bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Exploratory Study on Document the Major Income Risk Encountered by the Small and Marginal Farmers in Irrigated Agro-Ecosystem of Tamil Nadu
Authors: Poovarasan K. , Mahandrakumar K. , Selvam S. , Pushpa J. , Prabakaran K. 
Published: March 2022

The study proposes to assess the major risks encountered by the small and marginal farmers in the irrigated agro-ecosystem of Tamil Nadu with help of a risk matrix. A total of 240 respondents were selected for this study which consists of 80 small and marginal farmers each from three districts representing three irrigation systems viz., tank irrigation (Sivagangai district), cannel irrigation (Thiruvarur district) and well irrigation (Namakkal district) respectively. There are 34 risks identified in these irrigation systems, out of which 20 risks were found to be plotted between catastrophic to critical categories. In that, five risks viz., delay in the release of water in cannel/tank and water scarcity, lower than the cost of production, insufficient revenues to cover farm operational expenses, less insurance claim/coverage and late disbursement of loan from cooperative society were assessed as the catastrophic risks encountered by the small and marginal farmers in the irrigated agro-ecosystem of Tamil Nadu. This research study helps the policy-makers to utilize the above said findings and to develop the risk management strategies for the major risk faced by the small and marginal farmers in irrigated agro-ecosystem of Tamil Nadu.
Machine Learning Regression Tree Approach for Age Prediction from Eruption Status of Permanent Teeth in Sri Lankan Children
Authors: De Silva Harshani H. , Nawarathna Lakshika S. , Vithanaarachchi V. S. N. 
Published: March 2022

Prediction of age is a predominant facet in forensic and clinical fields. Forensic odontology is used to predict an age by using permanent teeth resistant to high temperatures and any mass disaster than other parts of the body. Although many studies have been carried out in other countries, this is the first study of age prediction using the eruption status of permanent teeth for Sri Lankans. Age-related memory loss, memory loss associated with dementia, and the absence of official documents to verify their age are the main reasons people have no knowledge about their age. Therefore, age prediction is used in various situations, such as identification, admission purposes, employment, criminal issues and judicial punishments. The main objective of this study is to predict the age of a child using the eruption status of permanent teeth. This cross-sectional study was conducted on 3321 individuals (1681 males and 1640 females) from 7 provinces and 20 schools in Sri Lanka. Regression tree algorithms in Machine learning were used for age prediction. Classification and regression trees (CART), gradient boosting (GB) classifier and extreme gradient boost (XGBoost) classifier were used to make predictions for the age of a child. Results were validated using cross-validation techniques, and root mean squared error (RMSE) and R-squared values were used as accuracy measures to select the best model. The best model for age prediction was the XGBoost model, which gives the highest accuracy (88%). This is the first study of age prediction using eruption status of permanent teeth for Sri Lankan children. The study results provide an XGBoost machine learning classifier as the most suitable method for age prediction with higher precision.
Prevalence of Diabetes Mellitus amongst Tuberculosis Patients Accessing Care at Model Healthcare Facility in Rivers State of Nigeria
Authors: Chiladi Isomah, , Ann Ekwe , Mbata U. Christian, , Huoma Priya , Didia Tarila Aleruchi- 
Published: March 2022

Background: Tuberculosis is a global issue including diabetes particularly the Sub Sahara regions. Mono infection of either of the two is burdensome nonetheless a huge burden is experienced in a comorbid state even death. There is paucity of data about the co-existence of these diseases in this region although, much have been documented on Tuberculosis and Diabetes singly. The study ascertained the prevalence of diabetes mellitus among tuberculosis patients in Obio /Akpor local government area of Rivers State, Nigeria.
Methods: This Cross-sectional survey used purposive sampling technique. 282 pulmonary tuberculosis samples were collected and analyzed for glucose, comprising of 158 females and 124 males. The population for this study was tuberculosis patients hence only tuberculosis patients were included while none tuberculosis patients excluded from the study. Written and Informed consent was obtained from each participant. Laboratory procedure involved the collection of fasting blood Samples collected from patients following the laboratory standard quality procedure. Statistical Package for Social Science software version 21 was used to estimate frequency and percentage including prevalence rates.
Results: Glucose estimation showed; 170 normal glucose level (93females and 77 males). With 45 known diabetics (28 females and 17 males), 29 newly diagnosed diabetes (15 were males and 14 females) and 38 prediabetics (23females and 15 males). The overall prevalence of diabetes mellitus amongst Tuberculosis was 112 (39.72%) including prediabetics subjects. About 65 (58%) were females and 47 (42%) were males. Also, the most affected ages were between 31 to 50 years (21.98%); likewise, females were mostly affected 65 (23.05%).
Conclusion: There is a growing prevalence of diabetes mellitus amongst Tuberculosis patients. Glucose estimation should form part of the routine investigations for Tuberculosis patients. Investigation should be done to ascertain the interaction between Tuberculosis and Diabetes comorbidity.
Wearable sensors detect impaired gait and coordination in LBSL during remote assessments
Authors: Smith Fine Amena , Kaufman Miriam , Goodman Jordan , Turk Bela , Bastian Amy , Lin Doris , Fatemi Ali , Keller Jennifer 
Published: March 2022

AbstractBackgroundLeukoencephalopathy with brainstem and spinal cord involvement and lactate elevation (LBSL) is a rare leukodystrophy with motor impairment due to biallelic mutations in DARS2, which encodes mitochondrial aspartyl tRNA synthetase. Progressive ataxia is the primary feature.ObjectiveThe study objective is to determine the feasibility of remotely collecting quantitative gait and balance measures in LBSL.MethodsThe study design uses wearable accelerometers and the scale for the assessment and rating of ataxia (SARA) scale to assess gait and postural sway in LBSL and control participants' homes through video conferencing.ResultsLateral step variability (LSV), which indicates stride variability, and elevation of the step at mid‐swing are increased for LBSL patients during brief walking tests. During stance with the eyes closed, LBSL participants show rapid accelerations and decelerations of body movement covering a large sway area and path. Both the LSV and sway area during stance with the feet together and eyes closed correlate strongly with the SARA.ConclusionsWearable accelerometers are valid and sensitive for detecting ataxia in LBSL patients during remote assessments. The finding of large increases in the sway area during stance with the eyes closed is intriguing since dorsal column dysfunction is universally seen in LBSL. This approach can be applied to related rare diseases that feature ataxia.
Chemical Passivation Stabilizes Zn Anode
Authors: He Pan , Huang Jiaxing 
Published: March 2022

AbstractAqueous zinc ion batteries are an attractive option for grid‐scale energy storage, which is vital to the integration of renewable energy resources with the electric energy infrastructure. The cycling stability of aqueous ZIBs is determined by the electrochemical reversibility of Zn anode, which is often deteriorated by its corrosion and dendritic Zn deposition. Here, a simple and rapid surface passivation strategy that can drastically improve the cycling stability of Zn anodes is demonstrated. For example, a dip in KMnO4 solution readily forms a continuous, conformal, and robust protective layer on the native Zn surface, leading to a more uniform plating/stripping process, increased corrosion resistance, and tolerance to manufacturing and processing defects on Zn metal electrodes. The Zn electrode cycling stabilities at 1 mA cm−2 and 1 mA h cm−2 are extended by ≈40 times. In full battery tests in the configuration of Zn||β‐MnO2, the full cell with passivated Zn anode exhibited a capacity retention of 68.7% after 300 cycles at a current density of 1.0 A g−1, while the cell with untreated Zn anode can only retain 7.4% of capacity under the same conditions.
Advances in SnO2 for Efficient and Stable n–i–p Perovskite Solar Cells
Authors: Park So Yeon , Zhu Kai 
Published: March 2022

AbstractPerovskite solar cells (PSCs) based on the regular n–i–p device architecture have reached above 25% certified efficiency with continuously reported improvements in recent years. A key common factor for these recent breakthroughs is the development of SnO2 as an effective electron transport layer in these devices. In this article, the key advances in SnO2 development are reviewed, including various deposition approaches and surface treatment strategies, to enhance the bulk and interface properties of SnO2 for highly efficient and stable n–i–p PSCs. In addition, the general materials chemistry associated with SnO2 along with the corresponding materials challenges and improvement strategies are discussed, focusing on defects, intrinsic properties, and impact on device characteristics. Finally, some SnO2 implementations related to scalable processes and flexible devices are highlighted, and perspectives on the future development of efficient and stable large‐scale perovskite solar modules are also provided.
Implanting an Electron Donor to Enlarge the d–p Hybridization of High‐Entropy (Oxy)hydroxide: A Novel Design to Boost Oxygen Evolution
Authors: Zhang Lingjie , Cai Weiwei , Bao Ningzhong , Yang Hui 
Published: March 2022

AbstractHigh‐entropy (HE) electrocatalysts are becoming a research hotspot due to their interesting “cocktail effect” and have great potential for tailored catalytic properties. However, it is still a great challenge to illustrate their inherent catalytic mechanism for the “cocktail effect”, and there is also a paucity of quantitative descriptors to characterize the specific catalytic activity and give logical design strategies for HE systems. Herein, the unexpected activation of all metal sites in HE Cu–Co–Fe–Ag–Mo (oxy)hydroxides for the oxygen evolution reaction (OER) is reported, and it is found that metal–oxygen d–p hybridization, as an effective descriptor, can indicate the intrinsic activity of each metal site. According to the quantitative hybridization, introducing an electron donor (e.g., Ag) is raised and verified to reinforce the electrocatalytic activity of the HE system. Consequently, Ag‐decorated Co–Cu–Fe–Ag–Mo (oxy)hydroxide (Ag@CoCuFeAgMoOOH) electrocatalysts are constructed by an electrochemical reconstruction method, and their OER performances are thoroughly characterized. The Ag@CoCuFeAgMoOOH is verified with a low overpotential (270 mV at 100 mA cm−2) and a small Tafel slope (35.3 mV dec−1), as well as good electrochemical stability. The favorable activity of the electron donor and underlying synergistic “cocktail effect” are demonstrated and disclosed. This work opens up a new strategy to guide the design/fabrication of advanced HE electrocatalysts.
Amyloid‐Like Protein Aggregation Toward Pesticide Reduction
Authors: Su Hao , Liu Yongchun , Gao Yingtao , Fu Chengyu , Li Chen , Qin Rongrong , Liang Lei , Yang Peng 
Published: March 2022

AbstractPesticide overuse is a major global problem and the cause of this problem is noticeable pesticide loss from undesired bouncing of sprayed pesticide droplets and rain erosion. This further becomes a primary source of soil and groundwater pollution. Herein, the authors report a method that can enhance pesticide droplet deposition and adhesion on superhydrophobic plant leave surfaces by amyloid‐like aggregation of bovine serum albumin (BSA). Through the reduction of the disulfide bond of BSA by tris(2‐carboxyethyl) phosphine hydrochloride (TCEP), the amyloid‐like phase transition of BSA is triggered that rapidly affords abundant phase‐transitioned BSA (PTB) oligomers to facilitate the invasion of the PTB droplet into the nanostructures on a leaf surface. Such easy penetration is further followed by a robust amyloid‐mediated interfacial adhesion of PTB on leaf surface. As a result, after mixing with pesticides, the PTB system exhibits a remarkable pesticide adhesion capacity that is more than 10 times higher than conventional fixation of commercial pesticides. The practical farmland experiments show that the use of PTB aggregation could reduce the use of pesticides by 70–90% while ensuring yield. This work demonstrates that current pesticide dosage in actual agriculture production may be largely reduced by utilizing eco‐friendly amyloid‐like protein aggregation.
Harnessing Friction in Intertwined Structures for High‐Capacity Reusable Energy‐Absorbing Architected Materials
Authors: Li Jinyou , Chen Zhe , Li Qunyang , Jin Lihua , Zhao Zhihua 
Published: March 2022

AbstractEnergy‐absorbing materials with both high absorption capacity and high reusability are ideal candidates for impact protection. Despite great demands, the current designs either exhibit limited energy‐absorption capacities or perform well only for one‐time usage. Here a new kind of energy‐absorbing architected materials is created with both high absorption capacity and superior reusability, reaching 10 kJ kg−1 per cycle for more than 200 cycles, that is, unprecedentedly 2000 kJ kg−1 per lifetime. The extraordinary performance is achieved by exploiting the rate‐dependent frictional dissipation between prestressed stiff cores and a porous soft elastomer, which is reinforced by an intertwined stiff porous frame. The vast interfaces between the cores and elastomer enable high energy dissipation, while the magnitude of the friction force can adapt passively with the loading rate. The intertwined structure prevents stress concentration and ensures no damage and reusability of the constituents after hundreds of loading cycles. The behaviors of the architected materials, such as self‐recoverability, force magnitude, and working stroke, are further tailored by tuning their structure and geometry. This design strategy opens an avenue for developing high‐performance reusable energy‐absorbing materials that enable novel designs of machines or structures.
Degenerated Hole Doping and Ultra‐Low Lattice Thermal Conductivity in Polycrystalline SnSe by Nonequilibrium Isovalent Te Substitution
Authors: He Xinyi , Zhang Haoyun , Nose Takumi , Katase Takayoshi , Tadano Terumasa , Ide Keisuke , Ueda Shigenori , Hiramatsu Hidenori , Hosono Hideo , Kamiya Toshio 
Published: March 2022

AbstractTin mono‐selenide (SnSe) exhibits the world record of thermoelectric conversion efficiency ZT in the single crystal form, but the performance of polycrystalline SnSe is restricted by low electronic conductivity (σ) and high thermal conductivity (κ), compared to those of the single crystal. Here an effective strategy to achieve high σ and low κ simultaneously is reported on p‐type polycrystalline SnSe with isovalent Te ion substitution. The nonequilibrium Sn(Se1−xTex) solid solution bulks with x up to 0.4 are synthesized by the two‐step process composed of high‐temperature solid‐state reaction and rapid thermal quenching. The Te ion substitution in SnSe realizes high σ due to the 103‐times increase in hole carrier concentration and effectively reduced lattice κ less than one‐third at room temperature. The large‐size Te ion in Sn(Se1−xTex) forms weak SnTe bonds, leading to the high‐density formation of hole‐donating Sn vacancies and the reduced phonon frequency and enhanced phonon scattering. This result—doping of large‐size ions beyond the equilibrium limit—proposes a new idea for carrier doping and controlling thermal properties to enhance the ZT of polycrystalline SnSe.
Impact of preoperative skeletal muscle mass and physical performance on short‐term and long‐term postoperative outcomes in patients with esophageal cancer after esophagectomy
Authors: Sugimura Keijiro , Miyata Hiroshi , Kanemura Takashi , Takeoka Tomohira , Shinnno Naoki , Yamamoto Kazuyoshi , Omori Takeshi , Motoori Masaaki , Ohue Masayuki , Yano Masahiko 
Published: March 2022

AbstractBackgroundIn patients with esophageal cancer who undergo esophagectomy, preoperative skeletal muscle mass loss has been reported to be associated with postoperative complications and poor prognosis. However, physical performance has not been fully investigated.MethodsThis study included 363 patients who underwent esophagectomy for thoracic esophageal cancer in 2013‐2018. Preoperative skeletal muscle index (SMI) was measured with multifrequency bioelectrical impedance. Preoperative 6‐minute walk distance (6MWD) was measured as an indicator of physical performance. We investigated the association between these factors and postoperative complications or long‐term prognosis.ResultsPreoperative SMI was not associated with the occurrence of postoperative complications (33% vs 35%, P = .820), but low preoperative 6MWD was significantly associated with the occurrence of postoperative complications rather than high 6MWD (60% vs 30%, P < .001), especially pulmonary complications (23% vs 8%, P = .001). In the analysis of long‐term prognosis, low preoperative SMI was associated with poor survival (Hazard ratio [HR] 1.77, P = .004). Low preoperative 6MWD was also associated with poor survival (HR 2.55, P < .001). Multivariate prognostic analysis showed that pT stage (HR 1.97, P = .001), pN stage (HR 3.27, P < .001), and 6MWD (HR 1.93, P = .008) were independent prognostic factors. In the low 6MWD group, the rate of death from other diseases was significantly higher than the other groups.ConclusionsIt is useful to evaluate 6MWD as a physical performance in addition to SMI when evaluating sarcopenia from the perspective of predicting postoperative complications and long‐term prognosis in patients with esophageal cancer undergoing esophagectomy.
Numerical study on settlement behaviors of slush hydrogen in cryogenic tank
Authors: Xia Siqi , Xie Fushou , Sun Qiang , Li Yanzhong 
Published: March 2022

AbstractSlush hydrogen can be used as a promising propulsion fuel for deep space exploration vehicles because of its more excellent thermodynamic properties compared with liquid hydrogen. To study stratification and settlement characteristics of slush hydrogen in cryogenic tanks, a transient model based on Eulerian–Eulerian two‐fluid method was developed and was verified by experiment data. Many numerical simulations were conducted to determine the influence of settlement, including particle diameter (dp = 0.5–0.015 mm), initial volume fraction of solid hydrogen (αs = 30%–50%), and heat leakage of cryogenic tank (qleak = 15–45 W m−2). It was found that there is a critical particle diameter for settlement of slush hydrogen, which is about 0.02 mm. Meanwhile, a large range of natural convection circulation has been observed in the entire tank. Numerical results of this paper could improve uniform distribution of slush hydrogen for highly efficient storage and application.
Synthesis of zeolite A with high whiteness from coal gangue by two‐step pretreatment method
Authors: Liu Shanfang , Yan Shuo , Li Yun , Cao Jilin 
Published: March 2022

AbstractThe comprehensive utilization of coal gangue (CG) is restricted by color elements in CG including C and FexOy. The magnetic separation and hydrothermal acid leaching are combined to pretreat the solid waste CG to synthesize zeolite A with high whiteness. Firstly, Fe2O3 component in CG is in situ reduced by C to magnetite in the process of high‐temperature calcination for decarburization followed by physical magnetic separation. Secondly, the residual Fe impurity in CG is further removed by hydrothermal acid leaching. The effects of calcination temperature, calcination time, acid leaching temperature, acid concentration, and liquid to solid ratio on Fe removal rate (RFe2O3) and the whiteness of the synthesized zeolite A are investigated. The influence of Fe impurities on the Ca2+ ion exchange capacity (E) of the zeolite A synthesized from CG is clarified. RFe2O3 could reach the value of 88.53%. The synthesized zeolite A exhibits a typical cubic morphology with rounded edges, the high whiteness of 95.46%, and the satisfactory E with the value of 296.02 mgCaCO3·g−1, both of which meet the requirements of national standard. This work suggests that this pretreatment method for CG would have broad prospects in the efficient resource utilization of CG.
Data‐mining‐based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID‐19
Authors: Han Yaxue , Yang Zi , Fang Shan , Zhang Mengqing , Xie Zhijun , Fan Yongsheng , Zhao Ting 
Published: March 2022

AbstractTraditional Chinese Medicine (TCM) plays a role in preventing and treating COVID‐19 in China. Based on the manifestations and symptoms of COVID‐19, our study used the data mining method to summarize related therapeutic experience left by predecessors who used TCM to treat epidemics in their eras. Initially, we collected abundant medical records with similar manifestations of COVID‐19 in Chinese ancient times. The key words including wen (瘟), yi (疫), li (疠), and zhang (瘴) were searched in ZhongyiZhiku (https://www.zk120.com/) from Warring States Period (475 BC–221 BC) to the Republic of China era (1912–1949) to locate ancient medical records according to inclusion criteria and exclusion criteria. Moreover, COVID‐19‐related manifestations and corresponding medications in those records were categorized. Eventually, Traditional Chinese Medicine Inheritance Support System version 2.5 was used to build a medical record database of TCM treating COVID‐19. Our study collected 263 epidemic medical records comprising COVID‐19 related manifestations and found that Chinese Materia Medica (CMM) combinations excavated from ancient medical records included Ren Shen Bai Du San, Wu Ling San, Xiao Chai Hu Tang, Da Cheng Qi Tang, Da Chai Hu Tang, Ling Gui Zhu Gan Tang, and Qing Wen Bai Du Yin. The recurrent CMMs with a high frequency for treating COVID‐19 manifestations were Scutellariae Radix (Huang Qin), Paeoniae Alba Radix (Bai Shao), Poria (Fu Ling), and Bupleuri Radix (Chai Hu). Our study suggests that TCM might offer new therapeutic strategies for COVID‐19.
SEntFiN 1.0: Entity‐aware sentiment analysis for financial news
Authors: Sinha Ankur , Kedas Satishwar , Kumar Rishu , Malo Pekka 
Published: March 2022

AbstractFine‐grained financial sentiment analysis on news headlines is a challenging task requiring human‐annotated datasets to achieve high performance. Limited studies have tried to address the sentiment extraction task in a setting where multiple entities are present in a news headline. In an effort to further research in this area, we make publicly available SEntFiN 1.0, a human‐annotated dataset of 10,753 news headlines with entity‐sentiment annotations, of which 2,847 headlines contain multiple entities, often with conflicting sentiments. We augment our dataset with a database of over 1,000 financial entities and their various representations in news media amounting to over 5,000 phrases. We propose a framework that enables the extraction of entity‐relevant sentiments using a feature‐based approach rather than an expression‐based approach. For sentiment extraction, we utilize 12 different learning schemes utilizing lexicon‐based and pretrained sentence representations and five classification approaches. Our experiments indicate that lexicon‐based N‐gram ensembles are above par with pretrained word embedding schemes such as GloVe. Overall, RoBERTa and finBERT (domain‐specific BERT) achieve the highest average accuracy of 94.29% and F1‐score of 93.27%. Further, using over 210,000 entity‐sentiment predictions, we validate the economic effect of sentiments on aggregate market movements over a long duration.