Browse Articles

Carpal tunnel release surgery restores force control but not force coordination in CTS patients

Fractional differentiation method: Application to the trapping reactions in the comb-like structures with relaxation

The theory of subdiffusion and reactions occurring in confined domains such as comb structures has widespread applications in various fields of science. We study trapping diffusion-controlled reactions taking place in the backbone of a two-dimensional comb-like structure. A brief survey of previously published works on diffusion transport, both without and with inertial effects, is given. To take into account inertial effects, in this paper, we used the known Compte–Metzler analysis to choose an appropriate fractional diffusive Cattaneo system. By means of the chosen suitable fractional diffusive Cattaneo system, we derive the diffusion equation comprising a 1/2-order fractional time derivative as a damping term. With the help of the fractional differentiation method, we analytically evaluate the trapping reaction rate coefficient for short and long time regimes. Numerical calculations performed for the reaction rate coefficient showed a very good agreement with the obtained analytical expressions.

Chemoenzymatic Site-Specific Lysine Modification of Nanobodies and Subsequent Bioconjugation via Potassium Acyltrifluoroborate (KAT) Ligations

Social network characteristics associated with mid-to-older aged adults’ co-engagement in physical activity

Objectives Physical activity is associated with a greater quantity and quality of social connections. Participating in physical activity with others (co-engagement) has dual physical and social benefits that can promote healthy ageing. We aimed to understand the social network characteristics of mid-to-older aged adults associated with co-engagement in physical activity. Methods Adults aged 55–75 years completed a social network survey (3679 social contacts reported by 140 participants). Multilevel modelling was used to identify the characteristics of participants, social contacts, and relationships that were predictive of co-engagement in physical activity. Results Network size and relationship quality were not associated with co-engagement. Similarity in age, greater interaction frequency, closer geographic proximity, and shorter relationship length were associated with higher odds of co-engagement. Discussion For co-engagement, the quality and quantity of relationships were less important than the convenience and accessibility of relationships, particularly newer relationships. As such, co-engagement ties can be understood as part of a dynamic social convoy which fulfil a specific function at a specific life stage. An understanding of naturally occurring tendencies for co-engagement may be utilised to identify leverage points for the development of interventions.

Research on association analysis between electricity consumption behaviors and weather factors based on mapreduce

Ensemble density functional theory with spherically symmetric densities

The spherical ensemble theory of excited states is developed. The Hohenberg–Kohn theorems are extended to ensembles with spherically symmetric densities via constrained search, and spherical ensemble Kohn–Sham-like equations are derived. The spherical ensemble theory makes it possible to apply a different partition of the energy functional. The spherical Hartree expression is generalized to ensembles. An exactly soluble model of a harmonic two-electron molecule is analyzed.

Photoelectrochemical Imaging of Charge Separation between MoS₂ Triangles and Insulating SiO₂ Support

Simple modification of the upper confidence bound algorithm by generalized weighted averages

The multi-armed bandit (MAB) problem is a classical problem that models sequential decision-making under uncertainty in reinforcement learning. In this study, we propose a new generalized upper confidence bound (UCB) algorithm (GWA-UCB1) by extending UCB1, which is a representative algorithm for MAB problems, using generalized weighted averages, and present an effective algorithm for various problem settings. GWA-UCB1 is a two-parameter generalization of the balance between exploration and exploitation in UCB1 and can be implemented with a simple modification of the UCB1 formula. Therefore, this algorithm can be easily applied to UCB-based reinforcement learning models. In preliminary experiments, we investigated the optimal parameters of a simple generalized UCB1 (G-UCB1), prepared for comparison and GWA-UCB1, in a stochastic MAB problem with two arms. Subsequently, we confirmed the performance of the algorithms with the investigated parameters on stochastic MAB problems when arm reward probabilities were sampled from uniform or normal distributions and on survival MAB problems assuming more realistic situations. GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at https://github.com/manome/python-mab.

Quantifying dislocation-type defects in post irradiation examination via transfer learning

Abstract The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

Evaluating wavefunction methods, the counterpoise correction, and the frozen core approximation for the optimization of van der Waals dimers

A number of benchmarking studies have assessed the accuracy of various electronic structure methods for computing the interaction energies of van der Waals dimers, but fewer have systematically assessed the quality of dimer geometries obtained by these methods. We present optimized geometries of 21 van der Waals dimers using a highly accurate level of theory, namely coupled-cluster through perturbative triples at the complete basis set limit [CCSD(T)/CBS], and compare these results with optimizations performed at lower levels of theory. The lower levels of theory include variants of Møller–Plesset perturbation theory (MP2, MP2D, and MP2.5) and coupled-cluster theory [CCSD and CCSD(T)], with basis sets ranging from double- to quadruple-zeta. The accuracy of these methods is assessed by comparing errors in the least-root-mean-squared deviations (LRMSDs) of atomic coordinates, center-of-mass distances (ΔdCOM), interaction energies, and rotational constants. We also investigate the impact of the counterpoise correction and the frozen core approximation on the quality of the optimized geometries. Our findings show that increasing the basis set size beyond double-zeta significantly improves the accuracy of the geometries, while further improvements due to the basis set size depend on the method used. The frozen core approximation induces very small changes in geometries, while the counterpoise correction has a larger effect. For double-zeta basis sets, the counterpoise correction tends to degrade the quality of the optimized geometries, regardless of the method used. Several methods yield geometries with LRMSDs and ΔdCOM within 0.1 Å for all 21 dimers, and MP2D with the aug-cc-pVTZ basis set emerges as the most computationally efficient among these well-performing approaches with an average LRMSD and an absolute ΔdCOM of 0.02 Å.

Fragmented Ultrathin Carbon Buffed Copper Clusters for Selective Hydrogenation of <i>N</i>-Heteroarenes under Ambient Pressure

Exploring support for medicalized female genital mutilation/cutting: A study on migrant women living in Italy

The medicalization of female genital mutilation/cutting (FGM/C) as a harm reduction strategy is a highly debated issue, although largely unexplored among migrants living outside practising countries. This study investigates the extent of the support for FGM/C conditioned on its medicalization among migrant women from FGM/C-practising countries residing in Italy, and the characteristics of women supporting the practice. Data are from a national survey on FGM/C conducted in Italy in 2016, covering a representative sample of 1,378 women aged 18 + who were born in Nigeria, Egypt, Eritrea, Senegal, Burkina Faso, Somalia, and Ivory Coast. A discrete choice framework and a multinomial probit choice model are adopted to analyze women’s preferences about FGM/C continuation and medicalization. Findings indicate that, compared with women who support the practice unconditionally, the requirement of medicalization correlates with higher educational level, age, being in a couple, and being from a country where FGM/C is more commonly medicalized. Perceived benefits linked to increased support for FGM/C medicalization include religious approval, better marriage prospects, cleanliness, and conformity to traditional cultural values. Our data show that higher education is a critical, but not unique, factor in understanding the support for FGM/C in its medicalized form.

Prospective uncontrolled clinical study shows rapid and long lasting relief of heartburn and acid related gastric discomfort with Refluthin

Abstract Heartburn and acid regurgitation are main symptoms of gastro-esophageal reflux, a widespread complaint with a significant impact on quality of life (QoL). Refluthin® for Heartburn chewable tablets (Refluthin) are a symptomatic treatment option containing a combination of an antacid (CaCO3, MgCO3) and a polysaccharide-rich extract with mucoprotective substances from Opuntia ficus-indica cladodes. To investigate performance and safety of Refluthin in the rapid and long lasting relief of heartburn and acid related gastric discomfort under practical use conditions, a prospective, clinical, uncontrolled, open-label study was conducted. Adults with symptomatic heartburn, acid regurgitation, and/or recurrent acid related gastric discomfort took one tablet Refluthin up to four times/day as needed for up to 4 weeks. Endpoints were both time to onset and duration of symptom relief; reflux symptom intensity/frequency; global assessments (QoL, performance, satisfaction, usability, tolerability); and safety. 81/100 participants (81%) responded with a first symptom relief within ≤ 20 min in ≥ 50% of the individual applications. Long lasting effects of &gt; 120 min were reported by 83/100 (83%) participants. Significant reductions in heartburn event frequency and intensity were seen within the 4 weeks of intermittent use (p &lt; 0.0001, respectively). Global assessment results and safety-relevant findings were also favorable. Results thus demonstrated a distinct rapid and long lasting symptom relief after intake of Refluthin, with a safe and easy use. The significant reductions in frequency and intensity of heartburn events over time indicate sustained effects under treatment. These long-term effects might be explainable by soothing and protection of the irritated mucous membrane by Refluthin.

A strict and internally consistent diabatic representation for coupled <i>N</i>-state diatomics: A hybrid asymptotic-property-based diabatization method

A robust regularization procedure for the radial non-adiabatic coupling (NAC) elements of the diatomic nuclear kinetic energy operator for the N-state diatomic problem is presented. This method ensures NACs are internally consistent with each other and with corresponding adiabatic properties, such as potentials or dipoles. Constructing a diabatic representation—where all components of the (radial) nuclear derivative couplings vanish—that is both physical and exactly equivalent to the adiabatic representation can be impossible due to inconsistencies between NACs and adiabatic properties. Such discrepancies arise from using different theory levels in ab initio molecular property calculations, convergence issues in quantum chemistry calculations, post-processing adjustments to computed property curves, and truncation errors when considering only a finite number of Born–Oppenheimer states. The presented regularization procedure leverages a hybrid asymptotic-property-based diabatization (HyAP), where the asymptotic behavior of diabatic properties is addressed and their smoothness maximized simultaneously. This is achieved through optimization of the trajectory of the adiabatic to diabatic transformation (AtDT) parameterized by the corresponding generator matrices (exponential mapping). The presented methodology is applied to the 3-state system of N2 [1Σ+1, 2Σ+1, and 3Σ+1] and the 4-state system of CH [CΣ+2, 2Σ+2, 3Σ+2, and 4Σ+2] via evolution of the AtDT, where a physical diabatization is achieved. The HyAP regularization, developed and tested for applications in spectroscopy, is guided by underlying electronic structure data to fulfill our pragmatic aim of constructing physical diabatic representations that effectively controls bound rovibronic molecular spectroscopy while remaining exactly equivalent to the adiabatic representation.

Excess weight is associated with neurological and neuropsychiatric symptoms in post-COVID-19 condition: A systematic review and meta-analysis

Background/purpose Excess weight has been identified as a potential risk factor for post-COVID-19 condition (PCC). This systematic review and meta-analysis aimed to investigate whether excess weight is associated with the development or experience of neurological and neuropsychiatric symptoms in PCC. Methods We conducted a comprehensive search of eight databases (PubMed, Embase, Scopus, Web of Science, VHL, Google Scholar, ProQuest, and medRxiv) for studies published up to July 2023. Studies were included if they assessed PCC symptoms in relation to nutritional status, specifically the development of neurological and neuropsychiatric symptoms more than 12 weeks post-infection. The analysis compared exposure and controls groups (excess weight vs. normal weight; obesity vs. non-obesity). Data were synthesized using a random-effects model. Results Of the 10,122 abstracts screened, 18 studies (n = 139,091 adults) were included. These studies included 79,050 individuals with excess weight vs 57,926 normal-weight individuals and 30,694 individuals with obesity vs 107,612 non-obese individuals. The presence of excess weight in PCC was significantly associated with persistent depression (RR = 1.21; 95% CI: 1.03–1.42), headache (OR = 1.23; 95% CI: 1.10–1.37), memory issues (RR = 1.43; 95% CI: 1.24–1.65), sleep disturbance (RR = 1.31; 95% CI: 1.16–1.48), and vertigo (RR = 1.21; 95% CI: 1.04–1.41). Obesity was significantly associated with persistent headache (OR = 1.45; 95% CI: 1.37–1.53), numbness (RR = 1.61; 95% CI: 1.46–1.78), smell disorder (OR = 1.16; 95% CI: 1.11–1.22), taste disorder (OR = 1.22; 95% CI: 1.08–1.38), and vertigo (RR = 1.44; 95% CI: 1.35–1.53). Conclusions Excess weight, including overweight and obesity, is associated with experiencing neuro-symptoms related to PCC. Individuals with these conditions urgently need enhanced personalized care management in current post-pandemic context.

A novel red blood cell deformability biomarker is associated with hemolysis and vaso-occlusive crises in sickle cell disease

Adsorption and reaction of 2-methylbenzimidazole molecules on a partially oxidized Cu(110) surface

N-Heterocyclic carbenes (NHCs) have emerged as a promising candidate for functionalizing and modifying metal surfaces. Despite extensive research, the influence of oxides, which frequently occur on metal surfaces, on the adsorption behavior of NHCs has received limited attention at the nanometric scale. In this study, the adsorption configurations and reactions of 2-methylbenzimidazole (MBI) molecules on a CuO/Cu(110) surface were investigated using scanning tunneling microscopy and non-contact atomic force microscopy (nc-AFM). Following the deposition of MBI molecules, Cu islands were observed, and the molecules predominantly adsorbed in a flat-lying configuration. Comparative experiments conducted on a bare Cu(110) surface indicate that the dehydrogenation of MBI molecules due to the cleavage of N–H bonds leads to CuO reduction and the release of Cu adatoms, which subsequently aggregate into islands. Upon annealing at 378 K, molecules adsorbed at the CuO strips assume a tilted flat-lying configuration, suggesting the formation of coordination bonds between nitrogen and copper atoms. On the copper regions, molecules assemble into double-chains, adopting an upright configuration. High-resolution nc-AFM images reveal a similarity between molecules in the double-chains and those at step edges, implying that Cu atoms are extracted from terraces to form slots where molecules preferentially occupy.

Cathode Electrolyte Interphase Regulation for High-Performance Lithium–Organic Batteries

Frequency and predictors of depression and anxiety in chronic illnesses: A multi disease study across non-communicable and communicable diseases

Background Depression and anxiety are among the most common mental health conditions globally that impact the lifestyle of affected individuals. Mental conditions and chronic diseases are linked to each other bidirectionally. Depression and anxiety with comorbid chronic conditions are often neglected or under-screened and possess challenges in treatment. This study aimed to know the frequency and determinants of depression and anxiety along with the severity level among common chronic communicable and non-communicable diseases. Methods We enrolled 200 healthy controls and 800 cases with equal number (n = 400) of patients with communicable and non-communicable diseases. Depression and anxiety were screened through Hamilton’s rating scale for depression and anxiety separately. We also measured the determinants of severe depression among patients with chronic diseases. Data was analyzed through SPSS version 23. Results We found higher frequency of depression (31% vs 11%; p=&lt;0.001) and anxiety (13.25% vs 6%; p = 0.021) among cases as compared to healthy controls respectively. We found higher levels of depression among participants with non-communicable diseases as compared to communicable diseases (37.25% vs 24.75%; p &lt; 0.05) respectively. Moreover, there was a higher frequency of anxiety in participants with communicable diseases as compared to those with non-communicable diseases, but the difference was non-significant (14% vs 12.5% p = 0.081). Among non-communicable diseases the highest percentage was found among individuals with cancer (67%), followed by diabetes (38%), cardiovascular diseases (33%) and respiratory disorders (11%). Among participants with communicable diseases, the highest percentage of depression was found in patients with Tuberculosis (29%) followed by HIV/AIDS (28%), Long COVID-19 (25%) and Hepatitis B/C (17%). Conclusion There is a significantly higher percentage of depression and anxiety among participants with chronic diseases. It calls for a comprehensive approach to patient care that incorporates mental health as a fundamental aspect of the treatment and management of chronic diseases. Understanding the predictors of severe depression across different chronic conditions helps in stratifying patients who may benefit most from integrated psychiatric and psychological interventions.

Water beetle networks differences and migration between natural lakes and post-exploitation water bodies

Abstract Water deficits are a serious problem around the world, which also affects young landscapes, where lakes are most abundant. This poses a threat to many habitats and biological diversity found here. The relationships between species in the ecological networks of lakes at different stages of development and in nearby post-exploitation water bodies remain poorly understood. To better understand the functioning of beetle communities in different ecosystems, we created five network models that we subjected to graph analysis. By analysing the general attributes of the network (number of neighbours, shortest path, characteristic path length, clustering coefficient, network centralisation, network density and network heterogeneity) and those related to the nodes (NCC—Node Closeness Centrality, NBC—Node Betweenness Centrality, NDC—Node Degree Centrality) and to the edges (EBC—Edge Betweenness Centrality and correlations between the biomass of species as nodes), we were able to determine the role of each species in the networks and the relationships between the species. We then used the machine learning ensemble modelling XGBoost—SHAP to identify species that are particularly important in migrations between water bodies and to assess the direction and strength of migrations using Shapley values. Our analyses are based on faunal material from 25 lakes (mesotrophic, eutrophic, dystrophic) and 31—post-exploitation water bodies (clay pits and gravel pits) in northern Poland, in the Masurian Lake District. We found a total of 169 species representing different ecological and functional components. We have shown that the structures of the network between the biomass of species in the analysed five water types differ significantly. The highest value for network density was recorded in eutrophic lakes and clay ponds, the lowest in dystrophic lakes. In eutrophic lakes these are mainly eurybionts, in clay pits–rheophiles and in gravel pits–argilophiles and tyrphophiles. The relationship between the species with the highest NBC and EBC values is particularly important in order to maintain the stability of the network. The periphery of the network usually consists of larger predators that do not compete with each other. By analysing the migration directions of beetles between different ecosystems, we were able to demonstrate a greater affinity of the beetle fauna, especially the argilophiles (e.g. Scarodytes halensis and Laccobius minutus) inhabiting gravel pits, to dystrophic lakes. The beetles in clay pits originate mainly from mesotrophic lakes. These are mainly rheophiles, mostly weakly flying species, such as: Haliplus fluviatilis, Haliplus fulvus, Ilybius fenestratus, Hygrotus vericolor and Haliplus flavicollis. These species are important for the stability of ecological networks in the studied lake types. Their movements between the ecosystems studied in turn contribute to the functional connectivity between the individual lakes, which ensures the stabilisation of biotic relationships at the landscape level. At the same time, they generally also indicate the optimisation of environmental conditions in post-exploitation water bodies, which makes them potential substitute habitats for natural lakes.