Balanced Decision Research Articles

Evaluating Microgrid Investments: Introducing the MPIR Index for Economic and Environmental Synergy

In view of the increasing environmental challenges and the growing demand for sustainable energy solutions, the optimization of microgrid systems with regard to economic efficiency and environmental compatibility is becoming ever more important. This paper presents the Microgrid Performance and Investment Rating (MPIR) index, a novel assessment framework developed to link economic and environmental objectives within microgrid configurations. The MPIR index evaluates microgrid configurations based on five critical dimensions: financial viability, sustainability, regional renewable integration readiness, energy demand, and community engagement, facilitating comprehensive and balanced decision making. The current cases focus on the area of Greece; however, the model can have a wider application. Developed using a two-target optimization model, this index integrates various energy sources—including photovoltaics, micro-wind turbines, and different types of batteries—with advanced energy management strategies to assess and improve microgrid performance. This paper presents case studies in which the MPIR index is applied to different microgrid scenarios. It demonstrates its effectiveness in identifying optimal configurations that reduce the carbon footprint while maximizing economic returns. The MPIR index provides a quantifiable, scalable tool for stakeholders, not only advancing the field of microgrid optimization, but also aligning with global sustainability goals and promoting the transition to a more resilient and sustainable energy future.

CIRA: Class imbalance resilient adaptive Gaussian process classifier

The problem of class imbalance is pervasive across various real-world applications, resulting in machine learning classifiers exhibiting bias towards majority classes. Algorithm-level balancing approaches adapt the machine learning algorithms to learn from imbalanced datasets while preserving the data’s original distribution. The Gaussian process classifier is a powerful machine learning classification algorithm, however, as with other standard classifiers, its classification performance could be exacerbated by class imbalance. In this work, we propose the Class Imbalance Resilient Adaptive Gaussian process classifier (CIRA), an algorithm-level adaptation of the binary Gaussian process classifier to alleviate the class imbalance. To the best of our knowledge, the proposed algorithm (CIRA) is the first adaptive method for the Gaussian process classifier to handle unbalanced data. The proposed CIRA algorithm consists of two balancing modifications to the original classifier. The first modification balances the posterior mean approximation to learn a more balanced decision boundary between the majority and minority classes. The second modification adopts an asymmetric conditional prediction model to give more emphasis to the minority points during the training process. We conduct extensive experiments and statistical significance tests on forty-two real-world unbalanced datasets. Through the experiments, our proposed CIRA algorithm surpasses six popular data sampling methods with an average of 2.29%, 3.25%, 3.67%, and 1.81% in terms of the Geometric mean, F1-measure, Matthew correlation coefficient, and Area under the receiver operating characteristics curve performance metrics respectively.

StaRS: Learning a Stable Representation Space for Continual Relation Classification.

Relation classification (RC) aims to detect the semantic relation between two annotated entities in a piece of sentence, serving as an essential task in automatic knowledge graph construction. Due to the emergence of new relations, there is a recent trend to train RC models in continual settings. To overcome the catastrophic forgetting problem in continual learning, existing research is devoted in a two-stage training paradigm, fast adaptation to novel relations, and memory replay for all historical relations. These memory-replay-based methods explore different techniques to mitigate the forgetting problem of continual RC (CRC) models during the memory replay stage. However, we find that the representation space undergoes distortion due to the incoming of fresh relations in the fast adaptation phase. To address this issue, we propose using a knowledge distillation strategy and designing a margin loss, aiming to maintain the stability of the RC model during adaptation to new relations. In addition, in the second stage, with a limited number of typical memory instances available, we introduce a self-contrastive learning objective to facilitate learning a balanced decision boundary for RC. Through training in two stages, our objective is to acquire a stable representation space to encode instances for CRC. We experimentally demonstrate the superiority of our model over competing methods in various settings, and the results suggest that our tailored designs can achieve better performance in CRC.

Exploring Connections Between Team Process and Automation Error Management

In complex social-technical systems, human teams are required to handle automation errors to maintain system performance. This study developed two path models that connected the team process variables with the automation error management process, based on data collected from a previous experiment. The models show that trust has negative effects on most of the management activities. Team situation awareness could facilitate the whole process by supporting information selecting activity during the analysis and planning stage. Better teamwork could assist the stages of error detection and analysis and planning. Teams with more balanced decision making and workload would find it easier to understand and handle an automation error. The results also reveal that forming an interpretation of the error is helpful but not a necessity for error management. Path models developed in this study provide a technical basis for better team processes in the face of automation error.

The incidence risk of gynecological cancer by antipsychotic use: a meta-analysis of 50,402 patients

BackgroundFemale gynecological cancers represent a serious public health problem, with 1,398,601 new diagnoses and 671,875 deaths per year worldwide. Antipsychotics are often used in psychiatric disorders, including schizophrenia, bipolar disorder, and major depression. It is estimated that the prescription of these drugs is linked to 1,800 deaths a year in the United States, but their association with cancer remains controversial.MethodsWe searched PubMed, Scopus, and Web of Science databases for studies reporting the correlation in the incidence risk of gynecological cancer by antipsychotic use. We used DerSimonian and Laird random-effect models to compute logit transformed odds ratio (OR) for the primary binary endpoint with 95% confidence interval (CI). Heterogeneity was assessed through effect size width along with I-squared and Tau-squared statistics. Review Manager 5.4.1. was used for statistical analyses. A p-value of < 0.05 denoted statistically significant.Results50,402 patients were included, of whom 778 (1,54%) took antipsychotic medication for at least 1 year. 1,086 (2,15%) with ovarian cancer and 49,316 (97,85%) with endometrial cancer. Antipsychotic use (OR 1.50; 1.06 to 2.13 95% CI; p-value 0.02), hypertension (OR 1.50; 95% CI 1.06 to 2.13; p-value < 0.01), nulliparity (OR 1.98; 95% CI 1.53 to 2.57; p-value < 0.01) and multiparity (OR 0.53; 95% CI 0.41 to 0.69; p-value < 0.01) showed significantly different distributions between groups of cancer and cancer-free patients. The primary endpoint of incidence risk of gynecological cancer by antipsychotic therapy showed a statistically significant difference (OR 1.67; 95% CI 1.02 to 2.73; p-value < 0.05) against the use of antipsychotic drugs.ConclusionsOur meta-analysis showed that the use of antipsychotic drugs increases the risk of gynecological cancers, particularly endometrial cancer. This result should be weighed against the potential effects of treatment for a balanced prescribing decision.

모의재판식 토론을 통해 포의 ｢검은 고양이｣ 가르치기

This essay explores the effects of teaching Edgar Allan Poe’s “The Black Cat” through mock trial debate. Based on the assumption that the mock trial debate form can complement the shortcomings of general discussion, the project assigns each student a different role - the accused narrator and his lawyer, the policeman as a witness and prosecutor, judge and court clerk. After preparing for 25 minutes, students start the mock trial under the judge’s moderation. The clerk records the process and presents the final verdict to the whole class. Through this approach, students are expected to improve skills not only for close reading, but also for reading with the grain and against the grain altogether; they are also expected to learn how to support their argument with evidence, persuade others, make a balanced decision, and deliver it neutrally. The mock trial debate was carried out in the fall semesters of 2022 and 2023, and was followed by a survey that asked students whether the experienced improvement in five areas: interest, text comprehension, critical thinking ability, communication skills, and other skills. The students answered most of the questions positively, thereby affirming the effectiveness of mock trial debate in the lesson on “The Black Cat.” The experiment exemplifies how we can develop our expertise as researchers and teachers to maximize the effectiveness of discussion.

Securing the network in e-retailing and manufacturing: a balanced decision analysis under competition and cooperation modes

With the continuous emergence of network problems, the e-commerce supply chain faces the risk of network attacks. This paper studies a dual-channel supply chain, where manufacturers can earn revenue through online channels (i.e. manufacturers sell products through e-retailers) and offline channels (i.e. manufacturers sell products directly to consumers). In the online channel, we analysed two modes. The first is the competitive model, where e-tailers buy products from manufacturers and resell them to consumers. The second is a cooperative model, in which manufacturers pay a commission to sell products to consumers on e-retailer platforms. We divide the network risk prevention methods into three models: the M model (wherein the manufacturer conducts risk defense blocking), the E model (wherein e-retailers conduct risk defense blocking), and the ME model (wherein e-retailers and manufacturers conduct risk defense blocking simultaneously). These cases are discussed in this paper. The results show that manufacturers and e-retailers will gain the highest profit in the ME model, regardless of competition mode or cooperation mode. As a result, manufacturers and retailers can simultaneously mount cyber defenses seeking to maximize profits. In addition, government subsidies have a positive effect on encouraging supply chain members to take defensive measures.

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Individualized survival prediction and surgery recommendation for patients with glioblastoma.

There is a lack of individualized evidence on surgical choices for glioblastoma (GBM) patients. This study aimed to make individualized treatment recommendations for patients with GBM and to determine the importance of demographic and tumor characteristic variables in the selection of extent of resection. We proposed Balanced Decision Ensembles (BDE) to make survival predictions and individualized treatment recommendations. We developed several DL models to counterfactually predict the individual treatment effect (ITE) of patients with GBM. We divided the patients into the recommended (Rec.) and anti-recommended groups based on whether their actual treatment was consistent with the model recommendation. The BDE achieved the best recommendation effects (difference in restricted mean survival time (dRMST): 5.90; 95% confidence interval (CI), 4.40-7.39; hazard ratio (HR): 0.71; 95% CI, 0.65-0.77), followed by BITES and DeepSurv. Inverse probability treatment weighting (IPTW)-adjusted HR, IPTW-adjusted OR, natural direct effect, and control direct effect demonstrated better survival outcomes of the Rec. group. The ITE calculation method is crucial, as it may result in better or worse recommendations. Furthermore, the significant protective effects of machine recommendations on survival time and mortality indicate the superiority of the model for application in patients with GBM. Overall, the model identifies patients with tumors located in the right and left frontal and middle temporal lobes, as well as those with larger tumor sizes, as optimal candidates for SpTR.

Effects of sediment-storage dams on suspended sediment transport in the Sera Lake Watershed, northeast Turkey

In this study, the effects of cascade sediment-storage dams (SSDs) on the suspended sediment (SS) transport in the Sera Lake Watershed (northeast Turkey) were investigated. Ten SS monitoring stations from upstream (S01) to downstream (S10) were selected for the study considering the locations of the SSDs and Sera Lake. In a gauging station, where S05 was selected, the water stage monitoring studies were also conducted, and daily discharges and SS loads were computed. The Spearman correlation coefficient between SS and discharges data was computed as 0.592. The deterioration of the naturalness of the watershed with external interventions was effective on this value. While the Sera Lake trapped 33% of the SS transport, this value varied between –25.8 and 44% for SSDs. Although the SSDs have been proportionately succeed in trapping the SS, they have been insufficient in preventing sedimentation and problems caused by sediment transport in the watershed. In addition, the annual average soil erosion amount was determined by the revised universal soil loss equation (RUSLE) method in the watershed. According to the RUSLE method, the annual average soil loss of the watershed is 1.65 tons/ha. The SDR value of the watershed was calculated as 0.104. Integrating different environmental management tools to achieve a balanced and sustainable decision, a strategic environmental management plan should be constituted.

Economic priorities over population health: A political dilemma in addressing noncommunicable diseases in developing countries.

The world is observing a rapid shift in the burden of diseases with predominance of noncommunicable diseases (NCDs). NCDs contribute to 41 million deaths which is equivalent to 74% of all death globally per year. There is ongoing debate on the approaches to reduce public exposure to NCDs' modifiable risk factors which are of economic potential. As the World Health Organizationand the World Bank recommend the implementation of taxation to these factors, still questions arise on the effectiveness, sustainability, and practicality of this strategy. With the ongoing transition globally from consumption of natural to processed foods, it is important to counter-check the best interventions on how to protect people from unhealthy eating behaviors. While taxation on unhealthy food and other products like tobacco has been recommended as one among interventional approaches, its effectiveness on sugar sweetened beverages is not reliable compared to approaches that increase self-control. Despite the perceived economic benefits of tobacco and sugar sweetened products, there is detrimental implication in terms of public health. The introduction of taxation which favors public health faces challenges due to conflict of interest from government authorities and other stakeholders. The intertwined relationship between public health and economic development becomes more obvious during implementation of preventive and control measures against modifiable risk factors for NCDs. It is evident that reaching a balanced rational decision on choosing between economic growth and public health is difficult. Countries should enhance both local and international intersectoral and multisectoral approaches in creating integrative policies which include health component in all non-health policies including economic policies so as to harmonize public health and economic growth during this era of extensive globalization.

Equine blood oxygenation as a coefficient of performance

In horse breeding, it is important to introduce affordable methods for assessing the potential of the horse’s body to perform work of varying severity and in different terrain conditions (altitude, landscape features, type of work). The applicability of the method of dosing the load of working horses in highland conditions has been established on the basis of the value of the horse’s body weight calculated using the “heart girth” measurement, but the work should already be classified as heavy at a load weight of 15% of the horse’s body weight. The arterial molecular oxygen saturation of the blood and the pulse rate are sufficient to assess the state of respiratory function and the nature of the involvement of associated systems. The studies carried out on 14 mature working horses and also on 5 young horses used for work in lowland and highland conditions have made it possible to recommend the widespread use of the pulse oximeter for rapid analysis of blood oxygen saturation and pulse rate in order to dose the workload of these animals appropriately. Veterinary examination of horses with abnormal oxygen saturation and pulse pattern detected by the pulse oximeter confirmed the presence of clinical signs and laboratory markers of disorders in the body of a stallion and a repair mare, excluding the use of these animals as working animals. Early detection of inadequate respiratory function in young animals can allow a balanced decision to be made to refuse special training and prevent economic losses.

МОДЕЛИРОВАНИЕ ЭКОЛОГИЧЕСКИ РАЦИОНАЛЬНОГО ВЫБОРА ТИПА ГОРОДСКОГО ПАССАЖИРСКОГО ТРАНСПОРТА

The issue of a rational and balanced management decision is being considered to determine the necessary use of passenger vehicles of various brands, their number and models according to passenger capacity, which will ensure a reduction in the negative impact of passenger vehicles on the ecological state of the environment.

Efficient and Balanced Exploration-driven Decision Making for Autonomous Racing Using Local Information

Efficient and Balanced Exploration-driven Decision Making for Autonomous Racing Using Local Information

Addressing Skewed Heterogeneity via Federated Prototype Rectification With Personalization.

Federated learning (FL) is an efficient framework designed to facilitate collaborative model training across multiple distributed devices while preserving user data privacy. A significant challenge of FL is data-level heterogeneity, i.e., skewed or long-tailed distribution of private data. Although various methods have been proposed to address this challenge, most of them assume that the underlying global data are uniformly distributed across all clients. This article investigates data-level heterogeneity FL with a brief review and redefines a more practical and challenging setting called skewed heterogeneous FL (SHFL). Accordingly, we propose a novel federated prototype rectification with personalization (FedPRP) which consists of two parts: federated personalization and federated prototype rectification. The former aims to construct balanced decision boundaries between dominant and minority classes based on private data, while the latter exploits both interclass discrimination and intraclass consistency to rectify empirical prototypes. Experiments on three popular benchmarks show that the proposed approach outperforms current state-of-the-art methods and achieves balanced performance in both personalization and generalization.

Certain aspects of the violation of the right to defense at the stage of notification of suspicion

The article focuses on the study of certain aspects of the violation of the right to defense at the stage of notification of suspicion. In the process of investigating the subject it is emphasized that the prosecution's unjustified delay in the notification of suspicion deprives a person of the right to protection against criminal prosecution. It was established that the decision to make a notification of suspicion should be made without delay in order to timely acquire the procedural status of a suspect and, accordingly, provide the suspect with the opportunity to defend himself against criminal prosecution. It was determined that the right to defense at a pre-trial investigation is violated not only as a result of untimely (late) notification of a person of suspicion, but also as a result of premature completion of a pre-trial investigation after notification of a person of suspicion. It is indicated that the quick completion of the pre-trial investigation (immediately after the notification of suspicion) deprives the person, against whom criminal prosecution was carried out, to fully exercise his right to protection against the already actually completed criminal prosecution within the framework of the pre-trial stage. Amendments to part 2 of article 283 of the Criminal Procedure Code of Ukraine, namely to provide for a mandatory minimum period of 14 days from the moment of notification of suspicion to the day of closing of criminal proceedings; petitioning the court to release a person from criminal liability; appeal to the court with an indictment, a request for the application of coercive measures of a medical or educational nature. Making such changes to the criminal procedural law will allow: to fully guarantee the observance of the right to defense at the stage of pre-trial investigation to persons subject to criminal prosecution; it is more rational to plan the conduct of the pre-trial investigation by the investigator/prosecutor; make a more balanced decision about notifying a person of suspicion. It was concluded that the right to protection violated at the stage of the pre-trial investigation cannot be compensated during the court proceedings, which leads to the unfairness of the criminal proceedings as a whole and the need to acquit the person on all charges.

ON THE IDENTITY OF THE LEGAL SYSTEM OF THE REPUBLIC OF UZBEKISTAN

xThe historical development and cultural and legal traditions of the Republic of Uzbekistan have had asignificant impact on the formation and improvement of its legal system. Original in content, it reflects thetransition from the socialist to another type associated with the strengthening of national Uzbek and Slaviccustoms. The modern policy of the state is aimed at creating a stable legal system through the legislativeconsolidation and consolidation of public relations and social values. Understanding the peculiarities ofthe legal system of the Republic of Uzbekistan is necessary for a qualified analysis of draft laws, for makinga balanced decision on the expediency of reception, competently overcoming current problems and a realassessment of the legal consciousness of the Uzbek people.

CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection.

O-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier design, greatly affect the accuracy of computational methods for predicting Oglyc sites. Based on an efficient feature selection algorithm and a classifier capable of handling imbalanced datasets, a new computational method, ChiMIC-based balanced decision table O-glycosylation (CBDT-Oglyc), is proposed. ChiMIC-based balanced decision table for O-glycosylation (CBDT-Oglyc), is proposed to predict Oglyc sites in proteins. Sequence characterization is performed by combining amino acid composition (AAC), undirected composition of [Formula: see text]-spaced amino acid pairs (undirected-CKSAAP) and pseudo-position-specific scoring matrix (PsePSSM). Chi-MIC-share algorithm is used for feature selection, which simplifies the model and improves predictive accuracy. For imbalanced classification, a backtracking method based on local chi-square test is designed, and then cost-sensitive learning is incorporated to construct a novel classifier named ChiMIC-based balanced decision table (CBDT). Based on a 1:49 (positives:negatives) training set, the CBDT classifier achieves significantly better prediction performance than traditional classifiers. Moreover, the independent test results on separate human and mouse glycoproteins show that CBDT-Oglyc outperforms previous methods in global accuracy. CBDT-Oglyc shows great promise in predicting Oglyc sites and is expected to facilitate further experimental studies on protein glycosylation.

Peri-Operative Mortality and Survival After Repair of Abdominal Aortic Aneurysm in Advanced Age Patients: A National Study from the Norwegian Registry for Vascular Surgery Focused on Nonagenarians

Treatment of abdominal aortic aneurysm (AAA) in nonagenarians has become more frequent. This national observational cohort study aimed to investigate peri-operative mortality and survival after AAA surgery in nonagenarians in Norway. All AAA repairs registered in the Norwegian Registry for Vascular Surgery from 2015 to 2021 were identified and stratified into nonagenarians > 90 years old (n= 77), octogenarians 80 - 89 years old (n= 1 362), and patients < 80 years old (n= 4 590). The patient characteristics and comorbidities were recorded, and the 30 and 90 day mortality rates were calculated. Kaplan-Meier analysis was performed to obtain the estimated median survival and survival curves. In the nonagenarians, the 30 day mortality rates were 2.5% in asymptomatic patients, 33.3% in symptomatic patients, and 59.1% in the patients with a ruptured AAA (rAAA). The estimated median survival (years) were 3.3 (95% confidence interval [CI] 1.95 - 4.59) for asymptomatic AAA, 2.9 (interquartile range [IQR] 2.82, 5.80) for symptomatic AAA, and 0.1 for rAAA (IQR 0.01, 3.04). For nonagenarians surviving the first 90 days, the estimated median survival (years) were 4.2 (95% CI 2.56 - 5.88) for asymptomatic AAA, 3.4 (IQR 2.86, 5.80) for symptomatic AAA, and 3.8 (IQR 1.49, 4.85) for rAAA. The 90 day mortality rates were 100.0%, 80.0%, and 62.5% for asymptomatic, symptomatic, and rAAA, respectively, after open surgical repair (OSR), and 5.1%, 10.0%, and 50.0%, respectively, after endovascular aortic repair (EVAR). Peri-operative mortality and survival results after AAA surgery in nonagenarians support treatment of selected asymptomatic patients. The 90 day survivors had an expected survival of more than three years, enabling balanced decision making regarding surgical vs. conservative treatment options in this challenging cohort. EVAR is the treatment method of choice for AAA in nonagenarians because most of them would probably live longer untreated than if treated by OSR.

Историко-правовые аспекты создания Ассамблеи по определению государственной целесообразности в Исламской Республике Иран

The Islamic Republic of Iran (hereinafter — Iran) is a unique state. It combines the functioning of republican institutions of state power along with religious specifics, due to the fact that in this state there is an official religion — Shia Islam of the Jafarite persuasion. When the Iranian constitution was created after the Islamic revolution of 1979, it fixed the presence of a religious-constitutional control of a body called the Guardian Council over the laws adopted by the parliament, which is one of the main manifestations of the Islamic nature of state power in Iran at the present time. It was this specificity of the state mechanism of Iran that served as the reason for the creation of the Expediency Discernment Council, because the practice of legislative activity has shown that sometimes the Parliament — the Islamic Consultative Assembly — and the Supervisory Board are not able to reach a compromise on about the law being passed. And this, in turn, led to a crisis in public administration, since, on the one hand, the need for legislative regulation of public relations remained, and on the other hand, there were no legal mechanisms for forcing the Parliament and the Guardian Council to make a balanced decision.