Delaying academic tasks and feeling bad about it

Abstract. Procrastination is the irrational delay of an intended task and is common among students. A delay can only be defined as procrastination when it is voluntary, the action was intended but not implemented, and the delay is accompanied by subjective discomfort. Established scales of procrastination cover mainly behavioral aspects but have neglected the emotional aspect. This inaccuracy concerning the construct validity might entail misconceptions of procrastination. Accordingly, we developed and validated the Behavioral and Emotional Academic Procrastination Scale (BEPS), which covers all aspects of the definition of procrastination. The 6-item scale measuring self-reported academic procrastination was tested in three studies. Study 1 (N = 239) evaluated the psychometric qualities of the BEPS, indicating good item characteristics and internal consistency. Study 2 (N = 1,441) used confirmatory factor analysis and revealed two correlated factors: one covering the behavioral aspect and the other reflecting the emotional aspect. Measurement invariance was shown through longitudinal and multigroup confirmatory factor analyses. Study 3 (N = 234) provided evidence for the scale’s convergent validity through correlations with established procrastination scales, self-efficacy, and neuroticism. The BEPS thus economically operationalizes all characteristics of academic procrastination and appears to be a reliable and valid self-report measure

Graduates

https://thekeep.eiu.edu/commencement_fall2015/1029/thumbnail.jp

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

Mitochondrial genes are altered in blood early in Alzheimer's disease

Although mitochondrial dysfunction is a consistent feature of Alzheimer's disease in the brain and blood, the molecular mechanisms behind these phenomena are unknown. Here we have replicated our previous findings demonstrating reduced expression of nuclear-encoded oxidative phosphorylation (OXPHOS) subunits and subunits required for the translation of mitochondrial-encoded OXPHOS genes in blood from people with Alzheimer's disease and mild cognitive impairment. Interestingly this was accompanied by increased expression of some mitochondrial-encoded OXPHOS genes, namely those residing closest to the transcription start site of the polycistronic heavy chain mitochondrial transcript (MT-ND1, MT-ND2, MT-ATP6, MT-CO1, MT-CO2, MT-C03) and MT-ND6 transcribed from the light chain. Further we show that mitochondrial DNA copy number was unchanged suggesting no change in steady-state numbers of mitochondria. We suggest that an imbalance in nuclear and mitochondrial genome-encoded OXPHOS transcripts may drive a negative feedback loop reducing mitochondrial translation and compromising OXPHOS efficiency, which is likely to generate damaging reactive oxygen species

Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of β1 immunoglobulin binding domain of protein G (GB1)

Magic-angle spinning solid-state NMR (MAS SSNMR) represents a fast developing experimental technique with great potential to provide structural and dynamics information for proteins not amenable to other methods. However, few automated analysis tools are currently available for MAS SSNMR. We present a methodology for automating protein resonance assignments of MAS SSNMR spectral data and its application to experimental peak lists of the β1 immunoglobulin binding domain of protein G (GB1) derived from a uniformly 13C- and 15N-labeled sample. This application to the 56 amino acid GB1 produced an overall 84.1% assignment of the N, CO, CA, and CB resonances with no errors using peak lists from NCACX 3D, CANcoCA 3D, and CANCOCX 4D experiments. This proof of concept demonstrates the tractability of this problem

Assessing the pre-implementation context for financial navigation in rural and non-rural oncology clinics

BackgroundFinancial navigation (FN) is an evidence-based intervention designed to address financial toxicity for cancer patients. FN's success depends on organizations' readiness to implement and other factors that may hinder or support implementation. Tailored implementation strategies can support practice change but must be matched to the implementation context. We assessed perceptions of readiness and perceived barriers and facilitators to successful implementation among staff at nine cancer care organizations (5 rural, 4 non-rural) recruited to participate in the scale-up of a FN intervention. To understand differences in the pre-implementation context and inform modifications to implementation strategies, we compared findings between rural and non-rural organizations.MethodsWe conducted surveys (n = 78) and in-depth interviews (n = 73) with staff at each organization. We assessed perceptions of readiness using the Organizational Readiness for Implementing Change (ORIC) scale. In-depth interviews elicited perceived barriers and facilitators to implementing FN in each context. We used descriptive statistics to analyze ORIC results and deductive thematic analysis, employing a codebook guided by the Consolidated Framework for Implementation Research (CFIR), to synthesize themes in barriers and facilitators across sites, and by rurality.ResultsResults from the ORIC scale indicated strong perceptions of organizational readiness across all sites. Staff from rural areas reported greater confidence in their ability to manage the politics of change (87% rural, 76% non-rural) and in their organization's ability to support staff adjusting to the change (96% rural, 75% non-rural). Staff at both rural and non-rural sites highlighted factors reflective of the Intervention Characteristics (relative advantage) and Implementation Climate (compatibility and tension for change) domains as facilitators. Although few barriers to implementation were reported, differences arose between rural and non-rural sites in these perceived barriers, with non-rural staff more often raising concerns about resistance to change and compatibility with existing work processes and rural staff more often raising concerns about competing time demands and limited resources.ConclusionsStaff across both rural and non-rural settings identified few, but different, barriers to implementing a novel FN intervention that they perceived as important and responsive to patients' needs. These findings can inform how strategies are tailored to support FN in diverse oncology practices

Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination

Radar vision in the mapping of forest biodiversity from space

Recent progress in remote sensing provides much-needed, large-scale spatio-temporal information on habitat structures important for biodiversity conservation. Here we examine the potential of a newly launched satellite-borne radar system (Sentinel-1) to map the biodiversity of twelve taxa across five temperate forest regions in central Europe. We show that the sensitivity of radar to habitat structure is similar to that of airborne laser scanning (ALS), the current gold standard in the measurement of forest structure. Our models of different facets of biodiversity reveal that radar performs as well as ALS; median R² over twelve taxa by ALS and radar are 0.51 and 0.57 respectively for the first non-metric multidimensional scaling axes representing assemblage composition. We further demonstrate the promising predictive ability of radar-derived data with external validation based on the species composition of birds and saproxylic beetles. Establishing new area-wide biodiversity monitoring by remote sensing will require the coupling of radar data to stratified and standardized collected local species data

Effect of the COVID-19 pandemic on surgery for indeterminate thyroid nodules (THYCOVID): a retrospective, international, multicentre, cross-sectional study

Background Since its outbreak in early 2020, the COVID-19 pandemic has diverted resources from non-urgent and elective procedures, leading to diagnosis and treatment delays, with an increased number of neoplasms at advanced stages worldwide. The aims of this study were to quantify the reduction in surgical activity for indeterminate thyroid nodules during the COVID-19 pandemic; and to evaluate whether delays in surgery led to an increased occurrence of aggressive tumours.Methods In this retrospective, international, cross-sectional study, centres were invited to participate in June 22, 2022; each centre joining the study was asked to provide data from medical records on all surgical thyroidectomies consecutively performed from Jan 1, 2019, to Dec 31, 2021. Patients with indeterminate thyroid nodules were divided into three groups according to when they underwent surgery: from Jan 1, 2019, to Feb 29, 2020 (global prepandemic phase), from March 1, 2020, to May 31, 2021 (pandemic escalation phase), and from June 1 to Dec 31, 2021 (pandemic decrease phase). The main outcomes were, for each phase, the number of surgeries for indeterminate thyroid nodules, and in patients with a postoperative diagnosis of thyroid cancers, the occurrence of tumours larger than 10 mm, extrathyroidal extension, lymph node metastases, vascular invasion, distant metastases, and tumours at high risk of structural disease recurrence. Univariate analysis was used to compare the probability of aggressive thyroid features between the first and third study phases. The study was registered on ClinicalTrials.gov, NCT05178186.Findings Data from 157 centres (n=49 countries) on 87 467 patients who underwent surgery for benign and malignant thyroid disease were collected, of whom 22 974 patients (18 052 [78 center dot 6%] female patients and 4922 [21 center dot 4%] male patients) received surgery for indeterminate thyroid nodules. We observed a significant reduction in surgery for indeterminate thyroid nodules during the pandemic escalation phase (median monthly surgeries per centre, 1 center dot 4 [IQR 0 center dot 6-3 center dot 4]) compared with the prepandemic phase (2 center dot 0 [0 center dot 9-3 center dot 7]; p<0 center dot 0001) and pandemic decrease phase (2 center dot 3 [1 center dot 0-5 center dot 0]; p<0 center dot 0001). Compared with the prepandemic phase, in the pandemic decrease phase we observed an increased occurrence of thyroid tumours larger than 10 mm (2554 [69 center dot 0%] of 3704 vs 1515 [71 center dot 5%] of 2119; OR 1 center dot 1 [95% CI 1 center dot 0-1 center dot 3]; p=0 center dot 042), lymph node metastases (343 [9 center dot 3%] vs 264 [12 center dot 5%]; OR 1 center dot 4 [1 center dot 2-1 center dot 7]; p=0 center dot 0001), and tumours at high risk of structural disease recurrence (203 [5 center dot 7%] of 3584 vs 155 [7 center dot 7%] of 2006; OR 1 center dot 4 [1 center dot 1-1 center dot 7]; p=0 center dot 0039).Interpretation Our study suggests that the reduction in surgical activity for indeterminate thyroid nodules during the COVID-19 pandemic period could have led to an increased occurrence of aggressive thyroid tumours. However, other compelling hypotheses, including increased selection of patients with aggressive malignancies during this period, should be considered. We suggest that surgery for indeterminate thyroid nodules should no longer be postponed even in future instances of pandemic escalation.Funding None.Copyright (c) 2023 Published by Elsevier Ltd. All rights reserved