Search Results (24,169)

Background: The primary effect of Botulinum toxin (BoNT) is to cause weakness in the injected muscles by inhibiting the release of acetyl choline from presynaptic nerve terminals. Its effect on sensorimotor integration (SMI) has largely been confined to small studies. The aim of this review is to highlight effect of BoNT on SMI in the context of Parkinson’s disease (PD), Cervical dystonia (CD), and Writer’s cramp (WC). Methods: Using keywords “Botulinum toxin” and “sensorimotor integration” or “Freezing of gait (FOG)” or ‘Tremor”or “Cervical dystonia” or “Parkinson’s disease”, or “Writer’s cramp”, PubMed database was searched for relevant articles supporting our view. The abstracts of all resultant articles (case reports, case series, randomized trials, observational studies) were reviewed to look for evidence of effects of botulinum toxin on SMI. The relevant articles were charted in excel sheet for further full text review. Results: In FOG, chronic BoNT injections may alter central motor patterns with inclusion of alternative striatal systems, cerebellum, and its connections. In tremor, the afferent proprioceptive input may be modified with reduction of intracortical facilitation and increment of intracortical inhibition. In CD, BoNT can restore disorganized cortical somatotrophy, the key pathophysiology behind cervical dystonia. Similarly, in WC, both the deficient sensory system and abnormal reorganization of the sensorimotor cortex may be altered following chronic BoNT injections. Conclusions: There is preliminary evidence that BoNT may modulate SMI in PD, CD, and WC by altering inputs from the muscle spindles in short term and modifying circuits/particular anatomic cerebral cortices in the long term. Properly conducted randomized trials comparing BoNT with placebo or prospective large-scale studies to look for effect on various surrogate markers reflective of changes in SMI should be the next step to confirm these findings. Targeting the system of afferents like spindles and golgi tendon organs in muscles may be a better way of injecting BoNT, with lower amounts of toxin needed and potential for lesser side-effects like weakness and atrophy. However, this needs to be proven in controlled trials. Full article

Air pollution is steadily increasing due to industrialization, economic activities, and transportation. High levels pose a significant threat to human health and well-being worldwide. Saudi Arabia is a growing country with air quality indices ranging from moderate to unhealthy. Although there are many monitoring stations distributed throughout the country, mathematical modeling of air pollution is still crucial for health and environmental decision-making. From this perspective, in this study, a data-driven approach based on pollutant records and a Deep Learning (DL) Long Short-Term Memory (LSTM) algorithm is carried out to perform temporal modeling of selected pollutants (PM₁₀, PM_2.5, CO and O₃) based on time series combined with a spatial modeling focused on selected cities (Riyadh, Jeddah, Mecca, Rabigh, Abha, Dammam and Taif), covering ~48% of the total population of the country. The best forecasts were provided by LSTM in cases where the datasets used were of relatively large size. Numerically, the obtained performance metrics such as the coefficient of determination (R²) ranged from 0.2425 to 0.8073. The best LSTM results were compared to those provided by two ensemble methods, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), where the merits of LSTM were confirmed mainly in terms of its ability to capture hidden relationships. We also found that overall, meteorological factors showed a weak association with pollutant concentrations, with ambient temperature exerting a moderate influence. However, incorporating ambient temperature into LSTM models did not lead to a significant improvement in predictive accuracy. The developed approach can be used to support decision-making in environmental and health domains, as well as to monitor pollutant concentrations based on historical time series records. Full article

This paper proposes a novel heart rate detection scheme to address key challenges in millimeter-wave radar-based vital sign monitoring, including weak signals, various types of interference, and the demand for high-precision and super-resolution frequency estimation under practical computational constraints. First, we propose a multi-dimensional coherent accumulation (MDCA) method to enhance the signal-to-noise ratio (SNR) by fully utilizing both spatial information from multiple receiving channels and temporal information from adjacent range bins. Additionally, we are the first to apply the fast iterative interpolated beamforming (FIIB) algorithm to radar-based heart rate detection, enabling super-resolution frequency estimation with low computational complexity. Compared to the traditional fast Fourier transform (FFT) method, the FIIB achieves an improvement of 1.08 beats per minute (bpm). A reordering strategy is also introduced to mitigate potential misjudgments by FIIB. Key parameters of FIIB, including the number of frequency components L and the number of iterations Q, are analyzed and recommended. Dozens of subjects were recruited for experiments, and the root mean square error (RMSE) of heart rate estimation was less than 1.12 bpm on average at a distance of 1 meter. Extensive experiments validate the high accuracy and robust performance of the proposed framework in heart rate estimation. Full article

We present a novel derivation of the spacetime metric generated by matter, without invoking Einstein’s field equations. For static sources, the metric arises from a relativistic formulation of D’Alembert’s principle, where the inertial force is treated as a real dynamical entity that exactly compensates gravity. This leads to a conformastatic metric whose geodesic equation—parametrized by proper time—reproduces the relativistic version of Newton’s second law for free fall. To extend the description to moving matter—uniformly or otherwise—we apply a Lorentz transformation to the static metric. The resulting non-static metric accounts for the motion of the sources and, remarkably, matches the weak-field limit of general relativity as obtained from the linearized Einstein equations in the de Donder (or Lorenz) gauge. This approach—at least at Solar System scales, where gravitational fields are weak—is grounded in a new dynamical interpretation of the Equivalence Principle. It demonstrates how gravity can emerge from the relativistic structure of inertia, without postulating or solving Einstein’s equations. Full article

This study investigates the application of the Keyhole–Tungsten Inert Gas Welding (K-TIG) hot-wire filling welding technique with mechanical arc oscillation to weld a 95 mm-thick Ti-6Al-4V titanium alloy plate. The root layer thickness achieved with this technique reaches up to 17 mm, with an average filling thickness of 2.5 mm. The weld bead displays a smooth, shiny appearance, and no significant welding defects are observed in the cross-section of the welded joint. Experimental results show that the welded joint consists of the α phase in different forms, as well as fine α+β microstructures. Compared to the base material, both the weld metal and the heat-affected zone exhibit a lower crystallographic texture strength, with more complex texture types. The impact toughness of the welded joint is excellent, with no significant weaknesses. The impact toughness of the weld metal significantly surpasses that of both the base material and the heat-affected zone. The engagement strengthening effect induced by high-current filling plays a crucial role in enhancing the impact toughness of the weld metal. Full article

In the era of data elements, it is extremely necessary and practically important to analyze network characteristics and evolutionary trends in academic research collaboration in the field of data assets research, which can provide valuable insights for promoting deep cooperation of scholars and enhancing their collaborative efficiency. However, existing studies on data assets research rarely delve into key differentiating characteristics and core thematic priorities between Chinese and international samples of collaboration networks. Based on bibliometric methods and social network analysis, a systematic comparative analysis between Chinese collaboration networks and international collaboration networks is conducted via CiteSpace software by using core literature from the China National Knowledge Infrastructure (CNKI) and Web of Science Core Collection, developed by Clarivate Analytics (WoS). Through observation, we find that the number of publications in this field has reached a preliminary scale with distinct differences in research focus and collaborative features between cooperation networks in China (CNCs) and international cooperation networks (ICNs). In recent years, Chinese samples have primarily focused upon research themes related to data value realization, such as data rights confirmation, data assets accounting, and data trusts. The overall connectivity of CNCs seems relatively weak, and a stable core author group has not formed, while collaborations in CNCs are predominantly localized and short-term. In contrast, international samples in recent years have mainly addressed the contextual application of data assets, exhibiting a collaboration network characterized by multi-center, interdisciplinary, and cross-institutional synergy, while core authors in ICNs are closely interconnected and their connectivity and structure are generally stronger than those of CNCs. Full article

The genomes of viruses in the Allexivirus genus encode the p42 protein, which is considered the hallmark of the genus. The functions of p42 have not yet been studied experimentally and cannot be predicted based on sequence similarity, as p42-related proteins are not found among known cell or viral proteins. Here, p42 of Shallot virus X (ShVX), the type allexivirus, is demonstrated to be translated via a leaky scanning mechanism on a template comprising three “triple gene block” (TGB) transport genes and the p42 gene. Sequence analysis shows that this p42 expression mechanism is conserved in the vast majority of allexiviruses. p42 binds single-stranded RNA (ssRNA) but not double-stranded RNA (dsRNA) in vitro and localizes to the cytoplasm in association with microtubules and microtubule-bound bodies. In transient expression assays, p42 exhibits weak but detectable suppression of silencing induced by ssRNA but not by dsRNA. In addition, p42 suppresses silencing in the context of virus infection. Furthermore, p42 inhibits nonsense-mediated RNA decay (NMD) induced by a long 3′-terminal untranslated region of mRNA. Taken together, these findings provide initial evidence that the ShVX TGB/p42 gene module functions as a single genomic unit in terms of protein expression, that p42 acts as a suppressor of NMD and silencing, and that it may have multiple roles, while the precise biological significance of p42 in these roles remains to be experimentally confirmed. Full article

This study aimed to validate the 9-point body condition score (BCS) system in sled dogs by assessing its reliability and by comparing it with objective measures including real-time ultrasonography, plicometry, and anthropometry. Twenty-seven Siberian Huskies (11 females, 16 males) from three sled dog teams were assessed for BCS by three trained veterinarians and their respective mushers. Intra-observer reliability was substantial (Krippendorff’s α = 0.734), while agreement between expert raters (Kα = 0.580) and between the expert rater and mushers (Kα = 0.691) was moderate, with mushers tending to overestimate the BCS of their own dogs (median difference = −0.5). BCS showed positive correlations with body mass index (BMI) and subcutaneous fat at the chest and flank via plicometry (for all: p < 0.05). Ultrasonography showed weak correlations with BCS, likely due to the different anatomical layers evaluated and the distinctively high muscle-to-fat ratio typical of sled dogs. Both univariate and multivariate analyses revealed sex- and neutering-related differences in body composition, with males generally presenting larger skeletal dimensions and neutering influencing patterns of fat distribution. These findings support the reliability and field applicability of the BCS system when used by trained evaluators, highlighting the importance of considering sex and anatomical site when assessing body condition in athletic dogs. The 9-point BCS, combined with accessible objective tools, represents a consistent, cost-effective method for monitoring body condition in long-distance performance sled dogs. Full article

Intergrown mixtures of nanostructured manganese oxide phases have been obtained using a highly complexing agent (ethylenediamine) and a weak complexer (urea) during their solvothermal synthesis. In this work, through a detailed structural analysis, it is evidenced the formation of an intergrown mixture of three distinct manganese oxide phases (β-MnO₂, α-Mn₂O₃, and Mn₃O₄). Scanning electron microscopy shows that the products have just one morphology, indicating that the different manganese oxide phases may have grown together, organizing themselves in a 3D crystal network. The reaction mechanisms are discussed in this paper. It is of great interest to produce intergrown mixtures of manganese oxide phases to take advantage of the availability of the different oxidation states of Mn in neighboring crystallites for applications like catalysis. Full article

Skeletal muscle, constituting ~40% of body mass, serves as a primary effector for movement and a key metabolic regulator through myokine secretion. Hereditary myopathies, including dystrophinopathies (DMD/BMD), limb–girdle muscular dystrophies (LGMD), and metabolic disorders like Pompe disease, arise from pathogenic mutations in structural, metabolic, or ion channel genes, leading to progressive weakness and multi-organ dysfunction. Gene therapy has emerged as a transformative strategy, leveraging viral and non-viral vectors to deliver therapeutic nucleic acids. Adeno-associated virus (AAV) vectors dominate clinical applications due to their efficient transduction of post-mitotic myofibers and sustained transgene expression. Innovations in AAV engineering, such as capsid modification (chemical conjugation, rational design, directed evolution), self-complementary genomes, and tissue-specific promoters (e.g., MHCK7), enhance muscle tropism while mitigating immunogenicity and off-target effects. Non-viral vectors (liposomes, polymers, exosomes) offer advantages in cargo capacity (delivering full-length dystrophin), biocompatibility, and scalable production but face challenges in transduction efficiency and endosomal escape. Clinically, AAV-based therapies (e.g., Elevidys^® for DMD, Zolgensma^® for SMA) demonstrate functional improvements, though immune responses and hepatotoxicity remain concerns. Future directions focus on AI-driven vector design, hybrid systems (AAV–exosomes), and standardized manufacturing to achieve “single-dose, lifelong cure” paradigms for muscular disorders. Full article

Magnetorheological elastomers (MREs) are a type of smart materials formed by dispersing magneto-responsive micron particles in an elastic polymer matrix. They hold significant potential for various applications due to their tunable stiffness, capability to carry out non-contact actuation, and rapid responsiveness to magnetic fields. However, weak interfacial interactions and poor dispersion of magnetic particles within the polymer matrix often lead to diminished magnetorheological (MR) performance. In this study, carbonyl iron powder (CIP) was chemically modified via polydopamine (PDA) deposition followed by grafting with isobutyl (trimethoxy)silane (IBTMO) to enhance its compatibility with a silicone-based matrix. The resulting anisotropic MREs fabricated using the dual-modified CIP exhibited a reduced elastic modulus, enhanced elongation, a large magnetically induced bending angle of 38°, and a notably improved MR effect of 246.8%. Furthermore, a magnetic soft actuator was designed based on the anisotropic dual-modified CIP-based MRE. When used as flippers for a duck model, the actuator successfully propelled a load approximately 76.8 times its own weight at a speed of 3.48 mm/s, thereby demonstrating promising potential for applications requiring load-bearing actuation. Full article

Fast, spark-free detection of hydrogen leaks is indispensable for large-scale hydrogen deployment, yet electronic sensors remain power-intensive and prone to cross-talk. Optical schemes based on surface plasmons enable remote read-out, but single-metal devices offer either weak H₂ affinity or poor plasmonic quality. Here we employ full-wave finite-difference time-domain (FDTD) simulations to map the hydrogen response of nanohole arrays (NAs) that can be mass-produced by colloidal lithography. Square lattices of 200 nm holes etched into 100 nm films of Pd, Mg, Ti, V, or Zr expose an intrinsic trade-off: Pd maintains sharp extraordinary optical transmission modes but shifts by only 28 nm upon hydriding, whereas Mg undergoes a large dielectric transition that extinguishes its resonance. Vertical pairing of a hydride-forming layer with a noble metal plasmonic cap overcomes this limitation. A Mg/Pd bilayer preserves all modes and red-shifts by 94 nm, while the predicted optimum Ag (60 nm)/Mg (40 nm) stack delivers a 163 nm shift with an 83 nm linewidth, yielding a figure of merit of 1.96—surpassing the best plasmonic hydrogen sensors reported to date. Continuous-film geometry suppresses mechanical degradation, and the design rules—noble-metal plasmon generator, buried hydride layer, and thickness tuning—are general. This study charts a scalable route to remote, sub-ppm, optical hydrogen sensors compatible with a carbon-neutral energy infrastructure. Full article

Three-dimensional concrete printing (3DCP) is an emerging additive manufacturing technology with increasing application potential in the construction industry, offering advantages such as reduced labor requirements, shortened construction time, and material efficiency. However, structural integrity remains a challenge, particularly due to weak interlayer bonding resulting from the layered manufacturing process. This study investigates the mechanical performance and anisotropy of 3D-printed mineral-based composites with respect to the time interval between successive layers. Specimens were printed with varying interlayer intervals (0, 25, and 50 min) and tested in different loading directions. Flexural, compressive, and tensile strengths (direct and splitting methods) were measured both parallel and perpendicular to the layer orientation. Results showed a clear degradation in mechanical properties with increasing interlayer time, particularly in the direction perpendicular to the layers. Flexural strength decreased by over 25% and direct tensile strength by up to 40% with a 25 min interval. Compressive strength also declined, though less dramatically. Compared to cast specimens, printed elements showed 3–4 times lower compressive strength, highlighting the significant impact of interlayer cohesion. This study confirms that both the time between layers and the loading direction strongly influence mechanical behavior, underlining the anisotropic nature of 3DCP elements and the need for process optimization to ensure structural reliability. Full article

The endangered plant Hopea hainanensis serves as both an indicator and keystone species in tropical rainforests, and its survival status is influenced by the interspecific relationships among coexisting tree species within the community. To explore these relationships, species resource utilization patterns, and community succession dynamics within the endangered plant community, this study utilized survey data from the Hopea hainanensis community in the Bawangling and Jianfengling branches of the National Park of Hainan Tropical Rainforest. Various analytical methods were employed, including the Variance Ratio (VR) method, test statistic (W), χ² test, Spearman’s rank correlation, and M. Godron’s stability analysis, to examine the interspecific associations among dominant tree species at different structural levels in the two regions and their effects on community stability. The results indicate that: (1) Hopea hainanensis is the dominant species in the medium tree layer in both study areas, while it functions as an associated species in other structural layers. (2) In communities where Hopea hainanensis is present in both Bawangling and Jianfengling, the dominant tree species across various structural layers generally show a non-significant positive association. (3) The results of the χ² test and Spearman’s rank correlation test reveal that the interspecific associations across different structural layers of the Hopea hainanensis communities in both regions are predominantly non-significant. This suggests weak interspecific relationships and a high degree of species independence. The communities at different structural levels in both Bawangling and Jianfengling are in an unstable state, with ongoing dynamic adjustments to their internal tree species composition and structure. In terms of stability, the community stability across structural levels in these two regions follows the order: middle shrub layer > middle arbor layer > small arbor layer > large shrub layer. This study reveals the interspecific relationships, community succession status, and stability of dominant tree species at different structural levels in slope barrier communities across regions. These findings provide a theoretical basis for developing scientifically sound and reasonable protection strategies for slope barrier populations, as well as for the restoration and sustainable development of tropical rainforest vegetation. Full article

The first part of this study is related to the search of fixed points for (E)-operators (Garcia-Falset operators), in the Banach setting, by means of a three-step iteration procedure. The main results reveal some conclusions related to weak and strong convergence of the considered iterative scheme toward a fixed point. On the other hand, the usefulness of the S_n iterative scheme is once again revealed by demonstrating through numerical simulations the advantages of using it for solving the problem of the maximum modulus of complex polynomials compared to standard algorithms, such as Newton, Halley, or Kalantary’s so-called B₄ iteration. Full article