Miracle-dz/UniFAR-FTUs huggingface dataset:
The Physiological Response of Green Algae (Chlorella vulgaris) to pH-Dependent Inhibitory Activity of Some Zinc(II) Compounds: Carboxylato- and Halogenocarboxylatozinc(II) Complexes

The inhibition of chlorophyll content in statically cultivated green algae Chlorella vulgaris caused by ZnSO4 ·H2O and nine carboxylatozinc(II) complexes was observed at pH = 5.8 and 7.2, respectively. At pH = 5.8 comparable inhibitory activity with that of ZnSO4 ·H2O was shown only by Zn(ClCH2COO)2 ·2H2O (IC50 = 0.111 mmol dm−3 and 0.104 mmol dm−3, respectively). The inhibitory activity of all other compounds was lower (the corresponding IC50 values varied in the range of 0.204—0.571 mmol dm−3) and it showed a decrease in the following order: Zn(ICH2COO)2, Zn(BrCH2COO)2 ·2H2O, Zn(CH3COO)2 · 2.5H2O, Zn(ClCH2CH2COO)2, Zn(CH3CH2CH2COO)2 or Zn(CH3CH2COO)2, Zn(CH3CH(Cl)COO)2, Zn((CH3)2CHCOO)2. At pH = 7.2 the inhibitory activity of all tested halogenocarboxylatozinc(II) complexes was higher than that of ZnSO4 ·H2O (0.300 mmol dm−3). The inhibition of chlorophyll a by ZnSO4 ·H2O and by the studied zinc(II) complexes was more strongly affected than that of chlorophyll b. The insertion of halogen atom into ligand led to the increase of biological activity whereas the branching of the alkyl chain was connected with activity decrease. In aqueous solutions in the investigated zinc(II) complexes zinc atom is coordinated with carboxylato ligands as well as with H2O molecules. We assume that its toxic effect can be manifested after exchange of these ligands (mainly H2O) with potential O- and N-donor ligands occurring in the algal cells. The higher the complex stability, i.e. the lower is the complex ability to exchange its ligands, the lower is its biological activity. Organic ligands could also affect the transport of metal ions through the lipophilic regions of cell membranes.
Exemplar-Free Video Retrieval

Video retrieval of activities has a wide range of applications. In the traditional mode of operation, a collection of example videos describing the activities are given and the retrieval technique identiﬁes other samples in a dataset that semantically match the examples provided. However, retrieval using a collection of example videos might not always be feasible, especially in the following two scenarios. The ﬁrst scenario is when we only have a textual description of a class of videos. The second scenario occurs when the activities under consideration are not temporally localized, making them harder to collect and annotate. For instance, most commonly-used action recognition datasets like Kinetics exploit public sources of videos like youtube for data collection, where all the categories are well localized and can be easily searched and annotated. This strategy does not extend to more complex activities like theft and object abandonment, both of which are not temporally localized, and are hard to annotate. In this thesis, we describe two video retrieval approaches that work in the absence of visual examples. First, a text based retrieval approach, where a text query allows us to bypass the use of a visual exemplar. Also text embedding models like GPT-2/GPT-3[19] are not trained in a dataset speciﬁc manner, ie . they are trained on all available data on the internet, and contain generalizable knowledge of all the activities in the real world. We will leverage that for developing retrieval models that work in the zeroshot/surprise setup. Since surprise activities are not known during the training time, the activity description/activity name is used during the test time to construct a textual embedding. First proposals are extracted from the video database using the TSM based model. For each proposal a visual embedding is computed. And similarity between video and textual embedding is used for retrieval. The second approach that we consider is a rule-based unsupervised retrieval framework for categories speciﬁc to object transfer. This works by ﬁrst detecting the objects and persons on a frame by frame basis. Followed by constructing short high-conﬁdence tracklets. These tracklets are further connected in a soft fashion, where each tracklet can be associated with other tracklets such that the cumulative probability
Exploring the potential greywater use in a typical microcosmic commercial area of South Africa

With water scarcity looming, South Africa needs to be mindful of the way water is used, conserved, or disposed of. By investigating the biological and physical characteristics of grey water, this paper attempted to explore the potential use of grey water within a microcosmic commercial area. Through different methods, samples were tested for Conductivity, Temperature, pH, and Turbidity. Using IDEXX 2000 method, biological characteristics of the grey water (Total Coliform (TC) and E-coli) were tested. At a pH range of 5.8 to 9, Turbidity in the grey water was found to be between 20.1 and 814. The count for TC ranged between 6.83 ×105 – 3.255 ×109 MPN/100 ml, and that for E-coli ranged between 0.1046 ×104 and 0.7701 ×108 MPN/100 ml. The study found that high turbidity values may have serious implications on the perception of people on grey water use as a potential substitute for potable water. However, the low number of E-coli counts suggests that greywater in commercial areas of South Africa may not pose a major health risk to people compared to black water. This paper will contribute to the knowledge about grey water characteristics expected to be encountered when contemplating exploiting grey water in commercial areas around South Africa.
A Comparison of K-Means and Mean Shift Algorithms

Clustering, or otherwise known as cluster analysis, is a learning problem that takes place without any human supervision. This technique has often been utilized, much efficiently, in data analysis, and serves for observing and identifying interesting, useful, or desired patterns in the said data. The clustering technique functions by performing a structured division of the data involved, in similar objects based on the characteristics that it identifies. This process results in the formation of groups, and each group that is formed, is called a cluster. A single said cluster consists of objects from the data, that have similarities among other objects found in the same cluster, and resemble differences when compared to objects identified from the data that now exist in other clusters. The process of clustering is very significant in various aspects of data analysis, as it determines and presents the intrinsic grouping of objects present in the data, based on their attributes, in a batch of unlabeled raw data. A textbook or otherwise said, good criteria, does not exist in this method of cluster analysis. That is because this process is so different and so customizable for every user, that needs it in his/her various and different needs. There is no outright best clustering algorithm, as it massively depends on the user’s scenario and needs. This paper is intended to compare and study two different clustering algorithms. The algorithms under investigation are k-mean and mean shift. These algorithms are compared according to the following factors: time complexity, training, prediction performance and accuracy of the clustering algorithms.
Tight Coupling of Character, Word, and Place Recognition for End-to-End Text Recognition in Maps

Text recognition in maps is a special case of general text recognition that features some especially difﬁcult challenges, including texts at extreme orientations, wide character spacings, complex text-like distractors, and unusual non-dictionary strings. Off-the-shelf OCR systems, and even sophisticated scene text recognition systems do not work satisfactorily on many map-text recognition problems. While many OCR and scene text systems have produced high quality results by considering detection, recognition, and error-correction as separate components, we believe that map text recognition can beneﬁt immensely from the tight coupling of different components of an overall sys-tem. In particular, we present an end-to-end system for recognizing text in maps that uses strong coupling in two different ways. In the ﬁrst, we train individual character detectors, and use these detections as inputs in a new word detection CNN architecture to improve word detection. We show dramatic increases in word detection accuracy for a strong baseline detection architecture. In the second contribution, we use a geographically-based lexicon to constrain our interpretations of initial detections. If the lexicon suggests that the word detection is either too short, we “re-prime” the word detector by inserting expected characters locations back into the word detector using a novel input mechanism. We then rerun the word detector using the additional character suggestions, giving a solid improvement in accuracy. We report end-to-end recognition results on a public map-text recognition benchmark.
Pyridine-functionalized carbazole donor and benzophenone acceptor design for thermally activated delayed fluorescence emitters in blue organic light-emitting diodes

Abstract. We report a molecular design approach for blue-emitting thermally activated delayed fluorescence (TADF) molecules. The two TADF emitters, (4-(3,6-di(pyridin-3-yl)-9H-carbazol-9-yl)phenyl)(phenyl)methanone (3PyCzBP) and (4-(3,6-diphenyl-9H-carbazol-9-yl)phenyl)(phenyl)methanone (4PyCzBP), possess a pyridine-functionalized carbazole donor and a benzophenone acceptor. Both compounds show broad charge-transfer emission in dichloromethane with a λmax at 497 nm and a photoluminescence quantum yield, ϕPL, of 56% for 3PyCzBP and a λmax at 477 nm and a ϕPL of 52% for 4PyCzBP. The ϕPL decreased to 18% and 10%, respectively, for 3PyCzBP and 4PyCzBP in the presence of O2 confirming that triplet states involved in emission. The poly(methyl methacrylate) (PMMA)-doped (10 wt. %) films show blueshifted emission with λmax at 450 and 449 nm for 3PyCzBP and 4PyCzBP, respectively. The maximum ϕPL of 23.4% is achieved for these compounds in PMMA-doped film. The difference in energy between the singlet and triplet excited states (ΔEST) is very small at 0.06 and 0.07 eV for 3PyCzBP and 4PyCzBP, respectively. Multilayer organic light-emitting diode devices fabricated using these molecules as emitters show that the maximum efficiency (EQEmax) of the blue devices is 5.0%.
Plant protection product losses via tile drainage: A conceptual model and mitigation measures

Drains can be installed to reduce saturated soil conditions and improve crop growth. This article evaluates the extent to which these systems may cause losses of plant protection products (PPP). To that end, we estimated the drained fraction of Swiss arable land using both existing drainage maps and machine learning. Our drainage map suggests that 25% of Swiss agricultural land has a moderate to high potential of being drained. We further evaluated the risk for PPP losses via drainage and the potential of selected mitigation measures based on a conceptual model summarising the relevant scientific literature. Although drainage losses are highly variable, they are strongly influenced by the extent of preferential flow (PF) in soils and are an important transport pathway to surface waters. Most agricultural soils in Switzerland are prone to PF, given their loamy texture, suggesting that PPP losses via tile drains are an important phenomenon in Switzerland’s drained arable fields. The most common mitigation measures for drainage are those recommended for runoff, erosion and leaching. However, given the uncertainty of the local PPP losses and driving factors, no siteor PPP-specific measures can currently be proposed to reduce PPP drainage losses. This study also examines the effectiveness of the regulatory model EXPOSIT in predicting total PPP losses and peak concentrations in watercourses. When compared with experimental data from Agroscope at ZurichAffoltern, our findings suggest that EXPOSIT does not yield the worst-case estimates for Swiss conditions.
A Double Loop Learning Model For Integrated and Proactive Customer Relationship Management

iv TABLE OF CONTENTS . vi LIST OF TABLES . ix LIST OF FIGURES . x MOTIVATION . 1 ESSAY1 . 4 A CONCEPTUAL FRAMEWORK FOR INTEGRATED AND PROACTIVE CRM . 4 1.
Highly Structured Polyvinyl Alcohol Porous Carriers: Tuning Inherent Stability and Release Kinetics in Water

Polyvinyl alcohol (PVA) porous carriers were prepared by means of ice templating of aqueous solutions containing of 90 kD and/or 16 kD PVA. The carriers were loaded with traces of a colored probe (methyl orange) to screen their release properties, once immersed in water. The carriers prepared from solutions containing 90 kD and 16 kD PVA resulted in intimate polymer mixtures, exhibiting physical properties that stand in between those of the bare 90 kD or 16 kD PVA end members. The freezing protocols employed were adapted to prepare carriers textured in the form of either monolithic scaffolds (directional constant freezing rate) or millimetric pellets (flash-freeze). Monolithic carriers remain stable in aqueous solution, and the probe release is governed by a swelling–diffusion mechanism. The kinetics of probe release can be tuned from minutes to hours by either increasing the total PVA content or the 90 kD-to-16 kD PVA ratio in the parent solution. In contrast, pellets (millimetric carriers) immersed in water release the probe on the scale of minutes, irrespective of the PVA content or composition. However, the PVA content and the 90 kD-to-16 kD PVA ratio dramatically affect the stability of the carriers. Depending on the formulation, these small carriers can develop swelling, erosion, or eventually massive dissolution.
Can Being Aware of the Illusion of Self Augment an Agent's Affordances: Integrating Buddhist Philosophy, Cognitive Science, and Artificial Life

1Center for the Study of Apparent Selves, Kathmandu, Nepal 2Centre for Buddhist Studies at Rangjung Yeshe Institute, Kathmandu University, Kathmandu, Nepal 3Department of Psychiatry, McGill University, Montreal, Quebec, Canada 4Bill Duane and Associates 5Cross Labs, Cross Compass Ltd., Japan 6Earth-Life Science Institute, Tokyo Institute of Technology, Japan 7College of Arts and Sciences, University of Tokyo, Japan info@csas.ai
Phenolic composition and antioxidant activity of sweetpotatoes [Ipomoea batatas (L.) Lam]

The influence of numerous factors on sweetpotato phenolic content and antioxidant activity was determined. Simplified, robust, and rapid methodologies were developed to quantify total phenolics and individual phenolic acids in sweetpotatoes. Quantification of total phenolic content using Folin-Denis reagent provided more reliable results than Folin-Ciocalteu reagent. Individual phenolic acids were quantified by reversed-phase high performance liquid chromatography (HPLC) and the best separation was achieved using a 5-μm, 4.6 × 250 mm column with a mobile phase of 1% (v/v) formic acid aqueous solution: acetonitrile: 2-propanol (70:22:8), pH 2.5. Methanol and ethanol provided higher phenolic extraction efficiency than acetone. In general, chlorogenic and 3,5-dicaffeoylquinic acid were the most prominent phenolics acids in sweetpotato root and leaf tissues. Immature roots and leaves at the initial stages of growth had the highest concentration of phenolics and antioxidant activity. In a comparison of plant parts, sweetpotato leaves had a significantly higher phenolic content and antioxidant activity than roots. Thermal processing of sweetpotato storage roots resulted in a significant loss of phenolic content and antioxidant activity. The outer skin tissue (raw or processed) contained the highest amounts of phenolic acids but also exhibited higher losses than cortex or pith tissue. After a 4 week exposure to 5 °C, the rate of increase in phenolic content and antioxidant activity in non-cured sweepotatoes was significantly higher than in cured roots. An ambient temperature exposure following low temperature storage accentuated the increase in phenolics and antioxidant activity. Minimally processed sweetpotatoes held at 5 °C accumulated more phenolic compounds and had a higher antioxidant activity than sweetpotatoes held at 0 °C. The increase in total phenolic
Correlative microscopy reveals abnormalities in type 1 diabetes

Nanodiamonds containing fluorescent nitrogen-vacancy centers are increasingly attracting interest for use as a probe in biological microscopy. This interest stems from (i) strong resistance to photobleaching allowing prolonged fluorescence observation times; (ii) the possibility to excite fluorescence using a focused electron beam (cathodoluminescence; CL) for high-resolution localization; and (iii) the potential use for nanoscale sensing. For all these schemes, the development of versatile molecular labeling using relatively small diamonds is essential. Here, we show the direct targeting of a biological molecule with nanodiamonds as small as 70 nm using a streptavidin conjugation and standard antibody labelling approach. We also show internalization of 40 nm sized nanodiamonds. The fluorescence from the nanodiamonds survives osmium-fixation and plastic embedding making them suited for correlative light and electron microscopy. We show that CL can be observed from epon-embedded nanodiamonds, while surface-exposed nanoparticles also stand out in secondary electron (SE) signal due to the exceptionally high diamond SE yield. Finally, we demonstrate the magnetic read-out using fluorescence from diamonds prior to embedding. Thus, our results firmly establish nanodiamonds containing nitrogen-vacancy centers as unique, versatile probes for combining and correlating different types of microscopy, from fluorescence imaging and magnetometry to ultrastructural investigation using electron microscopy.
TOR Gizli Servis Tarayıcılarının Performans Karşılaştırması

TOR (The Onion Routing) is a network structure that has become popular in recent years due to providing anonymity to its users and is often preferred by hidden services. Because the privacy is essential, this network draws attention, so the amount of data stored increases day by day, making it difficult to scan and analyze. Various crawler software has been developed in order to scan the services (onion web pages) in this network. However, crawling here is different from the surface network. Because the TOR network is located on the lower layers of the surface network and the pages in TOR are accessed only through the TOR browser. In the requests made to the addresses, to protect the confidentiality, the data was obtained by selecting paths through different relays. In TOR network, reaching the target address by passing over different relays in each request, slows down it. Also, the low performance of a crawler that tries to retrieve information through TOR, brings long periods of waiting. Therefore, working with a software with high crawling and information acquisition speed, will improve the analysis process of the researchers. 4 different crawler software was evaluated according to various criteria in terms of guiding the people who will conduct research in this field and evaluating the superior and weaknesses of the crawlers against each other. The study provides an important point of view for choosing the right crawler in terms of initial starting points for the researchers want to analyze of Tor web services.
Reinforcement Learning : Final Project Diversity is All You Need

Section 1 introduces the standard RL problem and spotlights some of its associated issues before introducing a workaround to the most pressing one. Section 2 delves into the workaround and explore a corresponding method that we later implement1, namely Diversity Is All You Need (DIAYN) [1]. Finally, section 3 briefly lay out where DIAYN stands in the RL literature before wrapping up the project with a few conclusive remarks.
Analysis of Sports Performance Prediction Model Based on GA-BP Neural Network Algorithm

There are many factors that affect athletes' sports performance in sports competitions. The traditional sports performance prediction method is difficult to obtain more accurate sports performance prediction results and corresponding data analysis in a short time, which is not conducive for coaches to formulate targeted and scientific training sprint plans for athletes' problems. Therefore, based on GA-BP neural network algorithm, this paper constructs a sports performance prediction model and carries out experiments and analysis. The experimental results show that GA-BP neural network algorithm has a faster convergence speed than BP neural network and can achieve the expected error accuracy in a shorter time, which overcomes the problems of the BP neural network. At the same time, different from the previous models, GA-BP neural network algorithm can get the athlete training model according to the relationship between quality training indicators and special sports training results, which can more intuitively show the advantages and disadvantages of athletes. In the final sports performance prediction results, GA-BP neural network prediction results have higher accuracy, better stability, better prediction effect, and higher application value than BP neural network.
The Eff ects of Diff erent Mydriatics on Intraocular Pressure and Central Corneal Thickness in New Zealand White Rabbits

This study was aimed to compare the eff ect of 1% atropine, 1% cyclopentolate, 0.5% tropicamide, and 10% phenylephrine eye drops on intraocular pressure (IOP) and central corneal thickness (CCT) in New Zealand White rabbits. Adult male, eight, New Zealand White rabbits were randomly received each of four mydriatic eye drops separately on left eye at a one-week washout period. Each rabbit received all of five diff erent treatments (sterile saline solution, four mydriatic drugs) on the left eye, whereas no measurements were performed on the right eyes during the experiment. The IOP and CCT recordings of rabbits were performed until the pupil returned to normal diameter. The mean CCT values of sterile saline, 1% atropine, 0.5% tropicamide, 1% cyclopentolate, and 10% phenylephrine were 370±15, 368±17, 372±15, 364±18, and 360±17 μm, respectively, and no statistically significant diff erences (P>0.05) were observed among groups. The mean IOP values of control (sterile saline), 1% atropine, 0.5% tropicamide, 1% cyclopentolate, and 10% phenylephrine as, 9.7±2.1, 10.4±1.8, 10.3±2.1, 11.0±2.1, and 10±1.8 mmHg, respectively, and these were not statistically significant among groups (P>0.05). In conclusion, topical 1% atropine, 0.5% tropicamide 1% cyclopentolate, and 10% phenylephrine do not have significantly eff ect on IOP and CCT in New Zealand white rabbits.
Property-Based Testing for Visualization Development

As the testing capabilities of current visualization software fail to cover a large space of rendering parameters, we propose to use property-based testing to automatically generate a large set of tests with different parameter sets. By comparing the resulting renderings for pairs of different parameters, we can verify certain effects to be expected in the rendering upon change of a speciﬁc parameter. This allows for testing visualization algorithms with a large coverage of rendering parameters. Our proposed approach can also be used in a test-driven manner, meaning the tests can be deﬁned alongside the actual algorithm. Lastly, we show that by integrating the proposed concepts into the existing regression testing pipeline of Inviwo, we can execute the property-based testing process in a continuous integration setup. To demonstrate our approach, we describe use cases where property-based testing can help to ﬁnd errors during visualization development.