Proprietary Information Research Articles

The library information resources of the Scientific Library of Yanka Kupala State University of Grodno

The author examines the experience of Yanka Kupala State University Library (Grodno, Belarus) in providing digital document resources to its users. The proprietary information resources are reviewed; the selection principles for library Internet-resources are specified; user awareness services are described. The library organizes information educational workshops intended for the faculty, though it experiences some problems in disseminating information on library services and resources, in particular, students’ low interest in information literacy and lacking teaching hours for library courses. The author suggests several possible solutions and prospective vectors for the academic library, i. e. development of proprietary resources, corporate collaboration, improvement, development and introduction of new methods of user services. The author emphasizes the importance of improving librarians’ professional competences in providing reliable and enhanced information.

A framework enabling LLMs into regulatory environment for transparency and trustworthiness and its application to drug labeling document

Regulatory agencies consistently deal with extensive document reviews, ranging from product submissions to both internal and external communications. Large Language Models (LLMs) like ChatGPT can be invaluable tools for these tasks, however present several challenges, particularly the proprietary information, combining customized function with specific review needs, and transparency and explainability of the model's output. Hence, a localized and customized solution is imperative.To tackle these challenges, we formulated a framework named askFDALabel on FDA drug labeling documents that is a crucial resource in the FDA drug review process. AskFDALabel operates within a secure IT environment and comprises two key modules: a semantic search and a Q&A/text-generation module. The Module S built on word embeddings to enable comprehensive semantic queries within labeling documents. The Module T utilizes a tuned LLM to generate responses based on references from Module S. As the result, our framework enabled small LLMs to perform comparably to ChatGPT with as a computationally inexpensive solution for regulatory application.To conclude, through AskFDALabel, we have showcased a pathway that harnesses LLMs to support agency operations within a secure environment, offering tailored functions for the needs of regulatory research.

A Critical Discussion of Alert Evaluations in the Context of Continuous Glucose Monitoring System Performance.

Many continuous glucose monitoring (CGM) systems provide functionality which alerts users of potentially unwanted glycemic conditions. These alerts can include glucose threshold alerts to call the user's attention to hypoglycemia or hyperglycemia, predictive alerts warning about impeding hypoglycemia or hyperglycemia, and rate-of-change alerts. A recent review identified 129 articles about CGM performance studies, of which approximately 25% contained alert evaluations. In some studies, real alerts were assessed; however, most of these studies retrospectively determined the timing of CGM alerts because not all CGM systems record alerts which necessitates manual documentation. In contrast to assessment of real alerts, retrospective determination allows assessment of a variety of alert settings for all three types of glycemic condition alerts. Based on the literature and the Clinical and Laboratory Standards Institute's POCT05 guideline, two common approaches to threshold alert evaluation were identified, one value-based and one episode-based approach. In this review, a critical discussion of the two approaches, including a post hoc analysis of clinical study data, indicates that the episode-based approach should be preferred over the value-based approach. For predictive alerts, fewer results were found in the literature, and retrospective determination of CGM alert timing is complicated by the prediction algorithms being proprietary information. Rate-of-change alert evaluations were not reported in the identified literature, and POCT05 does not contain recommendations for assessment. A possible approach is discussed including post hoc analysis of clinical study data. To conclude, CGM systems should record alerts, and the episode-based approach to alert evaluation should be preferred.

High Voltage Electrolyte Design Mediated by Advanced Solvation Chemistry Toward High Energy Density and Fast Charging Lithium‐Ion Batteries

AbstractElectrolyte is critical for transporting lithium‐ion (Li+) in lithium‐ion batteries (LIBs). However, there is no universally applicable principle for designing an optimal electrolyte. In most cases, the design process relies on empirical experiences and is often treated as highly confidential proprietary information. Herein, a solvation structure‐related model for the quantitative design of electrolytes is introduced, focusing on the principles of coordination chemistry. As a paradigmatic example, a high‐voltage electrolyte (i.e., 4.5 V vs anode) aimed at achieving a high energy density and fast charging LIB, which is specifically composed of an emerging, well‐constructed hybrid hard carbon‐silicon/carbon‐based anode, and lithium cobalt oxide cathode, is developed. Not only the functions of each electrolyte component at the molecular scale within the Li+ solvation structure are analyzed but also an interfacial model is introduced to elucidate their relationship with the battery performance. This study represents a pioneering effort in developing a methodology to guide electrolyte design, in which the mutual effects of the Li+ de‐solvation process and solid electrolyte interface (SEI) on the electrode surface are explored concurrently to understand the root cause of superior performance. This innovative approach establishes a new paradigm in electrolyte design, providing valuable insights at the molecular level.

The potential for blockchain to improve small-scale agri-food business’ supply chain resilience: a systematic review

PurposeWe conducted a systematic review to explore the potential for the application of blockchain technologies for supply chain resilience in a small-scale agri-food business context.Design/methodology/approachAs part of the research methodology, scientific databases such as Web of Science, Google Scholar and Scopus were used to find relevant articles for this review.FindingsThe systematic review of articles (n = 57) found that the use of blockchain technology in the small-scale agri-food business sector can reduce the risk of food fraud by assuring the provenance of food products.Research limitations/implicationsOnly a few papers were directly from a small-scale agribusiness context. Key challenges that limit the implementation of blockchain and other distributed ledger technologies include concerns over the disclosure of proprietary information and trade secrets, incomplete or inaccurate information, economic and technical difficulties, low levels of trust in the technology, risk of human error and poor governance of process-related issues.Originality/valueThe application of blockchain technology ensures that the risks and costs associated with non-compliance, product recalls and product loss are reduced. Improved communication and information sharing can increase resilience and better support provenance claims and traceability. Better customer relationships can be built, increasing supply chain efficiency and resilience.

Analysis of a logistics flow int the light of VSM 4.0: a case study of in a Distribution Center (DC) in Brazil

This article presents an application of Value Stream Mapping 4.0 (VSM 4.0) developed by Meudt et al. (2017) in the detailed identification of activities in information flows in a logistics Distribution Center (DC). The order generation, order picking, checking, consignor checking, and shipping flows were mapped. The research method applied was a case study in a distribution center of a large Brazilian industry in the metallurgical sector that manufactures consumer goods for retail. In this practical application, the approach produced satisfactory results as it was possible to identify and measure the informational indicators of VSM 4.0: the digitization/automation rate (DR) was 9%, the data utilization (DU) rate was 0%, and data availability (DA) rate of 16%. From this data, it was possible to verify that the company does not have a proprietary information flow, making this information sparse and management difficult, as 84% of the information is manual, that is, without the use of digital media, with low ERP use. The practical applicability of VSM 4.0 was verified in a logistics environment where information flow is significant. Furthermore, we observed that VSM 4.0 could contribute to the identification of waste in operations management and provide information for digital transformation inflows and processes, which are so crucial for the migration to Industry 4.0.

Proprietary Information Cost of Contracting with the Government

ABSTRACT We argue that contracting with the federal government involves significant proprietary information cost due to regulations requiring contractors to provide proprietary information, which may become available to outsiders via Freedom of Information Act (FOIA) requests. We provide evidence by showing that firms become more willing to bid for government contracts after a recent Supreme Court ruling on FOIA (Food Marketing Institute v. Argus Leader Media) that improved information protection for contractors and that this effect strengthens when the contracts entail higher proprietary information cost for contractors. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: K4; M4.

Resource allocation on periotity based schuduling and improve the security using DSSHA-256

Cloud computing has gained popularity with advancements in virtualization technology and the deployment of 5G. However, scheduling workload in a heterogeneous multi-cloud environment is a complicated process. Users of cloud services want to ensure that their data is secure and private, especially sensitive or proprietary information. Several research works have been proposed to solve the challenges associated with cloud computing. The proposed Adaptive Priority based scheduling (PBS) focuses on reducing data access completion time and computation expense for task scheduling in cloud computing. PBS assigns tasks depending on its size and selects the minimum cost path for data access. It contains a task register, scheduler, and task execution components for efficient task execution. The proposed system also executes a double signature mechanism for data privacy and security in data storage. This study correlates the performance of three algorithms, PBS, (Task Requirement Degree) TRD and (recommended a Risk adaptive Access Control) RADAC, in terms of task execution time and makespan time. The experimental results demonstrate that PBS outperforms TRD and RADAC in both metrics, as the number of tasks increases. PBS has a minimum task execution time and a lower makespan time than the other two algorithms

The Protection of Confidential Information in Restraint of Trade Agreements

This article examines the balance between protecting an employer’s confidential information and the enforceability of restraint of trade agreements. Central to the discourse is the principle that while employers legitimately seek to safeguard their proprietary information and trade secrets, such measures must align with public policy considerations to avoid unduly curtailing employees’ employment opportunities. Restraint of trade clauses are not inherently invalid but must be scrutinised for their reasonableness, necessity in protecting legitimate business interests and compliance with public policy. Focusing on confidential information as a key protectable interest, the article delineates the conditions under which such information qualifies for protection and how its misuse by former employees poses a legitimate concern for employers. The article underscores a growing tendency to prioritise the safeguarding of employers’ interests, particularly concerning proprietary information. This focus has led to foundational contractual principles being overlooked. The article argues for a nuanced understanding that considers the confidentiality undertaking, location and timing. It underscores the need for the judicious drafting and enforcement of restraint of trade clauses and confidentiality undertakings, guided by clear legal principles that safeguard both employers’ proprietary interests and the public interest in fair competition and employment mobility.

The Protection of Confidential Information in Restraint of Trade Agreements

This article examines the balance between protecting an employer’s confidential information and the enforceability of restraint of trade agreements. Central to the discourse is the principle that while employers legitimately seek to safeguard their proprietary information and trade secrets, such measures must align with public policy considerations to avoid unduly curtailing employees’ employment opportunities. Restraint of trade clauses are not inherently invalid but must be scrutinised for their reasonableness, necessity in protecting legitimate business interests and compliance with public policy. Focusing on confidential information as a key protectable interest, the article delineates the conditions under which such information qualifies for protection and how its misuse by former employees poses a legitimate concern for employers. The article underscores a growing tendency to prioritise the safeguarding of employers’ interests, particularly concerning proprietary information. This focus has led to foundational contractual principles being overlooked. The article argues for a nuanced understanding that considers the confidentiality undertaking, location and timing. It underscores the need for the judicious drafting and enforcement of restraint of trade clauses and confidentiality undertakings, guided by clear legal principles that safeguard both employers’ proprietary interests and the public interest in fair competition and employment mobility.

EuProGigant: A decentralized Federated Learning Approach based on Compute-to-Data and Gaia-X

Machine learning normally requires a considerable amount of data for model training, limiting the field of usage especially for small manufacturing companies due to their lack of machine data. Federated learning provides an opportunity to enlarge the data basis for model training without the need to directly share the machine data with other participants, addressing concerns regarding to privacy, intellectual property and potential reverse engineering of proprietary process information through competitors. Previous research focused mainly on federated learning models, mostly managed and orchestrated by some kind of centralized authority. The presented approach shows a more decentralized, self-sovereign concept of federated learning for the manufacturing industry, expanding its applicability to a broader range of participants. It combines existing solutions for machine learning and Compute-to-Data by Ocean Protocol with the concept of dataspaces as defined by Gaia-X. The methodology is demonstrated through an use case derived from industry demands involving several CNC milling machines.

Sharing surplus with clients: Evidence from the protection of bank proprietary information *

Sharing surplus with clients: Evidence from the protection of bank proprietary information *

A Simplified Chemical Reactor Network Approach for Aeroengine Combustion Chamber Modeling and Preliminary Design

In a time when low emission solutions and technologies are of utmost importance regarding the sustainability of the aviation sector, this publication introduces a reduced-order physics-based model for combustion chambers of aeroengines, which is capable of reliably producing accurate pollutant emission and combustion efficiency estimations. The burner is subdivided into three volumes, with each represented by a single perfectly stirred reactor, thereby resulting in a simplified three-element serial chemical reactor network configuration, reducing complexity, and promoting the generality and ease of use of the model, without requiring the proprietary engine information needed by other such models. A tuning method is proposed to circumvent the limitations of its simplified configuration and the lack of detailed geometric data for combustors in literature. In contrast to most similar frameworks, this also provides the model with the ability to simultaneously predict the combustion efficiency and all pollutant emissions of interest (NOx, CO and unburnt hydrocarbons) more effectively by means of implementing a detailed chemical kinetics model. Validation against three correlation methods and actual aeroengine configurations demonstrates accurate performance and emission trend predictions. Integrated within two distinct combustion chamber low-emission preliminary design processes, the proposed model evaluates each new design, thereby displaying the ability to be employed in terms of optimizing a combustor’s overall performance given its sensitivity to geometric changes. Overall, the proposed model proves its worth as a reliable and valuable tool for use towards a greener future in aviation.

Treat, Dump, or Export? How Domestic and International Waste Management Policies Shape Waste Chain Outcomes

Illegal or unwanted waste disposal methods such as dumping and export are prevalent in practice. To minimize the environmental harm of these methods, policymakers have implemented laws and regulations designed to combat them. Even so, violations are rampant as a high degree of heterogeneity between firms and proprietary information render monitoring imperfect. Decentralized waste disposal chains, a common form of interbusiness organization in this sector, compound this problem as firms also have limited information available on their waste chain partner, creating complex interactions between firm behavior and policy interventions. Against this background, we analyze the effects of domestic and international waste regulations targeting dumping and export, respectively, on firm incentives and compliance. We develop a two-tier waste chain with a producer that generates waste and an operator that treats it. The producer’s waste quality and the treatment operator’s efficiency can be private information. Either party can avoid compliance cost by violating regulations where the producer can arrange for export and the operator can dump locally. Our analysis reveals that primarily focusing on penalizing dumping by treatment operators can worsen environmental harm. Solely focusing on penalizing low-quality waste exports, a common intervention in practice, can also backfire. Instead, penalizing producers for downstream dumping should be given consideration. In addition, the asymmetry in export burden between waste quality levels should be reduced. This paper was accepted by Vishal Gaur, operations management.

Peer governance effects of information security breaches

Peers' information security risks may have sent negative signals to the market, thus forcing firms to strengthen their internal control governance. Solow's paradox, however, suggests that when information technology (IT) investment does not reach equilibrium, firms may still blindly increase IT investment while neglecting information security management. Using the unique information security breaches data released by the China National Information Security Vulnerability Database (CNVD), we find that the peers' information security breaches have a governance effect on firm internal control. The underlying mechanism is that peer information security breach increases the cost of proprietary information and reputation maintenance. In addition, we find that the above peer governance effects are more significant in samples with higher agency conflicts, high-tech industries, and higher supply. Further, our further analysis also shows that the peer governance effects of information security breaches positively affect firms' investment efficiency. Overall, our findings verify the peer governance effects of the information security breaches.

Algorithmic Transparency and Explainability under EU Law

This article focuses on algorithmic transparency under EU law, specifically exploring the ‘right to explanation’. It addresses the legal framework concerning Artificial Intelligence (AI) algorithms from the above – mentioned perspective, focusing on remedies which ensure transparency and accountability, given the black box effect of algorithms. Proprietary information, and transparency- performance trade-offs are analysed, as well as the ‘right to explanation’ within the General Data Protection Regulation (GDPR) and in light of the EU ‘AI Act’, which is expected to be adopted. The legal remedies under EU law are examined and assessed in terms of their efficiency. Algorithms, transparency, Explainability, GDPR, AI Act, Meaningful Information, EU Law

Co-Opetition and the Firm’s Information Environment

Some firms in the technology sector choose to cooperate with competitors (“co-opetition”) in standard setting organizations (SSOs). These SSOs create technology standards that facilitate rapid market penetration of new technologies such as Wi-Fi, Bluetooth, and 4G. Active participation in the standard setting process requires the exchange of proprietary information with competitors. Although the goal of such information sharing is to further a technology or a product market, firms potentially receive an additional benefit from access to competitor and industry information. We examine whether contributing to SSO committees enhances a firm’s information set and allows managers to better predict future sales. We find that the centrality of a firm’s location within the network of SSO collaborators is positively related to the accuracy of the firm’s sales forecasts. This relation is stronger when firms exchange more information with direct competitors and with larger firms, when forecasting is more difficult ex ante, and when firms forecast over longer horizons. Our findings show that collaborating with competitors in the product market provides an important additional benefit of improving the manager’s information set. This paper was accepted by David Simchi-Levi, accounting. Funding: This work was supported by the Wharton School, Institut Européen d’Administration des Affaires, the Institut Européen d’Administration des Affaires-Wharton Alliance, and the Mack Institute for Innovation Management. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2021.03152 .

Proprietary information and the choice between public and private debt

AbstractThe high costs of disclosing confidential information lead firms with proprietary information to prefer private debt (bank loan) to public debt (corporate bond). We provide empirical evidence supporting this proposition using the staggered adoption of the inevitable disclosure doctrine (IDD) by US state courts that exogenously increased the value of proprietary information. The focal firms are significantly less likely to issue bonds after the IDD adoption. Financing through public debt decreases more for firms in which the protection of proprietary information is relatively more important.

A Decade Review of Research Trends Using Waste Materials in the Building and Construction Industry: A Pathway towards a Circular Economy

The construction industry is among the most prominent contributors to global resource consumption, waste production, and greenhouse gas emissions. A pivotal step toward mitigating these sectoral impacts lies in the adoption of a circular production and consumption system. The use of alternative waste materials can mitigate landfill accumulation and the associated detrimental environmental effects. To highlight unconventional materials, this study began with a bibliometric assessment via a bibliography analyzis software called “Bibliometrix” (version 4.1.3). The outputs from the analyzis can assist in identifying research trends, gaps in literature and benchmark research performance. The search engine used for sourcing publications was Scopus, using the main criteria as “Waste materials used in building and construction”. The time-period analysed was from 2013 to 2023. The results included publications obtained in journal articles, book chapters and conference proceedings. The assessment reviewed 6238 documents from 1482 sources. The results revealed an array of waste materials; however, rubber, textiles, and ceramics had a significant reduction in research attention. Rubber waste presents promising opportunities in civil concrete construction methods. The preparatory steps of textile fibres in composite materials are frequently disregarded, resulting in structural issues for the end-product. Obstacles persist in ceramic technology due to the absence of transparency, primarily because industry entities closely safeguard proprietary information. While sustainability research often emphasizes emissions, practical trials commonly revolve around integrating materials into current systems. A more comprehensive approach, contemplating the complete lifecycle of materials, could provide deeper insights into fostering sustainable construction practices. Researchers can use these findings when determining trends, research gaps, and future research directions.

Multinationals' profits in China: Impact of tax avoidance

Based on proprietary and hand-collected source country information on foreign-owned firms in China, this paper empirically explores the effect of the tax avoidance of multinational firms on the profit rate of foreign-owned firms. Foreign firms in China previously benefited from various preferential tax policies and had a lower effective tax rate compared to domestic firms. The results show that the increase in the difference between the statutory maximum tax rate in the parent country and the domestic tax rate will increase foreign firms' pretax profit margin. This effect is more pronounced for younger firms and wholly foreign-owned firms. Further tests indicate that the transfer pricing in export and import activity of foreign firms is an important channel for multinational firms to shift profits. In year 2008, the implementation of the new Enterprise Income Tax Law has unified the corporate tax rate for both domestic and foreign firms at 25 percent. The tax reform reduces the profit margin of foreign firms, especially those with larger tax rate differentials. This paper explains multinational firms' profit performance from the novel perspective of tax avoidance.