Miracle-dz/UniFAR-FTUs huggingface dataset:
Curative effect analysis of robot-assisted drainage surgery in treatment of spontaneous hypertensive brainstem hemorrhage

Objective Spontaneous hypertensive brainstem hemorrhage (HBSH) is characterized by sudden onset, rapid progression and poor prognosis. There has been a growing tendency of surgical treatment for HBSH. This study aimed to investigate outcomes and potential factors associated with the prognosis of robot-assisted drainage surgery for HBSH treatment. Methods Patients with HBSH from July 2016 to March 2023 at a single neurosurgery center were included and divided into conservative group and surgical groups. Baseline and clinical data, radiographic characteristics, complications, and outcome evaluations were recorded and analyzed. Results A total of 125 patients, with 74 in the conservative group and 51 in the surgical group, were enrolled in the study. Mortality at 6 months was 59/74 (79.7%) in the conservative group and 9/51 (17.6%) in the surgical group. Twenty-four patients (47.1%) achieved favorable outcomes in the surgical group, whereas this rate in the conservative group was only 5.4% (4/74). There was a significant difference in NIHSS, GCS, and mRS at 6 months between surviving patients in the conservative and surgical groups. In prognostic analysis in the surgical subgroup, initial GCS score [5 (IQR 4–7) vs. 3 (IQR 3–4), p < 0.001], NIHSS [36 (IQR 32–38) vs. 40 (IQR 38–40), p < 0.001], smoking history [45.8% (11/24) vs. 74.1% (20/27), p = 0.039], hematoma volume [6.9 (IQR 6.2–7.6) vs. 9.6 (IQR 7.3–11.4), p = 0.001], and hemorrhage location (p = 0.001) were potential risk factors for poor 6-month prognosis after robot-assisted surgery for HBSH. Conclusion Based on the results of this study, robot-assisted minimally invasive drainage of brain stem hematoma may significantly reduce mortality and improve prognosis. Surgery should be conducted for selected patients.
Photogrammetric work without blunders

The method of least squares is unsuitable for dealing with blunders in measurements. Other so called robust computation methods are explained and applied to photogrammetric problems (relative and absolute orientation) enabling the automatic detection and elimination of blunders. It is shown that these robust methods considerably improve the photogrammetric mapping process. -Authors
Use of prestack depth migration for improving the accuracy of horizontal drilling in unconventional reservoirs

Abstract Depth imaging has long been a staple in offshore processing sequences; however, conventional wisdom often dictates that prestack depth migration is unnecessary in the onshore, geologically benign settings encountered in most unconventional shale reservoirs. Using examples from the Anadarko Basin, we demonstrate that careful depth imaging using updated processing flows yields significant benefits when compared to time imaging.
Retention of Ciprofloxacin and Carbamazepine from Aqueous Solutions Using Chitosan-Based Cryostructured Composites

Water pollution is becoming a great concern at the global level due to highly polluted effluents, which are charged year by year with increasing amounts of organic residues, dyes, pharmaceuticals and heavy metals. For some of these pollutants, the industrial treatment of wastewater is still relevant. Yet, in some cases, such as pharmaceuticals, specific treatment schemes are urgently required. Therefore, the present study describes the synthesis and evaluation of promising cryostructured composite adsorbents based on chitosan containing native minerals and two types of reinforcement materials (functionalized kaolin and synthetic silicate microparticles). The targeted pharmaceuticals refer to the ciprofloxacin (CIP) antibiotic and the carbamazepine (CBZ) drug, for which the current water treatment process seem to be less efficient, making them appear in exceedingly high concentrations, even in tap water. The study reveals first the progress made for improving the mechanical stability and resilience to water disintegration, as a function of pH, of chitosan-based cryostructures. Further on, a retention study shows that both pharmaceuticals are retained with high efficiency (up to 85.94% CIP and 86.38% CBZ) from diluted aqueous solutions.
Plant-Derived Senotherapeutics for the Prevention and Treatment of Intervertebral Disc Degeneration and Aging

Chronic low back pain, a major cause of disability with a great global socioeconomic impact, has been inextricably associated with intervertebral disc degeneration. On the other hand, an enhanced number of senescent cells has been identified in aged and degenerated intervertebral discs and their senescence-associated secretory phenotype (SASP) has been connected with qualitative/quantitative alterations in the extracellular matrix and ultimately with the disturbance of tissue homeostasis. Given that selective elimination of senescent cells (by the so-called senolytics) or amendment of their secretome towards a less catabolic/inflammatory phenotype (by molecules known as senomorphics) has been reported to alleviate symptoms of several age-associated diseases and to improve tissue quality during aging, here we will review the emerging role of senolytic and senomorphic agents derived from plants and natural products against intervertebral disc degeneration. The mode of action of these senotherapeutics, as well as the challenges in their practical application, will also be explicitly discussed in an attempt to direct their more targeted and effective use in exclusive or combinatorial therapeutic schemes for the prevention and/or treatment of disc degenerative disorders.
O-Antigen decorations in Salmonella enterica play a key role in eliciting functional immune responses against heterologous serovars in animal models

Introduction Different serovars of Salmonella enterica cause systemic diseases in humans including enteric fever, caused by S. Typhi and S. Paratyphi A, and invasive nontyphoidal salmonellosis (iNTS), caused mainly by S. Typhimurium and S. Enteritidis. No vaccines are yet available against paratyphoid fever and iNTS but different strategies, based on the immunodominant O-Antigen component of the lipopolysaccharide, are currently being tested. The O-Antigens of S. enterica serovars share structural features including the backbone comprising mannose, rhamnose and galactose as well as further modifications such as O-acetylation and glucosylation. The importance of these O-Antigen decorations for the induced immunogenicity and cross-reactivity has been poorly characterized. Methods These immunological aspects were investigated in this study using Generalized Modules for Membrane Antigens (GMMA) as delivery systems for the different O-Antigen variants. This platform allowed the rapid generation and in vivo testing of defined and controlled polysaccharide structures through genetic manipulation of the O-Antigen biosynthetic genes. Results Results from mice and rabbit immunization experiments highlighted the important role played by secondary O-Antigen decorations in the induced immunogenicity. Moreover, molecular modeling of O-Antigen conformations corroborated the likelihood of cross-protection between S. enterica serovars. Discussion Such results, if confirmed in humans, could have a great impact on the design of a simplified vaccine composition able to maximize functional immune responses against clinically relevant Salmonella enterica serovars.
Reading Comprehension in the Medical Education Curriculum during the covid 19: A global Perspective

The coronavirus caused the global effect of the COVID-19 pandemic, which began in early 2020. Due to the emergence of various infectious illnesses, it is essential for medical students to possess the skills to investigate and treat them. Therefore, it is essential for medical students to peruse the materials provided by the World Health Organisation in order to get a comprehensive understanding of the many symptoms associated with the recently emerged illness, as well as the need for early detection and prevention. Hence, the objective of this study is to emphasise the significance of medical students engaging with novel sources of information and how their proficiency in doing so, whether effective or ineffective, is contingent upon their reading comprehension strategies. Many medical students globally lack sufficient understanding of the recommended infection control practices. Their reading impairments also hindered their comprehension of their medical condition, resulting in delayed diagnosis and inadequate use of preventive medications. The study findings show that, due to the limited scope of medical education programmes, the curriculum for medical colleges did not provide comprehensive instruction on reading comprehension techniques. Currently, there is a lack of comprehensive academic literacy training for medical research in these curricula. Thus, anyone pursuing a medical education should acquire knowledge by studying the resources provided by the World Health Organisation.
System Dynamics Simulation of Information Diffusion Strategies for Typhoon Disasters: A Case from China Coastal Area

ABSTRACT Zhong, Z. , 2018. System dynamics simulation of information diffusion strategies for typhoon disasters: A case from China coastal area. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 741–753. Coconut Creek (Florida), ISSN 0749-0208. The purpose of this paper is to probe into the diffusion and evolution of typhoon disaster information on the Internet based on system dynamics to explore new potential emergency management strategies. Reducing losses, both economic and societal, is the most important response to typhoon disasters. In addition to the destruction directly caused by a typhoon event, information diffusion problems such as information interruption, false information, information fragmentation, and information distortion are highly problematic. This paper built a quantitative simulation model underlying the mechanism of network information diffusion specifically regarding typhoon disasters. This paper then explored the internal influence factors and associated mechanisms of the dynamic model as they relate to the effective control and guidance of information dissemination. It was found that the proposed reference model involving information diffusion strategies for typhoon disasters can successfully capture the key elements and information diffusion mechanism. The system dynamics approach can effectively enable a macro viewpoint of information diffusion strategies and policies for typhoon disasters. This paper provides a model for evaluating policy for information diffusion strategies for typhoon disasters in a dynamic context, for China. It is shown to be valuable to information diffusion strategies testing and simulating based on the system dynamics perspective.
mRNA-Based Vaccines Are Highly Immunogenic and Confer Protection in the Gnotobiotic Pig Model of Human Rotavirus Diarrhea

Human rotavirus (HRV) is still a leading cause of severe dehydrating gastroenteritis globally, particularly in infants and children. Previously, we demonstrated the immunogenicity of mRNA-based HRV vaccine candidates expressing the viral spike protein VP8* in rodent models. In the present study, we assessed the immunogenicity and protective efficacy of two mRNA-based HRV trivalent vaccine candidates, encoding VP8* of the genotypes P[8], P[6], or P[4], in the gnotobiotic (Gn) pig model of Wa (G1P[8]) HRV infection and diarrhea. Vaccines either encoded VP8* alone fused to the universal T-cell epitope P2 (P2-VP8*) or expressed P2-VP8* as a fusion protein with lumazine synthase (LS-P2-VP8*) to allow the formation and secretion of protein particles that present VP8* on their surface. Gn pigs were randomly assigned into groups and immunized three times with either P2-VP8* (30 µg) or LS-P2-VP8* (30 µg or 12 µg). A trivalent alum-adjuvanted P2-VP8* protein vaccine or an LNP-formulated irrelevant mRNA vaccine served as the positive and negative control, respectively. Upon challenge with virulent Wa HRV, a significantly shortened duration and decreased severity of diarrhea and significant protection from virus shedding was induced by both mRNA vaccine candidates compared to the negative control. Both LS-P2-VP8* doses induced significantly higher VP8*-specific IgG antibody titers in the serum after immunizations than the negative as well as the protein control. The P[8] VP8*-specific IgG antibody-secreting cells in the ileum, spleen, and blood seven days post-challenge, as well as VP8*-specific IFN-γ-producing T-cell numbers increased in all three mRNA-vaccinated pig groups compared to the negative control. Overall, there was a clear tendency towards improved responses in LS-P2-VP8* compared to the P2-VP8*mRNA vaccine. The demonstrated strong humoral immune responses, priming for effector T cells, and the significant reduction of viral shedding and duration of diarrhea in Gn pigs provide a promising proof of concept and may provide guidance for the further development of mRNA-based rotavirus vaccines.
Issues and Challenges in Seismic Risk Evaluation and its Uncertainty Reduction for the Nankai Trough Earthquake

Uncertainty Reduction for the Nankai Trough Earthquake Author(s) LEE, Seung Han; NISHIJIMA, Kazuyoshi; MATSUSHIMA, Shinichi; MIYAZAWA, Masatoshi; MOCHIZUKI, Kimihiro; IIDAKA, Takashi; UEDA, Kyohei; KAWASE, Hiroshi; MAKI, Norio Citation 京都大学防災研究所年報. B = Disaster Prevention Research Institute Annuals. B (2017), 60(B): 354-365 Issue Date 2017-09 URL http://hdl.handle. net/2433/229393 Right Type Departmental Bulletin Paper Textversion publisher
Utilizing mobile digital radiography for detection of thoracolumbar vertebrae traits in live donkeys

It has been well-established that the number of vertebrae is associated with body size and meat productivity. In current study we utilized a digital radiography (DR) technology to detect the number of thoracolumbar vertebrae in live donkeys. For this purpose, we introduced for the first time a groundbreaking device designed by our team for assessing thoracolumbar vertebrae number traits in equids, employing a sample of 1,000 donkeys sourced from five distinct donkey farms. This assessment incorporates a range of crucial body metrics, including body height, length, and various other measurements. Subsequently, our study determined the number of thoracolumbar vertebrae in 112 donkeys, utilizing the DR system. These findings were further validated through post-mortem evaluations conducted by slaughtering the donkeys. Our findings demonstrated a remarkable resemblance between the thoracolumbar vertebrae numbers visualized through the DR system in live donkeys and those obtained via slaughter verification. In conclusion, this research underscores the accuracy and effectiveness of the DR system for the detection of thoracolumbar vertebrae in live donkeys, which might be helpful for assessing the body size and meat productivity. We also recommended the utilization of DR system for counting thoracolumbar vertebrae in other animals in live state and could be a useful addition to livestock business industry for the prediction of body size and meat productivity efficiency.
Influence of ENSO on Deviation of The Season Onset in Java Based on CCAM Downscaling Data

The research of season onset in Java is very important, considering Java is the center of agriculture in Indonesia. The onset of the rainy and drought season in Java are strongly influenced by global atmospheric phenomena, such as monsoon and El Nino Southern Oscillation (ENSO). This study used spatial analysis from previous researches focusing on insitu data. The data used in this current study based on the downscaling output of atmospheric model with ±15km spatial resolution. The result shows that the season onset deviation in Java Island exist when El Nino and La Nina occurred. When the El Nino (La Nina) occurred, the onset of drought season in Java has a tendency to come faster (slower) than neutral conditions. On the other hand, when El Nino (La Nina) occurs, the onset of rainy season in Java comes slower (faster) compared to the neutral condition. This is probably related to disturbance of monsoon in Indonesia when El Nino and La Nina occurred. The study also confirmed that the effects of El Nino and La Nina in the rainy season are stronger than in the dry season.
On the ecohydrology of the Yucatan Peninsula: Evapotranspiration and carbon intake dynamics across an eco‐climatic gradient

The hydrology and productivity of the ecosystems of the Yucatan Peninsula (YP) are highly constrained by two factors: (a) the lack of surface drainage networks due to the existence of a highly permeable and connected karstic aquifer roughly the size of the peninsula and (b) a climatic gradient that leads to a transition from seasonally dry deciduous and sub‐deciduous tropical forests, in the north‐western and central parts of the Peninsula, to evergreen forests, in the southern and eastern parts. As a result, surface water fluxes of the YP are restricted to evapotranspiration (ET) that are tightly coupled to ecosystems health and gross primary productivity (GPP). The magnitude and seasonal variation of these fluxes are sensitive to climatic variability and perturbations caused by extreme events such as droughts and tropical storms that are frequent in the YP. In this study, we assess the spatio‐temporal dynamics of ET and GPP above average dry and wet conditions through time series analyses of 15 years of remotely sensed data from both Moderate Resolution Imaging Spectroradiometer and Tropical Rainfall Measuring Mission satellite products. Our results show that ET and GPP follow a regional moisture and temperature gradient that highly controls the distribution of ecosystems within the peninsula. We observe that ET and GPP are in phase with the rainy season in the deciduous forests, but for the evergreen forests, only the GPP is in phase. Additionally, and with the exception of droughts on deciduous ecosystems of the northern part of the YP, the productivity of these ecosystems shows a legacy effect, responding more to a defined trajectory (wetting or drying on the previous years), rather than to punctual extreme climatic events. This has implications on the resilience of these ecosystems to natural perturbations of climate. Comparisons between deciduous and evergreen forest indicate that both types of ecosystems have different plant water use strategies in response to hydrologic variability.
Learning from a failed project – challenges of implementing ‘green’ technology in a real world setting

ABSTRACT Sustainable development goals are defined at various institutional and organisational levels, and generate numerous ‘green’ technology projects. Most research concerns successful projects, and good examples are put forward for others to learn from. However, to pave the way for sustainability in practice, more knowledge is needed about the failed projects – what, or who, obstructs the realisation of ecologically motivated projects? This study explores, from a time-geographical perspective, a failed project concerning the introduction of individual metering and debiting of hot tap water in rented flats in Sweden. The study is based on interviews with key persons, observations and documents. The results underline the importance of acknowledging all project constraints and their interrelationship in an implementation process to explain project failure, being of an economic, political, social, cultural, technical, physical or legislative nature. Put into local contexts, similar ‘green technology’ will have different connotations and will have to deal with place-specific constraints. The project owner’s possibility to control and overcome local constraints will determine if the project will succeed or fail.
Identifying Environmental Risk Factors and Mapping the Distribution of West Nile Virus in an Endemic Region of North America

Understanding the geographic distribution of mosquito‐borne disease and mapping disease risk are important for prevention and control efforts. Mosquito‐borne viruses (arboviruses), such as West Nile virus (WNV), are highly dependent on environmental conditions. Therefore, the use of environmental data can help in making spatial predictions of disease distribution. We used geocoded human case data for 2004–2017 and population‐weighted control points in combination with multiple geospatial environmental data sets to assess the environmental drivers of WNV cases and to map relative infection risk in South Dakota, USA. We compared the effectiveness of (1) land cover and physiography data, (2) climate data, and (3) spectral data for mapping the risk of WNV in South Dakota. A final model combining all data sets was used to predict spatial patterns of disease transmission and characterize the associations between environmental factors and WNV risk. We used a boosted regression tree model to identify the most important variables driving WNV risk and generated risk maps by applying this model across the entire state. We found that combining multiple sources of environmental data resulted in the most accurate predictions. Elevation, late‐season humidity, and early‐season surface moisture were the most important predictors of disease distribution. Indices that quantified interannual variability of climatic conditions and land surface moisture were better predictors than interannual means. We suggest that combining measures of interannual environmental variability with static land cover and physiography variables can help to improve spatial predictions of arbovirus transmission risk.
Unsupervised Machine Learning for Bot Detection on Twitter: Generating and Selecting Features for Accurate Clustering

Twitter is a popular social media platform that is widely used by individuals and businesses. However, it is vulnerable to bot attacks, which can have negative effects on society. Supervised machine learning techniques can detect bots but require labeled data to differentiate between human and bot users. Twitter generates a significant amount of unlabeled data, which can be expensive to label. Unsupervised machine learning techniques, specifically clustering algorithms, are crucial for managing this data and reducing computational complexity. Effective feature selection is necessary for clustering, as some features are more important than others. This study aims to enhance feature reliability, introduce new features, and reduce them to improve bot identification accuracy using clustering algorithms. The study achieved an accuracy rate of 0.99 in four clustering algorithms, including agglomerative hierarchy, k-medoids, DBSCAN, and K-means. This was accomplished by minimizing dataset dimensions and selecting essential features. By employing unsupervised machine learning techniques, Twitter can detect and mitigate bot attacks more efficiently, which can positively impact society