Market Penetration of Office Automation Equipment; Trends and Forecasts

This article identifies the major factors that are influencing the rate of market penetration of office automation equipment, presents trend data on national and industry investment in office automation and other equipment, extrapolates these trends to 1995, and compares several recent penetration forecasts against the trend data. The data show that office-intensive industries such as finance are rapidly increasing their capital/labor ratios, and that office automation equipment represents a significant portion of this total investment (about 40%). The relative importance of equipment costs in determining the penetration rate is likely to decline as training and implementation costs increase and become more visible, and as more managerial and professional tasks become automated. Investment trends offer a useful basis from which to analyze and assess market penetration forecasts. The plausibility of forecasts can be judged by comparing them against extrapolations of past investment behavior, particularly the ratio of investment in equipment of all kinds to industry product or GNP. A forecast that appears plausible on these grounds must be examined further to determine whether it accounts for the effects of other costs that are more difficult to measure, and for less quantifiable factors that, overall, could play a dominant role in shaping market penetration patterns and rates

Tourette’s disorder and other tic disorders in DSM-5: a comment

Classification of tic disorders will be revised in the forthcoming edition of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5). We do not support the suggestion to move tic disorders to “Anxiety and Obsessive–Compulsive Disorders”, if the section “Disorders Usually First Diagnosed in Infancy, Childhood, or Adolescence” is not retained. Other than that, most proposed changes of the criteria for tic disorders contain a number of welcome improvements, e.g., the more unified definition of tics including the removal of the term “stereotyped” and the better capture of the temporal pattern of tics (e.g., removal of the maximum 3 months criterion for a tic-free period in chronic tic disorders). But, unfortunately there are some inconsistencies in detail, e.g., the unification of diagnostic criteria for tic disorders had not been consistently pursued in transient tic disorder. In sum, the proposed DSM-5 criteria could be seen as an important step forward particularly in clinical routine. However, continued research is needed to justify the existing and proposed classification of tic disorders as well as to better clarify what other changes should be made in the DSM-5 and beyond

European clinical guidelines for Tourette Syndrome and other tic disorders

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Evaluation of 2.1µm DFB lasers for space applications

This paper presents the results obtained in the frame of an ESA-funded project called “Screening and Preevaluation of Shortwave Infrared Laser Diode for Space Application” with the objective of verifying the maturity of state of the art SWIR DFB lasers at 2.1µm to be used for space applications (mainly based on the occultation measurement principle and spectroscopy). The paper focus on the functional and environmental evaluation test plan. It includes high precision characterization, mechanical test (vibration and SRS shocks), thermal cycling, gamma and proton radiation tests, life test and some details of the Destructive Physical Analysis performed. The electro-optical characterization includes measurements of the tuning capabilities of the laser both by current and by temperature, the wavelength stability and the optical power versus laser current

The problem of repulsive quark interactions - Lattice versus mean field models

We calculate the 2nd and 4th order quark number susceptibilities at zero baryochemical potential, using a PNJL approach and an approach which includes, in a single model, quark and hadronic degrees of freedom. We observe that the susceptibilities are very sensitive to possible quark-quark vector interactions. Compared to lattice data our results suggest that above $T_c$ any mean field type of repulsive vector interaction can be excluded from model calculations. Below $T_c$ our results show only very weak sensitivity on the strength of the quark and hadronic vector interaction. The best description of lattice data around $T_c$ is obtained for a case of coexistence of hadronic and quark degrees of freedom.Comment: 5 pages, 4 figure, version accepted by PL

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

Iran has experienced a drastic increase in water scarcity in the last decades. The main driver has been the substantial unsustainable water consumption of the agricultural sector. This study quantifies the spatiotemporal dynamics of Iran’s hydrometeorological water availability, land cover, and vegetation growth and evaluates their interrelations with a special focus on agricultural vegetation developments. It analyzes globally available reanalysis climate data and satellite time series data and products, allowing a country-wide investigation of recent 20+ years at detailed spatial and temporal scales. The results reveal a wide-spread agricultural expansion (27,000 km$^2$) and a significant cultivation intensification (48,000 km$^2$). At the same time, we observe a substantial decline in total water storage that is not represented by a decrease of meteorological water input, confirming an unsustainable use of groundwater mainly for agricultural irrigation. As consequence of water scarcity, we identify agricultural areas with a loss or reduction of vegetation growth (10,000 km$^2$), especially in irrigated agricultural areas under (hyper-)arid conditions. In Iran’s natural biomes, the results show declining trends in vegetation growth and land cover degradation from sparse vegetation to barren land in 40,000 km$^2$, mainly along the western plains and foothills of the Zagros Mountains, and at the same time wide-spread greening trends, particularly in regions of higher altitudes. Overall, the findings provide detailed insights in vegetation-related causes and consequences of Iran’s anthropogenic drought and can support sustainable management plans for Iran or other semi-arid regions worldwide, often facing similar conditions

Metabolic profiling of diabetic cats in remission

Background: The majority of diabetic cats in remission have abnormal glucose tolerance, and approximately one third relapse within 1 year. Greater understanding of the metabolic characteristics of diabetic cats in remission, and predictors of relapse is required to effectively monitor and manage these cats. Objectives: To identify and compare differences in plasma metabolites between diabetic cats in remission and healthy control cats using a metabolomics approach. Secondly, to assess whether identified metabolites are predictors of diabetic relapse. Animals: Twenty cats in diabetic remission for a median of 101 days, and 22 healthy matched control cats. Methods: Cats were admitted to a clinic, and casual blood glucose was recorded. After a 24 h fast, blood glucose concentration was measured, then a blood sample was taken for metabolomic (GCMS and LCMS) analyses. Three hours later, a simplified intravenous glucose tolerance test (1 g glucose/kg) was performed. Cats were monitored for diabetes relapse for at least 9 months (270 days) after baseline testing. Results: Most cats in remission continued to display impaired glucose tolerance. Concentrations of 16 identified metabolites differed (P ≤ 0.05) between remission and control cats: 10 amino acids and stearic acid (all lower in remission cats), and glucose, glycine, xylitol, urea and carnitine (all higher in remission cats). Moderately close correlations were found between these 16 metabolites and variables assessing glycaemic responses (most |r| = 0.31 to 0.69). Five cats in remission relapsed during the study period. No metabolite was identified as a predictor of relapse. Conclusion and clinical importance: This study shows that cats in diabetic remission have abnormal metabolism

Application of SAR time-series and deep learning for estimating landslide occurence time

The time series of normalized difference vegetation index (NDVI) and interferometric coherence extracted from optical and Synthetic Aperture Radar (SAR) images, respectively, have strong responses to sudden landslide failures in vegetated regions, which is expressed by a sudden increase or decrease in the values of NDVI and coherence. Compared with optical sensors, SAR sensors are not affected by cloud and daylight conditions and can detect the occurrence time of failure in near real-time. The purpose of this paper is to automatically determine the time of failure occurrence using time series coherence values. We propose, based on some existing anomaly detection algorithms, a deep neural network-based anomaly detection strategy that combines supervised and unsupervised learning without a priori knowledge about failure time. Our experiment using July 21, 2020 Shaziba landslide in China shows that in comparison to widely used unsupervised methodology, the use of our algorithm leads to a more accurate detection of the timing of the landslide failure

QGP Susceptibilities from PNJL Model

An improved version of the PNJL model is used to calculate various thermodynamical quantities, {\it viz.}, quark number susceptibility, isospin susceptibility, specific heat, speed of sound and conformal measure. Comparison with Lattice data is found to be encouraging.Comment: 4 pages, 2 figures, poster presented at Quark Matter'0