Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Phenolic Acids on Temperature-sensitive Property of Self-assembly of Ionic Pair of Poly(ethylene imine)/(phenylthio)Acetic Acid

The ionic pair self-assembly (IPSAM) composed of poly(ethyleneimine) (PEI) and (phenylthio)acetic acid (PTA) was prepared and the effect of phenolic acids (PAs) (e.g. cinnamic acid (CA), hydroxycinnamic acid (HCA), and dihydroxycinnamic acid (DHCA)) on the upper critical solution temperature (UCST) and the temperature-responsive releasing property of IPSAM were investigated. PEI/PTA ionic pair showed a UCST behavior and the PAs decreased the UCST effective in the order of DHCA > HCA > CA. The PAs were thought to attach to the PEI chain of PEI/PTA ionic pair as pendants. According to the interfacial tensiometry, PEI/PTA(3/7) ionic pair was found to be air/water interface-active due to their amphiphilic property. CA had little effect on the interfacial activity of the ionic pair. HCA and HDCA significantly decreased the interfacial activity possibly because they are more polar than CA thus the hydrophilic and lipophilic balance of PEI/PTA ionic pair could be broken by their attachment to PEI chains. IPSAM was found as nanoparticles whose diameter was tens of nanometer and PAs had little effect on the shape and the size of IPSAM, once the UCST of PEI/PTA/PA ionic pair was above room temperature where the TEM micrographs were taken. If the UCST of PEI/PTA/PA ionic pair was below room temperature, no particulate matters were found on the TEM micrographs. The release degree of cargo loaded in IPSAM increased slowly with time lapse below UCST. Whereas, the release degree increased rapidly with time lapse above UCST, possibly because of the thermally-induced disintegration of IPSAM.
User Mapping Strategy in Multi-CDN Streaming: A Data-Driven Approach

Using content delivery networks (CDNs) for video distribution has become the normalem de facto approach for video streaming today, because they are easy to use (e.g., video chunks can be delivered as files via HTTP) and have good scalability. Today, it has become the norm rather than the exception for video providers to hire multiple CDNs for their video services in a pay-per-use manner—not only to serve users at different locations, but also to reduce operational costs. Given that multiple CDNs and their peering servers exist at many different locations, selecting different CDNs for different users in the same online video system has become a critical decision that can significantly affect the users’ Quality of Experience (QoE). Conventional strategies are generally rule based, e.g., assigning users to CDNs according to their locations or ISPs, but cannot guarantee any particular QoE level because QoE is affected by a combination of complicated factors. In this article, we propose using a data-driven approach to study the factors determining users’ QoE, including both Quality of Service (QoS) and user factors. Our findings indicate that QoE is affected by both the QoS provided by the CDNs and user preferences for the video content. We design a machine learning-based predictive model to capture the “utility” of a video for a user given a particular QoS guarantee. Based on that, we strategically assign CDNs to users to maximize the overall QoE. One month trace-driven experiments are used to demonstrate the effectiveness and efficiency of our design.
Cloud-based Network Virtualization in IoT with OpenStack

In Cloud computing deployments, specifically in the Infrastructure-as-a-Service (IaaS) model, networking is one of the core enabling facilities provided for the users. The IaaS approach ensures significant flexibility and manageability, since the networking resources and topologies are entirely under users’ control. In this context, considerable efforts have been devoted to promoting the Cloud paradigm as a suitable solution for managing IoT environments. Deep and genuine integration between the two ecosystems, Cloud and IoT, may only be attainable at the IaaS level. In light of extending the IoT domain capabilities’ with Cloud-based mechanisms akin to the IaaS Cloud model, network virtualization is a fundamental enabler of infrastructure-oriented IoT deployments. Indeed, an IoT deployment without networking resilience and adaptability makes it unsuitable to meet user-level demands and services’ requirements. Such a limitation makes the IoT-based services adopted in very specific and statically defined scenarios, thus leading to limited plurality and diversity of use cases. This article presents a Cloud-based approach for network virtualization in an IoT context using the de-facto standard IaaS middleware, OpenStack, and its networking subsystem, Neutron. OpenStack is being extended to enable the instantiation of virtual/overlay networks between Cloud-based instances (e.g., virtual machines, containers, and bare metal servers) and/or geographically distributed IoT nodes deployed at the network edge.
Are you talking to me? Generation X, Y, Z responses to mobile advertising

This study explores intergenerational differences in attitudes toward mobile advertising (addressing their informativeness, irritation, trustworthiness, entertainment, and intrusiveness) and actual response to mobile advertising messages in Israel. Using an online survey (N = 408) and drawing on Congruence Theory and Generation Cohort Theory, we focus on three generations: X, Y, and Z. Findings show that all generations responded negatively when receiving an advertisement via smartphone. However, the generations differ in their patterns of association between mobile advertising attitudes and responses to mobile ads. Findings suggest that incongruence between each generation’s scheme and the five dimensions of advertising attitudes results in unfavorable responses to mobile advertising. These findings provide guidelines for future research and implications for marketers who intend to design behavioral targeting to consumers of various generational cohorts while using mobile platforms as an advertising channel.
Defining what constitutes a reliable dataset to test for hybridization and introgression in marine zooplankton: Comment on Choquet et al. 2020 “No evidence for hybridization between Calanus finmarchicus and C. glacialis in a subarctic area of sympatry”

The article ‘No evidence for hybridization between Calanus finmarchicus and C. glacialis in a subarctic area of sympatry’ (Choquet et al. 2020) concludes that “no evidence supports a potential for hybridization between C. finmarchicus and C. glacialis”. We argue that the InDel markers used by Choquet et al. (2020) may have limited capacity to detect admixed genotypes between C. finmarchicus and C. glacialis due to an inappropriate choice of reference sample for each species during the marker development. We first review terms and concepts used in genetic classification using reference samples and describe problems associated with the selection of genetic markers in the context of possible hybridization. We reanalyze InDel genotypes provided with Choquet et al. (2017) and identified an admixed individual. We then contrast methods used by Choquet et al. (2017) and Parent et al. (2012) and explain how Parent et al. (2012) developed microsatellite markers capable of discriminating admixed genotypes from parental species. In this comment, we have identified a major issue that must be considered when selecting reference samples in the context of testing for possible hybridization.
Estimation of IL-1β, Osteoprotegerin, and YKL-40: A Diagnostic Array for Prediction of Gestational Diabetes Mellitus complicated by Gestational Hypertension

Objectives: Estimation of serum levels of interleukin (IL)-1β, Osteoprotegerin (OPG) and YKL-40 early in pregnancy of normotensive normoglycemic women to find early predictors for development of gestational insulin resistance (GIR), hypertension (GHT) and/or diabetes mellitus (GDM). Patients & Methods: The study included 255 pregnant women who were evaluated during their 1 st antenatal visit (ANV-1) for age, body mass index (BMI), baseline systolic (SBP) and diastolic blood pressure (DBP) and gave blood samples for estimation of serum levels of insulin and the studied cytokines. Then, all women underwent 75-Oral glucose tolerance test (OGTT) for diagnosis of GDM and the homeostasis model assessment of IR (HOMA-IR) score at 6 th and 24 th GW. Results: 32 women developed GIR that progressed to GDM, 38 women developed GHT, 13 developed GIR and GHT and 7 women developed the triad of GIR, GDM and GHT. There are significant differences in serum IL-1β, YKL-40 and OPG levels in women free and with these disorders. Serum levels of IL-1β showed positive, while serum OPG levels showed negative significant correlations with the incidence of pregnancy-induced disorders, while high serum YKL-40 was positively correlated with the incidence of GIR with GHT or GDM or both. ROC curve and Regression analyses defined combination of high DBP and serum YKL-40 as the significant early predictors for development of the three disorders, while high HOMA-IR score, SBP and serum IL-1β as the significant predictors for GHT, high BMI, DBP and serum YKL-40 as early predictors for GIR and GHT and high serum YKL-40 and low serum OPG levels as early predictors for GIR and DM. Conclusion: Estimation of the studied array of cytokines at the 1 st ANV has a high diagnostic value for the upcoming pregnancy-induced disorders single or combination with higher predictive value than the reliance on clinical data.
Arylhydrazines: novel and versatile electrophilic partners in cross-coupling reactions

Arylhydrazines are extremely valuable compounds in organic chemistry that are widely used for the synthesis of a variety of biologically active molecules such as indoles, indazoles, pyrazoles, aryltriazoles, β-lactams and quinazolines. These compounds have also been widely utilized as arylation agents in oxidative cross-coupling reactions. In this review, we will highlight the most important explorations and developments in the carbon–carbon and carbon–heteroatom (nitrogen, phosphorus, sulfur, and selenium) cross-coupling of arylhydrazines. The literature has been surveyed from 2001 to June 2018.
Modeling of endothelial cell dysfunction using human induced pluripotent stem cells derived from patients with end-stage renal disease

Background Endothelial cell (EC) dysfunction is a frequent feature in patients with end-stage renal disease (ESRD). The aim of this study was to generate human induced pluripotent stem cells, differentiate ECs (hiPSC-ECs) from patients with ESRD, and appraise the usefulness of hiPSC-ECs as a model to investigate EC dysfunction. Methods We generated hiPSCs using peripheral blood mononuclear cells (PBMCs) isolated from three patients with ESRD and three healthy controls (HCs). Next, we differentiated hiPSC-ECs using the generated hiPSCs and assessed the expression of endothelial markers by immunofluorescence. The differentiation efficacy, EC dysfunction, and molecular signatures of EC-related genes based on microarray analysis were compared between the ESRD and HC groups. Results In both groups, hiPSCs and hiPSC-ECs were successfully obtained based on induced pluripotent stem cell or EC marker expression in immunofluorescence and flow cytometry. However, the efficiency of differentiation of ECs from hiPSCs was lower in the ESRD-hiPSCs than in the HC-hiPSCs. In addition, unlike HC-hiPSC-ECs, ESRD-hiPSC-ECs failed to form interconnecting branching point networks in an in vitro tube formation assay. During microarray analysis, transcripts associated with oxidative stress and inflammation were upregulated and transcripts associated with vascular development and basement membrane extracellular matrix components were downregulated in ESRD-hiPSC-ECs relative to in HC-hiPSC-ECs. Conclusion ESRD-hiPSC-ECs showed a greater level of EC dysfunction than HC-hiPSC-ECs did based on functional assay results and molecular profiles. hiPSC-ECs may be used as a disease model to investigate the pathophysiology of EC dysfunction in ESRD.
MEDIAL UNI-COMPARTMENT KNEE ARTHROPLASTY (U.K.A) ASSESSMENT & FOLLOW UP, SYSTEMATIC REVIEW & META-ANALYSIS

: Background: Osteoarthritis (OA) can affect all three compartments of the knee, but epidemiological studies have shown that the predominant pattern is disease localized to the medial side of the knee, although a lot of studies had been done to compare different modalities of treatment, the gold standard treatment for AMOA is not yet well known and the decision of which procedure is best suited to an individual, or whether an individual would be prepared to undergo one type of surgery, but not another is a complex issue. Aim of the work: This study is a systematic review and meta-analysis of studies that include patients underwent medial UKA for treating isolated medial knee osteoarthritis, and to provide cumulative data about the efficacy and safety of Uni-compartmental knee arthroplasty (UKA) in treating isolated medial compartment knee osteoarthritis Patients and Methods: This review was done using standard methodology outlined in the Cochrane Handbook and reported the findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement guidelines, (PubMed, were searched for relative studies which studied the outcome of Preoperative status versus Post-operative sequel of medial compartment knee osteoarthritis patients by estimating Mean, Standard deviation (± SD) and range for parametric numerical data, while Median, Geometric Mean and Inter-quartile range (IQR) for non-parametric numerical data, Frequency and percentage of non-numerical data and their 95% confidence intervals for each study. Results: 10 studies studied the outcome of Pre-operative status versus Post-operative sequel of medial compartment knee osteoarthritis were obtained for final research, in these studies 2304 knees underwent UKA, we qualitatively assessed 1ry efficacy outcome by assessing prevalence of moderate to severe pain and functional knee score (ROM – range of motion) and qualitatively assessed 2ry safety outcome by measuring complications rate, revision surgery (Failure) rate and survival probability %. Conclusions: UKA is a solution that is adapted to the treatment of unicompartmental osteoarthritis AMOA in old patients more than 60 years of age, this intervention provides the patient with excellent quality of life and satisfaction in more than 90% of the cases. article and Q heterogeneity = 39.5, of freedom 9, p < 0.0001**, I2 (inconsistency) = 77.2% and Odds Ratio (OR) = 0.395. I 2 (inconsistency) was 77.2% with highly significant Q test for heterogeneity (p < 0.0001), so random-effects model was chosen to assess safety; with overall OR= 0.395 (95% CI 0.223 to 0.700). The random-effects model of the meta-analysis study showed highly significant decrease in failure rate ―revisions‖ among overall complicated patients (p = 0.001).
3D autoencoder algorithm for lithological mapping using ZY-1 02D hyperspectral imagery: a case study of Liuyuan region

Abstract. A hyperspectral image (HSI) contains hundreds of spectral bands, which provide detailed spectral information, thus offering an inherent advantage in classification. The successful launch of the Gaofen-5 and ZY-1 02D hyperspectral satellites has promoted the need for large-scale geological applications, such as mineral and lithological mapping (LM). In recent years, following the success of computer vision, deep learning methods have shown their advantage in solving the problem of hyperspectral classification. However, the combination of deep learning and HSI to solve the problem of geological mapping is insufficient. We propose a new 3D convolutional autoencoder for LM. A pixel-based and cube-based 3D convolutional neural network architecture is designed to extract spatial–spectral features. Traditional and machine learning methods are employed as competing methods, trained on two real hyperspectral datasets, and evaluated according to the overall accuracy, F1 score, and other metrics. Results indicate that the proposed method can provide convincing results for LM applications on the basis of the hyperspectral data provided by the ZY-1 02D satellite. Compared with traditional methods, the combination of deep learning and hyperspectral can provide more efficient and highly accurate results. The proposed method has better robustness than supervised learning methods and shows great promise under small sample conditions. As far as we know, this work is the first attempt to apply unsupervised spatial–spectral feature learning technology in LM applications, which is of great significance for large-scale applications.
The Natural Products Targeting on Allergic Rhinitis: From Traditional Medicine to Modern Drug Discovery

More than 500 million people suffer from allergic rhinitis (AR) in the world. Current treatments include oral antihistamines and intranasal corticosteroids; however, they often cause side effects and are unsuitable for long-term exposure. Natural products could work as a feasible alternative, and this study aimed to review the efficacies and mechanisms of natural substances in AR therapies by examining previous literature. Fifty-seven studies were collected and classified into plants, fungi, and minerals decoction; clinical trials were organized separately. The majority of the natural products showed their efficacies by two mechanisms: anti-inflammation regulating diverse mediators and anti-oxidation controlling the activity of nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) pathway stimulated by reactive oxygen species (ROS). The main AR factors modified by natural products included interleukin (IL)-4, IL-5, IL-13, interferon-gamma (IFN-γ), tumor necrosis factor-α (TNF-α), cyclooxygenase 2 (COX-2), and phospho-ERK1/2 (p-ERK1/2). Although further studies are required to verify their efficacies and safeties, natural products can significantly contribute to the treatment of AR.
Community Use of Antibiotics in Turkey: The Role of Knowledge, Beliefs, Attitudes, and Health Anxiety

Turkey has been among the leading countries in antibiotic consumption. As a result of the 4-year National Action Plan for Rational Drug Use, antibiotic prescriptions had declined from 34.9% in 2011 to 24.6% in 2018. However, self-medication with antibiotics without prescription is common, which is not reflected in official statistics. The present study aims at investigating antibiotic use in the community and the factors related to it. A web-based survey was conducted among 945 Turkish-speaking respondents (61.3% female). The questionnaire included questions about antibiotic use for different illnesses, ways to obtain and handle leftover antibiotics, knowledge, beliefs of the antibiotic effectiveness, attitudes, health anxiety, and background factors. According to the results, 34.2% of the sample had self-medicated themselves with antibiotics without a valid prescription. The most common way to self-medicate was to use leftover antibiotics. While 80.4% knew that antibiotics are used to treat bacterial infections, 51.4% thought that antibiotics are effective for viral diseases. The most important predictor of antibiotic use frequency was the belief in their efficiency for various illnesses and symptoms, followed by negative attitudes to antibiotics, health anxiety, knowledge level, positive attitudes, and health status. The results underline the importance of targeting misbeliefs about antibiotics in future campaigns.
Dynamic Multi-Key FHE in Asymmetric Key Setting From LWE

Multi-key Fully homomorphic encryption (MFHE) schemes allow computation on the encrypted data under different keys. However, traditional multi-key FHE schemes based on Learning with errors (LWE) have the undesirable property that is the number of keys has to be fixed in advance. A dynamic multi-key FHE scheme is the most versatile variant which the information about the participants is not required before key generation. To support further homomorphic computation on extended ciphertexts and ciphertexts encrypted under additional keys, Peikert and Shiehian (TCC ’16) proposed a leveled dynamic multi-key FHE scheme. Nevertheless, it introduces the circular-security assumption for the LWE parameters to ensure its security, which provides weaker security to the scheme. The problem of how to construct a LWE-based dynamic multi-key FHE scheme is still open. To address the above problem, in this work, we present a dynamic multi-key FHE scheme based on the LWE assumption in public key setting. The ciphertext can be extended and performed homomorphic evaluation with the ciphertexts encrypted under additional keys. Compared with current constructions, our proposed method requires fewer “ local” memory and the process of ciphertext extension is distributed. Our proposed method provides a new way to extend the ciphertext such that the ciphertext homomorphism computation is more efficient. Our scheme is proven to be secure under standard LWE assumptions without using the circular-security assumption.
A note for the Ulam-Hyers-Rassias stability of differential equations on bounded intervals

: In this paper, we considered the stability problem of non-linear differential equations in the sense of Ulam-Hyers and Ulam-Hyers-Rassias on bounded intervals. We show that some widely used restrictions commonly assumed in similar problems are not necessary. Therefore we extend and improve some well-known results by dropping some of their assumptions.
Evolutionary Stable Solution Concepts for Initial Play

We model initial play in bimatrix games by a large population of agents. The agents have individual solution concepts (maps from games to strategy profiles) that they use to solve games. In contrast to evolutionary game theory, where the agents play the same game indefinitely, we consider a setting where they never play the same game twice. Individual solution concepts are represented as computer programs which develop over time by a process of natural selection. We derive an aggregate solution concept (ASC), which converges to a stochastically stable state where the population mean behavior remains constant. The logic and performance of the evolutionary stable ASC is examined in detail, and its solutions to many well-known games are held up against the theoretical and empirical evidence. For example, the ASC selects the “right” solution to traveler’s dilemma games, and predicts that the responder will get 40% of the pie in ultimatum games.
Effect of control measures on the pattern of COVID-19 Epidemics in Japan

Background COVID-19 has spread worldwide since its emergence in 2019. In contrast to many other countries with epidemics, Japan differed in that it avoided lockdowns and instead asked people for self-control. A travel campaign was conducted with a sizable budget, but the number of PCR tests was severely limited. These choices may have influenced the course of the epidemic. Methods The increase or decrease in the classes of SARS-CoV-2 variants was estimated by analyzing the published sequences with an objective multivariate analysis. This approach observes the samples in multiple directions, digesting complex differences into simpler forms. The results were compared over time with the number of confirmed cases, PCR tests, and overseas visitors. The kinetics of infection were analyzed using the logarithmic growth rate. Results The declared states of emergency failed to alter the movement of the growth rate. Three epidemic peaks were caused by domestically mutated variants. In other countries, there are few cases in which multiple variants have peaked. However, due to the relaxation of immigration restrictions, several infective variants have been imported from abroad and are currently competing for expansion, creating the fourth peak. By April 2021, these foreign variants exceeded 80%. The chaotic situation in Japan will continue for some time, in part because no effort has been made to identify asymptomatic carriers, and details of the vaccination program are undecided.