873 research outputs found
Screening and diagnostic assessment of neurodevelopmental disorders in a male prison
Purpose
The purpose of this paper is to identify neurodevelopmental disorders and difficulties (NDD) in a male prison. The study used standardised tools to carry out screening and diagnostic assessment of the attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and intellectual disability (ID).
Design/methodology/approach
The ADHD self-report scale, 20-item autism quotient and the Learning Disability Screening Questionnaire were used to screen 240 male prisoners. Prisoners who screened positive on one or more of these scales or self-reported a diagnosis of ADHD, ASD or ID were further assessed using the diagnostic interview for ADHD in adults, adapted Autism Diagnostic Observation Schedule and the Quick Test.
Findings
Of the 87 prisoners who screened positive for NDD and were further assessed, 70 met the study’s diagnostic criteria for ADHD, ASD or ID. Most of those with NDD (51 per cent) had previously gone unrecognised and a high proportion (51 per cent) were identified through staff- or self-referral to the study.
Originality/value
The study demonstrated that improving awareness and providing access to skilled, standardised assessment within a male prison can result in increased recognition and identification of NDD
Constructing Artificial Data for Fine-Tuning for Low-Resource Biomedical Text Tagging with Applications in PICO Annotation
Biomedical text tagging systems are plagued by the dearth of labeled training data. There have been recent attempts at using pre-trained encoders to deal with this issue. Pre-trained encoder provides representation of the input text which is then fed to task-specific layers for classification. The entire network is fine-tuned on the labeled data from the target task. Unfortunately, a low-resource biomedical task often has too few labeled instances for satisfactory fine-tuning. Also, if the label space is large, it contains few or no labeled instances for majority of the labels. Most biomedical tagging systems treat labels as indexes, ignoring the fact that these labels are often concepts expressed in natural language e.g. ‘Appearance of lesion on brain imaging’. To address these issues, we propose constructing extra labeled instances using label-text (i.e. label’s name) as input for the corresponding label-index (i.e. label’s index). In fact, we propose a number of strategies for manufacturing multiple artificial labeled instances from a single label. The network is then fine-tuned on a combination of real and these newly constructed artificial labeled instances. We evaluate the proposed approach on an important low-resource biomedical task called PICO annotation, which requires tagging raw text describing clinical trials with labels corresponding to different aspects of the trial i.e. PICO (Population, Intervention/Control, Outcome) characteristics of the trial. Our empirical results show that the proposed method achieves a new state-of-the-art performance for PICO annotation with very significant improvements over competitive baselines
Trade-offs in managing commercial consumer returns for online apparel retail
Purpose: This paper analyses the application of Lean Six Sigma framework for supporting continuous improvement in logistics services. Both the lean philosophy and the Six Sigma methodology have become two of the most important initiatives for continuous improvement in organizations. The combination of both alternatives - Lean Six Sigma (LSS) - brings significant benefits for companies applying this method and its influence in logistics services can be relevant. Design/methodology/approach: A case study on the logistics services of a large consumer electronics company is performed. In this sector, high quality in logistics services is crucial. Using within-case and cross-case analyses, the paper discusses the implementation of LSS in two internal logistics processes. Findings: The paper identifies important implementation aspects when applying LSS to logistics services, such as continuous improvement structure, strategic analysis, cross-functional teams, and process management. Furthermore, the paper discusses the potential in logistics services of the DMAIC approach and tools like VSM, SIPOC and Process Mapping. Practical implications: The paper analyses two logistics processes where LSS has been applied – a payment process and a request-to-ship process. The analysis of both processes offers relevant information about organizational implementation in a logistics services environment, about process improvement and about the use of LSS tools. Originality/value: Firstly, this paper addresses the gap in literature about LSS and logistics’ activities. Furthermore, the case company, with more than 9.000 employees and distributing its products to more than 100 countries, constitutes a valuable source of information to obtain insights in the implications of implementing LSS in logistics services
CFD Simulation of He/CH4 Separation by Hyflon AD60X Membrane
In this research, the membrane separation process was used to separate helium from methane gas. In order to do this, computational fluid dynamics (CFD) was used, and the effect of process parameters on the performance of the membrane separation process was studied by this method. To simulate the hydrodynamics of flow in the channel, the Navier-Stokes equation was used, and the Maxwell-Stefan equation was applied to simulate the mass transfer phenomenon. In addition, Fick’s law was utilized to simulate mass transfer in the membrane domain. The impacts of significant parameters such as feed pressure, feed flow rate, and feed concentration on parameters such as He/CH4 separation factor, methane and helium membrane flux and helium mole fraction in permeate stream were studied. The results of the simulation indicated that the feed pressure of 10 bar, feed flow rate of 120 cm3 min–1, and feed mole fraction of 0.0254 had the best membrane performance in He/CH4
separation.
This work is licensed under a Creative Commons Attribution 4.0 International License
Quality management in heavy duty manufacturing industry: TQM vs. Six Sigma
‘Is TQM a management fad?’ This question has been extensively documented in the quality management literature; and will be tackled in this research though a critical literature review on the area. ‘TQM versus Six-Sigma’ debate, which has also been a fundamental challenge in this research filed, is addressed by a thematic and chronological review on the peer papers. To evaluate this challenge in practice, a primary research in heavy duty machinery production industry have been conducted using a case-study on, J C Bamford Excavators Ltd (JCB), the largest European construction machinery producer. The result highlights that TQM is a natural foundation to build up Six-Sigma upon; and not surprisingly the quality yield in a TQM approach complemented by Six-sigma is far higher and more stable than when TQM with no Six-Sigma focus is being put in place; thus presenting the overall finding that TQM and Six Sigma are compliments, not substitutes. The study will be concluded with an overview on quality management approaches in the heavy duty manufacturing industry to highlight the way forward for the industry
A robust fuzzy mathematical programming model for the closed-loop supply chain network design and a whale optimization solution algorithm
The closed-loop supply chain (CLSC) management as one of the most significant management issues has been increasingly spotlighted by the government, companies and customers, over the past years. The primary reasons for this growing attention mainly down to the governments-driven and environmental-related regulations which has caused the overall supply cost to reduce while enhancing the customer satisfaction. Thereby, in the present study, efforts have been made to propose a facility location/allocation model for a multi-echelon multi-product multi-period CLSC network under shortage, uncertainty, and discount on the purchase of raw materials. To design the network, a mixed-integer nonlinear programming (MINLP) model capable of reducing total costs of network is proposed. Moreover, the model is developed using a robust fuzzy programming (RFP) to investigate the effects of uncertainty parameters including customer demand, fraction of returned products, transportation costs, the price of raw materials, and shortage costs. As the developed model was NP-hard, a novel whale optimization algorithm (WOA) aimed at minimizing the network total costs with application of a modified priority-based encoding procedure is proposed. To validate the model and effectiveness of the proposed algorithm, some quantitative experiments were designed and solved by an optimization solver package and the proposed algorithm. Comparison of the outcomes provided by the proposed algorithm and exact solution is indicative of high quality performance of the applied algorithm to find a near-optimal solution within the reasonable computational time
A Quantitative, High-Throughput Reverse Genetic Screen Reveals Novel Connections between Pre–mRNA Splicing and 5′ and 3′ End Transcript Determinants
Here we present the development and implementation of a genome-wide reverse genetic screen in the budding yeast, Saccharomyces cerevisiae, that couples high-throughput strain growth, robotic RNA isolation and cDNA synthesis, and quantitative PCR to allow for a robust determination of the level of nearly any cellular RNA in the background of 5,500 different mutants. As an initial test of this approach, we sought to identify the full complement of factors that impact pre–mRNA splicing. Increasing lines of evidence suggest a relationship between pre–mRNA splicing and other cellular pathways including chromatin remodeling, transcription, and 3′ end processing, yet in many cases the specific proteins responsible for functionally connecting these pathways remain unclear. Moreover, it is unclear whether all pathways that are coupled to splicing have been identified. As expected, our approach sensitively detects pre–mRNA accumulation in the vast majority of strains containing mutations in known splicing factors. Remarkably, however, several additional candidates were found to cause increases in pre–mRNA levels similar to that seen for canonical splicing mutants, none of which had previously been implicated in the splicing pathway. Instead, several of these factors have been previously implicated to play roles in chromatin remodeling, 3′ end processing, and other novel categories. Further analysis of these factors using splicing-sensitive microarrays confirms that deletion of Bdf1, a factor that links transcription initiation and chromatin remodeling, leads to a global splicing defect, providing evidence for a novel connection between pre–mRNA splicing and this component of the SWR1 complex. By contrast, mutations in 3′ end processing factors such as Cft2 and Yth1 also result in pre–mRNA splicing defects, although only for a subset of transcripts, suggesting that spliceosome assembly in S. cerevisiae may more closely resemble mammalian models of exon-definition. More broadly, our work demonstrates the capacity of this approach to identify novel regulators of various cellular RNAs
177 Lu-PSMA-617 radioligand therapy of metastatic castration-resistant prostate cancer: Initial 254-patient results from a prospective registry (REALITY Study)
Purpose Preliminary data from retrospective analyses and recent data from large randomized controlled trials suggest safety
and efcacy of radioligand therapy (RLT) targeting prostate-specifc membrane antigen (PSMA) in men with metastatic
castration-resistant prostate cancer (mCRPC). Limited data on this modality have been published regarding large samples
treated in everyday practice.
Methods We analyzed prospectively collected registry data regarding lutetium-177 (177Lu)-PSMA-617 RLT of 254 consecu tive men with mCRPC seen in everyday academic practice. Since 177Lu-PSMA-617 was experimental salvage treatment
following failure of individually appropriate conventional therapies, patients were generally elderly and heavily pretreated
(median age 70 years; prior taxanes 74.0%, 188/254), with late–end-stage disease (visceral metastasis in 32.7%, 83/254).
Primary endpoints were response to RLT, defned by changes from baseline serum prostate-specifc antigen (PSA) concen tration, PSA progression-free survival (PSA-PFS), and overall survival (OS), estimated with Kaplan–Meier statistics, and
caregiver-reported and patient-reported safety. Unless noted, median (minimum–maximum) values are given.
Results Patients received 3 (1–13) 177Lu-PSMA-617 activities (6.5 [2.5–11.6] GBq/cycle) every 5.7 (3.0–11.0) weeks. Best
response was≥50% PSA reduction in 52.0% of patients (132/254). PSA-PFS was 5.5 (95% confdence interval [95%CI]
4.4–6.6) months and OS, 14.5 (95%CI 11.5–17.5) months. In multivariable Cox proportional-hazards modeling, response
to the initial≤2 RLT administrations was the strongest signifcant prognosticator related to OS (hazard ratio 3.7 [95%CI
2.5–5.5], p<0.001). No RLT-related deaths or treatment discontinuations occurred; the most frequent RLT-related Grade
3/4 adverse events were anemia (18/254 patients, 7.1%), thrombocytopenia (11/254, 4.3%), and lymphopenia (7/254, 2.8%).
RLT-related xerostomia, all grade 1/2, was noted in 53/254 (20.9%).
Conclusions In a large, prospectively observed “real-world” cohort with late-stage/end-stage mCRPC and conventional
treatment failure, 177Lu-PSMA-617 RLT was efective, safe, and well-tolerated. Early biochemical disease control by such
therapy was associated with better OS. Prospective study earlier in the disease course may be warranted
Validation of a field deployable reactor for in situ formation of NOM-engineered nanoparticle corona
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