scholarly journals All Hands on Deck: Accelerating Ab Initio Thermochemistry via Wavefunction Approximations

2021 ◽  
Author(s):  
Sambit Kumar Das ◽  
Salini Senthil ◽  
Sabyasachi Chakraborty ◽  
Raghunathan Ramakrishnan
Keyword(s):  
Formation Enthalpy ◽  
Reference Value ◽  
Composite Model ◽  
Fine Tuning ◽  
Large Molecules ◽  
New Variant ◽  
Hands On ◽  
Standard Formation Enthalpy ◽  
Local Pair ◽  
The Individual

<div>We accelerate the G4(MP2) composite model by fine-tuning the individual steps using resolution-of-identity and domain‐based local pair‐natural orbitals. The new variant, G4(MP2)-XP, has a low prediction error when tested on 1694 benchmark molecules. To showcase the method's relevance for large molecules, we determine and present a new reference value for the standard formation enthalpy of buckminsterfullerene. We expect G4(MP2)-XP to become the <i>de facto</i> method for rapid and accurate production of thermochemistry big data.</div>

scholarly journals All Hands on Deck: Accelerating Ab Initio Thermochemistry via Wavefunction Approximations

2021 ◽  
Author(s):  
Sambit Kumar Das ◽  
Salini Senthil ◽  
Sabyasachi Chakraborty ◽  
Raghunathan Ramakrishnan
Keyword(s):  
Formation Enthalpy ◽  
Reference Value ◽  
Composite Model ◽  
Fine Tuning ◽  
Large Molecules ◽  
New Variant ◽  
Hands On ◽  
Standard Formation Enthalpy ◽  
Local Pair ◽  
The Individual

<div>We accelerate the G4(MP2) composite model by fine-tuning the individual steps using resolution-of-identity and domain‐based local pair‐natural orbitals. The new variant, G4(MP2)-XP, has a low prediction error when tested on 1694 benchmark molecules. To showcase the method's relevance for large molecules, we determine and present a new reference value for the standard formation enthalpy of buckminsterfullerene. We expect G4(MP2)-XP to become the <i>de facto</i> method for rapid and accurate production of thermochemistry big data.</div>

University Dropout

2008 ◽  
Vol 29 (3) ◽  
pp. 134-147 ◽  
Author(s):  
Manuel C. Voelkle ◽  
Nicolas Sander
Keyword(s):  
Grade Point Average ◽  
Structural Equation ◽  
Unobserved Heterogeneity ◽  
School Grade ◽  
Grade Point ◽  
High School Grade ◽  
Hands On ◽  
University Dropout ◽  
The Individual ◽  
A Prospective Study

University dropout is a politically and economically important factor. While a number of studies address this issue cross-sectionally by analyzing different cohorts, or retrospectively via questionnaires, few of them are truly longitudinal and focus on the individual as the unit of interest. In contrast to these studies, an individual differences perspective is adopted in the present paper. For this purpose, a hands-on introduction to a recently proposed structural equation (SEM) approach to discrete-time survival analysis is provided ( Muthén & Masyn, 2005 ). In a next step, a prospective study with N = 1096 students, observed across four semesters, is introduced. As expected, average university grade proved to be an important predictor of future dropout, while high-school grade-point average (GPA) yielded no incremental predictive validity but was completely mediated by university grade. Accounting for unobserved heterogeneity, three latent classes could be identified with differential predictor-criterion relations, suggesting the need to pay closer attention to the composition of the student population.

scholarly journals Importance of Individual Elements for Perineal Protection in Childbirth: An Interventional, Prospective Trial

2018 ◽  
Vol 08 (04) ◽  
pp. e289-e294 ◽  
Author(s):  
Ole Rasmussen ◽  
Annika Yding ◽  
Finn Lauszus ◽  
Charlotte Andersen ◽  
Jacob Anhøj ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Quality Improvement ◽  
Prospective Trial ◽  
Care Bundle ◽  
Number Needed To Treat ◽  
Improvement Project ◽  
Nulliparous Women ◽  
Hands On ◽  
Five Elements ◽  
The Individual

Objective To analyze the association between each element of a hands-on intervention in childbirth and the incidence of obstetric anal sphincter injuries (OASIS). Study Design We conducted a prospective, interventional quality improvement project and implemented a care bundle with five elements at an obstetric department in Denmark with 3,000 deliveries annually. We aimed at reducing the incidence of OASIS. In the preintervention period, 355 vaginally delivering nulliparous women were included. Similarly, 1,622 nulliparous women were included in the intervention period. The association of each element with the outcome was estimated using a regression analysis. Results The incidence of OASIS went down from 7.0 to 3.4% among nulliparous women delivering vaginally (p = 0.003; relative risk = 0.48; 95% confidence interval [CI]: 0.30–0.76). Number needed to treat was 28. Logistic regression analysis showed that using hand on the head of the child significantly reduced the risk of OASIS (odds ratio = 0.28; 95% CI: 0.14–0.58). Conclusion Using a quality improvement framework, we documented the individual elements of the intervention. Hand on the infant's head reduced the risk of OASIS.

Learning to Solve a Business Problem: ‘Hands-on’ Can Get Results

2007 ◽  
Vol 21 (6) ◽  
pp. 465-471 ◽  
Author(s):  
Robyn Neeson ◽  
Leo Billington ◽  
Rowena Barrett
Keyword(s):  
Small Business ◽  
Business Owner ◽  
Business Growth ◽  
Small Business Owner ◽  
Business Training ◽  
Hands On ◽  
Small Business Training ◽  
The One ◽  
The Individual ◽  
The Right

Small business training can facilitate business growth. The authors show that a ‘hands-on’ approach can have a direct impact on a business owner's current situation. They consider this in relation to the problem of being unable to find the right staff, demonstrating that a programme such as the one they describe enables learning and addresses the lack of time and resources faced by many small business owner-managers. Such programmes also accommodate the style, pace and circumstances of the individual learner. This has a number of implications for the delivery of training to small business owner-managers.

scholarly journals Cyber Business Law and Project-Based Learning

2017 ◽  
Vol 5 (11) ◽  
pp. 62-73
Author(s):  
Jason Powell ◽  
Carmella Parker ◽  
Margaret Kilcoyne
Keyword(s):  
Learning Style ◽  
Project Based Learning ◽  
Business Law ◽  
Approach To Learning ◽  
Individual Level ◽  
Computer Information Systems ◽  
Hands On ◽  
Group Environment ◽  
The Individual ◽  
Legal Concepts

This article describes a project-based learning pedagogical approach to learning legal concepts that transforms these concepts into managerial propositions for students, especially for computer information systems and business administration majors.  This pedagogy provides opportunities and experiences for students to become sensitive enough to real-world topics that they can posit a question to a legal professional regarding cyber business laws.  The hands-on project-based learning method is an engaging and interactive way to learn the information in a group environment, and then it requires the student to demonstrate knowledge at the individual level.  The data collected for this study suggests that the project-based learning style is effective for learning legal concepts.

scholarly journals ​Erythrocyte Parameters as a Diagnostic Tool in Canine Medicine: A Review

2021 ◽  
Author(s):  
S.N. Yadav ◽  
N. Ahmed ◽  
A.J. Nath ◽  
P.K. Boro
Keyword(s):  
Chronic Conditions ◽  
Reference Value ◽  
Clinical Findings ◽  
Parameters Estimation ◽  
Hydration Status ◽  
Blood Collection ◽  
Health Practitioner ◽  
Blood Transport ◽  
Haematological Analysis ◽  
The Individual

The haematological analysis is one of the essential diagnostic and prognostic tools for the health practitioner. Routine hematology consists of erythrocyte, leucocyte and platelet parameters estimation. Erythrocyte parameters (RBC, RDW, haemoglobin, haematocrit, MCV, MCH, MCHC) estimation plays a crucial role in identifying anemia and several other acute and chronic conditions. Accurate and precise haematology results depend on correct blood collection procedures, suitable anticoagulants, proper storage and effective blood transport. The individual reference value variance can be due to age, sex, stress, diet, body condition, hydration status and reproductive status. Automatic haeamtology analyzer can yield quick and accurate results provided the sample is free from any artifacts. In conclusion, the accuracy of the result of automatic haematology analyzer in canine medicine is impeded by the lack of precise and rapid comparison procedure, instability and complexity of blood cells. Therefore the findings of the automatic haemotolyzer should always be corroborated with the clinical findings and another laboratory test.

Maximizing the Number of Visible Labels on a Rotating Map

2021 ◽  
Vol 31 (2) ◽  
pp. 293-313
Author(s):  
Ali Gholami Rudi ◽  
Keyword(s):  
Polynomial Approximation ◽  
Approximation Scheme ◽  
Geometric Object ◽  
Np Hard ◽  
Feature Points ◽  
New Variant ◽  
Vertical Bars ◽  
The Individual

For a map that can be rotated, we consider the following problem. There are a number of feature points on the map, each having a geometric object as a label. The goal is to find the largest subset of these labels such that when the map is rotated and the labels remain vertical, no two labels in the subset intersect. We show that, even if the labels are vertical bars of zero width, this problem remains NP-hard, and present a polynomial approximation scheme for solving it. We also introduce a new variant of the problem for vertical labels of zero width, in which any label that does not appear in the output must be coalesced with a label that does. Coalescing a subset of the labels means to choose a representative among them and set its label height to the sum of the individual label heights.

scholarly journals Mask R-CNN Refitting Strategy for Plant Counting and Sizing in UAV Imagery

2020 ◽  
Vol 12 (18) ◽  
pp. 3015 ◽  
Author(s):  
Mélissande Machefer ◽  
François Lemarchand ◽  
Virginie Bonnefond ◽  
Alasdair Hitchins ◽  
Panagiotis Sidiropoulos
Keyword(s):  
Deep Learning ◽  
Fine Tuning ◽  
Aerial Images ◽  
Individual Plant ◽  
Low Density ◽  
Tracking Accuracy ◽  
Potato Plants ◽  
The Individual ◽  
Segmentation Task ◽  
Vision Algorithm

This work introduces a method that combines remote sensing and deep learning into a framework that is tailored for accurate, reliable and efficient counting and sizing of plants in aerial images. The investigated task focuses on two low-density crops, potato and lettuce. This double objective of counting and sizing is achieved through the detection and segmentation of individual plants by fine-tuning an existing deep learning architecture called Mask R-CNN. This paper includes a thorough discussion on the optimal parametrisation to adapt the Mask R-CNN architecture to this novel task. As we examine the correlation of the Mask R-CNN performance to the annotation volume and granularity (coarse or refined) of remotely sensed images of plants, we conclude that transfer learning can be effectively used to reduce the required amount of labelled data. Indeed, a previously trained Mask R-CNN on a low-density crop can improve performances after training on new crops. Once trained for a given crop, the Mask R-CNN solution is shown to outperform a manually-tuned computer vision algorithm. Model performances are assessed using intuitive metrics such as Mean Average Precision (mAP) from Intersection over Union (IoU) of the masks for individual plant segmentation and Multiple Object Tracking Accuracy (MOTA) for detection. The presented model reaches an mAP of 0.418 for potato plants and 0.660 for lettuces for the individual plant segmentation task. In detection, we obtain a MOTA of 0.781 for potato plants and 0.918 for lettuces.

scholarly journals “Do you Guys take Showers with your Children?”: Gendered Embodiment and the Legitimation of Italian Fathering Practices

2020 ◽  
pp. 1097184X2097672
Author(s):  
Eugenia Mercuri
Keyword(s):  
Qualitative Research ◽  
National Context ◽  
Individual Level ◽  
Hands On ◽  
Care Practices ◽  
The Individual ◽  
First Time

This work aims at investigating gendered embodiment in fathering practices in a national context, Italy, where understandings of fatherhood, at the institutional as well as the individual level, are still more centered on the provider ideal than on a model of nurturing and caring fatherhood. This qualitative research on Italian first-time fathers of children under three years of age focused on men’s participation in routine, instrumental, and material childcare practices, exploring the potential for a transformation in both the meanings attached to fatherhood as well as to aspects related to embodiment and constructions of masculinity that sustain inequalities. The findings show that, while participation in hands-on childcare plays an important role in the construction of intimate father-child relationships, a legitimation of men’s bodies’ involvement in interaction with children is still missing, especially for care practices that overlap with constructions of motherhood.

scholarly journals Research on Fine-Grained Classification of Rumors in Public Crisis ——Take the COVID-19 incident as an example

2020 ◽  
Vol 179 ◽  
pp. 02027
Author(s):  
Shuaipu Chen
Keyword(s):  
Reference Value ◽  
Training Model ◽  
Fine Tuning ◽  
The Public ◽  
Fine Grained ◽  
Model Method ◽  
Public Crisis ◽  
Sentence Level ◽  
Good Classification

[Purpose / Meaning] Rumors are frequent in the COVID-19 epidemic crisis. In order to unite the power of dispelling rumors of various media platforms to help to break the rumors in a timely and professional manner, this article has designed a new fine-grained classification of rumors about COVID-19 based on the BERT model. [Method / Process] Based on the rumor data of several mainstream rumor refuting platforms, the pre-training model of BERT was used to fine-tuning in the context of COVID-19 events to obtain the feature vector representation of the rumor sentence level to achieve fine-grained classification, and a comparative experiment was conducted with the TextCNN and TextRNN models. [Result / Conclusion] The results show that the classificationF1 value of the model designed in this paper reaches 98.34%, which is higher than the TextCNN and TextRNN models by 2%, indicating that the model in this paper has a good classification judgment ability for COVID-19 rumors, and provides certain reference value for promoting the coordinated refuting of rumors during the public crisis.

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