Miracle-dz/UniFAR-FTUs huggingface dataset:
Addressing labour exploitation in the data science pipeline: views of precarious US-based crowdworkers on adversarial and co-operative interventions

Purpose Underlying much recent development in data science and artificial intelligence (AI) is a dependence on the labour of precarious crowdworkers via platforms such as Amazon Mechanical Turk. These platforms have been widely critiqued for their exploitative labour relations, and over recent years, there have been various efforts by academic researchers to develop interventions aimed at improving labour conditions. The aim of this paper is to explore US-based crowdworkers’ views on two proposed interventions: a browser plugin that detects automated quality control “Gold Question” (GQ) checks and a proposal for a crowdworker co-operative. Design/methodology/approach The authors interviewed 20 US-based crowdworkers and undertook a thematic analysis of collected data. Findings The findings indicate that US-based crowdworkers tend to have negative and mixed feelings about the GQ detector, but were more enthusiastic about the crowdworker co-operative. Originality/value Drawing on theories of precarious labour, this study suggests an explanation for the findings based on US-based workers’ objective and subjective experiences of precarity. The authors argue that for US-based crowdworkers “constructive” interventions such as a crowdworker co-operative have more potential to improve labour conditions.
Peran Sinyal Keuangan pada Anggaran Pendapatan dan Belanja Daerah terhadap Kinerja Pemerintah Daerah

This research aims to allocate the APBD made and planned by the Regional Government to improve the performance of the Regional Government, especially in terms of regional welfare and development. The research population is 34 provinces in Indonesia in 2019-2021. This study uses several independent variables, namely regional wealth, regional size, and capital spending to examine the relationship between the dependency variables proxied by local government performance. The study used quantitative methods with multiple regression analysis using the IBM SPSS 25 statistical test tool. The results showed that regional wealth, regional size, and spending capital had no effect on regional government performance. Keywords: APBD; Local Government Financial Performance; Regional Wealth; Local Goverment Size; Capital Expenditures
A note on M2-branes in opposite charge

The energy content of our present universe is dominated by the dark-energy, or vacuum energy, which provides accelerated cosmic expansion. Dark energy has a possible effective explanation through a positive cosmological constant. The problem present in any fundamental theory is to explain the underlying dynamics of what gives rise to the cosmological constant.In string theory there are several scenarios that could give insight into what is behind the positive cosmological constant. One such construction uses anti-branes to achieve a net positive energy density of the vacuum. Anti-branes refers in this case to branes placed in a background with oppositely charged flux. As backreaction and localisation procedures are considered for anti-brane constructions a certain kind of singularity arise. This new type of singularity is present in the surrounding flux, which is not directly sourced by the brane.This thesis, and the works contained, considers several aspects of this type of singularity. The first such flux singularity were discovered for the anti-D3-branes, in which the approximations and assumptions of partial smearing and perturbative expansions are used. Included in this thesis are new anti-D6-brane solutions which are placed in oppositely charged flux. It is shown that after the anti-D6-branes are localised, they display the same type of singularity. The strength of this result lies in that it is possible to show the presence of the singularity beyond partial smearing and perturbative expansions. Similar to the anti-D6-brane solutions, new anti-M2-brane solutions are presented. These solutions are also argued to display the same type of singularity.The investigation into the presence of the singularity is just the first step. The second step is to deduce whether this singularity is acceptable and can somehow be resolved. Included in this thesis are two works that considers exactly this. One way of interpreting the singularity is through the absence of a no-force condition between the brane and the surrounding flux. This interpretation leads to the conclusion that the singularity is present due to the use of static Ansatze in a system that is inherently time dependent. Through an adiabatic approach it is here argued that this interpretation leads to a new type of instability.Another way of arguing for a possible resolution of this singularity is whether or not the singularity can be cloaked by an event horizon. This condition have been successful in other systems with singularities. It is argued in this thesis that it is not possible to hide the flux singularity behind a horizon. This leads to one out of two conclusions, either the condition is not a necessary one and the singularity can be resolved in a static manner, or the singularity does not have a resolution.To put these works in context the current singularities from anti-branes program is briefly reviewed to give a full overview of the current situation of these investigations.
THE APPLICATION OF KINESIOTAPE IN THROMBOLIZED PATIENTS WITH ISCHEMIC STROKE

The aim of the study was to investigate and compare different kinesitherapy techniques and their impact on the recovery of patients with ischemic stroke. Also, to investigate the effect of kinesiotaping on thrombolized patients. Materials and Methods. The study was conducted in 2014-2015 at the General Hospital for Treatment in Blagoevgrad - Neurology Department. The study contingent consisted of 20 patients, 10 of whom had an ischemic stroke and underwent venous thrombolysis (experimental group). In the other ten patients, no innovation was applied (control group). Results and analysis: In patients with a brain accident, the muscles in the affected limbs are hypotonic. From a kinesitherapeutic point of view, it is very important in the hospital setting not to allow a pathological increase in muscle tone without a precondition for spasticity in the muscles and subsequent contracture. In our study, we examined the change in muscle tone using the Ashworth test. All patients were tested on the day of hospitalization, on the 5th day and on the 7th day (the day of hospitalization), on the 30th day. Discussion. Kinesio tape provides maintenance of the affected muscles and causes significant proprioceptive irritation, which helps to restore the existing motor deficit. Conclusion. We believe that the choice of methodology is extremely difficult due to the colorful clinical picture and the general condition of the patient. The combination of different methods could help the patient recover faster.
Contemporary applications of Big Data Management Information System: An Empirical study

In the field of information systems in India, big data management has become a vital area in recent years. It is necessary to efficiently store, analyze, and use this vast amount of data for actionable insights and decision-making due to the exponential growth of data generated by different sources, including social media, IoT devices, e-commerce transactions, and more. Numerous industries, including e-commerce, marketing, logistics, healthcare, finance, and more have found extensive use for big data management in India. To measure risk and make investment decisions, it is used in finance to analyze market data, consumer behavior, and investment trends. It is used in e-commerce to examine client information, purchasing patterns, and preferences for individualized suggestions and niche marketing. It is applied to logistics to increase effectiveness and optimize supply chain operations. It is employed in marketing to segment customers, analyze sentiment, and improve campaigns. These modern Big Data Management software in India have transformed industries, made it possible to make decisions based on data, and altered the operations and business strategies of companies.
Antioxidative Effects of Black Currant and Cornelian Cherry Juices in Different Tissues of an Experimental Model of Metabolic Syndrome in Rats

A Western-style diet, rich in fat and simple sugars, is the main risk factor for a significant number of chronic diseases and disorders, as well as for a progression of metabolic syndrome (MetS). One of the key mechanisms involved in MetS development is increased oxidative stress caused by the accumulation of body fat. Some dietary polyphenols have shown a protective role in preventing oxidative-stress-induced damage. We investigated the difference in the oxidative response of plasma, liver, and visceral adipose tissue in rats fed with a high-fat high-fructose (HFF) diet for ten weeks, and the effectiveness of polyphenol-rich juices (black currant (BC) and cornelian cherry (CC)) in HFF-diet-induced oxidative stress prevention. The most prominent impact of the HFF diet on redox parameters was recorded in the liver, whereas adipose tissue showed the most potent protection mechanisms against oxidative stress. Consumption of both juices decreased advanced oxidation protein product (AOPP) level in plasma, increased paraoxonase1 (PON1) activity in the liver, and significantly decreased total oxidative status (TOS) in adipose tissue. BC exerted stronger antioxidative potential than CC and decreased the superoxide anion radical (O2•−) level in the liver. It also reduced TOS, total antioxidative status (TAS), and malondialdehyde (MDA) concentration in adipose tissue. The multiple linear regression analysis has shown that the best predictors of MetS development, estimated through the increase in visceral adiposity, were superoxide dismutase (SOD), AOPP, TOS, and TAS. The consumption of polyphenol-rich juices may provide a convenient approach for the systemic reduction of oxidative stress parameters.
Medical Treatment in Heart Failure with Reduced Ejection Fraction: A Proposed Algorithm Based on the Patient’s Electrolytes and Congestion Status

In heart failure (HF) with reduced ejection fraction (HFrEF), four classes of drugs (β-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor neprilysin inhibitors, mineralocorticoid receptor antagonists, and the most recent Sodium–Glucose Co-Transporters 2 Inhibitors) have demonstrated positive results in randomized controlled trials (RCTs). Nevertheless, the latest RCTs are not proper for comparison since they were carried out at various times with dissimilar background therapies and the patients enrolled did not have the same characteristics. The difficulty of extrapolating from these trials and proposing a common framework appropriate for all cases is thus obvious. Despite the fact that these four agents are now the fundamental pillars of HFrEF treatment, the built-up algorithm of initiation and titration is a matter of debate. Electrolyte disturbances are common in HFrEF patients and can be attributed to several factors, such as the use of diuretics, renal impairment, and neurohormonal activation. We have identified several HFrEF phenotypes according to their sodium (Na+) and potassium (K+) status in a “real world” setting and suggest an algorithm on how to introduce the most appropriate drug and set up therapy based on the patients’ electrolytes and the existence of congestion.
Application of Metaheuristic Algorithms and ANN Model for Univariate Water Level Forecasting

With the rapid development of machine learning (ML) models, the artificial neural network (ANN) is being increasingly applied for forecasting hydrological processes. However, researchers have not treated hybrid ML models in much detail. To address these issues, this study herein suggests a novel methodology to forecast the monthly water level (WL) based on multiple lags of the Tigris River in Al-Kut, Iraq, over ten years. The methodology includes preprocessing data methods, and the ANN model optimises with a marine predator algorithm (MPA). In the optimisation procedure, to decrease uncertainty and expand the predicting range, the slime mould algorithm (SMA-ANN), constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithms (CPSOCGSA-ANN), and particle swarm optimisation (PSO-ANN) are applied to compare and validate the MPA-ANN model performance. Analysis of results revealed that the data pretreatment methods improved the original data quality and selected the ideal predictors’ scenario by singular spectrum analysis and mutual information methods, respectively. For example, the correlation coefficient of the first lag improved from 0.648 to 0.938. Depending on various evaluation metrics, MPA-ANN tends to forecast WL better than SMA-ANN, PSO-ANN, and CPSOCGSA-ANN algorithms with coefficients of determination of 0.94, 0.81, 0.85, and 0.90, respectively. Evidence shows that the proposed methodology yields excellent results, with a scatter index equal to 0.002. The research outcomes represent an additional step towards evolving various hybrid ML techniques, which are valuable to practitioners wishing to forecast WL data and the management of water resources in light of environmental shifts.
An Improved Model-Free Active Disturbance Rejection Deadbeat Predictive Current Control Method of PMSM Based on Data-Driven

This article proposes an improved model-free active disturbance rejection deadbeat predictive current control(ADRDPCC) method for permanent magnet synchronous motor (PMSM) used in more electric aircraft (MEA) based on the data driven method, which is used to solve the parameter mismatch problem of deadbeat predictive current control (DPCC) and improve the performance of PMSM control system. DPCC model applied to the current loop of the MEA motor is established as the main control strategy of the system. The principle of active disturbance rejection control is combined with DPCC, and the ADRDPCC structure is formed to optimize the control strategy. A specific extended state observer (ESO) of ADRDPCC is designed to track the internal disturbance caused by parameter mismatch and the external disturbance in real time. DPCC is used as the control law of the ADRDPCC structure to predict the current and output the reference voltage based on the observation of ESO. A deep reinforcement learning model based on ADRDPCC is designed and trained based on the data-driven method. The trained model can compensate and optimize ADRDPCC based on the disturbance observed by ESO and the observed control state of PMSM. The simulated and experimental results show the superiority of the proposed method.
The Inner Ring of NGC 4736: Star Formation on a Resonant Pattern

We revise the explanation for the "expanding H II regions ring" of NGC 4736. From the analysis of long-slit spectra, we identify structures within the emission region previously reported in the literature as a single ring (former parameters: R ≈ 47″, FWHM = 21″). The H II ring is located at 35″ (1.12 kpc) galactocentric distance, and its thickness is 10″. The line width at the ring location is typical of H II regions, whereas a higher velocity dispersion (chaotic motions) is measured just outside. The location of the H II ring and of the outer stellar (300″) ring are defined by the resonances obtained from the stellar rotation curve. After modeling the surface brightness profile into the different structural components, we conclude that the massive triaxial bulge (re = 10″, (1 - b/a) ≈ 0.25) produces the galactic resonance pattern. We also find evidence for a fossil starburst nucleus of about 150 pc size. The bulge and the inner bar drive disk gas motion, causing inward movements outside the H II ring and outward just inside, thereby accumulating material to trigger star formation on the ring. In the central part the bar drives the gas toward the center, which explains the substantial amount of gas in the nucleus in spite of the presence of a fossil starburst. The peculiar motions reported in the literature in reference to the ionized gas of the H II ring can be understood as infalling gas encountering the shock waves generated by the starburst knots on the H II ring and being raised above the galaxy disk. The scenario of star formation propagating from the nucleus outward used to explain the apparent expanding motion of the Hα ring is not fully supported, in light of a comparison of the location of the Hα ring with that of the FUV ring. The FUV ring peaks at about 45″–48″, which might point to an inward-propagating star formation scenario.
Sacroiliac Joint Ankylosis Decreases Intervertebral Fusion Rate in L5/S1 Single Intervertebral Transforaminal Lumbar Interbody Fusion

Background Transforaminal lumbar interbody fusion (TLIF) is a common surgical procedure for lumbar spondylolisthesis and intervertebral foraminal stenosis. Sacroiliac joint ankylosis is also known to occur in patients without axial spondyloarthritis. When sacroiliac joint bony ankylosis occurs and sacroiliac joint mobility is lost, stresses from the lower extremities to the lumbar spine are no longer buffered and are expected to be concentrated between the fifth lumbar (L5) and the first sacral (S1) vertebrae. We hypothesized that sacroiliac joint bony ankylosis could adversely affect L5/S1 intervertebral fusion and investigated the postoperative intervertebral fusion rate in single intervertebral TLIF on L5/S1 among patients with bony ankylosis of the sacroiliac joint. Methods Seventy-two patients who had undergone TLIF in the L5/S1 single intervertebral segment since 2014 and had a follow-up of at least one year after surgery were included in the study. Seventy-two patients were divided into the following two groups for comparison: group A consisted of 17 patients with bony ankylosis of the sacroiliac joint on either side on preoperative CT, and group N consisted of 55 patients without ankylosis. We investigated the intervertebral segment fusion rate one year postoperatively. Fisher's exact tests were used for statistical analysis, with a significance level of P < 0.05. Results Twelve patients (71%) in group A and 50 patients (91%) in group N had a fusion of the L5/S1 intervertebral segment one year after TLIF surgery, with a significantly lower rate in group A (P = 0.049). Conclusions We conclude that the presence of preoperative sacroiliac joint bony ankylosis is a risk factor for postoperative intervertebral fusion failure after single-segment TLIF at L5/S1.
Screening of in vitro cytotoxicity and antioxidant potential of selected endemic plants in Turkey

In the present study, we evaluated antioxidant and cytotoxicity potentials of Astragalus tokatensis Fisch. , Helichrysum noeanum Boiss. and Stachys huber-morathii R. Bhattacharjee, endemic plant species in Turkey. We measured DPPH scavenging activity, metal chelating activity, total phenol and flavonoid contents of the extracts. In addition, the cytotoxic activities of the extracts were evaluated on human breast cancer cells (MCF-7). In the analysis of total phenol content, the water extract of S. huber-morathii had the highest value (116.34 µg gallic acid equivalent/mg extract). The highest total flavonoid content (83.39 µg quercetin equivalent/mg extract) was in the water extract of H. noeanum. Considering the DPPH scavenging and metal chelating activities, water extracts of H. noeanum (33.13 mg/L) and S. huber-morathii (49.00 mg/L) showed the lowest IC50 values. When cytotoxic activities on MCF-7 cells were examined, the water extract of H. noeanum stood out with the lowest IC50 value (96.94 mg/L).
GLOBAL WELL-POSEDNESS FOR THE KLEIN-GORDON EQUATION BELOW THE ENERGY NORM*

We study global well-posedness below the energy norm of the Cauchy problem for the Klein-Gordon equation in R n with n 3. By means of Bourgain's method along with the endpoint Strichartz estimates of Keel and Tao, we prove the H s -global well-posedness with s < 1 of the Cauchy problem for the Klein-Gordon equation. This we do by establishing a series of nonlinear a priori estimates in the setting of Besov spaces.
COVID-19 misinformation on YouTube: An analysis of its impact and subsequent online information searches for verification

Objectives COVID-19 vaccination misinformation on YouTube can have negative effects on users. Some, after being exposed to such misinformation, may search online for information that either debunks or confirms it. This study's objective is to examine the impact of YouTube videos spreading misinformation about COVID-19 vaccination and the influencing variables, as well as subsequent information seeking and its effect on attitudes toward vaccination. Methods In this observational and survey study, we used a three-group pre-test and post-tests design (N = 106 participants). We examined the effects of YouTube videos containing misinformation about COVID-19 vaccination on attitudes toward vaccination via surveys, employed screen recordings with integrated eye tracks to examine subsequent online information searches, and again surveyed participants to examine the effects of the individual searches on their attitudes. Results Receiving misinformation via video tended to have negative effects, mostly on unvaccinated participants. After watching the video, they believed and trusted less in the effectiveness of the vaccines. Internet searches led to more positive attitudes toward vaccination, regardless of vaccination status or prior beliefs. The valences of search words entered and search duration were independent of the participants’ prior attitudes. Misinforming content was rarely selected and perceived (read). In general, participants were more likely to perceive supportive and mostly neutral information about vaccination. Conclusion Misinformation about COVID-19 vaccination on YouTube can have a negative impact on recipients. Unvaccinated citizens in particular are a vulnerable group to online misinformation; therefore, it is important to take action against misinformation on YouTube. One approach could be to motivate users to verify online content by doing their own information search on the internet, which led to positive results in the study.
Job profiles for museums in the digital era: research conducted in Portugal, Italy and Greece within the Mu.SA project

Due to the increasing use of technologies in the museum sector, new job profiles are now emerging within that sector. This paper describes the key findings of the research activities carried out in Greece, Portugal and Italy within the Mu.SA – Museum Sector Alliance – project funded by the European Erasmus Plus Programme – Sector Skills Alliances. Our research addressed the questions of what skills and know-how are needed by museum professionals in the process of digital transformation of their sector and what emerging job profiles would help museums to thrive in the digital environment. The research validated four job profiles such as Digital Strategy Manager, Digital Collections Curator, Digital Interactive Experience Developer and Online Community Manager. It also showed that there are some digital and transferable competences common to the four museum job profiles, but, most importantly, that an awareness of digital culture should be developed throughout the whole of a museum's workforce.