Miracle-dz/UniFAR-FTUs huggingface dataset:
How Are Children of Older Mothers Doing? Evidence from the United Kingdom

Childbearing has been increasingly delayed in Western countries. As older mothers are likely to be advantaged over their younger counterparts, the demographic literature has tended to view this demographic trend as potentially beneficial for child well-being. Conversely, less attention has been given to medical studies showing that giving birth at advanced ages is associated with health risks for children. This article uses data from the Millennium Cohort Study (UK) and ordinary least squares and logistic regression models to compare cognitive and behavioral outcomes, and obesity at age 5 for first-born children by maternal age at first birth. On one hand, the findings suggest that giving birth to the first child at ages 30–39 compared to ages 23–29 is positively associated with children’s cognitive and behavioral outcomes and not associated with obesity. On the other hand, delaying the first birth to ages 40 and above is not associated with children’s cognitive and behavioral outcomes and is associated with increased risk of obesity. Although the results are unable to support the argument that this occurs because of the health risks associated with giving birth at advanced maternal ages, they suggest that there is a need to more closely investigate the potential trade-offs involved when births are delayed toward older maternal ages.
EphB Controls NMDA Receptor Function and Synaptic Targeting in a Subunit-Specific Manner

Dynamic regulation of the localization and function of NMDA receptors (NMDARs) is critical for synaptic development and function. The composition and localization of NMDAR subunits at synapses are tightly regulated and can influence the ability of individual synapses to undergo long-lasting changes in response to stimuli. Here, we examine mechanisms by which EphB2, a receptor tyrosine kinase that binds and phosphorylates NMDARs, controls NMDAR subunit localization and function at synapses. We find that, in mature neurons, EphB2 expression levels regulate the amount of NMDARs at synapses, and EphB activation decreases Ca2+-dependent desensitization of NR2B-containing NMDARs. EphBs are required for enhanced localization of NR2B-containing NMDARs at synapses of mature neurons; triple EphB knock-out mice lacking EphB1–3 exhibit homeostatic upregulation of NMDAR surface expression and loss of proper targeting to synaptic sites. These findings demonstrate that, in the mature nervous system, EphBs are key regulators of the synaptic localization of NMDARs.
The Knowledge Base for Beginning Teachers: Education Professionals' Expectations versus Research Findings on Learning to Teach

What should a newly licensed teacher know and be able to do? In this article, I discuss findings from 5 studies undertaken by Educational Testing Service to elicit judgments from education professionals (teachers, teacher educators, state department officials) regarding this question. The studies detail teaching tasks and knowledge/skills in 4 domains (general principles of teaching and learning, content, content-specific pedagogy, and enabling skills [e. g., reading and computational skills]). Results indicate that respondents considered most of the identified teaching tasks and knowledge/skills to be important. I then present findings from a review of the learning-to-teach literature; these findings suggest that beginners may not have all of the understandings and skills expected by education professionals. In the final section of the article, practitioners' expectations are contrasted with the research findings on beginning teaching, and the implications of this quandary for teacher education, induction, and assessment for licensure are discussed.
RAPOSA: Semi-Autonomous Robot for Rescue Operations

This work describes a semi-autonomous robot for rescue operations, nicknamed RAPOSA (FOX in English). The robot was designed and built to operate in outdoor environments hostile to the human presence, such as debris resulting from the collapse of built structures, and is targeted to the tele-operated detection of potential survivors using a set of specific sensors whose information is transmitted to a remote human operator. RAPOSA's mechanical structure is composed of a main body and a front body, whose locomotion is supported on tracked wheels, allowing motion even when the robot is upside down. The front body has variable tilting capabilities, providing means to overcome edges higher than the robot main body (e.g., when climbing a stair) and is also useful to grab the lower ground when only the main body has ground contact. This front body has one thermal camera and two web cameras installed. Additional sensors include gas, temperature and humidity sensors, Web cams, light diodes, microphone and loudspeaker. The robot uses wireless communications, with an option for tethered operation. The tether carries both power and communications, with an access point on its end, and can also be used to suspend the robot inside a deep hole. Docking and undocking the robot to the tether is accomplished remotely by the operator with the help of a camera located inside the robot, and represents the most innovative feature of RAPOSA
Fast determination of QoS-based multicast routes in wireless networks using genetic algorithm

In this paper, we propose a novel multicast route discovery scheme for wireless networks, satisfying quality of service (QoS) constraints such as bandwidth requirement and end-to-end delay guarantees. The underlying approach is based on a genetic algorithm (GA). The problem of (optimal) multicast route discovery is NP-hard when the network state information is inaccurate, which is so common in the wireless domain. In general, this makes it difficult to determine multicast routes on demand, and hence the network resources are never used to their full potential. The proposed GA based method, however, is shown to discover multicast routes for large networks within few iterations, even with imprecise network information, and thus it ran be used for an on-demand basis. We observed an approximate linear relationship between the computation time and the number of nodes in a network. In addition we have studied the effects of choosing the fitness function of the GA.
Resistance and Its Management to Microbial and Insect Growth Regulator Larvicides in Mosquitoes

Mosquito larvicides derived from microbial organisms and insect growth regulators have been increasingly used to control mosquito larvae worldwide. Their relative target specif‐ icity, nontarget safety, and environmentally friendly profile have been well documented. The current chapter was intended to review and analyze the relevant information regard‐ ing resistance development and resistance management tactics. Bacillus thuringiensis isra‐ elensis de Bajac (B.t.i.) is a quick-acting and highly target-specific biopesticide against mosquitoes, blackflies, and other nematoceran species. Resistance development toward intact complementary toxin complex of B.t. i. was rare; however, low to high levels of re‐ sistance to individual toxins have occurred in laboratory mosquito populations. The tox‐ ins from bacterium Bacillus sphaericus Neide (recently renamed Lysinibacillus sphaericus Meyer and Neide) is another highly active larvicide against mosquitoes, toward which low to high levels of resistance have occurred in both laboratory and field mosquito pop‐ ulations. The Cyt1A toxin from B.t. i. and Mtx toxin from certain strains of B. sphaericus are the key components in resistance management to B.t. i. and B. sphaericus. The resist‐ ance management strategies have been well developed and implemented. Spinosad de‐ rived from Saccharopolyspora spinosa Mertz and Yao has been recently used for mosquito control; high levels of resistance and cross-resistance have occurred in laboratory mosqui‐ to populations and no management tactics have ever been developed. Methoprene has been used to control mosquitoes for decades, and low to high levels of resistance have been occasionally reported in both laboratory and field mosquito populations. Studies on mechanism and management of methoprene resistance are quite meager. Very little at‐ tention has been paid to the resistance management in mosquitoes to other insect growth regulators such as pyriproxyfen and diflubenzuron. The prevention of resistance and re‐ storation of susceptibility in mosquitoes to these biorational larvicides are crucial to the success of sustainable integrated mosquito management.
Personal and Social Components of the Protestant Ethic

Summary In an attempt to assess social group correlates of scores on the Mirels-Garrett Protestant Ethic scale, 219 American male and female students were administered the scale, together with items dealing with religious group affiliation, ethnic self-identification, political self-identification, socioeconomic status, and religious beliefs. Results showed that for the American students, Protestant Ethic scores were related significantly to religious self-identification, ethnic background, political self-identification, and religious beliefs. They were not related to socioeconomic status. Results are interpreted as indicating that for the American student sample Protestant Ethic scores are not a “personality variable” but reflect social and cultural background elements.
Development of a thinking programme for engineering students

The challenge of preparing engineering graduates for a fast‐changing work environment calls for the development of thinking programmes. A psychological basis was used to develop the tenets of the approach. The Cognitive Modifiability Intervention (CMI) was rationalized and conceived as a corollary of observations of learning scenarios and an application of the theory of Structural Cognitive Modifiability (SCM). The CMI curriculum encapsulates the following key areas: (1) belief system and affective‐motivational processes; (2) mediated learning experience; (3) cognitive functions; (4) instruments for intervention; and (5) bridging for transfer of learning. The CMI included four major clusters of cognitive domains, namely the Affective‐Motivation Domain (ADM), the Systematic‐Strategic Thinking (SST) cluster, the Analytical‐Inferential Thinking (AIT) cluster and the Divergent‐Creative Thinking (DICT) cluster. It is argued that understanding the cognitive needs of engineering students, an approach of dealing with the prerequisites of thinking through active modification, and coaching skills through staff development are essential to the development of a cognitive curriculum for engineering education.
The DnaA Cycle in Escherichia coli: Activation, Function and Inactivation of the Initiator Protein

This review summarizes the mechanisms of the initiator protein DnaA in replication initiation and its regulation in Escherichia coli. The chromosomal origin (oriC) DNA is unwound by the replication initiation complex to allow loading of DnaB helicases and replisome formation. The initiation complex consists of the DnaA protein, DnaA-initiator-associating protein DiaA, integration host factor (IHF), and oriC, which contains a duplex-unwinding element (DUE) and a DnaA-oligomerization region (DOR) containing DnaA-binding sites (DnaA boxes) and a single IHF-binding site that induces sharp DNA bending. DiaA binds to DnaA and stimulates DnaA assembly at the DOR. DnaA binds tightly to ATP and ADP. ATP-DnaA constructs functionally different sub-complexes at DOR, and the DUE-proximal DnaA sub-complex contains IHF and promotes DUE unwinding. The first part of this review presents the structures and mechanisms of oriC-DnaA complexes involved in the regulation of replication initiation. During the cell cycle, the level of ATP-DnaA level, the active form for initiation, is strictly regulated by multiple systems, resulting in timely replication initiation. After initiation, regulatory inactivation of DnaA (RIDA) intervenes to reduce ATP-DnaA level by hydrolyzing the DnaA-bound ATP to ADP to yield ADP-DnaA, the inactive form. RIDA involves the binding of the DNA polymerase clamp on newly synthesized DNA to the DnaA-inactivator Hda protein. In datA-dependent DnaA-ATP hydrolysis (DDAH), binding of IHF at the chromosomal locus datA, which contains a cluster of DnaA boxes, results in further hydrolysis of DnaA-bound ATP. SeqA protein inhibits untimely initiation at oriC by binding to newly synthesized oriC DNA and represses dnaA transcription in a cell cycle dependent manner. To reinitiate DNA replication, ADP-DnaA forms oligomers at DnaA-reactivating sequences (DARS1 and DARS2), resulting in the dissociation of ADP and the release of nucleotide-free apo-DnaA, which then binds ATP to regenerate ATP-DnaA. In vivo, DARS2 plays an important role in this process and its activation is regulated by timely binding of IHF to DARS2 in the cell cycle. Chromosomal locations of DARS sites are optimized for the strict regulation for timely replication initiation. The last part of this review describes how DDAH and DARS regulate DnaA activity.
In nucleoli, the steady state of nucleolar proteins is leptomycin B‐sensitive

Background information. The nucleolus is a dynamic structure. It has been demonstrated that nucleolar proteins rapidly associate with and dissociate from nucleolar components in continuous exchanges with the nucleoplasm using GFP (green fluorescent protein)‐tagged proteins. However, how the exchanges within one nucleolus and between nucleoli within the nuclear volume occurred is still poorly understood.
GNFC: Towards network function cloudification

An increasing demand is seen from enterprises to host and dynamically manage middlebox services in public clouds in order to leverage the same benefits that network functions provide in traditional, in-house deployments. However, today's public clouds provide only a limited view and programmability for tenants that challenges flexible deployment of transparent, software-defined network functions. Moreover, current virtual network functions can't take full advantage of a virtualized cloud environment, limiting scalability and fault tolerance. In this paper we review and evaluate the current infrastructural limitations imposed by public cloud providers and present the design and implementation of GNFC, a cloud-based Network Function Virtualization (NFV) framework that gives tenants the ability to transparently attach stateless, container-based network functions to their services hosted in public clouds. We evaluate the proposed system over three public cloud providers (Amazon EC2, Microsoft Azure and Google Compute Engine) and show the effects on end-to-end latency and throughput using various instance types for NFV hosts.
Formal test-case generation for UML statecharts

The unified modelling language has been introduced as a notation for modelling and reasoning about large and complex systems, and their design, across a wide range of application domains. System modelling and analysis techniques, especially those based on formal methods, are more and more used for enhancing traditional system engineering techniques for improving system quality. In particular this holds for model-based formal test case derivation using formal conformance testing. The contribution of the present paper is to provide a solid mathematical basis for conformance testing and automatic test case generation for UML statecharts (UMLSCs). We propose a formal conformance-testing relation for input-enabled transition systems with transitions labelled by input/output-pairs (IOLTSs). IOLTSs provide a suitable semantic model for a behavioural subset of UMLSCs. We also provide an algorithm which, for a UMLSC specification and the alphabet of implementations, generates a test suite. The algorithm is proven exhaustive and sound w.r. t. the conformance relation.
Moment curves

We define a transfer function based on the first and second statistical moments. We consider the evolution of the mean and variance with respect to a growing neighborhood around a voxel. This evolution defines a curve in 3D for which we identify important trends and project it back to 2D. The resulting 2D projection can be brushed for easy and robust classification of materials and material borders. The transfer function is applied to both CT and MR data.
Towards asynchronous A-D conversion

Analog to digital (A-D) converters with a fixed conversion time are subject to errors due to metastability. These errors will occur in all converter designs with a bounded time for decisions, and are potentially severe. We estimate the frequency of these errors in a successive approximation converter, and compare the results with asynchronous designs using both a fully speed-independent, and a bundled data approach. It is shown that an asynchronous converter is more reliable than its synchronous counterpart, and that the bundled data design is also faster, on average, than the synchronous design. We also demonstrate trade-offs involved in asynchronous converter designs, such as speed, robustness to delay variations, circuit size and design scalability.
Mining probabilistic color palettes for summarizing color use in artwork collections

Artists and designers often use examples to find inspirational ideas for using colors. While growing public art repositories provide more examples to choose from, understanding the color use in such large artwork collections can be challenging. In this paper, we present a novel technique for summarizing the color use in large artwork collections. Our technique is based on a novel representation, probabilistic color palettes, which can intuitively summarize the contextual and stylistic use of colors in a collection of artworks. Unlike traditional color palettes that only encapsulate what colors are used using a compact set of representative colors, probabilistic color palettes encode the knowledge of how the colors are used in terms of frequencies, positions, and sizes, using an intuitive set of probability distributions. Given a collection of artworks organized by artist, we learn the probabilistic color palettes using a probabilistic colorization model, which describes the colorization process in a probabilistic framework and considers the impact of both spatial and semantic factors upon the colorization process. The learned probabilistic color palettes allows users to quickly understand the color use within the collection. We present results on a large collection of artworks by different artists, and evaluate the effectiveness of our probabilistic color palettes in a user study.
Interaction of Motor Training and Intermittent Theta Burst Stimulation in Modulating Motor Cortical Plasticity: Influence of BDNF Val66Met Polymorphism

Cortical physiology in human motor cortex is influenced by behavioral motor training (MT) as well as repetitive transcranial magnetic stimulation protocol such as intermittent theta burst stimulation (iTBS). This study aimed to test whether MT and iTBS can interact with each other to produce additive changes in motor cortical physiology. We hypothesized that potential interaction between MT and iTBS would be dependent on BDNF Val66Met polymorphism, which is known to affect neuroplasticity in the human motor cortex. Eighty two healthy volunteers were genotyped for BDNF polymorphism. Thirty subjects were assigned for MT alone, 23 for iTBS alone, and 29 for MT + iTBS paradigms. TMS indices for cortical excitability and motor map areas were measured prior to and after each paradigm. MT alone significantly increased the motor cortical excitability and expanded the motor map areas. The iTBS alone paradigm also enhanced excitability and increased the motor map areas to a slightly greater extent than MT alone. A combination of MT and iTBS resulted in the largest increases in the cortical excitability, and the representational motor map expansion of MT + iTBS was significantly greater than MT or iTBS alone only in Val/Val genotype. As a result, the additive interaction between MT and iTBS was highly dependent on BDNF Val66Met polymorphism. Our results may have clinical relevance in designing rehabilitative strategies that combine therapeutic cortical stimulation and physical exercise for patients with motor disabilities.
Dynamic dispersion framework for router load balancing

Load balancing is a key technology to achieve high performance as well as high reliability. Most of traditional approaches are based on a critical assumption that the service qualities of channels are already known. With such information, they attempted to preventively disperse workloads to attain fairness and therefore high efficiency. However, in practice, such information is difficult to obtain, especially when dispersion is performed at high-level layers. In this paper, we propose a novel scheme Dynamic dispersion frAMework (DAM), to adoptively disperse the traffic. Based on collected statistics, DAM dynamically adjusts the dispersion strategy to achieve fairness in terms of real capabilities of channels. Our experimental results show that DAM provides an accurate dispersion strategy compared with an offline optimal solution. The other advantage of DAM is that it is transparent to both the user and the server.
The Economics of the Diaspora Revisited

Comments are presented on an article by Reuven Brenner and Nicholas M. Kiefer in which they hypothesized that refugees will over-invest in human capital and under-invest in physical capital. In the original article data were presented showing "higher levels of schooling and occupational status for U.S. Jews compared with non-Jews and for Palestinian refugees compared with most other Arab groups in the Arab Middle East. " In the present critique the interpretation of these results is challenged. A reply by Brenner is also included (pp. 877-8). (EXCERPT)
Self-Evaluations of Social Rank and Affiliation in Social Anxiety: Explicit and Implicit Measures

We examined implicit and explicit self-evaluations (SEs) and their relation to social anxiety. So far, research indicated that individuals high in social anxiety consistently report low explicit SE, while concurrently exhibiting high implicit SE. To understand this pattern, we highlight the distinctions between the domains of social rank and of affiliation. In Study 1, participants (N = 113) completed a self-report measure of global SE, as well as self-ratings of social rank and affiliation measures. In Study 2 (N = 84), implicit measures (based on self-IAT, Implicit Association Task, Greenwald & Farnham, 2000) versions of social rank and affiliation SE were added. In both Study 1 and Study 2, severity of social anxiety was negatively associated with social rank, but not affiliation SEs, over and above the association with depression and global SE. In Study 2, social anxiety severity was negatively associated with explicit and implicit measures of social rank above and beyond the influence of general SE, .