Miracle-dz/UniFAR-FTUs huggingface dataset:
DÏoT: A Crowdsourced Self-learning Approach for Detecting Compromised IoT Devices

IoT devices are being widely deployed. Many of them are vulnerable due to insecure implementations and configuration. As a result, many networks already have vulnerable devices that are easy to compromise. This has led to a new category of malware specifically targeting IoT devices. Existing intrusion detection techniques are not effective in detecting compromised IoT devices given the massive scale of the problem in terms of the number of different manufacturers involved. In this paper, we present D\"IoT, a system for detecting compromised IoT devices effectively. In contrast to prior work, D\"IoT uses a novel self-learning approach to classify devices into device types and build for each of these normal communication profiles that can subsequently be used to detect anomalous deviations in communication patterns. D\"IoT is completely autonomous and can be trained in a distributed crowdsourced manner without requiring human intervention or labeled training data. Consequently, D\"IoT copes with the emergence of new device types as well as new attacks. By systematic experiments using more than 30 real-world IoT devices, we show that D\"IoT is effective (96% detection rate with 1% false alarms) and fast (<0.03 s.) at detecting devices compromised by the infamous Mirai malware.
CpeS Is a Lyase Specific for Attachment of 3Z-PEB to Cys82 of β-phycoerythrin from Prochlorococcus marinus MED4*

In contrast to the majority of cyanobacteria, the unicellular marine cyanobacterium Prochlorococcus marinus MED4 uses an intrinsic divinyl-chlorophyll-dependent light-harvesting system for photosynthesis. Despite the absence of phycobilisomes, this high-light adapted strain possesses β-phycoerythrin (CpeB), an S-type lyase (CpeS), and enzymes for the biosynthesis of phycoerythrobilin (PEB) and phycocyanobilin. Of all linear tetrapyrroles synthesized by Prochlorococcus including their 3Z- and 3E-isomers, CpeS binds both isomers of PEB and its biosynthetic precursor 15,16-dihydrobiliverdin (DHBV). However, dimerization of CpeS is independent of bilins, which are tightly bound in a complex at a ratio of 1:1. Although bilin binding by CpeS is fast, transfer to CpeB is rather slow. CpeS is able to attach 3E-PEB and 3Z-PEB to dimeric CpeB but not DHBV. CpeS transfer of 3Z-PEB exclusively yields correctly bound βCys82-PEB, whereas βCys82-DHBV is a side product of 3E-PEB transfer. Spontaneous 3E- and 3Z-PEB addition to CpeB is faulty, and products are in both cases βCys82-DHBV and likely a PEB bound at βCys82 in a non-native configuration. Our data indicate that CpeS is specific for 3Z-PEB transfer to βCys82 of phycoerythrin and essential for the correct configuration of the attachment product.
Should eGFR and Albuminuria Be Added to the Framingham Risk Score Chronic Kidney Disease and Cardiovascular Disease Risk Prediction

Presence of chronic kidney disease (CKD) defined as decreased glomerular filtration rate (GFR) and/or increased urine albumin excretion is associated with heightened risk of cardiovascular disease (CVD) and all-cause as well as CVD mortality. Although CKD is strongly linked with CVD, it remains undetermined whether this strong association is simply due to shared CVD risk factors or unique traits consequential to CKD. The probability of future CVD events can be estimated with reasonable accuracy using the Framingham equation which was derived from the Framingham study, a community-based cohort of 5,209 white adults aged 30–62 years who were first examined in 1948. Efforts to capture excess CVD risk associated with CKD have been evaluated by adding estimated GFR, cystatin C, serum creatinine and measures of urinary albumin excretion to the Framingham equation which is based on traditional cardiovascular risk factors. Although decreased GFR and increased urine albumin excretion are consistently associated with cardiovascular outcomes, the addition of these factors to the Framingham equation has not been shown to substantially improve overall CVD risk prediction in populations not enriched with CKD. Moreover, the Framingham equation itself underpredicts cardiovascular events among adults with stage 3 and 4 CKD without clinical CVD. Given the poor performance of the Framingham equation in adults with CKD, future studies should explore risk equations which include traditional CVD risk factors and the unique comorbidities associated with CKD for prediction of cardiovascular events in adults with CKD.
A review of thermal analysis methods in electromagnetic devices

This paper reviews different methods of thermal analysis, highlighting advantages, drawbacks, and limits. It represents the basics for both analytical methods and numerical ones; which the analytical method is discussed more in detail, including thermal coefficients relevant issues. Also, different applications are investigated, and related analytical and numerical techniques are represented. The aim is to give an exhaustive treatise of the various aspects concerning the thermal analysis. The key issues in thermal problem are represented. This paper is aimed as a tutor for designers who may be unfamiliar with this particular type of concepts; also they are leaded to some useful references for more details and investigation.
The Labour Market Impact of Adult Education and Training: A Cohort Analysis

Education boosts individuals' productivity and wages. Yet many individuals leave school with minimal skills and qualifications. One way for these workers to catch up might be lifelong learning. We find that a particular form of lifelong learning, work related training, does have a positive impact on earnings. However, firms tend only to train those workers who will gain from training. Training does benefit those chosen to receive it but if all workers received training, the average impact on wages would be low. Hence, this form of lifelong learning is not necessarily an effective way of raising wages.
Attendance at Australian Rules football: A panel study

The demand for Australian Rules football is examined using data on attendance at individual matches played between 1981 and 1986. An estimation methodology which is appropriate for a dynamic model with panel data is adopted and it is found that attendance at football is price inelastic and an inferior good. The effect of habit in consumption behaviour, stadium size, uncertainty of outcome and team success are also shown to be important determinants of attendance.
Long‐term hypovitaminosis D and secondary hyperparathyroidism outcomes of the Roux‐en‐Y gastric bypass: a systematic review

Pre‐operative Vitamin D deficiency is markedly prevalent in prospective bariatric surgery patients. While bariatric surgery leads to significant weight loss, it can exacerbate or prolong Vitamin D deficiency. We systematically reviewed the literature to assess whether secondary hyperparathyroidism is maintained in the medium to long term in patients following the Roux‐en‐Y gastric bypass.
Vertically aligned carbon nanotubes forest based flexible strain sensor for Internet of Things applications

In this work, we fabricated wearable strain sensors by iron-filled vertically-aligned carbon nanotubes (VA-CNTs), which would eliminate traditional nano-printing processes by directly depositing CNTs on bendable foil based substrate with Ferrocene (Fe(C5H5)2). The fabrication provides a forward potential for large-scale industrial manufacturing and flexible electronics design. Also, the vertically-aligned features give a significant improvement on the gauge factor compared to the mixed and multiple carbon nanotube-based material, the gauge factor (367) is higher than commercial strain sensors and previous research. The VA-CNTs sensor showed a high stability in the next generation mobile computing scenario by building a portable, cheaper, and highly synchronous embedded Internet of Things (IoT)-sensing system.
Efficiency of activation of the trauma team in a Norwegian trauma referral centre.

OBJECTIVE To evaluate the efficiency (sensitivity, specificity, positive predictive value, overtriage, and undertriage) of activation of the trauma team in a Norwegian trauma referral centre. DESIGN A cohort study with univariate and multivariate analysis. SETTING A primary trauma hospital and trauma referral centre, Norway. SUBJECTS 3391 injured patients admitted during a 12 months period, starting January 15th, 1996. MAIN OUTCOME MEASURES Activation of the trauma team for severely injured patients and factors associated with correct activation. RESULTS Of the 3383 injured patients admitted, 283 (8%) were classified as severely injured. Of 507 activations of the trauma team, 240 (47%) were for severely injured patients (sensitivity 85%, undertriage 15%, specificity 91%, overtriage 9%, positive predictive value 0.47). The system of activation was significantly more efficient for patients admitted by anaesthetist-manned ambulances than by ordinary ground ambulances (sensitivity 94% compared with 83%, corresponding positive predictive value 0.55 and 0.33, p < 0.05). Female sex and age over 70 years were independent factors associated with significantly less use of the trauma team in severely injured patients (p < 0.05). CONCLUSION The undertriage rate of 15% and a positive predictive value of only 0.47 indicates a need for improvement of our activation system. Female sex and age over 70 years were significantly associated with undertriage in severely injured patients. Our protocol for triage and the initial treatment of severely injured patients has been revised in the light of these findings, and we have established a trauma registry.
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines

NeuroNet is a deep convolutional neural network mimicking multiple popular and state-of-the-art brain segmentation tools including FSL, SPM, and MALPEM. The network is trained on 5,000 T1-weighted brain MRI scans from the UK Biobank Imaging Study that have been automatically segmented into brain tissue and cortical and sub-cortical structures using the standard neuroimaging pipelines. Training a single model from these complementary and partially overlapping label maps yields a new powerful "all-in-one", multi-output segmentation tool. The processing time for a single subject is reduced by an order of magnitude compared to running each individual software package. We demonstrate very good reproducibility of the original outputs while increasing robustness to variations in the input data. We believe NeuroNet could be an important tool in large-scale population imaging studies and serve as a new standard in neuroscience by reducing the risk of introducing bias when choosing a specific software package.
Meteosat Derived Planetary Temperature Trend 1982–2006

24 year of Meteosat hourly thermal infrared data have been used to study planetary surface temperature change. Thermal infrared radiation in the 10.5–12.5mm spectral window is not affected by CO2 and only slightly by atmospheric water vapor. Satellite thermal infrared data have been converted to brightness temperatures as prescribed by Eumetsat. Hourly brightness temperature images were then composed to corresponding noon and midnight temperature data fields. The resulting data fields were cloud filtered using 10, 20 and 30 day maximum temperature substitution. Filtered data were subsequently averaged for two 10 yearly periods: 1986–1995 and 1996–2005. Finally the change in brightness temperature was determined by subtraction. In addition nine locations were selected and data series were extracted and studied for the period 1982–2006. Our observations point to a decrease in planetary temperature over almost the entire hemisphere, most likely due to an increase of cloudiness. Two small areas are found where a considerable temperature increase has occurred. They are explained in terms of major human interventions in the hydrological balance at the earth surface.
Neural network embedded multiobjective genetic algorithm to solve non-linear time-cost tradeoff problems of project scheduling

This paper presents a novel method to solve non-linear time-cost tradeof f (TCT) problem of real world engineering projects. Multiobjective genetic algorithm (MOGA) is employed to search for optimal TCT profile. Applicability of ANN based model for rapid estimation of time-cost relationship by invoking its function approximation capability is investigated. ANN models are then integrated with MOGA so as to develop a comprehensive approach to solve non-linear TCT problems of project scheduling. The study has implications in real time monitoring and control of project scheduling process.
An Ancillary Services Model for Data Centers and Power Systems

Enormous energy consumption of data centers has a major impact on power systems by significantly increasing the electrical load. Due to the increase in electrical load, power systems are facing demand and supply miss-management problems. Therefore, power systems require efficient and intelligent ancillary services to maintain robustness, reliability, and stability. Data centers can provide the computational capabilities to manage power systems; however, data centers consume a tremendous amount of energy, and energy price accounts for a significant portion of their operational cost. Power system jobs will make this situation even more critical for data centers. In our work, we seek an Ancillary Services Model (ASM) to service data centers and power systems. In ASM, we find an optimal job scheduling technique for executing power systems’ jobs on data centers in terms of low power consumption, reduced makespan, and fewer preempted jobs. The power systems’ jobs include Optimal Power Flow (OPF) calculation, transmission line importance index, and bus importance index. Moreover, a Service Level Agreement (SLA) between data centers and power systems is shown to provide mutual benefits.
Acute effects of smoke exposure on airway and systemic inflammation in forest firefighters

Introduction The aim of this study was to assess respiratory health and airway and systemic inflammation in professional forest firefighters post firefighting. Methods A total of 60 firefighters who participated in forest firefighting operations in Greece during 2008 were included in the study. A questionnaire consisting of symptoms and exposure, pulmonary function, atopy, bronchial hyperresponsiveness, and markers of inflammation in induced sputum, serum, and bronchoalveolar lavage (BAL) fluid was assessed. Results A measurable eosinophilic and neutrophilic inflammation was shown to be induced in the bronchial airways after acute exposure during forest firefighting. This was associated with increased respiratory symptoms from the upper and lower respiratory tract and pulmonary function impairment. Additionally, a measurable systemic inflammatory response was demonstrated. This study showed that acute exposure during forest firefighting significantly augments the intensity of airway and systemic inflammation in relation to the baseline inflammatory background due to chronic exposure. Conclusion The repeated acute exposures during firefighting augment the burden of chronic airway and systemic inflammation and may eventually lead to allergic sensitization of the airways and increased incidence of rhinitis and asthma after prolonged exposure.
Collaborative Routing Algorithm for Fault Tolerance in Network on Chip CRAFT NoC

Many fault tolerance techniques have been proposed in Network on Chip to cope with defects during fabrication or faults during product lifetime. Fault tolerance routing algorithm provide reliable mechanisms for continue delivering their services in spite of defective nodes due to the presence of permanent and/or transient faults throughout their lifetime implementation. This paper presents a new approach in the domain of fault-tolerant NoC with two main contributions. Firstly, we consider a unified fault model that include transient faults, permanent faults and congestion considered as a fault. Secondly, we present a new architecture based on sub-nets and give an overview of the associated test and (re)routing algorithm. The main result of this paper, is a new routing algorithm called Collaborative Routing Algorithm for Fault Tolerance in Network on Chip (CRAFT-NoC). We compare our approach with ACOFAR that considers as well congestion and permanent faults. Our simulation results show significant improvements in terms of both latency and reliability.
Brand Elements Lead to Brand Equity: Differentiate or Die

The aim of this paper is to discuss brand elements and to explore its contribution to brand equity based on some relevant research reviews and some examples of prominent brands where brand elements have played a significant role to reach consumer’s head and heart. Brand is a combination of name, symbol or design, which creates a distinctive identity to consumers within a crowd of choices through its different brand elements. A distinctive or unique offering as well as get-up of a brand is the primary key of survival from the immature death in competition. Differentiating approach of different brand elements always cause a high level of brand awareness and familiarity among target consumers and later on individually or collectively, brand elements work as clue to consumers to recall and recognize the brand. Proper integration of both strong and weak brand elements of a brand contribute to brand equity, which has been focused here through some literature reviews.
Feedback and Motivation in Dynamic Tournaments

We investigate the choice to conduct interim performance evaluations in a dynamic tournament. When a worker's ability does not influence the marginal benefit of effort, the choice depends on the shape of the cost of effort function. When effort and ability are complementary, feedback has several competing effects: it informs workers about their relative position in the tournament (evaluation effect) as well as their relative productivity (motivation effect) and it creates signal-jamming incentives to exert effort prior to the performance evaluation. These effects suggest a tradeoff of performance feedback between evaluation and motivation which is in accordance with organizational behavior research and performance appraisal practices.
Modulation of F-actin dynamics by maternal Mid1ip1L controls germ plasm aggregation and furrow recruitment in the zebrafish embryo

ABSTRACT During the early embryonic cell cycles, zebrafish germ plasm ribonucleoparticles (RNPs) gradually multimerize and become recruited to the forming furrows. RNPs multimerization occurs prior to and during furrow initiation, as forming aggregates move outward through their association with the tips of growing interphase astral microtubules. Germ plasm RNPs are also associated with short cortical F-actin. We show that, in embryos mutant for the cytoskeletal regulator mid1ip1l, germ plasm RNPs fail to become recruited to the furrow, accumulating instead at the periphery of the blastodisc. RNP aggregates are associated with zones of mid1ip1l-dependent cyclical local cortical F-actin network enrichments, as well as contractions at both the cortex and the contractile ring. F-actin inhibition in wild-type embryos mimics the RNP peripheral accumulation defect of mid1ip1l mutants. Our studies suggest that a common mechanism underlies distinct steps of germ plasm RNP segregation. At the cortex, this process attenuates microtubule-dependent outward RNP movement to retain RNPs in the blastodisc cortex and allow their recruitment to the furrows. F-actin network contraction likely also facilitates higher-order germ plasm RNP multimerization. Summary: The cytoskeletal regulator Mid1ip1L is required in the early zebrafish embryo for F-actin dynamics and cortical contractions that modulate and facilitate germ plasm ribonucleoparticle aggregation.
Adaptive Fuzzy Neural-Network Control for Induction Spindle Motor Drive

An induction spindle motor drive using synchronous pulse width modulation (PWM) and dead-time compensatory techniques with an adaptive fuzzy neural-network controller (AFNNC) is proposed in this study for advanced spindle motor applications. First, the operating principles of a new synchronous PWM technique and the circuit of dead-time compensator are described in detail. Then, since the control characteristics and motor parameters for high speed operated induction spindle motor drive are time-varying, an AFNNC is proposed to control the rotor speed of the induction spindle motor. In the proposed controller, the induction spindle motor drive system is identified by a fuzzy neural-network identifier (FNNI) to provide the sensitivity information of the drive system to an adaptive controller. The back-propagation algorithm is used to train the FNNI online. Moreover, the effectiveness of the proposed induction spindle motor drive system is demonstrated using some simulated and experimental results.
Spontaneous changes in nucleotide sequence in proviruses of spleen necrosis virus, an avian retrovirus.

We determined the nucleotide sequence of about 1 kilobase of DNA 3' to the 5' long terminal repeat of three noninfectious ad one infectious proviral DNA clones of spleen necrosis virus, an avian retrovirus, to determine if the types of nucleic acid changes involved in retrovirus mutation shed light on special features of retrovirus replication. An open reading frame was found starting 411 base pairs from the end of the long terminal repeat. It contained sequences coding for the 36 amino acids at the amino terminus of the p30 of a related reticuloendotheliosis virus [Oroszlan, S. , Barbacid, M. , Copeland T. , Aaronson, S. A. & Gilden, R. V. (1981) J. Virol. 39, 845-854]. Therefore, the open reading frame represents the 5' end of the gag gene. A mutation in one noninfectious provirus changed the initiation codon for the gag polypeptide; a mutation in another noninfectious provirus caused premature termination of gag polypeptide synthesis; and a nontandem duplication into gag resulting from a mistake in initial (+) strand DNA synthesis changed amino acids and the reading frame in a third noninfectious provirus. These mutations appear to be responsible for the lack of infectivity of these provirus clones and indicate a higher relative frequency of mutation in this region of the genome. In addition, all four clones have multiple other mutations. These mutations are mostly base pair substitutions and many are clustered for any one clone, reflecting certain special features of retrovirus replication.