Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonal Changes in Hypoosmoregulatory Ability of Biwa Salmon Oncorhynchus rhodurus and Amago Salmon O. rhodurus*1

Seasonal changes in hypoosmoregulatory ability of hatchery-reared biwa salmon Oncorhynchus rhodurus and amago salmon O. rhodurus were examined by following changes in plasma Na+ con centration after transfer to 70% seawater. The landlocked biwa salmon lose parr marks and become silvery bodied (smolt) underyearling during early summer. They showed the maximum hypoosmoregulatory ability from underyearling May to July, when they transformed from parr to smolt and migrated to the lake. However, the smolt did not show increased seawater adaptability as compared with parr in underyearling May, and the ability decreased markedly in autumn and winter. There was no essential difference in seawater adaptability between smolt and dark parr or yearling parr. On the other hand, amago salmon, which smoltify and go down stream to the sea in late autumn and early winter, showed better seawater adaptability than biwa salmon through out all developmental stages examined. Especially, the smolts during the period from November to January showed good osmoregulatory ability. The poor hypoosmoregulatory ability of biwa salmon as compared with amago salmon may be related to their lacustrine nature and a long period passed since this species was landlocked in Lake Biwa.
A Large Scale Study and Classification of VirusTotal Reports on Phishing and Malware URLs

VirusTotal (VT) provides aggregated threat intelligence on various entities including URLs, IP addresses, and binaries. It is widely used by researchers and practitioners to collect ground truth and evaluate the maliciousness of entities. In this work, we provide a comprehensive analysis of VT URL scanning reports containing the results of 95 scanners for 1.577 Billion URLs over two years. Individual VT scanners are known to be noisy in terms of their detection and attack type classification. To obtain high quality ground truth of URLs and actively take proper actions to mitigate different types of attacks, there are two challenges: (1) how to decide whether a given URL is malicious given noisy reports and (2) how to determine attack types (e.g., phishing or malware hosting) that the URL is involved in, given conflicting attack labels from different scanners. In this work, we provide a systematic comparative study on the behavior of VT scanners for different attack types of URLs. A common practice to decide the maliciousness is to use a cut-off threshold of scanners that report the URL as malicious. However, in this work, we show that using a fixed threshold is suboptimal, due to several reasons: (1) correlations between scanners; (2) lead/lag behavior; (3) the specialty of scanners; (4) the quality and reliability of scanners. A common practice to determine an attack type is to use majority voting. However, we show that majority voting could not accurately classify the attack type of a URL due to the bias from correlated scanners. Instead, we propose a machine learning-based approach to assign an attack type to URLs given the VT reports.
Use of Fine Aggregate Matrix Experimental Data in Improving Reliability of Fatigue Life Prediction of Asphalt Concrete: Sensitivity of This Approach to Variation in Input Parameters

Asphalt concrete (AC) material performance has been assessed by numerous mechanistic models over the years. Often these models are purported to enable more accurate prediction of the pavement service life than existing empirical models. Most of these models use fundamental material properties, which are obtained by performing experiments on the materials, as input variables. However, by introducing more variables, these models create the potential for greater uncertainty because the variables have inherent variability. Variations observed in these input parameters affect the reliability of any resulting performance predictions. In an effort to improve the reliability of fatigue life predictions, experimental data from the fine aggregate matrix (FAM) phase was used in this study for predicting fatigue life. From the comparative assessment, it was observed that the reliability of fatigue life predictions was improved by more than 50% when data from the FAM phase rather than AC data were used. An upscaling procedure was used in predicting the AC material fundamental properties and then in performing a reliability analysis with the predicted data. More reliable fatigue prediction results were also observed when the AC predicted data were used; however, this improvement was not as good as that in the FAM phase. A parametric sensitivity analysis was performed to determine whether variation in any one parameter resulted in a greater impact on the resultant reliability than did variation of other parameters. From the analysis, it was observed that the variation of the modulus parameter affected the reliability predictions more than did the variation of the other input parameters considered in this study, regardless of the model failure criteria used.
Open quantum system approach for heavy quark thermalization

We treat heavy quark as an open quantum system in the hot medium, and rederive the Stochastic Schr"odinger Equation (SSE) from the full Schr"odinger equation for both heavy quarks and the medium. We apply the SSE to the dynamical evolutions of heavy quarks (as a system) in the static hot medium (as an environment). Heavy quarks interact with the medium via random scatterings, which exchange the momentum and phase factor randomly between two wave functions of the system and the environment. The exchange of momentum and phase factor results in the transition between different eigenstates of the system. These are included via an external stochastic potential in the Hamiltonian of SSE. Stochastic wave functions of heavy quarks are evolved with the stochastic external potential. The mean wave functions and the corresponding momentum distributions of heavy quarks are obtained after the ensemble average over a large set of stochastic wave functions. We present the thermalization of heavy quarks in the static medium with different coupling strength.
Semi-supervised Drifted Stream Learning with Short Lookback

In many scenarios, 1) data streams are generated in real time; 2) labeled data are expensive and only limited labels are available in the beginning; 3) real-world data is not always i.i. d. and data drift over time gradually; 4) the storage of historical streams is limited. This learning setting limits the applicability and availability of many Machine Learning (ML) algorithms. We generalize the learning task under such setting as a semi-supervised drifted stream learning with short lookback problem (SDSL). SDSL imposes two under-addressed challenges on existing methods in semi-supervised learning and continuous learning: 1) robust pseudo-labeling under gradual shifts and 2) anti-forgetting adaptation with short lookback. To tackle these challenges, we propose a principled and generic generation-replay framework to solve SDSL. To achieve robust pseudo-labeling, we develop a novel pseudo-label classification model to leverage supervised knowledge of previously labeled data, unsupervised knowledge of new data, and, structure knowledge of invariant label semantics. To achieve adaptive anti-forgetting model replay, we propose to view the anti-forgetting adaptation task as a flat region search problem. We propose a novel minimax game-based replay objective function to solve the flat region search problem and develop an effective optimization solver. Experimental results demonstrate the effectiveness of the proposed method.
Continual Learning for Visual Search with Backward Consistent Feature Embedding

In visual search, the gallery set could be incrementally growing and added to the database in practice. However, existing methods rely on the model trained on the entire dataset, ignoring the continual updating of the model. Besides, as the model updates, the new model must re-extract features for the entire gallery set to maintain compatible feature space, imposing a high computational cost for a large gallery set. To address the issues of long-term visual search, we introduce a continual learning (CL) approach that can handle the incrementally growing gallery set with backward embedding consistency. We enforce the losses of inter-session data coherence, neighbor-session model coherence, and intra-session discrimination to conduct a continual learner. In addition to the disjoint setup, our CL solution also tackles the situation of increasingly adding new classes for the blurry boundary without assuming all categories known in the beginning and during model update. To our knowledge, this is the first CL method both tackling the issue of backward-consistent feature embedding and allowing novel classes to occur in the new sessions. Extensive experiments on various benchmarks show the efficacy of our approach under a wide range of setups 11Code: https://github.com/ivclab/CVS.
Bags-of-Features for fish school cluster characterization in pelagic ecosystems: application to the discrimination of juvenile and adult anchovy clusters off Peru

Whereas fisheries characterization and recognition of individual fish schools, here we addressed the characterization and discrimination of fish school clusters. The proposed scheme relied on 35 the application of the Bags-of-Features (BoF) approach to acoustic echograms. This approach is widely exploited for pattern recognition issues and naturally applies here, considering fish schools as the relevant elementary objects. It relies on the extraction and categorization of fish schools in fisheries acoustic data. Echogram descriptors were computed per unit echogram length as the numbers of schools, in different school 40 categories. We applied this approach to the discrimination of juvenile and adult anchovy ( Engraulis ringens ) off Peru. Whereas the discrimination of individual schools is low (below 70%), the proposed BoF scheme achieved between 89% and 92% of correct classification of juvenile and adult echograms for different survey datasets and significantly outperformed classical school-based echogram characteristics (about 10% of improvement 45 of the correct classification rate). We further illustrate the potential of the proposed scheme for the estimation of the spatial distribution of juvenile and adult anchovy populations.
Inducible Expression of I k B a Repressor Mutants Interferes with NF- k B Activity and HIV-1 Replication in Jurkat T Cells*

, Human immunodeficiency virus (HIV-1) utilizes the NF- k B/Rel proteins to regulate transcription through NF- k B binding sites in the HIV-1 long terminal repeat (LTR). Normally, NF- k B is retained in the cytoplasm by inhibitory I k B proteins; after stimulation by multiple activators including viruses, I k B a is phosphorylated and degraded, resulting in NF- k B release. In the present study, we examined the effect of tetracycline-inducible expression of transdominant repressors of I k B a (TD-I k B a ) on HIV-1 multiplication using stably selected Jurkat T cells. TD-I k B a was inducibly expressed as early as 3 h after doxycycline addition and dramatically reduced both NF- k B DNA binding activity and LTR-directed gene activity. Interestingly, induced TD-I k B a expression also decreased endogenous I k B a expression to undetectable levels by 24 h after induction, demonstrating that TD-I k B a repressed endogenous NF- k B-dependent gene transcription. TD-I k B a expression also sensitized Jurkat cells to tumor necrosis factor-induced apoptosis. De novo HIV-1 infection of Jurkat cells was dramatically altered by TD-I k B a induction, resulting in inhibition of HIV-1 multiplication, as measured by p24 antigen, reverse
Dopamine/Serotonin interactions in reward-related behavior: Focus on the Iowa Gambling Task

low 5-HT levels may potentiate tonic and phasic dopamine release via 5-HT 1A and 5-HT 2A receptors. When dopamine activity diminishes, the activation of the mPFC diminishes, resulting in increased activity of the dorsal raphe and elevated 5-HT levels. The glutamatergic input to the VTA is inhibited directly by 5-HT 1A receptors and indirectly via 5-HT 2C receptors. In addition, indirect tonic inhibition by 5-HT 2C receptors in the VTA and mPFC and local facilitation of dopamine release by 5-HT 3 receptors is restored, ensuring static extracellular dopamine levels.
Image Modification using Text with GANs

: This paper works towards finding an effective solution for the task of image feature manipulation using natural language commands. The authors aim to modify the relevant features of an image using a natural language description of the target image, such that the irrelevant features are not modified. Majority of the research in this domain focuses on generating completely new images using natural language description, and the few methodologies which attempt manipulation of existing images super in a number of aspects such as modification of irrelevant features or the aesthetic quality of the generated image. The authors propose an architecture that combines the best components of existing techniques to create an effective system to solve the stated task. The proposed architecture generates images at a high resolution to maintain the aesthetic quality of the image and ensures that the irrelevant content of the original image is not affected. The authors present a qualitative and quantitative analysis of the system as compared to the existing baselines and demonstrate the system for a relevant application such as virtual trial of clothes.
Perspectives of Student Teacher Trainees’ Preparedness and Adoption on Integration of ICT in Public Teacher Training Colleges in Kenya

This study was concerned with perspectives of student teacher trainees’ preparedness and adoption on integration of ICTs in public teacher training colleges. Effective preparedness and adoption on integration of ICTs contributes greatly to the quality of education delivered in an instructional process. The rationale was conceptualized from the TPACK model that ICT use in the classroom is important for giving students opportunities to learn and apply the required 21st century skill, improves teaching and learning and important for teachers in performing their role as designers of pedagogical environments. The curriculum needs academic standards and the development of digital age skills for the 21st century learners to fit in the global job market. The literature review focused on the global overview on integration of ICT in education, status of integration of ICT in education in Africa, readiness in the integration of ICT in education in Kenya and challenges of integrating ICTs in the primary teacher curriculum. A descriptive survey research design was used in the study which was conducted in four (4) public primary teacher training colleges in Central region of Kenya. These provided an ideal population for the study. The target populations were second year student teacher trainees, College principals and Kenya Institute of Curriculum Development (KICD) e-learning Officers. The major research instruments were questionnaires for student teacher trainees, interview schedule for the principals and Kenya Institute of Curriculum Development e-learning developers, and observation schedule. The obtained data were analyzed systematically using descriptive statistics and presented with the help of frequency tables, figures and percentages. Findings of the study revealed that preparedness on integration of ICTs was at an infant stage. The study also revealed that the training was only offering pedagogy, content, knowledge but not the technology which make integration a reality in the classroom setting. There were inadequate infrastructure to enhance integration and student teacher trainees revealed lack policy that would help adoption on integration of ICTs in teaching learning process.
Epidemiologie and laboratory evaluation of homosexualmales f r om an area of low incidence f or acquired immunodeficiency syndrome (AIDS) 1

The northeastern Ohio area is currently one of low incidence for the acquired immunodeficiency syndrome (AIDS). From July through December 1983, 17 sexually active healthy homosexual males, 15 men with AIDS-related complex (ARC), and nine patients with AIDS were studied. In contrast to similar studies from high-incidence areas, healthy homosexuals did not have significant laboratory abnormalities, particularly of lymphocyte subpopula- tions, when compared with heterosexual controls. Epidemiologi-cally, there were no significant differences detected based on travel to epidemic areas or sexual practices between healthy homosexuals and patients with ARC. Furthermore, ARC patients were signifi- cantly less sexually active than healthy homosexual controls. It appears that subclinical immunodeficiency is uncommon in areas of low attack rates for AIDS and that studies from low-incidence areas may shed light on the early events in the spread of AIDS.
Determination of Optimum Ethanolic Extraction Conditions and Phenolic Profiles of Thyme, Mint, Uckun, Grape Seeds and Green Tea Waste Fiber

The objective of this study was to investigate the effect of different ethanol ratios in extraction solvent as well as the antioxidant properties of five plants. Thyme, mint, uckun, grape seeds and green tea waste fiber was analyzed to determine total phenolic content (TPC) and antioxidant activity by ABTS and DPPH radical scavenging activity assays. Individual phenolic components were analyzed with reverse phase high performance liquid chromatography (HPLC). TPC varied significantly from 2.00±0.27 to 172.68±0.19 mg GAE g -1 dw depending on the plant type and ethanol ratio of the solvent. The effect of ethanol ratio also varied among different plants. HPLC analysis was performed for the extracts showing highest antioxidant activity, and green tea waste fiber (699.89 mg 100 g -1 dw) had the highest concentration of phenolic compounds overall, while mint (173.67 mg 100 g -1 dw) had the lowest amount. Correlations between TPC and antioxidant activity was significant which is comparable to the previous report. evaluated by high performance liquid chromatography (HPLC) to identify and quantify the phenolic compounds of target plants. and AAE (R=0.789) and TE (R=0.790) determined by ABTS, and between TPC and AAE (R=0.577) and TE (R=0.582) determined by DPPH. The significant correlation suggest that antioxidant activity of the five plants tested is mainly due to their phenolic compounds. Our results are in accordance with previous work reporting varying correlations between TPC and antioxidant activity assays (ABTS and DPPH) (Piluzza and Bullitta, 2011; Alwazeer and Dham, 2018). mint and uckun, while 60% and 50% was optimum for green tea fiber waste and grape seeds, respectively. For DPPH assay, 70% ethanolic extraction showed highest antioxidant activity (lower IC50) for thyme and grape seeds, while 50% ethanol was optimum for mint and uckun, and pure ethanol extraction was best for green tea fiber waste. For two different antioxidant activity assays, different ethanol ratios were optimum for same plant due to the structural differences of DPPH and ABTS assays and differences in the compositions of phenolic compounds of the plants. Our results showed that the plants tested in this study have varying antioxidant activity and TPC. Extracting antioxidant compounds and showing optimum extraction conditions could provide further alternative application in food industry other than traditional utilization of these plants. Additionally, grape seeds and green tea waste fiber were found to have the highest level of TPC as well as highest antioxidant activity. Since grape seeds and green tea waste fiber are the waste products of food industry, they can be utilized in antioxidant compound production to be used in fortification of any product including functional food product development.
Protective Effects of Silymarin on Brain Injury in Rats

In this study, we evaluated the possible protective effects of silymarin on valproic acid-induced brain injury by histological and biochemical parameters in rats. The experiment was performed with 21 Sprague Dawley male rats. Rats were divided into three groups: group 1 control, group 2 valproic acid and group 3 valproic acid + silymarin. The groups received valproic acid 500 mg/kg/day and silymarin 100 mg/kg/day for 14 days except the control group. Increased serum glucose, cholesterol, triglyceride and creatine kinase BB levels with valproic acid were reversed with silymarin administration. Also, increased malondialdehyde and decreased glutathione levels in brain tissue with valproic acid were significantly suppressed by silymarin. In the valproic acid + silymarin group, oxidative stress was decreased, antioxidant activity was increased and histopathological changes were decreased compared to the valproic acid group. Brain injury caused by valproic acid was attenuated by silymarin treatment owing to the antioxidative and anti-apoptotic effects of silymarin. Silymarin may be useful for reducing the severity of valproic acid induced brain damage.
Análise de Situações de Canibalização de Produtos em Sistemas de Retalho

In this work we evaluate the performance of two data mining algorithms geared especially for the establishment of positive and negative association rules. For this we used a fairly comprehensive set of data from a retailer about the sales of products of a given period. The results achieved in this analysis and comparison work revealed a great potential for this type of solutions in the retail sector, where the use of knowledge acquired based on a set of positive association rules and negative association rules, despite its big difference, when combined is a major differentiating factor in terms of quality for customer personalization based on product relationships.
Dynamic Hedging and Order Flow Dynamics

The price process in a ﬁnancial market is driven by demand and supply. Statistical analyses have shown that price “feeds back” on future demand and supply. To date, few testable models have been proposed that oﬀer an economic explanation for this relationship. In this paper, we investigate a mechanism that might, at least to some extent, explain the positive feedback eﬀect of prices on future order volume, namely dynamic hedging. Using order book and transaction data from the Swiss Stock Exchange and Eurex, we investigate the dependencies between theoretical hedging demand generated by option holders and actual order volume in the underlying stock market. We are able to show that the popular belief that options trading has a negative systematic impact on the underlying market in the form of a positive feedback does not seem to be warranted.
EXISTENCE AND UNIQUENESS FOR D -SOLUTIONS OF REFLECTED BSDES WITH TWO BARRIERS WITHOUT MOKOBODZKI’S CONDITION

In this paper, we are interested in the problem of existence and uniqueness of a solution which belongs to class D for a backward stochastic diﬀerential equation with two strictly separated continuous reﬂecting barriers in the case when the data are L 1 -integrable and with generator satisfying the Lipschitz property. The main idea is to use the notion of local solution to obtain the global one.