Miracle-dz/UniFAR-FTUs huggingface dataset:
Water supply emergency preparedness and response in health care facilities: A systematic review on international evidence

Introduction Enabling health care facilities to deal with impairments or outages of water supply and sewage systems is essential and particularly important in the face of growing risk levels due to climate change and natural hazards. Yet, comprehensive assessments of the existing preparedness and response measures, both in theory and practice, are lacking. The objective of this review is to assess water supply and wastewater management in health care facilities in emergency settings and low-resource contexts. It thereby is a first step toward knowledge transfer across different world regions and/or contexts. Method A systematic review was performed to identify published articles on the subject using online MEDLINE and Web of Science. The initial searches yielded a total of 1,845 records. Two independent reviewers screened identified records using selection criteria. A total of 39 relevant studies were identified. Descriptive analyses were used to summarize evidence of included studies. Results Overall, water supply was far more discussed than wastewater management. Studies on emergency preparedness identified back-up water storage tank, additional pipelines, and underground wells as key sources to supply health care facilities with water during an emergency. In emergency response, bottled of water, followed by in-situ back-up water storage tanks previously installed as part of disaster preparedness measures, and tanker trucks to complete were most used. Questions on how to improve existing technologies, their uptake, but also the supplementation by alternative measures remain unanswered. Only few guidelines and tools on emergency preparedness were identified, while multiple studies formulated theoretical recommendations to guide preparedness. Recovery planning was rarely discussed, despite many studies mentioning the importance of the reconstruction and restoration phases. Literature focus on recovery is mostly on technical aspects, while organizational ones are largely absent. Despite their key role for preparedness and response, citizens and patients' perspectives are hugely underrepresented. This fits into the bigger picture as communication, awareness raising and actor cooperation in general is addressed comparatively little. Discussion Combining organizational and technical aspects, and intersecting theory and practice will be necessary to address existing gaps. Improving both, preparedness and response, is key to maintaining public health and providing primary care.
Aptamer nucleotide analog drug conjugates in the targeting therapy of cancers

Aptamers are short single-strand oligonucleotides that can form secondary and tertiary structures, fitting targets with high affinity and specificity. They are so-called “chemical antibodies” and can target specific biomarkers in both diagnostic and therapeutic applications. Systematic evolution of ligands by exponential enrichment (SELEX) is usually used for the enrichment and selection of aptamers, and the targets could be metal ions, small molecules, nucleotides, proteins, cells, or even tissues or organs. Due to the high specificity and distinctive binding affinity of aptamers, aptamer–drug conjugates (ApDCs) have demonstrated their potential role in drug delivery for cancer-targeting therapies. Compared with antibodies which are produced by a cell-based bioreactor, aptamers are chemically synthesized molecules that can be easily conjugated to drugs and modified; however, the conventional ApDCs conjugate the aptamer with an active drug using a linker which may add more concerns to the stability of the ApDC, the drug-releasing efficiency, and the drug-loading capacity. The function of aptamer in conventional ApDC is just as a targeting moiety which could not fully perform the advantages of aptamers. To address these drawbacks, scientists have started using active nucleotide analogs as the cargoes of ApDCs, such as clofarabine, ara-guanosine, gemcitabine, and floxuridine, to replace all or part of the natural nucleotides in aptamer sequences. In turn, these new types of ApDCs, aptamer nucleotide analog drug conjugates, show the strength for targeting efficacy but avoid the complex drug linker designation and improve the synthetic efficiency. More importantly, these classic nucleotide analog drugs have been used for many years, and aptamer nucleotide analog drug conjugates would not increase any unknown druggability risk but improve the target tumor accumulation. In this review, we mainly summarized aptamer-conjugated nucleotide analog drugs in cancer-targeting therapies.
On hypersonic boundary-layer interactions and transition

Certain features of recent theoretical research into hypersonic flow are described, concerning boundary layers, shock layers, nozzle flows, wakes, viscous-inviscid interactions, and hypersonic instability and transition. The research is on the continuum range, for high Mach numbers and high Reynolds numbers. The fundamental area of steady, laminar, external planar flows in the hypersonic strong- interaction regime is studied first, for flat-plate and thin airfoils. The interplay of the equally thick viscous and inviscid layers, and the bounding shock, induces global upstream influence of a particularly severe kind, requiring a special computational treatment to determine the flow solution. Secondly, internal steady flow is discussed for a slender hypersonic nozzle configuration which produces a two-stage flow structure downstream of the nozzle throat. Similarities and differences between these external and internal flows are pointed out. Thirdly, properties of instability and transition of the hypersonic boundary layer, its wake and the inviscid outer layer are considered. These include the viscous and the inviscid modes within the viscous boundary layer, inviscid modes within the outer layer, their interaction, vortex-wave interactions, finite-time break-up in the unsteady interactive boundary layer, and surface cooling. Some experimental comparisons, and open problems, are also described.
Evaluation of the pharmacological effects and exploration of the mechanism of traditional Chinese medicine preparation Ciwujia tablets in treating insomnia based on ethology, energy metabolism, and urine metabolomic approaches

Ciwujia Tablets (CWT) are produced by concentrating and drying the extract solution of the dried rhizome of Eleutherococcus senticosus (Rupr. & Maxim.) Maxim [Araliaceae; E. senticosus radix et rhizoma]. Besides, CWT is included in the 2020 edition of Chinese Pharmacopoeia and is widely used in the treatment of insomnia. It mainly contains eleutheroside B, eleutheroside E, isofraxidin, eleutheroside C, ciwujiatone, and chlorogenic acid, as well as other chemical components. Although the clinical efficacy of CWT in treating insomnia has been confirmed, its functions and pharmacological effects have not been systematically evaluated and its mechanism of action in the treatment of insomnia remains unclear. Therefore, in this study, behavioral, energy metabolism, and metabonomics methods were applied to systematically evaluate the effect of CWT on insomnia. Additionally, urine metabonomics based on UPLC-Q-TOF-MS/MS were utilized to identify potential endogenous biomarkers of insomnia, detect the various changes before and after CWT treatment, explore the metabolic pathway and potential target of CWT, and reveal its pharmacological mechanism. Results revealed that CWT increased inhibitory neurotransmitter (5-HT and GABA) content and reduced the content of excitatory neurotransmitters (DA and NE). Moreover, CWT enhanced autonomous behavioral activity, stabilized emotions, and promoted the return of daily basic metabolic indexes of insomniac rats to normal levels. The urine metabolomics experiment identified 28 potential endogenous biomarkers, such as allysine, 7,8-dihydroneopterin, 5-phosphonooxy-L-lysine, and N-acetylserotonin. After CWT treatment, the content of 22 biomarkers returned to normal levels. The representative markers included N-acetylserotonin, serotonin, N-methyltryptamine, and 6-hydroxymelatonin. Additionally, the metabolic pathways in rats were significantly reversed, such as tryptophan metabolism, folate biosynthesis, phenylalanine metabolism, and tyrosine metabolism. Ultimately, it is concluded that CWT regulated tryptophan metabolism, folate biosynthesis, phenylalanine metabolism, and other metabolic levels in the body. This drug has been confirmed to be effective in the treatment of insomnia by regulating the content of serotonin, 6-hydroxymelatonin, N-acetylserotonin, and N-methyltryptamine to a stable and normal level in tryptophan metabolism.
The mechanism of Renshen-Fuzi herb pair for treating heart failure—Integrating a cardiovascular pharmacological assessment with serum metabolomics

Background: Renshen-Fuzi herb pair (RS-FZ) is often used in the clinical treatment of heart failure (HF) and has a remarkable therapeutic effect. However, the mechanism of RS-FZ for treating HF remains unclear. In our study, we explored the mechanism of RS-FZ for treating HF. Methods: Evaluation of RS-FZ efficacy by cardiovascular pharmacology. Moreover, Global metabolomics profiling of the serum was detected by UPLC-QTOF/MS. Multivariate statistics analyzed the specific serum metabolites and corresponding metabolic pathways. Combining serum metabolomics with network pharmacology, animal experiments screened and validated the critical targets of RS-FZ intervention in HF. Results: RS-FZ significantly ameliorated myocardial fibrosis, enhanced cardiac function, and reduced the serum HF marker (brain natriuretic peptide) level in rats with HF. Through topological analysis of the “Metabolite-Target-Component” interaction network, we found that 79 compounds of RS-FZ directly regulated the downstream specific serum metabolites by acting on four critical target proteins (CYP2D6, EPHX2, MAOB, and ENPP2). The immunohistochemistry results showed that RS-FZ observably improved the expression of CYP2D6 and ENPP2 proteins while decreasing the expression of EPHX2 and MAOB proteins dramatically. Conclusion: The integrated cardiovascular pharmacological assessment with serum metabolomics revealed that RS-FZ plays a crucial role in the treatment of HF by intervening in CYP2D6, EPHX2, MAOB, and ENPP2 target proteins. It provides a theoretical basis for RS-FZ for treating HF.
Orbifolds and Orientifolds in String Theory and Gauge/String Dualities

We review various examples of gauge/string dualities between superconformal field theories (SCFTs) in four dimensions and Type IIB superstring theories compactified on orbifolds and orientifolds of the background AdS5×S in the near-horizon limit. In particular, we consider Type IIB theory on N |Zk| D3-branes at orbifold singularities of the form R/Zk and R/Zk, and review the degree of supersymmetry preserved in their SCFT dual description by considering different actions of the orbifold group on the coordinates of the transverse space. We also consider orientifold theories on AdS5 × RP with different amounts of discrete torsion and match them to the dual SCFT with appropriate gauge group. A thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Quantum Fields and Fundamental Forces of Imperial College London.
Glycan-Based Electrochemical Biosensors: Promising Tools for the Detection of Infectious Diseases and Cancer Biomarkers

Glycan-based electrochemical biosensors are emerging as analytical tools for determining multiple molecular targets relevant to diagnosing infectious diseases and detecting cancer biomarkers. These biosensors allow for the detection of target analytes at ultra-low concentrations, which is mandatory for early disease diagnosis. Nanostructure-decorated platforms have been demonstrated to enhance the analytical performance of electrochemical biosensors. In addition, glycans anchored to electrode platforms as bioreceptors exhibit high specificity toward biomarker detection. Both attributes offer a synergy that allows ultrasensitive detection of molecular targets of clinical interest. In this context, we review recent advances in electrochemical glycobiosensors for detecting infectious diseases and cancer biomarkers focused on colorectal cancer. We also describe general aspects of structural glycobiology, definitions, and classification of electrochemical biosensors and discuss relevant works on electrochemical glycobiosensors in the last ten years. Finally, we summarize the advances in electrochemical glycobiosensors and comment on some challenges and limitations needed to advance toward real clinical applications of these devices.
Adaptive Method of Particular Solution for Solving 3D Inhomogeneous Elliptic Equations

Recently, particular solutions using radial basis functions have been used as a basis for solving inhomogeneous partial differential equations as a one-stage approach without the need of finding homogeneous solutions. In this paper, we adopt a newly developed adaptive greedy algorithm to enhance the performance of the one-stage method and alleviate the difficulty of ill-conditioning of the resultant matrix. To demonstrate the effectiveness of coupling these two methods, we give two 3D examples with excellent numerical results.
Policy Resilience to Environment Poisoning Attacks on Reinforcement Learning

This paper investigates policy resilience to training-environment poisoning attacks on reinforcement learning (RL) policies, with the goal of recovering the deployment performance of a poisoned RL policy. Due to the fact that the policy resilience is an add-on concern to RL algorithms, it should be resource-efficient, time-conserving, and widely applicable without compromising the performance of RL algorithms. This paper proposes such a policy-resilience mechanism based on an idea of knowledge sharing. We summarize the policy resilience as three stages: preparation, diagnosis, recovery. Specifically, we design the mechanism as a federated architecture coupled with a meta-learning manner, pursuing an efficient extraction and sharing of the environment knowledge. With the shared knowledge, a poisoned agent can quickly identify the deployment condition and accordingly recover its policy performance. We empirically evaluate the resilience mechanism for both model-based and model-free RL algorithms, showing its effectiveness and efficiency in restoring the deployment performance of a poisoned policy.
Human Error Prediction Using Heart Rate Variability and Electroencephalography

As human’s simple tasks are being increasingly replaced by autonomous systems and robots, it is likely that the responsibility of handling more complex tasks will be more often placed on human workers. Thus, situations in which workplace tasks change before human workers become proficient at those tasks will arise more frequently due to rapid changes in business trends. Based on this background, the importance of preventing human error will become increasingly crucial. Existing studies on human error reveal how task errors are related to heart rate variability (HRV) indexes and electroencephalograph (EEG) indexes. However, in terms of preventing human error, analysis on their relationship with conditions before human error occurs (i.e., the human pre-error state) is still insufficient. This study aims at identifying biological indexes potentially useful for the detection of high-risk psychological states. As a result of correlation analysis between the number of errors in a Stroop task and the multiple HRV and EEG indexes obtained before and during the task, significant correlations were obtained with respect to several biological indexes. Specifically, we confirmed that conditions before the task are important for predicting the human error risk in high-cognitive-load tasks while conditions both before and during tasks are important in low-cognitive-load tasks.
On potential debt monetisation for China's post-Covid recovery: what can we learn from the past?

A measure of the degree of debt monetisation is constructed for its impact on the business cycle, to be studied in a standard VAR model. Debt monetisation is hardly stimulative, as it raises public demand that crowds out almost as much demand from the private sector. However, it generates inflation, presumably because of inflationary expectations. Nevertheless the impact of debt monetisation on business cycle dynamics is trivial, given the low efficiency of the monetary transmission mechanism. Unless policy proposals are for extraordinarily aggressive moves, or they are accompanied by monetary reforms which facilitate monetary transmission, the recent debate on debt monetisation, we argue, possesses more theoretical meaning than practical meaning for China's postCovid recovery.
Multimodal Video Understanding using Graph Neural Network

Majority of existing semantic video understanding methods process every video independently without considering the underlying inter-video relationships. However, videos uploaded by users on social media platforms like YouTube, Instagram etc. exhibit inter-video relationship which are a reflection of the interest, geography, culture etc. of the users. In this work, we explicitly attempt to model this inter-video relationship, originating from the creators of these videos using Graph Neural Networks (GNN) in a multimodal setup. We perform video classification by leveraging the creators of the videos and semantic similarity between videos for creating edges and observe improvements of 4% in accuracy.
Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome

In many clinical and epidemiologic studies, periodically measured disease markers are used to monitor progression to the onset of disease. Motivated by a study of CD4 counts in men infected with human immunodeficiency virus (HIV) at risk for acquired immunodeficiency syndrome (AIDS), we developed a joint model for analysis of both longitudinal and event time data. We use a longitudinal model for continuous data that incorporates a mean structure dependent on covariates, a random intercept, a stochastic process, and measurement error. A central component of the longitudinal model is an integrated Ornstein–Uhlenbeck stochastic process, which represents a family of covariance structures with a random effects model and Brownian motion as special cases. The regression model for the event time data is a proportional hazards model that includes the longitudinal marker as a time-dependent variable and other covariates. A Markov chain Monte Carlo algorithm was developed for fitting the joint model. The joint modeling approach is evaluated and compared with the approach of separate modeling through simulation studies, and it is applied to CD4 counts and AIDS event time data from a cohort study of HIV-infected men. The joint estimation approach allows the simultaneous estimation of the effect of baseline covariates on the progression of CD4 counts and the effect of the current CD4 count and baseline covariates on the hazard of AIDS. The joint modeling approach also gives a way to incorporate measurement error in CD4 counts into a hazard model.
Impact of Non-Accelerated Aging on the Properties of Parylene C

The polymer Parylene combines a variety of excellent properties and, hence, is an object of intensive research for packaging applications, such as the direct encapsulation of medical implants. Moreover, in the past years, an increasing interest for establishing new applications for Parylene is observed. These include the usage of Parylene as a flexible substrate, a dielectric, or a material for MEMS, e.g., a bonding adhesive. The increasing importance of Parylene raises questions regarding the long-term reliability and aging of Parylene as well as the impact of the aging on the Parylene properties. Within this paper, we present the first investigations on non-accelerated Parylene C aging for a period of about five years. Doing so, free-standing Parylene membranes were fabricated to investigate the barrier properties, the chemical stability, as well as the optical properties of Parylene in dependence on different post-treatments to the polymer. These properties were found to be excellent and with only a minor age-related impact. Additionally, the mechanical properties, i.e., the Young’s modulus and the hardness, were investigated via nano-indentation over the same period of time. For both mechanical properties only, minor changes were observed. The results prove that Parylene C is a highly reliable polymer for applications that needs a high long-term stability.
A Hand Direction Vector Extraction Method Based on K Vector and K-medoids Clustering Algorithm

This paper proposed a method of computing the hand direction vector. At first, using K-vector method, compute the K-slope of all the points on the contour to get a series of peak point sets; Then, cluster the sets which have been obtained through K-medoids algorithm; At last, detect the pointing direction of each fingertip from the clustering information, and get the hand's direction by it. The experiment shows that the method achieves the precise positioning of hand direction in palm contours.
Isotopic Composition ( δ 15 N and δ 18 O) of Urban Forests in Different Climate Types Indicates the Potential Influences of Traffic Exhaust and Relative Humidity

: Previous studies have shown that climatic and anthropogenic factors influence the varia ‐ tions in the stable isotope signature of tree materials in an urban ecosystem. However, the responses of urban trees to various anthropogenic and precipitation interventions are unclear. To fill the re ‐ search gap, the isotopic composition ( δ 15 N and δ 18 O) and total nitrogen content of the soil ‐ plant system of urban forests were measured, focusing on typical urban tree species ( Populus tomentosa and Ficus virens ). The research was done under various land uses in China’s Beijing and Shenzhen megacities (with different humidity conditions). The linear mixed ‐ effect model revealed that the δ 15 N values in the leaves of roadside Ficus virens were significantly higher than those in urban park sites, away from the road ( δ 15 N difference = 7.2‰). In contrast, Populus tomentosa leaves exhibited a non ‐ significant difference ( δ 15 N difference = − 1.8‰). Further regression analysis revealed that the variations in δ 15 N in tree leaves could be attributed to the proximity to highways, suggesting the influence of vehicle exhaust on δ 15 N values in roadside trees. The linear mixed ‐ effect model also revealed δ 18 O values significantly higher in Populus tomentosa leaves than in Ficus virens leaves. To assess the influence of humidity conditions on δ 18 O values in the leaves, the ratio of the atmospheric and intercellular vapor pressures (e a /e i ) of tree canopies was estimated. The result revealed that the e a /e i of Ficus virens was significantly higher than for Populus tomentosa , ascribed to the variation in the humidity conditions of the two megacities. These results highlight that urban trees can poten ‐ tially serve as bioindicators for atmospheric pollution and humidity. Our findings highlight the ecophysiological responses of urban forests related to N and O as they vary according to traffic exhaust and relative humidity. Consequently, they are potentially valuable indicators of urban at ‐ mospheric contamination, forming a nature ‐ based solution for citizen welfare improvement.