bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimising Access Surgery in Senior Haemodialysis Patients (OASIS): study protocol for a multicentre randomised controlled trial
Authors: Heggen Boudewijn DC , Ramspek Chava L , van der Bogt Koen E A , de Haan Michiel W , Hemmelder Marc H , Hiligsmann Mickaël J C , van Loon Magda M , Rotmans Joris I , Tordoir Jan H M , Dekker Friedo W , Schurink Geert Willem H , Snoeijs Maarten G J
Published: February 2022

Introduction

Current evidence on vascular access strategies for haemodialysis patients is based on observational studies that are at high risk of selection bias. For elderly patients, autologous arteriovenous fistulas that are typically created in usual care may not be the best option because a significant proportion of fistulas either fail to mature or remain unused. In addition, long-term complications associated with arteriovenous grafts and central venous catheters may be less relevant when considering the limited life expectancy of these patients. Therefore, we designed the Optimising Access Surgery in Senior Haemodialysis Patients (OASIS) trial to determine the best strategy for vascular access creation in elderly haemodialysis patients.

Methods and analysis

OASIS is a multicentre randomised controlled trial with an equal participant allocation in three treatment arms. Patients aged 70 years or older who are expected to initiate haemodialysis treatment in the next 6 months or who have started haemodialysis urgently with a catheter will be enrolled. To detect and exclude patients with an unusually long life expectancy, we will use a previously published mortality prediction model after external validation. Participants allocated to the usual care arm will be treated according to current guidelines on vascular access creation and will undergo fistula creation. Participants allocated to one of the two intervention arms will undergo graft placement or catheter insertion. The primary outcome is the number of access-related interventions required for each patient-year of haemodialysis treatment. We will enrol 195 patients to have sufficient statistical power to detect an absolute decrease of 0.80 interventions per year.

Ethics and dissemination

Because of clinical equipoise, we believe it is justified to randomly allocate elderly patients to the different vascular access strategies. The study was approved by an accredited medical ethics review committee. The results will be disseminated through peer-reviewed publications and will be implemented in clinical practice guidelines.

Trial registration number

NL7933.

Protocol version and date

V.5, 25 February 2021.
BOND study: a randomised double-blind, placebo-controlled trial over 12 months to assess the effects of benfotiamine on morphometric, neurophysiological and clinical measures in patients with type 2 diabetes with symptomatic polyneuropathy
Authors: Bönhof Gidon J , Sipola Gundega , Strom Alexander , Herder Christian , Strassburger Klaus , Knebel Birgit , Reule Claudia , Wollmann Jan-Christoph , Icks Andrea , Al-Hasani Hadi , Roden Michael , Kuss Oliver , Ziegler Dan
Published: February 2022

Introduction

Diabetic sensorimotor polyneuropathy (DSPN) affects approximately 30% of people with diabetes, while around half of cases are symptomatic. Currently, there are only few pathogenetically oriented pharmacotherapies for DSPN, one of which is benfotiamine, a prodrug of thiamine with a high bioavailability and favourable safety profile. While benfotiamine has shown positive effects in preclinical and short-term clinical studies, no long-term clinical trials are available to demonstrate disease-modifying effects on DSPN using a comprehensive set of disease-related endpoints.

Methods and analysis

The benfotiamine on morphometric, neurophysiological and clinical measures in patients with type 2 diabetes trial is a randomised double-blind, placebo-controlled parallel group monocentric phase II clinical trial to assess the effects of treatment with benfotiamine compared with placebo in participants with type 2 diabetes and mild to moderate symptomatic DSPN. Sixty participants will be 1:1 randomised to treatment with benfotiamine 300 mg or placebo two times a day over 12 months. The primary endpoint will be the change in corneal nerve fibre length assessed by corneal confocal microscopy (CCM) after 12 months of benfotiamine treatment compared with placebo. Secondary endpoints will include other CCM measures, skin biopsy and function indices, variables from somatic and autonomic nerve function tests, clinical examination and questionnaires, general health, health-related quality of life, cost, safety and blood tests.

Ethics and dissemination

The trial was approved by the competent authority and the local independent ethics committee. Trial results will be published in peer-reviewed journals, conference abstracts, and via online and print media.

Trial registration number

DRKS00014832.
Omega-3 polyunsaturated fatty acids: moving towards precision use for prevention and treatment of colorectal cancer
Authors: Aldoori Joanna , Cockbain Andrew J , Toogood Giles J , Hull Mark A
Published: February 2022

Data from experimental studies have demonstrated that marine omega-3 polyunsaturated fatty acids (O3FAs) have anti-inflammatory and anticancer properties. In the last decade, large-scale randomised controlled trials of pharmacological delivery of O3FAs and prospective cohort studies of dietary O3FA intake have continued to investigate the relationship between O3FA intake and colorectal cancer (CRC) risk and mortality. Clinical data suggest that O3FAs have differential anti-CRC activity depending on several host factors (including pretreatment blood O3FA level, ethnicity and systemic inflammatory response) and tumour characteristics (including location in the colorectum, histological phenotype (eg, conventional adenoma or serrated polyp) and molecular features (eg, microsatellite instability, cyclooxygenase expression)). Recent data also highlight the need for further investigation of the effect of O3FAs on the gut microbiota as a possible anti-CRC mechanism, when used either alone or in combination with other anti-CRC therapies. Overall, these data point towards a precision approach to using O3FAs for optimal prevention and treatment of CRC based on mechanistic understanding of host, tumour and gut microbiota factors that predict anticancer activity of O3FAs.
Computational image features of immune architecture is associated with clinical benefit and survival in gynecological cancers across treatment modalities
Authors: Azarianpour Sepideh , Corredor Germán , Bera Kaustav , Leo Patrick , Fu Pingfu , Toro Paula , Joehlin-Price Amy , Mokhtari Mojgan , Mahdi Haider , Madabhushi Anant
Published: February 2022

Background

We present a computational approach (ArcTIL) for quantitative characterization of the architecture of tumor-infiltrating lymphocytes (TILs) and their interplay with cancer cells from digitized H&E-stained histology whole slide images and evaluate its prognostic role in three different gynecological cancer (GC) types and across three different treatment types (platinum, radiation and immunotherapy).

Methods

In this retrospective study, we included 926 patients with GC diagnosed with ovarian cancer (OC), cervical cancer, and endometrial cancer with available digitized diagnostic histology slides and survival outcome information. ArcTIL features quantifying architecture and spatial interplay between immune cells and the rest of nucleated cells (mostly comprised cancer cells) were extracted from the cell cluster graphs of nuclei within the tumor epithelial nests, surrounding stroma and invasive tumor front compartments on H&E-stained slides. A Cox proportional hazards model, incorporating ArcTIL features was fit on the OC training cohort (N=51), yielding an ArcTIL signature. A unique threshold learned from the training set stratified the patients into a low and high-risk group.

Results

The seven feature ArcTIL classifier was found to significantly correlate with overall survival in chemotherapy and radiotherapy-treated validation cohorts and progression-free survival in an immunotherapy-treated validation cohort. ArcTIL features relating to increased density of TILs in the epithelium and invasive tumor front were found to be associated with better survival outcomes when compared with those patients with an increased TIL density in the stroma. A statistically significant association was found between the ArcTIL signature and signaling pathways for blood vessel morphogenesis, vasculature development, regulation of cell differentiation, cell-substrate adhesion, biological adhesion, regulation of vasculature development, and angiogenesis.

Conclusions

This study reveals that computationally-derived features from the spatial architecture of TILs and tumor cells are prognostic in GCs treated with chemotherapy, radiotherapy, and checkpoint blockade and are closely associated with central biological processes that impact tumor progression. These findings could aid in identifying therapy-refractory patients and further enable personalized treatment decision-making.
Controls on carbon dioxide and methane fluxes from a low-center polygonal peatland in the Mackenzie River Delta, Northwest Territories
Authors: Skeeter June , Christen Andreas , Henry Greg H.R.
Published: February 2022

Growing season surface–atmosphere exchange of carbon dioxide and methane were quantified at Fish Island, a wetland site in the lower northeast Mackenzie River Delta, Northwest Territories, Canada. The terrain consists of low-center polygonal tundra and is subject to infrequent flooding in high water years. Carbon dioxide and methane fluxes were continuously measured using eddy covariance and the relevance of different environmental controls were identified using neural networks. Net daily carbon dioxide uptake peaked in mid-July before gradually decreasing and transitioning to net daily emissions by September. Variations in light level and temperature were the main controls over diurnal net carbon dioxide uptake, whereas thaw depth and phenology were the main seasonal controls. Methane emissions measured at Fish Island were higher than comparable studies on river delta sites in the Arctic and were influenced by the interaction of a large number of factors including thaw and water table depth, soil temperatures, and net radiation. Spikes in methane emissions were associated with strong winds and turbulence. The Fish Island tundra was a net sink for carbon during the growing season and methane emissions only slightly reduced the overall sink strength.
Peccei–Quinn symmetry breaking via asymptotically safe dynamical scalegenesis: a walking axicolor and axion
Authors: Ishida Hiroyuki , Matsuzaki Shinya , Peng Xiao-Chang
Published: February 2022

Breaking the Pecci–Quinn (PQ) symmetry by the perturbative dynamics would suffer from a hierarchy problem, just like the electroweak symmetry breaking in the standard model. The dynamics of the axion, associated with the PQ symmetry breaking, would also involve a triviality problem. We provide a paradigm to resolve those two problems potentially existing in the PQ symmetry breaking scenario, with keeping the successful axion relaxation for the QCD strong CP phase. The proposed theory includes an axicolor dynamics with the axicolored fermions partially gauged by the QCD color, and is shown to be governed by an asymptotically safe (AS) fixed point: quantum scale invariance is built. The AS axicolor is actually a “walking” dynamics, which dynamically breaks a PQ symmetry, a part of the chiral symmetry carried by the axicolored fermions. The PQ scale generation is then triggered by the nonperturbative dimensional transmutation in the “walking” dynamics. A composite axion emerges as the associated Nambu-Goldstone boson. That is, no hierarchy or triviality problem is present there. The composite axion can potentially be light due to the characteristic feature of the AS axicolor (“walking” axicolor), becomes the QCD axion in the anti-Veneziano limit, and gets heavier by the subleading correction. The composite axion relaxes the QCD theta parameter, involving heavier relaxation partners such as axicolored pseudoscalar mesons, and the ultraviolet correction to the relaxation mechanism is protected by the established (near) scale invariance during the “walking” regime.
Efficient Cryptographic Hardware for Safety Message Verification in Internet of Connected Vehicles
Authors: Mehrabi Mohamad Ali , Jolfaei Alireza
Published: February 2022

An important security requirement in automotive networks is to authenticate, sign, and verify thousands of short messages per second by each vehicle. This requirement mandates the use of a high speed Elliptic Curve Cryptography (ECC) hardware. The Residue Number Systems (RNS) provide a natural parallelism and carry-free operations that could speed-up long integer arithmetics of cryptographic algorithms. In this article, we propose a high-speed RNS Montgomery modular reduction units with parallel computing to reduce the latency of the field modular operations. We propose a fully RNS-based ECC scalar multiplication co-processor for NIST-P256r1 and Brainpool256r1 standard curves and improved the scalar multiplication speed using NAF and DBC numbering systems. Compared to the literature, our scheme provides faster computation without compromising the security level. The performance of our fully RNS-ECC point multiplication meets the requirements of the automotive industry.
Acoustic Analysis of Vowels in Konkani
Authors: Fadte Swapnil , Fernandes Edna Vaz , Karmali Ramdas , Pawar Jyoti D.
Published: February 2022

Konkani is an under-resourced language mainly spoken on the west coast of India. Although linguistic analyses of vowel sounds in various dialects of Konkani have been done in the past, more accurate analysis of Konkani vowels, especially an acoustic-phonetic analysis, was never carried out. In this article, we present a detailed analysis of nine Konkani vowels, namely
/i/, /e/, /ε/, /u/, /o/, /ɔ/, /a/, /ə/, and /ɨ̞/
. The dataset used for the analysis was created from audio recordings of 28 native speakers of Goan Konkani. Based on the experimental results, we propose a vowel chart for Konkani. We also observed a partial loss of Konkani vowel /
ɨ̞
/ in the regular speech of native speakers. This change is also evident in the substitution analysis of vowel phonemes that was carried out by us as a part of this study.
Albanian Fake News Detection
Authors: Canhasi Ercan , Shijaku Rexhep , Berisha Erblin
Published: February 2022

Recent years have witnessed the vast increase of the phenomenon known as the fake news. Among the main reasons for this increase are the continuous growth of internet and social media usage and the real-time information dissemination opportunity offered by them. Deceiving, misleading content, such as the fake news, especially the type made by and for social media users, is becoming eminently hazardous. Hence, the fake news detection problem has become an important research topic. Despite the recent advances in fake news detection, the lack of fake news corpora for the under-resourced languages is compromising the development and the evaluation of existing approaches in these languages. To fill this huge gap, in this article, we investigate the issue of fake news detection for the Albanian language. In it, we present a new public dataset of labeled true and fake news in Albanian and perform an extensive analysis of machine learning methods for fake news detection. We performed a comprehensive feature engineering and feature selection experiments. In doing so, we explored the Albanian language-related feature categories such as the lexical, syntactic, lying-detection, and psycho-linguistic features. Each article was also modeled in four different ways: with the traditional bag-of-words (BoW) and with three distributed text representations using the state-of-the-art Word2Vec, FastText, and BERT methods. Additionally, we investigated the best combination of features and various types of classification methods. The conducted experiments and obtained results from evaluations are finally used to draw some conclusions. They shed light on the potentiality of the methods and the challenges that the Albanian fake news detection presents.
A Survey of Machine Learning for Computer Architecture and Systems
Authors: Wu Nan , Xie Yuan
Published: February 2022

It has been a long time that computer architecture and systems are optimized for efficient execution of machine learning (ML) models. Now, it is time to reconsider the relationship between ML and systems and let ML transform the way that computer architecture and systems are designed. This embraces a twofold meaning: improvement of designers’ productivity and completion of the virtuous cycle. In this article, we present a comprehensive review of the work that applies ML for computer architecture and system design. First, we perform a high-level taxonomy by considering the typical role that ML techniques take in architecture/system design, i.e., either for fast predictive modeling or as the design methodology. Then, we summarize the common problems in computer architecture/system design that can be solved by ML techniques and the typical ML techniques employed to resolve each of them. In addition to emphasis on computer architecture in a narrow sense, we adopt the concept that data centers can be recognized as warehouse-scale computers; sketchy discussions are provided in adjacent computer systems, such as code generation and compiler; we also give attention to how ML techniques can aid and transform design automation. We further provide a future vision of opportunities and potential directions and envision that applying ML for computer architecture and systems would thrive in the community.
A Review on Fairness in Machine Learning
Authors: Pessach Dana , Shmueli Erez
Published: February 2022

An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college admissions, recruitment, provision of loans, and many more realms. Since they now touch on many aspects of our lives, it is crucial to develop ML algorithms that are not only accurate but also objective and fair. Recent studies have shown that algorithmic decision making may be inherently prone to unfairness, even when there is no intention for it. This article presents an overview of the main concepts of identifying, measuring, and improving algorithmic fairness when using ML algorithms, focusing primarily on classification tasks. The article begins by discussing the causes of algorithmic bias and unfairness and the common definitions and measures for fairness. Fairness-enhancing mechanisms are then reviewed and divided into pre-process, in-process, and post-process mechanisms. A comprehensive comparison of the mechanisms is then conducted, toward a better understanding of which mechanisms should be used in different scenarios. The article ends by reviewing several emerging research sub-fields of algorithmic fairness, beyond classification.
Anomaly Detection and Failure Root Cause Analysis in (Micro) Service-Based Cloud Applications: A Survey
Authors: Soldani Jacopo , Brogi Antonio
Published: February 2022

The proliferation of services and service interactions within microservices and cloud-native applications, makes it harder to detect failures and to identify their possible root causes, which is, on the other hand crucial to promptly recover and fix applications. Various techniques have been proposed to promptly detect failures based on their symptoms, viz., observing anomalous behaviour in one or more application services, as well as to analyse logs or monitored performance of such services to determine the possible root causes for observed anomalies. The objective of this survey is to provide a structured overview and qualitative analysis of currently available techniques for anomaly detection and root cause analysis in modern multi-service applications. Some open challenges and research directions stemming out from the analysis are also discussed.
Understanding Online Privacy—A Systematic Review of Privacy Visualizations and Privacy by Design Guidelines
Authors: Barth Susanne , Ionita Dan , Hartel Pieter
Published: February 2022

Privacy visualizations help users understand the privacy implications of using an online service. Privacy by Design guidelines provide generally accepted privacy standards for developers of online services. To obtain a comprehensive understanding of online privacy, we review established approaches, distill a unified list of 15 privacy attributes and rank them based on perceived importance by users and privacy experts. We then discuss similarities, explain notable differences, and examine trends in terms of the attributes covered. Finally, we show how our results provide a foundation for user-centric privacy visualizations, inspire best practices for developers, and give structure to privacy policies.
A Reputation-based Framework for Honest Provenance Reporting
Authors: Barakat Lina , Taylor Phillip , Griffiths Nathan , Miles Simon
Published: February 2022

Given the distributed, heterogenous, and dynamic nature of service-based IoT systems, capturing circumstances data underlying service provisions becomes increasingly important for understanding process flow and tracing how outputs came about, thus enabling clients to make more informed decisions regarding future interaction partners. Whilst service providers are the main source of such circumstances data, they may often be reluctant to release it, e.g., due to the cost and effort required, or to protect their interests. In response, this article introduces a reputation-based framework, guided by intelligent software agents, to support the sharing of truthful circumstances information by providers. In this framework,
assessor agents
, acting on behalf of clients, rank and select service providers according to reputation, while
provider agents
, acting on behalf of service providers, learn from the environment and adjust provider’s circumstances provision policies in the direction that increases provider profit with respect to perceived reputation. The novelty of the reputation assessment model adopted by assessor agents lies in affecting provider reputation scores by whether or not they reveal truthful circumstances data underlying their service provisions, in addition to other factors commonly adopted by existing reputation schemes. The effectiveness of the proposed framework is demonstrated through an agent-based simulation including robustness against a number of attacks, with a comparative performance analysis against FIRE as a baseline reputation model.
Reduplication in Assamese: Identification and Modeling
Authors: Pathak Dhrubajyoti , Nandi Sukumar , Sarmah Priyankoo
Published: February 2022

Reduplication is a productive morphological process widely used in a substantial number of languages in the world. Reduplication is a well-studied phenomenon, and several typological works have provided evidence for different types of reduplication in most of the languages around the world. Addressing reduplication plays a vital role in the efficiency of POS tagger, sentiment analysis, as well as other NLP tasks. However, it is an understudied area in computational linguistics, especially in low-resource languages like Assamese. This article first describes different types of reduplication and their shapes that occur in Assamese. Second, an exhaustive set of reduplication formation rules is compiled that is incorporated to build a system to identify reduplication in Assamese text. The results of the experiments performed on three different domain datasets showed that the rule-based system can identify reduplicated expressions with an average precision, recall, and F1 scores of 94.19%, 98.07%, and 96.07%, respectively. Third, it is shown that the Assamese reduplication processes can be captured through a two-way finite-state transducer (2-way FST). Finally, two broad categories of reduplicative processes along with their corresponding 2-way FST model are presented.
Contextual-Aware Information Extractor with Adaptive Objective for Chinese Medical Dialogues
Authors: Hu Gangqiang , Lyu Shengfei , Wu Xingyu , Li Jinlong , Chen Huanhuan
Published: February 2022

Electronic Medical Records
(
EMRs
) are the foundation of modern medical information systems. Despite the benefits of EMRs, the exhausting process of constructing EMRs decreases the efficiency of medical consultation. Therefore, it becomes an emerging research field to automatically extract EMRs from medical dialogues. In Chinese medical dialogues, the phenomena of omission and reference are extremely common, leading to strong contextual relevance among utterances. However, recent studies on converting Chinese medical dialogues to EMRs lack a reliable mechanism to effectively exploit the contextual relevance information among utterances. Moreover, they neglect the frequency imbalance of different items and treat these items indiscriminately, which eventually degrade the overall system performance. In this article, we proposed a
Contextual-Aware Information Extractor
(
CANE
), which employs a local-to-global mechanism over utterances to model the contextual relevance among utterances. Furthermore, an adaptive objective is introduced to alleviate the frequency imbalance of items by dynamically assigning weights to each sample. Experimental results indicate that CANE outperforms previous state-of-the-arts with considerable improvements (+6.11% and +3.39% on F1-score).
Pit Stability Predictions of Additively Manufactured SS316 Surfaces Using Finite Element Analysis
Authors: Marshall Rebecca S. , Katona Ryan M. , Melia Michael A. , Kelly Robert G.
Published: February 2022

Stainless steels are susceptible to localized forms of corrosion attack, such as pitting. The size and lifetime of a nucleated pit can vary, depending on a critical potential or current density criterion, which determines if the pit repassivates or continues growing. This work uses finite element method (FEM) modeling to compare the critical pit radii predicted by thermodynamic and kinetic repassivation criteria. Experimental electrochemical boundary conditions are used to capture the active pit kinetics. Geometric and environmental parameters, such as the pit shape and size (analogous to additively manufactured lack-of-fusion pores), solution concentration, and water layer thickness were considered to assess their impact on the pit repassivation criterion. The critical pit radius (the transition point from stable growth to repassivation) predicted for a hemispherical pit was larger when using the repassivation potential (Erp) criteria, as opposed to the current density criteria (pit stability product). Including both the pit stability product and Erp into its calculations, the analytical maximum pit model predicted a critical radius two times more conservative than the FEA approach, under the conditions studied herein. The complex pits representing lack-of-fusion pores were shown to have minimal impact on the critical radius in atmospheric conditions.
Functionalized Carbon Nanotubes Supported 3D Zinc/Cobalt Oxide as an Efficient Electrocatalyst for Oxygen Evolution Reaction
Authors: Niyitanga Theophile , Kim Haekyoung
Published: February 2022

In this study, we developed 3D zinc oxide (ZnO) and cobalt oxide (Co3O4) supported by functionalized carbon nanotubes (O-CNT) to form a catalyst (ZnO/Co3O4@O-CNT) for oxygen evolution reaction (OER). The catalyst improved catalytic OER performance with the lowest overpotential of 260 mV to reach 10 mA cm−2 and a small Tafel slope of 79 mV dec−1, which is smaller than that of ZnO/Co3O4 and O-CNT. The catalyst exhibited fast electron transfer and high electrical conductivity owing to the O-CNT that acted as a conducting support, and the introduction of ZnO synergistically enhanced the OER activity of the synthesized catalyst. The specific activity and turnover frequency of the ZnO/Co3O4@O-CNT catalyst at an overpotential of 400 mV were 0.130 mA cm−2 and 2.45 s−1, respectively, which are considerably higher than those of pristine ZnO/Co3O4 (0.024 mA cm−2, 0.23 s−1) and O-CNT (0.012 mA cm−2, 0.03 s−1). The high catalytic performance of the catalyst is attributed to the presence of oxygen functional groups, which induced a high electrochemical surface area, additional active site exposure, fast electron transfer, and enhanced dispersion of the catalyst. Thus, the synthesized ZnO/Co3O4@O-CNT catalyst can be a good candidate as an alternative to high-cost noble metals for OER performance.
Parasternal intercostal function during sustained hypoxia
Authors: Ji Michael , Ikegami Tetsunori , Debru Estifanos , Easton Paul A.
Published: February 2022

With the potential to act as a surrogate for the generally inaccessible costal diaphragm, parasternal intercostal has gained great interest clinically as a muscle to monitor neural drive and function in respiratory disease. This study demonstrates for the first time the impact of sustained hypoxia on neural activation and mechanical contraction of the parasternal intercostals. Parasternal intercostals reveal a biphasic action during the time-dependent hypoxic response, with a transient increase in shortening and EMG activity with acute hypoxia followed by a progressive decline when hypoxia is sustained.
Traditional and Phytochemical Bases of Herbs, Shrubs, Climbers, and Trees from Ethiopia for Their Anticancer Response
Authors: Abate Limenew , Tadesse Mesfin Getachew , Bachheti Archana , Bachheti Rakesh Kumar
Published: February 2022

Ethiopia is one of Africa’s six plant‐rich countries, with around 60% of the plants being indigenous and most of them having medicinal properties. 80% of people in the country use these plants as a primary health care system to tackle different diseases, including cancer. This review is aimed at summarizing the evidence gained from diverse MPs in Ethiopia that have been used ethnobotanically and ethnopharmacologically for treatment of cancer. The primary data sources were Google Scholar, Web of Science, Science Direct, Scopus, PubMed, and other electronic scientific databases. This literature review showed that there are around 200 MPs used as anticancer. Seventy‐four herbs, 39 trees, 77 shrubs, and 17 weed/climbers belonging to 56 families have been identified for their ethnobotanical anticancer potential, and 31 species were recognized for their pharmaceutically anticancer activities. The reviewed data also indicated that many Ethiopian MPs had been used to treat breast, lung, blood, and skin cancers and other tumors. Besides, the collected data showed that the leaves (36.76%), roots (27.2%), bark (12.5%), stem (5.1%), and fruit (7.35%) of plants are commonly used for the preparation of anticancer remedies. Among the reported plant species, Euphorbiaceae (10.71%), Acanthaceae (7.14%), and Asteraceae (7.1%) are the most prominent plant families being used to treat cancer ethnobotanically. Phytochemicals such as flavonoids (like xanthone, indirubin, flavopiridol, and silybin), alkaloids (like taxol, vincristine, evodiamine, and berberine), and physalin B, D, and F steroids exhibited anticancer activity on various cancer cell lines. The crude extracts of Aerva javanica, Vernonia leopoldi, Withania somnifera, Kniphofia foliosa, and Catharanthus roseus were powerful anticancer agents with an IC50 value below 10 μg/mL. Although several Ethiopian plants possess anticancer potential, only a limited number of plants are scientifically studied. Therefore, more scientific studies on anticancer MPs should be carried out; it may lead to discovering and isolating cost‐effective and safe anticancer drugs.
Long Short-Term Memory-Based Model Predictive Control for Virtual Coupling in Railways
Authors: Chai Ming , Su Haoxiang , Liu Hongjie
Published: February 2022

The increasing need for capacity has led the railway industry to explore new train control systems based on a concept called virtual coupling. Inspired by the platooning of autonomous vehicles, the safe operation of virtual coupling is guaranteed by a relative brake distance-based train separation method. This paper proposes a novel long short-term memory (LSTM)-based model predictive control (MPC) method for train operations. An MPC-based control design for virtual coupled train operations is presented. The LSTM is introduced to model the dynamics of the preceding train to approximate the actual train operations. With the train dynamics models, the operation trajectories of the preceding train are predicted based on planned control inputs. A study of a metro line in Chengdu was chosen to analyze the proposed control approach. The simulation results of different scenarios show that compared with the conventional MPC methods, the proposed LSTM-based MPC can reduce the speed differences and position differences of tracking trains by up to 35

%

and 25

%

, respectively.
Machine Learning Techniques for Spam Detection in Email and IoT Platforms: Analysis and Research Challenges
Authors: Ahmed Naeem , Amin Rashid , Aldabbas Hamza , Koundal Deepika , Alouffi Bader , Shah Tariq
Published: February 2022

Nowaday, emails are used in almost every field, from business to education. Emails have two subcategories, i.e., ham and spam. Email spam, also called junk emails or unwanted emails, is a type of email that can be used to harm any user by wasting his/her time, computing resources, and stealing valuable information. The ratio of spam emails is increasing rapidly day by day. Spam detection and filtration are significant and enormous problems for email and IoT service providers nowadays. Among all the techniques developed for detecting and preventing spam, filtering email is one of the most essential and prominent approaches. Several machine learning and deep learning techniques have been used for this purpose, i.e., Naïve Bayes, decision trees, neural networks, and random forest. This paper surveys the machine learning techniques used for spam filtering techniques used in email and IoT platforms by classifying them into suitable categories. A comprehensive comparison of these techniques is also made based on accuracy, precision, recall, etc. In the end, comprehensive insights and future research directions are also discussed.
Numerical Investigation of Fractional‐Order Kawahara and Modified Kawahara Equations by a Semianalytical Method
Authors: Alhejaili Weaam , Alhazmi Sharifah E. , Nawaz Rashid , Ali Aatif , Asamoah Joshua Kiddy Kwasi , Zada Laiq
Published: February 2022

In this work, the optimal homotopy asymptotic method (OHAM) has been used to find approximate solutions to the nonlinear fractional‐order Kawahara and modified Kawahara equations. The method convergence is controlled by a flexible function known as the auxiliary function. The values of the unknown arbitrary constants in the auxiliary function are computed using the Caputo derivative fractional‐order and the well‐known approach of least squares. Fractional‐order derivatives are taken in the Caputo sense with numerical values in the closed interval [0, 1]. The suggested method is directly applied to fractional‐order Kawahara and modified Kawahara equations, with no need for small or large parameter assumptions. The numerical results obtained by the proposed method are compared to the new iterative method (NIM). Results reveal that the proposed method converges faster to the exact solution than other methods in the literature.
Throughput Optimization of Backscatter-Assisted Wireless Relay Networks in Obstacle Environment
Authors: Li Jinfeng , Ni Qinyin , Zhu Xiaorong
Published: February 2022

Internet of Things nodes need new charging methods, and RF energy is not well utilized. Backscatter can harvest RF energy from the environment and use the idle spectrum to realize wireless power supply communication. In this article, each enhanced backscatter device (eBD) can select from a variety of cooperative receivers (CR) to provide different transmission services in three modes: energy harvesting (EH), relay communication (RelayCom), and backscatter communication (BackCom). To analyze the throughput of the secondary network, we model the three working modes, respectively. We describe the problem as the objective function of three variables: the period α of EH when there are no obstacles, period

μ

of RelayCom with obstacles, and period

γ

of BackCom with obstacles. The ideal time allocation strategy is then investigated. Then, we apply the particle swarm optimization algorithm to obtain a solution that maximizes the throughput. The simulation results show that compared to the communication network using backscatter or relay protocol alone, the proposed backscatter-assisted wireless relay communication model can greatly improve the throughput and coverage of the secondary system.
Predictive Role of IL-2R and IL-10 in the Anti-inflammatory Response and Antiplatelet Therapy of Kawasaki Disease: A Retrospective Study
Authors: Zhang Chun , Chen Lun , Chen Sun , Bian Yan , Shen Jia , Zhang Peng , Song JiaNi
Published: February 2022

To date, Kawasaki disease (KD) has only been able to be diagnosed and evaluated using clinical characteristics. Additionally, the therapeutic effect and cardiovascular complications could not be verified until its occurrence. The present retrospective study analyzed the dynamic alterations of inflammatory cytokines, platelet (PLT) count, and subgroups of lymphocytes, such as cluster of differentiation (CD) 8+ T cells and CD19+ B cells, under different conditions in 64 children with KD. The percentage distribution of lymphocyte subgroups and the altered neutrophil lymphocyte ratio demonstrated that the inflammatory response was dominated by the B cell-mediated humoral immune response before intravenous immunoglobulin (IVIG) treatment, but mainly by T cells via cellular cytotoxic effects after IVIG treatment. Among the different types of inflammatory cytokines, the results of the present study revealed that the altered levels of interleukin-2 receptor (IL-2R) and interleukin-10 (IL-10) were closely associated with the percentage of CD8+ T cells and CD19+ B cells. Additionally, the two cytokines exhibited more sensitive fluctuations based on the status of the children with KD in various circumstances compared with other indexes, such as the percentages of CD8+ T cells and CD19+ B cells or the PLT count. These results suggested that children with KD who are ≥4 years old may benefit from IVIG but will not benefit from decreased platelet activation or suffer less cardiovascular complications. Additionally, starting clopidogrel usage earlier as an antiplatelet strategy should be considered based on the observed continuous rise in the PLT count in children with KD receiving IVIG. In conclusion, dynamically monitoring the levels of IL-2R and IL-10 has the potential to provide indications of the intensity and development of the inflammatory response in children with KD and may contribute to the early prediction and adjustment of pathological and pharmacological effects of therapy.
The Influence of Artificial Intelligence Technology on Teaching under the Threshold of “Internet+”: Based on the Application Example of an English Education Platform
Authors: Liu Yang , Ren Lei
Published: February 2022

Today’s era can be treated as the Internet era as the world revolves around the Internet for unlimited access to the resources available in a remote area. The Internet has made a deeper penetration in the education sector; the traditional offline classes are being replaced with online and offline classes to make the quick and effective teaching and learning process. Some researchers are exploring various technologies to incorporate digitization and visualization of courses to improve the independent learning among the students and for effective modeling of course contents. Artificial intelligence, deep learning, machine learning, and edge computing are some technologies implemented to increase the student’s and teachers’ interaction for improved performance of the learning process. A genetic algorithm with artificial intelligence is proposed in this research work to choose teaching and learning management with English courses in colleges and universities. For making analysis, the student performance dataset is taken from the UCI repository. The teaching and learning management of the English course is analyzed along with the student’s behavior towards the online English course. The results show that the student’s response to the classes is increased with the involvement of the artificial intelligence technology with the Internet.
Ribociclib Nanostructured Lipid Carrier Aimed for Breast Cancer: Formulation Optimization, Attenuating In Vitro Specification, and In Vivo Scrutinization
Authors: Sartaj Ali , Annu  , Biswas Largee , Verma Anita Kamra , Sahoo P. K. , Baboota Sanjula , Ali Javed
Published: February 2022

Purpose. The current investigation is on the explicit development and evaluation of nanostructured lipidic carriers (NLCs) through the oral route to overcome the inherent lacuna of chemotherapeutic drug, in which Ribociclib (RBO) was used for breast cancer to diminish the bioavailability issue. Method. The RBO‐NLCs were prepared using the solvent evaporation method and optimized method by the Box–Behnken design (BBD). Various assessment parameters characterized the optimized formulation and their in vivo study. Results. The prepared NLCs exhibited mean particle size of 114.23 ± 2.75 nm, mean polydispersity index of 0.649 ± 0.043, and high entrapment efficiency of 87.7 ± 1.79%. The structural analysis by TEM revealed the spherical size of NLCs and uniform drug distribution. An in vitro drug release study was established through the 0.1 N HCl pH 1.2, acetate buffer pH 4.5, and phosphate buffer pH 6.8 with % cumulative drug release of 86.71 ± 8.14, 85.82 ± 4.58, and 70.98 ± 5.69%, was found respectively, compared with the RBO suspension (RBO‐SUS). In vitro intestinal gut permeation studies unveiled a 1.95‐fold gain in gut permeation by RBO‐NLCs compared with RBO‐SUS. In vitro lipolysis suggests the drug availability at the absorption site. In vitro haemolysis study suggests the compatibility of NLCs to red blood cells compared to the suspension of the pure drug. The confocal study revealed the depth of penetration of the drug into the intestine by RBO‐NLCs which was enhanced compared to RBO‐SUS. A cell line study was done in MCF‐7 and significantly reduced the IC50 value compared to the pure drug. The in vivo parameters suggested the enhanced bioavailability by 3.54 times of RBO‐NLCs as compared to RBO‐SUS. Conclusion. The in vitro, ex vivo, and in vivo results showed a prominent potential for bioavailability enhancement of RBO and effective breast cancer therapy.
Evaluate the Correlation between the TIMI Frame Count, IMR, and CFR in Coronary Microvascular Disease
Authors: Xu Xinye , Zhou Jinbao , Zhang Yongzhen , Li Qian , Guo Lijun , Mao Yanyang , He Liyun
Published: February 2022

Objective. To evaluate the correlation between the TIMI frame count, IMR, and CFR in coronary microvascular disease (slow flow phenomenon). Methods. TFC and IMR were recorded in the nitroglycerin and ATP administration states, and the relationship between TFC, IMR, and CFR in specific states was analyzed. Results. A total of 41 patients with baseline TFC >25 frames on coronary angiography were enrolled, and nitroglycerin reduced TFC by 50% from baseline in 24 (58.54%) patients; 16 of the remaining 17 patients were able to achieve a 50% reduction in TFC by further intracoronary ATP injection. 10 patients were further tested for IMR, and the results showed significant correlations between baseline TFC and IMR (r = 0.775,

P
=
0.008

), TFC and IMR after nitroglycerin (r = 0.875,

P
=
0.001

), and the minimal TFC and IMR that could be obtained with nitroglycerin or ATP administration (r = 0.890,

P
=
0.001

). There was also a significant correlation between the proportional improvement in TFC and CFR before and after nitroglycerin injection (r = 0.685,

P
=
0.029

). In addition, we observed a lower IMR measured after nitroglycerin than after ATP in three patients, suggesting that CMD may be dominated by NO-sensitive vascular such as prearterioles and that an extensive analysis of the target site of CMD may be achieved by stepwise drug administration. Conclusion. Induction of TFC in different states by a stepwise drug approach may serve as a potential primary screening method for coronary microcirculatory dysfunction, thereby reducing the need for further IMR or CFR testing.
Calculation and Analysis of Vibration Stress of Guangxi Nanning Subway during Operation
Authors: Chang Zhenchao , Luo Junhui , Wang Shihai , Huang Haifeng , Mo Peng , Wu Chunwei , Liao Laixing , Chen Yuanpeng , Huang Mian , Wu Yuhang
Published: February 2022

In this study, based on the Mindlin solution in elastic half‐space, the stress calculation formula was determined with consideration of any point in the foundation under the dynamic amplification effect. The train load was simplified as a concentrated force moving in the direction of the train, and the stress of the soil under a single wheel load was analyzed. In the state, σz reached a maximum value of 0.56 kPa when the axle was directly above the soil, and the stress decreased until it approached zero as the distance from the soil unit increased. Then, taking the Nanning Metro Line 1 as an example, the load was regarded as the superposition of several single‐wheel loads, and the law of the soil stress change at a point directly below the moving line of the train load at different axle loads, speeds, and burial depths was studied. From the analysis of the results, it could be seen that the soil stress under different working conditions was always proportional to the train axle load, speed, and burial depths. The peak stress ratio corresponding to the depths of 9 m, 12 m, and 15 m was 1:2:11, indicating that the closer the load to the soil, the more significantly the stress of the soil element increased. Under multiple wheel loads, the soil stress always exhibited continuous cycle characteristics. The cycle period was related to the time it took for the metro to pass through the point in the soil, and the cycle period was the ratio of the distance between each axle and the vehicle speed.