Goalkeepers benefit from using deceptive actions in the soccer penalty kick.

Most studies on deception in soccer penalty kicks have focused on the deceptive actions used by penalty takers. However, it is worth noting that deception can also be played out by goalkeepers. To examine the effectiveness of goalkeepers' deceptive actions in professional competition, we analysed 714 penalty kicks taken during matches in the English Premier League and German Bundesliga, spanning the seasons from 2016-2017 to 2019-2020. We scored whether goalkeepers used deception, and if so, what type of deception, the outcome of the penalty and the kicking strategy of the penalty taker. The results showed that goalkeepers used deception in half of the penalty kicks, resulting in significantly less goals compared to penalties without deception. This advantage was similar for the different types of deception, but larger when penalty takers paid attention to goalkeepers. We propose that the deceptive actions by goalkeepers are effective, mainly because it leads the penalty taker to lose focus. The practical implications of these findings are discussed for both goalkeepers and penalty takers.

Health Care Provider Clustering Using Fusion Penalty in Quasi-Likelihood.

There has been growing research interest in developing methodology to evaluate the health care providers' performance with respect to a patient outcome. Random and fixed effects models are traditionally used for such a purpose. We propose a new method, using a fusion penalty to cluster health care providers based on quasi-likelihood. Without any priori knowledge of grouping information, our method provides a desirable data-driven approach for automatically clustering health care providers into different groups based on their performance. Further, the quasi-likelihood is more flexible and robust than the regular likelihood in that no distributional assumption is needed. An efficient alternating direction method of multipliers algorithm is developed to implement the proposed method. We show that the proposed method enjoys the oracle properties; namely, it performs as well as if the true group structure were known in advance. The consistency and asymptotic normality of the estimators are established. Simulation studies and analysis of the national kidney transplant registry data demonstrate the utility and validity of our method.

Effects of pay-for-performance based antimicrobial stewardship on antimicrobial consumption and expenditure: An interrupted time series analysis.

Objectives: To evaluate the impact of pay-for-performance on antimicrobial consumption and antimicrobial expenditure in a large teaching hospital in Guangzhou, China. Methods: We collected data from hospital information system from January 2018 through September 2022 in the inpatient wards. Antimicrobial consumption was evaluated using antibiotic use density (AUD) and antibiotic use rate (AUR). The economic impact of intervention was assessed by antimicrobial expenditure percentage. The data was analyzed using interrupted time series (ITS) analysis. Results: Following the implementation of the intervention, immediate decreases in the level of AUD were observed in Department of Hematology Unit 3 (ß = -66.93 DDDs/100PD, P = 0.002), Urology (ß = -32.80 DDDs/100PD, P < 0.001), Gastrointestinal Surgery Unit 3 (ß = -11.44 DDDs/100PD, P = 0.03), Cardiac Surgery (ß = -14.30 DDDs/100PD, P = 0.01), ICU, Unit 2 (ß = -81.91 DDDs/100PD, P = 0.02) and Cardiothoracic Surgery ICU (ß = -41.52 DDDs/100PD, P = 0.05). Long-term downward trends in AUD were also identified in Organ Transplant Unit (ß = -1.64 DDDs/100PD, P = 0.02). However, only Urology (ß = -6.56 DDDs/100PD, P = 0.02) and Gastrointestinal Surgery Unit 3 (ß = -8.50 %, P = 0.01) showed an immediate decrease in AUR, and long-term downward trends in AUR were observed in Pediatric ICU (ß = -1.88 %, P = 0.05) and ICU Unit 1 (ß = -0.55 %, P = 0.02). Conclusion: This study demonstrates that the adoption of pay-for-performance effectively reduces antibiotic consumption in specific departments of a hospital in Guangzhou in the short term. However, it is important to recognize that the long-term impact of such interventions is often limited. Additionally, it should be noted that the overall effectiveness of the intervention across the entire hospital was not significant.

Analysing substitutions in recent World Cups and European Championships in male and female elite football - influence of new substitution rules.

Substitutions play a key role in modern football and can substantially affect the physical and overall performance of a team, and the recent substitution rule changes are worth investigating. This study explored the characteristics of substitutions, including different substitution rules, game results, sex, competition stages, tournaments and penalty shoot-outs success rates. We analysed data from a total of 3,738 substitutions from the last 10 years (2013-2023) of European Championships and World Cups, both men's and women's games. Non-parametric tests and chi-square tests were used for statistical analysis with the significance level set at p < 0.05. With the 5-substitution rule, 48% more substitutions occurred compared to the 3-substitution rule (4.26 ± 1.07 vs. 2.87 ± 0.43, p < 0.05) with a slight increase in the average substitution time (70.6 ± 14.3 vs. 69.2 ± 14.6 min, p < 0.05), and 10% more substitutions in the men's game compared to the women's game (p < 0.05). The timing of the first substitution was slightly different in the knock-out stage compared to group stage (59.8 ± 14.7 vs. 57.2 ± 13.3 min, p < 0.05), and the timing for the winning team and drawing team was later than for the losing team (p < 0.05). A total of 13.2% goals were scored by substitutes, with no significant difference between the 5-substitution rule (15.9%) vs the 3-substition rule (12.5%) (p > 0.05). Interestingly, substitute players had a lower success rate in penalty shoot-out compared to starters (61 vs. 74%, p < 0.05). Additionally, substitute player goal scorers entered the pitch later (p < 0.05) in male games compared to female games and in knock-out stage games compared to group games. This study highlights the importance of substitution rules and timing in modern elite football matches. The timing of the first substitution, introduction of substitutes in knock-out stages, and a lower success rate of substitute players in penalty shoot-outs are crucial factors to consider. Coaches can use this information to make strategic substitution decisions to improve team performance.

The reward and penalty for ozone pollution control caused by natural sources and regional transport: A case study in Guangdong province.

Ground-level O3 pollution in the Pearl River Delta region (PRD) is closely related to anthropogenic, natural emissions and regional transport. However, the interactions among different sources and natural intervention in modulating anthropogenic management have not been comprehensively assessed. Here, the WRF-CMAQ-MEGAN modeling system was utilized to simulate an O3 episode over PRD. The integrated source apportionment method (ISAM) and brute-force top-down combined with factor separation approach (BF-TD-FSA) were applied to quantify source contributions, impacts of individual or multiple sources on O3, and decouple interactions among various emissions; additionally, based on ISAM, O3 isopleths visualized MDA8 O3 response of different source types to anthropogenic perturbations. ISAM concluded considerable MDA8 O3 contributions of regional transport in PRD/NPRD (non-PRD areas in Guangdong province) (38.8 %/35.7 %), followed by anthropogenic (32.7 %/24.8 %), BVOC (biogenic volatile organic compounds, 23.8 %/20.3 %) and SNO (soil NO, ∼4 %) emissions. Compared to concentrated anthropogenic contributions, widespread natural contributions were observed across their source areas and along the transport pathways. The BF-TD also revealed that regional transport had the largest impact (>90 µg m-3) on MDA8 O3 while anthropogenic and BVOC emissions greatly affected downwind PRD (64.5 and 7.7 µg m-3). Negative synergy between anthropogenic and natural emissions (especially BVOC emission) suggested potential natural-induced intensification of anthropogenic impact during O3 management. The MDA8 O3 isopleths further demonstrated significant BVOC-induced reward and regional transport-induced penalty for anthropogenic NOx (ANOx) emission control benefits, leading to additional maximum MDA8 O3 decrease and increase by -27.5 and 13.8 µg m-3 in polluted high-emission grids. The natural-induced reward effect could impose loose requirements on anthropogenic reduction (decreased by 13.3 %-17.7 %) if there were no regional transport-induced control penalty. It is advisable to prioritize ANOx control and seek collaboration on air quality management with neighboring provinces to maximize the natural-induced control reward and achieve desired targets with minimal human efforts.

Carbon taxation on high utility transport fuels: An implementation of enviro-economic analysis for the sustainable environment".

The humongous increase in carbon emissions in the past few decades presents an environmental challenge to the scientific community. The current study proposes a method of taxation on high-carbon emission fuels. For this purpose, a comparative enviro-economic analysis is carried out on the three most commonly used fuels (gasoline, Liquefied Petroleum Gas (LPG), and Compressed Natural Gas (CNG)). The speed of the test engine varied from 1800 to 4200 Revolution per Minute (RPM) in increments of 400 RPM. Performance parameters (Brake Power (BP), Brake Thermal Efficiency (BTHE), and Brake Specific Fuel Consumption (BSFC)) were measured using a hydro dynamometer. Emission analysis, including Carbon Dioxide (CO2), Carbon Monoxide (CO), Unburned Hydrocarbons (HC), and Nitrogen Oxide (NOx), was conducted using the TESTO 350 analyzer. The application of Weibull distribution with a 95 % confidence interval, on emission data, explained the adequacy of the data. Among test fuels, CNG emerged as an environment-friendly fuel with an emission reduction of 16, 42, and 43 percent for CO2, CO, and HC in comparison to gasoline. Also, BTHE and BSFC of CNG were better than other alternatives. Moreover, the carbon penalty for CNG fuel showed a price reduction of 32 and 20.8 percent in comparison to gasoline and LPG respectively. The study provides a novel approach to assess the environmental impact of fuels by economic analysis based on emitted carbon quantity. In addition, this very idea is novel in promoting the Sustainable Development Goals (SDG) of the United Nations (UN) through carbon taxation.

On the numerical corroboration of an obstacle problem for linearly elastic flexural shells.

In this article, we study the numerical corroboration of a variational model governed by a fourth-order elliptic operator that describes the deformation of a linearly elastic flexural shell subjected not to cross a prescribed flat obstacle. The problem under consideration is modelled by means of a set of variational inequalities posed over a non-empty, closed and convex subset of a suitable Sobolev space and is known to admit a unique solution. Qualitative and quantitative numerical experiments corroborating the validity of the model and its asymptotic similarity with Koiter's model are also presented.This article is part of the theme issue 'Non-smooth variational problems with applications in mechanics'.

Ultrafine CuO/graphene oxide cellulose nanocomposites with complementary framework for polycyclic aromatic hydrocarbon pollutants removal.

Efficient and sustainable methods for eliminating polycyclic aromatic hydrocarbon pollutants (PAHPs) are in highly desired. Proven technologies involve physical and chemical reactions that absorb PAHPs, however they encounter formidable challenges. Here, a bottom-up refining-grain strategy is proposed to rationally design ultrafine CuO/graphene oxide-cellulose nanocomposites (LCelCCu) with a mirror-like for tetracycline (TC) to substantially improve the efficient of the purification process by active integrated-sorption. The LCelCCu captures TC with a higher affinity and lower energy demand, as determined by sorption kinetic, isotherms, thermodynamics, and infrared and X-ray Photoelectron Spectroscopy. The resulting material could achieve ultra-high sorption capacity (2775.23 mg/g), kinetic (1.2499 L g-1 h-1) and high selectivity (up to 99.9 %) for TC, nearly surpassing all recent adsorbents. This study simultaneously unveils the pioneering role of simultaneous multi-site match sorption and subsequent advanced oxidation synergistically, fundamentally enhancing understanding of the structure-activity-selectivity relationship and inspires more sustainable water purification applications and broader material design considerations.

Parenthood, earnings, and the relevance of family formation sequences.

Prior research sheds little light on how shifts in family formation trajectories have implications for recent cohorts' earnings gains and losses with childbearing. Using longitudinal data from a contemporary cohort, we examine how the pay premium or penalty for parents varies by their relationship status at childbirth and subsequent changes in the status. Fixed effects models show that children born to unpartnered women are associated with substantial pay penalties for the mothers. Conversely, women giving birth within cohabiting or marital unions experience small or no motherhood penalties. For residential fathers, only children born after marriage are linked to pay increases. Men having children while cohabiting or unpartnered receive no fatherhood premiums even if they later transition into marriage. Married mothers' earnings outcomes also depend on their sequence of marriage and childbearing. Whereas women bearing children before marriage encounter a substantial motherhood penalty, those doing so after marriage face none. The variation in parenthood penalties or premiums by childbearing context cannot be entirely elucidated by the differences in the age of entering parenthood, ethnoracial composition, education, or pre-parenthood earnings growth rate among people having children in various contexts. We suggest that the family formation sequence is related to individuals' expectations and the support they receive for their parental roles, which shape parenthood earnings outcomes.

Effect of Jellyfish Body Parts and Presentation Form on Consumers Liking, Sensory Perception, Emotions, and Food Pairings.

Although jellyfish represent a food source in Asia, limited attention has been devoted to investigating Western consumers' perception and acceptance. This study explored the role of jellyfish body parts and presentation form in determining consumer perception. A local consumer test with 106 untrained subjects (57.5% female, 18-45 years) was performed in Italy over two days on six samples of jellyfish (Rhopilema esculentum Kishinouye) differing in terms of body parts (umbrella and oral arms) and presentation form (minced, striped, and pieced). For each sample, participants expressed their overall liking and, through three check-all-that-apply tests, described their perceived sensory properties and emotions and potential preferred food pairings. The results showed a significant effect of presentation form on liking (with striped and minced samples liked more than pieced samples), 18 sensory properties, four emotions, and five food pairings. Moreover, different drivers of liking and emotions were observed for three clusters of subjects named "In favour of", "Against", and "Picky towards" eating jellyfish. In conclusion, this study found that at least one segment of consumers could accept jellyfish as novel food. Moreover, the provided results could be useful for developing innovative jellyfish-based products and dishes that meet consumers' expectations.

How does stock market react to environmental penalty announcements?

Environmental penalty announcement (EPA) has received increasing attention for its potential to convey valuable information and affect capital market performance. Using data on listed companies in China, this paper examines stock market reaction to environmental penalty announcements, the behavior of different types of investors, and the moderating factors of these responses. The findings show that (1) disclosure of EPA by listed companies results in negative abnormal returns, but this negative market reaction is not sustained. (2) Heavy polluters and non-state-owned enterprises are exposed to more negative abnormal returns when they disclose EPA. (3) Environmental reputation can mitigate the negative stock market reaction to EPA, while the participation of green investors will intensify this reaction. (4) Retail investors tend to sell stocks of companies that disclose EPA as media attention increases, while institutional investors increase their shareholding especially in companies that already have high holdings, high ESG scores, and in regions with low levels of green finance development. This paper serves as a reference for governments, firms, and stakeholders on stock market reaction to environmental information disclosures.

A few theoretical results for Laplace and arctan penalized ordinary least squares linear regression estimators.

Two new nonconvex penalty functions - Laplace and arctan - were recently introduced in the literature to obtain sparse models for high-dimensional statistical problems. In this paper, we study the theoretical properties of Laplace and arctan penalized ordinary least squares linear regression models. We first illustrate the near-unbiasedness of the nonzero regression weights obtained by the new penalty functions, in the orthonormal design case. In the general design case, we present theoretical results in two asymptotic settings: (a) the number of features, p fixed, but the sample size, n → ∞ , and (b) both n and p tend to infinity. The theoretical results shed light onto the differences between the solutions based on the new penalty functions and those based on existing convex and nonconvex Bridge penalty functions. Our theory also shows that both Laplace and arctan penalties satisfy the oracle property. Finally, we also present results from a brief simulations study illustrating the performance of Laplace and arctan penalties based on the gradient descent optimization algorithm.

Renewable risk assessment of heterogeneous streaming time-to-event cohorts.

The analysis of streaming time-to-event cohorts has garnered significant research attention. Most existing methods require observed cohorts from a study sequence to be independent and identically sampled from a common model. This assumption may be easily violated in practice. Our methodology operates within the framework of online data updating, where risk estimates for each cohort of interest are continuously refreshed using the latest observations and historical summary statistics. At each streaming stage, we introduce parameters to quantify the potential discrepancy between batch-specific effects from adjacent cohorts. We then employ penalized estimation techniques to identify nonzero discrepancy parameters, allowing us to adaptively adjust risk estimates based on current data and historical trends. We illustrate our proposed method through extensive empirical simulations and a lung cancer data analysis.

Comparing the World Psychiatric Association and European Psychiatric Association Codes of Ethics: Discrepancies and shared grounds.

BACKGROUND: Codes of ethics provide guidance to address ethical challenges encountered in clinical practice. The harmonization of global, regional, and national codes of ethics is important to avoid gaps and discrepancies. METHODS: We compare the European Psychiatric Association (EPA) and the World Psychiatric Association (WPA) Codes of Ethics, addressing main key points, similarities, and divergences. RESULTS: The WPA and EPA codes are inspired by similar fundamental values but do show a few differences. The two codes have a different structure. The WPA code includes 4 sections and lists 5 overarching principles as the basis of psychiatrists' clinical practice; the EPA code is articulated in 8 sections, lists 4 ethical principles, and several fundamental values. The EPA code does not include a section on psychiatrists' education and does not contain specific references to domestic violence and death penalty. Differences can be found in how the two codes address the principle of equity: the EPA code explicitly refers to the principle of universal health care, while the WPA code mentions the principle of equity as reflected in the promotion of distributive justice. CONCLUSIONS: We recommend that both WPA and EPA periodically update their ethical codes to minimize differences, eliminate gaps, and help member societies to develop or revise national codes in line with the principles of the associations they belong to.Minimizing differences between national and international codes and fostering a continuous dialogue on ethical issues will provide guidance for psychiatrists and will raise awareness of the importance of ethics in our profession.

Intelligent Vehicle Path Planning Based on Optimized A* Algorithm.

With the rapid development of the intelligent driving technology, achieving accurate path planning for unmanned vehicles has become increasingly crucial. However, path planning algorithms face challenges when dealing with complex and ever-changing road conditions. In this paper, aiming at improving the accuracy and robustness of the generated path, a global programming algorithm based on optimization is proposed, while maintaining the efficiency of the traditional A* algorithm. Firstly, turning penalty function and obstacle raster coefficient are integrated into the search cost function to increase the adaptability and directionality of the search path to the map. Secondly, an efficient search strategy is proposed to solve the problem that trajectories will pass through sparse obstacles while reducing spatial complexity. Thirdly, a redundant node elimination strategy based on discrete smoothing optimization effectively reduces the total length of control points and paths, and greatly reduces the difficulty of subsequent trajectory optimization. Finally, the simulation results, based on real map rasterization, highlight the advanced performance of the path planning and the comparison among the baselines and the proposed strategy showcases that the optimized A* algorithm significantly enhances the security and rationality of the planned path. Notably, it reduces the number of traversed nodes by 84%, the total turning angle by 39%, and shortens the overall path length to a certain extent.

Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion.

Brain-computer interface (BCI) for motor imagery is an advanced technology used in the field of medical rehabilitation. However, due to the poor accuracy of electroencephalogram feature classification, BCI systems often misrecognize user commands. Although many state-of-the-art feature selection methods aim to enhance classification accuracy, they usually overlook the interrelationships between individual features, indirectly impacting the accuracy of feature classification. To overcome this issue, we propose an adaptive feature learning model that employs a Riemannian geometric approach to generate a feature matrix from electroencephalogram signals, serving as the model's input. By integrating the enhanced adaptive L1 penalty and weighted fusion penalty into the sparse learning model, we select the most informative features from the matrix. Specifically, we measure the importance of features using mutual information and introduce an adaptive weight construction strategy to penalize regression coefficients corresponding to each variable adaptively. Moreover, the weighted fusion penalty balances weight differences among correlated variables, reducing the model's overreliance on specific variables and enhancing accuracy. The performance of the proposed method was validated on BCI Competition IV datasets IIa and IIb using the support vector machine. Experimental results demonstrate the effectiveness and superiority of the proposed model compared to the existing models.

Flexible cost-penalized Bayesian model selection: Developing inclusion paths with an application to diagnosis of heart disease.

We propose a Bayesian model selection approach that allows medical practitioners to select among predictor variables while taking their respective costs into account. Medical procedures almost always incur costs in time and/or money. These costs might exceed their usefulness for modeling the outcome of interest. We develop Bayesian model selection that uses flexible model priors to penalize costly predictors a priori and select a subset of predictors useful relative to their costs. Our approach (i) gives the practitioner control over the magnitude of cost penalization, (ii) enables the prior to scale well with sample size, and (iii) enables the creation of our proposed inclusion path visualization, which can be used to make decisions about individual candidate predictors using both probabilistic and visual tools. We demonstrate the effectiveness of our inclusion path approach and the importance of being able to adjust the magnitude of the prior's cost penalization through a dataset pertaining to heart disease diagnosis in patients at the Cleveland Clinic Foundation, where several candidate predictors with various costs were recorded for patients, and through simulated data.

Intravoxel incoherent motion and diffusion kurtosis imaging and their machine-learning-based texture analysis for detection and assessment of prostate cancer severity at 3 T.

OBJECTIVES: To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa). MATERIALS AND METHODS: Eighty-eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM-DKI data were acquired using 13 b values (0-2000 s/mm2) and analyzed using the IVIM-DKI model with the total variation (TV) method. PCa patients were categorized into two groups: clinically insignificant prostate cancer (CISPCa) (Gleason grade ≤ 6) and clinically significant prostate cancer (CSPCa) (Gleason grade ≥ 7). One-way analysis-of-variance, t test, and receiver operating characteristic analysis was performed to measure the discriminative ability to detect PCa using IVIM-DKI parameters. A chi-square test was used to select important texture features of apparent diffusion coefficient (ADC) and IVIM-DKI parameters. These selected texture features were used in an artificial neural network for PCa detection. RESULTS: ADC and diffusion coefficient (D) were significantly lower (p < 0.001), and kurtosis (k) was significantly higher (p < 0.001), in PCa as compared with benign prostatic hyperplasia (BPH) and normal peripheral zone (PZ). ADC, D, and k showed high areas under the curves (AUCs) of 0.92, 0.89, and 0.88, respectively, in PCa detection. ADC and D were significantly lower (p < 0.05) as compared with CISPCa versus CSPCa. D for detecting CSPCa was high, with an AUC of 0.63. A negative correlation of ADC and D with GS (ADC, ρ = -0.33; D, ρ = -0.35, p < 0.05) and a positive correlation of k with GS (ρ = 0.22, p < 0.05) were observed. Combined IVIM-DKI texture showed high AUC of 0.83 for classification of PCa, BPH, and normal PZ. CONCLUSION: D, f, and k computed using the IVIM-DKI model with the TV method were able to differentiate PCa from BPH and normal PZ. Texture features of combined IVIM-DKI parameters showed high accuracy and AUC in PCa detection.

Lyapunov Drift-Plus-Penalty-Based Cooperative Uplink Scheduling in Dense Wi-Fi Networks.

In high-density network environments with multiple access points (APs) and stations, individual uplink scheduling by each AP can severely interfere with the uplink transmissions of neighboring APs and their associated stations. In congested areas where concurrent uplink transmissions may lead to significant interference, it would be beneficial to deploy a cooperative scheduler or a central coordinating entity responsible for orchestrating cooperative uplink scheduling by assigning several neighboring APs to support the uplink transmission of a single station within a proximate service area to alleviate the excessive interference. Cooperative uplink scheduling facilitated by cooperative information sharing and management is poised to improve the likelihood of successful uplink transmissions in areas with a high concentration of APs and stations. Nonetheless, it is crucial to account for the queue stability of the stations and the potential delays arising from information exchange and the decision-making process in uplink scheduling to maintain the overall effectiveness of the cooperative approach. In this paper, we propose a Lyapunov drift-plus-penalty framework-based cooperative uplink scheduling method for densely populated Wi-Fi networks. The cooperative scheduler aggregates information, such as signal-to-interference-plus-noise ratio (SINR) and queue status. During the aggregation procedure, propagation delays are also estimated and utilized as a value of expected cooperation delays in scheduling decisions. Upon aggregating the information, the cooperative scheduler calculates the Lyapunov drift-plus-penalty value, incorporating a predefined model parameter to adjust the system accordingly. Among the possible scheduling candidates, the proposed method proceeds to make uplink decisions that aim to reduce the upper bound of the Lyapunov drift-plus-penalty value, thereby improving the network performance and stability without a severe increase in cooperation delay in highly congested areas. Through comprehensive performance evaluations, the proposed method effectively enhances network performance with an appropriate model parameter. The performance improvement is particularly notable in highly congested areas and is achieved without a severe increase in cooperation delays.

Adaptive penalty-based neurodynamic approach for nonsmooth interval-valued optimization problem.

The complex and diverse practical background drives this paper to explore a new neurodynamic approach (NA) to solve nonsmooth interval-valued optimization problems (IVOPs) constrained by interval partial order and more general sets. On the one hand, to deal with the uncertainty of interval-valued information, the LU-optimality condition of IVOPs is established through a deterministic form. On the other hand, according to the penalty method and adaptive controller, the interval partial order constraint and set constraint are punished by one adaptive parameter, which is a key enabler for the feasibility of states while having a lower solution space dimension and avoiding estimating exact penalty parameters. Through nonsmooth analysis and Lyapunov theory, the proposed adaptive penalty-based neurodynamic approach (APNA) is proven to converge to an LU-solution of the considered IVOPs. Finally, the feasibility of the proposed APNA is illustrated by numerical simulations and an investment decision-making problem.