Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Cerebrospinal Fluid Aβ42 and Aβ40 are Related to White Matter Lesions in Cognitively Normal Elderly

Background: Low cerebrospinal fluid (CSF) levels of Aβ42 may be the earliest manifestation of Alzheimer’s disease (AD). Knowledge on how CSF Aβ interacts with different brain pathologies early in the disease process is limited. We examined how CSF Aβ markers relate to brain atrophy and white matter lesions (WMLs) in octogenarians with and without dementia to explore the earliest pathogenetic pathways of AD in the oldest old. Objective: To study CSF amyloid biomarkers in relation to brain atrophy and WMLs in 85-year-olds with and without dementia. Methods: 53 octogenarians took part in neuropsychiatric examinations and underwent both a lumbar puncture and a brain CT scan. CSF levels of Aβ42 and Aβ40 were examined in relation to cerebral atrophy and WMLs. Dementia was diagnosed. Results: In 85-year-olds without dementia, lower levels of both CSF Aβ42 and CSF Aβ40 were associated with WMLs. CSF Aβ42 also correlated with measures of central atrophy, but not with cortical atrophy. In participants with dementia, lower CSF levels of Aβ42 were related to frontal, temporal, and parietal cortical atrophy but not to WMLs. Conclusions: Our findings may suggest that there is an interrelationship between Aβ and subcortical WMLs in older persons without dementia. After onset of dementia, low CSF Aβ42, probably representing amyloid deposition in plaques, is associated with cortical atrophy. WMLs may be an earlier manifestation of Aβ deposition than cortical degeneration.
Effect of Substitution of Zn2+ and Zr4+ on Structural and Magnetic Properties of BaFe12O19 Powders

The Zn2+ and Zr4+-doped barium hexaferrite according to the stoichiometric formation BaFe(12-(2x /3))ZnxO19 and BaFe(12-(4x /3))ZrxO19 with x = 0, 0.1, 0.3 and 0.5 were prepared by conventional method using ball milling technique. These powders were calcined at various temperatures from 1000 °C to 1200 °C for 2 h. The structural, morphology and magnetic properties were carried out by X-ray diffraction (XRD), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM), respectively. The XRD confirmed the formation of main phase magneplumbite and the crystalline structure of samples is still hexagonal. Pure and dopes barium hexaferrite shows only single phase. The lattice parameter a and c increased with the Zn2+ and Zr4+ ion content increasing. The SEM results showed that the particles of pure BaFe12O19 were regular hexagonal while doped-samples showed spherical shape. After Fe3+ is partly substituted with Zn2+, the magnetic parameters like coercivity and saturation magnetization are decreased. On the other hand, with increasing Zr4+ ions, the coercive force and saturation magnetization are slightly increased. The behavior of magnetic properties of materials is explained by the combined effect of the coherent rotation of the magnetic domains and the replacements of Fe3+ by Zn2+ and Zr4+ ions in the tetrahedral and octahedral sites.
Direct Object Recognition Using No Higher Than Second or Third Order Statistics of the Image

Novel algorithms for object recognition are described that directly recover the transformations relating the image to its model. Unlike methods fitting the typical conventional framework, these new methods do not require exhaustive search for each feature correspondence in order to solve for the transformation. Yet they allow simultaneous object identification and recovery of the transformation. Given hypothesized % potentially corresponding regions in the model and data (2D views) --- which are from planar surfaces of the 3D objects --- these methods allow direct compututation of the parameters of the transformation by which the data may be generated from the model. We propose two algorithms: one based on invariants derived from no higher than second and third order moments of the image, the other via a combination of the affine properties of geometrical and the differential attributes of the image. Empirical results on natural images demonstrate the effectiveness of the proposed algorithms. A sensitivity analysis of the algorithm is presented. We demonstrate in particular that the differential method is quite stable against perturbations --- although not without some error --- when compared with conventional methods. We also demonstrate mathematically that even a single point correspondence suffices, theoretically at least, to recover affine parameters via the differential method.
Enhancing cybersecurity skills by creating serious games

Adversary thinking is an essential skill for cybersecurity experts, enabling them to understand cyber attacks and set up effective defenses. While this skill is commonly exercised by Capture the Flag games and hands-on activities, we complement these approaches with a key innovation: undergraduate students learn methods of network attack and defense by creating educational games in a cyber range. In this paper, we present the design of two courses, instruction and assessment techniques, as well as our observations over the last three semesters. The students report they had a unique opportunity to deeply understand the topic and practice their soft skills, as they presented their results at a faculty open day event. Their peers, who played the created games, rated the quality and educational value of the games overwhelmingly positively. Moreover, the open day raised awareness about cybersecurity and research and development in this field at our faculty. We believe that sharing our teaching experience will be valuable for instructors planning to introduce active learning of cybersecurity and adversary thinking.
Does eosinophilia and neutrophil to lymphocyte ratio affect hospital re-admission in cases of COPD exacerbation?

Introduction We aimed to assess the relationship between peripheral eosinophilia and neutrophil/lymphocyte ratio with hospital admissions and re-admissions with chronic obstructive pulmonary disease (COPD) exacerbations. Materials and Methods An observational cohort study was carried out in a tertiary teaching hospital. Subjects with previously diagnosed COPD and who were admitted as outpatients with acute exacerbations were included. The subjects' characteristics, complete blood count (CBC) parameters, neutrophil to lymphocyte rate (NLR), C-reactive protein (CRP), mean platelet volume (MPV) on admission and re-admission within the first 28 days. Patients were grouped according to their peripheral blood eosinophilia levels; group 1, > 2% (eosinophilic), group 2, ≤ 2% (non-eosinophilic or neutrophilic). The recorded data from the two groups were compared. Result 1490 eligible COPD subjects were enrolled. Approximately 42% were classified as eosinophilic. The non-eosinophilic group had a significantly higher leukocyte count, neutrophil percentage, and NLR than the eosinophilic group. The NLR value in patients with repeat re-admissions was higher than the average, i.e., 4.50 (p= 0.001). MPV and CRP measured on admission and re-admission were similar in both groups. The rate of hospital re-admission within 28 days was significantly higher in patients with a non-eosinophilic attack. Conclusions When a patient is admitted to outpatients with a NLR greater than 4.50 and with a non-eosinophilic exacerbation they have an increased risk of re-admission in the first month. Higher NLR values and non-eosinophilic exacerbations may be helpful for the early detection of potential acute attacks in COPD patients, and may be indicators for antibiotic management.
ARTISTIC ENGAGEMENT AT A MEMORY CARE FACILITY, VIA A TELEPRESENCE ROBOT

Abstract There is a growing body of research that shows participation in arts interventions (e.g., poetry, storytelling, music, and dance) can be beneficial for those living with dementia. The current study examines social interactions when the artist is not physically present, but in the room via a telepresence robot. Through the telepresence robot, dementia care residents were connected to a network of arts presenters. Using a checklist examining social behaviors (verbal and non-verbal), we assessed residents’ social engagement with the artist, other residents, and staff during these creative visits. Typical activities within the care facility were also observed. The observations were conducted on 10 individuals living within the memory care facility. Although the typical facility activities elicited social verbal behaviors, they tended to be more physical in nature and had a larger number of social nonverbal behaviors. When the behavior was verbal it tended to be more noises of excitement, such as “wooo” and “oh yeah. ” Although the artist engagement activities elicited social nonverbal behaviors, they tended to be more verbally engaging and there were a larger number of social verbal behaviors during these activities. With the artist engagement we observed residents spontaneously singing songs, and helping to create poetry. The facility was already using activities that allowed the residents to become physically engaged and with the addition of artist visits there was an increase in verbal engagement. By having greater options for residents to create engagement we may see people who don’t typically engage become more involved.
D Reconstruction of “ Inthe-Wild ” Faces in Images and Videos

3D Morphable Models (3DMMs) are powerful statistical models of 3D facial shape and texture, and among the state-of-the-art methods for reconstructing facial shape from single images. With the advent of new 3D sensors, many 3D facial datasets have been collected containing both neutral as well as expressive faces. However, all datasets are captured under controlled conditions. Thus, even though powerful 3D facial shape models can be learnt from such data, it is difficult to build statistical texture models that are sufficient to reconstruct faces captured in unconstrained conditions (“in-the-wild”). In this paper, we propose the first “in-the-wild” 3DMM by combining a statistical model of facial identity and expression shape with an “in-the-wild” texture model. We show that such an approach allows for the development of a greatly simplified fitting procedure for images and videos, as there is no need to optimise with regards to the illumination parameters. We have collected three new databases that combine “in-the-wild” images and video with ground truth 3D facial geometry, the first of their kind, and report extensive quantitative evaluations using them that demonstrate our method is state-of-the-art.
Recollections of My Life

Introducing a new hobby for other people may inspire them to join with you. Reading, as one of mutual hobby, is considered as the very easy hobby to do. But, many people are not interested in this hobby. Why? Boring is the reason of why. However, this feel actually can deal with the book and time of you reading. Yeah, one that we will refer to break the boredom in reading is choosing recollections of my life as the reading material.
The Incidence of Tuberculosis

There is much evidence that objectively gratifying results are obtainable in a relatively large number of conditions," even though failures have also been reported. In this respect it would be interesting to know whether the preparations of vitamin E employed were either of the two most potent and stable preparations, the d-alphatocopherol acetate and d-alpha-tocopherol acid succinate, and fOI' how long and in what dosage it was given.
Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System

Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.
Humor and Aging - A Mini-Review

Humor is one of the most important human activities, one that is enjoyed daily by people in every culture and at every age. However, very little is known about how aging affects humor experiences. Research suggests that elderly people enjoy humor more than younger people, but they have increasing difficulties in understanding jokes. Several cognitive mechanisms that may help explain this trend are discussed. Also, the amount of laughter exhibited by the elderly is smaller compared to young adults. In addition, the older population seems not to enjoy aggressive types of humor as much as the younger ones, and the elderly are especially sensitive to jokes referring to old age. Because most studies are cross-sectional, we cannot ignore possible cohort effects that might influence age differences in humor production and humor appreciation. Several future directions are mentioned with the hope for further research on the subject to follow.
A Privacy-Preserving Scheme for Incentive-Based Demand Response in the Smart Grid

The advanced metering infrastructure (AMI) in the smart grid provides real-time information to both grid operators and customers, exploiting the full potential of demand response (DR). However, it introduces new privacy threats to customers. Prior works have proposed privacy-preserving methods in the AMI, such as temporal or spatial aggregation. A main assumption in these works is that fine-grained data do not need to be attributable to individuals. However, this assumption does not hold in incentive-based demand response (IDR) programs where fine-grained metering data are required to analyze individual demand curtailments, and hence, need to be attributable. In this paper, we propose a privacy-preserving scheme for IDR programs in the smart grid, which enables the DR provider to compute individual demand curtailments and DR rewards while preserving customer privacy. Moreover, a customer can reveal his/her identity and prove ownership of his/her power usage profile in certain situations, such as legal disputes. We achieve both privacy and efficiency in our scheme through a combination of several cryptographic primitives, such as identity-committable signatures and partially blind signatures. As far as we know, we are the first to identify and address privacy issues for IDR programs in the smart grid.
MECHANICAL PROPERTIES AND RELIABILITY OF GLASS-ALUMINIUM COMPOSITE AS INSERT MOLD

Plastic injection mold made of tool steel is generally utilized for large lots production. Running for small lots of product is a new trend of demand, so that the mold would be relatively expensive and not competitive. The aim of the present work is to find an alternative material and process for low cost injection mold that suitable for small lots. For these reasons, aluminum-glassacrylic particulate composite would be proposed as a material for manufacturing of low cost plastic injection mold. In this work, an insert mold as part of the injection molding was selected for the case study. Composite was examined to know its characteristics. The part with size of (80mm x 10mm x 10mm) and (30mm x30mm x30mm) made of particulate composite material was selected as specimen. Material of the specimen was aluminum powders (<297 μm), glass powders (<74 μm) and acrylic powders (<74 μm); the volume ratio is 1:1:1. Acrylic was used for binder when composite made by layer manufacturing method, using Selective Heater Melting (SHM) machine. The specimen was prepared into three steps: manufacturing of composite (green specimen) by SHM machine, heating green specimen to burn up the acrylic, and resin impregnation. There were 3 types of specimens: green specimen before heating at 700°C, green specimen after heating at 700°C, and green specimen after heating at 700°C that continued by resin impregnation. Tests was performed to investigate its bending strength, surface hardness, surface roughness, and dimensional error. The other composite (specimen) was insert mold, made by layer manufacturing method, using SHM machine. Case study was carried out by testing an insert mold to know the reliability of insert mold. Bending strengths of green specimen, before and after heating at 700°C, were 2.07 and 8.23 MPa, respectively; and after resin impregnation was 17.15 MPa. Dimensional errors in the direction of X, Y, and Z-axis for green specimen of (30mm x 30mm x30mm) before heating at 700°C were 8.65, 2.7, and 3.8 mm, respectively; and after heating at 700°C were 7.90, 1.10 and 0.90 mm, respectively. Surface roughness of green specimen before and after heating at 700°C were 46.12 and 33.48 μm, respectively; and after resin impregnation was 12.17 μm. Surface hardness of specimen after resin impregnation was 14.199 BHN. The amount of plastic parts that could be produced by insert mold was 120 and 126 pieces. Although mechanical strength of this composite was lower than that of tool steel that used for common plastic injection mold, but this composite material was less expensive and suitable for small lots production.
ONLINE LEARNING WITH NOISE: A KERNEL-BASED POLICY-GRADIENT APPROACH

Various forms of noise are present in the brain. The role of noise in a exploration/exploitation trade-off is cast into the framework of reinforcement learning for a complex motor learning task. We present a simple and generic neuro-controler described by a linear projection from the input to the output spaces to which a gaussian independent noise is added. This stochastic controler can perform online-learning using a “direct policy-gradient” scheme. The reward signal is related to the sensory information, and no direct or inverse model of the system to control is needed. The task chosen (reaching with a multi-joint arm) is redundant and non-linear. The controler inputs are projected to a feature space of higher dimension using a topographic coding based on gaussian kernels. We show it possible, through a consistent noise level, to explore the environnment so as to find good control solution. Besides, the controler is able to adapt continuously to changes in the system dynamics. The general framework we present here should allow to build more realistic models of biological learning, in reason of its compatibility with Hebbian principles and straightforward extension to more complex stochastic neuronal models.
Exolytic and endolytic turnover of peptidoglycan by lytic transglycosylase Slt of Pseudomonas aeruginosa

Significance β-Lactam antibiotics are currently the most broadly used class of antibiotics. These antibiotics prevent bacterial cell wall from cross-linking, which leads to the accumulation of long non–cross-linked strands of peptidoglycan. Pseudomonas aeruginosa, a nefarious bacterial pathogen, attempts to repair this aberrantly formed peptidoglycan by the function of the lytic transglycosylase Slt. We document in the present report that Slt turns over the peptidoglycan by both scission of the glycosidic bonds from a terminus or in the middle of the peptidoglycan. In a series of seven X-ray crystal structures, we provide structural context to how these two reactions take place. These results disclose the details of bacterial response to the β-lactam antibiotic challenge. β-Lactam antibiotics inhibit cell-wall transpeptidases, preventing the peptidoglycan, the major constituent of the bacterial cell wall, from cross-linking. This causes accumulation of long non–cross-linked strands of peptidoglycan, which leads to bacterial death. Pseudomonas aeruginosa, a nefarious bacterial pathogen, attempts to repair this aberrantly formed peptidoglycan by the function of the lytic transglycosylase Slt. We document in this report that Slt turns over the peptidoglycan by both exolytic and endolytic reactions, which cause glycosidic bond scission from a terminus or in the middle of the peptidoglycan, respectively. These reactions were characterized with complex synthetic peptidoglycan fragments that ranged in size from tetrasaccharides to octasaccharides. The X-ray structure of the wild-type apo Slt revealed it to be a doughnut-shaped protein. In a series of six additional X-ray crystal structures, we provide insights with authentic substrates into how Slt is enabled for catalysis for both the endolytic and exolytic reactions. The substrate for the exolytic reaction binds Slt in a canonical arrangement and reveals how both the glycan chain and the peptide stems are recognized by the Slt. We document that the apo enzyme does not have a fully formed active site for the endolytic reaction. However, binding of the peptidoglycan at the existing subsites within the catalytic domain causes a conformational change in the protein that assembles the surface for binding of a more expansive peptidoglycan between the catalytic domain and an adjacent domain. The complexes of Slt with synthetic peptidoglycan substrates provide an unprecedented snapshot of the endolytic reaction.
An Agent-Based Approach to Interbank Market Lending Decisions and Risk Implications

In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending market. We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 U.S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literature. A key finding of this study is that risk preferences at the individual bank level can lead to unique interbank market structures that are suggestive of the capacity with which the market responds to surprising shocks.
e Films Grown by Laser Ablation

Pulsed laser ablation (PLA) has been used to grow barium ferrite films on AlzQ3 single crystal substrates. When deposition occurs in an oxidising atmosphere at high temperatures, the films are single BaFelz019 phase with very well orientation following the (001) texture, and exhibit a large perpendicular magnetic anisotropy. In this case, the microstructure and the anisotropy orientation are not influenced by variation of the oxygen pressure in the range 20-530 mtorr, but the coercivity and the remanence are affected. Films prepared without oxygen, are isotropic. XRD measurements reveal the absence of the BaFelzQp~ which becomes unstable. On the other hand, the presence of other phases as Ba2FehO1l and Fez03 is detected. The annealing study reveals the presence of the threshold temperature (620°C) for the appearance of the magnetisation and the anisotropy orientation. This temperature also corresponds to the onset in growth of the crystalline structure of barium ferrite. In the latter case, the coercivity was found to be greatly reduced by the increase in grain size at higher annealing tempera tures
On a circuit representation of the Hodgkin and Huxley nerve axon membrane equations

A circuit representation of the nerve axon membrane equations proposed by Hodgkin and Huxley is presented and discussed. In contrast with the usual circuit formulation found in the literature and based on 'time-varying conductances', all the elements of the present circuit are time-invariant and the whole structure is sufficiently detailed to become suitable for both theoretical and numerical investigations. In particular, this 'change of perspective' makes it possible to reproduce all the 'classical' results through the use of computer circuit analysis programmes and leads to some new considerations about the basic aspects of pulse generation mechanisms in the axon membrane.