S and D Wave Mixing in High TcT_c Superconductors

For a tight binding model with nearest neighbour attraction and a small orthorhombic distortion, we find a phase diagram for the gap at zero temperature which includes three distinct regions as a function of filling. In the first, the gap is a mixture of mainly $d$-wave with a smaller extended $s$-wave part. This is followed by a region in which there is a rapid increase in the $s$-wave part accompanied by a rapid increase in relative phase between $s$ and $d$ from 0 to $\pi$. Finally, there is a region of dominant $s$ with a mixture of $d$ and zero phase. In the mixed region with a finite phase, the $s$-wave part of the gap can show a sudden increase with decreasing temperature accompanied with a rapid increase in phase which shows many of the characteristics measured in the angular resolved photoemission experiments of Ma {\em et al.} in $\rm Bi_2Sr_2CaCu_2O_8$Comment: 12 pages, RevTeX 3.0, 3 PostScript figures uuencoded and compresse

Binary choice models for external auditors decisions in Asian banks

Summarization: The present study investigates the efficiency of four classification techniques, namely discriminant analysis, logit analysis, UTADIS multicriteria decision aid, and nearest neighbours, in the development of classification models that could assist auditors during the examination of Asian commercial banks. To develop the auditing models and examine their classification ability, the dataset is split into two distinct samples. The training sample consists of 1,701 unqualified financial statements and 146 ones that received a qualified opinion over the period 1996–2001. The models are tested in a holdout sample of 527 unqualified financial statements and 52 ones that received a qualified opinion over the period 2002–2004. The results show that the developed auditing models can discriminate between financial statements that should receive qualified opinions from the ones that should receive unqualified opinions with an out-of-sample accuracy around 60%. The highest classification accuracy is achieved by UTADIS, followed by logit analysis, nearest neighbours and discriminant analysis. Both financial variables and the environment in which banks operate appear to be important factors.Presented on: Operational Research, An International Journa

Material-specific gap function in the high-temperature superconductors

We present theoretical arguments and experimental support for the idea that high-Tc superconductivity can occur with s-wave, d-wave, or mixed-wave pairing in the context of a magnetic mechanism. The size and shape of the gap is different for different materials. The theoretical arguments are based on the t-J model as derived from the Hubbard model so that it necessarily includes three-site terms. We argue that this should be the basic minimal model for high-Tc systems. We analyze this model starting with the dilute limit which can be solved exactly, passing then to the Cooper problem which is numerically tractable, then ending with a mean field approach. It is found that the relative stability of s-wave and d-wave depends on the size and the shape of the Fermi surface. We identify three striking trends. First, materials with large next-nearest-neighbor hopping (such as YBa(2)Cu(3)O(7-x)) are nearly pure d-wave, whereas nearest-neighbor materials (such as La(2-x)Sr(x)CuO(4)) tend to be more s-wave-like. Second, low hole doping materials tend to be pure d-wave, but high hole doping leads to s-wave. Finally, the optimum hole doping level increases as the next-nearest-neighbor hopping increases. We examine the experimental evidence and find support for this idea that gap function in the high-temperature superconductors is material-specific.Comment: 20 pages; requires revtex.sty v3.0, epsf.sty; includes 6 EPS figures; Postscript version also available at http://lifshitz.physics.wisc.edu/www/koltenbah/papers/gapfunc2.ps . This version contains an extensive amount of new work including theoretical background, an additional mean field treatment with new figures, and a more thorough experimental surve

Management Accountant's Role and Functions in the Enterprise Resource Planning Environment - Author's Own Research into Enterprises in Poland

This article seeks to answer whether the implementation of an ERP system has an effect on the management accountant's tasks and functions, especially in the field of performance measurement and internal reporting. The ERP impacts on the controller's role in the organization will be evaluated using field studies on six enterprises owned by multinational corporations. The question that should be asked here is whether controller's functions and tasks will also be unaffected.Celem badania jest próba odpowiedzi na pytanie czy zastosowanie zintegrowanego systemu informatycznego w przedsiębiorstwie zmienia zadania i funkcje specjalisty do spraw rachunkowości zarządczej. Na podstawie studium przypadku sześciu przedsiębiorstw będących częścią koncernów międzynarodowych zostaje dokonana ocena wpływu zastosowania ERP na rolę kontrolera w organizacji. Autor odpowiada również na pytanie czy w funkcjach i zadaniach kontrolera nie zaobserwowane zostaną zmiany w związku z implementacją ERP

Joule-assisted silicidation for short-channel silicon nanowire devices

We report on a technique enabling electrical control of the contact silicidation process in silicon nanowire devices. Undoped silicon nanowires were contacted by pairs of nickel electrodes and each contact was selectively silicided by means of the Joule effect. By a realtime monitoring of the nanowire electrical resistance during the contact silicidation process we were able to fabricate nickel-silicide/silicon/nickel- silicide devices with controlled silicon channel length down to 8 nm.Comment: 6 pages, 4 figure

Multifunctional Devices and Logic Gates With Undoped Silicon Nanowires

We report on the electronic transport properties of multiple-gate devices fabricated from undoped silicon nanowires. Understanding and control of the relevant transport mechanisms was achieved by means of local electrostatic gating and temperature dependent measurements. The roles of the source/drain contacts and of the silicon channel could be independently evaluated and tuned. Wrap gates surrounding the silicide-silicon contact interfaces were proved to be effective in inducing a full suppression of the contact Schottky barriers, thereby enabling carrier injection down to liquid-helium temperature. By independently tuning the effective Schottky barrier heights, a variety of reconfigurable device functionalities could be obtained. In particular, the same nanowire device could be configured to work as a Schottky barrier transistor, a Schottky diode or a p-n diode with tunable polarities. This versatility was eventually exploited to realize a NAND logic gate with gain well above one.Comment: 6 pages, 5 figure

Interplay among critical temperature, hole content, and pressure in the cuprate superconductors

Within a BCS-type mean-field approach to the extended Hubbard model, a nontrivial dependence of T_c on the hole content per unit CuO_2 is recovered, in good agreement with the celebrated non-monotonic universal behaviour at normal pressure. Evaluation of T_c at higher pressures is then made possible by the introduction of an explicit dependence of the tight-binding band and of the carrier concentration on pressure P. Comparison with the known experimental data for underdoped Bi2212 allows to single out an `intrinsic' contribution to d T_c / d P from that due to the carrier concentration, and provides a remarkable estimate of the dependence of the inter-site coupling strength on the lattice scale.Comment: REVTeX 8 pages, including 5 embedded PostScript figures; other required macros included; to be published in Phys. Rev. B (vol. 54

Wearables, smartphones, and artificial intelligence for digital phenotyping and health

Ubiquitous progress in wearable sensing and mobile computing technologies, alongside growing diversity in sensor modalities, has created new pathways for the collection of health and well-being data outside of laboratory settings, in a longitudinal fashion. Wearable and mobile devices have the potential to provide low-cost, objective measures of physical activity, clinically relevant data for patient assessment, and scalable behavior monitoring in large populations. These data can be used in both interventional and observational studies to derive insights regarding the links between behavior, health. and disease, as well as to advance the personalization and effectiveness of commercial wellness applications. Today, over 400,000 participants have had their behavior tracked prospectively using accelerometers for epidemiological studies across the globe. Traditionally, epidemiologists and clinicians have relied upon self-report measures of physical activity and sleep which, while valuable in the absence of alternatives, are subject to bias and often provide partial, incomplete information Physical behavior data extracted from wearable devices are being used to derive sensor-assessed, objective measures of physical behaviors, overcoming the limitations of self-report with the aim of relating these to clinical endpoints and eventually applying the findings to preventive and predictive medicine. Moreover, the application of artificial intelligence (AI), sensor fusion, and signal processing to wearable sensor data has led to improved human activity recognition and behavioral phenotyping. Here, we review the state of the art in wearable and mobile sensing technology in epidemiology and clinical medicine and discuss how AI is changing the field

Sequence multi-task learning to forecast mental wellbeing from sparse self-reported data

Smartphones have started to be used as self reporting tools for mental health state as they accompany individuals during their days and can therefore gather temporally fine grained data. However, the analysis of self reported mood data offers challenges related to non-homogeneity of mood assessment among individuals due to the complexity of the feeling and the reporting scales, as well as the noise and sparseness of the reports when collected in the wild. In this paper, we propose a new end-to-end ML model inspired by video frame prediction and machine translation, that forecasts future sequences of mood from previous self-reported moods collected in the real world using mobile devices. Contrary to traditional time series forecasting algorithms, our multi-task encoder-decoder recurrent neural network learns patterns from different users, allowing and improving the prediction for users with limited number of self-reports. Unlike traditional feature-based machine learning algorithms, the encoder-decoder architecture enables to forecast a sequence of future moods rather than one single step. Meanwhile, multi-task learning exploits some unique characteristics of the data (mood is bi-dimensional), achieving better results than when training single-task networks or other classifiers. Our experiments using a real-world dataset of 33, 000 user-weeks revealed that (i) 3 weeks of sparsely reported mood is the optimal number to accurately forecast mood, (ii) multi-task learning models both dimensions of mood –valence and arousal– with higher accuracy than separate or traditional ML models, and (iii) mood variability, personality traits and day of the week play a key role in the performance of our model. We believe this work provides psychologists and developers of future mobile mental health applications with a ready-to-use and effective tool for early diagnosis of mental health issues at scale.This work was supported by the Embiricos Trust Scholarship of Jesus College Cambridge, EPSRC through Grants DTP (EP/N509620/1) and UBHAVE (EP/I032673/1), and Nokia Bell Labs through the Centre of Mobile, Wearable Systems and Augmented Intelligence

Characterization and Weathering of the Building Materials of Sanctuaries in the Archaeological Site of Dion, Greece

The sanctuaries of Demeter and Asklepios are part of the Dion archaeological site that sits among the eastern foothills of Mount Olympus. The main building materials are limestones and conglomerates. Sandstones, marbles, and ceramic plinths were also used. The materials consist mainly of calcite and/or dolomite, whereas the deteriorated surfaces contain also secondary and recrystallized calcite and dolomite, gypsum, various inorganic compounds, fluoroapatite, microorganisms and other organic compounds. Cracks and holes were observed in various parts of the stones. The influence of specific weathering agents and factors to the behavior of the materials was examined. The particular environmental conditions in Dion combine increased moisture and rain fall, insolation and great temperature differences, abundance of intensive surface and underground water bodies in the surrounding area, an area full of plants and trees, therefore, they can cause extensive chemical, biological and mechanical decay of the monuments. The following physical characteristics of the building materials have been studied: bulk density, open porosity, pore size distribution, water absorption and desorption, capillary absorption and desorption. The chemical composition of bulk precipitation, surface and underground water was investigated. The salts presence and crystallization was examined. The influence of the water presence to the behavior of the materials was examined by in situ IR thermometer measurements. Temperature values increased from the lower to the upper parts of the building stones and they significantly depend on the orientation of the walls. The results indicate the existence of water in the bulk of the materials due to capillary penetration. The existence of water in the bulk of the materials due to capillary penetration, the cycles of wet-dry conditions, correlated with the intensive surface and underground water presence in the whole surrounding area, lead to partial dissolution-recrystallization of the carbonate material and loss of the structural cohesion and the surface stability