Miracle-dz/UniFAR-FTUs huggingface dataset:
Journal Pre-proofs Detection of emerging neurodegeneration using Bayesian linear mixed-effect modeling Bayesian linear mixed-effect

Early detection of neurodegeneration, and prediction of when neurodegenerative diseases will lead to symptoms, are critical for developing and initiating disease modifying treatments for these disorders. While each neurodegenerative disease has a typical pattern of early changes in the brain, these disorders are heterogeneous, and early manifestations can vary greatly across people. Methods for detecting emerging neurodegeneration in any part of the brain are therefore needed. Prior publications have described the use of Bayesian linear mixed-eﬀects (BLME) modeling for characterizing the trajectory of change across the brain in healthy controls and patients with neurodegenerative disease. Here, we use an extension of such a model to detect emerging neurodegeneration in cognitively healthy individuals at risk for dementia. We use identiﬁedregionsofacceleratedvolumelosspriortooraccompanyingtheearliestsymptoms,and expanding across the brain over time, in all cases. The changes were detected in regions that are typicalforthelikelydiseasesaﬀectingeachpatient, includingmedialtemporalregionsinpatients at risk for Alzheimer’s disease, and insular, frontal, and/or anterior/inferior temporal regions in patients with likely or proven FTLD. In the cases where detailed histories were available, the ﬁrst regions identiﬁed were consistent with early symptoms. Furthermore, survival analysis in the ADNI cases demonstrated that the rate of spread of accelerated volume loss across the brain was a statistically signiﬁcant predictor of time to conversion to dementia. This method for detection of neurodegeneration is a potentially promising approach for identifying early changes due to a
ANN-based design of hybrid fractal antenna for biomedical applications

ABSTRACT In this research paper, the development of an artificial neural network (ANN) model for the designing of a compact dual-band hybrid fractal antenna (CDHFA) that covers Wireless Medical Telemetry Service and industrial, scientific and medical (ISM) bands are described. The projected CDHFA is designed by using 1.6mm thick, FR4 substrate whose permittivity is 4.4 and obtained by the combination of different fractal geometries. The dimensions of the projected CDHFA are interlinked with each other. A set of 80 CDHFAs with different dimensions is designed to obtain a data dictionary for the implementation of ANN. From the experimental results, it is depicted that the resonant frequencies are 1.4290 and 2.4380 GHz with S(1,1) values −12.4 and −15.72 dB, respectively. A comparison between feed forward back propagation network, generalised regression neural network and desired outputs in terms of average absolute error is also done. The simulation, experimental and ANN results are well matched that indicates the effectiveness and accuracy of the developed ANN model for biomedical applications.
A decision making system using Deep Learning for earthquake prediction by means of electromagnetic precursors

When a catastrophic event such as an earthquake (EQ) occurs, general guidelines related to the specific event particular location, must be dynamically adapted in near real time by ad-hoc team of experts in order to identify the most urgent recovery actions for the specific emergency. The procedure for hazard risk management, includes several pre and post disaster interventions to be considered in the preparedness and response phases of risk management. (STORM, 2018). In the case of EQs, the pre-disaster interventions, and level of preparedness are undoubtedly the most important phases in risk management. Therefore, possible EQ prediction, could help avoid disastrous effects caused by an EQ on vulnerable structures, such as these often located in cultural heritage sites. I this work, we propose a strategy for the calculation of the probability for a significant ( ) EQ occurrence in order to be co-evaluated within a decision making mechanism which could assist in reaching a high level of
Outcomes after HLA-matched sibling transplants or chemotherapy in children with B-precursor acute lymphoblastic leukemia in a second remission: a collaborative study of the Children’s Oncology Group and the Center for International Blood and Marrow Transplant Research. for in second CR

: 195 3090 Abstract The best treatment approach for children with B-precursor acute lymphoblastic leukemia (ALL) in second clinical remission (CR) after a marrow relapse is controversial. To address this question, we compared outcomes in 188 patients enrolled on chemotherapy trials and 186 HLA-matched sibling transplants, treated between 1991 and 1997. Groups were similar except that chemotherapy recipients were younger (median: 5 vs. 8 years) and less likely to have combined marrow and extra-medullary relapse (19% vs. 30%). To adjust for time-to-transplant bias, treatment outcomes were compared using left-truncated Cox regression models. The relative efficacy of chemotherapy and transplantation depended on time from diagnosis to first relapse and the transplant conditioning regimen used. For children with early first relapse ( < 36 months), risk of a second relapse was significantly lower after total body irradiation (TBI) containing transplant regimens (relative risk [RR] 0.49, 95% confidence interval [CI] 0.33-0.71, p < 0.001) than chemotherapy regimens. In contrast, for children with a late first relapse ( (cid:2) 36 months), risks of second relapse were similar after TBI-containing regimens and chemotherapy (RR 0.92, 95% CI 0.49-1.70, p=0.78). These data support HLA-matched sibling donor transplantation using a TBI-containing regimen in second CR for children with ALL and early relapse.
Serial Assessment of Tissue Precursors and Progression of Coronary Calci ﬁ cation Analyzed by Fusion of IVUS and OCT 5-Year Follow-Up

OBJECTIVES The aim of this study was to assess calcium growth with fused grayscale intravascular ultrasound (IVUS), IVUS – virtual histology, and optical coherence tomography (OCT) from baseline to 5-year follow-up in patients treated with bioresorbable vascular scaffolds. BACKGROUND IVUS and OCT have individual strengths in assessing plaque composition and volume. Fusion of images obtained using these methods could potentially aid in coronary plaque assessment. METHODS Anatomic landmarks and endoluminal radiopaque markers were used to fuse OCT and IVUS images and match baseline and follow-up. RESULTS Seventy-two IVUS – virtual histology and OCT paired matched cross-sectional in- and out-scaffold segments were fused at baseline and follow-up. In total, 46 calci ﬁ ed plaques at follow-up were detected using the fusion method (33 in-scaffold, 13 out-scaffold), showing either calcium progression (52.2%) or de
The Modulating Role of NF- κ B in the Action of α 7-nAChR and Cross-talk between 5-Lipoxygenase and Cyclooxygenase-2 in Colon Cancer Growth Induced by NNK

4-(N-Methyl-N-nitrosamino)-1-(3-pyridyl)-1-butanone (NNK), the tobacco specific nitrosamine, induces lung cancer in all animal species tested and is thought to contribute significantly to the high lung cancer burden associated with smoking. However, there is no report whether NNK could promote colon cancer growth. To address this hypothesis and the possible signaling pathways involved, we used SW1116 colon cancer cell line to study these biological events in vitro . Results showed that NNK, after 5-hour treatment, stimulated cell proliferation, enhanced alpha7 nicotinic acetylcholine receptor ( α 7-nAChR) mRNA level and NF- κ B DNA binding activity, as well as 5-lipoxygenase and cyclooxygenase-2 protein expressions. α -Bungarotoxin, the specific α 7-nAChR antagonist, inhibited these biological effects. However, 5-lipoxygenase inhibition had no effect on α 7-nAChR mRNA expression, but significantly inhibited cell proliferation and activation of NF- κ B and cyclooxygenase-2. While NF- κ B specific inhibitor, caffeic acid phenethyl ester, reduced both cell proliferation and cyclooxygenase expression induced by NNK without affecting α 7-nAChR mRNA level and 5-lipoxygenase expression. Taken together, the present study demonstrated that NNK promoted colon cancer growth in vitro . NF- κ B not only conveys the biological effect of α 7-nAChR activation but also involved in the cross-talk between 5-lipoxygenase and cyclooxygenase-2 in response to NNK in colon cancer cell development.
3DText: Perceiving sentence-level text on 3-D model of emotions

Emotion is a psychological process which reveals the sentiments and feelings of a human being. Relating emotions detection process with psychological theory of emotions serves as the strong foundation for the system. In this paper, a model, 3DText, is proposed foe textual emotion detection. VAD (Pleasure, Arousal, and Dominance), a 3-D theory of emotion is used to extract features (P-A-D) from text. For this purpose, the dataset ANEW and WordNet are used. The objective of this paper is to determine VAD values at the sentence level of any size using word level VAD values for domain independent text. The proposed approach is evaluated on ISEAR and EMOBANK datasets. To the best of authors’ knowledge, no such model exists till date.
Basic Relations between Ejection Fraction and ESPVR

Heart Failure with normal or Preserved Ejection Fraction (HFpEF) is a subject that has received particular attention in the medical literature. In this study we show how the Ejection Fraction (EF) can be expressed as function of parameters describing the End-Systolic Pressure-Volume Relation (ESPVR), and the areas under the ESPVR, with new insight in some aspects of ventricular contraction. It is shown also that the Ejection Fraction (EF) is just one index of several indexes that can be derived from the parameters describing the ESPVR in order to assess the performance of the ventricles. Bivariate (or multivariate) analysis of indexes gives better segregation between cardiac cardiomyopathies. The ordinates of the ESPVR (units of pressure), and the areas under the ESPVR (units of energy) are sensitive parameters that reflect the state of the myocardium. Possible application of these results to the study of HFpEF is explained. We then show some of give of the It is also shown that the EF is just one index several indexes that can be used to assess ventricular function. We finally indicate how the results obtained can open the way to new directions of research that can lead to new insight in the study of HFpEF.
Adenosine Triphosphate (ATP) and Protein Data in Some Species of Deep-Sea Corals in Newfoundland and Labrador Region (Northwest Atlantic Ocean)

Adenosine triphosphate (ATP) and protein data in some species of deep-sea corals in (Northwest Despite the fact that deep sea corals are recognized as a crucial part of the deep marine ecosystem, little information is available on the general physiology and biochemistry of these species. In this study we measured ATP and protein amounts in deep-sea corals sampled around the coast of Newfoundland. Information found in literature, as well as results obtained in this study highlight the need for a standardization of methods used for protein extraction and overall sample preparation prior to ATP measurement to allow comparisons between deep and shallow water corals. The overall results obtained after decision tree analysis of ATP and protein data show strong differences between species with low seasonality in the data (despite some non-significant variations). This suggests a weak influence of reproductive cycles on general metabolism. Nonetheless, the absence of trend with depth and season in protein data remains surprising considering its link with food availability and some of the observations obtained after previous work on lipids in deep-sea corals. Adenosine triphosphate (ATP) and protein data in some species of deep-sea corals in Newfoundland and Labrador Region (Northwest Atlantic Ocean). Can. Tech. Rep. Fish. Aquat. Sci. 2801: iv + p.
Running Head: TESTING THE SPIRAL OF SILENCE Speaking up or Silencing out in the Face of Rising Right-Wing Populism: A Dynamic Test of the Spiral of Silence across 15 European Countries A

The spiral of silence theory (Noelle-Neumann, 1993) posits that when a given political position comes to be seen as the majority opinion, perceivers holding alternative views will feel pressured to become silent, thereby contributing to the growing public decline of the minority camp. Testing the theory across 15 countries ( N = 195,194) with data taken from the European Social Survey (2002–2016), we examined whether recently rising right-wing populist positions silenced supranational opinions or whether, on the contrary, they were silenced by established norms of democratic governance and social inclusiveness. The proposed modeling overcomes two limitations of prior research by using a macroscopic and dynamic approach that allows the detection of the ‘spiraling’ normative conformity process in nationally representative samples.
A Stevedore's Protein Knot The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters

Protein knots, mostly regarded as intriguing oddities, are gradually being recognized as significant structural motifs. Seven distinctly knotted folds have already been identified. It is by and large unclear how these exceptional structures actually fold, and only recently, experiments and simulations have begun to shed some light on this issue. In checking the new protein structures submitted to the Protein Data Bank, we encountered the most complex and the smallest knots to date: A recently uncovered a -haloacid dehalogenase structure contains a knot with six crossings, a so-called Stevedore knot, in a projection onto a plane. The smallest protein knot is present in an as yet unclassified protein fragment that consists of only 92 amino acids. The topological complexity of the Stevedore knot presents a puzzle as to how it could possibly fold. To unravel this enigma, we performed folding simulations with a structure-based coarse-grained model and uncovered a possible mechanism by which the knot forms in a single loop flip. provided the original author and source are credited. the for The work of JIS was Theoretical Biological NSF-MCB-0543906. MK is NSF The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
hbtSOTLearner: A Hierarchical-Backtracking-Based Parameter Learner for Small Outline Transistor

This paper is concerned with parameter learning of chips with small outline transistor (SOT) package, which is one of the most widely used package in surface mount technology (SMT) and has various subcategories. Previously learned parameter is crucial to most SOT-related industrial applications, such as location and defect inspection. However, parameter learning is a challenging work because of package diversity and image-quality deterioration in practical industrial applications. The conventional methods, checking data sheet or manual measuring, cannot meet the accuracy requirement of SMT. This paper proposes a hierarchical-backtracking-based parameter learner for SOT chips. The Gaussian mixture model based clustering algorithm and random walker algorithm are firstly applied to extracting lead regions of SOT chip; Then, chip models are inferred by grouping these lead regions with a hierarchical backtracking algorithm. Finally, redundant models are eliminated with root set pyramids and the valid chip model is obtained. The experimental results show that the proposed parameter learner performs well on SOT chips and is robust to noisy sets.
Many Roads Lead To Rome: How Packet Headers Influence DNS Censorship Measurement

Internet censorship is widespread, impacting citizens of hundreds of countries around the world. Recent work has devel-oped techniques that can perform widespread, longitudinal measurements of global Internet manipulation remotely and have focused largely on the scale of censorship measurements with minimal focus on reproducibility and consistency. In this work we explore the role packet headers (e.g., source IP address and source port) have on DNS censorship. By performing a large-scale measurement study building on the techniques deployed by previous and current censorship measurement platforms, we ﬁnd that choice of ephemeral source port and local source IP address (e.g., x.x.x.7 vs x.x.x.8) inﬂuence routing, which in turn inﬂuences DNS censorship. We show that 37% of IPs across 56% ASes measured show some change in censorship behavior depending on source port and local source IP. This behavior is frequently all-or-nothing , where choice of header can result in no observable censorship. Such behavior mimics and could be misattributed to geolocation error, packet loss, or network outages. The scale of censorship differences can more than double depending on the lowest 3 bits of the source IP address, consistent with known router load balancing techniques. We also observe smaller-scale censorship variation where only a few domains experience censorship differences based on packet parameters. We lastly ﬁnd that these variations are persistent; packet retries do not control for observed variation. Our results point to the need for methodological changes in future DNS censorship measurement, which we discuss.
Direct Printing of a Multi-Layer Sensor on Pet Substrate for CO2 Detection

The use of inexpensive gas sensors is a real need for many applications requiring the use of disposable sensors. This work deals with the realization and characterization of a low cost CO2 sensor realized by rapid prototyping techniques. In particular, the sensor consists of a set of InterDigiTed electrodes, over which a double sensing layer made of PEDOT/PSS (CLEVIOS™ PHCV4, by H.C.Starck) and a solution of pristine graphene powder has been deposited. A silver nano-particle solution is used for inkjet printing the electrodes onto the PET (PolyEthylene Terephthalate) substrate, through a commercial inkjet printer. The sensing strategy is based on the variation of the electrical conductance of graphene due to gas molecules adsorption. The device responsivity observed in two different operating conditions (50 °C and 60 °C), is 4.0 µΩ/Ω/ppm and 4.7 µΩ/Ω/ppm. The corresponding values of the resolution are 400 ppm and 420 ppm. Main advantages of the developed sensor consist in the cost-effective fabrication techniques and the device flexibility, which are strategic for applications requiring disposable and shapeable devices to be installed into irregular surfaces.
Mantle Flow Pattern Associated With the Patagonian Slab Window Determined From Azimuthal Anisotropy

Geological processes in Southern Patagonia are affected by the Patagonian slab window, formed by the subduction of the Chile Ridge and subsequent northward migration of the Chile Triple Junction. Using shear wave splitting analysis, we observe strong splitting of up to 2.5 s with an E‐W fast direction just south of the triple junction and the edge of the subducting Nazca slab. This region of strong anisotropy is coincident with low uppermost mantle shear velocities and an absence of mantle lithosphere, indicating that the mantle flow occurs in a warm, low‐viscosity, 200–300 km wide shallow mantle channel just to the south of the Nazca slab. The region of flow corresponds to a volcanic gap caused by depleted mantle compositions and absence of slab‐derived water. In most of Patagonia to the south of this channel, splitting fast directions trend NE‐SW consistent with large‐scale asthenospheric flow.
Design and Evaluation of 5G mmWave Beam Management in Ultra-Dense Cellular Scenarios

The recent move of 5G towards the millimeter-wave (mmWave) spectrum (> 24 GHz) is a reaction to the exponential growth of wireless mobile data consumption and the need for significantly higher data rates for emerging applications such as VR and 8K video [1]. A similar move has also already occurred with Wi-Fi amendments IEEE 802.11ad/aj/ay, and there is already speculation whether 6G could even use THz frequencies. This drastic change of carrier frequency comes with new challenges due to the rather hostile propagation characteristics at the mmWave domain [2]. To overcome these, large planar antenna arrays and novel beamforming transceiver architectures are facilitated [3]. As a result, mmWave communication becomes directional such that base station (BS) and user equipment (UE) side pencil beams have to be aligned precisely by means of beam management (a.k.a. beamsteering) to establish the mmWave link. Afterwards, the beams have to be realigned continuously to enable robust communication at Gbps data rates in mobile environments as shown in Fig. 1 [4].
Improvements to the soil nitrate quick test for California small grains

Small-grain crop growers need to match their crops' nitrogen (N) needs with fertilizer applications. This can be challenging because small grains are grown under diverse conditions and their growing season interacts with unpredictable precipitation. Resulting conditions can lead to nitrate-N leaching and runoff losses. More widespread and accurate soil N testing could help growers improve N fertilizer use efficiency, reduce the risk of N loss, and fulfill regulatory requirements. Soil samples from across California small-grain growing regions were tested with a soil nitrate quick test as well as standard laboratory procedures. The quick test is inexpensive and easy to use, and it provides rapid results. A correction factor was developed to convert the quick test values to lab and fertilizer equivalents. The correction factor is based on site-specific soil bulk density and the extracting solution used. An interactive webtool was developed that integrates this information for users. The quick tests provide accurate, real-time estimates of soil nitrate-N in the field to help improve fertilizer use efficiency and reduce N losses.
AN ANALYSIS ON THE INFLUENCE OF ANXIETY IN POST ERROR SLOWING

Anxiety disorders are among the most common mental disorders and affect 15.7 million Americans each year (Lépine, 2002, p. 4). Anxiety is associated with reduced productivity, physical distress, and other diseases such as depression. Anxiety could also be influential in error response (Compton et al., 2008; Luu et al., 2000; Robinson et al., 2007). Increased response time (RT) to respond to a stimulus following an error is known as post error slowing (PES). PES is widely attributed to increased caution following a mistake or cognitive adaptation to optimize behavior for correct responses in the future (Danielmeier & Ullsperger, 2011). Another theory to explain PES is that unusual responses - whether mistakes or accurate ones depending on which is common - will catch the participant’s attention and distract them from their previous strategy leading to slower response times (King et al., 2010; Notebaert et al., 2009). This thesis examines the relationship between anxiety and post error slowing trends in a sample of young adults through linear mixed-effects (lme) modeling. Anxiety and demographic variables were included in a mixed linear model analysis to determine significant predictors of PES. A statistically significant positive association between anxiety and PES in this sample suggests that individuals with reported social anxiety experience an increased reorienting time following an error.
I MPROVED C ONTROL D ESIGN FOR A UTONOMOUS V EHICLES

In this paper, the autonomous vehicle presented as a discrete-time Takagi-Sugeno fuzzy (T-S) model. We used the discrete-time T-S model since it is ready for the implementation unlike the continuous T-S fuzzy model. The main goal is to keep the autonomous vehicle in the centreline of the lane regardless the external disturbances. These disturbances are the wind force and the unknown curvature; they are applied to test if the autonomous vehicle moves from the centreline. To ensure that the autonomous vehicle remain on the centreline we propose two discrete-time fuzzy lateral controllers called also steering controllers.