Objective: Endoscopic surgery is a minimally invasive option for effectively addressing lumbar degenerative diseases. This study aimed to describe the specific technology of percutaneous transforaminal endoscopic lumbar foraminotomy (PTELF) as a therapeutic intervention for managing radicular leg pain (RLP) resulting from stable degenerative lumbar isthmic spondylolisthesis (DLIS) and to present the associated clinical results. Methods: From March 2022 and April 2023, 25 patients were diagnosed with single-level stable DLIS with RLP and underwent PTELF. Clinical assessments utilized the visual analog scale (VAS), Oswestry Disability Index (ODI), and modified MacNab criteria. All endoscopic surgery videos were reviewed to interpret the pathology associated with DLIS. Results: The mean age of the cohort was 65.3 ± 11.0 years. The mean preoperative ODI score, VAS score for low back, and VAS score of the leg were 64.1 ± 8.2, 7.0 ± 0.7, and 7.3 ± 0.8, respectively. These scores significantly improved to 16.3 ± 10.4, 2.0 ± 0.6, and 1.7 ± 1.0 at the final follow-up, respectively (P<0.01). The modified MacNab criteria indicated "good" or "excellent" outcomes in 92.0% of cases. Analysis of 23 surgical videos revealed 15 patients with disc herniation, nine with lower vertebral endplate involvement, consistent presence of uneven bone spurs (at the proximal lamina stump and around the foramen), and accumulated scars. Two patients experienced postoperative dysesthesia, and one encountered a recurrence of RLP. Conclusion: PTELF emerges as a potentially safe and effective procedure for alleviating RLP in patients with stable DLIS. However, additional evidence and extended follow-up periods are imperative to evaluate the feasibility and potential risks associated with PTELF.
Irreversible ultrafast events are prevalent in nature, yet their capture in real time poses significant challenges. Traditional single-shot imaging technologies, which utilize a single optical pump and single delayed electron probe, offer high spatiotemporal resolution but fail to capture the entire dynamic evolutions. Here, we introduce a novel imaging method employing a single optical pump and delayed multiple electron probes. This approach, facilitated by an innovative deflector in ultrafast electron microscopy, enables the acquisition of nine frames per exposure, paving the way for statistical and quantitative analyses. We have developed an algorithm that corrects frame-by-frame distortions, realizing a cross-correlation enhancement of â¼26%. Achieving â¼12 nm and 20 ns resolution, our method allows for the comprehensive visualization of laser-induced behaviors in Au nanoparticles, including merging, jumping, and collision processes. Our results demonstrate the capability of this multiframe imaging technique to document irreversible processes across materials science and biology with unprecedented nanometer-nanosecond precision.
Aquatic ecosystems are being increasingly polluted by microplastics (MPs), which calls for an understanding of how MPs affect microbially driven biogenic element cycling in water environments. A 28-day incubation experiment was conducted using freshwater lake water added with three polymer types of MPs (i.e., polyethylene, polypropylene, polystyrene) separately or in combination at a concentration of 1 items/L. The effects of various MPs on microbial communities and functional genes related to carbon, nitrogen, phosphorus, and sulfur cycling were analyzed using metagenomics. Results showed that Sphingomonas and Novosphingobium, which were indicator taxa (genus level) in the polyethylene treatment group, made the largest functional contribution to biogenic element cycling. Following the addition of MPs, the relative abundances of genes related to methane oxidation (e.g., hdrD, frhB, accAB) and denitrification (napABC, nirK, norB) increased. These changes were accompanied by increased relative abundances of genes involved in organic phosphorus mineralization (e.g., phoAD) and sulfate reduction (cysHIJ), as well as decreased relative abundances of genes involved in phosphate transport (phnCDE) and the SOX system. Findings of this study underscore that MPs, especially polyethylene, increase the potential of greenhouse gas emissions (CO2, N2O) and water pollution (PO43-, H2S) in freshwater lakes at the functional gene level.
BACKGROUND: Caffeine, widely recognized as an ergogenic aid, has undergone extensive research, demonstrating its effectiveness to enhance endurance performance. However, there remains a significant gap in systematically evaluating its effects on time trial (TT) performance in cyclists. PURPOSE: This meta-analysis aimed to determine the efficacy of caffeine ingestion to increase cycling TT performance in cyclists and to evaluate the optimal dosage range for maximum effect. METHODS: A search of four databases was completed on 1 December 2023. The selected studies comprised crossover, placebo-controlled investigations into the effects of caffeine ingestion on cycling TT performance. Completion time (Time) and mean power output (MPO) were used as performance measures for TT. Meta-analyses were performed using a random-effects model to assess the standardized mean differences (SMD) in individual studies. RESULTS: Fifteen studies met the inclusion criteria for the meta-analyses. Subgroup analysis showed that moderate doses of caffeine intake (4-6 mg/kg) significantly improved cycling performance (SMD Time = -0.55, 95% confidence interval (CI) = -0.84 ~ -0.26, p < 0.01, I2 = 35%; SMD MPO = 0.44, 95% CI = 0.09 ~ 0.79, p < 0.05, I2 = 39%), while the effects of low doses (1-3 mg/kg) of caffeine were not significant (SMD Time = -0.34, 95% CI = -0.84 ~ 0.17, p = 0.19, I2 = 0%; SMD MPO = 0.31, 95% CI = -0.02 ~ 0.65, p = 0.07, I2 = 0%). CONCLUSION: A moderate dosage (4-6 mg/kg) of caffeine, identified as the optimal dose range, can significantly improve the time trial performance of cyclists, while a low dose (1-3 mg/kg) does not yield improvement. In addition, the improvements in completion time and mean power output resulting from a moderate dose of caffeine are essentially the same in cycling time trails.
Athletic Performance , Bicycling , Caffeine , Performance-Enhancing Substances , Caffeine/administration & dosage , Caffeine/pharmacology , Bicycling/physiology , Humans , Athletic Performance/physiology , Performance-Enhancing Substances/administration & dosage , Performance-Enhancing Substances/pharmacology , Dose-Response Relationship, Drug , Physical Endurance/drug effects
Integer and fractional Chern insulators have been extensively explored in correlated flat band models. Recently, the prediction and experimental observation of fractional quantum anomalous Hall (FQAH) states with spontaneous time-reversal symmetry breaking have garnered attention. While the thermodynamics of integer quantum anomalous Hall (IQAH) states have been systematically studied, our theoretical knowledge on thermodynamic properties of FQAH states has been severely limited. Here, we delve into the general thermodynamic response and collective excitations of both IQAH and FQAH states within the paradigmatic flat Chern-band model with remote band considered. Our key findings include (i) in both ν=1 IQAH and ν=1/3 FQAH states, even without spin fluctuations, the charge-neutral collective excitations would lower the onset temperature of these topological states, to a value significantly smaller than the charge gap, due to band mixing and multiparticle scattering; (ii) by employing large-scale thermodynamic simulations in FQAH states in the presence of strong interband mixing between C=±1 bands, we find that the lowest collective excitations manifest as the zero-momentum excitons in the IQAH state, whereas in the FQAH state, they take the form of magnetorotons with finite momentum; (iii) the unique charge oscillations in FQAH states are exhibited with distinct experimental signatures, which we propose to detect in future experiments.
Chirality plays a crucial role in biology, as it is highly conserved and fundamentally important in the developmental process. To better understand the relationship between the chirality of individual cells and that of tissues and organisms, we develop a generalized mechanics model of chiral polarized particles to investigate the swirling dynamics of cell populations on substrates. Our analysis reveals that cells with the same chirality can form distinct chiral patterns on ring-shaped or rectangular substrates. Interestingly, our studies indicate that an excessively strong or weak individual cellular chirality hinders the formation of such chiral patterns. Our studies also indicate that there exists the influence distance of substrate boundaries in chiral patterns. Smaller influence distances are observed when cell-cell interactions are weaker. Conversely, when cell-cell interactions are too strong, multiple cells tend to be stacked together, preventing the formation of chiral patterns on substrates in our analysis. Additionally, we demonstrate that the interaction between cells and substrate boundaries effectively controls the chiral distribution of cellular orientations on ring-shaped substrates. This research highlights the significance of coordinating boundary features, individual cellular chirality, and cell-cell interactions in governing the chiral movement of cell populations and provides valuable mechanics insights into comprehending the intricate connection between the chirality of single cells and that of tissues and organisms.
Cell Communication , Models, Biological , Cell Communication/physiology , Cell Movement/physiology , Cell Polarity/physiology
Deciphering the complex and redundant process of acute inflammation remains challenging. The failure of numerous clinical trials assessing anti-inflammation agents which had promising preclinical effects inevitably questions the validity of current animal models of inflammation. This study aimed to better understand the process of immune inflammatory response and to select more suitable models to evaluate the effect of potential anti-inflammatory drugs. Zymosan and λ-carrageenan are the most used representatives of particulate and soluble irritants that trigger acute inflammation in the air pouch inflammation model. When zymosan was used, the number of exudate cells first increased at 4 h-8 h, followed by a drop at 12 h-24 h. While, the changes in number of leukocytes in peripheral blood and proportion of neutrophils in bone marrow have the opposite trend. Meanwhile, neutrophils released neutrophil extracellular traps (NETs) to clean zymosan particles. In contrast, the cell migration response to carrageenan increased during 4 h to 24 h, no obvious NETs were observed, and the number of leukocytes in peripheral blood increased and the proportion of neutrophils in bone marrow decreased slightly. This study indicated that although both zymosan and carrageenan are sterile irritants, the characteristics of the inflammatory response induced by each other were different. In the acute phase of inflammation, zymosan-stimulated neutrophils were mobilized, recruited, and engulfed, and then died by NETs. Carrageenan stimulated the production of cytokines/chemokines by neutrophils or macrophages, but did not lead to an obvious death by releasing NETs.
BACKGROUND: Excessive noise levels may decrease patients' sleep quality and increase the risk of sleep disorders in patients. Given that only a few studies have been conducted on noise levels and sleep quality in hospitalized patients, this study investigated the effects of different noise environments on polysomnographic parameters and sleep in hospitalized patients. It also analyzed the factors associated with patients' sleep quality. METHODS: A sample of 244 cases of hospitalized patients were retrospectively selected from March 2020 to March 2023. A total of 122 patients without ward noise reduction treatment were set as the control group. A total of 122 patients who were treated with ward noise reduction were set as the observation group. The polysomnographic monitoring parameters and sleep conditions levels were compared between the two groups, after which logistic regression was used to analyze the relevant factors that affected patients' sleep. RESULTS: The incidence of noise level, rapid eye movement stage (R) phase proportion, nonrapid eye movement stage 1 (N1) phase proportion, and poorer sleep quality all had higher levels in the control group than in the observation group. In comparison, nonrapid eye movement stage 2 (N2) phase proportion, total sleep time (TST), and sleep efficiency (SE) were all lower than those in the observation group (P < 0.05). Regression analysis revealed that the need for surgery, having diabetes mellitus, higher noise level and low N2 percentage levels were all associated factors affecting the sleep quality of patients. CONCLUSION: Environments with higher levels of noise can lead to patients' poorer sleep quality. Thus, it is necessary to actively implement noise management measures to avoid higher noise levels and maintain good sleep quality among patients.
Noise , Polysomnography , Sleep Quality , Humans , Male , Female , Noise/adverse effects , Middle Aged , Retrospective Studies , Adult , Aged , Hospitalization/statistics & numerical data
In the last two decades, there has been a fast-growing prevalence of infertility reported in China. Moreover, Chinese reproductive health has shown a clear decline. Thus, it is imperative to determine the precipitating causes and the root causes of this decline. Environmental and climate risks (ECRs) may cause the decline in reproductive health. Experimental findings have shown that the impact of ECRs on reproductive health can be passed down from both males and females to their offspring, demonstrating an intergenerational and transgenerational lag effect. We perceive that the declined reproductive health may lead to negative demographic consequences in China; therefore, we suggest the following five regulations be implemented: (i) prevent Chinese of childbearing age from exposure to ECRs; (ii) further develop and promote assisted reproductive technology and set up sperm and ovum banks on a national scale; (iii) quantitatively establish the causality between fathers and mothers who suffer from ECRs and the impaired reproductive health in their progeny; (iv) teach ECRs-health knowledge in psychotherapeutic training and continuing education; and (v) propagate and further promote common prosperity.
OBJECTIVE: Spinal cord injury (SCI) is a devastating disease for which there is no safe and effective treatment at present. Daphnoretin is a natural discoumarin compound isolated from Wikstroemia indica with various pharmacological activities. Our study aimed to investigate the role of Daphnoretin in NF-κB pathway activation and inflammatory response after SCI. METHODS: A mouse SCI model was constructed, and the Basso Mouse Scale Score and subscore were used to evaluate the effect of Daphnoretin on the movement capacity of mice. The effect of Daphnoretin on the activation of glial cells in the mouse model and BV2 cells was observed by immunofluorescence. PCR and ELISA were used to detect the expression of inflammatory factors, and Western blot was performed to detect the protein expression associated with NF-κB pathway. RESULTS: Daphnoretin inhibited the loss of movement ability and the activation of glial cells in mice after SCI, and it also inhibited the activation of NF-κB pathway and the expression of inflammatory factors TNF-α and IL-1ß in vivo and in vitro. CONCLUSIONS: Daphnoretin can inhibit the activation of NF-κB pathway and the inflammatory response induced by SCI. Our study demonstrates the potential of Daphnoretin on clinical application for the treatment of SCI.
NF-kappa B , Signal Transduction , Spinal Cord Injuries , Animals , NF-kappa B/metabolism , Mice , Spinal Cord Injuries/metabolism , Spinal Cord Injuries/drug therapy , Signal Transduction/drug effects , Inflammation/metabolism , Inflammation/drug therapy , Spinal Cord Dorsal Horn/metabolism , Spinal Cord Dorsal Horn/drug effects , Disease Models, Animal , Male
In the context of escalating urban heat events due to climate change, air conditioning (AC) has become a critical factor in maintaining indoor thermal comfort. Yet the usage of AC can also exacerbate outdoor heat stress and burden the electricity system, and there is little scientific knowledge regarding how to balance these conflicting goals. To address this issue, we established a coupled modeling approach, integrating the Weather Research and Forecasting model with the building energy model (WRF_BEP + BEM), and designed multiple AC usage scenarios. We selected Chongqing, China's fourth-largest megacity, as our study area due to its significant socioeconomic importance, the severity of extreme heat events, and the uniqueness of its energy infrastructure. Our analysis reveals that AC systems can substantially reduce indoor temperatures by up to 18 °C; however, it also identifies substantial nighttime warming (2-2.5 °C) and a decline in thermal comfort. Particularly for high-density neighborhoods, when we increase 2 °C indoors, the outdoor temperature can be alleviated by up to 1 °C. Besides, despite the limited capacity to regulate peak electricity demand, we identified that reducing the spatial cooled fraction, increasing targeted indoor temperature by 2 °C, and implementing temporal AC schedules can effectively lower energy consumption in high-density neighborhoods, especially the reduction of spatial cooled fraction (up to 50%). Considering the substantial demand for cooling energy, it is imperative to carefully assess the adequacy and continuity of backup energy sources. The study underscores the urgency of reassessing energy resilience and advocates for addressing the thermal equity between indoor and outdoor environments, contributing to the development of a sustainable and just urban climate strategy in an era of intensifying heat events.
Air Conditioning , Climate Change , China , Temperature , Models, Theoretical
The effects of soluble dietary fiber (SDF) from pomegranate peel obtained through enzyme (E-SDF) and alkali (A-SDF) extractions on the structural, physicochemical properties, and in vitro digestibility of sweet potato starch (SPS) were investigated. The expansion degree of SPS granules, pasting viscosity, gel strength and hardness were decreased after adding E-SDF. The setback was accelerated in the presence of A-SDF but E-SDF delayed this effect during the cooling of the starch paste. However, the addition of A-SDF significantly reduced the breakdown of SPS and improved the freeze-thaw stability of starch gels, even at low concentrations (0.1 %), while E-SDF showed the opposite result. The structural characterization of SDF-SPS mixtures showed that A-SDF can help SPS form an enhanced microstructure compared with E-SDF, while polar groups such as hydroxyl group in E-SDF may bind to leached amylose through hydrogen bonding, leading to a decrease in SPS viscoelasticity. In addition, the results of in vitro digestion analysis indicated that A-SDF and E-SDF could decreased the digestibility of SPS and increased the content of resistant starch, especially when 0.5 % E-SDF was added. This study provides a new perspective on the application of SDF from pomegranate peel in improving starch-based foods processing and nutritional characteristics.
The emerging large language models (LLMs) are actively evaluated in various fields including healthcare. Most studies have focused on established benchmarks and standard parameters; however, the variation and impact of prompt engineering and fine-tuning strategies have not been fully explored. This study benchmarks GPT-3.5 Turbo, GPT-4, and Llama-7B against BERT models and medical fellows' annotations in identifying patients with metastatic cancer from discharge summaries. Results revealed that clear, concise prompts incorporating reasoning steps significantly enhanced performance. GPT-4 exhibited superior performance among all models. Notably, one-shot learning and fine-tuning provided no incremental benefit. The model's accuracy sustained even when keywords for metastatic cancer were removed or when half of the input tokens were randomly discarded. These findings underscore GPT-4's potential to substitute specialized models, such as PubMedBERT, through strategic prompt engineering, and suggest opportunities to improve open-source models, which are better suited to use in clinical settings.
BACKGROUND AND AIMS: Improving the care of decompensated cirrhosis is a significant clinical challenge. The primary aim of this trial was to assess the efficacy of a chronic disease management (CDM) model to reduce liver-related emergency admissions (LREA). The secondary aims were to assess model effects on quality-of-care and patient-reported outcomes. APPROACH AND RESULTS: The study design was a 2-year, multicenter, randomized controlled study with 1:1 allocation of a CDM model versus usual care. The study setting involved both tertiary and community care. Participants were randomly allocated following a decompensated cirrhosis admission. The intervention was a multifaceted CDM model coordinated by a liver nurse. A total of 147 participants (intervention=75, control=71) were recruited with a median Model for End-Stage Liver Disease score of 19. For the primary outcome, there was no difference in the overall LREA rate for the intervention group versus the control group (incident rate ratio 0.89; 95% CI: 0.53-1.50, p=0.666) or in actuarial survival (HR=1.14; 95% CI: 0.66-1.96, p=0.646). However, there was a reduced risk of LREA due to encephalopathy in the intervention versus control group (HR=1.87; 95% CI: 1.18-2.96, p=0.007). Significant improvement in quality-of-care measures was seen for the performance of bone density (p<0.001), vitamin D testing (p<0.001), and HCC surveillance adherence (p=0.050). For assessable participants (44/74 intervention, 32/71 controls) significant improvements in patient-reported outcomes at 3 months were seen in self-management ability and quality of life as assessed by visual analog scale (p=0.044). CONCLUSIONS: This CDM intervention did not reduce overall LREA events and may not be effective in decompensated cirrhosis for this end point.
Given that it was a once-in-a-century emergency event, the confinement measures related to the coronavirus disease 2019 (COVID-19) pandemic caused diverse disruptions and changes in life and work patterns. These changes significantly affected water consumption both during and after the pandemic, with direct and indirect consequences on biodiversity. However, there has been a lack of holistic evaluation of these responses. Here, we propose a novel framework to study the impacts of this unique global emergency event by embedding an environmentally extended supply-constrained global multi-regional input-output model (MRIO) into the drivers-pressure-state-impact-response (DPSIR) framework. This framework allowed us to develop scenarios related to COVID-19 confinement measures to quantify country-sector-specific changes in freshwater consumption and the associated changes in biodiversity for the period of 2020-2025. The results suggest progressively diminishing impacts due to the implementation of COVID-19 vaccines and the socio-economic system's self-adjustment to the new normal. In 2020, the confinement measures were estimated to decrease global water consumption by about 5.7% on average across all scenarios when compared with the baseline level with no confinement measures. Further, such a decrease is estimated to lead to a reduction of around 5% in the related pressure on biodiversity. Given the interdependencies and interactions across global supply chains, even those countries and sectors that were not directly affected by the COVID-19 shocks experienced significant impacts: Our results indicate that the supply chain propagations contributed to 79% of the total estimated decrease in water consumption and 84% of the reduction in biodiversity loss on average. Our study demonstrates that the MRIO-enhanced DSPIR framework can help quantify resource pressures and the resultant environmental impacts across supply chains when facing a global emergency event. Further, we recommend the development of more locally based water conservation measures-to mitigate the effects of trade disruptions-and the explicit inclusion of water resources in post-pandemic recovery schemes. In addition, innovations that help conserve natural resources are essential for maintaining environmental gains in the post-pandemic world.
Conventional radar jamming and deception systems typically necessitate the custom design of complex circuits and algorithms to transmit an additional radio signal toward a detector. Consequently, they are often cumbersome, energy-intensive, and difficult to operate in broadband electromagnetic environment. With the ongoing trend of miniaturization of various devices and the improvement of radar system performance, traditional techniques no longer meet the requirements for broadband, seamless integration, and energy efficiency. Time-varying metasurfaces, capable of manipulating electromagnetic parameters in both temporal and spatial domains, have thus inspired many contemporary research studies to revisit established fields. In this paper, we introduce a time-varying metasurface driven radar jamming and deception system (TVM-RJD), which can perfectly overcome the aforementioned intrinsic challenges. Leveraging a programmable bias voltage, the TVM-RJD can alter the spectrum distribution of incident waves, thereby deceiving radar into making erroneous judgments about the target's location. Experimental outcomes affirm that the accuracy deviation of the TVM-RJD system is less than 0.368 meters, while achieving a remarkable frequency conversion efficiency of up to 96.67%. The TVM-RJD heralds the expansion into a wider application of electromagnetic spatiotemporal manipulation, paving the way for advancements in electromagnetic illusion, radar invisibility, etc.
Laser-scanning confocal hyperspectral microscopy is a powerful technique to identify the different sample constituents and their spatial distribution in three-dimensional (3D). However, it suffers from low imaging speed because of the mechanical scanning methods. To overcome this challenge, we propose a snapshot hyperspectral confocal microscopy imaging system (SHCMS). It combined coded illumination microscopy based on a digital micromirror device (DMD) with a snapshot hyperspectral confocal neural network (SHCNet) to realize single-shot confocal hyperspectral imaging. With SHCMS, high-contrast 160-bands confocal hyperspectral images of potato tuber autofluorescence can be collected by only single-shot, which is almost 5 times improvement in the number of spectral channels than previously reported methods. Moreover, our approach can efficiently record hyperspectral volumetric imaging due to the optical sectioning capability. This fast high-resolution hyperspectral imaging method may pave the way for real-time highly multiplexed biological imaging.
Hydrogels capable of swift mechanical energy dissipation hold promise for a range of applications including impact protection, shock absorption, and enhanced damage resistance. Traditional energy absorption in such materials typically relies on viscoelastic mechanisms, involving sacrificial bond breakage, yet often suffers from prolonged recovery times. Here, we introduce a hydrogel designed for friction-based damping. This hydrogel features an internal structure that facilitates the motion of a chain walker within its network, effectively dissipating mechanical stress. The hydrogel network architecture allows for rapid restoration of its damping capacity, often within seconds, ensuring swift material recovery post-deformation. We further demonstrate that this hydrogel can significantly shield encapsulated cells from mechanical trauma under repetitive compression, owing to its proficient energy damping and rapid rebound characteristics. Therefore, this hydrogel has potential for dynamic load applications like artificial muscles and synthetic cartilage, expanding the use of hydrogel dampers in biomechanics and related areas.
The excellent electrical properties of graphene have received widespread attention. However, the difficulty of electron transfer between layers still restricts the application of graphene composite materials to a large extent. Therefore, in this study, graphene/polyimide films were subjected to a Joule heating treatment to improve the electrical conductivity of the film by ~76.85%. After multiple Joule thermal cycle treatments, the conductivity of the graphene/polyimide film still gradually increased, but the increase in amplitude tended to slow down. Finally, after eight Joule heat treatments, the conductivity of the graphene/polyimide film was improved by ~93.94%. The Joule heating treatment caused the polyimide to undergo atomic rearrangement near the interface bonded to the graphene, forming a new crystalline phase favourable for electron transport with graphene as a template. Accordingly, a model of the bilayer capacitive microstructure of graphene/polyimide was proposed. The experiment suggests that the Joule heating treatment can effectively reduce the distance between graphene electrode plates in the bilayer capacitive micro-nanostructures of graphene/polyimide and greatly increases the number of charge carriers on the electrode plates. The TEM and WAXS characterisation results imply atomic structure changes at the graphene/polyimide bonding interface.
Sensors with a small footprint and real-time detection capabilities are crucial in robotic surgery and smart wearable equipment. Reducing device footprint while maintaining its high performance is a major challenge and a significant limitation to their development. Here, we proposed a monolithic integrated micro-scale sensor, which can be used for vector force detection. This sensor combines an optical source, four photodetectors, and a hemispherical silicone elastomer component on the same sapphire-based AlGaInP wafer. The chip-scale optical coupling is achieved by employing the laser lift-off techniques and the flip-chip bonding to a processed sapphire substrate. This hemispherical structure device can detect normal and shear forces as low as 1 mN within a measurement range of 0-220 mN for normal force and 0-15 mN for shear force. After packaging, the sensor is capable of detecting forces over a broader range, with measurement capabilities extending up to 10 N for normal forces and 0.2 N for shear forces. It has an accuracy of detecting a minimum normal force of 25 mN and a minimum shear force of 20 mN. Furthermore, this sensor has been validated to have a compact footprint of approximately 1.5 mm2, while maintaining high real-time response. We also demonstrate its promising potential by combining this sensor with fine surface texture perception in the fields of compact medical robot interaction and wearable devices.
