julilili42/papers huggingface dataset:
Variability in n -caprylate and n -caproate producing microbiomes in reactors with in-line product extraction
2024-07-11

ABSTRACT Medium-chain carboxylates (MCCs) are used in various industrial applications. These chemicals are typically extracted from palm oil, which is deemed not sustainable. Recent research has focused on microbial chain elongation using reactors to produce MCCs, such as n -caproate (C6) and n -caprylate (C8), from organic substrates such as wastes. Even though the production of n -caproate is relatively well-characterized, bacteria and metabolic pathways that are responsible for n -caprylate production are not. Here, three 5 L reactors with continuous membrane-based liquid-liquid extraction (i.e., pertraction) were fed ethanol and acetate and operated for an operating period of 234 days with different operating conditions. Metagenomic and metaproteomic analyses were employed. n -Caprylate production rates and reactor microbiomes differed between reactors even when operated similarly due to differences in H 2 and O 2 between the reactors. The complete reverse β-oxidation (RBOX) pathway was present and expressed by several bacterial species in the Clostridia class. Several Oscillibacter spp., including Oscillibacter valericigenes , were positively correlated with n -caprylate production rates, while Clostridium kluyveri was positively correlated with n -caproate production. Pseudoclavibacter caeni , which is a strictly aerobic bacterium, was abundant across all the operating periods, regardless of n -caprylate production rates. This study provides insight into microbiota that are associated with n -caprylate production in open-culture reactors and provides ideas for further work. IMPORTANCE Microbial chain elongation pathways in open-culture biotechnology systems can be utilized to convert organic waste and industrial side streams into valuable industrial chemicals. Here, we investigated the microbiota and metabolic pathways that produce medium-chain carboxylates (MCCs), including n -caproate (C6) and n -caprylate (C8), in reactors with in-line product extraction. Although the reactors in this study were operated similarly, different microbial communities dominated and were responsible for chain elongation. We found that different microbiota were responsible for n -caproate or n -caprylate production, and this can inform engineers on how to operate the systems better. We also observed which changes in operating conditions steered the production toward and away from n -caprylate, but more work is necessary to ascertain a mechanistic understanding that could be predictive. This study provides pertinent research questions for future work.
Embryonic development and cranial ossification of the Japanese Aodaishō, Elaphe climacophora (Serpentes: Colubridae): with special reference to the prootic bone and auditory evolution in snakes
2024-07-11

Abstract Snakes show remarkably deviated “body plan” from other squamate reptiles. In addition to limb loss, they have accomplished enormous anatomical specialization of the skull associated with the pit organs and the reduction of the tympanic membranes and auditory canals in the outer ears. Despite being the most diverse group of snakes, our knowledge of the embryonic staging for organogenesis and cranial ossification has been minimal for Colubridae. Therefore, in the present observation, we provide the first embryonic description of the Japanese rat snake Elaphe climacophora . We based our study on the Standard Event System (SES) for external anatomical characters and on a description of the cranial ossification during post‐ovipositional development. We further estimated the relative ossification timing of each cranial bony element and compared it with that of selected other snakes, lizards, turtles, and crocodilians. The present study shows that the relative ossification timing of the palatine and pterygoid bones is relatively early in squamates when compared to other reptiles, implying the developmental integration as the palate–pterygoid complex in this clade and functional demands for the unique feeding adaptation to swallow large prey with the help of their large palatine and pterygoid teeth. Furthermore, unlike in species with pit organs, the prootic bone of Ela. climacophora is expanded to provide articulation with the supratemporal, thereby contributing to the hearing system by detecting substrate vibration. We also demonstrate that the relative timing of the prootic ossification is significantly accelerated in colubrids compared to snakes with pit organs. Our finding suggests that the temporal changes of the prootic ossification underpin the evolution of the perception of the ground‐bourne sound signals among snakes.
In-situ observations of charged Saharan dust from an uncrewed aircraft system
2024-07-11

Mineral dust from the Sahara desert can travel long distances at high altitudes, perturbing the energy budget of the atmosphere. Charging of dust has been observed to occur near the surface through triboelectric charging during dust lofting, potentially affecting particle coagulation, fall speeds, and the lofting process itself. Apart from near-surface studies, measurements at elevated dust layers, where charge may play a role in particle long-range transport, are rare. This study presents new observations from an uncrewed aircraft system (UAS) of type MASC-3, through an elevated Saharan dust layer over Cyprus on 6 April 2022. The dust layer ranged from 1500 to 2500 meters above sea level (a.s.l), with maximum particle number concentrations (PNC) of 80–100 cm−3, primarily consisting of particles up to 2.5 μm in size. Measurements showed elevated charge within the dust layer, with magnitude proportional to PNC. It was concluded that there was a small influence of aircraft charge on the measurements, which was handled by developing a PNC-based correction factor. Corrected charge within the dust layer ranged from 0.2 to 3 pC m−3, with most of the charge at the upper and lower dust layer boundaries. The magnitude and location of the charge was consistent with predictions of ion-particle attachment. This suggests that most of the measured charge did not originate from the lofting process, but dust particles were charged on site through ion-particle attachment processes
2D Gaussian Splatting for Geometrically Accurate Radiance Fields
2024-07-12

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the multi-view inconsistent nature of 3D Gaussians. We present 2D Gaussian Splatting (2DGS), a novel approach to model and reconstruct geometrically accurate radiance fields from multi-view images. Our key idea is to collapse the 3D volume into a set of 2D oriented planar Gaussian disks. Unlike 3D Gaussians, 2D Gaussians provide view-consistent geometry while modeling surfaces intrinsically. To accurately recover thin surfaces and achieve stable optimization, we introduce a perspective-correct 2D splatting process utilizing ray-splat intersection and rasterization. Additionally, we incorporate depth distortion and normal consistency terms to further enhance the quality of the reconstructions. We demonstrate that our differentiable renderer allows for noise-free and detailed geometry reconstruction while maintaining competitive appearance quality, fast training speed, and real-time rendering.
Assessment of Land Suitability Potential Using Ensemble Approaches of Advanced Multi-Criteria Decision Models and Machine Learning for Wheat Cultivation
2024-07-12

Land suitability assessment, as an important process in modern agriculture, involves the evaluation of numerous aspects such as soil properties, climate, relief, hydrology and socio-economic aspects. The aim of this study was to evaluate the suitability of soils for wheat cultivation in the Gavshan region, Iran, as the country is facing the task of becoming self-sufficient in wheat. Various methods were used to evaluate the land, such as multi-criteria decision-making (MCDM), which is proving to be important for land use planning. MCDM and machine learning (ML) are useful for decision-making processes because they use complicated spatial data and methods that are widely available. Using a geomorphological map, seventy soil profiles were selected and described, and ten soil properties and wheat yields were determined. Three MCDM approaches, including the technique of preference ordering by similarity to the ideal solution (TOPSIS), gray relational analysis (GRA), and simple additive weighting (SAW), were used and evaluated. The criteria weights were extracted using Shannon’s entropy method. Random forest (RF) model and auxiliary variables (remote sensing data, terrain data, and geomorphological maps) were used to represent the land suitability values. Spatial autocorrelation analysis as a statistical method was applied to analyze the spatial variability of the spatial data. Slope, CEC (cation exchange capacity), and OC (organic carbon) were the most important factors for wheat cultivation. The spatial autocorrelation between the key criteria (slope, CEC, and OC) and wheat yield confirmed these results. These results also showed a significant correlation between the land suitability values of TOPSIS, GRA, and SAW and wheat yield (0.74, 0.72, and 0.57, respectively). The spatial distribution of land suitability values showed that the areas classified as good according to TOPSIS and GRA were larger than those classified as moderate and weak according to the SAW approach. These results were also confirmed by the autocorrelation of the MCDM techniques with wheat yield. In addition, the RF model showed its effectiveness in processing complex spatial data and improved the accuracy of land suitability assessment. In this study, by integrating advanced MCDM techniques and ML, an applicable land evaluation approach for wheat cultivation was proposed, which can improve the accuracy of land suitability and be useful for considering sustainability principles in land management.
Dose prescription for stereotactic body radiotherapy: general and organ-specific consensus statement from the DEGRO/DGMP Working Group Stereotactic Radiotherapy and Radiosurgery
2024-07-12

Abstract Purpose and objective To develop expert consensus statements on multiparametric dose prescriptions for stereotactic body radiotherapy (SBRT) aligning with ICRU report 91. These statements serve as a foundational step towards harmonizing current SBRT practices and refining dose prescription and documentation requirements for clinical trial designs. Materials and methods Based on the results of a literature review by the working group, a two-tier Delphi consensus process was conducted among 24 physicians and physics experts from three European countries. The degree of consensus was predefined for overarching (OA) and organ-specific (OS) statements (≥ 80%, 60–79%, &lt; 60% for high, intermediate, and poor consensus, respectively). Post-first round statements were refined in a live discussion for the second round of the Delphi process. Results Experts consented on a total of 14 OA and 17 OS statements regarding SBRT of primary and secondary lung, liver, pancreatic, adrenal, and kidney tumors regarding dose prescription, target coverage, and organ at risk dose limitations. Degree of consent was ≥ 80% in 79% and 41% of OA and OS statements, respectively, with higher consensus for lung compared to the upper abdomen. In round 2, the degree of consent was ≥ 80 to 100% for OA and 88% in OS statements. No consensus was reached for dose escalation to liver metastases after chemotherapy (47%) or single-fraction SBRT for kidney primaries (13%). In round 2, no statement had 60–79% consensus. Conclusion In 29 of 31 statements a high consensus was achieved after a two-tier Delphi process and one statement (kidney) was clearly refused. The Delphi process was able to achieve a high degree of consensus for SBRT dose prescription. In summary, clear recommendations for both OA and OS could be defined. This contributes significantly to harmonization of SBRT practice and facilitates dose prescription and reporting in clinical trials investigating SBRT.
The pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics
2024-07-12

Abstract Using distributional semantics, we show that English nominal pluralization exhibits semantic clusters. For instance, the change in semantic space from singulars to plurals differs depending on whether a word denotes, e.g., a fruit, or an animal. Languages with extensive noun classes such as Swahili and Kiowa distinguish between these kind of words in their morphology. In English, even though not marked morphologically, plural semantics actually also varies by semantic class. A semantically informed method, CosClassAvg, is introduced that is compared to two other methods, one implementing a fixed shift from singular to plural, and one creating plural vectors from singular vectors using a linear mapping (FRACSS). Compared to FRACSS, CosClassAvg predicted plural vectors that were more similar to the corpus-extracted plural vectors in terms of vector length, but somewhat less similar in terms of orientation. Both FRACSS and CosClassAvg outperform the method using a fixed shift vector to create plural vectors, which does not do justice to the intricacies of English plural semantics. A computational modeling study revealed that the observed difference between the plural semantics generated by these three methods carries over to how well a computational model of the listener can understand previously unencountered plural forms. Among all methods, CosClassAvg provides a good balance for the trade-off between productivity (being able to understand novel plural forms) and faithfulness to corpus-extracted plural vectors (i.e., understanding the particulars of the meaning of a given plural form).
On Lieb–Robinson Bounds for a Class of Continuum Fermions
2024-07-12

Abstract We consider the quantum dynamics of a many-fermion system in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow> <mml:mi>R</mml:mi> </mml:mrow> <mml:mi>d</mml:mi> </mml:msup> </mml:math> with an ultraviolet regularized pair interaction as previously studied in Gebert et al. (Ann Henri Poincaré 21(11):3609–3637, 2020). We provide a Lieb–Robinson bound under substantially relaxed assumptions on the potentials. We also improve the associated one-body Lieb–Robinson bound on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>L</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> -overlaps to an almost ballistic one (i.e., an almost linear light cone) under the same relaxed assumptions. Applications include the existence of the infinite-volume dynamics and clustering of ground states in the presence of a spectral gap. We also develop a fermionic continuum notion of conditional expectation and use it to approximate time-evolved fermionic observables by local ones, which opens the door to other applications of the Lieb–Robinson bounds.
“I had to watch the commercial. That was annoying!” Audio-observing active parental mediation of advertising
2024-07-12

Active mediation is considered the gold standard mediation style for parents seeking to help their children cope with potentially harmful media content. However, little is known about what actually happens during active mediation episodes. In this study, we employ an interactive task on advertising formats to audio-observe parent – child interactions during active mediation episodes (n = 23 dyads). The study contributes to the body of knowledge by exploring the communicative repertoires that parents and children draw on during active mediation episodes. We show how parents and children, in exercising their agency, respond to one another by adopting the parent positions of educator, role model, investigator, and bridge builder, and the child positions of novice, informant, and cognoscente. Most of the time, the episodes follow a clear pattern according to which parents are in control of the mediation episode and children mainly react to their parents' initiatives. However, in instances of reverse mediation, this default hierarchy is turned upside down. Here, children explain media logics and educate their parents about advertising. The structure of active mediation episodes mapped in this study will allow researchers to develop a deeper understanding of active mediation as a complex and heterogenous phenomenon.
The Dynamic Sensorium competition for predicting large-scale mouse visual cortex activity from videos.
2024-07-12

Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding of this system by allowing computational neuroscientists to create predictive models and bridge biological and machine vision. During the Sensorium 2022 competition, we introduced benchmarks for vision models with static input (i.e. images). However, animals operate and excel in dynamic environments, making it crucial to study and understand how the brain functions under these conditions. Moreover, many biological theories, such as predictive coding, suggest that previous input is crucial for current input processing. Currently, there is no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we propose the Sensorium 2023 Benchmark Competition with dynamic input (https://www.sensorium-competition.net/). This competition includes the collection of a new large-scale dataset from the primary visual cortex of ten mice, containing responses from over 78,000 neurons to over 2 hours of dynamic stimuli per neuron. Participants in the main benchmark track will compete to identify the best predictive models of neuronal responses for dynamic input (i.e. video). We will also host a bonus track in which submission performance will be evaluated on out-of-domain input, using withheld neuronal responses to dynamic input stimuli whose statistics differ from the training set. Both tracks will offer behavioral data along with video stimuli. As before, we will provide code, tutorials, and strong pre-trained baseline models to encourage participation. We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and beyond.
Sensors for Antibiotics Susceptibility Testing—Recent Advances
2024-07-12

Abstract The age of antibiotics, which began with the discovery of penicillin in 1929, marks an important period in medical history, as deadly bacterial infections seemed to be a thing of the past. However, the tide turned as more and more resistance to all existing antibiotics emerged, leading to the still ongoing era of antibiotic resistance. To counter this development and slow it down, it is important to administer the appropriate, effective antibiotics, which requires the clinical transition from empirical to targeted antibiotic therapy. Antimicrobial susceptibility testing (AST) is a key pillar in the implementation of targeted antibiotic therapy. This review provides an overview of the different phenotypic and genotypic AST methods with their advantages and disadvantages, focusing on the turnaround time from patient to result, including preculture. In addition, an outlook on their future potential is given, also considering the impact of artificial intelligence on this field.
A robust second-order low-rank BUG integrator based on the midpoint rule
2024-07-13

Abstract Dynamical low-rank approximation has become a valuable tool to perform an on-the-fly model order reduction for prohibitively large matrix differential equations. A core ingredient is the construction of integrators that are robust to the presence of small singular values and the resulting large time derivatives of the orthogonal factors in the low-rank matrix representation. Recently, the robust basis-update &amp; Galerkin (BUG) class of integrators has been introduced. These methods require no steps that evolve the solution backward in time, often have favourable structure-preserving properties, and allow for parallel time-updates of the low-rank factors. The BUG framework is flexible enough to allow for adaptations to these and further requirements. However, the BUG methods presented so far have only first-order robust error bounds. This work proposes a second-order BUG integrator for dynamical low-rank approximation based on the midpoint quadrature rule. The integrator first performs a half-step with a first-order BUG integrator, followed by a Galerkin update with a suitably augmented basis. We prove a robust second-order error bound which in addition shows an improved dependence on the normal component of the vector field. These rigorous results are illustrated and complemented by a number of numerical experiments.
Economic impacts of an urban gully are driven by land degradation
2024-07-13

Abstract This study carries out the first evaluation of the impacts of ravines and gullies in urban areas in Brazil considering environmental damage, such as costs related to land restoration and erosion control, infrastructure destruction, economic losses and income losses related to property and urban land taxes. In this study, the city of Bauru, Brazil, has been selected as study site, where three areas were chosen due to the large impact that ravines and gullies have caused over the past two decades. Our analysis indicates that the total damage exceeds US 13.3 million. Furthermore, according to our analysis, urban areas affected by ravines and gullies represent problems similar to brownfields. The assessment of the impacts and challenges associated with urban ravines and gullies can help promote accountability by those responsible for their initiation and may contribute to decreasing the development of new eroded areas.