Miracle-dz/UniFAR-FTUs huggingface dataset:
Naturalness of electroweak physics within minimal supergravity

Low energy supersymmetry is motivated by its use as a solution to the hierarchy problem of the electroweak scale. Having motivated this model with naturalness arguments, it is then necessary to check whether the experimentally allowed parameter space permits realisations of the model with low fine tuning. The scope of this thesis is a study of naturalness of the electroweak physics in the minimal supergravity model. The latest experimental constraints are applied, and the fine tuning is quantitatively evaluated for a scan across the parameter space. The fine tuning of the electroweak scale is evaluated at 2-loop order, and the fine tuning of the neutralino dark matter thermal relic energy density is also determined. The natural regions of the parameter space are identified and the associated phenomenology relevant for detection discussed. Naturalness limits are also found for the parameter space and spectrum. The minimum fine tuning found is 1 part in 9 when dark matter constraints are neglected, and 1 part in 15 when dark matter constraints are satisfied. For both cases, the minimum fine tuning is found for a Higgs mass of 115 GeV irrespective of whether the Higgs mass constraint is applied or not. The most natural spectrum includes light superpartner fermions, and heavy superpartner scalars. Minimal supergravity currently remains viable with respect to naturalness and a natural realisation may be discovered within the next couple of years.
Socialization of prevention of domestic violence in the district X community

Participants numbered 35 people consisting of residents and posyandu cadres, aged 20-55 years, married and unmarried from 3 villages in District X. Based on the results of observations, interviews, and giving Aggression Questionnaire as screening obtained data that in the region these are areas that are vulnerable to physical violence. This is also supported by interviews with residents and posyandu cadres that they lack of knowledge related to other forms of violence and how to prevent other violence from happening. Preventive socialization is carried out in 4 sessions. The results of the socialization showed the mean value before the intervention was 2.63 and after the intervention it was 7.00 with sig. p> . 000 which means an increase in understanding and knowledge related to violence through psychoeducation.
Molecular Characterization of ﬂiD Gene Encoding Flagellar Cap and Its Expression among Clostridium difﬁcile Isolates from Different Serogroups

The ﬂiD gene encoding the ﬂagellar cap protein (FliD) of Clostridium difﬁcile was studied in 46 isolates belonging to serogroups A, B, C, D, F, G, H, I, K, X, and S3, including 30 ﬂagellated strains and 16 nonﬂagellated strains. In all but three isolates, ampliﬁcation by PCR and reverse transcription-PCR demonstrated that the ﬂiD gene is present and transcribed in both ﬂagellated and nonﬂagellated strains. PCR-restriction fragment length polymorphism (RFLP) analysis of ampliﬁed ﬂiD gene products revealed interstrain homogeneity, with one of two major patterns (a and b) found in all but one of the strains, which had pattern c. A polyclonal monospeciﬁc antiserum raised to the recombinant FliD protein reacted in immunoblots with crude ﬂagellar preparations from 28 of 30 ﬂagellated strains but did not recognize FliD from nonﬂagellated strains. The ﬂiD genes from ﬁve strains representative of the three different RFLP groups were sequenced, and sequencing revealed 100% identity between the strains with the same pattern and 88% identity among strains with different patterns. Our results show that even though FliD is a structure exposed to the outer environment, the ﬂagellar cap protein is very well conserved, and this high degree of conservation suggests that it has a very speciﬁc function in attachment to cell or mucus receptors. Microenvironmental could induce the production of ﬂagella and gut by difﬁcile . Important be concerning the exact role of ﬂagellar in and their vaccine
Development of Pre- and Postharvest Techniques to Produce Safe Baby Leaf Vegetables in a Plant Factory

This study was conducted to develop preharvest techniques at each cultivation stage in a plant factory for improving the safety and yield of baby leaf vegetables and postharvest techniques for cleaning them. In the first chapter of this thesis, seeds of tat soi, romaine lettuce, and beet were sterilized with electrolyzed water (EW) and chlorine (CL) for 5 and 10 min. Microbial populations of the sterilized
Improvement of a Distribution System Using a Heuristic Method: A Case Study

In this paper, we consider a two-echelon distribution system in Thailand. Currently, this system consists of 7 facilities, 77 distribution centers, and 928 retailers. The company would like to redesign the distribution system in order to minimize total travelling distance. The decisions for the company are 1) locating distribution centers, 2) allocating distribution centers to each facility and allocating retailers to each distribution center, and 3) assigning delivery routes for distribution centers. A mathematical formulation of this problem has been constructed. Due to the complexity of this problem, a heuristic method is proposed. The result indicates that the proposed heuristic method reduced the total travelling distance approximately 20.64% from the current plan. In addition, we investigate the effect of number of distribution centers on the travelling distance and compare the results with the solution obtained from the genetic algorithm (GA). The results show that our proposed method provides shorter travelling distance for most cases and has shorter computational time. ______________________________
Establishing the quantitative and qualitative limits of the applicability of the multi-stage dumping sequence in open pit mining

Environmental issues and sustainability are currently being discussed and studied in several areas of mining technology; combining these issues with improved mining operation and management is part of strategic mine planning. Waste management plays an important role in this process, as an alternative way of minimising environmental impacts and achieving more attractive economic scenarios, such as backfilling the pit. This study aimed to evaluate the application of the multi-stage dumping sequence (MSDS) in conjunction with in-pit deposition strategy for a phosphate mine providing general orientations and limits of applicability of the method. The MSDS makes use of temporary waste dumps which gives operational flexibility regarding waste management while reducing the Net Present Cost (NPC) (up to 8% in this study) compared with the traditional and sometimes untouchable rule of no re-handling approach during waste disposal.
NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model.
Wetin una dey yan: Variation in the use of copula dey in Nigerian Pidgin English

Abstract The present study shows variability in Nigerian Pidgin English (NPE) through its frequently used copula dey. Previous works on copulas in NPE have rarely shown the extent to which the copula varies, the extent to which attested variation is complex, or the extent to which the simple or complex variation found is related to processing both the verb phrase in which the copula operates and the overall sentential context it scans. Contributing to this question, the study shows that copula dey exhibits complex variability, which is strongly related to the difficulty in processing the meaning and interpretation of both the verb phrase and that of the overall sentence. The article also shows that variants of dey (i.e. deh and de) are unrelated to the exhibition of this complex variability, though their choice of use is related to formality or text type. Framed within a construction grammar theoretical framework, the article identifies and classifies five contextual scenarios showing creative movement and placement of the copula, including how structural variability (or lack thereof) distinguishes between copula dey, verbal dey and metaphoric dey.
Requirements for Localization of p130 cas to Focal Adhesions

p130 cas (Cas) is an adapter protein that has an SH3 domain followed by multiple SH2 binding motifs in the substrate domain. It also contains a tyrosine residue and a proline-rich sequence near the C terminus, which are the binding sites for the SH2 and SH3 domains of Src kinase, respectively. Cas was originally identiﬁed as a major tyrosine-phosphorylated protein in v-Crk- and v-Src-transformed cells. Subsequently, Cas was shown to be inducibly tyrosine phosphorylated upon integrin stimulation; it is therefore regarded as one of the focal adhesion proteins. Using an immunoﬂuorescence study, we examined the subcellular localization of Cas and determined the regions required for its localization to focal adhesions. In nontransformed cells, Cas was localized predominantly to the cytoplasm and partially to focal adhesions. However, in 527F-c-Src-transformed cells, Cas was localized mainly to podosomes, where the focal adhesion proteins are assembled. The localization of Cas to focal adhesions was also observed in cells expressing the kinase-negative 527F/295M-c-Src. A series of analyses with deletion mutants expressed in various cells revealed that the SH3 domain of Cas is necessary for its localization to focal adhesions in nontransformed cells while both the SH3 domain and the C-terminal Src binding domain of Cas are required in 527F-c-Src-transformed cells and ﬁbronectin-stimulated cells. In addition, the localization of Cas to focal adhesions was abolished in Src-negative cells. These results demonstrate that the SH3 domain of Cas and the association of Cas with Src kinase play a pivotal role in the localization of Cas to focal adhesions.
Zero-shot Reading Comprehension and Reasoning for Spanish with BERTIN GPT-J-6B

The first edition of the IberLEF 2022 shared task on Reading Comprehension and Reasoning Explanation for Spanish (ReCoRES) aimed at selecting correct answers for multiple-choice questions and providing their rationales. In this work, we tested the zero-shot capabilitiews of a custom trained decoder-only model of 6 billion parameters, BERTIN GPT-J-6B. We compared it against classic fine-tuning of encoder-only language models for the task of question answering, and sequence to sequence for the explanation generation task. While the results of our best BERT-based language model were mildly successful in the multiple-choice questions task surpassing random choice and the zero-shot approach, the generation of valid explanations for the answers using a BERTIN GPT-J-6B surpassed a strong fine-tuned sequence to sequence T5 model baseline while requiring no training data at all.
Quasiparticle effective temperature in superconducting thin films illuminated at THz frequencies

The response of superconducting pair-breaking detectors is dependent on the details of the quasiparticle distribution. In Kinetic Inductance Detectors (KIDs), where both pair breaking and non-pair breaking photons are absorbed simultaneously, calculating the detector response therefore requires knowledge of the often nonequilibrium distributions. The quasiparticle effective temperature provides a good approximation to these nonequilibrium distributions. We compare an analytical expression relating absorbed power and the quasiparticle effective temperature in superconducting thin films to full solutions for the nonequilibrium distributions, and find good agreement for a range of materials, absorbed powers, photon frequencies and temperatures typical of KIDs. This analytical expression allows inclusion of nonequilibrium effects in device models without solving for the detailed distributions. We also show our calculations of the frequency dependence of the detector response are in agreement with recent experimental measurements of the response of Ta KIDs at THz frequencies.
Tyche at Factify 2022: Fusion Networks for Multi-Modal Fact-Checking (short paper)

This paper describes our approach for the multimodal fact-checking (Factify) challenge at AAAI 2022. Fake news has the potential to harm people and society. To combat fake news, fact-checking becomes crucial. False claims are prevalent in both visual and textual forms. Multimodal techniques can merge information from both these modalities. In our approach, we treated this challenge as a multi-class classification task. We extracted textual and visual features from the texts and images, respectively. We used a single BERT module as a text feature extractor for both claim and reference text so that the extracted feature representations show the perspective of the same model on both claim and reference texts rather than two feature representations from two different models. The same goes for the image feature extractor. EfficientNet-B3 was used for extracting image features. Then the features were passed through a proposed fusion module and the classifier. The purpose of the fusion module is to enable the model to learn semantic similarities between texts and images. We achieved the best F1 score of 0.692 on the test set of the FACTIFY dataset.
A BP Neural Network-Based GIS-Data-Driven Automated Valuation Framework for Benchmark Land Price

The automated valuation of benchmark land price plays an essential role in regulating land demand in Chinese real-estate market as the big data are currently accumulated rapidly. However, this problem becomes highly challenging due to the multidimension, large volume, and nonlinearity of the land price-inﬂuencing factors. In this paper, an eﬀective data-driven automated valuation framework is proposed for valuing real estate assets by combining a GIS (geographic information system) and neural network technologies. This framework can automatically obtain the values of spatial factors aﬀecting land price from GIS and generate training set data for training the neural network to identify the complex relationship between all kinds of factors and benchmark land prices. The eﬀectiveness and universality of the framework is veriﬁed via the data of benchmark land prices in Wuhan. The framework can be applied for automated benchmark land price valuation in other cities.
A buffer-based approach to video rate adaptation

During peak viewing time, well over 50% of US Internet tra c is streamed video from Netflix and YouTube. To provide a better streaming experience, these services adapt their video rates by observing and estimating the available capacity. However, accurate capacity estimation is di cult due to highly variable throughput and complex interactions between layers. As a result, existing rate adaptation algorithms often lead to suboptimal video quality and unnecessary rebu↵ers. This thesis proposes an alternative bu↵er-based approach to adapt video rate. Rather than presuming that capacity estimation is always required, this approach starts the design by only using the playback bu↵er occupancy, and then ask when capacity estimation can be helpful. This design process leads to two separate phases of operation: during the steady-state phase, when the bu↵er encodes adequate information, we choose the video rate based only on the playback bu↵er; during the startup phase, when the bu↵er contains little information, we augment the bu↵er-based design with capacity estimation. This approach is tested with a series of field experiments spanning millions of Netflix users from May to September, 2013. The results demonstrate that although a simple capacity estimation is important during the startup phase, it is unnecessary in the steady state. The bu↵erbased approach allows us to reduce the rebu↵er rate by 10–20% compared to a commercial algorithm used in Netflix, while delivering a similar overall average video rate and a higher video rate in steady state.
BERT and Data Augmentation for Sentiment Analysis in TripAdvisor Reviews

Sentiment analysis is one of the most studied topics over years in the Natural Language Processing community. Usually, to solve this task, the solutions must classify the input text into a set of categories, ranging from negative (or very negative) to positive (or very positive). In this paper, we proposed a system for the sentiment analysis challenge in the Rest-Mex track at IberLEF 2022. The objective is to classify tourist opinions about places, restaurants, and hotels in Mexico through the data acquired by the TripAdvisor platform. Our solution explore deep learning (DL) architectures according to the subtasks related with this challenge. Those architectures includes convolutional neural networks (CNN), contex-tualized vector representations of the text based on BERT models and a particular data augmentation scheme.
GAN-BERT: Adversarial Learning for Detection of Aggressive and Violent Incidents from Social Media

In this paper, we address Subtask 1 of Detection of Aggressive and Violent INCIdents from Social Media in Spanish (DA-VINCIS). We introduced our method, using text embeddings from pre-trained transformer models for the training process by GAN-BERT, an adversarial learning architecture. Finally, we obtained F1 of 74.43%, Precision of 74.08%, and Recall of 74.79% on Subtask 1.
(PTZ)-induced increases in epilepsy-related gene expression

(CBDV), anticonvulsant effects confirmed at the molecular level. To examine changes to epilepsy-related gene expression following chemical convulsant treatment and their subsequent control by phytocannabinoid administration, we behaviourally evaluated effects of CBDV (400 mg/kg, p.o.) on acute, pentylenetetrazole (PTZ: 95 mg/kg, i.p.)-induced seizures, quantified expression levels of several epilepsy-related genes (Fos, Casp 3, Ccl3, Ccl4, Npy , Arc , Penk , Camk2a, Bdnf and Egr1) by qPCR using hippocampal, neocortical and prefrontal cortical tissue samples before examining correlations between expression changes and seizure severity. PTZ alone produced generalised seizures (median: 5.00 ) and significantly increased expression of Fos, Egr1, Arc , Ccl4 and Bdnf . Consistent with previous findings, CBDV significantly decreased PTZ-induced seizure severity (median: 3.25) and increased latency to the first sign of seizure. Furthermore, there were correlations between reductions of seizure severity and mRNA expression of Fos, Egr1, Arc , Ccl4 and Bdnf in the majority of brain regions in the CBDV+PTZ treated group. When CBDV treated animals were grouped into CBDV responders (criterion: seizure severity 3.25) and non- ≤ responders (criterion: seizure severity >3.25), PTZ-induced increases of Fos, Egr1, Arc , Ccl4 and Bdnf expression were suppressed in CBDV responders. These results provide the first molecular confirmation of behaviourally observed effects of the non-psychoactive, anticonvulsant cannabinoid, CBDV, upon chemically-induced seizures and (R 2 =0.71, P=0.0175) and neocortex (R 2 =0.65, P=0.0291) whilst Ccl4 mRNA expression was correlated with seizure severity in the hippocampus (R 2 =0.91, P=0.0008), neocortex (R 2 =0.71, P=0.0175) and prefrontal cortex (R 2 =0.71, P=0.0175). Together, these suggest a possible contribution of the anti-convulsant effects of CBDV in reduction of mRNA expression of Fos, Egr1, Arc, Bdnf and Ccl4.
Triples, Fluxes, and Strings

We study string compactications with sixteen supersymmetries. The moduli space for these compactications becomes quite intricate in lower dimensions, partly because there are many dierent irreducible components. We focus primarily, but not exclusively, on compactications to seven or more dimensions. These vacua can be realized in a number ways: the perturbative constructions we study include toroidal compactications of the heterotic/type I strings, asymmetric orbifolds, and orientifolds. In addition, we describe less conventional M and F theory compactications on smooth spaces. The last class of vacua considered are compactications on singular spaces with non-trivial discrete fluxes. We nd a number of new components in the string moduli space. Contained in some of these components are M theory compactications with novel kinds of \frozen" singularities. We are naturally led to conjecture the existence of new dualities relating spaces with dierent singular geometries and fluxes. As our study of these vacua unfolds, we also learn about additional topics including: F theory on spaces without section, automorphisms of del Pezzo surfaces, and novel physics (and puzzles) from equivariant K-theory. Lastly, we comment on how the data we gain about the M theory three-form might be interpreted.
CompeGen: Computing Company Competitor Pairs By Knowledge Based Inference Combined With Empirical Validation

This paper is an interim report about an industrial application that uses Datalog combined with empirical methods to compute competitor information from a knowledge graph. The Owler knowledge graph is one of the world’s largest companies information systems (CIS). It contains data about 16+ million companies crowd-sourced from over 1 million experts. In particular, for most companies, it contains a set of competitors. Such competitor information is very useful for many B2B applications such as lead generation . However, competitor relations in crowd-sourced CIS are naturally incomplete. This paper presents CompeGen, a method that applies Vadalog (a particular variant of Datalog) rules to infer new competitor pairs from existing ones in the Owler CIS. Since using the Vadalog inference program alone is insufficient, CompeGen combines its inference process with a “learning” process to acquire some required logical facts and further validates the inference results via an empirical validation process. CompeGen was tested using the companies belonging to the “Internet Software” sector in Owler. It has discovered 23,180 new competitors of which over 80% were correct. We are improving the system and will report further results in the full paper.
Application of virtual reality for dementia management

Age is recognized as the major factors of dementia, especially in for Alzheimer’s disease (AD). Given to the aged population, the increased number of demented population has been receiving a great impact in our society. Unfortunately, so far, no cured medicines have been demonstrated to provide effective treatment in AD. The combination of pharmacological and non-pharmacological interventions has been proposed to manage dementia with potential benefits especially in decreasing caregiver’s burden and behavior, as well as psychological problems of demented patients. Recently, giving to the glorious development in digital technologies, the virtual reality, one of the non-pharmacological interventions has been used extensively in dementia managements for its strengths which can be adapted in accordance with the heterogeneous needs from demented patients and their caregivers. However, various study designs and other reasons made these results difficult to be interpreted. In this review our goal is to provide a better understanding for these points.