bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contrastive Deep Encoding Enables Uncertainty-aware Machine-learning-assisted Histopathology
Authors: Wadduwage Dushan , Sivaroopan Nirhoshan , Jayanga Chamuditha , Ekanayake Chalani , Watawana Hasindri , Pradeepkumar Jathurshan , Anandakumar Mithunjha , Rodrigo Ranga , Edussooriya Chamira 
Published: October 2023

Abstract
Deep neural network models can learn clinically relevant features from millions of histopathology images. However generating high-quality annotations to train such models for each hospital, each cancer type, and each diagnostic task is prohibitively laborious. On the other hand, terabytes of training data –while lacking reliable annotations– are readily available in the public domain in some cases. In this work, we explore how these large datasets can be consciously utilized to pre-train deep networks to encode informative representations. We then fine-tune our pre-trained models on a fraction of annotated training data to perform specific downstream tasks. We show that our approach can reach the current state-of-the-art (SOTA) for patch-level classification with only 1-10% randomly selected annotations compared to other SOTA approaches. Moreover, we propose an uncertainty-aware loss function, to quantify the model confidence during inference. Quantified uncertainty helps experts select the best instances to label for further training. Our uncertainty-aware labeling reaches the SOTA with significantly fewer annotations compared to random labeling. Last, we demonstrate how our pre-trained encoders can surpass current SOTA for whole-slide image classification with weak supervision. Our work lays the foundation for data and task-agnostic pre-trained deep networks with quantified uncertainty.
Double-cropped Corn Ethanol in Brazil: An existing food-energy system that contributes to multiple Sustainable Development Goals
Authors: Gurgel Angelo , Seabra Joaquim Eugênio , Arantes Sofia , Moreira Marcelo , Lynd Lee , Galindo Rosana 
Published: October 2023

Abstract

We evaluate the fast-expanding food-energy system of double-cropped corn ethanol in the Brazilian Center-West region using a novel combination of environmental and socio-economic models. Based on this comprehensive approach, we find that this system provides renewable and affordable energy (5 billion liters of ethanol, 600 MWh of electrical power) and feed (4 thousand tonnes of distillers dried grains), reduces greenhouse gas emissions (9.3 million to 13.2 million tons of CO2e), saves land (160 thousand hectares), boosts regional income growth and consumption (0.05% to 0.6% increase in household income), improves food security, and benefits ecosystems and human health. These impacts are amplified when carbon capture and storage is coupled into the process. Key features responsible for this outcome include the integration of feedstock supply into existing practices and the use of sustainable biomass to provide process energy. Future analysis should consider region-specific factors when incorporating these features into other bioenergy systems.
The Role of Neural Plasticity in Vocal Skill Acquisition and Learning Among Novice Singers
Authors: Hongkun Zhu 
Published: October 2023

Abstract
This study presents a comprehensive framework for the analysis of neuroimaging data to uncover patterns of neural activation and connectivity changes before and after training among novice singers. The proposed framework encompasses various stages, including Data Preparation, Descriptive Analysis, Skill Improvement Analysis, Neural Changes Analysis, Correlation Analysis, Group Comparison, and Multipolynomial Lasso Regression Analysis. Four fundamental metrics, namely Percent Signal Change (PSC), Functional Connectivity (FC), Amplitude of Low-Frequency Fluctuations (ALFF), and Graph Theory Metrics, are employed within this framework to elucidate neuroplasticity alterations. PSC quantifies relative shifts in neural activation, FC assesses synchronized activity between brain regions, ALFF gauges regional spontaneous neural activity, and Graph Theory Metrics, including Degree Centrality, unveil the centrality and connectivity of specific brain regions within networks. By applying this comprehensive framework and the specified metrics and equations, this research endeavors to provide a robust understanding of the neural mechanisms underpinning vocal skill acquisition and their correlation with subjective skill improvement. This study offers valuable insights into the plasticity of the human brain in response to vocal training among novice singers.
Biochar and Farm Yard Manure Synergy: Enhancing Soil Health and Mitigating Climate Change Impacts in Cotton Production
Authors: Hussain Iqbal , Saleem Shahid , Ullah Hafeez , Nasir Muhammad , Iqbal Muhammad Umar , Sabir Saba , Nisar Madiha , Khaliq Abdul , Niaz Yasir , Ghafoor Muhammad Atif , Sheer Abbas , Fatima Sidra , Masood Syed Ahtisham , Rauf Hafiz Abdul , Hussain Fida 
Published: October 2023

Abstract
Soil health plays a pivotal role in ensuring sustainable agriculture, particularly in the face of climate change challenges. This field study investigated the potential synergistic effects of biochar and farm yard manure (FYM) applications on soil properties, nutrient availability, cotton growth, and yield in cotton. Our findings highlight the promising impact of biochar and FYM, each applied at a rate of 5 t ha-1, on various aspects of soil and crop performance. Results indicated the substantial reduction in soil temperature, especially in the biochar + FYM treatment (27.2°C) compared to control treatment (37°C). This reduction in soil temperature created a favorable microclimate for cotton plants, mitigated heat stress and fostered healthier growth. Likewise, biochar + FYM combination showed a minor decrease in soil pH (pH 7.7) compared to control treatment (pH 8.1). Furthermore, the application of biochar + FYM significantly increased soil organic carbon (0.89%) and organic matter content (0.97%) as compared to sole application of biochar or FYM. Additionally, macro and micronutrient availability, including nitrogen (N), phosphorus (P), potassium (K), copper (Cu), manganese (Mn), zinc (Zn), and iron (Fe), substantially increased after the application of these amendments, with the biochar + FYM treatment exhibiting the highest values. The positive impact of these amendments extended to cotton plant growth, with increased plant height (175 cm), a greater number of bolls per plant (43), and heavier open boll weight (3.18 g) observed in the biochar + FYM treatment. Moreover, improvements in ginning out turn (GOT), staple length, and fiber uniformity were notable outcomes of biochar and FYM applications, particularly in combination. Fiber fineness and strength remained consistent. In addition to their soil and crop benefits, the application of biochar and FYM led to reduced irrigation requirements and enhanced crop water use efficiency (WUE), promoting more sustainable water management practices in cotton cultivation. This research highlights the potential synergy between biochar and FYM as a promising approach to enhance soil health and mitigate the impacts of climate change in cotton production.
Orchestrated excitatory and inhibitory plasticity produces stable dynamics in heterogeneous neuromorphic computing systems
Authors: Maryada Maryada , Soldado-Magraner Saray , Sorbaro Martino , Laje Rodrigo , Buonomano Dean , Indiveri Giacomo 
Published: October 2023

Abstract
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition.
Neuromorphic electronic circuits that use the physics of silicon to emulate neuronal dynamics represent a promising approach for implementing the brain's computational primitives, including self-sustained neural activity.
However, achieving the same robustness of biological networks in neuromorphic computing systems remains a challenge, due to the high degree of heterogeneity and variability of their analog components.
Inspired by the strategies used by real cortical networks, we apply a biologically-plausible cross-homeostatic learning rule to balance excitation and inhibition in neuromorphic implementations of spiking neural networks.
We demonstrate how this learning rule allows the neuromorphic system to overcome device mismatch and to autonomously tune the spiking network to produce robust, self-sustained attractor dynamics in an inhibition-stabilized regime.
We also show that this rule can implement a stable working memory, and that the electronic circuits can reproduce biologically relevant emergent neural dynamics, including the so-called ``paradoxical effect''.
In addition to validating neuroscience models on a substrate that shares many similar properties and limitations with biological systems, this work enables the construction of ultra-low power, mixed-signal neuromorphic technologies that can be automatically configured to compute reliably, despite the large on-chip and chip-to-chip variability of their analog components.
Study on material removal mechanism and surface formation characteristics of reaction-bonded silicon carbide by electrical discharge grinding technology
Authors: Wu Mingtao , Deng Shibo , Lei Dajiang 
Published: October 2023

Abstract
Electrical discharge grinding technology (EDGT) is an efficient and high precision method for machining RB-SiC ceramic materials. In this paper, the mechanism of material removal in EDGT is deeply studied, and the formation characteristics of surface topography under different material removal methods affected by grinding depth are analyzed. A three-dimensional heat conduction analysis model in the process of single pulse discharge was established, and the temperature field distribution in RB-SiC ceramic material under different discharge energy was obtained by numerical calculation. It is found that the simulated crater radius and depth increase with the increase of the discharge time, and the material removal amount gradually increases, but the growth rate gradually decreases. In order to give full play to the advantages of EDGT, the discharge energy and grinding depth were optimized according to the material removal mechanism. Finally, RB-SiC ceramic machining experiments were carried out using the optimized machining parameters, and a smooth surface with few discharge craters was obtained. It is found that the grinding scratches on the material surface are mainly plastic grinding, and the material surface roughness is 0.443 µm. The research results of this paper can provide guidance for engineering practice of ductile grinding technology of RB-SiC ceramic materials.
Observational evidence of diapycnal upwelling within a sloping submarine canyon
Authors: Wynne-Cattanach Bethan , Alford Matthew , Couto Nicole , Drake Henri , Ferrari Raffaele , Boyer Arnaud Le , Mercier Herle , Messias Marie-Jose , Garabato Alberto Naveira , Polzin Kurt , Ruan Xiaozhou , Spingys Carl , van Haren Hans , Voet Gunnar 
Published: October 2023

Abstract

Small-scale turbulent mixing drives the upwelling of deep water masses in the abyssal ocean as part of the global overturning circulation (Wunsch & Ferrari 2004). However, the processes leading to mixing and the pathways through which this upwelling occurs remain insufficiently understood. Recent observational and theoretical work suggests that deep water upwelling may be focused in bottom boundary layers on the ocean’s sloping seafloor; however, direct evidence of this is lacking (Ledwell et al. 2000, St. Laurent et al. 2001, Ferrari et al. 2016, de Lavergne et al. 2016). Here, we present observations from a near-bottom dye release within a canyon on the North Atlantic continental slope showing upwelling across density surfaces at a rate of 250 +/- 75 m/day over three days, ∼10,000 times higher than the global average value required to account for ∼30 Sv of upwelling globally (Munk 1966). The vigourous upwelling is coupled with adiabatic exchange of near-boundary and interior fluid. These results provide direct evidence of strong, bottom-focused diapycnal upwelling in the deep ocean, supporting previous suggestions that mixing at topographic features, such as canyons, leads to upwelling.
Theory of photonic complement of fundamental particles
Authors: Singh Shalender , Parmar Vishnu Priya Singh 
Published: October 2023

Abstract
An important result of classical physics is the constancy of the speed of light in free space irrespective of the frame of reference. In this paper, we theorize a novel principle from the constancy of the speed of light: For every realizable particle, there exists at least one mathematical photonic complement particle, with the following properties - A photonic complement of a realizable particle is a “complementary” particle (not necessarily realizable) such that the sum of momentum and energy of the photonic complement and the particle obey the characteristics of a photon. In this paper, we develop the theory of photonic complement and show that we can use it along with the classical equation of relativity to derive the Klein Gordon equation. We solve the KG equation of pion and its photonic complement in a pionic atom and find both energy and momentum jump during the state transition of the pion. We also investigate the nature of photonic complement and how the “principle of photonic complement” is consistent with special relativity and Einstein's equivalence principle. Furthermore, we propose a condition under which a photonic complement state of a particle can be realized using a potential barrier higher than the total energy. The condition is very similar to that of the Klein paradox, and we deduce that when the particle is in the photonic complement state, it can pass through that barrier higher than its energy transparently - without any reflection. We further contend that Klein's paradox exists because the particle undergoes the transformation to a photonic complement state in those conditions and show that Klein's paradox can be achieved without the transfer or reflection of energy. The principle of complement adds an important constraint on the possible states of particles - the only possible states of a particle are when a photonic complement is possible.
Motivations for using misoprostol for abortion outside the formal healthcare system in Colombia: A qualitative study of women seeking postabortion care in Bogotá and the Coffee Axis
Authors: Ortiz Juliette , Blades Nakeisha , Prada Elena 
Published: October 2023

Abstract
Background
Throughout the 2000’s, Colombia progressively adopted more liberal abortion laws. In 2006, Colombia went from completely prohibiting abortion to allowing the procedure in cases of rape, risk to the health or life of the woman, and fetal malformations incompatible with life. In 2022, Colombia finally permitted abortion on request until the 24th week of pregnancy. Despite these changes, illegal, and probably unsafe, abortion has remained. Knowing the reasons why women turn to illegal sources to interrupt their pregnancies may inform strategies to increase knowledge of the abortion law and improve access to legal services.
Methods
In-depth interviews were conducted in 2018 with 47 women aged 18 and older who used misoprostol obtained outside of health facilities to induce an abortion, and who were receiving postabortion care in two private clinics. Interviews explored what women knew about the 2006 abortion law which was then in effect, and the reasons why they preferred informal channels for abortion care over formal healthcare services.
Results
Women’s motivations to use misoprostol obtained outside the formal healthcare system were influenced by incomplete and inaccurate knowledge of the abortion law, fear of legal consequences, fear of ill-treatment from healthcare professionals, and concerns about judgment and privacy. Misoprostol also offered effectiveness and affordability and appeared easier to access.
Conclusions
Obtaining misoprostol outside the formal healthcare system was a more appealing prospect for some women given fears of legal repercussion and stigma toward abortion. This preference may continue despite the more liberal abortion law. Strategies must be implemented to improve awareness of the abortion law while combating misinformation and stigma to ensure that women access quality abortion care.
A Simple Frailty Index Predicts in-hospital Mortality
Authors: Shimoni Zvi , Dusseldorp Natan , Cohen Yael , Barnisan Izack , Froom Paul 
Published: October 2023

Abstract
INTRODUCTION: A frailty model that predicts in-hospital mortality is important to compare different settings and perhaps to modify patient disposition and treatment. We attempt to determine (a) if a new scale (Laniado-4 scale) that includes only three yes/no questions derived from the Norton scale and the presence of a urinary catheter performs as well as the graded Norton scale (including all five domains), in predicting in-hospital mortality and (b) to determine the predictive value of a simple frailty index that includes the new scale as well as categories of age, serum albumin, and creatinine values. METHODS: The study cohort included all acutely admitted adult patients in 2020–2021 to the three internal medicine departments at a regional 400-bed hospital. We calculated odds ratios with 95% confidence intervals and c-statistics for the various models predicting in-hospital mortality. RESULTS: The mean patient age was 73 ± 19 years, and 49.1% (5665/11542) were males. The Laniado-4 scale performed better than the Norton scale for predicting in-hospital mortality. A simple frailty index ranging from 0 to ≥ 8 points was associated with rates of in-hospital mortality that increased from 0 to 37.7%, with an odds ratio of 2.13(2.03–2.25) per 1 index point. The c-statistic was 0.887(0.881–0.893). CONCLUSIONS. We conclude the Laniado-4 scale performed better than the Norton scale in predicting in-hospital mortality, and that a simple frailty index including the 4-question scale as well as categories of age, serum creatinine, and serum albumin performed as well or better than more complicated models.
Advances in Synthesis of Indazole Variants: A Comprehensive Review of
Transition Metal, Acid/Base and Green Chemistry-based Catalytic
Approaches
Authors: Yadav Mithlesh , Kapoor Archana 
Published: October 2023

Background::
Indazole is a heterocyclic motif widely used in medicinal chemistry due
to its positive photophysical properties. The development of new methods for synthesizing the indazole
scaffold is of great importance in drug discovery.

Methods::
This study presents a detailed review of current advances in indazole synthesis, focusing
on catalyst-based and green chemistry approaches. The analysis is classified based on acid-base and
transition-metal catalysts and green chemistry methods. Catalyst-based advances have given a new
impetus to the synthesis of this effective pharmacophore.

Results::
The extensive literature on indazole synthesis demonstrates the notable progress achieved
through catalyst-based approaches. These methods have enabled researchers to create a wide range
of indazole derivatives and analogs, facilitating their application in pharmaceutical products and
organic molecules. The use of acid-base and transition-metal catalysts has been particularly effective
in enhancing the efficiency and selectivity of indazole synthesis.

Conclusion::
Indazoles and their variants are widely used in pharmaceutical products and organic
molecules. The recent literature indicates that catalyst-based approaches have resulted in significant
advancements in indazole synthesis. This review may be useful for researchers in medicinal chemistry,
content chemistry, and agrochemistry.
THE CARDIOPROTECTIVE EFFECTS OF EMPAGLIFLOZIN IN PATIENTS WITH HEART FAILURE WITH PRESERVED EJECTION FRACTION AND TYPE 2 DIABETES MELLITUS
Authors: Андрій Геращенко  , Сергій Федоров  
Published: October 2023

Introduction. Heart failure with preserved ejection fraction (HFpEF) is a complex clinical syndrome associated with significant morbidity and mortality. Type 2 diabetes mellitus (T2DM) often coexists in patients with HFpEF, further exacerbating the cardiovascular risk. Empagliflozin, a sodium-glucose cotransporter 2 inhibitor, has shown promising results in improving cardiovascular outcomes in patients with T2DM. However, the specific cardioprotective effects of empagliflozin in patients with HFpEF and T2DM remain to be elucidated.
Aim. To assess the effect of empagliflozin on biochemical markers of heart failure in patients with type 2 diabetes mellitus and heart failure with preserved ejection fraction.
Materials and Methods. The study included 80 patients with HFpEF and T2DM, with 40 patients in the empagliflozin group and 40 patients in the control group. Baseline characteristics, including age, gender, blood pressure, body mass index, and cardiac markers (HbA1c, NT-proBNP, Galectin-3, and sST2), were assessed. Changes in glycemic control and cardiac markers were analyzed after the treatment period.
Results. Baseline characteristics showed no significant differences between the two groups, indicating successful randomization. Post-treatment analysis revealed a numerical trend towards improved glycemic control in the empagliflozin group compared to the control group. Notably, empagliflozin treatment led to a significant reduction in NT-proBNP levels, indicating improved cardiac function and reduced cardiac stress. Furthermore, empagliflozin was associated with lower Galectin-3 and sST2 levels, suggesting potential benefits in mitigating cardiac fibrosis, remodeling, and inflammation.
Conclusions. Empagliflozin treatment in patients with HFpEF and T2DM have multifaceted implications beyond glycemic control. The observed reductions in NT-proBNP, Galectin-3, and sST2 levels suggest potential improvements in cardiac function, fibrosis, remodeling, and inflammatory processes. These findings highlight the potential of empagliflozin as a therapeutic option for managing HFpEF and T2DM, offering the potential for comprehensive cardiovascular benefits in this patient population.