Shedding Light on Top Partner at the LHC

We investigate the sensitivity of the 14 TeV LHC to pair-produced top partners ($T$) decaying into the Standard Model top quark ($t$) plus either a gluon ($g$) or a photon ($\gamma$). The decays $T\rightarrow tg$ and $T\rightarrow t\gamma$ can be dominant when the mixing between the top partner and top quark are negligible. In this case, the conventional decays $T\rightarrow bW$, $T\rightarrow tZ$, and $T\rightarrow th$ are highly suppressed and can be neglected. We take a model-independent approach using effective operators for the $T$-$t$-$g$ and $T$-$t$-$\gamma$ interactions, considering both spin-$\frac{1}{2}$ and spin-$\frac{3}{2}$ top partners. We perform a semi-realistic simulation with boosted top quark tagging and an appropriate implementation of a jet-faking-photon rate. Despite a simple dimensional analysis indicating that the branching ratios ${\rm BR}(T\rightarrow t\gamma)\ll {\rm BR}(T\rightarrow tg)$ due to the electric-magnetic coupling being much smaller than the strong force coupling, our study shows that the LHC sensitivity to $T\bar{T}\rightarrow t\overline{t}\gamma g$ is more significant than the sensitivity to $T\overline{T}\rightarrow t\overline{t}gg$. This is due to much smaller backgrounds attributed to the isolated high-$p_T$ photon. We find that with these decay channels and 3 ab$^{-1}$ of data, the LHC is sensitive to top partner masses $m_T\lesssim 1.4-1.8$~TeV for spin-$\frac{1}{2}$ and spin-$\frac{3}{2}$ top partners, respectively.Comment: 33 pages, 10 figures, 7 table

RISCBOT: Mobile Robots Exploration and Mapping In 2D

The objectives of the robots are to explore the whole environment as a group, while maintaining communication with the base computer throughout the entire exploration. Our method was implemented using a mobile robot equipped with a sonar range finder, a communication unit, and a software module. The robot performs collision free navigation, dynamic object detection, data collection, and communication with a base computer. This work demonstrates that multiple robots can improve overall mapping performance of an unknown environment

Optimization and Management Techniques for Geo-distributed SDN-enabled Cloud Datacenters\u27 Provisioning

Cloud computing has become a business reality that impacts technology users around the world. It has become a cornerstone for emerging technologies and an enabler of future Internet services as it provides on-demand IT services delivery via geographically distributed data centers. At the core of cloud computing, virtualization technology has played a crucial role by allowing resource sharing, which in turn allows cloud service providers to offer computing services without discrepancies in platform compatibility. At the same time, a trend has emerged in which enterprises are adopting a software-based network infrastructure with paradigms, such as software-defined networking, gaining further attention for large-scale networks. This trend is due to the flexibility and agility offered to networks by such paradigms. Software-defined networks allow for network resource sharing by facilitating network virtualization. Hence, combining cloud computing with a software-defined network architecture promises to enhance the quality of services that are delivered to clients and reduces the operational costs to service providers. However, this combined architecture introduces several challenges to cloud service providers, including resource management, energy efficiency, virtual network provisioning, and controller placement. This thesis tackles these challenges by proposing innovative resource provisioning techniques and developing novel frameworks to improve resource utilization, power efficiency, and quality of service performance. These metrics have a direct impact on the capital and operational expenditure of service providers. In this thesis, the problem of virtual computing and network provisioning in geographically distributed software-defined network-enabled cloud data centers is modeled and formulated. It proposes and evaluates optimal and sub-optimal heuristic solutions to validate their efficiency. To address the energy efficiency of cloud environments that are enabled for software-defined networks, this thesis presents an innovative architecture and develops a comprehensive power consumption model that accurately describes the power consumption behavior of such environments. To address the challenge of the number of software-defined network controllers and locations, a sub-optimal solution is proposed that combines unsupervised hierarchical clustering. Finally, betweenness centrality is proposed as an efficient solution to the controller placement problem

Electric Power Grid Resilience to Cyber Adversaries: State of the Art

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The smart electricity grids have been evolving to a more complex cyber-physical ecosystem of infrastructures with integrated communication networks, new carbon-free sources of powergeneratio n, advanced monitoring and control systems, and a myriad of emerging modern physical hardware technologies. With the unprecedented complexity and heterogeneity in dynamic smart grid networks comes additional vulnerability to emerging threats such as cyber attacks. Rapid development and deployment of advanced network monitoring and communication systems on one hand, and the growing interdependence of the electric power grids to a multitude of lifeline critical infrastructures on the other, calls for holistic defense strategies to safeguard the power grids against cyber adversaries. In order to improve the resilience of the power grid against adversarial attacks and cyber intrusions, advancements should be sought on detection techniques, protection plans, and mitigation practices in all electricity generation, transmission, and distribution sectors. This survey discusses such major directions and recent advancements from a lens of different detection techniques, equipment protection plans, and mitigation strategies to enhance the energy delivery infrastructure resilience and operational endurance against cyber attacks. This undertaking is essential since even modest improvements in resilience of the power grid against cyber threats could lead to sizeable monetary savings and an enriched overall social welfare

Best Fit Activation Functions for Attention Mechanism: Comparison and Enhancement

Activation functions are one of the critical elements of neural networks that allow them to produce non-linear, fine and complex decision boundaries. Yet, their effects are not very well understood in the context of attention mechanisms. In this paper, we investigate the role of two widely used family of activation functions in conjunction with three attention mechanisms on two widely used image classification models; ResNet50 and MobileNetV2. We modified the structures of these classification models by infusing them with three attention mechanisms, CBAM, BAM, and Triplet Attention. In addition, we equipped them with different activation functions, including ReLU, ELU, and a newly proposed activation function that we call ELU+. The resultant models' performances were examined in the domain of facial expression recognition using three datasets; two lab-controlled, CK+ and JAFFE, and one real-world, FER2013. Compared with the baseline models, our results show a significant increase of up to +30% of models' performance when using the newly proposed AF

Parallel assessment of cell viability in cardiac and cancer cells following treatment with sunitinib

Various cardiopathological effects have been observed following chemotherapy treatment in cancer patients, due to anti-cancer drug-induced cardiotoxicity (CTX). A retrospective study of cancer survivors reported a 50% and 10% incidence of hypertension and heart failure respectively following treatment with the tyrosine kinase inhibitor sunitinib, licensed to treat pancreatic neuroendocrine tumours. The cellular mechanisms underlying CTX are not known. Here, for the first time, we compare the potency of sunitinib in both cardiac cells (primary cardiac fibroblasts (CFs)) and cancer cells (a pancreatic adenocarcinoma cell line (PANC-1)). Adult rat CFs were isolated by bulk collagenase digestion, maintained in culture and used between passages 1–2. PANC-1 cells, from previously-frozen stocks, were used between passages 41–49. Cells were treated with sunitinib (0–10 µM in CFs; 0–100 µM in PANC-1) for 24 hour prior to epifluorescent imaging for phenotypic assessment. Cell viability was examined by alamar blue assays following 24 hour sunitinib treatment (0–100 µM). Overall, results indicated increased sensitivity of CFs to sunitinib compared with PANC-1 cells. Phenotypic changes indicative of cell death, including appearance of intracellular vacuoles, were evident in CFs following 1 µM sunitinib treatment whereas similar effects were not induced until 10 µM treatment in PANC-1 cells. Alamar blue assays demonstrated a dramatic increase in CF death compared to PANC-1 death following treatment with 10 µM sunitinib (11.6±0.02 vs 56.5±1.5 (% viability) CF vs PANC-1, n=3). A lower IC50 value for sunitinib was required to exert the same effects on CF (IC505.2 µM) vs PANC-1 (IC5013.5 µM) cell viability. These results suggest sunitinib can cause lethal effects in cardiac cells at lower doses than those required to induce pancreatic cancer cell death. Future work will aim to identify cellular mechanisms responsible for these toxic effects. Parallel studies in cardiac and cancer cells will be beneficial in distinguishing how focused anti-cancer drug delivery could be improved to avoid CTX

Physical phenomena of spectral relationships via quadratic third kind mixed integral equation with discontinuous kernel

Spectral relationships explain many physical phenomena, especially in quantum physics and astrophysics. Therefore, in this paper, we first attempt to derive spectral relationships in position and time for an integral operator with a singular kernel. Second, using these relations to solve a mixed integral equation (MIE) of the second kind in the space {L}_{2}\left[-\mathrm{1, 1}\right]\times C\left[0, T\right], T < 1. The way to do this is to derive a general principal theorem of the spectral relations from the term of the Volterra-Fredholm integral equation (V-FIE), with the help of the Chebyshev polynomials (CPs), and then use the results in the general MIE to discuss its solution. More than that, some special and important cases will be devised that help explain many phenomena in the basic sciences in general. Here, the FI term is considered in position, in ${L}_{2}\left[-\mathrm{1, 1}\right],$ and its kernel takes a logarithmic form multiplied by a general continuous function. While the VI term in time, in C\left[0, T\right], T < 1, and its kernels are smooth functions. Many numerical results are considered, and the estimated error is also established using Maple 2022

Design of human heartbeat monitoring system based on wireless sensor networks

The IoT technology plays an important role in Industry 4.0 revolution. The IoT technology has potential to be implemented in the medical industry, especially for the development of telemedicine system. IoT able to send the medical sensor data wirelessly to the nearest medical facility like hospital. In this research, the author designed the heart beat monitoring system by using 802.11 communication protocol and simple web interface. The pulse sensor that used in this research was able to read the pulse rate of the human and convert it to BPM (beat per minute). It has 98.89% accuracy and 1.11% error compared to the smartwatch result. In the other hand, ESP-32 also implemented as the microcontroller as well as the sensor node of the system. It was able to send the data wirelessly from sensor node to the coordinator node. The coordinator node was also able to fetch the sensor data into the database using POST and GET method and then visualize the sensor data over web interface so the other users are able to see the visualization of the sensor data

High performance thin-layer chromatography and in vitro cytotoxic studies on ethanol extract of Matricaria chamomilla L (Asteraceae) flowers

Purpose: To develop a high performance thin-layer chromatography (HPTLC procedure for quantitation of apigenin in ethanol extract of Matricaria chamomilla (Babunaj) flowers, and to evaluate the extract for in vitro cytotoxic effect on MCF-7 cell lines. Methods: Quantification of apigenin was carried out using a CAMAG TLC system. A combination of toluene, ethyl acetate and formic acid (4.5:3.5:0.2 v/v/v) was used as mobile phase, with densitometry detection at 336 nm. The HPTLC procedure was subjected to validation as per ICH guidelines. The cytotoxicity of the extract was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. Results: A sharp apigenin band at Rf of 0.51 was obtained, and the content of apigenin in the extract was 0.062 % w/w. The detection limit (LOD) and quantification limit (LOQ) were 0.19 and 0.57 ng/band, respectively. MTT assay results indicate that M. chamomilla was cytotoxic to Michigan Cancer Foundation-7 (MCF-7) cells, with half-maximal concentration (IC50) of 74 µg/mL. Conclusion: The developed HPTLC method is linear, precise, accurate and specific for the determination of apigenin. M. chamomilla exerts cytotoxic effect on MCF-7 cell line via induction of apoptosis