Miracle-dz/UniFAR-FTUs huggingface dataset:
Relevance of the assessment mode in the digital assessment of processing speed

ABSTRACT Introduction: Many medical facilities and research institutes start using digital assessment methods to assess cognitive abilities, such as processing speed, instead of the traditional pen and paper versions. Even though many of the new digital assessment methods have shown to have a stable internal validity, the comparability of results across assessment modes is unclear. The study investigated whether results for assessing processing speed via (i) the traditional pen and paper version, (ii) a tablet and pen version, and (iii) a tablet and finger version are comparable. Methods: In a within-subject design, each participant (N= 30) completed the 90-number version by Oswald and Roth (1987) of the trail-making test (TMT) in three different assessment modes in randomized order. Each participant completed four TMT versions in each assessment mode (3 × 4 within-subject design). Results: Repeated measures ANOVA and mixed-effects analyses adjusted for age, gender, mode order, and trial number reveal significantly faster test TMT completion times (about 5 s) for the tablet and pen version compared to the pen and paper and the tablet and finger version. Conclusions: Our findings indicate that assessing processing speed can lead to different results with different digital versions depending on their setup, especially different input devices. Medical professionals and researchers who use digital assessment methods to assess cognitive abilities need to be aware of mode effects, even within the digital assessment domain, because the results may not be comparable and the available norms may not be applicable.
Dual effects of intermittent or continuous L‐DOPA administration on gene expression in the globus pallidus and subthalamic nucleus of adult rats with a unilateral 6‐OHDA lesion

Intermittent oral doses of levodopa (L‐DOPA) are routinely used to treat Parkinson's disease, but with prolonged use can result in adverse motor complications, such as dyskinesia. Continuous administration of L‐DOPA achieves therapeutic efficacy without producing this effect, yet the molecular mechanisms are unclear. This study examined, by in situ hybridization histochemistry, the effects of continuous or intermittent L‐DOPA administration on gene expression in the globus pallidus and subthalamic nucleus of adult rats with a unilateral 6‐hydroxydopamine (6‐OHDA) lesion of the nigrostriatal pathway. Results were compared to 6‐OHDA‐treated rats receiving vehicle. Our results provide original evidence that continuous L‐DOPA normalizes the 6‐OHDA‐lesion‐induced increase in mRNA levels encoding for the 67 kDa isoform of glutamate decarboxylase in neurons of the globus pallidus and cytochrome oxidase subunit I mRNA levels in the subthalamic nucleus. The extent of normalization did not differ between the continuous and intermittent groups. In addition, intermittent L‐DOPA induced an increase in the mRNA levels encoding for the 65 kDa isoform of glutamate decarboxylase in globus pallidus neurons ipsilateral to the lesion and a bilateral increase in c‐fos mRNA expression in the subthalamic nucleus. These results suggest that continuous L‐DOPA tends to normalize the 6‐OHDA‐lesion‐induced alterations in cell signaling in the pallido‐subthalamic loop. On the other hand, we propose that chronic intermittent L‐DOPA exerts a dual effect by normalizing cell signaling in a subpopulation of neurons in the globus pallidus and subthalamic nucleus while inducing abnormal signaling in another subpopulation. Synapse 49:246–260, 2003. © 2003 Wiley‐Liss, Inc.
Current density threshold for the stimulation of neurons in the motor cortex area

The aim of this study was to determine a current density threshold for exciting the motor cortex area of the brain. The current density threshold for excitation of nerve fibres (20 μm in diameter) found in the literature is approximately 1 A/m2 at frequencies lower than 1 kHz. In consideration of a safety factor of 100, the International Commission on Non‐Ionizing Radiation Protection (ICNIRP) recommends to restrict the exposure to 0.01 A/m2. The electromagnetic stimulation of neurons in the motor cortex is used in the clinical diagnosis of nerve lesions and neuropathy by means of magnetic or electrical transcranial stimulation. Combining medical data from clinical studies and technical specifications of the Magstim® Model 200 stimulator, we were able to compute the current density threshold for the excitation of the human motor cortex by means of the finite element method (FEM). A 3D‐CAD head model was built on the basis of magnetic resonance imaging (MRI) slices and segmented into four anatomical structures (scalp, skull, brain, and ventricular system) with different conductivities. A current density threshold for the stimulation of the motor cortex area of the upper limbs of 6 and 2.5 A/m2 at 2.44 kHz and 50 Hz, respectively, was calculated. As these values lie above the recommended ICNIRP values by two orders of magnitude there is no need for lower safety standards with regard to stimulation of the brain. Bioelectromagnetics 23:421–428, 2002. © 2002 Wiley‐Liss, Inc.
Improving Bug Triage with Relevant Search

Bug triage is a process where bugs are assigned to developers. In large open source projects such as Mozilla and Eclipse, bug triage is time-consuming because numerous bugs are submitted everyday. To improve bug triage, many studies have proposed automatic approaches to recommend proper developers for resolving bugs. These approaches are based on machine learning algorithms, which treat bug triage like text classification. Although they are effective, the accuracy of them can be further improved. Our goal is to propose a method not only has good performance but also is simple. We propose a method based on relevant search technique to recommend developers for the given bugs. First, we construct an index for bugs to make them searchable. Then, for a given bug to be assigned, we utilize the index to search for the bugs related to it. Finally, we analyze these related bugs and recommend developers based on them. We conduct experiments on bugs of Mozilla and Eclipse to evaluate our method. The results indicate that our method has a good performance and outperforms machine learning algorithms like Naïve Bayes and SVM. Keywords—bug triage; bug report assignment; issue tracking; problem tracking
Associations Between Age at Arterial Switch Operation, Brain Growth, and Development in Infants With Transposition of the Great Arteries.

BACKGROUND Brain injury, impaired brain growth, and long-term neurodevelopmental problems are common in children with transposition of the great arteries. We sought to identify clinical risk factors for brain injury and poor brain growth in infants with transposition of the great arteries undergoing the arterial switch operation, and to examine their relationship with neurodevelopmental outcome. METHODS The brains of 45 infants with transposition of the great arteries undergoing surgical repair were imaged pre- and postoperatively using magnetic resonance imaging. Brain weight z scores were calculated based on brain volume and autopsy reference data. Brain injury scores were determined as previously described. Neurodevelopment was assessed at 18 months using the Bayley-III scores of infant development. The relationships between clinical variables, brain injury, perioperative brain growth, and 18-month Bayley-III scores were analyzed. RESULTS On preoperative imaging, moderate or severe white matter injury was present in 10 of 45 patients, whereas stroke was seen in 4 of 45. A similar prevalence of injury was seen on postoperative imaging, and we were unable to identify any clinical risk factors for brain injury. Brain weight z scores decreased perioperatively in 35 of 45 patients. The presence of a ventricular septal defect ( P=0.009) and older age at surgery ( P=0.007) were associated with impaired perioperative brain growth. When patients were divided into those undergoing surgery during the first 2 weeks of life (32/45) versus those being repaired later (13/45), infants repaired later had significantly worse perioperative brain growth (late repair postoperative brain weight z = -1.0±0.90 versus early repair z = -0.33±0.64; P=0.008). Bayley-III testing scores fell within the normal range for all patients, although age at repair ( P=0.03) and days of open chest ( P=0.03) were associated with a lower composite language score, and length of stay was associated with a lower composite cognitive score ( P=0.02). CONCLUSIONS Surgery beyond 2 weeks of age is associated with impaired brain growth and slower language development in infants with transposition of the great arteries cared for at our center. Although the mechanisms underlying this association are still unclear, extended periods of cyanosis and pulmonary overcirculation may adversely impact brain growth and subsequent neurodevelopment.
Charged Particle Detection with NUV-Sensitive SiPM in a Beam of Relativistic Ions

Particle detector prototypes equipped with Silicon Photomultipliers designed to be sensitive in the near-ultraviolet wavelength region (NUV-SiPM) were tested in a beam of relativistic ions with electric charge Z in the range 1 ≤ Z ≤ 28, at energies 13 and 30 GeV/amu at CERN SPS. Two different prototypes of charged particle detectors were tested. The first one was a scintillating fiber hodoscope with individual fibers optically coupled to single SiPM devices. The second one consisted of an array of discrete SiPM sensors that were directly exposed to the ion beam to study their capability to trigger an avalanche in response to the ionization generated inside the silicon device. In this paper, we first report the results of the characterization and dedicated tests of the NUV-SiPM sensors that were carried out in our laboratory under controlled conditions; then, we discuss the analysis of the beam test data and the performance of both prototypes.
Machine Learning in the Detection of the Glaucomatous Disc and Visual Field

ABSTRACT Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients’ long-term quality of life. The structure and function thresholds that alert to the diagnosis of glaucoma can be obtained entirely via digital means, and as such, screening is well suited to benefit from artificial intelligence and specifically machine learning. This paper reviews the concepts and current literature on the use of machine learning for detection of the glaucomatous disc and visual field.
Design of Intermittent Control for Cortisol Secretion Under Time-Varying Demand and Holding Cost Constraints

Objective: We take the release of stress hormone cortisol as a part of an intermittent control feedback system in contrast to the existing continuous models. By modeling cortisol secretion as an impulsive system, we design an impulsive controller as opposed to a continuous controller for adjusting cortisol levels while maintaining the blood cortisol levels within bounds that satisfy circadian demand and cost constraints. Methods: We develop an analytical approach along with an algorithm for identifying both the timing and amplitude of the control. Results: The model and the algorithm are tested by two examples to illustrate that the proposed approach achieves impulsive control and that the obtained blood cortisol levels render the circadian rhythm and the ultradian rhythm consistent with the known physiology of cortisol secretion. Conclusions: The approach successfully achieves the desired circadian impulsive control, which has great potential to be used in personalizing the medications in order to control the cortisol levels optimally. Significance: This type of bioinspired intermittent controllers can be employed for designing noncontinuous controllers in treating Addisonian disease, which is caused by the adrenal deficiency.
Stochastic Recurrent Neural Network for Speech Recognition

This paper presents a new stochastic learning approach to construct a latent variable model for recurrent neural network (RNN) based speech recognition. A hybrid generative and discriminative stochastic network is implemented to build a deep classification model. In the implementation, we conduct stochastic modeling for hidden states of recurrent neural network based on the variational auto-encoder. The randomness of hidden neurons is represented by the Gaussian distribution with mean and variance parameters driven by neural weights and learned from variational inference. Importantly, the class labels of input speech frames are incorporated to regularize this deep model to sample the informative and discriminative features for reconstruction of classification outputs. We accordingly propose the stochastic RNN (SRNN) to reflect the probabilistic property in RNN classification system. A stochastic error backpropagation algorithm is implemented. The experiments on speech recognition using TIMIT and Aurora4 show the merit of the proposed SRNN.
Fat absorption and deposition in Japanese quail (Coturnix coturnix japonica) fed a high fat diet.

Dietary fat contributes significantly to the energy requirements of poultry. Not all species are able to increase their absorptive capacity for fats in response to a high fat diet. The effects of a high fat diet (10% canola oil) on the lipid absorption and deposition in the liver, breast and thigh muscles of male and female Japanese quail were investigated. Thirty-eight Japanese quail (Coturnix coturnix japonica) were randomly divided into a high fat diet (HFD) and a standard diet (STD) group. The birds were fed the diets for seven weeks after which half of the birds were subjected to oral fat loading tests (OFLT) with plant oils containing long-chain and medium-chain triglycerides. The remaining birds were included for the lipid deposition measurements. Thereafter the birds were euthanised, blood samples were collected and liver, breast and thigh muscle lipid deposition was determined. Female quail on both diets had significantly higher plasma triglyceride concentrations (p < 0.05) compared with their male counterparts. No significant differences in plasma triglyceride concentrations were observed after the OFLTs. Female quail had significantly heavier liver masses compared with the males but there was no significant difference in the liver lipid content per gram liver mass. Female quail on the HFD had higher lipid content (p < 0.05) in the breast muscle compared with their male counterparts whilst male quail on the HFD had higher lipid content (p < 0.05) in the thigh muscle in comparison with both males and females on the standard diet. Dietary supplementation with 10% canola oil did not alter gastrointestinal tract lipid absorption, but it caused differences between the sexes in muscle lipid accumulation, the physiological significance of which requires further investigation.
A critical review of quality of service models in mobile ad hoc networks

Quality of service (QoS) provisioning in mobile ad hoc networks (MANETs) consists of providing a complex functionality in a harsh environment where resources are scarce. Thus, it is very challenging to build an efficient solution to address this issue. The proposed solutions in the literature are broadly classified into four categories, namely: QoS routing protocols, QoS signalling, QoS-aware MAC protocols and QoS models, which are the main concern of our study. The contribution of this paper is threefold: Firstly, we propose a set of guidelines to deal with the challenges facing QoS models design in ad hoc networks. Secondly, we propose a new taxonomy for QoS models in ad hoc networks. Finally, we provide an in-depth survey and discussion of the most relevant proposed frameworks.
The role of early molecular predictor in transplant-eligible chronic myelogenous leukemia

Before the tyrosine kinase inhibitor (TKI) era, allogeneic stem cell trans-plantation (allo-SCT) was the only curative treatment for chronic my-elogenous leukemia (CML). TKI dis-continuation studies indicate that the use of TKIs in the treatment of CML can achieve an " operational cure, " with lasting freedom from disease progression and disease-related signs and symptoms [1]. However, if the patient has developed a TKI-resistance mutation or cannot tolerate several TKIs, allo-SCT is indicated with a suitable donor. If the patient has advanced CML, allo-SCT is recommended for the blastic phase and accelerated-phase patients who have not achieved an optimal response [2]. In this issue of the Korean Journal of Internal Medicine, Lee et al. [3] report that BCR-ABL1 transcripts (MR 4.5) at 3 months posttransplant predict the long-term outcomes in patients with chronic-phase CML. At 3 months post-transplant, MR 4.5 was associated with significantly longer event-free survival and showed a trend to lower relapse rates. Their study enrolled 101 patients, of whom 47 were TKI-naïve at the time of transplantation (most were treated during the period before the National Health Insurance Program covered imatinib), while 51 received imatinib as their front-line therapy, and the remaining three patients received one of dasatinib, nilotinib, or bosutinib as front-line therapy. Of the patients for whom a front-line TKI failed, 17 received second-line therapy, of whom eight were treated with a third-line TKI. Although not all enrolled patients were currently indicated for allo-SCT in patients with CML, this study shows the early predictive role of MR 4.5 at 3 months posttransplant. This is a meaningful finding because it suggests that early intervention with TKI therapy or modulation with immunosuppressive therapy (e.g., donor lymphocyte infusion [DLI] or withdrawal of an immu-nosuppressive agent) using early molecular monitoring could potentially reduce relapse after allo-SCT in transplant eligible CML patients. Previous studies reported that the early detection of BCR-ABL1 transcripts using polymerase chain reaction technology is associated with an increased risk of relapse [4,5]. However, the value of the BCR-ABL1 transcripts expressed in previous studies was not standardized. For molecular monitoring in CML, international efforts have been made to establish recommendations for the interpretation of molecular data. In 2005, experts suggested harmonizing the different methodologies
Melioidosis, report of first case from the Western Hemisphere.

Melioidosis is a specific infection caused by the glanders-like bacillus, Malleomyces pseudomallei. This organism usually produces an acute pulmonary and septicemic form of the disease, with multiple miliary abscesses in the viscera and with early death, but occasionally causes a chronic form, with multiple sinuses of the soft tissue, which is similar to glanders. About 300 cases have been reported, nearly all of them from the Far East. Krishnaswami 1 observed 200 cases in Rangoon and others have been reported from elsewhere in Burma, the Federated Malay States, Indo-China, Siam, Ceylon and the Dutch East Indies. Grant and Barwell 2 observed a chronic case in England in a British soldier who contracted it in the island of Penang. Mayer and Finlayson 1 reported a chronic case from South Africa in a soldier who contracted it in the island of Singapore. Cox and Arbogast 3 recorded an instance of the disease
Distraction osteogenesis for management of obstructive sleep apnea secondary to TMJ ankylosis

Mandibular retrognathism due to temporomandibular joint (TMJ) ankylosis is one of the important contributing factors to the obstructive sleep apnea(OSA). Such patients suffer from number of apneic or hyponeic events during sleep, snoring, daytime sleepiness, fatigue, inability to concentrate, irritability. At the same time facial asymmetry due TMJ ankylosis lead to a progressive lack of confidence. Distraction osteogenesis is a less invasive surgical technique in the management of OSA, secondary to TMJ ankylosis. This modality not only treats the OSA but also corrects the facial asymmetry at the same time, and the results have been gratifying.
The Gutman Index and the Edge-Wiener Index of Graphs with Given Vertex-Connectivity

Abstract The Gutman index and the edge-Wiener index have been extensively investigated particularly in the last decade. An important stream of re- search on graph indices is to bound indices in terms of the order and other parameters of given graph. In this paper we present asymptotically sharp upper bounds on the Gutman index and the edge-Wiener index for graphs of given order and vertex-connectivity κ, where κ is a constant. Our results substantially generalize and extend known results in the area.
Is Best Answer Really the Best Answer? The Politeness Bias

Popular knowledge management platforms such as community-based question answering sites (CQAs) and electronic networks of practice (ENPs) rely on accurate quality assessment of user-contributed content to ensure effective knowledge creation and exchange. However, quality assessment is subjective by nature. Based on the politeness theory, we hypothesize that answers written more politely are more likely to be perceived as high quality answers by the question asker due to the low face threat. We first test our hypotheses through a random coefficient logit model with data obtained from Stack Exchange, a popular CQA platform. We then conduct a randomized experiment where we exogenously manipulate the politeness level of otherwise similar answers. Our analyses, based on both the Stack Exchange dataset and the randomized experiment, lend strong support to the existence of a politeness bias, which affects question askers’ subjective evaluation of answer quality. This study contributes to the literature in knowledge management, cognitive bias, and behavioral issues in information systems.
The 'Experts' in the Crowd: The Role of Experienced Investors in a Crowdfunding Market

Online crowdfunding markets facilitate the unbundling of resources, expertise, and signals – the three important components of a transactions. This study examines whether an early investor’s expertise per se, serves as a credible signal of quality for the other investors in the crowd and if so under what conditions. Using a data set on individual investments in a crowdfunding market for mobile applications, we find that early investors with expertise – particularly, investors with app development expertise and investors with investment expertise - have a disproportionate influence on later investors in the crowd. Investors with app development expertise who are likely to have a better knowledge of the product are found to be more influential for “concept apps” (apps in the pre-release stage), while investors with investment expertise with a better knowledge of market performance are found to be more influential for “live apps” (apps that are already being sold in the market). Our findings show that the majority of investors in this market – the crowd – although inexperienced, are rather sophisticated in their ability to identify and exploit nuanced differences in the underlying expertise of the early investors – informational signals that align well with the specific nature of uncertainty they face. In examining the ex-post performance of apps, we find that apps with “expert” investors are positively associated with ex-post app sales. We also find that these “experts” have the ability to select better apps to invest in, making their investment choices credible signals of quality for the crowd. Contrary to popular perceptions of crowdfunding markets as means for democratizing expertise and as substitutes for traditional expert-dominated mechanisms, our findings indicate that the participation by individuals with expertise can be beneficial to these markets.