Miracle-dz/UniFAR-FTUs huggingface dataset:
A quantitative taxonomic review of Fusichonetes and Tethyochonetes (Chonetidina, Brachiopoda)

Abstract. Two middle Permian (Capitanian) to Early Triassic (Griesbachian) rugosochonetidae brachiopod genera, Fusichonetes Liao in Zhao et al., 1981 and Tethyochonetes Chen et al., 2000, have been regarded as two distinct taxa and used as such for a wide range of discussions including biostratigraphy, paleoecology, paleobiogeography, and the Permian-Triassic boundary mass extinction. However, the supposed morphological distinctions between the two taxa are subtle at best and appear to represent two end members of a continuum of morphological variations. In this study, we applied a range of quantitative and analytical procedures (bivariate plots, Kolmogorov-Smirnov test, categorical principle component analysis, and cladistic analysis) to a dataset of 15 quantified morphological variables, integrating both key external and internal characters, measured from 141 specimens of all well-known Fusichonetes and Tethyochonetes in order to test whether or not these two genera could be distinguished in view of the chosen characters. The results indicate that these two genera are morphologically indistinguishable and that the species classification previously applied to these two genera appears to represent polyphyletic groupings within the genus Fusichonetes. Consequently, Tethyochonetes is concluded to be a junior synonym of Fusichonetes. The diagnosis and key characteristics of Fusichonetes are clarified and refined based on a new suite of well-preserved specimens from the Permian −Triassic Xinmin section in South China.
Habitat isolation diminishes potential of self-organised pattern formation to promote local diversity in metacommunities

Progressive destruction and isolation of natural habitat is a major threat to biodiversity worldwide. In this study we use a trophic metacommunity model with complex, spatially explicit structure to address how the interaction of local and regional processes affects the functional diversity of autotroph (producer) communities within and between individual habitat patches. One important driver of biodiversity in metacommunities is spatial heterogeneity of the environment, as it enables source-sink dynamics between patches. Besides a-priori differences in the environmental conditions, heterogeneous distributions of resources and species biomasses can also emerge through self-organised pattern formation caused by scale-dependent feedback between local trophic and regional dispersal dynamics. We show that this emergent heterogeneity can enhance the functional diversity of local autotroph communities by jointly strengthening source-sink dynamics and reducing stabilising selection pressure. Our results indicate that this effect is particularly strong in highly connected metacommunities, while metacommunity size (number of patches) alone plays a lesser role. We demonstrate that the positive effect on local diversity is driven by an eco-evo-spatial feedback loop that is fueled by the asynchronous biomass- and trait dynamics between the patches created by self-organised pattern formation. In highly connected metacommunities, oscillatory biomass patterns with particularly large amplitude strengthen this feedback loop. Our findings are highly relevant in the light of anthropogenic habitat changes that often destroy dispersal pathways, thereby increasing habitat isolation, lowering overall connectance of metacommunities and ultimately threatening the biodiversity in local habitats. Only a joint investigation of the contributing ecological, evolutionary, and spatial mechanisms in complex model systems can yield comprehensive understanding of these processes, allowing for the development of strategies to mitigate adverse anthropogenic influence.
Correlation between bioluminescent blinks and swimming behavior in the splitfin flashlight fish Anomalops katoptron

The light organs of the splitfin flashlight fish Anomalops katoptron are necessary for schooling behavior, to determine nearest neighbor distance, and to feed on zooplankton under dim light conditions. Each behavior is coupled to context-dependent blink frequencies and can be regulated via mechanical occlusion of light organs. During shoaling in the laboratory individuals show moderate blink frequencies around 100 blinks per minute. In this study, we correlated bioluminescent blinks with the spatio-temporal dynamics of swimming profiles in three dimensions, using a stereoscopic, infrared camera system. Groups of flashlight fish showed intermediate levels of polarization and distances to the group centroid. Individuals showed higher swimming speeds and curved swimming profiles during light organ occlusion. The largest changes in swimming direction occurred when darkening the light organs. Before A. katoptron exposed light organs again, they adapted a nearly straight movement direction. Light organs create a strong contrast against the background. Therefore, a close combination of light signals and movement is crucial to the behavior of A. katoptron.
Escape from X inactivation is directly modulated by levels of Xist non-coding RNA

In placental females, one copy of the two X chromosomes is largely silenced during a narrow developmental time window, in a process mediated by the non-coding RNA Xist 1. Here, we demonstrate that Xist can initiate X-chromosome inactivation (XCI) well beyond early embryogenesis. By modifying its endogenous level, we show that Xist has the capacity to actively silence genes that escape XCI both in neuronal progenitor cells (NPCs) and in vivo, in mouse embryos. We also show that Xist plays a direct role in eliminating TAD-like structures associated with clusters of escapee genes on the inactive X chromosome, and that this is dependent on Xist’s XCI initiation partner, SPEN 2. We further demonstrate that Xist’s function in suppressing gene expression of escapees and topological domain formation is reversible for up to seven days post-induction, but that sustained Xist up-regulation leads to progressively irreversible silencing and CpG island DNA methylation of facultative escapees. Thus, the distinctive transcriptional and regulatory topologies of the silenced X chromosome is actively, directly - and reversibly - controlled by Xist RNA throughout life.
Cholesterol modifies Nav1.7 - an in-silico and in-vitro analysis

Cholesterol is a major component of plasma membranes and unsurprisingly plays a significant role in actively regulating the functioning of several membrane proteins in humans. Notably, recent studies have shown that cholesterol depletion can also impact transmission of potentially painful signals in the context of peripheral inflammation, via hyperexcitability of the voltage-gated sodium channel (Nav) subtype 1.9, but the structural mechanisms underlying this regulation remain to be elucidated. In this study, we focus on the role of cholesterol depletion on Nav1.7, which is primarily expressed in the peripheral sensory neurons and linked to various chronic inherited pain syndromes. Coarse-grained molecular dynamics simulations shed light on the dynamic changes of the geometry of Nav1.7 upon membrane cholesterol depletion: A loss of rigidity at key structural motifs linked to activation and fast-inactivation is observed, as well as changes in the geometry of drug-binding regions in the channel. Loss of rigidity in cholesterol depleted conditions should allow the channel to transition between different gating states more easily. In-vitro whole-cell patch clamp experiments on HEK293t cells expressing Nav1.7 validated these predictions made in silico at the functional level. Hyperpolarizing shifts in the voltage-dependence of activation and fast-inactivation were observed along with an acceleration of the time to peak and onset kinetics of fast inactivation. These results underline the critical role of membrane composition, and of cholesterol in particular, in influencing Nav1.7 gating characteristics. Furthermore, our results hint to a key role of the membrane environment in affecting drug effects and in pathophysiological dysregulation, sharpening our approaches for analgesics design.
Development of a 3D in vitro human-sized model of cervical dysplasia to evaluate the delivery of ethyl cellulose-ethanol injection for the treatment of cervical dysplasia ablation

Cervical cancer, the second leading cause of cancer-related death for women worldwide, remains a preventable yet persistent disease that disproportionately affects women in low and middle-income countries (LMICs). While existing therapies for treating cervical dysplasia are effective, they are often inaccessible in LMICs. Ethanol ablation is an alternative low-cost, accessible therapy that we previously enhanced into an ethyl cellulose (EC)-ethanol gel formulation to improve efficacy. When seeking to evaluate EC-ethanol for cervical dysplasia, we found a paucity of relevant animal models. Thus, in this study, we developed a 3D in vitro model of cervical dysplasia featuring a central lesion of cervical cancer cells surrounded by fibroblasts and keratinocytes to enable the evaluation of EC-ethanol and other novel therapeutics. Our GelMA-based 3D model successfully captured the architectural complexity of cervical dysplasia, showcasing cell response and high viability. The GelMA hydrogel formulation (8.7% w/v) exhibited viscoelastic properties akin to human cervical tissue. Using micro-CT imaging, we assessed EC-ethanol injection deposition in the hydrogel, revealing retention of virtually the entire injected volume near the injection site. Finally, we evaluated the EC-ethanol injection’s efficacy in eliminating cervical cancer cells. The EC-ethanol injection led to a significant decrease in cancer cell viability while preserving healthy cells in the 3D in vitro model. Taken together, our in vitro model mirrored the architecture of cervical dysplasia and demonstrated the potential of EC-ethanol for localized treatment of cervical dysplasia.
Reconstructing gait cycle patterns from non-invasive recorded low gamma modulations

This work presents a simple to set-up system for reconstructing gait cycle patterns from non-invasive recorded electroencephalographic (EEG) signals. It is based on the prior finding that low gamma amplitudes are modulated locked to the gait cycle in central sensorimotor areas. Therefore, we focused on a Laplacian Cz derivation and low gamma amplitude modulations to reconstruct the gait patterns. Our results show that this method was successful in reconstructing gait cycle patterns in 8/10 subjects during active walking and in every subject during passive walking. The median reconstruction error was 0.24±0.13 s for active and 0.26±0.10 s for passive walking. The presented methods and findings are a further step towards analysing and monitoring ongoing cortical activity during human upright walking.
Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors

1 Comprehensive Cancer Center Mainfranken, University of Würzburg, 97080 Würzburg, 5 Germany. 6 2 Institute of Pathology, University of Würzburg, 97080 Würzburg, Germany. 7 3 Bavarian Cancer Research Center (BZKF), 97080 Würzburg, Germany. 8 4 Center for Computational and Theoretical Biology, University of Würzburg, 97074 9 Würzburg, Germany. 10 5 Department of Urology and Pediatric Urology, University Hospital Würzburg, 97080 11 Würzburg 12 6 Klinikum Stuttgart, Department of Hematology, Oncology, Stem Cell Transplantation and 13 Palliative Care, 70174 Stuttgart, Germany 14 7 Klinikum Stuttgart, Stuttgart Cancer Center – Tumor Unit Eva Mayr-Stihl, 70174 Stuttgart, 15 Germany 16 8 Guido Baccelli Unit of Internal Medicine, Department of Biomedical Sciences and Human 17 Oncology, School of Medicine, Aldo Moro University of Bari, 70124 Bari, Italy. 18 9 IRCCS Istituto Tumori “Giovanni Paolo II” of Bari, 70124 Bari, Italy. 19
Synthetic or autologous plugs for the repair of osteochondral rabbit knee defects: A comparative study

The aim of this experimental animal study was to compare histologically and immunohistochemically knee cartilage appearances after cartilage resurfacing of iatrogenic de- fects with biosynthetic plug, autograft or conservative approach. Thirty New Zealand White rabbits were used. A full-thickness cylindrical defect of the femoral groove of 4,5mm x 7mm was created with a hand drill. In Group A the defect was repaired with a bone graft substitute (BGS) plug, in Group B with an osteochondral autograft, while in Group C rabbits were left untreated. 24 weeks postoperatively, smooth articular was found macroscopically in some trocleas’ surfaces; in all others, an articular surface with discontinuities was ob- served. Histology revealed many statistical differences between the groups as far as the ICRS categories are concerned. In particular, the mean scores were for the BGS group 1,2±1,55 (surface), 1,6±1,35(matrix), 0,7±0,82 (cell distribution), 3 (cell viability), 1,4±0,84 (subchondral bone) and 1,2±1,55 (cartilage mineralization). The values for the autograft group were 1,5±1,58, 3,2,3,2,3 respectively. The control group received the following val- ues respectively: 0,9±1,45, 0,7±0,67, 0,1±0,32, 2,6±0,84, 0,9±1,19, 0,6±1,26. Immunofluo- resence also revealed many differences. In group A, six specimens were found with collagen II. All specimens of group B revealed to have collagen II, while the control group only one specimen was found with collagen II. We found statistical differences as far as the matrix, cell distribution, subchondral bone and cartilage mineralization ICRS categories are concerned. Group B received the best scores, while group A was second; the control group got the worst ICRS scores in these categories. The treatment of osteochondral lesions is better amended with osteochondral autograft rather than with synthetic BGS implants.
Relationship Between Orogenic Gold Mineralization and Crustal Shearing Along Ailaoshan‐Red River Belt, Southeastern Tibetan Plateau: New Constraint From Paleomagnetism

A new perspective on the relationship between orogenic gold mineralization and crustal shearing is presented in this case study on the gold deposits along Ailaoshan‐Red River shear zone (ARSZ), southeastern Tibetan Plateau. The sinistral ductile shearing along the zone occurred from ca. 31 to 17 Ma resulting in a displacement of ~1,000 km. A series of orogenic gold deposits, represented by the Zhenyuan and Chang'an deposits, occur on western margin of the ARSZ. The timing of mineralization and its relationship to shearing continues to be debated despite extensive geological and geochemical studies. Here we try to clarify this issue by using paleomagnetism to constrain the paleolatitude of mineralized rocks. High temperature magnetization components were isolated from the mineralized rocks, and they record modification by ore‐forming fluid. Their magnetization yields a paleolatitude of 19.9° ± 3.6°N for the Zhenyuan deposit and 16.2° ± 2.9°N for the Chang'an deposit. The paleolatitudes from these deposits are similar to those of ca. 20 Ma strata (19.0° ± 3.6°N), deposited after the large‐scale shearing. By contrast, they differ significantly from the paleolatitude obtained from ca. 130 to 40 Ma strata (28.4° ± 1.1°N), which formed long before the onset of large‐scale shearing. These observations imply that the orogenic gold mineralization occurred after the main offset and associated ductile deformation of the ARSZ. Gold mineralization is thought to be related to ore‐forming fluids and metals derived from the subcrust, rather than from fluids released from shearing‐induced metamorphism of regional strata.
A Spiking Neuron Model ( To appear in Neural Networks

This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the model as well as its applications in Computational Neuroscience are demonstrated and a learning algorithm based on postsynaptic delays is proposed. The TNLI incorporates temporal dynamics at the neuron level by modelling both the temporal summation of dendritic postsynaptic currents which have controlled delay and duration and the decay of the somatic potential due to its membrane leak. Moreover, the TNLI models the stochastic neurotransmitter release by real neuron synapses (with probabilistic RAMs at each input) and the firing times including the refractory period and action potential repolarisation. The temporal features of the TNLI make it suitable for use in dynamic time-dependent tasks like its application as a motion and velocity detector system presented in this paper. This is done by modelling the experimental velocity selectivity curve of the motion sensitive H1 neuron of the visual system of the fly. This application of the TNLI indicates its potential applications in artificial vision systems for robots. It is also demonstrated that Hebbian-based learning can be applied in the TNLI for postsynaptic delay training based on coincidence detection, in such a way that an arbitrary temporal pattern can be detected and recognised. The paper also demonstrates that the TNLI can be used to control the firing variability through inhibition; with 80% inhibition to concurrent excitation, firing at high rates is nearly consistent with a Poisson-type firing variability observed in cortical neurons. It is also shown with the TNLI, that the gain of the neuron (slope of its transfer function) can be controlled by the balance between inhibition and excitation, the gain being a decreasing function of the proportion of inhibitory inputs. Finally, in the case of perfect balance between inhibition and excitation, i.e., where the average input current is zero, the neuron can still fire as a result of membrane potential fluctuations. The firing rate is then determined by the average input firing rate. Overall this work illustrates how a hardware-realisable neuron model can capitalise on the unique computational capabilities of biological neurons.
THE IMPACT OF INFORMATION SECURITY AWARENESS TRAINING ON INFORMATION SECURITY BEHAVIOUR

i DECLARATION ii ACKNOWLEDGEMENTS iii LIST OF TABLES vi LIST OF FIGURES vii Chapter 1 : INTRODUCTION 1 1.1. The impact on organisations is potentially significant 4 1.2. This research will help to solve the problem 7 1.3. Introducing a viable research design 10 1.4. Summary 16 Chapter 2 : THE INFORMATION SECURITY AWARENESS LANDSCAPE 17 2.
Uncertainty and Sensitivity Analyses of the Modified Wind Erosion Equation for Application in Canada

The wind erosion equation (WEQ) was used for several decades for predicting soil loss by wind erosion, but few systematic studies on the uncertainty of predicting wind erosion have been conducted. Several researchers found that WEQ is not accurately representing soil erosion and under‐represents soil erodibility that consequently results in WEQ underestimations. WEQ was modified under Canadian conditions for the National Agri‐Environmental Health Analysis and Reporting Program, referred as (WEQ‐NAHARP). The model, input, and parameter uncertainties that control model efficiency were used to analyze the local and universal uncertainties for WEQ‐NAHARP. One and ninety‐nine percentiles were used as lower and upper boundaries of uncertainty bound when using general likelihood uncertainty estimation for estimating the uncertainty of WEQ‐NAHARP's prediction. The soil erodibility (I), climate factor (C), and soil surface roughness factor (K) were found as the three most sensitive factors in predicting wind erosion in WEQ‐NAHARP. The vegetation cover factor (V) was discovered not sensitive to the prediction model as it is less than 1,000 kg ha−1 and became very sensitive as V‐value is greater than 5,000 kg ha−1. Field length along the prevailing wind erosion direction (L) and V have lower local sensitivity indexes than the other three factors. WEQ‐NAHARP underestimated wind erosion rate of Pampas, Argentina, and overestimated at Washington State, USA. This probably reflected the nature of WEQ‐NAHARP's behavior, which had a great uncertainty of its prediction. The model appears to underestimate total annual soil loss for coarse soil and overestimate annual soil loss for finer soil. Copyright © 2017 John Wiley & Sons, Ltd.
Estimation of soil moisture using deep learning based on satellite data: a case study of South Korea

The Korea Meteorological Administration uses soil moisture (SM) observed by the Advanced Microwave Scanning Radiometer-2 (AMSR2) to monitor drought. However, it may not be appropriate for monitoring drought in South Korea due to significant underestimation of SM. In this study, we used a deep learning method that performs better than traditional statistical and physical models for reliable estimation of SM based on remotely sensed satellite data. For estimating SM, we carefully selected input variables that exhibit a feedback loop with SM. To build an effective deep learning model, we examined the influences of sampling criteria and input parameters as well as the accuracy of several deep neural networks. The selected model was cross-validated to determine its stability. The estimated SM using deep learning had a high correlation coefficient (R) of 0.89 and a low root mean square error (RMSE; 3.825%) and bias (−0.039%) compared to in-situ measurements. A time series analysis using dynamic time warping was conducted which showed that the estimated SM was almost similar to the in-situ SM. In order to investigate the improvement in SM estimation using our method, it was compared with the Global Land Data Assimilation System and AMSR2. Significant improvements in R and a reduction in error values by more than half were achieved using our method. The estimated SM has finer spatial resolution at 4 km, and it can be rapidly produced, which will be useful for drought monitoring over the Korean Peninsula in near-real-time.
Infinite systems of interacting chains with memory of variable length beyond the Dobrushin condition

We study conditions that allow infinite systems of interacting chains with memory of variable length to go beyond the usual Dobrushin condition. Then, we derive an analytical characterization of the invariant state based on Replica Mean Field limits. As a result we extend the Galves-L\"ocherbach model beyond the restrictive Dobrushin condition of the model.
Iterative Frequency-Domain Channel Estimation and Equalization for Single-Carrier Transmissions without Cyclic-Pre x

Compared to conventional time-domain equalization, frequency-domain equalization (FDE) presents a computationally efcient alternative for the reception of single carrier (SC) transmissions. In this paper, we consider iterative FDE (IFDE) with explicit frequency-domain channel estimation (FDCE) for non-cyclic-prexed SC systems. First, an improved IFDE algorithm is presented based on soft iterative interferencecancellation. Second, a new adaptive FDCE (AFDCE) algorithm based on per-tone Kalman ltering is proposed to track and predict the frequency-domain channel coefcients. The AFDCE algorithm employs across-tone noise reduction, exploits temporal correlation between successive blocks, and adaptively updates the auto-regressive model coefcients, bypassing the need for prior knowledge of channel statistics. Finally, block-overlapping is used to facilitate the joint operation of IFDE and AFDCE. Simulation results show that, compared to related IFDE and adaptive channel estimation schemes, the proposed schemes offer lower mean-square error (MSE) in channel prediction, lower bit error rate (BER) after decoding, and robustness to non-stationary channels.