bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Hardware Ray Transforms to Accelerate Ray/Primitive Intersections for Long, Thin Primitive Types
Authors: Wald Ingo , Morrical Nate , Zellmann Stefan , Ma Lei , Usher Will , Huang Tiejun , Pascucci Valerio
Published: March 2021

With the recent addition of hardware ray tracing capabilities, GPUs have become incredibly efficient at ray tracing both triangular geometry, and instances thereof. However, the bounding volume hierarchies that current ray tracing hardware relies on are known to struggle with long, thin primitives like cylinders and curves, because the axis-aligned bounding boxes that these hierarchies rely on cannot tightly bound such primitives. In this paper, we evaluate the use of RTX ray tracing capabilities to accelerate these primitives by tricking the GPU's instancing units into executing a hardware-accelerated oriented bounding box (OBB) rejection test before calling the user's intersection program. We show that this can be done with minimal changes to the intersection programs and demonstrate speedups of up to 5.9× on a variety of data sets.
FLIP
Authors: Andersson Pontus , Nilsson Jim , Akenine-Möller Tomas , Oskarsson Magnus , Åström Kalle , Fairchild Mark D.
Published: March 2021

Image quality measures are becoming increasingly important in the field of computer graphics. For example, there is currently a major focus on generating photorealistic images in real time by combining path tracing with denoising, for which such quality assessment is integral. We present FLIP, which is a difference evaluator with a particular focus on the differences between rendered images and corresponding ground truths. Our algorithm produces a map that approximates the difference perceived by humans when alternating between two images. FLIP is a combination of modified existing building blocks, and the net result is surprisingly powerful. We have compared our work against a wide range of existing image difference algorithms and we have visually inspected over a thousand image pairs that were either retrieved from image databases or generated in-house. We also present results of a user study which indicate that our method performs substantially better, on average, than the other algorithms. To facilitate the use of FLIP, we provide source code in C++, MATLAB, NumPy/SciPy, and PyTorch.
The Revelation Principle for Mechanism Design with Signaling Costs
Authors: Kephart Andrew , Conitzer Vincent
Published: March 2021

The
revelation principle
is a key tool in mechanism design. It allows the designer to restrict attention to truthful mechanisms, greatly facilitating analysis. This is also borne out algorithmically, allowing certain computational problems in mechanism design to be solved in polynomial time. Unfortunately, when not every type can misreport every other type (the
partial verification
model) or—more generally—misreporting can be costly, the revelation principle can fail to hold. This also leads to NP-hardness results. The primary contribution of this article consists of characterizations of conditions under which the revelation principle still holds when reporting can be costly. (These are generalizations of conditions given earlier for the partial verification case [11, 21].) Furthermore, our results extend to cases where, instead of reporting types directly, agents send signals that do not directly correspond to types. In this case, we obtain conditions for when the mechanism designer can restrict attention to a given (but arbitrary) mapping from types to signals without loss of generality.
MPEG column: 125th MPEG meeting in Marrakesh, Morocco
Authors: Timmerer Christian
Published: March 2021

The original blog post can be found at the Bitmovin Techblog and has been modified/updated here to focus on and highlight research aspects.

The 125th MPEG meeting concluded on January 18, 2019 in Marrakesh, Morocco with the following topics:

Network-Based Media Processing (NBMP) - MPEG promotes NBMP to Committee Draft stage

3DoF+ Visual - MPEG issues Call for Proposals on Immersive 3DoF+ Video Coding Technology

MPEG-5 Essential Video Coding (EVC) - MPEG starts work on MPEG-5 Essential Video Coding

ISOBMFF - MPEG issues Final Draft International Standard of Conformance and Reference software for formats based on the ISO Base Media File Format (ISOBMFF)

MPEG-21 User Description - MPEG finalizes 2nd edition of the MPEG-21 User Description

The corresponding press release of the 125th MPEG meeting can be found here. In this blog post I'd like to focus on those topics potentially relevant for over-the-top (OTT), namely NBMP, EVC, and ISOBMFF.
Report on the CHIIR 2019 Second Workshop on Evaluation of Personalisation in Information Retrieval (WEPIR 2019)
Authors: Jones Gareth J. F. , Belkin Nicholas J. , Lawless Séamus , Pasi Gabriella
Published: March 2021

The Second Workshop on Evaluation of Personalisation in Information Retrieval (WEPIR 2019) was held in conjunction with the ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR 2019) in Glasgow, Scotland. WEPIR 2019 followed on from the first WEPIR held at CHIIR 2018. The purpose of the workshop was again to bring together researchers from different backgrounds, interested in advancing the evaluation of personalisation in information retrieval. The workshop focused on further development of a common understanding of the challenges, requirements and practical limitations of personalisation in information retrieval and its evaluation.
The neural hype, justified!
Authors: Lin Jimmy
Published: March 2021

One year ago, in the SIGIR Forum issue of December 2018, I ranted about the "neural hype" [9]. One year later, I write again to publicly recant my heretical beliefs. What a difference a year makes! In accelerated "deep learning" time, a year seems like an eternity---so much exciting progress has been made in the previous months!
Neural generative models and representation learning for information retrieval
Authors: Ai Qingyao
Published: March 2021

Information Retrieval (IR) concerns about the structure, analysis, organization, storage, and retrieval of information. Among different retrieval models proposed in the past decades, generative retrieval models, especially those under the statistical probabilistic framework, are one of the most popular techniques that have been widely applied to Information Retrieval problems. While they are famous for their well-grounded theory and good empirical performance in text retrieval, their applications in IR are often limited by their complexity and low extendability in the modeling of high-dimensional information. Recently, advances in deep learning techniques provide new opportunities for representation learning and generative models for information retrieval. In contrast to statistical models, neural models have much more flexibility because they model information and data correlation in latent spaces without explicitly relying on any prior knowledge. Previous studies on pattern recognition and natural language processing have shown that semantically meaningful representations of text, images, and many types of information can be acquired with neural models through supervised or unsupervised training. Nonetheless, the effectiveness of neural models for information retrieval is mostly unexplored. In this thesis, we study how to develop new generative models and representation learning frameworks with neural models for information retrieval. Specifically, our contributions include three main components: (1)
Theoretical Analysis
: We present the first theoretical analysis and adaptation of existing neural embedding models for ad-hoc retrieval tasks; (2)
Design Practice
: Based on our experience and knowledge, we show how to design an embedding-based neural generative model for practical information retrieval tasks such as personalized product search; And (3)
Generic Framework
: We further generalize our proposed neural generative framework for complicated heterogeneous information retrieval scenarios that concern text, images, knowledge entities, and their relationships. Empirical results show that the proposed neural generative framework can effectively learn information representations and construct retrieval models that outperform the state-of-the-art systems in a variety of IR tasks.
ACM SIGIR annual business meeting 2019
Authors: Hauff Claudia
Published: March 2021

The 2019 ACM SIGIR Annual Business Meeting took place on July 24, 2019, at the SIGIR '19 Conference in Paris, France. The meeting was held between 12:50-14:20 and was led by the chair of the SIGIR Executive Committee, Ben Carterette.
The Role of the Medial Prefrontal Cortex in Moderating Neural Representations of Self and Other in Primates
Authors: Isoda Masaki
Published: March 2021

As a frontal node in the primate social brain, the medial prefrontal cortex (MPFC) plays a critical role in coordinating one's own behavior with respect to that of others. Current literature demonstrates that single neurons in the MPFC encode behavior-related variables such as intentions, actions, and rewards, specifically for self and other, and that the MPFC comes into play when reflecting upon oneself and others. The social moderator account of MPFC function can explain maladaptive social cognition in people with autism spectrum disorder, which tips the balance in favor of self-centered perspectives rather than taking into consideration the perspective of others. Several strands of evidence suggest a hypothesis that the MPFC represents different other mental models, depending on the context at hand, to better predict others’ emotions and behaviors. This hypothesis also accounts for aberrant MPFC activity in autistic individuals while they are mentalizing others.
Cardiac Disorder Classification by Electrocardiogram Sensing Using Deep Neural Network
Authors: Khan Ali Haider , Hussain Muzammil , Malik Muhammad Kamran
Published: March 2021

Cardiac disease is the leading cause of death worldwide. Cardiovascular diseases can be prevented if an effective diagnostic is made at the initial stages. The ECG test is referred to as the diagnostic assistant tool for screening of cardiac disorder. The research purposes of a cardiac disorder detection system from 12‐lead‐based ECG Images. The healthcare institutes used various ECG equipment that present results in nonuniform formats of ECG images. The research study proposes a generalized methodology to process all formats of ECG. Single Shoot Detection (SSD) MobileNet v2‐based Deep Neural Network architecture was used to detect cardiovascular disease detection. The study focused on detecting the four major cardiac abnormalities (i.e., myocardial infarction, abnormal heartbeat, previous history of MI, and normal class) with 98% accuracy results were calculated. The work is relatively rare based on their dataset; a collection of 11,148 standard 12‐lead‐based ECG images used in this study were manually collected from health care institutes and annotated by the domain experts. The study achieved high accuracy results to differentiate and detect four major cardiac abnormalities. Several cardiologists manually verified the proposed system’s accuracy result and recommended that the proposed system can be used to screen for a cardiac disorder.
Advances in Understanding Mitochondrial MicroRNAs (mitomiRs) on the Pathogenesis of Triple‐Negative Breast Cancer (TNBC)
Authors: Lin Hung-Yu , Chu Pei-Yi
Published: March 2021

Triple‐negative breast cancer (TNBC) is characterized by poor outcome and the most challenging breast cancer type to treat worldwide. TNBC manifests distinct profile of mitochondrial functions, which dictates reprogrammed metabolism, fosters tumor progression, and notably serves as therapeutic targets. Mitochondrial microRNAs (mitomiRs) are a group of microRNAs that critically modulate mitochondrial homeostasis. By a pathway‐centric manner, mitomiRs tightly orchestrate metabolic reprogramming, redox status, cell apoptosis, mitochondrial dynamics, mitophagy, mitochondrial DNA (mtDNA) maintenance, and calcium balance, leading to an emerging field of study in various cancer types, including TNBC. We herein review the recent insights into the roles and mechanism of mitomiRs in TNBC and highlight its clinical value in diagnosis and prognosis as well as vital advances on therapeutics of preclinical and clinical studies.
Features to Text: A Comprehensive Survey of Deep Learning on Semantic Segmentation and Image Captioning
Authors: Oluwasammi Ariyo , Aftab Muhammad Umar , Qin Zhiguang , Ngo Son Tung , Doan Thang Van , Nguyen Son Ba , Nguyen Son Hoang , Nguyen Giang Hoang
Published: March 2021

With the emergence of deep learning, computer vision has witnessed extensive advancement and has seen immense applications in multiple domains. Specifically, image captioning has become an attractive focal direction for most machine learning experts, which includes the prerequisite of object identification, location, and semantic understanding. In this paper, semantic segmentation and image captioning are comprehensively investigated based on traditional and state‐of‐the‐art methodologies. In this survey, we deliberate on the use of deep learning techniques on the segmentation analysis of both 2D and 3D images using a fully convolutional network and other high‐level hierarchical feature extraction methods. First, each domain’s preliminaries and concept are described, and then semantic segmentation is discussed alongside its relevant features, available datasets, and evaluation criteria. Also, the semantic information capturing of objects and their attributes is presented in relation to their annotation generation. Finally, analysis of the existing methods, their contributions, and relevance are highlighted, informing the importance of these methods and illuminating a possible research continuation for the application of semantic image segmentation and image captioning approaches.
A Security Log Analysis Scheme Using Deep Learning Algorithm for IDSs in Social Network
Authors: Zhong Ming , Zhou Yajin , Chen Gang
Published: March 2021

Due to the complexity of the social network server system, various system abnormalities may occur and in turn will lead to subsequent system failures and information losses. Thus, to monitor the system state and detect the system abnormalities are of great importance. As the system log contains valuable information and records the system operating status and users’ behaviors, log data in system abnormality detection and diagnosis can ensure system availability and reliability. This paper discloses a log analysis method based on deep learning for an intrusion detection system, which includes the following steps: preprocess the acquired logs of different types in the target system; perform log analysis on the preprocessed logs using a clustering-based method; then, encode the parsed log events into digital feature vectors; use LSTM-based neural network and log collect-based clustering methods to learn the encoded logs to form warning information; lastly, trace the source of the warning information to the corresponding component to determine the point of intrusion. The paper finally implements the proposed intrusion detection method in the server system, thereby improving the system’s security status.
Hybrid Decision-Making Frameworks under Complex Spherical Fuzzy
N
-Soft Sets
Authors: Akram Muhammad , Shabir Maria , Al-Kenani Ahmad N. , Alcantud José Carlos R.
Published: March 2021

This paper presents the novel concept of complex spherical fuzzy

N

-soft set (

C
S
F
N

S

f

S

) which is capable of handling two-dimensional vague information with parameterized ranking systems. First, we propose the basic notions for a theoretical development of

C
S
F
N

S

f

S
s

, including ranking functions, comparison rule, and fundamental operations (complement, union, intersection, sum, and product). Furthermore, we look into some properties of

C
S
F
N

S

f

S
s

. We then produce three algorithms for multiattribute decision-making that take advantage of these elements. We demonstrate their applicability with the assistance of a numerical problem (selection of best third-party app of the year). A comparison with the performance of Pythagorean

N

-soft sets speaks for the superiority of our approach. Moreover, with an aim to expand the range of techniques for multiattribute group decision-making problems, we design a

C
S
F
N

S

f

-TOPSIS method. We use a complex spherical fuzzy

N

-soft weighted average operator in order to aggregate the decisions of all experts according to the power of the attributes and features of alternatives. We present normalized-Euclidean distances (from the alternatives to both the

C
S
F
N

S

f

positive and negative ideal solutions, respectively) and revised closeness index in order to produce a best feasible alternative. As an illustration, we design a mathematical model for the selection of the best physiotherapist doctor of Mayo hospital, Lahore. We conduct a comparison with the existing complex spherical fuzzy TOPSIS method that confirms the stability of the proposed model and the reliability of its results.
Implementing Multilabeling, ADASYN, and ReliefF Techniques for Classification of Breast Cancer Diagnostic through Machine Learning: Efficient Computer-Aided Diagnostic System
Authors: Khan Taha Muthar , Xu Shengjun , Khan Zullatun Gull , Uzair chishti Muhammad
Published: March 2021

Multilabel recognition of morphological images and detection of cancerous areas are difficult to locate in the scenario of the image redundancy and less resolution. Cancerous tissues are incredibly tiny in various scenarios. Therefore, for automatic classification, the characteristics of cancer patches in the X-ray image are of critical importance. Due to the slight variation between the textures, using just one feature or using a few features contributes to inaccurate classification outcomes. The present study focuses on five different algorithms for extracting features that can extract further different features. The algorithms are GLCM, LBGLCM, LBP, GLRLM, and SFTA from 8 image groups, and then, the extracted feature spaces are combined. The dataset used for classification is most probably imbalanced. Additionally, another focal point is to eradicate the unbalanced data problem by creating more samples using the ADASYN algorithm so that the error rate is minimized and the accuracy is increased. By using the ReliefF algorithm, it skips less contributing features that relieve the burden on the process. Finally, the feedforward neural network is used for the classification of data. The proposed method showed 99.5% micro, 99.5% macro, 0.5% misclassification, 99.5% recall rats, specificity 99.4%, precision 99.5%, and accuracy 99.5%, showing its robustness in these results. To assess the feasibility of the new system, the INbreast database was used.
Heart-Protective Mechanical Ventilation in Postoperative Cardiosurgical Patients
Authors: Mazurok Vadim , Kasherininov Igor , Bautin Andrey , Kulemina Olga , Rzheutskaya Ryta
Published: March 2021

Background. This study compared the hemodynamic effects and gas exchange under several different ventilator settings—with regard to tidal volume, respiratory rate, and end-expiratory pressure—in patients after coronary artery bypass grafting (CABG). Methods. Prospective interventional cohort study with a controlled group in a single cardiosurgical ICU involving 119 patients following on-pump CABG surgery. During the 1st postoperative hour, the intervention group patients were ventilated with Vt 10 ml × kg−1, RR 14/min, PEEP 5 cmH2O (“conventional ventilation”). During the 2nd hour, RR was reduced to 8/min (“reduced RR ventilation”). At 3 hrs, Vt was decreased to 6 ml × kg−1, RR returned to 14/min, and PEEP increased to 10 cmH2O (“low Vt-high PEEP ventilation”). Results. Patients in the “low Vt-high PEEP” ventilation period showed significantly lower alveolar ventilation and thoraco-pulmonary compliance than during “reduced RR” ventilation. Mean airway pressure and Vds/Vt peaked during low Vt-high PEEP ventilation; however, driving pressure was lower. Vt decrease and PEEP increase did not lead to oxygenation improvement and worsened CO2 elimination. Hemodynamically, the study revealed significant cardiac output decrease during low Vt-high PEEP ventilation. In 23.2% of patients, catecholamine therapy was initiated. Conclusions. In postoperative cardiosurgical patients, MV with Vt 6 ml × kg−1 and PEEP 10 cm H2O is characterized by worsened oxygenation and elimination of CO2 and a less favorable hemodynamic profile than ventilation with Vt 10 ml × kg−1 and PEEP 5 cmH2O. New and Noteworthy. (i) Patients after CABG may be especially sensitive to low tidal volume and increased PEEP as it negatively affects hemodynamic profile by means of the right heart preload decrease and afterload increase. (ii) Mechanical ventilation settings aiming to minimize mean airway pressure reduce the negative effects of positive inspiratory pressure and are favorable for hemodynamics.
Increasing Quantity and Internal Quality of Japanese Quail (Coturnix coturnix japonica) Eggs by Shooting Laser Puncture at Reproductive Acupuncture Points
Authors: Warsito Sunaryo Hadi , Adikara Tatang Santanu , Megasari Septiana , Pratama Ilham Radifan , Lamid Mirni , Hermadi Herry Agoes
Published: March 2021

This study aims to determine the effect of laser puncture shooting on the reproductive acupuncture points of Japanese quail (Coturnix coturnix japonica) egg quantity (egg production) and internal egg quality (Haugh unit, yolk index, and yolk colour). This research was conducted for 30 days using a sample of Japanese quail aged 4 weeks because for the first 2 weeks, the quail did not produce and it was in production in the last 2 weeks. There were 4 treatments and 25 replications each. So, there were a total of 100 quails. Laser puncture shooting was carried out at 3-day intervals at the Ova point and 6-day intervals at Hu Men, Bei Ji, and Wei Gen points. So, on the first day, laser puncture shooting was carried out at 4 points, on the 4th day, only at 1 point, and then, on the 7th day, it returned to 4 points. And so, it was carried out for 4 weeks. T0 (−) was considered as a negative control because quails are not given laser puncture shooting; T0 (+) was considered as a positive control because quails are treated with laser puncture shooting which is deactivated or a dose of 0 Joule; T1 was a group treated with laser puncture shooting at a dose of 0.2 Joule, and T2 was a group treated with laser puncture shooting at a dose of 0.5 Joule. Then, the research results were analyzed using Analysis of Variance and followed by Duncan’s Multiple Range Test. Laser puncture shooting at the reproductive acupuncture point of Japanese quail (Coturnix coturnix japonica) can increase the quantity of eggs (

p
<
0.05

). While the results of the egg internal quality in the form of the Haugh unit value and the yolk index increased (

p
<
0.05

), the value of the yolk colour did not change compared to the control (

p
>
0.05

). Laser puncture shooting at the reproductive acupuncture point of Japanese quail (Coturnix coturnix japonica) can increase egg quantity (egg production) and internal egg quality (Haugh unit and yolk index) with the best dose of 0.5 Joule.
Deformation Mechanism and Support Technology of Deep and High‐Stress Soft Rock Roadway
Authors: Zheng Lujing , Zuo Yujun , Hu Yafei , Wu Wei
Published: March 2021

In this study, the analysis and control of stability of surrounding rock in deep fractured soft rock roadway located in the underground mine of Jinfeng gold mine in Guizhou Province, China, has been investigated. The surrounding rock of roadway has been analyzed to characterize its deformation and failure mechanism through field survey, testing of rock physical and mechanical properties, in situ stress measure, analysis of mineral components of rock, and investigation of rock fragmentation degree. Based on the numerical simulation technology, the influence of different factors on the stability of roadway is studied. The physical and mechanical properties of surrounding rock and the bearing capacity of surrounding rock layer are to be improved to maintain the stability of broken soft rock roadway as high ground stress, rock fragmentation, and poor lithology leading to tunnel instability. Hence, a high‐strength “cable bolt + fiber‐reinforced shotcrete + steel mesh + split sets + resin bolt + cement grouting” combined support system has been proposed to improve the effective bearing structure significantly with high integrity and bearing capacity.
I‐GANs for Infrared Image Generation
Authors: Li Bing , Xian Yong , Su Juan , Zhang Da Q. , Guo Wei L.
Published: March 2021

The making of infrared templates is of great significance for improving the accuracy and precision of infrared imaging guidance. However, collecting infrared images from fields is difficult, of high cost, and time‐consuming. In order to address this problem, an infrared image generation method, infrared generative adversarial networks (I‐GANs), based on conditional generative adversarial networks (CGAN) architecture is proposed. In I‐GANs, visible images instead of random noise are used as the inputs, and the D‐LinkNet network is also utilized to build the generative model, enabling improved learning of rich image textures and identification of dependencies between images. Moreover, the PatchGAN architecture is employed to build a discriminant model to process the high‐frequency components of the images effectively and reduce the amount of calculation required. In addition, batch normalization is used to optimize the training process, and thereby, the instability and mode collapse of the generated adversarial network training can be alleviated. Finally, experimental verification is conducted on the produced infrared/visible light dataset (IVFG). The experimental results reveal that high‐quality and reliable infrared data are generated by the proposed I‐GANs.
Fractional Plasticity Model for Coarse Aggregates Incorporating Particle Breakage under Triaxial Loading
Authors: Yang Jiangong , Sun Yifei
Published: March 2021

Fractional plasticity has been originally proposed for capturing the state‐dependent nonassociated behaviour of sand, with no use of state variables and additional plastic potentials. However, for coarse aggregates, significant particle breakage would occur, which could influence the stress‐strain behaviour of the material, by shifting the critical state line in the e − ln  p′ plane. In this note, an extension of the fractional plasticity for constitutive modelling of coarse aggregates is made by incorporating particle breakage under triaxial loading. The developed model is validated by simulating a series of laboratory test results of different coarse aggregates under triaxial loading, where a good agreement between the model simulations and test results is observed.
TIFNCWBHG-MAGDM for System Evaluation Based on TIFNs for the Safety Input of Coal Enterprise
Authors: Zhang Chao , Qi Qingjie
Published: March 2021

Determining the safety input structure is essential to achieve efficient resource utilization and the safe production of coal enterprises. In this paper, the system evaluation method, TIFNCWBHG-MAGDM, is proposed to evaluate the safety input of coal enterprises. It is based on the integration of the intuitionistic triangular fuzzy numbers (TIFNs), TIFNs Compound Weight Bonferroni Hybrid Geometric (TIFNCWBHG) operator, and multiattribute group decision-making (MAGDM) theory. First, the judgment matrix of TIFNs is constructed from multiperspective: multitime points, multiattributes, and multiexperts. The TIFNCWBHG operator integrates the TIFNs score function, stability weight, and position weight. Then, the priorities for safety inputs are determined. The experimental results showed that safety inputs in industrial hygiene, propaganda, and education significantly impact the overall level of safety inputs. Also, it was proved that the efficiency of the safety input is important. The proposed TIFNCWBHG-MAGDM effectively coordinated the stability weight, position weight, and computation of TIFNs score function, taking the advantages of TIFNs. Accordingly, it was proved that it could optimize the safety input structure.
Convolutional Neural Network for Voltage Sag Source Azimuth Recognition in Electrical Internet of Things
Authors: Kai Ding , Wei Li , Jianfeng Sun , Xianyong Xiao , Ying Wang
Published: March 2021

Recognition and analytics at the edge enable utility companies to predict and prevent problems in real time. Clearing the voltage sag disturbance source by the positioning method is the most effective way to solve and improve the voltage sag. However, for different grid structures and fault types, the existing methods usually achieve a sag source location based on the single feature of monitoring data extraction. However, due to the effectiveness and applicability of the existing method features, this paper proposes a multidimensional feature of the voltage sag source positioning method of the matrix. Based on the analysis of the characteristics of the voltage sag event caused by the fault, this paper proposes a multidimensional feature matrix for voltage sag source location, based on the convolutional neural network to establish the mapping relationship between the feature matrix and the voltage sag position, thus achieving multiple points based on multiple points. The voltage sag source orientation is identified by the monitoring data. Finally, the voltage sag event caused by the short‐circuit fault is simulated in the IEEE14 node model, and the effectiveness of the proposed method is verified by simulation data. The simulation results show that the proposed method has higher accuracy than the traditional method, and the method can be applied to different grid structures and different types of faults.
Generative Adversarial Network for Image Raindrop Removal of Transmission Line Based on Unmanned Aerial Vehicle Inspection
Authors: Xu Changbao , Gao Jipu , Wen Qi , Wang Bo
Published: March 2021

In the process of UAV line inspection, there may be raindrops on the camera lens. Raindrops have a serious impact on the details of the image, reducing the identification of the target transmission equipment in the image, reducing the accuracy of the target detection algorithm, and hindering the practicability of UAV line inspection technology in cyber‐physical energy systems. In this paper, the principle of raindrop image formation is studied, and a method of raindrop removal based on generation countermeasure network is proposed. In this method, the attention recurrent network is used to generate the raindrop attention map, and the context code decoder is used to generate the raindrop image. The experimental results show that the proposed method can remove the raindrops in the image and repair the background image of raindrop coverage area and can generate a higher quality raindrop removal image than the traditional method.
Acute Effects of Ketamine Infusion on Postoperative Mood Scores in Patients Undergoing Dilation and Curettage: A Randomized Double-Blind Controlled Study
Authors: Mostafa Raham Hasan , Khamis Ahmed Mohamed , Saleh Ashraf Nabil , Mekki Yehia Mamdouh Hassan , Kamal Mohamed Mohamed , Ibrahim Ismail Mohammed , Ismaiel Mohamed Abdulmohsen Abdulnaiem
Published: March 2021

Background. Emotional and psychological effects following abortion are more common than physical side effects and can range from mild regret to more serious complications such as depression. In the last decade, it has been suggested that low dose of ketamine is a fast-acting antidepressant. Purpose. The aim of this study was to investigate the impact of intraoperative ketamine infusion on postoperative mood score in patients undergoing Dilation and Curettage (D&C) under spinal anesthesia. We hypothesized that a single low-dose administration of ketamine infusion during D&C surgery can improve mood scores in the immediate postoperative period. Methods. A prospective, randomized, double-blind, parallel-group, placebo-controlled trial. The study included a total of 60 patients, ≥18 years, physical status ASA II, with up to 12-week gestation undergoing elective D&C surgery. Patients were divided randomly into a ketamine group (group K) and a control group (group C). In group K, 0.4 mg/kg ketamine was given as a continuous infusion over 20 min intraoperatively. Main Outcome Measure. Profile of Mood States (POMS) was recorded preoperatively and 2 hours postoperatively. Results. There were no differences in preoperative POMS between the two groups. Mean postoperative POMS of group K was lower than that of group C indicating mood improvement. Ketamine group patients showed higher sedation score and increased, although self-limiting, psychedelic phenomena than the control group. Conclusion. Observed data here support an acute effect of ketamine on mood but any further claim will be speculative. Further future studies exploring postoperative mood scores after 24 hours post-infusion are needed. This trial is registered with PACTR201907779292947.
Negative Energy Solutions for a New Fractionalpx-Kirchhoff Problem without the (AR) Condition
Authors: Bu Weichun , An Tianqing , Ye Guoju , Taarabti Said
Published: March 2021

In this paper, we investigate the following Kirchhoff type problem involving the fractionalpx-Laplacian operator.a−b∫Ω×Ωux−uypx,y/px,yx−yN+spx,ydxdyLu=λuqx−2u+fx,ux∈Ωu=0 x∈∂Ω,, whereΩis a bounded domain inℝNwith Lipschitz boundary,a≥b>0are constants,px,yis a function defined onΩ¯×Ω¯,s∈0,1, andqx>1,Luis the fractionalpx-Laplacian operator,N>spx,y, for anyx,y∈Ω¯×Ω¯,px∗=px,xN/N−spx,x,λis a given positive parameter, andfis a continuous function. By using Ekeland’s variational principle and dual fountain theorem, we obtain some new existence and multiplicity of negative energy solutions for the above problem without the Ambrosetti-Rabinowitz ((AR) for short) condition.
End‐to‐End Ship Detection in SAR Images for Complex Scenes Based on Deep CNNs
Authors: Chen Yao , Duan Tao , Wang Changyuan , Zhang Yuanyuan , Huang Mo
Published: March 2021

Ship detection on synthetic aperture radar (SAR) imagery has many valuable applications for both civil and military fields and has received extraordinary attention in recent years. The traditional detection methods are insensitive to multiscale ships and usually time‐consuming, results in low detection accuracy and limitation for real‐time processing. To balance the accuracy and speed, an end‐to‐end ship detection method for complex inshore and offshore scenes based on deep convolutional neural networks (CNNs) is proposed in this paper. First, the SAR images are divided into different grids, and the anchor boxes are predefined based on the responsible grids for dense ship prediction. Then, Darknet‐53 with residual units is adopted as a backbone to extract features, and a top‐down pyramid structure is added for multiscale feature fusion with concatenation. By this means, abundant hierarchical features containing both spatial and semantic information are extracted. Meanwhile, the strategies such as soft non‐maximum suppression (Soft‐NMS), mix‐up and mosaic data augmentation, multiscale training, and hybrid optimization are used for performance enhancement. Besides, the model is trained from scratch to avoid learning objective bias of pretraining. The proposed one‐stage method adopts end‐to‐end inference by a single network, so the detection speed can be guaranteed due to the concise paradigm. Extensive experiments are performed on the public SAR ship detection dataset (SSDD), and the results show that the method can detect both inshore and offshore ships with higher accuracy than other mainstream methods, yielding the accuracy with an average of 95.52%, and the detection speed is quite fast with about 72 frames per second (FPS). The actual Sentinel‐1 and Gaofen‐3 data are utilized for verification, and the detection results also show the effectiveness and robustness of the method.
Case Report of a Rare Incidence of IgH Amplification Leading to Acute Kidney Injury in a Multiple Myeloma Patient
Authors: Thanikachalam Sowmya , Srinivasalu Vijay Kumar , Nataraj K.S. , Damodar Sharat , Das Manjula
Published: March 2021

We present a case report of a 62-year-old male, treated for kappa light chain multiple myeloma with chemotherapy followed by autologous stem cell transplant (ASCT) in 2014. He has been in complete remission for 4 years. In 2018, he was evaluated for hypercreatinemia and acute kidney injury(AKI) with a suspicion of disease relapse; he underwent evaluation with bone marrow aspiration cytology which showed no evidence of relapse. However, careful cytogenetic analyses showed IgH amplification (14q32) which probably was the cause for AKI in the absence of any structural abnormality in the kidney. Heavy chain deposition leads to AKI in multiple myeloma, and its association with IgH amplification leading to AKI is reported here. Though heavy chain deposition leading to AKI is common, IgH amplification at chromosome level is the first case observed.
Post-Surgery Subcutaneous Seeding of Laryngeal Squamous Cell Carcinoma: A Rare Case
Authors: Jiang Yongquan , Cao Wanxin , Luo Yuanbo , Xu Ji , Li Ying , Li Jiping
Published: March 2021

Laryngeal squamous cell carcinoma (LSCC) is the most common malignant head and neck cancer, with a 40% recurrence rate in the first 3 years after radical treatment. Recurrence of LSCC mostly comprises lymphogenous metastasis, hematogenic metastasis, and locoregional recurrence, while LSCC seeding is rarest: there are only 4 cases reported in PubMed, and none of them is one of subcutaneous seeding. We report a case with post-surgery subcutaneous seeding of LSCC. The final biopsy demonstrated that the subcutaneous seeding of the LSCC was 2 cm away from the primary lesion, with no recurrent foci observed in the larynx and tracheostoma and little relation to the primary lesion. Thus, we drew the conclusion that LSCC surgeries should stick to the principle of the non-tumor technique to prevent subcutaneous seeding.
Calcitonin-Negative Neuroendocrine Carcinoma of the Thyroid Gland: Case Report and Literature Review
Authors: Fernández-Ferreira Ricardo , De la Peña-López Ildefonso Roberto , Zamudio-Coronado Karla Walkiria , Delgado-Soler Luis Antonio , Torres-Pérez María Eugenia , Bourlón-de los Ríos Christianne , Cortés-González Rubén
Published: March 2021

Calcitonin-negative neuroendocrine tumor (CNNET) of the thyroid is an extremely rare entity. In some of the previously reported cases within the literature, the terms “atypical medullary thyroid carcinoma,” “calcitonin-free oat cell carcinoma,” and “a distinct clinical entity” were applied to NETs without definitive evidence of calcitonin production. In the English-language literature, not only are there only few reported cases of CNNET, but the criteria for diagnosis in these cases are also controversial. Most of the current published cases were also treated surgically for local disease. We describe a case of NET of the thyroid with calcitonin, chromogranin A and thyroglobulin negativity, synaptophysin and TTF-1 positivity, and a high Ki-67 proliferation index with metastases in the cervical region as well as mediastinal adenopathies. This case was considered an unresectable thyroid carcinoma, and chemotherapy including cisplatin and etoposide was started as neoadjuvant treatment at the department of medical oncology. Total thyroidectomy plus bilateral and central cervical dissection was performed, and the patient underwent 2 cycles of adjuvant radiotherapy. Currently, the patient’s 18F-FDG-PET/CT findings show a complete response 17 months after diagnosis. In conclusion, CNNET of the thyroid is very rare and there is limited evidence regarding treatment in patients with metastases. Chemotherapy including cisplatin and etoposide as well as early aggressive surgical resection appears to positively impact patients’ survival.
Leptomeningeal Carcinomatosis with Delayed Ocular Manifestations
Authors: Czyz Craig , Blair Kyle , Bergstrom Reece
Published: March 2021

The most common presenting symptoms of leptomeningeal carcinomatosis (LC) are ocular manifestations with vision loss. There are multiple reports of undiagnosed LC causing sudden, complete, monocular vision loss as the presenting symptom; however, sudden bilateral vision loss 6 months following diagnosis has not been described. Any new ocular involvement or worsening of previous ocular symptoms warrants reimaging and prompt ophthalmology consultation, as this likely indicates disease progression. This report details a unique case of LC where a previously diagnosed patient developed sudden, complete, bilateral vision loss and multiple cranial nerve palsies with progression of LC on imaging.
Liver Segmentectomy by Intrahepatic Lithiasis
Authors: Rayya Fadi , Alhasan Ehab
Published: March 2021

Intrahepatic cholelithiasis, which is defined as stones proximal to the confluence of the hepatic ducts, is considered endemic in Southeast Asia. Its pathogenesis is not completely understood yet. A 19-year-old female was admitted to the hospital with a history of recurrent biliary pancreatitis. Abdominal ultrasound detected normal gallbladder while magnetic resonance cholangiopancreatography revealed lithiasis at the hepatic duct of liver segment V. After preoperative evaluation a typical segmentectomy was done. The postoperative period was uneventful and the patient was well at 6-month follow-up.
Idiopathic Hypereosinophilic Syndrome with Multiple Organ Involvement
Authors: Abo Shdid Reham , Azrieh Bahjat , Alebbi Seham , Mansour Shafik , Naeem Muhammad
Published: March 2021

Idiopathic hypereosinophilic syndrome is a rare disease which is diagnosed after excluding other conditions. The syndrome is characterized by multiple organ involvement including the heart, nervous system, lungs, and gastrointestinal tract. The disease is suspected if there is peripheral blood eosinophilia and no clear etiology. The main treatment is corticosteroids. Patients who do not respond to corticosteroids can be treated with imatinib, immunomodulatory agents, myelosuppressive therapy, or mepolizumab. Alemtuzumab can be considered in severe cases that are unresponsive to other therapies. In this paper, we describe a case of idiopathic hypereosinophilic syndrome with mainly cardiac system involvement and left ventricular thrombus formation which was complicated by cerebral thromboemboli while on warfarin with international normalized ratio in the therapeutic range. Our patient responded well to steroids appreciated by improvement in clinical symptoms and decrease in eosinophil count.
Efficiency of a 15-Week Weight-Loss Program, Including a Low-Calorie Formula Diet, on Glycemic Control in Patients with Type 2 Diabetes Mellitus and Overweight or Obesity
Authors: Storck Lena J. , Meffert Peter J. , Rausch Janine , Gärtner Simone , Aghdassi Ali A. , Kühn Jens-Peter , Kraft Matthias , Pietzner Maik , Lerch Markus M. , Steveling Antje
Published: March 2021

Introduction: Patients who are overweight or obese have an increased risk of developing type 2 diabetes mellitus (T2DM). Weight loss can have a positive effect on glycemic control. Objective: We aimed to investigate glycemic control in patients with T2DM and overweight or obesity during a structured weight-loss program. Methods: This was a prospective, interventional study. We recruited 36 patients (14 men and 22 women) with a median age of 58.5 years and median body mass index (BMI) of 34.1, to a 15-week structured weight-loss program with a low-calorie (800 kcal) formula diet for 6 weeks. The primary end point, HbA1c level, and secondary end points, anthropometric data, medication, and safety, were assessed weekly. Laboratory values and quality of life were assessed at baseline and after 15 weeks. Results: HbA1c decreased from 7.3% at baseline to 6.5% at 15 weeks (p < 0.001), median body weight by 11.9 kg (p < 0.001), median BMI by 4.3 (p < 0.001) and median waist circumference by 11.0 cm (p < 0.001). Two participants discontinued insulin therapy, 4 could reduce their dosage of oral antidiabetic agents, and 6 completely discontinued their antidiabetic medication. Insulin dose decreased from 0.63 (0.38–0.89) to 0.39 (0.15–0.70) units/kg body weight (p < 0.001). No patient experienced hypoglycemic episodes or hospital emergency visits. Triglycerides and total cholesterol decreased as well as surrogate markers of liver function. However, the levels of high-density and low-density lipoprotein cholesterol (HDL-C and LDL-C) as well as uric acid remain unchanged. Regarding quality of life, the median physical health score increased from 44.5 (39.7–51.4) at baseline to 48.0 (43.1–55.3; p = 0.007), and the median mental health score decreased from 42.1 (36.1–46.7) to 37.4 (30.3–43.7; p = 0.004). Conclusions: A structured weight-loss program is effective in the short term in reducing HbA1c, weight, and antidiabetic medication in patients with T2DM who are overweight or obese. Levels of HDL-C and LDL-C were not affected by short-term weight loss. The decline in mental health and the long-term effects of improved glycemic control require further trials.
Locally Invasive Diffuse Iris Ring Melanoma Presenting as Unilateral Severe Glaucoma: Case Report and Review of Molecular Genetics
Authors: Naguib Mina M. , Chévez-Barrios Patricia , Orengo-Nania Silvia , Schefler Amy C.
Published: March 2021

We report the clinical history and histopathological findings in a case of diffuse iris ring melanoma (DIM) and review the most recent literature and modern molecular genetics of this entity. An 85-year-old Hispanic man presented with severe unilateral glaucoma, managed at an outside institution for 2 years prior to presentation. Diffuse pigmentation was noted in the angle, on the intraocular lens implant, and in the vitreous without clear demonstration of a mass on ultrasound biomicroscopy. Workup for metastatic cutaneous melanoma was negative. Histopathological examination of the enucleated eye revealed a mixed cell type iris ring melanoma with diffuse intraocular involvement. Gene expression profiling (GEP) revealed a class 2 molecular signature indicating a very high risk for metastases. Unilateral glaucoma presenting with marked pigmentation in the anterior chamber angle should be managed as melanoma until proven otherwise. Iris ring melanomas are known to have an aggressive clinical course, and recent molecular analyses indicate that they are likely primarily GEP class 2 with a very poor prognosis, similar to the majority of ciliary body melanomas.
Unusual Tissue – Unusual Issue: Pancreatic Heterotopia Presenting as Gastric Outlet Obstruction
Authors: Nguyen Thu L. , Kapur Shivani , Schlack-Haerer Stephen C. , Gurda Grzegorz T. , Folkers Milan E.
Published: March 2021

Pancreatic heterotopia (PH) is a common, but typically small (<1 cm), incidental and asymptomatic finding; however, PH should be considered even for large and symptomatic upper gastrointestinal masses. A 27-year-old white woman presented with a 3-week history of burning epigastric pain, nausea, early satiety, and constipation. Physical examination revealed epigastric and right upper quadrant tenderness with normal laboratory workup, but imaging revealed a 5-cm, partly cystic mass arising from the gastric antrum with resulting pyloric stenosis and partial gastric outlet obstruction. Endoscopic ultrasound-guided fine needle aspiration revealed PH – an anomalous pancreatic tissue lying in a nonphysiological site. The patient ultimately underwent a resection and recovered uneventfully, with a complete pathologic examination revealing normal exocrine pancreatic tissue (PH type 2) without malignant transformation. We report a case of heterotopic pancreas manifesting as severe gastric outlet obstruction, in addition to a thorough diagnostic workup and surgical follow-up, in a young adult. Differential diagnoses and features that speak to benignity of a large, symptomatic mass lesion (PH in particular) are discussed.