Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination Of Optimal Number Of Clusters In Wireless Sensor Networks

Prolonged network lifetime, scalability and efficient load balancing are essential for optimal performance of a wireless sensor network. Clustering provides an effective way of extending the lifetime of a sensor network. Clustering is the process that divides sensor networks into smaller localized group (called clusters) of members with a cluster head. Clustering protocols need to elect optimal number of clusters in hierarchically structured wireless sensor networks. Any clustering scheme that elects clusters uniformly (irrespective of the distance from Base Station) incurs excessive energy usage on clusters proximal and distant to Base Station. In single hop networks a gradual increment in the energy depletion rate is observed as the distance from the cluster head increases. This work focuses on the analysis of wasteful energy consumption within a uniform cluster head election model (EPEM) and provides an analytic solution to reduce the overall consumption of energy usage amongst the clusters elected in a wireless sensor network. A circular model of sensor network is considered, where the sensor nodes are deployed around a centrally located Base Station. The sensor network is divided into several concentric rings centred at the Base Station. A model, Unequal Probability Election Model (UEPEM), which elects cluster heads non-uniformly is proposed. The probability of cluster head election depends on the distance from the Base Station. UEPEM reduces the overall energy usage by about 21% over EPEM. The performance of UEPEM improves as the number of rings is increased.
Target Detection and Segmentation Technology for Zero-shot Learning

Zero-shot learning (ZSL) in the field of computer vision refers to enabling the model to recognize and understand categories that have not been encountered during the training phase. It is particularly critical for object detection and segmentation tasks, because these tasks require the model to have good generalization capabilities to unknown categories. Object detection requires the model to determine the location of the object, while segmentation further requires the precise demarcation of the object's boundaries. In ZSL research, knowledge representation and transfer are core issues. Researchers have tried to use semantic attributes as a knowledge bridge to connect categories seen during the training phase and categories not seen during the testing phase. These attributes may be color, shape, etc., but this method requires accurate attribute annotation, which is often not easy to achieve in practice. Therefore, researchers have begun to explore the use of non-visual information such as knowledge maps and text descriptions to enrich the recognition capabilities of models, but this also introduces the challenge of information integration and alignment. At present, ZSL has made certain progress in target detection and segmentation tasks, but there is still a significant gap compared with traditional supervised learning. This is mainly due to the limited ability of ZSL models to generalize to new categories. To this end, researchers have begun to explore combining ZSL with other technologies, such as generative adversarial networks (GANs) and reinforcement learning, to enhance the model's detection and segmentation capabilities for new categories. Future research needs to focus on several aspects. The first is how to design a more effective knowledge representation and transfer mechanism so that the model can better utilize existing knowledge. The second step is to develop new algorithms to improve the performance of ZSL in complex environments. In addition, research should focus on how to reduce the dependence on computing resources so that the ZSL method can run effectively in resource-limited environments. In summary, the research on target detection and segmentation technology of zero-shot learning is a cutting-edge topic in the field of computer vision. Despite the challenges, with the deepening of research, we expect these technologies to contribute to improving the generalization ability and intelligence level of computer vision systems.
Casablanca: Towards a Dataset-Independent Tool for Semantic Web Annotation

Semantic Web Annotation is the process of mapping named entities that appear in free-text to universal identifiers, typically made available by a Linked Data provider such as DBpedia or Freebase. This is a time consuming process, as it is usually performed by human experts with little or no computational assistance. This paper describes Casablanca, a tool built in order to make Semantic Web Annotation an accessible process for any dataset. Casablanca's approach is to request a minimal configuration describing a dataset. It then provides unified programming and user interfaces to perform annotation based on this configuration. To perform the necessary disambiguation between named entities, Casablanca relies on existing data available in the targeted dataset.
A Symmetric Non-Stationary Loop Subdivision with Applications in Initial Point Interpolation

Loop subdivision is a significant surface scheme with wide applications in fields like computer graphics and wavelet. As a type of stationary scheme, Loop subdivision cannot adjust the limit surface directly. In this paper, we present a new way to solve this problem by proposing a symmetric non-stationary Loop subdivision based on a suitable iteration. This new scheme can be used to adjust the limit surfaces freely and thus can generate surfaces with different shapes. For this new scheme, we show that it is C2 convergent in the regular part of mesh and is at least tangent plane continuous at the limit positions of the extraordinary points. Additionally, we present a non-uniform generalization of this new symmetric non-stationary subdivision so as to locally control the shape of the limit surfaces. More interestingly, we present the limit positions of the initial points, both for the symmetric non-stationary Loop subdivision and its non-uniform generalization. Such limit positions can be used to interpolate the initial points with different valences, generalizing the existing result. Several numerical examples are given to illustrate the performance of the new schemes.
Evolution of the Pingluo Section of the Upper Yellow River over the Past 50 Years: Responses to Environmental Change and Human Activity

The instability of the river channels has increased in response to the combined effects of global warming and human activity. This instability threatens the lives and property of people who live along river courses. This study takes the Pingluo section of the upper Yellow River, which is ~28 km long and ~400 m wide, as its research focus. We studied 11 periods of Landsat remote sensing images from 1973 to 2023 and analyzed the evolutionary characteristics of the Pingluo section over the past 50 years. The channel morphology indices included the channel braiding index (BIT), the bar braiding index (BIB), the average area of the bar (Ab), and the width of the wet channel area (BW). The results showed that there was an overall shrinking trend in this section of the Yellow River; more particularly, fluctuations in indicators such as the river width and the braiding index highlighted an increasing–decreasing–increasing pattern of change. During the 1973–1986 period, the river showed a widening trend, with narrow anabranches cutting through the floodplain and both the river width and the braiding index increasing dramatically over a short period. Over the 1986–2018 period, the area of the wet channel continued to shrink to its lowest level for the past 50 years, the river’s branches were diverted and abandoned, and the channel tended to straighten out. Between 2018 and 2023, the river showed a slightly expanding trend. The evolution of the river channel appears to be related to regional human activity and climate change. For example, after the joint filling of the Longyangxia and Liujiaxia reservoirs in the upper reaches of the Pingluo section of the Yellow River in 1986, runoff and sediment load along this section decreased, flood events became less frequent, and the channel tended to contract. In addition, the increase in extreme precipitation events over the last five years has led to an increase in the magnitude and frequency of peak discharge values in the region, which is the main reason for the increase in the river braiding index and area.
A Foundation for Efficient Indoor Distance-Aware Query Processing

Indoor spaces accommodate large numbers of spatial objects, e.g., points of interest (POIs), and moving populations. A variety of services, e.g., location-based services and security control, are relevant to indoor spaces. Such services can be improved substantially if they are capable of utilizing indoor distances. However, existing indoor space models do not account well for indoor distances. To address this shortcoming, we propose a data management infrastructure that captures indoor distance and facilitates distance-aware query processing. In particular, we propose a distance-aware indoor space model that integrates indoor distance seamlessly. To enable the use of the model as a foundation for query processing, we develop accompanying, efficient algorithms that compute indoor distances for different indoor entities like doors as well as locations. We also propose an indexing framework that accommodates indoor distances that are pre-computed using the proposed algorithms. On top of this foundation, we develop efficient algorithms for typical indoor, distance-aware queries. The results of an extensive experimental evaluation demonstrate the efficacy of the proposals.
Transparent, Low Resource, and Context-Aware Information Retrieval From a Closed Domain Knowledge Base

In large-scale enterprises, vast amounts of textual information are shared across corporate repositories and intranet websites. Traditional search techniques that lack context sensitivity, often fail to retrieve pertinent data efficiently. Modern techniques that use a distributed representation of words require a considerable training dataset and computation, thereby presenting financial and operational burdens. Generative models for information search suffer from problems of transparency and hallucination, which can be detrimental, especially for organizations and their stakeholders who rely on these results for critical business operations. This paper presents a non-goal oriented conversational agent based on a collection of finite state machines and an information search model for text search from an extensive collection of stored corporate documents and intranet websites. We used a distributed representation of words derived from the BERT model, which allows for contextual searching. We minimally fine-tuned a BERT model on a multi-label text classification task specific to a closed-domain knowledge base. Based on DCG metrics, our information retrieval model using distributed embeddings from the minimally trained BERT model and Word Movers Distance for calculating topic similarity is more relevant to user queries than BERT embeddings with cosine similarity and BM25. Our architecture promises to significantly expedite and improve the accuracy of information retrieval in closed-domain systems without the need for a massive training dataset or expensive computing while maintaining transparency.
Semantic Data Management for db4o

Object databases such as db4o provide a very simple and eective way of making application objects persistent. However, they oer limited support for high-level database application programming in terms of facilities for the management of complex interrelated collections of data objects over long periods of time. Concepts of semantic data models such as role modelling, and associations are lacking and this results in a new impedance mismatch between the program and data models of the application. To address this problem, we have developed a semantic data management layer for db4o which supports role modelling, associations and a declarative query language.
Detection of P300 Waves in Single Trials by the Wavelet Transform (WT)

The P300 response is conventionally obtained by averaging the responses to the task-relevant (target) stimuli of the oddball paradigm. However, it is well known that cognitive ERP components show a high variability due to changes of cognitive state during an experimental session. With simple tasks such changes may not be demonstrable by the conventional method of averaging the sweeps chosen according to task-relevance. Therefore, the present work employed a response-based classification procedure to choose the trials containing the P300 component from the whole set of sweeps of an auditory oddball paradigm. For this purpose, the most significant response property reflecting the P300 wave was identified by using the wavelet transform (WT). The application of a 5 octave quadratic B-spline-WT on single sweeps yielded discrete coefficients in each octave with an appropriate time resolution for each frequency range. The main feature indicating a P300 response was the positivity of the 4th delta (0.5-4 Hz) coefficient (310-430 ms) after stimulus onset. The average of selected single sweeps from the whole set of data according to this criterion yielded more enhanced P300 waves compared with the average of the target responses, and the average of the remaining sweeps showed a significantly smaller positivity in the P300 latency range compared with the average of the non-target responses. The combination of sweeps classified according to the task-based and response-based criteria differed significantly. This suggests an influence of changes in cognitive state on the presence of the P300 wave which cannot be assessed by task performance alone.
Individual Differences and Decision Making: When the Lure Effect of Gain Is a Matter of Size

The Iowa Gambling Task (IGT) is widely used in investigations of decision making. A growing number of studies have linked performance on this task to personality differences, with the aim of explaining the large degree of variability in healthy individuals' performance of the task. However, this line of research has yielded inconsistent results. In the present study, we tested whether increasing the conflict between short-term and long-term gains in the IGT can clarify personality-related modulations of decision making. We assessed performance on the original IGT as a function of the personality traits typically involved in risky decision making (i.e., impulsivity, sensation seeking, sensitivity to reward and punishment). The impact of these same personality traits was also evaluated on a modified version of the task in which the difference in immediate reward magnitude between disadvantageous and advantageous decks was increased, while keeping the net gain fixed. The results showed that only in this latter IGT variant were highly impulsive individuals and high sensation seekers lured into making disadvantageous choices. The opposite seems to be the case for participants who were highly sensitive to punishment, although further data are needed to corroborate this finding. The present preliminary results suggest that the IGT variant used in this study could be more effective than the original task at identifying personality effects in decision making. Implications for dispositional and situational effects on decision making are discussed.
Influence of Reduced Graphene Oxide on Effective Absorption Bandwidth Shift of Hybrid Absorbers

The magnetic nanoparticle composite NiFe2O4 has traditionally been studied for high-frequency microwave absorption with marginal performance towards low-frequency radar bands (particularly L and S bands). Here, NiFe2O4 nanoparticles and nanohybrids using large-diameter graphene oxide (GO) sheets are prepared via solvothermal synthesis for low-frequency wide bandwidth shielding (L and S radar bands). The synthesized materials were characterized using XRD, SEM, FTIR and microwave magneto dielectric spectroscopy. The dimension of these solvothermally synthesized pristine particles and hybrids lies within 30–58 nm. Microwave magneto-dielectric spectroscopy was performed in the low-frequency region in the 1 MHz-3 GHz spectrum. The as-synthesized pristine nanoparticles and hybrids were found to be highly absorbing for microwaves throughout the L and S radar bands (< −10 dB from 1 MHz to 3 GHz). This excellent microwave absorbing property induced by graphene sheet coupling shows application of these materials with absorption bandwidth which is tailored such that these could be used for low frequency. Previously, these were used for high frequency absorptions (typically > 4 GHz) with limited selective bandwidth.
Importance of endogenous extracellular matrix in biomechanical properties of human skin model

The physical and mechanical properties of cells modulate their behavior such proliferation rate, migration and extracellular matrix remodeling. In order to study cell behavior in a tissue-like environment in vitro, it is of utmost importance to develop biologically and physically relevant 3D cell models. Here, we characterized the physical properties of a single cell type growing in configurations of increasing complexity. From one human skin biopsy, primary dermal fibroblasts were isolated and seeded to give monolayer (2D model), spheroid (3D model poor in extracellular matrix) and tissue-engineered cell sheet (3D model rich in endogenous extracellular matrix). Living native human dermis tissue was used as a gold standard. Nanomechanical and viscoelastic properties at the cell scale were measured by atomic force microscopy (AFM) while biphoton microscopy allowed collagen detection by second harmonic generation and scanning electron microscopy helped in model morphological characterization. In all models, fibroblasts presented a similar typical elongated cell shape, with a cytoskeleton well-arranged along the long axis of the cell. However, elastic moduli of the tissue-engineered cell sheet and native dermis tissue were similar and statistically lower than monolayer and spheroid models. We successfully carried out AFM force measurements on 3D models such as spheroids and tissue-engineered cell sheets, as well as on living native human tissue. We demonstrated that a tissue-engineered dermal model recapitulates the mechanical properties of human native dermal tissue unlike the classically used monolayer and spheroid models. Furthermore, we give statistical evidence to indicate a correlation between cell mechanical properties and the presence of collagens in the models studied.
Automatic Deployment of Streaming Applications on Hybrid Architectures

Embedded applications are often streaming in nature and are frequently deployed on hybrid architectures that include multiple types of computing resources, such as chip multiprocessors and FPGAs. Such architectures can potentially exploit the unique features of a resource and can exploit pipelining and parallelism to achieve higher overall performance. However, applications are difficult to design, analyze and deploy on real hybrid systems.
Institute for Mathematical Physics Differential Twisted K-theory and Applications Differential Twisted K-theory and Applications

In this paper, we develop differential characters in twisted K-theory and use them to define a twisted Chern character. In the usual formalism the 'twist' is given by a degree threě Cech class while we work with differential twisted K-theory with twisting given by a degree 3 Deligne class. This resolves an unsatisfactory dependence on choices of representatives of differential forms in the definition of the Chern character map for twisted K-theory in the current literature. Twisted eta forms and twisted spin c structures are also defined. To show the efficacy of our point of view we use our approach to study D-brane charges on a compact Lie group with non-trivial twisting by a Deligne class.
Cutaneous and pulmonary nocardiosis in pemphigus vulgaris: a rare complication of immunosuppressive therapy

Pemphigus vulgaris (PV) is a chronic blistering disorder of the skin and mucous membranes, which is classified in the group of immunobullous skin diseases. Infectious diseases, in particular, septicemia caused by staphylococci and Pseudomonas aeruginosa , are the most common and severe complications of immunosuppressive therapy for PV. Infection by nocardia is a rare complication in PV. We report a new case of a patient suffering from such complication. A 56-year-old man with generalized bullous lesions on the skin and oral mucous membrane was admitted to the Department of Dermatology, St. Zahra University Hospital, Isfahan, in December 2001. On the basis of skin histopathology, direct and indirect immunofluorescence, the diagnosis was confirmed. The patient was treated with prednisolone (65 mg/day) and azathioprine (100 mg/day). Because of leukopenia and thrombocytopenia, azathioprine was discontinued. Therefore, the patient was subsequently treated with intravenous (i.v.) cyclophosphamide pulse therapy (500 mg, monthly) along with oral cyclophosphamide (50 mg/day) between pulses. After the disease was controlled, prednisolone was tapered. The disease relapsed when the dose of prednisolone was decreased to 30 mg/day. The period of relapse was treated by increasing the dose of prednisolone (65 mg/day), i.v. cyclophosphamide pulse (500 mg, monthly), and plasmapheresis (five times during 2 weeks). Because of inadequate response, intravenous immunoglobulin (IVIG) (0.4 g/kg/day, 5 days) was added. The disease was controlled by the above protocol. Again, the patient was referred to the department in February 2002, because of a soft tissue mass on the lateral aspect of his left arm. Two weeks before referral, a tender, skin-colored nodule developed on the above anatomic site. During the next 2 weeks, the lesion enlarged and covered all of the lateral aspect of the patient’s left arm. Physical examination showed a skin mass with well-defined border, 8 cm × 10 cm, skin colored, fluctuant, slightly tender, without any epidermal change on the lateral aspect of the left arm (Fig. 1). Fluid collection with pus density was detected in ultrasound. Sixty milliliters of yellow, pus-like fluid was drained by a large needle (Fig. 2). Smear with Gram stain and culture was performed on aspirated fluid and the patient was treated with oral ciprofloxacin (500 mg, b.i.d.) empirically. The pus smear and culture showed Gram-positive cocci with numerous polymorphonuclear neutrophil and coagulase-negative staphylococci, respectively. Two weeks later, the patient was referred again to the clinic because of recurrence of skin abscess on the same location beside a new abscess-like lesion (size, 3 cm × 3 cm) on the anterior aspect of his right thigh. He also complained of mild cough and dyspnea. The arm lesion was drained by incision and insertion of a Penrose drainage system. The thigh lesion was also drained by