bluuebunny/crossref_metadata_2025_split huggingface dataset:
Noise Learning of Instruments for High-contrast, High-resolution and Fast Hyperspectral Microscopy and Nanoscopy
Authors: Ren Bin , He Hao , Cao Maofeng , Gao Yun , Zheng Peng , Yan Sen , Zhong Jin-Hui , Wang Lei , Jin Dayong 
Published: January 2023

Abstract
Raman spectroscopy provides molecular fingerprint information of materials and live-cells in a label-free way, but the intrinsic low Raman scattering efficiency makes it vulnerable to noise. There has to be a trade-off among signal-to-noise ratio (SNR), imaging speed, and spatial and spectral resolutions when Raman spectroscopy is combined with microscopy and especially nanoscopy. Here, we report a noise learning (NL) approach that can fit the intrinsic noise distribution of each instrument by statistically learning the noise in the frequency domain. The fitted noise is then removed from the noisy spectra to improve their SNR as well as the contrast of hyperspectral images. The approach enhances the SNR by ca. 10 folds on a 12,500-spectra dataset, and suppresses the mean-square error by almost 150 folds. It significantly reduces the pixel-dwell time by 10 folds for tip-enhanced Raman imaging and the impact of drift on nanoimaging, leading to ca.2-fold improvement of the spatial resolution of 2.9 nm in air that reveals atomic-scale properties of bimetallic catalysts. We further demonstrate that NL can be broadly applied to enhance SNR in fluorescence and photoluminescence imaging, which allows the reduction of laser fluence by ca. 40 folds, thereby, circumventing the photobleaching and phototoxicity problems for long-term imaging of live-cells. NL manages the ground truth spectra and the instrumental noise simultaneously within the training dataset, and thus, bypasses the tedious labelling of the huge dataset required in conventional deep learning, which shifts deep learning from sample-dependent to instrument-dependent. NL is robust for a broad range of spectroscopic techniques for biomedical, photonic, and catalytic applications.
Reducing Cooling Water Consumption in a Solar Absorption Chiller for Mali Climates
Authors: Camara Soumaila , Sulin Aleksandr Borisovich 
Published: January 2023

Abstract
Air conditioning systems based on solar energy can be considered today as an alternative to air conditioning systems with electrical mechanical compressions to reduce building energy consumption from fossil energy sources and achieve climate change goals. This paper proposes a new concept for the efficient use of an absorption cooling system with a wet cooling tower and a type of dual-acting combined collector for DSH and NRC in accordance with the climatic conditions of Bamako. The operation of a type of dual-acting combined collector and cooling tower was studied throughout the year. The solar energy generated by the dual-acting combined collector on the first day of operation heats the water in the storage tank 1 to 80 °C after 6 to 7 hours of operation, and on subsequent days this time is reduced by 3 to 4 hours depending on the weather conditions. Thus, a dual-acting combined collector allows the system to provide cooling for an average of 8 hours per day throughout the year. The water in the cold-water tank, cooled by night radiation into space, ensures operation without turning on the cooling tower for an average of 73 minutes per day. The wet cooling tower efficiency is about 0.86, and the annual water savings in cooling tower losses due to the night operation of the dual-acting combined collector is estimated at about 35 m3.
A Two-Stage Hybrid Feature Selection Method of Communication Signals Based on Combined Scoring and Improved Binary Whale Optimization Algorithm
Authors: Liu Pengfei , Ke Jing , Zhao Hang , Shang Peng , Huang Kaijing 
Published: January 2023

Abstract
Communication signals have many modulation types in the current complex electromagnetic environment, so it is more and more difficult to recognize them accurately. Extracting features from different dimensions can describe the essence of the signals in different aspects and better distinguish various signal modulation formats. However, there may be features with poor anti-noise performance, irrelevant features and redundant features in the original high-dimensional feature set, which not only reduce the recognition probability of the signals but also make the feature selection space grow exponentially. Aiming at the problem of multi-dimensional feature selection of communication signals, this paper proposes a two-stage hybrid feature selection method based on combined scoring and improved binary whale optimization algorithm. In the first stage, the method uses the combined algorithm to initially filter the extracted signal features, and in the second stage, the improved binary whale optimization algorithm is used for further optimization. The results show that, compared with the original feature set, this method can increase the average recognition probability of the signals by up to 17%, and the feature reduction rate up to 81%. Besides, we prove that the proposed algorithm has certain generalization ability for different signal-to-noise ratio (SNR) and classifiers.
Regular penis-root masturbation: a promising behavioral treatment method for lifelong premature ejaculation
Authors: Memik Ömür , Voyvoda Bekir , Üstüner Murat , Karslı Onur , Halat Ahmed , ozcan levent 
Published: January 2023

Abstract
Purpose Premature ejaculation (PE) is a common male sexual dysfunction. Various treatments have been proposed for PE, including pharmacotherapy, behavioral therapy (BT), and combined BT and pharmacotherapy. Although pharmacotherapy is accepted as the first-line treatment for lifelong PE, high rates of discontinuation occur due to variable efficacy and side effects. In this study, the efficacy of penis-root masturbation (PRM), a newly described BT technique, was investigated in patients in whom medical treatment for PE was not successful.
Material and Methods The study included 35 patients aged 25-43 years, who were diagnosed with lifelong PE. Patients and their partners were informed about the PRM technique and asked to practice PRM three times a week for three months, with or without sexual intercourse. The patients' Premature Ejaculation Diagnostic Tool (PEDT) scores and intravaginal ejaculatory latency time (IELT) were recorded and compared before PRM training (T0) and at the third (T3) month after the start of PRM training.
Results The mean±SD PEDT scores were 16.26±1.94 at T0, 10.63±1.14 at T3. When compared to T0, the PEDT values at T3 were significantly lower (p=0.021). In terms of IELT, the mean T3 values (192.43±56.71) were significantly longer (p=0.035) than at T0 (50.43±13.84 seconds).
Conclusion PRM BT shows promise for lifelong PE patients who do not benefit from or discontinue to pharmacotherapy. Larger prospective trials are required to confirm these findings. Key words: Life-long premature ejaculation, penis root masturbation, behavioral therapy
The Relationship between Psychological Resilience and Quality of Life among the Chinese Diabetes Patients: The Mediating role of Stigma and the The Moderating role of Empowerment
Authors: Mei Yujin , Yang Xue , Gui Jiaofeng , Li Yuqing , Zhang Xiaoyun , Wang Ying , Chen Wenyue , Chen Mingjia , Liu Changjun , Zhang Lin 
Published: January 2023

Abstract
Objective: The quality of life of diabetes patients is associated with their disease or surrounding social environment. How to deal with psychological changes and adjust psychological stress response is worth further discussion. The researchers constructed moderated mediation models to test the impact of psychological resilience on the quality of life of people with diabetes, as well as the mediating role of stigma and the moderating role of empowerment.
Method: From June to September 2022, data were collected by multi-stage stratified sampling. Firstly, the First Affiliated Hospital of Wannan Medical College was randomly selected from all tertiary hospitals in Wuhu, Anhui Province. Secondly, two departments were randomly selected from this hospital: endocrinology and geriatrics. Thirdly, survey points were set up in each department, and T2DM patients were randomly selected for questionnaire surveys. In addition, we used the Connor-Davidson Elasticity Scale (CD-RISC) to measure the psychological resilience of patients, and used the Stigma Scale for Chronic Illness (SSCI) to measure stigma. Empowerment was measured by the Diabetes Empowerment Scale (DES). Quality of Life was assessed by the Diabetes Quality of Life Scale (DQoL). We used SPSS (version 21) and PROCESS (version 4.1) for data analysis.
Results: (1) Psychological resilience was negatively correlated with stigma and quality of life, and positively correlated with empowerment. Stigma was positively associated with empowerment and quality of life. Empowerment was negatively correlated with quality of life. (2) The mediation analysis showed that psychological resilience had a direct predictive effect on the quality of life, and stigma partially mediated the relationship; Empowerment moderates the first half of "PR→ stigma → quality of life"; Empowerment moderates the latter part of "PR→ stigma → quality of life."
Conclusion: Under the mediating effect of stigma, psychological resilience can improve quality of life. Empowerment has a moderating effect on the relationship between psychological resilience and stigma, and it also has a moderating effect on the relationship between stigma and quality of life. These results facilitate the understanding of the relationship mechanisms between psychological resilience and quality of life.
The Application of a Universal Assay for Identifying the Source of Fecal Contamination in Southeast Michigan Water Bodies
Authors: Jamison Megan N. , Hart John J. , Szlag David C. 
Published: January 2023

Abstract
Recreational water quality monitoring (RWQM) is an important tool to aid public health officials in preventing exposure to waterborne pathogens originating from fecal contamination. RWQM methods rely on fecal indicator bacteria (FIB) such as E. coli or enterococci. Unfortunately, E. coli and other FIB are not strict anaerobes and can naturalize and reproduce in the environment. These naturalized populations can be resuspended due to wave action or other disturbances, sometimes giving a false positive for fecal contamination using RWQM methods. This project implemented a universal marker or a non-host specific MST target to determine whether it could differentiate between recent fecal contamination and resuspended populations of bacteria. Five public beaches in southeast Michigan were monitored for FIB and MST. The non-host specific marker in addition to the FIB was successfully applied to determine whether elevated E. coli levels were caused by recent fecal contamination or resuspension.
Time step adaptivity in the method of Dahlquist, Liniger and Nevanlinna
Authors: Layton William , Pei Wenlong , Trenchea Catalin 
Published: January 2023

Abstract
Dahlquist, Liniger and Nevanlinna devised a family of one-leg two-step methods (DLN) that is second order, A- and G- stable for arbitrary, non-uniform time steps. The DLN method thus has strong potential for use in adaptive codes, but its adaptive step size selection is little explored. This report develops two approaches for the efficient local error estimation in the DLN method, and tests their use in a standard adaptivity framework. Many methods of error estimation are possible; herein we focus on two complementary estimators which involve minimal extra storage and computations. First we evaluate the local truncation error of the DLN method by Milne’s device, using the difference between the solution of the DLN method and the solution of a variable-step, explicit, second-order Adams-Bashforth-like method. Second, we use a recent refactorization of the DLN method, which eases implementation of DLN in legacy codes, to obtain an effective error estimation at no extra cost. We perform a number of numerical tests, comparing the two time adaptive DLN algorithms with some standard numerical ODE packages. Our tests indicate that the adaptive DLN method, with error estimated by Milne’s device, is an efficient and reliable method, even for stiff and unstable problems.
A Novel Clinical Prognostic Model for Breast Cancer Patients with Malignant Pleural Effusion: Avoiding Chemotherapy in Low-risk Groups?
Authors: Wang Yichen , Zhou Tao , Zhao Shanshan , Li Ning , Sun Siwen , Li Man 
Published: January 2023

Abstract
Malignant pleural effusion (MPE) is a severe complication in patients with advanced cancer that is associated with a poor prognosis, and breast cancer is the second leading cause of MPE after lung cancer. Herein, our study aimed to construct a machine learning-based model for predicting the prognosis of patients with MPE combined with breast cancer. We analyzed 196 patients with both MPE and breast cancer (143 in the training group and 53 in the external validation group). Least absolute shrinkage and selection operator and univariate Cox regression analyses were applied to identify eight key clinical variables, and a nomogram model was established. To facilitate the use of the model, an online web server was also created. Model performance was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses. Based on the ROC curves for 3-, 6-, and 12-month survival, the areas under the curves were 0.824, 0.824, and 0.818 in the training set and 0.777, 0.790, and 0.715 in the validation set, respectively. In the follow-up analysis, both systemic and intrapleural chemotherapy significantly increased survival in the high-risk group compared to the low-risk group. Collectively, we have developed a first-ever survival prediction model for breast cancer patients with newly diagnosed MPE and validated the model using an independent cohort. The model can be used to accurately predict prognosis and guide individualized treatment.
Fetal Outcomes &amp; Continuity in Perinatal Palliative Care Patients at a Quaternary Care Pediatric Hospital
Authors: Farmer Zachary , Palmaccio-Lawton Samantha , Flint Hilary , Whitford Brittney , Thienprayoon Rachel , Nee Krista 
Published: January 2023

Abstract
Objective: Perinatal palliative care (PPC) is the coordinated application of palliative care principles to the care of families, fetuses and newborns with suspected life limiting conditions. This approach relies on continuity of care that spans pregnancy, birth and beyond. The goal of this retrospective cohort study was to evaluate outcomes and PPC continuity in infants born to families who received PPC at a quaternary care pediatric hospital, and to identify targets to improve care continuity.
Study Design: PPC patients seen between July 2018 and June 2021 were identified via local PPC registry. Demographic, outcome, and continuity data were gathered from the electronic medical record. Descriptive statistics were used to calculate the rate of postnatal palliative consult and infant mortality rates.
Results: 181 mother-infant dyads were identified as having a PPC consultation and had available data following birth. Overall perinatal mortality was 65%; 51% of all liveborn infants died prior to discharge. Only 48.1 % of liveborn infants who lived for more than 24 hours received postnatal palliative care. Location of birth (primary versus non-network hospital) was significantly associated with postnatal PPC consult rate (p=0.007).
Conclusion: Continuation of palliative care after birth in families who received perinatal palliative care is inconsistently achieved. Creating reliable systems for PPC continuity will depend on location of care.
The Relationship Between Oxidative Stress and Hematological Parameters in Ghanaian Patients With Chronic Kidney Disease
Authors: Asmah Richard Harry , Archampong Timothy , Amoakohene Francis Newton , Amegatcher Gloria , Attoh Seth , Adedia David , Botchway Felix , Doku Derek , Squire Daniel 
Published: January 2023

Abstract
Background
Chronic kidney disease (CKD) is a major cause of morbidity and mortality worldwide with a rising burden in sub-Saharan Africa. Evidence from previous studies suggest high oxidative stress levels in CKD patients. Anti-oxidative enzymes such as superoxide dismutase (SOD) are impaired in kidney disease. Oxidative stress situations result in red blood cell dysfunction, platelet destruction and tissue injury. In this study we investigated hematological indices and superoxide dismutase activity during CKD.
Methods
The study utilized a cross-sectional design consecutively recruiting patients attending the Renal Unit of Korle-Bu Teaching Hospital (KBTH), Accra, with known CKD (n = 41). Healthy subjects (n = 41) from the Outpatients Department (KBTH) were recruited as controls. Blood samples were collected to determine hematological indices. The oxidative stress level in cases and control groups were determined by measuring superoxide dismutase enzyme activity. A diagnostic predictability analysis was also performed for the various parameters measured in this work.
Results
SOD activity level was significantly lower in CKD patients than in the control group (p < 0.0001). Red blood cell (r = 0.299; p = 0.039) hemoglobin (r = 0.383; p = 0.001) and hematocrit (r = 0.306; p = 0.005) correlated positively with SOD activity in cases compared with control group. Patients with CKD had significantly higher numbers of white blood cells (p < 0.0001), neutrophils (p < 0.0001) and lymphocytes (p = 0.0001) comparing with controls. White blood cell (WBC) (r= -0.331; p = 0.002), platelet levels (r= -0.234; p = 0.034) and neutrophil level (r= -0.238; p = 0.031) correlated negatively with SOD activity. In predicting CKD, SOD activity had sensitivity of 66% and specificity of 100% while WBC had higher sensitivity of 76% and comparable specificity of 90%.
Conclusion
SOD activity correlated negatively with total white blood cell, neutrophils and platelets. Red blood cells, hemoglobin concentration, and hematocrit indices had positive correlation with SOD activity. Both SOD and WBC had high specificity, 100% and 90%, respectively for the occurrence of CKD. In predicting CKD, WBC had a relatively higher sensitivity to SOD and could play a role in risk stratifying patients in resource-limited settings.
Machine learning for predicting the risk stratification of 1-5 cm gastric gastrointestinal stromal tumors based on CT
Authors: Zhang Cui , Wang Jian , Yang Yang , Dai Bailing , Xu Zhihua , Zhu Fangmei , Yu Huajun 
Published: January 2023

Abstract
Backgroud: To predict the malignancy of 1-5 cm gastric gastrointestinal stromal tumors (GISTs) in a CT risk assessment by machine learning (ML) using three models - Logistic Regression (LR), Decision Tree (DT) and Gradient Boosting Decision Tree (GBDT).
Methods: 309 patients with gastric GISTs enrolled were divided into three cohorts for training (n=161), as well as internal validation (n=70) and external validation (n=78). Scikit-learn software was used to build three classifiers. Sensitivity, specificity, accuracy and area under the curve (AUC) were calculated to evaluate the performance of three models. The diagnostic difference between ML models and radiologists were compared in internal validation cohort. Important features were analyzed and compared in LR and GBDT.
Results: GBDT achieved the largest AUC values (0.981 and 0.815) among three classifiers in training and internal validation cohorts and greatest accuracy (0.923, 0.833 and 0.844) in three cohorts. LR was found to have the largest AUC value (0.910) in external validation cohort. DT yielded the worst accuracy (0.790 and 0.727) and AUC (0.803 and 0.700) both in two validation cohorts. GBDT and LR showed more favorable performances than two radiologists. Long diameter was demonstrated to be the same and most important CT feature for GBDT and LR.
Conclusions: ML classifiers were considered to be promising in prediction of risk classification of gastric GISTs less than 5 cm based on CT, especially GBDT and LR due to the high accuracy and strong robustness. Long diameter was found as the most important feature for risk stratification.
Binary mixtures solids with nonlinear localized damping: General decay
Authors: Santos Mauro de L 
Published: January 2023

Abstract
We analyze the uniform general decay of the solution of a system modeling a mixture of two interacting continua with nonlinear localized damping acting in a arbitrary small region of the interval under consideration, assuming appropriate assumptions on the nonlinear terms. To do this, we used a observability inequality obtained for the conservative system combined with the Holmgren's uniqueness theorem and the reduction principle (see \cite{Daloutli}) where the problem of decay rates with nonlinear damping is reduced to an appropriate stabilizability inequality for the linear equation. This study generalizes and improves previous literature outcomes.
Biophysical Sequence Analysis of Functional Differences of Piezo1 and Piezo2
Authors: Phillips James 
Published: January 2023

Abstract
Because of their large size and widespread mechanosensitive interactions the only recently discovered titled transmembrane proteins have attracted much attention. Here we present and discuss their hydropathic profiles using a new method of sequence analysis. We find large-scale similarities and differences not obtainable by conventional sequence or structural studies. These differences support the evolution-towards-criticality conjecture popular among physicists. In this case the elastic properties are critical.
Effects of Natural Dietary Supplementation on Growth and Survival rate of Freshwater Ornamental Fish, Pseudotropheus demasoni (Konings, 1994)
Authors: Veeruraj Anguchamy , Ghosh Swagat , Mondal Arijit , Biswas Sumana , Ethiraj Kannapiran 
Published: January 2023

Abstract
Ornamental Fishery is one of the fast growing fisheries sector, for its increasing demands in world markets due to their attractive colour. Colouration is one of the essential supremacy qualities of the fish for consumer acceptability. Carotenoids are accountable for colouration of muscle in food fish and skin colour in ornamental fish. The present experiment was carried out to investigate the effect of three different natural feed supplements for the growth and survival rate in Demasoni Cichlids (Pseudotropheus demasoni). Totally 100 numbers of Demasoni Cichlids are equally distributed (10 fish in each tank) in ten different aquarium tanks and every 3 groups of cultural tanks were fixed with three different concentration of feed composition with remaining one fish tank as a control group. Four different treatments were selected for this present experiment with naturally obtained feed used as the base additive feed. Three different natural feed sources of raw materials tested were Dragon Fruit (Hylocereus undatus (Haw.), China Rose (Hibiscus rosasinensis L.) and Beetroot (Beta vulgaris L.), with an incorporation level of 7.5%, 10% and 12.5% respectively, including control feed without any natural feed additives. The total experiment was performed for a period of 60 days and all the fishes of each tank were fed with different feeds thrice a day. The preset study revealed that 12.5% of maximum value of crude protein was found in natural sources of dragon fruit could be incorporated in fish feed and it was expressed highest level of length and weight with 100% survival rates were found in each experimental tanks. The water quality parameters of all the experimental tanks were kept within the optimum range. The present result concluded that supplementation of incorporated Dragon Fruit, Beetroot and China Rose fish feed additives can successfully improve the growth and survival performance.