Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dual-Layer Broadband Compact UHF RFID Tag Antenna for Platform Tolerant Application

In this paper, we present a compact tag antenna for radio frequency identification (RFID) application. By embedding four parasitic planar inverted-F antennas under the top patch, four adjacent resonant modes are excited simultaneously and the impedance bandwidth is broadened to 140 MHz or more, which fully covers the entire worldwide ultra high frequency (UHF) band (860-960 MHz). The proposed antenna is printed on two FR4 substrates with a total volume of 56 mm×26 mm×3.2 mm. The measured read range was 4 m in a copper plate sized of 500 mm × 500 mm. Experimental studies demonstrate that the proposed antenna could work properly on general tagged objects.
Self-Organizing Maps for Anatomical Joint Constraint Modelling

The accurate simulation of anatomical joint models is becoming increasingly important for both realistic animation and diagnostic medical applications. Recent models have exploited unit quaternions to eliminate singularities when modelling orientations between limbs at a joint. This has led to the development of quaternion based joint constraint validation and correction methods. In this paper a novel method for implicitly modelling unit quaternion joint constraints using Self Organizing Maps (SOMs) is proposed which attempts to address the limitations of current constraint validation and correction approaches. Initial results show that the resulting SOMs are capable of modelling regular spherical constraints on the orientation of the limb.
Wave propagation in piezoelectric layered structure of film bulk acoustic resonator

In this paper, we consider the sandwich structure composed of silicon substrate, piezoelectric layer and electrode layers in the typical structure of FBAR. We assume a special solution in the form of harmonic wave in the piezoelectric layer, and substitute it into the simplified stress equations of motion and the charge equation of electrostatic. A correction to the solution assumed is obtained in order to satisfy these equations. Similarly, a correctional solution assumed in the form of harmonic wave in the silicon substrate can be obtained. We can substitute these correctional solutions into continuity conditions and boundary conditions. The relations of wave number and frequency are obtained. The dispersion curves are calculated from the relation. The frequencies when wave number is zero, the influence of the mass ratio of piezoelectric layer and electrode plate, and the vibration images are discussed further.
Negative Regulation of Phosphatidylinositol 4,5-Bisphosphate Levels by the INP51-associated Proteins TAX4 and IRS4*

Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) is an important second messenger in signaling pathways in organisms ranging from yeast to mammals, but the regulation of PI(4,5)P2 levels remains unclear. Here we present evidence that PI(4,5)P2 levels in Saccharomyces cerevisiae are down-regulated by the homologous and functionally redundant proteins TAX4 and IRS4. The EPS15 homology domain-containing proteins TAX4 and IRS4 bind and activate the PI(4,5)P 5-phosphatase INP51 via an Asn-Pro-Phe motif in INP51. Furthermore, the INP51-TAX4/IRS4 complex negatively regulates the cell integrity pathway. Thus, TAX4 and IRS4 are novel regulators of PI(4,5)P2 and PI(4,5)P2-dependent signaling. The interaction between TAX4/IRS4 and INP51 is analogous to the association of EPS15 with the 5-phosphatase synaptojanin 1 in mammalian cells, suggesting that EPS15 is an activator of synaptojanin 1.
FACTORS INFLUENCING RESOURCE USE BEHAVIOR IN EWASO NAROK WETLAND, KENYA

Wetlands are areas permanently or seasonally flooded by water where plants and animals have become adapted over time. They provide critical ecosystem services and contribute to the national economy both directly and indirectly. The Ewaso Narok Wetland is an important ecosystem providing water, farming land and pasture for the livestock. Despite its importance, the wetland is threatened by human activities such as over-cultivation and overgrazing. Therefore, there is a need for sustainable management of the wetland in order to increase its contribution to livelihoods of the current and future generations. The objective of this study was to characterize the major wetland users, to assess the determinants of the individual rate of time preference and resource use behavior among the users. Stratified simple random sampling technique was used to select 99 pastoralists, 95 commercial and 106 small scale farmers in Ewaso Narok Wetland, Kenya. A questionnaire was used to collect household level data. Descriptive statistics, cross tabulations, one-way ANOVA with Tukey's HSD test were used to characterize the wetland users. Hyperbolic model was used in after the choice and matching tasks in calculating the individual rate of time preference while land use intensity index was used as a proxy for the resource use behaviour. Seemingly unrelated regression estimator (SURE) model was used to identify the factors influencing the individual rate of time preference and resource use behavior of the wetland users. Results show that the individual rate of time preference was influenced positively by the size of land area under crop, conflicts among the users, being a commercial farmer and the distance of a homestead to piped water. The resource use behavior was influenced positively by the individual rate of time preference, household size, the number of years of using the wetland and tropical livestock units and negatively by membership to credit lending groups, the level of education, and security of land tenure. The study concludes that the individual rate of time preference was the major contributor of the high intensity of land use and hence its determinants should be considered in sustainable management of the Ewaso Narok Wetland. Consequently, the study recommends that there should be a provision of title deeds to users in areas outside the wetland area to facilitate sustainable wetland use. Diversification into alternative income generating activities should be encouraged through groups and encourage infrastructural development like installation of piped water as an alternative source of resource to minimize dependency on the wetland.
Coronaviruses in bats from Mexico

Bats are reservoirs for a wide range of human pathogens including Nipah, Hendra, rabies, Ebola, Marburg and severe acute respiratory syndrome coronavirus (CoV). The recent implication of a novel beta (β)-CoV as the cause of fatal respiratory disease in the Middle East emphasizes the importance of surveillance for CoVs that have potential to move from bats into the human population. In a screen of 606 bats from 42 different species in Campeche, Chiapas and Mexico City we identified 13 distinct CoVs. Nine were alpha (α)-CoVs; four were β-CoVs. Twelve were novel. Analyses of these viruses in the context of their hosts and ecological habitat indicated that host species is a strong selective driver in CoV evolution, even in allopatric populations separated by significant geographical distance; and that a single species/genus of bat can contain multiple CoVs. A β-CoV with 96.5 % amino acid identity to the β-CoV associated with human disease in the Middle East was found in a Nyctinomops laticaudatus bat, suggesting that efforts to identify the viral reservoir should include surveillance of the bat families Molossidae/Vespertilionidae, or the closely related Nycteridae/Emballonuridae. While it is important to investigate unknown viral diversity in bats, it is also important to remember that the majority of viruses they carry will not pose any clinical risk, and bats should not be stigmatized ubiquitously as significant threats to public health.
An Exploration of Human-Environment Interactions that Shape the Earth's Surface

The world’s population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to differences between estimates, and illustrate the consequences of applying different estimates in model-based assessments of land-use change. The review estimates a range from 1552 to 5131 Mha, which includes 1550 Mha that is already cropland. Hence, the lowest estimates indicate that there is almost no room for cropland expansion, while the highest estimates indicate that cropland could potentially expand to over three times its current area. Differences can largely be attributed to institutional assumptions, i.e. which land covers/uses (e.g. forests or grasslands) are societally or governmentally allowed to convert to cropland, while there was little variation in biophysical assumptions. Estimates based on comparable assumptions showed a variation of up to 84%, which originated mainly from different underlying data sources. On the basis of this synthesis of the assumptions underlying these estimates, we constructed a high, a medium, and a low estimate of cropland availability that are representative of the range of estimates in the reviewed studies. We apply these estimates in a land-change model to illustrate the consequences on cropland expansion and intensification as well as deforestation. While uncertainty in cropland availability is hardly addressed in global land-use change assessments, the results indicate a large range of estimates with important consequences for model-based assessments. 2.
Optic cup characterization through sparse representation and dictionary learning

This paper describes how to construct a probability map using sparse representation and dictionary learning to indicate the probability of each optic disk pixel of belonging to the optic cup. This probability map will be used in the future as input to a method for automatically detecting glaucoma from color fundus images. The probability map was obtained constructing a model (using the Bayes classifier) which takes into account texture information, by means of sparse representation and RLS-DLA dictionary learning technique, and intensity information. Several experiments on a private database are presented in this work. The results are compared with the segmentation made by specialists, highlighting the promising performance of this technique in difficult cases where the optic cup is barely visible.
Frequent itemset mining on graphics processors

We present two efficient Apriori implementations of Frequent Itemset Mining (FIM) that utilize new-generation graphics processing units (GPUs). Our implementations take advantage of the GPU's massively multi-threaded SIMD (Single Instruction, Multiple Data) architecture. Both implementations employ a bitmap data structure to exploit the GPU's SIMD parallelism and to accelerate the frequency counting operation. One implementation runs entirely on the GPU and eliminates intermediate data transfer between the GPU memory and the CPU memory. The other implementation employs both the GPU and the CPU for processing. It represents itemsets in a trie, and uses the CPU for trie traversing and incremental maintenance. Our preliminary results show that both implementations achieve a speedup of up to two orders of magnitude over optimized CPU Apriori implementations on a PC with an NVIDIA GTX 280 GPU and a quad-core CPU.
An fMRI study dissociating distance measures computed by Broca's area in movement processing: clause boundary vs. identity

Behavioral studies of sentence comprehension suggest that processing long-distance dependencies is subject to interference effects when Noun Phrases (NP) similar to the dependency head intervene in the dependency. Neuroimaging studies converge in localizing such effects to Broca's area, showing that activity in Broca's area increases with the number of NP interveners crossed by a moved NP of the same type. To test if NP interference effects are modulated by adding an intervening clause boundary, which should by hypothesis increase the number of successive-cyclic movements, we conducted an fMRI study contrasting NP interveners with clausal (CP) interveners. Our design thus had two components: (I) the number of NP interveners crossed by movement was parametrically modulated; (II) CP-intervention was contrasted with NP-intervention. The number of NP interveners parametrically modulated a cluster straddling left BA44/45 of Broca's area, replicating earlier studies. Adding an intervening clause boundary did not significantly modulate the size of the NP interference effect in Broca's area. Yet, such an interaction effect was observed in the Superior Frontal Gyrus (SFG). Therefore, the involvement of Broca's area in processing syntactic movement is best captured by memory mechanisms affected by a grammatically instantiated type-identity (i.e., NP) intervention.
Relation Learning Reasoning Meets Tiny Object Tracking in Satellite Videos

Tiny objects in satellite videos are usually not independent individuals; there exist rich semantic and temporal relations with each other. Thus, modeling and reasoning the variation of such intrinsic relationships can be beneficial for tiny object tracking. In this article, a relation learning reasoning method is proposed for tiny object tracking in satellite videos. The core of the proposed is the relation reasoning network that consists of a key context module, a global semantic module, and a relation reasoning module sequentially. First, the key context module exploits global key contexts which explicitly or implicitly contribute to the target object, modeling the intrinsic relations with the target. Second, to reason the contribution, the global semantic module analyses the interaction between them in the same frame. Third, the relation reasoning module deduces the target based on the variation of the semantic relations among different frames. Such a relation learning reasoning approach which takes the target as the core is aligned with the satellite tiny object tracking task, significantly improves the identification performance in dense similarity (DS) scenes and the retrieval ability after completely occluded. Furthermore, the proposed method is shown to report improved qualitative and quantitative results on Jilin-1 and SkySat satellite video datasets.
Studies on a group of previously unclassified bacteria associated with meningitis in infants.

The author's purpose in this report is to describe the morphologic, cultural, and biochemical characteristics of a previously unclassified organism that is apparently an etiologic agent of meningitis in infants. I t causes both sporadic infections and welldefined hospital outbreaks. The first strain reported here was received by this laboratory for identification in August 1949. By August 1956, a total of 7 strains had been received, recognized as unusual organisms, and designated as group I la in our collection of late or nonfermenting Gram-negative rods. Five of these strains were from either the blood or spinal fluid of infants. One strain from an adult's throat remains to be the only strain in our collection known to be from an adult. The age of one patient was unknown. From August 1956 to the end of that year, 4 strains were received—all from infants. This apparent rise in numbers increased our awareness of this problem in relation to the age group involved. When an outbreak in a premature nursery of a South Carolina hospital occurred, the group of organisms was already well defined. The report on this outbreak and a second that occurred later has been the subject of a previous report.
Accounting for the Spatio-Temporal Variability of Pollutant Processes in Stormwater TSS Modeling Based on Stochastic Approaches

Stormwater quality modeling remains one of the most challenging issues in urban hydrology today. The processes involved in contaminant generation and transport are very complex, with many associated uncertainties, including uncertainty arising from process variability. In this study, the spatio-temporal variability of build-up/wash-off processes in a heterogeneous urban catchment within the Parisian region is assessed based on three stochastic modeling approaches integrated into the physically based distributed hydrological model, the Urban Runoff Branching Structure (URBS) model. Results demonstrate that accounting for process variability at the scale of a hydrological element is important for analyzing the contamination recorded at the catchment outlet. The intra-event dynamics of total suspended solids (TSS) were most accurately selected for the stochastic exponential SWMM model, as this model succeeded not only in simulating the general trend of TSS concentrations fluctuations but also in replicating multiple peaks observed in pollutographs. The advantage of this approach is that it captures the stochastic nature of the processes with minimal prior knowledge and without extensive calibration, though further enhancement is necessary for it to become a useful tool to support decision making.
Improved Load-Shedding Scheme Considering Distributed Generation

With high penetration of distributed generation (DG), the conventional underfrequency load shedding (UFLS) faces many challenges and may not perform as expected. This paper proposes new UFLS schemes, which are designed to overcome the shortcomings of the traditional load-shedding scheme. These schemes utilize directional relays, power flow through feeders, wind, and photovoltaic (PV) measurements to optimally select the feeders to be disconnected during load shedding such that DG disconnection is minimized while disconnecting the required amount of consumption. These different UFLS schemes are compared in terms of frequency response, amount of consumption, and DG disconnected during load shedding.
Learning Curve for Seawater Reverse Osmosis Desalination Plants: Capital Cost Trend of the Past, Present, and Future

Seawater reverse osmosis (SWRO) desalination is expected to play a pivotal role in helping to secure future global water supply. While the global reliance on SWRO plants for water security increases, there is no consensus on how the capital costs of SWRO plants will vary in the future. The aim of this paper is to analyze the past trends of the SWRO capital expenditures (capex) as the historic global cumulative online SWRO capacity increases, based on the learning curve concept. The SWRO capex learning curve is found based on 4,237 plants that came online from 1977 to 2015. A learning rate of 15% is determined, implying that the SWRO capex reduced by 15% when the cumulative capacity was doubled. Based on SWRO capacity annual growth rates of 10% and 20%, by 2030, the global average capex of SWRO plants is found to fall to 1,580 USD/(m3/d) and 1,340 USD/(m3/d), respectively. A learning curve for SWRO capital costs has not been presented previously. This research highlights the potential for decrease in SWRO capex with the increase in installation of SWRO plants and the value of the learning curve approach to estimate future SWRO capex.
Chemical inhibition of Wip1 phosphatase contributes to suppression of tumorigenesis

Wip1 is an amplified oncogene whose deletion causes a tumor resistant phenotype in mice. These observations provide justification for a search for Wip1 chemical inhibitors as potential anticancer drugs. Here we report a group of Wip1 inhibitors with anticancer properties both in vitro and in vivo. In vitro, inactivation of Wip1 reduces the proliferation rate of breast cancer cell lines and enhances growth inhibition caused by doxorubicin. In vivo, administration of Wip1 inhibitors decreases proliferation of xenograph tumors and tumors developed in MMTV-c-Neu transgenic mice. We propose that these agents may serve as lead compounds for the development of anticancer drugs targeting Wip1 phosphatase.
One Sense Per Discourse

It is well-known that there are polysemous words like sentence whose "meaning" or "sense" depends on the context of use. We have recently reported on two new word-sense disambiguation systems, one trained on bilingual material (the Canadian Hansards) and the other trained on monolingual material (Roget's Thesaurus and Grolier's Encyclopedia). As this work was nearing completion, we observed a very strong discourse effect. That is, if a polysemous word such as sentence appears two or more times in a well-written discourse, it is extremely likely that they will all share the same sense. This paper describes an experiment which confirmed this hypothesis and found that the tendency to share sense in the same discourse is extremely strong (98%). This result can be used as an additional source of constraint for improving the performance of the word-sense disambiguation algorithm. In addition, it could also be used to help evaluate disambiguation algorithms that did not make use of the discourse constraint.
Prevalence of gastrointestinal symptoms associated with diabetes mellitus: a population-based survey of 15,000 adults.

BACKGROUND Gastrointestinal symptoms are reportedly common in diabetes, but a causal link is controversial and adequate population control data are lacking. OBJECTIVE To determine whether gastrointestinal symptoms are more frequent in persons with diabetes, particularly in those with poor glycemic control. METHODS Fifteen thousand adults were mailed a questionnaire (response rate, 60.0%) containing validated questions on the frequency of troublesome gastrointestinal symptoms within the past 3 months, diabetic status, and self-reported glycemic control. The prevalence of 16 symptoms and 5 symptom complexes, reported to occur often or very often, was compared using logistic regression analysis, adjusting for age and sex. RESULTS Overall, 8657 eligible subjects responded; 423 (4.9%) reported having diabetes. Most (94.8%) had type 2 diabetes mellitus. Adjusting for age and sex, all 16 symptoms and the 5 symptom complexes were significantly more frequent in subjects with diabetes compared with controls. An increased prevalence rate of symptoms was significantly associated with poorer levels of glycemic control but not with duration of diabetes or type of diabetic treatment. CONCLUSIONS Diabetes mellitus is associated with an increased prevalence of upper and lower gastrointestinal symptoms. This effect may be linked to poor glycemic control but not to duration of diabetes or type of treatment.
Grammatical Models

The Markovian nature follows readily from a mechanistic view, where complete knowledge of a system and sufficient computational resources will allow us to determine the state of the system – or distribution over possible states for stochastic systems – at any given point in the future. Markovian need not progress in time, in fact, for many bioinformatics applications the progression will be in one or more sequences. For example, whether a position in a chromosome is maternally or paternally inherited is quite accurately modelled with a dependency only on whether the previous position was maternally or paternally inherited. In alignments we also commonly assume that the homology of a pair of nucleotides only depends on the homology of the predecessor nucleotides, and not the full alignment. Before continuing it may be informative to remember that not all processes we encounter are Markovian, at least not unless further information is included in the state space. A few examples of this include
On the Need for Incentives to Support Personalization Systems - Turning Users into Active Providers of Contents and Metadata

A furnace air filter includes a structure which has two identical rectangularly shaped grid members. The grid members are joined together at one side by a hinge, which hinge is made of the same plastic material as the grid members. The grid members and hinge are integrally formed preferably by an injection molding process. A filter media is placed between the grid members so as to form a filter unit adapted to be positioned in the filter track of a furnace air duct. The plastic grid structure is reusable, requiring the replacement of only the filter media.