Miracle-dz/UniFAR-FTUs huggingface dataset:
Laser-activated drug implant for controlled release to the posterior segment of the eye

The current standard of care for posterior segment eye diseases, such as age-related macular degeneration and diabetic macular edema, is frequent intravitreal injections or sustained-release drug implants. Drug implants have side effects due to the burst release of the drugs, and their release cannot be easily controlled after implantation. Present study attempts to develop a dosage-controllable drug delivery implant which consists of a nanoporous biodegradable PLGA capsule and light-activated liposomes. Controllable drug release from the implant was achieved by using pulsed near-infrared (NIR) laser both in vitro and in vivo. The in vitro drug release kinetics from two different initial dose implants, 1000 μg and 500 μg, was analyzed by fitting zero order and first order kinetics, as well as the Korsmeyer-Peppas and Higuchi models. The 1000 μg and 500 μg implants fit the first-order and zero-order kinetics model, respectively, the best. The multiple drug releases in the vitreous was determined by in vivo fluorimeter, which was consistent with the in vitro data. The dose released was also clinically relevant. Histology and optical and ultrasound imaging data showed no abnormality in the eyes received implant treatment suggesting that the drug delivery system was safe to the retina. This on-demand dose-controllable drug delivery system could be potentially used for long-term posterior eye disease treatment.
The preventative benefit of group diversification on group performance decline: An investigation with latent growth models

Integrating the open systems perspective of groups and the contingency approach to diversity, we study how group diversification (i.e. a process in which a group becomes more diverse over time as members join and/or leave the group) affects group performance change in an adverse task environment characterized with uncertainty and risks for failure. We argue that diversification benefits performance by reducing group performance decline in adversity. Group size increase, however, attenuates this preventative benefit of group diversification. Focusing on organizational tenure and gender, we studied 279 sales groups (3,277 individuals) in a large German financial consulting company from 2004 to 2008. In this period, a national legislative change prompted the company to withdraw its star product from the market and presented adversity to the sales groups. Results from latent growth models (LGMs) overall support our arguments. This research extends the (conditional) beneficial view of diversity from a static theoretical space about groups’ being diverse to a dynamic one about groups’ becoming diverse.
Weighted User Goal Sampling for Dialog Policy Learning

A deep reinforcement learning algorithm has been widely used for learning dialog policy in a task-oriented dialog system. Dialog agent collects training data and improves its policy by interacting with users. Interact with real users is time-consuming and not realistic. Consequently, we usually build a user simulator instead of a real user. At the beginning of each dialogue, the simulator will sample a user goal extract from training data. Then the simulator will communicate with the dialog agent to accomplish this user goal. The existing user simulator usually samples this user goal randomly. This will cause the dialog agent to waste a lot of time to learn what it already learned. To solve this problem, we propose two user goal weighting methods which give relatively large weight to the user goal the current dialog agent can’t accomplish. This lets the dialog agent pay more attention to those user goals. Experiment result in a movie-ticket booking task shows that the proposed weighted user goal sampling method can effectively accelerate the policy learning progress compares to the random sampling method.
HYDROGELS THE THREE DIMENSIONAL NETWORKS: A REVIEW

Hydrogel products constitute polymeric materials as a group, the hydrophilic structure which renders them the capability of holding large amounts of water in their 3-dimensional networks. Extensive employment of those products during a number of commercial and environmental areas of application is taken into account to be of prime importance. Needless to say, natural hydrogels were gradually replaced by synthetic types thanks to their higher water absorption capacity, long service life, and wide sorts of raw chemical resources. Literature on this subject was found to be expanding, especially within the scientific areas of research. However, variety of technical reports publications and handling hydrogel products from the points of view of engineering were examined to overview technological aspects covering this growing the field of research. the first objective of this text is to review the literature concerning classification of hydrogels on different bases, chemical characteristics and physical characteristics of those products, and technical feasibility of their best utilization. It also involved the technologies adopted for hydrogel production along-side process and design implications, optimized conditions, and the block diagrams of the preparation process. Recent forms of hydrogel material generations are also presented in some details that are innovative in nature.
Central bank’s supervision on commercial banks’ credit business an exploratory post-epidemic-based research

The epidemic of COVID-19 broke out, domestic economy suffered a heavy setback, the Central Bank of China launched a series of policies against this backdrop, aiming to stimulate the economy. However, some investors speculate from the loose loans in real estate, which makes the funds policy originally used for stimulating the real economy to be artificially drained into the real estate market, further resulting in the imbalance of social supply. To solve this problem, from the perspective of the central bank and with the use of literature research and other methods, this paper makes research on analyzes the central bank’s credit supervision on commercial banks. Study shows that information collection and monetary policy are the problems with central bank. Through big data technology and monetary policy into the new reference index two angles to try to solve the problem. It aims to effectively strengthen the efficiency and level of central bank’s supervision. Meanwhile it can provide corresponding theories and references for subsequent research. The limitation of this study is that there is no specific application supporting the analysis. Otherwise the paper would be more applicable in practice. Therefore, this problem needs to be further studied and solved.
A systematic synthesis on the context reliant performance of organic farming

The argument on whether organic agriculture can produce enough food to cater for the world’s growing population has been debated severally by various scholars. While organic farming is rapidly increasing, the paramount question is to know how organic farming can yield to viable systems of producing food. This paper aims to identify the benefits and context reliant performance of organic farming as a development trail to sustainable farming. Gathering of articles from different peer review journals was used to develop this paper. The findings of this paper show that organic farming has many potential benefits including higher biodiversity, improved soil, and enhanced profitability as well as supporting local production, with locally produced source inputs. The findings also show that organic farming is environmentally friendly, promotes distribution of resources, and is economically and socially acceptable to mankind. In order to have a clear view of the contribution that organic farming plays on sustainability, further research is necessary.
Robust Denoising of Cryo-EM Images via β-GAN

The cryo-electron microscopy (Cryo-EM) becomes popular for macromolecular structure determination. However, the 2D images which Cryo-EM detects are of high noise and often mixed with multiple heterogeneous conformations and contamination, imposing a challenge for denoising. Traditional image denoising methods and simple Denoising Autoencoder can not remove Cryo-EM image noise well when the signal-noise-ratio (SNR) of images is meager and contamination distribution is complex. Thus it is desired to develop new effective denoising techniques to facilitate further research such as 3D reconstruction, 2D conformation classification, and so on. In this paper, we approach the robust denoising problem for Cryo-EM images by introducing a family of Generative Adversarial Networks (GAN), called β-GAN, which is able to achieve robust estimate of certain distributional parameters under Huber contamination model with statistical optimality. To address the challenge of robust denoising where the traditional image generative model might be contaminated by a small portion of unknown outliers, β-GANs are exploited to enhance the robustness of denoising Autoencoder. The method is evaluated by both a simulated dataset on the Thermus aquaticus RNA Polymerase (RNAP) and a real dataset on the Plasmodium falciparum 80S ribosome dataset (EMPIRE-10028), in terms of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and 3D Reconstruction as well. The results show that equipped with some designs of β-GANs and the robust ℓ1-Autoencoder, one can stabilize the training of GANs and achieve the state-of-the-art performance of robust denoising with low SNR data and against possible information contamination. Our proposed methodology thus provides an effective tool for robust denoising of Cryo-EM 2D images, which is helpful for 3D structure reconstruction.
A Statistical Evaluation of the Frictional Pressure Losses Correlations for Slurry Flow

Hydraulic fracturing has increased immensely in recent years. An accurate prediction of frictional pressure losses of fracturing slurries is crucial for successful treatment and avoiding premature screen-out or even treatment failure. Scarce data and lack of theoretical basis of slurry flow, especially in coiled tubing, has led to very limited number of correlations that are available to predict slurry frictional pressure losses. Yet, the accuracy of the available correlations is still questionable. The current paper presents a statistical comparative analysis of the available frictional pressure losses correlations for slurry flow in straight and coiled tubing employing the recently introduced math modeling technique giving weight for the models known as AIC (Akaike information criterion). With the help of AIC, the authors evaluated the available correlations to examine their accuracy. The results show that none of the available correlations can accurately predict friction pressure losses of slurries. The correlations show some reasonable accuracy within a very limited data range. However, they failed outside this range indicative of their poor applicability. AIC shows how much information is lost when using these correlations which can lead to erroneous results, and even job failure. This fact keeps the gates widely opened for more in-depth experimental, analytical, and theoretical analysis for better understanding of flow behavior with fracturing slurries aiming at developing a more realistic correlation to predict their frictional pressure losses. This paper represents the authors’ first step toward developing such correlation, with the application of information theory and AIC.
The DNA damage inducible lncRNA SCAT7 regulates genomic integrity and topoisomerase 1 turnover in lung adenocarcinoma

Abstract Despite the rapid improvements in unveiling the importance of lncRNAs in all aspects of cancer biology, there is still a void in mechanistic understanding of their role in the DNA damage response. Here we explored the potential role of the oncogenic lncRNA SCAT7 (ELF3-AS1) in the maintenance of genome integrity. We show that SCAT7 is upregulated in response to DNA-damaging drugs like cisplatin and camptothecin, where SCAT7 expression is required to promote cell survival. SCAT7 silencing leads to decreased proliferation of cisplatin-resistant cells in vitro and in vivo through interfering with cell cycle checkpoints and DNA repair molecular pathways. SCAT7 regulates ATR signaling, promoting homologous recombination. Importantly, SCAT7 also takes part in proteasome-mediated topoisomerase I (TOP1) degradation, and its depletion causes an accumulation of TOP1–cc structures responsible for the high levels of intrinsic DNA damage. Thus, our data demonstrate that SCAT7 is an important constituent of the DNA damage response pathway and serves as a potential therapeutic target for hard-to-treat drug resistant cancers.
IMPROVING A POSTERIORI SPATIAL DISCRETIZATION ERROR ESTIMATION FOR SN TRANSPORT BY SINGULAR CHARACTERISTICS TRACKING

Previously, we have developed a novel spatial discretization error estimator, the “residual source” estimator, in which an error transport problem, analogous to the discretized transport equation, is solved to acquire an estimate of the error, with a residual term acting as a fixed source. Like all error estimators, the residual source estimator suffers inaccuracy and imprecision in the proximity of singular characteristics, lines across which the solution is irregular. Estimator performance worsens as the irregularities become more pronounced, especially so if the true solution itself is discontinuous. This work introduces a modification to the residual approximation procedure that seeks to reduce the adverse effects of the singular characteristics on the error estimate. A partial singular characteristic tracking scheme is implemented to reduce the portion of the error in the numerical solution born by irregularities in the true solution. This treated numerical solution informs the residual approximations. The partial singular characteristic tracking scheme greatly enhances the numerical solution for a problem with prominent singular characteristics. The residual approximation and resultant residual source error estimate are likewise improved by the scheme, which only incurs the computational cost of an extra inner iteration.
Performance of Wild Non-Conventional Yeasts in Fermentation of Wort Based on Different Malt Extracts to Select Novel Starters for Low-Alcohol Beers

Nowadays, the increasing interest in new market demand for alcoholic beverages has stimulated the research on useful strategies to reduce the ethanol content in beer. In this context, the use of non-Saccharomyces yeasts to produce low-alcohol or alcohol-free beer may provide an innovative approach for the beer market. In our study, four wild non-Saccharomyces yeasts, belonging to Torulaspora delbrueckii, Candida zemplinina and Zygosaccharomyces bailii species, were tested in mixed fermentation with a wild selected Saccharomyces cerevisiae strain as starters for fermentation of different commercial substrates used for production of different beer styles (Pilsner, Weizen and Amber) to evaluate the influence of the fermentative medium on starter behaviour. The results obtained showed the influence of non-Saccharomyces strains on the ethanol content and organoleptic quality of the final beers and a significant wort–starter interaction. In particular, each starter showed a different sugar utilization rate in each substrate, in consequence of uptake efficiency correlated to the strain-specific metabolic pathway and substrate composition. The most suitable mixed starter was P4-CZ3 (S. cerevisiae–C. zemplinina), which is a promising starter for the production of low-alcohol beers with pleasant organoleptic characteristics in all the tested fermentation media.
A dropout prediction method based on time series model in MOOCs

In recent years, MOOCs has enjoyed great popularity due to its convenience and openness. However, with the development of MOOCs, the high dropout rate has aroused extensive attention. By analyzing the data of students’ behavior and then predicting whether students are at risk of dropout, it can improve the course completion rate. Most of the existing methods relying on feature engineering and the sequential characteristic of data is not effectively utilized. In this paper, we propose a time series model named CNN-LSTM-ATT, which focuses more on local valid information and temporal information of the data. Through extensive experiments on a public dataset, it shows that the proposed model can effectively predict students’ dropout behavior.
Milk feeding quantity and feeding frequency: effects on growth performance, rumen fermentation and blood metabolites of Holstein dairy calves

Abstract The aim of this study was to investigate interactions between milk feeding quantity (FL) and feeding frequency (FF) on intake, growth performance, rumen development and blood metabolites in dairy calves. A total of 48 Holstein calves (n = 12 calves per treatment: 6 males and 6 females) were randomly assigned to one of four treatments, including (1) two low plane of milk feeding (2 meals/d, LPM-2×; 3 meals/d, LPM-3×; total milk intake = 210 L) and two high plane of milk feeding (2 meals/d, HPM-2×; 3 meals/d, HPM-3×; total milk intake = 371 L). Calves fed HPM had higher BW, ADG, blood glucose and triglycerides concentration during the preweaning. Calves fed HPM received more ME, total DMI and ate less starter than LPM calves during preweaning. Regardless of the milk feeding quantity, with increasing FF, starter intake, total DMI and ME were reduced without a negative effect on ADG. Calves fed 3 times/d compared with 2 times/d had a lower final hip width. Calves fed HPM had higher ruminal pH and molar proportion of acetate and acetate to propionate ratio, but less molar proportion of propionate and butyrate and total VFA compared with calves fed LPM on d 35 of the study. Interaction between milk feeding level and feeding frequency was observed for plasma glucose concentration with HPM-3× calves having the greatest value at d 35 of study. In conclusion, at both levels of milk feeding, calves did not benefit from the increased feeding frequency, but calves benefitted from HPM. Highlights Calves did not benefit from increased milk feeding frequency at either low or high plane of milk feeding. The performance of calves on low plane of milk feeding was constrained by the low nutrient intake and not the feeding frequency. Regardless of plane of milk feeding, feeding 3 meals/d reduced total DM and starter intake with no detrimental effects on overall average daily gain.
The Causality Relationship Between Financial Sector Profitability and the Botswana Economy

Previous research has lamented on both the importance and the symbiotic relationship between financial sector performance and the state of a country’s economy. Findings of these studies are generally in concert in that the performance of the financial sector is intertwined with macroeconomic indicators. There is, however, a difference in opinion on the precise nature of the relationship between these sets of variables. This difference of opinion has led to the development of three parallel strands of theory: demand-driven relationship; supply-driven relationship; and economic developmental stage. To the extent that an understanding of the precise nature of the relationship between these critical variables would promote economic growth, it was found imperative to investigate the phenomenon in the context of a developing economy. This paper examines the causal relationship between the financial sector index and GDP in Botswana. The study uses data over a period of 10 years (2003-2013). This study timeframe is significant because previous research does not incorporate the critical periods in financial markets history over which the global economy experienced the economic cycle of the boom years (2003-2006), followed by a recession (2007-2010) and finally the recovery period (2010 and beyond). This financial cycle provides a unique opportunity for new insights into how financial sector performance relates to the economy. The findings are suggestive of an existence of a stable long-run relationship between the financial sector and the economy. In addition, the results show that the economy granger-cause the financial sector index with no reverse causality observed. Policy implications of these findings are discussed in the paper.
Managing global supply chain risks: effects of the industry sector

ABSTRACT Despite the abundance of articles addressing global supply chain risks and their mitigation strategies, there are surprisingly few insights into how different industries manage global supply chain risks while internationalising abroad. There are conflicting results from previous researches that specific global supply chain risk management practices work in one industry but not in others. We believe that in each industry sector, the global supply chain risks and their mitigation strategies differ. We used profile deviation and ideal profile methodology to identify top performers in three industry sectors (Audit, Finance and Consulting, Automotive, and IT and Software) and evaluated their best practices towards managing global supply chain risks. This study used an online survey to gather information on how Indian executives across these industries manage global supply chain risks during their internationalisation process and found the ‘ideal’ risk mitigation profiles for all three industries. These findings provide new insights to practitioners as they will serve as a useful reference tool for Indian executives planning to internationalise.
Prospects for Handling 5G Network Security: Challenges, Recommendations and Future Directions

The cellular network is the today’s requirement, and telecommunication industries are in creatin new infrastructures and technologies to give more benefits to the end users. New generation like 5G are have various benefits as compared to old generations (1G to 4G). 5G system flexible, provides lower latency, interoperable, and 10 time faster than 4G that helps all stakeholder of 5G. As the 5G network is growing and many challenges will be arising with the development in the technologies. This paper includes background of 5G network and security challenges, recommendations and some future direction that an be considered by the organization before developing and integrating 5G. We finally give some directions to overcome these issues.