Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotional Processing Impairments in Apathetic Patients with Parkinson's Disease: An ERP Study in Early Time Windows

We investigated emotional processing in apathetic patients with Parkinson's disease (PD) by observing components of event-related potentials (ERPs) in early time windows. Forty PD patients and 21 healthy controls (HCs) were enrolled. The Starkstein Apathy Scale (SAS) was used to divide the PD patients into apathetic and nonapathetic groups. Cognitive function was evaluated by the forward and backward Digit Span tests, Trail Making Test (TMT), and Word Fluency Test. The participants were required to recognize positive, neutral, and negative emotional faces and engage in an emotion categorization task while EEG was recorded. The time to completion for the TMT (Part A and Part B) from highest to lowest was in the order of apathetic group > nonapathetic group > HC group. Compared with the nonapathetic and HC groups, in the apathetic group, P100 amplitudes were smaller for positive expressions in the right hemisphere and latencies were longer for positive expressions in the left hemisphere, while latencies were longer for neutral expressions bilaterally. Compared with the nonapathetic group, in the apathetic group, N170 amplitudes were attenuated and latencies were delayed for neutral and negative expressions in the right hemisphere. A trend towards larger N170 amplitudes in the right hemisphere than in the left was observed in the nonapathetic and HC groups, but this difference was not significant in the apathetic group. In the apathetic group, bilateral P100 amplitudes elicited by negative expressions were negatively correlated with SAS scores, and SAS scores were positively correlated with Part B of the TMT. N170 amplitudes elicited by negative expressions in the right hemisphere were negatively correlated with SAS in the apathetic group and with Part B of TMT in both PD groups. Our findings suggested that emotional processing was impaired in apathetic PD patients and that the right hemisphere was more sensitive to reflecting this impairment in the early time windows of ERPs.
Space-time processing for broadband wireless access

We present an overview of research activities on space-time coding for broadband wireless transmission performed at AT&T Shannon Laboratory over the past two years. The emphasis is on physical layer modem algorithms such as channel estimation, equalization, and interference cancellation. However, we also discuss the impact of space-time coding gains at the physical layer on throughput at or above the networking layer. Furthermore, we describe a flexible graphical user interface attached to our physical layer simulation engine in order to explore the performance of space-time codes under a variety of practical transmission scenarios. Simulation results for the EDGE cellular system and the 802.11 wireless LAN environment are presented.
The cAMP Pathway Amplifies Early MyD88-Dependent and Type I Interferon-Independent LPS-Induced Interleukin-10 Expression in Mouse Macrophages

Interleukin-10 (IL-10) is a key anti-inflammatory cytokine, secreted by macrophages and other immune cells to attenuate inflammation. Autocrine type I interferons (IFNs) largely mediate the delayed expression of IL-10 by LPS-stimulated macrophages. We have previously shown that IL-10 is synergistically expressed in macrophages following a costimulus of a TLR agonist and cAMP. We now show that the cAMP pathway directly upregulates IL-10 transcription and plays an important permissive and synergistic role in early, but not late, LPS-stimulated IL-10 mRNA and protein expression in mouse macrophages and in a mouse septic shock model. Our results suggest that the loss of synergism is not due to desensitization of the cAMP inducing signal, and it is not mediated by a positive crosstalk between the cAMP and type I IFN pathways. First, cAMP elevation in LPS-treated cells decreased the secretion of type I IFN. Second, autocrine/paracrine type I IFNs induce IL-10 promoter reporter activity only additively, but not synergistically, with the cAMP pathway. IL-10 promoter reporter activity was synergistically induced by cAMP elevation in macrophages stimulated by an agonist of either TLR4, TLR2/6, or TLR7, receptors which signal via MyD88, but not by an agonist of TLR3 which signals independently of MyD88. Moreover, MyD88 knockout largely reduced the synergistic IL-10 expression, indicating that MyD88 is required for the synergism displayed by LPS with cAMP. This report delineates the temporal regulation of early cAMP-accelerated vs. late type I IFN-dependent IL-10 transcription in LPS-stimulated murine macrophages that can limit inflammation at its onset.
Multiresolution mesh morphing

We present a new method for user controlled morphing of two homeomorphic triangle meshes of arbitrary topology. In particular we focus on the problem of establishing a correspondence map between source and target meshes. Our method employs the MAPS algorithm to parameterize both meshes over simple base domains and an additional harmonic map bringing the latter into correspondence. To control the mapping the user specifies any number of feature pairs, which control the parameterizations produced by the MAPS algorithm. Additional controls are provided through a direct manipulation interface allowing the user to tune the mapping between the base domains. We give several examples of aesthetically pleasing morphs which can be created in this manner with little user input. Additionally we demonstrate examples of temporal and spatial control over the morph.
Body adiposity index, body mass index, and body fat in white and black adults.

To the Editor: Body mass index (BMI) is widely used as a proxy for body fat and has been shown to correlate with other measures of adiposity.1 However, its use is limited by differences in body fatness for a given BMI across age, sex, and race.2–3 To address this limitation, Bergman et al. developed the body adiposity index (BAI) in samples of Mexican-Americans and blacks.4 However, no sex-specific information was provided, and it is unknown how well BAI performs in whites. We investigated the sex-specific relationship between both BMI and BAI and body fat in white and black adults.
Population attributable fraction of leading non-communicable cardiovascular diseases due to leisure-time physical inactivity: a systematic review

Objective The aim of this systematic review was to investigate the methods used for estimating the population attributable fraction (PAF) to leisure-time physical inactivity (PI) of coronary artery diseases, hypertension and stroke in order to provide the best available estimate for PAF. Design Systematic review. Data sources Four electronic databases (MEDLINE/PubMed, EMBASE, SPORTDiscus, and Cumulative Index to Nursing and Allied Health Literature) were searched from inception to August 2018. Eligibility criteria for selecting studies This review included prospective cohort studies, with men and women aged ≥18 years old, investigating the PAF attributable to leisure-time PI related to coronary artery diseases, hypertension and stroke. Results The PAF estimates of the three studies included were 13% (3%–22%) for ‘stage-1 hypertension’ subtype incidence due to ‘non-regular exercise’; 25% (10.4%–35.8%) for ‘stage-2 hypertension’ subtype incidence due to ‘activity of daily living’ and ‘vigorous-intensity sports’; and 8.5% (1.7%–16.7%) for ‘total: fatal and non-fatal’ cardiovascular events of ‘incidence and mortality’ endpoints due to non-accumulation of 550 kcal/week (subsets not specified). Conclusions The PAF estimate exhibited a protective dose–response relationship between hypertension and an increased amount of energy expenditure of leisure-time PI. In order to enhance accuracy of PAF estimates, the following steps are recommended: (1) to clearly define and state the working definition of leisure-time PI and dose using a reliable and valid objective measurement tool; (2) use a clear definition of outcome subtypes and endpoints using reliable and valid objective measures; and (3) estimate PAF using modelling techniques based on prospective data and ensuring to report 95% CI.
Protein denaturation during freezing and thawing in phosphate buffer systems: monomeric and tetrameric beta-galactosidase.

During freezing in sodium and potassium phosphate (NaP and KP) buffer solutions, changes in pH may impact the stability of proteins. Since the degradation pathways for the model proteins, monomeric and tetrameric beta-galactosidase (beta-gal), chosen for this study are governed by conformational changes (i.e., physical instability) as opposed to chemical transformations, we explored how the stresses of freezing and thawing alter the protein's native structure and if preservation of the native conformation during freeze-thawing is a requisite for optimal recovery of activity. During freezing in NaP buffer, a significant pH decrease from 7.0 to as low as 3.8 was observed due to the selective precipitation of the disodium phosphate; however, the pH during freezing in KP buffer only increased by at most 0.3 pH units. pH-induced inactivation was evident as seen by the lower recovery of activity when freeze-thawing in NaP buffer as compared to KP buffer for both sources of beta-gal. In addition, we investigated the effects of cooling rate and warming rate on the recovery of activity for monomeric and tetrameric beta-gal. Optimal recovery of activity for the NaP samples was obtained when the processing protocol involved a fast cool/fast warm combination, which minimizes exposure to acidic conditions and concentrated solutes. Alterations in the native secondary structure of monomeric beta-gal as measured by infrared spectroscopy were more significant when freezing and thawing in NaP buffer as opposed to KP buffer. Conformational and activity analyses indicate that pH changes during freezing in NaP buffer contribute to denaturation of beta-gal. These results suggest that proteins formulated in NaP buffer should be frozen and thawed rapidly to minimize exposure to low pH and high buffer salts.
Integrated DC-DC Converters for Adaptive Ultra-Low-Energy Processors

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto. fi Author Matthew Turnquist Name of the doctoral dissertation Integrated DC-DC Converters for Adaptive Ultra-Low-Energy Processors Publisher School of Electrical Engineering Unit Department of Microand Nanosciences Series Aalto University publication series DOCTORAL DISSERTATIONS 216/2016 Field of research Electronic circuit design Manuscript submitted 19 August 2015 Date of the defence 21 January 2016 Permission to publish granted (date) 19 November 2015 Language English Monograph Article dissertation (summary + original articles) Abstract There is an emerging class of energy-constrained adaptive processors that operate primarily at near-threshold (NT) voltages. Operating at NT significantly reduces energy consumption but avoids the large variance and performance penalties of sub-threshold. NT processors are useful for sensor-based platforms within ultra-portable electronics that require minimum energy consumption. Typically, the NT voltages are supplied by a DC-DC converter. Energy consumption of the DC-DC converter/processor system is proportional to the DC-DC's conversion efficiency. Thus, supplying the NT voltage with high efficiency is essential in realizing ultra-low-energy consumption. High efficiency over an increasingly large power range (due to large differences in sleep and active power levels) also require careful consideration. Besides the challenges in efficiency, the DC-DC converter should be fully integrated to meet the increasingly small form factor requirements of modern ultra-portable electronics. Research work presented in this thesis addresses the previous challenges by introducing new NT DC-DC converters, new techniques for reducing the increasingly dominant DC-DC control circuitry power losses, and new DC-DC/processor co-design methodologies. There are three main focus areas within the thesis: SC DC-DC converters, adaptive processors, and DC-DC converter/adaptive processor systems. The thesis gives the necessary background of DC-DC converters and adaptive processors. The research work is demonstrated with five integrated circuit (IC) implementations and ten publications. Three of the IC implementations are fully integrated SC DC-DC converters. A step-down Dickson topology in 28 nm CMOS is first presented. An improved Dickson converter and a selfoscillating converter are then presented. Both of these converters are built in 28 nm UTBB FDSOI, and both take advantage of the strong impact of back-gate biasing in order to improve efficiency. Practical design considerations of the converter's input voltage are shown with a prototype Li-ion battery. All three of the implemented DC-DC converters are measured with adaptive (processor) loads. The final two IC implementations are adaptive processors. Both of the processors are built in 65 nm CMOS. The processors use an adaptive scheme called timing-error detection (TED) to ensure reliability at NT voltages. One of the processors is the first-known TED processor
Online Latent Structure Training for Language Acquisition

A fundamental step in sentence comprehension involves assigning semantic roles to sentence constituents. To accomplish this, the listener must parse the sentence, find constituents that are candidate arguments, and assign semantic roles to those constituents. Where do children learning their first languages begin in solving this problem? Even assuming children can derive a rough meaning for the sentence from the situation, how do they begin to map this meaning to the structure and the structure to the form of the sentence? In this paper we use feedback from a semantic role labeling (SRL) task to improve the intermediate syntactic representations that feed the SRL. We accomplish this by training an intermediate classifier using signals derived from latent structure optimization techniques. By using a separate classifier to predict internal structure we see benefits due to knowledge embedded in the classifier's feature representation. This extra structure allows the system to begin to learn using weaker, more plausible semantic feedback.
BIO-BASED POLYURETHANE PREPARED FROM RENEWABLE FEEDSTOCKS

Non-isocyanate polyurethane (NIPU)s were prepared by reacting carbonated soybean oil with kraft lignin using two pot reactions. In the first stage, epoxidized soybean oil (ESBO) reacted with carbon dioxide to form carbonated soybean oil (CSBO) with tetra-butylammonium bromide (TBAB) as the catalyst. In the second stage, urethane monomer was formed from the reaction of CSBO with 3-aminopropyltriethoxylsilane (APES) and was reacted with the kraft lignin. The reaction was catalyzed by lithium chloride and the NIPU was cured both at room temperature and at 70 oC. Effects of lignin composition (20 – 50 wt%) on the NIPU mechanical properties were studied. Fourier transform infrared spectroscopy (FTIR) analysis was used to determine the structure of the lignin, CSBO, and lignin polyurethane. Tensile strength of the NIPU was much more improved when the polymer was cured at elevated temperature compared to when cured at room temperature. On the other hand, room temperature curing favoured high elongation at break.
Çoklu Veri Füzyonu Tabanlı İç Ortam Konumlandırma ve Takip Sistemi Tasarımı

Bu tez calismasinda alinan sinyal gucu ve ivme olcumleri kullanilarak ic ortam konumlandirma sistemi calisilmistir. Alinan sinyal gucu ve ivmeolcer ile ayri ayri yapilan konumlandirma calismalarinin ardindan bu iki veri farkli tipte Kalman filtresinde fuzyonda kullanilarak ic ortamda konumlandirma ve takip konusu uzerine calisilmistir. Alinan sinyal gucu ile yapilan calismalarda ic ortamda yol kayip katsayisi olasi farkli anten konumlari ve bunun sonucu olarak farkli anten oruntuleri kesisimleri dikkate alinarak hesaplanmistir. Simulasyon ortaminda trilaterasyon yontemi kullanilarak farkli standart sapmalara sahip gurultu sinyalleri ile alinan sinyal gucu tabanli konumlandirma hedef hareketli ve hedef sabitken yapilmistir. Sayisal integral alma yontemleri kullanilarak ivme verisinden konum hesaplanmistir. Ivmeolcer tabanli konumlandirmada iki farkli ivmeolcer modeli cikarilmis ve bu modeller uzerinden iki farkli algoritma ile hiz ve konum hesaplanmistir. Farkli ivme modelleri ile farkli iki konum ve hiz hesaplama algoritmasi simulasyon ortaminda test edilmistir. Secilen algoritma kullanilarak elde edilen hiz verisi, veri fuzyonunda ekstra girdi olarak kullanilmistir. Ivme ve alinan sinyal gucu olcumlerini veri fuzyonunda kullanmak amaciyla genisletilmis Kalman filtresi uygulanmistir. Surec gurultusunun Genisletilmis Kalman filtresinin kestirim performansina etkisi uretilen gurultusuz ve gurultulu hareket verileri uzerinden incelenmistir. Genisletilmis Kalman filtresinde ivme ve alinan sinyal gucu verilerine ek olarak, hiz verisinin fuzyona dâhil edilmesinin konum kestirim performansina etkileri incelenmistir. Alinan sinyal gucu gibi gurultu sinyalinin modellenmesi zor ve gurultu karakteristigi degisken verilerin kullanildigi sistemlerde olcume ve surece ait gurultu kovaryanslarini uyarlanir olarak hesaplayan uyarlanir Kalman filtresi tezde calisilmistir. Uyarlanir Kalman filtresinin degisken surec gurultulerinde konum kestirim performansi incelenmistir. Ayrica, alinan sinyal gucu, ivme ve hiz verilerine eklenen standart sapmasi degisen gurultu sinyalleri ile genisletilmis Kalman filtresi ve uyarlanir genisletilmis Kalman filtresinin konum kestirim performanslari simulasyonlar yapilarak karsilastirilmistir. Tez calismasinda kapali ortamda deneysel veri toplamak ve simulasyonlar ile elde edilen sonuclari deneysel veriler uzerinde gozlemlemek amaciyla bir test duzenegi tasarlanmistir. Sistemde sabit hareketli dugumler arasinda alinan sinyal gucu olcumu yapan ve olculen degeri sayisal sinyal islemcisine gonderen, ivmeolcerden ve dugumlerden alinan ham verileri anlamlandiran ve veri kaydediciye istenilen frekansta gonderen gercek zamanliya yakin yazilimlar gelistirilmistir. Simulasyonlardan elde edilen cikarimlar, veri kaydedicide kayit altina alinan deneysel veriler uzerinde uygulanmis konum kestirim ciktilari gosterilmistir.
Semi-supervised Transfer Learning for Convolutional Neural Networks for Glaucoma Detection

Convolutional neural network (CNN) can be applied in glaucoma detection for achieving good performance. However, its performance depends on the availability of a large number of the labelled samples for its training phase. To solve this problem, this paper present a semi-supervised transfer learning CNN model for automatic glaucoma detection based on both labeled and unlabeled data. First, a pre-trained CNN from non-medical data is fine-tuned and trained in a supervised fashion using the labeled data. The self-learning approach is then used to predict the labels for the unlabeled data and utilize it for training. The experimental results on the RIM-ONE database demonstrate the effectiveness of the proposed algorithm despite the lack of initial labeled samples.
RNA-Seq-Based Gene Expression Pattern and Morphological Alterations in Chick Thymus during Postnatal Development

The thymus is a lobulated unique lymphoid immune organ that plays a critical role in the selection, development, proliferation, and differentiation of T cells. The thymus of developing chickens undergoes continued morphological alterations; however, the biomolecular and transcriptional dynamics of the postnatal thymus in avian species is not clear yet. Therefore, the thymuses from chickens at different stages of development (at weeks 0, 1, 5, 9, 18, and 27) were used in the present study. The RNA-seq method was used to study the gene expression patterns. On average, 24120819 clean reads were mapped, differentially expressed genes (DEGs) were identified on the basis of log values (fold change), including 744 upregulated and 425 downregulated genes. The expression pattern revealed by RNA-seq was validated by quantitative real-time PCR (qPCR) analysis of four important genes, which are PCNA, CCNA2, CCNB2, and CDK1. Thus, the current study revealed that during postnatal development, the thymus undergoes severe atrophy. Thymus structure was damaged and gene expression changed dramatically, especially at the 27th week of age. Moreover, we found significant changes of several signaling pathways such as the cytokine-cytokine receptor interaction and cell cycle signaling pathways. Hence, it may be inferred that those signaling pathways might be closely related to the postnatal chicken thymus development.
A cognitive agent architecture for feedback control scheme design

We present a novel architecture for the design of feedback control schemes, aiming to automate the cognitive process performed by human experts when designing control schemes for certain systems. The work starts with the identification of types of cyber-physical modules participating in a feedback control scheme. Each module is defined as a functional mapping between inputs-vectors and an output vector. The inputs and outputs are then mapped to a semantic space formed by linguistic variables that model the expert knowledge. These semantic annotations of the modules are then exploited by a Cognitive Agent with semantic reasoning capabilities, to achieve the online configuration of a feedback control scheme, given a set of specifications and a database of available modules' implementations. The adopted knowledge modelling and reasoning techniques are driven by past efforts of the World Wide Web Consortium on the semantic composition of Web services. The applicability of the method is tested via a paper-based simulation of a use-case from the smart buildings domain.
My WorkSphere: Integrative work environment for grid-unaware biomedical researchers and applications

In order to deliver cyberinfrastructure to the general scientific and biomedical research community, transparent access and ease of use are of critical importance. Applications in systematic modeling of biological processes across scales of time and length demand more and more sophisticated algorithms and larger and longer simulations. The increased level of sophistication requires that cyberinfrastructure developers either work closely with the applications scientists, or develop middleware that flattens the learning curve for these scientists to use the grid willingly and transparently. Many life sciences researchers prefer to run applications in the grid environment without modifications, and without knowledge of specific computational resources being utilized. Here we report the latest advances in the use of Gfarm-FUSE (Grid Data Farm-Filesystem in UserSpaceE) as a computational data grid, with CSF4 (Community Scheduler Framework 4) as the metascheduler, through a GridSphere portal based environment, termed My WorkSphere. We describe the design and performance of this transparent grid computing environment using bioinformatics and computational biology applications as examples. All the components developed or utilized are open source and available freely.