Miracle-dz/UniFAR-FTUs huggingface dataset:
Principles, structure and application of dynamic regional sector model of Finnish agriculture

This study presents a dynamic regional sector model for Finnish agriculture (DREMFIA) to be used in evaluating the effects of different agricultural policies on production and agricultural income in Finland. Since agriculture is characterised by the long duration of investments, the economic adjustment to policy changes, like the EU integration and Agenda 2000, is likely to take a long time. Recursive programming has been used in simulating annual market reactions and economic adjustments. A process of adjustments in dis-equilibrium is assumed. The theoretical basis of the chosen modelling methodology is presented and discussed. Two versions of the model are presented. The base model assumes exogenous efficiency development, i.e. labour and capital inputs needed per hectare and animal, in agriculture. In the Finnish agriculture technical change is largely a policy variable because of the publicly financed and controlled investment aid system. Using the base model one may analyse the levels of production and income at different levels of efficiency development. The technology diffusion model used in the extended version models the change in capital invested in alternative production techniques. The change in capital is affected by the profitability of each technique, as well as the relative spread of each technique, i.e. commonly used techniques are more accessible to farmers. Hence, the new best performing techniques may only gradually replace the existing ones. In both variants, empirically validated production functions are used in determining the milk yields of dairy cows and crop yields. Feed use of animals is endogenous in the model, as is the number of animals and hectares of crops. Appropriate energy, protein, and roughage requirements of animals are included. Agricultural policy measures are modelled in detail in all 14 production regions in the model. Processing activities of 18 different dairy products have been included. Domestic and imported products are assumed imperfect substitutes (Armington assumption). It is found that Agenda 2000 results in larger grain areas and farm income in medium term, but in lower milk and beef production volumes in the long term compared to the base scenario. Also farm income will slightly decrease due to the Agenda 2000 dairy reform starting at 2005. It is also found that the long term effects of Agenda 2000 on milk production are larger if the endogenous investments are taken into account in the analysis. Index words: Agricultural sector model, policy analysis, Recursive Programming, technology diffusion, Armington assumption
Diagnostic Approach and Management of Clostridium difficile Infection

Clostridium difficile infection (CDI) was first viewed as a nosocomial infection as it is associated with antibiotics administration. But since antibiotics are more frequently to be prescribed in the community setting, clinicians should investigate the probability of all antibiotics-associated diarrhea as CDI.Diagnostic of CDI should be conducted cautiously as the manifestation of CDI varies from asymptomatic to fatal consequences and is associated with morbidity, mortality, recurrence risk, outbreak possibility, and low quality of life. Management of this infection should include infection prevention and control, stopping the offending antibiotics, and administration of specific antimicrobials.Clinicians should also recognize the risk of recurrence and the higher probability of less efficacious specific antimicrobials in each episode of recurrence.
Analysis of the Principle, Facility and State-of-art Applications of Different Types Inductive Sensor

As a matter of fact, different types of inductive sensor are widely used in various aspects. In this case, this study introduces the development history and current status of electromagnetic sensors, as well as the basic principles and future trends of different types of electromagnetic sensors. It provides a detailed introduction to the principles, structures, and measurement specifications of self-inductive sensors, differential air gap self-inductive sensors, mutual inductance sensors, and helical coil mutual inductance electromagnetic sensors. The characteristics and application scenarios of each sensor are analyzed. A comparison of the advantages and disadvantages of various electromagnetic sensors is presented. Furthermore, predictions are made regarding the future research directions and application trends of electromagnetic sensors. This study has gained a good understanding of the basic principles of various electromagnetic sensors and has learned about the selection of electromagnetic sensors for different scenarios, providing guidance for the study of new electromagnetic sensors and their practical applications.
Discovery of Garnet-humite-hornblende Schist in Ophiolite Suite and its Geological Significance in the Garzê-Litang Suture Zone

Garnet-humite-hornblende schist is discovered in ophiolite suite in the Garze-Litang suture zone by 1:50,000 regional geological survey in the Litang and Cogsum quadrangles. The schist is characterized by plastic deformation and metamorphism.This discovery gives a new evidence for oceanic crustal property of the Garze-Litang suture zone.
Research Progress of CRISPR/Cas9 Application in Rice Cultivation

Rice, being one of the world's most important staple crops, plays an important role in global food security and sustainable agriculture. The CRISPR/Cas9 gene editing technology has attracted widespread attention globally. With its precision and simplicity, rice breeding and research now heavily rely on the CRISPR gene editing method. The rice genome has been fully sequenced and intensively studied. Genome editing in rice holds great potential for variety improvement and agricultural production. In recent years, many studies have reported successful cases of gene knockout, point mutations, and targeted genome insertions using CRISPR-mediated genetic improvement strategies in rice. Using CRISPR gene editing technology to introduce new beneficial traits in rice, such as increased quality and nutritional value, disease resistance, stress tolerance, and greater control of rice growth and development has shown great potential. However, despite the broad prospects of CRISPR technology in rice, there are still many challenges and technical limitations to overcome, and issues regarding precision and safety remain unresolved. This review intended to provide an overview of the CRISPR technology's principles, methods, and researched progress in rice, as well as to analyze its possible benefits and difficulties in rice breeding while also providing information on its potential future applications.
Constructing Tumor Organoid-like Tissue for Reliable Drug Screening Using Liver-Decellularized Extracellular Matrix Scaffolds

The interplay between cells and their microenvironments plays a pivotal role in in vitro drug screening. Creating an environment that faithfully mimics the conditions of tumor cells within organ tissues is essential for enhancing the relevance of drug screening to real-world clinical scenarios. In our research, we utilized chemical decellularization techniques to engineer liver-decellularized extracellular matrix (L-dECM) scaffolds. These scaffolds were subsequently recellularized with HepG2 cells to establish a tumor organoid-like tissue model. Compared to the conventional tissue culture plate (TCP) culture, the tumor organoid-like tissue model demonstrated a remarkable enhancement in HepG2 cell growth, leading to increased levels of albumin secretion and urea synthesis. Additionally, our results revealed that, within a 3-day time frame, the cytotoxicity of doxorubicin (DOX) against cells cultured in the tumor organoid-like tissue model was notably reduced when compared to cells grown on TCPs. In contrast, there was no significant difference in the cytotoxicity of two compounds, triptolide and honokiol, both derived from traditional Chinese medicine, between TCP culture and the tumor organoid-like tissue culture, indicating a lack of substantial drug resistance. Western blotting assays further confirmed our findings by revealing elevated expressions of E-cadherin and vimentin proteins, which are closely associated with the epithelial–mesenchymal transition (EMT). These results underscored that the tumor organoid-like tissue model effectively promoted the EMT process in HepG2 cells. Moreover, we identified that triptolide and honokiol possess the capacity to reverse the EMT process in HepG2 cells, whereas DOX did not exhibit a significant effect. In light of these findings, the tumor organoid-like tissue model stands as a valuable predictive platform for screening antitumor agents and investigating the dynamics of the EMT process in tumor cells.
Impact of Training Discipline and Experience on Inhibitory Control and Cognitive Performance in Pet Dogs

Simple Summary Training experience has been shown to have positive impacts on the behaviour of dogs when solving cognitive tasks, but previous work has focused on comparing highly trained working and sporting dogs with untrained pet dogs. Here, we assessed whether training a pet dog in scent work, agility, and obedience can also improve the dog’s ability in two tasks: (1) the A-not-B task, in which a dog first learns to go to a pot on one side of a three-pot lineup to obtain a reward and then must change this behaviour to go to the pot on the opposite side; and (2) the detour task, in which a dog must navigate around a transparent barrier to obtain a visible reward. Dogs that performed better on the A-not-B task were also more likely to be successful in the detour task, showing that there is a relationship between the skills required to perform well in both tasks. Training did not affect overall performance in either task, but dogs trained in scent work showed better inhibitory control across the two tasks. This indicates that scent training for pet dogs may be beneficial in improving behaviours that require inhibition. Abstract Training experience has been shown to enhance a dog’s cognitive performance when comparing highly trained working or sporting dogs with untrained dogs. However, whether the type or level of training a pet dog receives can alter their performance in cognitive tasks requiring inhibitory control has not been assessed. Here, we tested whether pet dogs trained in scent work, agility, and obedience differ in cognitive performance. The impact of primary training discipline and combined training experience was assessed using two well-defined tasks that require inhibitory control: (1) the A-not-B task, in which dogs must inhibit a previously learned response in favour of an alternative response; and (2) the detour task, in which dogs must inhibit a direct approach to food to gain a reward. Dogs trained in scent work demonstrated higher levels of inhibitory control and persistence across the two tasks, but this did not affect individual task performance. Increased combined training experience improved learning in the A-not-B task training phase, but did not alter performance during the test phase, whereas it had no effect on success in the detour task. Overall, dogs that performed better in the A-not-B task were also more likely to succeed in the detour task, showing a relationship in the cognitive ability underpinning performance in the two tasks. The effect of the primary discipline on the behavioural phenotype shows that this should be accounted for in future studies, rather than applying the practice of partitioning dogs into highly trained vs. untrained groups.
Effect of Optimized UV-LED Technology on Modeling, Inactivation Kinetics and Microbiological Safety in Tomato Juice

This research analyzed, optimized and modeled the inactivation kinetics of pathogenic bacteria (PB1: Escherichia coli O157:H7 and PB2: Listeria monocytogenes) and determined the microbiological safety of tomato juice processed by UV-LED irradiation and heat treatment. UV-LED processing conditions were optimized using response surface methodology (RSM) and were 90% power intensity, 21 min and 273–275 nm (251 mJ/cm2) with R2 > 0.96. Using the optimal conditions, levels of PB1 and PB2 resulted a log reduction of 2.89 and 2.74 CFU/mL, respectively. The Weibull model was efficient for estimating the log inactivation of PB1 and PB2 (CFU/mL). The kinetic parameter δ showed that 465.2 mJ/cm2 is needed to achieve a 90% log (CFU/mL) reduction in PB1 and 511.3 mJ/cm2 for PB2. With respect to the scale parameter p > 1, there is a descending concave curve. UV-LED-treated tomato juice had an 11.4% lower Listeria monocytogenes count than heat-treated juice on day 28 (4.0 ± 0.82 °C). Therefore, UV-LED technology could be used to inactivate Escherichia coli O157:H7 and Listeria monocytogenes, preserving tomato juice for microbiological safety, but studies are required to further improve the inactivation of these pathogens and analyze other fruit and vegetable juices.
Use of sulfur dioxide to reduce postharvest decay and preserve the quality of fresh tomatoes

Tomatoes are an important and versatile crop with a short shelf life. Postharvest losses due to fruit decay and handling are reportedly as high as 30–50% globally; therefore, the agricultural sector would benefit from solutions that target the preservation of crops such as tomatoes. In this study, we investigated the potential use of sulfur dioxide (SO2) to provide postharvest protection against fungal decay in tomatoes whilst maintaining the quality of tomato fruit. Three tomato varieties packed as bulk (3–5 kg) cartons were exposed to SO2-generating sheets applied as either a top sheet over the fruit or a bottom sheet placed on the base of the carton before packing the fruit on the top. The results show that the application of SO2- generating sheets reduced the natural progression of decay on ‘Roma’ tomatoes by up to 60% and up to 80% on ‘Rosa’ tomatoes. Only marginal decay control was observed on ‘Round’ tomatoes. The top sheet application rendered the best results, as the application of the bottom sheet resulted in phytotoxicity in the form of SO2 damage. SO2 application reduced fruit shrivelling, especially when tomatoes were stored at higher temperatures during their shelf life. The application of SO2 on the tomatoes did not have any negative effects on fruit firmness. The results of this study provide a case to further explore the use of SO2-generating sheets on tomatoes to prevent postharvest decay. Differences in varietal physiology may be key to the successful application of this technology.
Assessing Matrix Solid-Phase Dispersion Extraction Strategies for Determining Bisphenols and Phthalates in Gilthead Sea Bream Samples

Microplastics (MPs) and nanoplastics (NPs) are widely spread in the environment, generating significant concern due to their potential impact on environmental health. Marine species usually ingest plastic fragments, mistaking them for food. Many toxic compounds, such as plastic additives that are not chemically bound to the plastic matrix, can be released from MPs and NPs and reach humans via the food chain. This paper highlights the development and validation of a straightforward solid–liquid extraction clean-up procedure in combination with a matrix solid-phase dispersion method using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) detection, enabling facile, precise, and reliable identification and quantitation of a total of six bisphenols and phthalates in gilthead sea breams. Under the optimized conditions, the developed method showed good linearity (R2 > 0.993) for all target compounds. The recoveries obtained were between 70 and 92%. The relative standard deviations (RSDs) for reproducibility (inter-day) and repeatability (intra-day) were less than 9% and 10%, respectively. The limit of detection (LOD) and limit of quantification (LOQ) for the target compounds ranged from 0.11 to 0.68 µg/kg and from 0.37 to 2.28 µg/kg, respectively. A new, efficient extraction methodology for the determination of BPA, BPS, BPF, DBP, DEP, and DHEP in gilthead seabream has been optimized and validated.
SMAP Passive Microwave Radiometer for Global River Flow Monitoring

River flow is a fundamental observable in hydrology, but there is no consistent global ground measurement network. Various types of orbital remote sensing are, therefore, well positioned to meet an important observational need, including for hydrological modeling and for understanding trends through time. In previous studies, we showed that passive microwave radiometry (PMR) can measure streamflow over selected locations around the globe with a high correlation to colocated in situ discharge observations. This article demonstrates the potential of low-frequency, L-band NASA Soil Moisture Active and Passive (SMAP) satellite observations for streamflow measurement: an unanticipated but exceptionally valuable use of this sensor. By using the fully polarimetric capability of SMAP with full Stokes parameters, we optimize the polarization combinations of the observations to retrieve accurate river hydrographs from space. Flow measurements over 150 satellite gauging reaches (SGR) are retrieved over different continents, and 14 SGRs provide comparisons to available in situ river gauging data. Results from linear correlation calculations provide coefficients of determination $r^{2}$ of approximately 0.75 for SMAP-based discharge measurements when compared to in situ streamflow observations. SMAP river observations thereby improve river gauging results compared to ESA’s Soil Moisture Ocean Salinity (SMOS) satellite L-band PMR as the analysis indicates typically lower $r^{2}$ values of approximately 0.68 for SMOS.
Final report on impact of catchment scale processes and climate change on cause-effect and recovery-chains

Catchment wide integrated basin management requires knowledge on cause-effect and recovery chains within water bodies as well as on the interactions between water bodies and categories. In the WISER WP6.4 recovery processes in rivers, lakes and estuarine and coastal waters were evaluated. The major objectives were: - to analyse and compare (cause-effect and) recovery chains within water categories based on processes and structural and functional features; - to detect commonalities among different chains in different water categories ( to compare recovery chains between water categories); - to link recovery chains to over-arching biological processes and global change; - to develop a method to combine recovery effects in a summarising ‘catchment’ metric. The main stressors studied to reach these objectives were acidification, eutrophication and hydromorphological changes.
PEG–Lipid–PLGA Hybrid Particles for Targeted Delivery of Anti-Inflammatory Drugs

Hybrid nanoparticles (HNPs) were designed by combining a PLGA core with a lipid shell that incorporated PEG–Lipid conjugates with various functionalities (-RGD, -cRGD, -NH2, and -COOH) to create targeted drug delivery systems. Loaded with a neutral lipid orange dye, the HNPs were extensively characterized using various techniques and investigated for their uptake in human monocyte-derived macrophages (MDMs) using FC and CLSM. Moreover, the best-performing HNPs (i.e., HNP-COOH and HNP-RGD as well as HNP-RGD/COOH mixed) were loaded with the anti-inflammatory drug BRP-201 and prepared in two size ranges (dH ~140 nm and dH ~250 nm). The HNPs were examined further for their stability, degradation, MDM uptake, and drug delivery efficiency by studying the inhibition of 5-lipoxygenase (5-LOX) product formation, whereby HNP-COOH and HNP-RGD both exhibited superior uptake, and the HNP-COOH/RGD (2:1) displayed the highest inhibition.
The persuasive effects of political microtargeting in the age of generative artificial intelligence

Abstract The increasing availability of microtargeted advertising and the accessibility of generative artificial intelligence (AI) tools, such as ChatGPT, have raised concerns about the potential misuse of large language models in scaling microtargeting efforts for political purposes. Recent technological advancements, involving generative AI and personality inference from consumed text, can potentially create a highly scalable “manipulation machine” that targets individuals based on their unique vulnerabilities without requiring human input. This paper presents four studies examining the effectiveness of this putative “manipulation machine. ” The results demonstrate that personalized political ads tailored to individuals’ personalities are more effective than nonpersonalized ads (studies 1a and 1b). Additionally, we showcase the feasibility of automatically generating and validating these personalized ads on a large scale (studies 2a and 2b). These findings highlight the potential risks of utilizing AI and microtargeting to craft political messages that resonate with individuals based on their personality traits. This should be an area of concern to ethicists and policy makers.
Detecção de lesões de esclerose múltipla em imagens de ressonância magnética do tipo Fluid Attenuated Inversion Recovery (FLAIR)

The white matter lesion detection is an important procedure for the diagnostic of Multiple Sclerosis in patients. As important as the detection, monitoring the progression of the disease, by calculating the volumes of the lesions, also shows itself necessary. In clinical practice, this procedure is done manually by a professional or, in many cases, only a qualitative analysis is made. The manual nature of this procedure implies in a series of deficiencies on the procedure, such as variations between diagnoses from different experts on the same subject and variation between diagnostics from the same expert to the same subject at distinct moments. Yet, the manual procedure shows itself time consuming, due the large amount of slices acquired by exam and the need for a careful analysis from the expert to quantify the lesions. In order to avoid these problems, automatic approaches for Multiple Sclerosis lesion detection and quantification using computer aided diagnostic systems are proposed. These methods, mostly, demand for the acquisition of an extra modality of magnetic resonance images, where the anatomy of the brain is evidenced, thus allowing the white matter lesion identification. This additional exam goes beyond the scope of the traditional clinical practice, which implies in additional costs and prevents the method of being applied to old exams, for monitoring the disease progression. This work proposes a method for automatic detection and segmentation of Multiple Sclerosis Lesions that uses only the modality of magnetic resonance exam adopted for clinical practice, using probabilistic atlases spatially aligned to the patient’s exams for identifying the brain structures. The results obtained through the usage of the method into a set of 24 patients and 6 healthy controls of different ages, showed that the developed method is capable of detecting white matter lesions with some precision. However, the quantification of these lesions was impaired mostly due divergences between the white matter probabilistic atlas and the real white matter region of the exams.