Miracle-dz/UniFAR-FTUs huggingface dataset:
Individual Analysts' Earnings Forecasts: Evidence for Overreaction in the UK Stock Market

This paper presents an analysis of two forms of overreaction (generalized overreaction and overreaction to prior earnings changes) in analysts’ earnings forecasts for the UK stock market, using a sample of individual forecasts of earning per share from a British investment bank over the period 1989-2002. Given that previous UK empirical research over 1980s and mid ‘90s has provided limited and contradictory findings, we investigate whether and how overreaction of analysts forecasts varies across forecast horizons, firm size (small and large) and growth opportunities (high and low P/E ratio) in order to provide further and comparable evidence. Overall, our findings support the generalized overreaction hypothesis but reject the firm size effect, the overreaction for high P/E ratio companies and the higher overreaction regarding the forecasting horizon.
The Broadband Digital Divide and the Economic Benefits of Mobile Broadband for Rural Areas

Broadband is becoming increasingly important to national economies and the personal lives of users. However, broadband availability and adoption are not diffusing in rural and urban areas at the same rates. This article updates the rural broadband digital divide, with special attention paid to mobility. Empirical estimations of broadband provision and usage in the US show that rural areas have fewer high-speed fixed and mobile providers but more slower-speed fixed providers than urban areas. While rural availability of mobile broadband is lower than in urban areas, it still helps fill in gaps in fixed broadband coverage in rural areas. The rural gap in fixed broadband usage remains, but the mobile broadband usage gap disappears after controlling for household demographics. The raw broadband usage gaps between rural and urban households are proportionally greater for low-income households. The potential for mobile broadband to benefit rural areas through economic development is also examined.
Improved Adaptive Signal Power Loss Prediction Using Combined Vector Statistics Based Smoothing and Neural Network Approach

Predicting signal power loss between the transmitter and receiver with minimal error is an important issue in telecommunication network planning and optimization process. In recent years, median order statistic filters have been exploited as a preprocessing constituent for analyzing signals. This work presents a resourceful predictive model, built on multi-layer perceptron (MLP) network with vector order statistic filter based preprocessing technique for improved prediction of measured signal power loss in a microcellular LTE network environment. The predictive model is termed Vector statistic filters multilayer perceptron (VSF-MLP). In terms of some essential performance evaluation indices such as the correlation coefficient, root-mean-square error and coefficient of efficiency, results show that VSFMLP model prediction performs considerably better than the standard MLP model prediction approach on signal power data collected from different study locations in typical urban terrain.
DENTAL STATUS OF NON-CONTACT SPORTS ATHLETES

Th e health of athletes plays an important role in the training process; it directly aff ects the body’s response to physical activity, and athletic performance and results (1-3). Intense physical and psycho-emotional activities can cause the overtraining syndrome, aff ecting both the training process eff ectiveness and the health of the athlete (4-6). Signifi cant physical and psycho-emotional activities deplete the body, aff ect the metabolism level, lead to an immunity decrease and contribute to suppression of the overall reactivity of the body. Th is may lead to the protein and electrolyte metabolism disorder, shift ing the acid-base balance towards metabolic acidosis with respiratory alkalosis, the loss of calcium, phosphorus, potassium and fl uorine. As a result, saliva acidity is increasing, and in combination with immunosuppression the microbial metabolism of the mouth is changing, creating conditions for demineralization of tooth enamel and reduced blood fl ow in the salivary glands (1,7-10).
S1 Employs Feature-Dependent Differential Selectivity of Single Cells and Distributed Patterns of Populations to Encode Mechanosensations

The primary somatosensory (S1) cortex plays an important role in the perception and discrimination of touch and pain mechanosensations. Conventionally, neurons in the somatosensory system including S1 cortex have been classified into low/high threshold (HT; non-nociceptive/nociceptive) or wide dynamic range (WDR; convergent) neurons by their electrophysiological responses to innocuous brush-stroke and noxious forceps-pinch stimuli. Besides this “noxiousness” (innocuous/noxious) feature, each stimulus also includes other stimulus features: “texture” (brush hairs/forceps-steel arm), “dynamics” (dynamic stroke/static press) and “intensity” (weak/strong). However, it remains unknown how S1 neurons inclusively process such diverse features of brushing and pinch at the single-cell and population levels. Using in vivo two-photon Ca2+ imaging in the layer 2/3 neurons of the mouse S1 cortex, we identified clearly separated response patterns of the S1 neural population with distinct tuning properties of individual cells to texture, dynamics and noxiousness features of cutaneous mechanical stimuli. Among cells other than broadly tuned neurons, the majority of the cells showed a highly selective response to the difference in texture, but low selectivity to the difference in dynamics or noxiousness. Between the two low selectivity features, the difference in dynamics was slightly more specific, yet both could be decoded using the response patterns of neural populations. In addition, more neurons are recruited and stronger Ca2+ responses are evoked as the intensity of forceps-pinch is gradually increased. Our results suggest that S1 neurons encode various features of mechanosensations with feature-dependent differential selectivity of single cells and distributed response patterns of populations. Moreover, we raise a caution about describing neurons by a single stimulus feature ignoring other aspects of the sensory stimuli.
Transcriptome Analysis on Maternal Separation Rats With Depression-Related Manifestations Ameliorated by Electroacupuncture

Maternal separation (MS), a stressful event in early life, has been linked to neuropsychiatric disorders later in life, especially depression. In this study we investigated whether treatment with electroacupuncture (EA) could ameliorate depression-related manifestations in adult animals that had adverse early life experiences. We demonstrated depression-like behavior deficiencies in a sucrose preference test and a forced swimming test in a rat model with neonatal MS. Repeated EA treatment at the acupoints Baihui (GV20) and Yintang (GV29) during adulthood was shown to be remarkably attenuated above behavioral deficits. Using unbiased genome-wide RNA sequencing to investigate alterations in the transcriptome of the prefrontal cortex (PFC), we explored the altered gene sets involved in circadian rhythm and neurotransmitter transporter activity in MS rats, and their expression tended to be reversed after EA treatment. In addition, we analyzed the interaction network of differentiated lncRNA– or circRNA–miRNA–mRNA by using the principle of competitive endogenous RNA (ceRNA). These results suggest that EA at GV20 and GV29 ameliorates depression-related manifestations by regulating the expression of multiple genes.
Resilience in Cancer Patients

Background: Being diagnosed with cancer and undergoing its treatment are associated with substantial distress that can cause long-lasting negative psychological outcomes. Resilience is an individual’s ability to maintain or restore relatively stable psychological and physical functioning when confronted with stressful life events and adversities. Posttraumatic growth (PTG) can be defined as positive life changes that result from major life crises or stressful events. Objectives: The aims of this study were to 1) investigate which factors can strengthen or weaken resilience and PTG in cancer patients and survivors; 2) explore the relationship between resilience and PTG, and mental health outcomes; and 3) discuss the impact and clinical implications of resilience and PTG on the process of recovery from cancer. Methods: A literature search was conducted, restricted to PubMed from inception until May 2018, utilizing the following key words: cancer, cancer patients, cancer survivors, resilience, posttraumatic growth, coping, social support, and distress. Results: Biological, personal, and most importantly social factors contribute to cancer patients’ resilience and, consequently, to favorable psychological and treatment-related outcomes. PTG is an important phenomenon in the adjustment to cancer. From the literature included in this review, a model of resilience and PTG in cancer patients and survivors was developed. Conclusions: The cancer experience is associated with positive and negative life changes. Resilience and PTG are quantifiable and can be modified through psychological and pharmacological interventions. Promoting resilience and PTG should be a critical component of cancer care.
Impostor Phenomenon Measurement Scales: A Systematic Review

The impostor phenomenon is a pervasive psychological experience of perceived intellectual and professional fraudulence. It is not a diagnosable condition yet observed in clinical and normal populations. Increasingly, impostorism research has expanded beyond clinical and into applied settings. However, to date, a systematic review examining the methodological quality of impostorism measures used to conduct such research has yet to be carried out. This systematic review examines trait impostor phenomenon measures and evaluates their psychometric properties against a quality assessment framework. Systematic searches were carried out on six electronic databases, seeking original empirical studies examining the conceptualization, development, or validation of self-report impostor phenomenon scales. A subsequent review of reference lists also included two full-text dissertations. Predetermined inclusion and exclusion criteria were specified to select the final 18 studies in the review sample. Of the studies included, four measures of the impostor phenomenon were identified and their psychometric properties assessed against the quality appraisal tool—Clance Impostor Phenomenon Scale, Harvey Impostor Scale, Perceived Fraudulence Scale, and Leary Impostor Scale. The findings often highlighted that studies did not necessarily report poor psychometric properties; rather an absence of data and stringent assessment criteria resulted in lower methodological ratings. Recommendations for future research are made to address the conceptual clarification of the construct's dimensionality, to improve future study quality and to enable better discrimination between measures.
The Central Complex as a Potential Substrate for Vector Based Navigation

Insects use path integration (PI) to maintain a home vector, but can also store and recall vector-memories that take them from home to a food location, and even allow them to take novel shortcuts between food locations. The neural circuit of the Central Complex (a brain area that receives compass and optic flow information) forms a plausible substrate for these behaviors. A recent model, grounded in neurophysiological and neuroanatomical data, can account for PI during outbound exploratory routes and the control of steering to return home. Here, we show that minor, hypothetical but neurally plausible, extensions of this model can additionally explain how insects could store and recall PI vectors to follow food-ward paths, take shortcuts, search at the feeder and re-calibrate their vector-memories with experience. In addition, a simple assumption about how one of multiple vector-memories might be chosen at any point in time can produce the development and maintenance of efficient routes between multiple locations, as observed in bees. The central complex circuitry is therefore well-suited to allow for a rich vector-based navigational repertoire.
Workplace Violence Among Frontline Clinicians in Emergency Departments Amidst the COVID-19 Pandemic

Background: Frontline clinicians working in the emergency department (ED) were at disportionate risk of workplace violence (WPV). This study investigated the prevalence of WPV and its association on quality of life (QOL) among this population in China during the COVID-19 pandemic.Results: The overall prevalence of WPV was 29.2% (95%CI: 26.5%-31.9%). Multiple logistic regression analysis revealed that having family/friends/colleagues infected with COVID-19 (OR=1.81, P=0.01), current smoking status (OR=3.24, P<0.01) and severity of anxiety symptoms (OR=1.13, P<0.01) were positively associated with WPV. Working in inpatient ED units (OR=0.45, P<0.01) was negatively associated with WPV. After controlling for covariates, clinicians experiencing WPV had a lower overall QOL compared to those without (F (1, 1103) =14.2, P<0.01). Conclusions: Prevalence of workplace violence was common among ED clinicians in China during the COVID-19 pandemic. Considering the negative impact of WPV on QOL and care quality, timely preventive measures should be undertaken for ED clinicians.
Treadmill Exercise Decreases Aβ Deposition and Counteracts Cognitive Decline in APP/PS1 Mice, Possibly via Hippocampal Microglia Modifications

Recent studies have suggested that exercise may be beneficial for delaying or attenuating Alzheimer’s disease (AD). However, the underlying mechanisms were not clear. Microglia-mediated neuroinflammation is suggested to play an important role in the pathology of AD. The present study investigated the beneficial effects of treadmill exercise on amyloid-β (Aβ) deposition and cognitive function in amyloid precursor protein (APP)/PS1 mice in the early stage of AD progression and microglia-mediated neuroinflammation was mainly analyzed. The results demonstrated that 12 weeks of treadmill exercise preserved hippocampal cognitive function in APP/PS1 mice and substantially suppressed Aβ accumulation in the hippocampus. Treadmill exercise significantly inhibited neuroinflammation, which was characterized by a remarkably reduced expression of pro-inflammatory factors and increased expression of anti-inflammatory mediators in the hippocampus, resulting from a shift in activated microglia from the M1 to M2 phenotype. Treadmill exercise also attenuated oxidative stress presented by a marked reduction in methane dicarboxylic aldehyde (MDA) level and dramatically elevated SOD and Mn-SOD activities in the hippocampus. These findings suggest that treadmill exercise can effectively prevent the decrease in hippocampal-dependent cognitive function and Aβ deposits in early AD progression possibly via modulating microglia-mediated neuroinflammation and oxidative stress.
Nested Dilation Networks for Brain Tumor Segmentation Based on Magnetic Resonance Imaging

Aim: Brain tumors are among the most fatal cancers worldwide. Diagnosing and manually segmenting tumors are time-consuming clinical tasks, and success strongly depends on the doctor's experience. Automatic quantitative analysis and accurate segmentation of brain tumors are greatly needed for cancer diagnosis. Methods:This paper presents an advanced three-dimensional multimodal segmentation algorithm called nested dilation networks (NDNs). It is inspired by the U-Net architecture, a convolutional neural network (CNN) developed for biomedical image segmentation and is modified to achieve better performance for brain tumor segmentation. Thus, we propose residual blocks nested with dilations (RnD) in the encoding part to enrich the low-level features and use squeeze-and-excitation (SE) blocks in both the encoding and decoding parts to boost significant features. To prove the reliability of the network structure, we compare our results with those of the standard U-Net and its transmutation networks. Different loss functions are considered to cope with class imbalance problems to maximize the brain tumor segmentation results. A cascade training strategy is employed to run NDNs for coarse-to-fine tumor segmentation. This strategy decomposes the multiclass segmentation problem into three binary segmentation problems and trains each task sequentially. Various augmentation techniques are utilized to increase the diversity of the data to avoid overfitting. Results: This approach achieves Dice similarity scores of 0.6652, 0.5880, and 0.6682 for edema, non-enhancing tumors, and enhancing tumors, respectively, in which the Dice loss is used for single-pass training. After cascade training, the Dice similarity scores rise to 0.7043, 0.5889, and 0.7206, respectively. Conclusion: Experiments show that the proposed deep learning algorithm outperforms other U-Net transmutation networks for brain tumor segmentation. Moreover, applying cascade training to NDNs facilitates better performance than other methods. The findings of this study provide considerable insight into the automatic and accurate segmentation of brain tumors.
Endotype-Phenotype Patterns in Meniere's Disease Based on Gadolinium-Enhanced MRI of the Vestibular Aqueduct

Two histopathological subtypes of Meniere's disease (MD) were recently described in a human post-mortem pathology study. The first subtype demonstrated a degenerating distal endolymphatic sac (ES) in the affected inner ear (subtype MD-dg); the second subtype (MD-hp) demonstrated an ES that was developmentally hypoplastic. The two subtypes were associated with different clinical disease features (phenotypes), suggesting that distinct endotype-phenotype patterns exist among MD patients. Therefore, clinical endotyping based on ES pathology may reveal clinically meaningful MD patient subgroups. Here, we retrospectively determined the ES pathologies of clinical MD patients (n = 72) who underwent intravenous delayed gadolinium-enhanced inner ear magnetic resonance imaging using previously established indirect radiographic markers for both ES pathologies. Phenotypic subgroup differences were evidenced; for example, the MD-dg group presented a higher average of vertigo attacks (ratio of vertigo patterns daily/weekly/other vs. monthly, MD-dg: 6.87: 1; MD-hp: 1.43: 1; p = 0.048) and more severely reduced vestibular function upon caloric testing (average caloric asymmetry ratio, MD-dg: 30.2% ± 30.4%; MD-hp: 13.5% ± 15.2%; p = 0.009), while the MD-hp group presented a predominantly male sex ratio (MD-hp: 0.06:1 [f/m]; MD-dg: 1.2:1 [f/m]; p = 0.0004), higher frequencies of bilateral clinical affection (MD-hp: 29.4%; MD-dg: 5.5%; p = 0.015), a positive family history for hearing loss/vertigo/MD (MD-hp: 41.2%; MD-dg: 15.7%; p = 0.028), and radiographic signs of concomitant temporal bone abnormalities, i.e., semicircular canal dehiscence (MD-hp: 29.4%; MD-dg: 3.6%; p = 0.007). In conclusion, this new endotyping approach may potentially improve the diagnosis, prognosis and clinical decision-making for individual MD patients.
Prevention Focus Relates to Performance on a Loss-Framed Inhibitory Control Task

Information framing can be critical to the impact of information and can affect individuals differently. One contributing factor is a person’s regulatory focus, which describes their focus on achieving gains vs. avoiding losses. We hypothesized that alignment between individual regulatory focus and the framing of performance feedback as either gain or loss would enhance performance improvements from computer-based training. We measured participants’ (N = 93) trait-level regulatory focus; they then trained in a go/no-go inhibitory control task with feedback framed as gains, losses, or control feedback conditions. Some changes in performance with training (correct rejection rate and response time) were consistent with regulatory fit, but only in the loss-framed condition. This suggests that regulatory fit is more complex than cursory categorization of trait regulatory focus and feedback framing might indicate. Regulatory fit, feedback framing, and task affordances should be considered when designing feedback or including game-like feedback elements to aid computer-based training.
Eco-Friendly Iron-Humic Nanofertilizers Synthesis for the Prevention of Iron Chlorosis in Soybean (Glycine max) Grown in Calcareous Soil

Iron deficiency is a frequent problem for many crops, particularly in calcareous soils and iron humates are commonly applied in the Mediterranean basin in spite of their lesser efficiency than iron synthetic chelates. Development and application of new fertilizers using nanotechnology are one of the potentially effective options of enhancing the iron humates, according to the sustainable agriculture. Particle size, pH, and kinetics constrain the iron humate efficiency. Thus, it is relevant to understand the iron humate mechanism in the plant–soil system linking their particle size, characterization and iron distribution in plant and soil using 57Fe as a tracer tool. Three hybrid nanomaterials (F, S, and M) were synthesized as iron-humic nanofertilizers (57Fe-NFs) from leonardite potassium humate and 57Fe used in the form of 57Fe(NO3)3 or 57Fe2(SO4)3. They were characterized using Mössbauer spectroscopy, X-ray diffraction (XRD), extended X-ray absorption fine structure spectroscopy (EXAFS), transmission electron microscopy (TEM) and tested for iron availability in a calcareous soil pot experiment carried out under growth chamber conditions. Three doses (35, 75, and 150 μmol pot-1) of each iron-humic material were applied to soybean iron deficient plants and their iron nutrition contributions were compared to 57FeEDDHA and leonardite potassium humate as control treatments. Ferrihydrite was detected as the main structure of all three 57Fe-NFs and the plants tested with iron-humic compounds exhibited continuous long-term statistically reproducible iron uptake and showed high shoot fresh weight. Moreover, the 57Fe from the humic nanofertilizers remained available in soil and was detected in soybean pods. The Fe-NFs offers a natural, low cost and environmental option to the traditional iron fertilization in calcareous soils.