Mutual Combination Research Articles

Performance of an oscillating water column wave energy converter device under random ocean waves and ocean currents

The present study investigates the hydrodynamic performance of an onshore oscillating water column (OWC) device placed over an undulated bottom topography by analyzing its hydrodynamic efficiency under the action of combined wave–current interaction. The classical small-amplitude water wave theory is used to model the physical problem. The constant boundary element method is employed to solve the boundary value problem. Significant attention is devoted to describing the hydrodynamic parameters associated with the OWC device by considering the mutual combination of the random waves and ocean currents in the wave propagation phenomena. To examine the complex dynamics of the combined irregular wave current phenomena, the Det Norske Veritas spectrum accompanied by a suitable sea state has been considered for the present study. Considering the existence of opposing and following currents in wave propagation, a comprehensive analysis is conducted on the interactions of regular and irregular water waves with the OWC device. The simulated results demonstrate that the presence of ocean currents in the wave propagation phenomenon strongly influences the resonating patterns of the efficiency and force curves. Additionally, the Doppler shift in the apparent frequency caused by the following currents in the random wave–current interaction significantly improves the device's efficiency for an appropriate structural design.

БИОПРОДУКТ ДЛЯ ПРОФИЛАКТИЧЕСКОГО ПИТАНИЯ

The purpose of the study is to develop technology for a preventive bioproduct based on raw milk, enriched with plant components and probiotic cultures. Objectives: creating a biological product with a good mutual combination of ingredients of plant and animal origin, allowing to obtain high nutritional and biological value in the final product; determination of quality indicators and sanitary-significant indicators of the finished enriched bioproduct. Research was carried out at the Siberian Cossack Institute of Technology and Management (branch of the FSBEI HE Moscow State University of Technology and Management named after K.G. Razumovsky) using the production and laboratory facilities of VNIMI-Sibir LLC (Omsk). The main characteristics of the enriched product are planned: high protein-energy index, high content of macro- and microelements and probiotic microorganisms. In order to comply with all the declared characteristics of the product with preventive properties, it was decided to use curd cheese obtained by the acid method using the enrichment of probiotic microflora as the basis for the dessert bioproduct. In the course of research, the composition of a combined starter was experimentally selected, consisting of a monospecies lyophilized concentrate of thermophilic streptococci of the species Streptococcus thermophilus “BK-Uglich-TNV” and a complex probiotic culture AiBi B6.10MIX (Bifidobacterium sp., Lactobacillus casei, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus ). The study investigated the feasibility of using natural frozen cranberry puree, pine nut seeds and apple pectin in the recipe as functional plant ingredients, which were introduced into dairy raw materials to enrich the dessert bioproduct with biologically active nutrients. A dessert bioproduct was developed with a high protein content (animal and vegetable) and high probiotic properties (Lg number of cells, CFU/1 cm3: lactic acid bacteria – 10.14 ± 0.1, bifidobacteria – 7.15 ± 0.1) and organoleptic characteristics, enriched with macro- and microelements, vitamins and dietary fiber, which is recommended for use in preventive nutrition.

Hybrid machine learning approach for accurate and expeditious 3D scanning to enhance rapid prototyping reliability in orthotics using RSM-RSMOGA-MOGANN

Abstract This study aims to develop a multidisciplinary artificial hybrid machine learning (AHML) approach to reduce the scanning time (ST) of the human wrist and improve the accuracy of 3D scanning for anthropometric data collection. A systematic AHML approach was deployed to scan the human wrist distal end optimally using a portable SENSE 2.0 3D scanner. A central composite design (CCD) matrix was developed for three input variables; light intensity (LI = 12–20 W/m2), capture angle (CA = 10°–50°), and scanning distance (SD = 10–20 inches) for executing the experimental runs. For accuracy evaluation, the wrist perimeter on the distal end was checked using CREO Parametric software for wrist perimeter error (WPE). Various AHML tools were developed using: response surface methodology (RSM), multi-objective genetic algorithm RSM, and multi-objective genetic algorithm neural networking (MOGANN). The optimal process parameters recommended by the hybrid tools were experimentally validated for their prediction accuracy. The MOGANN approach combined with the Bayesian regularization algorithm (trainabr) provided the best mutual combination of optimal ST = 20.072 sec and WPE = 0.375 cm corresponding to LI = 12.001 W/m2, CA = 29.428°, and SD = 18.214 inch, with a significant percentage reduction of 55.83% in WPE. Executing 3D scanning of the human wrist over the optimized process parameters predicted by AHML tools will ensure the availability of precise scans for the rapid prototyping of customized orthotic devices in a reliable manner.

THE IMPLEMENTATION OF POSITIVISTIC PRINCIPLE IN QUALITATIVE RESEARCH

Nowadays, mainstream scientific research activities have been carried out using two methods or approaches, the first is quantitative (positivistic) by testing hypotheses as evidence and the second is qualitative (post-positivistic) by analyzing case studies, phenomena to measure the depth of formal aspects in assessing subjective events that occur in the field. This research provides a thorough understanding to identify the differences between positivistic and post-positivistic lines of thought and review the mutual combination of positivistic thinking with qualitative-based research activities which tend to be at odds. This research was conducted through library research method. Reference sources are obtained from books, journals and other relevant references. The results of this research indicate that positivistic thinking of thought does not tend to be an obstacle to conduct a qualitative research. This is proven by the emergence of several theories that can be used as analytical tools to provide additional references to support the validity of data collection in the field.

TECHNOLOGY OF PARTICLEBOARD’S PREPARATION BY COLD PRESSING AFTER HOT MAT COMPRESSION

The article describes amethod of preparing particleboards (PB) from fresh and recycled chips by anew technology of cold pressing after hot compression of the mat according to PCT/SK2023/000007 (ÚPV SR, 13.06.2023) using polyvinyl acetate (PVAc) glue. Forcomparison, the experiment was also carried out using urea formaldehyde (UF) glue and their mutual combination. The new method shortens hot pressing, or causes reduction of pressing temperatures, while the prepared PB released from pressure no longer spring and cure over time. The curing kinetics of both PVAc and UF adhesives were described by monitoring the flexural strength and modulus of elasticity of PB as a function of time after release of pressure.Modeling of the PB pressing process based on PVAc glue, which consists of overheating the pressed cross-section of the board to 90°Cand its subsequent cooling to a temperature when the board is already stable, i.e. below a temperature of 70°C, was carried out using of a hot and cold press, while the pressing cycle lasted 140 s. Shortening the pressing cycle to 100 s was achieved by applying the glue to the chips already preheated to 92°C.Laboratory tests have confirmed that the mechanical properties of PB are in accordance with the requirements of EN 312/3 for chipboards for interior conditions, including furniture, for use in dry environments.

A temperature-sensitive plugging material composed of shape memory polymer and self-made gel

Polymers with shape memory property and gel with resistance to high temperature can be both used for plugging formation, but they also have shortcomings. Nevertheless, it is possible to mix shape memory polymer(SMP) particles in the gel solution and use formation temperature to stimulate them to complete morphological transformation to achieve the purpose of plugging. This mutual combination method can help them reduce the shortcomings between each other. Here, a series of SMP with different glass transition temperatures and self-made gel were prepared. SMP needs to be prepared into particles to meet the dimensional requirements of plugging materials, but it can also retain shape memory property and pressure bearing capacity. The composition and thermal properties of both SMP and gel were characterized by FTIR and DMA. The plugging performance and mechanism of the composite of SMP and gel were systematically studied. The results show that the addition of SMP could improve the mechanical strength in system, and the viscosity gel can help stabilize the bridging structure formed by SMP particles at cracks. This composite of SMP and gel is expected to be a potential plugging material.

Prospects of the use of high-tension fiber concrete as the basis for the formation of protective shelters and fortification structures during the russian-ukrainian war

This article analyzes the current state of protective shelters and fortification structures, foresees the modern possibilities of using fastening and basalt-type structures to increase the stability of concrete fortifications both during the construction of buildings for the protection of the civilian population, and for the creation of dugouts, fortifications and fire structures for the protection of personnel in accordance.
 Studies of the physical and mechanical properties of fiber concrete modified with plasticizers and active mineral additives using basalt and polypropylene fibers have shown that their introduction has a positive effect on the strength characteristics of concrete. The compressive strength of fiber concrete at day 28 increases from 61.4 to 77.0 and 96.2 MPa, respectively, and the flexural strength from 7.4 to 12.7 and 13.8 MPa, respectively.
 For the production of reinforced concrete protective materials, it is more effective to create hybrid high-strength concrete using fibers of different nature, followed by the formation of a reinforced concrete slab of the appropriate size. At the same time, the standard provides for the manufacture of prefabricated reinforced concrete elements of fortification structures and platoon support points of wall panels of the SP-1, SP-2 type and floor slabs PP-1 with a thickness of at least 300 mm from heavy concrete of strength class C32/40 with the use of plasticizers and active chemical additives.
 However, when using the obtained hybrid fiber concrete with strength class C50/60 and using a reinforcing mesh according to the calculated data, it is possible to reduce the effective thickness of the fiber concrete slab to 27.5 cm installation of fortification.
 The use of a reinforcing mesh in a complex with basalt fiber provides increased resistance of fiber concrete to the action of a high-speed impact due to an increase in the density of the cementing matrix as a result of a decrease in water consumption, as well as due to spatial three-dimensional reinforcement with dispersed basalt fiber. As a result of the mutual combination of the strength characteristics of the concrete matrix at the micro- and macro-levels in hybrid fiber concrete, it is possible to reduce the thickness of reinforced concrete elements and reduce the weight of the protective structure while meeting the requirements of the standards for such fortifications. An increase in the strength of cement stone occurs due to a decrease in the concentration of stresses in places of local stresses and a redistribution of energy throughout the volume of the material.
 The conducted studies of modern hybrid high-strength concrete with basalt fiber create new opportunities for the creation of protective concrete fortifications and fortification structures.

The effect of therapeutic physical modalities on pain, function, and quality of life in patients with myofascial pain syndrome: a systematic review

BackgroundMyofascial pain syndrome (MPS) is a common musculoskeletal pain and dysfunction, which is characterised by myofascial trigger points. Therapeutic physical modalities, as potentially effective treatment options, are commonly used in the clinical setting for the patients with MPS.ObjectiveThis systematic review aimed to evaluate the safety and effectiveness of therapeutic physical modalities in the treatment of MPS, investigate its therapeutic mechanisms and provide a scientific evidence-based decision.MethodsAccording to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the PubMed, Cochrane Central Library, Embase, and CINAHL databases were searched for randomized controlled clinical studies published from database inception to October 30, 2022. A total of 25 articles met the study inclusion criteria. Data were extracted from these studies and a qualitative analysis was performed.ResultsTranscutaneous electrical nerve stimulation therapy, extracorporeal shock wave therapy, laser therapy, and other therapeutic physical modalities have been demonstrated to improve the pain symptoms, joint mobility, psychological state, and quality of life in the patients with MPS and no side effects have been reported. The curative effect of therapeutic physical modalities was found to be possibly associated with increased blood perfusion and oxygen supply in ischaemic tissues, reduced hyperalgesia in the peripheral and central nerves, and decreased involuntary muscle contractions.ConclusionThe systematic review has shown that therapeutic physical modalities could provide a safe and effective therapeutic option for MPS. However, the consensus is currently lacking regarding the optimal treatment paradigm, therapeutic parameters, and mutual combination of therapeutic physical modalities. The clinical trials with robust quality are required to further promote the evidence-based application of therapeutic physical modalities for MPS.

Efficacy of manuka honey with conventional antifungals on Malassezia pachydermatis.

Yeast infections such as otitis externa and seborrheic dermatitis in dogs and cats are frequently associated with Malassezia pachydermatis secondary infection. It is part of the normal cutaneous microflora of most warm-blooded vertebrates, however, under certain conditions, it can become a causative agent of infection that needs to be treated pharmacologically. Azole derivatives are the drugs of the first choice. An interesting trend in developing resistance is the use of natural substances, which include manuka honey with confirmed antimicrobial properties. The main intention of this research was to evaluate the mutual effect of manuka honey in combination with four conventional azole antifungals - clotrimazole, fluconazole, itraconazole, and miconazole - on 14 Malassezia pachydermatis isolates obtained from dogs and 1 reference strain. A slightly modified M27-A3 method (CLSI 2008) and the checkerboard test (Nikolić et al. 2017) were used for this purpose. Our results show an additive effect of all 4 antifungals with manuka honey concurrent use. Based on the determined values of fractional inhibitory concentration index (FICI - 0.74±0.03 when manuka honey combined with clotrimazole, 0.96±0.08 with fluconazole, 1.0±0 with miconazole and 1.16±0.26 with itraconazole), it was found in all cases that the effect of substances used is more pronounced in mutual combination than when used separately.

Prohibited artificial intelligence practices in the proposed EU artificial intelligence act (AIA)

Artificial intelligence (AI) now forms a more and more important part of human lives. After years focussed on the development of AI, the initial hype about its many expected benefits has gradually given way to rising ethical concerns about its inherent risks and dangers. Efforts to confront and contain the most serious risks related to AI have now prompted a number of legislative or regulatory proposals at the national, regional and global level. One of the most comprehensive regulatory initiatives is the European Union's proposal for an Artificial Intelligence Act (AIA), which was released in April 2021 with a view towards establishing a legal framework for trustworthy AI. To this end, the draft AIA pursues a proportionate horizontal and risk-based regulatory approach to AI, broadly classifying AI into the categories of unacceptable risks, high risks and low or minimal risks. The unacceptable risks are those that are deemed to contravene European Union values, and therefore, they are considered to be ‘prohibited AI practices’ by Article 5 AIA. The prohibited AI practices are classified into four categories, namely 1) AI systems deploying subliminal techniques; 2) AI practices exploiting vulnerabilities; 3) social scoring systems; and 4) ‘real-time’ remote biometric identification systems. The proposed regulatory approach, however, appears problematic given the four categories’ inherent interrelatedness and the numerous possibilities for their mutual combination and entwinement. It is also problematic from the perspective of the human mind, as each of the four categories alone allows for the manipulation of human thought and behaviour, thereby endangering freedom of thought and other fundamental rights. In the context of the proposed AIA, both aspects give rise to unknown and unsolved conundrums that create difficult regulatory challenges that raise the necessity to also look at the wider implications of these technologies for the entire legal system. As these conundrums often find their expression in paradoxes and oxymora, this article calls for a wider interdisciplinary debate and advocates a different regulatory strategy using these concepts to transcend the limitations inherent in dualistic or dichotomous modes of legal thinking.

Economic feasibility study for artificial lighting of microalgal flat-panel photobioreactors

Lightning belongs among critical process parameters that significantly affect growth and microalgal yield in photobioreactors. Sunshine or artificial lighting is applied to irradiate photobioreactors. Nevertheless, sunshine lighting is limited by locality and weather conditions. On the contrary, there is a typical demand for nonstop or 8000 annual working hours for industrial biorefineries using photobioreactors as an economic point of view. Thus the paper scopes to evaluate the fundamental economic feasibility of artificial lightning provided by electric energy from fossil fuels, renewable energy systems, or their mutual combinations. The economic feasibility is discussed concerning local annual sunshine hours for a model 1-ha microalgae cultivation plant. It was found that combined sunlight, solar energy- and electric energy-based artificial lighting has a significant positive effect on the economic behavior of a model biorefinery. The mutual combination of sunshine, solar energy- and electric artificial energy-based light evinces a profit increase of 2.18 for microalgal powder, 3.09 for microalgal lipids and 4.11 for microalga carotenoids production technologies all compared only to sun lighted photobioreactors. Nevertheless, capital investments in artificial lightings, solar systems, or photobioreactors, and high operating expenses represent the dominant risk factors of the discussed microalgal biorefinery. Developing cheap and reliable artificial lighting systems, solar and energy storage systems, and improving process characteristics of microalgal cultivation (process stability, high concentrated suspension in thin layer photobioreactors avoiding biofilm formation) were identified as the essential research needs and challenges to improve the economic feasibility of artificially lighted microalgal biorefinery.

Co-MOF induced “blossom branch like” MoS2@Co9S8/C nanofibers as a bifunctional catalyst for HER and OER

The design and heterostructure construction of electrocatalysts is an essential approach for accomplishing bifunctional catalytic activity toward hydrogen and oxygen evolution (HER/OER). Here, MoS2@Co9S8/C composite nanofibers with a “blossom branch” distributed structure were prepared via a facile method. Unlike traditional composites, the MoS2 and Co9S8 consistently grow together due to the coaxed growing effect of Co toward MoS2, forming flower-like MoS2@Co9S8 nanoparticles and staggered distributed on carbon nanofibers. Transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) measurements, and density functional theory (DFT) calculation revealed that the close mutual combination between MoS2 and Co9S8 enhances the synergistic effect of the heterointerface, which improves the chemisorption of intermediates and further facility the catalytic reaction. MoS2@Co9S8/C composite nanofibers exhibited high activity toward HER and OER. This work provides a facile strategy for designing a heterostructure that with close mutual heterogeneous combination and without aggregation.

Multi-scale self-attention-based feature enhancement for detection of targets with small image sizes

In this paper, we propose a feature enhancement method based on multi-scale self-attention, mainly including a multi-scale feature combination module and a self-attention module. The multi-scale feature combination module integrates the multi-layers’ features extracted from the backbone network in both the top-down and bottom-up directions. Then, the shallow and deep features are combined. The self-attention module enhances the feature representation by assigning attention weights to the features that have intrinsic connection to the features of the target. The multi-scale self-attention-based feature enhancement method improves the performance for detecting targets with small image sizes in complex scenes by mutual combination between deep and shallow features and between local and global features. The experimental results show the effectiveness of the proposed feature enhancement method.

PASTURE OF PHARMACEUTICAL, MACHINE LEARNING HAS A NUMBER OF APPLIANCES

These years, with computer science and machine learning changing into the hotspot of analysis, many appliances have emerged in every of those areas. It exists not solely as a form of educational frontier however conjointly one thing on the point of our life. during this trend, the mixture of medical aid and machine learning becomes additional and additional tighter. The proposal of its main plan conjointly greatly mitigated the prevailing scenario of unbalanced medical distribution and resources strain. This paper summarizes some application of machine learning and auxiliary growth treatment within the method of medical resource allocation, and puts forward some new strategies of application to appreciate it nearer to human life within the era of computer science and therefore the explores an honest scenario of mutual combination of medical business and industry, that is profit each.

Assessment of the potential for quantifying multi-period suspended sediment concentration variations using satellites with different temporal resolution

Suspended sediment concentration (SSC) is a crucial indicator for coastal health and geomorphological evolution, featured by complex periodic processes on multiple timescales in response to different cyclic forcing factors. Although remote sensing has functioned as an important means for SSC estimation with sufficient spatio-temporal coverage, the low effective sampling rates and resulting unevenly spaced characteristics of the retrieved time series would hamper the extraction of the representative SSC portrayal (amplitude and phase) on multiple timescales, especially for low-resolution satellites. Here, we retrieved a 9-year hourly GOCI SSC time series (January 2012 to December 2020) at two coastal sites in China (Haimen and Haizhou Bay) as reference cases, and utilized them to obtain MODIS, Sentinel and Landsat sequences with average temporal resolutions of 0.5, 5.6 and 11.2 days as preliminary investigations into amplitude and phase extractions. Furthermore, we generated GOCI-based hypothetical satellite time series with temporal resolutions ranging from 1 to 16 days (1088 subsets) and their mutual combination (591,328 subsets) to explore general laws when extracting amplitudes and phases from satellites with different temporal resolutions by application of the Lomb-Scargle Periodogram and phase-folded diagram methods. The amplitude and phase deviations were found to increase with decreasing temporal resolution on seasonal and fortnightly timescales at Haimen and in Haizhou Bay, while by mutual combination of satellites the errors could be reduced as more data were utilized for the extraction. It is shown that larger amplitude and phase deviations occur on the seasonal timescale in comparison to the fortnightly timescale at Haimen, whereas the situation reverses in the case of Haizhou Bay. These results demonstrate that temporal resolution, data characteristics on the target timescale and absolute SSC amplitude codetermine the extraction accuracy. This further indicates that satellites with lower temporal resolutions can potentially be used on a global scale for extracting the feature changes of multi-period SSC variations, in particular as continuous improvements in data quantity and quality can be expected in the future.

Development of novel crystal scintillators for lunar surface science

The development of novel crystal scintillators for a lunar landed mission near future is reported. On that mission, we aim to assess the radiation dose, biological effect, water, and other resources on the lunar surface. To accomplish this, a Lunar Vehicle Radiation Dosimeter (LVRAD) made up of several radiation detectors has been proposed. New scintillation crystals are being developed for neutron and gamma measurements. Stilbene and undoped LaCl3 crystal were selected for fast neutron/gamma spectrometers. The mutual combination of organic and inorganic detectors benefits from direct fast neutron detection via 35Cl(n, p)35S reaction as well as the good gamma resolution of LaCl3 and the high detection efficiency of stilbene. LaCl3 crystals with the diameter of 38.1 mm were grown by a homemade modified Bridgman furnace. For epithermal neutron spectrometer, 6LiI:Ag crystal was selected due to its pulse shape discrimination capability and highest detection efficiency in terms of size for both thermal and epithermal neutron among scintillation materials. Enrich 6LiI was purified using the zone-refining technique. The crystal was then grown by the same Bridgman furnace.

Satellite Observation of the Long-Term Dynamics of Particulate Organic Carbon in the East China Sea Based on a Hybrid Algorithm

The distribution pattern and flux variation of POC in the continental shelf seas are essential for understanding the carbon cycle in marginal seas. The hydrodynamic environment and complicated estuarine processes in the East China Sea result in challenging estimates and substantial spatio-temporal variability in terms of POC concentrations. A hybrid retrieval model based on the mutual combination of the color index algorithm (CIPOC) and the empirical band ratio algorithm was applied in this study to effectively and dynamically monitor the surface POC concentration in the East China Sea in a long-term series for the first time using MODIS/Aqua remote sensing satellite data from 2003 to 2020. A hybrid retrieval model based on the mutual combination of the color index algorithm (CIPOC) and the empirical band ratio algorithm was applied in this study. The MODIS/Aqua remote sensing satellite data from 2003 to 2020 were employed for the first time to dynamically monitor the surface POC concentrations in the East China Sea for a long time series. The results demonstrated that the performance (R2 = 0.84, RMSE = 156.14 mg/m3, MAPE = 43.30%, bias = −64.79 mg/m3) exhibited by this hybrid retrieval algorithm confirms the usability of inversion studies of surface POC in the East China Sea. Different drivers such as river discharge, phytoplankton, wind, and the sea surface current field jointly influence the spatial and temporal distribution of POC concentrations in the East China Sea. This paper also verifies that the hybrid algorithm can be applied to retrieval tasks for POC in different seas with similar optical properties to the waters of the East China Sea. In conclusion, the long-term series East China Sea POC data record, which was established based on MODIS/Aqua, provides supplementary information for in-situ sampling, which will aid the long-term monitoring of POC fluxes in shelf seas. At the same time, it has also improved our understanding of the transport and spatio-temporal variability of POC in the East China Sea, enhancing our comprehension of the impact of POC on environmental changes and carbon cycling in marginal seas.

A Chaotic Antlion Optimization Algorithm for Text Feature Selection

Text classification is one of the important technologies in the field of text data mining. Feature selection, as a key step in processing text classification tasks, is used to process high-dimensional feature sets, which directly affects the final classification performance. At present, the most widely used text feature selection methods in academia are to calculate the importance of each feature for classification through an evaluation function, and then select the most important feature subsets that meet the quantitative requirements in turn. However, ignoring the correlation between the features and the effect of their mutual combination in this way may not guarantee the best classification effect. Therefore, this paper proposes a chaotic antlion feature selection algorithm (CAFSA) to solve this problem. The main contributions include: (1) Propose a chaotic antlion algorithm (CAA) based on quasi-opposition learning mechanism and chaos strategy, and compare it with the other four algorithms on 11 benchmark functions. The algorithm has achieved a higher convergence speed and the highest optimization accuracy. (2) Study the performance of CAFSA using CAA for feature selection when using different learning models, including decision tree, Naive Bayes, and SVM classifier. (3) The performance of CAFSA is compared with that of eight other feature selection methods on three Chinese datasets. The experimental results show that using CAFSA can reduce the number of features and improve the classification accuracy of the classifier, which has a better classification effect than other feature selection methods.

Effect of composition and nanostructure on the mechanical properties and thermal stability of Zr100-xCux thin film metallic glasses

Thin film metallic glasses (TFMGs) are a novel class of materials showing a mutual combination of large plastic deformation in tension (>10% strain) and superior yield strength up to ∼ 3.5 GPa, which make them ideal candidates for applications such as flexible electronics. Nevertheless, a clear relationship between the atomic structure and mechanical properties of TFMGs has not yet been achieved. In particular, the role of composition in determining a different local atomic order and the effect of nanostructure on TFMGs properties must be further investigated. In this work, the mechanical properties and thermal stability of several amorphous Zr100-xCux TFMGs with either compact or fine columnar nanostructure were studied. The mediating role of composition in controlling crystallization temperature and hardness is here reported, which was found to increase from 4.6 to 7.7 GPa with increasing Cu content from 26 to 76 at.%. Moreover, plastic behavior and fracture resistance are shown to be highly dependent on both composition and nanostructure, with the Cu-rich and homogeneous film able to withstand elongation up to 2% strain before crack initiation. These results underline how atomic structure changes induced by composition can effectively influence TFMG properties, while demonstrating an approach to tune their behavior for various technological applications.

Targeted Strategy in Lipid-Lowering Therapy.

Dyslipidemia is characterized by a diminished lipid profile, including increased level of total cholesterol and low-density lipoprotein cholesterol (LDL-c) and reduced level of high-density lipoprotein cholesterol (HDL-c). Lipid-lowering agents represent an efficient tool for the prevention or reduction of progression of atherosclerosis, coronary heart diseases and metabolic syndrome. Statins, ezetimibe, and recently proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors are the most effective and used drugs in clinical lipid-lowering therapy. These drugs are mainly aimed to lower cholesterol levels by different mechanisms of actions. Statins, the agents of the first-line therapy—known as 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) reductase inhibitors—suppress the liver cholesterol synthesis. Ezetimibe as the second-line therapy can decrease cholesterol by inhibiting cholesterol absorption. Finally, the PCSK9 inhibitors act as an inducer of LDL excretion. In spite of their beneficial lipid-lowering properties, many patients suffer from their serious side effects, route of administration, or unsatisfactory physicochemical characteristics. Clinical demand for dose reduction and the improvement of bioavailability as well as pharmacodynamic and pharmacokinetic profile has resulted in the development of a new targeted therapy that includes nanoparticle carriers, emulsions or vaccination often associated with another more subtle form of administration. Targeted therapy aims to exert a more potent drug profile with lipid-lowering properties either alone or in mutual combination to potentiate their beneficial effects. This review describes the most effective lipid-lowering drugs, their favorable and adverse effects, as well as targeted therapy and alternative treatments to help reduce or prevent atherosclerotic processes and cardiovascular events.