Miracle-dz/UniFAR-FTUs huggingface dataset:
A cytomegalovirus immunevasin triggers integrated stress response-dependent reorganization of the endoplasmic reticulum

Human cytomegalovirus (HCMV) encodes an ER-resident glycoprotein, UL148, which activates the unfolded protein response (UPR) but is fully dispensable for viral replication in cultured cells. Hence, its previously ascribed roles in immune evasion and modulation of viral cell tropism are hypothesized to cause ER stress. Here, we show that UL148 is necessary and sufficient to drive the formation of large ER-derived structures that occupy up to 7% of the infected cell cytosol. The structures are found to be sites where UL148 coalesces with cellular proteins involved in ER quality control, such as Hrd1 and EDEM1. Transmission electron microscopy analyses reveal the structures to be comprised of tortuous, densely packed and apparently collapsed ER membranes that connect to distended cisternae. During induced ectopic expression of UL148-GFP fusion protein, punctate signals traffic to accumulate at prominent structures that exhibit poor recovery of fluorescence after photobleaching. Small molecule blockade of the integrated stress response (ISR) prevents the formation of puncta, leading to a uniform reticular fluorescent signal. Accordingly, ISR inhibition during HCMV infection abolishes the coalescence of UL148 and Hrd1 into discrete structures, which argues that UL148 requires the ISR to cause ER reorganization. Given that UL148 stabilizes immature forms of a receptor binding subunit for a viral envelope glycoprotein complex important for HCMV infectivity, our results imply that stress-dependent ER remodeling contributes to viral cell tropism. IMPORTANCE Perturbations to ER morphology occur during infection with various intracellular pathogens and in certain genetic disorders. We identify that an HCMV gene product, UL148, profoundly reorganizes the ER during infection, and is sufficient to do so when expressed on its own. Our results reveal that UL148-dependent reorganization of the ER is a prominent feature of HCMV infected cells. Moreover, we find that this example of virally induced organelle remodeling requires the integrated stress response (ISR), a stress adaptation pathway that contributes to a number of disease states. Since ER reorganization accompanies the roles of UL148 in HCMV cell tropism and intracellular retention of the immune cell co-stimulatory ligand CD58, our results may have implications for understanding the mechanisms involved. Furthermore, our findings provide a basis to utilize UL148 as a tool to investigate organelle responses to stress and to identify novel drugs targeting the ISR.
A Novel Front-End Design for Bioelectrical Signal Wearable Acquisition

Mismatch of front-end branches introduced by the numerical error of the peripheral components will limit the matching level of the front end and lead to the difficulty for obtaining high common mode rejection ratio. In this paper, a novel front-end design is proposed for high-quality bioelectrical signal wearable acquisition. Through partial public dc bias circuit and virtual right leg drive circuit, the common-mode rejection ration of the proposed design can be improved effectively without accurate matching the peripheral components, which is valuable for engineering simplification and wearable device development. Both theoretical analysis and experiment results are given to show the advantages of the proposed design compared with the traditional design. Based on the proposed front-end design, an ECG system with common precision configuration of peripheral components is developed, and its common-mode rejection ratio can reach 100 dB. Three wearable ECG applications, portable finger ECG measurement, palm ECG acquisition for cycling, and chest ECG test under different motion states, are carried out and the experimental results of the proposed design are compared with those of traditional design with the same parameter error, which show that the developed ECG system with the proposed design can effectively suppress power line interference and motion artifact and has the superiority for bioelectrical signal wearable acquisition.
DCLK1 Plays a Metastatic-Promoting Role in Human Breast Cancer Cells

Background Doublecortin-like kinase 1 (DCLK1) has been universally identified as a cancer stem cell (CSC) marker and is found to be overexpressed in many types of cancers including breast cancer. However, there is little data regarding the functional role of DCLK1 in breast cancer metastasis. In the present study, we sought to investigate whether and how DCLK1 plays a metastatic-promoting role in human breast cancer cells. Methods We used Crispr/Cas9 technology to knock out DCLK1 in breast cancer cell line BT474, which basically possesses DCLK1 at a higher level, and stably overexpressed DCLK1 in another breast cancer cell line, T47D, that basically expresses DCLK1 at a lower level. We further analyzed the alterations of metastatic characteristics and the underlying mechanisms in these cells. Results It was shown that, compared with the corresponding control cells, DCLK1 overexpression led to an increase in metastatic behaviors including enhanced migration and invasion of T47D cells. By contrast, forced depletion of DCLK1 drastically inhibited these metastatic characteristics in BT474 cells. Mechanistically, the epithelial-mesenchymal transition (EMT) program, which is critical for cancer metastasis, was prominently activated in DCLK1-overexpressing cancer cells, evidenced by a decrease in an epithelial marker ZO-1 and an enhancement in several mesenchymal markers including ZEB1 and Vimentin. In addition, DCLK1 overexpression induced the ERK MAPK pathway, which resultantly enhanced the expression of MT1-MMP that is also involved in cancer metastasis. Knockout of DCLK1 could reverse these events, further supporting a metastatic-promoting role for DCLK1. Conclusions Collectively, our data suggested that DCLK1 overexpression may be responsible for the increased metastatic features in breast cancer cells. Targeting DCLK1 may become a therapeutic option for breast cancer metastasis.
Board 120: University-based Engineering Training of High School Science Teachers to Implement the Next Generation Science Standards (Work in progress)

Angela M. Kelly is an Associate Professor of Physics and the Associate Director of the Science Education Program at Stony Brook University, New York. She attended La Salle University, Philadelphia, Pennsylvania, where she received her B.A. degree in chemistry, and completed her M.A. and Ph.D. degrees in science education (2000 and 2006, respectively) and her Ed.M. degree in curriculum and teaching (2007) at Teachers College, Columbia University, New York. She is the recipient of the SUNY Chancellor’s Award for Excellence in Teaching (2016); the Provost’s Faculty Recognition Award for Excellence in Scholarship and Research from Lehman College, City University of New York (2010); and the Outstanding Teaching Award from Teachers College, Columbia University (2006). Her research has been rooted in a commitment to equity in precollege and university science and engineering.
NATURE AND CAUSES OF OCCUPATIONAL HEALTH CONDITIONS IN THE DEVELOPING WORLD

Workers around the world—despite vast differences in their physical, social, economic, and political environments—face virtually the same kinds of workplace hazards. These hazards are traditionally categorized into four broad types: chemical, biological, physical, and psychosocial. What emerges from our incomplete knowledge of their risk, however, is that the more than 80 percent of the world’s workforce that resides in the developing world disproportionately shares in the global burden of occupational disease and injury. Several classic occupational diseases, such as silicosis and lead poisoning, that have been substantially eliminated in industrial countries remain endemic elsewhere in the world. Whether this high and preventable burden of ill health faced by workers in the developing world is the result of ignorance, inattention, or intent, compelling evidence indicates that work-related health conditions could be substantially reduced, often at modest cost.
Mathematical Statistics Method of Residual Static Torque Controlling

This paper analyzes the problems existing in the detection and determination on the traditional residual torque. It is pointed out that the detection value is mistakenly used as the truth value and the lower limit of design torque is mistakenly used as the residual torque criterion. The calculation formula of the determination (limit) value of the test value of RM and DFM is proposed. By defining related parameters,the torque limit value corresponding to the tightening level, the ratio of the measured value to the truth value, μ and σ related to the ratio of A and C, and the confidence coefficient related to the confidence probability, a mathematical statistical method of residual static torque controlling is established, which improves the control precision on the residual torque.
Simultaneous distributed strain and temperature measurement using a dual-Brillouin-peak optical fiber

Simultaneous distributed strain and temperature measurement based on Brillouin frequency shift (BFS) was demonstrated using a dual-Brillouin-peak single-mode (SM) optical fiber. The fiber is designed and fabricated with enhanced Brillouin gain of higher-order acoustic modes so that the gains of the multiple Brillouin peaks are at a similar level. In a 25-kilometer sensing length with 5-meter spatial resolution, the achieved temperature resolution is 2°C and the strain resolution is 40 microstrain.
Shift Force Optimization and Trajectory Tracking Control for a Novel Gearshift System Equipped With Electromagnetic Linear Actuators

Electromagnetic linear actuators (ELAs) are used to engage gears in an electric automated manual transmission. The structure is simplified due to the elimination of intermediate mechanisms. An ELA can provide 1500 N of electromagnetic force to drive the synchronizer mechanisms. Additionally, the dynamic characteristics of the actuator are remarkable, improving the performance of shifting gears. To achieve balanceable and comprehensive gearshift performance including shift time, friction work, and degrees of jerk, Pontryagin's minimum principle is employed to optimize the friction torque, and current feed-forward active disturbance rejection control is proposed to track the optimized shift force. Moreover, a double closed-loop controller based on active disturbance rejection control is used to achieve fast and stable displacement control. Comparative simulations and experiments are carried out, and the results indicate that the proposed tracking method can implement the optimal shift force well and can integrate the optimal shift indices, including shift time, degrees of jerk, and friction work. Combined with the proposed control method, the superiority and feasibility of the novel direct-drive electromagnetic gearshift system are validated.
Variability management in safety‐critical systems design and dependability analysis

Safety‐critical systems are of paramount importance for many application domains, where safety properties are a key driver to engineer critical aspects and avoid system failures. For the benefits of large‐scale reuse, software product lines (SPL) have been adopted in critical systems industry. However, the integration of safety analysis in the SPL development process is nontrivial. Also, the different usage contexts of safety‐critical systems complicates component fault modeling tasks and the identification of potential hazards. In this light, better methods become necessary to estimate the impact of dependability properties during Hazard Analysis and Risk Assessment. Existing methods incorporating the analysis of safety properties in SPL are limited as they do not include hazard analysis and component fault modeling. In this paper, we present the novel DEPendable Software Product Line Engineering (DEPendable‐SPLE) approach, which extends traditional SPL processes to support the reuse of safety assets. We also present a detailed analysis of the impact of product and context features on the SPL design, safety analysis, and safety requirements. We applied DEPendable‐SPLE to a realistic case study from the aerospace domain to illustrate how to model and reuse safety properties. DEPendable‐SPLE reduced the effort of safety analysis for certifying system variants.
MOTION PICTURES

37:120 CENSORSHIP IN THEATRE AND CINEMA by Anthony Aldgate and James C. Robertson (Edinburgh: Edinburgh University Press, 2005—$80.00/$30.00, ISBN 0-7486-1960-7 hard, 0-7486-1961-5 paper, 195 pp., black and white photos, bibliography, index) offers a useful comparison of film and stage censorship in Great Britain. With studies based upon the Lord Chamberlain’s correspondence concerning theatre censorship and the British Board of Film Censor files, the text is thematic in its organization: sex, foreign affairs, delinquency, homosexuality and lesbianism, and the angry young men of the 1950s and the swinging sixties. Especially valuable for U.S. students who may be well versed in domestic concerns but without sufficient international understanding. Aldgate is a reader in film and history at the Open University; Robertson is a retired teacher and author of two books on censorship. (Bruce A. Austin)
Delayed and Switched Control of Formations on a Line Segment: Delays and Switches Do Not Matter

The agents’ deployment over a line segment under protocols with communication delays and switching is studied. It is assumed that no information about the value of the communication delay and no information about switching policy in the communication graph is available. It is shown that neither delay values nor switching policy in a natural class may influence convergence of the agent states to the equidistant distribution over the line segment. Similar result is obtained for deployment over the circle. The theoretical results are illustrated by simulations. The proofs relay on both well-known and recent approaches to the stability analysis of positive systems.
H-infinity controller with graphical LMI region profile for liquid slosh suppression

This paper presents a H-infinity synthesis with pole clustering based on LMI region schemes for liquid slosh control. Using LMI approach, the regional pole placement known as LMI region combined with design objective in H-infinity controller guarantee a fast input tracking capability and very minimal liquid slosh. A graphical profile of the transient response of liquid slosh suppression system with respect to pole placement is very useful in giving more flexibility to the researcher in choosing a specific LMI region. With the purpose to confirm the design of control scheme, a liquid slosh model is considered to represent the lateral slosh movement. Supremacy of the proposed approach is shown by comparing the results with hybrid model-free fuzzy-PID controller with derivative filter. The performance of the control schemes is examined in terms of time response specifications of lateral tank tracking capability and level of liquid slosh reduction.
A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine

This paper intends to present a new model for the accurate forecast of the stock’s future price. Stock price forecasting is one of the most complicated issues in view of the high fluctuation of the stock exchange and also it is a key issue for traders and investors. Many predicting models were upgraded by academy investigators to predict stock price. Despite this, after reviewing the past research, there are several negative aspects in the previous approaches, namely: (1) stringent statistical hypotheses are essential; (2) human interventions take part in predicting process; and (3) an appropriate range is complex to be discovered. Due to the problems mentioned, we plan to provide a new integrated approach based on Artificial Bee Colony (ABC), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Support Vector Machine (SVM). ABC is employed to optimize the technical indicators for forecasting instruments. To achieve a more precise approach, ANFIS has been applied to predict long-run price fluctuations of the stocks. SVM was applied to create the nexus between the stock price and technical indicator and to further decrease the forecasting errors of the presented model, whose performance is examined by five criteria. The comparative outcomes, obtained by running on datasets taken from 50 largest companies of the U.S. Stock Exchange from 2008 to 2018, have clearly demonstrated that the suggested approach outperforms the other methods in accuracy and quality. The findings proved that our model is a successful instrument in stock price forecasting and will assist traders and investors to identify stock price trends, as well as it is an innovation in algorithmic trading.
Link Predictions for Social Networks in an Online Health Community

Online social networks are ubiquitous in our daily life and offer different ways for people to interact with each other. Link prediction aims at predicting future social connections or interactions between two users within a social network. This project implements different link prediction algorithms and evaluates their performance for online social networks among users of an online health community for smoking cessations. The social networks were based on users’ online interactions via four communication channels: blog comments, message boards, group discussions and private messages. The outcome of this study will help to provide insights into the design of recommender systems in such online social networks, and to improve user experience and engagement in online health communities.
Insulin-like growth factor-1, metabolic abnormalities, and pathological complete remission rate in HER2-positive breast cancer patients receiving neoadjuvant therapy

Purpose: HER2-positive breast cancer (BC) achieving pathological complete remission (pCR) after neoadjuvant therapy (NAT) had a superior disease outcome. Dysmetabolism and stimulation of insulin-like growth factor 1 (IGF-1)-axis would increase BC risk, but we are lacking data for their association with pCR in HER2-positive+ BC. We aim to evaluate the pCR predictive value of above factors in HER2-positive BC patients receiving NAT. Patients and methods: HER2-positive BC patients receiving NAT ± trastuzumab were retrospectively included between January 2013 and December 2016. Data were compared between baseline at biopsy and surgery. Median value of IGF-1 expression was used as cutoff value to classify patients into low or high group. pCR was defined as no residual invasive carcinoma in breast and axilla. Results: Overall, 101 patients were included. Metabolic syndrome was diagnosed in 29 (28.71%) with an average of 1.71±1.51 metabolic disorders at baseline, significantly increased after NAT (2.12±1.54, P<0.001). Lipid metabolism factors, including triglycerides, TC, HDL-C and LDL-C significantly worsened after NAT (all P<0.05). Average post-NAT IGF-1 was 196.14±86.03 ng/mL (vs preNAT 186.41±75.03 ng/mL, P=0.182). pCR was achieved in 29 (28.71%) patients. pCR rate was 40.00% and 17.65% for those with low or high preIGF-1 level (P=0.013). Multivariate analysis found that low IGF-1 expression, but not any other metabolic variable, was significantly associated with higher pCR rate in whole population (OR: 3.83, 95%CI: 1.32–11.11, P=0.014) or in patients receiving NAT + trastuzumab (OR: 3.93, 95%CI: 1.13–13.63, P=0.031). With a median follow-up of 29.03 (range: 10.42–56.98) months, IGF-1 level was not associated with overall survival (P=0.328) or disease-free survival (P=0.288). Conclusion: Low IGF-1 level was related with higher pCR rate in HER2-positive BC patients receiving NAT, which deserves further clinical evaluation.
Human activity recognition using skeleton data and support vector machine

In this paper, we propose a method for recognizing human activities using skeleton data by RGB-D camera, namely Kinect device. The human activity recognition is a learning in the field of computer vision. In its application, the recognition of human activity can be used for a sign language learning, human-computer interaction, surveillance of the elderly, image processing and etc. Our approach is based on skeleton data with coordinate value of each joints in human body, that will be classified using support vector machine algorithm when performing a movement to predict the activities name. Experiments were performed with a new training data that we’ve create manual from capturing movement while human target are doing activities. Experiments result show that the system best average accuracy is 93.75% of all activities prediction with the optimal distance of object to the devices is 2 meters.
Verteilungseigenschaften der Renditen von Kryptowährungen: Sind sie mit Aktien vergleichbar?

Zusammenfassung: Neben Bitcoin existieren über 1 500 weitere Kryptowährungen, die sich durch die Art der Nutzung oder durch die zugrunde liegende Blockchain-Technologie voneinander erheblich unterscheiden. Die meisten dieser Währungen lassen sich auf Börsen und Marktplätzen handeln und können als Investitionsobjekte dienen. In diesem Beitrag werden die empirischen Verteilungseigenschaften ihrer Renditen für einen sehr breiten Querschnitt untersucht und mit denen von Aktienrenditen verglichen. Die Renditen von Kryptowährungen weisen viele ähnliche Charakteristika zu den Aktienrenditen auf: Renditebeobachtungen häufen sich um den Erwartungswert, die Autokorrelation ist, wenn überhaupt, nur sehr schwach, das Phänomen des Volatility-Clusterings und der Asymmetrie von Gewinnen und Verlusten ist vorhanden, ein Faktor kann circa 60 Prozent der gemeinsamen Variation der Renditen erklären und es existiert ein Wochentageffekt. Dagegen können im Querschnitt der Kryptowährungen keine Heavy-Tails identifiziert werden und der Momentum-Effekt ist nur sehr schwach ausgeprägt. Die Ergebnisse lassen die Vermutung zu, nach der die Renditeeigenschaften von Kryptowährungen nicht wesentlich von denen der Aktien abweichen. Summary: There are more than 1,500 other cryptocurrencies, which differ significantly from each other in terms of their usage or the underlying blockchain technology. Most of these cryptocurrencies can be traded on exchanges and can serve as investment instruments. In this paper, the empirical distribution properties of their returns for a very broad cross-section are examined and compared with those of stock returns. Returns on cryptocurrencies have several characteristics similar to equity returns: Returns are more likely observable around the averages; the autocorrelation of returns is very weak; the phenomenon of volatility clustering and the asymmetry of gains and losses do exist; the factor analysis of the returns reveals that one factor (the first principal component) explains about 60 percent of the common variation of returns; there is a weekday effect. However, there are some differences. For example, no heavy-tails can be identified and the momentum effect is only very weak. The results suggest that the stylezed facts of cryptocurrency returns are not very different from stock returns.