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Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ABSTRACT Framings may affect individuals' choices. In particular, the perception of (implicit) risks and their costs may influence intertemporal choices. In a between‐subjects experimental design, participants are presented choices either in a standard (i.e., current vs. future payoffs), penalty (i.e., the same as before, presenting the differences between present and future amounts as losses), future‐improved (i.e., increasing by 35% the future payoff with respect to the standard frame) or penalty present‐improved way (i.e., with small differences between present and future amounts). Undergraduate students participated in 3 two‐step experiments. The results show that the negative and the present‐improved frames render the participants more patient and subjects who are trained to be more farsighted using a penalty decision problem continue to be patient in subsequent classical formulations where that specific attribute is no longer present. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos de Psicología del Deporte is the property of Cuadernos de Psicologia del Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Perceptual training enhances the ability to anticipate crucial information for decision‐making, for example, a soccer goalkeeper predicting penalty kick direction. However, it remains unclear whether perceptual practice alone (implicit method) is sufficient for optimal decision‐making improvement, or whether emphasising pertinent details during practice (explicit method) could yield better results. This study compared implicit and explicit methods of learning ball direction prediction during soccer penalties, involving both goalkeepers and non‐soccer players (novices). Participants engaged in a single training session, either through the explicit method (watching videos highlighting relevant information) or implicit method (watching regular videos). Specialised software was used to display penalty kick videos, mimicking the goalkeeper's viewpoint up to 200 ms before ball contact, and measuring reaction time and response choice. Both implicit and explicit training led to consistent performance gains for goalkeepers and novices alike, notably enhancing ball direction prediction accuracy. Reaction time was unaffected by training. This suggests that both explicit and implicit training methods exhibit similar effectiveness, applicable to soccer goalkeepers and novices. [ABSTRACT FROM AUTHOR]

Preterm birth (PTB) is a major cause of child and mother mortality, a PTB classification model can assist in assessing the health condition ahead of time and help avoid complications during childbirth. Mother's significant feature (MSF) dataset created for this study has features derived from mother's physical, lifestyle, social and stress attributes. MSF dataset consists of 119 features of 1,000 mothers with 172 preterm and 828 full-term deliveries, resulting in issues of dataset imbalance namely class inseparability and classification bias. To overcome the imbalance issue, a novel algorithm named majority penalizing minority upsampling (MPMU) is proposed. MPMU forms clusters looking into the degree of dataset imbalance, it analyses the composition of each cluster individually and computes the varied penalty for majority class instances. It further balances dataset composition by oversampling minority class instances. MPMU processed dataset is further used to train the proposed 6L-ANN network which finds the probability of occurrence of PTB. The proposed model has shown efficient results on MSF sub-datasets with precision values ranging from 0.90 to 0.97, area under the curve (AUC) between 0.86 to 0.99, and prediction accuracy ranging from 93.04% to 99.47%. Experiment results show that a mother's lifestyle and stress features have a strong influence on the childbirth outcome. [ABSTRACT FROM AUTHOR]

Copyright of Foro Revista de Derecho is the property of Universidad Andina Simon Bolivar, Sede Ecuador and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Foro Revista de Derecho is the property of Universidad Andina Simon Bolivar, Sede Ecuador and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main objective was to examine the various enforcement action (penalties) which were imposed by IRDAI on Life and General insurance industry for violation of various insurance rules and regulations. The research was a fact-finding descriptive research based on historical penalty orders published by IRDAI. After analysing the 67 orders published on IRDAI website, it was found that penalty amounting to Rs 1190 lakhs was imposed on general insurers and Rs 206 lakhs was imposed on life insurers. Total penalty amount combined for life and general insurers was 1396 lakhs. Out of which 607 lakhs (43.48%) was related to uncommon category violation and 789 lakhs (56.52%) was related to common category violation between life and general insurers. Total frequency of violation for general and life insurance industry combined was 127 times, with common category violation was 101 times (79.52%) and uncommon category violation was 26 times (20.48%). [ABSTRACT FROM AUTHOR]

We study the optimal penalty scheme for an expert firm and a layman client against shirking in their costly interaction that helps the firm discover the unsuitable transaction, i.e. one that yields a loss for the client. The market solution to the bilateral hidden action problem fails to incentivize sufficient effort and leads to an inefficient outcome, which creates scope for government action. By contrast, private contracts obtain efficiency in an alternative framework with just the firm's unilateral effort, highlighting the role of the client's effort in rationalizing legal intervention. Under the unique first-best policy, the firm not only refunds the client but also pays the client's loss to the government if the firm fails to stop a transaction that ends up being unsuitable. The client receives the refund but submits the firm's production cost to the government. The optimal punitive penalty is their total contingent loss and is robust to private contracts. The optimal penalty generalizes to a multi-agent team by making each agent internalize all others' contingent losses. [ABSTRACT FROM AUTHOR]

Introduction: This study examines the distribution of events and event records (EVRs) in elite judo competitions, encompassing both male and female categories. Sample: By analyzing data from the 2018, 2019, and 2021 World Championships, the study incorporates 6487 events (EVs) and 2340 contests classified by their last event (cEV). Results: The predominant occurrence of EV2 and EV3 in male (23.2% and 36.6%) and female (26.8% and 31.7%) contests suggests consistent patterns. Statistical analyses reveal non-uniform distributions of events within temporal units (TUs). Small associations were found between EVRs and TUs for EV1, EV2 and EV3 (Cramer’s V = 0.103 to 0.171; p

The risks of contracts are increasing nowadays. The reasons for this are increasing economic and social uncertainties. The role of important contract law principles, such as vis maior, pacta sunt servanda, or clausula rebus sic stantibus, has changed. Judicial practice must also follow this. It is an important requirement that the parties properly assess their ability to perform when concluding the contract, and price the risks well. Institutions that ratify and insure contracts are important means of mitigating contract risks. The protection of the deposit, the penalty, the surety, the protection of the balance of the contracts, and the possibility of challenging the contract in the event of a value imbalance. In case of unfair general terms and conditions, the possibility of referring to their nullity.

Unfitted finite element methods (FEM) have attractive merits for problems with evolving or geometrically complex boundaries. Conventional unfitted FEMs incorporate penalty terms, parameters, or Lagrange multipliers to impose the Dirichlet boundary condition weakly. This to some extent increases computational complexity in implementation. In this article, we propose an unfitted generalized FEM (GFEM) for the Dirichlet problem, which is free from any penalty or stabilization. This is achieved by means of partition of unity frameworks of GFEM and designing a set of new enrichments for the Dirichlet boundary. The enrichments are divided into two groups: the one is used to impose the Dirichlet boundary condition strongly, and the other one serves as energy space of variational formulations. The shape functions in energy space vanish at the boundary so that standard variational formulae like those in the conventional fitted FEM can be applied, and thus the penalty and stabilization are not needed. The optimal convergence rate in the energy norm is proven rigorously. Numerical experiments and comparisons with other methods are executed to verify the theoretical result and effectiveness of the algorithm. The conditioning of new method is numerically shown to be of same order as that of the standard FEM. [ABSTRACT FROM AUTHOR]

Copyright of Revista CES Derecho is the property of Universidad CES and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper concerns an optimal dividend problem for an insurance company whose uncontrolled surplus process evolves as a piecewise deterministic compound Poisson risk process (in the absence of dividend payments). With each dividend payment, there is a proportional and a fixed cost. The objective is to maximize the sum of the expected cumulative discounted dividend payments received until the time of ruin and a penalty payment at the time of ruin. We first introduce the characteristics of the Markov controls in the optimal dividend problem and the dividend strategy is an additive functional of the controlled surplus process. Under a certain assumption, we get that the dynamic programming equation (DPE) is measure-valued, and the optimal dividend strategy is a Markov control. A verification theorem is proved in the class of all admissible strategies. Furthermore, we give a short discussion on the optimal dividend problem for general distributed claim amounts, and the optimal dividend strategy has a band structure. Finally, an example with a gamma distribution for the claim amount is analyzed, in terms of a particular Gerber-Shiu function. [ABSTRACT FROM AUTHOR]

The article dwells upon the current Ukrainian legislation, which is being changed both at the legislative and legal level in connection with ratification of international conventions and practice of the ECtHR, which is the source of criminal responsibility under the Law of Ukraine "On the implementation of decisions and application of the practice of the European Court of Human Rights". Although the Istanbul Convention was signed by Ukraine back in 2011, it was ratified only on February 1, 2022. However, over the past 5 years, the national legislation has been brought into line with the requirements of the Convention and the practice of the ECtHR, but the change of legislation must be in line with the national legislation. We analyzed these inconsistencies and conflicts, which, in our view, relate more to the responsibility for the act of domestic violence. The types of punishment and penalties do not correspond to the purpose of the punishment, which is studied in more detail in the article. Besides, a large number of repetition and recidivism shows that the purpose of punishment, namely the correction of the sentenced person, does not reach its goal. The judicial statistics concerning administrative and criminal responsibility over the last three years was analyzed. The analyzed data of the polled police officers who are responsible for the regulation of problems in the family related to domestic violence are presented. As a result, conclusions and proposals to the current legislation were developed to improve the situation in the appointment of penalties and punishment for domestic violence. [ABSTRACT FROM AUTHOR]

Dropout is perhaps the most popular regularization method for deep learning. Due to the stochastic nature of the Dropout mechanism, the convergence analysis of Dropout learning is challenging and the existing convergence results are mainly of probability nature. In this paper, we investigate the deterministic convergence of the mini-batch gradient learning method with Dropconnect and penalty. By drawing and presenting a set of samples of the mask matrix of Dropconnect regularization into the learning process in a cyclic manner, we establish an upper bound of the norm of the weight vector sequence and prove that the gradient of the cost function, the cost function itself, and the weight vector sequence deterministically converge to zero, a constant, and a fixed point respectively. Considering Dropout is mathematically a specific realization of Dropconnect, the established theoretical results in this paper are also valid for Dropout learning. Illustrative simulations on the MNIST dataset are provided to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

Copyright of Jurnal Nusantara Aplikasi Manajemen Bisnis is the property of Universitas Nusantara PGRI Kediri and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to decipher the elliptic PDEs defined over curved complex domains with a penalty approach in a finite difference scheme. Using the penalty approach, we utilize the finite difference scheme with the aid of uniform Cartesian mesh irrespective of the shape and convexity of the domain. We introduce the finite difference schemes with the H 1 and L 2 penalties and furnish the sharp convergence of the solution of the penalized problems to the solution of the original problem. Several iterative solvers are also equipped for both the H 1 and L 2 penalty schemes to compare the required number of iterations and CPU time to achieve the desired accuracy. The comprehensive numerical experiments are performed to uphold the mathematical results and to exhibit the efficiency of the proposed idea for practical scenarios. [ABSTRACT FROM AUTHOR]

Introduction Stratification sampling is one of the most widely used sampling methods. In some cases, it is up to the researcher to determine the boundaries of the classes, and in some cases, the society is already classified. The optimal classification for a situation is obtained from the boundary of the classes, based on those boundaries, the variance of the average (or total) estimator of the community reaches its minimum value. In traditional methods, the variance of the estimator is considered as a function of the boundaries of the response variable, and in order to achieve the minimum of the variance, equations are obtained, which are often solved by numerical methods. Considering that one of the boundaries of stratum h, i.e. yn, appear only in two terms WASH and Wh+1Sh+1, we have (EWS) (WAS) = дуп дуп + (Wh+1Sh+1) дун ciency, Now, if f(y) is the density function of y, the weight of the stratum can be written based on it, as follows; W = f(t)dt Уһ-1 a(W) дуп = f(yn) Therefore, the derivative can be written as follows. a(WS) дуп = Sh дуп W (Sn) f(yn) (VP)²+ = дуп 2 Sh Similarly, a similar formula is obtained for the next stratum, and finally for h = 1,2,..., H-1, we have f(yn) (yn-Pn)²+Shf(yn) (yn-Pn+1)² + Sh+1 2 Sh Sh+1 2 These equations do not have a closed solution and are solved using approximate numerical methods. The first disadvantage of this optimal classification style is not considering independent variables. The second disadvantage is complicated equations that do not have a closed and understandable answer. Since the objectives of multiple data mining and the role of classification are not limited to the estimation of one parameter, it is necessary to seek to classify the observations into homogeneous subgroups so as to help more interpretability of the data. The decision tree, which is basically a prediction method, partitions the data into subgroups with the highest purity based on quantitative or qualitative auxiliary variables in successive branches. The simple interpretability of the decision tree is more prominent than its predictive accuracy. Material and Methods In this paper, we have tried to build the optimal classification based on the new criterion, C = Var(s) + H, that is a combination of variance and a penalty for increasing the number of strata, so that important auxiliary variables in the formation of the decision tree determine the limits of the strata. In the introduced criterion the penalty term is AH, where H is the number of strata and A is a tunning parameter. For zero value of 2, only the first term of the criterion, which is the variance, will play a role. As the tuning parameter λ increases, the number of optimal starts is reduced from 128 to 84, 6, and 2. Results and discussion By pruning the saturated tree successively until reaching the root node, different values of the variance of the estimator are obtained. By drawing a plot including the variance versus the number of strata, similar to the Figure 2. on the top- left, a curve is obtained that has the highest concavity in the corner. Using the information obtained from this corner and the number of strata related to it will lead us to choose the appropriate value of λ. The classification process starts from the saturated tree and with successive pruning until reaching the tree stump, the number of strata decreases, the optimal classification is achieved based on the introduced combined criteria. Conclusion By applying the established criteria to the real population of Razi University students' academic progress, which includes the response variable of academic progress and twelve auxiliary variables in Table (1), the optimal classification with six strata was the result. The decision tree that produces this classification is shown in Figure 3. [ABSTRACT FROM AUTHOR]

What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that errors are frequent but trivial as infants acquire foundational skills. In learning to walk, for example, falling is commonplace but appears to incur only a negligible penalty. Behavioral data, however, cannot reveal whether a low penalty for falling is beneficial for learning to walk. Here, we used a simulated bipedal robot as an embodied model to test the optimal penalty for errors in learning to walk. We trained the robot to walk using 12,500 independent simulations on walking paths produced by infants during free play and systematically varied the penalty for falling—a level of precision, control, and magnitude impossible with real infants. When trained with lower penalties for falling, the robot learned to walk farther and better on familiar, trained paths and better generalized its learning to novel, untrained paths. Indeed, zero penalty for errors led to the best performance for both learning and generalization. Moreover, the beneficial effects of a low penalty were stronger for generalization than for learning. Robot simulations corroborate prior behavioral data and suggest that a low penalty for errors helps infants learn foundational skills (e.g., walking, talking, and social interactions) that require immense flexibility, creativity, and adaptability. Research Highlights: During infant skill acquisition, errors are commonplace but appear to incur a low penalty; when learning to walk, for example, falls are frequent but trivial.To test the optimal penalty for errors, we trained a simulated robot to walk using real infant paths and systematically manipulated the penalty for falling.Lower penalties in training led to better performance on familiar, trained paths and on novel untrained paths, and zero penalty was most beneficial.Benefits of a low penalty were stronger for untrained than for trained paths, suggesting that discounting errors facilitates acquiring skills that require immense flexibility and generalization. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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 (β = −66.93 DDDs/100PD, P = 0.002), Urology (β = −32.80 DDDs/100PD, P

Background: This study aimed to evaluate the sensory acceptability of four sweet potato cultivars (Beauregard, Morada‐INTA, Colorado‐INTA, and Arapey), considering two cooking methods: boiled and baked; and two cities, 9 de Julio (9DJ) and San Pedro (SP), of Buenos Aires province. 120 women were recruited in each city. A home use test was carried out. Each consumer received at home each sample in a bag containing three sweet potatoes and the evaluation form. The sensory acceptability of different characteristics of the samples was evaluated, before and after cooking. To inquire the reasons for consumption of each sample, the methodology check all that apply (CATA) was used. Results: Of the two factors evaluated (city and cooking method), city had a significant influence when evaluating the samples. Participants of SP gave higher acceptability to Beauregard cultivar than 9DJ in most attributes. Colorado INTA had greater acceptability in some descriptors by the consumers of 9DJ. While Arapey and Morada INTA had the greatest acceptability in 9DJ trial. In CATA results 9DJ consumers associated the Beauregard cultivar with negative phrases: It tastes weird and It has little flavor/tasteless and to a lesser extent to The internal color is artificial and It breaks when cooking. While SP consumers characterized with negative phrases the Arapey and Morada INTA samples as follows: It changes color (brown) quickly, Its shape is not regular and When cooked, it has threads or fibers. Conclusion: Consumer preferences provide opportunities for the development or improvement of new cultivars. It would be interesting to extend this study to other regions and/or countries. [ABSTRACT FROM AUTHOR]

In the present essay I question the essential foundations of the criminal law of the enemy, such as the expulsion of the potentially dangerous individual to a natural factual state, the lack of consideration of the existence of more than one kind of social contract, the absence of analysis of the potentially unlawful inclination through a cognitive structure of the enemy, and punishment as a legal mechanism of appearances. [ABSTRACT FROM AUTHOR]

Demand response (DR) is the short-term change of consumers energy usage patterns in response to power utility needs. The utility benefits from DR adoption in terms of better load management, reduction of peak power deficits, energy deficits, enhanced reliability, and improved economic performance. Consumers gain from energy bill savings and incentive payments. Accurately estimating the consumer baseline load (CBL) is critical for evaluating the success of a DR program implementation. Estimation of CBL helps to decide the volume of load curtailment, decide the incentives to be offered, and assess the impacts of consumer participation. The real-time domestic 11 kV feeder data of the 6.3 MVA substation of Goa electricity board, Goa, India is used to analyze the performance of the DR program. For CBL analysis time series average, adjustment, exponential moving average, decomposition, and forecasting techniques are applied. For performance evaluation of DR programs, the Artificial neural network (ANN) based CBL estimation technique is utilized. The ANN-based technique of estimation has better prediction accuracy, lower bias, and reduced variability as compared to other CBL estimation techniques. Consumer response to demand changes is computed using elasticity and consumer benefit function. The ANN-based CBL estimation and demand variation obtained from elasticity values are further used to analyze the technical and financial performance factors, for dynamic price and incentive-based DR program implementation. The research can assist a state power utility that is implementing smart grids in categorizing consumers, establishing a baseline, identifying potential demand reductions, and evaluating the feasibility DR programs. [ABSTRACT FROM AUTHOR]

This study examined the impact of the COVID-19 pandemic on men's ice hockey in Kanagawa prefecture. We investigated the number and type of penalties and injuries that occurred in men's ice hockey league games in Kanagawa between September 2018 and March 2023. In total, data from 734 games were analyzed, and data were compared between seasons. The average number of penalties per game was 5.93 in the 2018-2019 season, 5.66 in the 2019-2020 season, 4.96 in 2020-2021, and 4.40 in 2021-2022, 4.64 in the 2022-2023 season, indicating that the number of penalties decreased during the COVID-19 pandemic. However, the number of penalties involving the stick increased. Injuries during games also increased during the COVID-19 pandemic, from 0 in the 20182019 (175 games) and 2019-2020 (191 games) seasons to 1 case in the 2020-2021 (73 games) season, 6 cases in the 2021-2022 (119 games) season and 2 cases in the 2022-2023 (176 games) season. The increased number of injuries observed may have been due to the closure of ice rinks by the state of emergency, which restricted on-ice training. As players avoided contact to prevent the spread of COVID-19, penalties caused by contact play decreased, whereas those involving sticks increased. [ABSTRACT FROM AUTHOR]

Industrial development not only proved to be the forerunner of revolutionary development in financials, it also opened new avenues in Islamic Financial fiqh. In fact, the industrial revolution has created new challenges for Islamic fiqh, which need to be addressed. Now the world has become a global village and business has expanded from a small scale to very large scale in the form of multinational companies. Thus, people from different geographical backgrounds, religious affiliations and fiqh interact with each other. Therefore, due to this mutual trade among traders having different fiqh backgrounds, sometimes face issues due to different fiqhi background. Jurists have difference of opinion in financial matters like Imam Abu Ḥanīfa, Imam Mālik, Imam Shāfiʿī and Imam Ahmad bin Hanbal have different opinions on permissibility or impermissibility of different financial matters. Therefore, it is a challenge to do business and financial dealings with persons having different followings. Many fiqh bodies (institutions) worldwide are working to resolve such issues. These institutions set the standard for Islamic Financial Institutions (IFIs) by addressing such issues by combining different fiqh on predefined parameters. Therefore, the objective of this study is to critically discuss and evaluate the talfīq with respect to financial matters in light of the resolutions of International Islamic fiqh Academy. Being qualitative in nature, this study uses content analysis to achieve its objective. To resolve the issues faced in financial matters, abandoning one fiqh and adopting another is called "talfīq ". Different bodies are working for this in the world and locally in Pakistan as well. They are all working as Sharī ʻah standard setting bodies, for all aspects of the life of the Muslim ummah, including financial matters. One of the standard setting bodies is International Islamic Fiqh Academy Jeddah. Since its inception, the academy has passed resolutions on hundreds of important financial matters, most of which adopted a consolidation approach. Some of these important financial issues are discussed in this paper. The purposes of this academy which is giving a ruling in financial matters, are also discussed in detail. A critical review of isti ṣnā ʿ (It refers to a contract under which an item is purchased before it comes into existence and an order is given for its manufacture.), as a binding contract and penalty clause in case of delayed delivery is particularly presented in this paper. [ABSTRACT FROM AUTHOR]

he notion of multiple offenses is regulated by the current Criminal Code in Title II concerning the offense, Articles 38-45, and encompasses three forms: the concurrence of offenses, recidivism, and intermediary plurality. Among these forms, recidivism is regulated by Article 41 of the Criminal Code. According to this article, "recidivism occurs when, after a final conviction to a prison sentence of more than one year and until rehabilitation or the expiration of the rehabilitation term, the convict commits a new offense with intent or aggravated intent, for which the law prescribes a prison sentence of one year or more. Additionally, recidivism also occurs when one of the penalties is life imprisonment." (Florin Streteanu, 2010). The issue of recidivism generates interest in the current landscape due to the enormous expenses incurred by the justice system in this regard and the consequences this phenomenon has on society. The public perception of recurring criminal behaviors and prolonged sentences is associated with a reduction in the chances of social reintegration for inmates. [ABSTRACT FROM AUTHOR]

The recently enacted Inflation Reduction Act (IRA) includes a number of incentive-based programs (e.g., tax credits) designed to motivate firms to develop new clean technologies for fighting climate change. However, the IRA also includes a fee firms incur for excessive methane emissions. This represents the first time the United States government has ever levied a fee on greenhouse gas emissions, and it raises an interesting research question—how should a budget-constrained regulator balance the use of both incentive and penalty-based levers for stimulating investment in clean technology development? In this paper, we examine a regulator's optimal penalty and subsidy decisions for motivating firms to invest in clean technology development. We illustrate how the level of competitive intensity in the market can influence a budget-constrained regulator with multiple competing objectives—the environment, firm profits, and consumer welfare. We find that a subsidy is always beneficial, irrespective of the regulator's objective. While imposing a firm penalty always benefits the environment, it always negatively impacts the sum of firm profits and consumer welfare. However, depending on the level of competition in the market, instances can occur where imposing a high penalty actually benefits total firm profits or consumer welfare (separately). Interestingly, a regulator that cares about all three dimensions of its objective equally, should always set the penalty to either its minimum or maximum value, depending on whether the environmental cost of the harmful product is high or low. [ABSTRACT FROM AUTHOR]

Ramp-rate limitation is a strategy to reduce wind power variability and to permit the integration of wind power into the grid. However, penalties occur whenever the ramp-rate limitations are not respected. The purpose of this paper is to compute the penalties to which a wind farm may undergo when a battery storage system is put alongside the wind farm. This is achieved by advancing a semi-Markov model which mimes the operations on the battery and considers a new reward structure which is dependent on the time length of the battery operations. Two Monte Carlo algorithms are proposed for simulating the penalty process. The paper shows the validity of the methodology by verifying the model assumptions directly on real data and through a comparison of the real and the simulated results. This paper contributes to the literature by extending previous stochastic models and providing a general methodology for the economical characterization of ramp-rate limitation policies. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to identify reasons for punishing employees, prevalent types of punishment, consequences of punishment, and the factors that determine whether employees are punished for the poor quality of products and services. The main research method was a diagnostic survey using a questionnaire technique. A personal interview was a complementary method aimed at providing additional data and broaden the extent of research findings. The conducted research shows that employees are punished mainly when some irregularities occur and are detected (someone does not respect the procedures and standards in force in a given organization). Penalties provided for in-work discipline systems are rarely used. They are supplemented by various informal punishments. As a consequence of penalties received, employees feel injustice, a lack of motivation to work, a lack of satisfaction, and an unwillingness to propose improvement actions. The factors influencing punishment include the ability to set a quality criterion for a job appraisal, the presence of a quality criterion in a remuneration system, as well as the results of quality audits. The narrow spatial and temporal scope of the conducted research should be considered as its main limitation. The research was of a partial character, so its representativeness is rather limited. The interpretation of data obtained through interviews depends on their structure, the knowledge and skills of interviewees, and their ability to avoid bias. [ABSTRACT FROM AUTHOR]

Pruning of neural networks is undoubtedly a popular approach to cope with the current compression of large-scale, high-cost network models. However, most of the existing methods require a high level of human-regulated pruning criteria, which requires a lot of human effort to figure out a reasonable pruning strength. One of the main reasons is that there are different levels of sensitivity distribution in the network. Our main goal is to discover compression methods that adapt to this distribution to avoid deep architectural damage to the network due to unnecessary pruning. In this paper, we propose a filter texture distribution that affects the training of the network. We also analyze the sensitivity of each of the diverse states of this distribution. To do so, we first use a multidimensional penalty method that can analyze the potential sensitivity based on this texture distribution to obtain a pruning-friendly sparse environment. Then, we set up a lightweight dynamic threshold container in order to prune the sparse network. By providing each filter with a suitable threshold for that filter at a low cost, a massive reduction in the number of parameters is achieved without affecting the contribution of certain pruning-sensitive layers to the network as a whole. In the final experiments, our two methods adapted to texture distribution were applied to ResNet Deep Neural Network (DNN) and VGG-16, which were deployed on the classical CIFAR-10/100 and ImageNet datasets with excellent results in order to facilitate comparison with good cutting-edge pruning methods. Code is available at . [ABSTRACT FROM AUTHOR]

Hotel cancellation policies have shifted considerably in recent years. This is mainly in response to growing rates of last-minute cancellations and no shows and the resulting negative impact on the hotel's performance. This study explores how two key policy elements, the penalty and the cancellation window, are likely to benefit the hotel. That is, how the severity of the policies is likely to positively impact the hotel's financial performance. We developed a mathematical model and used cancellation and performance information data from a random sample of over 500 U.S. hotels to examine the effectiveness of a range of cancellation policies. The empirical findings support the mathematical model's prediction that moderate cancellation policies are likely to generate better financial performance levels, compared to more lenient or more stringent policies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Anbar University for Law & Political Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Sometimes, teams or players violate the rules of their leagues or associations. And sometimes, their leagues or associations respond by striking their wins from the official record. Especially in American college sports governed by the NCAA, this practice of vacating results is unpopular and widely decried. It should not be. Vacating wins can be an appropriate response to rules violations in higher-order competitions in the same way that it can be appropriate to call back a scoring play due to a penalty. We outline the conceptual framework that makes sense of when, why, and how it is appropriate to vacate wins. [ABSTRACT FROM AUTHOR]

In this paper, penalties to banks violating economic sanctions have been investigated and discussed. This topic has sparked renewed interest and attention following the beginning of the conflict in Ukraine due to the Russian aggression in February 2022 and the ongoing general deterioration in the global economic climate. Thus, based on the experience with penalties to banks for violations of economic sanctions from 2007, a theoretical model has been proposed. It is proposed that this model may be informative in devising the optimal level of penalties based on behavioral characteristics of banks and regulators. The model is based on the economic examination of the motives and incentives for bank misconduct, by drawing on the Shapiro-Stiglitz model addressing typical consequences of asymmetric information in principal-agent models. From a policy perspective, the proposed model also has the potential to provide opportunities for standardization of restrictions posed on banks as a result of bank misconduct. Relevant policy implications concerning penalties are put forward that may be implemented for future considerations, particularly in cases related to violations of economic sanctions.

In this study, a network created by converting the Petri net into a network for shutdown system, by calculating a network’s nonlinear reliability polynomial by splitting the network into two, each having a source node and an terminal node. This the procedure converts the system into two parallel-series block diagrams that are connected in a series. The metaheuristic algorithm using the honey badger algorithm (HBA) and Dwarf Mongoose Optimization Algorithm (DMO) have been used to improve the problem for the shutdown network hybridizing these algorithms employing the penalty method, we will obtained the (PFMHBA, PFMDMO) algorithms. Thereafter, we compared the results of the use of the hybridization technique with the results of the process that does not use this technique. The objective of this comparison was to ascertain whether the use of hybridization makes the results increasing reliable, reducing cost, and shortening the duration of implementation.

The article does an incisive analysis of 'Penalties' imposed by the Reserve Bank of India on the Indian commercial banks. Since 'Penalty' cannot be dissociated from 'Regulation' and 'Compliance,' the paper also studies the latter two. To the best of our knowledge, the 'Penalty' aspect has not hitherto received any serious attention in the literature. The paper covers the decade 2012-13 to 2021-22 and all the commercial banks (except Foreign Banks, Regional Rural Banks, Small Finance Banks and Payment Banks). The study does a disaggregate analysis by dividing the banks into three groups: Public Sector Banks, Old Private Banks and New Private Banks. The study not only computes the amount of penalty levied on these banks over the decade, but also analyses the reasons thereof under various sections of the relevant acts. The paper also briefly looks at the international position and concludes with a menu of policies in order to improve the trinity of 'Regulation', 'Compliance' and 'Penalty' in Indian commercial banking. [ABSTRACT FROM AUTHOR]

The article deals with topical issues of applying liability measures for untimely return of property provided for use under lease terms. Based on the norms of the current legislation, the specific features of the penalty provided for in Part 2 of Art. 785 of the Civil Code of Ukraine, and outlined the problematic issues of legal qualification of the relevant accruals from the point of view of their legal nature, the calculation period, and the duration of the statute of limitations. It is noted that the imperfection of the legislative technique led to the emergence of opposite approaches to clarifying the nature of the increased costs of the tenant for the use of the property in the non-contractual period - such charges are considered as double rent for the use of the property and as a penalty for violating the obligation to return the property. The position regarding the possibility of simultaneous charging of rent for the period of non-contractual use of the property and a penalty as a penalty for late return of the property, which was reflected in the materials of court practice, also turned out to be controversial. The legal conclusions of the Supreme Court formed at the time of preparation of the article are presented, according to which the calculation of rent must take place exclusively during the period of validity of the lease agreement, and outside the contractual period of use of the property, a penalty in the amount of double the rent for the time the property is actually in the use of the tenant is subject to application. The corresponding position was formed by the cassation instance based on the distinction between regulatory and protective prescriptions and the impossibility of their combination (identification). The work indicates the need to establish the lessee's fault in the untimely return of the property, highlighted the problematic issues of calculating the cost of using the property when renewing the lease agreement on the basis of Art. 764 of the Civil Code of Ukraine and Art. 284 of the Economic Code of Ukraine. Based on the results of the research, proposals were made to improve the current legislation, aimed at ensuring its unambiguous understanding by the participants of the tenancy relationship and the unification of the judicial practice of resolving disputes of the relevant category. [ABSTRACT FROM AUTHOR]