Miracle-dz/UniFAR-FTUs huggingface dataset:
2,2′,2′′-[(2,4,6-Trimethoxybenzene-1,3,5-triyl)tris(methylene)]tris(isoindole-1,3-dione)

The title molecule, C36H27N3O9, adopts an almost symmetric conformation in which the mean planes of the phthalimido units are inclined at dihedral angles of 81.1 (1), 85.3 (1) and 86.3 (1)° with respect to the plane of the central aromatic ring. The O atoms are involved in intra- and intermolecular C—H⋯O hydrogen bonding. The crystal structure also features π–π arene interactions [minimum ring centroid separation = 3.683 (2) Å]. The present mode of non-covalent interactions leads to a three-dimensional supramolecular architecture.
4-Benzyloxy-3-(2,4-dichlorophenyl)-1-oxaspiro[4.5]dec-3-en-2-one

In the title compound, C22H20Cl2O3, the cyclohexyl ring adopts a chair conformation. The furanyl ring plane makes dihedral angles of 70.10 (2) and 86.12 (3)° with the 2,4-dichlorophenyl ring and aromatic ring of the benzyl group, respectively. The crystal structure features weak intermolecular C—H⋯O and C—H⋯Cl hydrogen bonds.
1-(3-Fluorophenyl)-4,4,6-trimethyl-3,4-dihydropyrimidine-2(1H)-thione

In the title compound, C13H15FN2S, the dihydropyrimidine ring is essentially planar, with a maximum deviation of 0.086 (3) Å from the mean plane of the rest of the ring for the dimethylated C atom. The benzene ring is almost perpendicular to the dihydropyrimidine ring, with a dihedral angle of 83.97 (14)°. The crystal packing is characterized by centrosymmetric dimers resulting from pairs of intermolecular N—H⋯S hydrogen bonds. There are also C—H⋯π interactions.
1,3-Dimethyl-4-phenylsulfanyl-1H-pyrazol-5-ol

In the title compound, C11H12N2OS, the pyrazole ring makes a dihedral angle of 85.40 (8)° with the phenyl ring. In the crystal, intermolecular N—H⋯O and C—H⋯O hydrogen bonds link molecules into a two-dimensional network parallel to the bc plane.
5-Fluoro-1-(4-methoxybenzyl)indoline-2,3-dione

In the title compound, C16H12FNO3, the dihedral angle between the benzene ring and the plane of the indole ring system is 71.60 (6)°. In the crystal, molecules stack along the b axis through π–π interactions between the adjacent indole-2,3-dione units with a centroid–centroid distance of 3.649 (3) Å. Intermolecular C—H⋯O=C and C—H⋯π interactions further stabilize the structure, forming a three-dimensional framework.
Bonny babies? Motherhood and nurturing in the age of obesity

The ‘bonny’ baby is traditionally the prized emblem of good health, yet there has been speculation that within the context of rising levels of obesity and diabetes within childbearing populations that this may change. Within epidemiological understandings, obesity and diabetes in pregnancy are strongly implicated in the increasing numbers of very large babies. Given the power of biomedical risk discourses to shape women's experiences of pregnancy, motherhood and infant feeding, lay understandings of infant size/health and the ‘bonny’ baby are perhaps subject to revision. This paper, draws upon critical obesity studies and contemporary commentaries regarding ‘parental causality’ to discuss the medicalisation (through BMI) and moralisation of large bodies in pregnancy as ‘obese’ and (by implication) the creation of subjects ‘at risk’ to themselves and their foetus/infant. Through an analysis of longitudinal interview data from large-bodied women in their transitions to motherhood, this paper explores how this powerful biomedical discourse plays out in women's reported interactions with maternity professionals in pregnancy, birth and the months that follow. The paper concludes by discussing the implications of such findings for contemporary parenting, policy and professional practice.
2-(1,2-Dimethyl-1H-indol-3-yl)-1-{5-[3-(1,3-dioxolan-2-yl)phenyl]-2-methylthiophen-3-yl}-3,3,4,4,5,5-hexafluorocyclopent-1-ene

The title compound, C29H23F6NO2S, a member of a new family of photochromic diarylethene compounds having an unsymmetrically substituted hexafluorocyclopentene unit, displays dihedral angles between the indole and thiophene rings of 52.5 (4)°, and between the indole ring and the planar C—C=C—C unit of the cyclopentene ring of 53.8 (6)°. The distance between the potentially reactive C atoms from the two heteroaryl substituents of 3.817 (6) Å is proven to be short enough for photocyclization to occur.
High Intensity Circuit Training on Body Composition, Cardiovascular Risk Factors and Physical Fitness Status Among Overweight and Obese Female Students

Obesity is characterised by an excessive amount of body fat accumulation which leads to multiple chronic diseases. Bodies of evidence showed physical activity (PA) plays an important role in the management of obesity. The aim of this study to measure the effect of High Intensity Circuit Training (HICT) on body composition, cardiovascular risk factors, and physical fitness among overweight and obese female students. Subjects were recruited among students of the Faculty of Health Science, UKM. They were assigned into intervention and control group with. Intervention group (n = 10) underwent HICT, thrice weekly for 12 weeks. While control (n = 10) were asked continue their daily routine without any changes. Body body composition, (BMI, fat percentage, fat and muscle mass), biochemical parameters (Glucose, Total Cholesterol, Triglyceride, Blood Pressure) and physical fitness (cardiorespiratory, muscle strength and agility) were assessed at baseline and after 12 weeks training. Body weight and composition revealed no significant difference (p > 0.05) between group and no interaction between time and group (p > 0.05). Total cholesterol, triglycerides, systolic blood pressure and diastolic blood pressure also showed no significant difference (p > 0.05) between group and also no interaction (p > 0.05) between time and group. However, blood glucose level showed significant interaction (p 0.05) between time and group after 12 week exercise training. Agility test also showed no significant difference (p > 0.05) between group and no interaction (p > 0.05) was observed after end of 12 week HICT. In conclusion, this study showed that High Intensity Circuit Training can significantly improving the blood glucose level, VO 2max and muscle strength of the subjects however revealed no significant changes to other parameters. Key words: Obese Students, HICT, Body Composition, Physical Fitness
2,2′-Dimethoxy-6,6′-dinitrobiphenyl

In the title compound, C14H12N2O6, the half molecule in the asymmetric unit of the cell is completed by a crystallographic twofold rotation axis, and the two benzene rings of the complete molecule make a dihedral angle of 60.5 (3)°. Furthermore, intermolecular weak C—H⋯O hydrogen bonds link adjacent molecules, forming a two-dimensional sheet. These sheets are stablized by face-to-face weak π–π contacts [centroid–centroid distance = 3.682 (1) Å] between the nearly parallel [dihedral angle = 0.12 (7)°] benzene rings of the neighboring molecules, resulting in a three-dimensional network.
1-(4-Aminophenyl)-3-[2-(trifluoromethyl)phenyl]prop-2-en-1-one

The title compound, C16H12F3NO, a derivative of biologically active chalcones, comprises two benzene rings and a central –CH=CH—C(=O)– unit. The dihedral angle between the two rings is 10.9 (1)° and the molecule adopts an E configuration about the central olefinic bond. The crystal structure is stabilized by intermolecular N—H⋯O and N—H⋯N hydrogen bonds.
{2,7-Diethoxy-8-[(naphthalen-1-yl)carbonyl]naphthalen-1-yl}(naphthalen-1-yl)methanone

In the title compound, C36H28O4, the 1-naphthoyl groups at the 1- and 8-positions of the central 2,7-diethoxynaphthalene ring system are aligned almost antiparallel and make a dihedral angle of 76.59 (4)°. The dihedral angles between the central 2,7-diethoxynaphthalene ring system and the terminal naphthalene ring systems are 86.48 (4) and 83.97 (4)°. In the crystal, C—H⋯π interactions between the central naphthalene ring systems and the naphthoyl groups are observed along the a axis, with the molecules forming a columnar structure. The columns are linked into chains parallel to the b axis by C—H⋯O interactions.
1-(4-Fluorophenyl)-3-methyl-4-phenylsulfanyl-1H-pyrazol-5(4H)-one

The title compound, C16H13FN2OS, has undergone enol-to-keto tautomerism during the crystallization process. The 1H-pyrazole-5-one ring [maximum deviation = 0.0198 (11) Å] is inclined at angles of 33.10 (5) and 79.57 (5)° with respect to the fluorophenyl [maximum deviation = 0.0090 (12) Å] and phenylthiol [maximum deviation = 0.0229 (3) Å] rings attached to it. In the crystal, neighbouring molecules are linked into inversion dimers, generating R 2 2(8) ring motifs. These dimers are further linked into two-dimensional arrays parallel to the bc plane via intermolecular N—H⋯O, C—H⋯F and C—H⋯O hydrogen bonds. The crystal is further stabilized by weak π–π [centroid–centroid distance = 3.6921 (7) Å] and C—H⋯π interactions.
2,7-Bis(2-nitrophenyl)-9-octyl-9H-carbazole

The title compound, C32H31N3O4, was obtained in a Suzuki coupling of carbazole diboronic acid and bromonitrobenzene. In the crystal, the molecule adopts a non-symmetric conformation. The carbazole ring system is approximately planar [maximum deviation from the least-squares plane = 0.039 (2) Å]. The planes of the carbazole unit and the benzene rings subtend dihedral angles of 48.42 (7) and 41.81 (6)°. The dihedral angles between the planes of the nitrophenyl rings and the nitro groups are 44.34 (19) and 61.64 (15)°. The crystal is built from two strands of parallel molecules with interdigitated octyl chains. These strands are symmetry related by a twofold screw axis.
(1S,3′S,3a′R,6′S)-6′-(2-Chlorophenyl)-3′-[(2R,3S)-1-(4-methoxyphenyl)-4-oxo-3-phenylazetidin-2-yl]-2-oxo-3′,3′a,4′,6′-tetrahydro-2H,2′H-spiro[acenaphthylene-1,1′-pyrrolo[1,2-c][1,3]thiazole]-2′,2′-dicarbonitrile

The molecular conformation of the title compound, C41H29ClN4O3S, is stabilized by intramolecular C—H⋯O and C—H⋯Cl hydrogen bonds. The thiazole ring adopts an envelope conformation with the N atom as the flap, while the pyrrolidine ring has a twisted conformation on the N—C bond involving the spiro C atom. The β lactam ring makes dihedral angles of 39.74 (15) and 16.21 (16)° with the mean planes of the thiazole and pyrrolidine rings, respectively. The thiazole ring mean plane makes dihedral angles of 23.79 (13) and 70.88 (13) ° with the pyrrolidine and cyclopentane rings, respectively, while the pyrrolidine ring makes a dihedral angle of 85.63 (13)° with the cyclopentane ring. The O atom attached to the β lactam ring deviates from its mean plane by 0.040 (2) Å, while the O atom attached to the cyclopentane ring deviates from its mean plane by 0.132 (2) Å. In the crystal, molecules are linked by C—H⋯O hydrogen bonds, forming chains along [010], and C—H⋯π and π-π interactions [centroid-centroid distance = 3.6928 (17) Å].
1-(2-Phenylethyl)adamantane

In the title compound, C18H24, the adamantane cage consists of three fused cyclohexane rings in almost ideal chair conformations, with C—C—C angles in the range 108.0 (14)–111.1 (15)°. The phenyl and 1-adamantyl substituents adopt anti orientations with a C—C—C—C torsion angle of 177.10 (16)°. In the crystal packing, the molecules are linked by weak C—H⋯π interactions into chains along the a axis.
A Study to Know the Prevalence and Awareness of Hypertension in Market Population of Ras Al Khaimah, UAE

Background: Hypertension is an important public health challenge in both economically developing and a developed country is a commonest non-communicable disease and a global epidemic. The global prevalence of hypertension has been increasing. Method: In a cross-sectional prospective study on unselected population of market workers were screened for hypertension and its risk factors by anthropometric measurements and a structured questionnaire for demographic and awareness (Knowledge and attitude) of these subjects regarding hypertension. Hypertension was defined as BP ≥ 140 and/or ≥ 90 mmHg or being on drug therapy. Results: Fifty percent of the screened populations were hypertensive. Of this number, 35% were not aware of their condition and diagnosed on screening. 44% had high BMI. Conclusion: The prevalence of hypertension in market workers in this study was 50%, and the majority of them were unaware of their disease.
No Representation without Transformation

We extend the framework of variational autoencoders to represent transformations explicitly in the latent space. In the family of hierarchical graphical models that emerges, the latent space is populated by higher order objects that are inferred jointly with the latent representations they act on. To explicitly demonstrate the effect of these higher order objects, we show that the inferred latent transformations reflect interpretable properties in the observation space. Furthermore, the model is structured in such a way that in the absence of transformations, we can run inference and obtain generative capabilities comparable with standard variational autoencoders. Finally, utilizing the trained encoder, we outperform the baselines by a wide margin on a challenging out-of-distribution classification task.
Realizing the Frugal 5G Network

In order to make effective use of the Internet, broadband connectivity is a pre-requisite. However, in the majority of rural areas in developing countries, high-speed connectivity is unavailable. The Frugal 5G network architecture presented in this paper aims at enabling broadband in rural areas by addressing the challenges associated with it. The work presented in this paper is a development over our previous work, in which we proposed abstract network architecture for Frugal 5G. In this paper, we provide an innovative solution to realize the Frugal 5G network. We identify the key system requirements and show that the proposed solution enables an uncomplicated and flexible realization of the Frugal 5G network. We are currently building a testbed to implement the proposed changes.
Lightweight Container-based User Environment

Modern operating systems all support multi-users that users could share a computer simultaneously and not affect each other. However, there are some limitations. For example, privacy problem exists that users are visible to each other in terms of running processes and files. Moreover, users have little freedom to customize the system environment. Last, it is a burden for system administrator to safely manage and update system environment while satisfying multiple users. Facing the above problems, this paper proposes CUE, a Lightweight Container-based User Environment. CUE proposes a new notion that stands in between application container and operating system container:user container. CUE is able to give users more flexibility to customize their environment, achieve privacy isolation, and make system update easier and safer. Its goal is to optimize and enhance the multi-user notion of current operating system and being lightweight. Moreover, it is able to facilitate application deployment in high performance clusters. It is currently deployed in NUDT's Tianhe E prototype supercomputer. Experiment results show that it introduces negligible overhead.
Cascaded Deep Neural Networks for Retinal Layer Segmentation of Optical Coherence Tomography with Fluid Presence

Optical coherence tomography (OCT) is a non-invasive imaging technology which can provide micrometer-resolution cross-sectional images of the inner structures of the eye. It is widely used for the diagnosis of ophthalmic diseases with retinal alteration, such as layer deformation and fluid accumulation. In this paper, a novel framework was proposed to segment retinal layers with fluid presence. The main contribution of this study is two folds: 1) we developed a cascaded network framework to incorporate the prior structural knowledge; 2) we proposed a novel deep neural network based on U-Net and fully convolutional network, termed LF-UNet. Cross validation experiments proved that the proposed LF-UNet has superior performance comparing with the state-of-the-art methods, and incorporating the relative distance map structural prior information could further improve the performance regardless the network.
Learning Latent State Spaces for Planning through Reward Prediction

Model-based reinforcement learning methods typically learn models for high-dimensional state spaces by aiming to reconstruct and predict the original observations. However, drawing inspiration from model-free reinforcement learning, we propose learning a latent dynamics model directly from rewards. In this work, we introduce a model-based planning framework which learns a latent reward prediction model and then plans in the latent state-space. The latent representation is learned exclusively from multi-step reward prediction which we show to be the only necessary information for successful planning. With this framework, we are able to benefit from the concise model-free representation, while still enjoying the data-efficiency of model-based algorithms. We demonstrate our framework in multi-pendulum and multi-cheetah environments where several pendulums or cheetahs are shown to the agent but only one of which produces rewards. In these environments, it is important for the agent to construct a concise latent representation to filter out irrelevant observations. We find that our method can successfully learn an accurate latent reward prediction model in the presence of the irrelevant information while existing model-based methods fail. Planning in the learned latent state-space shows strong performance and high sample efficiency over model-free and model-based baselines.
Comparison of Neuronal Attention Models

Recent models for image processing are using the Convolutional neural network (CNN) which requires a pixel per pixel analysis of the input image. This method works well. However, it is time-consuming if we have large images. To increase the performance, by improving the training time or the accuracy, we need a size-independent method. As a solution, we can add a Neuronal Attention model (NAM). The power of this new approach is that it can efficiently choose several small regions from the initial image to focus on. The purpose of this paper is to explain and also test each of the NAM's parameters.
Learning to Recommend via Meta Parameter Partition

In this paper we propose to solve an important problem in recommendation -- user cold start, based on meta leaning method. Previous meta learning approaches finetune all parameters for each new user, which is both computing and storage expensive. In contrast, we divide model parameters into fixed and adaptive parts and develop a two-stage meta learning algorithm to learn them separately. The fixed part, capturing user invariant features, is shared by all users and is learned during offline meta learning stage. The adaptive part, capturing user specific features, is learned during online meta learning stage. By decoupling user invariant parameters from user dependent parameters, the proposed approach is more efficient and storage cheaper than previous methods. It also has potential to deal with catastrophic forgetting while continually adapting for streaming coming users. Experiments on production data demonstrates that the proposed method converges faster and to a better performance than baseline methods. Meta-training without online meta model finetuning increases the AUC from 72.24% to 74.72% (2.48% absolute improvement). Online meta training achieves a further gain of 2.46\% absolute improvement comparing with offline meta training.
DClaims: A Censorship Resistant Web Annotations System using IPFS and Ethereum

The proliferation of unreliable and biased information is a significant problem on the Internet. To assess the credibility of the information retrieved from news websites and other sources, users often resort to social platforms looking for confirmation with trustworthy parties. However, users may be faced with considerable obstacles posed by the platform provider, who can prevent access to certain content. This paper presents DClaims, a system that provides a censorship-resistant distributed service for the exchange of information over the Internet using web annotations. DClaims' fully decentralized architecture relies on Inter-Planetary File System (IPFS) and Ethereum blockchain, both of which offer desirable censorship resistant properties. DClaims is implemented as a web annotations browser extension which allows for the classification of news articles, on news websites. From our evaluation of the system, we conclude that a large scale implementation of the system is practical and economically viable.
(3-Anilino-1-phenyliminothioureato)chloridodimethyltin(IV)

In the title compound, [Sn(CH3)2(C13H11N4S)Cl], the Sn atom is five-coordinated in a distorted trigonal-bipyramidal geometry, with two methyl groups and one S atom in the equatorial plane, and one N atom and the Cl atom occupying the apical positions.
ClusterFit: Improving Generalization of Visual Representations

Pre-training convolutional neural networks with weakly-supervised and self-supervised strategies is becoming increasingly popular for several computer vision tasks. However, due to the lack of strong discriminative signals, these learned representations may overfit to the pre-training objective (e.g., hashtag prediction) and not generalize well to downstream tasks. In this work, we present a simple strategy - ClusterFit to improve the robustness of the visual representations learned during pre-training. Given a dataset, we (a) cluster its features extracted from a pre-trained network using k-means and (b) re-train a new network from scratch on this dataset using cluster assignments as pseudo-labels. We empirically show that clustering helps reduce the pre-training task-specific information from the extracted features thereby minimizing overfitting to the same. Our approach is extensible to different pre-training frameworks -- weak- and self-supervised, modalities -- images and videos, and pre-training tasks -- object and action classification. Through extensive transfer learning experiments on 11 different target datasets of varied vocabularies and granularities, we show that ClusterFit significantly improves the representation quality compared to the state-of-the-art large-scale (millions / billions) weakly-supervised image and video models and self-supervised image models.
Tensor Low Rank Modeling and Its Applications in Signal Processing

Modeling of multidimensional signal using tensor is more convincing than representing it as a collection of matrices. The tensor based approaches can explore the abundant spatial and temporal structures of the mutlidimensional signal. The backbone of this modeling is the mathematical foundations of tensor algebra. The linear transform based tensor algebra furnishes low complex and high performance algebraic structures suitable for the introspection of the multidimensional signal. A comprehensive introduction of the linear transform based tensor algebra is provided from the signal processing viewpoint. The rank of a multidimensional signal is a precious property which gives an insight into the structural aspects of it. All natural multidimensional signals can be approximated to a low rank signal without losing significant information. The low rank approximation is beneficial in many signal processing applications such as denoising, missing sample estimation, resolution enhancement, classification, background estimation, object detection, deweathering, clustering and much more applications. Detailed case study of the ways and means of the low rank modeling in the above said signal processing applications are also presented.
3-(2-Chlorophenyl)-4-hydroxyfuran-2(5H)-one

In the title molecule, C10H7ClO3, the butyrolactone core, a furan-2(5H)-one, forms a dihedral angle of 59.21 (5)° with the benzene ring. In the crystal, two types of hydrogen bonds (O—H⋯O and C—H⋯Cl) link molecules into infinite chains along the b axis. π–π contacts [centroid–centroid distances = 3.6359 (10) and 3.8776 (11) Å] link the chains into a three-dimensional network.