Different effect of mycorrhizal inoculation in direct and indirect reclamation of spoil banks

Spoil banks generated during coal mining are usually reclaimed by layering of fertile soil over original barren clay (co called indirect reclamation). This well-proven method is effective from the aspect of vegetation establishment and production, but it is very expensive. Direct reclamation of spoil bank clay promises much cheaper approach, yet its success is uncertain and the process might be rather long-term.This two-year field study aimed to assess the effect of application of commercially produced inoculum of arbuscular mycorrhizal fungi (AMF) Symbivit® on growth of two plant species commonly used for reclamation (Lotus corniculatus and Arrhenatherum elatius) sown on three different substrates: organic substrate (mixture of papermill waste, tree-bark and compost) and loess (both substrates typical for indirect reclamation) and original spoil bank clays (simulation of direct reclamation). On organic substrate and loess, A. elatius outcompeted the legume and established 100 % cover in all treatments. The effect of mycorrhizal inoculation was not observed. In contrast, on clay both species established successfully. The produced biomass and cover were, however, substantially lower compared to organic substrate and loess. In clay the positive effect of introduced AMF on plant was observed.Mycorrhizal inoculation was useful for supporting plant growth at direct reclamation. Direct reclamation in itself seems suitable for small-scale application, i.e. in patches where indirect reclamation is inconvenient or more diverse vegetation is required. Key words: arbuscular mycorrhizal fungi; inoculum; clay; papermill waste; loess; Arrhenatherum elatius; Lotus corniculatu

The Solar Cycle: A new prediction technique based on logarithmic values

A new prediction technique based on logarithmic values is proposed to predict the maximum amplitude (Rm) of a solar cycle from the preceding minimum aa geomagnetic index (aamin). The correlation between lnRm and lnaamin (r = 0.92) is slightly stronger than that between Rm and aamin (r = 0.90). From this method, cycle 24 is predicted to have a peak size of Rm (24) = 81.7(1\pm13.2%). If the suggested error in aa (3 nT) before 1957 is corrected, the correlation coefficient between Rm and aamin (r = 0.94) will be slightly higher, and the peak of cycle 24 is predicted much lower, Rm(24) = 52.5\pm13.1. Therefore, the prediction of Rm based on the relationship between Rm and aamin depends greatly on the accurate measurement of aa.Comment: 6 pages, 3 figures, Accepted for publication in Astrophysics & Space Scienc

Oxidative protein labeling in mass-spectrometry-based proteomics

Oxidation of proteins and peptides is a common phenomenon, and can be employed as a labeling technique for mass-spectrometry-based proteomics. Nonspecific oxidative labeling methods can modify almost any amino acid residue in a protein or only surface-exposed regions. Specific agents may label reactive functional groups in amino acids, primarily cysteine, methionine, tyrosine, and tryptophan. Nonspecific radical intermediates (reactive oxygen, nitrogen, or halogen species) can be produced by chemical, photochemical, electrochemical, or enzymatic methods. More targeted oxidation can be achieved by chemical reagents but also by direct electrochemical oxidation, which opens the way to instrumental labeling methods. Oxidative labeling of amino acids in the context of liquid chromatography(LC)–mass spectrometry (MS) based proteomics allows for differential LC separation, improved MS ionization, and label-specific fragmentation and detection. Oxidation of proteins can create new reactive groups which are useful for secondary, more conventional derivatization reactions with, e.g., fluorescent labels. This review summarizes reactions of oxidizing agents with peptides and proteins, the corresponding methodologies and instrumentation, and the major, innovative applications of oxidative protein labeling described in selected literature from the last decade

Landed property of the Cistercian houses of Bohemia 1142–1420

Praca dotyczy posiadłości ziemskich czeskich klasztorów cysterskich w średniowieczu, od ich początku do czasów wojen husyckich, które zupełnie zmieniły sytuację własności czeskich zakonów. Między 1142 a 1357 w królestwie Czech ufundowano dziesięć opactw białych mnichów. W tym kontekście nader ważne okazują się ramy czasowe powstawania indywidualnych domów klasztornych w relacji do głównych średniowiecznych przeobrażeń krajobrazowych (karczowanie) i działalności kultywacyjnej. W Czechach, proces ten, który znacznie zmienił krajobraz księstwa i późniejszego królestwa, nastąpił pomiędzy ostatnimi dziesięcioleciami XII a pierwszymi XIV w. Założenie najwcześniejszych opactw wyprzedziło Pozemková držba českých cisterciáckých klášterů 1142–1420 /Landed property of the Cistercian houses of Bohemia 1142–1420 15 ten wzrost aktywności, ale większość cysterskich klasztorów stanowiła, w taki czy inny sposób, jej integralny komponent. Tylko najpóźniej powstałe cenobium białych mnichów wyłoniło się po zakończeniu tego intensywnego procesu osiedlania się. Dwunastowieczne darowizny dla opactw cysterskich bez wątpienia nie pokrywały ekonomicznych potrzeb klasztorów. Wszystkie fundacje opierały się nie na gospodarstwach uprawianych pracą ręczną beneficjentów zakonu, ale na pobieraniu dochodów poszczególnych wsi. To dotyczyło nawet najwcześniejszych fundacji, które powstawały za życia Bernarda z Clairvaux. Przykład darowizn dla opactw jasno wskazuje, do jakiego stopnia zwyczaje i przyzwyczajenia kraju goszczącego formacje zakonu wpływały na materialne środki nowych fundacji. Zakonnicy cysterscy otrzymywali taką samą materialną pomoc jak inne kościelne instytucje w Czechach, a nie takie, jakimi cieszyły się zakony w Europie Zachodniej. W XIII w. nastąpił znaczny wzrost własności ziemskiej wszystkich klasztorów, większy niż ten z wcześniejszych i późniejszych epok. Choć rozwój poszczególnych klasztornych posiadłości ziemskich trwał aż do wojen husyckich, wszystkie regularne domy musiały poradzić sobie z kryzysem gospodarczym, który rozpoczął się na początku lat 40. XIV w., a szczyt osiągnął na początku kolejnego stulecia. W latach 20. XV w. większość klasztorów cysterskich Czech została podbita przez husytów i stanęła w płomieniach. Po sekularyzacji pozbawiono cystersów większości z ich własności ziemskich i dzierżaw.This is a paper on landed property of Bohemian monasteries of the Cistercian order in the Middle Ages, from their beginnings up to the epoch of the Hussite wars which completely changed the property situation of the Bohemian houses. Between 1142 and 1357, the kingdom of Bohemia saw the foundation of ten abbeys of the white monks. In view of the emergence and development of monastic landholdings, a major role apparently fell to the chronological range of establishment of individual houses in relation to the main phase of medieval landscape-assarting and -cultivation activities. In Bohemia, this process, which substantially changed the landscapes of the duchy and later kingdom, was situated between the last decades of the 12th and the fi rst decades of the 14th century. Foundations of the earliest houses of the Order preceded this upsurge of activities, but most of the Cistercian abbeys constituted, in one way or another, its integral component. Only the very latest house of the white monks emerged after the termination of this intensive settlement process, which, in the course of the “long 13th century”, covered the entire Bohemia. 12th-century donations to Cistercian abbeys show beyond all doubt that in terms of the property transferred to them, they fell short of complying with economic demands of the Order. All the foundations were based not on landholdings cultivated by manual labour of the monastery incumbents, but on the perception of revenues from singular villages. This related even to the earliest foundations of the Order which sprang up in the lifetime of Bernard of Clairvaux. The example of donations to the abbeys shows clearly to what extent the customs and habits of the land hosting the Order establishments infl uenced the material sustenance of the new foundations. Cistercian monks received the same kind of material support as other ecclesiastical institutions of Bohemia, not that enjoyed by the Order houses in western Europe. The 13th century saw a considerable growth of the extent of landed property of all monasteries, surpassing in its scale that of the earlier and later epochs. Though the expansion of particular monastic landholdings continued until the Hussite wars, all regular houses had to cope with an economic crisis beginning in the forties of 14th century, and climaxing at the beginning of 15th century. During the twenties of the 15th century, most of the Cistercian monasteries of Bohemia were conquered by the Hussites and went up in fl ames. The following secularization, acknowledged by king Sigismund mostly in 1420 and 1421, and confi rmed in writing in 1436–1437, deprived the Cistercians of most of their possessions, leasing them but tiny vestiges of their former landholdings

Discrimination of cycling patterns using accelerometric data and deep learning techniques

The monitoring of physical activities and recognition of motion disorders belong to important diagnostical tools in neurology and rehabilitation. The goal of the present paper is in the contribution to this topic by (1) analysis of accelerometric signals recorded by wearable sensors located at specific body positions and by (2) implementation of deep learning methods to classify signal features. This paper uses the general methodology to analysis of accelerometric signals acquired during cycling at different routes followed by the global positioning system. The experimental dataset includes 850 observations that were recorded by a mobile device in the spine area (L3 verterbra) for cycling routes with the different slope. The proposed methodology includes the use of deep learning convolutional neural networks with five layers applied to signal values transformed into the frequency domain without specification of any signal features. The accuracy of discrimination between different motion patterns for the uphill and downhill cycling and recognition of 4 classes associated with different route slopes was 96.6% with the loss criterion of 0.275 for sigmoidal activation functions. These results were compared with those evaluated for selected sets of features estimated for each observation and classified by the support vector machine, Bayesian methods, and the two-layer neural network. The best cross-validation error of 0.361 was achieved for the two-layer neural network model with the sigmoidal and softmax transfer functions. Our methodology suggests that deep learning neural networks are efficient in the assessment of motion activities for automated data processing and have a wide range of applications, including rehabilitation, early diagnosis of neurological problems, and possible use in engineering as well