Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlations and path analysis studies on yield and its components in F2 generation of vegetable Indian bean (Lablab purpureus L.) sweet

The present research work was carried out at Navsari Agricultural University, Navsari during the rabi-2017 to study correlations among quantitative traits and their direct and indirect effect on pod yield per plant in F2 populations (N1-05-19 x N1-13-465, N1-13-465 x N1-08-203 and N1-05-19 x N1-08-225) of Indian bean. Correlation analysis revealed that, pod yield per plant showed positive and significant correlation with plant height at first picking, branches per plant at first picking, pods per plant, pods per cluster and average pod weight in all the three crosses. This indicated the simultaneous improvement of these characters by selection is possible. Path coefficient analysis revealed that plant height at first picking, pods per plant, average pod weight and fibre content had direct positive effects on pod yield per plant for all the crosses. This indicated that these characters played an important role in expressing high pod yield. Pod length exhibited direct positive effects on pod yield in crosses NI-05-19×NI-13-465 and NI-05-19×NI-08-225 while, shelling ratio and protein content depicted positive direct effect on pod yield per plant in crosses NI-05-19×NI-13-465 and NI-13-465×NI-08-203, indicating that direct selection for these characters may bring about an overall improvement in the pod yield of Indian bean.
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes

Motivated by the transformative impact of deep neural networks (DNNs) in various domains, researchers and anti-virus vendors have proposed DNNs for malware detection from raw bytes that do not require manual feature engineering. In this work, we propose an attack that interweaves binary-diversification techniques and optimization frameworks to mislead such DNNs while preserving the functionality of binaries. Unlike prior attacks, ours manipulates instructions that are a functional part of the binary, which makes it particularly challenging to defend against. We evaluated our attack against three DNNs in white- and black-box settings, and found that it often achieved success rates near 100%. Moreover, we found that our attack can fool some commercial anti-viruses, in certain cases with a success rate of 85%. We explored several defenses, both new and old, and identified some that can foil over 80% of our evasion attempts. However, these defenses may still be susceptible to evasion by attacks, and so we advocate for augmenting malware-detection systems with methods that do not rely on machine learning.
Reinforcement Learning Contextual Bandits

This note is an introduction to contextual bandits, a class of multi-armed bandits where an agent must take sequential actions at time t = 1, 2, . based on observed rewards that are supposed to depend on some unknown parameter θ (the context). In recommander systems for instance, the parameter θ is supposed to characterize the user. This parameter is learnt based on the feedback provided by the user for each proposed item. Each item corresponds to an action of the agent, who must learn the best actions, i.e., the items providing the best rewards. We mainly focus on so-called linear bandits, where expected rewards are linear functions of the actions, then present the extension to logistic bandits.
Non-manipulability in Set-valued and Probabilistic Social Choice Theory

A fundamental requirement in social choice theory is non-manipula-bility, i.e., voters should not be able to benefit by voting dishonestly. Unfortunately, a seminal result by Gibbard [12] and Satterthwaite [15] states that only extremely unattractive voting rules can be strat-egyproof if it is required to choose a single winner deterministically. Two common approaches for circumventing this impossibility are to allow for sets of winners and to allow for randomization. It is for both approaches possible to define various strategyproofness notions based on different assumptions on how voters compare sets of alternatives or lotteries on alternatives, and consequently, both positive and negative results can be obtained. The goal of this PhD project is to analyze for both models the boundary between possibility and impossibility results for various strategyproofness notions.
Stationarity Conditions and Scalarization in Multiobjective Optimal Control of a Nonsmooth PDE

This work deals with the numerical characterization of Pareto stationary fronts for multiobjective optimal control problems with moderately many cost functionals with a mildly nonsmooth, elliptic, semilinear PDE constraint. We extend known stationarity conditions for ample controls to weaker conditions in the case where the controls are taken from a finite dimensional space and thus not “ample”. The conditions associated with strong stationarity remain meaningful when numerically characterizing the fronts. We compare the performance of the weighted-sum and the (Euclidean) reference point method for this application using quantifiable measures for approximation quality of the fronts. The subproblems of either method are solved with a line search globalized pseudo semismooth Newton method that seems to remove the degenerate behavior of the local version employed previously. When solving the subproblems of the reference point method, memory and computation complexity related issues appear and are tackled using a matrix-free, iterative approach and comparing multiple preconditioning tactics.
Structure, activity, and stability of platinum alloys as catalysts for the oxygen reduction reaction

In this thesis I present our work on theoretical modelling of platinum alloys as catalysts for the Oxygen Reduction Reaction (ORR). The losses associated with the kinetics of the ORR is the main bottleneck in low-temperature fuel cells for transport applications, and more active catalysts are essential for wide-spread use of this technology. platinum alloys have shown great promise as more active catalysts, which are still stable under reaction conditions. We have investigated these systems on multiple scales, using either Density Functional Theory (DFT) or Effective Medium Theory (EMT), depending on the length and time scales involved. Using DFT, we show how diffusion barriers in transition metal alloys in the L12 structure depend on the alloying energy, supporting the assumption that an intrinsically more stable alloy is also more stable towards diffusion-related degradation and dealloying due to kinetic barriers, despite the thermodynamic driving force for dissolution. This is followed by our results on trying to decouple the strain and ligand effects for platinum skin structures, and determining whether there is any correlation between adsorption energy and surface stability in these systems. We find that there is such a correlation for some adsorbates, indicating that there exists a limit for the stability of an overlayer for a given adsorption strength. Finally, we introduce our work on platinum alloy nanoparticles, and our attempt to isolate the features which result in the increased activity that has been seen experimentally. We show how the platinum-platinum distance at the surface is decreased for a variety of alloy phases in the core, with greater compression of the overlayer for core phases with lattice parameters which are either much smaller or much larger than pure platinum.
AutoKG: Constructing Virtual Knowledge Graphs from Unstructured Documents for Question Answering

Knowledge graphs (KGs) have the advantage of providing ﬁne-grained detail for question-answering systems. Unfortunately, building a reliable KG is time-consuming and expensive as it requires human intervention. To overcome this issue, we propose a novel framework to automatically construct a KG from unstructured documents that does not require external alignment. We ﬁrst extract surface-form knowledge tuples from unstructured documents and encode them with contextual information. Entities with similar context semantics are then linked through internal alignment to form a graph structure. This allows us to extract the desired information from multiple documents by traversing the generated KG without a manual process. We examine its performance in retrieval based QA systems by reformulating the WikiMovies and MetaQA datasets into a tuple-level retrieval task. The experimental results show that our method out-performs traditional retrieval methods by a large margin.
Muslim Acculturation in a Catholic Country: Its Associations with Religious Identity, Beliefs and Practices

The literature suggests that religion may play an important role in the acculturation process of immigrants by contributing to the maintenance of the heritage culture and preventing identification with the mainstream. With few exceptions, studies on this topic have focused on religion as a whole by assessing specific aspects or dimensions (such as religious identification, beliefs and practices) and creating a composite measure without analyzing the contribution of each dimension to the acculturation process. In this study, the relationships between specific religious dimensions and acculturation were assessed with a sample of 282 Muslim immigrants who were recruited in the Northern part of Italy. Two regression models show that religious identification drives the maintenance of Muslim culture but is unrelated to the acculturation to Italian culture, whereas beliefs and practices do not contribute to heritage acculturation but are negatively associated to acculturation to the host culture.
EMPLOYEES’ PROACTIVE BEHAVIOR AND INNOVATION PERFORMANCE: EXAMINING THE MODERATING ROLE OF INFORMAL AND FORMAL CONTROLS Abstract

Purpose. This study aims to analyze the degree to which employees’ proactive behavior contributes to innovation performance in firms operating in high technology sectors. Despite the benefits of these behaviors for individuals and organizations, few studies have analyzed the contextual conditions that enable firms to capture their value in order to improve innovation performance. Drawing on the interactionist perspective, we also examine the extent to which informal and formal controls, such as perceived support for innovation and innovation process formalization, can facilitate the contribution of proactive behaviors to improve innovation performance (product and process innovation). Design/methodology/approach. Based on an empirical study with a sample of 173 firms operating in chemical and information technology service sectors, hierarchical regression analysis was used to test the relationship between employees’ proactive behavior and innovation performance, and the moderating effects of informal and formal controls. Findings. Our results reveal a positive and significant association between proactive behaviors and product and process innovation performance. Both control mechanisms positively moderate the association between proactive behavior and product innovation, but no moderating role was found for process innovation. Moreover, rather than inhibiting innovation performance, innovation process formalization is positively associated with innovation. More specifically, a curvilinear relationship was found, which implies that when the level of formalization is high it is able to improve product and process innovation. Practical implications. Our findings suggest that managers should consider proactive behavior in selection processes and performance management, and should cultivate a climate to support innovation and establish formal controls for innovation as a way to channel employees’ initiatives into product innovation. Originality/value. This study contributes to the theoretical and managerial understanding of the extent to which proactive employees and organizational controls are able to enhance innovation in a technologically dynamic context.
FREELANCERS INTENTIONS TOWARDS ADOPTION OF ISLAMIC BANKING

The purpose of this research is to measure the impact of consumer attitude, social norms and perceived behavior on the intention to adopt Islamic banking by freelancers in Pakistan. The sample of the study is taken from the young freelance professionals that are currently working it the city of Mirpur Azad Kashmir. The number of respondents is limited to 150. Correlation, reliability, regression and ANOVA tests are performed to check the accuracy and association of the data variables. The results showed that the variables of religiosity and subjective norms has a positive impact on the behavioral intention to adopt Islamic banking. There for the research team can conclude that religiosity has an impact on the intention of the free lancers of the city of Mirpur to adopt to Islamic banking and subjective norms also has an impact on the intention of the free lancers of the city of Mirpur to adopt to Islamic banking. The study also notes that subjective norms also have an effect the intention to adopt there for allowing customers to know of the ethical and socially responsible practices can also help them to adopt. For any future researchers the study recommends that they can apply the same model in another area to see the results of add or remove variables to see the difference it can make.
Structural and Thermal Investigations of L-CuC4H4O6·3H2O and DL-CuC4H4O6·2H2O Single Crystals

Copper(II) L-tartrate trihydrate, L-CuC4H4O6·3H2O, and copper(II) DL-tartrate dihydrate, DL-CuC4H4O6·2H2O, crystals were grown at room temperature by the gel method using silica gels as the growth medium. Differential scanning calorimetry, thermogravimetric-differential thermal analysis, and X-ray diffraction measurements were performed on both crystals. The space group symmetries (monoclinic P21 and P21/c) and structural parameters of the crystals were determined at room temperature and at 114 K. Both structures consisted of slightly distorted CuO6 octahedra, C4H4O6 and H2O molecules, C4H4O6–Cu–C4H4O6 chains linked by Cu–O bonds, and O–H–O hydrogen-bonding frameworks between adjacent molecules. Weight losses due to thermal decomposition of the crystals were found to occur in the temperature range of 300–1250 K. We inferred that the weight losses were caused by the evaporation of bound water molecules and the evolution of H2CO, CO, and O2 gases from C4H4O6 molecules, and that the residual reddish-brown substance left in the vessels after decomposition was copper(I) oxide (Cu2O).
Sanctuaries in the Sardinian Bronze Age and Early Iron Age landscape (1200-700 BC): Network analysis and GIS approach

This paper aims to investigate the role of the sanctuaries in regards to the settlement-pattern, control of metal resources and mobility of those resources during the Final Bronze Age (1200-900 BC) and Early Iron Age (900-700 BC) in Nuragic Sardinia. The rise of Nuragic sanctuaries relates as a response to a profound societal and economic crisis that invests the Nuragic civilization around 1200 BC. Defined as ‘territorial compounds’ and generally associated with the cult of water, the rise of these new types of settlements corresponds also to a period of increasing metal production, internal and external metal trade. However, their role in a model that investigates the control, exchange and the internal mobility of metal resources have never been conceptualized or tested. In this paper, I argue that the rise of the sanctuaries acted as symbolic, territorial and economic nodes within and between Nuragic settlements and natural resources. The study takes advantage of spatial analysis applied with two different methods: Terrain analyses through GIS and Network Analysis. Cost Surface Analysis and Least Cost Path to investigate mobility patterns between sanctuaries, settlements and metal resources. The results will be used in the Network Analysis to understand the role of sanctuaries in connection to the exchange of metal resources among settlements.
Effect of Bactericidal Substance from Staphylococcus aureus on Group A Streptococci II. Structural Alterations

Ultrastructural alterations brought about by treatment of a β-hemolytic streptococcus with a bactericidal substance from Staphylococcus aureus are described and illustrated. The substance causes an early condensation of nucleoid deoxyribonucleic acid (DNA) and a partial loss of ribosomes. These changes are followed by a dissolution of the cell contents resulting in bacterial “ghosts” composed of empty cell wall and capsule. These morphological findings correlate with known biochemical effects of the bactericidal substance on ribonucleic acid degradation and cessation of DNA and protein synthesis.
Nutritional Evaluation of Milky Mushroom calocybe indica) grown on different substrates

Milky mushroom (Calocybe indica) is a potential new species to the world mushroom growers. This species is suitable for hot humid Climate and can be cultivated indoor at high temperature and high humid areas. Milky mushroom is gaining popularity among the edible mushroom because of its white attractive robust sporocaps highest ptotein content long self life and taste. This variety of mushroom can be cultivated easily at home without much expenditure. The different substrates were tested along and in combination with spent wheat straw (SWS) to determine the effect of substrates nutritional level on the nutritive value of fruiting bodies produced. Mushroom have attracted to attention of human from very ancient times and the use of mushroom is an old as human civilization. Mature fruit bodies are C. Indica contains high protein content (19.72%) it has 12 amino acids. Out of all amino acids glycine is predomiment and the essential acids like tryptophan, methionine and Lysine conteut in dry weight baris are 0.92, 0.93 and 7.86 (mg/ 100g protein).
Induced Automation: Evidence from Firm-level Patent Data

Do higher wages lead to more automation innovation? To answer this question, we first use the frequency of certain keywords in patent text to create a new measure of automation innovation in machinery. We show that our measure is correlated with a reduction in routine tasks in a cross-sectoral analysis in the US. We combine macroeconomic data from 41 countries and information on geographical patent history to build firm-specific measures of low- and high-skill wages. In a firm-level panel analysis, we find that an increase in low-skill wages leads to more automation innovation with an elasticity between 2 and 5. Placebo regressions show that the effect is specific to automation innovations. Finally, we focus on a specific labor market shock, the German Hartz reforms, and show that they reduced automation innovations by those non-German firms relatively more exposed to Germany.
Corporate Social Responsibility Disclosure and Cost of Equity of ASEAN-5 Public Companies

This research aims to analyze the influence of corporate social responsibility (CSR) disclosure, leverage, and ownership structure – consisting of institutional ownership, managerial ownership and concentrated ownership – on cost of equity with book-to-market ratio and firm size as control variables. The population was non-financial public companies listed in ASEAN. There was a total of 76 companies obtained using a purposive sampling technique. The data was analyzed using the multiple regression technique. The results show that the data is normally distributed and has met the requirements for using the multiple linear regression models. The findings indicate that the CSR and leverage have a positive and significant influence on cost of equity. Similarly, the institutional ownership also has a positive and significant influence on cost of equity. However, the managerial ownership and concentrated ownership have a negative and significant influence on cost of equity. Meanwhile, the book-to-market ratio has a negative and significant influence on cost of equity. In contrast, the firm size has a positive and significant influence on cost of equity.
Gender Representation in Subscription Video-On-Demand Spanish TV Series

In recent years, the increasing popularity of video-on-demand (VOD) platforms has changed Spanish audiovisual consumption. The main objectives of this article are to analyze the representation of gender in VOD Spanish productions. We pay particular attention to whether there is underrepresentation of character types and gender stereotyping with respect to occupation, traits, attitudes, and conversations. In addition, we set out to verify whether the image of women is different in VOD platforms compared with generalist television channels. To this end, we carried out a quantitative content analysis on a sample of 760 characters from Spanish fiction series produced by VOD platforms, broadcast between 2017 and 2020. The results obtained prove that even though new audiovisual platforms tend to incorporate equality, the underrepresentation and stereotyping of female characters in terms of professional occupation, family, and emotions still exist.
Response of three successive generations of maize aphid, Rhopalosiphum maidis Fitch (Aphididae: Hemiptera) reared on maize, Zea mays Linnaeus under elevated carbon dioxide and temperature

The objective of this study was to examine the response of three successive generations of maize aphid, Rhopalosiphum maidis Fitch (Aphididae: Hemiptera), reared on maize Zea mays Linnaeus under elevated Carbon dioxide (eCO2) (550 ppm ± 25 ppm) and ambient Carbon dioxide (aCO2) (380 ppm ± 25 ppm) concentrations at six temperatures of 20, 25, 27, 30, 33 and 35 ±1C in open-top chambers and CO2 growth chambers with CO2 and temperature regulation. Experiment was conducted by adopting agar-leaf method. Elevated CO2 and temperature significantly extended the duration of reproductive time (19.9623.32 days) with highest fecundity (83.20-87.68 nymphs per female) whereas the development time (6.60-7.16 days) and total life cycle (26.96-29.92 days) were declined compared to that of aCO2 and temperatures in R. maidis across the three generations. The findings showed that eCO2 and temperature significantly increased the number of generations of R. maidis with reduced generation time influenced the crop-insect interactions. The results indicated that the target agricultural management practices for effectively mitigating the concentrations of CO2 and temperature.
Detecting Tor Bridge from Sampled Traffic in Backbone Networks

—Due to the concealment of the dark web, many criminal activities choose to be conducted on it. The use of Tor bridges further obfuscates the trafﬁc and enhances the concealment. Current researches on Tor bridge detection have used a small amount of complete trafﬁc, which makes their methods not very practical in the backbone network. In this paper, we proposed a method for the detection of obfs4 bridge in backbone networks. To solve current limitations, we sample trafﬁc to reduce the amount of data and put forward the Nested Count Bloom Filter structure to process the sampled network trafﬁc. Besides, we extract features that can be used for bridge detection after trafﬁc sampling. The experiment uses real backbone network trafﬁc mixed with Tor trafﬁc for veriﬁcation. The experimental result shows that when Tor trafﬁc accounts for only 0.15% and the sampling ratio is 64:1, the F1 score of the detection result is maintained at about 0.9.