Miracle-dz/UniFAR-FTUs huggingface dataset:
A general approach to bridge the reality-gap

Employing machine learning models in the real world requires collecting large amounts of data, which is both time consuming and costly to collect. A common approach to circumvent this is to leverage existing, similar data-sets with large amounts of labelled data. However, models trained on these canonical distributions do not readily transfer to real-world ones. Domain adaptation and transfer learning are often used to breach this "reality gap", though both require a substantial amount of real-world data. In this paper we discuss a more general approach: we propose learning a general transformation to bring arbitrary images towards a canonical distribution where we can naively apply the trained machine learning models. This transformation is trained in an unsupervised regime, leveraging data augmentation to generate off-canonical examples of images and training a Deep Learning model to recover their original counterpart. We quantify the performance of this transformation using pre-trained ImageNet classifiers, demonstrating that this procedure can recover half of the loss in performance on the distorted data-set. We then validate the effectiveness of this approach on a series of pre-trained ImageNet models on a real world data set collected by printing and photographing images in different lighting conditions.
Evolving Intelligent Reflector Surface Toward 6G for Public Health: Application in Airborne Virus Detection

While metasurface-based intelligent reflecting surfaces (IRS) are an important emerging technology for future generations of wireless connectivity in its own right, plans for the mass deployment of these surfaces motivate the question of their integration with other new and emerging technologies that would require such widespread deployment. This question of integration and the vision of future communication systems as an invaluable component for public health motivated our new concept of Intelligent Reflector-Viral Detectors (IR-VD). In this novel scheme, we propose deployment of intelligent reflectors with strips of receptor-based viral detectors placed between the reflective surface tiles. Our proposed approach encodes information of the presence of the virus by flicking the angle of the reflected beams, using time variations between the beam deviations to represent the messages. This information includes the presence of the virus, its location and load size. The article presents simulations to demonstrate the encoding process that represents the number of virus particles that have bound to the IR-VD.
Attribute Adaptive Margin Softmax Loss using Privileged Information

We present a novel framework to exploit privileged information for recognition which is provided only during the training phase. Here, we focus on recognition task where images are provided as the main view and soft biometric traits (attributes) are provided as the privileged data (only available during training phase). We demonstrate that more discriminative feature space can be learned by enforcing a deep network to adjust adaptive margins between classes utilizing attributes. This tight constraint also effectively reduces the class imbalance inherent in the local data neighborhood, thus carving more balanced class boundaries locally and using feature space more efficiently. Extensive experiments are performed on five different datasets and the results show the superiority of our method compared to the state-of-the-art models in both tasks of face recognition and person re-identification.
Collaboratively Optimizing Power Scheduling and Mitigating Congestion using Local Pricing in a Receding Horizon Market

A distributed, hierarchical, market based approach is introduced to solve the economic dispatch problem. The approach requires only a minimal amount of information to be shared between a central market operator and the end-users. Price signals from the market operator are sent down to end-user device agents, which in turn respond with power schedules. Intermediate congestion agents make sure that local power constraints are satisfied and any potential congestion is avoided by adding local pricing differences. Our results show that in 20% of the evaluated scenarios the solutions are identical to the global optimum when perfect knowledge is available. In the other 80% the results are not significantly worse, while providing a higher level of scalability and increasing the consumer's privacy.
Deuteron production in AuAu collisions at 
sNN=7–200
 GeV via pion catalysis

We study deuteron production using no-coalescence hydrodynamic + transport simulations of central AuAu collisions at $\sqrt{s_{NN}} = 7 - 200$ GeV. Deuterons are sampled thermally at the transition from hydrodynamics to transport, and interact in transport dominantly via $\pi p n \leftrightarrow \pi d$ reactions. The measured proton, Lambda, and deuteron transverse momentum spectra and yields are reproduced well for all collision energies considered. We further provide a possible explanation for the measured minimum in the energy dependence of the coalescence parameter, $B_2(\sqrt{s_{NN}})$ as well as for the difference between $B_2(d)$ for deuterons and that for anti-deuterons, $B_2(\bar{d})$.
Marketing and communication Competitive session Exploring the effect of empathy , attributional complexity and cognitive style on adaptive selling behaviour

This pilot study examines the role of empathy, attributional complexity and cognitive style on adaptive selling behavior, which is important in cross-cultural encounters. The findings show that that empathy and attributional complexity are positively related to adaptive selling behavior. Salespeople who prefer an intuiting style of information-intake have higher levels of attributional complexity than those who prefer a sensory style. Salespeople who prefer a feeling style of information-processing have higher levels of empathy than those who prefer a thinking style. Finally, for salespeople who have a low learning orientation (in a selling situation), incremental increases in empathy and attributional complexity have a greater impact on adaptive selling behaviours than incremental increases for those salespeople with higher learning orientation.
Reducing Implicit Cognitive Biases Through the Performing Arts

The aim of the present research was to test whether involvement in a 14-days training program in the performing arts could reduce implicit biases. We asked healthy participants to complete an Implicit Association Test (IAT) to assess biased attitudes to physical illness in two separate sessions, before and after the training program. Two separate control groups matched by age, gender and educational level completed the two IAT sessions, separated by same number of days, without being involved in the training program. Results showed that participants who were involved in the training program reduced their implicit bias toward illness measured through IAT in the second session. This reduction in IAT measures was not observed in the control samples, despite the two IAT measures being matched in temporal delay with the experimental group. These findings suggest that an interventional program based on the performing arts could be effective in reducing levels of implicit biases among the general population.
Characteristics of an acoustic community: Puerto Rican frogs of the genus Eleutherodactylus

The advertisement calling of 14 of the 15 species of Eleutherodactylus known from the main island of Puerto Rico was studied. When and where the species call and the characteristics of their advertisement calls are described. Calling assemblages of 4 to 6 species were found to be common, assemblages of more than 8 species were rare. The maximum numbers of species heard calling in one assemblage were at mid-elevations, at the border between forest and open habitat. Within an assemblage calls of different species differ in both dominant frequency and temporal patterning (duration and number of notes and durations of intervals). Potentially, differences in both frequency and temporal pattern in these frogs may contribute to species recognition and to the minimization of interference between the calls of different species in the same assemblage.
Citizen Participation in the Government Budget Process: The Case of Kibaha District Council, Tanzania

The study aimed at examining citizens’ participation in the government budget process. Specifically, the study intended to find out the local government officials’ perception on involvement of citizens in the budget process and establish the challenges hindering citizens’ participation in the budget process. This was an exploratory research which used qualitative research methods to explore respondents’ opinions and perception towards citizen participation in the budget process. Focus group discussions (6) were employed using small groups of 10 participants; whereby a total of 60 respondents were involved. Besides, the study employed Key Informants Interviews (27), Observation and Desk Reviews to further triangulate the findings from the Focus Group Discussions. The respondents were purposively selected based on their experience and knowledge on government budgeting process and citizens above the age of 18. The findings revealed that, local government officials believed in the importance of citizen to participate in the budgeting process but Obstacles and Opportunity to Development (O&OD) was not fully implemented, O&OD process was not well understood by the local government leaders at the lower level; and the average citizens generally lacked knowledge on the budgeting process since the whole process was monopolized by the leaders. The study recommended that, citizens should be educated and sensitized on the budget process along with improved service delivery to the citizens in order to persuade them to participate in the budget process; and lastly, the government should allocate more resource to implement O&OD at the government local levels.
Generic Representation Learning for Dynamic Social Interaction

Social interactions, such as eye contact, speaking and listening, are ubiquitous in our life and carry important clues of human’s social status and psychological state. With evolving dynamics fundamentally different from social relationships, the complex interactions among a group of people are another informative resource to analyze patterns of social behaviors and characteristics. Despite the great importance, previous approaches on extracting patterns from such dynamic social interactions are still underdeveloped and overly task-specific. We fill this gap by proposing a temporal network formulation of the problem, together with a representation learning framework, temporal network-diffusion convolution networks (TNDCN). The framework accommodates the many downstream tasks with a unified structure: we creatively propagate people’s fast-changing descriptive traits among their evolving gazing networks with specially designed (1) network diffusion scheme and (2) hierarchical pooling to learn high-quality embeddings for downstream tasks using a consistent structure and minimal feature engineering. Analysis show that (1) can not only capture patterns from existed interactions but also people’s avoidance of interactions that turn out just as critical. (2) allows us to flexibly collect different fine-grained critical interaction features scattered over an extremely long time span, which is also key to success while it empirically fails almost all the previous temporal GNNs based on recurrent structures. We evaluate our model over three different prediction tasks, detecting deception, dominance and nervousness. Our model not only consistently outperforms previous baselines but also provides good interpretation by implying two important pieces of social insight derived from the learned coefficients.
Deep Learning Based Hybrid Precoding For Millimeter Wave Massive MIMO Systems

- The spatial diversity offers advantages when Multiple-Input Multiple-Output (MIMO) antenna techniques are considered as compared to traditional point to point MIMO systems. In massive MIMO technology, the Base Station (BS) equipped with large number of antennas serves many users in the same time-frequency network and therefore, it is a promising candidate technology for next generations of wireless systems. Because of the multiplexing gain and the array gain, huge performance can be accomplished with massive antenna arrays
Structural Bot Detection in Social Networks Structural Bot Detection in Social Networks

Social network platforms are a major part of toady’s life. They are usually used for entertainment, news, advertisements, and branding for businesses and individuals alike. However, use of automated accounts, also known as bots, pollute this environment and avoid having a reliable clean online world. In this work, I address the problem of detecting bots in online social networks.
Impact on Capacity Bounds under Higher Order Hardware Impairments for MIMO Configurations: Novel Approaches

: The massive dimension antenna arrays can lead to enhancement in the capacity and spectral efficiency of the mobile cellular networks. The major challenge of massive MIMO design is degradation in capacity bounds in the presence of hardware impairments caused due to distortion noise and non linear devices. Thus, system must be designed for the worst case of impairments loses. This paper considers the massive MIMO device for the transmission and reception of the individual data. Initially paper contribute to address major problem and challenges of large MIMO designing, which can reduce correlations between transmitting channels with increasing the antenna dimensions. Thus, this paper contributed to evaluate the performance of such Massive MIMO transceiver under the exposure of higher degree of the hardware impairments with different level of the signal to noise ratio (SNR). Paper also addressed number of reasons of hardware impairments in the massive MIMO system. The channel capacity bounds are examined against the N individual antennas to compare the system performance. The paper assume LMMSE channel estimation model for cellular mobile network to model up link and down link. As another contribution, performance of MIMO configurations are evaluated for distinctive degree of higher Kappa values for hardware impairments of every individual antenna. Finally the degree of overall performance degradation under worst case of hardware is evaluated for capability bounds. Higher performance loss is noted under the higher impairments level of the MIMO system model. But the capacity performance is increased by around the 4 times towards the optimum with the proposed massive MIMO structure with N=64.
INEQUALITY OF OPPORTUNITY IN SPAIN: NEW INSIGHTS FROM NEW DATA

Modern theories of justice consider Inequality of Opportunity (IO), the part of overall inequality explained by individual circumstances (factors beyond the individual control, like socioeconomic background), as the truly concept of unfair inequality. In addition, recent empirical studies have found that IO harms growth. Then, given the big increase in income inequality in Spain during the last decade (now one of the highest levels in the EU), how large is IO in Spain? By using a novel database from the Centro de Investigaciones Sociológicas (CIS) questionnaire on ‘Social inequality and social mobility in Spain’, we observe that the share of IO is 44% of overall inequality (Gini index). By circumstances, we find that about 90% of IO is due to parental education and occupation, the type of school attended, the gender of the household’s head and the size of the household. In addition, it is found that a large share of IO is channeled through the occupation and, especially, the level of education of the individual. These findings are consistent with the low levels of relative mobility in education and occupation observed in the database for Spain (2017).
Components of host plant resistance to insect pests with specific emphasis on spotted stem borer, Chilo partellus in maize

The spotted stem borer, Chilo partellus (Swinhoe) (Lepidoptera: Crambidae) is an important pest of maizein Asia. Host plant resistance is one of the effective way to minimise crop losses due to insect pests. Various morphological and biochemical factors of host plant lead to the development of resistance/ susceptibility in insects. The host plant resistance can be studied through the establishment and orientation behaviour which may be constitutive or induced.Biochemical constituents both in terms of quantities and proportions to each other in host plant have a great influence on growth, development, survival and reproduction of insects. More importantly, the performance and abundance of herbivores is attributed to the variations in host plant quality being determined by nutritional composition, allele chemistry and specific anatomical features The ROS react with wide range of molecules leading to membrane destruction, lipid peroxidation, causing pigment co-oxidation and membrane destruction. In order to compensate oxidation burst due to production of ROS, plants have evolved complex protective mechanism for scavenging ROS, which include small molecular antioxidants and enzymatic components. In this series there are several naturally occurring plant cell antioxidants/enzymes like catalases, ascorbic acid oxidase, ascorbic acid peroxidase, phenyl ammonia lyase and tyrosine ammonia lyase; and constitutive plant defense compounds such as phenolics, flavonoids, tannins, chlorophyll and carotenoid derivatives which could be potential plant defence factors against herbivores.
GENETIC DIVERSITY ANALYSIS OF BRINJAL (SOLANUM MELONGENA L.) USING RAPD MARKERS

An experiment was conducted at the Horticulture Farm, Department of Horticulture, Bangladesh Agricultural University, Mymensingh to study the variability of 12 selected accessions of brinjal using morphological traits and RAPD. Molecular characterization and diversity study was conducted using RAPD markers. Amplification with 5 decamer primers produced 54 RAPD markers of which 49 (89.56%) were polymorphic and 5 (10.44%) were monomorphic. The highest genetic distance (0.9445) and the lowest genetic identity (0.3889) were observed in the accessions SM59 vs. SM11 combination. The lowest genetic distance (0.1388) was observed between the accessions SM22 and SM29 and higher genetic identity was also observed in this combination. Dendrogram was constructed from genetic distance and 12 brinjal accessions fall in five clusters. Thus the RAPD analysis provided an effective method in investigating genetic variation and relatedness in twelve
Interactive comment on “ Modeling micro-topographic controls on boreal peatland hydrology and methane fluxes ” by F . Cresto Aleina

3. P 10197, line 15-16: This is not quite true. In addition to Baird et al. (2009), Bohn et al. (2007), Bohn and Lettenmaier (2010), and Bohn et al. (2013) specifically examined the effects of water table heterogeneity on methane emissions (not just water table, as you imply on lines 17-18) from high-latitude peatlands, albeit restricted to West Siberia. While the first two papers used a TOPMODEL approach, Bohn et al. (2013) considered hummocks and hollows. In addition, Bohn et al. (2013) considered the impoundment of surface water (although not via the rigorous method you employed), which raised the water table in hummocks and hollows. What is new/novel in your approach is that you are handling lateral flow through the peatland in a process-based way (Bohn et al 2013 treated all hummocks and hollows as identical to a single hummock and hollow, without considering lateral differences and flow between them, therefore their approach was not completely process-based). Your approach is therefore much more realistic than any previous approach that I am aware of. So, while I agree that your approach is novel, I ask that you clarify how your approach is novel and different from the previous approaches.
THE INSTITUTE OF CHARTERED ACCOUNTANTS OF NIGERIA

This research investigates whether firms’ performance (FP) enhances Web-based Environmental Disclosure (WED). This study is very fundamental because it presents some of the first empirically tested evidence of the effects of FP on WED employing firms listed on the Nigeria Stock Exchange (NSE). The findings indicate an insignificant negative relationship between WED and EPS on one hand and an insignificant positive relationship between WED and ROTA on the other. The study also indicates that the average disclosure content over the study period (2010 – 2013) is 25.76%, which is very low. It was recommended amongst others that regulatory regime is considered mandating listed firms to own websites and dedicate separate pages on their corporate websites for solely reporting environmental events.
Clinical signs, prevalence, and hematobiochemical profiles associated with Anaplasma infections in sheep of North Iraq

Background and Aim: Anaplasma infection is a worldwide prevalent condition that causes significant economic losses in affected flocks. This study was conducted to determine the prevalence and clinical signs associated with ovine anaplasmosis as well as the hematological and biochemical changes associated with the disease in natural infection in North Iraq. Materials and Methods: A total of 420 sheep were appropriately examined, and the clinical signs were documented accordingly. Blood samples were collected and subjected to parasitological, hematological, and biochemical analyses. Results: Anaplasma-infected sheep displayed the following clinical signs: Paleness of the mucous membrane, bloody diarrhea, emaciation, pyrexia, jaundice, nasal discharge, coughing, loss of wool, nervous signs, hemoglobinuria, and lacrimation. The prevalence of Anaplasma infection was 66.19%, and female sheep were significantly (p<0.05) more infected than male sheep. The hematological and biochemical parameters were significantly different between Anaplasma-positive and Anaplasma-negative sheep. Conclusion: Anaplasma infection among sheep is a significant concern in North Iraq considering its prevalence, clinical signs, and hematological and biochemical findings, which entirely causes significant debilitating effects on sheep productivity. It is important to pay more attention toward managing tick infestation among sheep to reduce the occurrence of this rickettsial disease for a more robust livestock sector of the Iraqi economy.
VOLUMETRIC MULTIBEAM SONAR MEASUREMENTS OF FISH, ZOOPLANKTON, AND TURBULENCE

In late 2002 an evaluation of the mid-water survey capability of a high-resolution multibeam sonar (RESON SeaBat 8125) was performed. This was conducted as part of a larger investigation of zooplankton aggregations in Knight Inlet, B.C., and included simultaneous measurements with a conventional, three-frequency (38, 120, and 200 kHz), calibrated echo-sounder system. This multibeam sonar, adapted from a standard bathymetric system, operated at 455 kHz and provided 240 one-half-degree beams in the across-track plane with a one-degree along-track beam angle. The multibeam sonar was able to provide well-resolved mid-water images of fish schools (likely juvenile herring), crustacean zooplankton (dominantly euphausiids), and near-surface turbulent micro-structure features. Close comparisons with the echo-sounders confirmed the multibeam calibrations, allowing assessment of the multibeam volumetric sampling capabilities.