Miracle-dz/UniFAR-FTUs huggingface dataset:
Ignorance is bliss: Or seven reasons not to use uncertainty analysis

Uncertainty analysis of models has received increasing attention over the last two decades in water resources research. However, a significant part of the community is still reluctant to embrace the estimation of uncertainty in hydrological and hydraulic modeling. In this paper, we summarize and explore seven common arguments: uncertainty analysis is not necessary given physically realistic models; uncertainty analysis cannot be used in hydrological and hydraulic hypothesis testing; uncertainty (probability) distributions cannot be understood by policy makers and the public; uncertainty analysis cannot be incorporated into the decision‐making process; uncertainty analysis is too subjective; uncertainty analysis is too difficult to perform; uncertainty does not really matter in making the final decision. We will argue that none of the arguments against uncertainty analysis rehearsed are, in the end, tenable. Moreover, we suggest that one reason why the application of uncertainty analysis is not normal and expected part of modeling practice is that mature guidance on methods and applications does not exist. The paper concludes with suggesting that a Code of Practice is needed as a way of formalizing such guidance.
Global Transmission of Returns among Financial, Traditional Energy, Renewable Energy and Carbon Markets: New Evidence

Connections to world markets facilitate local markets developments to support more efficient capital allocation and greater investment and growth opportunities. Under the framework of cross-market rebalancing theory, in this study, we aim to systematically examine the market connections among world financial, energy, renewable energy and European carbon markets by measuring the return spillovers from 2008 to 2021. We find that the renewable energy market is more closely connected to the world financial and energy markets in the sense of the return transmission, while the carbon market is less connected to them. However, due to improved market regulations and determinations related to fighting climate change, the connections between the carbon market and other markets have gradually intensified. Plotting the return spillover indexes, we observe that strong return spillovers from the renewable energy market to other markets occurred when large investment plans were announced. Regarding the carbon market, regulation changes introduced by the EU Commission to improve and stabilize market environment induced intensified return transmission from carbon market to other markets. Another interesting finding is that the highly intensified return transmission among markets due to the COVID-19 crisis started to loosen when COVAX published the first interim distribution forecast on 3 February 2021.
Evaluation of the Cross-Protective Efficacy of a Chimeric PRRSV Vaccine against Two Genetically Diverse PRRSV2 Field Strains in a Reproductive Model

Despite the routine use of porcine reproductive and respiratory syndrome (PRRS)-modified live vaccines, serious concerns are currently being raised due to their quick reversion to virulence and limited cross-protection against divergent PRRS virus (PRRSV) strains circulating in the field. Therefore, a PRRS chimeric vaccine (JB1) was produced using a DNA-launched infectious clone by replacing open reading frames (ORFs) 3–6 with those from a mixture of two genetically different PRRSV2 strains (K07–2273 and K08–1054) and ORF1a with that from a mutation-resistant PRRSV strain (RVRp22) exhibiting an attenuated phenotype. To evaluate the safety and cross-protective efficacy of JB1 in a reproductive model, eight PRRS-negative pregnant sows were purchased and divided into four groups. Four sows in two of the groups were vaccinated with JB1, and the other 4 sows were untreated at gestational day 60. At gestational day 93, one vaccinated group and one nonvaccinated group each were challenged with either K07–2273 or K08–1054. All of the sows aborted or delivered until gestation day 115 (24 days post challenge), and the newborn piglets were observed up to the 28th day after birth, which was the end of the experiment. Overall, pregnant sows of the JB1-vaccinated groups showed no meaningful viremia after vaccination and significant reductions in viremia with K07–2273 and K08–1054, exhibiting significantly higher levels of serum virus-neutralizing antibodies than non-vaccinated sows. Moreover, the JB1-vaccinated groups did not exhibit any abortion due to vaccination and showed improved piglet viability and birth weight. The piglets from JB1-vaccinated sows displayed lower viral concentrations in serum and fewer lung lesions compared with those of the piglets from the nonvaccinated sows. Therefore, JB1 is a safe and effective vaccine candidate that confers simultaneous protection against two genetically different PRRSV strains.
Information dissemination during the COVID-19 pandemic: The role of librarians in Borno State Public Library

This study investigated information dissemination need in the era of COVID-19 pandemic taking into cognizance the role of librarians in Borno State public library. Three research questions were raised. This study adopted a descriptive survey research design. It was found that librarians’ roles included advising the public on how to avoid misinformation; highlighting the importance of social distancing; giving general instructions to library users on the use of face masks, handwashing and use of sanitizers; enlightening library users to avoid handshakes in or outside the library. Public libraries in Borno State can support researchers by drawing attention to the latest developments regarding vaccination; drawing relevant studies published in medical journals; providing free access to the latest literature on coronavirus. Based on this finding, it was recommended that librarians should disseminate information via existing and digital media platforms to educate users.
Methodology for achieving GASB 34 modified approach compliance using U.S. Navy "Smart Base" facility management practices

Abstract : Historically, local infrastructure assets have been overlooked and under-funded, viewed more often as sunk costs than as strategic assets. While the growth of enterprise software solutions for asset management has begun to change this, the high cost and complexity of such systems has primarily limited their implementation to large government agencies and major cities. With the creation of its Statement 34 requirements, the Government Accounting Standards Board (GASB) seeks to improve the tracking, management and reporting of infrastructure assets by smaller cities and towns. Due to phase in between 2001 and 2003, depending on annual revenue levels, GASB 34 has forced a renewed focus on infrastructure portfolios at the local level. This research develops a strategy and methodology for small local governments to create flexible, cost effective asset management systems. Faced with the management of a global infrastructure portfolio exceeding $130 billion in 2001, the U.S. Navy has invested heavily in the area of public works management. The Smart Base project at Naval Shipyard Portsmouth, an ongoing initiative to develop customized information technology solutions at the installation level, is examined as a model for small towns to emulate during the development of GASB 34 compliant asset management systems. The resultant methodology provides a simple, robust framework for the integration of inventory, condition and valuation data within the existing GIS system used by the town of Winchester, Massachusetts.
Ad-hoc platoon formation and dissolution strategies for multi-lane highways

Abstract Vehicle platooning, a coordinated and controlled vehicle-following strategy, addresses the issue of high fuel consumption of heavy-duty vehicles. This research considers platoons that are formed on the fly in an ad-hoc manner. We investigate two types of ad-hoc platoon formation and corresponding platoon dissolution strategies. The first approach forms a platoon greedily without considering the order of destinations of the platoon members. This approach enables a quick formation but imposes an overhead of platoon rebuilding, and consequently, additional fuel cost when platoon members leave. An alternative approach forms a platoon in the order of the destinations of its platoon members. This ordered approach incurs a comparatively higher formation time due to vehicles’ reorganization but does not lead to further overhead of platoon rebuilding. We investigate whether these ad-hoc formation and dissolution strategies can preserve the original fuel benefit of platooning, and which of the two ad-hoc formation strategies are more fuel-efficient. The experimental results show that the greedy formation of the platoon is more fuel-efficient for a multi-lane highway. The proposed prediction model provides 90.4% prediction accuracy for the greedy approach and 82.2% prediction accuracy for the ordered approach on average, for platoon sizes from two to six vehicles.
Electroacupuncture for Temporomandibular Disorders: A Systematic Review of Randomized Controlled Trials

Although electroacupuncture (EA) is an effective treatment for pain relief, there has been no systematic review of EA treatment for temporomandibular disorder TMD. This systematic review aimed to evaluate the efficacy and safety of EA in TMD management. We searched 14 databases until April 2021 for randomized controlled trials (RCTs) evaluating the effects of EA on TMDs. Eleven RCTs with 667 patients that used three acupuncture points (ST6, ST7, and LI4) were included. Two RCTs reported significant effects of EA plus microwave treatment compared with EA treatment alone on the total effectiveness rate (TER) for TMD. Further, two studies reported that compared with ultrashort wave alone, EA plus ultrashort wave had a significant effect on the TER for TMD and visual analog scale. All RCTs did not report adverse events. Our findings demonstrated the positive potential of EA in TMD management. However, there was weak evidence regarding EA use for TMD management given the poor quality and small sample sizes of the included studies. In the future, well-designed RCTs are required. It is necessary to investigate clinical trials and systematic reviews to compare the effectiveness and safety of EA and acupuncture for TMD.
Leveraging biochemical reactions to unravel functional impacts of cancer somatic variants affecting protein interaction interfaces

Background: Considering protein mutations in their biological context is essential for understanding their functional impact, interpretation of high-dimensional datasets and development of effective targeted therapies in personalized medicine. Methods: We combined the curated knowledge of biochemical reactions from Reactome with the analysis of interaction-mediating 3D interfaces from Mechismo. In addition, we provided a software tool for users to explore and browse the analysis results in a multi-scale perspective starting from pathways and reactions to protein-protein interactions and protein 3D structures. Results: We analyzed somatic mutations from TCGA, revealing several significantly impacted reactions and pathways in specific cancer types. We found examples of genes not yet listed as oncodrivers, whose rare mutations were predicted to affect cancer processes similarly to known oncodrivers. Some identified processes lack any known oncodrivers, which suggests potentially new cancer-related processes (e.g. complement cascade reactions). Furthermore, we found that mutations perturbing certain processes are significantly associated with distinct phenotypes (i.e. survival time) in specific cancer types (e.g. PIK3CA centered pathways in LGG and UCEC cancer types), suggesting the translational potential of our approach for patient stratification. Our analysis also uncovered several druggable processes (e.g. GPCR signalling pathways) containing enriched reactions, providing support for new off-label therapeutic options. Conclusions: In summary, we have established a multi-scale approach to study genetic variants based on protein-protein interaction 3D structures. Our approach is different from previously published studies in its focus on biochemical reactions and can be applied to other data types (e.g. post-translational modifications) collected for many types of disease.
Improving Disaster Risk Management According to Development Projects

Since the 1990s, efforts have been made to reduce the damage caused by natural disasters, among which the Disaster Impact Assessment (DIA) System implemented in 1995 is noteworthy for its proactive response. The DIA System has undergone various institutional and technological changes to retain its original purpose. However, its operation has become inadequate because of the diversification of business types. This paper presents the improvements required in the DIA System based on an analysis of the problems that have emerged during its institutional development and over 9000 pieces of data collected from 2015 to 2017. The results show that, first, the DIA’s Practical Guidelines should be subdivided, considering the diversity of projects. Second, the system should be strengthened to ensure it is not mistaken for a mere bureaucratic box-ticking exercise. Third, non-structural measures should be expanded to reduce the number of casualties after development. Incorporating the improvements proposed in this study will improve the effectiveness of the DIA. Additionally, the DIA System could be established as an important model for Korea’s disaster risk reduction activities.
EVs mass adoption in Colombia — A first approach model

In Colombia, the electrification of the transportation sector has become an interesting possibility to consider in order to reduce pollution, global warming and promote efficient vehicles. Currently, most vehicles run on an internal combustion engine (ICE). However, the introduction of electric vehicles (EVs) raises questions regarding the impact of these alternative technologies on: users' driving patterns, the mobility of cities, energy consumption, environmental impact, the energy distribution network, comfort conditions and adaptation to new ranges and speeds. Therefore, given their limitations, it is necessary to know the potential that the EVs technologies have in order to be properly adopted by users. This paper describes the application of a statistical prediction model, which determines the EVs technology that is most likely to be adopted in the city of Bogota, Colombia.
GPR Environmental-Based Landmine Automatic Detection

According to the United Nations, as of the year 2000 there were 70 million landmines planted in a third of the world’s nations affecting global causality rate of up to 20,000/year, (Anderson, 2002). That is why landmine detection has attracted much attention by many research teams around the world during the last two decades; among them is our research team in Nagoya University. Anti-personnel (AP) mine ranges from 5 to 15 cm in size; they can be metal, plastic, or wood. AP mines are normally buried at shallow depth; detonated by very low pressure, and designated to kill or maim people. PMN2, Type72 and PMN are examples, Fig. 1. In real world clearance activities, AP mine suspect areas are divided into 1 m grid squares, and each square meter is probed with a bayonet or plastic rod. Probing is done at an oblique angle to the ground so that the rod will encounter the side of a land mine and not trip the fuse. No need to say, this work is very dangerous and proceeds very slow, (Siegel, 2002). The need for a safer and more fast humanitarian demining action by replacing a manual sensing task by vehicle sensing task have motivated our research team to introduce a low-ground-pressure tires detection vehicle, (Hasegawa et al, 2004-A). The unmanned vehicle that can move in mine field without detonating a group of AP mines will be presented in this chapter. One of the big challenges in demining process is detection. If a mine is detected, deminers can explode, mark or move it to a pit for later detonation or defusing. Conventional mine detection, by a metal detector, is often difficult for two reasons. First, mines are increasingly being made of plastics, minimizing the more easily detectable metal components. Second, mined areas are often equipped with metal scraps creating a high false alarm rate. Because of the difficulty encountered in detecting the tiny amounts of metal in a plastic landmine with a metal detector, technology development has been extended to other sensors. Ground penetrating radar (GPR) used for about 70 years for a variety of geophysical subsurface imaging applications including utility mapping and hazardous waste container has been actively applied to the problem of land mine detection for nearly the last two decades of research. It provides sensing objects underground based on dielectric properties. It senses the reflected electromagnetic wave by a buried object. It is expected that GPR be a good alternative sensor and/or an important support sensor when fused with a metal detector for
Accelerated Discovery of Single‐Atom Catalysts for Nitrogen Fixation via Machine Learning

Developing high‐performance catalysts using traditional trial‐and‐error methods is generally time consuming and inefficient. Here, by combining machine learning techniques and first‐principle calculations, we are able to discover novel graphene‐supported single‐atom catalysts for nitrogen reduction reaction in a rapid way. Successfully, 45 promising catalysts with highly efficient catalytic performance are screened out from 1626 candidates. Furthermore, based on the optimal feature sets, new catalytic descriptors are constructed via symbolic regression, which can be directly used to predict single‐atom catalysts with good accuracy and good generalizability. This study not only provides dozens of promising catalysts and new descriptors for nitrogen reduction reaction but also offers a potential way for rapid screening of new electrocatalysts.
A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.
SCALPEL VERSUS DIODE LASER FOR GINGIVAL DEPIGMENTATION: A CASE REPORT

Gingival hyperpigmentation is believed to be a genetic trait in populations and is more appropriately termed physiologic or racial gingival pigmentation a condition, which affects all races differently. Gingival depigmentation is most frequently performed as an esthetic periodontal plastic surgical procedure. There are various procedures like scalpel, laser. Cryosurgery, diamond burs and chemical methods have been used in this procedure. This case report compares the efficacy of two techniques. Maxillary anterior region was treated with scalpel technique and the mandibular anterior region was treated using Diode Laser. Both the treatment modalities were effective in terms of patient acceptance. Scalpel depigmentation resulted in uneventful healing of the treated site. Laser depigmentation showed some beneficial effects like bloodless field during surgical procedure which healed uneventfully. Patient discomfort was more in laser treated site during the initial healing period as compared to scalpel.
Multilineage plasticity in prostate cancer through expansion of stem–like luminal epithelial cells with elevated inflammatory signaling

Lineage plasticity is a well–established mechanism of resistance to targeted therapies in lung and prostate cancer, where tumors transition from adenocarcinoma to small–cell or neuroendocrine carcinoma. Through single–cell analysis of a cohort of heavily–treated castration–resistant human prostate cancers (CRPC), we report a greater degree of plasticity than previously appreciated, with multiple distinct neuroendocrine (NEPC), mesenchymal (EMT–like), and other subpopulations detected within single biopsies. To explore the steps leading to this plasticity, we turned to two genetically engineered mouse models of prostate cancer that recapitulate progression from adenocarcinoma to neuroendocrine disease. Time course studies reveal expansion of stem–like luminal epithelial cells (Sca1+, Psca+, called L2) that, based on trajectories, gave rise to at least 4 distinct subpopulations, NEPC (Ascl1+), POU2F3 (Pou2f3+), TFF3 (Tff3+) and EMT–like (Vim+, Ncam1+)––these populations are also seen in human prostate and small cell lung cancers. Transformed L2–like cells express stem–like and gastrointestinal endoderm–like transcriptional programs, indicative of reemerging developmental plasticity programs, as well as elevated Jak/Stat and interferon pathway signaling. In sum, while the magnitude of multilineage heterogeneity, both within and across patients, raises considerable treatment challenges, the identification of highly plastic luminal cells as the likely source of this heterogeneity provides a target for more focused therapeutic intervention. One Sentence Summary Multilineage plasticity results from expansion of stem–like luminal cells with JAK/STAT activation, serving as a therapeutic target.
Multiagent evacuation framework for a virtual fire emergency scenario based on generative adversarial imitation learning

One of the most common solutions for the prevention of fire accidents is to conduct extensive fire evacuation drills in crowded places. However, there are multiple salient advantages to using virtual reality technology to simulate emergency solutions, for instance, saving costs and greatly decreasing uncertain risks or accidents. Therefore, in this article, a multiagent evacuation framework for complex virtual fire scenarios is proposed and effectively used to simulate a multiagent evacuation procedure to approximate the goal of fire drills in a less costly manner. Specifically, the concept of a multihierarchy agent group model is proposed; that is, the evacuation of multiple agents is separated into leader‐follower and freedom modes. Additionally, several complex actions of individual humans in actual fire drills are fully considered, and a multiaction agent schema is presented to characterize the associated real effects. In addition, generative adversarial imitation learning is adopted to obtain the evacuation path of the leader‐agent by training numerous learning epochs. Finally, extensive experiments are conducted to validate the feasibility of our proposed method. The results show that the proposed method is superior to other methods and that it realistically and reasonably shows the procedure of multiagent evacuation in complex fire emergency scenarios.