Miracle-dz/UniFAR-FTUs huggingface dataset:
A note on adaptivity in factorized approximate inverse preconditioning

Abstract The problem of solving large-scale systems of linear algebraic equations arises in a wide range of applications. In many cases the preconditioned iterative method is a method of choice. This paper deals with the approximate inverse preconditioning AINV/SAINV based on the incomplete generalized Gram–Schmidt process. This type of the approximate inverse preconditioning has been repeatedly used for matrix diagonalization in computation of electronic structures but approximating inverses is of an interest in parallel computations in general. Our approach uses adaptive dropping of the matrix entries with the control based on the computed intermediate quantities. Strategy has been introduced as a way to solve di cult application problems and it is motivated by recent theoretical results on the loss of orthogonality in the generalized Gram– Schmidt process. Nevertheless, there are more aspects of the approach that need to be better understood. The diagonal pivoting based on a rough estimation of condition numbers of leading principal submatrices can sometimes provide inefficient preconditioners. This short study proposes another type of pivoting, namely the pivoting that exploits incremental condition estimation based on monitoring both direct and inverse factors of the approximate factorization. Such pivoting remains rather cheap and it can provide in many cases more reliable preconditioner. Numerical examples from real-world problems, small enough to enable a full analysis, are used to illustrate the potential gains of the new approach.
Eusocial bee male aggregations: spatially and temporally separated but genetically homogenous

Male insects mostly aggregate near sites where sexually reproductive virgin females are found and where mating occur. This reproductive strategy is quite common in Hymenoptera and appears to decrease the chances of inbreeding. In Hymenoptera, inbred mating frequently result in sterile diploid males. Production of diploid males may reach high proportions in small bee populations, and it usually lead to population extinction within a small number of generations. Aggregation of males during a short period of time allow the mixing of local genes. In this paper, we analyzed male aggregations of Tetragonisca angustula (Latreille) (Hymenoptera: Apidae), a eusocial stingless bee, using microsatellite molecular markers. We used population genetic statistics for haplodiploid organisms to address genetic structuring among male aggregations. Our findings indicate that, in general, male aggregations of T. angustula occurring over short time scales and in close proximity are genetically homogeneous as if a single aggregation. We conclude that T. angustula males randomly disperse within a population looking for mating chances rather than settle on a distinct male aggregation. This behavior seems to contribute to the reduction of inbreeding in this species.
Enhanced separation of cellulose from bamboo with a combined process of steam explosion pretreatment and alkaline-oxidative cooking

Abstract A synergistic process with steam explosion pretreatment (SEP) followed by sodium carbonate-oxygen cooking (SCOC) upon bamboo was evaluated for its effect on separating hemicellulose and lignin from bamboo while preserving cellulose, providing cellulose substrate susceptible to chemicals in producing platform chemicals such as levulinic acid. The results showed that through the SEP with 2.5 MPa for 10 min, the hemicellulose content reduced by 60.85 %, the specific surface area of bamboo fiber increased to 1.9494 m2g-1 from 0.8061 m2g-1 of raw material. The synergistic SEP-SCOC significantly removed 73.33 % lignin, and yielded 73.9 % cellulose under the optimal condition of SEP with 2.5 MPa for 10 min and followed by SCOC with 30 % total titratable alkali (TTA) at 180 °C for 2 h and 2 MPa oxygen pressure. The results also proved the total lignin removal was improved by 8.07–18.95 % for the steam exploded bamboo fibers than the untreated one, indicating SEP increased the accessibility of cooking reagents to fibre during subsequent SCOC process. Furthermore, the low value of biological oxygen demand (BOD) and chemical oxygen demand (COD) in the final spent liquor indicated the lower pollution level of the process.
Nordic Noir from Within and Beyond: Negotiating geopolitical regionalisation through SVoD crime narratives

Abstract In this article, I show how a vision for the Nordic region exists as a banal Nordism, based on years of content exchange, Nordic co-production models, and public funding opportunities. I document how new commercial players have been able to gain a very large market share in only a few years, significantly disrupting the reach of public service broadcasters in the Nordic region. The three largest contemporary commercial players on the Nordic market – Viaplay, HBO, and Netflix – have been able to, in very different ways, tap into the ideology of banal Nordism and the geopolitical unity of the Nordic region, and they have done so by producing and acquiring content that has deep associations with one of the Nordic region's main international brands: Scandinavian crime fiction and Nordic Noir.
Human umbilical cord stem cells – the discovery, history and possible application

Abstract Stem cells are now one of the most extensively studied fields in experimental medicine. Although embryonic stem cells (ESCs) have the capability to differentiate into lineages derived from all three primary germ layers, their use remains ethically controversial. Mesenchymal stromal cells’ (MSCs) utilization is not burdened with such concerns. MSCs were primarily characterized as fibroblastic cells from bone marrow stroma, with the ability to adhere to plastic and form clonogenic colonies (CFU-Fs – colony-forming unit-fibroblasts). Subsequent studies led to their isolation from various other adult or perinatal tissues, including the umbilical cord. Although in most cases MSCs are obtained from umbilical cords’ stroma (Wharton’s jelly), it has been demonstrated that both cord’s lining and endothelial layer of umbilical vein possess the cells that fulfill the minimal criteria for MSCs published in 2006 by the International Society for Cellular Therapy. Since the initial discovery, a number of pre-clinical and clinical studies were conducted with the use of MSCs derived from umbilical cords, targeting diseases such as cancer or autoimmune diseases. Moreover, their secretome may be even more beneficial, providing an opportunity to create cell-free therapies. Running title: The history of human umbilical cord stem cells
Numerical approach to the controllability of fractional order impulsive differential equations

Abstract In this manuscript, a numerical approach for the stronger concept of exact controllability (total controllability) is provided. The proposed control problem is a nonlinear fractional differential equation of order α ∈ ( 1 , 2 ] \alpha \in (1,2] with non-instantaneous impulses in finite-dimensional spaces. Furthermore, the numerical controllability of an integro-differential equation is briefly discussed. The tool for studying includes the Laplace transform, the Mittag-Leffler matrix function and the iterative scheme. Finally, a few numerical illustrations are provided through MATLAB graphs.
Extending the Theory of Planned Behaviour to Explain Energy Saving Behaviour

Abstract Existing research in environmental psychology suggests that humans are conscious of the impact that their actions have on the environment. However, a corresponding change is yet to be seen in the voluntary adoption of pro-environmental behaviour by the Indian population. While there is an overall improvement in the ecological consciousness, we need to find out the psychological factors that promote adoption and maintenance of environmentally responsible behaviour. The current study incorporated the construct of consideration of future consequences (CFC) into the theory of planned behaviour (TPB) to investigate energy-conservation behaviour in 232 college students. Results confirmed that TPB constructs predict pro-environmental behaviour. Results also confirmed that consideration of future consequences is positively related to efficiency enhancing pro-environment behaviour. The research has implications for planning interventions that address both adoption and maintenance of pro-environment behaviour.
Novel coronavirus – SARS CoV-2

Abstract Coronaviruses cause a variety of diseases in mammals and birds. In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). This virus appears to be a new human pathogen. In this article the biology of virus has been described, replication cycle and epidemiology of COVID 19. The next part discusses current methods of laboratory diagnostics. The coronavirus disease 2019 (COVID-19) pandemic has focused attention on the need to develop effective therapies against the causative agent, SARS-CoV-2. Researchers are therefore focusing on steps in the CoV replication cycle that may be target to inhibition by broad-spectrum or specific antiviral agents. Many laboratories focus on vaccine development. SARS-CoV-2 vaccines will be essential to reduce morbidity and mortality if the virus establishes itself in the human population.
Using LSI to Detect Unknown Malicious VBA Macros

: Targeted email attacks are one of the main threats to organizations of all sizes and ﬁelds. In targeted email attacks, malicious VBA (Visual Basic for Applications) macros are often embedded into the attachment ﬁles to compromise the target computers. These malicious VBA macros are obfuscated in several ways to deceive anti-virus programs. Therefore there are limitations on applying pattern-based detection to detecting these unknown malicious VBA macros. To detect unknown malicious VBA macros, some methods with machine learning techniques are applicable. One method extracts words from the source code, and constructs a language model to represent VBA macros for machine learning techniques. This method constructs a language model from all the extracted words which include trivial words. Hence, there seems still room for improvement of this model. To construct an e ﬃ cient language model, this paper focuses on LSI (Latent Semantic Indexing). LSI is a fundamental technique in topic modeling and calculates similarity of documents. Our method extracts words from the source code and converts them into feature vectors with several natural language processing techniques. Our method trains a classiﬁer with benign and malicious VBA macros and detects unknown malicious VBA macros. Several thousands of samples for evaluation are obtained from Virus Total. The experimental results show that our method could detect unknown malicious VBA macros more e ﬃ ciently, and reveal the advantages and disadvantages of each language model.
Dropping out from Higher Education in Germany an Empirical Evaluation of Determinants for Bachelor Students

Abstract Withdrawing from university is a complex decision-making process, during which several conditions and problems from different areas of life and study accumulate and affect each other. This study is based on the National Educational Panel Study (NEPS), which includes a wide range of information on study course and students’ characteristics, and aims at providing an encompassing analysis of determinants influencing students’ dropout decision. Determinants can be categorized into demographic and family background, the financial situation of students, their prior education, institutional determinants, as well as motivation and satisfaction with study. Both, a bivariate analysis, as well as a logistic regression model with LASSO regularization identify many important determinants already known before or at the beginning of the study, such as prior education and satisfaction related variables, allowing early identification of at-risk students and the implementation of prevention programs.
Compact Elliptic Curve Scalar Multiplication with a Secure Generality

Elliptic curve cryptosystems (ECCs) are widely used because of their short key size. ECCs can ensure sufficient security with shorter keys, using less memory to reduce parameters. Hence, ECCs are typically used in IoT devices. The dominant computation of an ECC is scalar multiplication Q = kP for P ∈ E(Fq). Thus, the security and efficiency of scalar multiplication are paramount. To render secure ECCs, complete addition (CA) formulae can be employed for secure scalar multiplication algorithms. However, this requires significant memory; thus, it is not suitable for compact devices. Several types of coordinates exist for elliptic curves such as affine, Jacobian, Projective and so on. The CA formulae are not based on affine coordinates and, thus, require considerable memory. In this study, we achieve a compact ECC by focusing on affine coordinates. In fact, affine coordinates are highly advantageous in terms of memory but require many if statements for scalar multiplication owing to exceptional points. We propose two scalar multiplication algorithms with the extended affine formulae to delete some exceptional inputs for scalar multiplication. Our two algorithms reduce memory cost up to 37% or 21%. In many cases such as NIST elliptic curves, our two algorithms are the most efficient if I M < 12, for the ratio of computational cost of inversion and multiplication. The experiment shows that our algorithms can compute the elliptic curve scalar multiplication correctly and efficiently.
Adaptive Participation in Forest Planning Contingent on a Hypothetical Large-Scale Forest Disturbance

Public involvement in management decisions is a vital requirement for successful adaptive forest management. I suggest that a critical and systematic examination is needed to understand why various publics become involved in forest-related management decisions and, more importantly, how public involvement in forest planning is likely to change under altered biophysical and social conditions caused by large-scale forest disturbances such as invasive species outbreaks. I address this need through a field-based stated preference experiment administered to three communities located near national forests within the eastern United States. I specifically examine three reasons that might compel individuals to become involved in forest planning: the loss of forest-related jobs, the loss of recreational amenities, and the loss of wildlife habitat and also examine the effects of gender on contingent behavior. The data suggest that all three potential losses have significant effects on individuals’ behavioral intentions to participate in forest planning. The potential loss of wildlife habitat had the strongest influence on individuals’ behavioral intentions. The potential loss of local forest-related jobs and recreational amenities had slightly less influence. Behavioral intentions to participate in forest planning also differed significantly by gender. The results suggest that changes in biophysical and social systems due to large-scale forest disturbances have the potential to dramatically alter public participation in environmental decisionmaking processes. Various factors, including the system properties likely to be affected, the extent to which those properties are affected, and the gender of potential participants, are likely to be key variables that result in new patterns of involvement in forest planning and management decisions. FOR. SCI. 59(6):637–648.
Soft computing based compressive sensing techniques in signal processing: A comprehensive review

Abstract In this modern world, a massive amount of data is processed and broadcasted daily. This includes the use of high energy, massive use of memory space, and increased power use. In a few applications, for example, image processing, signal processing, and possession of data signals, etc., the signals included can be viewed as light in a few spaces. The compressive sensing theory could be an appropriate contender to manage these limitations. “Compressive Sensing theory” preserves extremely helpful while signals are sparse or compressible. It very well may be utilized to recoup light or compressive signals with less estimation than customary strategies. Two issues must be addressed by CS: plan of the estimation framework and advancement of a proficient sparse recovery calculation. The essential intention of this work expects to audit a few ideas and utilizations of compressive sensing and to give an overview of the most significant sparse recovery calculations from every class. The exhibition of acquisition and reconstruction strategies is examined regarding the Compression Ratio, Reconstruction Accuracy, Mean Square Error, and so on.
A new classification method of nanotechnology for design integration in biomaterials

Abstract Currently, advanced biomaterial design solutions often have more than two kinds of nanotechnology design strategies, but there is no suitable classification to describe these designs systematically. Based on the material design ideas and the modes of implementing functions, this article exemplifies and proposes a new nanotechnology classification that includes physical properties, the chemical reactions that respond to the microenvironment and bio-inspired incorporation. If two or more nanotechnology designs in the same classification are to be integrated into the same biological material, it is necessary to analyze the integration conflict between the designs. With the development of big data, this classification method may help researchers and artificial intelligence to realize automated integration of multiple designs and provide new material nanotechnology design integration solutions.
An immune-relevant signature of nine genes as a prognostic biomarker in patients with gastric carcinoma

Abstract Background As one of the most common malignant tumors worldwide, the morbidity and mortality of gastric carcinoma (GC) are gradually increasing. The aim of this study was to construct a signature according to immune-relevant genes to predict the survival outcome of GC patients using The Cancer Genome Altas (TCGA). Methods Univariate Cox regression analysis was used to assess the relationship between immune-relevant genes regarding the prognosis of patients with GC. The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to select prognostic immune-relevant genes and to establish the signature for the prognostic evaluation of patients with GC. Multivariate Cox regression analysis and Kaplan–Meier survival analysis were used to assess the independent prognostic ability of the immune-relevant gene signature. Results A total of 113 prognostic immune-relevant genes were identified using univariate Cox proportional hazards regression analysis. A signature of nine immune-relevant genes was constructed using the LASSO Cox regression. The GC samples were assigned to two groups (low- and high risk) according to the optimal cutoff value of the signature score. Compared with the patients in the high-risk group, patients in the low-risk group had a significantly better prognosis in the TCGA and GSE84437 cohorts (log-rank test P < 0.001). Multivariate Cox regression analysis demonstrated that the signature of nine immune-relevant genes might serve as an independent predictor of GC. Conclusions Our results showed that the signature of nine immune-relevant genes may potentially serve as a prognostic prediction for patients with GC, which may contribute to the decision-making of personalized treatment for the patients.
Early Parkinson’s Disease-Like Pathology in a Transgenic Mouse Model Involves a Decreased Cst3 mRNA Expression But Not Neuroinflammatory Response in the Brain

Abstract Pathological aggregation and accumulation of α-synuclein in neurons play a core role in Parkinson’s disease (PD) while its overexpression is a common PD model. Autophagy-lysosomal pathways are general intraneural mechanisms of protein clearance. Earlier a suppressed autophagy in the brain of young transgenic mice overexpressing the А53Т-mutant human α-synuclein (mut(PD)) was revealed. Previous studies have recognized that Cystatin C displays protective activity against neurodegeneration. This cysteine protease inhibitor attracts particular attention as a potential target for PD treatment related to autophagy modulation. Here we evaluated the mRNA levels of Cst3 encoding Cystatin C in different brain structures of 5 m.o. mut(PD) mice at standard conditions and after the chronic treatment with a neuroprotective agent, ceftriaxone (100 mg/kg, 36 days). The inflammatory markers, namely, microglial activation by IBA1 expression and mRNA levels of two chitinases genes (Chit1, Chia1), were also assessed but no significant difference was found between control and transgenic mice. Cst3 mRNA levels were significantly reduced in the striatum and amygdala in the transgenic PD model. Furthermore, this was associated with autophagy decline and might be added to early signs of synucleinopathy development. We first demonstrated the modulation of mRNA levels of Cst3 and autophagy marker Becn1 in the brain by ceftriaxone treatment. Taken together, the results support the potential of autophagy modulation through Cystatin C at early stages of PD-like pathology.
Forest care, interconnectivity and maintenance of ecological resources among the Manobo-Matigsalug people of the Southern Philippines

Abstract This article discusses the knowledge of indigenous people about forest care, interconnectivity and maintenance of their ecological resources as well as the challenges they face among the Matigsalug-Manobo people of Marilog District, Davao City, Philippines. The researchers utilized a descriptive research design through qualitative methods such as in-depth interviews, focus-group discussions and photo-video documentation. To extract the data, the necessary permits and ethical compliance were provided by the respective parties of the Department of Environment and Natural Resources Region 11, the Local Government Unit of Marilog District and the Manobo-Matigsalug Tribal Council Incorporated. The data gathered were analyzed through thematic analysis focusing on the dominant themes from the respondents’ narratives. The results revealed that these people’s indigenous knowledge on biodiversity conservation has been challenged by changes in the natural landscape, forest deterioration and the unintended consequences of these such as cultural loss and economic well-being. Thus, this has led to major implications of how they conserve the forest and manage their ecological resources in the current times. This calls for building a sustainable and inclusive economic livelihood for the indigenous group and other stakeholders in the Marilog district. This is a vital step in order not to compromise their economic livelihood, to retain cultural practices and to maintain their rights to manage and sustain their ecological resources. Overall, the Matigsalug-Manobos are actively negotiating the cause and effects of these socio-economic factors and are able to devise ways to use the forest and its ecological resources for their survival.