Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-bit sliding stack decoding algorithm for OVXDM

Overlapped x domain multiplexing (OVXDM) is a promising encoding technique to obtain high spectral efficiency by utilizing inter-symbol interference (ISI) intelligently. However, the computational complexity of maximum likelihood sequence detection (MLSD) increases exponentially with the growth of spectral efficiency in OVXDM, which is unbearable for practical implementations. In this paper, based on a novel path metric associating adjacent symbols, we propose a multi-bit sliding stack decoding (Multi-Bit SSD) algorithm to achieve multiple-bit decoding simultaneously in OVXDM. Theoretical analysis is provided for the algorithm, which indicates the relationship between the performance and parameters including multiplexing waveform, overlapping fold and sliding window size. Simulation results show that the proposed algorithm can achieve better decoding performance and higher spectral efficiency than conventional fast decoding algorithms.
A fast intra prediction mode decision algorithm for HEVC intra coding of 4K ultra-HD video

Ultra HD 4K/8K video has gradually drawn more attention, but using High Efficiency Video Coding (HEVC) to encode it is time-consuming. Therefore, this paper proposes a fast intra prediction mode decision algorithm for 4K videos, which uses different optimization algorithms for different PU sizes. The 64×64 sized PUs with simple texture use direct predicting mode to optimize the algorithm. The other 64×64 sized PUs and 32×32, 16×16 sized PUs use group traversal optimization algorithm. The other sized PUs use Soble operator to determine the texture in advance. Experimental results show that the proposed method provides a reduction of up to 26.7% in computational complexity with a small increase in the bit-rate and a negligible reduction in PSNR values.
Integrative omics - from data to biology

ABSTRACT Introduction: Multi-omic approaches are promising a broader view on cellular processes and a deeper understanding of biological systems. with strongly improved high-throughput methods the amounts of data generated have become huge, and their handling challenging. Area Covered: New bioinformatic tools and pipelines for the integration of data from different omics disciplines continue to emerge, and will support scientists to reliably interpret data in the context of biological processes. comprehensive data integration strategies will fundamentally improve systems biology and systems medicine. to present recent developments of integrative omics, the göttingen proteomics forum (gpf) organized its 6th symposium on the 23rd of november 2017, as part of a series of regular gpf symposia. more than 140 scientists attended the event that highlighted the challenges and opportunities but also the caveats of integrating data from different omics disciplines. Expert commentary: The continuous exponential growth in omics data require similar development in software solutions for handling this challenge. Integrative omics tools offer the chance to handle this challenge but profound investigations and coordinated efforts are required to boost this field.
Mobile Technology in Undergraduate Nursing Education: A Systematic Review

Objectives This study aimed to identify and systematically review the literature on the use of mobile technology in nursing education. The research findings could evidence the effectiveness of mobile technology in undergraduate nursing students' learning outcomes. Methods Computerized searches were conducted using the Ovid-MEDLINE, Ovid-EMBASE, Cochrane Library, and CINAHL databases for relevant primary studies and limited to those between 2000 and February 2018. Only randomized controlled trials (RCTs) and quasi-experimental studies published in either English or Korean were included and critically appraised using Joanna Briggs Institute tools. Results Seven RCTs and 7 quasi-experimental studies were identified. The mobile device and intervention applied varied throughout all the studies. Studies published earlier in the 2000s found that immediate access to clinical and pharmacological referencing information through the mobile device increased students' efficacy in clinical practice. Later studies, which were mostly conducted in Korea, reported that smartphone-based applications could promote nursing students' learning motivation and satisfaction but not their clinical skills and knowledge. Conclusions We still seem to be in the beginning stage of implementing mobile technology in nursing education due to the limited implication of mobile technology and inconsistent research conclusions. In the future, rigorous primary empirical studies are needed to suggest the effective use of mobile devices in nursing education.
Automatic change detection and spatial attention: a visual mismatch negativity study

Visual mismatch negativity (vMMN) is the electrophysiological correlate of automatic detection of unattended changes in the visual environment. However, vMMNs’ relatedness to spatial attention has not been explicitly tested. Thus, the aim of the study was to investigate the effects of spatial attention on the vMMN event‐related potential component. To this end, participants were instructed to fixate and attend to task‐related stimuli. In an oddball sequence, offset stimuli were applied, i.e., from time‐to time, the two sides of permanently presented objects disappeared. Distance between the task‐related and unrelated events resulted in the typical finding of spatial attention; the amplitude of the N1 component was larger at the shorter distance between the two kinds of events. VMMN was elicited by the deviant vanishing parts, with no reliable effect of distance between the task‐field and vMMN‐related stimuli. In terms of the difference potentials, vMMN was followed by a positive posterior component in the 270–330 ms range. This positivity was much larger when the task‐field was close to vMMN‐related stimuli. The reappearance of the vanishing parts was also investigated. The reappearance of the whole objects after a deviant offset elicited vMMN but only when the task‐field was close to the oddball sequence. We concluded that infrequently vanishing parts of objects are detected automatically. However, these deviant events initiate orientation only if the objects are close to the field of task‐relevant events. Similarly, automatic registration of the rare but expected events are registered only in the visual field close to the focus of attention.
Physics requirements for the FCC-hh calorimeter system

The future proton-proton collider (FCC-hh) will deliver collisions at a center of mass energies up to √s = 100 TeV at an unprecedented instantaneous luminosity of L = 3 1035cm−2s−1, resulting in extremely challenging radiation conditions up to a maximum of 5 1018cm2MeV neutron equivalent fluence and dose up to 5 GGy in the forward calorimeters (up to |η| = 6) and up to 1000 simultaneous proton-proton interactions per bunch-crossing. By delivering an integrated luminosity of few tens of ab−1, the FCC-hh will provide an unrivalled discovery potential for new physics. Requiring high sensitivity for resonant searches at masses up to tens of TeV imposes strong constraints on the design of the calorimeters. Resonant searches in final states containing jets, taus and electrons require both excellent energy resolution at multi-TeV energies as well as outstanding ability to resolve highly collimated decay products resulting from extreme boosts. In addition, the FCC-hh provides the unique opportunity to precisely measure the Higgs self-coupling in the di-photon and b-jets channel. Excellent photon and jet energy resolution at low energies as well as excellent angular resolution for pion background rejection are required in this challenging environment.
Safe memory read-path using silent CRC calculation of binary bit-inversion for low-power fast ROM integrity verifcation

The integrity verifcation of on-chip fash memory data as code memory is becoming important in microcontroller-based applications. On-the-fy memory fail-detection without any interruption of CPU operation requires a fast detection method and low-power fash access hardware to provide safety-conscious execution of the user-programmed frmware during system operations. In this paper, newly-designed read-path architecture for an on-chip fash-embedded microcontroller is proposed in order to provide a memory scrambling method that enables fail-safe low-power memory access with zero hardware overhead by embedding the scramble fags on the CRC protection code. Time-multiplexed CRC calculation for bit-inversion binary code is automatically executed with the silent background mode during CPU idle time without any CPU wait cost. Te implementation result shows the de-inversion procedure could be achieved with only additional 1024 bits CRC data in case of 64 sectors for 4 KB fash memory by reducing 75% area of the previous work.
Emerging abstractions: Lexical conventions are shaped by communicative context

Words exist for referring at many levels of specificity: from the broadest (thing) to the most specific (Fido). What drives the emergence of these taxonomies of reference? Recent computational theories of language evolution suggest that communicative demands of the environment may play a deciding role. Here, we investigate local pragmatic mechanisms of lexical adaptation that may undergird global emergence by manipulating context in a repeated reference game where pairs of participants interactively coordinate on an artificial communication system. We hypothesize that pairs should converge on specific names (e.g. Fido) when the context requires frequently making fine distinctions between entities; conversely, they should converge on a more compressed system of conventions for abstract categories (e.g. dog) in coarser contexts, even if a finer mapping would be sufficient. We show differences in the levels of abstraction that emerged in different environments and introduce a statistical approach to probe the dynamics of emergence.
The Most Important Lesson Schools Can Teach Kids About Reading: It's Fun

In a 2005 speech to the American Library Association, then-senator Obama described his view of the importance of literacy: “In this new economy, teaching our kids just enough so that they can get through Dick and Jane isn't going to cut it,” he said. “The kind of literacy necessary for 21st-century employment requires detailed understanding and complex comprehension. ” Education secretary Arne Duncan’s response to the 2013 National Assessment of Educational Progress earlier this week reinforced a pragmatic approach to literacy: “If America's students are to remain competitive in a knowledge-based economy, our public schools must greatly accelerate the rate of progress of the last four years and do more to narrow America's large achievement gaps. It is an urgent moral and economic imperative that our schools do a better job of preparing students for today's globally-competitive world. ”
An Empirical Estimate for Britain of the Impact of the Real Balance Effect on Income and Interest

In the years since Haberler [15], Scitovsky [33] and Pigou [30;31] first introduced wealth into classical economic theory there have been two main strands to the debate on that part of the wealth effect that has come to be called the real balance effect. One has been the question of whether it is the sine qua non of monetary theory; the other has been the question of its significance for the Keynesian prediction of unemployment equilibrium. Whether the real balance effect is necessary for the integration of money and value theory still seems to be an unresolved issue depending on the nature of the model of the economy specified, and whether or not equilibrium is postulated.l It is not the purpose here to add to this debate. But can the real balance effect guarantee full employment? This is an empirical question, and an important one, because if the real balance effect is weak the
Trader See, Trader Do: How Do (Small) FX Traders React to Large Counterparties’ Trades?

We show that information about the counterparty of a trade affects the future trading decisions of individual traders. The effect is such that traders tend to reverse their order flow in line with the better-informed counterparties. Informed traders primarily incorporate their own private as well as publicly available information into prices, whereas uninformed traders mainly magnify the effect of the informed. This pattern of interaction among traders extends to different order types: traders treat their own and others’ market orders as more informative than limit orders.
Normalized mutual information-based registration using K-means clustering-based histogram binning

A new method for the estimation of the intensity distributions of the images prior to normalized mutual information (NMI) based registration is presented. Our method is based on the K-means clustering algorithm as opposed to the generally used equidistant binning method. K-means clustering is a binning method with a variable size for each bin which is adjusted to achieve a natural clustering. Registering clinical MR-CT and MR-PET images with K-means clustering based intensity distribution estimation shows that a significant reduction is computational time without loss of accuracy as compared to the standard equidistant binning based registration is possible. Further inspection shows a reduction in the NMI variance and a reduction in local maxima for K-means clustering based NMI registration as opposed to equidistant binning based NMI registration.
Allelopathic Activity of Some Medicinal Plants against Erwinia carotovora

Many medicinal plants, exhibit allelopathy to biological management of plant pathogens by reducing their regeneration. This process involving secondary metabolites produced by plant influence the growth and development of agricultural and biological system. This research was to determine the allelopathic potential of aqueous extracts of different medicinal species (Artemisia herba alba, Pistacia atlantica and Juniperus phoenicea) against plant pathogenic bacteria (Erwinia carotovora subsp. Carotovora) in comparison to the antibiotic Streptomycin (positive control). Effect of water extracts evaluated for different concentrations of different extracts for each plant studied was examined under laboratory conditions in petri dishes. The results showed that all the extracts significantly inhibited growth of tested bacteria. The differences in their inhibition depend on to the type of plant and concentration of extract. However, Artemisia herba alba extracts had greater inhibitory potential. Based on the study results, aqueous extracts of three plant species (A. herba alba, P. atlantica and J. phoenicea) showed a negative allelopathic effects on plant pathogenic bacteria (Erwinia carotovora subsp. Carotovora).
Mouse models for investigating the underlying mechanisms of nonalcoholic steatohepatitis-derived hepatocellular carcinoma

As the incidence of hepatocellular carcinoma (HCC) caused by infection with the hepatotropic viruses hepatitis B and hepatitis C decreases, greater attention has become focused on HCC caused by nonalcoholic steatohepatitis (NASH), an advanced form of nonalcoholic fatty liver disease which has shown increasing prevalence in correspondence with the overall increase in metabolic syndrome over the recent decades. Several clinical population studies have shown a positive relationship between NASH and HCC, while also providing initial insights into the underlying mechanisms of HCC development from NASH. Research into the pathological progression of NASH to HCC has advanced by use of several beneficial rodent models. In this review, we summarize the established mouse models for preclinical research of NASH-associated HCC and discuss the underlying hepatic mechanisms of NASH-related tumorigenesis identified to date that could lead to new targets for treatment and prevention.
Anti-inflammatory Activity of New Guaiane Acid Derivatives from Achillea Coarctata

Chromatographic investigation of the methylene chloride/methanol extract of aerial parts of Achillea coarctata afforded two new guaiane acid derivatives, 1α,6α,8α-trihydroxy-5α,7βH-guaia-3,10(14),11(13)-trien-12-oic acid (1) and 1α,6α,8α-trihydroxy-5α,7βH-guaia-3,9,11(13)-trien-12-oic acid (2), in addition to three known compounds, ligustolide-A (3), arteludovicinolide-A (4) and austricin (5). Structures were elucidated by spectroscopic analyses including: 1H and 13C NMR, COSY, HMQC, HMBC and NOESY NMR spectroscopy, as well as MS analysis. Proliferation of beneficial macrophages was significantly enhanced by treatment with 1 and 2. Additionally, treatment with compounds 2 and 4 led to a potentially significant inhibition in nitric oxide generation from raw murine macrophage 264.7, which was stimulated by bacterial lipopolysaccharide. Compounds 2 and 4 exhibited anti-inflammatory properties, based on a nitric oxide assay.
Huddling Conserves Energy, Decreases Core Body Temperature, but Increases Activity in Brandt's Voles (Lasiopodomys brandtii)

Huddling as social thermoregulatory behavior is commonly used by small mammals to reduce heat loss and energy expenditure in the cold. Our study aimed to determine the effect of huddling behavior on energy conservation, thermogenesis, core body temperature (Tb) regulation and body composition in Brandt's voles (Lasiopodomys brandtii). Adult captive-bred female Brandt's voles (n = 124) (~50 g) in 31 cages with 4 individuals each were exposed to cool (23 ± 1°C) and cold (4 ± 1°C) ambient temperatures (Ta) and were allowed to huddle or were physically separated. The cold huddling (Cold-H) groups significantly reduced food intake by 29% and saved digestible energy 156.99 kJ/day compared with cold separated groups (Cold-S); in cool huddling groups (Cool-H) the reduction in food intake was 26% and digestible energy was saved by 105.19 kJ/day in comparison to the separated groups (Cool-S). Resting metabolic rate (RMR) of huddling groups was 35.7 and 37.2% lower than in separated groups at cold and cool Tas, respectively. Maximum non-shivering thermogenesis (NSTmax) of huddling voles was not affected by Ta, but in Cold-S voles it was significantly increased in comparison to Cool-S. Huddling groups decreased wet thermal conductance by 39% compared with separated groups in the cold, but not in the cool Ta. Unexpectedly, huddling voles significantly decreased Tb by 0.25 – 0.50°C at each Ta. Nevertheless, activity of Cold-H voles was higher than in Cold-S voles. Thus, huddling is energetically highly effective because of reduced metabolic rate, thermogenic capacity and relaxed Tb regulation despite the increase of activity. Therefore, Brandt's voles can remain active and maintain their body condition without increased energetic costs during cold exposure. This study highlights the ecological significance of huddling behavior for maintenance of individual fitness at low costs, and thus survival of population during severe winter in small mammals.
The fetus at the tipping point: modifying the outcome of fetal asphyxia

Brain injury around birth is associated with nearly half of all cases of cerebral palsy. Although brain injury is multifactorial, particularly after preterm birth, acute hypoxia–ischaemia is a major contributor to injury. It is now well established that the severity of injury after hypoxia–ischaemia is determined by a dynamic balance between injurious and protective processes. In addition, mothers who are at risk of premature delivery have high rates of diabetes and antepartum infection/inflammation and are almost universally given treatments such as antenatal glucocorticoids and magnesium sulphate to reduce the risk of death and complications after preterm birth. We review evidence that these common factors affect responses to fetal asphyxia, often in unexpected ways. For example, glucocorticoid exposure dramatically increases delayed cell loss after acute hypoxia–ischaemia, largely through secondary hyperglycaemia. This critical new information is important to understand the effects of clinical treatments of women whose fetuses are at risk of perinatal asphyxia.
Two dimensional paraspinal muscle segmentation in CT images

Paraspinal muscles support the spine and are the source of movement force. The size, shape, density, and volume of the paraspinal muscles cross-section area (CSA) are affected by many factors, such as age, health condition, exercise, and low back pain. It is invaluable to segment the paraspinal muscle regions in images in order to measure and study them. Manual segmentation of the paraspinal muscle CSA is time-consuming and inaccurate. In this work, an atlas-based image segmentation algorithm is proposed to segment the paraspinal muscles in CT images. To address the challenges of variations of muscle shape and its relative spatial relationship to other organs, mutual information is utilized to register the atlas and target images, followed by gradient vector flow contour deformation. Experimental results show that the proposed method can successfully segment paraspinal muscle regions in CT images in both intrapatient and interpatient cases. Furthermore, using mutual information to register atlas and target images outperforms the method using spine-spine registration. It segments the muscle regions accurately without the need of the computationally expensive iterative local contour optimization. The results can be used to evaluate paraspinal muscle tissue injury and postoperative back muscle atrophy of spine surgery patients.
Error Analysis of Uyghur Name Tagging: Language-specific Techniques and Remaining Challenges

Regardless of numerous efforts at name tagging for Uyghur, there is limited understanding on the performance ceiling. In this paper, we take a close look at the successful cases and perform careful analysis on the remaining errors of a state-of-the-art Uyghur name tagger, systematically categorize challenges, and propose possible solutions. We conclude that simply adopting a machine learning model which is proven successful for high-resource languages along with language-independent superficial features is unlikely to be effective for Uyghur, or low-resource languages in general. Further advancement requires exploiting rich language-specific knowledge and non-traditional linguistic resources, and novel methods to encode them into machine learning frameworks.
Oxidative Stress in Preeclampsia and Placental Diseases

Preeclampsia is a persistent hypertensive gestational disease characterized by high blood pressure and proteinuria, which presents from the second trimester of pregnancy. At the cellular level, preeclampsia has largely been associated with the release of free radicals by the placenta. Placenta-borne oxidative and nitrosative stresses are even sometimes considered as the major molecular determinants of the maternal disease. In this review, we present the recent literature evaluating free radical production in both normal and pathological placentas (including preeclampsia and other major pregnancy diseases), in humans and animal models. We then assess the putative effects of these free radicals on the placenta and maternal endothelium. This analysis was conducted with regard to recent papers and possible therapeutic avenues.