How automated image analysis techniques help scientists in species identification and classification?

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification incre­ased over the last two decades. Automation of data classification is primarily focussed on images while incorporating and analysing image data has recently become easier due to developments in computational technology. Research ef­forts on identification of species include specimens’ image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, mainly for categorising and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies. (Folia Morphol 2018; 77, 2: 179–193

The Impact of Health Information Technology on Hospital Productivity

Health information technology (IT) has been championed as a tool that can transform health care delivery. We estimate the parameters of a value-added hospital production function correcting for endogenous input choices to assess the private returns hospitals earn from health IT. Despite high marginal products, the total benefits from expanded IT adoption are modest. Over the span of our data, health IT inputs increased by more than 210% and contributed about 6% to the increase in value-added. Not-for-profits invested more heavily and differently in IT. Finally, we find no compelling evidence of labor complementarities or network externalities from competitors’ IT investment

Is affect experiencing therapeutic in major depressive disorder? Examining associations between affect experiencing and changes to the alliance and outcome in intensive short-term dynamic psychotherapy.

Affect experiencing (AE), defined as the facilitation of client in-session bodily arousal and visceral experiencing of affect, is a distinct theoretical process presumed to contribute to therapeutic improvement. This study examined the role of AE in the treatment of major depressive disorder by exploring its association to client distress and therapeutic alliance on a session-by-session basis. A case series design was used to conduct an intensive analysis of the treatment process of 4 clients who received time-limited intensive short-term dynamic psychotherapy, 2 of whom were considered "recovered" and 2 who showed "no change" based upon posttreatment outcomes. Consistent with our hypothesis, we found that cross-correlations between AE and client distress discriminated between "recovered" and "no change" clients. In "recovered" clients, there was evidence that higher in-session peak affect experience was associated with reduced distress 7 days later. The results did not provide consistent evidence for a reverse effect, showing that lower distress during the preceding week predicted higher AE in that session. Finally, there was evidence that AE is an in-session activity that can promote the strengthening of the therapeutic alliance. These collective findings suggest that AE is an important treatment process that contributes to alliance formation and psychotherapeutic improvement. Clinical implications include further evidence that psychodynamic therapists can utilize AE as an active change ingredient for depression

Survey of Infections Transmissible Between Baboons and Humans, Cape Town, South Africa

Baboons on South Africa’s Cape Peninsula come in frequent contact with humans. To determine potential health risks for both species, we screened 27 baboons from 5 troops for 10 infections. Most (56%) baboons had antibodies reactive or cross-reactive to human viruses. Spatial overlap between these species poses low but potential health risks

An aggregator-based-strategy to minimize the cost of energy consumption by optimal utilization of energy resources in an apartment building

© 2019 IEEE. Buildings and transport consume two thirds of the total global energy. It is desirable to maximize the use of renewable generation in these sectors, and to optimize the use of that energy by managing diverse sources and loads. This is particularly challenging in high-density residential premises where the space for such infrastructure is limited, and storage can have significant impact on energy utilization and demand. In this paper, we have proposed an aggregator-based-strategy (ABS) to optimally utilize the available energy resources and storage in an apartment building with twenty households, each having an electric vehicle (EV), and an aggregated solar photovoltaic (PV) energy and stationary battery storage (BS) system. The strategy is flexible and can be applied to any building with EVs, solar PV and BS to minimize the cost of energy consumption without compromising the flexibility of energy usage or travel requirements. The model also accounts for the battery capacity degradation and its associated cost to make it more realistic. The model is evaluated using real data and the results show that the strategy not only reduces the cost of energy consumption but also reduces the amount of energy drawn from the grid significantly

Broadband optical supercontinuum generation in a long cavity fibre laser

We describe optical supercontinuum generation in an actively mode-locked fibre ring laser using a pulsed mode-locking technique. Recirculation of a section of the continuum facilitated spectral broadening

Evaluating local anthropogenic impact on remote Arctic monitoring stations: a case study at Summit, Greenland

International audienceSummit, Greenland is a remote Arctic research station allowing for field measurements at the highest point of the Greenland Ice Sheet. Due to the current reliance on diesel generators for electricity at Summit, unavoidable local emissions are a potential contamination threat to the measurement of combustion-related species in the air and snow. The effect of fossil-fuel combustion on particulate elemental carbon (EC) is assessed by a combination of ambient measurements (~1 km from the main camp), a series of snow pits (up to 20 km from Summit Camp), and Gaussian plume modeling. Ambient measurements indicate that the air directly downwind of the research station generators experiences particulate absorption coefficient (closely related to EC) values that are up to a factor of 200 higher than the summer 2006 non-camp-impacted ambient average. Local anthropogenic influence on snow EC content is also evident. The average EC concentration in 1-m snow pits in the "clean air" sector of Summit Camp are a factor of 1.8?2.4 higher than in snow pits located 10 km and 20 km to the north ("downwind") and south ("upwind") of the research site. Gaussian plume modeling performed using meteorological data from years 2003?2006 suggests a strong angular dependence of anthropogenic impact, with highest risk to the northwest of Summit Camp and lowest to the southeast. Along a transect to the southeast (5 degree angle bin), the modeled frequency of significant camp contribution to atmospheric EC (i.e. camp-produced EC>2006 summer average EC) at a distance of 0.5 km, 10 km, and 20 km is 1%, 0.2%, and 0.05%, respectively. According to both the snow pit and model results, a distance exceeding 10 km towards the southeast is expected to minimize risk of contamination. These results also suggest that other remote Arctic monitoring stations powered by local fuel combustion may need to account for local air and snow contamination in field sampling design and data interpretation