Selecting cultivars with greater biomass results in higher yields and greater carbon sequestration. Storage of atmospheric carbon in the plant/soil pool contributes not only to food security but also to mitigating climate change and other agroecological benefits. The objective of this study was to determine: (1) grain, residue, and root biomass yields; (2) harvest indexes; (3) residue-to-product ratio; (4) root-to-shoot ratio; (5) biomass carbon and nitrogen contents; and (6) C:N ratios for two new and two old winter wheat cultivars. The greatest yield difference was found between old Srpanjka (the lowest) and new Kraljica (the highest) cultivar where grain, residue, root, and total biomass yield was higher by 38%, 91%, 71%, and 64%, respectively. Total biomass was composed of 40–47% grain, 10–11% roots, 32–36% stems + leaves, 9–11% chaff, and 1–2% spindle. The range of HI was 0.45–0.53, RPR 0.91–1.25, and R:S ratio 0.12–0.13. For all cultivars, positive carbon and negative nitrogen balance within the plant pool was determined. Still, root biomass and rhizodeposition carbon remain open questions for a better understanding of agroecosystems’ C dynamics.

Intraorbital and transorbital injuries are included in the group of head injuries with low frequency. In particular, such injuries rarely result in infectious processes in the brain parenchyma. This case presents a case where a 57-year-old man reported to the neurosurgery department that he had sustained an injury to the conjunctiva of the upper eyelid a month earlier. The patient was injured by a tree branch, which he removed on his own initiative. After persistent eye abduction palsy, an MRI was performed, which showed a compressive mass in the frontal lobe of the brain. A surgical procedure was indicated, which found a piece of twig 3 mm long inside the abscess. Surgical intervention and antibiotic therapy led to the complete recovery of the patient.

Stochastic structures with semi-controlled nodes were generated in the software Rhinoceros 7/Grasshopper using the Voronoi tessellation method, which divides a given volume into Voronoi cells. The structures were tested in Ansys software to obtain von Mises stresses and required forces. The results differ for the same seed number in the same volume but for different seed positions. For this reason, the distribution of seed points directly affects their mechanical properties.

Digital computers have been getting exponentially faster for decades, but huge challenges exist today. Transistor scaling, described by Moore's law, has been slowing down over the last few years, ending the era of fully predictable performance improvements. Furthermore, the data-centric computing demands fueled by machine learning applications are rapidly growing, and current computing systems -- even with the historical rate of improvements driven by Moore's law -- cannot keep up with these enormous computational demands. Some are turning to analogue in-memory computing as a solution, where specialised systems operating on physical principles accelerate specific tasks. We explore how emerging nonvolatile memories can be used to implement such systems tailored for machine learning. In particular, we discuss how memristive crossbar arrays can accelerate key linear algebra operations used in neural networks, what technological challenges remain, and how they can be overcome.

A test of CP invariance in Higgs boson production via vector-boson fusion has been performed in the H→γγ channel using 139  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV collected by the ATLAS detector at the LHC. The optimal observable method is used to probe the CP structure of interactions between the Higgs boson and electroweak gauge bosons, as described by an effective field theory. No sign of CP violation is observed in the data. Constraints are set on the parameters describing the strength of the CP-odd component in the coupling between the Higgs boson and the electroweak gauge bosons in two effective field theory bases: d[over ˜] in the HISZ basis and c_{HW[over ˜]} in the Warsaw basis. The results presented are the most stringent constraints on CP violation in the coupling between Higgs and weak bosons. The 95% C.L. constraint on d[over ˜] is derived for the first time and the 95% C.L. constraint on c_{HW[over ˜]} has been improved by a factor of 5 compared to the previous measurement.

Os Portais da Transparência (TPs) são uma forma de o cidadão acompanhar as informações sobre as ações do governo e entender como são utilizados os recursos provenientes da arrecadação de impostos. No entanto, existem diversos instrumentos que indicam requisitos legais e boas práticas para implementação de TPs, dificultando a tarefa de avaliar a completude de um TP. O objetivo deste trabalho é propor uma ferramenta computacional para apoiar tal avaliação. Para tanto, foram analisados guias de boas práticas e leis que indicam os requisitos necessários para a construção de BTs, a fim de apresentar um guia unificado que permita o processo de avaliação da completude de tais requisitos. Avaliamos este guia por meio de dois estudos: (i) pela avaliação de três portais de diferentes prefeituras; e (ii) pela realização de avaliação empírica do guia, por meio de entrevistas com profissionais usuários do BT de Niterói. Implementamos uma ferramenta web, pois nosso guia é composto por 268 itens (requisitos para avaliação da completude). Pudemos observar em nossa análise quais itens são bem atendidos pelo guia e pela ferramenta e quais ainda precisam ser melhorados. Um importante trabalho futuro é evoluir a ferramenta para permitir a incorporação de novos instrumentos.

Group recommender systems (GRSs) identify items to recommend to a group of people by aggregating group members’ individual preferences into a group profile and selecting the items that have the largest score in the group profile. The GRS predicts that these recommendations would be chosen by the group by assuming that the group is applying the same preference aggregation strategy as the one adopted by the GRS. However, predicting the choice of a group is more complex since the GRS is not aware of the exact preference aggregation strategy that is going to be used by the group. To this end, the aim of this article is to validate the research hypothesis that, by using a machine learning approach and a dataset of observed group choices, it is possible to predict a group’s final choice better than by using a standard preference aggregation strategy. Inspired by the Decision Scheme theory, which first tried to address the group choice prediction problem, we search for a group profile definition that, in conjunction with a machine learning model, can be used to accurately predict a group choice. Moreover, to cope with the data scarcity problem, we propose two data augmentation methods, which add synthetic group profiles to the training data, and we hypothesize that they can further improve the choice prediction accuracy. We validate our research hypotheses by using a dataset containing 282 participants organized in 79 groups. The experiments indicate that the proposed method outperforms baseline aggregation strategies when used for group choice prediction. The method we propose is robust with the presence of missing preference data and achieves a performance superior to what humans can achieve on the group choice prediction task. Finally, the proposed data augmentation method can also improve the prediction accuracy. Our approach can be exploited in novel GRSs to identify the items that the group is likely to choose and to help groups to make even better and fairer choices.

Carbohydrate sulfotransferases (CHST) catalyse the biosynthesis of proteoglycans that enable physical interactions and signalling between different neighbouring cells in physiological and pathological states. The study aim was to provide an overview of emerging diagnostic and prognostic applications of CHST. PubMed database search was conducted using the keywords “carbohydrate sulfotransferase” together with appropriate inclusion and exclusion criteria, whereby 41 publications were selected. Additionally, 40 records on CHST genetic and biochemical properties were hand-picked from UniProt, GeneCards, InterPro, and neXtProt databases. Carbohydrate sulfotransferases have been applied mainly in diagnostics of connective tissue disorders, cancer and inflammations. The lack of CHST activity was found in congenital connective tissue disorders while CHST overexpression was detected in different malignancies. Mutations of CHST3 gene cause skeletal dysplasia, chondrodysplasia, and autosomal recessive multiple joint dislocations while increased tissue expression of CHST11, CHST12 and CHST15 is an unfavourable prognostic factor in ovarian cancer, glioblastoma and pancreatic cancer, respectively. Recently, CHST11 and CHST15 overexpression in the vascular smooth muscle cells was linked to the severe lung pathology in COVID-19 patients. Promising CHST diagnostic and prognostic applications have been described but larger clinical studies and robust analytical procedures are required for the more reliable diagnostic performance estimations.

Abdominal actinomycosis remains an uncommon condition that mimics a wide range of intra-abdominal conditions ranging from acute inflammatory pathologies such as appendicitis to colonic or gynecological malignancies. Any abdominal organ can be affected. Preoperative diagnosis is often difficult and radiological imaging is unlikely to provide a definitive diagnosis. Surgical resection is often required in combination with long-term high-dose antibiotic therapy.

Spirodiclofen is characterized by a relatively slow acaricidal action against adult females of the two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae), with reduction of their fecundity (eggs laid/female) and fertility (eggs hatched/female). Exposure of pre-ovipositing T. urticae females to the acaricide may affect population growth, considering that a high reproduction of young females is crucial in the population biology of this colonizing species. Effects of spirodiclofen on life-history traits and population parameters of T. urticae were evaluated in demographic bioassay using the age-stage two-sex life table, constructed in fecundity-based and fertility-based variants. The acaricide was applied against pre-ovipositing females in a series of nine concentrations, starting from the recommended field rate (96 mg/l). The treatments with concentrations ranging from 12 - 96 mg/l significantly reduced fecundity and longevity, while 27 - 40% of females didn’t lay eggs. Exposure was lethal to 2 - 21% of the females, of whom a large majority didn’t lay eggs. A considerable part of surviving females also failed to lay eggs within the first four post-treatment days (when around 50% of all eggs in the control were laid) i.e., they were sterilized by the acaricide. At the same time, the percentage of dead females rose to 17 - 55%, mainly due to the mortality of sterilized females. The three highest concentrations (24 – 96 mg/l) significantly reduced the net reproductive rate (R0), intrinsic rate of increase (r) and finite rate of increase (λ), by 49-72%, 20-34%, and 4-6%, respectively, compared to the control. This reduction was mainly the result of sterilization and high mortality of treated females, in combination with reduced fecundity and longevity of reproductive ones. Application of the fertility-based life table showed significant decrease of r and λ (by 23-40%, and 4-7%, respectively, compared to the control), in the treatments with the three highest concentrations. The short-lived transovarial toxic effect observed in the fertility-based life table was not sufficient to cause a significant reduction in population parameters, compared to those acquired by the fecundity-based life table.

In the field of science, human rights and environmental protection are multidisciplinary fields. Hence different approaches to their interaction. In the context of the historical development of human rights, the right to a healthy environment belongs to the third generation of human rights. Due to the increase in industrialization around the world and the use of technologies which main feature is the easy availability and low cost of raw materials and processes, a number of global environmental problems have appeared (ozone depletion, global warming, climate change, etc.) which required a global response. The previous approaches (Stockholm Conference, etc.) were not enough, a new concept was needed that prevents the emergence of problems. A new concept, called sustainable development, implies economic development without permanent impact on the environment. Through the principle of sustainable development, the last UN concept for environmental protection and improvement of society in all segments was formulated, called Agenda 2030. BiH is a signatory to the agenda, but main driver of progress in the field of environmental protection and human rights is BiH’s aspiration to join the EU. One of the key meeting points of human rights and environmental protection should be the rights of activists for environmental protection, resolving their legal status through a law that will recognize their importance. The EU is specifically working on this, so it is expected that BiH will also make progress in the field of better status of activists for environmental protection, through the process of joining EU.

No abstract available.

This paper researches the decisions of the Council of Ministers of Bosnia and Herzegovina as general sub-laws and compares them with regulations of governments on other levels of government in Bosnia and Herzegovina. The comparison of the decisions of the Council of Ministers is carried out with the regulations of the Government of the Federation and the Government of Sarajevo Canton, with the intention to determine that decisions of the Council of Ministers have in essence the same scope and subject of regulating as the aforementioned government regulations, placing emphasis on the constitutional distribution of competencies between state, entities and cantons. The original research has determined that the Council of Ministers carries out the majority of legislative activities with their decisions, but rulebooks and instructions also appear as sub-laws, which isn’t the case on federal and cantonal levels, where rulebooks and instructions are exclusively adopted by administrative bodies, although administrative bodies on the level of Bosnia and Herzegovina also adopt these types of legislation. It has been determined that most decisions, rulebooks and instructions of the Council of Ministers, as well as regulations of governments are adopted for the purpose of executing the law, therefore as classical sub-laws, although different examples also appear. Finally, an amendment to the law is proposed in the sense that the Council of Ministers adopts regulations as sub-laws, with the cessation of adoption of rulebooks and instructions, which would be more appropriate from the aspect of our administrative law and bring about more order and would systematise this area.

Obtaining versions of deep neural networks that are both highly-accurate and highly-sparse is one of the main challenges in the area of model compression, and several high-performance pruning techniques have been investigated by the community. Yet, much less is known about the interaction between sparsity and the standard stochastic optimization techniques used for training sparse networks, and most existing work uses standard dense schedules and hyperparameters for training sparse networks. In this work, we examine the impact of high sparsity on model training using the standard computer vision and natural language processing sparsity benchmarks. We begin by showing that using standard dense training recipes for sparse training is suboptimal, and results in under-training. We provide new approaches for mitigating this issue for both sparse pre-training of vision models (e.g. ResNet50/ImageNet) and sparse fine-tuning of language models (e.g. BERT/GLUE), achieving state-of-the-art results in both settings in the high-sparsity regime, and providing detailed analyses for the difficulty of sparse training in both scenarios. Our work sets a new threshold in terms of the accuracies that can be achieved under high sparsity, and should inspire further research into improving sparse model training, to reach higher accuracies under high sparsity, but also to do so efficiently.