Digital forensics plays a key role in investigating different types of crimes. It involves analyzing evidence from electronic devices, social media, and system logs. However, investigators face major challenges due to the large size of digital data. Information from networks, smartphones, and online platforms is often too complex to analyze within a limited time. The large size of digital evidence and the pressure of a strict timeline for case investigation force the investigator to do data reduction and selective analysis. It is also difficult for the investigator to correlate the various digital evidence to create the complete picture of the crime story. To address these challenges, we propose a Multimodal Artificial Intelligence Framework designed to integrate heterogeneous digital evidence analysis capabilities by leveraging artificial intelligence. The proof-of-concept architecture proposed in the paper incorporates explainable AI, pattern recognition, and a confidence-aware inference mechanism for semantic evidence analysis. The experimental analysis of the proposed model shows improved investigative efficiency. The analysis of the research results endorses the effectiveness of AI-assisted workflow in digital forensics investigation.

Hearing loss is a prevalent condition affecting over 500 million people globally, with projections estimating more than 700 million cases by 2050. Artificial Intelligence (AI) holds transformative potential in audiology, enhancing diagnostic, therapeutic, and rehabilitation outcomes. This review explores the applications of AI in hearing aids, cochlear implants, sign language recognition, and tele-audiology. A comprehensive literature review was conducted using PubMed, Google Scholar, and other academic databases. Relevant studies on AI-driven advancements in audiology were analyzed, focusing on hearing aid technologies, cochlear implants, diagnostics, and tele-audiology platforms. AI technologies significantly enhance hearing aids through real-time personalization and adaptive algorithms. Cochlear implants leverage AI for improved speech recognition and listening comfort. AI-powered sign language systems facilitate communication through real-time gestureto- text conversions, while tele-audiology expands care access using AI-enabled platforms. Diagnostic advancements include AI-enhanced audiometric testing and otoscopy. AI is revolutionizing hearing healthcare by providing personalized, efficient, and accessible solutions. Its integration into audiology represents a paradigm shift, offering significant improvements in patient outcomes and quality of life.

The presence of antibiotic residues in poultry meat poses a growing risk of non-compliance with maximum residue limits under international food safety regulations. However, existing screening methods to detect antibiotic overuse rely mainly on LC-MS with dispersive solid-phase extraction (dSPE) clean-up using instrumentation and sorbents that are economically inaccessible to many food-safety laboratories in resource-limited countries where such monitoring is most needed. This work develops and validates a sorbent-free, HPLC-UV multiclass screening procedure for six antibiotic residues (sulfadiazine, trimethoprim, ciprofloxacin, enrofloxacin, sulfamethoxazole and doxycycline) in chicken meat samples prior to confirmatory testing by the LC-MS technique. Three integrated methodological milestones were achieved in this work. First, mechanistic retention-time modeling equations were applied to optimize a gradient HPLC-UV separation for the studied compounds based on only six scouting runs without trial-and-error effort. Second, the extraction procedure was optimized using the Plackett-Burman screening, followed by Box-Behnken response surface design, yielding a modified QuEChERS extraction method, eliminating the dSPE step. Third, a salt-assisted liquid-liquid microextraction (SALLME) preconcentration step for the recovered analytes mitigated the sensitivity limitations of UV detection, enabling detection at food-safety-relevant concentration ranges. A robust HPLC-UV method was developed with good peak separation within 17 min using a Zorbax SB C8 column (150 × 4.6 mm, 5 µm) with a gradient system consisting of a 20 mM formate buffer (pH 3.0) and an acetonitrile-methanol (1 : 1, v/v) blend. Detection was performed using the dual-wavelength mode at 230 and 275 nm. The procedure met the linearity, repeatability and recovery validation criteria under Commission Implementing Regulation (EU) 2021/808, with recoveries of 77.7-109.2% and expanded measurement uncertainty values not exceeding 42.8%, in accordance with SANTE/11312/2021 v2. The presented sorbent-free workflow provided a validated screening platform accessible in resource-limited settings worldwide.

Hydrophilic perovskite quantum dots (PQDs) have emerged as promising materials for biomedical diagnostics due to their exceptional optical tunability and high photoluminescence quantum yield. However, their instability, toxicity, and degradation in aqueous and biological environments remain critical barriers to practical applications. This review integrates predictive modeling and bioinspired stabilization strategies to provide a comprehensive understanding of the mechanisms governing PQD instability and the design of robust, biocompatible nanostructures. Multiscale computational approaches-including density functional theory, molecular dynamics, and machine learning-are analyzed to elucidate degradation pathways and forecast material performance under physiological conditions. In parallel, bioinspired and hybrid stabilization strategies, such as ligand engineering, polymer/silica encapsulations, and adaptive coating design, are critically evaluated for enhancing aqueous stability and biosafety. The stabilized PQDs are further discussed in multiplexed biomedical diagnostics, highlighting their potential for precision sensing of multiple biomarkers. This is the comprehensive review that bridges predictive modeling with bioinspired stabilization to advance hydrophilic PQDs toward intelligent and multiplexed diagnostic platforms.

Layered organic halide perovskites exhibit better chemical and structural stability than its bulk counterparts. Strong exciton binding also promotes excellent light-matter interaction with the possibility to tune the emission position using halide atom interchange. Despite excellent physical properties, the reported light sensitivity is lower than those of other material systems, largely ascribed to poor in-plane carrier transport and efficient recombination processes. Here, we show that large area CVD grown layered PEA2PbI4 can show an enhanced photoresponse with strong exciton resonance enhancement. The device exhibits gate-field sensitivity with a 1.5-fold enhancement at negative gate fields achieving a responsivity of 0.52 mA W-1 at the exciton position (520 nm). These results show that the layered perovskite with simple large area deposition shows excellent promise in optoelectronic device applications.

Hybrid metal halides (HMHs) have emerged as promising functional materials owing to their versatile structural tunability and outstanding optoelectronic properties. In particular, chiral HMHs could be endowed with fascinating chiroptoelectronic properties such as circularly polarized light emission, circularly polarized photodetection, and spin regulation. However, the implementation of their practical integrated optoelectronic applications has been mainly restricted to planar thin-film devices due to the poor processability of chiral HMHs for the construction of complex three-dimensional (3D) architectures. Here, we take advantage of the glass transition of chiral HMH with 3D printing technology to construct self-supported 3D architectures with high-performance linear and nonlinear optical functionalities. Chiral HMH (R/S-THNA)3SbCl6·0.5H2O (R/S-THNA = R/S-1,2,3,4-tetrahydro-1-naphthylammonium) forms transparent amorphous glass upon rapid quenching from its molten state. The resulting R/S-SbCl-glass favors tunable photoluminescence colors and a large, continuously tunable range of glass transition temperature (∼50°C) through metal halide infusion. The intrinsic thermoplasticity of HMH glasses allows for additive-free, thermally assisted extrusion-based printing of self-supporting 3D architectures. Upon recrystallization, the printed structures recovered non-centrosymmetric crystal lattices and exhibited strong isotropic second harmonic generation response, enabling customized nonlinear optical imaging. This work establishes a thermally programmable paradigm for transforming HMHs from molecularly designed materials into 3D optical architectures.

Electrocaloric (EC) refrigeration uses dielectric capacitors that are naturally efficient and have no direct carbon emissions. The idea that electrical capacitors can serve as working bodies in a refrigeration cycle implies that electricity can be directly harnessed, potentially enabling the development of miniature and portable refrigerators, and has therefore attracted considerable attention from both academia and industry. Poly(vinylidene fluoride) (PVDF)-based fluoropolymers exhibit strong dipolar responses and have been extensively studied for EC devices. However, despite their exceptional flexibility, straightforward synthesis, self-healing capability, and low breakdown risk, their relatively low polar entropy-changes limit their refrigeration capacities in practical applications. Rationally designing an EC polymer considering its molecular-scale structure, crystalline features, and interfacial effects remains a major, nontrivial challenge. This work systematically reviews recent advances in EC polymers and focuses on two fundamental points pivotal for enhancing the polar entropy change, that is the electrocaloric effect (ECE): increasing zero-field entropy and reducing the energy barrier of dipolar switching to increase electric field responsiveness. Together, they form a high-polar-entropy strategy that shows the potential to approach the lower and upper bounds of polar entropy to maximize the ECE. This strategy is expected to be effective in predicting and designing other potential EC material systems.

The superconducting diode effect (SDE), characterized by nonreciprocal critical supercurrents, plays a key role for next-generation dissipationless electronics. Typically, the SDE requires external magnetic fields to break time-reversal symmetry, limiting its practical applications. Superconductor/ferromagnet heterostructures offer an alternative way to enable field-free nonreciprocal transport by using magnetic proximity effects to break time-reversal symmetry. However, the SDE in these cases generally show a fixed sign of the critical current asymmetry, without any polarity reversal. Therefore, a polarity-reversible SDE with a sign-switchable critical current difference remains unexplored. Here, we demonstrate a high-field robust and polarity-reversible SDE in a van der Waals FeSeTe/Fe3GaTe2 heterostructure. We found that, even though the pristine FeSeTe shows no diode response, the heterostructure exhibits a pronounced zero-field SDE arising from proximity-induced time-reversal symmetry breaking. Notably, the diode polarity can be effectively switched by both temperature and magnetic field. Strikingly, the SDE persists under magnetic fields of up to 10 T, exceeding the operational limits of most reported SDE platforms. These results establish such heterostructures as a versatile materials platform for high-field and polarity-reversible superconducting diodes for low-dissipation rectifiers and superconducting logic devices.

Hospital-acquired pressure injuries remain an important patient-safety burden, yet direct evidence comparing prophylactic sacral dressing technologies is absent.