Miracle-dz/UniFAR-FTUs huggingface dataset:
Irreversible Thermodynamics and Modelling of Random Media

Engineering and Nature very often are concerned with media that do contain some randomness. One particularly well known example is given by turbulent flows, where random fluctuations are the results of the growth of unstable motions from small perturbations in the initial or boundary conditions, when the velocity gradients or/and temperature gradients are too large in some place within the flow. These fluctuating motions result in effective additional friction, effective additional diffusion of species or heat, and additional energy dissipation (i.e. transfer from organized kinetic energy to turbulent kinetic energy, and finally to internal energy). Another example of random flows is seen in two-phase flows, either with particles dispersed into a liquid or gaseous continuous phase, or built with a bubbly liquid. Here, a first reason of randomness is given by the fact that the locations and velocities of the particles (or bubbles) at initial time and in entrance sections cannot be known or controlled, and the induced fluctuations are not rapidly damped with time. Generally, this randomness becomes rapidly uncorrelated with these initial conditions due to the complex interactions between the flow of the continuous phase and the moving inclusions, interactions that modify also the number and sizes of these inclusions. Consequently, the flow conditions in both phases are or become turbulent, with interconnected fluctuations of velocities. Again, the effective result of the fluctuations is additional friction, additional diffusion or dispersion, and additional energy dissipation. Two-phase or multiphase flows with a large amount of solid particles are used in the industrial devices called as “Fluidized Beds”, and are encountered naturally in “Granular Flows”, and in this case there are many lasting contacts between the particles. The so called “Granular Media”, even without actual flow but just with some deformations or slow motions, are also subjected to randomness, due to the preparation of the medium but also to the differences between the grains shapes, and even the global properties of these media are very difficult to predict. The properties of these kinds of media and flows have been studied since more than hundred years, and very useful prediction methods have been proposed so far, with methodologies becoming more and more clearly similar. Although all these media are showing clearly irreversible and dissipative processes, the typical reasoning of irreversible thermodynamics has never been used, at least explicitly (it might be present, but not consciously, in the brain of the authors). Our purpose here is to show that the Irreversible Thermodynamics and the “Second Principle” can justify many features of the models that
Automorphic products on unitary groups

The dissertation provides a construction for Borcherds products on unitary groups of signature (1,q). The starting point for this is the multiplicative lifting due to R. E. Borcherds. He employs the singular theta-correspondence to construct a lifting, which takes as inputs weakly holomorphic vector valued modular forms, transforming under the Weil-representation of SL(2,Z) for a quadratic lattice, and lifts these to meromorphic automorphic forms for an arithmetic subgroup of O(2,n). The resulting functions have expansions as infinite products and take their zeros and poles along Heegner divisors. In order to transfer this result to unitary groups, we construct an embedding between the symmetric domain of the unitary group and that of an orthogonal group, respectively. This embedding is compatible with the complex structures of either symmetric domain and a suitable choice of cusps. The main result is the construction of Borcherds products, on unitary groups of signature (1,q). In this setting we prove a result which is analogous to that of Borcherds. As in the case of orthogonal groups, the infinite products thus constructed have their zeros and poles on Heegner divisors. Here, the role of the quadratic lattice is taken by a hermitian lattice, which we assume to have as multiplier system the ring of integers of an imaginary quadratic number field. Further, we study the behavior of these automorphic products on the boundary of the symmetric domain. It turns out that the values taken on the boundary points can be interpreted as CM-values of generalized eta-products. In the finial chapter, we construct examples for the unitary group SU(1,1) and unimodular lattices, which in this case are simply hyperbolic planes over the rings of integers of imaginary quadratic number fields. In this case, the resulting products can be viewed as meromorphic elliptic modular forms on the (classical) complex upper half-plane.
Detecting Diachronic Syntactic Developments in Presence of Bias Terms

Corpus-based studies of diachronic syntactic changes are typically guided by the results of previous qualitative research. When such results are missing or, as is the case for Vedic Sanskrit, are restricted to small parts of a transmitted corpus, an exploratory framework that detects such changes in a data-driven fashion can substantially support the research process. In this paper, we introduce a customized version of the infinite relational model that groups syntactic constituents based on their structural similarities and their diachronic distributions. We propose a simple way to control for register and intellectual affiliation, and discuss our findings for four syntactic structures in Vedic texts.
Political Accountability for Populist Policies: Lessons from India’s Demonetization ∗

How do voters respond to popular policies that appeal to moral sentiments, but have negative economic consequences? We examine voter dynamics following one such policy – India’s 2016 demonetization that made 86% of currency-in-circulation redundant overnight. Leveraging discontinuities in banking access, we identify the impacts of demonetization’s severity. Places with more severe demonetization had lower economic activity, and voters had less favorable views on demonetization. Diﬀerence-in-discontinuity estimates show that the ruling party subsequently received a 4.7pp lower vote share and were less likely to win in regions with fewer banks. Yet, ruling-party strongholds remained unresponsive in voting behavior.
Artificial intelligence using deep neural network learning for automatic location of the interscalene brachial plexus in ultrasound images

BACKGROUND Identifying the interscalene brachial plexus can be challenging during ultrasound-guided interscalene block. OBJECTIVE We hypothesised that an algorithm based on deep learning could locate the interscalene brachial plexus in ultrasound images better than a nonexpert anaesthesiologist, thus possessing the potential to aid anaesthesiologists. DESIGN Observational study. SETTING A tertiary hospital in Shanghai, China. PATIENTS Patients undergoing elective surgery. INTERVENTIONS Ultrasound images at the interscalene level were collected from patients. Two independent image datasets were prepared to train and evaluate the deep learning model. Three senior anaesthesiologists who were experts in regional anaesthesia annotated the images. A deep convolutional neural network was developed, trained and optimised to locate the interscalene brachial plexus in the ultrasound images. Expert annotations on the datasets were regarded as an accurate baseline (ground truth). The test dataset was also annotated by five nonexpert anaesthesiologists. MAIN OUTCOME MEASURES The primary outcome of the research was the distance between the lateral midpoints of the nerve sheath contours of the model predictions and ground truth. RESULTS The data set was obtained from 1126 patients. The training dataset comprised 11 392 images from 1076 patients. The test dataset constituted 100 images from 50 patients. In the test dataset, the median [IQR] distance between the lateral midpoints of the nerve sheath contours of the model predictions and ground truth was 0.8 [0.4 to 2.9] mm: this was significantly shorter than that between nonexpert predictions and ground truth (3.4 mm [2.1 to 4.5] mm; P < 0.001). CONCLUSION The proposed model was able to locate the interscalene brachial plexus in ultrasound images more accurately than nonexperts. TRIAL REGISTRATION ClinicalTrials.gov (https://clinicaltrials.gov) identifier: NCT04183972.
Marker Assisted Introgression of Gall Midge ( Gm4 ) and Bacterial Blight ( xa13 ) Resistant Genes in to Tellahamsa Rice Cultivar

data complies data for secondary data original T ellahamsa is a high yielding, long-slender (LS) grain type rice variety with 120 days of duration. However, it is highly susceptible to rice Gall Midge (GM) and Bacterial Blight (BB). In order to improve Tellahamsa for resistance against Gm and BB, a gene each conferring resistance against Gm (i.e. Gm4 ) and BB (i.e. xa13 ) was introgressed into Tellahamsa. An introgression line of Samba Mahsuri (RP1) possessing Gm4 and xa13 genes and with fine-grain type was used as donor parent in a backcross breeding strategy for targeted introgression of the resistance genes. PCR based molecular markers RM547, RM22554 and LRR-del for Gm4 and xa13 promoter for xa13 genes were used for foreground selection of target genes in F 1 , BC 1 F 1, BC 2 F 1 and BC 3 F 1 generations, while 123 rice microsatellite markers polymorphic between the donor and recurrent parent were used to identify the best backcross plants, which not only possess the two target genes, but also have maximum recovery of recurrent parent genome at each generation. At BC 3 F 6 , four backcross derived line viz . , WGL-1145, WGL-1146, WGL-1147 and WGL-1150 possessing Gm4 and xa13 genes, high yield, long-slender grain type, recurrent parent genome recovery ranging from 88.8-98.6% and closely resembling Tellahamsa were selected and advanced for further evaluation. ABSTRACT Bacterial blight, Gall
GHC: U: Robustness of Fairness in Machine Learning

As machine learning algorithms become widely used in society, certain subgroups are more at risk of being harmed by unfair treat-ment. Fairness metrics have been proposed to quantify this harm by measuring certain statistics with respect to an evaluation dataset. In this work, we seek to analyze how robust these metrics are. That is, we are interested in whether these metrics give the same “fair-ness score” when measured on different sets of samples from the same distribution. This is important because it gives us insight into how much we can trust the conclusions given by a fairness metric prior to deployment of a model. We design a framework to conduct experiments to test the robustness of a popular fairness metric. We find that, when compared to more traditional performance metrics, it is more sensitive to fluctuations in the evaluation dataset in a variety of settings. Additionally, our work provides a foundation for studying the robustness of fairness metrics in general.
Use of Adaptive Learning in an Engineering Technology Course: A Case Study

engineering to evaluate diverse pedagogy strategies within the classroom to create effective learning experiences for engineering sustainability. Abstract This study explores the use of an adaptive learning module implemented in a sophomore-level course for engineering technology and construction management students. Adaptive learning provides personalized learning pathways for students through the use of computers. Just-in-time feedback is one of its innovative features that helps to accomplish a unique student learning environment. While adaptive learning is explored in other disciplines, there is limited literature in the engineering education context. The research goal of this study is to examine student learning and behavioral engagement when an adaptive learning module is introduced. The topic for this module, “Pumps,” was selected due to a need to improve traditional instruction for this topic, indicated by student performance on the associated assignment. The adaptive learning module was designed to further engage students in personalized instruction and was used as a supplement to the instructor’s in-class lectures on the topic. The researchers gathered and analyzed 42 students’ data on learning, performance, and user pathways on the adaptive learning platform, Smart Sparrow. Preliminary results show 81 percent demonstrated mastery across all modules. In total, 65 percent interacted with at least one adaptive learning module due to assessment, and 24 percent had more than one interaction. Time spent with the adaptive content was much shorter than the original content interaction, suggesting many students were able to resolve uncertainty within the lesson efficiently. By implementing adaptive learning technology, students experience a tailored learning experience, specific to their learning path towards their mastery of the given topic. Expanded research in the engineering education context can lead to more closely aligning instructors’ teaching styles and students’ learning styles.
Assessment of beneficial effect of Badri cow urine distillate on serum biochemical profile in Wistar rats

Present study was carried out to find the effect of Badri cow urine distillate on serum biochemical parameters in Wistar rats. Badri cow urine distillate was given to rats orally with drinking water at 0. 25ml/day/rat for 90 days. The blood sample were collected from retro orbital sinus of rats at 0 th , 30 th , 60 th , 90 th day post treatment in clot activator vials. Then serum was separated from blood by standard protocol for assessment of serum biochemical parameters. There was significant increase in serum total protein, serum globulin while other parameters like serum glucose, cholesterol values were significantly decrease in treated group as compare to control group. Some parameters like aspartate amino transaminase (AST), alanine amino transaminase (ALT) were decrease in value in treated group as compared to control group. Results of present study revealed that Badri cow urine distillate show ameliorative effect on serum biochemical parameters.
To MOOC or not to MOOC: An Empirical Study of Chinese Students’ MOOC Learning

: MOOC is becoming increasingly popular around the world. However, its status and effectiveness in higher education are still controversial. This study investigates Chinese postgraduate students' MOOC learning experiences (factors driving them to learn and future optimisation suggestions) on the Chinese University MOOC (iCourse) platform. By conducting semi-structured interviews with five Chinese graduate students, data was gathered. According to the findings, students choose to learn on MOOC because of its flexibility and their need for professional expertise. MOOC learning can be improved by providing more flexible courses, improving interactivity, and providing more assistance for learners. Future research could use larger samples to investigate students' learning accomplishments and the effectiveness of MOOC learning.
Representing and Processing Emotions in a Cognitive Architecture

This paper briefly proposes a theory of emotions that clarifies their role in architectures for intelligent agents. The account posits that emotions take the form of symbolic cognitive structures, that generic emotional rules produce concrete instances of these relational concepts, that such rules underlie both generation and understanding of emotions, and that their results play a metacognitive role in influencing behavior. In this framework, emotions are central to high-level, human-like cognition.
Global Solutions in Gravity. Lorentzian signature

The constructive method of conformal blocks is developed for the construction of global solutions for two-dimensional metrics having one Killing vector. The method is proved to yeild a smooth universal covering space with a smooth pseudo-Riemannian metric. The Schwarzschild, Reisner--Nordstrom solutions, extremal black hole, dilaton black hole, and constant curvature surfaces are considered as examples.
An 81-Year-Old Man with a 6-Year History of Chronic Lymphocytic Leukemia Presenting with Disease Flare Following Ibrutinib Discontinuation

Patient: Male, 81-year-old Final Diagnosis: Chronic lymphocytic leukemia Symptoms: Fever Medication: — Clinical Procedure: — Specialty: Hematology Objective: Unusual clinical course Background: Chronic lymphocytic leukemia (CLL) is a mature B-cell neoplasm and the most common leukemia in adults in Western countries. Novel agents, including BTK inhibitors and the BCL2 inhibitor venetoclax, have dramatically changed the treatment landscape. Moreover, a disease flare, characterized by sudden worsening of clinical symptoms, radiographic findings of rapidly worsening splenomegaly or lymphadenopathy, and laboratory changes (increased absolute lymphocyte count or lactate dehydrogenase), is a phenomenon described in up to 25% of patients with CLL after ibrutinib discontinuation. We describe a patient with CLL with disease flare after ibrutinib discontinuation due to disease progression and describe the subsequent management of venetoclax initial treatment in the course of the disease flare. Case Report: We describe the case of an 81-year-old man with a 6-year history of CLL who was treated with multiple lines of therapy and developed worsening of disease-related signs and symptoms with fever, marked increase of lymphocyte count, acute worsening of renal function, and increase in lymph nodes and spleen size following cessation of targeted therapy with ibrutinib at the time of disease progression. There was subsequent overlapping of ibrutinib during the venetoclax dose escalation period to prevent disease flare recurrence. Conclusions: Our report highlights the problem of disease flare after ibrutinib discontinuation in order to avoid associated patient morbidity, underscoring the importance of awareness of this phenomenon and focusing on the addition of venetoclax at time of progression in ibrutinib-treated patients, as a temporary overlap strategy, to prevent disease flare.
The Study on the Metaphorical Expressions About the Word Face

The study aims to investigate how the word face is used in metaphorical expressions and try to identify the ways in which these expressions are used to understand other concepts. The Greek philosopher Protagoras states that “man is the measure of all things” (Douglas, 2009, p. 83). Most of the time, it is understood in terms of phylosophy. However, to some extent, it can be understood as: people perceive the world via measuring other unknown concepts according to human body, which is called the human body metaphor. This study is done within the framework of cognitive linguistics, and it focuses on how metaphors are reflected in English expressions containing the word face. The examples in this study are selected from BNC (British National Corpus) online, Wiktionary online, and Google. The result is that face is widely used in many metaphorical expressions to reflect many metaphors in which the body organ face is usually portrayed as a container, the surface of a concret object or a natural physical object and so on. Finally, people can understand other abstract concepts via projecting the concept of face. This study provides us with a new angle to understand better how the metaphorical expressions of face works and what conceptual mataphors they are based on.
Drought-Induced Oxidative Stress in Pearl Millet (Cenchrus americanus L.) at Seedling Stage: Survival Mechanisms through Alteration of Morphophysiological and Antioxidants Activity

We report the impact of drought stress on pearl millet during the early seedling stage and its survival mechanism. Drought stress imposed for a period of 7, 14 and 21 days showed considerable changes in morphophysiological attributes, which were evident by a decline in seedling elongation, fresh and dry biomass, and relative water content (RWC) and degradation of chlorophyll pigment. Besides this, visible chlorosis lesions were observed in leaves as compared to the control. As compared to the respective controls, a nearly 60% decline in chlorophyll content was recorded after 14 and 21 days of drought stress. In both root and shoot, drought stress raised the reactive oxygen species (ROS) levels. Both H2O2 and O2●− levels were significantly elevated along with a significant increase in lipid peroxidation in both roots and shoots, which clearly indicated ROS-induced oxidative stress. Concomitant with the increase in ROS levels and malondialdehyde (MDA) content in roots, membrane integrity was also lost, which clearly indicated ROS-induced peroxidation of membrane lipids. The activities of antioxidant enzymes and levels of non-enzymatic antioxidants were significant (p ≤ 0.001). After 7, 14 and 21 days of drought stress, activities of all the antioxidant enzymes viz., catalase (CAT), guaiacol peroxidase (GPX), superoxide dismutase (SOD) and glutathione reductase (GR) were inhibited, clearly indicating a loss of antioxidant defense machinery. Likewise, the levels of ascorbate (AsA) and reduced glutathione (GSH) levels declined significantly (p ≤ 0.01). Our results reveal that, being tolerant to arid climatic conditions, pearl millet is highly susceptible to drought stress at the early seedling stage.
An Energy-Efficient Clustering Method for Target Tracking Based on Tracking Anchors in Wireless Sensor Networks

As a key technology in wireless sensor networks (WSNs), target tracking plays an essential role in many applications. To improve energy efficiency, clustering is widely used in tracking to organize the network to achieve data fusion and reduce communication costs. Many existing studies make dynamic adjustments based on static clusters to track moving targets. However, the additional overhead caused by frequent cluster reconstruction and redundant data transmission is rarely considered. To address this issue, we propose a tracking-anchor-based clustering method (TACM) in this paper, in which tracking anchors are introduced to provide activation indications for sensors according to the target position. We use the rough fuzzy C-means (RFCM) algorithm to locate the anchors and use the membership table to activate sensors to form a cluster. Since there are no sending, receiving, and fusing data tasks for anchors, they are lightly burdened and can significantly reduce the frequency of being rotated. Moreover, the state of cluster members (CMs) is scheduled using the linear 0–1 programming to reduce redundant transmissions. The simulation results demonstrate that, compared with some existing clustering methods, the proposed TACM effectively reduces the energy consumption when tracking a moving target, thus prolonging the network lifetime.
Estimation and Simulation of Forest Carbon Stock in Northeast China Forestry Based on Future Climate Change and LUCC

Forest carbon sinks (FCS) play an important role in mitigating global climate change, but there is a lack of more accurate, comprehensive, and efficient forest carbon stock estimates and projections for larger regions. By combining 1980–2020 land use data from the Northeast China Forestry (NCF) and climate change data under the Shared Socioeconomic Pathway (SSP), the land use and cover change (LUCC) of NCF in 2030 and 2050 and the FCS of NCF were estimated based on the measured data of forest carbon density. In general, the forest area of NCF has not yet recovered to the level of 1980. The temporal change in the FCS experienced a U-shaped trend of sharp decline to slow increase, with the inflection point occurring in 2010. If strict ecological conservation measures are implemented, the FCS of the NCF is expected to recover to the 1980 levels by 2050. We believe that the ecological priority (EP) scenario is the most likely and suitable direction for future development of the NCF. We also advocate for more scientific and stringent management measures for NCF natural forests to unlock the huge potential for forest carbon sequestration, which is important for China to meet its carbon neutrality commitments.