Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal trends in the incidence of multiple sclerosis

Background: Multiple sclerosis (MS) has been traditionally considered to be more frequent in women and in regions more distant from the equator. However, recent reports suggest that the latitude gradient could be disappearing and that the female-to-male ratio among patients with MS has increased in the last decades. We have conducted a systematic review of incidence studies of MS to assess the overall incidence of MS and explore possible changes in the latitude gradient and the female-to-male ratio over time. Methods: Systematic review of incidence studies of MS published in Medline between 1966 and February 2007. Age- and sex-specific incidence rates were collected from eligible publications. We computed age-adjusted rates using the world population as standard, and assessed differences in rates according to latitude and period of case ascertainment. Additionally, we evaluated the association between period of case ascertainment and the female-to-male ratio. Results: The overall incidence rate of MS was 3.6 cases per 100,000 person-years (95% CI 3.0, 4.2) in women and 2.0 (95% CI 1.5, 2.4) in men. Higher latitude was associated with higher MS incidence, though this latitude gradient was attenuated after 1980, apparently due to increased incidence of MS in lower latitudes. The female-to-male ratio in MS incidence increased over time, from an estimated 1.4 in 1955 to 2.3 in 2000. Conclusion: The latitude gradient present in older incidence studies of multiple sclerosis (MS) is decreasing. The female-to-male MS ratio has increased in the last five decades.
Amyloid β‐Peptide(1‐42) Contributes to the Oxidative Stress and Neurodegeneration Found in Alzheimer Disease Brain

Oxidative stress is extensive in Alzheimer disease (AD) brain. Amyloid β‐peptide (1–42) has been shown to induce oxidative stress and neurotoxicity in vitro and in vivo. Genetic mutations that result in increased production of Aβ1–42 from amyloid precursor protein are associated with an early onset and accelerated pathology of AD. Consequently, Aβ1–42 has been proposed to play a central role in the pathogenesis of AD as a mediator of oxidative stress. In this review, we discuss the role of Aβ1–42 in the lipid peroxidation and protein oxidation evident in AD brain and the implications of such oxidative stress for the function of various proteins that we have identified as specifically oxidized in AD brain compared to control, using proteomics methods. Additionally, we discuss the critical role of methionine 35 in the oxidative stress and neurotoxic properties exhibited by Aβ1–42.
Index formulae for Stark units and their solutions

Let $K/k$ be an abelian extension of number fields with a distinguished place of $k$ that splits totally in $K$. In that situation, the abelian rank one Stark conjecture predicts the existence of a unit in $K$, called the Stark unit, constructed from the values of the $L$-functions attached to the extension. In this paper, assuming the Stark unit exists, we prove index formulae for it. In a second part, we study the solutions of the index formulae and prove that they admit solutions unconditionally for quadratic, quartic and sextic (with some additional conditions) cyclic extensions. As a result we deduce a weak version of the conjecture ("up to absolute values") in these cases and precise results on when the Stark unit, if it exists, is a square.
Temperature and shear rate characteristics of electrorheological gel applied to a clutch

This investigation reports the physical characteristics of electrorheological (ER) gels, which are a type of functional material having controlled surface friction. We previously developed slip clutches using ER gels sandwiched between electrodes, and verified their responses and controllability. We newly report the temperature and shear rate characteristics of ER gel in this study because the input and output electrodes of the clutch continuously slip past each other. While the temperature of ER gels increased when energized, the shear stress hardly changed. Instead, wearing and adaptation to the electrode affect the property. The shear rate hardly affected the shear stress in the high-shear-rate region. Conversely, the shear stress depended on the shear rate in the lower region.
Matching texture units for face recognition

For an image, texture unit (TU) is a small complete unit which characterizes the local texture of a given pixel and its neighborhood. Recently, TU-based approaches have been widely used in face recognition. This paper proposes a novel face representation and recognition approach based on TU. We make three major contributions: (1) we introduce a novel TU feature, Local Gabor Quarternary Pattern (LGQP), which incorporates both Gabor magnitude and phase information in a single TU code; (2) similarity measure of two TU images is treated as a tracking problem between two images, and we present a novel point-to-point matching (PPM) approach for TU similarity measure; (3) based on an integral histogram technique, the PPM similarity can be computed very rapidly. Experimental results on CMU-PIE and FERET data sets show that our method is able to reach very promising results.
Effect of First Tarsometatarsal Joint Derotational Arthrodesis on First Ray Dynamic Stability Compared to Distal Chevron Osteotomy

Background: Hallux valgus alters gait, compromising first ray stability and function of the windlass mechanism at the late stance. Hallux valgus correction should restore the stability of the first metatarsal. Comparative studies reporting the impact of different hallux valgus correction methods on gait are rare. We report the results of a case-control study between distal chevron osteotomy and first tarsometatarsal joint derotational arthrodesis (FTJDA). Methods: Two previously studied hallux valgus cohorts were matched: distal chevron osteotomy and FTJDA. Seventy-seven feet that underwent distal chevron osteotomy (chevron group) and 76 feet that underwent FTJDA (FTJDA group) were available for follow-up, with a mean of 7.9 years (range, 5.8-9.4 years) and 5.1 years (range, 3.0-8.3 years), respectively. Matching criteria were the hallux valgus angle (HVA) and a follow-up time difference of a maximum 24 months. Two matches were made: according to the preoperative HVA and the HVA at late follow-up. Matching provided 30 and 31 pairs, respectively. Relative impulses (%) of the first toe (T1) and metatarsal heads 1 to 5 (MTH1-5), weightbearing radiographs, and American Orthopaedic Foot & Ankle Society (AOFAS) (hallux metatarsophalangeal-interphalangeal [MTP-IP]) scores were studied. Results: The relative impulse of MTH1 was higher in the FTJDA group, whereas a central dynamic loading pattern was seen in the chevron group. This result remained when relative impulses were analyzed according to the postoperative HVA. The mean difference in the HVA at follow-up was 6.2 degrees (95% confidence interval, 3.0-9.5; P = .001) in favor of the FTJDA group. Conclusion: The dynamic loading capacity of MTH1 was higher in the FTJDA group in comparison to the chevron group. The follow-up HVA remained better in the FTJDA group. Level of Evidence: Level III, case-control study.
Twenty-four-hour ambulatory blood pressure in shift workers.

Blood pressure and heart rate of 15 male shift workers were measured every 15 minutes for 24 hours during three work shifts: morning, 4:00 AM to noon; afternoon, noon to 8:00 PM; and night, 8:00 PM to 4:00 AM. For each shift, 24-hour systolic and diastolic blood pressure showed a large "trough" (the low pressure span) and a continuous range of elevated pressure (the high pressure span). Fourier series were used to model the 24-hour blood pressure profiles. A careful examination of the residuals (measured minus predicted pressures) showed that four harmonics were necessary to describe the data accurately. The model enabled localization in each blood pressure profile of the high and low pressure spans that did not coincide with the subject's work and rest periods. The time and slope of blood pressure entering and leaving these spans could also be individually determined. Mean blood pressure during the high pressure span was the same for the three shifts, but mean blood pressure during the low pressure span was lower when the subject worked in the afternoon. During that shift, the systolic blood pressure slopes entering and leaving the low pressure span were steeper than during the two other shifts. The high pressure span was longest during the night shift and shortest during the afternoon shift. Therefore, a change in the working time profoundly perturbed the 24-hour blood pressure profile. (ABSTRACT TRUNCATED AT 250 WORDS)
Livelihood Diversification in Tropical Coastal Communities: A Network-Based Approach to Analyzing ‘Livelihood Landscapes’

Background Diverse livelihood portfolios are frequently viewed as a critical component of household economies in developing countries. Within the context of natural resources governance in particular, the capacity of individual households to engage in multiple occupations has been shown to influence important issues such as whether fishers would exit a declining fishery, how people react to policy, the types of resource management systems that may be applicable, and other decisions about natural resource use. Methodology/Principal Findings This paper uses network analysis to provide a novel methodological framework for detailed systemic analysis of household livelihood portfolios. Paying particular attention to the role of natural resource-based occupations such as fisheries, we use network analyses to map occupations and their interrelationships- what we refer to as ‘livelihood landscapes’. This network approach allows for the visualization of complex information about dependence on natural resources that can be aggregated at different scales. We then examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities in 5 western Indian Ocean countries. Network statistics, including in- and out-degree centrality, the density of the network, and the level of network centralization are compared along a multivariate index of community-level socioeconomic development and a gradient of human population density. The combination of network analyses suggests an increase in household-level specialization with development for most occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified. Conclusions/Significance The novel modeling approach introduced here provides for various types of livelihood portfolio analyses at different scales of social aggregation. Our livelihood landscapes approach provides insights into communities' dependencies and usages of natural resources, and shows how patterns of occupational interrelationships relate to socioeconomic development and population density. A key question for future analysis is how the reduction of household occupational diversity, but maintenance of community diversity we see with increasing socioeconomic development influences key aspects of societies' vulnerability to environmental change or disasters.
Handwritten Character Recognition Using Multiclass SVM Classification with Hybrid Feature Extraction

In this paper, we describe hybrid feature extraction for offline handwritten character recognition. The proposed technique is a hybrid of structural, statistical and correlation features. In the first step, the proposed technique identifies the type and location of some elementary strokes in the character. The strokes to be looked for comprise horizontal, vertical, positive slant and negative slant lines–as we observe that the structure of any character can be approximated with the help of a combination of simple straight line strokes. The strokes are identified by correlating different segments of the character with the chosen elementary shapes. These normalized correlation values at different segments of the character give correlation features. For making feature extraction more robust, we add in the second step certain structural/statistical features to the correlation features. The added structural/statistical features are based on projections, profiles, invariant moments, endpoints and junction points. This enhanced, powerful combination of features results in a 157-variable feature vector for each character, which we find adequate enough to uniquely represent and identify each character. Prior, handwritten character recognition problem has not been addressed the way our proposed hybrid feature extraction technique deals with it. The extracted feature vector is used during the training phase for building a support vector machine (SVM) classifier. The trained SVM classifier is subsequently used during the testing phase for classifying unknown characters. Experiments were performed on handwritten digit characters and uppercase alphabets taken from different writers, without any constraint on writing style. The obtained results were compared with some related existing approaches. Owing to the proposed technique, the results obtained show higher efficiency regarding classifier accuracy, memory size and training time as compared to these other existing approaches.
Comparison of radii sets, entropy, QM methods, and sampling on MM‐PBSA, MM‐GBSA, and QM/MM‐GBSA ligand binding energies of F. tularensis enoyl‐ACP reductase (FabI)

To validate a method for predicting the binding affinities of FabI inhibitors, three implicit solvent methods, MM‐PBSA, MM‐GBSA, and QM/MM‐GBSA were carefully compared using 16 benzimidazole inhibitors in complex with Francisella tularensis FabI. The data suggests that the prediction results are sensitive to radii sets, GB methods, QM Hamiltonians, sampling protocols, and simulation length, if only one simulation trajectory is used for each ligand. In this case, QM/MM‐GBSA using 6 ns MD simulation trajectories together with GBneck2, PM3, and the mbondi2 radii set, generate the closest agreement with experimental values (r2 = 0.88). However, if the three implicit solvent methods are averaged from six 1 ns MD simulations for each ligand (called “multiple independent sampling”), the prediction results are relatively insensitive to all the tested parameters. Moreover, MM/GBSA together with GBHCT and mbondi, using 600 frames extracted evenly from six 0.25 ns MD simulations, can also provide accurate prediction to experimental values (r2 = 0.84). Therefore, the multiple independent sampling method can be more efficient than a single, long simulation method. Since future scaffold expansions may significantly change the benzimidazole's physiochemical properties (charges, etc.) and possibly binding modes, which may affect the sensitivities of various parameters, the relatively insensitive “multiple independent sampling method” may avoid the need of an entirely new validation study. Moreover, due to large fluctuating entropy values, (QM/)MM‐P(G)BSA were limited to inhibitors’ relative affinity prediction, but not the absolute affinity. The developed protocol will support an ongoing benzimidazole lead optimization program. © 2015 Wiley Periodicals, Inc.
Retrograde versus Prograde Models of Accreting Black Holes

There is a general consensus that magnetic fields, accretion disks, and rotating black holes are instrumental in the generation of the most powerful sources of energy in the known universe. Nonetheless, because magnetized accretion onto rotating black holes involves both the complications of nonlinear magnetohydrodynamics that currently cannot fully be treated numerically, and uncertainties about the origin of magnetic fields that at present are part of the input, the space of possible solutions remains less constrained. Consequently, the literature still bears witness to the proliferation of rather different black hole engine models. But the accumulated wealth of observational data is now sufficient to meaningfully distinguish between them. It is in this light that this critical paper compares the recent retrograde framework with standard “spin paradigm” prograde models.
A Simple Classifier Based on a Single Attribute

Seeking a simple but effective classifier is exciting and meaningful in both machine leaning and data mining. As usual, simplicity and high performance are two sides of a same coin. Our aim is to explore an easy-to-use classifier without losing its effectiveness. On this account, a single attribute based classification (SAC) algorithm is proposed. SAC first splits the original data set into multi one-dimensional data sets. After that, it creates a base classifier, e.g. C4.5, for each one-dimensional data, and then selects all classifiers having the highest accuracy. At last, SAC uses these selected classifiers to make prediction and the most frequent label is assigned to the new instance. Results of classification accuracy on 16 data sets from UCI machine learning repository indicate that the proposed method performs better in comparison with classical OneR algorithm. Experiments on high-dimensional data are also conducted to evaluate the proposed method, which demonstrates its scalability.
Prestimulus brain activity predicts primacy in list learning

Brain activity immediately before an event can predict whether the event will later be remembered. This indicates that memory formation is influenced by anticipatory mechanisms engaged ahead of stimulus presentation. Here, we asked whether anticipatory processes affect the learning of short word lists, and whether such activity varies as a function of serial position. Participants memorized lists of intermixed visual and auditory words with either an elaborative or rote rehearsal strategy. At the end of each list, a distraction task was performed followed by free recall. Recall performance was better for words in initial list positions and following elaborative rehearsal. Electrical brain activity before auditory words predicted later recall in the elaborative rehearsal condition. Crucially, anticipatory activity only affected recall when words occurred in initial list positions. This indicates that anticipatory processes, possibly related to general semantic preparation, contribute to primacy effects.
Associations of lead biomarkers and delta-aminolevulinic acid dehydratase and vitamin D receptor genotypes with hematopoietic outcomes in Korean lead workers.

OBJECTIVES This study compares and contrasts associations of dimercaptosuccinic acid (DMSA)-chelatable lead, tibia lead, and blood lead with five hematopoietic outcomes and evaluates the effect modification of these relations by polymorphisms in the delta-aminolevulinic acid dehydratase (ALAD) and vitamin D receptor (VDR) genes. METHODS A cross-sectional study of 798 lead workers and 135 unexposed referents was performed. RESULTS The DMSA-chelatable lead, tibia lead, and blood lead levels ranged in the lead (Pb) workers from 4.8 to 2103 g, -7 to 338 g Pb/g bone mineral, and 4 to 86 g/dl, respectively. The mean of the hemoglobin, hematocrit, zinc protoporphyrin (ZPP), and urinary (ALAU) and plasma (ALAP) delta-aminolevulinic acid levels of the lead workers were 14.2 (SD 1.4) g/dl, 42.4 (SD 4.4)%, 80.2 (SD 63.5) g/dl, 2.1 (SD 3.7) mg/l, and 17.7 (20.6) g/ml, respectively. After adjustment for the covariates, tibia lead was associated with all five hematopoietic outcomes, while blood lead and DMSA-chelatable lead were associated only with ZPP, ALAP, and ALAU. A comparison of the regression coefficients, total model adjusted R2 values, and delta R2 values revealed that blood lead was the best predictor of ZPP, ALAP, and ALAU. Only tibia lead was significantly associated with hemoglobin and hematocrit levels, but the additional variance explained by tibia lead was (<1%). No clear effect modification of the relations between the lead biomarkers and hematopoietic outcomes studied was caused by ALAD or VDR genotype. CONCLUSIONS Lead must have a chronic, cumulative effect on hemoglobin and hematocrit levels, and any speculated mechanism cannot merely involve short-term plasma or target organ lead levels.
Simultaneous Application of Pressure-Infusion-Gyration to Generate Polymeric Nanofibers

Polymeric nanofibers are a fascinating class of material that has been widely used in a myriad of applications, including fiber reinforced composites, protective clothing, and chemical sensors. Here, the science of the combined application of external pressure, controlled infusion of polymer solution and gyration, which allows mass production of uniform polymeric nanofibers in a single step, is uncovered. Using poly(ethylene oxide) as an example this study shows the use of this novel method to fabricate polymeric nanofibers and nanofibrous mats under different combinations of processing parameters such as working pressure (1 × 105 to 3 × 105 Pa), rotational speed (10 000–36 000 rpm), infusion rate (500–5000 µL min−1), and fiber collection distance (4–15 cm). The morphologies of the nanofibers are characterized using scanning electron microscopy and anisotropy of alignment of fiber is studied using 2D fast Fourier transform analysis. A correlation between the product morphology and the processing parameters is established. The produced fibers are in a range of 50–850 nm at an orifice-to-collector distance of 10 cm. The results indicate that the pressure coupled infusion gyration (PCIG) offers a facile way for forming nanofibers and nanofiber assemblies.
Performance Optimization of Organic Solar Cells by Simulation and Characterization

Compared with silicon based solar cells, organic solar cells (OSCs) are less expensive alternatives because the thin and flexible OSCs can be easily fabricated onto the substrate by roll to roll painting. The current power conversion efficiency (PCE) of OSCs is about 8%. For commercialization of OSCs, a reasonable PCE (10%), at which those devices could generate electricity at a comparable cost to that of silicon based solar cells, is required. This requirement is the major driving force of this Ph.D. thesis to optimize OSCs with high PCE.To optimize the performance of OSCs, guidance from theoretical and simulation studies will play a key role. After solving coupled Poisson and Continuity equations, we first developed a macroscopic simulation tool which can precisely describe the current-voltage (J-V) characteristics of organic solar cells under known conditions such as device physical dimension (device layer thickness), physical parameters (absorption, carrier mobility), carrier generation/recombination kinetics, and boundary conditions. With this macroscopic simulation tool, the loss mechanism in BHJ OSCs is first investigated by fitting the simulated intensity dependent current-voltage (J-V) curves to experimental measurements. It is found that monomolecular recombination is dominant. Then, we have used the simulation tool to investigate performance optimization regarding thickness optimization, lowering bandgap of conjugated polymer, and balancing carrier transport in OSCs.For the characterization, single-walled carbon nanotubes (SWCNTs) were introduced in OSCs to increase the carrier mobility. It is observed that the performance of the device increased with small amount of SWCNTs but decreased if large amount of SWCNTs were introduced. The effects of semiconducting and metallic SWCNTs were explored by J-V characterization. It is found that semiconducting SWCNTs benefit the transport of photoexcited carrier while metallic SWCNTs introduce severe bimolecular recombination. Moreover, Kelvin Probe Force Microscopy is utilized to locally investigate the electrical role of SWCNTs in OSCs. The observation indicates that SWCNTs work as donor materials to transport holes.The simulation and characterization studies not only provide fundamental understanding on the physics of OSCs but also offer a feasible way to further optimize their performance.