Browse Articles

Distilling structural reasoning: efficient semantic parsing via chain-of-thought rationalization and contrastive demonstration selection

Observation of quantum information collapse-and-revival in a strongly-interacting Rydberg atom array

Abstract Interactions of isolated quantum many-body systems typically scramble local information into the entire system and make it unrecoverable. Ergodicity-breaking systems possess the potential to exhibit fundamentally different information scrambling dynamics beyond this paradigm. For many-body localized systems with strong ergodicity breaking, local transport vanishes and information scrambles logarithmically slowly. Whereas in Rydberg atom arrays, local qubit flips induce dynamical retardation on surrounding qubits through the blockade effect, potentially leading to unconventional quantum information scrambling behaviours. Here, we present the measurements of out-of-time-ordered correlators and Holevo information in a Rydberg atom array, enabling us to precisely track quantum information scrambling and transport dynamics. By leveraging these tools, we observe a spatio-temporal collapse-and-revival behaviour of quantum information, which differs from both typical chaotic and many-body localized systems. Our experiment sheds light on the unique information dynamics in many-body systems with kinetic constraints, and demonstrates an effective digital-analogue approach to coherently reverse time evolution and steer information propagation in near-term quantum devices.

The cationic nanoliposomes loaded with asymmetric PCR product targeting PTK6 mRNA and induce apoptosis in PANC-1 cells

Dual activation of MC3R and MC4R drives weight loss and reduces food intake in male primates with obesity

Exploring generational differences in the impact of stigma on mental health among people affected by leprosy in rural India: a qualitative study

Abstract Leprosy continues to be highly stigmatised in India, resulting in the continuation of poor mental health outcomes for affected individuals and delays in seeking treatment. Whilst previous research suggests that the effectiveness of intervention strategies to reduce stigma and improve mental health can vary across generations, little is known about how leprosy-related stigma specifically impacts the mental health of different generational groups. This study, therefore, explored these generational differences in rural India. Through qualitative in-depth interviews conducted between June and July 2022 with 20 people affected by leprosy in Sitapur district, Uttar Pradesh, several themes related to stigma and its impact on mental health were identified using thematic analysis. These themes were categorized under broader umbrellas: conceptions, social interactions and behaviours, clinical management, and mental health manifestations. These findings highlight the complex interplay of societal, informational, and psychological factors influencing stigma and mental health outcomes. Understanding how stigma impacts the mental health of individuals affected by leprosy is a complicated and multifaceted challenge. While the findings of this study suggest that knowledge and beliefs play a significant role in shaping how younger and older generations experience stigma in rural India, the implications for mental health are wide-ranging. This work also has broader implications for other remote settings and diseases within similar contexts, highlighting the need for further research to better understand these dynamics.

Highly potent C-type nanoantibodies neutralize Nipah and Hendra viruses by cavity filling on fusion glycoprotein

Efficacy of Sr2⁺ and Cu2⁺ Ion Incorporation on the Mechanical, biological, and antibacterial properties of natural waste-derived borosilicate bioactive glasses for orthopaedic implants

Pyrrhotite-driven early-stage terrestrial alteration in Ryugu grains

Polyhydroxyalkanoate/seashell powder biocomposites with degradability and 3D printing applications

Secretin-interacting plug proteins prevent antibiotic influx during type IV pilus assembly in Pseudomonas aeruginosa

Rhythmic movements mimicking tremor under different metronome conditions

Ultrahigh piezoelectric performances in soft lead zirconate titanate/polydimethylsiloxane composites by ethanol-assisted freeze casting

Downregulation of CXCL16/ADAM10 axis by Simvastatin attenuates tacrolimus-induced tubulointerstitial fibrosis

Amplified friction via a cooperative entanglement domains and steric hindrance for damping hydrogels

Robust ranking of renewable energy alternatives handling uncertainty using novel hesitant bi-fuzzy MEREC-MOORA and Dombi aggregation approach

Programmable electric hysteresis in graphite/MoS2 heterojunctions through twisting

The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions

Abstract Chronic pain is a multifaceted condition shaped by biological, psychological, and social factors, which challenges its diagnosis and treatment. While prior research largely focused on sensory profiles to distinguish pain mechanisms, this study adopted a biopsychosocial perspective with the key addition of experimental pain paradigms to identify factors explaining variance in chronic pain severity across diverse etiologies. The dataset comprised 101 individuals with chronic pain and 63 pain-free controls. Participants were classified into three groups (no pain, mild-to-moderate pain, and severe pain) using three models: a sensory-profile-based model including quantitative sensory testing (QST model), a biopsychosocial model incorporating QST alongside psychological and social variables (biopsychosocial model), and a model using the same biopsychosocial data but excluding QST measures (noQST model). The QST model achieved an accuracy of 0.51 and an F1-score of 0.48. In contrast, the biopsychosocial model performed best, with both accuracy and F1-score of 0.71, while the noQST model reached 0.60 for both metrics. Key predictors in the best-performing model included quality of life, loss of sensation, depressive mood, pain catastrophizing, anxiety, fatigue, and general health. Overall, biopsychosocial factors enhanced chronic pain severity classification beyond sensory profiles alone across heterogeneous pain etiologies.

The benchmarking and application of tag-degraders in vivo to validate therapeutic targets

Application of artificial neural networks to solve differential equations in Zika virus dynamics with exponential kernel derivatives

A guide to transient absorption spectroscopy for porous crystalline materials in photocatalysis