Mayawaves: Python Library for Interacting with the Einstein Toolkit and the MAYA Catalog

Numerical relativity simulations are crucial for studying black holes and have been instrumental in the detection of gravitational waves by the LVK. However, these simulations produce vast amounts of data that must be processed in order to perform studies, create models, and use them with gravitational wave detection pipelines. This paper introduces mayawaves, an open-source python library for processing, studying, and exporting numerical relativity simulations performed using the Einstein Toolkit and MAYA. Mayawaves streamlines the process of analyzing simulations with an intuitive interface, greatly reducing the learning curve for numerical relativity.Comment: 2 page

INTERFERÊNCIA DE PLANTAS DANINHAS NA QUALIDADE E PRODUTIVIDADE DO GRÃO-DE-BICO

O cultivo de grão-de-bico (Cicer arietinum L.) tem sido dificultado devido às interferências das plantas daninhas. Objetivou-se verificar o efeito da interferência de seis diferentes espécies invasoras (Bidens pilosa, Commelina benghalensis, Eleusine indica, Ipomoea grandifolia, Uruchloa brizantha e Uruchloa ruziziensis) na qualidade e produtividade de dois cultivares de grão-de-bico (BRS Aleppo e FLIP 86-77c). A interferência das plantas daninhas reduziu o período vegetativo de ambos os cultivares. A espécie Uruchloa ruziziensis influenciou negativamente o número de vagens do cultivar BRS Aleppo sugerindo ser prejudicial ao cultivo. Além disso, os resultados indicaram que há relação entre o período de convivência e o nível de infestação no número de grãos por vagem e peso de cem grãos. Contudo, apesar de todas as espécies daninhas terem afetado a produtividade dos cultivares, tal efeito foi mais sobressalente no cultivar FLIP 86-77c, sobretudo na presença de C. benghalensis, U. brizantha e U. ruzizinsis. O teor de nutrientes no grão variou de acordo com a espécie daninha analisada. C. benghalensis, E. indica, U. brizantha e U. ruziziensis apresentam maior potencial de competição, sendo responsáveis pelos maiores danos na produtividade e nas características qualitativas dos grãos

Second MAYA Catalog of Binary Black Hole Numerical Relativity Waveforms

Numerical relativity waveforms are a critical resource in the quest to deepen our understanding of the dynamics of, and gravitational waves emitted from, merging binary systems. We present 181 new numerical relativity simulations as the second MAYA catalog of binary black hole waveforms (a sequel to the Georgia Tech waveform catalog). Most importantly, these include 55 high mass ratio (q >= 4), 48 precessing, and 92 eccentric (e > 0.01) simulations, including 7 simulations which are both eccentric and precessing. With these significant additions, this new catalog fills in considerable gaps in existing public numerical relativity waveform catalogs. The waveforms presented in this catalog are shown to be convergent and are consistent with current gravitational wave models. They are available to the public at https://cgp.ph.utexas.edu/waveform.Comment: 11 pages, 9 figure

Fish but not macroinvertebrates promote trophic cascading effects in high density submersed plant experimental lake food webs in two contrasting climate regions

Predators play a key role in the functioning of shallow lakes. Differences between the response of temperate and subtropical systems to fish predation have been proposed, but experimental evidence is scarce. To elucidate cascading effects produced by predators in contrasting climatic zones, we conducted a mesocosm experiment in three pairs of lakes in Uruguay and Denmark. We used two typical planktivorous-omnivorous fish species (Jenynsia multidentata + Cnesterodon decemmaculatus and Gasterosteus aculeatus + Perca fluviatilis) and one littoral omnivorous-predatory macroinvertebrate (Palaemonetes argentinus and Gammarus lacustris), alone and combined, in numbers resembling natural densities. Fish predation on zooplankton increased phytoplankton biomass in both climate zones, whereas the effects of predatory macroinvertebrates on zooplankton and phytoplankton were not significant in either climate zone. Macroinvertebrates (that freely colonized the sampling devices) were diminished by fish in both climate areas; however, periphyton biomass did not vary among treatments. Our experiments demonstrated that fish affected the structure of both planktonic and littoral herbivorous communities in both climate regions, with a visible positive cascading effect on phytoplankton biomass, but no effects on periphyton. Altogether, fish impacts appeared to be a strong driver of turbid water conditions in shallow lakes regardless of climatic zone by indirectly contributing to increasing phytoplankton biomass

Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data

Objectives The aim of this study was to investigate whether algorithmic interpretation (AI) of instantaneous wave-free ratio (iFR) pressure-wire pull back data would be noninferior to expert human interpretation. Background Interpretation of iFR pressure-wire pull back data can be complex and is subjective. Methods Fifteen human experts interpreted 1,008 iFR pull back traces (691 unique, 317 duplicate). For each trace, experts determined the hemodynamic appropriateness for percutaneous coronary intervention (PCI) and, in such cases, the optimal physiological strategy for PCI. The heart team (HT) interpretation was determined by consensus of the individual expert opinions. The same 1,008 pull back traces were also interpreted algorithmically. The coprimary hypotheses of this study were that AI would be noninferior to the interpretation of the median expert human in determining: 1) the hemodynamic appropriateness for PCI; and 2) the physiological strategy for PCI. Results Regarding the hemodynamic appropriateness for PCI, the median expert human demonstrated 89.3% agreement with the HT in comparison with 89.4% for AI (p < 0.01 for noninferiority). Across the 372 cases judged as hemodynamically appropriate for PCI according to the HT, the median expert human demonstrated 88.8% agreement with the HT in comparison with 89.7% for AI (p < 0.0001 for noninferiority). On reproducibility testing, the HT opinion itself changed 1 in 10 times for both the appropriateness for PCI and the physiological PCI strategy. In contrast, AI showed no change. Conclusions AI of iFR pressure-wire pull back data was noninferior to expert human interpretation in determining both the hemodynamic appropriateness for PCI and the optimal physiological strategy for PCI

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity &gt; 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to &lt;90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], &gt;300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of &lt;15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P&lt;0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P&lt;0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Online Failure Diagnostic in Full-Bridge Module for Optimum Setup of an IGBT-Based Multilevel Inverter

An online failure diagnostic test is essential to ensure the robustness and reliability of high-powered systems. Furthermore, the overall design must comprise diagnostic strategies to detect in-service and high-powered module defects. This paper describes the critical failure mechanisms––cross-conduction, inductive avalanche, second turn-on, VS-undershoot, inrush current, and thermal runaway––that directly affect insulated gate bipolar transistor (IGBT) operation. The constructed inverter contains 18 transformer-based taps (six per phase); however, this work studied a single tap (IGBT-based full-bridge module) to understand the reasons for failure and the routes to mitigate them. Moreover, a cost-effective solution using the IR2127STRPBF driver circuit was implemented to reduce the probability of thermal runaway in case of overcurrent, short-circuit, or avalanche events. For this reason, the electrical current state was adjusted using an FPGA digital resource to perform dynamic PWM control signals. The obtained correlation waveforms are valuable for verifying diagnostic data at the design stage to emphasize the significance of evading premature failure events. The comprehensive study on failure diagnosis enabled successful design strategies to construct a robust 45 kVA three-phase multilevel inverter for a 22 kW eolic-photovoltaic generation plant

Smart Load Management with Energy Storage for Power Quality Enhancement in Wind-Powered Oil and Gas Applications

This paper investigates power quality issues in a wind-powered offshore oil and gas platform operating in island mode. Topics of interest are the negative effects that load and wind power variability have on the electrical system frequency and voltage; and how those influence the gas turbine operation. The authors discuss how smart load management together with energy storage can mitigate those effects, and propose a control algorithm for that. Simulations in MATLAB/Simulink demonstrate that the proposed energy storage controller reduces frequency and voltage variations in a case study. Moreover, the paper presents a methodology to derive a simplified model of the hybrid energy system that reduces simulation time in at least two orders of magnitude. The latter can be a useful tool for optimization algorithms evaluating a huge number of scenarios, especially those dealing with economical dispatch of generators or sizing of energy storage systems