Miracle-dz/UniFAR-FTUs huggingface dataset:
PAEDOPHILIA: PREVALENCE, SITUATION, AND PERSPECTIVES OF TREATMENT

Paedophilia is a specific disorder in a spectre of sexual affinities in humans, which is in the nomenclature of the World Health Organization in the group of sexual preference disorders or paraphilia. Due to mobility, inventiveness, and invisibility, there is no relevant statistical data about this deviation’s volume and extensiveness. This paper aims to determine the prevalence of paedophiles in the general population based on an anonymous survey, the number of processed perpetrators of sexual offenses toward children, and the number of unique visitors of the Internet “decoy”. The research data were gathered through an anonymous survey (the survey was created for this research purposes, and it was an indirect, written survey) that enveloped a total of 658 individuals (60.49% males and 39.51% females) through the creation of a virtual Internet profile (1095 visitors, 89.86% males and 10.14% females), as well as through the statistical data of the Ministry of Interior of the Republic of Serbia (MUP RS) and the Ministry of Justice of the Republic of Serbia (Directorate for Enforcement of Criminal Sanctions) over the last six years. The prevalence of paedophilia in the general population is 2.13%, and the majority is between 30 and 50 years of age. There are no relevant data on the treatment of paedophiles in penitentiary conditions. The number of submitted criminal charges for crimes with sexual violence elements toward children is much larger than the number of verdicts for the said acts. The number of crimes of sexual offenses against children in the analysed period was 1,288. Paedophilia is a complex disorder that poses a threat to public health. It is under-researched, and it calls for a multidisciplinary approach in research with the goal of preventing these forms of behaviour and the protection of children from sexual abuse.
Enhancing the performance and stability of organic solar cells using solution processed MoO3 as hole transport layer

Efficient and stable poly(3-hexylthiophene) (P3HT):indene-C60 bisadduct (ICBA) based bulk-heterojunction (BHJ) organic solar cells (OSCs) with solution processed MoO3 (s-MoO3) as hole transport layer were fabricated. We used a facile and cost-effective preparation method to obtain a MoO3 aqueous solution by thermal decomposition of (NH4)6Mo7O24·4H2O. The s-MoO3 ultra-thin film was treated in three different ways to compare the effects of the annealing mode: no annealing, 100 °C thermal annealing and ultraviolet (UV) annealing. The transmittance, surface morphology and film quality of the s-MoO3 film can be enhanced by UV annealing treatment, which is favorable to the performance of devices. The OSCs with UV annealing treated s-MoO3 as the hole transport layer exhibit a good power conversion efficiency (PCE) of 5.4% and better stability.
A Social Portrait of the Subprime Crisis

The economic consequences of the Covid-19 pandemic invite comparisons with previous global economic crises, not least the recent subprime crisis.1 This crisis, which began in the United States and took on global proportions in September 2008, following the bankruptcy of Lehman Brothers, has been studied by numerous economists who have highlighted its structural mechanisms, most notably the deregulation and globalization of financial markets (Brender and Pisani 2009), as well as their increasing hold over the real productive sphere.2 Its social and urban consequences, however, are less well known, with relatively few studies having examined this subject (Rugh and Massey 2010; Vorms 2009). Isaac Martin and Christopher Niedt’s 2015 work Foreclosed America fills this gap with regard to the US case, by focusing on the epicenter of the crisis and its original victims: first-time-buyer households evicted through foreclosure owing to their inability to honor their mortgage payments. Using unpublished data, Foreclosed America paints a detailed portrait of the social profiles and trajectories of households and neighborhoods hit by the subprime crisis— including lessons for other countries on the relative place of property, private savings, and solidarity in social-protection systems.
Landmarks as Beacons: Pedestrian Navigation Based on Landmark Detection and Mobile Augmented Reality

The prevalence of cloud computing, mobile devices as well as ubiquitous sensors enables citizens to produce, acquire, and utilize geo-referenced data for various Location-Based Services (LBS). Navigation as one of these services has been widely used by people. Currently, most navigation methods are map-based approaches that depend on turn-byturn instructions displayed in a map (Giannopoulos et al., 2015). Traditional practices are based on interactive charts (Rümelin et al., 2011) and turn direction concepts (Klippel and Montello, 2007). These map-based methods may lead to ambiguity (Amirian and Basiri, 2016) as people may have different spatial cognition and interpretations due to the isolation between the instructions and the environment (Rao et al., 2017). Landmarks are salient geographic objects when compared with objects in the surrounding area (Richter and Winter, 2014; Zhu and Karimi, 2015). Some studies in the field of spatial cognition showed that landmark, as one of the three forms of spatial knowledge, is of great importance for navigating humans in complex environments (Siegel and White, 1975; Werner et al., 1997; Zhu and Karimi, 2015). Users often tend to rely on landmarks during wayfinding since they are easy to recognize and usually situate along the route (Millonig and Schechtner, 2007). However, the conversion from salient landmarks into navigational cues remains a challenge. For instance, the actual visibility of some landmarks may be ignored when navigating, which may cause navigation interruptions (Millonig and Schechtner, 2007).
TECHNICAL EFFICIENCY OF PADDY’S FARMING IN VARIOUS TYPES OF PADDY’S SEEDS IN INDONESIA

The increasing need for food along with increasing population is one of the problems that must be resolved by Indonesia. The government is trying to increase rice production and productivity by using certified seeds. Certified seeds is hyphotized affect to technical efficiency of rice farming. The objectives of this studies are to analyze the level of technical efficiency and to identify the factors that influence the technical efficiency of rice farming in various types of main sources of rice seeds in Indonesia. The study uses secondary data that obtained from Central Bureau of Statistic (BPS), the 2014 Paddy Farm Household Survey (SPD 2014). Data were analyzed using stochastic frontier. The results showed that the average technical efficiency level achieved by farmers in rice farming is 0,656 or less than 0,70 (<0,70) so it can be said that rice farming in Indonesia is still technically inefficient. Factors that affecting the technical efficiency of rice farming in various types of main sources of rice seeds in Indonesia were age, formal education, dummy participation of agricultural extension, and dummy certified seeds.
Knowledge Marketplaces: An Analysis of the Influence of Business Models on Instructors’ Motivations and Strategies

Unlike MOOC platforms such as Coursera or edX, which typically partner with institutions of higher education, online knowledge marketplaces allow anyone to broadcast courses and charge for them. In this article, we investigate, through a mixed-method approach, the motivations and strategies of the instructors of Udemy and Skillshare. Semi-structured interviews and a quantitative analysis of the characteristics of Skillshare’s courses, obtained using a Web scraper, suggest that while a significant proportion of the marketplace’s instructors are outreach driven, the majority are income driven. They develop strategies to maximize their revenues, notably by adapting the characteristics of their courses, such as the number of videos, to the business model of the platform. Courses are shorter on Skillshare than on Udemy, where instructors’ incomes are proportional to the number of registrations. We hypothesize that the latter platform’s business model incentivizes instructors to create longer courses in order to attract wider audiences.
The Acupuncture Effect for Low Back Pain; Biochemical and Protein Profile Analysis

Low back pain (LBP) is one of the common symptoms experienced by some of the world community. Acupuncture as a method of healing a disease offers a solution for LBP symptom. This study aimed to determine the effect of acupuncture with local and Yamamoto New Scalp Acupuncture (YNSA) points with biochemical analysis related to total protein, albumin, and globulin, and analysis of blood serum protein profiles using the SDS-PAGE method. This research was conducted using sterile acupuncture needles that inserted in patients with several local points, namely BL22 (Sanjiaoshu), BL23 (Shenshu), BL24 (Qihaishu), BL25C (Dachangshu), and BL26C (Guanyuanshu) and combined with the YNSA points through somatotope D points and extra lumbar points H and I. Blood serum was collected for total protein, albumin, and globulin analysis. That blood serum was also used for protein profile analysis using Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) method. The results showed that six times of acupuncture treatments gave positive correlation in total protein, albumin, and globulin. Analysis of blood serum protein profiles using SDS-PAGE showed a protein band of about 12 KDa and it might be a interleukin-13 protein. The results were expected can be useful as scientific information especially related to acupuncture for LBP treatment and this of about 12 KDa protein band can be used as biomarker candidates for the symptoms.
Common and Disorders-Specific Cortical Thickness Alterations in Internalizing, Externalizing and Thought Disorders in the Preadolescents of the ABCD Study

Objective: Overlap of brain changes across mental disorders has reinforced transdiagnostic models. However, the developmental basis for this overlap is unclear as are neural differences among internalizing, externalizing and thought disorders. These issues are critical to inform the theoretical framework for hierarchical transdiagnostic psychiatric taxonomy. Methods: This study involved 11,878 preadolescents (9-10 years) with baseline and 2-year follow-up data (n=6571) from the Adolescent Brain and Cognitive Development Study release 3.0. Linear mixed models were implemented in comparative and association analyses. Genome-wide association analysis, gene set enrichment analysis and cell type specificity analysis were performed on regional cortical thickness (CT) across 4,716 unrelated European youth. Results: Youth with externalizing or internalizing disorders, but not thought disorders, exhibited significantly thicker cortex than controls. Externalizing and internalizing disorders shared thicker CT in left pars opercularis and caudal middle frontal gyrus, which related to lower cognitive performance. Somatosensory and primary auditory cortex were uniquely affected in externalizing disorders; primary motor cortex and higher-order visual association areas (fusiform and inferior temporal gyrus) were uniquely affected in internalizing disorders. Baseline CT in one externalizing-specific region (left isthmus of cingulate cortex) related to externalizing behaviors at both baseline and 2-year follow-up. Genes associated with CT in common and disorders-specific regions were also implicated in related diagnostic families. Microglia were the cell-type associated with CT for both externalizing/internalizing while dopaminergic/ glutamatergic/GABAergic cells related only to externalizing-specific regions. Conclusions: Distinct anatomical trajectories relevant to internalizing/externalizing phenotypes may result from unique genetic and cell-type changes, but these occur in the background of significantly shared morphological variance.
Relative Thermal Stability of Thiolate- and Selenolate-Bonded Aromatic Monolayers on the Au(111) Substrate

The thermal stability of self-assembled monolayers (SAMs) is of fundamental importance for the majority of their applications. It strongly depends on the type of chemical group used for bonding the molecules forming the SAMs to the selected substrate. Here, we compare the impact of using S and Se bonding groups on the thermal stability of aromatic model SAMs based on naphthalene, containing a polar substituent, and formed on a Au(111) substrate. Using a combination of secondary ion mass spectrometry (SIMS) and X-ray photoelectron spectroscopy (XPS) while heating the samples, we show that the thermal stability of S-bonded SAMs is higher although the bonding between Se and the Au substrate is stronger. This seeming contradiction is found to result from a higher stability of the S–C compared to the Se–C bond. The latter forms the weakest link in the SAMs with Se anchor and, thus, controls its thermal stability. These conclusions are supported by state-of-the art dispersion-corrected density functional theory.
Interventions in social networks: Impact on positive mood and network dynamics

Results from two studies on longitudinal friendship networks exploring the impact of a positive psychology based gratitude intervention on the social network dynamics in relation to positive and negative affect are presented. The interventions are designed to increase positive affect and decrease negative affect in the subjects. The first study involves administering intervention to the whole network while the second study involves selecting a subgroup of individuals as ‘agents of change’. We analyse the data using stochastic actor modelling techniques to identify resulting network changes, impact on positive and negative affect and potential contagion of mood within the population. The first study results in a significant increase in positive and decrease in negative affect between baseline and post intervention measures across the population. We find homophily with regard to positive and negative affect but no evidence of contagion is found. Network became more volatile along with a fall in rate of change of negative affect. The best broadcasters in the population tended to be the ones with least negative affect levels. The second study involved two groups, and in each group a certain number of individuals were chosen as recipients of the intervention. There was evidence of positive affect contagion in the group with low initial level of negative affect and contagion in negative affect in the group with high initial level. Also, different positive and negative affect dynamics in intervention and non-intervention part of the networks were observed in the two groups.
Exxon Valdez Oil Spill Long-Term Herring Research and Monitoring Program Final Report Non-lethal sampling: In situ estimation of juvenile herring sizes

This project examined the use of a remotely operated vehicle to collect species and size information of forage fish. A Seamor Marine remotely operated vehicle with a 300 m fiber optic tether, with an integrated imaging sonar and a live-feed camera with recording capabilities, was used to collect data for this project. Fish species identification was based on the camera images. The imaging sonar was then used to provide information about the forage fish schools, such as the size distribution. The remotely operated vehicle was deployed from the R/V Auklet during a series of cruises between the fall of 2013 and spring 2015. The remotely operated vehicle was deployed under ice shelves to examine if juvenile herring were using them as a habitat area. Fish under ice were smaller than those in open water. Fish lengths inferred by the sonar measurements were significantly less than those based on trawls, but the inferred lengths were within the range observed for that age of herring. We were able to distinguish characteristics between schools and bays. We did not observe length stratification within age-0 schools.
FORMATION OF CLATHRATE HYDRATES OF HYDROCHLOROFLUOROCARBON 141B IN THE DEEP BOREHOLE AT VOSTOK STATION (ANTARCTICA) IN THE COURSE OF THE UNSEALING OF SUBGLACIAL LAKE VOSTOK

1 Nikolaev Institute of Inorganic Chemistry, SB RAS, 3, Acad. Lavrentiev ave., Novosibirsk, 630090, Russia; manakov@niic.nsc. ru 2 Arctic and Antarctic Research Institute, 38, Beringa str. , St. Petersburg, 199387, Russia; lipenkov@aari.ru 3 Limnological Institute, SB RAS, 3, Ulan-Batorskaya str. , Irkutsk, 664033, Russia; khodzher@lin.irk. ru 4Institute of Earth Science, St. Petersburg State University, 33-35, 10th Line of Vasilievsky Ostrov, St. Petersburg, 199178, Russia
Leaf Segmentation Challenge Using UNET

— in this paper, we're concentrating at the hassle of segmenting tobacco and arbidopsis leaves from an RGB photo, an vital assignment in plant phenotyping.to complete this project this venture, we use ultra-modern deep gaining knowledge of architectures: UNET, a convolutional neural community for initial segmentation. assessment is done on the leaf segmentation task dataset at CVPPP-2017.despite the fact that the small variety of education samples on this dataset, in comparison to standard deep mastering photo sets, we attain exceptional overall performance on segmenting leaves from the inside the from of binary segmentation as a whole and we need to paintings in addition to be counted the range of leaves. comparing evaluation supplied against strategies evaluated on the previous opposition datasets.
Numerical Simulation of Flow past a Circular Cylinder between Parallel Walls

Abstract: This study has been undertaken to investigate the flow past a circular cylinder placed between parallel wall to see the effect of wall confinement on flow patterns. The fluid flow is numerically simulated by finite difference method, based on vorticitystream function formulation for Reynolds numbers in the range consistent with two dimensional assumption and gap ratios (G/D), ratio of gap to diameter in the range between 0.5 and 2.0. The transitions from steady flow to a periodic vortex shedding regime are investigated. The results are consistent with previous investigations the suppression of vortex shedding for a cylinder placed near one wall. The unsteady vortex shedding regime changes, from a pattern similar to the von Karman vortex street when the body is in about the centre of the walls. The vortex shedding influences by wall opposite sign vorticity as the body approaches one wall. As the cylinder approaches nearest wall, cylinder vorticity elongates with the interactions from wall vorticity for lower Reylonds number. As Reynolds number increases suppression of shedding noticed as the cylinder vortices interacts with wall vorticity.
Training Data Set Refinement for the Machine Learning Potential of Li-Si Alloys via Structural Similarity Analysis

Machine learning potential enables molecular dynamics simulations of systems beyond the capability of classical force fields. The traditional approach to develop structural sets for training machine learning potential typically generate a great number of redundant configurations, which will result in unnecessary computational costs. This work investigates the possibility of reducing redundancy in an initial data set containing 6183 configurations for a Li-Si machine learning potential. Starting from the initial data set, we constructed a series of subsets ranging from 25 to 1500 configurations by combining a structural similarity analysis algorithm and the farthest point sampling method. Results show that the machine learning potential trained from a data set containing 400 configurations can achieve an accuracy comparable to the one developed from the initial data set of 6183 configurations in describing potential energies, atomic forces, and structural properties of Li-Si systems. In addition, the redundancy reducing approach also demonstrates advantages over the classic stochastic method for constructing a concise training data set for Li-Si systems.
Software-hardware co-design for fast and scalable training of deep learning recommendation models

Deep learning recommendation models (DLRMs) have been used across many business-critical services at Meta and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper, we present Neo, a software-hardware co-designed system for high-performance distributed training of large-scale DLRMs. Neo employs a novel 4D parallelism strategy that combines table-wise, row-wise, column-wise, and data parallelism for training massive embedding operators in DLRMs. In addition, Neo enables extremely high-performance and memory-efficient embedding computations using a variety of critical systems optimizations, including hybrid kernel fusion, software-managed caching, and quality-preserving compression. Finally, Neo is paired with ZionEX, a new hardware platform co-designed with Neo's 4D parallelism for optimizing communications for large-scale DLRM training. Our evaluation on 128 GPUs using 16 ZionEX nodes shows that Neo outperforms existing systems by up to 40× for training 12-trillion-parameter DLRM models deployed in production.
Cross-Document Language Modeling

We introduce a new pretraining approach geared for multi-document language modeling, incorporating two key ideas into the masked language modeling self-supervised objective. First, instead of considering documents in isolation, we pretrain over sets of multiple related documents, encouraging the model to learn cross-document relationships. Second, we improve over recent long-range transformers by introducing dynamic global attention that has access to the entire input to predict masked tokens. We release CDLM (Cross-Document Language Model), a new general language model for multi-document setting that can be easily applied to downstream tasks. Our extensive analysis shows that both ideas are essential for the success of CDLM, and work in synergy to set new state-of-the-art results for several multi-text tasks. Code and models are available at https://github.com/aviclu/CDLM.
Effects of Cover Crops on Soil Quality: Selected Chemical and Biological Parameters

ABSTRACT Cover crops improve soil quality properties and thus land productivity. We compared soil chemical and biological changes influenced by hairy vetch (Vicia villosa Roth.) and cereal rye (Secale cereal) cover crops grown in Menfro silt loam (fine-silty, mixed, superactive, mesic Typic Hapludalfs), Mexico silt loam (fine, smectitic, mesic Vertic Epiaqualfs), or sand in the greenhouse. Cover crop biomass, soil β-glucosidase, β-glucosaminidase, and fluorescein diacetate (FDA) hydrolase activities, and soil chemical properties were measured at six, nine, and twelve weeks after planting. Cover crop biomass increased with highest (p < 0.0001) yields for hairy vetch and cereal rye in Menfro and Mexico soils, respectively. β-glucosaminidase, FDA, organic carbon (C), total nitrogen (N), and total phosphorus (P) contents significantly decreased in all soils for both cover crops. However, β-glucosidase activity significantly increased (p < 0.0001). Long-term field studies are needed to evaluate soil quality improvement under cover crops, especially for soils with marginal organic matter and fertility.