Essential Structure Research Articles

A Comprehensive Review on Different Aspects on Current Scenario of Analysis of Box Culvert

Abstract: Box culverts serve as essential structure for drainage relief, water passage and traffic route under roads. They have been constructed in various shapes and sizes, accommodating different waterway and traffic needs. This review paper provides an in-depth analysis of various research papers associated with the topic of box culvert and its various advancements. Through a thorough literature review and analysis of previous works in this field, this study has identified conclusive outcomes that form the basis of our research objectives for checking the box culvert with different skew angles along with different S/H ratios for 2 cell box culvert and aim to provide technical insights and recommendations for future research in this area.

The behaviour of a forced spherical pendulum operating in a weightless environment

Summary In this article, we show that by subjecting the pivot of a simple inextensible pendulum to small amplitude high frequency rectilinear oscillations it is possible to make it operate in a weightless environment. The axis of vibration of the pivot defines a preferred direction in space and a consequential dynamical structure which is completely absent when the pivot is fixed. Using spherical polar coordinates centred at the pivot, we show that the motion of such a pendulum has fast and slow-scale components which we analyse using the method of multiple scales. The slow scale equation for the polar angle is autonomous, and a phase plane analysis reveals the essential orbital structure including the existence of conical solutions analogous to the terrestrial fixed pivot conical pendulum. In the absence of an azimuthal velocity component, its behaviour can provide a direct simulation of a plane terrestrial simple fixed pivot pendulum with a correspondingly simple form for the small amplitude period. We can also use a two-scale analysis to examine the effects of damping. Here, the slow scale polar equation has two asymptotically stable states, and we employ a combination of numerical and asymptotic analyses to elicit the slow scale orbital trajectories.

Theoretical and practical approach to the essential characteristics and structure of digital ecosystems of industrial enterprises

Our scientific article is devoted to the study of the essential characteristics and structure of digital ecosystems of industrial enterprises based on the applied theoretical and practical approach. In particular, the author’s definitions of the concepts «digital platform» and «digital ecosystem of an industrial enterprise» were given, the distinctive features and advantages of using digital ecosystems, including within the framework of industrial production, were highlighted, the conceptual structure of the digital ecosystem of an industrial enterprise was developed and presented, the examples of practical implementation of digital ecosystems at industrial enterprises in Kazakhstan and neighbouring countries were considered. We also carried out a scientometric analysis of publications based on the using of materials from the Web of Knowledge database (Web of Science Core Collection) for 1992-2024 using the capabilities of the VOSviewer software product to build thematic frames in the context of three search queries: 1. ««digital ecosystem» and «industry»»; 2. ««digital platform» and «digital transformation»»; 3. ««Digital transformation» and «Industry 4.0»». The final sample within each of the search formulas was: 1859, 3259 and 689 publications, respectively. The article has developed a comprehensive and adaptive proprietary methodology for conducting scientometric analysis (created taking into account PRISMA recommendations, ensuring validation of the research procedure used in the research), including both the main stages of obtaining a data array and their subsequent analysis based on the specialized software product VOSviewer with the construction of the final frame clusters according to the following criteria: Co-Authorship Analysis, Co-Occurrence Analysis.

Chlamydospore dormancy and predatory activity of nematophagous fungus Duddingtonia flagrans.

The chlamydospores of Duddingtonia flagrans are an essential survival and reproductive structure and also an effective ingredient for the biocontrol of parasitic nematodes in livestock. In this study, entering and exiting dormancy conditions and predatory activity of the fungal chlamydospores were conducted. During this fungal growth process, the cultivation time is negatively correlated with spore germination rates. After the spores were processed by vacuum drying for 168 h, their germination rate dropped to 0.94%. In contrast, the percentage of living spores remained 54.82%, suggesting that the spores entered structural dormancy in the arid environment. Meanwhile, the efficacies of the spore against Haemonchus contortus larvae were 93.05% (0 h), 92.19% (16 h), 92.77% (96 h), and 86.45% (168 h), respectively. After dormant spores were stored at 4°C, -20°C, and 28°C (RH90 ~ 95%) for 7 days, their germination rate began to increase significantly (p < 0.05). For in vitro predation assay under the condition of 28°C (RH90 ~ 95%), the predation rate was significantly higher on the 7th day after incubation than that on the 3rd day (p < 0.05). During the period when spores were stored at room temperature for 8 months, their germination rate decreased in the first 5 months and then increased slowly to reach a peak in the 7th month. However, the reduction rate of H. contortus L3 in feces captured by spores remained above 71% for the first 7 months. These results will help us increase the end products yield and the quality of biological control of parasitic nematodes in livestock.

“A Certainty for you Does Not Mean That it is a Certainty for Science”: A Phenomenological Analysis of Experiences of Uncertainty in Clinical Reasoning of Nurses in the Postanesthesia Care Unit

PurposeTo explore the experiences of uncertainty in the clinical reasoning of nurses in the postanesthesia care unit (PACU). DesignA phenomenological descriptive design, following Colaizzi's analysis. MethodsSemistructured interviews were conducted with 14 nurses from a PACU on their experience of uncertainty in clinical reasoning. The interviews were digitally audio-recorded and transcribed verbatim. Two researchers conducted data analysis independently and followed seven phases: (re)reading the transcripts, extracting significant statements, formulating meanings from significant statements, aggregating formulated meanings into themes, developing a description of the phenomenon’s essential structure, generating of the fundamental structure of the phenomenon, validating of the findings through participant feedback. The process employed MAXQDA analytics Pro 2022 software. Consolidated Criteria for Reporting A Qualitative Research checklist was used for reporting. FindingsFrom uncertainty experiences in nurses' clinical reasoning, 10 themes emerged: ambiguity and decision latitude, communication, work ethic, difficulty interpreting and predicting outcomes, cognitive performance impairment, incivility, core competence vagueness of postanesthesia nurses, high-tech care, (in)security and risk, and occupational stress. ConclusionsThe experiences of uncertainty in clinical reasoning of nurses in postanesthesia care units are highly focused on patient safety. Exploring these experiences has made uncertainty more tangible and explicit, which will enable nurses in postanesthesia care units to prepare for adaptive responses to deal with uncertainty when it occurs in clinical practice.

Design and synthesis of novel cycloalkanecarboxamide parabanic acid hybrids as anticonvulsants

Aiming to develop novel anticonvulsant agents a new series of novel cycloalkanecarboxamide parabanic acid hybrids series 8, 9 and 10 possessing the essential structure requirements for anticonvulsant activity was synthesized starting from cycloalkanones. All final target compounds were primary screened for chemically and electrically induced seizures using pentylenetetrazole “scPTZ” and maximal electroshock seizure “MES” models. In phase I anticonvulsant evaluation compounds 8b and 10b exhibited the highest potency among all the target compounds with 100% protection towards chemically induced seizures. Results of phase II anticonvulsant screening showed that compounds 8b and 10b are more potent than standard drug ethosuximide by about 11 and 9 fold, respectively. Regarding MES test, compounds 8b and 9a-d exhibited 100% protection with ED50 values ranged between 0.107–0.177 mmol/Kg. All final compounds did not display any signs of motor impairment in the neurotoxicity screening test. Also, compounds 8a, 9a-d and 10b were devoid of hepatotoxicity as shown by measurement of serum levels of liver enzymes, albumin as well as total protein. Moreover, the cyclohexyl derivative 10b produced a significant increase of Gamma-aminobutyric acid “GABA” brain’s content of mice compared to control group confirmed its GABAergic modulating activity. Molecular docking, physicochemical and pharmacokinetic properties were carried out for all compounds as well. These outcomes support that cycloalkanecarboxamide parabanic acid hybrid is a promising scaffold to pave the way towards further development of novel class of antiepileptic drugs.

Abnormalities of Hippocampal Subfield and Amygdalar Nuclei Volumes and Clinical Correlates in Behavioral Variant Frontotemporal Dementia with Obsessive-Compulsive Behavior-A Pilot Study.

(1) Background: The hippocampus (HP) and amygdala are essential structures in obsessive-compulsive behavior (OCB); however, the specific role of the HP in patients with behavioral variant frontotemporal dementia (bvFTD) and OCB remains unclear. (2) Objective: We investigated the alterations of hippocampal and amygdalar volumes in patients with bvFTD and OCB and assessed the correlations of clinical severity with hippocampal subfield and amygdalar nuclei volumes in bvFTD patients with OCB. (3) Materials and methods: Eight bvFTD patients with OCB were recruited and compared with eight age- and sex-matched healthy controls (HCs). Hippocampal subfield and amygdalar nuclei volumes were analyzed automatically using a 3T magnetic resonance image and FreeSurfer v7.1.1. All participants completed the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Neuropsychiatric Inventory (NPI), and Frontal Behavioral Inventory (FBI). (4) Results: We observed remarkable reductions in bilateral total hippocampal volumes. Compared with the HCs, reductions in the left hippocampal subfield volume over the cornu ammonis (CA)1 body, CA2/3 body, CA4 body, granule cell layer, and molecular layer of the dentate gyrus (GC-ML-DG) body, molecular layer of the HP body, and hippocampal tail were more obvious in patients with bvFTD and OCB. Right subfield volumes over the CA1 body and molecular layer of the HP body were more significantly reduced in bvFTD patients with OCB than in those in HCs. We observed no significant difference in amygdalar nuclei volume between the groups. Among patients with bvFTD and OCB, Y-BOCS score was negatively correlated with left CA2/3 body volume (τb = -0.729, p < 0.001); total NPI score was negatively correlated with left GC-ML-DG body (τb = -0.648, p = 0.001) and total bilateral hippocampal volumes (left, τb = -0.629, p = 0.002; right, τb = -0.455, p = 0.023); and FBI score was negatively correlated with the left molecular layer of the HP body (τb = -0.668, p = 0.001), CA4 body (τb = -0.610, p = 0.002), and hippocampal tail volumes (τb = -0.552, p < 0.006). Mediation analysis confirmed these subfield volumes as direct biomarkers for clinical severity, independent of medial and lateral orbitofrontal volumes. (5) Conclusions: Alterations in hippocampal subfield volumes appear to be crucial in the pathophysiology of OCB development in patients with bvFTD.

A variational approach to effective models for inelastic systems

Given a set of inelastic material models, a microstructure, a macroscopic structural geometry, and a set of boundary conditions, one can in principle always solve the governing equations to determine the system’s mechanical response. However, for large systems this procedure can quickly become computationally overwhelming, especially in three-dimensions when the microstructure is locally complex. In such settings multi-scale modeling offers a route to a more efficient model by holding out the promise of a framework with fewer degrees of freedom, which at the same time faithfully represents, up to a certain scale, the behavior of the system. In this paper, we present a methodology that produces such models for inelastic systems upon the basis of a variational scheme. The essence of the scheme is the construction of a variational statement for the free energy as well as the dissipation potential for a coarse scale model in terms of the free energy and dissipation functions of the fine scale model. From the coarse scale energy and dissipation we can then generate coarse scale material models that are computationally far more efficient than either directly solving the fine scale model or by resorting to FE2 type modeling. Moreover, the coarse scale model preserves the essential mathematical structure of the fine scale model. An essential feature for such schemes is the proper definition of the coarse scale inelastic variables. By way of concrete examples, we illustrate the needed steps to generate successful models via application to problems in classical plasticity, included are comparisons to direct numerical simulations of the microstructure to illustrate the accuracy of the proposed methodology.

Receiving a gift and feeling robbed: a phenomenological study on parents’ experiences of Brief Admissions for teenagers who self-harm at risk for suicide

BackgroundBrief Admission by self-referral is a preventive intervention here intended for individuals who recurrently self-harm and have a history of contact with emergency psychiatric services. Individuals with access to Brief Admission are empowered to self-admit to inpatient care for up to three days per stay and are encouraged to do so before experiencing crisis. Brief Admission was implemented relatively recently in child and adolescent psychiatric settings in Sweden. The purpose of this study was to phenomenologically explore the lived experience of parents whose teenagers, who recurrently self-harm and experience suicidal thoughts, use Brief Admissions.MethodsThis is a qualitative study using phenomenological psychological analysis. We interviewed 17 parents who had experienced their teenagers using Brief Admissions. The interviews were recorded and transcribed verbatim and analyzed to arrive at the essential meaning structure of the phenomenon of Brief Admissions for the parent.ResultsWe identified two essential meaning structures of the parent’s experience of their teenager’s use of Brief Admissions: being gifted relief and hope or being robbed of everything you believed in. The experience of Brief Admissions as a gift was structured by the following constituents: ‘a sense of safety and containment’, ‘liberation from a hostage situation’, ‘a return to wellbeing’, and ‘catalysts for relational shifts’. In contrast, the constituents of the experience of being robbed included ‘a tug of war for control’, ‘an unworthy wasteland’, ‘abandonment and collapse of authority’, and ‘no sense of purpose and plan’.ConclusionsBrief Admissions may come across as challenging, futile and painful in the life of the parent, yet they may also support a process of recovery and healthy development for the entire family. To realize the full potential of the intervention, mental health professionals providing Brief Admission must be mindful of the challenges the parent may face as their teenager starts self-admitting, tactfully and sensitively preparing the parent for a new parental role.

Research on a monitoring model of revolute pair clearance based on dynamic features and thermal imaging fusion

The revolute pair is an essential structure. The running of the revolute pair with clearance leads to energy loss due to collision. Partial energy loss is distributed in the form of heat energy. This provides the possibility for using thermal imaging to determine the clearance size of the revolute pair. A clearance monitoring method for revolute pairs fusing dynamic and thermal image features is proposed. The penetration depth and energy loss caused by collision are calculated as dynamic data, and dynamic features are extracted from the dynamic data by a multilayer perceptron. The convolutional block attention module embedded with a convolutional neural network is used to extract thermal imaging features. Clearance monitoring of revolute pairs is conducted based on fusion features of dynamic features and thermal image features. The experimental results on the test bench for revolute pair clearance show that the revolute pair clearance monitoring method based on fusion features can effectively monitor the revolute pair clearance.

Discovery of tetrazolo-pyridazine-based small molecules as inhibitors of MACC1-driven cancer metastasis

Metastasis is directly linked to poor prognosis of cancer patients and warrants search for effective anti-metastatic drugs. MACC1 is a causal key molecule for metastasis. High MACC1 expression is prognostic for metastasis and poor survival. Here, we developed novel small molecule inhibitors targeting MACC1 expression to impede metastasis formation. We performed a human MACC1 promoter-driven luciferase reporter-based high-throughput screen (HTS; 118.500 compound library) to identify MACC1 transcriptional inhibitors. HTS revealed 1,2,3,4-tetrazolo[1,5-b]pyridazine-based compounds as efficient transcriptional inhibitors of MACC1 expression, able to decrease MACC1-induced cancer cell motility in vitro. Structure-activity relationships identified the essential inhibitory core structure. Best candidates were evaluated for metastasis inhibition in xenografted mouse models demonstrating metastasis restriction. ADMET showed high drug-likeness of these new candidates for cancer therapy. The NFκB pathway was identified as one mode of action targeted by these compounds. Taken together, 1,2,3,4-tetrazolo[1,5-b]pyridazine-based compounds are effective MACC1 inhibitors and pose promising candidates for anti-metastatic therapies particularly for patients with MACC1-overexpressing cancers, that are at high risk to develop metastases. Although further preclinical and clinical development is necessary, these compounds represent important building blocks for an individualized anti-metastatic therapy for solid cancers.

Inhibitors targeting BamA in gram-negative bacteria

Antibiotic resistance has led to an increase in the number of patient hospitalizations and deaths. The situation for gram-negative bacteria is especially dire as the last new class of antibiotics active against these bacteria was introduced to the clinic over 60 years ago, thus there is an immediate unmet need for new antibiotic classes able to overcome resistance. The outer membrane, a unique and essential structure in gram-negative bacteria, contains multiple potential antibacterial targets including BamA, an outer membrane protein that folds and inserts transmembrane β-barrel proteins. BamA is essential and conserved, and its outer membrane location eliminates a barrier that molecules must overcome to access this target. Recently, antibacterial small molecules, natural products, peptides, and antibodies that inhibit BamA activity have been reported, validating the druggability of this target and generating potential leads for antibiotic development. This review will describe these BamA inhibitors, highlight their key attributes, and identify challenges with this potential target.

Delving into Earth Dam Dynamics: Exploring the Impact of Inner Impervious Core and Toe Drain Arrangement on Seepage and Factor of Safety during Rapid Drawdown Scenarios

The study examined the intricate relationships between embankment slope configurations, toe drain designs, and drawdown scenarios. It utilized a unique combination of numerical, physical, and mathematical models. The investigation involved 16 numerical models and 8 physical models with distinct characteristics. The research explored the correlations of key parameters: matric suction, horizontal water conductivity, time, and factor of safety. The factor of safety values varied from 0.62 to 1.03 as a result of the different investigated combinations. For instance, a 1:2 embankment slope without a toe drain under instantaneous drawdown led to the factor of safety values ranging from 1.22 to 1.57. Additionally, incorporating elements like a 30 m toe drain and a 1 m per day drawdown rate influenced these values, with extremes recorded from 1.337 to 2.21, shedding light on embankment stability under diverse conditions and configurations. When subjected to a 1 m per day drawdown, water flow rates decreased significantly at the upstream face and increased downstream, accompanied by an increase in water mass flux at the upstream face and a decrease at the downstream toe, suggesting dynamic changes in water behavior in response to drawdown. Moreover, the findings unveiled significant correlations between matric suction and time (correlation coefficient of 0.950) and factor of safety and water conductivity (correlation coefficient of 0.750). Conversely, a distinct negative correlation emerged between matric suction and factor of safety (correlation coefficient of −0.864). The study’s distinctive insights contribute to our understanding of seepage behavior and dam stability across varied scenarios, offering valuable input for resilient dam construction approaches that will ensure the longevity and effectiveness of these essential structures.

High-order moment closure models with random batch method for efficient computation of multiscale turbulent systems.

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment equations are closed by a precise calibration of the high-order feedbacks using ensemble solutions of the consistent stochastic equations, suitable for modeling complex phenomena including non-Gaussian statistics and extreme events. To address challenges associated with closely coupled spatiotemporal scales in turbulent states and expensive large ensemble simulation for high-dimensional systems, we introduce efficient computational strategies using the random batch method (RBM). This approach significantly reduces the required ensemble size while accurately capturing essential high-order structures. Only a small batch of small-scale fluctuation modes is used for each time update of the samples, and exact convergence to the full model statistics is ensured through frequent resampling of the batches during time evolution. Furthermore, we develop a reduced-order model to handle systems with really high dimensions by linking the large number of small-scale fluctuation modes to ensemble samples of dominant leading modes. The effectiveness of the proposed models is validated by numerical experiments on the one-layer and two-layer Lorenz '96 systems, which exhibit representative chaotic features and various statistical regimes. The full and reduced-order RBM models demonstrate uniformly high skill in capturing the time evolution of crucial leading-order statistics, non-Gaussian probability distributions, while achieving significantly lower computational cost compared to direct Monte-Carlo approaches. The models provide effective tools for a wide range of real-world applications in prediction, uncertainty quantification, and data assimilation.

A3DyDB: exploring structural aggregation propensities in the yeast proteome

BackgroundThe budding yeast Saccharomyces cerevisiae (S. cerevisiae) is a well-established model system for studying protein aggregation due to the conservation of essential cellular structures and pathways found across eukaryotes. However, limited structural knowledge of its proteome has prevented a deeper understanding of yeast functionalities, interactions, and aggregation.ResultsIn this study, we introduce the A3D yeast database (A3DyDB), which offers an extensive catalog of aggregation propensity predictions for the S. cerevisiae proteome. We used Aggrescan 3D (A3D) and the newly released protein models from AlphaFold2 (AF2) to compute the structure-based aggregation predictions for 6039 yeast proteins. The A3D algorithm exploits the information from 3D protein structures to calculate their intrinsic aggregation propensities. To facilitate simple and intuitive data analysis, A3DyDB provides a user-friendly interface for querying, browsing, and visualizing information on aggregation predictions from yeast protein structures. The A3DyDB also allows for the evaluation of the influence of natural or engineered mutations on protein stability and solubility. The A3DyDB is freely available at http://biocomp.chem.uw.edu.pl/A3D2/yeast.ConclusionThe A3DyDB addresses a gap in yeast resources by facilitating the exploration of correlations between structural aggregation propensity and diverse protein properties at the proteome level. We anticipate that this comprehensive database will become a standard tool in the modeling of protein aggregation and its implications in budding yeast.

Development and validation of a deep learning-based fully automated algorithm for pre-TAVR CT assessment of the aortic valvular complex and detection of anatomical risk factors: a retrospective, multicentre study

Pre-procedural computed tomography (CT) imaging assessment of the aortic valvular complex (AVC) is essential for the success of transcatheter aortic valve replacement (TAVR). However, pre-TAVR assessment is a time-intensive process, and the visual assessment of anatomical structures at the AVC shows interobserver variability. This study aimed to develop and validate a deep learning-based algorithm for pre-TAVR CT assessment and anatomical risk factor detection. This retrospective, multicentre study used AVC CT scans to develop a deep learning-based, fully automated algorithm, which was then internally and externally validated. After loading CT scans into the algorithm, it automatically assessed the essential anatomical structure data required for TAVR planning. CT scans of 1252 TAVR candidates continuously enrolled from Fuwai Hospital were used to establish training and internal validation datasets, while CT scans of 100 patients with aortic valve disease across 19 Chinese hospitals served as an external validation dataset. The validation focused on segmentation performance, localisation and measurement accuracy of key anatomical structures, detection ability of specific anatomical risk factors, and improvement in assessment efficiency. Relative to senior observers, our algorithm achieved significant consistent performance with remarkable accuracy, efficiency and ease in segmentation, localisation, and the assessment of the aortic annulus perimeter-derived diameter, and other basic planes, coronary ostia height, calcification volume, and aortic angle. The intraclass correlation coefficient values for the algorithm in the internal and external validation datasets were up to 0.998 (95% confidence interval 0.998-0.998), respectively. Furthermore, the algorithm demonstrated high alignment in detecting specific anatomical risk factors, with accuracy, sensitivity, and specificity up to 0.989 (95% CI 0.973-0.996), 0.979 (95% CI 0.936-0.995), 0.986 (95% CI 0.945-0.998), respectively. Our algorithm efficiently performs pre-TAVR assessments by using AVC CT imaging with accuracy comparable to senior observers, potentially improving TAVR planning in clinical practice. National Key R&D Program of China (2020YFC2008100), CAMS Innovation Fund for Medical Sciences (2022-I2M-C&T-B-044).

Metabolism of dipentylone in zebrafish and human liver microsomes determined by liquid chromatography–high resolution mass spectrometry

The consumption of novel psychoactive substances (NPS) is exceedingly prevalent in society, as these substances are sold and distributed as “legal highs.” One novel synthetic cathinone emerging in the market is 1-(1,3-benzodioxol-5-yl)–2-(dimethylamino) pentan-1-one (dipentylone). The goal of this work was to study the in vivo and in vitro metabolism of dipentylone in zebrafish and human liver microsomes (HLMs) by liquid chromatography-high resolution mass spectrometry (LC-HRMS). The zebrafish and HLM samples contained 14 dipentylone metabolites, specifically 12 phase Ⅰ metabolites and 2 phase Ⅱ metabolites. The main metabolic pathways included monohydroxylation (M1 and M2), N-dealkylation (M3), hydroxylation of the aromatic ring and dealkoxylation of M3 (M4), O-dealkylation (M5), N-dealkylation of M5 (M6), reduction of carboxide (M7), monohydroxylation of M5 (M8), dehydrogenation (M9), dealkoxylation (M10), N-dealkylation of M10 (M11), dealkoxylation of M9 (M12), glucuronidation of M5 (M13), and sulfation (M14). The monohydroxylated metabolite (M2) can be recommended as metabolic markers for dipentylone. This study is the first to identify a target compound for monitoring the abuse of dipentylone and to determine the essential chemical structure of the metabolites for further toxicological research.

Effectiveness of Non-Custodial Reintegration Programmes on Welfare of Returnee Terrorist Fighters in Mombasa, Kenya

A strong and effective non-custodial reintegration process, working in close collaboration with civil society organizations and communities, will facilitate transition back into society for former violent extremist offenders, demonstrate ongoing goodwill, and provide an essential support structure for the returnee terrorist fighters. This study aimed to assess the influence that non-custodial reintegration programs have on the well-being of returned terrorist fighters in Mombasa County, while also taking into consideration the risk that these programs may present if they are not employed appropriately. This understanding contributes to the growing necessity for both governmental and non-governmental actors to contribute to the development and implementation of non-custodial reintegration programs. The study utilized a descriptive research design using quantitative and qualitative methods to evaluate the efficacy of non-custodial reintegration programs on the well-being of returnee terrorist fighters in Mombasa County, Kenya. From a sample size of 400 respondents needed for investigation from the target population of Mombasa Count, the study drew data from focus group discussions (FGDs), interviews with key informants, and questionnaires that were physically delivered and electronically disseminated using the Google Forms application. The county was shown to have the highest rates of violent extremism and recidivism in Kenya. From the findings it is evident that for non-custodial reintegration programmes for returnee terrorist fighters to be effective, it is necessary to ensure that community stakeholders and other non-governmental actors have the required legal and policy space and capacity to engage; acknowledge the relative advantages of government and non-governmental stakeholders; and clearly identify the appropriate division of responsibilities between them in supporting non-custodial reintegration programmes and to make this strategy a reality. In conclusion, a strong and effective non-custodial reintegration process, working in close collaboration with civil society organizations and communities facilitates the transition back into society for former violent extremist offenders and thereby providing required support system to the former violent extremist offenders.

A BEM broadband topology optimization strategy based on Taylor expansion and SOAR method—Application to 2D acoustic scattering problems

AbstractIn this article, an innovative method is proposed for broadband topology optimization of sound‐absorbing materials adhering to the surface of a sound barrier structure. Helmholtz equation for the acoustic problems is solved using the boundary element method, while sensitivities of the objective function with respect to a large number of design variables are calculated via a sensitivity analysis method originated from the adjoint variable method (AVM), and the optimal solution is obtained by the method of moving asymptotes (MMA). Since the traditional single‐frequency topology optimization is frequency dependent, that is, the optimal solution at a certain frequency may not be optimal at other frequencies, broadband topology optimization of sound‐absorbing materials is conducted in this work. To address the problem of tremendous computational cost due to repetitive calculations at each discrete frequency point during broadband optimization, Taylor expansion of the Hankel function is performed to decouple the frequency dependent and independent terms in the BEM equations. For large‐scale problems, a reduced‐order model that retains the essential structures and key properties of the original model is built using the second‐order Arnoldi (SOAR) method. The accuracy and feasibility of the proposed algorithms are finally validated via some two‐dimensional numerical examples.

Spatiotemporal monitoring of hard tissue development reveals unknown features of tooth and bone development.

Mineralized tissues, such as bones or teeth, are essential structures of all vertebrates. They enable rapid movement, protection, and food processing, in addition to providing physiological functions. Although the development, regeneration, and pathogenesis of teeth and bones have been intensely studied, there is currently no tool to accurately follow the dynamics of growth and healing of these vital tissues in space and time. Here, we present the BEE-ST (Bones and tEEth Spatio-Temporal growth monitoring) approach, which allows precise quantification of development, regeneration, remodeling, and healing in any type of calcified tissue across different species. Using mouse teeth as model the turnover rate of continuously growing incisors was quantified, and role of hard/soft diet on molar root growth was shown. Furthermore, the dynamics of bones and teeth growth in lizards, frogs, birds, and zebrafish was uncovered. This approach represents an effective, highly reproducible, and versatile tool that opens up diverse possibilities in developmental biology, bone and tooth healing, tissue engineering, and disease modeling.