Miracle-dz/UniFAR-FTUs huggingface dataset:
DFT calculations on the Friedel-Crafts benzylation of 1,4-dimethoxybenzene using ZnCl2 impregnated montmorillonite K10 — inversion of relative selectivities and reactivities of aryl halides

Zinc was bound on montmorillonite K10 by cation exchange to obtain a catalyst named clayzic. In the Friedel-Crafts benzylation of 1,4-dimethoxybenzene, this catalyst was used for the synthesis of substituted diphenylmethanes using 4-chlorobenzyl chloride and 4-bromobenzyl bromide. During the reaction, sub-products from a second benzylation reaction process were observed. For a better understanding of their formation, reactions were carried out at different times to obtain data on the progress of benzylation and the relative ratio of each product was calculated using two different analytical methods. It was shown that the selectivity and reactivity of both aryl halides were reversed under these experimental conditions contrary to those obtained using the more conventional catalyst, zinc dichloride. These results were explained by geometrical and electronic considerations. It was found that the formation of transition states and Wheland intermediates from aryl bromide and chloride in the presence of clayzic can be explained in terms of preferential absorption. Moreover, the high percentage of 4-chlorobenzyl chloride conversion was attributed to its covalent radius, which is smaller than that of Br. At the same time it was shown that the presence of a Brönsted acid, due to the liberation of HCl during the benzylation, is responsible for the poisoning of the clayzic catalyst. Moreover, poisoning effect of the bromine anion could not be excluded.
Related Party Transactions and the Cost of Debt: Evidence from China *

This paper investigates the interrelationship between related party transactions (RPTs), cost of debt, and state ownership in the Chinese setting. Using data from listed Chinese companies during the period 2003 to 2013, we find that total RPTs increase firms’ cost of debt financing and that such a result is mainly driven by abnormal RPTs. Hence, the value-destroying argument with respect to the use of RPTs is empirically supported. We further partition our sample on the basis of the nature of ownership and find that state ownership plays a moderating role in the positive association between RPTs and cost of debt. Such a moderating effect remains significant for firms with tunnelling activities. Finally, we document that the adverse effect of RPTs on the cost of debt capital is more pronounced for firms with weak, as opposed to strong, internal control environments. Again, state-owned enterprises (SOEs) with lower internal control quality are found to have a higher cost of debt when they report a higher level of total RPTs. Our research contributes to the inconclusive literature on the influence of state ownership on the cost of debt by documenting a detrimental impact of RPTs on the cost of debt for SOEs; thus, it also has policy implications. We suggest that stricter regulation of SOE bankruptcies may enhance the credibility of SOEs and hence improve lenders’ credit risk assessments of those SOEs with reported RPTs. Our study also provides practical implications to corporate boards and senior management teams by highlighting the detrimental effect of opportunistic RPTs on the cost of debt financing.
Accounting Students’ Motivation for Getting Professionally Qualified

To move Malaysia to a developing nation, 60,000 professionally qualified accountants are needed by 2030. However, as of April 2017, only 33,000 accountants have registered as members of the Malaysian Institute of Accountants (MIA). The purpose of this research is to analyse students’ behaviour on the motivational factors to obtain professional accounting qualifications. This study gathered the response of 187 students as samples from the only public university in Malaysia that offers ACCA professional accounting certificate. The results show that most students are motivated by intrinsic and extrinsic motivations, while there is no relationship between third parties’ influence and demographic factors with the decision to pursue a professional accounting qualification. Keywords: Professional qualified; intrinsic motivation; extrinsic motivation; accounting students eISSN: 2398-4287© 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v5i15. 2454.
Malaysian female users ’ purchase intentions of celebrity-endorsed products on Instagram : A parasocial interaction perspective

A media user’s imagined relationship with mediated characters and personalities can influence him/her in a variety of ways. Through celebrity-fan engagement on social media, fans can be influenced by their favourite celebrities in various ways, including wanting to practice a healthier lifestyle, considering cosmetic surgery or using certain brands. The introduction of contemporary new media, with easy access and heightened interactivity, has motivated scholars to re-examine how parasocial relationships may form online, and their effect on media users. However, little is known about how parasocial relationships influence online consumer behaviour. Accordingly, this study focuses on identifying the predictors of purchase intentions of celebrity-endorsed products among female Instagram users in Malaysia (N = 630). Using an online survey, they were asked to rate their social media engagement with a celebrity that they follow on Instagram as well as provide responses about the celebrity characteristics. Overall, results highlight the positive impact of parasocial interaction on the purchase intentions of celebrity-endorsed products. Specifically, findings suggest that parasocial interaction: (a) mediates the relationship between Instagram use and purchase intentions, and (b) partially mediates the relationship between attitude homophily and purchase intentions. The ramifications of these findings on parasocial interaction theory and the effect of celebrity endorsements on social media are also discussed.
Do Auditors Use The Information Reflected In Book-Tax Differences ? Discussion

Hanlon and Krishnan (2006), hereinafter HK, address an interesting bridge between audit and tax research by examining the association between book-tax differences and audit fees, modified audit opinions and auditor turnover. HK report positive relations between book-tax differences and each of these audit variables, and interpret these results as evidence “consistent with booktax differences reflecting information about possible earnings management and with auditors examining and using this information in auditing and opining on firms’ financial statements” (page 29).
Effect of Immobilizing Substances and Salinity on Heavy Metals Availability to Wheat Grown on Sewage Sludge-Contaminated Soil

The objective of the investigation was to evaluate the effect of immobilizing substances and NaCl salinity on the availability of heavy metals: Zn, Cd, Cu, Ni, and Pb to wheat (Triticum aestivum L.). In greenhouse pot experiment, a sewage sludge amended soil was treated with the following immobilizing substances: three clay minerals (Na-bentonite, Ca-bentonite and zeolite), iron oxides (goethite and hematite), and phosphate fertilizers (superphosphate and Novaphos). The pots were planted with wheat and were irrigated either with deionized or saline water containing 1600 mg L−1 NaCl. Wheat was harvested two times for shoot metal concentrations and biomass measurements. Metal species in soil solution were estimated using the software MINEQL+. The addition of metal immobilizing substances to the soil significantly decreased metal availability to wheat. The largest reduction in metal bioavailability was found for bentonites. The irrigation with saline water (1600 mg L−1 NaCl) resulted in a significant increase in metal chloride species (MCl+ and MCl2 0). The highest metal complexation with Cl occurred for Cd, which was about 53% of its total soil solution concentration. The total concentration of Cd (CdT) in soil solution increased by 1.6–2.8-fold due to saline water. The NaCl salinity caused a significant increase in uptake and shoot concentration of Cd for two harvests and small but significant increase in shoot Pb concentration for the second harvest. It was concluded that the use of bentonites is the most promising for the reduction of heavy metal availability to plants. Saline water containing 1600 mg L− 1 NaCl increased the availability of Cd and Pb to wheat and decreased the efficiency of bentonites to immobilize soluble Cd.
Mining the Stars: Learning Quality Ratings with User-facing Explanations for Vacation Rentals

Online Travel Platforms are virtual two-sided marketplaces where guests search for accommodations and accommodation providers list their properties such as hotels and vacation rentals. The large majority of hotels are rated by official institutions with a number of stars indicating the quality of service they provide. It is a simple and effective mechanism that contributes to match supply with demand by helping guests to find options meeting their criteria and accommodation suppliers to market their product to the right segment directly impacting the number of transactions on the platform. Unfortunately, no similar rating system exists for the large majority of vacation rentals, making it difficult for guests to search and compare options and hard for vacation rentals suppliers to market their product effectively. In this work we describe a machine learned quality rating system for vacation rentals. The problem is challenging, mainly due to explainability requirements and the lack of ground truth. We present techniques to address these challenges and empirical evidence of their efficacy. Our system was successfully deployed and validated through Online Controlled Experiments performed in Booking.com, a large Online Travel Platform, and running for more than one year, impacting more than a million accommodations and millions of guests.
Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification

Semi-supervised learning through deep generative models and multi-lingual pretraining techniques have orchestrated tremendous success across different areas of NLP. Nonetheless, their development has happened in isolation, while the combination of both could potentially be effective for tackling task-specific labelled data shortage. To bridge this gap, we combine semi-supervised deep generative models and multi-lingual pretraining to form a pipeline for document classification task. Compared to strong supervised learning baselines, our semi-supervised classification framework is highly competitive and outperforms the state-of-the-art counterparts in low-resource settings across several languages.
Self Sparse Generative Adversarial Networks

Generative Adversarial Networks (GANs) are an unsupervised generative model that learns data distribution through adversarial training. However, recent experiments indicated that GANs are difficult to train due to the requirement of optimization in the high dimensional parameter space and the zero gradient problem. In this work, we propose a Self Sparse Generative Adversarial Network (Self-Sparse GAN) that reduces the parameter space and alleviates the zero gradient problem. In the Self-Sparse GAN, we design a Self-Adaptive Sparse Transform Module (SASTM) comprising the sparsity decomposition and feature-map recombination, which can be applied on multi-channel feature maps to obtain sparse feature maps. The key idea of Self-Sparse GAN is to add the SASTM following every deconvolution layer in the generator, which can adaptively reduce the parameter space by utilizing the sparsity in multi-channel feature maps. We theoretically prove that the SASTM can not only reduce the search space of the convolution kernel weight of the generator but also alleviate the zero gradient problem by maintaining meaningful features in the Batch Normalization layer and driving the weight of deconvolution layers away from being negative. The experimental results show that our method achieves the best FID scores for image generation compared with WGAN-GP on MNIST, Fashion-MNIST, CIFAR-10, STL-10, mini-ImageNet, CELEBA-HQ, and LSUN bedrooms, and the relative decrease of FID is 4.76% ~ 21.84%.
Effect of seed biopriming with plant growth promoting rhizobacteria (PGPR) on yield and dry matter accumulation of spring barley (Hordeum vulgare L.) at various levels of nitrogen and phosphorus fertilizers

In order to study the effects of PGPR at various levels of nitrogen and phosphorus fertilizers on yield and dry matter accumulation of barley, an experiment was conducted at the Research Farm of Islamic Azad University, Ardabil Branch, during 2009-2010 cropping. The combination of nitrogen (N 0, 40 and 80 kg/ha as urea) and phosphorus (P 2 O 5 0, 30 and 60 kg/ha) fertilizers were factorially assigned to the main plots and seed biopriming with plant growth promoting rhizobacteria in four levels (no priming, seed biopriming with Azotobacter chroococcum strain 5, Azospirillum lipoferum strain OF and combination of seed biopriming with Azotobacter + Azospirillum) were assigned to the subplots. The results showed that yield and dry matter accumulation were significantly affected by nitrogen and phosphorus fertilizer levels and seed priming with PGPR. With increasing of nitrogen and phosphorus levels and seed priming with PGPR, yield and dry matter accumulation were increased. Maximum 1000 grain weight, grain yield, biological yield and harvest index were obtained in the plots which was applied the highest levels of nitrogen and phosphorus fertilizers in seed priming with both Azospirillum + Azotobacter compared to control treatment and minimum was obtained in control treatment.
Emergent moments in a Hund's impurity

Victor Drouin-Touchette, Elio J. König, 2 Yashar Komijani, 3 and Piers Coleman 4 Center for Materials Theory, Rutgers University, Piscataway, New Jersey 08854, USA Max-Planck Institute for Solid State Research, 70569 Stuttgart, Germany Department of Physics, University of Cincinnati, Cincinnati, Ohio 45221-0011, USA Hubbard Theory Consortium and Department of Physics, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK (Dated: January 27, 2021)
Studies on pyrazine derivatives LII: Antibacterial and antifungal activity of nitrogen heterocyclic compounds obtained by pyrazinamidrazone usage

Using reactivity of pyrazinamidrazones and their N′-substituted derivatives 1–8 in reaction with sulfonyl chlorides sulfone derivatives 9–17 were obtained, with orthoformate cyclized to sulfonyl compounds 18–20. Amidrazones in reaction with pyraziniminoesters gave dihydrazidines 21–23, which cyclized to 3,5-dipyrazine derivatives of 1,2,4-triazole 24–26. 1-Methyl- or 1-phenyl-3-pyrazine-1,2,4-triazole 27–38 was formed in reaction of amidrazones 1–8 with orthoformate and orthoacetate or benzoyl chloride. N′-Phenylamidrazones 3, 8 in reaction with thionyl chloride were transformed to 1,2,3,5-thiatriazole S-oxides 39, 40. Obtained compounds exhibited low antibacterial activity. Antifungal activity was affirmed for compounds 1, 3, 4, 5, 8, 37, 39, and 40, for which minimal inhibitory concentration (MIC) was in the concentration range of 16–128 μg/mL. © 2011 Wiley Periodicals, Inc. Heteroatom Chem 23:49–58, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/hc.20751
Anticancer drug delivery systems based on noncovalent interactions between carbon nanotubes and linear–dendritic copolymers

Hybrid nanomaterial-based drug delivery systems (HNDDSs) consisting of carbon nanotubes and linear–dendritic copolymers linked to anticancer drugs were synthesized and characterized. Polycitric acid–polyethylene glycol–polycitric acid (PCA–PEG–PCA) linear–dendritic copolymers were used to solubilize and functionalize multi-walled carbon nanotubes (MWCNTs) by noncovalent interactions. There are two key features of HNDDSs: (a) functionalized MWCNTs as a biocompatible platform for the delivery of therapeutic agents and diagnostics, (b) PCA–PEG–PCA linear–dendritic copolymers as water soluble, biocompatible and highly functional hybrid materials with a linear PEG block and two dendritic PCA blocks that improve the solubility and functionality of MWCNTs respectively. In this work, cisplatin (cis-diamminedichloroplatinum (CDDP)—a platinum-based chemotherapy drug) was conjugated to the carboxyl functional groups of the dendritic blocks of PCA–PEG–PCA linear–dendritic copolymers and then the prodrugs interacted with the MWCNTs noncovalently and HNDDSs were obtained. To prove the efficacy of the synthesized HNDDSs, they were subjected to endocytosis and released CDDP molecules inside murine colon adenocarcinoma tumor C26 cancer cells. Then it was proved that HNDDSs are able to kill cancer cells effectively. Release of the anticancer drug from HNDDSs was also investigated.
THE NUTRITIONAL VALUE OF FLAXSEED MEAL FOR SWINE

The nutritional value of flaxseed meal (FSM), a by-product of the flax crushing industry, has not been evaluated properly for use within swine rations. A series of experiments were conducted to determine the nutritional profile of this novel feed ingredient for pigs. The analysis of FSM revealed that it contains, on a dry matter (DM) basis, 133 g/kg ether extract (EE), 345 g/kg crude protein (CP), 60 g/kg ash, 164 g/kg ADF, 250 g/kg NDF, 102 g/kg crude fibre, 14 g/kg starch and 9 g/kg phosphorus. The gross energy (GE) content of the meal was 5.2 Mcal/kg DM. The ether extract fraction was characterized by, as a percent of total fat, 46.6% αlinolenic acid, an omega-3 fatty acid. Palmitic, stearic, oleic and linoleic acids accounted for 9.5, 4.8, 20.7 and 18.4% of the total fat content respectively. The crude protein content was well balanced for all amino acids with the exception of lysine (4.1% of CP), the level of which falls below that of the requirements for growing pigs (5.3% of CP for pigs 20-50 kg). The apparent digestibility of DM, nitrogen, ash, EE and GE as well as determination of the DE and NE content of FSM was determined for both growing pigs (32 pigs, initial weight 70 ± 3 kg) and gestating sows (26 pigs, parities 2 – 4). Animals were fed wheat/barley based diets containing 0, 10, 20 or 30% FSM. Faecal grab samples were collected for 3 days after a dietary adaptation period. The apparent digestibility of nutrients in FSM was determined both by regression and by difference calculations. As calculated by difference, the apparent digestibility coefficients for DM, nitrogen, ash, and GE were 63.0, 60.8, 22.3 and 60.5% respectively for growing pigs. The values obtained for sows were 64.1, 58.8, 20.8, 94.9 and 65.4% for DM, nitrogen, ash, EE and GE respectively. The DE content was 3.37 Mcal/kg for growing pigs and 3.52 Mcal/kg for sows. Net energy was then estimated by use of a prediction equation to be 2.34 and 2.44 Mcal/kg for growing pigs and sows. An experiment was conducted to evaluate the growth performances and carcass fatty acid profiles of pigs fed with graded levels of FSM. A total of 200 pigs (100 barrows, 100 gilts; initial weight 32 ± 4 kg) were blocked by gender and housed in groups of 5 pigs per pen. The experiment was divided into three phases for pigs 32-60 kg, 60-85 kg and 85-115 kg. Each group was assigned to one of four dietary treatments containing 0, 5, 10 or 15% FSM at the expense of wheat and soybean meal. At the time of market, 6 pigs per treatment group were randomly selected for carcass fatty acid analysis, and backfat and rib-end loin samples were collected. The average daily gains, average daily feed intakes and gain to feed ratios were not affected by dietary treatment (P > 0.05). Inclusion of 15% dietary FSM increased the ALA content from 11 to 47 (± 0.8) mg/g of backfat (P < 0.001) and
Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yolóxochitl Mixtec

“Transcription bottlenecks”, created by a shortage of effective human transcribers (i.e., transcriber shortage), are one of the main challenges to endangered language (EL) documentation. Automatic speech recognition (ASR) has been suggested as a tool to overcome such bottlenecks. Following this suggestion, we investigated the effectiveness for EL documentation of end-to-end ASR, which unlike Hidden Markov Model ASR systems, eschews linguistic resources but is instead more dependent on large-data settings. We open source a Yoloxóchitl Mixtec EL corpus. First, we review our method in building an end-to-end ASR system in a way that would be reproducible by the ASR community. We then propose a novice transcription correction task and demonstrate how ASR systems and novice transcribers can work together to improve EL documentation. We believe this combinatory methodology would mitigate the transcription bottleneck and transcriber shortage that hinders EL documentation.
The Granularity Gap Problem: A Hurdle for Applying Approximate Memory to Complex Data Layout

The main memory access latency has not much improved for more than two decades while the CPU performance had been exponentially increasing until recently.Approximate memory is a technique to reduce the DRAM access latency in return of losing data integrity. It is expected to be beneficial for applications that are robust to noisy input and intermediate data such as artificial intelligence, image/video processing, and big-data analytics. To obtain reasonable outputs from applications on approximate memory, it is crucial to protect critical data while accelerating accesses to non-critical data. We refer the minimum size of a continuous memory region that the same error rate is applied in approximate memory to as the approximation granularity. A fundamental limitation of approximate memory is that the approximation granularity is as large as a few kilo bytes. However, applications may have critical and non-critical data interleaved with smaller granularity. For example, a data structure for graph nodes can have pointers (critical) to neighboring nodes and its score (non-critical, depending on the use-case). This data structure cannot be directly mapped to approximate memory due to the gap between the approximation granularity and the granularity of data criticality. We refer to this issue as the granularity gap problem. In this paper, we first show that many applications potentially suffer from this problem. Then we propose a framework to quantitatively evaluate the performance overhead of a possible method to avoid this problem using known techniques.The evaluation results show that the performance overhead is non-negligible compared to expected benefit from approximate memory,suggesting that the granularity gap problem is a significant concern.