bluuebunny/crossref_metadata_2025_split huggingface dataset:
Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions
Authors: Wang Wenjia , Wang Yanyuan , Zhang Xiaowei 
Published: March 2024

Nested simulation concerns estimating functionals of a conditional expectation via simulation. In this paper, we propose a new method based on kernel ridge regression to exploit the smoothness of the conditional expectation as a function of the multidimensional conditioning variable. Asymptotic analysis shows that the proposed method can effectively alleviate the curse of dimensionality on the convergence rate as the simulation budget increases, provided that the conditional expectation is sufficiently smooth. The smoothness bridges the gap between the cubic root convergence rate (that is, the optimal rate for the standard nested simulation) and the square root convergence rate (that is, the canonical rate for the standard Monte Carlo simulation). We demonstrate the performance of the proposed method via numerical examples from portfolio risk management and input uncertainty quantification. This paper was accepted by Baris Ata, stochastic models and simulation. Funding: The authors acknowledge financial support from the National Natural Science Foundation of China [Grant NSFC 12101149] and the Hong Kong Research Grants Council [Grants GRF 17201520 and GRF 17206821]. Supplemental Material: The e-companion and data files are available at https://doi.org/10.1287/mnsc.2022.00204 .
Optimal Impact Portfolios with General Dependence and Marginals
Authors: Lo Andrew W. , Wu Lan , Zhang Ruixun , Zhao Chaoyi 
Published: March 2024

Using Induced Order Statistics to Construct Optimal Impact Portfolios with General Dependence and Marginals We develop a mathematical framework for constructing optimal impact portfolios and quantifying their financial performance by characterizing the returns of impact-ranked assets using induced order statistics and copulas. Our results apply to any joint distribution of impact factors and residual returns, making them broadly applicable to a wide range of contexts. We develop significant extensions of the theory of induced order statistics, with which we are able to characterize the distribution of residual returns of individual assets ranked by the impact factor. Our framework provides a toolkit for practitioners to construct impact portfolios and quantify their performance based on real data. This allows impact investors to achieve higher risk-adjusted returns than those with impact portfolios constructed using simpler heuristics such as negative or positive screening.
Alkaline Hydrolysis of Poultry Carcasses and Health Risk Assessment of Exposure to Target Volatile Organic Compounds
Authors: Sun Zhihui , Akdeniz Neslihan , Banik Chumki , Koziel Jacek A. 
Published: March 2024

HighlightsHydroxide solutions (1 M, 2 M, 4 M) were used for chicken carcass hydrolysis.pH of hydrolysates remained above 13.1 for the entire 10 weeks.Headspace samples had characteristic fish odor due to trimethylamine.Over 17% of the workers exposed to gases for 3 hours daily risk developing serious health risks.Abstract. Animal carcass management is an essential part of a livestock production system. Alkaline hydrolysis is a relatively new disposal method used to digest and break down animal tissues. Despite the effectiveness of inactivating pathogens, alkaline hydrolysis has not been widely accepted as a disposal method because of its high capital and operating costs when done at high temperatures and pressure. The objectives of this research were (1) to test if alkaline solutions at ambient temperature and pressure can be used to hydrolyze poultry carcasses; (2) to quantify target VOCs emitted from carcasses, and (3) to neutralize and aerobically treat hydrolysates to prepare liquid fertilizer. 1 molar (M), 2 M, and 4 M potassium hydroxide solutions were used to hydrolyze chicken carcasses, and the headspace was sampled to quantify target VOCs. The pH of the hydrolysates stayed above 13.1 during the study, which was considered sufficient for eliminating pathogens of concern. Concentrations of target VOCs fluctuated over 10 weeks, and concentrations of trimethylamine (TMA), acetic acid, and propionic acid exceeded their recommended inhalation exposure limits. It was found that more than 17% of the workers exposed to the process headspace gases for 3 h a day would be at a high risk of developing serious chronic health problems. Although the results of this study indicated that chicken carcasses can be hydrolyzed under ambient conditions, they raised concerns about the health risks associated with inhalation exposure to the gases produced during the process. Future studies are needed to adjust daily exposure times depending on the ventilation rates of full-scale alkaline hydrolysis sites. Keywords: Alkaline hydrolysis, Cancer risk, Carcass, Livestock, Solid-phase microextraction.
Exploring Resistance Reduction of Subsoiling Through Sandfish (Scincus scincus) Inspired Sinusoidal Locomotion
Authors: Wei Zhiming , Gan Shuaihui , Zhang Zhihong , Sun Yitian , Li Qinglong , Sun Yongjia , Li Rui 
Published: March 2024

HighlightsBiomimetic design, inspired by sandfish locomotion, decreased subsoiling resistance.Penetration tests and simulations showed bioinspired tines outperforming traditional ones in resistance reduction.DEM-MBD co-simulation effectively modeled the sandfish's movement, revealing the mechanisms of soil interactions.Simulations confirmed that sinusoidal subsoiler movement significantly reduced soil resistance.Abstract. This study addresses the issue of high resistance and low efficiency in subsoiling operations by employing a novel method inspired by the unique locomotion of the sandfish (scincus scincus), aimed at reducing forward resistance. The unparalleled adaptability of the sandfish in navigating granular media, such as desert sand, offers valuable insights for enhancing agricultural machinery. This research employs sandfish’s movement principles to propose innovative strategies for improving subsoiling efficiency. A sandfish inspired prototype, created through reverse engineering, served as the basis for the analysis. The models of both traditional (T-S) and bioinspired (B-S) subsoiler tines for comparative assessment were developed. The EDEM simulation model’s performance was calibrated using soil penetration tests and integrated with multibody dynamics (MBD) to analyze the sandfish’s variable locomotion in sandy soil. The impact of linear and sinusoidal locomotion at velocities of 0.8 m/s, 1.0 m/s, and 1.2 m/s on resistance and soil disturbance were investigated and contrasted. The congruence between measured and simulated resistance-depth curves for T-S and B-S models was desirable, with maximum resistance errors of 2.54% and 2.47%, respectively, confirming the simulation model’s accuracy in predicting mechanical interactions. A comparison of characteristic angles validated the close correlation between simulated and actual sandfish locomotion in soil. Stress analysis during soil locomotion of the sandfish head indicated a 25.1% reduction in resistance with sinusoidal motion compared to linear motion. At the specified velocities, sinusoidal locomotion of the subsoiler tine showed resistance reductions of 6.75%, 7.39%, and 9.40%, respectively, relative to linear locomotion. The mechanism of resistance reduction in sinusoidal locomotion was further verified through soil compression force analysis, supporting the adoption of sandfish-inspired sinusoidal behavior as an innovative approach to enhance efficiency in agricultural practices. Keywords: Bioinspired design, DEM-MBD simulation, Sandfish (Scincus scincus), Sinusoidal locomotion, Subsoiling.
Sorption Kinetics and Equilibrium Isotherms of Phosphine Gas into Wheat Kernels
Authors: Buenavista Rania Marie , Casada Mark E. , Phillips Thomas W. , Siliveru Kaliramesh 
Published: March 2024

HighlightsThe pseudo-first order kinetic model fits well with the experimental data of sorbed phosphine versus time.Sorption isotherm curves were developed using Langmuir, Freundlich, and Redlich-Peterson models.Phosphine adsorption capacity of wheat kernels increased with increase in applied concentration (400-2400 ppm).Abstract. Phosphine (PH3) is the most used fumigant in the U.S. due to its low price, ease of use, and wide accessibility. With the growing concerns of phosphine-resistant insect pests, the sustainability of PH3 as an effective fumigant has been put at risk. Sorption equilibrium data is critical for improving the accuracy of modeling studies for phosphine-wheat fumigation systems and would clarify the PH3 uptake and sorption capacity of wheat. The objectives of this study were to determine the effect of initial concentration (from 400 to 2400 ppm) on the equilibrium concentration for PH3 in wheat kernels and on cumulative and daily PH3 sorption through time. Kinetic data showed the sorption process was time-dependent and occurred in two phases: an initial faster adsorption phase, followed by a phase with a slower sorption rate as the grain and PH3 reached equilibrium. Pseudo-first and pseudo-second order models were fit to PH3 concentrations versus time experimental data. The pseudo-first order model provided better equilibrium estimates and was used for the sorption isotherm analysis. Langmuir, Freundlich, and Redlich-Peterson sorption isotherm models were fit to the plot of equilibrium headspace gas concentration versus sorbed PH3 quantity. All three models had low standard errors of prediction (0.46-0.47). These PH3 sorption kinetics and values of total sorbed quantity at equilibrium are valuable for modeling the rate and maximum quantity of PH3 uptake in wheat. Keywords: Fumigation, Kinetics, Phosphine, Sorption Isotherm, Wheat.
Indoor visible light communication denoising system combining iterative variational mode decomposition and multiple frequency shift keying modulation
Authors: Yang Chunyong , Hu Xin , Ni Wenjun , Shum Perry Ping 
Published: March 2024

To reduce noise in indoor visible light communication (IVLC), the Pearson correlation coefficient difference (PCCD), a denoising system combining iterative variational mode decomposition (IVMD) and multiple frequency shift keying modulation (MFSK), is proposed. Compared with VMD, the method can directly determine the optimal number of VMD modes and solve the issue of VMD penalty factor selection to some extent. The simulation results show that, when the input SNRs vary from −15 to −8dB, the proposed method can improve the output SNRs of the 2FSK signal by an average of 15.5 dB and reduce the BER by 55.8%, improve the output SNR of the 4FSK signal by an average of 13 dB, and reduce the BER by 54.4%. The proposed method can also effectively suppress noise interference in real IVLC experiments at a distance of 1 m. In addition, the IVMD-MFSK denoising system can be applied to denoise all frequency-modulated signals with high applicability.
FPM-WSI: Fourier ptychographic whole slide imaging via feature-domain backdiffraction
Authors: Zhang Shuhe , Wang Aiye , Xu Jinghao , Feng Tianci , Zhou Jinhua , Pan An 
Published: March 2024

Fourier ptychographic microscopy (FPM) theoretically provides a
solution to the trade-off between spatial resolution and field of view
(FOV), and has promising prospects in digital pathology. However,
block reconstruction and then stitching has become an unavoidable
procedure for reconstruction of large FOV due to vignetting artifacts.
This introduces digital stitching artifacts, as the existing
image-domain optimization algorithms are highly sensitive to
systematic errors. Such obstacles significantly impede the advancement
and practical implementation of FPM, explaining why, despite a decade
of development, FPM has not gained widespread recognition in the field
of biomedicine. We report a feature-domain FPM (FD-FPM) based on the
structure-aware forward model to realize stitching-free, full-FOV
reconstruction. The loss function is uniquely formulated in the
feature domain of images, which bypasses the troublesome vignetting
effect and algorithmic vulnerability via feature-domain
backdiffraction. Through massive simulations and experiments, we show
that FD-FPM effectively eliminates vignetting artifacts for full-FOV
reconstruction, and still achieves impressive reconstructions despite
the presence of various systematic errors. We also found it has great
potential in recovering the data with a lower spectrum overlapping
rate, and in realizing digital refocusing without a prior defocus
distance. With FD-FPM, we achieved full-color and high-throughput
imaging (4.7 mm diameter FOV, 336 nm resolution in the blue channel)
free of blocking-and-stitching procedures on a self-developed Fourier
ptychographic microscopy whole slide imaging platform. The reported
FD-FPM shows the value of FPM for various experimental circumstances,
and offers physical insights useful for the developments of models for
other computational imaging techniques. The reported platform
demonstrates high-quality, high-speed imaging and low cost, and could
find applications in many fields of biomedical research, as well as in
clinical applications.
Multi-level factors associated with utilization of water, sanitation and hygiene services by mothers in Nepal
Authors: Dhital Shalik Ram , Chojenta Catherine , Loxton Deborah 
Published: March 2024

Background
Providing improved water, sanitation, and hygiene (WASH) at a household level remains one of the major public health challenges in Nepal. Household mothers are likely to have limited access to combined WASH services, this is influenced by individual, and community factors. Individual components of an improved water source, sanitary toilet, fixed place for handwashing, and availability of soap and water were merged into one and called combined WASH. This paper aimed to identify the individual and community factors associated with combined WASH facilities and practices among mothers with children under five years in Nepal.

Methods
A cross-sectional study was conducted using data from the Nepal Demographic and Health Survey (NDHS), 2016. The weighted sample size of this study was 4887 mothers with children under five years. The independent variables within the mothers included age, education, occupation, and caste/ethnicity in addition to education of the husband, wealth index, exposure to the newspaper, radio and television, residence, ecological zones, provinces, distance and participation in health mother groups were analyzed with the outcome variable of combined WASH. A multi-level mixed effects logistic regression model was used to assess the relationship of explanatory variables with WASH.

Results
At an individual level, a rich wealth index was positively associated with combined WASH (AOR = 6.29; 95%CI: 4.63–8.54). Higher education levels and exposure to television had higher odds of having combined WASH. At the community level, the hill zone, urban residence, and Sudurpashim Provinces were positively associated with combined WASH while Madesh and Karnali Provinces and distance to water source greater than 31 minutes were associated with lower access to combined WASH.

Conclusion
Educated and rich household have positive association with combined WASH. It is recommended that both the health and other sectors may be instrumental in improving the combined WASH service for mothers at households.
Long-term results of transferring the patient from therapy with glucagon-like peptide-1 receptor agonists in combination with metformin to a dipeptidyl peptidase-4 inhibitor in combination with pioglitazone and inhibitor of type 2 sodium-glucose cotransporter in type 2 diabetes
Authors: Salukhov V. V. , Shipilova D. A. , Minakov A. A. 
Published: March 2024

The pioglitazone belongs to the class of antidiabetic medications and has various pleiotropic effects. The evidence base for this medication, based on the results of randomized clinical trials, demonstrates convincing cardio- and cerebroprotective efficacy of pioglitazone, comparable to innovative glucose-lowering drugs from the classes of GLP-1 agonists and SGLT-2 inhibitors. Currently, in Russia, a fixed combination of pioglitazone and alogliptin is available. However, it should be noted that there has been a recent lack of GLP-1 agonists on the domestic pharmaceutical market, which raises questions about the choice of further tactics for patients who have been taking them until recently.This clinical case presents an example of the transformation of glucose-lowering therapy from a combined treatment regimen with semaglutide and metformin to the combined use of a fixed combination of alogliptin and pioglitazone with empagliflozin. Against the background of therapy change, a stable and pronounced glucose-lowering effect was obtained and confirmed after six months, comparable to GLP-1 receptor agonists without the effect of escape and hypoglycemia. No edema or weight gain was observed, and no other adverse events were detected, which allowed continuing the chosen glucose-lowering therapy. Strategic perspectives of the prescribed therapy were determined — reducing cardio- and cerebrovascular risk and improving the patient’s prognosis.
Clinical prediction model for MODY type diabetes mellitus in children
Authors: Laptev D. N. , Sechko E. A. , Romanenkova E. M. , Eremina I. A. , Bezlepkina O. B. , Peterkova V. A. , Mokrysheva N. G. 
Published: March 2024

BACKGROUND: MODY (maturity-onset diabetes of the young) is a rare monogenic form of diabetes mellitus, the gold standard of diagnosis is mutations detection in the genes responsible for the development of this form diabetes. Genetic test is expensive and takes a lot of time. The diagnostic criteria for MODY are well known. The development of clinical decision support system (CDSS) which allows physicians based on clinical data to determine who should have molecular genetic testing is relevant.AIM: Provided a retrospective analysis of clinical data of the patients with T1DM and MODY, from 0 to 18 years old, regardless of the duration of the disease to develop the model. Based on clinical data, a feedforward neural network (NN) was implemented - a multilayer perceptron.MATERIALS AND METHODS: Development of the most effective algorithm for predicting MODY in children based on available clinical indicators of 1710 patients with diabetes under the age of 18 years using a multilayer feedforward neural network.RESULTS: The sample consisted of 1710 children under the age of 18 years with T1DM (78%) and MODY (22%) diabetes. For the final configuration of NS the following predictors were selected: gender, age at passport age, age at the diagnosis with DM, HbA1c, BMI SDS, family history of DM, treatment. The performance (quality) assessment of the NN was carried out on a test sample (the area under the ROC (receiver operating characteristics) curve reached 0.97). The positive predictive value of PCPR was achieved at a cut-off value of 0.40 (predicted probability of MODY diabetes 40%). At which the sensitivity was 98%, specificity 93%, PCR with prevalence correction was 78%, and PCR with prevalence correction was 99%, the overall accuracy of the model was 94%.Based on the NN model, a CDSS was developed to determine whether a patient has MODY diabetes, implemented as an application.CONCLUSION: The clinical prediction model MODY developed in this work based on the NN, uses the clinical characteristic available for each patient to determine the probability of the patient having MODY. The use of the developed model in clinical practice will assist in the selection of patients for diagnostic genetic testing for MODY, which will allow for the efficient allocation of healthcare resources, the selection of personalized treatment and patient monitoring.
Hypoglycemic episodes among type 1 diabetic patients in Unaizah, Saudi Arabia: causes, management, and associated factors
Authors: Aldekheel S.K.S. , Shahin M.A.S. 
Published: March 2024

BACKGROUND: Diabetes mellitus is a prevalent condition in Saudi Arabia, with approximately 20% of the adult population affected, ranking sixth highest in the world. This disease is associated with both acute and chronic complications. Among these complications, hypoglycemia is particularly dangerous and can occur during diabetes treatment. Individuals diagnosed with type 1 diabetes may experience multiple episodes of asymptomatic or symptomatic hypoglycemia per week.AIM: To assess the frequency of hypoglycemic episodes and identify associated factors among individuals with type 1 diabetes in Unaizah City, Saudi Arabia.MATERIALS AND METHODS: A quantitative, cross-sectional, descriptive research design was employed in April and May of 2023. A convenience sample of 280 type 1 diabetic clients living in the Qassim region of Unaizah City was selected. Participants completed an electronic structured questionnaire that collected information on sociodemographic factors and hypoglycemia-related data. Descriptive statistics and a Chi-square test were used for data analysis, utilizing SPSS version 23. Ethical considerations were strictly adhered to throughout the study.RESULTS: The findings revealed that over two-thirds of the participants (72.1%) reported experiencing hypoglycemic episodes within the past week. Furthermore, more than one-fifth of these individuals attributed the cause of the episodes to high insulin doses (21%). Seeking medical assistance to change medications for hypoglycemia was reported by more than half of the participants (55.4%), while less than half received help from others during hypoglycemic episodes (42.9%). It was observed that adherence to diabetic medication was higher than adherence to diabetic diet and exercise regimens. Males, as well as single or divorced participants, reported a higher frequency of hypoglycemic episodes. Additionally, patients with higher levels of education and those residing in rural regions reported a higher exposure to hypoglycemic episodes.CONCLUSION: The effective management of hypoglycemia necessitates patient education and awareness regarding its causes and symptoms. Targeted interventions are required to improve adherence to therapeutic regimens and lifestyle modifications. Furthermore, when managing hypoglycemia, it is important to consider the gender, marital status, educational level, and residence of diabetic patients.
Hybrid approach for cost estimation of sustainable building projects using artificial neural networks
Authors: Al-Somaydaii Jumaa A. , Albadri Aminah T. , Al-Zwainy Faiq M. S. 
Published: March 2024

Abstract
Inaccurate estimation in sustainable construction projects is a significant challenge for appraisers, particularly when data and knowledge about the projects are lacking. As a result, there is a need to use cutting-edge technology to solve the issue of estimation inaccuracy. Iraq’s productivity estimates are now made using outdated, ineffective methodologies and procedures. In addition, it is essential to implement cutting-edge, quick, precise, and adaptable technology for productivity estimation. This study’s major goal is to calculate the overall costs of sustainable buildings using the cutting-edge technique known as artificial neural networks (ANNs). For Iraq’s construction industry to handle projects successfully, ANNs must be used as a new technology, a methodology developed to estimate the overall costs of sustainable construction projects. In this study, the process of cost estimation was modeled using ANNs. Investigations of a number of examples involving the creation of ANNs have also been made, including network design and internal elements and how much they impact the effectiveness of models built using ANNs. Equations were developed to determine structural productivity. These networks were shown to have extremely strong predictive power for both accounting coefficients (R) (93.33%) and the overall costs of sustainable construction projects, with a prediction accuracy of 87.00 and 93.33%, respectively.