Miracle-dz/UniFAR-FTUs huggingface dataset:
Progesterone Levels During Pregnancy in Ewes Treated with Bone Marrow Stromal Cells

This study was conducted to determine the effect of bone marrow stromal cells (BMSCs) on progesterone level during pregnancy in ewes. Flurogestone Acetate Sponges 40 mg, followed by 400 i.u. Equine chorionic gonadotropin (eCG) were used to synchronize estrus and ovulation. The animals were divided into three equal groups (5 animals for each group). The 1st and 2nd group injected intravenously after eCG injection with 1x108 and 2x108 respectively with BMSCs while the 3rd group was injected with normal saline which serve as a control group. Blood samples were collected during pregnancy, at day 10, 21, 85 from the jugular vein. At day 10, 21 the results showed that there was a significant difference (p≤0.05) in the level of progesterone between treated groups as compared with the control group. While there was no significant difference between different groups at day 85. It was concluded from this study that BMSCs have a beneficial effect in ewe’s reproductive system, by increasing the level of progesterone at early pregnancy.
The Role of Fructophilic Lactic Acid Bacteria in the Restoration of Infected Wounds and IL-17 Level in Rabbits

Fructophilic lactic acid bacteria (FLAB) isolated from honeybeeâ€™s nectar stomach represent an important source of antimicrobial substances that has been focused on nowadays. In this study, these FLABs were tested for their antibacterial activity in vivo as well as the detection of Interleukine -17 in the serum of rabbits ingested with FLAB isolates. Fructobacillus fructosus FH1, Fructobacillus fructosus FH8 and Lactobacillus kunkeei SHGH-7 FLAB isolates were used against wound infections caused by Pseudomonas aeruginosa and Staphylococcus aureus (MRSA) in rabbit skin . Enzyme linked sorbent immunoassay (ELISA) was used to detect the levels of Interleukine-17 in the sera of rabbits ingested with these three FLAB isolates. The results showed that the time of wound healing process was shorter in the FLAB treated wounds when compared to control untreated wounds with a significant difference at pâ‰¤0.01. Histopathological examination of wounds treated with FLAB isolates showed normal thickness in skin layers with no pathological effect, as well as tissue repair and presence of new blood vessels when compared to pathogen groups that were infected with pathogenic bacteria without any treatment, which showed hyperplasia with necrosis in tissue. Results of the FLAB-ingested groups showed an increase in the level of IL-17 when compared to the control with no statistical significance (Pâ‰¤0.05). To the best of our knowledge, this is the first study on using FLAB microorganisms in the treatment of infected wounds.
Open Challenges in Medical Visualization

The underlined authors are joint ﬁrst authors and contributed equally to this work Abstract —While the number of publications in the medical ﬁeld constantly increases, medical visualization publications do not necessarily follow the same trend. As developments in the medical domain are the driving force of medical visualization research, there are still many open challenges for medical visualization researchers. This is currently not reﬂected in the number of publications on this topic at our premier publication venues. At IEEE VIS 2020, we hosted an Application Spotlight session to highlight such open challenges. With this article, we hope to inspire the visualization community by providing an overview of open challenges and setting a research agenda for the future of medical visualization.
METODE MULTIPLE IMPUTATION UNTUK

Multiple imputation is one of estimation method used to impute missing observations. This method imputes missing observation several times then it is more possible to get the right estimate than just one time imputation. In this research, the method will be applied to estimate missing observations in covariates of recurrent event data. Some multiple imputation methods will be considered including combination of the event indicator, the event times, the logarithm of event times, and the cumulative baseline hazard. To compare these methods, Monte Carlo simulation will be used based on relative bias and Mean Squared Error (MSE). The recurrent events will be modelled using Cox proportional hazard model. Furthermore, real data application will be presented.
The Performance of Broiler Chickens Fed on Miana Plant Flour (Plectranthus scutellarioides, L.) R. Br.

The aim of the present study was to evaluate the effect of Miana plant flour (Plectranthus scutellarioides, L.) R. Br. in the diet on the performance of broiler chickens. The current study used 100 broiler chickens from day-old chicks, and a commercial diet was given up to seven days for the adaptation period. The present experiment was designed in a completely randomized design with five different levels of Miana plant flour (0, 5%, 7.5%, 10%, and 12.5%) in broiler chicken’s diet as treatments (N = 20 bird/level), and each treatment was repeated four times. The diet was arranged iso-protein (21%) and iso-energy (2900 kcal/kg). Daily feed intake, daily weight gain, feed conversion ratio (measured every week and divided by seven to get daily data), Live weight, Carcass percentage with skin, Carcass percentage nonskin, and abdominal fat pad percentage were measured at the end of the study. The results showed that the inclusion of Miana plant flour in broiler chickens’ diet significantly affected daily weight gain, live weight, feed conversion, carcass percentage with skin, carcass percentage except for skin while it did not affect daily feed intake and abdominal fat pad percentage. In conclusion, Miana plant flour can be used up to 12.5% in the diet non any negative effect on broiler chickens performance.
Organoleptic evaluation of products formulated from (Tamarindus indica L.) tender tamarind leaves

Tamarind is one of the medicinally important tree got good nutritional and medicinal values and also having pharmacological effects based on the finding the main objective of this study is organoleptic evaluation of products formulated from tender tamarind leaves, the products were prepared using standard procedure and were given for the sensory evaluation (Organoleptic evaluation) to 20 panelists to test for appearance, colour, texture, aroma, taste and overall acceptability using 9-Point hedonic scale. It was found that in roasted bangal gram chutney powder, (RBCP-1) has got good sensory score in all the parameters 7.65, 7.6, 7.65, 7.65, 7.4 and 7.6 in appearance, colour, texture, aroma, taste and in overall acceptability respectively compared to other two variation. Where as in Niger seed chutney powder, (NSCP-1) scored highest in all the sensory attributes, (NSCP-2) and (NSCP-3) scored low in all the attributes because of more sourness. Among all variation hurigalu-2 (HG-2) scored highest in all the sensory attributes with appearance (7.6), colour (7.4), texture (7.35), aroma (7.5), taste (7.5) and overall acceptability (7.95). This might be due to less incorporation of tender tamarind leaves and amla powder which results in less sourness when compared to other two variations. Hence all the products were nutridense and got good sensory scores for the acceptability which can be promoted for regular consumption.
Contribution of Insurance Business In Nepal

This study aims to find the contribution of insurance business in Nepalese economy. The insurance sector is assumed to be an infrastructural pillar of the financial sector of the economy. The role of insurance business has been growing importance in financial intermediation, which has received less attention than bank and stock markets. The ultimate goal of insurance business is to provide security to insurance industry according to national need by protecting all classes of the society from natural and social risks while embracing the globally accepted insurance norms. There has been significant contribution of insurance business boosting economic development of Nepal. The objective of the study is to investigate insurance business and examine its contribution on financial resources mobilizations in Nepal. For this theoretical analysis, different research studies have studied to draw the fundamental issues of insurance business in the economy. The simple statistical tools have been applied to analyze the collected data. Furthermore the findings of the study emphasize the development of insurance business and its contribution in mobilizing financial resources needs to be paid more attention in financial sector analysis and macroeconomic policy.
Nurse staffing levels and patient outcomes: a systematic review of longitudinal studies

Background: The contribution of registered nurses (RN) towards safe patient care has been demonstrated by several studies. However, most of the evidence is cross-sectional, hence the inability to demonstrate that staffing levels precede patient outcomes. No reviews have summarised longitudinal studies considering nurse staffing and patient outcomes. Objectives: To synthesise longitudinal studies focusing on associations between nurse staffing levels and patient outcomes. Methods: Systematic review. We conducted our search in 2020 and updated it in July 2021. We searched Medline, CINAHL, Embase and the Cochrane Library. We used the ROBINS-I tool for assessing risk of bias. We reported results narratively grouped by outcome. Results: 28 papers were included. Most studies were either at serious (n=12) or critical (n=6) risk of bias, with 3 studies at low risk of bias. Studies were conducted in a variety of settings and populations. Notwithstanding the limitations, findings are consistent with an overall picture of a beneficial effect from higher RN staffing on preventing patient death. Studies with the greatest risk of bias were judged as most likely to underestimate the effect of higher RN staffing. The evidence is less clear for other patient outcomes, but estimates, though at moderate or serious risk of bias, indicate that higher RN staffing is likely to lead to better patient outcomes. Evidence about the contribution of other nursing staff groups and skill mix of the team is unclear. Conclusion: There is a likely causal relationship between low RN staffing and harm to patients, although uncertainties remain regarding the magnitude of effect. To address these uncertainties, future studies should be conducted in more than one hospital and using standardised measures when reporting staffing levels.
TÁC ĐỘNG CỦA ĐẠI SỨ THƯƠNG HIỆU LÊNĐẾN Ý ĐỊNH MUA CỦA KHÁCH HÀNG TẠI THÀNHPHỐ HỒ CHÍ MINH (The Impacts of Brand Ambassador on Purchase Intention among Customers in Ho Chi Minh City)

Vietnamese Abstract: Mục đích của nghiên cứu này nhằm phân tích những yếu tố của đại sứ thương hiệu tác động đến ý định mua của khách hàng tại khu vực Thành phố Hồ Chí Minh, với số lượng mẫunghiên cứu là 210 người đang sinh sống tại Thành phố Hồ Chí Minh, độ tuổi từ 16 và lớn hơn, khảo sát được thực hiện thông qua bảng câu hỏi trực tuyến. Nhóm tác giả tiến hành phân tích hồi quy tuyến tính với ý định mua hàng là biến phụ thuộc và 6 biến độc lập có nguồn gốc từ các tài liệu tham khảo, gồm: Sự thu hút, sự tin cậy, chuyên môn, sự quen thuộc, sự phù hợp của người nổi tiếng với thương hiệu/sản phẩm và các thông tin tiêu cực. English Abstract: The purpose of this study is to investigate the factors of brand ambassador that influence the intention to purchase product among customers in Ho Chi Minh City. The research sample includes 210 responses of the participants aged 16 years old and above in Ho Chi Minh City. The survey was conducted via an online questionnaire. Data was analysied by SPSS 20 statistical software. The authors conduct linear regression analysis with purchase intention as the dependent variable and 6 independent variables including: attractiveness, trustworthiness, expertise, familarity, celebrity match-up congruence with the brand/product, negative publicity.
Sensitivities-Based Method and Expected Shortfall for Market Risk Under FRTB and Its Impact on Options Risk Capital

PurposeThis paper measures different market risk impacts on options portfolios under the new Fundamental Review of the Trading Book (FRTB) regulation, issued in Basel and coming into effect in 2023.Design/methodology/approachThis paper first suggests an algorithm for implementing the FRTB standardised approach via the sensitivities-based method to estimate a portfolio's risk capital and presents an illustration applied to an option position. Second, it proposes a methodology to estimate the expected shortfall in options portfolios from the FRTB internal models approach. In this regard, an application is developed to measure expected shortfall (ES) and value at risk (VaR) impacts under FRTB versus conventional VaR in a currency option position by considering stress scenarios from the 2007–9 and 2020–1 crises and back-testing procedures.FindingsThe suggested algorithm satisfactorily captures impacts via the sensitivities-based method, and higher risk capital demands are expected for emerging economies. Also, the planned FRTB methodology to measure ES and VaR is appropriate; in particular, historical metrics perform well. Astonishingly, their revealed impacts are more significant under the 2020–1 pandemic crisis than the 2007–9 financial crisis.Originality/valueThe proposals developed weave a communication bridge between the standardised and internal approaches of FRTB regulation, which can be scaled up technologically and institutionally.
TAII Framework for Trustworthy AI Systems

Organizations and companies need practical tools and guidelines to kick-off the implementation of Trustworthy Artificial Intelligence (TAI) systems. AI development companies are still in the beginning of this process or have not even started yet. The findings of this article address to decrease the entry level barrier for AI ethics implementation by introducing the Trustworthy Artificial Intelligence Implementation (TAII) Framework. The outcome is comparatively unique given that it considers a meta perspective of implementing TAI within organizations. As such, this research aims to fill a literature gap for management guidance to tackle trustworthy AI implementation while considering ethical dependencies within the company. The TAII Framework takes a holistic approach to identify the systemic relationships of ethics for the company ecosystem and considers corporate values, business models, and common good aspects like the Sustainable Development Goals and the Universal Declaration of Human Rights. The TAII Framework creates guidance to initiate the implementation of AI ethics in organizations without requiring a deep background in philosophy and considers the social impacts outside of a software and data engineering setting. Depending on the legal regulation or area of application, the TAII Framework can be adapted and used with different regulations and ethical principles.
Generating Local Maps of Science using Deep Bibliographic Coupling

Bibliographic and co-citation coupling are two analytical methods widely used to measure the degree of similarity between scientific papers. These approaches are intuitive, easy to put into practice, and computationally cheap. Moreover, they have been used to generate a map of science, allowing visualizing research field interactions. Nonetheless, these methods do not work unless two papers share a standard reference, limiting the two papers usability with no direct connection. In this work, we propose to extend bibliographic coupling to the deep neighborhood, by using graph diffusion methods. This method allows defining similarity between any two papers, making it possible to generate a local map of science, highlighting field organization.
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents

Document-level neural machine translation (DocNMT) achieves coherent translations by incorporating cross-sentence context. However, for most language pairs there’s a shortage of parallel documents, although parallel sentences are readily available. In this paper, we study whether and how contextual modeling in DocNMT is transferable via multilingual modeling. We focus on the scenario of zero-shot transfer from teacher languages with document level data to student languages with no documents but sentence level data, and for the first time treat document-level translation as a transfer learning problem. Using simple concatenation-based DocNMT, we explore the effect of 3 factors on the transfer: the number of teacher languages with document level data, the balance between document and sentence level data at training, and the data condition of parallel documents (genuine vs. back-translated). Our experiments on Europarl-7 and IWSLT-10 show the feasibility of multilingual transfer for DocNMT, particularly on document-specific metrics. We observe that more teacher languages and adequate data balance both contribute to better transfer quality. Surprisingly, the transfer is less sensitive to the data condition, where multilingual DocNMT delivers decent performance with either back-translated or genuine document pairs.
Network meta‐analysis of rare events using penalized likelihood regression

Network meta‐analysis (NMA) of rare events has attracted little attention in the literature. Until recently, networks of interventions with rare events were analyzed using the inverse‐variance NMA approach. However, when events are rare the normal approximations made by this model can be poor and effect estimates are potentially biased. Other methods for the synthesis of such data are the recent extension of the Mantel‐Haenszel approach to NMA or the use of the noncentral hypergeometric distribution. In this article, we suggest a new common‐effect NMA approach that can be applied even in networks of interventions with extremely low or even zero number of events without requiring study exclusion or arbitrary imputations. Our method is based on the implementation of the penalized likelihood function proposed by Firth for bias reduction of the maximum likelihood estimate to the logistic expression of the NMA model. A limitation of our method is that heterogeneity cannot be taken into account as an additive parameter as in most meta‐analytical models. However, we account for heterogeneity by incorporating a multiplicative overdispersion term using a two‐stage approach. We show through simulation that our method performs consistently well across all tested scenarios and most often results in smaller bias than other available methods. We also illustrate the use of our method through two clinical examples. We conclude that our “penalized likelihood NMA” approach is promising for the analysis of binary outcomes with rare events especially for networks with very few studies per comparison and very low control group risks.
Severi varieties on blow‐ups of the symmetric square of an elliptic curve

We prove that certain Severi varieties of nodal curves of positive genus on general blow‐ups of the twofold symmetric product of a general elliptic curve are nonempty and smooth of the expected dimension. This result, besides its intrinsic value, is an important preliminary step for the proof of nonemptiness of Severi varieties on general Enriques surfaces.
Identifiability of Chemical Reaction Networks with Intrinsic and Extrinsic Noise from Stationary Distributions

Many biological systems can be modeled as a chemical reaction network with unknown parameters. Data available to identify these parameters are often in the form of a stationary distribution, such as that obtained from measurements of a cell population. In this work, we introduce a framework for analyzing the identifiability of the reaction rate coefficients of chemical reaction networks from stationary distribution data. Working with the linear noise approximation, which is a diffusive approximation to the chemical master equation, we give a computational procedure to certify global identifiability based on Hilbert's Nullstellensatz. We present a variety of examples that show the applicability of our method to chemical reaction networks of interest in systems and synthetic biology, including discrimination between possible molecular mechanisms for the interaction between biochemical species.
Polarization measurement for the dileptonic channel of 
W+W−
 scattering using generative adversarial network

1 College of Physics, Sichuan University, Chengdu 610065, China Abstract Measuring polarization modes of the W+W− scattering reveals the interactions of the Higgs boson as well as new neutral states that are related to the standard model electroweak symmetry breaking. The dileptonic channel suffers from less background, but the kinematics of final states can not be fully reconstructed due to the presence of two neutrinos. We propose neural networks to establish the mapping between distributions of measurable quantities and the distributions of the lepton angles in W boson rest frames. New physics contribution and collision energy can largely affect the kinematic properties of the W+W− scattering beside the lepton angles. To make the network in ignorance of those information, the loss function is modified in two different ways. For the W+W− scattering process, we show that the networks are promising in reproducing the lepton angle distributions. And the precision of fitted polarization fractions obtained from the network predictions are comparable to that obtained with truth lepton angle. Although the best fit values of polarization fractions are not changed much after including the background uncertainty, the precisions are substantially reduced. Our trained models are available at GitHub .
Pilot-Based Unsourced Random Access With a Massive MIMO Receiver, Interference Cancellation, and Power Control

We consider the unsourced random access problem on a Rayleigh block-fading AWGN channel with multiple receive antennas. Specifically, we treat the slow fading scenario where the coherence blocklength is large compared to the number of active users and a message can be transmitted in a single fading coherence block. Unsourced random access refers to a form of grant-free random access where users are constrained to use the same codebook and therefore are a priori indistinguishable. The receiver must recover the list of transmitted messages up to permutations. In this paper, we propose an approach based on splitting the user messages into two parts. First, a small block of bits selects a relatively short codeword from a common “pilot” codebook. Then the remaining message bits are encoded by a standard block code for the Gaussian channel. The receiver makes use of a multiple measurement vector approximate message passing (MMV-AMP) algorithm to estimate the active user channels from the “pilot” part, and then uses the estimated channels to perform coherent maximum ratio combining (MRC) to decode the second part. We provide an accurate closed-form approximated analysis of the proposed scheme. Furthermore, we analyze the MRC decoding when successive interference cancellation is performed over groups of users, striking an attractive tradeoff between complexity and performance. Finally, we investigate the impact of power control policies, taking into account the unique nature of massive random access. As a byproduct, we also present an extension of the MMV-AMP algorithm which allows pathloss coefficients to be treated as deterministic unknowns by performing maximum likelihood estimation in each step of the MMV-AMP algorithm.
A note on gradient Ricci soliton warped metrics

In this note, we prove triviality and nonexistence results for gradient Ricci soliton warped metrics. The proofs stem from the construction of gradient Ricci solitons that are realized as warped products, from which we know that the base spaces of these products are Ricci–Hessian type manifolds. We study this latter class of manifolds as the most appropriate setting to prove our results.