bluuebunny/crossref_metadata_2025 huggingface dataset:
«I Wanted to Avenge the Spilled Innocent Jewish Blood»: Resistance of Mizoch Jews during the Holocaust
Authors: Mykhalchuk Roman
Published: January 2023

The purpose of the study is to uncover the resistance of Volyn Jews during the Holocaust at the local level, in particular the uprising in Mizoch (Mizocz) ghetto in October 1942 and the struggle of Jews after its suppression. The author finds out the background, course, and consequences of the uprising in the ghetto, rescue and survival strategies, and the further fate of the Jews who later struggled in various partisan units, and joined the ranks of the Red Army, etc.

The scientific novelty of the study is in the fact that, for the first time in the historiography of the Holocaust, the resistance of Mizoch Jews to the Nazis during the uprising in the local ghetto, and the implementation of their individual and collective resistance as the members of various units and groups are studied. New, previously unpublished sources are introduced into scientific circulation.

Conclusions. The resistance of Volyn Jews to Nazism during the Holocaust at the local level is analyzed in the research paper. The uprising in Mizoch ghetto had the following stages: the creation of an underground in the ghetto, preparation for the uprising – getting cold weapons (they couldn’t have got any firearms), beginning of the action during the liquidation of the ghetto, setting fire to the houses, fighting with the ghetto guards, and the escaping of some Jews to the ‘Aryan side.’ Among the participants of the uprising were the representatives of the Judenrat. During the fire, some Jews died in the flames committing suicide in order not to give themselves up to the occupiers. In this context, setting fire to ghetto houses should be considered as a set of actions for the carrying out of the uprising.

After the liquidation of the ghetto, the active forms of Mizoch Jews resistance included both individual struggle (attacking the occupiers, harming their lives and health) and fighting in organized groups (participation in Soviet partisan units, Ukrainian underground, Polish self-defense, Czech groups, and detachments of the Soviet Army). Jews took revenge for the death of the representatives of their nation and their relatives not only to the German occupiers, but also to civilians who participated in the slaughtering of the Jews.

Thus, the Jews were not submissive victims of the Nazis but actively resisted from the first to the last days of the occupation on an individual and group level. The uniqueness of the Jewish resistance consisted in the absence of a single political center for the Jewish partisans to get orders from, and its specificity was in the exceptional cruelty of the Nazi regime against the Jews in comparison with other occupied peoples.
Case report: Ultrasound-guided bilateral serratus anterior plane block in intensive care unit—An alternative to opioid-sparing postoperative analgesia after sternotomy in infants
Authors: Xu MingZhe , Li Zhi , He Yi , Deng LiJing
Published: January 2023

Introduction

The high-opioid technique was applied in the setting of congenital cardiac surgery on the belief of severe pain management and analgesic limitation in children along with delayed extubation time and other side effects. Thoracic nerve blockade demonstrated superior postoperative analgesia and stable hemodynamics and lower perioperative opioid consumption and related complications in cardiac surgery. SAPB is a fascial plane block technique that is considered an alternative to paravertebral block for perioperative thoracic pain relief, targeting intercostal never.

Cases presentation

We present 3 cases to describe the efficacy of SAPB as an alternative to opioid-sparing analgesia performed in infant patients after sternotomy in pediatric cardiac intensive care units. It was successfully used as a part of perioperative pain management. All patients were extubated early and recovered soon with no other complications.

Conclusion

SAPB lowers perioperative opioid consumption and related complications in cardiac surgery with satisfactory postoperative analgesia and stable hemodynamics.
Application of survival analysis to model proliferation likelihood of Escherichia coli biofilm following laser-induced hyperthermia treatment
Authors: Burden Bradley , Rodriguez-Alvarez Juan Sebastian , Levi Nicole , Gayzik F. Scott
Published: January 2023

Eighty percent of bacterial infections associated with living tissue and medical devices are linked to drug-resistant biofilms, leading to lengthy and costly recoveries. Laser-induced hyperthermia can disrupt cell proliferation within biofilms and increase susceptibility to antibiotics. However, there can be bacterial survival differences dependent upon laser irradiation times, and prolonged time at elevated temperature can damage healthy tissue. The objective of this study was to use survival analysis to model the impact of temperature increases on reducing viable biofilm bacteria. In vitro biofilms of Escherichia coli were grown on silicone discs or silicone doped with photothermal poly(3,4-ethylenedioxythiophene) hydrate (PEDOT) nanotubes, and subjected to laser-induced hyperthermia, using a 3 W continuous wave laser at 800 nm for varying times. The number of colony forming units per milliliter (CFU/mL) and maximum temperature were measured after each trial. Survival analysis was employed to estimate bacterial cell proliferation post-treatment to provide a quantitative framework for future studies evaluating photothermal inactivation of bacterial biofilms. The results demonstrate the first application of survival analysis for predicting the likelihood of bacterial cell proliferation based on temperature.
Effect of incorporation of broccoli residues into soil on occurrence of verticillium wilt of spring-sowing-cotton and on rhizosphere microbial communities structure and function
Authors: Zhao Weisong , Wang Peipei , Dong Lihong , Li Shezeng , Lu Xiuyun , Zhang Xiaoyun , Su Zhenhe , Guo Qinggang , Ma Ping
Published: January 2023

Cotton verticillium wilt (CVW) represented a typical plant soil-borne disease and resulted in widespread economic losses in cotton production. However, the effect of broccoli residues (BR) on verticillium wilt of spring-sowing-cotton was not clear. We investigated the effects of BR on CVW, microbial communities structure and function in rhizosphere of two cotton cultivars with different CVW resistance using amplicon sequencing methods. Results showed that control effects of BR on CVW of susceptible cultivar (cv. EJ-1) and resistant cultivar (cv. J863) were 58.49% and 85.96%, and the populations of V. dahliae decreased by 14.31% and 34.19%, respectively. The bacterial diversity indices significantly increased in BR treatment, while fungal diversity indices significantly decreased. In terms of microbial community composition, the abilities to recruit bacteria and fungi were enhanced in BR treatment, including RB41, Gemmatimonas, Pontibacter, Streptomyces, Blastococcus, Massilia, Bacillus, and Gibberella, Plectosphaerella, Neocosmospora, Aspergillus and Preussia. However, the relative abundances of Sphingomonas, Nocardioides, Haliangium, Lysobacter, Penicillium, Mortierella and Chaetomidium were opposite tendency between cultivars in BR treatment. According to PICRUSt analysis, functional profiles prediction showed that significant shifts in metabolic functions impacting KEGG pathways of BR treatment were related to metabolism and biosynthesis. FUNGuild analysis indicated that BR treatment altered the relative abundances of fungal trophic modes. The results of this study demonstrated that BR treatment decreased the populations of V. dahliae in soil, increased bacterial diversity, decreased fungal diversity, changed the microbial community structure and function, and increased the abundances of beneficial microorganisms.
Fuzzy Logic, Artificial Neural Network, and Adaptive Neuro-Fuzzy Inference Methodology for Soft Computation and Modeling of Ion Sensing Data of a Terpyridyl-Imidazole Based Bifunctional Receptor
Authors: Sahoo Anik , Baitalik Sujoy
Published: January 2023

Anion and cation sensing aspects of a terpyridyl-imidazole based receptor have been utilized in this work for the fabrication of multiply configurable Boolean and fuzzy logic systems. The terpyridine moiety of the receptor is used for cation sensing through coordination, whereas the imidazole motif is utilized for anion sensing via hydrogen bonding interaction and/or anion-induced deprotonation, and the recognition event was monitored through absorption and emission spectroscopy. The receptor functions as a selective sensor for F− and Fe2+ among the studied anions and cations, respectively. Interestingly, the complexation of the receptor by Fe2+ and its decomplexation by F− and deprotonation of the receptor by F− and restoration to its initial form by acid are reversible and can be recycled. The receptor can mimic various logic operations such as combinatorial logic gate and keypad lock using its spectral responses through the sequential use of ionic inputs. Conducting very detailed sensing studies by varying the concentration of the analytes within a wide domain is often very time-consuming, laborious, and expensive. To decrease the time and expenses of the investigations, soft computing approaches such as artificial neural networks (ANNs), fuzzy logic, or adaptive neuro-fuzzy inference system (ANFIS) can be recommended to predict the experimental spectral data. Soft computing approaches to artificial intelligence (AI) include neural networks, fuzzy systems, evolutionary computation, and other tools based on statistical and mathematical optimizations. This study compares fuzzy, ANN, and ANFIS outputs to model the protonation-deprotonation and complexation-decomplexation behaviors of the receptor. Triangular membership functions (trimf) are used to model the ANFIS methodology. A good correlation is observed between experimental and model output data. The testing root mean square error (RMSE) for the ANFIS model is 0.0023 for protonation-deprotonation and 0.0036 for complexation-decomplexation data.
Al2O3-MgO Supported Ni, Mo, and NiMo Mixed Phosphidic-Sulphidic Phase for Hydrotreating of Stearic and Oleic Acids Into Green Diesel
Authors: Puello-Polo Esneyder , Arias Dana , Márquez Edgar
Published: January 2023

GRAPHICAL ABSTRACT

The sulfur and metal-type content in MoP-S/γ-Al2O3-MgO, NiMoP-S/γ-Al2O3-MgO, and NiP-S/γ-Al2O3-MgO influence the reaction pathways for hydrotreating fatty acids, improving the dispersion of MoS2 on phosphide “mixed phosphidic-sulphidic species” and increasing the number of Lewis and Brönsted sites, which correlates well with the HDO and HDCx-HDCn pathways.
Peptide-assembled nanoparticles targeting tumor cells and tumor microenvironment for cancer therapy
Authors: Zhang Meichen , Xu Haiyan
Published: January 2023

Graphical Abstract

The interactions between tumor cells and stromal cells create the tumor microenvironment (TME) which largely affects the cancer progression. The stromal cells can be grouped into three general classes: angiogenic vascular cells, infiltrating immune cells, and tumor fibrosis-related cells. This review introduces the peptide-assembled nanoparticles targeting tumor cells and three types of stromal cells for cancer therapy.
Machine-learning based automatic assessment of communication in interpreting
Authors: Wang Xiaoman , Yuan Lu
Published: January 2023

Communication assessment in interpreting has developed into an area with new models and continues to receive growing attention in recent years. The process refers to the assessment of messages composed of both “verbal” and “nonverbal” signals. A few relevant studies revolving around automatic scoring investigated the assessment of fluency based on objective temporal measures, and the correlation between the machine translation metrics and human scores. There is no research exploring machine-learning-based automatic scoring in-depth integrating parameters of delivery and information. What remains fundamentally challenging to demonstrate is which parameters, extracted through an automatic methodology, predict more reliable results. This study presents an original study with the aim to propose and test a machine learning approach to automatically assess communication in English/Chinese interpreting. It proposes to build predictive models using machine learning algorithms, extracting parameters for delivery, and applying a translation quality estimation model for information assessment to describe the final model. It employs the K-nearest neighbour algorithm and support vector machine for further analysis. It is found that the best machine-learning model built with all features by Support Vector Machine shows an accuracy of 62.96%, which is better than the K-nearest neighbour model with an accuracy of 55.56%. The assessment results of the pass level can be accurately predicted, which indicates that the machine learning models are able to screen the interpretations that pass the exam. The study is the first to build supervised machine learning models integrating both delivery and fidelity features to predict quality of interpreting. The machine learning models point to the great potential of automatic scoring with little human evaluation involved in the process. Automatic assessment of communication is expected to complete multi-tasks within a brief period by taking both holistic and analytical approaches to assess accuracy, fidelity and delivery. The proposed automatic scoring system might facilitate human-machine collaboration in the future. It can generate instant feedback for students by evaluating input renditions or abridge the workload for educators in interpreting education by screening performance for subsequent human scoring.
COVID-19 Therapies: Protease Inhibitions and Novel Degrader Strategies
Authors: Reboud-Ravaux Michèle , El Amri Chahrazade
Published: January 2023

The global spread of severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) variants is alarming. In addition to vaccines, effective antiviral agents are urgently needed to combat corona virus disease 2019 (COVID-19). In this review, we will give insights on several canonical approaches using current medicinal chemistry. They target host (TMPRSS2, cathepsins B/L, furin) and viral (3CLpro and PLPro) proteases involved in virus cell entry and virus production, respectively. Innovative mechanisms of drug action are now explored whereby the drug triggers a cellular event that reduces the level of disease-implicated protein or RNA. The potential therapeutic power of induced degradations of viral proteins by PROTACs and of RNA by RIBOTACs for the treatment of COVID-19 will be discussed. Degraders of host cell RNA-binding proteins (RNA-PROTACs) may also constitute a therapeutical opportunity. First applicated to oncology, these novel technologies may be of a particular interest to obtain therapeutics susceptible to act on mutated viruses.
Study on failure modes of a new staggered story isolated structure based on IDA method
Authors: Chen Lihao , Wang Taize , Wang Qinyue , Liu Dewen , Xiao Zhiyi , Liao Gengjie , Yang Zhuoxin , Lei Min
Published: January 2023

New staggered story isolated structure is a new type of isolated system. This paper explores the failure mode of a new staggered story isolated structure with the increment dynamic analysis (IDA) method. On the basis of a finite model of a new isolated structure with staggered stories, a failure criterion for isolated structure was established. The findings indicate that the new staggered, isolated structure has good collapse resistance. When the story angle limit is 1/100, the primary structure will fail before the isolated layer in the event of a strong earthquake, and failure typically happens at the base of the structure where components with a higher bearing capacity should be used. Under the impact of the P-δ effect, the upper isolated layer is more prone to failure than the lower isolated layer. The upper isolated layer may have a tensile stress exceeding 1MP and a horizontal displacement exceeding 385 mm, which may lead to the risk of structural overturning. Therefore, higher strength supports should be selected for the weak position of the isolated layer.
Microphysical processes under different hourly rainfall intensities in super typhoon Rammasun
Authors: Xue Yidi , Cui Xiaopeng
Published: January 2023

High-resolution numerical simulation data of super typhoon Rammasun simulated by the Weather Research and Forecasting (WRF) Model was used to study the cloud microphysical processes under different hourly rainfall intensities. The grid points in the gale circle were categorized into four types (0–5, 5–20, 20–50, and 50- mm) based on hourly rainfall. The precipitation and microphysical characteristics under different types were investigated by diagnostic and statistical methods. The results showed that on the eve of the first landfall, extremely hourly heavy precipitation (50- mm type) was significantly enhanced compared to other types. The vertical movement was significantly reduced to the middle and lower troposphere which was very conducive to the relative movement and interaction of hydrometeors with the enhancement of the collision processes. The rainfall in the 5–20 and 20–50 mm types both mostly accounted for about 40% of the total rainfall in the gale circle, while that of the 0–5 and 50- mm types were generally smaller than the former two. As the rainfall intensity increased, the absolute conversion rates of all major cloud microphysical processes had shown increasing trends, especially the non-uniformity of Cnd (the condensation of water vapor to cloud water), Pracw (the accretion of cloud water by rain) and Dgacw (the accretion of cloud water by graupel). The relative contribution of Pgmlt (the melting of graupel) increased slightly and then decreased significantly from the 20–50 mm type (36.28%) to the 50- mm type (25.06%), while that of Pracw had significantly increased especially from the 20–50 mm type (41.77%) to the 50- mm type (50.97%), which was related to the upward motion characteristics.
Seismic random noise suppression using improved CycleGAN
Authors: Sun Shimin , Li Guihua , Ding Renwei , Zhao Lihong , Zhang Yujie , Zhao Shuo , Zhang Jinwei , Ye Junlin
Published: January 2023

Random noise adversely affects the signal-to-noise ratio of complex seismic signals in complex surface conditions and media. The primary challenges related to processing seismic data have always been reducing the random noise and increasing the signal-to-noise ratio. In this study, we propose an improved cycle-consistent generative adversarial network (CycleGAN) seismic random noise suppression method. First, the generator replaces the original cycle-consistent generative adversarial network generator network structure with the Unet structure combined with the Resnet structure in order to increase the diversity of seismic data feature extraction and decrease the loss of seismic data details. Second, in order to improve the network’s stability, the feature extraction effect, the event texture preservation effect, and the signal-to-noise ratio, the Least Square GAN (LSGAN) square difference loss is used in place of the conventional generative adversarial network cross-entropy loss. The feasibility of the proposed method was confirmed using model and real seismic data, both of which demonstrated that the improved cycle-consistent generative adversarial network method effectively suppressed random noise in seismic data. In addition, the denoising effect was superior to both the widely used FX deconvolution denoising method and original cycle-consistent generative adversarial network denoising method.
Changes in online course designs: Before, during, and after the pandemic
Authors: Misiejuk Kamila , Ness Ingunn Johanne , Gray Robert , Wasson Barbara
Published: January 2023

The switch to emergency remote teaching during the COVID-19 pandemic became for many university instructors a necessity to familiarise themselves with the institution’s online learning management system (LMS). This switch to online teaching made learning activities, course design patterns, and pedagogical approaches more visible than during face-to-face teaching. Furthermore, the process of translating physical learning activities to the digital space was challenging and needed institutional and leadership support. This paper presents an analysis of the changes made to the learning designs of 102 courses in a university’s LMS before, during, and after the pandemic. Using descriptive statistics and Epistemic Network Analysis we used LMS data to explore the use of LMS features revealing not only the overall university trends, but also faculty differences. In addition, we compared the learning activities as described in course descriptions with the actual learning activities designed in the LMS. Our findings show that although the switch to emergency remote teaching forced many instructors to change the learning designs of their courses, some instructors reverted to their pre-pandemic learning designs after the pandemic, while other instructors did not change their learning design during the pandemic at all. In addition, we identified a positive trend of an increased use of activity features in the learning management system. Finally, we reflected on the importance of the university leadership supporting the digital transformation.
Middle leaders as teacher educators: The case of the Kenkyushunin (chief teacher of school research) in Japan
Authors: Yonezawa Takashi , Watanabe Takumi , Yamasaki Akane
Published: January 2023

Currently, Japan needs to create a framework that facilitates improving teachers’ professional development—a situation in which teacher educators become vital. This study focuses on the role of the kenkyushunin (chief teacher of school research) in the professional development of in-service teachers through school-based training, lesson studies, peer mentorship, and student guidance. Extant literature was analyzed to enable an in-depth understanding of their role. The findings indicated that the roles of a kenkyushunin as a teacher educator could be categorized as that of a teacher of teachers, researcher, coach, curriculum developer, and a broker. However, their role as a gatekeeper could not be confirmed. Further, their behaviors in each of these roles were also discussed. It was found that, as a school-based teacher educator, the kenkyushunin conducts lesson studies and joint research relating to the practice of teaching with colleagues and undertakes the professional development of teachers.
Altered dynamic functional architecture in type 2 diabetes mellitus
Authors: Li Yifan , Li Mingrui , Zhao Kui , Wang Yan , Tan Xin , Qin Chunhong , Rao Yawen , Sun Zhizhong , Ge Limin , Cao Zidong , Liang Yi , Qiu Shijun
Published: January 2023

Introduction

Type 2 diabetes mellitus (T2DM) can accelerate cognitive decline and even dementia so that the underlying mechanism deserves further exploration. In the resting state, brain function is still changing dynamically. At present, it is still unknown whether the dynamic functional connectivity (dFC) between various brain regions is in a stable state. It is necessary to interpret brain changes from a new perspective, that is, the stability of brain architecture.

Methods

In this study, we used a fixed dynamic time scale to explore the stability of dynamic functional architecture in T2DM, then the dynamic effective connectivity (dEC) was used to further explain how information flows through dynamically fluctuating brain architecture in T2DM.

Result

Two brain regions with decreased stability were found including the right supra-marginal gyrus (SMG) and the right median cingulate gyrus (MCG) in T2DM subjects. The dEC variation has increased between the left inferior frontal gyrus (IFG) and the right MCG. The direction of causal flow is from the right MCG to the left IFG.

Conclusion

The combination of stability and dEC can not only show the stability of dynamic functional architecture in brain but also reflect the fluidity of brain information, which is an innovative and interesting attempt in the field of neuroimaging. The changes of dynamic architecture in T2DM patients may present an innovative perspective and explanation for their cognitive decline.
The efficacy and safety of quinagolide in hyperprolactinemia treatment: A systematic review and meta-analysis
Authors: Zeng Yanyang , Huang Qingliang , Zou Yunzhi , Tan Jiacong , Zhou Wu , Li Meihua
Published: January 2023

Purpose

Three dopamine agonists [bromocriptine, cabergoline, and quinagolide (CV)] have been used for hyperprolactinemia treatment for decades. Several studies have reviewed the efficacy and safety of bromocriptine and cabergoline. However, no systematic review or meta-analysis has discussed the efficacy and safety of CV in hyperprolactinemia and prolactinoma treatment.

Methods

Five medical databases (PubMed, Web of Science, Embase, Scopus, and Cochrane Library) were searched up to 9 May 2022 to identify studies related to CV and hyperprolactinemia. A meta-analysis was implemented by using a forest plot, funnel plot, sensitivity analysis, meta-regression, and Egger’s test via software R 4.0 and STATA 12.

Results

A total of 1,211 studies were retrieved from the five medical databases, and 33 studies consisting of 827 patients were finally included in the analysis. The pooled proportions of patients with prolactin concentration normalization and tumor reduction (>50%) under CV treatment were 69% and 20%, respectively, with 95% confidence intervals of 61%–76% and 15%–28%, respectively. The pooled proportion of adverse effects was 13%, with a 95% confidence interval of 11%–16%.

Conclusion

Our study showed that CV is not less effective than cabergoline and bromocriptine in treating hyperprolactinemia, and the side effects were not significant. Hence, this drug could be considered an alternative first-line or rescue treatment in treating hyperprolactinemia in the future.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42022347750.
Relationships of adiponectin to regional adiposity, insulin sensitivity, serum lipids, and inflammatory markers in sedentary and endurance-trained Japanese young women
Authors: Guan Yaxin , Zuo Fan , Zhao Juan , Nian Xin , Shi Li , Xu Yushan , Huang Jingshan , Kazumi Tsutomu , Wu Bin
Published: January 2023

Introduction

This study aims to compare the differences in circulating adiponectin levels and their relationships to regional adiposity, insulin resistance, serum lipid, and inflammatory factors in young, healthy Japanese women with different physical activity statuses.

Methods

Adipokines (adiponectin and leptin), full serum lipid, and inflammatory factors [white blood cell counts, C-reactive protein, tumor necrosis factor-α, tissue plasminogen activator inhibitor-1 (PAI-1)] were measured in 101 sedentary and 100 endurance-trained healthy Japanese women (aged 18–23 years). Insulin sensitivity was obtained through a quantitative insulin-sensitivity check index (QUICKI). Regional adiposity [trunk fat mass (TFM), lower-body fat mass (LFM), and arm fat mass (AFM)] was evaluated using the dual-energy X-ray absorptiometry method.

Results

No significant difference was observed between the sedentary and trained women in terms of adiponectin levels. The LFM-to-TFM ratio and the high-density lipoprotein cholesterol (HDL-C) were the strong positive determinants for adiponectin in both groups. Triglyceride in the sedentary women was closely and negatively associated with adiponectin, as well as PAI-1 in the trained women. The QUICKI level was higher in the trained than sedentary women. However, no significant correlation between adiponectin and insulin sensitivity was detected in both groups. Furthermore, LFM was associated with a favorable lipid profile against cardiovascular diseases (CVDs) in the whole study cohort, but this association became insignificant when adiponectin was taken into account.

Conclusions

These findings suggest that adiponectin is primarily associated with regional adiposity and HDL-C regardless of insulin sensitivity and physical activity status in young, healthy women. The associations among adiponectin, lipid, and inflammatory factors are likely different in women with different physical activity statuses. The correlation of LFM and a favorable lipid profile against CVD and adiponectin is likely involved in this association.
Innovative technology for large-scale photovoltaic consumption using reversible solid oxide cells
Authors: Mao Hongtao , Nie Dong , Chen Xi , Cai Yanan , Zhao Jie , Zhang Xuzheng , Yu Haoyu , Ma Wanli , Lv Zepeng , Zhou Jun
Published: January 2023

It is inevitable that renewable energy consumption will increase as installed capacity continues to increase, primarily wind and photovoltaic power generation. Power to Gas (P2G) technology can store electrical energy in the form of chemical energy on a large scale. Reversible solid oxide cell (RSOC) has a very high conversion efficiency in both electrolytic gas production and fuel cell power generation compared with traditional electricity-to-gas devices. For the future integrated energy system, Reversible solid oxide cells are expected to play a significant role in integrating power generation and energy storage. This work proposes a new integrated energy system based on Reversible solid oxide cell for photovoltaic (PV) consumption. The Integrated Electricity-Gas System (IEGS) considers the two modes of electrolysis and power generation of Reversible solid oxide cell in the model. The model takes the minimum running cost as the objective function to linearize part of the model to generate a mixed integer linearization problem and solve it in GAMS. The case study shows that wind power is maximized, and the gas mixture can be transported in natural gas pipelines, improving the economics and stability of Integrated Electricity-Gas System. This work not only can reduce the operating cost of the system but also increase the high penetration of photovoltaic power generation. A quantitative assessment of the impact of hydrogen injection ratio and renewable energy penetration was also carried out.
Heterogeneous response of the stock market to CO2 emissions in China
Authors: Li Wenhui , Liu Tianzi , Wei Mengying
Published: January 2023

CO2 emissions have been a great challenge in China, especially in recent years. Meanwhile, the CO2 emissions allowance price cannot accurately reflect the CO2 emissions information in China because of the limited efficiency in China’s carbon market. Accordingly, this study constructs a CO2 emissions index and provides an empirical investigation of the heterogeneous response of stock markets to CO2 emissions. With a quantile regression approach, we document that the effect of CO2 emissions on stock returns is significant in 2021, while it is insignificant in 2019 and 2020. In addition, its influence is more significant at the upper and lower quantiles than at the median quantile. Our findings indicate that investors and the government should pay more attention to carbon risk in the future and under extreme market conditions.
Research on the pricing of PPP project ABS products based on the right of income of heating
Authors: Duan Zheng , Zhang Yifan
Published: January 2023

Introduction: The Public-Private Partnership (PPP) model has the advantages of enhancing the efficiency of social infrastructure construction and reducing the risk of government liabilities, and has been widely used and developed in China. In the current securitization of PPP project assets, the question of how to price them is key to whether the Asset-backed Securities (ABS) products can be issued successfully.

Methods: This study analyzes the pricing process and influencing factors of PPP project ABS in the context of PPP projects in China by collating the relevant literature on PPP project ABS products and collating the advantages and disadvantages of the static discounted cash flow (SCF), static spread (SS), and option-adjusted spread (OAS) methods. The study finds that the SCF and SS methods, primarily used in pricing PPP project ABS products, lack consideration of interest rate changes, early repayment rates, and multiple interest rate path options, leading to biased results. This study introduces the Monte Carlo simulation pricing method (MCSM) and conducts an empirical analysis based on the case of the Heating income right ABS of Huaxia Happiness PPP Project ABS.

Results: It is concluded that the Monte Carlo simulation method can more flexibly and accurately price PPP project ABS products with revenue rights as the underlying assets.

Discussion: This study has reference significance for the pricing of ABS products in future PPP projects and the construction of PPP projects in integrated energy service industrial parks, and can promote the development of new integrated energy service industrial parks, thereby helping to improve the energy consumption structure of enterprises in industrial parks, improve energy use efficiency, ensure the safety of energy use by enterprises, and further enhance the application of new energy by enterprises, thereby reducing their Greenhouse gas emissions.
An Approach to Correlate Chemical Pretreatment to Digestibility Through Biomass Characterization by SEM, FTIR and XRD
Authors: Sunkar Bindu , Bhukya Bhima
Published: January 2023

A comprehensive study was carried out to assess the efficiency of different chemicals on the pretreatment of plant biomass, corn cobs. The efficiency was assessed based on its effect on subsequent hydrolysis of biomass for the conversion to fermentable sugars. Both alkali- and acid-based pretreatments were carried out under optimized conditions to avoid the formation of inhibitors and also to yield more sugars. Among the different chemicals used, 2% NaOH (w/v) was found to be effective with the delignification efficiency of 84.32%, and furthermore, the biomass saccharification efficiency was found to be 86.28% using 1.20% (v/v) HNO3 at 100°C for 90 min, whereas the pretreatment with other chemicals such as KOH, NaClO2, Na2SO3, and NH3 had significantly (p < 0.05) low delignification, which ultimately reduced the saccharification efficiency. In acid–base-based pretreatment, 1.5% (v/v) HNO3 resulted in 63.42% delignification along with 68% digestion of hemicelluloses. The effect of pretreatment efficiency on digestibility was investigated by biomass characterization using SEM, FTIR, and XRD analyses before and after the treatment process. The imaging studies clearly indicated that 2% NaOH efficiently digested the complex matrix alignment and enhanced the surface area of the carbohydrate polymer which had shown a positive impact on the rate of hydrolysis. The study concludes that alkali-based pretreatment is the efficient and cost-viable technique for the effective valorization of corn cobs for the production of fermentable sugars which can be further converted to various valuable bioproducts.
Probabilistic prediction by means of the propagation of response variable uncertainty through a Monte Carlo approach in regression random forest: Application to soil moisture regionalization
Authors: Dega Ségolène , Dietrich Peter , Schrön Martin , Paasche Hendrik
Published: January 2023

Probabilistic predictions aim to produce a prediction interval with probabilities associated with each possible outcome instead of a single value for each outcome. In multiple regression problems, this can be achieved by propagating the known uncertainties in data of the response variables through a Monte Carlo approach. This paper presents an analysis of the impact of the training response variable uncertainty on the prediction uncertainties with the help of a comparison with probabilistic prediction obtained with quantile regression random forest. The result is an uncertainty quantification of the impact on the prediction. The approach is illustrated with the example of the probabilistic regionalization of soil moisture derived from cosmic-ray neutron sensing measurements, providing a regional-scale soil moisture map with data uncertainty quantification covering the Selke river catchment, eastern Germany.
The impact of digital transformation on low-carbon development of manufacturing
Authors: Lyu Yanfang , Zhang Leifeng , Wang Dong
Published: January 2023

Objective: To measure the low-carbon development level and digital transformation degree of China’s manufacturing industry, and to examine the impact of digital transformation on low-carbon development.

Methods: This paper uses Super Slack Based Measure (SBM) model and multi-regional input-output model to measure the low-carbon development level and digital transformation degree of 17 manufacturing industries in 30 provinces of China from 2012 to 2018, and uses high-dimensional fixed effect model and mediation model to study the impact of digital transformation on low-carbon development.

Results: 1) During the study period, China’s manufacturing industry showed an upward trend in terms of low-carbon development level and digital transformation, but there were significant regional and industrial disparities. 2) Digital transformation can significantly promote the low-carbon development of manufacturing industry, which is still valid in the robustness test. 3) For sub-indicators, digital industrialization has the most obvious effect on the low-carbon development of manufacturing industry, and the improvement of digital development environment also has a positive impact on low-carbon development. 4) The heterogeneity analysis indicate that digital transformation has a greater impact on promoting low-carbon development of manufacturing in underdeveloped regions, and the positive effect is obvious in medium-low-energy-consuming industries, but not in high-energy-consuming industries. 5) The mechanism test shows that technological innovation is a channel for digital transformation to promote low-carbon development.

Value: This paper provides empirical evidence for the environmental impact of digital transformation, and offers a scientific basis for relevant departments to formulate low-carbon development policies from the perspective of digital transformation.
Research on the promotion of digital teaching and learning toward achieving China’s dual-carbon strategy
Authors: Xinfa Tang , Yifei Sun , Chenhui Zhang , Lihong Wu , Yan Luo
Published: January 2023

The dual-carbon strategy of China affects all walks of life, all of which will be affected in realizing these goals. The same is true of the education sector, and China has the world’s largest education population. The education sector has a large potential to reduce carbon emissions due to its high carbon consumption. Based on the requirements of carbon emission reduction in education, this paper studied the contribution of digital teaching and learning and the education sector toward reducing carbon emissions and discusses how to promote the mechanism construction of carbon emission reduction in the education sector. The study used a comparative analysis and questionnaire research method to analyze the impact of digital teaching and learning on energy saving and emission reduction in the education sector. Research shows that using the Internet and fully utilizing the advantages of digital teaching and learning could improve the quality of teaching, reduce carbon emissions, and help achieve the goal of dual-carbon.
Uganda chicken genetic resources: I. phenotypic and production characteristics
Authors: Yussif Illyass , Kugonza Donald Rugira , Okot Marion Wilfred , Amuge Peace Oliver , Costa Rosa , Dos Anjos Filomena
Published: January 2023

The extent of diversity in the indigenous chicken breeds of Uganda was assessed for their potential utilisation in breeding programmes. A total of 293 indigenous-chicken-keeping households in villages across 35 districts forming 12 sub-regions of the four regions were randomly sampled for 586 mature chickens of both sexes. While only 20.8% of households were headed by women, 40.6% of indigenous chicken keepers were women. The production objectives mainly focused on chickens as sources of income from sales and household food. The chickens were predominantly managed in a scavenging (94.2%) feeding system in a mainly (96.9%) mixed crop-livestock system. The average flock size was 19.80 ± 1.21 chickens with 3.83 ± 0.29 laying hens, each producing an average of 13.41 ± 0.20 eggs/clutch and 40.3 ± 0.6 eggs/annum of 5.20 ± 0.03-month egg production age. Normal-feather strains predominated (>90%), with scattered incidences of naked neck, frizzles, polydactyl, and ptilopody traits in both sexes. Dark (49.0% hen; 43.8% cock) and white (38.3% hen; 42.4% cock) skin colours were most common among the chickens compared to yellow skin. However, yellow-coloured shanks were proportionally the most observed (41% cock; 29% hen). Orange and brown iris (eye) colours were the most common in both sexes. The hens commonly had small round earlobes with varying colours, while cocks had large oval-shaped, mainly red (70%) earlobes. The single-comb type was dominant in both sexes, with wattles almost universally present. Frizzle and polydactyl allele frequencies were significantly lower (p < 0.05) than the expected Mendelian proportions, indicating a possible state of endangerment. Meanwhile, the estimated allele frequencies of ptilopody, tufted-crest, and rose comb alleles in the population were similar (p > 0.05) to the expected Mendelian frequencies. However, these strains did not show any significant (p > 0.05) influence on the body weight or the linear morphometric estimates except for being marginally higher than the normal strains. The phenotypic correlations of body weight and morphometric traits ranged from 0.457 to 0.668 and 0.292 to 0.454 in cocks and hens, respectively. These findings provide hints about the prospects for improved performance with modifications in the production environment. The wide phenotypic diversity would support management efforts for their sustainable utilisation and preservation.
Cytokine/chemokine levels in the CSF and serum of anti-NMDAR encephalitis: A systematic review and meta-analysis
Authors: Ma Yushan , Wang Jierui , Guo Shuo , Meng Zirui , Ren Yan , Xie Yi , Wang Minjin
Published: January 2023

Objectives

To summarize the cytokine/chemokine levels of anti-N-methyl-Daspartate receptor encephalitis (NMDAR-E) and explore the potential role of these molecules and immune cells in the pathogenic mechanism.

Methods

The PubMed, Cochrane Library, Embase, and Web of Science databases were searched for various articles that assessed the concentrations of cytokines/chemokines in the unstimulated cerebrospinal fluid (CSF) or serum of patients with NMDAR-E in this systematic review and meta-analysis. The standardized mean difference (SMD) and 95% confidence interval (CI) were calculated by Stata17.0.

Results

A total of 19 articles were included in the systematic review from 260 candidate papers, and cytokine/chemokine levels reported in the CSF/serum were examined in each article. This meta-analysis included 17 eligible studies comprising 579 patients with NMDAR-E, 367 patients with noninflammatory neurological disorders, and 42 healthy controls from China, Spain, South Korea, Australia, Czechia, and Sweden. The results indicated that the levels of different cytokines interleukin (IL)-6, tumor necrosis factor (TNF)-α, IL-10, IL-13, IL-1β, IL-12, and IL-17 and chemokine C-X-C motif ligand (CXCL)10 in the CSF were significantly higher in NMDAR-E patients with a large effect size. In addition, B cell activating factor (BAFF), CXCL13, and interferon (IFN)-γ levels in the CSF were higher in NMDAR-E patients with a middle effect size. In contrast, levels of IL-2 and IL-4 in the CSF and CXCL13 and BAFF in the serum did not show a significant difference between cases and controls.

Conclusions

These analyses showed that the central immune response in NMDAR-E is a process that involves multiple immune cell interactions mediated by cytokines/chemokines, and T cells play an important role in the pathogenesis of immunity.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier (CRD42022342485).
Quantitative fluorescence resonance energy transfer-based immunoassay for activated complement C1s
Authors: Ye Jun , Xu Jie , Zhang Chuanmeng , Zhu Li , Xia Sheng
Published: January 2023

Objectives

C1s activation is associated with the pathogenesis of various diseases, indicating the potential value of C1s activation detection in clinic. Here we aimed to establish fluorescence resonance energy transfer (FRET)-based immunoassay for the quantitative detection of activated C1s in serum.

Methods

FRET-based fluorogenic peptides, sensitive to the enzymatic activity of activated C1s, were prepared and labeled with the fluorophore ortho-aminobenzoic acid (Abz) and quencher 2,4-dinitrophenyl (Dnp), and then were further selected depending on its Kcat/Km value. C1s in the samples was captured and separated using anti-C1s-conjugated magnetic microbeads. Next, enzymatic activity of activated C1s in samples and standards was examined using fluorescent quenched substrate assays. Limit of detection (LOD), accuracy, precision, and specificity of FRET-based immunoassay were also investigated.

Results

This method presented a linear quantification range for the enzymatic activity of activated C1s up to 10 μmol min-1 mL-1 and LOD of 0.096 μmol·min-1·mL-1 for serum samples. The recovery of the method was in the range of 90% ~ 110%. All CV values of the intra-analysis and inter-analysis of three levels in samples were less than 10%. The cross-reaction rates with C1r enzyme, MASP1, and MASP2 were less than 0.5%. No significant interferences were found with bilirubin (0.2 mg mL-1), Chyle (2000 FTU), and haemoglobin (5 mg mL-1), but anticoagulants (EDTA, citrate and heparin) inhibited the enzymatic ability of activated C1s. Thus, this established method can be used for the determination of active C1s in human serum samples in the concentration interval of 0.096-10.000 μmol min-1 mL-1.

Conclusions

One anti-C1s-based FRET immunoassay for activated C1s detection in serum samples were established, and it will be useful to explore the role of C1s activation in the pathogenesis, diagnosis and treatment in complement-related diseases.
Treatment with Helicobacter pylori-derived VacA attenuates allergic airway disease
Authors: Reuter Sebastian , Raspe Jonas , Uebner Hendrik , Contoyannis Alexandros , Pastille Eva , Westendorf Astrid M. , Caso Georgia C. , Cover Timothy L. , Müller Anne , Taube Christian
Published: January 2023

Background

Asthma is an incurable heterogeneous disease with variations in clinical and underlying immunological phenotype. New approaches could help to support existing therapy concepts. Neonatal infection of mice with Helicobacter pylori or administration of H. pylori-derived extracts or molecules after birth have been shown to prevent the development of allergic airway disease later in life. This study evaluated the potential therapeutic efficacy of H. pylori vacuolating cytotoxin A (VacA) in allergic airway inflammation and investigated the underlying immunological mechanisms for its actions.

Methods

Murine models of allergic airway diseases, and murine and human in vitro models were used.

Results

In both an acute model and a therapeutic house dust mite model of allergic airway disease, treatment with H. pylori-derived VacA reduced several asthma hallmarks, including airway hyperresponsiveness, inflammation and goblet cell metaplasia. Flow cytometry and ELISA analyses revealed induction of tolerogenic dendritic cells (DC) and FoxP3 positive regulatory T cells (Tregs), and a shift in the composition of allergen-specific immunoglobulins. Depletion of Tregs during treatment with VacA reversed treatment-mediated suppression of allergic airway disease. Human monocyte derived DCs (moDC) that were exposed to VacA induced Tregs in co-cultured naïve autologous T cells, replicating key observations made in vivo.

Conclusion

H. pylori-derived VacA suppressed allergic airway inflammation via induction of Tregs in both allergic airway disease models. These data suggest that the immunomodulatory activity of VacA could potentially be exploited for the prevention and treatment of allergic airway disease.