Digital System Research Articles

Assessment of organizational factors affecting utilization of Monitoring and Evaluation results in delivering government programs: A case of Ministry of Education and Sports (MoES), Uganda

The field of Monitoring and Evaluation (M&E) is often restricted to the technical aspects of conducting M&E. However, it is increasingly being acknowledged that organizational factors of entities are regularly more influential as far as mainstreaming the adoption and utilization of M&E is concerned. This study sought to assess the organizational factors affecting utilization of M&E results, specifically by analyzing how information availability, information processing skills and organizational culture affect utilization of M&E results in MoES. The study methodology entailed grounded theory and quantitative research methods and covered a sample of 191 respondents. The study’s key findings, among others, include: M&E information is often stored as manual paper records which subjects the information to wastage through poor handling and physical deterioration; and, poorly presented M&E results have a negative effect on their utilization. The study generated a number of recommendations, which inter alia include MoES should: design and implement a mind–set change programme for all staff of the Ministry to embracing and utilize of M&E results; design and implement regular capacity building and retooling programmes for all staff involved in the generation and utilization of M&E results; and, migrate its M&E records and management procedures from paper–based systems to digital systems. The study's conclusions inform various government MDAs about the relevance of using M&E results for planning, budgeting, and policy making. The study findings will enable MoES appreciate the need for installation of appropriate information management systems necessary for improved uptake of M&E results utilization. The study suggests a number of areas for further investigation, such as, examining the influence of political direction and choices on the application and usefulness of M&E results in government organizations, and analyzing the impact of information dissemination on demand and utilization of M&E results in Government agencies.

The effects of students’ self-efficacy, self-regulated learning strategy, perceived and actual learning effectiveness: A digital game-based learning system

The effects of students’ self-efficacy, self-regulated learning strategy, perceived and actual learning effectiveness: A digital game-based learning system

Esthetic outcomes in orthodontics through digital customization with a lingual appliance system.

Contemporary fixed orthodontic appliances are shifting from non-customized pre-adjusted appliances to custom-designed and printed appliances with novel digital setup systems. We are one step closer to precision dentistry and orthodontics using personalized mechanics and custom appliances. However, despite the evidential enhancement and other improvements to fixed appliances, tooth movement is still limited to five degrees of freedom. Opening or closing spaces still requires manually placing elastomeric chains or coil springs. In this article, we aimed to demonstrate how advancements in CAD/CAM technology, reverse engineering, and digital customization are helping orthodontics constantly evolve, enabling treatment with enhanced esthetics and minimal compliance. The clinical system (InBrace®, Irvine, CA) described in this article uses a patient-specific, digitally designed multiloop NITI wire that delivers friction-free, light, and continuous forces and activates automatically whenever the malocclusion deviates from the digital setup. Through digital customization, InBrace allows for automated tooth movement in all six degrees of freedom, including space opening or closure, via programmed non-sliding mechanics. Precision orthodontics and personalized treatment have been significant developments in orthodontics recently. This article focuses on how a technologically advanced lingual appliance system could achieve targeted cosmetic results methodically via automation and personalization.

Fractional Fourier-transform off-axis digital holographic imaging

A fractional Fourier-transform digital holographic imaging method with resolution enhancement features is presented. In an optical configuration, an extended fractional Fourier-transform optical setup is set in the object arm of an off-axis digital holographic recording system to record a fractional Fourier-transform hologram via the optical interference of the fractional Fourier-transform wavefront of an object wave with a reference wave. For reconstruction imaging, the reconstruction approach for fractional Fourier-transform holograms is given. In the experiment, the fractional Fourier-transform digital holograms are recorded under the different recording parameters, and their amplitude images are effectively reconstructed. The imaging results demonstrate that the reconstruction-imaging resolution of fractional-order Fourier-transform holograms is obviously enhanced compared to that of conventional image-plane holograms. The presented fractional Fourier-transform digital holographic imaging with resolution enhancement and optical configuration flexibility provides, to our knowledge, a novel way for off-axis digital holographic imaging.

Human Resource: Futuristic Role of HR Professional Enhancing Technical Skills

As technology continues to revolutionize the workplace, the role of HR professionals is undergoing a profound transformation. In the future, HR professionals will play a pivotal role in leveraging advanced technologies to drive strategic HR initiatives and enhance organizational performance. This abstract explores the key aspects of this evolving role, focusing particularly on the imperative for HR professionals to enhance their technical skills. One critical area where HR professionals will need to excel is in data analysis and analytics. By harnessing the power of data-driven insights, HR professionals can make informed decisions, predict future workforce needs, and optimize workforce management strategies. Additionally, as artificial intelligence (AI) and automation become increasingly prevalent, HR professionals must understand how to effectively implement and manage these technologies to streamline HR processes and enhance efficiency. Furthermore, in the realm of recruitment and talent acquisition, HR professionals must adapt their strategies to the digital age. This involves leveraging digital platforms, social media, and applicant tracking systems to attract, engage, and retain top talent in an increasingly competitive landscape. Moreover, the rise of remote work necessitates proficiency in collaboration tools and virtual communication platforms. HR professionals must ensure that remote teams remain connected, engaged, and productive by leveraging tools such as Slack, Zoom, and Microsoft Teams. In addition to these technical skills, HR professionals must prioritize cybersecurity and data privacy to protect sensitive employee information in an increasingly digitized HR environment. By implementing robust security measures and complying with data protection regulations, HR professionals can safeguard employee data and maintain trust within the organization. Finally, proficiency in HR information systems (HRIS) and other HR technology platforms is essential for streamlining HR processes, managing employee data effectively, and driving operational excellence. Keywords- HR professionals, technical skills, Data analysis, Artificial intelligence, Recruitment, Talent acquisition, Digital platforms, Remote work, Collaboration tools, Cybersecurity, Data privacy, HRIS, HR technology.

Adding External Artificial Intelligence (AI) into Internal Firm-Wide Smart Dynamic Warehousing Solutions

This study advances knowledge in the AI field. It provides deep insight into current industry generative AI inclusion systems. It shows both literature and practical leading industry operations can link, overlap, and complement each other when it comes to AI and understanding its complexities. It shows how to structurally model and link AI inclusions towards delivering a suitable sustainability positioning. It shows approaches to integrate external AI contributions from one firm into another firm’s intelligences developments. It shows how to track, and maybe benchmark, the progress of such AI inclusions from either an external or an integrated internal software developer perspective. It shows how to understand and create a more sustainable, AI-integrated business positioning. This study considers firm artificial intelligence (AI) and the inclusion of additional external software developer engineering as another AI related pathway to future firm or industry advancement. Several substantive industrial warehousing throughput areas are discussed. Amazon’s ‘smart dynamic warehousing’ necessitates both digital and generative ongoing AI system prowess. Amazon and other substantive, digitally focused industry warehousing operations also likely benefit from astute ongoing external software developer firm inclusions. This study causally, and stagewise, models significant global software development firms involved in generative AI systems developments—specifically ones designed to beneficially enhance both warehouse operational productivity and its ongoing sustainability. A structural equation model (SEM) approach offers unique perspectives through which substantive firms already using AI can now model and track/benchmark the relevance of their prospective or existing external software developer firms, and so create rapid internal ‘net-AI’ competencies incorporations and AI capabilities developments through to sustainable operational and performance outcomes solutions.

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry.

Quantitative evaluation of the effects of flow diverter treatment on aneurysm hemodynamics using time-resolved rotational angiography.

There have been immense advancements in the hardware and software of digital subtraction angiography systems over the last several years. These advancements continue to make progress toward the goals of offering better visualization and reducing radiation exposure. A newer advancement in this arena is presenting three-dimension data over time resulting in four-dimensional-digital subtracted angiography visualization. We have evaluated these protocols related to the evaluation of the treatment of intracranial aneurysms with pipeline flow diversion. Four-dimensional-digital subtracted angiography imaging was acquired on an Artis Q Biplane angiographic system (Siemens Healthcare AG, Forchheim, Germany). A six second four-dimensional-digital subtracted angiography protocol was performed pre and post flow diverter placement. Pre and post reconstructed images were sent through a dedicated prototype research workstation (Syngo X-Workplace; Siemens Healthineers AG) for further flow evaluation. The treatment of an aneurysm with flow diversion led to a filling delay of 0.278 ± 0.422 s inside the aneurysms, whereas distal to the aneurysms the filling of the vessel segment occurred earlier post procedural (negative filling delay of -0.15 ± 0.31 s. The flow ratio inside the aneurysm decreased to 63.6 ± 23% of its pre-treatment value and distal to the aneurysm the flow remained substantially the same (flow ratio: 95.6 ± 0.29%). Data showed a relative filling delay of the aneurysm normalized to the distal vessel of 0.43 ± 0.36 s. The relative flow ratio of the aneurysm in comparison to the distal parent vessel was 72.2 ± 31%. Analysis of a four-dimensional-digital subtracted angiography acquisition allows assessment of the effects of flow diversion treatment on aneurysm hemodynamic parameters and shows a significant decrease in flow inside the aneurysm compared to the parent vessel distal to the aneurysm.

Digital payments Impact on Indian Economy through Banking systems & Global Comparisons

India’s financial sector has witnessed a significant digital transformation, particularly in the realm of payments. The shift towards digital payment systems has reshaped transactional practices and contributed to financial inclusion. The adoption of digital payment systems like UPI and e-wallets has led to a surge in online transaction volumes, indicating a gradual move towards a cashless economy. Government initiatives and the COVID-19 pandemic have played crucial roles in promoting digital payments. However, challenges remain in achieving complete financial inclusion with approximately 190 million unbanked adults in India. Fintech companies are addressing this by providing a wide range of financial services and utilizing alternative data sources to evaluate creditworthiness. The key factors driving the adoption of digital payments in India include increased awareness, favorable government policies, quick onboarding and ease of use, smartphone proliferation and internet expansion, regulatory support, and improved technology. These factors, coupled with the enabling role of various entities and technologies, are shaping the future of digital payments in India. The rapid growth of digital payment systems, driven by a combination of technological advancements, government initiatives, and changing consumer preferences, is revolutionizing the financial landscape. As the fintech sector continues to evolve, it promises to bring about further innovations, making financial services more accessible and inclusive. The journey towards a digital economy is well underway, and with continued efforts, India is poised to emerge as a global leader in digital payments. The impact of this digital revolution extends beyond the financial sector, influencing various aspects of the economy and society, and paving the way for a more inclusive and efficient future.

Working of E-Ticketing for Public Buses

The transition from manual, cash-based ticketing procedures to a cutting-edge digital system represents a pivotal advancement in modernizing India's public bus transportation. This research paper delves into the working model of e-ticketing for public buses, aimed at addressing long-standing challenges of wait times, operational hurdles, and inefficiencies inherent in traditional systems. By leveraging state-of-the-art digital technology, this initiative aims to revolutionize the public transportation experience, enhancing security, convenience, and operational efficiency for both administrators and passengers. Thus, to provide an agile and smooth ticketing experience, we have proposed the smart application. [4] Key objectives of this research include the elimination of manual cash transactions, reduction of wait times, and mitigation of operational inefficiencies. Through the implementation of a digital ticketing system, the paper explores how transaction processes are streamlined, providing passengers with a seamless interface for ticket purchases. Not only does this innovation enhance transaction security, but it also fosters a more agile and responsive public bus transportation system. The research assesses the tangible benefits of the digital ticketing solution, highlighting its role in increasing passenger flexibility and reducing congestion through shorter wait times and improved traffic flow. Real-time data analytics are examined as a critical tool for administrators, enabling enhanced resource allocation and informed decision-making processes. This paper presents a comprehensive analysis of the working model of e-ticketing for public buses, offering insights into its functionality, implementation challenges, and the transformative impact it has on India's public transport sector. By promoting a more sophisticated and user-friendly framework, the research underscores the potential of digital ticketing solutions to redefine the landscape of public transportation, paving the way for a more efficient and accessible urban mobility system in India. Key Word: E-ticketing, Public buses, Digital technology, Operational efficiency, Urban mobility

Adaptive Random Mac Strategy for IoT Security Through Network Forensics Investigation

In the rapidly evolving landscape of digital systems and networks, ensuring robust cyber security measures is of paramount importance. This study delves into the evaluation of a proposed security method's efficiency through a comprehensive comparative analysis conducted under diverse security breach simulations. The objective is to discern the method's effectiveness in safeguarding sensitive information and maintaining system integrity.The research methodology involves the selection of representative security breach scenarios, each emulating distinct attack vectors and potential vulnerabilities. A benchmark security protocol, widely acknowledged for its reliability, serves as a reference for the proposed method's assessment. A series of controlled breach simulations are executed, simulating real-world cyber threats, ranging from sophisticated malware intrusions to social engineering attacks. Key performance metrics, such as response time, resource utilization, and data recovery rates, are meticulously recorded and analyzed for both the benchmark and proposed methods. Furthermore, the impact on system functionality and user experience is evaluated to comprehend the trade-off between heightened security and seamless user interaction. The experiments are conducted across multiple system architectures to account for variations in hardware and software configurations. The findings reveal nuanced insights into the proposed method's efficiency under distinct breach scenarios. It showcases commendable resilience against certain attack vectors while potentially exposing limitations in others. The comparative analysis provides a comprehensive overview of the method's overall efficacy and enables the identification of scenarios where enhancements might be necessary. The performance of the suggested approach under various security breach simulations is empirically demonstrated in this paper, adding to the body of current knowledge. The insights gained from this research aid in refining the method's design and implementation, bolstering its potential to address the dynamic and evolving landscape of cyber security threats. As digital systems continue to play an increasingly integral role in our lives, the significance of such evaluations cannot be overstated, ensuring that our vital digital infrastructure remains secure and resilient.

Danish Women Make Decisions about Participation in Breast Cancer Screening prior to Invitation Information: An Online Survey Using Experimental Methods.

At mammography screening invitation, the Danish Health Authority recommends women aged 50 to 69 y make an informed decision about whether to be screened. Previous studies have shown that women have very positive attitudes about screening participation. Therefore, we hypothesized that Danish women may already have decided to participate in breast cancer screening prior to receiving their screening invitation at age 50 y. We invited a random sample of 2,952 Danish women aged 44 to 49 y (prescreening age) to complete an online questionnaire about barriers to informed screening decision making using the official digital mailbox system in Denmark. We asked participants about their screening intentions using 3 different questions to which women were randomized: screening presented 1) as an opportunity, 2) as a choice, and 3) as an opportunity plus a question about women's stage of decision making. All women completed questions about background characteristics, intended participation in the screening program, use and impact of screening information, and preferences for the decision-making process. Data were linked to sociodemographic register data. A total of 790 (26.8%) women participated in the study. Herein, 97% (95% confidence interval: 96%-98%) reported that they wanted to participate in breast cancer screening when invited at age 50 y. When presented with the choice compared with the opportunity framing, more women rejected screening. When asked about their stage of decision making, most (87%) had already made a decision about screening participation and were unlikely to change their mind. In our study, almost all women of prescreening age wanted to participate in breast cancer screening, suggesting that providing information at the time of screening invitation may be too late to support informed decision making. Almost all women of prescreening age (44-49 y) in our study wanted to participate in the Danish national mammography screening program starting at age 50 y.Early decision making represents a barrier for informed decision making as women in this study had intentions to participate in breast cancer screening prior to receiving an official screening invitation, and therefore, providing information at the time of screening invitation may be too late to support informed decision making.Very few women rejected screening participation; however, more women rejected screening when the information was framed as an active choice between having or declining breast cancer screening (continue with usual care) compared with presenting only the option of screening with no description of the alternative.Two-thirds of women reading the screening information in this study had unchanged attitudes toward screening after reading the presented information.

Real-time data visualization of welding robot data and preparation for future of digital twin system

The application of industrial technologies is undergoing significant changes. Finding the level at which to use efficient cyberphysical systems is perhaps one of the most important technical preparatory tasks in implementing digital manufacturing. Welding technology systems are investigated, and a framework for capturing the data sets required for data-driven manufacturing is developed. To make full autonomy in a manufacturing environment meaningful, formerly isolated groups of equipment need to be organized into a production information system. In our research, a test system is created that can implement a digital virtual interface and achieve new levels of efficiency with a future digital twin system. In the discourse of the study, the technological parameters of welding test pieces were investigated, namely the available measurement data sets of current, and voltage data. In the summary section, most of the tasks and research directions are presented, which can be envisaged as a continuation of the present study. Our study will be followed by further research, already testing a complete digital twin system, thus reaching another milestone on the way to autonomous manufacturing.

Theorizing data analysis platforms – digital refractions and reconfigurations of pasts, presents and futures

ABSTRACT Digital platforms are a pervasive force in the transformation of business, organization and social order, but also an evolving phenomenon in need of further conceptualization and detailed analysis. This article offers a theorization and analytical framework for the study of a sub-type of digital platforms that we may think of as data analysis platforms, and which play an increasingly important role in organizations, business, and society more broadly. Starting from a theoretical focus on how data, algorithms and technological systems work as ‘digital prisms’ that refract and reconfigure social phenomena, the article articulates how data integration and data-driven prediction can be seen as forms of knowledge production that allow for new dynamics of seeing, knowing and governing. On this backdrop, the article highlights five analytical dimensions of data analysis platforms (domains, datasets, models, humans and temporality) and offers a conceptualization of three different types and uses of data analysis platforms (data merging platforms, data prognosis platforms and data projection platforms). Taken together, this analytical framework may guide conceptual and empirical investigations and pave the way for more nuanced understandings of the shape, workings and societal ramifications of data analysis platforms. The article contributes to emergent research seeking to articulate the shapes and workings of digital platforms. The conceptualization of digital platforms may help us understand as the digitalization and datafication of knowledge production, work and organization, the reliance on platforms, as well as broader questions about how data, algorithms and digital systems are used in attempts to grasp and shape futures.

Project ECHO®: a global cross-sectional examination of implementation success

BackgroundOrganizations implement innovations to disrupt the status quo and create value. Within sectors such as healthcare, innovations need to navigate large scale system and organizational factors to succeed. This research explores the implementation of a global innovation– Project ECHO®. Project ECHO® is a validated virtual communities of practice model organizational teams implement to build workforce capacity and capability. Project ECHO® has experienced broad global adoption, particularly within the healthcare sector, and is experiencing growth across other sectors. This study sought to examine the state of implementation success for Project ECHO® globally, to understand how these implementations compare across geographic and sectoral contexts, and understand what enablers/barriers exist for organizational teams implementing the innovation.MethodsAn empirical study was conducted to collect data on 54 Project ECHO® implementation success indicators across an international sample. An online survey questionnaire was developed and distributed to all Project ECHO® hub organizations globally to collect data. Data was analyzed using descriptive statistics.ResultsThe 54 implementation success indicators measured in this survey revealed that the adoption of Project ECHO® across 13 organizations varied on a case-by-case basis, with a strong rate of adoption within the healthcare sector. Implementation teams from these organizations successfully implemented Project ECHO® within 12–18 months after completing Immersion partner launch training and operated 51 ECHO® Networks at the time of data collection. Implementation teams which liaised more regularly with ECHO® Superhub mentors often went on to launch a higher number of ECHO® Networks that were sustained over the longer term. This suggests that these implementation teams better aligned and consolidated their Project ECHO® pilots as new innovations within the local context and strategic organizational priorities. Access to research and evaluation capability, and a more automated digital client relationship management system were key limitations to showcasing implementation success outcomes experienced by the majority of implementation teams.ConclusionsThese findings make a valuable contribution to address a knowledge gap regarding how a global sample of organizations adopting Project ECHO® measured and reported their implementation successes. Key successes included pre-launch experimentation and expansion, Superhub mentorship, stakeholder engagement, and alignment to strategic priorities.

Wavy-attention network for real-time cyber-attack detection in a small modular pressurized water reactor digital control system

Global interest in advanced reactors has been reignited by recent investments in small modular reactors and micro-reactor design. The use of digital devices is essential for meeting the size and modularity requirements of small modular reactor controls. By fully digitizing the small modular reactor control systems, critical information can be obtained to optimize control, reduce costs, and extend the reactor’s lifetime. However, the potential for cyber-attacks on digital devices leaves digital control systems vulnerable. To address this risk, this study presents a novel wavy-attention network for sensor attack detection in nuclear plants. The wavy-attention network comprises stacks of batch-normalized, dilated, one-dimensional convolution neural networks, and sequential self-attention modules, superior to conventional single-layer networks on sequence classification tasks. To evaluate the proposed wavy-attention network architecture, the International Atomic Energy Agency’s Asherah Nuclear Simulator and a false data injection toolbox found in the literature, both implemented in MATLAB/SIMULINK, are utilized. This approach leverages changes in process measurements to identify and classify cyber-attacks on priority signals using the proposed wavy-attention network. Three false data injection attacks are simulated on the simulator’s pressure, temperature, and level sensors to obtain representative process measurements. The wavy-attention network is trained and validated with normal and compromised process variables obtained from the simulator. The performance of the wavy-attention network to discriminate between the reactor states using the test set shows 99% accuracy, as opposed to other baseline models such as vanilla convolution neural networks, long short-term memory networks, and bi-directional long short-term memory networks with 90%, 77%, and 91% accuracy, respectively. An ablation study is also conducted to test the contribution of each component of the proposed architecture. The theoretical framework of the proposed wavy-attention network and its implementation for nuclear reactor digital sensor attack detection are discussed in this paper.

Efficient Cyber Security Framework for IoT Using Machine Learning Algorithms

Through the network's infrastructure, the IoT can impart perception, recognition, and remote control to inanimate objects. Due to IoT's characteristics, it's possible to integrate the real world into a digital system, which improves precision, productivity, and bottom line. While traditional internet infrastructure comprises of highly capable computers and servers, IoT gadgets have limited processing power and storage space. The authentication and key agreement system SecureAuthKey is very lightweight. The suggested technique is meant to solve the security and privacy problems that plague modern constraint-based CPS programmes. A lightweight approach for authenticating cyber-physical objects is one of the expected outcomes. Adaptation and autonomy in cyber-physical systems need not be compromised by a lack of trust or security in users' data or the devices themselves, according to a new type of security algorithm. To provide flexibility and scalability, a new middleware module has been developed on the Raspberry platform to facilitate communication between CPS-based devices and services. Secure Internet of Things (IoT) evaluation methodology that may be used in a variety of contexts and is user-focused. With the suggested system, the two CPS units will be able to authenticate one another. When a network grows larger, the possibility of an attack rises. Therefore, the IoT network is much more susceptible to attacks than conventional networks. As the number of connected devices grows, so do the number of potential threats to their security. To protect the IoT ecosystem from current threats, cutting-edge technology is essential. The proposed approach must be very efficient and have low computational overheads. It creates random session keys to protect wireless transmissions. The system is protected from a variety of cyber threats. The current constraint-based CPS system requires a new lightweight security solution.

Impact of pump-phase noise in PPLN-based optical parametric amplifier and wavelength converter for digital coherent transmission

Wideband signal amplification and optical signal processing with a high gain using an optical parametric amplifier based on a periodically poled LiNbO3 (PPLN) waveguide is attractive for constructing wideband optical fiber networks. We experimentally investigate the transfer characteristics of the phase noise of a pump laser in χ(2)-based optical parametric amplification and wavelength conversion on the basis of second-harmonic-generation and differential-frequency-generation processes. We also evaluate the effect of the transferred phase noise on signal quality in dispersion-unmanaged digital coherent fiber transmission systems. We show that the phase noise is transferred only to the wavelength-converted idler and does not affect the amplified signal even by using a pump laser with a MHz-order linewidth. We also show that the phase noise transferred to the idler light can have a similar impact on signal quality as equalization-enhanced phase noise (EEPN) in digital coherent transmission. The signal penalty including EEPN was evaluated with several pump lasers and at symbol rates of 32, 64, and 96 Gbaud. We also propose a method of using correlated pump lights between a wavelength converter pair to cancel out the transfer of phase noise.

Abstract PO2-28-11: How to improve margins in breast cancer surgery: a

Abstract Objective: Intraoperative specimen mammography (ISM) is a diffuse technique that allows surgeons to check specimens immediately after lumpectomy, instead of intraoperative frozen sections, definitely abandoned. in Italy and Europe, because it is regarded as too expensive and time-consuming examination. Although the specimen is slightly compressed, the radiological image can be distorted by tissue overlap, and this may affect the evaluation of tumor borders, resulting in extension of the lumpectomy. As ISM may be less precise due to inadequate compression, a vacuum effect was applied to the specimen to increase the precision of margin detection. Study design: This study was conducted at St. Anna Hospital Breast Unit, Turin, Italy. Women who underwent lumpectomy for cancer were eligible for inclusion. BCS resection was performed with a free margin, and the surgical specimen was imaged immediately by SSM and evaluated by an expert radiologist and surgeon.Inclusion criteria were: breast cancer detected by a screening test, and treatment with surgical lumpectomy. Both standard ISM (sISM) and vacuum ISM (vISM) were performed. A dedicated breast surgeon at the study institution performed both surgery and radiological scans, and their interpretation. A dedicated radiologist reviewed all of the images. ISM was performed by a digital specimen mammography system (Faxitron, Bioptics Inc., Tucson, AZ, USA) in the operating room. Specimen registration and ISM analysis took 3 min. sISM (two orthogonal projections) was performed. Specimens were sealed in plastic bags in the vacuum apparatus (TissueSAFE Milestone Medical, Sorisole, Italy); this process took a few seconds. 152 specimens obtained after lumpectomy from 1 April 2021 to 31 April 2022 were scanned. sISM (two orthogonal projections) was performed. Next, the specimen was placed in a vacuum bag, and vISM was performed. Additional tissue was removed if the surgeon considered that excision was inadequate. Finally, the specimen was sent for definitive histopathological analysis, which is the gold standard for the assessment of surgical margins. Intraoperative histological margin assessment was not performed. The sISM and vISM images and final histopathology reports were compared. A first experience on a limited number of patients to demonstrate feasibility of the technique, is reported in table 1 and 2. Results: For sISM, specificity was 43,85% [95 % confidence interval (CI) 35.96-51.73], sensitivity was 40.91% (95 % CI 33.09-48.73), positive predictive value (PPV) 10.98% (95 % CI 6.01-15.95) and negative predictive value (NPV) 81.43% (95 % CI 75.25-87.61). For vISM, specificity 92,31% (95 % CI 88,07-96.54), sensitivity 72.73% (95 % CI 65.65-79.81), PPV 61.54% (95 % CI 53.80-69.27) and NPV 95.24% (95 % CI 91.85-98.62). Conclusion: ISM is a valid, safe and quicker alternative to intraoperative histopathological study, but has been reported to be limited due to less compression than standard SSM. Consequently, ISM may result in a high percentage of false-positive results, meaning unnecessary wider resections that lead to increased operative times and worse aesthetic results. A vacuum effect was performed on the specimen to increase the precision of margin detection. vISM images seem to be easier to interpret than sISM images (Figs. 1–3) as they are characterized by a vacuum-created radiolucent rim that better defines the tumor margins. These data suggest that the vacuum technique is feasible, cost-saving and yields results that are similar to those from frozen sections but without the limitations, such as prolonged operating time, high variability in sensitivity due to pathologists abilities, risk of compromising the histology, and unreliability for small lumps and ductal carcinoma in situ. Keywords: Breast cancer; Intraoperative mammography; Lumpectomy; Specimen mammography; Vacuum intraoperative mammography. Table 1. Clinical Data IC, invasive cancer; DCIS ductal carcinoma in situ; ADH, atypical ductal hyperplasia; ILC, invasive lobular cancer; B3, lesions of uncertain malignant potential; IMPC, invasive micropapillary carcinoma; NST, no special type; sISM, standard intraoperative specimen mammography; vISM, vacuum intraoperative specimen mammography. ª Margin: 0, involved; 1, free Table 2. Figure 1 - 2 - 3 Standard intraoperative specimen mammography (left) and vacuum intraoperative specimen mammography (right). Citation Format: Maria Grazia Baù, Vincenzo Marra, Alessandra Surace, Donatella Tota, Maria Piera Mano, Aurelia Mondino, Alessandro Bottero, Elisabetta Robba. How to improve margins in breast cancer surgery: a [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-28-11.

ANALYSIS OF SHARE PRICES OF NYKAA AND PAYTM AFTER THEIR IPO

The Initial Public Offering (IPO) market is a turning point for many businesses as they seek to grow their business, raise capital, and attract public investment. Going public is a huge deal for every party concerned, from the firm itself to the investors who stand to gain from its growth in the future. Investors, experts, and the general public have been captivated by the initial public offerings (IPOs) of two prominent startups in recent years—Nykaa and Paytm. Nykaa, an e-commerce website based in India, made its stock market debut in November 2021. Things related to personal hygiene and cosmetics are the platform's forte. Nykaa, founded in 2012 by Falguni Nayar, a former investment banker, is currently a major player in the booming cosmetics industry in India. An increase in interest in the company's IPO was driven by the growing demand for cosmetics and the allure of online shopping in India's market. Also in November 2021, India's leading digital payment and financial services platform, Paytm, went public for the first time. When Vijay Shekhar Sharma launched his mobile payment system Paytm in 2010, it revolutionised the way Indians handled their money and made online transactions. The IPO marked a watershed moment in the development of digital payment systems and financial technology, both of which have the potential to radically alter the Indian economy. Investor mood, underlying prospects, and market expectations are all gauged by the share prices of Nykaa and Paytm, which have been the topic of extensive investigation and study since their initial public offerings (IPOs). To understand the factors driving these stocks' performance, it's important to look at more than just financial results; you need to look at industry trends, market sentiment, and company advancements as well. This study aims to examine the performance of Nykaa and Paytm since their IPOs, the factors that have influenced their share prices, and the potential future directions of these companies. Our goal is to help investors make sense of the volatile stock market by studying key indicators, market dynamics, and industry trends. The intricacies of investing in these renowned organisations can be better grasped with this information. After that, we'll take a look at the stock prices of Nykaa and Paytm since their IPOs, analyse the factors that have impacted them, and then draw some conclusions about what this means for investors who are trying to make money off of these companies' fast development. In this article, we will provide a comprehensive overview of Nykaa and Paytm's post-IPO process and use quantitative research, qualitative insights, and industry experience to shed light on the benefits and drawbacks of investing in these companies. The initial public offerings (IPOs) of Nykaa and Paytm have wowed investors and industry participants, proving that technology and innovation can propel value creation. As these businesses make their way as publicly traded corporations, share prices will continue to reflect the interplay between basic considerations, market sentiment, and broader economic trends. Investors can benefit from the ever-changing stock market and make informed decisions by closely monitoring their performance following an initial public offering (IPO).