Bureaucratic malaises and their remedies in Public and Nonprofit Organizations

Many experts have observed that bureaucratic malaises are endemic in public sector organizations. These so-called “diseases,” which include personnel constraints, red tape and risk avoidance, can discourage workers, damage organizational performance, and lower the quality of public services. The depth and impact of these malaises are tested across the public and nonprofit sectors using data from the third National Administrative Studies Project (NASP III). NASP III surveyed randomly selected managers in public and nonprofit organizations in Georgia and Illinois. Multiple informant data are aggregated to the organizational level resulting 47 public and 64 nonprofit organizations for further analysis. Multivariate statistical analysis suggests that most of the maladies have harmful effects on work quality in the public sector, but not on the nonprofit agencies studied in this sample. The results further show that task clarity does not mitigate the performance effects of these maladies in the public sector whereas in the nonprofit sector it is associated with higher levels of performance. The implications for theory and practice are discussed.postprin

Uncovering relationships between Management Innovation and Service Innovation, time lags and performance

Conference Theme: Shaping the future: transforming public management - 'Re-invention or 'revolution'?The study focuses on public service innovation because it is a critically important area of investigation that scholars, policy makers and public administrators maintain delivers economic, political and social benefits (Borins, 1998; Tidd, Bessant and Pavitt 2009). Public organizations have put in place a range of innovative practices that bring societal benefits, but more needs to be known about public service innovation, and in particular its performance consequences (Damanpour, Walker and Avellaneda 2009; Walker and Damanpour 2008). Innovations come in different guises. In this study we focus on ...postprin

Developing an EEG-based on-line closed-loop lapse detection and mitigation system

© 2014 Wang, Huang, Wei, Huang, Ko, Lin, Cheng and Jung. In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments

Age-related human small intestine methylation: evidence for stem cell niches

BACKGROUND: The small intestine is constructed of many crypts and villi, and mouse studies suggest that each crypt contains multiple stem cells. Very little is known about human small intestines because mouse fate mapping strategies are impractical in humans. However, it is theoretically possible that stem cell histories are inherently written within their genomes. Genomes appear to record histories (as exemplified by use of molecular clocks), and therefore it may be possible to reconstruct somatic cell dynamics from somatic cell errors. Recent human colon studies suggest that random somatic epigenetic errors record stem cell histories (ancestry and total numbers of divisions). Potentially age-related methylation also occurs in human small intestines, which would allow characterization of their stem cells and comparisons with the colon. METHODS: Methylation patterns in individual crypts from 13 small intestines (17 to 78 years old) were measured by bisulfite sequencing. The methylation patterns were analyzed by a quantitative model to distinguish between immortal or niche stem cell lineages. RESULTS: Age-related methylation was observed in the human small intestines. Crypt methylation patterns were more consistent with stem cell niches than immortal stem cell lineages. Human large and small intestine crypt niches appeared to have similar stem cell dynamics, but relatively less methylation accumulated with age in the small intestines. There were no apparent stem cell differences between the duodenum and ileum, and stem cell survival did not appear to decline with aging. CONCLUSION: Crypt niches containing multiple stem cells appear to maintain human small intestines. Crypt niches appear similar in the colon and small intestine, and the small intestinal stem cell mitotic rate is the same as or perhaps slower than that of the colon. Although further studies are needed, age-related methylation appears to record somatic cell histories, and a somatic epigenetic molecular clock strategy may potentially be applied to other human tissues to reconstruct otherwise occult stem cell histories

Transfer learning with large-scale data in brain-computer interfaces

© 2016 IEEE. Human variability in electroencephalogram (EEG) poses significant challenges for developing practical real-world applications of brain-computer interfaces (BCIs). The intuitive solution of collecting sufficient user-specific training/calibration data can be very labor-intensive and time-consuming, hindering the practicability of BCIs. To address this problem, transfer learning (TL), which leverages existing data from other sessions or subjects, has recently been adopted by the BCI community to build a BCI for a new user with limited calibration data. However, current TL approaches still require training/calibration data from each of conditions, which might be difficult or expensive to obtain. This study proposed a novel TL framework that could nearly eliminate requirement of subject-specific calibration data by leveraging large-scale data from other subjects. The efficacy of this method was validated in a passive BCI that was designed to detect neurocognitive lapses during driving. With the help of large-scale data, the proposed TL approach outperformed the within-subject approach while considerably reducing the amount of calibration data required for each individual (∼1.5 min of data from each individual as opposed to a 90 min pilot session used in a standard within-subject approach). This demonstration might considerably facilitate the real-world applications of BCIs

Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression

In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties

Impact of the Specific Mutation in KRAS Codon 12 Mutated Tumors on Treatment Efficacy in Patients with Metastatic Colorectal Cancer Receiving Cetuximab-Based First-Line Therapy: A Pooled Analysis of Three Trials

Purpose: This study investigated the impact of specific mutations in codon 12 of the Kirsten-ras (KRAS) gene on treatment efficacy in patients with metastatic colorectal cancer (mCRC). Patients: Overall, 119 patients bearing a KRAS mutation in codon 12 were evaluated. All patients received cetuximab-based first-line chemotherapy within the Central European Cooperative Oncology Group (CECOG), AIO KRK-0104 or AIO KRK-0306 trials. Results: Patients with KRAS codon 12 mutant mCRC showed a broad range of outcome when treated with cetuximab-based first-line regimens. Patients with tumors bearing a KRAS p.G12D mutation showed a strong trend to a more favorable outcome compared to other mutations (overall survival 23.3 vs. 14-18 months; hazard ratio 0.66, range 0.43-1.03). An interaction model illustrated that KRAS p.G12C was associated with unfavorable outcome when treated with oxaliplatin plus cetuximab. Conclusion: The present analysis suggests that KRAS codon 12 mutation may not represent a homogeneous entity in mCRC when treated with cetuximab-based first-line therapy. Copyright (C) 2012 S. Karger AG, Base