Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion in Metallen : Grundlagen, Theorie, Vorgänge in Reinmetallen und Legierungen

Diffusionsvorg{nge legen Zeugnis ab von den {u erst komplizierten energetischen und strukturellen Zusammenh{ngen in Festkrpern, welche eine fast perfekte Ordnung mit Elementen einer Fehlordnung verbinden, die f}r ihrVerhalten oft entscheidend sind. Auch wenn der Diffusion und den diffusionsgesteuerten Umwandlungen, Grenzfl{chenreaktionen und Verformungsvorg{ngen in vielen Lehr- und Fachb}chern Beachtung zuteil wird, so hat es doch seit mehr als 30 Jahren keine deutschsprachige Monographie gegeben, welche dieses wichtige Gebiet umfassend und detailliertdarstellt. Der Autor, der Jahrzehnte hindurch den einschl{gigen wissenschaftlichen Fortschritt mitgepr{gt hat, hilft nun diesem Mangel ab. Er hat ein grundlegendes Werk verfa t, das Wissenschaftlern nicht nur bei der Erforschung modernster - u.a. keramischer oder hochpolymerer - Werkstoffe oder metallischer Schmelzen, sondern auch Studenten bei Vorlesungen, Seminar und Diplomarbeit unterst}tzt.
Planning of a multiple sensor system for human activities space: aspects of iso-disparity surface

The Intelligent Vision Agent System, IVAS, is a system for automatic target detection, identification and information processing for use in human activities surveillance. This system consists of multiple sensors, and with control of their deployment and autonomous servo. Finding the optimal configuration for these sensors in order to capture the target objects and their environment to a required specification is a crucial problem. With a stereo pair of sensors, the 3D space can be discretized by an iso-disparity surface, and the depth reconstruction accuracy of the space is closely related to the iso-disparity curve positions. This paper presents a method to enable planning the position of these multiple stereo sensors in indoor environments. The proposed method is a mathematical geometry model, used to analyze the isodisparity surface. We will show that the distribution of the iso-disparity surface and the depth reconstruction accuracy are controllable by the parameters of such model. This model can be used to dynamically adjust the positions, poses and baselines lengths of multiple stereo pairs of cameras in 3D space in order to get sufficient visibility and accuracy for surveillance tracking and 3D reconstruction. We implement the model and present uncertainty maps of depth reconstruction calculated while varying the baseline length, focal length, stereo convergence angle and sensor pixel length. The results of these experiments show how the depth reconstruction uncertainty depends on stereo pair's baseline length, zooming and sensor physical properties.
TMO-structured cluster-based real-time management of location data on massive volume of moving items

A major challenge in the field of location based service (LBS) system engineering, is to establish a highly scalable system architecture which can be instantiated in moderate-size configurations handling thousands of moving items as well as in upper-end configurations handling millions of moving items. We are exploring an approach of using a cluster of database server nodes and effecting efficient distributed and parallel computing in both real-time update of location records of moving items and processing of location-related queries. The approach of developing efficient middleware which is layered on a cluster of nodes running commercial off-the-shelf database servers, has been adopted. The middleware design is substantially based on the TMO scheme for real-time distributed object programming and real-time distributed computing system design, which enables low-overhead coordination of distributed computations and highly abstract distributed programming styles.
Enjoyment and absorption: An electronic diary study on daily flow patterns

Abstract Flow experience is a state of mind in which one is totally absorbed in a task. This study explored the daily flow patterns related to working and non-working tasks among healthy and non-healthy (burned-out) individuals using the Experience Sampling Method. Previously the flow experience has been measured in terms of high challenges and high skills. The main aim of this study was to explore flow throughout the day using an operationalization that focused on the flow experience itself, as indicated by enjoyment and absorption. Forty healthy participants and 60 burned-out individuals kept an electronic diary on activities (work/non-work), and levels of flow (enjoyment and absorption) for 14 days. Entries were prompted by a signal on average five times a day, thus rendering 5455 entries. A curvilinear daily flow pattern was observed, with lower levels of flow during working hours. Differences were found between the components of flow: enjoyment was higher during non-working tasks, whereas absorption was higher when working. There were no differences in flow patterns between the healthy and burned-out group although the actual levels differed, with the former experiencing more flow than the latter. The results confirm the validity of this means of measuring flow, using enjoyment and absorption as indicators.
Improvement of Ultra-Low Field Magnetic Resonance Recordings With a Multilayer Flux-Transformer-Based High-$T_{\rm C}$ SQUID Magnetometer

We have developed a multilayer flux-transformer-based high-TC SQUID (flip-chip) magnetometer that improves signal-to-noise-ratios (SNR) in ultra-low field magnetic resonance (ulf-MR) recordings of protons in water. Direct ulf-MR-based benchmarking of the flip-chip versus a standard planar high-TC SQUID magnetometer resulted in improvement of the SNR by a factor of 2. This gain is attributable to the improved transformation coefficient (1.9 vs 5.3 nT/Φ0) that increased the signal available to the flip-chip sensor and to the lower noise at the measurement frequency (15 vs 25 fT/Hz1/2 at 4 kHz). The improved SNR can lead to better spectroscopic resolution, lower imaging times, and higher resolution in ulf-MR imaging systems based on high- TC SQUID technology. The experimental details of the sensors, calibration, and ulf-MR benchmarking are presented in this report.
Love, Trust, and Evolution: Nurturance/Love and Trust as Two Independent Attachment Systems Underlying Intimate Relationships

Research has indicated two dimensions of attachment, Avoidance and Anxiety. We show that Avoidance is better conceptualized as Nurturance/Love within an evolved systems perspective on personality, and that the Anxiety dimension in infancy measures trust in the face of threat based on experience. These two dimensions have important differences, including different evolutionary functions and phylogeny, as well as different emotions, brain mechanisms, and patterns of sex differences and heritability. We used two versions of the Experiences in Close Relationships Survey yielding measures of Anxiety and Avoidance, and the Interpersonal Adjective Scale-Revised-Big 5, the latter chosen because it measures Nurturance/Love in a manner consistent with an evolutionary perspective on close relationships. 635 subjects participated in the study. Results supported the hypotheses of a strong negative association between Nurturance/Love and Avoidance as measured by the ECR and no association between Nurturance/Love and Anxiety as measured by the ECR.
Application of Hierarchical Linear Models to Assessing Change

Developments over the past 10 years in the statistical theory of hierarchical linear models (HLMs) now enable an integrated approach for (a) studying the structure of individual growth and estimating important statistical and psychometric properties of collections of growth trajectories; (b) discovering correlates of change factors that influence the rate at which individuals develop; and (c) testing hypotheses about the effects of on or more experimental or quasi-experimental treatments on growth curves. The approach is based on a two-stage hierarchical model. An example based on Head Start data illustrated key analytic uses of HLMs; (a) describing the structure of the mean growth trajectory; (b) estimating the extent and character of individual variation around mean growth; (c) assessing the reliability of measures for studying both status and change; (d) estimating the correlation between subjects entry status and rates of growth; (e) estimating correlates of both status and change; (f) assessing the adequacy of between-subjects models by estimating reduction in unexplained parameter variance (reduction in uncertainty about the individual growth parameters as distinguished from errors in their estimation); and (g) predicting future individual growth. HLMs can be applied in experimental and quasi-experimental settings. The HLM approach requires multi-time point data. The special strengths of HLMs in individual prediction are remarkable. The study of growth curves using HLMs requires special care to distributional assumptions covariance assumptions and the metric of measurement. HLMs seem broadly applicable to the study of change and are likely to extend substantially the empirical research on change. To the extent that HLMs enrich the class of testable hypotheses about the structure of growth it may also encourage a broadened discussion about the nature of change itself.
Osteoporosis prevention in college women: application of the expanded health belief model.

OBJECTIVE To examine personal characteristics and expanded health belief model (EHBM) constructs associated with the practice of osteoporosis-protective behaviors among a random sample of nontraditional college women. METHODS A valid and reliable written mail questionnaire assessing osteoporosis knowledge, EHBM constructs, weight-bearing exercise (EX), and dietary calcium intake (CA) was completed by 273 women. RESULTS A high proportion of women did not meet current guidelines for EX (50.7%) or CA (67.8%). Exercise self-efficacy and barriers to exercise were the best predictors of overall EX and CA behaviors. CONCLUSION The EHBM was useful in predicting EX and CA.
Data security frameworks in cloud

Cloud computing provides a wide range of services to consumers with lesser investment which are delivered over Internet. Security is considered to be a significant problem in the development of cloud computing which is actually an obstacle to the growth of cloud is computing. The most challenging task in a shared environment like cloud is data security. Cloud enables the clients to store data on remote servers thereby preventing direct control over this data. Data in cloud is not controlled by the data owner. So, proper data security mechanism must be maintained. A new hybrid model for data security in cloud targets encrypting data and ensures that the proper policies are enforced. The major objective is to transmit, store and retrieve data in a secure manner. The main focus of this paper is to highlight the various encryption techniques and data integrity proofs. Speed of processing and computational efficiency of encrypting data should also be considered since the cloud environment involves large amount of data transfer, storage and usage. This paper presents the survey about data security in cloud computing.
A study of Legionella pneumophilia in Tianjin, China

Abstract Legionella is a bacterium identified as the causative agent of Legionnaires' disease commonly found in water and soil in natural environments and human habitats. While most studies are focused on cooling tower water as the source of infection, few studies have compared Legionella from cooling-tower water and water in man-made environments. This cross-sectional study with a randomized cluster sampling design aims to provide information on Legionella found in cooling-tower water and water in man-made environments. Legionella was identified using a dual analytical approach: the serological and the 16SrRNA semi-nest PCR methods. Nine different types of Legionella were identified with the Lp7 type detected in China for the first time. Results indicated slight but insignificantly increased odds (OR=1.64, 95%CI=0.54-4.98) of Legionella detection in cooling tower water as compared to water obtained from fountains and parks, suggesting that the mechanism of exposure plays an important role in the causal pathway of outbreaks of Legionnaires' disease.
Improved Fault Tolerant Elastic Scheduling Algorithm for Cloud Computing

The paper focus on Fault Tolerance, a long standing problem in cloud computing by extending Primary Backup model to include cloud features such as virtualization and elasticity. Fault tolerance is a challenging work in Cloud Computing as virtual machines are the basic computing instances rather than hosts that enable virtual machines to migrate to other hosts. The on demand provisioning of resources makes the cloud elastic thus resources can be added on demand and when no longer requirement exists, the resources can be released. Prevailing fault tolerant scheduling algorithms which studied PB model approach in cloud computing investigated single Host crashes. The proposed algorithm, improved Fault Tolerant Elastic Scheduling Algorithm identified as IFTESA, is able to handle two host crashes concurrently. IFTESA attempts to boost performance by involving virtual machine migration and overlapping technique. The constraints have been investigated to full fill fault tolerance needs.
FAMILY LITERACY ENVIRONMENT AND PARENTAL EDUCATION IN RELATION TO DIFFERENT MEASURES OF CHILD'S LANGUAGE

The family literacy environment is reported to be an important predictor of a child’s language and early literacy development. This study examined the relations between various aspects of family literacy environment and different measures of children’s language, assessed in three different settings, namely in a structured test situation, at home and in preschool. The sample included 80 preschool children, randomly selected from 13 preschools, aged approximately 4 years. The quality of family literacy environment was estimated by mothers, using the Home literacy environment questionnaire. Children’s language development and storytelling ability was assessed by a testator, while their spontaneous language was assessed by their mothers and preschool teachers. Family literacy environment was found to be an important factor of the child’s storytelling ability and the complexity of his spontaneous language, used at home and in preschool. Maternal education proved to be associated with the quality of the family literacy environment and also related to all measures of the child’s language except for maternal assessment. The findings have implications for understanding the role of family environment in the development of different aspects of a child’s language and the importance of assessing the child’s language in various settings thus obtaining a complete estimation of his language ability.
An investigation of polyethylene composites containing silica sol-gel building-blocks

Controlling the interface has always been a challenge when designing a new type of nanocomposite. In this work, an innovative approach is proposed. It starts with depositing a 60-nm thick silica layer on a PE substrate, using a sol-gel method. This layered object is further covered by thermally pressing over it a sheet of PE. The thus obtained composite is indented into small building blocks which have the advantage of possessing each a controlled interface. The building blocks are then used to thermally press samples of low-density polyethylene (LDPE) with ultra-low content of nanostructured additives. Only after completing a thorough investigation, it was possible to state that the neat and the composite materials behaved more or less the same. This is explained by the very low resulting content of silica, i.e. 0.02 wt% in the composite, defining it as having a very low-degree of self-assembly. However, the constructing approach has a great potential if used with a nanometric extra-ordinary filler deposited at the interface of the building block.
Adaptive Systems with Closed-Loop Reference Models: Composite Control and Observer Feedback

Abstract A class of Closed-loop Reference Models (CRM) was shown in Gibson et al. (2013) to have improved transient performance. In this paper, we show that the introduction of CRM in Combined direct and indirect Model Reference Adaptive Control (CMRAC) leads to significant improvement in their transient response as well. We also show that CRM allow stable feedback of noise-free state estimates in CMRAC. Theoretical derivations are supported with numerical simulations.
Effects of shade from multiple kelp canopies on an understory algal assemblage

We examined the effects of shade from multiple kelp canopy layers (surface Macrocystis pyrifera canopy, understory Pterygophora californica canopy), both individually and in combination, on an understory algal assemblage in a central Californian kelp forest. The removal of both kelp canopies resulted in a dense recruitment of the understory brown alga Desmarestia ligulata that formed a third canopy layer, which significantly decreased bottom light and the abundance of under- story red algae. We subsequently created an additional canopy treatment by removing this third canopy layer. In general, the understory red algae fluctuated seasonally with winter swell intensity, changes in kelp canopy cover, and grazing; and although species richness increased significantly with increased bottom light, red algal bottom cover did not respond significantly to the canopy clear- ings until 2 yr after the canopies were initially cleared. Red algal cover within the Pterygophora canopy treatment was similar to that in the control treatment. In the absence of Pterygophora, the Macrocystis canopy treatment and 'no canopy' treatment were found to have greater red algal cover and species richness. Individual understory species were rare, which resulted in small effects sizes and thus low statistical power. However, when grouped post hoc, according to how they responded to the canopy clearings (i.e. response groups), we were able to detect canopy treatment effects as much as 1 yr earlier. This method identified that some understory red algae adapted to areas of canopy removal (light-adapted), and others adapted to a variety of light regimes (shade-tolerant). We were able to classify the light-adapted algae into 2 subgroups: the high-light species and the inter- mediate-light species. Although this method of grouping was done post hoc, our results indicate that it may provide the clearest assessment of how understory algae respond to shading from kelp canopies.
Control-oriented averaging of tail-actuated robotic fish dynamics

Motivated by the need for efficient control design, in this paper we consider the averaging of dynamics for a tail-actuated robotic fish, based on an experimentally validated dynamic model that incorporates rigid body dynamics and Lighthill's large-amplitude elongated-body theory. We first show that classical averaging theory fails in this case because of the relatively large oscillatory input in the driving terms. On the other hand, while the first-order geometric averaging method for systems with highly oscillatory inputs is able to capture the original time-dependent dynamics, the resulting average model is overly complex for controller design. We propose a novel control-oriented, data-driven averaging approach for robotic fish dynamics, where a scaling function is introduced on top of the classical averaging method. We run extensive simulations for different combinations of tail-beat bias, amplitude, and frequency, and find that the scaling function is constant for the force equations and varies linearly with the tail-beat bias for the moment equation. The validity of the resulting average model has been confirmed in simulation results for open-loop dynamics with new sets of tail-beat parameters, and for closed-loop dynamics when proportional control of the tail-beat bias is used in target tracking.
Reboxetine Adjuvant Therapy in Patients With Schizophrenia Showing a Suboptimal Response to Clozapine: A 12-Week, Open-Label, Pilot Study

Abstract The present 12-week open-label uncontrolled trial was aimed to explore the efficacy of reboxetine add-on pharmacotherapy on clinical symptoms and cognitive functioning in 15 patients with schizophrenia with suboptimal response (mean [SD] Brief Psychiatric Rating Scale baseline total score, 32.2 [5.4]) despite receiving clozapine monotherapy at the highest tolerated dosage. The results obtained evidenced that reboxetine at a dosage of 4 mg/d mildly reduced only depressive symptoms (Calgary Depression Scale for Schizophrenia: P = 0.035, Cohen d = 0.7), whereas worsening of performances on phonemic fluency (P = 0.012, Cohen d = 0.5) was observed. After Bonferroni correction, changes at the Calgary Depression Scale for Schizophrenia and at the Verbal Fluency Task were not further confirmed. The results obtained indicate that reboxetine seemed to be scarcely effective for reducing clinical symptoms in patients with schizophrenia who have had an incomplete clinical response to clozapine. Regarding cognitive functioning, in our sample, a trend to experience cognitive impairment in the examined domains was observed, as confirmed by a mild worsening of performances on cognitive tasks. Schizophrenia is a heterogeneous disorder with regard to pathophysiology; therefore, data reflecting the mean response of a sample of patients may fail to reveal therapeutic effects. More research is needed to better identify subgroups of patients with peculiar features, which may account for responsivity to experimental medications and augmentation strategies.
CLUMPED CHLOROPLASTS 1 is required for plastid separation in Arabidopsis

We identified an Arabidopsis thaliana mutant, clumped chloroplasts 1 (clmp1), in which disruption of a gene of unknown function causes chloroplasts to cluster instead of being distributed throughout the cytoplasm. The phenotype affects chloroplasts and nongreen plastids in multiple organs and cell types, but is detectable only at certain developmental stages. In young leaf petioles of clmp1, where clustering is prevalent, cells lacking chloroplasts are detected, suggesting impaired chloroplast partitioning during mitosis. Although organelle distribution and partitioning are actin-dependent in plants, the actin cytoskeleton in clmp1 is indistinguishable from that in WT, and peroxisomes and mitochondria are distributed normally. A CLMP1-YFP fusion protein that complements clmp1 localizes to discrete foci in the cytoplasm, most of which colocalize with the cell periphery or with chloroplasts. Ultrastructural analysis revealed that chloroplasts within clmp1 clusters are held together by membranous connections, including thin isthmi characteristic of late-stage chloroplast division. This finding suggests that constriction of dividing chloroplasts proceeds normally in clmp1, but separation is impaired. Consistently, chloroplast size and number, as well as positioning of the plastid division proteins FtsZ and ARC5/DRP5B, are unaffected in clmp1, indicating that loss of CLMP1-mediated chloroplast separation does not prevent otherwise normal division. CLMP1-like sequences are unique to green algae and land plants, and the CLMP1 sequence suggests that it functions through protein–protein interactions. Our studies identify a unique class of proteins required for plastid separation after the constriction stage of plastid division and indicate that CLMP1 activity is also required for plastid distribution and partitioning during cell division.