bluuebunny/crossref_metadata_2025 huggingface dataset:
The Photoelastic Constant of (0001) 4H Silicon Carbide Determined by Scanning Infrared Polariscopy
Authors: Herms Martin , Irmer Gert , Spira Susanne , Wagner Matthias
Published: July 2021

The piezo‐optic coefficients (π11‐π12) and the photoelastic constant Cσ of on‐axis (0001) 4H silicon carbide at λ = 1.3 μm are determined to (−3.3 ± 0.5) × 10−13 and (−2.8 ± 0.4) × 10−12 Pa−1, respectively. The experiment is conducted using a scanning infrared depolarization imager (SIRD) that uses a rotational mode for wafer scanning equipped with a special calibration setup for diametrical loading of 150 mm diameter wafers. The loading force is varied by gradually setting the wafer rotation frequency. (π11–π12) and Cσ are determined by analyzing the dependence of the shear stress equivalent on the loading force in the wafer center. This calibration procedure is made difficult by the pronounced inhomogeneous defect distribution on the wafer under study. Furthermore, the unloaded wafer is characterized using the multipolarization analysis on the base of an eccentric measurement mode. The resulting map of the shear stress maximum τmax completed by the direction of the large principal stress component reveals that the outer wafer part is tensile stressed in circumferential direction like a ring with magnitudes up to 10 MPa.
High‐Performance AlGaN‐Based Solar‐Blind UV Photodetectors for Sensing Applications
Authors: Chen Yiping , Zheng Chaohong , Chen Yiren
Published: July 2021

The full solid‐state, intrinsic cutoff solar‐blind UV photodetectors are widely used in the military and civilian fields. Herein, to achieve real‐time solar‐blind UV signal detection for application in portable equipment, the material epitaxy, device fabrication, and performance characterization of high‐performance back‐illuminated AlGaN‐based solar‐blind UV photodetectors are conducted at first. Based on the photodetector, a discrete signal amplifier circuit is subsequently designed and prepared to fulfill the weak solar‐blind signal detection. Through assembling the amplifier circuit with the AlGaN‐based solar‐blind UV photodetector, it can output real‐time voltage signal with different amplitude according to the intensity of the incident UV light signal. This study is of great significance for developing a portable solar‐blind UV detection system.
Accelerated Design of Battery Materials Interfaces by Embedded‐Atom‐Inspired Bond Valence Sum Forcefields
Authors: Pu Yuhan , Dai Ruoyu , Adams Stefan
Published: July 2021

To achieve higher energy density in safer energy storage systems, a transition to ceramic all‐solid‐state batteries is widely expected. Their performance and cycle‐life is largely controlled by processes at buried interfaces. While experimental operando probing of interfacial processes is under development, first‐principle computational methods are challenged by the complexity of the multiphase models and long simulation periods required to capture slow degradation processes. Thus, simpler empirical reactive forcefields have the potential to substantially accelerate the design and optimization of all‐solid‐state batteries, provided that parameters are available for a wide range of relevant atom types. The energy‐scaled bond valence‐based softBV forcefield has successfully enabled the design of new solid electrolytes or insertion‐type electrode materials and analyses of ion transport processes therein. As a two‐body forcefield, it enables fast simulations for complex structures over long periods, but inevitably shares the tendency of two‐body forcefields to maximize coordination numbers if free volume facilitates a reorganization of the atoms, which makes them less suitable for studying interfacial processes. Herein, this vulnerability of two‐body forcefields is overcome in a computationally efficient way by introducing an embedded‐atom‐method‐inspired bond‐valence‐sum‐based new class of transferable forcefields and its effective use for modeling of surfaces and interfaces is demonstrated.
Evaluation of operational system structures based on reliability data
Authors: Polansky Alan M. , Ryu Duchwan
Published: July 2021

Systems of components have a structure that plays an important role in determining how the reliability of the individual components relates to the reliability of the system. The system reliability can be computed from component reliabilities using results from basic probability theory in the simplest case with all of the components assumed to act independently of one another. However, in the case of dependence, such calculations can be much more involved. When reliability data have been independently collected on both the system and each component in the system, it can be difficult to model any possible dependence between components. Established methods use the known structure of a system, along with these data, to assess whether the reliability of the individual components are mutually independent. In this paper, we expand this methodology to include an assessment of the type of dependence that may exist between the components. This is based on finding the system structure that would most likely produce the observed reliability data, under independence. In the frequentist setting, the likelihood approach is used to find these structures and an observed confidence measure is used to assess the strength of the statistical evidence in favor of each possible structure. In the Bayesian setting, posterior probabilities along with Bayes factors are used. An example demonstrates how these methods can be used in an applied setting.
Reliability analysis of systems with discrete event data using association rules
Authors: He Kangzhe , Liu Bin , Xie Min , Do Phuc , Iung Benoit , Kuo Way
Published: July 2021

With the popularization of big data, an increasing number of discrete event data have been collected and recorded during system operations. These events are usually stored in the form of event logs, which contain rich information of system operations and have potential applications in fault diagnosis and failure prediction. In manufacturing processes, various levels of correlations exist among the events, which can be used to predict the occurrence of failure events. However, two challenges remain to be solved for effective reliability analysis and failure prediction: (1) how to leverage various information from the event log to predict the occurrence of failure events and (2) how to model the effects of multiple correlations on the prediction. To address these issues, this paper proposes a novel reliability model, which integrates Cox proportional hazards (PHs) regression into survival analysis and association rule mining methodology. The model is used to evaluate the probability of failure event, which occurs within a certain period of time conditional on the occurrence history of correlated events. To estimate parameters and predict occurrence of failure events in the model, an effective algorithm is proposed based on piecewise‐constant time axis division, Cox PHs model, and maximum likelihood estimation. Unlike the existing literature, our model focuses on the interactions among events. The applicability of the proposed model is illustrated through a case study of a manufacturing company. Sensitivity analysis is conducted to illustrate the effectiveness of the proposed model.
Diagnostics and prognostics for complex systems: A review of methods and challenges
Authors: Soleimani Morteza , Campean Felician , Neagu Daniel
Published: July 2021

Diagnostics and prognostics have a significant role in the reliability enhancement of systems and are focused topics of active research. Engineered systems are becoming more complex and are subjected to miscellaneous failure modes that impact adversely their performability. This ever‐increasing complexity makes fault diagnostics and prognostics challenging for the system‐level functions. A significant number of successes have been achieved and acknowledged in some review papers; however, these reviews rarely focused on application to complex engineered systems nor provided a systematic review of diverse techniques and approaches to address the related challenges. To bridge the gap, this paper first presents a review to systematically cover the general concepts and recent development of various diagnostics and prognostics approaches, along with their strengths and shortcomings for the application of diverse engineered systems. Afterwards, given the characteristics of complex systems, the applicability of different techniques and methods that are capable to address the features of complex systems are reviewed and discussed, and some of the recent achievements in the literature are introduced. Finally, the unaddressed challenges are discussed by taking into account the characteristics of automotive systems as an example of complex systems. In addition, future development and potential research trends are offered to address those challenges. Consequently, this review provides a systematic view of the state‐of‐the‐art and case studies with a reference value for scholars and practitioners.
Functional regression control chart for monitoring ship CO2$_{2}$ emissions
Authors: Capezza Christian , Centofanti Fabio , Lepore Antonio , Menafoglio Alessandra , Palumbo Biagio , Vantini Simone
Published: July 2021

On modern ships, the quick development in data acquisition technologies is producing data‐rich environments where variable measurements are continuously streamed and stored during navigation and thus can be naturally modelled as functional data or profiles. Then, both the CO emissions (i.e. the quality characteristic of interest) and the variable profiles that have an impact on them (i.e. the covariates) are called to be explored in the light of the new worldwide and European regulations on the monitoring, reporting and verification of harmful emissions. In this paper, we show an application of the functional regression control chart (FRCC) with the ultimate goal of answering, at the end of each ship voyage, the question: given the value of the covariates, is the observed CO emission profile as expected? To this aim, the FRCC focuses on the monitoring of residuals obtained from a multivariate functional linear regression of the CO emission profiles on the functional covariates. The applicability of the FRCC is demonstrated through a real‐case study of a Ro‐Pax ship operating in the Mediterranean Sea. The proposed FRCC is also compared with other alternatives available in the literature and its advantages are discussed over some practical examples.
Quantum Neuromorphic Computing with Reservoir Computing Networks
Authors: Ghosh Sanjib , Nakajima Kohei , Krisnanda Tanjung , Fujii Keisuke , Liew Timothy C. H.
Published: July 2021

Quantum reservoir networks combine the intelligence of neural networks with the potential of quantum computing in a single platform. This platform operates on the architecture of reservoir computing, which can function even with random connections between neural nodes. This is a major advantage for hardware implementation. Herein is described how reservoir computing is brought into the quantum domain to perform various tasks, including characterization of quantum states, quantum estimation, quantum state preparation, and quantum computing. It shows quantum enhancement in classical data processing, and creates the opportunity for quantum information processing within the robust paradigm of neural networks. It is friendly for implementation in a wide range of physical systems, including quantum dots, superconductors, trapped ions, cold atoms, and exciton‐polaritons.
Hydroxychloroquine in the treatment of coronavirus disease 2019: Rapid updated systematic review and meta‐analysis
Authors: Gupta Tejpal , Thakkar Prafulla , Kalra Babusha , Kannan Sadhana
Published: July 2021

Coronavirus disease 2019 (COVID‐19) caused by the novel severe acute respiratory syndrome coronavirus 2 continues to grow and spread throughout the world since being declared a pandemic. Despite extensive scientific research globally including repurposing of several existing drugs, there is no effective or proven therapy for this enigmatic disease which is still largely managed empirically This systematic review evaluated the role of hydroxychloroquine (HCQ) in the treatment of COVID‐19 infection and was conducted using Cochrane methodology for systematic reviews of interventional studies including risk of bias assessment and grading of the quality of evidence. Only prospective clinical trials randomly assigning COVID‐19 patients to HCQ plus standard of care therapy (test arm) versus placebo/standard of care (control arm) were included. Data were pooled using the random‐effects model and expressed as risk ratio (RR) with 95% confidence interval (CI). A total of 10,492 patients from 19 randomised controlled trials were included. The use of HCQ was not associated with higher rates of clinical improvement (RR = 1.00, 95% CI: 0.96–1.03, p = 0.79) or reduction in all‐cause mortality by Day14 (RR = 1.07, 95% CI: 0.97–1.19, p = 0.19) or Day28 (RR = 1.08, 95% CI: 0.99–1.19, p = 0.09) compared to placebo/standard of care. There was no significant difference in serious adverse events between the two arms (RR = 1.01, 95% CI: 0.85–1.19, p = 0.95). There is low‐to‐moderate certainty evidence that HCQ therapy is generally safe but does not reduce mortality or enhance recovery in patients with COVID‐19 infection.
Adaptive dynamic programming‐based event‐triggered optimal tracking control
Authors: Xue Shan , Luo Biao , Liu Derong , Gao Ying
Published: July 2021

In this article, an event‐triggered constrained optimal tracking control algorithm using integral reinforcement learning (IRL) is developed. First, the constrained optimal tracking control problem is transformed into an optimal regulation problem by employing an augmented system with a discounted value function. Then, IRL is introduced to solve the Hamilton‐Jacobi‐Bellman equation, where the drift dynamics and reference dynamics are not required. The learning of neural network weights is event‐triggered and there is no restriction on the initial control to be admissible. The involvement of event‐triggering mechanism alleviates the pressure of data transmission on the network to some extent, which is suitable for control systems with limited computational and communication resources. Moreover, the nonexistence of Zeno behavior and the stability of the impulsive system are proved, respectively. Finally, the application of the algorithm on a mass‐spring‐damper system verifies its effectiveness.
Optimal observer‐based output feedback controller for traffic congestion with bottleneck
Authors: Guan Lina , Zhang Liguo , Prieur Christophe
Published: July 2021

This article designs an optimal observer‐based output feedback control for traffic breakdown to dissolve traffic congestion using the backstepping method and optimization. The linearized Aw–Rascle–Zhang model is used to represent the congested traffic dynamics resulting from traffic breakdown. Based on the factors leading to traffic breakdown, we take into account the boundary conditions consisting of a boundary with a constant density and a speed drop at the upstream inlet of a bottleneck, and a boundary with a disturbance of inflow (high traffic demand) at the inlet of the road segment under consideration. To dissolve traffic congestion, a dynamic feedback controller is designed at the upstream boundary. By using the backstepping approach, an observer‐based output feedback controller is computed to guarantee the integral input‐to‐state stability of the closed‐loop system. By establishing an optimization problem and solving it, the optimal value of the considered class controller is obtained. The performance of the output feedback controller is also validated by numerical simulations.
How conceptual blends support sensemaking: A case study from introductory physics
Authors: Odden Tor Ole B.
Published: July 2021

When learning science, students must often make sense of complex and counterintuitive ideas. However, this process of sensemaking is difficult, and consequently students risk emerging from science courses with highly fragmented understandings. In this study, I examine the ways in which students create conceptual connections to resolve such difficulties and defragment their understandings. Using three intersecting theoretical frameworks—Knowledge in Pieces, sensemaking, and conceptual blends—I analyze a case study of two undergraduate physics students making sense of the concepts of voltage, electric potential, and electric potential energy. I show how the students move through the different stages of the sensemaking process and how a conceptual blend was constructed and productively applied to help them resolve their knowledge fragmentation. Based on this case, I argue that conceptual blends can serve as a cognitive mechanism for the sensemaking process.
Sample size considerations for matched‐pair cluster randomization design with incomplete observations of binary outcomes
Authors: Xu Xiaohan , Zhu Hong , Hoang Anh Q. , Ahn Chul
Published: July 2021

Multiple public health and medical research studies have applied matched‐pair cluster randomization design to the evaluation of the intervention and/or prevention effects. One of the most common and severe problems faced by researchers when conducting cluster randomized trials (CRTs) is incomplete observations, which are associated with various reasons causing the individuals to discontinue participating in the trials. Although statistical methods to remedy the problems of missing data have already been proposed, there are still methodological gaps in research concerning the determination of sample size in matched‐pair CRTs with incomplete binary outcomes. One conventional method for adjusting for missing data in the sample size determination is to divide the sample size under complete data by the expected follow‐up rate. However, such crude adjustment ignores the impact of the structure and strength of correlations regarding both outcome data and missing data mechanism. This article provides a closed‐form sample size formula for matched‐pair CRTs with incomplete binary outcomes, which appropriately accounts for different missing patterns and magnitudes as well as the effects of matching and clustering on the outcome and missing data. The generalized estimating equation (GEE) approach treats incomplete observations as missing data in a marginal logistic regression model, which flexibly accommodates various types of intraclass correlation, missing patterns, and missing proportions. In the presence of missing data, the proposed GEE sample size method provides higher accuracy as compared with the conventional method. The performance of the proposed method is assessed by simulation studies. This article also illustrates how the proposed method can be used to design a real‐world matched‐pair CRT to examine the effect of a team‐based approach on controlling blood pressure (BP).
Recent Advances in the Use of Biomass‐Derived Activated Carbon as an Electrode Material for Electroanalysis
Authors: Akanda Md. Rajibul , Bibi Aisha , Aziz Md. Abdul
Published: July 2021

Activated carbon (AC), which has attracted considerable attention as an electrode material, holds much promise for electroanalysis. The unique physical and chemical properties of AC, such as the high surface area, good thermal and electrical conductivity, good anti‐causticity, high stability, and low cost make it an electrode material which can generate large profits from a commercialization perspective. Number of biomass‐derived ACs (BACs) with a variety of pore sizes, porosity, morphology, and crystallinity have been prepared from a range of sources of biomass, including agro‐wastes on a large scale. BACs exhibit unique and tunable electrochemical properties depending on their physicochemical properties and thus, have found number of applications in industries, pharmaceutical industry, and water treatment plants. From an electrochemical perspective, researchers have demonstrated the impact of BAC as an electrode material for detecting electroactive drugs, environmental pollutants, and developing electrochemical biosensors. Hence, this paper thoroughly reviews and summarizes the literature published within the last ten years, focusing specifically on the types of analytes detected and electrochemical techniques employed and evaluating their performance (in terms of sensitivity, selectivity, and dynamic ranges) and feasibility for electroanalysis. In addition, the review outlines some constructive advice and scope for further research.
Metal–Organic Frameworks‐Derived Nitrogen‐Doped Porous Carbon Nanocubes with Embedded Co Nanoparticles as Efficient Sulfur Immobilizers for Room Temperature Sodium–Sulfur Batteries
Authors: Mou Jirong , Li Yijuan , Liu Ting , Zhang Wenjia , Li Mei , Xu Yuting , Zhong Lei , Pan Wenhao , Yang Chenghao , Huang Jianlin , Liu Meilin
Published: July 2021

Room temperature sodium–sulfur (RT Na–S) batteries are considered a promising candidate for energy‐storage due to their high energy‐density and low‐cost. However, the shutting effect of polysulfides and sluggish kinetics of sulfur redox reactions still severely limit their practical implementation. Herein, a new type of 3D hierarchical porous carbonaceous nanocubes is reported as efficient sulfur hosts, composed of carbon nanotubes (CNT) and Co nanoparticles (NPs) uniformly embedded into a nitrogen‐doped carbon matrix (NC). Because of the high specific surface area, large degree of graphitization, and the synergetic effects between Co NPs and N‐doping, the as‐designed CNTs/Co@NC electrodes not only significantly increase polysulfides immobilization, but also efficiently catalyze sulfur redox reactions, as confirmed by experimental results and DFT calculations. When tested in a RT Na–S battery, the S@CNTs/Co@NC‐0.25 cathode demonstrates outstanding electrochemical performance, achieving high initial specific capacity of 1200.3 mAh g−1 at 0.1 C, remarkable rate capability up to 5.0 C (474.2 mAh g−1), and superior cyclic performance of 450.5 mAh g−1 (292 mAh g−1) after 400 cycles at 1.0 C (5.0 C). The integration of a 3D hierarchical porous architecture with well‐dispersed Co NPs of an electro‐catalyst provides valuable insights based on structure‐adsorption‐catalysis engineering for advanced RT Na–S batteries.
Fast Lithium Ionic Conductivity in Complex Hydride‐Sulfide Electrolytes by Double Anions Substitution
Authors: Zhang Tengfei , Shao Yifei , Zhang Xiang , Huang Yuqin , Wang Shuai , Zhou Wei , Li Peng , Xia Guanglin , Yu Xuebin
Published: July 2021

Hydride‐based solid‐state electrolytes (SSEs) can maintain their stability against Li metal and exhibit high compatibility with a Li metal anode owing to their reducing property and flexible character. However, poor ionic conductivity at room temperature is a major challenge for hydride materials used as SSEs in a lithium ion battery. In this work, a room‐temperature fast lithium‐ion conductor is explored in response to double anion substitution, (100‐x)(3LiBH4‐LiI)‐xP2S5 (LLPx, 0 ≤ x ≤ 50). Among these samples, LLP20 respectively delivers an ionic conductivity up to 3.77 × 10−4 S cm−1 at 30 °C and 1.0 × 10−2 S cm−1 at 100 °C, with a stable electrochemical window of 0–5 V. A Li plating/stripping test has been conducted under a current density of 1.0 mA cm−2, which exhibits an excellent stability even after 1000 h. Moreover, the all solid‐state cell exhibits a remarkable electrochemical performance in a wide temperature range including high reversible capacity, good rate capability, and long cycling durability. These outstanding performances present a practical strategy for developing ambient‐temperature, fast ionic conductors for all solid‐state batteries in near future.
Mesoporous Au@Cu2−xS Core–Shell Nanoparticles with Double Localized Surface Plasmon Resonance and Ligand Modulation for Hole‐Selective Passivation in Perovskite Solar Cells
Authors: Wu Tong , Wang Zhengchun , Xiao Lan , Qin Pingli , Qin Zhongli , Ma Liang , Zeng Wei , Chen Xiangbai , Xiong Liangbin , Fang Guojia
Published: July 2021

Core–shell nanomaterials have led to their fascinating properties in optical applications due to the localized surface plasmon resonance (LSPR). Herein, a mesoporous core–shell Au@Cu2−x
S nanomaterial with dual LSPR characteristics is introduced to stabilize and passivate the perovskite/spiro‐OMeTAD interface of perovskite solar cells (PSCs). Thanks to the LSPR, Au@Cu2−x
S nanoparticles (NPs) have the potential to enhance the infrared absorption and intensify the local electric field at the perovskite/spiro‐OMeTAD interface. The embedding of the mesoporous Au@Cu2−x
S in the spiro‐OMeTAD layer can improve the contact and form “bridges” between perovskite grains and spiro‐OMeTAD. With the help of cationic surfactant cetyltrimethylammonium bromide, these mesoporous Au@Cu2−x
S NPs can passivate surface traps and smooth the valence‐band offset at the perovskite/spiro‐OMeTAD interface for hole transferring. Furthermore, the improved hole mobility can offer balanced charge transport and prevent the carrier accumulation at interfaces. As a result, the Au@Cu2−x
S(20:10)‐based PSCs achieves a champion efficiency over 22%, higher than that of the Au@Cu2−x
S‐based device.
Genotyping of Brucella strains isolated from humans and cattle of different geographical regions of Pakistan using MLVA‐15
Authors: Akhtar Raheela , Ali Muhammad Muddassir , Ullah Asad , Muttalib Abdul , Mehboob Kashan , Ullah Arif , Ahmad Nasim , Chohan Tahir Zahoor
Published: July 2021

Background

Prevalence of brucellosis and MLVA genotyping in animals and humans, isolated from different regions of Pakistan was performed. Animals having history of brucellosis from the field and local farms of Bannu, Mardan, Peshawar, Swat, Lahore and Islamabad were selected for blood collection. Humans that work with them were also selected for sampling in this study. Total of 600 samples were taken from cattle and humans and subjected to Rose Bengal plate Test (RBPT) for the initial screening of positive samples. Designed primers of B.abortus for cattle and B.melitensis for humans were utilised to perform PCR. Culturing and isolation was carried to further to perform MLVA genotyping assay through the selection of two panels of primer markers.

Results

RBPT showed more number of cases of brucellosis in animals and humans compared to the PCR findings. Genotyping findings based upon MLVA‐15 set of markers demonstrated that the isolated strains of B.abortus fall in the same clade with strain A1, P8 and A2 from Pakistan and also similar with BCCN#02‐45 strain from India. On the other hand, B.melitensis isolated from different districts of Pakistan shared the same clade with BwIM‐AFG 63, BwIM‐AFG 44 strains from Afghanistan and BwIM IRN 37 strain from Iran. Selected VNTR alleles were sequenced for calibration purposes.

Conclusion

It is concluded that Brucella is prevalent in animals and humans in studied districts of Pakistan. Moreover, A1, P8, BwIM‐AFG 63, BwIM‐AFG 44 and A2 were found the common genotypes in Pakistan.
A case of canineSalmonella spp. osteomyelitis with secondary fracture following dog bite
Authors: Williams Elroy , Towle Heather Ann Marie
Published: July 2021

An immature canine was attacked by another dog in a kennel facility and sustained multiple wounds to the lateral right forelimb and cranial right lateral thoracic region. General surgical and antimicrobial therapies were instituted immediately. The patient battled with recurrent infections and subsequent delayed healing. After approximately 35 days from the initial injury, the patient became acutely lame and febrile. The persistently open wounds were cultured and returned positive forSalmonella spp. Within the following days, the patient became painful, and the lameness progressed significantly. Radiographs confirmed pathologic humeral fracture, and the patient was referred for specialty evaluation. Zoonotic preventative protocols were adopted at the specialty facility upon arrival. Complete forequarter limb amputation was curative in this patient.
Foot lesion in a male Boer goat associated with caprine digital dermatitis
Authors: Mostafa Mohamed Barakat , Koma Lee Martin , Galiwango Badr Mohamed
Published: July 2021

A case of interdigital hyperplasia and digital dermatitis on the dorsal aspect of the right hind digit in an adult male Boer goat was described. The digital dermatitis was complicated by granular ulceration of the skin on the dorsal aspect of the foot. Histologically, the lesion was characterised by the presence of numerous papillae‐like growths in the epidermis. Some papillae had mononuclear inflammatory cells. A number of papillae‐like growths hardly had any cells in the core; however, a few plasma cells and lymphocytes were present. The goat was moderately lame on the affected limb. The lesion was excised surgically and healed without any complication. Surgical excision proved to be uneventful healing.
Lyapunov instability of the stationary flows of polymeric fluid with constant flow rate
Authors: Blokhin Alexander M. , Tkachev Dmitry L.
Published: July 2021

We study a rheological Pokrovski‐Vinogradov model for the flows of solutions and melts of incompressible viscoelastic polymeric medium in case of a flow in an infinite plane channel with perforated walls. We prove the linear Lyapunov instability of the base solution with the constant flow rate in a perturbation class, periodic with respect to the variable, changing along the channel wall.
Correction to: Crop Establishment in Direct-Seeded Rice: Traits, Physiology, and Genetics
Authors: Quilloy Fergie Ann , Labaco Benedick , Casal Carlos , Dixit Shalabh
Published: July 2021

“Owing to an error on the part of the editor and corresponding chapter author, the author sequence in the chapter opening page of chapter Crop Establishment in Direct-Seeded Rice: Traits, Physiology, and Genetics was presented wrongly. The author sequence has now been updated to be Fergie Ann Quilloy, Benedick Labaco, Carlos Casal Jr., Shalabh Dixit in the chapter opening page, table of contents, and wherever applicable throughout the book.”
Double copy structure of parity-violating CFT correlators
Authors: Jain Sachin , John Renjan Rajan , Mehta Abhishek , Nizami Amin A. , Suresh Adithya
Published: July 2021

Abstract

We show that general parity-violating 3d conformal field theories show a double copy structure for momentum space 3-point functions of conserved currents, stress tensor and marginal scalar operators. Splitting up the CFT correlator into two parts — called homogeneous and non-homogeneous — we show that double copy relations exist for each part separately. We arrive at similar conclusions regarding double copy structures using tree-level correlators of massless fields in dS4. We also discuss the flat space limit of these correlators. We further extend the double copy analysis to correlators involving higher-spin conserved currents, which suggests that the spin-s current correlator can be thought of as s copies of the spin one current correlator.
Automatic enhancement in 6D supergravity and F-theory models
Authors: Raghuram Nikhil , Taylor Washington , Turner Andrew P.
Published: July 2021

Abstract

We observe that in many F-theory models, tuning a specific gauge group G and matter content M under certain circumstances leads to an automatic enhancement to a larger gauge group G′ ⊃ G and matter content M′ ⊃ M. We propose that this is true for any theory G, M whenever there exists a containing theory G′, M′ that cannot be Higgsed down to G, M. We give a number of examples including non-Higgsable gauge factors, nonabelian gauge factors, abelian gauge factors, and exotic matter. In each of these cases, tuning an F-theory model with the desired features produces either an enhancement or an inconsistency, often when the associated anomaly coefficient becomes too large. This principle applies to a variety of models in the apparent 6D supergravity swampland, including some of the simplest cases with U(1) and SU(N) gauge groups and generic matter, as well as infinite families of U(1) models with higher charges presented in the prior literature, potentially ruling out all these apparent swampland theories.
Celestial fields on the string and the Schwarzian action
Authors: Vegh David
Published: July 2021

Abstract

This paper describes the motion of a classical Nambu-Goto string in three-dimensional anti-de Sitter spacetime in terms of two ‘celestial’ fields on the worldsheet. The fields correspond to retarded and advanced boundary times at which null rays emanating from the string reach the boundary. The formalism allows for a simple derivation of the Schwarzian action for near-AdS2 embeddings.
Islands and stretched horizon
Authors: Matsuo Yoshinori
Published: July 2021

Abstract

Recently it was proposed that the entanglement entropy of the Hawking radiation contains the information of a region including the interior of the event horizon, which is called “island.” In studies of the entanglement entropy of the Hawking radiation, the total system in the black hole geometry is separated into the Hawking radiation and black hole. In this paper, we study the entanglement entropy of the black hole in the asymptotically flat Schwarzschild spacetime. Consistency with the island rule for the Hawking radiation implies that the information of the black hole is located in a different region than the island. We found an instability of the island in the calculation of the entanglement entropy of the region outside a surface near the horizon. This implies that the region contains all the information of the total system and the information of the black hole is localized on the surface. Thus the surface would be interpreted as the stretched horizon. This structure also resembles black holes in the AdS spacetime with an auxiliary flat spacetime, where the information of the black hole is localized at the interface between the AdS spacetime and the flat spacetime.
Quantum gravity states, entanglement graphs and second-quantized tensor networks
Authors: Colafranceschi Eugenia , Oriti Daniele
Published: July 2021

Abstract

In recent years, the import of quantum information techniques in quantum gravity opened new perspectives in the study of the microscopic structure of spacetime. We contribute to such a program by establishing a precise correspondence between the quantum information formalism of tensor networks (TN), in the case of projected entangled-pair states (PEPS) generalised to a second-quantized framework, and group field theory (GFT) states, and by showing how, in this quantum gravity approach, discrete spatial manifolds arise as entanglement patterns among quanta of space, having a dual representation in terms of graphs and simplicial complexes. We devote special attention to the implementation and consequences of the label independence of the graphs/networks, corresponding to the indistinguishability of the space quanta and representing a discrete counterpart of the diffeomorphism invariance of a consistent quantum gravity formalism. We also outline a relational setting to recover distinguishability of graph/network vertices at an effective and physical level, in a partial semi-classical limit of the theory.
Solitons in lattice field theories via tight-binding supersymmetry
Authors: Balasubramanian Shankar , Patoary Abu , Galitski Victor
Published: July 2021

Abstract

Reflectionless potentials play an important role in constructing exact solutions to classical dynamical systems (such as the Korteweg-de Vries equation), non-perturbative solutions of various large-Nfield theories (such as the Gross-Neveu model), and closely related solitonic solutions to the Bogoliubov-de Gennes equations in the theory of superconductivity. These solutions rely on the inverse scattering method, which reduces these seemingly unrelated problems to identifying reflectionless potentials of an auxiliary one-dimensional quantum scattering problem. There are several ways of constructing these potentials, one of which is quantum mechanical supersymmetry (SUSY). In this paper, motivated by recent experimental platforms, we generalize this framework to develop a theory of lattice solitons. We first briefly review the classical inverse scattering method in the continuum limit, focusing on the Korteweg-de Vries (KdV) equation and SU(N) Gross-Neveu model in the largeNlimit. We then generalize this methodology to lattice versions of interacting field theories. Our analysis hinges on the use of trace identities, which are relations connecting the potential of an equation of motion to the scattering data. For a discrete Schrödinger operator, such trace identities had been known as far back as Toda; however, we derive a new set of identities for the discrete Dirac operator. We then use these identities in a lattice Gross-Neveu and chiral Gross-Neveu (Nambu-Jona-Lasinio) model to show that lattice solitons correspond to reflectionless potentials associated with the discrete scattering problem. These models are of significance as they are equivalent to a mean-field theory of a lattice superconductor. To explicitly construct these solitons, we generalize supersymmetric quantum mechanics to tight-binding models. We show that a matrix transformation exists that maps a tight-binding model to an isospectral one which shares the same structure and scattering properties. The corresponding soliton solutions have both modulated hopping and onsite potential, the former of which has no analogue in the continuum limit. We explicitly compute both topological and non-topological soliton solutions as well as bound state spectra in the aforementioned models.
Genetic architecture underlying the expression of eight α-amylase trypsin inhibitors
Authors: EL Hassouni Khaoula , Sielaff Malte , Curella Valentina , Neerukonda Manjusha , Leiser Willmar , Würschum Tobias , Schuppan Detlef , Tenzer Stefan , Longin C. Friedrich H.
Published: July 2021

Key message

Wheat cultivars largely differ in the content and composition of ATI proteins, but heritability was quite low for six out of eight ATIs. The genetic architecture of ATI proteins is built up of few major and numerous small effect QTL.

Amylase trypsin inhibitors (ATIs) are important allergens in baker’s asthma and suspected triggers of non-celiac wheat sensitivity (NCWS) inducing intestinal and extra-intestinal inflammation. As studies on the expression and genetic architecture of ATI proteins in wheat are lacking, we evaluated 149 European old and modern bread wheat cultivars grown at three different field locations for their content of eight ATI proteins. Large differences in the content and composition of ATIs in the different cultivars were identified ranging from 3.76 pmol for ATI CM2 to 80.4 pmol for ATI 0.19, with up to 2.5-fold variation in CM-type and up to sixfold variation in mono/dimeric ATIs. Generally, heritability estimates were low except for ATI 0.28 and ATI CM2. ATI protein content showed a low correlation with quality traits commonly analyzed in wheat breeding. Similarly, no trends were found regarding ATI content in wheat cultivars originating from numerous countries and decades of breeding history. Genome-wide association mapping revealed a complex genetic architecture built of many small, few medium and two major quantitative trait loci (QTL). The major QTL were located on chromosomes 3B for ATI 0.19-like and 6B for ATI 0.28, explaining 70.6 and 68.7% of the genotypic variance, respectively. Within close physical proximity to the medium and major QTL, we identified eight potential candidate genes on the wheat reference genome encoding structurally related lipid transfer proteins. Consequently, selection and breeding of wheat cultivars with low ATI protein amounts appear difficult requiring other strategies to reduce ATI content in wheat products.
Quantitative Trait Loci and Candidate Genes Associated with Photoperiod Sensitivity in Lettuce (Lactuca spp.)
Authors: Han Rongkui , Lavelle Dean , Truco Maria José , Michelmore Richard
Published: July 2021

Key message

A population of lettuce that segregated for photoperiod sensitivity was planted under long-day and short-day conditions. Genetic mapping revealed two distinct sets of QTLs controlling daylength-independent and photoperiod-sensitive flowering time.

The molecular mechanism of flowering time regulation in lettuce is of interest to both geneticists and breeders because of the extensive impact of this trait on agricultural production. Lettuce is a facultative long-day plant which changes in flowering time in response to photoperiod. Variations exist in both flowering time and the degree of photoperiod sensitivity among accessions of wild (Lactuca serriola) and cultivated (L. sativa) lettuce. An F6 population of 236 recombinant inbred lines (RILs) was previously developed from a cross between a late-flowering, photoperiod-sensitive L. serriola accession and an early-flowering, photoperiod-insensitive L. sativa accession. This population was planted under long-day (LD) and short-day (SD) conditions in a total of four field and screenhouse trials; the developmental phenotype was scored weekly in each trial. Using genotyping-by-sequencing (GBS) data of the RILs, quantitative trait loci (QTL) mapping revealed five flowering time QTLs that together explained more than 20% of the variation in flowering time under LD conditions. Using two independent statistical models to extract the photoperiod sensitivity phenotype from the LD and SD flowering time data, we identified an additional five QTLs that together explained more than 30% of the variation in photoperiod sensitivity in the population. Orthology and sequence analysis of genes within the nine QTLs revealed potential functional equivalents in the lettuce genome to the key regulators of flowering time and photoperiodism, FD and CONSTANS, respectively, in Arabidopsis.
The mechanics of sawing granite with diamond wire
Authors: Konstanty Janusz Stefan
Published: July 2021

Today, wire sawing of natural stone is undergoing widespread commercialization. In addition to rock extraction and processing with single wires, composed of a multitude of diamond-impregnated beads mounted onto a steel rope, this technology is increasingly used for slabbing of granite blocks on multi-wire machines. Evolving sophistication of stone sawing equipment dictates novel tool designs and formulations. For technologists specifying bead compositions, it is a common habit to instinctively follow the circular saw segment design guidelines. A poor tool performance is often an undesirable consequence of such an approach. To meet that challenge, theoretical models of sawing granite by means of a diamond wire saw and a diamond circular saw have been presented and contrasted with respect to diamond loading conditions. The analytical treatments are supported by scarcely available industrial quantitative assessments and qualitative observations. The evaluation of cutting forces and the identification of system characteristics affecting wire vibration and wire rotation are instrumental in both machine design and tool formulation. For practitioners working with granite, the provided knowledge is also essential to diagnose and prevent problems inherent in wire sawing, such as the high incidence of wire breakage, unsatisfactory tool life and cutting capability and eccentric bead wear.

Graphical abstract
Pelvic organ prolapse surgery and overactive bladder symptoms—a population-based cohort (FINPOP)
Authors: Karjalainen Päivi K. , Tolppanen Anna-Maija , Mattsson Nina K. , Wihersaari Olga A.E. , Jalkanen Jyrki T. , Nieminen Kari
Published: July 2021

Introduction and hypothesis

It is unclear how compartment of pelvic organ prolapse (POP) impacts overactive bladder (OAB) symptom severity or improvement after POP surgery. We hypothesized that anterior and apical prolapse are more strongly associated with OAB symptoms than posterior compartment prolapse.

Methods

A total of 2933 POP surgeries from a prospective population-based cohort were divided into two groups: (1) anterior and/or apical compartment surgery (± posterior repair), N = 2091; (2) posterior repair only, N = 478. Urinary frequency and urgency urinary incontinence (UUI) were evaluated using PFDI-20 (bothersome symptom: score 3–4) at baseline, 6, and 24 months. Association between degree of POP in specific compartments and symptoms at baseline was estimated with generalized linear models and between compartment of surgery and symptom improvement with generalized estimating equations.

Results

At least one bothersome symptom was reported by 40% at baseline, 14% at 6, and 19% at 24 months. At baseline, urinary frequency was associated with degree of anterior and apical and UUI with anterior compartment prolapse. Women undergoing surgery for anterior/apical compartment started with worse symptoms and experienced greater improvement than women undergoing posterior compartment surgery. Bothersome frequency resolved in 82% after anterior/apical and in 63% after posterior compartment surgery. Bothersome UUI resolved in 75% after anterior/apical and in 61% after posterior compartment surgery. After surgery, symptom severity was comparable between groups. Bothersome de novo symptoms occurred in 1–3%.

Conclusions

OAB symptoms are more strongly related to anterior and apical than to posterior compartment prolapse, but improvement is seen after surgery for any vaginal compartment.
Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning
Authors: Wills John W. , Verma Jatin R. , Rees Benjamin J. , Harte Danielle S. G. , Haxhiraj Qiellor , Barnes Claire M. , Barnes Rachel , Rodrigues Matthew A. , Doan Minh , Filby Andrew , Hewitt Rachel E. , Thornton Catherine A. , Cronin James G. , Kenny Julia D. , Buckley Ruby , Lynch Anthony M. , Carpenter Anne E. , Summers Huw D. , Johnson George E. , Rees Paul
Published: July 2021

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25–5.0 μg/mL) and/or carbendazim (0.8–1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the “DeepFlow” neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for ‘mononucleates’, ‘binucleates’, ‘mononucleates with MN’ and ‘binucleates with MN’, respectively. Successful classifications of ‘trinucleates’ (90%) and ‘tetranucleates’ (88%) in addition to ‘other or unscorable’ phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.