bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Fatigue Characteristics of Polyester and Nylon Mooring Lines for Shallow Water Floating Offshore Wind Turbines
Authors: Saleh Samer , Akers Richard , Koo Bonjun , Yau Henry , Lopez Tomas , Thiagarajan Krish
Published: January 2024

The offshore wind industry is growing, and turbines with power production of 10 MW or greater are likely to become the norm in the future for both shallow and deep waters. For up to 50 m water depth, bottom fixed structures like monopiles and jackets are considered technically and economically feasible. Beyond this water depth, floating sub-structures offer the promise of cost reduction. Synthetic fiber ropes like nylon and polyester are good candidates for mooring system designs not only for their low cost, corrosion resistance, and fatigue life compared to steel wires and chains but also for their low stiffness which can reduce the wave frequency loads on the floater, especially in shallow water. In an IOWTC 2022 paper, the present authors discussed the strength characteristics of a shallow water mooring system comprising of chain-heavy chain-polyester-chain combination. This combination was specially chosen to work in shallow water conditions (60–100 m). Using simulations, the most probable maximum values of the mooring line were presented and discussed. In this paper, fatigue analysis has been performed on a similar mooring configuration wherein we consider two synthetic material options: polyester and nylon. The IEA 10 MW reference wind turbine and a semi-submersible floating platform were used in our simulation in Nantucket, MA (Water Depth (WD) = 60m). Three different design load cases DLC 1.2, DLC 6.1, and SLC I.1 were conducted in our simulations and the mooring line fatigue damages converted to represent 25-year service life. The analysis of mooring line tension-tension fatigue damage is calculated using the T-N curves. The fatigue damage is estimated using the built-in fatigue analysis toolbox in OrcaFlex after performing a set of OrcaFlex simulation files based on different mooring line configurations and design load cases. In this work, the behavior of nylon vs. polyester in shallow water hybrid mooring applications is investigated and discussed.
Comparison of O&M Cost of Different Scenarios for a 1GW Floating Offshore Wind Farm
Authors: Zhao Chenyu , Johanning Lars
Published: January 2024

Operation and Maintenance (O&M) costs in an offshore wind project can constitute up to 30% of its total cost, a figure that can increase with the distance of the project offshore. The University of Exeter’s Renewable Energy Group developed a study utilising the O&M module of Ec simulator, which can furnish a user with critical performance indicators, to examine O&M costs under various scenarios for 1 GW floating offshore wind (FLOW) farm sites in the Celtic Sea. The simulator conducts a range of Monte Carlo simulations over the entire lifespan of the FLOW farm, considering user-specified variables and limitations such as fleet size and the vessel’s weather resilience. In this study, three different O&M cases are used to demonstrate the flexibility and functionality of the O&M module. Each case represents different wind farm selections under the exactly farm configuration, such as the capacity and numbers of the wind turbine. Results of these simulations offer a multitude of key performance indicators (KPIs), including energy production, downtime, energy-based availability and comprehensive O&M costs. It also gives more granular data, such as the number of component failures and vessel operating hours, aiding in the critical decision-making process for successful project management. The main objective of this study is to demonstrate how manipulating specific parameters can impact the viability of FLOW farms in the Celtic Sea.
Comparative Study of TLP and Semisubmersible for a 15 MW Horizontal Axis Wind Turbine (HAWT)
Authors: Huang Edward , Tang Zhaoxiang , Periyaiah Rathinam
Published: January 2024

This paper presents a conceptual design comparison between a 3-Column Tension Leg Platform (TLP) and a Semisubmersible (Semi) floating offshore wind turbine (FOWT) platform for the US west coast at a water depth of 1,100 m. The International Energy Agency (IEA) 15 MW horizontal-axis wind turbine (HAWT) is utilized to compare the floating platform design options.

TLP demonstrates exceptional dynamic behavior with very low displacements and almost no vertical/rotational motions. Its lightweight structure weight and simple geometry lend themselves to simplifying fabrication/integration processes and competitive LCOE levels.

This paper contains a quantitative comparison of TLP and Semisubmersible FOWT platforms in the following aspects:

• Applicable Design Codes

• Design environment load cases

• Platform configurations

• Hull weight and CG

• Global performance

• Tendon and mooring loads

• TLP with a slanted tendon as a sensitivity case

Additionally, it provides a qualitative comparison between the TLP and Semisubmersible FOWT platform from various perspectives, including platform configuration design, structure weight, center of gravity, fabrication, transportation, and installation (T&I) of floating substructure, station keeping, and the wind turbine installation.
Initial Global Design for Three-Column Semi-Submersible Hulls of a 15-MW Floating Wind Turbine
Authors: Wang Shuaishuai , Moan Torgeir
Published: January 2024

Support structure design of floating wind turbines (FWTs) is an iterative process, which can be accomplished into three phases, named 1) selecting of floater type (barge, semi, spar, TLP, etc.); 2) determining global dimensions for a given floater type; 3) determining scantlings of the floater based on detailed design. This study deals with the design phase 2), namely initial global design, for a three-column semi-submersible hull for a 15-MW FWT. An efficient and effective methodology, which was developed by authors in a previous study and successfully used for the global design of a 10-MW semi-submersible floater, is used in this case study. The initial global design criteria include simplified serviceability criteria related to the power performance as well as safety criteria in terms of intact stability and indirect global strength criteria through requirements to natural frequencies of rigid-body motions. First, a sensitivity study will be conducted to various design variables of the floater, including draft, column centerline spacing, outer column radius, outer pontoon radius, pontoon width and pontoon height. Based on the sensitivity study, important global design parameters are recognized for the floater, which facilitates the determination of initial design options. Subsequently, the intact stability analysis is performed for the selected design options for different wind directions. Critical load directions of the floater will be identified. In addition, the influence of deck beam dimensions and freeboard on intact stability is investigated. Finally, the global layouts of the floater are assessed based on global design criteria. This study provides new insights into the quasi-static or/and dynamic behavior of the promising FWT concept, which is essential to achieve serviceability and safety. In addition, it provides a basis for carrying out the detailed design to determine the scantlings in the third design phase.
Impact of Viscous Damping Linearization on FOWT Control Design
Authors: Fabregas Flavia Francesc , Browne Ian , Alexandre Armando , Chatzopoulos Aristeidis
Published: January 2024

Control design is traditionally carried out based on simplified linear models and subsequently tested on more realistic non-linear time domain models of a system. Issues with control performance and robustness can be introduced if the linear model is not representative of the real system, requiring additional design and testing with the realistic non-linear time domain models. This can be time consuming, and, in some cases, a satisfactory control design solution may not be achieved. It is therefore paramount to capture, in the linear model, the key physical drivers of the different system responses, which are generally referred to as states in the context of control design.

Floating Offshore Wind Turbine (FOWT) numerical models present several non-linearities, which are associated with the different sub-systems they are composed of, including the turbine, the platform and the moorings. In the context of the platform, and to some extent the mooring system, viscous nonlinear hydrodynamic damping effects have a significant impact on the response of the FOWT when subject to different environmental conditions. However, these viscous damping effects are generally not easily captured in the linear FOWT models generated by several aero-hydro-servo-elastic tools, including but not limited to BLADED and OpenFAST.

The focus of this paper is to investigate several methodologies to linearize viscous damping forces and to incorporate them in simplified linear models of FOWTs, with a strong emphasis on the initial control design phase in linear space. Two FOWT systems based on the semi-submersible DeepCWind (OC4), and VolturnUS-S platforms are investigated, with 5MW and 15MW ratings respectively. Results show that the impact of linearized viscous damping may depend on system size, and that some degrees of freedom may be more sensitive than others to the methodology used to linearize viscous damping.
Wake Effects on Multiline Anchor Loads for Floating Offshore Wind Turbines
Authors: Balakrishnan Krishnaveni , Arwade Sanjay , DeGroot Don
Published: January 2024

This paper studies the influence of wake effects on multiline anchor mooring line forces for floating offshore wind turbines for different environmental scenarios. Multiline anchoring is a concept in which seabed anchors are shared among three adjacent turbines through their mooring lines. In this scenario, one or more adjacent turbines could be in the downstream wind direction. In an offshore wind farm, the turbines in the downstream position experience lower wind speed and higher turbulence intensity because of the wake disturbances caused by the upstream turbines. Therefore, the multiline anchor system must be evaluated for each location for a given wind farm configuration. This paper studies five NREL 5MW turbines supported by OC3 Hywind spar buoys in the Hywind Scotland wind farm layout. Wind wake effects are predominant when the turbines are operating. Therefore, the operational design load case DLC1.6 is chosen for the analysis with three different environmental loading directions. NREL open-source tool FAST is used to perform the simulations. Jensen’s wake model and Frandsen’s Turbulence intensity (TI) model are employed to calculate the waked downstream turbine parameters such as reduced wind velocity and turbulence intensity. For each of the wind wave current directions, a case with wake and without wake has been studied. The result from each study is observed as peak multiline anchor force, which is the average of the maxima from six one-hour simulations. In the case of 30° and 120° load directions, one of the downstream turbines in the multiline system is experiencing wake effects, whereas in the case of 90°, two of the turbines are experiencing wake effects. Results show that the multiline system exhibited less tension with waked wind, resulting in decreased mooring line forces compared to cases without wake.
Streamlined Loads Analysis of Floating Wind Turbines With Fiber Rope Mooring Lines
Authors: Hall Matthew , Duong Brian , Lozon Ericka
Published: January 2024

This paper presents an approach for more accurate yet relatively streamlined accounting for the nonlinear characteristics of synthetic fiber rope mooring lines for floating wind turbines. First, we select a minimal set of parameters that can efficiently approximate a mooring line material’s quasi-static and dynamic stiffness characteristics. We also develop a set of baseline coefficients for different rope materials based on published product information and research papers. We then expand a quasi-static mooring model to include dynamic mooring line stiffness terms in a way that allows the nonlinear stiffness behavior of fiber ropes to be considered even in quasi-static analyses. For dynamic analysis, we have updated the model MoorDyn, coupled with OpenFAST, to work with the new dynamic mooring line stiffness terms. This includes the implementation of a new viscoelastic approach that allows the tension-strain relation of each mooring line segment to vary between two stiffness values, depending on the strain rate. After presenting the formulation of the approaches for modeling synthetic ropes, they are demonstrated on a floating wind turbine mooring system with taut polyester rope mooring lines. The results are compared with those of other approaches of similar fidelity, including the static-dynamic method and separate simulations with static and dynamic stiffness values. Comparing the results shows the ability of the new method to match the results of the previous methods in a more streamlined manner.
Effect of Training Model on the Physical Condition of Young Female Football Players
Authors: Pérez-Muñoz Salvador , Alonso García Gema , Benito García Laura , Rodríguez-Cayetano Alberto
Published: January 2024

The aim of the study was to analyze the impact of two training models—the traditional methodology and an alternative or nonlinear mixed methodology—on coordination, speed, and changes of direction (COD) in U-12 football players. The subjects were divided into two groups: a traditional group of 11 female players and a second group of 14 female players, which followed a mixed methodology. Ten training sessions of 30 min were carried out focusing on motor coordination and COD. The variables analyzed were motor coordination with the SportComp test, COD with the Modified Agility test, and the Suttle Sprint and Dribbling test, with and without the ball, and speed over 30 m, with and without the ball. Overall, improvements were obtained in the mixed training program, leading to significant improvements (p < .05) in the variables of motor coordination, speed, and COD, with a large effect size. Therefore, coaches and physical trainers, taking into account that it causes greater benefits in the physical condition of female football players in training, than the traditional training program, can use the mixed training program.
Ground penetrating radar observations of the contact between the western delta and the crater floor of Jezero crater, Mars
Authors: Paige David A. , Hamran Svein-Erik , Amundsen Hans E. F. , Berger Tor , Russell Patrick , Kakaria Reva , Mellon Michael T. , Eide Sigurd , Carter Lynn M. , Casademont Titus M. , Nunes Daniel C. , Shoemaker Emileigh S. , Plettemeier Dirk , Dypvik Henning , Holm-Alwmark Sanna , Horgan Briony H. N.
Published: January 2024

The delta deposits in Jezero crater contain sedimentary records of potentially habitable conditions on Mars. NASA’s Perseverance rover is exploring the Jezero western delta with a suite of instruments that include the RIMFAX ground penetrating radar, which provides continuous subsurface images that probe up to 20 meters below the rover. As Perseverance traversed across the contact between the Jezero crater floor and the delta, RIMFAX detected a distinct discontinuity in the subsurface layer structure. Below the contact boundary are older crater floor units exhibiting discontinuous inclined layering. Above the contact boundary are younger basal delta units exhibiting regular horizontal layering. At one location, there is a clear unconformity between the crater floor and delta layers, which implies that the crater floor experienced a period of erosion before the deposition of the overlying delta strata. The regularity and horizontality of the basal delta sediments observed in the radar cross sections indicate that they were deposited in a low-energy lake environment.
Nanoparticulate apatite and greenalite in oldest, well-preserved hydrothermal vent precipitates
Authors: Rasmussen Birger , Muhling Janet R. , Tosca Nicholas J.
Published: January 2024

Paleoarchean jaspilites are used to track ancient ocean chemistry and photoautotrophy because they contain hematite interpreted to have formed following biological oxidation of vent-derived Fe(II) and seawater P-scavenging. However, recent studies have triggered debate about ancient seawater Fe and P deposition. Here, we report greenalite and fluorapatite (FAP) nanoparticles in the oldest, well-preserved jaspilites from the ~3.5-billion-year Dresser Formation, Pilbara Craton, Australia. We argue that both phases are vent plume particles, whereas coexisting hematite is linked to secondary oxidation. Geochemical modeling predicts that hydrothermal alteration of seafloor basalts by anoxic, sulfate-free seawater releases Fe(II) and P that simultaneously precipitate as greenalite and FAP upon venting. The formation, transport, and preservation of FAP nanoparticles indicate that seawater P concentrations were ≥1 to 2 orders of magnitude higher than in modern deepwater. We speculate that Archean seafloor vents were nanoparticle “factories” that, on prebiotic Earth, produced countless Fe(II)- and P-rich templates available for catalysis and biosynthesis.
Field-controlled dynamics of skyrmions and monopoles
Authors: Tai Jung-Shen B. , Hess Andrew J. , Wu Jin-Sheng , Smalyukh Ivan I.
Published: January 2024

Magnetic monopoles, despite their ongoing experimental search as elementary particles, have inspired the discovery of analogous excitations in condensed matter systems. In chiral condensed matter systems, emergent monopoles are responsible for the onset of transitions between topologically distinct states and phases, such as in the case of transitions from helical and conical phase to A-phase comprising periodic arrays of skyrmions. By combining numerical modeling and optical characterizations, we describe how different geometrical configurations of skyrmions terminating at monopoles can be realized in liquid crystals and liquid crystal ferromagnets. We demonstrate how these complex structures can be effectively manipulated by external magnetic and electric fields. Furthermore, we discuss how our findings may hint at similar dynamics in other physical systems and their potential applications.
The E3 ligase TRIM22 restricts SARS-CoV-2 replication by promoting proteasomal degradation of NSP8
Authors: Fan Lujie , Zhou Yuzheng , Wei Xiafei , Feng Wei , Guo Huimin , Li Yunfei , Gao Xiang , Zhou Jian , Wen Yanling , Wu Yezi , Shen Xiaotong , Liu Lei , Xu Gang , Zhang Zheng
Published: January 2024

Non-structural proteins (NSPs) play a crucial role in the replication of severe acute respiratory syndrome coronavirus 2, facilitating virus amplification and propagation. In this study, we conducted a comprehensive investigation into the stability of all subunits comprising the RNA-dependent RNA polymerase complex. Notably, our results reveal for the first time that NSP8 is a relatively unstable protein, which is found to be readily recognized and degraded by the proteasome. This degradation process is mediated by the host E3 ligase tripartite motif containing 22 (TRIM22), which is also a member of the interferon stimulated gene (ISG) family. Our study elucidates a novel mechanism of antiviral effect of TRIM22, which utilizes its own E3 ubiquitin ligase activity to hinder viral replication by inducing ubiquitination and subsequent degradation of NSP8. These findings provide new ideas for the development of novel therapeutic strategies. In addition, the conserved property of NSP8 raises the possibility of developing broad antiviral drugs targeting the TRIM22-NSP8 interaction.
MEndoB, a chimeric lysin featuring a novel domain architecture and superior activity for the treatment of staphylococcal infections
Authors: Roehrig Christian , Huemer Markus , Lorgé Dominique , Arn Fabienne , Heinrich Nadine , Selvakumar Lavanja , Gasser Lynn , Hauswirth Patrick , Chang Chun-Chi , Schweizer Tiziano A. , Eichenseher Fritz , Lehmann Steffi , Zinkernagel Annelies S. , Schmelcher Mathias
Published: January 2024

One of the most pressing challenges of our era is the rising occurrence of bacteria that are resistant to antibiotics. Staphylococci are prominent pathogens in humans, which have developed multiple strategies to evade the effects of antibiotics. Infections caused by these bacteria have resulted in a high burden on the health care system and a significant loss of lives. In this study, we have successfully engineered lytic enzymes that exhibit an extraordinary ability to eradicate staphylococci. Our findings substantiate the importance of meticulous lead candidate selection to identify therapeutically promising peptidoglycan hydrolases with unprecedented activity. Hence, they offer a promising new avenue for treating staphylococcal infections.
Supplemental Material: Constraining the provenance of black shales using rare earth elements and neodymium isotopes, Midcontinent United States
Authors: Morris Noah , et al.
Published: January 2024

Table S1: Locality information for each sample. Table S2: Detailed mineralogical compositions of each sample based on X-ray diffraction measurements. Table S3: Trace-element concentrations in each sample (in ppm). Table S4: Trace-element concentration uncertainty (1σ). Table S5: Calculated dissimilarity values of each sample relative to other samples. Lower values correspond with increasing similarity in rare earth element patterns.
Synthesis and Properties of (+)-Ketopinic and (–)-Camphanic Acids Esters Bearing a Nitrogen-Containing Heterocycle
Authors: Sokolova A. S. , Yarovaya O. I. , Kuzminykh L. V. , Ilyina M. G. , Borisevich S. S. , Esaulkova Ya. L. , Zarubaev V. V. , Salakhutdinov N. F.
Published: January 2024

A three-stage method was proposed for the synthesis of (1S)-(+)-camphor-10-sulfonic acid, (+)-ketopinic and (–)-camphanic acids esters containing a saturated nitrogen-containing heterocycle. It was found that (1S)-(+)-camphor-10-sulfonic acid esters undergo destruction with elimination of the sulfonic acid group in substitution reactions involving nitrogen-containing heterocycles. Esters of (+)-ketopinic and (–)-camphanic acids were formed during the proposed synthetic route, but undergo transesterification under column chromatography conditions. Quantum chemical calculations showed that the destruction of the ester bond in the case of (+)-ketopinic and (–)-camphanic acids requires less energy than the breaking of a similar bond in (–)-borneol esters. It was revealed that the internal bond strength index (IBSI) for the alkyl C–O bond in (–)-borneol esters is higher than in (+)-ketopinic and (–)-camphanic acid esters. Antiviral properties against the H1N1 influenza virus were studied for derivatives of (+)-ketopinic and (–)-camphanic acids.
Prospects for $$B_c^+$$ and $$B^+\rightarrow \tau ^+ \nu _\tau $$ at FCC-ee
Authors: Zuo Xunwu , Fedele Marco , Helsens Clément , Hill Donal , Iguro Syuhei , Klute Markus
Published: January 2024

The prospects are presented for precise measurements of the branching ratios of the purely leptonic $$B_c^+ \rightarrow \tau ^+ \nu _\tau $$

B
c
+

→

τ
+

ν
τ

and $$B^+ \rightarrow \tau ^+ \nu _\tau $$

B
+

→

τ
+

ν
τ

decays at the Future Circular Collider (FCC). This work is focused on the hadronic $$\tau ^{+} \rightarrow \pi ^+ \pi ^+ \pi ^- {\bar{\nu }}_\tau $$

τ
+

→

π
+

π
+

π
-

ν

¯

τ

decay in both $$B_c^+ \rightarrow \tau ^+ \nu _\tau $$

B
c
+

→

τ
+

ν
τ

and $$B^+ \rightarrow \tau ^+ \nu _\tau $$

B
+

→

τ
+

ν
τ

processes. Events are selected with two Boosted Decision Tree algorithms to optimise the separation between the two signal processes as well as the generic hadronic Z decay backgrounds. The range of the expected precision for both signals are evaluated in different scenarios of non-ideal background modelling. This paper demonstrates, for the first time, that the $$B^+ \rightarrow \tau ^+ \nu _\tau $$

B
+

→

τ
+

ν
τ

decay can be well separated from both $$B_c^+ \rightarrow \tau ^+ \nu _\tau $$

B
c
+

→

τ
+

ν
τ

and generic $$Z\rightarrow b{\bar{b}}$$

Z
→
b

b

¯

processes in the FCC-ee collision environment and proposes the corresponding branching ratio measurement as a novel way to determine the CKM matrix element $$|V_{ub}|$$

|

V

ub

|

. The theoretical impacts of both $$B^+ \rightarrow \tau ^+ \nu _\tau $$

B
+

→

τ
+

ν
τ

and $$B_c^+ \rightarrow \tau ^+ \nu _\tau $$

B
c
+

→

τ
+

ν
τ

measurements on New Physics cases are discussed for interpretations in the generic Two-Higgs-doublet model and leptoquark models.
Late time cosmological solutions in f(R,T) gravity in a viscous universe
Authors: Shabani Hamid , Cruz Norman , Ziaie Amir Hadi
Published: January 2024

Considering the condition on conservation of energy–momentum tensor (EMT), we study late time cosmological solutions in the context of [Formula: see text] gravity (where [Formula: see text] and n are constants) in a flat Friedmann–Lemaître–Robertson–Walker (FLRW) spacetime. The present model discusses the case of a barotropic perfect fluid as the matter content of the Universe, along with the case when dissipative effects are taken into account. Briefly, assuming a single perfect fluid, we find that the mentioned model is not capable of presenting an observationally consistent picture of the late time accelerated expansion of the Universe; nevertheless, the model leads to admissible solutions when the bulk viscosity is included. In this regard, a consistent setting is found considering the Eckart, Truncated and Full Israel–Stewart theories which determine the behavior of bulk viscosity. In the presence of bulk viscosity, the behavior of the deceleration parameter (DP) shows that the underlying model can describe an acceptable evolution even if the isotropic pressure of matter content of the Universe is negligible.
A comparative analysis of spherically and cylindrically shaped nanoparticles containing nanofluid flows over a permeable rotating disk affected by nanoparticles radius and nanolayer
Authors: Ramzan Muhammad , Shahmir Nazia , Kadry Seifedine , Saleel C Ahamed
Published: January 2024

The aim of this paper is to present a comparative analysis of spherically and cylindrically shaped nanoparticles immersed separately in a graphene oxide/water nanofluid mixture over a rotating disk influenced by Hall current. The disk’s surface is permeable with suction/injection impact. In order to reveal the thermal integrity of the flow, the effect of nanoparticle diameter and the liquid–solid interfacial layer at the molecular level is also introduced. Estimates of thermal conductivity, interfacial layer thickness and the radius of both spherical and cylindrical particles are taken from experimental studies and utilized to investigate the thermal behavior of the flows. The Tiwari–Das model for nanofluid flow is considered that incorporates the thermal radiative impact in the energy equation. The equations obeying boundary layer theory are resolved to ordinary differential equations using a transformation, and further numerically computed with the bvp4c scheme. The velocities and the temperature profiles are graphically demonstrated versus the dimensionless parameters. Quantities of physical interest such as surface heat flux and surface drag coefficient are tabulated numerically. The results show that the surface drag is larger for nanofluids having cylindrical particles than for nanofluids containing spherical particles. Is also found that the heat transfer rate is greater for nanofluids containing cylindrical particles than spherical particles at higher interfacial layer thicknesses.
Hermitian Dynamic Mode Decomposition - Numerical Analysis and Software Solution
Authors: Drmač Zlatko
Published: January 2024

The Dynamic Mode Decomposition (DMD) is a versatile and increasingly popular method for data driven analysis of dynamical systems that arise in a variety of applications in, e.g., computational fluid dynamics, robotics or machine learning. In the framework of numerical linear algebra, it is a data driven Rayleigh-Ritz procedure applied to a DMD matrix that is derived from the supplied data. In some applications, the physics of the underlying problem implies hermiticity of the DMD matrix, so the general DMD procedure is not computationally optimal. Furthermore, it does not guarantee important structural properties of the Hermitian eigenvalue problem and may return non-physical solutions. This paper proposes a software solution to the Hermitian (including the real symmetric) DMD matrices, accompanied with a numerical analysis that contains several fine and instructive numerical details. The eigenpairs are computed together with their residuals, and perturbation theory provides error bounds for the eigenvalues and eigenvectors. The software is developed and tested using the
LAPACK
package.
Mechanism-Driven Design of Multispecific Antibodies for Targeted Disease Treatment
Authors: Fine Justyn , Meksiriporn Bunyarit , Tan Jiacheng , Spangler Jamie B.
Published: January 2024

Antibody-based therapeutics constitute a rapidly growing class of pharmaceutical compounds. However, monoclonal antibodies, which specifically engage only one target, often lack the mechanistic intricacy to treat complex diseases. To expand the utility of antibody therapies, significant efforts have been invested in designing multispecific antibodies, which engage multiple targets using a single molecule. These efforts have culminated in remarkable translational progress, including nine US Food and Drug Administration–approved multispecific antibodies, with countless others in various stages of preclinical or clinical development. In this review, we discuss several categories of multispecific antibodies that have achieved clinical approval or shown promise in earlier stages of development. We focus on the molecular mechanisms used by multispecific antibodies and how these mechanisms inform their customized design and formulation. In particular, we discuss multispecific antibodies that target multiple disease markers, multiparatopic antibodies, and immune-interfacing antibodies. Overall, these innovative multispecific antibody designs are fueling exciting advances across the immunotherapeutic landscape.
Sample Processing and Concentration Methods for Viruses from Foods and the Environment Prior to Detection
Authors: Stoufer Sloane , Soorneedi Anand R. , Kim Minji , Moore Matthew D.
Published: January 2024

Viruses are the leading cause of foodborne illness globally. Concentration of viruses from samples is important for detection because viral contamination of foods often occurs at low levels. In general, virus concentration methods can be classified as either nonspecific, exploiting the relatively homogeneous physicochemical properties of the virus to separate/concentrate it from the sample matrix, or specific, relying on recognition elements such as antibodies to specifically capture and separate viruses from foods. Numerous nonspecific and specific techniques for virus concentration have been reported, each with its own advantages and limitations. Factors to consider can include reagent and equipment costs, time-to-result, ease of use, and potential to eliminate matrix-associated inhibitors. The purpose of this review is to survey the different foodborne virus concentration techniques and their efficacy in various food and environmental matrices as well as discuss some emerging techniques for purification and concentration of viral pathogens from food samples.
Systemic Immune Modulation by Gastrointestinal Nematodes
Authors: Kasal Darshan N. , Warner Lindsey M. , Bryant Astra S. , Tait Wojno Elia , von Moltke Jakob
Published: January 2024

Gastrointestinal nematode (GIN) infection has applied significant evolutionary pressure to the mammalian immune system and remains a global economic and human health burden. Upon infection, type 2 immune sentinels activate a common antihelminth response that mobilizes and remodels the intestinal tissue for effector function; however, there is growing appreciation of the impact GIN infection also has on the distal tissue immune state. Indeed, this effect is observed even in tissues through which GINs never transit. This review highlights how GIN infection modulates systemic immunity through (a) induction of host resistance and tolerance responses, (b) secretion of immunomodulatory products, and (c) interaction with the intestinal microbiome. It also discusses the direct consequences that changes to distal tissue immunity can have for concurrent and subsequent infection, chronic noncommunicable diseases, and vaccination efficacy.
Data from Histone Demethylase JMJD1A Promotes Tumor Progression via Activating Snail in Prostate Cancer
Authors: Tang Dong-E , Dai Yong , Xu Song-Hui
Published: January 2024

Abstract
The histone demethylase JMJD1A plays a key functional role in spermatogenesis, sex determination, stem cell renewal, and cancer via removing mono- and di-methyl groups from H3K9 to epigenetically control gene expression. However, its role in prostate cancer progression remains unclear. Here, we found JMJD1A was significantly elevated in prostate cancer tissue compared with matched normal tissue. Ectopic JMJD1A expression in prostate cancer cells promoted proliferation, migration, and invasion in vitro, and tumorigenesis in vivo; JMJD1A knockdown exhibited the opposite effects. Mechanically, we revealed that JMJD1A directly interacted with the Snail gene promoter and regulated its transcriptional activity, promoting prostate cancer progression both in vitro and in vivo. Furthermore, we found that JMJD1A transcriptionally activated Snail expression via H3K9me1 and H3K9me2 demethylation at its special promoter region. In summary, our studies reveal JMJD1A plays an important role in regulating proliferation and progression of prostate cancer cells though Snail, and thus highlight JMJD1A as potential therapeutic target for advanced prostate cancer.
Implications:
Our studies identify that JMJD1A promotes the proliferation and progression of prostate cancer cells through enabling Snail transcriptional activation, and thus highlight JMJD1A as potential therapeutic target for advanced prostate cancer.
Supplementary Table 6 from Exploring Co-occurring POLE Exonuclease and Non-exonuclease Domain Mutations and Their Impact on Tumor Mutagenicity
Authors: Shah Shreya M. , Demidova Elena V. , Ringenbach Salena , Faezov Bulat , Andrake Mark , Gandhi Arjun , Mur Pilar , Viana-Errasti Julen , Xiu Joanne , Swensen Jeffrey , Valle Laura , Dunbrack Roland L. , Hall Michael J. , Arora Sanjeevani
Published: January 2024

Rosetta ΔΔG values for POLE variants and drivers with or without DNA
Supplementary Table 2 from Exploring Co-occurring POLE Exonuclease and Non-exonuclease Domain Mutations and Their Impact on Tumor Mutagenicity
Authors: Shah Shreya M. , Demidova Elena V. , Ringenbach Salena , Faezov Bulat , Andrake Mark , Gandhi Arjun , Mur Pilar , Viana-Errasti Julen , Xiu Joanne , Swensen Jeffrey , Valle Laura , Dunbrack Roland L. , Hall Michael J. , Arora Sanjeevani
Published: January 2024

Age Distribution of CRC, EC, and OC patients with POLE-mutated tumors.
Atopische Dermatitis: Dupilumab-Einsatz ab dem 6. Lebensmonat – Wirksamkeit und Sicherheit in der Praxis
Authors: Fölster-Holst Regina
Published: January 2024

Background and objective: Previous studies of dupilumab for the treatment of moderate-to-severe atopic dermatitis in adults and adolescents, and severe atopic dermatitis in children aged 6 to < 12 years demonstrate no clinically important changes in laboratory parameters. The objective of this study was to assess laboratory outcomes in children aged 6 months to < 6 years with moderate-to-severe atopic dermatitis treated with dupilumab. Methods: In this randomized, placebo-controlled, phase III trial of dupilumab, 161 children aged 6 months to < 6 years with moderate-to-severe atopic dermatitis were enrolled from 31 sites in Europe and North America and randomized 1:1 to receive subcutaneous placebo or dupilumab (5 kg to < 15 kg: 200 mg; 15 kg to < 30 kg: 300 mg) every 4 weeks plus topical corticosteroids for 16 weeks. Hematology, serum chemistry, and urinalysis assessments were analyzed on blood and urine samples collected at screening and weeks 4 and 16; descriptive statistics are provided. Results: No clinically meaningful changes in laboratory parameters were observed. While two cases of eosinophilia and one case each of neutropenia and leukocytosis were reported as treatment-emergent adverse events in the dupilumab plus topical corticosteroids group, these events were not associated with clinical symptoms and did not lead to treatment discontinuation or study withdrawal. Clinical trial registration: ClinicalTrials.gov: NCT03346434, part B.
Machine learning-based electricity theft detection using support vector machines
Authors: Abro Safdar Ali , Hua Lyu Guang , Laghari Javed Ahmed , Bhayo Muhammad Akram , Memon Abdul Aziz
Published: January 2024

Electricity theft is a serious issue that many nations face, especially in developing areas where non-technical losses can make up a significant percentage of the overall losses sustained by utilities. Electricity theft detection (ETD) is a very challenging task because it frequently introduces irregularities in customer electricity consumption patterns. In recent times, machine learning (ML) techniques have been investigated as a potential solution for ETD. In this research, author propose electricity theft detection based on four kernel functions of support vector machines (SVM). The proposed method analyzes the electricity consumption patterns and then predicts the category of the user. The kernel functions utilized includes polynomial, sigmoid, radial basis function (RBF) and linear kernel function. For experimentation and model training, a dataset of Pakistani utility company is used, which contains the electricity consumption information. The results highlight SVM method works well for accurate ETD. The detection accuracy of the various kernel functions of SVM is 83%, 79%, 80%, and 76% for RBF, polynomial, sigmoid, and linear kernel functions, respectively, demonstrating the effectiveness of the proposed SVM-based method for theft detection. By leveraging these ML-based methods, utility companies can strengthen their ability to detect and prevent electricity theft, leading to improved revenue management and dependability of services.
Research on the impact of sliding window and differencing procedures on the support vector regression model for load forecasting
Authors: Tran Thanh Ngoc , Dang Thi Phuc , Lam Binh Minh , Nguyen Anh Tuan
Published: January 2024

Load forecasting is a critical aspect of energy management and grid operations. Machine learning techniques as support vector regression (SVR), have been widely used for load forecasting. However, the effectiveness of SVR is highly dependent on its hyperparameters, including the error sensitivity parameter, penalty factor, and kernel function. Furthermore, as the load data follows a time series pattern, the accuracy of the SVR model is influenced by the data's characteristics. In this regard, the present study aims to investigate the impact of combining the sliding window procedure and differencing the input data on the prediction accuracy of the SVR model. The study utilizes daily maximum load data from the Queensland and Victoria states in Australia. The analyses revealed that while the sliding window procedure had a minimal impact on the prediction results, the differencing of the input data significantly improved the accuracy of the predictions.
Hardware-in-the-loop setup for enhanced modular multi-level converter with reduced circulating currents
Authors: Soomro Jahangeer Badar , Ali Khawaja Haider , Memon Abdul Aziz
Published: January 2024

Owing to its essential features, such as modularity and exceptional power quality, the modular multilevel converter (MMC) emerges as the optimal converter topology for high-voltage direct current (HVDC) applications. Traditionally, MMCs are controlled through a method called nearest level modulation (NLM), which generates N+1 AC output voltages, where N represents the number of sub modules (SMs) per arm. In this paper, we introduce a modified NLM technique designed to yield 2N+1 and 4N+1 levels, with a focus on efficiently controlling internal dynamics. The proposed MMC is evaluated using a hardware-in-the-loop (HIL) environment to obtain real-time simulation outcomes. This MMC topology demonstrates a reduction in circulating currents and capacitor voltage ripple.
Integrated application of synergetic approach for enhancing intelligent steam generator control systems
Authors: Isamiddin Siddikov , Dilnoza Umurzakova
Published: January 2024

This article focuses on the integrated application of the synergetic approach to enhance the quality of intelligent steam generator control systems.By combining various techniques such as model-based control, adaptive control, and artificial intelligence, an efficient and flexible control system can be developed. Model-based control utilizes mathematical models of steam generators to formulate control algorithms and predict system behavior. Adaptive control enables the system to adapt to changing conditions by adjusting control parameters based on real-time measurements. Artificial intelligence techniques, including neural networks and genetic algorithms, facilitate learning, optimization, and data-driven decision-making processes. The objectives of this research are to investigate the benefits of the synergetic approach in steam generator control, including improved steam generation efficiency, optimized energy consumption, enhanced system stability and reliability, and adaptability to varying operating conditions and disturbances. The findings and conclusions of this study are expected to provide valuable insights for engineers, researchers, and professionals involved in the design and implementation of intelligent steam generator control systems. By integrating the synergetic approach, substantial enhancements in control quality can be achieved, leading to optimal operation and maximum efficiency of power plants.
Three layer hybrid learning to improve intrusion detection system performance
Authors: Harwahyu Ruki , Erasmus Ndolu Fajar Henri , Overbeek Marlinda Vasty
Published: January 2024

In imbalanced network traffic, malicious cyberattacks can be hidden in a large amount of normal traffic, making it difficult for intrusion detection systems (IDS) to detect them. Therefore, anomaly-based IDS with machine learning is the solution. However, a single machine learning cannot accurately detect all types of attacks. Therefore, a hybrid model that combines long short-term memory (LSTM) and random forest (RF) in three layers is proposed. Building the hybrid model starts with Nearmiss-2 class balancing, which reduces normal samples without increasing minority samples. Then, feature selection is performed using chi-square and RF. Next, hyperparameter tuning is performed to obtain the optimal model. In the first and second layers, LSTM and RF are used for binary classification to detect normal data and attack data. While the third layer model uses RF for multiclass classification. The hybrid model verified using the CSE-CIC-IDS2018 dataset, showed better performance compared to the single algorithm. For multiclass classification, the hybrid model achieved 99.76% accuracy, 99.76% precision, 99.76% recall, and 99.75% F1-score.
Predictive analysis of terrorist activities in Thailand's Southern provinces: a deep learning approach
Authors: Ganokratanaa Thittaporn , Ketcham Mahasak
Published: January 2024

Terrorist activities have been on the rise globally, with Thailand experiencing significant challenges, particularly in its three southern border provinces. This study offers a comprehensive analysis aiming to predict forthcoming terrorist events in these provinces. We employed historical data, categorized into nine groups based on military expert recommendations, to train our prediction model. This research tested the prediction capabilities of various methodologies, including decision trees, naïve Bayesian learning techniques, and deep learning artificial neural networks. Notably, the deep neural network emerged as the superior predictive tool, achieving an impressive accuracy of 98.21% and a root mean square error (RMSE) of 0.59%. The primary anticipated events include bombings, shootings, assaults, and acts of vandalism. Our findings also revealed that Pattani Province was the most affected, accounting for 45% of incidents. Specific districts, such as Panare and Yarang, exhibited high crime rates of 40% and 36.84%, respectively. Yala Province, particularly Bannang Sata District, was identified as the hotspot for shooting incidents, with a rate of 34%.
An advanced ensemble load balancing approach for fog computing applications
Authors: Ravi Kiran Koppolu , Lokesh Sai Kumar Dasari , Esther Jyothi Veerapaneni , Ha Huy Cuon Nguyen , Hoang Ha Nguyen
Published: January 2024

Fog computing has emerged as a viable concept for expanding the capabilities of cloud computing to the periphery of the network allowing for efficient data processing and analysis from internet of things (IoT) devices. Load balancing is essential in fog computing because it ensures optimal resource utilization and performance among distributed fog nodes. This paper proposed an ensemble-based load-balancing approach for fog computing environments. An advanced ensemble load balancing approach (AELBA) uses real-time monitoring and analysis of fog node metrics, such as resource utilization, network congestion, and service response times, to facilitate effective load distribution. Based on the ensemble's collective decision-making, these metrics are fed into a centralized load-balancing controller, which dynamically adjusts the load distribution across fog nodes. Performance of the proposed ensemble load-balancing approach is evaluated and compared it to traditional load-balancing techniques in fog using extensive simulation experiments. The results demonstrate that our ensemble-based approach outperforms individual load-balancing algorithms regarding response time, resource utilization, and scalability. It adapts to dynamic fog environments, providing efficient load balancing even under varying workload conditions.
System call frequency analysis-based generative adversarial network model for zero-day detection on mobile devices
Authors: Chhaybi Akram , Lazaar Saiida
Published: January 2024

In today's digital age, mobile applications have become essential in connecting people from diverse domains. They play a crucial role in enabling communication, facilitating business transactions, and providing access to a range of services. Mobile communication is widespread due to its portability and ease of use, with an increasing number of mobile devices projected to reach 18.22 billion by the end of 2025. However, this convenience comes at a cost, as cybercriminals are constantly looking for ways to exploit security vulnerabilities in mobile applications. Among the several varieties of malicious applications, zero-day malware is particularly dangerous since it cannot be removed by antivirus software. To detect zero-day Android malware, this paper introduces a novel approach based on generative adversarial networks (GANs), which generates new frequencies of feature vectors from system calls. In the proposed approach, the generator is fed with a mixture of real samples and noise, and then trained to create new samples, while the discriminator model aims to classify these samples as either real or fake. We assess the performance of our model through different measures, including loss functions, the Frechet Inception distance, and the inception score evaluation metrics.