Miracle-dz/UniFAR-FTUs huggingface dataset:
A prognostic model for tumor recurrence and progression after meningioma surgery: preselection for further molecular work-up

Purpose The selection of patients for further therapy after meningioma surgery remains a challenge. Progress has been made in this setting in selecting patients that are more likely to have an aggressive disease course by using molecular tests such as gene panel sequencing and DNA methylation profiling. The aim of this study was to create a preselection tool warranting further molecular work-up. Methods All patients undergoing surgery for resection or biopsy of a cranial meningioma from January 2013 until December 2018 at the University Hospital Zurich with available tumor histology were included. Various prospectively collected clinical, radiological, histological and immunohistochemical variables were analyzed and used to train a logistic regression model to predict tumor recurrence or progression. Regression coefficients were used to generate a scoring system grading every patient into low, intermediate, and high-risk group for tumor progression or recurrence. Results Out of a total of 13 variables preselected for this study, previous meningioma surgery, Simpson grade, progesterone receptor staining as well as presence of necrosis and patternless growth on histopathological analysis of 378 patients were included into the final model. Discrimination showed an AUC of 0.81 (95% CI 0.73 – 0.88), the model was well-calibrated. Recurrence-free survival was significantly decreased in patients in intermediate and high-risk score groups (p-value < 0.001). Conclusion The proposed prediction model showed good discrimination and calibration. This prediction model is based on easily obtainable information and can be used as an adjunct for patient selection for further molecular work-up in a tertiary hospital setting.
Instability in tropical Pacific sea-surface temperatures during the early Aptian

The Cretaceous has long been recognized as a time when greenhouse conditions were fueled by elevated atmospheric CO2 and accompanied by perturbations of the global carbon cycle described as oceanic anoxic events (OAEs). Yet, the magnitude and frequency of temperature change during this interval of warm and equable climate are poorly constrained. Here we present a ighresolution record of sea-surface temperatures (SSTs) reconstructed using the TEX86 paleothermometer for a sequence of early Aptian organic-rich sediments deposited during the first Cretaceous OAE (OAE1a) at Shatsky Rise in the tropical Pacific. SSTs range from ~30 to ~36 0C and include two prominent cooling episodes of ~4 0C. The cooler temperatures reflect significant temperature instability in the tropics likely triggered by changes in carbon cycling induced by enhanced burial of organic matter. SST instability recorded during the early Aptian in the Pacific is comparable to that reported for the late Albian–early Cenomanian in the Atlantic, suggesting that such climate perturbations may have recurred during the Cretaceous with concomitant consequences for biota and the marine environment.
Epistemic Inclusion as the Key to Benefiting from Cognitive Diversity in Science

ABSTRACT Throughout scientific history, there have been cases of mainstream science dismissing novel ideas of less prominent researchers. Nowadays, many researchers with different social and academic backgrounds, origins and gender identities work together on topics of crucial importance. Still, it is questionable whether the privileged groups consider the views of underprivileged colleagues with sufficient attention. To profit from the diversity of thoughts, the scientific community first has to be open to minority viewpoints and epistemically include them in mainstream research. Moreover, the idea of inclusive science poses stronger requirements than the paradigm of open science. We argue that the concept of integration of different opinions is insufficient because the process of integration assumes adjusting oneself to the majority view and fitting into the dominant paradigm while contributing only with smaller amendments. Epistemic inclusion, on the other hand, means dynamically changing the research paradigm during the interaction with diverse methods and hypotheses. The process of inclusion preserves marginalized views and increases epistemic justice.
Holocene slope dynamics in Sierra Nevada (south Spain). Sedimentological analysis of solifluction landforms and lake deposits

Abstract The activity of geomorphic processes in the current periglacial belt of Sierra Nevada during the Holocene has been strongly controlled by climate variability. We examined two sedimentary records showing several cycles with varying intensity of slope processes in the massif. Chronostratigraphic studies of solifluction landforms have revealed seven cycles of enhanced slope activity in Sierra Nevada during the last 7 ka. Lake sediments show eight periods with increased slope activity over the last 6 ka. Depending on temperature and moisture regime, erosion or conditions of slope stability prevailed. Cold and wet periods triggered slope processes and favoured deposition of coarse-grained sediments into the lakes, whereas warm phases were prone to soil development and fine-grained sedimentation in the lakes. The lake sediments also show evidence for an increasing aridity trend since the Holocene Optimum Warm Period in Sierra Nevada, which induced a shift of solifluction processes to higher elevations accompanying late-lying snow patches.
The meteorological control on the anthropogenic ion content of precipitation at three sites in the UK: The utility of lamb weather types

Daily observations of concentrations of non-marine sulphate, nitrate, ammonium, and hydrogen ion in precipitation at three sites in the UK (south-west England, eastern England, southern Scotland) have been used to attribute proportions of the total annual depositions of these ions to various Lamb Weather Types (LWTs). The LWT classification is a convenient description of the daily atmospheric circulation over the British Isles. In terms of affecting the annual character of total annual deposition of the ions, it is Cyclonic, Westerly, and Anticyclonic weather types that play the dominant roles. These roles vary from station to station. Other LWTs can also play important roles, but there is much site-to-site and year-to-year variation. The patterns of the relationships for each of the stations are explained in terms of the ‘average’ back-trajectories from each station for precipitation events associated with each of the major LWTs. It is the relative dispositions of these average trajectories with respect to the major pollutant source regions that allows the use of LWTs as simple tools in the interpretation of precipitation composition. There are indications that atmospheric circulation changes may play a part in the variations of precipitation composition over years to decades.
Mathematical Considerations in Energy Spectrum Recovery for Digital Energy Spectrometers

Energy spectra of particles allow people to observe underlying matter composition and properties in particle physics applications by depicting the probability density function of particle energy. As the most widely used method to estimate energy spectra, energy histograms discretely represent them with precision depending on adopted bin widths. Till recently, the range of bin widths for the nondistortion recovery of energy spectra is still indefinite, especially when digital spectrometers are involved. This can lead to the miss of potential discoveries in studies relying on spectral analysis. Here we propose a novel method that recovers energy spectra from histograms without distortion and the corresponding quantitative method of selecting bin widths with the bandwidths of energy spectra. To do so, we model histograms as equally spaced samples of energy spectra and measure their bandwidths with the frequency spectra of the histograms. By the sampling theorem, we choose bin widths quantitatively and recover energy spectra without distortion by interpolating histograms, showing that our method could be used in the accurate analysis of particle energy data and reliable evaluation of energy spectrometers. For digital spectrometers, we also show that bin widths should be chosen as multiples of energy quantization errors (EQEs) caused by the limited analog-to-digit resolution of digital spectrometers to avoid periodic artifacts in energy histograms.
A new brushless DC motor driving resonant pole inverter optimized for batteries

The brushless DC motor (BLDC) has gained significant popularity in industrial settings due to its notable attributes such as low inertia, rapid response, high power density, exceptional dependability, and reputation for being conservation-free. Typically, these are equipped by a tight-switching PWM inverter, which results in significant switching losses. Consequently, the dissipation of switching loss necessitates the use of sizable heat sinks, resulting in an increase in both the physical dimensions and mass of the drive system. Numerous researchers have developed soft switching inverters with the aim of minimizing switching losses. The utilization of a soft-switching circuit may give rise to additional issues, including heightened voltage stress, incomplete pulse width modulation control, and intricate control scheme or implementation. The present study introduces a basic soft switch inverter design that is suitable for employment in BLDC drive systems powered by batteries. The inverter exhibits low loss for power switching and voltage stress is less on the main switches, while also featuring a straightforward control scheme that is easily implementable. Upon conducting analytical analysis, simulation results were presented by evaluating the theoretical analysis.
Polyarginine Cell-Penetrating Peptides Bind and Inhibit SERCA2

Cell-penetrating peptides (CPPs) are short peptide sequences that have the ability to cross the cell membrane and deliver cargo. Although it is critical that CPPs accomplish this task with minimal off-target effects, such actions have in many cases not been robustly screened. We presently investigated whether the commonly used CPPs TAT and the polyarginines Arg9 and Arg11 exert off-target effects on cellular Ca2+ homeostasis. In experiments employing myocytes and homogenates from the cardiac left ventricle or soleus muscle, we observed marked inhibition of Ca2+ recycling into the sarcoplasmic reticulum (SR) following incubation with polyarginine CPPs. In both tissues, the rate of SR Ca2+ leak remained unchanged, indicating that protracted Ca2+ removal from the cytosol stemmed from inhibition of the SR Ca2+ ATPase 2 (SERCA2). No such inhibition occurred following treatment with TAT, or in preparations from the SERCA1-expressing extensor digitorum longus muscle. Experiments in HEK cells overexpressing individual SERCA isoforms confirmed that polyarginine incubation specifically inhibited the activity of SERCA2a and 2b, but not SERCA1 or 3. The attenuation of SERCA2 activity was not dependent on the presence of phospholamban, and ELISA-based analyses rather revealed direct interaction between the polyarginines and the actuator domain of the protein. Surface plasmon resonance experiments confirmed strong binding within this region of SERCA2, and slow dissociation between the two species. Based on these observations, we urge caution when employing polyarginine CPPs. Indeed, as SERCA2 is expressed in diverse cell types, the wide-ranging consequences of SERCA2 binding and inhibition should be anticipated in both experimental and therapeutic settings.
Metal-Promoted Higher-Order Assembly of Disulfide-Stapled Helical Barrels

Peptide-based helical barrels are a noteworthy building block for hierarchical assembly, with a hydrophobic cavity that can serve as a host for cargo. In this study, disulfide-stapled helical barrels were synthesized containing ligands for metal ions on the hydrophilic face of each amphiphilic peptide helix. The major product of the disulfide-stapling reaction was found to be composed of five amphiphilic peptides, thereby going from a 16-amino-acid peptide to a stapled 80-residue protein in one step. The structure of this pentamer, 5HB1, was optimized in silico, indicating a significant hydrophobic cavity of ~6 Å within a helical barrel. Metal-ion-promoted assembly of the helical barrel building blocks generated higher order assemblies with a three-dimensional (3D) matrix morphology. The matrix was decorated with hydrophobic dyes and His-tagged proteins both before and after assembly, taking advantage of the hydrophobic pocket within the helical barrels and coordination sites within the metal ion-peptide framework. As such, this peptide-based biomaterial has potential for a number of biotechnology applications, including supplying small molecule and protein growth factors during cell and tissue growth within the matrix.
EVALUATION OF COMMUNITY PARTICIPATION FOR THE DEVELOPMENT OF CULTURE-BASED FISHERIES IN VILLAGE RESERVOIRS OF SRI LANKA

In this paper, an attempt is made to identify the socioeconomic characteristics of a community that influence the development and management of culture-based fisheries in village reservoirs of Sri Lanka. Socioeconomic data were collected from 46 agricultural farming communities associated with 47 village reservoirs in Sri Lanka. Principal component analysis indicated that scores of the first principal component were positively influenced by socioeconomic characteristics that are favorable for making collective decisions. These included leadership of the officers, age of the group, percentage of active members of the group, percentage of kinship of the group, percentage of common interest of the group, and percentage of participation of the group. The size of the group had a negative effect on the first principal component. The principal component scores of communities were positively related to willingness to pay (P < 0.001). The communities with socioeconomic characteristics favoring collective decision making were in favor of culture-based fisheries. Homogeneity of group characteristics facilitated successful development of culture-based fisheries.
Network Resource Allocation for Industry 4.0 With Delay and Safety Constraints

In this paper, we model a futuristic factory floor equipped with Automated Guided Vehicles (AGVs), cameras, and a Virtual Reality (VR) surveillance system; and connected to a 5G network for communication purposes. Motion planning of AGVs and VR applications is offloaded to an edge server for computational flexibility and reduced hardware on the factory floor. Decisions on the edge server are made using the video feed provided by the cameras in a controlled manner. Our objectives are to ensure factory floor safety and provide smooth VR experience in the surveillance room. Providing proper and timely allocation of network resources is of utmost importance to maintain the end-to-end delay necessary to achieve these objectives. We provide a statistical analysis to estimate the bandwidth required by a factory to satisfy the delay requirements 99.999 percent of the time. We formulate a nonconvex integer nonlinear problem aiming to minimize the safety and delay violations. To solve it, we propose a real-time network resource allocation algorithm that has linear time complexity in terms of the number of components connected to the wireless network. Our algorithm significantly outperforms existing solvers (genetic algorithm, surrogate optimizer) and meets the objectives using less bandwidth compared to existing methods.
A coupled model study of the Last Glacial Maximum: Was part of the North Atlantic relatively warm?

A coupled ocean‐atmosphere general circulation model is used to simulate the climates of today and the last glacial maximum (LGM). The model, which does not require artificial flux adjustments, produces a pattern of cooling at the LGM that is broadly consistent with the findings from simpler models and palaeoclimatic data. However, changes to the ocean circulation produce anomalously warm LGM surface conditions over parts of the North Atlantic, seemingly at odds with palaeoceanographic data. The thermohaline circulation is intensified for several centuries, as is the northward heat transport in the Atlantic equatorward of 55°N, but this may be a transient result. Mechanisms that lead to this response are discussed.
Space weathering on airless bodies: Resolving a mystery with lunar samples

Abstract— Using new techniques to examine the products of space weathering of lunar soils, we demonstrate that nanophase reduced iron (npFe0) is produced on the surface of grains by a combination of vapor deposition and irradiation effects. The optical properties of soils (both measured and modeled) are shown to be highly dependent on the cumulative amount of npFe0, which varies with different starting materials and the energetics of different parts of the solar system. The measured properties of intermediate albedo asteroids, the abundant S‐type asteroids in particular, are shown to directly mimic the effects predicted for small amounts of npFe0 on grains of an ordinary chondrite regolith. This measurement and characterization of space weathering products seems to remove a final obstacle hindering a link between the abundant ordinary chondrite meteorites and common asteroids.
Behavior of Niobium, Tantalum and other high field strength elements in adakites and related lavas from The Philippines

Abstract Pliocene–Quaternary adakites and spatially and temporally associated niobium‐enriched basalts (the latter thought to be derived by melting of slab melt‐metasomatized mantle) from the Philippine island arcs have been selected for analysis of high field strength elements (HFSE). All these samples have nearly constant and chondritic Zr/Hf ratio (36.5) and slightly infrachondritic Nb/Ta ratio (14.7). We interpret adakitic magmas to be derived from the partial melting at approximately 900°C of subducted mid‐ocean ridge basalts (MORB) crust, with rutile and/or ilmenite as residual minerals. Melting calculations show that, under these conditions, slab melts should have suprachondritic Nb/Ta ratios. The obvious discrepancy with our data is attributed to insufficient knowledge of rutile‐melt partition coefficients for HFSE. Consequently, abnormal Nb/Ta or Zr/Hf ratios cannot be considered as potential markers of slab melting processes in island arcs.
Intercomparison of Deep Learning Architectures for the Prediction of Precipitation Fields With a Focus on Extremes

In recent years, the use of deep learning methods has rapidly increased in many research fields. Similarly, they have become a powerful tool within the climate scientific community. Deep learning methods have been successfully applied for different tasks, such as the identification of atmospheric patterns, weather extreme classification, or weather forecasting. However, due to the inherent complexity of atmospheric processes, the ability of deep learning models to simulate natural processes, particularly in the case of weather extremes, is still challenging. Therefore, a thorough evaluation of their performance and robustness in predicting precipitation fields is still needed, especially for extreme precipitation events, which can have devastating consequences in terms of infrastructure damage, economic losses, and even loss of life. In this study, we present a comprehensive evaluation of a set of deep learning architectures to simulate precipitation, including heavy precipitation events (>95th percentile) and extreme events (>99th percentile) over the European domain. Among the architectures analyzed here, the U‐Net network was found to be superior and outperformed the other networks in simulating precipitation events. In particular, we found that a simplified version of the original U‐Net with two encoder‐decoder levels generally achieved similar skill scores than deeper versions for predicting precipitation extremes, while significantly reducing the overall complexity and computing resources. We further assess how the model predicts through the attribution heatmaps from a layer‐wise relevance propagation explainability method.
Carter, C.S. and Chorley, R.J. 1961: Early slope development in an expanding stream system. Geographical Magazine 97, 117-30

The transformation of American geomorphology after the second world war was a real phenomenon, albeit one in which some of its revolutionary aspects were probably overstated at the time. The foundations of the changed approach can be traced to three particularly significant articles, of which R.E. Horton’s posthumous (1945) treatise is, of course, the first and most important in opening up the whole sweep of drainage-basin evolution to quantitative description and analysis. The significance of A.N. Strahler’s 1950 work on valley-side slope and L.B. Leopold and T. Maddock’s 1953 introduction of hydraulic geometery concepts, while of less philosophical weight, nevertheless signalled
A review of remote sensing based productivity models and their suitability for studying oil palm productivity in tropical regions

Oil palm (Elaeis guineensis Jacq.) cultivation has been expanding and has become one of the fastest developing agricultural crops in tropical regions. Therefore, it is critical to understand the carbon balance and dynamics within oil palm estates to determine its role in the global carbon cycle. Estimating oil palm productivity on a large scale is most feasible with remote sensing based models. Thus, the objective of this paper is to review existing remote sensing based models (i.e. CASA, GLO-PEM, VPM, C-Fix, TURC, EC-LUE, VI, TG, 3-PGS and MOD17) that use light use efficiency (LUE) logic, and subsequently to evaluate the suitability of these models for estimating oil palm productivity. This paper also highlights the limitation of current remote sensing based models for estimating oil palm productivity. From the review of existing literature, it is clear that the existing remote sensing based models need to be modified in terms of meteorological inputs, maximum LUE and environmental constraints in order to improve the estimation of oil palm productivity.
Review and evaluation of recent advancements in image dehazing techniques for vision improvement and visualization

Abstract. Vision gets obscured in adverse weather conditions, such as heavy downpours, dense fog, haze, snowfall, etc., which increase the number of road accidents yearly. Modern methodologies are being developed at various academics and laboratories to enhance visibility in such adverse weather with the help of technologies. We review different dehazing techniques in many applications, such as outdoor surveillance, underwater navigation, intelligent transportation systems, object detection, etc. Dehazing is achieved in four primary steps: the capture of hazy images, estimation of atmospheric light with transmission map, image enhancement, and restoration. These four dehazing procedures allow for a step-by-step method for resolving the complicated haze removal issue. Furthermore, it also explores the limitations of existing deep learning-based methods with the available datasets and the challenges of the algorithms for enhancing visibility in adverse weather. Reviewed techniques reveal gaps in the case of remote sensing, satellite, and telescopic imaging. In the experimental analysis of various image dehazing approaches, one can learn the effectiveness of each phase in the image dehazing process and create more effective dehazing techniques.