Static Techniques Research Articles

A reliable GTR-PLC approach for power enhancement and online monitoring of solar PV arrays during partial shading

The PV system encounters severe power loss due to the existence of unavoidable partial shading that is mainly overcome by reconfiguration techniques. Besides the advantage of power enhancement, reconfiguration techniques deal with drawbacks such as limited to symmetrical arrays, higher switches and sensors requirements, lower convergence to optimal solution, and improper monitoring. In this paper, a gorilla troop reconfiguration-power line communication (GTR-PLC) approach is proposed for performance enhancement and monitoring of PV arrays during partial shading. The proposed approach uses a considerably lower switch count along with a low-cost simple architecture for loss reduction and smooth operation of the PV array during partial shading. The proposed approach is validated for 5 × 5 and 9 × 9 arrays under time-domain dynamic shading scenarios in simulation whereas real-time hardware setup-based analysis is conducted for 2 × 3 and 12 × 4 arrays using numerous artificial shading cases. The performance of the proposed system is compared with twelve existing static and dynamic techniques and found to have zero misleading power loss with an average power increment of 38.37 %. Also, a power extraction efficiency of 98.99 % and an average calculation time of 0.09 s in the proposed system during partial shading is recorded.

Survey of techniques to detect common weaknesses in program binaries

Software vulnerabilities resulting from coding weaknesses and poor development practices are common. Attackers can exploit these vulnerabilities and impact the security and privacy of end-users. Most end-user software is distributed as program binaries. Therefore, to increase trust in third-party software, researchers have built techniques and tools to detect and resolve different classes of coding weaknesses in binary software. Our work is motivated by the need to survey the state-of-the-art and understand the capabilities and challenges faced by binary-level techniques that were built to detect the most important coding weaknesses in software binaries. Therefore, in this paper, we first show the most critical coding weaknesses for compiled programming languages. We then survey, explore, and compare the static techniques that were developed to detect each such coding weakness in software binaries. Our other goal in this work is to discover and report the state of published open-source implementations of static binary-level security techniques. For the open-source frameworks that work as documented, we independently evaluate their effectiveness in detecting code vulnerabilities on a suite of program binaries. To our knowledge, this is the first work that surveys and independently evaluates the performance of state-of-the-art binary-level techniques to detect weaknesses in binary software.

Clinical Outcomes of Cephalomedullary and Static Transverse Proximal Locking Techniques in Femoral Intramedullary Nailing in Geriatric Patients

Clinical Outcomes of Cephalomedullary and Static Transverse Proximal Locking Techniques in Femoral Intramedullary Nailing in Geriatric Patients

Static Compaction on Coupled Precursors and Optimizing Molarity for Enhanced Strength and Durability of Geopolymer.

The static compaction technique emphasizes the reduced activator dosage required to develop geopolymers. Therefore, it is crucial to comprehend the optimal alkaline activator concentration for blending low-calcium precursor (fly ash) with high-calcium precursor (GGBS) to produce geopolymer blocks. This work was designed to optimize structural blocks' compressive strength and durability. In experimentation, fly ash (FA) and slag (GGBS) proportions were initially investigated under NaOH solution with varying molarity (8-12) and curing conditions to develop a load-bearing structural block. Subsequently, the durability of the optimized block was evaluated over 56 days through subjection to sulfate and acidic solutions, with efflorescence monitored over the same period. The results reveal that the structural block comprised of 100% FA exhibits the highest compressive strength and lowest bulk density. Conversely, the block incorporating 25% slag that underwent hot curing demonstrates a remarkable 305% strength increase compared to ambient curing. Considering the physico-mechanical performance, the 100% FA block was chosen for durability investigation. The findings indicate a substantial strength loss exceeding 40% after exposure to sulfate and acidic environments over 56 days, coupled with pronounced efflorescence. Catastrophic failure occurs in all cases due to significant strength deterioration. The FTIR spectrum revealed the shifting of the wavenumber to a higher value and verified the depolymerization and leaching of alumina under acidic exposure. However, the developed geopolymer blocks demonstrate superior sustainability and feasibility compared to conventional fired clay bricks and cement-based FA bricks. Despite slightly higher costs, these blocks exhibit greater strength than their counterparts after enduring severe exposures.

Damage detection in space truss structures using a third-level approach

Monitoring civil engineering infrastructure is crucial to ensuring that the structures can continue to function properly. An important aspect of this assessment is detecting structural damage. This study proposed a method that combined static loading techniques and modal parameters to establish a third level of damage detection. Specifically, the damage locating vector (DLV) was used as the static technique, and mode shapes, along with Modal Assurance Criteria (MAC), were integrated with the Firefly Algorithm (FA) to define the damage percentage. The objective of this method is to determine the location of the damaged members in space truss structures and accurately estimate the reduction in stiffness of the damaged members. DLV was used to show the location of damaged members, while the Modal Assurance Criteria – Firefly Algorithm (MAC-FA) was used to predict the stiffness loss in structural elements. This combined approach improved the DLV method, which could only identify potentially damaged parts. The fundamental concept behind MAC-FA was the relationship between the predicted mode shape and the mode shape of the structure, represented by the MAC value. This method was used to investigate damage detection in two space truss structures. The results demonstrated that the proposed method could identify damaged elements and quantify the loss of stiffness in space truss structures.

Insights on the G protein-coupled receptor helix 8 solution structure and orientation using a neurotensin receptor 1 peptide.

G-protein coupled receptors (GPCRs) are the largest class of membrane proteins encoded in the human genome with high pharmaceutical relevance and implications to human health. These receptors share a prevalent architecture of seven transmembrane helices followed by an intracellular, amphipathic helix 8 (H8) and a disordered C-terminal tail (Ctail). Technological advancements have led to over 1000 receptor structures in the last two decades, yet frequently H8 and the Ctail are conformationally heterogeneous or altogether absent. Here we synthesize a peptide comprising the neurotensin receptor 1 (NTS1) H8 and Ctail (H8-Ctail) to investigate its structural stability, conformational dynamics, and orientation in the presence of detergent and phospholipid micelles, which mimic the membrane. Circular dichroism (CD) and nuclear magnetic resonance (NMR) measurements confirm that zwitterionic 1,2-diheptanoyl-sn-glycero-3-phosphocholine is a potent stabilizer of H8 structure, whereas the commonly-used branched detergent lauryl maltose neopentyl glycol (LMNG) is unable to completely stabilize the helix - even at amounts four orders of magnitude greater than its critical micellar concentration. We then used NMR spectroscopy to assign the backbone chemical shifts. A series of temperature and lipid titrations were used to define the H8 boundaries as F376-R392 from chemical shift perturbations, changes in resonance intensity, and chemical-shift-derived phi/psi angles. Finally, the H8 azimuthal and tilt angles, defining the helix orientation relative of the membrane normal were measured using paramagnetic relaxation enhancement NMR. Taken together, our studies reveal the H8-Ctail region is sensitive to membrane physicochemical properties and is capable of more adaptive behavior than previously suggested by static structural techniques.

Cultivated Grassland Types Differently Affected Carbon Flux Downstream of the Yellow River

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties.

Code search engines for the next generation

Given the abundance of software in open source repositories, code search engines are increasingly turning to “big data” technologies such as natural language processing and machine learning, to deliver more useful search results. However, like the syntax-based approaches traditionally used to analyze and compare code in the first generation of code search engines, big data technologies are essentially static analysis processes. When dynamic properties of software, such as run-time behavior (i.e., semantics) and performance, are among the search criteria, the exclusive use of static algorithms has a significant negative impact on the precision and recall of the search results as well as other key usability factors such as ranking quality. Therefore, to address these weaknesses and provide a more reliable and usable service, the next generation of code search engines needs to complement static code analysis techniques with equally large-scale, dynamic analysis techniques based on its execution and observation. In this paper we describe a new software platform specifically developed to achieve this by simplifying and largely automating the dynamic analysis (i.e., observation) of code at a large scale. We show how this platform can combine dynamically observed properties of code modules with static properties to improve the quality and usability of code search results.

Analyzing Rinex Data Files Using the Python Programming Language

Abstract The techniques and tools developed for geodetic determinations have made it possible, over the past half century, to carry out measurements using global navigation satellite systems. As the accuracy and precision of positioning solutions, such as Fast Static and RTK, improve through technological advances, more applications will become available that can provide users with positioning information over time, autonomously verify the integrity of transmitted data, and ensure sufficient accuracy for their intended purposes. In our study for the interpretation, analysis, and visualization of raw and/or processed RINEX GNSS data recorded over time at a geodetic point using the information available from the Fast Static technique, we used the GeoRinex library from the Python programming language. This library converts data to xarray.data set, for easy use in processing parameter sets, from Rinex files: of ROMPOS reference stations and of the new B10 point resulting from measurements using the Fast Static technique: pseudorange (C1, C2, P1, P2....), carrier phase (L1, L2,…), doppler (D1, D2....) and signal strength (S1, S2....). All this information will help us to analyse and interpret the degradation of the parameters associated with Rinex version 2.11 epoch positioning files 12.02.2023, time interval 12:00-14:00 (fast static) and to understand their accuracy and behavior in different environments. Based on this study, our aim was to evaluate the error in determining the positioning accuracy of the B10 point located in a crowded and heavily trafficked area, which allows sufficient coverage of the GNSS satellites.

Observation of high-pressure polymorphs in bulk silicon formed at relativistic laser intensities

Silicon polymorphs with exotic electronic and optical properties have recently attracted significant attention due to their wide range of useful band gap characteristics. They are typically formed by static high-pressure techniques, which limits the crystal structures that can be made. This constitutes a major obstacle to study these polymorphs and their incorporation into existing technology. Approaches have attempted to address this shortcoming through using dynamic conditions and chemical precursor materials. Here, we report on an approach to create unusual crystal structures deep in the bulk of a silicon crystal by irradiating it with a laser pulse at ultrarelativistic intensity of up to 7.5×1019 W/cm2. Laser-generated electrons with MeV energy swiftly penetrate the target with speed close to the speed of light and deposit their energy into a large volume across the whole thickness of the sample. The relativistic electron current creates, via branching propagation and ionization, high-energy-density conditions for thermodynamically nonequilibrium phase transformation paths into new crystal polymorphs. X-ray microdiffraction and synchrotron x-ray diffraction analyses indicate, along with conventional dc-Si, the presence of exotic silicon structures in the bulk of the laser intact target volume. These structures are identified as body-centered bc8-Si, rhombohedral r8-Si, hexagonal-diamond hd-Si, and the tetragonal Si-VIII, all phases of Si that have previously been made through static techniques. Additionally, simple-tetragonal st12-Si and body-centered tetragonal bt8-Si were observed along with signatures of not yet identified diffraction spots. Both st12-Si and bt8-Si have only been observed in ultrafast laser microexplosion conditions at much lower laser intensity ∼1014 W/cm2 and within a micron-thin surface layer. The findings here are supported by direct observation of nanoparticles with high-resolution transmission electron microscopy and corresponding fast Fourier transform analysis of their interatomic distances. The presented analyses of absorbed laser energy, generation of the MeV electron current, and deposition of energy across the whole target thickness provide a solid basis for drawing the conclusion that the observed silicon polymorphs were produced because of laser-generated high-energy electrons fast-penetrating deeply into the bulk of silicon. In contrast to solid-solid transformations, the plasma-solid transitions offer a paradigm for the creation of exotic, high-energy density materials inside the bulk of the sample by using laser pulses at relativistic intensities. Published by the American Physical Society 2024

Role of Dynamic Ultrasound Scan in Detection of Hip Instability and Changing Management Plan

Objectives: To show the vital role of dynamic ultrasound in hip instability screening and review the management plans available for DDH associated with instability with a view to reduce the incidence of complication from delayed diagnosis in our region. Place and Duration of the study: Helena governmental rehabilitation center for children with special needs, Erbil-Iraq, between Nov’21 to Jan’23. Material and Method: This study included 942 infants’ hips presenting with high-risk indicators or a positive clinical examination ranging in age from 6 weeks to 6 months. We performed the ultrasonography using the static Graf technique to determine the DDH Types and then apply the dynamic scan to find stability using Moren-Terjesen’s and Harcke methods. The management approaches were conducted considering both techniques. We used SPSS version 28 along with Chi-square test for data analysis and comparison of proportions. Results: In this retrospective cross-sectional study of 942 hips, the mean age of the infants was 11.9±4.8 weeks with male to female percentage of 46% to 54%. We found a correlation between family history and breech presentation to the dynamic scan stability. In the Graf technique 55% showed the absence of dysplasia while the dynamic scan showed 66% of the hips as normal and 34% as unstable. Further, the significant statistical association (P= 0.001) between the results of dynamic scan stability to the effect on the management plan was also found to advise the change for the unstable hips. Conclusion: It is crucial to apply both static and dynamic scans in the screening of DDH, so that we can reduce the possibility of late detection and elevate the level of diagnostic accuracy. We should follow a strict guideline for the management of all DDH cases (stable and unstable) and change the plan accordingly.

Promoting sustainability in developing Countries: A Machine Learning-based approach to understanding the relationship between green investment and environmental degradation

The main objective of this study is to examine the impact of green investment on environmental degradation in developing countries using machine learning-based estimation combined with robustness tests of static and dynamic panel data modeling techniques. The scope of this study covers 30 developing countries for 2009–2019. This study introduces a new index of environmental degradation that uses the entropy method and includes green gas emissions and deforestation. The study addresses trade openness, the quadratic shape of economic growth, and urbanization in the context of the Environmental Kuznets Curve Hypothesis (EKC) and the Ecological Modernization Theory (EMT), in addition to green investment. This study considers the kernel-based regularized least squares (KRLS) approach, the static panel technique Driscoll & Kraay standards error method, and a dynamic panel technique system generalized moment techniques. The empirical findings from the machine learning method show that green investment significantly reduces environmental degradation with a higher coefficient resulting from the static fixed effect estimation. The study also reveals that the main hypotheses, such as EKC and EMT, are confirmed by all estimation techniques. Based on the results, the study recommends that policymakers take pragmatic steps toward green investments and increase the financing of green energy initiatives to combat environmental degradation.

MeMalDet: A memory analysis-based malware detection framework using deep autoencoders and stacked ensemble under temporal evaluations

Malware attacks continue to evolve, making detection challenging for traditional static and dynamic analysis techniques. On the other hand, memory analysis provides valuable behavioral insights, but prior research lacks temporal evaluations which are critical for robust detection of new malware variants over time. This paper presents MeMalDet, a novel memory analysis-based malware detection technique using deep autoencoders and stacked ensemble learning. We introduce an improved dataset with temporal attributes enabling more realistic evaluations of memory-based malware detection techniques under concept drift (temporal data split). MeMalDet extracts optimal features from memory dumps using deep autoencoders in an unsupervised manner, avoiding manual feature engineering. A stacked ensemble of supervised classifiers then performs highly accurate malware detection. Extensive experiments on our improved large-scale public dataset demonstrate MeMalDet’s ability to maintain high performance when detecting obfuscated malware under temporal splits. We achieve up to 98.82% accuracy and 98.72% F1-score in detecting previously unseen advanced obfuscated malware, significantly improving upon state-of-the-art memory analysis-based malware detection techniques. The improved dataset enables temporally robust evaluations, which is a novel contribution. MeMalDet combines the benefits of representation learning and supervised machine learning ensemble classification for effective malware detection over time using memory analysis. This research provides a new capability for identifying evasive modern malware and combating evolving real-world threats.

Exploiting DBSCAN and Combination Strategy to Prioritize the Test Suite in Regression Testing

Test case prioritization techniques improve the fault detection rate by adjusting the execution sequence of test cases. For static black-box test case prioritization techniques, existing methods generally improve the fault detection rate by increasing the early diversity of execution sequences based on string distance differences. However, such methods have a high time overhead and are less stable. This paper proposes a novel test case prioritization method (DC-TCP) based on density-based spatial clustering of applications with noise (DBSCAN) and combination policies. By introducing a combination strategy to model the inputs to generate a mapping model, the test inputs are mapped to consistent types to improve generality. The DBSCAN method is then used to refine the classification of test cases further, and finally, the Firefly search strategy is introduced to improve the effectiveness of sequence merging. Extensive experimental results demonstrate that the proposed DC-TCP method outperforms other methods in terms of the average percentage of faults detected and exhibits advantages in terms of time efficiency when compared to several existing static black-box sorting methods.

Optimization of the static brewing technique for ready-to-drink Kangra orthodox green tea, sweetened with selected sweeteners

Optimization of the static brewing technique for ready-to-drink Kangra orthodox green tea, sweetened with selected sweeteners

Consistency in the assessment of postural balance using static stabilometry and scale techniques in older individuals: An observational study

BACKGROUND: In clinical practice, both clinical scales and instrumental methods are used in parallel to assess postural stability and the risk of falls. Literature data on the comparability of postural balance estimates obtained using scale techniques and stabilometry, particularly in older patients, are conflicting.
 AIM: to analyze the consistency in the assessment of postural balance by static stabilometry and scale techniques in older patients.
 MATERIALS AND METHODS: A pilot observational, nonrandomized, single-center study was conducted. The study participants were 39 women aged 60–75 years who did not have diseases or conditions that significantly affected the postural control system. Postural balance was assessed using clinical scales and tests (timed up and go test, classic and a double task; Berg balance scale; Mini-BESTest, balance evaluation systems test; performance-oriented mobility assessment; and falls efficacy scale) and basic spatial, spatiotemporal, and spectral parameters of static stabilometry. A stabilometric study was conducted at the posturological complex Biokinect. Correlation analysis of the data of the scale techniques and stabilometry was performed.
 RESULTS: The correlation analysis showed both the correlation between some parameters of stabilogram and scale techniques and the complete absence of a significant correlation between others. However, even in the presence of a statistically significant correlation, the relationship between the parameters did not exceed the moderate or average level (maximum value of the correlation coefficient, 0.685, p 0.01). The largest correlation was found between the stabilometric parameters and the timed up and go test (correlated with 11 out of 21 parameters) and the falls efficacy scale (10 parameters), and the smallest was found with the Mini-BESTest (5 parameters). The values of the stabilometric parameter (speed of movement of the center of pressure) demonstrated a statistically significant correlation with most of the clinical instruments (4 out of 6).
 CONCLUSION: This study showed low consistency between the basic parameters of static stabilometry and scale techniques in older people. The results of simpler scale techniques for the assessment of postural balance correlated better with stabilometry data than with more complex and multicomponent ones because the total indicator of the latter is a generalized assessment of postural stability and other elements of complex motor behavior associated with postural balance. Therefore, simple scale techniques and tasks should be preferred when assessing the basic postural stability and risk of falls in older people.

Statistical physics modelling of adsorption isotherms of water vapour on shale: Stereographic, energetic and thermodynamic investigations

AbstractUnderstanding the mechanisms of shale–water interaction by water vapour adsorption is crucial for predicting shale gas productivity. In this study, equilibrium adsorption data of water vapour on four different shales of the Sichuan Basin at three temperatures (298, 308, and 318 K) were measured using static gravity techniques. The water vapour adsorption isotherms were simulated by three statistical physics models. Steric parameters, including the number of water vapour molecules adsorbed per site (n), monolayer adsorption amount (q0), and adsorption energy (ΔEa), and thermodynamic parameters such as configuration entropy (Sa), internal energy (Eint), and free energy (Ga) derived from the selected model were used to explain the adsorption mechanism. The model analyses suggest that the adsorbed water vapour molecules are attached to the shale surface in a multi‐anchorage manner. The adsorption of the first layer shows a Type I characteristics, while the adsorption of the subsequent layer is of Type III. The calculated adsorption energies indicate that the physical adsorption takes place on the water vapour molecules on the shale, and the main interaction forces are hydrophilic bonding forces and van der Waals forces. Negative Eint and Ga values indicate that the spontaneous properties are for water vapour adsorption and that the system requires the release of energy to capture the water vapour molecules.

Evaluation of the offset static rope evacuation procedure: insights from a safe job analysis.

Recently, the Norwegian Helicopter Emergency Medical Service (HEMS) has developed a procedure for a special type of static rope rescue operation, referred to as the offset technique. In this technique, the helicopter is offset from the accident site, and the HEMS technical crew member uses an offset throw line to gain access to the scene. Today, there is little practical experience of such operations, and a need has been identified for more knowledge on the potential hazards encountered during this type of operation. Such knowledge is of importance for further development of the procedure for the offset technique. To identify potential hazards for helicopter rescue operations using the static rope offset technique and, thereby, to improve the procedure for such operations. This may lead to improved safety for patients and crew members during offset rescue operations. A Safe Job Analysis was used to identify the hazards of offset rescue operations. Such operations are divided into tasks and sub-tasks. For each sub-task, we identified potential hazards and suggested ways of preventing these. Through the Safe Job Analysis, we suggest some changes in the existing procedure for the offset technique, to make it more robust against potential hazards. We have demonstrated the value of Safe Job Analysis for improving the static rope offset evacuation procedure. Our analysis has led to some changes in the procedure for offset rescue operations. This is the importance of having two throw lines and focusing on "why" in the procedure.

Thermodynamic analysis for the dissolution of two similar amino acids in sodium sulfate aqueous solution

In the current work, the analyti cal static gravimetric technique was used to assess the solubilities of DL-α-amino butyric acid and DL-valine in an aqueous binary solvent mixture of sodium sulfate (Na2SO4) under equilibrium saturation conditions in between temperature range 288.15 and 308.15 K. Different thermodynamic factors along with transfer Gibbs energetics and entropies under standard conditions were estimated by using computational as well as theoretical method by using the experimental solubilities. Several modes of interactions that occur during solvation were also explained. The manner that solvent molecules of solute amino acids are surrounded in the aforementioned medium employed during the process is taken into consideration. Amino acids become more soluble as the temperature rises. The study also helps us to reach the conclusion that physical properties of electrolyte (Na2SO4), mixed solvent, and the size of the amino acids’ molecules are the main governing factors for the chemical stability as well as other thermodynamic and physical property like solubility of solute amino acids.

Enhancing security of cloud using static IP techniques

The user authentication and access control procedures for data stored on a cloud server encountered numerous security risks and concerns. Because critical company data should only be accessible by authorized workers, enhancing cloud security with static IP approaches is more beneficial. Even though the cloud providers maintain many security mechanisms, still the level of security should be raised by them due to lot of intruders who want to break their security mechanism. An encryption method is frequently used in most servers’ security mechanisms. In this security mechanism, data in the cloud server may be stolen and misused. Security mechanisms using static IP addresses are another method for data security in cloud security. This paper explains that the static IP address security mechanism is better and more goal-oriented than that of earlier security systems.