Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequential unconstrained minimization algorithms for constrained optimization

The problem of minimizing a function f(x):RJ → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function to obtain xk. The auxiliary functions gk(x):D ⊆ RJ → R+ are nonnegative on the set D, each xk is assumed to lie within D, and the objective is to minimize the continuous function f:RJ → R over x in the set , the closure of D. We assume that such minimizers exist, and denote one such by . We assume that the functions gk(x) satisfy the inequalities for k = 2, 3, …. Using this assumption, we show that the sequence {f(xk)} is decreasing and converges to . If the restriction of f(x) to D has bounded level sets, which happens if is unique and f(x) is closed, proper and convex, then the sequence {xk} is bounded, and , for any cluster point x*. Therefore, if is unique, and . When is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton–Raphson method. The proof techniques used for SUMMA can be extended to obtain related results for the induced proximal distance method of Auslander and Teboulle.
Biochemical and Microstructural Characteristics of Collagen Biopolymer from Unicornfish (Naso reticulatus Randall, 2001) Bone Prepared with Various Acid Types

Biopolymer-like collagen has great industrial potential in terms of its excellent properties, such as strong biocompatibility, high degradability, and low antigenicity. Collagen derived from fish by-products is preferable as it is safer (free from transmittable diseases) and acceptable to most religious beliefs. This study aimed to characterize the unicornfish (Naso reticulatus Randall, 2001) bone collagens prepared with different type of acids, i.e., acetic acid, lactic acid, and citric acid. A higher yield (Y) (p < 0.05) was obtained in the citric-acid-soluble collagen (CASC) (Y = 1.36%), followed by the lactic-acid-soluble collagen (LASC) (Y = 1.08%) and acetic-acid-soluble collagen (AASC) (Y = 0.40%). All extracted collagens were classified as type I due to the presence of 2-alpha chains (α1 and α2). Their prominent absorption spectra were located at the wavelengths of 229.83 nm to 231.17 nm. This is similar to wavelengths reported for other fish collagens. The X-ray diffraction (XRD) and infrared (IR) data demonstrated that the triple-helical structure of type I collagens was still preserved after the acid-extraction process. In terms of thermal stability, all samples had similar maximum transition temperatures (Tmax = 33.34–33.51 °C). A higher relative solubility (RS) of the unicornfish bone collagens was observed at low salt concentration (0–10 g/L) (RS > 80%) and at acidic condition (pH 1.0 to pH 3.0) (RS > 75%). The extracted collagen samples had an irregular and dense flake structure with random coiled filaments. Overall, bones of unicornfish may be used as a substitute source of collagen.
A Novel Preclinical In Vitro 3D Model of Oral Carcinogenesis for Biomarker Discovery and Drug Testing

This study aimed to develop an in vitro three-dimensional (3D) cell culture model of oral carcinogenesis for the rapid, scalable testing of chemotherapeutic agents. Spheroids of normal (HOK) and dysplastic (DOK) human oral keratinocytes were cultured and treated with 4-nitroquinoline-1-oxide (4NQO). A 3D invasion assay using Matrigel was performed to validate the model. RNA was extracted and subjected to transcriptomic analysis to validate the model and assess carcinogen-induced changes. The VEGF inhibitors pazopanib and lenvatinib were tested in the model and were validated by a 3D invasion assay, which demonstrated that changes induced by the carcinogen in spheroids were consistent with a malignant phenotype. Further validation was obtained by bioinformatic analyses, which showed the enrichment of pathways associated with hallmarks of cancer and VEGF signalling. Overexpression of common genes associated with tobacco-induced oral squamous cell carcinoma (OSCC), such as MMP1, MMP3, MMP9, YAP1, CYP1A1, and CYP1B1, was also observed. Pazopanib and lenvatinib inhibited the invasion of transformed spheroids. In summary, we successfully established a 3D spheroid model of oral carcinogenesis for biomarker discovery and drug testing. This model is a validated preclinical model for OSCC development and would be suitable for testing a range of chemotherapeutic agents.
Bound populations around cD galaxies and cD velocity offsets in clusters of galaxies

Recent claims in the literature for the existence of a low velocity dispersion population of galaxies in the cores of rich clusters are investigated. The suggested population, which has been generally interpreted as gravitationally bound to the potential well of the first-ranked cluster galaxy, is taken as evidence in support of the galactic cannibalism model for D/cD galaxy formation. Five clusters which have been suggested in the literature to possess bound population of galaxies associated with the D/cD are examined with a statistical test, which compares the number of galaxies with relative velocities less than a given fraction of the cluster scale to the number expected for an assumed parent velocity dispersion
Sleep quality is mediated by physical activity level in adolescents.

BACKGROUND Sleep is essential for the adolescent's health and well-being. Despite existing evidence of the positive relationship between physical activity and quality of sleep, some other factors could mediate this association. The purpose of the present study was to clarify the interaction between the level of physical activity and sleep in adolescents depending on their gender. METHODS A total of 12,459 subjects 11 to 19 years old (5073 male and 5016 female) reported data regarding their quality of sleep and their level of physical activity. RESULTS Better quality of sleep was reported by males regardless of the level of physical activity (d=0.25, P<0.001). Better quality of sleep was reported by active subjects (P<0.05), and it improved in both sexes as the level of physical activity was higher (P<0.001). CONCLUSIONS Male adolescents have better sleep quality than females regardless of their competitive level. The higher the adolescents' physical activity level the higher the quality of sleep.
Machine Learning Methods Improve Specificity in Newborn Screening for Isovaleric Aciduria

Isovaleric aciduria (IVA) is a rare disorder of leucine metabolism and part of newborn screening (NBS) programs worldwide. However, NBS for IVA is hampered by, first, the increased birth prevalence due to the identification of individuals with an attenuated disease variant (so-called “mild” IVA) and, second, an increasing number of false positive screening results due to the use of pivmecillinam contained in the medication. Recently, machine learning (ML) methods have been analyzed, analogous to new biomarkers or second-tier methods, in the context of NBS. In this study, we investigated the application of machine learning classification methods to improve IVA classification using an NBS data set containing 2,106,090 newborns screened in Heidelberg, Germany. Therefore, we propose to combine two methods, linear discriminant analysis, and ridge logistic regression as an additional step, a digital-tier, to traditional NBS. Our results show that this reduces the false positive rate by 69.9% from 103 to 31 while maintaining 100% sensitivity in cross-validation. The ML methods were able to classify mild and classic IVA from normal newborns solely based on the NBS data and revealed that besides isovalerylcarnitine (C5), the metabolite concentration of tryptophan (Trp) is important for improved classification. Overall, applying ML methods to improve the specificity of IVA could have a major impact on newborns, as it could reduce the newborns’ and families’ burden of false positives or over-treatment.
Affective Signal Processing (ASP): Unraveling the mystery of emotions

Slowly computers are being dressed and becoming huggable and tangible. They are being personalized and are expected to understand more of their users' feelings, emotions, and moods: This we refer to as affective computing. The work and experiences from 50+ publications on affective computing is collected and reported in one concise monograph. A brief introduction on emotion theory and affective computing is given and its relevance for computer science (i.e., Human-Computer Interaction, Artificial Intelligence (AI), and Health Informatics) is denoted. Next, a closed model for affective computing is introduced and reviews of both biosignals and affective computing are presented. The conclusion of all of this is that affective computing lacks standards. Affective computing's key dimensions need to be identified and studied to bring the field the progress it needs. A series of studies is presented that explore baseline-free affective computing, the influence of a range of distinct triggers for emotions, the influence of time windows, several combinations of biosignals with and without speech, the impact of the context, the personality traits neuroticism and extroversion, and demographics. Moreover, a complete signal processing + classification processing pipeline for affective computing is developed and executed on the data gathered. This pipeline is also applied on two clinical case studies, which proves that affective computing is already feasible in clinical practice; that is, Computer Aided Diagnosis (CAD) for patients suffering from a Post-Traumatic Stress Disorder (PTSD). A set of key dimensions for affective computing and, subsequently, prerequisites and guidelines are defined, based on the author's work and experiences. Moreover, historical, emotion theoretical, and computer science perspectives are taken to reflect upon the work and five applications (i.e., next-generation TV, knowledge representations, CAD, robot nannies, and digital human models) are presented to illustrate the field's future impact. If anything, this monograph shows that affective computing will become unstoppable, will determine our relation with ICT and, as such, will reshape our lives.
Keynes's monetary theory : a different interpretation

Preface 1. Introduction 2. Keynes in the 1920s: ideas, beliefs, and events 3. Theories, implications, and conjectures in the 1920s 4. The General Theory: a different perspective 5. Monetary reform and international economic order 6. Other interpretations of The General Theory 7. Conclusion References Index.
The geometric parameters of solar wind discontinuities based on STEREO, ACE and WIND measurements

A case study of solar wind discontinuity geometry analysis, based on magnetosphere satellites Solar TErrestrial RElations Observatory (STEREO) A, STEREO B, ACE (Advanced Composition Explorer) and Wind measurements in 2007, is presented. The normal wind direction obtained by different spacecraft, depending on the cross spacecraft distance, has been analysed. The value of the curvature radius of a discontinuity's front appeared to be independent from the spatial scale within the range of STEREO A and STEREO B observation. The curvature radii of processed events were estimated to be of the order of a thousand R E (where R E is the radius of the earth).
Neutral winds and phase velocity of the instabilities in the equatorial electrojet

It is shown that a neutral wind in the equatorial electrojet induces variations of the phase velocities of the type I (two stream) and type II (cross field) instabilities, which are related to the local wind velocity and to the mean wind velocity (averaged along the whole magnetic field line), respectively. This difference is discussed, particular attention being devoted to its effects on the evaluation of the primary electric field in the electrojet.
Predictors of Nurses’ Practice of Eye Care for Patients in Intensive Care Units

Introduction Taking care of patients’ eyes is an important nursing skill. Nurses must be capable of providing a standard assessment of the eye and vision as well as necessary care such as eye cleaning. Intensive care unit (ICU) nurses typically focus on life-threatening issues while giving little attention to other serious issues. The purpose of this study was to assess predictors of nurses’ practice of eye care for patients in ICUs in the West Bank. Method A cross-sectional study was conducted with all ICU nurses from West Bank hospitals. The researchers developed a self-administered questionnaire to collect data. Results One hundred and fifty-two nurses participated in this study. The findings revealed that the mean age of nurses was 31.2 (SD = 7.5) years. The analysis revealed that only 0.7% had a good knowledge level, 7.2% had a fair knowledge level, and 25.7% had a good practice level of eye care for patients in an ICU. Knowledge of patients’ eye care in the ICU, as well as an eye care protocol or policy for unconscious patients, was found to be significant predictors of practice (p < .001). Conclusion The study confirmed that the nurses had poor knowledge and inadequate practice of eye care for patients in the ICU. Also, the study confirmed that a nurse's knowledge of patients’ eye care in the ICU and an eye care protocol or policy for unconscious patients were significant predictors of practice.
Fast Recombination of Charge-Transfer State in Organic Photovoltaic Composite of P3HT and Semiconducting Carbon Nanotubes Is the Reason for Its Poor Photovoltaic Performance

Although the photovoltaic performance of the composite of poly-3-hexylthiophene (P3HT) with semiconducting single-walled carbon nanotubes (s-SWCNT) is promising, the short-circuit current density jSC is much lower than that for typical polymer/fullerene composites. Out-of-phase electron spin echo (ESE) technique with laser excitation of the P3HT/s-SWCNT composite was used to clarify the origin of the poor photogeneration of free charges. The appearance of out-of-phase ESE signal is a solid proof that the charge-transfer state of P3HT+/s-SWCNT− is formed upon photoexcitation and the electron spins of P3HT+ and s-SWCNT− are correlated. No out-of-phase ESE signal was detected in the same experiment with pristine P3HT film. The out-of-phase ESE envelope modulation trace for P3HT/s-SWCNT composite was close to that for the polymer/fullerene photovoltaic composite PCDTBT/PC70BM, which implies a similar distance of initial charge separation in the range 2–4 nm. However, out-of-phase ESE signal decay with delay after laser flash increase for P3HT/s-SWCNT composite was much faster, with a characteristic time of 10 µs at 30 K. This points to the higher geminate recombination rate for the P3HT/s-SWCNT composite, which may be one of the reasons for the relatively poor photovoltaic performance of this system.
A NEW LOOK AT THE LOCAL WHITE DWARF POPULATION

We have conducted a detailed new survey of the local population of white dwarfs lying within 20 pc of the Sun. A new revised catalog of local white dwarfs containing 122 entries (126 individual degenerate stars) is presented. This list contains 27 white dwarfs not included in a previous list from 2002, as well as new and recently published trigonometric parallaxes. In several cases new members of the local white dwarf population have come to light through accurate photometric distance estimates. In addition, a suspected new double degenerate system (WD 0423+120) has been identified. The 20 pc sample is currently estimated to be 80% complete. Using a variety of recent spectroscopic, photometric, and trigonometric distance determinations, we re-compute a space density of 4.8 ± 0.5 × 10−3 pc−3 corresponding to a mass density of 3.2 ± 0.3 × 10−3 M☉ pc−3 from the complete portion of the sample within 13 pc. We find an overall mean mass for the local white dwarfs of 0.665 M☉, a value larger than most other non-volume-limited estimates. Although the sample is small, we find no evidence of a correlation between mass and temperature in which white dwarfs below 13,000 K are systematically more massive than those above this temperature. Within 20 pc 25% of the white dwarfs are in binary systems (including double degenerate systems). Approximately 6% are double degenerates and 6.5% are Sirius-like systems. The fraction of magnetic white dwarfs in the local population is found to be 13%.
Phase Distribution of High-Pressure Steam-Water Flow at Large-Diameter Tee Junctions (Data Bank Contribution)

Experimental data are presented for the phase distribution of high pressure (2.75 to 5.5 MPa) steam-water mixtures at horizontal, equal-sided dividing tee junctions of two different sizes (49.3 and 97.3 mm i.d.). These data correspond to wide ranges of inlet qualities, inlet superficial vapor velocities, and extraction rates. Influences of the independent parameters on the phase-distribution phenomenon are presented and discussed. Comparisons between the present data and existing models have shown that the applicability of some models can be extended to the present test conditions.
Causal Inference of Central Nervous System-Regulated Hormones in COVID-19: A Bidirectional Two-Sample Mendelian Randomization Study

We assessed the causal association of three COVID-19 phenotypes with insulin-like growth factor 1, estrogen, testosterone, dehydroepiandrosterone (DHEA), thyroid-stimulating hormone, thyrotropin-releasing hormone, luteinizing hormone (LH), and follicle-stimulating hormone. We used bidirectional two-sample univariate and multivariable Mendelian randomization (MR) analyses to evaluate the direction, specificity, and causality of the association between CNS-regulated hormones and COVID-19 phenotypes. Genetic instruments for CNS-regulated hormones were selected from the largest publicly available genome-wide association studies of the European population. Summary-level data on COVID-19 severity, hospitalization, and susceptibility were obtained from the COVID-19 host genetic initiative. DHEA was associated with increased risks of very severe respiratory syndrome (odds ratio [OR] = 4.21, 95% confidence interval [CI]: 1.41–12.59), consistent with multivariate MR results (OR = 3.72, 95% CI: 1.20–11.51), and hospitalization (OR = 2.31, 95% CI: 1.13–4.72) in univariate MR. LH was associated with very severe respiratory syndrome (OR = 0.83; 95% CI: 0.71–0.96) in univariate MR. Estrogen was negatively associated with very severe respiratory syndrome (OR = 0.09, 95% CI: 0.02–0.51), hospitalization (OR = 0.25, 95% CI: 0.08–0.78), and susceptibility (OR = 0.50, 95% CI: 0.28–0.89) in multivariate MR. We found strong evidence for the causal relationship of DHEA, LH, and estrogen with COVID-19 phenotypes.
Bayesian inversion with Markov chains—I. The magnetotelluric one-dimensional case

SUMMARY We use Monte Carlo Markov chains to solve the Bayesian MT inverse problem in layered situations. The domain under study is divided into homogeneous layers, and the model parameters are the conductivity of each layer. We use an a priori distribution of the parameters which favours smooth models. For each layer, the a priori and a posteriori distributions are digitized over a limited set of conductivity values. The Markov chain relies on updating the model parameters during successive scanning of the domain under study. For each step of the scanning, the conductivity is updated in one layer given the actual value of the conductivity in the other layers. Thus we designed an ergodic Markov chain, the invariant distribution of which is the a posteriori distribution of the parameters, provided the forward problem is completely solved at each step. We have estimated the a posteriori marginal probability distributions from the simulated successive values of the Markov chain. In addition, we give examples of complex magnetotelluric impedance inversion in tabular situations, for both synthetic models and field situations, and discuss the influence of the smoothing parameter.
Image analysis and benthic ecology: Proceedings to analyze in situ long‐term image series

Long time series of underwater images have become a tool widely used within the benthic ecology research community. The development of new acquisition systems with bigger storing capacities lead researchers and scientists to deploy them for longer periods resulting in large amounts of data. This paper focuses on the first steps of analyzing large numbers of underwater images, which involves assessing the amount of valid data while assuming no technical problems. The question here addressed is how many of the in situ images can reliably be really used for benthic ecology purposes. To answer this question, we propose a method to eliminate nonvalid images and use it with four different sets of time‐lapsed images acquired for long periods ranging from 73 to 371 ds in a row. The results show that elimination of between 8% and 22% of the images is possible depending on the data set. The main advantage of the method is easing and accelerating automation of subsequent analysis.
p-Xylene Oxidation to Terephthalic Acid: New Trends

Large-scale terephthalic acid production from the oxidation of p-xylene is an especially important process in the polyester industry, as it is mainly used in polyethylene terephthalate (PET) manufacturing, a polymer that is widely used in fibers, films, and plastic products. This review presents and discusses catalytic advances and new trends in terephthalic acid production (since 2014), innovations in terephthalic acid purification processes, and simulations of reactors and reaction mechanisms.
High-Dose Intravenous Steroid Treatment Seems to Have No Long-Term Negative Effect on Bone Mineral Density of Young and Newly Diagnosed Multiple Sclerosis Patients: A Pilot Study

High-dose intravenous steroid treatment (HDIST) represents the first choice of treatment for multiple sclerosis (MS) relapses. Chronic oral glucocorticoid (GC) administration correlates with bone loss whereas data regarding HDIST in MS are still conflicting. Twenty-five newly diagnosed MS patients (NDMSP) (median age: 37 years) were prospectively studied for the effects of HDIST on bone mineral density (BMD) and bone metabolism. Patients received 1000 mg methylprednisolone intravenously every day for 5 days followed by oral prednisolone tapering over 21 days. Bone metabolism indices were determined prior to GC, on days 2, 4, 6, and 90, and at months 6, 12, 18, and 24 post GC therapy. Femoral, lumbar-spine BMD, and whole-body measurement of adipose/lean tissue were assessed prior to GC-administration and then every six months. Ten patients completed the study. N-terminal-propeptide-procollagen-type-1 and bone-specific alkaline phosphatase showed a significant increase at day-90 (p < 0.05). A transient non-significant fall of BMD was observed at 6 months after GC-administration, which subsequently appeared to be restored. We conclude that HDIST seems not to have long-term negative effects on BMD, while the observed transient increase of bone formation markers probably indicates a high bone turnover phase to GC-administration. Additional prospective studies with larger sample size are needed.