Ta Solutions (China)

To assess the performance of an AI algorithm, an independent dataset is needed that matches the intended clinical claim and intended population (e.g., patient characteristics) for which the algorithm is meant. Using all available data for performance assessment may not be practical or optimal; to reduce the risk of sampling bias, the user is expected to utilize training and test data that are representative of the intended population. This work outlines a computational method for task-based sampling of data from a large repository and demonstrates its use, utilizing demographic characteristics and disease states as examples of the clinical attributes to match to an intended population. To run our developed task-based sampling algorithm, the user defines the initial cohort from which to sample, a target distribution profile, and a maximum allowable deviation in any subcategory. The functionality and results of the developed workflow are described in the context of sampling the Medical Imaging and Data Resource Center (MIDRC) data commons for algorithm performance assessment. An initial cohort of over 4000 patients was selected from the MIDRC public data commons. The task-based sampling algorithm was used to select samples matched to an approximate CDC demographic distribution with maximum allowable deviations of 5% and 10%. Resulting final cohorts of 542 and 870 unique patients with average clinical attribute differences of 1.0% and 2.1% were sampled, respectively. This investigation demonstrates that the developed task-based sampling algorithm can generate matched samples from a large dataset for reducing sampling bias in algorithm training and performance assessment.

Retrospective Cohort. This study aimed to: (1) compare opioid use between primary and revision fusion patients; (2) evaluate differences in non-opioid analgesic use; and (3) identify risk factors of long-term opioid consumption. Preoperative opioid exposure and revision surgery are recognized risk factors for prolonged postoperative opioid use after lumbar fusion, yet long-term data remain limited. Patients who underwent elective 1-3 level lumbar spine fusion between were retrospectively identified and chart reviewed (2018-2023). Opioid and non-opioid prescription data was extracted from the state prescription drug monitoring program (PDMP) at 30 days, 90 days, 1 year, and 2 years. Patients were stratified into primary versus revision fusion cohorts and compared using bivariate and multivariable analyses. A total of 1,938 patients were analyzed (1,498 primary, 440 revision). Revision patients had greater preoperative opioid morphine milligram equivalent (MME) burden (953 vs. 334, P<0.001). Postoperatively, opioid use rates were similar through 30 days, but revision patients demonstrated higher MME use at 90 days (428 vs. 219, P<0.001), 1 year (1,142 vs. 382, P<0.001), and 2 years (1,550 vs. 497, P<0.001). Gabapentinoid use was also higher in revision patients beginning at 90 days (19.3% vs. 13.4%, P=0.003). Multivariable regression confirmed preoperative MME as the strongest risk factor of long-term opioid burden. Revision status was independently associated with higher MME use at 1 year (β=348.3, P=0.011) and 2 years (β=964.4, P<0.001), but not at 90 days. Revision lumbar fusion patients demonstrate a greater pre- and postoperative opioid burden, and a greater postoperative gabapentinoid burden. Multivariable analysis confirms revision status as an independent risk factor of greater long-term MME use, beginning at 1 year. Together these findings suggest a complex, possibly neuropathic pain phenotype in revision patients, underscoring the need for tailored perioperative counseling and consistent long-term, multidisciplinary pain management.

Evidence related to anemia in early pregnancy, and its resolution or persistence by late pregnancy, is limited. We evaluated pregnancy outcomes associated with anemia in early pregnancy and resolution compared with persistence in late pregnancy. We used the Merative™ Marketscan ® Commercial Database of nationwide insurance claims (2018-2023) and included pregnant individuals without hereditary anemias. We used hemoglobin and hematocrit to identify anemia in early pregnancy (before 14 weeks of gestation) and late pregnancy (at or after 24 weeks of gestation). Pregnancy outcomes included preeclampsia, placenta previa, placental abruption, severe postpartum hemorrhage, blood products transfusion, cesarean birth, nontransfusion severe maternal morbidity (SMM), spontaneous preterm birth, medically indicated preterm birth, and small-for-gestational-age (SGA) birth weight. We used modified Poisson regression to estimate associations between: 1) anemia in early pregnancy and pregnancy outcomes; and 2) anemia resolution by late pregnancy and pregnancy outcomes, adjusting for confounders by inverse probability weighting. Among 73,586 individuals, 4.4% (95% CI, 4.3-4.6%) had anemia in early pregnancy. Early pregnancy anemia was associated with higher risk of each outcome assessed, with the exception of placenta previa, with the highest associated risk of blood products transfusion (2.4% vs 0.8%; adjusted risk ratio [aRR] 2.45; 95% CI, 1.91-3.13). Of those with early pregnancy anemia and laboratory values in late pregnancy (72.1%), 53.4% had persistent anemia and 46.6% had resolved anemia. Persistent anemia was associated with nontransfusion SMM (2.6% vs 1.1%, aRR 1.64; 95% CI, 1.13-2.37), blood products transfusion (2.9% vs 0.8%, aRR 2.60; 95% CI, 1.84-3.69), and SGA birth weight (8.5% vs 6.8%, aRR 1.23; 95% CI, 1.01-1.50), compared with those without anemia in the first trimester. The resolution of anemia by late pregnancy was not associated with nontransfusion SMM (1.6% vs 1.1%; aRR 1.07; 95% CI, 0.65-1.74) but was associated with blood products transfusion (1.6% vs 0.8%; aRR 1.64; 95% CI, 1.01-2.67) and SGA birth weight (10.0% vs 6.8%; aRR 1.38; 95% CI, 1.15-1.67) compared with those without anemia in the first trimester. Anemia in the first trimester was associated with adverse maternal and neonatal outcomes. The resolution of anemia by late pregnancy eliminated the association with nontransfusion SMM but not other outcomes, emphasizing the importance of treating anemia in early pregnancy and before pregnancy.

VibeOps is a next-generation spacecraft operations co-pilot that combines a Natural User Interface with a self-hosted large language model (LLM) stack to assist operators during live ground contact passes and between-pass analysis. The system ingests streaming telemetry, procedures, and mission configuration data to expose high-level semantic intents that are translated into platform-specific control actions. A multi-agent architecture orchestrates subsystem-specific experts running on a cost-effective on-premises workstation. Retrieval-augmented grounding, schema-constrained function calls, and mandatory human approval are used to ensure safety for command sequencing. This paper presents the VibeOps Minimum Viable Product (MVP) architecture, the ground-segment integration strategy, and an evaluation methodology focused on shadow-mode operation for the LUR-1 mission. We relate the work to prior autonomy heritage, including Mars rover systems and recent LLM-based operator agents, and outline a development roadmap toward supervised in-orbit demonstrations using the LUR-1 and UND ROADS spacecraft.

The latest study sheds light on distributed ledger technologies (DLTs) outside blockchain systems. The first section of this article introduces DLTs, focusing on blockchain as the main paradigm. It highlights three critical characteristics of blockchain: decentralisation, transparency, and security, and emphasises how blockchain is transforming various industries, including supply chain management and finance. Subsequently, the discussion shifts to new developments and approaches in the DLT space. It introduces next-generation ledgers designed to address traditional blockchains' scalability, energy efficiency, and interoperability challenges. The study delves into modern innovations that achieve higher transaction speeds and greater flexibility, such as hybrid models and directed acyclic graphs (DAGs). A significant portion is dedicated to how these advanced DLTs are used to transform sectors like healthcare government, secure patient data management, and enhance transparency and citizen participation. The article also addresses the challenges and ethical considerations of using these technologies. Finally, the paper predicts that DLTs will improve efficiency and innovation in industries outside blockchain technology. To maximise these new technologies' potential, research and interdisciplinary collaboration are essential.

This study employs an industry-specific patent classification methodology (ISPCM) and conducts complex network analysis across temporal, industrial, and spatial dimensions to examine China’s new energy vehicle (NEV) patent collaboration network and to uncover the mechanisms underlying China’s global rise in the NEV sector. The results demonstrate the effectiveness of the ISPCM and reveal a three-phase growth pattern that is driven by policy initiatives and market expansion. Domestic entities dominate the patent landscape, with a noticeable shift from invention patents to utility model patents, which reflects a focus on application-oriented innovation. The collaboration network exhibits a heavy-tailed characteristic, and it forms an oligopolistic structure in which state-owned enterprises (SOEs) act as “innovation orchestrators,” while private firms concentrate on specialized R&amp;D. Across the industrial chain, the component segment forms the largest network, the complete vehicle segment comprises the smallest network, and the aftermarket is clustered around battery recycling. A clear divide between domestic and foreign entities suggests potential decoupling risks. The findings reveal a dual-circulation innovation model that combines state-led coordinated research with market-driven independent research, offering valuable insights for sustainable industrial transformation.

Getters have been used since the invention of the vacuum tube to bind undesirable gases in vacuum systems. They are still used today in many high-reliability electronics applications. Traditional getters are open loop systems: packaged device failure may be the first sign that the getter has saturated. Some getter materials experience a change in their electrochemical properties as that bind water vapor or other gases, making their status electrically detectable. This was previously demonstrated using a polyimide PCB with an IDE sensing structure that was placed inside the sealed package with the commercially available getter attached to it. Although this design worked well, it required the addition of the sensing PCB to the sealed package. To alleviate this issue, the PCB was replaced with the sensing IDE structure AM printed onto the package lid to which the getter would be attached. The electronics inside the package would then monitor the getter status. This was successfully demonstrated using an alumina substrate for the package lid, with an AM printed silver ink IDE structure, and an adhesive backed commercially available moisture getter. A 6 day humidity chamber soak resulted in a 2.4% decrease in measurable sensor capacitance.

The effect of stress relieving and substrate preheating on the grain refinement of additively manufactured Ti‐6Al‐4V at room and elevated temperatures is investigated. Specimens are produced using wire‐based directed energy deposition under vacuum conditions. The microstructure is characterized by scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and X‐ray diffraction (XRD). Tensile tests are conducted at room temperature and at 700 °C. The as‐deposited specimens exhibit a heterogeneous microstructure consisting of fine acicular α′‐martensite and fine Widmanstätten structures. Substrate preheating at 600 °C enables a complete transition from a columnar grain structure in the as‐deposited condition to a refined prior‐β grain structure. The as‐substrate‐heated specimens show the highest tensile strength of 1010 MPa with 3% elongation at room temperature and 600 MPa with 15% elongation at 700 °C.