•We focus on business model innovation for demand response services in Finland.•We identify drivers and business model innovation behaviours of firms.•The identified behaviours do not neatly fall in ...the niche-regime dichotomy.•To overcome binary thinking we suggest adopting a morphological box.•Multi-sector interaction creates opportunities for business model innovation.
Demand response (DR) is an innovation emerging at the intersection of the energy and information and communications technology sectors. This paper aims to investigate the drivers of—and differences in—business model innovation (BMI) behaviours of firms operating in these two interacting industries. Results from 22 semi-structured interviews with representatives of Finnish DR companies show that external drivers of BMI include regulation, competition, and the demise of the telecom industry following the fall of Nokia. Whereas technology start-ups and companies from adjacent industries are motivated by entrepreneurial opportunities, incumbent energy companies are driven by the threat of losing their existing customers and need to increase efficiency. The BMI behaviours observed do not fall neatly into the often-used dichotomous categories of niche/new entrant and regime/incumbent, as firms show behaviours from both extremes. To overcome this binary thinking, we propose a morphological box model that represents the extreme states of firm BMI while allowing for flexibility.
We utilized citizen scientist photographs of subauroral emissions in the upper atmosphere and identified a repeatable sequence of proton aurora and subauroral red (SAR) arc during substorms. The ...sequence started with a pair of green diffuse emissions and a red arc that drifted equatorward during the substorm expansion phase. Simultaneous spectrograph and satellite observations showed that they were subauroral proton aurora, where ion precipitation created secondary electrons that illuminated aurora in green and red colors. The ray structures in the red arc also indicated existence of low‐energy electron precipitation. The green diffuse aurora then decayed but the red arc (SAR arc) continued to move equatorward during the substorm recovery phase. This sequence suggests that the SAR arc was first generated by secondary electrons associated with ion precipitation and may then transition to heat flux or Joule heating. Proton aurora provides observational evidence that ion injection to the inner magnetosphere is the energy source for the initiation of the SAR arc.
Plain Language Summary
Photographs that were taken by citizen scientists at Strathmore (Canada), Orimattila (Finland) and Ikaalinen (Finland) revealed peculiar green bands and blobs and red arcs in the night sky equatorward of the auroral oval. Those are different from STEVE (Strong Thermal Emission Velocity Enhancement) due to the lack of the purple/mauve arc and green picket fence. Using concurrent scientific instruments, we identified that those are a type of proton aurora that is illuminated by electrons induced by proton precipitation from space. The proton aurora transitions to a stable auroral red (SAR) arc. A series of photographs suggests that the SAR arc is initiated by proton precipitation, which has been suggested but never been demonstrated previously. The citizen scientist photographs played a critical role in unveiling the interaction between the proton aurora and SAR arc.
Key Points
Citizen scientist photographs revealed a peculiar evolution of subauroral emission during substorms
Initial red and green emissions were identified as proton aurora by secondary electrons
The transition from proton aurora to a SAR arc was found. Proton aurora gives evidence of proton injection as initiation of the SAR arc
Background
Musculoskeletal pain at several sites (multisite pain) is more common than single‐site pain. Little is known on its effects on disability pension (DP) retirement.
Methods
A nationally ...representative sample comprised 4071 Finns in the workforce aged 30 to 63. Data (questionnaire, interview, clinical examination) were gathered in 2000–2001 and linked with national DP registers for 2000–2011. Pain during the preceding month in 18 locations was combined into four sites (neck, upper limbs, low back, lower limbs). Hazard ratios (HR) of DP were estimated by Cox regression.
Results
The HR of any DP (n = 477) was 1.6 (95% confidence interval 1.2–2.1) for one, 2.5 (1.9–3.3) for two, 3.1 (2.3–4.3) for three and 5.6 (4.0–7.8) for four pain sites, when adjusted for age and gender. When additionally adjusted for clinically assessed chronic diseases, the HRs varied from 1.4 (1.0–1.8) to 3.5 (2.5–4.9), respectively. When further adjusted for physical and psychosocial workload, education, body mass index, smoking, exercise and sleep disorders, the HRs were 1.3 (0.9–1.7), 1.6 (1.2–2.2), 1.8 (1.3–2.5) and 2.5 (1.8–3.6). The number of pain sites was especially strong in predicting DPs due to musculoskeletal diseases (HRs in the full model; 3.1 to 4.3), but it also predicted DPs due to other somatic diseases (respective HRs 1.3 to 2.3); pain in all four sites was also predictive of DPs due to mental disorders (full model HR 2.2).
Conclusions
The number of pain sites independently predicted DP retirement. Employees with multisite pain may need specific support to maintain their work ability.
The predictions of two road dust suspension emission models were compared with the on-site mobile measurements of suspension emission factors. Such a quantitative comparison has not previously been ...reported in the reviewed literature. The models used were the Nordic collaboration model NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and the Swedish–Finnish FORE model (Forecasting Of Road dust Emissions). These models describe particulate matter generated by the wear of road surface due to traction control methods and processes that control the suspension of road dust particles into the air. An experimental measurement campaign was conducted using a mobile laboratory called SNIFFER, along two selected road segments in central Helsinki in 2007 and 2008. The suspended PM10 concentration was measured behind the left rear tyre and the street background PM10 concentration in front of the van. Both models reproduced the measured seasonal variation of suspension emission factors fairly well during both years at both measurement sites. However, both models substantially under-predicted the measured emission values. The article illustrates the challenges in conducting road suspension measurements in densely trafficked urban conditions, and the numerous requirements for input data that are needed for accurately applying road suspension emission models.
We present an overview of the modelling of particle number concentrations (PNCs) in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008. Novel emission ...inventories of particle numbers have been compiled both on urban and European scales. We used atmospheric dispersion modelling for PNCs in the five target cities and on a European scale, and evaluated the predicted results against available measured concentrations. In all the target cities, the concentrations of particle numbers (PNs) were mostly influenced by the emissions originating from local vehicular traffic. The influence of shipping and harbours was also significant for Helsinki, Oslo, Rotterdam, and Athens, but not for London. The influence of the aviation emissions in Athens was also notable. The regional background concentrations were clearly lower than the contributions originating from urban sources in Helsinki, Oslo, and Athens. The regional background was also lower than urban contributions in traffic environments in London, but higher or approximately equal to urban contributions in Rotterdam. It was numerically evaluated that the influence of coagulation and dry deposition on the predicted PNCs was substantial for the urban background in Oslo. The predicted and measured annual average PNCs in four cities agreed within approximately ≤ 26 % (measured as fractional biases), except for one traffic station in London. This study indicates that it is feasible to model PNCs in major cities within a reasonable accuracy, although major challenges remain in the evaluation of both the emissions and atmospheric transformation of PNCs.
A mathematical model is presented for the determination of human exposure to ambient air pollution in an urban area; the model is a refined version of a previously developed mathematical model EXPAND ...(EXposure model for Particulate matter And Nitrogen oxiDes). The model combines predicted concentrations, information on people's activities and location of the population to evaluate the spatial and temporal variation of average exposure of the urban population to ambient air pollution in different microenvironments. The revisions of the modelling system containing the EXPAND model include improvements of the associated urban emission and dispersion modelling system, an improved treatment of the time use of population, and better treatment for the infiltration coefficients from outdoor to indoor air. The revised model version can also be used for estimating intake fractions for various pollutants, source categories and population subgroups. We present numerical results on annual spatial concentration, time activity and population exposures to PM2.5 in the Helsinki Metropolitan Area and Helsinki for 2008 and 2009, respectively. Approximately 60% of the total exposure occurred at home, 17% at work, 4% in traffic and 19% in other microenvironments in the Helsinki Metropolitan Area. The population exposure originating from the long-range transported background concentrations was responsible for a major fraction, 86%, of the total exposure in Helsinki. The largest local contributors were vehicular emissions (12%) and shipping (2%).
Ospemifene is a non-estrogen agent that exerts tissue-specific estrogen agonistic and weak antagonistic effects (i. e., is a selective estrogen receptor modulator SERM). The effects of various ...once-daily oral doses of ospemifene on bone are examined across 3 studies for 4 or 52 weeks after surgery in the ovariectomized (OVX) rat model of postmenopausal bone loss. Ospemifene treatment reduced the loss of bone mineral content and density observed in untreated OVX rats, significantly increased distal femur bone mineral content at 51 weeks at 25 mg/kg dose compared with untreated OVX rats (p<0.01), and significantly increased trabecular bone mineral density of the distal femur and proximal tibia with 1, 5, or 25 mg/kg doses after 52 weeks. Ospemifene 5 and 25 mg/kg preserved distal femur trabecular structure; trabecular number was significantly increased, whereas trabecular separation and eroded surface values were significantly decreased (all p<0.01). Structural changes associated with ospemifene were accompanied by increased mechanical strength of femurs and 4th lumbar vertebra compared with untreated OVX rats. Ospemifene 10 mg/kg prevented OVX-induced bone loss; trabecular bone volume of distal femurs was increased after 4 weeks. Further, histomorphometric measures revealed decreased bone resorption after 4 weeks of ospemifene treatment, with effects similar to other SERMs (raloxifene and droloxifene). Ospemifene 3 and 10 mg/kg significantly inhibited OVX-induced increases in osteoclast number, and doses ≥0.3 mg/kg dose-dependently reversed the OVX-induced increase in the double-labeled volume:bone volume ratio. These results demonstrate antiresorptive, selective agonist effects of ospemifene on bone that appear similar to raloxifene in this in vivo animal model of estrogen deficiency.
Previous literature suggests that better cognitive ability and insight are associated with greater lifetime risk of suicide attempts in schizophrenia, counter to the direction of association in the ...general population. However, the conjoint association between distinct cognitive domains, insight, and suicidality has not been assessed.
In a cross-sectional study, 162 adults with schizophrenia or schizoaffective disorder completed cognitive testing via the MATRICS battery, symptom and cognitive insight assessments, along with the Columbia Suicide Severity Rating Scale. We then contrasted participants based on history of suicidality by cognitive domains and insight measures and conducted multivariate analyses.
Although a history of any passive ideation was not associated with cognitive ability or insight, verbal learning was positively associated with a greater history of suicidal attempt and prior ideation with a plan and intent. Higher cognitive insight, and the self-reflectiveness subscale insight, was also associated with history of passive or active suicidal ideation. Cognitive insight and cognitive ability were independent from each other, and there were no moderating influences of insight on the effect of cognitive ability on suicide related history. Exploratory analyses revealed that history of planned attempts were associated with greater verbal learning, whereas histories of aborted attempts were associated with poorer reasoning and problem-solving.
Although cross-sectional and retrospective, this study provides support that greater cognitive ability, specifically verbal learning, along with self-reflectiveness, may confer elevated risk for more severe suicidal ideation and behavior in an independent fashion. Interestingly, poorer problem-solving was associated with aborted suicide attempts.
Ospemifene is a tissue-selective estrogen agonist/antagonist that was recently approved for the treatment of dyspareunia associated with vulvar and vaginal atrophy, which occurs in up to ...approximately 50% of postmenopausal women. The current analyses were conducted to determine whether ospemifene exhibits estrogenic activity in the mammary glands of ovariectomized rats and to compare potential estrogenic activity with selective estrogen receptor modulators (tamoxifen, raloxifene, and toremifene). Three separate studies with differing durations (6, 9, and 28 days) were conducted using similar procedures in ovariectomized Sprague-Dawley rats. Estradiol treatment and sham-treated ovariectomized rats were used as positive and negative controls, respectively. Cell proliferation was examined using labeled 5-bromo-2-deoxyuridine; cytoplasmic prolactin was characterized with antibody staining. The morphology of the mammary gland was studied by histological staining of sections from the right fourth mammary glands, and the excised gland from the left side was used for counting the lobulus number. Neither ospemifene nor selective estrogen receptor modulators substantially induced 5-bromo-2-deoxyuridine staining, altered the morphology of the mammary glands, or changed prolactin immunostaining in ovariectomized rats compared with the ovariectomized controls. With the exception of toremifene, the selective estrogen receptor modulators did not cause a substantial induction in mammary gland lobuli. Estradiol had effects opposite to those of the selective estrogen receptor modulators in these studies. Ospemifene exhibited no substantial estrogenic activity in the mammary gland of ovariectomized rats. Activity in the mammary gland of ovariectomized rats with ospemifene was comparable to raloxifene and tamoxifen.
We have slightly refined, evaluated and tested a mathematical model for predicting the vehicular suspension emissions of PM₁₀. The model describes particulate matter generated by the wear of road ...pavement, traction sand, and the processes that control the suspension of road dust particles into the air. However, the model does not address the emissions from the wear of vehicle components. The performance of this suspension emission model has been evaluated in combination with the street canyon dispersion model OSPM. We used data from a measurement campaign that was conducted in the street canyon Runeberg Street in Helsinki from 8 January to 2 May, 2004. The model reproduced fairly well the seasonal variation of the PM₁₀ concentrations, also during the time periods, when studded tyres and anti-skid treatments were commonly in use. For instance, the index of agreement (IA) was 0.83 for the time series of the hourly predicted and observed concentrations of PM₁₀. The predictions of the model were found to be sensitive to precipitation and street traction sanding. The main uncertainties in the predictions are probably caused by (i) the cleaning processes of the streets, which are currently not included in the model, (ii) the uncertainties in the estimation of the sanding days, and (iii) the uncertainties in the evaluation of precipitation. This study provides more confidence that this model could potentially be a valuable tool of assessment to evaluate and forecast the suspension PM₁₀ emissions worldwide. However, a further evaluation of the model is needed against other datasets in various vehicle fleet, speed and climatic conditions.