Miracle-dz/UniFAR-FTUs huggingface dataset:
Monetary Exchange as a Social Convention: Emergence and Stability of an Intermediating Commodity

This paper investigates the stability of monetary exchange equilibria and the conditions necessary for an equilibrium of this type to emerge endogenously. Previous research on money as a medium of exchange has depended on either initial conditions or steady state conditions to pinpoint equilibria, These approaches are not satisfactory for addressing the issue of emergence, either because the determining element is exogeneous, or because there are multiple equilibria without criteria for selecting between them. We construct an N-person non-cooperative anonymous game from an economy with many commodities and bilateral exchange. The environment is restricted so that in addition to direct barter opportunities there is a commodity - a token commodity with no value in consumption - which cab be used for intermediate exchanges. We make use of recent advances in evolutionary learning in games pioneered in Young (1003) and Kandori, Mailath, and Rob (1993) to characterize conditions under which monetary trade is typically observed in the long run regardless of initial conditions and discuss how informational assumptions affect transition time.
Lane marking aided vehicle localization

A localization system that exploits L1-GPS estimates, vehicle data, and features from a video camera as well as lane markings embedded in digital navigation maps is presented. A sensitivity analysis of the detected lane markings is proposed in order to quantify both the lateral and longitudinal errors caused by 2D-world hypothesis violation. From this, a camera observation model for vehicle localization is proposed. The paper presents also a method to build a map of the lane markings in a first stage. The solver is based on dynamical Kalman filtering with a two-stage map-matching process which is described in details. This is a software-based solution using existing automotive components. Experimental results in urban conditions demonstrate an significant increase in the positioning quality.
From Tenuous to Tenacious: Social Justice Practice in Child Welfare

ABSTRACT This qualitative study explores the relationship between social workers’ understanding of their professional obligation to work for social justice and their practice as child welfare workers. Twenty-five social workers with at least six months front line child welfare experience, from two Canadian provinces, were interviewed. Findings suggest that experienced workers were best able to link their understanding of social justice with their practice. In contrast novice workers, preoccupied with understanding and adhering to policy and procedures, were less able. Implications are discussed and suggestions made for better supporting new workers in aligning child welfare practice with social work’s social justice mission.
How Risky is College Investment?

This paper is motivated by the fact that nearly half of U.S. college students drop out without earning a bachelor’s degree. Its objective is to quantify how much uncertainty college entrants face about their graduation outcomes. To do so, we develop a quantitative model of college choice. The innovation is to model in detail how students progress towards a college degree. The model is calibrated using transcript and financial data. We find that more than half of college entrants can predict whether they will graduate with at least 80% probability. As a result, stylized policies that insure students against the financial risks associated with uncertain graduation have little value for the majority of college entrants.
Precise Modelling of Instruction Cache Behaviour

Safety critical real-time applications in aviation, automotive and industrial automation have to guarantee not only the functionality, but also the timeliness of the results. Here, a deadline is associated with the software tasks, and a failure to complete prior to this deadline could lead to a catastrophic consequences. Hence, for the correctness of real-time systems, it is essential to be able to compute the worst case execution time (WCET) of the tasks in order to guarantee their deadlines. However, the problem of WCET analysing is difficult, because of processors use cache-based memory systems that vary memory access time significantly. Any pessimistic estimation of the number of cache hits/misses will result in loose precision of the WCET analyses, which could lead to over use of hardware resources. In this paper, we present a new approach for statically analysing the behaviour of instructions on a direct mapped cache. The proposed approach combines binary representation and a new abstraction that reduces the analysis time without sacrificing the precision. This is unlike the existing cache analysing approaches where either precision or scalability (analysis time) is sacrificed. Experimental results are presented that demonstrate the practical applicability of this analysis.
Central Opioid Inhibition of Neuroendocrine Stress Responses in Pregnancy in the Rat Is Induced by the Neurosteroid Allopregnanolone

The hypothalamus–pituitary–adrenal (HPA) axis is the major neuroendocrine stress response system. Corticotropin-releasing hormone (CRH) neurons in the parvocellular paraventricular nucleus (pPVN) play a key role in coordinating responses of this system to stressors. The cytokine interleukin-1β (IL-1β), mimicking infection, robustly activates these CRH neurons via a noradrenergic input arising from the nucleus tractus solitarii (NTS). In late pregnancy, HPA axis responses to stressors, including IL-1β, are attenuated by a central opioid mechanism that auto-inhibits noradrenaline release in the PVN. Here we show that the neuroactive progesterone metabolite allopregnanolone induces these changes in HPA responsiveness to IL-1β in pregnancy. In late pregnancy, inhibition of 5α-reductase (an allopregnanolone-synthesizing enzyme) with finasteride restored HPA axis responses (rapidly increased pPVN CRH mRNA expression, ACTH, and corticosterone secretion) to IL-1β. Conversely, allopregnanolone reduced HPA responses in virgin rats. In late pregnancy, activity of the allopregnanolone-synthesizing enzymes (5α-reductase and 3α-hydroxysteroid dehydrogenase) was increased in the hypothalamus as was mRNA expression in the NTS and PVN. Naloxone, an opioid antagonist, restores HPA axis responses to IL-1β in pregnancy but had no additional effect after finasteride, indicating a causal connection between allopregnanolone and the endogenous opioid mechanism. Indeed, allopregnanolone induced opioid inhibition over HPA responses to IL-1β in virgin rats. Furthermore, in virgin rats, allopregnanolone treatment increased, whereas in pregnant rats finasteride decreased proenkephalin-A mRNA expression in the NTS. Thus, in pregnancy, allopregnanolone induces opioid inhibition over HPA axis responses to immune challenge. This novel opioid-mediated mechanism of allopregnanolone action may alter regulation of other brain systems in pregnancy.
Collective use of a situated display to encourage positive behaviors in children with behavioral challenges

Situated displays can support behavior management for children with behavioral challenges. However, existing tools are often static, rarely engaging, and tend to focus only on individual behavior. In this work, we designed and deployed a situated display to support teamwork and cooperation in children with behavioral challenges. We evaluated this tool in two classrooms of a public school specializing in behavioral interventions with 28 children over four weeks. The results of this work demonstrate that situated displays focused on collective behavioral performance can support reflection on individual performance, improve behavior for students with behavioral challenges, as well as encourage teamwork and cooperative behavior in classrooms. These results also indicate a variety of issues to be considered when designing situated displays for these environments, including considerations for the representation of ambiguity and failure as well as the relationship between novelty and engagement.
Efficient search of obstacle-free paths for anthropomorphic hands

The planning of collision-free motions of a hand-arm system to reach a grasp or preshape configuration is not a simple issue due to the high number of involved degrees of freedom. This paper presents an efficient sampling-based path planner that copes with this issue by considering a reduced search space. The dimension of this space is not fixed but it is iteratively increased according to the difficulty of the task at hand. Initially the search space is 1-dimensional along the line defined by the initial and goal hand configurations (by construction those configurations always belong to the search space), and then its dimension is increased by iteratively adding principal motion directions (that couple the finger motions), trying in this way to produce hand movements through anthropomorphic natural postures.
Information following a Diagnosis of Congenital Heart Defect: Experiences among Parents to Prenatally Diagnosed Children

Background Prenatal screening of pregnant women in Sweden has improved the detection of major congenital heart defects (CHD). The aim was to explore parental experiences and need for information following a prenatal diagnosis of CHD. Methods Semi-structured interviews conducted with six fathers and five mothers to seven prenatally diagnosed children. Data were analyzed through content analysis. Results Three themes and 9 categories emerged. Theme 1, Grasping the facts today while reflecting on the future, containing five categories: Difficulties sorting out information when in emotional chaos; Respectful information regarding termination of pregnancy; Early information is crucial; Understanding the facts regarding the anomaly; Preparing for the future. Theme 2, Personal contact with medical specialists who give honest and trustworthy information is valued, containing two categories: Trust in information received from medical specialists and Truth and honesty is valued. Theme 3, An overwhelming amount of information on the Internet, containing two categories: Difficulties in finding relevant information and Easy to focus on cases with a poor outcome when searching the Internet. Conclusion Early and honest information in line with individual preferences is crucial to support the decisional process regarding whether to continue or terminate the pregnancy. The use of illustrations is recommended, as a complement to oral information, as it increases comprehension and satisfaction with obtained information. Furthermore, the overwhelming amount of information on the Internet calls for compilation of easily accessible and reliable information sources via the Internet.
The application of the modular multilevel matrix converter in high-power wind turbines

The trend in wind turbines has shown an ongoing power rating growth, reaching sizes up to 10 MW. Multilevel converters have therefore become a favourable solution for Multi-MW Wind Energy Conversion Systems (WECSs), due to high efficiency, reliability, controllability and the ability to reach high power/voltage ratings. Moreover, stringent grid codes to regulate the connection of WECSs to the electrical networks have been developed in countries with a high penetration of wind energy. In this context, this paper introduces the novel application of the Modular Multilevel Matrix Converter for interfacing Multi-MW Wind Turbines to provide decoupled input-output regulation, variable speed operation and fulfilment of modern grid codes.
Development of Genetic Markers for Environmental DNA (eDNA) Monitoring of Sturgeon

EXECUTIVE SUMMARY: All living organisms shed DNA into the environment. Recent studies have demonstrated that environmental water samples can be effectively assayed for the DNA of target organisms. The DNA contained in these samples is commonly referred to as environmental DNA or eDNA. Because DNA assays can be sensitive to very small amounts of genetic material, eDNA surveys have the potential to detect sites where target organisms occur at very low abundances, potentially even when organisms are too rare for conventional survey methods to effectively detect them. We designed and tested twelve new eDNA markers for aquatic eDNA surveys of North American sturgeon. Eight of the markers are general for all North American sturgeon (i.e., not genus- or species-specific), two are specific to Scaphirhynchus sturgeon, and two are specific to white sturgeon (Acipenser transmontanus). The Scaphirhynchus marker could identify sites where endangered species like the pallid (S. albus) or Alabama (S. suttkusi) sturgeon might occur. Positive detections with the general sturgeon marker combined with the absence of positive detections with the white sturgeon marker could be used to discern if green sturgeon (A. medirostris) might occur at a location. All sturgeon markers were tested for specificity against a battery of 32 non-target fish species common to the Mississippi and Illinois River watersheds and the “sensitivity” or limit of detection for each marker was determined with assays of increasingly dilute solutions of target DNA. Four of the general sturgeon markers were used to assay 88 water samples from the Lower Mississippi River for sturgeon eDNA and resulted in 3 positive detections. While additional optimization of sturgeonspecific sampling protocols and marker assays is advised prior to use of these markers for sturgeon eDNA surveys, the newly designed markers represent a significant step forward in the use of eDNA in sturgeon monitoring and management. PURPOSE: This technical note focuses on the development of environmental DNA (eDNA) markers for detection of North American sturgeon species. Topics include design and laboratory testing of markers for a polymerase chain reaction (PCR)-based eDNA assay and an overview of good laboratory practices for the handling and processing of eDNA samples.
Automated anatomical labeling of bronchial branches using multiple classifiers and its application to bronchoscopy guidance based on fusion of virtual and real bronchoscopy

This paper presents a method for automated anatomical labeling of bronchial branches (ALBB) extracted from 3D CT datasets. The proposed method constructs classifiers that output anatomical names of bronchial branches by employing the machine-learning approach. We also present its application to a bronchoscopy guidance system. Since the bronchus has a complex tree structure, bronchoscopists easily tend to get disoriented and lose the way to a target location. A bronchoscopy guidance system is strongly expected to be developed to assist bronchoscopists. In such guidance system, automated presentation of anatomical names is quite useful information for bronchoscopy. Although several methods for automated ALBB were reported, most of them constructed models taking only variations of branching patterns into account and did not consider those of running directions. Since the running directions of bronchial branches differ greatly in individuals, they could not perform ALBB accurately when running directions of bronchial branches were different from those of models. Our method tries to solve such problems by utilizing the machine-learning approach. Actual procedure consists of three steps: (a) extraction of bronchial tree structures from 3D CT datasets, (b) construction of classifiers using the multi-class AdaBoost technique, and (c) automated classification of bronchial branches by using the constructed classifiers. We applied the proposed method to 51 cases of 3D CT datasets. The constructed classifiers were evaluated by leave-one-out scheme. The experimental results showed that the proposed method could assign correct anatomical names to bronchial branches of 89.1% up to segmental lobe branches. Also, we confirmed that it was quite useful to assist the bronchoscopy by presenting anatomical names of bronchial branches on real bronchoscopic views.
Study Of Vision Based Hand Gesture Recognition Using Indian Sign Language

Abstract Human Computer Interaction moves forward in the field of sign language interpretation. Indian Sign Language (ISL) Interpretation system is a good way to help the Indian hearing impaired people to interact with normal people with the help of computer. As compared to other sign languages, ISL interpretation has got less attention by the researcher. In this paper, some historical background, need, scope and concern of ISL are given. Vision based hand gesture recognition system have been discussed as hand plays vital communication mode. Considering earlier reported work, various techniques available for hand tracking, segmentation, feature extraction and classification are listed. Vision based system have challenges over traditional hardware based approach; by efficient use of computer vision and pattern recognition, it is possible to work on such system which will be natural and accepted, in general.
An NN-based Approach to Prosody Generation for English Word Spelling in English-Chinese Bilingual TTS

In this paper, an RNN-MLP-based scheme to generate proper prosodic information for spelling English words embedded in Chinese text background is proposed. It is extended from the RNN prosody synthesis scheme of an existing Mandarin TTS by adding four MLPs to follow the RNN. It first treats each English word as a Chinese word and uses the RNN to generate eight prosodic parameters for each alphabet of the word. It then uses these four MLPs to refine these prosodic parameters. Experimental results showed that the proposed RNN-MLP scheme led to 36.3, 37.3, 11.6, and 29.1% reductions in RMSE for the synthesized alphabet duration, log-energy level, pitch contour, and pause duration, respectively, over the scheme using the RNN only.
Fixation of buried and surface mounted magnets in high-speed permanent magnet synchronous motors

High-speed applications involve technical and economical advantages, because as direct drives they avoid the gear as an additional mechanical drive component Permanent magnet synchronous machines are attracting growing attention for high-speed drives. Surface mounted permanent magnet synchronous machines request a glass or carbon fibre bandage to fasten the magnets to the rotor surface at high speed. At rotors with "buried" magnets the rotor iron itself fixes the magnets. The paper presents simple calculation strategies and discusses their limits for the mechanical design of high-speed machines with either surface mounted or buried magnets. The results of the calculations are compared with FE-calculations.
A non-parametric statistics based method for generic curve partition and classification

Generic shape feature extraction is a challenging task for image and video content analysis. We present a non-parametric statistics based method for extracting generic shape tokens based on a Perceptual Curve Partition and Grouping (PCPG) model. In this PCPG model, each curve is made up of Generic Edge Tokens (GET) connected at Curve Partitioning Points (CPP). The types of GET and CPP provide a set of basic shape descriptors for semantic vocabulary. The new implementation of the PCPG is based on: 1) An arctangent space is employed to signify the evidence of CPPs at pixel-level. 2) The pixels' sequential order is taken as heuristic to establish a bin order preserving arctangent histogram for locating CPPs by examining the continuity of generic feature criteria statistically. 3) A new CPP detection scheme is capable of detecting CPPs and classifying GETs on the fly. Experiments are presented for performance demonstration.
Principals’ and Teachers’ Reports of Successful Teaching Strategies With Children With High-Functioning Autism Spectrum Disorder

Little research has been conducted on the evidence base for educational interventions implemented by teachers targeting students with high-functioning autism spectrum disorder (HFASD). Research examining particular techniques perceived as effective may facilitate guidelines for the application of evidence-based practices. A principal and teacher of students with HFASD from each of 29 different schools provided information on their current teaching interventions. Principals participated in an online survey designed to ascertain support for HFASD learners in their school, whereas teachers completed an online reflective journal to document methods they used in the classroom. Both teachers and principals found numerous strategies such as structure and incorporating needs to be successful. Inappropriate communication, disorganisation, and a lack of understanding were considered unhelpful. These results have implications for current practices in classrooms.
A comparison of in vivo 13C MR brain glycogen quantification at 9.4 and 14.1 T

The high molecular weight and low concentration of brain glycogen render its noninvasive quantification challenging. Therefore, the precision increase of the quantification by localized 13C MR at 9.4 to 14.1 T was investigated. Signal‐to‐noise ratio increased by 66%, slightly offset by a T1 increase of 332 ± 15 to 521 ± 34 ms. Isotopic enrichment after long‐term 13C administration was comparable (∼40%) as was the nominal linewidth of glycogen C1 (∼50 Hz). Among the factors that contributed to the 66% observed increase in signal‐to‐noise ratio, the T1 relaxation time impacted the effective signal‐to‐noise ratio by only 10% at a repetition time = 1 s. The signal‐to‐noise ratio increase together with the larger spectral dispersion at 14.1 T resulted in a better defined baseline, which allowed for more accurate fitting. Quantified glycogen concentrations were 5.8 ± 0.9 mM at 9.4 T and 6.0 ± 0.4 mM at 14.1 T; the decreased standard deviation demonstrates the compounded effect of increased magnetization and improved baseline on the precision of glycogen quantification. Magn Reson Med, 2011. © 2011 Wiley Periodicals, Inc.
Regression Estimation Combined with Conformal Mapping and Boundary Extracting and It's Application

The more training data there is, the slower training the support vector regression technique gives rise to. Thus, it is good to remove the non-support vector examples beforehand. In addition, small variation in kernel parameter has more influence on the generalization performance of the support vector regression approach than that in other parameters such as the regularization parameter C and the tube width ϵ. Therefore, kernel parameter optimization contributes to the small generalization error. This paper proposed a novel conformal kernel parameter transformation as well as training patterns reduction method to solve the regression problem. It determined the kernel center and kernel width in the factor function of kernel function based on data distribution of the high dimensional feature space. In particular, it preserved the volume around the boundary space, and reduced the spatial space on the non-support vector region. Moreover, it converted the regression problem to a classification problem, extracted the boundary points and then reduced the training patterns. Simulation results indicated that the present algorithm supported Housing dataset, improved the prediction accuracy by 10.76 percent over the primal approach, and reduced the number of support vectors from 192.4 to 144.7 over support vector regression. The proposed method also estimated the propylene concentration of propylene rectification tower. The experimental result of the propylene content demonstrated that our method decreased the prediction error by 14.07 percent over the neural network technique.