Vital Attributes Research Articles

Prediction of Multi-Pharmacokinetics Property in Multi-Species: Bayesian Neural Network Stacking Model with Uncertainty.

Pharmacokinetic (PK) properties of a drug are vital attributes influencing its therapeutic effectiveness, playing an important role in the drug development process. Focusing on the difficult task of predicting PK parameters, we compiled an extensive data set comprising parameters across multiple species. Building upon this groundwork, we introduced the PKStack ensemble model to predict PK parameters across diverse species. PKStack integrates a variety of base models and includes uncertainty in its predictions. We also manually collected PK data from animals as an external test set. We predicted a total of 45 tasks for nine PK parameters in five species, and in general, the prediction accuracy was better for intravenous injections, including parameters such as human Vd (R2 = 0.72, RMSE = 0.31), human CL (R2 = 0.52, RMSE = 0.32), and others. In addition to predictive accuracy, we also considered the interpretability of the results and the definition of the model's application domain. Based on the findings, our model has great potential for practical applications in drug discovery.

Effect of Creativity on Emotional Intelligence, Self-Esteem and Resilience in Visual Arts and Engineering Students

This research looks into the complex interactions between creativity, emotional intelligence, resilience, and self-esteem, focusing on two distinct student groups: arts and engineering. Understanding the impact of creativity on these vital attributes becomes increasingly important as social needs grow, embracing both technological knowledge and emotional intelligence, resilience, and self-esteem. The study investigates the link between creativity and emotional intelligence, resilience, and self-esteem, offering light on how academic fields influence these vital characteristics. Purposive sampling was used in the research to sample 106 people from different colleges in North India. Self-report questionnaires such as the Emotional Quotient Test, Rosenberg Self-Esteem Scale, Nicholson McBride Resilience Questionnaire, and KDOCS 20 for creativity were used in the data collection process. With Jamovi, statistical studies such as regression, correlation, and t-tests were carried out. According to the findings, self-esteem, emotional intelligence, and resilience significantly correlate with creativity. Notably, students studying engineering and the arts showed different approaches to the scientific aspect of creativity. The scientific dimension was a significant predictor by regression analysis, indicating that it had a distinct impact on both student groups. Prioritizing ethical issues included obtaining participants' informed consent, managing data securely, and respecting participant autonomy.

Application and performance evaluation of recycled building materials in civil engineering

The concept of renewable materials has received extensive advocacy and promotion in the ongoing development of the construction industry. Furthermore, emerging renewable building materials, such as bio-based composite materials, are continually evolving and gradually being incorporated into civil engineering applications. This paper focuses on the application and performance assessment of recycled building materials in civil engineering. As a crucial component of environmental protection and sustainable development, recycled building materials possess vast potential for application. In this article, the characteristics of common materials such as recycled concrete, recycled steel, and recycled glass are introduced, and their mechanical performance, durability, and other vital attributes are evaluated. Finally, the feasibility and challenges of recycled building materials are analyzed, along with discussions on sustainable development strategies and policy support. The comprehensive research results demonstrate the significant role of recycled building materials in promoting sustainable development in civil engineering, warranting increased support and promotion at the policy and societal levels.

Mapping content-driven engagement and attitudinal spillover effect of influencer marketing

PurposeThis study analyzes the indirect (i.e. through brand content engagement-BCE) and direct effects of informative, credible, novel, and aesthetically pleasing attributes of influencer-generated branded content on endorsed brand-related attitude and a subsequent attitudinal spillover effect on the followers' firm-generated endorsed brand-related ad click behavior.Design/methodology/approachData for this study were collected from 300 users who follow the top 40 Pakistani social media macro-influencers using an online survey. The conceptual model and hypotheses were tested through process macro and structural equation modeling.FindingsThis study finds informative, credible, novel, and aesthetically pleasing factors vital attributes of influencer-generated branded content, which indirectly (i.e. via BCE) and directly affects followers’ endorsed brand-related attitude. This study also finds that these factors have a positive attitudinal spillover effect on followers’ firm-generated endorsed brand-related ad-click behavior on social media.Practical implicationsThis study presents guidelines to firms and their partner influencers about designing and implementing follower-valued content-driven influencer marketing campaigns.Originality/valueThis study contributes to extant influencer marketing literature by integrating multiple attributes of influencer-generated branded content, which carry different values for followers, and using the Self-perception theory, the Multi-attribute attitude model, and the Spillover theory to explain their indirect and direct effects on endorsed brand-related attitude and a subsequent attitudinal spillover effect on firm-generated endorsed brand-related ads.

Implementing multi-attribute utility theory in service recovery: An operational management perspective on online retailing

How corporate decision-makers allocate resources to address the major issues of service recovery is critical. This article, from the perspective of operations management, integrates Multi-Attribute Utility theory into the field of service recovery. Through the use of online review data from smart home products, the PCRA-Multi-Attribute Utility model is proposed. Based on the model, this paper presents a prioritization strategy for service recovery and reveals that the utility of intelligent products is primarily influenced by service attitude. Furthermore, we discovered that manager's response strategies should pay more attention to recovery related to vital attributes. Strategy optimization can be achieved by adjusting the response length of these key attributes.

An approach to identify assistive technology attributes for people with locomotor disability by using a refined Kano model

This study aims to identify and evaluate the attributes of assistive products for people with locomotor disabilities using the refined Kano model. Thirty experts from various disciplines (product engineers and designers engineers, rehabilitation professionals, and users of assistive technology with locomotor disabilities) participated in the study. They were asked to complete a survey based on the Kano model questionnaire, which included functional and dysfunctional questions for each attribute. The findings reveal that performance, accessibility, functionality, and repairability are one-dimensional characteristics, while quality, modularity, intuitiveness, and aesthetics are attractive attributes. Affordability and durability are identified as must-be attributes. Subsequently, an importance scale was created on a 5-point Likert scale to further analyze the attributes based on the refined Kano model. The results indicate that functionality, quality, aesthetics, affordability, repairability, and durability are the vital attributes. Following this, a case study was conducted based on these attributes, focusing on the two most commonly used products in India: the ALIMCO basic manual wheelchair and the KARMA basic manual wheelchair. By incorporating identified attributes, manufacturers can establish marketing strategies that promote sustainable product development and enhance assistive product satisfaction among individuals with locomotor disabilities.

ON THE ANALYTICAL STUDY OF THE SERVICE QUALITY OF INDIAN RAILWAYS UNDER SOFT-COMPUTING PARADIGM

Indian Railway Catering and Tourism Corporation (IRCTC) is among the busiest railways reservation systems since the Indian Railways (IR) is the vital and economical mode of transportation in India. Hence, rating of the trains seems to be critical aspect for selecting an appropriate train for travelling. In this study, we have considered 7 vital attributes of 500 popular trains and rate their performance based on 7 important related attributes. For this purpose, we have employed 2 different approaches to analyse of the train attributes, which eventually contribute to the overall performance of the trains. Here, we have developed a rule based rough set decision support system to analyse the criticality of the train attributes while rating the train performance. Furthermore, we have also used 3 Machine Learning (ML) model estimators: Extra Trees Classifier (ETC), Support Vector Machine Classifier (SVMC) and Multinomial Naive Bayes Classifier (MNBC) and perform their comparative analysis with respect to 7 performance metrics while predicting the overall train rating based.

Linear semantic transformation for semi-supervised medical image segmentation

Medical image segmentation is a focus research and foundation in developing intelligent medical systems. Recently, deep learning for medical image segmentation has become a standard process and succeeded significantly, promoting the development of reconstruction, and surgical planning of disease diagnosis. However, semantic learning is often inefficient owing to the lack of supervision of feature maps, resulting in that high-quality segmentation models always rely on numerous and accurate data annotations. Learning robust semantic representation in latent spaces remains a challenge. In this paper, we propose a novel semi-supervised learning framework to learn vital attributes in medical images, which constructs generalized representation from diverse semantics to realize medical image segmentation. We first build a self-supervised learning part that achieves context recovery by reconstructing space and intensity of medical images, which conduct semantic representation for feature maps. Subsequently, we combine semantic-rich feature maps and utilize simple linear semantic transformation to convert them into image segmentation. The proposed framework was tested using five medical segmentation datasets. Quantitative assessments indicate the highest scores of our method on IXI (73.78%), ScaF (47.50%), COVID-19-Seg (50.72%), PC-Seg (65.06%), and Brain-MR (72.63%) datasets. Finally, we compared our method with the latest semi-supervised learning methods and obtained 77.15% and 75.22% DSC values, respectively, ranking first on two representative datasets. The experimental results not only proved that the proposed linear semantic transformation was effectively applied to medical image segmentation, but also presented its simplicity and ease-of-use to pursue robust segmentation in semi-supervised learning. Our code is now open at: https://github.com/QingYunA/Linear-Semantic-Transformation-for-Semi-Supervised-Medical-Image-Segmentation.

Nursing privilege: A concept analysis.

The study aimed to provide a comprehensive concept analysis of nursing privileges by elucidating its meaning and implications within the healthcare context. A concept analysis paper. A comprehensive literature review was conducted from nursing and healthcare databases, professional nursing organizations, and regulatory bodies. Documents reviewed include research studies, policy documents and professional guidelines. The study employed Walker and Avant's eight-step method of concept analysis. This involved identifying the uses of the concept, its underlying attributes and referents, and constructing model, borderline, related and contrary cases. The antecedents, consequences and empirical referents of nursing privileges were also determined. The analysis uncovered vital attributes defining nursing privileges, encompassing professional authority, autonomy, access to resources, information, influence, decision-making power, respect and recognition. Additionally, antecedents and consequences of nursing privilege were identified, spanning development and resource access, as well as professional satisfaction and enhanced patient care. No patient or public contribution.

Mitigating bias in artificial intelligence: Fair data generation via causal models for transparent and explainable decision-making

In the evolving field of Artificial Intelligence, concerns have arisen about the opacity of certain models and their potential biases. This study aims to improve fairness and explainability in AI decision making. Existing bias mitigation strategies are classified as pre-training, training, and post-training approaches. This paper proposes a novel technique to create a mitigated bias dataset. This is achieved using a mitigated causal model that adjusts cause-and-effect relationships and probabilities within a Bayesian network. Contributions of this work include (1) the introduction of a novel mitigation training algorithm for causal model; (2) a pioneering pretraining methodology for producing a fair dataset for Artificial Intelligence model training; (3) the diligent maintenance of sensitive features in the dataset, ensuring that these vital attributes are not overlooked during analysis and model training; (4) the enhancement of explainability and transparency around biases; and finally (5) the development of an interactive demonstration that vividly displays experimental results and provides the code for facilitating replication of the work.

Co-delivery of Brinzolamide and Timolol from Micelles-laden Contact Lenses: In vitro and In Vivo Evaluation.

Traditional eye drops exhibit a modest bioavailability ranging from 1 to 5%, necessitating recurrent application. Thus, a contact lens-based drug delivery system presents substantial benefits. Nonetheless, pharmaceutical agents exhibiting poor solubility may compromise the quintessential characteristics of contact lenses and are, consequently, deemed unsuitable for incorporation. To address this issue, the present study has engineered a novel composite drug delivery system that amalgamates micellar technology with contact lenses, designed specifically for the efficacious conveyance of timolol and brinzolamide. Utilizing mPEG-PCL as the micellar material, this study crafted mPEG-PCL micelles loaded with brinzolamide and timolol through the film hydration technique. The micelle-loaded contact lens was fabricated employing the casting method; a uniform mixture of HEMA and EGDMA with the mPEG-PCL micelles enshrouding brinzolamide and timolol was synthesized. Following the addition of a photoinitiator, 50 μL of the concoction was deposited into a contact lens mold. Subsequently, the assembly was subjected to polymerization under 365 nm ultraviolet light for 35 min, resulting in the formation of the micelle-loaded contact lenses. In the present article, we delineate the construction of a micelle-loaded contact lens designed for the administration of brinzolamide and timolol in the treatment of glaucoma. The study characterizes crucial properties of the micelle-loaded contact lenses, such as transmittance and ionic permeability. It was observed that these vital attributes meet the standard requirements for contact lenses. In vitro release studies revealed that timolol and brinzolamide could be gradually liberated over periods of up to 72 and 84 h, respectively. In vivo pharmacodynamic evaluation showed a significant reduction in intraocular pressure and a relative bioavailability of 10.84 times that of commercially available eye drops. In vivo pharmacokinetic evaluation, MRT was significantly increased, and the bioavailability of timolol and brinzolamide was 2.71 and 1.41 times that of eye drops, respectively. Safety assessments, including in vivo irritation, histopathological sections, and protein adsorption studies, were conducted as per established protocols, confirming that the experiments were in compliance with safety standards. The manuscript delineates the development of a safe and efficacious micelle-loaded contact lens drug delivery system, which presents a novel therapeutic alternative for the management of glaucoma.

Data-driven zero-carbon transition analysis in the industrial and manufacturing sectors: a world-regional perspective

ABSTRACT This study contributes to concerning data-driven zero-carbon transition in the industrial and manufacturing sectors. Zero-carbon transition ensures that regions meet energy system provisions, are resilient to climate change, and adopt transition assessments toward the goal of low or zero carbon. Prior studies have failed to (1) generate these attributes from databases and confirm the validity of prominent attributes, (2) build a hierarchical model with an interrelationship from the world-regional perspective, and (3) determine the vital attributes representing knowledge gaps for zero-carbon transition. The proposed hybrid method is employed to obtain attributes from a database and is based on the literature. The results indicate that energy system provisions, low-carbon transition assessment and resilience in terms of climate change adaptation are significant in directing zero-carbon transition studies and challenges. This study shows that Asia and Oceania, Latin America and the Caribbean need to improve their zero-carbon transition performance.

Outsourcing or in-house manufacturing in Hi-tech industry: supply chain process with Delphi-AHP approach

PurposeTechnological advancements have benefited businesses all over the world in how they set up production lines, create new products/services and trade goods. Multinational corporations can communicate instantly with their distant operations by utilizing information technology tools and communication networks. Businesses have taken a significant shift and new factors have emerged which affect company's competitiveness. In case of resorting to an outsourcing option, a comprehensive approach for valuing the essential criteria is often missing. While specifically focusing on the decisions that have a huge impact on company's performance, it is crucial to pay close attention to the ways of selecting suppliers. The purpose of research is to choose the optimal manufacturing alternative from a set of possibilities.Design/methodology/approachThe current research utilizes the Delphi technique for collection of vital criteria such as “quality”, “cost”, “delivery”, “warranties and claims”, “supplier profile”, “relationship and communication” and their respective sub-criteria. The purpose of research is to choose the optimal manufacturing alternative from a set of possibilities. In this regard, Analytical Hierarchy Process (AHP) technique is employed.FindingsThe current research enlightens that outsourcing can yield promising beneficial results. The results highlighted that in Hi-tech public sector organizations, international alternative is found best in almost all criteria especially in vital criteria such as “Quality”, “Cost”, “Delivery”, “Supplier Profile,” etc. Similarly, in case the outsourcing is done to a Domestic alternative, still the Domestic alternative is found effective in comparison to in-house manufacturing setups. The research showed unexpected results. Because previously it was assumed that in-house manufacturing would be more beneficial. However, the current findings support the “NASA” strategy which moved toward outsourcing to private sector.Research limitations/implicationsLimitations of the proposed methodology also produce opportunities for further exploration of the topic. One key limitation of the research described in this study is that the parameters and their sub-parameters interdependency were not taken under consideration. This means that quality and cost are not dependent upon each other. However, in reality quality and cost are interlinked. This means if quality is increased, cost is also increased. Similarly, for products having zero percent of re-claim, the product would have to be manufactured with high quality.Practical implicationsThe study is advantageous for both suppliers and purchasers, in any type of businesses where decision-making problem are under consideration. This model aids suppliers in revealing, how they can expand their profile, by focusing on the current research's selection criteria. In this way alternatives profile can now be perfected. Moreover, buyers can now rank suppliers on their quality management, financial status and other essential factors in order to conduct purchasing decisions. For the decision maker, the results illustrate which critical factors to evaluate when screening suppliers by applying current model techniques.Social implicationsIt is obvious that nearly almost every industry is forced to look for alternatives for all of its operations if outsourcing is an option. The study's findings have major benefits for all industries with an important role in manufacturing and supply chain operations. These objectives will serve the industries well and they will be able to prioritize their alternative selection criteria based on their operations. The findings of this study can assist any organization in their selection of vendors by providing a more detailed explanation of the impact that various criteria have on the decision-making process.Originality/valueTo the best of authors' knowledge, no previous study has used two approaches (AHP and Delphi study) to propose a model for making manufacturing decisions with domestic, in house and international alternatives in Hi-tech public sector organizations. The model not only benefits the manufacturers for choosing suitable suppliers but also aids suppliers to build their profile in an improved fashion by focusing on the vital attributes. This research benefits managers to improve their ability to make effective purchasing decisions, and also opens new avenues for researchers to further explore such findings in other areas as well.

Exploring the undermined: Pharmacy students' perceptions of their role models’ core competencies

Background: As an integrated part of pharmacy education, role modelling is pivotal in fostering desirable professional attributes in students. This study aimed to explore top pharmacist role model competencies as perceived by pharmacy students of different years of the curriculum. Methods: A newly developed 14-item questionnaire (The Competencies of Role Models in Pharmacy (CRMP) questionnaire) was distributed among 207 pharmacy students and filled out anonymously, and the results obtained were analysed on SPSS 26 software. The Kolmogorov-Smirnov test was used to check data normality, and Kruskal-Wallis one-way analysis was utilised to assess the variations in CRMP scores based on the students’ academic year. Results: Teaching skills and professionalism were the most vital attributes selected by pharmacy students, followed by communication skills and laboratory skills. Interestingly, students perceived business and entrepreneurship skills as well as the career status of role models as the least essential competencies. Moreover, notable differences were observed in the overall opinions of students in different academic years, which may be indicative of the dynamic changes in student perspectives as they move forward in their pharmacy programme. Conclusion: The competencies of pharmacist role models were assessed and ranked according to their importance as perceived by pharmacy students across different academic years. This information helps gain insight into students’ prioritisation of role model competencies and sheds light on the path toward developing future role model training/assessment programmes to improve the quality of pharmacy education.

Person Re-Identification Method Based on the Construction of Graph Convolutional Network with Attribute Feature

To fully pay attention to identity-sensitive feature information and utilize the correlations of inter-attributes and attributes-body parts, this paper proposes a person re-identification (re-ID) method based on the construction of graph convolutional network (GCN) with crucial attribute feature and body parts. First, it establishes the multiscale context-aware network (MSCAN) using dilated convolution with different expansion ratios, which can learn multiscale context information and obtain diversified global features. Subsequently, the human parsing model is utilized to extract the body part features. According to the attribute importance degree, the paper constructs low-dimensional GCN integrating the vital attributes and body parts of person descriptions to obtain discriminative local features. Finally, based on attribute prediction, it reduces the range of the images to be matched with discriminating possible objects from query images, thereby simplifying retrieval process. The experimental results demonstrate that the novel designed method can effectively improve person re-ID performance and achieve competitive evaluation results on typical public testing datasets.

Rapid evolution of a coastal marsh ecosystem engineer in response to global change

There is increasing evidence that global change can alter ecosystems by eliciting rapid evolution of foundational plants capable of shaping vital attributes and processes. Here we describe results of a field-scale exposure experiment and multilocus assays illustrating that elevated CO2 (eCO2) and nitrogen (N) enrichment can result in rapid shifts in genetic and genotypic variation in Phragmites australis, an ecologically dominant plant that acts as an ecosystem engineer in coastal marshes worldwide. Compared to control treatments, genotypic diversity declined over three years of exposure, especially to N enrichment. The magnitude of loss also increased over time under conditions of N enrichment. Comparisons of genotype frequencies revealed that proportional abundances shifted with exposure to eCO2 and N in a manner consistent with expected responses to selection. Comparisons also revealed evidence of tradeoffs that constrained exposure responses, where any particular genotype responded favorably to one factor rather than to different factors or to combinations of factors. These findings challenge the prevailing view that plant-mediated ecosystem outcomes of global change are governed primarily by differences in species responses to shifting environmental pressures and highlight the value of accounting for organismal evolution in predictive models to improve forecasts of ecosystem responses to global change.

A genome-wide association study of important reproduction traits in large white pigs

Augmenting the reproductive efficiency of sows remains the predominant challenge in the swine industry. This work was aimed at scrutinizing vital genetic markers for reproductive traits in this animal. This entailed probing of the records of vital attributes of Large White pigs (n = 695) inclusive of the total number of born (TNB), number of born alive (NBA), number of weaned pigs (NWP), number of healthy births (NHS), total litter weight of piglets born alive (BALWT), weaning litter weight (WNWT), and corrected litter weight at 21 days (W21). A genome-wide association study (GWAS) for the four litter traits and three traits of litter weight in the Denmark Large White population then ensued. We discovered seven significantly related SNPs and eleven potential candidate genes (e.g., TUSC3, THRB for TNB; STT3B for NBA). The subsequent functional enrichment analysis of these genes showed that the significant gene were associated with steroid hormone receptor activity. Our findings indicated that the genes TUSC3, THRB and STT3B probably contribute to litter traits in this population. This work reveals genetic mechanisms of reproduction traits and also supports ensuing genetic improvement employing marker-assisted selection in Large White pigs.

Harvest quotas, free markets and the sustainable trade in pythons

Assessing the sustainability of the harvest of animals can be done by obtaining data from processing facilities and establishing that vital attributes of the harvested animals (e.g., size, age structure, sex ratio) do not change over time. This model works if the traders operate in a free market without any regulations on what can be harvested, processed or exported, and when harvest methods and harvest areas do not change between assessment periods. Several studies assessed the harvest effects on blood pythons (Python brongersmai) in North Sumatra, Indonesia seemingly under a free market scenario, with some concluding that trade was sustainable and the others hinting at an overharvest. Indonesia has established harvest and export quotas and, internationally, trade in blood pythons is regulated through CITES, and the blood python trade clearly does not operate in a free market. Data suggest that the three (or four) slaughterhouses included in these studies processed ~27,000 blood pythons a year against a quota of 18,000. There is a risk that data from traders alone purporting to show that harvest is sustainable will lead to an increase of quotas or an abandonment of quotas altogether. There is no conclusive data to support that the harvest of blood pythons in North Sumatra is sustainable but there is sufficient evidence to suggest that a substantial part of this trade is illegal. Likewise, at a global level there are clear indications of misdeclared, underreported and illegal trade involving 10,000 s of blood pythons. While important biological information can be obtained from harvested animals, to assess whether harvest is sustainable there is no substitute for monitoring wild populations. After decades of international trade in blood pythons from Indonesia, during which at least half a million blood pythons were exported, it is all the more urgent that systematic monitoring of wild populations commences.

Key preferences of tourists during COVID-19 pandemic in luxury hotels: Evidence from qualitative data

There is a decline in revenue and occupancy rates in the hotels during the pandemic. For the sustainable and long-term recovery of the hotel industry, the guests need to be analyzed for their stay preferences. This study attempts to find the preferred attributes of the travelers visiting the Indian luxury hotels during the COVID-19 pandemic. The research investigated the post-visit experiences from the online reviews published by tourists on TripAdvisor.com. Thematic salience valence analysis and lexical salience valence analysis was used to identify the vital attributes of the hotel industry. The study revealed staff, location, food, hygiene, and rooms as the preferred hotel attributes, in which the coastal locations were highly considered for location based marketing of luxury hotels, and non-compliance of COVID-19 standards and complaints for upgradations in the rooms were the non-recommenders for the luxury hotels. The dashboard-based salience valence zone analysis was used to provide suggestions to the hotel authorities by revealing the significant and critical hotel attributes simultaneously for prompt handling of the issues during the COVID-19 pandemic.

Combining Ability and Gene Action Controlling Chocolate Spot Resistance and Yield Traits in Faba Bean (Vicia faba L.)

Chocolate spot disease devastatingly impacts faba bean growth and productivity. Thenceforth, genetic study of chocolate spot resistance and yield traits is crucial to conceive appropriate strategies for breeding and sustaining faba bean production particularly under abrupt climate change and fast-growing global population. The current study was performed to identify promising resistant and high-yielding progenies, to study the mode of inheritance for chocolate spot resistance and yield traits using half diallel mating design, and to investigate the association between seed yield and its attributes traits under conditions of chocolate spot disease.Two resistant (Nubaria-1and Sakha-1) and two susceptible (Tribe-White and Camolina) parents previously characterized were used to generate six F1 hybrids which were selfed to produce F2 progenies. The parents and their F1 and F2 were evaluated at hot-spot location for chocolate spot disease. Significant variation was detected for chocolate spot resistance and yield traits among the evaluated parents and their cross combinations in both generations. The general (GCA) and specific (SCA) combining ability effects were highly significant for chocolate spot severity and yield traits in both generations. From the results, it is noteworthy that the cross combinations of P1(Nubaria-1)×P2(Sakha-1), P1×P4(Camolina) and P2×P3(Tribe-white) displayed constant performance through both generations (F1 and F2) with high-yielding and resistance to chocolate spot. Consequently, these crosses could be promising combinations for increasing seed yield, and resistance to chocolate spot in breeding programs of faba bean. The additive gene effect was predominant for chocolate spot resistance, plant height, days to flowering, number of branches per plant and 100-seed weight in both generations. Accordingly, selection could be effective to improve these traits in early generations. By contrast, the non-additive gene effects were preponderant for seed yield per plant, number of seeds per plant and number of pods per plant. This suggests the importance of transgressive segregation for improving these traits through breeding programs. While selection for improving these traits could be less effective in the segregated generations which should be postponed to advanced generations. A strong positive association was identified between seed yield per plant and each of number of branches per plant, 100-seed weight, plant height, days to flowering, number of pods per plant and number of seeds per plant. This signifies their significance as vital attributes for indirect selection, especially in the early generations due to their ease of evaluation in comparison with seed yield. On the contrary, linear regression analysis revealed a steeply inverse relationship between seed yield and chocolate spot disease in both generations.