Miracle-dz/UniFAR-FTUs huggingface dataset:
An IoT Unified Access Platform for Heterogeneity Sensing Devices Based on Edge Computing

With the rapid development of the Internet of Things (IoT), a large number of heterogeneous sensing devices are accessed in their proprietary ways to IoT applications, formed “silos” application mode. The growth of IoT applications has been hampered by this mode due to the barriers of resource sharing of heterogeneous sensing devices. This paper proposes an IoT access platform deployed at the network edge near the sensing devices. This architecture can enable more responsive IoT applications and provide efficient privacy protection for sensitive data. We propose a general ontology-based resource description model of IoT devices to provide a consistent view of heterogeneous sensing devices for IoT applications in the cloud. Based on this model, we propose an adaptive access method to provide unified access, control, and management of IoT devices with various intelligence levels. The access platform turns the “silos” application mode of IoT into a horizontal application mode, supports applications to share and reuse the resources of IoT devices. We demonstrate the efficacy of our architecture with an application case study that highlights our proposed resource description model and adaptive access method and evaluate performance improvement with experiments.
Anonymity in Body Area Sensor Networks-an Insight

Based on the statistical surveys and United Nations report; by 2050, 805 out of 1000 people; older than 65 years of age, would suffer from at least one chronic disease. As per estimation 89% of these elderly people are expected to live independently which suggests the adoption of automated mechanism of health monitoring for the elderly. The need arises for developing components of Internet of things and Body Sensor Networks which have the ability to collect and transfer data over network without requiring any assistance. However, the most critical issue with Body sensor networks is the employment of critical and personal data. Our article focuses on the security and privacy concerns of such networks. We propose a mechanism through which data stored in the cloud as well as transferred on the network would be secure with the help of integrating anonymity as a feature.
Pilot-Aided Channel Estimation on SC-PAM Based Visible Light Communications

Estimation of the time-varying optical wireless channel response is crucial in order to decode received signals coherently. In this work, we investigate symbol-error-rate and mean absolute error performance of different interpolation techniques including linear, nearest, spline, and piece-wise cubic Hermite interpolating polynomial (pchip), which are used in pilot-aided channel estimation process for visible light communication. The performance of interpolators is evaluated in realistic time-varying channel model, generated on Zemax software and compared with each other under the consideration of different modulation orders, different pilot symbol periods, and different user equipment (UE) speeds through Monte Carlo simulations. The results reveal that spline and pchip techniques are more robust to low pilot symbol transmission rate and fast time-varying channel conditions as a consequence of high UE speeds. However, low complex linear interpolation technique can be chosen for highly rated pilot signal transmission cases or when optical channel varies slowly over the time.
Motion Planning of a Welding Robot for Cooperative Tasks with a Sequential Positioning Device

This paper deals with the motion planning problem of an industrial robot to achieve welding tasks working in cooperation with a positioning table. We consider that sequential displacements must be achieved by the robot and the table until finish the whole task. Thus, a method is proposed to find the successive placements that must be attained by the cooperative table in order to locate the workpiece in such a way that the kinematic performance of the robot be optimized during the task. The method is applied for a welding robot during the tracking of a 3D path. Simulation studies show the efficacy of the proposed method.
A Novel scheme of High-Speed Phase-Frequency Detector for Low-Power Low-Phase noise PLL Design

Phase-Frequency Detectors are commonly used in Phase-Locked Loop circuits, which they have been applied in many high-speed designs such as microprocessors and communication systems. In this work, a new structure of Phase-Frequency Detector (PDF1) is proposed to overcome the frequency limitations and the dead zone of the conventional design. The proposed PFD has been designed in Cadence virtuoso environment and implemented using 130 nm technology with a supply voltage of one Volt (1V). The results show excellent agreement with computer simulations, and significant reduction in area and power dissipation was observed, also the reset path has been completely removed in this design.
Performance Evaluation of LoRaWAN in North America Urban Scenario

This paper evaluates the single channel throughput, packet delivery ratio, average packet delay, and the end device battery lifetime performance of the LoRaWAN technology for deployment in North America urban scenario. In order to account for the operational details of the technology, the simulation approach is used for performance evaluation. The simulation results reveal that, by using four data rates on a single 125 kHz channel, the throughput is 1.8 times of the one data rate scenario. Second, for the simulated elderly sensor devices network with 1000 EDs, at least 6 GWs are needed to guarantee the packet delivery ratio to be higher than 0.8, the average packet delay to be less than 3 s, and the end device battery lifetime to be higher than 1300 h.
Real-World ISAR Object Recognition and Relation Discovery Using Deep Relation Graph Learning

Real-world inverse synthetic aperture radar (ISAR) object recognition is the most critical and challenging problem in computer vision tasks. In this paper, an efficient real-world ISAR object recognition and relation discovery method are proposed, based on deep relation graph learning. It not only handles the real-world object recognition problem efficiently, but also exploits the inter-modal relationships among features, attributes, and classes with semantic knowledge. First, dilated deformable convolutional neural network, including dilated deformable convolution and dilated deformable location-aware RoI pooling, is introduced to greatly improve CNNs’ sampling and transformation ability, and increase the output feature maps’ resolutions significantly. And a related multi-modal regions ranking strategy is proposed. Second, deep graph attribute-association learning is proposed to jointly estimate a large number of multi-heterogeneous attributes, and leverage features, attributes, and semantic knowledge to learn their relations. Third, multi-scale relational-regularized convolutional sparse learning is proposed to further improve the accuracy and speed of the whole system. The extensive experiments are performed on two real-world ISAR datasets, showing our proposed method outperforms the state-of-the-art methods.
Magnetic properties of oxides and silicon single crystals

The magnetic properties of single crystals Si, SrTiO3, LaAlO3, MgO, and (La,Sr)(Al,Ta)O3 were investigated systematically. Three origins of the magnetizations of these crystals, namely, an intrinsic diamagnetic, a paramagnetic, and a ferromagnetic contribution, have been found to influence the magnetic signals measured on the crystals, in some important application scenarios such crystals being served as substrates with the magnetic thin film epitaxially grown on. Quantitative analyses methodologies were developed and thorough investigations were performed on the crystals with the intrinsic materials parameters thus revealed, especially that the intrinsic diamagnetic susceptibility differential dχ dia/dT were identified quantitatively for the first time in SrTiO3, LaAlO3, MgO, and (La,Sr)(Al,Ta)O3. The paramagnetic contribution is found to be the key in terms of the magnetic properties of the crystals, which in turn is in fact a consequence of the 3d impurities doping inside the crystal. All the intrinsic materials parameters are given in this paper as datasets, the datasets are openly available at https://www.doi. org/10.57760/sciencedb.j00113. 00028.
An Improved LSTM Structure for Natural Language Processing

Natural language processing technology is widely used in artificial intelligence fields such as machine translation, human-computer interaction and speech recognition. Natural language processing is a daunting task due to the variability, ambiguity and context-dependent interpretation of human language. The current deep learning technology has made great progress in NLP technology. However, many NLP systems still have practical problems, such as high training complexity, computational difficulties in large-scale content scenarios, high retrieval complexity and lack of probabilistic significance. This paper proposes an improved NLP method based on long short-term memory (LSTM) structure, whose parameters are randomly discarded when they are passed backwards in the recursive projection layer. Compared with baseline and other LSTM, the improved method has better F1 score results on the Wall Street Journal dataset, including the word2vec word vector and the one-hot word vector, which indicates that our method is more suitable for NLP in limited computing resources and high amount of data.
Joint User Scheduling and Power Allocation for Energy Efficient Millimeter Wave NOMA Systems With Random Beamforming

In this paper, we investigate the user scheduling and power allocation scheme for a millimeter wave non-orthogonal multiple access system. To reduce the feedback overhead, random beamforming is adopted at a base station. The optimization problem is formulated to maximize the energy efficiency. To solve this problem, we first address the user scheduling and power allocation problem separately, then an iterative algorithm is proposed to jointly optimize the user scheduling and power allocation. Simulation results show that the proposed scheme achieves higher energy efficiency than the conventional scheme.
Reproductive Sociality. (Book Reviews: Cooperative Breeding in Birds. Long-Term Studies of Ecology and Behavior.)

Frontispiece Contributors Introduction P. B. Stacey and W. D. Koenig 1. Splendid Fairy-wrens: demonstrating the importance of longevity I. C. R. Rowley and E. Russell 2. Green Woodhoopoes: life history traits and sociality J. D. Ligon and S. H. Ligon 3. Red-cockaded Woodpeckers: a 'primitive' cooperative breeder J. R. Walters 4. Arabian Babblers: the quest for social status in a cooperative breeder A. Zahavi 5. Hoatzins: cooperative breeding in a folivorous neotropical bird S. D. Strahl and A. Schmitz 6. Campylorhynchus wrens: the ecology of delayed dispersal and cooperation in the Venezuelan savanna K. N. Rabenold 7. Pinyon Jays: making the best of a bad situation by helping J. M. Marzluff and R. P. Balda 8. Florida Scrub Jays: a synopsis after 18 years of study G. E. Woolfenden and J. W. Fitzpatrick 9. Mexican Jays: uncooperative breeding J. L. Brown and E. R. Brown 10. Galapagos mockingbirds: territorial cooperative breeding in a climatically variable environment R. L. Curry and P. R. Grant 11. Groove-billed Anis: joint-nesting in a tropical cuckoo R. R. Koford, B. S. Bowen and S. L. Vehrencamp 12. Galapagos and Harris' Hawks: divergent causes of sociality in two raptors J. Faaborg and J. C. Bednarz 13. Pukeko: different approaches and some different answers J. L. Craig and I. G. Jamieson 14. Acorn Woodpeckers: group-living and food storage under contrasting ecological conditions W. D. Koenig and P. B. Stacey 15. Dunnocks: cooperation and conflict among males and females in a variable mating system N. B. Davies 16. White-fronted Bee-eaters: helping in a colonially nesting species S. T. Emlen 17. Pied Kingfishers: ecological causes and reproductive consequences of cooperative breeding H. -U. Reyer 18. Noisy Miners: variations on the theme of communality D. D. Dow and M. J. Whitmore Summary J. N. M. Smith Index.
Assessing Cybersecurity Risks When Adopting Internet of Things (IOT) Devices

The Internet of Things (IoT) is a term covering a broad array of Internet-connected devices adopted by both business entities and consumers. Unfortunately, this connection to the Internet also exposes these devices to connections from other devices on the Internet. In the current cybersecurity environment, this means that IoT devices are susceptible to all manner of cybersecurity threats. Thus, the adoption of IoT devices brings with it exposure to an array of cybersecurity risks. This paper attempts to develop a framework to analyze the nature of cybersecurity threats and the resulting risks faced by entities adopting IoT devices.
Caracterización de harina y almidón de frutos de banano Gros Michel (Musa acuminata AAA)

En el estudio se determinaron las caracteristicas fisicoquimicas, termicas y reologicas de la harina y el almidon de frutos de banano Gros Michel (Musa acuminata) cosechado en fincas del departamento del Quindio, Colombia. En el analisis proximal, la harina presento un contenido de fibra de 18.82% y el almidon presento contenidos de proteina de 1.92%, grasa de 5.3% y fibra de 2.76%. La harina presento la temperatura mas alta de absorcion de calor (68.88 °C) y su entalpia de gelatinizacion fue de 2.17 J/g; mientras que para el almidon estos valores fueron de 48.36 °C y 44.62 J/g, respectivamente. El analisis termogravimetrico (TGA) de la harina o temperaturas en las cuales se registra la descomposicion de carbohidratos (componentes de bajo peso molecular) y polisacaridos (componentes de alto peso molecular) fueron, respectivamente, de 284.51 °C y 470.42 °C; y para el almidon fueron de 307.51 °C y 500.46 °C. Los granulos de almidon de banano tienen forma elipsoidal con un tamano longitudinal promedio de 39.39 µm y tamano transversal promedio de 29.47 µm. Los difractogramas de rayos X mostraron patrones de difraccion tipo B. Los viscoamilogramas mostraron que para la harina la temperatura de inicio de gelatinizacion (Tg) es de 76.3 °C, la viscosidad maxima de 1120 cP, y para el almidon la Tg fue de 70.75 °C y la viscosidad maxima de 2087 cP.
Randomised controlled trial of a nurse-led falls

SIR—The report of the randomised controlled trial of a nurse-led falls prevention programme (with a Falls Nurse), targeted at older people discharged from A&E departments after a fall, included several interesting findings [1]. The findings by Lightbody et al. have important implications about successful and unsuccessful elements in a falls reduction programme, but their conclusions cannot be supported by the data they present. The primary outcome measure (on which they based their power calculation) was the number of falls in each of the intervention and control groups, by 6 months after the index fall. This number (but not the number of fallers) was smaller in the intervention group, but the P value was 0.65 (questionnaire) or 0.89 (diary). The authors concluded that their intervention produced a reduction of falls-related hospital admissions, although this number was non significantly different (8 intervention and 10 controls) and they do not discuss that there were 91 and 67 falls-related GP attendances respectively. They highlight the fewer falls-related hospital inpatient days (69 and 233 days respectively) but this difference was also not significant and was probably explained by a few long stayers in the control group as we estimate, from their data, that the average length of stay was 8.6 and 23.3 days respectively. Therefore, and in contrast to their conclusion, their study showed that a nursedelivered intervention consisting of assessment, advice and referrals to a range of primary and community professionals has either no or at best only moderate efficacy in reducing subsequent falls. This contrasts with the results of Close et al. [2], who used a different approach to both diagnostic assessment and intervention. It is also consistent with what previous studies have shown to be the important risk factors and components of a successful approach [3, 4]. Compliance with the recommendations of the Falls Nurse was low, particularly when routed with a letter through primary care. No reduction in polypharmacy or culprit medications was achieved. A reduction in use of antihypertension medications and diuretics was achieved Letters to the Editor
Food-searching in parasitoids: the dilemma of choosing between 'immediate' or future fitness gains

Many parasitoid wasps and flies feed habitually on sugar-rich foods, consuming nectar and/or homopteran honeydew in the wild, and substitutes such as diluted honey in the laboratory. Consumption of these ‘non-host foods’ generally results in increases in female life expectancy, dispersal capacity, and realized fecundity. Typically in the wild, hosts and food sources are spatially separate. A female parasitoid therefore faces a choice as to which of the two types of resource she should forage for. Foraging for hosts will increase the likelihood of her obtaining ‘immediate’ fitness gains, but it will decrease her life expectancy. Foraging for food will postpone egg-laying to a later stage in adult life (constituting an ‘immediate’ reproductive opportunity cost), and will also incur energetic and mortality costs. However, it will increase opportunities to locate hosts in the future. From the standpoint of the fitness consequences of parasitoid foraging decisions, the exploitation of non-host foods is thus a highly interesting topic, posing the question of how females should forage so as to optimize trade-offs with respect to the use of both time and metabolic resources, and also mortality risks. In order to understand how such optimization might be achieved, we review current knowledge regarding resource ‘income’ and ‘capital’ used by females of parasitoid species that feed solely on non-host materials. Host-foraging versus non-host food-foraging, in such insects, has previously been modeled by means of stochastic dynamic programming. Using this technique, we model the behavioral scenario in which hosts and food patches are concurrently available but spatially separate. We focus initially on the egg maturation strategy of pro-ovigeny (in which all eggs are mature upon female emergence), but then examine the alternative and more common strategy of synovigeny (some eggs are immature). We discuss briefly the implications of variation in food availability for host population dynamics, and relate these to biological control scenarios. Finally, we identify promising avenues of future research. 9781405163477_4_007. qxd 03/09/2007 04:08PM Page 129
Community Changing densities of generalist species underlie apparent homogenization of UK 3 bird communities 4

Generalist species are becoming increasingly dominant in European bird communities. This has been 14 taken as evidence of biotic homogenization, where generalist ‘winners’ systematically replace 15 specialist ‘losers’. We test this by relating changes in the average specialisation of UK bird 16 communities to changes in the density of species with different degrees of habitat-specialisation. Although we find the expected continued decline in community specialisation, this was driven by a combination of a strong increase in the density of the most generalist quartile of species and declines 19 in the density of moderately generalist species. Contrary to expectation, specialist species increased slightly over the 18 year study period, but had little effect on the overall trend in community 21 specialisation. Our results indicate that the apparent homogenization of UK bird communities is not driven by the replacement of specialists by generalists, but instead by the changing fortunes of generalist species.
The Revival of the Notes Field: Leveraging the Unstructured Content in Electronic Health Records

Problem: Clinical practice requires the production of a time- and resource-consuming great amount of notes. They contain relevant information, but their secondary use is almost impossible, due to their unstructured nature. Researchers are trying to address this problems, with traditional and promising novel techniques. Application in real hospital settings seems not to be possible yet, though, both because of relatively small and dirty dataset, and for the lack of language-specific pre-trained models. Aim: Our aim is to demonstrate the potential of the above techniques, but also raise awareness of the still open challenges that the scientific communities of IT and medical practitioners must jointly address to realize the full potential of unstructured content that is daily produced and digitized in hospital settings, both to improve its data quality and leverage the insights from data-driven predictive models. Methods: To this extent, we present a narrative literature review of the most recent and relevant contributions to leverage the application of Natural Language Processing techniques to the free-text content electronic patient records. In particular, we focused on four selected application domains, namely: data quality, information extraction, sentiment analysis and predictive models, and automated patient cohort selection. Then, we will present a few empirical studies that we undertook at a major teaching hospital specializing in musculoskeletal diseases. Results: We provide the reader with some simple and affordable pipelines, which demonstrate the feasibility of reaching literature performance levels with a single institution non-English dataset. In such a way, we bridged literature and real world needs, performing a step further toward the revival of notes fields.
the Immunological Synapse Cytoskeleton Is Critical for the Formation of Cutting Edge: The Dendritic Cell

The binding of a T cell to an APC results in T cell actin cytoskeletal rearrangement leading to the formation of an immunological synapse. The APC cytoskeleton has been thought to play a passive role in this process. In this study, we demonstrate that dendritic cells (DC), unlike other APC, actively polarize their actin cytoskeleton during interaction with T cells. DC cytoskeletal rearrangement was critical for both the clustering and the activation of resting T cells. This study provides compelling evidence that the APC cytoskeleton plays an active role in the immunological synapse and may explain the unique ability of DC to activate resting T cells. The Journal of Immunology, 2001, 166: 1452–1456.
Social Bots as Initiators of Human Interaction in Enterprise Social Networks

Enterprise Social Networks (ESNs) are said to have the potential to significantly improve communication and collaboration between employees. However, utilization is still a problem in organizations, as participation is voluntary. Current research on Affordance theory in IS research suggests one reason being that users may not always recognize the opportunities for action and the potential outcome of the corresponding actualization. In our qualitative study in a medium-sized company, we investigate how experiencing offline networking with other ESN users will help to recognize online networking potentials, leading to an increased actualization of ESN affordances. In addition, we investigate the role of social bots (here: Lunch Roulette Bot), which provoke interaction by inviting users to meet other employees for lunch, therefore nudging users to experience certain actualizations like offline networking. We find that social bots can be more helpful than conventional one-to-many solicitations of the management and help increase human interaction in ESN.