Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of deception on exercise performance: implications for determinants of fatigue in humans.

PURPOSE The aim of this study was to investigate whether it was possible to reduce the time taken to complete a 4000-m cycling time trial by misleading participants into believing they were racing against a previous trial, when, in fact, the power output was 2% greater. METHODS Nine trained male cyclists each completed four 4000-m time trials. The first trial was a habituation and the data from the second trial was used to form a baseline (BL). During trials 3 and 4, participants raced against an avatar, which they were informed represented their BL performance. However, whereas one of these trials was an accurate (ACC) representation of BL, the power output in the other trial was set at 102% of BL and formed the deception condition (DEC). Oxygen uptake and RER were measured continuously and used to determine aerobic and anaerobic contributions to power output. RESULTS There was a significant difference between trials for time to completion (F = 15.3, P = 0.00). Participants completed DEC more quickly than BL (90% CI = 2.1-10.1 s) and ACC (90% CI = 1.5-5.4 s) and completed ACC more quickly than BL (90% CI = 0.5-4.8 s). The difference in performance between DEC and ACC was attributable to a greater anaerobic contribution to power output at 90% of the total distance (F = 5.3, P = 0.02, 90% CI = 4-37 W). CONCLUSIONS The provision of surreptitiously augmented feedback derived from a previous performance reduces time taken for cyclists to accomplish a time trial of known duration. This suggests that cyclists operate with a metabolic reserve even during maximal time trials and that this reserve can be accessed after deception.
ORMDL3 expression levels have no influence on the activity of serine palmitoyltransferase

ORMDL proteins are believed to be negative regulators of serine palmitoyl transferase (SPT), which catalyzes the first and rate limiting step in sphingolipid (SL) de novo synthesis. Several single‐nucleotide polymorphisms (SNPs) that are close to the ORMDL3 locus have been reported to increase ORMDL3 expression and to be associated with an elevated risk for early childhood asthma; however, the direct effect of ORMDL3 expression on SPT activity and its link to asthma remains elusive. In this study, we investigated whether ORMDL3 expression is associated with changes in SPT activity and to tal SL levels. Orm d l3‐knockout (Ormd l3‐/‐) and transgenic (Ormd l3Tg/wt) micewere generated to study the effect of ORMDL3 on to tal SL levels inplasma and tissues. Cellular SPT activity was measured in mouse embryonic fibroblasts from Ormd l3‐/‐ mice, as well as in HEK293 cells in which ORMDL3 was overexpressed and silenced. Further more, we analyzed the association of the reported ORMDL3 asthma SNPs with plasma sphingoid bases in a population‐based cohort of 971 individuals. Total C18‐long chain bases were not significantly altered in the plasma and tissues of Ormd l3‐/‐ mice, whereas C18‐sphinganine showed a small and significant increase inplasma, lung, andliver tissues. Mouseembryonic fibroblast cells from Ormd l3‐/‐ mice didnot show an altered SPT activity compared with Ormd l3+/2 and Ormd l3+/+ mice. Overexpression or knock down of ORMDL 3 in HEK 293 cells did not alter SPT activity; however, parallel knock down of all 3 ORMDL iso forms increased enzyme activity significantly. A significant association of the annotated ORMDL3 asthma SNPs with plasma long‐chain sphingoid base levels could not be confirmed. ORMDL3 expression levels seemnot to be directly associatedwith changes in SPT activity. ORMDL3 might influence de novo sphingolipid metabolism downstream of SPT. —Zhakupova, A. , Debeuf, N. , Krols, M. , Toussaint, W. , Vanhoutte, L. , Alecu, I. , Kutalik, Z. , Vollenweider, P., Ernst, D. , von Eckardstein, A. , Lambrecht, B. N. , Janssens, S. , Hornemann, T. ORMDL3 expression levels have no influence on the activity of serine palmitoyltransferase. FASEB J. 30, 4289–4300 (2016). www.fasebj. org
Practitioner Review: Engaging fathers – recommendations for a game change in parenting interventions based on a systematic review of the global evidence

Background Despite robust evidence of fathers’ impact on children and mothers, engaging with fathers is one of the least well-explored and articulated aspects of parenting interventions. It is therefore critical to evaluate implicit and explicit biases manifested in current approaches to research, intervention, and policy. Methods We conducted a systematic database and a thematic hand search of the global literature on parenting interventions. Studies were selected from Medline, Psychinfo, SSCI, and Cochrane databases, and from gray literature on parenting programs, using multiple search terms for parent, father, intervention, and evaluation. We tabulated single programs and undertook systematic quality coding to review the evidence base in terms of the scope and nature of data reporting. Results After screening 786 nonduplicate records, we identified 199 publications that presented evidence on father participation and impact in parenting interventions. With some notable exceptions, few interventions disaggregate ‘father’ or ‘couple’ effects in their evaluation, being mostly driven by a focus on the mother–child dyad. We identified seven key barriers to engaging fathers in parenting programs, pertaining to cultural, institutional, professional, operational, content, resource, and policy considerations in their design and delivery. Conclusions Barriers to engaging men as parents work against father inclusion as well as father retention, and undervalue coparenting as contrasted with mothering. Robust evaluations of father participation and father impact on child or family outcomes are stymied by the ways in which parenting interventions are currently designed, delivered, and evaluated. Three key priorities are to engage fathers and coparenting couples successfully, to disaggregate process and impact data by fathers, mothers, and coparents, and to pay greater attention to issues of reach, sustainability, cost, equity, and scale-up. Clarity of purpose with respect to gender-differentiated and coparenting issues in the design, delivery, and evaluation of parenting programs will constitute a game change in this field.
Transcription and imprinting dynamics in developing postnatal male germline stem cells

Hammoud et al. conducted extensive genomic profiling and classified three broad spermatogonial stem cell (SSC) populations in juveniles: (1) epithelial-like SSCs, (2) more abundant mesenchymal-like SSCs, and (3) (in older juveniles) abundant cells committing to gametogenesis. Mesenchymal-like SSCs lacked imprinting specifically at paternally imprinted loci but fully restored imprinting prior to puberty. Mesenchymal-like SSCs also displayed developmentally linked DNA demethylation at meiotic genes and also at certain monoallelic neural genes.
Modifications in the glycerophospholipid composition between the Coxiella burnetii phase I and phase II cells suggest an association with phase variation of the bacterium.

Glycerophospholipids (GP) extracted from the Coxiella burnetii strain Nine Mile in virulent phase I (NM I) and low virulent phase II (NM II) were analyzed by Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry (MS) that gave a superior mass resolution and mass accuracy allowing unambiguous peak recognition and precise assignment of ions. We showed that GP present in the pathogen's outer membrane underwent considerable modifications during the phase variation that might be related to impact of various environmental factors. It was found that GP from phase I cells were much more complex than those from phase II cells. While glycerophosphoethanolamines (PE), glycerophosphocholines (PC) and glycerophosphoglycerols (PG) were present in both phases of C. burnetii, major differences were observed in the presence of glycerophosphates (PA) and glycerophosphoserines (PS). Thus, PA but no PS were detected in NM I variant in contrast with NM II cells where PS but no PA were identified. It is suggested that enzymes for PA head group modifications to form PS, PE, and PG become active during the phase variation of the bacterium.
Melting in a Single Screw Extruder: Experiments and 3D Finite Element Simulations

Abstract The melting of an ABS resin was simulated using a three-dimensional finite element simulation of the two-phase flow in the compression section of a single-screw extruder. Screw freezing experiments were also conducted to compare the numerical predictions with the corresponding experimental data. Numerical simulations as well as experiments exhibited the Maddock melting mechanism and numerical predictions were in good agreement with the corresponding experimental data. The sensitivity of the melting profile to various material properties and processing conditions was numerically analyzed. With a constant flow rate enforced at the entrance of the screw channel, the screw and barrel temperature were found to have a minor effect on the melting profile. However, these parameters were found to have a significant effect on the predicted pressure profile along the screw channel. When the zero-traction boundary condition was imposed at the entrance of the screw channel, a change in the screw or barrel temperature affected the flow rate in the screw channel, which resulted in a significant change in the solid fraction at the same cross-section.
TACO: Efficient SAT-Based Bounded Verification Using Symmetry Breaking and Tight Bounds

SAT-based bounded verification of annotated code consists of translating the code together with the annotations to a propositional formula, and analyzing the formula for specification violations using a SAT-solver. If a violation is found, an execution trace exposing the failure is exhibited. Code involving linked data structures with intricate invariants is particularly hard to analyze using these techniques. In this paper, we present Translation of Annotated COde (TACO), a prototype tool which implements a novel, general, and fully automated technique for the SAT-based analysis of JML-annotated Java sequential programs dealing with complex linked data structures. We instrument code analysis with a symmetry-breaking predicate which, on one hand, reduces the size of the search space by ignoring certain classes of isomorphic models and, on the other hand, allows for the parallel, automated computation of tight bounds for Java fields. Experiments show that the translations to propositional formulas require significantly less propositional variables, leading to an improvement of the efficiency of the analysis of orders of magnitude, compared to the noninstrumented SAT--based analysis. We show that in some cases our tool can uncover bugs that cannot be detected by state-of-the-art tools based on SAT-solving, model checking, or SMT-solving.
The Negative Consequences of Measurement Model Misspecification: A Response to Aguirre-Urreta and Marakas

It has been more than 40 years since Blalock (1964) noted thedistinction between what he called “cause” (formative) and“effect” (reflective) indicators of latent variables, and threedecades since the academic literature recognized that someSEM measurement models don’t fit classical test theory’sassumptions about the direction of causality of the relation-ships between constructs and their indicators (Bagozzi 1981;Fornell and Bookstein 1982). Since that time, interest inmodeling constructs with formative indicators has signi-ficantly increased in the business, social science, and informa-tion systems literatures (e.g., Bollen 2007; Cenfetelli andBassellier 2009; Diamantopoulos and Papadopoulos 2010;Diamantopoulos et al. 2008; Diamantopoulos and Winklhofer2001; Edwards and Bagozzi, 2000; Jarvis et. al. 2003; Lawand Wong 1999; MacKenzie et al. 2005; Marakas et al. 2007;Petter et al. 2007), and an increasing number of academicstudies are incorporating these types of measurement modelsin their substantive investigations. However, recentlyresearchers in a variety of disciplines (Franke et al. 2008;Howell et al. 2007; Kim et al. 2010) have raised questionssurrounding the correct conceptualization and operationa-lization of formative indicator measurement models.
Small-scale New Keynesian model features that can reproduce lead, lag and persistence patterns

Abstract This paper uses a new method for describing dynamic comovement and persistence in economic time series which builds on the contemporaneous forecast error method developed in den Haan [den Haan, W. J. 2000. “The Comovement between Output and Prices. ” Journal of Monetary Economics 46: 3–30]. This data description method is then used to address issues in New Keynesian model performance in two ways. First, well known data patterns, such as output and inflation leads and lags and inflation persistence, are decomposed into forecast horizon components to give a more complete description of the data patterns. These results show that the well-known lead and lag patterns between output and inflation arise mostly in the medium-term forecasts horizons. Second, the data summary method is used to investigate a small-scale New Keynesian model with some important modeling features to see which of these features can reproduce lead, lag and persistence patterns seen in the data. We show that a general equilibrium model with habit formation, persistent IS curve shocks and persistent supply shocks can reproduce the lead, lag and persistence patterns seen in the data.
Creating Public Awareness of How Goats Are Reared and Milk Produced May Affect Consumer Acceptability

This study evaluated whether showing a video of the different ways of raising goats for milk affected consumer acceptability. Four combinations, 2 Videos (intensive [INT] and semiextensive [SEM] system) × 2 Milk Types (semiskimmed [S] and whole [W] milk), were evaluated by 70 habitual consumers of goat milk, who scored their liking and purchase intention during blind (B), expected (E), and informed (I) acceptability sessions. In the B session, consumers tasted both milk types without information. S samples were preferred over W samples. In the E session, SEM video created high expectations in terms of milk liking and purchase intent, whereas the opposite happened when showing INT video. In the I session, consumers showed a clear preference for combinations created using SEM video, regardless of milk type. W-SEM and S-INT were worse (negative disconfirmation) and better (positive disconfirmation) than expected, respectively. A complete assimilation toward expectations occurred only for S-INT. INT video adversely affected the acceptability of S samples. Concerning purchase intent, W-SEM and S-SEM were worse than expected, but the assimilation was complete only for S-SEM: SEM video increased purchase intent for S samples.
Postoperative Deterioration in Health Related Quality of Life as Predictor for Survival in Patients with Glioblastoma: A Prospective Study

Background Studies indicate that acquired deficits negatively affect patients' self-reported health related quality of life (HRQOL) and survival, but the impact of HRQOL deterioration after surgery on survival has not been explored. Objective Assess if change in HRQOL after surgery is a predictor for survival in patients with glioblastoma. Methods Sixty-one patients with glioblastoma were included. The majority of patients (n = 56, 91.8%) were operated using a neuronavigation system which utilizes 3D preoperative MRI and updated intraoperative 3D ultrasound volumes to guide resection. HRQOL was assessed using EuroQol 5D (EQ-5D), a generic instrument. HRQOL data were collected 1–3 days preoperatively and after 6 weeks. The mean change in EQ-5D index was −0.05 (95% CI −0.15–0.05) 6 weeks after surgery (p = 0.285). There were 30 patients (49.2%) reporting deterioration 6 weeks after surgery. In a Cox multivariate survival analysis we evaluated deterioration in HRQOL after surgery together with established risk factors (age, preoperative condition, radiotherapy, temozolomide and extent of resection). Results There were significant independent associations between survival and use of temozolomide (HR 0.30, p = 0.019), radiotherapy (HR 0.26, p = 0.030), and deterioration in HRQOL after surgery (HR 2.02, p = 0.045). Inclusion of surgically acquired deficits in the model did not alter the conclusion. Conclusion Early deterioration in HRQOL after surgery is independently and markedly associated with impaired survival in patients with glioblastoma. Deterioration in patient reported HRQOL after surgery is a meaningful outcome in surgical neuro-oncology, as the measure reflects both the burden of symptoms and treatment hazards and is linked to overall survival.
3D-NonFAR: Three-dimensional non-volatile FPGA architecture using phase change memory

Memories play a key role in FGPAs in the forms of both programming bits and embedded memory blocks. FPGAs using non-volatile memories have been the focus of attention with zero boot-up delay, real-time reconfigurability, and superior energy efficiency. This paper presents a novel three-dimensional (3D) non-volatile FPGA architecture (3D-Non-FAR) using phase change memory (PCM) and 3D die stacking techniques. Basic structures in a conventional FPGA architecture are renovated with PCM, and components are repartitioned and reorganized in 3D-NonFAR to allow an efficient 3D integration of PCM elements. 3D-NonFAR not only preserves the advantages of existing non-volatile FP-GAs, but also provides high integration density, high performance, and bit-level programmability, which enable PCM as a universal memory replacement in FPGAs. Evaluation results show that 3D-NonFAR has smaller footprint, higher performance, and lower power consumption compared with other FPGA counterparts.
Characterization of Synthetic Chikungunya Viruses Based on the Consensus Sequence of Recent E1-226V Isolates

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that re-emerged in 2004 and has caused massive outbreaks in recent years. The lack of a licensed vaccine or treatment options emphasize the need to obtain more insight into the viral life cycle and CHIKV-host interactions. Infectious cDNA clones are important tools for such studies, and for mechanism of action studies on antiviral compounds. Existing CHIKV cDNA clones are based on a single genome from an individual clinical isolate, which is expected to have evolved specific characteristics in response to the host environment, and possibly also during subsequent cell culture passaging. To obtain a virus expected to have the general characteristics of the recent E1-226V CHIKV isolates, we have constructed a new CHIKV full-length cDNA clone, CHIKV LS3, based on the consensus sequence of their aligned genomes. Here we report the characterization of this synthetic virus and a green fluorescent protein-expressing variant (CHIKV LS3-GFP). Their characteristics were compared to those of natural strain ITA07-RA1, which was isolated during the 2007 outbreak in Italy. In cell culture the synthetic viruses displayed phenotypes comparable to the natural isolate, and in a mouse model they caused lethal infections that were indistinguishable from infections with a natural strain. Compared to ITA07-RA1 and clinical isolate NL10/152, the synthetic viruses displayed similar sensitivities to several antiviral compounds. 3-deaza-adenosine was identified as a new inhibitor of CHIKV replication. Cyclosporin A had no effect on CHIKV replication, suggesting that cyclophilins -opposite to what was found for other +RNA viruses- do not play an essential role in CHIKV replication. The characterization of the consensus sequence-based synthetic viruses and their comparison to natural isolates demonstrated that CHIKV LS3 and LS3-GFP are suitable and representative tools to study CHIKV-host interactions, screen for antiviral compounds and unravel their mode of action.
Native-State Stability Determines the Extent of Degradation Relative to Secretion of Protein Variants from Pichia pastoris

We have investigated the relationship between the stability and secreted yield of a series of mutational variants of human lysozyme (HuL) in Pichia pastoris. We show that genes directly involved in the unfolded protein response (UPR), ER-associated degradation (ERAD) and ER-phagy are transcriptionally up-regulated more quickly and to higher levels in response to expression of more highly-destabilised HuL variants and those variants are secreted to lower yield. We also show that the less stable variants are retained within the cell and may also be targeted for degradation. To explore the relationship between stability and secretion further, two different single-chain-variable-fragment (scFv) antibodies were also expressed in P. pastoris, but only one of the scFvs gave rise to secreted protein. The non-secreted scFv was detected within the cell and the UPR indicators were pronounced, as they were for the poorly-secreted HuL variants. The non-secreted scFv was modified by changing either the framework regions or the linker to improve the predicted stability of the scFv and secretion was then achieved and the levels of UPR indicators were lowered Our data support the hypothesis that less stable proteins are targeted for degradation over secretion and that this accounts for the decrease in the yields observed. We discuss the secretion of proteins in relation to lysozyme amyloidosis, in particular, and optimised protein secretion, in general.
Classifying Very High-Dimensional Data with Random Forests Built from Small Subspaces

The selection of feature subspaces for growing decision trees is a key step in building random forest models. However, the common approach using randomly sampling a few features in the subspace is not suitable for high dimensional data consisting of thousands of features, because such data often contains many features which are uninformative to classification, and the random sampling often doesn't include informative features in the selected subspaces. Consequently, classification performance of the random forest model is significantly affected. In this paper, the authors propose an improved random forest method which uses a novel feature weighting method for subspace selection and therefore enhances classification performance over high-dimensional data. A series of experiments on 9 real life high dimensional datasets demonstrated that using a subspace size of features where M is the total number of features in the dataset, our random forest model significantly outperforms existing random forest models.