Usual Strategy Research Articles

Combining a Risk Factor Score Designed From Electronic Health Records With a Digital Cytology Image Scoring System to Improve Bladder Cancer Detection: Proof-of-Concept Study.

To reduce the mortality related to bladder cancer, efforts need to be concentrated on early detection of the disease for more effective therapeutic intervention. Strong risk factors (eg, smoking status, age, professional exposure) have been identified, and some diagnostic tools (eg, by way of cystoscopy) have been proposed. However, to date, no fully satisfactory (noninvasive, inexpensive, high-performance) solution for widespread deployment has been proposed. Some new models based on cytology image classification were recently developed and bring good perspectives, but there are still avenues to explore to improve their performance. Our team aimed to evaluate the benefit of combining the reuse of massive clinical data to build a risk factor model and a digital cytology image-based model (VisioCyt) for bladder cancer detection. The first step relied on designing a predictive model based on clinical data (ie, risk factors identified in the literature) extracted from the clinical data warehouse of the Rennes Hospital and machine learning algorithms (logistic regression, random forest, and support vector machine). It provides a score corresponding to the risk of developing bladder cancer based on the patient's clinical profile. Second, we investigated 3 strategies (logistic regression, decision tree, and a custom strategy based on score interpretation) to combine the model's score with the score from an image-based model to produce a robust bladder cancer scoring system. We collected 2 data sets. The first set, including clinical data for 5422 patients extracted from the clinical data warehouse, was used to design the risk factor-based model. The second set was used to measure the models' performances and was composed of data for 620 patients from a clinical trial for which cytology images and clinicobiological features were collected. With this second data set, the combination of both models obtained areas under the curve of 0.82 on the training set and 0.83 on the test set, demonstrating the value of combining risk factor-based and image-based models. This combination offers a higher associated risk of cancer than VisioCyt alone for all classes, especially for low-grade bladder cancer. These results demonstrate the value of combining clinical and biological information, especially to improve detection of low-grade bladder cancer. Some improvements will need to be made to the automatic extraction of clinical features to make the risk factor-based model more robust. However, as of now, the results support the assumption that this type of approach will be of benefit to patients.

Beyond business as usual? How organisations navigate tensions between circular economy and intellectual property right strategies

ABSTRACT Intellectual property rights (IPRs) play a key role in the business strategies of innovators, hence also for companies innovating towards a circular economy (CE). IPRs can allow circular companies to benefit economically from their innovations but can also create tensions with their CE ambitions. However, a clear picture of such tensions and the way circular companies deal with them is missing. Our exploratory research aims to fill this gap by conducting in-depth qualitative interviews with frontrunner circular companies. Our results show that many firms experienced no tension between their CE and IPR strategies. If they did experience tensions, they found strategies to suppress, accept or resolve them. Instances where firms responded to tensions by clearly deviating from usual IPR strategies were rare. These findings suggest that most circular innovators embrace a ‘business case’ approach to circularity, which might limit the impact and transformative promises of a CE.

Perception of Pedodontists Regarding Dental Care in Children with Special Needs in India: A Cross-sectional Study.

Pedodontists have a vital role in maintaining the overall health of children with special health care needs (CSHCN) by providing basic, preventive, comprehensive, and restorative dental care to such children. In doing so, Pedodontists face many challenges due to several environmental and nonenvironmental barriers. The aim is to gain insight into the perceptions of Pedodontists in India on providing oral health care to CSHCN and the challenges they encounter in doing so. The self-administered questionnaire, with 20 questions, was made available through online resources to 250 randomly selected Pedodontists from all over India. The questionnaire evaluated the Pedodontists' practices, attitudes, level of knowledge/awareness, and the barriers they encounter during the management of CSHCN. Regarding attitude, even though 81.7% of Pedodontists were confident in managing CSHCN, 88.7% were in favor of developing super specialization in special care dentistry and skill upgradation at the postgraduation level. With regard to knowledge/awareness, about 98.6% of Pedodontists were aware of the dental home, and 45.1% were aware of Indian laws for disabled people. Even though inadequately motivated parents (39.4%) and lack of access to dentists providing care (22.5%) were stated as the greatest barriers to receiving dental treatment by CSHCN, lack of training was the major problem perceived by the Pedodontists in treating CSHCN. The dental curriculum model, both at the undergraduate and postgraduate levels, needs to be revived to equip future dentists to deal with CSHCN. Special care dentistry should be adopted as a super-specialty in pediatric dentistry for treating CSHCN. This study enlightened us about the difficulties faced by pediatric dentists in providing dental health care to CSHCN and explored customized strategies to address these challenges, thereby improving the quality of dental treatment for such children. Kaul S, Kumar A, Mahajan P, et al. Perception of Pedodontists Regarding Dental Care in Children with Special Needs in India: A Cross-sectional Study. Int J Clin Pediatr Dent 2024;17(12):1340-1345.

CATIL: Customized Adversarial Training based on Instance Loss

Adversarial training is one of the most effective adversarial defense methods currently recognized. It enhances the robustness of deep neural network (DNN) classifiers by generating adversarial samples. However, current adversarial training methods cannot effectively trade off the robust accuracy and natural accuracy when training DNN classifiers, and are prone to overfit. To solve these problems, we propose Customized Adversarial Training based on Instance Loss (CATIL), aiming to improve robust accuracy and natural accuracy while alleviating overfitting. We first comprehensively consider the influencing factors of adversarial training and propose the comprehensive customization strategy (CCS), which crafts unique attack strategies for each sample, fine-tunes the classifier's decision boundary, and boosts the robustness of the DNN classifier without compromising its natural accuracy. Second, the loss adjustment strategy (LAS) is designed to update the attack strategy according to the loss value. This increases the fitting difficulty of the DNN classifier and alleviates the overfitting problem. Finally, numerous experiments show that CATIL can effectively enhance robust accuracy and alleviate the overfitting problem without significantly compromising natural accuracy. When evaluating CIFAR-10 on Wide ResNet, CATIL achieves the best performance in both natural and robust accuracy compared to all benchmarks.

Kurčiųjų ar neprigirdinčiųjų tėvų ir girdinčiųjų vaikų šeima: dviejų atvejų tyrimas

The present study analyses the language policy of two families of deaf or hard-of-hearing parents and hearing children. The desire to explore this topic was motivated by the fact that the linguistic situation of families consisting of deaf parents and hearing children is either not explored or the material is inaccessible to those who do not know Lithuanian sign language. A qualitative method of analysis was chosen to collect the material: in-depth semi-structured interviews with both parents individually and observation of joint activities of the whole family. The aspects of the interview analysis were: pre-planning of language policy strategies before the birth of the child and changes as the child grows up, behavior during arguing or in more complicated linguistic situations, i.e. looking at what are the usual compensatory strategies of communication. The analysis of the data shows that families have not developed specific linguistic strategies before having children, but some decisions has been made after the birth of the children, based on the experience of other families in the same situation. However, unlike previous generations, deaf parents have not tried to talk to their hearing children because it is already known that this is not effective. The analysis of the data also shows that both families have not made any special efforts to teach their children either Lithuanian Language or Lithuanian Sign Language. The biggest problem in families is the manipulation of children by their parents’ hearing impairment, and it is also evident that the families in the study deal with this problem differently. When communication difficulties arise, the most common strategies used are cooperative: lip reading, voice pronunciation tactics, use of the alphabet, seeking help from hearing relatives, and the use of paraphrasing strategies. However, the non-cooperative strategies also were mentioned: ignoring, avoiding. This study could be of interest and benefit to researchers working in the field of applied linguistics, families of deaf and hearing people, social workers working with deaf and hearing families and teachers.

Product Recommendations

Product recommendations, or PRs, are becoming more and more popular every day. Product recommendations are an e-commerce customization strategy that creates products for a customer on a webpage, application, or email on a continual basis based on information such user attributes, browsing habits, or situational context, creating a personalized shopping experience. The recommendation system predicts or suggests a product based on the customer's preferences. Several e-commerce websites have adopted product suggestion systems in the modern day. A website that enables anyone to purchase and sell digital goods, services, and tangible items without needing to visit a physical store. An e-commerce website allows a business to handle customer service, shipping and logistics, payments, and orders. A recommendation may be of any kind. As an example, Spotify may be used to propose music, and movies YouTube for videos, Netflix, the Play Store (for several categories), and so on. To suggest products based on user preferences, a variety of filtering techniques and algorithms were employed. Machine Learning Techniques (MLT) that were currently in use for product recommendation were covered in this study. With these methods, an algorithm is utilized to forecast or suggest comparable things based on the user's input.

CLOTHING SALES STRATEGY AT ANEKATEX SHOP WITH E-CRM CONCEPT

Toko Anekatex is a business engaged in fashion for women, men, children, as well as school uniforms, pajamas, and other robes located on Jalan Dr. Sutomo No. 41 Kisaran city. In maintaining more advanced competitiveness, the company must continue to develop technology, another thing that needs to be considered in making the company more advanced is the relationship with customers which is also an important thing to always maintain. In an effort to manage good relationships with potential customers and customers, companies use Customer Relationship Management (CRM). CRM is a service to customers that is personal, with the aim of providing consistent experience, so that it can provide customer satisfaction, and also get good relationships in the long term. By implementing a good E-CRM, companies will more easily interact with potential customers and customers and provide information according to their needs Customers can also obtain the information they need more quickly and easily. By implementing Customer Relationship Management (CRM) carried out at Anekatex Stores as an effort to improve customer strategies are well proven by the series of processes above and with this application to increase buybacks from total sales every month.

Spatial transcriptome profiling identifies DTX3L and BST2 as key biomarkers in esophageal squamous cell carcinoma tumorigenesis

BackgroundUnderstanding the stepwise progression of esophageal squamous cell carcinoma (ESCC) is crucial for developing customized strategies for early detection and optimal clinical management. Herein, we aimed to unravel the transcriptional and immunologic alterations occurring during malignant transformation and identify clinically significant biomarkers of ESCC.MethodsDigital spatial profiling (DSP) was performed on 11 patients with early-stage ESCC (pT1) to explore the transcriptional alterations in epithelial, immune cell, and non-immune cell stromal compartments across regions of distinct histology, including normal tissues, low- and high-grade dysplasia, and cancerous tissues. Furthermore, single-cell spatial transcriptomics was performed using the CosMx Spatial Molecular Imaging (SMI) system on 4 additional patients with pT1 ESCC. Immunohistochemical (IHC) analysis was performed on consecutive histological sections of 20 pT1 ESCCs. Additionally, public bulk and single-cell RNA-sequencing (scRNA-seq) datasets were analyzed, and in vitro and in vivo functional studies were conducted.ResultsSpatial transcriptional reprogramming and dynamic cell signaling pathways that determined ESCC progression were delineated. Increased infiltration of macrophages from normal tissues through dysplasia to cancerous tissues occurred. Macrophage subtypes were characterized using the scRNA-seq dataset. Cell–cell communication analysis of scRNA-seq and SMI data indicated that the migration inhibitory factor (MIF)-CD74 axis may exhibit pro-tumor interactions between macrophages and epithelial cells. DSP, SMI, and IHC data demonstrated that DTX3L expression in epithelial cells and BST2 expression in stromal cells increased gradually with ESCC progression. Functional studies demonstrated that DTX3L or BST2 knockdown inhibited ESCC proliferation and migration and decreased M2 polarization of tumor-associated macrophages.ConclusionsSpatial profiling comprehensively characterized the molecular and immunological hallmarks from normal tissue to ESCC, guiding the way to a deeper understanding of the tumorigenesis and progression of this disease and contributing to the prevention of ESCC. Within this exploration, we uncovered biomarkers that exhibit a robust correlation with ESCC progression, offering potential new avenues for insightful therapeutic approaches.

PROSPECTS FOR THE DEVELOPMENT OF THE PET FOOD MARKET IN UKRAINE

The article examines current challenges and prospects for the development of the pet food market in Ukraine during the war. The main problems of the market include: disruption of logistics, supply and difficulties with the delivery of raw materials and finished products; limited availability of foreign raw materials, on which most feed producers depend; reduced purchasing power of the population, which forces some consumers to switch to more affordable feed or even to alternative types of pet food. Rising prices due to economic instability and declining incomes put additional pressure on the market, limiting growth opportunities. The general dynamics of sales in the Ukrainian cat and dog food market was analyzed, which showed a steady increase in sales of pet food in Ukraine from 2018 to 2021. However, starting in 2022, there was a sharp slowdown in growth rates, and in 2023, a slight decline was even recorded. This indicates that the full-scale war in Ukraine has had a significant impact on the pet food market. The reasons for the growth of the feed market in Ukraine in 2024 and the main trends observed are the growing responsibility of pet owners and the formation of a culture of attitude towards animals, which is not only to provide them with quality food; the domestic feed market is not much different from the markets of Eastern Europe and already has about 100 different brands; people want to buy the product in convenient packaging, which makes adjustments to the usual strategies of manufacturers; in Ukraine, sales have somewhat shifted to online shopping. In 2023, we see a positive trend in online sales, which is one third higher than last year. In 2023, online sales reached 4434 tons and UAH 331 million excluding VAT. In general, online channels are growing faster than physical channels year after year, and this trend has continued. Ukrainian companies should focus on is expanding the range of pet food in the middle price category, as 75% of respondents choose a product based primarily on its price. Given the growing demand for pet food produced by Ukrainian producers globally, and the fact that every tenth ton is exported abroad, we believe that Ukrainian companies should increase the supply of all types of pet food to international markets and consider entering new markets, particularly in Northern Europe.

Comparison between different sets of interpolation functions for Timoshenko frame elements

The objective of this paper is to discuss, in the context of a second-order geometric non-linear analysis, the differences in results considering different sets of interpolation functions for frame elements. The usual way to obtain interpolation functions for Timoshenko frame elements is using cubic Hermitian polynomials since they are the solution for the fourth-order differential equation which represents the bending behavior of the infinitesimal element. When dealing with more complex problems (geometrical and/or physical nonlinearities), the usual strategy is to subdivide the elements, which circumvents the limitation of the interpolation functions. Since discretization can sometimes be unwanted, especially for undergraduate students who still do not grasp this concept, a solution which overcomes this is interesting from a didactic point of view. This work proposes the use of different sets of shape functions to interpolate displacements, rotations and bending moments along the element’s length, to account for the nonlinearities that arise from the change in geometry during loading. Shape functions obtained directly from the solution of the differential equation of an axially loaded deformed infinitesimal element and traditional Hermitian polynomials are used. Comparisons were made against analytical and numerical solutions using the two-cycle approach. Initial results indicate the ability of the formulation to capture the nonlinear behavior without the need to over discretize the domain.

Strategic Insights into Bank Performance: CAMELS Analysis of Indian Banks

The banking sector is a cornerstone of the global economy, driving economic growth, financial sta-bility, and efficient resource allocation. Assessing the financial health and operational effectiveness of banks is crucial for maintaining the stability of the broader financial system. The CAMEL model, a well-established analytical framework, provides a comprehensive approach to evaluating key aspects of bank-ing performance, including Capital Adequacy, Asset Quality, Management Efficiency, Earnings Quality, and Liquidity. This model highlights areas for improvement and ensures a thorough assessment of a bank’s financial soundness. Extensive research has confirmed the model's applicability across various global contexts, including India, Nepal, Pakistan, Saudi Arabia, and Sri Lanka, consistently identifying asset quality, capital adequacy, and earnings as essential drivers of profitability. The model also reveals that private banks generally outperform public banks in most parameters. Moreover, the CAMEL model has proven to be a valuable tool in promoting financial inclusion, particularly through the analysis of Small Finance Banks, and its adaptability to emerging markets further underscores its relevance. Despite its broad applicability, gaps exist in the literature, particularly regarding the model’s adaptation to diverse regulatory environments and market dynamics. Addressing these gaps will enable more customized strategies for financial analysis and risk management, enhancing the resilience of the global banking system. This study aims to contribute to this discourse by exploring the nuanced use of the CAMEL model in assessing the financial performance of banks in varied contexts. The findings aim to offer ac-tionable insights for improving financial performance, managing risks, and fostering sustainable growth in the banking industry.

Strategies to scale up the Technical, Allocative and Economic Efficiency of Major Millet Growing Farmers in India – A Primal System Approach

Millet farming, a sustainable and economically viable option for farmers, providing resilience against climate variability and market fluctuations. Despite the increasing significance of millets in agriculture, there is a notable research gap concerning the efficiency of their cultivation and its impact on input demand and costs. This study leverages data from CCPC for the AY 2021-22, focusing on major millets—Bajra, Jowar, and Ragi cultivated across various Indian states. The research aims to understand the technical, allocative, and economic inefficiencies in millet farming to enhance productivity and resource utilization. It is hypothesized that inefficiencies in millet cultivation significantly impact input demand and cultivation costs, and addressing these inefficiencies can lead to improved agricultural practices and yields. Employing primal Cobb-Douglas production function showed that human labor, seed quantity, and fertilizers positively impact millet cultivation. Technical inefficiency is a major issue with Bajra farmers in Gujarat, Haryana, Maharashtra, Rajasthan and Uttar Pradesh. For Jowar, farmers in Andhra Pradesh, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan and Tamil Nadu are facing significant inefficiencies. In contrast, Karnataka and Odisha efficiently produce Ragi. Allocative inefficiency is noted in the over-utilization of animal and machine labor and fertilizers in Bajra cultivation, while these inputs are under-utilized in Jowar and Ragi cultivation. Both technical and allocative inefficiencies lead to increased input demand and higher cultivation costs across all three millets. The findings underscore the importance of state-specific strategies to address inefficiencies. These insights can guide policymakers in developing customized strategies to optimize millet cultivation, enhance yields and reduce costs.

Equilibrium Strategies in an Mn/M/1 Queue with Server Breakdowns and Delayed Repairs

Ophthalmic units use sophisticated equipment to enable accurate diagnosis of refractive errors. This equipment is subject to two types of breakdowns. One is simple breakdown which can be repaired in-house, and the other is complex breakdown which requires repair by the original equipment manufacturer (OEM) and results in a delay time between the server breakdown and the start of the repair. In this paper, we model this scenario as an Mn/M/1 queuing system with two types of breakdowns and delayed repairs due to complex breakdowns, where the delay time and repair times for simple and complex breakdowns are generally distributed. We obtain the steady-state probabilities and provide the recursive formulas for the Laplace–Stieltjes transforms (LSTs) of conditional residual delay time and repair times given the system state. For the fully observable case, we derive the equilibrium joining strategies of customers who decide to join or balk based on their observation of the system state. Moreover, two numerical experiments are conducted to explore the equilibrium joining probabilities.

Understanding public opinion and discussion dynamics of digital humans on social media: an analysis of sentiment, themes and user characteristics

PurposeThe emergence of artificial intelligence-generated content (AIGC) technology has markedly enhanced the capabilities of digital human content generation and natural language processing, thus further advancing the development of digital humans. To enable enterprises and governments to effectively address the challenges and opportunities arising from the rapid development of digital humans, it is imperative to understand the public opinion and discussion dynamics of digital humans.Design/methodology/approachThis study initially analyzed the trends and distribution patterns of public attention to digital humans. By utilizing word cloud technology, we explored the primary focal points of public interest and conducted a topic analysis using latent Dirichlet allocation (LDA) techniques. Subsequently, content analysis was conducted on the popular application domains of digital humans. Finally, this study examined the influence of user characteristics on emotional scores toward digital humans and the presence of differences in focus across user groups.FindingsThe results indicate a sustained increase in public attention toward digital humans, accompanied by notable geographic disparities in the distribution of discussions. Discussions on Weibo are primarily focused on four domains, whereas areas within the digital human application domain that provoke widespread discussion include live streaming, service, cultural entertainment and digital avatars. Significant impacts of user characteristics on sentiment scores were observed, revealing divergent focal points of interest among different user groups toward digital humans.Originality/valueThrough the deep analysis of Weibo data, this study offers new insights into the digital human industry, enabling governments and businesses to understand industry trends and develop targeted digital human customization strategies based on customer characteristics.

An approach based on data mining and genetic algorithm to optimizing time series clustering for efficient segmentation of customer behavior

In today's highly competitive market, organizations face significant challenges in accurately understanding and segmenting customer behavior due to the inherently dynamic and evolving nature of customer interactions over time. Traditional customer segmentation methods often neglect these temporal variations, leading to ineffective business strategies and missed opportunities. This research addresses this critical gap by introducing an innovative time series-based approach for customer behavior segmentation. By modeling each customer's behavior as a time series capturing key metrics such as purchase frequency, transaction amounts, and customer lifecycle costs the proposed method dynamically adapts to behavioral changes over time. To enhance segmentation precision, a genetic algorithm is employed to optimize feature weights, ensuring that the most relevant factors are emphasized. These optimized features are then clustered using spectral clustering to identify distinct and meaningful customer segments. The effectiveness of the proposed method is validated using 30 months of transactional data from a payment services company. The results demonstrate that the proposed approach, particularly when combined with spectral clustering and optimally weighted features, significantly surpassing the performance of traditional static segmentation techniques. This research not only provides a more accurate framework for uncovering hidden patterns in customer behavior but also delivers actionable insights for targeted marketing and personalized customer strategies.

문자중계와 몬테카를로 시뮬레이션 기반 배구 경기 승패 예측에 관한 연구

With advancements in science and technology, a vast amount of data from various media is being generated in the field of sports. Applying statistical methods to extract meaningful information from this data has become essential. This study aimed to predict volleyball match outcomes by performing Monte Carlo simulations based on live text commentary data from the 2023-2024 women's professional volleyball season. By generating the necessary variables for the simulation from the text commentary data and conducting 10,000 iterations of Monte Carlo simulations, the study confirmed that the simulations accurately mirrored actual match outcomes. In particular, when one team demonstrated overwhelming performance, the accuracy of set score predictions was notably high, and the simulation results demonstrated the potential for developing customized strategies. However, limitations were observed in predicting outcomes in specific scenarios, such as when a team with a high total score loses 3-2. To address these limitations, future work should focus on more precisely modeling the complex interactions between various situational and variable factors by converting qualitative factors, which have been challenging to quantify, into objective indicators for integration into the model.

Food security and dietary patterns in the Tajik Pamirs

For mountain regions in the so-called ‘developing world’, an increase in the number of people considered vulnerable to food insecurity has been noted since the turn of the millennium. Challenging environmental settings, as well as difficult societal conditions have been identified as sources of aggravation to mountain food systems. This paper applies a case study approach, conducted in a remote settlement in the Western Pamirs of Tajikistan, to underpin these general insights with detailed accounts of the complexity of the subject under study, and examines the question of how food security plays out in a specific local setting. The goal is to illustrate how socio-ecological conditions influence the food situation in a specific location, how different parameters generate unequal access to food and effect the nutrition patterns of local households, and what dynamics these patterns exhibit over time. Empirical material was analyzed using Cannon’s food systems approach. The findings exemplify how ensuring food security is made more difficult by the concurrence of challenging conditions, that there is a relationship between the socio-economic status and the dietary patterns of individual households, and how consumption patterns are subject to fluctuations over time. Based upon this, I argue that customized strategies are vital in order to tackle food security challenges in specific settings effectively, and that differentiated, empirically grounded analyses are essential to developing such approaches.

Penerapan Metode Antrian Dan Game-Theory Dalam Analisis Pengaruh Kenaikan Harga Pertalite-Pertamax Bagi Pengendara Roda Dua (SPBU XY)

Queuing problems in everyday life can hinder the smooth running of activities in terms of time. With queues, the time to get service will be longer. If this problem is not resolved it will have an impact on users of the related services. XY gas station is one of the gas stations that is quite busy with two-wheeled users. The research method used in this case was direct observation at SPBU XY and interviews. The data in this research was obtained at SPBU carried out for 3 hours, namely from 09.00 WIB to 12.00 WIB. With the method used, namely maximin and minimax in game theory, to find out in terms of the advantages of Pertalite and Pertamax, the saddle point in the pay off matrix is ​​known, namely it lies in price and quality because the saddle point value obtained is the same, namely 27. So it can be said that this calculation is optimal. Because the value obtained is optimal and has a saddle point, the type of game theory used is pure strategy. Knowing that the customer strategy results are that Pertalite wins the price strategy, while Pertamax wins the quality strategy. Keywords: Game theory, Queuing, SPBU

Successful Coronary Interventions with the Ingenious Vector\(\circledR\) Balloon in Chronic Total Occlusion (CTO): A Preliminary Study

Aims: To assess the safety and plausibility of successful coronary interventions in Chronic Total Occlusion (CTO) with the innovative Vector\(\circledR\) balloon through balloon-assisted crossing technique. Study Design: Observational, prospective study. Place and Duration of Study: Department of Cardiology, King Edward Memorial Hospital and Seth G. S. Medical College, Mumbai. The study was carried out between the months of March and June, 2024. Methodology: A total of 20 patients were included in the study. All patients with chronic coronary syndrome were being planned for Percutaneous Coronary Intervention (PCI) for CTO. During PCI, the standard protocol of intervening CTO lesions was followed. When the operator was not able to cross the lesion with standard CTO guidewires, Vector\(\circledR\) balloon-assisted crossing was planned. This technique was used in a total of seven (35%) patents. Success was defined as the possibility of advancing the guidewire further to the target lesion and being able to deploy a drug eluting stent. Safety was assessed as reporting complications like kinking or rupture of the balloon shaft, loss of balloon inside the guide or the coronary artery and the balloon burst rate after inflation exceeding the Rated Burst Pressure (RBP) according to the manufacturer’s reference table. Results: The mean age of the patients was 58.1 ± 3.6 years. The balloon-assisted crossing was successful in all seven patients. The most commonly used diameter of the balloon was 1.25 mm (42.85%). Conclusion: The novel Vector\(\circledR\) balloon catheter showed excellent result when deployed to treat the CTO after the usual strategy of guidewire escalation had failed. The proximal shaft with polytetrafluoroethylene (PTFE) coating brings the flexibility to navigate complex and tortuous vascular pathways with ease due to its laser welded core-wire. A study with a larger sample size and a comparator arm would rather clarify if such a balloon-assisted crossing technique in CTO would decrease the need of costly devices like double lumen microcatheters.

How Supplier Customization Influences Its Performance? A Moderated Mediation Model Based on the Contract Theory

ABSTRACT Purpose This study aims to investigate the underlying psychological mechanism and the boundary conditions of the effects supplier customization (SC) on its performance in supply chain management (SCM). Methodology/approach Based upon the contract theory, the study explores how SC influences its performance by revealing mediating role of customer entitlement (CE), and examines the boundary conditions of contractual governance (CG). The dyadic questionnaire survey data of 111 supplier and customer firms in China were used to validate a moderated mediation model. Findings It is found that SC enhances its performance through the increased CE. Furthermore, the above consequential link is moderated by both contractual completeness (CCP) rather than contractual enforcement (CEF). Specifically, CCP negatively moderates the indirect effect of SC on SP through CE. However, CEF negatively moderates the direct effect of SC on CE. Research implications This research are really limitations, including its focus on single industry; single-country system; its cross-sectional design; and the oversight of the possible impact of relational governance (RG) on the link between buyers and sellers. Practical implications Executives should always attach importance to the development of psychological contract (PC), and managers should identify the underlying psychological mechanisms of a customization strategy in B2B and use contractual design and execution with caution. Originality/value/contribution The study extends the literature of the psychological mechanism and more granular characterization of CG, and provides insights for managers to recognize reasonable governance tactics in the context of SCM.