Browse Articles

Gas mixing control system for the preservation of aquatic products using modified atmosphere packaging

Lab-in-a-cartridge for real-time detection of tuberculosis via precise measurement of urinary lipoarabinomannan

An intelligent fusion-based transfer learning model with artificial protozoa optimiser for enhancing gesture recognition to aid visually impaired people

Functional network collapse in neurodegenerative disease

Abstract Cognitive and behavioral deficits in Alzheimer’s disease (AD) and frontotemporal dementia (FTD) arise alongside gray matter atrophy and altered functional connectivity, yet the structure-function relationship across the dementia spectrum remains unclear. Here we combine structural and functional MRI from 221 patients—AD ( n  = 82), behavioral variant FTD ( n  = 41), corticobasal syndrome ( n  = 27), and nonfluent ( n  = 34) or semantic ( n  = 37) variant primary progressive aphasia—and 100 cognitively normal individuals. Partial least-squares regression reveals three structure–function components. Component 1 links cumulative atrophy to sensorimotor hypo-connectivity and hyper-connectivity in association cortical and subcortical brain regions. Components 2 and 3 tie focal, syndrome-specific atrophy to peri-lesional hypo-connectivity and distal hyper-connectivity. Structural and functional component scores explain 34% of the variance in global and domain-specific cognitive deficits on average. The functional connectivity changes reflect alterations of intrinsic activity gradients. Eigenmode analysis shows that atrophy relates to reduced gradient amplitudes and narrowed phase angles between gradients, offering a mechanistic account of network collapse in neurodegeneration.

Lateral spreading mitigation in gravity quay walls backfilled with coral sand through electrolysis desaturation treatment

Phosphorylation of peptides by a kinase domain in cyanobactin pathways

A secure multi phase authentication protocol for cloud infrastructure using elliptic curve cryptography

A standardized approach to characterize hysteresis in 2D-materials-based transistors for stability benchmarking and performance projection

Generalizable gesture classification of HDsEMG using volume representations of muscles averaged across multiple individuals

Abstract Human hands can perform far more gestures than the number of muscles controlling them, as most gestures result from coordinated combinations of muscle activations and relaxations. This complexity poses a key challenge for human-machine interfaces performing gesture classification based on electromyography (EMG). Rather than identifying all conceivable gestures, it may be simpler to instead identify the activity of the individual muscles which generate a variety of complicated gestures. Here we suggest a three-dimensional model with volume representations of individual digit extensor muscles, averaged across multiple individuals, and evaluate its application and performance in hand gesture classification. Time-domain peaks in high-density surface EMG data from different hand gestures were extracted and localized within the model, from which a gesture classification scheme was generated for both single and multi-label cases. The model was created and tested on a publicly available dataset with 19 participants, leveraging a leave-one-out approach to assess inter-subject generalizability, and multi-label data to assess generalizability to gestures not included in the creation of the model. For single-label classification performance, true positive rates were between 61.9 and 95.1%, with false positive rates between 0 and 24.1%, for different single-digit extensions. The multi-label test demonstrated some degree of generalizability in identifying completely new gesture compositions, while simultaneously maintaining the leave-one-out approach for inter-subject generalizability. A model generated with this approach could be used for gesture classification by anyone, without individual modelling data, with the potential to generalize to any number of gesture compositions.

A golay metalens for long-range, large aperture, thermal imaging via sparse aperture computational imaging

Synergistic effects of rice husk ash and extracted microsilica on the performance of high-strength concrete

ER protein CLCC1 promotes nuclear envelope fusion in herpesviral and host processes

Determinants of hypertension among diabetes mellitus patients on treatment follow-up in West Gojjam zone public hospitals, Northwest Ethiopia

A heterogeneous-structure facial mask for thermal and humidity regulation in cold environments

Determinants of delay in presentation to completion of treatment in cervical cancer

Hybrid TiO2/Al2O3 nanolayer overcoating enhances dental lithium disilicate glass-ceramics acid resistance and surface mechanical properties

Abstract Lithium disilicate glass-ceramics are increasingly utilized in dental applications due to their exceptional optical and aesthetic properties. However, lithium disilicate glass-ceramics possess a mixed crystalline and amorphous structure with variable resistance to external corrosion. Exposure of lithium disilicate glass-ceramics to acidic conditions in the oral cavity leads to pore formation, and the risk of cracking increases with long-term wear. Herein, we employed atomic layer deposition to precisely coat the TiO 2 /Al 2 O 3 hybrid nanolayer on the surface of lithium disilicate glass-ceramics to enhance acid resistance and surface mechanical properties. The TiO 2 species play crucial roles in improving acid resistance, and the Al 2 O 3 species, atomically bonded to the TiO 2 species in the hybrid layer, promote interfacial interactions. Moreover, the TiO 2 /Al 2 O 3 hybrid nanolayer shows no cytotoxicity while maintaining the aesthetics of lithium disilicate glass-ceramic restorations, thus offering broad prospects for oral restoration applications.

Experimental and numerical study on the Frost-Heaving characteristics of subgrade soil in the Qinghai-Tibet plateau

ARMH2 is a cytosolic component of CatSper crucial for sperm function

Abstract Sperm capacitation and fertilization are highly regulated by Ca 2+ signaling. CatSper, a sperm-specific calcium channel, plays a crucial role in sperm hyperactivated motility and fertility by mediating Ca 2+ influx into sperm. CatSper is the most complicated ion channel known, comprising the pore-forming CATSPER1-4 and multiple auxiliary subunits. However, our previous structural study of mouse CatSper suggests the presence of potential component(s) that remain to be identified. The identity and functional significance of the missing piece(s) of CatSper remain elusive. Here, by combining cryo-EM, mass spectrometry, AlphaFold structure prediction, and coevolutionary analysis, we identify armadillo-like helical domain containing 2 (ARMH2) as a cytosolic component of CatSper. ARMH2 forms a cytosolic ternary subcomplex with EFCAB9 and CATSPERζ, which contributes to the stable assembly of the linear arrangement of CatSper nanodomains along the sperm tail and regulates the pH and Ca 2+ sensitivity of the channel. Loss of ARMH2 leads to compromised physiological activation of CatSper, thereby resulting in asthenozoospermia and severe subfertility. These findings show that ARMH2 is crucial for sperm function and provide fresh insights into the composition and functional regulation of CatSper. The integrated methodology employed in identifying ARMH2 also provides valuable approaches for discovering uncharacterized components in other protein complexes.

Application of text mining and causal analysis for risk identification in air traffic control safety operations

Widely tunable and narrow-linewidth violet lasers enabled by UV-transparent materials

Abstract Embedding multi-wavelength lasers in photonic waveguide circuits is of interest for next-generation ion traps, such as for miniaturizing optical clocks or upscaling ion-based quantum computing. Critically, this path involves photonic integration of highly coherent lasers in the ultraviolet (UV) range, which is presently obstructed by the transparency limit of materials used in established integrated waveguides. Here, we demonstrate the first integrated, extended cavity diode laser based solely on UV-transparent materials. We integrate aluminum oxide waveguide circuits with gallium nitride amplifiers to generate milliwatt-level on-chip output power near the ultraviolet range. The extended cavity approach allows for wide wavelength coverage and precise frequency control, which is demonstrated by tuning mode-hop-free to a Sr-transition frequency. Due to the inherent stability of photonic circuits and UV-compatible integration, the intrinsic laser linewidth reaches a record-low value around 300 kHz with better than 43-dB side-mode suppression. These results announce the viability of a novel class of integrated lasers that opens access to the UV.