Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive and Affective Theory of Mind and Relations With Executive Functioning in Middle Childhood

Abstract:Theory of mind (ToM) refers to the ability to make inferences about mental states. Thus far, little research has examined ToM development in middle childhood. Importantly, recent studies have distinguished between making inferences about beliefs (cognitive ToM) and emotions (affective ToM). ToM has also been associated with executive functioning, though research on the differential relations between cognitive ToM and affective ToM and specific components of executive functioning is scarce. The current study examined advanced cognitive and affective ToM in 8-to 11-year-olds (N = 168). Working memory, inhibition, and set-shifting abilities were also assessed. Results showed that, in this age group, cognitive ToM increased significantly with age, and combined cognitive and affective ToM trendwise increased with age. All three domains of executive functioning (EF) showed age-related improvement. Inhibitory control and verbal IQ significantly predicted cognitive ToM, whereas verbal IQ predicted affective ToM. These results suggest that cognitive and affective components of ToM are distinguishable and may be differentially related to EF.
Nitrogen Deposition Enhances Carbon Sequestration by Plantations in Northern China

Nitrogen (N) deposition and its ecological effects on forest ecosystems have received global attention. Plantations play an important role in mitigating climate change through assimilating atmospheric CO2. However, the mechanisms by which increasing N additions affect net ecosystem production (NEP) of plantations remain poorly understood. A field experiment was initialized in May 2009, which incorporated additions of four rates of N (control (no N addition), low-N (5 g N m−2 yr−1), medium-N (10 g N m−2 yr−1), and high-N (15 g N m−2 yr−1)) at the Saihanba Forestry Center, Hebei Province, northern China, a locality that contains the largest area of plantations in China. Net primary production (NPP), soil respiration, and its autotrophic and heterotrophic components were measured. Plant tissue carbon (C) and N concentrations (including foliage, litter, and fine roots), microbial biomass, microbial community composition, extracellular enzyme activities, and soil pH were also measured. N addition significantly increased NPP, which was associated with increased litter N concentrations. Autotrophic respiration (AR) increased but heterotrophic respiration (HR) decreased in the high N compared with the medium N plots, although the HR in high and medium N plots did not significantly differ from that in the control. The increased AR may derive from mycorrhizal respiration and rhizospheric microbial respiration, not live root respiration, because fine root biomass and N concentrations showed no significant differences. Although the HR was significantly suppressed in the high-N plots, soil microbial biomass, composition, or activity of extracellular enzymes were not significantly changed. Reduced pH with fertilization also could not explain the pattern of HR. The reduction of HR may be related to altered microbial C use efficiency. NEP was significantly enhanced by N addition, from 149 to 426.6 g C m−2 yr−1. Short-term N addition may significantly enhance the role of plantations as an important C sink.
Privacy risks emerging from the adoption of innocuous wearable sensors in the mobile environment

Wearable sensors are revolutionizing healthcare and science by enabling capture of physiological, psychological, and behavioral measurements in natural environments. However, these seemingly innocuous measurements can be used to infer potentially private behaviors such as stress, conversation, smoking, drinking, illicit drug usage, and others. We conducted a study to assess how concerned people are about disclosure of a variety of behaviors and contexts that are embedded in wearable sensor data. Our results show participants are most concerned about disclosures of conversation episodes and stress - inferences that are not yet widely publicized. These concerns are mediated by temporal and physical context associated with the data and the participant's personal stake in the data. Our results provide key guidance on the extent to which people understand the potential for harm and data characteristics researchers should focus on to reduce the perceived harm from such datasets.
Prostaglandin E 2 Inhibits p 53 in Human Breast Adipose Stromal Cells : A Novel Mechanism for the Regulation of Aromatase in Obesity and Breast Cancer

Obesity is a risk factor for postmenopausal breast cancer and the majority of these cancers are estrogen dependent. Aromatase converts androgens into estrogens and its increased expression in breast adipose stromal cells (ASC) is a major driver of estrogen receptor–positive breast cancer. In particular, obesity-associated and tumor-derived factors, such as prostaglandin E2 (PGE2), have been shown to drive the expression of aromatase by stimulating the activity of the proximal promoter II (PII). The tumor-suppressor p53 is a key regulator of cell-cycle arrest and apoptosis and is frequentlymutated in breast cancer.Mutations in p53 are rare in tumor-associated ASCs. Therefore, it was hypothesized that p53 is regulated by PGE2 and involved in the PGE2-mediated regulation of aromatase. Results demonstrate that PGE2 causes a significant decrease in p53 transcript and nuclear protein expression, as well as phosphorylation at Ser15 in primary human breast ASCs. Stabilization of p53with RITA leads to a significant decrease in the PGE2-stimulated aromatase mRNA expression and activity, and PII activity. Interaction of p53with PII was demonstrated and this interaction is decreased in the presence of PGE2. Moreover, mutation of the identified p53 response element leads to an increase in the basal activity of the promoter. Immunofluorescence on clinical samples demonstrates that p53 is decreased in tumor-associated ASCs compared with ASCs from normal breast tissue, and that there is a positive association between perinuclear (inactive) p53 and aromatase expression in these cells. Furthermore, aromatase expression is increased in breast ASCs from Li–Fraumeni patients (germline TP53mutations) compared with non-Li–Fraumeni breast tissue. Overall, our results demonstrate that p53 is a negative regulator of aromatase in the breast and its inhibition by PGE2 provides a novelmechanism for aromatase regulation in obesity and breast cancer. Cancer Res; 75(4); 645–55.
Design of Dual Notch Filter from UWB Bandpass Filter to Reject 5 GHz Narrowband WLAN Service

This paper presents a dual notch filter from UltraWideband (UWB) bandpass filter for the purpose of avoiding the interference between the UWB radio system and the existing WLAN system. The 5 GHz WLAN (IEEE 802.11a) exists in 5.15-5.35 GHz and 5.725-5.825 GHz which are called as lower and upper band respectively. The filter is based on ring resonator with interdigital coupling at both sides. The interdigital coupling is used instead of direct coupling for the reason of strong coupling and to introduce capacitance effect to obtain flat passband. The notched band can be designed to some specific frequency band(s) by introducing four open stubs at the coupling arms nearby the ring geometry. Design of the UWB bandpass and notch filters are proposed and group delay has also been obtained for both filters in this paper. As the simulated results, for bandpass filter, the insertion and return loss are about -1.3 dB and -45 dB respectively over the passband of 5.56 GHz. For notch filter, the dual notch is obtained at 5.1 GHz with -20 dB and 5.9 GHz with -9 dB. The overall size of the designed filter is 6×39.2×1.6 mm3. The proposed filters have also shown good outband performance that is better than Federal Communications Commission’s (FCC) mask.
Pine dust, atopy and lung function: a cross-sectional study in sawmill workers

An increased risk of asthma symptoms has previously been shown in 772 pine sawmill workers. The aim of the current study was to assess the association between dust exposure, lung function and atopy. Subjects with (n = 59) and without (n = 167) asthma symptoms were randomly selected from the previous survey. Lung function and atopy were determined using spirometry and skin-prick tests, respectively. Inhalable dust levels were measured on the same day. The geometric mean dust concentration was 0.52 mg·m-3. Exposure to dry but not to green dust was associated with asthma symptoms. Green dust was associated with atopic sensitisation, particularly against outdoor allergens; no association was found for dry dust. Forced vital capacity, forced expiratory volume in one second and peak expiratory flow were significantly lower in workers exposed to high levels of green dust (-350 mL, -260 mL and -860 mL·s-1, respectively) and dry dust (-230 mL, -190 mL and -850 mL·s-1, respectively). These associations were observed both in subjects with and without asthma symptoms. No associations with cross-shift changes in lung function were found. Exposure to green pine sawdust may be a risk factor for atopy. Both green and dry dust were associated with obstructive as well as restrictive pulmonary effects.
Ontology-Based Application for Domain Rules Development

While there is a great interest in rule-based systems and their development, none of the proposed languages or methods has been accepted as a standard technology yet. Nowadays tools used in process of information systems (IS) development are not extended and adapted enough for modelling and implementation of application domain rules. A particular contingent of researchers proposes using of ontology for development of intelligent IS, since ontology is suitable to represent application domain knowledge. We are challenged in using ontology for the development of application domain rules. In this paper we present a method for ontology axioms transformation to application domain rules and describe how ontology-based development of application domain rules is integrated through IS development life cycle.
QuIT: Quantitative IP Traceback

Traceback is the technique to trace packets back to the sources or the routers near the sources, which is essential while defending against IP spoofing and denial of service attacks. In this paper we present the design of QuIT (Quantitative IP traceback) system which can trace the origin of a single packet and figure out the distribution of packets from each source. QuIT generates audit trails for packets and transfers them along with the traffic to provide the ability of audit for the downstream victims. The traceback can be operated locally near the victim without communicating with other routers or ISPs, which increases the feasibility of deployment. Theoretic analysis and simulation experiments demonstrated that the traffic increased by the QuIT system is less than 0.12% and computation complexity is affordable.
Toward Discovery of the Artist's Style: Learning to recognize artists by their artworks

Author attribution through the recognition of visual characteristics is a commonly used approach by art experts. By studying a vast number of artworks, art experts acquire the ability to recognize the unique characteristics of artists. In this article, we present an approach that uses the same principles to discover the characteristic features that determine an artist's touch. By training a convolutional neural network (PigeoNET) on a large collection of digitized artworks to perform the task of automatic artist attribution, the network is encouraged to discover artist-specific visual features. The trained network is shown to be capable of attributing previously unseen artworks to the actual artists with an accuracy of more than 70%. In addition, the trained network provides fine-grained information about the artist-specific characteristics of spatial regions within the artworks. We demonstrate this ability by means of a single artwork that combines characteristics of two closely collaborating artists. PigeoNET generates a visualization that indicates for each location on the artwork who is the most likely artist to have contributed to the visual characteristics at that location. We conclude that PigeoNET represents a fruitful approach for the future of computer-supported examination of artworks.
An embedded decryption/decompression engine using Handel-C

Speed and security of data streams are two key factors in different areas such as data communication and multimedia. Compression algorithms are applied to data streams to increase their communication speed while encryption algorithms are used for assuring the security of the data transfer. AES and LZ77 are two well known algorithms for data encryption and compression respectively. In this paper we propose a model to implement both algorithms, decryption and decompression, in a field programmable gate array chip. Such a design must address the issues of optimal resource usage of the FPGA, and balance between the throughput of both algorithms. Handel-C is considered as the specification language for this design.
Rural Teacher Practices and Partnerships to Address Behavioral Challenges: The Efficacy and Mechanisms of Conjoint Behavioral Consultation

The efficacy of conjoint behavioral consultation (CBC), a family-school partnership intervention, for teachers’ practices and process skills was evaluated. Participants were 152 teachers of grades K–3 in 45 Midwest rural schools randomly assigned to treatment or control conditions. Treatment group teachers participated in an 8- to 10-week CBC intervention. Outcome measures were (a) self-reports of classroom practices and collaborative process skills and (b) direct observations of teachers’ use of effective behavioral strategies. Relative to control group participants, there was a significant positive intervention effect on CBC teachers’ self-report of appropriate behavioral strategies (β = .47, p < .001), observations of their use of positive attention (β = .50, p < .001) and positive consequences (β = .72, p < .001), and competence in addressing problems (β = .95, p < .001). Teachers’ appropriate strategy use was mediated by their use of problem-solving processes. Implications for rural settings are discussed.
Proximity-based rocchio's model for pseudo relevance

Rocchio's relevance feedback model is a classic query expansion method and it has been shown to be effective in boosting information retrieval performance. The selection of expansion terms in this method, however, does not take into account the relationship between the candidate terms and the query terms (e.g., term proximity). Intuitively, the proximity between candidate expansion terms and query terms can be exploited in the process of query expansion, since terms closer to query terms are more likely to be related to the query topic. In this paper, we study how to incorporate proximity information into the Rocchio's model, and propose a proximity-based Rocchio's model, called PRoc, with three variants. In our PRoc models, a new concept (proximity-based term frequency, ptf) is introduced to model the proximity information in the pseudo relevant documents, which is then used in three kinds of proximity measures. Experimental results on TREC collections show that our proposed PRoc models are effective and generally superior to the state-of-the-art relevance feedback models with optimal parameters.A direct comparison with positional relevance model (PRM) on the GOV2 collection also indicates our proposed model is at least competitive to the most recent progress.
Multiple-symbol differential detection for space-time block codes with diversity reception

In this paper, the diversity reception of differential space-time block coding (STBC) system using multiple-symbol differential detection (MSDD) method with multiple receive antennas is considered. Postdetection maximum ratio combining (MRC), postdetection equal-gain combining (EGC) and predetection selective combining (SC) are used as diversity combining techniques. Their performance is analyzed by computer simulations
PAPEL : A lexical ontology for Portuguese [ Extended

PAPEL (Palavras Associadas Porto Editora Linguateca) is a lexical resource for natural language processing (NLP) of Portuguese which is being built by Linguateca, based on processing a major commercial Portuguese dictionary, the Dicionário da Ĺıngua Portuguesa (DLP) [1] developed and owned by the largest Portuguese dictionary publisher, Porto Editora. There are known similar lexical resources for English and other languages. WordNet [10] is probably the most important reference and it is widely used in NLP research. WordNet was created from scratch, while we are creating the tools needed to build PAPEL (semi)automatically. We could say that this work is mainly inspired by the MindNet [11] project. MindNet is a knowledge representation resource that used a broad-coverage parser to build semantic networks from machine readable human dictionaries (MRDs). The process of using MRDs to do NLP started back in the 1970’s. Early known publications were from Nicoletta Calzolari [4]. A lot of work around MRDs took place during the 1980’s ([9], [3], [5], [8], [2] and many more), but it was not until MindNet that we got an independent lexical ontology with knowledge automatically extracted from MRDs. As far as we know, PAPEL is the first lexical ontology built by semi-automatic means for Portuguese, whose developments started October 2007. To start our research some preliminary studies were made and some information about the dictionary structure was collected. After an empirical analysis of the most frequent ngrams, some initial grammars including specific string patterns to extract semantic relations were created and tested with a small portion of the dictionary (about 5000 entries). The grammars were developed for the PEN parser 1 which is a parser that implements the Earley’s algorithm [7]. The first grammar extracted Cause-of/Caused-by relations between words. Currently we are working on grammars to extract the Part-of and Hypernymy relations. In the PAPEL project we have also developed a system for automatically identifying differences between the output of different versions of the same grammar, for regression testing. In the future we intend to have a lexical resource whose base structures are concepts and not words. In order to accomplish our purpose we are hoping that, after having a network consisting of relations between words, some different senses of the same word might emerge. We are also planning is using some disambiguation methods (similar to [6]) to identify clustering related senses. This presentation will start with a quick overview of existing similar resources, focusing on the the relations they provide. We will then show several patterns consisting of Portuguese words that can be used to identify some of those relations in the definitions of the DLP. Some examples of extracted relations and relations we believe we can extract will also be shown, as well as the tools developed. We will end with some discussion about the directions our work can take in the next months.
On Effective Protection of Security and Privacy in XML Information Brokering

In contrast with the situations when the information seeker knows where the needed data is located, XML Information Brokering System (IBS) needs to help each information seeking query ”locate” the corresponding data source(s). Unlike early information sharing approaches that only involve a small number of databases, new information sharing applications are often assumed to be built atop a large volume of geographically distributed databases, such as emergence health care. Moreover, with increasing concerns on protecting the sensitive and/or proprietary data, the organizations prefer sharing data in a more secure and privacy-preserving manner, instead of establishing a purely full trust relationship and releasing the control over the shared data. In this paper, we explore new information sharing infrastructures to address the new challenges on security, privacy, load balancing, trust management and scalability. In this work, we present a flexible and scalable XML IBS using a broker-coordinator overlay network. Through a novel automaton segmentation scheme, in-network access control, distributed load balancing, trust management and query segment encryption, our system integrates security enforcement and query forwarding while preserving systemwide privacy. We first explore access control deployment strategies in distributed information sharing and the impacts of different deployment strategies on system-wide performance and security. From our study, we are motivated to enforce in-network access control by combining query security checking function with query routing function in Query Brokers and coordinators while maintaining distributed load balancing among peers. We perform a formal presentation of the threat models with a focus on two attacks: attribute-correlation attack and inference attack. Then, we propose a broker-coordinator overlay, as well as three schemes, automaton segmentation scheme, query segment encryption scheme and trust management scheme to share the secure query routing function among a set of brokering servers. We carried out a comprehensive analysis on privacy, end-to-end performance, load balancing and scalability, the proposed system integrate security enforcement, load balancing, trust management between peers and query routing while preserving system-wide privacy with reasonable overhead. Keywords— Privacy, XML, Access Control, load balancing, information sharing, peer to peer, PPIB
Time series prediction via neural network inversion

In this work, we propose neural network inversion of a backward predictor as a technique for multi-step prediction of dynamic time series. It may be difficult to train a large network to capture the correlation that exists in some dynamic time series represented by small data sets. The new approach combines an estimate obtained from a forward predictor with an estimate obtained by inverting a backward predictor to more efficiently capture the correlation and to achieve more accurate predictions. Inversion allows us to make causal use of prediction backward in time. Also a new regularization method is developed to make neural network inversion less ill-posed. Experimental results on two benchmark time series demonstrate the new approach's significant improvement over standard forward prediction, given comparable complexity.
ATMOSPHERIC PHASE CORRECTION USING CARMA-PACS: HIGH ANGULAR RESOLUTION OBSERVATIONS OF THE FU ORIONIS STAR PP 13S*

We present 0. ″15 resolution observations of the 227 GHz continuum emission from the circumstellar disk around the FU Orionis star PP 13S*. The data were obtained with the Combined Array for Research in Millimeter-wave Astronomy (CARMA) Paired Antenna Calibration System (C-PACS), which measures and corrects the atmospheric delay fluctuations on the longest baselines of the array in order to improve the sensitivity and angular resolution of the observations. A description of the C-PACS technique and the data reduction procedures are presented. C-PACS was applied to CARMA observations of PP 13S*, which led to a factor of 1.6 increase in the observed peak flux of the source, a 36% reduction in the noise of the image, and a 52% decrease in the measured size of the source major axis. The calibrated complex visibilities were fitted with a theoretical disk model to constrain the disk surface density. The total disk mass from the best-fit model corresponds to 0.06 M☉, which is larger than the median mass of a disk around a classical T Tauri star. The disk is optically thick at a wavelength of 1.3 mm for orbital radii less than 48 AU. At larger radii, the inferred surface density of the PP 13S* disk is an order of magnitude lower than that needed to develop a gravitational instability.