bluuebunny/crossref_metadata_2025 huggingface dataset:
Negative impact of the pandemic on hospital admissions, morbidity and early mortality for acute cirrhosis decompensation
Authors: Gananandan Kohilan , Phillips Alexandra , Chikhlia Anmol , Old Hannah , Sim Sharmaine Jia Ying , Thakur Niharika , Hussain Ishrat , Kazankov Konstantin , Mookerjee Rajeshwar P
Published: January 2023

Introduction

The global pandemic has diverted resources away from management of chronic diseases, including cirrhosis. While there is increasing knowledge on COVID-19 infection in liver cirrhosis, little is described on the impact of the pandemic on decompensated cirrhosis admissions and outcomes, which was the aim of this study.

Methods

A single-centre, retrospective study, evaluated decompensated cirrhosis admissions to a tertiary London hepatology and transplantation centre, from October 2018 to February 2021. Patients were included if they had an admission with cirrhosis decompensation defined as new-onset jaundice or ascites, infection, encephalopathy, portal hypertensive bleeding or renal dysfunction.

Results

The average number of admissions stayed constant between the pre-COVID-19 (October 2018–February 2020) and COVID-19 periods (March 2020–February 2021). Patients transferred in from secondary centres had consistently higher severity scores during the COVID-19 period (UK Model for End-Stage Liver Disease 58 vs 54; p=0.007, Model for End-Stage Liver Disease-Sodium 22 vs 18; p=0.006, EF-CLIF Acute Decompensation (AD) score 55.0 vs 51.0; p=0.055). Of those admitted to the intensive care without acute-on-chronic liver failure, there was a significant increase in AD scores during the COVID-19 period (58 vs 48, p=0.009). In addition, there was a trend towards increased hospital readmission rates during the COVID-19 period (29.5% vs 21.5%, p=0.067). When censored at 30 days, early mortality postdischarge was significantly higher during the COVID-19 period (p<0.001) with a median time to death of 35 days compared with 62 days pre-COVID-19.

Discussion

This study provides a unique perspective on the impact that the global pandemic had on decompensated cirrhosis admissions. The findings of increased early mortality and readmissions, and higher AD scores on ICU admission, highlight the need to maintain resourcing for high-level hepatology care and follow-up, in spite of other disease pressures.
Men’s motivations, barriers to and aspirations for their families’ health in the first 1000 days in sub-Saharan Africa: a secondary qualitative analysis
Authors: Watson Daniella , Chatio Samuel , Barker Mary , Boua Palwende Romuald , Compaoré Adélaïde , Dalaba Maxwell , Erzse Agnes , Godfrey Keith , Hofman Karen , Kehoe Sarah , McGrath Nuala , Mukoma Gudani , Nonterah Engelbert A , Norris Shane A , Sorgho Hermann , Ward Kate A , Hardy-Johnson Polly
Published: January 2023

Introduction

The first 1000 days of life are a critical period of growth and development that have lasting implications for health, cognitive, educational and economic outcomes. In sub-Saharan Africa, gender and social norms are such that many men have little engagement with maternal and child health and nutrition during pregnancy and early childhood. This study explores how men perceive their role in three sites in sub-Saharan Africa.

Methods

Secondary qualitative analysis of 10 focus group discussions with 76 men in Burkina Faso, Ghana and South Africa. Data were thematically analysed to explore men’s perceptions of maternal and child health and nutrition.

Results

Men considered themselves ‘providers’ and 'advisors' within their families, particularly of finances, food and medicines. They also indicated that this advice was out of care and concern for their families’ health. There were similarities in how the men perceive their role. Differences between men living in rural and urban settings included health priorities, the advice and the manner in which it was provided. Across all settings, men wanted to be more involved with maternal and child health and nutrition. Challenges to doing so included stigma and proscribed social gender roles.

Conclusion

Men want a greater engagement in improving maternal and child health and nutrition but felt that their ability to do so was limited by culture-specified gender roles, which are more focused on providing for and advising their families. Involving both men and women in intervention development alongside policymakers, health professionals and researchers is needed to improve maternal and child health and nutrition.
Determining the top research priorities in UK prehospital critical care: a modified Delphi study
Authors: Ramage Lisa , McLachlan Sarah , Williams Kristian
Published: January 2023

Background

Prehospital critical care is a rapidly evolving field. There is a paucity of evidence relating to its practice, with limited progress in answering those research questions identified over a decade ago. It is vital that evidence gaps are identified and addressed. This study aimed to define the current research priorities in UK prehospital critical care.

Methods

This modified national Delphi study was coordinated by the Pre-HOspital Trainee Operated research Network and conducted in four rounds between October 2021 and April 2022. Rounds 1 and 2 were conducted online with clinicians involved in prehospital critical care delivery and non-clinical prehospital researchers. Rounds 3 and 4 were completed online by a subject matter expert (SME) panel.

Results

In round 1, 78 participants submitted 394 research questions relating to prehospital critical care delivery in the UK. These were refined and categorised into 192 questions, which were scored for importance in round 2. Fifty questions were discussed and scored by the SME panel in round 3. Round 4 created a ranked top 20 list. The top research priority was ‘Which cardiac arrest patients should critical care teams be dispatched to; how do we identify these patients during the emergency call?’. Other priorities included dispatch optimisation, out-of-hospital medical cardiac arrest management, optimising resuscitation in haemorrhagic shock, improving traumatic brain injury outcomes and optimising management of traumatic cardiac arrest.

Conclusions

This modified Delphi study identified 20 research priorities where efforts should be concentrated to develop collaborative prehospital critical care research within the UK over the next 5 years.
Pornography use among adolescents and the role of primary care
Authors: Jhe Grace B , Addison Jessica , Lin Jessica , Pluhar Emily
Published: January 2023

Given the increase in pornography use among adolescents over the years, we discuss the impact of its use on sexual health development as well as the role of primary care providers (PCPs) in assessing use and providing sexual health education. While pornography use is often viewed negatively, it is important to develop unbiased understanding of the use in order to provide non-judgemental, adolescent-focused and educational care. As PCPs are often the first point of contact when adolescents experience medical and behavioural health concerns, it is essential for them to be equipped to screen for pornography use effectively, create a confidential and comfortable environment to talk about pornography use and sexuality, and be informed of ways to promote open discussion between youth and parents. In addition to PCP involvement, parental collaboration, knowledge and comfortability with discussing pornography use with their child are powerful tools in understanding and navigating pornography use in this population. This special communication seeks to provide an objective view of adolescents’ pornography use, guidelines for screening of pornography use and ways to facilitate conversations about the use between adolescents and caregivers.
Best practice for LDL-cholesterol: when and how to calculate
Authors: Martins Janine , Steyn Nicolene , Rossouw H Muller , Pillay Tahir S
Published: January 2023

The lipid profile is important in the risk assessment for cardiovascular disease. The lipid profile includes total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglycerides (TGs) and low-density lipoprotein (LDL)-cholesterol (LDL-C). LDL-C has traditionally been calculated using the Friedewald equation (invalid with TGs greater than 4.5 mmol/L and is based on the assumption that the ratio of TG to cholesterol in very- low-density lipoprotein (VLDL) is 5 when measured in mg /dL). LDL-C can be quantified with a reference method, beta-quantification involving ultracentrifugation and this is unsuitable for routine use. Direct measurement of LDL-C was expected to provide a solution with high TGs. However, this has some challenges because of a lack of standardisation between the reagents and assays from different manufacturers as well as the additional costs. Furthermore, mild hypertriglyceridaemia also distorts direct LDL-C measurements. With the limitations of the Friedewald equation, alternatives have been derived. Newer equations include the Sampson-National Institutes of Health (NIH) equation 2 and the Martin-Hopkins equation. The Sampson-NIH2 equation was derived using beta-quantification in a population with high TG and multiple least squares regression to calculate VLDL-C, using TGs and non-HDL-C as independent variables. These data were used in a second equation to calculate LDL-C. The Sampson-NIH2 equation can be used with TGs up to 9 mmol/L. The Martin-Hopkins equation uses a 180 cell stratification of TG/non-HDL-C to determine the TG:VLDL-C ratio and can be used with TGs up to 4.5 mmol/L. Recently, an extended Martin-Hopkins equation has become available for TGs up to 9.04 mmol/L.This article discusses the best practice approach to calculating LDL-C based on the available evidence.
Correlation of immediate prevalence of cervical precancers and cancers with HPV genotype and age in women with ASC-US/hrHPV+: a retrospective analysis of 2292 cases
Authors: Liu Qin , Zhang Tao , Chen Liqing , Zhou Xin , Zhang Xiaofei , Zheng Wenxin , Niu Shuang , Zhou Feng
Published: January 2023

Aims

To stratify the risk of cervical precancers (high-grade squamous intraepithelial lesion (HSIL) and adenocarcinoma in situ (AIS)) and cancers (squamous cell carcinoma (SCC) and adenocarcinoma) based on distinct high-risk human papillomavirus (hrHPV) genotypes as well as age groups among women with atypical squamous cells of undetermined significance (ASC-US) and hrHPV+results.

Methods

In total, 2292 cases of ASC-US/hrHPV+ with immediate follow-up biopsy results were included in the study for prevalence analysis.

Results

Overall, 12.2% women with ASC-US /hrHPV+ had HSIL+ while 0.22% had AIS+ lesions. The HPV-16+ group (31.6%) showed significantly higher prevalence of HSIL+ squamous lesions than other genotype groups (p<0.0001). The prevalence of SCC is significantly higher in HPV-16+ (1.8%) or HPV-18/45+ (1.1%) group than women in other genotype groups (0.1%) (p<0.0001). The HPV-18/45+ group (1.7%) showed significantly higher prevalence of AIS+ glandular lesions than other genotype groups (p=0.003). In addition, SCC prevalence was significantly higher in age over 50 group than that in age under 50 group (1.2% vs 0.2%, p=0.012).

Conclusion

Women with ASC-US/hrHPV+ are at significant risk of cervical precancers and cancers; notably, HPV-16+ group has a higher risk of HSIL squamous lesions and SCC while HPV-18/45+ group has a higher risk of AIS+ glandular lesions. In addition, the older patient group (>50 years) has a significantly higher risk of SCC. Therefore, HPV genotyping as well as patient age need to be considered in the clinical management of patient.
Novel banana lectin CAR-T cells to target pancreatic tumors and tumor-associated stroma
Authors: McKenna Mary K , Ozcan Ada , Brenner Daniel , Watanabe Norihiro , Legendre Maureen , Thomas Dafydd G , Ashwood Christopher , Cummings Richard D , Bonifant Challice , Markovitz David M , Brenner Malcolm K
Published: January 2023

Background

Cell therapies for solid tumors are thwarted by the hostile tumor microenvironment (TME) and by heterogeneous expression of tumor target antigens. We address both limitations with a novel class of chimeric antigen receptors based on plant lectins, which recognize the aberrant sugar residues that are a ‘hallmark’ of both malignant and associated stromal cells. We have expressed in T cells a modified lectin from banana, H84T BanLec, attached to a chimeric antigen receptor (H84T-CAR) that recognizes high-mannose (asparagine residue with five to nine mannoses). Here, we tested the efficacy of our novel H84T CAR in models of pancreatic ductal adenocarcinoma (PDAC), intractable tumors with aberrant glycosylation and characterized by desmoplastic stroma largely contributed by pancreatic stellate cells (PSCs).

Methods

We transduced human T cells with a second-generation retroviral construct expressing the H84T BanLec chimeric receptor, measured T-cell expansion, characterized T-cell phenotype, and tested their efficacy against PDAC tumor cells lines by flow cytometry quantification. In three-dimensional (3D) spheroid models, we measured H84T CAR T-cell disruption of PSC architecture, and T-cell infiltration by live imaging. We tested the activity of H84T CAR T cells against tumor xenografts derived from three PDAC cell lines. Antitumor activity was quantified by caliper measurement and bioluminescence signal and used anti-human vimentin to measure residual PSCs.

Results

H84T BanLec CAR was successfully transduced and expressed by T cells which had robust expansion and retained central memory phenotype in both CD4 and CD8 compartments. H84T CAR T cells targeted and eliminated PDAC tumor cell lines. They also disrupted PSC architecture in 3D models in vitro and reduced total tumor and stroma cells in mixed co-cultures. H84T CAR T cells exhibited improved T-cell infiltration in multicellular spheroids and had potent antitumor effects in the xenograft models. We observed no adverse effects against normal tissues.

Conclusions

T cells expressing H84T CAR target malignant cells and their stroma in PDAC tumor models. The incorporation of glycan-targeting lectins within CARs thus extends their activity to include both malignant cells and their supporting stromal cells, disrupting the TME that otherwise diminishes the activity of cellular therapies against solid tumors.
Statin drugs enhance responses to immune checkpoint blockade in head and neck cancer models
Authors: Kansal Vikash , Burnham Andre J , Kinney Brendan L C , Saba Nabil F , Paulos Chrystal , Lesinski Gregory B , Buchwald Zachary S , Schmitt Nicole C
Published: January 2023

Background

Anti-PD-1 immune checkpoint blockade is approved for first-line treatment of recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), but few patients respond. Statin drugs (HMG-CoA reductase inhibitors) are associated with superior survival in several cancer types, including HNSCC. Emerging data suggest that manipulation of cholesterol may enhance some aspects of antitumor immunity.

Methods

We used syngeneic murine models (mouse oral cancer, MOC1 and TC-1) to investigate our hypothesis that a subset of statin drugs would enhance antitumor immunity and delay tumor growth.

Results

Using an ex vivo coculture assay of murine cancer cells and tumor infiltrating lymphocytes, we discovered that all seven statin drugs inhibited tumor cell proliferation. Simvastatin and lovastatin also enhanced T-cell killing of tumor cells. In mice, daily oral simvastatin or lovastatin enhanced tumor control and extended survival when combined with PD-1 blockade, with rejection of MOC1 tumors in 30% of mice treated with lovastatin plus anti-PD-1. Results from flow cytometry of tumors and tumor-draining lymph nodes suggested T cell activation and shifts from M2 to M1 macrophage predominance as potential mechanisms of combination therapy.

Conclusions

These results suggest that statins deserve further study as well-tolerated, inexpensive drugs that may enhance responses to PD-1 checkpoint blockade and other immunotherapies for HNSCC.
Novel combination strategy of high intensity focused ultrasound (HIFU) and checkpoint blockade boosted by bioinspired and oxygen-supplied nanoprobe for multimodal imaging-guided cancer therapy
Authors: Tang Rui , He Hongye , Lin Xiaohong , Wu Nianhong , Wan Li , Chen Qiaoqi , Hu Yaqin , Cheng Chen , Cao Yuting , Guo Xun , Zhou Ying , Xiong Xialin , Zheng Min , Wang Qi , Li Faqi , Zhou Yang , Li Pan
Published: January 2023

Background

High-intensity focused ultrasound (HIFU) has shown considerable promise in treating solid tumors, but its ultrasonic energy is easily attenuated, resulting in insufficient energy accumulation in the target area. Moreover, HIFU ablation alone may inevitably lead to the presence of residual tumors, which may cause tumor recurrence and metastasis. Here, we describe a synergistic regimen combining HIFU facilitation with immunomodulation based on a novel oxygen-carrying biomimetic perfluorocarbon nanoparticle (M@P-SOP) to stimulate immunogenic cell death in tumor cells while alleviating immune suppression tumor microenvironment.

Methods

M@P-SOP was prepared by double emulsion and film extrusion method. The anticancer and antimetastatic effects of M@P-SOP were evaluated on a preclinical transplanted 4T1 tumor model by combining HIFU and immunotherapy. Flow cytometry and immunofluorescence were used to clarify the potential mechanism of HIFU+M@P-SOP and their role in anti-programmed death ligand-1 (PD-L1) therapy.

Results

Guided by photoacoustic/MR/ultrasound (US) multimodal imaging, M@P-SOP was abundantly enriched in tumor, which greatly enhanced HIFU’s killing of tumor tissue in situ, induced stronger tumor immunogenic cell death, stimulated dendritic cell maturation and activated CD8+T cells. At the same time, M@P-SOP released oxygen to alleviate the tumor hypoxic environment, repolarizing the protumor M2-type macrophages into antitumor M1-type. With concurrent anti-PD-L1 treatment, the antitumor immune response was further amplified to the whole body, and the growth of mimic distant tumor was effectively suppressed.

Conclusions

Our findings offer a highly promising HIFU synergist for effectively ameliorating acoustic and hypoxia environment, eventually inhibiting tumor growth and metastasis by stimulating host’s antitumor immunity under HIFU ablation, especially in synergizing with PD-L1 antibody immunotherapy.
Recent advances in neuroanatomy: the myotome update
Authors: Sonoo Masahiro
Published: January 2023

The myotome of a muscle is the basis for diagnosing spinal and peripheral nerve disorders. Despite its critical importance in clinical neurology, myotome charts presented in many textbooks, surprisingly, show non-negligible discordances with each other. Many authors do not even clearly state the bases of their charts. Studies that have presented with raw data regarding myotome identification are rather rare. A classic study in the 19th century that pursued the nerve course in cadavers still has a substantial influence on existing charts, despite its definite limitations. Other scarce studies in humans include identification by root stimulation during surgery, clinical observations in root avulsion or spinal cord injury and clinical and electromyographical investigations in patients with single radiculopathies or certain plexopathies. A few recent studies have proposed new theories regarding the myotomes of some muscles. T1 innervation of the median intrinsic hand muscles is a typical example. We have added a number of new findings, such as T1 innervation of the forearm flexor muscles innervated by the median nerve except the pronator teres and flexor carpi radialis, C5 innervation of the brachioradialis, and two C6 indicator muscles, pronator teres and extensor carpi radialis brevis. Increased accuracy of the myotome charts will improve the localisation in neurology.
Deep learning-based personalised outcome prediction after acute ischaemic stroke
Authors: Kim Doo-Young , Choi Kang-Ho , Kim Ja-Hae , Hong Jina , Choi Seong-Min , Park Man-Seok , Cho Ki-Hyun
Published: January 2023

Background

Whether deep learning models using clinical data and brain imaging can predict the long-term risk of major adverse cerebro/cardiovascular events (MACE) after acute ischaemic stroke (AIS) at the individual level has not yet been studied.

Methods

A total of 8590 patients with AIS admitted within 5 days of symptom onset were enrolled. The primary outcome was the occurrence of MACEs (a composite of stroke, acute myocardial infarction or death) over 12 months. The performance of deep learning models (DeepSurv and Deep-Survival-Machines (DeepSM)) and traditional survival models (Cox proportional hazards (CoxPH) and random survival forest (RSF)) were compared using the time-dependent concordance index (Ctdindex).

Results

Given the top 1 to all 60 clinical factors according to feature importance, CoxPH and RSF yieldedCtdindex of 0.7236–0.8222 and 0.7279–0.8335, respectively. Adding image features improved the performance of deep learning models and traditional models assisted by deep learning models. DeepSurv and DeepSM yielded the bestCtdindex of 0.8496 and 0.8531 when images were added to all 39 relevant clinical factors, respectively. In feature importance, brain image was consistently ranked highly. Deep learning models automatically extracted the image features directly from personalised brain images and predicted the risk and date of future MACEs at the individual level.

Conclusions

Deep learning models using clinical data and brain images could improve the prediction of MACEs and provide personalised outcome prediction for patients with AIS. Deep learning models will allow us to develop more accurate and tailored prognostic prediction systems that outperform traditional models.
Impact of psoriatic arthritis and comorbidities on ustekinumab outcomes in psoriasis: a retrospective, observational BADBIR cohort study
Authors: Tillett William , Ogdie Alexis , Passey Alun , Gorecki Patricia
Published: January 2023

Objectives

Psoriasis and psoriatic arthritis (PsA) are independently associated with comorbidities, including obesity and metabolic syndrome, which may impact treatment outcomes. This study aimed to assess baseline differences between patients with plaque psoriasis alone and those with concomitant PsA, and to investigate the impact of these characteristics on ustekinumab (UST) persistence and outcomes.

Methods

9057 patients receiving UST or conventional systemic disease-modifying antirheumatic drugs were selected from the British Association of Dermatologists Biologic and Immunomodulators Register. The psoriasis and PsA cohorts were compared at baseline. Time to discontinuation during 10-year follow-up was assessed using multivariable Cox regression and Kaplan–Meier analyses, stratifying for interacting covariates and PsA status. Generalised linear mixed models assessed the impact of baseline characteristics on Psoriasis Area and Severity Index (PASI) and Dermatology Life Quality Index over time.

Results

Greater comorbidity burden, including hypertension, diabetes, obesity and depression, and greater inability to work were observed in the PsA cohort than in the psoriasis cohort. PsA (HR 1.98), female sex (HR for male sex 0.72) and depression (HR 1.21) were associated with shorter UST persistence. PsA showed a differential association with UST persistence by PASI strata and prior biologic exposure. Quality of life was negatively impacted by depression and PsA.

Conclusions

The negative impact of comorbidities on treatment persistence identified in this study emphasises the need for patient-centric, multidisciplinary care in screening for and managing comorbidities in psoriasis and PsA treatment. Psychological support and lifestyle management of modifiable risk factors, including obesity, should be considered.
Reservoir Computing for Solving Ordinary Differential Equations
Authors: Mattheakis Marios , Joy Hayden , Protopapas Pavlos
Published: January 2023

There is a wave of interest in using physics-informed neural networks for solving differential equations. Most of the existing methods are based on feed-forward networks, while recurrent neural networks solvers have not been extensively explored. We introduce a reservoir computing (RC) architecture, an echo-state recurrent neural network capable of discovering approximate solutions that satisfy ordinary differential equations (ODEs). We suggest an approach to calculate time derivatives of recurrent neural network outputs without using back-propagation. The internal weights of an RC are fixed, while only a linear output layer is trained, yielding efficient training. However, RC performance strongly depends on finding the optimal hyper-parameters, which is a computationally expensive process. We use Bayesian optimization to discover optimal sets in a high-dimensional hyper-parameter space efficiently and numerically show that one set is robust and can be transferred to solve an ODE for different initial conditions and time ranges. A closed-form formula for the optimal output weights is derived to solve first-order linear equations in a one-shot backpropagation-free learning process. We extend the RC approach by solving nonlinear systems of ODEs using a hybrid optimization method consisting of gradient descent and Bayesian optimization. Evaluation of linear and nonlinear systems of equations demonstrates the efficiency of the RC ODE solver.
The images of some simple derivations
Authors: Yan Dan
Published: January 2023

In this paper, we study the relation between the images of polynomial derivations and their simplicity. We prove that the images of simple Shamsuddin derivations are not Mathieu–Zhao spaces. In addition, we show that the images of some simple derivations in dimension three are not Mathieu-Zhao spaces. Thus, we conjecture that the images of simple derivations in dimension greater than one are not Mathieu–Zhao spaces. We also prove that locally nilpotent derivations are not simple in dimension greater than one.
Self-supervised Image-based 3D Model Retrieval
Authors: Song Dan , Zhang Chu-Meng , Zhao Xiao-Qian , Wang Teng , Nie Wei-Zhi , Li Xuan-Ya , Liu An-An
Published: January 2023

Image-based 3D model retrieval aims at organizing unlabeled 3D models according to the relevance to the labeled 2D images. With easy accessibility of 2D images and wide applications of 3D models, image-based 3D model retrieval attracts more and more attentions. However, it is still a challenging problem due to the modality gap between 2D images and 3D models. In spite of the remarkable progress brought by domain adaptation techniques for this research topic, which usually propose to align the global distribution statistics of two domains, these methods are limited in learning discriminative features for target samples due to the lack of label information in target domain. In this article, besides utilizing the label information of 2D image domain and the adversarial domain alignment, we additionally incorporate self-supervision to address cross-domain 3D model retrieval problem. Specifically, we simultaneously optimize the adversarial adaptation for both domains based on visual features and the contrastive learning for unlabeled 3D model domain to help the feature extractor to learn discriminative feature representations. The contrastive learning is used to map view representations of the identical model nearby while view representations of different models far apart. To guarantee adequate and high-quality negative samples for contrastive learning, we design a memory bank to store and update representative view for each 3D model based on entropy minimization principle. Comprehensive experimental results on the public image-based 3D model retrieval datasets, i.e., MI3DOR and MI3DOR-2, have demonstrated the effectiveness of the proposed method.
Personality Detection using Kernel-based Ensemble Model for Leveraging Social Psychology in Online Networks
Authors: Kumar Akshi , Beniwal Rohit , Jain Dipika
Published: January 2023

The Asian social networking market dominates the world landscape with the highest consumer penetration rate. Businesses and investors often look for winning strategies to attract consumers to increase revenues from sales, advertisements, and other services offered on social media platforms. Social media engagement and online relational cohesion have often been defined within the frameworks of social psychology and personality identification is a possible way in which social psychology can inform, engage, and learn from social media. Personality profiling has many real-world applications, including preference-based recommendation systems, relationship building, and career counseling. This research puts forward a novel kernel-based soft-voting ensemble model for personality detection from natural language, KBSVE-P. The KBSVE-P model is built by first evaluating the performance of various Support Vector Machine (SVM) kernels, namely radial basis function (RBF), linear, sigmoidal, and polynomial, to find the best-suited kernel for automatic personality detection in natural language text. Next, an ensemble of SVM kernels is implemented with a variety of voting techniques, such as soft voting, hard voting, and weighted hard voting. The model is evaluated on the publicly available Kaggle_MBTI dataset and a novel South Asian, Indian, low-resource Hindi language_MBTI (pronounced as vishesh charitr, meaning personality in Hindi) dataset for detecting a user's personality across four personality traits, namely introvert/extrovert (IE), thinking/feeling (TF), sensing/intuitive (SI), and judging/perceiving (JP). The proposed kernel-based ensemble with soft voting, KBSVE-P, outperforms the existing models on English Kaggle-MBTI dataset with an average F-score of 85.677 and achieves an accuracy of 66.89 for the Hindi_MBTI dataset.
Academic Freedom, Deemed Exports and International Students, Part 3
Authors: Schaefer Robert
Published: January 2023

This column addresses: 1. Smallsats; 2. Smallsats and Software Engineering; 3. Smallsats and Export restrictions
The Java Pathfinder Workshop 2022
Authors: Sherman Elena , Noller Yannic , Artho Cyrille , van Breugel Franck , Nanah Ji Anto , Kellerman John , Khazra Parssa , Kliber Filip , Kudale Gaurang , Parízek Pavel , Pasareanu Corina S. , Pressler Ron , Walker Matt , Wang Hongru , Yan Qiuchen
Published: January 2023

Java Pathfinder (JPF) was originally developed as an explicit state software model checker and subsequently evolved into an extensible Java bytecode analysis framework that has been successfully used to implement techniques such as symbolic and concolic execution, compositional verification, parallel execution, incremental program analysis, and many more. Apart from its original domain of concurrent Java programs, JPF now supports the verification of new domains such as UMLs, numeric programs, graphical user interfaces, and Android applications.
Supporting the Task-driven Skill Identification in Open Source Project Issue Tracking Systems
Authors: Santos Fabio
Published: January 2023

[Background] Selecting an appropriate task is challenging for contributors to Open Source Software (OSS), mainly for those who are contributing for the first time. Therefore, researchers and OSS projects have proposed various strategies to aid newcomers, including labeling tasks. [Aims] In this research, we investigate the automatic labeling of open issues strategy to help the contributors to pick a task to contribute. We label the issues with APIdomains- categories of APIs parsed from the source code used to solve the issues. We plan to add social network analysis metrics gathered from the issues conversations as new predictors. By identifying the skills, we claim the contributor candidates should pick a task more suitable to their skill. [Method] We are employing mixed methods. We qualitatively analyzed interview transcripts and the survey's open-ended questions to comprehend the strategies communities use to assist in onboarding contributors and contributors used to pick up an issue. We applied quantitative studies to analyze the relevance of the API-domain labels in a user experiment and compare the strategies' relative importance for diverse contributor roles. We also mined project and issue data from OSS repositories to build the ground truth and predictors able to infer the API-domain labels with comparable precision, recall, and F-measure with the state-of-art. We also plan to use a skill ontology to assist the matching process between contributors and tasks. By quantitatively analyzing the confidence level of the matching instances in ontologies describing contributors' skills and tasks, we might recommend issues for contribution. In addition, we will measure the effectiveness of the API-domain labels by evaluating the issues solving time and the rate among the labeled and unlabelled ones. [Results] So far, the results showed that organizing the issues?which includes assigning labels is seen as an essential strategy for diverse roles in OSS communities. The API-domain labels are relevant, mainly for experienced practitioners. The predicted labels have an average precision of 75.5%. [Conclusions] Labeling the issues with the API-domain labels indicates the skills involved in an issue. The labels represent possible libraries (aggregated into domains) used in the source code related to an issue. By investigating this research topic, we expect to assist the new contributors in finding a task, helping OSS communities to attract and retain more contributors.
The Use of Exploratory Software Testing in SCRUM
Authors: Neri Giulia R.
Published: January 2023

Exploratory testing is a very common, yet under researched, software testing technique. Research has shown how this technique can provide a better insight about the system under test than other techniques, that it can find defects more efficiently than other testing approaches and even aid the design of other techniques.

This research aims at increasing the understanding of exploratory testing and the way it is used within industries utilizing SCRUM. Another aim is to identify and understand the factors that enable the tester to use this technique successfully. The decision to set the study in SCRUM comes from the fact that this Agile management framework is the most popular in industry and from the suggestion to focus on the relationship between Agile and exploratory testing. Also, the choice of a specific context adds significance to the findings.

This research will be conducted in a Sheffield based company, which produces data analytics software. The methodology will consist of three phases. During Phase 1 (Identification), SCRUM practitioners will be interviewed about the use of exploratory testing in SCRUM and the success factors of this technique. The aim of Phase 2 (Confirmation) will be to confirm the findings from Phase 1.

This will be accomplished with focus groups and widely-distributed online survey. Finally, during Phase 3 (Verification), practitioners will take part to experiments to verify that the success factors identified during the first two phases enable efficient and effective exploratory testing.

The purpose of this research is to enrich the academic field of software verification and validation, but also to provide industries utilising SCRUM with useful guidance.
Summary of the Tenth International Workshop on EyeMovements in Programming (EMIP 2022)
Authors: Al Madi Naser , Busjahn Teresa , Sharif Bonita
Published: January 2023

The study of eye movements in programming has many implications to software engineering and computing education in industry and academia. The 10th International Workshop on Eye Movements in Programming (EMIP 2022) was co-located with the 44th International Conference on Software Engineering (ICSE), with the goal to further develop the methodology of using eye tracking for programming and software engineering, both theoretically and in practice.
MSR4P&S 2022 Workshop Summary
Authors: Vidoni Melina , Díaz Ferreyra Nicolás E. , Codabux Zadia
Published: January 2023

The 1st edition of the workshop on Mining Software Repositories for Privacy and Security (MSR4P&S 2022) was held virtually on November 18th, 2022, co-located with the 30th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022), which took place in Singapore. MSR4P&S received a total of five submissions from diverse geographic locations, which were all included in the program after a rigorous peer-review process. The program also featured a keynote by M. Ali Babar on the quality of data mined for security research. This report summarises the event and insights stemming from the keynote and presentations in the workshop's two sessions.
Multi-task Label-wise Transformer for Chinese Named Entity Recognition
Authors: Wang Xuelei , Xu Xirong , Huang Degen , Zhang Ting
Published: January 2023

Benefiting from the improvement of positional encoding and the introduction of lexical knowledge, Transformer has achieved superior performance than the prevailing BiLSTM-based models in named entity recognition (NER) task. However, existing Transformer-based models for Chinese NER pay less attention to the information captured by the bottom layers of Transformer and the significance of representation subspace where each head of Transformer is projected. In this article, we propose
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ransformer (MTLWT). From a global perspective, we assign entity boundary prediction (EBP) and entity type prediction (ETP) tasks to the first two layers. In this way, we stimulate lower layers to participate more in constructing character representation. Besides, in each multi-head self-attention (MHSA) layer, we provide a specific focus for each individual head, making the head project into a significant subspace. Experiments on four datasets from different domains show that our proposed model achieves comparable performance with other state-of-the-art models. In particular, MTLWT outperforms the other frameworks without external knowledge on all the datasets.
I Depended on You and You Broke Me: An Empirical Study of Manifesting Breaking Changes in Client Packages
Authors: Venturini Daniel , Cogo Filipe Roseiro , Polato Ivanilton , Gerosa Marco A. , Wiese Igor Scaliante
Published: January 2023

Complex software systems have a network of dependencies. Developers often configure package managers (e.g.,
npm
) to automatically update dependencies with each publication of new releases containing bug fixes and new features. When a dependency release introduces backward-incompatible changes, commonly known as
breaking changes
, dependent packages may not build anymore. This may indirectly impact downstream packages, but the impact of breaking changes and how dependent packages recover from these breaking changes remain unclear. To close this gap, we investigated the manifestation of breaking changes in the
npm
ecosystem, focusing on cases where packages’ builds are impacted by breaking changes from their dependencies. We measured the extent to which breaking changes affect dependent packages. Our analyses show that around 12% of the dependent packages and 14% of their releases were impacted by a breaking change during updates of non-major releases of their dependencies. We observed that, from all of the manifesting breaking changes, 44% were introduced in both minor and patch releases, which in principle should be backward compatible. Clients recovered themselves from these breaking changes in half of the cases, most frequently by upgrading or downgrading the provider’s version without changing the versioning configuration in the package manager. We expect that these results help developers understand the potential impact of such changes and recover from them.
Performance and Usability Evaluation of Brainwave Authentication Techniques with Consumer Devices
Authors: Arias-Cabarcos Patricia , Fallahi Matin , Habrich Thilo , Schulze Karen , Becker Christian , Strufe Thorsten
Published: January 2023

Brainwaves have demonstrated to be unique enough across individuals to be useful as biometrics. They also provide promising advantages over traditional means of authentication, such as resistance to external observability, revocability, and intrinsic liveness detection. However, most of the research so far has been conducted with expensive, bulky, medical-grade helmets, which offer limited applicability for everyday usage. With the aim to bring brainwave authentication and its benefits closer to real world deployment, we investigate brain biometrics with consumer devices. We conduct a comprehensive measurement experiment and user study that compare five authentication tasks on a user sample up to 10 times larger than those from previous studies, introducing three novel techniques based on cognitive semantic processing. Furthermore, we apply our analysis on high-quality open brainwave data obtained with a medical-grade headset, to assess the differences. We investigate both the performance, security, and usability of the different options and use this evidence to elicit design and research recommendations. Our results show that it is possible to achieve Equal Error Rates as low as 7.2% (a reduction between 68–72% with respect to existing approaches) based on brain responses to images with current inexpensive technology. We show that the common practice of testing authentication systems only with known attacker data is unrealistic and may lead to overly optimistic evaluations. With regard to adoption, users call for simpler devices, faster authentication, and better privacy.
Ransomware as a Predator: Modelling the Systemic Risk to Prey
Authors: Axon Louise , Erola Arnau , Agrafiotis Ioannis , Uuganbayar Ganbayar , Goldsmith Michael , Creese Sadie
Published: January 2023

The accelerated pace with which companies, governments, and institutions embrace digital transformation is creating opportunities for economic prosperity, but also increases the threat landscape. Recent orchestrated cyber-attacks have revealed the unpredictability of the harm they can cause in our society, rendering the creation of new models that capture systemic risk more critical than ever. In this article, we model the behaviour of one of the most prominent cyber-attacks: ransomware; in particular, ransomware that propagates between organisations via the Internet. We draw concepts from epidemiological models of viral propagation to reason about policies that can reduce the systemic cyber-risk to the community. To achieve this, we present a compartment-based epidemiological model of predator-prey interactions and run simulations to validate the importance of defensive controls that reduce the propagation of ransomware. Our model suggests that with specific defensive controls in place, other response policies may also become more effective. A prey policy to not pay the ransom may improve the ability of the victim population to recover; while information-sharing may reduce the number of organisations compromised if certain conditions on the speed of threat-intelligence sharing practices are met. These results indicate the validity of the approach, which we believe could be extended to explore the impacts of a broad range of attacker and defender behaviours and characteristics of the digital environment on systemic risk.
Into the Unknown: Exploration of Search Engines’ Responses to Users with Depression and Anxiety
Authors: Milton Ashlee , Pera Maria Soledad
Published: January 2023

Researchers worldwide have explored the behavioral nuances that emerge from interactions of individuals afflicted by mental health disorders (MHD) with persuasive technologies, mainly social media. Yet, there is a gap in the analysis pertaining to a persuasive technology that is part of their everyday lives: web search engines (SE). Each day, users with MHD embark on information seeking journeys using popular SE, like Google or Bing. Every step of the search process for better or worse has the potential to influence a searcher’s mindset. In this work, we empirically investigate what subliminal stimulus SE present to these vulnerable individuals during their searches. For this, we use synthetic queries to produce associated query suggestions and search engine results pages. Then we infer the subliminal stimulus present in text from SE, i.e., query suggestions, snippets, and web resources. Findings from our empirical analysis reveal that the subliminal stimulus displayed by SE at different stages of the information seeking process differ between MHD searchers and our control group composed of “average” SE users. Outcomes from this work showcase open problems related to query suggestions, search engine result pages, and ranking that the information retrieval community needs to address so that SE can better support individuals with MHD.
Acute and Subacute Toxicity of Rhamnus prinoides Leaves on Histopathology of Liver, Kidney, and Brain Tissues, and Biochemical Profile of Rats
Authors: Abebe Melese Shenkut
Published: January 2023

Rhamnus prinoides is used as a traditional medicinal plant to treat pneumonia, sprain, gonorrhea, rheumatism, and ringworm infections as well as for the preparation of local beverages in Ethiopia. It has a widespread antioxidant, antimalarial, antimicrobial, wound healing, and anti-inflammatory activities. These activities are due to the presence of alkaloids, steroids, triterpenes, tannins, flavonoids, flavones, phenols, and glycosides. This study aimed to investigate acute and subacute toxicity of R. prinoides leaves on histopathology of the liver, kidney, and brain tissues, and biochemical profiles of rats. For the acute toxicity study, female rats were treated with R. prinoides at a dose of 5000 mg/kg body weight and followed-up for 14 days. In the subacute toxicity study, four groups of rats were used. The first three groups, respectively, received 250, 500, and 1000 mg/kg body weight of R. prinoides extract and the fourth group was a control group. Signs of toxicity, food intake, and weight was recorded. At necropsy, organ weight measurement and macroscopic and microscopic evaluations of the liver, kidney, and brain were carried out. Different clinical chemistry profiles of rats were also measured. Single-dose oral administration of R. prinoides extract at 5000 mg/kg produced no mortality indicating the LD50 is greater than 5000 mg/kg body weight. A four week administration of R. prinoides extract did not bring deleterious outcomes on the food consumption and weight gain of rats. Moreover, gross examination, histopathological evaluation, and weight measurement conducted on the liver, kidney, and brain did not reveal treatment related changes. The biochemical analysis showed no significant difference between the treatment and control groups. Consumption of R. prinoides leaf for 4 weeks might not have a toxic effect in rats. However, further investigations upon long-term administration should be conducted to have a wider safety margin.