bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved MAX-MIN method to estimate total magnetization direction using Wiener filtering
Authors: Wang Tianchi , Liu Shuang , Zuo Boxin , Hu Xiangyun
Published: September 2022

Knowledge of the total magnetization direction is useful for forward modeling and reduction-to-the-pole (RTP) of magnetic anomalies. However, remanent magnetization deviates the total magnetization direction from the induced magnetization direction; therefore, it is essential to determine the correct direction of total magnetization. Theoretically, the MAX-MIN method, which searches for the position of the maximum value of the function that comprises the minimum values of the RTP field with different directions, can yield the correct direction of total magnetization. However, such estimations of direction usually indicate large errors in comparison with the results of crosscorrelation methods, which calculate the correlation coefficient between the RTP field and the magnetic magnitude transforms. Our analysis reveals that noise is the primary cause of the inaccuracy in estimation results. We have improved the MAX-MIN method using Wiener filtering based on the principle of least-mean-squares deviation. The k-means clustering algorithm clusters points that are as closely connected as possible, while ensuring that the distances between clusters are as large as possible. Therefore, the k-means clustering algorithm is used to divide the radial logarithmic power spectrum into the effective signal with low wavenumbers and the noisy signal with high wavenumbers. Then, the Wiener filtering RTP operator is constructed using the slope and intercept of the fitted straight line in the corresponding wavenumber bands. The improved MAX-MIN method is tested using magnetic anomalies of spherical and combined cuboid models with different levels of added Gaussian noise and different total magnetization directions. The improved MAX-MIN method is applied to the magnetic anomaly in the Yeshan region (eastern China) and the Taihe region (southwestern China). Results indicate that the improved MAX-MIN method based on the principle of least-mean-squares deviation could obtain reliable estimation of direction from noisy magnetic anomaly data.
Enhancing one-way wave equation-based migration with deep learning
Authors: Yu Yuwei , Li Yaxing , Wu Xinming , Jia Xiaofeng
Published: September 2022

One advantage of one-way wave equation-based migration is its low computational cost. However, due to the limited wavefield propagation angle, it is difficult to use one-way wave equation-based migration for high-precision imaging of structures with large inclinations due to issues such as inaccurate amplitudes and migration image artifacts. In addition, when the model has large horizontal velocity differences, it is difficult for the one-way wave propagator to calculate an accurate wavefield phase. Reverse time migration (RTM) based on the two-way wave propagator has a high resolution and avoids the issues associated with one-way wave propagators; however, it has a high computational cost in practical applications. We develop a convolutional neural network (CNN) application mode that improves one migration method by learning from another one and design a CNN with a structure similar to U-net that combines the advantages of both migration methods. The CNN label is the RTM result, and the corresponding input is the result of one-way wave migration with a generalized screen propagator (GSP). The trained CNN model improves the amplitude in the one-way wave migration image and removes the errors caused by large lateral velocity perturbations. Moreover, by maintaining the high migration calculation efficiency, our CNN model allows for a high resolution, few artifacts, and accurate images of steep structures in the one-way wave migration result. With our method, the accuracy of the one-way wave migration result is close to that of the RTM result. The use of GSP-based migration in our CNN model rather than conventional RTM to generate prospecting images can considerably reduce the calculation costs.
Deep unfolding dictionary learning for seismic denoising
Authors: Sui Yuhan , Wang Xiaojing , Ma Jianwei
Published: September 2022

Seismic denoising is an essential step for seismic data processing. Conventionally, dictionary learning (DL) methods for seismic denoising always assume the representation coefficients to be sparse and the dictionary to be normalized or a tight frame. Current DL methods need to update the dictionary and the coefficients in an alternating iterative process. However, the dictionary obtained from the DL method often needs to be recalculated for different input data. Moreover, the performance of DL for seismic noise removal is related to the parameter selection and the prior constraints of dictionary and representation coefficients. Recently, deep learning demonstrates promising performance in data prediction and classification. Following the architecture of DL algorithms strictly, we have developed a novel and interpretable deep unfolding dictionary learning (DUDL) method for seismic denoising by unfolding the iterative algorithm of DL into a deep neural network (DNN). The proposed architecture of DUDL contains two main parts: the first is to update the dictionary and representation coefficients using least-squares inversion and the second is to apply a DNN to learn the prior representation of dictionary and representation coefficients, respectively. Numerical synthetic and field examples find the effectiveness of our method. More importantly, this method for seismic denoising obtains the dictionary for different seismic data adaptively and is suitable for seismic data with different noise levels.
On the role of artificial intelligence in psychiatry
Authors: Rocheteau Emma
Published: September 2022

Recently, there has been growing interest in artificial intelligence (AI) to improve efficiency and personalisation of mental health services. So far, the progress has been slow, however, advancements in deep learning may change this. This paper discusses the role for AI in psychiatry, in particular (a) diagnosis tools, (b) monitoring of symptoms, and (c) delivering personalised treatment recommendations. Finally, I discuss ethical concerns and technological limitations.
Improving Dose-Optimization Processes Used in Oncology Drug Development to Minimize Toxicity and Maximize Benefit to Patients
Authors: Fourie Zirkelbach Jeanne , Shah Mirat , Vallejo Jonathon , Cheng Joyce , Ayyoub Amal , Liu Jiang , Hudson Rachel , Sridhara Rajeshwari , Ison Gwynn , Amiri-Kordestani Laleh , Tang Shenghui , Gwise Thomas , Rahman Atiqur , Pazdur Richard , Theoret Marc R.
Published: September 2022

This review highlights strategies to integrate dose optimization into premarketing drug development and discusses the underlying statistical principles. Poor dose optimization can have negative consequences for patients, most commonly because of toxicity, including poor quality of life, reduced effectiveness because of inability of patients to stay on current therapy or receive subsequent therapy because of toxicities, and difficulty in developing combination regimens. We reviewed US Food and Drug Administration initial approvals (2019-2021) of small molecules and antibody-drug conjugates for oncologic indications to determine the proportion with a recommended dosage at the maximum tolerated dose or the maximal administered dose, to characterize the use of randomized evaluations of multiple dosages in dose selection, to describe the frequency of dose modifications at the recommended dosage, and to identify case examples that highlight key principles for premarket dose optimization during drug development. Herein, we highlight major principles for dose optimization and review examples of recent US Food and Drug Administration approvals that illustrate how investigation of dose- and exposure-response relationships and use of randomized dose trials can support dose optimization. Although there has been some progress, dose optimization through randomized dose evaluation in oncology trials is not routinely conducted. Dose optimization is essential to ensure that patients receive therapies which maximize efficacy while minimizing toxicity.
Collective phenomena in a quasi-classical electron fluid within the interpolational self-consistent method of moments
Authors: Syzganbayeva S. A. , Ara J. , Askaruly A. , Ashikbayeva A. B. , Tkachenko I. M. , Arkhipov Y. V.
Published: September 2022

Collective processes in a quasi-classical electron gas are investigated within the framework of the interpolational self-consistent method of moments, which makes it possible to express the dispersion and decrement of plasma waves, and the dynamic structural factor of the system exclusively in terms of its static structural factor so that five sum rules are satisfied automatically. Different models are used of the static structure factor; the stability and robustness of the results of the moment approach taking into account the accuracy of these models is confirmed and tested by comparison to the alternative molecular dynamics simulation data.
Standardized Interview Scoring Methodology for Neurosurgical Residency Applicant Selection
Authors: Soni Pranay , Davison Mark A. , Battisti Elizabeth A. , Schmidt Eric S. , Benzel Edward C. , Steinmetz Michael P. , Schlenk Richard P. , Benzil Deborah L.
Published: September 2022

Interviews are critical to the neurosurgery resident application process. The COVID-19 pandemic forced residency interview activities are conducted virtually. To maintain a degree of control during a period of uncertainty, our department implemented a standardized survey for interviewers to evaluate the noncognitive attributes and program compatibility of applicants. Our objective was to assess the reliability and biases associated with our standardized interviewer survey implemented in neurosurgical residency interviews. A 5-question interviewer survey to assess applicant interview performance and program compatibility was implemented during the 2020 to 2021 interview season. After the application cycle, survey metrics were retrospectively reviewed. Multiple cohort analyses were performed by dividing interviewers into cohorts based on status (faculty or resident) and sex. Applicant scores were assessed within sex subgroups for each aforementioned interviewer cohort. Intraclass correlation coefficients (ICCs) were calculated to assess survey reliability. Fifteen interviewers (8 faculty and 7 residents) and 35 applicants were included. Female applicants (17%) and interviewers (20%) comprised the minority. There were no differences between resident and faculty reviewer scores; however, female reviewers gave higher overall scores than male reviewers (P = .003). There was no difference in total scores between female and male applicants when evaluating all reviewers or subgroups of faculty, residents, females, or males. ICC analysis demonstrated good (ICC 0.75-0.90) or excellent (ICC > 0.90) reliability for all questions and overall score. The standardized interviewer survey was a feasible and reliable method for evaluating noncognitive attributes during neurosurgery residency interviews. There was no perceptible evidence of sex bias in our single-program experience.
Mesenchymal FGFR1 and FGFR2 control patterning of the ureteric mesenchyme by balancing SHH and BMP4 signaling
Authors: Deuper Lena , Meuser Max , Thiesler Hauke , Jany Ulrich W. H. , Rudat Carsten , Hildebrandt Herbert , Trowe Mark-Oliver , Kispert Andreas
Published: September 2022

The coordinated development of the mesenchymal and epithelial progenitors of the murine ureter depends on a complex interplay of diverse signaling activities. We have recently shown that epithelial FGFR2 signaling regulates stratification and differentiation of the epithelial compartment by enhancing epithelial Shh expression, and mesenchymal SHH and BMP4 activity. Here, we show that FGFR1 and FGFR2 expression in the mesenchymal primordium impinges on the SHH/BMP4 signaling axis to regulate mesenchymal patterning and differentiation. Mouse embryos with conditional loss of Fgfr1 and Fgfr2 in the ureteric mesenchyme exhibited reduced mesenchymal proliferation and prematurely activated lamina propria formation at the expense of the smooth muscle cell program. They also manifested hydroureter at birth. Molecular profiling detected increased SHH, WNT and retinoic acid signaling, whereas BMP4 signaling in the mesenchyme was reduced. Pharmacological activation of SHH signaling in combination with inhibition of BMP4 signaling recapitulated the cellular changes in explant cultures of wild-type ureters. Additional experiments suggest that mesenchymal FGFR1 and FGFR2 act as a sink for FGF ligands to dampen activation of Shh and BMP receptor gene expression by epithelial FGFR2 signaling.
A desert bee thermoregulates with an abdominal convector during flight
Authors: Johnson Meredith G. , Glass Jordan R. , Harrison Jon F.
Published: September 2022

Flying endothermic insects thermoregulate, likely to improve flight performance. Males of the Sonoran Desert bee, Centris caesalpiniae, seek females at aggregations beginning at sunrise and cease flight near midday when the air temperature peaks. To identify the thermoregulatory mechanisms for C. caesalpiniae males, we measured tagma temperature, wingbeat frequency, water loss rate, metabolic rate and tagma mass of flying bees across shaded air temperatures of 19–38°C. Surface area, wet mass and dry mass declined with air temperature, suggesting that individual bees do not persist for the entire morning. The largest bees may be associated with cool, early mornings because they are best able to warm themselves and/or because they run the risk of overheating in the hot afternoons. Thorax temperature was high (38–45°C) and moderately well regulated, while head and abdomen temperatures were cooler and less controlled. The abdominal temperature excess ratio increased as air temperature rose, indicating active heat transfer from the pubescent thorax to the relatively bare abdomen with warming. Mass-specific metabolic rate increased with time, and air and thorax temperatures, but wingbeat frequency did not vary. Mass-specific water loss rate increased with air temperature, but this was a minor mechanism of thermoregulation. Using a heat budget model, we showed that whole-body convective conductance more than doubled through the morning, providing strong evidence that the primary mechanism of regulating thorax temperature during flight for these bees is increased use of the abdomen as a convector at higher air temperatures.
Spontaneous coronary artery dissection in cutis laxa
Authors: Charters Pia Frances Pemberton , McKenzie Daniel Barnaby , Rodrigues Jonathan Carl Luis , Loughborough William Wynn
Published: September 2022

We describe the case of a 21-year-old female with Cutis Laxa presenting with an acute coronary syndrome. A CT coronary angiogram (CTCA) diagnosed spontaneous coronary artery dissection (SCAD) of the right coronary artery, which was successfully managed with medical therapy. Cutis Laxa is a rare connective-tissue disorder in which the skin becomes inelastic. Lax, redundant skin hangs in folds give a prematurely aged appearance and several forms of the disease have been described. Although certain cardiovascular complications are recognised in Cutis Laxa, to our knowledge SCAD has not been previously described.

SCAD is an uncommon cause of acute coronary syndrome and sudden cardiac death. The condition particularly affects young females, those with connective tissue diseases, arteriopathies, pregnant females, contraceptive use and cocaine use. Atherosclerotic risk factors are seldom reported. The condition is underdiagnosed as symptoms may not generate a high index of clinical suspicion in this demographic. Diagnosis is traditionally made on invasive coronary angiogram although the procedure carries risks in SCAD and non-invasive CTCA should be considered in appropriately selected patient cohorts or as an adjunctive measure to assess for extracoronary vascular abnormalities. Our patient was diagnosed on CTCA, avoiding the need for invasive catheter angiogram.
Conserved and transcript-specific functions of the RESC factors, RESC13 and RESC14, in kinetoplastid RNA editing
Authors: Sortino Katherine , Tylec Brianna L. , Chen Runpu , Sun Yijun , Read Laurie K.
Published: September 2022

Uridine insertion/deletion RNA editing is an extensive post-transcriptional modification of mitochondrial mRNAs in kinetoplastid organisms, includingTrypanosoma brucei. This process is carried out usingtrans-acting gRNAs and complex protein machinery. The essential RNA editing substrate binding complex (RESC) serves as the scaffold that modulates protein and RNA interactions during editing, and contains the guide RNA binding complex (GRBC), the RNA editing mediator complexes (REMCs), and organizer proteins. Despite the importance of RESC in editing, the functions of each protein comprising this complex are not completely understood. Here, we further define the roles of a REMC protein, RESC13, and a RESC organizer, RESC14, using high-throughput sequencing on two large pan-edited mRNAs, A6 and COIII. When comparing our analyses to that of a previously published small pan-edited mRNA, RPS12, we find that RESC13 has conserved functions across the three transcripts with regard to editing initiation, gRNA utilization, gRNA exchange, and restricting the formation of long misedited junctions that likely arise from its ability to modulate RNA structure. However, RESC13 does have transcript-specific effects on the types of long junctions whose formation it restricts. RESC14 has a conserved effect on gRNA utilization across the three transcripts analyzed, but has transcript-specific effects on editing initiation, gRNA exchange, and junction formation. Our data suggest that transcript-specific effects of both proteins are due to differences in transcript length and sequences as well as transcript-specific protein interactions. These findings highlight the importance of studying multiple transcripts to determine the function of editing factors.
Empowerment Mitigates Gender Differences in Tertius Iungens Brokering
Authors: Nicolaou Nicos , Kilduff Martin
Published: September 2022

Tertius iungens brokering that brings together people who might not otherwise meet is crucial for organizational effectiveness. But we know little about whether and why women and men differ in their propensity to engage in this brokering. Our paper focuses on the origins and mitigation of gender differences in the propensity to bring people together. In study 1, we showed that the Totterdell et al. (2008) propensity-to-join-others scale that we used in study 2 and the Obstfeld (2005) tertius iungens scale overlapped not only conceptually, but also empirically, and that these measures of tertius iungens were distinct from mediation- and separation-brokering propensities (Grosser et al. 2019). In study 2, we used a natural experiment to examine the tertius iungens brokering propensities of 876 identical and 625 fraternal same-sex twins. We found that brokering propensity was lower for women than for men, although the propensity toward sociability in terms of making friends and acquaintances was lower for men. We also found that for women, relative to men, tertius iungens brokering propensity was largely affected by environmental influences, such as the experience of stereotyping and discrimination, rather than representing an inherited disposition. Moreover, the differences between men and women with respect to brokering were mitigated for empowered samples, such as well-educated or entrepreneurial individuals. Our research asks new questions about how environmental pressures and empowerment affect social networking. Gender differences in brokering may be amenable to mitigation through empowering practices that include education and entrepreneurial experience.
Population-Level Evidence of the Gender Gap in Technology Entrepreneurship
Authors: Miric Milan , Yin Pai-Ling , Fehder Daniel C.
Published: September 2022

This study investigates the gender gap in entrepreneurship in the technology industry. Digitization has created vast economic opportunities in the technology sector and has lowered many barriers to entry, thus reducing traditional frictions regarding entrepreneurship and potentially increasing opportunities for female founders. However, anecdotal evidence has suggested that female technology founders are rare and that women are underrepresented in science, technology, engineering, and mathematics roles. Based on individual career histories collected from more than 42 million U.S.-based LinkedIn profiles, including more than 1.3 million founders, we explore whether there are higher rates of female founders in technology companies relative to other industries. Our analysis revealed the following: (1) Females were only half as likely as males to found businesses in the technology industry. (2) Females were less likely to found successive businesses (i.e., serial founders), which was even more pronounced in the technology industry. (3) When we used the gender gap in labor force participation as a baseline, the gender gap in technology entrepreneurship was particularly large, even compared with other male-dominated industries (e.g., construction). (4) The gender gap in technology entrepreneurship was driven by lower rates of entrepreneurship by females in lower positions in the organizational hierarchy. In contrast, females who reached the C-suite in technology sectors were 16% more likely to found firms compared with their female C-suite counterparts in nontechnology industries. Combined, the results provide a nuanced view of the gender gap in entrepreneurship.

Funding: Research support was provided by the Grief Center for Entrepreneurship Research and the Institute for Outlier Research in Business.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsc.2022.0170 .
The voice of ostomates: an exploration of stoma care in England
Authors: Bowles Theresa M , Moses Claire , Perry-Woodford Zarah L
Published: September 2022

Background:

This article is part one of a series presenting the findings of stakeholder surveys with ostomates and stoma care nurses for stoma services in England. Due to the volume of data and publication limits this article focuses on the views and experiences of 2504 people living with a stoma (ostomates).

Aim:

To understand the experience of ostomates in relation to the current services provided in hospital and at home, the delivery of care and views on areas that work well and areas that require improvement.

Methods:

Ostomates were asked to share their experiences in a national online survey, promoted via multiple organisations. The survey included sections for respondent demographics, interactions with the stoma care nurse (SCN), products and dispensing services, as well as patients' experiences relating to both hospital-based care and home-based care. Free-text responses relating to service delivery in hospital and at home were coded and thematically analysed.

Findings:

Results are presented, and verbatim quotes used to demonstrate themes. These include care provision and access to visits from the SCN, physical and psychological care, information sharing, specialist knowledge and products.

Conclusion:

Overall, the survey respondents praised the care given, however, the experiences and views shared via the survey show significant variation in the care and services received. This article presents the findings of a survey of ostomates living in England. A second article, presenting the findings about the experiences of stoma care nurses will be published in a forthcoming issue.
Prescribing in physiotherapy
Authors: Robertson Deborah
Published: September 2022

Deborah Robertson provides an overview of recently published articles that may be of interest to non-medical prescribers. Should you wish to look at any of the papers in more detail, a full reference is provided
Characterization of the shallow subsurface structure across the Carrascoy Fault System (SE Iberian Peninsula) using P-wave tomography and Multichannel Analysis of Surface Waves
Authors: Handoyo Handoyo , DeFelipe I , Martín Banda R , García Mayordomo J , Martí D , Martínez Díaz J.J , Insua Arévalo J.M , Teixidó T , Palomeras I , Alcalde J , Carbonell R
Published: September 2022

The seismicity in the SE Iberian Peninsula is distributed parallel to the coast in a well-developed strike-slip fracture system known as the Eastern Betic Shear Zone (EBSZ). This work focuses on the characterization of the shallow subsurface structure of the Algezares-Casas Nuevas Fault, within the Carrascoy Fault System of the EBSZ. The Carrascoy Fault borders the Guadalentín Depression to the south, which is a densely populated area with extensive agricultural activity. Therefore, this faults system represents a seismic hazard with significant social and economic implications. We have constructed two velocity-depth models based on P-wave tomography and Multichannel Analysis of Surface Waves (MASW) acquired from seismic reflection data. The resulting velocity models have allowed us to interpret the first ~250m depth and have revealed: i) the thickness of the critical zone; ii) the geometry of the Algezares-Casas Nuevas Fault; iii) the depth of the Messinian/Tortonian contact and iv) the presence of blind thrusts and damage zones under the Guadalentín Depression. Our results have also helped us to estimate an apparent vertical slip rate of 0.66±0.06m/ky for the Algezares-Casas Nuevas Fault since 209.1±6.2ka. Our results provide a methodological and backflow protocol to study the shallow subsurface of active faults, complementing previous geological models based on paleoseismological trenches, and can be used to improve the seismic hazard assessment of tectonically active regions around the world.
Arte y Cultura en procesos de transformación de entornos conflictivos. La Comuna 13 de Medellín
Authors: ÁLVAREZ DOMÍNGUEZ MÓNICA ENRIQUETA , TRACHANA ANGELIQUE
Published: September 2022

La acción colectiva y la resiliencia de la Comuna 13 de Medellín, en Colombia, después del conflicto armado y el narcotráfico que posicionaban el barrio como el lugar más peligroso y violento de América Latina, ha sido detonada por una intervención pública que mejoró el acceso con unas escaleras eléctricas. En torno a este acontecimiento, ha surgido un movimiento artístico de participación comunitaria, que por medio del arte mural como herramienta de comunicación no verbal y con un alto valor simbólico, ha modificado los imaginarios colectivos y ha mitigado las problemáticas sociales, consecuencia también de la mejora de las condiciones económicas por la atracción turística desencadenada. En este tipo de procesos, juega un papel significativo la difusión mediática como parte integral de la cultura globalizada que capitaliza las singularidades culturales para el turismo y el sistema de consumos de masas y que, sin embargo, han beneficiado los implicados con una mejora de su autopercepción y autoestima.
Non-uniform illumination underwater image enhancement via events and frame fusion
Authors: Bi Xiuwen , Wang Pengfei , Wu Tao , Zha Fusheng , Xu Peng
Published: September 2022

Absorption and scattering by aqueous media can attenuate light and cause underwater optical imagery difficulty. Artificial light sources are usually used to aid deep-sea imaging. Due to the limited dynamic range of standard cameras, artificial light sources often cause underwater images to be underexposed or overexposed. By contrast, event cameras have a high dynamic range and high temporal resolution but cannot provide frames with rich color characteristics. In this paper, we exploit the complementarity of the two types of cameras to propose an efficient yet simple method for image enhancement of uneven underwater illumination, which can generate enhanced images containing better scene details and colors similar to standard frames. Additionally, we create a dataset recorded by the Dynamic and Active-pixel Vision Sensor that includes both event streams and frames, enabling testing of the proposed method and frame-based image enhancement methods. The experimental results conducted on our dataset with qualitative and quantitative measures demonstrate that the proposed method outperforms the compared enhancement algorithms.
Quality-aware resource provisioning for multiband elastic optical networks: a deep-learning-assisted approach
Authors: Jana Rana Kumar , Chatterjee Bijoy Chand , Singh Abhishek Pratap , Srivastava Anand , Mukherjee Biswanath , Lord Andrew , Mitra Abhijit
Published: September 2022

Multiband elastic optical network (MB-EON) technology can help to sustain exponential traffic growth in the optical backbone network. However, multiband operation creates high inter-channel stimulated Raman scattering, leading to a high nonlinear impairment (NLI) that may severely affect the optical signal-to-noise ratio (OSNR) of a lightpath. Additionally, the severity of NLI on the channel of interest depends upon the choice of allocated wavelength. Hence, appropriate channel allocation may cumulatively lead to a higher network capacity. This paper proposes a quality-aware resource provisioning scheme in the context of MB-EON that selectively chooses the available channels from different bands in order to achieve the maximum network capacity in the long run. A deep neural network-assisted quality of transmission estimator is considered to estimate the OSNR of a lightpath with accuracy of 99.65% and 0.012 dB variance in estimation error. The performance of our algorithm in the proposed scheme, namely, optical signal-to-noise ratio adaptive first–last-fit (OA-FLF), is analyzed for two geographically diverse networks, namely, BT-UK and the 24-node USA network, in terms of traffic admissibility, quality of established lightpaths, and contiguous aligned available slot ratio (CAASR), and compared with four state-of-the-art baseline algorithms: first fit, last fit, route adaptive first–last-fit, and distance adaptive first–last-fit. Numerical results indicate that the proposed algorithm outperforms all of the baseline algorithms in terms of traffic admissibility. Reported results show that, compared to the baseline algorithms, consideration of the effect of NLI before resource allocation in the OA-FLF algorithm can provide a maximum gain of nearly 30% in terms of traffic admissibility for smaller networks such as BT-UK, whereas, for longer geography such as the 24-node USA network, this traffic admissibility gain becomes close to 61% till 1% blocking.
GeO2-doped ring-core photonic crystal fiber for supporting robust orbital angular momentum modes
Authors: Zhou Jingmin , Xie Shuyang , Nie Chen , Li Lin , Shan Zhengping , Liu Exian
Published: September 2022

Orbital angular momentum (OAM)-mode-supported photonic crystal fibers (PCFs) have inspired intensive research in modern fiber optics due to the robust propagation and theoretically unlimited signal-carried channels. In this paper, a dual-cladding

G
e
O

2

-doped ring-core PCF is designed, and a strategy for optimizing OAM mode properties is analyzed by structure parameters and

G
e
O

2

-doping concentration. Numeric results show that high structural degrees of freedom are available to improve the effective refractive index separation (within the vector modes), chromatic dispersion, effective mode field area, nonlinear coefficient, and OAM mode purity in terms of inner cladding, outer cladding, and ring-core. In particular, the effective refractive index separation and chromatic dispersion can exhibit a high order magnitude of

10

−
3

and a low value in the broad band from 1.3 µm to 1.7 µm, respectively. In addition to structural optimization, doping high index material into the ring-core is another way to regulate the fiber performance by controlling the doping concentration. A systematic investigation shows that as the doping concentration increases, the effective refractive index separation and mode purity increase obviously, while the dispersion and mode field area gradually decrease. This flexible manipulation offers a method for customizing the optical properties of OAM-supported PCFs in communication and sensor systems.
Single-pixel imaging with Gao-Boole patterns
Authors: Gao Zihan , Li Minghui , Zheng Peixia , Xiong Jiahao , Tang Zikang , Liu Hong-Chao
Published: September 2022

Single-pixel imaging (SPI) can perceive the world using only a single-pixel detector, but long sampling times with a series of patterns are inevitable for SPI, which is the bottleneck for its practical application. Developing new patterns to reduce the sampling times might provide opportunities to address this challenge. Based on the Kronecker product of Hadamard matrix, we here design a complete set of new patterns, called Gao-Boole patterns, for SPI. Compared to orthogonal Hadamard basis patterns with elements valued as +1 or −1, our Gao-Boole patterns are non-orthogonal ones and the element values are designed as +1 or 0. Using our Gao-Boole patterns, the reconstructed quality of a target image (N × N pixels) is as high as the Hadamard one but only with half pattern numbers of the Hadamard ones, for both full sampling (N2 for Gao-Boole patterns, 2N2 for Hadamard basis patterns) and undersampling cases in experiment. Effectively reducing the patterns numbers and sampling times without sacrificing imaging quality, our designed Gao-Boole patterns provide a superior option for structural patterns in SPI and help to steer SPI toward practical imaging application.
Deep optical reservoir computing and chaotic synchronization predictions based on the cascade coupled optically pumped spin-VCSELs
Authors: Zhong Dongzhou , Zhao Keke , Xu Zhe , Hu Yalan , Deng Wanan , Hou Peng , Zhang Jinbo , Zhang Jianming
Published: September 2022

In this work, we utilize two cascade coupling modes (unidirectional coupling and bidirectional coupling) to construct a four-layer deep reservoir computing (RC) system based on the cascade coupled optically-pumped spin-VCSEL. In such a system, there are double sub-reservoirs in each layer, which are formed by the chaotic x-PC and y-PC emitted by the reservoir spin-VCSEL in each layer. Under these two coupling modes, the chaotic x-PC and y-PC emitted by the driving optically-pumped spin-VCSEL (D-Spin-VCSEL), as two learning targets, are predicted by utilizing the four-layer reservoirs. In different parameter spaces, it is further explored that the outputs of the double sub-reservoirs in each layer are respectively synchronized with the chaotic x-PC and y-PC emitted by the D-Spin-VCSEL. The memory capacities (MCs) for the double sub-reservoirs in each layer are even further investigated. The results show that under two coupling modes, the predictions of the double sub-reservoirs with higher-layer for these two targets have smaller errors, denoting that the higher-layer double sub-reservoirs possess better predictive learning ability. Under the same system parameters, the outputs of the higher-layer dual parallel reservoirs are better synchronized with two chaotic PCs emitted by the D-Spin-VCSEL, respectively. The larger MCs can also be obtained by the higher-layer double reservoirs. In particular, compared with the four-layer reservoir computing system under unidirectional coupling, the four-layer reservoir computing system under bidirectional coupling shows better predictive ability in the same parameter space. The chaotic synchronizations predicted by each layer double sub-reservoirs under bidirectional coupling can be obtained higher qualities than those under unidirectional coupling. By the optimization of the system parameters, the outputs of the fourth-layer double sub-reservoirs are almost completely synchronized with the chaotic x-PC and y-PC emitted by the D-Spin-VCSEL, respectively, due to their correlation coefficient used to measure synchronization quality can be obtained as 0.99. These results have potential applications in chaotic computation, chaotic secure communication and accurate prediction of time series.
Magneto-optical diffractive deep neural network
Authors: Fujita Takumi , Sakaguchi Hotaka , Zhang Jian , Nonaka Hirofumi , Sumi Satoshi , Awano Hiroyuki , Ishibashi Takayuki
Published: September 2022

We propose a magneto-optical diffractive deep neural network (MO-D2NN). We simulated several MO-D2NNs, each of which consists of five hidden layers made of a magnetic material that contains 100 × 100 magnetic domains with a domain width of 1 µm and an interlayer distance of 0.7 mm. The networks demonstrate a classification accuracy of > 90% for the MNIST dataset when light intensity is used as the classification measure. Moreover, an accuracy of > 80% is obtained even for a small Faraday rotation angle of π/100 rad when the angle of polarization is used as the classification measure. The MO-D2NN allows the hidden layers to be rewritten, which is not possible with previous implementations of D2NNs.
Monocular kilometer-scale passive ranging by point-spread function engineering
Authors: Opatovski Nadav , Xiao Dafei , Harari Gal , Shechtman Yoav
Published: September 2022

Standard imaging systems are designed for 2D representation of objects, while information about the third dimension remains implicit, as imaging-based distance estimation is a difficult challenge. Existing long-range distance estimation technologies mostly rely on active emission of signal, which as a subsystem, constitutes a significant portion of the complexity, size and cost of the active-ranging apparatus. Despite the appeal of alleviating the requirement for signal-emission, passive distance estimation methods are essentially nonexistent for ranges greater than a few hundreds of meters. Here, we present monocular long-range, telescope-based passive ranging, realized by integration of point-spread-function engineering into a telescope, extending the scale of point-spread-function engineering-based ranging to distances where it has never been tested before. We provide experimental demonstrations of the optical system in a variety of challenging imaging scenarios, including adversarial weather conditions, dynamic targets and scenes of diversified textures, at distances extending beyond 1.7 km. We conclude with brief quantification of the effect of atmospheric turbulence on estimation precision, which becomes a significant error source in long-range optical imaging.
175 W average power from a single-core rod fiber-based chirped-pulse-amplification system
Authors: Pedersen Martin E. V. , Johansen Mette M. , Olesen Anders S. , Michieletto Mattia , Gaponenko Maxim , Maack Martin D.
Published: September 2022

We report on a fiber-based chirped-pulse-amplification laser system with bulk transmission grating compression to a pulse duration of 357 fs, average power of 175 W, and pulse energy of

233

μ

J

. The compressed pulse train has a beam quality factor M2 of 1.21. The power amplifier is based on a state-of-the-art single-mode photonic crystal rod-type ytterbium-doped fiber operating at 248 W of average power and a repetition rate of 750 kHz. The long-term stability of the laser system has been tested continuously for more than 4000 hours and shows no sign of transverse mode instability.
A nested U-shaped network for accurately predicting directional scattering of all-dielectric nanostructures
Authors: Liu Wenjing , Wang Xianghui , Zeng Ming
Published: September 2022

Forward prediction of directional scattering from all-dielectric nanostructures by a two-level nested U-shaped convolutional neural network (U2-Net) is investigated. Compared with the traditional U-Net method, the U2-Net model with lower model height outperforms for the case of a smaller image size. For the input image size of 40 × 40, the prediction performance of the U2-Net model with the height of three is enhanced by almost an order of magnitude, which can be attributed to the more excellent capacity in extracting richer multi-scale features. Since it is the common problem in nanophotonics that the model height is limited by the smaller image size, our findings can promote the nested U-shaped network as a powerful tool applied to various tasks concerning nanostructures.
Nonlinear focusing of supercontinuum driven by intense mid-infrared pulses in gas-filled capillaries
Authors: Gao Xiaohui
Published: September 2022

Strong mid-infrared light–matter interactions have attracted extensive attention as they open up new frontiers in nonlinear optics. Here we observe through simulations a novel, to the best of our knowledge, aspect of mid-infrared pulse dynamics in a high-pressure gas-filled capillary, where a pulse with a power well below the critical power for Kerr self-focusing undergoes an astonishing increase of the peak intensity following an extremely efficient spectral broadening. This intensity enhancement is attributed to the Kerr-induced focusing of the supercontinuum. Our study provides an interesting perspective for controlling the laser intensity with possible applications in nonlinear light conversion driven by mid-infrared pulses.
THO-OFDM scheme for visible light communication with noise suppression and dimming control
Authors: Li Yibin , Wei Zixian , Wang Zhaoming , Ali Amjad , Li Qian , Fu H. Y.
Published: September 2022

In recent years, visible light communication (VLC) has emerged as a dual-use technique for illumination as well as communication. In VLC system, dimming control is deemed to be an essential functionality for luminous intensity adjusting and energy saving. In this Letter, a noise-suppressed triple-layer hybrid optical orthogonal frequency division multiplexing (NSTHO-OFDM) is proposed and further combined with pulse width modulation (PWM) to achieve the functionality of dimming control. The proposed NSTHO-OFDM can attain a 4.28-dB maximum power gain compared with THO-OFDM with an overall bit error rate (BER) of 1 × 10−4. Moreover, the proposed dimming scheme can achieve a wide dimming range of 89.0% while maintaining a favorable BER below 3.8 × 10−3.
CINS: Cell Interaction Network inference from Single cell expression data
Authors: Yuan Ye , Cosme Carlos , Adams Taylor Sterling , Schupp Jonas , Sakamoto Koji , Xylourgidis Nikos , Ruffalo Matthew , Li Jiachen , Kaminski Naftali , Bar-Joseph Ziv
Published: September 2022

Studies comparing single cell RNA-Seq (scRNA-Seq) data between conditions mainly focus on differences in the proportion of cell types or on differentially expressed genes. In many cases these differences are driven by changes in cell interactions which are challenging to infer without spatial information. To determine cell-cell interactions that differ between conditions we developed the Cell Interaction Network Inference (CINS) pipeline. CINS combines Bayesian network analysis with regression-based modeling to identify differential cell type interactions and the proteins that underlie them. We tested CINS on a disease case control and on an aging mouse dataset. In both cases CINS correctly identifies cell type interactions and the ligands involved in these interactions improving on prior methods suggested for cell interaction predictions. We performed additional mouse aging scRNA-Seq experiments which further support the interactions identified by CINS.
Genome-wide analysis identifies Homothorax and Extradenticle as regulators of insulin in Drosophila Insulin-Producing cells
Authors: Winant Mattias , Buhler Kurt , Clements Jason , De Groef Sofie , Hens Korneel , Vulsteke Veerle , Callaerts Patrick
Published: September 2022

Drosophila Insulin-Producing Cells (IPCs) are the main production site of the Drosophila Insulin-like peptides or dilps which have key roles in regulating growth, development, reproduction, lifespan and metabolism. To better understand the signalling pathways and transcriptional networks that are active in the IPCs we queried publicly available transcriptome data of over 180 highly inbred fly lines for dilp expression and used dilp expression as the input for a Genome-wide association study (GWAS). This resulted in the identification of variants in 125 genes that were associated with variation in dilp expression. The function of 57 of these genes in the IPCs was tested using an RNAi-based approach. We found that IPC-specific depletion of most genes resulted in differences in expression of one or more of the dilps. We then elaborated further on one of the candidate genes with the strongest effect on dilp expression, Homothorax, a transcription factor known for its role in eye development. We found that Homothorax and its binding partner Extradenticle are involved in regulating dilp2, -3 and -5 expression and that genetic depletion of both TFs shows phenotypes associated with reduced insulin signalling. Furthermore, we provide evidence that other transcription factors involved in eye development are also functional in the IPCs. In conclusion, we showed that this expression level-based GWAS approach identified genetic regulators implicated in IPC function and dilp expression.
Effect of the COVID-19 pandemic on health service utilization across regions of Ethiopia: An interrupted time series analysis of health information system data from 2019–2020
Authors: Mebratie Anagaw Derseh , Nega Adiam , Gage Anna , Mariam Damen Haile , Eshetu Munir Kassa , Arsenault Catherine
Published: September 2022

The spread of COVID-19 and associated deaths have remained low in Ethiopia. However, the pandemic could pose a public health crisis indirectly through disruptions in essential health services. The aim of this study was to examine disruptions in health service utilization during the first nine months of the COVID-19 pandemic across 10 regions in Ethiopia. We analyzed utilization of 21 different health services across all of Ethiopia (except the Tigray region) for the period of January 2019 to December 2020. Data were extracted from the Ethiopian district health information system (DHIS2). Monthly visits in 2020 were graphed relative to the same months in 2019. Interrupted time series analysis was used to estimate the effect of the pandemic on service utilization in each region. We found that disruptions in health services were generally higher in urban regions which were most affected by COVID. Outpatient visits declined by 52%, 54%, and 58%, specifically in Dire Dawa, Addis Ababa and Harari, the three urban regions. Similarly, there was a 47% reduction in inpatient admissions in Addis Ababa. In agrarian regions, the pandemic caused an 11% to 17% reduction in outpatient visits and a 10% to 27% decline in inpatient admissions. Visits for children with diarrhea, pneumonia and malnutrition also declined substantially while maternal health services were less affected. Our study indicates that disruptions in health services were more pronounced in areas that were relatively harder hit by the pandemic. Our results show that the Ethiopian health system has a limited capacity to absorb shocks. During future waves of COVID or future pandemics, the Ethiopian health system must be better prepared to maintain essential services and mitigate the indirect impact of the pandemic on public health, particularly in urban areas.