Congenital anomalies from a physics perspective. The key role of "manufacturing" volatility

Genetic and environmental factors are traditionally seen as the sole causes of congenital anomalies. In this paper we introduce a third possible cause, namely random "manufacturing" discrepancies with respect to ``design'' values. A clear way to demonstrate the existence of this component is to ``shut'' the two others and to see whether or not there is remaining variability. Perfect clones raised under well controlled laboratory conditions fulfill the conditions for such a test. Carried out for four different species, the test reveals a variability remainder of the order of 10%-20% in terms of coefficient of variation. As an example, the CV of the volume of E.coli bacteria immediately after binary fission is of the order of 10%. In short, ``manufacturing'' discrepancies occur randomly, even when no harmful mutation or environmental factors are involved. Not surprisingly, there is a strong connection between congenital defects and infant mortality. In the wake of birth there is a gradual elimination of defective units and this screening accounts for the post-natal fall of infant mortality. Apart from this trend, post-natal death rates also have humps and peaks associated with various inabilities and defects.\qL In short, infant mortality rates convert the case-by-case and mostly qualitative problem of congenital malformations into a global quantitative effect which, so to say, summarizes and registers what goes wrong in the embryonic phase. Based on the natural assumption that for simple organisms (e.g. rotifers) the manufacturing processes are shorter than for more complex organisms (e.g. mammals), fewer congenital anomalies are expected. Somehow, this feature should be visible on the infant mortality rate. How this conjecture can be tested is outlined in our conclusion.Comment: 43 pages, 9 figure

Cascading hazards in the aftermath of Australia's 2019/2020 black summer wildfires

Following an unprecedented drought, Australia's 2019/2020 “Black Summer” fire season caused severe damage, gravely impacting both humans and ecosystems, and increasing susceptibility to other hazards. Heavy precipitation in early 2020 led to flooding and runoff that entrained ash and soil in burned areas, increasing sediment concentration in rivers, and reducing water quality. We exemplify this hazard cascade in a catchment in New South Wales by mapping burn severity, flood, and rainfall recurrence; estimating changes in soil erosion; and comparing them with river turbidity data. We show that following the extreme drought and wildfires, even moderate rain and floods led to undue increases in soil erosion and reductions in water quality. While natural risk analysis and planning commonly focuses on a single hazard, we emphasize the need to consider the entire hazard cascade, and highlight the impacts of ongoing climate change beyond its direct effect on wildfires.DFG, 251036843, GRK 2043: Naturgefahren und Risiken in einer Welt im Wande

Spatio-temporal climate variability and snow resource changes in Finland

Abstract In northern regions such as Finland, snowpack represents a major water resource for aquatic and terrestrial ecosystems and different human uses, and snowmelt usually controls peak annual river discharge. To understand potential impacts of climate change, this thesis explored the effects of changes in surface air temperature (SAT) and precipitation patterns on snowpack accumulation and snowmelt processes in Finland. Two initial studies provided national and spatial pictures of long-term variability and changes in observed SAT and precipitation in Finland and their relationships with the atmospheric circulation patterns (ACPs) of the Northern Hemisphere (NH). On national scale, mean annual SAT and annual precipitation increased significantly in Finland during the past century. Seasonal analysis revealed increases in spring (MAM) and summer (JJA) SAT and in winter (DJF) and summer precipitation. SAT and precipitation were most significantly correlated with the Arctic Oscillation (AO), East Atlantic/West Russia (EA/WR), East Atlantic (EA) and Scandinavia (SCA) patterns. However, there were spatial differences within Finland as regards climate trends and relationships with ACPs. A study examining the dependence of snow resources on winter climate in Finland revealed a decline in snow water equivalent (SWE) and shortening of continuous snow cover duration (CSCD) in Finland during 1909-2008. This was mainly due to reductions in snowfall owing to winter warming and decreased precipitation in southern areas, but only to decreases in winter precipitation at higher latitudes. In southern Finland SWE and CSCD were associated with ACP affecting winter SAT (AO), and in central and northern parts with ACPs influencing winter precipitation (EA, EA/WR and AO). Analysis of snowmelt hydrology in Finland indicated that snowmelt flux has a much greater influence than rainfall on simulated peak snowpack outflow in Finland, which has decreased and shifted towards earlier in the year.Tiivistelmä Pohjoisilla alueilla kuten Suomessa lumi edustaa merkittävää vesivarantoa mikä vaikuttaa vesi- ja maaekosysteemeihin sekä yhdyskuntien vesienkäyttöön. Lisäksi lumen sulanta aiheuttaa suurimmat vuosittaiset tulvahuiput. Tämä väitöstutkimus keskittyy ilmanlämpötilan ja sadannan muutoksien aiheuttamiin vaikutuksiin lumen kertymisessä ja lumen sulannan prosesseissa Suomessa, jotta ilmaston muutoksen aiheuttamia mahdollisia muutoksia voidaan paremmin ymmärtää. Väitöskirjan kaksi tutkimusta antavat kansallisen ja spatiaalisesti kattavan kuvan pitkäaikaisvaihtelusta ja muutoksista ilmanlämpötilassa ja sadannassa Suomessa ja niiden yhteyden ilmastojärjestelmiin (ACP) pohjoisella pallonpuoliskolla. Kansallisella tasolla, vuosittainen keski-ilmanlämpötila ja vuosisadanta lisääntyivät merkittävästä Suomessa viimeisen vuosisadan aikana. Kausittainen analyysi paljasti kevät ja kesä ilmanlämpötilojen sekä talvi ja kesä-sadantojen lisääntyneen. Ilmanlämpötila ja sadanta korreloi merkittävimmin Arktisen (AO), Itä Atlantti/Länsi Venäjä (EA/WR), Itä-Atlantti (EA) ja Skandinaavisen (SCA) oskillaatioiden kanssa. Eri puolilla Suomea tuloksissa oli spatiaalista eroa liittyen ilmasto trendeihin ja yhteyksiin ilmakehän kiertoliikkeisiin. Tässä tutkimuksessa selvitettiin lisäksi lumivarojen riippuvuutta talviajan ilmastosta Suomessa. Vuosien 1909-2008 aineiston perusteella lumenvesiarvossa (SWE) havaittiin laskua sekä pysyvän lumipeitteen kestossa (CSCD) lyhenemistä. Etelässä tämä todettiin pääosin olevan seurausta talviajan lumisateiden vähentymisestä, jota vuorostaan selitti ilman lämpeneminen ja kokonaissademäärän pienentyminen. Pohjoisilla leveysasteilla ainoastaan talviaikaisen kokonaissademäärän pienentyminen selitti vähentyneitä lumivaroja. Tutkimuksessa Etelä-Suomen aineiston osalta tulokset SWE ja CSCD:ssa voitiin yhdistää muutoksiin talviseen SAT:hen (AO) vaikuttavissa ilmastojärjestelmissä (ACP). Keski- ja pohjoisosissa Suomea ilmastojärjestelmät (EA, EA/WR ja AO) vaikuttivat ainoastaan talviaikaiseen sadantaan. Aineiston perusteella voitiin myös todeta, että Suomessa kevätaikaisesta lumensulannasta johtuvaan valuntahuippuun vaikuttaa enemmän välitön lumen sulanta kuin sulannan aikana esiintynyt vesisade. Lumen sulannan huippuarvo havaittiin myös laskeneen sekä sen ajoittuminen aikaistuneen

Non-stationary peaks-over-threshold analysis of extreme precipitation events in Finland, 1961–2016

There is an urgent need to understand and predict how extreme precipitation events (EPEs) will change at high latitudes, both for local climate change adaptation plans and risk mitigation and as a potential proxy \u201canticipating\u201d the impact of climate change elsewhere in the world. This paper illustrates that a combination of non-stationary modelling approaches can be adopted to evaluate trends in EPEs under uncertainty. A large database of daily rainfall events from 281 sparsely distributed weather stations in Finland between 1961 and 2016 was analysed. Among the tested methods, Poisson distributions provided a powerful method to evaluate the impacts of multiple physical covariates, including temperature and atmospheric circulation patterns (ACPs), on the resulting trends. The analysis demonstrates that non-stationarity is statistically valid for the majority of observations, independently of their location in the country and the season of the year. However, subsampling can severely hinder the statistical validity of the trends, which can be easily confused with random noise and therefore complicate the decision-making processes regarding long-term planning. Scaling effects have a strong impact on the estimates of non-stationary parameters, as homogenizing the data in space and time reduces the statistical validity of the trends. Trends in EPE statistics (mean, 90 and 99% percentiles) and best-fitted Generalized Pareto parameters in the tails of the distributions appear to be stronger when approaching the Polar region (Lapland) than away from it, consistent with the Arctic amplification of climate change. ACPs are key covariates in physically explaining these trends. In particular, the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) can explain statistically significant increases in extreme precipitation in Lapland, Bothnian and South regions of Finland, particularly during summer and fall seasons

A case Report of Human T-cell lymphotropic Virus Type 1(HTLV1) Infected Virus with Similar Multiple Sclerosis Symptoms in a Non-endemic Area

Background & aim: Human lymphotropic retrovirus type 1( HTLV1) is the first known virus which could cause serious diseases such as adult leukemia- lymphoma T-cell lymphoma (ATL) and Tropical Spastic (TSP). On the other hand, due to the HTLV1 similarity symptoms in patients with multiple sclerosis symptoms in Khorasan as the region's endemic, knowledge and understanding of the virus and the disease is necessary in other areas as well. The aim of the present case report study was to investigate the HTLV1 infected virus with similar multiple sclerosis symptoms in a Non-endemic area. Case presentation: The patient in the present case report study was a 56 years old women which her illness was early diagnosed as MS (multiple sclerosis).  No sign of improvement in therapy period was observed. Therefore, due to limited symptoms in lower extremities and sphincter dysfunction, her serum and cerebrospinal fluid for the presence of antibodies anti HTLV1 was evaluated. The presence of Abs with clinical symptoms, cause diagnosis of the virus in the patient. Conclusion: This patient was referred with symptoms of progressive paraparesis spatic and at first her disease was mistakenly diagnosed as MS.  Due to lack of response to treatment and atypical clinical symptoms related to MS and Khorasan province after two years the patient was diagnosis as HTLV1. It is recommended to apply differential diagnosis of MS in specific geographic regions, such infection  as HTLV1 especially in endemic areas should be considered

An integrated FCM-FBWM approach to assess and manage the readiness for blockchain incorporation in the supply chain

Despite the initial hype surrounding blockchain applications in the supply chain, real-world implementation of this disruptive technology faces significant challenges. To manage these challenges and ensure a smooth implementation, supply chain organizations must perform various activities to acquire readiness. This paper proposes a readiness assessment and management approach for blockchain implementation in the supply chain. The proposed approach allows supply chain decision-makers to (1) identify the readiness-relevant activities for blockchain implementation, (2) model the causal relationships among the identified activities, (3) assess the activities’ contribution weights to the overall readiness, and (4) develop an effective readiness improvement plan by prioritizing those activities with the most impact on the overall readiness. Fuzzy cognitive maps (FCMs) are employed to model the causal relationships between the activities. The fuzzy best–worst​ method (FBWM) is adopted to establish the contribution weights of the activities to the supply chain's overall readiness. The FCM inference process is also used to incorporate feedback loops among the activities. The proposed approach is then illustrated through an empirical study. © 2021 Elsevier B.V

Basal ice formation in snow cover in Northern Finland between 1948 and 2016

Abstract Basal ice formation in the terrestrial snow cover is a common phenomenon in northern circumpolar areas, one having significant impacts on ecosystems, vegetation, animals and human activities. There is limited knowledge on the spatial and temporal occurrence of basal ice formation because of the sparse observation network and challenges involved in detecting formation events. We present a unique dataset on the annual extent of ice formation events in northern Finland between 1948 and 2016 based on reindeer herders’ descriptions of the cold season in their management reports. In extreme years, basal ice can form over wide geographical extents. In approximately half of the herding districts studied, it occurred more frequently in the period 1983–2016 than in the period 1948–1982. Furthermore, five out of seven of the most extensive basal ice formation events (90th percentile) occurred between 1991 and 2016. The most commonly reported processes related to ice formation were thaw or rain-on-snow events followed by freezing of the snow cover. Years with extensive basal ice formation were often characterized by above-average October–December air temperatures, air temperature variations around 0 °C and relatively high precipitation. However, basal ice did not occur during all warm and wet early winters, and formation events were generally weakly linked to the large-scale atmospheric teleconnections. Another risk factor for reindeer grazing associated with warm and rainy early winters is the growth of mycotoxin-producing molds below the snow. Approximately 24% of all reported mold formation events co-occurred with basal ice formation. The prevalence and frequency of basal ice formation events can be assessed based on our results. Our work contributes to understanding long-term fluctuations and changes in snow and ice conditions and the impacts of this variability in circumpolar areas

Modeling and Risk Mapping of Forest Fires using Remote Sensing and GIS (Case Study: Baghe-Shadi Protected Area, Yazd Province)

Baghe-shadi in Yazd province is one the forests which is reported to be an area with high rate fire occurrence. The aim of this study was to model and map the fire risk area using geographic information system and remote sensing. In this study Analytical Hierarchy Process (AHP) with human related factors (distance from road, distance from settlements, and distance from vegetation), climatic related factors (air temperature and rainfall), and physiographic related factors (elevation, slope, aspect) were selected. Vegetation cover was estimated using Landsat OLI Normalized Difference Vegetation Index (NDVI). Weights were determined from specialists through questionnaire. Weight of each factor, elevation, slope and aspect, temperature, precipitation, distance from roads, distance from settlements and vegetation cover was achieved through multiple criteria decision making model, then areas with five susceptible classes were determined using GIS. Results showed that vegetation related factor and human related factor with weights of 0.569 and 0.204 are the most important factors respectively. In order to assess the accuracy of developed model, fire susceptibility map of was compared with the previously fired area. Result of comparison showed very high and high risk areas are corresponding to the controls area. Receiver operating charasteristic (ROC) test confirmed the high level (0.88) of accuracy of presented model