Proper Configuration Research Articles

QoS Management for XR Traffic in 5G NR: A Multi-Layer System View and End-to-End Evaluation

Extended reality (XR) applications are gaining a lot of momentum in the industry and consumer market. XR applications are characterized by multiple simultaneous data flows with different Quality-of-Service (QoS) requirements, imposing the need for advanced QoS management in 5G networks. Compared to 4G, the 5G NR technology has been designed with enhanced QoS support, by introducing the concept of QoS flows and an additional layer for QoS handling. However, recent studies show that additional QoS enhancements are needed in 5G to support the massive adoption of XR services. 3GPP envisions to include some enhancements for XR traffic in 5G-Advanced. In this paper, we review the current 5G QoS framework and study potential design improvements to fulfill XR QoS requirements in future cellular networks. We study QoS control procedures for XR traffics at different layers of the 5G NR protocol stack, including the proper configuration of radio access and core networks. In particular, we analyze various architectures for handling the peculiarities of XR, such as time-constraint and multi-flow applications. Also, we present XR traffic adaptation mechanisms at the application layer, to properly adapt XR traffic statistics to the actual 5G radio environment, and QoS schedulers for the MAC layer, leading to cross-layer performance optimization between XR application and 5G radio access network. Finally, we provide a validation study and end-to-end evaluation of QoS control mechanisms by simulating realistic mixed traffic scenarios in a 5G NR system-level simulator based on ns-3.

RANCANG BANGUN PENGELOLAAN BANDWIDTH INTERNET MENGGUNAKAN METODE QUEUE TREE DENGAN ROUTER MIKROTIK DI PT XYZ

Basically, the use of internet activities in companies is very dense, causing various problems, among the problems encountered related to internet connection is bandwidth usage that has not been optimally regulated, so that no matter how much bandwidth capacity is available, it will not meet the needs of internet bandwidth usage if it is not managed properly. . In order for internet user bandwidth allocation to be distributed evenly, bandwidth management is needed to overcome the existing bandwidth limitations. Bandwidth management aims to find a solution so that all user computer devices get internet bandwidth allocation and can find out how to manage good bandwidth so that user devices get a fair or even distribution of bandwidth. The methodology for implementing bandwidth management with the queue tree method is to observe a running network system, identify problems, collect data, then design a configuration system. After going through the design process then carrying out the configuration stage, and if the configuration is successfully applied then proceed to the testing phase using several user computers assisted by using the wireshark application to find out incoming or received data packets, the next stage is monitoring using monitoring applications such as Torch Winbox, speedtest or wireshark and the final stage is evaluation or management such as configuration backups and so on. This research and testing also takes into account Quality of Services (QoS) parameters such as throughput, delay, jitter, and packet loss to find out in more detail the calculation of packet traffic that has been captured by the wireshark application. So that with good design, proper configuration, careful monitoring, an even, optimal bandwidth usage and quality internet connection is produced, so that the implementation of the queue tree method of bandwidth management provides an effective solution in managing bandwidth allocation.

Association of DDX5/p68 protein with the upstream erythroid enhancer element (EHS1) of the gene encoding the KLF1 transcription factor

EKLF/KLF1 is an essential transcription factor that plays a global role in erythroid transcriptional activation. Regulation of KLF1 is of interest, as it displays a highly restricted expression pattern, limited to erythroid cells and its progenitors. Here we use biochemical affinity purification to identify the DDX5/p68 protein as an activator of KLF1 by virtue of its interaction with the erythroid-specific DNAse hypersensitive site upstream enhancer element (EHS1). We further show that this protein associates with DEK and CTCF. We postulate that the range of interactions of DDX5/p68 with these and other proteins known to interact with this element render it part of the enhanseosome complex critical for optimal expression of KLF1 and enables the formation of a proper chromatin configuration at the Klf1 locus. These individual interactions provide quantitative contributions that, in sum, establish the high-level activity of the Klf1 promoter and suggest they can be selectively manipulated for clinical benefit.

Durable poly(binaphthyl-co-p-terphenyl piperidinium)-based anion exchange membranes with dual side chains

Building well-developed ion-conductive highways is highly desirable for anion exchange membranes (AEMs). Grafting side chain is a highly effective approach for constructing a well-defined phase-separated morphological structure and forming unblocked ion pathways in AEMs for fast ion transport. Fluorination of side chains can further enhance phase separation due to the superhydrophobic nature of fluorine groups. However, their electronic effect on the alkaline stability of side chains and membranes is rarely reported. Here, fluorine-containing and fluorine-free side chains are introduced into the polyaromatic backbone in proper configuration to investigate the impact of the fluorine terminal group on the stability of the side chains and membrane properties. The poly(binaphthyl-co-p-terphenyl piperidinium) AEM (QBNpTP) has the highest molecular weight and most dimensional stability due to its favorable backbone arrangement among ortho- and meta-terphenyl based AEMs. Importantly, by introducing both a fluorinated piperidinium side chain and a hexane chain into the p-terphenyl-based backbone, the prepared AEM (QBNpTP-QFC) presents an enhanced conductivity (150.6 mS cm−1) and a constrained swelling at 80 °C. The electronic effect of fluorinated side chains is contemplated by experiments and simulations. The results demonstrate that the presence of strong electro-withdrawing fluorine groups weakens the electronic cloud of adjacent C atoms, increasing OH− attack on the C atom and improving the stability of piperidinium cations. Hence QBNpTP-QFC possesses a robust alkaline stability at 80 °C (95.3% conductivity retention after testing in 2 M NaOH for 2160 h). An excellent peak power density of 1.44 W cm−2 and a remarkable durability at 80 °C (4.5% voltage loss after 100 h) can be observed.

Performance evaluation of Cuckoo filters as an enhancement tool for password cracking

Cyberthreats continue their expansion, becoming more and more complex and varied. However, credentials and passwords are still a critical point in security. Password cracking can be a powerful tool to fight against cyber criminals if used by cybersecurity professionals and red teams, for instance, to evaluate compliance with security policies or in forensic investigations. For particular systems, one crucial step in the password-cracking process is comparison or matchmaking between password-guess hashes and real hashes. We hypothesize that using newer data structures such as Cuckoo filters could optimize this process. Experimental results show that, with a proper configuration, this data structure is two orders of magnitude more efficient in terms of size/usage compared to other data structures while keeping a comparable performance in terms of time.

Highly sensitive resistance spectroscopy technique for online monitoring of biofilm growth on metallic surfaces

Online techniques for monitoring biofilm formation and evolution are limited, especially as regards its application in flowing water systems. This is chiefly due to the absence of efficient non-destructive and non-invasive sensing methods. In this study, a sensitive electrical resistance spectroscopy technique is developed to monitor non-invasively and in real time the growth of biofilms over metallic surfaces inside water flow systems. To this aim, Pseudomonas fluorescens strain is used for biofilm development lasting 72 h in a laboratory-scale test channel of orthogonal cross section. Biofilm development corresponds to a progressively increasing coverage of the metallic surface area up to full coverage and a progressively increasing thickness. Biofilm development is registered by continuous recording of electrical impedance signals (time series). Proper configuration and tuning of the electronics promote the resistive contribution to the signal whereas careful grounding diminishes electrical interferences and yields superb sensing sensitivity. An increase of relative electrical resistance of around 15% is noticed in 72 h flow experiments which is attributed to both an increase of metallic surface area coverage and an increase of biofilm thickness. An independent estimation of these quantities using imaging tools and microscopy analysis, indicates that full coverage of the metallic surface occurs after only 48 h of the flow experiment, whereas biofilm thickness increases gradually along the entire 72 h of the experiment. Cross-examination of electrical signals with biofilm characteristics (metallic surface coverage and biofilm thickness) reveals that, qualitatively speaking, electrical signals are rather more sensitive to metallic surface coverage than biofilm thickness.

Mathematical Model and Parameter Analysis of the Sintering Process for Ternary Cathode Materials

AbstractThe ternary cathode material LiNi0.8Co0.1Mn0.1O2 is widely used in lithium batteries, and the sintering process plays a crucial role in its production. Proper configuration of sintering kiln parameters directly affects the quality of LiNi0.8Co0.1Mn0.1O2. However, determining optimal working conditions through onsite trials is time‐consuming and expensive. A predictive model for the sintering furnace of ternary cathode material is developed. The predictive model incorporates chemical reactions, thermal conduction inside the saggars, and convective and radiative heat transfer within the furnace. It comprehensively analyzes the relationship between furnace temperature and material temperature. Radiative heat transfer within the furnace is calculated using the Monte Carlo method, and convective heat transfer properties on the surface of the saggars are obtained through computational fluid dynamics simulations. Heat transfer inside the saggars is resolved using the finite difference method. The model accounts for the effects of operational and structural parameters. Onsite experiments validate the accuracy of the model, with a simulation error of <±10% under typical working conditions. Leveraging this model, the effects of loading quantity, moving velocity, and saggar size on the sintering of ternary cathode materials are compared. Optimization recommendations are proposed to enhance production capacity.

AlexandrusPS: A User-Friendly Pipeline for the Automated Detection of Orthologous Gene Clusters and Subsequent Positive Selection Analysis.

The detection of adaptive selection in a system approach considering all protein-coding genes allows for the identification of mechanisms and pathways that enabled adaptation to different environments. Currently, available programs for the estimation of positive selection signals can be divided into two groups. They are either easy to apply but can analyze only one gene family at a time, restricting system analysis; or they can handle larger cohorts of gene families, but require considerable prerequisite data such as orthology associations, codon alignments, phylogenetic trees, and proper configuration files. All these steps require extensive computational expertise, restricting this endeavor to specialists. Here, we introduce AlexandrusPS, a high-throughput pipeline that overcomes technical challenges when conducting transcriptome-wide positive selection analyses on large sets of nucleotide and protein sequences. The pipeline streamlines 1) the execution of an accurate orthology prediction as a precondition for positive selection analysis, 2) preparing and organizing configuration files for CodeML, 3) performing positive selection analysis using CodeML, and 4) generating an output that is easy to interpret, including all maximum likelihood and log-likelihood test results. The only input needed from the user is the CDS and peptide FASTA files of proteins of interest. The pipeline is provided in a Docker image, requiring no program or module installation, enabling the application of the pipeline in any computing environment. AlexandrusPS and its documentation are available via GitHub (https://github.com/alejocn5/AlexandrusPS).

The role of chemical and solvent-based recycling within a sustainable circular economy for plastics

Chemical and solvent-based recycling of plastic waste may help overcome some of the challenges faced by predominantly applied mechanical recycling techniques. This study quantifies the environmental impacts of chemical and solvent-based recycling as a function of varying process parameters and product composition using life cycle assessment. Furthermore, potential benefits and impacts on a system level are determined. To that end, a high-resolution material flow analysis is conducted for the reference system of Switzerland, covering all main plastic types and applications. In a scenario for the year 2040, we employ environmentally beneficial mechanical recycling where possible and convey suitable remaining waste streams to chemical or solvent-based recycling processes. Applying chemical or solvent-based recycling as a complement to maximum mechanical recycling, instead of thermal treatment with energy recovery, may achieve a reduction in the climate change impact of the system ranging from less than 10 % to almost 40 %. For achieving high environmental benefits, proper process choice and configuration are crucial. Dissolution or depolymerization provide higher benefits relative to other chemical recycling processes, but can only treat certain waste streams and require prior sorting into plastic types. Pyrolysis and gasification appeared to only have the ability to achieve substantial benefits over incineration if their output products can substitute high-impact chemicals and provided that efficient heat transfer and recovery is warranted when implemented on a large scale. As industrial-scale plants for chemical or solvent-based plastic recycling are still lacking, the upscaling potential and the environmental benefits achievable in practice are highly uncertain today.

A newly developed blasting cut in tunnels; application of “combined method” in small to medium-sized tunnels

Drilling and blasting method have been widely used for driving tunnels in hard rock. When designing a blast operation especially in case of long tunnels, the primary objective of contractors is to ensure optimized blast parameters for achieving the most economical and time-saving technique of excavation. Choosing a proper blasting cut has a crucial role in the successfulness of the whole blast round in terms of quality, time and cost. The first aim of cut is to break and throw rocks and create a cavity for the upcoming production detonators. An attempt has been made here to test and develop an innovative cutting system for small to medium-scale tunnels where classical wedge cut is physically difficult to execute; what is called in this paper “combined or quasi-wedge method”. Proposed drilling and blasting patterns have been first put in computerized drilling machines and then tested in the tunnels located in Rishikesh-Karnaprayag Railway Project, Package 2, driven in sedimentary rock mass. After thorough investigation of trial-and-error blasts economically and technically, necessary changes have been made to guarantee optimization and find proper design configurations. In comparison to conventional parallel cut, the newly developed cut leads not only to the betterment of cycle time for excavation but also improvement of specific drilling and specific charge, the two main performance indicators of blast operations. Vibration, fragmentation, pull length, fly rock and profile quality, as pro-blast parameters, were also found highly satisfactory.

Sensitivity of Burned Area and Fire Radiative Power Predictions to Containment Efforts, Fuel Density, and Fuel Moisture Using WRF‐Fire

AbstractPredicting the evolution of burned area, smoke emissions, and energy release from wildfires is crucial to air quality forecasting and emergency response planning yet has long posed a significant scientific challenge. Here we compare predictions of burned area and fire radiative power from the coupled weather/fire‐spread model WRF‐Fire (Weather and Research Forecasting Tool with fire code), against simpler methods typically used in air quality forecasts. We choose the 2019 Williams Flats Fire as our test case due to a wealth of observations and ignite the fire on different days and under different configurations. Using a novel re‐gridding scheme, we compare WRF‐Fire's heat output to geostationary satellite data at 1‐hr temporal resolution. We also evaluate WRF‐Fire's time‐resolved burned area against high‐resolution imaging from the National Infrared Operations aircraft data. Results indicate that for this study, accounting for containment efforts in WRF‐Fire simulations makes the biggest difference in achieving accurate results for daily burned area predictions. When incorporating novel containment line inputs, fuel density increases, and fuel moisture observations into the model, the error in average daily burned area is 30% lower than persistence forecasting over a 5‐day forecast. Prescribed diurnal cycles and those resolved by WRF‐Fire simulations show a phase offset of at least an hour ahead of observations, likely indicating the need for dynamic fuel moisture schemes. This work shows that with proper configuration and input data, coupled weather/fire‐spread modeling has the potential to improve smoke emission forecasts.

Observation of the extracavity propagation of amplified bound-state soliton pulses emitted from a SWNT mode-locked fiber laser

We have experimentally investigated the extracavity propagation of amplified bound-state soliton pulses from a passively single-wall carbon nanotube mode-locked fiber laser. Under proper configuration of pump power and state of polarization, bound-state pulses exhibit a modulated optical spectrum. Except for the two main center wavelengths of 1557.3 and 1560.5 nm, additional five sidelobes centered at 1548.9, 1552.8, 1565.5, 1569.0 and 1573.1 nm are observed. Besides, the propagation after the extracavity erbium-doped fiber amplification is also investigated. It is demonstrated the significant change of the pulse separation is experimentally obtained when adjusting the extracavity PC before the autocorrelator, which is attributed to the coherent nonlinear soliton-soliton interaction. In addition, when different lengths of single-mode fiber after extracavity amplifier is removed or added, the significant change of the pulse separation is also observed, which matches well with the simulated evolution of pulse separation with respect to the SMF length. The pulse separation change of amplified bound soliton pulses is experimentally and theoretically investigated. These results provide further physical understanding of the generation and extracavity propagation of bound-state soliton pulses.

Knowledge management based on the dynamism of the character of students, who are members of teams implementing social projects

Education for social work requires students to perform many tasks, ensuring interdisciplinary preparation for this profession. The usefulness of social design and its didactic value should be seen in this context. Didactic projects, thanks to multi-tasking, stimulate students' activity, teach responsibility, moreover, they enable combining knowledge with action, and develop reflectiveness. The implementation of social projects requires cooperation of students in project teams. However, the efficiency of team cooperation is determined by the proper configuration of the individual characteristics of team members, in accordance with the assumptions of M. Mazur's (1999) psychocybernetic theory of character. In terms of this theory, a man with a specific dynamism of character has a better chance of effective cooperation when he cooperates with people of the same dynamism. These chances are greater because allied people have a greater sum of their powers (synergy effect), it is easier for them to take challenges together. The aim of that paper is to present the results of the conducted diagnostic research - questionnaire research, in the field of the character of students in psychocybernetic terms. In total, 19 students, who were registered for the implementation of didactic social projects, took part in the study. Based on the estimations of character parameters, the most favorable configuration of members of 3-person project teams was indicated. This procedure is part of the knowledge management process - as improving the education process in the field of dynamic, time-limited, temporary and team-implemented didactic projects, where the problem is sharing knowledge in order to achieve team effects (through a group), resulting in low effectiveness undertaken projects, low quality of results, etc. Research objective: researching the usefulness of knowledge in the field of individual, autonomous character traits of students for designing effective teams implementing didactic social projects.

A surrogate-assisted highly cooperative coevolutionary algorithm for hyperparameter optimization in deep convolutional neural networks

Hyperparameter optimization in convolutional neural networks (CNNs) plays a vital role in ensuring the effectiveness of the models. However, with the depth of the existing CNN expanding, this task becomes very challenging due to the high-dimensional and computationally expensive characteristics. Given these difficulties, this study proposes a surrogate-assisted highly cooperative hyperparameter optimization (SHCHO) algorithm for large-scale chain-styled CNNs. SHCHO tackles the original hyperparameter optimization problem by cooperatively optimizing its subproblems. Specifically, it first decomposes the whole CNN into several overlapping sub-CNNs, which conforms to the inherent overlapping interaction structure among hyperparameters and significantly reduces the search space. The resulting hyperparameter optimization subproblems on these sub-CNNs are then coevolved collaboratively and competitively, facilitating a proper hyperparameter configuration for the whole CNN. Besides, SHCHO also employs the computationally efficient surrogate technique to assist in each subproblem optimization. As a result, the expensive computational cost can be greatly reduced. Extensive experimental results on three widely-used image classification datasets indicate that SHCHO shows competitive performance when compared with several state-of-the-art algorithms in terms of both hyperparameter superiority and computational cost.

Dielectric elastomer actuator biased by magnetorheological elastomer with permanent magnet

Dielectric elastomer actuators have become one of the most important smart material transducers in recent times. One of the crucial aspects in this field is the application of bias to find the best operating conditions. The basic task is to find the proper bias configuration to obtain a wide range of displacements in the actuator. In the literature, various biases, such as mechanical springs, permanent magnets (PMs), or pneumatic springs, are studied. In our work, the magnetorheological elastomer (MRE) is applied to build a novel bias that ensures a wide range of displacement. Because of the softness and the compliant chemical structure, the MRE can be easily integrated with the dielectric elastomer actuator. The MRE as a bias for a dielectric elastomer actuator is verified in the series of experiments. Finally, the discussion on the advantages and disadvantages of the new bias type is performed.

Dynamic mode II fracture mechanism of rocks using a novel double-edge notched flattened Brazilian disc specimen in the split Hopkinson pressure bar tests

The dynamic mode I fracture behaviors of rocks have been extensively investigated during recent decades, while the dynamic mode II fracture mechanism of rocks and its comparison with dynamic mode I fracture are poorly understood. In this study, a novel double-edge notched flattened Brazilian disc (DNFBD) specimen is introduced for dynamic mode II fracture toughness tests of rocks in the split Hopkinson pressure bar (SHPB) tests. First, using the finite element method (FEM), the stress distribution of the DNFBD specimen is analyzed and the stress intensity factors (SIFs) and the T-stress at the crack tips are determined. Then, dynamic mode II fracture tests are conducted on sandstone using the DNFBD specimen with proper specimen geometry configuration. High-speed photography and digital image correlation (DIC) results show that the shear crack initiates from the notch tips and propagates along the shear ligament of the DNFBD specimen, which demonstrates the reliability of the DNFBD-SHPB method for dynamic mode II fracture tests of rocks. Experimental results show that the dynamic mode II fracture toughness KIIC of rocks generally increases with increasing loading rate, exhibiting significant loading-rate dependence. For comparative investigation, dynamic mode I fracture tests using the notched semi-circular bend (NSCB) specimen are conducted on the same rocks. The results indicate that the mode II fracture toughness KIIC values are always higher than the mode I fracture toughness KIC values of rocks over a wide range of loading rates. The microscopic fracture mechanism of sandstone is interpreted based on the thin section observations. Under quasi-static loading, trans-granular (TG) fractures are more popular in the mode II fracture tests, while inter-granular (IG) fractures dominate the failure of mode I fracture. However, with the increase of loading rate, TG fracture becomes increasingly prevalent in both the dynamic mode II fracture and the dynamic mode I fracture of rocks. The results of this study are of great significance for understanding the dynamic mode II fracture mechanism of rocks.

Impact analysis and detection of time-delay attacks in time-sensitive networking

Time-sensitive networking (TSN) will be widely used in automotive industry and industrial automation because it can provide deterministic transmission. Most of the TSN traffic shaping mechanisms rely on clock synchronization between different devices in the network. However, Time-Delay Attacks (TDAs) can interfere with synchronization, which further reduces traffic transmission quality. Although some studies have proposed detection strategies against TDAs, they are oriented to traditional ethernet and restricted by network architecture and devices. Therefore, this paper first analyzes the impact of TDAs on traffic transmission quality under different combinations of Time-Aware Shaper (TAS) or Cyclic Queue Forwarding (CQF) with link redundancy. Then, this paper provides a distributed monitoring parameter using Per-Stream Filtering and Policing (PSFP) for the detection and localization of TDAs, in which a modified token bucket mechanism is applied. Finally, the paper models the application of TSN in automotive industry for verification and further evaluates the effectiveness of this parameter through simulation. The results show that TDAs can cause undesirable variations in traffic latency under TAS and CQF. While proper parameter configuration and link redundancy can mitigate the impact of TDAs, they cannot prevent them. Besides, the proposed parameter helps detect and locate TDAs in TSN effectively.

A Tensegrity Joint for Low‐Inertia, Compact, and Compliant Soft Manipulators

Compact, low‐inertia, and soft compliant robotic joint mechanisms are in great demand for ensuring safe interactions in human–robot collaborative tasks. Tensegrity, of which the structural integrity is constrained by tension, does not involve static/sliding friction among the rigid components. However, this mechanical stability is very susceptible to actuation errors. It requires complex kinematics modeling and sophisticated control model with sensing feedback. Herein, a low‐inertia tensegrity joint that is covered/protected by a fiber Bragg grating (FBG)‐embedded silicone sheath is proposed, with the aim to reinforce the joint motion stability and enable self‐contained sensing feedback. A learning‐based closed‐loop controller is also designed and trained with the proper joint configurations selected by a two‐step sampling method. Both the kinematics and static equilibriums of such configurations can be well satisfied. The experiments demonstrate that the joint can follow paths accurately in 2D by compensating manipulation error shortly under the closed‐loop control. The joint stiffness can also be varied against the external/impulsive disturbances. It can be foreseen that this primitive robot joint component with 2 degrees of freedom (DoFs) can provide safe, compliant interaction with human, for which a simple test of maneuvering a portable ultrasound probe (≈210 g) for abdominal imaging is demonstrated.

THE SPECIFICS OF ORGANIZING AN END-TO-END MARKETING INTERNET ANALYTICS SYSTEM

Introduction and purpose of the study. Nowadays, during the period of intensive development of the network economy, Internet marketing in business is becoming more and more relevant, in particular Web analytics of business, which should not be based on theoretical indicators, such as the number of applications/calls from the site, but on important for business: the number sales and the amount of income. End-to-end analytics allows you to understand which customers are really beneficial for the business. End-to-end analytics is an analysis of the effectiveness of advertising campaigns based on sales data. With proper configuration, such a system allows you to track the entire sales cycle, starting from the user's first visit to the site and ending with the sale of the order placed by him (possibly even a second one). End-to-end analytics makes it possible to calculate the payback and effectiveness of marketing campaigns, advertising channels, individual ads and even search phrases, which, in turn, allows you to allocate the budget more efficiently, while getting the maximum return on advertising investments. The above outlines the relevance of this research and reflects the purpose of this article as features of the formation of an end-to-end marketing system of Internet analytics.
 Research methods. The work uses methods of empirical analysis, in particular, methods of comparison, measurement and observation.
 The results. In this study, the process of optimizing each stage of the sales funnel and increasing conversion is considered. E-business conversion is proven to be affected by price, seasonality, competitors, etc., but analytics only affects ad traffic and site interface. The paper divides the tasks of web analytics into two groups: solving a specific problem and end-to-end analytics. The main components of the system of end-to-end marketing Internet analytics are highlighted and it is proved that end-to-end analytics is a system that allows analyzing the effectiveness of advertising based on a large pool of data: sources of advertising, socio-demographic portrait of the user, paths through the site, etc. in connection with CRM- system End-to-end analytics makes it possible to look at the advertising campaign as a whole, determine the effectiveness of individual advertising sources and search phrases and, accordingly, optimize the entire sales force.
 Conclusions. It should be noted that the basic components of end-to-end analytics, the list of stages and analyzed data will change for specific theoretical or practical tasks. For the implementation of practical tasks, the composition is directly influenced not only by the type of company and the market in which it operates, but also by its size and the specifics of the existing marketing information technology architecture. Including the structure of the marketing department, information systems, online services and traffic sources, as well as the structure of the company's sites.
 Keywords: Internet marketing; WEB analytics; business digitalization; sales funnel; conversions.

Calorimetric analysis of Mg–Li ultra light magnesium alloy

The Thermal-Derivative Analysis, or Computer-Aided Cooling Curve Analysis, is a commonly used method for determining the solidification parameters of metals and alloys. Knowledge of the enthalpy, kinetics and broad characteristics of the transformations taking place during the cooling of an alloy can be obtained with the proper configuration of analytical equipment and arrangement of test techniques. This work practically analyses the changes occurring in the Mg–4.5Li–1.5Al alloy as a result of the modification of the structure by the addition of TiB and Sr. The results indicate that adding grain refinements significantly affects the microstructure and thermal parameters of Mg–4.5Li–1.5Al alloy. The nucleation temperature and solidus temperature decrease with the addition of chemical reagents. Compressive strength improved due to the refinement of grain size. The results confirmed that thermal-derivative analysis is suitable for analysing changes in cast magnesium alloys.