Miracle-dz/UniFAR-FTUs huggingface dataset:
POSET CONVEX-EAR DECOMPOSITIONS AND APPLICATIONS TO THE FLAG H-VECTOR

Possibly the most fundamental combinatorial invariant associated to a finite simplicial complex is its f-vector, the integral sequence expressing the number of faces of the complex in each dimension. The h-vector of a complex is obtained by applying a simple invertible transformation to its f-vector, and thus the two contain the same information. Because some properties of the f-vector are easier expressed after applying this transformation , the h-vector has been the subject of much study in geometric and algebraic combinatorics. A convex-ear decomposition, first introduced by Chari in [7], is a way of writing a simplicial complex as a union of subcomplexes of simplicial polytope boundaries. When a (d − 1)-dimensional complex admits such a decomposition, its h-vector satisfies, for i < d/2, h i ≤ h i+1 and h i ≤ h d−i. Furthermore, its g-vector is an M-vector. We give convex-ear decompositions for the order complexes of rank-selected sub-posets of supersolvable lattices with nowhere-zero Möbius functions, rank-selected sub-posets of geometric lattices, and rank-selected face posets of shellable complexes (when the rank-selection does not include the maximal rank). Using these decompositions, we are able to show inequalities for the flag h-vectors of supersolvable lattices and face posets of Cohen-Macaulay complexes. Finally, we turn our attention to the h-vectors of lattice path matroids. A lattice path matroid is a certain type of transversal matroid whose bases correspond to planar lattice paths. We verify a conjecture of Stanley in the special case of lattice path matroids and, in doing so, introduce an interesting new class of monomial order ideals. relocation, he and his family finally settled in the Washington, D.C. suburb of Hern-don, Virginia. Jay attended Oakton High School, and later enrolled in nearby George Mason University as a philosophy major. Two years and many Aristotle treatises later, Jay switched to a mathematics concentration. After obtaining a bachelor's degree, Jay worked several odd jobs in the Northern Virginia area. He eventually entered the mathematics Ph.D. program at Cornell University in Ithaca, New York, initially as a topologist. Six short years later, his advisor suggested that he graduate. After graduation, Jay will be a Robert D. Adams visiting assistant professor at the University of Kansas.
Maximum Mutual Information and Word Classes

Herein, I present some notes concerning implementation of now classical method of data clustering, called Maximum Mutual Information Clustering. It was introduced in [Mercer et al., 1992] in context of language modeling. The original article contained some cues concerning its implementation. These are carried out in detail here, together with some new tricks. Results of the test run on 110M words long Czech National Corpus are briefly described then. Also, some problems of the original approach are identified and their possible cause is suggested.
Teacher Leadership as Distributed Leadership: Heresy, fantasy or possibility?

This article focuses on the issue of teacher leadership and explores various interpretations and definitions within the literature. It examines the relationship between teacher leadership and distributed leadership, focusing particularly upon the idea of activity theory. The article suggests that there are some important connections and overlaps between distributed leadership and teacher leadership. The article also discusses the possible sources of resistance to the idea of teachers as leaders in schools and explores how distributing leadership to teachers may contribute to building professional learning communities within and between schools.
Ten Misconceptions Concerning Neurobiology and Politics

Political science is far behind the other social science disciplines in incorporating neurobiological concepts, techniques, and theory. In recent years progress has been made in closing this gap but many in the political science mainstream view the movement with concern or even horror. Though a healthy dose of skepticism is appropriate and beneficial to the scientific endeavor, negative reactions to viewing politics through a neurobiological lens are often based on fundamental misconceptions regarding both neurobiology and politics. In this Reflections essay, I address ten of these misconceptions, including the beliefs that biology is deterministic, reductionist, unnecessary, irrelevant, normatively dangerous, and ideologically biased. The goal is to encourage a constructive dialogue on the relevance of neurobiology to political life—a dialogue that would in turn improve research in the fledgling subfield and lead to innovations in political science by encouraging new ways of conceptualizing and analyzing the variables at the discipline's core.
Detecting Exercise Induced Stress using the Photoplethysmogram

The effect of exercise on the cardiovascular system has been studied extensively using a wide range of physiological sensors. Athletes now commonly use EKG-based monitors to ascertain heart rate, but these devices cannot directly monitor the level of physical stress. We hypothesize that the low frequency spindle waves seen in the photoplethysmographs (PPG) of exercising individuals may be useful for noninvasively detecting hemodynamic stressors to the human vascular system. In a clinical trial with nine healthy subjects performing the Bruce Protocol treadmill test these low frequency spindle waves were observed in the forehead and ear PPG in all subjects before the onset of volitional fatigue. As volitional fatigue approached, the spindle waves become more pronounced, decreased in period and then within several seconds of the cessation of the protocol they disappeared. Using a software-based detector, these distinct spindle waves can be reliably detected. This technique holds promise for the automatic detection and characterization of exercise induced physical stress
Altered Clock Gene Expression in Obese Visceral Adipose Tissue Is Associated with Metabolic Syndrome

Clock gene expression was associated with different components of metabolic syndrome (MS) in human adipose tissue. However, no study has been done to compare the expression of clock genes in visceral adipose tissue (VAT) from lean and obese subjects and its clinical implications. Therefore, we studied in lean and obese women the endogenous 24 h expression of clock genes in isolated adipocytes and its association with MS components. VAT was obtained from lean (BMI 21–25 kg/m2; n = 21) and morbidly obese women (BMI >40 kg/m2; n = 28). The 24 h pattern of clock genes was analyzed every 6 hours using RT-PCR. Correlation of clinical data was studied by Spearman analysis. The 24 h pattern of clock genes showed that obesity alters the expression of CLOCK, BMAL1, PER1, CRY2 and REV-ERB ALPHA in adipocytes with changes found in CRY2 and REV-ERB ALPHA throughout the 24 h period. The same results were confirmed in VAT and stromal cells (SC) showing an upregulation of CRY2 and REV-ERB ALPHA from obese women. A positive correlation was observed for REV-ERB ALPHA gene expression with BMI and waist circumference in the obese population. Expression of ROR ALPHA was correlated with HDL levels and CLOCK with LDL. Obese subjects with MS exhibited positive correlation in the PER2 gene with LDL cholesterol, whereas REV-ERB ALPHA was correlated with waist circumference. We identified CRY2 and REV-ERB ALPHA as the clock genes upregulated in obesity during the 24 h period and that REV-ERB ALPHA is an important gene associated with MS.
Building a synchronous corpus of acoustic and 3D facial marker data for adaptive audio-visual speech synthesis

We have created a synchronous corpus of acoustic and 3D facial marker data from multiple speakers for adaptive audio-visual text-to-speech synthesis. The corpus contains data from one female and two male speakers and amounts to 223 Austrian German sentences each. In this paper, we first describe the recording process, using professional audio equipment and a marker-based 3D facial motion capturing system for the audio-visual recordings. We then turn to post-processing, which incorporates forced alignment, principal component analysis (PCA) on the visual data, and some manual checking and corrections. Finally, we describe the resulting corpus, which will be released under a research license at the end of our project. We show that the standard PCA based feature extraction approach also works on a multi-speaker database in the adaptation scenario, where there is no data from the target speaker available in the PCA step.
Metric-based simulation training to proficiency in medical education:- What it is and how to do it

High profile error cases and reduced work hours have forced medicine to consider new approaches to training. Simulation-based learning for the acquisition and maintenance of skills has a growing role to play. Considerable advances have been made during the last 20 years on how simulation should be used optimally. Simulation is also more than a technology learning experience for supplanting the traditional approach of repeated practice. Research has shown that simulation works best when it is integrated into a curriculum. Learning is optimal when trainees receive metric-based feedback on their performance. Metrics should unambiguously characterize important aspects of procedure or skill performance. They are developed from a task analysis of the procedure or skills to be learned. The outcome of the task analysis should also shape how the simulation looks and behaves. Metric-based performance characterization can be used to establish a benchmark (i.e., a level of proficiency) which trainees must demonstrate before training progression. This approach ensures a more homogeneous skill-set in graduating trainees and can be applied to any level of training. Prospective, randomized and blinded clinical studies have shown that trainees who acquired their skills to a level of proficiency on a simulator in the skills laboratory perform significantly better in vivo in comparison to their traditionally trained colleagues. The Food and Drug Administration in the USA and the Department of Health in the UK have candidly indicated that they see an emergent and fundamental role for simulation-based training. Although a simulation-based approach to medical education and training may be conceptually and intellectually appealing it represents a paradigm shift in how doctors are educated and trained.
Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos

In this work, we propose an approach to the spatiotemporal localisation (detection) and classification of multiple concurrent actions within temporally untrimmed videos. Our framework is composed of three stages. In stage 1, appearance and motion detection networks are employed to localise and score actions from colour images and optical flow. In stage 2, the appearance network detections are boosted by combining them with the motion detection scores, in proportion to their respective spatial overlap. In stage 3, sequences of detection boxes most likely to be associated with a single action instance, called action tubes, are constructed by solving two energy maximisation problems via dynamic programming. While in the first pass, action paths spanning the whole video are built by linking detection boxes over time using their class-specific scores and their spatial overlap, in the second pass, temporal trimming is performed by ensuring label consistency for all constituting detection boxes. We demonstrate the performance of our algorithm on the challenging UCF101, J-HMDB-21 and LIRIS-HARL datasets, achieving new state-of-the-art results across the board and significantly increasing detection speed at test time. We achieve a huge leap forward in action detection performance and report a 20% and 11% gain in mAP (mean average precision) on UCF-101 and J-HMDB-21 datasets respectively when compared to the state-of-the-art.
Heat Affected Zone in the MEMS Wire Bonding

In the wire bonding process of MEMS packaging, Heat Affect Zone (HAZ) is the important factor governing the loop profile of bonding. The height of loop is affected by the length of the HAZ. Factors governing the HAZ are studied. To investigate this relationship, the experiments were done for the various sizes of wire diameter and Free Air Ball (FAB). Electric Flame-Off (EFO) current, EFO time, EFO gap and the recrystallization were also studied. The results showed that as the size of FAB became larger, the length of HAZ increased. With the increase of EFO current and time, the length of HAZ became longer. When FAB was formed at the same parameter, the length of HAZ became shorter with the high temperature of recrystallization.
Achieving Competitive Advantage in Insurance Industry : The Impact of Marketing Innovation and Creativity

In order to achieve new gains for its stakeholders and fulfill their needs and requirements, organisations must continuously search for the development of its product and services through marketing innovation and creativity. This will play a very important role in achieving competitive advantage especially in the insurance industry where competition is much stiffed, through the forces of change brought into the industry by recapitalization and consolidation. The study was carried out to find out whether marketing innovation and creativity has an impact on achieving competitive advantage in the insurance industry. The study shows that marketing innovation and creativity are crucial in organisational success. It also concluded that through marketing innovation and creativity, the insurance industry can improve their businesses and achieve a competitive advantage. __________________________________________________________________________________________
Application of probability density estimation criteria in speaker recognition

With the rapid development of computer technology, speaker recognition has been widely used and researched. In this paper, a traditional code book based on VQ algorithm was improved by applying in probability density estimation criteria method. Through the method, the problem of easily falling into local optimum existing in traditional LBG codebook can be well solved, and controlling operation can be easily achieved. Experimental results show that improved codebook algorithm has less distortion than traditional LBG algorithm.
A feature level fusion fingerprint indexing approach based on MV and MCC using SVM classifier

Now a day, the biometric traits are widely used due to the growing demand for secure and reliable identification of an individual. Fingerprint is used by many fields like military for border control and government applications in India as the Aadhaar project, in Europe as the Visa Information System (VIS), in USA as the US-VISIT / IDENT which generally contain billions of samples of fingerprints. In this paper, we propose a fingerprint indexing scheme at feature level fusion based on Minutiae Vicinity and Minutiae Cylindrical Code and a support-vector-machine-based learning algorithm is used to train the system using the feature extracted which will improve the efficiency in seeking a candidate reference list from large scale biometric data databases, where the personality related with the input data is dictated by contrasting it with each and every entry in the database. This coordinating procedure is tedious and conceivably increments, the rate of wrong identification, hence we propose a new fingerprint indexing approach which would improve the performance of the system.
An Approach for Text Steganography Based on Markov Chains

A text steganography method based on Markov chains is in- troduced, together with a reference implementation. This method allows for information hiding in texts that are automatically generated following a given Markov model. Other Markov - based systems of this kind rely on big simplications of the language model to work, which produces less natural looking and more easily detectable texts. The method described here is designed to generate texts within a good approximation of the original language model provided.
The multicoupled magnetoelectric effect in three-phase Tb1−xDyxFe2/ Pb(Zr1−xTix)O3/NdFeB bimorph laminates

Multicoupled magnetoelectric (ME) effect originated from the interaction of magnetostriction, magnetic-torque and piezoelectricity was proposed. A three-phase Tb1-xDyxFe2/Pb(Zr1-xTix)O3/NdFeB bimorph laminates with this mechanism was designed and investigated. We found that the magnetic DC bias could tune the multicoupling and lead to an enhancement or attenuation in ME effect. The ME voltage coefficient could be enhanced by a factor of 2.6 times (or 2.2 times for practical device construction) that of a conventional bimorph ME device. A simple and effective mode analysis method was introduced for the multicoupled device design. This research has provided a sight of designing better ME devices with the multicoupling consideration.
Dealing with uncertain models in wireless communications

We advocate the use of interval-type bounds on cumulative distribution functions, called probability boxes, to handle several problems arising when a wireless communication system performance must be assessed in the presence of model uncertainties, poorly known or unknown dependencies of random variables, or imprecisely specified probability distributions. The amount of uncertainty is evaluated quantitatively by using sharp bounds on performance parameters.
Full Body: The Importance of the Phenotype in Evolution

This is a position paper on phenotype-based evolution modeling. It argues that evolutionary complexity is essentially a functional kind of complexity, and for it to evolve, a full body, or, in other words, a dynamically defined, deeply structured, and plasticity-bound phenotype is required. In approaching this subject, we ask and answer some key questions, which we think are interrelated. The questions we discuss and the answers we propose are: (a) How should complexity growth be measured or operationalized in natural and artificial systems? Evolutionary complexity is akin to that of machines, and to operationalize it, we need to study how machinelike organismic functions work and develop. Inspired by studies on causality, we propose the notion of mechanism. A mechanism is a simplified causal system that carries out a function. A growth of functional complexity involves interconversions between a deep (or unused) process and that of a mechanism. (b) Are the principles of natural selection, as they are currently understood, sufficient to explain the evolution of complexity? Our answer is strongly negative. Natural selection helps adapting mechanisms to carry out a given task, but will not generate a task. Hence there is a tradeoff between available tasks and mechanisms fulfilling them. To escape, we argue that competition avoidance is required for new complexity to emerge. (c) What are the environmental constraints on complexity growth in living systems? We think these constraints arise from the structure of the coevolving ecological system, and the basic frames are given by the niche structure. We consider the recently popular idea of niche construction and relate it to the plasticity of the phenotype. We derive a form of phenotype plasticity from the hidden (unused) and explicit (functional) factors discussed in the causality part. (d) What are the main hypotheses about complexity growth that can actually be tested? We hypothesize that a rich natural phenotype that supports causality-function conversions is a necessary ingredient of complexity growth. We review our work on the FATINT system, which incorporates similar ideas in a computer simulation, and shows that full-body phenotypes are sufficient for achieving functional evolution. (e) What language is most appropriate for speaking about the evolution of complexity in living systems? FATINT is developed using advanced agent-based modeling techniques, and we discuss the general relevance of this methodology for understanding and simulating the phenomena discussed.
mapping Multiplexed shotgun genotyping for rapid and efficient genetic Material

object identifier (DOIs) and date of initial publication. by PubMed from initial publication. Citations to Advance online articles must include the digital publication). Advance online articles are citable and establish publication priority; they are indexed appeared in the paper journal (edited, typeset versions may be posted when available prior to final Advance online articles have been peer reviewed and accepted for publication but have not yet
Modulation of the N170 with Classical Conditioning: The Use of Emotional Imagery and Acoustic Startle in Healthy and Depressed Participants

Recent studies have suggested that classical conditioning may be capable of modulating early sensory processing in the human brain, and that there may be differences in the magnitude of the conditioned changes for individuals with major depressive disorder. The effect of conditioning on the N170 event-related potential was investigated using neutral faces as conditioned stimuli (CS+) and emotional imagery and acoustic startle as unconditioned stimuli (UCS). In the first experiment, electroencephalogram was recorded from 24 undergraduate students (M = 21.07 years, SD = 3.38 years) under the following conditions: (i) CS+/aversive imagery, (ii) CS+/aversive imagery and acoustic startle, (iii) CS+/acoustic startle, and (iv) CS+/pleasant imagery. The amplitude of the N170 was enhanced following conditioning with aversive imagery as well as acoustic startle. In the second experiment, 26 healthy control participants were tested (17 females and 9 males, age M = 25.97 years, SD = 9.42) together with 18 depressed participants (13 females and 5 males, age M = 23.26 years, SD = 4.01) and three conditions were used: CS+/aversive imagery, CS+/pleasant imagery, and CS-. N170 amplitude at P7 was increased for the CS+/aversive condition in comparison to CS- in the conditioning blocks versus baseline. No differences between depressed and healthy participants were found. Across both experiments, evaluative conditioning was absent. It was concluded that aversive UCS are capable of modulating early sensory processing of faces, although further research is also warranted in regards to positive UCS.
Family History of Colorectal Cancer: Clinicians' Preventive Recommendations and Patient Behavior

Few population-based studies have addressed the role that family history of colorectal cancer (CRC) plays in clinician decision making or patient health choices. The objective of this study was to evaluate the effect of family history of CRC on clinician practice, patient CRC screening, and patient preventive behavior. We analyzed 2008 Oregon Behavioral Risk Factor Surveillance System data to examine associations between family history of CRC and 1) patient-reported clinician recommendations, 2) perceived risk of developing CRC, 3) adoption of preventive and screening behaviors, and 4) CRC risk factors among 1,795 respondents without CRC. A family history of CRC was positively associated with a higher likelihood of respondents reporting that their clinicians discussed colorectal cancer screening (OR, 4.2; 95% CI, 2.4-7.4) and of respondents having colorectal screening within the recommended time period (OR, 2.2; 95% CI, 1.3-3.9). A family history of CRC was also associated with respondents reporting lifestyle changes to prevent CRC (OR, 2.6; 95% CI, 1.7-4.0). A family history of CRC may prompt clinicians to recommend screening and preventive behavior changes and motivate patients to adopt such strategies.