314 research outputs found
CORPORATE GOVERNANCE CHALLENGES IN RELATION TO THE ESG REPORTING
Over the last decade, there has been an increasing emphasis on corporate social responsibility in business. The idea has evolved from CSR (Corporate Social Responsibility) to ESG Reporting (Environment, Social, Governance), with the latest trends developing towards a green transition. This genesis of development has been followed by corporate practice and legislation at European and national levels. Consequently, ESG and Green Transition guidelines have been incorporated into the liabilities and duties of the management and supervisory bodies of the company, resulting in a new view of the performance of these functions and their accountability. In this paper, the authors outline the basic postulates and roles of corporate governance bodies and their respective responsibilities for the implementation of ESG and the Green Transition. Sustainability as a value is highlighted in the EU and companies are committed to respecting human rights and reducing their impact on the planet. However, progress by companies (corporates) in integrating sustainability into their governance processes, in particular human rights and environmental due diligence, is still slow, and progress is visible with the drafting of the Corporate Sustainability Due Diligence Directive (CSDD) as a follow-up to the Directive 2014/95/EU (NFRD). The new rules are intended to provide companies with legal certainty and a level playing field. It should provide greater transparency for consumers and investors and should accelerate the green transition and protect human rights in Europe and beyond. These tasks are directly linked to the responsibilities of the authorities in society, who will have to respect these rules and be held accountable for failing to enforce them or for failing to achieve a transfer of capital to the green transition
Serological monitoring of ornitobacteriosis in broilers in South Banat district
Ornithobacterium rhinotracheale is a relatively recently discovered bacterium
and its role in the pathology of avian respiratory infections has not yet
been clarified. Since there was no data relating to the prevalence of this
infection in Serbia at the time of carrying out our investigations, we
decided to explore the prevalence of the infection in broilers and its
influence on clinical manifestations at the selected apizootiological area
with developed poultry industry. A total of 430 blood samples from 26 flocks
of broilers of different ages, from five municipalities were taken for
examination. The serum samples were tested by ELISA for the presence of
specific antibodies to the agent. Epizootiological investigation was carried
out based on the results obtained with serological testing and
epizootiological data, collected from the farms. The data were analyzed
statistically to identify association between the infection and manifestation
of clinical symptoms by Fisher’s exact test. Seropositive chickens were
detected in 16 out of 26 examined broiler flocks at the age of 3 to 56 days.
The percentage of seropositive samples per flock was 5-30%. The titer values
of specific antibodies ranged from 946 to 6886. Serological response to O.
rhinotracheale was evidenced in five flocks which had clinical symptoms in
the form of respiratory tract disorders or stunting. However, specific
antibodies against the agent were discovered in 11 flocks which did not show
clinical symptoms. Statistical analysis revealed no association between the
presence of infection and the appearance of clinical symptoms (p = 0.1213).
The results are in agreement with those of other authors who investigated the
prevalence of this infection and its manifestations in other countries. The
present investigation determined indirectly, serologically a presence of O.
rhinotracheale in the majority of examined broiler flocks (61,54%) and a
small average number of individual seropositive chickens per flock - 10 % of
all examined samples. Although O. rhinotracheale is wide-spread in intensive
broiler production in South Banat its presence does not always lead to
clinical manifestation of respiratory tract disorders. Seropositive chickens
are detected in the first week of life, which indicates the presence of
maternal antibodies. Presence of antibodies as the response of organism to
the natural infection is detected in chickens after four weeks of age
Analiza odabranih markera glioblastroma
Glioblastomas (GBM) represent one of the most aggressive types of diffuse glioma. Although they usually arise as primary brain tumors, in 10% of GBM cases, they develop from low-grade astrocytomas (secondary GBM). They express striking morphological heterogeneity, which is often encountered during a histopathological examination. Due to advances in molecular diagnostics, significant progress was made in understanding the pathogenesis of tumor growth and the development of personalized therapeutic protocols. The aim of this study was to evaluate the diagnostic, prognostic, and predictive properties of the selected markers -IDH1/2 (isocitrate-dehydrogenase 1 and 2) mutation and MGMT (O6-methylguanine-DNA methyltransferase) and CHI3L1 (Chitinase-3-like protein 1) methylation status of the promoter regions in a Serbian population of GBM patients. Patients operated on the Neurosurgery Clinic (The University Clinical Centre of Niš, Serbia) between 2013 and 2019 were included in this study. Sanger direct sequencing was used to detect the presence of IDH1/2 mutations in samples and conventional and Real-Time methylation-specific polymerase chain reaction methods for methylation status evaluation. Age, the extent of tumor resection, and type of adjuvant chemotherapy were recognized as independent prognostic factors in GBM patients. Furthermore, results suggested the superiority of adjuvant Temozolomide over adjuvant chemotherapy with a nitrosourea-based protocol (PCV and BCNU). IDH1 mutation was detected in 6.67% (3/45) of patients and was associated with more prolonged overall survival, younger age, and hypermethylation of the MGMT and CHI3L1 promoter. Semi-quantitative MSP approaches resulted in improved detection sensitivity of MGMT methylation status compared to the qualitative MSP method. Among IDH-wt homogenous cohort of GBM patients older than 50 years with complete/partial resection of the tumor, overall survival of patients harboring highly methylated MGMT was significantly longer in comparison with the unmethylated group. Complementary evaluation of CHI3L1 promoter methylation status potentially increases the prognostic value of the MGMT methylation status, which should be further investigated in more comprehensive research
Development for CO2 emissions reduction by the use of solar thermal collectors in the process of urban planning
Using RES is one of the most important characteristics of the sustainable and resilient development. Nowadays, need to minimize CO2 emissions is obligatory, especially in the sector of urban and architectural planning, since in Serbia approximately 50% of produced energy is spent in buildings. The CO2 emission, in urban structures, can and must be reduced at the different levels: building level, block, and city level. For the city of Kragujevac, based on urban parameters defined in General Urban Plan, typical urban block was chosen and typical building structure developed. Calculation were made, based on recommendations developed by the Ministry of mining and energy and Serbian regulations, for the energy needed for domestic hot water preparation. In this paper, the influences of architectural and urban parameters on the use of solar thermal collectors at the typical building and urban block level is investigated. Recommendations are prepared for principles of urban and architectural design in order to enable the use of collectors for domestic hot water preparation and in that way CO2 emission reduction. Developed methodology for the city of Kragujevac can be applied in defining design principles in whole the country and Balkans region, not only for the use of solar thermal collectors but also for the use of other RES
Possibilities for the use of geothermal energy in new residential buildings in Serbia, case study Urban Blocks in City of Kragujevac
Use of RES is an important element for achieving ambitious results for CO2 emission reduction in EU, emphasized and obligated by RES Directive, among other documents. In Serbia, as a candidate country and a signatory of Energy treaty, targets set by relevant documents reflect in benchmarks set by National Action Plan for Energy Efficiency, setting the level of reduction of energy consumption until 2018 for 9%, with more ambitious projections up to 2030. This calls for extensive research of possibilities for the use of renewable energy in buildings, its potentials and possible restrictions. Since the Directive states that low amount of energy required should be covered to a very significant extent by energy from renewable sources, including energy from renewable sources produced on-site or nearby, an investigation of possibilities for application of geothermal ground probes for a typical residential urban block in the city of Kragujevac is presented. This enables analysis of limitations imposed by legal and physical conditions: planning guidelines, type of ground, functional requests and infrastructural capacities. Typology of characteristic urban block layouts for residential buildings is generated, leading to projections of possible area covered with ground probes and calculations of relevant energy needed for heating, based on current regulations on energy efficiency in buildings. From these calculations, percentage of defined energy needs from possible geothermal ground probes is defined, enabling estimation of geothermal energy potential for new residential building blocks
Private and Reliable Neural Network Inference
Reliable neural networks (NNs) provide important inference-time reliability
guarantees such as fairness and robustness. Complementarily, privacy-preserving
NN inference protects the privacy of client data. So far these two emerging
areas have been largely disconnected, yet their combination will be
increasingly important. In this work, we present the first system which enables
privacy-preserving inference on reliable NNs. Our key idea is to design
efficient fully homomorphic encryption (FHE) counterparts for the core
algorithmic building blocks of randomized smoothing, a state-of-the-art
technique for obtaining reliable models. The lack of required control flow in
FHE makes this a demanding task, as na\"ive solutions lead to unacceptable
runtime. We employ these building blocks to enable privacy-preserving NN
inference with robustness and fairness guarantees in a system called Phoenix.
Experimentally, we demonstrate that Phoenix achieves its goals without
incurring prohibitive latencies. To our knowledge, this is the first work which
bridges the areas of client data privacy and reliability guarantees for NNs.Comment: In ACM Conference on Computer and Communications Security (CCS 2022
From Principle to Practice: Vertical Data Minimization for Machine Learning
Aiming to train and deploy predictive models, organizations collect large
amounts of detailed client data, risking the exposure of private information in
the event of a breach. To mitigate this, policymakers increasingly demand
compliance with the data minimization (DM) principle, restricting data
collection to only that data which is relevant and necessary for the task.
Despite regulatory pressure, the problem of deploying machine learning models
that obey DM has so far received little attention. In this work, we address
this challenge in a comprehensive manner. We propose a novel vertical DM (vDM)
workflow based on data generalization, which by design ensures that no
full-resolution client data is collected during training and deployment of
models, benefiting client privacy by reducing the attack surface in case of a
breach. We formalize and study the corresponding problem of finding
generalizations that both maximize data utility and minimize empirical privacy
risk, which we quantify by introducing a diverse set of policy-aligned
adversarial scenarios. Finally, we propose a range of baseline vDM algorithms,
as well as Privacy-aware Tree (PAT), an especially effective vDM algorithm that
outperforms all baselines across several settings. We plan to release our code
as a publicly available library, helping advance the standardization of DM for
machine learning. Overall, we believe our work can help lay the foundation for
further exploration and adoption of DM principles in real-world applications.Comment: Accepted at IEEE S&P 202
Influential Factors in the Loading of the Axial Bearing of the Slewing Platform Drive in Hydraulic Excavators
The paper contains the results of the analysis of factors that influence the loading of the axial bearing of the slewing platform drive mechanism in hydraulic excavators. The following influential factors are considered: the operations of the excavator manipulation tasks, the number of drives in the slewing platform mechanism, and the configuration of the excavator kinematic chain. The importance of the influence of these factors is assessed on the basis of the comparison between certain equivalent loads of the platform drive bearing with the diagrams of allowed load capacities of available bearings. The equivalent loads of the platform drive mechanism bearing are determined using the approach of static and dynamic excavator simulation in the programs developed on the basis of the defined mathematical models of the excavator. The equivalent loads are given with regard to the duration of the manipulation task and in the form of a spectrum of equivalent loads determined in the entire operating area of the excavator. The analysis is performed for three different configurations of the kinematic chain of a tracked hydraulic excavator with the mass of around 100000 kg
Certified Defenses: Why Tighter Relaxations May Hurt Training
Certified defenses based on convex relaxations are an established technique
for training provably robust models. The key component is the choice of
relaxation, varying from simple intervals to tight polyhedra. Paradoxically,
however, training with tighter relaxations can often lead to worse certified
robustness. The poor understanding of this paradox has forced recent
state-of-the-art certified defenses to focus on designing various heuristics in
order to mitigate its effects. In contrast, in this paper we study the
underlying causes and show that tightness alone may not be the determining
factor. Concretely, we identify two key properties of relaxations that impact
training dynamics: continuity and sensitivity. Our extensive experimental
evaluation demonstrates that these two factors, observed alongside tightness,
explain the drop in certified robustness for popular relaxations. Further, we
investigate the possibility of designing and training with relaxations that are
tight, continuous and not sensitive. We believe the insights of this work can
help drive the principled discovery of new and effective certified defense
mechanisms
DETERMINING THE IMPACTS OF FREIGHT TRANSPORT MODE COMBINATIONS ON AIR POLLUTION USING ARTIFICIAL NEURAL NETWORKS
Transport is one of the largest emitters of harmful substances that affect air quality. Each combination of freight transport modes has a different volume and at the same time has a differentiated negative impact on air quality. That is why the European Union has been making special efforts for many years to create and implement strategies aimed at improving air quality. The main goal of this paper is to present a methodology that enables quantification and analysis of the impact of each freight transport mode combination on air quality using feed-forward neural networks. The developed model uses the parameters of the EU member states in the period from 2000 to 2014. In addition to the scientific and practical contribution, the development of the model provides a good basis for the universal platform formation in order to create and develop strategies, i.e. measures to improve air quality on a global level
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