Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning zero-cost portfolio selection with pattern matching

We replicate and extend the adversarial expert based learning approach of Györfi et al to the situation of zero-cost portfolio selection implemented with a quadratic approximation derived from the mutual fund separation theorems. The algorithm is applied to daily sampled sequential Open-High-Low-Close data and sequential intraday 5-minute bar-data from the Johannesburg Stock Exchange (JSE). Statistical tests of the algorithms are considered. The algorithms are directly compared to standard NYSE test cases from prior literature. The learning algorithm is used to select parameters for experts generated by pattern matching past dynamics using a simple nearest-neighbour search algorithm. It is shown that there is a speed advantage associated with using an analytic solution of the mutual fund separation theorems. We argue that the strategies are on the boundary of profitability when considered in the context of their application to intraday quantitative trading but demonstrate that patterns in financial time-series on the JSE could be systematically exploited in collective and that they are persistent in the data investigated. We do not suggest that the strategies can be profitably implemented but argue that these types of patterns may exists for either structural of implementation cost reasons.
Systemic Inflammatory Response Syndrome as Predictor of Poor Outcome in Nontraumatic Subarachnoid Hemorrhage Patients

Objectives: Subarachnoid hemorrhage is a life-threatening disease associated with high mortality and morbidity. A substantial number of patients develop systemic inflammatory response syndrome. We aimed to identify risk factors for systemic inflammatory response syndrome development and to evaluate the role of systemic inflammatory response syndrome on patients’ outcome. Design: Retrospective observational cohort study of prospectively collected data. Setting: Neurocritical care unit at a tertiary academic medical center. Patients: Two-hundred and ninety-seven consecutive nontraumatic subarachnoid hemorrhage patients admitted to the neurologic ICU between 2010 and 2017. Interventions: Systemic inflammatory response syndrome was diagnosed based on greater than or equal to two criteria (hypo-/hyperthermia, tachypnea, leukopenia/leukocytosis, tachycardia) and defined as early (⩽ 3 d) and delayed (days 6–10) systemic inflammatory response syndrome burden (systemic inflammatory response syndrome positive days within the first 10 d). Using multivariate analysis, risk factors for the development of early and delayed systemic inflammatory response syndrome and the relationship of systemic inflammatory response syndrome with poor 3-month functional outcome (modified Rankin Scale score ≥ 3) were analyzed. Measurements and Main Results: Seventy-eight percent of subarachnoid hemorrhage patients had early systemic inflammatory response syndrome, and 69% developed delayed systemic inflammatory response syndrome. Median systemic inflammatory response syndrome burden was 60% (interquartile range, 10–90%). Risk factors for early systemic inflammatory response syndrome were higher admission Hunt and Hess grade (odds ratio, 1.75; 95% CI, 1.09–2.83; p = 0.02), aneurysm clipping (odds ratio, 4.84; 95% CI, 1.02–23.05; p = 0.048), and higher modified Fisher Scale score (odds ratio, 1.88; 95% CI, 1.25–2.89; p = 0.003). Hunt and Hess grade and pneumonia were independently associated with delayed systemic inflammatory response syndrome development. Systemic inflammatory response syndrome burden (area under the curve, 0.84; 95% CI, 0.79–0.88) had a higher predictive value for 3-month poor outcome compared with early systemic inflammatory response syndrome (area under the curve, 0.76; 95% CI, 0.70–0.81; p < 0.001). Conclusions: Systemic inflammatory response syndrome is common after subarachnoid hemorrhage and independently contributes to poor functional outcome. Systemic inflammatory response syndrome burden more accurately predicts poor outcome than early systemic inflammatory response syndrome.
Context‐dependent regulation of receptor tyrosine kinases: Insights from systems biology approaches

Receptor tyrosine kinases (RTKs) are cell membrane proteins that provide cells with the ability to sense proteins in their environments. Many RTKs are essential to development and organ growth. Derangement of RTKs—by mutation or by overexpression—is central to several developmental and adult disorders including cancer, short stature, and vascular pathologies. The mechanism of action of RTKs is complex and is regulated by contextual components, including the existence of multiple competing ligands and receptors in many families, the intracellular location of the RTK, the dynamic and cell‐specific coexpression of other RTKs, and the commonality of downstream signaling pathways. This means that both the state of the cell and the microenvironment outside the cell play a role, which makes sense given the pivotal location of RTKs as the nexus linking the extracellular milieu to intracellular signaling and modification of cell behavior. In this review, we describe these different contextual components through the lens of systems biology, in which both computational modeling and experimental “omics” approaches have been used to better understand RTK networks. The complexity of these networks is such that using these systems biology approaches is necessary to get a handle on the mechanisms of pathology and the design of therapeutics targeting RTKs. In particular, we describe in detail three concrete examples (involving ErbB3, VEGFR2, and AXL) that illustrate how systems approaches can reveal key mechanistic and therapeutic insights.
Selection of Waste Lubricant Oil Regenerative Technology Using Entropy-Weighted Risk-Based Fuzzy Axiomatic Design Approach

In the paper we study the possibility of constructing decision graphs with the help of several meta agents. Decision graphs are an extension of the well known decision trees and introduce the possibility of program nodes and cycles in a classification model. A two-leveled evolutionary algorithm for the induction of decision graphs is presented and the principle of classification based on the decision graphs is described. Several agents are used to construct the decision graphs; they are constructed and evolved with the help of automatic programming and evaluated with a universal complexity measure. The developed model is applied to a medical dataset for the classification of patients with mitral valve prolapse syndrome.
Embryonic macrophages and microglia ablation alter the development of dorsal root ganglion sensory neurons in mouse embryos

Microglia are known to regulate several aspects of the development of the central nervous system. When microglia colonize the spinal cord, from E11.5 in the mouse embryo, they interact with growing central axons of dorsal root ganglion sensory neurons (SNs), which suggests that they may have some functions in SN development. To address this issue, we analyzed the effects of embryonic macrophage ablation on the early development of SNs using mouse embryo lacking embryonic macrophages (PU.1 knock‐out mice) and immune cell ablation. We discovered that, in addition to microglia, embryonic macrophages contact tropomyosin receptor kinase (Trk) C+ SN, TrkB+ SN, and TrkA+ SN peripheral neurites from E11.5. Deprivation of immune cells resulted in an initial reduction of TrkC+ SN and TrkB+ SN populations at E11.5 that was unlikely to be related to an alteration in their developmental cell death (DCD), followed by a transitory increase in their number at E12.5. It also resulted in a reduction of TrkA+ SN number during the developmental period analyzed (E11.5–E15.5), although we did not observe any change in their DCD. Proliferation of cells negative for brain fatty acid‐binding protein (BFABP−), which likely correspond to neuronal progenitors, was increased at E11.5, while their proliferation was decreased at E12.5, which could partly explain the alterations of SN subtype production observed from E11.5. In addition, we observed alterations in the proliferation of glial cell progenitors (BFABP+ cells) in the absence of embryonic macrophages. Our data indicate that embryonic macrophages and microglia ablation alter the development of SNs.
Effects of Online Parental Remediation in Alternative School Mathematics

The focus of this non-experimental correlation designed study was to investigate the relationships between the use of teacher-made instructional videos for online parental remediation in algebraic content and parental self-efficacy and students’ mathematical achievement in alternative education. The population of this study consisted of a group of 28 parents and their children who were students enrolled in an alternative school in the Southeastern United States. Multiple forms of data were analyzed that included information gained from surveys, website analytics, student assessments and parent interviews. The analyses of the data found that most parents did watch the videos and the intervention did support parental selfefficacy in mathematics. However, there was no strong correlation between the use of the videos and student achievement. The preand post-assessments of the control and experimental phases were not significantly different. Therefore, more research is needed on web-based parental remediation using teacher-made instructional videos and its relationship with student achievement. ONLINE PARENT REMEDIATION IN ALTERNATIVE EDUCATION 5
Suppressor effects in associations between patient attachment to therapist and psychotherapy outcome

Abstract Objective Several studies propose that patient attachment to therapist is associated with therapy outcome. However, the magnitude of the effect is diverse, which might be explicable by suppressor effects and the new concept of pseudo‐security. Method Associations between patient attachment to therapist (client‐attachment‐to‐therapist‐scale [CATS]) and psychotherapy outcome (“global severity index” of the Symptom Check List) were evaluated in N = 368 patients. Multilevel models were performed. Results When tested in separate models, secure attachment to therapist was associated with a more favourable outcome (p < 0.05), whereas avoidant and preoccupied attachment to therapist were correlated with a less favourable outcome (both p < 0.05). Avoidant but not preoccupied attachment to therapist suppressed the association between secure attachment to therapist and the outcome. When controlling for the other two CATS scales, avoidant as well as preoccupied attachment to therapist remained associated with a less favourable outcome (p < 0.05). Conclusion Avoidant attachment to therapist suppresses the association between secure attachment to therapist and psychotherapy outcome. Pseudo‐security has to be taken into consideration in self‐report data on patient attachment to therapist.
S-acylation regulates the trafficking and stability of the unconventional Q-SNARE STX19

ABSTRACT STX19 is an unusual Qa-SNARE as it lacks a C-terminal transmembrane domain. However, it is efficiently targeted to post-Golgi membranes. Here, we set out to determine the intracellular localisation of endogenous STX19 and elucidate the mechanism by which it is targeted to membranes. We have found that a pool of STX19 is localised to tubular recycling endosomes where it colocalises with MICAL-L1 and Rab8 (which has Rab8a and Rab8b forms). Using a combination of genetic, biochemical and cell-based approaches, we have identified that STX19 is S-acylated at its C-terminus and is a substrate for several Golgi-localised S-acyltransferases, suggesting that STX19 is initially S-acylated at the Golgi before trafficking to the plasma membrane and endosomes. Surprisingly, we have found that S-acylation is a key determinant in targeting STX19 to tubular recycling endosomes, suggesting that S-acylation may play a general role in directing proteins to this compartment. In addition, S-acylation also protects STX19 from proteosomal degradation, indicating that S-acylation regulates the function of STX19 at multiple levels. This article has an associated First Person interview with the first author of the paper. Highlighted Article: The Q-SNARE STX19 is S-acylated by Golgi-localised S-acyltransferases, and this lipidation targets the protein to MICAL-L1-positive tubular recycling endosomes and also protects it from proteasomal degradation.
Harness Suspension Stress: Physiological and Safety Assessment

&NA; Hanging motionless in a full body harness may result in unwanted events, such as acute hypotension and syncope, which has been termed harness suspension stress (HSS). The etiology of HSS has not been explored, and it is unknown if the type of harness influences the HSS response. Objectives: Evaluate hemodynamics, subjective discomfort, and biological markers of muscle damage during 30-minutes suspension; and evaluate differences between harness attachment (frontal or dorsal). Methods: Heart rate, blood pressure, biological markers of muscle damage, and subjective discomfort were measured. Results: Trial time was shorter in the dorsal versus frontal point of attachment. Hemodynamic shift resulted in the dorsal trial which indicated possible perfusion abnormalities. Conclusions: Hemodynamic adjustments contributed to early termination observed in the dorsal trial. A frontal point of attachment may be more suitable for extended harness exposure.
Optimal protection against Salmonella infection requires noncirculating memory

Significance Effective vaccination against Salmonella infection requires the generation of memory T cells that can be reactivated upon exposure to bacteria in a natural setting. It is unclear whether immunity requires memory T cells that continuously patrol blood, lymphatics, and tissues, whether noncirculating T cells are important, or both. We demonstrate the generation of circulating and noncirculating memory pools after immunization. However, naive mice that previously shared a blood supply with vaccinated partners received recirculating memory T cells, but did not have T cell memory with characteristics of tissue residence, resulting in a failure to acquire robust protective immunity. Thus, noncirculating tissue-resident memory T cells are vital for effective protection against Salmonella. While CD4 Th1 cells are required for resistance to intramacrophage infections, adoptive transfer of Th1 cells is insufficient to protect against Salmonella infection. Using an epitope-tagged vaccine strain of Salmonella, we found that effective protection correlated with expanded Salmonella-specific memory CD4 T cells in circulation and nonlymphoid tissues. However, naive mice that previously shared a blood supply with vaccinated partners lacked T cell memory with characteristics of tissue residence and did not acquire robust protective immunity. Using a YFP–IFN-γ reporter system, we identified Th1 cells in the liver of immunized mice that displayed markers of tissue residence, including P2X7, ARTC2, LFA-1, and CD101. Adoptive transfer of liver memory cells after ARTC2 blockade increased protection against highly virulent bacteria. Taken together, these data demonstrate that noncirculating memory Th1 cells are a vital component of immunity to Salmonella infection and should be the focus of vaccine strategies.
Development of HCV Therapeutic Vaccines Using Hp91 Peptide and Small Heat Shock Protein 20 as an Adjuvant.

BACKGROUND Hepatitis C Virus (HCV) is a major cause of chronic liver disease in the world. Many studies showed that T-cell responses to HCV Nonstructural Protein 3 (NS3) play an important role in clearing acute HCV infections, thus NS3 can be considered as a suitable candidate antigen for development of a HCV therapeutic vaccine. OBJECTIVE We used Hp91 peptide and small heat shock protein 20 as an adjuvant for enhancement of NS3-specific humoral and cellular immunity in mice. METHOD In this study, various NS3 DNA and protein constructs were generated in eukaryotic and prokaryotic expression systems, and their potency in eliciting humoral and cellular immune responses was compared using small Heat shock protein 20 (Hsp20), the High Mobility Group Box 1 protein (HMGB1)-derived peptide (Hp91), and Freund's adjuvant in a BALB/c mouse model. RESULTS Our results indicated that both the Hsp20 conjugated with NS3 protein and Hp91 significantly enhanced the levels of IgG2a, IgG2b and IFN-γ directed toward Th1 responses compared to other groups. Moreover, the immunostimulatory properties of Hp91 were significantly higher than Hsp20 and Freund's adjuvant in various immunization strategies. Mice immunized by NS3 protein formulated with Freund's adjuvant, and also mixed with Hp91 peptide showed higher secretion of Granzyme B than other groups. CONCLUSION Hp91 peptide could develop NS3-specific B- and T-cell immune responses as a promising HCV therapeutic vaccine candidate in future.
Enantioselective, Catalytic Vicinal Difluorination of Alkenes.

The enantioselective, catalytic vicinal difluorination of alkenes is reported by II /IIII catalysis using a novel, C2 -symmetric resorcinol derivative. Catalyst turnover via in situ generation of an ArIIII F2 species is enabled by Selectfluor oxidation and addition of an inexpensive HF-amine complex. The HF:amine ratio employed in this process provides a handle for regioselective orthogonality as a function of Brønsted acidity. Selectivity reversal from the 1,1-difluorination pathway (geminal) to the desired 1,2-difluorination (vicinal) is disclosed (>20:1 in both directions). Validation with electron deficient styrenes facilitates generation of chiral bioisosteres of the venerable CF3 unit that is pervasive in drug discovery (20 examples, up to 94:06 e.r.). An achiral variant of the reaction is also presented using p-TolI (up to >95 % yield).
Hadoop‐based analytic framework for cyber forensics

With an exponential increase in the data size and complexity of various documents to be investigated, existing methods of network forensics are found not much efficient with respect to accuracy and detection ratio. The existing techniques for network forensic analysis exhibit inherent limitations while processing a huge volume, variety, and velocity of data. It makes network forensic a time‐consuming and resource‐consuming task. To balance time taken and output delivered, these existing techniques put a limit on the amount of data under analysis, which results in a polynomial time complexity of these solutions. So to mitigate these issues, in this paper, we propose an effective framework to overcome the limitation to handle large volume, variety, and velocity of data. An architectural setup that consists of MapReduce framework on top of Hadoop Distributed File System environment is proposed in this paper. The proposed framework demonstrates its capability to handle issues of storage and processing of big data using cloud computing. Also, in the proposed framework, supervised machine learning (random forest‐based decision tree) algorithm has been implemented to demonstrate better sensitivity. To train and validate the model, online available data set from CAIDA is taken and university network traffic samples, with increasing size, has been taken for experiment. Results thus obtained confirm the superiority of the proposed framework in network forensics, with an average accuracy of 99.34% (malicious and nonmalicious traffic).
Windthrows control biomass patterns and functional composition of Amazon forests

Amazon forests account for ~25% of global land biomass and tropical tree species. In these forests, windthrows (i.e., snapped and uprooted trees) are a major natural disturbance, but the rates and mechanisms of recovery are not known. To provide a predictive framework for understanding the effects of windthrows on forest structure and functional composition (DBH ≥10 cm), we quantified biomass recovery as a function of windthrow severity (i.e., fraction of windthrow tree mortality on Landsat pixels, ranging from 0%–70%) and time since disturbance for terra‐firme forests in the Central Amazon. Forest monitoring allowed insights into the processes and mechanisms driving the net biomass change (i.e., increment minus loss) and shifts in functional composition. Windthrown areas recovering for between 4–27 years had biomass stocks as low as 65.2–91.7 Mg/ha or 23%–38% of those in nearby undisturbed forests (~255.6 Mg/ha, all sites). Even low windthrow severities (4%–20% tree mortality) caused decadal changes in biomass stocks and structure. While rates of biomass increment in recovering vegetation were nearly double (6.3 ± 1.4 Mg ha−1 year−1) those of undisturbed forests (~3.7 Mg ha−1 year−1), biomass loss due to post‐windthrow mortality was high (up to −7.5 ± 8.7 Mg ha−1 year−1, 8.5 years since disturbance) and unpredictable. Consequently, recovery to 90% of “pre‐disturbance” biomass takes up to 40 years. Resprouting trees contributed little to biomass recovery. Instead, light‐demanding, low‐density genera (e.g., Cecropia, Inga, Miconia, Pourouma, Tachigali, and Tapirira) were favored, resulting in substantial post‐windthrow species turnover. Shifts in functional composition demonstrate that windthrows affect the resilience of live tree biomass by favoring soft‐wooded species with shorter life spans that are more vulnerable to future disturbances. As the time required for forests to recover biomass is likely similar to the recurrence interval of windthrows triggering succession, windthrows have the potential to control landscape biomass/carbon dynamics and functional composition in Amazon forests.
Optimised cost considering Huffman code for biological data compression

Classical Huffman code has been widely used to compress biological datasets. Though a considerable reduction of size of data can be obtained by classical Huffman code, a more efficient encoding is possible by treating binary bits differently considering requirement of transmission time, energy consumption, and similar. A number of techniques have already modified the Huffman code algorithm to obtain optimal prefix-codes for unequal letter costs in order to reduce overall transmission cost (time). In this paper, we propose a new approach to improve compression performance of one such extension, the cost considering approach (CCA), by applying a genetic algorithm for optimal allocation of the codewords to the symbols. The idea of the proposed approach is to sacrifice some cost to minimise the total number of bits, hence, the genetic algorithm works by giving penalty on the cost. The performance of the approach is evaluated by using it to compress some standard biological datasets. The experiments show that the proposed approach improves the compression performance of the CCA considerably without increasing the cost significantly.