bluuebunny/crossref_metadata_2025 huggingface dataset:
Environmental Factor-Based Segmentation of Images in Natural Environments
Authors: Jang Seok-Woo
Published: April 2022

The robust segmentation of color images in a natural environment without specific constraints such as lighting or background is very important in the field of image processing and computer vision. In this paper, an environmentally adaptive image segmentation method using color invariant
is proposed. The proposed method introduces a number of color invariant, such as W, C, U, N, and H, and automatically detects factors in the surrounding environment in which images such as lighting, shading, and highlights are taken. The image is then effectively split based on the edge by
selecting the color invariant optimal for the detected environmental factors. In the experiment, we implemented the proposed edge-based image segmentation algorithm. Various image data taken in general environments without specific constraints were utilized as input images of the suggested
system. In this study, various kinds of color images taken in different environments were tested, and each color invariant was extracted from the experiments that best expressed the environmental changes around them. As a result, a largest number of images were determined to have a change
in the intensity of lighting, followed by highlights and shadows. In addition, there were a few images that determined that no special state environmental changes existed. As the results of the experiment show visually, the existing method did not correctly remove shadows and did not detect
some areas of the circular shape. In addition, the existing method can also be found to be partially inaccurate in edge detection in many areas. On the other hand, the proposed method confirmed stable segmentation of images. The proposed color invariant-based image segmentation algorithm is
expected to be useful in various pattern recognition areas such as face tracking, mobile object detection, gesture recognition, motion understanding, etc.
An Analysis of Digital Assets on Exploiting Blockchain Management for Foreign Students
Authors: Lim Jin-Ho , Na Kwan-Sik , Kim Seung-Cheon
Published: April 2022

This study shows O2O (offline to online) based studying abroad platform, we called it as DRM (DoDream), that provides foreign students with various information for studying in Korea and matching platform with Korean universities (Language Institute) (Lim, J.H., et al., 2019. The architecture
design of students’ career information management system using blockchain technology. International Journal of Innovative Technology and Exploring Engineering, 8(8S2), pp.188–193). Empirical results reveal studying abroad provides a new environment for foreign students who
dream of studying in Korea by innovating structural problems of existing studying abroad market and sharing open information about Korea n universities, and to provide systematic and efficient study abroad support services to Korean universities (Language institutes) and local study abroad.
DRM (DoDream) Tokens will be otherwise intended to be generally obtainable by users of the DRM (DoDream) Platform through the methods externally from third party cryptocurrency exchanges or internally on the DRM (DoDream) platform through conversion of “step” points that are awarded
to users who have participated in events, promotions and/or who have made positive contributions to the DoDream Platform community.
A Convergence Model for Environment Analysis of SME (Small and Medium Enterprises) Using RPA (Robotic Process Automation)
Authors: Kim Young-Jin , Hong Jung-Wan , You Yen-Yoo
Published: April 2022

The purpose of this study is to investigate the effectiveness of the consulting project of the convergence model for analyzing the market environment of Small and Medium Enterprises (SME) using Robotic Process Automation (RPA). The subject of the study was the semiconductor manufacturing
machinery manufacturing industry (Korea Standard Industry Code (KSIC): C29271), and the market environment analysis process modeling was conducted using the RPA program. In fact, the Korean RPA program, “AutomateOne,” was used to automate market environment analysis. Currently,
RPA is used as a substitute for simple, repetitive and standardized work in the financial sector, and it is used only in limited fields such as accounting duties, so studies on the applicability in other industries are insufficient. In this study, in the field of knowledge service in which
consultants are mainly active, in market analysis work, scripts were created through actual business process modeling to show the possibility of application in the relevant work. The application of the consulting project was proved by the contribution of digital workers, which is a realistic
measure against the reduction of the production worker population. In this study, an application case of robot process automation was studied in the knowledge service industry. In the future, research is needed to increase the efficiency of business process modeling through linking with open
Python libraries and cognitive functions of machine learning or deep learning.
Implementation of Photoplethysmography Measurement System Based on Convolution Neural Network for Personalized Exercise Intensity
Authors: Lee Ji-Su , Seo Ji-Yun , Noh Yun-Hong , Jeong Do-Un
Published: April 2022

With increasing interest in health, many people are exercising to lose weight, prevent disease, and improve cardiorespiratory function. For effective exercise, users should proceed with appropriate intensity depending on their physical strength. The system implemented in this paper
classifies exercise intensity according to PPG signal using CNN training model for objective exercise intensity classification. The PPG signal was measured after exercise through the PPG sensor, and the training data set was constructed that based on the interval between P-peaks. The
training data set is trained on the CNN model to classify the three exercise intensity according to the PPG signal. In order to analyze the accuracy of the implemented CNN training model, the performance evaluation of the classification evaluation metrics and the exercise intensity classification
monitoring system was performed. First, the performance evaluation of the CNN model for classifying exercise intensity was conducted. In the performance evaluation, the classification evaluation metrics was calculated according to the training result, the recall rate representing the percentage
of successful prediction among the actual correct answers, the precision representing the actual correct answer rate among the predicted data, and the F 1 score representing the harmonic average of recall and precision were confirmed. As a result of CNN training model classification
evaluation metrics, it was the accuracy was 99.3%, the recall rate was 99.9%, the precision was 99.8%, and the F 1 score was 99.4%. Second, to evaluate the performance of the exercise intensity classification monitoring system, jump rope experiment was conducted with 5 subjects. The
experiment measured PPG at the end of each set after low, moderate, and high intensity jump rope. The classification accuracy was analyzed by entering the measured PPG data into the CNN model 50 times each. As a result of the experiment, the accuracy of low intensity was 98%, moderate intensity
was 93.6%, and high intensity was 97.6%, confirming a total accuracy of 96.4%. Some errors are thought to have occurred due to the fact that the data located at the boundary line between the exercise intensity was classified incorrectly. In future studies, we would like to conduct a study
of exercise intensity monitoring system that can be applied to various exercises by measuring acceleration signals for each exercise together.
A 4-Dimensional Service Evaluation Strategy on Web Services
Authors: Lim Ok-Sun , Shin Jee-Ah , Kim Jin-Hwa
Published: April 2022

The purpose of this study is to suggest a multi-dimensional model that evaluates services in web stores using data mining, text mining and surveys. Unlike other service evaluation model, this study suggests a 4 dimensional approach in evaluating web services. It uses reciprocal evaluation
methods on a web service by both services providers and service users. It identifies the cognitive differences on web services between these two groups. The study also uses text mining technologies such as social mining and topic analysis to find images of the web services. The results from
the study show that there are significant differences between the evaluations on web services by service providers and service users. There are also differences between images of a service provider from news data and social media data. These differences are represented with keywords related
to the service providers. Texts from news are collected and analyzed to have more object images of a web service providers. Texts from social media are collected and analyzed to have more personal images of a web service providers. A decision tree analysis, as a data mining tool, is used to
induce and to produce a strategy to understand the cognitive differences and to improve the quality of services. A decision tree analysis is used to find the pattern and to explain the difference between service providers and service users. It can be used to better understand the quality of
their services and to improve the quality of service from service provider’s point of view. The approach this study suggests can be used to other evaluation areas such as customer satisfaction on new products or services.
Stock Price Prediction by Using BLSTM (Bidirectional Long Short Term Memory)
Authors: Hong Sunghyuck , Han Jungsoo
Published: April 2022

Currently, many researchers are working on stock price prediction system by using deep learning algorithms. Stock market is completely random, and there is no pattern. Even though, a pattern in stock market could be found, it will not be last for a long time because the stock market
will adopt a new situation and the strategy is no longer available on already changed stock market. There are many auto trading programs such as a trading bot on stock market. However, they are literally trade stocks based on human’s direction or rules. It will not affect any changes,
and it keeps working as what rules are set up from the initial status on the stock market. Stock price depends on volume of total sales, stock news, revenue, total asset, big buyer’s position and so on. There are many aspects for affecting stock price, and it changes all the time. Therefore,
it keeps monitoring stock market and makes a decision whether buy or sell at the right time for earning profits. This research uses Bidirectional Long Short-Term Memory (BLSTM) to predict stock price in the near future. BLSTM is more accurate than LSTM which is one directional. In addition,
stock market is like a living creature. Data to manipulate stock price must be inputted and analyzed consistently. Therefore, stock price can be predicted by consistent monitoring with BLSTM.
Single Image Super Resolution Using Multiple Re-Evaluation Process
Authors: Han Hyun Ho , Lee Sang Hun
Published: April 2022

In this paper, we proposed improved single image super resolution using multiple re-evaluation Process model for use in various image processing fields. The proposed method generates the first super resolution using the input image, and analyzes the change for each region by comparing
the features of previous image and super resolution result. According to the analyzed features, the feature map for generate n-th super resolution was selected for improved detail. After then, next generate super resolution using previous super resolution result as input image. This
process is repeated for final result. The existing single image super resolution method has two areas to be improved. First, it minimizes artifacts or staircases, which are unnecessary details that can be created during the super resolution process. Second, it is necessary to consider the
input image because it affects the result depending on the quality of input image used in the super resolution process. Therefore, in order to minimize unnecessary details, the proposed method analyzed the feature map from the generated super resolution result and applied it according to the
amount of change. In addition, aimed to gradually improve the input image to be used in the super resolution process by using the super resolution generated in the previous step. By comparing and evaluating the proposed method with the conventional single image super resolution method with
PSNR and SSIM, it is improved by about 3%.
Dimming Level Improvement Method Through Simple Mapping Error Correction Code in Visible Light Communication
Authors: Han Doohee , Lee Kyujin
Published: April 2022

Since the visible light communication (VLC) has to perform the functions of communication and illumination at the same time, a method for communication as well as lighting is needed. In this paper, when text data is transmitted through visible light communication, the level of illumination
dimming according to the frequency of occurrence of alphabets in sentences is analyzed, and a method of improving the dimming level and Bit Error Rate (BER) performance through error correction codes generated during data transmission is studied. Visible light communication systems must perform
both communication and lighting functions, so not only communication but also a method for the lighting role is needed. When transferring data (transfer text), the frequency of occurrence of alphabets in sentences is different. Depending on the frequency of occurrence of these alphabetic characters,
if there are many ‘0’s in the code to be transmitted, the dimming level will be lowered and flicker will occur. Also, when a 1-bit error occurs, the alphabet code itself is changed. To solve this problem, an error correction code using parity bits has been added. Through this,
it was confirmed that the overall dimming level and Bit Error Rate (BER) performance were improved. Also, in visible light communication, the function of lighting is closely related to the performance of the overall system. As we have seen above, when there is a continuous zero period, the
function of the lighting is severely degraded. This reduces the performance of the entire system, not just the lighting. Therefore, the dimming level and BER performance were improved by improving the performance through the algorithm and error correction code to improve the overall dimming
level.
The Blanket Application Model of Reference Information for Effective Manufacturing Execution System Management
Authors: Park Sang-Hyock , Park Koo-Rack , Kim Dong-Hyun
Published: April 2022

In the manufacturing industry, there is a transition to multi-item production for reinforcement of competitiveness. Therefore, the hybrid manufacturing technology is increasing. Especially, many efforts in production quality improvement are made through the adoption of the Manufacturing
Execution System and ERP, so it is necessary to operate MES for prompt and effective management. Therefore, the adoption of MES is necessary. MES should improve ineffective parts in production activities while managing all stages related to production of products. If there is change in the
process, the changed items should be reflected to the system. However, most manufacturing execution systems are operated passively and repetitively by system administrators. This study presents a model that system administrators can comprehensively apply reference information about production
related requirements on specific line’s equipment to the same equipment of other lines. To practice the model, demands of MES administrators were organized, the current system’s screen is analyzed, data for applicable reference information are classified, the screens for blanket
and selective applications are designed and realized, the reference information is registered to same equipment in all the lines in case of blanket application. The reference information is registered to selected lines in case of selective application. In the results of the presented model’s
test, at first it wasn’t 100% successful due to exceptional situation that the wrong data exist in the database. The validity check function for the original data that causes the exceptional situation was added, which was notified to the system administrators so that they can correct
the wrong original data. The equipment reference information blanket application was implemented, and it was 100% data process accuracy. In addition, the flexible response for application to production lines is possible thanks to the division of blanket application and selective application
of reference information.
Internet of Things Simulation Learning Model Based on Virtual Remote Input Output
Authors: Seo Hyeon-Ho , Kim Jae-Woong , Kim Dong-Hyun , Park Seong-Hyun
Published: April 2022

In our technology-driven world, various methods for teaching in an educational venue or in a simulated environment have been suggested especially for computer and coding education, among which virtual learning is a widely used teaching approach. In particular, IoT (Internet of Things)-related
education has been made possible owing to the industrial developments that have occurred in various fields since the Fourth Industrial Revolution. Because it is mostly based on hardware and simple operations taught in a two-dimensional (2D) environment, conventional virtual learning of coding
decreases the interest among learners. Therefore, there is a need for a three-dimensional (3D)-based educational approach that can arouse interest in learners. The proposed model allows various IoT systems to be indirectly built; it provides an inexpensive learning method by applying a simulation
system in a 3D environment. The model is implemented on IoT devices, real IoT systems, and an IoT simulator based on the Arduino platform, thereby reducing the cost of building an education system while at the same time arousing the interest of learners with its 3D environment for learning.
Various education-related content can be provided to learners through such an indirectly developed system. A header file type library is created by analyzing the prototype of the GPIO (general-purpose input/output) function suitable for the IoT device to be used in the virtual IoT simulator;
a virtual remote IO module is also implemented. In addition, the physical and electrical characteristics of the peripheral devices to be applied were identified and implemented in a virtual space. Sensors and actuators with various characteristics were implemented to enhance the educational
effect, and a test code was written to check the consistency of an operation between the real system and the virtual system. An experiment conducted to check the update cycle of the actual input and output showed that they differ by more than 5,000 fold on average. This is a physical limitation
resulting from the difference between a method that directly controls an actual electrical signal with a register and a method of transmitting and receiving signals through a communication device. The actual system motion analysis showed no cases in which the automatic guided vehicle (AGV)
deviated from the line and there was a slight difference in the responsiveness when returning to the original position from the deviation.
Development of a Digilog Learning Model for Training on the Principles of Artificial Intelligence Learning in Elementary Education
Authors: Hwang Yuri , Park Namje
Published: April 2022

The importance of nurturing human resources who will lead the 4th Industrial Revolution is increasing, and artificial intelligence is a core factor of innovative technologies. Therefore, developing various and interesting teaching methods for principles of artificial intelligence is
necessary. This article suggests teaching principles of artificial intelligence by convergence of digital and analogue, called digilog. Students get to know how machines can learn and operate, which is digital, with paper worksheets and several physical teaching aids, which are analogue. In
digilog way, students figure out the principles of image recognition. There are two methods, MAX and filtration box. The principles of artificial intelligence are too abstract to understand for elementary learners who are yet at concrete operational period, according to Piaget. Therefore,
the convergence of digital and analogue is effective for teaching and learning about artificial intelligence in elementary education. Elementary learners examine colorful virtual images in their worksheet and use their hands and pencils to trace artificial intelligence’s work. They end
up with figuring out how artificial intelligence compresses inserted images into smaller reference images step by step. With the offered method and developing more diverse digilog elements, elementary learners’ knowledge and experiences necessary for the future society will be increased.
Computer-Vision-Based Advanced Optical Music Recognition System
Authors: Lee Minhoon , Kim Hobin , Moon Mikyeong , Park Seung-Min
Published: April 2022

Computer vision is an artificial intelligence technology that studies techniques for extracting information from images. Several studies have been performed to identify and edit music scores using computer vision. This study proposes a system to identify musical notes and print arranged
music. Music is produced by general rules; consequently, the components of music have specific patterns. There are four approaches in pattern recognition that can be used classify images using patterns. Our proposed method of identifying music sheets is as follows. Several pretreatment processes
(image binary, noise and staff elimination, image resizing) are performed to aid the identification. The components of the music sheet are identified by statistical pattern recognition. Applying an artificial intelligence model (Markov chain) to extracted music data aids in arranging the data.
From applying the pattern recognition technique, a recognition rate of 100% was shown for music sheets of low complexity. The components included in the recognition rate are signs, notes, and beats. However, there was a low recognition rate for some music sheet and can be addressed by adding
a classification to the navigation process. To increase the recognition rate of the music sheet with intermediate complexity, it is necessary to refine the pre-processing process and pattern recognition algorithm. We will also apply neural network-based models to the arrangement process.
Gender in the Markets for Expertise
Authors: de Vaan Mathijs , Stuart Toby
Published: April 2022

Stratification in professional careers arises in part from interpersonal dynamics in client-expert dyads. To reduce perceived uncertainty in judgments of the quality of experts, clients may rely on ascriptive characteristics of experts and on pairwise, relational factors to assess the advice they receive. Two such characteristics, expert gender and client-expert gender concordance, may lead to differences in clients’ trust in expert advice. To explore these issues, we investigate the incidence of patient-initiated second opinions (SOs) in medicine. In an examination of millions of medical claims in Massachusetts, we find that male patients are much more likely than female patients to obtain an SO if the first specialist they consult is female. Moreover, when the first specialist a patient consults is gender non-concordant and the patient seeks an SO, male patients are substantially more likely to switch to a same-gender specialist in the SO visit. Because patients who lack confidence in the advice of the first-seen specialist infrequently return to this specialist for medical services, female specialists generate lower billings. Analyses of medical spending in follow-up visits suggest that gendered patterns in questioning the advice of medical experts have the potential to contribute substantially to the gender pay gap in medicine.
How Safe Is Life on the Road? Criminal Victimization Among a Sample of U.S. Nomads and the #VanLife Community
Authors: Whaley Rachel Bridges , Abbott Jessica
Published: April 2022

The current study provides the first estimates of criminal victimization prevalence among Nomads and members of the VanLife community. People who live and travel in manufactured recreational vehicles, retrofitted vans or buses, and cars are a heterogenous group who face an unknown risk of life on the road. Analyses reveal high victimization prevalence rates. Guided by lifestyle-routine activities theories, regression analyses reveal that gender, Latino ethnicity, income, and education affect risk of rape, aggravated assault, physical threats, property crime, aggravated property crime, and financial identity theft. Disaggregated analyses highlight those demographics that impact victimization risk for year-round Nomads versus part-timers. Questions about the lifestyles-routine activities of Nomads emerge from the analyses and directions for future research are offered.
Prediction of clothing comfort sensation with different activities based on fuzzy comprehensive evaluation of variable weight
Authors: Jiang Rongfan , Wang Yunyi , Li Jian
Published: April 2022

There is no universal model for evaluating the clothing comfort sensation under various conditions due to the different effects of the sensory factors for different activities or environments. The current study aimed to develop a prediction method of the clothing comfort sensation for different activities. Two models were built using fuzzy comprehensive evaluation based on the constant weight (FCE-CW) and variable weight (FCE-VW). Firstly, four sensory factors (wetness, stickiness, hotness, roughness) were selected as input data. Subsequently, grey relation analysis was introduced to obtain the constant weight during the complete experimental process and variable weight for different activities. Finally, the FCE-CW and FCE-VW models were built. A psychological wearing evaluation experiment with different activities was conducted to examine the validity of the model. The results showed that the determination coefficient ( R2) of the FCE-VW model was above 85%, which was superior to that of the FCE-CW model, especially in the running and recovery phases. The high accuracy of the FCE-VW model indicated that grey relation analysis was a practical algorithm for determining the weight of sensory factors. The roughness and hotness sensations demonstrated higher weights during the resting and walking phases, respectively, whereas the wetness and stickiness sensations had a high weight during the running and recovery phases. Moreover, the associations between the physiological parameters and weights of the sensory factors were also explored. In the future, a more comprehensive model based on physiological and psychological parameters can be developed using this method.
Waste-to-energy in a developing country: The state of landfill gas to energy in the Republic of South Africa
Authors: Mbazima Setlamorago Jackson , Masekameni Masilu Daniel , Mmereki Daniel
Published: April 2022

Landfill gas to energy (LFGE) projects were implemented in the Republic of South Africa (RSA) to diversify the energy mix and transition to a green economy. This study provides an overview of the status of LFGE in RSA and identifies major factors that inhibit the adoption and utilization of this technology, using existing data from 2010–2020 from electronic databases, namely, ScienceDirect, Taylor & Francis, Google Scholar, Sage Open, Springer Link, Sabinet, and IEEE Xplore, and using a combination of keywords and Boolean functions. This study revealed that, although RSA has made significant progress in the adoption and utilization of landfill gas (LFG) through the seventeen (17) planned LFGE projects, only six (6) are operational and generate 15 MW of electricity supplied to the local grid in the KwaZulu-Natal, Western Cape, and Gauteng Province. The waste-to-energy (WtE) sources such as LFGE are not given priority, and the country continues to invest in coal-fired power stations, owing to the abundance, availability, and low cost of coal reserves, which will supply coal for the next 200 years. The study identified factors inhibiting LGFE projects in RSA, which included the lack of sanitary landfill sites, LFG monitoring, funding, skills, research, and development. Potential LFGE in RSA is evident, however, except for limited processing facilities, economic investment, and public awareness. Suggestions for further research on the techno-economic and policy assessments are provided in the study. This study contributes to synthesizing evidence of the status of LFGE, insights on state-of-the-art technologies of WtE and the associated challenges in the waste management sector, identifying the potential for LFGE, and LFGE in the circular economy, and building a foundation for future research on WtE such as LFGE. Moreover, it also offers a reference for policymakers, decision-makers, researchers in the waste management sector on the technologies of WtE, LFGE, and potential to reduce waste generated.
Civilization: Historicizing a Concept in the Indian Context
Authors: Mahalakshmi R.
Published: April 2022

The special issue on ‘Indian Civilization: Issues and Perspectives’ seeks to interrogate a concept that has often been loosely used by historians. Generally understood in terms of continuity from very early times, there has also been a tendency to read this concept in religio-cultural terms, with specific reference to the Sanskritic brahmanical traditions, as providing meaning to Indian civilization. The four essays in this issue engage with epistemological and contextual issues that both complicate as well as clarify the concept of civilization, and especially its usage in the Indian context.
An African Response to Karl Barth's Notion of Evil as Nothingness
Authors: Onyenali Rowland
Published: April 2022

In African spiritual exercises, there is so much talk about the menace of demons or evil spirits. These spirits are conceived of as the antithesis of God or as the spiritual opposition to the benign activities of God. Modern African religion sees them as the causes of sicknesses and any form of catastrophe in the lives of people. The paper takes off from Karl Barth's conception of evil and demons as nothingness and argues that when correctly understood, the so-called evil spirits or demons are nothing but the active agents of God in His relationship with humans. Since African cosmology sees the world as a universe of forces held in harmony by God, it seems that the African idea of the deities and spirits as subordinates of God better captures the idea of the evil spirits or demons as nothingness outside the purview of God than the Barthian conception.
Randomized, double-blind clinical trial comparing the healing of stasis ulcers in lower limbs with standard hydrocolloid gel dressings and with dressings with Syzygium cumini extract
Authors: Araújo Gilson Roberto de , Teles Bruna Stéfany Bento de Sousa , Xoteslem Giovana Cardoso , Gratieri Taís , Fortes Renata Costa , Novaes Maria Rita
Published: April 2022

Objective

To evaluate the healing of venous ulcers in the lower limbs (VLU) using dressings with hydrocolloid gel associated with Syzygium cumini extract (SHG) compared to standard hydrocolloid gel dressings (HG).

Method

This prospective, double-blind, randomized trial recruited 90 patients with VLU divided into: dressings with SHG ( n = 44) and dressings with HG ( n = 46). Primary endpoint was healing in the 14th visit. Secondary endpoints were healing rate, complete healing during follow-up, and improvement in the pain scale and in quality of life.

Results

There were no significant between-group differences in healing ( p = 0.15). The wound area made healing difficult ( p = 0.008). Age, body mass index, and wound time demonstrated a tendency to worsen the healing. Positive culture for Pseudomonas aeruginosa resulted in 88% reduction in the healing risk ( p < 0.0001).

Conclusion

There was no difference between the dressings evaluated. The presence of Pseudomonas aeruginosa significantly impaired wound healing.
Planning for FEWsheds: The Role of Planning in Integrating and Strengthening Food, Energy and Water Systems
Authors: Brinkley Catherine , Raj Subhashni , Raja Samina
Published: April 2022

As climate change and increased frequency of extreme weather events threaten local and national Food, Energy and Waters (FEW) systems, policymakers and planners are asked to secure the long-term sustainability of resources and address disaster management where failure in one system has cascading effects. The explicit acknowledgment of interdependencies and equity across FEW systems and scales of governance is an approach we term planning for “FEWsheds.” With this research, we build an integrated framework for understanding FEW supply, equity outcomes, available data, and efforts to make FEW systems more resilient through diversification, distributed systems, or relocalization. The literature review demonstrates common flaws in both research design and policy approaches. For example, few studies explicitly address demographic characteristics. Higher-income households use more water, energy and land; are less responsive to price signaling; and often do not bear the negative externalities of infrastructure siting compared to low-income families, who are, in turn, the most vulnerable to supply disruption and contamination. A FEWshed framework helps make apparent the regional interdependencies, inefficiencies and disparities so that policymakers can take corrective action in fostering just, vibrant and sustainable communities for all constituents.
Experiences of At-Risk Women in Accessing Breastfeeding Social Support During the Covid-19 Pandemic
Authors: Siwik Emila , Larose Samantha , Peres Dalia , Jackson Kimberley T. , Burke Shauna M. , Mantler Tara
Published: April 2022

Background:

With strict public health measures implemented in March 2020 due to the COVID-19 pandemic, many breastfeeding parents, who are within an at-risk population, have experienced limited formal and/or informal breastfeeding social support. In the Canadian context, the experiences of these women is unknown.

Research Aim:

To explore the experiences of at-risk postpartum breastfeeding women in accessing formal and informal breastfeeding social support during the COVID-19 pandemic.

Methods:

This was a prospective, longitudinal interpretive description study using mixed methods. Data were gathered using an online survey and one 52–112-min semi-structured interview at 12-weeks postpartum. At-risk breastfeeding participants were those who lack social support and had at least one of the following: age < 25 years; experiencing or had experienced intimate partner violence; or of low income. We sought participants’ experiences of accessing breastfeeding social support during the first few months of the COVID-19 pandemic/lockdown. Seven participants completed the survey and the interview.

Results:

Participants identified that the COVID-19 pandemic created barriers to accessing formal and informal breastfeeding social support, which stemmed from public health restrictions and difficulties communicating online with families and healthcare providers. Additionally, participants identified that the COVID-19 pandemic/lockdowns facilitated feelings of connectedness, protection, and resiliency.

Conclusion:

We provide preliminary insight into the experiences of trying to access breastfeeding social support during the COVID-19 pandemic. Future researchers should seek to prioritize improved communication and resources in supporting breastfeeding during COVID-19 and future pandemics/lockdowns.
Key Players in Corporate Social Responsibility (CSR) Institutionalization: An Analysis of Multinational Companies’ Interorganizational Positioning via CSR Reports
Authors: Xu Sifan , Woo DaJung
Published: April 2022

Drawing on institutional theory, we position CSR reports as a crucial communication practice that provides evidence of shared norms, values, and relationships among organizations operating within the institutionalized environment. Through Fortune Global 500 companies’ CSR reports published in 2018 and using named entity recognition, we analyzed interorganizational networks to understand the driving forces behind CSR institutionalization. After fitting exponential random graph models (ERGMs) to the network, we found that standards-setting organizations played the most prominent role. In addition, we identified distinct sectoral preferences in companies’ interorganizational positioning in relation to legitimacy-granting organizations such as (inter)governmental agencies and financial organizations. We discuss the implications of the emphasis on standardization, sectoral differences, and network dynamics among various legitimacy-granting organizations on CSR institutionalization and CSR reporting as communicative constitution of institutional legitimacy.
Recruitment Strategies to Engage Newcomer Mothers of African Descent in Maternal Mental Health Research in Canada
Authors: Baiden Deborah , Evans Marilyn
Published: April 2022

Introduction:

Newcomer mothers of African descent are at risk for maternal mental stress because of inadequate social support, newcomer status, and stress of motherhood. Limited participation of newcomer African mothers in mental health research contributes to a knowledge gap in this area further impacting culturally competent health services. This article reports recruitment strategies to better engage African newcomer women in maternal mental health research.

Methods:

In-depth discussion of recruitment strategies, used in a qualitative descriptive study conducted with Black African newcomer mothers in Canada.

Results:

Ten African newcomer mothers were successfully recruited using recruitment strategies such as engagement with religious organizations, snowballing, and the use of social media.

Discussion:

Cultural beliefs on motherhood, resilience, and mental illness may account for hesitancy to engage in maternal mental health research. Recruitment strategies could help overcome the challenges and potentially diversify maternal mental health research in Canada through the engagement of African newcomer mothers.
The Effect of Formal Time Allocations on Learning Trajectories and Performance
Authors: Goh Kenneth T. , Fisher Colin M. , Sommer S. Amy
Published: April 2022

How do formal time allocations in teams affect team learning trajectories and performance? We argue that allocating more time for transition phases induces steeper learning trajectories that engender a positive group atmosphere, which in turn improves team performance by improving coordination quality. We tested our hypotheses in a laboratory experiment in which teams worked on a creative design task over multiple iterations. Using a latent growth modeling approach, we found that teams with shorter action and longer transition phases during prototyping had lower initial performance but steeper learning trajectories, which indirectly led to better final team performance.
Identifying Feasible Heart Failure Interventions Suitable for the Jordan Healthcare system: A Delphi Study
Authors: Alkouri Osama , Hendriks Jeroen M. , Magarey Judy , Schultz Tim
Published: April 2022

Interventions and strategies should align with the context and capacity of the health system. Identifying the most feasible and appropriate heart failure interventions in Jordan will improve heart failure management and clinical outcomes. Therefore, this study aimed to derive consensus from clinicians (using the Delphi method) regarding the most feasible and appropriate heart failure interventions in Jordan. A two-round Delphi study involving seven clinicians and policy makers were conducted. The Delphi results found consensus for the feasibility of the educational materials, follow up phone call, cardiac rehabilitation, group session, and training courses for staff. The components that were not feasible were: multidisciplinary team, individual session, and telemonitoring devices. The present study demonstrates the importance of utilizing interventions tailored to patients’ characteristics and aligned with the capacity of healthcare system.
Unusual Presentations of Mycobacterium Tuberculosis in HIV-Positive Patients: A Case Series
Authors: AbdullGaffar Badr , Abdelkareem Fatema
Published: April 2022

Necrotizing and non-necrotizing epithelioid granulomatous chronic inflammation is the usual recognizable histopathologic presentation of mycobacterial infections. In immunosuppressed patients, atypical histomorphologic patterns may occur. Rare and diagnostically challenging manifestations of nontubercular mycobacterial infections in transplant and Human Immunodeficiency Virus (HIV)-infected patients include mycobacterial spindle cell pseudotumor and suppurative lesions. Lesions composed of nodular spindle cell proliferation mimicking inflammatory, histiocytoid and spindle cell tumors, and similarly suppurative lesions simulating abscesses have been mostly reported in association with nontuberculous mycobacterial infections mainly in nodal and various extranodal sites. Similar lesions related to Mycobacterium tuberculosis that involve serosal membranes are unusual and diagnostically challenging. Our aim is to report mycobacterial spindle cell pseudotumor-associated pericarditis, suppurative abscess-forming pleuritis, and cholesterol pleuritis due to tuberculosis in three HIV-infected young adult males. Initially, we confused the mycobacterial spindle cell pseudotumor for Kaposi sarcoma, the suppurative pleuritis for bacterial and fungal empyema, and the cholesterol pleuritis with rheumatoid arthritis. A prior knowledge of the immune status of our patients helped us confirm our final correct diagnosis of mycobacterial infection by performing Ziehl-Neelsen special stain. Polymerase chain reaction detected Mycobacterium tuberculosis in respiratory samples. Utilization of acid-fast special stains in all HIV-patients regardless of the histopathologic appearances, and the application of an appropriate panel of immunomarkers should help pathologists reach the correct diagnosis and avoid pitfalls. Without prior clinical knowledge, pathologists should raise this possibility in young patients with such unusual manifestations, because correct pathologic recognition is clinically important for the appropriate management of these vulnerable patients.
Risk and Prognostic Factors for Small Bowel Adenocarcinoma: A Multicenter Retrospective Observational Study in China
Authors: Wei Xin , Chen Ke , Li Dong-chang , Li He , Zhu Liang , Wang Zheng-guang
Published: April 2022

Background:

Small bowel adenocarcinoma (SBA) is a rare malignancy that accounts for 3% of all gastrointestinal tumors. We evaluated the clinical characteristics, outcomes, and prognostic factors of primary SBAs.

Methods:

We retrospectively analyzed the clinicopathological features and clinical outcomes of 300 patients with SBA from three institutions in China between January 2003 and July 2020. Overall survival (OS) was analyzed using the Kaplan–Meier method and it was statistically compared using the log-rank test. Single-variable and multivariate analyses were used to identify the significant correlates of OS.

Results:

The primary tumor was on the duodenal papilla in 156 patients (52%), in the duodenum in 60 patients (20%), and in the jejunum–ileum in 84 patients (28%). The median OS of the entire cohort was 32.5 months (range, 0-213 months), with a 1-year OS rate of 78.0%. For jejunoileal adenocarcinoma, advanced age, advanced T stage, advanced N stage, more positive lymph nodes, distant metastasis, high carcinoembryonic antigen (CEA), and lymphocyte-to-monocyte ratio < 2.32 predicted worse survival on single-variable analysis. Multivariate analysis showed that advanced age, advanced tumor node metastases (TNM) stage, high CEA level, high alpha fetoprotein (AFP) level, and low prealbumin level were independent prognostic factors for non-ampullary SBA. The independent prognostic factors for duodenal papilla adenocarcinoma included TNM Stage III, nerve invasion, low platelet/lymphocyte ratio, and high CA19-9.

Conclusion:

We found different independent prognostic factors for tumors at different locations. This finding warrants further investigation to ensure more effective management strategies for SBA.
Improvement in walking impairment following surgical and endovascular revascularization: Insights from VOYAGER PAD
Authors: Hogan Shea E , Nehler Mark R , Anand Sonia , Patel Manesh R , Debus Sebastian , Jackson Matthew T , Buchanan Cullen , King R Wilson , Hess Connie , Muehlhofer Eva , Haskell Lloyd P , Bauersachs Rupert M , Berkowitz Scott D , Hsia Judith , Bonaca Marc P
Published: April 2022

Background:

Peripheral artery disease (PAD) affects 200 million people worldwide and is associated with impaired quality of life, increased morbidity, and mortality. Supervised exercise therapy (SET) and lower-extremity revascularization (LER) are both proven strategies to improve patient symptoms. Short and long-term functional outcomes after LER for symptomatic PAD in a large, international cohort have not previously been described.

Methods:

The VOYAGER PAD trial (ClinicalTrials.gov identifier: NCT02504216) enrolled subjects after LER for symptomatic PAD (Rutherford category 2–6). Participants completed the Walking Impairment Questionnaire (WIQ) at baseline, 1, 3 and 6 months, and every 6 months thereafter. The primary outcome analysis was degree of difficulty walking two blocks at each of the aforementioned time points. Difficulty walking three blocks and climbing one flight of stairs at these time points was also analyzed. Data about supervised and home exercise therapy before or after revascularization were not collected in the VOYAGER PAD trial.

Results:

Of the 5614 VOYAGER PAD participants completing the WIQ at baseline, three-quarters presented with claudication and one-quarter with critical limb ischemia. Of these, the majority (62% with claudication and 74% with CLI) reported inability or much difficulty walking two blocks prior to LER. Walking improved after LER regardless of revascularization strategy, but one-fifth with claudication and one-third with CLI reported continued inability or much difficulty walking two blocks 1 month after LER. Participants who reported improved walking ability 1 month after LER experienced a durable functional result out to 3 years. Although the proportion of participants reporting significant baseline difficulty climbing one flight of stairs or walking three blocks differed, the trend in immediate and sustained improvement after LER was similar to that observed for walking two blocks.

Conclusion:

In this large, international cohort undergoing LER for symptomatic PAD, nearly two-thirds reported inability or much difficulty walking two blocks at baseline. Although many participants reported improved walking ability after LER, a substantial proportion remained severely disabled. These observations may help motivate providers, patients, and medical systems to improve awareness and engagement in SET referral after LER.