Miracle-dz/UniFAR-FTUs huggingface dataset:
International Journal of Innovative Research in Computer and Communication Engineering

Machine learning is a subfield ofcomputer science that includes the study of systems that can learn from data, rather than follow only explicitly programmed instructions. Some of the most common techniques used for machine learning are Support Vector Machine, Artificial Neural Networks, K Nearest Neighbor and Decision Tree. Machine learning techniques are widely used techniques in bioinformatics to solve different type of problems. Protein structure prediction is one of the problems that can be solved using machine learning. The molecules which are important in our cells are Proteins. They are virtually involved in all cell functions. Proteins are categorized on the basis of the occurrence of conserved amino acid patterns which is the feature extraction method. In the post-genomic era Protein function prediction is an important problem. Advancements in the experimental biology have enabled the production of enormous amount of protein-protein interaction data. Thus, to functionally annotate proteins has been extensively studied using protein-protein interaction data. When annotation and interaction information is inadequate in the networks most of the existing network based approaches do not work well. In this paper an attempt has been made to review different papers on proteins functions and structures that are predicted using the various machine learning methods.
Semantic segmentation-using Convolutional Neural Networks and Sparse Dictionaries

The two main bottlenecks using deep neural networks are data dependency and training time. This thesis proposes a novel method for weight initialization of the convolutional layers in a convolutional neural network. This thesis introduces the usage of sparse dictionaries. A sparse dictionary optimized on domain specific data can be seen as a set of intelligent feature extracting filters. This thesis investigates the effect of using such filters as kernels in the convolutional layers in the neural network. How do they affect the training time and final performance? The dataset used here is the Cityscapes-dataset which is a library of 25000 labeled road scene images. The sparse dictionary was acquired using the K-SVD method. The filters were added to two different networks whose performance was tested individually. One of the architectures is much deeper than the other. The results have been presented for both networks. The results show that filter initialization is an important aspect which should be taken into consideration while training the deep networks for semantic segmentation.
Coding and decoding for the Dynamic Decode and Forward relay protocol

We study the dynamic decode and forward (DDF) protocol for a single half-duplex relay, single-antenna channel with quasi-static fading. We analyze the diversity-multiplexing tradeoff (DMT) of the DDF protocol for the case of finite block-lengths, and provide simple constructions of explicit, DMT optimal codes. Reduced complexity lattice decoding algorithms for the proposed codes are investigated.
Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm

Leishmaniasis is a disease caused by at least 17 different species of protozoan Leishmania parasites and currently affects around 12 million people living mostly in tropical and subtropical areas. Failure to treat leishmaniasis successfully is often due to drug resistance. However, there are no cellular and molecular markers of chemoresistance against leishmanicidal drugs and the only reliable method for monitoring resistance of individual isolates is the in vitro amastigote/macrophage model. It is thus necessary to find cellular and molecular markers that can be used systematically to identify the drug-resistant phenotype of the infecting parasites. Until now, whether drug resistance in Leishmania compromises parasite proficiency, e.g. in terms of infectivity or metabolism, has not been systematically evaluated. Therefore, here we examine whether the physiological changes expressed by drug-resistant Leishmania reflect a modification of parasite vitality in drug-resistant compared with drug-sensitive parasites. Finally, the clinical implications of drug resistance in Leishmania are also discussed.
GECCO 2013 tutorial: cartesian genetic programming

Cartesian Genetic Programming (CGP) is an increasingly popular and efficient form of Genetic Programming. Cartesian Genetic Programming is a highly cited technique that was developed by Julian Miller in 1999 and 2000 from some earlier joint work of Julian Miller with Peter Thomson in 1997. In its classic form, it uses a very simple integer based genetic representation of a program in the form of a directed graph. Graphs are very useful program representations and can be applied to many domains (e.g. electronic circuits, neural networks). In a number of studies, CGP has been shown to be comparatively efficient to other GP techniques. It is also very simple to program. Since then, the classical form of CGP has been developed made more efficient in various ways. Notably by including automatically defined functions (modular CGP) and self-modification operators (self-modifying CGP). SMCGP was developed by Julian Miller, Simon Harding and Wolfgang Banzhaf. It uses functions that cause the evolved programs to change themselves as a function of time. Using this technique it is possible to find general solutions to classes of problems and mathematical algorithms (e.g. arbitrary parity, n-bit binary addition, sequences that provably compute pi and e to arbitrary precision, and so on). This tutorial is will cover the basic technique, advanced developments and applications to a variety of problem domains. The first edited book on CGP was published by Springer in September 2011. CGP has its own dedicated website http://www.cartesiangp. co.uk
Life‐history strategies indicate live‐bearing in Nothosaurus (Sauropterygia)

In Sauropterygia, a diverse group of Mesozoic marine reptiles, fossil evidence of viviparity (live‐bearing) only exists for Pachypleurosauria and Plesiosauria, and was assumed to also be the case for nothosaurs. Previous studies have successfully applied an extant squamate model to sauropterygian life‐history traits. In extant squamates, oviparity and viviparity are associated with differences in life‐history trait combinations. We establish growth curves for Nothosaurus specimens based on their humeral histology. We then analyse life‐history traits derived from these curves and compare inferred traits to those of modern squamates and pachypleurosaurs to assess their reproduction mode. We show that birth to adult size ratios (i.e. birth size divided by the mother's size) provide good estimates of clutch sizes in extant squamates and in viviparous extinct marine reptiles, but these ratios cannot discriminate viviparous and oviparous squamates. Thus, large ratios do not indicate viviparity in fossil taxa to which the extant squamate model is applicable. Applying differences in birth size, age at maturation, and maximum longevity that are observed between extant viviparous and oviparous squamates to our Nothosaurus sample, we identified 7 out of 24 specimens as being potentially viviparous. Conversely, they suggested oviparity for many nothosaurs but also for many pachypleurosaur samples. Under the assumption that the entire clade Pachypleurosauria was viviparous, the majority of nothosaurs would also have been viviparous as they comprised trait combinations similar to those seen in pachypleurosaurs. Overall, this suggests that within nothosaurs and pachypleurosaurs both reproduction modes existed in different taxa.
Interfirewall optimization across various administrative domain for enabling security and privacy preserving

Network security is usually protected by a firewall, which checks in-out packets against a set of defined policies or rules. Hence, the overall performance of the firewall generally depend on its rule management. For example, the performance can be decreased when there are firewall rule anomalies. The anomalies may happen when two sets of firewall rules are overlapped or their decision parts are both an acceptance and a denial simultaneously. Firewall optimization focuses on either inter-firewall or intra-firewall optimization within one administrative domain where the privacy of firewall policies is not a concern. Explore interfirewall optimization across administrative domain for the first time. The key technical challenge is that firewall policy cannot be shared across domains because a firewall policy contains confidential information and even potential security holes, which can be exploited by attackers. Using interfirewall redundant rule which overcome the prior problem and enable the interfirewall optimization across administrative domains. Also propose the first cross domain cooperative firewall (CDCF) policy optimization protocol. The optimization process involves cooperative computation between the two firewall without any party disclosing its policy to the other. KeywordsInterfirewall optimization, Redundancy Removal algorithm.
Social learning mechanisms compared in a simple environment

Social learning can be adaptive, but little is known about the underlying mechanisms. Many researchers have focused on imitation but this may have led to simpler mechanisms being underestimated. We demonstrate in simulation that imitative learning is not always the best strategy for a group-living animal, and that the effectiveness of any such strategy will depend on details of the environment and the animal's lifestyle. We show that observations of behavioural convergence or "traditions" might suggest effective social learning, but are meaningless considered alone.
Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method

We study the Lanczos method for approximating the action of a symmetric matrix function f ( A ) on a vector b (Lanczos-FA). For the function A − 1 , it is known that the error of Lanczos-FA after k iterations matches the error of the best approximation from the Krylov subspace of degree k when A is positive deﬁnite. We prove that the same holds, up to a multiplicative approximation factor, when f is a rational function with no poles in the interval containing A ’s eigenvalues. The approximation factor depends the degree of f ’s denominator and the condition number of A , but not on the number of iterations k . Experiments conﬁrm that our bound accurately predicts the convergence of Lanczos-FA. Moreover, we believe that our result provides strong theoretical justiﬁcation for the excellent practical performance that has long by observed of the Lanczos method, both for approximating rational functions and functions like A − 1 / 2 b that are well approximated by rationals.
International Food and Agribusiness Management Review

Soybean production has been widely promoted in sub-Saharan Africa as a means of improving rural household income. Numerous studies point to poor adoption levels, low yield levels, and limited profitability among smallholder farmers. Poor performance of soybean among smallholders generates numerous hypotheses as to the root causes. One logical cause is low prices, which result from anecdotes from the field, especially among producers and policymakers. In this study, the first of its kind that we are aware of, analyzes regional soybean prices over time across six key growing and commercial regions of Ghana. We employ cointegration and multivariate vector error correction model to measure the level of international and inter-market integration and performance. The results show regional and international integration as well as Granger Causality results consistent with the local supply-demand context. Specifically, the international market Granger causes Kumasi, Bolgatanga, and Wa markets, while the Tamale and Kumasi, serve as the leading production and demand markets, respectively. The results of the study provide evidence that prices do perform well in Ghana and are not a major source of weak adoption and low levels of profitability among smallholder soybean farmers.
Influence of the COVID-19 Outbreak in Vulnerable Patients (Pediatric Patients, Pregnant Women, and Elderly Patients) on an Emergency Medical Service System: A Pre- and Post-COVID-19 Pandemic Comparative Study Using the Population-Based ORION Registry

Background and Objective: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread all over the world. To assess the influence of the COVID-19 pandemic on emergency medical services (EMS) for vulnerable patients transported by ambulance. Materials and Methods: This study was a retrospective, descriptive study with a study period from 1 January 2019 to 31 December 2021 using the Osaka Emergency Information Research Intelligent Operation Network (ORION) system. We included all pediatric patients, pregnant women, and elderly patients ≥ 65 years of age transported by ambulance in Osaka Prefecture. The main outcome of this study was difficult-to-transport cases. We calculated the rate of difficult-to-transport cases under several conditions. Results: For the two year-long periods of 1 January 2019 to 31 December 2019 and 1 January 2021 to 31 December 2021, a total of 887,647 patients were transported to hospital by ambulance in Osaka Prefecture. The total number of vulnerable patients was 579,815 (304,882 in 2019 and 274,933 in 2021). Multivariate logistic regression analysis showed that difficult-to-transport cases were significantly more frequent in 2021 than in 2019. Difficult-to-transport cases were significantly less frequent in the vulnerable population than in the non-vulnerable population (adjusted odds ratio 0.81, 95% confidence interval 0.80–0.83; p < 0.001). Conclusion: During the pandemic (2021), difficult-to-transport cases were more frequent compared to before the pandemic (2019); however, vulnerable patients were not the cause of difficulties in obtaining hospital acceptance for transport.
Molecular Mechanism of Different Rooting Capacity between Two Clones of Taxodium hybrid ‘Zhongshanshan’

The conifer Taxodium hybrid ‘Zhongshanshan’ (T. hybrid ‘Zhongshanshan’) is characterized by rapid growth, strong stress resistance, and high ornamental value and has significant potential for use in afforestation, landscaping, and wood production. The main method of propagating T. hybrid ‘Zhongshanshan’ is tender branch cutting, but the cutting rooting abilities of different T. hybrid ‘Zhongshanshan’ clones differ significantly. To explore the causes of rooting ability differences at a molecular level, we analyzed the transcriptome data of cutting base and root tissues of T. hybrid ‘Zhongshanshan 149’ with a rooting rate of less than 5% and T. hybrid ‘Zhongshanshan 118’ with rooting rate greater than 60%, at the developmental time points in this study. The results indicated that differentially expressed genes between the two clones were mainly associated with copper ion binding, peroxidase, and oxidoreductase activity, response to oxidative stress, phenylpropanoid and flavonoid biosynthesis, and plant hormone signal transduction, among others. The expression pattern of ThAP2 was different throughout the development of the adventitive roots of the two clone cuttings. Therefore, this gene was selected for further study. It was shown that ThAP2 was a nuclear-localized transcription factor and demonstrated a positive feedback effect on rooting in transgenic Nicotiana benthamiana cuttings. Thus, the results of this study explain the molecular mechanism of cutting rooting and provide candidate gene resources for developing genetic breeding strategies for optimizing superior clones of T. hybrid ‘Zhongshanshan’.
The Hemorrhagic Side of Primary Angiitis of the Central Nervous System (PACNS)

Primary Angiitis of the Central Nervous System (PACNS) is a rare cerebrovascular disease involving the arteries of the leptomeninges, brain and spinal cord. Its diagnosis can be challenging, and the current diagnostic criteria show several limitations. Among the clinical and neuroimaging manifestations of PACNS, intracranial bleeding, particularly intracerebral hemorrhage (ICH), is poorly described in the available literature, and it is considered infrequent. This review aims to summarize the available data addressing this issue with a dedicated focus on the clinical, neuroradiological and neuropathological perspectives. Moreover, the limitations of the actual data and the unanswered questions about hemorrhagic PACNS are addressed from a double point of view (PACNS subtyping and ICH etiology). Fewer than 20% of patients diagnosed as PACNS had an ICH during the course of the disease, and in cases where ICH was reported, it usually did not occur at presentation. As trigger factors, both sympathomimetic drugs and illicit drugs have been proposed, under the hypothesis of an inflammatory response due to vasoconstriction in the distal cerebral arteries. Most neuroradiological descriptions documented a lobar location, and both the large-vessel PACNS (LV-PACNS) and small-vessel PACNS (SV-PACNS) subtypes might be the underlying associated phenotypes. Surprisingly, amyloid beta deposition was not associated with ICH when histopathology was available. Moreover, PACNS is not explicitly included in the etiological classification of spontaneous ICH. This issue has received little attention in the past, and it could be addressed in future prospective studies.
Understanding genetic diversity in drought-adaptive hybrid parental lines in pearl millet

Information on genetic diversity and population structure is helpful to strategize enhancing the genetic base of hybrid parental lines in breeding programs. The present study determined the population structure and genetic diversity of 109 pearl millet hybrid parental lines, known for their better adaptation and performance in drought-prone environments, using 16,472 single nucleotide polymorphic (SNP) markers generated from GBS (genotyping-by-sequencing) platforms. The SNPs were distributed uniformly across the pearl millet genome and showed considerable genetic diversity (0.337), expected heterozygosity (0.334), and observed heterozygosity (0.031). Most of the pairs of lines (78.36%) had Identity-by-State (IBS) based genetic distances of more than 0.3, indicating a significant amount of genetic diversity among the parental lines. Bayesian model-based population stratification, neighbor-joining phylogenetic analysis, and principal coordinate analysis (PCoA) differentiated all hybrid parental lines into two clear-cut major groups, one each for seed parents (B-lines) and pollinators (R-lines). Majority of parental lines sharing common parentages were found grouped in the same cluster. Analysis of molecular variance (AMOVA) revealed 7% of the variation among subpopulations, and 93% of the variation was attributable to within sub-populations. Chromosome 3 had the highest number of LD regions. Genomic LD decay distance was 0.69 Mb and varied across the different chromosomes. Genetic diversity based on 11 agro-morphological and grain quality traits also suggested that the majority of the B- and R-lines were grouped into two major clusters with few overlaps. In addition, the combined analysis of phenotypic and genotypic data showed similarities in the population grouping patterns. The present study revealed the uniqueness of most of the inbred lines, which can be a valuable source of new alleles and help breeders to utilize these inbred lines for the development of hybrids in drought-prone environments.
Alterations in Genome Organization in Lymphoma Cell Nuclei due to the Presence of the t(14;18) Translocation

Chromosomal rearrangements have been shown to alter genome organization, consequently having an impact on gene expression. Studies on certain types of leukemia have shown that gene expression can be exacerbated by the altered nuclear positioning of fusion genes arising from chromosomal translocations. However, studies on lymphoma have been, so far, very limited. The scope of this study was to explore genome organization in lymphoma cells carrying the t(14;18)(q32;q21) rearrangement known to results in over-expression of the BCL2 gene. In order to achieve this aim, we used fluorescence in situ hybridization to carefully map the positioning of whole chromosome territories and individual genes involved in translocation in the lymphoma-derived cell line Pfeiffer. Our data show that, although there is no obvious alteration in the positioning of the whole chromosome territories, the translocated genes may take the nuclear positioning of either of the wild-type genes. Furthermore, the BCL2 gene was looping out in a proportion of nuclei with the t(14;18) translocation but not in control nuclei without the translocation, indicating that chromosome looping may be an essential mechanism for BCL2 expression in lymphoma cells.
Deciphering Early-Stage Molecular Mechanisms of Negative Pressure Wound Therapy in a Murine Model

Negative Pressure Wound Therapy (NPWT) is a commonly employed clinical strategy for wound healing, yet its early-stage mechanisms remain poorly understood. To address this knowledge gap and overcome the limitations of human trials, we establish an NPWT C57BL/6JNarl mouse model to investigate the molecular mechanisms involved in NPWT. In this study, we investigate the intricate molecular mechanisms through which NPWT expedites wound healing. Our focus is on NPWT’s modulation of inflammatory immune responses and the concurrent orchestration of multiple signal transduction pathways, resulting in shortened coagulation time and reduced inflammation. Notably, we observe a significant rise in dickkopf-related protein 1 (DKK-1) concentration during NPWT, promoting the differentiation of Hair Follicle Stem Cells (HFSCs) into epidermal cells, expediting wound closure. Under negative pressure, macrophages express and release DKK-1 cytokines, crucial for stimulating HFSC differentiation, as validated in animal experiments and in vitro studies. Our findings illuminate the inflammatory dynamics under NPWT, revealing potential signal transduction pathways. The proposed framework, involving early hemostasis, balanced inflammation, and macrophage-mediated DKK-1 induction, provides a novel perspective on enhancing wound healing during NPWT. Furthermore, these insights lay the groundwork for future pharmacological advancements in managing extensive wounds, opening avenues for targeted therapeutic interventions in wound care.