bluuebunny/crossref_metadata_2025 huggingface dataset:
Outsciencing the scientists: a cross-sectional mixed-methods investigation of public trust in scientists in seven European countries
Authors: Heyerdahl Leonardo W , Borzykh Yanina , Lana Benedetta , Volkmann Anna-Maria , Crusefalk Lars , Colman Elien , Tvardik Nastassia , Anthierens Sibyl , Vray Muriel , Giles-Vernick Tamara
Published: December 2023

Background

In this era of global health crises, public trust in scientists is a crucial determinant of adherence to public health recommendations. Studies of trust in scientists often link sociodemographic and other factors to such adherence but rely on assumptions about scientists and neglect scientific uncertainty. We undertook a cross-sectional mixed-methods study evaluating factors associated with public trust of scientists in Europe, investigating how and why respondents embraced certain claims in scientific debates.

Methods

A survey was administered to 7000 participants across seven European countries in December 2020. Data concerning sociodemographic characteristics, trust in scientists, information source preferences, COVID-19 experiences and beliefs about pandemic origins were analysed using a multiple regression model. We employed thematic analysis to interpret open-text responses about pandemic origins and likely acceptance of treatments and vaccination.

Results

Trust in scientists was associated with multiple sociodemographic characteristics, including higher age and educational levels, left/centre political affiliation and use of certain information sources. Respondents claiming that COVID-19 was deliberately released and that 5G technology worsened COVID-19 symptoms had lower levels of trust in scientists. Explaining their positions in debates about pandemic origins, respondents trusting and not trusting scientists invoked scientific results and practices, arguing that scientists were not the most important actors in these debates.

Conclusions

Although our quantitative analyses align with prior studies, our qualitative analyses of scientists, their practices and perceived roles are more varied than prior research presumed. Further investigation of these variations is needed to strengthen scientific literacy and trust in scientists.
Firearms-related injury and sex: a comparative National Trauma Database (NTDB) Study
Authors: Zwemer Catherine , Kartiko Susan , Forssten Maximilian Peter , Zebley James A , Hughes Joy Dowden , Sarani Babak , Mohseni Shahin
Published: December 2023

Background

Existing study findings on firearms-related injury patterns are largely skewed towards males, who comprise the majority of this injury population. Given the paucity of existing data for females with these injuries, we aimed to elucidate the demographics, injury patterns, and outcomes of firearms-related injury in females compared with males in the USA.

Materials and methods

A 7-year (2013–2019) retrospective review of the National Trauma Database was conducted to identify all adult patients who suffered firearms-related injuries. Patients who were males were matched (1:1, caliper 0.2) to patients who were females by demographics, comorbidities, injury patterns and severity, and payment method, to compare differences in mortality and several other post-injury outcomes.

Results

There were 196 696 patients admitted after firearms-related injury during the study period. Of these patients, 23 379 (11.9%) were females, 23 378 of whom were successfully matched to a male counterpart. After matching, females had a lower rate of in-hospital mortality (18.6% vs. 20.0%, p<0.001), deep vein thrombosis (1.2% vs. 1.5%, p=0.014), and had a lower incidence of drug or alcohol withdrawal syndrome (0.2% vs. 0.5%, p<0.001) compared with males.

Conclusion

Female victims of firearms-related injuries experience lower rates of mortality and complications compared with males. Further studies are needed to elucidate the cause of these differences.

Level of evidence

Level III.
Options for substantiating protein content claims for conventional foods
Authors: House James D. , Brodkorb André , Messina Mark , Braun Michelle , Krul Elaine S.
Published: December 2023

In Canada and the United States, front-of-package protein content claims require data to support the quality of the protein. In general, protein quality reflects the product of the amino acid composition of the food protein relative to human amino acid requirements and a measure of digestibility. The currently accepted method in both jurisdictions is the protein digestibility-corrected amino acid score (PDCAAS) that requires the measurement of true fecal protein (nitrogen) digestibility. The latter must be measured in vivo using a rat model. This requirement for animal testing is inconsistent with international efforts to reduce the usage of animals in testing for regulatory purposes. The current commentary positions four options to remove the need to use animal testing for determining protein quality, when considering protein content claim substantiation. These options include ( i) a focus on protein quantity alone; ( ii) the use of the amino acid score alone, with no correction for digestibility; ( iii) the use of a fixed digestibility coefficient to estimate protein quality; and ( iv) the use of in vitro methods to measure protein and/or amino acid digestibility. The relative merits and deficiencies of the options are positioned with the goal of encouraging dialogue within the regulatory agencies to move towards alternative approaches for substantiating protein content claims on foods, including those derived from plant-based sources.
Development of EST-SSR markers in Bergenia ciliata using de novo transcriptome sequencing
Authors: Singh Harish Chandra , Tiwari Vandana , Tiwari Avinash , Rana Tikam S.
Published: December 2023

Bergenia ciliata (Haw.) Sternb. is an important herb predominantly found in the Indian Himalayan Region. It is widely used in medicines, healthcare systems, cosmetics, fodder, and ornamental purposes. The Illumina sequencing and de novo transcriptome assembly were carried out in B. ciliata to develop and identify simple sequence repeat markers. A total of 18 226 simple sequence repeats (SSRs) were identified wherein di-nucleotides were found to be abundant (47.88%), followed by mono-nucleotide (35.03%) and tri-nucleotide (15.88%) repeats. A total of 11 839 EST-SSR primers were designed, of which 96 primer pairs were commercially synthesized. Finally, 17 primer pairs revealed clear, distinct polymorphic bands, and these primers were validated with 40 diverse B. ciliata accessions. The present study revealed moderate level of genetic diversity ( Ho = 0.389, He = 0.542, and PIC = 0.513). Furthermore, the transcriptome data and EST-SSR markers generated during the present investigation could be an important genetic resource for functional genomics, population studies, and conservation genetics of the genus Bergenia.
Towards the optimal beam dump experiment to search for feebly interacting particles
Authors: Bondarenko Kyrylo , Boyarsky Alexey , Jacobsson Richard , Mikulenko Oleksii , Ovchynnikov Maksym
Published: December 2023

Future searches for new physics beyond the Standard Model are without doubt in need of a diverse approach and experiments with complementary sensitivities to different types of classes of models. One of the directions that should be explored is feebly interacting particles (FIPs) with masses below the electroweak scale. The interest in FIPs has significantly increased in the last ten years. Searches for FIPs at colliders have intrinsic limitations in the region they may probe, significantly restricting exploration of the mass range $$m_{\text {FIP}} < 5{-}10$$

m
FIP

<
5
-
10

 GeV/c$$^2$$

2

. Beam dump-like experiments, characterized by the possibility of extremely high luminosity at relatively high energies and the effective coverage of the production and decay acceptance, are the perfect option to generically explore the “coupling frontier” of the light FIPs. Several proposals for beam-dump detectors are currently being considered by CERN for implementation at the SPS ECN3 beam facility. In this paper, we analyse in depth how the characteristic geometric parameters of a beam dump experiment influence the signal yield. We apply an inclusive approach by considering the phenomenology of different types of FIPs. From the various production modes and kinematics, we demonstrate that the optimal layout that maximises the production and decay acceptance consists of a detector located on the beam-axis, at the shortest possible distance from the target defined by the systems required to suppress the beam-induced backgrounds.
Auger spectroscopy beyond the ultra-short core-hole relaxation time approximation
Authors: Nocera Alberto , Feiguin Adrian
Published: December 2023

We present a time-dependent computational approach to study Auger electron spectroscopy (AES) beyond the ultra-short core-hole relaxation time approximation and, as a test case, we apply it to the paradigmatic example of a one-dimensional Mott insulator represented by a half-filled Hubbard chain. The Auger spectrum is usually calculated by assuming that, after the creation of a core-hole, the system thermalizes almost instantaneously. This leads to a relatively simple analytical expression that uses the ground-state with a core-hole as a reference state and ignores all the transient dynamics related to the screening of the core-hole. In this picture, the response of the system can be associated to the pair spectral function. On the other hand, in our numerical calculations, the core hole is created by a light pulse, allowing one to study the transient dynamics of the system in terms of the pulse duration and in the non-perturbative regime. Time-dependent density matrix renormalization group calculations reveal that the relaxation process involves the creation of a polarization cloud of doublon excitations that have an effect similar to photo-doping. As a consequence, there is a leak of spectral weight to higher energies into what otherwise would be the Mott gap. For longer pulses, these excited states, mostly comprised of doublons, can dominate the spectrum. By changing the duration of the light-pulse, the entire screening process can be resolved in time.
A thermally reconfigurable metamaterial with switchable wideband absorption and sensing at THz band based on VO2 thin film
Authors: Wang Liansheng , Xia Dongyan , Fu Quanhong , Wang Yuan , Ding Xueyong
Published: December 2023

The VO2 thin film has the advantage of thermally controlled insulator-metal phase transition. Based on this, we presented a thermally reconfigurable metamaterial with switchable wideband absorption and sensing at THz band in this paper. At low temperature ([Formula: see text][Formula: see text]S/m), the metamaterial can realize nearly perfect absorption at the range of 6.88–9[Formula: see text]THz. When the temperature rises to a certain extent ([Formula: see text][Formula: see text]S/m), an absorption peak which can be used to sensing appears at 4.08[Formula: see text]THz with the permittivity sensitivity of 0.5[Formula: see text]THz/PU. The metamaterial has the advantages of simple structure and switchable wideband absorption/sensing functions with potential application value on terahertz stealth, detection, sensing, and so on.
On the semiconductor to metal transition in a quantum wire: Influence of geometry and laser
Authors: Vignesh G. , Balaji A. Sakthi , Mahalakshmi S. M. , Kalpana P. , Mohan C. Raja
Published: December 2023

The diamagnetic susceptibility and binding energy (BE) of a hydrogenic donor confined in a GaAs/AlGaAs QWW were theoretically studied in this paper under the influences of the applied laser field, QWW geometry, and non-parabolicity using variation technique combined with effective mass approximation. In the first part, the diamagnetic susceptibility and BE of the donor at the ground state are studied as a function of the size of the QWW, geometry, and applied laser field. The results reveal that changing the geometry of QWW enhances the quantum confinement effects. However, increasing the laser field reduces the BE by adding screening effects to the Coulomb interactions. Further, the diamagnetic susceptibility is available with the stability information about the carrier–parent donor system based on the mean square separation between them. It also demonstrates that susceptibility may remain stable regardless of the change in geometry and applied laser field. Thus, the diamagnetic behavior can serve as a better tool to evaluate the stability and Mott transition of donors in QWW. In the second section, the consequences of laser field and geometry on the SMT of confined donors in QWW have been studied. It is observed that the BE of donors remains constant until [Formula: see text] cm[Formula: see text] beyond which it starts to decrease gradually and vanishes exactly at critical concentration ([Formula: see text]. However, the diamagnetic susceptibility of the donor has remained constant until reaching [Formula: see text], beyond which it turned into a drastic fall, which manifested the SMT in the system. The current work is expected to add a few noteworthy points to the SMT phenomena in nanostructures.
Effect of Te doping in SnO2 in Sn and O sites: A DFT study
Authors: Shekhawat Pushpendra Singh , Sharma Neha , Dwivedi Umesh K. , Singh Mukhtiyar , Choudhury Sandip Paul
Published: December 2023

In this work, we have studied the electronic properties of SnO2 by employing the density functional theory. The aim of the work is to study the comparative effect of Te doping in SnO2 in Sn and O sites. The CASTEP module is used for the simulation. [Formula: see text] lattice of SnO2 was used for the study of the band structure and density of state. The electronic properties change significantly on doping the sample with Te. Also, when Te is doped in different quantities and at different sites in SnO2, the bandgap is overlapped in 0.75% Te doping at O site and the maximum is found to be 0.587 eV in 0.75% Te doping at Sn site. For pure SnO2, the bandgap is 1.064. Hence SnO2 when doped with Te influences the conductivity.
Design of an interface circuit system for mode-separation MEMS digital gyroscope
Authors: Zhang Huan , Yin Liang , Chen Weiping , Fu Qiang
Published: December 2023

In this paper, a novel digital closed-loop interface circuit system of MEMS vibrating gyroscope is proposed, which includes driving, detection and quadrature circuits. Because of the high sensitivity and precision of the MEMS gyroscope, the interface circuit system is established under the condition of mode separation. The driving circuit of MEMS gyroscope adopts digital automatic gain control (AGC) to realize self-excitation closed-loop control, which makes the gyroscope system simple in structure and good in robustness. First, the working principle of the gyroscope’s sensitive structure is introduced and the system simulation model of the sensitive structure is developed. Second, a [Formula: see text] ADC and DAC with single-bit output are designed and the feasibility of the driving circuit design is verified by the system-level model. Third, the quadrature closed-loop correction circuit is designed to reduce the coupling of the quadrature component to the gyroscope detection circuit. The simulation results show that the quadrature correction loop can effectively reduce the influence of the quadrature coupling on the detection loop of MEMS gyroscope. Finally, the system-level model of the gyroscope is established by SIMULINK, the overall system performance of the gyroscope is analyzed, and the test system of MEMS gyroscope is built by field-programmable gate array (FPGA) and application specific integrated circuit (ASIC). The experiment verifies the feasibility of the digital interface circuit design, and the zero-bias instability of the gyroscope system is 1.0∘/h.
Significance of slip velocity and couple-stress fluid lubrication on experiencing object sphere subject to Lorentz forces
Authors: Jyothi V. , Hanumagowda B. N. , Mishra Raghawendra , Tawade Jagadish. V. , Kumar Raman , Shanker B. , Kumar R. S. Varun
Published: December 2023

This study investigates the interaction between fluid dynamics and electromagnetic fields, a complex problem that has not been extensively studied. The Lorentz force, which arises due to the interaction between magnetic fields and currents in a fluid is considered in this study. This research investigates the effects of a magnetic field, couple stress, and slip velocity on the behavior of a squeeze film (SF) formed between a porous flat and spherical plate. The Stokes equation for couple stress fluids is used to produce a generalized version of the Reynolds equation, which is then used to determine the film pressure. Also, this study considers the impact of a constant magnetic field orthogonal to the plate. The fluid in the porous region is governed by modified Darcy law. The effect of a uniform magnetic field perpendicular to the plate is considered. The bearing characteristics pressure, squeeze film time, and load-carrying capacity are graphically presented. The results revealed that the load-carrying capacity, pressure, and squeeze film time are reduced with a rise in slip and porousness parameters. The slip parameter decreases the values of film pressure, squeeze time, and load-carrying capacity as related to the no-slip case.
Effortless Polite Telepresence using Intention Recognition
Authors: Daneshmand Morteza , Even Jani , Kanda Takayuki
Published: December 2023

Telepresence technology creates the opportunity for people that were traditionally left out of the workforce to work remotely. In the service industry, a pool of novice remote workers could teleoperate robots to perform short work stints to fill in the gaps left by the dwindling workforce. A hurdle is that consistently talking appropriately and politely imposes a severe mental burden on such novice operators and the quality of the service may suffer. In this study, we propose a teleoperation support system that lets novice remote workers talk freely without considering appropriateness and politeness while maintaining the quality of the service. The proposed system exploits intent recognition to transform casual utterances into predefined appropriate and polite utterances. We conducted a within-subject user study where 23 participants played the role of novice remote operators controlling a guardsman robot in charge of monitoring customers’ behaviors. We measured the workload with and without using the proposed support system using NASA task load index questionnaires. The workload was significantly lower (
p
< .001) when using the proposed support system (
M
= 46.07,
SD
= 14.36) than when not using it (
M
= 62.74,
SD
= 12.70). The effect size was large  (Cohen’s
d
= 1.23).
Against Predictive Optimization: On the Legitimacy of Decision-making Algorithms That Optimize Predictive Accuracy
Authors: Wang Angelina , Kapoor Sayash , Barocas Solon , Narayanan Arvind
Published: December 2023

We formalize predictive optimization, a category ofdecision-making algorithmsthatuse machine learning (ML)topredict future outcomesof interest aboutindividuals. For example, pre-trial risk prediction algorithms such as COMPAS use ML to predict whether an individual will re-offend in the future. Our thesis is that predictive optimization raises a distinctive and serious set of normative concerns that cause it to fail on its own terms. To test this, we review 387 reports, articles, and web pages from academia, industry, non-profits, governments, and data science contests, and we find many real-world examples of predictive optimization. We select eight particularly consequential examples as case studies. Simultaneously, we develop a set of normative and technical critiques that challenge the claims made by the developers of these applications—in particular, claims of increased accuracy, efficiency, and fairness. Our key finding is that these critiques apply to each of the applications, are not easily evaded by redesigning the systems, and thus challenge whether these applications should be deployed. We argue that the burden of evidence for justifying why the deployment of predictive optimization is not harmful should rest with the developers of the tools. Based on our analysis, we provide a rubric of critical questions that can be used to deliberate or contest specific predictive optimization applications.1
Two-Stage Perceptual Quality Oriented Rate Control Algorithm for HEVC
Authors: Yan Yunyao , Xiang Guoqing , Jia Huizhu , Chen Jie , Huang Xiaofeng , Xie Xiaodong
Published: December 2023

As a practical technique in mainstream video coding applications, rate control dominates important to ensure compression quality with limited bitrates constraints. However, most rate control methods mainly focus on objective quality while ignoring the perceptual quality improvement for human eyes. In this paper, we propose a two-stage rate control algorithm to optimize the perceptual quality at the frame encoding stage and the coding tree unit (CTU) encoding stage for high efficiency video coding (HEVC), respectively. Firstly, for the frame encoding stage, with inter-frame distortion dependency consideration, a frame-level rate control method is presented by adjusting the frame-level Lagrange multiplier adaptively with a preprocessing method. Secondly, for the CTU encoding stage, we propose a saliency-based CTU-level perceptual quality rate control algorithm, which employs CTU-level saliency weight to adjust the perceptual rate-distortion (R-D) model. We conduct the CTU-level rate control by an optimized Lagrange multiplier and quantization parameter (QP) to achieve perceptual quality optimization. Extensive experimental results reveal that, compared with state-of-the-art rate control methods on HEVC, our algorithm achieves significant perceptual coding performance with improved subjective visual quality.
A Systematic Review on Security Attacks and Countermeasures in Automotive Ethernet
Authors: De Vincenzi Marco , Costantino Gianpiero , Matteucci Ilaria , Fenzl Florian , Plappert Christian , Rieke Roland , Zelle Daniel
Published: December 2023

In the past years, the automotive industry has experienced a technological revolution driven by the increasing demand of connectivity and data to develop driver-assistance systems and autonomous vehicles, and improve the mobility experience. To provide higher bandwidth in in-vehicle communication networks, carmakers are choosing Ethernet technology, which becomes Automotive Ethernet (AE) when applied in in-vehicle communication networks. However, with the rise of vehicle connectivity, the cybersecurity of vehicle systems has become a primary concern for the automotive industry. To address this issue, we conducted a systematic review, deeply analyzing the impact of AE on security and safety, and comparing it with the current in-vehicle communication solutions like Controller Area Network protocol. We retrieved the key security attacks and mitigations proposed in the current literature to highlight their significance, including a mapping between the regulation UNECE WP.29 R155 and the retrieved answers. We found that the industry has only implemented some automotive-dedicated Ethernet solutions to date. In the near future, the vehicle and road ecosystems may require more exclusive automotive solutions to meet specific constraints such as low latency. Our results can provide a comprehensive baseline, both for industry and academia, for the current and future development of AE.
On the Complexity of Model Checking Knowledge and Time
Authors: Bozzelli Laura , Maubert Bastien , Murano Aniello
Published: December 2023

We establish the precise complexity of the model-checking problem for the main logics of knowledge and time. While this problem was known to be non-elementary for agents with perfect recall, with a number of exponentials that increases with the alternation of knowledge operators, the precise complexity of the problem when the maximum alternation is fixed has been an open problem for 20 years. We close it by establishing improved upper bounds for
CTL
* with knowledge and providing matching lower bounds that also apply for epistemic extensions of
LTL
and
CTL
. We also study the model-checking problem for these logics on systems satisfying the “no learning” property, introduced by Halpern and Vardi in their taxonomy of logics of knowledge and time, and we settle the complexity in almost all cases.
Multiple Pseudo-Siamese Network with Supervised Contrast Learning for Medical Multi-modal Retrieval
Authors: Zeng Xianhua , Wang Xinyu , Xie Yicai
Published: December 2023

Medical multi-modal retrieval aims to provide doctors with similar medical images from different modalities, which can greatly promote the efficiency and accuracy of clinical diagnosis. However, most existing medical retrieval methods hardly support the retrieval of multi-modal medical images, i.e., the number of modalities is greater than 2, and just convert retrieval to classification or clustering. It futilely breaks the gap between the visual information and the semantic information in different medical image modalities. To solve the problem, a
S
upervised
C
ontrast
L
earning method based on a
M
ultiple
P
seudo-
S
iamese network (SCL-MPS) is proposed for multi-modal medical image retrieval. In order to make the samples with semantic similarity close neighbors on Riemann manifold, the multiple constraints based on semantic consistency and modal invariance are designed in different forward stages of SCL-MPS. We theoretically demonstrate the feasibility of the designed constraints. Finally, experiments on four benchmark datasets (ADNI1, ADNI2, ADNI3, and OASIS3) show that SCL-MPS achieves state-of-the-art performance compared to 15 retrieval methods. Especially, SCL-MPS achieves a 100% mAP score in medical cross-modal retrieval on ADNI1.
Incomplete Cross-Modal Retrieval with Deep Correlation Transfer
Authors: Shi Dan , Zhu Lei , Li Jingjing , Dong Guohua , Zhang Huaxiang
Published: December 2023

Most cross-modal retrieval methods assume the multi-modal training data is complete and has a one-to-one correspondence. However, in the real world, multi-modal data generally suffers from missing modality information due to the uncertainty of data collection and storage processes, which limits the practical application of existing cross-modal retrieval methods. Although some solutions have been proposed to generate the missing modality data using a single pseudo sample, this may lead to incomplete semantic restoration and sub-optimal retrieval results due to the limited semantic information it provides. To address this challenge, this article proposes an Incomplete Cross-Modal Retrieval with Deep Correlation Transfer (ICMR-DCT) method that can robustly model incomplete multi-modal data and dynamically capture the adjacency semantic correlation for cross-modal retrieval. Specifically, we construct intra-modal graph attention-based auto-encoder to learn modality-invariant representations by performing semantic reconstruction through intra-modality adjacency correlation mining. Then, we design dual cross-modal alignment constraints to project multi-modal representations into a common semantic space, thus bridging the heterogeneous modality gap and enhancing the discriminability of the common representation. We further introduce semantic preservation to enhance adjacency semantic information and achieve cross-modal semantic correlation. Moreover, we propose a nearest-neighbor weighting integration strategy with cross-modal correlation transfer to generate the missing modality data according to inter-modality mapping relations and adjacency correlations between each sample and its neighbors, which improves the robustness of our method against incomplete multi-modal training data. Extensive experiments on three widely tested benchmark datasets demonstrate the superior performance of our method in cross-modal retrieval tasks under both complete and incomplete retrieval scenarios. Our used datasets and source codes are available at
https://github.com/shidan0122/DCT.git
.
An extended minimal model of OGTT: estimation of α- and β-cell dysfunction, insulin resistance, and the incretin effect
Authors: Subramanian Vijaya , Bagger Jonatan I. , Harihar Vinayak , Holst Jens J. , Knop Filip K. , Villsbøll Tina
Published: December 2023

A new extended model of oral glucose tolerance test (OGTT) has been developed that includes glucagon dynamics and incretin contribution to insulin secretion. The model allows the estimation of parameters related to α- and β-cell dysfunction, insulin sensitivity, and incretin action. A new function describing the influx of glucose from the gut has been introduced. A new rubric for estimating the incretin effect directly from the OGTT experiment has been developed. The effect of glucose dose was also investigated.
Short-Term Outcomes of Total Arterial Revascularization Compared to Conventional Coronary Artery Bypass Graft in Patients with Multivessel Disease and Left Ventricular Dysfunction
Authors: Lin Zhi-qin , Xu Zheng , Chen Liang-wan , Dai Xiao-fu
Published: December 2023

Background. Multivessel coronary artery disease (CAD) and left ventricular dysfunction (LVD) present challenges in CABG. We aimed to compare early outcomes of total arterial revascularization (TAR) versus conventional CABG in this high-risk population. Methods. This was a retrospective cohort study based on a single-center registry of patients who underwent isolated CABG for multivessel CAD and LVD between January 2014 and December 2022. Primary outcome was in-hospital mortality. Secondary outcomes were early complications, graft patency rate at 3 months, readmission rate within 6 months, and freedom from angina rate within 6 months. Results. A total of 112 cases were included in this study; 52 patients for TAR and 60 patients for conventional CABG. Both groups had comparable baselines and operative profiles. In-hospital mortality was similar between TAR and conventional CABG (2 deaths, 3.85% vs 4 deaths, 6.67%,

p

 = 0.810). TAR had shorter ICU (3.5 vs 5 days,

p

 = 0.016) and hospital stay (10.5 vs 12 days,

p

 = 0.007). Other postoperative complications were similar. At 3 months, TAR had superior graft patency (91.7% vs 83.7%,

p

 = 0.034) and lower 6-month readmission (TAR: 2/50, 4.0% vs. CR: 10/56, 17.9%,

p

 = 0.024). Freedom from angina rate within 6 months was similar between the two groups (TAR: 43/50, 86.0% vs. CR: 42/56, 75.0%,

p

 = 0.240). Conclusion. Our findings suggest that TAR may offer benefits in terms of shorter hospital stays, higher early graft patency, and lower readmission rates for patients with multivessel CAD and LVD. However, further research, particularly large-scale, randomized trials with longer follow-up periods, are needed to fully understand the long-term clinical outcomes and confirm these promising early results.
Effects of Roasting and Extrusion Puffing on the Antihypertensive Activity of Blended Grains in Spontaneously Hypertensive Rats
Authors: Han Byungkwon , Jeong Eun Woo , Han Areum , Baek Youjin , Kim Hyun-Joo , Lee Hyeon Gyu
Published: December 2023

We investigated the effects of processing (roasting and extrusion puffing) on the antihypertensive activity of blended grains both in vitro and in vivo. The blended grains were composed of sorghum (Sorghum bicolor), adzuki bean (Vigna angularis), and finger millet (Eleusine coracana). In the in vitro studies, total phenolic content (TPC), total flavonoid content (TFC), and angiotensin-converting enzyme (ACE) inhibitory activity of blended grains were evaluated. The results showed a significant decreasing trend in TPC, TFC, and ACE inhibitory activity in the following order: nonprocessed blended grains (NPBG) > roasted blended grains (RBG) > extrusion puffed blended grains (EPBG). Spontaneously hypertensive rats (SHRs) were fed a diet containing 40% blended grains (replacing the standard diet) for 8 weeks. None of the blended grains had any effects on feed intake, liver function, and serum lipid profile. Notably, NPBG showed the greatest reduction in systolic blood pressure compared to the model control (MC), followed by RBG, and EPBG, whereas diastolic blood pressure was significantly decreased in NPBG and RBG. Serum ACE activity and angiotensin II levels significantly decreased in all blended grains, with NPBG and RBG showing the most significant decrease in angiotensin II levels. Moreover, the mRNA expression of renin, a hormone involved in hypertension, was significantly decreased in NPBG and RBG. Only NPBG ameliorated aortic vascular remodeling compared to the MC. These results suggest that NPBG exhibited the most potent antihypertensive activity; however, roasting could be an effective processing method for maintaining antihypertensive effects compared to extrusion puffing.
Single-Cell Transcriptomics Reveals the Heterogeneity of the Immune Landscape of IDH–Wild-Type High-Grade Gliomas
Authors: Ran Xiaojuan , Zheng Jian , Chen Linchao , Xia Zhen , Wang Yin , Sun Chengfang , Guo Chen , Lin Peng , Liu Fuyi , Wang Chun , Zhou Jianguo , Sun Chongran , Liu Qichang , Ma Jianzhu , Qin Zhiyong , Zhu Xiangdong , Xie Qi
Published: December 2023

Isocitrate dehydrogenase (IDH)–wild-type (WT) high-grade gliomas, especially glioblastomas, are highly aggressive and have an immunosuppressive tumor microenvironment. Although tumor-infiltrating immune cells are known to play a critical role in glioma genesis, their heterogeneity and intercellular interactions remain poorly understood. In this study, we constructed a single-cell transcriptome landscape of immune cells from tumor tissue and matching peripheral blood mononuclear cells (PBMC) from IDH-WT high-grade glioma patients. Our analysis identified two subsets of tumor-associated macrophages (TAM) in tumors with the highest protumorigenesis signatures, highlighting their potential role in glioma progression. We also investigated the T-cell trajectory and identified the aryl hydrocarbon receptor (AHR) as a regulator of T-cell dysfunction, providing a potential target for glioma immunotherapy. We further demonstrated that knockout of AHR decreased chimeric antigen receptor (CAR) T-cell exhaustion and improved CAR T-cell antitumor efficacy both in vitro and in vivo. Finally, we explored intercellular communication mediated by ligand–receptor interactions within the tumor microenvironment and PBMCs and revealed the unique cellular interactions present in the tumor microenvironment. Taken together, our study provides a comprehensive immune landscape of IDH-WT high-grade gliomas and offers potential drug targets for glioma immunotherapy.
Evaluation of domain sulfur industry for DIA translator using bilingual evaluation understudy method
Authors: Mohammed Lateef Huda , Muter Awaad Ahmad , Ali Hameed Diadeen , Thiab Hasa Ghanim , Ameen Faisal Tahseen
Published: December 2023

Evaluation is important part of our system development cycle; it also contributes to improving new machine translation (MT) technology optimum via comparing them with the traditional systems available to determine the weaknesses and the effectiveness to be improved in the proposed MT system. This work aiming to make a study that evaluate the performance and effectivness of the domain sulfur industry (DSI) for English-Arabic DIA translator quality. The recent study has conducted evaluating by making a comparison between this programme with the prominent Google translator through applying a rendering of 1,200 English sentences in bilingual evaluation understudy (BLUE) method. The obtain results show that the efficiency of Google translator is about 30.325%, while DIA translator efficiency in domain sulfur industry is about 73.325% and it’s more effective and give a better translation accuracy. The BLUE method efficiency is about (90.478%) compared with the human expert evaluator.
A systematic literature review for smart hydroponic system
Authors: Muhasin Haifaa Jassim , Gheni Ali Yahya , Ismarau Tajuddin Nur Ilyana , Izni Nor Aziyatul , Yah Jusoh Yusmadi , Azhar Aziz Khairi
Published: December 2023

Hydroponics is the cultivation of plants by utilizing water without using soil which emphasizes the fulfillment of the nutritional needs of plants. This research has introduced smart hydroponic system that enables regular monitoring of every aspect to maintain the pH values, water, temperature, and soil. Nevertheless, there is a lack of knowledge that can systematically represent the current research. The proposed study suggests a systematic literature review of smart hydroponics system to overcome this limitation. This systematic literature review will assist practitioners draw on existing literature and propose new solutions based on available knowledge in the smart hydroponic system. The outcomes of this paper can assist future researchers by providing a guideline for user in highlighting approaches for the successful implementation of smart hydroponic system.
CaO:Tb3+  green-emitting phosphor for white light-emitted diode-phosphor applications: the improvement of light output intensity
Authors: Tung Ha Thanh , Nguyen Thi Dieu An
Published: December 2023

The use of CaO:Tb3+ with light green emission on for improvement of both luminescent output and chromatic fidelity of the white light emitted from a light-emitting diode (LED). The CaO:Tb3+ is combined with the yellow-emitting phosphor of YAG:Ce3+ to provide sufficient colored spectral proportion for the white light generation, enhancing the color performance. The phosphor combination is utilized for the three most applied LED structures: conformal, in-cup, and remote phosphor structures. The changes in optical properties of these three LEDs are monitored with adjustments in the proportion of CaO:Tb3+. The higher proportion of the green phosphor results in higher scattering efficiency in all structures, offering better color coordination and stronger luminous flux. The color quality scale is somehow reduced when CaO:Tb3+ concentration is more than a certain level. Therefore, depending on the phosphor configuration of the white light-emitting diode (WLED), the concentration of CaO:Tb3+ should be modified to achieve a good color rendition with improved color consistency and luminous properties.
The effect of thickness of a conductive nanocomposite ink printed on textile co-planar waveguide antenna
Authors: Mohd Radi Nor Hadzfizah , Ismail Mohd Muzafar , Zakaria Zahriladha , Razak Jeefferie Abd
Published: December 2023

In the area of wearable technology an enhancement of basic microstrip antenna is evolution of wearable textile antenna. A new development of wearable antenna is the incorporated of conductive plane using nanocomposite ink that embedded onto the fabric. In this paper, the performance of variety thickness of conductive Graphene-Ag-Cu ink on a drill fabric is presented. The performances include its resistivity and conductivity measurement. By performing a measurement using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and four-point probe, it can obtain and measure the composition and thickness of nanocomposite layered on a fabric and resistivity respectively. Hence, it can provide detailed information about the surface morphology, roughness, and thickness of the nanocomposite coating on the fabric as well as the electrical conductivity. Finally, the electrical conductivity increased to the fifth layered from 0.1473×104 S/cm up to 0.5393×104 S/cm.
Based on deep convolutional neural network, COVID-19 identification utilizing computed tomography scans
Authors: Yonan Janan Farag , Fadheel Fadil Raafat , Al-Doori Mohammed A. J. Hammeid , Ali Adnan Hussein
Published: December 2023

In the year 2019 specifically, on March 11th, the coronavirus illness two thousand nineteen (COVID-19) was announced a worldwide epidemic due to its rapid spread and lack of treatment options. As a result, infected individuals must be identified and quarantined quickly to prevent the illness from spreading. The method used to test for COVID-19 is called real-time-polymerase chain reaction (RT-PCR), which has problems with having low sensitivity and taking an extended amount of time. Because chest computed tomography (CT) scans are more sensitive than RT-PCR, it follows that such scans can be employed for diagnostic purposes. This study developed a deep convolutional neural network (CNN) approach to detect COVID-19 using CT scan images. An architecture of deep learning (DL) called convolutional neural network computed tomography scans (CT-CNN) was utilized to efficiently identify COVID-19. The findings of our suggested model are highly encouraging, with an accuracy of 96.14%, an F1 score of 96.21%, and a recall of 97.53% when it comes to classifying CT scans as either infected or not infected by COVID-19.
Link stability based multipath routing and effective mobility prediction in cognitive radio enabled vehicular ad hoc network
Authors: Rashid Sami AbdulJabbar , Hamdi Mustafa Maad , AbdulElah Aymen Jalil , Ahmed Rajab Yasir Jasim , Zaaile Khalid AbdulHakeem
Published: December 2023

Vehicular ad hoc networks (VANETs) provide a robust infrastructure for intelligent transportation system (ITS) applications. VANET communication involves vehicle-to-vehicle and vehicle-to-infrastructure connections, primarily with roadside units (RSUs). Analyzing cognitive radio (CR)-VANET studies revealed two key performance issues: high energy consumption and latency. To address these challenges, we propose a novel approach: link stability and mobility prediction-based clustered CR-VANETs, known as LMCCR-VANET. LMCCR-VANET consists of four main components: CR-VANET construction, clustering model, speed-based mobility prediction, and link-based multipath routing. Initially, we establish cluster-based CR-VANETs to analyze and mitigate spectrum scarcity and power utilization problems in VANETs. Mobility prediction evaluates vehicle speed variations and predictions. Finally, employing link stability-based multipath routing (LSMR) in conjunction with the fuzzy interference model and ad hoc on-demand multipath distance vector (AOMDV) routing protocol ensures stable and efficient routing. Experimental results showcase the superiority of LMCCR-VANET. It exhibits enhanced energy efficiency, delivery rates, reduced energy consumption, end-to-end latency, and routing overhead when compared to recent works such as SCCR-VANET, CFCR-VANET, and MMCR-VANET.
Skill optimization algorithm for solving optimal power flow problem
Authors: Hien Chiem Trong , Duong Minh Phuc , Pham Ly Huu
Published: December 2023

This research presents the implementation of a modern meta-heuristic algorithm called the skill optimization algorithm (SOA) to solve the optimal power flow problem (OPF). An IEEE 30-bus transmission system is selected to test the real performance of SOA. The main objective function of the study is to minimize the total fuel cost (TFC) of all thermal units. To clarify the high performance of SOA, a classical meta-heuristic named particle swarm optimization (PSO) is also applied for comparison. All results reached by SOA are compared with those of PSO on different criteria. Particularly, SOA has reached smaller cost than PSO by $1.04, equivalent to 0.13% of PSO’s TFC. Furthermore, SOA has reached a more stable performance by finding better average and maximum TFC over fifty runs. The evaluation of these criteria indicates that SOA completely outperforms PSO. Besides, the optimal solution reached by SOA satisfies all considered constraints with zero violation of the dependent variables. Therefore, SOA is highly suggested to handle the OPF problem.
Developing a model for unmanned aerial vehicle with fixed-wing using 3D-map exploring rapidly random tree technique
Authors: Dallal Bashi Omar I. , K. Hameed Husamuldeen , Al Kubaisi Yasir Mahmood , H. Sabry Ahmad
Published: December 2023

While the motion planning algorithms consider the obstacles that were known in the map, it is possible to use obstacle avoidance algorithms to take over and send commands to theunmanned aerial vehicle (UAV), when there is an unknown obstacle on the way. The rapidly random tree (RRT) algorithm is used to plan paths for a quad-copter or a fixed-wing UAV. This work develops a model for UAV with fixed-wing using a 3D map exploring the RRT technique. The first step is to obtain a 3D occupancy map from the map data stored in the UAV city to provide a map with some pre-generated obstacles. The contribution of this work is to use RRT planning for 3D state space, where the motion segment or motion primitive connecting the two consecutive states should be defined in a 3D space while satisfying the motion constraints of a UAV. The simulation includes setting up a 3D map, providing the starting and destination pose, planning a way using RRT and 3D Dubins moving primitives, smoothing the acquired trajectory, and simulating the UAV flight. The results obtained demonstrate that the smoothed-generated waypoints significantly improved tracking in general with shorter paths.
Modeling two loops RLC circuit AC power source using symbolic arithmetic differential equations
Authors: Hassan Inaam Rikan , Abed Ghuson S. , H. Sabry Ahmad
Published: December 2023

As oscillator applications, resistance-inductor-capacitor (RLC) circuits are employed in a diversity of settings. A low-pass, band-stop, band-pass, or high-pass filters can all be designed using an RLC circuit. A two-loop RLC circuit could not be represented mathematically in prior studies. Laplace transform is one type of integral transformation, which is able to resolve both second order non-uniform and uniform linear differential equations. This work solves the differential equations (DEs) of a two loops RLC circuit of an alternating voltage source by using two alternative approaches, Laplace transform (LT) and deep learning convolutional neural network (DLCNN). Initially, two DE have been declared. Next, Laplace transform is computed to solve these equations with symbolic variables for the first loop current and capacitor charge. Finally, we substitute the numerical values of the circuit elements for the symbolic variables. The charge and current initially decline exponentially. On the other hand, they oscillate over a long period of time. The capacitor charge and current initially decline exponentially and oscillate over a long period of time. The qualities of the result can be examined with a symbolic result, which is not possible with a numeric result.
Efficiency and performance ratio of photovoltaics on a 50 kWp Universitas Pamulang Viktor rooftop solar power plant
Authors: Rozak Ojak Abdul , Triyanto Aripin , Kusnadi Heri
Published: December 2023

To overcome the fossil energy crisis due to the increasing need for electrical energy, new renewable energy sources are needed. Due to technological developments in the fields of transportation, industry, household, and commercial use. Indonesia’s geography has the potential to apply new renewable energy, more specifically photovoltaic (PV). However, it is greatly influenced by environmental factors such as solar radiation, voltage, which have an impact on the output power efficiency and performance. So, it is necessary to test both measurements and calculations to see the optimization of output power and PV efficiency. From previous research, it has not been carried out, especially in the experimental method Universitas Pamulang: measurement and empirical and for a sufficiently high capacity with the aim of optimal output power. Methods of measuring sunlight intensity, voltage and current, the calculation of converting sunlight intensity to solar constellation, power, efficiency, and performance ratio (PR). The average value being 721 W/m2 an efficiency value of 19.9% and a value PR is obtained of 0.967 or 96.7% is still realistic. So that the system is declared optimal.