Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant Functional Group Composition Modifies the Effects of Precipitation Change on Grassland Ecosystem Function

Temperate grassland ecosystems face a future of precipitation change, which can alter community composition and ecosystem functions through reduced soil moisture and waterlogging. There is evidence that functionally diverse plant communities contain a wider range of water use and resource capture strategies, resulting in greater resistance of ecosystem function to precipitation change. To investigate this interaction between composition and precipitation change we performed a field experiment for three years in successional grassland in southern England. This consisted of two treatments. The first, precipitation change, simulated end of century predictions, and consisted of a summer drought phase alongside winter rainfall addition. The second, functional group identity, divided the plant community into three groups based on their functional traits- broadly described as perennials, caespitose grasses and annuals- and removed these groups in a factorial design. Ecosystem functions related to C, N and water cycling were measured regularly. Effects of functional groupidentity were apparent, with the dominant trend being that process rates were higher under control conditions where a range of perennial species were present. E.g. litter decomposition rates were significantly higher in plots containing several perennial species, the group with the highest average leaf N content. Process rates were also very strongly affected by the precipitation change treatmentwhen perennial plant species were dominant, but not where the community contained a high abundance of annual species and caespitose grasses. This contrasting response could be attributable to differing rooting patterns (shallower structures under annual plants, and deeper roots under perennials) and faster nutrient uptake in annuals compared to perennials. Our results indicate that precipitation change will have a smaller effect on key process rates in grasslandscontaining a range of perennial and annual species, and that maintaining the presence of key functional groups should be a crucial consideration in future grassland management.
Improved heart rate variability measurement based on modulation spectral processing of noisy electrocardiogram signals

Wearable device usage is burgeoning, with representative applications ranging from patient/athelete monitoring to stress/fatigue identification to the so-called quantified self movement. Typically, cardiac information is monitored via electrocardiograms (ECG) and information such as heart rate (HR) and heart rate variability (HRV) are used as key health-related metrics. With many wearable devices, however, lower quality sensors are used, thus resulting in devices that are highly sensible to artifacts due to e.g., user's movement. The introduced artifacts hamper HR/HRV analyses, thus ECG enhancement has been the focus of recent research. Existing enhancement algorithms, however, do not perform well in very noisy conditions, as well as add additional computational processing to already battery-hungry wearable applications. Here, we propose to overcome these limitations by describing a new ECG signal representation called the modulation spectrum. By quantifying the rate-of-change of ECG spectral components, signal and artifactual components become separable, thus allowing for accurate HR and HRV measurement from the noisy signal, even in very extreme conditions typically seen in athletic performance training. The proposed MD-HRV (modulation-domain HRV) metric is tested with noise-corrupted synthetic ECG signals and is compared to ‘true’ HRV values obtained from the clean signals. Experimental results show the proposed metric significantly outperforming conventional HRV indices computed on both the noisy, as well as enhanced ECG signals processed by a state-of-the-art wavelet-based algorithm. The obtained findings suggest that the proposed metric is well suited for wearable applications, particularly those involved with intense movement (e.g., in elite athletic training).
Combinatorial Analysis of Multiple Networks

The study of complex networks has been historically based on simple graph data models representing relationships between individuals. However, often reality cannot be accurately captured by a flat graph model. This has led to the development of multi-layer networks. These models have the potential of becoming the reference tools in network data analysis, but require the parallel development of specific analysis methods explicitly exploiting the information hidden in-between the layers and the availability of a critical mass of reference data to experiment with the tools and investigate the real-world organization of these complex systems. In this work we introduce a real-world layered network combining different kinds of online and offline relationships, and present an innovative methodology and related analysis tools suggesting the existence of hidden motifs traversing and correlating different representation layers. We also introduce a notion of betweenness centrality for multiple networks. While some preliminary experimental evidence is reported, our hypotheses are still largely unverified, and in our opinion this calls for the availability of new analysis methods but also new reference multi-layer social network data.
An exploratory examination of student dismissals and prompted resignations from clinical psychology PhD training programs : Does clinical competency matter?

How do clinical psychology PhD training programs decide whether a student should be dismissed? Are these decisions related to the student's clinical competency or suitability? Accredited, scientist-practitioner clinical psychology PhD training programs were surveyed about their experiences with dismissal decisions and clinical competency evaluations. Average rates of student dismissal and prompted resignations were low (less than 3% and 6%, respectively) but highly variable across programs. The most common basis for dismissals and resignations pertained to clinical competency concerns and academic standards. However, for 29% of programs, documented dismissal criteria did not include expectations for achievement of a prescribed level of clinical skills proficiency. Implications and suggested courses of action are discussed.
Plasma Neurofilament Heavy Chain Levels Correlate to Markers of Late Stage Disease Progression and Treatment Response in SOD1G93A Mice that Model ALS

Background Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disorder characterised by progressive degeneration of motor neurons leading to death, typically within 3–5 years of symptom onset. The diagnosis of ALS is largely reliant on clinical assessment and electrophysiological findings. Neither specific investigative tools nor reliable biomarkers are currently available to enable an early diagnosis or monitoring of disease progression, hindering the design of treatment trials. Methodology/Principal Findings In this study, using the well-established SOD1G93A mouse model of ALS and a new in-house ELISA method, we have validated that plasma neurofilament heavy chain protein (NfH) levels correlate with both functional markers of late stage disease progression and treatment response. We detected a significant increase in plasma levels of phosphorylated NfH during disease progression in SOD1G93A mice from 105 days onwards. Moreover, increased plasma NfH levels correlated with the decline in muscle force, motor unit survival and, more significantly, with the loss of spinal motor neurons in SOD1 mice during this critical period of decline. Importantly, mice treated with the disease modifying compound arimoclomol had lower plasma NfH levels, suggesting plasma NfH levels could be validated as an outcome measure for treatment trials. Conclusions/Significance These results show that plasma NfH levels closely reflect later stages of disease progression and therapeutic response in the SOD1G93A mouse model of ALS and may potentially be a valuable biomarker of later disease progression in ALS.
Essential Oils in Combination and Their Antimicrobial Properties

Essential oils (EOs) have been long recognized for their antibacterial, antifungal, antiviral, insecticidal and antioxidant properties. They are widely used in medicine and the food industry for these purposes. The increased interest in alternative natural substances is driving the research community to find new uses and applications of these substances. EOs and their components show promising activities against many food-borne pathogens and spoilage microorganisms when tested in vitro. In food systems, higher concentrations of EOs are needed to exert similar antibacterial effects as those obtained in in vitro assays. The use of combinations of EOs and their isolated components are thus new approaches to increase the efficacy of EOs in foods, taking advantage of their synergistic and additive effects. The purpose of this review is to provide an overview on the antimicrobial efficacy of these combinations. A survey of the methods used for the determination of the interactions and mechanisms involved in the antimicrobial activities of these combinations are also reported.
Angioarchitectures and Hemodynamic Characteristics of Posterior Communicating Artery Aneurysms and Their Association with Rupture Status

The authors studied 313 posterior communicating artery aneurysms (145 ruptured, 168 unruptured) with image-based computational fluid dynamics. Aneurysms were classified into different angioarchitecture types depending on the location of the aneurysm with respect to parent artery bifurcation. Ruptured aneurysms had higher, more concentrated, and more oscillatory wall shear stress distributions; stronger and more concentrated inflow jets; and more complex and unstable flow patterns compared with unruptured aneurysms. They conclude that high-flow intrasaccular hemodynamic characteristics, commonly found in bifurcation-type angioarchitectures, are associated with the posterior communicating artery aneurysm rupture status. BACKGROUND AND PURPOSE: Intracranial aneurysms originating at the posterior communicating artery are known to have high rupture risk compared with other locations. We tested the hypothesis that different angioarchitectures (ie, branch point configuration) of posterior communicating artery aneurysms are associated with aneurysm hemodynamics, which in turn predisposes aneurysms to rupture. MATERIALS AND METHODS: A total of 313 posterior communicating artery aneurysms (145 ruptured, 168 unruptured) were studied with image-based computational fluid dynamics. Aneurysms were classified into different angioarchitecture types depending on the location of the aneurysm with respect to parent artery bifurcation. Hemodynamic characteristics were compared between ruptured and unruptured aneurysms, as well as among aneurysms with different angioarchitectures. RESULTS: Angioarchitecture was associated with rupture (P = .003). Ruptured aneurysms had higher, more concentrated, and more oscillatory wall shear stress distributions (maximum wall shear stress, P < .001; shear concentration index, P < .001; mean oscillatory shear index, P < .001), stronger and more concentrated inflow jets (represented as Q, P = .01; inflow concentration index, P < .001), and more complex and unstable flow patterns (vortex core length, P < .001; proper orthogonal decomposition entropy, P < .001) compared with unruptured aneurysms. These adverse conditions were more common in aneurysms with bifurcation-type angioarchitectures compared with those with lateral or sidewall angioarchitectures. Interestingly, ruptured aneurysms also had lower normalized mean wall shear stress (P = .02) and minimum wall shear stress (P = .002) than unruptured aneurysms. CONCLUSIONS: High-flow intrasaccular hemodynamic characteristics, commonly found in bifurcation-type angioarchitectures, are associated with the posterior communicating artery aneurysm rupture status. These characteristics include strong and concentrated inflow jets, concentrated regions of elevated wall shear stress, oscillatory wall shear stress, lower normalized wall shear stress, and complex and unstable flow patterns.
Effect of adult leader participation on physical activity in children

Background: Participation in physically active games is one way to increase energy expendture in children. However, it is unknown whether adult leader participation (LP) in games can impact children’s physical activity (PA) levels. The purpose of this study was to examine the influence of LP compared to no LP on PA levels among children participating in organized active games. Methods: Children (n = 14) in grades 4 - 6 (Male = 42.8%, White = 50%, Overweight/ Obese = 42.8%) participated in four active games across two consecutive days. Each day, children participated in two 16-minute games and received verbal encouragement from an adult leader. Each game was divided into four-minute intervals alternating between LP or no LP. LP was counter-balanced across two days. Each child wore an Actigraph GT1M accelerometer. Time spent in moderate-to-vigorous PA (MVPA), vigorous PA (VPA), and sedentary behavior (SB) was determined by Freedson’s MET prediction. Data were analyzed using a condition (LP or no LP) by game repeated-measures ANCOVA. Results: Children participated in MVPA 52.3% of game time across all games. There were no differences in MVPA, VPA, and SB by gender, weight status, or ethnicity. LP and no LP conditions were not different for MVPA, VPA, or SB. Conclusions: These results show no effect of LP on PA in children during active games. It may be that LP could not increase PA because the children were already exhibiting high levels of MVPA.
Domestic, peridomestic and wild hosts in the transmission of Trypanosoma cruzi in the Caatinga area colonised by Triatoma brasiliensis

The role played by different mammal species in the maintenance of Trypanosoma cruzi is not constant and varies in time and place. This study aimed to characterise the importance of domestic, wild and peridomestic hosts in the transmission of T. cruzi in Tauá, state of Ceará, Caatinga area, Brazil, with an emphasis on those environments colonised by Triatoma brasiliensis. Direct parasitological examinations were performed on insects and mammals, serologic tests were performed on household and outdoor mammals and multiplex polymerase chain reaction was used on wild mammals. Cytochrome b was used as a food source for wild insects. The serum prevalence in dogs was 38% (20/53), while in pigs it was 6% (2/34). The percentages of the most abundantly infected wild animals were as follows: Thrichomys laurentius 74% (83/112) and Kerodon rupestris 10% (11/112). Of the 749 triatomines collected in the household research, 49.3% (369/749) were positive for T. brasiliensis, while 6.8% were infected with T. cruzi (25/369). In captured animals, T. brasiliensis shares a natural environment with T. laurentius, K. rupestris, Didelphis albiventris, Monodelphis domestica, Galea spixii, Wiedomys pyrrhorhinos, Conepatus semistriatus and Mus musculus. In animals identified via their food source, T. brasiliensis shares a natural environment with G. spixii, K. rupestris, Capra hircus, Gallus gallus, Tropidurus oreadicus and Tupinambis merianae. The high prevalence of T. cruzi in household and peridomiciliar animals reinforces the narrow relationship between the enzootic cycle and humans in environments with T. brasiliensis and characterises it as ubiquitous.
The Security Mechanism for IEEE 802.11 Wireless Networks

This paper provides an introduction to Wireless Local Area Networks (WLAN), and the methods employed to secure access using the IEEE 802.11 architecture. The vulnerability of IEEE 802.11 technology is disconcerting, although effective security mechanism can be implemented to secure a wireless network. In the future wireless connections will befall a standard on laptops, PDA's and other wireless devices so we need to secure all client and access points to mitigate threats.
Adaptive Weighted Ensemble Deep Learning for Robust Rumor Detection on Social Media

Rumor detection in social media is a critical concern and is exacerbated by the complexity and diversity of rumor texts. Within social media rumor posts, auxiliary elements such as real-time emerging comments regarding the event can reveal public uncertainty and skepticism about the content in question. Motivated by this intuition, we propose the Adaptive Weighted Ensemble Deep Learning model (AWEDL), an innovative framework that integrates rumor and stance models. AWEDL adeptly captures user attitudes embedded in comment data, without requiring explicit stance labels. Through a comprehensive process of weighted fusion and dynamic adjustment of vector representations pertaining to rumors and stances, AWEDL strikes an optimal balance between these features. This approach culminates in an increase in the precision of rumor detection. Extensive validation on three well-recognized datasets, including Twitter15, Twitter16, and Weibo, firmly establishes AWEDL's superiority over existing benchmarks, with notably remarkable performance on the Weibo dataset, achieving an average F1 score of 95.7%.
Targeting CTCF to Control Virus Gene Expression: A Common Theme amongst Diverse DNA Viruses

All viruses target host cell factors for successful life cycle completion. Transcriptional control of DNA viruses by host cell factors is important in the temporal and spatial regulation of virus gene expression. Many of these factors are recruited to enhance virus gene expression and thereby increase virus production, but host cell factors can also restrict virus gene expression and productivity of infection. CCCTC binding factor (CTCF) is a host cell DNA binding protein important for the regulation of genomic chromatin boundaries, transcriptional control and enhancer element usage. CTCF also functions in RNA polymerase II regulation and in doing so can influence co-transcriptional splicing events. Several DNA viruses, including Kaposi’s sarcoma-associated herpesvirus (KSHV), Epstein-Barr virus (EBV) and human papillomavirus (HPV) utilize CTCF to control virus gene expression and many studies have highlighted a role for CTCF in the persistence of these diverse oncogenic viruses. CTCF can both enhance and repress virus gene expression and in some cases CTCF increases the complexity of alternatively spliced transcripts. This review article will discuss the function of CTCF in the life cycle of DNA viruses in the context of known host cell CTCF functions.
On the Computation of Rigid Body Motion

We present two methods for generating trajectories and motion interpolants that minimize energy functionals on SE(3), the group of rigid body displacements. We treat SE(3) as a Lie Group and endow it with a left-invariant Riemannian metric derived from energy considerations. The first method is based on a relaxation formulation where the Euler-Lagrange equations for the minimization problem are solved. The second method offers a closed form, but approximate solution to the problem. Both methods preserve invariance. We compare the two methods in terms of computational efficiency and accuracy.
AN ANALYSIS OF SEX RATIO AT BIRTH IN CROATIA 1946 – 2007

Sex ratio at birth has been one of the most studied, yet most poorly understood demographic phenomena. Numerous physiological, ecological and demographic factors seem to influence it although an unequivocal explanation is lacking. Indeed, some countries have exhibited a trend in the sex ratio at birth over the years. Their sex ratio at birth time- -series can be modeled with the non-random stochastic processes which reflect the interdependency in the subsequent annual observations. This article examines sex ratio at birth for the Republic of Croatia during the years 1946 to 2007. The tests for assessing the time-series were performed, along with the autoregression modeling. The Croatian time-series is the product of a pure random process with no observable time trend despite the presence of some factors known to affect the sex ratio at birth. It is suggested that the size of the live-birth population is not great enough to reflect the subtle changes in these factors.
TERMINATION OF TOLERANCE TO HUMAN GAMMA GLOBULIN IN MICE BY ANTIGEN AND BACTERIAL LIPOPOLYSACCHARIDE (ENDOTOXIN)

Bacterial lipopolysaccharides (endotoxin) allowed the circumvention of the thymus-derived (T) cell helper function otherwise required for the antibody response in mice to human gamma globulin (HGG). In an analogous fashion, the state of tolerance to HGG, existing at a time when bone marrow-derived (B) cells had lost their unresponsiveness, could be terminated by the injection of both immunogenic HGG and endotoxin, but by neither given alone. However, no effect on tolerance to HGG could be observed when this regimen was followed at a time when B cells were tolerant. After the spontaneous recovery from tolerance in B cells, it seemed that specific priming was occurring in that population. This phenomenon was observed either by the injection of endotoxin and HGG or by the adoptive transfer of cells into irradiated hosts. These data have been discussed in the light of potential autoimmune manifestations that could theoretically follow a simultaneous gram-negative bacterial infection along with a release of self-antigen.
Streaming Terrains

Streaming computer graphics data is challenging because of the need to retrieve large triangle meshes before any display can begin. This paper proposes and analyzes the benefits of borrowing techniques from lossy image compression to implement a novel technique of progressive terrain rendering for streaming over a network. The goal of the work is to provide a qualityaware framework for 3-D rendering of heightfields.
Exploiting Hyperlinks to Study Academic Web Use

Hyperlinks have attracted a lot of attention over the past 7 years, from computer scientists, information scientists, physicists, and sociologists, all using them for different purposes. In this article, the authors review recent progress from the information science approach and summarize current techniques for extracting usable information from web links. The description is particularly aimed at those unfamiliar with the literature but who nevertheless wish to use web links to investigate some aspect of online behavior, particularly informal scholarly communication.
A non-myopic approach for a domotic battery management system

The foreseeable dynamic pricing of electricity combined with the emergence of the so-called electricity “prosumers” that not only consume, but also have the ability to produce and store electricity, necessitates the development of energy management systems even at residential level. In this context, the present work considers that in a modern residence, or a “smart house”, electricity is generated from micro-renewable energy sources, while the electricity storage options include a fixed battery as well as the battery from a plug-in electric vehicle. This paper presents the theoretical framework for the implementation of a domotic battery management system with the key characteristic that energy management decisions are made every 10 min, based on the forecasted conditions for the next 24 h. The results obtained from the simulation of the proposed system highlight the contribution not only of the fixed battery, but also of the electric vehicle's battery to the maximization of electricity cost savings.