Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional form of the superconducting critical temperature from machine learning

Predicting the critical temperature $T_c$ of new superconductors is a notoriously difficult task, even for electron-phonon paired superconductors for which the theory is relatively well understood. Early attempts by McMillan and Allen and Dynes to improve on the weak-coupling BCS formula led to closed-form approximate relations between $T_c$ and various measures of the phonon spectrum and the electron-phonon interaction appearing in Eliashberg theory. Here we propose that these approaches can be improved with the use of machine learning algorithms. As an initial test, we train a model for identifying low-dimensional descriptors using the $T_c < 10$ K data tested by Allen and Dynes, and show that a simple analytical expression thus obtained improves upon the Allen-Dynes fit. Furthermore, the prediction for the recently discovered high $T_c$ material H$_3$S at high pressure is quite reasonable. Interestingly, $T_c$'s for more recently discovered superconducting systems with a more two-dimensional electron-phonon coupling, which do not follow Allen and Dynes' expression, also do not follow our analytic expression. Thus, this machine learning approach appears to be a powerful method for highlighting the need for a new descriptor beyond those used by Allen and Dynes to describe their set of isotropic electron-phonon coupled superconductors. We argue that this machine learning method, and its implied need for a descriptor characterizing Fermi surface properties, represents a promising new approach to superconductor materials discovery which may eventually replace the serendipitous discovery paradigm begun by Kamerlingh Onnes.
The Study on Wireless Location Based on SQlite Database and ZigBee Technology

Applying SQlite database and ZigBee technology to the development of the smart supermarket shopping guide system and by prompting customers the target area and locating the real-time position of them, this paper solves the problem that customers can't find target goods quickly in large supermarkets. When customers want to search target goods quickly, firstly the monitor terminal installed in a shopping cart queries SQlite database table to obtain the position of the target area and display it on the electronic map, then it locates the real-time position of customers by ZigBee wireless network and refreshes coordinates of customers constantly. According to the electronic map, customers can go to the target area quickly and find the target goods easier.
Exploring the Inflammatory Pathogenesis of Colorectal Cancer

Colorectal cancer is one of the most commonly diagnosed cancers worldwide. Traditionally, mechanisms of colorectal cancer formation have focused on genetic alterations including chromosomal damage and microsatellite instability. In recent years, there has been a growing body of evidence supporting the role of inflammation in colorectal cancer formation. Multiple cytokines, immune cells such T cells and macrophages, and other immune mediators have been identified in pathways leading to the initiation, growth, and metastasis of colorectal cancer. Outside the previously explored mechanisms and pathways leading to colorectal cancer, initiatives have been shifted to further study the role of inflammation in pathogenesis. Inflammatory pathways have also been linked to some traditional risk factors of colorectal cancer such as obesity, smoking and diabetes, as well as more novel associations such as the gut microbiome, the gut mycobiome and exosomes. In this review, we will explore the roles of obesity and diet, smoking, diabetes, the microbiome, the mycobiome and exosomes in colorectal cancer, with a specific focus on the underlying inflammatory and metabolic pathways involved. We will also investigate how the study of colon cancer from an inflammatory background not only creates a more holistic and inclusive understanding of this disease, but also creates unique opportunities for prevention, early diagnosis and therapy.
Fake news and rumors: a trigger for proliferation or fading away

The dynamics of fake news and rumor spreading is investigated using a model with three kinds of agents who are respectively the Seeds, the Agnostics and the Others. While Seeds are the ones who start spreading the rumor being adamantly convinced of its truth, Agnostics reject any kind of rumor and do not believe in conspiracy theories. In between, the Others constitute the main part of the community. While Seeds are always Believers and Agnostics are always Indifferents, Others can switch between being Believer and Indifferent depending on who they are discussing with. The underlying driving dynamics is implemented via local updates of randomly formed groups of agents. In each group, an Other turns into a Believer as soon as $m$ or more Believers are present in the group. However, since some Believers may lose interest in the rumor as time passes by, we add a flipping fixed rate $0<d<1$ from Believers into Indifferents. Rigorous analysis of the associated dynamics reveals that switching from $m=1$ to $m\ge2$ triggers a drastic qualitative change in the spreading process. When $m=1$ even a small group of Believers may manage to convince a large part of the community very quickly. In contrast, for $m\ge 2$, even a substantial fraction of Believers does not prevent the rumor dying out after a few update rounds. Our results provide an explanation on why a given rumor spreads within a social group and not in another, and also why some rumors will not spread in neither groups.
Periodic components of hand acceleration/deceleration impulses during telemanipulation

Responsiveness is the ability of a telemanipulator to recreate user trajectories and impedance in time and space. For trajectory production, a key determinant of responsiveness is the ability of the system to accept user inputs, which are forces on the master handle generated by user hand acceleration/deceleration (a/d) impulses, and translate them into slave arm acceleration/deceleration. This paper presents observations of master controller a/d impulses during completion of a simple target acquisition task. Power spectral density functions calculated from hand controller a/d impulses were used to assess impulse waveform. The relative contributions of frequency intervals ranging up to 25 Hz for three spatially different versions of the task were used to determine which frequencies were most important. The highest relative power was observed in frequencies between 1 Hz and 6 Hz. The key frequencies related to task difficult were in the range from 2 Hz to 8 Hz. Differences were also observed from 9 Hz to 12 Hz. The results provide clues to the source of the performance inhibition.
Moderating Effects of Gender Relationship Between Quality of Work Life and Job Satisfaction: Total Quality Management Perceptions as a Mediating Factor

The aim of this study is to examine the moderating effects of gender relationship between quality of work life and job satisfaction using total quality management perceptions as a mediating factor. Data were collected from Private and Ministry of Health Training and Research Hospitals using 515 employees in Turkey. The moderated mediation analysis was set up according to the hypothesis model. Total quality management is the mediator, and gender is the moderator. The findings showed that the relationship between quality of work life and job satisfaction, quality of work life and total quality management, total quality management and job satisfaction. With respect to the gender variable, the total quality of management decreases; job satisfaction is a little stronger in males. However, even if job satisfaction increases, it is equal in both males and females.
Requirements of an Environment Artist When Accounting for the Needs of a Competitive Community

Electronic Sports, otherwise known as ‘eSports’, have been growing in popularity in player numbers and spectator numbers year by year. With the rise of eSports new challenges have arisen for game developers as communities who have built around these competitive games will reject certain games from tournament play if they are not competitively viable. A videogame’s competitive viability boils down to a number of issues and level design is one of them. Currently there is an abundance of published works and credible sources for environment artists to study single player and multiplayer level design but there are very little of these focused specifically on eSports centric level design. By researching past and present literature, surveying a dedicated competitive community and interviewing a renowned level artist who has experience in this specific field I have come up with a number of requirements that environment artists must take into consideration if they intend on creating a level for an eSports focused title. Through my research I have concluded that levels must have a strong emphasis on balanced level design. Environments must be visually clear to aid readability. Artists must either avoid the overuse of post processing effects or give the player the option to remove them through game options. Artists mustn’t sacrifice strong level design for the sake of visuals. However simple or complex a level is, the player must have freedom of movement and artists must avoid the use of dynamic objects. All of these statements have been backed by studies throughout this document and must be taken into consideration by environment artist and game developers alike if they would like their game’s levels to be competitively viable for the eSports community.
A novel balanced wideband power divider based on microstrip‐slot transitions

A novel design of a balanced wideband power divider (PD) with enhanced common‐mode (CM) suppression is proposed. The top and bottom layers of the structure contain tapered microstrip line. Those microstrip lines are coupled via slotline in the ground plane, which is located at the middle layer. With appropriate placement of the slotline, the coupling between the slotline mode and the differential‐mode (DM) signals can be maximized, while that between the slotline mode and the CM signals can be minimized. Simulated and measured results show that the proposed PD has equal power division, low insertion loss, and good return loss. In the measurement, the fractional bandwidth of the measured −10 dB (DM) return loss is about 101% (1.82–5.35 GHz), the insertion loss for the DM signals is less than 5 dB, the suppression of the CM signals is higher than 45 dB, and the DM isolation is better than 10 dB over the fractional bandwidth. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:437–442, 2014.
Plant Classification based on Leaves using Artificial Neural Network

Manual methods to examine leaf for plant classification can be tedious, therefore, automation is desired. Existing methods try distinctive approaches to accomplish this task. Nowadays, Convolution Neural Networks (CNN) are widely used for such application which achieves higher accuracy. However, CNN's are computationally expensive and require extensive dataset for training. Other existing methods are far less resource expensive but they also have their shortcomings for example, some features cannot be processed accurately with automation, some necessary differentiators are left out. To overcome this, we have proposed a simple Artificial Neural Network (ANN) for automatic classification of plants based on their leaf features. Experimental results show that the proposed algorithm able to achieve an accuracy of 96% by incorporating only a single hidden layer of ANN. Hence, our approach is computationally efficient compared to existing CNN based methods.
Dorsal striatum coding for the timely execution of action sequences

The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals’ subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states or explore-exploit balance.
We're delivering Game Sense … aren't we?

Although the English Rugby Football Union (RFU) introduced Game Sense pedagogy into its coach education courses in the mid-1990s, at the time of writing a definitive and consistent approach to it remains elusive. This paper highlights the experiences of RFU coaches and coach educators as they attempted to apply Game Sense pedagogy in their practice. Qualitative data were collected via questionnaires, field notes, and semi-structured interviews from coaches and coach educators on RFU Level 2 courses. Findings suggest that fundamental challenges exist when introducing Game Sense pedagogy to coaches: which include conceptual and pedagogical misunderstandings associated with the model as well as the structural mechanisms and support network surrounding the provision of mediated learning within coach education courses.
The Application of Curvelet Transform Method for Regional Gravity Data

Regional gravity anomaly provides important information for the study of regional geologic structure and the division of tectonic units. The major concern of the geophysicists is how to obtain the detailed data of regional gravity using reliable methods. In this study, curvelet transform was used for the first time in the multi-scale analysis of data of regional gravity. As one method for multi-scale geometric analysis, curvelet transform overcomes the limitations of wavelet transform in representing the high-dimensional singularities such as edges and contours. When processing of the data of regional gravity, the curvelet transform can more effectively present the detailed information. In this study, the data of synthetic model was respectively used for the experiments based on the wrapping algorithm of second-generation curvelet transform in combination with translation of cycle, iterative operation and Monte Carlo strategy for threshold adjustment. The experimental results show that the curvelet transform is efficient in multiscale separation for the data of regional gravity. This technique provides reference to the application of relevant multiscale and multi-orientational transform methods in the processing of data of gravity.
Interspecies Jumping of Bat Coronaviruses

In the last two decades, several coronavirus (CoV) interspecies jumping events have occurred between bats and other animals/humans, leading to major epidemics/pandemics and high fatalities. The SARS epidemic in 2002/2003 had a ~10% fatality. The discovery of SARS-related CoVs in horseshoe bats and civets and genomic studies have confirmed bat-to-civet-to-human transmission. The MERS epidemic that emerged in 2012 had a ~35% mortality, with dromedaries as the reservoir. Although CoVs with the same genome organization (e.g., Tylonycteris BatCoV HKU4 and Pipistrellus BatCoV HKU5) were also detected in bats, there is still a phylogenetic gap between these bat CoVs and MERS-CoV. In 2016, 10 years after the discovery of Rhinolophus BatCoV HKU2 in Chinese horseshoe bats, fatal swine disease outbreaks caused by this virus were reported in southern China. In late 2019, an outbreak of pneumonia emerged in Wuhan, China, and rapidly spread globally, leading to >4,000,000 fatalities so far. Although the genome of SARS-CoV-2 is highly similar to that of SARS-CoV, patient zero and the original source of the pandemic are still unknown. To protect humans from future public health threats, measures should be taken to monitor and reduce the chance of interspecies jumping events, either occurring naturally or through recombineering experiments.
The Protective Role of Prolyl Oligopeptidase (POP) Inhibition in Kidney Injury Induced by Renal Ischemia–Reperfusion

Ischemia/reperfusion injury (IRI) is a complex pathophysiological process characterized by blood circulation disorder caused by various factors, such as traumatic shock, surgery, organ transplantation, and thrombus. Severe metabolic dysregulation and tissue structure destruction are observed upon restoration of blood flow to the ischemic tissue. The kidney is a highly perfused organ, sensitive to ischemia and reperfusion injury, and the incidence of renal IRI has high morbidity and mortality. Several studies showed that infiltration of inflammatory cells, apoptosis, and angiogenesis are important mechanisms involved in renal IRI. Despite advances in research, effective therapies for renal IRI are lacking. Recently it has been demonstrated the role of KYP2047, a selective inhibitor of prolyl oligopeptidase (POP), in the regulation of inflammation, apoptosis, and angiogenesis. Thus, this research focused on the role of POP in kidney ischemia/reperfusion (KI/R). An in vivo model of KI/R was performed and mice were subjected to KYP2047 treatment (intraperitoneal, 0.5, 1 and 5 mg/kg). Histological analysis, Masson’s trichrome and periodic acid shift (PAS) staining, immunohistochemical and Western blots analysis, real-time PCR (RT-PCR) and ELISA were performed on kidney samples. Moreover, serum creatinine and blood urea nitrogen (BUN) were quantified. POP-inhibition by KYP2047 treatment, only at the doses of 1 and 5 mg/kg, significantly reduced renal injury and collagen amount, regulated inflammation through canonical and non-canonical NF-κB pathway, and restored renal function. Moreover, KYP2047 modulated angiogenesis markers, such as TGF-β and VEGF, also slowing down apoptosis. Interestingly, treatment with KYP2047 modulated PP2A activity. Thus, these findings clarified the role of POP inhibition in AKI, also offering novel therapeutic target for renal injury after KI/R.
Longitudinal treatment responsiveness on plasma neurofilament light chain and glial fibrillary acidic protein levels in neuromyelitis optica spectrum disorder

Background: Neurofilament light chain (NfL) and glial fibrilliary acidic protein (GFAP) have been suggested to be biomarkers of the pathophysiological process of neuromyelitis optica spectrum disorders (NMOSD), but the relationship between the plasma levels of these molecules with disease activity and treatment is incompletely understood. Objective: To investigate the treatment effects of disease-modifying drugs on plasma neurofilament light chain (pNfL) and plasma glial fibrillary acidic protein (pGFAP) and explore the predictive value of pNfL and pGFAP in the activity of NMOSD. Methods: pNfL and pGFAP levels were measured using single-molecule arrays in 72 patients with NMOSD and 38 healthy controls (HCs). Patients with NMOSD received tocilizumab (n = 29), rituximab (n = 23), oral prednisone (n = 16), and oral azathioprine or mycophenolate mofetil (n = 4). Results: NMOSD patients had significantly higher pNfL and pGFAP levels than HCs (pNfL, 18.3 (11.2–39.3) versus 11.5 (7.0–23.3) pg/mL; p = 0.001; pGFAP, 149.7 (88.6–406.5) versus 68.7 (59.4–80.8) pg/mL; p < 0.001). Multivariable regression analyses indicated that baseline pNfL concentration was associated with age (p = 0.017), Expanded Disability Status Scale (EDSS) score (p = 0.002), and recent relapses (p < 0.001). Baseline pGFAP concentration was also associated with EDSS (p < 0.001) and recent relapses (p < 0.001). Compared with prednisone, tocilizumab and rituximab significantly reduced pNfL [tocilizumab, exp(β), 0.65; 95% confidence interval (CI), 0.56–0.75; p < 0.001; rituximab, exp(β), 0.79; 95% CI = 0.68–0.93; p = 0.005] and pGFAP levels [tocilizumab, exp(β), 0.64; 95% CI, 0.51–0.80; p < 0.001; rituximab, exp(β), 0.77; 95% CI, 0.61–0.98; p = 0.041] at the end of the study. The pNfL levels in the tocilizumab and rituximab groups were reduced to those of HCs [tocilizumab, 8.5 (7.06–17.90) pg/mL; p = 0.426; rituximab, 14.0 (9.94–21.80) pg/mL; p = 0.216]. However, the pGFAP levels did not decrease to those of HCs in NMOSD patients at the end of study [tocilizumab, 88.9 (63.4–131.8) pg/mL; p = 0.012; rituximab, 141.7 (90.8–192.7) pg/mL; p < 0.001]. Conclusion: pNfL and pGFAP may serve as biomarkers for NMOSD disease activity and treatment effects.
Function allocation: optimising the automation boundary

Two topics are currently generating debate in the human factors literature. One is the importance of function allocation, and the second is the issue of improving the integration of human factors inputs to system design. The DERA Centre for Human Sciences has been conducting research into function allocation and methods of optimising the automation boundary in future military systems for a number of years. We suggest that the process of function allocation forms a critical part of the design process that impacts upon the overall system design and the human operators' roles within that system. This paper suggests a number of reasons why the process of function allocation requires greater attention during system design than has so far been the case. It also provides an overview of work being carried out to address the need for human factors methods to support the process of function allocation that are compatible with system design practice.
Estimating the Mode of Delivery through Cause Analysis A Systematic Literature Review on the context of Reducing Cesarean

In developing countries, many health workers force pregnant women in private hospitals having baby through cesarean delivery, even though most pregnant mothers are skeptical about the risk of going under such operations. Doctors often encourage pregnant mothers to have a cesarean on the basis of their physical condition and medical reports. Emergency cesarean patient cannot be prepared in advance but on real time, If a system can be developed that can forecast whether a woman need natural or cesarean delivery, then rate of the risk of the pregnant women get reduce. To design such system, we need to know what factors influences the doctors to choose cesarean over normal delivery. We have conducted a systematic review in well-known databases to understand the various factors of pregnant mothers. A total of 19 studies were selected among 2512 studies based on the relevancy to the research objective. The objective of this study is to predict the mode of delivery based on 10 specific parameters identified separately from 180 parameters present in various test reports.
Dislocations And Strength In Thin Films: Simulations And Modeling

Crystalline thin films have mechanical properties that cannot be predicted based on bulk scaling laws. Owing to their importance in technology, a great deal of effort has gone into modeling and simulation of the behaviors of dislocations in thin films. In this review, the successes and failures of modeling dislocations in thin films via analytical techniques, two dimensional dislocation dynamics simulations, and three dimensional discrete dislocation dynamics (DDD) simulations are discussed. Brief discussions of phase field models and level set methods are also included. The unique importance of three-dimensional DDD simulations is highlighted, as these simulations allow study of realistic dislocation behavior that is otherwise difficult or impossible to observe. The utility of three-dimensional DDD in discovering the mechanisms that control deformation in films is demonstrated, and first steps towards construction of a strain hardening model based on those mechanisms are described. 2.