Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of a Hypothesis to Speciation in Hominidae

I have previously hypothesized that biological species are not the result of gradual changes in the genome or morphology as suggested by Darwin, but rather the result of punctuated major pericentric or paracentric inversions or other rearrangements (e.g., chromosome fusions) that prevent reproductive compatibility with the parent group. Following the rearrangement, a new nascent species can be formed through inbreeding within two generations consistent with the views of Goldschmidt. Applying this hypothesis to speciation in Hominidae (the great apes) suggests that (i) orangutans are close to the common ancestor of Hominidae; (ii) humans are close to the common ancestor of Hominoids, which was adapted for efficient all-terrain locomotion; (iii) gorillas and chimpanzees have passed though more species as they have adapted to a very specialized ecological niche in the tropical forest, and (iv) speciation events in Homo facilitated evolution of the human brain.
Rank-Based Report Filtering Scheme (RRFS) for Verifying Phoney Reports in Wireless Sensor Networks

Wireless sensor networks (WSNs) are open to false data injection attack when they are deployed in hostile scenarios. Attackers can easily deceive the sink by compromising sensing nodes or by injecting phoney data into the network. Such attacks can deplete the energy resources of the network by providing wrong information which in turn can affect the proper network functioning or sometimes can shut the network from further functioning. The existing schemes that deal with this problem focus on only a few aspects of the false data injection attack. To resolve this problem, we propose a Rank-based Report Filtering Scheme (RRFS), a holistic and group verification scheme for the identification of compromised nodes and the filtering of false data injected into the network. The proposed scheme verifies report among clusters, en-routers, and sink. Hence, the RRFS, a holistic scheme that is composed of three-tier verifications, successfully rejects the false data before the attackers falsify the whole environment, and this makes the system unique. Reliability Index (RI) is calculated by the nodes for fellow cluster members, and the cluster head (CH) provides the score for a node based on its RI. This, in turn, strengthens the scheme by assisting the en-routers to detect the compromised nodes. The RRFS scheme has been verified and validated by extensive simulation and meticulous performance evaluation of filtering efficiency and energy consumption against various schemes. The scheme gives high filtering efficiency against the multiple compromised nodes and also improves the network’s lifespan. The sustainability of RRFS against numerous attacks that are launched in the sensor environment is thoroughly investigated.
Automatic Repair of Semantic Defects Using Restraint Mechanisms

Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair approaches have difficulty generating correct patches efficiently. This paper proposes an automatic method for repairing semantic defects in Java programs based on restricted sets which refer to the interval domains of related variables that can trigger program semantic defects. Our work introduces a repair mechanism symmetrically combining defect patterns and repair templates. First, the program semantic defects are summarized into defect patterns according to their grammar and semantic features. A repair template for each type of defect pattern is predefined based on a restricted-set. Then, for each specific defect, a patch statement is automatically synthesized according to the repair template, and the detected defect information is reported by the static detection tool (DTSJava). Next, the patch location is determined by the def-use chain of defect-related variables. Finally, we evaluate the patches generated by our method using DTSJava. We implemented the method in the defect automatic repair prototype tool DTSFix to verify the effect of repairing the semantic defects detected by DTSJava in 6 Java open-source projects. The experimental results showed that 109 of 129 program semantic defects were repaired.
Research Perspectives: Design Theory Indeterminacy: What Is it, How Can it Be Reduced, and Why Did the Polar Bear Drown?

Design science research strives to be practical and relevant. Yet few researchers have examined the extent to which practitioners can meaningfully utilize theoretical knowledge produced by design science research in solving concrete real-world problems. Are design theories developed by scientists readily amenable to application by practitioners? Does the application of a theory by practitioners always lead to the outcomes predicted (by the scientists)? We examine a particularly difficult challenge—ensuring that the development and deployment of an IT artifact by practitioners based on a design theory result in appropriate changes in the environment predicted by the design theory. As we show in our paper, a gulf exists between theoretical propositions and concrete issues faced in practice—a challenge we refer to as design theory indeterminacy . Design theory indeterminacy might result in considerable ambiguity when implementing a design theory in practice and reduce the potential relevance of information systems knowledge. In this paper, we articulate the problem of design theory indeterminacy, examine factors that contribute to it, and suggest fruitful directions for future research to help reduce it.
Chemistry of pyrrocorphins: synthesis of isobacteriochlorins and pyrrocorphins bearing a methyl group at the meso position between rings A and D

A sigmatropic methyl shift from the angular position C-1 in ring A to the meso position C-20 between rings A and D constitutes the crucial step in syntheses leading to a 20-methyl-isobacteriochlorin and to 20-methyl-pyrrocorphins which served as substrates in the investigation presented in the accompanying communication.
Symmetrical and Asymmetrical Rectifications Employed for Deeper Ocean Extrapolations of In Situ CTD Data and Subsequent Sound Speed Profiles

The multinational Argo program, which was initiated in 1999, has completed its global requirement of 3000 floats deployed by 2007. This program has revolutionized ocean observations with the provision of varying data in the upper half of the ocean. However, various studies have reiterated the requirement for deep ocean coverage, since the ocean below 2000 meters (m) is warming. In this regard, full-depth studies are mandatory in order to estimate the rising sea level due to thermal expansion and analyze critical parameters of deep ocean circulation sub 2000 m; further, data below 2000 m are mandatory for multifarious model simulations. As a landmark initiative, in mid-2015, the “Deep Argo Implementation Workshop” was held in Hobart. An array comprising 1228 floats was suggested by G. C. Johnson, rendering coverage of 5° latitude × 5° longitude × 15-day cycles. This was conclusively agreed to be an affordable solution for varying scientific needs for assessing data in abyssal oceans. Thence, Deep New profilINg float of JApan (NINJA) and Deep Arvor floats were developed by Japan and France, respectively, to cover depths of 0–4000 m. Similarly, Deep Autonomous Profiling Explorer (APEX) and Deep Sounding Oceanographic Lagrangian Observer (SOLO) by the United States were designed to cover 0–6000 m. The data offered by this underdeveloped deep pilot array are scarce on both temporal and spatial scales. This particular study offers an ingenious and novel approach to extrapolating conductivity–temperature–depth (CTD) profiles, as well as sound speed profiles (SSPs), in abyssal oceans below 2000 m. The primitive results of this method exhibited certain discrepancies which were subsequently rectified by modifying the aforementioned method both symmetrically and asymmetrically in an innovative way. The final outcomes of this method are almost identical to the in situ values obtained from Deep Argo floats, and in this way, offer a way to compute deep ocean calculations both spatially and temporally since Deep Argo floats are aimed at relatively sparse deployments and require a longer duration to provide data (5° latitude × 5° longitude × 15-day cycles) as compared to Core Argo data (3° latitude × 3° longitude × 10-day cycles). The SSP computations were conducted by employing multiple equations such as Chen and Millero, Del Grosso, and UNESCO (United Nations Educational, Scientific, and Cultural Organization) algorithms. The study concludes by offering transmission loss rectifications by employing the aforementioned method as a future course of action.
INTERFERTILITY BETWEEN TWO SYMPATRIC FISHES, NOTROPIS LUTRENSIS AND NOTROPIS VENUSTUS

The redhorse shiner, N otropis lutrcnsis (Baird and Girard) and spottail shiner. N otropis uenustus (Girard) are among the most abundant fishes in southwestern North America. They are considered to belong to separate subgenera, Moniana and Erogala respectively, by Hubbs (1955). The close relationship between the subgenera is shown by their adjacent position among the twelve subgenera of N otropis recognized by that author. The two species do not occupy entirely identical geographic ranges. N otropis uenustus is the more eastern in distribution. Populations are found from the Devil's River and the adjacent section of the Rio Grande, Texas, to the coastal streams emptying into the Gulf of Mexico near Houston. It is apparently absent from the Tamaulipan Biotic Province of Blair (1950). From Houston the range extends eastward in the coastal streams to the Apalachicola River in Georgia and Florida. Spottail shiners are found northward in the Mississippi River Valley to southern Illinois. The eastern and northern limits of the geographic range of the spottail shiner is taken from that given by Bailey, Winn, and Smith (1954). We have noted no pronounced morphologic variations of spottail shiners in those Texas populations we have studied. The northern limit of the range of Notropis Iutrensis extends from southeastern Wyoming, through Nebraska, southeastern South Dakota, western and southern Iowa, to central Illinois. The eastern limit extends from central Illinois southward in small numbers along the Mississippi River to southeastern Mississippi, and thence in fresh and even slightly brackish water along the western Gulf of Mexico to northern Mexico. It has not been recorded from the Ozark Highlands. Small populations are found in sandy streams along the Arkansas River as it passes through the Ozarks. On the west the redhorse shiner ranges from southeastern Wyoming through central Colorado and central New Mexico to Mexico. The southern extent of the range, in northern Mexico, is incompletely worked out. The problem there is complicated by the presence of many isolated populations that may be conspecific with N. lutrensis. The variability shown by the isolated populations in Mexico is continued over the adjacent semiisolated drainages in Texas and New Mexico. All of the individuals of the
The study of β-fibrinogen gene-455G/A、-148C/T polymorphisms in patients with cerebral infarction

Objective To explore the relationship between β-fibrinogen gene-455G/A、-148C/T polymorphisms and plasma fibrinogen level and to determine the influence of the mutation on cerebral infarction.Methods The β-Fg gene-455G/A、-148C/T of 90 patients with CI and 102 health individul controls were analyzed by restriction fragment length polymorphism(RFLP). Plasma fibrinogen levels were determined by clauss method. Results The plasma fibrinogen level of CI patients were significantly higher than that of health controls,3.55± 0.94 versus 2.67±0.78(P0.01). The frequencies of-455A、-148T allele were 0.186 and 0.206 in health controls,0.289 and 0.306 in CI patients.There was close linkage between-455G and-148C or between-455A and-148T,the correspondence was over 96%. In both control group and CI group,the plasma fibrinogen levels with-455A allele were higher than that of without-455A allele,3.44±0.67 versus 2.32±0.77(P0.01)and 3.80± 0.64 versus 3.31±0.97(P0.05) respectively;and the plasma fibrinogen levels with -148T allele were higher than that of without-148T allele,3.29±0.66 versus 2.33±0.77(P0.01)and 3.77±0.65 versus 3.31±0.97(P 0.01)respectively.Conclusions There is strong linkage disequilibrium between the two polymorphism loci.The alleles of-455A and-148T are not associated with the susceptibility to cerebral infarction.The Fgβ-455G/A and-148C/T polymorphisms are correlated to the plasma fibrinogen level.
P02.03 Microwave ablation enhances tumor-specific immune response in patients with hepatocellular carcinoma

Thermal ablative therapies, such as microwave ablation (MWA) or radiofrequency ablation (RFA), are standard treatments for HCC. In addition to the local tumor destruction, abscopal effects (a reduction of a tumor mass in areas that were not included in the thermal ablation) could be observed. These systemic effects may be mediated by anti-tumor immune response, which has been described for RFA. MWA is rapidly replacing RFA, but systemic immunostimulatory effects of MWA treatment have been poorly studied.Patients receiving MWA for localized HCC were included in this study. Effects of MWA on peripheral blood mononuclear cells (PBMC) of HCC patients treated with MWA were analyzed by multicolor flow cytometry. Tumor-specific immune responses against 7 shared tumor antigens were analyzed using peptide pools in 3-color Fluorospot assays (Interferon-y/Interleukin-5/Interleukin-10). The impact of type, density and localization of tumor-infiltrating lymphocytes was assessed by immunohistochemistry (IHC) of CD3, CD4, CD8, FoxP3, CD38 and CD20 and digital image analyses (Immunoscore) of tumor specimens in an additional cohort of patients who received combined surgical resection and thermal ablation.While comprehensive flow cytometric analyses in sequential samples (day 0, 7 and 90) of a prospective patient cohort (n=23) demonstrated only moderate effects of MWA on circulating immune cell subsets, Fluorospot analyses revealed de novo or enhanced tumor-specific immune responses in 30% of these patients. This anti-tumor immune response was related to tumor control. Interferon-y and Interleukin-5 T cell responses against cancer testis antigens were more frequent in patients with a long-time remission (>12 months) after MWA (7/16) compared to patients suffering from an early relapse (0/13 patients). Presence of tumor-specific T cell response (Interferon-y and/or Interleukin-5) was associated to longer progression-free survival (15.0 vs. 10.0 months). Immunohistochemical analyses of resected tumor samples revealed that a high T cell infiltration in a second tumor lesion at the time of thermal ablation was associated with superior disease-free survival (37.4 vs. 13.1 months). Our data demonstrates remarkable immune-related effects of MWA in HCC patients. This study and provides additional evidence for a combination of thermal ablation and immunotherapy in this challenging disease. ‘Koeln Fortune’ and ‘CAP-CMMC’ local research grant (to P.G. and H.A.S.) supported our research.E. Staib: None. K. Leuchte: None. M. Thelen: None. P. Gödel: None. A. Lechner: None. P. Zentis: None. M. Garcia-Marquez: None. D. Waldschmidt: None. R.R. Datta: None. R. Wahba: None. C. Wybranski: None. T. Zander: None. A. Quaas: None. U. Drebber: None. D.L. Stippel: None. C. Bruns: None. K. Wennhold: None. M. von Bergwelt-Baildon: None. H.A. Schlösser: None.
Components in Antineoplastic Actinomycete Strain (N2010-37) of Bottom Mud in Mangrove

Objective To study the antitumor components from an actinomycete strain(N2010-37) of bottom mud in Zhanjiang Mangrove,South China Sea.Methods The components were isolated and purified by chromatographic techniques and recrystallization,and the structures were identified by spectral methods together with physicochemical analyses.The antitumor effects of these components were tested in vitro by MTT method.Results Three compounds were identified including two anthrones and one novel lactone.They are(3S,4R,7R,8R,9S)-3,8-dihydroxy-4,7,9-trimethyl-2,6-cyclononanediolacetone(1) ,2-hydroxy-1-methoxy-3-methylanthraquinone(2) ,and 1,6,8-thihydroxy-3-methylanthraquinone(3) . Conclusion Compound 1 is a new compound,and compounds 1 and 3 show the favorable cytotoxic activities against human chronic granulocytic leukemia cell line K562 strain by MTT method in vitro.
Impact of Spreading Factor on LoRaWAN Propagation in a Metropolitan Environment

A practical investigation of LoRaWAN’s (longrange wide area network) propagation in an urban and semiurban environment is demonstrated and analyzed in this article. Measured data is analyzed to understand the attributes of LoRa, including: effective propagation range, chirp spread spectrum (CSS) modulation and spreading factor (SF). This analysis provides a better understanding of these attributes. In addition, a comparison was made with propagation models to benchmark and observe the impact of clutter, environment and structures in practice. For this purpose, log-distance, COST.W. I models were used. An average increase of 5.5 dB was observed on the received signal strength due to a higher spreading factor. This translated into a range extension of approximately 500 m in practice. Outcome of this study provides an insight of LoRa’s propagation in metropolitan environments, and facilitates the network planning in similar scenarios.
Diagnostics of an Aeroengine Automatic Control System under Conditions of Insufficient Apriorial Information

The optimality of an aero engine automatic control system (ACS) depends on the reliability of information about the current characteristics of the control object. It is proposed to increase the ACS robustness by creating an algorithmic information redundancy based on a built-in onboard mathematical model of the engine with the parametric gas- path diagnostics function. The method of the general matrix of influence coefficients (diagnostic matrix) is used. The study deals with the problem of incorrect conditionality of diagnostic matrices. The uncertainty of diagnostic systems is caused by the "noise" of the model. Two methods of reducing the model "stochastic noise" are considered. The first method is based on reducing undefined and ill-defined systems of equations to certain ones by selecting optimal sets of non-measurable parameters. The second approach is based on expanding the engine state space using numerical Monte Carlo methods. Based on the diagnostic results, the model is corrected in real time. "Random noise" in measured channels is compensated based on the Kalman filter. A semi-natural experiment on an industrial regulator with various engine power settings gave unsatisfactory results using the first method. The best accuracy is achieved when evaluating the high-pressure rotor speed, the worst-when evaluating the pressure behind the compressor. The second approach, based on statistical modeling, increases the identification accuracy by 1.5-4.7 times. Kalman filtering of input signals reduces the standard deviation of the obtained unmeasured parameters by 1.3-2.5 times.
Automated Object Recognition System based on Convolutional Autoencoder

This paper describes the model, implementation and the experimental verification of an aerial image processing and recognition technology based on artificial neural networks, specifically, convolutional autoencoders and classifying perceptrons. An originally developed model that includes autoencoder preprocessing for compression and extraction of informative features was applied to the task of pattern recognition, namely, locating and identifying the objects of certain higher-level classes of interest in the images produced by aerial photography. Classification efficiency of the method was measured and compared with other common methods of classification, the advantages and shortcomings of the proposed approach analyzed and potential applications in real-time remote object recognition systems, as well as in automating the generation of training data for image recognition systems discussed.
Histological Interactions of Paecilomyces lilacinus with Root-knot Nematode Meloidogyne incognita and Their Effect on the Growth of Tomato

A glasshouse experiment was conducted to assess the effect of Paecilomyces lilacinus on the reproduction of root-knot nematode and on the growth of tomato. Data on the plant growth, leaf area, yield characteristics, root-knot and egg-mass indices were recorded. The histological interactions studies were also carried out to check the parasitism of root-knot nematode eggs by P. lilacinus. The results indicated that the use of P. lilacinus one week before nematode inoculation caused an increase in growth and yield characteristics of tomato, and also reduced the reproduction of nematode as compared to other treatments. The results of histological studies indicated that P. lilacinus parasitized on the M. incognita eggs through the formation of fungal hyphae and conidiophores and caused the disintegration of the eggshells, egg masses and juveniles of M. incognita.
Online Knowledge Acquisition with the Selective Inherited Model

Continual learning, which updates machine learning models according to streaming data, is increasingly needed in the dynamic systems. Such a scenario requires both the preservation of previous knowledge, as well as the adaptation to new observations, with high computational and memory efficiency at the edge. Previous approaches attempt to learn the knowledge class by class from scratch, using either regularization based or memory replay-based methods. However, they still suffer from severe accuracy drop, a.k. a catastrophic forgetting, during this incremental process. Moreover, as the entire model is involved in each updating, their computation cost is too expensive for edge computing. In this work, we propose a novel brain- inspired paradigm named acquisitive learning (AL). Different from previous approaches that focus only on model adaptation, AL emphasizes the importance of both knowledge inheritance and acquisition: the model is first pre-trained and selected in the cloud (the selective inherited model) and then adapted to new knowledge (the acquisition). The quality of the inherited model is monitored by the landscape of the loss function, while the acquisition is realized by segmented training. The combination of both steps reduces accuracy drop by >10× on the CIFAR- 100 dataset. Furthermore, AL benefits edge computing with 5× reduction in latency per training image on FPGA prototype and 150× reduction in training FLOPs.