Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating distributed inspection through controlled experiments

Inspection methods can be classified according to their discipline and flexibility. The discipline concerns the formal aspect of an inspection method, whereas the flexibility is strongly related to the simplicity of organising and conducting a meeting. The majority of the available distributed inspection methods have a high level of discipline and flexibility as they are based on a well-defined process and the discussion among team members is easily organised and conducted. In this study the authors present two controlled experiments to evaluate the effectiveness and the efficacy of a distributed inspection process to discover defects within source code. In particular, the first experiment compares the distributed inspection method proposed to a disciplined but not flexible method (i.e. the Fagan's inspection process). In the second experiment the authors investigate differences between the same distributed inspection method and a flexible but not disciplined method (i.e. the pair inspection method). Data analysis reveals that more flexible methods require less time to inspect a software artefact, while the discipline level does not affect the inspection quality.
A scheduling architecture for enforcing quality of service in multi-process systems

There is a massive deployment of multi-core CPUs. It requires a significant drive to consolidate multiple services while still achieving high performance on these off-the-shelf CPUs. Each function had earlier an own execution environment, which guaranteed a certain Quality of Service (QoS). Consolidating multiple services can give rise to shared resource congestions, resulting in lower and non-deterministic QoS. We describe a method to increase the overall system performance by assisting the operating system process scheduler to utilize shared resources more efficiently. Our method utilizes hardware- and system-level performance counters to profile the shared resource usage of each process. We also use a big-data approach to analyzing statistics from many nodes. The outcome of the analysis is a decision support model that is utilized by the process scheduler when allocating and scheduling process. Our scheduler can efficiently distribute processes compared to traditional CPU-load based process schedulers by considering the hardware capacity and previous scheduling- and allocation decisions.
DNA replication timing alterations identify common markers between distinct progeroid diseases

Significance We show that the temporal order of replication (replication timing, RT), normally an extremely stable cell type-specific chromosomal property, is altered in cells from two different premature aging (progeroid) diseases. By converting patient cells to stem cells and redifferentiating them as a model of disease progression, we identified the TP63 gene as one of the earliest RT alterations and altered RT was associated with abnormal TP63 gene expression. TP63 mutations have been linked to other diseases that share clinical features of progeroid syndromes. These findings introduce an approach for disease marker discovery, identify molecular abnormalities distinguishing progeroid diseases from natural aging, and point to TP63 as a molecular link to the pathophysiological manifestations of progeroid diseases. Progeroid syndromes are rare genetic disorders that phenotypically resemble natural aging. Different causal mutations have been identified, but no molecular alterations have been identified that are in common to these diseases. DNA replication timing (RT) is a robust cell type-specific epigenetic feature highly conserved in the same cell types from different individuals but altered in disease. Here, we characterized DNA RT program alterations in Hutchinson–Gilford progeria syndrome (HGPS) and Rothmund–Thomson syndrome (RTS) patients compared with natural aging and cellular senescence. Our results identified a progeroid-specific RT signature that is common to cells from three HGPS and three RTS patients and distinguishes them from healthy individuals across a wide range of ages. Among the RT abnormalities, we identified the tumor protein p63 gene (TP63) as a gene marker for progeroid syndromes. By using the redifferentiation of four patient-derived induced pluripotent stem cells as a model for the onset of progeroid syndromes, we tracked the progression of RT abnormalities during development, revealing altered RT of the TP63 gene as an early event in disease progression of both HGPS and RTS. Moreover, the RT abnormalities in progeroid patients were associated with altered isoform expression of TP63. Our findings demonstrate the value of RT studies to identify biomarkers not detected by other methods, reveal abnormal TP63 RT as an early event in progeroid disease progression, and suggest TP63 gene regulation as a potential therapeutic target.
Impact of using different tissue classes on the accuracy of MR-based attenuation correction in PET-MRI

Diagnosis , staging and treatment of disease depends on the morphological and functional information obtained from multimodality molecular imaging systems. The combination of functional and morphological information is now routinely performed to overcome the limitations of each individual modality. Attenuation of photons in the object under study is one of the main limitations of quantitative PET imaging. Attenuation correction plays a pivotal role in PET imaging. However, the availability of CT data on hybrid PET/CT scanners made it possible to build an accurate attenuation map. One of the well-known methods for generation of the attenuation map on PE/MRI systems is MR-based attenuation correction (MRAC) where image segmentation is used to classify MRI into several classes corresponding to different attenuation factors. In this study we investigate the effect of using different numbers of classes for the generation of attenuation maps on the accuracy of attenuation correction of PET data. The study was carried out using simulations of the XCAT phantom and 10 clinical studies. For the later, CT and PET images of 10 patients were used with CT-based attenuation correction assumed as reference. MRI was classified into different classes to produce two, three and four-class attenuation maps using the ITK library. The relative error showed that the lower number of classes will increase the global error over 8%. The elimination of bony structures from the attenuation map will cause a local error over 3%. In clinical studies, SUVmean and SUVmax were calculated for each AC method. The results seem to indicate an underestimation of 11% because of neglecting bone.
Bass model revisited

Abstract Innovation Diffusion model due to Bass has been widely used in the literature and has found applications in several areas. The model categorizes the consumers into two categories viz. innovators and imitators. The model is based on simple assumptions and excludes some real life consumer behavior and market aspects. Further extension of the model results in complex mathematical form or is sometimes not possible to solve. This difficulty can be resolved using an alternative formulation of the model maintaining its flexible structure. In this paper we propose some extensions of the Bass model using the alternative formulation. Promotional effort is an important component of marketing mix that determines the success of a product in the market and should be incorporated in the diffusion model. The Generalized Bass model (GBM) developed by Bass can be used to predict the growth of sales incorporating current marketing effect. Like Bass model GBM is also based on simple assumptions and excludes some real life consumer behavior and market aspects. Further extension of GBM also results in complex mathematical form or is sometimes not possible to solve. In this paper we have derived an alternative solution of the Generalized Bass model maintaining its flexible structure. We have called current marketing effect as a measure of promotional efforts. The utility of this alternative derivation has been highlighted through new models that describe growing market size and repeat purchasing. The models have been validated on new product sales data sets cited in literature.
Uromodulin in Renal Transplant Recipients: Elevated Urinary Levels and Bimodal Association with Graft Failure

Background: Urinary uromodulin (UMOD) predicts renal prognosis in native kidneys, but data are conflicting. We investigated its prognostic impact for graft failure (GF) in renal transplant recipients (RTR; n = 600). Methods: UMOD concentration was measured cross-sectionally in RTR at 6.0 years [2.6–11.4] post-transplant, in matched patients with native chronic kidney disease (CKD) and healthy subjects. In 59 cases, RTR allograft biopsies were reviewed. Results: During a follow-up of 5.3 years [4.5–5.7], GF had occurred in 7% of RTR. Median UMOD excretion (mg/24 h) was 20.4 in RTR, 11.6 in CKD and 5.7 in controls (p < 0.001). There was a curvilinear association between UMOD excretion and baseline renal function (p < 0.003) and death-censored GF, with 5.5, 11.5 and 4.0% of the cases in subsequent UMOD excretion tertiles, respectively (p = 0.002). On multivariate Cox regression analysis, hazard ratios for GF for the 1st and 3rd tertiles were 0.37 (p = 0.01) and 0.21 (p = 0.001), respectively. Interstitial fibrosis and tubular atrophy were more severe in the middle tertile (p = 0.007). Conclusions: Urinary UMOD is elevated in RTR and associated with graft function, morphology and outcome in a bimodal fashion. Dissection of the disparate mechanisms of GF prediction by urinary UMOD might provide new clues for its alleged pathogenetic significance in progressive renal function loss.
A Comprehensive Review of Sentiment Analysis of Stocks

This paper comprehensively studies the sentiment analysis of stock market news and explains the maturity of sentiment analysis in the stock market scenario. I explain in its entirety the procedure, difficulties, and limitations concerning sentiment analysis of financial news to predict stocks. The stock market movements are regarded as highly unpredictable and a large number of factors contribute to that unpredictability. Factors such as market sentiment, government policies and company announcements are some of the major contributing factors however the list is not exhaustive. Technological advancements over the past two decades has enabled researchers and market professionals to develop mathematical models to optimize their returns and keep the risk in check. These advancements have given way to social media platforms especially Twitter to more conveniently express opinions and reviews. Narrowing it only to the stock market and financial scenario, Twitter is an attractive platform for the user community to discuss company health, company announcements, major news, and government policies etc to name a few. Companies or organizations in turn also boast their success on Twitter. This entire process of sharing news and opinions yields a large amount of financial data to be searched for an overall sentiment or a possible prediction of the stocks. This paper attempts to dive deep into the specifics of procedure, the current stage of its maturity, and the importance of Machine Learning in finance and the stock market.
Who Cares about the Health of Health Care Professionals? An 18-Year Longitudinal Study of Working Time, Health, and Occupational Turnover

Health care workers are employed in a complex, stressful, and sometimes hazardous work environment. Studies of the health of health care workers tend to focus on estimating the effects of short-term health outcomes on employee attitudes and performance, which are easier to observe than long-term health outcomes. Research has paid only scant attention to work characteristics that are controlled by the employer and its employees, and their relationship to employees’ long-term physical health and organizational outcomes. The authors use data from the National Longitudinal Survey of Youth (NLSY) from 1992 to 2010 to estimate the relationships among working time, long-term physical health, job satisfaction, and turnover among health care employees. Using a between- and within-person design, they estimate how within-person changes in work characteristics affect the within-person growth trajectory of body mass index (BMI) over time and the relationship between working-time changes and physical health, and occupational turnover. The study finds that health care employees who work more hours suffer from a higher level of BMI and are more likely to leave their occupation.
The Rentier Predatory State: An Empirical Investigation of the 'Resource Curse'

This paper introduces an empirical growth model that explains the observed perplexing growth-resource regime, dubbed the resource curse. The main hypothesis introduced here, the rentier predatory state hypothesis, holds that under autocracy, the interaction between political power and resource abundance is expected to lead to poor economic outcomes in long run. In the empirical model, resource abundance is allowed to interact with political repression to generate a negative impact on economic growth. Depending on the extent of the political repression, a state dependent on natural resources (a rentier state) can also become a predatory state, i.e., a rentier predatory state, or, in other words, a rentier state with high rate of political repression. The resulting net effect from natural resource abundance on economic growth is contingent on the extent of the repression, and a resource abundant state with a sufficiently high rate of political repression will have negative economic growth, while a state with low to moderate rate of political repression will have positive economic growth.
Chromatin remodeling and neuronal response: multiple signaling pathways induce specific histone H3 modifications and early gene expression in hippocampal neurons

Plasticity in gene expression is achieved by a complex array of molecular mechanisms by which intracellular signaling pathways directly govern transcriptional regulation. In addition to the remarkable variety of transcription factors and co-regulators, and their combinatorial interaction at specific promoter loci, the role of chromatin remodeling has been increasingly appreciated. The N-terminal tails of histones, the building blocks of nucleosomes, contain conserved residues that can be post-translationally modified by phosphorylation, acetylation, methylation and other modifications. Depending on their nature, these modifications have been linked to activation or silencing of gene expression. We wanted to investigate whether neuronal stimulation by various signaling pathways elicits chromatin modifications that would allow transcriptional activation of immediate early response genes. We have analysed the capacity of three drugs – SKF82958 (a dopaminergic receptor agonist), pilocarpine (a muscarinic acetylcholine receptor agonist) and kainic acid (a kainate glutamate receptor agonist) – to induce chromatin remodeling in hippocampal neurons. We show that all stimulations induce rapid, transient phosphorylation of histone H3 at serine 10. Importantly, the same agonists induce rapid activation of the mitogen-activated protein kinase pathway with similar kinetics to extracellular-regulated-kinase phosphorylation. In the same neurons where this dynamic signaling cascade is activated, there is induction of c-fos transcription. Histone H3 Ser10 phosphorylation is coupled to acetylation at the nearby Lys14 residue, an event that has been linked to local opening of chromatin structure. Our results underscore the importance of dynamic chromatin remodeling in the transcriptional response to various stimuli in neuronal cells.
Meaning perspective transformation following stroke: the process of change

Purpose. Transformative Learning in an educational theory that posits that individuals learn and grow when their meaning perspectives (frames of reference for interpreting an experience based on knowledge, feelings, values and beliefs) are reformulated following a critical event. This theory has become quite influential in the exploration of adaptation to chronic illness. This study explored whether the change that occurs following stroke follows a process similar to transformative learning. Method. Grounded Theory approach was used to explore changes in meaning perspective among 12 people who were members of stroke support organisations, had a stroke at least 1 year prior to the study and described themselves as viewing life positively following stroke. Constant comparison analysis of interviews with these individuals was used to explore their experience following stroke. Results. Meaning perspective transformation occurred with four factors contributing to transformation: triggers, support, knowledge and choices to action. A substantive grounded theory of the process of meaning perspective transformation following stroke is presented, which illustrates the interaction of these contributing factors in initiating and facilitating the transformation process. Conclusion. Transformative learning can offer insight into how people who have experienced stroke learn, rebuild competence and re-engage in valued activities.
THERM: a computer code for estimating thermodynamic properties for species important to combustion and reaction modeling

A computer package has been developed called THERM, an acronym for THermodynamic property Estimation for Radicals and Molecules. THERM is a versatile computer code designed to automate the estimation of ideal gas phase thermodynamic properties for radicals and molecules important to combustion and reaction-modeling studies. Thermodynamic properties calculated include heat of formation and entropies at 298 K and heat capacities from 300 to 1500 K. Heat capacity estimates are then extrapolated to above 5000 K, and NASA format polynomial thermodynamic property representations valid from 298 to 5000 K are generated. This code is written in Microsoft Fortran version 5.0 for use on machines running under MSDOS. THERM uses group additivity principles of Benson and current best values for bond strengths, changes in entropy, and loss of vibrational degrees of freedom to estimate properties for radical species from parent molecules. This ensemble of computer programs can be used to input literature data, estimate data when not available, and review, update, and revise entries to reflect improvements and modifications to the group contribution and bond dissociation databases. All input and output files are ASCII so that they can be easily edited, updated, or expanded. In addition, heats of reaction, entropy changes, Gibbs free-energy changes, and equilibrium constants can be calculated as functions of temperature from a NASA format polynomial database.
Dynamic Compensation of Nonlinear Sensors by a Learning-From-Examples Approach

In this paper, we address the problem of nonlinear sensor dynamic compensation that will be performed on board wireless sensor network nodes. To this aim, we design suitable reduced-complexity learning-from-example algorithms and implement them on resource-constrained devices, namely, 8-bit microcontrollers. The proposed approach is validated with simulations on different examples of nonlinear sensor models.
Tracking the recovery of local optic nerve function after optic neuritis: a multifocal VEP study.

PURPOSE To explore the multifocal visual evoked potential (mVEP) as a technique for tracking local optic nerve damage after unilateral optic neuritis (ON). METHODS Humphrey visual fields and mVEP recordings were obtained from three patients within 7 days of an episode of ON. Patients were retested during the recovery phase, approximately 4 to 7 weeks later. The multi-input procedure of Sutter was used to obtain 60 local VEP responses (the mVEP) to a scaled checkerboard pattern. The mVEPs were recorded separately for monocular stimulation of both eyes. RESULTS Initially, all three patients had extensive visual field defects, reduced visual acuity, and depressed mVEP amplitude in regions of poor visual field sensitivity. By 4 to 7 weeks, the fields recovered to near normal sensitivity in most locations, and visual acuity returned to 20/20. The mVEP recovered to nearly full amplitude in all regions, but substantial delays were present in many locations. The delayed responses were associated with regions of visual field loss documented during the acute phase. CONCLUSIONS The mVEP can be used to track local optic nerve damage after unilateral ON. This technique should be useful in observing the effects of treatments as well as in testing hypotheses about the mechanisms underlying both the acute loss of vision and the subsequent recovery.
Poultry feed metabolizable energy determination using total or partial excreta collection methods

The aim of this work was to compare the efficiency of total (TC) or partial (PC) collection excreta methods to determine metabolizable energy in poultry feeds. A number of 180 12- to 21-day-old broilers were distributed into two treatments of six replicates of 10 birds each. A reference-diet was formulated to supply broiler requirements, and the test-diets consisted of 60% of reference diets and 40% of corn or soybean meal. Celite was added at 1% to the diets as a marker. Excreta and diet samples were analyzed for dry matter, energy, nitrogen, and acid-insoluble ash (AIA). AME of corn determined by partial collection (PC) was higher (3544 kcal/kg) as compared to total collection (TC) (3133 kcal/kg). However, no difference were observed for soybean meal (1797 vs. 1821 kcal/kg) between both methods. Marker recovery rates in the excreta were 101, 111, and 96% for the basal-diet, and the test-diets with corn or soybean meal, respectively. This result indicates the importance of marker recovery rate in the excreta to evaluate feed AME and digestibility.
Association between management practices, dairy herd characteristics, and somatic cell count of bulk tank milk.

OBJECTIVE To determine whether particular dairy management practices and herd characteristics were associated with somatic cell count (SCC) of bulk tank milk. DESIGN Analysis of records. SAMPLE POPULATION Milk samples collected from 59,435 cows housed in 843 dairy herds between March 1992 and June 1994. PROCEDURE Results of bacterial culture of milk samples and data on farm housing, sanitation, milking system, and management were collected. Multiple regression analysis was used to determine sources of variation in bulk tank milk SCC among herds. RESULTS Prevalence of Streptococcus agalactiae and Staphylococcus aureus mastitis was associated with bulk tank milk SCC. In herds free of S agalactiae mastitis, prevalence of S aureus and Corynebacterium bovis mastitis were important. For herds without S agalactiae mastitis, use of sawdust bedding was associated with a decrease in SCC and a dirty loose housing area was associated with an increase. Increased milk production, repeated mastitis control visits, and use of particular predip compounds were significantly associated with reduced SCC in all herds, regardless of whether any cows in the herd had S agalactiae mastitis. In herds with S agalactiae mastitis, use of iodine (certain concentrations), chlorhexidine, peroxide, or sodium chlorite-lactic acid as a predip was associated with a decrease in SCC. Only use of sodium chlorite-lactic acid predip was significantly associated with a decrease in SCC in herds without S agalactiae mastitis. CLINICAL IMPLICATIONS Important factors associated with bulk tank milk SCC were prevalence of S agalactiae and S aureus mastitis, careful application of particular predip compounds, avoiding a dirty loose housing area, and use of a service to regularly monitor prevalence of mastitis in the herd.