Miracle-dz/UniFAR-FTUs huggingface dataset:
Ritual among the Masses: Deconstructing Identity and Class in an Ancient Maya Neighborhood

Abstract Equating a single cultural group to a classificatory scheme has implications for not only how archaeologists develop the concept of cultural identity but how we investigate and theorize about internal social dynamics within that same society. For the ancient Maya, social organization remains largely understood as a two-class system—that of commoner and elite. While these categories reflect the extreme ends of known social strata, they inadequately characterize the reality of day-to-day interactions. This has led to tacit assumptions that commoners did not participate in or comprehend the political and social complexity of the world around them. This paper examines how occupants of a Late Classic Maya neighborhood employed ritual and public practices as a means of social differentiation. Excavations at the Northeast Group, part of the ancient Maya site of Chan, Belize, identified considerable diversity between households, suggesting that occupants shaped status and identity through the control and centralization of ritual. Understanding how people distinguished themselves within the context of a neighborhood provides direct evidence of class complexity, challenging traditional models of commoner behavior and more importantly the role they played in ancient Maya society as a whole.
Optimization methods for computer-aided design of artificial dielectric lens antennas

The paper investigates the optimization of an electrically large antenna : a shaped dielectric substrate lens at millimeter wave frequencies (76 – 77 GHz). The aim is to determine the best lens profile that complies with arbitrary desired radiation pattern templates. A feed forward artificial neural network (ANN) was implemented in order to predict the radiation pattern of this antenna. Particle Swarm Optimization (PSO) procedure, combined with neural network modeling, is applied in order to minimize the cost function (the fitness function) and to fit specifications. The optimized results are in a good agreement with 3D MoM simulations.
Title Distinct neural activity associated with focused-attentionmeditation and loving-kindness meditation

This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (lovingkindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotionprocessing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing. Citation: Lee TMC, Leung M-K, Hou W-K, Tang JCY, Yin J, et al. (2012) Distinct Neural Activity Associated with Focused-Attention Meditation and Loving-Kindness Meditation. PLoS ONE 7(8): e40054. doi:10.1371/journal.pone. 0040054 Editor: Suliann Ben Hamed, CNRS Université Claude Bernard Lyon 1, France Received June 29, 2011; Accepted June 5, 2012; Published August 15, 2012 Copyright: 2012 Lee et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This study was supported by research funding from the Centre of Buddhist Studies of The University of Hong Kong and the Research Grant Council General Research Fund (Ref: HKU747612H). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: tmclee@hku.hk (TMCL); Chetwyn.Chan@inet.polyu. edu.hk (CCHC)
Treatment of anorexia nervosa in a specialty care continuum.

OBJECTIVE Inpatient hospitalization has been a mainstay of treatment for anorexia nervosa (AN), but decreasing lengths of inpatient stay have prompted the development of alternative care-continuum models. This study characterizes the 6-month outcomes of 71 patients with AN who completed an inpatient-treatment protocol (approximately 5 weeks), followed by a day-hospital program (DHP) (approximately 3 weeks). METHOD Data were derived from chart reviews and questionnaire data were collected during routine clinical care. RESULTS On discharge from DHP, 35.2% of patients showed excellent outcomes, whereas 23.9% exhibited poor outcomes. At 6 months after DHP discharge, 47.9% of the patients were successful in maintaining outpatient treatment status. Patients with successful 6-month outcomes were admitted to inpatient at a higher weight, had fewer previous hospitalizations, were younger, were rated by inpatient staff as more committed to treatment, endorsed less AN psychopathology during inpatient admission, and showed greater weight gain during DHP. Number of previous hospitalizations and weight gain immediately after inpatient discharge predicted 89.2% of outcome classifications 6 months after DHP discharge. CONCLUSION These findings highlight both the potential benefits of this care-continuum model for patients who previously have not been hospitalized and the pressing need to develop alternative treatment strategies for patients with more chronic AN.
Relevance Assessment ( Un-) Reliability in Information Retrieval : Minimizing Negative Impact

Collecting relevance assessments is a very important procedure in Information Retrieval. It is conducted to (1) evaluate the performance of an existing search engine, or (2) build and train a new one. While most of the popular performance evaluation measures and search engine training algorithms assume the relevance assessments are accurate and reliable, in practice this assumption is often violated. Whether intentionally or not, assessors may provide noisy and inconsistent relevance judgments potentially leading to (1) wrong conclusions about performance of a search engine, or (2) inefficient or suboptimal training of a search engine. Addressing the problem above, we first (a) demonstrate how one can quantify the negative effect of assessor disagreement (including intra-assessor disagreement as a special case) on the ranking performance of a search engine. Beside this theoretical result, we also propose practical recipes for (b) tuning existing evaluation measures with the goal of making them more robust to the label noise, (c) improving the reliability of relevance estimates by collecting and aggregating multiple assessments (potentially through crowdsourcing), and (d) incorporating noise reduction component into learning-to-rank algorithms.
Measuring anxiety: Parent‐child reporting differences in clinical samples

This study examines parent‐child reporting differences for childhood anxiety in normal controls (n = 16) and in children with diagnosed anxiety disorders (ANX; n = 15), attention‐deficit hyperactivity disorder (ADHD; n = 15), and comorbid ANX and ADHD (n = 16). Correspondence between child reports of anxiety on two self‐report inventories and diagnosis based on structured parent interview was assessed for all four groups. Parent‐child agreement did not appear to be measurement dependent but did differ by diagnostic group, with poorer agreement for clinical groups. Though needing replication, these findings suggest that it is inadvisable to rely exclusively on self‐report measures when assessing childhood anxiety, especially in clinical populations. Such measures can be useful in monitoring clinical progress, however, provided parent and child reports are examined separately. Depression and Anxiety 15:61–65, 2002. © 2002 Wiley‐Liss, Inc.
Successive Decoding with Hierarchical Interference Cancellation in Wireless (Physical Layer) Network Coding Systems

The intermediate network nodes (relays) in Wireless (Physical Layer) Network Coding (WNC) systems are allowed to process only some specific ("hierarchical") functions of user data (instead of separate decoding of individual user signals), which allows to overcome the rate limits induced by the conventional Multiple Access Channels capacity regions. Unfortunately, since the mapping between a specific decoded hierarchical function and the corresponding signal space representation is generally one-to-many, traditional successive decoding techniques with perfect interference cancellation (subtraction) of decoded signals cannot be directly employed in WNC systems. In this paper we show that even in this case the knowledge of hierarchical data can be efficiently exploited in the decoding process to significantly reduce the impact of interfering signal on the subsequent decoding operations in WNC systems.
A 1.52 uJ/classification patient-specific seizure classification processor using Linear SVM

This paper presents an 8-channel electroencephalograph (EEG) classification processor for seizure detection and recording. To integrate 8 channels, an area- and energy-efficient filter architecture using Distributed Quad-LUT (DQ-LUT) is proposed, which reduces area by 64.2% with minimal overhead in power-delay product. The on-chip patient specific classification with a Linear Support-Vector Machine (SVM) results in 82.7% seizure detection accuracy with a 2 second latency using the CHB-MIT EEG database [1]. The overall energy efficiency is measured as 1. 52μJ/classification while operating at 8 channel mode.
Telomere length and the risk of lung cancer

Telomeres play a key role in the maintenance of chromosome integrity and stability. There is growing evidence that short telomeres induce chromosome instability and thereby promote the development of cancer. We investigated the association of telomere length and the risk of lung cancer. Relative telomere length in peripheral blood lymphocytes was measured by quantitative polymerase chain reaction in 243 lung cancer patients and 243 healthy controls that were frequency‐matched for age, sex and smoking status. Telomere length was significantly shorter in lung cancer patients than in controls (mean ± standard deviation: 1.59 ± 0.75 versus 2.16 ± 1.10, P < 0.0001). When the subjects were categorized into quartiles based on telomere length, the risk of lung cancer was found to increase as telomere length shortened (Ptrend < 0.0001). In addition, when the median of telomere length was used as the cutoff between long and short telomeres, individuals with short telomeres were at a significantly higher risk of lung cancer than those with long telomeres (adjusted odds ratio = 3.15, 95% confidence interval = 2.12–4.67, P < 0.0001). When the cases were categorized by tumor histology, the effect of short telomere length on the risk of lung cancer was more pronounced in patients with small cell carcinoma than in those with squamous cell carcinoma and adenocarcinoma (P = 0.001, test for homogeneity). These findings suggest that shortening of the telomeres may be a risk factor for lung cancer, and therefore, the presence of shortened telomeres may be used as a marker for susceptibility to lung cancer. (Cancer Sci 2008; 99: 1385–1389)
BIOINFORMATICS APPLICATIONS

Summary: The Mirrortree server allows to graphically and interactively study the co-evolution of two protein families, and investigate their possible interactions and functional relationships in a taxonomic context. The server includes the possibility of starting from single sequences and hence it can be used by non-expert users. Availability and Implementation: The web server is freely available at http://csbg.cnb. csic.es/mtserver. It was tested in the main web browsers. Adobe Flash Player is required at the client side to perform the interactive assessment of co-evolution. Contact
Draft Genome Sequences of Two Streptococcus pneumoniae Serotype 19F Sequence Type 271 Clinical Isolates with Low- and High-Level Cefotaxime Resistance

ABSTRACT We report here the draft genomes of two pneumococcal isolates in Hong Kong, CU_SPNE1_05 and CU_SPNE32_06. Strain CU_SPNE1_05 had a cefotaxime MIC of 1 µg/ml, and CU_SPNE32_06 had an MIC of 32 µg/ml. Both strains belong to the multidrug-resistant serogroup 19, sequence type 271 (clonal complex 3200/271).
Crop water requirements model tested for crops grown in Greece

A model for estimating crop water requirements throughout crop development is presented. The model assumes horizontal uniformity and treats the two-component system of canopy and soil along the lines of Shuttleworth and Wallace (1985). Incorporated in the model is a 3-layer soil water budget allowing evaluation of the soil surface and canopy resistances and time evolution of the soil moisture in the root zone. Canopy interception is also taken into account. Model parameterization considered mostly the crop canopy resistance, assuming neutral atmospheric stability conditions, whereas parameterization of the aerodynamic resistances allows for smooth transition from bare soil to a fully developed crop canopy. The model has been validated with meteorological (temperature, relative humidity, wind speed, net radiation ̄ux density, solar radiation ̄ux density and soil heat ̄ux density, precipitation or irrigation) and crop (height, leaf area index and root depth) data collected from experimental ®elds of the Agricultural University of Athens (388230 N, 238060 E). Results were veri®ed for three crops (cotton, wheat and maize) against soil moisture pro®le changes with very satisfactory results. Agreement between observed and estimated evapotranspiration is within 8%. The model is sensitive to crop type and time evolution of the root zone penetration into soil while precise determination of the minimum stomata resistance is not exclusively important. # 2000 Elsevier Science B.V. All rights reserved.
Voltage Analytics for Power Distribution Network Topology Verification

Distribution grids constitute complex networks of lines oftentimes reconfigured to minimize losses, balance loads, alleviate faults, or for maintenance purposes. Topology monitoring becomes a critical task for optimal grid scheduling. While synchrophasor installations are limited in low-voltage grids, utilities have an abundance of smart meter data at their disposal. In this context, a statistical learning framework is put forth for verifying single-phase grid structures using non-synchronized voltage data. The related maximum likelihood task boils down to minimizing a non-convex function over a non-convex set. The function involves the sample voltage covariance matrix and the feasible set is relaxed to its convex hull. Asymptotically in the number of data, the actual topology yields the global minimizer of the original and the relaxed problems. Under a simplified data model, the function turns out to be convex, thus offering optimality guarantees. Prior information on line statuses is also incorporated via a maximum a-posteriori approach. The formulated tasks are tackled using solvers having complementary strengths. Numerical tests using real data on benchmark feeders demonstrate that reliable topology estimates can be acquired even with a few smart meter data, while the non-convex schemes exhibit superior line verification performance at the expense of additional computational time.
Polyglutamine toxicity in yeast uncovers phenotypic variations between different fluorescent protein fusions

The palette of fluorescent proteins (FPs) available for live‐cell imaging contains proteins that strongly differ in their biophysical properties. FPs cannot be assumed to be equivalent and in certain cases could significantly perturb the behavior of fluorescent reporters. We employed Saccharomyces cerevisiae to comprehensively study the impact of FPs on the toxicity of polyglutamine (polyQ) expansion proteins associated with Huntington's disease. The toxicity of polyQ fusion constructs is highly dependent on the sequences flanking the polyQ repeats. Thus, they represent a powerful tool to study the impact of fluorescent fusion partners. We observed significant differences on polyQ aggregation and toxicity between commonly used FPs. We generated a novel series of vectors with latest yeast‐optimized FPs for investigation of Htt toxicity, including a newly optimized blue FP for expression in yeast. Our study highlights the importance of carefully choosing the optimal FPs when designing tagging strategies.
Monad compositions II: Kleisli strength

In this paper we introduce the concept of Kleisli strength for monads in an arbitrary symmetric monoidal category. This generalises the notion of commutative monad and gives us new examples, even in the cartesian-closed category of sets. We exploit the presence of Kleisli strength to derive methods for generating distributive laws. We also introduce linear equations to extend the results to certain quotient monads. Mechanisms are described for finding strengths that produce a large collection of new distributive laws, and consequently monad compositions, including the composition of monadic data types such as lists, trees, exceptions and state.
Ensemble Kalman Filter based on the Image Structures

One major limitation of the motion estimation methods that are available in the literature concerns the availability of the uncertainty on the result. This is however assessed by a number of filtering methods, such as the ensemble Kalman filter (EnKF). The paper consequently discusses the use of a description of the displayed structures in an ensemble Kalman filter, which is applied for estimating motion on image acquisitions. An example of such structure is a cloud on meteorological satellite acquisitions. Compared to the Kalman filter, EnKF does not require propagating in time the error covariance matrix associated to the estimation, resulting in reduced computational requirements. However, EnKF is also known for exhibiting a shrinking effect when taking into account the observations on the studied system at the analysis step. Methods are available in the literature for correcting this shrinking effect, but they do not involve the spatial content of images and more specifically the structures that are displayed on the images. Two solutions are described and compared in the paper, which are first a dedicated localization function and second an adaptive domain decomposition. Both methods proved being well suited for fluid flows images, but only the domain decomposition is suitable for an operational setting. In the paper, the two methods are applied on synthetic data and on satellite images of the atmosphere, and the results are displayed and evaluated.
Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem

The electric power industry is going through deregulation. As a result, the load on the generating units of a utility is becoming increasingly unpredictable. Furthermore, electric utilities may need to buy power or sell their production to a power pool that serves as a spot market for electricity. These trading activities expose utilities to volatile electricity prices. In this paper, we present a stochastic model for the unit commitment that incorporates power trading into the picture. Our model also accounts for fuel constraints and prices that may vary with electricity prices and demand. The resulting model is a mixed-integer program that is solved using Lagrangian relaxation and Bender's decomposition. Using this solution approach, we solve problems with 729 demand scenarios on a single processor to within 0.1% of the optimal solution in less than 10 minutes. Our numerical results indicate that significant savings can be achieved when the spot market is entered into the problem and when stochastic policy is adopted instead of a deterministic one.
The complete mitochondrial genome of the Downy woodpecker, Picoides pubescens (Piciformes: Picidae)

Abstract The Downy woodpecker (Picoides pubescens) is a species of woodpecker which is the smallest in North America. This present study firstly reported the complete mitochondrial genome of downy woodpecker. We performed assembly of mitogenome structural by SPAdes and the Picidae species Dryocopus pileatus act as a reference. The mitogenome was 16 840 bp in length, which contains 13 protein-coding genes, 22 transfer RNAs, 2 ribosomal RNAs and 1 putative misc-feature region. The overall AT content is 52.76% which is higher than GC. To approve the accuracy of new determined mitogenome sequences, a phylogenetic tree of downy woodpecker together with other nine closely species was established by 12 protein-coding genes. This first complete mitogenome of Picoides species will contribute to identify species and study the related evolution events.
Cigarette Smoking among African American Youth from Single Mother Homes: Examining the Roles of Maternal Smoking and Positive Parenting within an Extended Family Framework.

The current study examined the main and interactive effects of three family context variables, maternal smoking, positive parenting behavior, and the quality of the mother’s relationship with another adult or family member who assists with parenting (i.e., coparent), and adolescent smoking among African American youth from single mother homes. The pattern of findings revealed maternal warmth buffered the association between maternal smoking and adolescent smoking, but only in families characterized by high levels of mother-coparent conflict. Results suggest the protective role of maternal warmth may be overlooked in studies that fail to consider the broader family network within which maternal behaviors occur in many African American single mother families. Findings are discussed with regard to their implications for smoking prevention programs aimed at African American youth.