bluuebunny/crossref_metadata_2025 huggingface dataset:
Petrophysical analysis of the unconventional reservoirs of the Lennard Shelf and Fitzroy Trough in Canning Basin, Australia
Authors: Shelokov Valeri , Hull Robert , Rudge Tony , Richmond Perry
Published: July 2021

A US operator with a commitment to future drilling, stimulation and testing of unconventional wells has initiated a new evaluation to better define and understand the hydrocarbon plays along the northern margin of the Canning Basin’s Lennard Shelf and Fitzroy Trough. The goal of the evaluation is to determine the commercial viability of the region. In this paper, an integrated petrophysical hybrid model that has been calibrated to core data is highlighted. From this model, multiple play types were identified, including an unconventional siltstone-shale play, a conventional basin-centred tight gas play and a fractured tight gas play with potential analogs to North American unconventional plays. Six primary lithofacies were identified through the integration of thin section analyses, core descriptions, logs and petrophysical models. The results were calibrated to high-resolution formation image data to better understand the thin-bedded nature of these plays. The lithofacies were also utilised for defining core poro/perm transforms. Furthermore, an integrated descriptive mud log algorithm was utilised to define the types of hydrocarbons, including wetness, balance and ratios as the hydrocarbons’ fingerprints. Significant gas influxes were noted at the intervals with highly permeable beds, at swarms of fractures and faults, as well as within the organic rich layers. In this study, a pressure top seal for the Laurel Formation was defined as well as the highlights of one well, which includes 11 zones and over 389m of net pay behind pipe. The significance of this work is that it highlights a path forward for unconventional development that, if economically viable, would provide increased energy independence for Australia.
Geological overview of the 2021 offshore acreage release areas
Authors: Bernecker Thomas , Owens Ryan , Kelman Andrew , Khider Kamal
Published: July 2021

In 2021, a total of 21 areas were released for offshore petroleum exploration. They are located in the Bonaparte Basin, Browse Basin, Northern Carnarvon Basin, Otway Basin, Sorell Basin and Gippsland Basin. Despite COVID-19 negatively impacting the industry, participation in the acreage release nomination process was again robust. However, as has been the case in recent years, industry interest is focussed on those areas that are close to existing discoveries and related infrastructure. In tune with the Australian government’s resource development strategy, the areas being offered for exploration are likely to supply extra volumes of natural gas, both for export to Southeast Asian markets and domestically to meet the forecasted shortage in supply to eastern Australia. According to the 2019 implementation of a modified release process, only one period for work program bidding has been scheduled. The closing date for all submissions is Thursday, 3 March 2022. Geoscience Australia continues to support industry activities by acquiring, interpreting and integrating pre-competitive datasets that are made freely available in the context of the agency’s regional petroleum geological studies. As part of a multidisciplinary study, new data, including regional seismic and petroleum systems modelling, for the Otway Basin are now available. Also, a stratigraphic/sedimentological review of the upper Permian to Early Triassic succession in the southern Bonaparte Basin has been completed, the results of which are being presented at this APPEA conference. Large seismic and well data sets, submitted under the Offshore Petroleum and Greenhouse Gas Storage Act 2006 (OPGSSA), are made available through the National Offshore Petroleum Information Management System (NOPIMS). Additional data and petroleum-related information can be accessed through Geoscience Australia’s data repository.
Top three LNG buyers to search for alternative LNG pricing structure after paying a total cost premium of $56 billion for oil-indexed LNG contracts in 2019 and 2020 – how will this affect Australia as the number one supplier to this market?
Authors: Knutsson Sindre
Published: July 2021

Increasing spreads between spot liquefied natural gas (LNG) and oil-indexed contracts have resulted in the world’s top three LNG buyers paying a cost premium of $33 billion in 2019 and 23 billion in 2020. The top three buyers are Japan, China and South Korea, which had a combined 151Mt of long-term LNG contracts indexed to oil in 2020. This cost premium shows what top Asian buyers are currently paying for the security of LNG supply through long-term oil-indexed contracts. However, it also shows the potential reward Asian buyers have if they manage to develop a liquid LNG pricing hub in Asia to which they can index their contracts. Japanese buyers’ efforts of increasing flexibility in contracts, both through take-or-pay agreements and destination flexibility and aims of growing the spot market, will increasingly support the liquidity of the LNG market. However, there will be resistance from the other side of the table, for where someone is paying a premium, or making a loss, someone is making money. 2020 was another year of plenty for LNG producers selling oil-indexed volumes to Asian markets. Australia is the largest seller of LNG to Japan, China and South Korea with over 60Mt of long-term LNG contracts indexed to oil in 2020. Australia has benefited from having their contracts indexed to oil, but what’s next? In this paper, Rystad Energy will discuss the future market for Australian LNG exports including development in LNG demand, contract trends and price spreads.
Keys to successful negotiation of indigenous land use agreements and building consent for the development of natural resources, The Great Sandy Desert Project, a case study
Authors: van Hattum Jop , Bin-Rasheed Martin (Kusi) , Castledine Graham
Published: July 2021

Theia Energy Pty Ltd discovered a substantial hydrocarbon resource in the Canning Basin, NW in Western Australia, just 150-km SE of Broome. Since 2014, Theia Energy has built a robust working relationship with the traditional owners of the land that hold native title over their permits. This relationship has developed through negotiation meetings, on-country cultural heritage surveys and cultural awareness training. The relationship has culminated in the negotiation of indigenous land use agreements (ILUA) with the Karajarri People that manage the impacts of potential development of the resource including the impacts of hydraulic fracture stimulation, and provide significant economic development opportunities. The consistent exchange of information and views has developed mutual understanding and respect allowing for the effective and pragmatic treatment of risks to allow for the exploration, and if successful the development, of the onshore Canning Basin. The Great Sandy Desert Project has the potential to bring substantial benefits to regional communities and is significant for economic development of the West Kimberley, state revenue and national liquid fuel security. This study discusses important lessons learned in building trust with traditional owners and custodians of the land and how cultural values can be protected while providing social and economic opportunities for Indigenous Australians in a sustainable and culturally appropriate way. It reflects on the outcomes of the many scientific inquiries into hydraulic fracture stimulation and the perception of risks and impacts of traditional owners which must be addressed in a genuine, meaningful and effective way. It also sets out how traditional owners have, through the negotiation of the ILUA with Theia Energy and in the absence of clear policy from Government, chosen to establish their own system of regulation and economic participation in the project to address and manage risks and impacts from the development of resources on their country.
Decommissioning and rehabilitation: funding models
Authors: Wee Kenneth
Published: July 2021

Decommissioning oil and gas facilities and rehabilitating a petroleum operation area involve complex, lengthy and costly processes. Funding the liability for the decommissioning and rehabilitation phase of a petroleum project is determined by the juxtaposition of a matrix of three fundamental and closely interdependent policy decisions on:
whose obligation it is (the proponent, the state or both) to carry out decommissioning,
whose liability it is (the proponent, the state or both) to pay for decommissioning and
which decommissioning funding model is appropriate for the proponent and/or the government (if there is state participation). Proponent models may include funding with or without security or contributions to a decommissioning fund. Government funding models are inextricably linked with the imposition, collection and appropriation of the fiscal take applying to the oil and gas sector.

There are therefore many variants in the responses to, and stance taken, on the above policy issues. It is, however, universally accepted that the state should not be inadvertently left with the ultimate obligation and/or the liability for decommissioning and rehabilitation. The preferred policy choice involves finely balancing the interests of the state without disincentivising private sector investment in the development of the petroleum resource. This study will review the pros and cons of the main alternative funding models typically used internationally, the status of Australia’s decommissioning funding and associated fiscal policies, whether and to what extent the Australian government participates in the funding of decommissioning and rehabilitation undertakings and proposed improvements to the policy design settings.
2021 Offshore petroleum exploration acreage release
Authors: Trotman Paul
Published: July 2021

In 2020, the liquefied natural gas (LNG) trade saw a modest increase of 1%, which is in contrast to the strong growth of previous years. Recently, the global LNG trade has picked up following the easing of impacts from the pandemic and demand growth in Asia. An increase of 6% in the global LNG trade is expected in 2021 and 2022. Domestic demand for gas remains high, with gas being used both for residential supply and also as an essential feedstock for the manufacturing industry. With a projected domestic gas shortfall, the future exploration and development of oil and gas will play a key role in ensuring access to secure, reliable and affordable energy in the future as well as assisting economic recovery from the pandemic. The importance of remaining an attractive investment destination is essential. Our challenge is to not only strike the balance of being agile and adaptive to market disruptions but also provide robust policy and regulatory frameworks to underpin future investment in the sector. Against this backdrop, this paper provides details of the 2021 offshore petroleum exploration acreage release and information about the ongoing policy work of the department.
Social licence: what is really going on out there?
Authors: Browne Sarah , Scales John
Published: July 2021

This extended abstract will explore the real community landscape facing the gas industry and how assessment of independent metrics can better help design strategy, guide investment and provide insight and support to decision makers. It draws on independent polling from JWS Research, comprehensive digital analysis and learnings from 3 years of APPEA’s community engagement program, Brighter. It will provide a comprehensive and up to date industry wide analysis of current community sentiment, influencing factors and effective ways of communicating. It also provides a practical assessment of the application of this information, measures of success and real-life examples. Finally, it identifies emerging themes among the community, stakeholders and media that impact the industry’s social licence and outline APPEA’s approach to the changing public affairs landscape.
Australian exploration review 2020
Authors: Cockerill Ian
Published: July 2021

Australian exploration battled on through the challenging headwinds of 2020 and surprisingly, 2020 saw an increase in exploration drilling on 2019 activity. Twenty-five exploration wells were drilled in 2020 versus 20 exploration wells drilled in 2019. Eight discoveries were made during the year, with the most significant being the Enterprise discovery in the Otway Basin. 2020 also saw a return to exploration drilling in the Beetaloo Sub-basin unconventional plays. Appraisal drilling was dominated by Cooper-Eromanga Basin and coal seam gas activity. There were no offshore appraisal wells in 2020. The exploration farm-in deals of note were Santos taking additional equity from Armour in their South Nicholson Basin unconventional project and Origin taking additional equity from Falcon in their Beetaloo Sub-basin unconventional project. Origin also farmed into the Canning Basin position of Buru Energy and Rey Resources. Australia is set for an exciting year of exploration ahead with a return to exploration drilling in the Bedout Sub-basin, further exploration drilling in the North Perth Basin and a continuation of drilling and testing of the unconventional plays in the Beetaloo Sub-basin.
Statistical analysis of ENDOR spectra
Authors: Pokern Yvo , Eltzner Benjamin , Huckemann Stephan F. , Beeken Clemens , Stubbe JoAnne , Tkach Igor , Bennati Marina , Hiller Markus
Published: July 2021

Significance

Statistical modeling of experimental data is gaining increasing importance in biological science due to the availability of large datasets. Here we present a statistical analysis of electron–nuclear double resonance, a technique that delivers information on the angstrom to nanometer scale around paramagnetic centers in proteins. The described method allows for recognizing experimental artifacts and provides the most probable signal as well as its uncertainty. Application to representative high-field electron–nuclear double resonance spectra of a prototype tyrosyl radical in a protein, theβ2subunit ofEscherichia coliribonucleotide reductase, demonstrates that subtle information can be uncovered, such as a distribution of molecular orientations relevant for the biological function of this essential radical.
Transparent communication about negative features of COVID-19 vaccines decreases acceptance but increases trust
Authors: Petersen Michael Bang , Bor Alexander , Jørgensen Frederik , Lindholt Marie Fly
Published: July 2021

Significance

During a pandemic, governments face incentives to not disclose negative information about vaccines to not jeopardize public vaccine acceptance. Against these incentives, the current study provides an experimental, cross-national demonstration of the importance of transparency in communication about a vaccine against COVID-19. While disclosing negative information may increase hesitancy, transparency sustains trust in health authorities and hinders the spread of conspiracy beliefs. Accordingly, the current results provide a clear warning against succumbing to the short-term incentive of withholding information. Sustaining trust during the pandemic is critical for health authorities, both if repeated vaccinations are necessary and in preparation for future health emergencies. Among those who have already lost trust, health communication has little persuasive effect.
Cytoklepty in the plankton: A host strategy to optimize the bioenergetic machinery of endosymbiotic algae
Authors: Uwizeye Clarisse , Mars Brisbin Margaret , Gallet Benoit , Chevalier Fabien , LeKieffre Charlotte , Schieber Nicole L. , Falconet Denis , Wangpraseurt Daniel , Schertel Lukas , Stryhanyuk Hryhoriy , Musat Niculina , Mitarai Satoshi , Schwab Yannick , Finazzi Giovanni , Decelle Johan
Published: July 2021

Significance

Symbiosis between single-celled hosts and microalgae is a widespread and ecologically important phenomenon in oceanic plankton. Investigating such relationships can increase understanding of how novel organelles are acquired. Here, we integrate multiple subcellular approaches to show how a unicellular host manipulates the bioenergetic machinery of its algal endosymbionts and maximizes organic carbon production for its own benefit. Symbionts are blocked from dividing, but their photosynthetic machinery and associated mitochondrial network dramatically expand while keeping close physical proximity to each other. Genes involved in photosynthesis and carbon fixation are up-regulated, while those for carbon storage are down-regulated. Such extreme remodeling of microalgae has not been reported in other photosymbioses and provides insight into the putative early steps of plastid acquisition.
An Unsupervised Machine Learning Approach for the Detection and Characterization of Illicit Drug-Dealing Comments and Interactions on Instagram
Authors: Shah Neal , Li Jiawei , Mackey Tim K.
Published: July 2021

Background: Growing use of social media has led to the emergence of virtual controlled substance and illicit drug marketplaces, prompting calls for action by government and law enforcement. Previous studies have analyzed Instagram drug selling via posts. However, comments made by users involving potential drug selling have not been analyzed. In this study, we use unsupervised machine learning to detect and classify prescription and illicit drug-related buying and selling interactions on Instagram. Methods: We used over 1,000 drug-related hashtags on Instagram to collect a total of 43,607 Instagram comments between February 1st, 2019 and May 31st, 2019 using data mining approaches in the Python programming language. We then used an unsupervised machine learning approach, the Biterm Topic Model (BTM), to thematically summarize Instagram comments into distinct topic groupings, which were then extracted and manually annotated to detect buying and selling comments. Results: We detected 5,589 comments from sellers, prospective buyers, and online pharmacies from 531 unique posts. The vast majority (99.7%) of comments originated from drug sellers and online pharmacies. Key themes from comments included providing contact information through encrypted third-party messaging platforms, drug availability, and price inquiry. Commonly offered drugs for sale included scheduled controlled substances such as Adderall and Xanax, as well as illicit hallucinogens and stimulants. Comments from prospective buyers of drugs most commonly included inquiries about price and availability. Conclusions: We detected prescription controlled substances and other illicit drug selling interactions via Instagram comments to posts. We observed that comments were primarily used by sellers offering drugs, and typically not by prospective buyers interacting with sellers. Further research is needed to characterize these “social” drug marketplace interactions on this and other popular social media platforms.
Understanding Caregiver Acceptance of Screening for Family Substance use in Pediatric Clinics Serving Economically Disadvantaged Children
Authors: Matson Pamela A. , Bakhai Neha , Solomon Barry S. , Flessa Sarah , Ramos Julia , Hammond Christopher J. , Adger Hoover
Published: July 2021

Background: Children of parents with substance use disorders are at greater risk for mental and physical health co-morbidities. Despite guidelines, pediatricians rarely screen for substance use in the family/household, citing fear of offending parents. The objectives of this study were to examine (1) caregiver acceptance of pediatricians screening for family/household substance use during well-child visits, (2) prevalence of family/household substance use, and (3) the association between family/household substance use and trust in their child's pediatrician. Methods: This cross-sectional study surveyed adult caregivers presenting a child for medical care at two urban pediatric outpatient clinics using a brief anonymous computer-based survey. The primary outcome measured the acceptability of pediatrician screening for family/household substance use. Substance use and concerns about use in the family/household were also assessed. Results: Adult caregivers ( n = 271) surveyed were mean age 35 years, 73% mothers, 90% African American, and 85% on Medicaid. Over half (51%) of caregivers reported substance use by someone in the family/household, most commonly cigarettes (38%), followed by alcohol (19%) and marijuana (10%). Sixty-one percent of caregivers who reported family substance use expressed concern about the use of this substance. The majority (87%) agreed it is appropriate for pediatricians to ask caregivers about family/household substance use. No differences were found between caregivers who did and did not report substance use in their family/household. Caregivers with concerning substance use in their family/household were less likely to trust their pediatrician [OR = 0.21, 95%CI: 0.05, 0.85] Conclusions: Caregivers endorsed acceptance of universal screening for substance use, including illicit substances, and substance use disorders in the family/household during well-child visits. Pediatricians are trusted professionals with expertise in communicating with parents to maximize the health of their patients; assessing family history of substance use and substance use disorders is a natural extension of their role.
Changes in Social Work Students’ Attitudes and Knowledge following Opioid Overdose Prevention Training
Authors: Halmo Rebekah S. , Sellers Christina M. , Collin Cali-Ryan R. , Chinamasa Gordon , Putney Jennifer M.
Published: July 2021

Background: Opioid use disorders are widespread, commonly occurring, and have serious impacts on individuals, families, and communities. When adequately trained, social workers play a pivotal role in treating populations impacted by opioid use through the provision of high-quality services and the shifting of negative attitudes related to opioid use. However, workforce projections indicate a growing shortage of behavioral health professionals qualified to work with such populations and, presently, social work programs are not equipped to meet these workforce needs. Emerging evidence suggests opioid overdose education is associated with improved attitudes and knowledge among health professions; however, less information exists on the outcomes of such training among social work students. Schools of social work must develop and evaluate curricular components related to opioid use prevention and management to adequately prepare students for clinical work as social work practitioners. Methods: Thirty-three advanced-year MSW students received opioid overdose training as part of a day-long seminar on substance use. Content included acute effects of opioids, withdrawal symptoms, risk factors, signs of overdose, naloxone training, and harm reduction principles. Using a single-group pretest-posttest design, students completed the Opioid Overdose Attitudes Scale (OOAS) and the Opioid Overdose Knowledge Scale (OOKS). To evaluate students’ attitudes and knowledge, investigators compared overall and subscale means before and after the training via paired samples t-tests. Results: Findings indicated statistically significant improvements in the “concerns” and “competence” domains of the OOAS. Likewise, findings indicated statistically significant improvements in the “risk,” “signs,” “action,” and “naloxone use” domains of the OOKS. Conclusion: Students reported improved opioid overdose-related knowledge and attitudes when assessed after the training as compared to before the training. Due to the nature of the study design, causality cannot be inferred from the training outcomes. Findings may help other social work programs develop curricular components related to opioid use.
Alcohol use Disorder in Active Duty Service Members: Incidence Rates over a 19-Year Period
Authors: Judkins Jason L. , Smith Kendra , Moore Brain A. , Morissette Sandra B.
Published: July 2021

Background: Alcohol use is a concerning issue for the military given its potential negative impact on human performance. Limited data are available regarding the incidence of alcohol use disorder in the military, which is critical to understand to evaluate force readiness, as well as for preventative initiatives and treatment planning. The aim was to examine the alcohol use disorder incidence rates (overall and across demographics) among active duty service members from 2001 to 2018. Methods: Data on 208,870 active duty service members between 2001 and 2018 from the Defense Medical Epidemiology Database was examined. Incidence rates were analyzed to determine the diagnostic rates of AUD (including both alcohol abuse and dependence), which were then examined by sex, age, service branch, military pay grade, marital status, and race. Results: Incidence rates of AUD in active duty service members (per 1,000 service members) ranged from 6.45 to 10.50 for alcohol abuse and 5.21 to 7.11 for alcohol dependence. Initial diagnoses of new-onset AUD occurred most frequently within 20–24 year-old, white, male, and non-married U.S. Army service members in the enlisted pay grades of E-1 to E-4. Statistically significant differences ( p <.001) were found between observed and expected counts across all examined demographic variables. Conclusions: To our knowledge, this is the first study to provide a comprehensive examination of AUD incidence rates in an active-duty military population over an extended 18-year period and during the last decade. Incidence rates were higher than expected for alcohol dependence and lower than expected for alcohol abuse. Given the untoward effects of AUD on overall health and force readiness, active-duty service members may benefit from more advanced preventative interventions to decrease incidence rates of AUD over time. Future research should use these data to develop targeted interventions for the demographics at greatest risk.
“The Gatekeepers in Prevention”: Community Pharmacist Perceptions of Their Role in the Opioid Epidemic
Authors: Vadiei Nina , Eldridge Lori Ann , Meyerson Beth E. , Agley Jon
Published: July 2021

Background: Community pharmacists are at the frontline of patient care, yet their role in the opioid epidemic remains unclear. This qualitative study examines the perception of community pharmacists about their role in the opioid epidemic and challenges to fulfilling this role. Methods: A secondary analysis of cross-sectional survey data from an Indiana census of community managing pharmacists was conducted. Qualitative data were coded using a priori and emergent themes. A priori categories included the perceived role of pharmacists in the opioid epidemic and perception of practice barriers. Results: A total of 215 Indiana community managing pharmacists participated in this study. Pharmacists understood themselves as gatekeepers in preventing opioid misuse and overdose. Reported pharmacy practices included providing patient education and communicating with prescribers. Challenges to fulfilling this role included pharmacy structure and operation, lack of patient and provider clarity about pharmacist scope of practice, and pharmacist perception that that there is no available discretionary time to support additional services. Conclusion: Pharmacists believe they have a vital role in combatting opioid misuse and overdose but are hampered by structural aspects of pharmacy practice and lack of recognition of their role. Pharmacy associations and policy partners are encouraged to identify opportunities to address these barriers.
Alternative use of Buprenorphine among People who use Opioids in Three U.S. Cities
Authors: Gandhi Priyal , Rouhani Saba , Park Ju Nyeong , Urquhart Glenna J. , Allen Sean T. , Morales Kenneth B. , Green Traci C. , Sherman Susan G.
Published: July 2021

Background: Buprenorphine is an effective treatment for opioid use disorder, yet some persons are concerned with its “alternative use” (i.e., any use unintended by the prescriber). There is limited evidence on the factors associated with alternative use of buprenorphine (AUB); in this study, we examined correlates of recent (past 6 months) AUB. Methods: Multivariable logistic regression was used to analyze survey data from a multi-site, cross-sectional study of people who use drugs (PWUD) ( N = 334) in Baltimore, Maryland; Boston, Massachusetts; and Providence, Rhode Island. Results: One-fifth (20%) of the sample reported recent AUB. In adjusted analyses, significant negative correlates of AUB were female gender (adjusted odds ratio [aOR] 0.48, 95% confidence intervals [CI] 0.24–0.95), recent emergency room visit (aOR 0.45, 95% CI 0.23–0.89), and recent injection drug use (aOR 0.41, 95% CI 0.19–0.88). Significant positive correlates were alternative use of other prescription opioids (aOR 8.32, 95% CI 4.22–16.38), three or more overdoses in the past year (aOR 3.74, 95% CI 1.53–9.17), recent buprenorphine use as prescribed (aOR 2.50, 95% CI 1.12–5.55), and recent residential rehabilitation treatment (aOR 3.71, 95% CI 1.50–9.16). Conclusions: Structural and behavioral correlates of AUB may help identify PWUD at high risk of overdose with unmet treatment needs.
Correlates of Alcohol Experimentation and Drunkenness Episodes among Secondary-School Students in Nigeria
Authors: Mehanović Emina , Virk Harsheth Kaur , Ibanga Akanidomo , Pwajok Juliet , Prichard Glen , van der Kreeft Peer , Vigna-Taglianti Federica ,   the Unplugged Nigeria Coordination Group
Published: July 2021

Background: Alcohol is the most used substance among adolescents in Nigeria. While risk factors for alcohol use among adolescents are well documented in Europe and the US, they have received less attention in the literature on African countries. This study aimed to investigate the factors associated with alcohol experimentation and drunkenness episodes in a national sample of Nigerian adolescents. Methods: A total sample of 4,078 secondary-school students participated in the survey during the school year 2015–2016. The survey involved 32 secondary schools of six geopolitical zones (South-South, South-West, South-East, North-Center, North-West, and North-East) and two metropolitan cities (Abuja and Lagos) of Nigeria. Sociodemographic characteristics, parental alcohol use and permissiveness, friends’ alcohol use, risk perceptions and beliefs were investigated as correlates of alcohol experimentation and drunkenness episodes through multilevel, mixed-effect logistic regression models. Results: The prevalence of alcohol experimentation was 34.0%, while the prevalence of drunkenness episodes was 13.4%. Results showed that male gender, family structure different from both parents’ families, parental and friends’ alcohol use, parental permissiveness to drink, low risk perceptions on drinking alcohol, and positive beliefs on consequences of alcohol use were associated with an increased probability of alcohol experimentation and drunkenness episodes. Family affluence and one-parent family structure were related to an increased probability of alcohol experimentation but not of drunkenness episodes. Conclusions: The majority of risk factors analyzed in this study generalize across drinking-behavior outcomes. Since the young population is dominant in Nigeria, alcohol use could become a big public health problem in the near future. High investment in adolescents’ well-being by addressing the factors that contribute to drinking behavior might help to reduce the burden of the problem. Evidence-based prevention curriculum addressing knowledge, risk perceptions, beliefs on consequences of alcohol use, and parental behaviors should be implemented as widely and early as possible.
The finiteness conjecture holds in

(SL2Z⩾0)2

*
Authors: Panti Giovanni , Sclosa Davide
Published: July 2021

Let A, B be matrices in

S
L

2

R

having trace greater than or equal to 2. Assume the pair A, B is coherently oriented, that is, can be conjugated to a pair having nonnegative entries. Assume also that either A, B
−1 is coherently oriented as well, or A, B have integer entries. Then the Lagarias–Wang finiteness conjecture holds for the set {A, B}, with optimal product in {A, B, AB, A
2
B, AB
2}. In particular, it holds for every pair of 2 × 2 matrices with nonnegative integer entries and determinant 1.
Complex mathematical model of the underwater robot operation
Authors: Borodavkin V A , Zazhigaev A V , Chirikov S A , Nilov A N
Published: July 2021

The article is devoted to a complex mathematical model of the functioning of an underwater robot that allows solving the problem of operational correction of a service task directly during its execution. The successful usage of UAV largely depends on the quality of preparation and programming of the UAV mission, including the current factors of the water environment. Since UAV works in an aquatic environment, the modeling of its functioning should be carried out taking into account both the environment itself and the dynamics of changes in its properties. The developed mathematical model was implemented in the form of a computer model and confirmed its operability within the declared ranges of initial conditions and initial data. The proposed complex mathematical model can be used for planning of assignments given available energy on board the UAV and allows to evaluate the energy for the operation of the on-board equipment after performing the UAV maneuver in the operating zone and the necessary reserves for the ascent of the unit, its detection and receiving aboard the carrier.
Classification analysis of analytical and probabilistic methods for predicting the state of complex systems
Authors: Brusnikin P M , Dudkin S O , Neretin E S
Published: July 2021

The paper considers a class of analytical forecasting methods, a class of probabilistic methods, and methods of artificial neural networks for solving the problem of predicting the state of complex systems on board an aircraft, such as: mathematical simulation, operator method, one-dimensional time series forecasting method, potential function method, zone method, and generalized point method.
The autonomous social robot control based on the situation analysis
Authors: Kim N V , Bodunkov N E
Published: July 2021

The problem of the autonomous task solution by the robotic system is considered in this paper. An approach based on the situational assessment and analysis is proposed for this. This approach makes it possible to plan the robot actions from the point of minimizing the situations informational uncertainty. The hirachical semantic descriptions of the target task, environment and the robot’s state were proposed. Within this approach the situational uncertainty in terms of informational entropy estimates. Each action, including planning, should be aimed to reduce entropy. An example of the proposed approach implementation for the object dellivery task was demonstrated. The efficiency ac the approach was shawn.
Mobile robot position assessment in the room with the use of on-board vision system
Authors: Udalova N V
Published: July 2021

The contemporary method of visual navigation of a mobile robot is presented. The visual navigation is an effective way to increase an accuracy of estimation for a current position of a mobile robot and its displacement. Using different specific features of a ceiling image along with photogrammetry theory permits to get a relative estimate for a current position of the mobile robot and its displacement in a room. Conventional approaches are ineffective because of presence of movable and immovable objects on the recognition scene. The ceiling image as the recognition scene is used in the proposed method. The recognition scene of ceiling is a stable and reliable image in the problem of finding reference points. Moreover there are no image distortions on the scene. All the mentioned above is a significant benefit of the proposed approach in terms of accuracy characteristics of the method of visual navigation of the mobile robot in the room.
Influence of surface damage and bulk defects on the interstrip isolation of p-type silicon strip sensors
Authors: Müller-Gosewisch J.-O. , Dierlamm A. , Nürnberg A.
Published: July 2021

Silicon strip sensors of upcoming tracking detectors in high
luminosity colliders usually consist of a p-doped bulk with n-type
strip implants. The general consensus is that such a design
requires an additional interstrip isolation structure such as a
p-stop implant. If there is no additional implant between the
strips, it is expected that the strip isolation will be
insufficient. Before irradiation, impurities and defects in the
material lead to positive charge in the oxide and Si/SiO_2
interface which attracts electrons from the bulk. Those electrons
accumulate just beneath the surface and between the n+ strip or
pixel implants, which decreases the interstrip resistance
significantly. Ionising radiation introduces even more charge
inside the silicon dioxide, which further decreases the interstrip
resistance. Contrary to that expectation of a decreasing interstrip
resistance due to irradiation, a high interstrip resistance was
sometimes observed after proton irradiation. Hence, bulk defects
induced by proton irradiation seem to have a non-negligible impact
on the strip isolation. Therefore, an irradiation campaign with
sensors without any interstrip isolation implant has been performed.
The use of sensors without isolation structures provides deeper
insight into the dominant isolation effects. The sensors'
performance is first evaluated before irradiation. Afterwards, a
set of sensors is irradiated with different particles in order to
systematically introduce a mixture of surface and bulk defects.
This enables the distinction and leads to a better understanding of
the different effects. Finally, a combined TCAD model is derived
which is able to describe the beneficial effect of bulk defects and
the complicated interplay between surface and bulk damage.
Changes in precipitation variability across time scales in multiple global climate model large ensembles
Authors: Wood Raul R , Lehner Flavio , Pendergrass Angeline G , Schlunegger Sarah
Published: July 2021

Anthropogenic changes in the variability of precipitation stand to impact both natural and human systems in profound ways. Precipitation variability encompasses not only extremes like droughts and floods, but also the spectrum of precipitation which populates the times between these extremes. Understanding the changes in precipitation variability alongside changes in mean and extreme precipitation is essential in unraveling the hydrological cycle’s response to warming. We use a suite of state-of-the-art climate models, with each model consisting of a single-model initial-condition large ensemble (SMILE), yielding at least 15 individual realizations of equally likely evolutions of future climate state for each climate model. The SMILE framework allows for increased precision in estimating the evolving distribution of precipitation, allowing for forced changes in precipitation variability to be compared across climate models. We show that the scaling rates of precipitation variability, the relation between the rise in global temperature and changes in precipitation variability, are markedly robust across timescales from interannual to decadal. Over mid- and high latitudes, it is very likely that precipitation is increasing across the entire spectrum from means to extremes, as is precipitation variability across all timescales, and seasonally these changes can be amplified. Model or structural uncertainty is a prevailing uncertainty especially over the Tropics and Subtropics. We uncover that model-based estimates of historical interannual precipitation variability are sensitive to the number of ensemble members used, with ‘small’ initial-condition ensembles (of less than 30 members) systematically underestimating precipitation variability, highlighting the utility of the SMILE framework for the representation of the full precipitation distribution.
The case for digital twins in metal additive manufacturing
Authors: Gunasegaram D R , Murphy A B , Matthews M J , DebRoy T
Published: July 2021

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).
Invited Commentary: Estimation and Bounds Under Data Fusion
Authors: Miao Wang , Li Wei , Hu Wenjie , Wang Ruoyu , Geng Zhi
Published: July 2021

In their recent article, Ogburn et al. (Am J Epidemiol. 2021;190(6):1142–1147) raised a cautionary tale for epidemiologic data fusion: Bias may occur if a variable that is completely missing in the primary data set is imputed according to a regression model estimated from an auxiliary data set. However, in some specific settings, a solution may exist. Focusing on a linear outcome regression model with a missing covariate, we show that the bias can be eliminated if the underlying imputation model for the missing covariate is nonlinear in the common variables measured in both data sets. Otherwise, we describe 2 alternative approaches existing in the data fusion literature that could partially resolve this issue: One fits the outcome model by leveraging an additional validation data set containing joint observations of the outcome and the missing covariate, and the other offers informative bounds for the outcome regression coefficients without using validation data. We justify these 3 methods in a linear outcome model and briefly discuss their extension to general settings.
Fully unsupervised deep mode of action learning for phenotyping high-content cellular images
Authors: Janssens Rens , Zhang Xian , Kauffmann Audrey , de Weck Antoine , Durand Eric Y
Published: July 2021

Motivation

The identification and discovery of phenotypes from high content screening images is a challenging task. Earlier works use image analysis pipelines to extract biological features, supervised training methods or generate features with neural networks pretrained on non-cellular images. We introduce a novel unsupervised deep learning algorithm to cluster cellular images with similar Mode-of-Action (MOA) together using only the images’ pixel intensity values as input. It corrects for batch effect during training. Importantly, our method does not require the extraction of cell candidates and works from the entire images directly.

Results

The method achieves competitive results on the labeled subset of the BBBC021 dataset with an accuracy of 97.09% for correctly classifying the MOA by nearest neighbors matching. Importantly, we can train our approach on unannotated datasets. Therefore, our method can discover novel MOAs and annotate unlabeled compounds. The ability to train end-to-end on the full resolution images makes our method easy to apply and allows it to further distinguish treatments by their effect on proliferation.

Availability and implementation

Our code is available at https://github.com/Novartis/UMM-Discovery.

Supplementary information

Supplementary data are available at Bioinformatics online.
Evidence and implications of abnormal predictive coding in dementia
Authors: Kocagoncu Ece , Klimovich-Gray Anastasia , Hughes Laura E , Rowe James B
Published: July 2021

The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of ‘memory centres’ or ‘language centres’, or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.