Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations of Maternal Urinary Concentrations of Phenols, Individually and as a Mixture, with Serum Biomarkers of Thyroid Function and Autoimmunity: Results from the EARTH Study

The associations between urinary phenol concentrations and markers of thyroid function and autoimmunity among potentially susceptible subgroups, such as subfertile women, have been understudied, especially when considering chemical mixtures. We evaluated cross-sectional associations of urinary phenol concentrations, individually and as a mixture, with serum markers of thyroid function and autoimmunity. We included 339 women attending a fertility center who provided one spot urine and one blood sample at enrollment (2009–2015). We quantified four phenols in urine using isotope dilution high-performance liquid chromatography–tandem mass spectrometry, and biomarkers of thyroid function (thyroid-stimulating hormone (TSH), free and total thyroxine (fT4, TT4), and triiodothyronine (fT3, TT3)), and autoimmunity (thyroid peroxidase (TPO) and thyroglobulin (Tg) antibodies (Ab)) in serum using electrochemoluminescence assays. We fit linear and additive models to investigate the association between urinary phenols—both individually and as a mixture—and serum thyroid function and autoimmunity, adjusted for confounders. As a sensitivity analysis, we also applied Bayesian Kernel Machine Regression (BKMR) to investigate non-linear and non-additive interactions. Urinary bisphenol A was associated with thyroid function, in particular, fT3 (mean difference for a 1 log unit increase in concentration: −0.088; 95% CI [−0.151, −0.025]) and TT3 (−0.066; 95% CI [−0.112, −0.020]). Urinary methylparaben and triclosan were also associated with several thyroid hormones. The overall mixture was negatively associated with serum fT3 concentrations (mean difference comparing all four mixture components at their 75th vs. 25th percentiles: −0.19, 95% CI [−0.35, −0.03]). We found no evidence of non-linearity or interactions. These results add to the current literature on phenol exposures and thyroid function in women, suggesting that some phenols may alter the thyroid system.
Minimizing the Complexity of Systems through Structural Optimization and Variability Reduction

Scholars have focused on two primary characteristics that reflect the complexity of a system: the structure of the system and in the variability in the relationships between the elements. This paper discusses both aspects of the system and shows that they can be treated separately during development to reduce complexity. The first part treats the structural aspect of complexity by employing the cluster analysis of (Hitchins 1993, 135‐147) and (Hitchins 2003, 143‐148; 449‐457). This method optimizes the architecture of the system and minimizes the number of sub‐elements by determining which elements have the maximum amount of functional affinity. The second part deals with the variability of the relationships between the elements also called information entropy defined by (Shannon 1948). However, this concept can apply to the relationships among the elements of any type of system. The application of both of these methods it is believed will result in a significant reduction in complexity.
More on Energy and Laplacian Energy

A lot of properties especially bounds for the energy and the Laplacian energy of a graph have been known. We now establish further upper bounds for the energy and upper and lower bounds for the Laplacian energy. An upper bound for the energy of bipartite graphs is given in terms of the Laplacian eigenvalues.
Northumbria Research Link

 Abstract —As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This article provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This article undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this article surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.
A Multicriteria-Based Comparison of Electric Vehicles Using q-Rung Orthopair Fuzzy Numbers

The subject of this research is the evaluation of electric cars and the choice of car that best meets the set research criteria. To this end, the criteria weights were determined using the entropy method with two-step normalization and a full consistency check. In addition, the entropy method was extended further with q-rung orthopair fuzzy (qROF) information and Einstein aggregation for carrying out decision making under uncertainty with imprecise information. Sustainable transportation was selected as the area of application. The current work compared a set of 20 leading EVs in India using the proposed decision-making model. The comparison was designed to cover two aspects: technical attributes and user opinions. For the ranking of the EVs, a recently developed multicriteria decision-making (MCDM) model, the alternative ranking order method with two-step normalization (AROMAN), was used. The present work is a novel hybridization of the entropy method, full consistency method (FUCOM), and AROMAN in an uncertain environment. The results show that the electricity consumption criterion (w = 0.0944) received the greatest weight, while the best ranked alternative was A7. The results also show robustness and stability, as revealed through a comparison with the other MCDM models and a sensitivity analysis. The present work is different from the past studies, as it provides a robust hybrid decision-making model that uses both objective and subjective information.
Quantum Field Theory for Philosophers

The metaphysical commitments of quantum field theory are examined. A thesis of underdetermination as between field and particle approaches to the "elementary particles" is argued for but only if a disputed notion of transcendental individuality is admitted. The superiority of the field approach is further emphasized in the context of heuristics.
A Survey on Artificial Intelligence-Based Acoustic Source Identification

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we provide a comprehensive review of AI-based acoustic source identification techniques. We analyze the strengths and weaknesses of AI-based ASI processes and associated methods proposed by researchers in the literature. Additionally, we did a detailed survey of ASI applications in machinery, underwater applications, environment/event source recognition, healthcare, and other fields. We also highlight relevant research directions.
The Finding of New In Vivo Metabolite Triptorelin (5-10) in Human Urine Using Liquid Chromatography Coupled with Ion Trap/Time-of-Flight Mass Spectrometry with Dimethyl Sulfoxide Additives in the Mobile Phase

Triptorelin and leuprorelin are synthetic gonadotrophin-releasing hormones (GnRH) that are on the World Anti-Doping Agency (WADA) list of prohibited substances. To investigate the possible in vivo metabolites of triptorelin and leuprorelin in humans compared to previously reported in vitro metabolites, excreted urine from five patients treated with either triptorelin or leuprorelin was analyzed by liquid chromatography coupled with ion trap/time-of-flight mass spectrometry (LC/MS-IT-TOF). The addition of dimethyl sulfoxide (DMSO) to the mobile phase was found to enhance the detection sensitivity of certain GnRH analogs. The method was validated, and the limit of detection (LOD) was found at 0.02−0.08 ng/mL. Using this method, a novel new metabolite of triptorelin was discovered in the urine of all subjects up to 1 month after triptorelin administration, but it was not observed in the urine of subjects before drug administration. The limit of detection was estimated to be 0.05 ng/mL. The structure of the metabolite, triptorelin (5-10), is proposed from bottom-up mass spectrometry analysis. The discovery of in vivo triptorelin (5-10) can possibly be used as supporting evidence of triptorelin misuse in athletes.
Greenlight laser (XPS-180watt) prostatectomy for treatment of benign prostate obstruction, Pursuit of durability

ABSTRACT Objectives To report 5-year outcomes, need and predictors of retreatment post greenlight laser photoselective vaporization (GL.PVP) and vapo-enucleation (GL.PVEP), as long-term data on safety and efficacy of GL.PVP and GL.PVEP and on the prostate using XPSTM system are still pending. Patients and methods Primary outcome was the need for retreatment (medical treatment and reintervention) for recurrent BOO. Time-to-event (retreatment) analysis, perioperative events, change in the urinary outcome measures at different follow-up visits, early and late complications and PSA kinetics were reported. Results Between September 2014 and April 2017, 248 patients underwent GL/XPS procedures. GL.PVP and GL.PVEP were carried out for 157 (63.3%) and 91 (36.7%) patients with mean prostate sizes of 60 ± 18 and 100 ± 22 cc, respectively. After a mean duration of 62 ± 9-month follow-up, overall retreatment rate (medical and interventional) was 23% (57 patients). It was comparable between both GL.PVP and GL.PVEP cases: 38 (24.2%) and 19 (20.9%) patients, P = 0.5, respectively. Significantly more surgical reintervention rate was reported after GL.PVP compared to GL.PVEP (P = 0.03). In retreatment group, more intraoperative bleeding (P = 0.02), early postoperative hematuria (P = 0.03), higher median preoperative PSA (P = 0.02) and less postoperative one-year percent PSA reduction (P = 0.02) were detected. Lower postoperative one-year percent PSA reduction independently predicts retreatment with a cut-off point of 64.2% (58.2% sensitivity, 73.4% specificity, AUC 0.647, 95% CI 0.52–0.76). Median (range in months) time to event was 20 (1–60) for all cases and 13.5 (1–42) and 30 (18–60), P = 0.7, for GL.PVP and GL.PVEP groups, respectively. Conclusion Greenlight laser XPS is an effective, durable and versatile tool in treating benign prostatic obstruction. Durability of the outcome is predictable with more postoperative PSA reduction.
Relationship between GABA-Ergic System and the Expression of Mephedrone-Induced Reward in Rats—Behavioral, Chromatographic and In Vivo Imaging Study

Mephedrone is a psychoactive drug that increases dopamine, serotonin and noradrenaline levels in the central nervous system via interaction with transporters or monoamines. The aim of the presented study was to assess the role of the GABA-ergic system in the expression of mephedrone-induced reward. For this purpose, we conducted (a) a behavioral evaluation of the impact of baclofen (a GABAB receptors agonist) and GS39783 (a positive allosteric modulator of GABAB receptors) on the expression of mephedrone-induced conditioned place preference (CPP) in rats, (b) an ex vivo chromatographic determination of the GABA level in the hippocampi of rats subchronically treated with mephedrone and (c) an in vivo evaluation of GABA hippocampal concentration in rats subchronically administered with mephedrone using magnetic resonance spectroscopy (MRS). The results show that GS39783 (but not baclofen) blocked the expression of CPP induced by (20 mg/kg of) mephedrone. The behavioral effect was consistent with chromatographic analysis, which showed that mephedrone (5 and 20 mg/kg) led to a decrease in GABA hippocampal concentration. Altogether, the presented study provides a new insight into the involvement of the GABA-ergic system in the rewarding effects of mephedrone, implying that those effects are at least partially mediated through GABAB receptors, which suggests their potential role as new targets for the pharmacological management of mephedrone use disorder.
Swedish word stress in optimality theory

The purpose of this paper is to give an introduction to how lexical word stress in Swedish can be analysed with modern phonological theories as metrical phonology (Liberman 1975) and optimality theory (Prince & Smolensky 1993). Central concepts and structures within the phonological theories are introduced and discussed, and examples of how the word stress pattern of Swedish can be treated within optimality theory (OT) are given. We will deal both with monomorphemic words, as well as compound words and affixes.
A Compressed Sensing Framework for Biological Microscopy

Compressed sensing (CS) is a new sampling theory that was recently introduced for efficient acquisition of compressible signals. In this thesis, we have studied practical applications of the Fourier-based CS sampling theory for biological microscopy imaging, with two main contributions: (i) Image denoising: microscopic images suffer from complex artifacts associated with noise and non-perfect illumination conditions. In fluorescence microscopy, noise and photobleaching degrade the quality of the image. In this work, we have exploited the CS theory as an image denoising tool, using multiple random undersampling in the Fourier domain and the Total Variation as a spatial sparsity prior. Compounding of images reconstructed from multiple sets of random measurements enforce spatial coherence of meaningful signal components and decorrelate noisy components. We have studied the relation between signal sparsity and noise reduction performance under different noise conditions. We have demonstrated on simulated and practical experiments on fluorescence microscopy that the proposed denoising framework provide images with similar or increased signal-to-noise ratio (SNR) compared to state of the art denoising methods while relying on a limited number of samples. If Fourier-domain image point acquisitions were feasible, the proposed denoising could be used as a fast acquisition scheme which would enable to reduce exposition times, and reduce the photobleaching effects. (ii) Compressed digital holographic microscopy: high data throughput is becoming increasingly important in microscopy, with high-resolution cameras (i.e. large numbers of samples per acquisition) and long observation times. The com- pressed sensing theory provides a framework to reconstruct images from fewer samples than traditional acquisition approaches. However, the very few measurements must be spread over a large field of view, which is difficult to achieve in conventional microscopy. In a first experiment, we have proposed a computational scheme to perform fast temporal acquisitions of sequences of Fourier amplitude measures in optical Fourier imaging and estimate the missing phase information from spectra interpolation between few in-between complete keyframes. This approach was evaluated for high-frame rate imaging of moving cells. In a second experiment, we have implemented a real CS acquisition scheme for digital holographic microscopy, acquiring a diffraction map of the optical field and recovering high quality images from as little as 7% of random measurements. The CS acquisition setup was successfully extended to high speed low-light single-shot off-axis holography.
Imputation for Missing Data in Statistical Matching Using Goal Programming

Nearly all common statistical approaches assume complete information for all variables involved in the analysis, which making missing data problematic. Imputation is the process of substituting a missing value with a specific value, and it is most likely the most popular method for compensating for missing item values in a survey. This study suggests use of mathematical goal programming approach to impute missing data in statistical matching. The suggested approach adopts the regression method in imputation of the missing values. The regression coefficients are estimated using an estimated mathematical goal programming approach. The paper studies the cases when having variables with different skewed probability distributions (lognormal, Cauchy, chi square). The results of the simulation study indicate a good performance of the suggested approach in cases of skewed probability distribution. Using goal programming in regression is based on the minimizing the sum of absolute errors which is less affected by outliers compared to sum of squares of errors.
Polynomial Identification in the Limit of Substitutable Context-free Languages

This paper formalises the idea of substitutability introduced by Zellig Harris in the 1950s and makes it the basis for a learning algorithm from positive data only for a subclass of context-free languages. We show that there is a polynomial characteristic set, and thus prove polynomial identification in the limit of this class. We discuss the relationship of this class of languages to other common classes discussed in grammatical inference. It transpires that it is not necessary to identify constituents in order to learn a context-free language—it is sufficient to identify the syntactic congruence, and the operations of the syntactic monoid can be converted into a context-free grammar. We also discuss modifications to the algorithm that produces a reduction system rather than a context-free grammar, that will be much more compact. We discuss the relationship to Angluin's notion of reversibility for regular languages. We also demonstrate that an implementation of this algorithm is capable of learning a classic example of structure dependent syntax in English: this constitutes a refutation of an argument that has been used in support of nativist theories of language.
Can a relaxation technique be used to validate clouds and sulphur species in a GCM?

The Hamburg version of the European Centre for Medium‐Range Weather Forecasting (ECMWF) general circulation model, ECHAM4, developed for climate studies, is used to study the hydrological cycle and the atmospheric sulphur cycle. A technique, the Newtonian relaxation, is introduced to compare results from the model with measurements of cloud parameters and sulphur species concentrations. The model is forced by ECMWF analyses to simulate September 1993, and results are compared to observations on different spatial and temporal scales: monthly mean horizontal satellite data, daily mean averages at European and Canadian stations and aircraft soundings over the north Atlantic off the Canadian coast. The model is able to reproduce monthly mean horizontal distributions of liquid water path and precipitation. Daily mean precipitation fluxes and the temporal evolution of gaseous and particulate sulphur also agree quite well with observations. Based on this comparison with observations the performance of two different cloud physics parametrizations is discussed. These experiments indicate that variables like relative humidity, cloud cover and precipitation are controlled by the large‐scale dynamics, whereas the cloud water content depends on the parametrization of the cloud microphysics. Coupling of the model‐calculated sulphate mixing ratios to the cloud microphysics improves the model's sulphate distribution but slightly worsens the agreement between calculated and observed precipitation.
Developing SAMM: A Model for Measuring Sustained Attention in Asynchronous Online Learning

There is a strong relationship between sustainability and equality education, as it is emphasized in the United Nations’ Sustainable Development Goals (SDGs). To maintain learning effectiveness, learning attention is a valuable consideration. By continuously monitoring learners’ attention, the teaching and learning process can be measured and adjusted as needed. However, it poses a challenge for measuring attention in online learning environments where all participants do not interact face-to-face. To address this concern, this paper proposes a sustained attention measurement model (SAMM) that establishes attention tests to gauge learners’ sustained attention levels during asynchronous online learning. SAMM presents learners with real-time questions based on course content, collecting both their response time and accuracy. In an experiment conducted over an academic semester, we recruited 213 students from a private Taiwanese university of technology and analyzed their response time and accuracy rate to identify attention patterns in the online learning system. This analysis can provide valuable feedback for instructors to adjust their teaching methods.
Clinical application of robots in dentistry: A scoping review.

PURPOSE The surge in digitalization and artificial intelligence has led to the wide application of robots in various fields, but their application in dentistry started relatively late. This scoping review aimed to comprehensively explore and map the current status of the clinical application of robots in dentistry. STUDY SELECTION An iterative approach was used to gather as much evidence as possible from four online databases, including PubMed, the China National Knowledge Infrastructure, the Japan Science and Technology Information Aggregator, Electronic, and the Institute of Electrical and Electronics Engineers, from January 1980 to December 2022. RESULTS A total of 113 eligible articles were selected from the search results, and it was found that most of the robots were developed and applied in the United States (n = 56; 50%). Robots were clinically applied in oral and maxillofacial surgery, oral implantology, prosthodontics, orthodontics, endodontics, and oral medicine. The development of robots in oral and maxillofacial surgery and oral implantology is relatively fast and comprehensive. About 51% (n = 58) of the systems had reached clinical application, while 49% (n = 55) were at the pre-clinical stage. Most of these are hard robots (90%; n = 103), and their invention and development were mainly focused on university research groups with long research periods and diverse components. CONCLUSIONS There are still limitations and gaps between research and application in dental robots. While robotics is threatening to replace clinical decision-making, combining it with dentistry to gain maximum benefit remains a challenge for the future.