Correct Decisions Research Articles

Strategic Analysis from a consulting context for the Super Kinder School Institution

In the current dynamic, managers of educational institutions such as Super Kinder School seek correct decisions to enhance internal efficiency and meet organizational objectives. A strategic analysis was carried out applying the interpretivist methodology through a case design and an interview with the director of the institution. This qualitative approach has given rise to strategic matrices such as Porter's Five Forces, EFE, EFI, IE, SWOT, PEYEA, MPCE, MIC MAC, complemented by the Balanced Scorecard tool. Strategies focused on market growth, product and service development, and market penetration were identified, seeking to improve internal processes and promote the growth of Super Kinder School. The consultancy is aimed at addressing essential activities for the continuous development of Super Kinder School, requiring a deep understanding of the institution, its achievements and educational service

Research on identification of flight cadets’ cognitive load based on multi-source physiological data and CGAN-DBN model

Modern aircraft cockpit system is highly information-intensive. Pilots often need to receive a large amount of information and make correct judgments and decisions in a short time. However, cognitive load can affect their ability to perceive, judge and make decisions accurately. Furthermore, the excessive cognitive load will induce incorrect operations and even lead to flight accidents. Accordingly, the research on cognitive load is crucial to reduce errors and even accidents caused by human factors. By using physiological acquisition systems such as eye movement, ECG, and respiration, multi-source physiological signals of flight cadets performing different flight tasks during the flight simulation experiment are obtained. Based on the characteristic indexes extracted from multi-source physiological data, the CGAN-DBN model is established by combining the conditional generative adversarial networks (CGAN) model with the deep belief network (DBN) model to identify the flight cadets’ cognitive load. The research results show that the flight cadets’ cognitive load identification based on the CGAN-DBN model established has high accuracy. And it can effectively identify the cognitive load of flight cadets. The research paper has important practical significance to reduce the flight accidents caused by the high cognitive load of pilots.

Incorporating multi-perspective information into reinforcement learning to address multi-hop knowledge graph question answering

Knowledge graph question answering (KGQA) aims to answer natural language questions from structured knowledge graphs (KGs). Traditional KQGA methods are usually limited to single-hop queries and cannot handle complex questions involving multi-hop reasoning well. To overcome this issue, multi-hop KGQA based on reinforcement learning (RL) has been proposed. However, multi-hop KGQA based on RL still faces some challenges. Firstly, due to the insufficient availability of latent environmental information during the reasoning process, the agent finds it challenging to make coherent and correct decisions. Secondly, the agent only receives rewards from the environment upon reaching the answer entity during the exploration, leading to slow or even obstructed learning. To address these shortcomings, we construct multi-perspective information based on the state of the environment, and integrate multi-perspective information with RL framework, thereby creating the Multi-Perspective Information Fusion Reasoning Network (MPIFRN). MPIFRN achieves the goal via three steps. (1) We construct three different views of information, i.e., expectation embedding, instruction-guided embedding, and path-aware embedding. These environmental cues provide more reliable support for decision-making. (2) We still adopt the method of mapping entities and relations into the knowledge graph embedding space to answer multi-hop questions. At each step of reasoning, we use a scoring function to measure the plausibility of each “triple” ¡topic entity, question, candidate entity¿ in the embedding space. (3) Furthermore, we employ the asynchronous advantage actor-critic (A3C) algorithm to guide the agent in selecting the most promising entities and to expand the reasoning paths in parallel by updating policy and value network parameters, thereby facilitating multi-hop knowledge graph question answering. We conduct extensive experiments on KGQA benchmark datasets, providing substantial evidence to demonstrate the effectiveness of our approach.

Age-related and experience-related differences in selected motor cognitive abilities of soccer players

Background: Soccer players constantly experience rapidly changing situations that challenge them to receive and process stimuli, make fast and correct decisions, and perform actions at specific moments. The aim of the present study was to analyze age and experience-related differences in the level of brain speed, disjunctive reaction time, and reaction speed of soccer players. Methods: A total of 111 soccer players (x=12.414; s=1.921) divided by age and level of experience participated in the study. The diagnosis of brain speed and disjunctive reactivity was carried out with the BrainHQ Hawk Eye test and BrainHQ Agility test using the Witty Sem system. Reaction speed was diagnosed with the Fitro Agility Check test using the Fitro Agility system. The Mann-Whitney U test and the Kruskal-Wallis analysis of variance were used to determine the significance of age and experiencerelated differences in the level of brain speed, disjunctive reaction time, and reaction speed of the soccer players. Results and conclusion: Statistically significant differences (p<0.01) in favor of older age categories were observed between disjunctive reaction time and brain speed. Younger soccer players showed significantly lower levels of lower limb reaction speed in both directions of the sagittal plane than older players (p<0.01). Less experienced soccer players demonstrated significantly lower levels of lower limb reaction speed in both directions of the sagittal plane than more experienced counterparts and lower levels of brain speed and disjunctive reaction time (p<0.01).

Application of autogenous block bone graft in the reconstruction of severe alveolar crest defect

Patients with severe alveolar ridge defects cannot be directly implanted and repaired, which seriously affects their quality of life. Onlay bone grafting is the main solution for severe alveolar ridge bone defect reconstruction, among which autogenous block bone grafting is the most widely used and is also the focus of clinical research on bone tissue reconstruction. This article expounds the characteristics and basic principles of autogenous bone block grafting, and comprehensively analyzes the selection of autogenous bone donor site, the principles of surgical operation, and the progress of bone graft techniques. In order to help surgeons make correct clinical decisions, increase the predictability of surgical effects, and improve the level of clinical diagnosis and treatment.

РАЗРАБОТКА МЕТОДИЧЕСКИХ ОСНОВ ОРГАНИЗАЦИИ ПРОВЕДЕНИЯ УЧЕНИЙ АВАРИЙНО-СПАСАТЕЛЬНЫХ СЛУЖБ ДЛЯ ОТРАБОТКИ ДЕЙСТВИЙ В ЧРЕЗВЫЧАЙНОЙ СИТУАЦИИ АВАРИИ ВОЗДУШНОГО СУДНА

The tasks that need to be worked out during exercises to improve the safety and efficiency of the organization of air traffic are considered. The main problem in solving the problems of fire safety is the time to make a single correct decision when carrying out rescue operations. Recently, exercises involving all responding units have become widespread because they can help to work out the practical tasks of rescuing people and the most rational management decisions in conditions of limited initial information and the presence of many criteria that can not be foreseen. This article considers the issues of management and interaction of fire-fighting, rescue, canine and other services during fire-extinguishing and tactical exercises to organize fire-fighting and rescue of people in situations of aircraft accidents. On the basis of the accumulated world experience in aircraft accidents and the analysis of the consequences of various aircraft accidents, the methodological recommendations for training of rescue units in simulating emergency situations of aircraft in various variants of abnormal situations were worked out.

Behavioral and neural measures of confidence using a novel auditory pitch identification task.

Observers can discriminate between correct versus incorrect perceptual decisions with feelings of confidence. The centro-parietal positivity build-up rate (CPP slope) has been suggested as a likely neural signature of accumulated evidence, which may guide both perceptual performance and confidence. However, CPP slope also covaries with reaction time, which also covaries with confidence in previous studies, and performance and confidence typically covary; thus, CPP slope may index signatures of perceptual performance rather than confidence per se. Moreover, perceptual metacognition-including neural correlates-has largely been studied in vision, with few exceptions. Thus, we lack understanding of domain-general neural signatures of perceptual metacognition outside vision. Here we designed a novel auditory pitch identification task and collected behavior with simultaneous 32-channel EEG in healthy adults. Participants saw two tone labels which varied in tonal distance on each trial (e.g., C vs D, C vs F), then heard a single auditory tone; they identified which label was correct and rated confidence. We found that pitch identification confidence varied with tonal distance, but performance, metacognitive sensitivity (trial-by-trial covariation of confidence with accuracy), and reaction time did not. Interestingly, however, while CPP slope covaried with performance and reaction time, it did not significantly covary with confidence. We interpret these results to mean that CPP slope is likely a signature of first-order perceptual processing and not confidence-specific signals or computations in auditory tasks. Our novel pitch identification task offers a valuable method to examine the neural correlates of auditory and domain-general perceptual confidence.

Biologically inspired architecture for the identification of ambiguous objects using scene associations

As humans, we have an excellent performance when perceiving the environment. In the artificial world, it is important for machines to perceive their environment so they can make correct decisions and act accordingly. An essential process to accomplish perception is to identify objects in a scene, but, as in reality, these objects can appear as ambiguous, and additionally, those objects are embedded into a particular scene. For our proposal, we created an architecture to identify ambiguous objects by using scene information to guide the identification process. The design is based on the human cortical systems that participate in object and scene recognition. In our study, we validate this proposal by analyzing a prior human experiment that demonstrates and quantifies the impact of scene information on ambiguous objects. Our findings demonstrate that employing the presented architecture on an object recognition task results in superior machine performance with familiar scenes, as opposed to unfamiliar or absent ones, consistent with human behavior.

Method for synthesis of models for assessing the state of ram memory of operators of human-machine systems based on fuzzy decision making logic

The purpose of the research is to develop a method for synthesizing models for assessing the state of RAM of operators of human-machine systems, the use of which in the decisive rules for predicting and diagnosing the states of RAM and its blocks ensures an increase in the quality of decisions made.Methods. To monitor the state of various RAM blocks, the following set of techniques was selected: searching for a signal in noise; "identification"; full reproduction; identification of missing digits; Memory. To select an adequate mathematical research apparatus, an exploratory analysis of the structure of the processed data was carried out, during which it was found that the selected classes of RAM states are of a fuzzy nature with uncertain boundaries of their intersections. Taking into account the peculiarities of the processed data, the selected methodology was modified by developing a new method for fuzzy assessment of the state of RAM based on the characteristics of its properties in combination with informative features characterizing the ergonomics of the workplace, the environmental component and individual risk factors.Results. In the course of the research, a model was synthesized for predicting the appearance and development of dysfunctions of RAM in operators of information-rich systems, characterized by the use of indicators characterizing the state of RAM blocks as predictors, which allows one to obtain confidence in the correct decision-making of no worse than 0,85.Conclusion. In the course of the studies, it was shown that in order to improve the quality indicators of forecasting and diagnosing the states of RAM and its blocks, when synthesizing the corresponding decision rules, indicators characterizing the state of RAM blocks, energy imbalance of BAP, ergonomic and individual risk factors should be taken into account. With this approach, in forecasting problems, confidence in the correct decision-making is achieved at least 0,85. In the tasks of diagnosing the early stages of RAM disorders among operators of information-rich systems, confidence in correct decision-making exceeds 0,95.

Design of an information-computer system for the automated modeling of systems for automatic orientation of production objects in the machine and instrument industries

An information-computer system has been developed for the automated modeling of systems for automatic orientation of production objects, which is one of the most important and complex creative flexible production systems of machine and instrument engineering. The proposed information-computer system for automated modeling of systems of automatic orientation of production objects is an effective tool for solving an important task of a scientific and applied nature. Its use makes it possible to increase the speed and efficiency of information processing and to make correct and well-founded decisions when determining the composition and method of organization of systems of automatic orientation of production objects. The structure of this information-computer system is a specific set of software and hardware and information and telecommunication tools and interactive functional modules. This structure reproduces a certain paradigm that conditions the integrity and integration of the information-computer system for automated modeling of systems for automatic orientation of production objects in flexible production systems. In addition, uniformity, extensibility, the possibility of modernization and changeability of software components, protection of information from unauthorized access and preservation of commercial secrets are ensured according to international criteria for evaluating the protection of the computer system. Neuro-fuzzy network information processing and computer vision algorithms have been implemented for automatic identification of production objects and orientation devices, which are components of automatic orientation systems of production objects. The developed information-computer system processes information in real time with high accuracy and speed

GraphMriNet: a few-shot brain tumor MRI image classification model based on Prewitt operator and graph isomorphic network

Brain tumors are regarded as one of the most lethal forms of cancer, primarily due to their heterogeneity and low survival rates. To tackle the challenge posed by brain tumor diagnostic models, which typically require extensive data for training and are often confined to a single dataset, we propose a diagnostic model based on the Prewitt operator and a graph isomorphic network. Firstly, during the graph construction stage, edge information is extracted from MRI (magnetic resonance imaging) images using the Prewitt filtering algorithm. Pixel points with a gray value intensity greater than 128 are designated as graph nodes, while the remaining pixel points are treated as edges of the graph. Secondly, the graph data is inputted into the GIN model for training, with model parameters optimized to enhance performance. Compared with existing work using small sample sizes, the GraphMriNet model has achieved classification accuracies of 100%, 100%, 100%, and 99.68% on the BMIBTD, CE-MRI, BTC-MRI, and FSB open datasets, respectively. The diagnostic accuracy has improved by 0.8% to 5.3% compared to existing research. In a few-shot scenario, GraphMriNet can accurately diagnose various types of brain tumors, providing crucial clinical guidance to assist doctors in making correct medical decisions. Additionally, the source code is available at this link: https://github.com/keepgoingzhx/GraphMriNet.

Goodness-of-fit tests for multinomial models with inverse sampling

This article proposes goodness-of-fit tests for multinomial models using an inverse sampling scheme. From the multiple decision-theoretic perspective, we devise a test statistic and stopping rule that satisfy a prespecified probability level P* and obtain corresponding optimal sample sizes. Incomplete Dirichlet type II distribution functions are used to develop the procedure and to express the probability of correct decisions for various cell configurations for multinomial models. For empirical studies, Monte Carlo experiments are conducted, and for illustrations, various cell configurations of a wheel of fortune are demonstrated.

Health professionals’ acceptance of mobile-based clinical guideline application in a resource-limited setting: using a modified UTAUT model

IntroductionClinical guidelines are crucial for assisting health professionals to make correct clinical decisions. However, manual clinical guidelines are not accessible, and this increases the workload. So, a mobile-based clinical guideline application is needed to provide real-time information access. Hence, this study aimed to assess health professionals’ intention to accept mobile-based clinical guideline applications and verify the unified theory of acceptance and technology utilization model.MethodsInstitutional-based cross-sectional study design was used among 803 study participants. The sample size was determined based on structural equation model parameter estimation criteria with stratified random sampling. Amos version 23 software was used for analysis. Internal consistency of latent variable items, and convergent and divergent validity, were evaluated using composite reliability, AVE, and a cross-loading matrix. Model fitness of the data was assessed based on a set of criteria, and it was achieved. P-value < 0.05 was considered for assessing the formulated hypothesis.ResultsEffort expectancy and social influence had a significant effect on health professionals’ attitudes, with path coefficients of (β = 0.61, P-value < 0.01), and (β = 0.510, P-value < 0.01) respectively. Performance expectancy, facilitating condition, and attitude had significant effects on health professionals’ acceptance of mobile-based clinical guideline applications with path coefficients of (β = 0.37, P-value < 0.001), (β = 0.44, P-value < 0.001) and (β = 0.57, P-value < 0.05) respectively. Effort expectancy and social influence were mediated by attitude and had a significant partial relationship with health professionals’ acceptance of mobile-based clinical guideline application with standardized estimation coefficients of (β = 0.22, P-value = 0.027), and (β = 0.19, P-value = 0.031) respectively. All the latent variables accounted for 57% of health professionals’ attitudes, and latent variables with attitudes accounted for 63% of individuals’ acceptance of mobile-based clinical guideline applications.ConclusionsThe unified theory of acceptance and use of the technology model was a good model for assessing individuals’ acceptance of mobile-based clinical guidelines applications. So, enhancing health professionals’ attitudes, and computer literacy through training are needed. Mobile application development based on user requirements is critical for technology adoption, and people’s support is also important for health professionals to accept and use the application.

Trust in automation and the accuracy of human–algorithm teams performing one-to-one face matching tasks

The human face is commonly used for identity verification. While this task was once exclusively performed by humans, technological advancements have seen automated facial recognition systems (AFRS) integrated into many identification scenarios. Although many state-of-the-art AFRS are exceptionally accurate, they often require human oversight or involvement, such that a human operator actions the final decision. Previously, we have shown that on average, humans assisted by a simulated AFRS (sAFRS) failed to reach the level of accuracy achieved by the same sAFRS alone, due to overturning the system’s correct decisions and/or failing to correct sAFRS errors. The aim of the current study was to investigate whether participants’ trust in automation was related to their performance on a one-to-one face matching task when assisted by a sAFRS. Participants (n = 160) completed a standard face matching task in two phases: an unassisted baseline phase, and an assisted phase where they were shown the identification decision (95% accurate) made by a sAFRS prior to submitting their own decision. While most participants improved with sAFRS assistance, those with greater relative trust in automation achieved larger gains in performance. However, the average aided performance of participants still failed to reach that of the sAFRS alone, regardless of trust status. Nonetheless, further analysis revealed a small sample of participants who achieved 100% accuracy when aided by the sAFRS. Our results speak to the importance of considering individual differences when selecting employees for roles requiring human–algorithm interaction, including identity verification tasks that incorporate facial recognition technologies.

Algorithm for forming a set of indicators of international trade customs regulation effectiveness in the EAEU member states

The relevance of the study is due to the fact that international trade globalization and intensification increase competitiveness of not only domestic but also foreign producers, so the business sector expects to facilitate business conditions, simplify customs procedures, increase customs activities efficiency, and improve customs services provision. Goods transportation across the customs borders of countries around the world presents challenges in filling out documentation, transportation methods, information processing, and compliance with regulations that are not internationally harmonized. It leads to customs laws violations that must be detected during the customs control process. Consequently, customs regulation effectiveness will depend directly on the customs control results. The article presents a theoretical and methodological description of the procedure for assessing international trade customs regulation effectiveness in the EAEU member states, as well as a vector for developing a comprehensive set of performance indicators. The proposed assessment algorithm and the set of quantitative and qualitative indicators can be regarded as fundamental interrelated criteria that ensure improvement of efficiency of control over the customs authorities’ activities and corrective management decisions, if necessary. The application in customs practice of the proposed indicators for assessing international trade customs regulation effectiveness will contribute to customs policy effective implementation for the harmonious development of the EAEU member states’ economies, including Russia, in modern society and the basis of their sustainable political, economic and social development.

The Role Of International Financial Reporting Standards (IFRS) In Enhancing The Quality Of Financial Reporting Applied Research In a Sample Of Iraqi Banks Listed On The Iraq Stock Exchange

The aim of the research is to show the importance of applying IFRS standards at the international and local levels in Iraqi banks and its reflection. This research used statistical methods and indicators, as the data were collected through the distribution of questionnaires to a sample of international development banks, and Gulf commercial banks, to accountants and auditors working in Iraq, where they were distributed to (226) participants and analyzed using SPSS v 26 and Amos v 26, as well as a study comparing the impact of the application of IFRS-9 before and after by analyzing the financial statements of the above banks. The research included the study of several topics, including an overview of IFRS standards and the quality of financial reports, the definition of international financial reporting standards, the objectives of financial reports prepared for public use, the importance of IFRS, the quality of financial reports, the factors affecting the quality of financial reports, the importance of IFRS standards, the factors affecting the quality of financial reports, the challenges faced by banks in preparing financial reports, the application of IFRS standards, the impact on the performance of banks, the application of IFRS standards, the fair presentation of the financial position, the application of IFRS standards and the presentation of cash flows to banks, and the reality of adopting IFRS standards in Iraqi banks. The research concluded that the presence of interest of Iraqi banks in the application of financial reporting standards in order to enhance the quality of financial reporting, that the level of impact of International Financial Reporting Standards (IFRS) in enhancing the qualitative characteristics of accounting information among Iraqi banks (the research sample), all of which increased the application of IFRS, reflected positively on the qualitative characteristics of accounting information. The research contributes to financial institutions such as banks and banks as a means of providing external users, investors and at all levels with the financial data and information necessary to make rational and correct decisions after the application of IFRS standards.

Pedagogical control scales of vertical jumping performance in untrained adolescents (13-16 years): research by strata.

A scale is used to establish performance ranges in different sciences, it being necessary to design specialized biological and pedagogical indicators in physical activity, sport and health. To design a scale for the pedagogical control of the vertical jumping ability in untrained adolescents (13-16 years), stratifying the sample by age range, ethnicity, urban and rural area, socioeconomic level, and gender. A representative sample of the Ecuadorian population (n = 3,705) is studied, classifying it into the aforementioned strata, controlling the vertical jump by ISAK I and II level experts, applying the Sargent Test to measure vertical jumps on a multi-force wall, establishing scales with seven percentile levels, and making comparisons related to chronological age, gender, socioeconomic, and genetic indicators. Significant differences in the vertical jumping performance were determined according to the category or age range (13-14 ≠ 15-16 years) and by gender (w = 0.000). Various levels of performance were determined, classifying the maximum level as talented in the female gender (≥40 cm; and ≥42 cm) and male gender (≥47 cm; and ≥57 cm) in the 13‒14 and 15‒16 years categories, respectively. Sampling comparisons by geographical area only determined significant differences in the male gender, with the jumping ability being higher in urban areas (13‒14 years: w = 0.046; 15‒16 years: w = 0.013). The comparison by ethnic groups showed significant differences (k = 0.030), favoring the Afro-Ecuadorian ethnic group in both genders, while there are significant differences by socioeconomic level, especially between the middle and lower classes. The present research solves the lack of a tool for making correct didactic decisions related to the vertical jumping ability, taking into account various important stratified indicators. The complementary conclusions show significant differences according to the category stratum or age range, the gender stratum, and the ethnic stratum in females and males, where the best average rank favored the Afro-Ecuadorian ethnic group in both genders. There are significant differences in the geographical area stratum in the male gender, and differences in the socioeconomic stratum in favor of the upper and middle classes.

Research on the Index System of Old Neighborhood Renovation Based on Green Building Evaluation Standard

With the advancement of the transformation, the contradiction between the residents’ demand for a better living environment and the convenience of living in the settlements comes to the fore. Effective identification, organic integration, timely adoption, and correct decision-making for the transformation of old neighborhoods are pressing issues in the transformation of old neighborhoods. Therefore, this paper takes the green building evaluation standards of various countries as the research basis and support for the construction of the transformation strategy of old neighborhoods. Through the collection and comparative analysis of the indicators of green building evaluation standards, the index system of transformation is formed, and it also provides a certain foundation for the subsequent related research.

Remote expert viewing, laboratory tests or objective metrics: which one(s) to trust?

We present a study on the validity of quality assessment in the context of the development of visual media coding schemes. The work is motivated by the need for reliable means for decision-taking in standardization efforts of MPEG and JVET, i.e., the adoption or rejection of coding tools during the development process of the coding standard. The study includes results considering three means: objective quality metrics, remote expert viewing, which is a method designed in the context of MPEG standardization, and formal laboratory visual evaluation. The focus of this work is on the comparison of pairs of coded video sequences, e.g., a proposed change and an anchor scheme at a given rate point. An aggregation of performance measurements across multiple rate points, such as the Bjøntegaard Delta rate, is out of the scope of this paper. The paper details the test setup for the subjective assessment methods and the objective quality metrics under consideration. The results of the three approaches are reviewed, analyzed, and compared with respect to their suitability for the decision-taking task. The study indicates that, subject to the chosen test content and test protocols, the results of remote expert viewing using a forced-choice scale can be considered more discriminatory than the results of naïve viewers in the laboratory tests. The results further that, in general, the well-established quality metrics, such as PSNR, SSIM, or MS-SSIM, exhibit a high rate of correct decision-making when their results are compared with both types of viewing tests. Among the learning-based metrics, VMAF and AVQT appear to be most robust. For the development process of a coding standard, the selection of the most suitable means must be guided by the context, where a small number of carefully selected objective metrics, in combination with viewing tests for unclear cases, appears recommendable.

Genome sequencing differentiates a paracentric inversion from a balanced insertion enabling more accurate preimplantation genetic testing.

Distinguishing paracentric inversions (PAIs) from chromosomal insertions has traditionally relied on fluorescent insitu hybridization (FISH) techniques, but recent advancements in high-throughput sequencing have enabled the use of genome sequencing for such differentiation. In this study, we present a 38-year-old male carrier of a paracentric inversion on chromosome 2q, inv (2)(q31.2q34), whose partner experienced recurrent miscarriages. FISH analysis confirmed the inversion, and genome sequencing was employed for detailed characterization. Preimplantation genetic testing (PGT) revealed that all assessed embryos were balanced, consistent with the low risk of unbalanced offspring associated with PAIs. While PAI carriers traditionally exhibit low risk of producing unbalanced offspring, exceptions exist due to crossover events within the inversion loop. Although the sample size was limited, the findings align with existing sperm study data, supporting the rare occurrence of unbalanced progeny in PAI carriers. This study highlights the possibility of characterizing PAIs using genome sequencing to enable correct reproductive counseling and PGT decisions. Detailed characterization of a PAI is crucial for understanding potential outcomes and guiding PGT strategies, as accurate knowledge of the inversion size is essential for appropriate method selection in PGT. Given the very low risk of unbalanced offspring in PAI carriers, routine PGT may not be warranted but should be considered in specific cases with a history of unbalanced progeny or recurrent miscarriages. This study contributes to our understanding of PAI segregation and its implications for reproductive outcomes.