bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neurostimulation success rate of repetitive‐pulse focused ultrasound in an in vivo giant axon model: An acoustic parametric study
Authors: Vion‐Bailly Jérémy , Suarez‐Castellanos Ivan M. , Chapelon Jean‐Yves , Carpentier Alexandre , N'Djin W. Apoutou 
Published: November 2021

AbstractPurposeFocused ultrasound (FUS) is a promising tool to develop new modalities of therapeutic neurostimulation. The ability of FUS to stimulate the nervous system, in a noninvasive and spatiotemporally precise manner, has been demonstrated in animals and human subjects, but the underlying biomechanisms are not fully understood yet. The objective of the present study was to investigate the bioeffects involved in the generation of trains of action potentials (APs) by repetitive‐pulse FUS stimuli in a simple invertebrate neural model.MethodsThe respective influences of different acoustic parameters on the neurostimulation success rate (NSR), defined as the rate of FUS stimuli capable of evoking at least one AP, were explored using the system of afferent nerves and giant fibers of Lumbricus terrestris as neural model. Each parameter was studied independently by administering random FUS sequences while keeping all but one FUS parameter constant. The NSR was evaluated as a function of (i) the spatial‐average pulse‐average intensity (Isapa); (ii) the pulse duration (PD); (iii) the pulse repetition frequency (PRF); iv) the number of cycles per pulse (Ncycles); (v) two ultrasound frequencies, f0 = 1.1 MHz and f3 = 3.3 MHz, corresponding to the fundamental and third‐harmonic resonant frequencies of the FUS transducer, respectively (spherical, radius of curvature: 50 mm); and (vi) levels of emerging stable cavitation and inertial cavitation.ResultsThe NSR associated to 1.1 MHz repetitive‐pulse FUS stimuli was found to increase as a function of increasing Isapa, PD, PRF, and Ncycles. When evaluating each parameter at f = 1.1 MHz, it was observed that NSRs close to 100% were achieved when sufficiently elevating their respective values. When computing the NSR as a function of the spatial‐average, temporal‐average intensity (Isata), defined as the product of PRF, PD, and Isapa, a significant elevation of the NSR from 0% to close to 100% was measured by increasing Isata from values approximate to 4 W/cm2 to values higher than 12 W/cm2. No clear and consistent trend was observed in trials aimed at exploring the effects of different levels of stable and inertial acoustic cavitation on the NSR. Finally, the feasibility of inducing neural responses with 3.3 MHz repetitive‐pulse FUS stimuli was also demonstrated with NSRs reaching up to 60%, in the range of FUS parameters studied.ConclusionThe time‐averaged value of the radiation force per unit volume of tissue is proportional to the acoustic intensity. As a result, the observations from this study suggest that the neural structure responding to the stimulus is sensitive to the mean radiation force carried by the FUS sequence, regardless of the combination of FUS parameters giving rise to such force. The results from this study further revealed the existence of a minimal activation threshold with regard to Isapa.
Impact of a spatially dependent dose delivery time structure on the biological effectiveness of scanning proton therapy
Authors: Kasamatsu Koki , Tanaka Sodai , Miyazaki Koichi , Takao Seishin , Miyamoto Naoki , Hirayama Shusuke , Nishioka Kentaro , Hashimoto Takayuki , Aoyama Hidefumi , Umegaki Kikuo , Matsuura Taeko 
Published: November 2021

AbstractPurposeIn the scanning beam delivery of protons, different portions of the target are irradiated with different linear energy transfer protons with various time intervals and irradiation times. This research aimed to evaluate the spatially dependent biological effectiveness of protracted irradiation in scanning proton therapy.MethodsOne and two parallel opposed fields plans were created in water phantom with the prescribed dose of 2 Gy. Three scenarios (instantaneous, continuous, and layered scans) were used with the corresponding beam delivery models. The biological dose (physical dose × relative biological effectiveness) was calculated using the linear quadratic model and the theory of dual radiation action to quantitatively evaluate the dose delivery time effect. In addition, simulations using clinical plans (postoperative seminoma and prostate tumor cases) were conducted to assess the impact of the effects on the dose volume histogram parameters and homogeneity coefficient (HC) in targets.ResultsIn a single‐field plan of water phantom, when the treatment time was 19 min, the layered‐scan scenario showed a decrease of <0.2% (almost 3.3%) in the biological dose from the plan on the distal (proximal) side because of the high (low) dose rate. This is in contrast to the continuous scenario, where the biological dose was almost uniformly decreased over the target by approximately 3.3%. The simulation with clinical geometry showed that the decrease rates in D99% were 0.9% and 1.5% for every 10 min of treatment time prolongation for postoperative seminoma and prostate tumor cases, respectively, whereas the increase rates in HC were 0.7% and 0.2%.ConclusionsIn protracted irradiation in scanning proton therapy, the spatially dependent dose delivery time structure in scanning beam delivery can be an important factor for accurate evaluation of biological effectiveness.
A C‐term truncated EIF2Bγ protein encoded by an intronically polyadenylated isoform introduces unfavorable EIF2Bγ–EIF2γ interactions
Authors: Circir Ayca , Koksal Bicakci Gozde , Savas Busra , Doken Didem Naz , Henden Şevki Onur , Can Tolga , Karaca Ezgi , Erson‐Bensan Ayse Elif 
Published: November 2021

AbstractEukaryotic translation initiates upon recruitment of the EIF2‐GTP·Met‐tRNAi ternary complex (TC) to the ribosomes. EIF2 (α, β, γ subunits) is a GTPase. The GDP to GTP exchange within EIF2 is facilitated by the guanine nucleotide exchange factor EIF2B (α‐ε subunits). During stress‐induced conditions, phosphorylation of the α‐subunit of EIF2 turns EIF2 into an inhibitor of EIF2B. In turn, inhibition of EIF2B decreases TC formation and triggers the internal stress response (ISR), which determines the cell fate. Deregulated ISR has been linked to neurodegenerative disorders and cancer, positioning EIF2B as a promising therapeutic target. Hence, a better understanding of the mechanisms/factors that regulate EIF2B activity is required. Here, combining transcript and protein level analyses, we describe an intronically polyadenylated (IPA) transcript of EIF2B's γ‐subunit. We show that the IPA mRNA isoform is translated into a C‐terminus truncated protein. Using structural modeling, we predict that the truncated EIF2Bγ protein has unfavorable interactions with EIF2γ, leading to a potential decrease in the stability of the nonproductive EIF2:EIF2B complex. While we discovered and confirmed the IPA mRNA isoform in breast cancer cells, the expression of this isoform is not cancer‐specific and is widely present in normal tissues. Overall, our data show that a truncated EIF2Bγ protein co‐exists with the canonical protein and is an additional player to regulate the equilibrium between productive and nonproductive states of the EIF2:EIF2B complex. These results may have implications in stress‐induced translation control in normal and disease states. Our combinatorial approach demonstrates the need to study noncanonical mRNA and protein isoforms to understand protein interactions and intricate molecular mechanisms.
Female workers, male managers: Gender, leadership, and risk‐taking
Authors: Rinne Ulf , Sonnabend Hendrik 
Published: November 2021

AbstractThis study examines gender differences in risk‐taking behavior among managers in a female‐dominated industry. Using data from international top‐level women's soccer, we provide evidence that on average, male coaches show a lower level of risk‐taking than female coaches. We also find a U‐shaped age effect that is independent of gender, meaning that young and more mature individuals tend to take riskier decisions. Our main results therefore strongly contrast with the majority of previous studies on gender differences in risk preferences, and thereby emphasize the importance of considering institutional differences or labor market specifics. Underlying selection processes may play an important role as well as gender stereotypes. Lastly, we find no correlation between gender differences in risk‐taking and female empowerment defined by national gender equality scores.
Small instantons in weakly-gauged holographic models
Authors: Gherghetta Tony , Pomarol Alex 
Published: November 2021

Abstract
Small instantons can play an important role in Yang-Mills theories whose gauge couplings are sizeable at small distances. An interesting class of theories where this could occur is in weakly-gauged holographic models (dual to Yang-Mills theories interacting with strongly-coupled CFTs), since gauge couplings are indeed enhanced towards the UV boundary of the 5D AdS space. However, contrary to expectations, we show that small instantons in these non-asymptotically-free models are highly suppressed and ineffective. This is due to the conservation of topological charge that forbids instantons to be localized near the UV boundary. Despite this fact we find non-trivial UV localized instanton-anti-instanton solutions of the Yang-Mills equations where the topological charges annihilate in the AdS bulk. These analytic solutions arise from a 5D conformal transformation of the uplifted 4D instanton. Our analysis therefore reveals unexpected nonperturbative configurations of Yang-Mills theories when they interact with strongly-coupled CFTs.
Stationary solutions in thermodynamics of stochastically forced fluids
Authors: Breit Dominic , Feireisl Eduard , Hofmanová Martina 
Published: November 2021

AbstractWe study the full Navier–Stokes–Fourier system governing the motion of a general viscous, heat-conducting, and compressible fluid subject to stochastic perturbation. The system is supplemented with non-homogeneous Neumann boundary conditions for the temperature and hence energetically open. We show that, in contrast with the energetically closed system, there exists a stationary solution. Our approach is based on new global-in-time estimates which rely on the non-homogeneous boundary conditions combined with estimates for the pressure.
Autosuggestion: a cognitive process that empowers your brain?
Authors: Myga Kasia A. , Kuehn Esther , Azanon Elena 
Published: November 2021

AbstractAutosuggestion is a cognitive process that is believed to enable control over one’s own cognitive and physiological states. Despite its potential importance for basic science and clinical applications, such as in rehabilitation, stress reduction, or pain therapy, the neurocognitive mechanisms and psychological concepts that underlie autosuggestion are poorly defined. Here, by reviewing empirical data on autosuggestion and related phenomena such as mental imagery, mental simulation, and suggestion, we offer a neurocognitive concept of autosuggestion. We argue that autosuggestion is characterized by three major factors: reinstantiation, reiteration, and volitional, active control over one’s own physiological states. We also propose that autosuggestion might involve the ‘overwriting’ of existing predictions or brain states that expect the most common (but not desired) outcome. We discuss potential experimental paradigms that could be used to study autosuggestion in the future, and discuss the strengths and weaknesses of current evidence. This review provides a first overview on how to define, experimentally induce, and study autosuggestion, which may facilitate its use in basic science and clinical practice.
High-intensity resistance exercise is not as effective as traditional high-intensity interval exercise for increasing the cardiorespiratory response and energy expenditure in recreationally active subjects
Authors: Järvinen Laura , Lundin Petersdotter Sofi , Chaillou Thomas 
Published: November 2021

Abstract
Purpose
Traditional high-intensity interval exercise (HIIE) highly stimulates the cardiorespiratory system and increases energy expenditure (EE) during exercise. High-intensity resistance exercise (HIRE) has become more popular in recreationally active subjects. The physiological responses to HIRE performed with light or moderate load is currently largely unknown. Here, we examined the effect of the type of interval exercise [HIRE at 40% (HIRE40) and 60% (HIRE60) 1-RM vs. traditional HIIE] on the cardiorespiratory response and EE during and after exercise.

Methods
Fifteen recreationally active adults randomly completed traditional HIIE on an ergocyle, HIRE40 and HIRE60. The sessions consisted of two sets of ten 30-s intervals (power at 100% VO2max during HIIE; maximal number of repetitions for 10 different free-weight exercises during HIRE40 and HIRE60) separated by 30-s active recovery periods. Gas exchange, heart rate (HR) and EE were assessed during and after exercise.

Results
VO2mean, VO2peak, HRmean, the time spent above 90% VO2max and HRmax, and aerobic EE were lower in both HIRE sessions compared with HIIE (P < 0.05). Anaerobic glycolytic contribution to total exercise EE was higher in HIRE40 and HIRE60 compared with HIIE (P < 0.001). EE from excess post-exercise oxygen consumption (EPOC) was similar after the three sessions. Overall, similar cardiorespiratory responses and EE were found in HIRE40 and HIRE60.

Conclusions
HIRE is not as effective as HIIE for increasing the cardiorespiratory response and EE during exercise, while EPOC remains similar in HIRE and HIIE. These parameters are not substantially different between HIRE40 and HIRE60.
An ensemble-based convolutional neural network model powered by a genetic algorithm for melanoma diagnosis
Authors: Pérez Eduardo , Ventura Sebastián 
Published: November 2021

AbstractMelanoma is one of the main causes of cancer-related deaths. The development of new computational methods as an important tool for assisting doctors can lead to early diagnosis and effectively reduce mortality. In this work, we propose a convolutional neural network architecture for melanoma diagnosis inspired by ensemble learning and genetic algorithms. The architecture is designed by a genetic algorithm that finds optimal members of the ensemble. Additionally, the abstract features of all models are merged and, as a result, additional prediction capabilities are obtained. The diagnosis is achieved by combining all individual predictions. In this manner, the training process is implicitly regularized, showing better convergence, mitigating the overfitting of the model, and improving the generalization performance. The aim is to find the models that best contribute to the ensemble. The proposed approach also leverages data augmentation, transfer learning, and a segmentation algorithm. The segmentation can be performed without training and with a central processing unit, thus avoiding a significant amount of computational power, while maintaining its competitive performance. To evaluate the proposal, an extensive experimental study was conducted on sixteen skin image datasets, where state-of-the-art models were significantly outperformed. This study corroborated that genetic algorithms can be employed to effectively find suitable architectures for the diagnosis of melanoma, achieving in overall 11% and 13% better prediction performances compared to the closest model in dermoscopic and non-dermoscopic images, respectively. Finally, the proposal was implemented in a web application in order to assist dermatologists and it can be consulted at http://skinensemble.com.
A deep learning model for gas storage optimization
Authors: Curin Nicolas , Kettler Michael , Kleisinger-Yu Xi , Komaric Vlatka , Krabichler Thomas , Teichmann Josef , Wutte Hanna 
Published: November 2021

AbstractTo the best of our knowledge, the application of deep learning in the field of quantitative risk management is still a relatively recent phenomenon. In this article, we utilize techniques inspired by reinforcement learning in order to optimize the operation plans of underground natural gas storage facilities. We provide a theoretical framework and assess the performance of the proposed method numerically in comparison to a state-of-the-art least-squares Monte-Carlo approach. Due to the inherent intricacy originating from the high-dimensional forward market as well as the numerous constraints and frictions, the optimization exercise can hardly be tackled by means of traditional techniques.
Intermittent Hormone Therapy Models Analysis and Bayesian Model Comparison for Prostate Cancer
Authors: Pasetto S. , Enderling H. , Gatenby R. A. , Brady-Nicholls R. 
Published: November 2021

AbstractThe prostate is an exocrine gland of the male reproductive system dependent on androgens (testosterone and dihydrotestosterone) for development and maintenance. First-line therapy for prostate cancer includes androgen deprivation therapy (ADT), depriving both the normal and malignant prostate cells of androgens required for proliferation and survival. A significant problem with continuous ADT at the maximum tolerable dose is the insurgence of cancer cell resistance. In recent years, intermittent ADT has been proposed as an alternative to continuous ADT, limiting toxicities and delaying time-to-progression. Several mathematical models with different biological resistance mechanisms have been considered to simulate intermittent ADT response dynamics. We present a comparison between 13 of these intermittent dynamical models and assess their ability to describe prostate-specific antigen (PSA) dynamics. The models are calibrated to longitudinal PSA data from the Canadian Prospective Phase II Trial of intermittent ADT for locally advanced prostate cancer. We perform Bayesian inference and model analysis over the models’ space of parameters on- and off-treatment to determine each model’s strength and weakness in describing the patient-specific PSA dynamics. Additionally, we carry out a classical Bayesian model comparison on the models’ evidence to determine the models with the highest likelihood to simulate the clinically observed dynamics. Our analysis identifies several models with critical abilities to disentangle between relapsing and not relapsing patients, together with parameter intervals where the critical points’ basin of attraction might be exploited for clinical purposes. Finally, within the Bayesian model comparison framework, we identify the most compelling models in the description of the clinical data.
Profit uplift modeling for direct marketing campaigns: approaches and applications for online shops
Authors: Baier Daniel , Stöcker Björn 
Published: November 2021

AbstractIn order to select “best” customers for a direct marketing campaign, response models are widespread: a sample of customers receives an ad, a catalog, a sample pack, or a discount offer on a test basis. Then, their responses (e.g., website visits, conversions, or revenues) are used to build a predictive model. Finally, this model is applied to all customers in order to select “best” ones for the campaign. However, up to now, only models that reflect website visits, conversions, or revenues have been proposed. In this paper, we discuss the shortcomings of these traditional approaches and propose profit uplift modeling appoaches based on one-stage ordinary regression and random forests as well as two-stage Heckman sample selection and zero-inflated negative binomial regression for parameter estimation. The new approaches demonstrate superiority to the traditional ones when applied to real-world datasets. One dataset reflects recent discount offers of a large online fashion retailer. The other is the well-known Hillstrom dataset that describes two Email campaigns.
The Ductility and Shape-Memory Properties of Ni–Mn–Ga–Cu Heusler Alloys
Authors: Brzoza-Kos Agnieszka , Cesari Eduard , Szczerba Maciej Jakub 
Published: November 2021

Abstract
The effect of Cu addition on crystal structure, compressive properties and shape-memory effect of Ni50Mn25Ga25−x
Cu
x
alloys was studied. With increasing Cu content, the type of crystal structure evolves following a sequence: L21 → 10M → 2M → 2M+γ. Addition of Cu significantly improves room temperature ductility. In polycrystalline Ni50Mn25Ga17Cu8 alloy, a full recoverable strain equal to 7 pct was achieved. High martensitic transformation temperature and large shape-memory effect makes this material potential candidate in high-temperature shape-memory applications.
Radiographic Measurement of Gastric Remnant Volume After Laparoscopic Sleeve Gastrectomy: Assessment of Reproducibility and Correlation with Weight Loss
Authors: Deręgowska-Cylke Małgorzata , Palczewski Piotr , Błaż Marcin , Cylke Radosław , Ziemiański Paweł , Szeszkowski Wojciech , Lisik Wojciech , Gołębiowski Marek 
Published: November 2021

Abstract
Background
As a restrictive procedure, laparoscopic sleeve gastrectomy (LSG) relies primarily on the reduction of gastric volume. It has been suggested that an immediate postoperative gastric remnant volume (GRV) may influence long-term results of LSG; however, there are no consensus in this matter. The aim of this study was to assess the reproducibility of different radiographic methods of GRV calculation and evaluate their correlation with the weight loss (WL) after surgery.

Methods
This retrospective study evaluated 174 patients who underwent LSG in the period from 2014 to 2017. Using UGI, GRV was measured with 3 different mathematical methods by 2 radiologists. Intraobserver and interobserver calculations were made. Correlation between GRV and WL were estimated with calculations percentage of total weight loss (%TWL) and percentage of excess weight loss (%EWL) after 1, 3, 6, 12, 18, and 24 months postoperatively.

Results
During analysis of intraobserver similarities, the results of ICC calculation showed that reproducibility was good to excellent for all GRV calculation methods. The intraobserver reproducibility for Reader I was highest for cylinder and truncated cone formula and for Reader II for ellipsoid formula. The interobserver reproducibility was highest for ellipsoid formula. Regarding correlation between GRV and WL, significant negative correlation has been shown on the 12th month after LSG in %TWL and %EWL for every method of GRV calculation, most important for ellipsoid formula (%TWL – r(X,Y) = -0.335, p < 0.001 and %EWL – r(X,Y) = -0.373, p < 0.001).

Conclusion
Radiographic methods of GRV calculation are characterized by good reproducibility and correlate with the postoperative WL.

Graphical Abstract