Miracle-dz/UniFAR-FTUs huggingface dataset:
GIS and RS soil-vegetation correlations for continental salt-lands habitats in NE Romania

Continental saltlands have a high degree of peculiarity amongst European primary habitats and a prominent insular character. The present scientific approach establishes the degree of soil-vegetation correlation in continental slatlands patches as a measure of habitat continuity/fragmentation and soil conservation/degradation. The use of hyperspectral imagery, soil types’ distribution and vegetal associations’ conservation status reveal disturbances in relation with human induced modifications in comparison with normal plant-soil interdependence. Supervised classifications of LANDSAT satellite imagery along with detailed soil maps, ground truth data provided by accurate GPS positioning and field based plants evaluation are used to perform landscape metrics analyses. The landscape metrics approach is meant to find the balance between extent and grain in the case of saltlands habitats analyses and the degree of patches and classes inhomogeneity. These also give an insight of habitats connectivity and/or isolation in relation with land use topology and soil multiplexing . The resulting training sets developed for a representative, protected area in the county of Iasi enhance the creation of a comprehensive mask to be used for the evaluation of larger areas in the silvan-steppes of North-Eastern Romania. The model is statistically tested to depict the degree of correlation and confidence. The final goal resides in more proper measures elaboration for the mitigation of continental saltland preservation and natural resources exploitation via agricultural and the associated activities.
Service level agreement trading for the differentiated services architectures

The differentiated services (DS) architecture provides a framework for the scalable provisioning of multiple service levels in the Internet. Its definition and initial work have concentrated mainly on per-hop behaviors (PHB) and mechanisms at each DS domain. Equally important is what happens between DS domains. Thanks to the flexibility of the architecture, it is the providers’ choice how to interconnect with peers. In principle, traditional, static peering agreements work together with DS, but they do not offer the flexibility and dynamics needed in an electronic market for network capacity. Therefore, we look at dynamic service level agreements at the interdomain level. Such agreements are established by software entities called traders. These traders follow market-based principles to decide which contracts will be beneficial. In particular, traders compare the offers made by neighbor providers and select the most interesting ones. This selection of peer services creates competition among providers and integrates route selection based on service level and destination. We describe and implement a framework for service level agreement trading. We show the basic workings and first performance results of SLA trading using specific traders and an experimentally defined PHB in a simulation environment. Keywords— Network architecture, differentiated services architecture, service level agreement, pricing, trading, interdomain QoS routing.
Culture, Beliefs and the Inequality-Growth Nexus

Methods and apparatus for optical communication are disclosed. An optical data stream is encoded to produce an optical data stream having a predetermined time-wavelength spectrum. Two or more encoded data streams are combined in a transmission medium (e.g., optical fiber) and the combined data stream is decoded with decoders corresponding to the encoding of the data streams, producing decoded outputs. The decoded outputs include a portion corresponding to a selected data stream as well as a portion corresponding to unselected data streams (crosstalk). A nonlinear detector receives the decoded outputs and rejects crosstalk. Coders produce temporal delays and phase shifts specified by a time-wavelength code for, the spectral components of an input optical signal. Some coders convert optical signals encoded with a first time-wavelength code into an output corresponding to a second time-wavelength code. Temporal delays and phase shifts can be selected to compensate for dispersion in a transmission medium. Coherent coders are provided in which the phase shifts produced on the spectral components of an optical signal are controlled within about one half of the wavelength of the spectral component.
Activity-Based Approach In Social Workers’ Professional Training

Social work education in Ukraine has changed dramatically over the last decades. It has a strong connection with the evolution of social work education as a field of professional practice. Recent changes in Ukrainian social policy, in particular the implementation of professional education requirements, based on the competency-oriented approach, the implementation of professional standards for social workers, the distinction of social work in a separate field of science and the complexity of social practice require the creation of unified training curriculum that corresponds to social needs and practice requirements. Creating a meaningful learning environment and raising awareness of professional objectives would be achievable by applying an activity-oriented approach to the professional education of social workers. This means that knowledge could never be isolated from activity. Activity-oriented educational practices contain the core components of professional activities and concern different aspects of social work. Profession-oriented practice includes general (volunteer activities, research, social project design, organizational and management) and additional (communicative, play and game, teamwork) forms and technologies, which demand from students to accumulate their experience in obtaining the essential forms of professional activities. Professional practice encompasses a set of principles, based on the prioritization of the social work profession, individual activity, participation and reflection, which make possible the development of the student's personal maturity and independence.
Peran Perceived Effectiveness of Escrow Services terhadap Satisfaction dan Trust pada E-Commerce di Indonesia

Keadaan pandemi COVID-19 mendorong masyarakat untuk berbelanja dari rumah dengan menggunakan e-commerce. Faktor kepuasan dan kepercayaan konsumen merupakan dua faktor kunci dalam meningkatkan penetrasi e-commerce. Guna meningkatkan kepercayaan dan kepuasan konsumen, pengelola e-commerce menawarkan jasa escrow dalam memproses pembayaran yang dilakukan pada platform e-commerce. Penelitian yang dilakukan merupakan penelitian kuantitatif non-probability dengan mengumpulkan data melalui kuisioner dan analisis data menggunakan metode moderated regression analysis. Hasil penelitian menunjukkan kepuasan yang dirasakan oleh responden terhadap pembelian sebelumnya dapat mempengaruhi kepercayaan konsumen terhadap penjual. Variabel perceived effectiveness of escrow services mampu memoderasi hubungan antara variabel kepuasan dan kepercayaan.
Experimental study on calculation model of road traffic noise radiated from semi-underground roads

For the assessment of road traffic noise, practical calculation model for various type of road structures are being discussed. Among them, a calculation model for semi-underground road is strongly required. As one of the practical models, the authors have proposed a hypothetical source model in which noise radiation from an opening of semi-underground road is expressed by a directional point source located at the opening of the semi-underground road. In this paper, the applicability of the calculation model is examined by 1/20 scale model experiment.
Homological invariants of powers of an ideal

For any fixed nonnegative integer i and all sufficiently large n, the following are shown to be polynomials in n: (1) The ith Betti number, f#O (,An), and the ith Bass number, #ij (An , where X= en>O n is a finitely generated graded module over a Noetherian graded ring R =MO [,W ] with So local. (2) The lengths, AR(TorR(M/IjM, Q)) and AR(Ext (Q, M/IjM)), for an ideal I of a Noetherian ring R and finitely generated R-modules M, Q with M OR Q of finite length. (3) The minimal number of generators, vR(TorR(M/IjM, Q)) and vR(Exti(Q, M/IjM)) , where I is an ideal of a Noetherian local ring R and M, Q are finitely generated R-modules. It is also shown that the degrees of these polynomials are bounded by constants independent of i. Let R be a Noetherian local ring with maximal ideal m and residue field k, and let I be a proper ideal of R. Let AR and VR denote, respectively, the length and minimal number of generator functions on R-modules. It is well known [9, Theorem 1] that if n is sufficiently large, then VR(In) = AlR(In/mIn) is a polynomial in n. The analytic spread of I, denoted l(I), is defined to be one more than the degree of this polynomial. This result may be rephrased as saying that the first Betti number of R/In is a polynomial in n for large n. Recall that for a finitely generated R-module M and nonnegative integer i, the ith Betti number of M, denoted flf? (M), is defined to be )lR(TorR(M, k)). Also recall the dual notion of the ith Bass number, defined by 4uR(M) = AR? (EXtR(k, M)) This paper generalizes the result above to the higher Betti numbers and to Bass numbers. A version for graded modules is also obtained. Theorem 1. Let R = en>own be a Noetherian graded ringgenerated as an Moalgebra by WI and with Sfo local with maximal ideal m. Let X' = en>O n be a finitely generated graded R? -module. Then, for any fixed integer i > 0 and for all large n, both flO(? n) and pi (.1(? n) are polynomials in n of degree at most dimw(go/m.#) 1. Received by the editors November 21, 1991; presented at the special session in Commutative Algebra at the 873rd meeting of the AMS at Springfield, Missouri, March 21, 1992. 1991 Mathematics Subject Classification. Primary 1 3D02; Secondary 1 3D40, 1 3A30. ( 1993 American Mathematical Society 0002-9939/93 $1.00 + $. 25 per page
Survival outcomes of hypomethylating agents maintenance therapy in new diagnosed AML patients: Real experience data

OBJECTIVE Acute myeloid leukemia (AML) is a hematological malignancy that frequently affects elderly population. With introducing the hypomethylating agents (HMAs) in elderly AML treatment, survival rates and quality of life have improved. However, long-term management in elderly and frail patients is still a challenge. In the present study, we aimed to determine whether HMA maintenance therapy is required until disease progression in frail and elderly AML patients by examining with a real-life data. METHODS In a multicenter study, we analyzed non-promyelocytic elderly AML patients who were treated with first-line azacitidine or decitabine monotherapy in two different groups, retrospectively. While patients were treated with HMA until progression in the maintenance group, 6+3 cycles of azacitidine or decitabine were administered as a standard care of elderly AML patients in the non-maintenance group. Survival outcomes were compared between the groups. RESULTS HMA therapy was maintained until progression in 20 patients, and HMA therapy was terminated after 6+3 cycles in 21 patients. Patients received a median of 6 (1–14) HMA cycles during follow-up time. The median 7.5 months of overall survival were observed (2–17 months) in maintenance and 3 months (1–13 months) in non-maintenance groups (p=0.001). CONCLUSION Despite long-term exposure to HMA may appear as a risk factor for complications and toxicities in elderly and frail AML patients, the maintenance of therapy until disease progression provides a significant survival advantage. Therefore, we suggest that HMA therapy should continue until disease progression regardless the sort of HMA.
Race Classification Using Deep Learning

: Race classification is a long-standing challenge in the field of face image analysis. The investigation of salient facial features is an important task to avoid processing all face parts. Face segmentation strongly benefits several face analysis tasks, including ethnicity and race classification. We propose a race-classification algorithm using a prior face segmentation framework. A deep convolutional neural network (DCNN) was used to construct a face segmentation model. For training the DCNN, we label face images according to seven different classes, that is, nose, skin, hair, eyes, brows, back, and mouth. The DCNN model developed in the first phase was used to create segmentation results. The probabilistic classification method is used, and probability maps (PMs) are created for each semantic class. We investigated five salient facial features from among seven that help in race classification. Features are extracted from the PMs of five classes, and a new model is trained based on the DCNN. We assessed the performance of the proposed race classification method on four standard face datasets, reporting superior results compared with previous studies.
Artificial Tesi de Màster Contextual Bag-of-Visual-Words and ECOC-Rank for Retrieval and Multi-class Object Recognition

Multi-class object categorization is an important line of research in Computer Vision and Pattern Recognition fields. An artificial intelligent system is able to interact with its environment if it is able to distinguish among a set of cases, instances, situations, objects, etc. The World is inherently multi-class, and thus, the efficiency of a system can be determined by its accuracy discriminating among a set of cases. A recently applied procedure in the literature is the Bag-Of-Visual-Words (BOVW). This methodology is based on the natural language processing theory, where a set of sentences are defined based on word frequencies. Analogy, in the pattern recognition domain, an object is described based on the frequency of its parts appearance. However, a general drawback of this method is that the dictionary construction does not take into account geometrical information about object parts. In order to include parts relations in the BOVW model, we propose the Contextual BOVW (C-BOVW), where the dictionary construction is guided by a geometricaly-based merging procedure. As a result, objects are described as sentences where geometrical information is implicitly considered. In order to extend the proposed system to the multi-class case, we used the Error-Correcting Output Codes framework (ECOC). State-of-the-art multi-class techniques are frequently defined as an ensemble of binary classifiers. In this sense, the ECOC framework, based on error-correcting principles, showed to be a powerful tool, being able to classify a huge number of classes at the same time that corrects classification errors produced by the individual learners. In our case, the C-BOVW sentences are learnt by means of an ECOC configuration, obtaining high discriminative power. Moreover, we used the ECOC outputs obtained by the new methodology to rank classes. In some situations, more than one label is required to work with multiple hypothesis and find similar cases, such as in the well-known retrieval problems. In this sense, we also included contextual and semantic information to modify the ECOC outputs and defined an ECOCrank methodology. Altering the ECOC output values by means of the adjacency of classes based on features and classes relations based on ontologies, we also reported a significant improvement in class-retrieval problems.
Chapter 2 Applicability of Quantum Dots in Biomedical Science

Quantum dots (QDs) are novel class of inorganic fluorophore with superior photophysical properties. Superior optical properties are a promising alternative to organic dyes for fluorescence biomedical applications. These nanoparticles have size-tunable emission, strong light absorbance, and very high levels of brightness and photostability. Highly luminescent QDs are prepared by coating the core with another material, resulting in core-shell quantum dots that are more stable in various chemical environments. These core-shell QDs are hydrophobic and only organic soluble as prepared. Hydrophobic QDs are insoluble in aqueous solution and cannot be directly employed in biomedical applications. They are necessarily made water soluble by surface modifying them with various bifunctional surface ligands or caps to promote aqueous solubility and enhancing biocompatibility. To make them useful for biomedical applications, QDs need to be conjugated to biological molecules without disturbing the biological function of these molecules. Most of the current studies were designed to ask questions concerning the physicochemical properties of novel QD products, not QD toxicity per se. The potential toxicity of the QDs is a cause for concern because they are made of heavy metals. The limitation of heavy metal–containing QDs stimulates extensive research interests in exploring alternative strategies for the design of fluorescent nanocrystals with high biocompatibility.
Who Is Still Haunted by the Specter of Communism?: Explaining Relative Output Contractions Under Transition

This paper analyzes the initial output decline in transition economies by estimating a cross-sectional model stressing two major factors: conflicts and the legacies of the Soviet period. We link the Soviet legacies in place at the outset of transition to the subsequent path for the development of market-related institutions. Institutional development, as proxied by measures of corruption, is used as an intermediate variable. An instrumental variable approach is followed to derive estimates that are not biased by the possible endogeneity of corruption with respect to output developments. Assuming that the extent of Soviet legacies was positively correlated with the length of communist rule allows us to use years under the Soviet regime as an instrument.
ULTRASONIC METHOD FOR METAL RECOGNITION BY MEANS OF FAST WAVELET TRANSFORMATION

A method for classification of metals is proposed in this paper. An ultrasound non-contact echo-location method is used for gathering information from tested metal samples, made of Aluminum, Chrome-Nickel, Brass, Copper, Castiron and Steel. The reflected signal is received and processed using methods for recognition of images. For forming of attributes for classification an apparatus of the discrete wavelet transformations with orthogonal wavelet basis functions is applied. The classification is realized by the method of “k-nearest neighbors” (kNN). The received data are shown and an evaluation of errors in the classification is done.
Understanding the relationship between rationality and intelligence: a latent-variable approach

Abstract A hallmark of intelligent behavior is rationality – the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a sample of 331 participants, we assessed the relationship between rationality and intelligence. There was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.
Change in Women's Descriptive Representation and the Belief in Women's Ability to Govern: A Virtuous Cycle

As a core principle of democratic theory, political scientists stress the importance of more inclusive and diverse elected bodies (Mansbridge 1999; Phillips 1995; Pitkin 1967; Williams 1998; Young 2000). A large portion of that literature discusses the positive symbolic effects of elected bodies when they come closer to mirroring the population from which they are drawn. For underrepresented groups, increases in their descriptive representation symbolize a more open political arena. This improves the group's political participation as well as beliefs about the group's role in politics.
The Influence of Ethical Leadership and Regulatory Focus on Employee Outcomes

ABSTRACT: Regulatory focus theory is proposed as offering an explanation for the influence of ethical leadership on organizational citizenship behaviors and employee commitments. The prevention focus mindset of an employee is argued to be the mechanism by which an ethical leader influences extra-role compliance behavior as well as normative commitment, whereas the promotion focus mindset of an employee is argued to be the mechanism by which an ethical leader influences extra-role voice behavior as well as affective commitment. Moreover, leader-member exchange is proposed as a moderator of the relationship of ethical leadership to regulatory focus mindsets and employee behavior and commitments. Using the data collected in two waves from 250 working adults, we tested the proposed relationships with moderated mediation bootstrap procedures. The findings generally support the hypothesized relationships and point toward important implications for ethical leadership in work settings.
A Feature Extraction Method Based on Differential Entropy and Linear Discriminant Analysis for Emotion Recognition

Feature extraction of electroencephalography (EEG) signals plays a significant role in the wearable computing field. Due to the practical applications of EEG emotion calculation, researchers often use edge calculation to reduce data transmission times, however, as EEG involves a large amount of data, determining how to effectively extract features and reduce the amount of calculation is still the focus of abundant research. Researchers have proposed many EEG feature extraction methods. However, these methods have problems such as high time complexity and insufficient precision. The main purpose of this paper is to introduce an innovative method for obtaining reliable distinguishing features from EEG signals. This feature extraction method combines differential entropy with Linear Discriminant Analysis (LDA) that can be applied in feature extraction of emotional EEG signals. We use a three-category sentiment EEG dataset to conduct experiments. The experimental results show that the proposed feature extraction method can significantly improve the performance of the EEG classification: Compared with the result of the original dataset, the average accuracy increases by 68%, which is 7% higher than the result obtained when only using differential entropy in feature extraction. The total execution time shows that the proposed method has a lower time complexity.