Miracle-dz/UniFAR-FTUs huggingface dataset:
Intermittent communications modeling and simulation for autonomous unmanned maritime vehicles using an integrated APM and FSMC framework

In this work a framework is presented for addressing the issue of intermittent communications faced by autonomous unmanned maritime vehicles operating at sea. In particular, this work considers the subject of predictive atmospheric signal transmission over multi-path fading channels in maritime environments. A Finite State Markov Channel is used to represent a Nakagami-m modeled physical fading radio channel. The range of the received signal-to-noise ratio is partitioned into a finite number of intervals which represent application-specific communications states. The Advanced Propagation Model (APM), developed at the Space and Naval Warfare Systems Center San Diego, provides a characterization of the transmission channel in terms of evaporation duct induced signal propagation loss. APM uses a hybrid ray-optic and parabolic equations model which allows for the computation of electromagnetic (EM) wave propagation over various sea and/or terrain paths. These models which have been integrated in the proposed framework provide a strategic and mission planning aid for the operation of maritime unmanned vehicles at sea.
Enhanced CDMA performance from an InGaP/InGaAsN/GaAs N-p-N double heterojunction bipolar transistor

We have demonstrated the DC characteristics and CDMA performance of an NpN InGaP/InGaAsN/GaAs double heterojunction bipolar transistor (DHBT) and compared the results to conventional InGaP/GaAs HBTs. A 100 mV reduction in base-emitter turn-on voltage and 35 mV reduction in offset voltage is established relative to InGaP/GaAs HBTs using a low energy-gap InGaAsN alloy base material and optimized heterointerfaces. InGaP/InGaAsN DHBT structures with high p-type doping levels (/spl sim/3/spl times/10/sup 19/ cm/sup -3/) have demonstrated DC current gains of /spl beta/=70 at 350 /spl Omega///spl square/ base sheet resistance. The DC current gain of InGaP/InGaAsN DHBTs has been improved by 46 % by grading the base layer composition. InGaAsN DHBTs have demonstrated 1.9 GHz CDMA IS-95 performance of 21 dBm output power (0.31 mW//spl mu/m/sup 2/ - 933 mW/mm), with 18.5 dB associated gain and greater than 53 % power-added efficiency at 45 dBc ACPR and 3 V operation. This represents an 83 mW/mm increase in output power and 3.8 percentage points improvement in PAE performance relative to InGaP/GaAs HBTs.
Mutations in SZT2 result in early‐onset epileptic encephalopathy and leukoencephalopathy

Early‐onset epileptic encephalopathies (EOEEs) are a genetically heterogeneous collection of severe epilepsies often associated with psychomotor regression. Mutations in SZT2, a known seizure threshold regulator gene, are a newly identified cause of EOEE. We present an individual with EOEE, macrocephaly, and developmental regression with compound heterozygous mutations in SZT2 as identified by whole exome sequencing. Serial imaging characterized the novel finding of progressive loss of central myelination. This case expands our clinical understanding of the SZT2‐phenotype and emphasizes the role of this gene in the diagnostic investigation for EOEE and leukoencephalopathies.
The Prevalence of Anxiety and Depression in Adult Hospitalized Pa- tients in Internal and Surgical Wards of Shiraz Hospitals-1387(2008).

Background and Objectives: The objective of this study was to find out the prevalence of anxiety and depression in adult hospitalized patients in internal and surgical wards of Shiraz University Hospitals in year 2008. Materials and Methods: The study was designed as a cross sectional study. A validated measurement tool was used in this study was the Hospital Anxiety and Depression Scale (HADS) (the questionnaire of case ness). Data collection was carried out in two major university hospitals and two private hospitals in Shiraz. Statistical analysis included the Student’s t test, and chi-square test and logistic regression analysis. Results: Thirty (4.3%) patients were normal within anxiety and depression, 216 (30.9%) were borderline cases of anxiety, 454 (64.9%) were probable cases of anxiety, 373 (53.4%) were borderline cases of depression and 296 (42.3%) were probable cases of depression. There was significant association between normal, borderline and probable groups of depression according to times of admissions and also between normal, borderline and probable groups of anxiety and depression according to duration of hospitalization and ward of admission. Most of borderline and probable cases of anxiety were admitted in internal ward. Most of normal and probable cases of depression were admitted in internal ward too. Discussion and conclusion: Prevalence of anxiety and depression in hospitalized medical patients is grate. The high levels of anxiety and depression detected in this sample suggests that screening for psychological co-morbidity is important in rehabilitation settings and should be included in the clinical interview carried out by the nurse at the duration of admission to the ward. Accurate diagnosis of co-morbid depressive and anxiety disorders in patients who admitted in medical care services is essential in understanding the cause and in optimizing the management of somatic symptom burden.
Apoptosis inhibitor of macrophage (AIM) reduces cell number in canine histiocytic sarcoma cell lines

Apoptosis inhibitor of macrophage (AIM) is initially reported to protect macrophages from apoptosis. In this study, we determined the effect of AIM on the macrophage-derived tumor, histiocytic sarcoma cell lines (HS) of dogs. Five HS and five other tumor cell lines were used. When recombinant canine AIM was applied to non-serum culture media, cell numbers of all the HS and two of other tumor cell lines decreased dose-dependently. The DNA fragmentation, TUNEL staining and flow cytometry tests revealed that AIM induced both of apoptosis and cell cycle arrest in the HS. Although AIM is known as an apoptosis inhibitor, these results suggest that a high dose of AIM could have an opposite function in HS and some tumor cell lines.
Effects of the November 2012 Flood Event on the Mobilization of Hg from the Mount Amiata Mining District to the Sediments of the Paglia River Basin

The Mount Amiata mining district (southern Tuscany, Italy) was, for decades, one of the world’s largest mercury (Hg) producing regions, where mining activity lasted until the 1980s. The Paglia River drains the eastern part of the district and is also the main western tributary of the Tiber River. Recent studies show that, still today, high total Hg contents severely affect the downstream ecosystems of these rivers. In November 2012, a major flood event occurred in the Paglia River basin, which drastically changed the river morphology and, possibly, the Hg concentrations. In the present work, stream sediment was sampled before and after the flood to evaluate possible changes in sediment total Hg concentrations as a consequence of this event. The comparison between pre- and post-flood Hg concentrations shows that Hg content increased up to an order of magnitude after the flood, suggesting that this event triggered Hg mobilization in the basin rather than its dilution.
Zone-Based Distributed Sensing Scheme in Decentralized Cognitive Radio Networks

In cognitive radio networks, secondary users conduct local sensing to use underutilized spectrum bands. However, every secondary user's local sensing usually gives rise to much sensing overhead. Moreover, a globally synchronized quiet period cannot be determined in a decentralized network. In this paper, we propose a zone-based distributed sensing scheme, in which multiple secondary users alternate in local sensing and share the results with others. To do that, we define a sensing zone in which one's sensing results are sharable with others. Moreover, a secondary user can determine its quiet period schedule efficiently while performing the proposed sensing. Numerical analyses and computer simulations show that our proposed sensing achieves the significantly reduced sensing overhead as well as the improved channel access opportunity.
Do Charitable Subsidies Crowd Out Political Giving? The Missing Link between Charitable and Political Contributions

Abstract In the United States, charitable contributions can be deducted from taxable income making the price of giving inversely related to the marginal tax rate. However, several other types of contributions such as donations to political organizations are not tax deductible. This paper investigates the spillover effects of charitable subsidies on political giving using five cross-sectional surveys of charitable and political giving in the United States conducted from 1990 to 2001. The results show that charitable and political giving are complements. Compared with non-donors, charitable donors are more likely to donate and give more to political organizations. Increasing the price of charitable giving decreases not only charitable giving but also the probability of giving and the amount of donations to political organizations. This effect is robust under different specifications and highlights the externalities created by charitable subsidies.
In-depth Analysis of the Adipocyte Proteome by Mass Spectrometry and Bioinformatics*S

Adipocytes are central players in energy metabolism and the obesity epidemic, yet their protein composition remains largely unexplored. We investigated the adipocyte proteome by combining high accuracy, high sensitivity protein identification technology with subcellular fractionation of nuclei, mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized role, is very complex. Comparison with microarray data showed that the mRNA abundance of detected versus non-detected proteins differed by less than 2-fold and that proteomics covered as large a proportion of the insulin signaling pathway. We used the Endeavour gene prioritization algorithm to associate a number of factors with vesicle transport in response to insulin stimulation, a key function of adipocytes. Our data and analysis can serve as a model for cellular proteomics. The adipocyte proteome is available as supplemental material and from the Max-Planck Unified Proteome database.
Simple, Fast Noise-Contrastive Estimation for Large RNN Vocabularies

We present a simple algorithm to efficiently train language models with noise-contrastive estimation (NCE) on graphics processing units (GPUs). Our NCE-trained language models achieve significantly lower perplexity on the One Billion Word Benchmark language modeling challenge, and contain one sixth of the parameters in the best single model in Chelba et al. (2013). When incorporated into a strong Arabic-English machine translation system they give a strong boost in translation quality. We release a toolkit so that others may also train large-scale, large vocabulary LSTM language models with NCE, parallelizing computation across multiple GPUs.
International Research/expert Conference " Trends in the Development of Machinery and Associated Technology " Monitoring of the Machining Process for Aluminium and Steel Division of Manufacturing Systems Engineering 2 Division of Sound and Vibrations 3 Ab Sandvik Coromant

Avoiding vibrations and tool failure during machining is of great importance for most machining applications, especially when manufacturing slender parts with thin walls as in aerospace industry. Excessive vibrations during machining of such a part will affect its fatigue life. Vibrations can be avoided by choosing appropriate process parameters, such as feeds and speeds. In order to predict the behaviour of a component while it is being machined and to adjust the process parameters so that harmful vibrations are avoided, a machining optimisation and control system is envisaged consisting of several modules. The present work studies the correlation between on-line sensor signals and properties of the machined surface. The experiments are done in a 5-axis, high-performance milling machine. Machining and on-line signal detection of an aluminium alloy and of a hardened steel type is studied for three different settings of the feed rate. The on-line applicability of the sensor test-bed during the cutting process is demonstrated, providing highly valuable vibration information on the process. 1. INTRODUCTION The milling process and how the parameters affect the stability, forces and surfaces generated is well known and has been researched during many year s, from the beginning of the '60s, where Tobias [1] looks into how to design machine tools considering vibrations during cutting, to the more recent work by Altintas [2] and Liu [3]. The use of accelerometers and force sensors is widely spread throughout the industry and the academic world for monitoring and studying the process and spindle behaviour. Different types of force sensor systems are described by Milfelner [4] and Rehorn [5]. The sensors can be used in different setups and evaluated with different mathematical models as shown by Kuo [6]. Another measuring method of acquiring data on the part behaviour during processing is LDV (Laser Doppler Vibrometry), see Rantatalo et al [7]. To move the experiments into the virtual world the Finite Element Modelling technique (FEM) is used, which can simulate many static or dynamic events. The biggest advantage over experimental work is that cases can be studied with many variables for lots of variations. FEM techniques are used by milling tool manufacturers [8] to design and optimize the tool geometry and performance, e.g. to simulate the workpiece movement during cutting [9] and in turn to calculate the tolerances of the finished part. When milling slender parts the general way of doing this is to stop machining at intervals …
General tax Structures and the Lévy Insurance Risk Model

In the spirit of Albrecher and Hipp (2007), and Albrecher, Renaud, and Zhou (2008) we consider a Lévy insurance risk model with tax payments of a more general structure than in the aforementioned papers, which was also considered in Albrecher, Borst, Boxma, and Resing (2009). In terms of scale functions, we establish three fundamental identities of interest which have stimulated a large volume of actuarial research in recent years. That is to say, the two-sided exit problem, the net present value of tax paid until ruin, as well as a generalized version of the Gerber–Shiu function. The method we appeal to differs from Albrecher and Hipp (2007), and Albrecher, Renaud, and Zhou (2008) in that we appeal predominantly to excursion theory.
Channel Estimation for Two-Way Relay Networks in the Presence of Synchronization Errors

This paper investigates pilot-aided channel estimation for two-way relay networks (TWRNs) in the presence of synchronization errors between the two sources. The unpredictable synchronization error leads to time domain offset and signal arriving order (SAO) ambiguity when two signals sent from two sources are superimposed at the relay. A two-step channel estimation algorithm is first proposed, in which the linear minimum mean-square-error (LMMSE) estimator is used to obtain initial channel estimates based on pilot symbols and a linear minimum error probability (LMEP) estimator is then developed to update these estimates. Optimal training sequences and power allocation at the relay are designed to further improve the performance for LMMSE based initial channel estimation. To tackle the SAO ambiguity problem, the generalized likelihood ratio testing method is applied and an upper bound on the SAO detection error probability is derived. By using the SAO information, a scaled LMEP estimation algorithm is proposed to compensate for the performance degradation caused by SAO detection error. Simulation results show that the proposed estimation algorithms can effectively mitigate the negative effects caused by asynchronous transmissions in TWRNs, thus significantly outperforming the existing channel estimation algorithms.
A review of the literature on effective leadership behaviours for safety

There is widespread agreement between industry, regulators, academics and the press that leadership is a key component of a safe organisation. This view is widely supported by findings from almost all major incident inquiries and investigations. However, the widespread agreement that leadership is central to safety does not extend to how leadership should deliver safety, what needs to be done, and rather importantly, who should be doing it. While there is considerable literature on leadership, very little of this addresses the issue of safety, particularly in the major hazard sector. This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents, including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily reflect HSE policy. You may reuse this information (not including logos) free of charge in any format or medium, under the terms of the Open Government Licence. To view the licence visit Some images and illustrations may not be owned by the Crown so cannot be reproduced without permission of the copyright owner. Enquiries should be sent to • Transformational and transactional theories of leadership have received considerable empirical support suggesting that they can be appropriate for the effective management of safety. Other leadership theories, such as authentic leadership, whilst holding great promise lack empirical research regarding their impact on safety. • Managers can have a positive influence on safety outcomes by articulating a clear vision for safety, and motivating employees to achieve it, acting as role models and showing concern for the welfare of employees (e.g. transformational leadership), communicating and setting clear goals and standards for safety, monitoring and recognising positive safety behaviours (e.g. transactional leadership). • Effective leaders are coaching-oriented, supportive, provide the necessary resources and encourage worker involvement in safety. • Managers' leadership styles and behaviours can impact on safety directly but also through indirect mechanisms. Managers who actively champion safety can foster perceptions of a positive safety climate, which in turn impact on safety. • Management commitment to safety, active involvement and participation in safety and consistent enforcement of safety policies is associated with positive safety outcomes, such as positive perceptions of safety climate and reduced levels of risk taking behaviours. • Safety communication and worker involvement in improving safety have a positive impact on safety. Good working relationships between management, typically supervisors and employees, and perceptions that management values safety influence …
Feature selection approach based on whale optimization algorithm

In this paper, a feature selection system is introduced applies the whale optimization algorithm (WOA). WOA is a recently introduced meta-heuristic optimization algorithm that mimics the natural behavior of the humpback whales. The proposed model applies the wrapper-based method to reach the optimal subset of features. This technique was applied to find the best feature subset that maximizes the accuracy of the classification while preserving the minimum number of features. The proposed model is compared with the particle swarm optimization (PSO) and genetic algorithm (GA) using a number of assessment indicators on 16 different data-sets from UCI data repository. The results demonstrate the advantage of the introduced algorithm compared to the other optimizers.
Religious Nonaffiliation and Schooling: The Educational Trajectories of Three Types of Religious “Nones”

Purpose – Previous studies have found that, for those born after 1960, individuals raised with no religious affiliation were less likely than any other religious group to complete a college degree. This finding is surprising in light of the increasing educational attainment of the American public, as well as the finding that declining religious belief is often presumed to accompany higher education. In this chapter, we explore the changing relationship between religious nonaffiliation and educational attainment for Americans over the past three decades. Methodology – In order to disentangle the mechanisms behind this relationship, we consider the heterogeneity of nonaffiliates and examine educational attainment for three types of religious “nones. ” Using the General Social Survey (1972–2008), we look for cohort differences in attaining a bachelor's degree among persistent nones, disaffiliates, and adult affiliates. Findings – While being raised in no religious tradition was once predictive of higher odds of completing a college degree, the positive relationship between being raised a religious none and college completion has reversed itself in the past 30 years. Instead, for individuals born after 1960, being raised in no religious tradition is actually associated with lower odds of completing a 4-year college degree relative to adults who were raised in any religious tradition and continue to claim a religious identity in adulthood. This effect is particularly pronounced for adults who maintain no religious identity throughout the life course. Social implications – We propose some explanations for this finding, with a particular emphasis on the potential significance of religious social networks in adolescence.
Does Gold Offer a Better Protection Against Sovereign Debt Crisis than Other Metals?

It is a commonly held view that gold protects investors’ wealth in the event of negative economic conditions. In this study, we test whether other metals offer similar or better investment opportunities in periods of market turmoil. Using a sample of 13 sovereign bonds, we show that other precious metals, palladium in particular, offer investors greater compensation for their bond market losses than gold. We also find that industrial metals, especially copper, tend to outperform gold and other precious metals as hedging vehicles and safe haven assets against losses in sovereign bonds. However, the outcome of the hedge and safe haven properties is not always consistent across the different bonds. Finally, our analysis suggests that copper is the best performing metal in the period immediately after negative bond price shocks.
Reasoning about Fences and Relaxed Atomics

For efficiency reasons, weak (or relaxed) memory is now the norm on modern architectures. To cater for this trend, modern programming languages are adapting their memory models. The new C11 memory model [1] allows several levels of memory weakening, including non-atomics, relaxed atomics, release-acquire atomics, and sequentially consistent atomics. Under such weak memory models, multithreaded programs exhibit more behaviours, some of which would have been inconsistent under the traditional strong (i.e. sequentially consistent) memory model. This makes the task of reasoning about concurrent programs even more challenging. The GPS framework, recently developed by Turon et al.[22], has made a step forward towards tackling this challenge. By integrating ghost states, per-location protocols and separation logic, GPS can successfully verify programs with release-acquire atomics. In this paper, we present a program logic, an enhancement of the GPS framework, that can support the verification of a bigger class of C11 programs, that is, programs with release-acquire atomics, relaxed atomics and release-acquire fences. Key elements of our proposed logic include two new types of assertions, a more expressive resource model and a set of newly-designed verification rules.