bluuebunny/crossref_metadata_2025 huggingface dataset:
A Context-Enhanced De-identification System
Authors: Lee Kahyun , Kayaalp Mehmet , Henry Sam , Uzuner Özlem
Published: October 2021

Many modern entity recognition systems, including the current state-of-the-art de-identification systems, are based on
bidirectional long short-term memory (biLSTM)
units augmented by a
conditional random field (CRF)
sequence optimizer. These systems process the input sentence by sentence. This approach prevents the systems from capturing dependencies over sentence boundaries and makes accurate sentence boundary detection a prerequisite. Since sentence boundary detection can be problematic especially in clinical reports, where dependencies and co-references across sentence boundaries are abundant, these systems have clear limitations. In this study, we built a new system on the framework of one of the current state-of-the-art de-identification systems, NeuroNER, to overcome these limitations. This new system incorporates context embeddings through forward and backward

n

-grams without using sentence boundaries. Our
context-enhanced de-identification (CEDI)
system captures dependencies over sentence boundaries and bypasses the sentence boundary detection problem altogether. We enhanced this system with deep affix features and an attention mechanism to capture the pertinent parts of the input. The CEDI system outperforms NeuroNER on the 2006 i2b2 de-identification challenge dataset, the 2014 i2b2 shared task de-identification dataset, and the 2016 CEGS N-GRID de-identification dataset (

p < 0.01

). All datasets comprise narrative clinical reports in English but contain different note types varying from discharge summaries to psychiatric notes. Enhancing CEDI with deep affix features and the attention mechanism further increased performance.
Attention-based Unsupervised Keyphrase Extraction and Phrase Graph for COVID-19 Medical Literature Retrieval
Authors: Ding Haoran , Luo Xiao
Published: October 2021

Searching, reading, and finding information from the massive medical text collections are challenging. A typical biomedical search engine is not feasible to navigate each article to find critical information or keyphrases. Moreover, few tools provide a visualization of the relevant phrases to the query. However, there is a need to extract the keyphrases from each document for indexing and efficient search. The transformer-based neural networks—BERT has been used for various natural language processing tasks. The built-in self-attention mechanism can capture the associations between words and phrases in a sentence. This research investigates whether the self-attentions can be utilized to extract keyphrases from a document in an unsupervised manner and identify relevancy between phrases to construct a query relevancy phrase graph to visualize the search corpus phrases on their relevancy and importance. The comparison with six baseline methods shows that the self-attention-based unsupervised keyphrase extraction works well on a medical literature dataset. This unsupervised keyphrase extraction model can also be applied to other text data. The query relevancy graph model is applied to the COVID-19 literature dataset and to demonstrate that the attention-based phrase graph can successfully identify the medical phrases relevant to the query terms.
Bridging the Gap between Structured and Free-form Radiology Reporting: A Case-study on Coronary CT Angiography
Authors: Tariq Amara , Van Assen Marly , De Cecco Carlo N. , Banerjee Imon
Published: October 2021

Free-form radiology reports associated with coronary computed tomography angiography (CCTA) include nuanced and complicated linguistics to report cardiovascular disease. Standardization and interpretation of such reports is crucial for clinical use of CCTA. Coronary Artery Disease Reporting and Data System (CAD-RADS) has been proposed to achieve such standardization by implementing a strict template-based report writing and assignment of a score between 0 and 5 indicating the severity of coronary artery lesions. Even after its introduction, free-form unstructured report writing remains popular among radiologists. In this work, we present our attempts at bridging the gap between structured and unstructured reporting by natural language processing. We present machine learning models that while being trained only on structured reports, can predict CAD-RADS scores by analysis of free-text of unstructured radiology reports. The best model achieves 98% accuracy on structured reports and 92% 1-margin accuracy (difference of\le1 in the predicted and the actual scores) for free-form unstructured reports. Our model also performs well under very difficult circumstances including nuanced and widely varying terminology used for reporting cardiovascular functions and diseases, scarcity of labeled data for training our model, and uneven class label distribution.
RocksDB: Evolution of Development Priorities in a Key-value Store Serving Large-scale Applications
Authors: Dong Siying , Kryczka Andrew , Jin Yanqin , Stumm Michael
Published: October 2021

This article is an eight-year retrospective on development priorities for RocksDB, a key-value store developed at Facebook that targets large-scale distributed systems and that is optimized for Solid State Drives (SSDs). We describe how the priorities evolved over time as a result of hardware trends and extensive experiences running RocksDB at scale in production at a number of organizations: from optimizing write amplification, to space amplification, to CPU utilization. We describe lessons from running large-scale applications, including that resource allocation needs to be managed across different RocksDB instances, that data formats need to remain backward- and forward-compatible to allow incremental software rollouts, and that appropriate support for database replication and backups are needed. Lessons from failure handling taught us that data corruption errors needed to be detected earlier and that data integrity protection mechanisms are needed at every layer of the system. We describe improvements to the key-value interface. We describe a number of efforts that in retrospect proved to be misguided. Finally, we describe a number of open problems that could benefit from future research.
Matchings under Preferences: Strength of Stability and Tradeoffs
Authors: Chen Jiehua , Skowron Piotr , Sorge Manuel
Published: October 2021

We propose two solution concepts for matchings under preferences:
robustness
and
near stability
. The former strengthens while the latter relaxes the classical definition of stability by Gale and Shapley (1962). Informally speaking, robustness requires that a matching must be stable in the classical sense, even if the agents slightly change their preferences. Near stability, however, imposes that a matching must become stable (again, in the classical sense) provided the agents are willing to adjust their preferences a bit. Both of our concepts are quantitative; together they provide means for a fine-grained analysis of the stability of matchings. Moreover, our concepts allow the exploration of tradeoffs between stability and other criteria of social optimality, such as the egalitarian cost and the number of unmatched agents. We investigate the computational complexity of finding matchings that implement certain predefined tradeoffs. We provide a polynomial-time algorithm that, given agent preferences, returns a socially optimal robust matching (if it exists), and we prove that finding a socially optimal and nearly stable matching is computationally hard.
Irisin Rescues Blood‐Brain Barrier Permeability following Traumatic Brain Injury and Contributes to the Neuroprotection of Exercise in Traumatic Brain Injury
Authors: Guo Peipei , Jin Zhao , Wang Jin , Sang Aming , Wu Huisheng
Published: October 2021

Traumatic brain injury (TBI) has a high incidence, mortality, and morbidity all over the world. One important reason for its poor clinical prognosis is brain edema caused by blood‐brain barrier (BBB) dysfunction after TBI. The mechanism may be related to the disorder of mitochondrial morphology and function of neurons in damaged brain tissue, the decrease of uncoupling protein 2 (UCP2) activity, and the increase of inflammatory reaction and oxidative stress. In this study, we aimed to investigate the effects of exogenous irisin on BBB dysfunction after TBI and its role in the neuroprotective effects of endurance exercise (EE) in mice. The concentrations of irisin in cerebrospinal fluid (CSF) and plasma of patients with mild to severe TBI were measured by ELISA. Then, male C57BL/6J mice and UCP2 knockout mice with C57BL/6J background were used to establish the TBI model. The BBB structure and permeability were examined by transmission electron microscopy and Evans blue extravasation, respectively. The protein expressions of irisin, occludin, claudin‐5, zonula occludens‐1 (ZO‐1), nuclear factor E2‐related factor 2(Nrf2), quinine oxidoreductase (NQO‐1), hemeoxygenase‐1 (HO‐1), cytochrome C (Cyt‐C), cytochrome C oxidase (COX IV), BCL2‐associated X protein (Bax), cleaved caspase‐3, and UCP2 were detected by western blot. The production of reactive oxygen species (ROS) was evaluated by the dihydroethidium (DHE) staining. The levels of inflammatory factors were detected by ELISA. In this study, we found that the CSF irisin levels were positively correlated with the severity of disease in patients with TBI and both EE and exogenous irisin could reduce BBB damage in a mouse model of TBI. In addition, we used UCP2−/− mice and further found that irisin could improve the dysfunction of BBB after TBI by promoting the expression of UCP2 on the mitochondrial membrane of neurons, reducing the damage of mitochondrial structure and function, thus alleviating the inflammatory response and oxidative stress. In conclusion, the results of this study suggested that irisin might alleviate brain edema after TBI by promoting the expression of UCP2 on the mitochondrial membrane of neurons and contribute to the neuroprotection of EE against TBI.
The Expression and Function of Circadian Rhythm Genes in Hepatocellular Carcinoma
Authors: Jiang Yanan , Shen Xiuyun , Fasae Moyondafoluwa Blessing , Zhi Fengnan , Chai Lu , Ou Yue , Feng Hai , Liu Siwei , Liu Ying , Yang Shucai
Published: October 2021

Hepatocellular carcinoma (HCC) is among the most common and lethal form of cancer worldwide. However, its diagnosis and treatment are still dissatisfactory, due to limitations in the understanding of its pathogenic mechanism. Therefore, it is important to elucidate the molecular mechanisms and identify novel therapeutic targets for HCC. Circadian rhythm‐related genes control a variety of biological processes. These genes play pivotal roles in the initiation and progression of HCC and are potential diagnostic markers and therapeutic targets. This review gives an update on the research progress of circadian rhythms, their effects on the initiation, progression, and prognosis of HCC, in a bid to provide new insights for the research and treatment of HCC.
Secure Outsourced Attribute-Based Signatures with Perfect Anonymity in the Standard Model
Authors: Huang Zhenjie , Duan Runlong , Chen Qunshan , Huang Hui , Zhou Yuping
Published: October 2021

Outsourced attribute-based signatures (OABS) enable users to sign messages without revealing specific identity information and are suitable for scenarios with limited computing power. Recently, Mo et al. proposed an expressive outsourced attribute-based signature scheme (Peer-to-Peer Networking and Applications, 11, 2017). In this paper, we show that Mo et al.’s scheme does not achieve any of the three security properties. Their scheme is incorrect. The adversary can collude with the malicious signing-cloud service provider (S-CSP) to forge valid signatures on any message and any attribute set. And the S-CSP could trace the access structures used to generate the signatures. Then, we treat the S-CSP as an adversary and present more accurate unforgeability and anonymity models for OABS to remedy the drawbacks of the previous ones. Finally, we propose a simple but significant improvement to fix our attacks. The improved scheme achieves correctness, unforgeability, and perfect anonymity while keeping the efficiency almost unchanged. We also prove the security of the improved scheme under the standard model.
Do Bilinguals Outperform Monolinguals in Switching Tasks? Contrary Evidence for Nonlinguistic and Linguistic Switching Tasks
Authors: Mas-Herrero Ernest , Adrover-Roig Daniel , Ruz María , de Diego-Balaguer Ruth
Published: October 2021

The benefits of bilingualism in executive functions are highly debated. Even so, in switching tasks, these effects seem robust, although smaller than initially thought (Gunnerud et al., 2020; Ware et al., 2020). By handling two languages throughout their lifespan, bilinguals appear to train their executive functions and show benefits in nonlinguistic switching tasks compared to monolinguals. Nevertheless, because bilinguals need to control for the interference of another language, they may show a disadvantage when dealing with task-switching paradigms requiring language control, particularly when those are performed in their less dominant language. The present work explored this issue by studying bilingualism’s effects on task switching within the visual and language domains. On the one hand, our results show that bilinguals were overall faster and presented reduced switch costs compared to monolinguals when performing perceptual geometric judgments with no time for task preparation. On the other hand, no bilingual advantage was found when a new sample of comparable bilinguals and monolinguals completed a within-language switching task. Our results provide clear evidence favoring the bilingual advantage, yet only when the task imposes greater executive demands and does not involve language control.
A meta-analysis of semantic classification of citations
Authors: Kunnath Suchetha N. , Herrmannova Drahomira , Pride David , Knoth Petr
Published: October 2021

The aim of this literature review is to examine the current state of the art in the area of citation classification. In particular, we investigate the approaches for characterizing citations based on their semantic type. We conduct this literature review as a meta-analysis covering 60 scholarly articles in this domain. Although we included some of the manual pioneering works in this review, more emphasis is placed on the later automated methods, which use Machine Learning and Natural Language Processing (NLP) for analyzing the fine-grained linguistic features in the surrounding text of citations. The sections are organized based on the steps involved in the pipeline for citation classification. Specifically, we explore the existing classification schemes, data sets, preprocessing methods, extraction of contextual and noncontextual features, and the different types of classifiers and evaluation approaches. The review highlights the importance of identifying the citation types for research evaluation, the challenges faced by the researchers in the process, and the existing research gaps in this field.
MasakhaNER: Named Entity Recognition for African Languages
Authors: Adelani David Ifeoluwa , Abbott Jade , Neubig Graham , D’souza Daniel , Kreutzer Julia , Lignos Constantine , Palen-Michel Chester , Buzaaba Happy , Rijhwani Shruti , Ruder Sebastian , Mayhew Stephen , Azime Israel Abebe , Muhammad Shamsuddeen H. , Emezue Chris Chinenye , Nakatumba-Nabende Joyce , Ogayo Perez , Anuoluwapo Aremu , Gitau Catherine , Mbaye Derguene , Alabi Jesujoba , Yimam Seid Muhie , Gwadabe Tajuddeen Rabiu , Ezeani Ignatius , Niyongabo Rubungo Andre , Mukiibi Jonathan , Otiende Verrah , Orife Iroro , David Davis , Ngom Samba , Adewumi Tosin , Rayson Paul , Adeyemi Mofetoluwa , Muriuki Gerald , Anebi Emmanuel , Chukwuneke Chiamaka , Odu Nkiruka , Wairagala Eric Peter , Oyerinde Samuel , Siro Clemencia , Bateesa Tobius Saul , Oloyede Temilola , Wambui Yvonne , Akinode Victor , Nabagereka Deborah , Katusiime Maurice , Awokoya Ayodele , MBOUP Mouhamadane , Gebreyohannes Dibora , Tilaye Henok , Nwaike Kelechi , Wolde Degaga , Faye Abdoulaye , Sibanda Blessing , Ahia Orevaoghene , Dossou Bonaventure F. P. , Ogueji Kelechi , DIOP Thierno Ibrahima , Diallo Abdoulaye , Akinfaderin Adewale , Marengereke Tendai , Osei Salomey
Published: October 2021

We take a step towards addressing the under- representation of the African continent in NLP research by bringing together different stakeholders to create the first large, publicly available, high-quality dataset for named entity recognition (NER) in ten African languages. We detail the characteristics of these languages to help researchers and practitioners better understand the challenges they pose for NER tasks. We analyze our datasets and conduct an extensive empirical evaluation of state- of-the-art methods across both supervised and transfer learning settings. Finally, we release the data, code, and models to inspire future research on African NLP.1
New spongillaflies of the genus Sisyrina Banks, 1939 (Neuroptera: Sisyridae) from the Oriental faunal region
Authors: YANG YING , LIU XINGYUE
Published: October 2021

The family Sisyridae (spongillaflies) constitute a minor group of Neuroptera, with 72 extant species in four genera. Sisyrina Banks, 1939 is a rare spongillafly genus, which previously comprised only three known species respectively from Australia, China, and India. Here we describe two new species of Sisyrina, namely Sisyrina fashengi sp. nov. from China and Laos, and Sisyrina vietnamica sp. nov. from Vietnam. Sisyrina qiong Yang & Gao, 2002 from Hainan Island is also redescribed. A key to the species of Sisyrina is provided.
COVID-19 Pandemic Impact on Students Intention to Use E-Learning Among Malaysian Higher Education Institutions
Authors: Ramasamy Siva Prakash , Shahzad Arfan , Hassan Rohail
Published: October 2021

In the emergence of pandemic Coronavirus Disease (COVID-19), the delivery of education service becomes a global issue, and many traditional higher education institutes are shifting toward digital alternatives methods. E-learning is considered the most appropriate effective method of knowledge delivery to meet the current academic requirements. This study investigates the key determinants which influence the Intentions to use e-learning among students in higher education institutes in Malaysia due to the outbreak of the novel Covid-19 pandemic. The data were collected through structured questionnaires from students. The data were analyzed using the structural equation modeling using partial least squares (SEMPLS). The research findings revealed that Attitude, Subjective Norm, Perceived usefulness, and Perceived behavioral becomes a positive predictor of Intention to use e-learning. However, Subjective norms found no significant effect on Intention to use e-learning in the Malaysian context. It is due to the COVID-19 emergency that an individual must choose for the e-learning method disregarding their perceptions. Perceived ease of use and Perceived usefulness has a significant positive effect on attitude. These findings offer guidelines to educational institutes for the implementation of the e-learning system during unavoidable circumstances for the sustainable education system.
Associations between traditional and non-traditional anthropometric indices and cardiometabolic risk factors among inpatients with type 2 diabetes mellitus: a cross-sectional study
Authors: Golabi Sahar , Ajloo Sajad , Maghsoudi Fatemeh , Adelipour Maryam , Naghashpour Mahshid
Published: October 2021

Objective

We aimed to evaluate whether traditional and non-traditional adiposity indicators are associated with cardiometabolic risk factors among adult patients with type 2 diabetes mellitus (DM).

Methods

In this cross-sectional study among 240 inpatients with type 2 DM, we determined traditional anthropometric indicators including body mass index, waist circumference, hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio, and non-traditional anthropometric indicators including lipid accumulation product (LAP), visceral adiposity index (VAI), deep abdominal adipose tissue (DAAT), and Després indices. Lipid profile, fasting blood glucose, glycated hemoglobin (HbA1c), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were measured to evaluate cardiometabolic parameters.

Results

In overweight patients, DAAT was positively correlated with total triglycerides. LAP was negatively correlated with serum HDL-C levels. WHR and DAAT were associated with total triglycerides, HbA1c, total cholesterol, total cholesterol/HDL-C, and total triglycerides/HDL-C, after adjustment for age and duration of disease. VAI, DAAT, LAP, and Després index were significant determinants of lipid profile and SBP.

Conclusion

Traditional and non-traditional anthropometric indices are associated with cardiometabolic risk factors in patients with type 2 DM.
A survey of anaesthetists on uterotonic usage practices for elective caesarean section in Australia and New Zealand
Authors: Terblanche Nico CS , Otahal Petr , Sharman James E
Published: October 2021

Prophylactic administration of uterotonics ensures adequate uterine contraction at elective caesarean section to prevent substantial haemorrhage. Royal College of Obstetricians and Gynaecologists guidelines advise the administration of oxytocin at 5 IU as a ‘slow bolus’ but there are variations in clinical practice. This study aimed to determine the beliefs and uterotonic usage practices at elective caesarean section by surveying anaesthetist members of the Obstetric Anaesthesia Special Interest Group in Australia and New Zealand. Questionnaires were emailed to Obstetric Anaesthesia Special Interest Group members and the response rate was 33%, with analysis of 279 completed reports. Oxytocin was the most commonly used first-line uterotonic, but extensive variation in oxytocin bolus use was identified. Thirty-eight per cent of anaesthetists routinely administered Royal College of Obstetricians and Gynaecologists guideline-recommended 5 IU, whereas 38% favoured low dose (<5 IU), 10% high dose (≥10 IU) oxytocin and 13% carbetocin (100 µg). More than 50% felt the evidence was weak for guideline-recommended 5 IU. Wide variation in the duration of oxytocin administration was also identified. Fifty-eight per cent of anaesthetists routinely gave follow-up oxytocin infusions, most commonly at 40 IU over 4 hours, but there was significant variation in the dosage (10–40 IU) and administration duration (1 hour to ≥6 hours). In conclusion, there is significant variation in oxytocin usage practices at elective caesarean section among Australian and New Zealand anaesthetists. This variation may be due to a lack of strong evidence to guide practice. This emphasises the need for high quality trials in this clinically important area.
Social Clubs in a Princely State: The Case from Hyderabad, Deccan
Authors: Cohen Benjamin B.
Published: October 2021

Social clubs began in India in the late eighteenth century in the wake of British colonial expansion. Clubs flourished in colonial India’s two great administrative divisions: those areas under direct control and the indirectly controlled princely states of India. This article explores the role of clubs in Hyderabad city, the capital city of India’s largest and wealthiest princely state. Here, club dynamics operated differently. By the nineteenth century, princely state urban capitals supported two centres of power: the local Indian ruler and that of the British Resident. These multiple centres of power forced clubs in this urban environment to be less attentive to difference among members (race and class) and more attentive to reaching across divisions. An examination of clubs in a princely state urban environment, thus, reveals an Indo-British clubland, largely marked by forms of social coexistence and cooperation.
Indian Women in World War II: The Air Raid Precaution ‘Comfort’ Women
Authors: Deepak Kashyap
Published: October 2021

The main focus of this article is on the war-stricken ecology of World War II and the notable role played by Indian women as Air Raid Precaution Wardens. They gave their unmatched services in the air raid–prone areas and earned a name. However, until the close of the war, they were reduced to not more than ‘comfort women’ for British officers and soldiers. Simultaneously, the article explains how the women’s influential roles are sidelined by giving too much preference to the topic such as rape, abduction and war crimes against women. The critics and historians remain busy in criticising other armies on the atrocities inflicted upon women by them. The conclusion exposes the double standard of the academic world: first, they criticise Japan over the issue of ‘comfort women’, but they close their eyes towards Indian women. The article explains how the British too exploited Indian women, but they remain hidden from the eyes of critics due to their gentlemen status.
India’s Quest for a National Space Law and the Missing Piece of Possessory Rights
Authors: Athar ud din
Published: October 2021

As the commercial use of outer space becomes feasible, the nature of possessory rights will potentially emerge as the central focus of future space-related activities. The existing international law relating to outer space does not address in detail the nature of possessory rights in outer space and is subject to multiple interpretations. Alarmingly, the recently adopted space policies and legislations by some States have taken a definitive position regarding the commercial use of natural resources in outer space.

In light of India’s increasing involvement in outer space, it circulated the Draft Space Activities Bill, 2017, to formulate a national space law. However, the nature of possessory rights in outer space is not addressed in detail in the Draft Space Activities Bill.

This study states that on account of recent developments happening elsewhere, it is extremely important for emerging powers like India to take a position on broader issues like the nature of possessory rights in outer space (which includes celestial bodies as well as resources contained therein). Not addressing the issue of possessory rights in outer space could have profound implications at both domestic as well as international levels.
Hegemonic Rivalry in a Peripheral Region: An Assessment of Nigeria–South Africa’s Role in African Politics
Authors: Olanrewaju John S. , Nwozor Agaptus
Published: October 2021

Nigeria’s claim as the giant of Africa is evident in her foreign policy articulation of African Centre Piece. From 1960, Nigeria has championed the project of Africa through different diplomatic engagements across the continent of Africa most especially under President Olusegun Obasanjo’s civilian administration. Nigeria’s unwavering support against the apartheid regime in South Africa led to the termination of apartheid government in 1994. However, the post- apartheid politics in Africa as well as the post-Cold War politics changed the dynamics of African politics. Nigeria’s claim as the giant of Africa became more contested and hypothetical with the emergence of notable countries such as Ethiopia and South Africa posing serious challenges to Nigeria’s hegemony in the continent. The most viable and notable threats came from South Africa following the end of apartheid regime in South Africa and coupled with its good governance rating, which had heightened the status of the country as a notable continental leader. This article attempts to explain the leadership roles of Nigeria and South Africa in a peripheral region of Africa with the view of analysing who has the sway to lead the affairs of Africa to the path of prosperity. Through the secondary method of data collection and qualitative method of data analysis (discourse analysis), the study concludes that Nigeria and South Africa roles in Africa were motivated by realist considerations. The study, however, recommends concerted efforts between Nigeria and South Africa in addressing socio-economic challenges in the African continent.
Posterior circulation stroke due to vertebral artery disease in the Chinese population
Authors: Zhang Changqing , Li Zixiao , Liu Liping , Pu Yuehua , Zou Xinying , Yan Hongyi , Pan Yuesong , Zhao Xingquan , Wang Yilong , Wang Yongjun
Published: October 2021

Background and purpose

Little is known about the distribution of the arteries responsible for noncardiogenic posterior circulation stroke due to vertebral artery disease in the Chinese population. Furthermore, few studies have compared the risk factors, imaging manifestations, and outcomes across different types of vertebral artery disease. Therefore, our aim was to compare the differences in the risk factors, imaging manifestations, and outcome across various types of vertebral artery disease.

Methods

We prospectively enrolled 228 patients from 22 Chinese centers with noncardiogenic posterior circulation stroke due to vertebral artery disease. Vertebral artery disease was classified by the involved segments of the responsible vertebral artery, and basilar artery (BA) involvement or not. Risk factors, clinical-radiologic patterns, and outcomes were compared across different types of vertebral artery disease.

Results

The intracranial vertebral artery (ICVA) was more frequently involved than was the extracranial vertebral artery (ECVA). The ICVA/ICVA + ECVA group more often presented with hypertension and higher systolic blood pressure than did the ECVA group. Compared with the single-segment-of-vertebral-artery group (SSVA), the group with multiple-segments-of-vertebral-artery (MSVA) involvement or SSVA with BA involvement had more serious clinical-radiologic patterns and worse outcomes. Multivariable Cox regression identified MSVA/SSVA + BA involvement as an independent predictor of recurrent ischemic cerebrovascular events.

Conclusions

The risk factors for ICVA/ICVA + ECVA were different from those of ECVA, and the MSVA/SSVA + BA group had more serious clinical-radiologic patterns and worse outcomes.
On the simplex, interior-point and objective space approaches to multiobjective linear programming
Authors: Nyiam Paschal B , Salhi Abdellah
Published: October 2021

Most Multiple Objective Linear Programming (MOLP) algorithms working in the decision variable space, are based on the simplex algorithm or interior-point method of Linear Programming. However, objective space based methods are becoming more and more prominent. This paper investigates three algorithms namely the Extended Multiobjective Simplex Algorithm (EMSA), Arbel’s Affine Scaling Interior-point (ASIMOLP) algorithm and Benson’s objective space Outer Approximation (BOA) algorithm. An extensive review of these algorithms is also included. Numerical results on non-trivial MOLP problems show that EMSA and BOA are at par and superior in terms of the quality of a most preferred nondominated point to ASIMOLP. However, ASIMOLP more than holds its own in terms of computing efficiency.
Does Financial Inclusion Promote Human Development? Evidence from India
Authors: Arora Neha , Kumar Naresh
Published: October 2021

The present study investigates the relationship between Financial Inclusion Index (FII) and Human Development Index (HDI) of Indian economy. The study developed FII for the Indian economy from 1991 to 2020 by using the dimensions of banking penetration, banking availability and usage of banking services. The well-known techniques of Analytical Hierarchy Process (AHP) and Technique of Preference by Similarity to Ideal Solution (TOPSIS) is used to develop FII. The ARDL bound test confirms the existence of a long-run relationship between financial inclusion and human development. Granger non-causality confirms the existence of bidirectional causality between financial inclusion and human development. As financial inclusion acts as a key for human development, government should adopt policies to speed up the financial inclusion process in India.
A germinal center–associated microenvironmental signature reflects malignant phenotype and outcome of DLBCL
Authors: Miyawaki Kohta , Kato Koji , Sugio Takeshi , Sasaki Kensuke , Miyoshi Hiroaki , Semba Yuichiro , Kikushige Yoshikane , Mori Yasuo , Kunisaki Yuya , Iwasaki Hiromi , Miyamoto Toshihiro , Kuo Frank C. , Aster Jon C. , Ohshima Koichi , Maeda Takahiro , Akashi Koichi
Published: October 2021

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy, with varying prognosis after the gold standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Several prognostic models have been established by focusing primarily on characteristics of lymphoma cells themselves, including cell-of-origin (COO), genomic alterations, and gene/protein expressions. However, the prognostic impact of the lymphoma microenvironment and its association with characteristics of lymphoma cells are not fully understood. Using the nCounter-based gene expression profiling of untreated DLBCL tissues, we assess the clinical impact of lymphoma microenvironment on the clinical outcomes and pathophysiological, molecular signatures in DLBCL. The presence of normal germinal center (GC)-microenvironmental cells, including follicular T cells, macrophage/dendritic cells, and stromal cells in lymphoma tissue indicates a positive therapeutic response. Our prognostic model, based on quantitation of transcripts from distinct GC-microenvironmental cell markers, clearly identified patients with graded prognosis independently of existing prognostic models. We observed increased incidences of genomic alterations and aberrant gene expression associated with poor prognosis in DLBCL tissues lacking GC-microenvironmental cells relative to those containing these cells. These data suggest that the loss of GC-associated microenvironmental signature dictates clinical outcomes of DLBCL patients reflecting the accumulation of “unfavorable” molecular signatures.
Preparation of ICA-loaded mPEG-ICA nanoparticles and their application in the treatment of LPS-induced H9c2 cell damage
Authors: Zhou Lin , Huang Zhi , Yang Shanyi , Wei Jiarui , Xu Yan , Hu Lin , Guo Xinrong , Yuan Limin , Yuan Zexuan , Yang Xiaoping , Tao Xiaojun , Zhang Qiufang
Published: October 2021

Hydrophilic polyethylene glycol monomethyl ether (mPEG) was grafted onto Icariin (ICA) by succinic anhydride to form a polyethylene glycol-Icariin (mPEG-ICA) polymer. The structure of the polymer was characterized by Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance spectroscopy (NMR). mPEG-ICA nanoparticles loaded with ICA were prepared by physical embedding of ICA by dialysis. The particle size was determined to be (220 ± 13.7) nm, and the ζ potential was (2.30 ± 1.33) mV by dynamic light scattering (DLS). Under a transmission electron microscope (TEM), the nanoparticles were spherical, and the morphology was regular. In the medium with pH 7.4, the drug release rate of mPEG-ICA nanoparticles reached (52.80 ± 1.70)% within 72 h. At pH 6.8, the cumulative drug release of nanoparticles reached (75.66 ± 0.17)% within 48 h. Treatment of the nanoparticles with LPS-treated H9c2 cells maintained cell viability, reduced LDH release and exerted antiapoptotic effects. Moreover, ICA-loaded mPEG-ICA nanoparticles significantly decreased the mRNA expression of the myocardial inflammatory cytokines TNF-α, IL-1β and IL-6M. In conclusion, ICA-loaded mPEG-ICA nanoparticles protected against LPS-induced H9c2 cell injury.
Random survival forests for dynamic predictions of a time-to-event outcome using a longitudinal biomarker
Authors: Pickett Kaci L , Suresh Krithika , Campbell Kristen R , Davis Scott , Juarez-Colunga Elizabeth
Published: October 2021

Background

Risk prediction models for time-to-event outcomes play a vital role in personalized decision-making. A patient’s biomarker values, such as medical lab results, are often measured over time but traditional prediction models ignore their longitudinal nature, using only baseline information. Dynamic prediction incorporates longitudinal information to produce updated survival predictions during follow-up. Existing methods for dynamic prediction include joint modeling, which often suffers from computational complexity and poor performance under misspecification, and landmarking, which has a straightforward implementation but typically relies on a proportional hazards model. Random survival forests (RSF), a machine learning algorithm for time-to-event outcomes, can capture complex relationships between the predictors and survival without requiring prior specification and has been shown to have superior predictive performance.

Methods

We propose an alternative approach for dynamic prediction using random survival forests in a landmarking framework. With a simulation study, we compared the predictive performance of our proposed method with Cox landmarking and joint modeling in situations where the proportional hazards assumption does not hold and the longitudinal marker(s) have a complex relationship with the survival outcome. We illustrated the use of the RSF landmark approach in two clinical applications to assess the performance of various RSF model building decisions and to demonstrate its use in obtaining dynamic predictions.

Results

In simulation studies, RSF landmarking outperformed joint modeling and Cox landmarking when a complex relationship between the survival and longitudinal marker processes was present. It was also useful in application when there were several predictors for which the clinical relevance was unknown and multiple longitudinal biomarkers were present. Individualized dynamic predictions can be obtained from this method and the variable importance metric is useful for examining the changing predictive power of variables over time. In addition, RSF landmarking is easily implementable in standard software and using suggested specifications requires less computation time than joint modeling.

Conclusions

RSF landmarking is a nonparametric, machine learning alternative to current methods for obtaining dynamic predictions when there are complex or unknown relationships present. It requires little upfront decision-making and has comparable predictive performance and has preferable computational speed.
Statistical reanalysis of vascular event outcomes in primary and secondary vascular prevention trials
Authors: Woodhouse Lisa J. , Montgomery Alan A. , Mant Jonathan , Davis Barry R. , Algra Ale , Mas Jean-Louis , Staessen Jan A. , Thijs Lutgarde , Tonkin Andrew , Kirby Adrienne , Pocock Stuart J. , Chalmers John , Hankey Graeme J. , Spence J. David , Sandercock Peter , Diener Hans-Christoph , Uchiyama Shinichiro , Sprigg Nikola , Bath Philip M.
Published: October 2021

Background

Vascular prevention trials typically use dichotomous event outcomes although this may be inefficient statistically and gives no indication of event severity. We assessed whether ordinal outcomes would be more efficient and how to best analyse them.

Methods

Chief investigators of vascular prevention randomised controlled trials that showed evidence of either benefit or harm, or were included in a systematic review that overall showed benefit or harm, shared individual participant data from their trials. Ordered categorical versions of vascular event outcomes (such as stroke and myocardial infarction) were analysed using 15 statistical techniques and their results then ranked, with the result with the smallest p-value given the smallest rank. Friedman and Duncan’s multiple range tests were performed to assess differences between tests by comparing the average ranks for each statistical test.

Results

Data from 35 trials (254,223 participants) were shared with the collaboration. 13 trials had more than two treatment arms, resulting in 59 comparisons. Analysis approaches (Mann Whitney U, ordinal logistic regression, multiple regression, bootstrapping) that used ordinal outcome data had a smaller average rank and therefore appeared to be more efficient statistically than those that analysed the original binary outcomes.

Conclusions

Ordinal vascular outcome measures appear to be more efficient statistically than binary outcomes and provide information on the severity of event. We suggest a potential role for using ordinal outcomes in vascular prevention trials.
A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies
Authors: Kubota Kiyoshi , Kelly Thu-Lan , Sato Tsugumichi , Pratt Nicole , Roughead Elizabeth , Yamaguchi Takuhiro
Published: October 2021

Background

Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied.

Methods

We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia.

Results

When the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 8.7) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression.

Conclusion

Case-crossover studies may be biased from within-subject exposure dependency, even without exposure time trends. This bias can be identified by comparing the odds ratio by the Mantel-Haenszel method and that by standard conditional logistic regression. We recommend using our proposed method which removes bias from within-subject exposure dependency and can account for time-varying confounders.
Analysis of COVID-19 data using neutrosophic Kruskal Wallis H test
Authors: Sherwani Rehan Ahmad Khan , Shakeel Huma , Awan Wajiha Batool , Faheem Maham , Aslam Muhammad
Published: October 2021

Background

Kruskal-Wallis H test from the bank of classical statistics tests is a well-known nonparametric alternative to a one-way analysis of variance. The test is extensively used in decision-making problems where one has to compare the equality of several means when the observations are in exact form. The test is helpless when the data is in an interval form and has some indeterminacy.

Methods

The interval-valued data often contain uncertainty and imprecision and often arise from situations that contain vagueness and ambiguity. In this research, a modified form of the Kruskal-Wallis H test has been proposed for indeterminacy data. A comprehensive theoretical methodology with an application and implementation of the test has been proposed in the research.

Results

The proposed test is applied on a Covid-19 data set for application purposes. The study results suggested that the proposed modified Kruskal-Wallis H test is more suitable in interval-valued data situations. The application of this new neutrosophic Kruskal-Wallis test on the Covid-19 data set showed that the proposed test provides more relevant and adequate results. The data representing the daily ICU occupancy by the Covid-19 patients were recorded for both determinate and indeterminate parts. The existing nonparametric Kruskal-Wallis H test under Classical Statistics would have given misleading results. The proposed test showed that at a 1% level of significance, there is a statistically significant difference among the average daily ICU occupancy by corona-positive patients of different age groups.

Conclusions

The findings of the results suggested that our proposed modified form of the Kruskal-Wallis is appropriate in place of the classical form of the test in the presence of the neutrosophic environment.
Extended parallel process model (EPPM) in evaluating lung Cancer risk perception among older smokers
Authors: Zarghami Fatemeh , Allahverdipour Hamid , Jafarabadi Mohammad Asghari
Published: October 2021

Background

There is a lack of scientific literature on the application of fear appeals theories to evaluate lung cancer risk perception among smokers. The aim of the present study is to apply the Extended Parallel Process Model (EPPM) to discover the perception of the smokers about their lifetime risk of developing lung cancer (perceived susceptibility), their perception of lung cancer survival (perceived severity), response efficacy, self-efficacy, and readiness to quit.

Methods

In this cross-sectional study, 215 eligible smokers (aged 45 years and over who have smoked at least 1 pack per day in the last 5 years) were recruited. The data collection tool was designed using validate self-report questionnaires and it was contained items on the perceived risk of a smoker contracting lung cancer and perceived lung cancer survival rate. It also had questions to measure the main constructs of the EPPM and Readiness to quit (“Low_Readiness”, and “High_Readiness”). To test how the data support conceptual EPPM to data, Generalized Structural Equation Modeling (GSEM) was used.

Results

Findings showed a significant relationship between Perceived_Susceptibility and Perceived_Response Efficacy; (B = 1.16,P < 0.001); between Perceived_Susceptibility and Perceived_Self Efficacy, (B = -0.93, P < 0.001), Perceived_Severity, and Perceived_Response Efficacy (B = 1.07, P < 0.001). There was also a significant relationship between Perceived_Threat and Perceived_Response Efficacy; between Perceived_Threat and Perceived_Self Efficacy. The relationship between High_Readiness and Perceived_Self Efficacy, and between High_Readiness and Perceived_Severity also were significant. However, the relationships between High_Readiness and Perceived_Threat were not significant (P > 0.05).

Conclusion

Perceived_threat and Perceived_efficacy were important for smokers with low readiness to quit, while Perceived_efficacy was most important for smokers with high readiness to quit. These findings could be used in promoting lung cancer awareness and designing smoking cessation programs based on smokers’ stages of change.