Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of the Blood Glucose, Growth Hormone, and Cortisol Responses to Two Doses of Insulin (0.15 U/kg vs. 0.10 U/kg) in the Insulin Tolerance Test: A Single-Centre Audit of 174 Cases

Objective The insulin tolerance test (ITT) is the gold standard endocrine test used to assess the integrity of the growth hormone (GH) and cortisol axes. The ITT has potential risks, and severe hypoglycaemia may necessitate intravenous glucose rescue. There is no clear consensus as to the optimal insulin dose for the ITT. Therefore, we sought to compare the standard dose (0.15 U/kg) and a low-dose ITT (0.1 U/kg). Design Single-centre audit of ITT data (2012–2021). Patients and Measurements. Patients who underwent an ITT to assess possible GH deficiency/adrenal insufficiency were included. Glucose, GH, and cortisol were measured at baseline and 30, 45, 60, 90, and 120 minutes following I.V. insulin bolus (0.15 U/kg or 0.10 U/kg). Results Of the ITTs performed, only 3/177 (1.7%) did not achieve adequate hypoglycaemia (≤2.2 mmol/L) with a single insulin dose. In total, 174 patients (43.5 ± 12.1 yrs, mean ± standard deviation) were included for analysis (0.15 U/kg: n = 113, 0.10 U/kg: n = 61). All 174 subjects had adequate hypoglycaemia regardless of baseline fasting blood glucose level or insulin dose. Neither nadir glucose nor glucose delta (i.e., baseline minus nadir) differed between insulin doses. Trends in both cortisol and GH responses over time were similar between groups, and a greater proportion of patients receiving the standard dose had an adequate cortisol response (77/106 (72.6%) vs. 32/60 (53.3%), p=0.01). The rates of glucose rescue did not differ in a subset of 79 patients, with on-demand glucose rescue in 4/35 (11%) for the standard dose and 2/44 (5%) for the low dose (p=0.25). Conclusions Our results suggest that the low-dose ITT produces comparable glucose, cortisol, and GH responses to the higher dose. Given the risks associated with hypoglycaemia, the low dose appears to be preferable to the standard dose ITT in most circumstances.
Human-Capital Formation: The Importance of Endogenous Longevity

We present a theory of human capital, with its two most essential components, health capital and, what we term, skill capital, endogenously determined within the model. Using the theory, and a calibrated version of it, we uncover and highlight an important economic mechanism driving human-capital formation, socio-economic and health disparities, human-capital based economic growth, and causal relations among the stocks of wealth, skill and health, namely whether individuals can influence their own length of life (endogenous longevity). Without the ability of individuals to influence their longevity, the effects of health, skill and wealth on later-life skill and health are muted. Any additional health, skill or wealth is not used for additional investment, but essentially consumed. These findings have important implications for the modeling of, and our understanding of, human-capital formation, disparities in human capital and health, and human-capital based economic growth.
Supplementary Material for Learning to Learn by Jointly Optimizing Neural Architecture and Weights

To avoid the computational cost of Hessian matrix, the first-order DARTS [11] and the first-order approximation of MAML [3] are employed for searching meta-learners. As for the inner-learners of φ and θ, we use the vanilla SGD with inner learning rate αinner = 1× e−2 for optimizing φ, while a inner learning rate βinner = 0.1 for training θ. In the meta-learner of φ, an Adam [6] optimizer is employed for updating, with an initial learning rate αmeta = 1× e−3 and a weight decay of 3 × 10−4. A similar Adam without weight decay is applied to training the meta-learner of θ. We choose M = 5 as the inner update step. The searching is executed on both Omniglot and Mini-Imagenet under the setting of 5-way, 5-shot. For each dataset, we sample 1200 tasks from Dmeta−train for training and 600 tasks from Dmeta−test for evaluation. On Omniglot, we prune the architecture every three epochs from the fifth epoch, while we do it every five epoch from ninth epoch in Mini-Imagenet. All search and adaptation experiments are carried out on NVIDIA RTX 2080TI GPUs. The whole search process requires about 0.6 GPU days on Mini-Imagenet. The searched architectures is visualized in Fig.1 and Fig.2.
OAEM_A_357320 123..131

Background: Shock is a life-threatening syndrome in which tissue perfusion and oxygen delivery are inadequate. Near-infrared spectroscopy (NIRS) has been suggested as a noninvasive tool for monitoring and detecting the state of inadequate tissue perfusion. Renal and mesenteric oximetry show decreased cardiac output earlier than systemic or global parameters of tissue oxygenation or cerebral oximetry. However, until now there has been no study on the validity of regional renal oxygen saturation (rRSO2) by NIRS for diagnosing shock in children. Purpose: To analyze the validity of rRSO2 by NIRS to diagnose shock in children. Patients and Methods: This cross-sectional study was conducted in critically ill children (aged 1 month–18 years) who were admitted to the pediatric intensive care unit (PICU), from September to November 2020, consecutively. Patients were classified into two groups: shock and non-shock. The diagnosis of shock is based on clinical criteria (tachycardia, sign of hypoperfusion and decrease systolic blood pressure <P5 according to age). Measurement of rRSO2 by NIRS was performed by the doctor in charge when the patient came to PICU. The baseline rRSO2 value (%) made a receiver operating characteristic (ROC) curve and was used to find the optimal cut-off value and calculated sensitivity and specificity. Results:We enrolled 20 critically ill patients. The baseline rRSO2 in the shock (n=10) and non-shock (n=10) groups were, 44.00±4.95 vs 78.70±4.52 (p 0.003). The optimal cutoff value of the baseline rRSO2 to predict shock is less than 58.5% with area under the curve (AUC) value is 94.4% (95% CI of 84.4–100%), p 0.001, sensitivity 90% and specificity 90% in critically ill children. Conclusion: The rRSO2 value by NIRS can differentiate between shock and non-shock in critically ill patients accurately.
Evaluation of Selected Physical Properties of Blighia

Blighia sapida, a Lesser-Used Species is being processed into sawn timber to meet the demand for wood. The knowledge of its wood quality would enhance its effective utilization. However, there is little information known on the physical properties of this species that could enhance its acceptability and optimum utilization. This, therefore, necessitate the need to investigate the physical properties of this wood species. Three standing trees of B. sapida were purposively felled for this study. Billets of 500 mm were obtained from the wood disc at the base, middle, and top of the tree. Each wood disc was partitioned into three; innerwood, middlewood, and outerwood following specified international standards for the physical properties test (wood colour, proportion of sapwood and heartwood, bark thickness, density, moisture content, and volumetric shrinkage). B. sapida wood density with a mean value of 709.78±8.88 kg/m, ranged from (571.59±13.45 to 854.81±7.08 kg/m. Moisture content percentage of average value 70.62±1.23%, ranged from 53.84±1.40 to 89.00±2.75%. Volumetric shrinkage of average value 15.24±0.25%, range from 13.38±0.66 to 16.89±0.83%. The range of B. sapida wood density value of the study falls within the range that could be categorized as medium density wood of medium construction strength properties. The 1:1.5% tangential–radial shrinkage observed in this study was low, an indicator of a low risk of deformation while seasoning the wood, as the ratios of tangential-radial shrinkage that is high are those over 2.2%.
Micro-credentials, Higher Education and Career Development: Perspectives of University Students Micro-credentials, Higher Education and Career Development: Perspectives of University Students

Emergence of micro-credentials, digital qualifications less than a degree, is rooted in an increased demand for quality and digitalized higher education, and a growing demand for skilled human capital tailored for the industry. There is now a wider acceptance of micro-credentials by the industry as proof of necessary skills set developed by employees, either as a supplement or an alternative pathway to traditional college diplomas. However, within the context of higher education, an enlarging ecosystem of micro-credentials is also raising concerns over the potential of micro-credentials in career development. This phenomenological study projects an in-depth understanding of the phenomenon of micro-credentials within the context of higher education by involving experiences and interpretations of key participants- university students. Participants involved 11 junior and senior students enrolled in an advanced communication skills course focused on preparing students for their careers. Data was collected using semi-structured interviews, and they were analysed using content analysis technique and MAXQDA software. The findings show that the employability and accessibility factors enable participants to adopt micro-credentials more in their career development. Additionally, participants’ belief that the university education is being more theoretical or fragmented, and the changing mindset of the participants towards higher education after the COVID-19 pandemic also facilitate the adoption of micro-credentials in building their careers. Participants are also deterred from embracing micro-credentials in their career pathways. This is due to participants’ discontent with the dominance of data science or computer engineering fields, perceived low prestige attributed to micro-credentials, and reservations about any possible prejudice against micro-credential holders. Another finding is that participants seem to perceive micro-credentials more as a supplement to traditional university degrees rather than an alternative pathway to career development. Finally, participants frequently related their adaptive career behaviour (using micro-credentials to advance in career) to setting specific career goals and enacting them with persistence. An additional finding is that participants’ display of this adaptive career behaviour is also contingent upon the personality traits of being entrepreneurial, conscientious, and extraverted. The findings have been discussed in the light of the existing literature on micro-credentials, higher education and the career self-management model, and some implications have been provided. From employer’s perspective, if the employer must make a decision between a traditional degree holder and a MC holder, I believe a traditional degree holder may be promoted; I am assuming that the employer has not observed both enough, and does not have enough data to compare both, I mean…A traditional degree holder may be more advantageous. (PT3)
Chapter 23 Dimension Reduction

Given a set P of n points in R, we need nd numbers to describe them. In many scenarios, d might be quite large, or even larger than n (in some applications, where the access to the points is given only through dot-product, it is useful to think about the dimension as being unbounded). If we care only about the distances between any pairs of points, then all we need to store are the pairwise distances between the points. This would require roughly n2 numbers, if we just write down the distance matrix. But can we do better? (I.e., use less space.) A natural idea is to reduce the dimension of the points. Namely, replace the ith point pi ∈ P, by a point ui ∈ R , where k ≪ d and k ≪ n. We would like k to be small. If we can do that, then we compress the data from size dn to size kn, which might be a large compression. Of course, one can do such compression of information without losing some information. In particular, we are willing to let the distances to be a bit off. Formally, we would like to have the property that (1 − ε)∥pi − p j ∥ ≤ ∥ui − u j ∥ ≤ (1 + ε)∥pi − p j ∥, for all i, j , where ui is the image of pi ∈ P after the dimension reduction. To this end, we generate a random matrix M of dimensions d × k, where k = Θ(ε−2 log n) (the exact details of how to generate this matrix are below, but informally every entry is going to be picked from a normal distribution and scaled appropriately). We then set ui = Mpi, for all pi ∈ P. Before dwelling on the details, we need to better understand the normal distribution.
DETERMINANTS OF TAX REVENUE: A COMPARISON BETWEEN ASEAN-7 PLUS CHINA AND 8- EUROPEAN COUNTRIES

The aim of this paper is analyzing the level ratio of tax revenue and GDP depending on different consumer behaviors between two groups of countries: ASEAN-7 plus China (called the Eastern) and eight European countries (called the Western). The study applied the Feasible Generalized Least Square model to confirm the robustness of the Panel Corrected Standard Errors model, and the results indicate that all countries have a positive association between tax revenue with the human capital and FDI variables. In addition, in the Eastern, forest area and broad money has a statistically significantly positive impact on tax revenue while gross savings has a negative one. Further, the Western witnessed the positive impact with gross savings while broad money variables lead to a decrease in tax revenue. The major results indicate that in the East, the Governments should focus on how to improve their taxation by promoting the broad money M2 and expanding the forest area as well as support their consumers spending more instead of saving. In contrast, European countries try to reduce the M2, encouraging their consumers to save more. The Eastern and Western governments may control natural and demographic determinants aimed to support taxation and sustainable economic growth.
Some Considerations Regarding the Assessment of Dynamic Characteristics

This paperwork deals with the estimation methods for the dynamic behavior and natural characteristics of structures. A structural case study of a 3 DOFS structure tested on the master shaking table of the Laboratory of Earthquake Engineering from the Faculty of Civil Engineering and Building Services from Iasi it is presented. The specimen is a 3 storey steel frame model with additional masses. The testing program consisted of low level sweep sine tests (OX & OY directions). Next, earthquake type excitations were applied, at several degrees of intensity (real and synthetic time-histories). The verification and validation of modeling assumptions of the finite element models for structural analysis were carried on by the means of dedicated software FEM tools. The conclusions are focused on the accuracy of the models and the dynamic model matrices.
LEVERAGING GREEN HUMAN RESOURCE MANAGEMENT PRACTICES TOWARDS ENVIRONMENTAL PERFORMANCE: AN EMPIRICAL EVIDENCE FROM THE MANUFACTURING CONTEXT IN EMERGING ECONOMY

This study investigates the role of green human resource management (GHRM) practices on environmental performance (EP) of manufacturing organizations in Bangladesh. The study utilized a questionnaire survey among 328 manufacturing organizations selected conveniently from a population of 5608 firms located in Dhaka and Chattogram. PLS-SEM (partial least squares) was employed to assess the proposed research model. Out of six, three hypotheses were supported. Particularly, green job analysis and job description, green training and development, and green reward and compensation practices significantly influence environmental performance of manufacturing organizations. This study provides valuable insights for organizations on the GHRM-EP link in a unique South-Asian context with high level of environmental degradation. This research also contributes to fill the research gap as few studies have investigated the under-researched area. The findings are of important to scholars, decision makers, and practitioners. Further, the study explains the limitations and directions for future studies.
THE IMPACT OF SUKUK STRUCTURES ON SUKUK RATINGS AND YIELDS

Sukuk has been developed into a global asset class, supporting development with the participation of a wide range of issuers and investors irrespective of demographic continents. Sukuk structuring is not only related to regulations imposed by the regulators but also has high consideration on rating and yield performance. This study aims to examine the effect of the Sukuk structures on Sukuk rating and yield in Bursa Malaysia (Malaysian Stock Exchange) listed companies during the term of 2008–2013. This study uses the ordinal logit regression model (OLRM) to investigate the effect of Sukuk structures on the rating, and the ordinary leastsquare (OLS) to investigate the effect of Sukuk structures on the yield. The result demonstrates two opposite directions after controlling for firm characteristics. While Sukuk rating is negatively related to Sukuk structures, Sukuk yield shows a positive direction with Sukuk structures. This study evidently shows that the selection of Sukuk structure is among the important factors for Sukuk yield performance, in addition to fulfilling the regulatory requirements on Sukuk structuring. The selection of the best structure can achieve the issuance and investment objectives. This study was limited to the study of the relationship between Sukuk structure on Sukuk ratings and yield using the aggregate data of Malaysian public listed companies that issued Sukuk during the period of 2008 to 2013. The study provides new insights into the issue of how the Sukuk structure influences the Sukuk rating and yield. The findings of this study contribute to the existing literature on the determinants of Sukuk ratings and yields.
VALHALLA: Visual Hallucination for Machine Translation

Designing better machine translation systems by considering auxiliary inputs such as images has attracted much attention in recent years. While existing methods show promising performance over the conventional text-only translation systems, they typically require paired text and image as input during inference, which limits their applicability to real-world scenarios. In this paper, we introduce a visual hallucination framework, called VALHALLA, which requires only source sentences at inference time and instead uses hallucinated visual representations for multi-modal machine translation. In particular, given a source sentence an autoregressive hallucination transformer is used to predict a discrete visual representation from the input text, and the combined text and hallucinated representations are utilized to obtain the target translation. We train the hallucination transformer jointly with the translation transformer using standard backpropagation with crossentropy losses while being guided by an additional loss that encourages consistency between predictions using either groundtruth or hallucinated visual representations. Extensive experiments on three standard translation datasets with a diverse set of language pairs demonstrate the effectiveness of our approach over both text-only baselines and state-of-the-art methods. Project page: http://www.svcl. ucsd.jects/valhalla.edu/pro.
DESIGNING A PEDAGOGY FOR HIGHER EDUCATION SUCCESS-AN EMPIRICAL STUDY IN MALAYSIA

The purpose of the present study is to develop a conceptual research model and test its applications to educationalists to design the pedagogy for higher education success particularly for higher education institutions in developing nations. Earlier studies have lesser dimensions on student-centered-learning whereas the current study exposes most of the potential predictors while conceptualizing the model and is highly suitable during the turbulence period of COVID-19. The findings of the study revealed that smart classroom, user-friendly technology, and partnership have a positive influence on higher education success. The present article considered the perceived benefits namely language skills, computing abilities, and rational thinking as a mediating variable and enact its important role in higher education success. The proposed model is useful for educationalists to design the course curriculum for higher education institutions. The significant findings obtained in the present study can be applied and customized to higher education institutions in the globe for long term sustainability to orient towards students’ career development. In the digital era with online education in force during an unforeseen situation like COVID19, user-friendly technology will be the ultimate alternative in higher education teaching and learning as it emerges as the result of this study.
LUPANE TRITERPENOIDS, PHYTOSTEROL, PHENOLIC ACID AND FATTY ACID FROM LEAVES OF BOUEA OPPOSITIFOLIA (ROXB.) MEISN

Phytochemical investigation of petroleum ether (PESF) and dichloromethane soluble (DCMSF) fractions designated as PESF and DCMSF, respectively of methanol extract of leaves of Bouea oppositifolia (Roxb. Meisn. (an endangered species of Bangladesh) yielded six compounds, which were characterized as betulin (1), lupeol (2), lupenone (3), stigmasterol (4), p-coumaric acid (5), and oleic acid (6) by high field NMR studies and comparison with published values. The identity of the isolated compounds were further substantiated by co-TLC. Since antiquity, plants and plant-derived herbal products have been used as drugs to alleviate different ailments (Balunas and Kinghorn 2005). Besides, plant-derived molecules also serve as templates for the designing, synthesis or semi-synthesis of other therapeutic agents. Bouea oppositifolia (Roxb.) Meisn. , locally known as Mali aam belonging to Anacardiaceae, is a tree that grows up to 33 meters in height in the hot, tropical monsoon climate such as in Bangladesh, Myanmar, Thailand, Laos, Cambodia, Vietnam, Malaysia, and Indonesia (Martin et al. 1987). The plant is mostly found in Khagrachari and Chittagong districts of Bangladesh which is considered as a critically endangered species (Rahman 2017). In Thailand, the fruits of this plant are used to treat phlegm and constipation, the root is used in fever, common cold and applied as a detoxifier in folkloric medicines (Neamsuvan et al. 2014). Ripe fruits are eaten and green fruits are used in cooking by the local people of Bangladesh. Recently, the antidiarrheal and analgesic activities of B. oppositifolia (Roxb.) have been reported in mice model (Islam et al. 2020). Neranon et al. (1998) investigated the methanolic extract of the twigs of B. oppositifolia and isolated phenolic compounds identified as astilbin, gallic acid methyl ester, epicatechin, and fustin. Both the unripe and ripe fruits of B. macrophylla (another species of Bouea genus) revealed the presence of 82 and 121 volatile compounds, respectively by gas chromatography-mass spectrometry (Rajan and Bhat, 2017). As part of the continuing research on medicinal plants of Bangladesh (Shajib et al. 2017, Ibrahim et al. 2018, Chowdhury et al. 2019, Soma et al. 2019), in the present study the leaf extract of B. oppositifolia was evaluated, and isolation and structure elucidation of six secondary metabolites are reported for the first time. The leaves of B. oppositifolia were collected from Remakri in Thanchi Upazila of Bandarban District in South Eastern Bangladesh in November 2018. The plant was taxonomically identified Author for correspondence: <r.pchem@yahoo.com>. Department of Pharmacy, State University of Bangladesh, Dhaka1205, Bangladesh. Institute of National Research and Services, Bangladesh Council of Scientific and Industrial Research, Dr. Kudrat-I-Khuda road, Dhanmondi, Dhaka-1205, Bangladesh.