bluuebunny/crossref_metadata_2025_split huggingface dataset:
Birdsongs alleviate anxiety and paranoia in healthy participants
Authors: Stobbe E. , Sundermann J. , Ascone L. , Kühn S. 
Published: May 2022

Abstract
The present study investigated the effect of urban (traffic noise) vs. natural (birdsongs) soundscapes on mood, state paranoia, and cognitive performance, hypothesizing that birdsongs lead to significant improvements in these outcomes. An additional goal was to examine the differential impact of lower vs. higher diversity of the soundscapes by manipulating the number of different typical traffic sounds or songs of different bird species within the respective soundscapes. In a randomized online experiment, 295 participants were exposed to one out of four conditions for six minutes: traffic noise low, traffic noise high, birdsong low, and birdsong high diversity soundscapes. Before and after the exposure, participants performed a digit-span and dual n-back task, and filled out depression, anxiety, and paranoia questionnaires. The traffic noise soundscapes were associated with a significant increase in depression (small effect size in low, medium effect size in high diversity condition). Concerning the birdsong conditions, depression exclusively decreased after exposure to the high diversity soundscape (small effect size). Anxiety and paranoia significantly improved in both birdsong conditions (medium effect size). For cognition, no effects were observed. In sum, the present study shows that listening to birdsongs improves anxiety, while traffic noise is generally related to higher depressiveness, regardless of diversity. Moreover, for the first time, a beneficial, medium-sized effect of a natural birdsong soundscape was demonstrated for paranoia, which bears interesting implications for further research in paranoia-prone individuals or even psychiatric samples.
Unsharp masking image enhancement the parallel algorithm based on cross-platform
Authors: Xiao Han , Song Yupu , Xiao Shiyang , Guo Baoyun , Li Cailin 
Published: May 2022

Abstract
In view of the low computational efficiency and the limitations of the platform of the unsharp masking image enhancement algorithm, an unsharp masking image enhancement parallel algorithm based on Open Computing Language (OpenCL) is proposed. Based on the analysis of the parallel characteristics of the algorithm, the problem of unsharp masking processing is implemented in parallel. Making use of the characteristics of data reuse in the algorithm, the effective allocation and optimization of global memory and constant memory are realized according to the access attributes of data and the characteristics of the OpenCL storage model, and the use efficiency of off-chip memory is improved. Through the data storage access mode, the fast computing local memory access mode is discovered, and the logical data space transformation is used to convert the storage access mode, so as to improve the bandwidth utilization of the on-chip memory. The experimental results show that, compared with the CPU serial algorithm, the OpenCL accelerated unsharp masking image enhancement parallel algorithm greatly reduces the execution time of the algorithm while maintaining the same image quality, and achieves a maximum speedup of 16.71 times. The high performance and platform transplantation of the algorithm on different hardware platforms are realized. It provides a reference method for real-time processing of a large amount of data of high-resolution images for image enhancement.
Iterated Cross Validation Method for Prediction of Survival in Diffuse Large B-cell Lymphoma for Small Size Dataset
Authors: Chang Chin-Chuan , Chen Chien-Hua , Hsieh Jer-Guang , Jeng Jyh-Horng 
Published: May 2022

Abstract
BackgroundEfforts have been made to improve the risk stratification model for patients with diffuse large B-cell lymphoma (DLBCL). This study aimed to evaluate the disease prognosis using machine learning models with iterated cross validation (CV) method.MethodsA total of 122 patients with pathologically confirmed DLBCL and receiving rituximab-containing chemotherapy were enrolled. Contributions of clinical, laboratory, and metabolic imaging parameters from fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scans to the prognosis were evaluated using five regression models, namely logistic regression, random forest, support vector classifier (SVC), deep neural network (DNN), and fuzzy neural network models. Binary classification predictions for 3-year progression free survival (PFS) and 3-year overall survival (OS) were conducted. The 10-iterated 5-fold CV with shuffling process was conducted to predict the capability of learning machines.ResultsThe median PFS and OS were 41.0 and 43.6 months, respectively. Two indicators were found to be independent predictors for prognosis: international prognostic index (IPI) and total metabolic tumor volume (MTVsum) from FDG PET/CT. For PFS, SVC and DNN (both with accuracy 71%) have the best predictive results, of which outperformed other algorithms. For OS, the DNN has the best predictive result (accuracy 76%).ConclusionUsing clinical and metabolic parameters as input variables, the machine learning methods with iterated CV method add the predictive values for PFS and OS evaluation in DLBCL patients.
GC-MS analysis of exhaled gas for fine detection of inflammatory diseases
Authors: Tsutsui Kensuke , Nemoto Masami , Kono Midori , Sato Takako , Yoshizawa Yukio , Yumoto Yoko , Nakagawa Ryo , Iwamoto Takeo , Wada Hiroshi , Sasaki Tasaki 
Published: May 2022

Abstract
Exhaled gas analysis is a non-invasive test ideal for continuous monitoring of biological metabolic information. We analyzed the exhaled gas of patients with inflammatory diseases for trace gas components that could serve as biomarkers that enable early detection of inflammatory diseases and assessment of treatment efficacy. Furthermore, we examined the clinical potential of this method. We enrolled 34 patients with inflammatory disease (male/female = 14/20, aged 20–89 years) and 69 healthy participants as controls (male/female ratio = 49/20 aged 30–70 years). Volatile components from exhaled gas were collected and analyzed by a gas chromatography-mass spectrometry system, and the data were examined for gender differences, age, correlation with inflammatory markers (white blood cell count, C-reactive protein, erythrocyte sedimentation rate), and changes in markers before and after treatment. The data was tested for statistical significance through discriminant analysis by Volcano plot, Analysis of variance test, principal component analysis, and cluster analysis comparing healthy and patient groups. There were no significant differences in the trace components of exhaled gas by gender or age. However, we found difference in some components of the exhaled gas between healthy and untreated patients. In addition, after treatment, gas patterns including the patient-specific components changed to a state closer to the inflammation-free status. We identified trace components in the exhaled gas of patients with inflammatory diseases and found that some of these regressed after treatment.
Synthesis and modification of Nickel /SAPO-34 Nanocatalyst for MTO Process via ultrasound and impregnation and hydrothermal methods
Authors: kianfar ehsan 
Published: May 2022

Abstract
In this paper, to research the effect of Ni on the structure and performance of the SAPO-34 catalyst, seven samples were synthesized. 3 samples were prepared via ultrasound, impregnation, and hydrothermal methods and with 2% Ni, the characteristics and performance of those samples were compared with SAPO-34 and was choosing the sole method. Then three samples were synthesized with a ratio of 3, 5, 7% Nickel then the optimized method. These catalysts were characterized by BET, NH3-TPD techniques. Cooperation of the performance of the catalysts showed that catalysts prepared by using ultrasound are more appropriate because of smaller particle size, Reduction of the expansion of the crystal, and uniform distribution of particles within the catalyst structure than the catalysts prepared by impregnation and hydrothermal method. Catalyst synthesized by ultrasound and 5% nickel, due to high crystallinity, the little size of crystals, high expanse, and suitable acid power showed the most effective possible selectivity for ethylene and propylene. The utmost ethylene and propylene selectivity for this sample was 47.89% and 35.16%. The sample was synthesized by using ultrasound and seven nickel, that possessed strong and high density of acidic sites thanks to the increasing amount of nickel, despite the reduction of particle size, was deactivated rapidly. Pure SAPO-34 was the underside selectivity to light olefins.
A Designed Photoenzyme Promotes Enantioselective [2+2]-Cycloadditions via Triplet Energy Transfer
Authors: Green Anthony , Trimble Jonathan , Crawshaw Rebecca , Hardy Florence , Levy Colin , Brown Murray , Fuerst Douglas , Heyes Derren , Obexer Richard 
Published: May 2022

Abstract
The ability to programme new modes of catalysis into proteins would allow the development of enzyme families with functions beyond those found in nature. To this end, genetic code expansion methodology holds particular promise, as it allows the site-selective introduction of new functional elements into proteins as non-canonical amino acid side chains. Here, we exploit an expanded genetic code to develop a photoenzyme that operates via triplet energy transfer catalysis, a versatile mode of reactivity in organic synthesis that is currently not accessible to biocatalysis. Installation of a genetically encoded photosensitiser into the beta-propeller scaffold of DA_20_00 converts a de novo Diels-Alderase into a photoenzyme for [2+2]-cycloadditions (EnT1.0). Subsequent development and implementation of a platform for photoenzyme evolution afforded an efficient and enantioselective enzyme (EnT1.3, up to 99% e.e.) that can promote selective cycloadditions that have proven challenging to achieve with small molecule catalysts. EnT1.3 performs >300 turnovers and, in contrast to small molecule photocatalysts, can operate effectively under aerobic conditions. A 1.7 Å resolution X-ray crystal structure of an EnT1.3-product complex shows how multiple functional components work in synergy to promote efficient and selective photocatalysis. This study opens the door to a wealth of new excited-state chemistry in protein active sites and establishes the framework for developing a new generation of evolvable photocatalysts with efficiencies and specificities akin to natural enzymes.
Impact of medical checkup parameters on major adverse cardiovascular events in the general Japanese population
Authors: Sugiura Tomonori , Takase Hiroyuki , Dohi Yasuaki , Seo Yoshihiro 
Published: May 2022

Abstract
Medical checkup plays a role in the identification of individuals with increased cardiovascular risk. We assessed predictors of major adverse cardiovascular events (MACEs) among parameters examined during medical checkup in the general Japanese population. A total of 13,522 individuals (52.8 ± 12.3 years) who participated in our medical checkup program were enrolled and followed up for 64,748 person-years, with the endpoint of MACE. MACE included cardiovascular death, non-fatal myocardial infarction, unstable angina, decompensated heart failure, stroke, and other cardiovascular events that required hospitalization. During the follow-up, MACE occurred in 196 participants. The risk of MACE was significantly increased across the quartiles of baseline B-type natriuretic peptide (BNP) levels (logrank, P < 0.001). Multivariate Cox-hazard analysis demonstrated that male sex, age, systolic blood pressure, and BNP at baseline independently correlated with future MACE after adjustment for confounders, while the impact of BNP was the most significant among the variables investigated. These results suggest that BNP levels, obtained during medical checkup examination, is an independent and the most significant predictor of MACE. The inclusion of BNP as part of medical checkup parameters may improve the quality of screening for individuals at increased cardiovascular risk and prevent cardiovascular disease.
The Effect of Geographic Agglomeration on the Efficacy and Welfare Consequences of Climate Action
Authors: Sudmant Andrew 
Published: May 2022

Abstract
If national climate plans match the priorities of the average community, to what extent does it matter that many communities are very different from the average? Using a dataset of c.33,000 community GHG footprints from Lower Level Super Output Areas in England made-up of 12 emissions sources, this analysis assesses the consequences of priority areas for climate action being set at different geographic levels. Results show that setting priorities at a local level could modestly increase the share of all emissions covered by a climate action plan. This suggests that the efficacy of a climate action plan may also be modestly improved by local prioritisation of climate actions. More significantly, the share of emissions covered by climate action is found to be dramatically less variable between communities when local priorities for action are used in place of national priorities. This suggests that the welfare consequences of action may also be shared more equally when local priorities guide action. These results show that the geographic lens applied to understanding the climate challenge – independent of governance approaches or policies for action – is a meaningful consideration for the efficacy and the welfare consequences of climate action. More generally, engaging with the effect of geographic agglomeration can help to inform the roles of national and local actors around prioritising and leading climate action. Further analysis is needed to understand how wider factors important to climate action, including capacity, are affected by agglomeration, whether these results hold in other nations, and how a dynamic assessment of climate action prioritisation over time might affect these results.
Comparative Study between Single Anastomosis Sleeve Jejunal Bypass, Sleeve Gastrectomy and One Anastomosis Gastric Bypass: A Prospective Randomized trial
Authors: Elrefai Mohamad , Ibrahim Ahmed , Zeid Mostafa Abu , Ezzat Helmy , Abdelgawad Mohamed , ElGeidie Ahmed 
Published: May 2022

Abstract
Background: A variety of bariatric procedures are being practiced nowadays. Laparoscopic sleeve gastrectomy (LSG) and one anastomosis gastric bypass (OAGB) are two commonly practiced bariatric procedures. Recently, single anastomosis sleeve jejunal bypass (SASJ) has emerged as a novel effective procedure with a decreased risk of malnutrition due to the presence of two pathways for food. Herein, we compared outcomes of these three procedures regarding short-term weight loss, complications, comorbidity resolution and quality of life.Patients and methods: We included a total of 60 cases in this prospective randomized study, and they were divided into three equal groups; SASJ, LSG and OAGB groups. The three procedures were performed by the same surgical team adapting standardized techniques. Weight loss parameters were our primary objectives, while secondary outcomes included post-operative complications, nutritional status, improvement/resolution of comorbidities and quality of life.Results: Operative time was significantly prolonged in the SASJ group, compared to the other two groups. Nevertheless, the incidence of post-operative complications did not significantly differ between the three groups, apart from GERD, that was more encountered in LSG group (20% of cases). Percentage of total weight loss (%TWL) were comparable among the 3 procedures; (SASJ 39.4 and 56.85%), (LSG 46.05 and 65.6%) and (OAGB 43 and 61.4%) at 6 and 12 months respectively. Comorbidity improvement, quality of life and nutritional status didn’t differ among the three study groups.Conclusion: SASJ bypass is an effective bariatric procedure regarding weight loss and comorbidity resolution, with a safe perioperative outcome comparable to OAGB and LSG.
Multi-omics construction of prognostic and immunotherapy-related gene signature and small molecule drug prediction for skin cutaneous melanoma
Authors: Xing Jiahua , Jia Ziqi , Li Yan , Han Yan 
Published: May 2022

Abstract
Background: Skin cutaneous melanoma (SKCM), a kind of skin cancer with a high rate of advanced mortality, exhibits a wide variety of driver and transmitter gene alterations in the immunological tumor microenvironment (TME) associated with tumor cell survival and proliferation.Methods: We analyzed the immunological infiltration of TME cells in normal and malignant tissues using 469 SKCM and 556 normal skin samples. We used a single sample gene set enrichment assay (ssGSEA) to quantify the relative abundance of 28 cells, developed a riskScore prognostic model using the LASSO COX regression model, and performed small molecule drug screening and molecular docking validation, which was finally validated using qRT-PCR and IHC.Results: We developed a prognosis model around seven essential protective genes for the first time, dramatically elevated in tumor tissues, as did immune cell infiltration. The results of multivariate Cox regression demonstrated that riskScore is an independent and robust prognostic indicator, and its predictive usefulness in immunotherapy was verified. Additionally, we identified Gabapentin as a possible small molecule therapeutic for SKCM.Conclusions: A riskScore model was developed in this work to analyze patient prognosis, TME cell infiltration features, and treatment responsiveness. The development of this model aid in predicting patient response to immunotherapy, but it also has significant implications for the development of novel immunotherapeutic agents and the promotion of tailored treatment regimens.
Kannada Handwritten Answer Recognition using Machine Learning Approach
Authors: S Sampathkumar 
Published: May 2022

Abstract
Handwriting recognition has been an issue of concern for many researchers and analysts throughout the previous few decades. Different applications need solution to recognize the cursive nature of handwritten text. The stated nature of written styles needs to implement. To build an efficient working OCR the main drawback is to preprocess noisy document, segment the word, character and then recognize the written text. This paper comprises the needs, relevant research towards handwritten recognition and how to process. We line-out the steps and stages used in the recognition of Kannada handwritten words. The main aim of proposed work is to identify Kannada handwritten answer written in answer booklet and to solve recognition problem by using machine learning algorithms. System provides a detailed concept on pre-processing, segmentation, classifier used to develop systematic OCR tool. The achieved accuracy is of 90% for Kannada handwritten words.
Removal mechanism of Microcystis aeruginosa in Fe2+ /sodium percarbonate and Fe2+ /sodium persulfate advanced oxidation-flocculation system
Authors: Zhai Qingyun , Song Lili , Ji Xiyan , Huang Saihua , Yu Yueshu , Ye Jing , Xu Wenwu , Hou Meifang 
Published: May 2022

Abstract
Advanced oxidation process (AOPs) can be used for the treatment of harmful algal blooms (HABs). In this study, two systems of Fe2+/sodium percarbonate (Fe2+/SPC system) and Fe2+/sodium persulfate (Fe2+/PS system) were established to explore the removal mechanism of Microcystis aeruginosa（M. aeruginosa）. The results indicated that the Fe2+/SPC system catalyzed H2O2 to generate a large amount of A for oxidation by Fe2+, and formed Fe3+ to promote the flocculation of M. aeruginosa. The persulfate was activated by Fe2+ to generate d with super-oxidizing properties, and Fe3+ was generated to realize the oxidation and flocculation of M. aeruginosa in the Fe2+/PS system. Compared with the traditional method in which the pre-oxidation and flocculation processes are carried out separately, the method in this study effectively improves the utilization rate of the flocculant and the removal effect of M. aeruginosa. The absolute value of zeta potential of Fe2+/PS system （|ζ| =0.808 mV） was significantly lower than that of Fe2+/SPC system （|ζ| =21.4 mV）（P<0.05）, which indicated that Fe2+/PS system was more favorable for the flocculation of M. aeruginosa cells than the Fe2+/SPC system.
Novel pseudo-crown ether-like lithium salt enabling fast charging/discharging high-energy lithium metal batteries
Authors: Xia Yingchun , Zhou Pan , Kong Xian , Tian Jiekang , Zhang Weili , Yan Shuaishuai , Hou Wenhui , Zhou Hangyu , Dong Hao , Chen Xiaoxia , Wang Peican , Xu Ziang , Wan Lei , Wang Baoguo , Liu Kai 
Published: May 2022

Abstract
Conventional carbonate-based electrolytes defected all racers and became a dominant leader in the lithium-ion battery industry due to superior overall performance of preferable physical, chemical and electrochemical properties. However, carbonate-based electrolytes with high corrosion towards lithium (Li) metal result in massive dendrites growth and limited cycling life, thereby blocking their application in Li metal batteries (LMBs). This is particularly true for practical LMBs with high areal capacity (> 3.5 mAh/cm2), which generally requires a high areal current density (> 1 mA/cm2) for an acceptable, realistic charging rate. Herein, we design an asymmetric functional lithium salt, lithium 1,1,1-trifluoro-N-[2-[2-(2-methoxy ethoxy)ethoxy)]ethyl] methanesulfonamide (LiFEA) that enables carbonate electrolytes with a large apparent donor number and transference number, thus leading to excellent compatibility with Li metal anodes even at high current densities. The unique pseudo-crown ether-like, folded molecular geometry endows its novel post-“self-cleaning” mechanism: the LiFEA could dissolve most undesirable organic species in the initial deposited solid electrolyte interphase (SEI) layer and gradually enrich the inorganic species. This self-cleaning behavior of LiFEA results in homogeneous and more inorganic-rich, ultrathin SEI layers (which also contributes to high-quality cathode electrolyte interphase) and, therefore, outstanding lithium metal battery performances. Advanced LiFEA-based carbonate electrolytes could achieve high-performance cyclability and fast charging/discharging performances for LMBs. Li||NCM811 half cells enabled 500 cycles with an 83.5% capacity retention for 5 C-cycling (i.e., 3 mA/cm2), and full cells allowed 100 cycles with 86.5% capacity retention for cycling under the high current density of 5.2 mA/cm2 (i.e., 2 C). Under realistic conditions, industrial Li||NCM811 metal pouch cells achieve ~ 310 Wh/kg (except taps and packing foil, 403 Wh/kg) for a cell-level energy density, enabling stable cycling up to 100 cycles under a high discharging current density of 3.66 mA/cm2 (i.e., 1 C) and yielding a record-high power density of ~ 408 W/kg (except taps and packing foil, 530 W/kg). Our designed functional lithium salt with a special molecular geometry for carbonate-based electrolytes enables a promising path to realistic LMBs with high energy and high discharging power densities.