bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic determinants of centenarian longevity, as quantified by the 'CentPGS' score, are associated with a lower risk of multiple age-related diseases and a longer healthspan.
Authors: Sasaki Takashi , Tadaka Shu , Hirata Takumi , Nishimoto Yoshinori , Shikimoto Ryo , Abe Yukiko , Shiohama Aiko , Shirota Matsuyuki , Motoike Ikuko , Tamiya Gen , Kinoshita Kengo , Yamamoto Masayuki , Latysheva Natasha , Ledsam Joseph , Kayama Hiroshi , Momozawa Yukihide , Kubo Michiaki , Inoue Ituro , Ikeuchi Takeshi , Mori Hiroshi , Takebayashi Toru , Okano Hideyuki , Suematsu Makoto , Kosaki Kenjiro , Hirose Nobuyoshi , Arai Yasumichi
Published: April 2024

Centenarians exhibit remarkable longevity, and exploring the genetic determinants of that longevity is crucial for understanding the mechanisms of human ageing. Although APOE4 is the most common implicated negative factor in longevity, other genetic factors and their associated phenotypes are not fully understood. We conducted a genome-wide association study (GWAS) of 964 Japanese centenarians (including 173 supercentenarians) and 7,306 controls to identify the genetic components of longevity and the correlated phenotypes. GWAS summary statistics revealed that the genetic components of longevity were negatively associated with the risk of multiple age-related diseases and biometrics. Survival analysis indicated that a polygenic score derived from these summary statistics, called CentPGS, was correlated with healthspan in a cohort of healthy older people. This association was independent of APOE4 genotype and sex, suggesting that CentPGS is a promising genetic indicator of healthspan and may be used in future investigations into healthy longevity.
A tailored small-group instruction intervention in mathematics benefits low achievers – evidence from two stratified randomized trials
Authors: Rosholm Michael , Tonnesen Pia , Rasmussen Klaus , Overgaard Steffen , Færch Julie , Malm Signe , Harder Jimmy
Published: April 2024

Running two separate two-stage randomized trials, we implement and test three variants of a small group instruction intervention aimed at improving mathematics competencies for the 20% lowest achievers in mathematics in grades 2 and 8 in Danish public schools. We calculate immediate impacts on math competencies as well as impacts in the medium term and conduct cost-effectiveness analyses of the different intervention arms. The context is the Scandinavian welfare state with an already high quality public school system. Nevertheless, we find very large positive and cost-effective impacts of several intervention variants, some of which persist in the medium term. In particular, interventions in grade 2 tend to persist, while 8th grade interventions tend to fade out in the medium term.
Winners, losers or ties? What game theory contributes to analysing a care network for patients with amyothrophic lateral sclerosis. A pilot project with a mixed-method approach.
Authors: Ates Gülay , Jaspers Birgit , Weydt Patrick , Mücke Martin , Radbruch Lukas
Published: April 2024

The expansion of palliative care for patients with amyotrophic lateral sclerosis (ALS) developed in a region of North Rhine-Westphalia rather by chance. A specialist palliative home care team was taken aback by the numerous challenges and significant needs of patients, their caregivers and healthcare professional. A pilot study using mixed methods and a theory-based data analysis helped to comprehend the underlying mechanisms in care networks. Semi-structured expert interviews (n = 15), an assessment of 50 ALS patients and a quantitative survey of 196 hospice and palliative care services were conducted to differentiate and refine the patients’ needs. ALS patients have multifaceted needs, including physical symptoms, psychosocial and financial issues and/or spiritual needs. Addressing these comprehensive needs requires complex solutions. Healthcare professionals demonstrated a greater willingness to provide additional support and allocate more time for appointments with ALS patients compared to patients with other diseases. Sociologically, a network's effectiveness is based on jointly agreed goals. So, social networks and game theories demonstrate that shared network goals are associated with knowledge, network size, heterogeneity, interrelations, and communication. Therefore, it is possible to develop a comprehensive care concept and a regional care network for ALS.
Integrating policy measures into the assessment of household livelihood resilience to climate change in the Pumqu River Basin, Tibetan Plateau
Authors: Wang Yutong , Yan Jianzhong , Wu Ya , Xiong Sihong
Published: April 2024

In the context of climate change, improving household livelihood resilience (HLR) especially in developing areas, has become an important agenda. However, previous studies of assessing HLR have ignored the behaviors of government authorities. Therefore, this study established an HLR evaluation index system based on household endowment and government behaviour from the dimensions of buffer capacity, self-organizing capacity, learning capacity and policy measures. Based on 701 questionnaires from the Pumqu River Basin (PRB), the level of local HLR was assessed and the key indicators that hinder the HLR were identified. The preliminary results indicate that the average HLR value in the PRB was 0.242, with Nyalam county > Dinggye county > Tingri county. In each dimension, the value of policy measures far outweighed the others, indicating policy measures should be integrated into assessing HLR. However, the implementation of policy measures, such as the promotion of new crops and skills training, are still insufficient. Household endowment aspects that hinder the development of HLR are mainly savings, leadership, education level of householders and relationship resources. The research results can provide a reliable basis for local governments to improve policies. In addition, we introduce the implementation experience of certain policies in the research area, providing a reference for other developing countries.
Automating Prostate Volume Acquisition Using Abdominal Ultrasound Scans for Prostate-Specific Antigen Density Calculations
Authors: Bennett Rory Douglas , Barrett Tristan , Sushentsev Nikita , Sanmugalingam Nimalan , Lee Kang-Lung , Gnanapragasam Vincent J. , Tse Zion Tsz Ho
Published: April 2024

Proposed methods for prostate cancer screening are currently prohibitively expensive, inadequate in their detection rates, require highly trained specialists, and/or are invasive, resulting in patient discomfort. These limitations make population-wide screening for prostate cancer challenging. Machine learning techniques applied to abdominal ultrasound scanning may help alleviate some of these disadvantages. Abdominal ultrasound scans are comparatively low cost and exhibit minimal patient discomfort, and machine learning can be applied to mitigate against the high operator-dependent variability of ultrasound scanning. In this study, a state-of-the-art machine learning model was compared to an expert radiologist and trainee radiologist registrars of varying experience when estimating prostate volume from abdominal ultrasound images, a crucial step in detecting prostate cancer using prostate-specific antigen density. The machine learning model calculated prostatic volume by marking out dimensions of the prolate ellipsoid formula from two orthogonal images of the prostate acquired with abdominal ultrasound scans (which could be conducted by operators with minimal experience in a primary care setting). While both the algorithm and the registrars showed high correlation with the expert (r ≥ 0.8) it was found that the model outperformed the trainees in both accuracy (lowest average volume error of 15%) and consistency (lowest IQR of 19% and lowest average volume standard deviation of 13%). The results are promising for the future development of an automated prostate cancer screening workflow using machine learning and abdominal ultrasound scans.
ST segment elevation for diagnosis of pericardial local blood clots after coronary artery bypass grafting: a case report
Authors: wang aiwen , Yuan Zhuo , Bi Shuzhen , Chen Huanzhen , Bo Xingpeng , Zong Liang
Published: April 2024

Backgroud: Local blood clots in the pericardium are a common complication after coronary artery bypass grafting (CABG). However, it is very rare to clinical present with persistent ST-segment elevation. To date, there have been no reported cases. Case presentation: A 54-year-old male was admitted due to exertional angina. Three-vessel coronary artery disease was initially diagnosed based on Coronary angiography. The patient underwent a selective three coronary artery bypass graft (CABG) and extracted the tube the next day. But, on the second postoperative day, type I respiratory failure and type 5 myocardial infarction were diagnosed based on elevated ST segment, high-sensitivity troponin T and decreased P02 (55mmHg). The patient was given intravenous nitroglycerin and invasive mechanical ventilation. Despite these interventions, the patient's condition deteriorated on the third postoperative day. Cardiac tamponade was diagnosed based on clinical presentation and echocardiography. He underwent an emergency procedure for retrograde pericardial effusion drainage, which led to a rapid improvement in his clinical symptoms. Unfortunately, the patient subsequently developed acute hepatic and renal failure. A rethoracotomy was performed on the fifth postoperative day, which showed a large amount of blood clots on the pericardial surface and partial occlusion of the inferior vena cava reflux. The patient 's condition improved significantly and the elevated ST segment returned to normal after the surgery. On the tenth day after reoperation, laboratory tests such as liver function, renal function, and troponin T returned to normal. The patient was discharged fourteen days after the reoperation. Conclusion: Persistent ST-segment elevation as a rare but easily detectable clinical presentation of of pericardial local blood clots after CABG.
Development and validation of a nomogram for predicting preterm birth among pregnant women who had Antenatal care follow-up at University of Gondar Comprehensive Specialized Hospital using maternal and fetal characteristics: Retrospective follow-up study
Authors: Gessese Rewina Tilahun , Geremew Bisrat Misganaw , Nigatu Solomon Gedlu , Wubneh Solomon Berehe , Tesfie Tigabu Kidie
Published: April 2024

Background: - Preterm complications are the leading cause of death in children under the age of 5. Estimating the probability of a pregnant woman being at risk of preterm delivery would help to initiate preventive measures to reduce preterm delivery. The available risk prediction models used non-feasible predictors and did not consider fetal characteristics. This study aimed to develop an easily interpretable nomogram based on maternal and fetal characteristics.
Methods: - A retrospective follow-up study was conducted with a total of 1039 pregnant women who were enrolled from June 1, 2021, to June 1, 2022, at the University of Gondar Comprehensive Specialized Hospital. Stata version 17 was used for data analysis. Important predictors were selected by the least absolute shrinkage and selection operator and entered into multivariable logistic regression. Statistically and clinically significant predictors were used for the nomogram’s development. Model performance was assessed by the area under the receiver operating curve (AUROC) and calibration plot. Internal validation was done through the bootstrapping method, and decision curve analysis was performed to evaluate the clinical and public health impacts of the model
Result: - The incidence proportion of preterm birth among pregnant women was 14.15% (95%CI: 12.03, 16.27). Antepartum hemorrhage, preeclampsia, polyhydramnios, anemia, human immune virus, malpresentation, premature rupture of membrane, and diabetic mellitus were used to develop a nomogram. The nomogram had a discriminating power AUROC of 0.79 (95% CI: 0.74, 0.83) and 0.78 (95% CI: 0.73, 0.82) on the development and validation sets. The calibration plots exhibited optimal agreement between the predicted and observed values; the Hosmer-Lemeshow test yielded a P-value of 0.602. The decision curve analysis revealed that the nomogram would add net clinical benefits at threshold probabilities less than 0.8.
Conclusion: - The developed nomogram had good discriminative performance and good calibration. Using this model could help identify pregnant women at a higher risk of preterm delivery and provide interventions like corticosteroid and progesterone administration, cervical cerclage, and nutritional support.
Brain Tumor Identification using Transfer Learning with Sugeno-Fuzzy Integral
Authors: Govil Nikhil , Choudhary Shailee Lohmor , Dixit Rinku Sharma , Anand Saurabh , Rachapudi Venubabu , Patro S Gopal Krishna , N Channa Keshava Naik , Muzammil Khursheed , Islam Saiful , Khan Wahaj Ahmad
Published: April 2024

Brain tumor identification is essential in determining the cause and treatment of brain tumors, which are abnormal cell growths in the brain. The identification of brain cancers early and accurately is critical for prompt management and better patient outcomes. Significant advancement has been made in the invention of computer-aided detection systems that use sophisticated imaging methods and ML algorithms for automated brain tumor diagnosis in recent years. We provide a strategy for classifying brain tumor images into Pituitary, Glioma, and Meningioma tumors using a Sugeno fuzzy integral ensemble approach with three transfer learning approaches, namely ResNet-164, SqueezeNet, and DenseNet-201. In terms of accuracy, the proposed fuzzy ensemble strategies exceed each separate transfer learning approach. The proposed DenseNet-201 combined with SFI ensemble model has an accuracy rating of 99.19%. This framework was used to detect brain tumors in the current study, but it might potentially be built and used for medical imaging assessments of other illnesses. This solution improves the diagnostic process's efficiency and automation in the healthcare business, saving time and improving accuracy in brain tumor detection.
A Lightweight Deeplab V3+ Network Integrating Deep Transitive Transfer Learning and Attention Mechanism for Burned Area Identification
Authors: Liu Lizhi , Chen Erxue , Li Zengyuan , Guo Ying , Zhang Qiuliang , Wang Bing , Li Yu , Liu Yang
Published: April 2024

Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. To achieve the the purpose of identifying burned area accurately and efficiency from remote sensing images, a lightweight deep learning model is proposed based on Deeplab V3+, which employs the combination of attention mechanism and deep transitive transfer learning (DTTL) strategy. The lightweight MobileNet V2 network integrated with Convolutional Block Attention Module (CBAM) is designed as the backbone network to replace the traditional time-consuming Xception of Deeplab V3+. The attention mechanism is introduced to enhance the recognition ability of the proposed deep learning model, and the deep transitive transfer learning strategy is adopted to solve the problem of incorrect identification of the burned area and discontinuous edge details caused by insufficient sample size during the extraction process. For the process of DTTL, the improved Deeplab V3 + network was first pre-trained on ImageNet. Sequentially, WorldView-2 and the Sentinel-2 dataset were employed to train the proposed network based on the ImageNet pre-trained weights. Experiments were conducted to extract burned area from remote sensing images based on the trained model, and the results show that the proposed methodology can improve extraction accuracy with OA of 92.97% and Kappa of 0.819, which is higher than the comparative methods, and it can reduce the training time at the same time. We applied this methodology to identify the burned area in Western Attica region of Greece, and a satisfactory result was achieved with. OA of 93.58% and Kappa of 0.8265. This study demonstrates the effectiveness of the improved Deeplab V3 + in identifying forest burned area. which can provide valuable information for forest protection and monitoring.
A Geomagnetic Estimate of Heliospheric Modulation Potential Over the Last 175 Years
Authors: Owens Mathew J. , Barnard Luke A. , Muscheler Raimund , Herbst Konstantin , Lockwood Mike , Usoskin Ilya , Asvestari Eleanna
Published: April 2024

Galactic cosmic rays (GCRs) interact with the Earth's atmosphere to produce energetic neutrons and cosmogenic radionuclides, such as 14C. The atmosphere is partially shielded from the interstellar GCR spectrum by both the geomagnetic and solar magnetic field. Solar shielding is often expressed as the heliospheric modulation potential, φ, which consolidates information about the strength and structure of the solar magnetic field into a single parameter. For the period 1951 to today, φ can be estimated from ground-based neutron monitor data. Prior to 1950, 14C in tree rings can be used to estimate φ, and hence the solar magnetic field, back centuries or millennia. Bridging the gap in the φ record is therefore of vital importance for long-term solar reconstructions. One method is to model φ using the sunspot number (SN) record. However, the SN record is only an indirect measure of the Sun's magnetic field, introducing uncertainty, and the record suffers from calibration issues. We here present a new reconstruction of φ based on geomagnetic data, which spans both the entire duration of the neutron monitor record and stretches back to 1845, providing a significant overlap with the 14C data. We first modify and test an existing model of φ based on a number of heliospheric parameters, namely the open solar flux, FS, the heliospheric current sheet tilt angle, α, and the global heliospheric magnetic polarity, p. This modified model is applied to recently updated geomagnetic estimates of FS and cyclic variations of α and p. This approach is shown to produce an annual φ estimate in excellent agreement with that obtained from neutron monitors over 1951-2023. It also suggests that ionisation chamber estimates of φ -- which have previously been used to extend the instrumental estimate back from 1951 to 1933 -- are not well calibrated. Comparison of the new geomagnetic φ with 14C estimates of φ suggests the long-term trend is overestimated in the most recent 14C data, possibly due to hemispheric differences in the Suess effect, related to the release of carbon by the burning of fossil fuels. We suggest that the new geomagnetic estimate of φ will provide an improved basis for future calibration of long-term solar activity reconstructions.
Synergistic Effect of Isomorphism Substitution of Double Metal Ce and Ti in Y Zeolite by Post-Synthesis Treatment for Efficient Removal of Dye Contamination
Authors: Moosavifar M. , Azarmehr M. , Fathyunes L.
Published: April 2024

The cationic interaction of binary metals in zeolite frameworks is a motivating field. Isomorphous substitution of Ti and Ce in the framework of NaY zeolite has been performed using post-synthesis treatment. Dealumination of the zeolite was performed by EDTA treatment, followed by the incorporation of Ce and Ti to decorate the metals in the zeolite framework. It was achieved in two steps based on their solubility in the corresponding solvents. The stability of the zeolite framework was studied using metal loading. It has been observed that as the amount of metals increased in the zeolite, the d spacing of the crystal lattice changed. Besides, at higher loading, certain metals are introduced into the framework, and others as exchangeable cations extra-framework in the zeolite network. The spectroscopic studies were used to characterize the modified zeolite, and the catalysts were studied for their catalytic activity in the photodegradation of 4-NP. Various parameters such as temperature, reaction time, pH, catalyst amount, and 4-NP concentration were studied to optimize the process. The synthesized catalysts show good activity for the photodegradation process. The study investigated the synergetic effect of Ce and Ti on the yield of photodegradation. The mineralization of 4-NP was confirmed by COD experiments with a removal efficiency of 68.76%. The catalyst was recoverable and maintained its catalytic activity after six runs. This finding is particularly significant as it suggests that the catalyst has the potential for industrial application and cost-effectiveness.
Social isolation emanated psychological exhaustion and disconnectedness among physicians during the COVID-19 pandemic: Results of a qualitative study in Pakistan
Authors: Rashid Muhammad Abo ul Hassan , Manzoor Malik Maliha , Fischer Florian
Published: April 2024

Background: During the COVID-19 pandemic, many healthcare providers remained on call in COVID-19 wards, isolation centres, and emergency departments, caring for both infected and non-infected patients. Physicians have faced various challenges during the pandemic, including the stress of working with limited resources, the physical burden of long work hours and fear of public abuse in terms of stigmatization. Therefore, this study focusses on social-psychological aspects of isolation period of physicians during the COVID-19 pandemic.
Methods: It is a qualitative study based on responses from 14 physicians working in two hospitals located in Islamabad, which is the capital city of Pakistan (Pakistan Institute of Medical Sciences [PIMS] and PolyclinicHospital). In-depth interviews were conducted with selected physicians by using an interview guide as a tool of data collection to explore the experiences of those physicians who suffered from COVID-19 and lived in isolation as their quarantine period. The data was analyzed by using thematic analysis technique.
Results: The study explored isolation experiences of physicians during the selected period of COVID-19 and significantly found that two major themes emerged, i.e. psychological exhaustion (depression, anxiety and loneliness were subthemes) and disconnectedness (relational detachment and lack of interaction were subthemes).
Conclusions: This pandemic crisis has significantly resulted in having adverse impact on the ability of physicians to approach both potential and existing patients. Particularly in times of such a crisis, adequate measures have to be taken to address mental health issues of the health workforce.
rtpcr: a package for statistical analysis of real-time PCR data in R
Authors: Mirzaghaderi Ghader
Published: April 2024

Background: Real-time polymerase chain reaction (real-time PCR), is widely used in biological research. Various analysis methods are employed on the real-time PCR data to measure the mRNA levels under different experimental conditions.
Results: ‘rtpcr’ package was developed for amplification efficiency calculation and statistical analysis of real-time PCR data in R. By accounting for up to two reference genes and amplification efficiency values, a general calculation methodology covering both the Livak and Pfaffl methods was used. Based on the experimental conditions, the functions of the ‘rtpcr’ package use a t-test (for experiments with a two-level factor) or analysis of variance (for cases where more than two levels or factors or a blocking factor exist) to calculate the fold change (FC) or relative expression (RE). The functions further provide standard deviations and confidence limits for means, apply statistical mean comparisons and present letter mean grouping. To facilitate function application, different data sets were used as examples and the outputs were explained. An outstanding feature of ‘rtpcr’ package is providing publication-ready bar plots with various controlling arguments for experiments with up to three different factors.
Conclusions:The ‘rtpcr’ is a useful and user-friendly package for analyzing real-time PCR data. It was built based on a general method with both calculational and graphical output capabilities.
Challenges Limiting Healthcare Data Utilization for Policy Decision-Making in Tanzania: A Qualitative Panel Discussion.
Authors: Chillo Omary , Kazyoba Paul , Giattas MaryRose , Mohamed Al-Mafazy , Magembe Grace , Kitali Erick
Published: April 2024

Background: Accurate and reliable healthcare data are essential for effective policy decision-making, resource allocation, and improved health outcomes. In Tanzania, healthcare data utilization remains low, with various obstacles limiting the effective use of health information for decision-making. This study aimed to identify and understand the key obstacles that limit healthcare data utilization for policy decision-making in Tanzania, based on a qualitative panel discussion.
Methods: A qualitative research approach was employed, focusing on a panel discussion with five experts in the field of health systems and Health Management Information Systems (HMIS) during the 8th Tanzania Health Summit. The panelists were purposively selected, representing diverse backgrounds and expertise in healthcare data utilization. Data were collected from the panelists' presentations and audience interaction, with 400 participants attending the session. A thematic analysis approach was used to identify the key obstacles limiting healthcare data utilization in Tanzania.
Results: The study identifies key obstacles limiting healthcare data utilization in Tanzania, which include unskilled professionals, multiple health information systems, poor data quality, competing donor priorities, poor communication, healthcare staff fatigue, and low working morale. These challenges hinder effective data-driven decision-making and healthcare service delivery. Addressing these obstacles requires a multifaceted approach involving collaboration among stakeholders, investment in capacity building, harmonization of health information systems, improved communication, and prioritization of healthcare worker well-being.
Conclusion: The findings of this study provide valuable insights into the challenges faced in healthcare data utilization for policy decision-making in Tanzania. Addressing these obstacles is critical for enhancing the capacity of healthcare professionals, policymakers, and other stakeholders to make informed decisions based on accurate, high-quality healthcare data. The study's results can serve as a foundation for targeted interventions and policy recommendations aimed at improving healthcare data utilization in Tanzania and in similar resource-limited settings.
Formalizing BPE Tokenization
Authors: Berglund Martin , Merwe Brink van der
Published: April 2024

In this paper, we formalize practical byte pair encoding tokenization as it is used in large language models and other NLP systems. There are subtle differences between implementations, so we in particular formally define and investigate the semantics of the SentencePiece and HuggingFace tokenizers, and how they relate to each other. These differences depend on the details of how the dictionary of tokenization rules is constructed. Beyond this, we consider how tokenization can be performed in an incremental fashion, as well as doing it left-to-right using an amount of memory constant in the length of the string, enabling e.g. using a finite state string-to-string transducer.
Genome-wide analysis of the BoBZR1 family genes and transcriptome analysis in Brassica oleracea
Authors: Ullah Muhammad Asad , Shafiq Muhammad , Wahid Abdul , Ahmad Shahab
Published: April 2024

The BRASSINAZOLE-RESISTANT 1 genes play a crucial role as key regulators in Brassinosteroid (BR) signaling, which affects various plant developmental and stress-responsive aspects. Understanding regulatory mechanisms via BZR1 in modulating target genes has become a main point in research on plant BR signaling networks. Despite this, the BZR1 functioning in B. oleracea remained poorly elucidated. A complete genome-wide analysis identified 12 BZR1 genes in B. oleracea, categorized into three groups based on their gene motif and structural features. These BoBZR1s were found on eight different chromosomes. Synteny analysis between B. oleracea, Arabidopsis, and potato provided perception into their evolutionary characteristics. Promoter regions of BoBZR1 family genes in B. oleracea have shown specific cis-elements associated with hormones, stress, and plant development. The expressions analysis toward cuticular wax synthesis has revealed various expression levels of all BoBZR1 genes from wild to mutant type. Differential expressions of BoBZR1 genes were observed for all seven different tested tissues. The whole study involved systematic characterization of the BoBZR1 family, and expression patterns, in BR signaling and its extensive involvement in developmental processes in B. oleracea. Results establish a theoretical foundation for deeper investigation of BoBZR1 structure and functions in B. oleracea, specifically toward regulating plant stress.
A System for Automatic Seamless Connection of Historical Cadastral Maps
Authors: Lenc Ladislav , Baloun Josef , Martínek Jiří , Král Pavel
Published: April 2024

This paper presents a way to create a complex system for the automatic connection of individual map sheets into one seamless map. The goal is to provide a seamlessly connected map and allow its online presentation. This way, the maps will be easily available and allow much more efficient work for historians, archivists, and the general public. We also detail a set of methods for processing and analysis of historical cadastral maps and evaluate and compare the methods among them. The processed maps are hand-drawn and bring many challenges for machine processing. We focus on the following tasks: nomenclature detection and recognition; map frame detection; landmark detection, and map area segmentation. The tasks are solved utilising a combination of traditional computer vision techniques and neural networks. The experimental section concentrates on the comparison of different methods and the selection of the best candidates for the final system. Moreover, we have created two annotated datasets that are used for the evaluation of the presented methods. The datasets are publicly available for research purposes.
Consumption and the permanent income of households
Authors: Frish Roni
Published: April 2024

This study examines the household consumption utilizing data from the Israeli Consumer Expenditure Surveys and longitudinal administrative income records for 2004–2016. Three key findings challenge the predictions of the Permanent Income Hypothesis (PIH) and the Life-Cycle Hypothesis (LCH): First, households with higher income growth (2004–2016) exhibited lower consumption levels in the earlier period (2004–2007) and higher consumption in the later period (2013–2016). Second, households tend to consume a significant portion of transitory incomes immediately. Third, households without a pension plan show a marked decrease in consumption upon retirement.
Bipedal Robot Joint Trajectory Generation for Predetermined Zero Momentum Point
Authors: Aghamohammadinazari Mohammadsaeid , Azimi Mohsen
Published: April 2024

Numerous control methodologies have been proposed by researchers to develop an efficient bipedal dynamic walking robots that emulate human locomotion. In our previous works we have introduced Energy Dissipation Rate Control (EDRC) where a stable walking gait was achieved by regulating the rate of the energy dissipation, during each Impact Phases (IP). This method opposes previous works in this field where their core underlying approach revolves around modulating the robot's energy levels throughout each Single Support Phase (SSP). To ensure the stability of the biped robots, compliance with the Zero Momentum Point (ZMP) criterion is crucial. In this work, a new semi-analytical pattern generation approach is introduced to address this requirement. This new approach is capable of deriving all the robot's joint trajectories and torques by formulating the inverse kinematic and kinetic equations, along with ZMP criterion as a nonlinear state space system. For the first time in this work, it is shown how ZMP cause the coupling between the kinetic and kinematic equations which requires solving the inverse kinematic and kinetic equations simultaneously. Subsequently, this system of equation is solved by direct integration using Runge–Kutta method. Simulation results confirm the compatibility of the previously introduced EDRC method and the proposed semi-analytical pattern generation approach, as they can facilitate stable walking gait for biped robots.
‘It’s not making a decision, it’s prompting the discussions’: a qualitative study exploring stakeholders’ views on the acceptability and feasibility of advance research planning (CONSULT-ADVANCE)
Authors: Shepherd Victoria , Hood Kerenza , Wood Fiona
Published: April 2024

Background
Health and care research involving people who lack capacity to consent requires an alternative decision maker to decide whether they participate or not based on their ‘presumed will’. However, this is often unknown. Advance research planning (ARP) is a process for people who anticipate periods of impaired capacity to prospectively express their preferences about research participation and identify who they wish to be involved in future decisions. This may help to extend individuals’ autonomy by ensuring that proxy decisions are based on their actual wishes. This qualitative study aimed to explore stakeholders’ views about the acceptability and feasibility of ARP and identify barriers and facilitators to its implementation in the UK.
Methods
We conducted semi-structured interviews with 27 researchers, practitioners, and members of the public who had participated in a preceding survey. Interviews were conducted remotely between April and November 2023. Data were analysed thematically.
Results
Participants were supportive of the concept of ARP, with differing amounts of support for the range of possible ARP activities depending on the context. Six main themes were identified: 1) Planting a seed – creating opportunities to initiate/engage with ARP; 2) One part of the puzzle – using preferences expressed through ARP to inform decisions; 3) Finding the sweet spot – optimising the timing of ARP; 4) More than a piece of paper – finding the best mode for recording preferences; 5) Not shutting the door on an opportunity – minimising the risk of unintended consequences; and 6) Navigating with a compass – principles underpinning ARP to ensure safeguarding and help address inequalities. Participants also identified a number of implementation challenges, and proposed facilitative strategies that might overcome them which included embedding advance research planning in existing future planning processes and research-focused activities.
Conclusions
This study provides a routemap to implementing ARP in the UK to enable people anticipating impaired capacity to express their preferences about research, thus ensuring greater opportunities for inclusion of this under-served group, and addressing the decisional burden experienced by some family members acting as proxies. Development of interventions and guidance to support ARP is needed, with a focus on ensuring accessibility.
Scheduling Optimization of Electric Trucks for Mines Based on Energy Recovery and Hybrid Genetic Algorithm
Authors: Yan Weigang , Yu Xiaoyuan , 吴 习
Published: April 2024

In the context of increasingly stringent fuel consumption regulations, new energy trucks have become one of the equipment for mining transportation. However, the batteries of new energy trucks consume a significant amount of energy, necessitating rational planning and scheduling to reduce energy consumption. This paper explores a mine transportation scheduling solution based on a hybrid genetic algorithm, with special consideration given to the energy recovery characteristics of electric trucks. Through an analysis of battery energy consumption and recovery during truck operation, and a comprehensive consideration of factors such as transportation time between various mine nodes, road slope and length, as well as node mining and queuing time, the constraints of transportation route selection and vehicle scheduling were examined. The study establishes a multi-objective optimization model that seeks a reasonable structure while taking into account maximizing transportation volume and minimizing costs.The Dijkstra algorithm, combined with the breadth-first search algorithm, is employed to calculate suitable paths. Subsequently, the non-dominated sorting genetic algorithm is utilized for vehicle task allocation through a unique genetic encoding method. Mathematical methods, including entropy weighting, are incorporated to address the multi-objective weighting problem of automatic truck scheduling. To enhance the realism of the solution, the model also accounts for time-varying changes in road congestion and road bifurcation points traversed by truck routes. Finally, simulation experiments validate that the established energy optimization model has a positive impact on mine operations by increasing mining transportation volume, reducing costs, and minimizing wasted time. Additionally, the proposed method exhibits robustness and practicality, demonstrating certain fault adjustment capabilities.
PASK-Net: A Hybrid Network for Polyps Image Segmentation
Authors: Lv Yankun , Lu Guohao , Li Yan
Published: April 2024

Accurate segmentation of polyps is crucial in the field of medical image recognition. Attention mechanisms have been widely applied in medical image segmentation, but attention mechanisms implemented by convolution are limited in capturing multi-scale information due to the constraints of convolution kernel sizes. This linear aggregation method restricts the network's adaptability to various complex situations and has limitations in handling multi-scale information. Therefore, this paper proposes PASK-Net, which performs serial computations in both channel and spatial dimensions. In the channel dimension, a nonlinear approach is introduced to achieve neuron-adaptive receptive field sizes, addressing the problem of fixed convolutional processing range in attention mechanisms that hinders effective acquisition of multi-scale information. Meanwhile, in the spatial dimension, Channel-Prioritized Convolutional Attention (CPCA) is introduced to enhance the network's feature representation capability by aggregating multi-scale information from different-sized convolutional kernel branches, while ensuring computational efficiency. Comparative experiments on the Kvasir dataset demonstrate that, compared to other networks, the PASK module performs well on six evaluation metrics including Dice and IOU, achieving a Dice value of 87.54% and an IOU value of 80.6%, effectively improving the accuracy of polyp segmentation. Results from ablation experiments also validate the effectiveness of the module. The codes are available at https://github.com/LvYamKun/PASK-Net
Incentive affects physicians’ willingness to participate in urban-rural medical consortia: A comparative study of county and provincial hospitals in Central China
Authors: Zhang Bowen , Ma Liang , Ma Wenjie , Kang Dingding , Mao Yiqing
Published: April 2024

Objectives
This study had three aims: (a) to examine the incentive measures that effectively affect physicians’ willingness to participate in urban-rural medical consortia. (b) to analyze the differences in the level of incentives implemented by county and provincial hospitals. (c) to identify the differences in incentive effects on county-level and provincial-level physicians’ willingness to participate in projects.
Methods
An online survey in Henan Province, Central China, was conducted among 1,837 physicians, comprising 1,088 respondents from county hospitals and 749 respondents from provincial hospitals. Participants reported their demographic characteristics, altruism, collaborative projects, incentive levels and willingness to participate. Chi-square and cumulative logistic regressions were used to determine the incentive factors of participants’ willingness.
Results
(a) For all participants, the level of economic returns and rewards were positively associated with willingness to participate in urban-rural medical consortia, while the level of professional title and status promotion were negatively associated with physicians’ willingness to participate. (b) County-level hospitals had lower level of various incentives for urban-rural medical consortium projects than provincial hospitals. (c) County-level physicians who had a high level of position promotion and professional skills improvement and provincial physicians who had a high level of economic returns and rewards had a high level of willingness to participate in urban-rural medical consortia.
Conclusion
This result reveals the effectiveness of the financial incentive mechanism and the issue of inadequate implementation of non-financial incentive measures. Comprehensive incentive mechanisms should be established to increase county-level doctors’ perceptions of the benefits of incentives. The rules of financial incentives should be dominated by value-based incentives rather than volume, and non-financial incentives should be standardized implemented for provincial hospitals.
Interactive effects of natural and anthropogenic factors on heterogenetic accumulations of heavy metals in surface drinking water sources in the upper Huaihe River Basin in China
Authors: Liu Tong , Wang Mingya , Zhang Chunhui , Yang Shili , Zhang Fan , Jia Luhao , Ma Wanqi , Sui Shaob o , Liu Qingwei , Wang Mingshi
Published: April 2024

The water quality of drinking water sources within the Huaihe River Basin directly affects the life and health of 1/6 of China's population. Identifying and quantifying pollution sources and risks is crucial for water resources management. This study combines Monte-Carlo and Geodetector to analyze the water quality and eutrophication status, the study of heavy metals source and health risk assessment for adults and children. The results showed that the eutrophication degree was serious, with 67.8% of water sources evaluated as mesotrophic and 32.2% as eutrophic. The water quality and eutrophication were better in the southern mountains than in the densely populated areas of the northern region. Adults had a higher carcinogenic risk than children, while children had a higher non-carcinogenic risk than adults. Cr had the highest carcinogenic risk, with more than 99.8% of both adults and children exposed to a higher carcinogenic risk than 1×10− 6, but not exceed 1×10− 4. The non-carcinogenic risk of the metals didn’t exceed 1, except for Pb. As was mainly influenced by agricultural activities and transportation, while Cd, Cr, and Pb were mainly influenced by industrial production, especially by local textile industries, such as knitting and clothing factories. The influence of anthropogenic factors has been significantly increased after interacting with natural factors. This finding indicated that Geodetector can be a helpful method for us to understand the factors affecting the distribution patterns of heavy metals in water, and help provide a universal result for the pollution sources of drinking water sources worldwide.
Multifactorial Memetic Algorithm with Adaptive Auxiliary Tasks for Service Migration Optimization in Mobile Edge Computing
Authors: Li Guo , Liu Zhaobo , Liu Ling , Zhu Zexuan
Published: April 2024

In high-speed mobile networks, mobile edge computing is tasked with service migration optimization, i.e., assigning mobile users to the right servers to minimize the response time. Service migration optimization is a complex problem posing significant challenges to conventional optimization methods. To tackle this problem , we develop a multifactorial memetic algorithm with adaptive auxiliary tasks or MFMA-AAT for short. MFMA-AAT solves the target service migration optimization problem and an adaptively selected auxiliary task simultaneously, where the auxiliary task is a simplified version of the target problem to guide the search towards promising regions faster via knowledge transfer. Multiple auxiliary tasks are pre-constructed based on the distribution of the mobile users and the one with best improvement at each generation is selected for knowledge transfer. A community detection based memetic operator is also introduced to accelerate the local convergence of the proposed algorithm. Experimental results on test problems demonstrate that MFMA-AAT is more efficient than traditional service migration approaches and other state-of-the-art multifactorial evolutionary algorithms.
Investigating additional malignancies rates and overall survival of multiple myeloma patients: a SEER database study
Authors: Dong Nanxi , Ye Baodong , Liu Shuyan
Published: April 2024

Objective
The development of effective treatments for multiple myeloma (MM) has resulted in longer surviving of patients. However, these patients are at risk of developing additional malignancies. This study aimed to investigate rates of additional malignancies in MM patients and the median of latency. Findings from this study are expected to improve patient outcomes.
Methods
Data of MM patients with additional malignancies between 1992 and 2020 was extracted from SEER. The developed of different additional systems and malignancies were analyzed, including solid tumors and hematology. A standardized incidence ratio (SIR) for second primary malignancies (SPMs) was calculated to determine the MM risk. Cox regressions were performed to predict the risk factors associated with MM in patients with additional malignancies. Two nomograms were developed to determine the patient's probability prognosis.
Results
Regarding different additional malignancies, the most common types of solid tumors of prior malignancies (PMs) and SPMs are prostate cancer. Non-Hodgkin's lymphoma (NHL) as an additional malignancy of MM is the most frequent types of hematology. To construct the diagnostic nomogram, 3676 MM patients with SPMs were included. The nomogram, consisting of six independent risk factors, demonstrated high accuracy with a 3-year survival area under the curve (AUC) of 0.94400 and a 5-year survival AUC of 0.94377. Moreover, 1663 MM patients with PMs were analyzed. The diagnostic nomogram, comprising four independent risk factors, showed moderate accuracy (P < 0.05) with a 3-year survival AUC of 0.62200 and a 5-year survival AUC of 0.61743.
Conclusion
The present analysis and nomograms are expected to help clinicians in assessing individual survival outcomes of additional malignancies and implementing personalized clinical decisions. Several factors can decrease the survival rate of MM patients with SPMs including bones and joints in solid tumors, hematopoietic system disorders, occurrence of third or subsequent primary malignancies, and advanced age. During the assessment of MM patients with PMs, various parameters should be considered such as advanced age, presence of non-Hodgkin lymphoma, and development of third or subsequent primary malignancies.