Miracle-dz/UniFAR-FTUs huggingface dataset:
Longitudinal Associations Between Adult Children’s Relations With Parents and Intimate Partners

Drawing on 5 waves of multiple-informant data gathered from focal participants and their parents and intimate partners (n = 360 families) who completed annual surveys in the German Family Panel (pairfam) study, the present investigation examined bidirectional associations between the development of adults’ conflictual and intimate interactions with their parents and intimate partners. Autoregressive cross-lagged latent change score modeling results revealed a robust pattern of coordinated development between parent-adult child and couple conflictual and intimate interactions: increases in conflict and intimacy in one relationship were contemporaneously intertwined with changes in the other relationship. Additionally, prior couple intimacy and conflict predicted future parent-adult child relations in 7 out of 14 cross-lagged pathways examined, but parent-adult child conflict and intimacy was only associated with future couple interactions in 1 pathway. These associations were not moderated by the gender of parents or the adult child or whether the adult child was a young adult or nearing midlife. Frequency of contact between parents and the adult child moderated some associations. Adults simultaneously juggle ties with parents and intimate partners, and this study provides strong evidence supporting the coordinated development of conflictual and intimate patterns of interaction in each relationship.
Polymer/QDs nanocomposites for waveguiding applications

In this paper we review our recent progress in a still young type of active waveguides based on hybrid organic (polymer)-- inorganic (semiconductor quantum dots) materials. They can be useful for the implementation of new photonic devices, because combining the properties of the semiconductor nanostructures (quantum size carrier confinement and temperature independent emission) with the technological capabilities of polymers. These optical waveguides can be easily fabricated by spin-coating and UV photolithography on many substrates (SiO2/Si, in the present work). We demonstrate that it is possible to control the active wavelength in a broad range (400-1100 nm), just by changing the base quantum dotmaterial (CdS, CdSe, CdTe and PbS, but other are possible), without the necessity of changing fabrication conditions. Particularly, we have determined the optimum conditions to produce multi-color photoluminescence waveguiding by embedding CdS, CdSe and CdTe quantum dots into Poly(methyl methacrylate). Finally, we show new results regarding the incorporation of CdSe nanocrystals into a SU-8 resist, in order to extrapolate the study to a photolithographic and technologically more important polymer. In this case ridge waveguides are able to confine in 2D the light emitted by the quantum dots.
Immunocytochemistry and distribution of parabrachial terminals in the lateral geniculate nucleus of the cat: A comparison with corticogeniculate terminals

We used immunohistochemistry in cats to demonstrate the presence of brain nitric oxide synthase (BNOS) in cholinergic fibers within the A‐laminae of the lateral geniculate nucleus. We used a double labeling procedure with electron microscopy and found that all terminals labeled for choline acetyltransferase (ChAT) in the geniculate A‐laminae were double labeled for BNOS. Also, some interneuron dendrites, identified by labeling for γ‐aminobutyric acid (GABA), contained BNOS, but relay cell dendrites did not. We then compared parabrachial and corticogeniculate terminals, identifying the former by BNOS/ChAT labeling and the latter by orthograde transport of biocytin injected into cortical area 17, 18, or 19. All corticogeniculate terminals and most BNOS‐ or ChAT‐positive brainstem terminals displayed RSD morphology, whereas some brainstem terminals exhibited RLD morphology. However, parabrachial terminals were larger, on average, then corticogeniculate terminals. We also found that parabrachial terminals were located both inside and outside of glomeruli, and they always contacted relay cell dendrites proximally among retinal terminals (the retinal recipient zone). In contrast, the cortical terminals were limited to peripheral dendrites (the cortical recipient zone). Thus, little if any overlap exists in the distribution of parabrachial and corticogeniculate terminals on the dendrites of relay cells. J. Comp. Neurol. 377:535–549, 1997. © 1997 Wiley‐Liss, Inc.
Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns Study

Background— Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. Methods and Results— A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3–18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P<0.0001) and validation data (AUC=0.769 versus AUC=0.747, P=0.026). WGRS97 improved the accuracy in training (AUC=0.782 versus AUC=0.744, P<0.0001) but not in validation data (AUC=0.749 versus AUC=0.747, P=0.785). Higher WGRS19 associated with higher body mass index at 9 years and WGRS97 at 6 years. Replication in BHS confirmed our findings that WGRS19 and WGRS97 are associated with body mass index. Conclusions— WGRS19 improves prediction of adulthood obesity. Predictive accuracy is highest among young children (3–6 years), whereas among older children (9–18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity.
A Cellular Automata Based Reconfigurable Architecture for Hybrid Cryptosystems

In this paper, a low-complexity Programmable Cellular Automata (PCA) based reconfigurable architecture is proposed. Through simple configurations, it cannot only be used in the PCA-based block cipher of symmetric-key encryption, but also can be configured to be an efficient versatile modular multiplier in GF(2m), an essential operation in public-key cryptography. The proposed reconfigurable hybrid-crypto architecture has a regular structure and is very suitable for high speed VLSI implementation, increasing the flexibility of security schemes and reducing the total cost of the hybrid cryptosystems. Moreover, the low-cost serial implementation of this reconfigurable architecture is feasible in restricted computing environments, such as embedded systems and wireless devices.
Contractile behavior of the left ventricle in diastolic heart failure: with emphasis on regional systolic function.

We appreciate Dr Sanderson’s interest and support of our efforts to better understand cardiac function in patients with diastolic heart failure (DHF) and welcome the opportunity to respond. We have previously reported normal left ventricular systolic performance, function, and contractility in patients with DHF and have concluded that the pumping ability of the whole ventricle is normal in the basal state.1 To our knowledge, there are no published data that refute this …
PAI-1 -675 4G/5G Polymorphism in Association with Diabetes and Diabetic Complications Susceptibility: a Meta-Analysis Study

A meta-analysis was performed to assess the association between the PAI-1 -675 4G/5G polymorphism and susceptibility to diabetes mellitus (DM), diabetic nephropathy (DN), diabetic retinopathy (DR) and diabetic coronary artery disease (CAD). A literature-based search was conducted to identify all relevant studies. The fixed or random effect pooled measure was calculated mainly at the allele level to determine heterogeneity bias among studies. Further stratified analyses and sensitivity analyses were also performed. Publication bias was examined by the modified Begg’s and Egger’s test. Twenty published articles with twenty-seven outcomes were included in the meta-analysis: 6 studies with a total of 1,333 cases and 3,011 controls were analyzed for the PAI-1 -675 4G/5G polymorphism with diabetes risk, 7 studies with 1,060 cases and 1,139 controls for DN risk, 10 studies with 1,327 cases and 1,557 controls for DR and 4 studies with 610 cases and 1,042 controls for diabetic CAD risk respectively. Using allelic comparison (4G vs. 5G), the PAI-1 -675 4G/5G polymorphism was observed to have no significant association with diabetes (REM OR 1.07, 95% CI 0.96, 1.20), DN (REM OR 1.10, 95% CI 0.98, 1.25), DR (REM OR 1.09, 95% CI 0.97, 1.22) or diabetic CAD risk (REM OR 1.07, 95% CI 0.81, 1.42), and similar results were obtained in the dominant, recessive and co-dominant models. Our meta-analyses suggest that the PAI-1 -675 4G/5G polymorphism might not be a risk factor for DM, DN, DR or diabetic CAD risk in the populations investigated. This conclusion warrants confirmation by further studies.
Final Technical Report: Nanostructured Shape Memory ALloys

With this grant we explored the properties that result from combining the effects of nanostructuring and shape memory using both experimental and theoretical approaches. We developed new methods to make nanostructured NiTi by melt-spinning and cold rolling fabrication strategies, which elicited significantly different behavior. A template synthesis method was also used to created nanoparticles. In order to characterize the particles we created, we developed a new magnetically-assisted particle manipulation technique to manipulate and position nanoscale samples for testing. Beyond characterization, this technique has broader implications for assembly of nanoscale devices and we demonstrated promising applications for optical switching through magnetically-controlled scattering and polarization capabilities. Nanoparticles of nickel-titanium (NiTi) shape memory alloy were also produced using thin film deposition technology and nanosphere lithography. Our work revealed the first direct evidence that the thermally-induced martensitic transformation of these films allows for partial indent recovery on the nanoscale. In addition to thoroughly characterizing and modeling the nanoindentation behavior in NiTi thin films, we demonstrated the feasibility of using nanoindentation on an SMA film for write-read-erase schemes for data storage.
Iterative Rounding Approximation Algorithms for Degree-Bounded Node-Connectivity Network Design

We consider the problem of finding a minimum edge cost subgraph of an undirected or a directed graph satisfying given connectivity requirements and degree bounds b(·) on nodes. We present an iterative rounding algorithm for this problem. When the graph is undirected and the connectivity requirements are on the element-connectivity with maximum value k, our algorithm computes a solution that is an O(k)-approximation for the edge cost in which the degree of each node v is at most O(k) · b(v). We also consider the no edge cost case where the objective is to find a subgraph satisfying connectivity requirements and degree bounds. Our algorithm for this case outputs a solution in which the degree of each node v is at most 6·b(v)+O(k2). These algorithms can be extended to other well-studied undirected node-connectivity requirements such as uniform, subset and rooted connectivity. When the graph is directed and the connectivity requirement is k-out-connectivity from a root, our algorithm computes a solution that is a 2-approximation for the edge cost in which the degree of each node v is at most 2 · b(v) + O(k).
A tool for prediction of risk of rehospitalisation and mortality in the hospitalised elderly: secondary analysis of clinical trial data

Objectives To construct and internally validate a risk score, the ‘80+ score’, for revisits to hospital and mortality for older patients, incorporating aspects of pharmacotherapy. Our secondary aim was to compare the discriminatory ability of the score with that of three validated tools for measuring inappropriate prescribing: Screening Tool of Older Person's Prescriptions (STOPP), Screening Tool to Alert doctors to Right Treatment (START) and Medication Appropriateness Index (MAI). Setting Two acute internal medicine wards at Uppsala University hospital. Patient data were used from a randomised controlled trial investigating the effects of a comprehensive clinical pharmacist intervention. Participants Data from 368 patients, aged 80 years and older, admitted to one of the study wards. Primary outcome measure Time to rehospitalisation or death during the year after discharge from hospital. Candidate variables were selected among a large number of clinical and drug-specific variables. After a selection process, a score for risk estimation was constructed. The 80+ score was internally validated, and the discriminatory ability of the score and of STOPP, START and MAI was assessed using C-statistics. Results Seven variables were selected. Impaired renal function, pulmonary disease, malignant disease, living in a nursing home, being prescribed an opioid or being prescribed a drug for peptic ulcer or gastroesophageal reflux disease were associated with an increased risk, while being prescribed an antidepressant drug (tricyclic antidepressants not included) was linked to a lower risk of the outcome. These variables made up the components of the 80+ score. The C-statistics were 0.71 (80+), 0.57 (STOPP), 0.54 (START) and 0.63 (MAI). Conclusions We developed and internally validated a score for prediction of risk of rehospitalisation and mortality in hospitalised older people. The score discriminated risk better than available tools for inappropriate prescribing. Pending external validation, this score can aid in clinical identification of high-risk patients and targeting of interventions.
PISCES: Participatory Incentive Strategies for Effective Community Engagement in Smart Cities

A key challenge in participatory sensing systems has been the design of incentive mechanisms that motivate individuals to contribute data to consuming applications. Emerging trends in urban development and smart city planning indicate the use of citizen reports to gather insights and identify areas for transformation. Consumers of these reports (e.g. city agencies) typically associate non-uniform utility (or values) to different reports based on the spatio-temporal context of the reports. For example, a report indicating traffic congestion near an airport, in early morning hours, would tend to have much higher utility than a similar report from a sparse residential area. In such cases, the design of an incentive mechanism must motivate participants, via appropriate rewards (or payments), to provide higher utility reports when compared to less valued ones. The main challenge in designing such an incentive scheme is two-fold: (i) lack of prior knowledge of participants in terms of their availability (i.e. who are in the vicinity) and reporting behaviour (i.e. what are the rewards expected); and (ii) minimizing payments to the reporters while ensuring that the desired number of reports are collected. In this paper, we propose STOC-PISCES, an algorithm that guarantees a stochastic optimal solution in the generalized setting of an unknown set of participants, with non-deterministic availabilities and stochastically rational reporting behaviour. The superior performance of STOC-PISCES in experimental settings, based on real-world data, endorses its adoption as an incentive strategy in participatory sensing applications like smart city management.
Repetition suppression: a means to index neural representations using BOLD?

Understanding how the human brain gives rise to complex cognitive processes remains one of the biggest challenges of contemporary neuroscience. While invasive recording in animal models can provide insight into neural processes that are conserved across species, our understanding of cognition more broadly relies upon investigation of the human brain itself. There is therefore an imperative to establish non-invasive tools that allow human brain activity to be measured at high spatial and temporal resolution. In recent years, various attempts have been made to refine the coarse signal available in functional magnetic resonance imaging (fMRI), providing a means to investigate neural activity at the meso-scale, i.e. at the level of neural populations. The most widely used techniques include repetition suppression and multivariate pattern analysis. Human neuroscience can now use these techniques to investigate how representations are encoded across neural populations and transformed by relevant computations. Here, we review the physiological basis, applications and limitations of fMRI repetition suppression with a brief comparison to multivariate techniques. By doing so, we show how fMRI repetition suppression holds promise as a tool to reveal complex neural mechanisms that underlie human cognitive function. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.
TRANSFER OF NATURAL LANGUAGE PROCESSING TECHNOLOGy : EXPERIMENTS , POSSIbILITIES AND LIMITATIONS CASE STUDy : ENGLISH TO SERbIAN

No 1-2, vol IX, May 2008 in the area of Natural Language Processing, with an emphasis on those related to small languages like Serbian. Theory and practice of searching and retrieval of text and bibliographic information were introduced with a special prominence placed on question answering issues. In addition, current and most successful approaches to the problem of identifying the answers to a naturallanguage question from a large quantity of online text documents was studied in depth to set the stage for the concurrent and subsequent research proceedings.
Algorithm 908

We present a novel, online algorithm for exact summation of a stream of floating-point numbers. By “online” we mean that the algorithm needs to see only one input at a time, and can take an arbitrary length input stream of such inputs while requiring only constant memory. By “exact” we mean that the sum of the internal array of our algorithm is exactly equal to the sum of all the inputs, and the returned result is the correctly-rounded sum. The proof of correctness is valid for all inputs (including nonnormalized numbers but modulo intermediate overflow), and is independent of the number of summands or the condition number of the sum. The algorithm asymptotically needs only 5 FLOPs per summand, and due to instruction-level parallelism runs only about 2--3 times slower than the obvious, fast-but-dumb “ordinary recursive summation” loop when the number of summands is greater than 10,000. Thus, to our knowledge, it is the fastest, most accurate, and most memory efficient among known algorithms. Indeed, it is difficult to see how a faster algorithm or one requiring significantly fewer FLOPs could exist without hardware improvements. An application for a large number of summands is provided.
Tensile Behaviour of Staple Yarns

The tensile properties of staple yarns strongly depend on yarn structure. The differences in the yarn structure reflecting different distribution of fibres in the yarn and different fibre migration patterns result from different manufacture methods. The tensile behaviour of ring, open end, air jet and vortex yarns has been studied. The yarns were tested on a tensile tester. The images of the yarn before and after the break were recorded. On the basis of yarn images the distribution of number of fibres and fibre ends on the yarn length as well as the relative disposition of the fibres in yarn were determined. The models have been developed on the basis of these parameters to predict the tensile properties of staple yarns.
An Algorithm for Recognizing Runway Based on Improved Radon Transformation

In order to achieve runway recognition correctly, aiming at the characteristics of area grey and edge line of runway, an algorithm for recognizing runway based on improved Radon transformation is presented. Firstly, the edge detectors are used to get edge image, and straight lines are extracted with improved Radon transformation in the edge image. Then straight lines are connected and parallel straight lines are extracted. Finally, the runway is recognized correctly based on the characteristics of area grey. Many experiments show that this method can find runway of airport exactly and quickly in the aerial image, and is robust for the influence of cloud cover and noise. Experimental results verify the algorithm's effectiveness.
Adaptive resolution simulation of an atomistic protein in MARTINI water.

We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecular dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.
Video retrieval based on deep convolutional neural network

Recently, with the enormous growth of online videos, fast video retrieval research has received increasing attention. As an extension of image hashing techniques, traditional video hashing methods mainly depend on hand-crafted features and transform the real-valued features into binary hash codes. As videos provide far more diverse and complex visual information than images, extracting features from videos is much more challenging than that from images. Therefore, high-level semantic features to represent videos are needed rather than low-level hand-crafted methods. In this paper, a deep convolutional neural network is proposed to extract high-level semantic features and a binary hash function is then integrated into this framework to achieve an end-to-end optimization. Particularly, our approach also combines triplet loss function which preserves the relative similarity and difference of videos and classification loss function as the optimization objective. Experiments have been performed on two public datasets and the results demonstrate the superiority of our proposed method compared with other state-of-the-art video retrieval methods.