Miracle-dz/UniFAR-FTUs huggingface dataset:
Who Moved The Market? Analyzing The Role Of Federal Reserve Speeches

We quantify the sentiment from central bank speeches of five leading developed nations (US, UK, Japan, France, and Germany) and analyze their role in explaining the return of stock market indices for the respective nations. In this study we improve upon existing sentiment quantification techniques by introducing two innovations: (i) by introducing the sentence as the unit of analysis, and (ii) by introducing "valence shifters", which assign appropriate weights to adjectives and adverbs. We demonstrate that our modified sentiment extractor is a more effective explanatory variable as compared to both direct measures (Consumer Confidence Indices) as well as indirect measures (Baker and Wurgler Index).
2D and 3D patient's representation of simulated restorative esthetic outcomes using different computer-aided design software programs: A systematic review.

OBJECTIVE To review the techniques and available 2D and 3D computer-aided design (CAD) software programs to perform a diagnostic waxing for restorative procedures when cone beam computed tomography is not indicated. OVERVIEW An electronic review was performed in Medline, Embase, and Scopus search engines. A manual search was also conducted. The articles evaluating methods to obtain a 2D or 3D patient's representation for restorative dental procedures were included. A total of 33 articles were included for full text review. CAD programs provide the capability to integrate facial features from 2D photographs or 3D facial scans and facilitate facially driven digital diagnostic waxing procedures. Diagnostic and design tools varied among the programs, and multiple technique descriptions were found. However, the literature evaluating the accuracy of virtual patients and the perception variations between the 2D and 3D dimensional representations is limited. CONCLUSIONS The integration of digital technologies into treatment planning procedures introduce variation into the conventional interfaces; however, the concepts remain the same. Further studies are needed to evaluate the accuracy of the virtual representations and the influence of the type of dimensional representation on the esthetic perceptions among dental professionals. CLINICAL SIGNIFICANCE The 2D and 3D CAD software programs facilitate the integration of facial features into digital diagnostic waxing procedures; however, the esthetic perception of the patient's virtual representation might vary among the different systems.
THE IMPACT OF COVID-19 ON EUROPEAN FINANCIAL MARKETS AND ECONOMIC SENTIMENT

COVID-19 pandemic created a lot of challenges not only for society but also for financial markets and economics. Various authors analysed different financial crisis and discussed spillover effects using two different approaches of micro and macro level. The main object of this study is to identify the relationship between COVID-19 pandemic, financial markets and economic sentiment. Authors analysed the main impact of COVID-19 pandemic using two different frameworks: micro and macro. Micro-level is focused on the sentiment of different sectors and the macro level is focused on broad economic sentiment and tendencies in financial markets. The object of the research is the European financial markets and economies. Based on the research results, it became obvious that different countries react in different ways to the COVID-19 pandemic. Also different tendencies in the construction sector compared with broad economic sentiment have been noticed. The research has shown that the mood of consumers is not as volatile as in the business segment.
Radar-Spectrogram-Based UAV Classification Using Convolutional Neural Networks

With the upsurge in the use of Unmanned Aerial Vehicles (UAVs) in various fields, detecting and identifying them in real-time are becoming important topics. However, the identification of UAVs is difficult due to their characteristics such as low altitude, slow speed, and small radar cross-section (LSS). With the existing deterministic approach, the algorithm becomes complex and requires a large number of computations, making it unsuitable for real-time systems. Hence, effective alternatives enabling real-time identification of these new threats are needed. Deep learning-based classification models learn features from data by themselves and have shown outstanding performance in computer vision tasks. In this paper, we propose a deep learning-based classification model that learns the micro-Doppler signatures (MDS) of targets represented on radar spectrogram images. To enable this, first, we recorded five LSS targets (three types of UAVs and two different types of human activities) with a frequency modulated continuous wave (FMCW) radar in various scenarios. Then, we converted signals into spectrograms in the form of images by Short time Fourier transform (STFT). After the data refinement and augmentation, we made our own radar spectrogram dataset. Secondly, we analyzed characteristics of the radar spectrogram dataset with the ResNet-18 model and designed the ResNet-SP model with less computation, higher accuracy and stability based on the ResNet-18 model. The results show that the proposed ResNet-SP has a training time of 242 s and an accuracy of 83.39%, which is superior to the ResNet-18 that takes 640 s for training with an accuracy of 79.88%.
A new approach for seasonal pattern: is it related to bipolarity dimension? Findings from an Italian multicenter study

Abstract Objective The aims of this study were to assess the impact of seasonal pattern on several clinical dimensions in inpatients with a current major depressive episode and to evaluate clinical differences between unipolar and bipolar depression according to seasonal pattern. Methods Study participants were 300 patients affected by major depressive disorder (MDD) or bipolar disorder (BD) currently experiencing a major depressive episode (MDE) and were recruited at three University Medical Centres in Italy. All study subjects completed several evaluation scales for depressive and hypomanic symptoms, quality of life and functioning, impulsiveness, and seasonal pattern. Results Several differences between BD with and without seasonal pattern, MDD with and without seasonal pattern but in particular between BD and MDD with seasonal pattern were found. Patients with MDE with seasonal pattern had more frequently received a longitudinal diagnosis of BD. Conclusions A large number of patients with BD and seasonal pattern, but also a considerable number of patients with MDD and seasonal pattern, endorsed manic items during a current MDE. Seasonal pattern should be associated with a concept of bipolarity in mood disorders and not only related to bipolar disorder. A correct identification of seasonal patterns may lead to the implementation of personalised pharmacological treatment approaches. KEY POINTS High prevalence of mixed features in mood disorders with seasonal pattern, supporting the need for a dimensional approach to major depressive disorder and bipolar disorder. Significant percentage of patients with a primary diagnosis of major depressive disorder had seasonal pattern. Significant percentage of patients with a primary diagnosis of major depressive disorder reported (hypo)manic symptomatology.
The Effects of Physicochemical Parameters on Analysed Soil Enzyme Activity from Alice Landfill Site

The soil pollution as a product of xenobiotics, industrial action, agricultural chemicals, or inappropriate disposal of waste can change the natural environment of soil indices and trigger life-threatening situations. Soil enzyme activity is the suitable bio-indicator or parameter for monitoring soil pollution due to their sensitivity that quickly responds to any soil disturbances. Also, they are known to play an essential role in maintaining soil health and a quality environment. This study aimed to determine the levels of enzyme activity in soil from polluted and unpolluted sites and study the relationship between the physicochemical properties and soil enzyme activity to manage soil pollution. Four selected enzymes (Urease, Invertase, Catalase, and Phosphatase) were examined for their activity from forty samples using the assay method for 24 h; the colorimetry spectrophotometer measured their activity. The obtained data revealed that Invertase activity was a predominant enzyme in all soil samples. Whereas, the urease activity had obtained in low amounts for all collection sites, especially on Site A1. Soil pH had discovered to range between 5.8 and 8.51, moisture content values recorded to vary from 0.12% to 9.09%, and soil organic carbon recorded to fluctuate between 0.08% and 1.54%. Urease and phosphatase activity correlated positively with all soil physicochemical properties except for moisture content, which correlated negatively (r = −0.297; p ≥ 0.05). The invertase activity negatively associated all soil physicochemical properties, excluding the moisture content that correlated positively and significantly with invertase activity. We noted that the dumpsite soil contains low enzyme activity levels, which might attribute to the type of waste disposed off. Also, only the phosphatase activity reported correlating positively with all examined physicochemical parameters entirely.
Social anxiety is associated with BNST response to unpredictability

Anxiety disorders are highly prevalent and cause substantial suffering and impairment. Whereas the amygdala has well‐established contributions to anxiety, evidence from rodent and nonhuman primate models suggests that the bed nucleus of the stria terminalis (BNST) may play a critical, and possibly distinct, role in human anxiety disorders. The BNST mediates hypervigilance and anticipatory anxiety in response to an unpredictable or ambiguous threat, core symptoms of social anxiety, yet little is known about the BNST's role in social anxiety.
Platelet-rich clots as identified by Martius Scarlet Blue staining are isodense on NCCT

Background Current studies on clot characterization in acute ischemic stroke focus on fibrin and red blood cell composition. Few studies have examined platelet composition in acute ischemic stroke clots. We characterize clot composition using the Martius Scarlet Blue stain and assess associations between platelet density and CT density. Materials and method Histopathological analysis of the clots collected as part of the multi-institutional STRIP registry was performed using Martius Scarlet Blue stain and the composition of the clots was quantified using Orbit Image Analysis (www.orbit.bio) machine learning software. Prior to endovascular treatment, each patient underwent non-contrast CT (NCCT) and the CT density of each clot was measured. Correlations between clot components and clinical information were assessed using the χ2 test. Results Eighty-five patients were included in the study. The mean platelet density of the clots was 15.7% (2.5–72.5%). There was a significant correlation between platelet-rich clots and the absence of hyperdensity on NCCT, (ρ=0.321, p=0.003*, n=85). Similarly, there was a significant inverse correlation between the percentage of platelets and the mean Hounsfield Units on NCCT (ρ=−0.243, p=0.025*, n=85). Conclusion Martius Scarlet Blue stain can identify patients who have platelet-rich clots. Platelet-rich clots are isodense on NCCT.
Identifying Needs for Self-management Interventions for Adults With CKD and Their Caregivers: A Qualitative Study.

RATIONALE & OBJECTIVE Fostering the ability of patients to self-manage their chronic kidney disease (CKD), with support from caregivers and providers, may slow disease progression and improve health outcomes. However, little is known about such patients' needs for self-management interventions. We aimed to identify and describe the needs of adults with CKD and informal caregivers for CKD self-management support. STUDY DESIGN Descriptive qualitative study using semi-structured interviews and focus groups. SETTING & PARTICIPANTS 6 focus groups (37 participants) and 11 telephone interviews with adults with CKD (stages 1-5, not on renal replacement therapy) and informal caregivers from across Canada. ANALYTIC APPROACH Thematic analysis. RESULTS 3 major themes were identified: (1) empowerment through knowledge (awareness and understanding of CKD, diet challenges, medication and alternative treatments, attuning to the body, financial implications, mental and physical health consequences, travel and transportation restrictions, and maintaining work and education), (2) activation through information sharing (access, meaningful and relevant, timing, and amount), and (3) tangible supports for the health journey (family, community, and professionals). LIMITATIONS Participants were primarily white, educated, married, and English speaking, which limits generalizability. CONCLUSIONS There are opportunities to enhance CKD self-management support by addressing knowledge pertinent to living well with CKD and priority areas for sharing information and providing tangible support. Future efforts may consider the development of innovative CKD self-management support interventions based on the diverse patient and caregiver needs identified in this study.
Polypharmacy in Patients with Ovarian Cancer.

OBJECTIVE Polypharmacy has been associated with morbidity and mortality in patients with cancer. Data about polypharmacy among patients with ovarian cancer are limited. The primary objective of this study was to evaluate polypharmacy in a cohort of patients with ovarian cancer and to assess the evolution of polypharmacy from initial presentation to 2 years posttreatment. A secondary objective was to evaluate differences in polypharmacy between a subset of patients primarily treated in our comprehensive cancer center (CCC) and our safety net hospital (SNH). METHODS Women treated for ovarian cancer between January 1, 2011, and December 31, 2016, were included. Data were abstracted from the electronic medical record. Medication safety was assessed using the established Anticholinergic Burden (ACB) scale and the Beers criteria. Statistical analyses were performed using paired t tests and Cox proportional hazards models, with significance set at p < . 05. RESULTS The study included 152 patients. The majority of patients had high-grade serous carcinoma. Hypertension was the most common medical problem. The mean number of medications at the time of diagnosis was 3.72. Paired testing demonstrated significant patient-level increases in the number medications at 2 years following initial diagnosis (4.16 vs. 7.01, p < .001). At the CCC, 47.4% of patients met criteria for polypharmacy at diagnosis compared with 19.4% at the SNH (p < .001). By 2 years postdiagnosis, 77.6% of patients at the CCC met criteria for polypharmacy compared with 43.3% at the SNH (p = .001). The use of any medications on the ACB scale (p < .001) increased significantly between initial diagnosis and 2 years for the entire population. Polypharmacy was not a significant predictor of overall survival. CONCLUSION Polypharmacy worsens as women go through ovarian cancer treatment. Both at initial presentation and at 2 years postdiagnosis, rates of polypharmacy were higher at the CCC. Polypharmacy did not have an effect on survival in this cohort. IMPLICATIONS FOR PRACTICE Awareness of escalating numbers of medications and potentially adverse interactions is crucial among women with ovarian cancer, who are at high risk for polypharmacy.
Real‐time ensemble microalgae growth forecasting with data assimilation

Accurate short‐range (e.g., 7 days) microalgae growth forecasts will be beneficial for both the production and harvesting of microalgae. This study developed an operational microalgae growth forecasting system comprised of the Huesemann Algae Biomass Growth Model (BGM), the Modular Aquatic Simulation System in Two Dimensions (MASS2) hydrodynamic model, and ensemble data assimilation (DA). The novelty of this study is the use of ensemble DA to sequentially update the BGM model's initial condition (IC) with the assimilation of measured biomass optical density to improve short‐range biomass forecasting skills. The forecasting system was run in pseudo‐real‐time and validated against observed Monoraphidium minutum 26B‐AM growth in two outdoor pond cultures located in Mesa, Arizona, United States. We found the DA forecasting system could improve the 7‐day microalgae forecasting skill by about 85% on average compared to model forecasts without DA. These results suggest the potential accuracy of biomass growth forecasts may be sufficient to inform real‐time operational decisions, such as pond operation and harvest planning, for commercial‐scale microalgae production.
Influence of surgical margin completeness on risk of local tumour recurrence in canine cutaneous and subcutaneous soft tissue sarcoma: A systematic review and meta-analysis.

The present peer-reviewed veterinary literature contains conflicting information regarding the impact of surgical margin completeness on risk of local tumour recurrence in canine soft tissue sarcoma (STS). This systematic review and meta-analysis was designed to answer the clinical question: "Does obtaining microscopically tumour-free surgical margins reduce risk for local tumour recurrence in canine cutaneous and subcutaneous STS? " A total of 486 citations were screened, 66 of which underwent full-text evaluation, with 10 studies representing 278 STS excisions ultimately included. Cumulatively, 16/164 (9.8%) of completely excised and 38/114 (33.3%) of incompletely excised STS recurred. Overall relative risk of 0.396 (95% confidence interval = 0.248-0.632) was calculated for local recurrence in STS excised with complete margins as compared to STS excised with incomplete margins. Risk of bias was judged to be low for all studies in terms of selection bias and detection bias but high for all studies in terms of performance bias and exclusion bias. The results of the present meta-analysis, coupled with the results of individual previous studies, strongly suggest that microscopically complete surgical margins confer a significantly reduced risk for local tumour recurrence in canine STS. Future studies ideally should adhere to standardized conducting and reporting guidelines to reduce systematic bias.
An investigation of power law distribution in wildebeest (Connochaetes taurinus) herds in Serengeti National Park, Tanzania

Animal group dynamics have often been studied by biologists through the use of mathematical models and statistical analyses. Wildebeest herds (Connochaetes taurinus) occur in large numbers and follow certain migration patterns throughout the year. However, it is not known whether the aggregation patterns of migrating wildebeest herds follow predictable statistical distributions. In this work, we investigated whether social interactions between individual wildebeest can generate the observed distribution patterns of herds based on empirical data of wildebeest in the Serengeti, Tanzania. We quantified the distribution of real herds by analyzing the frequency distribution of wildebeest counts in aerial survey images collected in 2015. We then used a Lagrangian model of animal interactions to simulate individual movement and herd aggregation patterns. We equipped the model with parameter values that matched empirical distributions. Our results from the empirical data analysis reveal that wildebeest herds follow a truncated power law in their aggregation patterns. We claim that this behaviour can be explained by social interactions between individual wildebeest.
FINANCIAL PERFORMANCE AGAINST STOCK PRICES IN TELECOMMUNICATION SUB SECTOR COMPANIES

The stock price is an indicator of the success of company management, so there is a need for a decision which must be of good quality. So that can be used as a reference to see the business entity/company can make an assessment by looking at the side of financial performance. Therefore, p enelitian was done in order to test and analyze the financial performance terhada p stock prices as measured by the ratio l ikuiditas by proxy current r atio , the ratio p roftabilitas by proxy return on equity , the solvency ratio by proxy of debt to asset ratio , the market ratio with the proxy of earnings per share, the ratio of activity to the proxy for total asset turnover . The population of this study is the telecommunications sub-sector companies listed on the Indonesia Stock Exchange (BEI) for the 2014-2018 period. The sample in this study using purposive sampling technique . The sample in this study were 7 companies in the telecommunications sub-sector listed on the Indonesia Stock Exchange (BEI) for the 2014-2018 period. Data used is secondary data derived from the statement of financial position (balance sheet) and a comprehensive income statement via the website . The analysis technique uses multiple linear regression analysis. The results of this study indicate that there are only two independent variables that have a positive and significant effect on stock prices. There are independent variables, namely the liquidity ratio and the activity ratio which have a positive and significant effect on the company's stock price. Meanwhile, the other independent variables, namely profitability ratio, solvency ratio and market ratio have no effect on stock prices.
An Investigation on Extrinsic and Intrinsic Rewards on Employee Retention among Gen Y: A Study in Malaysian Manufacturing Companies

The aim of this study is to investigate the relationship between extrinsic and intrinsic reward on retention among Gen Y employees in Malaysian manufacturing companies. The data was collected from 113 respondents worked in manufacturing companies located in Seri Kembangan, Selangor using questionnaires. Multiple regression analysis was conducted to test the hypotheses. The results showed both extrinsic and intrinsic reward are the factors influencing retaining Gen Y in manufacturing companies. The discussion on the analysis, limitation of the study, recommendation for future research and conclusion were discussed at the end of this study. In a nutshell, it was proven extrinsic reward and intrinsic reward has contributed to the retention of Gen Y employees.
Perspectives on Wnt Signal Pathway in the Pathogenesis and Therapeutics of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a chronic lung disease with progressive airflow limitation and functional decline. The pathogenic mechanisms for this disease include oxidative stress, inflammatory responses, disturbed protease/antiprotease equilibrium, apoptosis/proliferation imbalance, senescence, autophagy, metabolic reprogramming, and mitochondrial dysfunction. The Wnt signaling pathway is an evolutionarily conserved signaling pathway that is abnormal in COPD, including chronic bronchitis and pulmonary emphysema. Furthermore, Wnt signaling has been shown to modulate aforementioned cellular processes involved in COPD. From this perspective, we provide an updated understanding of the crosstalk between Wnt signal and these cellular processes, and highlight the crucial role of the Wnt signal during the development of COPD. We also discuss the potential for targeting the Wnt signal in future translational and pharmacological therapeutics aimed at prevention and treatment of this disease.