bluuebunny/crossref_metadata_2025_split huggingface dataset:
High sensitivity refractive index sensing using zone plate metasurfaces with a conical phase profile
Authors: Abdel-Galil Manar , Swillam Mohamed , Ismail Yehea , Khalil Diaa 
Published: May 2022

AbstractIn this paper, we showed how a bulky Axicon lens can be transformed to a compact binary zone plate with conical phase profile. We built three zone plates made of three different materials and designed each zone plate to be used in high sensitivity refractive index sensing. This work is complementary to another work we have done before in which we showed mathematically how maximum sensitivity can be achieved in case of using an Axicon lens in sensing. The zone plates are designed to generate a Bessel–Gauss beam at the wavelength of 3.3 microns at which the absorption of methane gas is maximum leading to a maximum change in the refractive index. The generated intensity in the output is very sensitive to any slight change in the refractive index of the surrounding medium. Therefore, if an optical detector is positioned at the point of maximum change in the intensity with refractive index, we can easily measure the change in refractive index and hence the percentage of the gas with very high sensitivity.
Fishing capacity evaluation of fishing vessel based on cloud model
Authors: Lyu Chao , Zhang He-xu , Liu Shuang , Guo Yi 
Published: May 2022

AbstractIn the evaluation problem of fishing vessel fishing capacity, the imperfect evaluation index system and the methods of evaluation indexes are mostly artificial qualitative evaluation methods, which lead to strong subjectivity and fuzziness as well as low accuracy of evaluation results. Therefore, this study introduces cloud model theory on the basis of improving the evaluation index system, converts the artificial qualitative evaluation results into the digital characteristics of clouds, realizes the mutual transformation of qualitative evaluation and quantitative evaluation, and improves the accuracy of evaluation results. Taking the trawler as an example, the cloud model method is used to evaluate the fishing capacity, and the result obtained is (77.1408, 1.6897, 0.0), the result obtained by the fuzzy comprehensive evaluation method is 76.664785, and the result obtained by the cloud center of gravity evaluation method is 0.7919. Compared with the other two methods, the cloud model method uses three numerical characteristics to describe the results, and combining the different numerical characteristics meanings, the evaluation results can be judged to be accurate, and the influence of ambiguity on the results is greatly reduced. Meanwhile, the evaluation results can be presented in the form of pictures, and the results are more intuitive; in addition, the cloud model of the evaluation results is compared with the standard cloud model for similarity, which improves the credibility and authenticity of the results.
Data mining analyses for precision medicine in acromegaly: a proof of concept
Authors: Gil Joan , Marques-Pamies Montserrat , Sampedro Miguel , Webb Susan M. , Serra Guillermo , Salinas Isabel , Blanco Alberto , Valassi Elena , Carrato Cristina , Picó Antonio , García-Martínez Araceli , Martel-Duguech Luciana , Sardon Teresa , Simó-Servat Andreu , Biagetti Betina , Villabona Carles , Cámara Rosa , Fajardo-Montañana Carmen , Álvarez-Escolá Cristina , Lamas Cristina , Alvarez Clara V. , Bernabéu Ignacio , Marazuela Mónica , Jordà Mireia , Puig-Domingo Manel 
Published: May 2022

AbstractPredicting which acromegaly patients could benefit from somatostatin receptor ligands (SRL) is a must for personalized medicine. Although many biomarkers linked to SRL response have been identified, there is no consensus criterion on how to assign this pharmacologic treatment according to biomarker levels. Our aim is to provide better predictive tools for an accurate acromegaly patient stratification regarding the ability to respond to SRL. We took advantage of a multicenter study of 71 acromegaly patients and we used advanced mathematical modelling to predict SRL response combining molecular and clinical information. Different models of patient stratification were obtained, with a much higher accuracy when the studied cohort is fragmented according to relevant clinical characteristics. Considering all the models, a patient stratification based on the extrasellar growth of the tumor, sex, age and the expression of E-cadherin,GHRL,IN1-GHRL,DRD2,SSTR5andPEBP1is proposed, with accuracies that stand between 71 to 95%. In conclusion, the use of data mining could be very useful for implementation of personalized medicine in acromegaly through an interdisciplinary work between computer science, mathematics, biology and medicine. This new methodology opens a door to more precise and personalized medicine for acromegaly patients.
Torsional and lateral eigenmode oscillations for atomic resolution imaging of HOPG in air under ambient conditions
Authors: Eichhorn Anna L. , Dietz Christian 
Published: May 2022

AbstractCombined in-plane and out-of-plane multifrequency atomic force microscopy techniques have been demonstrated to be important tools to decipher spatial differences of sample surfaces at the atomic scale. The analysis of physical properties perpendicular to the sample surface is routinely achieved from flexural cantilever oscillations, whereas the interpretation of in-plane sample properties via force microscopy is still challenging. Besides the torsional oscillation, there is the additional option to exploit the lateral oscillation of the cantilever for in-plane surface analysis. In this study, we used different multifrequency force microscopy approaches to attain better understanding of the interactions between a super-sharp tip and an HOPG surface focusing on the discrimination between friction and shear forces. We found that the lateral eigenmode is suitable for the determination of the shear modulus whereas the torsional eigenmode provides information on local friction forces between tip and sample. Based on the results, we propose that the full set of elastic constants of graphite can be determined from combined in-plane and out-of-plane multifrequency atomic force microscopy if ultrasmall amplitudes and high force constants are used.
Quantitative study for control of air–liquid segmented flow in a 3D-printed chip using a vacuum-driven system
Authors: Hong Hyeonji , Song Jae Min , Yeom Eunseop 
Published: May 2022

AbstractThe formation of droplets or bubbles in a microfluidic system is a significant topic requiring device miniaturization and a small volume of samples. Especially, a two-phase segmented flow can be applied to micro-mixing for chemical reactions and the treatment of heat and mass transfer. In this study, a flow of liquid slugs and bubbles was generated in a 3D-printed chip and controlled by a single pump creating a vacuum at the outlet. The pump and chip device were integrated to form a simple and portable system. The size and flow rate of liquid slugs, obtained through image processing techniques, were analyzed considering several parameters related to hydraulic resistance and pressure drop. In addition, the effect of segmentation on mixing was observed by measuring the intensity change using two different colored inks. The hydraulic resistance of air and liquid flows can be controlled by changing the tube length of air flow and the viscosity of liquid flow. Because the total pressure drop along the channel was produced using a single pump at the outlet of the channel, the size and flow rate of the liquid slugs showed a near linear relation depending on the hydraulic resistances. In contrast, as the total pressure varied with the flow rate of the pump, the size of the liquid slugs showed a nonlinear trend. This indicates that the frequency of the liquid slug formation induced by the squeezed bubble may be affected by several forces during the development of the liquid slugs and bubbles. In addition, each volume of liquid slug segmented by the air is within the range of 10–1 to 2 µL for this microfluidic system. The segmentation contributes to mixing efficiency based on the increased homogeneity factor of liquid. This study provides a new insight to better understand the liquid slug or droplet formation and predict the segmented flow based on the relationship between the resistance, flow rate, and pressure drop.
Simplified model for pre-code RC column exposed to fire followed by earthquake
Authors: Ioannou Ioanna , Rossetto Tiziana , Rush David , Melo José 
Published: May 2022

AbstractThe behaviour of pre-code reinforced concrete (RC) columns in sequence of fire and earthquake is not well understood and can be critical in case of buildings which experienced fire and are either unrepaired or poorly repaired when exposed to an earthquake. This study proposes a framework on how to construct a simplified model to assess the post-fire cyclic behaviour of such columns. Emphasis is given to the development of simplified material models which can be used to describe the performance of the confined concrete, as its post-fire behaviour is not well studied. The model’s performance is validated against the experimental results of a square, non-seismically designed RC column. Three scenarios are considered. The reference scenario, where the column is exposed only to cyclic loading. In the other two, the column is firstly exposed to an ISO-834 time–temperature curves in a furnace of 30 min and 90 min duration and after it cooled down, it is exposed to cyclic loading. The results showed that simplified material models can be used to capture the post-fire cyclic behaviour of an RC column, built without seismic design. It was also found that the confined model adopted played an important role after the peak strength is reached.
Stabilization of highly nonlinear stochastic neutral Markovian jump systems with multiple delays
Authors: Fan Qiuqiu , Park Ju H. , Li Zhao‐Yan , Li Longsuo 
Published: May 2022

AbstractThis paper is concerned with the stabilization of highly nonlinear stochastic neutral Markovian jump systems (HNSNMJSs) with multiple delays. First, mild conditions are imposed on the coefficients of the system to ensure the existence and uniqueness of the solution. Second, the design method of the delayed feedback control is provided to stabilize an unstable HNSNMJS with multiple delays in the neutral term. In particular, novel conditions in terms of M‐matrices are proposed for the control function, which facilitate derivation and calculation and are easy to verify. Then, by applying Lyapunov functional‐based approach, new theories on the asymptotic stabilization and exponential stabilization are established. Finally, the validity of the theoretical results is illustrated through a numerical example.
Cascaded control for LCL filter based grid‐tied system with reduced sensors
Authors: Kumari Khushboo , Jain Amit Kumar 
Published: May 2022

AbstractThis work implements a cascaded control for the LCL filter‐based grid‐connected neutral point clamped (NPC) inverter with the reduced sensor. The conventional three‐loop control requires two current sensors for the inverter side, two voltage sensors for the voltage side, and two current sensors for the grid side in total for sensing. This work proposes a novel cascaded control scheme that allows a considerable reduction of grid‐side current sensors and capacitor‐side voltage sensors. Only two inverter‐side current sensors are required for the same. The sensing point is implemented by the proposed estimation algorithm. As an outcome, the hardware complexity, weight, size, and implementation cost of the system are downsized. A comparative assessment is performed between the conventional technique and the proposed methodology. The system is analysed for grid inductance and LCL filter parametric variations in order to assure the robustness and stability of the system. In addition, the system is also investigated for the influence of digital control delay. The implemented system offers enhanced system stability and improved dynamic performance. In order to meet grid regulation, it offers an economical solution. The proposed system is justified by simulated results on the MATLAB/Simulink platform and verified by the experimental results.
Heat wave mitigation of ecosystems in mountain areas — a case study of the Upper Yangtze River basin
Authors: Zhang Yuxin , Fu Bin , Sun Juying 
Published: May 2022

ABSTRACT

Background
Natural ecosystems, such as forests and grasslands, can mitigate heat waves, but research on heat wave mitigation in mountain ecosystems is lacking. Considering the upper reaches of the Yangtze River basin (URYB) as the study area, we first divided the URYB into mountainous and non-mountainous areas based on a digital elevation model (DEM). Then, we used temperature to identify heat waves and used the temperature and humidity index to identify suitable days. Finally, the differences between mountainous and non-mountainous areas were compared, and regional development strategies are proposed.

Result
(1)The frequency and duration of heat waves increased by 0.433/y (P < 0.1), 0.07/y (P < 0.05), while the number of suitable days in June, July, and August gradually decreased slightly by 0.0096/y (P < 0.1), 0.0125/y (P < 0.1), 0.004/y (P < 0.1), respectively from 1986 to 2015. (2)The average monthly number of suitable days was the highest in mountainous areas during the summer from 1986 to 2015. Mountainous areas have an advantage in mitigating heat waves owing to landform-based changes in the local climate. (3)In addition to the landform, altitude was the main factor responsible for mitigating heat waves in mountainous areas.

Conclusion
Parts of the plateau and whole mountain areas were found to be best for avoiding extremely high temperatures based on the number of suitable summer days from 1986 to 2015. We suggest formulating tourism promotion strategies, and strengthening tourism infrastructure, considering landscape protection and creation to promote sustainable regional development.
Independent assessment of a deep learning system for lymph node metastasis detection on the Augmented Reality Microscope
Authors: Jin David , Rosenthal Joseph H. , Thompson Elaine E. , Dunnmon Jared , Olson Niels H. 
Published: May 2022

AbstractSeveral machine learning algorithms have demonstrated high predictive capability in the identification of cancer within digitized pathology slides. The Augmented Reality Microscope (ARM) has allowed these algorithms to be seamlessly integrated within the current pathology workflow by overlaying their inferences onto its microscopic field of view in real time. In this paper, we present an independent assessment of the LYmph Node Assistant (LYNA) models, state-of-the-art algorithms for the identification of breast cancer metastases in lymph node biopsies which have been optimized for usage at different ARM magnifications. We assessed the models on a set of 40 whole slide images at the commonly used objective magnifications of 10x, 20x, and 40x. We analyzed the performance of the models across clinically relevant subclasses of tissue, including metastatic breast cancer, lymphocytes, histiocytes, veins, and fat. We also analyzed the models’ performance on potential types of contaminant tissue such as endometrial carcinoma and papillary thyroid cancer. Each model obtained overall AUC values of approximately 0.98, accuracy values of approximately 0.94, and sensitivity values above 0.88 at classifying small regions of a field of view as benign or cancerous. Across tissue subclasses, the models performed most accurately on fat and blood, and least accurately on histiocytes, germinal centers, and sinus. The models also struggled with the identification of isolated tumor cells, especially at lower magnifications. After testing, we manually reviewed the discrepancies between model predictions and ground truth in order to understand the causes of error. We introduce a distinction between proper and improper ground truth to allow for analysis in cases of uncertain annotations or on tasks with low inter-rater reliability. Taken together, these methods comprise a novel approach for exploratory model analysis over complex anatomic pathology data in which precise ground truth is difficult to establish.
Saccadic modulation of neural excitability in auditory areas of the neocortex
Authors: Leszczynski Marcin , Bickel Stephan , Nentwich Maximilian , Russ Brian E. , Parra Lucas , Lakatos Peter , Mehta Ashesh , Schroeder Charles E. 
Published: May 2022

SummaryIn natural “active” vision, humans and other primates use eye movements (saccades) to sample bits of information from visual scenes. In this process, nonretinal signals linked to saccades shift visual cortical neurons to a high excitability state as each saccade ends. The extent of this saccadic modulation outside of the visual system is unknown. Here, we show that during natural viewing, saccades modulate excitability in numerous auditory cortical areas, with a pattern complementary to that seen in visual areas. Bi-directional functional connectivity patterns suggest that these effects may arise from regions involved in saccade generation. By using saccadic signals to yoke excitability states in auditory areas to those in visual areas, the brain can improve information processing in complex natural settings.
Bundling and segregation affects “liking”, but not “wanting”, in an insect
Authors: De Agrò Massimo , Matschunas Chiara , Czaczkes Tomer J. 
Published: May 2022

AbstractBehavioural economists have identified many psychological manipulations which affect perceived value, although value in humans is not a unitary experience, with “liking” and “wanting” being neurologically separate processes. A prominent example of this is bundling, in which several small gains (or costs) are experienced as more valuable (or costly) than if the same total amount is presented together. While extensively demonstrated in humans, to our knowledge this effect has never been investigated in an animal, let alone an invertebrate. We trained individual Lasius niger workers to two of three conditions in which either costs (travel distance), gains (sucrose reward), or both were either bundled or segregated: A) both costs and gains bundled, B) both segregated, and C) only gains segregated. We recorded pheromone deposition on the ants’ return trips to the nest as measure of “liking”. After training, we offer the ants a binary choice between odours associated with the treatments, as a measure of “wanting”. While bundling treatment did not affect choice, i.e. “wanting”, it strongly influenced pheromone deposition, i.e. “liking”. Ants deposited c. 80% more pheromone when rewards were segregated but costs bundled as compared with both costs and rewards being bundled. This pattern is further complicated by the pairwise experience each animal made, and which of the treatments it experiences first during training. The current study is the first to demonstrate a bundling effect in an animal, and the first to report a dichotomy between “liking” and “wanting” in an insect. We propose that the deviation between “wanting” and “liking” in this case is due to the unique nature of distance perception in ants, which is recorded linearly, while almost all other sensory perception in animals is logarithmic.
Negative Control Exposures: Causal effect Identifiability and Use in Probabilistic-Bias and Bayesian Analyses with Unmeasured Confounders
Authors: Flanders WD , Waller LA , Zhang Q , Getahun D , Silverberg M , Goodman M 
Published: May 2022

AbstractProbabilistic bias and Bayesian analyses are important tools for bias correction, particularly if required parameters are nonidentifiable. Negative controls are another tool; they can detect confounding and correct for confounders. Our goals are to present conditions that assure identifiability of certain causal effects and to describe and illustrate a probabilistic bias analysis and related Bayesian analysis that use a negative control exposure.Using potential-outcome models, we characterize assumptions needed for identification of causal effects using a dichotomous, negative control exposure when residual confounding exists. We define bias parameters, characterize their relationships with the negative control and with specified causal effects, and describe the corresponding probabilistic-bias and Bayesian analyses.We exemplify analyses using data on hormone therapy and suicide attempts among transgender people. To address possible confounding by healthcare utilization, we used prior TdaP (tetanus-diphtheria-pertussis) vaccination as a negative control exposure. Hormone therapy was weakly associated with risk (risk ratio (RR) = 0.9). The negative control exposure was associated with risk (RR = 1.7), suggesting confounding. Based on an assumed prior distribution for the bias parameter, the 95% simulation interval for the distribution of confounding-adjusted RR was (0.17, 1.64), with median 0.5; the 95% credibility interval was similar.A dichotomous negative control exposure can be used to identify causal effects when a confounder is unmeasured under strong assumptions. More realistically, assumptions can be relaxed and the negative control exposure may prove helpful for probabilistic bias analyses and Bayesian analyses.
Joint engagement is associated with greater development of language and sensory awareness in children with autism
Authors: Vyshedskiy Andrey , Khokhlovich Edward 
Published: May 2022

AbstractThe effect of joint engagement in 2- to 6-year-old children with ASD was investigated in the largest and the longest observational study to-date. Parents assessed the development of 12081 children quarterly for three years on five subscales: receptive language, expressive language, sociability, sensory awareness, and health. Longer duration of time spent with an adult actively involved in the same activity was associated with improved trajectory of receptive language, expressive language, and sensory awareness. On the annualized basis, the high-joint-engagement group (3 hours or more of joint engagement per day) improved their combinatorial receptive language 1.4-times faster (p=0.0019), expressive language 1.5-times faster (p<0.0001), and sensory awareness 1.5-times faster (p=0.0248) than the low-joint-engagement group (1 hour or less joint engagement per day). The difference in the sociability and the health scores at the end of 3-year study was insignificant. This study confirms the importance of ASD children spending more time with adults actively involved in the same activity and highlights the need to include joint engagement as a target for intervention with this population.Lay summaryParents of 2- to 6-year-old children with ASD assessed the development of 12081 children quarterly for three years. Longer duration of time spent with an adult actively involved in the same activity was associated with improved developmental trajectory. This study confirms the importance of ASD children spending more time with adults actively involved in the same activity and highlights the need to include joint engagement as a target for intervention with this population.