Miracle-dz/UniFAR-FTUs huggingface dataset:
Throttling Twitter: an emerging censorship technique in Russia

In March 2021, the Russian government started to throttle Twitter on a national level, marking the first ever use of large-scale, targeted throttling for censorship purposes. The slowdown was intended to pressure Twitter to comply with content removal requests from the Russian government. In this paper, we take a first look at this emerging censorship technique. We work with local activists in Russia to detect and measure the throttling and reverse engineer the throttler from in-country vantage points. We find that the throttling is triggered by Twitter domains in the TLS SNI extension, and the throttling limits both upstream and downstream traffic to a value between 130 kbps and 150 kbps by dropping packets that exceed this rate. We also find that the throttling devices appear to be located close to end-users, and that the throttling behaviors are consistent across different ISPs suggesting that they are centrally coordinated. Notably, this deployment marks a departure from Russia's previously decentralized model to a more centralized one that gives significant power to the authority to impose desired restrictions unilaterally. Russia's throttling of Twitter serves as a wake-up call to censorship researchers, and we hope to encourage future work in detecting and circumventing this emerging censorship technique.
Open for hire: attack trends and misconfiguration pitfalls of IoT devices

Mirai and its variants have demonstrated the ease and devastating effects of exploiting vulnerable Internet of Things (IoT) devices. In many cases, the exploitation vector is not sophisticated; rather, adversaries exploit misconfigured devices (e.g. unauthenticated protocol settings or weak/default passwords). Our work aims at unveiling the state of IoT devices along with an exploration of the current attack landscape. In this paper, we perform an Internet-level IPv4 scan to unveil 1.8 million misconfigured IoT devices that may be exploited to perform large-scale attacks. These results are filtered to exclude a total of 8,192 devices that we identify as honeypots during our scan. To study current attack trends, we deploy six state-of-art IoT honeypots for a period of 1 month. We gather a total of 200, 209 attacks and investigate how adversaries leverage misconfigured IoT devices. In particular, we study different attack types, including denial of service, multistage attacks and attacks from infected online hosts. Furthermore, we analyze data from a /8 network telescope covering a total of 81 billion requests towards IoT protocols (e.g. CoAP, UPnP). Combining knowledge from the aforementioned experiments, we identify 11, 118 IP addresses (that are part of the detected misconfigured IoT devices) that attacked our honeypot setup and the network telescope.
Social isolation, anxiety, mental well-being and push travel motivation: the case of COVID-19 in Turkey

ABSTRACT This study investigates the effects of social isolation, anxiety, and mental well-being perceptions on push travel motivations, in the context of the COVID-19 crisis affecting individuals living in Turkey. The reason for examining this period specifically is to reveal how the push travel motivations of potential holidaymakers have been affected due to the new situation whereby they have had to stay at home. Determining the reasons affecting the holiday motivations of individuals is vital for predicting future tourist mobility, especially during this tourism crisis. Data were collected from individuals staying at home due to the curfew during the COVID-19 crisis. Findings reveal that push travel motivation differs according to demographic factors, and that social isolation affects mental well-being negatively, while anxiety and push travel motivation are positively affected. It was found that mental well-being has a positive effect on push travel motivation. In addition, mental well-being has a higher positive effect on push travel motivation than anxiety.
Tour guides’ dilemma under the pandemic: to stay or not to stay? An investigation of occupational loyalty among tour guides in Macao

ABSTRACT COVID-19 has struck the tourism industry and its professions with unprecedented severity. The tour guides are among the most impacted group in the industry, with many now facing the dilemma of whether to remain guides or switch to other professions. This study aims to identify the mitigators that keep tour guides from switching to other professions. It also provides insights regarding their current situation and how they cope with the unexpected adversity. Data are mainly collected via in-depth interviews in Macao and analyzed thematically. The findings contribute to the scholarly knowledge of occupational commitment via the lens of mitigating factors.
Thermophysical properties of liquid (U, Zr)O2 by molecular dynamics

ABSTRACT In-depth understanding of nuclear fuel behaviour under operation is critical to anticipate and prevent severe accidents. Loss-of-cooling events can lead to core meltdown, and formation of U–Zr–O liquids (the basic components of corium lavas), formed of molten fuel and cladding. To improve the knowledge on those liquid mixtures, we evaluate the ability of existing interatomic potentials (CRG and Yakub) for solid-phase (U, Zr)O to accurately reproduce density and heat capacity of molten UO and ZrO and their binary mixes within molecular dynamics simulations. Facing their limits, we determine a new set of parameters for the CRG potential through optimisation on a single experimental density point for ZrO (d=0.070 atoms/Å at T=2900 K). The proposed fitted potential shows good agreement during validation with experimental data when applied at high temperatures.
CAR‐NK cells from engineered pluripotent stem cells: Off‐the‐shelf therapeutics for all patients

Clinical success of adoptive cell therapy with chimeric antigen receptor (CAR) T cells for treating hematological malignancies has revolutionized the field of cellular immunotherapy. However, due to the nature of utilizing autologous T cells, affordability and availability are major hurdles, in addition to scientific challenges relating to CAR‐T therapy optimization. Natural killer (NK) cell is a specialized immune effector cell type that recognizes and kills targets without human leukocyte antigen (HLA) restriction and prior sensitization. CAR‐NK cells do not cause graft vs host disease and can be obtained from unrelated donors as well as pluripotent stem cells (PSC), representing an ideal off‐the‐shelf therapeutics readily available for patients. Furthermore, unlike cytotoxic T cells, NK cells specifically target and eliminate cancer stem cells, which are the cells causing relapse and metastasis. PSCs can be genetically manipulated and engineered with CARs at the pluripotent stage, which allows the establishment of permanent, stable, and clonal PSC‐CAR lines for the manufacture of unlimited homogenous CAR‐NK cells. Multiple master PSC‐CAR cell banks targeting a variety of antigens for cancer, viral infection, and autoimmune diseases provide inexhaustible cell sources for all patients. Development of a next‐generation 3D bioreactor platform for PSC expansion and NK cell production overcomes major barriers related to cost and scalability for CAR‐NK product.
Application programming interface recommendation according to the knowledge indexed by app feature mined from app stores

Application programming interfaces (APIs) play an important role in the increasingly competitive mobile application development industry, as they can greatly improve the efficiency of app development. However, finding proper APIs is often time‐consuming for the gap between the knowledge of APIs and app features. To solve this problem, we give an approach to summarize the wisdom of developers contained in the products in app stores and establish the system of API knowledge indexed by app features for the API recommendation. First, we extract features from the app descriptions and define the feature framework. Second, we parse the APK files of apps to gain the methods in code and APIs called by them and further introduce such API knowledge into the feature framework by utilizing method names as bridges. Finally, according to features in developers' queries, we locate corresponding feature nodes in the API knowledge system and recommend related API knowledge to developers. We conduct experiments based on 38,952 apps from five categories on Google Play, and the experimental results show that our approach has a good recommendation effect for the queries on app features.
Proteins mediating different DNA topologies block RNAP elongation with different efficiency

Many DNA-binding proteins induce topological structures such as loops or wraps through binding to two or more sites along the DNA. Such topologies may regulate transcription initiation and may also be roadblocks for elongating RNA polymerase (RNAP). Remarkably, a lac repressor protein bound to a weak binding site (O2) does not obstruct RNAP in vitro but becomes an effective roadblock when securing a loop of 400 bp between two widely separated binding sites. To investigate whether topological structures mediated by proteins bound to closely spaced binding sites and interacting cooperatively also represent roadblocks, we compared the effect of the lambda CI and 186 CI repressors on RNAP elongation. Dimers of lambda CI can bind to two sets of adjacent sites separated by hundreds of bp and form a DNA loop via the interaction between their C-terminal domains. The 186 CI protein can form a wheel of seven dimers around which specific DNA binding sequences can wrap. Atomic force microscopy (AFM) was used to image transcription elongation complexes of DNA templates that contained binding sites for either the lambda or 186 CI repressor. While RNAP elongated past lambda CI on unlooped DNA, as well as past 186 CI-wrapped DNA, it did not pass the lambda CI-mediated loop. These results may indicate that protein-mediated loops with widely separated binding sites more effectively block transcription than a wrapped topology with multiple, closely spaced binding sites.
Nuclear damage in LMNA mutant iPSC-derived cardiomyocytes is associated with impaired lamin localization to the nuclear envelope

The LMNA gene encodes the nuclear envelope proteins Lamins A and C, which comprise a major part of the nuclear lamina, provide mechanical support to the nucleus, and participate in diverse intracellular signaling. LMNA mutations give rise to a collection of diseases called laminopathies, including dilated cardiomyopathy (LMNA-DCM) and muscular dystrophies. Although nuclear deformities are a hallmark of LMNA-DCM, the role of nuclear abnormalities in the pathogenesis of LMNA-DCM remains incompletely understood. Using induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from LMNA mutant patients and healthy controls, we show that LMNA mutant iPSC-CM nuclei have altered shape or increased size compared to healthy control iPSC-CM nuclei. The LMNA mutation exhibiting the most severe nuclear deformities, R249Q, additionally caused reduced nuclear stiffness and increased nuclear fragility. Importantly, for all cell lines, the degree of nuclear abnormalities corresponded to the degree of Lamin A/C and Lamin B1 mislocalization from the nuclear envelope. The mislocalization was likely due to altered assembly of Lamin A/C. Collectively, these results point to the importance of correct lamin assembly at the nuclear envelope in providing mechanical stability to the nucleus and suggest that defects in nuclear lamina organization may contribute to the nuclear and cellular dysfunction in LMNA-DCM.
The compound of baicalein, wogonin, and oroxylin-A inhibits EMT in A549 cell line via PI3K/AKT-TWIST1- glycolysis pathway

Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC.
Evaluation of small ncRNAs as a possible epigenetic mechanism mediating the transition from biotrophy to necrotrophy in the life cycle of Phytophthora infestans

Background: Phytophthora infestans, the causal agent of late blight disease of potato and tomato, is responsible for billions of dollars in losses worldwide each year. This plant pathogen is a hemibiotroph, meaning that in the early stages of infection, it feeds on living host tissue, and later in the infection cycle, it kills the host. Even though the transcription dynamics of this transition are well characterized, information on the role of small noncoding RNAs (ncRNAs) during this process is still being obtained. Furthermore, a methodological pipeline useful for searching and analyzing small ncRNAs in this pathogen is needed. Results: Using the proposed pipeline, a set of 146 small ncRNAs were found to be significantly differentially expressed among the analyzed samples. From these, 100 small ncRNAs were successfully annotated to specific genes, some of them encoding effector proteins produced by the pathogen during its life cycle. Other molecular regulatory processes, mainly mediated by enzymes and transporters, were also identified. Conclusions: The pipeline presented here is an easy-to-use, comprehensive and efficient option for analyzing small ncRNA profiles of P. infestans small RNA-seq data sets. Additionally, the results presented here may further contribute to elucidating the specific molecular and epigenetic mechanisms controlling the life cycle of P. infestans.
Incipient Chiller Fault Diagnosis Using an Optimized Least Squares Support Vector Machine With Gravitational Search Algorithm

Operational faults in centrifugal chillers will lead to high energy consumption, poor indoor thermal comfort, and low operational safety, and thus it is of significance to detect and diagnose the anomalies timely and effectively, especially for those at their incipient stages. The least squares support vector machine (LSSVM) has been regarded as an effective algorithm for multiclass classification. One of the most difficult issues in LSSVM is parameter tuning. Therefore, this paper reports a development of a gravitational search algorithm (GSA) optimized LSSVM method for incipient fault diagnosis in centrifugal chillers. Considering the inadequacies of conventional principle component analysis (PCA) algorithm for nonlinear data transformation, kernel principle component analysis (KPCA) was firstly employed to reduce the dimensionality of the original input data. Secondly, an optimized “one against one” multi-class LSSVM classifier was developed and its penalty constant and kernel bandwidth were tuned by GSA. Based on the fault samples of seven typical faults at their incipient stages in chillers from ASHRAE RP 1043, the proposed GSA optimized LSSVM fault diagnostic model was trained and validated. For the purpose of demonstrating the priority of the proposed fault diagnosis method, the obtained results were compared to that of using the LSSVM classifier optimized by another two algorithms, namely, the conventional cross-validation method and particle swarm optimizer. Results showed that the best fault diagnosis performance could be achieved using the proposed GSA-LSSVM classifier. The overall average fault diagnosis accuracy for the least severity faults was reported over 95%.
Tap Test Can Predict Cognitive Improvement in Patients With iNPH—Results From the Multicenter Prospective Studies SINPHONI-1 and –2

Background: We analyzed the predictive value of the tap test (TT) on the outcome of cerebrospinal fluid (CSF) shunting in patients with idiopathic normal pressure hydrocephalus (iNPH) and cognitive impairment up to 12 months postoperatively. Methods: We analyzed the data of two prospective multicenter studies on ventriculoperitoneal shunt (VPS) and lumboperitoneal shunt (LPS) use in iNPH patients. We selected patients with Mini-Mental State Examination (MMSE) scores ≤ 26 points as study subjects. We used a multivariate logistic regression model to obtain the optimal threshold of MMSE scores after TT to predict the score improvement at 12 months following shunting and that helped to control for confounding factors such as age and MMSE scores before TT. We used logistic regression models to identify variables with age-adjusted odds ratio (A-OR) and multivariate-adjusted OR (M-OR). Results: For an improvement of ≥3 points in the MMSE score cutoff 7 days following TT in VPS and LPS cohort studies, the MMSE scores improved by 6 points after 12 months. The VPS cohort had sensitivity, specificity, and area under the curve (AUC) of 69.2, 73.7, and 0.771%, respectively; however, for the LPS cohort, they were 86.2, 90.9, and 0.906%, respectively. For MMSE scores that improved by ≥3 points in patients after the TT, the possibility of an improvement by 6 points at 12 months following CSF shunt had A-OR 7.77 and M-OR 6.3 times for the VPS, and A-OR 62.3 and M-OR 59.6 times for the LPS cohort. Conclusion: CSF shunting contributes to improved cognitive function in iNPH patients. Furthermore, MMSE score evaluation at the TT can sensitively predict improvement in postoperative MMSE scores following LPS intervention. Clinical Trial Registration: SINPHONI-1 (ClinicalTrials.gov, no. NCT00221091), first posted: September 22, 2005. SINPHONI-2 [University Hospital Medical Information Network (UMIN) Clinical Trials no. UMIN000002730], the posted: February 1, 2010.
Slc39a2-Mediated Zinc Homeostasis Modulates Innate Immune Signaling in Phenylephrine-Induced Cardiomyocyte Hypertrophy

Zinc dyshomeostasis has been involved in the pathogenesis of cardiac hypertrophy; however, the dynamic regulation of intracellular zinc and its downstream signaling in cardiac hypertrophy remain largely unknown. Using Zincpyr1 staining, we found a significant decrease of intracellular Zinc concentration in phenylephrine (PE)-induced hypertrophy of neonatal rat ventricular myocytes (NRVMs). We then screened SLC39 family members responsible for zinc uptake and identified Slc39a2 as the only one altered by PE treatment. Slc39a2 knockdown in NRVMs reduced the intracellular Zinc level, and exacerbated the hypertrophic responses to PE treatment. In contrast, adenovirus-mediated Slc39a2 overexpression enhanced zinc uptake and suppressed PE-induced Nppb expression. RNA sequencing analysis showed a pro-hypertrophic transcriptome reprogramming after Slc39a2 knockdown. Interestingly, the innate immune signaling pathways, including NOD signaling, TOLL-like receptor, NFκB, and IRFs, were remarkably enriched in the Slc39a2-regulated genes. Slc39a2 deficiency enhanced the phosphorylation of P65 NFκB and STAT3, and reduced the expression of IκBα. Finally, the expression of IRF7 was significantly increased by Slc39a2 knockdown, which was in turn suppressed by IRF7 knockdown. Our data demonstrate that zinc homeostasis mediated by a Slc39a2/IRF7 regulatory circuit contributes to the alteration of innate immune signaling in cardiomyocyte hypertrophy.
Vaccine Development in the Time of COVID-19: The Relevance of the Risklick AI to Assist in Risk Assessment and Optimize Performance

The 2019 coronavirus (COVID-19) pandemic revealed the urgent need for the acceleration of vaccine development worldwide. Rapid vaccine development poses numerous risks for each category of vaccine technology. By using the Risklick artificial intelligence (AI), we estimated the risks associated with all types of COVID-19 vaccine during the early phase of vaccine development. We then performed a postmortem analysis of the probability and the impact matrix calculations by comparing the 2020 prognosis to the contemporary situation. We used the Risklick AI to evaluate the risks and their incidence associated with vaccine development in the early stage of the COVID-19 pandemic. Our analysis revealed the diversity of risks among vaccine technologies currently used by pharmaceutical companies providing vaccines. This analysis highlighted the current and future potential pitfalls connected to vaccine production during the COVID-19 pandemic. Hence, the Risklick AI appears as an essential tool in vaccine development for the treatment of COVID-19 in order to formally anticipate the risks, and increases the overall performance from the production to the distribution of the vaccines. The Risklick AI could, therefore, be extended to other fields of research and development and represent a novel opportunity in the calculation of production-associated risks.
Development of an Irrigation Water Quality Database to Identify Water Resources and Assess Microbiological Risks During the Production of Fresh Fruits and Vegetables

An Irrigation Water Quality Database was developed to help assess the microbiological quality of irrigation water used in fruit and vegetable production in 15 counties in New York (NY) State. Water samples from Tennessee (TN) were also included in the database. Four water quality parameters, quantified generic Escherichia coli, specific conductance, pH, and turbidity, were tested. Ground, reservoir, and running water were sampled over 2 years (2009 and 2010), covering three seasons each year (spring, summer, and fall). TN data are for all three seasons in 2010 only. Overall in NY (254 total samples), ground water had a geometric mean of 1 most probable number (MPN)/100 ml, reservoir water had a geometric mean of 8 MPN/100 ml, and running water had a geometric mean of 52 MPN/100 ml. Overall in TN (63 total samples), ground water had a geometric mean of 1 colony forming unit (CFU)/100 ml, reservoir water had a geometric mean of 5 CFU/100 ml, and running water had a geometric mean of 38 CFU/100 ml. These values are all below the 126 MPN/100 ml United States Environmental Protection Agency's Ambient Water Quality Standards (AWQS) standard for fresh water. The presence of E. coli had very weak but sometimes statistically signficiant correlatation with water specific conductance, pH, and turbidity, depending on the water source but the r-squared effect was not strong enough to make the other measurements a substitute for testing specifically for E. coli in water.