Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Theoretic Causality Detection between Financial and Sentiment Data

The interaction between the flow of sentiment expressed on blogs and media and the dynamics of the stock market prices are analyzed through an information-theoretic measure, the transfer entropy, to quantify causality relations. We analyzed daily stock price and daily social media sentiment for the top 50 companies in the Standard & Poor (S&P) index during the period from November 2018 to November 2020. We also analyzed news mentioning these companies during the same period. We found that there is a causal flux of information that links those companies. The largest fraction of significant causal links is between prices and between sentiments, but there is also significant causal information which goes both ways from sentiment to prices and from prices to sentiment. We observe that the strongest causal signal between sentiment and prices is associated with the Tech sector.
New Multilevel Topology for Harmonic Reduction

Two topologies are compared in this paper as well as analyzed the conversion of DC to AC power. Series connected inverter is use in the first topology. Ne w multilevel scheme is use by another and having H-Bridge and Lev l modules. Software part is done in the MATLAB Software. For new topology prototype hardware is implemented using PIC microcontroller. We compare MATLAB, SIMULINK and hardware results. In MATLAB, SIMULINK conventional and new topology comparative analysis i done. We compare total harmonic distortion and real and reactive power for both systems. From that we analyze new to p logy having less harmonic distortion.
Dormant mechanisms reveal the clinical significance of tumor dormancy: a narrative review

After successful treatment, there is still the possibility of recurrence and metastasis in patients with malignant tumor. The reason why malignant tumor can recur after years and even decades of successful treatment is attributed to a small amount of dormant tumor cells remained in host for years. The dormancy state is unstable and may re-enter the proliferating state under appropriate conditions, leading to tumor recurrence and metastasis. Compared with the primary tumors, recurrent tumors or metastatic tumors are insensitive to conventional radiotherapy and chemotherapy. This characteristic of malignant tumor has become the difficulty of treatment, and it is also the cause of death of most tumor patients. Tumor dormancy puts forward challenges for clinical control and opportunities for scientific discovery. With its current pictures of the mechanisms of tumor dormancy and reawakening remaining incomplete, it is unclear when and which dormant cells will resume proliferation causing late relapse, and which will remain asymptomatic and harmless to their hosts. Here, we will discuss the regulation of autophagy, angiogenesis and immunity on tumor dormancy, and briefly introduce the clinical implications of tumor dormancy from the perspective of the above mechanisms. With better understanding of tumor dormancy at the molecular level, novel cancer therapeutics could be provided, turning into effective treatments for cancer patients.
Driver Sleepiness Detection Algorithm Based on Relevance Vector Machine

Driver sleepiness is one of the most important causes of traffic accidents. Efficient and stable algorithms are crucial for distinguishing nonfatigue from fatigue state. Relevance vector machine (RVM) as a leading-edge detection approach allows meeting this requirement and represents a potential solution for fatigue state detection. To accurately and effectively identify the driver’s fatigue state and reduce the number of traffic accidents caused by driver sleepiness, this paper considers the degree of driver’s mouth opening and eye state as multi-source related variables and establishes classification of fatigue and non-fatigue states based on the related literature and investigation. On this basis, an RVM model for automatic detection of the fatigue state is proposed. Twenty male respondents participated in the data collection process and a total of 1000 datasets of driving status (half of non-fatigue and half of fatigue) were obtained. The results of fatigue state recognition were analysed by different RVM classifiers. The results show that the recognition accuracy of the RVM-driven state classifiers with different kernel functions was higher than 90%, which indicated that the mouth-opening degree and the eye state index used in this work were closely related to the fatigue state. Based on the obtained results, the proposed fatigue state identification method has the potential to improve the fatigue state detection accuracy. More importantly, it provides a scientific theoretical basis for the development of fatigue state warning methods.
Adenocarcinoma of the Third Portion of the Duodenum with an Acute Cholecystitis

Primary adenocarcinoma of the third portion of the duodenum is rare. Therefore, few reports have investigated the diagnosis and treatment of this malignancy. In October 2012, a 52-yearold Japanese female was referred to our hospital complaining of epigastric pain due to acute cholecystitis. Subsequent esophagogastroduodenoscopy (EGD) revealed a depressedtype duodenal tumor 15mm in size on the third portion, while abdominal ultrasound and computed tomography scan revealed cholecystitis with a gallstone. Thereafter, partial duodenectomy and cholecystectomy was performed, with his tological examination showing welland moderately differentiated tubular adenocarcinoma without lymph node metastasis. According, a definitive diagnosis of T1N0M0, pStage IA duodenal adenocarcinoma was established according to the TNM classification of malignant tumors. The patient had an excellent recovery, with no duodenal carcinoma recurrence having been clinically diagnosed eight years post-surgery. The appreciation of the distal duodenum by EGD is important for the proper diagnosis and treatment of this rare early duodenal adenocarcinoma.
Rectangular drainage pattern evolution controlled by pipe cave collapse along clastic dikes, the Dead Sea Basin, Israel

Rectangular drainage networks are characterized by right‐angle bends and confluences. The formation of such drainage patterns is commonly associated with orthogonal sets of fractures, making them an outstanding example for structurally controlled landscape evolution. However, this association remains largely circumstantial because little is known about how rectangular drainages mechanistically link to orthogonal fractures. We investigated these linkages in the hyper‐arid Ami'az Plain located within the Dead Sea Basin in Israel. The Ami'az Plain is penetrated by hundreds of sub‐vertical clastic dikes (mode‐I fractures infilled with sediments) and is also incised by a rectangular canyon system. Numerous caves extend from the banks and heads of the canyon system. Based on field surveys and analysis of high‐resolution airborne LiDAR data, we mapped the Ami'az Plain drainage network and its associated landforms, including sinkholes. Our analysis revealed that the subaerial tributaries of the canyon system and the strike of the clastic dikes show similar orientations. In addition, subsurface mapping with a ground‐based scanning LiDAR, together with field experiments, demonstrated that the caves and sinkholes in the Ami'az Plain are spatially associated with clastic dikes and that the caves formed through piping erosion along dikes. Based on these findings, we suggest that clastic dikes act as efficient infiltration pathways to the subsurface, where flow along clastic dikes induces internal erosion that forms pipe caves. The sinkholes form by collapses of cave roofs. Coalescence of sinkholes and seepage erosion where dikes intersect canyon heads generate new tributaries and act to extend existing ones. Fluvial erosion and subsequent bank collapse modify the canyon network. Our findings emphasize the critical role of subsurface erosion, caves and sinkholes in linking fractures to drainage pattern evolution, and provide a new process‐based framework to interpret rectangular drainage networks on Earth and possibly other planetary surfaces.
Analysis of language learning strategies and stereotypical thoughts of preparatory school students

This study identifies the usage of language learning strategies and stereotypical thoughts on foreign languages regarding gender and language marks. It is designed in both correlation model and descriptive comparative model. The research sample is composed of 184 preparatory school students studying at a state university. Two questionnaires are used in the collection of data: Oxford's Language Learning Strategies Scale (1990) and Unal's (2015) Stereotypical Thoughts towards Foreign Language Scale. The findings show that the use of language learning strategies is moderate and metacognitive strategies are the most widely used ones. The strategies that are used more are indirect ones while cognitive strategies are the least frequently employed ones. Additionally, while female students use indirect strategies more than males, the use of direct strategies does not differ significantly according to gender. Also, in terms of foreign language scores, it is found out that students with higher marks tend to use indirect strategies more. The findings also indicate that stereotypical thoughts towards foreign languages are moderate. The highest mean scores are indicated by regret and collectivity when compared to the other categories. In terms of gender, the stereotypical thoughts of students differ significantly in favor of female students in categories as regret and collectivity. Regarding language scores, the level of stereotypical thoughts towards foreign language is high for unsuccessful students while successful ones tend to have less stereotypical thoughts. Finally, there is a mild and inverse relationship between the use of language learning strategies and stereotypical thoughts towards languages.
Collecting and Characterizing Natural Language Utterances for Specifying Data Visualizations

Natural language interfaces (NLIs) for data visualization are becoming increasingly popular both in academic research and in commercial software. Yet, there is a lack of empirical understanding of how people specify visualizations through natural language. We conducted an online study (N = 102), showing participants a series of visualizations and asking them to provide utterances they would pose to generate the displayed charts. From the responses, we curated a dataset of 893 utterances and characterized the utterances according to (1) their phrasing (e.g., commands, queries, questions) and (2) the information they contained (e.g., chart types, data aggregations). To help guide future research and development, we contribute this utterance dataset and discuss its applications toward the creation and benchmarking of NLIs for visualization.
Social capital of sustainable solid waste management in Joyotakan Climate Village Surakarta

Limited land in the provision of solid waste infrastructure is one of the challenges in solid waste management. Solid waste also contributes to greenhouse gas emissions which have implications for climate change. The Indonesia Ministry of Environment and Forestry has launched a climate village program as a form of capacity building to mitigate climate change through a series of activities, one of which is sustainable waste management. The paradigm shift in conventional waste management towards a sustainable concepts with the principles of reuse, reduce, and recycle (3R) began to be implemented. Social capital is one of the important aspects of the success of programs based on community participation. The study area in this research is Joyotakan Climate Village which was established by the Surakarta City Environment Agency in 2017. The purpose of this study is to explain how social capital in solid waste management in Joyotakan Climate Village. This study uses a qualitative method. The results showed that the four aspects of social capital that were the focus of discussion in this study, namely the capacity of human resources, forms of social interaction, leadership, and governance, had a positive relationship with the level of community participation in sustainable solid waste management. Although, there are several things that can be potential to strengthen social capital in the context of maximizing community participation in sustainable waste management. Among them are the increase in economic value in waste management, the transfer of knowledge related to waste processing and technology to the entire community, and greater community involvement in various programs which initiated by various stakeholders.
Opleiding Informatica Classifying citizen complaints using pre-trained language models

This thesis shows the eﬀectiveness of state-of-the-art Natural Language Models on a customer complaint data-set owned by the company Decos which consists of municipalities, their self-chosen categories and the issues which their citizens submitted. The model used for this classiﬁcation problem is BERT which was introduced by researchers of Google in late 2018. To achieve the highest model quality, parameters such as the learning rate, the learning policy, the maximum length of tokens and the amount of epochs are experimented with while ﬁne-tuning a pre-trained Dutch model. The data-set poses a lot of challenges such as short and under-speciﬁed issues, imbalanced data, miss-labelled issues and per municipality unique categories. The model trained with the most optimal variables achieved an 86% F 1 score on the original data-set consisting of 145,000 records using cross-validation. Finally it is discussed what there could’ve been done better and what could be improved on in further research.
Transcription Factor NF-κβ and Molecules Derived from its Activation in Age-Related Macular Degeneration

Activation of the nuclear factor kappa β (NF-κβ) is related to many inflammatory diseases, including age-related macular degeneration (AMD). The imbalance in the redox state, which happens mainly in senescence, associated with several peculiar characteristics of the macular region, has led to studies of this molecule for AMD therapeutic interventions. Findings report the involvement of NF-κβ both in the triggering as well as in the worsening condition of AMD. The present article correlates AMD oxidant and inflammatory genesis with the action of the nuclear factor kappa β. Besides its mechanism of action, this study also analyzes the main inflammatory cytokines and adhesion molecules that may be activated by NF-κβ and are closely
Bioguided isolation, structure elucidation and evaluation of new antimicrobial flavonoid from Carica papaya leaves

The emergence of antimicrobial resistance is a global concern, particularly in developing countries. The aims of this study were to isolate and identify antimicrobial fractions of C. papaya based on their antimicrobial activity and evaluate the antimicrobial effects of flavonoid to provide natural resources against S. enteretidis, S. typhi, E. coli, S. flexneri and K. pneumonia using the broth microdilution method. The aqueous fraction showed high inhibition potentials against all the tested bacteria with a Minimum Inhibitory Concentration value of 500 μg/mL. Subsequent phytochemical investigation of aqueous fraction by bioactive-guided column chromatography identified by H NMR, C NMR and ESIMS experiments, one new flavonoid named 6"-O-acetyl-3'-O-methyl orientin. The antimicrobial effects of flavonoid against the same pathogens were close to those of the aqueous fraction. This result showed that 6"-O-acetyl-3'-Omethyl orientin is responsible for the antimicrobial activity of Carica papaya leaves and may be considered as antimicrobial lead compound.
Compliant activity accelerates all thought probe responses and inhibits deliberate mind wandering

Introduction:Mind wandering is a cognitive state that leads to diminished performance and error risk. A controversy over whether easier or more difficult tasks enhance mind wandering has led to mind wandering being proposed as two different states: deliberate and spontaneous. We hypothesise that forced engagement may inhibit non-instrumental activities including deliberate mind wandering.Methods: Twenty-eight seated, healthy participants (age range 19-35, 9 male) interacted with two pairs of stimuli, each pair having one low-interactivity version and a high-interactivity version requiring compliant activity. Mind wandering was assessed by thought probes, and mind wandering and challenge and boredom were also tested using visual analogue scales at the end of each stimulus. Reaction times were measured using Superlab with an RB530 interaction device.Results:Compliant activity decreased deliberate mind wandering but not overall mind wandering. Thought probe durations were significantly shortened by increasing interaction frequency, while deliberate and spontaneous mind wandering elicited equivalent thought probe durations. Conclusion: Compliant activity works synergistically with lack of mind wandering to accelerate the difficult task of thought probe response. This does not fit with the attentional resource model, and may require a clearer definition of how tasks may be labelled as difficult. CCS CONCEPTS • HCI design and evaluation methods;
Types of Mycotoxins and different approaches used for their detection in foodstuffs

Mycotoxins are toxic complexes generated by various genera of filamentous fungi and pose severe public health hazards due to their carcinogenic and mutagenic properties. Toxigenic fungi produce mycotoxins on various foodstuffs when favorable conditions for their production are exist. The most important mycotoxin-producing fungal genera are Aspergillus, Fusarium and Penicillium. The major mycotoxin of concern, including aflatoxins, trichothecenes, ochratoxins, patulin, fumonisins, and zearalenone, are expressively contaminate foodstuffs, with implications for human and animal health. There are various environmental factors influencing mycotoxin production involving temperature, water activity, animal type, aeration, pH, light, and nature of substrate. The temperature and relative moistness range for ideal mycotoxin generation may shift from that steady fungal development. The high temperature and moistness stress primarily have a potential issue. A full understanding of the existence of mycotoxins in addition the implementation measures to overcome their contamination of foodstuffs is crucial. There are different important analytical techniques to precisely screen the levels of mycotoxins contamination and give a wider overview about what is the most common, pathogenic; along with further strategies to control measures. Thus, in this review sampling, sample preparation and different analytical methods for determination of mycotoxins have been discussed.
Genomics for veterinarians

Genomic selection refers to selection decisions based on genomic breeding values. A genomic prediction equation is calculated from a reference population of bulls/cows that have genetic markers and phenotypes. This is done by looking for associations between phenotypes and dense genetic markers that are approximately equally spaced across the entire genome. In cattle a variety of marker panels are used, varying from a few thousand genetic markers per panel to hundreds of thousands. Genomic breeding values are calculated as the sum of each of the genotypes multiplied by its respective effect on a trait, thereby potentially capturing most of the genes that cause differences among animals in the traits of interest. This prediction equation can then be applied to individuals that are genotyped, but have no phenotypes. Therefore, the genetic merit of an individual can be calculated as early as birth and, therefore, selection decisions can be made earlier in life than traditional approaches, such as progeny testing.
Use of Artichoke Leaves in Meatballs as a Functional Product

Numerous studies have been demonstrated the beneficial effects of dietary fiber (DF) consumption in prevention heart disease, cancer, cholesterol, lipid regulation of glucose absorption, insulin secretion and constipation. Meats are undoubtedly major source of proteins with high biological value. However, most of the meat products are deficient in fiber. The aim of this study was to use artichoke leaves (AL) (Cynara scolymus L.) in meatballs to reduce the caloric content by fat substitution. Meatballs were prepared from meat fortification with four different level of artichoke leaf powder "AL" (2.5, 5, 7.5, and 10 %). The results revealed that the meatballs were high contained in fiber, protein and low amount low in fats. The sensory evaluation of the meatballs gives acceptable sensory result in levels 2.5 and 5% AL, while 7.5 and 10% meatballs of AL were less acceptability. As well as study of texture properties in supplemented meatballs indicated that adding AL in meatball showed the highest effect on firmness, chewiness and gumminess , no significant differences between springiness and resilience. While showed significant decrease differences between cohesiveness, Meatballs containing artichoke leaves had lower of saturated fatty acids and higher of unsaturated fatty acids compared to the control and there was a significant increase in unsaturated fatty acids by the addition of fiber through artichoke leaves. It can be recommended that the necessity to adding 2.5, 5, 7. 5 and 10% of artichoke leaves when making meatballs, to increase the meatballs' content of dietary fiber and protein and decrease their saturated fat content, which reflects the importance of consumption for patients with hyperlipidemia.
The Effectiveness of Music Therapy on Reducing Alexithymia Symptoms and Improvement of Peer Relationships

Abstract Introduction: Individuals with alexithymia are under the pressure of correlated physio-emotional stress that would not come out as speech. These problems prevent emotion regulation and make people incompatible in life. Method: The purpose of this study was examining the effectiveness of music therapy on reducing symptoms of alexithymia and enhancing peer relationships. The method was quasi-experimental with two experimental and control groups. Through multi-stage sampling, one hundred and eighty girls were screened for alexithymia’s symptoms. Thirty of the 57 identified children, were selected randomly and assigned into control (n=15) and experimental (n=15) groups (mean 11.8 Years old) randomly in Isfahan, Iran. The instruments were the Rieffe’s Alexithymia Questionnaire for children and Sociometry for evaluating peer relationships. The music therapy was nine sessions which was done for the experimental group. Data was analysed with the repeated measure ANCOVA. Results: The results indicated that music therapy had a significant positive effect on reducing alexithymia in the experiment group (ES = -0.34, (OP = -0.92), while there was no significant change in the control group (p >0.05). The results stayed stable after two months follow-up. Although the results showed peer relationships, the helper dimension improved; other peer relationships, the popularity, and rejection, were not influenced significantly. Conclusion: In conclusion, music therapy positively affects reducing alexithymia symptoms of female preadolescents. Thus, using music therapy for reducing alexithymia symptoms is suggested.