer (GRO), grey wolf optimizer (GWO), and spider wasp optimizer (SWO). Annual substation demand, solar irradiance, and photovoltaic (PV) temperature datasets are utilized in this study to describe the demand as well as the generation profiles in the proposed real network. A principal component analysis (PCA) is employed to reduce the complexity of each dataset and to prepare them for the k-means algorithm. Then, k-means clustering is used to partition each dataset into k distinct clusters evaluated using internal and external validity indices. The values of these indices are weighted to select the best number of clusters. Moreover, a Monte Carlo simulation (MCS) is applied to probabilistically determine the daily profile of each data set. According to the obtained results, the proposed RTH outperformed the others, achieving the lowest fitness value of 0.134346 pu, while the GRO came in second place with a voltage deviation of 0.135646 pu. Conversely, the KOA was the worst method, achieving a fitness value of 0.148358 pu. The outcomes attained validate the suggested approach’s competency in integrating FCSs into a real transmission grid by selecting their best locations and sizes. Full article

In this paper, we present the design of a fractional-order sliding mode observer (FO-SMO) for actuator fault estimation in a quadrotor unmanned aerial vehicle (QUAV) system. Actuator faults can significantly compromise the stability and performance of QUAV systems; therefore, early detection and compensation are crucial. Sliding mode observers (SMOs) have recently demonstrated their accuracy in estimating faults in QUAV systems under matched uncertainties. However, existing SMOs encounter difficulties associated with chattering and sensitivity to initial conditions and noise. These challenges significantly impact the precision of fault estimation and may even render fault estimation impossible depending on the magnitude of the fault. To address these challenges, we propose a new fractional-order SMO structure based on the Caputo derivative definition. To demonstrate the effectiveness of the proposed FO-SMO in overcoming the limitations associated with classical SMOs, we assess the robustness of the FO-SMO under three distinct scenarios. First, we examined its performance in estimating actuator faults under varying initial conditions. Second, we evaluated its ability to handle significant chattering phenomena during fault estimation. Finally, we analyzed its performance in fault estimation under noisy conditions. For comparison purposes, we assess the performance of both observers using the Normalized Root-Mean-Square Error (NRMSE) criterion. The results demonstrate that our approach enables more accurate actuator fault estimation, particularly in scenarios involving chattering phenomena and noise. In contrast, the performance of classical (non-fractional) SMO suffers significantly under these conditions. We concluded that our FO-SMO is more robust to initial conditions, chattering phenomena, and noise than the classical SMO. Full article

Currently, two significant problems involve the government, population, and environment: the accelerated increase in organic waste and the need to replace conventional energy with environmentally sustainable energy. The sustainable use of organic waste is being intensely investigated to generate energy plants that produce alternative sustainable electrical energy beneficial to the population at a low cost. The novelty of this research is given by the use of pepper waste as fuel in the generation of bioelectricity, giving added value to these types of waste, benefiting farmers and companies dedicated to the export and import of these fruits, because they will be able to generate their own electrical energy using their own waste at a lower cost. For this reason, this research uses pepper waste as fuel in single-chamber microbial fuel cells manufactured at a low cost as its primary objective. The maximum values of the electric current (5.118 ± 0.065 mA) and electric potential (1.018 ± 0.101 V) were shown on the fourteenth day, with an optimal operating pH of 7.141 ± 0.134 and electrical conductivity of 112.846 ± 4.888 mS/cm. Likewise, a reduction in the COD was observed from 1210.15 ± 0.89 mg/L to 190.36 ± 16.58 mg/L in the 35 days of monitoring and with a maximum ORP of 426.995 ± 8.615 mV, whose internal resistance was 33.541 ± 2.471 Ω. The peak power density was 154.142 ± 8.151 mW/cm² at a current density of 4.834 A/cm², and the Rossellomorea marisflavi strain was identified with 99.57% identity. Full article

This work assessed the influence of the amount of dentifrice and fluoride (F) concentration in the product on the pH and inorganic components of Streptococcus mutans and Candida albicans dual-species biofilms. The biofilms were treated with suspensions of fluoride dentifrices containing 550 or 1100 ppm of F (550 F or 1100 F, respectively) administered at comparable intensities: (i-1) 550 F/0.08 g or 1100 F/0.04 g; (i-2) 550 F/0.16 g or 1100 F/0.08 g; and (i-3) 550 F/0.32 g or 1100 F/0.16 g. A placebo dentifrice (without NaF, 0.32 g) was used as a negative control. After the last treatment, the biofilm pH was measured and the F, calcium (Ca), and phosphorus (P) concentrations were determined. Data were subjected to an ANOVA/Kruskal–Wallis test, and a Student–Newman–Keuls test. The highest biofilm pH and F concentrations (biomass and fluid) were observed for 1100 F at i-3. Overall, 1100 F resulted in F levels similar to 550 F for i-1 and i-2. In addition, 550 F applied at i-2 and i-3 led to higher F in the biomass/fluid compared to 1100 F applied at i-1 and i-2, respectively. In biomass, the lowest Ca concentrations were observed for 1100 F at i-3. The conclusion drawn is that the treatment intensity holds greater significance as a parameter compared to the concentration of F or the amount of dentifrice when considered individually. Full article

Interest in bacterial nanocellulose (BNC) has grown due to its purity, mechanical properties, and biological compatibility. To address the need for alternative carbon sources in the industrial production of BNC, this study focuses on banana leaves, discarded during harvesting, as a valuable source. Banana midrib juice, rich in nutrients and reducing sugars, is identified as a potential carbon source. An optimal culture medium was designed using a simplex-centroid mixing design and evaluated in a 10 L bioreactor. Techniques such as Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA) were used to characterize the structural, thermal, and morphological properties of BNC. Banana midrib juice exhibited specific properties, such as pH (5.64), reducing sugars (15.97 g/L), Trolox (45.07 µM), °Brix (4.00), and antioxidant activity (71% DPPH). The model achieved a 99.97% R-adjusted yield of 6.82 g BNC/L. Physicochemical analyses revealed distinctive attributes associated with BNC. This approach optimizes BNC production and emphasizes the banana midrib as a circular solution for BNC production, promoting sustainability in banana farming and contributing to the sustainable development goals. Full article

The application of Artificial Intelligence in Education (AIED) is experiencing widespread interest among students, educators, researchers, and policymakers. AIED is expected, among other things, to enhance learning environments in the higher education system. However, in line with the general trends, there are also increasing concerns about possible negative and collateral effects. The consequent social impact cannot be currently assessed in depth. Balancing benefits with social considerations according to a socio-technical approach is essential for harnessing the true power of AI in a responsible and trustworthy context. This study proposes a semi-systematic literature review of the available knowledge on the adoption of artificial intelligence (AI) in the higher education system. It presents a stakeholder-centric analysis to explore multiple perspectives, including pedagogical, managerial, technological, governmental, external, and social ones. The main goal is to identify and discuss major gaps and challenges in context, looking at the existing body of knowledge and momentum. AIED should encompass pedagogical, ethical, and social dimensions to be properly addressed. This review highlights a not-always-explicit socio-technical perspective. Additionally, this study reveals a significant lack of empirical systematic evaluation of added value and institutional readiness. Because of the broad scope of the study and the intense ongoing debate on the topic, an exhaustive identification of the current body of knowledge is probably unrealistic, so this study aims mainly to identify the mainstream and major trends by looking at the most recent contributions. Full article

The extent to which early weight loss in behavioral weight control interventions predicts long-term success remains unclear. In this study, we developed an algorithm aimed at classifying weight change trajectories and examined its ability to predict long-term weight loss based on weight early change. We utilized data from 667 de-identified individuals who participated in a commercial weight loss program (Instinct Health Science), comprising 69,363 weight records. Sequential polynomial regression models were employed to classify participants into distinct weight trajectory patterns based on key model parameters. Next, we applied multinomial logistic models to evaluate if early weight loss in the first 14 days and prolonged duration of participation were significantly associated with long-term weight loss patterns. The mean percentage of weight loss was 7.9 ± 5.1% over 133 ± 69 days. Our analysis revealed four main weight loss trajectory patterns: a steady decrease over time (30.6%), a decrease to a plateau with subsequent decline (15.8%), a decrease to a plateau with subsequent increase (46.9%), and no substantial decrease (6.7%). Early weight change rate and total participating duration emerged as significant factors in differentiating long-term weight loss patterns. These findings contribute to support the provision of tailored advice in the early phase of behavioral interventions for weight loss. Full article

The crucial role of urban industrial land redevelopment in sustainable urban renewal has garnered widespread attention. While some scholars have explored the interest game among stakeholders in industrial land redevelopment, they primarily focus on the government-led model. Moreover, there remains a research gap concerning the impact of government intervention on the redevelopment of industrial land. This article utilizes evolutionary game theory to investigate the interest game between local governments and original land users in the model of urban industrial land redevelopment dominated by original land users. We establish evolutionary game models considering incentives and the combination of incentives and regulations, explore the interest balance strategy, and examine the impact of positive incentives and mandatory regulations on industrial land redevelopment. Furthermore, we employ a numerical simulation to unveil the impact of initial strategies and parameter adjustments on game strategy. The research results are as follows: (1) Under the original land user-led redevelopment model, only two evolutionary stability strategies exist: either the original land users implement industrial land redevelopment with positive responses from local governments, or neither party advances the process. (2) Government intervention is pivotal in facilitating the redevelopment of inefficient industrial land as economic subsidies and punitive measures motivate more participants to adopt proactive strategies. (3) The increase in government support positively correlates with the likelihood of industrial land redevelopment implementation by original land users. (4) The interests and costs of original land users emerge as crucial parameters influencing strategic decisions. This study enriches the understanding of the interests of core participants in industrial land redevelopment and provides valuable insights for sustainable urban renewal. Full article