Rapid Performance Improvement Research Articles

Distinct mechanisms for online and offline motor skill learning across human development.

The human central nervous system (CNS) undergoes tremendous changes from childhood to adulthood and this may affect how individuals at different stages of development learn new skills. Here, we studied motor skill learning in children, adolescents, and young adults to test the prediction that differences in the maturation of different learning mechanisms lead to distinct temporal patterns of motor learning during practice and overnight. We found that overall learning did not differ between children, adolescents, and young adults. However, we demonstrate that adult-like skill learning is characterized by rapid and large improvements in motor performance during practice (i.e., online) that are susceptible to forgetting and decay over time (i.e., offline). On the other hand, child-like learning exhibits slower and less pronounced improvements in performance during practice, but these improvements are robust against forgetting and lead to gains in performance overnight without further practice. The different temporal dynamics of motor skill learning suggest an engagement of distinct learning mechanisms in the human CNS during development. In conclusion, adult-like skill learning mechanisms favor online improvements in motor performance whereas child-like learning mechanisms favors offline behavioral gains. RESEARCH HIGHLIGHTS: Many essential motor skills, like walking, talking, and writing, are acquired during childhood, and it is colloquially thought that children learn better than adults. We investigated dynamics of motor skill learning in children, adolescents, and young adults. Adults displayed substantial improvements during practice that was susceptible to forgetting over time. Children displayed smaller improvements during practice that were resilient against forgetting. The distinct age-related characteristics of these processes of acquisition and consolidation suggest that skill learning relies on different mechanisms in the immature and mature central nervous system.

Advantages of Friend-Modelled Social Interactive Feedforward for VR Exergaming

VR exergaming is a promising motivational tool to incentivise exercise. We present a novel VR exergaming method called social interactive feedforward. The player competes with an 'enhanced model' of one of their friends in a real-time VR environment, showing improved performance levels in a way the player can relate to. Social interactive feedforward was tested in a cycling-based VR exergame and players competed with enhanced models of themselves, their friend, and a stranger moving at the same enhanced pace. Results show that friend-modelled social interactive feedforward improves performance and intrinsic motivation the most. This indicates that the mere association of the enhanced model with their friend results in a rapid improvement in performance and motivation which implies that social feedforward was successfully elicited by using an enhanced friend's model. This widens the application of self-modelled feedforward to a wide range of social options which enables players to also reap the benefits of socialising in addition to feedforward benefits.

Multi-Functional Silole Hole Transport Layer for Efficient and Stable Lead-Tin Perovskite and Tandem Solar Cells.

Despite high theoretical efficiencies and rapid improvements in performance, high-efficiency ≈1.2eV mixed Sn-Pb perovskite solar cells (PSCs) generally rely on poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT: PSS) as the hole transport layer (HTL); a material that is considered to be a bottleneck for long-term stability due to its acidity and hygroscopic nature. Seeking to replace PEDOT: PSS with an alternative HTL with improved atmospheric and thermal stability, herein, a silole derivative (Silole-COOH) tuned with optimal electronic properties and efficient carrier transport by incorporating a carboxyl functional group is designed, which results in an optimal band alignment for hole extraction from Sn-Pb perovskites and robust air and thermal stability. Thin films composed of the Silole-COOH exhibit superior conductivity and carrier mobility compared to PEDOT: PSS, in addition to reduced nonradiative quasi-Fermi-level splitting losses at the HTL/perovskite interface and improved quality of Sn-Pb perovskite. Replacement of PEDOT: PSS with Silole-COOH leads to 23.2%-efficient single-junction Sn-Pb PSCs, 25.8%-efficient all-perovskite tandems, and long operating stability in ambient air.

Abbreviated in-situ inter-professional debriefing simulation training in peri-operative care environments: Minimizing the impact on clinical care using standardized videos

IntroductionOur facility leadership posed questions to the perioperative leadership team regarding the presence of collaborative communication during the reconciliation of events occurring in several perioperative care areas (operating rooms {OR}, clinic procedure areas, Intensive Care Unit {ICU}). Our team* collaborated to pilot a rapid cycle performance improvement project focused on improving the effectiveness of debriefings and handoffs that could conceivably lead to more effective after-action reviews following events which were complicated by multiple simultaneous unexpected factors. We proposed we could implement standardized abbreviated low-fidelity point of care (in-situ) inter-professional simulation training across the healthcare system with minimal impact on clinical schedules. We believed this would improve the perception of teamwork and collaboration among surgical team members. MethodsInter-professional in-situ simulation training exercises were designed and performed in perioperative care areas systemwide at our three major facilities (Main hospital and two Healthcare Community Centers [HCC]). Multiple iterations of styles of training were conceived and trialed. In the end, preconstructed videos were used to standardize the processes that framed the simulation role-playing of a debriefing after a complex situation. These videos contain the pre-simulation pre-briefings, the clinical situation that preceded the clinical debriefing and the simulation debriefing. Successful reconciliation of the multiple events required team members to exercise closed-loop communication, mutual trust, reengagement, and de-escalation of disengaged team members. Anonymous institutional review board reviewed, and Association of Federal Government Employees (AFGE) approved retrospective pre/post implementation surveys were made available to participants immediately after and sixty to ninety days following simulation exercises. ResultsBetween July 2023 and March 2024, one hundred and six staff in the perioperative care areas participated in twenty-two inter-professional simulation trainings (eleven OR, eight clinic, and three ICU simulations). Fourteen simulation scenarios in seven surgical disciplines were created. Eleven videos were produced covering cases in the O.R., clinic and ICU. Ultimately, the simulations were completed within twenty minutes in the three perioperative care clinical areas. Seventy-nine staff responded to the initial surveys after the simulation training. Eighty percent of the respondents gave favorable assessments regarding the effectiveness of the training in improving components of teamwork and agreed this program should continue. ConclusionsThe pilot program affirmed that we could implement simulations across the healthcare system in a format that minimally impacted the staffs’ clinical schedule. The process was standardized through the creation of multiple specialty specific videos. We proposed that perioperative team leadership could utilize these videos in the future to conduct spontaneously arranged simulations when they identified the presence of members naïve to this training and opportunities in the clinical schedule.*Refer to the acknowledgments for construct of our perioperative leadership simulation advisory team

Practice Reshapes the Geometry and Dynamics of Task-tailored Representations.

Extensive practice makes task performance more efficient and precise, leading to automaticity. However, theories of automaticity differ on which levels of task representations (e.g., low-level features, stimulus-response mappings, or high-level conjunctive memories of individual events) change with practice, despite predicting the same pattern of improvement (e.g., power law of practice). To resolve this controversy, we built on recent theoretical advances in understanding computations through neural population dynamics. Specifically, we hypothesized that practice optimizes the neural representational geometry of task representations to minimally separate the highest-level task contingencies needed for successful performance. This involves efficiently reaching conjunctive neural states that integrate task-critical features nonlinearly while abstracting over non-critical dimensions. To test this hypothesis, human participants (n = 40) engaged in extensive practice of a simple, context-dependent action selection task over 3 days while recording EEG. During initial rapid improvement in task performance, representations of the highest-level, context-specific conjunctions of task-features were enhanced as a function of the number of successful episodes. Crucially, only enhancement of these conjunctive representations, and not lower-order representations, predicted the power-law improvement in performance. Simultaneously, over sessions, these conjunctive neural states became more stable earlier in time and more aligned, abstracting over redundant task features, which correlated with offline performance gain in reducing switch costs. Thus, practice optimizes the dynamic representational geometry as task-tailored neural states that minimally tesselate the task space, taming their high-dimensionality.

Abstract P406: Transforming Clinical Practices for Blood Pressure Management in Community Health Centers through Timely Data and Technical Support

Introduction: Blood pressure (BP) control can prevent major adverse cardiac events and is monitored through various means, including the Centers for Medicare and Medicaid Services 165 metric for BP control - an annual reporting metric for community health centers (CHCs) within the Uniform Data System framework that becomes accessible 6 months after the conclusion of the reporting period. In pursuit of more immediate indicators related to BP management, the National Hypertension Control Initiative (NHCI) initiated collaboration with a population health platform to support select CHCs with rapidly available data on 19 BP-related metrics. Hypothesis: With technical support and regular access to data, CHCs can implement timely clinical practice and process changes. Methods: To support CHCs in using the population health platform, NHCI staff provided technical assistance in a rapid cycle performance improvement (RCPI) to 10 interested CHCs. This opportunity allowed CHCs to partner with NHCI staff to review BP related metrics in the population health platform and to identify opportunities for clinical process and practice changes. Over an 8-week period from October to December 2023, 7 CHCs were actively involved in a series of 5-6 structured 30–60-minute meetings with both NHCI registered nurse and quality improvement staff. These meetings reviewed BP metrics, mapped clinical workflows for improvement, and supported data analytics. CHCs often chose 1-2 BP metrics for focus, concentrating on incremental change and short-term improvement. Results: Among participating CHCs that reported, they revealed successful or anticipated adjustments in team responsibilities and clinical processes, including leadership involvement and new methods. Limitations included CHC staff engagement, time, concerns with data reliability, and familiarity with the population health platform. Most reporting CHCs shared that their goals were greatly impacted by access to readily available performance data and that they plan to continue using the population health platform to affect performance moving forward. Conclusions: For participating CHCs, individualized guidance based on timely data may have been helpful in analyzing workflows and procedures, assessing clinical care practices, and implementing quality improvement plans. Frequent data may allow CHCs to make clinical practice and process changes to efficiently measure impact and more quickly improve BP control than standard methods.

The development history and future prospects of artificial intelligence in facial recognition technology

In recent decades, with the fast development of various algorithms and the rapid improvement of computer hardware performance, the development of facial recognition technology has been very rapid. This technology used to only appear in science fiction movies, but now it has been widely used in mobile payments, identity recognition, and other fields, and it also has very reliable performance. This article introduces the different facial recognition methods used in different periods of facial recognition technology from the 1960s and 1970s to the present day, to help people understand the development process of facial recognition technology. Among them, the focus is on early methods based on geometric features, grayscale information, and feature extraction, as well as recent applications based on deep learning and convolutional neural networks. In response to some challenges faced by current technology, some speculations on possible future development directions are proposed.

Hospital Allocation and Racial Disparities in Health Care

Abstract We develop a framework to measure the role of hospital allocation in racial disparities in health care and use it to study Black and white heart attack patients. Black patients receive care at lower-performing hospitals than white patients. However, over two decades, the performance gap between hospitals treating Black and white patients shrank by over two-thirds. This progress is due to more rapid performance improvement at hospitals that tended to treat Black patients rather than reallocation of patients. Hospital improvement is correlated with adoption of a productivity-raising input, beta blockers. Our work highlights reallocation and performance improvement as future disparity-reduction levers.

PPG-based Vital Signs Measurement Using SmartPhone Camera: Review

Due to their growing popularity and rapid performance improvements, smartphones have the potential to be an accurate, low-cost physiological monitoring tool that is useful outside of the clinical setting. Since the cardiac pulse is responsible for the slight color changes in skin, a pulsatile signal that is also known as a photoplethysmographic (PPG) signal can be evaluated by utilizing a digital camera to record a video of your Region Of Interest (ROI). This review Study focuses on several research works that have used PPG-based video smartphone camera methods to measure Heart Rate (HR), Blood Pressure (BP), Oxygen Saturation (SpO2), and Respiratory Rate (RR). Comparing the approaches and results of each study (HR measurement studies produced acceptable findings with error rates less than 5%, BP error rates of results less than 10%, and SpO2 =<3.5%, by comparing the predicted models reading with the standard references reading) shows how smartphone-based physiological monitoring might be used in medical settings.

Impacts of Maternal Nutrition on Sow Performance and Potential Positive Effects on Piglet Performance.

The objectives of this review are to identify the nutritional challenges faced by modern sows and present potential solutions to mitigate excessive maternal tissue loss and reproductive failure as it relates to recent genetic improvements. Current feeding programs have limitations to support the rapid genetic improvements in reproductive performance for modern sows. Since 2012, both litter size at birth and fetal weight have increased by 2.26 pigs per litter and 0.22 kg per piglet, respectively, thereby increasing the nutrient needs for sows during gestation and lactation. Prediction models generated in this review predict that modern sows would need 31% more lysine during gestation when compared with current feeding programs. Physiological challenges facing modern sows are also addressed in this review. High oxidative stress, pelvic organ prolapse, and lameness can directly affect the sow, whereas these physiological challenges can have negative impacts on colostrum and milk quality. In response, there is growing interest in investigating the functional roles of select bioactive compounds as feed additives to mitigate the severity of these challenges. Selenium sources, catechins, and select plant extracts have been utilized to reduce oxidative stress, calcium chloride and phytase have been used to mitigate pelvic organ prolapse and lameness, algae and yeast derivatives have been used to improve colostrum and milk quality, and fiber sources and probiotics have been commonly utilized to improve sow intestinal health. Collectively, this review demonstrates the unique challenges associated with managing the feeding programs for modern sows and the opportunities for revision of the amino acid requirements as well as the use of select bioactive compounds to improve reproductive performance.

The reproductive performance of phosphorus-deficient mature cows improved rapidly when given supplementary phosphorus in the Victoria River District of the Northern Territory

Context There is little published information on how long it takes for the performance of phosphorus (P)-deficient mature cows to improve once they start receiving P supplements, or whether their long-term performance is impaired by P deficiency early in life. Aims The performance of mature P-deficient and P-adequate Brahman cows was compared over 3 years to investigate the time it takes for the performance of P-deficient mature cows to improve once they are supplemented with P, and whether their long-term performance is compromised by P deficiency early in life. Methods Cows that had been a part of a P-supplementation trial at Victoria River Research Station from weaning until they were 5.5 years old were used for this study. One treatment group had received continuous P supplement (P+) since weaning and the other treatment had never received any P supplement (P−). At the conclusion of the original trial, 42 cows were randomly selected from each treatment and then grazed together in the same paddock for 3 years, during which time they were given P supplement continuously. Performance attributes were measured and compared. Key results This study found that P supplementation rapidly improved the liveweight, body condition, reproductive performance and survival rate of the P-deficient (P−) mature cows. Within a year of receiving P supplement, their performance improved to be similar to that of P+ cows. However, P deficiency early in life did have some residual stunting effects, resulting in lower mean hip height and liveweights of P− cows. Conclusions The performance of P-deficient mature cows improved rapidly once they were given P supplements and matched that of cows that had always been supplemented. However, P deficiency early in life caused stunting, resulting in mature cows being shorter and lighter. Implications Cattle producers in P-deficient country should see a rapid improvement in performance and return on investment once they start supplementing P-deficient cows. However, it is better to supplement cattle throughout their lives in P-deficient areas to avoid stunting.

Investigation on buried interfacial charge carrier dynamics of the MAPbI3/NiO interface by mismatch strain and termination

Organic-inorganic halide perovskite solar cells (PSCs) have attracted significant attention due to their low cost, simple fabrication process, and rapid improvement in photovoltaic performance. NiO is often considered as a potential hole transport layer (HTL) in these PSCs owing to its wide band gap and deep valence band level. However, uncertainties remain regarding the interfacial charge carrier dynamics at the perovskite/HTL interface induced by the interfacial mismatch strain and terminal configuration. Herein, typical MAPbI3/NiO interfacial terminal configurations (MAI-Ni, MAI-O, PbI-Ni, PbI-O) with strain-configured interfaces were explored by first-principle and device simulation. The results indicate that the binding energy decreases, the carrier transport efficiency increases, and the valence band offset (VBO) decreases as the interfacial atomic configuration of the perovskite surface changes from MAI to PbI. Meanwhile, the compressive strain applied on the perovskite surface also increases the interfacial VBO. The J-V curves and energy band of the PSCs show that the device performance tends to enhance first and then decrease as the positive VBO of the MAPbI3/NiO interface increases. Thus, the strain and termination configuration could modulate the device's photovoltaic performance, which is dependent on the energy band bending caused by the strain and termination configuration. This work provides a valuable understanding of the MAPbI3/NiO interface and contributes new strategies to interface optimization for further improving the photoelectric conversion efficiency of PSCs.

XAI SHAP 기반 토지 피복 구성에 따른 지표면 온도의 영향 분석

Recently, with the development of artificial intelligence architecture and the rapid improvement of hardware performance, various artificial intelligence models are attracting attention and their usefulness are increasing. However, unlike the rate of development of performance, the development of model's explanatory ability is slow to progress. The increasingly complex decision branching points of AI models are increasing exponentially, which hinders researchers' ease of model interpretation. Explainable Artificial Intelligence, XAI has emerged to solve the above complexity, and helps to improve interpretability and reliability by decomposing the black box of the model to a level that researchers can understand. This study estimates the surface temperature of a specific spatial unit using land cover data of a cell unit in Korea, Seoul. The limitations of the existing statistical model for high-dimensional data were examined, and the estimation results were compared using a machine learning model. Models used include Lasso regression(Least absolute linkage and selection operator), random forest regression, and XGBoost (eXtreme Gradient Boosting) regression. Finally, based on the fitted result of the XGBoost regression model, XAI SHAP was carried out.

Generalization of procedural motor sequence learning after a single practice trial

When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments (N = 2095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0–30 s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill.

Experiment study on heat transfer enhancement of micro heat pipe PV/T by Reynolds number improvement

The rapid performance improvement of photovoltaic/thermal (PV/T) implies great potential application to various aspects of society. The previously developed micro heat pipe PV/T by our team has shown favorable cogeneration of electricity and heat in cold regions, while it is badly needed to improve its comprehensive performance by enhancement of heat transfer. For same working fluid as HCFC141b in micro heat pipe, higher Reynolds Number (Re) theoretically means better heat transfer. Therefore, two available micro heat pipes were developed with trapezoidal cross section and rectangular cross section respectively while with same cross section area and applied in two micro heat pipe PV/T systems. Subsequent experiment study testifies that the rectangular micro heat pipe PV/T of higher theoretical Re verily shows more favorable performance than the trapezoidal micro heat pipe PV/T when they are at 45° inclination angle. Deducting power consumption of circulating pump, the average electrical efficiency of rectangular micro heat pipe PV/T system is 12.4%, while that of trapezoidal micro heat pipe PV/T system is 11.9%. Moreover, the thermal efficiency, total energy power, and total energy efficiency of rectangular micro heat pipe PV/T system are respectively 28.1%, 472.3 W, and 40.5%, which are 10.1%, 119.8 W, and 10.8% higher than those of trapezoidal micro heat pipe PV/T system. The results are significant and valuable for the application of micro heat pipe PV/T in cold regions.

Sandwich self-heating structure-based lithium-ion battery system and its application in the fuel cell bus for Beijing Winter Olympic Games

Hydrogen fuel cell vehicles (HFCVs), consisting of dual energy sources of fuel cell system (FCS) and lithium-ion battery system (LIBS), have become the technological frontier of electric vehicles due to the advantages of no mileage anxiety, fast hydrogen refueling, and zero emissions. However, the deterioration of battery performance at low temperatures makes it difficult to start the FCS and seriously hinders the application range of HFCVs. Herein, a sandwich self-heating structure-based LIBS is proposed to realize rapid self-heating and performance recovery of the LIBS without relying on external energy and achieve a fast cold start of the HFCV at extremely low temperatures. Furthermore, the proposed LIBS were successfully applied to all fuel cell buses in the core area of the 2022 Beijing Winter Olympic Games in batches. Firstly, compared with the mainstream heating methods, this sandwich self-heating structure has the advantages of fast heating speed (5.9 °C/min), high heating efficiency (78.75 %), and good temperature uniformity. More importantly, this structure has a small impact on the life and energy density of the LIBS. Secondly, in response to the severe road conditions in the Winter Olympic Games area, we matched the FCS and sandwich self-heating LIBS parameters based on multi-objective optimization and realized fast cold start and rapid performance improvement of fuel cell buses. Thirdly, the sandwich self-heating structure can realize the cold start of FCS with a smaller LIBS, which provides a new possibility to reduce the cost and light weight of HFCVs. Finally, the configuration is also applicable to pure electric vehicles, showing great application potential.

Cathodes for Electrochemical Carbon Dioxide Reduction to Multi-Carbon Products: Part II

This is Part II of a focused review of recent highlights in the literature in cathode development for low temperature electrochemical carbon dioxide and carbon monoxide reduction to multi-carbon (C2+) products. Part I () introduced the role of CO2 reduction in decarbonising the chemical industry and described the catalysts and modelling approaches. Part II describes in situ characterisation to improve the understanding and development of catalysts, the catalyst layer and the gas diffusion layer.

A Novel Turbo Detector Design for a High-Speed SSVEP-Based Brain Speller

The past decade has witnessed the rapid development of brain-computer interfaces (BCIs). The contradiction between communication rates and tedious training processes has become one of the major barriers restricting the application of steady-state visual-evoked potential (SSVEP)-based BCIs. A turbo detector was proposed in this study to resolve this issue. The turbo detector uses the filter bank canonical correlation analysis (FBCCA) as the first-stage detector and then utilizes the soft information generated by the first-stage detector and the pool of identified data generated during use to complete the second-stage detection. This strategy allows for rapid performance improvements as the data pool size increases. A standard benchmark dataset was used to evaluate the performance of the proposed method. The results show that the turbo detector can achieve an average ITR of 130 bits/min, which is about 8% higher than FBCCA. As the size of the data pool increases, the ITR of the turbo detector could be further improved.

Weed detection to weed recognition: reviewing 50 years of research to identify constraints and opportunities for large-scale cropping systems

AbstractThe past 50 yr of advances in weed recognition technologies have poised site-specific weed control (SSWC) on the cusp of requisite performance for large-scale production systems. The technology offers improved management of diverse weed morphology over highly variable background environments. SSWC enables the use of nonselective weed control options, such as lasers and electrical weeding, as feasible in-crop selective alternatives to herbicides by targeting individual weeds. This review looks at the progress made over this half-century of research and its implications for future weed recognition and control efforts; summarizing advances in computer vision techniques and the most recent deep convolutional neural network (CNN) approaches to weed recognition. The first use of CNNs for plant identification in 2015 began an era of rapid improvement in algorithm performance on larger and more diverse datasets. These performance gains and subsequent research have shown that the variability of large-scale cropping systems is best managed by deep learning for in-crop weed recognition. The benefits of deep learning and improved accessibility to open-source software and hardware tools has been evident in the adoption of these tools by weed researchers and the increased popularity of CNN-based weed recognition research. The field of machine learning holds substantial promise for weed control, especially the implementation of truly integrated weed management strategies. Whereas previous approaches sought to reduce environmental variability or manage it with advanced algorithms, research in deep learning architectures suggests that large-scale, multi-modal approaches are the future for weed recognition.

The dark side of political promotion incentives: Evidence from firm performance

This paper evaluates Chinese state-owned enterprises (SOEs) to examine the influence of the CEO political promotion incentive (PPI) on the long-term performance and performance volatility of their firm. Empirical tests demonstrate that CEO PPI is negatively correlated with long-term performance because CEOs favor investment over innovation to cater to the government. Moreover, CEO PPI is positively correlated with performance volatility because the rapid performance improvement adopted over a short period to achieve political promotion are usually followed by a subsequent decline. Further analyses suggest that foreign institutional investors play a key role in alleviating the negative impact of CEO PPI.