Miracle-dz/UniFAR-FTUs huggingface dataset:
Bidentate Rh(I)‐Phosphine Complexes for the C−H Activation of Alkanes: Computational Modelling and Mechanistic Insight

The C−H activation and subsequent carbonylation mediated by metal complexes, i. e. , Rh(I) complexes, has drawn considerable attention in the past. To extend the mechanistic insight from Rh complexes featuring monodentate ligands like P(Me)3 towards more active bisphosphines (PLP), a computationally derived fully conclusive mechanistic picture of the Rh(I)‐catalyzed C−H activation and carbonylation is presented here. Depending on the nature of the bisphosphine ligand, the highest lying transition state (TS) is associated either to the initial C−H activation in [Rh(PLP)(CO)(Cl)] or to the rearrangement of the chloride in [Rh(PLP)(H)(R)(Cl)]. The chloride rearrangement was found to play a key role in the subsequent carbonylation. A set of 20 complexes of different architectures was studied, in order to fine tune the C−H activation in a knowledge‐driven approach. The computational analysis suggests that a flexible ligand architecture with aromatic rings can potentially increase the performance of Rh‐based catalysts for the C−H activation.
Application of the Quality Management Tools in the Textile Industry

Textile and apparel industry in Europe is faced with higher cost structure than many of its competitors on world markets. Focusing on higher quality is a way to distinguish from competition and reduce total cost.In the past few years this industrial branch has been expecting problems because the total production is significantly smaller. Therefore, industry management has been warned about giving constant attention to: reducing costs and promoting their own brands. Hypothesis of this paper are that: Croatian managers in textile and apparel industry are not familiar with quality concepts;and that application of quality tools and concepts contributes to achievement of better business results and competitiveness. It was critically assessed by survey sent to 150 managers in Croatian textile companies. Results showed that managers were not familiar with different quality concepts, but their perceptions about benefits from application were positive.
Preliminary Component Definition of ReusableStaged-Combustion Rocket Engine

Full-flow staged combustion cycle rocket engines with a moderate 15 to 17 MPa range in chamber pressure have been selected as the baseline propulsion system of DLR’s visionary fully reusable SpaceLiner concept. After completing the Mission Requirements Review, the SpaceLiner Main Engine (SLME) component definition is progressing at Phase A conceptual design level. Refinements are focusing on the turbo-machinery designed as an integrated power-head and a suitable thrust-chamber lay-out. One key-objective is a light-weight, long-life, low-maintenance architecture. The paper describes the latest status of the SpaceLiner 7 propulsion system: • The reference vehicle’s preliminary design, • Main propulsion feed-and pressurization system definition and architectural lay-out, • Thrust chamber regenerative circuit, • Pre-design of different turbomachinery and attached preburners, Design solutions are traded and compared to other recent high-performance rocket engine developments based on available design data or reassessment.
Pragmatic evaluation of methods for retrieving unpublished information on comparator interventions in a systematic review of smoking cessation trials

Abstract Objective Reporting of the content and delivery characteristics of comparator interventions in published articles is often incomplete. This study examines the feasibility and validity of two methods for collecting additional information on comparator interventions from trial authors. Methods & Measures In a systematic review of smoking cessation trials (IC-Smoke), all trial authors were asked to send unpublished comparator intervention materials and complete a specially-developed comparator intervention checklist. All published and additionally obtained information from authors were coded for behaviour change techniques (BCTs) and other characteristics (type of comparator, provider, provider training, delivery mode and treatment duration). To assess representativeness, we assessed the amount of additional information obtained from trial authors compared with the amount that was published. We examined known-group and convergent validity of comparator intervention data when using only published or also unpublished information. Results Additional information were obtained from 91/136 (67%) of trial authors. Representativeness, known-group and convergent validity improved substantially based on the data collected by means of the comparator intervention checklist, but not by requesting authors to send any existing comparator materials. Conclusions Requesting authors for unpublished comparator intervention data, using specially-developed checklists and unpublished materials, substantially improves the quality of data available for systematic reviews.
From progressiveness to perfection: Mothers’ descriptions of their children in print media, 1970–1979 versus 2010–2019

In this article, I address how mothers’ public discourse about their children has changed over time by analysing 130 interviews with mothers published in Icelandic magazines and newspapers in 1970–1979 and 2010–2019. The analysis is framed by scholarship on intensive mothering and the affective aspects of neoliberalism, including Berlant’s cruel optimism. The results show that in the former period, children are depicted as equality minded and independent, echoing the then public debate about mothers’ participation in the workforce and gender equality. In the latter era, the children are characterised as talented, perfect, happy and spiritually inspiring for the mothers. This stark contrast between the time periods suggests that today, the feeling-rules of neoliberalism influence mothers’ public portrayal of their children. In that way, children have become proxies to the neoliberal and competitive pursuit of perfection as well as perceived pathways to the personal enlightenment of adults.
REGIONAL EPIDEMIOLOGY AND ASSOCIATED RISK FATORS OF PESTE DES PETITS RUMINANTS IN ASIA – A REVIEW

Abstract: Peste des petits ruminants (PPR) is World Organization for Animal Health (OIE) notifiable, economically important transboundary, highly contagious, and an acute viral disease of small ruminants. The disease is caused by the PPR virus (PPRV). PPRV belongs to the genus Morbillivirus of the family Paramyxoviridae. The recent epidemiological and molecular characterization of PPR virus isolates subdivides them into four genetically distinct lineages (I, II, III and IV). The disease is endemic across Asia, the Middle East and African regions and is considered a major obstacle to the development of sustainable agriculture across the developing world due to its huge burden on the economy and development of the affected countries and has recently been targeted by the Food and Agriculture Organization (FAO) and the OIE for global eradication by 2030. PPR-endemic countries should join the regional force, and implement regional road maps for the progressive and successful control and elimination of PPRV. In this review, the regional epidemiology of PPR outbreaks and associated risk factors, including animal factors (age, species and sex), environmental factors (season, spatial distribution of disease in various locations) and trade associated factors with special reference to the PPR affected countries in South, Central and East Asia are comprehensively discussed.Key words: epidemiology; PPR-virus; risk factors; control; eradication; AsiaREGIONALNA EPIDEMIOLOGIJA IN Z NJO POVEZANI DEJAVNIKI TVEGANJA ZA KUGO DROBNICE V AZIJI – PREGLEDIzvleček: Kuga drobnice (angl., Peste des petits ruminants, PPR) je gospodarsko pomembna, čezmejno nevarna, visoko nalezljiva, akutna virusna bolezen drobnice, ki jo je potrebno prijaviti Svetovni organizaciji za zdravje živali (OIE). Bolezen povzroča virus PPR (PPRV). PPRV spada v rod virusov Morbillivirus iz družine Paramyxoviridae. Nedavna epidemiološka in molekularna karakterizacija izolatov virusa PPRV deli izolate na štiri genetsko različne linije (I, II, III in IV). Bolezen je endemična v Aziji, na bližnjem vzhodu in v Afriki. Zaradi močnega bremena za gospodarstvo in razvoj prizadetih držav velja za glavno oviro pri razvoju trajnostnega kmetijstva v državah v razvoju. Organizacija Združenih narodov za prehrano in kmetijstvo (FAO) in OIE sta nedavno določili, da je bolezen potrebno do leta 2030 izkoreniniti po vsem svetu. Države z endemijo PPR bi se morale pridružiti regionalnim silam in izvajati regionalne načrte za postopen in uspešen nadzor in izkoreninjenje PPRV. V tem pregledu so izčrpno obravnavani regionalna epidemiologija izbruhov PPR in povezani dejavniki tveganja, vključno z dejavniki živali (starost, vrsta in spol), okolja (letni čas, prostorska razširjenost bolezni na različnih lokacijah) in trgovine, s posebnim poudarkom na državah s PPR v južni, osrednji in vzhodni Aziji. Ključne besede: epidemiologija; virus PPR; dejavniki tveganja; nadzor; izkoreninjenje; Azija
Attention Based BERT-FastText Model for Hate Speech and Offensive Content Identification in English and Hindi Languages

This paper describes our model submitted for HASOC-2021 as the IIT_Patna team for hate and offensive content identification in English and Hindi languages. A deep learning model, namely BERT+FastText-GRU, has been developed based on BERT and FastText, followed by GRU with attention. Our proposed model uses a BiGRU-based deep neural network to extract textual features, followed by an Attention layer to focus on the most important phrase of the text. The BERT language model and FastText embedding have been employed to examine the effectiveness of joint embedding representation compared to a single one. We have set up some baselines by varying the RNN architecture (LSTM/GRU) and the word vector representation approach (BERT/FastText). Our model outperforms all the baselines with the highest accuracy values of 76.32% for subtask-1A (EN), 56.73% for subtask-1B (EN), 69.17% for subtask-1A (HI) and 40.45% for subtask-1B (HI).
Gastronomy as an effect of visitor loyalty: the Peruvian (Lima) case

Purpose The purpose of this study is to analyse Peruvian cuisine in the context of visitors’ overall experience, focusing on the loyalty of tourists in terms of gastronomy, their satisfaction with the destination, and the overall image. Design/methodology/approach Data were obtained from tourists who visited Lima (Peru). Structural equation modeling was used to verify the hypothesized relationships. Findings The results obtained confirm that satisfaction and appreciation, such as quality, have a positive influence on tourists’ loyalty and, therefore, they recommend and express their desire to come back to this destination. The traditional gastronomy of Lima stands out as a prominent factor on overall experience. Research limitations/implications This paper helps the managers of cities in their decisions to improve the satisfaction and seek loyalty of those who visit a city, emphasizes the role of gastronomy. Practical implications The results obtained in this research can be used for the establishment of new strategies for the promotion of the destination in terms of tourism and traditional food. Originality/value The gastronomy in Lima, (Peru) is recognized worldwide, as well as a stimulus for tourism because it increases the number of visits to the destination. Several studies carried out in these types of destinations have shown the existence of a relationship between gastronomy, overall experience, satisfaction and loyalty. However, there are no previous studies carried out in Lima that sustain this relationship. This work makes a contribution that completes the academic literature on the study of the emotional bonds between Peruvian gastronomy and the tourist who visits it and its behaviour.
How to Use Simulation Games in the Classroom?

An enhanced, new venture simulation can be a game changer within a school’s entrepreneurial ecosystem, providing students with a holistic vision of a new venture and skills relevant to its potential success. The purpose of this article is to help faculty design and deliver a simulation experience that will engage, challenge, inspire and transform students into entrepreneurial enthusiasts with practical new venture knowledge and skills. Attention is given to (a) the factors to consider in choosing the right simulation, (b) the best practices for structuring a class for maximum impact and (c) the role of the instructor as an entrepreneurial coach.
Deep Realistic Facial Editing via Label-restricted Mask Disentanglement

With the rapid development of GAN (generative adversarial network), recent years have witnessed an increasing number of tasks on reference-guided facial attributes transfer. Most state-of-the-art methods consist of facial information extraction, latent space disentanglement, and target attribute manipulation. However, they either adopt reference-guided translation methods for manipulation or monolithic modules for diverse attribute exchange, which cannot accurately disentangle the exact facial attributes with specific styles from the reference image. In this paper, we propose a deep realistic facial editing method (termed LMGAN) based on target region focusing and dual label constraint. The proposed method, manipulating target attributes by latent space exchange, consists of subnetworks for every individual attribute. Each subnetwork exerts label-restrictions on both the target attributes exchanging stage and the training process aimed at optimizing generative quality and reference-style correlation. Our method performs greatly on disentangled representation and transferring the target attribute's style accurately. A global discriminator is introduced to combine the generated editing regional image with other nonediting areas of the source image. Both qualitative and quantitative results on the CelebA dataset verify the ability of the proposed LMGAN.
D139N mutation of PsbP enhances the oxygen-evolving activity of photosystem II through stabilized binding of a chloride ion

Abstract Photosystem II (PSII) is a multisubunit membrane protein complex that catalyzes light-driven oxidation of water to molecular oxygen. The chloride ion (Cl−) has long been known as an essential cofactor for oxygen evolution by PSII, and two Cl− ions (Cl-1 and Cl-2) have been found to specifically bind near the Mn4CaO5 cluster within the oxygen-evolving center (OEC). However, despite intensive studies on these Cl− ions, little is known about the function of Cl-2, the Cl− ion that is associated with the backbone nitrogens of D1-Asn338, D1-Phe339, and CP43-Glu354. In green plant PSII, the membrane extrinsic subunits—PsbP and PsbQ—are responsible for Cl− retention within the OEC. The Loop 4 region of PsbP, consisting of highly conserved residues Thr135–Gly142, is inserted close to Cl-2, but its importance has not been examined to date. Here, we investigated the importance of PsbP-Loop 4 using spinach PSII membranes reconstituted with spinach PsbP proteins harboring mutations in this region. Mutations in PsbP-Loop 4 had remarkable effects on the rate of oxygen evolution by PSII. Moreover, we found that a specific mutation, PsbP-D139N, significantly enhances the oxygen-evolving activity in the absence of PsbQ, but not significantly in its presence. The D139N mutation increased the Cl− retention ability of PsbP and induced a unique structural change in the OEC, as indicated by light-induced Fourier transform infrared (FTIR) difference spectroscopy and theoretical calculations. Our findings provide insight into the functional significance of Cl-2 in the water-oxidizing reaction of PSII.
Anti-Occlusion Target Tracking Based on Joint Confidence

Aiming to the challenge of occlusion during tracking, this paper proposes an anti-occlusion tracking based on joint confidence. Under the framework of the kernel correlation filter (KCF) tracking, the dimension of the feature is extended to construct a robust target appearance model, and the size of the target is estimated during the tracking process. We first judge whether occlusion occurs or not by the measurement by combining the maximum of the detection response map with the average peak correlation energy, then design the corresponding anti-interference tracking strategy. If the occlusion does not occur during the tracking process, the KCF tracking is performed, otherwise, re-detection is introduced to locate the target position, and the region corresponding to the re-detection is added to the regulation term of the KCF for context learning. The fusion of the filter template before occlusion and the context model learned during occlusion is used to locate the target and to update the model. Experimental evaluations on the datasets OTB2013, OTB100 and TC128 show that compared with the state-of-the-art algorithms such as KCF, Siamese and other algorithms, our proposed algorithm has stronger robustness and higher tracking accuracy when occlusion occurs.
Model predictive control for autonomous and cooperative driving. (Commande prédictive pour conduite autonome et coopérative)

Autonomous driving has been gaining more and more attention in the last decades, thanks to its positive social-economic impacts including the enhancement of traffic efficiency and the reduction of road accidents. A number of research institutes and companies have tested autonomous vehicles in traffic, accumulating tens of millions of kilometers traveled in autonomous driving. With the vision of massive deployment of autonomous vehicles, researchers have also started to envision cooperative strategies among autonomous vehicles. This thesis deals with the control architecture design of individual autonomous vehicles and cooperative autonomous vehicles. Model Predictive Control (MPC), thanks to its efficiency and versatility, is chosen as the building block for various control architectures proposed in this thesis. In more detail, this thesis first presents a classical hierarchical control architecture for individual vehicle control that decomposes the controller into a motion planner and a tracking controller, both using nonlinear MPC. In a second step, we analyze the inability of the proposed planner in handling logical constraints raised from traffic rules and multiple maneuver variants, and propose a hybrid MPC based motion planner that solves this issue. We then consider the convoy control problem of autonomous vehicles in which multiple vehicles maintain a formation during autonomous driving. A hierarchical formation control architecture is proposed composing of a convoy supervisor and local MPC based vehicle controllers. Finally, we consider the problem of coordinating a group of autonomous vehicles at an intersection without traffic lights. A hierarchical architecture composed of an intersection controller and multiple local vehicle controllers is proposed to allow vehicles to cross the intersection smoothly and safely.
A Deep Learning Approach in Scalable High Efficiency Video Coding for Fast Coding Unit Size Decision

The High Efficiency Video Coding (HEVC) with scalable extension known as SHVC allows encoding the same video with different resolutions in a single bitstream. However, this process increases the encoding complexity. The complexity is increased mainly due to the motion estimation process and the Rate-Distortion Optimization (RDO) search process. The Test Zonal (TZ) algorithm with fast search patterns helps to accelerate the motion estimation process. However, the search patterns may get trapped to local minima, leading to inaccurate motion vectors. Moreover, the RDO search process used to determine the Coding Unit (CU) size increases the complexity. We proposed the Horizontal Subsampling Motion Estimation (HSME) method to find the accurate motion vectors with reduced complexity. The experimental results prove that the HSME method saves the encoding time by 53.03% with a 6.45% increase in Bjøntegaard delta bit rate and 0.28 dB loss in Bjøntegaard Delta Peak Signal-to-Noise Ratio (BD-PSNR) compared to standard SHM-12.1. In addition, we designed the Early Terminated Long- and Short-Term Memory (ET-LSTM) network that predicts the CU partition by taking the output features of the Early Terminated Convolutional Neural Network (ET-CNN). The ET-CNN learns the CU partitions from the residual Coding Tree Unit (CTU) using the deep learning approach. Our proposed method (HSME + ET-CNN + ET-LSTM) achieves 53% savings in encoding time, which is significantly higher than state-of-the-art methods.
Image recognition for x-ray luggage scanners using free and open source software

This paper describes the status of a currently ongoing research and development project that proposes the implementation of a system to be connected to x-ray luggage scanning equipment used by the Airport Security Police (Policía de Seguridad Aeroportuaria, PSA), having as main objective to automatically recognize images obtained in real time from the scanners to alert the x-ray machine operators or screeners about those identified as threats (explosive devices, firearms, etc.) Technical instructions and source code of a web-service and auxiliary scripts developed for the evaluations were published on github in order to enable interested researchers, developers and other potential contributors to repeat or reproduce the training and testing summarized in this paper with freely available image data-sets.
High speed structured illumination microscopy based on compressed sensing: numerical simulation

In traditional optical microscopy imaging system, the resolution of time mainly depends on the detector’s detection speed, usually in millisecond or microsecond magnitude. While the spatial resolution is limited by the optical diffraction limit, the lateral resolution of ordinary microscopies generally only reaches 200nm.Just as biological structure has a wide spatial scale, biological living processes also have a broad time scale. When observing biological subcellular organelles, resolution and the speed of life activities should be considered. For the dynamic process, it’s meaningless to simply improve the spatial resolution without correspondingly increasing the imaging speed which should be no less than the movement speed of the observed object. Existing super-resolution or high-speed optical imaging is limited by the mutual constraints of spatial and time resolution, making it difficult to obtain both super-resolution and high-speed optical imaging. In order to break the constraints of this game and gain high-speed super-resolution images, the CS-SIM system combines SIM (structured illumination microscopy) and CSP (compressed sensing photography). Since they both are wide filed imaging and CSP is a passive receiving imaging technology, SIM and CSP have potential to combine closely and achieve super-resolution and highspeed imaging.