Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of genetic and chemical variability of five Curcuma species based on DNA barcoding and HPLC fingerprints

The rhizomes of Curcuma species have a long medicinal history in Asia. In China, Curcuma species mainly be utilized to make pharmaceutical products, including C. phaecocaulis, C. aromatica, C. wenyujin, C. kwangsiensis and C. longa. In this study, twenty-four samples were selected to study the genetic and chemical variability among five Curcuma species. The ITS2 and trnK intron gene fragment were used to identify the five Curcuma species, the differences in chemical composition were computed using the Euclidean distance based on the data of HPLC characteristic peak areas and the content of six key components, and agronomic characteristics were analyzed including morphological and volatile oil characteristics. The ITS2 and trnK intron gene fragment could distinguish the five Curcuma species clearly. The genetic distance between Curcuma species ranged from 0.0085 to 0.0767 based on the data of ITS2 gene sequences with 32 variation sites, and the genetic distance between Curcuma species ranged from 0.0003 to 0.0194 based on the data of trnK intron gene sequences with 39 variation sites. Five Curcuma species showed otherness chemical composition characteristics, with the Euclidean distance ranging from 3.373 to 6.998. The C. longa showed the biggest variation compared with other species, with the Euclidean distance above 6.239. Among the samples of the original plants of Ezhu, the volatile oil yield of W1 was the highest, reached to 105.75 mL per single plant. Among all the samples, J6 showed the highest yield of volatile oil, reached to 149.42 mL per single plant. The results showed that chemical composition similarity of the medicinal plants was the primary proof for the selection of the original plants of the Curcuma medicinal materials. The genetic distance and chemical variability were important references for discovering new medicinal plant resources.
Reliability tests for Doppler imaging

In recent years, Doppler imaging codes have been developed by a number of different groups and successfully applied to map the spot distribution on stellar surfaces. As more and more images are obtained we tend to see a pattern of high-latitude spots, particularly on RS CVn systems. These high-latitude spots were and still are greeted with scepticism as they are inferred from non-varying profile deformations. Here, I describe some of the problems of Doppler imaging and their likely impact on the resulting images.
The Eurabia Conspiracy Theory: Twitter’s Political Influencers, Narratives, and Information Sources

In recent years, conspiracy theories on social media have emerged as a significant issue capable of undermining social perceptions of European integration. Narratives such as the Eurabia doctrine, which would imply an ethnic replacement of the indigenous European population with migrants (Bergmann, 2018), have been a significant resonance. Thanks to computational analysis, we have collected data from Twitter over three years (2020, 2021, and 2022) during the Covid-19 pandemic. In this period, we collected over 50,000 tweets strictly related to the Eurabia doctrine topic in different European languages. Analysing the collected data, we identified the most relevant voices spreading conspiracy theories online, the emerging narratives related to the Eurabia doctrine, and the primary sources used by the most active or mentioned subjects in spreading disinformation.
Edge Sensing of Mental States Using a Scale-Balancing Brain–Computer Interface

Negative mental states often cause inappropriate behaviors or incorrect operations. Human factors, in particular, are responsible for more than half of all mining safety accidents in the dim and noisy mining environments, endangering workers’ lives and production safety. Although the audiovisual brain–computer interface (BCI) can collect electroencephalogram (EEG) signals, which objectively reflect an individual’s mental state without brain invasion, it is difficult to adapt it for the mining industry because of the lacked balances in the scales for the key electrode determination, EEG filtering, and feature optimization. This work proposes an edge-sensing method for mental states by using a scale-balancing BCI. First, the balanced electrode positions of a BCI are determined by using a fused node integrity evaluation algorithm, which overcomes the coarse-grained sorting problem of the ${k}$ -shell analysis. Second, an improved filtering algorithm is used for the EEG signal filtering, in which a center frequency aliasing factor is defined to avoid the overlapping problem of the variation mode component analysis. Third, the feature optimal learning algorithm is formed by a hybrid loss function with manifold learning. Fourth, mental state sensing is implemented by using the proposed edge sensing method and the EEG features of intensity and connectivity. Experiments show that a noise intensity above 80 dB is likely to evoke a negative mental state, and a noise intensity above 105 dB is more likely to evoke a fearful mental state in the mining environment.
Sustainable Indigenous Knowledge Systems in Agriculture in Zimbabwe's Rural Areas of Matabelel and North and South Provinces: Zimbabwe Case Study

This study researched Indigenous Knowledge Systems (IKS) in agriculture in Zimbabwe's rural areas, focusing on crop farming in the Tonga of Binga District in Matebeleland's North Province, and livestock in the Kalanga tribe of the Plumtree District in Matebeleland's South Province. The study aimed to uncover some of the knowledge that indigenous people used to survive under the harsh climatic and physical conditions of the region. Specific goals in both the Binga and Plumtree Districts were: 1) to uncover the socio-political, religious, economic, and environmental implications of IKS in farming; 2) to identify and analyze the methods of natural resources management; and 3) to assess the value and limitations of IKS in agriculture.
Development of a Liquid Chromatography–Tandem Mass Spectrometry (LC–MS/MS) Method for Characterizing Linalool Oral Pharmacokinetics in Humans

Lavender (Lavandula angustifolia Miller or Lavandula officinalis Chaix) is an ethnopharmacological plant commonly known as English lavender. Linalool and linalyl acetate are putative phytoactives in lavender essential oil (LEO) derived from the flower heads. LEO has been used in aroma or massage therapy to reduce sleep disturbance and to mitigate anxiety. Recently, an oral LEO formulation was administered in human clinical trials designed to ascertain its anxiolytic effect. However, human pharmacokinetics and an LC–MS/MS method for the measurement of linalool are lacking. To address this deficiency, a rapid and sensitive liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was developed for the analysis of linalool in human serum. Prior to the analysis, a simple sample preparation protocol including protein precipitation and liquid–liquid extraction of serum samples was created. The prepared samples were analyzed using a C18 reversed-phase column and gradient elution (acetonitrile and water, both containing 0.1% formic acid). A Waters Xevo TQ-S tandem mass spectrometer (positive mode) was used to quantitatively determine linalool and IS according to transitions of m/z 137.1→95.1 (tR 0.79 min) and 205.2→149.1 (tR 1.56 min), respectively. The method was validated for precision, accuracy, selectivity, linearity, sensitivity, matrix effects, and stability, and it was successfully applied to characterize the oral pharmacokinetics of linalool in humans. The newly developed LC–MS/MS-based method and its application in clinical trial serum samples are essential for the characterization of potential pharmacokinetic and pharmacodynamic interactions.
On the Late Saalian glaciation (160 - 140 ka): a climate modeling study

This thesis focuses on the glaciation of the Late Saalian period (160 -140 ka) over Eurasia. The Quaternary Environment of the Eurasian North project evidenced that during this period, the Eurasian ice sheet was substantially larger than during the entire Weichselian cycle and especially than during the Last Glacial Maximum (21 ka, LGM). The Late Saalian astronomical forcing were different than during the LGM while greenhouse gas concentrations were similar. To understand how this ice sheet could have grown so large over Eurasia during the Late Saalian, we use an Atmospherical General Circulation Model (AGCM), an AGCM coupled to an oceanic mixed layer and a vegetation model to explore the influence of regional parameters, sea surface temperatures (SST) and orbital parameters on the surface mass balance (SMB) of the Late Saalian Eurasian ice sheet. At 140 ka, proglacial lakes, vegetation and simulated Late Saalian SST cool the Eurasian climate, reducing the ablation along the southen margins. Dust deposition on snow have the opposite effect. The presence of a Canada Basin ice-shelf during MIS 6 in the Arctic Ocean, does not affect the mass balance of the ice sheet. According to geological evidences, the Late Saalian Eurasian ice sheet reached its maximum extent before 160 ka. Northern Hemisphere high latitudes summer insolation shows a large insolation peak towards 150 ka. The simulated climate prior to 140 ka is milder and ablation is larger along the southern margins of the Eurasian ice sheet although the mean annual SMB is positive. The Late Saalian Eurasian ice sheet, may have been large enough to generate its own cooling needed for its maintenance over Eurasia.
PARP inhibitors: risk factors for toxicity and matching patients to the proper poly (ADP-ribose) polymerase inhibitor (PARPi) therapy

The past 5 years have seen several fundamental advances in ovarian cancer, with important new insights towards novel therapeutic opportunities within the DNA repair pathway. With the incorporation of poly (ADP-ribose) polymerase inhibitors (PARPi) into maintenance treatment regimens, the management of short- and long-term adverse events are key clinical priorities. Currently, three different PARPi are clinically beneficial and have been approved for primary and recurrent ovarian cancer: olaparib, niraparib, and rucaparib. The duration of treatment with PARPi in patients with ovarian cancer varies; patients can receive treatment for up to 2 or 3 years in first-line setting, or continue treatment until unacceptable toxicity or progression occurs in recurrent disease. Despite their similar mechanisms of action, these three inhibitors have specific toxicity profiles, which may lead to dose interruptions or discontinuation of treatment. This review summarizes the current indications for PARPi, including their role in recurrent and first-line maintenance treatment for advanced ovarian cancer. We also outline dose modifications leading to treatment disruption and potential changes in quality of life after prolonged treatment. Finally, we highlight the patient groups most likely to benefit from each of the three different PARPi.
‘Candidatus Phytoplasma ziziphi’ Changes the Metabolite Composition of Jujube Tree Leaves and Affects the Feeding Behavior of Its Insect Vector Hishimonus hamatus Kuoh

Simple Summary Phytoplasma are wall-less phytopathogens that invade hundreds of plant species, causing symptoms, including witches’ broom, phyllody, and leaf yellowing. The difficulty in phytoplasma artificial cultivation makes research on the interactions of phytoplasma–plant–vector insects lag behind the research on interactions of other phytopathogen–plant–vector insects. The spread of phytoplasma heavily relies on piercing–sucking insects. In this study, the feeding behavior of the leafhopper Hishimonus hamatus Kuoh fed on healthy Chinese jujube leaves and on jujube witches’ broom (JWB) leaves was investigated to find whether JWB infection changed the feeding behavior or preference of H. hamatus. Then, we performed a metabolomic analysis to inspect the metabolite composition of healthy and JWB-infected jujube leaves and tried to explain why the leafhopper tended to feed on JWB-infected leaves. We found that more small-molecular carbohydrates, free amino acids, and free fatty acids and less lignans, coumarins and triterpenoids were accumulated in JWB-infected leaves, which might be related to more vector leafhopper feeding with a higher frequency. Abstract Hishimonus hamatus Kuoh is a leafhopper species native to China that feeds on Chinese jujube leaves. This leafhopper species has been verified to transmit jujube witches’ broom (JWB) disease, caused by phytoplasma, a fatal plant pathogen, which belongs to the phytoplasma subgroup 16SrV-B. The transmission of JWB phytoplasma largely relies on the feeding behavior of piercing–sucking leafhoppers. However, the specific mechanisms behind how and why the infection of JWB influences the feeding behavior of these leafhoppers are not fully understood. To address this, a study was conducted to compare the feeding patterns of H. hamatus when feeding JWB-infested jujube leaves to healthy leaves using the electrical penetration graph (EPG) technique. Then, a widely targeted metabolome analysis was performed to identify differences in the metabolite composition of JWB-infected jujube leaves and that of healthy jujube leaves. The results of EPG analyses revealed that when feeding on JWB-infected jujube leaves, H. hamatus exhibited an increased frequency of phloem ingestion and spent longer in the phloem feeding phase compared to when feeding on healthy leaves. In addition, the results of metabolomic analyses showed that JWB-infected leaves accumulated higher levels of small-molecular carbohydrates, free amino acids, and free fatty acids, as well as lower levels of lignans, coumarins and triterpenoids compared to healthy leaves. The above results indicated that the H. hamatus preferentially fed on the phloem of infected leaves, which seems to be linked to the transmission of the JWB phytoplasma. The results of metabolomic analyses partially imply that the chemical compounds might play a role in making the infected leaves more attractive to H. hamatus for feeding.
Efficacy of Lenvatinib Combined with Transcatheter Intra-Arterial Therapies for Patients with Advanced-Stage of Hepatocellular Carcinoma: A Propensity Score Matching

This study aimed to evaluate the effect of lenvatinib (LEN) combined with transcatheter intra-arterial therapy (TIT) for advanced-stage hepatocellular carcinoma (HCC) after propensity score matching (PSM). This retrospective study enrolled 115 patients with advanced-stage HCC who received LEN treatment. The patients were categorized into the LEN combined with TIT group (n = 30) or the LEN monotherapy group (n = 85). After PSM, 38 patients (LEN + TIT group, n = 19; LEN monotherapy group, n = 19) were analyzed. The median overall survival (OS) in the LEN + TIT group was significantly higher than that in the LEN monotherapy group (median survival time (MST): 28.1 months vs. 11.6 months, p = 0.014). The OS in the LEN combined with transcatheter arterial chemoembolization and LEN combined with hepatic arterial infusion chemotherapy groups was significantly higher than that in the LEN monotherapy group (MST 20.0 vs. 11.6 months, 30.2 vs. 11.6 months, p = 0.048, and p = 0.029, respectively). Independent factors associated with OS were alpha-fetoprotein and LEN combined with TIT. The indications for LEN combined with TIT were age <75 years and modified albumin bilirubin (m-ALBI) grade 1. We concluded that LEN combined with TIT may improve prognosis compared with LEN monotherapy in patients with advanced-stage HCC.
Consideration of historical authenticity in heritage tourism planning and development

A review of heritage tourism literature reveals a fundamental tension over the use, function, and degree of authenticity of historic resources used for tourism development. Using a case study approach, this paper explores how stakeholder beliefs regarding historical authenticity influence the heritage tourism products, services, and experiences created for visitors and the value of historical authenticity to community stakeholders relative to other factors involved with heritage tourism development. Heritage tourism stakeholders in Manistee and Ludington, Michigan consider historic preservation and historical authenticity to be important components of heritage tourism development; however, other factors, such as providing an engaging and entertaining experience, have resulted in the creation of inauthentic contexts, stories, and experiences at some sites. Enhanced development of interpretive services is suggested as a way to preserve authenticity while also providing a more engaging experience.
Context-Aware Meta-RL With Two-Stage Constrained Adaptation for Urban Driving

End-to-end driving based on reinforcement learning (RL) has emerged as a promising approach in autonomous driving, with the potential to surpass human drivers. However, the exploration and exploitation dilemma of RL leads to low sample efficiency and high computational costs to train an optimal driving model, and the environment feedback-oriented learning mode limits the model's ability to handle unseen traffic scenarios, especially when dealing with the highly varied tasks of urban driving. In this article, we proposed a context-aware meta-RL framework with two-stage constrained adaptation for challenging urban driving. Firstly, the context-aware state representation enhanced by historical behavior is construct to improve the learning efficiency and robustness, where the most efficient context encoder is selected among four different forms. Next, the end-to-end meta-driving model with high generalization ability is built through the parallel rollouts of multiple tasks and simplified meta-training procedure. Then, a two-stage constrained adaptation strategy is designed to quickly transfer the meta model to new tasks while maintaining good performance, where the meta-training data are reused through the context-based propensity estimation to constrain the optimization objective of new tasks. Extensive experiments are performed in CARLA simulator with various urban scenarios, and the results validate the superiority of our proposed models in both learning efficiencyand generalization compared to state-of-the-art algorithms.
Examining Challenges In The Adoption of Big Data In Health Care Institutions And Its Impact On Patients Satisfaction: An empirical study in Delhi, India

The study aims to investigate the obstacles and factors influencing the adoption of big data in healthcare organizations, and its subsequent impact on patient satisfaction. Big data in healthcare refers to the collecting, analysis, and use of clinical data from patients that is too massive or complex to be grasped by standard data processing methods. Adopting big data in health care will enable manages to render services to patient and customer satisfaction. However, in the health care sector, firms must overcome several hurdles and problems by adopting new technology. A detailed literature review was undertaken to examine many obstacles associated with the use of Big Data. A well-structured questionnaire was prepared in Likert scale to find the elements that influence big data adoption and its impact on patient satisfaction. To evaluate factors, exploratory factor analysis using SPSS 21 was performed, and Structural Equation Modelling (SEM) was performed to assess key significant factors that impact patient satisfaction. The data was gathered from employees associated with the hospitals. The survey received responses from 212 participants. Following the analysis of the data, it was found that five challenging factors influences big data adoption. These are data integration, data understanding, technology and infrastructure, lack of expert and regulation barrier. These factors explained 70.36% of variance. Whereas, SEM analysis indicated that both data integration, data understanding and lack of expertise significantly affect big data adoption Furthermore, big data adoption in hospitals will help in improving patient satisfaction.
Nonlinear Relationship Between Maternal and Cord Blood Vitamin B12 and Folate from a Chinese Population-Based Study

Purpose There remains a data gap on vitamin B12 and folate level in maternal and child populations. This study aimed to assess the status of vitamin B12 and folate in maternal serum (MS) and umbilical cord serum (UCS). Materials and Methods This was a planned secondary analysis of a case-control study. A total of 858 pregnant women during late pregnancy and their newborns in the hospitals of China were included. Maternal peripheral venous blood and neonatal umbilical cord blood were collected to determine serum vitamin B12 and folate concentration. Relationship of vitamin B12 or folate concentration between MS and UCS was assessed by a quantile regression model and the non-linear relationship between them was examined. Results Nutritional status of serum folate was better than that of vitamin B12. Prevalence of deficiency in MS vitamin B12 and folate was 73.4% and 14.2%, respectively and these figures were about 17.8% and 0.1% in UCS. Both vitamin B12 and folate levels in UCS were significantly higher than those in MS (vitamin B12: 321.0 pg/mL vs 158.3 pg/mL, folate: 16.5 ng/mL vs 7.0 ng/mL, P <0.001). The median UCS-MS ratio of vitamin B12 and folate was 2.0 (95% CI: 1.94–2.06) and 2.4 (95% CI: 2.30–2.53), respectively. The levels of folate and vitamin B12 in UCS increased nonlinearly with their increase in MS which presented an inverted U-shaped curve. Conclusion Deficiency in vitamin B12 and folate in the women during late pregnancy in China is prevalent. Nutritional status of the two vitamins in umbilical cord serum is correlated nonlinearly with that in maternal serum. Folic acid supplementation may be accompanied with vitamin B12 to improve status of vitamin B12 and folate during pregnancy.
Characterization of Viral Interference in Aedes albopictus C6/36 Cells Persistently Infected with Dengue Virus 2

Arboviruses are an important group of pathogens that cause diseases of medical and veterinary concern worldwide. The interactions of these viruses with their host cells are complex, and frequently, the coexistence of two different viruses in the same cell results in the inhibition of replication in one of the viruses, which is a phenomenon called viral interference. This phenomenon can be exploited to develop antiviral strategies. Insect cell lines persistently infected with arboviruses are useful models with which to study viral interference. In this work, a model of C6/36-HT cells (from Aedes albopictus mosquitoes) persistently infected with Dengue virus, serotype 2, was used. Viral interference was evaluated via plaque and flow cytometry assays. The presence of heterotypic interference against the other serotypes of the same virus and homologous interference against yellow fever virus was determined; however, this cell line did not display heterologous viral interference against Sindbis virus. The mechanisms responsible for viral interference have not been fully elucidated, but small RNAs could be involved. However, the silencing of Ago3, a key protein in the genome-derived P-element-induced wimpy testis pathway, did not alter the viral interference process, suggesting that viral interference occurs independent of this pathway.