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In our pursuit of understanding the intricacies of microbial life, the isolation and characterization of new microbial species and strains play a pivotal role [...]
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Housing different animal groups in close-by facilities is common in wildlife centers. However, the impact on animal welfare is insufficiently studied in the literature. In this study, we analyzed the behavior of two adjacently housed chimpanzee groups to investigate how intergroup interactions may
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Housing different animal groups in close-by facilities is common in wildlife centers. However, the impact on animal welfare is insufficiently studied in the literature. In this study, we analyzed the behavior of two adjacently housed chimpanzee groups to investigate how intergroup interactions may affect their behavior and, thus, their welfare. We recorded occurrences of abnormal and self-directed behaviors, two well-known indicators of stress in chimpanzees. Furthermore, we explored the social responses to said intergroup interactions by recording all inter- and intragroup affiliative and agonistic behaviors. Finally, we measured the number of vigilance occurrences that individuals directed towards other chimpanzees as an indicator of interest. Generalized Linear Mixed Models (GLMMs) were used to assess whether and how social interactions between neighboring groups might influence their behaviors, taking gender, age, group, and intergroup participation into account. Our results suggest that intergroup interactions promoted the occurrence of affiliative behaviors between group members. However, intergroup interactions caused the chimpanzees to exhibit a higher number of abnormal and self-directed behaviors and increased vigilance towards their group members when agonistic intergroup interactions occurred. Thus, adjacent housing does impact the chimpanzees’ behavior and welfare and should be continuously monitored and assessed to promote and maximize welfare.
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The development of cell-based biomaterial alternatives holds significant promise in tissue engineering applications, but it requires accurate mechanical assessment. Herein, we present the development of a novel 3D-printed confined compression apparatus, fabricated using clear resin, designed to cater to the unique demands of
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The development of cell-based biomaterial alternatives holds significant promise in tissue engineering applications, but it requires accurate mechanical assessment. Herein, we present the development of a novel 3D-printed confined compression apparatus, fabricated using clear resin, designed to cater to the unique demands of biomaterial developers. Our objective was to enhance the precision of force measurements and improve sample visibility during compression testing. We compared the performance of our innovative 3D-printed confined compression setup to a conventional setup by performing stress relaxation testing on hydrogels with variable degrees of crosslinking. We assessed equilibrium force, aggregate modulus, and peak force. This study demonstrates that our revised setup can capture a larger range of force values while simultaneously improving accuracy. We were able to detect significant differences in force and aggregate modulus measurements of hydrogels with variable degrees of crosslinking using our revised setup, whereas these were indistinguishable with the convectional apparatus. Further, by incorporating a clear resin in the fabrication of the compression chamber, we improved sample visibility, thus enabling real-time monitoring and informed assessment of biomaterial behavior under compressive testing.
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Satellite computing represents a recent computational paradigm in the development of low Earth orbit (LEO) satellites. It aims to augment the capabilities of LEO satellites beyond their current transparent relay functions by enabling real-time processing, thereby providing low-latency computational services to end users.
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Satellite computing represents a recent computational paradigm in the development of low Earth orbit (LEO) satellites. It aims to augment the capabilities of LEO satellites beyond their current transparent relay functions by enabling real-time processing, thereby providing low-latency computational services to end users. In LEO constellations, a significant deployment of computationally capable satellites is orchestrated to offer enhanced computational resources. Challenges arise in the optimal allocation of terminal services to the most suitable satellite due to overlapping coverage among neighboring satellites, compounded by constraints on satellite energy and computational resources. The satellite service allocation (SSA) problem is recognized as NP-hard, yet assessing allocation methods through results allows for the application of deep reinforcement learning (DRL) to obtain improved solutions, partially addressing the SSA challenge. In this paper, we introduce a satellite computing capability model to quantify satellite computational resources. A DRL model is proposed to address service demands, computational resources, and resolve service allocation conflicts, strategically placing each service on appropriate servers. Through simulation experiments, numerical results demonstrate the superiority of our proposed method over baseline approaches in service allocation and satellite resource utilization, showcasing advancements in this field.
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Ammonia is a very promising alternative fuel for internal combustion engines, but there are some disadvantages, such as difficulty in ignition and slow combustion rate when ammonia is used alone. Aiming to address the problem of ammonia combustion difficulty, measures are proposed to
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Ammonia is a very promising alternative fuel for internal combustion engines, but there are some disadvantages, such as difficulty in ignition and slow combustion rate when ammonia is used alone. Aiming to address the problem of ammonia combustion difficulty, measures are proposed to improve ammonia combustion by blending hydrogen. A one-dimensional turbocharged ammonia-hydrogen engine simulation model was established, and the combustion model was corrected and verified. Using the verified one-dimensional model, the effects of different ratios of hydrogen to ammonia, different rotational speeds and loads on the combustion performance are investigated. The results show that the ignition delay and combustion duration is shortened with the increase of the hydrogen blending ratio. The appropriate amount of hydrogen blending can improve the brake’s thermal efficiency. With the increase in engine speed, increasing the proportion of hydrogen blending is necessary to ensure reliable ignition. In conclusion, the ammonia-hydrogen fuel engine has good combustion performance, but it is necessary to choose the appropriate hydrogen blending ratio according to the engine’s operating conditions and requirements.
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The aging intensity (AI), defined as the ratio of the instantaneous hazard rate and a baseline hazard rate, is a useful tool for the describing reliability properties of a random variable corresponding to a lifetime. In this work, the concept of AI is
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The aging intensity (AI), defined as the ratio of the instantaneous hazard rate and a baseline hazard rate, is a useful tool for the describing reliability properties of a random variable corresponding to a lifetime. In this work, the concept of AI is introduced in step-stress accelerated life testing (SSALT) experiments, providing new insights to the model and enabling the further clarification of the differences between the two commonly employed cumulative exposure (CE) and tampered failure rate (TFR) models. New AI-based estimators for the parameters of a SSALT model are proposed and compared to the MLEs in terms of examples and a simulation study.
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In everyday life, we recurrently perform two tasks simultaneously, which is called dual-tasking. A common dual task is smartphone use while standing or walking. According to previous studies, this task can compromise postural stability. However, few studies have analyzed lower limb muscle activity
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In everyday life, we recurrently perform two tasks simultaneously, which is called dual-tasking. A common dual task is smartphone use while standing or walking. According to previous studies, this task can compromise postural stability. However, few studies have analyzed lower limb muscle activity during dual-tasking using smartphones. This study aimed to assess the postural sway and muscle activity during dual-tasking in young adults. Thirty-six healthy young adults (23.08 ± 3.92 years) participated in this study. They performed a single task (ST: keeping a quiet standing posture) and a dual task (DT: keeping the ST while simultaneously performing a cognitive task on their smartphone). Postural sway was assessed through the center of pressure (CoP) analysis using a force platform: total CoP displacement, CoP displacement in the anterior–posterior and medial–lateral directions, mean total velocity of the CoP, mean velocity of the CoP in the anterior–posterior and medial–lateral directions, and 95% confidence ellipse sway area. A surface electromyography system recorded the muscle activity of the lumbar spinal erector and five muscles of the lower limb (bilaterally). The results showed an increase in postural sway from the ST to the DT in all CoP variables (p < 0.05), and muscle activity in most muscles analyzed decreased from the ST to the DT (p < 0.05). In conclusion, our results reflect a decentralization of attention from motor performance once postural sway increased and muscle activity decreased in dual-task conditions.
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Trust plays a crucial role in effectively responding to public health emergencies. Drawing on COVID-19 survey data conducted in Hubei, China, during August 2020 with a sample size of 5494, this study investigated the influence of individuals’ socioeconomic status on trust in acquaintances,
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Trust plays a crucial role in effectively responding to public health emergencies. Drawing on COVID-19 survey data conducted in Hubei, China, during August 2020 with a sample size of 5494, this study investigated the influence of individuals’ socioeconomic status on trust in acquaintances, strangers and institutions, and how this relationship is moderated by epidemic prevention, policy perception and family structure. The findings showed that individuals with higher socioeconomic status tend to have higher levels of trust. Those with higher income but being married demonstrate higher trust. When perceiving epidemic prevention policies as stringent, those with higher income display increased trust in acquaintances and institutions; similarly, those with lower education levels exhibit heightened trust in acquaintances and strangers. Individuals working in social organizations express higher trust in strangers; however, their trust is compromised under stringent epidemic prevention policies due to potentially heavier work burdens.
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Grasslands in China cover an extensive area and rank second globally. They constitute the second-largest carbon reservoir in China after forests, holding about 8% of the total carbon stock of the world’s grassland ecosystems. This study focuses on the grasslands of Wuchuan County,
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Grasslands in China cover an extensive area and rank second globally. They constitute the second-largest carbon reservoir in China after forests, holding about 8% of the total carbon stock of the world’s grassland ecosystems. This study focuses on the grasslands of Wuchuan County, Inner Mongolia Autonomous Region of Northern China. This study compares the carbon stock and density characteristics across different communities based on plot survey and GIS vector data. It also anticipates the region’s carbon sequestration potential using biomass-to-carbon conversion and extrapolation methods. The findings indicate that (1) the total carbon stock in the study area is 1805.65 × 104 tons with an average carbon density of 77.50 t/ha. The distribution of carbon density and stock follows a pattern: soil layer > herbaceous layer > litter layer; (2) the Stipa krylovii + Leymus chinensis community exhibits the highest carbon stock and density; (3) there is a positive correlation between herbaceous carbon density and NPP (Net Primary Productivity) values in the study area; and (4) the overall carbon stock in the region is projected to increase, with growth rates accelerating annually. These results contribute to our understanding of the formation, turnover, stability maintenance, and regulation mechanisms of grassland soil organic carbon. Furthermore, they hold significant implications for enhancing the carbon sequestration capacity of ecosystems.
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The Maronite Church states that it is an Antiochene and Syriac Church. This article traces, in chronological and discursive fashion, the emergence of the Maronite tradition. It explores the life and significance of St Maroun (d. ca AD 418–23), giving consideration to thinkers
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The Maronite Church states that it is an Antiochene and Syriac Church. This article traces, in chronological and discursive fashion, the emergence of the Maronite tradition. It explores the life and significance of St Maroun (d. ca AD 418–23), giving consideration to thinkers who helped to understand his outlook and methods and assessing what we know of the St Maroun monastery (Dayr Mar Maroun) and its vicissitudes down to the sixth century. The piece then treats Maronites in the context of the seventh-century monothelite controversy, following their foundational developments up to the time of their first patriarch Yohanna Maroun (flor. 680s). The paper considers not only the ascetic and monastic currents in the early Maronite community but also touches on the influence of Syriac typology and its gradual displacement by analytic and dogmatic theology.
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The widespread vibration is one of the most promising energy sources for IoT and small sensors, and broad-frequency vibration energy harvesting is important. Triboelectric nanogenerators (TENGs) can convert vibration energy into electrical energy through triboelectricity and electrostatic induction, providing an effective solution to
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The widespread vibration is one of the most promising energy sources for IoT and small sensors, and broad-frequency vibration energy harvesting is important. Triboelectric nanogenerators (TENGs) can convert vibration energy into electrical energy through triboelectricity and electrostatic induction, providing an effective solution to the collection of broad-frequency vibration energy. Also, the power supply in constrained and compact spaces has been a long-standing challenge. Here, a miniaturized power supply (MPS) based on a broad-frequency vibration-driven triboelectric nanogenerator (TENG) is developed. The size of the MPS is 38 mm × 26 mm × 20 mm, which can adapt to most space-limited environments. The TENG device is optimized through theoretical mechanical modeling for the external stimuli, it can efficiently harvest vibrational energy in the frequency range of 1–100 Hz and has a high output power density of 134.11 W/cm3. The developed device demonstrates its practical application potential in powering small electronics like LEDs, watches, and timers.
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by
Yee Chang Soh, Andrea Fairley, Mawada Alawad, Siew Siew Lee, Tin Tin Su, Blossom Christa Maree Stephan, Daniel Reidpath, Louise Robinson, Shajahan Yasin, Mario Siervo and Devi Mohan
Nutrients2024, 16(10), 1461; https://doi.org/10.3390/nu16101461 (registering DOI) - 13 May 2024
This cross-sectional study evaluated the validity of three alternative methods compared to the gold standard 24-h urine collection for estimating dietary sodium intake, a modifiable risk factor for hypertension, among middle-aged and older adults with elevated blood pressure. These included spot urine collection
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This cross-sectional study evaluated the validity of three alternative methods compared to the gold standard 24-h urine collection for estimating dietary sodium intake, a modifiable risk factor for hypertension, among middle-aged and older adults with elevated blood pressure. These included spot urine collection (using Kawasaki, Tanaka, and INTERSALT equations), 24-h dietary recall, and food frequency questionnaire responses, compared to 24-h urine collection in a subset of 65 participants (aged 50–75 years, 58.5% women, 61.6% hypertensive) from the DePEC-Nutrition trial. The validity of the methods was assessed using bias, the Spearman correlation coefficient (SCC), the intraclass correlation coefficient (ICC), and Bland–Altman analysis. Among the alternative methods, spot urine collection using the Kawasaki equation showed the strongest correlation (SCC 0.238; ICC 0.119, 95% CI −0.079 to 0.323), but it exhibited a significant bias (1414 mg/day, p-value < 0.001) relative to 24-h urine collection. Conversely, dietary surveys had a smaller bias but wider limits of agreement. These findings underscore the complexities of accurately estimating dietary sodium intake using spot urine collection or dietary surveys in this specific population, suggesting that a combination or the refinement of existing methodologies might improve accuracy. Further research with larger samples is necessary to develop more reliable methods for assessing sodium intake in this high-risk group.
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The article presents the results of obtaining a composite material by sintering nickel-containing raw materials mixed with carbon-containing materials, namely using coke and semi-coke. The sintering process was performed at a charge layer height of 240 mm and the temperature of the lower
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The article presents the results of obtaining a composite material by sintering nickel-containing raw materials mixed with carbon-containing materials, namely using coke and semi-coke. The sintering process was performed at a charge layer height of 240 mm and the temperature of the lower layer was T = 1200 °C. The results of the sieve analysis showed (a fraction of 10 mm) that the yield of a suitable composite material using coke was 68.3% and with semi-coke 67.0%. The average nickel and chromium content in the composite materials was 1.42% and 3.07%, accordingly. As a result of determining the strength characteristics of the obtained composite materials with various reducing agents by dropping from a height of 2 m onto a steel pallet, it was found that the obtained composite materials have high mechanical properties in terms of strength of 81% and 89.2%. The results of the elemental composition at the studied points and the thermal analysis of the studied composite material are presented. The mineralogical composition of the composite material is presented in the form of serpentine and nontronite, and the empty rock is made of quartz and talc. The activation energy of thermal analysis by the method of non-isothermal kinetics were calculated. The results of experiments on the production of composite materials from nickel-containing raw materials will be recommended for obtaining the optimal composition of composite materials at the stage of pilot tests and industrial development of the developed technology for processing nickel ores of the Republic of Kazakhstan. For the processing of nickel-poor nickel ores, it is of great importance to obtain optimal technological and technical and economic indicators that ensure low cost of nickel in the resulting product.
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In unstructured environments, robots need to deal with a wide variety of objects with diverse shapes, and often, the instances of these objects are unknown. Traditional methods rely on training with large-scale labeled data, but in environments with continuous and high-dimensional state spaces,
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In unstructured environments, robots need to deal with a wide variety of objects with diverse shapes, and often, the instances of these objects are unknown. Traditional methods rely on training with large-scale labeled data, but in environments with continuous and high-dimensional state spaces, the data become sparse, leading to weak generalization ability of the trained models when transferred to real-world applications. To address this challenge, we present an innovative maximum entropy Deep Q-Network (ME-DQN), which leverages an attention mechanism. The framework solves complex and sparse reward tasks through probabilistic reasoning while eliminating the trouble of adjusting hyper-parameters. This approach aims to merge the robust feature extraction capabilities of Fully Convolutional Networks (FCNs) with the efficient feature selection of the attention mechanism across diverse task scenarios. By integrating an advantage function with the reasoning and decision-making of deep reinforcement learning, ME-DQN propels the frontier of robotic grasping and expands the boundaries of intelligent perception and grasping decision-making in unstructured environments. Our simulations demonstrate a remarkable grasping success rate of 91.6%, while maintaining excellent generalization performance in the real world.
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The paper presents a critical review and new accomplishments on the equivalence of the first-order displacement-based zigzag theories for laminated composite and sandwich structures. Zigzag theories (ZZTs) have widely spread among researchers over the last few decades thanks to their accuracy in predicting
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The paper presents a critical review and new accomplishments on the equivalence of the first-order displacement-based zigzag theories for laminated composite and sandwich structures. Zigzag theories (ZZTs) have widely spread among researchers over the last few decades thanks to their accuracy in predicting the response of multilayered composite and sandwich structures while retaining the simplicity of their underlying equivalent single-layer (ESL) theory. The displacement field consists of two main contributions: the global one, able to describe the overall structural behaviour, and the local layer-wise one that considers the transverse shear continuity at the layer interfaces that describe the “zigzag” displacement pattern typical of multilayered structures. In the framework of displacement-based linear ZZTs, various assumptions have been made on the local contribution, and different theories have been deduced. This paper aims to provide a unified formulation for first-order ZZTs, highlighting some common aspects and underlying equivalencies with existing formulations. The mathematical demonstrations and the numerical examples prove the equivalence of the approaches to characterising local zigzag enrichment. Finally, it is demonstrated that the kinematic assumptions are the discriminants of the ZZTs’ accuracy.
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In this paper, experimental results about the performance of a Takagi–Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration of the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is
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In this paper, experimental results about the performance of a Takagi–Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration of the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. In this work, following the Takagi–Sugeno (TS) fuzzy control design methodology, the Parallel Distributed Compensation (PDC) approach is used in the design of the TSFC. The EV3BRS’s TS Fuzzy Model (TSFM) design comes from linearization of the nonlinear model around two operation points near the upright position of EV3BRS’s body. The Linear Matrix Inequality (LMI) approach was used to obtain the feedback gains for every local linear controller, guaranteeing, via a conservative stability condition, the global asymptotic stability of the overall fuzzy control system. The main goal of the control task consists of maintaining the EV3BRS’s body at its upright position. Measurement and control data from and to the EV3BRS are transferred via telecontrol and telemetry. The appropriate performance of the controller design is corroborated via experimentation.
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In this paper, we provide a blow-up criterion for the density-dependent incompressible magnetohydrodynamic system with zero viscosity. The proof uses the -method and the Kato–Ponce inequalities in the harmonic analysis. The novelty of our work lies in the fact that we
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In this paper, we provide a blow-up criterion for the density-dependent incompressible magnetohydrodynamic system with zero viscosity. The proof uses the -method and the Kato–Ponce inequalities in the harmonic analysis. The novelty of our work lies in the fact that we deal with the case in which the resistivity is positive.
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This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease
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This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease human processing times while maintaining a reduced root mean square error (RMSE) for 3D reconstruction. Additionally, we propose utilizing COLMAP to enhance reconstruction accuracy by solely utilizing a sparse point cloud. The results demonstrate that implementing COLMAP for pre-processing reduces the RMSE by up to 16.9% in most cases. We prove that VGCPs further reduce the RMSE by up to 61.08%.
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Having a comprehensive knowledge of phase equilibrium is advantageous for industrial simulation and design of chemical processes. For further acquisition of primary data to facilitate the separation and purification of waste oil biodiesel systems, a liquid–liquid equilibrium (LLE) tank is deployed for the
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Having a comprehensive knowledge of phase equilibrium is advantageous for industrial simulation and design of chemical processes. For further acquisition of primary data to facilitate the separation and purification of waste oil biodiesel systems, a liquid–liquid equilibrium (LLE) tank is deployed for the ternary system of waste oil biodiesel + methanol + glycerin, thereby enhancing the precision and efficiency of the process. The phase equilibrium system was constructed under the influence of atmospheric pressure at precise temperatures of 303.15 K, 313.15 K, and 323.15 K. The equilibrium components of each substance were analyzed by employing high-temperature gas chromatography, a sophisticated analytical method that enables the identification and quantification of individual components of a sample. Moreover, the ternary liquid–liquid equilibrium data were correlated by implementing the NRTL and UNIQUAC activity coefficient models. Subsequently, the binary interaction parameters of the ternary system were derived by conducting regression analysis. The experimental data demonstrated that the presence of lower methanol content in the system resulted in nearly immiscible biodiesel and glycerol phases, which ultimately facilitated the separation of biodiesel and glycerol. Conversely, with the increase in methanol content, the mutual solubility of biodiesel and glycerol was observed to increase gradually. The results showed that the calculated values of the NRTL and UNIQUAC models aligned well with the experimental values. The root-mean-square deviations of the NRTL and UNIQUAC models at 313.15 K were 2.76% and 3.56%, respectively.
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The ecumene defines a beyond-border space of strong cultural encounters, flows, and merging, grounded within the traditions of world-systems, globalization, transnationalism, and cosmopolitanism discourses. Furthermore, the ecumene links directly with international regions as core political platforms in the making. As such, there are
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The ecumene defines a beyond-border space of strong cultural encounters, flows, and merging, grounded within the traditions of world-systems, globalization, transnationalism, and cosmopolitanism discourses. Furthermore, the ecumene links directly with international regions as core political platforms in the making. As such, there are several ecumenes on the forefront, as evidenced by the literature, which can be clustered into ideal types. Epistemologically, it is a relevant concept and tool for a science-of-the-future that focuses on conviviality and transformation for the yet-to-come. Analytically, the ecumene has a descriptive, normative, and critical dimension, and can be empirically accessed through operational concepts such as triggers, hubs, and types of beyond-border conviviality. To apply the ecumene as a research program means to detect convivial common-sense spaces within the global context.
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The Nature Park Ponjavica (NP) is the habitat of strictly protected plant and animal species, located in AP Vojvodina, in southern Banat (Northern Serbia). The area of the park covers 302,96 ha. Protection zones I, II, and III have been established in the
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The Nature Park Ponjavica (NP) is the habitat of strictly protected plant and animal species, located in AP Vojvodina, in southern Banat (Northern Serbia). The area of the park covers 302,96 ha. Protection zones I, II, and III have been established in the protected area of the NP. The NP includes the middle course of the Ponjavica River, which has preserved characteristics of watercourses of plain areas and coastal remains of wetland habitats. The most valuable area of this park in terms of protection is an island with an area of slightly less than 1 hectare. According to the IUCN (International Union for Conservation of Nature), the NP is classified as the fourth category—Habitat and species management area. The good geographical position of NP is one of its main characteristics. The NP can be a destination where specific forms of tourism can be developed, such as ecotourism, nature-based tourism, birdwatching, scientific and research tourism, etc. Numerous historical sites represent a significant potential for the development of cultural tourism. The research examined the influence of institutional, economic, ecological, and socio-cultural sustainability on the respondents’ satisfaction. The quantitative methodology in this research included a questionnaire as a survey instrument for respondents. A total of 547 residents were surveyed. The results of the research indicate that there is considerable satisfaction among residents with sustainable tourism. The results of the research can help in the development of numerous tourism development strategies in which the wetland is the primary resource.
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The advancement of sensor, actuator, and flight control technologies has increasingly expanded the possibilities for drone utilization. Among the technologies related to drone applications, the vibration isolator technology for payload has a significant impact on the precision of optical equipment in missions such
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The advancement of sensor, actuator, and flight control technologies has increasingly expanded the possibilities for drone utilization. Among the technologies related to drone applications, the vibration isolator technology for payload has a significant impact on the precision of optical equipment in missions such as detection, reconnaissance, and tracking. However, despite ongoing efforts to develop vibration isolators to mitigate the impact of vibrations transmitted to optical equipment, research on drone-specific natural frequencies and payloads has been lacking. Consequently, there is a need for research on vibration isolators tailored to specific drone types and optical equipment payloads. This study focuses on exploring the correlation between the natural frequencies of drones and the weight of the payload, and proposes methods for developing and testing vibration isolators that consider both factors. To achieve this, the study measured the stiffness of vibration isolator rubbers and conducted cross-validation between random vibration tests and finite element method (FEM) analyses to verify the vibration reduction effects resulting from changes in the dynamic characteristics of vibration isolator rubbers. The rubber with a shore hardness of 70 exhibited relatively high damping and damping performance during random vibration tests. Additionally, it showed relatively high stability with only one resonance point measured within the operational frequency band. Through the findings of this study, a methodology for selecting vibration isolators for drones is proposed, aiming to enhance the stability of optical equipment.
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The Internet of Things (IoT) and blockchain are emerging technologies that have attracted attention in many industries, including healthcare, automotive, and supply chain. IoT networks and devices are typically low-powered and susceptible to cyber intrusions. However, blockchains hold considerable potential for securing low-power
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The Internet of Things (IoT) and blockchain are emerging technologies that have attracted attention in many industries, including healthcare, automotive, and supply chain. IoT networks and devices are typically low-powered and susceptible to cyber intrusions. However, blockchains hold considerable potential for securing low-power IoT networks. Blockchain networks provide security features such as encryption, decentralisation, time stamps, and ledger functions. The integration of blockchain and IoT technologies may address many of the security concerns. However, integrating blockchain with IoT raises several issues, including the security vulnerabilities and anomalies of blockchain-based IoT networks. In this paper, we report on our experiments using our blockchain test bed to demonstrate that blockchains on IoT platforms are vulnerable to DDoS attacks, which can also potentially lead to device hardware failures. We show that a number of anomalies are visible during either a DDoS attack or IoT device failure. In particular, the temperature of IoT hardware devices can exceed 90 °C during a DDoS attack, which could lead to hardware failure and potential fire hazards. We also found that the Block Transaction Rate (BTR) and network block loss percentage can increase due to corrupted hardware, with the BTR dropping to nearly zero blocks/sec and a block loss percentage of over 50 percent for all evaluated blockchains, and as high as 81.3 percent in one case. Our experiments demonstrate that anomalous temperature, latency, bandwidth, BTR, and network block loss percentage can potentially be used to identify DDoS attacks.
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