Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of phosphorus and sulphur on yield, yield attributes and biochemical composition of brinjal

A pot experiment was conducted in the net house of the department of Agricultural Chemistry, Bangladesh Agricultural University (BAU), Mymensingh to observe the influence of phosphorus (P) and sulphur (S) on yield, yield attributes and biochemical composition of brinjal cv. BARI brinjal-8 during the period from October, 2011 to May, 2012. The experiment was laid out in completely randomized design with 12 treatments and 3 replications using four (0, 30, 60 and 90 kg P ha) levels of P and three (0, 15 and 30 kg S ha) levels of S. The combinations of P and S were P0S0, P0S15, P0S30, P30S0, P30S15, P30S30, P60S0, P60S15, P60S30, P90S0, P90S15 and P90S60. Urea, muriate of potash, boric acid, zinc oxide, cowdung and poultry manure were applied with all the treatments as basal dose according to the fertilizer recommendation guide. The study revealed that yield and yield attributes such as plant height, no. of branches, no. of leaves, no. of flowers, no. of fruits, fruit length, fruit diameter, fruit weight, vitamin C and protein content of brinjal were significantly influenced by P, S and their interactions. Plant height, number of branches, leaves, flowers and fruits were increased 90, 60, 120 and 105 days after transplanting (DAT), respectively and then either decreased or remained constant. The highest values of all the parameters were obtained from P60 and S30 treatments except the vitamin C content which was maximum in P30 and S15 treatment. The results suggest that P and S @ 60 and 30 kg ha along with basal doses of other inorganic fertilizers and organic manures can be used to increase brinjal yield and vitamin C content under the agro climatic condition of BAU.
Errata of “On a definition of multi-Koszul algebras” by E. Herscovich and A. Rey

Some time after the publication of our article [3] we noticed that Lemma 3.16 in the mentioned article is incorrect. A simple counterexample is given by the sequence 0→ A→ k of graded left A-modules. The lemma however holds –but with another proof– if one further imposes that the modules L, M and N are free, and In/In+1 is a free A/I-module for every n ∈N (see [1], Lemme 1.6). The last assumption is verified if I = A>0, but unfortunately not in general. As a consequence, the new correct version of Theorem 3.17 should only state that condition (ii) implies (i), and the converse holds if As is s-Koszul, for all s ∈ S. An algebra A = T V /〈R〉 satisfying the condition (ii) in Theorem 3.17 will be called restricted multi-Koszul. In the remaining results in Section 3 and all of the results in Subsections 5.4 and 5.5 of [3] concerning multi-Koszul algebras, one should further impose that they are restricted in the previous sense, so the given proofs still hold. Despite the previous drawback, the results of [3] that are (in our opinion) the most interesting still hold, and they were proved using completely different tools in [2]. More precisely, in the mentioned article we proved that Corollary 3.23 in [3] holds for any multi-Koszul algebra (see [2], Thm. 4.1), and that the description of the A∞-algebra structure on the Yoneda algebra of a multi-Koszul algebra stated in Remark 3.25 of [3] also holds (see [2], Thm. 4.8). Additionally, we would like to point out that (the proof of) Theorem 4.1 in [3] is still true, using the new version of Lemma 3.16 stated previously.
How does macroprudential regulation change bank credit

We analyze a variant of the Diamond-Dybvig (1983) model of banking in which savers can use a bank to invest in a risky project operated by an entrepreneur. The savers can buy equity in the bank and save via deposits. The bank chooses to invest in a safe asset or to fund the entrepreneur. The bank and the entrepreneur face limited liability and there is a probability of a run which is governed by the bank’s leverage and its mix of safe and risky assets. The possibility of the run reduces the incentive to lend and take risk, while limited liability pushes for excessive lending and risk-taking. We explore how capital regulation, liquidity regulation, deposit insurance, loan to value limits, and dividend taxes interact to offset these frictions. We compare agents welfare in the decentralized equilibrium absent regulation with welfare in equilibria that prevail with various regulations that are optimally chosen. In general, regulation can lead to Pareto improvements but fully correcting both distortions requires more than one regulation.
The Joint Distribution of Income, Wealth and Consumption in Germany

How wealth, income and consumption are jointly distributed, is an important topic in the empirical micro-economic literature and the theoretical literature using heterogeneous agent models. Most papers, due to a lack of data, focus on inequality in at most two dimensions. We analyse the joint distribution of income, wealth and consumption using micro-data from the German wealth survey. While wealth and income is directly collected in the wealth survey, total consumption is calculated using information on active savings flows and non-durable consumption is imputed. We find that net wealth and net saving flows are much more unequally distributed than income and consumption. The income and consumption distributions are more closely linked than the wealth and consumption distribution. Another finding is that the joint distribution of net wealth, net income and total consumption overlap much stronger at the bottom of the distribution than at the top. These results improve our understanding of inequality in the largest Euro area economy and furthermore add new dimensions to measuring inequality which has been impeded by data limitations in the past.
Morphometric Measurements of

Morphometric measurements of martian valley networks using Mars Orbiter Laser Altimeter (MOLA) topographic data yield mean valley width values of x σ ± : 2040 ± 1548 m and depth values of x σ ± : 109 ± 137 m. Our analysis of changes in valley shape with latitude and wall slope with depth indicate infilling and mass wasting processes have not greatly altered the original valley shape; thus, valley network morphometry is dominantly due to channel formation mechanisms. Both Uand V-shape profiles are observed, commonly within the same valley network system. The average U-shape valley is slightly deeper (18 m) and significantly wider (1313 m) than its V-shape counterpart. Valley networks have decreasing width-to-depth ratios and increasing wall slopes as valley depth increases. Our observations are consistent with a two-phase valley network formation model proposed by Baker and Partridge [1986]. (1) Valleys initially form via surface runoff, a process that creates V-shape profiles and quasidendritic form. The observed linear correlation of top width and depth (below 125 m depth) suggests the depth of vertical incisement governs top width. (2) Reactivation of the same valleys by headward extending sapping processes widens the channel to form U-shape cross-sections in downstream reaches. The availability of liquid water within a few hundred meters of the surface appears to be a necessary requirement for valley network formation. Mean valley depth decreases by ~50 m from equatorial to higher latitudes (~50°), contrary to the relationship predicted if the sapping depth was governed by the ice-water boundary. Deeper equatorial valley networks may result from latitudinal variations in the availability of water or formation efficiency.
CLPred: a sequence-based protein crystallization predictor using BLSTM neural network.

MOTIVATION Determining the structures of proteins is a critical step to understand their biological functions. Crystallography-based X-ray diffraction technique is the main method for experimental protein structure determination. However, the underlying crystallization process, which needs multiple time-consuming and costly experimental steps, has a high attrition rate. To overcome this issue, a series of in silico methods have been developed with the primary aim of selecting the protein sequences that are promising to be crystallized. However, the predictive performance of the current methods is modest. RESULTS We propose a deep learning model, so-called CLPred, which uses a bidirectional recurrent neural network with long short-term memory (BLSTM) to capture the long-range interaction patterns between k-mers amino acids to predict protein crystallizability. Using sequence only information, CLPred outperforms the existing deep-learning predictors and a vast majority of sequence-based diffraction-quality crystals predictors on three independent test sets. The results highlight the effectiveness of BLSTM in capturing non-local, long-range inter-peptide interaction patterns to distinguish proteins that can result in diffraction-quality crystals from those that cannot. CLPred has been steadily improved over the previous window-based neural networks, which is able to predict crystallization propensity with high accuracy. CLPred can also be improved significantly if it incorporates additional features from pre-extracted evolutional, structural and physicochemical characteristics. The correctness of CLPred predictions is further validated by the case studies of Sox transcription factor family member proteins and Zika virus non-structural proteins. AVAILABILITY AND IMPLEMENTATION https://github.com/xuanwenjing/CLPred.
Data vs Collateral

Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that the wider use of big tech credit could reduce the importance of the collateral channel but, at the same time, make lending more reactive to changes in firms’ business activity.
Anesthetic Preconditioning An Anesthesiologist’s Tale

Mimics Ischemic Preconditioning via Activation of K ATP Channels: Reduction of Size with an Acute ABSTRACT: Background: Thehypothesesthatisofluranedirectlyprecondi-tions myocardium against infarction via activation of adenosine triphosphate–regulated potassium channels and that the protection afforded by isoflurane is associated with a short-term mem-oryphasesimilartothatofischemicpreconditioningweretested. Methods: Barbiturate-anesthetized dogs (n (cid:1) 71) underwent
Detecting Outliers in High Dimensional Categorical Data through Feature Selection

: Extensive use of qualitative features for describing categorical data leads to high dimensional scenario in which outlier detection turns out to be a challenging task due to data sparseness. The curse of dimensionality has been well addressed in the case of numerical data by developing various feature selection methods, whereas the categorical data scenario is actively being explored. As the outlier detection problem is generally known to be unsupervised in nature due to lack of knowledge about various types of outliers, a novel unsupervised feature selection method is proposed in this paper for effective detection of outliers in categorical data. The proposed algo-rithm establishes the relevance and the redundancy of a feature through the entropy and the mutual information computation. By measuring the inherent redundancy of the features describing a data set, a threshold is applied on the allowed maximum redundancy of a candidate feature with already selected sub-set of features. This way of selecting features among the relevant ones results in a feature subset with less redundancy. The performance of the proposed algorithm in comparison with the information gain based feature selection shows its effectiveness for outlier detection. The efﬁcacy of the proposed algorithm is demonstrated on various high-dimensional benchmark data sets employing two existing outlier detection methods
Profit management in the case of financial distress and global volatile market behaviour: Evidence from Borsa Istanbul Stock Exchange

The purpose of this paper is to find out how firms manage earnings under volatile market behaviour and financial distress in Borsa Istanbul Stock Exchange (BIST). We used in order to determine four discretionary accruals models such as Jones, Adjusted-Jones, Kasznik, and Kothari. 171 listed companies in BIST for the annual data between 2006 and 2016 were used. Model was analysed by using panel data methods such as fixed effects, random effects estimation. Our results indicate that nondiscretionary accruals, discretionary accruals, firm size and leverage by the future profit value are significant determinants of earning management behaviour in Turkey. However, we do not find a significant relation between future profitability and volatile market index, financial distress. This research will lead the way of accounting standard setters and policy makers to understand earning management activities under volatile market behaviour and financial distress in Borsa Istanbul Stock Exchange BIST.
Optical variability of unidentified Active Galactic Nuclei with blazar characteristics in the Fermi-2LAC catalogue

BL Lacartae objects (BL Lacs) and flat spectrum radio quasars (FSRQs) exhibit variability in the continuum flux at multiple wavelengths on timescales of hours to days. We report on optical photometric observations of 8 unidentified Active Galactic Nuclei (AGN) from the second FermiLAT catalogue of AGN, that shows potential blazar characteristics. We mainly focus our attention on the intra-day variability (IDV) with timescales of a few minutes to within a day and the short term variability (STV) on timescales of a few days to months. Variability on these timescales are known to be the result of the shock zones within the jet, hot spots and/or instabilities in the accretion disk. Preliminary differential photometric results, for the 8 target sources, obtained with the SAAO 1.9-m Sutherland High-Speed Optical Camera (SHOC) during December 2014 and May 2015, are discussed. Currently, optical long term monitoring of the entire target sample using the Watcher Robotic Telescope is undertaken to determine magnitudes in the RVi filters, as well as radio observations with the the HartRAO 26-m radio telescope to construct light curves in order to study the variability.
SecureBP from Homomorphic Encryption

We present a secure backpropagation neural network training model (SecureBP), which allows a neural network to be trained while retaining the confidentiality of the training data, based on the homomorphic encryption scheme. We make two contributions. The first one is to introduce a method to find a more accurate and numerically stable polynomial approximation of functions in a certain interval. The second one is to find a strategy of refreshing ciphertext during training, which keeps the order of magnitude of noise at .
CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Management

The outbreak of COVID-19 raises attention from the researchers from various communities. While many scientific articles have been published, a system that can provide reliable information to COVID-19 related questions from the latest academic resources is crucial, especially for the medical community in the current time-critical race to treat patients and to find a cure for the virus. To address the requests, we propose our CAiRE-COVID, a neural-based system that uses open-domain question answering (QA) techniques combined with summarization techniques for mining the available scientific literature. It leverages the Information Retrieval (IR) system and QA models to extract relevant snippets from existing literature given a query. Fluent summaries are also provided to help understand the content in a more efficient way. Our system has been awarded as winner for one of the tasks in CORD-19 Kaggle Challenge. We also launched our CAiRE-COVID website for broader use. The code for our system is also open-sourced to bootstrap further study.
Effect of phosphorus, FYM and bio-fertilizer on growth, yield attribute, yield and quality of summer greengram (Vigna radiate L.)

A field experiment was conducted during 2018 to study the effect of phosphorus, FYM and bio-fertilizer on yield and quality of greengram. There were twelve treatments comprising of three phosphorus levels [Control (P0), 20 kg P2O5 ha (P1) and 40 kg P2O5 ha (P2)] combined with two FYM levels [control (F0) and 5 t FYM ha(F1)] along with two levels of bio-fertilizer [control (B0) and PSB inoculation (B1)]. Phosphorus applied in the form of SSP and PSB as seed inoculation. The experiment was laid out in factorial RBD with three replications. The recommended dose of N was applied uniformly to all the treatments. Seed yield and stover yield of greengram was significantly increased by the phosphorus, FYM and bio-fertilizer treatments. The increased in seed yield due to P2 and P1 over P0 (797.6 kg ha) was 18.98 and 10.97 per cent, respectively. The treatment F1 increased the seed yield by 14.55 per cent and B1 increased 12.65 per cent, over their respective control F0 (817.7 kg ha) and B0 (825.0 kg ha ). Similar trend in stover yield was noted by phosphorus, FYM and bio-fertilizer treatments. The interaction of P x F x B effect was significant on seed and stover yield indicate that nutrient use efficiency of P was higher when phosphorus was applied along with organic FYM @ 5 t ha and PSB inoculation to the seed. Growth and yield attribute like plant height, number of nodules per plant, 100 seed weight, seeds per pod, and pods per plant were studied. Quality parameters viz. protein content and protein yield studied. Application of organics P2 and P1, as well as FYM and PSB inoculation favourably influenced quality parameters in comparison to their respective control. A synergistic interaction of P x F x B on protein content indicates improvement in quality of greengram.
Uncertainty of GDP Gap in Real Time: The Case of Japan

GDP gap is the most watched economic statistics after 90th in JAPAN. In fact, the certainty of the government forecast on the economic condition is mainly judged by the preliminary GDP but not by the revised ones. We think that most misleading problems around the GDP were occurred due to the undesirable characteristics of uncertainty of the preliminary GDP. Though almost all observers inspect economic conditions by preliminary GDP, however, few know the statistical property of errors including the estimated GDP. We have estimated the reliability of the GDP gap based on the Real-Time data. Main conclusions as follow; 1) The difference (the revision width) between the real-time GDP gap and ex post GDP gap is the same order of magnitude as the GDP gap itself. 2) The real-time gap is almost underestimated against final gap until the 1990s, but after the 1990s, the real-time gap is almost overestimated. 3) Assuming that later estimates are more accurate than earlier ones, the revisions reflect improvements in accuracy relative to earlier estimates. But the revisions of GDP are more like measurement error than like efficient forecast. That is, early GDP is quiet different from final GDP. Our findings have important suggestion for the use of preliminary GDP by policymaker and forecasters. If the policymaker decides budget policy with using the preliminary GDP, it is probable for best selection of policy to be no good. The estimates of the GDP gap have attracted relatively little to the revision of the GDP data. However, actually, the GDP gap which was estimated at real-time is different from the GDP gap on the ex post. We can not ignore the influence of the revision of the GDP data
The Challenges with Rules-Based Policy Implementation

I discuss challenges in implementing a rule-based monetary policy (RBP) regime. Many of the arguments for and against RBP are similar to ones prominent 20 years ago in debates over inflation targeting. I draw a distinction, common in the literature on inflation targeting, between a strict and a flexible RBP regime, highlighting the trade-offs involved in moving towards a stricter regime. Under flexible regimes, deviations from the reference rule are allowed, and I derive the rule for deviating from the rule. Stochastic, transitory fluctuations in non-rulable variables, such as the long-run equilibrium real interest rate, are shown to increase the volatility of expected future inflation around target under a level rule, while permanent shifts threaten credibility as either policymakers must act consistent with the rule or with achieving the inflation target. The best simple rule depends on policymakers’preferences, which may make it diffi cult for a policy committee to agree if the central bank is charged with picking the rule. Turning to practical issues, I discuss how a desire to promote transparency and accountability can help one in choosing between alternative rules. ∗Prepared for the 2017 Annual Conference of the Federal Reserve Bank of Boston, Are Rules Made to be Broken? Discretion and Monetary Policy, October 13-14, 2017. I would like to thank, without implicating, Mike Dooley, Andy Levin, Athansios Orphanides, and Glenn Rudebusch for helpful discussions, and Alan Ledesma for excellent research assistance. †Department of Economics, University of California, Santa Cruz, walshc@ucsc.edu.
Ja n 20 06 Eigenvalue distributions for some correlated complex sample covariance matrices

The distributions of the smallest and largest eigenvalues for the matrix product ZZ, where Z is an n×m complex Gaussian matrix with correlations both along rows and down columns, are expressed as m × m determinants. In the case of correlation along rows, these expressions are computationally more efficient than those involving sums over partitions and Schur polynomials reported recently for the same distributions.
Multivalued φ-Contractions on Extended b-Metric Spaces

In this paper, we have established some fixed-point results for the class of multivalued - contractions in the setting of extended - metric space. An example is furnished to show the validity of our results. The results we have obtained generalize/extend many recent results by Asl, Bota, Samreen et al., and those contained therein.