Potential Asset Research Articles

In-House Virtual Planning and 3D Printed Surgical Guides for Reconstructive Rhinoplasty.

Performing rhinoplasty in patients with craniofacial malformations remains a challenge, even for experienced surgeons. Advances in 3D technology and its application in surgical planning and printing of cutting guides and splints have become important tools to improve aesthetic and functional results. To describe an in-house workflow for surgical planning and printing of cutting guides and splints for complex rhinoplasty cases. This article describes an in-house workflow for complex rhinoplasty, as used in the maxillofacial department of a children's hospital specialized in the treatment of cleft and craniofacial malformations. Customized surgical guides help the surgeon to harvest and mold potential septal and costochondral grafts more accurately, to reduce surgical time and to verify the dimensions of the sculpted nasal shape following surgical planning templates. Patient satisfaction degree according to Rhinoplasty Outcome Evaluation questionnaire was 18/24. The presented workflow represents a potential asset in obtaining more accurate and satisfactory results in complex rhinoplasties.

Factors Affecting Seaweed (Eucheuma cottoni) Production in Banten Province (Case in Lontar Village)

Seaweed is one of the plants that has a lot of potential as a functional food ingredient, active ingredient of drug preparation and even cosmetics that are quite natural in producing various pharmacological activities both as a source of antioxidants, antibacterials, antimicrobials and anticancer. Seaweed is currently a potential asset for areas that are able to produce it to meet the increasing market needs. Lontar Village, located in Banten Province, is one of the main seed producing areas. However, seed production factors are one of the main indicators that need to be used as a standard in this study, such as the length of the rope span, age characteristics, education characteristics, characteristics of the seed farmer's business experience. This type of research is quantitative and data is obtained primarily and secondarily. The data obtained were analyzed using the SPSS 26 program. The results of the study showed that the factors that influence seaweed production in Banten Province, especially Lontar Village, are influenced by the length of the rope span, age characteristics, education characteristics, characteristics of the seaweed farmer's business experience. The conclusion is that seaweed production is influenced by various characteristics, namely age, education, and seaweed farming experience.

Constructing Sukuk-linked Awqaf (endowment) model

PurposeIslamic endowment (awqaf), particularly awqaf land, is one of the potential Islamic social assets to serve the public interest, particularly to provide public infrastructures such as business centers, public hospitals and airports. However, unfortunately, most of them are still unproductive lands, especially in the form of idle lands. One problem to use such unproductive awqaf lands is the lack of awqaf land model as the platform to use such awqaf lands. This paper aims to construct and propose a model called Sukuk-linked Awqaf (SLA) to use awqaf lands as an underlying for Sukuk issuance.Design/methodology/approachThis paper constructs mechanisms and formulas of SLA by involving Sukuk issuer, awqaf management (Nadzhir), Sukuk investors and tenants of the infrastructure. In particular, the SLA model is proposed based on the unique characteristics of both awqaf asset and Ijarah (leasing) Sukuk, considers the intention of state-owned enterprise (SOE) to construct buildings to be rented to the tenant and to be owned by the awqaf manager and formulates equations and uses net present value theory to determine Nadzhir and Sukuk investors’ investment decisions.FindingsEngaging awqaf land with SLA model can ease its benefit for the society. The model addresses the strategic roles of Nadzhir, SOE, investors and contractor in using awqaf land.Research limitations/implicationsThe SLA model could ease related parties to use the awqaf land for the sake of public benefits.Originality/valueTo the best of the author’s knowledge, this is the first assessment on the potential implementation of Islamic hedging with a commodity as an alternative hedging in Indonesia.

Innovative foresight for water utilities asset management using PRISM software

Our analysis aims to better understand water losses by developing a specific methodology for estimating water leak flow rates and durations. Additionally, it aims to improve asset management practices for drinking water utilities by forecasting the costs and benefits of investment and operational decisions on the network. Current utility practices are compared to a "do nothing" policy and to the potential effective asset management policies proposed by an artificial neural network (ANN) based software, PRISM. Applied to four utilities in France, our methodology provides valuable insights for enhancing water loss estimates and finding trade-off asset management policies.

Unsupervised Feature Selection to Identify Important ICD-10 and ATC Codes for Machine Learning on a Cohort of Patients With Coronary Heart Disease: Retrospective Study.

The application of machine learning in health care often necessitates the use of hierarchical codes such as the International Classification of Diseases (ICD) and Anatomical Therapeutic Chemical (ATC) systems. These codes classify diseases and medications, respectively, thereby forming extensive data dimensions. Unsupervised feature selection tackles the "curse of dimensionality" and helps to improve the accuracy and performance of supervised learning models by reducing the number of irrelevant or redundant features and avoiding overfitting. Techniques for unsupervised feature selection, such as filter, wrapper, and embedded methods, are implemented to select the most important features with the most intrinsic information. However, they face challenges due to the sheer volume of ICD and ATC codes and the hierarchical structures of these systems. The objective of this study was to compare several unsupervised feature selection methods for ICD and ATC code databases of patients with coronary artery disease in different aspects of performance and complexity and select the best set of features representing these patients. We compared several unsupervised feature selection methods for 2 ICD and 1 ATC code databases of 51,506 patients with coronary artery disease in Alberta, Canada. Specifically, we used the Laplacian score, unsupervised feature selection for multicluster data, autoencoder-inspired unsupervised feature selection, principal feature analysis, and concrete autoencoders with and without ICD or ATC tree weight adjustment to select the 100 best features from over 9000 ICD and 2000 ATC codes. We assessed the selected features based on their ability to reconstruct the initial feature space and predict 90-day mortality following discharge. We also compared the complexity of the selected features by mean code level in the ICD or ATC tree and the interpretability of the features in the mortality prediction task using Shapley analysis. In feature space reconstruction and mortality prediction, the concrete autoencoder-based methods outperformed other techniques. Particularly, a weight-adjusted concrete autoencoder variant demonstrated improved reconstruction accuracy and significant predictive performance enhancement, confirmed by DeLong and McNemar tests (P<.05). Concrete autoencoders preferred more general codes, and they consistently reconstructed all features accurately. Additionally, features selected by weight-adjusted concrete autoencoders yielded higher Shapley values in mortality prediction than most alternatives. This study scrutinized 5 feature selection methods in ICD and ATC code data sets in an unsupervised context. Our findings underscore the superiority of the concrete autoencoder method in selecting salient features that represent the entire data set, offering a potential asset for subsequent machine learning research. We also present a novel weight adjustment approach for the concrete autoencoders specifically tailored for ICD and ATC code data sets to enhance the generalizability and interpretability of the selected features.

Investment Portfolio with Convex Optimization and Risk Adjustment Using Multi-Factor Model and Multi-Armed Bandit Algorithm

This paper examines the creation of investment portfolios through convex optimization, multifactor models, and the multi-armed bandit (MAB) algorithms, focusing on the KL-UCB strategy to optimize decisions in uncertain settings. It explores the impact of systematic risk factors using the Fama-French three-factor model, estimating the influence of market, size, and value premiums via linear regression. The use of Monte Carlo simulation is detailed for generating potential asset allocations and calculating their expected returns, volatility, and Sharpe ratios. The optimize minimize function from the SciPy library is employed to construct an efficient frontier and determine optimal asset allocation, aiming to maximize returns or minimize volatility across various risk levels. The findings suggest that the strategy of dynamic weight adjustments combined with the KL-UCB algorithm enhances portfolio returns, particularly during market volatility. The research also reveals a portfolio inclination towards large-cap growth stocks due to the negative impacts of size and value premiums. It concludes that dynamic weight adjustment strategies offer significant potential in optimizing portfolio performance in complex market conditions, though leveraging increases risk and should be carefully managed according to investor risk tolerance.

Selenium mitigates the loss of nutritional quality in rice grown at an elevated concentration of carbon dioxide

Atmospheric CO2 enrichment has the potential to improve rice (Oryza sativa L.) yield, but it may also reduce grain nutritional quality, by reducing mineral and protein concentrations. Selenium (Se) fertilization may improve rice grain nutritional composition, but it is not known if this response extends to plants grown in elevated carbon dioxide concentration (eCO2). We conducted experiments to identify the impacts of Se fertilization on yield and quality of rice grains in response to eCO2. The effect of the Se treatment was not significant for the grain yield within each CO2 condition. However, the reduction in macronutrients and micronutrients under eCO2 was mitigated in grains of plants fertilized with Se. Fertilization with Se increased the concentration of Se in roots, flag leaves, and grains independently of atmospheric CO2 concentrations. Elevation of the transcripts of ion transport-related genes could, at least partially, explain the positive relationship between mineral concentrations and grain mass resulting from Se fertilization under eCO2. Treatment with Se also increased the accumulation of total protein in grains under eCO2. Overall, our results revealed that Se fertilization represents a potential asset to maintain rice grain nutritional quality in a future with rising atmospheric CO2 concentration.

DMPs as Management Tool for Intellectual Assets by SMART-metrics

Data Management Plans (DMPs) are vital components of effective research data management (RDM). They serve not only as organisational tools but also as a structured framework dictating the collection, processing, sharing/publishing, and management of data throughout the research data life cycle. This can include existing data curation standards, the establishment of data handling protocols, and the creation, when necessary, of community curation policies. Therefore, DMPs present a unique opportunity to harmonise project management efforts for optimising the formulation and execution of project objectives. To harness the full potential of DMPs as project management tools, the SMART approach (i.e., Specific, Measurable, Achievable, Relevant, and Time-bound) emerges as a compelling methodology. During the initial stage of the project proposal, drafted SMART metrics can offer a systematic approach to map work packages (WPs) and deliverables to the overarching project objectives. Then, the Principal Investigators (PIs) can ensure the consortia that all the project potential intellectual assets (i.e., expected research results) were considered properly, as well as their necessary timelines, resources, and execution. It becomes imperative for data stewards (DSs) and governance policymakers to educate and provide guidelines to researchers on the advantages of developing well-curated DMPs that align results with SMART metrics. This alignment ensures that every intellectual asset intended as a research result (e.g., intellectual properties, publications, datasets, and software) within the project is subject to rigorous drafted planning, execution, and accountability. Consequently, the risk of unforeseen setbacks and/or deviations from the original objectives is minimised, increasing the traceability and transparency of the research data life cycle. In addition, the integration of Technology Readiness Levels (TRLs) into this proposed enhanced DMP provides a systematic method to evaluate the maturity and readiness of technologies across scientific disciplines. Regular TRL assessments will allow PIs: (1) to monitor the WP progress, (2) to adapt research strategies if required, and (3) to ensure the projects remain in line with the drafted SMART metrics in the enhanced DMP before the project started. The TRLs can also help PIs maintain their focus on project milestones and specific tasks aligned with the original objectives, contributing to the overall success of their endeavours, while improving the transparency for the reporting and divulgation of the research results. The paper presents the overall framework for enhancing DMPs as project management tools for any intellectual assets using SMART metrics and TRLs, as well as introducing suggested support services for data stewardship teams to assist PIs when implementing this novel framework effectively.

Students’ Growth Mindset: Potential Asset in Fostering Educational Equity

Students’ Growth Mindset: Potential Asset in Fostering Educational Equity

Enhancing reconnaissance security: a 2-tier deception-driven model approach (2TDDSM)

The emergence of network security has revolutionized the way educational institutions operate, providing advanced connectivity, enhanced communication, and efficient management of resources. However, with the increasing dependence on interconnected systems, institutions and organizations became vulnerable targets for cyber threats. To address these security challenges, a two-tier deception-driven model specifically designed to for the initial phase of attacks in reconnaissance period where the adversaries is to gather information of the targets. Defending threats in this phase can provide active and proactive defense allowing the administrator to identify potential attackers and understanding their methods, motivation and potential target assets. The model's layered approach creates a resilient defense mechanism that aligns with the advanced deception techniques which aims to misguide potential threats attempting to gather intelligence within the network.

Application Of Markowitz and Index Models to Real Markets

After Markowitz put forward the portfolio theory in the 1950s, the modern investment theory was developed, and more related theoretical models were created based on it. To find the optimal portfolio in the market, this paper randomly selects 7 stock types, uses three different constraint methods to show the investment characteristics of different group of investors, and uses Index model and Markowitz model to find efficient frontier and the proportion of asset allocation under the condition of maximum Sharpe ratio and minimum variance. The results show that to achieve the maximum Sharpe ratio and find the best combination, it is necessary to purchase AAPL primarily. Secondly, it chooses to purchase assets with less correlation and relatively large return rate, such as MSFT and WMT. The results in this paper shed lights for investor in selecting potential assets and may provide helpful insight for future investments.

The gamma-variate in contrast-enhanced imaging: a unified view and method from computed to electrical impedance tomography

Objective. Modern medical imaging plays a vital role in clinical practice, enabling non-invasive visualization of anatomical structures. Dynamic contrast enhancement (DCE) imaging is a technique that uses contrast agents to visualize blood flow dynamics in a time-resolved manner. It can be applied to different modalities, such as computed tomography (CT) and electrical impedance tomography (EIT). This study aims to develop a common theoretical and practical hemodynamic extraction basis for DCE modelling across modalities, based on the gamma-variate function. Approach. The study introduces a framework to generate time-intensity curves for multiple DCE imaging modalities from user-defined hemodynamic parameters. Thus, extensive datasets were simulated for both DCE-CT and EIT, representing different hemodynamic scenarios. Additionally, gamma-variate extensions to account for several physiological effects were detailed in a modality-agnostic manner, and three corresponding fitting strategies, namely nonlinear, linear, and a novel hybrid approach, were implemented and compared on the basis of accuracy of parameter estimation, first pass reconstruction, speed of computation, and failure rate. Main results. As a result, we found the linear method to be the most modality-dependent, exhibiting the greatest bias, variance and failure rates, although remaining the fastest alternative. The hybrid method at least matches the state-of-the-art nonlinear method’s accuracy, while improving its robustness and speed by 10 times. Significance. Our research suggests that the hybrid method may bring noteworthy accuracy and efficiency improvements in handling the high-dimensionality of DCE imaging in general, being a step towards real-time processing. Moreover, our generative model presents a potential asset to produce benchmarking and data augmentation datasets across modalities.

Bank Specialization and Zombie Lending

We study whether banks internalize congestion externalities when lending to zombie firms. We conjecture that banks should be better informed about the presence of zombie firms and the congestion externalities that such firms exert on healthy borrowers in industries where banks are specialized and show that banks’ credit supply to zombie firms relates negatively to their industry specialization. This relation is stronger when congestion externalities are likely to have stronger adverse effects, namely when zombie firms take a higher fraction of resources in the industry or when the industry is geographically more concentrated. Additionally, this relation is weaker in industries with higher asset specificity as zombie firms’ default (and potential asset fire sales) could reduce healthy borrowers’ collateral value. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.01437 .

Analysis of asset management difficulties observed in Brazilian firms: a study based on expert survey and fuzzy TOPSIS

PurposeThe purpose of this paper was to understand the difficulties related to asset management observed by experts in Brazilian organizations in light of the requirements outlined in the ISO 55001:2014 standard.Design/methodology/approachA survey was performed with asset management experts. The collected data were analyzed using frequency analysis, hierarchical cluster analysis and fuzzy technique for order preference by similarity to deal solution (TOPSIS).FindingsBased on data analysis, the most critical difficulties observed were related to managing and controlling the impact of changes in the company that affect asset management objectives; to the committing to and supporting the asset management system by the top management of the organization; to manage the processes for dealing with risks and opportunities for the asset management system and plans, and correcting failures in asset performance; and to plan and conduct actions in an integrated manner to identify and minimize adverse impacts associated with the asset management system, and afterwards verifying their effectiveness.Originality/valueThe findings of this study have important theoretical and practical contributions, since they indicate the most critical points observed in asset management in Brazil, which can be used as a source for future research and by professionals to prioritize difficulties in future planning and develop action plans to overcome them. The step-by-step methodological approach presented in this study provides professionals and researchers with a replicable method of identifying potential asset management difficulties in a given specific reality.

Heat Transfer Analysis of Insulation Material for the Reserve Hot Water Tank

A domestic hot water tank represents a significant potential demand-side management asset in energy systems. The selection of insulation materials is crucial for maintaining the temperature of the hot water tank and preventing massive heat loss from the tank. This study aims to analyze the different combinations of insulation material for the reserve hot water tank. Several materials, such as plywood, white bricks, red bricks, plasticine, aluminum foil, styrofoam, fine sand, and glass, were used as the insulation layer in experiments. Seven combinations of insulation layers were made to insulate the mini reserve water tank in the experiment. The insulation layers covered the surface of the water tank, and the initial and final temperature of the hot water was measured. The heat loss from the hot water tank and the thermal resistivity of the insulators were also studied. The experimental results revealed that the combination of plastic, plasticines, styrofoam, and timber yields the lowest heat loss for the hot water tank. This finding indicated that the material with low thermal conductivity is the best insulator for preventing heat loss from the thermal system. Thus, this study is useful in designing and selecting the insulation materials for the reserve hot water tank for domestic and industrial use.

Criminal Defense Attorneys and Client Suicide: Survey and Recommendations From Washington State.

The connection between suicide and incarceration is well documented, in particular after recent arrest. Criminal defense attorneys may be one of the few people in meaningful contact with this population, and lawyers have a unique window into their clients' well-being. In this Viewpoint, we explore the experiences of attorneys who work with clients with suicidal thoughts and behaviors. We developed and administered a survey to criminal defense attorneys in the State of Washington, ascertaining their experiences with client suicide. A total of 44 responses were collected, with over 95% of respondents having been concerned about a client's risk for suicide. We conclude that client suicide widely impacts criminal defense attorneys, and lawyers' role with justice-involved clients uniquely positions them to be a potential asset in suicide prevention efforts.

Social networks of people with serious mental illness who smoke: potential role in a smoking cessation intervention.

Smoking is a major contributor to morbidity and mortality among individuals with serious mental illness (SMI) and social networks may play an important role in smoking behaviors. Our objectives were to (1) describe the network characteristics of adults with SMI who smoke tobacco (2) explore whether network attributes were associated with nicotine dependence. We performed a secondary analysis of baseline data from a tobacco smoking cessation intervention trial among 192 participants with SMI. A subgroup (n = 75) completed questions on the characteristics of their social network members. The network characteristics included network composition (e.g. proportion who smoke) and network structure (e.g. density of connections between members). We used multilevel models to examine associations with nicotine dependence. Participant characteristics included: a mean age 50 years, 49% women, 48% Black, and 41% primary diagnosis of schizophrenia/schizoaffective disorder. The median personal network proportion of active smokers was 22%, active quitters 0%, and non-smokers 53%. The density of ties between actively smoking network members was greater than between non-smoking members (55% vs 43%, p = .02). Proportion of network smokers was not associated with nicotine dependence. We identified potential social network challenges and assets to smoking cessation and implications for network interventions among individuals with SMI.

Do Green Bonds Affect Extreme Spillover and Hedging Effects Across Stocks and Commodities?

This study investigates the extreme connectedness network among Green bonds, stocks and commodities and its implications for portfolio diversification during the turbulent periods. To this end, we implement the novel QVAR methodology by Ando, Greenwood-Nimmo, and Shin to study the connectedness at the median, extreme lower, and extreme upper quantiles. The results reveal dynamic spillovers among markets. Interestingly, static spillover effects are stronger for the extreme upper and lower quantiles than for the intermediate quantiles. Commodities are the major net transmitters, whereas Shanghai Stock Exchange green bond is the net receiver of shocks in the system. These results are supported by the findings of portfolio management analyses, which suggest that Green bonds and gold could function as potential diversification assets, serving as safe havens, particularly for the stock and Brent markets. Our study provides valuable insights for investors aiming to optimize their hedging strategies, guiding risk management, and portfolio diversification.

Mushroom Picking as a Special Form of Recreation and Tourism in Woodland Areas—A Case Study of Poland

The paper looks at the potential benefits of mushrooms in terms of health, recreation, and tourism. Mycotourism is an innovative, specialised tourism product that has been successfully introduced in some regions of the world, helping to combat seasonality and promote economic development in rural areas. The aim of the study was to analyse the development of mycotourism in Poland in comparison with other countries. As a method, a questionnaire on the cultural significance of mushrooms was developed and disseminated via social media. It was found that there are strong mycophilic tendencies in Poland, leading to a strong interest in mushrooms, both in terms of cultural and culinary traditions. They are also a factor that attracts tourists to the forest areas. In contrast, the UK and Germany are more mycophobic, resulting in a lower interest in mushrooms, limited culinary use, and a lower awareness of their role in the ecosystem and their potential health benefits. The low average score for knowledge of mushrooms in countries such as the UK indicates a need for increased mycological education that can contribute to a better understanding of the conservation of these important components of the forest floor. The high proportion of people who see mushroom picking in Poland as a form of recreation emphasises its role as an important cultural and potential nature tourism asset. In Poland, where long traditions are associated with mushrooms and mushroom picking, they have a strong influence on the choice of mycological tourism, especially in regions with a rich tradition of mushroom picking. The high percentage of mushrooms used for culinary purposes, especially in Poland, emphasises their value and influences the health component of the diet, which is rich in proteins, vitamins, and minerals. Research has shown that mushroom consumption and its effects on health are perceived positively. This is evidenced by higher ratings in Poland than in the UK and Germany, indicating a general awareness of the health benefits of mushrooms, even though their use in medicine remains limited. The low level of awareness of the role of mushrooms and their potential health benefits suggests that educational and promotional activities should be increased to sensitise the public to mushrooms.

Study of land potential based on soil characteristics using interpolation and scoring methods for non agricultural uses: a case study in Wonosalam, Jombang District, East Java

The state asset land managed by UPN "Veteran" East Java is located in the Wonosalam District based on land certificate data issued by the Jombang BPN covering 13.5 hectares. Currently more than 50% of the land has not been used optimally to support learning, research and community service. The problems that arise in utilizing land assets to support learning, research and community service are 1) the legal boundaries of land ownership are not yet clear, 2) there is no land use master plan to support the learning process, 3) there is no potential data that can be used. prepare use and development plans. Against the background of the problems above, this research aims to map the potential of state land assets by "spatial interpolation, scoring and weight overlay" of land characteristics. Interpolation is a way of calculating the area of several representative measurement points, while scoring and "Weight Overlay" is a facility provided by ArcMap GIS which combines input spatial data with weighting (weight factor) and scoring. Land unit maps are obtained from overlaying relief, geology, slope and land use maps. Interpolation, Scoring and Weight Overlay of the nine land characteristics yielded a potential land asset for buildings, good category 16.61% (44,130.38 m2); moderate 25.66% (67,382.75 m2) and bad 7.523% (19,784.88 m2). Playing field potential, good category 54.73% (71,865.05 m2) and medium 45.27% (59,432.62 m2). Potential for road infrastructure development in the good category 32.38% (42513.74 m2); Moderate 42.68% (56035.24 m2) and Bad 24.94% (32748.69 m2), and all of these potentials are in Slightly Flat topography (Slope, 0-3%) to hilly (Slope, 15-25%).