Transport Domain Research Articles

Molecular architecture of human LYCHOS involved in lysosomal cholesterol signaling.

Lysosomal membrane protein LYCHOS (lysosomal cholesterol signaling) translates cholesterol abundance to mammalian target of rapamycin activation. Here we report the 2.11-Å structure of human LYCHOS, revealing a unique fusion architecture comprising a G-protein-coupled receptor (GPCR)-like domain and a transporter domain that mediates homodimer assembly. The NhaA-fold transporter harbors a previously uncharacterized intramembrane Na+ pocket. The GPCR-like domain is stabilized, by analogy to canonical GPCRs, in an inactive state through 'tethered antagonism' by a lumenal loop and strong interactions at the cytosol side preventing the hallmark swing of the sixth transmembrane helix seen in active GPCRs. A cholesterol molecule and an associated docosahexaenoic acid (DHA)-phospholipid are entrapped between the transporter and GPCR-like domains, with the DHA-phospholipid occupying a pocket previously implicated in cholesterol sensing, indicating inter-domain coupling via dynamic lipid-protein interactions. Our work provides a high-resolution framework for functional investigations of the understudied LYCHOS protein.

Resolution and resistance: what shaped New Zealand’s climate change policies under the sixth Labour government?

ABSTRACT The sixth Labour government under Jacinda Ardern placed climate change at the centre of their agenda, referring to it as the ‘greatest challenge facing the world’. Definite progress was made on climate policy during the government’s tenure, particularly with the flagship Zero Carbon Act. Overall, however, policy changes were not transformative, and few policies were enacted that will substantially decrease emissions. This article sheds light on this gap between the sixth Labour government’s resolution to tackle climate change and the reality of actual policy outputs. We ask: what are the main factors that shaped climate policy outputs under the sixth Labour government? Using process tracing, we examine the ‘digital wake’ of key debates in three climate policy domains of energy, transport and agriculture. Using publicly available documents to investigate policies pursued by the government between 2018 and 2022, we find that industry resistance (particularly from the farming sector), coalition dynamics and public opinion all hindered progress. However, the government was not always fully committed to climate action,g particularly on reducing agricultural emissions. The difficulties experienced by the sixth Labour government in achieving their climate ambitions illustrate the strong political headwinds that impede delivery of substantive climate change mitigation in New Zealand.

PHYSICS BASED ALGORITHMS FOR FUZZY TRANSPORTATION PROBLEM

Transportation problems are computationally challenging due to their nondeterministic polynomial-time hard (NP-hard) nature, especially when uncertainties in costs, supply, and demand are involved. The fuzzy transportation problem addresses these uncertainties by representing them as fuzzy numbers, requiring robust methods for ranking and solving optimization models. Traditional exact methods become impractical for such problems, leading to the adoption of metaheuristic approaches. This study introduces three novel physics-based algorithms: one single-point-based and two population-based methods. These algorithms leverage principles from gravitational attraction, electromagnetism, and water flow dynamics, incorporating innovative neighborhood structures tailored to the fuzzy nature of transportation problems. The proposed methods were tested on diverse problem sizes and compared against established optimization techniques, such as genetic algorithms and commercial software, using Python implementations. An experimental design methodology was employed to optimize parameter tuning, enhancing computational efficiency and reducing experimentation time. Results demonstrate that the physics-based algorithms achieve competitive performance in terms of solution quality, computational efficiency, and adaptability to uncertainty. These findings underscore the potential of physics-based methods to advance optimization in fuzzy transportation and other domains with inherent uncertainties, paving the way for further research in hybrid and multi-objective approaches.

Photon localization transition in a magnetorheological fluid

We investigate photon transport in magnetically tunable fluids, specifically magnetic nanofluids and magnetorheological fluids (MRFs). Our study focuses on the statistical analysis of light transport in these fluids, with a particular focus on earlier theoretical proposals related to the possibility of Anderson localization in these systems. We employ a well-known mesoscopic quantifier, the generalized conductance, to assess the domain of light transport in these systems. Magnetic nanofluids, which contain nanometer-sized magnetite particles, exhibit weak scattering with no substantial consequence on conductance, regardless of the applied magnetic field. In contrast, magnetorheological fluids, a bidispersion of micrometer-sized magnetizable spheres in a magnetic nanofluid, show a decrease in conductance to values below unity as the magnetic field strength increases. This decrease occurs at the magnetic-field-induced photonic bandgap in MRFs, which plays a crucial role in the localization process and is characterized by reduced transmitted intensity, altered speckle patterns, and significant changes in intensity statistics. Our findings also highlight the temporal evolution of field-induced speckles, where the initial high correlation decreases over time, and the correlation width widens indicating that the duration of sustained correlation enhances as the system reaches equilibrium. Consequently, the evolution of field-induced scatterers in MRFs significantly emulates light localization effects as the system attains equilibrium. This study concludes that our system is a prime candidate to observe possible strong localization in a magnetically tunable, dissipative complex system. Such systems hold potential applications in optical switching, adaptive optics, and smart materials design through controlled light manipulation using external magnetic fields.

Substrate-Induced Structural Dynamics and Evolutionary Linkage of Siderophore-Iron ABC Transporters of Mycobacterium tuberculosis.

Background and Objective: ATP-binding cassette (ABC) transporters are prominent drug targets due to their highly efficient trafficking capabilities and their significant physiological and clinical roles. Gaining insight into their biophysical and biomechanistic properties is crucial to maximize their pharmacological potential. Materials and Methods: In this study, we present the biochemical and biophysical characterization, and phylogenetic analysis of the domains of Mycobacterium tuberculosis (M. tuberculosis) ABC transporters: the exporter Rv1348 (IrtA) and the importer system Rv1349-Rv2895c (IrtB-Rv2895c), both involved in siderophore-mediated iron uptake. Results: Our findings reveal that the substrate-binding domain (SBD) of IrtA functions as an active monomer, while Rv2895c, which facilitates the uptake of siderophore-bound iron, exists in a dynamic equilibrium between dimeric and monomeric forms. Furthermore, ATP binding induces the dimerization of the ATPase domains in both IrtA (ATPase I) and IrtB (ATPaseII), but only the ATPase domain of IrtA (ATPase I) is active independently. We also analyzed the stability of substrate binding to the domains of the two transporters across varying temperature and pH ranges, revealing significant shifts in their activity under different conditions. Our study highlights the conformational changes that accompany substrate interaction with the transporter domains, providing insights into the fundamental mechanism required for the translocation of siderophore to the extracytoplasmic milieu by IrtB and, subsequently, import of their ferrated forms by the IrtB-Rv2895c complex. Phylogenetic analyses based on ATPase domains reveal that IrtA shares features with both archaeal and eukaryotic transporters, while IrtB is unique to mycobacterial species. Conclusions: Together, these findings provide valuable insights, which could accelerate the development of intervention strategies for this critical pathway pivotal in the progression of M. tuberculosis infection.

Advances in machine learning methods in copper alloys: a review.

Advanced copper and copper alloys, as significant engineering structural materials, have recently been extensively used in energy, electron, transportation, and aviation domains. Higher requirements urge the emergence of high-performance copper alloys. However, the traditional trial-and-error experimental observations and computational simulation research used to design and develop novel materials are time-consuming and costly. With the accumulation of material research and rapid development of computational ability, the thorough application of material genome engineering has sped up the development of novel materials and facilitates the process of systematic engineering application. This review summarizes the benefits of data-driven machine learning techniques and the state of the art of machine learning research in the area of copper alloys. It also displays the widely used computational simulation approaches (e.g., the first-principles calculation, molecular dynamics simulation, phase-field simulations, and finite element analysis) and their combined applications in material design and property prediction. Finally, the limitations of machine learning research methods are outlined, and future development directions are proposed.

Molecular insights into substrate translocation in an elevator-type metal transporter

The Zrt/Irt-like protein (ZIP) metal transporters are key players in maintaining the homeostasis of a panel of essential microelements. The prototypical ZIP from Bordetella bronchiseptica (BbZIP) is an elevator transporter, but how the metal substrate moves along the transport pathway and how the transporter changes conformation to allow alternating access remain to be elucidated. Here, we combine structural, biochemical, and computational approaches to investigate the process of metal substrate translocation along with the global structural rearrangement. Our study reveals an upward hinge motion of the transport domain in a high-resolution crystal structure of a cross-linked variant, elucidates the mechanisms of metal release from the transport site into the cytoplasm and activity regulation by a cytoplasmic metal-binding loop, and unravels an unusual elevator mode in enhanced sampling simulations that distinguishes BbZIP from other elevator transporters. This work provides important insights into the metal transport mechanism of the ZIP family.

Study of Access Control Techniques on the Blockchain-enabled Secure Data Sharing Scheme in Edge Computing

Background: The pervasive adoption of edge computing is reshaping real-time big data analysis, smart city management, intelligent transportation, and various other domains. Its appeal lies in its distributed nature, decentralization, low latency, mobile support, and spatial awareness. However, this ubiquity exposes data to security threats, jeopardizing privacy and integrity. Consequently, access control assumes paramount importance in securing data sharing within edge computing and blockchain technologies. Methods: This research addresses this critical issue by conducting a comprehensive study on access control techniques within the context of edge computing and blockchain for secure data sharing. Our methodology commences with an exhaustive review of relevant articles, aiming to identify and expound upon gaps in existing research. Subsequently, we perform a meticulous analysis of access control methods, mechanisms, and performance metrics, seeking to establish a holistic understanding of the landscape. Results: The culmination of this research effort is a multifaceted contribution. We distill insights from a diverse range of access control schemes, shedding light on their nuances and effectiveness. Our analysis extends to evaluating the performance metrics vital for ensuring robust access control. Through this research, we also pinpoint critical research gaps within traditional access control methods, creating a foundation for innovative approaches to address the evolving challenges within edge computing and blockchain environments. Conclusion: In conclusion, this research venture paves the way for secure data sharing in edge computing and blockchain by offering a thorough examination of access control. The findings from this study are anticipated to guide future developments in access control techniques and facilitate the evolution of secure, privacy-conscious, and efficient data sharing practices in the dynamic landscape of digital technology.

Integrating Radial Basis Networks and Deep Learning for Transportation

Introduction This research focuses on the concept of integrating Radial Basis Function Networks with deep learning models to solve robust regression tasks in both transportation and logistics. Methods It examines such combined models as RNNs with RBFNs, Attention Mechanisms with Radial Basis Function Networks (RBFNs), and Capsule Networks with RBFNs and clearly shows that, in all cases, compared to the others, the former model has a Mean Squared Error (MSE) of 0.010 to 0.013, Mean Absolute Error (MAE) – 0.078 to 0.088, and R-squared (R2) – 0.928 to 0.945, across ten experiments. In the case of Attention Mechanisms with RBFNs, the models also demonstrate strong performance in terms of making predictions. The MSE ranges from 0.012 to 0.015, the MAE from 0.086 to 0.095, and the R2 from 0.914 to 0.933. Results However, it is critical to note that the Capsule Networks with RBFNs outperform other models. In particular, they offer the lowest MSE, which is between 0.009 and 0.012, the smallest MAE, which ranges from 0.075 to 0.083, and the highest R2, from 0.935 to 0.950. Conclusion Overall, the results indicate that the use of RBFNs in combination with different types of deep learning networks can provide highly accurate and reliable solutions for regression problems in the domain of transportation and logistics.

Barriers to a sustainable living in Italy: results of a national survey

Abstract Background Sustainable living plays a crucial role in creating a fairer society, but various constraints prevent consumers from adopting sustainable behaviours. This study investigated the reasons for non-adoption of sustainable products or behaviours among the Italian population. Methods From January to June 2023, we surveyed the Italian population using a 40-question online survey that asked about knowledge, awareness, and attitudes toward sustainable behaviours and products. Participants were asked about the reasons why they did not engage in a certain behaviour or did not use a selected product. Descriptive statistics, t-test and chi-square tests were performed to assess association with participant characteristics. Results The 420 participants had a median age of 39 years (interquartile range: 32-56), 66% were female. The largest discrepancy between knowledge of sustainability impacts and implementation was in the personal care (92% knowledge, 31% implementation) and transportation (85% knowledge, 48% implementation) domains. In general, the main reasons for not using the surveyed products were practical complications in everyday life (25%), the difficulty of finding or producing them (23%) and their cost (13%). Specifically, practical complications (42%) were the main reason for not adopting sustainable behaviours in the transport domain. In the personal care domain, low confidence in product quality or ignorance of their existence accounted for only 26% of reasons for non-use, while supply problems, practical complications in everyday life and existence unawareness accounted for 61%. Conclusions Targeted measures are needed to address the reasons for non-use or adoption of sustainable products and behaviours. In this way, these actions will help to promote healthy living, protect our planet, support socio-economic development, and ensure global prosperity. Key messages • A greater sustainability- implementation awareness gap was found in personal care and transportation domains. • The main reasons for not implementing sustainable living were practical complications in daily life, supply difficulties and product cost.

Structural resilience disparities in regional city networks under the influence of Typhoon Fitow and COVID-19

The integration of regional city networks plays a pivotal role in the regional development. Assessing and analyzing the structural resilience of these networks holds significance in enhancing regional comprehensive disaster prevention. This study focuses on the Yangtze River Delta, examining its regional city networks encompassing information, economic, transportation, and innovation domains. Utilizing the social network analysis, projection pursuit model based on the genetic algorithm, coupling coordination degree model, coefficient of variation and spatial Gini coefficient, we scrutinized the structural resilience and evolution difference of these networks under different disasters. We found that the structural resilience of economic and transportation networks that depend on infrastructure construction are more limited by geographical distance, and information and innovation networks with weaker physical dependence have stronger structural resilience. The impact of Typhoon Fitow on the structural resilience of individual networks was mainly concentrated in coastal affected cities, while the impact after COVID-19 was mainly in marginal cities. The spatial pattern of the structural resilience of multiple networks shifted from low level equilibrium to agglomeration development. Finally, nodes were identified into three types according to the resilience performance. This research offers a scientific foundation for quantifying regional resilience and formulating network optimization strategies.

LYCHOS is a human hybrid of a plant-like PIN transporter and a GPCR

Lysosomes have crucial roles in regulating eukaryotic metabolism and cell growth by acting as signalling platforms to sense and respond to changes in nutrient and energy availability1. LYCHOS (GPR155) is a lysosomal transmembrane protein that functions as a cholesterol sensor, facilitating the cholesterol-dependent activation of the master protein kinase mechanistic target of rapamycin complex 1 (mTORC1)2. However, the structural basis of LYCHOS assembly and activity remains unclear. Here we determine several high-resolution cryo-electron microscopy structures of human LYCHOS, revealing a homodimeric transmembrane assembly of a transporter-like domain fused to a G-protein-coupled receptor (GPCR) domain. The class B2-like GPCR domain is captured in the apo state and packs against the surface of the transporter-like domain, providing an unusual example of a GPCR as a domain in a larger transmembrane assembly. Cholesterol sensing is mediated by a conserved cholesterol-binding motif, positioned between the GPCR and transporter domains. We reveal that the LYCHOS transporter-like domain is an orthologue of the plant PIN-FORMED (PIN) auxin transporter family, and has greater structural similarity to plant auxin transporters than to known human transporters. Activity assays support a model in which the LYCHOS transporter and GPCR domains coordinate to sense cholesterol and regulate mTORC1 activation.

Growing Digital Divide for Expatriates Population in China: A User Perspective Analysis During the COVID-19 Pandemic

The COVID-19 pandemic has influenced many movements of rapid digitization in several sectors/areas used by the public. The three primary sectors/areas affected by such digitization process are identified as healthcare, transportation, and public domain registration. There are only a few studies investigating the impacts of the COVID-19 pandemic on the digital divide for the expatriate population. To fill this research gap, this study investigates these three primary sectors/areas while highlighting the growing digital divide in the expatriate population, using Chinese cities as case studies. The study finds that the emerging barrier is beyond language barriers related to digital access and utilization issues. The study finds that the ongoing digital inequality is related to the autonomy of use, suggesting the urgency for technological upgrades, inclusive digital platforms, and reversing digital design marginalization. This study is sample-based research, using limited samples of expatriate populations in nine major cities in three primary economic clusters in China. The user perspective is assessed against five digital inequalities, namely “technical means,” “autonomy of use,” “social support networks,” “experience,” and “skills.” The analysis is followed by further research on digital divide barriers, addressing how the newly installed digital devices/facilities/services affect the expatriate population beyond the traditional language barriers. The analysis evaluates challenges based on four DDB pillars (i.e., availability, access, renovation, and utilization) and language barrier. The findings show the high correlation between the autonomy of use and digital utilization has led to further disparities and disconnection of the expatriate population from the smart city movements, such as digitized healthcare, transportation, and public domain registration. This study contributes to digital divide research, enhancing awareness of such research related to technological/digital changes and the expatriate populations.

Transport properties of canonical PIN-FORMED proteins from Arabidopsis and the role of the loop domain in auxin transport.

The phytohormone auxin is polarly transported in plants by PIN-FORMED (PIN) transporters and controls virtually all growth and developmental processes. Canonical PINs possess a long, largely disordered cytosolic loop. Auxin transport by canonical PINs is activated by loop phosphorylation by certain kinases. The structure of the PIN transmembrane domains was recently determined, their transport properties remained poorly characterized, and the role of the loop in the transport process was unclear. Here, we determined the quantitative kinetic parameters of auxin transport mediated by Arabidopsis PINs to mathematically model auxin distribution in roots and to test these predictions invivo. Using chimeras between transmembrane and loop domains of different PINs, we demonstrate a strong correlation between transport parameters and physiological output, indicating that the loop domain is not only required to activate PIN-mediated auxin transport, but it has an additional role in the transport process by a currently unknown mechanism.

Prevalencia y factores asociados con los comportamientos sedentarios y la actividad física en escolares de básica primaria

The school and its curricular proposals promote prolonged sedentary behavior, fostering a sedentary behavioral culture that is reinforced extracurricularly, possibly affecting the health of schoolchildren. However, the Physical Education class, and particularly the promotion of school physical activity within it, is one of the most important strategies to mitigate the harmful effects of sedentary behaviors in children. Therefore, the main objective was to establish the prevalence and factors associated with sedentary behaviors in elementary school students. The results reveal that in the school transportation domain, there is an average prevalence of 114 minutes per week of sedentary behavior. In the school environment, walking is common, but sitting time has a weekly average of 1680 ± 102 minutes. Meanwhile, in the home domain, women show higher participation in physical activity. This study highlights the need for school interventions to promote active and healthy habits in childhood.

Molecular insights into substrate translocation in an elevator-type metal transporter.

The Zrt/Irt-like protein (ZIP) metal transporters are key players in maintaining the homeostasis of a panel of essential microelements. The prototypical ZIP from Bordetella bronchiseptica (BbZIP) is an elevator transporter, but how the metal substrate moves along the transport pathway and how the transporter changes conformation to allow alternating access remain to be elucidated. Here, we combined structural, biochemical, and computational approaches to investigate the process of metal substrate translocation along with the global structural rearrangement. Our study revealed an upward hinge motion of the transport domain in a high-resolution crystal structure of a cross-linked variant, elucidated the mechanisms of metal release from the transport site into the cytoplasm and activity regulation by a cytoplasmic metal-binding loop, and unraveled an unusual elevator mode in enhanced sampling simulations that distinguishes BbZIP from other elevator transporters. This work provides important insights into the metal transport mechanism of the ZIP family.

Selection of drive system and chassis structure basic design and analysis for medium-sized urban electric bus

One of the alternative solutions to address environmental and energy challenges is the utilization of electric vehicles, particularly in the domain of public transportation. The focus was on the development of medium-sized electric buses to expand the reach of electric-powered public transport. The design process encompasses the selection of vehicle components, such as the drive system, and the configuration of a space frame chassis structure. The drive system was meticulously chosen and proved to exceed the design requirements, as it achieved a gradability of 12.44%, surpassing the targeted capability of 10% slope. Moreover, it boasts a maximum speed of 108 km/h, exceeding the design requirement of a maximum speed of 50 km/h, and can accelerate at a rate of 1-2 m/s². The chassis design adheres to regulations and standards and is grounded in the strength, stiffness, and natural frequency criteria. The initial chassis design did not meet the design requirement, however, through several iterations, a chassis structure was achieved with a vertical bending stiffness of 8.57 kN/mm and a torsional stiffness of 9.63 kNm/°. Based on the outcomes of this research, a drive system and chassis structure design that fully satisfies all the existing design requirements has been successfully attained.

Interdomain-linkers control conformational transitions in the SLC23 elevator transporter UraA

Uptake of nucleobases and ascorbate is an essential process in all living organisms mediated by SLC23 transport proteins. These transmembrane carriers operate via the elevator alternating-access mechanism, and are composed of two rigid domains whose relative motion drives transport. The lack of large conformational changes within these domains suggests that the interdomain-linkers act as flexible tethers. Here, we show that interdomain-linkers are not mere tethers, but have a key regulatory role in dictating the conformational space of the transporter and defining the rotation axis of the mobile transport domain. By resolving a wide inward-open conformation of the SLC23 elevator transporter UraA and combining biochemical studies using a synthetic nanobody as conformational probe with hydrogen-deuterium exchange mass spectrometry, we demonstrate that interdomain-linkers control the function of transport proteins by influencing substrate affinity and transport rate. These findings open the possibility to allosterically modulate the activity of elevator proteins by targeting their linkers.

Toward Linux-based safety-critical systems—Execution time variability analysis of Linux system calls

Modern transportation and industrial domain safety-critical applications, such as autonomous vehicles and collaborative robots, exhibit a combination of escalating software complexity and the need to integrate diverse software stacks and machine learning algorithms, consequently demanding complex high-performance hardware. Linux’s extensive platform support and library ecosystem make it a valuable general-purpose operating system for developing complex software systems. However, because the Linux kernel has not been designed to comply with safety standards, it has a high execution path variability and does not provide execution time guarantees. In this context, several research initiatives have studied the usage of Linux for developing complex safety-related systems, focusing on topics that include its development process, isolation architectures, or test coverage estimation. Nonetheless, execution-time analysis and providing temporal guarantees is still a challenge. This work extends the novel statistical analysis of Linux system call execution paths with the analysis of execution-time variability and proposes a method for estimating the worst-case execution time, forming a sound approach for an in-depth analysis of the Linux kernel execution paths and execution times for safety-related systems. The proposed method is applied to a representative use case that implements an Autonomous Emergency Brake application in an NVIDIA Jetson Nano board connected to the CARLA autonomous driving simulator.

Critical Success Factors of Electric Mobility Transition in Indonesia: A DEMATEL-Based ANP Approach

The high index of poor air quality and the increasing demand for oil fuel pose severe problems for Indonesia. The largest sector contributing to both of these issues is the transportation sector. Electric mobility offers a notable opportunity for decreasing carbon emissions within the transportation domain. Despite the Indonesian government's notable backing of this initiative, the implementation has been slow. Therefore, this study aims to identify the critical factors necessary for a successful transition to electric mobility. This study identifies the factors influencing the transition to e-mobility in the initial stage. Subsequently, these factors are validated and assessed by a panel of nine experts. In the validation phase, data processing involves the use of the Content Validity Index (CVI) and Modified Kappa methods. To assess relationships and prioritize essential success factors, the Decision-making Trial and Evaluation Laboratory-based Analytic Network Process (DEMATEL-based ANP) is applied. This study identifies six dimensions and 24 critical success factors. The political dimension emerges as the most significant, with the top five priorities being government funding, charging infrastructure, value proposition, fuel price, and charging time. The findings can be used to provide recommendations to the government or relevant stakeholders in supporting the shift to electric mobility in Indonesia.