Miracle-dz/UniFAR-FTUs huggingface dataset:
Circulating tumor cells: capture with a micromachined device

The isolation and analysis of circulating tumor cells from blood is the subject of intense research. Tests to detect metastasis are available, but progress has been hampered by the lack of tumor-specific markers and predictable DNA abnormalities. CTCs from solid tumors can be separated from normal hematopoietic cells based on size and other inherent physical and biological properties. The main challenge in this endeavor is the small number of available cells of interest, 1-2 per ml in human whole blood. A micromachined device for fractioning whole blood using physical methods to enrich and/or isolate rare cell types from peripheral circulation has been designed. It has four segments of microfluidic channels, each consisting of a 2-D array of columns. The gap between the columns progressively narrows across the device. Current devices have channels ranging in width from 20µm down to 5µm, and in depth from 20µm down to 5µm. When healthy adult blood, spiked with cells from each of eight cancer cell lines tested was loaded into the device, all cancerous cells were retained in a well-defined area of the device, while blood cells migrated to the output reservoir. Use of these devices will advance non-invasive methods used to monitor patients, stage disease, and assess treatment. Furthermore, insights into metastasis will be gained.
Low Overhead TCP/UDP Socket-based Tracing for Discovering Network Services Dependencies

: The widespread use of cloud computing has made it easier for service providers to develop new features and handle increased access. However, the network dependencies among components in distributed applications deployed in the cloud are becoming more complex because the number and types of components are increasing. When system administrators make changes to a system, they cannot specify the impact of the changes, which may lead to larger failures than expected. Current methods of automatically discovering dependencies trace network ﬂows included in TCP / UDP sockets in the Linux kernel on all hosts deployed in distributed applications. However, as the rate of communication increases, the number of ﬂows transferred from the kernel space to user space increases, which increases CPU usage for tracing. We propose a low-overhead method of bundling multiple ﬂows with the same network service into a single ﬂow in a kernel to discover dependencies. The proposed method reduces the number of transferred ﬂows to the user space, thus reducing CPU usage. Experimental results from evaluating our method indicate that the method maintains a CPU overhead below 2.2% when the number of ﬂows increases.
Robustness analysis of scale-free networks against cascading failures with tunable redistribution load parameters

In this paper, we investigate the robustness properties of scale-free networks against cascading failures, where the parameters of the redistribution load are assumed to be tunable. By analyzing the relation between the critical threshold and the redistribution load parameter, we find that the avalanche size is suppressed when the redistribution load parameter and initial load parameter are both taken to 1. In this case, the scale-free networks reach the strongest robustness level against cascading failures. Numerical experiments confirm our theoretical analysis.
EFFECTS OF IDENTITY STYLES AND INSECURE ATTACHMENT DIMENSIONS ON INTERNALIZING BEHAVIORS

The present study sought to explore how identity styles and attachment dimensions work together to influence internalizing behaviors (anxiety and depression) in emerging adulthood. The data for this study came from a 2017 study known as the “Identity Attachment Project”, which was supported by the College of Health Sciences at the University of Rhode Island. The analysis sample consisted of 438 participants from the University of Rhode Island who were in a romantic relationship and not already cohabitating, engaged, or married. Two multiple regression analyses were conducted to evaluate whether the identity styles and both attachment dimensions were related to depression and anxiety. Results indicated that the informational identity style, the diffuseavoidant identity style, avoidant attachment, and anxious attachment were positively related to anxiety and/or depression. Interaction terms were also created for each identity style interacting with each attachment dimension while controlling for the remaining predictors. A total of six interaction terms (three per each model) were created but only one was significant for each model. Results indicated that individuals showing high levels of an informational identity style and an avoidant attachment style indicated higher levels of anxiety as well as higher levels of depression. These findings suggest that identity styles and attachment dimensions can work together to increase the levels of internalizing behaviors among emerging adults, particularly emerging adults in dating relationships.
Impact of irrigation on farm household diet quality: Evidence from Ethiopia

In theory, irrigation could affect farm households' nutritional status in either direction. On the one hand, irrigation may improve nutritional status by boosting farm productivity and household income. On the other hand, it may deter diet quality by shifting farmers' attention from nutrition‐rich food to cash crops. This study examines the impact of irrigation schemes on farm households' nutritional status using nationally representative data from Ethiopia. Using the endogenous switching regression model, the study shows that irrigation improves diet quality. In addition, the study also identifies the production of micronutrient‐rich crops such as vegetables and fruit and the adoption of productivity‐enhancing inputs as the main pathways through which irrigation affects dietary quality. Hence, irrigation can be considered a viable instrument to enhance the diet quality of smallholders, and efforts should be made to tackle constraints that impede the adoption of irrigation technologies.
Working Algorithms and Detection Methods of Autoantibodies in Autoimmune Liver Disease: A Nationwide Study

Autoantibody detection is the cornerstone of autoimmune liver diseases (AILD) diagnosis. Standardisation of working algorithms among autoimmunity laboratories, as well as being aware of the sensitivity and specificity of various commercial techniques in daily practice, are still necessary. The aim of this nationwide study is to report the results of the 2020 Autoimmunity Workshop organised by the Autoimmunity Group of the Spanish Society of Immunology and to provide useful information to clinicians and laboratory specialists to improve the management of autoantibody detection in AILD diagnoses. Serum samples from 17 patients with liver diseases were provided by the organisers of the 2020 Autoimmunity Workshop and were subsequently analysed by the 40 participating laboratories. Each laboratory used different techniques for the detection of autoantibodies in each patients’ serum sample, according to their working algorithm. Thus, almost 680 total complete patient reports were obtained, and the number of results from different autoantibody detection techniques was >3000. Up to eight different working algorithms were employed, including indirect immunofluorescence assays (IFA) and antigen-specific techniques (AgST). The IFA of HEp-2 cells was more sensitive than IFA of rat triple tissue for the study of anti-nuclear autoantibodies (ANA) associated with AILD. The IFA of a human neutrophil study for the analysis of anti-neutrophil cytoplasmic autoantibodies was not carried out systemically in all patients, or by all laboratories. AgSTs were the most sensitive methods for the detection of anti-smooth muscle/F-actin, soluble liver antigen, liver cytosol-1, M2-mitochondrial autoantibodies, and ANA associated with primary biliary cholangitis. The main differences in AMA detection were due to patients with autoantibodies against the non-dominant epitope of pyruvate dehydrogenase complex. Given that they are complementary, IFA and AgST should be performed in parallel. If there is high suspicion of AILD, AgST should always be performed.
Sampled-Data Observer Design With Exponential Time-Varying Gains for Semilinear Parabolic PDE Systems

For semilinear parabolic PDE systems, the sampled-data observer (SDO) design under spatially point measurements (SPMs) with exponential time-varying gains is concerned. On basis of a Lyapunov functional, a SDO with exponential time-varying gains under SPMs via linear matrix inequalities is presented to guarantee the exponential stability of estimation error PDE system. Lastly, two numerical examples are provided to support the proposed SDO design approach.
Pigeon-inspired Formation Control for Multi-UAVs under Obstacle Environments

In the real world, neighboring individuals with communication links determine the state and the weight of different individuals in the group. There are closer relations between the status of neighboring individuals in a collective system. To imitate this situation, a strategic model of collective system coordination and control was proposed by imitating the decision- making mechanism of pigeon flocks. Each individual changes its situation based on the weighting and distance to the neighboring individuals in the collective system. This paper mainly studies the problem of formation control inspired by the decision-making mechanism of pigeon flocks under obstacle environments. By designing the control law of fixed relative position and speed consistency and integrating it with the decision-making mechanism of pigeon flocks, formation control of the unmanned aerial vehicle (UAV) swarm is realized. A judging mechanism is proposed to determine whether it is necessary for UAVs to avoid obstacles. The simulation results show that the UAVs can generate, maintain and reconstruct the desired formation in a real-time manner under consideration of avoiding obstacles.
Application of Support Vector Regression in Predicting Cutting Chatter Trend

Having been encountered the difficulty of properly predicting the cutting chatter trend at present, a novel cutting chatter trend prediction method based on support vector regression algorithm(SVR) was put forward, meanwhile, the principle about how to select the SVR parameters was discussed. Ways about how to extract features from cutting signal process based on wavelet package decomposition were studied. Gabor wavelet basis was used to decompose the cutting signal to 3-order. The energy in each spectrum section was calculated and scaled. The resultswere input to the SVR model. Sampling and simulating on lathe (CA6140), the results turned out that the energy transition curve in each spectrum segment retrieved from above mentioned method gave a fine reflection of the cutting process transition from normal to chatter. The trend predicted by SVR shows a satisfactory consequence.
BPRIA: Crosstalk-Avoided Bi-Partitioning-Based Counter-Propagation Resource Identification and Allocation for Spectrally-Spatially Elastic Optical Networks

Signal transmission using counter-propagation nowadays is adopted to enhance resource utilization in spectrally-spatially elastic optical networks (SS-EONs), where inter-mode and inter-core crosstalks always degrade signal quality and become bottlenecks for high transport capacity. In this paper, we propose BPRIA for the first time, a Bi-Partitioning-based crosstalk-avoided Resource Identification and Allocation scheme in SS-EONs to enhance resource utilization while suppressing both inter-mode and inter-core crosstalks. We introduce a bi-partitioning optimization problem with vertex elimination to maximize the number of non-adjacent cores and modes in each partition of the bipartite graph; two distinct sets of cores and modes are used in a counter-propagation manner for lightpath allocation. The optimization problem is formulated as an integer linear programming (ILP) problem, and we prove that the optimization problem is NP-complete. An algorithm for core-mode-spectrum allocation is developed considering two distinct sets of cores and modes obtained by ILP to serve lightpath requests while avoiding inter-mode and inter-core crosstalks. For dynamic scenarios, we present core-mode-spectrum allocation. Numerical results reveal that the blocking probability is reduced by BPRIA in SS-EONs, and it enhances traffic admissibility in the network.
Mathematical Derivation and Simulational Verification for Aggressive Quadrotor Perching Control

Utilizing small quadrotor unmanned aerial vehicle (UAV) for data acquisition and environment surveillance in various situations has become a dazzling application in many fields. However, some applications require UAVs to make aggressive maneuvers to achieve perching landing, which can not be handled well by conventional PID control. A special Euclid group (SE(3)) control method based on geometric tracking method is studied, and the expressions of critical variables are mathematically derived in detail. The trajectory generation is solved by gorubi optimization tool under given constraints, and the effectiveness of this controller is verified by MATLAB simulation. The results show that this control method has very high control accuracy (position tracking and attitude tracking in 0.3s) and robustness, and suitable for the following quadrotor perching control study.
Critical Computational Evidence Regarding the Long-Standing Controversy over the Main Electrophilic Species in Hypochlorous Acid Solution

Although hypochlorous acid (HOCl) solution has become a popular electrophilic reagent for industrial uses, the question of which molecule (HOCl or Cl2) undergoes electrophilic addition with olefins remains a controversial issue in some literature and textbooks, and this problem has been largely underexplored in theoretical studies. In this work, we computationally studied the electrophilic addition mechanism of olefins using three experimentally predicted effective electrophilic chlorinating agents, i.e., HOCl, Cl2, and Cl2O molecules. Our results demonstrate that Cl2 and Cl2O are the main electrophilic agents in HOCl solution, whereas the HOCl molecule cannot be the electrophile since the energy barrier when directly adding HOCl molecule to olefins is too high to overcome and the “anti-Markovnikov” regioselectivity for tri-substituted olefin is not consistent with experiments. Notably, the HOCl molecule prefers to form oxonium ion intermediate with a double bond, rather than the generally believed chlorium ion intermediate. This work could benefit mechanistic studies of critical biological and chemical processes with HOCl solution and may be used to update textbooks.
Performance Analysis and Evaluation of Quantitative Real Time PCR for Diagnosis of Scrub Typhus in North-East India

Aims: Scrub typhus is a life-threatening infectious disease and always creating a diagnostic dilemma in terms of rapid turnaround time and accuracy, qRT PCR can become a very good option to achieve the desired result. This study was performed to evaluate the performance of qRT PCR in comparison to commonly used IgM ELISA and Weil-Felix tests to diagnose scrub typhus, in North-East India. Study Design: This was a hospital based prospective study. Place and Duration of Study: The study was conducted in the Department of Microbiology, of a tertiary care centre of North-East India over a period of 1 year (June 2019– May 2020). Methodology: Samples from suspected scrub typhus cases were screened by Weil-Felix test, followed by IgM ELISA for the confirmation of diagnosis. All the IgM positive samples and 20 highly suspected but ELISA negative samples were subjected to qRT PCR. Results: Out of 54 samples tested, 24 IgM ELISA positive samples and three IgM ELISA negative samples have shown the presence of bacterial DNA with quantification of DNA copies. It has also been observed that 21 out of 27 PCR positive samples (77.8%) were detected within the first seven days of illness. Conclusion: The performance of the commercial qRT PCR kit used in our study is satisfactory, which provides the extra advantage of quantification of DNA copies and increases diagnostic accuracy within the first week of fever.
Automation over Internet & Android app using RTOS

We need automation everywhere. From driving systems to theft security. It makes things fast & better without manual working. Microcontrollers are key to build such automation systems. We’re aiming to do a Home/office automation using AVR development board over (WAN) internet & Android App. It is based on AVR family controller (Atmega328). It’s an 8 bit controller with 32Kb flash with built in ADC, I2C, PWM, etc. The main theme of project is the, controlling GPIO (General Purpose Input/Output) of ATmega328 controller by Android app by Network Layer (UDP, TCP) communication with it. And also creating a Proximate Alert System which detects motion at home when we left it, and then sends message to API site which forwards it as a tweet to www.twitter. com site. And our android will give notification about the alert message. Also controlling many devices connected in LAN of the company with the help of web server created on our AVR board using popular POST method of web services. Which can also be helpful to automate a whole office (PCs, machines) using any PC in its network by Administrator. Also another application in the project is to log data of different sensors connected to GPIO ports of microcontroller on SD card in the form of . CSV file which can be used to plot graph of different sensor values at different times. Such logging of data also done on the web site called xively.com (formerly pachube) which is real time & can be possible when Microcontroller is online (Using Ethernet module via RJ45).
When a door becomes a window: using Glassdoor to examine game industry work cultures

ABSTRACT Despite a growing interest in its labour conditions, research about the games industry remains constrained by the streetlight effect. Non-disclosure and non-disparagement agreements, or HR blocking access for embedded research, are examples of how the industry can shield itself from outside view. Furthermore, when access is granted, researchers might find themselves constrained by their own timelines (tenure clocks, graduation deadlines, etc.) that are antithetical to long-term, embedded ethnographic research. In this article, I discuss an opportunity to look behind the curtain of the game industry via employee reviews left on Glassdoor, a popular job-seeking website. These reviews provide a means to gather worker perspectives in a way that reduces the potential for harm for those who speak out to counter the dominant, PR-polished narratives about working in the game industry being a ‘dream job. ’ To demonstrate Glassdoor’s utility as a supplemental data source for investigations of industry workplace cultures, I draw on employee reviews describing their experiences at Riot Games, developer of the Multiplayer Online Battle Arena League of Legends. These first-hand accounts of working at Riot provide a view into the games industry, allowing observation of how problematic work cultures become normalized, and ultimately, how workers who do not come to internalize these norms may be pushed out.
Joint Optimization of Task Offloading and Resource Allocation in UAV-Assisted MEC Networks

The cooperation between unmanned aerial vehicles (UAVs) and edge clouds (ECs) in mobile edge computing (MEC) networks can provide improved offloading services to the ground mobile users (MUs), especially in special situations where the number of MUs surges or the infrastructure is sparely scattered. In this work, we aim to minimize the weighted sum of delay and energy consumption among all MUs and the UAV via appropriate task offloading decision, resource allocation and location placement in the UAV-assisted MEC system. The optimization problem is formulated as a mix-integer nonconvex one, and a joint optimization algorithm based on the semidefinite relaxation (SDR) and successive convex approximation (SCA) techniques is proposed to obtain a feasible suboptimal solution. The numerical results are provided to demonstrate that our proposed joint optimization algorithm achieves lower system cost than other four baseline schemes in different scenarios.
Neutrophil extracellular traps promote cancer-associated inflammation and myocardial stress

ABSTRACT Cancer is associated with systemic pathologies that contribute to mortality, such as thrombosis and distant organ failure. The aim of this study was to investigate the potential role of neutrophil extracellular traps (NETs) in myocardial inflammation and tissue damage in treatment-naïve individuals with cancer. Mice with mammary carcinoma (MMTV-PyMT) had increased plasma levels of NETs measured as H3Cit-DNA complexes, paralleled with elevated coagulation, compared to healthy littermates. MMTV-PyMT mice displayed upregulation of pro-inflammatory markers in the heart, myocardial hypertrophy and elevated cardiac disease biomarkers in the blood, but not echocardiographic heart failure. Moreover, increased endothelial proliferation was observed in hearts from tumor-bearing mice. Removal of NETs by DNase I treatment suppressed the myocardial inflammation, expression of cardiac disease biomarkers and endothelial proliferation. Compared to a healthy control group, treatment-naïve cancer patients with different malignant disorders had increased NET formation, which correlated to plasma levels of the inflammatory marker CRP and the cardiac disease biomarkers NT-proBNP and sTNFR1, in agreement with the mouse data. Altogether, our data indicate that NETs contribute to inflammation and myocardial stress during malignancy. These findings suggest NETs as potential therapeutic targets to prevent cardiac inflammation and dysfunction in cancer patients.
Data-driven-based model predictive control of reagents addition for tungsten flotation process

In the actual froth flotation process, the complexity of the mechanistic model and the frequent fluctuations of production conditions make the design of control strategies for flotation reagents very difficult. Therefore, this paper proposes a data-driven-based Model Predictive Control (MPC) strategy of reagents addition for tungsten flotation process, which includes a flotation dynamic model based on Gate Recurrent Unit(GRU) network and an optimizer. Firstly, for the flotation process variables with time-series characteristics, a GRU network model is designed to achieve accurate prediction of concentrate grade. Then based on the principles of maximizing the tracking performance of the controller and minimizing the fluctuation of the control signal, a cost function is proposed to form an optimizer combined the constraints of reagents dose. Finally, the output of the optimizer is used to guide the flotation reagents addition process so that the concentrate grade tracks the set value. Experimental results show that the proposed GRU-MPC control strategy has good control performance.