bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of forest fires on the permafrost environment in the northern Da Xing'anling (Hinggan) mountains, Northeast China
Authors: Li Xiaoying , Jin Huijun , He Ruixia , Huang Yadong , Wang Hongwei , Luo Dongliang , Jin Xiaoying , Lü Lanzhi , Wang Lizhong , Li Wei'hai , Wei Changlei , Chang Xiaoli , Yang Sizhong , Yu Shaopeng 
Published: August 2019

AbstractForest fires have significantly impacted the permafrost environment, and many research programs looking at this have been undertaken at higher latitudes. However, their impacts have not yet been systematically studied and evaluated in the northern part of northeast China at mid‐latitudes. This study simultaneously measured ecological and geocryological changes at various sites in the boreal forest at different stages after forest fires (chronosequence approach) in the northern Da Xing'anling (Hinggan) Mountains, Northeast China. We obtained results through field investigations, monitoring and observations, remote sensing interpretations, and laboratory tests. The results show that forest fires have resulted in a decreased Normalized Difference Vegetation Index (NDVI) and soil moisture contents in the active layer, increased active layer thickness (ALT) and ground temperatures, and the release of a large amount of C and N from the soils in the active layer and at shallow depths of permafrost. NDVI and species biodiversity have gradually increased in the years since forest fires. However, the vegetation has not fully recovered to the climax community structures and functions of the boreal forest ecosystems. For example, ground temperatures, ALT, and soil C and N contents have been slowly recovering in the 30 years after the forest fires, but they have not yet been restored to pre‐fire levels. This study provides important scientific bases for assessment of the impacts of forest fires on the boreal forest ecosystems in permafrost regions, environmental restoration and management, and changes in the carbon stock of soils at shallow (<3 m) depths in the Da Xingan'ling Mountains in northeast China.
Ground temperature and deformation analysis for an expressway embankment in warm permafrost regions of the Tibet plateau
Authors: Liu Jiankun , Tai Bowen , Fang Jianhong 
Published: August 2019

AbstractThe physical and mechanical processes relating to infrastructure are strongly intertwined in subgrades of road or railway in warm permafrost regions, where the evolution of these processes may influence the functionality of infrastructure. Thus, this study analyzed the embankment thermal regime and thaw settlement behavior based on monitored data for three sections of the newly constructed Gonghe–Yushu expressway (GYE) in a warm permafrost area of Tibet. The efficiencies of crushed rock, ventilated, and insulated embankments in maintaining permafrost temperature were evaluated in relation to the permafrost table (PT) and the annual warming rate of the permafrost. The deformation characteristics of three embankments for different soil layers are summarized, along with analysis of heat balance. The results show that: (a) the permafrost thaw rate has a positive linear correlation with mean annual ground temperature; (b) the permafrost displays a warming trend regardless of whether PT increases or decreases; (c) the total deformation of a given embankment shows a tendency toward settlement; and (d) subgrade peak thaw settlement occurs later than its maximum seasonal thaw depth.
Boosting phosphorylation site prediction with sequence feature‐based machine learning
Authors: Maiti Shyantani , Hassan Atif , Mitra Pralay 
Published: August 2019

AbstractProtein phosphorylation is one of the essential posttranslation modifications playing a vital role in the regulation of many fundamental cellular processes. We propose a LightGBM‐based computational approach that uses evolutionary, geometric, sequence environment, and amino acid‐specific features to decipher phosphate binding sites from a protein sequence. Our method, while compared with other existing methods on 2429 protein sequences taken from standard Phospho.ELM (P.ELM) benchmark data set featuring 11 organisms reports a higher F1 score = 0.504 (harmonic mean of the precision and recall) and ROC AUC = 0.836 (area under the curve of the receiver operating characteristics). The computation time of our proposed approach is much less than that of the recently developed deep learning‐based framework. Structural analysis on selected protein sequences informs that our prediction is the superset of the phosphorylation sites, as mentioned in P.ELM data set. The foundation of our scheme is manual feature engineering and a decision tree‐based classification. Hence, it is intuitive, and one can interpret the final tree as a set of rules resulting in a deeper understanding of the relationships between biophysical features and phosphorylation sites. Our innovative problem transformation method permits more control over precision and recall as is demonstrated by the fact that if we incorporate output probability of the existing deep learning framework as an additional feature, then our prediction improves (F1 score = 0.546; ROC AUC = 0.849). The implementation of our method can be accessed at http://cse.iitkgp.ac.in/~pralay/resources/PPSBoost/ and is mirrored at https://cosmos.iitkgp.ac.in/PPSBoost.
Surface temperature distribution on a spherical ice particle growing by accretion in wet growth regime
Authors: Luque Melina Y. , Bürgesser Rodrigo E. , Castellano Nesvit E. 
Published: August 2019

AbstractExperimental evidence has demonstrated that temperature on the surface of an ice particle growing by accretion is not uniform. This non‐uniformity is relevant because the ice particle surface temperature is an important microphysical parameter that influences the sign and magnitude of the charge transfer during ice particles collisions. In particular, when high values of ambient temperature and liquid water content are reached, the ice particle surface temperature is expected to reach 0 °C, which is known as wet growth regime. Previous experimental results have shown that wet growth is not uniformly reached on the ice particle surface and a surface temperature distribution is developed. In order to know the surface temperature distribution of a fixed ice particle growing by accretion of supercooled water, numerical calculations were carried out. It was found that the surface temperature distribution has a strong dependence on liquid water content, ambient temperature, airflow velocity and water droplet size. The stagnation point always reaches higher temperatures and, in many cases, its temperature is near 0 °C. For some values of the liquid water content, ambient temperature and airflow velocity, it was possible to determine temperature differences up to 7 °C between the stagnation point and the equator. This variation in the surface temperature implies that the region near the stagnation point would experience wet growth, while the rest of the ice particle surface would remain in dry growth regime, supporting the partial wet growth hypothesis. This could also explain the charge transfer reported during ice particles collisions under wet growth conditions.
Identification of novel biomarkers of hepatocellular carcinoma by high‐definition mass spectrometry: Ultrahigh‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry and desorption electrospray ionization mass spectrometry imaging
Authors: Nagai Koshi , Uranbileg Baasanjav , Chen Zhen , Fujioka Amane , Yamazaki Takahiro , Matsumoto Yotaro , Tsukamoto Hiroki , Ikeda Hitoshi , Yatomi Yutaka , Chiba Hitoshi , Hui Shu‐Ping , Nakazawa Toru , Saito Ritsumi , Koshiba Seizo , Aoki Junken , Saigusa Daisuke , Tomioka Yoshihisa 
Published: August 2019

RationaleHepatocellular carcinoma (HCC) is a highly malignant disease for which the development of prospective or prognostic biomarkers is urgently required. Although metabolomics is widely used for biomarker discovery, there are some bottlenecks regarding the comprehensiveness of detected features, reproducibility of methods, and identification of metabolites. In addition, information on localization of metabolites in tumor tissue is needed for functional analysis. Here, we developed a wide‐polarity global metabolomics (G‐Met) method, identified HCC biomarkers in human liver samples by high‐definition mass spectrometry (HDMS), and demonstrated localization in cryosections using desorption electrospray ionization MS imaging (DESI‐MSI) analysis.MethodsMetabolic profiling of tumor (n = 38) and nontumor (n = 72) regions in human livers of HCC was performed by an ultrahigh‐performance liquid chromatography quadrupole time‐of‐flight MS (UHPLC/QTOFMS) instrument equipped with a mixed‐mode column. The HCC biomarker candidates were extracted by multivariate analyses and identified by matching values of the collision cross section and their fragment ions on the mass spectra obtained by HDMS. Cryosections of HCC livers, which included both tumor and nontumor regions, were analyzed by DESI‐MSI.ResultsFrom the multivariate analysis, m/z 904.83 and m/z 874.79 were significantly high and low, respectively, in tumor samples and were identified as triglyceride (TG) 16:0/18:1(9Z)/20:1(11Z) and TG 16:0/18:1(9Z)/18:2(9Z,12Z) using the synthetic compounds. The TGs were clearly localized in the tumor or nontumor areas of the cryosection.ConclusionsNovel biomarkers for HCC were identified by a comprehensive and reproducible G‐Met method with HDMS using a mixed‐mode column. The combination analysis of UHPLC/QTOFMS and DESI‐MSI revealed that the different molecular species of TGs were associated with tumor distribution and were useful for characterizing the progression of tumor cells and discovering prospective biomarkers.
Differential processing of high‐molecular‐weight kininogen during normal pregnancy
Authors: Droll Stephenie H. , Hsu Yen‐Michael Sheng , Drake Steven K. , Kim Ashley , Wang Weixin , Calvo Katherine R. , Cao Zheng , Hu Tony Y. , Zhao Zhen 
Published: August 2019

RationaleStudies identified kininogen as a potential biomarker of preeclampsia, a major cause of adverse maternal outcomes. High‐molecular‐weight kininogen (HK) and its activated form participate in numerous pathways associated with establishing and maintaining pregnancy. However, dynamic changes in HK and naturally occurring HK‐derived peptides during the natural course of pregnancy are largely unknown.MethodsLongitudinal serum samples during the course of normal pregnancy (trimesters T1, T2, T3) from 60 pregnant women were analyzed by western blot with an anti‐HK antibody. Circulating peptides in longitudinal serum specimens derived from 50 participants were enriched using nanoporous silica thin films. Peptides were identified by liquid chromatography/tandem mass spectrometry (LC/MS/MS) and database searching. Relative quantification was performed using MaxQuant and in‐house scripts. Normality was evaluated by either ANOVA or Friedman tests with p < 0.05 for statistical significance.ResultsWestern blotting revealed that HK significantly decreased during normal pregnancy (T1 vs T2, p < 0.05; T1 vs T3, p < 0.0001). A 100 kDa intermediate increased during pregnancy (T1 vs T2, p < 0.005; T1 vs T3, p < 0.01). Moreover, the heavy chain (T1 vs T2, p < 0.0001; T1 vs T3, p < 0.0001; T2 vs T3, p < 0.01) and light chain (T1 vs T2, p < 0.0001; T1 vs T3, p < 0.0001; T2 vs T3, p < 0.05) significantly increased during pregnancy. LC/MS/MS analysis identified 180 kininogen‐1 peptides, of which 167 mapped to domain 5 (D5). Seventy‐three peptides with ten or more complete data sets were included for further analysis. Seventy peptides mapped to D5, and 3, 24, and 43 peptides showed significant decrease, no trend, and significant increase, respectively, during pregnancy.ConclusionsThis study demonstrates dynamic changes in HK and naturally occurring HK‐derived peptides during pregnancy. Our study sheds light on the gestational changes of HK and its peptides for further validation of them as potential biomarkers for pregnancy‐related complications.
The nanoeconomics of firm‐level decision‐making and industry evolution: Evidence from 200 years of paper and pulp making
Authors: Lamberg Juha‐Antti , Peltoniemi Mirva 
Published: August 2019

AbstractResearch SummaryWe explore the qualitative differences in entries and exits over time. Using qualitative and quantitative data on 96 firms over 200 years, we study industry evolution from the perspective of individual decision‐making situations. Our historical and statistical analyses reveal the vital role of technology investments in determining firm outcomes, and the technological, institutional and governance dynamics that lead firms to invest or to abstain. Our main theoretical and methodological contribution concerns the importance of the multiplicity of firm‐level rationalities and decisions as fundamentals in theorizing on industry evolution.Managerial SummaryWhat determines firm outcomes in terms of acquisition, dissolution, and survival? This article answers this crucial question of strategy and elaborates on the extent to which the outcome is under top management control. Our findings highlight the importance of technology investments and we identify factors that make such investments possible and profitable. Our results emphasize that firms weighing options must assess the economic meaningfulness of generational technology investments which result in narrowing profit margins and intensifying competition. Another insight concerns the management of political risks. Long‐term fluctuations in regulation and foreign trade policy make it hazardous to optimize to the contemporary political regime. Skillful strategists invest in geographical and technological complexity, which in combination increase the chances of survival in rapidly changing political regimes.
Location and survival of MNEs' subsidiaries: Agglomeration and heterogeneity of firms
Authors: Mariotti Sergio , Mosconi Rocco , Piscitello Lucia 
Published: August 2019

AbstractResearch summaryOur study provides a quasi–replication of Shaver and Flyer (2000), which was among the first studies that challenged the positive role of agglomeration in determining companies' location choice and performances, thus changing the way management scholars view companies' attitude towards agglomeration forces. We employ the same research design, specification and tests, and a different population, to discuss the generalizability of the original study. Building on the framework of Shaver and Flyer (2000), our findings offer intriguing new empirical evidence highlighting the importance of the differential between entering foreign firms and host country firms as a crucial condition in understanding agglomeration forces and adverse selection mechanisms.Managerial summaryOur exercise confirms that agglomeration forces act differently on stronger versus weaker multinational enterprises (MNEs). However, we find that stronger MNEs tend to avoid location in highly specialized areas when they are afraid of knowledge leakages towards host country–based rivals that have enough absorptive capacity to benefit and improve their competitive advantages. Managerial implications are quite relevant. Indeed, when MNEs avoid co–location in highly specialized areas, they also limit their own access to local knowledge and other agglomeration economies, such as supply networks and qualified workforce. Thus, MNEs managers need to design and implement devices that, on the one hand prevent local leakages of their knowledge and, on the other, do not hinder their access to local unique knowledge and resources.
Socially advantaged? How social affiliations influence access to valuable service professional transactions
Authors: Gubler Timothy , Cooper Ryan 
Published: August 2019

AbstractResearch summaryThis article theorizes that social capital produced by social affiliations allows service professionals to gain access to higher‐value transactions through increased reputation for trustworthiness, which then aids them in further building reputation and engaging in entrepreneurship. Using a unique approach that pairs Utah residential real estate data with church congregation boundaries, we find that affiliations enable real estate agents to list 14% more expensive homes, and to consequently build reputation useful for future nonaffiliated transactions. We observe large reputation‐building benefits for early‐career agents, particularly for agents in low‐reputation firms. Strikingly, we find this lowers entrepreneurship entry by 6%. These results imply that social affiliations can substitute for reputation in selection, enabling professionals to build reputation, which then has important career implications.Managerial summaryThis article explores how social relationships between real estate agents and home sellers influence the value of transactions agents engage in. Sellers increasingly trust agents with whom they share a social affiliation, which allows agents to better secure high‐value listings and build reputation. This benefits agent in securing future valuable transactions with nonaffiliated clients. Using residential real estate data and geographically assigned church congregations, we find that agents list 14% more expensive homes when listing for affiliated clients, and that this builds agent reputation significantly faster than listing for nonaffiliated clients. Interestingly, we find listing for affiliated clients reduces future entrepreneurship 6%. Our study suggests that service professionals can leverage social affiliations to build reputation that helps them establish clientele and improve performance.
Seeds of change: How current structure shapes the type and timing of reorganizations
Authors: Raveendran Marlo 
Published: August 2019

AbstractResearch SummaryThis article develops theory on how an organization's structure affects future reorganizations. I highlight that a firm's structure shapes not only the locus of decision‐making power (i.e., centralization and decentralization) but also the employees' interaction structure. I develop microlevel theory that connects the firm's structure to the interactions among its employees—for instance, its influence on the time employees spend adjusting their behavior after a reorganization. This theory predicts that some structures are more likely than others to promote a reorganization to occur sooner. I use a unique, hand‐collected data set of reorganizations in the cell‐phone manufacturing industry to test and find directional support for this theory.Managerial SummaryI examine the effect of a firm's current structure on its corporate reorganization decisions, which are defined as the addition and/or removal of business units. I posit that the way employees are grouped into those business units may affect both the type and timing of subsequent reorganizations; the reason is that employees of similar (resp. different) backgrounds should need less (resp. more) time to achieve effective collaboration. Using data on the reorganizations of cell‐phone manufacturing firms during 1983–2008, I find directional support for the theory. This result implies that managers may need to watch closely any reorganization that shifts the firm toward more heterogeneous interaction structures—because its implementation may well require additional time.
2D Crystal–Based Fibers: Status and Challenges
Authors: Meng Si , Kong Tiantian , Ma Wujun , Wang Huide , Zhang Han 
Published: August 2019

Abstract2D crystals are emerging new materials in multidisciplinary fields including condensed state physics, electronics, energy, environmental engineering, and biomedicine. To employ 2D crystals for practical applications, these nanoscale crystals need to be processed into macroscale materials, such as suspensions, fibers, films, and 3D macrostructures. Among these macromaterials, fibers are flexible, knittable, and easy to use, which can fully reflect the advantages of the structure and properties of 2D crystals. Therefore, the fabrication and application of 2D crystal–based fibers is of great importance for expanding the impact of 2D crystals. In this Review, 2D crystals that are successfully prepared are overviewed based on their composition of elements. Subsequently, methods for preparing 2D crystals, 2D crystals dispersions, and 2D crystal–based fibers are systematically introduced. Then, the applications of 2D crystal–based fibers, such as flexible electronic devices, high‐efficiency catalysis, and adsorption, are also discussed. Finally, the status‐of‐quo, perspectives, and future challenges of 2D crystal–based fibers are summarized. This Review provides directions and guidelines for developing new 2D crystal–based fibers and exploring their potentials in the fields of smart wearable devices.
Physical exercise improves quality of life, depressive symptoms, and cognition across chronic brain disorders: a transdiagnostic systematic review and meta-analysis of randomized controlled trials
Authors: Dauwan Meenakshi , Begemann Marieke J. H. , Slot Margot I. E. , Lee Edwin H. M. , Scheltens Philip , Sommer Iris E. C. 
Published: August 2019

AbstractWe performed a meta-analysis to synthesize evidence on the efficacy and safety of physical exercise as an add-on therapeutic intervention for quality of life (QoL), depressive symptoms and cognition across six chronic brain disorders: Alzheimer’s disease, Huntington’s disease, multiple sclerosis, Parkinson’s disease, schizophrenia and unipolar depression. 122 studies ( = k) (n = 7231) were included. Exercise was superior to treatment as usual in improving QoL (k = 64,n = 4334, ES = 0.40,p < 0.0001), depressive symptoms (k = 60,n = 2909, ES = 0.78,p < 0.0001), the cognitive domains attention and working memory (k = 21,n = 1313, ES = 0.24,p < 0.009), executive functioning (k = 14,n = 977, ES = 0.15,p = 0.013), memory (k = 12,n = 994, ES = 0.12,p = 0.038) and psychomotor speed (k = 16,n = 896, ES = 0.23,p = 0.003). Meta-regression showed a dose–response effect for exercise time (min/week) on depressive symptoms (β = 0.007,p = 0.012). 69% of the studies that reported on safety, found no complications. Exercise is an efficacious and safe add-on therapeutic intervention showing a medium-sized effect on QoL and a large effect on mood in patients with chronic brain disorders, with a positive dose–response correlation. Exercise also improved several cognitive domains with small but significant effects.
Why employees matter in the fight against ransomware
Authors: Chung Marcus 
Published: August 2019

Ransomware attacks keep coming and the stakes get higher every day. Each employee in a company, from the newest hire to the CEO, can either strengthen or weaken an organisation's security posture. For this reason, companies should help employees take precautions against the latest ransomware scams. Ransomware attacks keep coming and each employee, from the newest hire to the CEO, can either strengthen or weaken an organisation's security posture. Many malicious attacks can be stopped by endpoint security products and advanced threat protection solutions, but creative scammers keep finding ways to get past these defences. If a company's security programme does not empower employees to defend themselves, they will be more likely to engage in actions that threaten the security of the network, says Marcus Chung of BoldCloud.