Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical star formation from the time—space distribution of star clusters in the Large Magellanic Cloud

ABSTRA C T The average age difference between pairs of star clusters in the Large Magellanic Cloud (LMC) increases with their separation as the ,0:35 power. This suggests that star formation is hierarchical in space and in time. Small regions form stars quickly and large regions, which often contain the small regions, form stars over a longer period. A similar result found previously for Cepheid variables is statistically less certain than the cluster result.
Fully digital multi‐frequency compact high‐frequency radar system for sea surface remote sensing

Compared with single-frequency high frequency surface wave radar (HFSWR), a multi-frequency (MF) system provides more feasibility in sea surface dynamic parameters measurement and target detection. In this study, a novel multi-frequency compact HFSWR based on a fully digital architecture is developed. This system employs a flexible signal processing procedure with low hardware complexity. Without changing the circuit, it can realise two typical multi-frequency schemes, including time-division MF (TDMF) and frequency-division MF (FDMF). Furthermore, a waveform selection criterion is proposed by analysing the difference between the TDMF and FDMF schemes in frequency-modulated interrupted continuous wave (FMICW). The system performance is preliminarily validated in two frequencies by both close-loop test and field experiment. It is shown that the range processing of two frequencies are coherent with an amplitude variation 0.93 and a root-mean-square error between 11.0 and 13.0 cm/s.
A Novel Technique to Create Energy-Efficient Contexts for Reconfigurable Logic

High power consumption is a constraining factor for the growth of programmable logic devices. We propose two techniques in order to reduce power consumption. The first is a technique for creating contexts. This technique uses data-dependent circuits and wire sharing between contexts. The second is a technique for switching the contexts. In this paper, we evaluate the capability of the two techniques to reduce power consumption using a multi-context logic device. As a result, as compared with the original circuit, our multi-context circuits can reduce the power consumption by 9.1% on an average and by a maximum of 19.0%. Furthermore, applying our resource sharing technique to these circuits, we achieved a reduction of 10.6% on an average and a maximum reduction of 18.8%.
Functional genomics identifies a Myb domain–containing protein family required for assembly of CENP-A chromatin

Nucleosomes containing the centromere-specific histone H3 variant centromere protein A (CENP-A) create the chromatin foundation for kinetochore assembly. To understand the mechanisms that selectively target CENP-A to centromeres, we took a functional genomics approach in the nematode Caenorhabditis elegans, in which failure to load CENP-A results in a signature kinetochore-null (KNL) phenotype. We identified a single protein, KNL-2, that is specifically required for CENP-A incorporation into chromatin. KNL-2 and CENP-A localize to centromeres throughout the cell cycle in an interdependent manner and coordinately direct chromosome condensation, kinetochore assembly, and chromosome segregation. The isolation of KNL-2–associated chromatin coenriched CENP-A, indicating their close proximity on DNA. KNL-2 defines a new conserved family of Myb DNA-binding domain–containing proteins. The human homologue of KNL-2 is also specifically required for CENP-A loading and kinetochore assembly but is only transiently present at centromeres after mitotic exit. These results implicate a new protein class in the assembly of centromeric chromatin and suggest that holocentric and monocentric chromosomes share a common mechanism for CENP-A loading.
Notice of RetractionReasons and Countermeasures for Job Burnout of Female Employees: An Explorative Case Study of Female Employees in Shanghai

With the development of the national economy and the society in China, job burnout has become an epidemic syndrome. As for female employees, they face greater job pressures and suffer form more serious job burnout than their male counterparts. The purpose of this paper is to probe what causes job burnout of female employees and how job burnout can be prevented and mitigated. Based on the study of female employees at Huangpu district of Shanghai through interviews and questionnaires, we conclude that job burnout of female employees is due to organizational, environmental, and personal factors. Finally, we propose some measures for preventing and mitigating job burnout of female employees.
Correlated flooding in low-duty-cycle wireless sensor networks

Flooding in low-duty-cycle wireless sensor networks is very costly due to asynchronous schedules of sensor nodes. To adapt existing flooding-tree-based designs for low-duty-cycle networks, we shall schedule nodes of common parents wake up simultaneously. Traditionally, energy optimality in a designated flooding-tree is achieved by selecting parents with the highest link quality. In this work, we demonstrate that surprisingly more energy can be saved by considering link correlation. Specifically, this work first experimentally verifies the existence of link correlation and mathematically proves that the energy consumption of broadcasting can be reduced by letting nodes with higher correlation receive packets simultaneously. A novel flooding scheme, named Correlated Flooding, is then designed so that nodes with high correlation are assigned to a common sender and their receptions of a broadcasting packet are only acknowledged by a single ACK. This unique feature effectively ameliorates the ACK implosion problem, saving energy on both data packets and ACKs. We evaluate Correlated Flooding with extensive simulations and a testbed implementation with 20 MICAz nodes. We show that Correlated Flooding saves more than 66% energy on ACKs and 15%–50% energy on data packets for most network settings, while having similar performance on flooding delay and reliability.
A pan‐Arctic synthesis of CH4 and CO2 production from anoxic soil incubations

Permafrost thaw can alter the soil environment through changes in soil moisture, frequently resulting in soil saturation, a shift to anaerobic decomposition, and changes in the plant community. These changes, along with thawing of previously frozen organic material, can alter the form and magnitude of greenhouse gas production from permafrost ecosystems. We synthesized existing methane (CH4) and carbon dioxide (CO2) production measurements from anaerobic incubations of boreal and tundra soils from the geographic permafrost region to evaluate large‐scale controls of anaerobic CO2 and CH4 production and compare the relative importance of landscape‐level factors (e.g., vegetation type and landscape position), soil properties (e.g., pH, depth, and soil type), and soil environmental conditions (e.g., temperature and relative water table position). We found fivefold higher maximum CH4 production per gram soil carbon from organic soils than mineral soils. Maximum CH4 production from soils in the active layer (ground that thaws and refreezes annually) was nearly four times that of permafrost per gram soil carbon, and CH4 production per gram soil carbon was two times greater from sites without permafrost than sites with permafrost. Maximum CH4 and median anaerobic CO2 production decreased with depth, while CO2:CH4 production increased with depth. Maximum CH4 production was highest in soils with herbaceous vegetation and soils that were either consistently or periodically inundated. This synthesis identifies the need to consider biome, landscape position, and vascular/moss vegetation types when modeling CH4 production in permafrost ecosystems and suggests the need for longer‐term anaerobic incubations to fully capture CH4 dynamics. Our results demonstrate that as climate warms in arctic and boreal regions, rates of anaerobic CO2 and CH4 production will increase, not only as a result of increased temperature, but also from shifts in vegetation and increased ground saturation that will accompany permafrost thaw.
Fetal Cyclophosphamide Exposure Induces Testicular Cancer and Reduced Spermatogenesis and Ovarian Follicle Numbers in Mice

Exposure to radiation during fetal development induces testicular germ cell tumors (TGCT) and reduces spermatogenesis in mice. However, whether DNA damaging chemotherapeutic agents elicit these effects in mice remains unclear. Among such agents, cyclophosphamide (CP) is currently used to treat breast cancer in pregnant women, and the effects of fetal exposure to this drug manifested in the offspring must be better understood to offer such patients suitable counseling. The present study was designed to determine whether fetal exposure to CP induces testicular cancer and/or gonadal toxicity in 129 and in 129.MOLF congenic (L1) mice. Exposure to CP on embryonic days 10.5 and 11.5 dramatically increased TGCT incidence to 28% in offspring of 129 mice (control value, 2%) and to 80% in the male offspring of L1 (control value 33%). These increases are similar to those observed in both lines of mice by radiation. In utero exposure to CP also significantly reduced testis weights at 4 weeks of age to ∼70% of control and induced atrophic seminiferous tubules in ∼30% of the testes. When the in utero CP-exposed 129 mice reached adulthood, there were significant reductions in testicular and epididymal sperm counts to 62% and 70%, respectively, of controls. In female offspring, CP caused the loss of 77% of primordial follicles and increased follicle growth activation. The results indicate that i) DNA damage is a common mechanism leading to induction of testicular cancer, ii) increased induction of testis cancer by external agents is proportional to the spontaneous incidence due to inherent genetic susceptibility, and iii) children exposed to radiation or DNA damaging chemotherapeutic agents in utero may have increased risks of developing testis cancer and having reduced spermatogenic potential or diminished reproductive lifespan.
Solving the Round Robin Problem Using Propositional Logic

In this paper we present a new and extremely competitive approach to solving a notoriously hard problem from the sports scheduling domain, the round robin problem. By combining local search satisfiability algorithms and an appropriate problem encoding based on classical propositional logic, we are able to find feasible schedules many times faster than using the best existing approaches to the round robin problem. Moreover, using this scheduling as satisfiability approach we are able to solve a previously unsolved instance, the round robin problem for 20 teams.
Teaching and Learning Computing

ion Level Low High P rogram m ing-nguage O rinted Thnking P rogram m ng O rinted Tinkin g P rogram -ree Thnking Programming Context Thinking Figure 3: Abstraction Levels of Thinking Types Relating to Programming Ahanori (2000) proposes developing students’ skills in posing ‘ abstraction barriers’ (refer to the Action-Process-Object model) as an effective way to develop their Program-Free Thinking abilities. He recommends that hiding data structure implementations from students so that they can experiment with the data structure operations (in a concrete manner) provides an abstraction barrier that allows students to form cognitive schema that can eventually facilitate the development of higher level abstraction. In a different study Hazzan (2003) presents a model of how students reduce the level of abstraction in Mathematics and Computer Science in order to cope with unfamiliarity. He defines levels of abstraction in three ways: “1. abstraction level as the quality of the relationships between the object of thought and the thinking person (Wilensky, 1991); 2. abstraction level as reflection of the process-object duality (Dubinsky, 1991; Sfard, 1991); 3. abstraction level as the degree of complexity of the concept of thought. ”
A Survey on Distribution Testing: Your Data is Big. But is it Blue?

The field of property testing originated in work on program checking, and has evolved into an established and very active research area. In this work, we survey the developments of one of its most recent and prolific offsprings, distribution testing. This subfield, at the junction of property testing and Statistics, is concerned with studying properties of probability distributions. We cover the current status of distribution testing in several settings, starting with the traditional sampling model where the algorithm obtains independent samples from the distribution. We then discuss different recent models, which either grant the testing algorithms more powerful types of queries, or evaluate their performance against that of an information-theoretically optimal “adversary” (for a given number of samples). In each setting, we describe the state of the art for a variety of testing problems. We hope this survey will serve as a self-contained introduction for those considering research in this field. ∗Research supported by NSF CCF-1115703 and NSF CCF-1319788. ACM Classification: G.3, F.2. 2 AMS Classification: 68Q32, 68W20, 68Q17, 68Q87
Exact solution of the Dirac equation for a Coulomb and scalar potential in the presence of an Aharonov-Bohm and a magnetic monopole fields

In the present paper the problem of a relativistic Dirac electron is analyzed in the presence of a combination of a Coulomb field, a 1/r scalar potential, as well as a Dirac magnetic monopole and an Aharonov–Bohm potential. Using the algebraic method of separation of variables, the Dirac equation expressed in the local rotating diagonal gauge is completely separated in spherical coordinates, and exact solutions are obtained. The energy spectrum is computed and its dependence on the intensity of the Aharonov–Bohm and the magnetic monopole strengths is analyzed.
Distributed Genetic Algorithm for Optimization of Wind Farm Annual Profits

In this paper, a distributed genetic algorithm is adopted to search the optimal number and locations of wind turbines in large wind farms. The objective of this optimal process is to find a solution that maximizes the annual profit obtained from a wind farm. It is well known that traditional genetic algorithms are time consuming and the quality of final solution is not very well. For improving the performance of finding the optimal solution in large search space, the distributed genetic algorithm provides a powerful strategy for searching the global optimal by dividing large population into multiple small subpopulations that occasionally exchange some individuals. Test results show that the distributed genetic algorithm well demonstrates its effectiveness on solution quality and execution time.
Regularization schemes involving self-similarity in imaging inverse problems

In this paper we introduce and analyze a set of regularization expressions based on self-similarity properties of images in order to address the classical inverse problem of image denoising and the ill-posed inverse problem of single-frame image zooming. The regularization expressions introduced are constructed using either the fractal image transform or the newly developed 'Nonlocal-means (NL-means) image denoising filter' of Buades et al. (2005). We exploit these regularization terms in a global MAP-based formulation and produce analytical and computational solutions. Analytical comparisions are made with results based on classical methods (e.g., fractal-based denoising and zooming, and NL-means image denoising).
Characterization of the human CD34+ hematopoietic progenitor cell compartment during the second trimester of pregnancy.

BACKGROUND AND OBJECTIVES Characterization of the different sites of fetal hematopoiesis during the second trimester of pregnancy can provide important information for the timing of in utero stem cell transplantation (SCT), as an experimental treatment for congenital hematologic disorders. DESIGN AND METHODS We analyzed the distribution of the different hematopoietic precursor cells in fetal blood, liver, bone marrow (BM), spleen and thymus from 66 fetuses between the ages of 13 to 23 weeks of gestation by flow cytometry and culture of hematopoietic progenitor cells (HPC) in semi-solid media. RESULTS During the second trimester the percentages of CD34+ cells did not change and were 4.0% (1.0-12.0%) (median [min.-max.]) in blood, 16.5% (3.0-32.0%) in BM, 6.0% (2.0-16.0%) in liver, 5.0% (2.0-14.0%) in spleen, and 1.1% (0.9-3.0%) in the thymus. Each tissue contained all subsets of CD34+ cells at various levels. Within the CD34+ population, in BM the main sub-population was CD34+CD19+ (38% (11-67%)), in thymus CD34+ CD7+ (83% [45-98%]), and in blood and liver CD34+ CD33+ (57% (30-80%) and 48% (20-82%), respectively). In all tissues approximately 1 % of nucleated cells were non-committed CD34+ CD38- cells. The frequencies of both committed CD34+ cells and non-committed CD34+ CD38- cells were constant from 13 to 23 weeks in fetal blood, BM, liver and spleen. The frequencies of cultured HPC were high in fetal liver, low in fetal BM, and increasing in fetal blood. INTERPRETATION AND CONCLUSIONS During the second trimester of gestation, all CD34+ subsets were present in each hematopoietic compartment at different levels. An exchange of stem cells between organs is likely, but no major shift of the hematopoietic stem cell compartment from the liver to other hematopoietic organs was found during the mid-trimester. No arguments for a specific time window for performing in utero SCT were found, but if engraftment of donor stem cells in the human fetus is influenced by competition of endogenous stem cells or fetal immune competence, in utero SCT should be performed as early as possible during fetal development.
Multiclass Object Recognition Inspired by the Ventral Visual Pathway

We describe a biologically-inspired system for classifying objects in still images. Our system learns to identify the class (car, person, etc.) of a previously-unseen instance of an object. As the primate visual system still outperforms computer vision systems on this task by a wide margin, we base our work on a model of the ventral visual pathway, thought to be primarily responsible for object recognition in cortex. Our model modifies that of Serre, Wolf, and Poggio, which hierarchically builds up feature selectivity and invariance to position and scale in a manner analogous to that of visual areas V1, V2, V4, and IT. As in that work, we first apply Gabor filters at all positions and scales; selectivity and invariance are then built up by alternating template matching and max pooling operations. We refine the approach in several biologically plausible ways, using simple versions of sparsification and lateral inhibition. We demonstrate the value of retaining some position and scale information above the intermediate feature level. Using feature selection we arrive at a model that performs better with fewer features. Our final model is tested on the Caltech 101 object categories and the UIUC car localization task, in both cases achieving state-of-the-art performance. The results strengthen the case for using this type of model in computer vision.
Layered resource allocation for video broadcasts over wireless networks

This paper aims to combine adaptive modulation and coding with layered video coding to improve the quality of video services to users experiencing differing radio conditions, in the context of broadcast and multicast standards such as MBMS and BCMCS. We propose an optimal radio resource allocation algorithm which maximizes a general performance metric for a video session in polynomial time. We show that system-wide optimal resource allocation can be obtained by combining our algorithm with a simple two-step decomposition of the system. In some configurations frequent re-allocations of resource are required, so we also present a sub-optimal allocation algorithm which runs in near linear time. Simulation results show better video quality than existing resource allocation schemes over a range of conditions, and also suggest that the difference between the performance of optimal and suboptimal solutions is less than 3%.
Replay attack: Its effect on GMM-UBM based text-independent speaker verification system

Spoofing is a technique to bias the system decisions towards target speakers without the physical presence of genuines. The focus of spoofing is on target speakers, resulting a sharp increase in false acceptance. The availability of high quality recording and playback devices (i.e. smart phones), have made spoof attacks by replay data a most common and easy approach, even without much knowledge about speech processing. In this work we analyze and demonstrate the seriousness of replay attacks, and then examine the vulnerability of classic GMMUBM based speaker verification (SV) system to replay data by experimental studies. Since no standard database is available, we develop a replay dataset of 34 speakers from Indian Institute of Technology Guwahati - Multi-Variability (IITG-MV) speech database, that covers all kind of variabilities. To avoid any gender biasing, we made our studies for male and female speakers independently and finally in together. Under replay attacks, for genuine 459 male and 220 female trials, the equal error rate (EER) increases from 2.61% to 15.03% and 1.82% to 34.09%, respectively. In total, the EER increases from 2.50% to 20.76%. As obvious, the degradation in EER is mainly due to increase in false acceptance ratio (FAR). The case is worsen for female speakers. It may be due to the fine spectral structures of female speakers. These observations reveal that GMM-UBM based SV system is highly vulnerable to replay attacks and needs wider attentions.
Data validation for business continuity planning

In this paper we present a system and case study for business data validation in large organizations. The validated and consistent data provides the capability to handle outages and incidents in a more principled fashion and helps in business continuity. Typically, different business units employ separate systems to produce and store their data. The data owners choose their own technology for data base storage. It is a non-trivial task to keep the data consistent across business units in the organization. This non-availability of consistent data can lead to sub optimal planning during outages and organizations can incur huge financial costs. Traditional custom data validation system fetches the data from various data sources and flow it through the central validation system resulting in huge data transfer cost. Moreover, accommodating change in business rules is laborious process. Accommodating such changes in the system can lead to re-design and re-development of the system. This is a very costly and time consuming activity. In this paper, we employ a Metadata driven rule-based data validation system, which is domain independent, distributed, scalable and can easily accommodate changes in business requirements. We have deployed our system in real life settings. We present some of the results in this paper.
An object-oriented approach for PC clusters

This paper addresses a methodology for designing PC clusters using object-oriented technology. The proposed methodology simplifies the design process and manages specification differences in both the academic and the industrial environments. This is to respond to the need to implement an existing CFD code on PC clusters for research purposes and future industrial usage. The objectoriented technology is well suited to solve this kind of design problems.