Search Results (16,819)

Copper has emerged as a major potential bottleneck in the global energy transition. Electrification, AI-driven data centers, electric vehicles, renewable energy deployment, grid expansion, and rising defense spending are projected to increase global copper demand by approximately 50% by 2040, while supply remains constrained by declining ore grades, lengthy permitting processes, and a decade of underinvestment. According to S&P Global demand could reach 42 Mt by 2040, resulting in a supply deficit exceeding 10 Mt, despite USGS estimates of 820 Mt of global copper reserves. The challenge is therefore not primarily one of geological scarcity, but rather of reserve concentration, geopolitical access, and the pace of new discoveries and mine development. This study evaluates whether Bayesian artificial intelligence (AI) can help alleviate these constraints by combining Bayesian exploration analysis with Monte Carlo simulations of long-term copper supply and price risk. Bayesian exploration may reduce dry-hole rates by 30–50%, shorten exploration timelines by 3–4 years, and lower exploration costs by 10–15%, as suggested by KoBold Metals’ rapid advancement of the Mingomba deposit. However, AI cannot accelerate permitting, mine construction, social licensing, or geopolitical access. A stochastic price model based on 5000 Monte Carlo simulations indicates that, without AI-enabled exploration and renewed mining investment, copper prices could exceed USD 16,000/t by 2036, increasing the risk of substitution and demand destruction. By contrast, Bayesian optimization could support a more sustainable long-term price equilibrium of USD 11,000–13,000/t (constant 2026 USD). AI should therefore be viewed as a supply-side risk mitigator with potentially stabilizing macroeconomic effects, rather than as an independent stabilizer. It can improve exploration efficiency and capital allocation but cannot replace new mine development or overcome the geological, regulatory, and geopolitical constraints future copper supply. Full article

The implementation of collaborative robots (cobots) in Industry 5.0 requires a synergistic connection between technical safety and integrated management systems (IMSs). This article introduces three newly defined interaction concepts that map technological evolution: HCDI, an approximation for Industry 4.0; HCD_XI, designed for anthropocentric Industry 5.0; and aICD_XI, which anticipates the emerging cognitive era of artificial intelligence. The principal contribution is an original four-phase engineering algorithm for cobot implementation linked to thirteen ISO standards, including ISO 9001, ISO 45001, ISO 14001, ISO/IEC 27001, and ISO/IEC 42001. The algorithm applies the multicriteria SCATI method for process prioritization and the probabilistic reliability performance index (RPI) based on conditional probabilities as an operational reliability acceptance gate, distinct from ISO/TS 15066 functional safety requirements. IMS synergies are visualized by the Synergy HOUSE architectural model. The methodology was validated in an optical quality-inspection cell consisting of MiR100 + UR5e + Robotiq + Smart Vision ADMIN 4.0. Evaluated via Monte Carlo simulation, the pre-operational index reached RPI = 0.9801. Deployment of the node demonstrated a 60.0% increase in productivity, a 64.5% decrease in the defect rate, a statistically significant 32.0% reduction in cognitive workload, and a 50.0% reduction in total energy consumption (ISO 50001), enabled by the transition to lights-out operation. At the same time, the energy paradox of edge cooling for AI was described. The results confirm the robustness of the algorithm for systematic and sustainable enterprise transformation. Full article

This article exposes how Chile permits photovoltaic plants on its land of highest agricultural capability, withdrawing the material basis of long-term food security for at least a generation, in full legality. Linking environmental-assessment records, fiscal cadastral microdata and the CIREN capability survey, I document 135 approved plants sited dominantly on Class I–III soil, 5836 declared hectares; elite soil covers 18.2% of the farmed landscape yet hosts 42.8% of the approved plants, 2.35 times its share. That the system processes this tension without friction reveals the socio-legal infrastructure of property, whose dephysicalisation erases the land’s food-producing capability from every register of decision. The regime fuses three securities (legal certainty, juridical security and land-tenure security), serving as the foundation of the energy transition. The fusion shields the proprietor and confines all protection to the voluntary, visible in the compensations proponents offer when the Agriculture and Livestock Service (SAG) objects. A documentary census of the permitting files supplies the new evidence. The SAG objects in writing to the loss of productive agricultural land in 64 of 136 approved files, and no objection prevents approval; in 21 a favourable qualification is issued with the objection still standing. The Service refutes, with measurements of its own, proponents who declare their soil poor, up to Class I, and the projects are approved nonetheless. If rural land is to be protected as a public good, voluntariness must yield to obligation. Full article

Resistive random-access memory (RRAM) has emerged as one of the most promising device platforms for neuromorphic, in-memory computing because its two-terminal metal–insulator–metal (MIM) structure can reproduce the weight-update behavior of biological synapses while remaining compatible with mainstream CMOS processing. This review summarizes the current state of RRAM-based neuromorphic technology from four complementary perspectives: device physics, materials, fabrication processes, and packaging. We first describe the operating principles of filamentary and interface-type RRAM, including the forming/set/reset switching sequence, and the two dominant analytical frameworks used to describe the reset transition—the ion-migration model and the thermally driven filament-dissolution model. We then review the switching-layer and electrode materials that have been most widely investigated such as HfO_x, TiO_x, TaO_x, ZnO, ZrO₂, and Cu/Ag-based conductive-bridge systems, together with representative bilayer and doped architectures reported for synaptic devices. The biological functions that RRAM can emulate are discussed alongside the non-ideal characteristics that currently limit on-chip training accuracy, with emphasis on separating device-to-device from cycle-to-cycle variability and on the workload-dependent nature of endurance and retention requirements. We further summarize the process technologies used to integrate RRAM into large-scale, CMOS-compatible arrays, including atomic layer deposition, interfacial oxygen-reservoir engineering, low-thermal-budget back-end-of-line integration, and three-dimensional vertical RRAM patterning, and discuss the advanced packaging strategies such as 2.5D/3D heterogeneous integration, chiplet architectures, thermal-interface materials, and nanostructured underfills required to manage the power density and interconnect demands of large synaptic arrays, distinguishing solutions that have been demonstrated specifically for RRAM neuromorphic arrays from those that remain general advanced-packaging concepts. Finally, RRAM is benchmarked against competing emerging non-volatile memories, and the key research directions such as three-terminal memtransistor architectures, three-dimensional integration with high-performance selectors, and hardware–algorithm co-design that will determine whether RRAM-based neuromorphic hardware can move from laboratory demonstrations to on-device AI, autonomous systems, and large-scale artificial-neural-network accelerators are outlined. Relative to prior reviews that focus primarily on RRAM device physics or on switching-layer materials in isolation, the distinctive contribution of this review is an explicit, cross-layer synthesis that connects device-level non-idealities to their consequences for wafer-scale process integration and for advanced 2.5D/3D packaging—a combination that, to our knowledge, has not been jointly treated in the recent review literature on RRAM-based neuromorphic hardware. Full article

High-resolution measurements of near-surface optical turbulence over the Tibetan Plateau are essential for optical propagation studies, astronomical site characterization, and adaptive optics applications. In this study, a multi-level tethered UAV system was deployed in Ngari Prefecture, China, to obtain synchronous in situ observations of atmospheric optical turbulence from 10 to 190 m above ground. Using measurements at 10–90 m as inputs, we developed a physics-informed reconstruction framework to estimate $C_n^2$ profiles at 110–190 m, thereby approximately doubling the vertical range covered relative to the directly used observations. The framework decomposes the turbulence structure into an equilibrium component describing the large-scale vertical profile and a residual component representing departures from equilibrium. The equilibrium structure is modeled using a dynamically fitted power-law relationship, while a residual-learning module captures short-term variability associated with evolving thermal and dynamical processes. On the independent test period from the same field campaign, the reconstructed profiles achieve an average RMSE below 0.6 in $\lg \left(C_n^2\right)$ and an average $R^2$ above 0.75, outperforming empirical extrapolation and representative data-driven baselines. The proposed framework provides reliable estimates of upper-layer optical turbulence under daytime and transition-period conditions over the Ngari Plateau. Full article

The study presents the results of experimental investigations into hybrid additive–subtractive manufacturing of lightweight PLA fixtures with gyroid internal structures. The proposed manufacturing approach combines FFF (Fused Filament Fabrication) printing with finish CNC milling in order to improve the dimensional accuracy, surface quality, and functional performance of polymer components intended for rapid tooling and functional prototyping applications. Test specimens with gyroid infill densities of 30% and 60% were manufactured from PLA material and subsequently subjected to finish milling under various cutting conditions. Particular attention was paid to the influence of cutting speed and feed per tooth on surface integrity, dimensional stability, and thermal effects occurring during machining. Maintaining the process temperature below the glass transition range of PLA (approximately 50 °C–60 °C) was identified as a critical factor for minimizing deformation and preserving geometric accuracy. The obtained results demonstrate that hybrid FFF-CNC processing enables the fabrication of lightweight yet sufficiently stiff fixtures characterized by improved surface roughness and high dimensional precision. The application of gyroid internal structures significantly reduces component mass while maintaining adequate mechanical rigidity. Moreover, the milled reference surfaces ensure precise positioning and repeatable geometric basing of cooperating machine and robotic assembly elements. The proposed hybrid manufacturing approach shows considerable potential for industrial implementation, particularly in the production of customized positioning fixtures, jigs, and functional tooling components used in automated assembly systems and rapid tooling applications. Full article

The transition toward more sustainable diets has increased interest in alternative protein sources, including plant-based meat substitutes, cultured meat, edible insects, microalgae, and microbial fermentation products. Their successful adoption depends not only on technological advances and market availability but also on consumer acceptance shaped by cultural, sensory, psychological, ethical, and socio-demographic factors. This narrative review synthesizes evidence on consumer acceptance of alternative proteins in Poland, a country characterized by strong culinary traditions, high attachment to meat, and selective openness to food innovation. The evidence base is fragmented and uneven across product categories. Plant-based alternatives are the most established but face barriers related to price, sensory expectations, perceived nutritional quality, and concerns about ultra-processing. Cultured meat shows moderate acceptance, limited by perceived unnaturalness, safety concerns, and low familiarity. Edible insects remain the least accepted due to disgust, food neophobia, and cultural barriers. Evidence on microalgae and mycoproteins is scarce, while consumer responses to fermentation-derived proteins are largely unexplored. Overall, acceptance varies by product type and requires targeted improvements, culturally sensitive communication, and more robust research. Full article

The Youjiang Basin is located in the southwestern margin of the South China Block and at the junction between the South China and Indochina Blocks at the eastern end of the Tethyan tectonic domain. The processes responsible for Triassic magmatism in the basin are crucial to understanding the closure of the Paleo-Tethys Ocean. This study presents the geochemistry and zircon U-Pb-Hf isotopes of granites from the Pingxiang area in the southwestern Youjiang Basin. The granites belong to the high-K and peraluminous series with A/CNK ratios of 1.16–1.38. They have high SiO₂ and K₂O contents and moderate Al₂O₃ content with moderately fractionated REE patterns (La_N/Yb_N = 6.35–7.83) and negative Ba, Sr, P and Ti anomalies, consistent with peraluminous A₂-type granites. The granites have LA-ICP-MS zircon U-Pb ages of 243–241 Ma, with negative εHf_(t) values ranging from −13.22 to −6.52 and T_DM2 model ages from 1654 to 2073 Ma. They were formed by partial melting of Paleoproterozoic metasedimentary rocks in an extensional setting. Combined with existing data, we suggest that the 243–241 Ma extensional event is related to the subduction-to-collision transition likely induced by slab breakoff during the closure of the Paleo-Tethys Ocean. Full article

The role of land use/land cover (LULC) dynamics in predisposing slopes to shallow landsliding is widely acknowledged but seldom translated into operational susceptibility modelling. Most data-driven approaches still treat LULC as a static factor, neglecting the legacy effects of recent transitions. This study presents a methodological framework to quantify the influence of multi-temporal LULC changes on shallow landslide initiation and to incorporate this information into susceptibility mapping. The procedure was tested in the Metropolitan City of Messina (formerly known as the Province of Messina), Southern Italy, a representative Mediterranean area repeatedly affected by rainfall-triggered slope failures. Freely available LULC maps from 1990 to 2006 were processed through post-classification change detection to identify dominant land cover trajectories. Preliminary analyses within buffer areas showed higher landslide indices (LI, LAI) and Frequency Ratios for some transition classes, suggesting a potential role of LULC changes. These findings motivated the comparison between a static LULC configuration and a dynamic one incorporating the detected transitions within a Frequency Ratio susceptibility model. The dynamic model did not improve the mean Area Under the Curve (AUC) compared to the static model (0.7774 vs. 0.7742), and the observed reduction in variability across five independent random splits (standard deviation 0.012 vs. 0.064) should be considered preliminary. The proposed workflow, based entirely on open data and GIS-based processing, offers a transparent and reproducible methodology for integrating LULC transitions into dynamic susceptibility maps. The use of higher-resolution input data could potentially reduce the scale mismatch and improve the detection of fine-scale transitions, supporting more effective landslide risk mitigation and evidence-based land planning. Full article

While variable-latency AI dialogue processing proceeds asynchronously, the VR state continues to be updated frame by frame. In this study, we implemented “guard-mediated LLM-VR scene control” for breastfeeding support training, in which LLM-derived ActionClass and PhaseCandidate are not used to update the phase directly, but are instead provided as inputs to phase-specific deterministic guards together with the VR state and the ActionClass-mediated mother-avatar state on the Unity side. We conducted human-in-the-loop sessions with 20 nursing students, post-study guard/Turn-ID tests, a 2-expert semantic evaluation of 639 cases, and state-binding and local guard sensitivity analyses. There were no failures preventing session continuation, and the median of the participant-specific median latencies was 2.61 s. Phase guards matched a separately implemented specification-based oracle in 1600 out of 1600 cases, and the Turn-ID gate eliminated cross-turn stale results. LLM-expert strict agreement was 74.5%/77.8% for ActionClass and 16.9%/35.2% for PhaseCandidate. The local outcome divergence in cases where semantic labels differed between the two experts was 85.2% in Phase 1, 1.9% in Phase 2, and 56.8% in Phase 3; the impact of semantic variability differed across phases. In particular, the current topology, which uses PhaseCandidate as a standalone transition-enabling disjunct, requires reevaluation. This study is a technical pilot and mechanism-specific characterization; it does not evaluate educational effectiveness, clinical efficacy or safety, or superiority over alternative architectures. Full article

Background/Objectives: Shape-memory biodegradable scaffolds (4D scaffolds) represent promising platforms for minimally invasive tissue engineering and localized drug delivery. This study investigated how two different fabrication techniques, electrospinning (ES) and extrusion-based direct ink writing (DIW), influence the structural, thermal, mechanical, shape-memory, and drug-release properties of poly(L-lactide-co-caprolactone) (PLA/PCL 70:30) scaffolds loaded with dexamethasone (DXM). Methods: DXM-loaded PLA/PCL 70:30 scaffolds were fabricated by ES and DIW. The resulting matrices were characterized in terms of morphology, mass, thickness, drug-loading efficiency, thermal properties by differential scanning calorimetry, shape-memory performance, tensile mechanical properties, and in vitro DXM release. Results: Both fabrication techniques produced DXM-loaded matrices with comparable mass and thickness and high loading efficiencies (>82%). Glass transition temperatures ranged between 33 and 39 °C, supporting thermally induced shape recovery under physiologically relevant conditions, while ES processing was associated with higher polymer crystallinity. All scaffolds exhibited shape-memory behavior, with recovery ratios exceeding 90%. ES scaffolds displayed a microporous nanofibrous architecture, whereas DIW scaffolds showed a more open and highly porous structure. These morphological differences were reflected in their mechanical behavior: ES scaffolds exhibited higher tensile strength (up to 16.5 MPa vs. 1.9 MPa) and elongation at break (up to 320% vs. 243%). Drug-release profiles were also fabrication-dependent, with ES scaffolds reaching a plateau at approximately 80% DXM release, whereas DIW scaffolds showed near-complete release within 48 h. Conclusions: Both fabrication approaches preserved the thermoresponsive shape-memory behavior of PLA/PCL 70:30 but generated distinct scaffold architectures that strongly influenced mechanical performance and DXM-release kinetics. Full article

Earth’s early history provides the only natural record for evaluating how planetary evolution can generate environments capable of initiating life. Here we review early Earth evolution through the lens of urability: the time-dependent capacity of planetary environments to support prebiotic chemistry progressing toward compartmentalized, self-propagating, information-bearing systems. We argue that urability is not a single globally habitable state, but a transient overlap among several coupled dimensions: liquid water availability, permissive temperature, ocean pH and salinity, access to bioessential elements, atmospheric shielding and volatile retention, and exposed or shallow environments that enable concentration, mineral catalysis, and wet–dry cycling. During the Hadean–early Archean transition, these dimensions were shaped by magma-ocean degassing, late accretion history, atmospheric compositional evolution from CO₂-rich to more N₂-dominated states, ferruginous ocean chemistry, tectonic recycling, continental growth, and intermittent land emergence. These processes created tradeoffs: high pCO₂ may have enhanced abiotic nitrogen fixation but imposed hot and acidic conditions, whereas CO₂ drawdown improved climate and ocean pH while weakening some fixed-nitrogen sources; ferruginous chemistry could locally enhance phosphate availability while also promoting nutrient scavenging; and tectonic recycling could stabilize the carbon cycle while generating chemically diverse but spatially intermittent land environments. We therefore frame life’s origin as a planetary timing problem, in which prebiotic opportunities opened and closed as multiple environmental constraints came into and out of overlap. This perspective motivates coupled models that resolve when and where water, temperature, pH, nutrients, energy, atmospheric photochemistry, and exposed land surfaces jointly produced urable environments on Earth and other rocky planets. Full article

Surface wettability is a critical factor influencing the biological performance of orthopedic Ti implants. The native TiO₂ film on Ti undergoes changes in wettability under ultraviolet (UV) irradiation. However, the limited tissue penetration of UV light compared with near-infrared (NIR) light restricts its potential clinical application. In this study, a black TiO₂ (b-TiO₂) coating with NIR-responsive wettability was fabricated directly on a Ti substrate using a one-step atmospheric plasma spraying process. Under 808 nm NIR irradiation, the water contact angle of the b-TiO₂ coating increased from 0° to 154.4 ± 4.0°, indicating a transition from a superhydrophilic to a stable superhydrophobic state. FTIR and XPS analyses showed that NIR-induced photothermal heating promoted the removal of surface hydroxyl groups and the passivation of oxygen-deficient sites, thereby driving the wettability transition. Among TiO₂ coatings with hydrophilic, intermediate-wettability, and hydrophobic surfaces, the hydrophobic coating effectively directed macrophage polarization toward the anti-inflammatory M2 phenotype and delivered slightly superior osteoblast activity. It also markedly inhibited Staphylococcus aureus adhesion, achieving an anti-adhesion efficiency of 98.61%. These findings demonstrate that NIR irradiation can regulate the wettability of plasma-sprayed b-TiO₂ coatings and provide concurrent immunomodulatory and antibacterial effects. This approach may support the development of light-responsive surfaces for orthopedic implants. Full article

The field of cosmetic science is rapidly evolving due to advances in skin biology research and increasing demand for evidence-based, personalized skincare solutions. A key aspect of this progress is the targeted modulation of biological macromolecules involved in skin aging, pigmentation, inflammation, and tissue regeneration. This review highlights major molecular targets in modern cosmetic research, focusing on telomerase, histone deacetylases (particularly sirtuins), matrix metalloproteinases, antioxidant enzymes, CD44 receptor, tyrosinase, microphthalmia-associated transcription factor, and melanocortin receptors, all of which regulate processes such as DNA repair, gene expression, extracellular matrix remodeling, and melanogenesis. Recent findings indicate that natural and synthetic compounds can effectively modulate these targets, supporting anti-aging and depigmenting strategies. Telomerase activators and sirtuin modulators show potential in maintaining cellular homeostasis and delaying skin aging. In pigmentation research, the transition from mushroom to human tyrosinase assays has enabled development of more selective inhibitors, including thiamidol. The review also addresses molecular targets relevant to inflammatory skin disorders, scars, and skin atrophy. Advances in molecular and biotechnological methods are expected to improve mechanistic understanding and support the rational design of safer, more effective next-generation cosmetic ingredients and formulations. Full article

Cancer therapy-related acute kidney injury has become an increasingly common challenge as modern treatments prolong survival and increase exposure to potentially nephrotoxic therapies. Decisions regarding therapeutic rechallenge have relied on normalizing serum creatinine and recovering estimated glomerular filtration rate, despite growing evidence that biochemical recovery does not necessarily indicate restoration of kidney integrity or resilience. In this review, we propose biological kidney recovery as a conceptual framework that integrates mechanisms of kidney injury and repair (adaptive and maladaptive) with emerging biomarkers and therapeutic rechallenge. We first summarize the distinct mechanisms of kidney injury induced by platinum-based chemotherapy, immune checkpoint inhibitors, and vascular endothelial growth factor pathway inhibitors, highlighting how these differences influence subsequent repair. We then discuss the cellular and metabolic processes underlying adaptive repair, the transition to maladaptive remodeling, and current approaches for assessing biological recovery through pathology, biomarkers, and multi-omics technologies. Finally, we present a practical framework for individualized therapeutic rechallenge based on an integrated assessment of kidney-, tumor-, and patient-related factors and outline future directions for precision onco-nephrology. By shifting the focus from filtration alone to biological recovery, this framework enables more informed therapeutic rechallenge aimed at preserving both oncologic efficacy and long-term kidney health. Full article