Miracle-dz/UniFAR-FTUs huggingface dataset:
Volume Visualization of Large Tetrahedral Meshes on Low Cost Platforms

Abstract Inthispaper,wepresentaninteractivesystemforvisu-alizationofthree-dimensionalscalarﬁelds. Thesystemhasbeendesignedinordertoovercomesomeoftheproblems posed by very large volume data sets. Theadopted solution exploits an eﬃcient multiresolutiondatastructurebasedonatetrahedraldomaindecompo-sition. Themeshtoberenderedcanbeselectivelyre-ﬁnedoverareasthattheuserconsidersmorecritical,onthebasisofeitherﬁeldvaluesordomainlocations. Thesystemsupportsdiﬀerentrenderingtechniques,suchasisosurfaceﬁttingandDirectVolumeRendering(DVR). 1 Introduction Space requirements and rendering time for a tetrahe-dralmeshareproportionaltoitsresolution,i.e.,tothedensity of its tetrahedra, and, thus, to the density ofthe underlying point set. When a tetrahedral mesh istoo large, data simpliﬁcation can be used in order tobring it to a more manageable size prior to visualiza-tion[3,1,8,7,6,11]. Inmanycases,itisveryusefultoapplysimpliﬁcationselectively,e.g.,onlyinaportionofthedomain,oronlyintheproximityofinterestingﬁeldvalues. Thisprocessisusuallycalled
FPGA dedicated hardware architecture of 3D image reconstruction: Marching cubes algorithm

Generally, the implementation of various treatments of medical images, especially the 3D reconstruction, should support a real-time execution of the algorithm on the architecture: It is to meet the constraints of latency and circuit space while minimizing the resource consumption. We are interested in this project for a 3D reconstruction of medical images on a platform based on an FPGA. We have as an objective the specification and hardware implementation of the reconstruction algorithm, the Marching Cubes.
Eating Behaviours of Preadolescent Children over Time: Stability, Continuity and the Moderating Role of Perceived Parental Feeding Practices

The links between childhood eating behaviours and parental feeding practices are well-established in younger children, but there is a lack of research examining these variables in a preadolescent age group, particularly from the child’s perspective, and longitudinally. This study firstly aimed to examine the continuity and stability of preadolescent perceptions of their parents’ controlling feeding practices (pressure to eat and restriction) over a 12 month period. The second aim was to explore if perceptions of parental feeding practices moderated the relationship between preadolescents’ eating behaviours longitudinally. Two hundred and twenty nine preadolescents (mean age at recruitment 8.73 years) completed questionnaires assessing their eating behaviours and their perceptions of parental feeding practices at two time points, 12 months apart (T1 and T2). Preadolescents’ perceptions of their parental feeding practices remained stable. Perceptions of restriction and pressure to eat were continuous. Perceptions of parental pressure to eat and restriction significantly moderated the relationships between eating behaviours at T1 and T2. The findings from this study suggest that in a preadolescent population, perceptions of parental pressure to eat and restriction of food may exacerbate the development of problematic eating behaviours.
Robot Learning with Neural Self-Organization

In this paper we describe a learning technique for reactive path-planning and guidance of autonomous robots using a Kohonen self-organizing neural network. The intended application is mineral exploration or agricultural monitoring using simple lowcost robots which do not contain a complete stored map of the environment, and may have unreliable sensor information. The network learns based on a simple sense of value, and our experiments with a simulated world show that this performs signi cantly better than rule-based learning.
An integrated data compression scheme using process monitoring and lifting wavelet transform

Based on the analysis of real-time data function of power plant and some current data compression methods, an integrated data compression scheme using process monitoring and lifting wavelet transform is proposed. In this method, the signal is first examined in order to find out the samples from abnormal states via process monitoring method. Then, the lifting wavelet transform is performed. As to signal with samples from abnormal states, approximate coefficients and detail coefficients that correspond to the abnormal data are reserved. Otherwise, only approximate coefficients are retained. As a consequence, the cost related with data storage and transmission is reduced. Meanwhile the samples from abnormal states that contain abundant fault information are preserved perfectly. The integrated scheme has been tested on real life signal and simulation results indicate that this method is valid and has a wide potential in application.
The anticancer agent YC-1 suppresses progestin-stimulated VEGF in breast cancer cells and arrests breast tumor development

Recent epidemiological studies show that postmenopausal women taking estrogen-progestin hormone replacement therapy (HRT) have a higher risk of breast cancer than women on an HRT regimen lacking progestins. This may be related to the observation that progestin-treated breast cancer cells express and secrete high levels of vascular endothelial growth factor (VEGF), a potent angiogenic factor that promotes breast tumor growth. Anti-progestins such as RU-486 block this effect, indicating that progesterone receptors (PR) are involved in promoting VEGF induction; however antiprogestins cross-react with other steroid receptors which limits their clinical use. Alternative strategies are, therefore, needed to arrest the growth of progestin-dependent tumors. 3-(5′-hydroxymethyl-2′-furyl)-1-benzylindazole (YC-1), a novel anticancer drug initially developed as an inhibitor of HIF-1α, is currently undergoing preclinical trials against various forms of cancer. Since HIF-1α has recently been implicated in PR-mediated VEGF synthesis, we undertook studies to determine whether YC-1 inhibits progestin-dependent VEGF induction and tumor progression. Surprisingly, we found that YC-1 downregulated PR in human breast cancer cells, both in vivo and in vitro, thereby blocking progestin-dependent induction of VEGF and tumor growth. YC-1 also inhibited progestin-accelerated DMBA-induced mammary tumors in rats, properties which would likely render it effective against progestin-dependent tumors which frequently develop in post-menopausal women. We, therefore, propose that based on our observations, YC-1 warrants further investigation as a novel agent which could prove extremely useful as an anti-angiogenic chemotherapeutic drug.
Loss and Recovery of Genetic Diversity in Adapting Populations of HIV

The evolution of drug resistance in HIV occurs by the fixation of specific, well-known, drug-resistance mutations, but the underlying population genetic processes are not well understood. By analyzing within-patient longitudinal sequence data, we make four observations that shed a light on the underlying processes and allow us to infer the short-term effective population size of the viral population in a patient. Our first observation is that the evolution of drug resistance usually occurs by the fixation of one drug-resistance mutation at a time, as opposed to several changes simultaneously. Second, we find that these fixation events are accompanied by a reduction in genetic diversity in the region surrounding the fixed drug-resistance mutation, due to the hitchhiking effect. Third, we observe that the fixation of drug-resistance mutations involves both hard and soft selective sweeps. In a hard sweep, a resistance mutation arises in a single viral particle and drives all linked mutations with it when it spreads in the viral population, which dramatically reduces genetic diversity. On the other hand, in a soft sweep, a resistance mutation occurs multiple times on different genetic backgrounds, and the reduction of diversity is weak. Using the frequency of occurrence of hard and soft sweeps we estimate the effective population size of HIV to be ( confidence interval ). This number is much lower than the actual number of infected cells, but much larger than previous population size estimates based on synonymous diversity. We propose several explanations for the observed discrepancies. Finally, our fourth observation is that genetic diversity at non-synonymous sites recovers to its pre-fixation value within 18 months, whereas diversity at synonymous sites remains depressed after this time period. These results improve our understanding of HIV evolution and have potential implications for treatment strategies.
The Influence of Transformation in Effective Training: Perspectives from Trainers in the Field

Training and development is often directly connected to human resources and less associated with adult education. However, through interviews of three trainers, it was found that through personal experiences, trainers undergo transformative learning to become trainers and such effects the way they perceive effective training. Introduction Training and development is often directly connected to human resources and less associated with adult education. In defining human resource development (HRD), Swanson (2001) stated “[it] is a process of developing and/or unleashing human expertise through organization development and personnel training and development for the purpose of improving performance” (p. 304); thus, indicating training and development as a major component of the responsibility of human resources for organizational effectiveness. However some trainers and scholars in HRD have recognized that effective training seeks to educate and not to simply train; therefore, there is an increasing emphasis on utilizing principles of adult education as foundational tools for facilitating trainings (Silberman, 2006). This study examines the experiences of three trainers in the automotive, international finance, and sales communication industries. The purpose of this study is to understand how work and life experiences contribute to the perceptions of effective training from three professional trainers. The study was guided by the following research questions: How do trainers learn to become trainers? How do trainers perceive effective training? Conceptual Framework This study is grounded in the adult learning theories of constructivist theory of learning and Mezirow’s transformative learning theory (Merriam, Caffarella, & Baumgartner, 2007). The ability to create an environment that encompasses a learner’s unique experiences and learning goals is important in effective training. The constructivist theory refers to how learners make meaning through prior experiences (Taylor, 2002). Additionally, it focuses on how facilitators can help adults learn and foster such learning through the structure of challenging learning activities and relevant curriculums (Taylor, 2002). The constructivist orientation recognizes that the learner’s perspective and experiences are critical in his/her decision to learn and participate in learning activities (Merriam et al., 2007). Furthermore, for adults to fully engage in the learning process, they must be able to relate the subject matter to their experiences and understand its relevance to improve their current state (Silberman, 2006). Transformative learning also provides the basis for creating a learning environment and facilitation of training sessions. Transformative learning theory operates on the importance of several experiences an individual encounters on the path to the development of a new transformative perspective of themselves and their roles based on past experiences (Mezirow, 1981). Mezirow (1981) asserts “transformation is the emancipatory process of becoming critically aware of how and why the structure
Turbo Equalization for Gray-Coded M-ary QAM with Bit-Level Soft Decisions

This paper investigates the soft-in soft-out (SISO) equalization of multilevel QAM symbols in coded inter-symbol interference (ISI) channels. Unlike the conventional approach of performing equalization at the symbol level, the proposed scheme targets the channel bits directly. This solution can be seen to belong to a family of SISO detection schemes which we call Bit-Level Equalization and Soft Detection (BLESD), stemming from the minimization of variational free energy given different postulates about the prior and posterior distributions of the channel bits. Simulation results demonstrate that the bit-level approach outperforms the symbol-level alternative in terms of error rate in the Porat-Friedlander channel.
Molecular Basis for Severe Epimerase Deficiency Galactosemia

Galactosemia is an inherited disorder characterized by an inability to metabolize galactose. Although classical galactosemia results from impairment of the second enzyme of the Leloir pathway, namely galactose-1-phosphate uridylyltransferase, alternate forms of the disorder can occur due to either galactokinase or UDP-galactose 4-epimerase deficiencies. One of the more severe cases of epimerase deficiency galactosemia arises from an amino acid substitution at position 94. It has been previously demonstrated that the V94M protein is impaired relative to the wild-type enzyme predominantly at the level of V max rather thanK m . To address the molecular consequences the mutation imparts on the three-dimensional architecture of the enzyme, we have solved the structures of the V94M-substituted human epimerase complexed with NADH and UDP-glucose, UDP-galactose, UDP-GlcNAc, or UDP-GalNAc. In the wild-type enzyme, the hydrophobic side chain of Val94 packs near the aromatic group of the catalytic Tyr157 and serves as a molecular “fence” to limit the rotation of the glycosyl portions of the UDP-sugar substrates within the active site. The net effect of the V94M substitution is an opening up of the Ala93 to Glu96 surface loop, which allows free rotation of the sugars into nonproductive binding modes.
Real-time communication network solution based on Zigbee and Ethernet for photovoltaic systems

The fast grow of photovoltaic (PV) systems is making more green energy but also creating challenges on how to communicate in a large system with a lot of distribution solar sources when they all connect to the national grid. The communication becomes the important part for data acquisition in order to control the whole system stable and efficiency. To deal with this challenge, this paper presents a solution based on Zigbee and Ethernet communication standard. Zigbee standard was created to be a specification of a high level wireless communication protocol which is not only secure, reliable, simple but also low cost and low power. Zigbee is especially suitable for a large network with thousands of devices. So with Zigbee, we can create a communication network for hundreds to thousands of mini solar sources in a large scale of photovoltaic system. Ethernet is a high speed wired communication technology that is used widely in industrial and automatic applications. Together Zigbee and Ethernet bring to us a real-time communication solution for the system. In the experiment prototype of this paper, we use the CC2530ZNP-Mini Kit to create a simple network includes one coordinate and one end device for the first step. The end device was configured to get current and voltage values from a 3-phase gird-connected solar inverter 800Wpk and then send the values to the coordinate. After the coordinate received data, it would send them to an Ethernet controller board. This board was controlled by the STM32F407 chip which is based on the high-performance ARM®Cortex™-M4 32-bit RISC core operating at a frequency of up to 168 MHz. To display the data through Ethernet, we embedded a web server on the chip. By this way, the data was easy to visualize and supervised by using any web browser.
A Defect Prediction Model for Open Source Software

Defect prediction models are significantly beneficial for software systems, where testing experts need to focus their attention and resources on problematic areas in the software under development. In this paper we find the relation between object oriented metrics and fault proneness using logistic regression method. The results are analyzed using open source software. The performance of the predicted models is evaluated using Receiver Operating Characteristic (ROC) analysis. The results show that Area under Curve (calculated by ROC analysis) of the predicted model is 0.829.
Understanding Parole Officers’ Responses to Sanctioning Reform

There are constant calls for reform in the criminal justice system, but observers have often reported that criminal justice reform is an exceptionally challenging task. As with any organizational change, resistance to new policies, procedures, and practices comes from a variety of sources. The relatively broad discretionary authority vested in line-level personnel often contributes to the difficulty associated with implementing change in criminal justice agencies. There is ample evidence that line staff resistance to organizational reform can undermine the implementation of organizational change. In this study, the authors examine the effects of the state of Ohio’s transition to graduated sanctioning guidelines on parole officers—in particular, how these reforms were perceived by the key actors in the sanctioning process: parole officers. Findings from a statewide survey revealed that officers were generally dissatisfied with the restrictions on their discretion resulting from the reform. Analyses revealed that organizational factors such as officers’ perceptions concerning how the sanctioning policy was implemented and its intended purposes were more influential than individual characteristics in shaping officers’ views concerning the efficacy of the reform.
Toward fine-grained online task characteristics estimation in scientific workflows

Task characteristics estimations such as runtime, disk space, and memory consumption, are commonly used by scheduling algorithms and resource provisioning techniques to provide successful and efficient workflow executions. These methods assume that accurate estimations are available, but in production systems it is hard to compute such estimates with good accuracy. In this work, we first profile three real scientific workflows collecting fine-grained information such as process I/O, runtime, memory usage, and CPU utilization. We then propose a method to automatically characterize workflow task needs based on these profiles. Our method estimates task runtime, disk space, and memory consumption based on the size of tasks input data. It looks for correlations between the parameters of a dataset, and if no correlation is found, the dataset is divided into smaller subsets by using a clustering technique. Task behavior estimates are done based on the ratio parameter/input data size if they are correlated, or based on the mean value. However, task dependencies in scientific workflows lead to a chain of estimation errors. To correct such errors, we propose an online estimation process based on the MAPE-K loop where task executions are constantly monitored and estimates are updated accordingly. Experiment results show that our online estimation process yields much more accurate predictions than an offline approach, where all task needs are estimated at once.
Asymptotics and 6 j-symbols

Recent interest in the Kashaev-Murakami-Murakami hyperbolic volume conjecture has made it seem important to be able to understand the asymptotic behaviour of certain special functions arising from representation theory — for example, of the quantum 6j -symbols for SU(2). In 1998 I worked out the asymptotic behaviour of the classical 6j -symbols, proving a formula involving the geometry of a Euclidean tetrahedron which was conjectured by Ponzano and Regge in 1968. In this note I will try to explain the methods and philosophy behind this calculation, and speculate on how similar techniques might be useful in studying the quantum case. AMS Classification 22E99; 81R05, 51M20
Linguistic Indicators for Quality Estimation of Machine Translations

This work presents a study of linguistically-informed features for the automatic quality estimation of machine translations. In particular, we address the problem of estimating quality when no reference translations are available, as this is the most common case in real world situations. Unlike previous attempts that make use of internal information from translation systems or rely on purely shallow aspects, our approach uses features derived from the source and target text as well as additional linguistic resources, such as parsers and monolingual corpora. We built several models using a supervised regression algorithm and different combinations of features, contrasting purely shallow, linguistic and hybrid sets. Evaluation of our linguistically-enriched models yields mixed results. On the one hand, all our hybrid sets beat a shallow baseline in terms of Mean Average Error but on the other hand, purely linguistic feature sets are unable to outperform shallow features. However, a detailed analysis of individual feature performance and optimal sets obtained from feature selection reveals that shallow and linguistic features are in fact complementary and must be carefully combined to achieve optimal results. In effect, we demonstrate that the best performing models are actually based on hybrid sets having a significant proportion of linguistic features. Furthermore, we show that linguistic information can produce consistently better quality estimates for specific score intervals. Finally, we analyse many factors that may have an impact on the performance of linguistic features and suggest new directions to mitigate them in the future.
Biochemical Pregnancy During Assisted Conception: A Little Bit Pregnant

Assisted reproductive technology (ART) has revolutionized the management of subfertility as many couples who previously had no hope of achieving a pregnancy are able to do so. Several factors contribute to the successful outcome of assisted conception. The period of waiting for the pregnancy test after assisted conception could be very crucial to the patient. One outcome of assisted conception could be a positive pregnancy test which could lead to a clinical pregnancy resulting in a live birth, clinical pregnancy resulting in a miscarriage or a biochemical pregnancy. A negative pregnancy test, failure to fertilise and failure to respond to stimulation usually lead to a big blow to the couple. As far as biochemical pregnancy is concerned, its exact aetiology remains unknown. There are no definite predictive factors for its occurrence that can be remedied in subsequent cycles. Several associated aetiologies have been suggested in the literature. This review aims at addressing the issue of biochemical pregnancy after assisted conception as a prelude to conducting further studies to assess if there are any predictive factors for its occurrence.