Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence That the “Lid” Domain of Nicastrin Is Not Essential for Regulating γ-Secretase Activity*

Understanding of the structure of the γ-secretase complex consisting of presenilin (PS), anterior pharynx-defective 1 (APH-1), nicastrin (NCT), and presenilin enhancer 2 (PEN-2) is of significant therapeutic interest for the design of γ-secretase modulators for Alzheimer disease. The structure of γ-secretase revealed by cryo-EM approaches suggested a substrate binding mechanism for NCT, a bilobar structure that involved rotation of the two lobes around a central pivot and opening of a “lid” region that facilitates substrate recruitment. To validate this proposal, we expressed NCT that lacks the lid entirely, or a variety of NCT variants that harbor mutations at highly conserved residues in the lid region in NCT-deficient cells, and then assessed their impact on γ-secretase assembly, activity, and stability. In addition, we assessed the impact of mutating a critical residue proposed to be a pivot around which the two lobes of NCT rotate. Our results show that neither the mutations on the lid tested here nor the entire lid deletion has any significant impact on γ-secretase assembly, activity, and stability, and that NCT with the mutation of the proposed pivot rescues γ-secretase activity in NCT-deficient cells in a manner indistinguishable from WT NCT. These findings indicate that the NCT lid is not an essential element necessary for γ-secretase assembly, activity, and stability, and that rotation of the two lobes appears not to be a prerequisite for substrate binding and γ-secretase function.
Forward Field Computation with OpenMEEG

To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric Boundary Element Method, which is based on an extended Green Representation theorem. OpenMEEG is able to provide lead fields for four different electromagnetic forward problems: Electroencephalography (EEG), Magnetoencephalography (MEG), Electrical Impedance Tomography (EIT), and intracranial electric potentials (IPs). OpenMEEG is open source and multiplatform. It can be used from Python and Matlab in conjunction with toolboxes that solve the inverse problem; its integration within FieldTrip is operational since release 2.0.
The impact of eplerenone at different levels of risk in patients with systolic heart failure and mild symptoms: insight from a novel risk score for prognosis derived from the EMPHASIS-HF trial.

AIMS Our objective was to create a simple prognostic risk score for patients with systolic heart failure and mild symptoms. We then assessed the efficacy of eplerenone across different categories of risk. METHODS AND RESULTS The Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure trial (EMPHASIS-HF) was an international randomized trial, comparing eplerenone with placebo in 2737 patients with systolic heart failure and mild symptoms. The primary outcome was a composite of cardiovascular death or hospitalization for heart failure, over a median 2.1 years follow-up. Using multivariable Cox modelling age, sex, systolic blood pressure, estimated glomerular filtration rate, diabetes, BMI, haemoglobin, prior heart failure (HF) hospitalization, prior myocardial infarction/coronary artery bypass surgery (CABG), and heart rate were identified as strong independent risk factors. Estimates from the model were converted into a simple integer risk score which was categorized into three groups of low-, medium-, and high risk. In placebo patients, the rates (per 100 patient-years) for the primary outcome were 7.6, 19.0, and 39.4 in the low-, medium-, and high-risk groups, respectively. On eplerenone, these rates were reduced to 5.6, 12.2, and 24.2, respectively. Eplerenone was beneficial across all risk categories and the hazard ratios were similar. The absolute treatment benefit was greatest among those at highest risk. Similar patterns emerged for all-cause mortality and for all HF hospitalizations. CONCLUSION This easy-to-use integer risk score should be of value in quantifying individual patient risk in patients with systolic HF and mild symptoms. The relative benefits of eplerenone appeared consistent across the whole spectrum of risk, including those at lower risk.
Self-Stabilizing Disconnected Components Detection and Rooted Shortest-Path Tree Maintenance in Polynomial Steps

We deal with the problem of maintaining a shortest-path tree rooted at some process $r$ in a network that may be disconnected after topological changes. The goal is then to maintain a shortest-path tree rooted at $r$ in its connected component, $V_r$, and make all processes of other components detecting that $r$ is not part of their connected component. We propose, in the composite atomicity model, a silent self-stabilizing algorithm for this problem working in semi-anonymous networks under the distributed unfair daemon (the most general daemon) without requiring any {\em a priori} knowledge about global parameters of the network. This is the first algorithm for this problem that is proven to achieve a polynomial stabilization time in steps. Namely, we exhibit a bound in $O(\texttt{W}_{\max} {n_{\texttt{maxCC}}}^3 n)$, where $\texttt{W}_{\max}$ is the maximum weight of an edge, ${n_{\texttt{maxCC}}}$ is the maximum number of non-root processes in a connected component, and $n$ is the number of processes. The stabilization time in rounds is at most~$3{n_{\texttt{maxCC}}}+D$, where $D$ is the hop-diameter of $V_r$.
Cellular Energy Efficiency Evaluation Framework

In order to quantify the energy savings in wireless networks, the power consumption of the entire system needs to be captured and an appropriate energy efficiency evaluation framework must be defined. In this paper, the necessary enhancements over existing performance evaluation frameworks are discussed, such that the energy efficiency of the entire network comprising component, node and network level contributions can be quantified. The most important addendums over existing frameworks include a sophisticated power model for various base station (BS) types, which maps the RF output power radiated at the antenna elements to the total supply power of a BS site. We also consider an approach to quantify the energy efficiency of large geographical areas by using the existing small scale deployment models along with long term traffic models. Finally, the proposed evaluation framework is applied to quantify the energy efficiency of the downlink of a 3GPP LTE radio access network.
Robust and Efficient Page Rank for Word Sense Disambiguation

Graph-based methods that are en vogue in the social network analysis area, such as centrality models, have been recently applied to linguistic knowledge bases, including unsupervised Word Sense Disambiguation. Although the achievable accuracy is rather high, the main drawback of these methods is the high computational demanding whenever applied to the large scale sense repositories. In this paper an adaptation of the PageRank algorithm recently proposed for Word Sense Disambiguation is presented that preserves the reachable accuracy while significantly reducing the requested processing time. Experimental analysis over well-known benchmarks will be presented in the paper and the results confirm our hypothesis.
Urban Planning and Cultural Identity

Acknowledgements. Preface 1. Knowing Your Place: Urban Planning and the Spatiality of Cultural Identity 2. Planning, Memory and Identity 1: Acknowledging the Past in the City of Remorse 3. Planning, Memory and Identity 2: Erasing the Past in the City of the Victors 4. Place-making and the Failure of Multi-Culturalism in the African-American City 5. Cosmopolis Postponed: Planning and the Management of Cultural Conflict in the British and/or Irish City of Belfast 6. Conclusion: Environmental Citizenship as Civic Glue? Bibliography. Index.
BaCoN: Building a Classifier from only N Samples

We propose a model able to learn new object classes with a very limited amount of training samples (i.e. 1 to 5), while requiring near zero runtime cost for learning new object classes. After extracting Convolutional Neural Network (CNN) features, we discriminatively learn embeddings to separate the classes in feature space. The proposed method is especially useful for applications such as dish or logo recognition, where users typically add object classes comprising a wide variety of representations. Another benefit of our method is the low demand for computing power and memory, making it applicable for object classification on embedded devices. We demonstrate on the Food-101 dataset that even one single training example is sufficient to recognize new object classes and considerably improve results over the probabilistic Nearest Class Means
On the specific vaso‐dilating and plain muscle stimulating substances from accessory genital glands in man and certain animals (prostaglandin and vesiglandin)

EARLIER investigations [Euler, 1934a, 1935a] have shown that extracts and secretions from the human prostate gland and seminal vesicles, as well as seminal fluid, greatly lower the blood pressure after injection into animals and, even in small amounts, stimulate the isolated intestine and the uterus. At about the same time Goldblatt [1933, 1935] independently observed similar actions for human seminal plasma. The active substance is different from hitherto known autopharmacologic active substances, including the "substance P" [Euler & Gaddum, 1931; Gaddum & Schild, 1934]. The latter substance, which is obtained from intestinal muscle and brain, stimulates the isolated intestine and lowers the blood pressure; it has recently been shown to be an albumose-like substance [Euler, 1936]. Biological actions of extracts from the accessory genital glands have been described several times before, but the older observations have received no great attention, probably because the experimental data do not permit of definite conclusions as regards the nature and the specificity of the active constituents.
Automatic Term Extraction in Cryptology Based on Extension of Central String

The features of terms in Cryptology are analyzed. A method of automatic term extraction based on extension of central strings is addressed, in view of linguistic and statistical characteristics. Experimental results indicate that in contrast to common methods, the velocity of extraction in the proposed method is improved as well as precision and receivable recall. When applied to Ontology learning of Cryptology, an excellent performance has been achieved.
Pacific Asia Conference on Information Systems ( PACIS ) 6-18-2013 Sustainable Information Systems : Does It Matter ?

Using the Natural Resource Based View (NRBV) as our theoretical lens, green IS or sustainable IS is conceptualized as comprising the different dimensions of sustainability practices that can create competitive advantage for the organization. This study examines (i) the impact of adoption of sustainable IS on organizational performance; and (ii) the impact of the extent of adoption of sustainable IS on organizational performance. Analyzing secondary data on sustainable IS and performance measures of 115 global organizations, we find that the adoption of sustainable IS is positively associated with market valuation and innovativeness but not with profitability. However, sustainable IS organizations that have greater extent of adoption realize better profitability, market valuation and innovativeness. Implications of results for research and practice are discussed.
Active exploration in parameterized reinforcement learning

Online model-free reinforcement learning (RL) methods with continuous actions are playing a prominent role when dealing with real-world applications such as Robotics. However, when confronted to non-stationary environments, these methods crucially rely on an exploration-exploitation trade-off which is rarely dynamically and automatically adjusted to changes in the environment. Here we propose an active exploration algorithm for RL in structured (parameterized) continuous action space. This framework deals with a set of discrete actions, each of which is parameterized with continuous variables. Discrete exploration is controlled through a Boltzmann softmax function with an inverse temperature $\beta$ parameter. In parallel, a Gaussian exploration is applied to the continuous action parameters. We apply a meta-learning algorithm based on the comparison between variations of short-term and long-term reward running averages to simultaneously tune $\beta$ and the width of the Gaussian distribution from which continuous action parameters are drawn. When applied to a simple virtual human-robot interaction task, we show that this algorithm outperforms continuous parameterized RL both without active exploration and with active exploration based on uncertainty variations measured by a Kalman-Q-learning algorithm.
Policing Neighbourhoods: Exploring the Geographies of Crime, Policing and Performance Assessment

Recent developments under the Public Service Reform agenda in the United Kingdom have increasingly focused upon public accountability and the needs of local communities. Similarly, crime, fear of crime and the efficacy of public service delivery have become central to the domestic political debate in recent years, with all three main political parties campaigning on local policing issues in the run up to the 2005 General Election. This article explores the drive for robust performance assessment frameworks across different policing geographies and highlights some of the inconsistencies between the new localism agenda and current data infrastructures and analytical techniques. The significance of neighbourhood composition is expressed, and the potential of local analytical techniques for both performance assessment and resource determination is highlighted. Specifically, the value of geodemographic neighbourhood typologies, spatial analysis and geographical expertise in the evaluation of policing performance and the refinement of local service delivery is discussed.
The entrepreneurial personality : concepts, cases, and categories

1. Prologue 2. The Economists' View of the Entrepreneur 3. The Search for Entrepreneurial Traits 4. The Entrepreneur in Context 5. Categorization Processes and Procedures 6. Case Studies of Five Business Owners and Their Firms 7. Other Findings and the Application of Neural Networks 8. Epilogue.
Experimental and numerical assessment of low-frequency current distributions from UMTS and GSM mobile phones

The evaluation of the exposure from mobile communication devices requires consideration of electromagnetic fields (EMFs) over a broad frequency range from dc to GHz. Mobile phones in operation have prominent spectral components in the low-frequency (LF) and radio-frequency (RF) ranges. While the exposure to RF fields from mobile phones has been comprehensively assessed in the past, the LF fields have received much less attention. In this study, LF fields from mobile phones are assessed experimentally and numerically for the global system for mobile (GSM) and universal mobile telecommunications system (UMTS) communication systems and conclusions about the global (LF and RF) EMF exposure from both systems are drawn. From the measurements of the time-domain magnetic fields, it was found that the contribution from the audio signal at a normal speech level, i.e., −16 dBm0, is the same order of magnitude as the fields induced by the current bursts generated from the implementation of the GSM communication system at maximum RF output level. The B-field induced by currents in phones using the UMTS is two orders of magnitude lower than that induced by GSM. Knowing that the RF exposure from the UMTS is also two orders of magnitude lower than from GSM, it is now possible to state that there is an overall reduction of the exposure from this communication system.
On the validity and consistency of misjudgment of stepping ability in young and older adults

Disparities between perceived and actual physical abilities have been shown in older adults and may lead to balance loss or falls. However, it is unclear whether one’s misjudgment is an inherent trait and thus consistent across different tasks, and whether this misjudgment is age-related. We measured the degree of misjudgment in young and older adults on four different stepping tasks; stepping over a raised bar, crossing a declining cord by stepping over it at a self-selected height, crossing a virtual river by stepping over it at a self-selected width, and making a recovery step after release from an inclined position. Before comparison, we carefully checked the validity of the different tasks to determine the misjudgment. No substantial differences were found in the amplitude of the misjudgment between the age groups, and the degree of misjudgment did not transfer across different stepping tasks. However, since only one task (i.e., stepping over a raised bar) met our criteria for validly assessing one’s misjudgment, it remains unclear whether the degree of misjudgment is task-specific or an inherent trait. These findings stress the importance of testing the construct validity of the task, prior to the examination of the misjudgment of stepping ability.
Comparison of CoAP and CoCoA+ congestion control mechanisms for different IoT application scenarios

CoAP is a web transfer protocol that provides basic RESTful services for IoT devices. Since CoAP operates on top of UDP, CoAP must support additional congestion control and reliability mechanisms. However, CoAP is originally designed to allow implementations that do not maintain any end-to-end connection information. Thus, the default congestion control mechanisms are not capable of adapting to network conditions. A few enhancements of the basic congestion control mechanism of CoAP have been recently proposed, and CoCoA+ is commonly considered the most mature of these proposals. However, the shortcomings of CoCoA+ have not been sufficiently investigated in the literature. In this paper, we present an in-depth analysis of the congestion control mechanisms of CoCoA+ and CoAP for a variety of traffic patterns under realistic IoT setups. The results of this evaluation indicate that CoCoA+ can perform significantly worse than default CoAP, especially with bursty traffic and in networks with few clients as a result of an improper selection of the retransmission timeouts. Furthermore, large variability of RTO values in CoCoA+ makes difficult to meet end-to-end delay requirements of typical IoT monitoring applications.
Pathology Databanking and Biobanking in The Netherlands, a Central Role for PALGA, the Nationwide Histopathology and Cytopathology Data Network and Archive

Since 1991, a nationwide histopathology and cytopathology network and archive is in operation in The Netherlands under the name PALGA, encompassing all sixty-four pathology laboratories in The Netherlands. The overall system comprises decentralized systems at the participating laboratories, a central databank, and a dedicated communication and information exchange tool. Excerpts of all histopathology and cytopathology reports are generated automatically at the participating laboratories and transferred to the central databank. Both the decentralized systems and the central system perform checks on the quality and completeness of excerpts. Currently, about 42 million records on almost 10 million patients are stored in the central databank. Each excerpt contains patient identifiers, including demographic data and the so-called PALGA diagnosis. The latter is structured along five classification axes: topography, morphology, function, procedure, and diseases. All data transfer and communication occurs electronically with encryption of patient and laboratory identifiers. All excerpts are continuously available to all participating pathology laboratories, thus contributing to the quality of daily patient care. In addition, external parties may obtain permission to use data from the PALGA system, either on an ongoing basis or on the basis of a specific permission. Annually, 40 to 60 applications for permission to use PALGA data are submitted. Among external users are the Dutch cancer registry, population-based screening programs for cancer of the uterine cervix and breast cancer in The Netherlands, and individual investigators addressing a range of research questions. Many scientific papers and theses incorporating PALGA data have been published already. In conclusion, the PALGA system is a unique system that requires a minimal effort on the part of the participating laboratories, while providing them a powerful tool in their daily practices.
What Clinical Strategies are Applied for Botulinum Toxin Injection in the Oromandibular Region

Botulinum neurotoxin (BoNT) inhibits the release of acetylcholine from cholinergic nerve terminals in muscles or salivary glands. With reduced activation, the muscle activity or secretion decreases. Indications for medical, non‐cosmetic use of BoNT in the orofacial area include among others oromandibular dystonia, painful masseter hypertrophy, Frey's syndrome, and severe drooling. The chapter covers anamnestic characteristics of these conditions as well as clinical, electromyographic (EMG) and laboratory findings, treatment methods with guided injections, and outcome from systematic treatment controls and follow‐up examinations.
Iranian Dialectology and Dialectometry

This dissertation investigates the forces at work in the formation of a tightly knit but ultimately non-genetic dialect group. The Iranian languages, a genetic sub-branch of the larger Indo-European language family, are a group whose development has been profoundly affected by millennia of internal contact. This work is concerned with aspects of the diversification and disparification (i.e., the development of different versus near-identical features across languages) of this group of languages, namely issues pertaining to the development of the so-called West Iranian group, whose status as a legitimate genetic subgroup has long remained unclear. To address the phenomena under study, I combine a traditional comparative-historical approach with existing quantitative methods as well as newly developed quantitative methods designed to deal with the sort of linguistic situation that Iranian typifies. The studies I undertake support the idea that West Iranian is not a genetic subgroup, as sometimes assumed; instead, similarities between West Iranian languages that give the impression of close genetic relatedness have come about due to interactions between contact and parallel driftlike tendencies. I develop new methodologies which make it possible to demonstrate which similarities are due to contact and which are due to drift.
Semantic Textual Similarity in Quality Estimation

Quality Estimation (QE) predicts the quality of machine translation output without the need for a reference translation. This quality can be deﬁned differently based on the task at hand. In an attempt to focus further on the adequacy and informativeness of translations, we integrate features of semantic similarity into QuEst, a framework for QE feature extraction. By using methods previously employed in Semantic Textual Similarity (STS) tasks, we use semantically similar sentences and their quality scores as features to estimate the quality of machine translated sentences. Preliminary experiments show that ﬁnding semantically similar sentences for some datasets is difﬁcult and time-consuming. Therefore, we opt to start from the assumption that we already have access to semantically similar sentences. Our results show that this method can improve the prediction of machine translation quality for semantically similar sentences.