Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-Cultural Validation of the Portuguese Version of the Quality of Oncology Nursing Care Scale

Simple Summary Patients are the center and focus of care delivery, but frequently, their perceptions are overlooked. Patients are vital to promoting optimal oncology nursing care and should be considered in order to provide patient-centered holistic care. The Quality of Oncology Nursing Care Scale was translated and validated cross-culturally for the Portuguese context. In Portugal, there is no instrument that evaluates the quality of nursing care provided to cancer patients, so our study fills this major gap in the scientific evidence. This scale should be used by nurses, nurse managers, and researchers that strive to improve patient, nurse, and organizational outcomes. Abstract Background: Quality assessment in oncology nursing care has been a growing topic in the literature, gaining relevance as oncological nursing care becomes more complex as the science progresses. However, there are no instruments that assess the perception of the quality of oncology nursing care from the point of view of patients for the Portuguese population. Thus, the cross-cultural translation and validation of the Quality of Oncology Nursing Care Scale (QONCS) was performed for the Portuguese context. This instrument allows nurses to assess patients’ self-perception of the quality of nursing care provided in an oncological setting. It also allows researchers to compare the results obtained internationally with the application of this scale. Methods: This is a methodological study, with two distinct phases: the first corresponded to the translation and cultural adaptation of the scale to the Portuguese context, and the second consisted of the psychometric validation of the QONCS, which included factor analysis and the evaluation of the psychometric properties of the instrument. We obtained responses from 402 patients from a Portuguese oncology hospital. Results: The Portuguese version of the Quality of Oncology Nursing Care Scale (QONCS_PT) consists of 34 items inserted into a tetra-factorial model, which explains a total variance of the instrument of 69.8%. A Cronbach’s alpha of 0.93 was obtained for the complete instrument. Conclusions: QONCS_PT has a competent and reliable structure. The scale’s validity was assured and can be used in the Portuguese population, as it is useful for direct care provision but also for researchers and managers.
Design and Developments of AODV & TAODV Routing Protocols for VANETs

Ad_hoc Vehicle Networks (VANETs) are self-convening networks that are formed between shifting vehicles equipped with wireless transmission devices. This type of network develops within the framework of intelligent transit systems to achieve a significant refinement in the overall performance of the transportation system. As the foundation regarding that network will increase implementation, challenges have to be taken into account. These challenges are broadcasting, routing, precedence scheduling, safety then privacy. In this research, orientation is viewed as a research factor. Several routing protocols have been introduced and evaluated to restructure the efficiency of VANET. Follow-up research about VANETs has established that the Ad_hoc on-demand distance vector (AODV) has the very best efficiency in structure-based protocols. The research analyzes and evaluates the performance of AODV under specific node densities. Different sets of node densities are used to compare the overall performance of the mentioned protocol. Then the obtained simulation outcomes are compared among graphic shapes below specific parameters such as delay rate, on the one hand, packet size, packet loss, etc. on the other. The proposed research suggested the most useful path using the cloned routing protocol via customizing interpretation, simulation, data visualization, and results then comparative evaluation into the current AODV routing protocol and the TAODV cloned routing protocol. The objective of this research is to Unveil the Development and Design of Routing Protocols for VANETs. The result in this paper of dropped packets affects the AODV protocol during the entire lifetime of the network, but in the case of TAODV, it is only partially affected by the time the malicious node is identified and eliminated. The increased network throughput in the case of using TAODV is attributed to each node using its local table of other nodes' trust values in choosing the next hop node to establish the data path. In this paper, AODV simulations are performed on simulators with the aid of the used network simulator NS-2 which approves customers to create real-world kinetic models for VANET simulation.
Processing English Verb Phrase Ellipsis for Conversational English-Hindi Machine Translation

In this paper, we try to tackle the problem of erroneous English-Hindi machine translation (MT) outputs due to the presence of the Verb Phrase Ellipsis (VPE) in English. The phenomenon of VPE is prominent in spoken English, and the antecedent to the ellipsis can come from previous sentences in a conversation as well. MT systems translate sentences as a whole and ignore the contextual information from the previous sentences. For these two reasons, spoken English-Hindi translations suffer. We approached this problem by manually annotating 1200 two-person conversations that contain VPE and by studying how their resolution affects the translation qualities. Using our studies, we designed a rule-based system for the detection and resolution of VPE in English with the goal of improving their subsequent Hindi translation qualities. Our rule-based system is capable of the following: 1) Detection of VPE, 2) Resolution of Elided Head verb, 3) Resolution of Elided Head verb’s children, 4) Resolution of non-verbal predicates of a copula or a ’be’ main verb, 5) Modifying original sentence in the conversation with the resolved verb phrase. We also tested the system’s performance on VPE datasets outside of our annotated data. In this paper, we present our annotated corpus on conversational English VPE, our rule-based system to tackle VPE in the context of improving English-Hindi MT, the observations made as we designed this rule-based system and the performance-related observations of our system.
OPTIMIZING THE SOWING DATE AND PATTERN TO IMPROVE WHEAT PRODUCTIVITY USING A CROP GROWTH SIMULATION MODEL IN KHARGA OASIS-EGYPT

he timing and methods of sowing wheat can significantly impact its productivity, especially in the face of climate change. To investigate this, two field experiments were conducted over consecutive winter seasons in 2021/22 and 2022/23 in Kharga Oasis, Egypt. The aim was to assess the effects of five different sowing dates (30 th October, 10 th , 20 th , and 30 th of November, and 10 th of December) using four distinct sowing methods (flatbed broadcast, ridges, rows, and raised-bed) on the productivity of the wheat cultivar Giza 171. The Decision Support System for Agrotechnology Transfer (DSSAT) software was employed to simulate wheat yield. The results of the experiments revealed that planting wheat on the optimal date of 20 th November proved superior for grain yield in the first season. However, the highest grain yield in the second season was achieved with a sowing date of 10 th November, which showed no significant difference compared to the 30 th of October and 20 th of November. Among the different sowing methods, raised-bed cultivation consistently produced the highest values for most of the parameters studied in both growing seasons. Furthermore, the DSSAT model effectively simulated grain yield, total biomass, and harvest index, with the Nash-Sutcliff efficiency (NSE) values exceeding 0.75. The findings highlight the significant impact of sowing dates and patterns on wheat yield and its associated attributes. Moreover, the successful simulation of these effects by the DSSAT model further validates its usefulness in predicting the outcomes of different management practices.
Ages and sources of mantle eclogites: ID-TIMS U-Pb-Sr isotope systematics of clinopyroxene

Mantle eclogites form an integral, in cases dominant, part of most kimberlite-borne xenolith suites. They have been variously interpreted as representing the metamorphosed equivalents of underplated high-pressure melts or of subducted oceanic crust (Jacob 2004). However, it has proven notoriously difficult to extract meaningful age information from the radiogenic isotope systematics of mantle eclogites. In addition, clinopyroxene (cpx), a major carrier of incompatible lithophile elements, including the parent elements of most commonly used radioactive decay systems, is frequently altered. This can preclude separation of enough pristine material for accurate and precise analysis by common mass spectrometric techniques and hinders efforts to unravel the origins and evolution of mantle eclogites and to link their formation to regional or global tectonothermal events.
Research on Bayesian Statistics Teaching with R

Bayesian statistics uses the mathematical rules of probability to combine data with prior information to yield inferences which are always more precise than would be obtained by either source of information alone. The current Bayesian education has not yet attracted enough attention from the education community in China. The rise of MCMC and probabilistic programming languages has profoundly reshaped Bayesian statistics. Compared to precise mathematical analysis, the simulation-based teaching can help students to avoid tedious statistical calculations and cultivate Bayesian thinking.
Joint inverse estimation of fossil fuel and biogenic CO 2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO 2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO 2 fluxes and atmospheric transport errors on estimating fossil fuel CO 2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO 2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 μ mol m –2 s –1 compared to the spatially averaged anthropogenic CO 2 emissions of 5 μ mol m –2 s –1 . The presence of biogenic CO 2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO 2 measurements with 1 ppm random error in addition to total CO 2 measurements can partially compensate for the interference from biogenic CO 2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO 2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO 2 flux estimates.
Reliable Off-Resonance Correction in High-Field Cardiac MRI Using Autonomous Cardiac B0 Segmentation with Dual-Modality Deep Neural Networks

B0 field inhomogeneity is a long-lasting issue for Cardiac MRI (CMR) in high-field (3T and above) scanners. The inhomogeneous B0 fields can lead to corrupted image quality, prolonged scan time, and false diagnosis. B0 shimming is the most straightforward way to improve the B0 homogeneity. However, today’s standard cardiac shimming protocol requires manual selection of a shim volume, which often falsely includes regions with large B0 deviation (e.g., liver, fat, and chest wall). The flawed shim field compromises the reliability of high-field CMR protocols, which significantly reduces the scan efficiency and hinders its wider clinical adoption. This study aims to develop a dual-channel deep learning model that can reliably contour the cardiac region for B0 shim without human interaction and under variable imaging protocols. By utilizing both the magnitude and phase information, the model achieved a high segmentation accuracy in the B0 field maps compared to the conventional single-channel methods (Dice score: 2D-mag = 0.866, 3D-mag = 0.907, and 3D-mag-phase = 0.938, all p < 0.05). Furthermore, it shows better generalizability against the common variations in MRI imaging parameters and enables significantly improved B0 shim compared to the standard method (SD(B0Shim): Proposed = 15 ± 11% vs. Standard = 6 ± 12%, p < 0.05). The proposed autonomous model can boost the reliability of cardiac shimming at 3T and serve as the foundation for more reliable and efficient high-field CMR imaging in clinical routines.
Evaluation of AWRA-L for national drought and soil moisture monitoring

Assessing water resources and accounting for their availability and use at a regional and continental scale requires comprehensive and consistent information on water distribution, storage, availability, and use. The Australian Water Resource Assessment Modelling System (AWRAMS) provides nationally consistent and robust water balance estimates at a national to regional scale for the past and present using observations where available, and modelling otherwise. The AWRAMS uses on-ground observations and remotely sensed data sets, combined with hydrological science and computing technology, to estimate water balance fluxes and stores. This includes all major water storages, and the movement of water in and between these, at a 5 km spatial resolution and daily time step. The AWRAMS has two modelling components, one for landscape water balances (AWRA landscape model: AWRA-L) and the other for river balances (AWRA rivers model: AWRA-R). AWRA-L is a 0.05 degrees ( 5km) gridded soil and groundwater balance model which provides credible estimates of landscape water yield (runoff and baseflow), evapotranspiration, soil moisture, and aquifer recharge across Australia, specifically for retrospective Water Resource Assessment, National Water Account and soil moisture monitoring purposes. This paper evaluates the ability of the AWRA-L model to accurately characterise drought conditions according to soil moisture observations. Data from the OzNet soil moisture monitoring networks covering the Murrumbidgee catchment are used to evaluate the performance of the model over the millennium drought period (2001-2012). Multiple versions of AWRA-L are presented, highlighting the effect of input spatial fields being used. Two other national models (WaterDyn and CABLE-SLI) producing soil moisture are presented for comparison purposes.
Ground Penetrating Radar Measurements in a Controlled Vadose Zone: Influence of the Water Content

Ground penetrating radar (GPR) is a nondestructive method, which, as with other geophysical methods, has been successfully used to estimate the water content or hydraulic properties of soils. We performed GPR measurements to calibrate and compare water content estimates with actual water contents in a sand box. A vadose zone was simulated by injecting water in a sand box. We obtained four GPR data sets: for dry sand, for sand with water tables at 72‐ and 48‐cm depths, and for sand after drainage. Using the reflections (or diffractions) from the bottom of the sand box (or objects buried in the sand), mean relative dielectric permittivities were determined at several depths in the sand box. These relative dielectric permittivities were used to calculate “real” mean relative dielectric permittivities of a sand box made up of three layers (dry sand, unsaturated sand, and fully saturated sand), knowing that a layer can be subdivided into more layers depending on the depth of the reflections (or diffractions) recorded. We used three relationships between relative dielectric permittivity and the water content to estimate the mean water content for each layer. From these water contents and the known volume of sand considered, we estimated the amount of water in the sand box for each water table. Subtracting the volume obtained for dry sand from the volume obtained for the different water tables gave estimates of the variations in water quantities in the sand box; these were compared with the quantities injected in the sand box. Despite uncertainties in the determination of the mean relative dielectric permittivities, the calculated variations in water quantities were very similar to those injected in the sand box.
Artificial Intelligence Adoption in the Workplace and Its Impact on the Upskilling and Reskilling Strategies

The technology innovation, especially in the case of artificial intelligence, has significantly transformed the work processes and how they are organised and performed. Even if the adoption of advanced technologies usually leads to a higher work performance, there are risks of negative disruptions in the working systems, such as non-ethical use and social negative effects. The paper presents the results of an ethnographic research conducted by the authors, with the objective to identify the impact of the artificial intelligence adoption in the workplace on the professional knowledge and skills requirements and on the upskilling and reskilling strategies. Three different domains were considered: information technology, education
Molecular Serum Albumin Unmask Nanobio Properties of Molecular Graphenes in Shungite Carbon Nanoparticles

Serum albumin is a popular macromolecule for studying the effect of proteins on the colloidal stability of nanoparticle (NP) dispersions, as well as the protein–nanoparticle interaction and protein corona formation. In this work, we analyze the specific conformation-dependent phase, redox, and fatty acid delivery properties of bovine albumin in the presence of shungite carbon (ShC) molecular graphenes stabilized in aqueous dispersions in the form of NPs in order to reveal the features of NP bioactivity. The formation of NP complexes with proteins (protein corona around NP) affects the transport properties of albumin for the delivery of fatty acids. Being acceptors of electrons and ligands, ShC NPs are capable of exhibiting both their own biological activity and significantly affecting conformational and phase transformations in protein systems.
Spatially Referenced Decision Analysis of Long-Term Forest Management Scenarios in Southwestern Finland

Multi-criteria decision analysis (MCDA) of regional level long-term forest management scenarios was conducted by applying spatially explicit information to examine the trade-offs between ecological, economic and social impacts. Interval scale judgements were applied to mapped and numerical information jointly, while assessing the performance of alternative scenarios. The experts relied mostly on the numerical information, with which they might have been more confident and familiar. The weight elicitation was based on SMART using Swings (SMARTS) and SMART Exploiting Ranks (SMARTER). SMARTS resulted in two scenarios being quite equal either due to experts truly considering them equally important or being unconfident to express their weights applying SMARTS. SMARTER was considered more understandable, but lead to total utilities having wider range. However, impact information had a greater effect on the overall utility than the weighting. Future insights include use of dynamic approach, considering the issue more from ecosystem services point of view and tighter integration of participatory MCDA and geographic information systems (GIS).
Passivity-Based Control of Three-Phase PWM AC-DC Converters with Close to Unity Power Factor and RL Load

In the present work, a strategy is proposed to control the pulse width modulation signals of the power devices of high switching of a three-phase alternating current to direct current converter as well as the current of a load type RL guaranteeing that the power factor of the supply be the unity, which is achieved by taking advantage of the properties that the complete mathematical model has in the two-phase synchronous frame of reference. Likewise, a formal stability analysis of the complete closed-loop system is presented, thereby demonstrating that the proposed scheme guarantees global asymptotic stability with all bounded internal signals.
An integrated approach for extraction of lithology information using the SPOT 6 imagery in a heavily Quaternary‐covered region—North Baoji District of China

We studied the applicability of SPOT (Systeme Probatoire d'Observation de la Terre) 6 satellite imagery for red sandstone interpretation in the heavily loess‐covered northern Baoji District, China, which is always a crucial but challenging issue in remote sensing geological mapping. First, the non‐ or sparsely vegetated subareas were outlined in order to narrow the interpretation target area; second, band‐math and the fractal “DN‐N” (digital number‐frequency) algorithm was conducted to extract the sandstone‐associated anomalies; third, a series of spatial analysis, for example, overlaying and clumping, was employed for elimination of the false anomalies; finally, we took advantage of matched filtering to discern the non‐ (red) sandstone outcrops in local areas. Generally, the interpretation accuracy based on this novel technical proposal is acceptable—74% or slightly less (taking the geological sketch as reference criteria)—and can be well proven by field investigation. This study may have contributed a useful case study for remote‐sensing lithological mapping in the Quaternary‐covered areas.
THE ROLE OF PERSUASIVE DIALOGUE IN THE NEGOTIATION OF THE SALE OF GOODS AT SIMPUR CENTER, BANDAR LAMPUNG CITY

This study discusses the role of persuasive dialogue in negotiating the sale of goods at the Simpur Center in Bandar Lampung City. This shopping center has a significant role in meeting consumer needs and in the context of intense competition, the ability to conduct effective sales negotiations becomes important. This study uses a qualitative approach with the case study method to explore a deep understanding of how persuasive dialogue contributes to the outcome of sales negotiations. The main findings of this study include persuasive dialogue strategies used by sellers, customizing messages according to buyer profiles, managing rejection, and building customer relationships. This study shows that the seller's ability to use persuasive dialogue influences the success of sales negotiations. Tailoring messages based on local preferences and culture, as well as being able to overcome resistance with relevant solutions, also contribute to successful negotiations. Furthermore, this study emphasizes the importance of understanding local culture in persuasive dialogue, because adaptation to cultural values can strengthen communication. Persuasive dialogue plays a central role in negotiating the sale of goods at the Simpur Center in Bandar Lampung City. In a competitive environment, product knowledge, tailored persuasive dialogue strategies and the ability to manage rejection wisely are all important factors in achieving success in sales. In closing, suggestions are given to improve the seller's ability to apply effective persuasive dialogue in order to achieve success in the sales negotiation process.