Miracle-dz/UniFAR-FTUs huggingface dataset:
Attention-Enhanced And More Balanced R-CNN For Object Detection

Attention mechanisms have been widely used in deep neural convolution networks and different fields, such as object detection and instance segmentation. Many attention mechanisms will cost too much calculation, so in this paper, we incorporate a kind of light attention mechanism, the attended residual module, into our object detection backbone to get an accuracy-efficiency trade-off. Besides, to solve the imbalance problem in region sample level, we use the cascade region proposal network(RPN) module to gain anchors of higher quality resulting in higher average recall(AR). Furthermore, we replace the non-local attention module in feature fusion level with the criss-cross attention module to reduce computation and improve performance. With them all, our method significantly improves the detection performance and achieves 43.6 AP in COCO test-dev.
Investigation of Analgesic Activity of Leaves and Seed extracts of Abelmoschus moschatus Medik

Abelmoschus moschatus Medik commonly known as Musk mallow (E) and Kasturi bhendi (Hindi) is an aromatic and medicinal plant belongs to Malvaceae family. The plant has numerous medicinal values as claimed by traditional and folk lore. The PEE, CE, EE and AE of Abelmoschus moschatus leaves and seed were evaluated for analgesic activity in animal models and the results obtained indicates that the extract found to have significant (P < 0.01) analgesic activity in rats. The PEE, CE, EE and AE of Abelmoschus moschatus leaves at the test doses 200 and 400 mg/kg b.w. produced prodound analgesic activity 5 h is more more potent, when compared with the PEE, CE, EE and AE of Abelmoschus moschatus seeds at the test doses 200 and 400 mg/kg b.w. when compared to standard drug and control group
Mitochondrial genome of the Common burrowing snake Achalinus spinalis (Reptilia: Xenodermatidae)

Abstract Common burrowing snake Achalinus spinalis is the type species of Achalinus. The complete mitochondrial genome (mitogenome) sequence of A. spinalis was determined by using a PCR-based method. The total length of mitogenome is 17,165 bp and contains 13 protein-coding genes, 22 tRNA genes, 2 ribosome RNA genes and 2 control regions (CR). All the protein-coding genes in A. spinalis were distributed on the H-strand, except for the ND6 subunit gene and eight tRNA genes which were encoded on the L-strand. The phylogenetic tree of A. spinalis and 12 other closely species was built. The DNA data presented here will be useful to study the evolutionary relationships and genetic diversity of A. spinalis.
Study on k-best sphere decoding algorithm in MIMO systems

Maximum likelihood detection(MLD) can provide the best performance in minimum bit errors ratio rule in multiple input multiple output(MIMO) system.However,exponentially searching for the ML solution becomes infeasible as the number of antenna and constellation points increases.Thus,the sphere decoding algorithm with the middle searching complexity is regarded extensively as a sub-MLD.In this paper,k-best SDA with fixed complexity,which adopt breath-first search strategy,was analyzed.And a type of k-best SDA with remaining dynamic number of expended node in each node was proposed.In real SDA model with 64QAM modulation when the number of remaining spanning node is 8,result of simulation shows the performance is basically invariable when the number of remaining spanning node is 2 in k-best SDA with remaining fixed spanning nodes where the algorithm is named k-best SDA Ⅰ. Performance and complexity of the improved k-best SDA Ⅱ are relatively ideal compared with k-best SDA Ⅰ,with complexity reduced by 28% and performance lost capable of being ignored.
The tribological properties of lubricating greases produced on vegetable base and modified of polytetrafluoroethylene

The article presents the results of research on the influence of polytetrafluoroethylene additive on the tribological and rheological properties of selected lubricant compositions. Based on the obtained test results, it was found that the introduction of a modifying additive to the lubricant structure allows a significant reduction of the coefficient of friction, thus increasing the efficiency of tribological protection of the tribosystem. All lubricating compositions modified with at least 1% polytetrafluoroethylene guarantee effective anti-wear protection under load conditions of the tribosystem. Modification of the tested lubricating compositions with the applied additive affects the increase of indicators characterizing the fatigue life of the examined lubricating greases based on sunflower oil. The introduction of the polytetrafluoroethylene into the structure of the tested lubricants changed the values of the MSD correlation function and the G’ and G’’ modules, which significantly influenced the internal structure of the tested lubricant compositions.
Deep Learning – A Review

In recent years, tech giants in various parts are showing Curiosity on Artificial Intelligence by investment on the project that can be a game-changer for both corporate and researchers. A company such as Google, Baidu, and Yandex have already started their multimillion-dollar project in this pitch. This article presents the latest progress and also tries to paint a predictive picture of future research directions and developments in the domain of deep learning. Each of the said research directions and avenues is analyzed and summarized in a brief yet concise manner in this article. Initially, an outline of the three elementary models of deep learning that including multilayer perceptions and perceptrons, convolutional neural networks and recurrent neural networks. Building on the bases of foundation, further analyses of the emerging new types of convolutional neural networks and recurrent neural networks are also undertaken in this current study. This article then summarizes deep learning and its applications in the domain of artificial intelligence, counting speech processing, computer vision, and natural language processing. Finally, the purpose of deep learning is discussed. The current article also delves a little deeper into the inner workings of the neural networking architecture associated with object detection and computer vision.
Fixation, Partitioning and Export of Carbon in two Species of the Plantaginaceae

Fixation, Partitioning and Export of Carbon in two Species of the Plantaginaceae Ildiko Szucs Advisor: University of Guelph, 2013 Professor B. Grodzinski During photosynthesis Plantaginaceae species can produce glucose derivatives such as iridoid glycosides and alcohol sugars that in addition to sucrose can be exported from leaves. Plantago lanceolata transported sorbitol in addition to sucrose especially at warmer leaf temperatures. However, two iridoids, catalpol and aucubin, found in P. lanceolata were not readily labelled from CO2 under any conditions examined. In contrast, in two greenhouse, cut-flower cultivars of Antirrhinum majus the iridoids, antirrhinoside and antirrhide, were readily C-labelled along with sucrose but little C was recovered in alcohol sugars (e.g., mannitol). The amount of C-partitioned into antirrhinoside increased at higher temperatures. Exposing leaves of P. lanceolata and A. majus to reduced-photorespiratory conditions (e.g. short-term CO2 enrichment and/or low O2) increased fixation and export. Under low O2 in P. lanceolata sorbitol Clabelling increased relative to sucrose and in A. majus C-labelling of sucrose increased relative to antirrhinoside. Also C-labelling of antirrhide increased more than antirrhinoside. During both short-term and long-term acclimation to high CO2, whole plant NCER, leaf photosynthesis and export increased in A. majus. Taken together the temperature and CO2 enrichment studies show plasticity in Plantaginaceae species to synthesize and transport sucrose and auxiliary glucose esters and alcohol sugars in a species-specific manner (depending on the rate of carboxylation).
Impacts of climate change on eucalypt distributions in Australia: an examination of a recent study

ABSTRACT A recent study examined the possible impacts of climate change on 657 Australian eucalypt species in the period to 2085 using species distribution modelling (SDM). The study predicted that ‘within the next 60 years the vast majority of species distributions (91%) across Australia will shrink in size (on average by 51%)’. The purpose of the present paper is to demonstrate some of the strengths and weaknesses of this previous study. Its main strength is that it identifies relatively hot and dry areas of species distributions that may be vulnerable under climate change. Its main weakness is that the individual analyses tend to overestimate the areas of species natural distributions. Consequently, the predicted percentage losses of species distribution areas are unreliable. To illustrate the problem the freely available Atlas of Living Australia (ALA) is used examine two contrasting species (Eucalyptus diversicolor and E. nitens) in detail, so readers will be able to apply similar methods to any eucalypt species of interest. For well-known species a more reliable assessment of likely losses of distributional area under climate change may be obtained by applying the results of the SDM analysis, but assuming that ALA occurrences within 25 km x 25 km areas are an accurate representation of present natural distributions. Using this approach the estimated loss of area of natural distribution by 2085 for both E. diversicolor and E. nitens are less than half the estimates provided by the original paper. For lesser-known species, it is concluded that an additional SDM analysis is required to provide a closer representation of species natural distributions, to which the original SDM climate change results, which attempt to capture some of the species adaptability/plasticity, could be applied.
Phytochemical Screening and Antimicrobial Studies of Crateva adansonii Leaf Extract

Diverse challenges of microbial infections and upsurge of multi-drug resistant microbes informed the investigation into the phytochemical and antibacterial properties of Crateva adansonii. Cold extraction was carried out using methanol solvent. The crude extract of Crateva adansonii was fractionated into the n-hexane, methanol and chloroform layers successively. The phytochemical screening indicated the presence of alkaloids, saponins, terpenoids, flavonoids and cardiac glycosides. The antimicrobial assay showed that, for Bacillus spp, the organism was sensitive to the chloroform fraction of leaf extract at 1.562 mg/ml. For Microccocus varians, result showed organism was sensitive to the crude extract at 3.125 mg/ml. According to the result of antifungal screening, the n-hexane fraction and crude extract showed activity against Aspergillus niger at 12.500 mg/ml and 3.125 mg/ml respectively. From these results, the crude extract of the leaf of Crateva adansonii shows activity against both bacteria and Fungi; hence, it may might be a good source of new drug for treating infections caused by these pathogens.
FPHA-Afford: A Domain-Specific Benchmark Dataset for Occluded Object Affordance Estimation in Human-Object-Robot Interaction

In human-object-robot interactions, the recent explosion of standard datasets has offered promising opportunities for deep learning techniques in understanding the functionalities of object parts. But most of existing datasets are only suitable for the applications where objects are non-occluded or isolated during interaction while occlusion is a common challenge in practical object affordance estimation task. In this paper, we attempt to address this issue by introducing a new benchmark dataset named FPHA-Afford that is built upon the popular dataset FPHA. In FPHA-Afford, we adopt egocentric-view to pre-process the videos from FPHA and select part of the frames that contain objects under the strong occlusion of hand. To transfer the domain of FPHA into object affordance estimation task, all of the frames are re-annotated with pixel-level affordance masks. In total, our FPHA-Afford collects 61 videos containing 4.3K frames with 6.55K annotated affordance masks belonging to 9 classes. Some of state-of-the-art semantic segmentation architectures are explored and evaluated over FPHA-Afford. We believe the scale, diversity and novelty of our FPHA-Afford could offer great opportunities to researchers in the computer vision community and beyond. Our dataset and experiment code will be made publicly available on https://github.com/Hussainflr/FPHA-Afford
The pre-independence psychological experiences of the Namibian children of the liberation struggle: a qualitative study

The Independence of Namibia in 1990 witnessed the voluntary repatriation of exiled Namibian people back home. Children of the liberation struggle is the term used to refer to the grown-up children of veterans who were under the age of 18 years before Namibian Independence. Since 2008, demonstrations and demands for jobs from government by the children of the liberation struggle have taken place regularly, drawing harsh criticism about the behaviour and demands of the children of the liberation struggle from the general private and public Namibian domain. This study aims to explore the pre-Independence psychological experiences of the Namibian children of the liberation struggle in an attempt to understand their conduct. A qualitative approach was employed where in-depth interviews were conducted with 10 employed children of the liberation struggle in the Khomas region. The collected data were categorised by means of thematic analysis. The results revealed themes which demonstrate that most children of the liberation struggle experienced adversities like growing up separated from their parents, in unstable conditions, having experienced maltreatment, constantly afraid of the enemy and having endured traumatic war-related situations. The study recommends sensitisation of the broad Namibian public on the lived experiences of the children of the liberation struggle. Psycho-education programmes and psychological interventions in the form of therapeutic group sessions and individual sessions with children of the liberation struggle can assist with reflection on the past, making sense of it and find healing to move on with their lives. Government and the private sector should cooperate in rendering training and job opportunities for the children of the liberation struggle.
An overview of the mathematical modelling of perovskite solar cells towards achieving highly efficient perovskite devices

Researchers have at different times focused on designing perovskite solar cells (PSCs) that are flexible yet highly efficient, to enable the fabrication of portable photovoltaic solar cell (PVSC) devices in large quantities. This upcoming organometal trihalide perovskite has high tendencies of being a highly efficient, yet inexpensive solar cell. This is because the solution processing method is carried out at a reduced temperature and increased solar to electricity conversion efficiency (>25%) obtained within few innovative years. The nanostructured morphology and film quality is essential in obtaining functional power conversion efficiency. It could be a great task for the two characteristics to be present, especially within solutions where very good films are in contact with smooth morphological surfaces. A fast increase in the energy conversion efficiency of these PSCs incorporated with metal halides has been recorded. The next line of research should be to extend the existing models to 3D explicit models of the meso‐structured layer, to verify the 1D effective medium method discussed in the literature. Several models have been discussed to that effect. This review intensively discusses several perovskite models in a bid to understand PSCs. The challenges and future perspectives have also been highlighted.
Effect of Ionic Strength and Coexisting Ions on the Biosorption of Divalent Nickel by the Acorn Shell of the Oak Quercus crassipes Humb. & Bonpl.

This study investigated the effect of ionic strength and background electrolytes on the biosorption of Ni2+ from aqueous solutions by the acorn shell of Quercus crassipes Humb. & Bonpl. (QCS). A NaCl ionic strength of 0.2 mM was established to have no effect on the Ni2+ biosorption and the biosorption capacity of the heavy metal decreased as the ionic strength increased from 2 to 2000 mM. The background electrolytes (KCl, NaNO3, Na2SO4, CaCl2, MgSO4, and MgCl2) had no adverse effects on the biosorption of Ni2+ at a concentration of 0.2 mM. However, at background electrolyte concentrations of 2 and 20 mM, divalent cations (Ca2+ and Mg2+) had greater negative effects on the biosorption of Ni2+ compared to the monovalent cations (Na+ and K+). Additionally, the SO42− and Cl− anions affected the biosorption of Ni2+. The fractional power, Elovich, and pseudo-second order models represented the kinetic processes of the biosorption of Ni2+ adequately. The results show that QCS can be a promising and low-cost biosorbent for removing Ni2+ ions from aqueous solutions containing various types of impurities with different concentrations.
Modulated Uniaxial Compression Analysis of Respirable Pharmaceutical Powders

We describe a new instrument and method for measuring compressed bulk density of respirable pharmaceutical powders under low compression pressure: the modulated compression tester. The instrument modulates compression and decompression steps, allowing scrutiny of the overall compression response of samples. Compared to established methods for the determination of density and related parameters for pharmaceutical powders, this instrument has the capability of measuring smaller samples. The relative humidity can also be controlled in the instrument (3 % to 95 % RH), allowing assessment of the effect of moisture on compression response. We have used the instrument to determine the compressed bulk density of Trehalose, Leucine, Trileucine, and Mannitol powders of varying crystalline and amorphous compositions and particle size and size distribution, demonstrating that the new modulated compression tester is suitable for low pressure (< 1200 kPa) density measurement of respirable powders (< 10 μm) and expensive active pharmaceutical ingredients available in limited quantities (typical sample mass requirement of < 100 mg). In addition, the modulation feature of the instrument allows the analysis of the transition from plastic to semi-elastic compression response. The outputs and features of this instrument are useful for formulation development, quality control measurements, discerning between different or similar powders due to differences in the compression response, and optimizing powder compression parameters for pharmaceutical applications.
Seed germination response of a noxious agricultural weed Echium plantagineum to temperature, light, pH, drought stress, salinity, heat and smoke

Abstract. Echium plantagineum is a significant pasture weed in the Mediterranean climatic zone of several countries, including Australia. This invasive weed, introduced as an ornamental into Australia (where it is known as Paterson’s curse), quickly became established and is now a significant weed of agriculture. Although E. plantagineum is a well-established, highly competitive weed that thrives under disturbance and is tolerant of a wide variety of conditions, including varying soil moisture and drought, and some aspects of its ecology remain unknown. This study investigated germination response to temperature and light, pH, soil moisture, salinity, and pre-germination exposure of seed to heat and smoke. Temperature was found to be more influential on germination than light and the species is tolerant to a wide range of pH. However, available moisture may limit germination, as may elevated salinity. Management of this weed requires approaches that minimise soil seedbank input or prevent germination of soil seedbanks.
Benchmark of lncRNA Quantification for RNA-Seq of Cancer Samples

Long non-coding RNAs (lncRNAs) emerge as important regulators of various biological processes. Many lncRNAs with tumor-suppressor or oncogenic functions in cancer have been discovered. While many studies have exploited public resources such as RNA-Seq data in The Cancer Genome Atlas (TCGA) to study lncRNAs in cancer, it is crucial to choose the optimal method for accurate expression quantification of lncRNAs. In this benchmarking study, we compared the performance of pseudoalignment methods Kallisto and Salmon, and alignment-based methods HTSeq, featureCounts, and RSEM, in lncRNA quantification, by applying them to a simulated RNA-Seq dataset and a pan-cancer RNA-Seq dataset from TCGA. We observed that full transcriptome annotation, including both protein coding and noncoding RNAs, greatly improves the specificity of lncRNA expression quantification. Pseudoalignment-based methods detect more lncRNAs than alignment-based methods and correlate highly with simulated ground truth. On the contrary, alignment-based methods tend to underestimate lncRNA expression or even fail to capture lncRNA signal in the ground truth. These underestimated genes include cancer-relevant lncRNAs such as TERC and ZEB2-AS1. Overall, 10–16% of lncRNAs can be detected in the samples, with antisense and lincRNAs the two most abundant categories. A higher proportion of antisense RNAs are detected than lincRNAs. Moreover, among the expressed lncRNAs, more antisense RNAs are discordant from ground truth than lincRNAs when measured by alignment-based methods, indicating that antisense RNAs are more susceptible to mis-quantification. In addition, the lncRNAs with fewer transcripts, less than three exons, and lower sequence uniqueness tend to be more discordant. In summary, pseudoalignment methods Kallisto or Salmon in combination with the full transcriptome annotation is our recommended strategy for RNA-Seq analysis for lncRNAs. AUTHOR SUMMARY Long non-coding RNAs (lncRNAs) emerge as important regulators of various biological processes. Our benchmarking work on both simulated RNA-Seq dataset and pan-cancer dataset provides timely and useful recommendations for wide research community who are studying lncRNAs, especially for those who are exploring public resources such as TCGA RNA-Seq data. We demonstrate that using full transcriptome annotation in RNA-Seq analysis is strongly recommended as it greatly improves the specificity of lncRNA quantification. What’s more, pseudoalignment methods Kallisto and Salmon outperform alignment-based methods in lncRNA quantification. It is worth noting that the default workflow for TCGA RNA-Seq data stored in Genomic Data Commons (GDC) data portal uses HTSeq, an alignment-based method. Thus, reanalyzing the data might be considered when checking gene expression in TCGA datasets. In summary, pseudoalignment methods Kallisto or Salmon in combination with full transcriptome annotation is our recommended strategy for RNA-Seq analysis for lncRNAs.
Areas of endemism persist through time: A palaeoclimatic analysis in the Mexican Transition Zone

The Mexican Transition Zone (MTZ) is an area where the Nearctic and Neotropical biogeographical regions overlap, generating high species richness and endemism. The objective of this study was to analyse if potential changes in the composition and the geographical location of areas of endemism (AEs) for beetles and mammals during the Last Glacial Maximum (LGM), the mid‐Holocene (MH) or the Last Interglacial (LIG) have influenced the definition of the MTZ in the present.