Miracle-dz/UniFAR-FTUs huggingface dataset:
The expansion and severity of chronic MS lesions follows a periventricular gradient

Background and Objectives: Expansion of chronic lesions in multiple sclerosis (MS) patients and recently described cerebrospinal fluid (CSF)-related gradient of tissue damage are linked to microglial activation. The aim of this study was to investigate whether lesion expansion is associated with proximity to ventricular CSF spaces. Methods: Pre- and post-gadolinium three-dimensional (3D)-T1, 3D FLAIR and diffusion tensor images were acquired from 36 relapsing-remitting MS (RRMS) patients. Lesional activity was analysed between baseline and 48 months at different distances from the CSF using successive 1 mm thick concentric bands radiating from the ventricles. Results: Voxel-based analysis of the rate of lesion expansion demonstrated a clear periventricular gradient decreasing away from the ventricles. This was particularly apparent when lesions of equal diameter were analysed. Periventricular lesional tissue showed higher degree of tissue destruction at baseline that significantly increased during follow-up in bands close to CSF. This longitudinal change was proportional to degree of lesion expansion. Lesion-wise analysis revealed a gradual, centrifugal decrease in the proportion of expanding lesions from the immediate periventricular zone. Discussion: Our data suggest that chronic white matter lesions in close proximity to the ventricles are more destructive, show a higher degree of expansion at the lesion border and accelerated tissue loss in the lesion core.
SUCCESS FACTORS OF HOME-BASED DIGITAL ENTREPRENEURS : EMPIRICAL STUDY

The pandemic made a great impact on our lives. It caused many business activities to shut down and their employees are forced to leave their jobs. As a result, people are looking for other sources to earn their livelihood. Businesses are also forced to transform their business into online. Social media networks such as Facebook, Instagram, WhatsApp have created tremendous opportunities to start a home-based business for these people. Despite having many negative ripples effects on global business due to pandemics, home-based digital businesses have been accelerated extremely. Hence, the study investigates the success factors of home-based digital businesses by applying social capital theory. A total of 222 home-based digital entrepreneurs who are marketing their products through Facebook and Instagram were taken part in the study. The study adopted a quantitative method and data analysed PLS method y using Adanco software. The findings showed that ethicality, human capital, and social capital, and innovation are the determinant of success factors of home-based businesses. The study contributed to the academic literature on home-based businesses and insights of the success factors of home-based entrepreneurs for people who intend to venture into home-based businesses using social media network platforms.
Self-Instantiated Recurrent Units with Dynamic Soft Recursion

While standard recurrent neural networks explicitly impose a chain structure on different forms of data, they do not have an explicit bias towards recursive self-instantiation where the extent of recursion is dynamic. Given diverse and even growing data modalities (e.g., logic, algorithmic input and output, music, code, images, and language) that can be expressed in sequences and may beneﬁt from more architectural ﬂexibility, we propose the self-instantiated recurrent unit (Self-IRU) with a novel inductive bias towards dynamic soft recursion. On one hand, the Self-IRU is characterized by recursive self-instantiation via its gating functions, i.e., gating mechanisms of the Self-IRU are controlled by instances of the Self-IRU itself, which are repeatedly invoked in a recursive fashion. On the other hand, the extent of the Self-IRU recursion is controlled by gates whose values are between 0 and 1 and may vary across the temporal dimension of sequences, enabling dynamic soft recursion depth at each time step. The architectural ﬂexibility and effectiveness of our proposed approach are demonstrated across multiple data modalities. For example, the Self-IRU achieves state-of-the-art performance on the logical inference dataset [Bowman et al., 2014] even when comparing with competitive models that have access to ground-truth syntactic information.
Halal Industry’s Organizational Performance Factors: A Systematic Literature Review

The global Halal industry is one of the world’s fastest-growing consumer segments, as evidenced by substantial research and published papers. This paper aims to identify and characterize the factors that influence organizational performance in companies within the Halal industry. It also offers an overview of the factors influencing companies’ organizational performance in various Halal industry sectors. A systematic Literature Review (SLR) of the Web of Science, Scopus, Emerald, and Science Direct databases guided by PRISMA (Preferred Reporting Items for Systematic Review and Meta- Analyses) protocol was used to analyze the data. The electronic database’s search results included articles focused on halal certification, halal product development, and supply chain management. A methodical review of these articles found four main factors that influence the organizational performance of halal companies: 1) the strategic management of Halal business, 2) the management of Halal requirements, 3) the understanding of consumer demands, and 4) the creation of the best organizational environment. This review provides detailed guidelines based on important research findings on how Halal organizations can manage and excel in their businesses. As a result, companies can better minimize the effect of volatile, uncertain, complex, and ambiguous (VUCA) environments in managing the business.
The Oxford Handbook of Political Consumerism Veganism and plant-based eating: analysis of interplay between discursive strategies and lifestyle political consumerism

In recent years, there has been an increased mobilization around vegan and plant-based diets. The chapter will analyze this mobilization, the evolution of the images and practices of vegan eating and what kind of political consumerism they constitute. We show how vegan eating takes place as an assemblage of several actors and platforms, such as consciousness-raising campaigns, vegan bloggers, pledges and festivals and new vegan foods marketed as ‘cool’ and suitable for everyone. The concepts of boycott and buycott are too narrow to adequately describe veganism as political consumerism. Instead, discursive and lifestyle political consumerism and their interplay characterize the current building of new images and communities. The Internet and social media have a central role in shaping the cultural contents of the ‘veggie trend’. Moreover, vegan eating is not always inspired by otheroriented motives, but also by self-regarding motives, such as health, pleasure and distinction.
Latin American integration and the survival of trade relationships

In a previous work, Besedes et al. (2015) studied the effects of trade agreements on the survival of trade relationships. Their main results were that trade agreements significantly increase the survival of trade relationships which had already started when the agreement takes place. Moreover, they find that these agreements increase the hazard and reduce the initial volumes for those that start afterwards.These results, however, may not be homogeneous across regions as aggregation may hide different reactions of trade to economic integration agreements (EIAs). In the present paper we use annual trade data at the 5-digit SITC level for Latin America exports to over 150 countries from 1962 to 2009. We analyze whether the effects of EIAs on trade survival, initial volumes of trade and export growthare the same as those described for the whole world (mostly, they are not). As our main contribution, we examine if these effects differ depending on the required depth for an agreement to be considered as an EIA (they do). We also test if the quality of trade agreements, as measured by Kohl et al. (2016) has an impact on the survival of trade relationships (it does).
An Analysis of Politeness Strategy and Cooperation Principle in ‘Gravity’movie

This research studies about the politeness strategies and cooperation principle that are used in ‘Gravity’ movie. This was adescriptive qualitative research, which used the movie transcript as the data source. Then, the researcher used politeness strategies theory by Brown and Levinson (1987) and cooperation principle by Grice (1975) to analyze the data. The result from the analysis showed that 1) all politeness strategies theories proposed by Brown and Levinson (1987) are employed in the script and 2) out of four strategies, the most used strategy was positive politeness strategy. Then, from the result, it can be concluded that.
The Texas Sharpshooter in the Three Grand Tours (1933-2013): No Evidence for Superior Time Trial Performances in the "Epo Era"

Studies examining effects of doping in professional road racing building on archival records of the three major European stage races—the Tour de France, Giro d’Italia, and Vuelta a Espana—con- cluded that riders’ final performances in the “epo era” (>19.
Artificial neural network for computing the resonant frequency of circular patch antennas

In this paper, an artificial neural network (ANN) model for computing the resonant frequency of circular patch antennas (CPA) based on the feed‐forward network and back‐propagation algorithm is presented. The network is trained with the data obtained from CPA measurements. The network is trained by varying the patch radius, the height of the substrate, and the dielectric permittivity. The parameters of the proposed ANN model are the learning rate (0.0125), the number of epochs for training (399), the performance goal (1 × 10−5) and the parameters for the network, the number of hidden layers (two), with 20 neurons for each hidden layer, three neurons for the input layer, and a single neuron in the output layer. the results obtained from the trained neural network are compared with the values obtained from mathematical computations and from measurements presented in other works. The proposed ANN with two hidden layers gives accurate results and requires no additional training epochs. © 2005 Wiley Periodicals, Inc. Microwave Opt Technol Lett 47: 564–566, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.21230
Three-dimensional kinematic evaluation of lateral suture stabilization in an in vitro canine cranial cruciate deficient stifle model

The impact of surgical correction of cranial cruciate ligament rupture (CCLR) on 3D kinematics has not been thoroughly evaluated in dogs. The success of current techniques remains limited, as illustrated by suboptimal weightbearing and progression of osteoarthritis. The inability to restore the stifle’s 3D kinematics might be a key element in understanding these suboptimal outcomes. The objective of this study was to evaluate the impact of lateral suture stabilization (LSS) on the 3D kinematics of the canine stifle joint. We hypothesized that LSS would not restore 3D kinematics in our model. Ten cadaveric pelvic limbs collected from large dogs (25–40 kg) were tested using a previously validated apparatus that simulates gait. Three experimental conditions were compared: (a) intact stifle; (b) unstable stifle following cranial cruciate ligament transection (CCLt) and (c) CCLt stabilized by LSS. Three-dimensional kinematics were collected through 5 loading cycles simulating the stance phase of gait and curves were analyzed using a Wilcoxon signed-rank test. LSS restored baseline kinematics for the entire stance phase for cranial and lateromedial translation, flexion, and abduction. It restored distraction over 90% of the stance phase. Internal rotation was limited, but not restored. This in vitro study had limitations, as it used a simplified model of stifle motion and weight-bearing. The results of this study report that LSS can restore physiologic 3D kinematics largely comparable to those of healthy stifles. Suboptimal outcome in patients following CCLR stabilization by LSS may therefore result from causes other than immediate postoperative abnormal 3D kinematics.
Association of vitamin D, BMD and knee osteoarthritis in postmenopausal women

Objectives: The aim of this study was to analyze the association of knee OA with bone mineral density (BMD) and vitamin D serum levels in postmenopausal women. Methods: A cross-sectional study including 240 postmenopausal women with knee OA was conducted. Demographic data were recorded along with balance and functionality scores. Knee OA severity was assessed by the radiological Kellgren & Lawrence scale. BMD and T-scores were calculated in hips and lumbar spine. Serum levels of vitamin D were also measured. Results: High BMI (p<0.005), high number of children (p=0.022) and family history of hip fracture (p=0.011) are significantly associated with knee OA severity. Lumbar spine OP is negatively associated with knee OA (p<0.005). A significant difference was detected between vitamin D deficiency and severe knee OA, adjusted for BMD [OR (95%CI); 3.1 (1.6-6.1), p=0.001]. BMD does not affect the relationship of vitamin D levels in relation to OA and vitamin D levels do not affect the relationship of BMD with OA. Conclusions: Low BMD has a protective role against knee OA while vitamin D deficiency contributes significantly to knee OA severity. However, the association between OA and OP is not affected by vitamin D deficiency and the association of OA and vitamin D serum levels is not affected by BMD.
THE ESS LINAC SIMULATOR: A FIRST BENCHMARK WITH TRACEWIN

The ESS Linac Simulator, ELS, will be the core of the online model used in the normal operations of the ESS linac. ESS Linac Simulator will operate through the eXtensible Accelerator Language, XAL, in order to provide an effective interface capable to simulate and predict the beam dynamics of the accelerator. The ELS is capable of simulating the dynamics of the beam envelope in both transverse and longitudinal planes in real time. In order to validate the effectiveness of the physics implemented, the ELS calculations are here benchmarked with TraceWin: the simulation code used for the design of the accelerator.
MLL1 is regulated by KSHV LANA and is important for virus latency

Abstract Mixed lineage leukemia 1 (MLL1) is a histone methyltransferase. Kaposi's sarcoma-associated herpesvirus (KSHV) is a leading cause of malignancy in AIDS. KSHV latently infects tumor cells and its genome is decorated with epigenetic marks. Here, we show that KSHV latency-associated nuclear antigen (LANA) recruits MLL1 to viral DNA where it establishes H3K4me3 modifications at the extensive KSHV terminal repeat elements during primary infection. LANA interacts with MLL1 complex members, including WDR5, integrates into the MLL1 complex, and regulates MLL1 activity. We describe the 1.5-Å crystal structure of N-terminal LANA peptide complexed with MLL1 complex member WDR5, which reveals a potential regulatory mechanism. Disruption of MLL1 expression rendered KSHV latency establishment highly deficient. This deficiency was rescued by MLL1 but not by catalytically inactive MLL1. Therefore, MLL1 is LANA regulable and exerts a central role in virus infection. These results suggest broad potential for MLL1 regulation, including by non-host factors.
A distinct complex of PRP19-related and trypanosomatid-specific proteins is required for pre-mRNA splicing in trypanosomes

Abstract The pre-mRNA splicing factor PRP19 is recruited into the spliceosome after forming the PRP19/CDC5L complex in humans and the Nineteen complex in yeast. Additionally, ‘PRP19-related’ proteins enter the spliceosome individually or in pre-assemblies that differ in these systems. The protistan family Trypanosomatidae, which harbors parasites such as Trypanosoma brucei, diverged early during evolution from opisthokonts. While introns are rare in these organisms, spliced leader trans splicing is an obligatory step in mRNA maturation. So far, ∼70 proteins have been identified as homologs of human and yeast splicing factors. Moreover, few proteins of unknown function have recurrently co-purified with splicing proteins. Here we silenced the gene of one of these proteins, termed PRC5, and found it to be essential for cell viability and pre-mRNA splicing. Purification of PRC5 combined with sucrose gradient sedimentation revealed a complex of PRC5 with a second trypanosomatid-specific protein, PRC3, and PRP19-related proteins SYF1, SYF3 and ISY1, which we named PRP19-related complex (PRC). Importantly, PRC and the previously described PRP19 complex are distinct from each other because PRC, unlike PRP19, co-precipitates U4 snRNA, which indicates that PRC enters the spliceosome prior to PRP19 and uncovers a unique pre-organization of these proteins in trypanosomes.
Cosmic adventures in stringland: Scattering of bosonic and fermionic fields in gravitating cosmic string spacetimes

Cosmic strings are line-like topological defects expected to have formed during cosmological phase transitions in the early universe when the Higgs field acquired a non-vanishing expectation value. Because of being thin, on a cosmological scale, their gravitational effects are usually studied using the wire approximation, in which the string has a negligible width. Although the wire approximation seems reasonable in the cosmological context, local gravitational interaction with matter fields can be significant when considering a non-vanishing radius. Generally, the spacetime of a gravitating vortex is flat at the center, has a localized curvature at some finite distance from the core, and is flat and conical far from the center. The conical structure is characterized by an angular variable ranging from 0 to less than 2π, i.e., the space has an angular deficit. This work shows that when considering a scalar field scattering in a gravitating cosmic string spacetime, the standard partial-wave approach’s scattering amplitude is singular. In order to avoid the divergence caused by the spacetime asymptotically conical structure, we propose a modification of the asymptotic ansatz in the partial-wave formalism and find the corrections in the phase-shift and total scattering cross-section. We also developed a toy model for the spacetime metric of a cosmic string and showed how local interaction with the vortex gauge field affects the scalar field total cross-section. Then we apply this formalism to a Dirac field and show the explicit formula for the fermionic total cross-section. Finally, we study the scattering of bosonic and fermionic fields in the spacetime of an abelian and a nonabelian gravitating cosmic strings and show that the cross-sections have damped oscillations. In order to understand the origin of this behavior, we used the aforementioned toy model to show that the spacetime particular asymptotical structure causes the observed oscillations.
PRONTO: Preamble Overhead Reduction With Neural Networks for Coarse Synchronization

In IEEE 802.11 WiFi-based waveforms, the receiver performs coarse time and frequency synchronization using the first field of the preamble known as the legacy short training field (L-STF). The L-STF occupies upto 40% of the preamble length and takes upto $32 \mu \text{s}$ of airtime. With the goal of reducing communication overhead, we propose a modified waveform, where the preamble length is reduced by eliminating the L-STF. To decode this modified waveform, we propose a neural network (NN)-based scheme called PRONTO that performs coarse time and frequency estimations using other preamble fields, specifically the legacy long training field (L-LTF). Our contributions are threefold: (i) We present PRONTO featuring customized convolutional neural networks (CNNs) for packet detection and coarse carrier frequency offset (CFO) estimation, along with data augmentation steps for robust training. (ii) We propose a generalized decision flow that makes PRONTO compatible with legacy waveforms that include the standard L-STF. (iii) We validate the outcomes on an over-the-air WiFi dataset from a testbed of software defined radios (SDRs). Our evaluations show that PRONTO can perform packet detection with 100% accuracy, and coarse CFO estimation with errors as small as 3%. We demonstrate that PRONTO provides upto 40% preamble length reduction with no bit error rate (BER) degradation. We further show that PRONTO is able to achieve the same performance in new environments without the need to re-train the CNNs. Finally, we experimentally show the speedup achieved by PRONTO through GPU parallelization over the corresponding CPU-only implementations.
Generating Photo-realistic Images from LiDAR Point Clouds with Generative Adversarial Networks

We examined the feasibility of generative adversarial networks (GANs) to generate photo-realistic images from LiDAR point clouds. For this purpose, we created a dataset of point cloud–image pairs and trained the GAN to predict photo-realistic images from LiDAR point clouds containing reflectance and distance information. Our models learned how to predict realistically looking images from just point cloud data, even images with black cars. Black cars are difficult to detect directly from point clouds because of their low level of reflectivity. This approach might be used in the future to perform visual object recognition on photo-realistic images generated from LiDAR point clouds. In addition to the conventional LiDAR system, a second system that generates photo-realistic images from LiDAR point clouds would run simultaneously for visual object recognition in real-time. In this way, we might preserve the supremacy of LiDAR and benefit from using photorealistic images for visual object recognition without the usage of any camera. In addition, this approach could be used to colorize point clouds without the usage of any camera images.
The fixed-cycle traffic-light queue with multiple lanes and temporary blockages

Traffic-light modelling is a complex task, because many factors have to be taken into account. In particular, capturing all traffic flows in one model can significantly complicate the model. Therefore, several realistic features are typically omitted from most models. We introduce a mechanism to include pedestrians and focus on situations where they may block vehicles that get a green light simultaneously. More specifically, we consider a generalisation of the Fixed-Cycle Traffic-Light (FCTL) queue. Our framework allows us to model situations where (part of the) vehicles are blocked, e.g. by pedestrians that block turning traffic and where several vehicles might depart simultaneously, e.g. in case of multiple lanes receiving a green light simultaneously. We rely on probability generating function and complex analysis techniques which are also used to study the regular FCTL queue. We study the effect of several parameters on performance measures such as the mean delay and queue-length distribution.