Miracle-dz/UniFAR-FTUs huggingface dataset:
Drone Detection and Classification Using Cellular Network: A Machine Learning Approach

The main target of this paper is to propose a preferred set of features from a cellular network for using as predictors to do the classification between the rogue flying drone User Equipments (UEs) and regular UEs for different Machine Learning (ML) models. Furthermore, the target is to study four different machine learning models i.e. Decision Tree (DT), Logistic Regression (LR). Discriminant Analysis (DA) and K-Nearest Neighbour (KNN) in this paper, and evaluate/compare their performance in terms of identifying the flying drone UE using three performance metrics i.e. True Positive Rate (TPR), False Positive Rate (FPR) and area under Receiver Operating Characteristic (ROC) curve. The simulations are performed using an agreed 3GPP scenario, and a MATLAB machine learning tool box. All considered ML models provide high drone detection probability for drones flying at 60 m and above height. However, the true drone detection probability degrades for drones at lower altitude. Whereas, the fine DT method and the coarse KNN model performs relatively better compared with LR and DA at low altitude, and therefore can be considered as a preferable choice for a drone classification problem.
Social interactions do not drive territory aggregation in a grassland songbird.

Understanding the drivers of animal distributions is a fundamental goal of ecology and informs habitat management. The costs and benefits of colonial aggregations in animals are well established, but the factors leading to aggregation in territorial animals remain unclear. Territorial animals might aggregate to facilitate social behavior such as (1) group defense from predators and/or parasites, (2) cooperative care of offspring, (3) extra-pair mating, and/or (4) mitigating costs of extra-pair mating through kin selection. Using experimental and observational methods, we tested predictions of all four hypotheses in a tallgrass prairie in NE Kansas, USA. Grasshopper Sparrow (Ammodramus savannarum) males formed clumps of territories in some parts of the site while leaving other apparently suitable areas unoccupied. Despite substantial sampling effort (653 territories and 223 nests), we found no support for any hypothesized social driver of aggregation, nor evidence that aggregation increases nest success. Our results run counter to previous evidence that conspecific interactions shape territory distributions. These results suggest one of the following alternatives: (1) the benefits of aggregation accrue to different life history stages, or (2) the benefits of territory aggregation may be too small to detect in short-term studies and/or the consequences of aggregation are sufficiently temporally and spatially variable that they do not always appear to be locally adaptive, perhaps exacerbated by changing landscape contexts and declining population sizes.
Studying the Applicability of Intrusion Detection to Multi-Tenant Container Environments

The use of containers in cloud-based applications allows for rapid and scalable deployments. Containers are lightweight and appealing to be used even in business-critical systems, but their use implies great security concerns, which are exacerbated in multi-tenant environments. To mitigate these concerns, techniques such as intrusion detection are a must, however, in the containers' context, it has received limited attention. Thus, it is necessary to define an improved approach to container-level intrusion detection for multi-tenant environments. In this paper we make a preliminary feasibility analysis of host-based container-level intrusion detection. For this, we are currently focusing on achieving a stable container profile definition and the results obtained show we are following the correct path.
X-RDMA: Effective RDMA Middleware in Large-scale Production Environments

X-RDMA is a communication middleware deployed and heavily used in Alibaba’s large-scale cluster hosting cloud storage and database systems. Unlike recent research projects which purely focus on squeezing out the raw hardware performance, it puts emphasis on robustness, scalability and maintainability of large-scale production clusters. X-RDMA integrates necessary features, not available in current RDMA ecosystem, to release the developers from complex and imperfect details. X-RDMA simplifies the programming model, extends RDMA protocols for application awareness, and proposes mechanisms for resource management with thousands of connections per machine. It also reduces the work for administration and performance tuning with built-in tracing, tuning and monitoring tools.X-RDMA has been deployed in several large-scale clusters with over 4000 servers in Alibaba cloud since 2016. It can save at least 70% development and maintenance time over RDMA, effectively improve performance and reduce network jitter especially when production servers are under pressure. It also helped locate over 30 issues in different layers of productions with over 5000 connections for each server on average.
Life Transitions and Social Technologies: Research and Design for Times of Life Change

When people experience major changes in their lives (e.g., relationship changes, transition from high school to college, realizing an LGBTQ identity, etc.), they often turn to social technologies to help navigate shifting identities and networks and find support and resources. People's experiences using social technologies during times of life transition, and how to better design such technologies, has been a major focus of social computing research. This workshop will gather researchers working in this space to discuss eight themes: life events vs. processes; changing identities; multiple overlapping life events; physical and digital transitions; technology non-use during life transitions; liminality framework; theoretical frames; and methodological considerations. Collaboratively, we will 1) synergize insights from workshop organizers' and participants' research to determine how social technologies can be designed to better support people during life transitions and 2) outline an agenda for the future of social computing work on life transitions.
CDK5: Key Regulator of Apoptosis and Cell Survival

The atypical cyclin-dependent kinase 5 (CDK5) is considered as a neuron-specific kinase that plays important roles in many cellular functions including cell motility and survival. The activation of CDK5 is dependent on interaction with its activator p35, p39, or p25. These activators share a CDK5-binding domain and form a tertiary structure similar to that of cyclins. Upon activation, CDK5/p35 complexes localize primarily in the plasma membrane, cytosol, and perinuclear region. Although other CDKs are activated by cyclins, binding of cyclin D and E showed no effect on CDK5 activation. However, it has been shown that CDK5 can be activated by cyclin I, which results in anti-apoptotic functions due to the increased expression of Bcl-2 family proteins. Treatment with the CDK5 inhibitor roscovitine sensitizes cells to heat-induced apoptosis and its phosphorylation, which results in prevention of the apoptotic protein functions. Here, we highlight the regulatory mechanisms of CDK5 and its roles in cellular processes such as gene regulation, cell survival, and apoptosis.
Advances on Dientamoeba fragilis Infections

Dientamoeba fragilis is an enteric protozoan parasite that remains neglected, probably due to the misconception that it is uncommon and non-pathogenic. As more information be‐ came available and antimicrobial agents were developed with activity against this para‐ site, it became clear that D. fragilis is responsible of an active infection, associated with symptoms such as abdominal pain and diarrhea. The clinical presentation of dientamoe‐ biasis varies from asymptomatic carriage to symptoms ranging from altered bowel mo‐ tions, abdominal discomfort, nausea and diarrhea with associated eosinophilia reported in up to 50% of paediatric and 10% of adult patients. Moreover, controversy exists over the protective role of the parasite in priming the immune system in a beneficial way such as in selecting beneficial bacteria, keeping potential harmful microbial intruders at bay or producing metabolites beneficial to the host. Thus, a number of ambiguities and obscuri‐ ties surrounding D. fragilis infections exist. Moreover, the means by which this parasite is transmitted has not been fully defined. The diagnostic recognition of this parasite in fecal examinations requires specific processing and expertise; thus, it is possible that many in‐ fections with D. fragilis may go undiagnosed. A number of studies conducted on small numbers of case reports have demonstrated parasite clearance, as well as resolution of clinical symptoms following treatment with various antiparasitic compounds such as pa‐ romomycin, hydroxyquinolines and the 5-nitroimidazoles, including metronidazole and tinidazole. In addition there is very little in vitro susceptibility data available for the or‐ ganism making some current treatment options questionable. This chapter reviews the scientific literature relating to Dientamoeba's life cycle, prevalence, diagnosis and patho‐ genicity.
Proxy Individual Positioning via IEEE 802.11 Monitor Mode and Fine-Tuned Analytics

Indoor positioning of individuals is one of the most important technologies in smart home applications for user-customized support. The indoor positioning is typically fulfilled through radio signal strength indicators (RSSIs) of referred devices with specific media such as Wi-Fi access points (APs) and Wi-Fi station devices (STAs). So, the capability of typical positioning schemes is highly close to the signal acquisition environments of such media. In other words, since STAs frequently fall into a sleep mode to save the battery power and some data acquisition technologies are based on advertising intervals, the amount of RSSIs of referring devices could not be gathered enough to detect correct positions of individuals. In this paper, a novel individual positioning mechanism, called PIPing (Proxy Individual Positioning), is come up with. The PIPing mechanism carries out proxy signal acquisition via IEEE 802.11 monitor mode devices to overcome such restrictions. In addition, PIPing includes machine learning based signal data analytics to provide high reliable results for positioning. Based on the proof-of-concept prototype, PIPing can acquire much higher amount of RSSI data than existing manners, about 330% increment; the reliability of positioning for a home with seven rooms shows 96.4% via the support vector machine (SVM) and 96.5% by the multilayer perceptron (MLP) with autoencoder denoising to tune up signals.
High glucose inhibits osteogenic differentiation and proliferation of MC3T3-E1 cells by regulating P2X7

Diabetes mellitus adversely affects human bones and increases the risk of developing osteoporosis. In the present study, treatment with 30 mmol/l glucose was used to establish a high glucose (HG) cell model in vitro. Plasmids were used to overexpress the P2X purinoceptor 7 (P2X7) gene. Brilliant blue G and (4-benzoyl-benzoyl)-ATP were used as a P2X7 antagonist and agonist, respectively. Proliferation of osteogenic MC3T3-E1 cells and alkaline phosphatase (ALP) activity were determined using MTT and colorimetric assays, respectively. Alizarin Red S was used to assess calcification of MC3T3-E1 cells. Western blotting and reverse transcription-quantitative PCR were performed to determine protein and mRNA expression levels. The results demonstrated that HG inhibited MC3T3-E1 cell proliferation and P2X7 expression, reduced calcification, and downregulated the expression levels of ALP and osteocalcin (Ocn) in MC3T3-E1 cells. Overexpression of P2X7 in HG conditions increased calcification and proliferation, and upregulated the levels of ALP and Ocn in MC3T3-E1 cells. Inhibition of P2X7 downregulated the expressions of ALP and Ocn in MC3T3-E1 cells under HG conditions. Therefore, the present results indicated that HG caused damage to osteogenic MC3T3-E1 cells. Thus, P2X7 may be a regulatory factor that may be used to counteract the effects of HG on osteogenesis.
Pragmatic Tool vs. Relational Hindrance

Social media privacy features can act as a mechanism for regulating interpersonal relationships, but why do some people not use these features? Through an interview study of 56 social media users, we found two high-level perspectives towards social media and privacy that affected attitudes towards and usage of privacy features. Some users took a pragmatic approach to using social media and felt comfortable using various privacy features as a tool to manage their social relationships (e.g., avoiding bothersome posts, not feeling compelled to interact). However, there were also users who viewed taking such privacy actions as a relational hindrance and were concerned how using certain features to meet their own needs would harm their relationships with others. Through a subsequent survey (N=320), we reveal how these two perspectives impact user behavior across four social media platforms (Facebook, Instagram, LinkedIn, Twitter). Users who viewed social media as a pragmatic tool indeed used privacy features more. On the other hand, users who focused on how privacy can serve as a relational hindrance avoided using these features and, instead, prioritized social engagement and took a more indirect approach to protecting their privacy. Furthermore, the results show how these perspectives vary by individual rather than by privacy feature. These findings demonstrate the need to consider different perspectives towards social media and privacy when trying to understand and design for user behavior.
Letter to the Editor

We are in reply to the study of Kersnovske et al. [1]. The authors have clearly described the process and outcome of a validation study by means of a questionnaire survey among experts in the field of functional capacity evaluations (FCEs). In our opinion, however, the study comprises a limitation, which has not been addressed in the discussion section of the paper, but which may be important for the interpretation of the results. The limitation concerns the use of experts for the purpose of validation. The authors described that experts were selected on the basis of knowledge in the area under investigation and experience. Experience was operationally defined in number of years. As skeptical readers we tend to think: ‘they know about FCEs and may have done this for a while, but what makes them experts in the field? ’ Are the ‘experts’ truly experts? Should experts not be people with outstanding knowledge and experience, operationally defined for example in number of FCEs done? Additionally, how should the results of this study be generalized? Do the results represent OTs in general, OTs trained in FCEs, Australian OTs, Australian GAPP FCE trained OTs, or ‘the FCE field’? It would be worth a follow-up study to determine whether differences exist between the expert opinions of the current group and another group of experts with different operational definitions of ‘experts’.
Spontaneous Gait Recovery after Sciatic Nerve Transection Impairs the Non-Invasive Evaluation of Artificial Nerve Guides in Rats

Purpose: The study of the in-vivo regeneration of a nerve, made by purely histological methods, requires a high number of animals: this poses serious problems of technique, ethics and funding. A cheaper analysis, performed on the same animal along the duration of a study, is seeked with favour and Authors wanted to evaluate gait recovery after sciatic nerve transection as a non-invasive method to evaluate the performance of an artificial nerve-guide in rats. Methods: Male Wistar rats (n=16) were divided into three groups: in group A (n=5) the experimental gap produced was bridged by a custom-made guide; in group B (n=7) animals were “sham-operated”; in group C (n=4) a PMMA cap sealed the proximal
Jeavons syndrome – updated review

Summary Introduction Eyelid myoclonia and absences (ELMA) was first described by Jeavons in 1977 as a separate type of photosensitive epilepsy. Aim and method The aim is to consider the updated electro-clinical pathophysiology and to discuss terminology, classification and differential diagnosis. The review includes our own research and relevant papers on the subject of Jeavons syndrome (JS). Review and differential diagnosis Definition eavons syndrome is a generalized idiopathic (genetic) epilepsy syndrome (IGE) characterized by eyelid myoclonia, other seizures (absences, myoclonic and or generalized tonic-clonic) and EEG paroxysms induced by voluntary or on command eye closure, in the light and photosensitivity. Demographical data The prevalence of JS has been reported to vary from 7.3% to 12.9% among idiopathic generalized epilepsies and 2.5% to 2.7% among all patients with epileptic disorders. Etiology JS, as is the case for all idiopathic generalized epilepsies, is genetic and the familial preponderance and concordance is high. Pathophysiology Three factors are important in order for JS to manifest clinically; the genetic predisposition, the voluntary or on command eye closure and the light input. Clinical forms of JS we have identified four forms of JS; early onset (< 4 years), mild form, classical form and an ELMA-JME form. Diagnosis the diagnosis of JS is based on the history, clinical observation and provocation and the confirmation with an EEG. Differential diagnosis is easily made from tics, other idiopathic generalized or focal cryptogenic/symptomatic epilepsies. Conclusion JS is characterized by unique electro-clinical features evoked by voluntary or on command eye closure in the light and photosensitivity.
Generative Interior Design using BIM

Computational methods for automatically generating multiple valid alternative solutions to design problems offer the potential for creativity and innovation, by efficiently creating a potentially much larger number of alternatives, among which to select the design that best suits a variety of criteria. In this paper, we present our work on a particular instance of the general generative-design problem, namely the task of generating 3D kitchen layouts, based on a BIM model of the kitchen space, a product catalog of 3D models of kitchen furnishings, and a set of kitchen design rules. Our generative-design method starts with an empty kitchen and implements a heuristic search of the solution space by incrementally selecting and placing a required item and checking the degree to which the resulting model complies with the given kitchen design rules. We have demonstrated the effectiveness of our method by comparing the designs it produces against a set of real-world kitchen examples, obtained from architecture diagrams available online.
Poster: Using Generative Adversarial Networks for Secure Pseudorandom Number Generation

Generation of secure random numbers has always been a challenging issue in design and development of secure computer systems. Random numbers have important applications in the field of cryptography where the security of the scheme relies upon the random nature of the keys. It is not practically possible to achieve true randomness in a machine, and hence we rely upon Pseudo Random Number Generators (PRNGs) to produce near-true randomness. PRNGs use a mathematical function that relies upon a seed (a preset value required by the function to generate values) and it generates numbers which satisfy certain tests for randomness and appear to be random for a user having no knowledge of the generator function. These pseudorandom functions have their drawbacks due to them being derived from a mathematical function. To generate random numbers that can never be predicted by any observer, requires a causally non-deterministic process where events are not fully determined by prior states. Due to the physical impossibility of acquiring sufficient information to predict the outcome of such an event, its outcomes are guaranteed to be random to all. Various methods to generate pseudorandomness have been employed over the years which includes using mathematical functions, keyboard typing latency of the user, network latency, memory latency etc. as sources of generating random numbers. In this work, we propose a new way of generating pseudorandom numbers using generative adversarial networks. We demonstrate that a GAN can act as a Cryptographically Secure Pseudorandom Number Generator (CPRNG) passing 97% of National Institute of Standards and Technology (NIST) tests.
Contemporary Screening in Pregnancy

Screening tests and genetic ultrasonography have great importance in pregnancy management and follow-up. First-trimester screening, second trimester screening and genetic ultrasonography have widespread use globally. Although, some obstetricians still insist on using the second trimester screening as a first line choice, first-trimester screening with ultrasound including nuchal thickness, nasal bone, tricuspid regurgitation, ductus venosus blood flow and biochemical tests are getting more pronounced rather than the second trimester screening test in the upcoming literature. In this paper, we have aimed to review the new approaches and current screening methods in pregnancy.
Joint Computation Offloading and Resource Configuration in Ultra-Dense Edge Computing Networks: A Deep Reinforcement Learning Solution

The prompt development of wireless communication network and emerging technologies such as Internet of Things (IoT) and 5G have increased the number of various mobile devices (MDs). In order to enlarge the capacity of the system and meet the high computation demands of MDs, the integration of ultra-dense heterogeneous networks (UDN) and mobile edge computing (MEC) is proposed as a promising paradigm. However, when massively deploying edge servers in UDN scenario, the operating expense reduction has become an essential issue to be solved, which can be achieved by computation ofﬂoading decision-making optimization and edge servers' computing resource conﬁguration. In consideration of the complicated state information and ever-changing environment in UDN, applying reinforcement learning (RL) to the dynamical systems is envisioned as an effective way. Toward this end, we combine the deep learning with RL and propose a deep Qnetwork based method to address this high-dimensional problem. The experimental results demonstrate the superior performance of our proposed scheme on reducing the processing delay and enhancing the computing resource utilization.
Phase Rotated Non-Orthogonal Multiple Access for 3-User Superposition Signals

Non-orthogonal multiple access (NOMA) is one of the most promising techniques to achieve high spectral efficiency for 5G. In the NOMA downlink, a transmitter allocates different power levels to users and linearly combines user signals using the square roots of the power levels. A constellation point of the combined signal can be very close to other points, which degrades bit error rate (BER) performance severely. To overcome such degradation, the proposed NOMA system rotates phases of the user signals and then linearly combines the resultant signals. On the receiver side, multiuser detection (MUD) is introduced so as to improve BER performance more than successive interference cancellation (SIC), which the conventional scheme employs. Since the proposed scheme with phase rotation (PR) for 2-user signal transmission has been thoroughly investigated, this paper considers 3-user transmission in the proposed NOMA scheme and proposes one method to optimize two angles of PR, whereas another method previously proposed by the authors can control only one angle. Computer simulations under the 3-user condition demonstrate that the proposed scheme employing PR and joint MUD and SIC for signal detection is much superior to other schemes in downlink BER performance and that the two optimization methods bring about almost the same BER.