Miracle-dz/UniFAR-FTUs huggingface dataset:
Housing Vacancy Rate in Major Cities in China: Perspectives from Nighttime Light Data

In recent years, the phenomenon of housing vacancy rate (HVR) has attracted considerable attention, especially concerning unjustified expansions of Chinese cities. The aforementioned trend is disadvantageous in that it will ultimately lead to tremendous wastage of valuable land that could otherwise be more productively utilized. Consequently, the methods for accurately determining the HVR are of great importance. Based on nighttime light data from the Luojia 1-01 nighttime light imagery provided by Wuhan University in June 2018 and the building data obtained from the Resources and Environmental Sciences Data Center, we estimated the HVRs of 49 cities in China by determining the building areas and considering the floor height. The results revealed that (1) the lowest (15%) and highest (24.3%) HVRs occur in Shenzhen and Nanning, respectively. (2) The urban HVR correlates positively with the three production structures (0.3143) but is significantly negatively correlated with population (0.3841), GDP (0.6139), and urban average housing prices (0.5083). (3) The first-tier, new first-tier, and second-tier cities showed the lowest (16.9%), relatively concentrated (20.5%), and highest (21.3%) average vacancy rates, respectively. (4) The vacancy rate is relatively low in the eastern coastal areas, whereas high in the northeast and western inland areas. The proposed method can help urban planners by identifying vacant areas and providing building information.
Screening of phytotoxicity of Alternaria macrospora MKP1 against Parthenium hysterophorus L.

Parthenium hysterophorus L. an exotic, pernicious weed is considered as one of the most troublesome weeds for agricultural sector by virtue of its high ecological amplitude and adaptability. Microbes and their by-products are now proved to be a worthy alternative to toxic chemicals used for weed management. Alternaria macrospora MKPI was isolated from the parthenium leaves infected with leaf blight and found pathogenic to the weed. The herbicidal potential of cell free culture filtrate of A. macrospora MKP1 has been tested against parthenium by employing detached leaf bioassay and seed germination bioassay and a significant damage was exhibited by the cultural filtrate of pathogen to the parthenium leaves and seeds.
Assessing Browser-level Defense against IDN-based Phishing

Internationalized Domain Names (IDN) allow people around the world to use their native languages for domain names. Unfortunately, because characters from different languages can look like each other, IDNs have been used to imperson-ate popular domains for phishing, i.e. , IDN homograph. To mitigate this risk, browsers have recently introduced defense policies. However, it is not yet well understood regarding how these policies are constructed and how effective they are. In this paper, we present an empirical analysis of browser IDN policies, and a user study to understand user perception of homograph IDNs. We focus on 5 major web browsers (Chrome, Firefox, Safari, Microsoft Edge, and IE), and 2 mobile browsers (Android Chrome and iOS Safari) and analyze their current and historical versions released from January 2015 to April 2020. By treating each browser instance as a black box, we develop an automated tool to test the browser policies with over 9,000 testing cases. We ﬁnd that all the tested browsers have weaknesses in their rules, leaving opportunities for attackers to craft homograph IDNs to impersonate target websites while bypassing browsers’ defense. In addition, a browser’s defense is not always getting stricter over time. For example, we observe Chrome has reversed its rules to re-allow certain homograph IDNs. Finally, our user study shows that the homograph IDNs that can bypass browsers’ defense are still highly deceptive to users. Overall, our results suggest the need to improve the current defense against IDN homograph.
Evaluating Short-term Forecast among Different Epidemiological Models under a Bayesian Framework

Forecasting of COVID-19 daily confirmed cases has been one of the several challenges posed on the governments and health sectors on a global scale. To facilitate informed public health decisions, the concerned parties rely on short-term daily projections generated via predictive modeling. We calibrate stochastic variants of growth models and the standard SIR model into one Bayesian framework to evaluate their short-term forecasts. In summary, it was noted that none of the models proved to be golden standards across all the regions in their entirety, while all outperformed ARIMA in a predictive capacity as well as in terms of interpretability.
SARS-CoV-2 sequencing reveals rapid transmission from college student clusters resulting in morbidity and deaths in vulnerable populations

College reopening decisions during the SARS-CoV-2 pandemic represent a trade-off between competing risks to students, faculty and staff, and college finances. Additionally, risks taken in reopening colleges can impose significant burdens on individuals living in surrounding communities. Many colleges that reopened for in-person instruction have reported frequent SARS-CoV-2 outbreaks. La Crosse County, Wisconsin experienced a substantial SARS-CoV-2 outbreak (2,002 cases in September 2020) that coincided with the return to in-person instruction at three local academic institutions. Genomic sequencing of SARS-CoV-2 cases in La Crosse during that period found rapid expansion of two viral substrains. Although the majority of cases were among college-age individuals, from a total of 111 genomes sequenced we identified rapid transmission of the virus into more vulnerable populations. Eight sampled genomes represented two independent transmission events into two skilled nursing facilities, resulting in two fatalities. Our study highlights the very significant risks imposed by college administrator reopening decisions, not just on college-associated populations, but on vulnerable individuals in surrounding communities.
Malaria and polypeptides of Plasmodium falciparum at the infected erythrocyte surface

Malaria is one of the top three most lethal infectious diseases in the world after tuberculosis and HIV. The disease is caused by intracellular parasites of the genus Plasmodium spp. To date, five Plasmodium spp have been linked to human infection, where Plasmodium falciparum is known to cause the most severe forms of the disease, killing upwards of 600 000 people per year. The parasite has a complex life cycle that involves two hosts, the Anopheles mosquito and the human. Humans become infected when bitten by an infected mosquito. In the human host the parasite divides asexually inside the red blood cells, each infected erythrocyte gives rise to 16-32 merozoites that egress and reinvade new red blood cells. A small subset of the parasites also sexually commit and become female or male gametocytes that are crucial for the transmission back to the mosquito. The intra erythrocytic cycle is responsible for causing the symptoms in the human host. During development in the red blood cell the parasite transports and expresses polypeptides on the cell surface making the membrane of the infected erythrocyte “sticky”. These sticky proteins mediate adhesion to uninfected red blood cells forming, so called “rosettes”. Moreover, these proteins can also bind to endothelial cells in the microvasculature, a phenomenon known as “sequestration”, which leads to severe obstruction of the blood flow in the host. Rosetting and sequestration are major pathological features of severe malaria. This thesis focuses on the polypeptides involved in parasite sequestration and rosetting. We identified the RIFIN protein family as a major mediating factor in rosetting and describe how the binding properties are dependent on the ABO blood group antigens of the human host. In addition we utilized single cell RNASeq to study differential gene expression, of important gene families that are linked to sexual commitment, sequestration and rosetting, in malaria-infected red blood cells at single cell resolution. These discoveries regarding the RIFINs are key findings in the development of novel drugs/vaccines against severe malaria disease. LIST OF SCIENTIFIC PAPERS This thesis is based on the following papers, which will be referred in the text by their Roman numbers. I. Goel S*, Mia Palmkvist*, Moll K*, Joannin N, Lara P, Akhouri RR, Moradi N, Ojemalm K, Westman M, Angeletti D, Kjellin H, Lehtio J, Blixt O, Idestrom L, Gahmberg CG, Storry JR, Hult AK, Olsson ML, von Heijne G, Nilsson I, Wahlgren M. RIFINs are adhesins implicated in severe Plasmodium falciparum malaria. Nature Medicine. 2015 Apr;21(4):314-7 II. Moll K, Mia Palmkvist, Ch'ng J, Kiwuwa MS, Wahlgren M. Evasion of Immunity to Plasmodium falciparum: Rosettes of blood group A impair recognition of PfEMP1 PLoS One. 2016 Feb 12;11(2):e0149765 III. Ngara M*, Mia Palmkvist*, Sagasser S*, Ankarklev J, Bjorklund K. A, Wahlgren M, Sandberg R. Transcriptional heterogeneity of Plasmodium falciparum at cellular level Manuscript * Equal contribution CONTENTS
The effect of protease on growth performance, nutrient digestibility, and expression of growth-related genes and amino acid transporters in broilers

Abstract During the course of this trial, our team assessed the influence of protease upon the growth performance, the nutrient digestibility, and the expression of growth-related genes and amino acid transporters within the liver, muscle, and small intestines of broilers. During the first step, our team allocated 600 broilers into four dietary treatments for a period of 35 days in order to measure the growth performance and nutrient digestibility of the broilers selected. The separate treatments contained 10 replicates (15 birds per replicate). The treatments were composed of: 1) CON, basal diet; 2) T1, basal diet + 0.03% protease; 3) T2, basal diet + 0.06% protease; and 4) T3, basal diet + 0.09% protease. Next, the broiler chick sample tissue was harvested from the CON and T3 groups in order to conduct gene expression analysis following the feeding trials the broilers underwent. Our team discovered that the broilers fed protease diets possessed increased body weight and an average daily gain, but conversely, had lower feed conversion ratios when their dietary protease levels increased from 0% to 0.09% (p < 0.05). Additionally, significant linear improvements were identified among the nutrient digestibility of dry matter, crude protein, energy, and amino acids within broilers supplied with protease diets when contrasted and compared with broilers supplied with the basal diet (p < 0.05). In addition, the gene expression of the genes IGF1, IGF2, GH, and LEP in the liver, and the genes MYOD1 and MYOG in the breast muscles, was significantly increased after broilers were fed with a protease diet as compared to broilers that subsisted on a basal diet (p < 0.05). Protease supplementation also raised the expression levels within these amino acid transporters: SCL6A19, SLC7A1, SLC7A7, SLC7A2, SLC7A6, SLC7A9, and SLC15A1, located in the small intestine, when compared to the basal diet (p < 0.05). Our results suggest that protease supplementation in their diet improved the growth performance of broilers via an increase in the expression growth-related genes within broiler liver and muscle tissue. In addition, protease supplementation enhanced broiler digestibility via the upregulation of amino acid transporter expression within the small intestine.
Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Neighborhood Features

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks? Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking. We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images. Methods: Satellite images were extracted with the Google Static Maps application programming interface for 430 counties representing approximately 68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors. Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r=0.72). Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race and age. Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g. sidewalks, driveways and hiking trails) associated with lower mortality. Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.
COVID-19 in Italy: targeted testing as a proxy of limited health care facilities and a key to reducing hospitalization rate and the death toll.

The novel Coronavirus SARS-CoV-2 (CoV) has induced a worldwide pandemic, notably in Italy, one of the worst-hit countries in Europe, which witnessed a death toll unseen in the recent past. There are potentially many factors, such as infections from undetected index cases, early vs late testing strategies, limited health care facilities etc., that might have aggravated the COVID-19 situation in Italy. We developed a COVID-19 specific infection epidemic model composed of susceptible (S), exposed (E), carrier (C), infected (I), recovery (R) and dead (D) (SECIRD), specifically parameterized for Italy to disentangle the impact of these factors and their implications on infection dynamics to help planning an effective control strategy for a possible second wave. Our model discriminates between detected infected and undetected individuals who played a crucial role in the disease spreading and is not well addressed by classical SEIR-like transmission models. We first estimated the number of undetected infections through a Bayesian Markov Chain Monte Carlo (MCMC) framework, which ranges from ~7 to ~22 fold higher than reported infections, depending upon regions. We exploited this information to evaluate the impact of the undetected component on the evolution of the pandemic and the benefits of an enhanced testing strategy. In high testing regions like Veneto, 18% of all infections resulted in hospitalization, while for Lombardia and Piemonte, it is 25% and 27%, respectively. We investigated the impact of an overwhelmed health care system upon death toll by applying hospital and intensive care unit (ICU) capacities in the SECIRD model, and we estimated a 10% reduction in death in Lombardia, the worst hit region, if a higher number of hospital facilities had been available since the beginning. Adopting a combined strategy of rapid early and targeted testing (~10 fold) with increased hospital capacity would help in avoiding bottlenecks affecting the health care system. Our results demonstrate that the early testing would have a strong impact on the overall hospital accessibility and, hence, upon death toll (~20% to 50% reduction) and could have mitigated the lack of facilities at the crucial middle stage of the epidemic.
Prone positioning of non-intubated patients with COVID-19 - A Systematic Review and Meta-analysis

Purpose: Several studies have reported adopting prone positioning (PP) in non-intubated patients with COVID-19-related hypoxaemic respiratory failure. This systematic review and meta-analysis evaluated the impact of PP on oxygenation and clinical outcomes. Methods: We searched PubMed, Embase and COVID-19 living systematic review from December1st 2019 to July23rd 2020. We included studies that reported using PP in hypoxaemic, non-intubated adult COVID-19 patients. Primary outcome measure was the weighted mean difference (MD) in oxygenation parameters (PaO2/FiO2, PaO2 or SpO2) pre and post-PP. Results: Fifteen single arm observational studies reporting PP in 449 patients were included. Substantial heterogeneity was noted in terms of, location within hospital where PP was instituted, respiratory supports, frequency and duration of PP. Significant improvement in oxygenation was reported post-PP: PaO2/FiO2, (MD 37.6, 95%CI 18.8, 56.5); PaO2, , (MD 30.4 mmHg, 95%CI 10.9, 49.9); and SpO2, (MD 5.8%, 95%CI 3.7, 7.9). Patients with a pre-PP PaO2/FiO2 [≤]150 experienced greater oxygenation improvements compared with those with a pre-PP PaO2/FiO2 >150 (MD 40.5, 95%CI -3.5, 84.6) vs. 37, 95%CI 17.1, 56.9). Respiratory rate decreased post-PP (MD -2.9, 95%CI -5.4, -0.4). Overall intubation and mortality rates were 21% (90/426) and 26% (101/390) respectively. No major adverse events were reported. Conclusions: Despite significant variability in frequency and duration of PP and respiratory supports, PP was associated with improvements in oxygenation parameters without any reported serious adverse events. Major limitation being lack of control arm and adjustment for confounders. Clinical trials are required to determine the effect of awake PP on patient-centred outcomes.
Tissue Standards Using Stain Free Gels as a Superior Approach for Aging Research

A good loading control is critical for accurate comparison of tissue protein levels in aged and young tissue. After reviewing the literature we discovered that the housekeeping proteins commonly used in Western analysis had significant drawbacks. The purpose of this study was to evaluate the linearity and reproducibility of common housekeeping proteins tubulin, actin and GAPDH compared to measures of total protein staining using Direct Blue and Stain Free gels. We found that measurements of total protein staining were superior to housekeeping proteins both in linearity and reproducibility in young and old mouse, liver, heart, and brain. Among the total protein staining methods, the Stain Free method was superior to Direct Blue, in terms of lower variability and higher accuracy in all tissues, at both ages.
Synthesis and characterization of fruit mediated silver nanoparticles using tamarindus indica fruit extract

The production of silver nanoparticles by chemical and physical methods is expensive and the reagents used are deleterious. Green syntheses of silver nanoparticles have more attention due to their eco-friendliness, least toxicity and cost effective. Tamarindus indica fruit was selected, because of its low cost, easily available and medicinal value. Silver nanoparticles are prepared using aqueous silver nitrate with tamarindus indica fruit extract as reducing and stabilizing agent. The formation of silver nanoparticles was monitored by UVVis spectrophotometry. The mean particle diameter of silver nanoparticles was calculated from the XRD pattern according to the line width of the plane and refraction peak using the Scherrer’s equation. The FTIR spectrum analyses identify the biomolecule that are responsible for reduction and stabilization of silver nanoparticles.
Implementation of a Model of Inventories in Five Mipymes in the City of Neiva, Republic of Colombia

Bearing in mind that most of the productive units in the country correspond to Mipymes and the contribution they are making to the economy. It is necessary to know some series of situations related to their administrative management that, due to lack of knowledge, resources, the same business culture, make them are uncompetitive and productive in an environment in which every day there are major challenges. One of the aspects that affect them, has to do with the handling of inventories, this to the extent that many of the Mipymes do not have an inventory management system that allows them to make efficient use of resources. Precisely this was proven during the development of the applied research instruments, which included the implementation of the ABC Inventory Management Model, where the companies have low rotation products in their inventories, which leads to a series of unnecessary costs and that undoubtedly affects your finances. All this leads to the idea of working on the implementation of an inventory management model according to the needs of Mipymes For this, it is necessary to know the way in which the inventories are handled, for such case from the development of the survey and the five selected MSMEs. The second is to identify the shortcomings of the inventories studied, and the third to determine the inventory model to be used and to implement it in Mipymes. Keyword: Inventory, Optimization, Simulation, Implementation
A New Species of Phrynopus (Anura: Leptodactylidae) from Perú@@@A New Species of Phrynopus (Anura: Leptodactylidae) from Peru

THE leptodactylid genus Phrynopus includes 18 species occupying moderate to high elevations (>1000 m) in the Andes of South America (Frost, 1985; Cannatella, 1985; Lynch, 1986). Most species are allopatric in distribution. Phylogenetically, Phrynopus is believed to be an offshoot of the large genus Eleutherodactylus (ca 450 sp.; Hedges, 1989), differing from that group by the absence of circumferential grooves on the digital pads (Lynch, 1975; Cannatella, 1984, 1985). Also, some species ofPhrynopus lack the T-shaped terminal phalanges present in Eleutherodactylus (Lynch, 1975). Recently, I had the opportunity to collect in a relatively isolated mountain range east of the Andes in central Peru. Rising to over 4000 m, the Cordillera Yanachaga is bordered on the west by the Rio Huancabamba and Rio Chontabamba, and on the east by the drainage system of the Rio Palcazu and Rio Cacazu. Most of the