Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and solutions of interoperability on IoT: How far have we come in resolving the IoT interoperability issues

Internet of Things (IoT) is the new digital realm that is taking the world by storm. With intense connectivity requirements and standards, IoT devices need to communicate with other devices through a common protocol. For these reason the interoperability is the most defining and crucial element in the Internet of Things. This paper has delved in the literature on IoT journals and article to identify the pertinent issues that require to be addressed if success of the system is to be realized. A primary break down of the IoT system has been done to identify the key issues upon which a list of challenges have been addressed with a help of literature. It has been discovered that as new devices are being developed at an unprecedented pace, their interoperability is becoming an issue. The nature of the challenges identifies requires that the stakeholders develop a standard that will guide them in their device development to ultimately to overcome the interoperability in the IoT system.
A REVIEW PAPER ON PREDICTION ANALYSIS: PREDICTING STUDENT RESULT ON THE BASIS OF PAST RESULT

— In today’s world competition is increasing day by day. In field of higher education as competition is increasing so the student self-harm rate is increasing. The reason for this is because students are not able to cope with studies and under pressure they do self-harm. Data mining is a technique which can be used to decrease this self-harm rate. In this paper we want to explain that using data mining we can predict result of students beforehand by using previous year result or any other factors in early stages of any course. This technique is called Prediction Analysis and this an example of use of data mining in the field of education. It can also be called as educational data mining. Any Data mining can be used for this prediction analysis and we will be using WEKA tool of data mining to predict result.
Nefopam for the prevention of postoperative pain: quantitative systematic review.

Nefopam, a centrally acting analgesic, has been used in the surgical setting in many countries since the mid-1970s. However, clinical trials provide contflicting results for its analgesic potency. We performed a systematic search (multiple databases, bibliographies, any language, to January 2008) for randomized, placebo-controlled trials of nefopam for the prevention of postoperative pain. Data were combined using classic methods of meta-analyses and were expressed as weighted mean difference (WMD), relative risk (RR), and number needed to treat/harm (NNT/H) with 95% confidence interval (CI). Nine trials (847 adult patients, 359 received nefopam) were included. Nefopam (cumulative doses, 20-160 mg) was given orally or i.v. , as single or multiple doses, or as a continuous infusion. Compared with placebo, cumulative 24 h morphine consumption was decreased with nefopam: WMD -13 mg (95% CI -17.9 to -8.15). Pain intensity at 24 h was also decreased: on a 100 mm visual analogue scale, WMD -11.5 mm (95% CI -15.1 to -7.85). The incidence of tachycardia was increased with nefopam (RR 3.12, 95% CI 1.11-8.79; NNH 7), as was the incidence of sweating (RR 4.92, 95% CI 2.0-12.1; NNH 13). There is limited evidence from the published literature that nefopam may be a useful non-opioid analgesic in surgical patients. The analgesic potency seems to be similar to non-steroidal anti-inflammatory drugs. However, dose responsiveness and adverse effect profile remain unclear, and the role of nefopam as part of multimodal analgesia needs to be established. Data in children are lacking.
A Two-Sample Test for Equality of Means in High Dimension

We develop a test statistic for testing the equality of two population mean vectors in the “large-p-small-n” setting. Such a test must surmount the rank-deficiency of the sample covariance matrix, which breaks down the classic Hotelling T2 test. The proposed procedure, called the generalized component test, avoids full estimation of the covariance matrix by assuming that the p components admit a logical ordering such that the dependence between components is related to their displacement. The test is shown to be competitive with other recently developed methods under ARMA and long-range dependence structures and to achieve superior power for heavy-tailed data. The test does not assume equality of covariance matrices between the two populations, is robust to heteroscedasticity in the component variances, and requires very little computation time, which allows its use in settings with very large p. An analysis of mitochondrial calcium concentration in mouse cardiac muscles over time and of copy number variations in a glioblastoma multiforme dataset from The Cancer Genome Atlas are carried out to illustrate the test. Supplementary materials for this article are available online.
A control algorithm for co-operatively aerial survey by using multiple UAVs

This paper addresses a coverage path planning algorithm for multiple Unmanned Aerial vehicles (UAV). The N number of UAVs are simultaneously planning the path to survey a given region. During the path planning, they avoid to survey the user defined no fly zone or obstacles. The proposed algorithm produces M number of ways to survey the region co-operatively. Out of those M ways the best solution is suggested by an objective function. The objective function is designed to calculate paths which will most equally distribute the work among the N number of UAVs. The main advantage of multiple UAVs over single UAV is redundancy. This implies that in case of failure of any of the UAV during survey operation, other UAV will compensate for the remaining uncovered area and thereby not affect the assigned mission target. This feature also included and testing within the Algorithm.
Alternative Control Strategies with Uncertain Trade Barriers for Foot-and-Mouth Disease in Feedlot Operations

Emergency response exercises have recognized issues associated with traditional control of foot-and-mouth disease (FMD) in large feedlots. The depopulation and disposal of large numbers of animals poses difficult challenges for environmental management and resource requirements. The study has focused on the epidemiological and economic consequences of allowing infected cattle to recover at the feedlot, as well as the economic consequences including uncertainty in trade sanctions.
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching

Poaching continues to be a significant threat to the conservation of wildlife and the associated ecosystem. Estimating and predicting where the poachers have committed or would commit crimes is essential to more effective allocation of patrolling resources. The real-world data in this domain is often sparse, noisy and incomplete, consisting of a small number of positive data (poaching signs), a large number of negative data with label uncertainty, and an even larger number of unlabeled data. Fortunately, domain experts such as rangers can provide complementary information about poaching activity patterns. However, this kind of human knowledge has rarely been used in previous approaches. In this paper, we contribute new solutions to the predictive analysis of poaching patterns by exploiting both very limited data and human knowledge. We propose an approach to elicit quantitative information from domain experts through a questionnaire built upon a clustering-based division of the conservation area. In addition, we propose algorithms that exploit qualitative and quantitative information provided by the domain experts to augment the dataset and improve learning. In collaboration with World Wild Fund for Nature, we show that incorporating human knowledge leads to better predictions in a conservation area in Northeastern China where the charismatic species is Siberian Tiger. The results show the importance of exploiting human knowledge when learning from limited data.
Sliding Dynamics of Parallel Graphene Sheets: Effect of Geometry and Van Der Waals Interactions on Nano-Spring Behavior

Graphene and carbon nanotubes are promising materials for nanoelectromechanical systems. Among other aspects, a proper understanding of the sliding dynamics of parallel graphene sheets or concentric nanotubes is of crucial importance for the design of nano-springs. Here, we analytically investigate the sliding dynamics between two parallel, rigid graphene sheets. In particular, the analysis focuses on configurations in which the distance between the sheets is kept constant and lower than the equilibrium interlayer spacing of graphite (unstable configurations). The aim is to understand how the interlayer force due to van der Waals interactions along the sliding direction changes with the geometrical characteristics of the configuration, namely size and interlayer spacing. Results show metastable equilibrium positions with completely faced sheets, namely a null force along the sliding direction, whereas net negative/positive forces arise when the sheets are approaching/leaving each other. This behavior resembles a molecular spring, being able to convert kinetic into potential energy (van der Waals potential), and viceversa. The amplitude of both storable energy and entrance/exit forces is found to be proportional to the sheet size, and inversely proportional to their interlayer spacing. This model could also be generalized to describe the behavior of configurations made of concentric carbon nanotubes, therefore allowing a rational design of some elements of carbon-based nanoelectromechanical systems.
Market Making Rents Under Discrete Prices - Theory and Evidence

The paper presents a value maximizing rationale for an exchange imposed restriction on prices to be multiple of (for example) 1/8th of a dollar. The minimum "tick size" poses a barrier to competing forces, thereby creating positive profits for the market maker. Discrete prices can, therefore, serve as a credible mechanism for enforcing cartel-like behavior of market makers. We also show thatthe effective commissions in a discrete price economy depend on the location of the underlying fundamental value. Discreteness of prices, per se, can cause asymmetric ask and bid commissions as well as market breakdowns. Interest- ingly, discrete prices need not always result in additional transaction costs for liquidity traders. Informed traders respond to the additional transaction costs by investing less in acquiring information. Thus, discrete prices can reduce the asymmetry of information. We find on both the bid and ask sides of the market, locations of the underlying fundamental value for which the effective commissions are less than the continuous-case equilibrium commission. Our model predicts that the variance of the location of the fundamental value is decreasing in the quoted spread. We use intraday transaction data to test this implication and report evidence consistent with our model.
IgG4‐Related Disease: Clinical and Laboratory Features in One Hundred Twenty‐Five Patients

IgG4‐related disease (IgG4‐RD) is an immune‐mediated fibroinflammatory condition that can affect nearly any organ. Prior studies have focused on individual cases of IgG4‐RD or small case series. This study was undertaken to report detailed clinical and laboratory findings in a larger group of patients with IgG4‐RD whose diagnosis was established by strict clinicopathologic correlation.
Robust Facial Landmark Localization Based on Texture and Pose Correlated Initialization

Robust facial landmark localization remains a challenging task when faces are partially occluded. Recently, the cascaded pose regression has attracted increasing attentions, due to it's superior performance in facial landmark localization and occlusion detection. However, such an approach is sensitive to initialization, where an improper initialization can severly degrade the performance. In this paper, we propose a Robust Initialization for Cascaded Pose Regression (RICPR) by providing texture and pose correlated initial shapes for the testing face. By examining the correlation of local binary patterns histograms between the testing face and the training faces, the shapes of the training faces that are most correlated with the testing face are selected as the texture correlated initialization. To make the initialization more robust to various poses, we estimate the rough pose of the testing face according to five fiducial landmarks located by multitask cascaded convolutional networks. Then the pose correlated initial shapes are constructed by the mean face's shape and the rough testing face pose. Finally, the texture correlated and the pose correlated initial shapes are joined together as the robust initialization. We evaluate RICPR on the challenging dataset of COFW. The experimental results demonstrate that the proposed scheme achieves better performances than the state-of-the-art methods in facial landmark localization and occlusion detection.
Quantifying Direct DNA Damage in the Basal Layer of Skin Exposed to UV Radiation from Sunbeds

Nonmelanoma and melanoma skin cancers are attributable to DNA damage caused by ultraviolet (UV) radiation exposure. One DNA photoproduct, the cyclobutane pyrimidine dimer (CPD), is believed to lead to DNA mutations caused by UV radiation. Using radiative transfer simulations, we compare the number of CPDs directly induced by UV irradiation from artificial and natural UV sources (a standard sunbed and the midday summer Mediterranean sun) for skin types I and II on the Fitzpatrick scale. We use Monte Carlo radiative transfer (MCRT) modeling to track the progression of UV photons through a multilayered three dimensional (3D) grid that simulates the upper layers of the skin. By recording the energy deposited in the DNA‐containing cells of the basal layer, the number of CPDs formed can be quantified. The aim of this work was to compare the number of CPDs formed in the basal layer of the skin and by implication the risk of developing cancer, as a consequence of irradiation by artificial and natural sources. Our simulations show that the number of CPDs formed per second during sunbed irradiation is almost three times that formed during solar irradiation.
Economic Sanctions as a Policy Instrument

E CONOMIC sanctions are economic measures directed to political objectives. They are normally supplemented by other measures, such as the severance or restriction of diplomatic and cultural ties; but unless otherwise stated the use of the term ' sanctions ' in this paper refers only to economic sanctions. Sanctions are sometimes employed in addition to force, but here we are primarily considering situations short of war. Not that the distinction is always easy to draw-many Arab states have, for example, imposed sanctions against Israel, but they see these sanctions as the economic dimension of a wider war effort. Indeed, the relationship between sanctions and the use of force is fraught with ambiguity. Whilst some advocates of sanctions see them as an alternative to force, there is a contrary view that sanctions can only be effective when force is available and ready to be used if required. This ambiguity has naturally led sometimes to confusion: for example, when the League of Nations was preparing in 1935 to impose sanctions against Italy some members were opposed to blocking the Suez Canal or cutting communications with Italy because the League was ' a great instrument of peace '. In contrast others believed that ' collective security '-the prevailing doctrine of the day-could only be ensured if force were available. This ambiguity, or double thinking, was exemplified in the case of Stanley Baldwin, the British Prime Minister of the time. According to Winston Churchill, Baldwin felt ' that Sanctions meant war; secondly he was resolved there must be no war; and thirdly, he decided upon Sanctions '. Some of those who oppose the use of force argue from the importance of moral factors in international relations, emphasising collective action to sustain prevailing international norms. Woodrow Wilson expounded this idea in Paris in December 1918 when he spoke of 'the organized moral force of man' working throughout the world so that 'whenever and wherever wrong -and aggression are planned or contemplated, this searching light of conscience will be turned upon them, and men everywhere will ask, " what are the purposes that you hold in your heart against the fortunes of the world? " Just a little
Regulatory and Mechanistic Actions of Glucocorticoids on T and Inflammatory Cells

Glucocorticoids (GCs) play an important role in regulating the inflammatory and immune response and have been used since decades to treat various inflammatory and autoimmune disorders. Fine-tuning the glucocorticoid receptor (GR) activity is instrumental in the search for novel therapeutic strategies aimed to reduce pathological signaling and restoring homeostasis. Despite the primary anti-inflammatory actions of GCs, there are studies suggesting that under certain conditions GCs may also exert pro-inflammatory responses. For these reasons the understanding of the GR basic mechanisms of action on different immune cells in the periphery (e.g., macrophages, dendritic cells, neutrophils, and T cells) and in the brain (microglia) contexts, that we review in this chapter, is a continuous matter of interest and may reveal novel therapeutic targets for the treatment of immune and inflammatory response.
Beginning at the ends: telomeres and human disease

Studies of rare and common illnesses have led to remarkable progress in the understanding of the role of telomeres (nucleoprotein complexes at chromosome ends essential for chromosomal integrity) in human disease. Telomere biology disorders encompass a growing spectrum of conditions caused by rare pathogenic germline variants in genes encoding essential aspects of telomere function. Dyskeratosis congenita, a disorder at the severe end of this spectrum, typically presents in childhood with the classic triad of abnormal skin pigmentation, nail dystrophy, and oral leukoplakia, accompanied by a very high risk of bone marrow failure, cancer, pulmonary fibrosis, and other medical problems. In contrast, the less severe end of the telomere biology disorder spectrum consists of middle-age or older adults with just one feature typically seen in dyskeratosis congenita, such as pulmonary fibrosis or bone marrow failure. In the common disease realm, large-scale molecular epidemiology studies have discovered novel associations between illnesses, such as cancer, heart disease, and mental health, and both telomere length and common genetic variants in telomere biology genes. This review highlights recent findings of telomere biology in human disease from both the rare and common disease perspectives. Multi-disciplinary collaborations between clinicians, basic scientists, and epidemiologist are essential as we seek to incorporate new telomere biology discoveries to improve health outcomes.
A Cyclic Prefix Assisted Spectrum Sensing Method for Aeronautical Communication Systems

Continuous growth of air-traffic demands new technologies for future aeronautical communication systems. L-band Digital Aeronautical Communications System (LDACS) is considered as a potential candidate for the future air-to-ground links. Spectrum utilization efficiency of LDACS can be improved by enabling dynamic spectrum access (DSA) in the system. In this context, the present paper proposes a novel cyclostationary feature detection scheme based on the periodicity of the autocorrelation of LDACS signals for spectrum sensing, which is key requirement in DSA. A wideband spectrum sensing simulation model is developed to evaluate the detection performance of the proposed scheme. To improve the adaptability of the spectrum sensing unit to variable wide bandwidth, the proposed system uses interpolation and masking based filters that can extract individual LDACS channels from the wide-band signals. Results of simulation studies show that the proposed scheme provides better detection accuracy against the conventional cyclostationary feature detection scheme and energy detection scheme, while maintaining the false alarm rates to an acceptable level which balances the overall throughput of the system.
Link between ICT investments, growth and jobs creation in Senegal : research paper

Empirical work of Jorgenson and al (2003), Timmer et al. (2003) showed that the development of new technologies was not always accompanied by an improvement of labour productivity. Under these conditions, it is essential to study the impact of the investment in ICT on the economic growth and employment in Senegal. Our methodology takes as a starting point the model of social account matrix multiplier, Pyatt and Round (1979), Defourny and Thorbecke (1984), and the multipliers derivation initiated by Thorbecke et al. (1996), aiming to measuring the possible externalities and impacts that investments on ICT generate on poverty reduction and jobs creation. The results highlight a significant effect of the ICT investment on growth, employment and poverty alleviation in Senegal.
The role of the lectin-like oxLDL receptor (LOX-1) in traffic-generated air pollution exposure-mediated alteration of the brain microvasculature in Apolipoprotein (Apo) E knockout mice

Abstract Recent studies have shown a strong correlation between air pollution-exposure and detrimental outcomes in the central nervous system, including alterations in blood brain barrier (BBB) integrity, neuroinflammation, and neurodegeneration. However, the mechanisms mediating these pathologies have not yet been fully elucidated. We have previously reported that exposure to traffic-generated air pollution results in increased circulating oxidized low-density lipoprotein (oxLDL), associated with alterations in BBB integrity, in atherosclerotic Apolipoprotein E null (ApoE−/−) mice. Thus, we investigated the role of the lectin-like oxLDL receptor (LOX)-1 in mediating these deleterious effects in ApoE−/− mice exposed to a mixture of gasoline and diesel engine exhaust (MVE: 100 PM µg/m3) for 6 h/d, 7d/week, for 30 d by inhalation. Concurrent with exposures, a subset of mice were treated with neutralizing antibodies to LOX-1 (LOX-1 Ab) i.p., or IgG (control) i.p., every other day during exposures. Resulting brain microvascular integrity, tight junction (TJ) protein expression, matrix metalloproteinase (MMP)-9/-2 activity, ROS, and markers of cellular adhesion and monocyte/macrophage sequestration were assessed. MVE-exposure resulted in decreased BBB integrity and alterations in microvascular TJ protein expression, associated with increased LOX-1 expression, MMP-9/-2 activities, and lipid peroxidation, each of which was attenuated with LOX-1 Ab treatment. Furthermore, MVE-exposure induced cerebral microvascular ROS and adhesion molecules, expression of which was not normalized through LOX-1 Ab-treatment. Such findings suggest that alterations in brain microvascular structure and integrity observed with MVE-exposure may be mediated, at least in part, via LOX-1 signaling.