bluuebunny/crossref_metadata_2025 huggingface dataset:
Cinco preguntas para analizar tendencias de regulación de comercio internacional: entre multilateralidad, regionalismo y proteccionismo
Authors: Szegedy-Maszák Ildikó
Published: June 2022

Este artículo es el resultado de una investigación sobre las tendencias actuales de la regulación del comercio internacional. La investigación se basó en un método interdisciplinario en el que se utilizaron enfoques de economía política y relaciones internacionales para analizar los principales desafíos de la regulación del comercio multilateral en la Organización Mundial del Comercio. El efecto China, la falta de apoyo político de Estados Unidos durante la administración del expresidente Donald Trump, así como las fallas internas del sistema son consideradas como posibles causas de la actual crisis de la Organización Mundial del Comercio. No obstante, el choque del sistema capitalista estatal chino con el sistema multilateral de comercio basado en economías de mercado se considera un factor importante de la crisis actual. La guerra comercial es una manifestación de esta crisis. La actual regionalización del comercio es otra fuerza motriz peligrosa presente en el sistema de comercio mundial. Se propone una solución basada en las perspectivas del derecho transnacional para evitar el desarrollo de una globalización fragmentada.
An automated piecewise synthesis method for cetacean tonal sounds based on time-frequency spectrogram
Authors: Sun Zhongbo , Jiang Jiajia , Li Yao , Li Chunyue , Li Zhuochen , Fu Xiao , Duan Fajie
Published: June 2022

Bionic signal waveform design plays an important role in biological research, as well as bionic underwater acoustic detection and communication. Most conventional methods cannot construct high-similarity bionic waveforms to match complex cetacean sounds or easily modify the time-frequency structure of the synthesized bionic signals. In our previous work, we proposed a synthesis and modification method for cetacean tonal sounds, but it requires a lot of manpower to construct each bionic signal segment to match the tonal sound contour. To solve these problems, an automated piecewise synthesis method is proposed. First, based on the time-frequency spectrogram of each tonal sound, the fundamental contour and each harmonic contour of the tonal sound is automatically recognized and extracted. Then, based on the extracted contours, four sub power frequency modulation bionic signal models are combined to match cetacean sound contours. Finally, combining the envelopes of the fundamental frequency and each harmonic, the synthesized bionic signal is obtained. Experimental results show that the Pearson correlation coefficient (PCC) between all true cetacean sounds and their corresponding bionic signals are higher than 0.95, demonstrating that the proposed method can automatically imitate all kinds of simple and complex cetacean tonal sounds with high similarity.
Influence of thermal deformations on sound absorption of three-dimensional printed metamaterials
Authors: Cingolani Matteo , Fusaro Gioia , Fratoni Giulia , Garai Massimo
Published: June 2022

Acoustic metamaterials (AMMs) are designed with complex geometrical shapes to obtain unconventional sound-absorbing performances. As additive manufacturing is particularly suited to print complex structures in a more straightforward and controllable way, AMMs often exploit three-dimensional (3-D) printing techniques. However, when exposed to different temperature conditions, such structures can be affected by geometrical deformations, especially when they are polymer-based. This can cause a mismatch between the experimental data and the expected theoretical performance; therefore, it is important to take thermal effects into account. The present paper investigates the influence of thermal deformations on the sound absorption of three geometries: a coplanar spiral tube, a system with double coiled resonators, and a neck-embedded resonator. Measurements were performed on each 3-D printed specimen in the impedance tube after the samples had been placed in a climate chamber to modify the temperature settings (T = 10–50 °C). Numerical models, validated on the measurements, were employed to quantify the geometrical deformation of AMM structures through a multiphysics approach, highlighting the effects of thermal stress on the acoustic behavior. The main outcomes prove that the frequency shifts of sound absorption peaks depend on temperature configurations and follow exponential regressions, in accordance with previous literature on polymeric materials.
Rheology and microstructure of discontinuous shear thickening suspensions
Authors: Prabhu Tekkati Ajeeth , Singh Anugrah
Published: June 2022

We report experimental studies on rheology and microstructure in discontinuous shear thickening of fumed silica suspensions. Formation of particle clusters was observed after the critical shear rate, and their size increases during shear thickening. At higher shear rates, these clusters were found to break down due to strong shear forces, and a continuous decrease in viscosity was observed. The suspension viscosity and the first normal stress difference variation with the shear rate showed similar dependence. The sign of first normal stress difference was negative during shear thickening, which is consistent with the hydrodynamic model of cluster formation. A linear variation of the first normal stress difference with shear rate during shear thickening further indicates its predominant hydrodynamic origin and supports the recent Stokesian dynamics simulation studies on discontinuous shear thickening based on the hydrodynamic model of nonsmooth colloids by Wang et al. [J. Rheol. 64, 379–394 (2020)]. On the other hand, a nonlinear decrease in the first normal stress difference with shear rate in the second shear-thinning region is primarily due to breaking of large clusters into smaller ones and with a possibility of frictional contacts within these hydroclusters. The oscillatory shear measurements were also performed and the samples displayed strain thickening similar to shear thickening. The similarity between the steady and dynamic shear rheology at high strain amplitudes was observed using the modified Cox–Merz rule.
Pseudomonas aeruginosa
Secretes the Oxylipin Autoinducer Synthases OdsA and OdsB via the Xcp Type 2 Secretion System
Authors: Martínez Eriel , Orihuela Carlos J. , Campos-Gomez Javier
Published: June 2022

We previously showed that the ODS of
P. aeruginosa
produces and responds to oxylipins derived from host oleic acid by enhancing biofilm formation and virulence. Here, we developed a genetic screen strategy to explore the molecular basis for oxylipins synthesis and detection.
An Upper-Division, Remote Microbiology Laboratory That Blends Virtual and Hands-on Components to Promote Student Success during the COVID-19 Pandemic
Authors: Guzman-Cole Candace , García-Ojeda Marcos E.
Published: June 2022

The COVID-19 shutdown forced many institutions of higher education to shift in-person teaching to emergency remote teaching. This was particularly challenging for laboratory courses, where students are expected to learn hands-on skills needed for their career goals.
Assessing the Variability of Cell-Associated HIV DNA Quantification through a Multicenter Collaborative Study
Authors: Le Duff Yann , Gärtner Kathleen , Busby Eloise J. , Dalzini Annalisa , Danaviah Sivapragashini , Fuentes José Luis Jiménez , Giaquinto Carlo , Huggett Jim F. , Hurley Matthew , Marcellin Anne-Geneviève , Muñoz-Fernández María Ángeles , O’Sullivan Denise M. , Persaud Deborah , Powell Laura , Rigsby Peter , Rossi Paolo , de Rossi Anita , Siems Lilly , Smit Theresa , Watters Sarah A. , Almond Neil , Nastouli Eleni
Published: June 2022

Despite a global effort, HIV remains a major public health burden with an estimated 1.5 million new infections occurring in 2020. HIV DNA is an important viral marker, and its monitoring plays a critical role in the fight against HIV: supporting diagnosis in infants and underpinning clinical management of patients under therapy.
Limosilactobacillus reuteri SLZX19-12 Protects the Colon from Infection by Enhancing Stability of the Gut Microbiota and Barrier Integrity and Reducing Inflammation
Authors: Wu Jianmin , Lin Zishen , Wang Xian , Zhao Ying , Zhao Jinbiao , Liu Hu , Johnston Lee J. , Lu Lin , Ma Xi
Published: June 2022

The use of antibiotics to treat bacterial infections leads to a series of side effects. As an alternative method, the biocontrol strategy, which uses probiotics to suppress pathogens, is considered a potential way to deal with bacterial infections in gut.
Peritonsillar abscess due to temporomandibular joint septic arthritis: an uncommon cause of a common disease
Authors: Thakur Neha , Negi Sarita , Thakur Jagdeep S , Arora Ripu Daman
Published: June 2022

Peritonsillar abscess is a common presentation of complicated acute tonsillitis. The temporomandibular joint septic arthritis is an uncommon clinical entity while its complications are further rare. We present a case of a man in his late 30s who presented with a painful swelling in the left preauricular region along with increasing trismus. A diagnosis of peritonsillar abscess due to septic arthritis was made based on clinical history and examination. Patient recovered fully after antibiotic and abscess drainage. This is the first case report of temporomandibular septic arthritis leading to peritonsillar abscess.
Continuous cardiac monitoring in a patient with terminal pulmonary hypertension and eventual bilateral lung transplantation
Authors: Andersen Mads Ørbæk , Diederichsen Søren Zöga , Svendsen Jesper Hastrup , Carlsen Jørn
Published: June 2022

As pulmonary arterial hypertension (PAH) progress, arrhythmias are becoming an increasingly prominent phenomenon. Supraventricular tachycardias have been shown to have an incidence of up to 35% in pulmonary hypertension.

Continuous cardiac monitoring was deployed in a patient with severe PAH 100 days before bilateral lung transplantation (BLTX). Despite being graded as WHO functional class IV, no arrhythmias were observed before BLTX. Furthermore, the case describes clinical improvement, along with a significant increase in heart rate variability (HRV) and decrease in night-time heart rate in the post-transplantation period.

No arrhythmias were observed preoperatively during continuous monitoring in a 100-day period despite the patient’s intrinsically high risk for arrhythmias. Increasing HRV and lower resting heart rate were observed after BLTX. Since these parameters correlate with the clinical condition, they might be valuable in risk assessment in patients with pulmonary hypertension.
Protocol for Rhapsody: a longitudinal observational study examining the feasibility of speech phenotyping for remote assessment of neurodegenerative and psychiatric disorders
Authors: Hampsey Elliot , Meszaros Marton , Skirrow Caroline , Strawbridge Rebecca , Taylor Rosie H , Chok Lazarus , Aarsland Dag , Al-Chalabi Ammar , Chaudhuri Ray , Weston Jack , Fristed Emil , Podlewska Aleksandra , Awogbemila Olabisi , Young Allan H
Published: June 2022

Introduction

Neurodegenerative and psychiatric disorders (NPDs) confer a huge health burden, which is set to increase as populations age. New, remotely delivered diagnostic assessments that can detect early stage NPDs by profiling speech could enable earlier intervention and fewer missed diagnoses. The feasibility of collecting speech data remotely in those with NPDs should be established.

Methods and analysis

The present study will assess the feasibility of obtaining speech data, collected remotely using a smartphone app, from individuals across three NPD cohorts: neurodegenerative cognitive diseases (n=50), other neurodegenerative diseases (n=50) and affective disorders (n=50), in addition to matched controls (n=75). Participants will complete audio-recorded speech tasks and both general and cohort-specific symptom scales. The battery of speech tasks will serve several purposes, such as measuring various elements of executive control (eg, attention and short-term memory), as well as measures of voice quality. Participants will then remotely self-administer speech tasks and follow-up symptom scales over a 4-week period. The primary objective is to assess the feasibility of remote collection of continuous narrative speech across a wide range of NPDs using self-administered speech tasks. Additionally, the study evaluates if acoustic and linguistic patterns can predict diagnostic group, as measured by the sensitivity, specificity, Cohen’s kappa and area under the receiver operating characteristic curve of the binary classifiers distinguishing each diagnostic group from each other. Acoustic features analysed include mel-frequency cepstrum coefficients, formant frequencies, intensity and loudness, whereas text-based features such as number of words, noun and pronoun rate and idea density will also be used.

Ethics and dissemination

The study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC reference: 21/PR/0070). Results will be disseminated through open access publication in academic journals, relevant conferences and other publicly accessible channels. Results will be made available to participants on request.

Trial registration number

NCT04939818.
Nuclear data evaluation for decay heat analysis of spent nuclear fuel over 1–100 k year timescale
Authors: Doran Hannah R. , Cresswell Alan J. , Sanderson David C. W. , Falcone Gioia
Published: June 2022

Accurate nuclear data are essential in the evaluation of decay heat from spent nuclear fuel (SNF). The accuracy of such data was assessed using an approach that compares values reported in different evaluated libraries and determines whether discrepancies reflect inaccuracies in primary data. A short list of 43 isotopes which are most significant to SNF decay heat calculations over 1–100 k years was produced by combining generic reactor inventory code with decay heat analysis for undifferentiated SNF. Decay properties (half-lives and decay energies) and neutron interactions (cross section and fission yields) were compared from 6 evaluated libraries. Fission product (FP) discrepancies identified are 90Sr half-life, where inclusion of a single measurement significantly reduces the evaluated value; 95mNb beta energy, where DDEP evaluation omits the decay to the 95Mo ground state; 99Tc beta energy, where evaluations differ by approximately 10% with a variety of shape factors used; 126Sb/126mSb beta (JEF2.2/3.1.1/3.3) and electron energies (JEFF3.1.1), where intensity differences are reported; and 137Cs beta energy, where ENDF/B-VIII.0 and JEF3.3 evaluations use incorrect shape factors. For actinides, the major discrepancies identified were 237Np alpha energy (JEF2.2/3.1.1) and 225Ac electron energies (ENDF/B-VIII.0) but overall show less discrepancies during long-term disposal (0.1–100 ky) compared to FP’s during interim storage (1–100 years). Further assessments of the 90Sr half-life and the best shape factor for the 99Tc beta decay are needed to improve future decay heat analyses, which are important for designing future stores and evaluating schemes for possible heat recovery.
SimNet
Authors: Li Lingda , Pandey Santosh , Flynn Thomas , Liu Hang , Wheeler Noel , Hoisie Adolfy
Published: June 2022

While cycle-accurate simulators are essential tools for architecture research, design, and development, their practicality is limited by an extremely long time-to-solution for realistic applications under investigation. This work describes a concerted effort, where machine learning (ML) is used to accelerate microarchitecture simulation. First, an ML-based instruction latency prediction framework that accounts for both static instruction properties and dynamic processor states is constructed. Then, a GPU-accelerated parallel simulator is implemented based on the proposed instruction latency predictor, and its simulation accuracy and throughput are validated and evaluated against a state-of-the-art simulator. Leveraging modern GPUs, the ML-based simulator outperforms traditional CPU-based simulators significantly.
WISEFUSE
Authors: Mahgoub Ashraf , Yi Edgardo Barsallo , Shankar Karthick , Minocha Eshaan , Elnikety Sameh , Bagchi Saurabh , Chaterji Somali
Published: June 2022

We characterize production workloads of serverless DAGs at a major cloud provider. Our analysis highlights two major factors that limit performance: (a) lack of efficient communication methods between the serverless functions in the DAG, and (b) stragglers when a DAG stage invokes a set of parallel functions that must complete before starting the next DAG stage. To address these limitations, we propose WISEFUSE, an automated approach to generate an optimized execution plan for serverless DAGs for a user-specified latency objective or budget. We introduce three optimizations: (1) Fusion combines in-series functions together in a single VM to reduce the communication overhead between cascaded functions. (2) Bundling executes a group of parallel invocations of a function in one VM to improve resource sharing among the parallel workers to reduce skew. (3) Resource Allocation assigns the right VM size to each function or function bundle in the DAG to reduce the E2E latency and cost. We implement WISEFUSE to evaluate it experimentally using three popular serverless applications with different DAG structures, memory footprints, and intermediate data sizes. Compared to competing approaches and other alternatives, WISEFUSE shows significant improvements in E2E latency and cost. Specifically, for a machine learning pipeline, WISEFUSE achieves P95 latency that is 67% lower than Photons, 39% lower than Faastlane, and 90% lower than SONIC without increasing the cost.
Expert-Calibrated Learning for Online Optimization with Switching Costs
Authors: Li Pengfei , Yang Jianyi , Ren Shaolei
Published: June 2022

We study online convex optimization with switching costs, a practically important but also extremely challenging problem due to the lack of complete offline information. By tapping into the power of machine learning (ML) based optimizers, ML-augmented online algorithms (also referred to as expert calibration in this paper) have been emerging as state of the art, with provable worst-case performance guarantees. Nonetheless, by using the standard practice of training an ML model as a standalone optimizer and plugging it into an ML-augmented algorithm, the average cost performance can be highly unsatisfactory. In order to address the "how to learn" challenge, we propose EC-L2O (expert-calibrated learning to optimize), which trains an ML-based optimizer by explicitly taking into account the downstream expert calibrator. To accomplish this, we propose a new differentiable expert calibrator that generalizes regularized online balanced descent and offers a provably better competitive ratio than pure ML predictions when the prediction error is large. For training, our loss function is a weighted sum of two different losses --- one minimizing the average ML prediction error for better robustness, and the other one minimizing the post-calibration average cost. We also provide theoretical analysis for EC-L2O, highlighting that expert calibration can be even beneficial for the average cost performance and that the high-percentile tail ratio of the cost achieved by EC-L2O to that of the offline optimal oracle (i.e., tail cost ratio) can be bounded. Finally, we test EC-L2O by running simulations for sustainable datacenter demand response. Our results demonstrate that EC-L2O can empirically achieve a lower average cost as well as a lower competitive ratio than the existing baseline algorithms.
Asymptotic Convergence Rate of Dropout on Shallow Linear Neural Networks
Authors: Senen-Cerda Albert , Sanders Jaron
Published: June 2022

We analyze the convergence rate of gradient flows on objective functions induced by Dropout and Dropconnect, when applying them to shallow linear Neural Networks(NN) ---which can also be viewed as doing matrix factorization using a particular regularizer. Dropout algorithms such as these are thus regularization techniques that use 0,1-valued random variables to filter weights during training in order to avoid coadaptation of features. By leveraging a recent result on nonconvex optimization and conducting a careful analysis of the set of minimizers as well as the Hessian of the loss function, we are able to obtain (i) a local convergence proof of the gradient flow and (ii) a bound on the convergence rate that depends on the data, the dropout probability, and the width of the NN. Finally, we compare this theoretical bound to numerical simulations, which are in qualitative agreement with the convergence bound and match it when starting sufficiently close to a minimizer.
A Detailed Look at MIMO Performance in 60 GHz WLANs
Authors: Aggarwal Shivang , Neelamraju Srisai Karthik , Bhat Ajit , Koutsonikolas Dimitrios
Published: June 2022

One of the key enhancements in the upcoming 802.11ay standard for 60 GHz WLANs is the support for simultaneous transmissions of up to 8 data streams via SU- and MU-MIMO, which has the potential to enable data rates up to 100 Gbps. However, in spite of the key role MIMO is expected to play in 802.11ay, experimental evaluation of MIMO performance in 60 GHz WLANs has been limited to date, primarily due to lack of hardware supporting MIMO transmissions at millimeter wave frequencies. In this work, we fill this gap by conducting the first large-scale experimental evaluation of SU- and MU-MIMO performance in 60 GHz WLANs. Unlike previous studies, our study involves multiple environments with very different multipath characteristics. We analyze the performance in each environment, identify the factors that affect it, and compare it against the performance of SISO. Further, we seek to identify factors that can guide beam and user selection to limit the (often prohibitive in practice) overhead of exhaustive search. Finally, we propose two heuristics that perform both user and beam selection with low overhead, and show that they perform close to an Oracle solution and outperform previously proposed approaches in both static and mobile scenarios, regardless of the environment and number of users.
MalRadar
Authors: Wang Liu , Wang Haoyu , He Ren , Tao Ran , Meng Guozhu , Luo Xiapu , Liu Xuanzhe
Published: June 2022

Mobile malware detection has attracted massive research effort in our community. A reliable and up-to-date malware dataset is critical to evaluate the effectiveness of malware detection approaches. Essentially, the malware ground truth should be manually verified by security experts, and their malicious behaviors should be carefully labelled. Although there are several widely-used malware benchmarks in our community (e.g., MalGenome, Drebin, Piggybacking and AMD, etc.), these benchmarks face several limitations including out-of-date, size, coverage, and reliability issues, etc. In this paper, we first make efforts to create MalRadar, a growing and up-to-date Android malware dataset using the most reliable way, i.e., by collecting malware based on the analysis reports of security experts. We have crawled all the mobile security related reports released by ten leading security companies, and used an automated approach to extract and label the useful ones describing new Android malware and containing Indicators of Compromise (IoC) information. We have successfully compiled MalRadar, a dataset that contains 4,534 unique Android malware samples (including both apks and metadata) released from 2014 to April 2021 by the time of this paper, all of which were manually verified by security experts with detailed behavior analysis. Then we characterize the MalRadar dataset from malware distribution channels, app installation methods, malware activation, malicious behaviors and anti-analysis techniques. We further investigate the malware evolution over the last decade. At last, we measure the effectiveness of commercial anti-virus engines and malware detection techniques on detecting malware in MalRadar. Our dataset can be served as the representative Android malware benchmark in the new era, and our observations can positively contribute to the community and boost a series of research studies on mobile security.
A Formalism of DNN Accelerator Flexibility
Authors: Kao Sheng-Chun , Kwon Hyoukjun , Pellauer Michael , Parashar Angshuman , Krishna Tushar
Published: June 2022

The high efficiency of domain-specific hardware accelerators for machine learning (ML) has come fromspecialization, with the trade-off of less configurability/ flexibility. There is growing interest in developingflexible ML accelerators to make them future-proof to the rapid evolution of Deep Neural Networks (DNNs). However, the notion of accelerator flexibility has always been used in an informal manner, restricting computer architects from conducting systematic apples-to-apples design-space exploration (DSE) across trillions of choices. In this work, we formally define accelerator flexibility and show how it can be integrated for DSE. % flows. Specifically, we capture DNN accelerator flexibility across four axes: %the map-space of DNN accelerator along four flexibility axes: tiling, ordering, parallelization, and array shape. We categorize existing accelerators into 16 classes based on their axes of flexibility support, and define a precise quantification of the degree of flexibility of an accelerator across each axis. We leverage these to develop a novel flexibility-aware DSE framework. %It respects the difference of accelerator flexibility classes and degree of flexibility support in different accelerators, creating unique map-spaces. %and forms a unique map space for exploration. % We demonstrate how this can be used to perform first-of-their-kind evaluations, including an isolation study to identify the individual impact of the flexibility axes. We demonstrate that adding flexibility features to a hypothetical DNN accelerator designed in 2014 improves runtime on future (i.e., present-day) DNNs by 11.8x geomean.
Aide-mémoire: Improving a Project’s Collective Memory via Pull Request–Issue Links
Authors: Pârţachi Profir-Petru , White David R. , Barr Earl T.
Published: June 2022

Links between pull request and the issues they address document and accelerate the development of a software project but are often omitted. We present a new tool, Aide-mémoire, to suggest such links when a developer submits a pull request or closes an issue, smoothly integrating into existing workflows. In contrast to previous state-of-the-art approaches that repair related commit histories, Aide-mémoire is designed for continuous, real-time, and long-term use, employing Mondrian forest to adapt over a project’s lifetime and continuously improve traceability. Aide-mémoire is tailored for two specific instances of the general traceability problem—namely, commit to issue and pull request to issue links, with a focus on the latter—and exploits data inherent to these two problems to outperform tools for general purpose link recovery. Our approach is online, language-agnostic, and scalable. We evaluate over a corpus of 213 projects and six programming languages, achieving a mean average precision of 0.95. Adopting Aide-mémoire is both efficient and effective: A programmer need only evaluate a single suggested link 94% of the time, and 16% of all discovered links were originally missed by developers.
Updating the Content of Performance Analysis Textbooks
Authors: Serazzi Giuseppe
Published: June 2022

Fifty years have passed since Performance Evaluation (PE) was recognized as a discipline in its own right even if closely linked to computer science. In this period, computer systems, networks, applications and services have changed dramatically. Modern systems are very complex, current workloads consist of hundreds of thousands requests, and user expectations for performance become even more stringent. The computer engineering curricula for undergrad/graduate students and the courses taught in universities are very different from those of a few years ago. With such a completely new scenario, the time has come to analyze the situation in order to identify the teaching techniques of performance analysis in university courses that are best suited to today's world.
Special issue on the Workshop on TOols for Stochastic Modeling and Evaluation (TOSME 2021)
Authors: Donatelli Susanna , Franceschinis Giuliana
Published: June 2022

This special issue collects the contributions of the Workshop on TOols for Stochastic Modeling and Evaluation, held virtually on November 12, 2021, in conjunction with the 30th IFIP WG 7.3 Performance conference, Performance 2021.
TAPAS
Authors: Masetti Giulio , Robol Leonardo , Chiaradonna Silvano , Di Giandomenico Felicita
Published: June 2022

TAPAS is a new tool for efficient evaluation of dependability and performability attributes of systems composed of many interconnected components. The tool solves homogeneous continuous time Markov chains described by stochastic automata network models structured in submodels with absorbing states. The measures of interest are defined by a reward structure based on submodels composed through transition-based synchronization. The tool has been conceived in a modular and flexible fashion, to easily accommodate new features. Currently, it implements an array of state-based solvers that addresses the state explosion problem through powerful mathematical techniques, including Kronecker algebra, Tensor Trains and Exponential Sums. A simple, yet representative, case study is adopted, to present the tool and to show the feasibility of the supported methods, in particular frommemory consumption point of view.
FIG
Authors: Budde Carlos E.
Published: June 2022

This work presents version 1.3 of the Finite Improbability Generator (FIG): a statistical model checker to estimate transient and steady-state reachability properties in stochastic automata. Specialised in rare event simulation via importance splitting, FIG implements RESTART and Fixed Effort algorithms. Its distinctive feature is push-button automation: users need not define an importance function, because FIG can derive it from the property query and model specifications. The input models are Input/Output Stochastic Automata with Urgency, written either in the native IOSA syntax or in the JANI exchange format. The theory backing FIG has demonstrated good efficiency, comparable to optimal importance splitting implemented ad hoc for specific systems. Written in C++, FIG is FOSS released under the GPLv3 in https://git.cs.famaf.unc.edu.ar/dsg/fig.
Improving accuracy and adaptability of SSD failure prediction in hyper-scale data centers
Authors: Hao Wenwen , Niu Ben , Luo Yin , Liu Kangkang , Liu Na
Published: June 2022

The rapid expansion of flash-based solid state drives (SSDs) makes SSD failure an important factor impacting the reliability of storage systems in data centers.
Understanding mobility in networks
Authors: Barros Matheus F. C. , Ferreira Carlos H. G. , Junior Lourenco A. P. , Mellia Marco , Almeida Jussara M. , dos Santos Bruno Pereira
Published: June 2022

Motivated by the growing number of mobile devices capable of connecting and exchanging messages, we propose a methodology aiming to model and analyze node mobility in networks. We note that many existing solutions in the literature rely on topological measurements calculated directly on the graph of node contacts, aiming to capture the notion of the node's importance in terms of connectivity and mobility patterns beneficial for prototyping, design, and deployment of mobile networks. However, each measure has its specificity and fails to generalize the node importance notions that ultimately change over time. Unlike previous approaches, our methodology is based on a node embedding method that models and unveils the nodes' importance in mobility and connectivity patterns while preserving their spatial and temporal characteristics. We focus on a case study based on a trace of group meetings. The results show that our methodology provides a rich representation for extracting different mobility and connectivity patterns, which can be helpful for various applications and services in mobile networks.
Explanations for the Vanishing Trial in the United States
Authors: Staszak Sarah
Published: June 2022

The phenomenon Marc Galanter famously termed the vanishing trial has been widely explored by scholars of law and politics, particularly as the continued decrease of trials in court raises concerns about access to justice and legal recourse in the United States. But a lingering question remains: Where have trials gone? This article argues that we need to diversify the potential range of explanations for the vanishing trial by taking an interbranch perspective that brings to bear the ongoing tension between legal and other forms of dispute resolution and governance. Given that courts are but one venue in which disputes are resolved, this approach expands upon the thesis that disputes have not disappeared but rather have been diverted elsewhere. I argue that reframing the conversation in this way stands to generate a revised set of explanations for this trend that are worthy of future research.
Source/Drain Activation for Flexible Poly-Si Nanoscale pFETs with a Laser-Buffer Layer by CO2 laser Annealing
Authors: Hou Po-Cheng , Huang Wen-Hsien , Kao Ming-Hsuan , Wang Hsing-Hsiang , Shieh Jia-Min , Shen Chang-Hong , Pan Fu-Ming , Chang Li
Published: June 2022

A laser-buffer layer of SiO2/W/SiO2 with a high reflectivity at 10.6 μm enables CO2 laser treatment for the source/drain dopant activation of poly-Si nanoscale field-effect transistor (nano-FET) (Wch/Lg = 70/70 nm) on the flexible polyimide substrate. The laser-buffer layer thermally modified by CO2 laser reduces the sheet resistance of the source/drain to 1.4 kΩ/sq. at low laser energy of 15 W and low substrate temperature of 125 °C. The flexible nano-FET (nano-fFET) exhibits a subthreshold swing (S.S) of 84 mV/dec. and a low drain-induced barrier lowering of 202 mV/V at a bending radius of 10 mm. Low degradation rate of S.S and threshold voltage (Vth) for single- and multi-channel nano-fFETs arises from oxide-trap predomination after long time hot-carrier stress as demonstrated by a ΔVth power-factor of ∼0.2.
Characterization of Nanomechanical Properties and Scratch Hardness of (111) Nanotwinned Copper Thin Film in Ambient and Slurry Conditions
Authors: Sharma Mohit , Chen Chao-Chang A. , Chen Chih , He Pin-Syuan
Published: June 2022

Nanotwinned copper possesses a distinctive structure with higher mechanical strength and stability without compromising on resistivity. This paper aims to characterize the nanomechanical properties along with the scratch hardness of the (111) nanotwinned copper thin film wafer in ambient and slurry conditions by triboindenter. Experiments are performed on Hysitron TI 980 Triboindenter using Berkovich and conical indenter for nanoindentation and nano scratch respectively. This paper studies the impact of nanotwinned structures on quasistatic and scratch hardness of copper thin film wafers given the potential applicability of nanotwinned copper thin films as interconnects. CMP is extensively applied to obtain the nanoscale surface finish required in the semiconductor micro-nano fabrication industry. The nanomechanical properties of (111) nanotwinned copper thin film wafer with passivation in polishing slurry conditions are imperative parameters to study the polishing behavior of material. Hardness, Young’s modulus, and scratch hardness of the nanotwinned copper thin film specimens are evaluated by nanoindenter in ambient and slurry conditions. Results of this study with characteristic parameters of (111) nanotwinned copper thin film wafer can be further used to estimate the material removal of chemical mechanical polishing for high volume production of IC devices in future work.
Luminescence Characteristics of Dy3+/Eu3+ Doped CaBi2Ta2O9 Phosphors
Authors: Yang Yu-Guo , Luo Qing-Li , Wei Lei , Yu Hua-Jian , Qiu Cheng-Cheng , Li Qing-Gang , Wang Xu-Ping , Liu Bing , Wang Ji-Yang , Li Jing-Feng
Published: June 2022

The Dy3+/Eu3+ doped CaBi2Ta2O9 phosphors had been obtained via the sintering processes at 1200 °C for 3 h. The phase and luminescence performance of the prepared phosphors had been researched. The X-ray diffraction results indicate the pure orthorhombic phase of the prepared phosphors. When the phosphors are excited at 355 nm, the Dy3+/Eu3+ single doped CaBi2Ta2O9 phosphors exhibit the characteristic emission bands corresponding to Dy3+ and Eu3+, and the Dy3+/Eu3+ codoped CaBi2Ta2O9 phosphors exhibit tunable luminescence on account of the Dy3+ → Eu3+ energy transfers. In this process, the dipole-dipole interaction is dominated.
Characteristics Extraction of Fully Symmetric GAA and Top-Gate CNTFETs with 6 nm Channel Length
Authors: Shiri Nabiollah , Rafiee Mahmood , Sadeghi Ayoub , Ghayour Rahim
Published: June 2022

High-compatible applications for top-gate and gate-all-around (GAA) carbon nanotube field-effect transistors (CNTFETs) are presented. The geometrical specifications of these CNTFETs are evaluated and their effects on the characteristics are highlighted. The channel length is considered 6 nm, while the drain, source, and spacer are symmetric with channel length. The evaluations are performed by the COMSOL Multiphysics, and the Shockley-Read-Hall (SRH) recombination model is used to analyze doping, electron, and hole distributions. The drain and source wells are considered with donor doping of ND0 = 1 × 1021 cm−3 and acceptor doping of NA = 1 × 1019 cm−3, then, the current-voltage (I–V) characteristics are extracted. Also, the CNTs with 1.12 nm are placed accurately through the channel, and the terminals are constructed with graphene. The I–V curves show that the threshold voltage for the top-gate and GAA are 0.23 V and 0.21 V, respectively. Besides, the short channel effect (SCE) is reduced which is confirmed by a subthreshold swing (SS) of 62 mV/dec for the top-gate and 58 mV/dec for the GAA. Moreover, drain-induced barrier lowering (DIBL) and ION/IOFF ratio parameters are studied to investigate scaled-down devices. The discussed structures are compared by the figure of merit (FoM) of ΔVDIBLSS/(ION/IOFF), which shows more desirable and better channel control. The temperature variations show that there is no dramatic increase in the leakage current, which proves that symmetric structure is reliable in short-channel devices.
Oral Health Knowledge and Experience of Pediatricians and Pediatric Residents in Kuwait: A Nationwide Cross-Sectional Survey Study
Authors: Alanzi Abrar , Hajiah Saleh , Faridoun Anfal , Alterkait Aisha
Published: June 2022

Objective. To evaluate the knowledge level and practice of pediatricians and pediatric residents regarding children’s oral health in Kuwait. Subjects and Methods. A nationwide cross-sectional survey was distributed to pediatricians and pediatric residents practicing in Kuwait. Data concerning demographic variables, knowledge on dental caries preventive measures, current anticipatory guidance, and experience with dental problems and oral care were collected using online and paper-based surveys. Results. A total of 230 completed the survey with a response rate of 50.1%. Most respondents (81%) had noticed dental caries in children more frequently. Two-thirds of respondents felt confident in detecting dental caries. However, more than two-thirds were unfamiliar with preventive dental practices and the management of dental trauma. Only 16.5% of the respondents got satisfactory knowledge score on the preventive measures questions, and nearly 51% got satisfactory knowledge on the recent anticipatory guidance questions. No significant correlations were found between gender or years of practice and knowledge scores. Respondents’ confidence in detecting caries was significantly associated with the knowledge score of the anticipatory guidance (

p
=
0.003

). Conclusion. Dental caries is an oral problem commonly encountered by many pediatricians and pediatric residents in Kuwait. The majority has adequate knowledge of the current anticipatory guidance of oral health issues, but they have insufficient knowledge levels on oral preventative measures. Adequate education and training in oral health are highly recommended.
Digital Evaluation of Nitrite-Reduced “Kulen” Fermented Sausage Quality
Authors: Simunovic Stefan , Đorđević Vesna Ž. , Lakićević Brankica , Djekic Ilija , Lorenzo Jose M. , Barba Francisco J. , Tomasevic Igor
Published: June 2022

This study aimed to evaluate nitrite reduction impact on geometry, colour, chemical, microbiological, and sensory traits of dry sausage (kulen) traditionally prepared with red hot paprika powder. Three batches of kulen with different nitrite levels were produced and assessed: N110 (control with 110 mg/kg of sodium nitrite), N55 (55 mg/kg of sodium nitrite), and NF (without sodium nitrite). Samples for the analyses were taken on production day, after 8, 16, 24, 32, and 40 days of ripening and after 50 and 100 days of storage. Four novel digital methods for quality assessment were deployed such as computer vision system (CVS), three-dimensional (3D) laser imaging, oral processing, and temporal dominance of sensations (TDS). Reduction and removal of nitrites from the formulation of kulen did not result in significant (

P
<
0.01

) differences in lightness (

L

∗

), redness (

a

∗

), and yellowness (

b

∗

) of the sausage surface, meat, and fat parts that were measured independently by means CVS. Sausages produced by 50% nitrite reduction (N55) showed no significant (

P
<
0.01

) differences in terms of geometrical, chemical, colour, microbiological, and oral processing parameters compared with the control (N110) batch. On the other hand, the complete removal of nitrites from kulen formulation negatively affected biogenic amine levels and oral processing properties of the product. Nitrite reduction showed no significant effect on TDS curves among the batches. The results of this study indicate that nitrite content in traditional kulen can be reduced by 50% (55 mg/kg of sodium nitrite) without adversely affecting the various quality properties of the product.
SHC1 Promotes Lung Cancer Metastasis by Interacting with EGFR
Authors: Yang Pan , Li Wei , Li Xiaoping
Published: June 2022

The study aims to explore the biological function of SHC1 in the development and progression of lung cancer. Meanwhile, the effect of SHC1 and EGFR on lung cancer was analyzed. The expression of SHC1 in lung cancer and adjacent tissues was analyzed by bioinformatics and immunohistochemistry. Meanwhile, the relationship between SHC1 expression and prognosis was analyzed. SHC1 overexpression and knockdown cell lines were constructed by overexpression plasmid and knockdown plasmid. Cell proliferation was detected by CCK-8. Cell invasion was detected by transwell. Apoptosis was detected by TUNEL. Interaction between SHC1 and EGFR was detected. The expression of SHC1 in lung adenocarcinoma tissues was significantly higher than that in paracancer tissues. Lung cancer patients with high SHC1 expression have a poor prognosis. The proliferation and invasion of SHC1 decreased with SHC1 knockout but increased after overexpression. EGFR may be a key interaction protein of SHC1. Overexpression of EGFR increases the oncogenic effect of SHC1. In conclusion, SHC1 plays a carcinogenic role in lung cancer. EGFR expression was significantly correlated with SHC1 and maybe a key interaction protein of SHC1. SHC1 interacts with EGFR to form a protein complex, which may be a new target for lung cancer metastasis.
Analytical, Dynamic, and Interactive Platform for Generation and Managing Predictive Models Focused on Energy Sector
Authors: Romero Inés , Ochoa-Zezzati Alberto
Published: June 2022

Ensuring the supply of electricity in a reliable and safe way is not an easy task, especially when considering renewable and clean energy generated with wind turbines given the intermittency or variability of the wind; also considering different time horizons increases complexity. Mexico has great potential for wind energy in the Eastern region and, to meet this challenge, a platform capable of generating forecast models automatically through mathematical techniques and artificial intelligence and managing them is proposed aimed at providing support based on knowledge and presenting the information graphically through a flexible dashboard, which is customizable and accessible when and where required. In this investigation, components related to the generation of electrical energy in this area are identified and a centralized system is proposed, with information segmentation, management of 3 user profiles, 6 KPIs, 5 configurable parameters, 7 different forecast models using statistical techniques, support vector machines, and automatic and deep learning, with 2 ways of visualization, to carry out analyses at 3 different time horizons. It is built in a modular way with free and open-source software. The results in the energy sector show that it allows focusing on priority activities avoiding rework, ensures reliability and completeness, is scalable, avoids duplication, allows resources to be shared, responds quickly to hypotheses, and has a global and summarized view of relevant data according to the interested party for different periods of time in an agile way, reducing times and offering support to the decision maker.
On Solutions to a Class of Functional Differential Equations with Time-Dependent Coefficients
Authors: Mohsin Muhammad , Shah Syed Touqeer H. , Zaidi Ali A.
Published: June 2022

In this paper, we study initial boundary value problems that involve functional (nonlocal) partial differential equations with variable coefficients. These problems arise in cell growth models with symmetric and asymmetric modes of division. We determine the general solution to the symmetric cell division problem for a certain class of coefficients and establish the convergence of solutions to a large time asymptotic solution. The existence of a steady size distribution (SSD) solution for an asymmetric cell division problem is established and is shown to be the large time-attracting solution for a certain class of coefficients. The rate of convergence of solutions towards the SSD solution is affected by the choice of coefficients and remains unaffected by the asymmetry in cell division. The uniqueness of solutions to the initial boundary value problem is also established.
Boundary Determination of Lake-Type Wetland Park Based on GIS Multifactor Analysis
Authors: Chen Guodong , Tang Peng , Wang Hao
Published: June 2022

One key carrier for wetland resource protection is wetland park, the main form of which includes lake-type wetland park. To determine the management and control boundary of lake-type wetland parks scientifically and reasonably is of great significance to the sustainable protection and utilization of wetland resources. From the perspective of landscape architecture, and landscape ecology, this paper studies the boundary determination of Changdang Lake National Wetland Park (the Park) based on satellite remote sensing information technology and GIS technology and in virtue of Analytic Hierarchy Process (AHP). In this study, 12 subindicators were selected from three levels including visual control, human geography, and ecological control. The weight of each indicator was determined by AHP, and then the influencing factors were transformed into graphic data by using GIS technology. Finally, the Park’s boundary was determined by factor superposition analysis based on the weight. The research shows that the newly defined management and control boundary are about 340 sq.km, which effectively integrates the human and natural ecological resources around the lake area, makes the development of the surrounding areas harmonious, ensures the integrity of the lake area ecosystem, and facilitates the sustainable development of wetland resources.