bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Review on Deep mixing method for soil improvement
Authors: Alhamdi Mohammed Khalil , Albusoda Bushra Suhale 
Published: July 2021

Abstract
Deep mixing method, the ideal choice that can be used to treat problems arising from the presence of soft clay soil as a basis for constructing a specific structure. Soft clay soil covers large areas in some countries around the world, making it difficult to find suitable places for construction. Soft clay soil which has a high moisture content that makes it with small shear resistance and high settlement capability is not suitable as a bearing layer under the foundations of the facilities, Therefore, the need arose to either the use of a certain type of foundation, such as deep foundations Which are more complicated compared to the second option, or the use a specific treatment technique to improve the properties of the soft clay soil and make it suitable for the construction with the using of a certain type of foundations other than deep foundations. One of the most suitable treatment techniques for soft clay soils in terms of structural purpose, cost and time is the deep mixing process. Deep soil mixing is a complex process in terms of factors that affect the improved soil quality and the processes that causing the improvement. This process has been covered in a lot of books and published researches in many of its aspects, but there is some of that relates to this process has not been significantly highlighted such as improved soil permanence over time, which causes a poor understanding of the behavior of improved soil after the improvement process. In this research paper, everything related to the deep mixing process will be touch upon, starting with the historical development of this process, its beginnings to its types, classifications and applications, and the accompanying chemical and physical processes, in addition to a literary review for what related to this process.
Effect of fine Aggregate Replacement with Dolomite powder on GFRC Mechanical Properties
Authors: Manikandan P , Dhivya S , Poornima S , Mahesh Raj M , Prabhu C , Keerthivasan R 
Published: July 2021

Abstract
Portland cement, sand, water, acrylic copolymer, alkali resistant glass fibre reinforcement (GFR), and additives make up Glass Fiber Reinforced Concrete (GFRC). Dolomite is a calcium magnesium carbonate anhydrous carbonate mineral. The aim of this study is to find the flexural strength of the concrete, split tensile of beam, and compressive strength of Glass Fibre Reinforced Concrete (GFRC) with Dolomite Waste used as the partial sand (fine aggregate) substitute. In this direction, an investigation of strength was conducted to find the use of dolomite as a partial (10%, 20%, 30%, 40%, 50%, and 60%) substitute for fine aggregate in GFRC. The M25 grade of concrete was subjected to hardened concrete tests at the ages of seven and twenty-eight days. The findings of the tests are compared to those of standard concrete.
Minimization of Hiring cost for n-Jobs, 2-Machines Flow Shop Scheduling: Processing Time Associated with Probabilities with Transportation Time including Break down interval
Authors: Gupta Deepak , Sehgal Poojadeep 
Published: July 2021

Abstract
This paper examines a heuristic programmed algorithm for the problem of two-stage flow shop scheduling in which the time to process their respective probabilities and to minimize the cost of hiring machines under a given rental policy. Furthermore, it takes into account the transfer time from one device to another system. The algorithm is very easy to understand and also offers an significant technique for decision-making.
A microfabricated ion trap chip with a sloped loading slot to minimize exposing trapped ions to stray charges
Authors: Jung Changhyun , Lee Woojun , Jeong Junho , Lee Minjae , Park Yunjae , Kim Taehyun , "Dan" Cho Dong-II 
Published: July 2021

Abstract
A novel microfabricated ion trap chip that can geometrically minimize exposing trapped ions to stray charges on dielectric surfaces is developed. The new design utilizes a sloped loading slot to make the dielectric layers of the loading slot sidewalls invisible to the trapped ions. The designed loading slot is realized by applying silicon anisotropic etching processes, and the ion trap chip that contains the sloped loading slot is fabricated using microelectromechanical system processes. Stray charges induced by injecting an ultraviolet laser on the surface of the fabricated ion trap chip are experimentally characterized by measuring stray electric fields at the location of the trapped ions. The measured results are compared to those of a previous ion trap chip with a vertical loading slot. The magnitude of the measured stray electric field in the axial direction is within 1.5 V m−1 for the proposed ion trap chip, whereas it is approximately 10 V m−1 for the previously reported ion trap chip.
Interfacial informatics
Authors: Fischer Julia M , Parker Amanda J , Barnard Amanda S 
Published: July 2021

Abstract
Using machine learning methods to analyse and predict events occurring at interfaces is more complicated than applying machine learning to participating entities, such as adsorbates and adsorbents separately. Whether combining molecular or materials descriptors, or explicitly defining the topology of the space in between, the choice of features is critical to successfully understanding the potential energy surface that determines the probability of events, or the importance of unique characteristics that can guide decision making. If reliably defined these descriptors can be used in advanced machine learning methods to model dynamics, co-adsorption and interfacial evolution based on complex data; an area traditionally reserved for molecular dynamics or kinetic Monte Carlo. In this perspective, we provide some insights into how interactions and interfaces can be more effectively described and introduce some relevant machine learning methods that go beyond the unsupervised pattern recognition or supervised classification and regression currently preferred by the community.
Confession of a causal decision theorist
Authors: Elga Adam 
Published: July 2021

Abstract
(1) Suppose that you care only about speaking the truth, and are confident that some particular deterministic theory is true. If someone asks you whether that theory is true, are you rationally required to answer ‘yes’? (2) Suppose that you face a problem in which (as in Newcomb's problem) one of your options – call it ‘taking two boxes’ – causally dominates your only other option. Are you rationally required to take two boxes? Those of us attracted to causal decision theory are under pressure to answer ‘yes’ to both questions. However, it has been shown that many existing decision theories are inconsistent with doing so (Ahmed 2014). A simple proof shows that the same goes for an even wider class of theories: all ‘suppositional’ decision theories. The moral is that causal decision theorists must either answer ‘no’ to one of the above questions, or else abandon suppositional decision theories.
Animal Allergens, Endotoxin, and β-(1,3)-Glucan in Small Animal Practices: Exposure Levels at Work and in Homes of Veterinary Staff
Authors: Zahradnik Eva , Sander Ingrid , Kleinmüller Olaf , Lotz Anne , Liebers Verena , Janssen-Weets Bente , Kler Stéphanie , Hilger Christiane , Beine Alexandra , Hoffmeyer Frank , Nienhaus Albert , Raulf Monika 
Published: July 2021

Abstract

Objectives
In veterinary settings, high exposures to animal allergens and microbial agents can be expected. However, occupational exposure levels are largely unknown. The objective of this study was to estimate the allergen, endotoxin, and β-(1,3)-glucan concentrations in small animal practices and in the homes of practice employees.

Methods
Dust samples were collected using electrostatic dust fall collectors in diverse rooms of 36 small animal practices, as well as in employees’ homes. Major animal allergens (Fel d 1, Can f 1, Ory c 3, Cav p 1, Equ c 1, Bos d 2), domestic mite (DM) allergens, and β-(1,3)-glucan levels were measured using enzyme immunoassays. Endotoxin was determined using the Limulus amoebocyte lysate assay. Influences on exposure levels were analyzed using multilevel models.

Results
The levels of Can f 1, Fel d 1, Ory c 3, and Cav p 1 were up to 30 times higher in practices compared with homes without animals, but significantly lower compared with the homes with the respective pet. Although horses were not treated in the practices, Equ c 1 was found in 87.5% of samples, with the highest concentrations measured in changing rooms. DM levels were significantly lower in practices than in all private homes, and endotoxin levels were similar to those in homes with pets. In the practice itself, exposure levels were significantly influenced by animal presence, type of the room, and area per employee; whereas, room volume and diverse cleaning measures had mostly no effect.

Conclusions
Exposure to animal allergens is high in veterinary practices, but it does not reach levels of households with pets. Domestic mite allergen and endotoxin exposure seem to be low for workers in veterinary practices. The high Equ c 1 detection rate strongly indicates dispersal of allergens, most likely through clothing and hair.
Recognizing binding sites of poorly characterized RNA-binding proteins on circular RNAs using attention Siamese network
Authors: Wu Hehe , Pan Xiaoyong , Yang Yang , Shen Hong-Bin 
Published: July 2021

Abstract
Circular RNAs (circRNAs) interact with RNA-binding proteins (RBPs) to play crucial roles in gene regulation and disease development. Computational approaches have attracted much attention to quickly predict highly potential RBP binding sites on circRNAs using the sequence or structure statistical binding knowledge. Deep learning is one of the popular learning models in this area but usually requires a lot of labeled training data. It would perform unsatisfactorily for the less characterized RBPs with a limited number of known target circRNAs. How to improve the prediction performance for such small-size labeled characterized RBPs is a challenging task for deep learning–based models. In this study, we propose an RBP-specific method iDeepC for predicting RBP binding sites on circRNAs from sequences. It adopts a Siamese neural network consisting of a lightweight attention module and a metric module. We have found that Siamese neural network effectively enhances the network capability of capturing mutual information between circRNAs with pairwise metric learning. To further deal with the small-sample size problem, we have performed the pretraining using available labeled data from other RBPs and also demonstrate the efficacy of this transfer-learning pipeline. We comprehensively evaluated iDeepC on the benchmark datasets of RBP-binding circRNAs, and the results suggest iDeepC achieving promising results on the poorly characterized RBPs. The source code is available at https://github.com/hehew321/iDeepC.
Medical concept normalization in clinical trials with drug and disease representation learning
Authors: Miftahutdinov Zulfat , Kadurin Artur , Kudrin Roman , Tutubalina Elena 
Published: July 2021

Abstract

Motivation
Clinical trials are the essential stage of every drug development program for the treatment to become available to patients. Despite the importance of well-structured clinical trial databases and their tremendous value for drug discovery and development such instances are very rare. Presently large-scale information on clinical trials is stored in clinical trial registers which are relatively structured, but the mappings to external databases of drugs and diseases are increasingly lacking. The precise production of such links would enable us to interrogate richer harmonized datasets for invaluable insights.

Results
We present a neural approach for medical concept normalization of diseases and drugs. Our two-stage approach is based on Bidirectional Encoder Representations from Transformers (BERT). In the training stage, we optimize the relative similarity of mentions and concept names from a terminology via triplet loss. In the inference stage, we obtain the closest concept name representation in a common embedding space to a given mention representation. We performed a set of experiments on a dataset of abstracts and a real-world dataset of trial records with interventions and conditions mapped to drug and disease terminologies. The latter includes mentions associated with one or more concepts (in-KB) or zero (out-of-KB, nil prediction). Experiments show that our approach significantly outperforms baseline and state-of-the-art architectures. Moreover, we demonstrate that our approach is effective in knowledge transfer from the scientific literature to clinical trial data.

Availability and implementation
We make code and data freely available at https://github.com/insilicomedicine/DILBERT.
tRNA-derived fragment tRFLys-CTT-010 promotes triple-negative breast cancer progression by regulating glucose metabolism via G6PC
Authors: Zhu Ping , Lu Jingjing , Zhi Xiuling , Zhou Yue , Wang Xue , Wang Chaofu , Gao Yabiao , Zhang Xiufen , Yu Jerry , Sun Yangbai , Zhou Ping 
Published: July 2021

Abstract
tRNA-derived fragments (tRFs) are a novel class of small non-coding RNAs whose biological roles are not well defined. Here, using multiple approaches, we investigated its role in human triple-negative breast cancer (TNBC). Our genome-wide transcriptome analysis of small non-coding RNAs revealed that tRFLys-CTT-010 was significantly increased in human TNBC. It promoted TNBC proliferation and migration. It also closely associated with starch and sucrose metabolism pathways (Kyoto Encyclopedia of Genes and Genomes analysis) and positively regulated the expression of glucose-6-phosphatase catalytic subunit (G6PC), one of the related genes in the pathway. G6PC, a complex of glucose-6-phosphatase in gluconeogenesis and glycogenolysis, is upregulated in human TNBC samples. Further studies demonstrated that overexpression of G6PC in tRFLys-CTT-010 inhibitor-transfected TNBC cell lines can reverse malignant biological behavior and knockdown of G6PC in TNBC cell lines inhibited tumor progression and reversed the oncogenic function of tRFLys-CTT-010. In addition, tRFLys-CTT-010 interacted with G6PC to regulate cellular lactate production and glycogen consumption, resulting in cell survival and proliferation. Thus, fine-tuning glucose metabolism and the tRFLys-CTT-010/G6PC axis may provide a therapeutic target for TNBC treatment.
Adaptation of the Corticomuscular and Biomechanical Systems of Pianists
Authors: Kimoto Yudai , Hirano Masato , Furuya Shinichi 
Published: July 2021

AbstractIndependent control of movements between the fingers plays a role in hand dexterity characterizing skilled individuals. However, it remains unknown whether and in what manner neuromuscular and biomechanical constraints on the movement independence of the fingers depend on motor expertise. Here, we compared motor dexterity, corticospinal excitability of multiple muscles, muscular activation, and anatomical features of the fingers between the pianists and nonpianists. When the ring finger was passively moved by a robot, passive motions produced at the adjacent fingers were smaller for the pianists than the nonpianists, indicating reduced biomechanical constraint of fingers in the pianists. In contrast, when the ring finger moved actively, we found no group difference in passive motions produced at the adjacent fingers; however, reduced inhibition of corticospinal excitability of the adjacent fingers in the pianists compared with the nonpianists. This suggests strengthened neuromuscular coupling between the fingers of the pianists, enhancing the production of coordinated finger movements. These group differences were not evident during the index and little finger movements. Together, pianists show expertise-dependent biomechanical and neurophysiological adaptations, specifically at the finger with innately low movement independence. Such contrasting adaptations of pianists may subserve dexterous control of both the individuated and coordinated finger movements.
Cytomegalovirus Viremia and Clinical Outcomes in Kenyan Children Diagnosed With Human Immunodeficiency Virus (HIV) in Hospital
Authors: Wamalwa Dalton , Njuguna Irene , Maleche-Obimbo Elizabeth , Begnel Emily , Chebet Daisy J , Onyango Judith A , Cranmer Lisa Marie , Huang Meei-Li , Richardson Barbra A , Boeckh Michael , John-Stewart Grace , Slyker Jennifer 
Published: July 2021

Abstract

Background
Cytomegalovirus (CMV) viremia is common in human immunodeficiency virus (HIV) infection and is associated with worse long-term outcomes. To date, no studies have assessed CMV viremia in children diagnosed with HIV in hospital.

Methods
We studied CMV viremia and clinical outcomes in 163 Kenyan children aged 2 months to 12 years, diagnosed with HIV in hospital. CMV DNA levels in plasma were measured using quantitative polymerase chain reaction (PCR). Regression models were used to assess associations between CMV viremia ≥1000 IU/mL and the risk of continued hospitalization or death at 15 days, duration of hospitalization, and 6-month mortality.

Results
At enrollment, 62/114 (54%) children had CMV viremia, and 20 (32%) were ≥1000 IU/mL. Eleven CMV reactivations were observed after admission. The prevalence and level of CMV viremia were highest in children &lt;2 years and lowest in children ≥5 years old. CMV viremia ≥1000 IU/mL was independently associated with age &lt;2 years (P = .03), higher log10 HIV RNA level (P = .01), and height-for-age z score &gt;−2 (P = .02). Adjusting for age and log10 HIV RNA, the relative risk of death or continued hospitalization at 15 days was 1.74 (95% confidence interval [CI] = 1.04, 2.90), and the hazard ratio of 6-month mortality was 1.97 (95% CI = .57, 5.07) for children with CMV DNA ≥1000 IU/mL compared to lower-level or undetectable CMV DNA. Children with CMV DNA ≥1000 IU/mL were hospitalized a median ~5 days longer than children with lower-level or undetectable CMV DNA (P = .002).

Conclusions
In this nested observational study, CMV viremia was common in hospitalized children with HIV, and levels ≥1000 IU/mL were associated with increased risk of mortality and longer hospitalization.
Persistent Symptoms in Adult Patients 1 Year After Coronavirus Disease 2019 (COVID-19): A Prospective Cohort Study
Authors: Seeßle Jessica , Waterboer Tim , Hippchen Theresa , Simon Julia , Kirchner Marietta , Lim Adeline , Müller Barbara , Merle Uta 
Published: July 2021

AbstractBackgroundLong COVID is defined as the persistence of symptoms beyond 3 months after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To better understand the long-term course and etiology of symptoms we analyzed a cohort of patients with COVID-19 prospectively.MethodsPatients were included at 5 months after acute COVID-19 in this prospective, noninterventional, follow-up study. Patients followed until 12 months after COVID-19 symptom onset (n = 96; 32.3% hospitalized, 55.2% females) were included in this analysis of symptoms, quality of life (based on an SF-12 survey), laboratory parameters including antinuclear antibodies (ANAs), and SARS-CoV-2 antibody levels.ResultsAt month 12, only 22.9% of patients were completely free of symptoms and the most frequent symptoms were reduced exercise capacity (56.3%), fatigue (53.1%), dyspnea (37.5%), and problems with concentration (39.6%), finding words (32.3%), and sleeping (26.0%). Females showed significantly more neurocognitive symptoms than males. ANA titers were ≥1:160 in 43.6% of patients at 12 months post–COVID-19 symptom onset, and neurocognitive symptom frequency was significantly higher in the group with an ANA titer ≥1:160 versus &lt;1:160. Compared with patients without symptoms, patients with ≥1 long-COVID symptom at 12 months did not differ significantly with respect to their SARS-CoV-2 antibody levels but had a significantly reduced physical and mental life quality compared with patients without symptoms.ConclusionsNeurocognitive long-COVID symptoms can persist ≥1 year after COVID-19 symptom onset and reduce life quality significantly. Several neurocognitive symptoms were associated with ANA titer elevations. This may indicate autoimmunity as a cofactor in etiology of long COVID.
SwabExpress: An End-to-End Protocol for Extraction-Free COVID-19 Testing
Authors: Srivatsan Sanjay , Heidl Sarah , Pfau Brian , Martin Beth K , Han Peter D , Zhong Weizhi , van Raay Katrina , McDermot Evan , Opsahl Jordan , Gamboa Luis , Smith Nahum , Truong Melissa , Cho Shari , Barrow Kaitlyn A , Rich Lucille M , Stone Jeremy , Wolf Caitlin R , McCulloch Denise J , Kim Ashley E , Brandstetter Elisabeth , Sohlberg Sarah L , Ilcisin Misja , Geyer Rachel E , Chen Wei , Gehring Jase ,   Seattle Flu Study Investigators, Chu Helen Y , Boeckh Michael , Englund Janet A , Famulare Michael , Lockwood Christina M , Lutz Barry R , Nickerson Deborah A , Rieder Mark J , Starita Lea M , Thompson Matthew , Viboud Cécile , Shendure Jay , Bedford Trevor , Kosuri Sriram , Bedford Trevor , Rieder Mark J , Nickerson Deborah A , Chu Helen Y , Konnick Eric Q , Debley Jason S , Shendure Jay , Lockwood Christina M , Starita Lea M 
Published: July 2021

Abstract

Background
The urgent need for massively scaled clinical testing for SARS-CoV-2, along with global shortages of critical reagents and supplies, has necessitated development of streamlined laboratory testing protocols. Conventional nucleic acid testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab in transport medium, nucleic acid extraction, and quantitative reverse-transcription PCR (RT–qPCR). As testing has scaled across the world, the global supply chain has buckled, rendering testing reagents and materials scarce. To address shortages, we developed SwabExpress, an end-to-end protocol developed to employ mass produced anterior nares swabs and bypass the requirement for transport media and nucleic acid extraction.

Methods
We evaluated anterior nares swabs, transported dry and eluted in low-TE buffer as a direct-to-RT–qPCR alternative to extraction-dependent viral transport media. We validated our protocol of using heat treatment for viral inactivation and added a proteinase K digestion step to reduce amplification interference. We tested this protocol across archived and prospectively collected swab specimens to fine-tune test performance.

Results
After optimization, SwabExpress has a low limit of detection at 2–4 molecules/µL, 100% sensitivity, and 99.4% specificity when compared side by side with a traditional RT–qPCR protocol employing extraction. On real-world specimens, SwabExpress outperforms an automated extraction system while simultaneously reducing cost and hands-on time.

Conclusion
SwabExpress is a simplified workflow that facilitates scaled testing for COVID-19 without sacrificing test performance. It may serve as a template for the simplification of PCR-based clinical laboratory tests, particularly in times of critical shortages during pandemics.