Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure of the herpes simplex virus portal-vertex

Herpesviruses include many important human pathogens such as herpes simplex virus, cytomegalovirus, varicella-zoster virus, and the oncogenic Epstein–Barr virus and Kaposi sarcoma–associated herpesvirus. Herpes virions contain a large icosahedral capsid that has a portal at a unique 5-fold vertex, similar to that seen in the tailed bacteriophages. The portal is a molecular motor through which the viral genome enters the capsid during virion morphogenesis. The genome also exits the capsid through the portal-vertex when it is injected through the nuclear pore into the nucleus of a new host cell to initiate infection. Structural investigations of the herpesvirus portal-vertex have proven challenging, owing to the small size of the tail-like portal-vertex–associated tegument (PVAT) and the presence of the tegument layer that lays between the nucleocapsid and the viral envelope, obscuring the view of the portal-vertex. Here, we show the structure of the herpes simplex virus portal-vertex at subnanometer resolution, solved by electron cryomicroscopy (cryoEM) and single-particle 3D reconstruction. This led to a number of new discoveries, including the presence of two previously unknown portal-associated structures that occupy the sites normally taken by the penton and the Ta triplex. Our data revealed that the PVAT is composed of 10 copies of the C-terminal domain of pUL25, which are uniquely arranged as two tiers of star-shaped density. Our 3D reconstruction of the portal-vertex also shows that one end of the viral genome extends outside the portal in the manner described for some bacteriophages but not previously seen in any eukaryote viruses. Finally, we show that the viral genome is consistently packed in a highly ordered left-handed spool to form concentric shells of DNA. Our data provide new insights into the structure of a molecular machine critical to the biology of an important class of human pathogens.
Simultaneous Detection and Channel Estimation for Censoring-Based Spectrum Sensing in Cognitive Radio Networks

This letter considers simultaneous primary user (PU) detection and channel estimation for censoring-based spectrum sensing in cognitive radio networks over fading channels. We formulate the problem mathematically for Rician and Rayleigh fading channels. Closed-form expressions are derived for the critical performance metrics in low SNR regime. Further, we optimize the censoring parameter and the power allocation for throughput maximization under transmit and interference power constraints. Our results demonstrate that simultaneous PU detection and channel estimation substantially improve the throughput of cognitive radio networks over an approach where PU detection and channel estimation are treated independently.
Sequencing and Annotation of the Genome of Mycobacterium tuberculosis MYC004, a Strain Causing Meningitis in Mexico

ABSTRACT Mycobacterium tuberculosis strain MYC004 was isolated from a Mexican patient with tuberculous meningitis, the most aggressive form of tuberculosis. The draft genome sequence is the first of a meningeal strain of M. tuberculosis reported from Latin America and consists of 4,411,530 bp, including 4,251 protein-encoding genes.
CaloriNet: From silhouettes to calorie estimation in private environments

We propose a novel deep fusion architecture, CaloriNet, for the online estimation of energy expenditure for free living monitoring in private environments, where RGB data is discarded and replaced by silhouettes. Our fused convolutional neural network architecture is trainable end-to-end, to estimate calorie expenditure, using temporal foreground silhouettes alongside accelerometer data. The network is trained and cross-validated on a publicly available dataset, SPHERE_RGBD + Inertial_calorie. Results show state-of-the-art minimum error on the estimation of energy expenditure (calories per minute), outperforming alternative, standard and single-modal techniques.
Model for the Dimensioning of WiMAX Networks Supporting Multi-profile

This paper tackles the challenging task of developing a simp le and accurate analytical model for performance evaluation of WiMAX networks. The need for accurate and fast-compu ting tools is of primary importance to face complex and exhaustive dimensioning issues for this promising acce ss technology. In this paper, we present a generic Markovian model developed for three usual scheduling policies (s lot sharing fairness, throughput fairness and opportunist ic scheduling) that provides closed-form expressions for all the required performance parameters instantaneously. We also present and evaluate the performance of a fourth policy , called throttling policy, that limits the maximum user throughput and makes use of the Maximum Sustained Tra ffic Rate (MSTR) parameter foreseen by the standard. At last, we extend these studies to multi-profile tra ffic patterns. The proposed models are compared in depth with re alistic simulations that show their accuracy and robustness regard ing the di fferent modeling assumptions. Finally, the speed of our analytical tools allows us to carry on dimensioning st udies that require several thousands of evaluations, which would not be tractable with any simulation tool.
Rift interaction at the Galápagos Triple Junction

The Galapágos Triple Junction is a complex ridge-ridge-ridge triple junction located 1000 km west of the Galapágos Islands in the eastern equatorial Pacific Ocean. A northern ridgeridge-ridge triple junction intersects the East Pacific Rise at 2°40’ N while a southern triple ridge-ridge-ridge junction intersects the East Pacific Rise at 1°10’ N. A series of smaller extinct rifts found parallel and to the northeast of the 2°40’ N triple junction suggests that rifts associated with this triple junction, similar to the current Incipient Rift, were at one time an active triple junction at 2°40’ N along the East Pacific Rise but eventually cease to be active and are carried away from the triple junction with the Cocos plate. Numerical models, in which the geometry and locations of various rifts are varied in the general triple junction vicinity, are analyzed to constrain the factors that have led to the consistent location of secondary rift at the northern triple junction. The results indicate that once a rift has become detached from the East Pacific Rise, a zone of reduced tension forms at the rift tip prohibiting reconnection. Instead, two peaks of tensile stress enhancement form along the East Pacific Rise and are offset from the detached rift indicating where a new crack is likely to form. I show that the magnitude of tensile stress enhancement is controlled by the gap between the detached rift and the East Pacific Rise, but the presence of the Cocos-Nazca Rift controls the location of new rift formation along the ridge of the East Pacific Rise. Therefore, I infer that the sequence of ancient rifts at the 2°40’ N triple junction represents the natural consequence of rift disconnection events and their position reflects the history of the gap between the EPR and the Cocos-Nazca Rift.
DIY Model for Mobile Network Deployment: A Step Towards 5G for All

Mobile phones and innovative data oriented mobile services have the potential to bridge the digital divide in Internet access and have transformative developmental impact. However as things stand currently, economics come in the way for traditional mobile operators to reach out and provide high-end services to under-served regions. We propose a do-it-yourself (DIY) model for deploying mobile networks in such regions that is in the spirit of earlier community cellular networks but aimed at provisioning high-end (4G and beyond) mobile services. Our proposed model captures and incorporates some of the key trends underlying 5G mobile networks and look to expand their scope beyond urban areas to reach all by empowering small-scale local operators and communities to build and operate modern mobile networks themselves. We showcase a particular instance of the proposed deployment model through a trial deployment in rural UK to demonstrate its practical feasibility.
Analysis of three phase quadratic boost derived hybrid converter

This paper presents a power converter architecture, referred as Quadratic Boost Derived Hybrid Converter (QBDHC), which can provide step up dc output and three phase ac output simultaneously from a single dc input. The converter is derived from the single switch quadratic boost converter by replacing the controlled switch with a three phase bridge inverter network. 3-Ø QBDHC has higher voltage gain compared to boost derived hybrid converter. This hybrid converter has improved power processing capability since the boost and inverter operations are incorporated in a single circuit. Such hybrid converters are well suited for dc nanogrid applications, hybrid electric vehicle etc. The converter utilizes shoot-through state of the inverter bridge unlike traditional voltage source inverter (VSI). Hence it has better reliability due to inherent shoot through protection in the hybrid converter. The Sinusoidal Pulse Width Modulation (SPWM) techniques of VSI is modified here in order to incorporate the shoot-through interval in each switching cycle. The steady-state behavior of the 3-Ø QBDHC has been studied in this paper. Simulations illustrating the main results are also included.
Single Point Conducted EMI Sensor With Intelligent Inference for Detecting IT Appliances

Electrical grids need to embed smartness not just at the generation and distribution side but also at the consumption side. Specifically, in regard to office buildings, information technology (IT) loads such as desktops and printers, operating in non-working hours, can lead to significant energy wastage. Detailed understanding and quantification of this wastage can lead to motivational insights for reduction in this wastage. However, it is impractical to monitor such a large number of loads individually. In this paper, we propose a single point smart sensor to detect and track the operation of these IT appliances. Existing methods, based on state-of-the art sensors, have been ineffective at detecting IT loads that have time-varying power consumption patterns. Our proposed sensor detects IT loads using their common mode electromagnetic emissions (CM EMI) injected on the grid. The sensor is low cost, portable, and built using commercial off-the-shelf components. We use a nearest neighbor-based classification algorithm on the statistical features extracted from histograms of the measured CM EMI. Experimental evaluations carried out with multiple instances of commonly found IT appliances display up to 87% detection accuracy, thus validating the real world applicability of our proposed system.
Automatic sarcasm detection using feature selection

Sarcasm is an expression of humor, mockery or criticism with the help of ironic remarks that seems positive. Sarcasm detection in sentiment analysis is essential for understanding the emotions and thoughts of the people. Automatic sarcasm detection refers to the detection of sarcasm in the text written in natural language. Various natural language processing techniques carry out this purpose. Recognition of Sarcasm is of extraordinary significance and is valuable to numerous NLP applications such as Opinion Mining and multiple advertisings. Sarcasm detection is a complex task, because of the challenges involved in determining the nature of the sarcasm bearing text. Automatic sarcasm detection is thus, one of the hardest challenges in Sentiment Analysis, including complex linguistic analyzing and machine learning methods. This paper focuses on various sarcasm analyzing techniques employed for filtering of sarcastic statements from a text and the use of Automatic sarcasm detection in the categorization of tweets and product review texts.
To achieve or not to achieve? Comparative mindsets elicit assimilation and contrast in goal priming

Goal priming typically leads to goal-consistent behavior. This uniform pattern is surprising given other types of priming effects, which have been found to be more variable. On the basis of previous research on judgment priming effects, we predicted that a comparative mindset to focus on similarities versus differences also affects the direction of goal priming. Two studies show that assimilation to a primed goal results if participants focus on similarities, whereas a focus on differences leads to contrast. In Study 1, participants induced to focus on similarities behaved more neatly after being primed with neatness rather than the goal to be carefree. For participants induced to focus on differences, the opposite pattern emerged. In Study 2, a similarity focus led to assimilation to an achievement prime, whereas a difference focus resulted in contrast. These findings highlight the importance of comparative processes in goal striving and demonstrate that assimilative goal-priming effects are less invariable than existing research suggests. Copyright © 2012 John Wiley & Sons, Ltd.
Influence of different substitution levels of Balangu seed gum on textural characteristics of selected hydrocolloids

Lallemantia royleana with vernacular name of Balangu is a mucilaginous endemic plant which is grown in different regions of world especially Middle East countries. Because of high mucilage content, the seeds can be used as a new source of food hydrocolloid in food formulations. The effect of five substitution levels (0%, 25%, 50%, 75% and 100%, w/w) of Balangu seed gum (BSG) on the textural characteristics of xanthan gum (XG), guar gum (GG) and locust bean gum (LBG) gels were investigated by using the TPA test. The result showed that the springiness of GG-BSG and XG-BSG mixed gels increase significantly when the concentration of BSG increases. It was also found that the chewiness, hardness and adhesiveness of LBG were very sensitive to the substitution levels of BSG.
Biogenic synthesis of silver nanoparticles from aqueous flower extract of Bougainvillea spectabilis and their antibacterial activity

In this study, silver nanoparticles were biologically synthesized by using aqueous flower extract of Bougainvillea spectabilis wild. Synthesis and formation of silver nanoparticles were confirmed by colour change from pink colour to brown colour and it was further characterized by ultraviolet (UV) visible spectroscopy at the range of 300 to 800 nm. The peak showed at 431 nm. Further morphology, shape and size of the synthesized nanoparticles were characterized by field emission electron microscopy and the presence of metal silver was analysed by energy dispersive x-ray spectroscopy. Reducing and capping agents for synthesized silver nanoparticles were studied by Fourier transform infrared spectroscopy. The in vitro antibacterial activity of silver nanoparticles was tested against both Gram-positive and Gramnegative bacterial strains. Result showed that synthesized nanoparticles have potential and high antibacterial activity against Gram-positive bacterial strains compared to Gram negative bacterial strains.
Social Data Driven SDN Network Operation using Northbound Interface

Software Defined Networking (SDN) enables highly flexible routing and traffic engineering. The network using the centralized SDN control can be operated by globally viewing the entire network. On the other hand, the network operation of the routing and traffic engineering based on internal network traffic monitoring does not immediately perform the network recovery specifically in case of the multiple network failures induced by the large scale disaster such as Great East Japan Earthquake. Hence, we will investigate the new network operation utilizing the external information abstracted from the social data. The social data contains the real-time user experience of the network quality degradation due to the emergency events, natural disaster etc. and useful for the immediate network recovery. The integration of the social data with SDN will enable the new network operation. In order to obtain the real-time information from the social data, Twitter is most relevant for our purpose. First, we constructed the SDN enabled network testbed in the wide area network controlled by the centralized system using th northbound interface (NBI). Next using the testbed, the network restoration experiment was successfully performed by the network path computation algorithm using actual Tweet logs of the Great East Japan Earthquake.
Dynamic malware analysis using machine learning algorithm

Malware detection is a vital think about the protection of the Personal computer systems. However, presently using signature-based strategies cannot offer correct detection of zero-day attacks and polymorphic viruses. That's why the requirement for machine learning-based detection arises. The purpose of this work was to work out the most effective feature extraction, feature illustration, and classification ways that end in the most effective accuracy. This work presents suggested ways for machine learning based malware classification and detection, also as the tips for its implementation. Moreover, the study performed is often helpful as a base for any analysis within the field of malware analysis with machine learning strategies.
Reacting to Variations in Product Demand: An Application for Conversion Rate (CR) Prediction in Sponsored Search

In online internet advertising, machine learning models are widely used to compute the likelihood of a user engaging with product related advertisements. However, the performance of traditional machine learning models is often impacted due to variations in user and advertiser behavior. For example, search engine traffic for florists usually tends to peak around Valentine’s day, Mother’s day, etc. To overcome, this challenge, in this manuscript we propose three models which are able to incorporate the effects arising due to variations in product demand. The proposed models are a combination of product demand features, specialized data sampling methodologies and ensemble techniques. We demonstrate the performance of our proposed models on datasets obtained from a real-world setting. Our results show that the proposed models more accurately predict the outcome of users interactions with product related advertisements while simultaneously being robust to fluctuations in user and advertiser behaviors.
Power balancing in autonomous micro grid with variable speed pump

This paper presents a method for supply-demand balancing in autonomous micro-grids using a variable speed pump. The pump is driven by a wound rotor induction motor (WRIM) utilizing a slip power recovery control. The slip power from the rotor is recovered through a line-commutated inverter, which gives the capability for the motor to obtain variable speed operation. Power drawn by the pump being proportional to cube of the speed, the stator power is varied over a wide range as the speed is varied. A load frequency controller senses the deviation in the micro-grid frequency due to the supply-demand mismatch and it suggests the triggering angle of the inverter. This makes the power drawn by the pump track the load variation, so as to nullify the frequency drift and restores the power balance in the micro-grid. A 250kW WRIM is used to drive the proposed micro-grid, which has a maximum demand of 250 kW. The entire system is simulated in MATLAB/Simulink and the variable speed operation of the pump is demonstrated for different triggering angles of the inverter.
Complete Genome Sequence of Broad-Host-Range Shiga Toxin-Converting Bacteriophage SH2026Stx1, Isolated from Escherichia coli O157:H7

ABSTRACT The Shiga toxin-encoding phage SH2026Stx1 was isolated from Escherichia coli O157:H7 strain 2026. SH2026Stx1 and its detoxified derivative can infect a broad range of E. coli strains, including commensal, enteropathogenic, and enteroaggregative strains. We report here the complete genome sequence of phage SH2026Stx1 and its important features.
The effect of cultural dimensions on service quality expectations of the Thai restaurants: In case of Japanese customers

the research focused on studying the effect of cultural dimensions on service quality expectation. Research methodologies used were mainly quantitative research, by collecting 300 questionnaires from Japanese consumers. The data was analyzed by descriptive and inferential analyses. The results showed that the most of Japanese customers' expected to service quality were Tangibles Assurance and Responsiveness respectively. However, Japanese customers expected a little level of Empathy. The results of hypothesis testing were summarized and reported. In summary, five cultural dimensions explained a significant R square of 0.55. The standardized regression coefficients revealed that LTO was the most influential predictor, followed by UAI, MAS and PDI respectively while, IDV is not a significant factor.
Smoking, health and academic outcomes: evidence from a limited smoking campus policy

Abstract Although there is substantial literature on the impact of smoking laws, the number of studies that investigate the impact of such policies on college campuses is sparse. Using a rich data set from various waves of the American College Health Association National College Health Assessment survey for a mid-sized public university in the southern United States, we investigate a possible causal link between a limited smoking policy and smoking behaviours, health and academic outcomes among college students. We employ propensity score matching methods to control for endogeneity of unobservable characteristics. Our results show a significant reduction in the propensity to smoke cigarettes and cigars following the introduction of the policy. Further, we find that the policy has increased academic outcomes; however, it has no significant effect on student health. These findings have important policy implications for schools that are considering instituting comprehensive smoking bans on college.
Gateway Placement for Reliability Optimization in 5G-Satellite Hybrid Networks

The placement of satellite gateways, as critical devices for data transmission between terrestrial networks and satellites, is of fundamental importance for the design of 5G-satellite hybrid networks, especially for the network reliability since the satellite links are prone to failing due to poor meteorological conditions. To the best of our knowledge, this problem almost remains untouched. Existing works in this line mainly focused on gateway placement in wireless mesh networks and sensor networks, which have totally different network topologies and optimization targets, and thus cannot be readily adopted. In light of this, two algorithms are proposed as our solutions, i.e., an optimal enumeration algorithm (OEA) and a cluster based approximation placement algorithm (CAPA). Extensive experiments based on real world online network topologies have been conducted and as validated by our numerical results, OEA can obtain an optimal result with computational complexity of O(kn$C_{n}^{k}$) and CAPA can achieve a near-optimal solution with much lower computational complexity of O(n2).