Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluación de Formulaciones en Aceites de Beauveria bassiana1 y Metarhizium anisopliae2 Contra Chloridea virescens F.3

Resumen. El objetivo de este trabajo fue evaluar formulaciones de Beauveria bassiana y de Metarhizium anisopliae en aceites contra larvas de Chloridea virescens “gusano del fruto”, una plaga que causa importantes pérdidas económicas de tomate en Sinaloa. Cada formulación de los hongos se hizo a una concentración de 1 × 108 conidias/ml, mezclando aceite mineral, de maíz y de soya, respectivamente, adicionando extracto de alga y un colorante protector de luz ultravioleta como adyuvantes. En el laboratorio las formulaciones de los dos hongos en aceite mineral HF2-Ma y HF1-Bb causaron mortalidad de larvas de tercer ínstar de 93.3 y 96.6 % con tiempo letal medio (TL50) de 3 días, mientras que en aceite de maíz (HF4-Ma y HF3-Bb) y de soya (HF6-Ma y HF5-Bb), la mortalidad fue de 63.3, 63.3, 50.0, y 53.3% con TL50 de 3.5 días. La formulación con solo aceite mineral causó 36.6% con TL50 de 4 días y en el control con agua no hubo mortalidad. Esto indicó que todas las formulaciones tuvieron actividad biológica para matar larvas y la mayor mortalidad se obtuvo con las conidias en aceite mineral, el tiempo letal fue más corto con los hongos en aceite mineral que con aceite vegetal y más largo con solo aceite mineral. En invernadero se usaron las formulaciones HF2-Ma y HF1-Bb, las cuales fueron asperjadas a una concentración de 3.0 × 108 conidias/ml sobre plantas de tomate var. Saladette infestadas artificialmente con larvas de segundo y tercer ínstar, causando mortalidad de 64.5% (HF2-Ma) y 50.5% (HF-Bb) con TL50 de 4 y 4.5 días. La movilidad de las larvas evitó el contacto directo con las formulaciones; sin embargo, se obtuvieron porcentajes de mortalidad de 64.5 y 50.5%, los cuales fueron altos con respecto al control (3.5%). La persistencia de las conidias en las hojas fue de 14 días, mostrando la efectividad de la formulación para matar larvas de estos instares en 4 y 4.5 días. Estos resultados se consideran promisorios para realizar estudios de control de C. virescens con la mezcla de estos hongos en aceite mineral, evaluando mortalidad de larvas más jóvenes y la producción de tomate en invernadero.
Drug-drug-gene Interactions as Mediators of Adverse Drug Reactions to Diclofenac and Statins: A Case Report and Literature Review

Abstract Concomitant treatment with drugs that inhibit drug metabolising enzymes and/or transporters, such as commonly prescribed statins and nonsteroidal anti-inflammatory drugs (NSAIDs), has been associated with prolonged drug exposure and increased risk of adverse drug reactions (ADRs) due to drug-drug interactions. The risk is further increased in patients with chronic diseases/comorbidities who are more susceptible because of their genetic setup or external factors. In that light, we present a case of a 46-year-old woman who had been experiencing acute renal and hepatic injury and myalgia over two years of concomitant treatment with diclofenac, atorvastatin, simvastatin/fenofibrate, and several other drugs, including pantoprazole and furosemide. Our pharmacogenomic findings supported the suspicion that ADRs, most notably the multi-organ toxicity experienced by our patient, may be owed to drug-drug-gene interactions and increased bioavailability of the prescribed drugs due to slower detoxification capacity and decreased hepatic and renal elimination. We also discuss the importance of CYP polymorphisms in the biotransformation of endogenous substrates such as arachidonic acid and their modulating role in pathophysiological processes. Yet even though the risks of ADRs related to the above mentioned drugs are substantially evidenced in literature, pre-emptive pharmacogenetic analysis has not yet found its way into common clinical practice.
Cocrystals of 1,3,5,7-Tetranitro-1,3,5,7-tetrazacyclooctane (HMX)

Energetic materials (energetics), including explosives, propellants, and pyrotechnics, are an important class of materials for which performance depends critically on solid-state properties such as density and stability. Cocrystallization is emerging as a strategy to enhance materials properties of new and existing energetics; however, few examples exist where the principles to enable the successful engineering of such cocrystals have been delineated. To address this need, the cocrystallization of 1,3,5,7-tetranitro-1,3,5,7-tetrazacyclooctane (HMX), a powerful and widely used explosive, was investigated. Seven cocrystals of HMX were structurally elucidated using single crystal X-ray diffraction. These cocrystal structures, in addition to three previously reported structures, reveal at least three distinct structural motifs by which HMX cocrystals form, each dictated by the electronic character and size of the cocrystal former. From these structures, general trends emerge having direct implications for coc.
HIF-1 inhibitors: differential effects of Acriflavine and Echinomycin on tumor associated CA-IX enzyme and VEGF in melanoma

Abstract Objectives To determine the effects of hypoxia-inducible factors (HIF)-1 inhibitors on carbonic anhydrase-IX (CA-IX) enzyme and vascular endothelial growth factor (VEGF) in melanoma. The HIF-1 pathway induces tumor growth and metastasis by stimulating the expression of CA-IX enzyme and VEGF proteins. Methods We evaluated the inhibition effects of Acriflavine and Echinomycin on CA-IX enzyme and VEGF in WM115 (primary) and SKMEL30 (metastatic) cell lines in normoxic and hypoxic conditions with Enzyme Linked Immunosorbent Assay. The cytotoxic activity of HIF-1 inhibitors was performed by using WST-1 assay. All experiments were performed at 450 nm using Epoch™ Microplate Spectrophotometer. Results IC50 values were observed with a concentration of 3 μmol/L for Echinomycin and Acriflavine in the WST-1 assay. Decreased CA-IX and VEGF levels were determined in both normoxia and hypoxia after inhibitors’ treatment with WM115 and SKMEL30 cell lines (p<0.05). Inhibitory effect of HIF-1 inhibitors on CA-IX and VEGF proteins was observed in cell lines WM115 and SKMEL30. Conclusions Due to the importance of our study, using HIF-1 inhibitors may be an alternative treatment for melanoma. Also to design new HIF-1 inhibitor derivatives is a promising approach for further studies targeting CA-IX enzyme and VEGF.
Effects of Three Nutrition Salts on Growth of Pleurochrysis Carterae

Pleurochrysis carterae is a species of ubiquitous planktons frequently blooming in marine area of high latitued. This paper discussed the effects of three putrition salt NaHCO_3、KNO_3and K_2HPO_4 on the growth of P.carterae with orthogonal design.Under the three concentrations of NaHCO_3(0mmol/L、2mmol/l、5mmol/l)and KNO_3(0.25 mmol/l、0.5mmol/l、0.75(mmol/l))obvioas difference was observed in the stagnant stage of P.carterae biomass and the disparity between the highest and the lowest was almost 20×10~4/ml.After analysis of variance.Value F_(90)equaled to 36.08 and 19.86. But defferent concentrations of K_2HPO_4(0.04mmol/1、0.05mmol/l、0.06mmol/l)had no obvious effect on P.carterae growth and the value F_(90) merely equaled to 5.12. At the same time,this paper discussed the growth dynamics of the algae and build mathematic equations which are 1nN_t=49.25t+[1nN_0-49.25t_0]and N_t=[Nt_o-32.61t_0]+32.61t individually after regression with data of exponential stage and stagnant stage.All these data may offer a basis for the cultivation of algae plurochrysis carterae.
Stroke in women: Is it different?

In the last decades, there has been great progress in the field of stroke. With the introduction of acute therapies (intravenous thrombolysis and intra-arterial treatment), the outcome after stroke has improved significantly. Better prevention, improved acute therapy, and acute rehabilitation improved the morbidity and mortality rate after stroke. Gender differences in risk factors and epidemiology have been known for a long time, but lately attention to gender differences in stroke has increased. The aim of this mini-review is to demonstrate gender disparities in stroke with a focus on epidemiology, specific risk factors (gender-specific and unspecific), and outcomes. The influence of some risk factors for stroke is stronger in women (atrial fibrillation and hypertension) and there are risk factors exclusive to women such as pregnancy, pregnancy-associated hypertensive disorders, oral contraceptives, and hormonal replacement treatment. Data on the impact of other risk factors are inconsistent. The worse outcome after a stroke is mainly caused by demographic characteristics in women. Specific gender research is needed to better understand gender disparities in stroke to improve prevention strategies and treatment for women.
Factors associated with early reperfusion improvement after intra-arterial fibrinolytics as rescue for mechanical thrombectomy

Objective: To identify factors associated with early angiographic reperfusion improvement (EARI) following intra-arterial fibrinolytics (IAF) after failed or incomplete mechanical thrombectomy (MT). Methods: A subset of patients treated with MT and IAF rescue after incomplete reperfusion included in the INFINITY (INtra-arterial FIbriNolytics In ThrombectomY) multicenter observational registry was analyzed. Multivariable logistic regression was used to identify factors associated with EARI. Heterogeneity of the clinical effect of EARI on functional independence (defined as modified Rankin Score ≤2) was tested with interaction terms. Results: A total of 228 patients (median age: 72 years, 44.1% female) received IAF as rescue for failed or incomplete MT and had a post-fibrinolytic angiographic control run available (50.9% EARI). A cardioembolic stroke origin (adjusted odds ratio (aOR) 3.72, 95% confidence interval (CI) 1.39–10.0) and shorter groin puncture to IAF intervals (aOR 0.82, 95% CI 0.71–0.95 per 15-min delay) were associated with EARI, while pre-interventional thrombolysis showed no association (aOR 1.15, 95% CI 0.59–2.26). The clinical benefit of EARI after IAF seemed more pronounced in patients without or only minor early ischemic changes (Alberta Stroke Program Early Computed Tomography Score (ASPECTS) ≥9, aOR 4.00, 95% CI 1.37–11.61) and was absent in patients with moderate to severe ischemic changes (ASPECTS ≤8, aOR 0.94, 95% CI 0.27–3.27, p for interaction: 0.095). Conclusion: Early rescue and a cardioembolic stroke origin were associated with more frequent EARI after IAF. The clinical effect of EARI seemed reduced in patients with already established infarcts. If confirmed, these findings can help to inform patient selection and inclusion criteria for randomized-controlled trials evaluating IAF as rescue after MT.
Improved modified kraft cooking

In previous studies (Mao, Hartler 1992a, 1994), a modified vapour-phase kraft cooking process with an initial vapour-phase stage followed by a liquid-phase stage (at a liquorto-wood ratio of 6:l) has been developed. In order to achieve a high initial sulfide concentration, divided white liquors (a "sulfide-rich" and a "sulfide-free" liquor) were used. In this work, the same process has been studied using instead a conventional white liquor throughout the cook. Results show that this process without exchange of the cooking liquor has the same cooking selectivity as the modified reference. The same process with exchange of the cooking liquor (achieved by drainage of the free liquor followed by addition of fresh white liquor, see fig. 1) has, however, a significantly better cooking selectivity than the modified reference.
Line Weaver: Importance‐Driven Order Enhanced Rendering of Dense Line Charts

Line charts are an effective and widely used technique for visualizing series of ordered two‐dimensional data points. The relationship between consecutive points is indicated by connecting line segments, revealing potential trends or clusters in the underlying data. However, when dealing with an increasing number of lines, the render order substantially influences the resulting visualization. Rendering transparent lines can help but unfortunately the blending order is currently either ignored or naively used, for example, assuming it is implicitly given by the order in which the data was saved in a file. Due to the non‐commutativity of classic alpha blending, this results in contradicting visualizations of the same underlying data set, so‐called “hallucinators”. In this paper, we therefore present line weaver, a novel visualization technique for dense line charts. Using an importance function, we developed an approach that correctly considers the blending order independently of the render order and without any prior sorting of the data. We allow for importance functions which are either explicitly given or implicitly derived from the geometric properties of the data if no external data is available. The importance can then be applied globally to entire lines, or locally per pixel which simultaneously supports various types of user interaction. Finally, we discuss the potential of our contribution based on different synthetic and real‐world data sets where classic or naive approaches would fail.
Estimating the epidemic consequences of HIV prevention gaps among key populations

HIV epidemic appraisals are used to characterize heterogeneity and inequities in the context of the HIV pandemic and the response. However, classic measures used in appraisals have been shown to underestimate disproportionate risks of onward transmission, particularly among key populations. In response, a growing number of modelling studies have quantified the consequences of unmet prevention and treatment needs (prevention gaps) among key populations as a transmission population attributable fraction over time (tPAFt). To aid its interpretation and use by programme implementers and policy makers, we outline and discuss a conceptual framework for understanding and estimating the tPAFt via transmission modelling as a measure of onward transmission risk from HIV prevention gaps; and discuss properties of the tPAFt.
Uncertainty‐aware Visualization of Regional Time Series Correlation in Spatio‐temporal Ensembles

Given a time‐varying scalar field, the analysis of correlations between different spatial regions, i.e., the linear dependence of time series within these regions, provides insights into the structural properties of the data. In this context, regions are connected components of the spatial domain with high time series correlations. The detection and analysis of such regions is often performed globally, which requires pairwise correlation computations that are quadratic in the number of spatial data samples. Thus, operations based on all pairwise correlations are computationally demanding, especially when dealing with ensembles that model the uncertainty in the spatio‐temporal phenomena using multiple simulation runs. We propose a two‐step procedure: In a first step, we map the spatial samples to a 3D embedding based on a pairwise correlation matrix computed from the ensemble of time series. The 3D embedding allows for a one‐to‐one mapping to a 3D color space such that the outcome can be visually investigated by rendering the colors for all samples in the spatial domain. In a second step, we generate a hierarchical image segmentation based on the color images. From then on, we can visually analyze correlations of regions at all levels in the hierarchy within an interactive setting, which includes the uncertainty‐aware analysis of the region's time series correlation and respective time lags.
Learning Contextualized User Preferences for Co‐Adaptive Guidance in Mixed‐Initiative Topic Model Refinement

Mixed‐initiative visual analytics systems support collaborative human‐machine decision‐making processes. However, many multi‐objective optimization tasks, such as topic model refinement, are highly subjective and context‐dependent. Hence, systems need to adapt their optimization suggestions throughout the interactive refinement process to provide efficient guidance. To tackle this challenge, we present a technique for learning context‐dependent user preferences and demonstrate its applicability to topic model refinement. We deploy agents with distinct associated optimization strategies that compete for the user's acceptance of their suggestions. To decide when to provide guidance, each agent maintains an intelligible, rule‐based classifier over context vectorizations that captures the development of quality metrics between distinct analysis states. By observing implicit and explicit user feedback, agents learn in which contexts to provide their specific guidance operation. An agent in topic model refinement might, for example, learn to react to declining model coherence by suggesting to split a topic. Our results confirm that the rules learned by agents capture contextual user preferences. Further, we show that the learned rules are transferable between similar datasets, avoiding common cold‐start problems and enabling a continuous refinement of agents across corpora.
I know it's still you: A study of using the PPG sensor to support zero re-authentications

The Photoplethysmogram (PPG) sensor is found in most smart wearables and fitness trackers to support the physical wellness monitoring of it's user. The popularity of this sensor has encouraged the exploration of it's use in other domains particularly in the field of banking, education, training, wellness etc. as a form of biometric authentication. These studies are however limited in the evaluation of the sensor in the wild. We created several datasets of continuous in-the-wild PPG across multiple participants and devices and propose the use of different statistical, signal processing and machine learning based techniques to support zero re-authentications using in-situ PPG data.
Person Re-Identification in a Car Seat: Comparison of Cosine Similarity and Triplet Loss based approaches on Capacitive Proximity Sensing data

Currently there is much research in the area of person identification. Mostly it is based on multi-biometric data. In this paper, we aim to leverage soft biometric properties to achieve person re-identification by using unobtrusive sensors, envisioning assistive environments, which recognize their user and thus automatically personalize and adapt. In practice, a car seat recognizes the person who sits down and greets the person with their own name, enabling various customisation in the car unique to the user, like seat configurations. We present a system composed of a sensor equipped car seat, which is able to recognize a person from a predefined group. We contribute two classification approaches based on cosine similarity measure and on triplet loss learning. These are thoroughly analysed and evaluated in a user study with nine participants. We achieve the best re-identification performance using a hand-crafted feature approach based on the comparing measure of cosine similarity combined with majority voting. The highest overall precision achieved in re-identifying a person from a group of nine users is 80 %.
Macroscale structural changes of thylakoid architecture during high light acclimation in Chlamydomonas reinhardtii

Photoprotection mechanisms are ubiquitous among photosynthetic organisms. The photoprotection capacity of the green alga Chlamydomonas reinhardtii is correlated with protein levels of stress-related light-harvesting complex (LHCSR) proteins, which are strongly induced by high light (HL). However, the dynamic response of overall thylakoid structure during acclimation to growth in HL has not been fully understood. Here, we combined live-cell super-resolution microscopy and analytical membrane subfractionation to investigate macroscale structural changes of thylakoid membranes during HL acclimation in Chlamydomonas . Subdiffraction-resolution live-cell imaging revealed that the overall thylakoid structures became thinned and shrunken during HL acclimation. The stromal space around the pyrenoid also became enlarged. Analytical density-dependent membrane fractionation indicated that the structural changes were partly a consequence of membrane unstacking. The analysis of both an LHCSR loss-of-function mutant , npq4 lhcsr1 , and a regulatory mutant that over-expresses LHCSR, spa1-1 , showed that structural changes occurred independently of LHCSR protein levels, demonstrating that LHCSR was neither necessary nor sufficient to induce the thylakoid structural changes associated with HL acclimation. In contrast, stt7-9 , a mutant lacking a kinase of major light-harvesting antenna proteins, had a slower thylakoid structural response to HL relative to all other lines tested but still showed membrane unstacking. These results indicate that neither LHCSR- nor antenna-phosphorylation-dependent HL acclimation are required for the observed macroscale structural changes of thylakoid membranes in HL conditions.
Computational mechanisms for neural representation of words

A critical way for humans to acquire, represent and communicate information is through language, yet the underlying computation mechanisms through which language contributes to our word meaning representations are poorly understood. We compared three major types of word computation mechanisms from large language corpus (simple co-occurrence, graph-space relations and neural-network-vector-embedding relations) in terms of the association of words’ brain activity patterns, measured by two functional magnetic resonance imaging (fMRI) experiments. Word relations derived from a graph-space representation, and not neural-network-vector-embedding, had unique explanatory power for the neural activity patterns in brain regions that have been shown to be particularly sensitive to language processes, including the anterior temporal lobe (capturing graph-common-neighbors), inferior frontal gyrus, and posterior middle/inferior temporal gyrus (capturing graph-shortest-path). These results were robust across different window sizes and graph sizes and were relatively specific to language inputs. These findings highlight the role of cumulative language inputs in organizing word meaning neural representations and provide a mathematical model to explain how different brain regions capture different types of language-derived information.
Learning Long-Term Behavior through Continuous Emotion Estimation

Emotions convey concise information regarding an individual’s internal state, while in the long-term they can be used to form an opinion about his/her overall personality. The latter can be proved particularly vital in many human-robot interaction tasks, like in the case of an assisted living robotic agent, where the human’s mood may in turn require the adaptation of the robot’s behavior. As a result, the paper at hand proposes a novel approach enabling an artificial agent to conceive and gradually learn the personality of a human, by tracking his emotional variations throughout their interaction time. To achieve that, the facial landmarks of the subject are extracted and fed into a Deep Neural Network architecture that estimates the two coefficients of human emotions, viz., arousal and valence, as introduced by the broadly known Russell’s model. Finally, by creating a dashboard for user-friendly display of our results, we present both momentarily and in the long-term the monitored fluctuations of a person’s emotional state.