General Public Research Articles

Network hub gene detection using the entire solution path information.

Gene co-expression networks typically comprise modules and their associated hub genes, which are regulating numerous downstream interactions within the network. Methods for hub screening, as well as data-driven estimation of hub co-expression networks using graphical models, can serve as useful tools for identifying these hubs. Graphical model-based penalization methods typically have one or multiple regularization terms, each of which encourages some favorable characteristics (e.g., sparsity, hubs, power-law) to the estimated complex gene network. It is common practice to find a single optimal graphical model corresponding to a specific value of the regularization parameter(s). However, instead of doing this, one could aggregate information across several graphical models, all of which depend on the same data set, along the solution path in the hub gene detection process. We propose a novel method for detecting hub genes that utilizes the information available in the solution path. Our procedure is related to stability selection, but we replace resampling with a simple statistic. This procedure amalgamates information from each node of the data-driven graphical models into a single influence statistic, similar to Cook's distance. We call this statistic the Mean Degree Squared Distance (MDSD). Our simulation and empirical studies demonstrate that the MDSD statistic maintains a good balance between false positive and true positive hubs. An R package MDSD is publicly available on GitHub under the General Public License https://github.com/markkukuismin/MDSD.

The General Public as well as Physiotherapists Evaluate Spinal Flexion as Dangerous Regardless of Their Own Low Back Pain History

BackgroundMaladaptive fear of movement in individuals with low back pain may be associated with worse clinical outcomes. ObjectiveTo explore beliefs about the perceived dangers regarding different spinal postures within the Czech Republic. DesignExploratory cross-sectional study including physiotherapists and members of the general public. MethodsSelf-reported perceived safety/danger of “straight” and “flexed” spinal postures regarding 1) sitting, 2) lifting of light and 3) heavy object from the floor based on three pairs of photographs was measured using numeric rating scales (0-10, safe to dangerous) without any given context and in the context of low back pain. The sum of differences between the ratings of flexed and straight postures were used to calculate Bending Safety Beliefs Thermometer (BSBThermometer) total score potentially ranging -60‒60 (higher values indicates evaluation of flexed spinal postures as more dangerous in comparison to straight postures). Results760 participants were included in the analysis. The mean BSBThermometer total score was 31.1 (SD 16.1) and higher scores were positively associated with being women (b=14.8, 95% CI [9.9-19.8]); non-medical profession (b=24.7, 95% CI [15.2-34.2]); age (b=0.38, 95% CI [0.16-0.6]; and their interactions. There was no significant association with current low back pain status or history of low back pain. ConclusionsOn average, participants evaluated “flexed” spinal postures as significantly more dangerous when compared with “straight” spinal postures, with only subgroups of physiotherapists scoring lower than the general public. Clinically, these beliefs could be targeted by individualized education, exposure-based interventions and public campaigns; however, further research is required.

Unraveling Myths: Assessing Beliefs in Disaster Management Misconceptions Among First Responders and the General Public

Unraveling Myths: Assessing Beliefs in Disaster Management Misconceptions Among First Responders and the General Public

Environmental niche models improve species identification in DNA barcoding

Abstract Recent advances in DNA barcoding have immeasurably advanced global biodiversity research in the last two decades. However, inherent limitations in barcode sequences, such as hybridization, introgression or incomplete lineage sorting can lead to misidentifications when relying solely on barcode sequences. Here, we propose a new Niche‐model‐Based Species Identification (NBSI) method based on the idea that species distribution information is a potential complement to DNA barcoding species identifications. NBSI performs species membership inference by incorporating niche modelling predictions and traditional DNA barcoding identifications. Systematic tests across diverse scenarios show significant improvements in species identification success rates under the newly proposed NBSI framework, where the largest increase is from 4.7% (95% CI: 3.51%–6.25%) to 94.8% (95% CI: 93.19%–96.06%). Additionally, obvious improvements were observed when using NBSI on potentially ambiguous sequences whose genetic nearest neighbours belongs to another species or more than two species, which occurs commonly with species represented by single or short DNA barcodes. These results support our assertion that environmental factors/variables are valuable complements to DNA sequence data for species identification by avoiding potential misidentifications inferred from genetic information alone. The NBSI framework is currently implemented as a new R package, ‘NicheBarcoding’, that is open source under GNU General Public Licence and freely available from https://CRAN.R‐project.org/package=NicheBarcoding.

Cryptocurrency Security Risk: Awareness Among General Public in Malaysia

In the age of digital payments, cryptocurrencies have gained significant attention as an alternative investment option. However, security risks such as phishing, hacking, and fraudulent exchanges present challenges for investors. This study aims to assess the level of awareness among the general public in Malaysia regarding cryptocurrency security risks. A quantitative research method was employed, using a survey questionnaire distributed to 150 Malaysian citizens via social media platforms. The questionnaire explored respondents' knowledge of cryptocurrencies, awareness of security risks, and protective measures such as security programs, two-factor authentication (2FA), and education. The results of the regression analysis show that the installation of security programs, 2FA, and public education are all significant predictors of increased awareness of cryptocurrency security risks, with a combined R² value of 0.523. This suggests that 52.3% of the variance in awareness is explained by these factors. The study concludes that strengthening security measures and providing education can significantly improve public understanding of cryptocurrency risks, leading to safer investment practices. The implications of these findings highlight the need for targeted education and security initiatives to enhance public confidence in cryptocurrency, making digital currency investments more secure

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains. Program summaryProgram Title: VAN-DAMMECPC Library link to program files::https://doi.org/10.17632/zcgw2n5bjf.1Licensing provisions: GNU General Public License 3Programming language: C++ and CUDANature of problem: The VAN-DAMME software package utilizes GPU-accelerated routines and new algorithmic improvements to compute optimized time-dependent magnetic fields that can drive a system from a known initial qubit configuration to a specified target state with a large (≈1) transition probability.Solution method: Quantum control, GPU acceleration, analytic gradients, matrix exponential, and gradient ascent optimization.

The Impact of Perceived Risk to AI Music on the General Public's Music Listening Behavioral Intention: Using Extended MGB Model

The Impact of Perceived Risk to AI Music on the General Public's Music Listening Behavioral Intention: Using Extended MGB Model

The Mediating Effect of Digital Usage Attitude and the Moderated Mediating Effect of Age in the Influence of the General Public's Awareness of Digital Transformation on Digital Transformation Satisfaction

The Mediating Effect of Digital Usage Attitude and the Moderated Mediating Effect of Age in the Influence of the General Public's Awareness of Digital Transformation on Digital Transformation Satisfaction

BAD2matrix: Phylogenomic matrix concatenation, indel coding, and more

AbstractPremiseCommon steps in phylogenomic matrix production include biological sequence concatenation, morphological data concatenation, insertion/deletion (indel) coding, gene content (presence/absence) coding, removing uninformative characters for parsimony analysis, recording with reduced amino acid alphabets, and occupancy filtering. Existing software does not accomplish these tasks on a phylogenomic scale using a single program.Methods and ResultsBAD2matrix is a Python script that performs the above‐mentioned steps in phylogenomic matrix construction for DNA or amino acid sequences as well as morphological data. The script works in UNIX‐like environments (e.g., LINUX, MacOS, Windows Subsystem for LINUX).ConclusionsBAD2matrix helps simplify phylogenomic pipelines and can be downloaded from https://github.com/dpl10/BAD2matrix/tree/master under a GNU General Public License v2.

SSLG4: A novel scintillator simulation library for Geant4

This study introduces a new Scintillator Simulation Library called SSLG4 for the Geant4 Monte Carlo simulation package. With SSLG4, we aim to enhance efficiency and accelerate progress in optical simulations within the Geant4 framework by simplifying scintillator handling and providing a rich repository of scintillators. The SSLG4 enables users to quickly include predefined scintillator materials in their simulations without requiring manual definition. The library initially contains 68 scintillators, consisting of 58 organic and 10 inorganic types. Most of these scintillators are selected from the catalogs of several scintillator manufacturers, notably Eljen and Luxium. Other scintillators are included based on their widespread use across various physics domains. The library stores optical data of scintillators in ASCII files with .mac and .txt extensions, enabling users to add, remove, or modify properties of scintillators at runtime of their applications. In addition, we made all the scintillator data available in the library on a dedicated page of our website to ensure convenient access for all users. Program summaryProgram title: SSLG4CPC Library link to program files:https://doi.org/10.17632/3zbwr5wf7z.1Developer's repository link:https://github.com/mkandemirr/SSLG4, https://neutrino.erciyes.edu.tr/SSLG4/Licensing provisions: GNU General Public License 3Programming language: C++External routines/libraries: Geant4, CMake, OPSimNature of problem: Defining a new scintillator in Geant4 is a cumbersome process for some users due to three main reasons: (1) It requires a lot of data input from users, (2) collecting the scintillator data requires an extensive literature review, and (3) the collected data needs to be converted into the desired format. In addition, the interfaces provided to define a scintillator direct users to embed scintillator data into their source code, resulting in increased code complexity, reduced code readability, and an inefficient working environment.Solution method: To solve the problems mentioned above, developing and introducing a new library consisting of fully parameterized and ready-to-use scintillators would greatly increase the useability of the Geant4 simulation package for scintillator studies and interest a wide range of scientific communities.

Will a government subsidy increase couples' further fertility intentions? A real-world study from a large-scale online survey in Eastern China.

How many couples with at least one child under 3 years would like to have another one or more child(ren) in Eastern China and will an in-cash subsidy be conducive to couple's fertility intentions? In sum, only 15.1% of respondents had further fertility intentions (FFI) before learning about the subsidy, and the planned in-cash subsidy policy increased respondents' overall FFI by 8.5%. Fertility has been declining globally and has reached a new low in China. The reasons why the Chinese three-child policy was under-realized, and how couples will react to a planned monthly ¥1000 (€141.2) subsidy policy, are not fully understood. During January and February 2022, a cross-sectional online survey aiming to understand families' expenses of raising a child under 3 years old, and couples' FFI, was conducted. During the survey period, 272510 respondents scanned the QR code. This study reports the findings pertaining to questions on respondents' sociodemographic characteristics, household factors, FFI, and changes in intention from negative to positive after learning about the planned in-cash subsidy. After exclusion, 144893 eligible responses were included. Respondents' FFI, the effect of a planned ¥1000/month*36 months' in-cash subsidy (€5083.2 in total) on people with a negative FFI before the subsidy, and potential reasons for persistent negative FFI after learning about the subsidy were collected through an anonymous online survey. Stepwise binary logistic regression models were used to select associated factors. The potential fertility rate change and government costs were estimated. A stratified analysis by current child number and sensitivity analysis were also conducted. In sum, 15.7% (22804/144893) of respondents were male, 15.1% of respondents reported a positive FFI, and 10.0% (12288/123051) without an FFI at first changed their intention after learning about the planned in-cash subsidy policy. For those who still said 'no FFI', 46.5%, 20.6%, and 14.7% chose pressure on housing status, expenses on children's education, and lack of time or energy for caring for another child as their first reasons. FFI was strongest in participants receiving the most financial support from their parents, i.e. grandparents (OR = 1.73, 95% CI = 1.63-1.84 for the >¥100000/year group), and weakest in those already having two children (OR = 0.23, 95% CI = 0.22-0.24). For those with no FFI before learning about the subsidy policy, respondents with the highest house loan/rent (>¥120000/year, OR = 1.27, 95% CI = 1.18-1.36) were more likely to change their FFI from 'No' to 'Yes', and those with the highest household income (>¥300000/year, OR = 0.65, 95% CI = 0.60-0.71) were least susceptible to the policy. In our study population, about 1843 more births every year and an additional 0.3 children per woman were projected under a conservative estimation. Annual estimated cost at the provincial scale would be ¥817.7 (€115.5) million, about 1.02‰ of the total General Public Budget Revenue in 2022. The findings were generally robust in the stratified analysis and sensitivity analysis. Selection bias and information errors may exist in the online survey responses. The large sample size and detailed further analysis were used to minimize such biases. Fertility intentions in Eastern China are rather low. Policymakers should focus more on financial and childcare burdens for a better realization of the three-child policy, including housing, education and childcare services. An in-cash subsidy, which has never been used in China previously, shows promising potential for increasing FFI. However, the application of such policy should be in line with local conditions for better cost-effectiveness regarding fertility-boosting and fiscal sustainability for the government in the long run. This work was supported by the National Key Research and Development Plan of China (2019YFC0840702). The authors declare no conflict of interests. N/A.

Scywalker: scalable end-to-end data analysis workflow for long-read single-cell transcriptome sequencing.

Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes. We introduce scywalker, an innovative and scalable package developed to comprehensively analyze long-read sequencing data of full-length single-cell or single-nuclei cDNA. We developed novel scalable methods for cell barcode demultiplexing and single-cell isoform calling and quantification and incorporated these in an easily deployable package. Scywalker streamlines the entire analysis process, from sequenced fragments in FASTQ format to demultiplexed pseudobulk isoform counts, into a single command suitable for execution on either server or cluster. Scywalker includes data quality control, cell type identification, and an interactive report. Assessment of datasets from the human brain, Arabidopsis leaves, and previously benchmarked data from mixed cell lines demonstrate excellent correlation with short-read analyses at both the cell-barcoding and gene quantification levels. At the isoform level, we show that scywalker facilitates the direct identification of cell-type-specific expression of novel isoforms. Scywalker is available on github.com/derijkp/scywalker under the GNU General Public License (GPL) and at https://zenodo.org/records/13359438/files/scywalker-0.108.0-Linux-x86_64.tar.gz.

Drug Management and Service Quality in Outpatient Pharmacies at the Haji Padjonga Daeng Ngalle Regional General Public Hospital in Takalar Regency, Indonesia

Drug Management and Service Quality in Outpatient Pharmacies at the Haji Padjonga Daeng Ngalle Regional General Public Hospital in Takalar Regency, Indonesia

Why Insects Don’t Get No Respect, and How We Can Change That by Engaging the General Public

Why Insects Don’t Get No Respect, and How We Can Change That by Engaging the General Public

Health Awareness Exhibition Emphasizing Cancer Causes Improves Knowledge of the General Public: A Pilot Study

Abstract Aim In India, science exhibitions are conducted to create awareness in the community and offer education about health using instructive materials and explanations by trained community workers. This study aimed to understand the usefulness of cancer exhibition in creating cancer awareness in the participants. Materials and Methods This was a prospective pretest and posttest study and was performed with the general public who participated in a health awareness exhibition at Mangalore Institute of Oncology, Mangalore, Karnataka, India. The knowledge gained by the volunteers was ascertained by calculating the difference between the pretest and posttest using McNemar, chi-square, or Fisher Exact test. A probability value <0.05 was considered significant. Results: The results revealed that a total of 378 participated in the study. Pretest scores indicated most volunteers were aware of tobacco and alcohol in cancer, whereas the majority were unaware of the role of fruits and vegetables and sedentary life in enhancing the possibility of cancer development. The posttest showed a significant increase in knowledge gain (P = 0.003–<0.001). Conclusions This study concludes that for the first time, this study shows that the exhibition can be useful in improving knowledge of cancer awareness among community members. When compared with other educational modes, the exhibition is a relatively inexpensive and easy way to educate the general public in the community.

Surgical decision-making: key factors influencing the shift from laparoscopic to open cholecystectomy

Background: Recognizing the preoperatively and intraoperatively factors can aid surgeons in making timely decisions to shift from laparoscopic cholecystectomy (LC) to open cholecystectomy (OC). This study aims to identify the main factors leading to LC conversion to OC among Iraqi patients. Methods: One-year prospective research was performed using cross-sectional design between 1st April, 2023, and 3oth March, 2024, at Alkalis General Public Hospital and Al Hayat Private Hospital, Diyala, Iraq. Pre and intraoperative data were collected from the planned LC surgeries including demographics, medical history, laboratory and Ultrasound findings. Descriptive and bivariate analysis was carried out to compare variables between patients undergoing LC and those requiring conversion to OC. Results: Out of 172 LC patients (mean age 48.28±12.62), 52.9% were female, 55.8% obese, 50.6% aged 49+, 23.3% diabetic, and 19.8% had emergency cholecystectomy; 15 (8.7%) required conversion to open surgery. The conversion group was mainly men (66.7% vs. 46.5%, P = 0.001) and older (73.3% vs. 48.4% aged 49+, P = 0.003). Obesity (60.0% vs. 55.4%, P = 0.005) and diabetes (53.3% vs. 20.4%, P < 0.001) were more common. Public hospital referrals were higher (86.7% vs. 52.2%, P < 0.001). Elevated total bilirubin, direct bilirubin, and alkaline phosphatase levels were significant predictors of conversion to OC. Adhesions in Calot's triangle (20.0% vs. 13.4%, P = 0.021) were more common in the conversion group, along with unclear anatomy, thick gallbladder wall, bleeding, stone and bile spillage, and cystic duct injury. Conclusion: In conclusion, out of 172 LC patients, 15 (8.7%) required conversion to open surgery, predominantly older men with higher obesity, diabetes, and elevated bilirubin and alkaline phosphatase levels, and more adhesions in Calot's triangle.

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Biochemical Systems Analytically.

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al. (J. Gen. Physiol., 2020, 152, e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

Redefining General Public Segment In Kustomfest: A Research On Visitor Motives In Attending A Kustom Kulture Festival

The Indonesian creative economy has experienced significant growth, with creative tourism emerging as a prominent driver. This study centers on Kustomfest, the Indonesian Kustom Kulture Festival, recognized as one of the largest Kustom Kulture hubs in the country. Between 2019 and 2023, there was a notable shift in the festival's audience composition, with the general public now constituting the majority segment. The research aims to identify and analyze the key motives driving the general public to attend Kustomfest, segment the market based on these motives, and examine each segment's sociodemographic profiles and behavioral characteristics. Three distinct market segments were identified, each motivated by different factors. Insights from this study can assist organizers of similar Kustom Kulture-related events in expanding creative tourism in Indonesia. By understanding visitor motivations and behaviors, event organizers can tailor marketing strategies, enhance visitor experiences, and capitalize on revenue opportunities from the general public segment. Recommendations are provided to attract, retain, and expand each segment through business model innovation, thus contributing to the sustained growth of Indonesia's creative economy. The findings highlight the importance of understanding visitor motivations and behaviors to maximize the impact of cultural events on the broader creative economy. These insights enable event organizers to foster growth in Indonesia's creative sector, ensuring that cultural festivals like Kustomfest continue to evolve and appeal to a diverse audience.

A Dementia-Friendly Educational Program Using Virtual Reality for the General Public in Japan: A Randomized Controlled Trial for DRIVE.

Raising dementia awareness is essential for building a dementia-friendly community. However, existing studies have underexplored the effects of virtual reality (VR) dementia educational programs for the general public on enhancing positive attitude toward dementia. This study aimed to examine the effectiveness of a VR dementia-friendly educational program called the Drive for Dementia Readiness Inside Virtual Reality (DRIVE) program to improve attitude toward dementia of the general public. A two-arm randomized controlled trial was conducted. Eligibility criteria for participants included being 16 years and older in Japan and having no professional license in healthcare and social care. We randomized individuals to attend a multielement VR dementia-friendly educational program (intervention), including simulation, VR films, short films, lectures, and discussions or a lecture-based program (control). Data were collected 3 times, including at baseline, postintervention, and 3-month follow-up. The primary outcome was attitude toward dementia. The secondary outcomes were intention of helping behavior for people living with dementia and knowledge of dementia. We recruited 157 community residents, among whom 130 were included in the analysis. Although the mean changes in attitude score were not significantly different between the groups (Hedge's g = 0.26), the intention of helping behavior score was significantly higher in the intervention group (g = 0.49). The DRIVE, a VR-based multielement dementia-friendly educational intervention, was shown as a promising tool for significantly affecting the intention of helping behavior for people living with dementia to establish dementia-friendly communities. UMIN000044901.

Building shape-focused pharmacophore models for effective docking screening

The performance of molecular docking can be improved by comparing the shape similarity of the flexibly sampled poses against the target proteins’ inverted binding cavities. The effectiveness of these pseudo-ligands or negative image-based models in docking rescoring is boosted further by performing enrichment-driven optimization. Here, we introduce a novel shape-focused pharmacophore modeling algorithm O-LAP that generates a new class of cavity-filling models by clumping together overlapping atomic content via pairwise distance graph clustering. Top-ranked poses of flexibly docked active ligands were used as the modeling input and multiple alternative clustering settings were benchmark-tested thoroughly with five demanding drug targets using random training/test divisions. In docking rescoring, the O-LAP modeling typically improved massively on the default docking enrichment; furthermore, the results indicate that the clustered models work well in rigid docking. The C+ +/Qt5-based algorithm O-LAP is released under the GNU General Public License v3.0 via GitHub (https://github.com/jvlehtonen/overlap-toolkit).Scientific contributionThis study introduces O-LAP, a C++/Qt5-based graph clustering software for generating new type of shape-focused pharmacophore models. In the O-LAP modeling, the target protein cavity is filled with flexibly docked active ligands, the overlapping ligand atoms are clustered, and the shape/electrostatic potential of the resulting model is compared against the flexibly sampled molecular docking poses. The O-LAP modeling is shown to ensure high enrichment in both docking rescoring and rigid docking based on comprehensive benchmark-testing.Graphical