Dirac t-Boron Nitride Monolayer as an Appealing Binder-Free Anode for Alkali Metal Ion Batteries.

The development of universal anode materials with superlative electrochemical performance poses a great challenge for rechargeable alkali metal (AM) ion battery technologies. In the present work, the viability of the gapless Dirac t-BN (tetragonal boron nitride) monolayer as a lightweight binder-free anode has been systematically evaluated via comprehensive first-principles calculations. Aside from the desirable electronic conductivity, the t-BN monolayer exhibits an excellent ionic conductivity as well due to its moderate affinity for Li, Na, and K atoms with favorable in-plane barriers of 0.36, 0.18, and 0.19 eV, respectively. Meanwhile, the presence of B4N4 octagons allows the AM atoms to penetrate through the t-BN monolayer. Excitingly, the host material delivers an ultrahigh specific capacity up to 1080 mA h g-1 for Li, 5400 mA h g-1 for Na, and 2160 mA h g-1 for K in the wake of low mean open-circuit voltages of 0.033, 0.203, and 0.300 V at the half-cell level. According to the standard hydrogen electrode methodology, the energy densities are forecasted to be as large as 3240, 13500, and 5680 mW h g-1 for Li, Na, and K ion batteries, respectively, with robust thermal stability up to at least 400 K. The safety and cycling durability of the t-BN monolayer are jointly corroborated via the moderate mechanical strengths and ab initio molecular dynamics simulations at the maximum intercalated states, as well as via the small lattice changes and its ultrahigh tolerable ultimate tensile strain. These findings unambiguously promise that the t-BN monolayer can serve as an appealing candidate for anode applications in AM ion batteries.

Conformational and static properties of tagged chains in solvents: effect of chain connectivity in solvent molecules.

Polymer chains immersed in different solvent molecules exhibit diverse properties due to multiple spatiotemporal scales and complex interactions. Using molecular dynamics simulations, we study the conformational and static properties of tagged chains in different solvent molecules. Two types of solvent molecules were examined: one type consisted of chain molecules connected by bonds, while the other type consisted of individual bead molecules without any bonds. The only difference between the two solvent molecules lies in the chain connectivity. Our results show a compression of the tagged chains with the addition of bead or chain molecules. Chain molecule confinement induces a stronger compression compared to bead molecule confinement. In chain solvent molecules, the tagged chain's radius of gyration reached a minimum at a monomer volume fraction of ∼0.3. Notably, the probability distributions of chain size remain unchanged at different solvent densities, irrespective of whether the solvent consists of beads or polymers. Furthermore, as solvent density increases, a crossover from a unimodal to a bimodal distribution of bond angles is observed, indicating the presence of both compressed and expanded regions within the chain. The effective monomer-solvent interaction is obtained by calculating the partial radial distribution function and the potential of the mean force. In chain solvents, the correlation hole effect results in a reduced number of nearest neighbors around tagged monomers compared to bead solvents. The calculation of pore size distribution reveals that the solvent nonhomogeneity induced by chain connectivity leads to a broader distribution of pore sizes and larger pore dimensions at low volume fractions. These findings provide a deeper understanding of the conformational behavior of polymer chains in different solvent environments.

Activity-induced stiffness, entanglement network and dynamic slowdown in unentangled semidilute polymer solutions.

Active polymers possess numerous unique properties that are quite different from those observed in the system of small active molecules due to the intricate interplay between their activity and topological constraints. This study focuses on the conformational changes induced by activity, impacting effective stiffness and crucially influencing entanglement and dynamics. When the two terminals of a linear chain undergo active modification through coupling to a high-temperature thermal bath, there is a substantial increase in chain size, indicating a notable enhancement in effective stiffness. Unlike in passive semiflexible chains where stiffness predominantly affects local bond angles, activity-induced stiffness manifests at the scale of tens of monomers. While activity raises the ambient temperature, it significantly decreases diffusion by over an order of magnitude. The slowdown of the dynamics observed can be attributed to increased entanglement due to chain elongation.

An effective and efficient model of the near-field hydrodynamic interactions for active suspensions of bacteria.

Near-field hydrodynamic interactions in active fluids are essential to determine many important emergent behaviors observed, but have not been successfully modeled so far. In this work, we propose an effective model capturing the essence of the near-field hydrodynamic interactions through a tensorial coefficient of resistance, validated numerically by a pedagogic model system consisting of an Escherichia coli bacterium and a passive sphere. In a critical test case that studies the scattering angle of the bacterium-sphere pair dynamics, we prove that the near-field hydrodynamics can make a qualitative difference even for this simple two-body system: Calculations based on the proposed model reveal a region in parameter space where the bacterium is trapped by the passive sphere, a phenomenon that is regularly observed in experiments but cannot be explained by any existing model. In the end, we demonstrate that our model also leads to efficient simulation of active fluids with tens of thousands of bacteria, sufficiently large for investigations of many emergent behaviors.

Reconstruction Strategy for Upper Extremity Defects After Bone Tumor Resection Based on 3D Customized Bone Cement Mold.

BACKGROUND: Reconstructing bone defects in the upper extremities and restoring their functions poses a significant challenge. In this study, we describe a novel workflow for designing and manufacturing customized bone cement molds using 3D printing technology to reconstruct upper extremity defects after bone tumor resection. METHODS: Computer tomography data was acquired from the unaffected upper extremities to create a detachable mold, which can be customized to fit the joint precisely by shaping the bone cement accordingly. Fourteen patients who underwent reconstructive surgery following bone tumor resection in the proximal humerus (13 cases) or distal radius (1 case) between January 2014 and December 2022 were retrospectively evaluated. The medical records of this case series were reviewed for the demographic, radiological, and operative data. Metastasis, local recurrence, and complication were also reviewed. Additionally, Musculoskeletal Tumor Society Score (MSTS) and Visual Analogue Scale (VAS) were used to assess clinical outcomes. RESULTS: The mean follow-up period was 49.36 ± 15.18 months (range, 27-82 months). At the end of follow-up, there were no cases of metastasis or recurrence, and patients did not experience complications such as infection, dislocation, or implant loosening. Two cases complicated with subluxation (14.3%), and 1 case underwent revision surgery for prosthetic fracture (7.1%). The average MSTS score was 23.2 ± 1.76 (77.4%, range, 66.7%-86.7%), and the postoperative VAS score was 1.86 ± 1.03 (range, 1-4), which was significantly lower than that before surgery (average preoperative VAS score was 5.21 ± 2.00 (range, 2-8)) (P < .001). CONCLUSION: Customized 3D molds can be utilized to shape bone cement prostheses, which may serve as a potential alternative for reconstructing the proximal humerus and distal radius following en bloc resection of bone tumors. This reconstruction strategy offers apparent advantages, including precise matching of articular surfaces and comparatively reduced costs.

Horizontal inequity trends of health care utilization in rural China after the medicine and healthcare system reform: based on longitudinal data from 2010 to 2018.

BACKGROUND: To assess the effectiveness of China's medicine and health care reform in promoting equity in health care utilization among rural residents, it is necessary to analyze temporal trends in equity in health care utilization among rural residents in China. This study is the first to assess horizontal inequity trends in health care utilization among rural Chinese residents from 2010 to 2018 and provides evidence for improving government health policies. METHODS: Longitudinal data obtained from China Family Panel Studies from 2010 to 2018 were used to determine trends in outpatient and inpatient utilization. Concentration index, concentration curve, and horizontal inequity index were calculated to measure inequalities. Decomposition analysis was applied to measure the contribution of need and non-need factors to the unfairness. RESULTS: From 2010 to 2018, outpatient utilization among rural residents increased by 35.10%, while inpatient utilization increased by 80.68%. Concentration indices for health care utilization were negative in all years. In 2012, there was an increase in the concentration index for outpatient utilization (CI = -0.0219). The concentration index for inpatient utilization decreased from -0.0478 in 2010 to -0.0888 in 2018. Except for outpatient utilization in 2012 (HI = 0.0214), horizontal inequity indices for outpatient utilization were negative in all years. The horizontal inequity index for inpatient utilization was highest in 2010 (HI = -0.0068) and lowest in 2018 (HI = -0.0303). The contribution of need factors to the inequity exceeded 50% in all years. CONCLUSIONS: Between 2010 and 2018, low-income groups in rural China used more health services. This seemingly pro-poor income-related inequality was due in large part to the greater health care need among low-income groups. Government policies aimed at increasing access to health services, particularly primary health care had helped to make health care utilization in rural China more equitable. It is necessary to design better health policies for disadvantaged groups to reduce future inequities in the use of health services by rural populations.

Piezoelectricity and valley polarization in a semilithiated 2H-TiTe2 monolayer with near room-temperature ferromagnetism.

Two-dimensional ferromagnetic semiconductors with coupled valley physics and piezoelectric responses offer unprecedented opportunities to miniaturize low-power multifunctional integrated devices. Prompted by epitaxial fabrication of nonmagnetic 2H-TiTe2 monolayer on the Au(111) substrate, we predict through both density functional theory and Monte Carlo simulations that the semilithiated 2H-TiTe2 monolayer (Li@2H-TiTe2) is a stable near room-temperature semiconducting ferromagnet. Under an out-of-plane magnetization, Li@2H-TiTe2 exhibits a clean valley polarization up to 160 meV in its conduction band and a valley-contrasting Berry curvature due to the broken inversion and time-reversal symmetries, in favor of achievable anomalous valley Hall effect. Alternatively, the simultaneous charge, spin, valley Hall currents can be realized as well in the ferromagnetic system with circularly polarized light. Furthermore, the missing mirror symmetry generates a scarce vertical piezoelectricity as large as 0.89 pm V-1. These findings indicate that asymmetric surface functionalization by Li deposition on the 2H-TiTe2 monolayer opens up a vital avenue to predesign superior and tailored multifunctional materials.

An artificial intelligence model that automatically labels roux-en-Y gastric bypasses, a comparison to trained surgeon annotators.

INTRODUCTION: Artificial intelligence (AI) can automate certain tasks to improve data collection. Models have been created to annotate the steps of Roux-en-Y Gastric Bypass (RYGB). However, model performance has not been compared with individual surgeon annotator performance. We developed a model that automatically labels RYGB steps and compares its performance to surgeons. METHODS AND PROCEDURES: 545 videos (17 surgeons) of laparoscopic RYGB procedures were collected. An annotation guide (12 steps, 52 tasks) was developed. Steps were annotated by 11 surgeons. Each video was annotated by two surgeons and a third reconciled the differences. A convolutional AI model was trained to identify steps and compared with manual annotation. For modeling, we used 390 videos for training, 95 for validation, and 60 for testing. The performance comparison between AI model versus manual annotation was performed using ANOVA (Analysis of Variance) in a subset of 60 testing videos. We assessed the performance of the model at each step and poor performance was defined (F1-score < 80%). RESULTS: The convolutional model identified 12 steps in the RYGB architecture. Model performance varied at each step [F1 > 90% for 7, and > 80% for 2]. The reconciled manual annotation data (F1 > 80% for > 5 steps) performed better than trainee's (F1 > 80% for 2-5 steps for 4 annotators, and < 2 steps for 4 annotators). In testing subset, certain steps had low performance, indicating potential ambiguities in surgical landmarks. Additionally, some videos were easier to annotate than others, suggesting variability. After controlling for variability, the AI algorithm was comparable to the manual (p < 0.0001). CONCLUSION: AI can be used to identify surgical landmarks in RYGB comparable to the manual process. AI was more accurate to recognize some landmarks more accurately than surgeons. This technology has the potential to improve surgical training by assessing the learning curves of surgeons at scale.

Dissecting the cosegregation probability from genome architecture mapping.

Genome architecture mapping (GAM) is a recently developed methodology that offers the cosegregation probability of two genomic segments from an ensemble of thinly sliced nuclear profiles, enabling us to probe and decipher three-dimensional chromatin organization. The cosegregation probability from GAM binned at 1 Mb, which thus probes the length scale associated with the genomic separation greater than 1 Mb, is, however, not identical to the contact probability obtained from Hi-C, and its correlation with interlocus distance measured with fluorescence in situ hybridization is not so good as the contact probability. In this study, by using a polymer-based model of chromatins, we derive a theoretical expression of the cosegregation probability as well as that of the contact probability and carry out quantitative analyses of how they differ from each other. The results from our study, validated with in silico GAM analysis on three-dimensional genome structures from fluorescence in situ hybridization, suggest that to attain strong correlation with the interlocus distance, a properly normalized version of cosegregation probability needs to be calculated based on a large number of nuclear slices (n>103).

Extracting multi-way chromatin contacts from Hi-C data.

There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity and complexity of such contacts, it is challenging to detect and identify them using experiments. Based on an assumption that chromosome structures can be mapped onto a network of Gaussian polymer, here we derive analytic expressions for n-body contact probabilities (n > 2) among chromatin loci based on pairwise genomic contact frequencies available in Hi-C, and show that multi-way contact probability maps can in principle be extracted from Hi-C. The three-body (triplet) contact probabilities, calculated from our theory, are in good correlation with those from measurements including Tri-C, MC-4C and SPRITE. Maps of multi-way chromatin contacts calculated from our analytic expressions can not only complement experimental measurements, but also can offer better understanding of the related issues, such as cell-line dependent assemblies of multiple genes and enhancers to chromatin hubs, competition between long-range and short-range multi-way contacts, and condensates of multiple CTCF anchors.

The influence of cross-regional medical treatment on total medical expenses, medical insurance payments, and out-of-pocket expenses of patients with malignant tumors in Chinese low-income areas.

BACKGROUND: In recent years, due to the increasing number of cross-regional medical patients, countries around the world have issued a series of policies or regulations to reduce their out-of-pocket burden. In this context, this study intended to explore the impact of the Spatio-temporal characteristics of cross-regional medical treatment on total medical expenses, medical insurance payments, and out-of-pocket expenses of patients with malignant tumors in low-income areas. METHODS: This study included 54,904 data of cross-provincial medical treatment of malignant tumor patients insured in Heilongjiang Province, China in 2020. Firstly, Microsoft Excel 2019 and ArcGIS 10.2 were applied to conduct a descriptive analysis of the Spatio-temporal characteristics of their cross-provincial medical treatment. Then, binary and multivariate logistic regression models were used to explore the specific impact of economic level and geographical distance of medical regions on total medical expenses, medical insurance payments, and out-of-pocket expenses. RESULTS: The number of cross-regional medical patients showed a gradual upward trend from February to December, and fell back in January. They were concentrated in regions with high economic level and short distance from the insured region, where were more likely to form the group with high out-of-pocket expenses (AOR = 3.620, P < 0.001; AOR = 1.882, P < 0.001). While this possibility in middle-distance medical regions were less (AOR = 0.545, P < 0.001). Afterwards, two sensitivity analysis methods showed that the results were robust. CONCLUSION: The number of cross-regional medical patients with malignant tumors in low-income areas is affected by seasonal factors, meanwhile, their total medical expenses, actual medical insurance payment levels, and out-of-pocket expenses are all affected by the economic level and geographical distance of medical regions. And the middle-distance medical regions may be the best choice for patients with planned cross-regional medical treatment. These provide some evidence for policymakers to improve the fairness and sustainability of medical security for cross-regional medical patients and reduce their direct economic burden of disease.

Education level has an effect on the recovery of total knee arthroplasty: a retrospective study.

OBJECTIVE: This study aimed to observe the relationship between education level and outcomes after total knee arthroplasty (TKA). METHODS: One thousand two hundred sixty four patients after TKA in our hospital from April 2016 to April 2020 were reviewed. These patients were divided into 4 groups (A who were illiterate, B who had elementary school degree, C who had junior high school degree, D who had senior high school degree or higher) by the educational level, which was blinded to the observers. The postoperative outcomes of KSS score, pain, joint extension and flexion function were observed 1 year after discharged from hospital. RESULTS: Among 1253 patients met the inclusion criteria, the average age was 68.63 years, the average body mass was 57.73 kg. There are no distinctions among 4 groups one day after the surgery. However, the outcomes of the follow up were that, the KSS score was: 77.84 ± 10.635; 80.70 ± 8.956; 87.92 ± 8.123;91.27 ± 8.262, with significant differences (P < 0.05). The mean VAS scores were: 1.97 ± 1.60; 2.07 ± 1.66; 1.197 ± 1.5265, 1.044 ± 1.4662. Patients in Group C and D had significantly less pain than that in Group A and B (P < 0.05). The knee flexion range of motion (ROM) was: 91.21 ± 11.69°; 91.77 ± 11.95°; 102.12 ± 11.38°; 109.96 ± 10.64°, Group D performed best, with significant differences (P < 0.05). The knee extension ROM were: - 2.41 ± 4.49°; - 0.91 ± 2.82°; - 0.83 ± 2.87°; - 0.35 ± 1.60°, with significant difference between Group D and the others (P < 0.05). CONCLUSION: Education level affects the outcomes such as VAS score, KSS score, the extension and flexion ROM of the knee after TKA. The patients with higher education level have better outcomes.

Theory of polymer diffusion in polymer-nanoparticle mixtures: effect of nanoparticle concentration and polymer length.

The dynamics of polymer-nanoparticle (NP) mixtures, which involves multiple scales and system-specific variables, has posed a long-standing challenge on its theoretical description. In this paper, we construct a microscopic theory for polymer diffusion in mixtures based on a combination of the generalized Langevin equation, mode-coupling approach, and polymer physics ideas. The parameter-free theory has an explicit expression and remains tractable on a pair correlation level with system-specific equilibrium structures as input. Taking a minimal polymer-NP mixture as an example, our theory correctly captures the dependence of polymer diffusion on NP concentration and average interparticle distance. Importantly, the polymer diffusion exhibits a power law decay as the polymer length increases at dense NPs and/or a long chain, which marks the emergence of entanglement-like motion. The work provides a first-principles theoretical foundation to investigate dynamic problems in diverse polymer nanocomposites.

Biomechanical Heterogeneity of Living Cells: Comparison between Atomic Force Microscopy and Finite Element Simulation.

Atomic force microscopy (AFM) indentation is a popular method for characterizing the micromechanical properties of soft materials such as living cells. However, the mechanical data obtained from deep indentation measurements can be difficult and problematic to interpret as a result of the complex geometry of a cell, the nonlinearity of indentation contact, and constitutive relations of heterogeneous hyperelastic soft components. Living MDA-MB-231 cells were indented by spherical probes to obtain morphological and mechanical data that were adopted to build an accurate finite element model (FEM) for a parametric study. Initially, a 2D-axisymmetric numerical model was constructed with the main purpose of understanding the effect of geometrical and mechanical properties of constitutive parts such as the cell body, nucleus, and lamellipodium. A series of FEM deformation fields were directly compared with atomic force spectroscopy in order to resolve the mechanical convolution of heterogeneous parts and quantify Young's modulus and the geometry of nuclei. Furthermore, a 3D finite element model was constructed to investigate indentation events located far from the axisymmetric geometry. In this framework, the joint FEM/AFM approach has provided a useful methodology and a comprehensive characterization of the heterogeneous structure of living cells, emphasizing the deconvolution of geometrical structure and the true elastic modulus of the cell nucleus.

The unique role of bond length in the glassy dynamics of colloidal polymers.

Bond length is generally not considered as a controllable variable for molecular polymers. Hence, no experimental, simulation or theoretical research, to our knowledge, has examined the influence of bond length on the glassy dynamics of polymers. Recently, a new class of assembling materials called "colloidal polymers" has been synthesized. These colloidal polymers have advantages over molecular polymers in the visibility and flexibility of tuning, for example, the size and shape of the "monomers", the interaction, and the bond length. Dense suspension of colloidal polymers will become a very promising ideal model system for exploring the fundamental problems in the glass transition of chain "molecules". Here, we study the static structure and activated dynamics of hard-sphere colloidal polymers by generalizing the colloidal nonlinear Langevin equation theory to colloidal polymers. Surprisingly, we find that the bond length plays a critical and unique role in many aspects. For instance, the universal relations of the characteristic local lengths and the activated barrier versus the "degree of supercooling", and the structural relaxation versus local vibrational motion are found to be dependent on bond length and independent of chain length and rigidity. We hope that our findings inspire future experimental and simulation research studies on the glassy dynamics of colloidal polymers.

Glassy dynamics of model colloidal polymers: The effect of "monomer" size.

In recent years, attempts have been made to assemble colloidal particles into chains, which are termed "colloidal polymers." An apparent difference between molecular and colloidal polymers is the "monomer" size. Here, we propose a model to represent the variation from molecular polymer to colloidal polymer and study the quantitative differences in their glassy dynamics. For chains, two incompatible local length scales, i.e., monomer size and bond length, are manifested in the radial distribution function and intramolecular correlation function. The mean square displacement of monomers exhibits Rouse-like sub-diffusion at intermediate time/length scale and the corresponding exponent depends on the volume fraction and the monomer size. We find that the threshold volume fraction at which the caging regime emerges can be used as a rescaling unit so that the data of localization length versus volume fraction for different monomer sizes can gather close to an exponential curve. The increase of monomer size effectively increases the hardness of monomers and thus makes the colloidal polymers vitrify at lower volume fraction. Static and dynamic equivalences between colloidal polymers of different monomer sizes have been discussed. In the case of having the same peak time of the non-Gaussian parameter, the motion of monomers of larger size is much less non-Gaussian. The mode-coupling critical exponents for colloidal polymers are in agreement with that of flexible bead-spring chains.

Brush in the bath of active particles: Anomalous stretching of chains and distribution of particles.

The interaction between polymer brush and colloidal particles has been intensively studied in the last two decades. Here, we consider a flat chain-grafted substrate immersed in a bath of active particles. Simulations show that an increase in the self-propelling force causes an increase in the number of particles that penetrate into the brush. Anomalously, the particle density inside the main body of the brush eventually becomes higher than that outside the brush at very large self-propelling force. The grafted chains are further stretched due to the steric repulsion from the intruded particles. Upon the increase of the self-propelling force, distinct stretching behaviors of the chains were observed for low and high grafting densities. Surprisingly, we find a weak descent of the average end-to-end distance of chains at high grafting density and very large force which is reminiscent of the compression effect of a chain in the active bath.

Theory of activated dynamics and glass transition of hard colloids in two dimensions.

The microscopic nonlinear Langevin equation theory is applied to study the localization and activated hopping of two-dimensional hard disks in the deeply supercooled and glass states. Quantitative comparisons of dynamic characteristic length scales, barrier, and their dependence on the reduced packing fraction are presented between hard-disk and hard-sphere suspensions. The dynamic barrier of hard disks emerges at higher absolute and reduced packing fractions and correspondingly, the crossover size of the dynamic cage which correlates to the Lindemann length for melting is smaller. The localization lengths of both hard disks and spheres decrease exponentially with packing fraction. Larger localization length of hard disks than that of hard spheres is found at the same reduced packing fraction. The relaxation time of hard disks rises dramatically above the reduced packing fraction of 0.88, which leads to lower reduced packing fraction at the kinetic glass transition than that of hard spheres. The present work provides a foundation for the subsequent study of the glass transition of binary or polydisperse mixtures of hard disks, normally adopted in experiments and simulations to avoid crystallization, and further, the rheology and mechanical response of the two-dimensional glassy colloidal systems.

Extreme risk spillovers between US and Chinese agricultural futures markets in crises: A dependence-switching copula-CoVaR model.

The linkages between the US and China, the world's two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.

SF-TMN: SlowFast temporal modeling network for surgical phase recognition.

PURPOSE: Automatic surgical phase recognition is crucial for video-based assessment systems in surgical education. Utilizing temporal information is crucial for surgical phase recognition; hence, various recent approaches extract frame-level features to conduct full video temporal modeling. METHODS: For better temporal modeling, we propose SlowFast temporal modeling network (SF-TMN) for offline surgical phase recognition that can achieve not only frame-level full video temporal modeling but also segment-level full video temporal modeling. We employ a feature extraction network, pretrained on the target dataset, to extract features from video frames as the training data for SF-TMN. The Slow Path in SF-TMN utilizes all frame features for frame temporal modeling. The Fast Path in SF-TMN utilizes segment-level features summarized from frame features for segment temporal modeling. The proposed paradigm is flexible regarding the choice of temporal modeling networks. RESULTS: We explore MS-TCN and ASFormer as temporal modeling networks and experiment with multiple combination strategies for Slow and Fast Paths. We evaluate SF-TMN on Cholec80 and Cataract-101 surgical phase recognition tasks and demonstrate that SF-TMN can achieve state-of-the-art results on all considered metrics. SF-TMN with ASFormer backbone outperforms the state-of-the-art Swin BiGRU by approximately 1% in accuracy and 1.5% in recall on Cholec80. We also evaluate SF-TMN on action segmentation datasets including 50salads, GTEA, and Breakfast, and achieve state-of-the-art results. CONCLUSION: The improvement in the results shows that combining temporal information from both frame level and segment level by refining outputs with temporal refinement stages is beneficial for the temporal modeling of surgical phases.