Miracle-dz/UniFAR-FTUs huggingface dataset:
The Value of Pulmonary Bedside Ultrasound System in the Evaluation of Severity and Prognosis of Acute Lung Injury

Objective To evaluate the value of pulmonary bedside ultrasound system in the assessment of severity and prognosis of acute lung injury (ALI). Method Seventy-two ALI patients in the intensive care unit (ICU) of our hospital from April 2019 to April 2021 were selected as subjects. The changes of lung ultrasound score (LUS) and parameters at D1, D2, and D3 after admission were analyzed (LUS, oxygenation index (PaO2/FiO2), Acute Physiology and Chronic Health Evaluation II (APACHE-II), and Sequential Organ Failure Assessment (SOFA) score). Pearson correlation analysis was used to assess the relationship between LUS and PaO2/FiO2, APACHE-II score, and SOFA score at D1, D2, and D3. Logistic regression analysis was used for influencing factors for the prognosis of ALI patients. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of baseline LUS, PaO2/FiO2, APACHE-II score, and SOFA score for the prognosis of ALI patients. Result LUSs at D1, D2 and D3 showed an increasing trend with the increase of disease severity (P < 0.05). From D1 to D3, LUS, PaO2/FiO2, APACHE-II score, and SOFA score showed a downward trend (P < 0.05). LUS was negatively correlated with PaO2/FiO2 at D1, D2, and D3 but positively correlated with APACHE-II score and SOFA score (P < 0.05). Logistic regression analysis showed that after controlling for age, PaO2 and PaCO2, an increase in baseline LUS, APACHE-II score, SOFA score, and a decrease in PaO2/FiO2 were independent risk factors for death at 28 d in ALI patients (P < 0.05). ROC curve showed that LUS, PaO2/FiO2, APACHE-II score, and SOFA score were combined to predict the prognosis of ALI patients with the highest AUC value of 0.920, corresponding sensitivity of 88.89%, and specificity of 95.56%. Conclusion LUS can evaluate the change of pulmonary ventilation area in ALI patients, further evaluate the severity of the disease, and effectively predict the prognosis of patients.
Sequestration of Defenses against Predators Drives Specialized Host Plant Associations in Preadapted Milkweed Bugs (Heteroptera: Lygaeinae)

Host plant specialization across herbivorous insects varies dramatically, but while the molecular mechanisms of host plant adaptations are increasingly known, we often lack a comprehensive understanding of the selective forces that favor specialization. The milkweed bugs (Heteroptera: Lygaeinae) are ancestrally associated with plants of the Apocynaceae from which they commonly sequester cardiac glycosides for defense, facilitated by resistant Na+/K+-ATPases and adaptations for transport, storage, and discharge of toxins. Here, we show that three Lygaeinae species independently colonized four novel nonapocynaceous hosts that convergently produce cardiac glycosides. A fourth species shifted to a new source of toxins by tolerating and sequestering alkaloids from meadow saffron (Colchicum autumnale, Colchicaceae). Across three milkweed bug species tested, feeding on seeds containing toxins did not improve growth or speed of development and even impaired growth and development in two species, but sequestration mediated protection of milkweed bugs against two natural predators: lacewing larvae and passerine birds. We conclude that physiological preadaptations and convergent phytochemistry facilitated novel specialized host associations. Since toxic seeds did not improve growth but either impaired growth or, at most, had neutral effects, selection by predators on sequestration of defenses, rather than the exploitation of additional profitable dietary resources, can lead to obligatory specialized host associations in otherwise generalist insects.
The SARS-CoV-2 protein NSP2 impairs the microRNA-induced silencing capacity of human cells

The coronavirus SARS-CoV-2 is the cause of the ongoing pandemic of COVID-19. Given the absence of effective treatments against SARS-CoV-2, there is an urgent need for a molecular understanding of how the virus influences the machineries of the host cell. The SARS-CoV-2 generates 16 Non-Structural Proteins (NSPs) through proteolytic cleavage of a large precursor protein. In the present study, we focused our attention on the SARS-CoV-2 protein NSP2, whose role in the viral pathogenicity is poorly understood. Recent proteomic studies shed light on the capacity of NSP2 to bind the 4EHP-GIGYF2 complex, a key factor involved in microRNA-mediated silencing of gene expression in human cells. In order to gain a better understanding of the function of NSP2, we attempted to identify the molecular basis of its interaction with 4EHP-GIGYF2. Our data demonstrate that NSP2 physically associates with the endogenous 4EHP-GIGYF2 complex in the cytoplasm. Using co-immunoprecipitation and in vitro interaction assays, we identified both 4EHP and a central segment in GIGYF2 as binding sites for NSP2. We also provide functional evidence that NSP2 impairs the function of GIGYF2 in mediating mRNA silencing using reporter-based assays, thus leading to a reduced activity of microRNAs. Altogether, these data reveal the profound impact of NSP2 on the post-transcriptional silencing of gene expression in human cells, pointing out 4EHP-GIGYF2 targeting as a possible strategy of SARS-CoV-2 to take over the silencing machinery and to suppress host defenses.
Predicting Future Locations with Semantic Trajectories

Location prediction has attracted much attention due to its important role in many location-based services, including taxi services, route navigation, traffic planning, and location-based advertisements. Traditional methods only use spatial-temporal trajectory data to predict where a user will go next. The divorce of semantic knowledge from the spatial-temporal one inhibits our better understanding of users’ activities. Inspired by the architecture of Long Short Term Memory (LSTM), we design ST-LSTM, which draws on semantic trajectories to predict future locations. Semantic data add a new dimension to our study, increasing the accuracy of prediction. Since semantic trajectories are sparser than the spatial-temporal ones, we propose a strategic filling algorithm to solve this problem. In addition, as the prediction is based on the historical trajectories of users, the cold-start problem arises. We build a new virtual social network for users to resolve the issue. Experiments on two real-world datasets show that the performance of our method is superior to those of the baselines.
Twitter and human trafficking: Purposes, actors and topics in the Spanish-speaking scene

Human trafficking is a phenomenon linked to several forms of exploitation, such as sexual exploitation, forced labour, forced marriage, begging, forced criminal activity, or organ removal. There are different debates about a potential overrepresentation of some of these exploitation purposes, such as the sexual one, in the discourses underlying international regulations, news or institutional campaigns. This may have consequences on the identification of some of the population affected by this phenomenon and the assistance provided to them. The aim of this paper is to analyse the temporal evolution of the purposes of exploitation, actors and topics most represented in the activity on human trafficking and exploitation on Twitter during the 2011-2020 period. The results show that sexual exploitation is the purpose most represented in Twitter activity and the fact that international organisations and the criminal prosecution of the crime of human trafficking have progressively become more relevant. Furthermore, the networks of topics suggest that sexual exploitation seems to be linked to the notion of prostitution. This may have consequences for the displacement of other purposes of exploitation or the approaches centred on the promotion of human rights to less relevant positions, as well as for the construction of certain images of victims of human trafficking. La trata de personas es un fenómeno vinculado a diferentes finalidades de explotación, como la sexual, laboral, para el matrimonio, la mendicidad, la comisión de delitos o la extracción de órganos. Existen numerosos debates que remiten a una posible sobrerrepresentación de algunas de estas finalidades, como la sexual, en los discursos presentes en normativa internacional, prensa escrita o campañas institucionales. Esto puede derivar en posibles consecuencias sobre la detección de parte de la población afectada por este fenómeno y la atención que se le proporciona. El presente trabajo tiene como objetivo analizar la evolución temporal de las finalidades de explotación, actores y temas más representados en la actividad sobre trata de personas y explotación acontecida en Twitter durante el periodo 2011-2020. Los resultados arrojan que la explotación sexual es aquella con una mayor presencia en la actividad en esta red social, así como que los organismos internacionales y la persecución penal del delito de trata se tornan progresivamente más relevantes. Además, las redes de comunidades de temas analizadas sugieren que la explotación sexual parece estar vinculada a la idea de prostitución en los tuits publicados. Todo ello puede tener consecuencias sobre el desplazamiento de otras finalidades de explotación o de enfoques como los centrados en la promoción de Derechos Humanos a posiciones menos relevantes, así como sobre la construcción de determinadas imágenes de víctimas de este fenómeno.
A computational method for predicting the most likely evolutionary trajectories in the stepwise accumulation of resistance mutations

Pathogen evolution of drug resistance often occurs in a stepwise manner via the accumulation of multiple mutations that in combination have a non-additive impact on fitness, a phenomenon known as epistasis. The evolution of resistance via the accumulation of point mutations in the DHFR genes of Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) has been studied extensively and multiple studies have shown epistatic interactions between these mutations determine the accessible evolutionary trajectories to highly resistant multiple mutations. Here, we simulated these evolutionary trajectories using a model of molecular evolution, parameterized using Rosetta Flex ddG predictions, where selection acts to reduce the target-drug binding affinity. We observe strong agreement with pathways determined using experimentally measured IC50 values of pyrimethamine binding, which suggests binding affinity is strongly predictive of resistance and epistasis in binding affinity strongly influences the order of fixation of resistance mutations. We also infer pathways directly from the frequency of mutations found in isolate data, and observe remarkable agreement with the most likely pathways predicted by our mechanistic model, as well as those determined experimentally. This suggests mutation frequency data can be used to intuitively infer evolutionary pathways, provided sufficient sampling of the population.
Precipitation Dependence of Temperature Trends Across the Contiguous US

Temperature and precipitation covary across timescales due to thermodynamic and dynamic processes. We examine spatial patterns and trends of daily precipitation dependence of maximum and minimum temperature anomalies across the contiguous United States during 1950–2020. In the warm season, maximum temperatures are anomalously cool on wet days, while in the cool season, minimum temperatures are anomalously warm on wet days. During 1950–2020, warm‐season maximum temperatures increased 0.5°C more on wet days than on dry days, whereas minimum temperature on dry days warmed slightly more than on wet days in both the warm and cool season. By contrast, climate models show more subtle and consistent precipitation dependence of temperature trends with approximately 0.2°C more warming on dry days than on wet days. Improved understanding of precipitation‐dependent temperature trends is critical for understanding and modeling the impacts of changing climate on snowpack, drought, and heat stress.
Ground source heat pumps: observations from United Kingdom ground thermal response tests

The United Kingdom is experiencing a period of rapid growth in the use of ground source heat pump systems. Most installations in the United Kingdom use vertical ‘borehole’ heat-exchanger arrays, the design of which depends on four parameters: formation thermal conductivity, formation heat capacity, heat-exchanger resistance and heat-exchanger grout material heat capacity. Conventionally, two of these parameters (conductivity and resistance) are obtained from a thermal response test carried out on a trial heat exchanger at the site of interest by fitting thermal response data to classical line-source heat conduction theory. This test method gives no information on the heat capacities of the formation and grout material and requires an assumption about the former to enable the heat-exchanger resistance parameter to be extracted. In this work, a new method is developed for extracting all four parameters using a trust-region search algorithm in conjunction with a detailed numerical model of the test heat exchanger. Results give excellent agreement between the fitted-model predictions of heat-exchanger outlet water temperature and measured outlet water temperature for 13 test cases. A further advantage of the method developed here is that it can be used with data sets that contain disturbances and discontinuities. Practical applications : Most of the ground source heat pump installations in the United Kingdom use vertical ‘borehole’ heat-exchanger arrays. The design of these arrays requires information about the rock formation thermal conductivity and volume specific heat capacity and the borehole heat-exchanger thermal resistance and grout material volume specific heat capacity. These design parameters are usually obtained from a thermal response test carried out on a trial heat exchanger at the site of interest. In this work, thermal response test results from 13 UK sites are presented and a new method for obtaining the four design parameters is developed and proposed.
Frequency-specific age-related changes in the amplitude of spontaneous fluctuations in autism

Background Autism spectrum disorder is characterized by atypical developmental changes during brain maturation, but regional brain functional changes that occur with age and across different frequency bands are unknown. Therefore, the current study aimed to explore potential age and frequency band-related changes in the regional brain activities in autism. Methods A total of 65 participants who met the DSM-IV criteria for autistic disorder and 55 typically developed (TD) participants (both age 6–30 years) were recruited in the current study. The two groups were matched in age (t=−1.314, P=0.191) and gender (χ2=2.760, P=0.097). The amplitude of low-frequency fluctuations (ALFF) was employed to explore the effect of development on spontaneous brain activity in individuals with autism and in TD participants across slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), and slow-3 (0.073–0.1 Hz) frequency bands. The diagnosis-by-age interaction effect in the whole brain voxels in autism and TD groups was investigated. Results Autism individuals showed significantly higher ALFF in the dorsal striatum in childhood (Caudate cluster: t=3.626, P=0.001; Putamen cluster: t=2.839, P=0.007) and remarkably lower ALFF in the dorsal striatum in adulthood (Caudate cluster: t=−2.198, P=0.038; Putamen cluster: t=−2.314, P=0.030) relative to TD, while no significant differences were observed in adolescence (all P>0.05). In addition, abnormal ALFF amplitudes were specific to the slow-4 (0.027–0.073 Hz) frequency band in the clusters above. Conclusions The current study indicated abnormal development patterns in the spontaneous activity of the dorsal striatum in autism and highlighted the potential role of the slow-4 frequency band in the pathology of autism. Also, the potential brain mechanism of autism was revealed, suggesting that autism-related variations should be investigated in a specific frequency.
Multimaterial Additive Manufacturing of LTCC Matrix and Silver Conductors for 3D Ceramic Electronics

Ceramic electronics have the advantages of large ampacity, high thermal conductivity, and excellent dielectric properties which are widely used in power electronics, optoelectronics, automotive industry, and aerospace technology. This work proposes a multimaterial dispensing additive manufacturing technology for customizing the 3D low‐temperature‐cofired ceramic (LTCC) circuitry. Customized LTCC aqueous slurry is first developed and then 3D printed together with commercial silver paste to build the green body. Then, the green body is debinded and sintered with a three‐stage process at 200, 500, and 850 °C, respectively. The shrinkage rate in 3D is around 17% which is comparable with commercial LTCCs. The surface quality of the sintered ceramic is improved obviously compared with that of the green body due to the glazing effect of the glass phase. For the silver conductor, the resistivity and the temperature coefficient of resistance are 2.34 ± 0.04 µΩ cm and 3.56 × 10−3 °C−1, respectively. A serial of demonstrators including 2D, 3D light‐emitting diode ceramic circuit boards and a ceramic heater/thermometer is developed to prove the potential and feasibility of the proposed technology.
BEHAVIORAL NICHE PARTITIONING IN EMBLYNA FRANCISCA AND EMBLYNA RETICULATA (ARANEAE, DICTYNIDAE)

Abstract I investigated behavioral niche partitioning in two morphologically similar and sympatric Emblyna spiders by collecting webs of Emblyna francisca and Emblyna reticulata from Sambucus and Atriplex plants at the Panorama Vista Preserve in Kern County, California. I measured web heights and identified prey found in webs to compare web placement and prey distributions in each habitat. Emblyna francisca webs contained more prey than did E. reticulata webs in both habitats. The two spiders had similar abundance in Atriplex, but in Sambucus, E. reticulata was more abundant than E. francisca. Emblyna reticulata placed its webs higher than E. francisca in Atriplex but not in Sambucus, and the distribution of prey in webs differed between the two spiders in Sambucus, but not in Atriplex.
Push or Pull? Measuring the labor supply response to the minimum wage using an individual-level panel

ABSTRACT For individuals in low-wage labour markets, an increase in the minimum wage can theoretically pull them into or push them out of the labour force. If increases raise expected wages beyond reservation wages, marginal individuals could enter the labour force and begin searching for employment. If increases lower expected wages, marginal individuals already in the labour force could exit. Leveraging revised individual identifiers in the U.S. Current Population Survey, this research estimates the contemporaneous effects of minimum wage increases on labour force participation. The use of within-person variation, short individual panels, and flexible controls for time create an empirical strategy that mitigates potential biases from unobserved constant individual-level heterogeneity and time-varying factors. This research finds that minimum wage changes tend to impact the youngest individuals, but there is substantial heterogeneity in responses by age, race/ethnicity, and sex. There is stronger evidence of pull effects amongst young white men and Latinos, and weaker evidence amongst young Black women and older Latinas. Weak evidence of push effects is observed amongst younger white women, younger Latinos, and older Latinas. This research highlights heterogeneous labour force participation responses to further inform our understanding of search behaviour and labour market churn.
Research on dynamic characteristics of an explosion-proof rubber-tyred vehicle

To investigate the dynamic characteristics of an explosion-proof tire vehicle,and obtain the dynamic stress and strain distribution,simulation research on its dynamic characteristics was conducted with multi-body dynamics and finite element method.An ADAMS-based model of the vehicle was established and dynamic load curves of all hinge points on the rectangular pit road condition were obtained by multi-body dynamic simulation.Then random excitation peaks of dynamic simulation result were applied to the finite element model established through ANSYS under typical load condition.Both dynamic stress distribution and stress concentration locations of the frame were obtained.The research result can be used to evaluate dynamic stress and strain,also providing certain significance for the vehicle lightweight improved design.
Penerapan Metode Convolutional Neural Network untuk Klasifikasi Penyakit Daun Apel pada Imbalanced Data

Menurut data produksi buah-buahan di Indonesia yang dipublikasikan oleh BPS, produksi apel pada tahun 2017 mengalami penurunan sebesar 3.3% atau sejumlah 10.780 ton dari tahun 2016 yang menghasilkan sebanyak 329.780 ton. Hal itu disebabkan oleh berbagai penyakit yang sering terjadi pada produksi apel, oleh karena itu pendeteksian penyakit daun apel yang tepat waktu menjadi sangat penting untuk industri apel yang berkembang dengan sehat. Sehingga dibutuhkan sistem yang efektif seperti klasifikasi citra digital pada tanaman. Metode yang digunakan pada penelitian ini merupakan adalah Convolutional Neural Network (CNN) dengan arsitektur InceptionV3. Penelitian ini menggunakan dataset Plant Pathology 2020 - FGV C7 sebanyak 1821 data citra dengan 4 kelas. Data dibagi menjadi 3 set data (latih, validasi, dan uji) dengan rasio 70:10:20. Hasil pengujian dievaluasi dengan menggunakan data uji, untuk proses evaluasi menggunakan confusion matrix. Berdasarkan hasil pelatihan mencapai akurasi 96.37%. Pad pengujian hasil akurasi pada masing-masing kelas sebesar 90,6%, 62,3%, 94,3%, dan 92%.
ADVANCED GENETIC STRATEGIES FOR IMPROVING RICE YIELD

Every crop breeding effort aims to increase production. Despite several advances, most worldwide breeding projects have traditionally focused on improving grain production potential, insect/pest and disease resistance, grain quality, and stress tolerance. Almost all rice breeding initiatives aim to increase grain yield. However, the value of this crop varies by area, country, and even within a country. Finding innovative ways to increase the genetic grain production potential of all kinds has significant ramifications. Rice breeders have improved crop yields significantly. The green revolution gave us semi-dwarf rice types, a new rice plant type, and hybrid rice. Conventional hybridization, ideotype and heterosis breeding, broad hybridization, genetic engineering, molecular marker-assisted breeding, and CRISPR-Cas9 are all possibilities for increasing yield potential. Pedigree is the most common breeding technique for enhancing rice, but hybrids and population improvement are also used. Many groups are still working to integrate biotechnology tools into breeding programs and balance budget allocation between conventional and innovative approaches. Modern technology, such as biotechnology, has recently increased agricultural productivity by improving crop yields and reviewing several genome editing methods to enhance rice production. Keywords: Rice (Oryza sativa L.), genetic engineering, ideotype breeding, RISPR-Cas9.
Rewriting Marx to expose the data society and AI

As I show with examples from the Grundrisse and the Capital, some fundamentals of Marx’s critique of political economy can be rewritten with simple substitutions to yield surprisingly pertinent analyses of today’s “information society” and the role that data and AI play in it. The reason behind this strange phenomenon is that Marx’s penetrating study of money as a dehumanizing abstraction and self-replicating capital can be extended with minor changes to the main abstraction and “automatic fetish” of our historical regime: digital data. As money-capital tends to grow by itself independently of humans, so does data. AI is the main engine of this new dangerous cycle.