bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic mapping and pedigree analysis of non-syndromic congenital deafness in Surabaya, Indonesia
Authors: Purnami Nyilo , Kusumagani Hamam , Nugroho Puguh Setyo , Faizah Zakiyatul , Moon In Seok
Published: January 2023

Background: Genetic mutations cause 50-75% of congenital deafness. Congenital deafness is a disease divided into syndromic and non-syndromic types. Type B special schools facilitate children with deafness in Surabaya. This study aimed to identify a mutation gene that causes non-syndromic hearing impairment in school students.

Methods: This research was an analytic observational study using a cross-sectional method applying simple random sampling of non-syndromic deaf children. The applied tests were pure tone audiometry, polymerase chain reaction (PCR), and hybridization tests. Subjects were evaluated on the pedigree route and then analyzed.

Results: A total of 138 participants with non-syndromic hearing loss were enrolled in this study and 49 patients met the inclusion criteria. The subject’s average age was 16.16 years, with more male subjects than female.  The hybridization results obtained six genetic mutations, one subject with mtDNA 1555, one subject with GJB2-299, two subjects with SLC26A4-IVS(7)2, and 3 subjects with unknown mutations. In pedigree analysis, the same genetic mutation was found in two generations of subjects with mtDNA 1555 and GJB2-299 mutations, and mutations of more than one genetic type were found in two generations of subjects with the SLC26A4-IVS(7)2 mutation.

Conclusions: This study obtained six genetic mutations in non-syndromic congenital deaf children. Non-syndromic congenital deafness in Indonesia was found to have genetic mutations as a health risk. The risk was heredity with diverse inheritance patterns.
Pre-clinical undergraduate students’ perspectives on the adoption of virtual and augmented reality to their dental learning experience: A one-group pre- and post-test design protocol
Authors: Afrashtehfar Kelvin I. , Yang Jing-Wen , Al-Sammarraie A. , Chen Hui , Saeed Musab H.
Published: January 2023

Background: We live in a time where traditional education has rapidly incorporated online modalities due to the recent SARS-CoV-2 (COVID-19) safety measures such as social distancing. Regardless of these challenges, health education constantly strives to implement the best technologies available for an effective student deep learning outcome. Virtual (VR) and augmented reality (AR) in the dental pre-clinical stage may help stimulate students to better understand the foundation material prescribed in the curriculum. Most visual material available for students is still mainly based on 2D graphics. Thus, this study will attempt to evaluate the students' perceptions about implementing VR/AR technologies in the learning setting.

Methods: A single-group pretest-posttest design will be implemented where students will be exposed to VR/AR and fill out two questionnaires, one before and one after the exposure.

Conclusions: This project is intended to start once the institutional ethical approval is obtained. It is expected that the analysis from the current project will provide recommendations to improve the students' academic curriculum pre-clinical experience. The recommendations will be provided in the form of at least three scientific publications, with one publication for each subject area intended to be evaluated (i.e., head and neck anatomy, dental anatomy, and removable prosthodontics).
Nutrient dynamics in water and soil under conventional rice cultivation in the Vietnamese Mekong Delta
Authors: Ngan Nguyen Vo Chau , Thao Huynh Van , Giang Nam Nguyen Dinh
Published: January 2023

Background The evaluation of nutrient variability plays a crucial role in accessing soil potentials and practical intervention responses in rice production systems. Synthetic fertilizer applications and cultivation practices are considered key factors affecting nutrient dynamics and availability. Here, we assessed the nutrient dynamics in surface, subsurface water and soil under local water management and conventional rice cultivation practices in the Vietnamese Mekong Delta.

Methods We implemented a field experiment (200 m  2) in the 2018 wet season and the 2019 dry season in a triple rice-cropping field. Surface water, subsurface water (30–45 cm), and topsoil (0–20 cm) were collected eight samples during the rice-growing seasons to clarify its nutrient dynamic.

Results The results showed that N-NH  4 +, P-PO  4 3- and total P peaks were achieved after fertilizing. Irrespective of seasons, the nutrient content in surface water was always greater than that of subsurface water ( P<0.001), with the exception of N-NO  3 -, no significant difference was disclosed ( P>0.05). When comparing the wet and dry seasons, nutrient concentrations exhibited minor differences ( P>0.05). Under conventional rice cultivation, the effects of synthetic fertilizer topdressing on the total N, soil organic matter (SOM), and total P were negligible in the soil. Higher rates of N fertilizer application did not significantly increase soil N-NH  4 +, total N, yet larger P fertilizer amounts substantially enhanced soil total P ( P<0.001).

Conclusions Under conventional rice cultivation, the low concentration of N-NH  4 +, P-PO  4 3- and total P in the subsurface water indicated that nutrient losses mainly occur through runoff rather than leaching. Notably, nutrient content in soil was fairly high, whilst SOM was varied from low to medium between seasons. Future work should consider the nutrient balance and nutrient dynamic simulation on surface and subsurface.
Filosofía Aplicada durante la pandemia: bailando en la Noosfera.
Authors: Marinoff Lou
Published: January 2023

: Este ensayo reflexiona sobre los problemas no médicos generalizados que plantea la pandemia, especialmente su intensificación del trasplante de la conciencia humana a dominios virtuales. Resucitando la concepción de la noosfera de Teilhard de Chardin de 1922, “la envoltura pensante de la tierra”, ilustramos cómo la tradición digital que Chardin anticipó surgió de las tradiciones orales, escritas y visuales que la precedieron. Identificamos algunos defectos de percepción de la noosfera, en términos de sus efectos nocivos sobre la cognición y la socialización. También evaluamos algunas dificultades epistémicas y políticas que surgen de los intentos de controlar la “fuente de poder” de la noosfera, a saber, la conciencia misma. Finalmente, citamos breves ejemplos de la filosofía india, la mitología griega, la literatura victoriana, la tradición cabalística y la especulación cosmobiológica, todos los cuales ofrecen marcos explicativos para interpretar la pandemia. Implícita y explícitamente, este discurso llama a los practicantes de la filosofía a la acción, ya que tanto el COVID-19 como su población acelerada de la noosfera plantean una plétora de preocupaciones humanas no médicas pero vitales. Los consejeros filosóficos están posicionados para ayudar a la humanidad a reconcebirse y, por lo tanto, reinventarse a sí misma, en caminos constructivos, durante estos tiempos difíciles. Y con ese fin, también necesitamos adaptar nuestras prácticas filosóficas a la noosfera; porque, como la filosofía misma, es un producto de la conciencia racional.
Determining the Accuracy of the Triangular and PERT Distributions
Authors: Khan Imran A. , Bickel J. Eric , Hammond Robert K.
Published: January 2023

The Triangular and PERT (Program Evaluation Review Technique) distribution probability density functions are commonly used in decision and risk analyses. These distributions are popular because they are each specified by only three points (two support bounds and the mode) that are believed to be easy to assess from experts or data. In this paper, we carefully analyze how close the Triangular and PERT distributions are to other distributions sharing the same support and mode and show that the errors induced by the Triangular and PERT distributions are significant. We further show that distributions that are characterized by the median tend to provide a better fit than do those that are characterized by the mode.

Funding: This research was supported by the Equinor Fellows Program and the Operating System 2.0 research program developed by the Construction Industry Institute.
Diagnostic Tools for Evaluating and Comparing Simulation-Optimization Algorithms
Authors: Eckman David J. , Henderson Shane G. , Shashaani Sara
Published: January 2023

Simulation optimization involves optimizing some objective function that can only be estimated via stochastic simulation. Many important problems can be profitably viewed within this framework. Whereas many solvers—implementations of simulation-optimization algorithms—exist or are in development, comparisons among solvers are not standardized and are often limited in scope. Such comparisons help advance solver development, clarify the relative performance of solvers, and identify classes of problems that defy efficient solution, among many other uses. We develop performance measures and plots, and estimators thereof, to evaluate and compare solvers and diagnose their strengths and weaknesses on a testbed of simulation-optimization problems. We explain the need for two-level simulation in this context and provide supporting convergence theory. We also describe how to use bootstrapping to obtain error estimates for the estimators.

History: Accepted by Bruno Tuffin, area editor for simulation.

Funding: This work was supported by the National Science Foundation [Grants CMMI-2035086, CMMI-2206972, and TRIPODS+X DMS-1839346].

Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplementary Information [ https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.1261 ] or is available from the IJOC GitHub software repository ( https://github.com/INFORMSJoC ) at [ http://dx.doi.org/10.5281/zenodo.7329235 ].
The Impact of Optimized Fleets in Transportation Networks
Authors: Battifarano Matthew , Qian Sean
Published: January 2023

Connected technologies have engendered a paradigm shift in mobility systems by enabling digital platforms to coordinate large sets of vehicles in real time. Recent research has investigated how a small number of connected vehicles may be coordinated to reduce total system cost. However, platforms may coordinate vehicles to optimize a fleet-wide objective which is neither user nor system optimal. We study the behavior of optimized fleets in mixed traffic and find that, at small penetrations, fleets may worsen system cost relative to user equilibrium, and provide a concrete example of this paradox. Past a critical penetration level, however, optimized fleets reduce system cost in the network, up to achieving system optimal traffic flow, without need for an external subsidy. We introduce two novel notions of fleet-optimal mixed equilibria: critical fleet size for user equilibrium (CFS-UE) and critical fleet size for system optimum (CFS-SO). We demonstrate on the Sioux Falls and Pittsburgh networks that 33% and 83% of vehicles, respectively, must participate in the fleet to achieve system optimum. In Pittsburgh, we find that, although fleets permeate the network, they accumulate on highways and major arterials; the majority of origin-destination pairs are either occupied exclusively by users or by the fleet. Critical fleet size offers regulators greater insight into where fleet and system interests align, transportation planners a novel metric to evaluate road improvements, and fleet coordinators a better understanding of their efforts to optimize their fleet.

History: This paper has been accepted for the Transportation Science Special Issue on Emerging Topics in Transportation Science and Logistics.

Funding: This work was supported by the U.S. Department of Transportation [Mobility21] and the National Science Foundation [CMMI-1931827].

Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2022.1189 .
Machine learning for enhanced healthcare: an overview for operational and clinical leads
Authors: Roberts Luke , Dhanoa Harpreet , Lanes Sadie , Holdship Jonathan
Published: January 2023

Machine learning has the potential to transform how healthcare is delivered. It can support clinical decision making, determine the risk, presence and prognosis of disease and help optimise patient pathways. Widespread use and access to digital health records mean implementing machine learning models is quicker and easier than ever before. It is imperative for clinical and operational leads to understand the principles behind machine learning, so they can evaluate how it may be helpful to them and their teams. This article provides an overview of machine learning and how it can be used to help solve common healthcare-related problems.
Strategies to Retain Employees in the IT Industry: The Case In India
Authors:   Chitkara Business School, Chitkara University, Punjab, India, Nijjer Shivinder , Sood Kiran ,   Chitkara Business School, Chitkara University, Punjab, India, Grima Simon ,   Department of Insurance and Risk Management, Faculty of Economics, Management and Accountancy, University of Malta, Malta
Published: January 2023

Although the Information Technology (IT) sector accounts for the highest contribution to Gross Development Product in India, it has high employee turnover. This turnover is a waste of investment and detracts from organizations’ knowledge and experience pools. Person organization (PO) fit theories posit that when people are hired by and for organizations (not just individual jobs), they are less likely to quit. This study examines the benefits provided by IT firms to retain their employees and how these benefits’ effectiveness vary by designation and firm. It does so by employing the ‘work environment congruence’ approach to PO fit. Moreover, it proposes how to build a strategic model of the mix of benefits for retaining staff at different position levels (designations) in the firm. Findings show that preferred benefits differ by designation. For all factors except location, organization does not play an important role in retention, but designation impacts it in all the factors. Keywords: Retention strategies, Retaining employees, Information technology, Indian IT industry.
Prevention and Management of Sudden Cardiac Death in Athletes
Authors: Thiagarajan Alwar , Prakash Ayyadurai , Janani Gopalakrishnan , Rao Vikram , Arumugam Sivaraman
Published: January 2023

Sudden cardiac death (SCD) is the biggest challenge of all sports emergencies, as it is the leading cause of preventable deaths in both professional and recreational athletes. There is also an ongoing concern about COVID-19-associated cardiac pathology among athletes because myocarditis is an important cause of SCD during exercise. Hypertrophic cardiomyopathy represents 24% of SCD and Sudden Unexplained Death (normal heart at autopsy) represents 34% of SCD. To make sports participation safer, it is important to synergistically combine primary prevention of SCD by pre-participation identification of athletes affected by at-risk cardiomyopathies and secondary prevention with backup defibrillation of unpredictable sudden cardiac arrest on the field. The prompt application of an automated external defibrillator itself is associated with a greater likelihood of survival. With the advancement in the field of sports cardiology, the implantation of implantable cardioverter defibrillator has been promising in getting the athlete back on the field including in contact sports. Hence, knowledge of primary and secondary prevention is of great importance in reducing the incidence of SCD as well as improvising existing strategies.
Exchange nailing, for atrophic non-union of the tibia, after implant breakage, post a non-traumatic event
Authors: Sane Rohit Mahesh , Parelkar Kedar Anil , Shetty Sunil Hiriyanna
Published: January 2023

Background: The most feared complication of fracture management is non-union. Non-union can be of the following types, hypertrophic, oligotrophic, atrophic, and septic. In view of a non-union, exchange nailing is preferred and so routinely performed for non-unions and fractures of the tibia. Case Presentation: Here, we present a case of an implant failure from an atraumatic event in a case of atrophic non-union of the tibia, which was treated by exchange nailing and bone grafting. A 22-year-old male, with a history of the left closed tibia fibula diaphysis fracture 1 year ago, underwent exchange nailing with bone grating after having an atrophic non-union with implant breakage. Conclusion: Implant failure and non-union are caused due to a wide variety of factors. Appropriate implant selection for fracture type, reaming, fracture site compression, good reduction, and adequate and early mobilization are important factors for a satisfactory union and prevention of secondary surgeries.
A Lumpy-Bumpy Painful Ankle – Trevor Disease of the Ankle in a 9-year-old
Authors: Dhillon Mandeep Singh , Dhillon Mehar , Patel Sandeep , Sharma Siddhartha
Published: January 2023

Introduction: Dysplasia epiphysealis hemimelica, also known as Trevor disease, is a rare skeletal development disorder of childhood, characterized by asymmetric growth of the epiphyseal cartilage in childhood. The disease can be locally aggressive at the ankle, and can result in deformity or instability. We present a case of Trevor disease involving the lateral aspect of distal tibia and talus in a 9-year-old patient, and of highlight its clinical and radiological presentation, treatment, and outcomes. Case Report: A 9-year-old male presented with a painful swelling over the lateral aspect of the dorsum of right ankle and foot swelling for the past 1.5 years. Radiographs and computed tomography scan revealed exostoses arising from the lateral distal tibial epiphysis and talar dome. Skeletal survey revealed cartilaginous exostoses in distal femoral epiphyses, confirming the diagnosis. Wide resection was done, and the patients were asymptomatic and recurrence-free at 8 months follow-up. Conclusion: Trevor disease around the ankle can have an aggressive course. Prompt recognition and timely surgical excision can prevent morbidity, instability, and deformity.
Functional Scaphoid Pseudarthrosis. Two Cases with Long-term Follow-up after Closed Wedge Osteotomy of the Distal Radius
Authors: Mastrantonakis Konstantinos N , Daskalogiannakis Emmanouil I , Papadaki Haris I , Kalinterakis Georgios , Liodakis Konstantinos , Prevezanos Dionysios
Published: January 2023

Introduction: Closed wedge osteotomy of the distal radius represents a treatment option for the advanced scaphoid pseudarthrosis. Few authors have reported good results with many of the cases achieving union of the scaphoid. The aim of this study is to inform about the functional long-term outcome of two patients in whom bone union was not achieved after this procedure. Case Report: In this article, we present two patients, one with 5 and one with 40 years of follow-up who were treated with closed wedge osteotomy of the distal radius due to advanced scaphoid nonunion. We evaluated the functional outcome which was excellent and in addition radial translocation of the carpus was found as it was compared the anteroposterior radiographs before surgery and at the end of the follow-up period. Conclusion: Closed wedge osteotomy of the radius is an extra articular procedure that can cause radial translocation of the wrist and change its biomechanics, while the functional outcome does not depend on whether fracture healing is achieved.
Responsivity enhancement of a PtSi photodetector with graphene by the photogating effect
Authors: Mehrfar Amir Hossein , Majd Abdollah Eslami
Published: January 2023

In this paper, by adding graphene to the platinum silicide (PtSi) photodetector and using the photogating effect, the responsivity is significantly improved in the PtSi photodetector. In this photodetector, the PtSi layer detects the light, and the graphene increases the responsivity with the photogating effect. The responsivity of the PtSi photodetector with graphene is 1.5 A/W in the optical power of 13.6 µW. The responsivity in the PtSi photodetector with graphene and without graphene is compared. By adding graphene to the PtSi photodetector, the responsivity is much improved compared to the conventional PtSi photodetector.
Fiber-based photon-pair generation: tutorial
Authors: Garay-Palmett Karina , Kim Dong Beom , Zhang Yujie , Domínguez-Serna Francisco A. , Lorenz Virginia O. , U’Ren Alfred B.
Published: January 2023

The purpose of this tutorial paper is to present a broad overview of photon-pair generation through the spontaneous four wave mixing (SFWM) process in optical fibers. Progress in optical fiber technology means that today we have at our disposal a wide variety of types of fiber, which, together with the fact that SFWM uses two pump fields, implies a truly remarkable versatility in the resulting possible photon-pair properties. We discuss how the interplay of frequency, transverse mode, and polarization degrees of freedom—the first linked to the latter two through fiber dispersion—leads to interesting entanglement properties both in individual degrees of freedom and also permitting hybrid and hyper entanglement in combinations of degrees of freedom. This tutorial covers methods for photon-pair factorability, frequency tunability, and SFWM bandwidth control, the effect of frequency non-degenerate and counterpropagating pumps, as well as methods for characterizing photon pairs generated in optical fibers.
Modulating optical vortices in an Airy beam by the electromagnetically induced transparency
Authors: Wang Zhiguo , Zheng Rui , Hu ZhiYu , Liu Tiancong , Yang Xiaoxi , Zhang Yanpeng
Published: January 2023

We have introduced vortex fields in an Airy beam using interference between the lobes of the Airy beam, which is different from the previous method to generate optical vortices in an Airy beam. Compared to the interference of Gaussian beams, the vortex introduced by the interference between the Airy lobes is more robust due to the nondiffraction property of an Airy beam. The formation and disappearance of the vortex fields can be modulated by the electromagnetically induced transparency (EIT) effect and the probe field power. Specifically, no optical vortices are formed because interference between the lobes of an Airy beam cannot occur if there is a weak probe field. The EIT effect can control the generation and disappearance of the vortex field when the probe field power is critical. In the meantime, the vortex field changes the energy distribution in an Airy beam because of constructive and destructive interference in the main lobe and the side lobes. In particular, the EIT effect also can be used to regulate the position of the vortex phase singularity. We achieved Airy vortex beam regulation using multiparameters, which we believe can play a significant role in complex optical micromanipulation.
τ-algorithm for gathering spectroscopic information by modeling emission line shapes: application to laser-induced plasmas
Authors: Díaz Pace D. M. , Molina M. J.
Published: January 2023

In this work, a fitting algorithm was implemented and applied to analyze emission line shapes in laser-induced breakdown spectroscopy. By modeling emission spectral lines, the optical thickness was calculated for each line of interest and the intensity line profiles were computed and matched to measured spectra. The algorithm was applied to analyze the experimental profiles of a hydrogen

H

α

line at 6562.8 Å, and the resonant lines of Mg II at 2795.5 Å and at 2802.7 Å. Spectroscopic information was obtained about the physical processes occurring in the plasma, such as self-absorption and Stark broadening. The results demonstrated the potential of the developed method to provide valuable information in plasma spectroscopy for both fundamental and applied research.
Numerical modeling of continuous wave intracavity self-Raman lasers considering the influence of the thermal effect
Authors: Ma Yayun , Yang Fen
Published: January 2023

A space-dependent theoretical model is developed to study the influence of the thermal effect on the characteristics of self-Raman lasers. The performances of the Raman laser are well researched by solving rate equations numerically. The simulation results show that the performance of the Raman laser can be improved by narrowing the linewidth of the fundamental field and using an output coupler with optimum transmission for 880 nm and 914 nm pump wavelengths. Also, cooling the temperature of the crystal for the 880 nm pump wavelength and heating the crystal temperature appropriately for the 914 nm pump wavelength are promising routes to further improve the Raman power.
Conservation of orbital angular momentum throughout amplification of high order harmonics in Ni-like krypton and silver plasmas
Authors: López Santiago , de la Fuente Elena , Alonso Agustín , Pandey Alok Kumar , Guilbaud Olivier , Oliva Eduardo
Published: January 2023

In this article we present modelling results of the amplification of High Order Harmonics (HOH) carrying orbital angular momentum (OAM) in plasma amplifiers created from krypton gas and silver solid targets. The resulting amplified beam is characterized in terms of intensity, phase and decomposition in helical and Laguerre-Gauss modes. Results show that the amplification process conserves OAM, although some degradation is apparent. Several structures appear in the intensity and phase profiles. These structures have been characterized with our model and related to refraction and interference with the plasma self-emission. Thus, these results not only demonstrate the capability of plasma amplifiers to deliver HOH amplified beams carrying OAM but also pave the way towards using HOH carrying OAM as a probe beam to diagnose the dynamics of hot, dense plasmas.
From picture to 3D hologram: end-to-end learning of real-time 3D photorealistic hologram generation from 2D image input
Authors: Chang Chenliang , Dai Bo , Zhu Dongchen , Li Jiamao , Xia Jun , Zhang Dawei , Hou Lianping , Zhuang Songlin
Published: January 2023

In this Letter, we demonstrate a deep-learning-based method capable of synthesizing a photorealistic 3D hologram in real-time directly from the input of a single 2D image. We design a fully automatic pipeline to create large-scale datasets by converting any collection of real-life images into pairs of 2D images and corresponding 3D holograms and train our convolutional neural network (CNN) end-to-end in a supervised way. Our method is extremely computation-efficient and memory-efficient for 3D hologram generation merely from the knowledge of on-hand 2D image content. We experimentally demonstrate speckle-free and photorealistic holographic 3D displays from a variety of scene images, opening up a way of creating real-time 3D holography from everyday pictures. © 2023 Optical Society of America
Lensless holographic microscope with a time and memory-saving algorithm for large-volume imaging of organoids
Authors: Zheng Weiqiang , Wang Juan , Zhou Yunhong , Zeng Qiang , Zhang Cheng , Liu Li , Yu Hui , Yang Yuting
Published: January 2023

Organoids, the 3D culture systems derived from stem cells, are promising models for human organs. However, organoid study requires large-volume imaging with single cell resolution, which is beyond the spatial bandwidth limit of conventional optical microscopy. Herein, we propose a lensless holographic microscope empowered with a time and memory-saving algorithm. It solves the trade-off between the imaging field of view, resolution, and processing speed, and provides a practical tool for the study of organoids. We first build a compact microscopy system using a multi-angle LED illumination scheme and an on-chip structure. Then we develop a fast angular spectrum formula for fast reconstruction of oblique-illuminated coaxial holography under the under-sampling condition. Additionally, we derive a multi-angle illuminated filtered backpropagation algorithm to achieve high-precision and slice-wise recovery of 3D structures of objects. The reconstruction process demands only 1/50 of the memory required by a traditional optical diffraction tomography algorithm. Experimental results indicate that the proposed method can achieve 6.28 mm × 4.71 mm × 0.37 mm volume imaging within 104 s. Through the standardized polystyrene beads test, we demonstrate that the proposed microscope has micrometer-scale resolution in both lateral and axial directions. In addition, the 3D imaging results of salivary gland organoids show great application prospects of the proposed method in the field of living biological sampling imaging.
Selectively reflective edge detection system based on cholesteric liquid crystal
Authors: Zeng Tibin , Xie Jin , Zhou Yingjie , Fan Fan , Wen Shuangchun
Published: January 2023

Optical analog computing has attracted extensive interest in image processing and optical engineering in recent decades. Here, we propose a reflective optical analog computing system based on a cholesteric liquid crystal (CLC), which simplifies the traditional optical analog computing system by taking advantage of the CLC reflecting the light with specified circular polarization and provides a new, to the best of our knowledge, idea for the integration of optical analog computing systems. Meanwhile, we present results in which a section of an insect foot is observed using the reflective optical analog computing system, which may develop valuable applications in biomedical imaging.
Ultrawide dynamic modulation of perfect absorption with a Friedrich–Wintgen BIC
Authors: Gao Enduo , Jin Rong , Fu Zhenchu , Cao Guangtao , Deng Yan , Chen Jian , Li Guanhai , Chen Xiaoshuang , Li Hongjian
Published: January 2023

Dynamical control of perfect absorption plays an indispensable role in optical switch and modulators. However, it always suffers from the limited modulation range, small depth, and susceptible absorption efficiencies. Here, we propose a new strategy based on Friedrich–Wintgen bound states in the continuum (F–W BICs) to realize a tunable perfect absorber with large dynamic modulation range. For proof of concept, we demonstrate a pentaband ultrahigh absorption system consisting of graphene gratings and graphene sheets through elaborately tuning F–W BIC. The nature of the F–W BIC arises from the destructive interference between Fabry–Perot resonance and guided mode resonance modes in the coherent phase-matching condition. The radiation channels are avoided from crossing. The BIC can be dynamically modulated by engineering the Fermi level of graphene gratings, which breaks the traditional modulation methods with an incidence angle. Remarkably, the perfect absorber with this F–W BIC approach achieves the largest modulation range of up to 3.5 THz. We believe that this work provides a new way to dynamically engineer perfect absorption and stimulates the development of multiband ultracompact devices.
Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons
Authors: Roussel Yann , Verasztó Csaba , Rodarie Dimitri , Damart Tanguy , Reimann Michael , Ramaswamy Srikanth , Markram Henry , Keller Daniel
Published: January 2023

Knowledge of the cell-type-specific composition of the brain is useful in order to understand the role of each cell type as part of the network. Here, we estimated the composition of the whole cortex in terms of well characterized morphological and electrophysiological inhibitory neuron types (me-types). We derived probabilistic me-type densities from an existing atlas of molecularly defined cell-type densities in the mouse cortex. We used a well-established me-type classification from rat somatosensory cortex to populate the cortex. These me-types were well characterized morphologically and electrophysiologically but they lacked molecular marker identity labels. To extrapolate this missing information, we employed an additional dataset from the Allen Institute for Brain Science containing molecular identity as well as morphological and electrophysiological data for mouse cortical neurons. We first built a latent space based on a number of comparable morphological and electrical features common to both data sources. We then identified 19 morpho-electrical clusters that merged neurons from both datasets while being molecularly homogeneous. The resulting clusters best mirror the molecular identity classification solely using available morpho-electrical features. Finally, we stochastically assigned a molecular identity to a me-type neuron based on the latent space cluster it was assigned to. The resulting mapping was used to derive inhibitory me-types densities in the cortex.
Ten simple rules for using public biological data for your research
Authors: Oza Vishal H. , Whitlock Jordan H. , Wilk Elizabeth J. , Uno-Antonison Angelina , Wilk Brandon , Gajapathy Manavalan , Howton Timothy C. , Trull Austyn , Ianov Lara , Worthey Elizabeth A. , Lasseigne Brittany N.
Published: January 2023

With an increasing amount of biological data available publicly, there is a need for a guide on how to successfully download and use this data. The 10 simple rules for using public biological data are: (1) use public data purposefully in your research; (2) evaluate data for your use case; (3) check data reuse requirements and embargoes; (4) be aware of ethics for data reuse; (5) plan for data storage and compute requirements; (6) know what you are downloading; (7) download programmatically and verify integrity; (8) properly cite data; (9) make reprocessed data and models Findable, Accessible, Interoperable, and Reusable (FAIR) and share; and (10) make pipelines and code FAIR and share. These rules are intended as a guide for researchers wanting to make use of available data and to increase data reuse and reproducibility.
Ten simple rules for implementing open and reproducible research practices after attending a training course
Authors: Heise Verena , Holman Constance , Lo Hung , Lyras Ekaterini Maria , Adkins Mark Christopher , Aquino Maria Raisa Jessica , Bougioukas Konstantinos I. , Bray Katherine O. , Gajos Martyna , Guo Xuanzong , Hartling Corinna , Huerta-Gutierrez Rodrigo , Jindrová Miroslava , Kenney Joanne P. M. , Kępińska Adrianna P. , Kneller Laura , Lopez-Rodriguez Elena , Mühlensiepen Felix , Richards Angela , Richards Gareth , Siebert Maximilian , Smith James A. , Smith Natalie , Stransky Nicolai , Tarvainen Sirpa , Valdes Daniela Sofia , Warrington Kayleigh L. , Wilpert Nina-Maria , Witkowska Disa , Zaneva Mirela , Zanker Jeanette , Weissgerber Tracey L.
Published: January 2023

Open, reproducible, and replicable research practices are a fundamental part of science. Training is often organized on a grassroots level, offered by early career researchers, for early career researchers. Buffet style courses that cover many topics can inspire participants to try new things; however, they can also be overwhelming. Participants who want to implement new practices may not know where to start once they return to their research team. We describe ten simple rules to guide participants of relevant training courses in implementing robust research practices in their own projects, once they return to their research group. This includes (1) prioritizing and planning which practices to implement, which involves obtaining support and convincing others involved in the research project of the added value of implementing new practices; (2) managing problems that arise during implementation; and (3) making reproducible research and open science practices an integral part of a future research career. We also outline strategies that course organizers can use to prepare participants for implementation and support them during this process.
Informing antimicrobial stewardship with explainable AI
Authors: Cavallaro Massimo , Moran Ed , Collyer Benjamin , McCarthy Noel D. , Green Christopher , Keeling Matt J.
Published: January 2023

The accuracy and flexibility of artificial intelligence (AI) systems often comes at the cost of a decreased ability to offer an intuitive explanation of their predictions. This hinders trust and discourage adoption of AI in healthcare, exacerbated by concerns over liabilities and risks to patients’ health in case of misdiagnosis. Providing an explanation for a model’s prediction is possible due to recent advances in the field of interpretable machine learning. We considered a data set of hospital admissions linked to records of antibiotic prescriptions and susceptibilities of bacterial isolates. An appropriately trained gradient boosted decision tree algorithm, supplemented by a Shapley explanation model, predicts the likely antimicrobial drug resistance, with the odds of resistance informed by characteristics of the patient, admission data, and historical drug treatments and culture test results. Applying this AI-based system, we found that it substantially reduces the risk of mismatched treatment compared with the observed prescriptions. The Shapley values provide an intuitive association between observations/data and outcomes; the associations identified are broadly consistent with expectations based on prior knowledge from health specialists. The results, and the ability to attribute confidence and explanations, support the wider adoption of AI in healthcare.
Reinforcing personalized persuasion in task-oriented virtual sales assistant
Authors: Raut Aritra , Tiwari Abhisek , Das Subrata , Saha Sriparna , Maitra Anutosh , Ramnani Roshni , Sengupta Shubhashis
Published: January 2023

Purpose

Existing task-oriented virtual agents can assist users with simple tasks like ticket booking, hotel reservations, etc. effectively and with high confidence. These virtual assistants, however, assume specific, predictable end-user behavior, such as predefined/servable objectives, which results in conversation failures in challenging situations, such as when goals are unavailable.

Methodology

Inspired by the practice and its efficacy, we propose an end-to-end framework for task-oriented persuasive dialogue generation that combines pre-training and reinforcement learning for generating context-aware persuasive responses. We utilize four novel rewards to improve consistency and repetitiveness in generated responses. Additionally, a meta-learning strategy has also been utilized to make the model parameters better for domain adaptation. Furthermore, we also curate a personalized persuasive dialogue (PPD) corpus, which contains utterance-level intent, slot, sentiment, and persuasion strategy annotation.

Findings

The obtained results and detailed analysis firmly establish the effectiveness of the proposed persuasive virtual assistant over traditional task-oriented virtual assistants. The proposed framework considerably increases the quality of dialogue generation in terms of consistency and repetitiveness. Additionally, our experiment with a few shot and zero-shot settings proves that our meta-learned model learns to quickly adopt new domains with a few or even zero no. of training epochs. It outperforms the non-meta-learning-based approaches keeping the base model constant.

Originality

To the best of our knowledge, this is the first effort to improve a task-oriented virtual agent’s persuasiveness and domain adaptation.
The impact of gender and age on bullying role, self-harm and suicide: Evidence from a cohort study of Australian children
Authors: Ahmad Kabir , Beatson Amanda , Campbell Marilyn , Hashmi Rubayyat , Keating Byron W. , Mulcahy Rory , Riedel Aimee , Wang Shasha
Published: January 2023

There has been limited longitudinal investigation to date into the association between bullying, self-harm, and suicidality in Australia and the impact of specific demographic differences on this relationship. This is despite the continued rise in the incidence of bullying, self-harm, and suicide. As such, the current study draws on data from the Longitudinal Survey of Australian children (LSAC) to examine the association between bullying, self-harm, and suicidality and explore the impact of demographic differences across three bullying related behaviors (being bullied, bullying others and being both bullied and bullying others). The evidence indicates that bully-victims exhibit the highest risk of self-harm and suicidality in Australia. When considering demographic differences, it was identified that females and adolescents aged 16-17-years-of-age had the highest risk of self-harm and suicidality. Further, a direct curvilinear relationship between age and the categories of self-harm was identified with an inflection point around 16–17 years. The study supports the need for further investigation into the association between bullying, self-harm, and suicidality longitudinally with a particular focus on other moderators.
Motion artifact reduction for magnetic resonance imaging with deep learning and k-space analysis
Authors: Cui Long , Song Yang , Wang Yida , Wang Rui , Wu Dongmei , Xie Haibin , Li Jianqi , Yang Guang
Published: January 2023

Motion artifacts deteriorate the quality of magnetic resonance (MR) images. This study proposes a new method to detect phase-encoding (PE) lines corrupted by motion and remove motion artifacts in MR images. 67 cases containing 8710 slices of axial T2-weighted images from the IXI public dataset were split into three datasets, i.e., training (50 cases/6500 slices), validation (5/650), and test (12/1560) sets. First, motion-corrupted k-spaces and images were simulated using a pseudo-random sampling order and random motion tracks. A convolutional neural network (CNN) model was trained to filter the motion-corrupted images. Then, the k-space of the filtered image was compared with the motion-corrupted k-space line-by-line, to detect the PE lines affected by motion. Finally, the unaffected PE lines were used to reconstruct the final image using compressed sensing (CS). For the simulated images with 35%, 40%, 45%, and 50% unaffected PE lines, the mean peak signal-to-noise ratio (PSNRs) of resulting images (mean±standard deviation) were 36.129±3.678, 38.646±3.526, 40.426±3.223, and 41.510±3.167, respectively, and the mean structural similarity (SSIMs) were 0.950±0.046, 0.964±0.035, 0.975±0.025, and 0.979±0.023, respectively. For images with more than 35% PE lines unaffected by motion, images reconstructed with proposed algorithm exhibited better quality than those images reconstructed with CS using 35% under-sampled data (PSNR 37.678±3.261, SSIM 0.964±0.028). It was proved that deep learning and k-space analysis can detect the k-space PE lines affected by motion and CS can be used to reconstruct images from unaffected data, effectively alleviating the motion artifacts.
Transforming brownfields into urban greenspaces: A working process for stakeholder analysis
Authors: Chowdhury Shaswati , Kain Jaan-Henrik , Adelfio Marco , Volchko Yevheniya , Norrman Jenny
Published: January 2023

Urban greenspaces (UGS) provide a range of ecosystem services and are instrumental in ensuring the liveability of cities. Whilst incorporating UGS in increasingly denser cities is a challenge to planners, brownfields form a latent resource with the potential of being converted into UGS. Transformation of brownfields to greenspaces, however, requires engagement of a variety of stakeholders, from providers to users. The overall aim of this study was to support effective and realistic realisations of UGS in the context of urban brownfields’ regeneration and stakeholder engagement. A working process was developed to: 1) integrate methods relevant for UGS realisation for a) identification and categorising of relevant stakeholders, b) mapping their interests and resources, c) identifying various challenges, and d) matching those challenges with the mapped resources over the timeline of UGS development; and 2) apply these methods to assess relevance and shortcomings. The methods were applied to a study site in Sweden, and data was collected using a questionnaire survey. The survey received 31 responses and the respondents’ comments indicated that the combination of several uses, especially integrated with an urban park, is preferable. Visualisation was an important component for data analysis: stakeholder categorisation was effectively visualised using a Venn diagram, and the needed mobilisation of resources among stakeholders to manage identified challenges was visualised using a timeline. The analysis demonstrates the need for collaboration between stakeholders to achieve an effective realisation of UGS and how multiple methods can be used in concert to map stakeholders, preferences, challenges, and resources for a particular site. The application at a study site provided site-specific data but the developed stakeholder categorisation, and the method for matching identified challenges with the stakeholders’ resources using a timeline, can be generalised to applications at other sites.
Giant clams as open-source, scalable reef environmental biomonitors
Authors: Killam Daniel , Thompson Diane , Morgan Katherine , Russell Megan
Published: January 2023

Valvometry, the electronic measurement of bivalve shell opening and closing, has been demonstrated to be a valuable biomonitoring technique in previous ecological and environmental studies. Valvometric data has been shown to relate significantly to pollution, predation, animal stress and feeding activity. However, there is a need for valvometric techniques applicable to coral reef environments, which may provide critical insights into reef resilience to ocean warming and acidification. Giant clams are endemic to coral reefs and hold great promise as valvometric recorders of light availability, productivity and other environmental variables. Despite this promise, prior valvometric work on giant clams has been limited by specialized hardware less accessible to developing countries where many coral reefs are found. Here we report on an open-source approach that uses off-the-shelf components to monitor smooth giant clam (Tridacna derasa) valve opening behavior, and tests this approach in the simulated reef environment of the Biosphere 2 Ocean. Valvometric data corroborates the influence of light availability on diurnal behavior of giant clams. The clams basked during daylight hours to expose their photosymbionts to light, and adopted a partially-closed defensive posture at night. The animals showed variations in the frequency of complete closures, with most occurring during night-time hours when the animals prioritize filter-feeding activity, clapping their valves to expel pseudofeces from their gills. Closure frequency showed a significant relation to pH and a significant lagged relationship to chlorophyll-a productivity, which are both a function of algal productivity in the Biosphere 2 Ocean tank. These results suggest that the animals fed on phytoplankton following periodic bloom events in the Biosphere 2 Ocean during the experiment. We propose that giant clams exhibit behavioral plasticity between individuals and populations, and advocate for the more widespread use of valvometry to enable comparative studies of reef environment and animal health.