Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of the Acute Physiology and Chronic Health Evaluation (APACHE) II and IV Score in COVID-19 Patients

Background Severity scoring systems are inherent to ICU practice for multiple purposes. Acute Physiology and Chronic Health Evaluation (APACHE) scoring systems are designed for ICU mortality prediction. This study aims to validate APACHE IV in COVID-19 patients admitted to the ICU. Methods All COVID-19 patients admitted to the ICU between March 13, 2020, and October 17, 2020, were retrospectively analyzed. APACHE II and APACHE IV scores as well as SOFA scores were calculated within 24 hours after admission. Discrimination for mortality of all three scoring systems was assessed by receiver operating characteristic curves. Youden index was determined for the scoring system with the best discriminative performance. The Hosmer–Lemeshow goodness-of-fit test was used to assess calibration. All analyses were performed for both the overall population as in a subgroup treated with anti-Xa adjusted dosages of LMWHs. Results 116 patients were admitted to our ICU during the study period. 13 were excluded for various reasons, leaving 103 patients in the statistical analysis of the overall population. 57 patients were treated with anti-Xa adjusted prophylactic dosages of LMWH and were supplementary analyzed in a subgroup analysis. APACHE IV had the best discriminative power of the three scoring systems, both in the overall population (APACHE IV ROC AUC 0.67 vs. APACHE II ROC AUC 0.63) as in the subgroup (APACHE IV ROC AUC 0.82 vs. APACHE II ROC AUC 0.7). This model exhibits good calibration. Hosmer–Lemeshow p values for APACHE IV were 0.9234 for the overall population and 0.8017 for the subgroup. Calibration p values of the APACHE II score were 0.1394 and 0.6475 for the overall versus subgroup, respectively. Conclusions APACHE IV provided the best discrimination and calibration of the considered scoring systems in critically ill COVID-19 patients, both in the overall group and in the subgroup with anti-Xa adjusted LMWH doses. Only in the subgroup analysis, discriminative abilities of APACHE IV were very good. This trial is registered with NCT04713852.
A Study on Gentiana dahurica Fisch Ethanol Extract Alleviating Alcoholic Liver Disease in Mice: A Metabolomic Analysis of the Liver

We clarified the hepatoprotective effect of Gentiana dahurica Fisch ethanol extract (GDEE) in our previous study, and we further revealed the mechanism with the help of metabolomics technology in this study. The livers from Control group, Alcohol group, and Alcohol + GDEE group were analyzed by metabolomics. The metabolites in the liver were separated by ultra-high-performance liquid chromatography (UHPLC) and were tentatively identified using mass spectrometry (MS)/MS analysis. Differential metabolites were defined with VIP > 1 and P < 0.05. Principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to analyze differences among these groups. The results showed that the groups could be clearly distinguished by PCA and OPLS-DA analysis. Alcohol and GDEE could change the overall profile of liver metabolites. Alterations in liver tissues of ALD mice induced by alcohol were mainly involved in the dipeptides, purine and pyrimidine metabolism and glucose and lipid metabolism, which could be partly affected by GDEE. This study revealed that the mechanism of GDEE in alleviating ALD had the characteristics of multitarget and multipathway.
Environmental filtering and dispersal limitation jointly shaped the taxonomic and phylogenetic beta diversity of natural forests in southern China

Abstract Aim The mechanisms underlying the maintenance of biodiversity remain to be elucidated. Taxonomic diversity alone remains an unresolved issue, especially in terms of the mechanisms of species co‐existence. We hypothesized that phylogenetic information could help to elucidate the mechanism of community assembly and the services and functions of ecosystems. The aim of this study was to explore the mechanisms driving floral diversity in subtropical forests and evaluate the relative effects of these mechanisms on diversity variation, by combining taxonomic and phylogenetic information. Location We examined 35 1‐ha tree stem‐mapped plots across eight national nature reserves in Guangxi Zhuang Autonomous Region, China. Taxon Trees. Methods We quantified the taxonomic and phylogenetic β‐diversity between each pair of plots using the (abundance‐based) Rao's quadratic entropy and the (incidence‐based) Sørensen dissimilarity indices. Using a null model approach, we compared the observed β‐diversity with the expected diversity at random and calculated the standard effect size of the observed β‐diversity deviation. Furthermore, we used distance‐based redundancy analysis (dbRDA) to partition the variations in taxonomic and phylogenetic observed β‐diversity and β‐deviation into four parts to assess the environmental and spatial effects. Results The taxonomic β‐deviation was related to and higher than the phylogenetic β‐deviation (r = .74). This indicated that the species turnover between pairwise plots was mainly the turnover of closely related species. Higher taxonomic and phylogenetic β‐deviation were mainly concentrated in the pairwise karst and nonkarst forest plots, indicating that the species in karst forests and nonkarst forests were predominantly from distantly related clades. A large proportions of the variation in taxonomic and phylogenetic β‐deviation were explained by the joint effect of environmental and spatial variables, while the contribution of environmental variables was greater than that of spatial variables, probably owing to the influence of the sampling scale dependence, integrality of sampling size and species pool, and the unique climatic and geomorphic characteristics. Main conclusions Our study highlights the importance of phylogeny in biodiversity research. The incorporation of taxonomic and phylogenetic information provides a perspective to explore potential underlying mechanisms that have shaped species assemblages and phylogenetic patterns in biodiversity hotspots.
Multilength Scale Studies of the Confined Crystallization in Poly(l-lactide)-block-Poly(ethylene glycol) Copolymer

In this work, we investigated the structure and morphology formation in crystalline–crystalline diblock copolymer of poly(l-lactide)-block-poly(ethylene glycol) (PLLA-b-PEG) on different length scales with optical microscopy (OM), atomic force microscopy (AFM), synchrotron time-resolved small-angle X-ray scattering (TR-SAXS) and wide-angle X-ray scattering (WAXS) methods. The PLLA-b-PEG copolymer with 5000 of number-average of molecular weight of PLLA and PEG blocks was used in this work. The structure and morphology of PLLA-b-PEG copolymers were formatted by a two-step crystallization process: i.e., the PLLA block crystallized fully at 110 °C in the first step, and then the PEG block crystallized fully at 30 °C in the second step. The OM, AFM, and SAXS results indicated that the PEG block crystallized in the multilength scales amorphous regions confined by PLLA crystals. The PEG block crystallized not only in the interlamellar regions of PLLA crystals, but also in the interfibrillar regions of PLLA. Howe.
Influence of Extracorporeal Haemodialysis on the Mean Whole-Body Intracellular pH

Cortisol production rate estimated by the urine method, was applied to the follow-up of three cases of Cushing's syndrome treated by the operation of bilateral adrenalectomy with transplantation of one sixth of the total adrenal tissue into the rectal sheath of the anterior abdominal wall. In two patients, lower than normal cortisol production rates associated with hypoadrenocorticism were detected several months after the operation and steroid therapy had to be started. It is believed that control cortisol production rate estimation should be taken as the basis in considering the amount of adrenocortical tissue to be transplanted before deciding whether, this factor or some other factors related to this surgical technique itself, is responsible for the failure of some of this type of operation.
Consumer fair prices for less pesticide in potato

This study estimates Turkish citizens’ willingness to pay (WTP) for reduced pesticides on potatoes. These estimates rely on data collected from 393 persons covering all regions in Turkey through an online survey during the period from June 22 - July 21, 2014. The average WTP was found to be about TL 1.68 for all observations including zero bids and TL 2.91 excluding zero bids. The results of the probit model show that cosmetic defects, free-pesticide potatoes with insect damages, age, and gender were identified by the model to have significant impacts on the probability of WTP.
Paraxial propagation and focusing of higher-order cosh-Gaussian beams

Based on the Huygens-Fresnel diffraction integral, a concise formula for the higher-order cosh-Gaussian beams (HOChGB) propagating through a paraxial ABCD optical system is derived. The propagation formula of the HOChGB is expressed as a superposition of cosh-Gaussian modes and in terms of the Gaussian beam-parameter q. The profile and the inter-lobe space of the beam at the initial plane are analyzed with the help of the maximum intensity criterion as a function of the decentered parameter and the beam order. It is shown that during propagation the HOChGB with appropriate parameters may progressively change profile, and in far-field the amplitude of the beam is expressed as a superposition of cosine functions modulated by a Gaussian envelope. Furthermore, it is found that the focal shift of the focused HOChGB increases with the decrease of the Fresnel number, the decentered parameter and the beam order.
Tackling SAR Imagery Ship Classification Imbalance via Deep Convolutional Generative Adversarial Network

Abstract Shipping constitutes the majority of the world trade, and Synthetic Aperture Radar (SAR) imagery is the primary involuntary all-condition ship monitoring and classification approach. However, large SAR datasets for deep learning are difficult to curate, usually leading to imbalanced classes. Herein, conventional methods such as weighted cost function or over-sampling are shown to be insufficient for our application. Therefore, we propose to utilize a Deep Convolutional Generative Adversarial Network (DCGAN) to be trained on the minority class, and generate new SAR chips to balance the training dataset. A case study is consequently presented that utilizes our methodology, and a base classifier is devised to evaluate its performance. The investigation of the classification metrics confirms that DCGAN is an effective alternative for tackling imbalanced ship SAR data for deep learning applications.
Dutch Design: Practice Guidelines for Group Treatment in the Netherlands

ABSTRACT The American Group Psychotherapy Association (AGPA) Practice Guidelines helped inspire the Dutch Group Therapy Association (NVGP) to develop the Dutch Practice Guidelines for Group Treatment. In this article, we provide a short review of the history of Dutch group psychotherapy. We discuss socioeconomic developments in the Netherlands and their consequences for health care in general and group psychotherapy in particular. After that, we introduce the procedures of the NVGP Dutch Task Force in developing their Practice Guidelines including their process to reach expert consensus. We then elaborate on the similarities and differences between the American and the Dutch Practice Guidelines. We end by presenting future directions and thoughts on international cooperation in the development of evidence-based practice guidelines for group treatment.
When taking the bull by the horns is not possible: comprehension of idioms in patients with aphasia and dementia (Cuando no es posible coger el toro por los cuernos: la comprensión de modismos en pacientes con afasia y demencia)

Abstract This work analysed the comprehension of three types of idioms of the V+NP form (e.g., bite the dust) in seven patients with aphasia and two patients with probable Alzheimer’s disease, frontal variant. The aphasic patients included in the study had a severe semantic disorder or a mild semantic deficit, or only a lexical disturbance. Participants with dementia showed a moderate deterioration in their executive functions and no impairment in their psycholinguistic performance. In this study, we used an idiom–word matching task, administered in two versions. The results indicate dissimilar performance patterns, according to patients’ neuropsychological impairment. In particular, patients with a severe semantic disorder showed a poor understanding of the figurative meanings of idioms, especially if those idioms were not fully transparent or opaque. Participants with a mild semantic deficit accessed the non-literal meanings of the idioms showing less difficulty in the case of certain idiomatic expressions. Patients with executive function deficit showed a double interference effect, and although they could activate the figurative and literal meanings of idioms according to the context in which they were presented, it was difficult for them to inhibit those meanings whenever necessary and activate the alternative meaning. This effect was more pronounced the less transparent the idiom was.
Responding to the Needs of the Homeless in the COVID-19 Pandemic: A Review of Initiatives in 20 Major U.S. Cities

ABSTRACT This research examines the crisis management approaches of local governments in responding to the service demands of their homeless populations during the COVID-19 pandemic. The pandemic has generated challenges for cities in serving the homeless who often lack access to health care and may reside in outdoor camps or congregate shelters where the virus may spread. A review of the websites in 20 major U.S. cities shows that they are adopting a number of diverse and innovative crisis management strategies to mitigate the effects of the COVID-19 pandemic for their most vulnerable population. Information useful to practitioners and scholars is presented.
Propaganda innovation and resilient governance: the case of China’s smog crisis

Crisis communication is essential to the political stability and legitimacy of the Chinese Communist Party (CCP), but how crises are managed in China is little understood. This paper aims to pursue this question through a case study of China’s smog crisis since 2013 – a regular recurring crisis that confronts the population and the Chinese government. The paper explores what innovative media strategies and practices have been deployed by the Chinese government to effectively guide public opinion and maintain social and political stability during smog crises. We first examine the smog coverage in People’s Daily to critique the propaganda and persuasion techniques in its modern crisis reporting. We then look at WeChat-based citizen journalism as alternative crisis communication to identify its popular themes and the CCP’s censorship tactics to manage it. We argue that the CCP’s propaganda during times of crisis has been mainly achieved through the revamping of official journalism on its state media and the differential censorship of citizen discourse on social media. The double-pronged approach ensures the public opinion is properly guided in crises and possible disruption to the regime’s stability is minimized.
Human sickness detection is not dependent on cultural experience

Animals across phyla can detect early cues of infection in conspecifics, thereby reducing the risk of contamination. It is unknown, however, if humans can detect cues of sickness in people belonging to communities with whom they have limited or no experience. To test this, we presented Western faces photographed 2 h after the experimental induction of an acute immune response to one Western and five non-Western communities, including small-scale hunter–gatherer and large urban-dwelling communities. All communities could detect sick individuals. There were group differences in performance but Western participants, who observed faces from their own community, were not systematically better than all non-Western participants. At odds with the common belief that sickness detection of an out-group member should be biased to err on the side of caution, the majority of non-Western communities were unbiased. Our results show that subtle cues of a general immune response are recognized across cultures and may aid in detecting infectious threats.
Deep classification of cut-marks on bones from Arroyo del Vizcaíno (Uruguay)

The earliest widely accepted presence of humans in America dates to approximately 17.5 cal kyr BP, at the end of the Last Glacial Maximum (LGM). Among other evidence, this presence is attested by stone tools and associated cut-marks and other bone surface modifications (BSM), interpreted as the result of the consumption of animals by humans. Claims of an older human presence in the continent have been made based on the proposed anthropogenic modification of faunal remains; however, these have been controversial due to the highly subjective nature of the interpretations. Here, we employ advanced deep learning algorithms to objectively increase the accuracy of BSM identification on bones. With several models that exhibit BSM classification accuracies greater than 94%, we use ensemble learning techniques to robustly classify a selected sample of BSM from the approximately 30 kyr BP site of Arroyo del Vizcaíno, Uruguay. Our results confidently show the presence of cut-marks imparted by stone tools on bones at the site. This result supports an earlier presence of humans in the American continent, expanding additional genetic and archaeological evidence of a human LGM and pre-LGM presence in the continent.
Indentation mapping of stretched adhesive membranes

Unilateral adhesive contact between a rigid indenter and a uniformly stretched membrane of arbitrary shape is considered. The generalized Johnson–Kendall–Roberts (JKR)-type and Derjaguin– Muller–Toporov (DMT)-type models of non-axisymmetric adhesive contact are presented for short- and long-range adhesion, respectively, and the JKR–DMT transition is established in the framework of the generalized Maugis–Dugdale model. A refined method of matched asymptotic expansions is applied to construct the leading-order asymptotic model for indentation mapping of freestanding two-dimensional materials with an axisymmetric probe, using the approximate analytical solution obtained in explicit form for an infinite membrane in the limit of short-range adhesive contact with an indenter in the form of an elliptic paraboloid. The cases of a spherical indenter and a rectangular membrane are studied in detail.
Thousands of induced germline mutations affecting immune cells identified by automated meiotic mapping coupled with machine learning

Significance We developed software called Candidate Explorer (CE) that uses a machine-learning algorithm to identify chemically induced mutations that are causative of screened phenotypes. CE determines the probability that a mutation will be verified as causative for a phenotype if the gene is independently targeted for knockout or recreation of the mutation. CE uses 67 parameters from the mapping data—including gene, mutation, genotype, allelism, and phenotype information—to determine the CE Score and verification probability. We used CE to evaluate ∼87,000 mutation/phenotype associations identified by flow cytometry screening of circulating immune cells from mutagenized mice: 1,279 genes representing 2,336 mutations were rated good or excellent candidates for causation of phenotypes. Many of these genes were not previously implicated in immunity. Forward genetic studies use meiotic mapping to adduce evidence that a particular mutation, normally induced by a germline mutagen, is causative of a particular phenotype. Particularly in small pedigrees, cosegregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the identification of mutations causing immune phenotypes in mice by creating Candidate Explorer (CE), a machine-learning software program that integrates 67 features of genetic mapping data into a single numeric score, mathematically convertible to the probability of verification of any putative mutation–phenotype association. At this time, CE has evaluated putative mutation–phenotype associations arising from screening damaging mutations in ∼55% of mouse genes for effects on flow cytometry measurements of immune cells in the blood. CE has therefore identified more than half of genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.
A self-powered implantable and bioresorbable electrostimulation device for biofeedback bone fracture healing

Significance Bone fracture represents a significant problem in public health. State-of-the-art clinical study demonstrated that by correlating the stimulation amplitude and frequency directly to dynamic locomotion, biofeedback electrostimulation therapy is particularly effective compared to conventional continuous electrostimulation for postoperative therapy and rehabilitation after musculoskeletal injury. However, implementation of biofeedback still relies on complex electronics and sensing systems, which largely limits its accessibility to patients. Here we developed a self-powered implantable and bioresorbable device that directly applies biofeedback electrostimulations to the treatment of bone fracture. The electrostimulation signals are generated solely from relevant body motions, providing a closed-loop biofeedback therapy bringing rapid healing to fractures. This device is self-responsive, battery free, and requires no surgical removal after fulfilling the biomedical intervention. Electrostimulation has been recognized as a promising nonpharmacological treatment in orthopedics to promote bone fracture healing. However, clinical applications have been largely limited by the complexity of equipment operation and stimulation implementation. Here, we present a self-powered implantable and bioresorbable bone fracture electrostimulation device, which consists of a triboelectric nanogenerator for electricity generation and a pair of dressing electrodes for applying electrostimulations directly toward the fracture. The device can be attached to irregular tissue surfaces and provide biphasic electric pulses in response to nearby body movements. We demonstrated the operation of this device on rats and achieved effective bone fracture healing in as short as 6 wk versus the controls for more than 10 wk to reach the same healing result. The optimized electrical field could activate relevant growth factors to regulate bone microenvironment for promoting bone formation and bone remodeling to accelerate bone regeneration and maturation, with statistically significant 27% and 83% improvement over the control groups in mineral density and flexural strength, respectively. This work provided an effective implantable fracture therapy device that is self-responsive, battery free, and requires no surgical removal after fulfilling the biomedical intervention.