Rural areas characterized by resource-dependent industries often experience growth but also lock-in and transformation pressures. We ask what strategies industries and businesses pursue that successfully exploit the transformative potential of such a location and what prevents other industries and businesses from doing the same. Based on interviews with stakeholders and experts from the livestock and meat sector in a highly specialized location, we explore the will, resources, and capabilities of industries and actors to transform their businesses and entire value chains in ways that can stabilize the local growth regime. The analysis is based on a conceptual framework derived from resource-based and dynamic capability theories at the micro level and the concept of Strategic Action Fields (SAFs) at the meso level. The results suggest that incumbents from the old industrial core tend to counteract the transformation of the SAF with conservative strategies. Challengers from former support activities, in contrast, want to move away from cost competition towards new markets. Their product variation and horizontal diversification can exploit favorable cluster characteristics to develop future-proof capabilities. This should be encouraged, along with new entrepreneurial activity, even if the region is then no longer hosting the core industries of the transformed field.
A summary, based upon foresight, futures, ideation and frontier technology studies of prospective approaches to foster ecosystem sustainability including climate mitigation at the technology and societal levels which are at scale and profitable. Approaches summarized include halophytes/salt plants grown on deserts/wastelands using saline/seawater, to address land, water, food, energy and climate, frontier energetics, nascent climate mitigation concepts, cellular agriculture, materials optimization, the virtual age, efficiency and redesigning the ecosystem for the Anthropocene. Solution/mitigation approaches are targeted at deforestation, desertification, pollution writ large (land, sea, air, space), and extensive urbanization along with soil salination, ocean acidification, mining, and water scarcity.
Reversible protonic solid oxide cell (P-SOC) operating at intermediate-temperature exhibits excellent potential as a power generation and green hydrogen production device in fuel cell and electrolysis cell modes because of the high conversion efficiency. However, the lack of efficient air electrodes is the main challenge to obtain P-SOC with remarkable performance. Typically, air electrodes should possess high proton, oxygen ion and electron conductivity, outstanding catalytic ability for oxygen reduction reaction and H2O splitting, and also long-term durability. Recently, high entropy oxides (HEO) have become popular due to their various potential applications in terms of outstanding properties, including catalysis ability, conductivity, thermal stability, etc. HEO air electrodes have been confirmed to show good electrochemical performance in P-SOC, but the complex compositions and structure make it difficult to study HEO by traditional experimental methods. Machine learning (ML) has been regarded as a powerful tool in materials research and can solve the drawbacks in the discovery of HEO in a traditional way. In this perspective, we not only discuss the current utilization of HEO in P-SOC but also provide a possible process to use ML to guide the development of HEO.
The ubiquitin system has been shown to play an important role in regulation of immune responses during viral infection. In a recent article published in Science Signaling, Wu and colleagues revealed that transcriptional factor Miz1 plays a pro-viral role in influenza A virus (IAV) infection by suppressing type I interferons (IFNs) production through recruiting HDAC1 to ifnb1 promoter. They show that a series of E3 ligases combinatorially regulates Miz1 ubiquitination and degradation and modulates IFNs production and viral replication.
Vitrimers are crosslinked polymers containing dynamic covalent linkages. Because of their crosslinked structure, they are stable as thermosets at their service temperatures. At high enough temperatures, dynamic exchange reactions occur and rearrange the polymer network, thus vitrimers become malleable and reprocessable like thermoplastics. The dynamic covalent bonds can also undergo dissociative cleavage reactions under specific conditions, so vitrimers are inherently degradable. To achieve a sustainable future, various biomass resources have been used as raw materials in vitrimer preparation. This review summarizes recent developments in biobased vitrimers and highlights their preparation methods. The limitations of current biobased vitrimers are also discussed.
As wind energy becomes increasingly vital in global energy strategies, optimizing wind turbine design is essential. This research focuses on the development of a 100 kW single rotor horizontal axis wind turbine (HAWT) tailored to meet the energy needs of Jamshoro, Pakistan. The turbine design leverages SolidWorks for structural modeling and is validated through comprehensive simulations using ANSYS and Q-Blade. Operating at an optimal wind speed of 6.9 m/s, the turbine achieves maximum efficiency, as indicated by the highest power factor. This efficiency translates to an estimated power output of approximately 100 kW, suitable for common household consumption. The study integrates regional climatic data and wind conditions to enhance turbine performance and durability. The findings offer a sustainable energy solution for Jamshoro, contributing to Pakistan’s renewable energy infrastructure and addressing local energy demands effectively. The focus of this study will be Jamshoro, a region in Pakistan as a case study. The software simulations will consider a variety of elements, including as wind speeds, variable loads, and environmental factors unique to the chosen region (Jamshoro). This research proposes a sustainable solution for addressing the energy demands in Jamshoro by integrating accurate data based on software analysis with real-world concerns, adding to the larger goal of developing sustainable sources of energy in Pakistan.
This paper presents, an autonomous and scalable monitoring system for early detection and spread estimation of wildfires by leveraging low-cost UAVs, satellite data and ground sensors. An array of ground sensors, such as fixed towers equipped with infrared cameras and IoT sensors strategically placed in areas with a high probability of wildfire, will work in tandem with the space domain as well as the air domain to generate an accurate and comprehensive flow of information. This system-of-systems approach aims to take advantage of the key benefits across all systems while ensuring seamless cooperation. Having scalability and effectiveness in mind, the system is designed to work with low-cost COTS UAVs that leverage infrared and RGB sensors which will act as the primary situational awareness generator on demand. AI task allocation algorithms and swarming-oriented area coverage methods are at the heart of the system, effectively managing the aerial assets High-level mission planning takes place in the GCS, where information from all sensors is gathered and compiled into a user-understandable schema. In addition, the GCS issues warnings for events such as the detection of fire and hardware failures, live video feed and lower-level control of the swarm and IoT sensors when requested. By performing intelligent sensor fusion, this solution will offer unparalleled reaction times to wildfires while also being resilient and reconfigurable should any hardware failures arise by incorporating state of the art swarming capabilities.
This paper gives a comprehensive review of scientific interests and current methodologies of artificial intelligence applied to advanced material design and discovery by taking into account multiple sustainable design criteria such as functionalities, costs, environmental impacts, and recyclability. The main research activities include predicting material properties, compositions, and structures with data mining, new material discovery, hybrid modeling approaches combining AI techniques and classical computational formulations based on physical and chemical laws, and multicriteria optimization of materials. Based on this review, a short analysis is provided on the perspectives of this research area in the future, aiming at creating an everything connected material life cycle with real-time traceability systems
Pulmonary arterial hypertension (PAH) is a devastating disease characterized by high blood pressure in the pulmonary arteries, which can potentially lead to heart failure over time. Previously, our lab found that endothelia-specific knockout of Egln1, encoding prolyl 4-hydroxylase-2 (PHD2), induced spontaneous pulmonary hypertension (PH). Recently, we elucidated that Tmem100 is a lung-specific endothelial gene using Tmem100-CreERT2 mice. We hypothesize that lung endothelial-specific deletion of Egln1 could lead to the development of PH without affecting Egln1 gene expression in other organs. Tmem100-CreERT2 mice were crossed with Egln1flox/flox mice to generate Egln1f/f;Tmem100-CreERT2 (LiCKO) mice. Western blot and immunofluorescent staining were performed to verify the knockout efficacy of Egln1 in multiple organs of LiCKO mice. PH phenotypes, including hemodynamics, right heart size and function, pulmonary vascular remodeling, were evaluated by right heart catheterization and echocardiography measurements. Tamoxifen treatment induced Egln1 deletion in the lung endothelial cells (ECs) but not in other organs of adult LiCKO mice. LiCKO mice exhibited an increase in right ventricular systolic pressure (RVSP, ~35 mmHg) and right heart hypertrophy. Echocardiography measurements showed right heart hypertrophy, as well as cardiac and pulmonary arterial dysfunction. Pulmonary vascular remodeling, including increased pulmonary wall thickness and muscularization of distal pulmonary arterials, was enhanced in LiCKO mice compared to wild-type mice. Tmem100 promoter-mediated lung endothelial knockout of Egln1 in mice leads to development of spontaneous PH. LiCKO mice could serve as a novel mouse model for PH to study lung and other organ crosstalk.
Pressure garment therapy (PGT) and silicone gel sheeting (SGS) predominate non-invasive interventions for burn injuries, but the market lacks a composite solution combining pressure garment fabric (PGF) and medical-grade silicone (e.g. Biopor®AB) for multi-therapeutic efficacy. To address this gap, a versatile composite dressing of PGF-Biopor®AB was developed. PGF-Biopor®AB incorporates dual PGF-SGS therapy, mechanotherapy, and active moisture management, to facilitate recovery of hypertrophic subsidiary structures. The PGF structure enables the application of PGT, while the Biopor®AB silicone characteristics enforce silicone gel therapy (SGT). The PGF-SGS efficacy optimization not only reduces tension but also facilitates water vapor and oxygen penetration, along with hydration of the stratum corneum. Mechanotherapy, involving tension-shielding and pressure redistribution, promotes the reorganization of the collagen-fiber network. For active moisture management, the incorporation of a microchannel structure with active nylon absorbency facilitates effective moisture control through water absorption, retention, and cellular pathways of transport. In this study, the microscale features in the structure were further investigated. Under ISO 10993-5 standard, an over 70% cell viability in 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay containing the L929 cell line verified the enhanced cell growth and inhibited proliferation, endorsing the safe usage of PGF-Biopor®AB. Patient studies of one-month efficacy in both high and low-cell-density samples and an early scarless healed wound suggest that over 70% cell viability is sufficient for optimal scar therapeutics. The multifaceted scar repair roles are fulfilled by addressing persistent inflammation, insufficient oxygenation, low levels of perfusion, and scar-healing tension, hence realising the multi-therapeutic efficacy of the composite dressing.