Miracle-dz/UniFAR-FTUs huggingface dataset:
A compact second-order LTCC bandpass filter with two finite transmission zeros

A novel implementation and associated design formula for a compact low-temperature cofired ceramics (LTCC) lumped-element second-order bandpass filter are proposed in this paper. The filter schematic that provides two finite transmission zeros is well known. It is shown in the paper that the filter schematic is built on a pair of conventional inductive coupled resonator tanks with a feedback capacitor between input and output. While revealing its working mechanism both graphically and mathematically, a simple design procedure for such a compact filter is also given. The proposed filter has been implemented in a six-layer ceramic substrate using LTCC technology, showing promising application potentials in miniaturized mobile terminals and Bluetooth RF front-ends. The measured results agree very well with the full-wave electromagnetic designed responses.
Tornado: A System For Real-Time Iterative Analysis Over Evolving Data

There is an increasing demand for real-time iterative analysis over evolving data. In this paper, we propose a novel execution model to obtain timely results at given instants. We notice that a loop starting from a good initial guess usually converges fast. Hence we organize the execution of iterative methods over evolving data into a main loop and several branch loops. The main loop is responsible for the gathering of inputs and maintains the approximation to the timely results. When the results are requested by a user, a branch loop is forked from the main loop and iterates until convergence to produce the results. Using the approximation of the main loop, the branch loops can start from a place near the fixed-point and converge quickly. Since the inputs not reflected in the approximation is concerned with the approximation error, we develop a novel bounded asynchronous iteration model to enhance the timeliness. The bounded asynchronous iteration model can achieve fine-grained updates while ensuring correctness for general iterative methods. Based on the proposed execution model, we design and implement a prototype system named Tornado on top of Storm. Tornado provides a graph-parallel programming model which eases the programming of most real-time iterative analysis tasks. The reliability is also enhanced by provisioning efficient fault tolerance mechanisms. Empirical evaluation conducted on Tornado validates that various real-time iterative analysis tasks can improve their performance and efficiently tolerate failures with our execution model.
Concentric Anchor-Beacons (CAB) Localization for Wireless Sensor Networks

Many applications in wireless sensor networks require sensor nodes to obtain their absolute or relative geographical positions. Although various localization algorithms have been proposed recently, most of them require nodes be equipped with range-determining hardware to obtain distance information. In this paper, we propose a concentric anchor-beacons (CAB) localization algorithm for wireless sensor networks. CAB is a range-free approach and uses a small number of anchor nodes. Each anchor emits beacons at different power levels. From the information received by each beacon heard, nodes determine which annular ring they are located within each anchor. Each node uses the approximated center of intersection of the rings as its position estimate. Simulation results show that the estimation error reduces by half when anchors transmit beacons at two different power levels instead of at a single level. CAB also gives a lower estimation error than other range-free localization schemes (e.g., Centroid, APIT) when the anchor-to-node range ratio is less than four.
Embryonic fibroblast motility and orientation can be influenced by physiological electric fields

Epithelial layers in developing embryos are known to drive ion currents through themselves that will, in turn, generate small electric fields within the embryo. We hypothesized that the movement of migratory embryonic cells might be guided by such fields, and report here that embryonic quail somite fibroblast motility can be strongly influenced by small DC electric fields. These cells responded to such fields in three ways: (a) The cells migrated towards the cathodal end of the field by extending lamellipodia in that direction. The threshold field strength for this galvanotaxis was between 1 and 10 mV/mm when the cells were cultured in plasma. (b) The cells oriented their long axes perpendicular to the field lines. The threshold field strength for this response for a 90-min interval in the field was 150 mV/mm in F12 medium and between 50 and 100 mV/mm in plasma. (c) The cells elongated under the influence of field strengths of 400 mV/mm and greater. These fibroblasts were therefore able to detect a voltage gradient at least as low as 0.2 mV across their width. Electric fields of at least 10- fold larger in magnitude than this threshold field have been detected in vivo in at least one vertebrate thus far, so we believe that these field effects encompass a physiological range.
Outlier Detection in Stream Data by Clustering Method

The fundamental and active research problem in a lot of fields is outlier detection. It is involved many applications. A lot of these methods based on distance measure. But for stream data these methods are not efficient. Most of the previous work on outlier detection declares online outlier and these have less accuracy and it may be lead to a wrong decision. moreover the exiting work on outlier detection in data stream declare a point as an outlier/inlier as soon as it arrive due to limited memory resources as compared to the huge data stream, to declare an outlier as it arrive often can lead us to a wrong decision, because of dynamic nature of the incoming data. The aim of this study is to present an algorithm to detect outlier in stream data by clustering method that concentrate to find real outlier in period of time. It is considered some outlier that has received in previous time and find out real outlier in stream data. The accuracy of this method is more than other methods.
Galaxies as a cosmological test

The relativistic LambdaCDM cosmological model has passed a demanding network of tests that convincingly demonstrate it is a useful approximation to what happened back to high redshift. But there are anomalies in its application to structure formation on the scales of galaxies that show we have much to learn about what this theory actually predicts and possibly something also of value to learn about the fundamental theoretical basis for observational cosmology. This is slightly revised and enlarged from a contribution to A Century of Cosmology, Venice, August 2007.
Cogging torque fast computation method for Surface Permanent Magnet machines based on winding function theory

Various analytical techniques have been proposed in the literature for cogging torque computation in Surface Permanent Magnet (SPM) machines. Among the various available methods, the ones found to be satisfactorily accurate are based on the Maxwell's stress tensor, which involves both normal and tangential air-gap field and lead to quite involved calculation formulas. In this paper, a relatively simple alternative is proposed where permanent magnets are modeled as equivalent field circuits to which a well defined winding function can be associated. The approach leads to a plain cogging torque formulation where only the normal no-load air-gap flux density appears. The accuracy of the method is assessed by Finite Element (FE) analysis on some sample SPM machine geometries. The results are shown to match FE simulations with a satisfactory accuracy compared to Maxwell-stress-tensor-based analytical techniques available from the literature.
Reachable subwebs for traversal-based query execution

Traversal-based approaches to execute queries over data on the Web have recently been studied. These approaches make use of up-to-date data from initially unknown data sources and, thus, enable applications to tap the full potential of the Web. While existing work focuses primarily on implementation techniques, a principled analysis of subwebs that are reachable by such approaches is missing. Such an analysis may help to gain new insight into the problem of optimizing the response time of traversal-based query engines. Furthermore, a better understanding of characteristics of such subwebs may also inform approaches to benchmark these engines. This paper provides such an analysis. In particular, we identify typical graph-based properties of query-specific reachable subwebs and quantify their diversity. Furthermore, we investigate whether vertex scoring methods (e.g., PageRank) are able to predict query-relevance of data sources when applied to such subwebs.
Working Memory-Related Functional Brain Patterns in Never Medicated Children with ADHD

Attention Deficit/Hyperactivity Disorder (ADHD) is a pervasive neurodevelopmental disorder characterized by 3 clusters of age-inappropriate cardinal symptoms: inattention, hyperactivity and impulsivity. These clinical/behavioural symptoms are assumed to result from disturbances within brain systems supporting executive functions including working memory (WM), which refers to the ability to transiently store and flexibly manipulate task-relevant information. Ongoing or past medications, co-morbidity and differences in task performance are potential, independent confounds in assessing the integrity of cerebral patterns in ADHD. In the present study, we recorded WM-related cerebral activity during a memory updating N-back task using functional Magnetic Resonance Imaging (fMRI) in control children and never medicated, prepubescent children with ADHD but without comorbid symptoms. Despite similar updating performance than controls, children with ADHD exhibited decreased, below baseline WM-related activation levels in a widespread cortico-subcortical network encompassing bilateral occipital and inferior parietal areas, caudate nucleus, cerebellum and functionally connected brainstem nuclei. Distinctive functional connectivity patterns were also found in the ADHD in these regions, with a tighter coupling in the updating than in the control condition with a distributed WM-related cerebral network. Especially, cerebellum showed tighter coupling with activity in an area compatible with the brainstem red nucleus. These results in children with clinical core symptoms of ADHD but without comorbid affections and never treated with medication yield evidence for a core functional neuroanatomical network subtending WM-related processes in ADHD, which may participate to the pathophysiology and expression of clinical symptoms.
Doppler mapping of postoperative left atrioventricular valve regurgitation.

Left atrioventricular valve regurgitation often occurs as a postoperative hemodynamic complication from repair of an atrioventricular septal defect. In this study, cross-sectional two-dimensional Doppler flow mapping of the left atrium was used to quantify postoperative regurgitant flow in 29 patients. Its severity and location was related to the shape of the three leaflets of the left component of the atrioventricular valve, especially to the size of the mural leaflet. To identify which leaflet configuration was likely to cause regurgitation, the position of the leaflets was obtained from the parasternal short-axis view and the angular size of the mural leaflet expressed in degrees of an arc. Doppler mapping was performed in the apical four-chamber and the parasternal long-axis views, dividing the left atrium in nine squares in each. Regurgitation was defined as a jetlike systolic downstroke of the Doppler frequency shift in early systole. The angular size of the mural leaflet varied from 38 to 144 degrees (mean 86 +/- 36 SD). Massive regurgitation (six to nine sites) was encountered in seven patients, five with a mural leaflet size of over 110 degrees, one with mural leaflet size between 70 and 110 degrees, and one with a mural leaflet size of under 70 degrees. No or minimal regurgitation was encountered in 10 patients, three having a mural leaflet size of 70 to 110 degrees and seven with a mural leaflet size of less than 70 degrees. These data suggest that massive regurgitation is encountered in patients with large mural leaflets, whereas patients with smaller mural leaflets tend to have no or mild regurgitation. (ABSTRACT TRUNCATED AT 250 WORDS)
Selection from parasites favours immunogenetic diversity but not divergence among locally adapted host populations

The unprecedented polymorphism in the major histocompatibility complex (MHC) genes is thought to be maintained by balancing selection from parasites. However, do parasites also drive divergence at MHC loci between host populations, or do the effects of balancing selection maintain similarities among populations? We examined MHC variation in populations of the livebearing fish Poecilia mexicana and characterized their parasite communities. Poecilia mexicana populations in the Cueva del Azufre system are locally adapted to darkness and the presence of toxic hydrogen sulphide, representing highly divergent ecotypes or incipient species. Parasite communities differed significantly across populations, and populations with higher parasite loads had higher levels of diversity at class II MHC genes. However, despite different parasite communities, marked divergence in adaptive traits and in neutral genetic markers, we found MHC alleles to be remarkably similar among host populations. Our findings indicate that balancing selection from parasites maintains immunogenetic diversity of hosts, but this process does not promote MHC divergence in this system. On the contrary, we suggest that balancing selection on immunogenetic loci may outweigh divergent selection causing divergence, thereby hindering host divergence and speciation. Our findings support the hypothesis that balancing selection maintains MHC similarities among lineages during and after speciation (trans‐species evolution).
Graveoline Analogs Exhibiting Selective Acetylcholinesterase Inhibitory Activity as Potential Lead Compounds for the Treatment of Alzheimer’s Disease

This study designed and synthesized a series of new graveoline analogs on the basis of the structural characteristics of acetylcholinesterase (AChE) dual-site inhibitors. The activity of these analogs was also evaluated. Results showed that the synthesized graveoline analogs displayed stronger inhibitory activity against AChE and higher selectivity than butyrylcholine esterase (BuChE) (Selectivity Index from 45 to 486). When the two sites in the graveoline parent ring substituting phenyl and amino terminal had six chemical bonds (n = 3) and the terminal amino was piperidine, compound 5c showed the best activity. Furthermore, the mechanism of action and binding mode were explored by enzyme kinetic simulation, molecular docking, and thioflavin T-based fluorometric assay. Cytotoxicity assay showed that the low concentration of the analogs did not affect the viability of the neurocyte SH-SY5Y.
Potential of Fermented Sausage-Associated Lactic Acid Bacteria to Degrade Biogenic Amines During Storage

© 2013 Kongkiattikajorn, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Potential of Fermented Sausage-Associated Lactic Acid Bacteria to Degrade Biogenic Amines During Storage
Estimating the Two-Dimensional Coherence Function

In this paper, we extend the one-dimensional Capon-based magnitude square coherence (MSC) spectral estimator, to form two-dimensional Capon- and APES-based MSC spectral estimators. The resulting estimators are found to yield significantly improved estimates as compared to the typical Welch-based estimator. Furthermore, we introduce a computationally efficient time-updating of the presented MSC estimators, exploiting their inherent time-varying displacement structure. The presented updating is found to dramatically lower the computational requirement of reevaluating the MSC spectral estimates.
Deep-Water Macroid Beds of the Ryukyu Islands, Japan: Encrusting Acervulinids as Ecosystem Engineers

ABSTRACT Bassi, D. ; Iryu, Y. ; Humblet, M. ; Matsuda, H. ; Machiyama, H. ; Sasaki, K. ; Matsuda, S. ; Arai, K. , and Inoue, T. , 2019. Deep-water macroid beds of the Ryukyu Islands, Japan: Encrusting acervulinids as ecosystem engineers. Journal of Coastal Research, 35(2), 463–466. Coconut Creek (Florida), ISSN 0749-0208. Encrusting acervulinid foraminifera can produce centimeter-sized, free-living coated grains named macroids. Macroid beds are an interesting feature of subtidal environments and have been recognized as important carbonate producers, habitat-forming structures, and paleoenvironmental indicators. Macroids provide a hard, three-dimensional substrate serving as microhabitat for a wide range of diverse organisms. As yet, the most extensive known occurrence of macroid beds in the western Pacific Ocean is found on the insular shelf of Kikai-jima, a coral reef–related island in the central Ryukyu Islands. The surveyed beds occur at water depth of 61–105 m arrayed on a ca. 6-km2 area. Despite their importance for the benthic communities of the Ryukyu Islands, only in the last decade have sampling efforts led to a more comprehensive understanding of the beds' distribution, their structure and associated communities, and the data concerning the influence of environmental factors on macroid beds and their ecological dynamics. In this study, the available information on the biodiversity associated with the recently described Ryukyu macroid beds are reviewed. This review is intended to inform and influence future research and policy planning on this largely unexplored, highly diverse marine ecosystem.
Hyperchaotic Synchronization

In this work we study the synchronization between identical pairs of hyperchaotic mathematical systems symmetrically coupled. Calculations are performed firstly in two well-known hyperchaotic systems, and then compared with the results obtained coupling symmetrically two Takens–Bogdanov systems (TBS) which represent a bifurcation in Codimension 2 (a point with two modes bifurcating simultaneously). In all of these systems, complete synchronization is achieved for some intervals of the coupling strength. As it will be shown, these windows can be localized by using the representation of the Lyapounov exponents against the coupling parameter. We analyze here these three models looking for general features in synchronization of hypercaotic systems, that could be useful to model mutual synchronization of two timedependent convection experiments. We plan to use the results obtained in the TBS as a direct guide to control our experiment because this model was successfully used before to represent the observed dynamics. The other two systems presented here (Chen and Lü) are used to look for the possibility of general features and to check the used numerical methods.
DORC: Distributed online route computation - Higher throughput, more privacy

We propose a technique to distribute the workload of online route planners as offered for example by Bing/Google/Yahoo Maps, etc. among the clients requesting the routes. Our scheme not only increases the throughput of a server answering the requests of clients but also yields a simple way of providing some degree of privacy for the user. A prototype implementation of our system is available as an Android app in Google Play and on Github.
MIMICA: A GENERAL FRAMEWORK FOR SELF-LEARNING COMPANION AI BEHAVIOR

We explore fully autonomous companion characters within the context of Real Time Strategy games. Non-player Characters that are controlled by Artiﬁcial Intelligence to some de- gree, have been a feature of Role Playing games for decades. But RTS games rarely have a player avatar, and thus no real companions. The universe of RTS games where both an avatar and a companion character exist is small. Most friendly RTS units are semi-autonomous at best, requiring player micromanagement of their behavior. We present Mim- icA, a real-time framework to govern AI companion behavior by modeling that of the current player. Built for the Unity engine, MimicA is a learn-by-demonstration framework that differs from existing practices in that the behavior is fully au- tonomous, does not rely on previous modeling exercises and is designed to be generalized and extensible. We analyze and discuss MimicA through a thirty-person user study with our own demonstration game, Lord of Towers . We ﬁnd that 22 out of 30 participants (73%) indicate they enjoyed the game, and this self-reported enjoyment was on par with “traditional tower defense games”. 63% agree that MimicA controlled NPCs are doing what the player would do while 20% disagree. Similarly, 53% realize the NPCs are learning from the player while 20% do not. We also show that NPC with un-derlying Decision Tree and Naive Bayes algorithms are better than KNN in making the player realize the learning nature of the NPC.
Active Learning for Machine Translation in Low Resource Scenarios

Corpus based approaches to automatic translation such as Example Based and Statistical Machine Translation systems use large amounts of parallel data created by humans to train mathematical models for automatic language translation. Large scale parallel data generation for new language pairs requires intensive human effort and availability of fluent bilinguals or expert translators. Therefore it becomes immensely difficult and expensive to provide state-of-theart Machine Translation (MT) systems for rare languages. In this thesis, we propose active learning to reduce costs and make best use of human resources for generating parallel data for MT systems. Active learning approaches help us identify sentences, which if translated have the potential to provide maximal improvement to an existing system. We then expand active learning to other MT relevant tasks such as word alignment, classifying monolingual text by topic, and a joint elicitation of two or more annotations for building domain specific MT systems. As part of this thesis, we develop a new framework Active Crowd Translation (ACT), a cost sensitive active learning setup for building MT systems for lowresource language pairs. Our framework will provide a suitable platform for involving disparately spread out human translators around the world, in a timely and sparingly fashion for rapid building of translation systems. We first explore the ACT paradigm with expert translators and then generalize to fullscale crowdsourcing with non-expert bilingual speakers. In case of Machine Translation, although crowdsourcing services like Amazon’s Mechanical Turk have opened doors to tap human potential, they do not guarantee translation expertise nor extended availability of translators. We address several challenges in eliciting quality translations from an unvetted crowd of bilingual speakers.