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most exciting work published in the various research areas of the journal.
Abstract: The genus Aeromonas includes well-known pathogenic species for fishes and humans that are widely distributed in the aquatic environment and foods. Nowadays, one of the main issues related to wild Aeromonas isolates is their identification at the species level, which is challenging
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Abstract: The genus Aeromonas includes well-known pathogenic species for fishes and humans that are widely distributed in the aquatic environment and foods. Nowadays, one of the main issues related to wild Aeromonas isolates is their identification at the species level, which is challenging using classical microbiological and biomolecular methods. This study aims to test MALDI-TOF MS technology in the identification of Aeromonas strains isolated from n. 60 retail sushi and sashimi boxes using an implemented version of the SARAMIS software V4.12. A total of 43 certified Aeromonas strains were used to implement the SARAMIS database by importing the spectra obtained from their identification. The original SARAMIS version (V4.12) failed to recognize 62.79% of the certified strains, while the herein-implemented version (V4.12plus) allowed the identification of all the certified strains at least to the genus level with a match of no less than 85%. Regarding the sushi and sashimi samples, Aeromonas spp. was detected in n. 18 (30%) boxes. A total of 127 colonies were identified at the species level, with A. salmonicida detected as the most prevalent species, followed by A. bestiarum and A. caviae. Based on the results of the present study, we could speculate that MALDI-TOF technology could be a useful tool both for the food industry to monitor product contamination and for clinical purposes to make diagnoses effectively and quickly.
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The role of the extracellular matrix (ECM) in Parkinson’s disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA)
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The role of the extracellular matrix (ECM) in Parkinson’s disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA) to document transcriptomic, proteomic, or genomic alterations in PD. PubMed and Google scholar were searched for transcriptomics, proteomics, or genomics studies that employed GSEA on data from PD tissues or cells and reported ECM-related pathways among the top-10 most enriched versus controls. Twenty-seven studies were included, two of which used multiple omics analyses. Transcriptomics and proteomics studies were conducted on a variety of tissue and cell types. Of the 17 transcriptomics studies (16 data sets), 13 identified one or more adhesion pathways in the top-10 deregulated gene sets or pathways, primarily related to cell adhesion and focal adhesion. Among the 8 proteomics studies, 5 identified altered overarching ECM gene sets or pathways among the top 10. Among the 4 genomics studies, 3 identified focal adhesion pathways among the top 10. The findings summarized here suggest that ECM organization/structure and cell adhesion (particularly focal adhesion) are altered in PD and should be the focus of future studies.
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We consider an optimal control problem with the boundary functional for a Schrödinger equation describing the motion of a charged particle. By using the existence of an optimal solution, we search the necessary optimality conditions for the examined control problem. First, we constitute
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We consider an optimal control problem with the boundary functional for a Schrödinger equation describing the motion of a charged particle. By using the existence of an optimal solution, we search the necessary optimality conditions for the examined control problem. First, we constitute an adjoint problem by a Lagrange multiplier that is related to constraints of theory on symmetries and conservation laws. The adjoint problem obtained is a boundary value problem with a nonhomogeneous boundary condition. We prove the existence and uniqueness of the solution of the adjoint problem. Then, we demonstrate the differentiability of the objective functional in the sense of Frechet and get a formula for its gradient. Finally, we give a necessary optimality condition in the form of a variational inequality.
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This study proposes a hybrid pitching motion for oscillating flat plates aimed at augmenting the energy extraction efficiency of an energy harvester. The proposed hybrid pitching motion, within the first half cycle, integrates a non−sinusoidal movement starting at t/T = 0 and progressing
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This study proposes a hybrid pitching motion for oscillating flat plates aimed at augmenting the energy extraction efficiency of an energy harvester. The proposed hybrid pitching motion, within the first half cycle, integrates a non−sinusoidal movement starting at t/T = 0 and progressing to t/T = 0.25, with a sinusoidal movement initiating after t/T > 0.25 and continuing to t/T = 0.5. The second half of the cycle is symmetric to the first half but in the opposite direction. The calculated results show that the proposed hybrid pitching motion outperforms both the sinusoidal and the non−sinusoidal motions. The hybrid pitching motion merges the merits of both the sinusoidal and non−sinusoidal motions to optimize pitch angle variation. This integration is pivotal for enhancing the overall power output performance of an oscillating energy harvester characterized by momentum change that enhances the orientation of the heaving movement, smoother motion transitions, and consistent energy harvesting. The power generation is obtained at wing pitch angles of 55°, 65°, 70°, 75°, and 80° during a hybrid pitching motion. The proposed hybrid pitching motion, set at a pitch angle of 70°, achieves a maximum power output that exceeds the oscillating flat plate using a sinusoidal pitching motion by 16.0% at the same angle.
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The restriction on the use of antibiotics in poultry has led to an increase in the use of natural products that could serve as alternatives to antibiotics. Mushrooms contain bioactive compounds that exhibit antifungal, antiparasitic, antibacterial, antioxidant, antiviral, anti-inflammatory, and cytotoxic properties. Hence,
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The restriction on the use of antibiotics in poultry has led to an increase in the use of natural products that could serve as alternatives to antibiotics. Mushrooms contain bioactive compounds that exhibit antifungal, antiparasitic, antibacterial, antioxidant, antiviral, anti-inflammatory, and cytotoxic properties. Hence, they are being tested, revealing as performance-enhancing natural feed additives for livestock. This review focused on the role of different species of mushrooms commonly used in poultry on the performance, immunomodulatory actions, cholesterolemic properties, and meat quality of poultry birds. Different studies reviewed show that mushrooms could positively impact poultry production, improve growth performance, modulate immune response, exert tissue antioxidant activity, influence intestinal morphology, enhance gut microbiome, and improve lipid profile. The variations in their efficacy could be attributed to the variations in physicochemical properties of different species and dosage levels applied in the experiments. However, the use of mushrooms as a natural product supplement is in its infancy, and more basic, pilot and large-scale research is required to make it a viable approach for improving immune responses in the poultry industry.
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Background: Having an infant in the Neonatal Intensive Care Unit (NICU) can disrupt parent well-being, the transition to parenthood, and the typical trajectories of infant and child health. For lesbian, gay, bisexual, transgender, queer, or other sexual and gender minority identity (LGBTQ+) parents,
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Background: Having an infant in the Neonatal Intensive Care Unit (NICU) can disrupt parent well-being, the transition to parenthood, and the typical trajectories of infant and child health. For lesbian, gay, bisexual, transgender, queer, or other sexual and gender minority identity (LGBTQ+) parents, this stress may be compounded by health disparities and fear of stigma and discrimination; however, research is lacking about LGBTQ+ parents of infants in the NICU. Objectives: The purpose of this integrative review was to better understand the experiences of LGBTQ+ parents of NICU infants, with a focus on experiences of stigma and discrimination, sources of strength and resilience, and provision of family-centered care. Method: We searched EBSCOHost, ProQuest, Web of Science, and Google Scholar between 30 May 2023 and 18 September 2023 for empirical studies published in English in peer-reviewed scholarly journals in which LGBTQ+ parents shared their experiences with having infants admitted to the NICU. Results: We identified six articles that met inclusion criteria, all of which were qualitative studies that included 12–14 LGBTQ+ parents of NICU infants. Conclusions: LGBTQ+ parents in all studies reported instances of perceived stigma and discrimination while their infants were in the NICU, whereas parents in two studies mentioned strength and resilience, and parents in three studies described elements of family-centered care. There is a need for rigorous research on family-centered NICU care that includes questions about sources of strength and resilience in addition to challenges. We propose that future researchers use community engaged methods to center perspectives of LGBTQ+ parents.
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1H fast field-cycling and time-domain nuclear magnetic resonance relaxometry studies have been performed for 15 samples of sugar of different kinds and origins (brown, white, cane, beet sugar). The extensive data set, including results for crystal sugar and sugar/water mixtures, has been
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1H fast field-cycling and time-domain nuclear magnetic resonance relaxometry studies have been performed for 15 samples of sugar of different kinds and origins (brown, white, cane, beet sugar). The extensive data set, including results for crystal sugar and sugar/water mixtures, has been thoroughly analyzed, with a focus on identifying relaxation contributions associated with the solid and liquid fractions of the systems and non-exponentiality of the relaxation processes. It has been observed that 1H spin–lattice relaxation rates for crystal sugar (solid) vary between 0.45 s−1 and 0.59 s−1, and the relaxation process shows only small deviations from exponentiality (a quantitative measure of the exponentiality has been provided). The 1H spin–lattice relaxation process for sugar/water mixtures has turned out to be bi-exponential, with the relaxation rates varying between about 13 s−1–17 s−1 (for the faster component) and about 2.1 s−1–3.5 s−1 (for the slower component), with the ratio between the amplitudes of the relaxation contributions ranging between 2.8 and 4.2. The narrow ranges in which the parameters vary make them a promising marker of the quality and authenticity of sugar.
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Conventional few-shot learning (FSL) mainly focuses on knowledge transfer from a single source dataset to a recognition scenario with only a few training samples available but still similar to the source domain. In this paper, we consider a more practical FSL setting where
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Conventional few-shot learning (FSL) mainly focuses on knowledge transfer from a single source dataset to a recognition scenario with only a few training samples available but still similar to the source domain. In this paper, we consider a more practical FSL setting where multiple semantically different datasets are available to address a wide range of FSL tasks, especially for some recognition scenarios beyond natural images, such as remote sensing and medical imagery. It can be referred to as multi-source cross-domain FSL. To tackle the problem, we propose a two-stage learning scheme, termed learning and adapting multi-source representations (LAMR). In the first stage, we propose a multi-head network to obtain efficient multi-domain representations, where all source domains share the same backbone except for the last parallel projection layers for domain specialization. We train the representations in a multi-task setting where each in-domain classification task is taken by a cosine classifier. In the second stage, considering that instance discrimination and class discrimination are crucial for robust recognition, we propose two contrastive objectives for adapting the pre-trained representations to be task-specialized on the few-shot data. Careful ablation studies verify that LAMR significantly improves representation transferability, showing consistent performance boosts. We also extend LAMR to single-source FSL by introducing a dataset-splitting strategy that equally splits one source dataset into sub-domains. The empirical results show that LAMR can achieve SOTA performance on the BSCD-FSL benchmark and competitive performance on mini-ImageNet, highlighting its versatility and effectiveness for FSL of both natural and specific imaging.
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The seasonal fluctuations of the copepod Eodiaptomus japonicus, which dominates the zooplankton community of Lake Biwa, have been disrupted several times over the past 45 years. The aim of this study was to clarify the primary environmental factor that caused the disrupted
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The seasonal fluctuations of the copepod Eodiaptomus japonicus, which dominates the zooplankton community of Lake Biwa, have been disrupted several times over the past 45 years. The aim of this study was to clarify the primary environmental factor that caused the disrupted seasonal cycle in population density of E. japonicus. Here, we tested the hypothesis that the disruption in their seasonal cycle was due to the impacts of water temperature, food conditions, and predator pressure, using an individual-based model (IBM). Based on the experimental data from the literature, we described the growth and reproduction of E. japonicus using temperature- and food-dependent functions. Previously, the developmental time of this species was expressed using Bělehrádek’s equation. In this study, we applied the Kontodimas equation, which successfully reproduced the effects of food scarcity at higher temperatures. Additionally, the influence of predators was incorporated into the survival rate of adult individuals. The long-term data set of Lake Biwa was input into the developed model to simulate the population fluctuations during the disruption period (1975–1979) and stable period (1995–1999) of their seasonal cycle. The combination of environmental data to be input was (1) water temperature, food availability, and predators; (2) water temperature and food availability; and (3) water temperature and predators. Disruptions in the seasonal cycle of the population were only observed in scenario (1) during the disruption period simulation, suggesting that the disrupted seasonal cycle of this species in Lake Biwa may have been caused by the effects of both food condition and predators. The results of simulation scenarios (2) and (3) indicated that predators have a stronger impact on the population than food availability. This time, we used common and simple indicators to describe food conditions and predators, but the model can be improved to be more complex and accurate as more data become available. Such models are important tools for understanding the relationship between environmental factors and the dynamics of diaptomid copepod populations.
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In the process of tissue engineering, several types of stresses can influence the outcome of tissue regeneration. This outcome can be understood by designing hydrogels that mimic this process and studying how such hydrogel scaffolds and cells behave under a set of stresses.
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In the process of tissue engineering, several types of stresses can influence the outcome of tissue regeneration. This outcome can be understood by designing hydrogels that mimic this process and studying how such hydrogel scaffolds and cells behave under a set of stresses. Here, a hydrogel formulation is proposed to create biomimetic scaffolds suitable for fibroblast cell culture. Subsequently, we examine the impact of external stresses on fibroblast cells cultured on both solid and porous hydrogels. These stresses included mechanical tension and altered-gravity conditions experienced during the 83rd parabolic flight campaign conducted by the European Space Agency. This study shows distinct cellular responses characterized by cell aggregation and redistribution in regions of intensified stress concentration. This paper presents a new biomimetic hydrogel that fulfills tissue-engineering requirements in terms of biocompatibility and mechanical stability. Moreover, it contributes to our comprehension of cellular biomechanics under diverse gravitational conditions, shedding light on the dynamic cellular adaptations versus varying stress environments.
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In Apis mellifera, csd is the primary gene involved in sex determination: haploid hemizygous eggs develop as drones, while females develop from eggs heterozygous for the csd gene. If diploid eggs are homozygous for the csd gene, diploid drones will develop, but
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In Apis mellifera, csd is the primary gene involved in sex determination: haploid hemizygous eggs develop as drones, while females develop from eggs heterozygous for the csd gene. If diploid eggs are homozygous for the csd gene, diploid drones will develop, but will be eaten by worker bees before they are born. Therefore, high csd allelic diversity is a priority for colony survival and breeding. This study aims to investigate the variability of the hypervariable region (HVR) of the csd gene in bees sampled in an apiary under a selection scheme. To this end, an existing dataset of 100 whole-genome sequences was analyzed with a validated pipeline based on de novo assembly of sequences within the HVR region. In total, 102 allelic sequences were reconstructed and translated into amino acid sequences. Among these, 47 different alleles were identified, 44 of which had previously been observed, while 3 are novel alleles. The results show a high variability in the csd region in this breeding population of honeybees.
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Loss of hand functions, often manifesting in the form of weakness or spasticity from conditions like stroke or multiple sclerosis, poses challenges in performing activities of daily living (ADLs). The broad area of rehabilitation robotics provides the tools and knowledge necessary for implementing
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Loss of hand functions, often manifesting in the form of weakness or spasticity from conditions like stroke or multiple sclerosis, poses challenges in performing activities of daily living (ADLs). The broad area of rehabilitation robotics provides the tools and knowledge necessary for implementing efficient restorative therapies. These therapies aim to improve hand functionality with minimal therapist intervention. However, the human hand evolved for various precision and power gripping tasks, with its intricate anatomy featuring a large number of degrees of freedom—up to 31—which hinder its modeling in many rehabilitation scenarios. In the process of designing prosthetic devices, instrumented gloves, and rehabilitation devices, there is a clear need to obtain simplified rehabilitation-oriented hand models without compromising their representativeness across the population. This is where the concept of kinematic reduction, focusing on specific grasps, becomes essential. Thus, the objective of this study is to uncover the intra-finger dependencies during finger flexion/extension by analyzing a comprehensive database containing recorded trajectories for 23 different functional movements related to ADLs, involving 77 test subjects. The initial phase involves data wrangling, followed by correlation analysis aimed at selecting 116 dependency-movement relationships across all grasps. A regularized generalized linear model is then applied to select uncorrelated predictors, while a linear mixed-effect model, with reductions based on both predictor significance and effect size, is used for modeling the dependencies. As a final step, agglomerative clustering of models is performed to further facilitate flexibility in tradeoffs in hand model accuracy/reduction, allowing the modeling of finger flexion extensions using 5–15 degrees of freedom only.
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Abstract: With the rapid growth of the new energy vehicle market, efficient management of the closed-loop supply chain of power batteries has become an important issue. Effective closed-loop supply chain management is very critical, which is related to the efficient utilization of
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Abstract: With the rapid growth of the new energy vehicle market, efficient management of the closed-loop supply chain of power batteries has become an important issue. Effective closed-loop supply chain management is very critical, which is related to the efficient utilization of resources, environmental responsibility, and the realization of economic benefits. In this paper, the Markov Decision Process (MDP) is used to model the decision-making and coordination mechanism of the closed-loop supply chain of power batteries in order to cope with the challenges in the management process, such as cost, quality, and technological progress. By constructing the MDP model for different supply chain participants, this paper investigates the optimization strategy of the supply chain and applies two solution methods: dynamic programming and reinforcement learning. The case study results show that the model can effectively identify optimized supply chain decisions, improve the overall efficiency of the supply chain, and coordinate the interests among parties. The contribution of this study is to provide a new modeling framework for power battery recycling and to demonstrate the practicality and effectiveness of the method with empirical data. This study demonstrates that the Markov decision-making process can be a powerful tool for closed-loop supply chain management, promotes a deeper understanding of the complex decision-making environment of the supply chain, and provides a new solution path for decision-making and coordination in the supply chain.
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Malnutrition remains a critical global health challenge, especially in rural areas, where it significantly impacts the health and economic stability of households. This study explores (1) the relationship between labor migration and dietary protein intake in households remaining in economically disadvantaged rural regions
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Malnutrition remains a critical global health challenge, especially in rural areas, where it significantly impacts the health and economic stability of households. This study explores (1) the relationship between labor migration and dietary protein intake in households remaining in economically disadvantaged rural regions and (2) the influence of remittance income, farm earnings, self-produced food, and changes in family size due to migration on their dietary protein. Panel data were collected through a three-wave household survey of 1368 rural households across six counties in the provinces of Guizhou, Yunnan, and Shaanxi during 2012, 2015, and 2018. Employing a two-way fixed effects model, we found that labor migration positively affects the protein consumption of families left behind. The mediated effects model indicated that decreases in family size had the most significant impact on protein intake, with a value of 8.714, accounting for 0.729 of the total effect; followed by the mediating effect through crop income, at 2.579, representing 0.216 of the total effect; and livestock income, at 0.772, contributing 0.073 of the total effect. However, the mediating effects of remittance income and self-production were found to be insignificant. In conclusion, our study found that migration improves protein intake primarily through increased crop and livestock production and decreased family size. These results highlight the critical role of family structure and farm productivity in enhancing the nutrition of families affected by labor migration, offering valuable insights for policymakers.
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The farmers’ deep participation in the classification of domestic waste plays a crucial role in reducing the amount of waste out of the village from the source, lowering the cost of waste treatment, and realizing the sustainable development of rural waste resocialization, reduction,
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The farmers’ deep participation in the classification of domestic waste plays a crucial role in reducing the amount of waste out of the village from the source, lowering the cost of waste treatment, and realizing the sustainable development of rural waste resocialization, reduction, and harmlessness. This paper aims to identify the key factors and logical structure that influence the farmers’ behavior in classifying domestic waste and provide recommendations for improving it. Based on the Participants’ Intellectual Decision (PID) Model, we constructed a theoretical analysis framework for farmers’ decision-making on domestic waste classification, and the PID model was further extended by combining with the practice of rural domestic waste management in China and proposing the research hypothesis that factors, such as community attributes, rules of operation, the status of the participants, and the situation of external actions, have a significant impact on the farmers’ behavior in classifying domestic waste. Empirical analyses were carried out with the help of the ordered logistic model and the DEMATEL-ISM using 939 research data of farmers in Jiangsu and Gansu provinces of China. The results show the following: (1) classification of domestic waste by farmers in the sample area was predominantly unclassified (34.40%) and two-classified (40.58%); (2) 17 factors, including regional disparity, Party affiliation, organizational support perception, environmental emotions, conscious governance attitudes, trust in village cadres, social reference norms, and expected outcomes, have a significant impact on the farmers’ behavior in classifying domestic waste; (3) trust in village cadres, organizational support perception, and environmental emotion are superficial direct factors; incentive measures, fee level, waste transport situation, difficulty perception, self-consciousness perception, social reference norms, and expected outcomes are middle indirect factors; whether or not it is a demonstration village, Party membership and regional disparity are deep root factors affecting farmers to classify their domestic waste.
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This article explores novel in-orbit drag-free technology that can be utilized for deep space detection scientific missions. In this study, we considered a two-test-mass drag-free method and analyzed the design of the drag-free and attitude control system for the TianQin mission. The entire
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This article explores novel in-orbit drag-free technology that can be utilized for deep space detection scientific missions. In this study, we considered a two-test-mass drag-free method and analyzed the design of the drag-free and attitude control system for the TianQin mission. The entire control system was comprehensively designed, including an actuator allocation design and controllers for two test masses and one spacecraft, with a total of 18 degrees of freedom. Furthermore, stability analysis was conducted. Based on our design, numerical analysis and simulations were performed assuming geocentric orbit conditions in the TianQin mission, confirming the feasibility of this aerospace engineering concept. The versatility of the design allows for its application to scientific observations across various disciplines by modifying the structure of the simulation environment, and consequently, the approach discussed in this study holds significant practical implications for effectively accomplishing deep space observation tasks.
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To provide diverse in-home services like elderly care, versatile activity recognition technology is essential. Radio-based methods, including WiFi CSI, RFID, and backscatter communication, are preferred due to their minimal privacy intrusion, reduced physical burden, and low maintenance costs. However, these methods face challenges,
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To provide diverse in-home services like elderly care, versatile activity recognition technology is essential. Radio-based methods, including WiFi CSI, RFID, and backscatter communication, are preferred due to their minimal privacy intrusion, reduced physical burden, and low maintenance costs. However, these methods face challenges, including environmental dependence, proximity limitations between the device and the user, and untested accuracy amidst various radio obstacles such as furniture, appliances, walls, and other radio waves. In this paper, we propose a frequency-shift backscatter tag-based in-home activity recognition method and test its feasibility in a near-real residential setting. Consisting of simple components such as antennas and switches, these tags facilitate ultra-low power consumption and demonstrate robustness against environmental noise because a context corresponding to a tag can be obtained by only observing frequency shifts. We implemented a sensing system consisting of SD-WiFi, a software-defined WiFi AP, and physical switches on backscatter tags tailored for detecting the movements of daily objects. Our experiments demonstrate that frequency shifts by tags can be detected within a 2 m range with 72% accuracy under the line of sight (LoS) conditions and achieve a 96.0% accuracy (F-score) in recognizing seven typical daily living activities with an appropriate receiver/transmitter layout. Furthermore, in an additional experiment, we confirmed that increasing the number of overlaying packets enables frequency shift-detection even without LoS at distances of 3–5 m.
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Access and exposure to urban green space—the combination of parks and vegetative cover in cities—are associated with various health benefits. As urban green space is often unequally distributed throughout cities, understanding how it is allocated across socio-demographic populations can help city planners and
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Access and exposure to urban green space—the combination of parks and vegetative cover in cities—are associated with various health benefits. As urban green space is often unequally distributed throughout cities, understanding how it is allocated across socio-demographic populations can help city planners and policy makers identify and address urban environmental justice and health equity issues. To our knowledge, no studies have yet combined assessments of park quality, park availability, and green cover to inform equitable urban green space planning. To this end, we developed a comprehensive methodology to identify urban green space inequities at the city scale and applied it in Portland, OR, USA. After auditing all public parks in Portland and gathering green cover data from publicly accessible repositories, we used a suite of statistical tests to evaluate distribution of parks and green cover across Census block groups, comprising race, ethnicity, income, and educational attainment characteristics. Right-of-way tree canopy cover was the most significant urban green space inequity identified in bivariate analysis (rs = −0.73). Spatial autoregressive models identified that right-of-way, private, and overall tree canopy cover (Nagelkerke pseudo-R2 = 0.66, 0.77, and 0.67, respectively) significantly decreased with the proportion of minoritized racial population and increased with median income. The results were then used to identify priority locations for specific urban green space investments. This research establishes a process to assess intra-urban green space inequities, as well as identify data-informed and spatially explicit planning priorities to promote health equity and environmental justice.
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Invasive alien species (IAS) significantly affect global native biodiversity, agriculture, industry, and human health. Carpomya vesuviana Costa, 1854 (Diptera: Tephritidae), a significant global IAS, affects various date species, leading to substantial economic losses and adverse effects on human health and the environment. This
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Invasive alien species (IAS) significantly affect global native biodiversity, agriculture, industry, and human health. Carpomya vesuviana Costa, 1854 (Diptera: Tephritidae), a significant global IAS, affects various date species, leading to substantial economic losses and adverse effects on human health and the environment. This study employed biomod2 ensemble models, multivariate environmental similarity surface and most dissimilar variable analyses, and ecological niche dynamics based on environmental and species data to predict the potential distribution of C. vesuviana and explore the environmental variables affecting observed patterns and impacts. Compared to native ranges, ecological niche shifts at invaded sites increased the invasion risk of C. vesuviana globally. The potential geographical distribution was primarily in Asia, Africa, and Australia, with a gradual increase in suitability with time and radiation levels. The potential geographic distribution centre of C. vesuviana is likely to shift poleward between the present and the 2090s. We also show that precipitation is a key factor influencing the likely future distribution of this species. In conclusion, climate change has facilitated the expansion of the geographic range and ecological niche of C. vesuviana, requiring effective transnational management strategies to mitigate its impacts on the natural environment and public health during the Anthropocene. This study aims to assess the potential threat of C. vesuviana to date palms globally through quantitative analytical methods. By modelling and analysing its potential geographic distribution, ecological niche, and environmental similarities, this paper predicts the pest’s dispersal potential and possible transfer trends in geographic centres of mass in order to provide prevention and control strategies for the global date palm industry.
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The Neoproterozoic (>1160 to ~540 Ma) sedimentary record of the Tandilia System is reorganized into eight depositional sequences based on a detailed review of published sources and new lithological observations. The main compositional attributes compiled from the studied units were used to indicate
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The Neoproterozoic (>1160 to ~540 Ma) sedimentary record of the Tandilia System is reorganized into eight depositional sequences based on a detailed review of published sources and new lithological observations. The main compositional attributes compiled from the studied units were used to indicate changes in lithology regarding their origin. Epiclastic sections reveal supply and sources changes through the succession. Basement detritus was dominant during the deposition of the basal sequences turning drastically to a volcanic affinity dominance. The carbonate sections, dominated by intra-basinal components, were deposited in periods of rare or restricted detrital input. The older, described as a cap-dolostone, was related to bio-induced dolomite precipitation under a deglacial to interglacial context. The younger, a carbonate ramp, reveals to have been built by microbial activity adding high levels of oxygen to seawater correlated to a global oxygenation event. Compositional changes recorded in the shallow marine deposits of Tandilia could have been intricately linked to periods of tectonic and paleo-relief configurations, favoring the detrital supply into the basin, followed by relevant episodic biogeochemical changes. This study shows that the basinal-components progression was controlled by paleoclimate and paleoenvironments associated to the extensive interval between the rupture of the Rodinia to Gondwana paleogeographical framework.
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This paper develops a methodology to accommodate uncertainty in a GARCH model with the goal of improving portfolio decisions via Bayesian learning. Given the abundant evidence of uncertainty in estimating expected returns, we focus our analyses on the single parameter driving expected returns.
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This paper develops a methodology to accommodate uncertainty in a GARCH model with the goal of improving portfolio decisions via Bayesian learning. Given the abundant evidence of uncertainty in estimating expected returns, we focus our analyses on the single parameter driving expected returns. After deriving an Uncertainty-Implied GARCH (UI-GARCH) model, we investigate how learning about uncertainty affects investments in a dynamic portfolio optimization problem. We consider an investor with constant relative risk aversion (CRRA) utility who wants to maximize her expected utility from terminal wealth under an Affine GARCH(1,1) model. The corresponding stock evolution, and therefore, the wealth process, is treated as a Bayesian information model that learns about the expected return with each period. We explore the one- and two-period cases, demonstrating a significant impact of uncertainty on optimal allocation and wealth-equivalent losses, particularly in the case of a small sample size or large standard errors in the parameter estimation. These analyses are conducted under well-documented parametric choices. The methodology can be adapted to other GARCH models and applications beyond portfolio optimization.
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Jordan faces significant, immediate challenges of enhancing energy security while mitigating greenhouse gas emissions. One of the most promising approaches to achieve sustainable development, energy security, and environmental conservation is to increase the integration of renewable energy into electricity generation. To this end,
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Jordan faces significant, immediate challenges of enhancing energy security while mitigating greenhouse gas emissions. One of the most promising approaches to achieve sustainable development, energy security, and environmental conservation is to increase the integration of renewable energy into electricity generation. To this end, the Jordanian government aims to expand investments in the green energy sector, with solar and wind energy expected to play a crucial role in meeting energy demands and promoting environmental sustainability. This paper aims to examine the distinct dynamics, challenges, obstacles, and potential solutions related to establishing community solar and wind farms in suburban areas of Jordan. It seeks to highlight the opportunities and barriers influencing the adoption of sustainable energy in the country. Evaluation results from engaging 320 key stakeholders were obtained through a questionnaire, and after comprehensive analysis, it became evident that the benefits and positive aspects of solar and wind farms outweigh their drawbacks and obstacles. These insights can be useful in guiding policies and practices to make renewable energy community projects a reality within Jordan’s suburban areas. Additionally, the findings may serve as a valuable benchmark for other regions facing similar challenges in their pursuit of a sustainable energy future.
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Skin aging is an unavoidable natural phenomenon caused by intrinsic and extrinsic factors. In modern society, the pursuit of a wrinkle-free and aesthetically appealing face has gained considerable prominence. Numerous studies have aimed at mitigating the appearance of facial wrinkles. Antiaging research focused
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Skin aging is an unavoidable natural phenomenon caused by intrinsic and extrinsic factors. In modern society, the pursuit of a wrinkle-free and aesthetically appealing face has gained considerable prominence. Numerous studies have aimed at mitigating the appearance of facial wrinkles. Antiaging research focused on regulating the function of mitochondria, the main reactive oxygen species-generating organelles, has been extensively conducted. In this study, we investigated the correlation between facial wrinkles and the expression of PPARGC1B, considering the association of this gene with mitochondrial function, to identify its potential as a target for exploring antiaging cosmetic materials. We elucidated the role of PPARGC1B in the skin and identified five bioactive materials that modulated its expression. The effectiveness of these materials was verified through in vitro experiments on human dermal fibroblasts. We prepared cosmetic formulations incorporating the five materials and confirmed their ability to enhance dermal collagen in three-dimensional skin models and reduce facial wrinkles under the eyes and nasolabial fold areas in human subjects. The study findings have significant implications for developing novel antiaging cosmetic formulations by reinforcing mitochondrial functions.
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