Miracle-dz/UniFAR-FTUs huggingface dataset:
Sociodemographic and psychological determinants of influenza vaccine intention among recipients of autologous and allogeneic haematopoietic stem cell transplant: a cross-sectional survey of UK transplant recipients using a modified health belief model

Objectives Studies exploring vaccination rates among haematopoietic stem cell transplant (HSCT) recipients have focused on physician factors that limit uptake. Understanding the patient factors that determine vaccination intention is crucial to delivering a successful vaccination programme. Using a modified health belief model (mHBM), we conducted a cross-sectional survey with the objective of exploring the sociodemographic and psychological factors that determined autologous and allogeneic HSCT recipients’ intention to receive the seasonal inactivated influenza vaccine (SIIV) during the 2015–2016 influenza season. Setting The setting of our study was three tertiary level, UK National Health Service (NHS) autologous and allogeneic HSCT centres. Participants Eligible patients were aged 16 years or over and recipients of autologous or allogeneic HSCT for any disease indication, with no absolute contraindication to receiving the SIIV during the next influenza season, and having not received the SIIV since transplant. 93 participants from 3 UK NHS HSCT centres completed an anonymous study-specific questionnaire. 78.5% were recipients of allogeneic and 21.5% autologous HSCT. Results 23.7% of participants expressed low intent to receive the SIIV. Patients aged over 65 (OR 0.02, 95% CI 0.01 to 0.57, p=0.02) and those who had not received the SIIV prior to HSCT (OR 0.04, 95% CI 0.02 to 0.56, p=0.02) were less likely to have high intent. A multivariate logistic regression model incorporating constructs of the mHBM was statistically significant (p<0.001) and explained 74.7% of variation in SIIV intention. More patients felt that a recommendation from their HSCT team than their general practitioner would prompt them to receive the SIIV, and this was most pronounced in those who had low intent. Conclusions The mHBM may provide a useful structure for addressing low vaccine intent among HSCT recipients and further interventional studies are warranted. We would encourage HSCT and general practitioners to discuss SIIV intention as a routine part of care.
APOBEC3B gene expression as a novel predictive factor for pathological complete response to neoadjuvant chemotherapy in breast cancer

Background Apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3B (APOBEC3B) is a gene editing enzyme with cytidine deaminase activity and high expression of its mRNA in breast tumors have been shown to be associated with progressive cases and poor prognosis. In this study, we aimed to examine the relationship between the expression of APOBEC3B and the effect of neoadjuvant chemotherapy (NAC) using pretreatment biopsy tissue, and examined whether the expression of APOBEC3B influenced chemotherapy efficacy. Methods We retrospectively selected a total of 274 patients with primary breast cancer who received NAC in more than 4 courses and underwent surgery at our institute. We assessed the expression of APOBEC3B mRNA using pretreatment biopsy specimens of NAC by quantitative real-time PCR (qRT-PCR) and examined the relationship between APOBEC3B mRNA expression and sensitivity to chemotherapy using pathological complete response (pCR) as an indicator. Further, we assessed the prognostic value of APOBEC3B in the patients receiving NAC. Results APOBEC3B mRNA expression levels were successfully assessed in 173 (63.1%) of the 274 specimens. The total pCR rate was 36.4% (n = 63). An association between APOBEC3B expression levels and pCR was observed (Wilcoxon test, P ≤ 0.0001). The patients were divided into two groups, low (n = 66) and high (n = 107), according to the APOBEC3B expression levels, using the cut-off value calculated by the receiver operating characteristics (ROC) curve for pCR. The rate of pCR was significantly higher among the patients in the high group than among those in the low group (47.7% vs 18.2%, P ≤ 0.0001). High APOBEC3B expression was significantly associated with high nuclear grade (P = 0.0078), high Ki-67 labeling index (P = 0.0087), estrogen receptor (ER) negativity (P ≤ 0.0001) and human epidermal growth factor receptor 2 (HER2) negativity (P = 0.032). Tumor size (P = 0.011), ER (P ≤ 0.0001), HER2 (P = 0.0013) and APOBEC3B expression (P = 0.037) were independent predictive factors for pCR in multivariate analysis. However, there was no association between APOBEC3B expression and prognosis. Conclusions Our study showed that APOBEC3B mRNA expression correlated with sensitivity to NAC in breast cancer patients. In contrast to previous studies, APOBEC3B mRNA expression was not associated with breast cancer prognosis in patients receiving NAC.
The intuitionistic temporal logic of dynamical systems

A dynamical system is a pair $(X,f)$, where $X$ is a topological space and $f\colon X\to X$ is continuous. Kremer observed that the language of propositional linear temporal logic can be interpreted over the class of dynamical systems, giving rise to a natural intuitionistic temporal logic. We introduce a variant of Kremer's logic, which we denote ${\sf ITL^c}$, and show that it is decidable. We also show that minimality and Poincare recurrence are both expressible in the language of ${\sf ITL^c}$, thus providing a decidable logic expressive enough to reason about non-trivial asymptotic behavior in dynamical systems.
CFIXX: Object Type Integrity for C++

—C++ relies on object type information for dynamic dispatch and casting. The association of type information to an object is implemented via the virtual table pointer, which is stored in the object itself. As C++ has neither memory nor type safety, adversaries may therefore overwrite an object’s type. If the corrupted type is used for dynamic dispatch, the attacker has hijacked the application’s control ﬂow. This vulnerability is widespread and commonly exploited. Firefox, Chrome, and other major C++ applications are network facing, commonly attacked, and make signiﬁcant use of dynamic dispatch. Control-Flow Integrity (CFI) is the state of the art policy for efﬁcient mitigation of control-ﬂow hijacking attacks. CFI mechanisms determine statically (i.e., at compile time) the set of functions that are valid at a given call site, based on C++ semantics. We propose an orthogonal policy, Object Type Integrity (OTI), that dynamically tracks object types. Consequently, instead of allowing a set of targets for each dynamic dispatch on an object, only the single, correct target for the object’s type is allowed. To show the efﬁcacy of OTI, we present CFIXX, which enforces OTI. CFIXX enforces OTI by dynamically tracking the type of each object and enforcing its integrity against arbitrary writes. CFIXX has minimal overhead on CPU bound applications such as SPEC CPU2006 — 4.98%. On key applications like Chromium, CFIXX has negligible overhead on JavaScript benchmarks: 2.03% on Octane, 1.99% on Kraken, and 2.80% on JetStream. We show that CFIXX can be deployed in conjunction with CFI, providing a signiﬁcant security improvement.
Using Social Cognitive Career Theory to Understand Why Students Choose to Study Computer Science

The aim of this research is to use Social Cognitive Career Theory (SCCT) to identify and understand reasons why students choose to study Computer Science (CS) at university. SCCT focuses on students' prior experience, social support, self-efficacy and outcome expectation. The research is partly motivated by the desire to increase female participation rates in CS, particularly in the UK. Policymakers can use the factors that both females and males identify as influencing their choice of studying CS to enhance the experiences of all students prior to coming to university, but female students in particular. The study uses a semi-structured interview with 17 mixed gender subjects currently studying CS at three Scottish universities. The findings are that social support from family, teachers, friends and mentors is a particularly important factor in choosing to study CS, especially for female subjects. The career paths offered by a CS degree is another major factor, not just the potential jobs, but also the general value of a CS education and the potential to make useful contributions to society. School education appeared to have limited influence, though exposure to problem solving, programming, online self-learning and internships are positive influences. The stereotypical view of CS students as 'geeks' is outdated and unhelpful - it is more appropriate to see them as 'analytical' or 'over-achievers'. Subjects make many suggestions for improving the CS education provided at school, especially to make it more attractive to females, including: make it compulsory, teach it earlier, include more programming and problem solving, and increase the visibility of female exemplars and role models.
Parents Matter: Associations of Parental BMI and Feeding Behaviors With Child BMI in Brazilian Preschool and School-Aged Children

Background: Brazil is undergoing nutritional transition and rates of obesity in preschool and school-aged children are increasing. Excess weight in the first years of life could predict excess weight in adulthood, making it essential to study risk factors in this population. Objective: Our goal was to investigate associations of parent feeding behaviors, as well as more distal familial influences including family SES and maternal and paternal weight, with BMI z-score in preschool and school-aged children in a Brazilian sample. Methods: Cross-sectional study. Data were collected in 14 Brazilian private schools. Parents of children aged 2–8 years (n = 1,071) completed a questionnaire assessing parent feeding behaviors, as well as sociodemographic and anthropometric information. Hierarchical linear regression models were fitted to investigate relationships between parent and child characteristics and child BMI z-score in preschool (2–5 years, n = 397) and school-aged (6–8 years, n = 618) children. Results: Final models indicated that higher maternal BMI and “restriction for weight control” were associated with higher child BMI z-score in both age groups (excessive weight, i.e., BMI ≥ +1 z-score, in preschoolers and school-aged children: 24.4 and 35.9%, respectively). In preschoolers only, “healthy eating guidance” and “pressure” were associated with lower child BMI z-score. For school-aged children, male sex, higher father BMI, and “restriction for health” were associated with higher child BMI z-score. Conclusions: Parent feeding behaviors and parent weight, as well as child sex, are associated with child BMI z-score, with evidence for differential relationships in preschool and school-aged children. Optimal obesity prevention and treatment strategies may differ by child age.
Complication and Failures of Central Vascular Access Device in Adult Critical Care Settings*

Objectives: To examine the proportion and rate of central venous access device failure and complications across central venous access device types in adult intensive care. Data Sources: A systematic search was undertaken in the electronic databases Cochrane Central Register of Controlled Trials, Embase, U.S. National Library of Medicine National Institutes of Health, and Cumulative Index to Nursing and Allied Health in September 2017. Study Selection: Included studies were of observational (prospective and retrospective) or interventional design and reported central venous access device failure and complications in adult ICU settings. Studies were excluded if they were published prior to November 2006 or not reported in English. Two reviewers independently screened articles, assessed eligibility, extracted data, and assessed risk of bias. Data Extraction: Data were extracted on the primary outcome, central venous access device failure, and secondary outcomes: central venous access device complications (central line-associated bloodstream infection, catheter-related bloodstream infection, catheter-related thrombosis, occlusion, catheter removal due to suspected infection, dislodgement, breakage, and local infection). Patient and device data and study details to assess the study quality were also extracted. Data Synthesis: A total of 63 studies involving 50,000 central venous access devices (396,951 catheter days) were included. Central venous access device failure was 5% (95% CI, 3–6%), with the highest rates and proportion of failure in hemodialysis catheters. Overall central line-associated bloodstream infection rate was 4.59 per 1,000 catheter days (95% CI, 2.31–6.86), with the highest rate in nontunneled central venous access devices. Removal of central venous access device due to suspected infection was high (17%; 20.4 per 1,000 catheter days; 95% CI, 15.7–25.2). Conclusions: Central venous access device complications and device failure is a prevalent and significant problem in the adult ICU, leading to substantial patient harm and increased healthcare costs. The high proportion of central venous access devices removed due to suspicion of infection, despite low overall central line-associated bloodstream infection and catheter-related bloodstream infection rates, indicates a need for robust practice guidelines to inform decision-making surrounding removal of central venous access devices suspected of infection.
The Feasibility and Effectiveness of PASS Plus, A Lay Health Worker Delivered Comprehensive Intervention for Autism Spectrum Disorders: Pilot RCT in a Rural Low and Middle Income Country Setting

The treatment gap for autism globally is high. Our previous PASS intervention, delivered by community based lay health workers, showed effectiveness. This article reports the development and evaluation of a new “PASS ‘Plus’” intervention in a rural population in India. Using formative research methods, we supplemented the PASS intervention with additional (Plus) modules to address autism comorbidities. This is the first time that a rigorous methodology has been used to evaluate autism symptom outcomes in a low and middle‐income country setting. 40 parent–child dyads were recruited in a pilot randomized controlled trial against usual care (mean age 65 months (34 boys); n = 19 PASS Plus, n = 21 UC). 89% of intervention families partially or entirely completed the 12‐session intervention. Intention to treat analysis showed a reduction in mean scores of autism symptom severity, though the confidence interval contains zero, (adjusted mean difference AMD −2.42 95% CI −7.75, 2.92; ES 0.22); large treatment effects on proximal outcomes of proportion of parent synchronous responses (AMD 0.35; 95% CI 0.18, 0.52; effect size ES 3.97) and proportion of child communication initiations with parent (AMD 0·17; 95% CI 0.03, 0.32; ES 1.02). Confidence intervals for effects on mutual shared attention (AMD 0.10; 95% CI −0.07, 0.27; ES 0.5) and co‐morbid symptoms (AMD −9.0; 95% CI −24.26, 6.26; ES 0.32) contained zero. There were significant effects to improve parental mental health. PASS Plus shows good feasibility and adds to the evidence of the effectiveness of task sharing complex autism interventions to lay health workers in India. Autism Res 2019, 12: 328–339 © 2018 International Society for Autism Research, Wiley Periodicals, Inc.
Children's eye‐fixations on google search results

We investigate how children in grades 6 and 8 (ages 11 and 13, respectively) read search engine results pages (SERPs) in the context of searching Google. We use eye‐tracking to detect children's reading of SERPs, and the effect of grade level and task type on reading behaviors and interactions. We have created a web search interface that retrieved data in the background from Google search engine. Preliminary findings show a significant difference in the number of reading fixations by grade level. Grade level or age had a more significant effect on reading behaviors, fixations, first result rank, and interactions with SERPs than task type. Findings and future work are discussed.
Relationship Between Platelet Count and Insulin Resistance in Korean Adolescents: A Nationwide Population-Based Study.

BACKGROUND To examine the relationship between platelet count and insulin resistance, as measured by a homeostasis model assessment of insulin resistance (HOMA-IR), in a nationally representative sample of Korean adolescents. METHODS The study population comprised 1133 participants (636 male and 497 female participants) aged 12-18 years selected from the 2008-2010 Korea National Health and Nutrition Examination Survey. Insulin resistance was defined as a HOMA-IR value greater than the 85th percentile. The odds ratios (ORs) and 95% confidence intervals (95% CIs) for insulin resistance were calculated using multiple logistic regression analysis. RESULTS The mean values of insulin and HOMA-IR increased proportionally with platelet count quartiles for all, male, and female participants. The prevalence of insulin resistance increased significantly with an increase in platelet count quartiles in all, male, and female participants. Compared with the ORs for individuals in the lowest platelet count quartile, the ORs (95% CIs) for insulin resistance in individuals in the highest quartile was 2.90 (1.39-6.07) for all, 2.98 (1.14-8.31) for male, and 2.14 (0.88-5.32) for female participants, after adjusting for age, gender (for all participants), household income, residential area, family history of diabetes mellitus, and overweight [85th percentile ≤ body mass index (BMI) <95th percentiles for age and gender] or obesity (BMI ≥95th percentile). CONCLUSION Platelet count was positively associated with insulin resistance in Korean adolescents. These findings suggest that platelet count could be a useful indicator for identifying adolescents with insulin resistance.
On Feature Selection and Evaluation of Transportation Mode Prediction Strategies

Transportation modes prediction is a fundamental task for decision making in smart cities and traffic management systems. Traffic policies designed based on trajectory mining can save money and time for authorities and the public. It may reduce the fuel consumption and commute time and moreover, may provide more pleasant moments for residents and tourists. Since the number of features that may be used to predict a user transportation mode can be substantial, finding a subset of features that maximizes a performance measure is worth investigating. In this work, we explore wrapper and information retrieval methods to find the best subset of trajectory features. After finding the best classifier and the best feature subset, our results were compared with two related papers that applied deep learning methods and the results showed that our framework achieved better performance. Furthermore, two types of cross-validation approaches were investigated, and the performance results show that the random cross-validation method provides optimistic results.
Effectiveness of an Exercise-Based Active Rehabilitation Intervention for Youth Who Are Slow to Recover After Concussion.

OBJECTIVE (1) To determine the impact of providing participants aged 8 to 17 years who are slow to recover after a concussion with a well-developed active rehabilitation intervention (ARI), compared with receiving standard care alone, on postconcussion symptoms (PCS) at 2 and 6 weeks after the initiation of ARI; and (2) to investigate functional recovery 6 weeks after initiation of ARI. DESIGN A multicenter prospective quasi-experimental control group design. SETTING Tertiary care pediatric trauma center and community health care providers. PARTICIPANTS Forty-nine youth were enrolled (experimental n = 36; control n = 13). PROCEDURES Participants were assessed on 3 different occasions: (1) initial visit (baseline); (2) 2 weeks; and (3) 6 weeks after enrollment. MAIN OUTCOME MEASURES Child- and parent-reported PCS were obtained by the PCS Inventory Scale (primary outcome). Secondary outcomes included: (1) mood and anxiety; (2) quality of life; (3) energy level; (4) coordination and balance; (5) neurocognition; (6) parental anxiety; and (7) satisfaction with intervention. RESULTS Both groups reported decrease of PCS over time (child: P = 0.01; parent: P = 0.03). Children in the experimental group presented higher quality of life (P = 0.04) and less anger (P = 0.02). A trend toward significance was observed for better tandem gait (P = 0.07) and for less general fatigue on self-reported PCS (P = 0.09) in the experimental group. CONCLUSIONS Active rehabilitation intervention does not affect the PCS beyond the usual management, but it increases their quality of life, decreases anger, and potentially increases energy level and balance.
Opioid Use Disorder Documented at Delivery Hospitalization — United States, 1999–2014

Opioid use by pregnant women represents a significant public health concern given the association of opioid exposure and adverse maternal and neonatal outcomes, including preterm labor, stillbirth, neonatal abstinence syndrome, and maternal mortality (1,2). State-level actions are critical to curbing the opioid epidemic through programs and policies to reduce use of prescription opioids and illegal opioids including heroin and illicitly manufactured fentanyl, both of which contribute to the epidemic (3). Hospital discharge data from the 1999–2014 Healthcare Cost and Utilization Project (HCUP) were analyzed to describe U.S. national and state-specific trends in opioid use disorder documented at delivery hospitalization. Nationally, the prevalence of opioid use disorder more than quadrupled during 1999–2014 (from 1.5 per 1,000 delivery hospitalizations to 6.5; p<0.05). Increasing trends over time were observed in all 28 states with available data (p<0.05). In 2014, prevalence ranged from 0.7 in the District of Columbia (DC) to 48.6 in Vermont. Continued national, state, and provider efforts to prevent, monitor, and treat opioid use disorder among reproductive-aged and pregnant women are needed. Efforts might include improved access to data in Prescription Drug Monitoring Programs, increased substance abuse screening, use of medication-assisted therapy, and substance abuse treatment referrals.
Exploiting Effective Representations for Chinese Sentiment Analysis Using a Multi-Channel Convolutional Neural Network

Effective representation of a text is critical for various natural language processing tasks. For the particular task of Chinese sentiment analysis, it is important to understand and choose an effective representation of a text from different forms of Chinese representations such as word, character and pinyin. This paper presents a systematic study of the effect of these representations for Chinese sentiment analysis by proposing a multi-channel convolutional neural network (MCCNN), where each channel corresponds to a representation. Experimental results show that: (1) Word wins on the dataset of low OOV rate while character wins otherwise; (2) Using these representations in combination generally improves the performance; (3) The representations based on MCCNN outperform conventional ngram features using SVM; (4) The proposed MCCNN model achieves the competitive performance against the state-of-the-art model fastText for Chinese sentiment analysis.