bluuebunny/crossref_metadata_2025 huggingface dataset:
Macro X-ray fluorescence analysis of XVI-XVII century Italian paintings and preliminary test for developing a combined fluorescence apparatus with digital radiography
Authors: Sottili Leandro , Guidorzi Laura , Lo Giudice Alessandro , Mazzinghi Anna , Ruberto Chiara , Castelli Lisa , Czelusniak Caroline , Giuntini Lorenzo , Massi Mirko , Taccetti Francesco , Nervo Marco , Torres Rodrigo , Arneodo Francesco , Re Alessandro
Published: March 2022

Using portable instruments for the preservation of artworks in heritage science is more and more common. Among the techniques, Macro X-Ray Fluorescence (MA-XRF) and digital radiography (DR) play a key-role in the field, therefore a number of MA-XRF scanners and radiographic apparatuses have been developed for this scope. Recently, the INFN-CHNet group, the network of the INFN devoted to cultural heritage, has developed a MA-XRF scanner for in-situ analyses. The instrument is fully operative, and it has already been employed in museums, conservation centres and out-door fields. In the present paper, the MA-XRF analysis conducted with the instrument on four Italian artworks undertaking conservation treatments at the conservation centre CCR “La Venaria Reale” are presented. Results on the preliminary test to combine DR with MA-XRF in a single apparatus are also shown.
Analysis of multiband rectangular patch antenna with defected ground structure using reflection coefficient measurement
Authors: Suneetha Thalluru , Bhavanam S. Naga Kishore
Published: March 2022

In this paper, a novel quad band antenna to operate at four different frequency bands is designed and simulated using Computer Simulation Technology (CST) Microwave Studio software. To achieve better performance of the antenna, various parameters were optimized using parametric analysis. During this analysis, various antenna parameters were need to be measured. The proposed antenna uses asymmetrical ‘U’ and ‘T’ shaped radiating elements printed on an FR-4 substrate with dimensions of 1.6 × 34 × 20 mm3. The measurement of various antenna parameters like reflection coefficient, return loss, radiation intensity are key tasks to be performed in the antenna measurement laboratory before going to the real time application. A stair case defected ground structure with rectangular center slot is used to attain a better bandwidth. The antenna resonates at four different frequencies 3 GHz, 4.8 GHz, 9 GHz, 13.2 GHz with operating bandwidths of 980 MHz, 2.05 GHz, 3.84 GHz, and 3.82 GHz respectively. The S11 value at these resonant frequencies is measured as -23.6 dB, -29.4 dB, -34.2 dB, -49.05 dB respectively. The voltage standing wave ratio of the proposed antenna at four resonant frequencies is equal to one. The gain of the antenna is consistent throughout the four pass bands. The antenna is suitable for Bluetooth (2.4) GHz, WLAN (5.125-5.35) GHz and (5.725-5.825) GHz, WiMAX (5.25-5.85) GHz, C-band (3.7-4.2) GHz and Ku-band (12-18) GHz.
Multi-input multi-output antenna measurements with super wide bandwidth for wireless applications using isolated T stub and defected ground structure
Authors: Kodavanti Pradeep Vinaik , Jayasree P .V. Y. , Bhima Prabhakara Rao
Published: March 2022

The paper presents the idea of defective ground structures for the improvement in the radiation characteristics of the antenna especially in the multi-input multi-output (MIMO) configuration. The proposed antenna model with partially flared out feed system is designed and analyzed with defective ground in both single and array configuration. A T stub is a T shaped stub used in this work with defected ground structure. A T stub is included along with defective ground to enhance the MIMO configuration features. The simulations are carried out on electromagnetic modelling tool and analyzed by measuring the parameters like reflection coefficient, voltage standing wave ratio (VSWR), gain, radiation pattern and current distribution plots. For the fabrication of the proposed antenna these measurements are very important. The antenna is fabricated and validated in terms of S-parameters and VSWR. The proposed results are good agreement with the simulated results. The overall size of the antenna is 24 × 18 x 0.8 mm3.
Efficient deep learning based data augmentation techniques for enhanced learning on inadequate medical imaging data
Authors: Sashank Madipally Sai Krishna , Maddila Vijay Souri , Boddu Vikas , Radhika Y.
Published: March 2022

The world has come to a standstill with the Coronavirus taking over. In these dire times, there are fewer doctors and more patients and hence, treatment is becoming more and more difficult and expensive. In recent times, Computer Science, Machine Intelligence, measurement technology has made a lot of progress in the field of Medical Science hence aiding the automation of a lot of medical activities. One area of progress in this regard is the automation of the process of detection of respiratory diseases (such as COVID-19). There have been many Convolutional Neural Network (CNN) architectures and approaches that have been proposed for Chest X-Ray Classification. But a big problem still remains and that is the minimal availability of Medical X-Ray Images due to improper measurements. Due to this minimal availability of Chest X-Ray data, most CNN classifiers do not get trained to an optimal level and the required standards for automating the process are not met. In order to overcome this problem, we propose a new deep learning based approach for accurate measurements of physiological data.
Spectrum Sensing using Energy Measurement in Wireless Telemetry Networks using Logarithmic Adaptive Learning
Authors: Mantravadi Nagesh , Ur Rahman Md Zia , Surekha Sala , Guptha Navarun
Published: March 2022

To identify primary user signals in cognitive radios spectrum sensing method is used. Due to statistical variances in received signal, noise is present in primary user signals, this noise powers are varied due to random nature of noise signals and leads to noise uncertainty problem in the performance of energy detection. The task of energy measurement and further detecting the unused frequency spectrum is a key task in cognitive radio applications. For avoiding these problems, least logarithmic absolute difference (LLAD) algorithm is proposed in which noise powers are adjusted at sensing point of licensed users. With help of proposed method, estimated noise signals are eliminated. Sign regressor version of LLAD algorithm is considered due to it reduces computational complexity and convergence rate is improved. Further probability of detection (Pod), probability of false alarm (Pofa) is estimated to know threshold value. From results, it is clear that good performance in terms of Pofa versus Pod in range of low signal to noise ratio in multiple nodes. Therefore, the proposed energy measurement-based spectrum sensing method is useful in remote health care monitoring, medical telemetry applications by sharing the un-used spectrum.
The Transition to Practice from Residency and Fellowship
Authors: Sommi Corinne , Kogan Monica , Eberson Craig P. , Mulcahey Mary K.
Published: March 2022

» There is currently no standard method or time requirement devoted to the teaching of practice management in orthopaedic residency, but there is widespread agreement that it is a necessary part of orthopaedic education.

» Overall, there are 3 major components to an effective transition-to-practice model: mock independent practice, appropriate feedback and oversight, and consistent exposure.

» An overarching theme is the importance of debriefing by senior faculty, coupled with mock practice scenarios.
Technology Focus: Drilling Automation and Innovation (February 2022)
Authors: Weatherl Michael H.
Published: March 2022

What was impossible a few short years ago is reality today.” This quote, taken from the opening paragraph of featured paper IPTC 19671, is a most relevant statement for the state of drilling technology today. Adverse effects of economic down cycles, commodity fluctuation, geopolitical events, weather patterns, and the pandemic have imposed harsh realities on the energy sector along with almost every aspect of life on Earth as we know it.

As these events have continued to unfold in recent years, surprising trends with unexpected outcomes have resulted. For example, demand destruction because of commodity price collapse necessitated increased emphasis on efficiency and productivity. Business as usual was out of the question. Higher productivity, lower cost, environmental stewardship, and increased safety standards have become more critical than ever before.

As these forces persist, changes in our industry have accelerated at a dramatic rate in an array of key technologies. Some of these initiatives have been under way for years and are familiar themes to SPE readers: artificial intelligence, automated decision making, data analytics, and visualization, to name a few.

Papers selected for this feature were chosen to highlight some of these areas of advancement, with particular emphasis on breakthrough technologies where step changes have been delivered or are seen as imminent. For instance, much has been written about the profound impact of managed-pressure-drilling (MPD) systems with ongoing breakthroughs in areas such as advanced modeling, automation, and analytics. Likewise, automated directional drilling has been established as a pre-eminent technology destined to continue to revolutionize the way in which wells are constructed. While many of the published manuscripts highlight onshore applications, offshore, deep water, and high-pressure/high-temperature operations are being transformed as well.

Finally, don’t miss paper IADC/SPE 199573, “World’s First Hybrid Drilling Rig,” a recommended reading paper. Several key opportunities for improvements specific to drilling rig machinery and power are addressed in this manuscript, including reduced fuel consumption, emissions, and well costs, and increased overall generator efficiency. Although hybrid drilling rigs are still in the early stages with regard to practical application within the global fleet of active rigs, it is difficult not to recognize as legitimate the basic ideas and potential breakthroughs being detailed.

Recommended additional reading at OnePetro: www.onepetro.org.

SPE/IADC 199573 - World’s First Hybrid Drilling Rig by Memet Bilgin, CleanDesign Power Systems, et al.

IPTC 19817 - Automated Steering With Real-Time Model-Based Control by Nazli Demirer, Halliburton, et al.
Collaborative Strategy Heightens Efficiency of North Sea Predrilling Campaign
Authors: Carpenter Chris
Published: March 2022

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30850, “Perfecting the ‘Perfect Well’: Lessons Learned From the Predrilling Campaign for Johan Sverdrup,” by Janne Vølstad and Stian Bærheim, Equinor, and Knut Henriksen, Baker Hughes, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission.

The predrilling campaign for the Johan Sverdrup development was a key contributor to the successful execution of the first phase of the megaproject. After a summary of the results of the campaign, the focus of the complete paper is to identify some of the key factors behind the success of the campaign and outline lessons learned relevant to future drilling campaigns. Since the completion of the predrilling campaign, the project has successfully tied back, completed, and begun production of eight predrilled oil producers and injection in 12 subsea injectors.

Johan Sverdrup Field

The field is approximately 150 km west of Stavanger in a water depth of 110–120 m. The top reservoir is situated approximately 1800 m below mean sea level. The reservoir features hydrostatic pressure and undersaturated oil with a low gas/oil ratio.

The field has been developed in two phases. Phase 1, approved by Norwegian authorities in 2015, includes four bridge-linked platforms (Fig. 1). These platforms include a living-quarters platform (LQ) with utility system functions, a process platform (P1), a drilling platform (DP), and a riser platform (RP) with tie-in of onshore power. Phase 1 includes three injection templates tied back to the RP. All platforms have jacket substructures. Main power to the field is supplied from shore. The full field development includes 64 wells, both platform and subsea. The field came onstream in October 2019. Ramp-up of the predrilled wells went smoothly to a field production level of approximately 350,000 B/D.

Phase 2 of the development was approved in 2019 and is expected to begin production in Q4 2022. Phase 2 includes development of another processing platform (P2), modifications of the RP and the field center, and five subsea production and injection templates.

At peak, this field will account for approximately one-third of all oil production in Norway. Expected recoverable reserves are 2.7 billion BOE. The full field (Phase 1 and 2) expected oil production capacity is 105,000 std m3/d (660,000 B/D) at peak. Breakeven price for the full-field development is less than $20/bbl.
Drilling-Systems Automation Roadmap Improves Decision Making
Authors: Carpenter Chris
Published: March 2022

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199556, “Directional Drilling Automation: Human Factors and Automated Decision Making,” by Bill Chmela, SPE, Sarah Kern, SPE, and Tyler Quarles, Helmerich and Payne, et al. The paper has not been peer reviewed.

A joint industry project has created a drilling-systems-automation (DSA) roadmap to help the industry understand and anticipate the direction of drilling systems automation. In the complete paper, the authors suggest that the transition from human action to automation in the general drilling space can occur across four cognitive functions: acquiring information, analyzing and displaying information, deciding action, and implementing action. They also suggest that value exists in partial automation.

Directional Drilling: Human to Automated

One of the more-important tasks of the directional driller historically has been to decide when to rotate the pipe from the surface in an attempt to drill relatively straight and when to stop rotation, point a bent sub in the desired direction, and determine how long to drill using only the downhole mud motor (sliding) and then implement that decision on the rig.

While some directional drillers perform this task at a high level, others often fail to compensate properly for multiple variables including variations in rotary walk and build, motor-yield variations, tortuosity risks, target uncertainty, and deflections. Even expert directional drillers rarely account for reduced hydrocarbon production potential related to drilling accuracy on a survey-by-survey basis.

The following individual tasks, detailed in the complete paper, have been automated in a bit-guidance system that operates across the four cognitive functions detailed in the DSA roadmap.

- Acquire information

- Analyze and display information

- Decide action

- Implement action
Seismic Work Flow Characterizes Deep, Thin Formation Layers Offshore South China Sea
Authors: Carpenter Chris
Published: March 2022

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30164, “Deep and Thin Overpressure Reservoir Characterization of Paleogene Wenchang Formation in the Enping 17 Sag of the South China Sea,” by Jun Liu and Yingwei Li, CNOOC, and Donghai Liang, Schlumberger, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission.

The complete paper describes an integrated work flow for 3D seismic reservoir characterization of offshore deep and thin layers in the Eocene Wenchang formation (WCF) without sufficient well data. The work flow includes seismic data reprocessing, well-log-based rock physics analysis, seismic structure interpretation, 3D simultaneous amplitude variation with offset (AVO) inversion, 3D lithology prediction, and geological integrated analysis.

Formation Development and Objectives

The Pearl River Mouth basin (PRMB) on the northern continental margin of the South China Sea has undergone multistage extensional rifts. The Enping Sag lies in the Zhu1 depression, north of the PRMB, and consists of three subsags. Enping 17 is the largest and deepest sag, with an area of 550 km2, and the thickness of Eocene sediments is greater than 3000 m. The deep middle Eocene WCF, with gray lacustrine mudstones, is hydrocarbon-rich and is the major source rock in the area.

A wildcat well had penetrated the WCF at an area with a vertical thickness of 380 m. During drilling, the mud weight was increased to 1.46 g/cm3 from 4570 m total vertical depth (TVD) downward because of increasing pore pressure and higher background gas abnormalities in the WCF. A high pore-pressure gradient of 14.5 KPa/m was measured by drillstem test (DST) at a depth of 4641.5 m TVD. Under the protection of the high pore pressure, the high-quality reservoir layer from 4642 to 4651 m TVD was encountered with 12% average porosity, 3.6-md permeability, and 47.1% saturation. Although a hydrocarbon sample was not obtained during the downhole test because of technical restrictions of DST in 1985, gas surge and a small amount of gas and condensate oil were observed after the test instruments were pulled to surface. With the subsequent development of field techniques, it was likely that current drilling and DST techniques could achieve productive oil flow in this layer.
Simulating Oil and Water Production in Reservoirs with Generative Deep Learning
Authors: Alakeely Abdullah , Horne Roland
Published: March 2022

This study investigated the ability to produce accurate multiphase flow profiles simulating the response of producing reservoirs, using generative deep learning (GDL) methods. Historical production data from numerical simulators were used to train a variational autoencoder (VAE) algorithm that was then used to predict the output of new wells in unseen locations.

This work describes a procedure in which data analysis techniques can be applied to existing historical production profiles to gain insight into field-level reservoir flow behavior. The procedure includes clustering, dimensionality reduction, correlation, in addition to novel interpretation methodologies that synthesize the results from reservoir simulation output, characterizing flow conditions. The insight was then used to build and select samples to train a VAE algorithm that reproduces the multiphase reservoir behavior for unseen operational conditions with high accuracy. Furthermore, using deep feature space interpolation, the trained algorithm can be used to further generate new predictions of the reservoir response under operational conditions for which we do not have previous examples in the training data set.

It is found that VAE can be used as a robust multiphase flow simulator. Applying the methodology to the problem of determining multiphase production rate from new producing wells in undrilled locations showed positive results. The methodology was tested successfully in predicting multiphase production under different scenarios including multiwell channelized and heterogeneous reservoirs. Comparison with other shallow supervised algorithms demonstrated improvements realized by the proposed methodology.

The study developed a novel methodology to interpret both data and GDL algorithms, geared toward improving reservoir management. The method was able to predict the performance of new wells in previously undrilled locations, potentially without using a reservoir simulator.
An Assessment of the Kick Tolerance Calculation, Its Uncertainty, and Sensitivity
Authors: Thorogood John , Robertson Ewen , Castillo David , Sawaryn Steven
Published: March 2022

Much of the contemporary literature on kick tolerance relates to the practical aspects of the calculation and the effects of the underlying assumptions and necessary simplifications. It tends to a formulaic approach involving unconstrained uncertainties about pore pressure, kick intensity, drilling fluid density safety factors which tend to overlook the inherent complexities of the subsurface environment, and the reality of model limitations.

The literature on kick tolerance highlighting the strengths, weaknesses, and limitations of the classic calculation is reviewed before describing a first-principles approach to determining the consequences which casing seat strength limitations and strength variations in the overall openhole section impose on safe well designs as a result of uncertainties in the input variables and basic model assumptions.

The classic kick tolerance calculation, together with its associated assumptions, yields only a single value for a given set of inputs. The uncertainties and sensitivities are those introduced by the variables and the choice of operational procedures. The Monte Carlo method is used to explore the effect of uncertainties in the input parameters and associated assumptions.

The analysis is based on the driller’s method for kick circulation, with a single-bubble insoluble gas with optional allowances for gas gravity and thermal regimes. To examine the various factors influencing kick tolerance, the problem is framed graphically in terms of an allowable influx volume, the dependent variable, against bottomhole pressure (BHP), the independent variable, on which pore pressure, its uncertainty, possible variations in shoe strength, strength in the openhole section, drilling fluid density with associated equivalent circulating density (ECD) and swab effects can be examined.

Application of the new approach demands significant prior work to determine the uncertainties inherent in the problem. Some of these uncertainties, such as drilling fluid density variations, swabbing, and ECD, must be evaluated by the engineer as part of the normal well design. Other factors, such as shoe strength, pore pressure variability, and formation depth error bars must be developed as part of a multidisciplinary effort within the planning team. Often ignored due to the spatial uncertainties, natural fractures intersecting the borehole could be inherently unstable and prone to hydraulic communication between borehole and formation.

Synthesizing some of these considerations into a simple calculation framework allows the effect of these parameters either individually or collectively to be quantified and provides a view of the potential geological uncertainties inherent in a well design. The approach offers a starting point for thinking about the nature of geological uncertainties and carrying them into drilling programs.
An improved ultrasensitive dual-luciferase assay for sequential detection of Cypridina and Gaussia luciferases in the same sample
Authors: Walia Rampyari R. , Weigel Paul H.
Published: March 2022

We describe a rapid ultrasensitive dual luciferase (Luc) assay for sequential detection of Cypridina Luc (CLuc) and Gaussia Luc (GLuc) in supernatant or lysates samples from transfected cells. Our assay is based on the principle that the bioluminescence of CLuc can be quenched by inhibitors present in the GLuc assay buffer. The assay is far more sensitive than Firefly-Renilla dual Luc assays because the brightness of the CLuc and GLuc reporters is, respectively, 1000-times and 20-times brighter than these early-generation Luc reporters. Both the CLuc and GLuc reporters are secreted, so there is no need for cell lysis and assays can be carried out sequentially over several days using the same starting cell population. Improved assay sensitivity plus the ability to study gene expression in real time makes this assay particularly attractive for high throughput screening.
Long-term trends in nitrate and chloride in streams in an exurban watershed
Authors: Castiblanco Emma Skye , Groffman Peter , Duncan Jonathan , Band Lawrence E. , Doheny Edward , Fisher Gary T. , Rosi Emma , Suchy Amanda K.
Published: March 2022

The lines between natural areas and human habitats have blurred as urbanization continues, creating a need for the study of ecosystems at all levels of development. This need is particularly acute for exurban environments, which have low population density but are rapidly changing and have a dynamic mix of natural and human-dominated features. We examined long-term (1998 - 2018) trends in nitrate and chloride concentrations and fluxes in forested and exurban streams in Baltimore County, Md USA. Concentrations and fluxes of nitrate and chloride were an order of magnitude higher in the exurban stream than the forested stream and were increasing even though snowfall and road salt use did not increase over the study period. In the forested stream, concentrations of chloride increased from 1998 to 2008, but decreased from 2008 to 2018 due to unquantified factors. Concentrations of nitrate decreased in the forested stream, likely due to decreases in atmospheric deposition. These decreases in atmospheric deposition, and efforts to reduce fertilizer use by county governments, do not appear to have affected nitrate concentrations in the exurban watershed. Any efforts to reduce the concentrations and fluxes of chloride and nitrate in exurban streams will likely benefit substantially from further understanding of the mechanisms underlying the temporal patterns.
Perceived barriers to low vision rehabilitation services among eye care practitioners in Ethiopia: a cross-sectional study
Authors: Dendea Sinbona Geleta , Ababor Jafar Kedir , Daba Kumale Tolesa , Molla Jemal Mohammed
Published: March 2022

Background: Low vision rehabilitation services are one of the least covered subjects in ophthalmic literatures. In contrary to this, 2.2 billion people have visual impairment or blindness worldwide. Among these, 1 billion people have a vision impairment that could have been prevented or could be addressed. Objective of the study is to determine the barriers of low vision rehabilitation services in Ethiopia.Methodology: A cross sectional descriptive survey was conducted over practicing ophthalmic personnel in Ethiopia during a 2 months period (June 1 to July 30, 2020). The data was entered to Epi data manager version 4.4.1.0 and exported to SPSS version 23 for different analyses. Descriptive statistics like means, proportions and frequency tables was applied for different analysis. Chi-square test was used to test association between independent variable and dependent variables.Result: A total of 150(72.8%) out of 206 responded to the questionnaire and completed it in appropriate way. Out of 150 participants 115(76.7%) were males. Mean and standard deviation of age was 30.62±3.89 years. Among study participant’s 54(36.0%) were Ophthalmologists and subspecialists, 6(4.0%) Cataract-Surgeon, 49(32.7%) Ophthalmology-Residents and 27(18%) Optometry-Professionals. The major barriers that ophthalmic personnel face in providing low visions care includes: non-availability and expensiveness of low vision devices136 (90.67%), lack of training 117(78%), lack of awareness 49 (32.7%), lack of interest/motivation 38(25.3%) and more work load and lack of man power 34(22.67%). The perception that lack of interest/motivation is a major barrier in providing low vision rehabilitation is significantly higher [OR 3.148(1.459, 6.795)] among those who were knowledgeable than not knowledgeable about low vision services and among those trained in Ethiopia [OR 5.062(1.345, 19.050)] than abroad. Lack of training was perceived to be a major constraint for the provision of low vision rehabilitation in a greater proportion of respondents who were from institution giving low vision rehabilitation [OR 4.0125 (1.471, 10.945)] than who didn’t provide low vision rehabilitation services.Conclusion and recommendation - Non-availability of low-vision devices and expensiveness of low vision device within the country is the most common constraint for the provision of low vision rehabilitation. Majority of the participants have good awareness about low vision rehabilitation service but less knowledgeable. Training in low-vision care should be provided for eye care personnel at all levels. It is better if Ethiopian Ministry of Health give concern for ways to provide low vision devices at all government eye care services.
Plastic pollution in riverbeds fundamentally affects natural sand transport
Authors: Russell Catherine , Fernández Roberto , Parsons Daniel , Gabbott Sarah
Published: March 2022

Rivers link terrestrial and ocean environments, distributing fresh water, nutrients, and sediment to diverse ecosystems. Over the past 50 years, rivers have become increasingly significant vectors for plastic pollution. Lowland riverbeds exhibit coherent features including ripple and dune bedforms, which transport sediment downstream via well-understood processes, yet the impact of plastic on sediment transport behaviours is largely unknown. Here we use a flume tank to show that when plastic particles are introduced to sandy riverbeds, even at relatively low concentrations, novel bedform morphologies and altered processes emerge, including irregular bedform stoss erosion and dune “washout”, causing topographic bedform amplitudes to decline. We detail i) new mechanisms of plastic incorporation and transport in riverbed dunes, and ii) how sedimentary processes are fundamentally influenced. Hence, plastic is not a passive component of river systems; it directly affects bed topography, whilst increasing the proportion of sand suspended in the water, which has the potential to impact river ecosystems and the wider landscape. The resulting plastic distribution in the sediment is heterogeneous, highlighting the challenge of representatively monitoring plastic concentrations. Our insights establish a new branch of process sedimentology: plastic and sand interactions, set to be increasingly relevant amongst emerging challenges of the Anthropocene.
Tool wear predicting based on weighted multi-kernel relevance vector machine and probabilistic kernel principal component analysis
Authors: Song Guohao , Zhang Jianhua , Ge Yingshang , Zhu Kangyi , Fu Zhensheng , Yu Luchuan
Published: March 2022

This paper proposes a novel tool wear predicting method based on weighted multi-kernel relevance vector machine (WMKRVM) and the integrated radial basis function-based probabilistic kernel principal component analysis (PKPCA_IRBF). The proposed WMKRVM model constructs the optimal multi-kernel model by seeking the weight parameter of the optimized single kernel RVM. As a new dimension increment technique, PKPCA_IRBF can extract the noise information of the process data and incorporate the noise information into the model. Moreover, this work first proposes using PKPCA_IRBF to fuse monitoring feature to improve the CI provided by the WMKRVM model. Besides, the parameter selection region and model accuracy of the PKPCA_IRBF are better than the conventional PKPCA_RBF technique, which helps improve the efficiency of model construction. The cutting experiment is conducted to validate the effectiveness of the proposed tool wear predicting technique. Experimental results show that the proposed tool wear predicting technique can accurately monitor the tool wear width with strong robustness under various cutting conditions, laying the foundation for applying to the industrial field.
Identification, algicidal activity and complete genomic sequencing of the newly found algicidal bacteria Enterobacter hormaechei F2
Authors: Zhang Bin , Yang Ying , Xu Liang , He Wei , Xie Wenjia , Liu Wei
Published: March 2022

An effective algicidal bacterium, Enterobacter hormaechei F2, was isolated and identified using 16S rDNA sequencing. The increased production of algal catalases and peroxidases as well as the production of reactive oxygen species demonstrated the effective and distinctive algicidal activities of E. hormaechei F2. The comparative effects of different components of bacterial solutions suggested that indirect algicidal disruption was the major mechanism of E. hormaechei F2 performance. Dialysis of the extracellular material revealed that the molecular weight of the algicides was less than 3.5 kDa. These were inferred to be proteins, amino acids, and other small molecules. Gene enrichment analysis shows the pathways such as amino acid metabolism and Type n secretion systems involved in the algicidal process, which can predict that prodigiosin and signaling systems may play a role in the algicidal activity.
Observed spatial heterogeneity in insect-vectored pathogen promotes pathogen survival
Authors: Tomkins Melissa , Groves Russell , Grieneisen Verônica , Hogenhout Saskia , Marée Athanasius
Published: March 2022

Insect-vectored plant pathogens cause massive crop yield losses worldwide. Outbreaks often have patchy incidences on both spatial and temporal scales, which are thought to be driven by external factors such as the level of heterogeneity in plant hosts and vector dispersal. Mathematical modelling of Aster Yellows phytoplasma disease spread, a vector-borne plant pathogen, predicts under the assumption of well-mixed population dynamics only one possible stable outcome: all insect vectors end up being carriers of the pathogen. This outcome is in stark contrast to multi-year datasets revealing local co-existence of carrier and non-carrier vectors. We predict however dramatically different tripartite plant-vector-pathogen dynamics when explicitly taking space into account. Spatial simulations allow to explain both the stable coexistence of carrier and non-carrier insects and the large spatial and temporal variations in disease incidence, this co-existence being driven by emergent patterning. Moreover, simulations of the eco-evolutionary progression of the infection dynamics predict an evolutionary stable state that quantitatively matches field observations and prove that empirically observed complex patterning is the inevitable evolutionary outcome of this tripartite system. We infer that the known diversity in phytoplasma effector proteins could be an evolved mechanism for pathogen survival in fast-changing environments, such as agricultural areas.
Kinetochore- and chromosome-driven transition of microtubules into bundles promotes spindle assembly
Authors: Matković Jurica , Ghosh Subhadip , Ćosić Mateja , Barisic Marin , Pavin Nenad , Tolić Iva
Published: March 2022

Mitotic spindle assembly is crucial for chromosome segregation and relies on bundles of microtubules that extend from the poles and overlap in the middle. However, how these structures form remains poorly understood. Here we show that overlap bundles arise through a network-to-bundles transition driven by kinetochores and chromosomes. STED super-resolution microscopy revealed that PRC1-crosslinked microtubules initially form loose arrays, which become rearranged into bundles. Kinetochores promote microtubule bundling by lateral binding via CENP-E/kinesin-7 in an Aurora B-regulated manner. Bundle separation is driven by steric interactions of the bundle-associated chromosomes at the spindle midplane since spindles with uncondensed or uncongressed chromosomes are narrower. In agreement with experiments, theoretical modeling suggests that bundles arise through competing attractive and repulsive mechanisms. Finally, perturbation of overlap bundles led to inefficient correction of erroneous kinetochore-microtubule attachments. Thus, kinetochores and chromosomes drive coarsening of a uniform microtubule array into overlap bundles, which promote not only spindle formation but also chromosome segregation fidelity.
Mapping of glacial lakes and glacial lake outburst flood in Lahul and Spiti district using remote sensing and GIS
Authors: Vishwas Poonam , Nadh Gopi , Tiwari kc
Published: March 2022

Glacial lake outburst floods (GLOFs) refers to the sudden release of water from a glacial lake. This has the potential to endanger human lives as well as cause environmental and economic damage. Climate change is causing glaciers to retreat and subsequent formation of new glacial lakes. GLOFs are one of the most common climate change hazards in India's Himalayan region of Himachal Pradesh. In the present study, GLOFs mapping has been carried out using remote sensing (RS) and geographic information system (GIS). For glacial lake mapping, Landsat-7 and 8 data from 2005, 2010, 2015, and 2019 were employed. Landsat images were employed for classification and change detection using normalized difference water index (NDWI) to identify the temporal variation of Samudra Tapu glacier lake and Geepang Gath glacial lake, which are two major glacial lakes in the Lahul and Spiti district. A 30 m digital elevation model (DEM) was created by the data providers by the shuttle radar topography mission (SRTM) 1arc sec global used for calculating the parameters such as maximum, minimum, mean elevation, slope, and aspect. The lake volume and depth have been calculated using Huggel empirical formulae, and other parameters such as area, slope, aspect, and drainage network have been prepared using ArcGIS 10.8. The maps for land use and land cover (LULC) were produced using the supervised classification technique by considering the maximum likelihood classification (MLC) algorithm. The lake size has increased from 0.542 to 0.929 km 2 for Geepang Gath glacial lake and 0.849 to 1.239 km 2 for Samudra Tapu glacial lake during the time period of 2005-2019. The findings indicate that there is a need to build risk management plans, improve spatial planning in order to be well prepared for future potential GLOF hazards.
Herbicidal secondary metabolites from Bacillus velezensis JTB8-2 against Orobanche aegyptiaca
Authors: He Wei , Li Yan , Luo Wenfang , Zhou Junhui , Zhao Sifeng , Jianjun Xu
Published: March 2022

Egyptian broomrape (Orobanche aegyptiaca) is a parasitic plants that cause significant losses to important crops. The effective methods for controlling this weed are rare. Biological control could be one of the possible strategies to tackle these weeds efficiently. In this work, a bacteria strain Bacillus velezensis JTB8–2 was proven to possesse biological control functions against broomrapes in both pot and field experiments. Four secondary metabolites (1–4) were isolated from the B. velezensis JTB8–2 crude extracts, and all of them could inhibit the germination of O. aegyptiaca seeds at concentrations from 0.5 mM to 4 mM. Their structures were further elucidatedby Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) analysis. Among the isolated compounds, 1 and 2 exhibited the strongest herbicidal activity with 100% inhibition rate against the germination of O. aegyptiaca seeds at 4 mM, and thus had great potential in the development of new herbicidal products to control O. aegyptiaca in the future.
First-principle investigation of CO, CH4 and CO2 adsorption on Cr-doped graphene-like hexagonal borophene
Authors: Wang Chao , Gao Caihong , Hou Jianhua , Duan Qian
Published: March 2022

It is important for life safety and scientific research to design new sensing materials for detecting CO, CH 4 and CO 2 from environment. We theoretically designed a new Cr-doped graphene-like hexagonal borophene (CrB 6 ) as potential sensor material for these gases. Carrying out firstprinciples density-functional calculations, we calculated the adsorption energy, band structure, adsorption distance, charge transfer, charge density difference, density of states and partial density of states of CO, CH 4 and CO 2 gas molecules absorbed on CrB 6 monolayer. The calculated results show that the adsorption behavior of CO is different from those of CH 4 and CO 2 . CO adsorbed on CrB 6 monolayer prefers chemisorption while CH 4 and CO 2 adsorbed on CrB 6 monolayer prefers physisorption. As a result, the different adsorption behaviors have significant influence on the band structures and density of states of CrB 6 monolayer. We hope that our results can help experimentalists synthesize better sensor materials based on hexagonal borophene.
Rigorous probing of the electronic structure of Berkelium and Californium actinide atoms
Authors: Msezane Alfred , Felfli Zineb
Published: March 2022

A recent experiment identified a weak spin-orbit-coupling in atomic Bk while a jj coupling scheme described atomic Cf. It concluded that these observations strengthen Cf as a transitional element in the actinide series. This paper uses Ramsauer-Townsend (R-T) minima and shape resonances (SRs) from low-energy electron elastic total cross sections (TCSs) calculated using the rigorous Regge pole method as novel confirmation of the observation. Regge pole-calculated TCSs for Bk and Cf atoms are characterized generally by ground, metastable and excited states negative-ion formation, R-T minima and SRs. Additionally, a polarization-induced metastable TCS with a deep R-T minimum near threshold characterizes the Bk TCSs, which flips over to a well pronounced SR appearing very close to threshold in the Cf TCSs. This demonstrates the sensitivity of R-T minima and SRs to the electronic structure of these atoms, thereby permitting their first time ever use as novel and rigorous validation of the experimental observation.
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Hydrogen-Bonded Networks in Acetone-Alcohol Binary Mixture: Molecular Dynamics Study
Authors: U Abdulkareem , Kartha Thejus R , Madhurima V
Published: March 2022

Our previous studies on various hydrogen-bonded binary systems have shown anomalous physico-chemical properties at lower (10–30%) volume concentrations of either one or both of the components [1]. In order to have a better understanding of this phenomenon, a systematic molecular dynamics study of binary mixtures of acetone with 8 primary alcohols (R-OH, with R = 1 to 8) was undertaken. The radial distribution function results indicate that the hydrogen bond distribution among alcohols in R=(1, 2) increases as the concentration of acetone increases, indicating the hydrogen bond networks are not disrupted by acetone, unlike that of higher alcohols. It is also seen, from the hydrogen bond statistics, that the number of acetone-alcohol hydrogen bonds are predominant for R= (3, 4, 6) and the hydrogen bonds between alcohols for the rest, suggesting R= (3, 4, 6) are attractive to acetone compared to other alcohols. The hydrogen bond networks are visualized using the graph-theoretical approach to get a clearer picture of their hydrogen-bonding network. With an increase in acetone concentration, the average number of degrees of association decreases for all systems, showing an overall decrease in hydrogen bond multimers structures.
Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease
Authors: Uddin Md Mesbah , Nguyen Ngoc Quynh , Yu Bing , Brody Jennifer , Pampana Akhil , Nakao Tetsushi , Fornage Myriam , Bressler Jan , Sotoodehnia Nona , Weinstock Josh , Honigberg Michael , Nachun Daniel , Bhattacharya Romit , Griffin Gabriel , Chander Varuna , Gibbs Richard , Rotter Jerome , Liu Chunyu , Baccarelli Andrea , Chasman Daniel , Whitsel Eric , Kiel Douglas , Murabito Joanne , Boerwinkle Eric , Ebert Benjamin , JAISWAL SIDDHARTHA , Floyd James , Bick Alexander , Ballantyne Christie , Psaty Bruce , Natarajan Pradeep , Conneely Karen
Published: March 2022

Age-related changes to the epigenome are well-documented, especially the pattern of genome-wide DNA methylation (DNAm) changes observed in blood. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by the age-related acquisition and expansion of leukemogenic mutations in hematopoietic stem cells (HSCs), is associated with blood cancer and coronary artery disease (CAD). Epigenetic regulators DNMT3A and TET2 are the two most frequently mutated CHIP genes. Here, we present results from an epigenome-wide association study for CHIP in 582 Cardiovascular Health Study participants, with replication in 2655 Atherosclerosis Risk in Communities Study participants. We show that DNMT3A and TET2 CHIP have distinct and directionally opposing genome-wide DNAm association patterns consistent with their regulatory roles, albeit both promoting self-renewal of HSCs. Mendelian randomization analyses indicate that a subset of DNAm alterations for these two leading CHIP genes may promote the risk for CAD.
Cryo-EM structures reveal the activation and substrate recognition mechanism of human enteropeptidase
Authors: Huang Haojie , Li Zhaoshen , Yang Xiaoli , Ding Zhanyu , Peng Lisi , Song Qiuyue , Cui Fang , Zhang Deyu , Xia Chuanchao , Li Keliang , Yin Hua , Li Shiyu
Published: March 2022

The enteropeptidase (EP) initiates the intestinal digestion by proteolytic processing of trypsinogen, generating catalytic active trypsin. The dysfunction of EP will cause a series of pancreatic diseases, the most severe of which is acute necrotizing pancreatitis. However, the molecular mechanism of EP activation and substrate recognition remain elusive due to the lack of structural information, hampering the structure-based research of EP and even further EP-targeted drug design. Here we report cryo-EM structures of human EP in multiple states, covering the functional cycle spanning from inactive to active state and eventually to the substrate binding state, with the inactive core region reached an atomic 2.7-Å-resolution. The heavy chain of EP exhibits a clamping configuration with the CUB2 domain serving for substrate recognition. The N-terminus of light chain induces the surface loop remodeling from inactive to active conformation, resulting in a highly dynamic and active EP. Then the heavy chain performs like a hinge to ensure the flexibility of light chain for substrate recruitment and subsequent cleavage. Our study provides structural insights of EP remodeling and heavy chain dynamics while performing enzymatic function, facilitating our understanding of the pathogenies of EP-related pancreatitis and the EP-targeted treatment of pancreatitis.