DNeRV: Modeling Inherent Dynamics via Difference Neural Representation for Videos

Existing implicit neural representation (INR) methods do not fully exploit spatiotemporal redundancies in videos. Index-based INRs ignore the content-specific spatial features and hybrid INRs ignore the contextual dependency on adjacent frames, leading to poor modeling capability for scenes with large motion or dynamics. We analyze this limitation from the perspective of function fitting and reveal the importance of frame difference. To use explicit motion information, we propose Difference Neural Representation for Videos (DNeRV), which consists of two streams for content and frame difference. We also introduce a collaborative content unit for effective feature fusion. We test DNeRV for video compression, inpainting, and interpolation. DNeRV achieves competitive results against the state-of-the-art neural compression approaches and outperforms existing implicit methods on downstream inpainting and interpolation for $960 \times 1920$ videos

The asymmetric effect of film and drama industry, energy efficiency and economic growth on green innovation: Empirical evidence from quantile estimation

The popularity of green innovation has dramatically increased in the recent times because of the potential benefits attached with it. Therefore, in order to make the technology more affordable, green innovation is the key to enhancing the affordability factor. On the other hand, in order to safeguard the environment, the role of media is one of fundamental importance. In contrast, energy consumption is often regarded as a key indicator of economic prosperity, mostly at the cost of the environment. Hence, the present study attempts to explore the asymmetric effect of the film and drama industry, energy efficiency, and economic growth on green innovation, with the help of the latest quantile autoregressive distributed lag (QARDL) method for the period 2000Q1 to 2019Q4. The results have reported a positive and significant association of the Film and Drama Industry, Energy Efficiency, and economic growth on the quantiles of Green Innovation. Based on the findings, it is recommended that there is a dire need to develop content that promotes the green innovation, whereas, more investments are to be sought after, so as to enhance the level of energy efficiency

Performance analysis of the closed loop supply chain

Purpose: The question of resource scarcity and emerging pressure of environmental legislations has brought a new challenge for the manufacturing industry. On the one hand, there is a huge population that demands a large quantity of commodities; on the other hand, these demands have to be met by minimum resources and pollution. Resource conservative manufacturing (ResCoM) is a proposed holistic concept to manage these challenges. The successful implementation of this concept requires cross functional collaboration among relevant fields, and among them, closed loop supply chain is an essential domain. The paper aims to highlight some misconceptions concerning the closed loop supply chain, to discuss different challenges, and in addition, to show how the proposed concept deals with those challenges through analysis of key performance indicators (KPI). Methods: The work presented in this paper is mainly based on the literature review. The analysis of performance of the closed loop supply chain is done using system dynamics, and the Stella software has been used to do the simulation. Findings: The results of the simulation depict that in ResCoM; the performance of the closed loop supply chain is much enhanced in terms of supply, demand, and other uncertainties involved. The results may particularly be interesting for industries involved in remanufacturing, researchers in the field of closed loop supply chain, and other relevant areas. Originality: The paper presented a novel research concept called ResCoM which is supported by system dynamics models of the closed loop supply chain to demonstrate the behavior of KPI in the closed loop supply chain

H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System

High-speed, high-resolution stereoscopic (H2-Stereo) video allows us to perceive dynamic 3D content at fine granularity. The acquisition of H2-Stereo video, however, remains challenging with commodity cameras. Existing spatial super-resolution or temporal frame interpolation methods provide compromised solutions that lack temporal or spatial details, respectively. To alleviate this problem, we propose a dual camera system, in which one camera captures high-spatial-resolution low-frame-rate (HSR-LFR) videos with rich spatial details, and the other captures low-spatial-resolution high-frame-rate (LSR-HFR) videos with smooth temporal details. We then devise a Learned Information Fusion network (LIFnet) that exploits the cross-camera redundancies to enhance both camera views to high spatiotemporal resolution (HSTR) for reconstructing the H2-Stereo video effectively. We utilize a disparity network to transfer spatiotemporal information across views even in large disparity scenes, based on which, we propose disparity-guided flow-based warping for LSR-HFR view and complementary warping for HSR-LFR view. A multi-scale fusion method in feature domain is proposed to minimize occlusion-induced warping ghosts and holes in HSR-LFR view. The LIFnet is trained in an end-to-end manner using our collected high-quality Stereo Video dataset from YouTube. Extensive experiments demonstrate that our model outperforms existing state-of-the-art methods for both views on synthetic data and camera-captured real data with large disparity. Ablation studies explore various aspects, including spatiotemporal resolution, camera baseline, camera desynchronization, long/short exposures and applications, of our system to fully understand its capability for potential applications

A double-blinded, randomized, placebo-controlled study evaluating the impact of dates vinegar consumption on blood biochemical and hematological parameters in patients with type 2 diabetes

Purpose: To determine the effects of dates vinegar on blood biochemical and hematological parameters in type 2 diabetic subjects.Methods: Current research focused on fifty-five subjects having blood sugar more than126 mg/dL. Participants ingested dates vinegar (20 mL) daily into their normal diets for a period of 10 weeks. Glycated hemoglobin (HbA1c), fasting blood sugar (FBS), total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), creatinine (Cr), urea, complete blood count (CBC), alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), potassium and folate levels were analyzed before, after 5 weeks and after the experiment Results: Dates vinegar improved the blood concentrations of HbA1c (6.80 ±2.34 to 6.17 ± 2.14 (%)), FBS (171.43 ±36.74 to 147.56 ± 38.86 mg/dL,p=0.001), TC (218.10 ± 16.9 to 191.14 ± 14.23 mg/dL, p<0.001), ALT (24.94 ± 5.03 to 21.88±5.08 IU/L, p=0.002) and ALP (264.32± 45.26 to 257.30 ±44.21 IU/L) and folate (34.6 ± 6.6 to 41.7 ± 6.5 nmol/ L, p<0.001).Conclusion: Dates vinegar significantly improved the total cholesterol.The other blood biochemical and hematological factors were also improved however; the improvements were not significant.Keywords: Dates vinegar, diabetes, glycated hemoglobin, hyperlipidemi

Point Cloud Distortion Quantification based on Potential Energy for Human and Machine Perception

Distortion quantification of point clouds plays a stealth, yet vital role in a wide range of human and machine perception tasks. For human perception tasks, a distortion quantification can substitute subjective experiments to guide 3D visualization; while for machine perception tasks, a distortion quantification can work as a loss function to guide the training of deep neural networks for unsupervised learning tasks. To handle a variety of demands in many applications, a distortion quantification needs to be distortion discriminable, differentiable, and have a low computational complexity. Currently, however, there is a lack of a general distortion quantification that can satisfy all three conditions. To fill this gap, this work proposes multiscale potential energy discrepancy (MPED), a distortion quantification to measure point cloud geometry and color difference. By evaluating at various neighborhood sizes, the proposed MPED achieves global-local tradeoffs, capturing distortion in a multiscale fashion. Extensive experimental studies validate MPED's superiority for both human and machine perception tasks

Homozygosity Mapping and Genetic Analysis of Autosomal Recessive Retinal Dystrophies in 144 Consanguineous Pakistani Families.

PurposeThe Pakistan Punjab population has been a rich source for identifying genes causing or contributing to autosomal recessive retinal degenerations (arRD). This study was carried out to delineate the genetic architecture of arRD in the Pakistani population.MethodsThe genetic origin of arRD in a total of 144 families selected only for having consanguineous marriages and multiple members affected with arRD was examined. Of these, causative mutations had been identified in 62 families while only the locus had been identified for an additional 15. The remaining 67 families were subjected to homozygosity exclusion mapping by screening of closely flanking microsatellite markers at 180 known candidate genes/loci followed by sequencing of the candidate gene for pathogenic changes.ResultsOf these 67 families subjected to homozygosity mapping, 38 showed homozygosity for at least one of the 180 regions, and sequencing of the corresponding genes showed homozygous cosegregating mutations in 27 families. Overall, mutations were detected in approximately 61.8 % (89/144) of arRD families tested, with another 10.4% (15/144) being mapped to a locus but without a gene identified.ConclusionsThese results suggest the involvement of unmapped novel genes in the remaining 27.8% (40/144) of families. In addition, this study demonstrates that homozygosity mapping remains a powerful tool for identifying the genetic defect underlying genetically heterogeneous arRD disorders in consanguineous marriages for both research and clinical applications

Phalaris minor control, resistance development and strategies for integrated management of resistance to fenoxaprop-ethyl

Phalaris minor (Littleseed canary grass) is a very important and annual weed of winter cereal crops. It is a very competitive weed of wheat, oat and barley crops in Pakistan. Usually, three aryloxyphenoxypropionate herbicides, fenoxaprop-P-ethyl, diclofop-methyl and clodinafop-propargyl are used as chemical weed control against different grassy weeds like P. minor, Avena sativa and Cyperus rotundus L. This review describes fenoxaprop-ethyl, a selective chemical herbicide used to control P. minor in wheat crop. High production of wheat is associated with its continuous use. But this practice enhances the development of resistant biotypes of P. minor. Different management approaches like preference of mechanical weeding over chemical weed control, integration of competitive varietal selection, crop rotation and herbicide rotation can be long duration strategies of resistance management in P. minor. However, tillage method, planting time, method of herbicide application, optimum dose, higher seed rate, early sowing, bed planting, stale seed bed and zero tillage are short duration resistance management strategies. Use of water extracts of herbicidal potential (allelopathic) plants can be effective integrated management of herbicide resistant against P. minor in wheat and for eco-friendly and sustainable weed management.Key words: Control, fenoxaprop-ethyl, management, Phalaris minor, resistance, wheat

Consistent association of fungus Fusarium mangiferae Britz with mango malformation disease in Pakistan

Mango malformation disease (MMD) deforms the natural shape of panicles and shoots. The disease incitant is of great concern due to its complexity and mode of infection. Recently, a new species Fusarium mangiferae Britz was confirmed as the etiological agent of MMD in African and Asian clade. There was a need to confirm the fungus in other Asian countries. We investigated the association of F. mangiferae with malformed branches of five exotic and five indigenous cultivars of Mangifera indica L. in Pakistan. F. mangiferae proved to be the dominant fungus hosting majority of the malformed tissues. Among the indigenous cultivars, maximum tissue infection of 96.66% was found in cultivar Anwar Rataul and minimum was found in cultivar Late Chaunsa (48.33%). In exotic ones, maximum and minimum infections of 97.33 and 70.67% were noted in the cultivars Sensation and Pop, respectively. Light and transmission electron microscopy proved helpful in investigating the morphological matrix and ultrastructure of the propagules of fungus F. mangiferae.Key words: Mangifera indica, microconidium, Pakistan, tissue assay, transmission electron microscopy

Plastic flow and failure resistance of metallic glass: Insight from \u3cem\u3ein situ\u3c/em\u3e compression of nanopillars

We report in situ nanocompression tests of Cu-Zr-Al metallic glass (MG) pillars in a transmission electron microscope. This technique is capable of spatially and temporally resolving the plastic flow in MGs. The observations reveal the intrinsic ability of fully glassy MGs to sustain large plastic strains, which would otherwise be preempted by catastrophic instability in macroscopic samples and conventional tests. The high ductility in volume-limited MGs and the sample size effects in suppressing the rapid failure common to MGs are analyzed by modeling the evolution of the collectivity of flow defects toward localization