Miracle-dz/UniFAR-FTUs huggingface dataset:
Labour Wages, Fringe Benefit as Hedonic Motivation for Employee Workplace Behaviour in Corporate Establishment

The study assessed labour wages, fringe benefits as hedonic motivation for employee workplace behaviour. Adopting a descriptive and quantitative approach, the survey method was adopted to collect data from 436 participants from a population of 736 staff of eight selected commercial banks in cross river state, Nigeria using the purposive, proportional and simple random sampling. The instrument of data collection is the self-developed and administered questionnaire, designed in a four-point format. Data collected was analyzed using descriptive and parametric statistics. Result revealed that 72.2 per cent of bank employees believe that a good wage will improve productivity, 95.2 per cent reported that a good performance deserves good pay. All employees interviewed reported being paid overtime. 89.9 per cent reported that they go on paid leave. From the parametric analysis carried out, a significant correlation exists between labour wages, fringe benefits and employee workplace behaviour. The study recommends, amongst others, that bank management need to review their compensation packages
Online Gain-Phase Self-Calibration Method of MIMO Array Based on Statistical Characteristics of Target Angle Distribution

As a hot research topic, the gain-phase error self-calibration in MIMO radar systems has been investigated for many years. In this paper, we proposed a novel array error self-calibration method, termed online errors self-calibration based on feature learning (OES-FL). This method regards the statistical characteristics of the detected targets’ DOA as a prior knowledge and does not require the calibrated antenna subarray or external reference source to correct the array disturbances in real time. First, we analyse the monostatic MIMO signal model suffering gain-phase error. Then, we exploit the statistical characteristics of DOA of many targets for correcting gain-phase error of antenna array. Next, the gain-phase error estimation scheme based on LMS and the DOA deviation estimation method based on LSTM are proposed, respectively. Using real-life radar data collected at the integrated transportation hubs to generate simulation data, the proposed approach is shown to be effective in correcting gain-phase errors and, therefore, provides a promising model for online error self-calibration in monostatic MIMO radars.
A New Tourist Typology Proposal: Digital Nomad

It is known that the development of the internet and technology provides many conveniences to people. In particular, people can carry out their work outside the offices in different environments where they can enjoy. These environments can be a cafe or library with the necessary infrastructure, as well as a touristic destination in the country or abroad. This situation is called digital nomadism. This concept argues that people can fulfill their duties even when they are traveling without going to their workplaces. Especially during the Covid-19 pandemic period, it has been seen that most professions can be done remotely outside of the office environment. In this context, the aim of the study is to reveal the theoretical foundations of the concept of digital nomadism. In this context, the aim of the study was to reveal the theoretical foundations of the concept of digital nomadism and to evaluate digital nomadism as a tourist typology. A literature review was made using secondary data sources, and a conceptual framework was created from domestic and foreign sources related to the subject. As a result of the research, there is not study has been found in which digital nomadism, which is a new concept, is expressed as a tourist typology. In this context, comparisons with the tourist typologies of the most well-known Cohen, Plog and Smith were made and their similar and different aspects were revealed. Finally, the characteristics of digital nomadism, which is considered as a tourist typology and proposed, are determined and presented to the tourism literature.
Towards Europe's AI Strategy: Desires & Realities

: Artificial Intelligence is possibly the most talked about topic among all emerging and disruptive technologies. Being under continuous development for the last 60 years or more, AI promises to provide benefits within a number of domains, including healthcare, finance security and energy, to name only a few. In this paper, we explore stakeholder perceptions with regards to the forthcoming European AI Strategy, as expressed during the European Commission’s formal consultation process. We follow a qualitative inquiry to analyse our data and identify emerging themes. Our findings reveal six dimensions that are considered crucial for a responsible and ethical AI strategy: ecosystems; education; liability & accountability; data availability, data sufficiency & protection; and governance. We elaborate on these dimensions and develop a desires-realities framework. Our work contributes to a better understanding of stakeholder expectations from the AI strategy and holds important implications for research on addressing grey areas and overcoming the realities in the AI domain.
Acronym Identification using Transformers and Flair Framework

The amount of acronyms in texts is growing with the increase in the number of scientific articles and it is not bound only to English texts. The Acronym Extraction (AE) task aims at automatically identifying and extracting the acronyms and their long forms in the given text. To tackle the challenge of AE in different languages, this paper describes the participation of the team MUCIC in the AE shared task at the AAAI-22 Workshop on Scientific Document Understanding (SDU@AAAI-22). This shared task aims at identifying and extracting acronyms and their long forms from English, Spanish, French, Danish, Persian, and Vietnamese texts. The proposed methodology consists of data transformation using Spacy and/or other libraries depending on the language and a Flair framework to fine-tune the transformers of the corresponding languages to extract acronyms and their long-forms. For the Spanish language, the proposed methodology secured the second rank and for all other languages, the results obtained are reasonable.
Deep density estimation based on multi-spectral remote sensing data for in-field crop yield forecasting

Yield forecasting has been a central task in computational agriculture because of its impact on agricultural management from the individual farmer to the government level. With advances in remote sensing technology, computational processing power, and machine learning, the ability to forecast yield has improved substantially over the past years. However, most previous work has been done leveraging low-resolution satellite imagery and forecasting yield at the region, county, or occasionally farm-level. In this work, we use high-resolution aerial imagery and output from high-precision harvesters to predict in-field harvest values for corn-raising farms in the US Midwest. By using the harvester information, we are able to cast the problem of yield-forecasting as a density estimation problem and predict a harvest rate, in bushels/acre, at every pixel in the field image. This approach provides the farmer with a detailed view of which areas of the farm may be performing poorly so he can make the appropriate management decisions in addition to providing an improved prediction of total yield. We evaluate both traditional machine learning approaches with hand-crafted features alongside deep learning methods. We demonstrate the superiority of our pixel-level approach based on an encoder-decoder framework which produces a 5.41% MAPE at the field-level.
Evaluating the accuracy of gridded water resources reanalysis and 1 evapotranspiration products for assessing water security in ungauged basins 2

10 Achieving water security in ungauged basins is critically hindered by a lack of in situ river discharge 11 data to assess past, current and future evolution of water resources. To overcome this challenge, there 12 has been a shift toward the use of freely available satellite and reanalysis data products. However, 13 due to inherent bias and uncertainty, these secondary sources require careful evaluation to ascertain 14 their performance before being applied in ungauged basins. The objectives of this study were to 15 evaluate river discharge and evapotranspiration estimates from eight gridded water resources 16 reanalysis (WRR), six satellite-based evapotranspiration (ET) products and ET estimates derived 17 from complimentary relationship (CR-ET) across eight river basins located in Central-West Africa. 18 We also estimated the relative uncertainties in monthly basin-scale water balance evapotranspiration 19 (ET WB ) across all the basins. Results highlight strengths and weaknesses of the different WRR in 20 simulating discharge dynamics and ET across the basins. Likewise satellite-based products also show 21 some strength and weaknesses in simulating monthly ET. Analyses further revealed that the relative 22 uncertainties in monthly ET WB range from 4–25 % with a significant increase in magnitude during 23 the rainy season while river discharge appear to be the dominant source of uncertainty. Our results further revealed that the performance of the models in simulating river discharge and 25 evapotranspiration is strongly influenced by model
Sexual homicides and interpersonal violence: Expanded forensic nurse examiner roles

T is a lack of research about social support (attachment, integration, interaction) in Mozambique and sub-Saharan Africa among women victims and perpetrators of intimate partner violence (IPV) by type of abuse (psychological aggression, physical assault without/with injury, and sexual coercion). This research examines factors associated with social support (attachment, integration) in women victims and perpetrators of IPV over the 12 months prior to the research. Methods and materials: Data were collected between April 1, 2007 and March 31, 2008. They consist in consecutive cases of 1442 women aged 15-49 years-old visiting forensic services at Maputo Central Hospital (Maputo City, Mozambique) after abuse by an intimate partner. Interviews were conducted by trained female interviewers. Social support were analysed with bivariate and multivariate methods. Results: In bivariate analyses, victims and perpetrators of psychological aggression, physical assault and sexual coercion scored higher on social support than their unaffected counterparts. However, no significant differences were found among victims and perpetrators of physical assault with injury compared to their unaffected counterparts. Multiple regressions revealed that divorced/separated, widow, middle/high white-collar-worker, somatisation and control by/over partner were important factors in “predicting” social support, whereas victimization/perpetration across types were not independently connected with social support. Conclusions: In the current study, victimization and perpetration was not important factors in “predicting” social support, which is contrary to other findings. More research into the association between social support and IPV victimization/perpetration is warranted in the context of Sub-Saharan Africa, particularly Mozambique. Antonio Eugenio Zacarias, J Forensic Res 2013, 4:4 http://dx.doi. org/10.4172/2157-7145.S1. 010
Género y efectividad de la metodología enfermera en pacientes con insuficiencia cardiaca

Recent studies show that nurse intervention in health education in Heart Failure (HF) prevents decompensation in Heart Failure(HF). Furthermore, given gender differences in HF patterns, the interventions will also have different effects. Objective: To determinethe existence of possible differences in the effects of a nurse’s intervention regarding self-care based on the patient’s gender. Materialsand method: A quasi-experimental study was carried out with HF patients (129). They were selected at two different times: firstquarter’s control group (62) and second quarter’s intervention group (67). They were all assessed three times: first appointment, threeand six month check-ups. The intervention group underwent a nurse intervention during each visit, consisting of therapeutic education,control and monitoring of their HF. Results: Beginning: Systolic blood pressure in men 133.90±0.96 (DE 27.77), women 119.64±0.57(DE18.72). Caregiver 93% male, 63% female. Therapeutic approach 2.07+0.02 (DE0.20) men, 3.04+0.01 (DE 0.31) women. Final: self-care-16.00±2.08 (DE10.99) men, -9.68±2.22 (DE12.92) women. Therapeutic adherence 1.32±0.35 (DE1.83) men, 2.94±1.87 (DE10.93) women.Very similar improvements in the NOC of all patients. Conclusions: More women participated in the study than men; [1] the formershowed a higher percentage of comorbidity, smoking and alcohol consumption than women and they had an informal caregiver. As toself-care and adherence to treatment, no significant differences were found between genders, while quality of life was better in men. Afterthe intervention, the researchers found that all patients improved in terms of quality of life and NOC (Nursing outcomes classification),as did the self-care and therapeutic adherence of all participants. [2] It is worth noting that men scored twice as high in self-care, whilewomen did so in therapeutic adherence.
Election Forecast

It has often been said that forecasting elections is a dangerous business. Unlike most of what we do as political scientists, forecasting is the one area where you can be proven wrong and quite publicly at that. ' As Jay Greene's "Forewarned Before Forecast: Presidential Election Forecasting Models and the 1992 Election" article in the March 1993 issue demonstrates, forecasting elections is even a dangerous business when you are right. By Labor Day, two months before the election, I produced election forecasts from both my national and state level forecast models. Both indicated a Clinton victory of modest proportions. The national model forecast based on the second-quarter change in the economy (GNP) and the Gallup presidential trial-heat poll in early September was the most thoroughly tested of the models (Lewis-Beck 1985; Campbell and Wink 1990). Based on the sluggish economic growth of the second quarter and Clinton's lead over Bush in the early September poll, the equation predicted that Clinton would receive 52.9% of the popular twoparty vote. He actually received 53.5% of the two-party popular vote. The forecast was off by just a bit over half of a percentage point. I should note that the median error of the out-of-sample tests of the model is on the same order, plus or minus one-half of a percentage point. Moreover, to have predicted the incorrect election winner in 1992, the prediction would have had to have been three percentage points off. In the 11 out-of-sample trials, the prediction error only exceeded three percentage points once and otherwise was less than two percentage points off. Several other forecasts were equally successful. Alan Abramowitz's equation, based on the July presidential approval rating, the rate of economic growth over the first half of the year and whether the incumbent presidential party was running for more than a second term, also was right on target. His equation predicted that Clinton would win 53.7% of the vote, just two-tenths of a percentage point off. Even though Lewis-Beck and Rice incorrectly predicted a Bush victory, based on a revised and elaborated model, their original model came pretty close to the vote. Based on only July approval ratings and economic growth in the first half of the election year, the ingredients of their original model (Lewis-Beck and Rice 1984), Clinton should have been expected to win 52.7% of the twoparty popular vote, again an error of less than one percentage point. All of this is to say there were several forecasting models that were quite accurate in their 1992 forecasts. There were models that did not fare well, most notably Ray Fair's equation that primarily depended on incumbents being reelected and to a lesser degree economic conditions (Fair 1988), but with the exception of the overly elaborated Lewis-Beck and Rice model, the political science models proved to be quite accurate.
COMPARATIVE STUDY OF MAGNETOTHERAPY ACTION IN SKIN DAMAGES

BACKGROUND: Magnetic is a pulsed electromagnetic field that induces the formation of other electromagnetic fields perpendicular to their place of incidence, is a therapeutic resource of physiotherapy used for tissue repair. OBJECTIVE: The study exposes the effects of Magnetic the healing process of diabetic rats. METHODS: This was an experimental study with a sample of 30 rats, weighing between 100 and 160 g were divided into 5 groups, where each animal received on his back the application of Magnetic. There uninjured control group, without application and without diabetes with immediate sacrifice (G1); control with injury without application and without diabetes sacrificed 48 h (G2); 48h without diabetes treated and sacrificed 48 hours (G3); control with injury without application and sacrificed 48h diabetes (G4); treated with injury, with application with diabetes and sacrifice 48h (G5). RESULTS: Histological analysis showed that the G1 did not change in G2 presented mild granulation, edema, inflammation and the presence of neutrophils in the G3 observed the presence of marked granulation, lots of blood vessels and connective tissue and the formation of new vessels in the G4 edema, dense crust with neutrophils and bleeding and G5 area little edema, inflammation, presence of micro vessels, monocytes and potted red blood cells. CONCLUSION: Therefore, it was revealed that the healing process was accelerated by the application of Magnetic. Key word: Repair, Skin, Wound, Therapy
T5 Encoder Based Acronym Disambiguation with Weak Supervision

An acronym is a word formed by abbreviating a phrase by combining certain letters of words in the phrase into a single term. Acronym disambiguation task selects the correct expansion of an ambiguous acronym in a sentence among the candidate expansions in a dictionary. Although it is convenient to use acronyms, identifying the appropriate expansions of an acronym in a sentence is a difficult task in natural language processing. Based on the recent success of the large-scale pre-trained language models such as BERT and T5, we propose a binary classification model using those language models for acronym disambiguation. To overcome the limited coverage of a training data, we use a weak supervision approach to increase the training data. Specifically, after collecting sentences containing an expansion of an acronym from Wikipedia, we replace the expansion with its acronym and label the sentence with the expansion. By conducting extensive experiments, we show the effectiveness of the proposed model. Our model is placed in the top 3 models for three of four categories in SDU@AAAI-22 shared task 2: Acronym Disambiguation.
Design change prediction based on social media sentiment analysis

Abstract The use of artificial intelligence (AI) techniques to uncover customer sentiment is not uncommon. However, the integration of sentiment analysis with research in design change prediction remains an untapped potential. This paper presents a method that uses social media sentiment analysis to identify opportunities for design change and the set of product components affected by the change. The method builds on natural language processing to determine change candidates from textual data and uses dependency modeling to reveal direct and indirect change propagation paths arising from the change candidates. The method was applied in a case example where 3665 YouTube comments on a diesel engine were analyzed. Based on the results, two engine components were recommended for design change with six others predicted as likely to be affected through change propagation. The findings suggest that the method can be used to aid decision quality in product planning through a better understanding of the change impact associated with the opportunities identified.
Potential theory in conical domains

We shall denote throughout by Ω⊂≠ℝd some conical region with vertex at 0. Let Σ=Σd={x∈ℝd; [mid ]x[mid ]=1} denote the unit sphere and by ΩΣ=Σ∩Ω. Let formula here be the expression of the Laplacian in polar coordinates x=(r, σ) (r=[mid ]x[mid ], σ∈Σ) where Δr denote the corresponding r-dimensional spherical Laplacian. For d[ges ]2 we can always solve the first eigenfunction problem for ΩΣ formula here with Dirichlet boundary conditions. We shall assume throughout that ∂Ω is sufficiently regular to ensure that u is continuous up to the boundary and vanishes there. With α>0α(α+d−2)=λ the function u(x)=rαu(σ)= [mid ]x[mid ]αu(x/[mid ]x[mid ]) is then harmonic in Ω. It should be observed that α[ges ]1 if Ω is convex. If we further assume, as we shall do in this paper, that ∂Ω is Lipschitz, u(x) (x∈ℝd) is the unique, up tp multiplicative constant positive harmonic function in Ω that vanishes at the boundary ∂Ω This function is homogeneous and is called the réduite of Ω (cf. [1]). We shall denote throughout by α=degΩ the homogenity degree of u. If d=1 the réduite is u(x)≡Cx(x>0). We shall denote by b(t)∈ℝd the standard Brownian motion in ℝd and by formula here the first exit time from Ω. We shall then define the corresponding heat diffusion kernel and the corresponding ‘probability of life’ formula here
County and Township Government in 1942

During the first war year, it was to be expected that popular interest in rural local government would be subordinated, in large measure, to problems more directly connected with the national war effort. Nevertheless, vigorous prosecution of the war program has required coöperation on the part of government at all levels; and the impact of that program has been felt in various ways, both directly and indirectly, by local governmental units. Indeed, in surveying county and township government in 1942 one is inevitably impressed by the extent to which developments of the year were either the product of, or at least intensified by, wartime conditions. As in previous reviews, events will be summarized under the following headings: (1) areas; (2) organization and personnel; (3) functions; (4) finance; (5) home rule and optional charters; and (6) intergovernmental relations.
Pentraxin 3 in Cardiovascular Disease

The long pentraxin PTX3 is a member of the pentraxin family produced locally by stromal and myeloid cells in response to proinflammatory signals and microbial moieties. The prototype of the pentraxin family is C reactive protein (CRP), a widely-used biomarker in human pathologies with an inflammatory or infectious origin. Data so far describe PTX3 as a multifunctional protein acting as a functional ancestor of antibodies and playing a regulatory role in inflammation. Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and inflammation is crucial in promoting it. Data from animal models indicate that PTX3 can have cardioprotective and atheroprotective roles regulating inflammation. PTX3 has been investigated in several clinical settings as possible biomarker of CVD. Data collected so far indicate that PTX3 plasma levels rise rapidly in acute myocardial infarction, heart failure and cardiac arrest, reflecting the extent of tissue damage and predicting the risk of mortality.