bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on heat transfer performance of cold plate with grid channel
Authors: Zhang Kaihua , Ye Xiaojiang , Hou Zhijian , Ren Yahui , Shi Qiuyi 
Published: February 2024

AbstractThe utilization of cold plate radiators as a prevalent method for indirect liquid cooling has been extensively investigated and implemented in server cooling systems. However, there is a lack of comprehensive study on the application of this technology at the chip size, indicating a need for more development and exploration in this area. A proposal was made for a grid-channel chip cold plate heat sink to facilitate the dissipation of heat from a chip. tests were conducted to investigate the impact of the flow rate of the cold plate and the layout of the inlet and outlet on various thermal parameters, including the average temperature, maximum temperature, thermal resistance, and uniformity coefficient of the cold plate. The tests were specifically conducted under a chip power of 150W, and the accuracy of the simulation was confirmed through the use of FLUENT. The findings indicate that the cold plate effectively regulates the temperature of the chip, ensuring it remains below 85 °C throughout all experimental groups. In contrast to the single in single out configuration, the single-in multiple-out layout exhibits a higher degree of temperature uniformity within the cold plate. Nevertheless, it is important to note that augmenting the quantity of exits does not guarantee an improvement in heat transfer efficiency. This outcome is contingent upon the presence of a longitudinal flow channel shared by the outlet and intake, as well as the dispersion characteristics of the outlet. Enhancing the dispersion of the exit can significantly enhance the thermal transfer efficiency of the cold plate. Furthermore, a strategy for adjusting the aperture of the orifice is proposed as a solution to address the challenges related to flow uniformity and the issue of high pressure drop in the cold plate.
NEDD4-2 and the CLC-2 channel regulate neuronal excitability in the pathogenesis of mesial temporal lobe epilepsy
Authors: Liu Yuting , Yang Haiyan , Zeng Rongrong , He Lu , Xiao Ting , Peng Xiaomei , Kuang Zhuo , Wu Liwen 
Published: February 2024

AbstractAn increasing number of studies have focused on the role of NEDD4-2 in regulating neuronal excitability and the mechanism of epilepsy. However, the exact mechanism has not yet been elucidated. Here, we explored the roles of NEDD4-2 and the CLC-2 channel in regulating neuronal excitability and mesial temporal lobe epilepsy (MTLE) pathogenesis. First, chronic MTLE models were induced by lithium-pilocarpine in developmental rats. Coimmunoprecipitation analysis revealed that the interaction between CLC-2 and NEDD4-2. Western blot analyses indicated that NEDD4-2 expression was downregulated, while phosphorylated (P-) NEDD4-2 and CLC-2 expression was upregulated in adult MTLE rats. Then, the primary hippocampal neuronal cells were isolated and cultured, and the NEDD4-2 was knocked down by shRNA vector, resulting in decreased protein levels of CLC-2. While CLC-2 absence caused increased NEDD4-2 in cells. Next, in an epileptic cell model induced by a Mg2+-free culture, whole-cell current-clamp recording demonstrated that NEDD4-2 deficiency inhibited the spontaneous action potentials of cells, and CLC-2 absence caused more significant decrease in the spontaneous action potentials of cells. In conclusion, we herein revealed that NEDD4-2 regulates the expression of CLC-2, which is involved in neuronal excitability, and participates in the pathogenesis of MTLE.
On thermal characterization method of integrated magnetic components
Authors: Basma Bechir Mahamat , Piétroy David , Boukhari Mahamat Issa , Chahbi Zacharia , Blanchet Thomas , Chatelon Jean Pierre , Capraro Stéphane , Rousseau Jean Jacques 
Published: February 2024

AbstractThe operating temperature of integrated magnetic components can be critical. Excessively high temperature can significantly modify the properties of components, especially those of magnetic material, such as saturation magnetization and magnetic permeability. This article introduces an experimental characterization method using two different sensors. We compare the results obtained from these sensors. Initially, the method is validated using a “meander component, and subsequently, it is applied to planar spiral inductors, both with and without magnetic material.
Association of the trajectory of plasma aldosterone concentration with the risk of cardiovascular disease in patients with hypertension: a cohort study
Authors: Cai Xintian , Song Shuaiwei , Hu Junli , Zhu Qing , Shen Di , Yang Wenbo , Ma Huimin , Luo Qin , Hong Jing , Zhang Delian , Li Nanfang 
Published: February 2024

AbstractThe purpose of this study was to determine the long-term pattern of plasma aldosterone concentration (PAC) trajectories and to explore the relationship between PAC trajectory patterns and cardiovascular disease (CVD) risk in patients with hypertension. Participants were surveyed three times between 2010 and 2016, and latent mixed modeling was employed to determine the trajectory of PAC over the exposure period (2010–2016). A Cox regression analysis was used to examine the association between PAC trajectory patterns and the risk of CVD (stroke and myocardial infarction). Hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) were calculated and reported. During a median follow-up of 4.10 (3.37–4.50) years, 82 incident CVD cases (33 myocardial infarction cases and 49 stroke cases) were identified. Among all three PAC models, the high-stability PAC pattern exhibited the highest risk of CVD. After full adjustment for all covariables, HRs were 2.19 (95% CI 1.59–3.01) for the moderate-stable pattern and 2.56 (95% CI 1.68–3.91) for the high-stable pattern in comparison to the low-stable pattern. Subgroup and sensitivity analyses verified this association. The presence of a high-stable PAC trajectory pattern is associated with an elevated risk of CVD in hypertensive patients. Nevertheless, more studies are warranted to confirm these findings.
Measures of type 2 diabetes burden in Italy assessed using the AMD dataset over a twelve year span across the Great Recession
Authors: Abbafati Cristiana , Nieddu Luciano , Monasta Lorenzo 
Published: February 2024

AbstractPatients with Type 2 Diabetes Mellitus (T2DM) are rapidly increasing in Italy due to aging, preventable risk factors, and worsening socioeconomic context. T2DM and its sequelae take a heavy toll on healthcare systems and the economy, given costly management, difficulties in coping with everyday life, and decreasing patient/worker productivity. Considering long life expectancy in Italy and a decreasing mortality rate due to T2DM, this study aims to calculate the years lived with disability (YLDs) of T2DM and its sequelae grouped into three categories: Neuropathy, Chronic Kidney Disease and No Complications, taking into consideration sex, year, and geographical location. This is the first attempt to measure YLDs from data that do not rely on self-reported diabetes diagnoses. Data come from the Italian Diabetologists Association dataset, the most comprehensive longitudinal source of national outpatient data. YLDs are obtained by multiplying the number of individuals living with a specific health condition and a disability weight which represents the magnitude of health loss associated with that particular condition. Findings show increasing YLD age-standardized rates for T2DM and its sequelae, especially Neuropathy, with the trend being stronger in the central macro-region and among men, and that 2009 marks a structural change in YLD growth rate. Systematic data collection for measuring the burden of diseases is key, among other things, to policy-making and implementation.
Dickson polynomial-based secure group authentication scheme for Internet of Things
Authors: Syed Salman Ali , Manickam Selvakumar , Uddin Mueen , Alsufyani Hamed , Shorfuzzaman Mohammad , Selvarajan Shitharth , Mohammed Gouse Baig 
Published: February 2024

AbstractInternet of Things (IoT) paves the way for the modern smart industrial applications and cities. Trusted Authority acts as a sole control in monitoring and maintaining the communications between the IoT devices and the infrastructure. The communication between the IoT devices happens from one trusted entity of an area to the other by way of generating security certificates. Establishing trust by way of generating security certificates for the IoT devices in a smart city application can be of high cost and expensive. In order to facilitate this, a secure group authentication scheme that creates trust amongst a group of IoT devices owned by several entities has been proposed. The majority of proposed authentication techniques are made for individual device authentication and are also utilized for group authentication; nevertheless, a unique solution for group authentication is the Dickson polynomial based secure group authentication scheme. The secret keys used in our proposed authentication technique are generated using the Dickson polynomial, which enables the group to authenticate without generating an excessive amount of network traffic overhead. IoT devices' group authentication has made use of the Dickson polynomial. Blockchain technology is employed to enable secure, efficient, and fast data transfer among the unique IoT devices of each group deployed at different places. Also, the proposed secure group authentication scheme developed based on Dickson polynomials is resistant to replay, man-in-the-middle, tampering, side channel and signature forgeries, impersonation, and ephemeral key secret leakage attacks. In order to accomplish this, we have implemented a hardware-based physically unclonable function. Implementation has been carried using python language and deployed and tested on Blockchain using Ethereum Goerli’s Testnet framework. Performance analysis has been carried out by choosing various benchmarks and found that the proposed framework outperforms its counterparts through various metrics. Different parameters are also utilized to assess the performance of the proposed blockchain framework and shows that it has better performance in terms of computation, communication, storage and latency.
Prevalence and predictors of postcholecystectomy syndrome in Nepalese patients after 1 week of laparoscopic cholecystectomy: a cross-sectional study
Authors: Shrestha Roshani , Chayaput Prangtip , Wongkongkam Kessiri , Chanruangvanich Wallada 
Published: February 2024

AbstractPostcholecystectomy syndrome (PCS) is persistent distressing symptoms which develops following a laparoscopic cholecystectomy (LC); in cases when the condition is severe, readmission may be necessary. However, research on the prevalence of PCS and potential factors associated with PCS in Nepalese patients is still limited. An observational point-prevalence, correlational predictive cross-sectional study was conducted to determine the prevalence of PCS and examine what predicting factors including preoperative anxiety, preoperative dyspepsia, smoking, alcohol consumption, and duration of preoperative symptoms are associated with PCS. A total of 127 eligible Nepalese patients who came for follow-up after 1 week of LC at outpatient department of surgery in one single university hospital, Kathmandu, Nepal, were recruited. A set of questionnaires consisting participants' information record form, Hospital Anxiety and Depression Scale (HADS), Leeds Dyspepsia Questionnaires (LDQ), Fagerstrom Test for Nicotine Dependence (FTND), and Alcohol Use Disorder Identification Test (AUDIT) was administered for data collection. The associations between influential factors and PCS were analyzed using Binary logistic regression. 43.3% of participants reported PCS after 1 week of surgery. The findings from logistic regression analysis affirmed that the patients with preoperative anxiety (OR = 6.38, 95%CI = 2.07–19.67, p < 0.01) and moderate to severe dyspepsia (OR = 4.01, 95%CI = 1.34–12.02, p < 0.05) held the likelihood to report PCS 6.38 and 4.01 times, respectively, greater than others. The implications from study results are that screening of anxiety and patients’ tailored interventions to reduce anxiety should be implemented preoperatively. An appropriate health education about persistence of PCS and self-management should be provided to those postoperative patients.
Anthropogenic warming degrades spring air quality in Northeast Asia by enhancing atmospheric stability and transboundary transport
Authors: Ryu Young-Hee , Min Seung-Ki 
Published: February 2024

AbstractAir pollutants can travel long distances from their sources, often causing severe particulate matter (PM) pollution in downwind regions. This transboundary pollution is largely influenced by meteorology and hence its changes associated with climate change. However, the effects of anthropogenic warming on transboundary pollution remain unclear. We show that springtime PM pollution can worsen with anthropogenic warming not only in the upwind region (northern China) but also in the downwind regions (South Korea and southern Japan). The worse air quality in northern China is attributed to a shallower boundary layer due to warmer air advection in the upper levels from high-latitude Eurasia and thus increased atmospheric stability. In the downwind regions, enhanced westerly/southwesterly anomalies induced by anthropogenic warming strengthen transboundary transport. The increase in primary aerosol concentrations due to the shallower boundary layer and/or enhanced transboundary transport is ~14% in northern China, ~13% in South Korea, and ~17% in southern Japan. The elevated relative humidity due to enhanced moisture transport by the wind anomalies promotes secondary aerosol formation, which further degrades the air quality in the downwind regions. The enhancement ratio of secondary aerosols relative to changes in primary aerosols is ~1 in northern China, ~1.12 in South Korea, and ~1.18 in southern Japan due to anthropogenic warming.
Global, neuronal or β cell-specific deletion of inceptor improves glucose homeostasis in male mice with diet-induced obesity
Authors: Grandl Gerald , Collden Gustav , Feng Jin , Bhattacharya Sreya , Klingelhuber Felix , Schomann Leopold , Bilekova Sara , Ansarullah  , Xu Weiwei , Far Fataneh Fathi , Tost Monica , Gruber Tim , Bastidas-Ponce Aimée , Zhang Qian , Novikoff Aaron , Liskiewicz Arkadiusz , Liskiewicz Daniela , Garcia-Caceres Cristina , Feuchtinger Annette , Tschöp Matthias H. , Krahmer Natalie , Lickert Heiko , Müller Timo D. 
Published: February 2024

AbstractInsulin resistance is an early complication of diet-induced obesity (DIO)1, potentially leading to hyperglycaemia and hyperinsulinaemia, accompanied by adaptive β cell hypertrophy and development of type 2 diabetes2. Insulin not only signals via the insulin receptor (INSR), but also promotes β cell survival, growth and function via the insulin-like growth factor 1 receptor (IGF1R)3–6. We recently identified the insulin inhibitory receptor (inceptor) as the key mediator of IGF1R and INSR desensitization7. But, although β cell-specific loss of inceptor improves β cell function in lean mice7, it warrants clarification whether inceptor signal inhibition also improves glycaemia under conditions of obesity. We assessed the glucometabolic effects of targeted inceptor deletion in either the brain or the pancreatic β cells under conditions of DIO in male mice. In the present study, we show that global and neuronal deletion of inceptor, as well as its adult-onset deletion in the β cells, improves glucose homeostasis by enhancing β cell health and function. Moreover, we demonstrate that inceptor-mediated improvement in glucose control does not depend on inceptor function in agouti-related protein-expressing or pro-opiomelanocortin neurons. Our data demonstrate that inceptor inhibition improves glucose homeostasis in mice with DIO, hence corroborating that inceptor is a crucial regulator of INSR and IGF1R signalling.
Generating mutants of monotone affinity towards stronger protein complexes through adversarial learning
Authors: Lan Tian , Su Shuquan , Ping Pengyao , Hutvagner Gyorgy , Liu Tao , Pan Yi , Li Jinyan 
Published: February 2024

AbstractDespite breakthroughs achieved in protein sequence-to-structure and function-to-sequence predictions, the affinity-to-mutation prediction problem remains unsolved. Such a problem is of exponential complexity deemed to find a mutated protein or protein complex having a guaranteed binding-affinity change. Here we introduce an adversarial learning-based mutation method that creates optimal amino acid substitutions and changes the mutant’s affinity change significantly in a preset direction. The key aspect in our method is the adversarial training process that dynamically labels the real side of the protein data and generates fake pseudo-data accordingly to construct a deep learning architecture for guiding the mutation. The method is sufficiently flexible to generate both single- and multipointed mutations at the adversarial learning step to mimic the natural circumstances of protein evolution. Compared with random mutants, our mutated sequences have in silico exhibited more than one order of change in magnitude of binding free energy change towards stronger complexes in the case study of Novavax–angiotensin-converting enzyme-related carboxypeptidase vaccine construct optimization. We also applied the method iteratively each time, using the output as the input sequence of the next iteration, to generate paths and a landscape of mutants with affinity-increasing monotonicity to understand SARS-CoV-2 Omicron’s spike evolution. With these steps taken for effective generation of protein mutants of monotone affinity, our method will provide potential benefits to many other applications including protein bioengineering, drug design, antibody reformulation and therapeutic protein medication.
Control of complement-induced inflammatory responses to SARS-CoV-2 infection by anti-SARS-CoV-2 antibodies
Authors: Bermejo-Jambrina Marta , van der Donk Lieve EH , van Hamme John L , Wilflingseder Doris , de Bree Godelieve , Prins Maria , de Jong Menno , Nieuwkerk Pythia , van Gils Marit J , Kootstra Neeltje A , Geijtenbeek Teunis BH 
Published: February 2024

AbstractDysregulated immune responses contribute to the excessive and uncontrolled inflammation observed in severe COVID-19. However, how immunity to SARS-CoV-2 is induced and regulated remains unclear. Here, we uncover the role of the complement system in the induction of innate and adaptive immunity to SARS-CoV-2. Complement rapidly opsonizes SARS-CoV-2 particles via the lectin pathway. Complement-opsonized SARS-CoV-2 efficiently induces type-I interferon and pro-inflammatory cytokine responses via activation of dendritic cells, which are inhibited by antibodies against the complement receptors (CR) 3 and 4. Serum from COVID-19 patients, or monoclonal antibodies against SARS-CoV-2, attenuate innate and adaptive immunity induced by complement-opsonized SARS-CoV-2. Blocking of CD32, the FcγRII antibody receptor of dendritic cells, restores complement-induced immunity. These results suggest that opsonization of SARS-CoV-2 by complement is involved in the induction of innate and adaptive immunity to SARS-CoV-2 in the acute phase of infection. Subsequent antibody responses limit inflammation and restore immune homeostasis. These findings suggest that dysregulation of the complement system and FcγRII signaling may contribute to severe COVID-19.
Highly efficient catalysts for CO2 hydrogenation to formic acid in water catalyzed by hydrophobic porous polymers containing stable metal–hydride
Authors: Ma Wentao , Xiong Wenjie , Hu Jinling , Geng Jiao , Hu Xingbang 
Published: February 2024

Hydrophobic porous polymers can protect the active metal-hydride intermediate, bring highly efficient catalyst for CO2 hydrogenation to formic acid in water. An higher conversion can be achieved using p-PNP-Ir in aqueous solution.
Blockchain for finance: A survey
Authors: Wu Hanjie , Yao Qian , Liu Zhenguang , Huang Butian , Zhuang Yuan , Tang Huayun , Liu Erwu 
Published: February 2024

AbstractAs an innovative technology for enhancing authenticity, security, and risk management, blockchain is being widely adopted in trade and finance systems. The unique capabilities of blockchain, such as immutability and transparency, enable new business models of distributed data storage, point‐to‐point transactions, and decentralized autonomous organizations. Here, the authors focus on blockchain‐based securities trading, in which blockchain technology plays a vital role in financial services as it ultimately lifts trust and frees the need for third‐party verification by using consensus‐based verification. The 12 most popular blockchain platforms are investigated and 6 platforms that are related to finance are elaborated on, seeking to provide a panorama of securities trading practices. Meanwhile, this survey provides a comprehensive summary of blockchain‐based securities trading applications. Numerous practical applications of blockchain‐based securities trading are gathered and they are categorized into four distinct categories. For each category, a typical example is introduced and how blockchain contributes to solving the key problems faced by FinTech companies and researchers explained. Finally, interesting observations are provided ranging from mainstream blockchain‐based financial institutions to security issues of decentralized finance applications, aiming to picture the current blockchain ecosystem in finance.
Adaptable integrated sensing and communication for UAV‐empowered 6G networks
Authors: Yang Yan , Zhao Jianwei , Gao Feifei , Jia Weimin , Mu Di 
Published: February 2024

AbstractIntegrated sensing and communication (ISAC) is a promising technique for unmanned aerial vehicle‐empowered 6G networks. This letter proposes a novel, adaptable ISAC mechanism. Firstly, both the communication and sensing channel models under the Doppler and beam‐squint effects are investigated. Then, an adaptive sensing method is proposed by the joint design of signal echo sensing and beam‐squint sensing under practical environment. Specifically, when the echo power is larger than the minimum detectable power, the proposed method could realize the effective sensing by utilizing the system model without feedback. Otherwise, the proposed method could exploit the beam‐squint for sensing with the feedback of the sub‐carrier index. Finally, various simulation results are provided to demonstrate the effectiveness of the proposed scheme.
A method for localization TDOA estimation based on signal‐level fusion and analysis
Authors: Hu Dexiu , Wang Zewen , Huang Jie , Li Pangzhe 
Published: February 2024

AbstractPassive localization using time difference of arrival (TDOA) is one of the common methods for radiated source target localization, and its localization performance depends on the accuracy of TDOA estimation. In many localization scenarios, the signals of target are intricate and often contain multiple ones, so how to effectively extract the time difference parameters from them becomes a difficult problem. This letter proposes a signal‐level fusion method for TDOA estimation to address this problem. At the receiver terminal, multiple signals are fused to obtain their cross‐ambiguity function, so as to estimate the TDOA value for target localization. The effect of fused signals on the accuracy of TDOA estimation is analyzed and the concept of frequency depression is proposed. Simulation experiments verify that the estimation method with signal‐level fusion gets a higher accuracy of the TDOA value and a smaller position error in target localization.