Miracle-dz/UniFAR-FTUs huggingface dataset:
SHREDDED CONTROL OF DRONES VIA MOTOR IMAGERY BRAIN COMPUTER INTERFACE

In this paper, we present architecture for an auxiliary shredded control that can be used in combination with a BCI control system. BCI systems are known for low reliability and accuracy. We are presenting a method to enhance this inherent weakness of BCI systems, by providing an assistive autonomous controller whenever the BCI system reaches to the point where fine control is necessary. Â The course control is performed by the motor imagery BCI which decodes the thinking process of the user and use it for navigating a quadcopter drone. Once the quadcopter reaches an area where the object selected to be picked up enters in the field of view of the bottom camera of the quadcopter, the autonomous controller is taking over the fine movement navigation to handle the rest of the task. This method is an exciting opportunity for several other BCI applications to enhance the reliability and accuracy of BCI systems to be adopted in everyday life of severely disabled patients.
Comparing the Relationship of Different Drip Irrigation Uniformity Parameters with Crop Yield

Drip irrigation system has the ability to apply water over the field uniformly. Uniformity of drip irrigation can be measured through many parameters. Uniformity is one of the procedures which should be considered in drip irrigation design and management to gain the maximum possible crop yield. The objective of this study was to investigate the effect of some uniformity parameters including Christiansen’s uniformity coefficient (UC), distribution uniformity (DU), Manufacturing coefficient of variation (CVf), and emission uniformity (EU) on crop yield and water productivity, in addition to evaluate the strength of the relationship between each of studied uniformity parameter and crop yield. Four operating pressure heads 5, 10, 15, and 20m were used to operate the irrigation system to make the required change in drip irrigation system uniformity level. The study included two crops which were lettuce and turnip. Results indicated that increasing drip irrigation system uniformity will lead to increase crop yield and water productivity of both crops. Values of correlation coefficient (r) were less than 0.5 for all uniformity parameters when correlated to crop yield. This indicated that uniformity might not be the most important factor representing the quantity of crop yield though its importance. According to the values of the (r) resulted from the relationship between each uniformity parameter and crop yield; EU had the strongest effect on crop yield. The study recommended modeling the relationship between drip irrigation uniformity and crop yield basing on EU.
Leishmania amazonensis Promastigotes or Extracellular Vesicles Modulate B-1 Cell Activation and Differentiation

B-1 cells are considered an innate-like B cell population that participates in effective innate and adaptive responses to pathogens. B-1 cells produce immunoglobulins, cytokines, chemokines, migrate to inflammatory sites, and differentiate into mononuclear phagocyte-like cells. Murine B-1 cells phagocytosed Leishmania in vitro and in vivo and participate in immunity against Leishmania. Our group showed that B-1 cells or their extracellular vesicles (EVs) led to a resistance to experimental infection by L. amazonensis. However, the B-1 cells’ responses to Leishmania or EVs isolated from parasites are still poorly characterized. Studying the activation and differentiation of B-1 cells in vivo can contribute to a better understanding of how these cells participate in immunity to L. amazonensis. Thus, we evaluated the expression of myeloid (M-csfr, G-csfr, Spi-1) and lymphoid (EBF, E2A, IL-7R) lineage commitment factors, Toll-like receptors (TLRs), activation cell surface markers, nitric oxide (NO) and reactive oxygen species (ROS) production in murine peritoneal B-1 cells collected after 24 or 48 h post-infection with Leishmania (Leishmania) amazonensis promastigotes or EVs released by the parasites. Our results demonstrated that L. amazonensis infection did not stimulate the expression of CD40, CD80, CD86, F4/80, and MHC II in B-1 cells, but a significant decrease in the production of NO and ROS was observed. The infection induced a significantly higher arginase expression in B-1 cells, but the stimulation with EVs led to a decrease in this gene expression. TLR-2 and TLR-6 had significantly higher expression in B-1 cells from mice intraperitoneally stimulated with the parasite. The TLR-9 expression was higher in animals infected or stimulated for 48 h with EVs. Interestingly, in B-1 cells the stimulus with L. amazonensis led to a substantial increase in the expression of myeloid restricted transcription factors. Thus, our study suggests that the parasites or EVs differently modulated the activation and differentiation of B-1 cells.
Differences between temperate and tropical birds in seasonal acclimatization of thermoregulatory traits

Phenotypic flexibility can be an important determinant of fitness in variable environments. The climatic variability hypothesis (CVH) predicts that phenotypic flexibility in thermoregulatory traits will be greater in temperate species than tropical species as a means of coping with increased temperature seasonality at higher latitudes. However, support for the CVH has been mixed, and recent studies suggest that tropical birds are capable of substantial phenotypic flexibility. To test the generality of the CVH, we used flow-through respirometry to quantify seasonal acclimatization in thermoregulatory traits in suites of temperate (n = 6) and tropical (n = 41) birds. We used W/S ratios (winter/summer trait values) to quantify the direction and magnitude of seasonal change (W/S ratio of 1 means no seasonal change). Temperate species exhibited coordinated changes in thermoregulatory traits in winter, including large increases in thermoneutral zone (TNZ) breadth and reductions in heat loss below the lower limit of the TNZ. Conversely, tropical species exhibited idiosyncratic seasonal thermoregulatory responses, and mean W/S ratios were close to 1 for all traits, indicative of little seasonal change and consistent with predictions of the CVH. Nevertheless, mean W/S ratios did not differ significantly between temperate and tropical species for either Mb or BMR, demonstrating that tropical birds can also exhibit substantial thermoregulatory flexibility. Our results highlight the need for complementary acclimation experiments to determine if latitudinal differences in seasonal acclimatization are due to inherent differences in capacity for flexibility.
Highly efficient editing of the β-globin gene in patient-derived hematopoietic stem and progenitor cells to treat sickle cell disease

Abstract Sickle cell disease (SCD) is a monogenic disorder that affects millions worldwide. Allogeneic hematopoietic stem cell transplantation is the only available cure. Here, we demonstrate the use of CRISPR/Cas9 and a short single-stranded oligonucleotide template to correct the sickle mutation in the β-globin gene in hematopoietic stem and progenitor cells (HSPCs) from peripheral blood or bone marrow of patients with SCD, with 24.5 ± 7.6% efficiency without selection. Erythrocytes derived from gene-edited cells showed a marked reduction of sickle cells, with the level of normal hemoglobin (HbA) increased to 25.3 ± 13.9%. Gene-corrected SCD HSPCs retained the ability to engraft when transplanted into non-obese diabetic (NOD)-SCID-gamma (NSG) mice with detectable levels of gene correction 16–19 weeks post-transplantation. We show that, by using a high-fidelity SpyCas9 that maintained the same level of on-target gene modification, the off-target effects including chromosomal rearrangements were significantly reduced. Taken together, our results demonstrate efficient gene correction of the sickle mutation in both peripheral blood and bone marrow-derived SCD HSPCs, a significant reduction in sickling of red blood cells, engraftment of gene-edited SCD HSPCs in vivo and the importance of reducing off-target effects; all are essential for moving genome editing based SCD treatment into clinical practice.
Quantum Chemical Calculations

The current methods of quantum chemical calculations will be reviewed. The accent will be on the accuracy that can be achieved with these methods. The basis set requirements and computer resources for the various methods will be discussed. The utility of the methods will be illustrated with some examples, which include the calculation of accurate bond energies for SiF$_n$ and SiF$_n^+$ and the modeling of chemical data storage.
Predicting species distribution from fishers’ local ecological knowledge: a new alternative for data-poor management

Many developing countries lack information to manage their endangered species, urging the need for affordable and reliable information. We used Bayesian hierarchical spatial models, with oceanographic variables, to predict the distribution range of Epinephelus marginatus, the dusky grouper, for the entire Southwest Atlantic. We ran a model using scientific information gathered from the literature and another using information gathered from fishers on species presence or absence. In both models, temperature was an important determinant of species occurrence. The predicted occurrence of the dusky grouper overlapped widely (Schoener’s D = 0.71; Warren’s I = 0.91) between the models, despite small differences on the southern and northern extremes of the distribution. These results suggest that basic information provided by fishers on species occurrence in their area can be reliable enough to predict species occurrence over large scales and can be potentially useful for marine spatial planning. Fishers’ knowledge may be an even more viable alternative to data collection than what was previously thought, for countries that both struggle with financial limitations and have urgent conservation needs.
Pruning Random Forest with Orthogonal Matching Trees

In this paper we propose a new method to reduce the size of Breiman's Random Forests. Given a Random Forest and a target size, our algorithm builds a linear combination of trees which minimizes the training error. Selected trees, as well as weights of the linear combination are obtained by mean of the Orthogonal Matching Pursuit algorithm. We test our method on many public benchmark datasets both on regression and binary classification and we compare it to other pruning techniques. Experiments show that our technique performs significantly better or equally good on many datasets 1. We also discuss the benefit and shortcoming of learning weights for the pruned forest which lead us to propose to use a non-negative constraint on the OMP weights for better empirical results.
QUANTITATIVE DETECTION OF CAMV- 35S PROMOTER AND T-NOS TERMINATOR IN GENETIC MODIFIED TOMATO FROM IRAQI MARKETS

Aim of this research was quantitative detection of Increase and decrease in copy number of CaMV-35S promoter and Nos terminator in genetic modified tomato by using Real-time PCR. Twenty four samples of genetic modified tomato seeds were isolated from 84 tomato samples collected from Iraqi markets during the period from December 2016 to January 2017. The experiences were conducted in the Institute of Genetic Engineering, University of Baghdad. Go Taq®qPCR master mix kit supplied by USA Promega Company, three specific primers to CaMV-35S promoter, T-Nos terminator and β-actin housekeeping gene supplied by Canadian Alpha Company were used. To quantitative detection of increase and decrease in copy number of GM tomato samples contain CaMV-35S promoter and T-Nos terminator, comparing with the β-actin (houskeeping gene) using Multiple of Median (MoM) equation. The results showed that the lowest recorded of Ct value was (27.88) for CaMV-35S promoter gave an increase in copy number (1.1766) above the normal limit, while highest recorded of Ct value was (32.67) gave an increase in copy number (1.0350) above the normal limit. The lowest recorded of Ct value was (27.35) for T-Nos terminator gave an increase in copy number (1.1600) above the normal limit, whereas highest recorded of Ct value was (32.82) gave a decrease in copy number (0.9920) under the normal limit.
Docking Studies on Anticancer Drugs for Breast Cancer Using Hex

Cancer can be described as the uncontrolled growth of abnormal cells. Breast cancer is the second most common type of cancer after lung cancer. Normal breast cells and most breast cancer cells have receptors that attach to circulating estrogen and progesterone. Estrogen and progesterone bind to the receptors and may work with growth factors (e.g., oncogenes and mutated tumor suppressor genes) to cause cancer cell growth and proliferation. Some of the most commonly used breast cancer drugs are Tamoxifen, Raloxifene, Toremifene etc, breast cancer cells need estrogen to grow. These drugs mainly work against the effects of estrogen on these cells. The Protein- Ligand interaction plays a significant role in structural based drug designing. In our research work we have taken the Human estrogen receptor and the commercially available drugs against breast cancer. The receptor was docked to the above said drugs and the energy value obtained as follows Tamoxifen (-49.0), Raloxifene (-158.0), Toremifene (-108.0) using the HEX docking software. Depending on the energy values we have chosen the best two drugs they are Raloxifene and Toremifene. We tried to improve the binding efficiency and steric compatibility of the two drugs namely Raloxifene and Toremifene. Several modifications were made to the probable functional groups which were interacting with the receptor molecule. Analogs of this drug molecule were prepared using ACD ChemSketch and docked using HeX docking software. Raloxifene Analog 7 and Toremifene analog 6 were detected with significant energy values and probable lead molecules. The Modified drugs was sketched using Chemsketch were found to be better than the conventional drugs available. Further from this work we can improve the steric compatibility and then ADME/T properties of the Analogs can be analyzed using Inslico ADME/T tools available.
Grass greenness and grass height promote the resource partitioning among reintroduced Burchell's zebra and blue wildebeest in southern Mozambique

Differences in the selection of habitat and specific dietary items support resource partitioning and coexistence of sympatric African grazing herbivores, such as zebra and wildebeest. In Maputo Special Reserve (MSR), southern Mozambique, these two species were extirpated during the civil war (1977–1992); since 2010, they have been reintroduced into the Reserve. Identifying the resource selection by reintroduced species and how these species coexist, while utilising the same resources, is both of ecological interest and important for the management of wildlife communities and parks. This is a key application of our research. Therefore, the present study investigated resource partitioning between Burchell's zebra (Equus burchelli, Smuts 1832) and blue wildebeest (Connochaetes taurinus, Burchell 1823) in the MSR. We conducted the study from July 2016 to June 2017. The data were collected by direct observation, driving the vehicle along the reserve's roads that covered the vegetation communities where zebras and wildebeest are known to commonly occur. The composition of the diet and specific features of the grass grazed by the two species, including greenness, height, and the number of stems, were assessed. The widely available grass, Aristida barbicollis, contributed most to the diet of both herbivores. The dietary overlap between the two herbivores was higher during the dry season (95%) than wet season (86%). Resources partitioning appears to be determined, principally, by the height and greenness of the grass, with the zebra grazing taller grass, which may facilitate the access of the wildebeest to the greener, lower proportion of the forage. That results follow the expectation that, among native herbivores, overlap in resource use is not expected based on evolutionary segregation.
Non-line-of-sight object detection based on the orthogonal matching pursuit compressive sensing reconstruction

Recently, non-line-of-sight (NLOS) imaging is a novel optical computational imaging technology developed. In NLOS imaging, objects are reconstructed by analyzing information carried in the reflected light. Considering the flaws in NLOS such as information loss and weak target detection due to diffuse reflection of light, developing a stable and effective imaging system is nontrivial. Therefore, in this paper, a 2D object inspection system based on compressed sensing and Orthogonal Matching Pursuit (CSOMP) approaches for effective NLOS imaging is proposed. This will not only alleviate the difficulty in collecting object information in a low light environment but also make the reconstruction process with a few measurements. Specifically, the single-pixel camera based on Digital Micromirror Device (DMD) is introduced to fully exploit the programmable pattern information and the correlation between the measured intensity data for image renovation. To reduce acquisition time, a high-efficiency single-pixel detector is employed that obviates the need for mechanical scanning. Also, in the image reconstruction stage, the residuals of the measurement matrix are obtained through OMP. The proposed method combines with the CS theory; thus, the target can be rebuilt with fewer measurements. Experimental results on NLOS images illustrate that the proposed imaging scheme reconstructed the image exactly similar to the real object.
Signatures of divergent antimalarial treatment responses in peripheral blood from infants and adults in Malawi

Background Heterogeneity in the immune response to parasite infection is mediated in part by differences in host genetics, sex, and age group. In neonates and infants, ongoing immunological maturation often results in increased susceptibility to infection and variable responses to drug treatment, increasing the risk of complications. Even though significant age-specific effects on host cytokine responses to Plasmodium falciparum infection have been identified, age effects on uncomplicated malaria infection and antimalarial treatment remain poorly understood. Methods In samples of whole blood from a cohort of naturally infected malaria-positive individuals in Malawi (n=63 total; 34 infants <2 years old, 29 adults >18 years old), we assessed blood cytokine levels and characterized monocyte and dendritic cell frequencies at two timepoints: acute infection, and four weeks post antimalarial treatment. We modeled the effects of age group, sex, and timepoint, and evaluated the role of these factors on infection and treatment outcomes. Results Regardless of treatment timepoint, in our population age was significantly associated with overall blood hemoglobin, which was higher in adults, and plasma nitric oxide, IL-10, and TNF-α levels, which were higher in infants. We found a significant effect of age on the hemoglobin treatment response, whereby after treatment, levels increased in infants and decreased in adults. Furthermore, we observed significant age-specific effects on treatment response for overall parasite load, IFN-γ and IL-12(p40), and these effects were sex-dependent. We uncovered significant age effects on the overall levels and treatment response of myeloid dendritic cell frequencies. In addition, within each age group, we found continuous age effects on gametocyte levels (Pfs16), TNF-α, and nitric oxide. Conclusions In a clinical study of infants and adults experiencing natural malaria infection and receiving antimalarial treatment, we identified age-specific signatures of infection and treatment responses in peripheral blood. We describe host markers that may indicate, and potentially mediate, differential post-treatment outcomes for malaria in infants versus adults.
Biological age is a universal marker of aging, stress, and frailty

We carried out a systematic investigation of supervised learning techniques for biological age modeling. The biological aging acceleration is associated with the remaining health- and life-span. Artificial Deep Neural Networks (DNN) could be used to reduce the error of chronological age predictors, though often at the expense of the ability to distinguish health conditions. Mortality and morbidity hazards models based on survival follow-up data showed the best performance. Alternatively, logistic regression trained to identify chronic diseases was shown to be a good approximation of hazards models when data on survival follow-up times were unavailable. In all models, the biological aging acceleration was associated with disease burden in persons with diagnosed chronic age-related conditions. For healthy individuals, the same quantity was associated with molecular markers of inflammation (such as C-reactive protein), smoking, current physical, and mental health (including sleeping troubles, feeling tired or little interest in doing things). The biological age thus emerged as a universal biomarker of age, frailty and stress for applications involving large scale studies of the effects of longevity drugs on risks of diseases and quality of life. To be published as Chapter 2 in “Biomarkers of aging”, ed. A. Moskalev, Springer, 2019.
Automated performance tuning of distributed storage system based on deep reinforcement learning

Automated performance tuning is a tricky task for a large scale storage system. Traditional methods highly reply on experience of system administrators and cannot adapt to changes of working load and system configurations. Reinforcement learning is a promising machine learning paradigm which learns an optimized strategy from the trials and errors between agents and environments. Combining with the strong feature learning capability of deep learning, deep reinforcement learning has showed its success in many fields. We implemented a performance parameter tuning engine based on deep reinforcement learning for Lustre file system, a distributed file system widely used in HEP data centres. Three reinforcement learning algorithms: Deep Q-learning, A2C, and PPO are enabled in the tuning engine. Experiments show that, in a small test bed, with IOzone workload, this method can increase the random read throughput by about 30% compared to default settings of Lustre. In the future, it is possible to apply this method to other parameter tuning use cases of data centre operations.
Silencing of Rape: Treatment of Rape Events and Rape Victims by Media and Fiction

Sexual abuse affects over 120 million children globally (UNICEF, 2018). There has been a total of 48, 338 cases of rape of minors in India, with an increase of 336% from 2,113 in 2001 to 7,112 in 2011 (Gohain, 2013). In US, almost half of female victims (46.7%) had been raped by an acquaintance (Breiding, 2014), with assaults (55%) occurring at or near the victim’s house (Planty & Langton, 2013). Each time a rape victim dies, there is public outcry with both press and writers’ calling for action but this has not helped the cause. Largely because “rape is not just forcible intercourse; rape means to inhabit and destroy everything” (Sebold, Lucky, 2002). This research analyses headlines and quotations on sexual crimes from mainstream online news from 2018 to 2019 from India and Malaysia. Using Austin’s Speech act theory, the study compares voices of rape victims and witnesses and argues for reason and social responsibility. The findings revealed significant differences in discourse patterns, language use, and witness response. In providing a worm’s eye view, Indian press in appearing to speak louder for victims, create greater sensationalism compared to Malaysian press which often focus on the culprit and process of law and quickly silences the matter. Given media sensationalism and agenda setting of both nations, there is the need for greater scrutiny on how media provides a voice to victims and helps raise awareness and social responsibility when reporting sexual crimes. Keywords: W omen, rape survivors, trial by media, voicing, stylistic analysis.