Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine Learning Methods for "Small-n, Large-p" Problems: Understanding the Complex Drivers of Modern-Day Slavery

40 million people are estimated to be in some form of modern slavery across the globe. Understanding the factors that make any particular individual or geographical region vulnerable to such abuse is essential for the development of effective interventions and policy. Efforts to isolate and assess the importance of individual drivers statistically are impeded by two key challenges: data scarcity and high dimensionality. The hidden nature of modern slavery restricts available datapoints; and the large number of candidate variables that are potentially predictive of slavery inflates the feature space exponentially. The result is a highly problematic "small-n, large-p' setting, where overfitting and multi-collinearity can render more traditional statistical approaches inapplicable. Recent advances in non-parametric computational methods, however, offer scope to overcome such challenges. We present an approach that combines non-linear machine learning models and strict cross-validation methods with novel variable importance techniques, emphasising the importance of stability of model explanations via Rashomon-set analysis. This approach is used to model the prevalence of slavery in 48 countries, with results bringing to light the importance predictive factors - such as a country's capacity to protect the physical security of women, which has previously been under-emphasized in the literature. Out-of-sample estimates of slavery prevalence are then made for countries where no survey data currently exists.
Habraken, Jacobs, and Ostrom on governing the built environment: the case of common interest developments

Abstract Habraken's Structure of the Ordinary (SOTO), Jacobs' view of cities, and Ostrom's Design Principles and Institutional Analysis and Development (IAD) framework focus on essential elements and relationships for the effective governance of the environment. However, they have different perspectives about what is necessary for successful governance. This article compares and contrasts Habraken's, Jacobs', and Ostrom's views and applies them to Common Interest Developments (CIDs). Habraken, Jacobs, and Habraken discuss the importance of public territory. Habraken views public territory as relative: a territory in a built environment can be private relative to a larger, or higher level, territory, and public relative to an included, lower level, territory. Jacobs discusses the importance of connections and accommodating strangers without sacrificing safety. Ostrom views common-pool resources as goods whose use causes less to be available to others. For their part, CIDs represent a particular governance vehicle for defining what is public and private in large residential developments. For both Habraken and Ostrom, the transformation of the physical environment reflects agents' common values constrained by material, technical, cultural, and economic conditions. Rather than one mutual understanding, Jacobs wrote that balancing the commercial and the guardian values is crucial for society's health and survival.
An Improved Quadrangle Control Method for Four-Switch Buck-Boost Converter With Reduced Loss and Decoupling Strategy

Four-switch buck-boost (FSBB) converter is widely used in battery applications due to the simple structure and the excellent performance of both voltage step-up and step-down. With the quadrangle control method, FSBB converter can realize zero voltage switching (ZVS) of all power switches, and thus can adapt to the high-frequency trends. However, the conventional quadrangle control method has two problems: 1) the efficiency degradation caused by the large root mean square (RMS) current of the inductor, and 2) the instability caused by the coupling relationship between multiple control variables. In this article, an improved quadrangle control method is proposed to solve the two problems, making FSBB converter a good candidate for high-frequency battery applications. First, the loss analysis is built to determine the relationship between loss and the control variables. Then, the conditions to achieve the minimum loss are obtained. Second, the decoupling compensation strategy is applied to free the coupling relationship to improve the stability. The proposed strategy can achieve three control goals: 1) ZVS of all power switches; 2) minimize the total loss; and 3) stable closed-loop system. Finally, a 1MHz 280W FSBB prototype is built to verify the proposed control method. The prototype achieves all control goals and 98.1% peak efficiency.
Reproductive and Sexual Health in Males with Physical, Hearing, and Vision Disabilities

Abstract Objective This study aimed to determine reproductive health, sexual functions, and sexual satisfaction levels of males with disabilities. Methods: The study had a cross-sectional, descriptive, and correlational design and was conducted on 136 males with disabilities. Data was collected using an introduction form, International Index of Erectile Function, the Erectile Performance Anxiety Index (EPAI), the Premature Ejaculation Profile (PEP), and the Sexual Satisfaction Scale (SSS). Results: The total EPAI score was 19.86 ± 8.98(10–50), the total PEP score was 9.91 ± 4.20(0–16) and the total SSS score was 86.79 ± 18.20(44–119). Conclusions: Education and counseling on reproductive and sexual health should be given based on their individual needs.
Light Spectra during Somatic Embryogenesis of Norway Spruce—Impact on Growth, Embryo Productivity, and Embling Survival

For Norway spruce (Picea abies (L.) Karst. ) somatic embryogenesis (SE) culture conditions throughout the propagation process affect the final result. Many critical phases can be identified, and all of them cumulatively increase the production costs of SE plants if they cannot be controlled. In order to determine the best lighting protocol for each SE step, Norway spruce embryogenic tissue (ET) was proliferated, and somatic embryos were matured under different light wavelengths, wavelength combinations, and in the dark. Overall, using low-intensity LED lights during proliferation or at the end of maturation had little effect on the growth of ET, embryo productivity, or embryo survival; on the other hand, major negative effects could not be seen. This is beneficial from a practical point of view, indicating no need for lighting or protection of SE cultures from light during their handling in these steps of the propagation process. When somatic embryos were germinated under different spectra, significant differences in embling shoot and root growth, as well as in the survival of the emblings, were found. The best treatment varied between trials, and the genotype of the SE culture was found to have a stronger effect than the light spectrum, indicating that various light spectra and also intensity adjusted using pulse width modulation (PWM) can be successfully applied to the SE germination phase in Norway spruce.
Simulation of the Ozone Monitoring Instrument aerosol index using the NASA Goddard Earth Observing System aerosol reanalysis products

Abstract. We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI near-UV aerosol retrieval algorithms (known as OMAERUV) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining to the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600 and 1013.25 hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial-resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.
The estimation of transmission line loadability Based on Artificial Intelligence Algorithm & Voltage Stability Index

The continuous changes in electricity demand and supply are contributing to the disparity in quantities of power transferred between transmission networks, i.e. some lines are lightly loaded and others are overloaded. This presents a significant challenge to the secure and reliable operation of the power system. The current research is concerned with enhancing the loadability of electric transmission lines, that secure the increase in load demand through Flexible AC Transmission System (FACTS) injection. This paper is focused on the -Thyristor Controlled Series Compensator (TCSC), the optimum location of the TCSC was determined by applying two different techniques. The first technique was based on an artificial intelligence algorithm while the second technique was based on the level of voltage stability indices for all system lines. The optimal location is based on the fulfillment of multi-objective functions represented by an increase in the load capacity, reduce levels of the voltage stability index, the cost of installing the TCSC, and the voltage deviation. The IEEE-9 bus standard test system as a study case and MATLAB-programmes has been used for the analysis of the optimal power flow, and estimating the loadability of transmission lines without and with TCSC.
Learning adaptive spatial-temporal regularized correlation filters for visual tracking

Recently, there have been many visual tracking methods based on correlation ﬁlters. These methods mainly enhance the tracking performances by considering the information of background, space, or time in the appearance model. This paper proposes an effective tracking method, named adaptive spatial–temporal regularized correlation ﬁlter (ASTRCF) tracker, based on the popular adaptive spatially regularized correlation ﬁlter (ASRCF) tracker. That is, the continuity of object’s motion in the process of tracking is considered by introducing a temporal-regularized term in the appearance model of ASRCF tracker. Furthermore, its solution is inferred by applying the alternating direction method of multipliers. The proposed appearance model contains a background-awareness term, a spatially regularized term, an adaptive-weight term, and a temporal-regularized term. Therefore, it can not only keep the good performances of ASRCF tracker, such as learning the background information and the spatial information adaptively to enhance the discriminating ability, but also take advantage of the relation of correlation ﬁlters in the last frame and the current frame for addressing the complex cases, such as occlusion, and fast motion. Extensive experimental results on various challenging databases show that the proposed ASTRCF tracker achieves better tracking performances than some state-of-the-art trackers.
An explicitly designed paratope of amyloid-β prevents neuronal apoptosis in vitro and hippocampal damage in rat brain

Synthetic antibodies hold great promise in combating diseases, diagnosis, and a wide range of biomedical applications. However, designing a therapeutically amenable, synthetic antibody that can arrest the aggregation of amyloid-β (Aβ) remains challenging. Here, we report a flexible, hairpin-like synthetic paratope (SP1, ∼2 kDa), which prevents the aggregation of Aβ monomers and reverses the preformed amyloid fibril to a non-toxic species. Structural and biophysical studies further allowed dissecting the mode and affinity of molecular recognition events between SP1 and Aβ. Subsequently, SP1 reduces Aβ-induced neurotoxicity, neuronal apoptosis, and ROS-mediated oxidative damage in human neuroblastoma cells (SH-SY5Y). The non-toxic nature of SP1 and its ability to ameliorate hippocampal neurodegeneration in a rat model of AD demonstrate its therapeutic potential. This paratope engineering module could readily implement discoveries of cost-effective molecular probes to nurture the basic principles of protein misfolding, thus combating related diseases.
A coupled finite difference and material point method for simulation of gas–solid flow of thermobaric explosions

A coupled finite difference and material point method (CFDMP) was presented to simulate the dynamic of the gas–solid flow of thermobaric explosions. The coupled method takes advantages of both the two methods where the finite difference method captures the wave structures of gas phase and the material point method tracks the movement of solid phase. Particle collision is easily realized in MPM framework. By using a uniform grid system, the grid nodes have both the two phases’ information and their interactions are directly calculated. The simulation of thermobaric explosions in different containers is carried out and the results validate the accuracy of CFDMP program. The particle collision reduce the compression degree of the solid phase in the initial expansion stage but slightly influence the pressure history at the gauge. The process of particle movement in the container is demonstrate and the wall-reflected wave enhances the burning rate of particles.
Adaptive Multi-Level Search for Global Optimization: An Integrated Swarm Intelligence-Metamodelling Technique

Over the last decade, metaheuristic algorithms have emerged as a powerful paradigm for global optimization of multimodal functions formulated by nonlinear problems arising from various engineering subjects. However, numerical analyses of many complex engineering design problems may be performed using finite element method (FEM) or computational fluid dynamics (CFD), by which function evaluations of population-based algorithms are repetitively computed to seek a global optimum. It is noted that these simulations become computationally prohibitive for design optimization of complex structures. To efficiently and effectively address this class of problems, an adaptively integrated swarm intelligence-metamodelling (ASIM) technique enabling multi-level search and model management for the optimal solution is proposed in this paper. The developed technique comprises two steps: in the first step, a global-level exploration for near optimal solution is performed by adaptive swarm-intelligence algorithm, and in the second step, a local-level exploitation for the fine optimal solution is studied on adaptive metamodels, which are constructed by the multipoint approximation method (MAM). To demonstrate the superiority of the proposed technique over other methods, such as conventional MAM, particle swarm optimization, hybrid cuckoo search, and water cycle algorithm in terms of computational expense associated with solving complex optimization problems, one benchmark mathematical example and two real-world complex design problems are examined. In particular, the key factors responsible for the balance between exploration and exploitation are discussed as well.
The distribution of reduced sulphur compounds in polar environments : insights from observations and climatologies

ii PREFACE.iv TABLE OF CONTENTS . v LIST OF TABLES . ix LIST OF FIGURES . x LIST OF SYMBOLS AND ABBREVIATIONS . xi ACKNOWLEDGEMENTS . xiv DEDICATION . xvi CHAPTER 1: INTRODUCTION . 1 1.1 BIOLOGICAL ROLES FOR DMS/P . 2 1.2 CLIMATE EFFECTS OF DMS EMISSIONS . 3 1.3 DMS/P IN POLAR REGIONS . 4 1.4 THESIS OVERVIEW . 5 CHAPTER 2: TOWARDS A REVISED CLIMATOLOGY OF SUMMER-TIME DIMETHYLSULFIDE CONCENTRATIONS AND SEA-AIR FLUXES IN THE SOUTHERN OCEAN.6 2.
QTL mapping for resistance to Cercospora sojina in Essex Forrest soybean (Glycine max L.) lines

Frogeye leafspot (FLS), caused by Cercospora sojina, is observed as red-brown lesions on leaves that can coalesce and decrease the photosynthetic ability of soybeans. The average yield loss due to Frogeye Leaf Spot is estimated at approximately 40% in established fields, whereas 100% incidence was previously recorded. QoI inhibitor fungicides were considered an effective control method, but the pathogen quickly evolved an ability to thrive post-application. This trait quickly spread across North America. Therefore, genetic host resistance is likely the most effective method to prevent the disease. To achieve this goal, we aimed to screen 91 recombinant inbred lines (RILs) of ‘Essex’ × ‘Forrest’ under greenhouse conditions for FLS resistance and used single nucleotide polymorphism (SNP) markers to identify associated quantitative trait loci (QTL). Two QTL were mapped in this study. One QTL reported on Chr. 13 coincides with the QTL previously reported, and the QTL on Chr. 19 was novel. Overall, this study will help to better understand the underlying mechanisms of soybean resistance to C. sojina as well as to develop soybean varieties with resistance to FLS using marker assisted selection. Key words: Cercospora sojina, quantitative trait loci, Frogeye Leaf Spot, Essex × Forrest, disease resistance, genotypic and phenotypic traits.
Construction and Validation of a Robust Genomic Classifier for High-Risk Sporadic Type 2 Papillary Renal Cell Carcinoma: Support More Accurate Utilization of mTOR inhibitors

To construct a robust genomic classifier for high-risk sporadic type 2 papillary renal cell carcinoma (sPRCC2) and identify potential therapeutic targets. A cohort from The Cancer Genome Atlas and two datasets from Gene Expression Omnibus were examined. Common differentially expressed genes were screened, and the ConsensusClusterPlus package was used to identify potential high-risk molecular subtypes of sPRCC2. Targeting protein for Xklp2 (TPX2) expression was used to simulate the classifier according to the logistic model. Ninety-two samples from Fudan University Shanghai Cancer Center (FUSCC) were obtained, and TPX2 immunostaining was performed to validate the predictive ability of the genomic classifier. Retrospective analysis was used to compare drug efficacy between the groups. High-risk sPRCC2 had worse overall (hazard ratio [HR] = 7.804) and disease-free survival (HR = 8.777) than low-risk sPRCC2, and the tumor and lymph node stages were significantly higher in high-risk sPRCC2. Gene set enrichment analysis revealed significant enrichment of genes in the mammalian target of rapamycin (mTOR) complex 1 signaling pathway in the high-risk group. In the FUSCC cohort, high-risk sPRCC2 (high TPX2 expression) was significantly correlated with worse overall and progression-free survival. Retrospective analysis indicated that mTOR inhibitor (everolimus) had greater efficacy in the high-risk group than in the low-risk group (overall response rate: 28.6% vs. 16.7%) and that everolimus had greater efficacy than sunitinib in the high-risk group (overall response rate: 28.6% vs. 20%). This study successfully constructed a genomic classifier for identifying high-risk sPRCC2. mTOR inhibitors may have good efficacy in patients with high-risk sPRCC2.
A modified inverse method for determining spectral radiative properties of participating medium from normal-hemispherical transmittance and reflectance

This paper presents a modified inverse method for retrieving the spectral absorption and transport scattering coefficients of participating medium, the method combines (i) several analytical expressions obtained from the modified two-flux (TF) approximation, (ii) the Monte Carlo (MC) method for predicting normal-hemispherical transmittance Tnh and reflectance Rnh generally obtained from experiments, as well as (iii) an optimization method employing the genetic algorithm (GA). Three types of typical participating medium, the green glass, the low-iron glass, and the silica aerogel with known radiative properties taken form the literatures, were used to illustrate the accuracy and robustness of the modified method by retrieving the input properties from the inverse identification in which the Tnh and Rnh ‘experimental data’ were obtained from the MC predictions. The results show that the modified inverse method was able to retrieve accurately the absorption and transport scattering coefficients of participating medium.
An Adaptive Memetic Algorithm for Dynamic Electric Vehicle Routing Problem with Time-Varying Demands

Dynamic electric vehicle routing problem (DEVRP) is an extension of the electric vehicle routing problem (EVRP) into dynamic logistical transportation system such that the demand of customer may change over time. The routing decision of DEVRP must concern with the driving range limitation of electric vehicle (EV) in a dynamic environment since both load degree and battery capacity are variable according to the time-varying demands. This paper proposes an adaptive memetic algorithm, where a special encoding strategy, an adaptive local search operator, and an economical random immigrant scheme are employed in the framework of evolutionary algorithm, to solve DEVRP efficiently. Numeric experiments are carried out upon a series of test instances that are constructed from a stationary VRP benchmark. The computational results show that the proposed algorithm is more effective in finding high-quality solution than several peer algorithms as well as significant in improving the capacity of the routing plan of EVs in dynamic transportation environment.
A perspective on sustainable energy materials for lithium batteries

Lithium ion battery has achieved great success in portable electronics and even recently electronic vehicles since its commercialization in 1990s. However, lithium‐ion batteries are confronted with several issues in terms of the sustainable development such as the high price of raw materials and electronic products, the emerging safety accidents, etc. The recent progresses are herein emphasized on lithium batteries for energy storage to clearly understand the sustainable energy chemistry and emerging energy materials. The Perspective presents novel lithium‐ion batteries developed with the aims of enhancing the electrochemical performance and sustainability of energy storage systems. First, revolutionary material chemistries, including novel low‐cobalt cathode, organic electrode, and aqueous electrolyte, are discussed. Then, the characteristics of safety performance are analyzed and strategies to enhance safety are subsequently evaluated. Battery recycling is considered as the key factor for a sustainable society and related technologies are present as well. Finally, conclusion and outlook are drawn to shed lights on the further development of sustainable lithium‐ion batteries.