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To achieve optimal thermoelectric performance, it is crucial to manipulate the scattering processes within materials to decouple the transport of phonons and electrons. In half-Heusler (hH) compounds, selective defect reduction can significantly improve performance due to the weak electron-acoustic phonon interaction. This study utilized Sb-pressure controlled annealing process to modulate the microstructure and point defects of Nb 0.55 Ta 0.40 Ti 0.05 FeSb compound, resulting in a 100% increase in carrier mobility and a maximum power factor of 78 µW cm −1 K −2 , approaching the theoretical prediction for NbFeSb single crystal. This approach yielded the highest average zT of ~0.86 among hH in the temperature range of 300-873 K. The use of this material led to a 210% enhancement in cooling power density compared to Bi 2 Te 3 -based devices and a conversion efficiency of 12%. These results demonstrate a promising strategy for optimizing hH materials for near-room-temperature thermoelectric applications. Here, the authors increase the grain size of Nb 0.55 Ta 0.4 Ti 0.05 FeSb by three orders of magnitude by Sb-pressure controlled annealing, resulting in enhanced mobility and cooling power density compared to Bi 2 Te 3 -based devices.

The design of functional materials with desired properties is essential in driving technological advances in areas such as energy storage, catalysis and carbon capture 1 , 2 – 3 . Generative models accelerate materials design by directly generating new materials given desired property constraints, but current methods have a low success rate in proposing stable crystals or can satisfy only a limited set of property constraints 4 , 5 , 6 , 7 , 8 , 9 , 10 – 11 . Here we present MatterGen, a model that generates stable, diverse inorganic materials across the periodic table and can further be fine-tuned to steer the generation towards a broad range of property constraints. Compared with previous generative models 4 , 12 , structures produced by MatterGen are more than twice as likely to be new and stable, and more than ten times closer to the local energy minimum. After fine-tuning, MatterGen successfully generates stable, new materials with desired chemistry, symmetry and mechanical, electronic and magnetic properties. As a proof of concept, we synthesize one of the generated structures and measure its property value to be within 20% of our target. We believe that the quality of generated materials and the breadth of abilities of MatterGen represent an important advancement towards creating a foundational generative model for materials design. MatterGen is a model that generates stable, diverse inorganic materials across the periodic table and can further be fine-tuned to steer the generation towards a broad range of property constraints.

This paper considers the stability of a fractional differential equation with multi-point boundary conditions and non-instantaneous integral impulse. Some sufficient conditions for the existence, uniqueness and at least one solution of the aforementioned equation are studied by using the Diaz-Margolis fixed point theorem. Secondly, the Ulam stability of the equation is also discussed. Lastly, we give one example to support our main results. It is worth pointing out that these two non-instantaneous integral impulse and multi-point boundary conditions factors are simultaneously considered in the fractional differential equations studied for the first time.

Borderlands are increasingly recognized as critically important for biodiversity conservation owing to their ecological significance and high political profile. However, the species ranges covered by protected areas and their influencing factors in transboundary areas are still largely unknown worldwide. Here, based on the distributional ranges of 19,039 terrestrial vertebrates, we find that three-quarters of species’ ranges in global borders remain uncovered by protected areas, particularly in tropical areas of Southeast Asia and West Africa. The average protected area coverage of species ranges is lower in transboundary areas than non-transboundary areas after accounting for geographical differences in sampling efforts. We also observe that protected area coverage of species ranges increases with governance effectiveness, collaboration abilities, protection levels, sizes and establishment years of protected areas, and topographic complexity, but decreases with human population density, human development index, and cropland expansion. Furthermore, protected areas simultaneously face threats of ongoing global challenges from climate change, land-use modification, and alien species invasion, and the proportions of borderlands threatened by global changes are higher than elsewhere. All these findings demonstrate that cross-border cooperation is urgently needed to achieve the ambitious goal of global biodiversity conservation by 2050. Transboundary areas are critical refuges for many threatened species. However, this study reveals that three-quarters of species’ ranges in global border regions remain uncovered by protected areas, and that these regions are facing greater challenges from global change.

Cancer is a global intractable disease, and its morbidity and mortality are increasing year by year in developing countries. Surgery and chemotherapy are often used to treat cancer, but they result in unsatisfactory outcomes, such as severe side effects and drug resistance. With the accelerated modernization of traditional Chinese medicine (TCM), an increasing body of evidence has shown that several TCM components have significant anticancer activities. Astragaloside IV (AS-IV) is considered the main active ingredient of the dried root of Astragalus membranaceus . AS-IV exhibits various pharmacological effects, such as anti-inflammatory, hypoglycemic, antifibrotic, and anticancer activities. AS-IV possesses a wide range of activities, such as the modulation of reactive oxygen species-scavenging enzyme activities, participation in cell cycle arrest, induction of apoptosis and autophagy, and suppression of cancer cell proliferation, invasiveness, and metastasis. These effects are involved in the inhibition of different malignant tumors, such as lung, liver, breast, and gastric cancers. This article reviews the bioavailability, anticancer activity, and mechanism of AS-IV and provides suggestions for further research of this TCM.

Reservoir computing (RC) offers efficient temporal information processing with low training cost. All-ferroelectric implementation of RC is appealing because it can fully exploit the merits of ferroelectric memristors (e.g., good controllability); however, this has been undemonstrated due to the challenge of developing ferroelectric memristors with distinctly different switching characteristics specific to the reservoir and readout network. Here, we experimentally demonstrate an all-ferroelectric RC system whose reservoir and readout network are implemented with volatile and nonvolatile ferroelectric diodes (FDs), respectively. The volatile and nonvolatile FDs are derived from the same Pt/BiFeO 3 /SrRuO 3 structure via the manipulation of an imprint field ( E imp ). It is shown that the volatile FD with E imp exhibits short-term memory and nonlinearity while the nonvolatile FD with negligible E imp displays long-term potentiation/depression, fulfilling the functional requirements of the reservoir and readout network, respectively. Hence, the all-ferroelectric RC system is competent for handling various temporal tasks. In particular, it achieves an ultralow normalized root mean square error of 0.017 in the Hénon map time-series prediction. Besides, both the volatile and nonvolatile FDs demonstrate long-term stability in ambient air, high endurance, and low power consumption, promising the all-ferroelectric RC system as a reliable and low-power neuromorphic hardware for temporal information processing. While reservoir computing can process temporal information efficiently, its hardware implementation remains a challenge due to the lack of robust and energy efficient hardware. Here, the authors develop an all-ferroelectric reservoir computing system, showing high accuracies and low power consumptions in various tasks like the time-series prediction.

In-sensor computing has emerged as an ultrafast and low-power technique for next-generation machine vision. However, in situ training of in-sensor computing systems remains challenging due to the demands for both high-performance devices and efficient programming schemes. Here, we experimentally demonstrate the in situ training of an in-sensor artificial neural network (ANN) based on ferroelectric photosensors (FE-PSs). Our FE-PS exhibits self-powered, fast (<30 μs), and multilevel (>4 bits) photoresponses, as well as long retention (50 days), high endurance (10 9 ), high write speed (100 ns), and small cycle-to-cycle and device-to-device variations (~0.66% and ~2.72%, respectively), all of which are desirable for the in situ training. Additionally, a bi-directional closed-loop programming scheme is developed, achieving a precise and efficient weight update for the FE-PS. Using this programming scheme, an in-sensor ANN based on the FE-PSs is trained in situ to recognize traffic signs for commanding a prototype autonomous vehicle. Moreover, this in-sensor ANN operates 50 times faster than a von Neumann machine vision system. This study paves the way for the development of in-sensor computing systems with in situ training capability, which may find applications in new data-streaming machine vision tasks. In-sensor computing with in-situ training capability is promising for machine vision applications, yet their implementation remains a challenge. Here, the authors demonstrate in-situ training of an in-sensor artificial neural network using ferroelectric photosensors.

Background While clinical trials have demonstrated enduring responses to amivantamab among advanced non-small cell lung cancer (NSCLC) patients bearing EGFR exon 20 insertion mutations, the associated toxicity profile in real-world scenarios remains elusive. Methods This pharmacovigilance study analyzed data from the FDA Adverse Event Reporting System (FAERS) to investigate adverse events associated with amivantamab over the period from September 2021 to December 2023. A comprehensive disproportionality analysis was performed, employing the reporting odds ratio (ROR), proportional reporting ratio (PRR), Empirical Bayes Geometric Mean (EBGM), and the Bayesian confidence propagation neural network to calculate information components (ICs), to identify statistically significant adverse events. Results A significant proportion of adverse events (AEs) was attributable to injury, poisoning, and procedural complications, cutaneous disorders, respiratory ailments, infections, as well as vascular and lymphatic system disturbances. There were noteworthy incidences of AEs including infusion-related reactions, rash, dyspnea, pneumonitis, paronychia, pulmonary embolism, thrombocytopenia, nausea, acneiform dermatitis, deep vein thrombosis, febrile neutropenia, peripheral edema, hypokalemia, and neutropenia. Furthermore, the majority of AEs occurred within the first month following the initiation of amivantamab treatment, accounting for 51.74% of cases. Conclusion The reversibility of amivantamab-related toxicities suggests its promising utility in patients with EGFR exon 20 insertion mutations NSCLC.

Malignant tumors are often multifactorial. Epidemiological studies have shown that hyperglycemia raises the prevalence and mortality of certain malignancies, like breast, liver, bladder, pancreatic, colorectal, endometrial cancers. Hyperglycemia can promote the proliferation, invasion and migration, induce the apoptotic resistance and enhance the chemoresistance of tumor cells. This review focuses on the new findings in the relationship between hyperglycemia and tumor development.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality, highlighting the urgent need for novel therapeutic strategies. Apoptin, encoded by the VP3 gene of the chicken anemia virus, selectively induces apoptosis in cancer cells while sparing normal cells. We previously engineered a recombinant oncolytic adenovirus (Ad-VP3) capable of high-level Apoptin expression in tumor cells. In this study, we evaluated the antitumor activity of Ad-VP3 in the human HCC cell line Hep3B. CCK-8, crystal violet, Hoechst 33342 staining, flow cytometry, and tumor sphere formation assays revealed that Ad-VP3 inhibited cell viability, proliferation, and stemness. Annexin V staining, JC-1/TMRM probes, and Western blot analysis demonstrated induction of apoptosis and reduction of mitochondrial membrane potential. Wound-healing, Transwell, and BioCoat invasion assays, along with Western blotting, confirmed suppression of migration and invasion. Ad-VP3 significantly inhibited the viability, proliferation, migration, and invasion of Hep3B cells in a time- and dose-dependent manner. It induced mitochondrial membrane potential loss and apoptosis, downregulated stemness-related proteins (ALDH1A1, KLF4, and Sox2), and suppressed epithelial–mesenchymal transition markers (Snail, Twist1, Slug, Vimentin, and MMP-9), indicating strong antitumor activity. The recombinant oncolytic adenovirus Ad-VP3 exerts potent antitumor effects on hepatocellular carcinoma cells by inducing mitochondrial dysfunctionmediated apoptosis and impairing stemness and metastatic potential, suggesting its promise as a novel therapeutic strategy for HCC.