Miracle-dz/UniFAR-FTUs huggingface dataset:
Creating a Common Trajectory: Shared Decision Making and Creating a Common Trajectory: Shared Decision Making and Distributed Cognition in Medical Consultations Distributed Cognition in Medical Consultations

The growing literature on shared decision making and patient centered care emphasizes the patient’s role in clinical care, but research on clinical reasoning almost exclusively addresses physician cognition. In this article, we suggest clinical cognition is distributed between physicians and patients and assess how distributed clinical cognition functions during interactions between medical professionals and patients with Multiple Sclerosis (MS). A combination of cognitive task analysis and discourse analysis reveals the distribution of clinical reasoning between 24 patients and 3 medical professionals engaged in MS management. Findings suggest that cognition was distributed between patients and physicians in all major tasks except for the interpretation of MRI results. Otherwise, patients and physicians collaborated through discourse to develop a common trajectory to guide clinical reasoning. The patients’ role in cli nical cognition expands the concept of patient-centered care and suggests the need to optimize physician-patient distributed cognition rather than physician cognition in isolation.
Impact of Microfinance on Farm Income of Small and Marginal Farmers in Western Tamil Nadu

The small and marginal farmers were more dependent on the private credit sources with higher interest rate for their family needs and timely agricultural practices. Drought, pest and disease incidence, higher input cost, less product price and non-timely availability of credit were the major reasons for indebtedness of the small and marginal farmers. In this context, microcredit through bank linkage self-help groups (SHGs) served as the credit source to the small and marginal farmers. A study was conducted on the tribal and non-tribal SHG and non-SHG members in western Tamil Nadu in order to study the impact of microfinance on income of members and non-members of self-help groups on the selected tribal and non-tribal women in the study area. In the case of tribal SHG members, income from agricultural source was Rs. 48772 compared with Rs. 29900 of non-members. The average annual income of SHG members in before operation period was Rs. 11944 and it was Rs. 21415 in after implementation period and the difference was Rs. 9471. The non-tribal SHG member’s average annual income difference between the two periods before and after implementation period was Rs. 17332.Non-follow up practices from government officials was the main problem faced by SHG members in tribal sample farmers.
Combined Diffusion Tensor Imaging and Apparent Transverse Relaxation Rate Differentiate Parkinson Disease and Atypical Parkinsonism

BACKGROUND AND PURPOSE: Both diffusion tensor imaging and the apparent transverse relaxation rate have shown promise in differentiating Parkinson disease from atypical parkinsonism (particularly multiple system atrophy and progressive supranuclear palsy). The objective of the study was to assess the ability of DTI, the apparent transverse relaxation rate, and their combination for differentiating Parkinson disease, multiple system atrophy, progressive supranuclear palsy, and controls. MATERIALS AND METHODS: A total of 106 subjects (36 controls, 35 patients with Parkinson disease, 16 with multiple system atrophy, and 19 with progressive supranuclear palsy) were included. DTI and the apparent transverse relaxation rate measures from the striatal, midbrain, limbic, and cerebellar regions were obtained and compared among groups. The discrimination performance of DTI and the apparent transverse relaxation rate among groups was assessed by using Elastic-Net machine learning and receiver operating characteristic curve analysis. RESULTS: Compared with controls, patients with Parkinson disease showed significant apparent transverse relaxation rate differences in the red nucleus. Compared to those with Parkinson disease, patients with both multiple system atrophy and progressive supranuclear palsy showed more widespread changes, extending from the midbrain to striatal and cerebellar structures. The pattern of changes, however, was different between the 2 groups. For instance, patients with multiple system atrophy showed decreased fractional anisotropy and an increased apparent transverse relaxation rate in the subthalamic nucleus, whereas patients with progressive supranuclear palsy showed an increased mean diffusivity in the hippocampus. Combined, DTI and the apparent transverse relaxation rate were significantly better than DTI or the apparent transverse relaxation rate alone in separating controls from those with Parkinson disease/multiple system atrophy/progressive supranuclear palsy; controls from those with Parkinson disease; those with Parkinson disease from those with multiple system atrophy/progressive supranuclear palsy; and those with Parkinson disease from those with multiple system atrophy; but not those with Parkinson disease from those with progressive supranuclear palsy, or those with multiple system atrophy from those with progressive supranuclear palsy. CONCLUSIONS: DTI and the apparent transverse relaxation rate provide different but complementary information for different parkinsonisms. Combined DTI and apparent transverse relaxation rate may be a superior marker for the differential diagnosis of parkinsonisms.
Waveform Simulation in PandaX-4T

Signal reconstruction through software processing is a crucial component of the background and signal models in the PandaX-4T experiment, which is a multi-tonne dark matter direct search experiment. The accuracy of signal reconstruction is influenced by various detector artifacts, including noise, dark count of photomultiplier, impurity photoionization in the detector, and other relevant considerations. In this study, we present a detailed description of a semi-data-driven approach designed to simulate the signal waveform. This work provides a reliable model for the efficiency and bias of the signal reconstruction in the data analysis of PandaX-4T. By comparing critical variables which relate to the temporal shape and hit pattern of the signals, we demonstrate a good agreement between the simulation and data.
ScholarWorks@UARK ScholarWorks@UARK

Photosynthesis in living organisms is one of the most efficient, natural energy harvesting processes on Earth. The absorption of light energy as photons directly energizes electrons in metabolite molecules. These molecules transfer their high energy electrons through a chain system to provide the energy needed for carbon dioxide metabolism. Recently, it has been a subject of debate how this energy transfer via electron transport achieved such high efficiency. One hypothesis is that this transfer system displays fundamentally quantum mechanical behaviors, such as coherence. Here, I will briefly define this concept in quantum mechanics, and explain the role it might play in excited electron energy transfer. I will also discuss alternative hypotheses proposed that claim photosynthetic energy transfer efficiency may not be explained entirely or at all by quantum coherence, as well as what all possibilities could mean for the future of quantum biology.
Vegetation control on nutrient availability and supply in high-elevation tropical Andean ecosystems

Plants absorb nutrients and water through their roots, and modulate soil biogeochemical cycles. The mechanisms of water and nutrient uptake by plants depend on climatic and edaphic conditions, as well as the plant root system. Soil solution is the 20 medium in which abiotic and biotic processes exchange nutrients, and nutrient concentrations vary with the abundance of reactive minerals and fluid residence times. High-altitude ecosystems of the tropical Andes are particularly interesting to study the association between vegetation patterns, soil hydrology and soil nutrient availability. The páramo landscape forms a vegetation mosaic of bunch-grasses, cushion-forming plants and forests. In the nutrient-depleted nonallophanic Andosols, the plant rooting depth varies with drainage and soil moisture conditions. Vegetation composition is a relevant indicator of rock-25 derived nutrient availability in soil solutions. The soil solute chemistry revealed patterns in plant available nutrients that were not mimicking the distribution of total rock-derived nutrients nor the exchangeable nutrient pool, but clearly resulted from strong biocycling of cations and removal of nutrients from the soil by plant uptake or deep leaching. Our findings have important implications for future management of Andean páramo ecosystems where vegetation type distributions are dynamically changing as a result of warming temperatures and anthropogenic disturbances. Such alterations may not only lead 30 to changes in soil hydrology and solute geochemistry but also to complex changes in weathering rates and solute export downstream with effects on nutrient availability in Andean rivers and high-mountain lakes.
The Quality Evaluation of Giant Panda's Habitat Based on Analytic Hierarchy Process

Habitat is the decisive factor for giant pandas' survival,and the protection of habitats is more important than each giant panda's conservation,which is the long-range measure for protection of pandas.The paper select three natural factors which affect the quality of giant panda's habitat and can be divided into seven evaluation indexes: origin forest,shadow-covering ration,shrub covering ration,bamboo covering ration,bamboo growing situation,slope and aspect,then calculate the weight value of seven indexes through Analytic Hierarchy Process(AHP) according to the data of the third giant pandas investigation in Shaanxi province,and overlay the seven indexes based on spatial analysis of GIS.Quality grade graph of giant panda's habitat is obtained,from which we can see that the optimum and fitting areas are mainly distributed in northeast,and the not-very fitting and incongruity areas are located in west,that is,the quality status has gradually become worse and worse from east to west.Finally we conclude that the quality status is good and is fit for giant panda's survival,and hope that the above results can offer advice and scientific basis for related wildlife nature conservation and administration office.
The Productivity Advantages of Large Cities: Distinguishing Agglomeration from Firm Selection

Firms are more productive on average in larger cities. Two main explanations have been offered: firm selection (larger cities toughen competition, allowing only the most productive to survive) and agglomeration economies (larger cities promote interactions that increase productivity), possibly reinforced by localised natural advantage. To distinguish between them, we nest a generalised version of a tractable firm selection model and a standard model of agglomeration. Stronger selection in larger cities left-truncates the productivity distribution whereas stronger agglomeration right-shifts and dilates the distribution. Using this prediction, French establishment level data, and a new quantile approach, we show that firm selection cannot explain spatial productivity differences. This result holds across sectors, city size thresholds, establishment samples, and area definitions.
Sustainable Economic Growth in Iraq: Role of Industrialization, Deforestation, Trade, Employment, Technology, and Agriculture

In the present study, the sustainable economic growth of Iraq is evaluated by analyzing six key explanatory variables, namely industrialization, deforestation, trade, employment, and agricultural expansion, which is measured by arable land. The study utilizes a time series research design spanning from 2000 to 2021. A quantitative approach was adopted, and data were collected from the World Bank database. The study utilized FMOLS (fully modified ordinary least squares) and DOLS (dynamic ordinary least squares) regression techniques to investigate the relationship. Additionally, canonical cointegrating regression (CCR) estimation was employed as a robust estimator. The results reveal significant negative effects of employment and deforestation on GDP per capita (GDPC). Industrialization also negatively impacts GDPC, while trade shows a positive influence. On the other hand, arable land does not exhibit a significant impact on GDPC. Based on the findings, the research suggests several policy implications.
A Multiple Kernel Learning based Model with Clustered Features for Cancer Stage Detection using Gene Datasets

Genomic data is used in various fields of medicine including diagnosis, prediction, and treatment of diseases. Stage detection of cancer progression is crucial for treating patients because the mortality rate of cancer is higher when it is diagnosed in the late stages. Furthermore, the type of treatment varies depending on the cancer stage. This paper presents a Multiple Kernel Learning based algorithm to predict the stage of cancer using genomic data. Because of the high dimension of genomic data, the curse of dimensionality may degrade the stage prediction. To reduce the dimension, features are clustered first in the proposed algorithm. Then, the original data samples are clustered into smaller subsets with reduced dimensions based on the computed feature clusters. Afterward, for each subset, a kernel matrix is calculated. The kernel matrices are weighted and then combined linearly. Finally, a cancer stage prediction model is trained using the combined kernel matrix and Support Vector Machine. The proposed algorithm is compared with the baseline methods. The classification accuracy of the proposed method outperforms the other methods in 13 cancer groups of 15 from the cancer genome atlas program (TCGA) dataset. doi: 10.5829/ije.2023. 36.11b. 08
Clínica y Salud

Introduction: This review focuses on social stigma associated with mental health problems in Spain in recent years. Method: A systematic search was conducted in SCOPUS, PsycInfo and Pubmed from 2010 to 2021. Twenty-six articles met inclusion criteria, and their quality was assessed following the STROBE-checklist. Results: In the Spanish population, stigmatising dynamics are detected in three dimensions of stigma: cognitive (beliefs of dangerousness, unpredictability, irresponsibility); emotional (prejudices and emotions of fear, anger, blaming for the psychological problem); and behavioural (discriminatory behaviours, avoidance, coercion). The results also show significant levels of stigma among health professionals. In contrast, those who have contact with mental health problems, or are trained in mental health, tend to show lower stigma. Conclusions: Longitudinal studies with rigorous methodology are needed to access strong empirical evidence in this field. Contact and education may be relevant factors in programming interventions, both in the general population and in health professionals.
Long‐term predictability of soil moisture dynamics at the global scale: Persistence versus large‐scale drivers

Here we investigate factors that influence the long lead time predictability of soil moisture variability using standard statistical methods. As predictors we first consider soil moisture persistence only, using two independent global soil moisture data sets. In a second step we include three teleconnection indices indicative of the main northern, tropical, and southern atmospheric modes, i.e., the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI), and the Antarctic Oscillation (AAO). For many regions results show significant skill in predicting soil moisture variability with lead times up to 5 months. Soil moisture persistence plays a key role at monthly to subseasonal time scales. With increasing lead times large‐scale atmospheric drivers become more important, and areas influenced by teleconnection indices show higher predictability. This long lead time predictability of soil moisture may help to improve early warning systems for important natural hazards, such as heat waves, droughts, wildfires, and floods.
Enzymatic evidence that the natural product N -nitroglycine is degraded by diverse bacteria

Linear nitramines (R-N(R′)NO 2 ; R′ = H or alkyl) are toxic compounds, some with environmental relevance while others are rare natural product nitramines. One of these natural product nitramines is N -nitroglycine (NNG) is produced by some Streptomyces strains and exhibits antibiotic activity towards Gram-negative bacteria. An NNG degrading heme enzyme, called NnlA, has recently been discovered in the genome of Variovorax sp. Strain JS1663 ( Vs NnlA). Evidence is presented that NnlA and therefore, NNG degradation activity is widespread. To achieve this objective, we tested characterized and tested the NNG degradation activity of five Vs NnlA homologs originating from bacteria spanning several classes and isolated from geographically distinct locations. E. coli transformants containing all five homologs converted NNG to nitrite. Four of these five homologs were isolated and characterized. Each isolated homolog exhibited similar oligomerization and heme occupancy as Vs NnlA. Reduction of this heme was shown to be required for NnlA activity in each homolog, and each homolog degraded NNG to glyoxylate, NO 2– and NH 4+ in accordance with observations of Vs NnlA. It was also shown that NnlA cannot degrade the NNG analog 2-nitroaminoethanol. The combined data strongly suggest that NnlA enzymes specifically degrade NNG and are found in diverse bacteria and environments. These results imply that NNG is also produced in diverse environments and NnlA may act as a detoxification enzyme to protect bacteria from exposure to NNG.
DNA Barcoding of Pest Rodents: An Approach in Integrated Rodent Pest Management

The most significant vertebrate pests in agriculture are rodents and their habitation, dispersal, mass, and productive importance differs depending upon the intake of crops, climatic seasons, and terrestrial areas across India. Molecular identification using DNA barcoding with the COI gene provides a high level of taxonomic differentiation (>95%) at the species level. An attempt was made to identify certain pest species of rodent namely Bandicota indica, Rattus rattus, Millardia meltada, and Tatera indica , from six different places through the COI gene in the context of rodent pest management program (RPM). The present study also covered the population survey, seasonal variation, and species of rodent pest morphology. The study revealed that the number of rodents seems to be equal in pre-monsoon and post-monsoon and there is a seasonal variation between the numbers of species in different localities. However, there were no morphological changes within the species. The present investigation showed that there were no intra-specific nucleotide alterations within M. meltada and T. indica and low intraspecific variation within B. indica and R. rattus at a greatest 0.3% and 0.5%, respectively. T. indica and R. rattus had the most elevated interspecific divergence, around 22%, and M. meltada and B. indica had the lowest, around 4%. The current results revealed that the COI gene’s 650 bp is accurate for the finding of major species of rodents from other species. Consequently, molecular identification of individual rodent pest species would generally assist to develop rodent pest programs by using species-specific (i
Artiﬁcial Intelligence in Medicine

Objective: Access to the vast body of research literature that is available in biomedicine and related ﬁelds may be improved by automatic summarisation. This paper presents a method for summarising biomedical scientiﬁc literature that takes into consideration the characteristics of the domain and the type of documents. Methods: To address the problem of identifying salient sentences in biomedical texts, concepts and relations derived from the Uniﬁed Medical Language System (UMLS) are arranged to construct a semantic graph that represents the document. A degree-based clustering algorithm is then used to identify different themes or topics within the text. Different heuristics for sentence selection, intended to generate different types of summaries, are tested. A real document case is drawn up to illustrate how the method works. Results: A large-scale evaluation is performed using the recall-oriented understudy for gisting-evaluation (ROUGE) metrics. The results are compared with those achieved by three well-known summarisers (two research prototypes and a commercial application) and two baselines. Our method signiﬁcantly outperforms all summarisers and baselines. The best of our heuristics achieves an improvement in performance of almost 7.7 percentage units in the ROUGE-1 score over the LexRank summariser (0.7862 versus 0.7302). A qualitative analysis of the summaries also shows that our method succeeds in identifying sentences that cover the main topic of the document and also considers other secondary or “satellite” information that might be relevant to the user. Conclusion: The method proposed is proved to be an efﬁcient approach to biomedical literature sum-marisation, which conﬁrms that the use of concepts rather than terms can be very useful in automatic summarisation, especially when dealing with highly specialised domains. © 2011 Elsevier B.V. All rights reserved.
Obstacles to cross-border tourism cooperation across the Baltic Sea as seen by Interreg stakeholders

Obstacles to cross - border tourism cooperation across the Baltic Sea as seen by Interreg stakeholders Cross - border tourism cooperation offers significant benefits, yet it faces numerous barriers and obstacles. Unfortunately, studies on cross - border cooperation across sea borders remain limited, with a lack of scientific discourse on key topics such as obstacles to cooperation. To address this gap, this paper aims to identify and discuss the main obstacles to cross - border tourism cooperation across sea borders in the Baltic Sea region. Through qualitative analysis involving 35 in - depth interviews with stake-holders representing various aspects of tourism cooperation within the EU Interreg programme and different parts of the region, 43 distinct obstacles were identified. Among these, five obstacles were consistently mentioned by a significant portion of respondents: language barriers, poor human resources, reimbursement principles of financing projects, bureaucracy, and cultural differences. The identified obstacles were categorized and discussed in relation to the existing literature on cross - border cooperation barriers. Surprisingly, the Baltic Sea itself, often perceived as a hindrance due to vast distances and limited accessibility, was not highly ranked as an obstacle by stakeholders. Instead, it was seen as both a reason and an opportunity for cooperation. The research confirmed that the most significant obstacles to tourism cross - border cooperation in the Baltic Sea region align with those found in the literature on land borders, albeit with different importance.