Miracle-dz/UniFAR-FTUs huggingface dataset:
Community seismic network and localized earthquake situational awareness

Community-hosted seismic networks are a solution to the need for large numbers of sensors to operate over a seismically active region in order to accurately measure the size and location of an earthquake, assess resulting damage, and provide alerts. The Community Seismic Network is one such strong-motion network, currently comprising hundreds of elements located in California. It consists of low-cost, three-component, MEMS accelerometers capable of recording accelerations up to twice the level of gravity. The primary product of the network is to produce measurements of shaking of the ground and multiple locations of every upper floor in buildings, in the seconds during and following a major earthquake. Each sensor uses a small, dedicated ARM processor computer running Linux, and analyzes time series data in real time at hundreds of samples per second. The network reports on shaking parameters that indicate intensity of the structural response levels such as maximum floor acceleration and velocity, displacement of a floor in a building, as well as data products that depend on the response time histories. To do this, Cloud computing has been expanded through the use of statically defined subsets of sensors called cloudlets. These are smaller subsets of similar sensors that carry out customized calculations for those locations. The measurements are reported as rapidly as possible following an earthquake so that they may be incorporated into structural diagnosis and prognosis applications that can be used by first responders to prioritize their initial disaster management efforts. The cloudlet displays are customized for specific buildings and they show in real time: instantaneous displacement, inter-story drift, and resonant frequency and mode shapes using system identification software tools. The real-time display products are useful for decision-making about whether the potential for damage exists, what level of damage may have occurred and where, and whether total business disruption is necessary. City-wide dense monitoring makes it possible for emergency response managers to prioritize the target locations requiring first response on a block-by-block scale based on reports of shaking intensity.
Thin Film Composite Conductive Polymers Chemiresistive Sensor and Sample Holder for Methanol Detection in Adulterated Beverages

An inexpensive methanol sensor lid fabricated from a composite conductive polymer comprised of cellulose nanocrystals, carbon nanotubes and polyanilines (PANI@CNC/CNT) has been demonstrated. The sample holder composed of an inexpensive tube with Kanthal resistive heating for preferential methanol headspace sampling. The PANI@CNC/CNT nanoporous aerogel film has inherent ultra-high surface area, with the CNT/PANI free valence electrons affording a high electrical conductive material. The PANI@CNC/CNT methanol sensor performance was tested for its response to methanol, ethanol standards and methanol/ethanol mixtures. The sensor was 46 times more sensitive and selective to methanol compared to ethanol, and afforded a linear response in the 0-7% methanol concentration range, deviating from linearity above 10%. The sensor was also used to test methanol standards spiked in wine, yielding a linear (R2 = 0.9842) resistance change in response with methanol concentrations in the range, 0-7%. The sensor precision for triplicate standards for different concentrations (0.5-5.0%) averaged ~4.5%, indicating overall reliability of the device. With sample heating and detection time fixed at 10 mins, the sensor demonstrated optimal performance with a limit of detection of 0.30% for methanol. The sensor was tested for over 24 runs over a one-month period without significant loss in performance due to degradation. multiple uses without degradation in performance. The PANI@CNC/CNT has been found effective for as a dosimetric sensor for use in indoor air quality monitoring and beverage adulteration analysis.
The ubiquitin-proteasome system productively adapts to proteasomal and protein folding stressors via independent mechanisms

Aging, disease, and environmental stress are associated with failures in the ubiquitin-proteasome system (UPS), yet a quantitative understanding of how the UPS responds to stress conditions is lacking. Here we assessed the performance and adaptability of the UPS in yeast under stress conditions using quantitative measurements of misfolded substrate stability and stress-dependent UPS regulation by the transcription factor Rpn4. We found that impairing degradation rates (“proteasomal stress”) and generating misfolded proteins (“folding stress”) stabilized UPS substrates through separate, non-overlapping mechanisms. Folding stress stabilized proteins by causing aggregation rather than targeting to the proteasome and increasing overall proteasomal load. Despite differences in underlying proteostasis defects, the UPS productively adapted to both proteasomal and folding stressors using separate mechanisms of Rpn4 activation, in some cases resulting in no loss in UPS substrate degradation. Our work reveals the distinct effects of proteotoxic stressors and the versatility of cells in productively adapting the UPS.
Total vegetation control: a comprehensive summary of herbicides, application timings, and resistance management options

Abstract Total vegetation control (TVC) is an essential management practice to eliminate all vegetation for the purpose of protecting infrastructure, people, or natural resources on sites where vegetation poses major fire, visibility, and infrastructure risks. TVC is implemented on sites such as railroads, power substations, airports, roadsides, and oil and gas facilities. Current research has identified that tank-mixing two effective mechanisms of action is a superior resistance management strategy compared to rotating mechanisms of action; however, effective tank mixes for TVC have not been thoroughly evaluated. A field experiment was conducted from 2013 to 2014 at five sites in Colorado to compare 32 treatment combinations to two industry standards for TVC. Research objectives were (1) to identify herbicide tank-mix combinations for TVC with multiple effective mechanisms of action for resistance management, (2) to evaluate lower use rate alternatives to minimize nontarget impacts, and (3) to determine the efficacy of fall versus spring application timings. Seven treatments were identified as top-ranking treatments, averaging 96% bare-ground (BG) across five sites and two application timings. Four out of the seven top-ranked treatments included aminocyclopyrachlor, chlorsulfuron, and indaziflam. The industry standard diuron plus imazapyr was in the top ranking, whereas the other industry standard bromacil plus diuron performed inconsistently across sites. Probability modeling was used to predict the probability of achieving 97% or 100% BG with various treatment combinations. The combination of aminocyclopyrachlor, chlorsulfuron, indaziflam, and imazapyr had the highest predicted BG probability, with 88% predicted probability of achieving 100% BG, compared to 67% and 52% predicted probabilities for the industry standards diuron plus imazapyr and bromacil plus diuron, respectively. In three of the five sites, fall applications outperformed the same treatments applied in the spring. Several top-ranking treatments represent newer, lower use rate herbicide combinations that provide multiple mechanisms of action to manage herbicide-resistant weeds and minimize nontarget impacts. Nomenclature: Aminocyclopyrachlor; bromacil; chlorsulfuron; diuron; imazapyr; indaziflam
Variation in carbon and nitrogen isotopic ratios of fin and muscle tissues of Longnose Gar (
 Lepisosteus osseus
 ) and Smallmouth Buffalo (
 Ictiobus bubalus
 )

Fin clips have been proposed as a non‐lethal and non‐invasive alternative to dorsal muscle samples in stable isotope analysis. However, potential differences in elemental composition and turnover rates can bias inferences when different tissues are combined. Here, we tested the average difference and correlation of the isotopic signature of δ¹³C and δ¹⁵N between muscle and fin samples in two arge‐bodied fishes: Longnose Gar (Lepisosteus osseus) and Smallmouth Buffalo (Ictiobus bubalus). We found that δ¹⁵N signatures of muscle and fin tissues were strongly and positively correlated for both species, although the muscle tissue for Smallmouth Buffalo was slightly more enriched in δ15N. δ¹³C signatures of both tissues were significatively different and not strongly correlated for Longnose Gar, but similar and strongly correlated for Smallmouth Buffalo. Our results suggest that fin and muscle tissue can be combined for analyses of δ¹⁵N, but correction for higher enrichment of muscle tissue may be necessary for Smallmouth Buffalo. Conversely, combining fin and muscle tissue for analysis of δ¹³C requires more caution due to their weaker correlation and dependence of species identity.
FELAS: Fog Enhanced Look Ahead Secure Framework With Separable Data Aggregation Scheme for Efficient Information Management in Internet of Things Networks

Abstract With the recent development in cloud computing and adoption of the Internet of Things (IoT), the number of encoding and monitoring devices on IoT are expected to remain on the rise. This leads to unimaginable volume of data on IoT, thus affecting the performance of IoT networks. To mitigate this, several network arrangements and privacy-preserving security schemes that engage data aggregation to secure and reduce traffics in IoT or other forms of network had been proposed. However, most of these network arrangements not only incur high data traffic but also the employed data aggregation schemes are incapable of aggregating heterogenous IoT devices data. To address this challenge, we propose an efficient approach and framework for a secure IoT’s data management. The framework consists of a cascaded look ahead fog devices, which effectively solve problems associated with data locality and information management in IoT. It frequently keeps used data in closer and computationally cheaper fog levels while rarely used data are pushed to cloud data center. An effective aggregation and de-aggregation technique which allows aggregation of heterogenous devices’ data and de-aggregation of individual device data was proposed. Extensive performance analysis and evaluations are conducted, and the results indicated that the approach not only secure IoT network but with relatively low latency.
Ethical norms and issues in crowdsourcing practices: A Habermasian analysis

Crowdsourcing practices have generated much discussion on their ethics and fairness, yet these topics have received little scholarly investigation. Some have criticized crowdsourcing for worker exploitation and for undermining workplace regulations. Others have lauded crowdsourcing for enabling workers' autonomy and allowing disadvantaged people to access previously unreachable job markets. In this paper, we examine the ethics in crowdsourcing practices by focusing on three questions: (a) What ethical issues exist in crowdsourcing practices? (b) are ethical norms emerging or are issues emerging that require ethical norms? and, more generally, (c) how can the ethics of crowdsourcing practices be established? We answer these questions by engaging with Jürgen Habermas' discourse ethics theory to interpret findings from a longitudinal field study (from 2013 to 2016) involving key crowdsourcing participants (workers, platform organizers, and requesters) of three crowdsourcing communities. Grounded in this empirical study, we identify ethical concerns and discuss the ones for which ethical norms have emerged as well as others which remain unresolved and problematic in crowdsourcing practices. Furthermore, we provide normative considerations of how ethical concerns can be identified, discussed, and resolved based on the principles of discourse ethics.
Initial data release and announcement of the Fish10K: Fish 10,000 Genomes Project

With more than 30,000 species, fish are the largest and most ancient vertebrate group. Despite their critical roles in many ecosystems and human society, fish genomics lags behind work on birds and mammals. This severely limits our understanding of evolution and hinders progress on the conservation and sustainable utilization of fish. Here, we announce the Fish10K project, an international collaborative project or initiative? aiming to sequence 10,000 representative fish genomes under a systematic context within ten years, and officially welcome collaborators to join this effort. As a step towards this goal, we herein describe a feasible workflow for the procurement and storage of biospecimens, and sequencing and assembly strategies. To illustrate, we present the genomes of ten fish species from a cohort of 93 species chosen for technology development.
Long-Term N Fertilization Decreased Diversity and Altered the Composition of Soil Bacterial and Archaeal Communities

Soil microbial communities are essential in the cycling of nutrients that affect crop production. Our goal was to characterize the microbial community structure following 34 years of nitrogen (N) fertilization treatments in continuous maize production in highly fertile soils. Using 16S rRNA gene-based analysis of the V4 region via Illumina HiSeq2500 technology with downstream bioinformatics processing and analysis with QIIME 2.0, we aimed to characterize the prokaryotic communities under three increasing N fertilization rates. Factor analyses indicated that a high N level decreased the diversity of soil bacterial and archaeal communities and altered the relative abundance (RA) of the dominant (>1% RA) and minor (<1% RA) phyla. Among the 12 major phyla, we determined increases in Gemmatimonadetes, Proteobacteria, and Euryarchaeota, accompanied by reductions in Cyanobacteria, Chloroflexi, Firmicutes, and Planctomycetes with increasing N. Within the 29 minor phyla, N fertilization led to increases in Aquificae, WPS2, Parvarchaeota, AD3, FCPU426, Armatimonadetes, TM7, Chlamydiae, and OD1, along with reductions of Nitrospirae, WS3, Tenericutes, Lentisphaerae, OP3, Synergistetes, Thermotogae, and prokaryotes that could not be reliably assigned to a phylum (classified as Other).
Close-to-process strain measurement in ultrasonic vibration-assisted turning

Abstract. The application of ultrasonic vibration assistance in machining offers many benefits over conventional machining. In some machining processes, like the generation of geometrically defined microstructures by cutting, the interaction of the system components and the machining process can be particularly crucial with respect to the production result. Monitoring of ultrasonic vibration-assisted machining in terms of the in-process measurement of frequency and amplitude is currently realized by measurement inside the actuator; thus, measurement is presently undertaken relatively far away from the cutting process. In this paper an in-process measurement set-up based on strain gauges positioned close to the cutting edges is presented. It is used to investigate the induced vibration in the ultrasonic horn. Experiments on machine samples with and without ultrasonic vibration assistance are performed using the in-process measurement set-up described. The results of the strain gauges are analysed in comparison to internal feedback signal and surface measurements. The experiments show the high sensitivity of the measurement set-up presented and a huge gain of information compared with the conventional measurement approach. This enables improved controllability of the excited mode shapes as well as in-process adjustment of the ultrasonic vibration frequency and amplitude for the manufacturing of defined microstructures.
SIGNAL TRANSMISSION PERFORMANCE AT 1550NM OVER DIFFERENT FIBER LINKS.

We experimentally characterized and optimized the performance of a vertical cavity surface-emitting laser (VCSEL) in a communication link. VCSEL at 1550nm transmission windows was chosen for data rate of 10 G bps for metro networks due to its wavelength tune ability, cost and energy efficiency. The optical link was evaluated through Bit Error Rate (BER) measurements for 17 km over G.652 traditional fiber and compared to 24.69 km of Single Mode Fiber-Reduced Slope (SMF-RS) at 5.5mA bias current. The corresponding eye diagrams at telecommunication BER threshold of 10 -9 were captured on the scope. The BER for the two measurements were then compared. Transmission Pattern (PPG) a Bias-Tee (BT). The was above the threshold current at 5.5 m The modulated signal the VCSEL was then transmitted over the fiber under test (FUT). In this experiment, the FUT comprised of 17 km G.652 fiber and 24.69 km of G.655 fiber. A variable optical attenuator (VOA) was used to vary the optical signal power entering the photodiode to mimic the typical losses in a fiber link.The receiver consisted of Positive Intrinsic Negative (PIN) photodiode and an Electrical Amplifier (EA). This EA was used to amplify the electrical signal to meet the operational requirements of a (Bit Error Rate Tester) BERT. The quality of the transmitted signal was then evaluated by the eye diagram and BER measurements using an oscilloscope and BERT respectively. The BERT determines the number of errors received and compares the errors to the total number of transmitted bits. A clock signal from the PPG was used to synchronize the 10 G bps transmitted and received data signals. Then finally the quality of the optical signal was characterized by observing the electrical data eye diagrams, BER measurements and penalties. The optical communication system tolerance to the effects of dispersion were measured for the two fibers. The G.652 fiber used has low attenuation but has very high CD parameter of 17 p s/nm.km at 1550 nm compared to 0.35 p s/nm.km at 1310 nm.
Design and Assessment of Random Access Procedures Supporting Massive Connectivity and Low-Delay and High-Reliability Services in 5G

5G networks are expected to be used in many markets, one of which is the Factories of the Future (FoF). In the FoF, applications like regular monitoring and controlling of components (e.g. temperature) are introducing the need of massive deployment of sensors and actuators. Additionally, sensors which are monitoring time-critical components of the factory (e.g. pressure in power plants) should experience low delays with a high reliability. The current LTE-based technology for machine-type communications, namely Cat-M1, imposes limitations in supporting massive connectivity and application with low delay and high reliability requirements, primarily due to the so-called ‘Random Access’ (RA) procedure which is used by the devices to establish a connection with the base station, before the actual transmission of their data. The key objectives of this study are to assess the RA procedure currently used in Cat-M1 networks as a baseline, and furthermore design and evaluate a new RA procedure for 5G networks, which targets typical FoF applications and their requirements. Based on the simulation assessment of the procedures studied, it was found that the so-called ‘Two-Step RA procedure’ is performing the best regarding end-to-end delay. Specifically, it was found that e.g. in a FoF network with 3000 devices an end-to-end delay of 16 ms can be achieved with 99.99% reliability, introducing a gain of 64 ms compared to the end-to-end delay in Cat-M1 networks.
Spatial-temporal attention in Bi-LSTM networks based on multiple features for video captioning

Automatically generating rich natural language descriptions for open-domain videos is among the most challenging tasks of computer vision, natural language processing and machine learning. Based on the general approach of encoder-decoder frameworks, we propose a bidirectional long short-term memory network with spatial-temporal attention based on multiple features of objects, activities and scenes, which can learn valuable and complementary high-level visual representations, and dynamically focus on the most important context information of diverse frames within different subsets of videos. From the experimental results, our proposed methods achieve competitive or better than state-of-the-art performance on the MSVD video dataset.
Genetic scheduling policy on codelet model

The Codelet Model is a fine‐grained event‐driven hybrid parallel model inspired by dataflow, whose computing performance depends on the scheduling policy. An approximate optimal codelet scheduling policy based on the features of the task graphs is important to accelerate the performance of dataflow computer system. Therefore, we have proposed an adaptive genetic scheduling policy (GSP) for codelet by improving a “pure” genetic algorithm (IPGA) for given tasks with complex dependencies. It is verified that the genetic scheduling policy is effective according to bunches of experimental results.
Optimasi Algoritma C4.5 Dalam Prediksi Web Phishing Menggunakan Seleksi Fitur Genetic Algoritma

Salah satu isu terpenting saat ini dalam dunia online yaitu keamanan. Masalah keamanan terbesar salah satunya adalah Phishing yang melibatkan duplikat situs yang sah atau asli untuk menipu dengan mencuri informasi pengguna online. Memang diakui sangat sukar untuk membedakan situs asli dengan palsu. Oleh sebab itu dibutuhkan klasifikasi dalam memprediksi website yang terindikasi Phishing . Dengan klasifikasi dalam Algoritma C4.5, permasalahan tersebut dapat diselesaikan dengan menghasilkan rule dari pohon keputusan. Untuk dapat meningkatkan akurasi dari prediksi algoritma C4.5 dapat digunakan fitur seleksi dengan menggunakan algoritma genetika . Berdasarkan penerapan algorima C4.5 dihasilkan akurasi sebesar 83,81% untuk memprediksi website Phishing dan dengan seleksi fitur menggunakan algoritma genetika meningkatkan akurasi sebesar 3,22% menjadi 86,47. Dari penelitian ini algoritma genetika terbukti dapat meningkatkan akurasi untuk prediksi website phishing .
Spatial niche modelling of five endemic cacti from the Brazilian Caatinga: Past, present and future

Climate change, together with human activities, impacts on natural and human systems on all continents and poses a major threat to biodiversity, especially in environments with a high rate of endemism and where species are profoundly adapted to specific environmental conditions, as is the case of the seasonally dry tropical forests, noticeably the Caatinga, an exclusively Brazilian biome. The objective of this study was to build spatial niche models of five species of Cactaceae (Arrojadoa penicillata, Brasilicereus phaeacanthus, Pereskia aureiflora, Stephanocereus leucostele and Tacinga inamoena) endemic to the Caatinga and with different traits, to evaluate the impact of climate change on their geographical distribution. The species records and environmental variable values were overlaid on a grid of 6818 cells with 0.5° spatial resolution. Niche models were obtained for five types of general circulation models between ocean and atmosphere and 12 different ecological models. The ensemble ecological niche model was calculated at present and projected to past (last glacial maximum – LGM, 21 000; and mid‐Holocene – Hol, 6000 years ago) and future climate conditions (average of 2080), under the effect of climate change, in the greenhouse gas emission scenario RCP4.5. The distribution pattern of the studied species indicates an area with less environmental suitability in the LGM, followed by an expansion that began in the Hol and continued until the present period. In the future (2080), the models predicted a retraction of areas of environmental suitability, in which P. aureiflora and B. phaeacanthus, given their more restricted, marginal habitat and woody habit, present a great risk of extinction, whilst S. leucostele, A. penicillata and T. inamoena present a smaller reduction in suitable area, partly reflecting their spreading, less woody habit. Regional conservation actions for Cactaceae species and their habitat need to take these findings into account if we are to ensure the survival of these species.