Miracle-dz/UniFAR-FTUs huggingface dataset:
Image segmentation algorithm based on feature fusion and cluster

In order to make balance between the effect and time consumption of image segmentation, an image segmentation algorithm based on feature fusion and cluster is proposed in this paper. Firstly, the segmentation granularity is obtained adaptively according to the coarseness of image; secondly, different features are extracted, multi features are fused and classified by K-means clustering, and the image can be segmented quickly. Experiments show that the proposed algorithm can segment image quickly, and the segmentation effect is good, which has verified the validity.
Differential Role of the Proteasome in the Early and Late Phases of BDNF-Induced Facilitation of LTP

The neurotrophin brain-derived neurotrophic factor (BDNF) mediates activity-dependent long-term changes of synaptic strength in the CNS. The effects of BDNF are partly mediated by stimulation of local translation, with consequent alterations in the synaptic proteome. The ubiquitin-proteasome system (UPS) also plays an important role in protein homeostasis at the synapse by regulating synaptic activity. However, whether BDNF acts on the UPS to mediate the effects on long-term synaptic potentiation (LTP) has not been investigated. In the present study, we show similar and nonadditive effects of BDNF and proteasome inhibition on the early phase of synaptic potentiation (E-LTP) induced by theta-burst stimulation of rat hippocampal CA1 synapses. The effects of BDNF were blocked by the proteasome activator IU1, suggesting that the neurotrophin acts by decreasing proteasome activity. Accordingly, BDNF downregulated the proteasome activity in cultured hippocampal neurons and in hippocampal synaptoneurosomes. Furthermore, BDNF increased the activity of the deubiquitinating enzyme UchL1 in synaptoneurosomes and upregulated free ubiquitin. In contrast to the effects on posttetanic potentiation, proteasome activity was required for BDNF-mediated LTP. These results show a novel role for BDNF in UPS regulation at the synapse, which is likely to act together with the increased translation activity in the regulation of the synaptic proteome during E-LTP.
A fall avoidance foot mechanism for a biped locomotor

This paper describes one method to stop suddenly and safely avoid falling using only hardware and without a computer system. This method consists of attaching a braking function to leg actuators and the development of a fall avoidance mechanism, attached to the robot's foot. Using the human-carrying biped locomotor WL-16RII developed by Sugahara et al., the effectiveness of the method proposed in this paper was confirmed through an emergency stopping experiment during walking, while carrying a heavy load
Design Considerations of Very Low Profile Coupled Inductors for Flexible Photovoltaic Module

Power converters with flexible PCB integrated magnetic components are highly demanded in future photovoltaic (PV) applications, resulting in a higher power density. In this paper, a 1.5-mm thickness integrated coupled inductor with planar sandwich core structure is under investigation. Several important design issues for the sandwich core structure including self-inductance, leakage inductance, eddy current effect and core loss are analyzed in-depth in this work. Since the non-uniform flux is distributed in the core plates, the parameters calculation and the design considerations are completely different with the traditional magnetic approaches. Accordingly, this paper enables original design considerations as a guideline for sandwiched coupled inductor. In order to reduce the high frequency eddy current effect in sandwich core structure, section III initiates a discussion with adjustable core structures and winding arrangements such as closed core structure, gapped structure and meander winding. The tradeoffs among them are presented.
Science and dance collective motions

Modelling collective movements of animals, which is a field of current research in physics, was used to support educational innovation involving scientists (students and researchers) and professional dancers at the end of their initial training process. The basic elements to understand this model and the original association between science and art are described by showing the contributions - and their limits – to the informal teaching of science and dance.
Simple mathematical model for solar cell development forecasting

Solar cells are made of several materials and device structures with the main goal of having maximum efficiency at low cost. Some types of solar cells have shown a rapid efficiency progress whereas others seem to remain constant as a consequence of different factors such as the technological and economic ones. Using information published by the National Renewable Energy Laboratory (NREL) about the increase of solar cells record efficiency we are proposing a mathematical model which let us estimate the evolution in the near future for the different cell technologies. Here, as an example, we use data for solar cells made with representative materials and structures of each of the three “PV generations”.
On Trading Off Consistency and Coverage in Inductive Rule Learning

Evaluation metrics for rule learning typically, in one way or another, trade off consistency and coverage. In this work, we investigate this tradeoff for three different families of rule learning heuristics, all of them featuring a parameter that implements this trade-off in different guises. These heuristics are the m-estimate, the F -measure, and the Klosgen measures. The main goals of this work are to extend our understanding of these heuristics by visualizing their behavior via isometrics in coverage space, and to determine optimal parameter settings for them. Interestingly, even though the heuristics use quite different ways for implementing this trade-off, their optimal settings realize quite similar evaluation functions. Our empirical results on a large number of datasets demonstrate that, even though we do not use any form of pruning, the quality of the rules learned with these settings outperforms standard rule learning heuristics and approaches the performance of Ripper, a state-of-the-art rule learning system that uses extensive pruning and optimization phases.
ACTA: The SAGA Continues

ACTA is a comprehensive transaction framework that permits a transaction modeler to specify the e ects of extended transactions on each other and on objects in the database. ACTA allows the speci cation of (1) the interactions between transactions in terms of relationships between signi cant (transaction management) events, such as begin, commit, abort, delegate, split, and join, pertaining to di erent transactions and (2) transactions' e ects on objects' state and concurrency status (i.e., synchronization state). Various extended traditional models have been proposed to deal with applications that involve reactive (endless), open-ended (long-lived) and collaborative (interactive) activities. One such model is Sagas [GS87] A Saga is a set of relatively independent (component) transactions T 1 , T 2 ,. , T n which can interleave in any way with component transactions of other Sagas. Components can commit even before the Saga commits. However, if the Saga subsequently aborts, e ects of the committed components are nulli ed through the invocation of compensating transactions. After giving a brief introduction to the modeling primitives of ACTA, we illustrate their use by giving a complete formal characterization of Sagas. Subsequently, the reasoning power of ACTA is shown by proving properties of Sagas. Finally, the exibility of ACTA is displayed through a series of variations to the original model of Sagas, each variation coming out of changes to the formal characterization of Sagas. This is a reprint of Chapter 10 of \Transactions Models for Advanced Database Applications," edited by A. K. Elmagarmid of Purdue University and published by Morgan Kaufmann (1992) This material is based upon work supported by the N.S. F. under grant CDA-8922572. E-mail: panos@cs.pitt. edu, krithi@cs.umass. edu. Panos K. Chrysanthis Krithi Ramamritham
Multi-Task Feature Selection on Multiple Networks via Maximum Flows

We propose a new formulation of multi-task feature selection coupled with multiple network regularizers, and show that the problem can be exactly and efficiently solved by maximum flow algorithms. This method contributes to one of the central topics in data mining: How to exploit structural information in multivariate data analysis, which has numerous applications, such as gene regulatory and social network analysis. On simulated data, we show that the proposed method leads to higher accuracy in discovering causal features by solving multiple tasks simultaneously using networks over features. Moreover, we apply the method to multi-locus association mapping with Arabidopsis thaliana genotypes and flowering time phenotypes, and demonstrate its ability to recover more known phenotype-related genes than other state-of-the-art methods.
Designing a commutative replicated data type for cooperative editing systems

Cooperative editing systems enable distributed users to collaborate by concurrently editing a shared document, but care is required to ensure convergence and correctness. This problem turns out to be surprisingly complex. In this paper, we present a new approach for managing replicated data in cooperative editing systems, Commutative Replicated Data Types (CRDT). In a CRDT, all concurrent operations commute. Along with causal ordering, this suffices to guarantee convergence and preserve correctness, requiring no further concurrency control. We propose a novel CRDT for concurrent editing, the treedoc, which requires considerably less storage than the state of the art. Furthermore, a novel technique, background consensus, is used to clean up redundant metadata without interfering with ordinary edit operations. This mechanism is generic, and could be used to improve other algorithms.
Walls of Red Wing: An Examination of Culturally-Informed Sentencing, Risk/Need Factors, and Treatment for Peoples of Indigenous Heritage in Canada's Criminal Justice System

Given the over-representation of Indigenous peoples in the criminal justice system, steps have been taken to enhance the cultural relevance of sentencing, assessment and treatment. Specifically, changes to legislation and sentencing (e.g., s. 718.2 [e] of the Criminal Code, introduction of conditional sentence orders), as well as operational changes (e.g., creation of culturally-relevant programming), were introduced to address over-representation. More recently, the question of whether commonly-used risk assessments contain cultural-bias when applied to Indigenous peoples has been argued before the Supreme Court (i.e., Ewert v. Canada, 2018). To better understand the potential impacts of these legislative and operational changes, and seek to better understand the potentially unique causes of criminal behaviour for Indigenous peoples, three studies were conducted. Study 1 examined the application of conditional sentence orders (CSOs) with a sample of Indigenous offenders (n = 749) compared to Caucasian offenders (n = 1,625). It was found that Indigenous individuals received shorter CSOs and had a higher likelihood of being convicted of breach. However, no differences regarding the number and type of optional supervision conditions were found between groups, after controlling for individual-level factors (e.g., risk level, severity of offence). Study 2 identified and examined culturally-relevant risk/need factors with an Indigenous Advisory Group (N = 51). The process of co-development and thematic analysis resulted in the Culturally-Relevant Factors Questionnaire, consisting of 12 themes (e.g. residential school experience, stability of upbringing, experience of discrimination, extreme poverty). The questionnaire was administered to a sample (N = 36) of Indigenous males on community supervision. Lastly, Study 3 consisted of a meta-analysis examining the effectiveness of culturally-relevant correctional programming with Indigenous offenders. Results based on seven studies (N = 1,731) indicated that Indigenous offenders who participate in these programs have significantly lower odds of recidivism (odds ratio = 0.72) compared to Indigenous offenders who participate in generic programs. The implications of the three studies lend support to increasing the cultural relevance of sentencing, assessment, and programming. Furthermore, they highlight the need to better understand potentially unique or salient factors that can enhance the effectiveness of strategies for Indigenous peoples in the criminal justice system.
Evolutionary ARMA Model Identification With Unknown Process Order

The fundamental problem of selecting the order and identifying the parameters of an AutoRegressive Moving Average model (ARMA) has been faced effectively, using the Multi Model Partitioning (MMP) theory. The disadvantage of this method is the use of a fixed population of candidate models. Depending on the a priori selection of the set of conditional models, this method gives (near) optimal solutions. This disadvantage can be alleviated using natural selection techniques, such as the Genetic Algorithms (GAs). Thus, a new Evolution Program (EP) is developed in this work. This method combines the effectiveness of the MMP theory with the robustness of the GAs. Although the parameters' coding is more complicated, simulation results show that the proposed algorithm succeeds better results compared to the conventional one, since it has the ability to search the whole parameter space. Key-Words: AutoRegressive Moving Average model, Multi Model Partitioning theory, Genetic Algorithms, Evolution Program. CSCC'99 Proceedings: Pages 1951-1958
Complete font generation of Chinese characters in personal handwriting style

Since a complete Chinese font has typically several thousand or more Chinese characters and symbols, and most of them are much more complicated than English alphabets, it takes a lot of time and efforts for even professional font engineers to create a Chinese font. Although several attempts had been made to synthesize Chinese characters from strokes and components, it is still not easy to synthesize so many Chinese characters at one time. In this paper, we present an easy and fast solution for an ordinary user to create a Chinese font of his or her handwriting style. We adopt the approach: to synthesize Chinese characters using components extracted from the user's handwritings. In the preprocessing phase, we built a Web interface for crowds to label the positions and sizes of components of every Chinese character in the target character set. The standard Kai font was selected as a reference. We also devised an algorithm to find a small subset of Chinese characters having all required components to synthesize other Chinese characters. To create a personal handwriting font, with commonly-used 3,914 traditional Chinese characters, a user only has to handwrite 400 or so Chinese characters on a pad. One character by one character, our system can track every stroke, recognize and extract components from the user's handwritings. Then, every target Chinese character is synthesized from the extracted components, by placing them properly according to their position and size information. The experiment results show that although manually fine-tune is still required for few synthesized Chinese characters, users can create a Chinese font of their personal handwriting styles more easily and quickly.
High-value document generation: a common methodology proposal

Lean extended enterprise and build-to-order induce better integration of PLM activities that go through computer aided systems and knowledge-based information environments [1]. This change of landmarks from physical document to electronics claims to redefine information support functionalities [2]. These information have to be shared and exchanged between the actors of the process. Specifications or constraints are usually transmitted from one expert to the other in a global convergence [3]. The differences between their competencies limit the global understanding of problems. Computer integration in the expertise chain aims to optimize this kind of relations and thus the use of enterprise knowledge. The number of different enterprise concepts and complexities caused by different interpretations of these concepts encourages enterprises to standardize concepts and formalize behaviors. These efforts build re-usable and adaptable platforms and imply deep business architecture redeployments [4]. The rapidly changing environment requires convenient collaboration knowledge integration tools [5] and interoperability between different information sources [6]. The main difficulty encountered is to control the complexity of information quantity and informality. A reduction of the work-structure diversity helps in this regard to optimize the information efficiency. Seen from the process of collaborative document writing, it is hard to guarantee the consistency of the document's subject. The contents of shared documents may deal with many subjects and fields, and every collaborator would compose the text by its own understanding, different from other's because of different knowledge backgrounds. As a result the subject of the shared documents will be inconsistent among many copies. Furthermore, the communications between col-laborative systems, the systems and environments will also influence the consistency of the subject. An approach focusing on the semantic and syntax distinction can help to resolve the consistency problems involved in collaborative writing [7]. This work is part of a collaboration project between two research teams supported by NRF in South Africa and CNRS in France. It aims at the identification of possible synergy around performance indicators for knowledge management improvement. This collaboration starts from a global observation. When benefits from productivity optimization be
Preserving Subjective Wellbeing in the Face of Psychopathology: Buffering Effects of Personal Strengths and Resources

Background Many studies on resilience have shown that people can succeed in preserving mental health after a traumatic event. Less is known about whether and how people can preserve subjective wellbeing in the presence of psychopathology. We examined to what extent psychopathology can co-exist with acceptable levels of subjective wellbeing and which personal strengths and resources moderate the association between psychopathology and wellbeing. Methods Questionnaire data on wellbeing (Manchester Short Assessment of Quality of Life/Happiness Index), psychological symptoms (Depression Anxiety Stress Scales), and personal strengths and resources (humor, Humor Style questionnaire; empathy, Empathy Quotient questionnaire; social company; religion; daytime activities, Living situation questionnaire) were collected in a population-based internet study (HowNutsAreTheDutch; N = 12,503). Data of the subset of participants who completed the above questionnaires (n = 2411) were used for the present study. Regression analyses were performed to predict wellbeing from symptoms, resources, and their interactions. Results Satisfactory levels of wellbeing (happiness score 6 or higher) were found in a substantial proportion of the participants with psychological symptoms (58% and 30% of those with moderate and severe symptom levels, respectively). The association between symptoms and wellbeing was large and negative (-0.67, P < .001), but less so in persons with high levels of self-defeating humor and in those with a partner and/or pet. Several of the personal strengths and resources had a positive main effect on wellbeing, especially self-enhancing humor, having a partner, and daytime activities. Conclusions Cultivating personal strengths and resources, like humor, social/animal company, and daily occupations, may help people preserve acceptable levels of wellbeing despite the presence of symptoms of depression, anxiety, and stress.
The networking shape of vehicular mobility

Mobility is the distinguishing feature of vehicular networks, affecting the evolution of network connectivity over space and time in a unique way. Connectivity dynamics, in turn, determine the performance of networking protocols, when they are employed in vehicle-based, large-scale communication systems. Thus, a key question in vehicular networking is: which effects does nodes mobility generate on the topology of a network built over vehicles? Surprisingly, such a question has been quite overlooked by the networking research community. In this paper, we present an in-depth analysis of the topological properties of a vehicular network, unveiling the physical reasons behind the peculiar connectivity dynamics generated by a number of mobility models. Results make one think about the validity of studies conducted under unrealistic car mobility and stimulate interesting considerations on how network protocols could take advantage of vehicular mobility to improve their performance.
Pallister-Killian syndrome

Patient: Male, 0 Final Diagnosis: Pallister-Killian syndrome Symptoms: Decidious tooth • flattened nasal bridge • frontal bossing • grooved palate • low-set ears • mid-facial hypoplasia • nuchal fold thickening • right inquinal testis • shortened upper extremities • undescended left intraabdominal testis • widely spaced nipples Medication: — Clinical Procedure: — Specialty: Pediatrics and Neonatology Objective: Congenital defects/diseases Background: Pallister-Killian syndrome (PKS) is a rare, sporadic, polydysmorphic condition that often has highly distinctive features. The clinical features are highly variable, ranging from mild to severe intellectual disability and birth defects. We here report the first case of PKS diagnosed at our institution in a patient in the second trimester of pregnancy. Case Report: A pregnant 43-year-old woman presented for genetic counseling secondary to advanced maternal age and an increased risk for Down syndrome. Ultrasound showed increased fetal nuchal fold thickness, short limbs, polyhydramnios, and a small stomach. The ultrasound evaluation was compromised due to the patient’s body habitus. The patient subsequently underwent amniocentesis and the karyotype revealed the presence of an isochromosome in the short arm of chromosome 12 consistent with the diagnosis of Pallister-Killian syndrome. Postnatally, the infant showed frontal bossing, a flattened nasal bridge, mid-facial hypoplasia, low-set ears, a right upper deciduous tooth, grooved palate, nuchal fold thickening, widely spaced nipples, left ulnar polydactyly, simian creases, flexion contractures of the right middle finger, shortened upper extremities, undescended left intraabdominal testis, and right inguinal testis. Conclusions: The occurrence of PKS is sporadic in nature, but prenatal diagnosis is possible.