bluuebunny/crossref_metadata_2025_split huggingface dataset:
Column-Randomized Linear Programs: Performance Guarantees and Applications
Authors: Akchen Yi-Chun , Mišić Velibor V. 
Published: February 2024

Solving Large-Scale Linear Programs by Randomly Sampling Columns Large-scale linear programs (LPs) play a pivotal role in various applications, including the classic cutting-stock problem and the vehicle routing problem. The standard solution approach for these LPs, namely, column generation (CG), is often computationally intractable because of the NP-hard nature of the corresponding subproblem in many applications. In “Column-Randomized Linear Programs: Performance Guarantees and Applications,” Akchen and Mišić introduce a randomized method that involves first sampling a set of columns from the original LP and subsequently solving an LP composed of the sampled columns, termed the column-randomized LP. The authors analyze the optimality gap of the column-randomized LPs and establish conditions under which the gap is small. Empirical findings demonstrate the effectiveness of the column-randomized LP approach, showcasing its advantages over the CG approach in two practical applications: the cutting-stock problem and nonparametric choice model estimation.
A New Simheuristic Approach for Stochastic Runway Scheduling
Authors: Shone Rob , Glazebrook Kevin , Zografos Konstantinos G. 
Published: February 2024

We consider a stochastic, dynamic runway scheduling problem involving aircraft landings on a single runway. Sequencing decisions are made with knowledge of the estimated arrival times (ETAs) of all aircraft due to arrive at the airport, and these ETAs vary according to continuous-time stochastic processes. Time separations between consecutive runway landings are modeled via sequence-dependent Erlang distributions and are affected by weather conditions, which also evolve continuously over time. The resulting multistage optimization problem is intractable using exact methods, and we propose a novel simheuristic approach based on the application of methods analogous to variable neighborhood search in a high-dimensional stochastic environment. Our model is calibrated using flight tracking data for over 98,000 arrivals at Heathrow Airport. Results from numerical experiments indicate that our proposed simheuristic algorithm outperforms an alternative based on deterministic forecasts under a wide range of parameter values, with the largest benefits seen when the underlying stochastic processes become more volatile and also when the on-time requirements of individual flights are given greater weight in the objective function.Funding: This work was supported by the Engineering and Physical Sciences Research Council [Grant EP/M020258/1].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/trsc.2022.0400 .
A Historiographic Review of the Research on Undecided Students
Authors: Spight David B. , Mooney Deirdre , Orr Rachael 
Published: February 2024

Abstract
Advising programs for undecided/exploratory students risk reinvention of the wheel through lack of familiarity with existing literature. This lack can also leave the scholar and the practitioner unable to identify potential gaps within the research. Applying the methodological approach of qualitative historiography to literature from 1950 to 2022, our findings clarify the need for a nuanced and clear understanding of undecided/exploratory students. Observed throughout the literature is an awareness that exploration and decision-making skills are valuable to all students. Additionally, cultural context—examining the various models, programs, and interventions through a lens of equity and inclusion—and a more global perspective are critical for future research.
The role of medical-grade maggots in facilitating healing of diabetic foot ulcers in Kano, northern Nigeria: a case series
Authors: Yusuf Mustapha Ahmed , Ibrahim Bashir Mohammed , Abubakar Firdausi , Ibrahim Mustapha , Sheshe Abdulrahman Abba , Abubakar Mohammed Kabir , Aji Sani A , Gbadamasi Kamaldeen A , Busayo Jatto Kabir , Sallau Suleiman Bala , Ridwan Bakare Ajibola , Uloko Andrew E , Gezawa Ibrahim D , Ramalan Mansur , Sidi Kamal , Abdullahi Sani , Adamu Kabir Musa , Bello Nafisatu , Muhammad Abdullahi , Mukhtar Rabiu , Aina Deji 
Published: February 2024

Objective: Approximately 13% of people living with diabetes develop one or more ulcers during the course of the disease, and diabetic foot ulcer (DFU) is responsible for >60% of lower limb amputations worldwide. This case series aimed to demonstrate the effectiveness of medical-grade maggots on DFUs in promoting wound healing and reducing related hospital stays in northern Nigeria. Method: Maggot debridement therapy (MDT) was applied to the DFUs of patients who consented to this treatment between January–August 2021 at the Orthopaedic Unit of the Aminu Kano Teaching Hospital (AKTH), Kano, Nigeria. Sterile first instar larvae of Lucilia sericata were obtained indigenously and applied using the confinement (free-range) method under aseptic procedure. Results: A total of 15 patients with DFUs of Wagner classification grades III (33.3%) and IV (66.7%), were seen and documented. The patients included 10 (66.7%) females and five (33.3%) males, giving a female:male ratio of 2:1. The mean age (±standard deviation) of the respondents was 51.6±10.8 years. The surface area of the wounds ranged from 24–140cm2, with a median value of 75cm2. Among the patients, 60% had two cycles of MDT, with a median duration of five days. Most of the wounds (53.3%) were debrided within five days; 13.3% (two wounds) took seven days to be fully debrided. A paired sample t-test showed a statistically significant association between wound surface area and therapy duration (t=8.0; p=0.000) and between wound surface area and cycles of therapy (t=8.3; p=0.000). Before maggot application, 14 (93.3%) DFUs were completely (100%) covered with slough and only one (6.7%) was 95% covered with slough. After maggot application, 10 (66.7%) wounds were completely debrided while five (33.3%) wounds required bedside surgical debridement to achieve complete debridement. A paired sample t-test showed statistically significant difference between the pre- and post-MDT slough covering the wounds (t=45.1; p=0.000). Conclusion: In this case series, MDT was successfully used in the debridement of DFUs, which facilitated the healing process with an encouraging clinical outcome.
Predicting and identifying factors associated with undernutrition among children under five years in Ghana using machine learning algorithms
Authors: Anku Eric Komla , Duah Henry Ofori 
Published: February 2024

Background
Undernutrition among children under the age of five is a major public health concern, especially in developing countries. This study aimed to use machine learning (ML) algorithms to predict undernutrition and identify its associated factors.

Methods
Secondary data analysis of the 2017 Multiple Indicator Cluster Survey (MICS) was performed using R and Python. The main outcomes of interest were undernutrition (stunting: height-for-age (HAZ) < -2 SD; wasting: weight-for-height (WHZ) < -2 SD; and underweight: weight-for-age (WAZ) < -2 SD). Seven ML algorithms were trained and tested: linear discriminant analysis (LDA), logistic model, support vector machine (SVM), random forest (RF), least absolute shrinkage and selection operator (LASSO), ridge regression, and extreme gradient boosting (XGBoost). The ML models were evaluated using the accuracy, confusion matrix, and area under the curve (AUC) receiver operating characteristics (ROC).

Results
In total, 8564 children were included in the final analysis. The average age of the children was 926 days, and the majority were females. The weighted prevalence rates of stunting, wasting, and underweight were 17%, 7%, and 12%, respectively. The accuracies of all the ML models for wasting were (LDA: 84%; Logistic: 95%; SVM: 92%; RF: 94%; LASSO: 96%; Ridge: 84%, XGBoost: 98%), stunting (LDA: 86%; Logistic: 86%; SVM: 98%; RF: 88%; LASSO: 86%; Ridge: 86%, XGBoost: 98%), and for underweight were (LDA: 90%; Logistic: 92%; SVM: 98%; RF: 89%; LASSO: 92%; Ridge: 88%, XGBoost: 98%). The AUC values of the wasting models were (LDA: 99%; Logistic: 100%; SVM: 72%; RF: 94%; LASSO: 99%; Ridge: 59%, XGBoost: 100%), for stunting were (LDA: 89%; Logistic: 90%; SVM: 100%; RF: 92%; LASSO: 90%; Ridge: 89%, XGBoost: 100%), and for underweight were (LDA: 95%; Logistic: 96%; SVM: 100%; RF: 94%; LASSO: 96%; Ridge: 82%, XGBoost: 82%). Age, weight, length/height, sex, region of residence and ethnicity were important predictors of wasting, stunting and underweight.

Conclusion
The XGBoost model was the best model for predicting wasting, stunting, and underweight. The findings showed that different ML algorithms could be useful for predicting undernutrition and identifying important predictors for targeted interventions among children under five years in Ghana.
Perceptions of diabetes risk and prevention in Nairobi, Kenya: A qualitative and theory of change development study
Authors: Manyara Anthony Muchai , Mwaniki Elizabeth , Gill Jason M. R. , Gray Cindy M. 
Published: February 2024

Background
Type 2 diabetes is increasing in Kenya, especially in urban settings, and prevention interventions based on local evidence and context are urgently needed. Therefore, this study aimed to explore diabetes risk and co-create a diabetes prevention theory of change in two socioeconomically distinct communities to inform future diabetes prevention interventions.

Methods
In-depth interviews were conducted with middle-aged residents in two communities in Nairobi (one low-income (n = 15), one middle-income (n = 14)), and thematically analysed. The theory of change for diabetes prevention was informed by analysis of the in-depth interviews and the Behaviour Change Wheel framework, and reviewed by a sub-set (n = 13) of interviewees.

Results
The key factors that influenced diabetes preventive practices in both communities included knowledge and skills for diabetes prevention, understanding of the benefits/consequences of (un)healthy lifestyle, social influences (e.g., upbringing, societal perceptions), and environmental contexts (e.g., access to (un)healthy foods and physical activity facilities). The proposed strategies for diabetes prevention included: increasing knowledge and understanding about diabetes risk and preventive measures particularly in the low-income community; supporting lifestyle modification (e.g., upskilling, goal setting, action planning) in both communities; identifying people at high risk of diabetes through screening in both communities; and creating social and physical environments for lifestyle modification (e.g., positive social influences on healthy living, access to healthy foods and physical activity infrastructure) particularly in the low-income community. Residents from both communities agreed that the strategies were broadly feasible for diabetes prevention but proposed the addition of door-to-door campaigns and community theatre for health education. However, residents from the low-income community were concerned about the lack of government prioritisation for implementing population-level interventions, e.g., improving access to healthy foods and physical activity facilities/infrastructure.

Conclusion
Diabetes prevention initiatives in Kenya should involve multicomponent interventions for lifestyle modification including increasing education and upskilling at individual level; promoting social and physical environments that support healthy living at population level; and are particularly needed in low-income communities.
Physical activity and cognitive function in adults born very preterm or with very low birth weight–an individual participant data meta-analysis
Authors: Aakvik Kristina Anna Djupvik , Benum Silje Dahl , Tikanmäki Marjaana , Hovi Petteri , Räikkönen Katri , Harris Sarah L. , Woodward Lianne J. , Darlow Brian A. , Indredavik Marit S. , Lydersen Stian , Mork Paul Jarle , Kajantie Eero , Evensen Kari Anne I. 
Published: February 2024

Objective
Individuals born very preterm (<32 weeks of gestation) or with very low birthweight (<1500g) have lower cognitive function compared with term-born peers. Furthermore, some studies suggest that they are less physically active as young adults than controls, but the relationship between physical activity and cognitive function remains unclear. We performed an individual participant data meta-analysis to examine whether being born preterm/with very low birth weight is associated with physical activity in adulthood and examined if cognitive function mediates this association.

Study design
Cohorts with data on physical activity and cognitive function in adults born very preterm/very low birth weight and term-born controls were recruited from the Research on European Children and Adults Born Preterm, and the Adults Born Preterm International Collaboration Consortia. A systematic literature search was performed in PubMed and Embase.

Results
Five cohorts with 1644 participants aged 22–28 years (595 very preterm/very low birth weight and 1049 controls) were included. Adults born very preterm/very low birth weight reported 1.11 (95% CI: 0.68 to 1.54) hours less moderate to vigorous physical activity per week than controls, adjusted for cohort, age and sex. The difference between individuals born very preterm/very low birth weight and controls was larger among women than among men. Neither intelligence quotient nor self-reported executive function mediated the association between very preterm/very low birth weight and moderate to vigorous physical activity. Results were essentially the same when we excluded individuals with neurosensory impairments.

Conclusion
Adults born very preterm/very low birth weight, especially women, reported less moderate to vigorous physical activity than their term-born peers. Cognitive function did not mediate this association. Considering the risk of adverse health outcomes among individuals born preterm, physical activity could be a target for intervention.
Modelling effects of nutrients and hypoxia on Lake Erie's central basin foodweb
Authors: Zhang Hongyan , Mason Doran M. , Rutherford Edward S. , Koops Marten A. , Johnson Timothy B. , Gorman Ann Marie , Rowe Mark , Zhu Xinhua , Hossain Monir , Cook H. Andrew 
Published: February 2024

Abstract
Hypoxia (dissolved oxygen &lt;2 mg l-1) has long been a prevalent feature of the central basin of Lake Erie. Studies of the sublethal impacts of hypoxia on fishes have focused on individual species feeding rates, behavior and spatial distributions over short time periods, but the long-term effects on the fish community and its foodweb are poorly known. Sublethal effects of hypoxia on fish include: interrupting their vertical migration, displacing them from bottom habitats either up into the water column or away from the hypoxic zones, altering predator-prey relationships by segregation or aggregation of predators and their prey, and increasing fishing mortality by concentrating fish at the edge of hypoxic zones. We used the Ecopath with Ecosim foodweb model to investigate the singular and combined effects of nutrient concentration and hypoxia on the foodweb structure in Lake Erie's central basin. Our model tracked predator-prey interactions and population biomass of 33 model groups. We balanced the model in Ecopath and calibrated it against biomass time series data from 1996 up to 2020. Model simulations were run with varied nutrients (from 20 to 220% of the previous nutrient loading target level) and hypoxia (none, average summer value from 1996 to 2017, historical high) as forcing variables on the foodweb. Model results suggested that nutrients had positive, non-linear effects on foodweb biomass, while hypoxia decreased biomass of benthos, benthivorous fishes, and some omnivores, but increased biomass of plankton and planktivorous fishes. Nutrient effects were greater than hypoxia effects on the foodweb. Results of the foodweb model analysis may inform water quality and fisheries management strategies for Lake Erie's central basin.
Modelling the current status of Lake Malawi fish stocks, an inland lake in East Africa
Authors: Weyl O. L. , M'balaka M. S. , Sharma R. , Cope J , Kafumbata D. 
Published: February 2024

Abstract
Inland rift valley lake systems have been sustaining humanity for a long time. Only recently have commercial fisheries entered these systems and for Lake Malawi, this occurred in the mid-1970s upon successful experimental trawl fishing. Lake Malawi with the highest diversity of freshwater fishes in the world has had fisheries for centuries. Previous assessment of the impact of commercial trawl fisheries revealed significant changes in stock composition and overall biomass. The study evaluates the state of fisheries resources using novel techniques developed using integrated assessment methods amenable to data poor fisheries. Data from biomass assessment surveys and landed catch from 2016 to 2019 were examined to determine the status of selected fish stocks over time. Stock Synthesis for Data Limited tools in R environment were used to run the models. The Surplus Production Models and Statistical catch-at-age models that were used to examine alternative hypotheses on life history parameters on the key stocks exploited primarily by the commercial trawl fishery and evaluate long-term trends on these populations. The study results revealed that Mcheni (Rhamphochromis spp.), Ndunduma (Diplotaxodon limnothrissa) and Utaka (Copadichromis virginalis) stocks are within the sustainable limits, while Chambo (Oreochromis karongae), Chisawasawa (Lethrinops gossei), Mlamba (Bathyclarias nyasensis) and Kampango (Bagrus meridionalis) appear to be overfished in recent years, though Kampango may have recovered recently. Given, the large uncertainties with productivity of most tropical fishes with climate change, as well as large uncertainties due to inaccurate and untimely data submissions, it is recommended that a systematic monitoring and evaluation program, like the one being conducted in Lake Malawi should be developed for other inland lake systems. If stocks are facing overfishing by both the small-scale and commercial trawl fisheries, limits to overall catch and size should be implemented possibly through output controls such that the fisheries remain sustainable for the long term.
Dynamic modelling of coastal aquaculture systems: A Review
Authors: Muralidhar M. , Kumar J. Ashok , Suvana S. , Jayanthi M. , Vishwajeet P. , Dayal J. Syama 
Published: February 2024

AbstractCoastal aquaculture is an important economic activity in India dominated majorly by shrimp culture, which involves a range of interconnected processes that are challenging to analyse and optimise without a systematic approach. System dynamics modelling is a useful tool for understanding and predicting the behavior of complex coastal aquaculture systems. Here, we review the status of dynamic simulation modelling works undertaken in aquaculture, which can provide directives for various researchers working on developing simulation models for shrimp aquaculture. There is a need to assess the impact of dynamic forces on the animals during the culture period which could be addressed through these models. System dynamic models assist decision-makers to augment potential measures for aquaculture-related problems under different possible scenarios. System dynamic models developed in aquaculture were related to feeding, water quality parameters, nitrogen dynamics, growth, etc. The strengths and limitations of software packages used in developing the simulation models are discussed. Considering the economic potential of shrimp aquaculture, it is important to develop an integrated dynamic model for predicting all the sub-processes of shrimp aquaculture.
Strategic plan to restore a shallow overgrowing macrophyte lake
Authors: Maileht Kairi , Nõges Tiina , Laarmaa Ronald , Lehtpuu Maili , Sepp Margot , Luigujõe Leho , Saar Katrin , Krause Teet , Metsur Madis , Raadla Kalev , Võhandu Kaarel , Zingel Priit , Nõges Peeter , Ott Ingmar 
Published: February 2024

Abstract
As a result of natural and anthropogenic eutrophication, shallow lakes ultimately become wetlands. Several aquatic ecosystem values diminish, but some biotic communities may benefit. Lake Lahepera is a very shallow lake filled with sediments and overgrown with macrophytes. It is a former bay and an important spawning ground for fishes of Lake Peipsi, the fourth largest lake in Europe. The main question is, how to reconcile the goals of nature conservation and circular economy – restore and maintain good functioning of the lake ecosystem, preserve habitats for wetland communities, make economic use of sapropel, and renew spawning conditions for fish. The lake has been investigated since the 1950s. Resulting from strong human pressure, especially in the 1970s and 1980s, the accumulated organic sediments and macrophyte overgrowth have diminished the habitat diversity of the lake. Irregular flushing of the lake with Lake Peipsi waters can wash away large amounts of phosphorus. According to the investigations in 2014-15, phosphorus in- and outflow are in balance, but the internal loading is high. A set of possible restoration options with sediment and macrophyte removal methods is proposed and their outcome assessed using the ecosystem service concept. A comparison of possible future scenarios, based ecosystem service values shows that with a balanced combination of different habitat restoration methods it is possible to achieve stable ecological status of the lake. Species diversity, especially that of floating leaved macrophytes, will increase in the lake. At the same time, wetland habitats will retain their values.